id	sid	tid	token	lemma	pos
cana-2667	1	1	communications	communication	NOUN
cana-2667	1	2	on	on	ADP
cana-2667	1	3	applied	apply	VERB
cana-2667	1	4	nonlinear	nonlinear	ADJ
cana-2667	1	5	analysis	analysis	NOUN
cana-2667	1	6	issn	issn	NOUN
cana-2667	1	7	:	:	PUNCT
cana-2667	1	8	1074	1074	NUM
cana-2667	1	9	-	-	PUNCT
cana-2667	1	10	133x	133x	NUM
cana-2667	1	11	vol	vol	NOUN
cana-2667	1	12	32	32	NUM
cana-2667	1	13	no	no	NOUN
cana-2667	1	14	.	.	PUNCT
cana-2667	2	1	3s	3s	NUM
cana-2667	2	2	(	(	PUNCT
cana-2667	2	3	2025	2025	NUM
cana-2667	2	4	)	)	PUNCT
cana-2667	2	5	379	379	NUM
cana-2667	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	2	7	improving	improve	VERB
cana-2667	2	8	retinopathy	retinopathy	ADJ
cana-2667	2	9	classification	classification	NOUN
cana-2667	2	10	using	use	VERB
cana-2667	2	11	optimized	optimize	VERB
cana-2667	2	12	support	support	NOUN
cana-2667	2	13	vector	vector	NOUN
cana-2667	2	14	machines	machine	NOUN
cana-2667	2	15	and	and	CCONJ
cana-2667	2	16	deep	deep	ADJ
cana-2667	2	17	learning	learning	NOUN
cana-2667	2	18	techniques	technique	NOUN
cana-2667	2	19	mrs	mrs	PROPN
cana-2667	2	20	.	.	PROPN
cana-2667	2	21	k.	k.	PROPN
cana-2667	2	22	deepthi1	deepthi1	PROPN
cana-2667	2	23	,	,	PUNCT
cana-2667	2	24	dr	dr	PROPN
cana-2667	2	25	.	.	PROPN
cana-2667	2	26	b.	b.	PROPN
cana-2667	2	27	naveen	naveen	PROPN
cana-2667	2	28	kumar2	kumar2	PROPN
cana-2667	2	29	,	,	PUNCT
cana-2667	2	30	dr	dr	PROPN
cana-2667	2	31	.	.	PROPN
cana-2667	2	32	ashish	ashish	PROPN
cana-2667	2	33	kumar	kumar	PROPN
cana-2667	2	34	soni3	soni3	PROPN
cana-2667	2	35	,	,	PUNCT
cana-2667	3	1	dr	dr	PROPN
cana-2667	3	2	.	.	PROPN
cana-2667	3	3	b.	b.	PROPN
cana-2667	3	4	ramesh4	ramesh4	PROPN
cana-2667	3	5	,	,	PUNCT
cana-2667	3	6	mr	mr	PROPN
cana-2667	3	7	.	.	PROPN
cana-2667	3	8	satti	satti	PROPN
cana-2667	3	9	harichandra	harichandra	PROPN
cana-2667	3	10	prasad5	prasad5	PROPN
cana-2667	3	11	,	,	PUNCT
cana-2667	3	12	dr	dr	PROPN
cana-2667	3	13	.	.	PROPN
cana-2667	3	14	atul	atul	PROPN
cana-2667	3	15	tripathi6	tripathi6	PROPN
cana-2667	3	16	,	,	PUNCT
cana-2667	3	17	dr	dr	PROPN
cana-2667	3	18	.	.	PROPN
cana-2667	3	19	avinash7	avinash7	PROPN
cana-2667	3	20	1assistant	1assistant	NUM
cana-2667	3	21	professor	professor	NOUN
cana-2667	3	22	,	,	PUNCT
cana-2667	3	23	information	information	NOUN
cana-2667	3	24	technology	technology	NOUN
cana-2667	3	25	,	,	PUNCT
cana-2667	3	26	anurag	anurag	PROPN
cana-2667	3	27	university	university	PROPN
cana-2667	3	28	,	,	PUNCT
cana-2667	3	29	deepthikalwa@gmail.com	deepthikalwa@gmail.com	X
cana-2667	3	30	2lecturer	2lecturer	NUM
cana-2667	3	31	,	,	PUNCT
cana-2667	3	32	computer	computer	NOUN
cana-2667	3	33	science	science	NOUN
cana-2667	3	34	engineering	engineering	NOUN
cana-2667	3	35	,	,	PUNCT
cana-2667	3	36	government	government	NOUN
cana-2667	3	37	engineering	engineering	NOUN
cana-2667	3	38	college	college	NOUN
cana-2667	3	39	,	,	PUNCT
cana-2667	3	40	kosgi	kosgi	PROPN
cana-2667	3	41	,	,	PUNCT
cana-2667	3	42	naveenkumar0206@gmail.com	naveenkumar0206@gmail.com	X
cana-2667	4	1	3department	3department	NUM
cana-2667	4	2	mathematics	mathematic	NOUN
cana-2667	4	3	,	,	PUNCT
cana-2667	4	4	medicaps	medicap	NOUN
cana-2667	4	5	university	university	NOUN
cana-2667	4	6	indore	indore	NOUN
cana-2667	4	7	,	,	PUNCT
cana-2667	4	8	ashishkumar.soni@medicaps.ac.in	ashishkumar.soni@medicaps.ac.in	NUM
cana-2667	4	9	4associate	4associate	NUM
cana-2667	4	10	professor	professor	NOUN
cana-2667	4	11	,	,	PUNCT
cana-2667	4	12	department	department	NOUN
cana-2667	4	13	of	of	ADP
cana-2667	4	14	electronics	electronic	NOUN
cana-2667	4	15	and	and	CCONJ
cana-2667	4	16	communication	communication	NOUN
cana-2667	4	17	engineering	engineering	NOUN
cana-2667	4	18	,	,	PUNCT
cana-2667	4	19	annapoorana	annapoorana	PROPN
cana-2667	4	20	engineering	engineering	PROPN
cana-2667	4	21	college	college	PROPN
cana-2667	4	22	,	,	PUNCT
cana-2667	4	23	autonomous	autonomous	ADJ
cana-2667	4	24	,	,	PUNCT
cana-2667	4	25	mailrameshece@gmail.com	mailrameshece@gmail.com	X
cana-2667	5	1	5department	5department	NUM
cana-2667	5	2	of	of	ADP
cana-2667	5	3	ece	ece	PROPN
cana-2667	5	4	,	,	PUNCT
cana-2667	5	5	aditya	aditya	PROPN
cana-2667	5	6	university	university	PROPN
cana-2667	5	7	,	,	PUNCT
cana-2667	5	8	surampalem	surampalem	NOUN
cana-2667	5	9	,	,	PUNCT
cana-2667	5	10	andhra	andhra	PROPN
cana-2667	5	11	pradesh	pradesh	PROPN
cana-2667	5	12	,	,	PUNCT
cana-2667	5	13	hariprasad.satti@adityauniversity.in	hariprasad.satti@adityauniversity.in	PROPN
cana-2667	5	14	6assistant	6assistant	NUM
cana-2667	5	15	professor	professor	NOUN
cana-2667	5	16	,	,	PUNCT
cana-2667	5	17	university	university	NOUN
cana-2667	5	18	school	school	NOUN
cana-2667	5	19	of	of	ADP
cana-2667	5	20	automation	automation	NOUN
cana-2667	5	21	&	&	CCONJ
cana-2667	5	22	robotics	robotic	NOUN
cana-2667	5	23	,	,	PUNCT
cana-2667	5	24	guru	guru	NOUN
cana-2667	5	25	gobind	gobind	PROPN
cana-2667	5	26	singh	singh	PROPN
cana-2667	5	27	indraprastha	indraprastha	PROPN
cana-2667	5	28	university	university	PROPN
cana-2667	5	29	,	,	PUNCT
cana-2667	5	30	delhi	delhi	PROPN
cana-2667	5	31	,	,	PUNCT
cana-2667	5	32	atul.usar@ipu.ac.in	atul.usar@ipu.ac.in	PROPN
cana-2667	5	33	7assistant	7assistant	NUM
cana-2667	5	34	professor	professor	NOUN
cana-2667	5	35	,	,	PUNCT
cana-2667	5	36	bharati	bharati	PROPN
cana-2667	5	37	vidyapeeth	vidyapeeth	PROPN
cana-2667	5	38	's	's	PART
cana-2667	5	39	college	college	NOUN
cana-2667	5	40	of	of	ADP
cana-2667	5	41	engineering	engineering	PROPN
cana-2667	5	42	,	,	PUNCT
cana-2667	5	43	new	new	ADJ
cana-2667	5	44	delhi	delhi	PROPN
cana-2667	5	45	,	,	PUNCT
cana-2667	5	46	singh.avinash@bharatividyapeeth.edu	singh.avinash@bharatividyapeeth.edu	NUM
cana-2667	5	47	article	article	NOUN
cana-2667	5	48	history	history	NOUN
cana-2667	5	49	:	:	PUNCT
cana-2667	5	50	received	receive	VERB
cana-2667	5	51	:	:	PUNCT
cana-2667	5	52	20	20	NUM
cana-2667	5	53	-	-	SYM
cana-2667	5	54	09	09	NUM
cana-2667	5	55	-	-	PUNCT
cana-2667	5	56	2024	2024	NUM
cana-2667	5	57	revised	revise	VERB
cana-2667	5	58	:	:	PUNCT
cana-2667	5	59	01	01	NUM
cana-2667	5	60	-	-	SYM
cana-2667	5	61	11	11	NUM
cana-2667	5	62	-	-	PUNCT
cana-2667	5	63	2024	2024	NUM
cana-2667	5	64	accepted	accept	VERB
cana-2667	5	65	:	:	PUNCT
cana-2667	5	66	20	20	NUM
cana-2667	5	67	-	-	SYM
cana-2667	5	68	11	11	NUM
cana-2667	5	69	-	-	PUNCT
cana-2667	5	70	2024	2024	NUM
cana-2667	5	71	abstract	abstract	NOUN
cana-2667	5	72	:	:	PUNCT
cana-2667	5	73	retinopathy	retinopathy	ADJ
cana-2667	5	74	is	be	AUX
cana-2667	5	75	one	one	NUM
cana-2667	5	76	of	of	ADP
cana-2667	5	77	the	the	DET
cana-2667	5	78	primary	primary	ADJ
cana-2667	5	79	causes	cause	NOUN
cana-2667	5	80	of	of	ADP
cana-2667	5	81	blindness	blindness	NOUN
cana-2667	5	82	,	,	PUNCT
cana-2667	5	83	making	make	VERB
cana-2667	5	84	early	early	ADJ
cana-2667	5	85	detection	detection	NOUN
cana-2667	5	86	and	and	CCONJ
cana-2667	5	87	diagnosis	diagnosis	NOUN
cana-2667	5	88	challenging	challenging	ADJ
cana-2667	5	89	.	.	PUNCT
cana-2667	6	1	conventional	conventional	ADJ
cana-2667	6	2	techniques	technique	NOUN
cana-2667	6	3	of	of	ADP
cana-2667	6	4	retinopathy	retinopathy	ADJ
cana-2667	6	5	classification	classification	NOUN
cana-2667	6	6	depend	depend	VERB
cana-2667	6	7	on	on	ADP
cana-2667	6	8	manual	manual	ADJ
cana-2667	6	9	observation	observation	NOUN
cana-2667	6	10	and	and	CCONJ
cana-2667	6	11	rule	rule	NOUN
cana-2667	6	12	-	-	PUNCT
cana-2667	6	13	driven	drive	VERB
cana-2667	6	14	methods	method	NOUN
cana-2667	6	15	,	,	PUNCT
cana-2667	6	16	which	which	PRON
cana-2667	6	17	may	may	AUX
cana-2667	6	18	be	be	AUX
cana-2667	6	19	time	time	NOUN
cana-2667	6	20	-	-	PUNCT
cana-2667	6	21	consuming	consume	VERB
cana-2667	6	22	and	and	CCONJ
cana-2667	6	23	errorprone	errorprone	NOUN
cana-2667	6	24	.	.	PUNCT
cana-2667	7	1	machine	machine	NOUN
cana-2667	7	2	learning	learning	NOUN
cana-2667	7	3	algorithms	algorithm	NOUN
cana-2667	7	4	,	,	PUNCT
cana-2667	7	5	such	such	ADJ
cana-2667	7	6	as	as	ADP
cana-2667	7	7	support	support	NOUN
cana-2667	7	8	vector	vector	NOUN
cana-2667	7	9	machines	machine	NOUN
cana-2667	7	10	(	(	PUNCT
cana-2667	7	11	svms	svms	NOUN
cana-2667	7	12	)	)	PUNCT
cana-2667	7	13	and	and	CCONJ
cana-2667	7	14	deep	deep	ADJ
cana-2667	7	15	learning	learning	NOUN
cana-2667	7	16	(	(	PUNCT
cana-2667	7	17	dl	dl	PROPN
cana-2667	7	18	)	)	PUNCT
cana-2667	7	19	,	,	PUNCT
cana-2667	7	20	have	have	AUX
cana-2667	7	21	recently	recently	ADV
cana-2667	7	22	exhibited	exhibit	VERB
cana-2667	7	23	efficacy	efficacy	NOUN
cana-2667	7	24	and	and	CCONJ
cana-2667	7	25	substantial	substantial	ADJ
cana-2667	7	26	accuracy	accuracy	NOUN
cana-2667	7	27	enhancements	enhancement	NOUN
cana-2667	7	28	in	in	ADP
cana-2667	7	29	classification	classification	NOUN
cana-2667	7	30	.	.	PUNCT
cana-2667	8	1	but	but	CCONJ
cana-2667	8	2	problems	problem	NOUN
cana-2667	8	3	like	like	ADP
cana-2667	8	4	overfitting	overfitte	VERB
cana-2667	8	5	,	,	PUNCT
cana-2667	8	6	parameters	parameter	NOUN
cana-2667	8	7	adjustment	adjustment	NOUN
cana-2667	8	8	and	and	CCONJ
cana-2667	8	9	the	the	DET
cana-2667	8	10	requirement	requirement	NOUN
cana-2667	8	11	for	for	ADP
cana-2667	8	12	huge	huge	ADJ
cana-2667	8	13	annotated	annotate	VERB
cana-2667	8	14	datasets	dataset	NOUN
cana-2667	8	15	can	can	AUX
cana-2667	8	16	limit	limit	VERB
cana-2667	8	17	the	the	DET
cana-2667	8	18	power	power	NOUN
cana-2667	8	19	of	of	ADP
cana-2667	8	20	these	these	DET
cana-2667	8	21	models	model	NOUN
cana-2667	8	22	.	.	PUNCT
cana-2667	9	1	therefore	therefore	ADV
cana-2667	9	2	,	,	PUNCT
cana-2667	9	3	in	in	ADP
cana-2667	9	4	this	this	DET
cana-2667	9	5	paper	paper	NOUN
cana-2667	9	6	,	,	PUNCT
cana-2667	9	7	we	we	PRON
cana-2667	9	8	are	be	AUX
cana-2667	9	9	proposing	propose	VERB
cana-2667	9	10	enhanced	enhanced	ADJ
cana-2667	9	11	classification	classification	NOUN
cana-2667	9	12	of	of	ADP
cana-2667	9	13	retinopathy	retinopathy	ADJ
cana-2667	9	14	byhelping	byhelping	NOUN
cana-2667	9	15	support	support	NOUN
cana-2667	9	16	vector	vector	NOUN
cana-2667	9	17	machines	machine	NOUN
cana-2667	9	18	and	and	CCONJ
cana-2667	9	19	deep	deep	ADJ
cana-2667	9	20	learning	learning	NOUN
cana-2667	9	21	model	model	NOUN
cana-2667	9	22	.	.	PUNCT
cana-2667	10	1	more	more	ADV
cana-2667	10	2	specifically	specifically	ADV
cana-2667	10	3	,	,	PUNCT
cana-2667	10	4	we	we	PRON
cana-2667	10	5	present	present	VERB
cana-2667	10	6	a	a	DET
cana-2667	10	7	hybrid	hybrid	ADJ
cana-2667	10	8	approach	approach	NOUN
cana-2667	10	9	which	which	PRON
cana-2667	10	10	combines	combine	VERB
cana-2667	10	11	a	a	DET
cana-2667	10	12	deep	deep	ADJ
cana-2667	10	13	convolutional	convolutional	ADJ
cana-2667	10	14	neural	neural	ADJ
cana-2667	10	15	network	network	NOUN
cana-2667	10	16	(	(	PUNCT
cana-2667	10	17	cnn	cnn	PROPN
cana-2667	10	18	)	)	PUNCT
cana-2667	10	19	for	for	ADP
cana-2667	10	20	feature	feature	NOUN
cana-2667	10	21	extraction	extraction	NOUN
cana-2667	10	22	with	with	ADP
cana-2667	10	23	a	a	DET
cana-2667	10	24	finely	finely	ADV
cana-2667	10	25	-	-	PUNCT
cana-2667	10	26	tuned	tune	VERB
cana-2667	10	27	svm	svm	NOUN
cana-2667	10	28	for	for	ADP
cana-2667	10	29	classification	classification	NOUN
cana-2667	10	30	.	.	PUNCT
cana-2667	11	1	to	to	PART
cana-2667	11	2	improve	improve	VERB
cana-2667	11	3	the	the	DET
cana-2667	11	4	generalization	generalization	NOUN
cana-2667	11	5	ability	ability	NOUN
cana-2667	11	6	of	of	ADP
cana-2667	11	7	the	the	DET
cana-2667	11	8	svm	svm	PROPN
cana-2667	11	9	,	,	PUNCT
cana-2667	11	10	we	we	PRON
cana-2667	11	11	utilize	utilize	VERB
cana-2667	11	12	a	a	DET
cana-2667	11	13	grid	grid	NOUN
cana-2667	11	14	search	search	NOUN
cana-2667	11	15	approach	approach	NOUN
cana-2667	11	16	to	to	PART
cana-2667	11	17	optimize	optimize	VERB
cana-2667	11	18	the	the	DET
cana-2667	11	19	svm	svm	ADJ
cana-2667	11	20	parameters	parameter	NOUN
cana-2667	11	21	.	.	PUNCT
cana-2667	12	1	we	we	PRON
cana-2667	12	2	validate	validate	VERB
cana-2667	12	3	our	our	PRON
cana-2667	12	4	method	method	NOUN
cana-2667	12	5	on	on	ADP
cana-2667	12	6	a	a	DET
cana-2667	12	7	publicly	publicly	ADV
cana-2667	12	8	available	available	ADJ
cana-2667	12	9	retinopathy	retinopathy	ADJ
cana-2667	12	10	dataset	dataset	NOUN
cana-2667	12	11	which	which	PRON
cana-2667	12	12	shows	show	VERB
cana-2667	12	13	a	a	DET
cana-2667	12	14	strong	strong	ADJ
cana-2667	12	15	gain	gain	NOUN
cana-2667	12	16	in	in	ADP
cana-2667	12	17	classification	classification	NOUN
cana-2667	12	18	accuracy	accuracy	NOUN
cana-2667	12	19	over	over	ADP
cana-2667	12	20	existing	exist	VERB
cana-2667	12	21	methods	method	NOUN
cana-2667	12	22	.	.	PUNCT
cana-2667	13	1	we	we	PRON
cana-2667	13	2	present	present	VERB
cana-2667	13	3	our	our	PRON
cana-2667	13	4	approach	approach	NOUN
cana-2667	13	5	,	,	PUNCT
cana-2667	13	6	with	with	ADP
cana-2667	13	7	the	the	DET
cana-2667	13	8	results	result	NOUN
cana-2667	13	9	showing	show	VERB
cana-2667	13	10	that	that	SCONJ
cana-2667	13	11	,	,	PUNCT
cana-2667	13	12	compared	compare	VERB
cana-2667	13	13	to	to	ADP
cana-2667	13	14	traditional	traditional	ADJ
cana-2667	13	15	svm	svm	PROPN
cana-2667	13	16	and	and	CCONJ
cana-2667	13	17	cnn	cnn	PROPN
cana-2667	13	18	-	-	PUNCT
cana-2667	13	19	based	base	VERB
cana-2667	13	20	models	model	NOUN
cana-2667	13	21	,	,	PUNCT
cana-2667	13	22	we	we	PRON
cana-2667	13	23	achieve	achieve	VERB
cana-2667	13	24	an	an	DET
cana-2667	13	25	accuracy	accuracy	NOUN
cana-2667	13	26	of	of	ADP
cana-2667	13	27	95	95	NUM
cana-2667	13	28	%	%	NOUN
cana-2667	13	29	,	,	PUNCT
cana-2667	13	30	while	while	SCONJ
cana-2667	13	31	reducing	reduce	VERB
cana-2667	13	32	false	false	ADJ
cana-2667	13	33	positives	positive	NOUN
cana-2667	13	34	.	.	PUNCT
cana-2667	14	1	providing	provide	VERB
cana-2667	14	2	early	early	ADJ
cana-2667	14	3	detection	detection	NOUN
cana-2667	14	4	and	and	CCONJ
cana-2667	14	5	alleviating	alleviate	VERB
cana-2667	14	6	the	the	DET
cana-2667	14	7	burden	burden	NOUN
cana-2667	14	8	on	on	ADP
cana-2667	14	9	healthcare	healthcare	PROPN
cana-2667	14	10	staff	staff	NOUN
cana-2667	14	11	,	,	PUNCT
cana-2667	14	12	this	this	DET
cana-2667	14	13	hybrid	hybrid	ADJ
cana-2667	14	14	approach	approach	NOUN
cana-2667	14	15	provides	provide	VERB
cana-2667	14	16	a	a	DET
cana-2667	14	17	more	more	ADV
cana-2667	14	18	robust	robust	ADJ
cana-2667	14	19	and	and	CCONJ
cana-2667	14	20	scalable	scalable	ADJ
cana-2667	14	21	method	method	NOUN
cana-2667	14	22	for	for	ADP
cana-2667	14	23	automated	automate	VERB
cana-2667	14	24	screening	screening	NOUN
cana-2667	14	25	of	of	ADP
cana-2667	14	26	retinopathy	retinopathy	NOUN
cana-2667	14	27	.	.	PUNCT
cana-2667	15	1	overall	overall	ADV
cana-2667	15	2	,	,	PUNCT
cana-2667	15	3	we	we	PRON
cana-2667	15	4	have	have	AUX
cana-2667	15	5	presented	present	VERB
cana-2667	15	6	a	a	DET
cana-2667	15	7	novel	novel	ADJ
cana-2667	15	8	model	model	NOUN
cana-2667	15	9	that	that	PRON
cana-2667	15	10	now	now	ADV
cana-2667	15	11	automates	automate	VERB
cana-2667	15	12	retinopathy	retinopathy	ADJ
cana-2667	15	13	prediction	prediction	NOUN
cana-2667	15	14	to	to	ADP
cana-2667	15	15	a	a	DET
cana-2667	15	16	point	point	NOUN
cana-2667	15	17	where	where	SCONJ
cana-2667	15	18	it	it	PRON
cana-2667	15	19	could	could	AUX
cana-2667	15	20	be	be	AUX
cana-2667	15	21	useful	useful	ADJ
cana-2667	15	22	in	in	ADP
cana-2667	15	23	the	the	DET
cana-2667	15	24	clinic	clinic	NOUN
cana-2667	15	25	.	.	PUNCT
cana-2667	16	1	keywords	keyword	NOUN
cana-2667	16	2	:	:	PUNCT
cana-2667	16	3	retinopathy	retinopathy	ADJ
cana-2667	16	4	,	,	PUNCT
cana-2667	16	5	blindness	blindness	NOUN
cana-2667	16	6	,	,	PUNCT
cana-2667	16	7	robust	robust	ADJ
cana-2667	16	8	,	,	PUNCT
cana-2667	16	9	learning	learning	NOUN
cana-2667	16	10	,	,	PUNCT
cana-2667	16	11	detection	detection	NOUN
cana-2667	16	12	,	,	PUNCT
cana-2667	16	13	accuracy	accuracy	NOUN
cana-2667	16	14	,	,	PUNCT
cana-2667	16	15	techniques	technique	NOUN
cana-2667	16	16	,	,	PUNCT
cana-2667	16	17	optimized	optimize	VERB
cana-2667	16	18	.	.	PROPN
cana-2667	17	1	1	1	X
cana-2667	17	2	.	.	X
cana-2667	17	3	introduction	introduction	NOUN
cana-2667	17	4	retinopathy	retinopathy	ADJ
cana-2667	17	5	is	be	AUX
cana-2667	17	6	a	a	DET
cana-2667	17	7	term	term	NOUN
cana-2667	17	8	for	for	ADP
cana-2667	17	9	diseases	disease	NOUN
cana-2667	17	10	that	that	PRON
cana-2667	17	11	affect	affect	VERB
cana-2667	17	12	the	the	DET
cana-2667	17	13	retina	retina	NOUN
cana-2667	17	14	(	(	PUNCT
cana-2667	17	15	the	the	DET
cana-2667	17	16	light	light	ADJ
cana-2667	17	17	-	-	PUNCT
cana-2667	17	18	sensitive	sensitive	ADJ
cana-2667	17	19	layer	layer	NOUN
cana-2667	17	20	at	at	ADP
cana-2667	17	21	the	the	DET
cana-2667	17	22	back	back	NOUN
cana-2667	17	23	of	of	ADP
cana-2667	17	24	the	the	DET
cana-2667	17	25	eye	eye	NOUN
cana-2667	17	26	)	)	PUNCT
cana-2667	17	27	.	.	PUNCT
cana-2667	18	1	if	if	SCONJ
cana-2667	18	2	left	leave	VERB
cana-2667	18	3	undiagnosed	undiagnosed	ADJ
cana-2667	18	4	and	and	CCONJ
cana-2667	18	5	untreated	untreated	ADJ
cana-2667	18	6	,	,	PUNCT
cana-2667	18	7	these	these	DET
cana-2667	18	8	conditions	condition	NOUN
cana-2667	18	9	can	can	AUX
cana-2667	18	10	result	result	VERB
cana-2667	18	11	in	in	ADP
cana-2667	18	12	decreased	decrease	VERB
cana-2667	18	13	vision	vision	NOUN
cana-2667	18	14	function	function	NOUN
cana-2667	18	15	,	,	PUNCT
cana-2667	18	16	including	include	VERB
cana-2667	18	17	blindness	blindness	NOUN
cana-2667	18	18	.	.	PUNCT
cana-2667	19	1	diabetic	diabetic	ADJ
cana-2667	19	2	retinopathy	retinopathy	ADJ
cana-2667	19	3	(	(	PUNCT
cana-2667	19	4	dr	dr	PROPN
cana-2667	19	5	)	)	PUNCT
cana-2667	19	6	,	,	PUNCT
cana-2667	19	7	which	which	PRON
cana-2667	19	8	is	be	AUX
cana-2667	19	9	a	a	DET
cana-2667	19	10	leading	lead	VERB
cana-2667	19	11	cause	cause	NOUN
cana-2667	19	12	of	of	ADP
cana-2667	19	13	vision	vision	NOUN
cana-2667	19	14	impairment	impairment	NOUN
cana-2667	19	15	,	,	PUNCT
cana-2667	19	16	is	be	AUX
cana-2667	19	17	the	the	DET
cana-2667	19	18	most	most	ADJ
cana-2667	19	19	communications	communication	NOUN
cana-2667	19	20	on	on	ADP
cana-2667	19	21	applied	apply	VERB
cana-2667	19	22	nonlinear	nonlinear	ADJ
cana-2667	19	23	analysis	analysis	NOUN
cana-2667	19	24	issn	issn	NOUN
cana-2667	19	25	:	:	PUNCT
cana-2667	19	26	1074	1074	NUM
cana-2667	19	27	-	-	PUNCT
cana-2667	19	28	133x	133x	NUM
cana-2667	19	29	vol	vol	NOUN
cana-2667	19	30	32	32	NUM
cana-2667	19	31	no	no	NOUN
cana-2667	19	32	.	.	PUNCT
cana-2667	20	1	3s	3s	NUM
cana-2667	20	2	(	(	PUNCT
cana-2667	20	3	2025	2025	NUM
cana-2667	20	4	)	)	PUNCT
cana-2667	20	5	380	380	NUM
cana-2667	20	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	20	7	prevalent	prevalent	ADJ
cana-2667	20	8	type	type	NOUN
cana-2667	20	9	of	of	ADP
cana-2667	20	10	retinopathy	retinopathy	NOUN
cana-2667	20	11	that	that	PRON
cana-2667	20	12	is	be	AUX
cana-2667	20	13	related	relate	VERB
cana-2667	20	14	to	to	ADP
cana-2667	20	15	diabetes	diabetes	NOUN
cana-2667	20	16	mellitus	mellitus	NOUN
cana-2667	20	17	.	.	PUNCT
cana-2667	21	1	the	the	DET
cana-2667	21	2	disease	disease	NOUN
cana-2667	21	3	mostly	mostly	ADV
cana-2667	21	4	affects	affect	VERB
cana-2667	21	5	people	people	NOUN
cana-2667	21	6	with	with	ADP
cana-2667	21	7	longstanding	longstanding	ADJ
cana-2667	21	8	or	or	CCONJ
cana-2667	21	9	poorly	poorly	ADV
cana-2667	21	10	controlled	control	VERB
cana-2667	21	11	diabetes	diabetes	NOUN
cana-2667	21	12	and	and	CCONJ
cana-2667	21	13	damages	damage	VERB
cana-2667	21	14	blood	blood	NOUN
cana-2667	21	15	vessels	vessel	NOUN
cana-2667	21	16	in	in	ADP
cana-2667	21	17	the	the	DET
cana-2667	21	18	retina	retina	NOUN
cana-2667	21	19	,	,	PUNCT
cana-2667	21	20	causing	cause	VERB
cana-2667	21	21	them	they	PRON
cana-2667	21	22	to	to	PART
cana-2667	21	23	leak	leak	VERB
cana-2667	21	24	or	or	CCONJ
cana-2667	21	25	bleed	bleed	VERB
cana-2667	21	26	.	.	PUNCT
cana-2667	22	1	there	there	PRON
cana-2667	22	2	are	be	VERB
cana-2667	22	3	other	other	ADJ
cana-2667	22	4	types	type	NOUN
cana-2667	22	5	of	of	ADP
cana-2667	22	6	retinopathy	retinopathy	ADJ
cana-2667	22	7	,	,	PUNCT
cana-2667	22	8	such	such	ADJ
cana-2667	22	9	as	as	ADP
cana-2667	22	10	hypertensive	hypertensive	ADJ
cana-2667	22	11	retinopathy	retinopathy	NOUN
cana-2667	22	12	,	,	PUNCT
cana-2667	22	13	retinal	retinal	ADJ
cana-2667	22	14	vein	vein	ADJ
cana-2667	22	15	occlusion	occlusion	NOUN
cana-2667	22	16	and	and	CCONJ
cana-2667	22	17	age	age	NOUN
cana-2667	22	18	-	-	PUNCT
cana-2667	22	19	related	relate	VERB
cana-2667	22	20	macular	macular	ADJ
cana-2667	22	21	degeneration	degeneration	NOUN
cana-2667	22	22	,	,	PUNCT
cana-2667	22	23	which	which	PRON
cana-2667	22	24	might	might	AUX
cana-2667	22	25	similarly	similarly	ADV
cana-2667	22	26	lead	lead	VERB
cana-2667	22	27	to	to	ADP
cana-2667	22	28	loss	loss	NOUN
cana-2667	22	29	of	of	ADP
cana-2667	22	30	sight	sight	NOUN
cana-2667	22	31	.	.	PUNCT
cana-2667	23	1	these	these	DET
cana-2667	23	2	diseases	disease	NOUN
cana-2667	23	3	have	have	AUX
cana-2667	23	4	emerged	emerge	VERB
cana-2667	23	5	as	as	ADP
cana-2667	23	6	a	a	DET
cana-2667	23	7	major	major	ADJ
cana-2667	23	8	health	health	NOUN
cana-2667	23	9	threat	threat	NOUN
cana-2667	23	10	and	and	CCONJ
cana-2667	23	11	their	their	PRON
cana-2667	23	12	incidence	incidence	NOUN
cana-2667	23	13	is	be	AUX
cana-2667	23	14	expected	expect	VERB
cana-2667	23	15	to	to	PART
cana-2667	23	16	rise	rise	VERB
cana-2667	23	17	with	with	ADP
cana-2667	23	18	increasing	increase	VERB
cana-2667	23	19	global	global	ADJ
cana-2667	23	20	diabetes	diabete	NOUN
cana-2667	23	21	and	and	CCONJ
cana-2667	23	22	aging	age	VERB
cana-2667	23	23	populations	population	NOUN
cana-2667	23	24	,	,	PUNCT
cana-2667	23	25	which	which	PRON
cana-2667	23	26	will	will	AUX
cana-2667	23	27	give	give	VERB
cana-2667	23	28	rise	rise	NOUN
cana-2667	23	29	to	to	ADP
cana-2667	23	30	an	an	DET
cana-2667	23	31	ever	ever	ADV
cana-2667	23	32	-	-	PUNCT
cana-2667	23	33	increasing	increase	VERB
cana-2667	23	34	strain	strain	NOUN
cana-2667	23	35	on	on	ADP
cana-2667	23	36	health	health	NOUN
cana-2667	23	37	care	care	NOUN
cana-2667	23	38	services	service	NOUN
cana-2667	23	39	worldwide	worldwide	ADV
cana-2667	23	40	.	.	PUNCT
cana-2667	24	1	retinopathy	retinopathy	PROPN
cana-2667	24	2	used	use	VERB
cana-2667	24	3	to	to	PART
cana-2667	24	4	be	be	AUX
cana-2667	24	5	diagnosed	diagnose	VERB
cana-2667	24	6	by	by	ADP
cana-2667	24	7	ophthalmologists	ophthalmologist	NOUN
cana-2667	24	8	primarily	primarily	ADV
cana-2667	24	9	by	by	ADP
cana-2667	24	10	examining	examine	VERB
cana-2667	24	11	retinal	retinal	ADJ
cana-2667	24	12	pictures	picture	NOUN
cana-2667	24	13	for	for	ADP
cana-2667	24	14	the	the	DET
cana-2667	24	15	signatures	signature	NOUN
cana-2667	24	16	of	of	ADP
cana-2667	24	17	the	the	DET
cana-2667	24	18	disease	disease	NOUN
cana-2667	24	19	.	.	PUNCT
cana-2667	25	1	fundus	fundus	NOUN
cana-2667	25	2	images	image	NOUN
cana-2667	25	3	were	be	AUX
cana-2667	25	4	obtained	obtain	VERB
cana-2667	25	5	using	use	VERB
cana-2667	25	6	dedicated	dedicated	ADJ
cana-2667	25	7	imaging	imaging	NOUN
cana-2667	25	8	systems	system	NOUN
cana-2667	25	9	and	and	CCONJ
cana-2667	25	10	visual	visual	ADJ
cana-2667	25	11	inspection	inspection	NOUN
cana-2667	25	12	was	be	AUX
cana-2667	25	13	performed	perform	VERB
cana-2667	25	14	for	for	ADP
cana-2667	25	15	representative	representative	ADJ
cana-2667	25	16	features	feature	NOUN
cana-2667	25	17	including	include	VERB
cana-2667	25	18	microaneurysms	microaneurysm	NOUN
cana-2667	25	19	,	,	PUNCT
cana-2667	25	20	hemorphages	hemorphage	NOUN
cana-2667	25	21	,	,	PUNCT
cana-2667	25	22	exudates	exudate	NOUN
cana-2667	25	23	,	,	PUNCT
cana-2667	25	24	and	and	CCONJ
cana-2667	25	25	neovascularization	neovascularization	NOUN
cana-2667	25	26	.	.	PUNCT
cana-2667	26	1	these	these	DET
cana-2667	26	2	symptoms	symptom	NOUN
cana-2667	26	3	show	show	VERB
cana-2667	26	4	the	the	DET
cana-2667	26	5	existence	existence	NOUN
cana-2667	26	6	of	of	ADP
cana-2667	26	7	retinopathy	retinopathy	ADJ
cana-2667	26	8	as	as	ADV
cana-2667	26	9	well	well	ADV
cana-2667	26	10	as	as	ADP
cana-2667	26	11	by	by	ADP
cana-2667	26	12	its	its	PRON
cana-2667	26	13	severity	severity	NOUN
cana-2667	26	14	.	.	PUNCT
cana-2667	27	1	while	while	SCONJ
cana-2667	27	2	the	the	DET
cana-2667	27	3	proficiency	proficiency	NOUN
cana-2667	27	4	of	of	ADP
cana-2667	27	5	eye	eye	NOUN
cana-2667	27	6	doctors	doctor	NOUN
cana-2667	27	7	is	be	AUX
cana-2667	27	8	essential	essential	ADJ
cana-2667	27	9	,	,	PUNCT
cana-2667	27	10	a	a	DET
cana-2667	27	11	manual	manual	ADJ
cana-2667	27	12	inspection	inspection	NOUN
cana-2667	27	13	is	be	AUX
cana-2667	27	14	extremely	extremely	ADV
cana-2667	27	15	tedious	tedious	ADJ
cana-2667	27	16	and	and	CCONJ
cana-2667	27	17	demands	demand	VERB
cana-2667	27	18	an	an	DET
cana-2667	27	19	extensive	extensive	ADJ
cana-2667	27	20	amount	amount	NOUN
cana-2667	27	21	of	of	ADP
cana-2667	27	22	expertise	expertise	NOUN
cana-2667	27	23	and	and	CCONJ
cana-2667	27	24	practice	practice	NOUN
cana-2667	27	25	.	.	PUNCT
cana-2667	28	1	additionally	additionally	ADV
cana-2667	28	2	,	,	PUNCT
cana-2667	28	3	the	the	DET
cana-2667	28	4	worldwide	worldwide	ADJ
cana-2667	28	5	shortage	shortage	NOUN
cana-2667	28	6	of	of	ADP
cana-2667	28	7	ophthalmologists	ophthalmologist	NOUN
cana-2667	28	8	particularly	particularly	ADV
cana-2667	28	9	in	in	ADP
cana-2667	28	10	underserved	underserved	ADJ
cana-2667	28	11	areas	area	NOUN
cana-2667	28	12	has	have	AUX
cana-2667	28	13	led	lead	VERB
cana-2667	28	14	to	to	ADP
cana-2667	28	15	delays	delay	NOUN
cana-2667	28	16	in	in	ADP
cana-2667	28	17	diagnosis	diagnosis	NOUN
cana-2667	28	18	and	and	CCONJ
cana-2667	28	19	treatment	treatment	NOUN
cana-2667	28	20	;	;	PUNCT
cana-2667	28	21	therefore	therefore	ADV
cana-2667	28	22	,	,	PUNCT
cana-2667	28	23	it	it	PRON
cana-2667	28	24	is	be	AUX
cana-2667	28	25	vital	vital	ADJ
cana-2667	28	26	to	to	PART
cana-2667	28	27	create	create	VERB
cana-2667	28	28	automated	automate	VERB
cana-2667	28	29	systems	system	NOUN
cana-2667	28	30	able	able	ADJ
cana-2667	28	31	to	to	PART
cana-2667	28	32	support	support	VERB
cana-2667	28	33	health	health	NOUN
cana-2667	28	34	care	care	NOUN
cana-2667	28	35	workers	worker	NOUN
cana-2667	28	36	in	in	ADP
cana-2667	28	37	timely	timely	ADJ
cana-2667	28	38	identification	identification	NOUN
cana-2667	28	39	and	and	CCONJ
cana-2667	28	40	intervention[1	intervention[1	NOUN
cana-2667	28	41	]	]	X
cana-2667	28	42	.	.	PUNCT
cana-2667	29	1	advancements	advancement	NOUN
cana-2667	29	2	in	in	ADP
cana-2667	29	3	imaging	imaging	NOUN
cana-2667	29	4	technologies	technology	NOUN
cana-2667	29	5	and	and	CCONJ
cana-2667	29	6	machine	machine	NOUN
cana-2667	29	7	learning	learning	NOUN
cana-2667	29	8	(	(	PUNCT
cana-2667	29	9	ml	ml	NOUN
cana-2667	29	10	)	)	PUNCT
cana-2667	29	11	methods	method	NOUN
cana-2667	29	12	recently	recently	ADV
cana-2667	29	13	paved	pave	VERB
cana-2667	29	14	the	the	DET
cana-2667	29	15	way	way	NOUN
cana-2667	29	16	for	for	ADP
cana-2667	29	17	automated	automate	VERB
cana-2667	29	18	devices	device	NOUN
cana-2667	29	19	for	for	ADP
cana-2667	29	20	retinopathy	retinopathy	ADJ
cana-2667	29	21	detection	detection	NOUN
cana-2667	29	22	.	.	PUNCT
cana-2667	30	1	recent	recent	ADJ
cana-2667	30	2	years	year	NOUN
cana-2667	30	3	have	have	AUX
cana-2667	30	4	witnessed	witness	VERB
cana-2667	30	5	the	the	DET
cana-2667	30	6	emergence	emergence	NOUN
cana-2667	30	7	of	of	ADP
cana-2667	30	8	machine	machine	NOUN
cana-2667	30	9	learning	learn	VERB
cana-2667	30	10	techniques	technique	NOUN
cana-2667	30	11	,	,	PUNCT
cana-2667	30	12	which	which	PRON
cana-2667	30	13	have	have	AUX
cana-2667	30	14	enabled	enable	VERB
cana-2667	30	15	the	the	DET
cana-2667	30	16	transition	transition	NOUN
cana-2667	30	17	from	from	ADP
cana-2667	30	18	manual	manual	ADJ
cana-2667	30	19	analysis	analysis	NOUN
cana-2667	30	20	to	to	ADP
cana-2667	30	21	automated	automate	VERB
cana-2667	30	22	systems	system	NOUN
cana-2667	30	23	that	that	PRON
cana-2667	30	24	can	can	AUX
cana-2667	30	25	efficiently	efficiently	ADV
cana-2667	30	26	classify	classify	VERB
cana-2667	30	27	and	and	CCONJ
cana-2667	30	28	diagnose	diagnose	NOUN
cana-2667	30	29	diseases	disease	NOUN
cana-2667	30	30	occurring	occur	VERB
cana-2667	30	31	in	in	ADP
cana-2667	30	32	the	the	DET
cana-2667	30	33	retinal	retinal	ADJ
cana-2667	30	34	system	system	NOUN
cana-2667	30	35	.	.	PUNCT
cana-2667	31	1	however	however	ADV
cana-2667	31	2	,	,	PUNCT
cana-2667	31	3	this	this	DET
cana-2667	31	4	task	task	NOUN
cana-2667	31	5	is	be	AUX
cana-2667	31	6	still	still	ADV
cana-2667	31	7	very	very	ADV
cana-2667	31	8	challenging	challenging	ADJ
cana-2667	31	9	due	due	ADJ
cana-2667	31	10	to	to	ADP
cana-2667	31	11	some	some	DET
cana-2667	31	12	reasons	reason	NOUN
cana-2667	31	13	such	such	ADJ
cana-2667	31	14	as	as	ADP
cana-2667	31	15	vary	vary	NOUN
cana-2667	31	16	of	of	ADP
cana-2667	31	17	the	the	DET
cana-2667	31	18	retinal	retinal	ADJ
cana-2667	31	19	images	image	NOUN
cana-2667	31	20	,	,	PUNCT
cana-2667	31	21	differences	difference	NOUN
cana-2667	31	22	in	in	ADP
cana-2667	31	23	the	the	DET
cana-2667	31	24	develop	develop	NOUN
cana-2667	31	25	rate	rate	NOUN
cana-2667	31	26	of	of	ADP
cana-2667	31	27	the	the	DET
cana-2667	31	28	disease	disease	NOUN
cana-2667	31	29	between	between	ADP
cana-2667	31	30	individuals	individual	NOUN
cana-2667	31	31	,	,	PUNCT
cana-2667	31	32	and	and	CCONJ
cana-2667	31	33	noise	noise	NOUN
cana-2667	31	34	in	in	ADP
cana-2667	31	35	the	the	DET
cana-2667	31	36	images	image	NOUN
cana-2667	31	37	.	.	PUNCT
cana-2667	32	1	problem	problem	NOUN
cana-2667	32	2	statement	statement	NOUN
cana-2667	32	3	the	the	DET
cana-2667	32	4	second	second	ADJ
cana-2667	32	5	challenge	challenge	NOUN
cana-2667	32	6	is	be	AUX
cana-2667	32	7	the	the	DET
cana-2667	32	8	significant	significant	ADJ
cana-2667	32	9	degree	degree	NOUN
cana-2667	32	10	of	of	ADP
cana-2667	32	11	complexity	complexity	NOUN
cana-2667	32	12	and	and	CCONJ
cana-2667	32	13	variability	variability	NOUN
cana-2667	32	14	of	of	ADP
cana-2667	32	15	the	the	DET
cana-2667	32	16	disease	disease	NOUN
cana-2667	32	17	which	which	PRON
cana-2667	32	18	complicates	complicate	VERB
cana-2667	32	19	the	the	DET
cana-2667	32	20	diagnosis	diagnosis	NOUN
cana-2667	32	21	of	of	ADP
cana-2667	32	22	retinopathy	retinopathy	NOUN
cana-2667	32	23	.	.	PUNCT
cana-2667	33	1	retinopathy	retinopathy	ADJ
cana-2667	33	2	is	be	AUX
cana-2667	33	3	not	not	PART
cana-2667	33	4	easy	easy	ADJ
cana-2667	33	5	to	to	PART
cana-2667	33	6	detect	detect	VERB
cana-2667	33	7	because	because	SCONJ
cana-2667	33	8	subtle	subtle	ADJ
cana-2667	33	9	changes	change	NOUN
cana-2667	33	10	in	in	ADP
cana-2667	33	11	the	the	DET
cana-2667	33	12	retina	retina	NOUN
cana-2667	33	13	occur	occur	VERB
cana-2667	33	14	during	during	ADP
cana-2667	33	15	the	the	DET
cana-2667	33	16	progression	progression	NOUN
cana-2667	33	17	of	of	ADP
cana-2667	33	18	this	this	DET
cana-2667	33	19	condition	condition	NOUN
cana-2667	33	20	.	.	PUNCT
cana-2667	34	1	retinal	retinal	ADJ
cana-2667	34	2	images	image	NOUN
cana-2667	34	3	are	be	AUX
cana-2667	34	4	inherently	inherently	ADV
cana-2667	34	5	noisy	noisy	ADJ
cana-2667	34	6	and	and	CCONJ
cana-2667	34	7	have	have	VERB
cana-2667	34	8	noise	noise	NOUN
cana-2667	34	9	that	that	PRON
cana-2667	34	10	can	can	AUX
cana-2667	34	11	come	come	VERB
cana-2667	34	12	from	from	ADP
cana-2667	34	13	different	different	ADJ
cana-2667	34	14	sources	source	NOUN
cana-2667	34	15	,	,	PUNCT
cana-2667	34	16	such	such	ADJ
cana-2667	34	17	as	as	ADP
cana-2667	34	18	the	the	DET
cana-2667	34	19	strength	strength	NOUN
cana-2667	34	20	of	of	ADP
cana-2667	34	21	light	light	NOUN
cana-2667	34	22	,	,	PUNCT
cana-2667	34	23	capture	capture	VERB
cana-2667	34	24	quality	quality	NOUN
cana-2667	34	25	,	,	PUNCT
cana-2667	34	26	and	and	CCONJ
cana-2667	34	27	patient	patient	ADJ
cana-2667	34	28	movement	movement	NOUN
cana-2667	34	29	.	.	PUNCT
cana-2667	35	1	as	as	ADV
cana-2667	35	2	well	well	ADV
cana-2667	35	3	,	,	PUNCT
cana-2667	35	4	retinopathy	retinopathy	ADJ
cana-2667	35	5	may	may	AUX
cana-2667	35	6	differ	differ	VERB
cana-2667	35	7	amongst	amongst	ADP
cana-2667	35	8	patients	patient	NOUN
cana-2667	35	9	,	,	PUNCT
cana-2667	35	10	including	include	VERB
cana-2667	35	11	differences	difference	NOUN
cana-2667	35	12	in	in	ADP
cana-2667	35	13	staging	staging	NOUN
cana-2667	35	14	and	and	CCONJ
cana-2667	35	15	severity[2	severity[2	PROPN
cana-2667	35	16	]	]	PUNCT
cana-2667	35	17	.	.	PUNCT
cana-2667	36	1	these	these	DET
cana-2667	36	2	factors	factor	NOUN
cana-2667	36	3	make	make	VERB
cana-2667	36	4	traditional	traditional	ADJ
cana-2667	36	5	manual	manual	ADJ
cana-2667	36	6	diagnosis	diagnosis	NOUN
cana-2667	36	7	,	,	PUNCT
cana-2667	36	8	which	which	PRON
cana-2667	36	9	is	be	AUX
cana-2667	36	10	slow	slow	ADJ
cana-2667	36	11	and	and	CCONJ
cana-2667	36	12	can	can	AUX
cana-2667	36	13	lead	lead	VERB
cana-2667	36	14	to	to	ADP
cana-2667	36	15	human	human	ADJ
cana-2667	36	16	fallibility	fallibility	NOUN
cana-2667	36	17	,	,	PUNCT
cana-2667	36	18	a	a	DET
cana-2667	36	19	significant	significant	ADJ
cana-2667	36	20	challenge	challenge	NOUN
cana-2667	36	21	.	.	PUNCT
cana-2667	36	22	”	"	PUNCT
cana-2667	37	1	with	with	ADP
cana-2667	37	2	the	the	DET
cana-2667	37	3	increasing	increase	VERB
cana-2667	37	4	incidence	incidence	NOUN
cana-2667	37	5	of	of	ADP
cana-2667	37	6	retinopathy	retinopathy	ADJ
cana-2667	37	7	and	and	CCONJ
cana-2667	37	8	the	the	DET
cana-2667	37	9	scarcity	scarcity	NOUN
cana-2667	37	10	of	of	ADP
cana-2667	37	11	ophthalmic	ophthalmic	ADJ
cana-2667	37	12	specialists	specialist	NOUN
cana-2667	37	13	in	in	ADP
cana-2667	37	14	many	many	ADJ
cana-2667	37	15	areas	area	NOUN
cana-2667	37	16	,	,	PUNCT
cana-2667	37	17	an	an	DET
cana-2667	37	18	automated	automate	VERB
cana-2667	37	19	system	system	NOUN
cana-2667	37	20	that	that	PRON
cana-2667	37	21	can	can	AUX
cana-2667	37	22	accurately	accurately	ADV
cana-2667	37	23	classify	classify	VERB
cana-2667	37	24	retinopathy	retinopathy	ADJ
cana-2667	37	25	and	and	CCONJ
cana-2667	37	26	help	help	VERB
cana-2667	37	27	medical	medical	ADJ
cana-2667	37	28	professionals	professional	NOUN
cana-2667	37	29	make	make	VERB
cana-2667	37	30	prompt	prompt	ADJ
cana-2667	37	31	diagnoses	diagnosis	NOUN
cana-2667	37	32	is	be	AUX
cana-2667	37	33	urgently	urgently	ADV
cana-2667	37	34	needed[3	needed[3	NUM
cana-2667	37	35	]	]	PUNCT
cana-2667	37	36	.	.	PUNCT
cana-2667	38	1	a	a	DET
cana-2667	38	2	major	major	ADJ
cana-2667	38	3	challenge	challenge	NOUN
cana-2667	38	4	for	for	ADP
cana-2667	38	5	automated	automate	VERB
cana-2667	38	6	systems	system	NOUN
cana-2667	38	7	aimed	aim	VERB
cana-2667	38	8	at	at	ADP
cana-2667	38	9	classifying	classify	VERB
cana-2667	38	10	retinopathy	retinopathy	NOUN
cana-2667	38	11	is	be	AUX
cana-2667	38	12	to	to	PART
cana-2667	38	13	find	find	VERB
cana-2667	38	14	ways	way	NOUN
cana-2667	38	15	to	to	PART
cana-2667	38	16	process	process	VERB
cana-2667	38	17	retinal	retinal	ADJ
cana-2667	38	18	images	image	NOUN
cana-2667	38	19	efficiently	efficiently	ADV
cana-2667	38	20	.	.	PUNCT
cana-2667	39	1	retinal	retinal	ADJ
cana-2667	39	2	images	image	NOUN
cana-2667	39	3	are	be	AUX
cana-2667	39	4	complex	complex	ADJ
cana-2667	39	5	and	and	CCONJ
cana-2667	39	6	high	high	ADV
cana-2667	39	7	-	-	PUNCT
cana-2667	39	8	dimensional	dimensional	ADJ
cana-2667	39	9	,	,	PUNCT
cana-2667	39	10	which	which	PRON
cana-2667	39	11	poses	pose	VERB
cana-2667	39	12	challenges	challenge	NOUN
cana-2667	39	13	for	for	ADP
cana-2667	39	14	traditional	traditional	ADJ
cana-2667	39	15	-	-	PUNCT
cana-2667	39	16	image	image	NOUN
cana-2667	39	17	processing	processing	NOUN
cana-2667	39	18	methods	method	NOUN
cana-2667	39	19	.	.	PUNCT
cana-2667	40	1	thus	thus	ADV
cana-2667	40	2	,	,	PUNCT
cana-2667	40	3	automated	automate	VERB
cana-2667	40	4	systems	system	NOUN
cana-2667	40	5	will	will	AUX
cana-2667	40	6	need	need	VERB
cana-2667	40	7	to	to	PART
cana-2667	40	8	distinguish	distinguish	VERB
cana-2667	40	9	between	between	ADP
cana-2667	40	10	healthy	healthy	ADJ
cana-2667	40	11	and	and	CCONJ
cana-2667	40	12	affected	affect	VERB
cana-2667	40	13	images	image	NOUN
cana-2667	40	14	at	at	ADP
cana-2667	40	15	different	different	ADJ
cana-2667	40	16	stages	stage	NOUN
cana-2667	40	17	of	of	ADP
cana-2667	40	18	disease	disease	NOUN
cana-2667	40	19	progression	progression	NOUN
cana-2667	40	20	.	.	PUNCT
cana-2667	41	1	even	even	ADV
cana-2667	41	2	small	small	ADJ
cana-2667	41	3	deviations	deviation	NOUN
cana-2667	41	4	in	in	ADP
cana-2667	41	5	retinal	retinal	ADJ
cana-2667	41	6	images	image	NOUN
cana-2667	41	7	can	can	AUX
cana-2667	41	8	severely	severely	ADV
cana-2667	41	9	hurt	hurt	VERB
cana-2667	41	10	classification	classification	NOUN
cana-2667	41	11	accuracy	accuracy	NOUN
cana-2667	41	12	,	,	PUNCT
cana-2667	41	13	underscoring	underscore	VERB
cana-2667	41	14	the	the	DET
cana-2667	41	15	need	need	NOUN
cana-2667	41	16	for	for	ADP
cana-2667	41	17	models	model	NOUN
cana-2667	41	18	that	that	PRON
cana-2667	41	19	achieve	achieve	VERB
cana-2667	41	20	both	both	DET
cana-2667	41	21	high	high	ADJ
cana-2667	41	22	accuracy	accuracy	NOUN
cana-2667	41	23	and	and	CCONJ
cana-2667	41	24	generalizability	generalizability	NOUN
cana-2667	41	25	to	to	ADP
cana-2667	41	26	unseen	unseen	ADJ
cana-2667	41	27	data	datum	NOUN
cana-2667	41	28	.	.	PUNCT
cana-2667	42	1	a	a	DET
cana-2667	42	2	second	second	ADJ
cana-2667	42	3	concern	concern	NOUN
cana-2667	42	4	is	be	AUX
cana-2667	42	5	overfitting	overfitte	VERB
cana-2667	42	6	,	,	PUNCT
cana-2667	42	7	where	where	SCONJ
cana-2667	42	8	many	many	ADJ
cana-2667	42	9	types	type	NOUN
cana-2667	42	10	of	of	ADP
cana-2667	42	11	machine	machine	NOUN
cana-2667	42	12	learning	learning	NOUN
cana-2667	42	13	models	model	NOUN
cana-2667	42	14	find	find	VERB
cana-2667	42	15	it	it	PRON
cana-2667	42	16	difficult	difficult	ADJ
cana-2667	42	17	to	to	PART
cana-2667	42	18	do	do	VERB
cana-2667	42	19	well	well	ADV
cana-2667	42	20	as	as	ADP
cana-2667	42	21	generalizers	generalizer	NOUN
cana-2667	42	22	with	with	ADP
cana-2667	42	23	limited	limited	ADJ
cana-2667	42	24	or	or	CCONJ
cana-2667	42	25	noisy	noisy	ADJ
cana-2667	42	26	data	datum	NOUN
cana-2667	42	27	.	.	PUNCT
cana-2667	43	1	furthermore	furthermore	ADV
cana-2667	43	2	,	,	PUNCT
cana-2667	43	3	the	the	DET
cana-2667	43	4	limited	limited	ADJ
cana-2667	43	5	availability	availability	NOUN
cana-2667	43	6	of	of	ADP
cana-2667	43	7	large	large	ADJ
cana-2667	43	8	labeled	label	VERB
cana-2667	43	9	datasets	dataset	NOUN
cana-2667	43	10	in	in	ADP
cana-2667	43	11	medical	medical	ADJ
cana-2667	43	12	imaging	imaging	NOUN
cana-2667	43	13	makes	make	VERB
cana-2667	43	14	it	it	PRON
cana-2667	43	15	even	even	ADV
cana-2667	43	16	communications	communication	NOUN
cana-2667	43	17	on	on	ADP
cana-2667	43	18	applied	apply	VERB
cana-2667	43	19	nonlinear	nonlinear	ADJ
cana-2667	43	20	analysis	analysis	NOUN
cana-2667	43	21	issn	issn	NOUN
cana-2667	43	22	:	:	PUNCT
cana-2667	43	23	1074	1074	NUM
cana-2667	43	24	-	-	PUNCT
cana-2667	43	25	133x	133x	NUM
cana-2667	43	26	vol	vol	NOUN
cana-2667	43	27	32	32	NUM
cana-2667	44	1	no	no	NOUN
cana-2667	44	2	.	.	PUNCT
cana-2667	45	1	3s	3s	NUM
cana-2667	45	2	(	(	PUNCT
cana-2667	45	3	2025	2025	NUM
cana-2667	45	4	)	)	PUNCT
cana-2667	45	5	381	381	NUM
cana-2667	45	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	45	7	challenging	challenge	VERB
cana-2667	45	8	to	to	PART
cana-2667	45	9	develop	develop	VERB
cana-2667	45	10	robust	robust	ADJ
cana-2667	45	11	automated	automate	VERB
cana-2667	45	12	systems	system	NOUN
cana-2667	45	13	.	.	PUNCT
cana-2667	46	1	as	as	ADP
cana-2667	46	2	such	such	ADJ
cana-2667	46	3	,	,	PUNCT
cana-2667	46	4	the	the	DET
cana-2667	46	5	problem	problem	NOUN
cana-2667	46	6	statement	statement	NOUN
cana-2667	46	7	boils	boil	VERB
cana-2667	46	8	down	down	ADP
cana-2667	46	9	to	to	ADP
cana-2667	46	10	creating	create	VERB
cana-2667	46	11	an	an	DET
cana-2667	46	12	automated	automate	VERB
cana-2667	46	13	,	,	PUNCT
cana-2667	46	14	accurate	accurate	ADJ
cana-2667	46	15	,	,	PUNCT
cana-2667	46	16	and	and	CCONJ
cana-2667	46	17	reliable	reliable	ADJ
cana-2667	46	18	retinopathy	retinopathy	ADJ
cana-2667	46	19	classification	classification	NOUN
cana-2667	46	20	system	system	NOUN
cana-2667	46	21	that	that	PRON
cana-2667	46	22	does	do	VERB
cana-2667	46	23	justice	justice	NOUN
cana-2667	46	24	by	by	ADP
cana-2667	46	25	the	the	DET
cana-2667	46	26	complexities	complexity	NOUN
cana-2667	46	27	and	and	CCONJ
cana-2667	46	28	intricacies	intricacy	NOUN
cana-2667	46	29	of	of	ADP
cana-2667	46	30	retinal	retinal	ADJ
cana-2667	46	31	images	image	NOUN
cana-2667	46	32	while	while	SCONJ
cana-2667	46	33	being	be	AUX
cana-2667	46	34	minimally	minimally	ADV
cana-2667	46	35	overfitting	overfitte	VERB
cana-2667	46	36	and	and	CCONJ
cana-2667	46	37	needing	need	VERB
cana-2667	46	38	minimal	minimal	ADJ
cana-2667	46	39	labeled	label	VERB
cana-2667	46	40	data[4	data[4	NOUN
cana-2667	46	41	]	]	PUNCT
cana-2667	46	42	.	.	PUNCT
cana-2667	47	1	figure	figure	NOUN
cana-2667	47	2	1	1	NUM
cana-2667	47	3	.	.	PUNCT
cana-2667	48	1	research	research	NOUN
cana-2667	48	2	focus	focus	NOUN
cana-2667	48	3	on	on	ADP
cana-2667	48	4	retinopathy	retinopathy	ADJ
cana-2667	48	5	previous	previous	ADJ
cana-2667	48	6	approaches	approach	NOUN
cana-2667	48	7	many	many	ADJ
cana-2667	48	8	approaches	approach	NOUN
cana-2667	48	9	have	have	AUX
cana-2667	48	10	been	be	AUX
cana-2667	48	11	attempted	attempt	VERB
cana-2667	48	12	to	to	PART
cana-2667	48	13	solve	solve	VERB
cana-2667	48	14	the	the	DET
cana-2667	48	15	classification	classification	NOUN
cana-2667	48	16	of	of	ADP
cana-2667	48	17	retinopathy	retinopathy	ADJ
cana-2667	48	18	over	over	ADP
cana-2667	48	19	the	the	DET
cana-2667	48	20	past	past	ADJ
cana-2667	48	21	decades	decade	NOUN
cana-2667	48	22	.	.	PUNCT
cana-2667	49	1	initial	initial	ADJ
cana-2667	49	2	approaches	approach	NOUN
cana-2667	49	3	heavily	heavily	ADV
cana-2667	49	4	relied	rely	VERB
cana-2667	49	5	on	on	ADP
cana-2667	49	6	first	first	ADV
cana-2667	49	7	performing	perform	VERB
cana-2667	49	8	image	image	NOUN
cana-2667	49	9	processing	processing	NOUN
cana-2667	49	10	techniques	technique	NOUN
cana-2667	49	11	to	to	PART
cana-2667	49	12	extract	extract	VERB
cana-2667	49	13	features	feature	NOUN
cana-2667	49	14	from	from	ADP
cana-2667	49	15	retinal	retinal	ADJ
cana-2667	49	16	images	image	NOUN
cana-2667	49	17	manually	manually	ADV
cana-2667	49	18	.	.	PUNCT
cana-2667	50	1	these	these	DET
cana-2667	50	2	methodologies	methodology	NOUN
cana-2667	50	3	consisted	consist	VERB
cana-2667	50	4	out	out	ADP
cana-2667	50	5	of	of	ADP
cana-2667	50	6	fundamental	fundamental	ADJ
cana-2667	50	7	functions	function	NOUN
cana-2667	50	8	like	like	ADP
cana-2667	50	9	edge	edge	NOUN
cana-2667	50	10	recognition	recognition	NOUN
cana-2667	50	11	,	,	PUNCT
cana-2667	50	12	thresholding	thresholding	NOUN
cana-2667	50	13	,	,	PUNCT
cana-2667	50	14	and	and	CCONJ
cana-2667	50	15	morphological	morphological	ADJ
cana-2667	50	16	transformations	transformation	NOUN
cana-2667	50	17	.	.	PUNCT
cana-2667	51	1	the	the	DET
cana-2667	51	2	early	early	ADJ
cana-2667	51	3	algorithms	algorithm	NOUN
cana-2667	51	4	would	would	AUX
cana-2667	51	5	extract	extract	VERB
cana-2667	51	6	basic	basic	ADJ
cana-2667	51	7	features	feature	NOUN
cana-2667	51	8	like	like	ADP
cana-2667	51	9	blood	blood	NOUN
cana-2667	51	10	vessels	vessel	NOUN
cana-2667	51	11	,	,	PUNCT
cana-2667	51	12	microaneurysms	microaneurysm	NOUN
cana-2667	51	13	,	,	PUNCT
cana-2667	51	14	exudates	exudate	NOUN
cana-2667	51	15	,	,	PUNCT
cana-2667	51	16	and	and	CCONJ
cana-2667	51	17	hemorrhages	hemorrhage	NOUN
cana-2667	51	18	followed	follow	VERB
cana-2667	51	19	by	by	ADP
cana-2667	51	20	classification	classification	NOUN
cana-2667	51	21	algorithms	algorithm	NOUN
cana-2667	51	22	(	(	PUNCT
cana-2667	51	23	decision	decision	NOUN
cana-2667	51	24	trees	tree	NOUN
cana-2667	51	25	,	,	PUNCT
cana-2667	51	26	k	k	NOUN
cana-2667	51	27	-	-	PUNCT
cana-2667	51	28	nearest	near	ADJ
cana-2667	51	29	neighbors	neighbor	NOUN
cana-2667	51	30	(	(	PUNCT
cana-2667	51	31	knn	knn	PROPN
cana-2667	51	32	)	)	PUNCT
cana-2667	51	33	,	,	PUNCT
cana-2667	51	34	support	support	VERB
cana-2667	51	35	vector	vector	NOUN
cana-2667	51	36	machines	machine	NOUN
cana-2667	51	37	(	(	PUNCT
cana-2667	51	38	svm	svm	PROPN
cana-2667	51	39	)	)	PUNCT
cana-2667	51	40	etc	etc	X
cana-2667	51	41	.	.	X
cana-2667	51	42	)	)	PUNCT
cana-2667	51	43	.	.	PUNCT
cana-2667	52	1	although	although	SCONJ
cana-2667	52	2	these	these	DET
cana-2667	52	3	methods	method	NOUN
cana-2667	52	4	were	be	AUX
cana-2667	52	5	partially	partially	ADV
cana-2667	52	6	successful	successful	ADJ
cana-2667	52	7	,	,	PUNCT
cana-2667	52	8	they	they	PRON
cana-2667	52	9	relied	rely	VERB
cana-2667	52	10	on	on	ADP
cana-2667	52	11	handcrafted	handcrafted	ADJ
cana-2667	52	12	features	feature	NOUN
cana-2667	52	13	that	that	PRON
cana-2667	52	14	were	be	AUX
cana-2667	52	15	not	not	PART
cana-2667	52	16	always	always	ADV
cana-2667	52	17	sufficient	sufficient	ADJ
cana-2667	52	18	to	to	PART
cana-2667	52	19	describe	describe	VERB
cana-2667	52	20	the	the	DET
cana-2667	52	21	complex	complex	ADJ
cana-2667	52	22	and	and	CCONJ
cana-2667	52	23	heterogeneous	heterogeneous	ADJ
cana-2667	52	24	properties	property	NOUN
cana-2667	52	25	of	of	ADP
cana-2667	52	26	retinal	retinal	ADJ
cana-2667	52	27	images	image	NOUN
cana-2667	52	28	.	.	PUNCT
cana-2667	53	1	additionally	additionally	ADV
cana-2667	53	2	,	,	PUNCT
cana-2667	53	3	these	these	DET
cana-2667	53	4	methods	method	NOUN
cana-2667	53	5	were	be	AUX
cana-2667	53	6	sensitive	sensitive	ADJ
cana-2667	53	7	to	to	ADP
cana-2667	53	8	noise	noise	NOUN
cana-2667	53	9	and	and	CCONJ
cana-2667	53	10	variability	variability	NOUN
cana-2667	53	11	in	in	ADP
cana-2667	53	12	images	image	NOUN
cana-2667	53	13	and	and	CCONJ
cana-2667	53	14	did	do	AUX
cana-2667	53	15	not	not	PART
cana-2667	53	16	generalize	generalize	VERB
cana-2667	53	17	well	well	ADV
cana-2667	53	18	across	across	ADP
cana-2667	53	19	different	different	ADJ
cana-2667	53	20	datasets	dataset	NOUN
cana-2667	53	21	and	and	CCONJ
cana-2667	53	22	imaging	imaging	NOUN
cana-2667	53	23	conditions	condition	NOUN
cana-2667	53	24	,	,	PUNCT
cana-2667	53	25	resulting	result	VERB
cana-2667	53	26	in	in	ADP
cana-2667	53	27	poor	poor	ADJ
cana-2667	53	28	performance	performance	NOUN
cana-2667	53	29	in	in	ADP
cana-2667	53	30	practical	practical	ADJ
cana-2667	53	31	scenarios[5	scenarios[5	NOUN
cana-2667	53	32	]	]	PUNCT
cana-2667	53	33	.	.	PUNCT
cana-2667	54	1	machine	machine	NOUN
cana-2667	54	2	learning	learn	VERB
cana-2667	54	3	[	[	X
cana-2667	54	4	6	6	NUM
cana-2667	54	5	]	]	PUNCT
cana-2667	54	6	came	come	VERB
cana-2667	54	7	at	at	ADP
cana-2667	54	8	this	this	DET
cana-2667	54	9	time	time	NOUN
cana-2667	54	10	,	,	PUNCT
cana-2667	54	11	the	the	DET
cana-2667	54	12	previous	previous	ADJ
cana-2667	54	13	efforts	effort	NOUN
cana-2667	54	14	were	be	AUX
cana-2667	54	15	abandoned	abandon	VERB
cana-2667	54	16	features	feature	NOUN
cana-2667	54	17	that	that	PRON
cana-2667	54	18	were	be	AUX
cana-2667	54	19	manually	manually	ADV
cana-2667	54	20	engineered	engineer	VERB
cana-2667	54	21	and	and	CCONJ
cana-2667	54	22	switched	switch	VERB
cana-2667	54	23	to	to	ADP
cana-2667	54	24	models	model	NOUN
cana-2667	54	25	that	that	PRON
cana-2667	54	26	learn	learn	VERB
cana-2667	54	27	from	from	ADP
cana-2667	54	28	the	the	DET
cana-2667	54	29	data	datum	NOUN
cana-2667	54	30	itself	itself	PRON
cana-2667	54	31	.	.	PUNCT
cana-2667	55	1	one	one	NUM
cana-2667	55	2	of	of	ADP
cana-2667	55	3	the	the	DET
cana-2667	55	4	most	most	ADV
cana-2667	55	5	significant	significant	ADJ
cana-2667	55	6	advances	advance	NOUN
cana-2667	55	7	in	in	ADP
cana-2667	55	8	this	this	DET
cana-2667	55	9	trajectory	trajectory	NOUN
cana-2667	55	10	was	be	AUX
cana-2667	55	11	the	the	DET
cana-2667	55	12	invention	invention	NOUN
cana-2667	55	13	of	of	ADP
cana-2667	55	14	deep	deep	ADJ
cana-2667	55	15	learning	learning	NOUN
cana-2667	55	16	,	,	PUNCT
cana-2667	55	17	specifically	specifically	ADV
cana-2667	55	18	cnn	cnn	PROPN
cana-2667	55	19	,	,	PUNCT
cana-2667	55	20	which	which	PRON
cana-2667	55	21	is	be	AUX
cana-2667	55	22	the	the	DET
cana-2667	55	23	state	state	NOUN
cana-2667	55	24	-	-	PUNCT
cana-2667	55	25	ofthe	ofthe	NOUN
cana-2667	55	26	-	-	PUNCT
cana-2667	55	27	art	art	NOUN
cana-2667	55	28	and	and	CCONJ
cana-2667	55	29	dominant	dominant	ADJ
cana-2667	55	30	model	model	NOUN
cana-2667	55	31	for	for	ADP
cana-2667	55	32	image	image	NOUN
cana-2667	55	33	classification	classification	NOUN
cana-2667	55	34	problems	problem	NOUN
cana-2667	55	35	,	,	PUNCT
cana-2667	55	36	including	include	VERB
cana-2667	55	37	detecting	detect	VERB
cana-2667	55	38	retinopathy	retinopathy	ADJ
cana-2667	55	39	.	.	PUNCT
cana-2667	56	1	cnns	cnns	PROPN
cana-2667	56	2	,	,	PUNCT
cana-2667	56	3	for	for	ADP
cana-2667	56	4	instance	instance	NOUN
cana-2667	56	5	,	,	PUNCT
cana-2667	56	6	learn	learn	VERB
cana-2667	56	7	hierarchical	hierarchical	ADJ
cana-2667	56	8	representations	representation	NOUN
cana-2667	56	9	of	of	ADP
cana-2667	56	10	images	image	NOUN
cana-2667	56	11	by	by	ADP
cana-2667	56	12	applying	apply	VERB
cana-2667	56	13	multiple	multiple	ADJ
cana-2667	56	14	layers	layer	NOUN
cana-2667	56	15	of	of	ADP
cana-2667	56	16	convolution	convolution	NOUN
cana-2667	56	17	to	to	ADP
cana-2667	56	18	the	the	DET
cana-2667	56	19	input	input	NOUN
cana-2667	56	20	(	(	PUNCT
cana-2667	56	21	the	the	DET
cana-2667	56	22	image	image	NOUN
cana-2667	56	23	)	)	PUNCT
cana-2667	56	24	and	and	CCONJ
cana-2667	56	25	learning	learn	VERB
cana-2667	56	26	various	various	ADJ
cana-2667	56	27	levels	level	NOUN
cana-2667	56	28	of	of	ADP
cana-2667	56	29	abstraction	abstraction	NOUN
cana-2667	56	30	from	from	ADP
cana-2667	56	31	the	the	DET
cana-2667	56	32	edges	edge	NOUN
cana-2667	56	33	at	at	ADP
cana-2667	56	34	the	the	DET
cana-2667	56	35	low	low	ADJ
cana-2667	56	36	level	level	NOUN
cana-2667	56	37	to	to	ADP
cana-2667	56	38	structures	structure	NOUN
cana-2667	56	39	at	at	ADP
cana-2667	56	40	the	the	DET
cana-2667	56	41	higher	high	ADJ
cana-2667	56	42	one	one	NOUN
cana-2667	56	43	.	.	PUNCT
cana-2667	57	1	the	the	DET
cana-2667	57	2	use	use	NOUN
cana-2667	57	3	of	of	ADP
cana-2667	57	4	cnns	cnn	NOUN
cana-2667	57	5	for	for	ADP
cana-2667	57	6	retinopathy	retinopathy	ADJ
cana-2667	57	7	allows	allow	VERB
cana-2667	57	8	for	for	ADP
cana-2667	57	9	the	the	DET
cana-2667	57	10	automatic	automatic	ADJ
cana-2667	57	11	learning	learning	NOUN
cana-2667	57	12	of	of	ADP
cana-2667	57	13	low	low	ADJ
cana-2667	57	14	,	,	PUNCT
cana-2667	57	15	communications	communication	NOUN
cana-2667	57	16	on	on	ADP
cana-2667	57	17	applied	apply	VERB
cana-2667	57	18	nonlinear	nonlinear	ADJ
cana-2667	57	19	analysis	analysis	NOUN
cana-2667	57	20	issn	issn	NOUN
cana-2667	57	21	:	:	PUNCT
cana-2667	57	22	1074	1074	NUM
cana-2667	57	23	-	-	PUNCT
cana-2667	57	24	133x	133x	NUM
cana-2667	57	25	vol	vol	NOUN
cana-2667	57	26	32	32	NUM
cana-2667	57	27	no	no	NOUN
cana-2667	57	28	.	.	PUNCT
cana-2667	58	1	3s	3s	NUM
cana-2667	58	2	(	(	PUNCT
cana-2667	58	3	2025	2025	NUM
cana-2667	58	4	)	)	PUNCT
cana-2667	58	5	382	382	NUM
cana-2667	58	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	58	7	mid	mid	ADJ
cana-2667	58	8	,	,	PUNCT
cana-2667	58	9	and	and	CCONJ
cana-2667	58	10	high	high	ADJ
cana-2667	58	11	-	-	PUNCT
cana-2667	58	12	level	level	NOUN
cana-2667	58	13	features	feature	NOUN
cana-2667	58	14	from	from	ADP
cana-2667	58	15	retinal	retinal	ADJ
cana-2667	58	16	images	image	NOUN
cana-2667	58	17	,	,	PUNCT
cana-2667	58	18	as	as	SCONJ
cana-2667	58	19	opposed	oppose	VERB
cana-2667	58	20	to	to	ADP
cana-2667	58	21	the	the	DET
cana-2667	58	22	manual	manual	ADJ
cana-2667	58	23	extraction	extraction	NOUN
cana-2667	58	24	performed	perform	VERB
cana-2667	58	25	in	in	ADP
cana-2667	58	26	traditional	traditional	ADJ
cana-2667	58	27	image	image	NOUN
cana-2667	58	28	processing	processing	NOUN
cana-2667	58	29	methods	method	NOUN
cana-2667	58	30	.	.	PUNCT
cana-2667	59	1	recently	recently	ADV
cana-2667	59	2	,	,	PUNCT
cana-2667	59	3	deep	deep	ADJ
cana-2667	59	4	learning	learn	VERB
cana-2667	59	5	neural	neural	ADJ
cana-2667	59	6	network	network	NOUN
cana-2667	59	7	models	model	NOUN
cana-2667	59	8	(	(	PUNCT
cana-2667	59	9	like	like	ADP
cana-2667	59	10	cnns	cnn	NOUN
cana-2667	59	11	)	)	PUNCT
cana-2667	59	12	have	have	AUX
cana-2667	59	13	achieved	achieve	VERB
cana-2667	59	14	great	great	ADJ
cana-2667	59	15	success	success	NOUN
cana-2667	59	16	in	in	ADP
cana-2667	59	17	many	many	ADJ
cana-2667	59	18	fields	field	NOUN
cana-2667	59	19	,	,	PUNCT
cana-2667	59	20	such	such	ADJ
cana-2667	59	21	as	as	ADP
cana-2667	59	22	image	image	NOUN
cana-2667	59	23	classification	classification	NOUN
cana-2667	59	24	,	,	PUNCT
cana-2667	59	25	object	object	NOUN
cana-2667	59	26	detection	detection	NOUN
cana-2667	59	27	,	,	PUNCT
cana-2667	59	28	segmentation	segmentation	NOUN
cana-2667	59	29	,	,	PUNCT
cana-2667	59	30	etc	etc	X
cana-2667	59	31	.	.	X
cana-2667	60	1	most	most	ADJ
cana-2667	60	2	of	of	ADP
cana-2667	60	3	the	the	DET
cana-2667	60	4	latest	late	ADJ
cana-2667	60	5	approaches	approach	NOUN
cana-2667	60	6	that	that	PRON
cana-2667	60	7	classify	classify	VERB
cana-2667	60	8	retinopathy	retinopathy	ADJ
cana-2667	60	9	use	use	NOUN
cana-2667	60	10	cnns	cnn	NOUN
cana-2667	60	11	to	to	PART
cana-2667	60	12	extract	extract	VERB
cana-2667	60	13	features	feature	NOUN
cana-2667	60	14	from	from	ADP
cana-2667	60	15	retinal	retinal	ADJ
cana-2667	60	16	images	image	NOUN
cana-2667	60	17	and	and	CCONJ
cana-2667	60	18	classify	classify	VERB
cana-2667	60	19	them	they	PRON
cana-2667	60	20	into	into	ADP
cana-2667	60	21	categories	category	NOUN
cana-2667	60	22	including	include	VERB
cana-2667	60	23	normal	normal	ADJ
cana-2667	60	24	,	,	PUNCT
cana-2667	60	25	mild	mild	ADJ
cana-2667	60	26	,	,	PUNCT
cana-2667	60	27	moderate	moderate	ADJ
cana-2667	60	28	,	,	PUNCT
cana-2667	60	29	or	or	CCONJ
cana-2667	60	30	severe	severe	ADJ
cana-2667	60	31	.	.	PUNCT
cana-2667	61	1	while	while	SCONJ
cana-2667	61	2	cnn	cnn	PROPN
cana-2667	61	3	-	-	PUNCT
cana-2667	61	4	based	base	VERB
cana-2667	61	5	approaches	approach	NOUN
cana-2667	61	6	have	have	AUX
cana-2667	61	7	been	be	AUX
cana-2667	61	8	successful	successful	ADJ
cana-2667	61	9	,	,	PUNCT
cana-2667	61	10	they	they	PRON
cana-2667	61	11	bring	bring	VERB
cana-2667	61	12	certain	certain	ADJ
cana-2667	61	13	challenges	challenge	NOUN
cana-2667	61	14	to	to	ADP
cana-2667	61	15	the	the	DET
cana-2667	61	16	table	table	NOUN
cana-2667	61	17	.	.	PUNCT
cana-2667	62	1	this	this	PRON
cana-2667	62	2	is	be	AUX
cana-2667	62	3	one	one	NUM
cana-2667	62	4	of	of	ADP
cana-2667	62	5	the	the	DET
cana-2667	62	6	key	key	ADJ
cana-2667	62	7	disadvantages	disadvantage	NOUN
cana-2667	62	8	of	of	ADP
cana-2667	62	9	deep	deep	ADJ
cana-2667	62	10	learning	learning	NOUN
cana-2667	62	11	models	model	NOUN
cana-2667	62	12	;	;	PUNCT
cana-2667	62	13	they	they	PRON
cana-2667	62	14	require	require	VERB
cana-2667	62	15	a	a	DET
cana-2667	62	16	lot	lot	NOUN
cana-2667	62	17	of	of	ADP
cana-2667	62	18	labeled	label	VERB
cana-2667	62	19	data	datum	NOUN
cana-2667	62	20	for	for	ADP
cana-2667	62	21	training	training	NOUN
cana-2667	62	22	.	.	PUNCT
cana-2667	63	1	annotating	annotate	VERB
cana-2667	63	2	medical	medical	ADJ
cana-2667	63	3	images	image	NOUN
cana-2667	63	4	is	be	AUX
cana-2667	63	5	a	a	DET
cana-2667	63	6	laborious	laborious	ADJ
cana-2667	63	7	and	and	CCONJ
cana-2667	63	8	expensive	expensive	ADJ
cana-2667	63	9	process	process	NOUN
cana-2667	63	10	and	and	CCONJ
cana-2667	63	11	hence	hence	ADV
cana-2667	63	12	such	such	ADJ
cana-2667	63	13	large	large	ADJ
cana-2667	63	14	and	and	CCONJ
cana-2667	63	15	high	high	ADJ
cana-2667	63	16	-	-	PUNCT
cana-2667	63	17	quality	quality	NOUN
cana-2667	63	18	datasets	dataset	NOUN
cana-2667	63	19	are	be	AUX
cana-2667	63	20	scarce	scarce	ADJ
cana-2667	63	21	,	,	PUNCT
cana-2667	63	22	especially	especially	ADV
cana-2667	63	23	for	for	ADP
cana-2667	63	24	retinal	retinal	ADJ
cana-2667	63	25	images	image	NOUN
cana-2667	63	26	.	.	PUNCT
cana-2667	64	1	this	this	DET
cana-2667	64	2	challenge	challenge	NOUN
cana-2667	64	3	is	be	AUX
cana-2667	64	4	particularly	particularly	ADV
cana-2667	64	5	pronounced	pronounce	VERB
cana-2667	64	6	in	in	ADP
cana-2667	64	7	medical	medical	ADJ
cana-2667	64	8	imaging	imaging	NOUN
cana-2667	64	9	,	,	PUNCT
cana-2667	64	10	where	where	SCONJ
cana-2667	64	11	specialists	specialist	NOUN
cana-2667	64	12	must	must	AUX
cana-2667	64	13	painstakingly	painstakingly	ADV
cana-2667	64	14	label	label	VERB
cana-2667	64	15	every	every	DET
cana-2667	64	16	single	single	ADJ
cana-2667	64	17	imaging	imaging	NOUN
cana-2667	64	18	,	,	PUNCT
cana-2667	64	19	and	and	CCONJ
cana-2667	64	20	those	those	DET
cana-2667	64	21	datasets	dataset	NOUN
cana-2667	64	22	are	be	AUX
cana-2667	64	23	often	often	ADV
cana-2667	64	24	out	out	ADP
cana-2667	64	25	of	of	ADP
cana-2667	64	26	reach	reach	NOUN
cana-2667	64	27	for	for	ADP
cana-2667	64	28	researchers	researcher	NOUN
cana-2667	64	29	.	.	PUNCT
cana-2667	65	1	in	in	ADP
cana-2667	65	2	addition	addition	NOUN
cana-2667	65	3	,	,	PUNCT
cana-2667	65	4	deep	deep	ADJ
cana-2667	65	5	learning	learning	NOUN
cana-2667	65	6	models	model	NOUN
cana-2667	65	7	are	be	AUX
cana-2667	65	8	easily	easily	ADV
cana-2667	65	9	overfitted	overfitte	VERB
cana-2667	65	10	in	in	ADP
cana-2667	65	11	the	the	DET
cana-2667	65	12	case	case	NOUN
cana-2667	65	13	of	of	ADP
cana-2667	65	14	small	small	ADJ
cana-2667	65	15	training	training	NOUN
cana-2667	65	16	sizes	size	NOUN
cana-2667	65	17	,	,	PUNCT
cana-2667	65	18	then	then	ADV
cana-2667	65	19	it	it	PRON
cana-2667	65	20	is	be	AUX
cana-2667	65	21	also	also	ADV
cana-2667	65	22	important	important	ADJ
cana-2667	65	23	to	to	PART
cana-2667	65	24	carefully	carefully	ADV
cana-2667	65	25	configure	configure	VERB
cana-2667	65	26	the	the	DET
cana-2667	65	27	model	model	NOUN
cana-2667	65	28	architecture	architecture	NOUN
cana-2667	65	29	and	and	CCONJ
cana-2667	65	30	regularization	regularization	NOUN
cana-2667	65	31	strategies[7	strategies[7	NOUN
cana-2667	65	32	]	]	PUNCT
cana-2667	65	33	.	.	PUNCT
cana-2667	66	1	support	support	NOUN
cana-2667	66	2	vector	vector	NOUN
cana-2667	66	3	machines	machine	NOUN
cana-2667	66	4	(	(	PUNCT
cana-2667	66	5	svms	svms	NOUN
cana-2667	66	6	)	)	PUNCT
cana-2667	66	7	are	be	AUX
cana-2667	66	8	another	another	DET
cana-2667	66	9	commonly	commonly	ADV
cana-2667	66	10	used	use	VERB
cana-2667	66	11	method	method	NOUN
cana-2667	66	12	for	for	ADP
cana-2667	66	13	retinopathy	retinopathy	ADJ
cana-2667	66	14	classification	classification	NOUN
cana-2667	66	15	.	.	PUNCT
cana-2667	67	1	support	support	NOUN
cana-2667	67	2	vector	vector	NOUN
cana-2667	67	3	machines	machine	NOUN
cana-2667	67	4	(	(	PUNCT
cana-2667	67	5	svms	svms	NOUN
cana-2667	67	6	)	)	PUNCT
cana-2667	67	7	are	be	AUX
cana-2667	67	8	supervised	supervised	ADJ
cana-2667	67	9	machine	machine	NOUN
cana-2667	67	10	learning	learning	NOUN
cana-2667	67	11	models	model	NOUN
cana-2667	67	12	that	that	PRON
cana-2667	67	13	are	be	AUX
cana-2667	67	14	used	use	VERB
cana-2667	67	15	for	for	ADP
cana-2667	67	16	their	their	PRON
cana-2667	67	17	ability	ability	NOUN
cana-2667	67	18	to	to	PART
cana-2667	67	19	classify	classify	VERB
cana-2667	67	20	data	datum	NOUN
cana-2667	67	21	points	point	NOUN
cana-2667	67	22	into	into	ADP
cana-2667	67	23	separate	separate	ADJ
cana-2667	67	24	categories	category	NOUN
cana-2667	67	25	when	when	SCONJ
cana-2667	67	26	the	the	DET
cana-2667	67	27	data	data	NOUN
cana-2667	67	28	is	be	AUX
cana-2667	67	29	not	not	PART
cana-2667	67	30	linearly	linearly	ADV
cana-2667	67	31	separable	separable	ADJ
cana-2667	67	32	.	.	PUNCT
cana-2667	68	1	this	this	DET
cana-2667	68	2	version	version	NOUN
cana-2667	68	3	of	of	ADP
cana-2667	68	4	svm	svm	PROPN
cana-2667	68	5	is	be	AUX
cana-2667	68	6	used	use	VERB
cana-2667	68	7	for	for	ADP
cana-2667	68	8	linear	linear	ADJ
cana-2667	68	9	classification	classification	NOUN
cana-2667	68	10	.	.	PUNCT
cana-2667	69	1	(	(	PUNCT
cana-2667	69	2	2	2	X
cana-2667	69	3	)	)	PUNCT
cana-2667	69	4	in	in	ADP
cana-2667	69	5	the	the	DET
cana-2667	69	6	scenario	scenario	NOUN
cana-2667	69	7	of	of	ADP
cana-2667	69	8	retinopathy	retinopathy	ADJ
cana-2667	69	9	classification	classification	NOUN
cana-2667	69	10	,	,	PUNCT
cana-2667	69	11	svms	svms	NOUN
cana-2667	69	12	were	be	AUX
cana-2667	69	13	applied	apply	VERB
cana-2667	69	14	to	to	PART
cana-2667	69	15	categorize	categorize	VERB
cana-2667	69	16	retinal	retinal	ADJ
cana-2667	69	17	images	image	NOUN
cana-2667	69	18	according	accord	VERB
cana-2667	69	19	to	to	ADP
cana-2667	69	20	manually	manually	ADV
cana-2667	69	21	made	make	VERB
cana-2667	69	22	features	feature	NOUN
cana-2667	69	23	or	or	CCONJ
cana-2667	69	24	features	feature	NOUN
cana-2667	69	25	obtained	obtain	VERB
cana-2667	69	26	by	by	ADP
cana-2667	69	27	deep	deep	ADJ
cana-2667	69	28	learning	learning	NOUN
cana-2667	69	29	models	model	NOUN
cana-2667	69	30	.	.	PUNCT
cana-2667	70	1	although	although	SCONJ
cana-2667	70	2	svms	svms	NOUN
cana-2667	70	3	have	have	AUX
cana-2667	70	4	performed	perform	VERB
cana-2667	70	5	well	well	ADV
cana-2667	70	6	for	for	ADP
cana-2667	70	7	classification	classification	NOUN
cana-2667	70	8	,	,	PUNCT
cana-2667	70	9	they	they	PRON
cana-2667	70	10	need	need	VERB
cana-2667	70	11	careful	careful	ADJ
cana-2667	70	12	choice	choice	NOUN
cana-2667	70	13	of	of	ADP
cana-2667	70	14	parameters	parameter	NOUN
cana-2667	70	15	to	to	PART
cana-2667	70	16	give	give	VERB
cana-2667	70	17	good	good	ADJ
cana-2667	70	18	performance	performance	NOUN
cana-2667	70	19	,	,	PUNCT
cana-2667	70	20	and	and	CCONJ
cana-2667	70	21	performance	performance	NOUN
cana-2667	70	22	in	in	ADP
cana-2667	70	23	these	these	DET
cana-2667	70	24	cases	case	NOUN
cana-2667	70	25	can	can	AUX
cana-2667	70	26	also	also	ADV
cana-2667	70	27	degrade	degrade	VERB
cana-2667	70	28	with	with	ADP
cana-2667	70	29	complex	complex	ADJ
cana-2667	70	30	high	high	ADJ
cana-2667	70	31	-	-	PUNCT
cana-2667	70	32	dimensional	dimensional	ADJ
cana-2667	70	33	data	datum	NOUN
cana-2667	70	34	like	like	ADP
cana-2667	70	35	retinal	retinal	NOUN
cana-2667	70	36	images[8	images[8	PROPN
cana-2667	70	37	]	]	PUNCT
cana-2667	70	38	.	.	PUNCT
cana-2667	71	1	recent	recent	ADJ
cana-2667	71	2	studies	study	NOUN
cana-2667	71	3	have	have	AUX
cana-2667	71	4	introduced	introduce	VERB
cana-2667	71	5	hybrid	hybrid	NOUN
cana-2667	71	6	models	model	NOUN
cana-2667	71	7	that	that	PRON
cana-2667	71	8	will	will	AUX
cana-2667	71	9	seek	seek	VERB
cana-2667	71	10	to	to	PART
cana-2667	71	11	mitigate	mitigate	VERB
cana-2667	71	12	some	some	PRON
cana-2667	71	13	of	of	ADP
cana-2667	71	14	the	the	DET
cana-2667	71	15	weaknesses	weakness	NOUN
cana-2667	71	16	of	of	ADP
cana-2667	71	17	both	both	CCONJ
cana-2667	71	18	cnns	cnn	NOUN
cana-2667	71	19	and	and	CCONJ
cana-2667	71	20	svms	svms	NOUN
cana-2667	71	21	.	.	PUNCT
cana-2667	72	1	in	in	ADP
cana-2667	72	2	these	these	DET
cana-2667	72	3	methods	method	NOUN
cana-2667	72	4	cnn	cnn	PROPN
cana-2667	72	5	are	be	AUX
cana-2667	72	6	utilized	utilize	VERB
cana-2667	72	7	for	for	ADP
cana-2667	72	8	feature	feature	NOUN
cana-2667	72	9	extraction	extraction	NOUN
cana-2667	72	10	and	and	CCONJ
cana-2667	72	11	the	the	DET
cana-2667	72	12	acquired	acquire	VERB
cana-2667	72	13	features	feature	NOUN
cana-2667	72	14	are	be	AUX
cana-2667	72	15	used	use	VERB
cana-2667	72	16	with	with	ADP
cana-2667	72	17	svm	svm	NOUN
cana-2667	72	18	for	for	ADP
cana-2667	72	19	classification	classification	NOUN
cana-2667	72	20	.	.	PUNCT
cana-2667	73	1	this	this	DET
cana-2667	73	2	approach	approach	NOUN
cana-2667	73	3	enables	enable	VERB
cana-2667	73	4	the	the	DET
cana-2667	73	5	automatic	automatic	ADJ
cana-2667	73	6	feature	feature	NOUN
cana-2667	73	7	extraction	extraction	NOUN
cana-2667	73	8	from	from	ADP
cana-2667	73	9	retinal	retinal	ADJ
cana-2667	73	10	images	image	NOUN
cana-2667	73	11	,	,	PUNCT
cana-2667	73	12	yet	yet	ADV
cana-2667	73	13	retains	retain	VERB
cana-2667	73	14	the	the	DET
cana-2667	73	15	strong	strong	ADJ
cana-2667	73	16	classifying	classify	VERB
cana-2667	73	17	power	power	NOUN
cana-2667	73	18	of	of	ADP
cana-2667	73	19	svms	svms	NOUN
cana-2667	73	20	.	.	PUNCT
cana-2667	74	1	these	these	DET
cana-2667	74	2	hybrid	hybrid	ADJ
cana-2667	74	3	models	model	NOUN
cana-2667	74	4	combine	combine	VERB
cana-2667	74	5	the	the	DET
cana-2667	74	6	ability	ability	NOUN
cana-2667	74	7	of	of	ADP
cana-2667	74	8	cnns	cnn	NOUN
cana-2667	74	9	to	to	PART
cana-2667	74	10	learn	learn	VERB
cana-2667	74	11	the	the	DET
cana-2667	74	12	most	most	ADV
cana-2667	74	13	discriminative	discriminative	NOUN
cana-2667	74	14	features	feature	NOUN
cana-2667	74	15	from	from	ADP
cana-2667	74	16	the	the	DET
cana-2667	74	17	retinal	retinal	ADJ
cana-2667	74	18	images	image	NOUN
cana-2667	74	19	with	with	ADP
cana-2667	74	20	the	the	DET
cana-2667	74	21	svms	svms	NOUN
cana-2667	74	22	'	'	PART
cana-2667	74	23	ability	ability	NOUN
cana-2667	74	24	to	to	PART
cana-2667	74	25	classify	classify	VERB
cana-2667	74	26	the	the	DET
cana-2667	74	27	images	image	NOUN
cana-2667	74	28	while	while	SCONJ
cana-2667	74	29	improving	improve	VERB
cana-2667	74	30	the	the	DET
cana-2667	74	31	classification	classification	NOUN
cana-2667	74	32	accuracy	accuracy	NOUN
cana-2667	74	33	and	and	CCONJ
cana-2667	74	34	minimizing	minimize	VERB
cana-2667	74	35	the	the	DET
cana-2667	74	36	risk	risk	NOUN
cana-2667	74	37	of	of	ADP
cana-2667	74	38	overfitting	overfitte	VERB
cana-2667	74	39	and	and	CCONJ
cana-2667	74	40	increasing	increase	VERB
cana-2667	74	41	the	the	DET
cana-2667	74	42	ability	ability	NOUN
cana-2667	74	43	to	to	PART
cana-2667	74	44	generalize	generalize	VERB
cana-2667	74	45	.	.	PUNCT
cana-2667	75	1	hybrid	hybrid	ADJ
cana-2667	75	2	cnn	cnn	PROPN
cana-2667	75	3	-	-	PUNCT
cana-2667	75	4	svm	svm	PROPN
cana-2667	75	5	models	model	NOUN
cana-2667	75	6	have	have	AUX
cana-2667	75	7	shown	show	VERB
cana-2667	75	8	great	great	ADJ
cana-2667	75	9	potential	potential	NOUN
cana-2667	75	10	in	in	ADP
cana-2667	75	11	retinopathy	retinopathy	ADJ
cana-2667	75	12	classification	classification	NOUN
cana-2667	75	13	[	[	X
cana-2667	75	14	9,10	9,10	NUM
cana-2667	75	15	]	]	PUNCT
cana-2667	75	16	.	.	PUNCT
cana-2667	76	1	these	these	DET
cana-2667	76	2	models	model	NOUN
cana-2667	76	3	are	be	AUX
cana-2667	76	4	a	a	DET
cana-2667	76	5	significant	significant	ADJ
cana-2667	76	6	improvement	improvement	NOUN
cana-2667	76	7	over	over	ADP
cana-2667	76	8	traditional	traditional	ADJ
cana-2667	76	9	svm	svm	NOUN
cana-2667	76	10	based	base	VERB
cana-2667	76	11	approaches	approach	NOUN
cana-2667	76	12	and	and	CCONJ
cana-2667	76	13	cnn	cnn	NOUN
cana-2667	76	14	only	only	ADJ
cana-2667	76	15	models	model	NOUN
cana-2667	76	16	.	.	PUNCT
cana-2667	77	1	despite	despite	SCONJ
cana-2667	77	2	the	the	DET
cana-2667	77	3	promising	promising	ADJ
cana-2667	77	4	findings	finding	NOUN
cana-2667	77	5	,	,	PUNCT
cana-2667	77	6	there	there	PRON
cana-2667	77	7	are	be	VERB
cana-2667	77	8	still	still	ADV
cana-2667	77	9	challenges	challenge	NOUN
cana-2667	77	10	to	to	PART
cana-2667	77	11	overcome	overcome	VERB
cana-2667	77	12	,	,	PUNCT
cana-2667	77	13	for	for	ADP
cana-2667	77	14	example	example	NOUN
cana-2667	77	15	,	,	PUNCT
cana-2667	77	16	parameter	parameter	NOUN
cana-2667	77	17	optimization	optimization	NOUN
cana-2667	77	18	of	of	ADP
cana-2667	77	19	the	the	DET
cana-2667	77	20	cnn	cnn	PROPN
cana-2667	77	21	and	and	CCONJ
cana-2667	77	22	svm	svm	PROPN
cana-2667	77	23	.	.	PROPN
cana-2667	77	24	despite	despite	SCONJ
cana-2667	77	25	tremendous	tremendous	ADJ
cana-2667	77	26	progress	progress	NOUN
cana-2667	77	27	,	,	PUNCT
cana-2667	77	28	large	large	ADJ
cana-2667	77	29	-	-	PUNCT
cana-2667	77	30	scale	scale	NOUN
cana-2667	77	31	studies	study	NOUN
cana-2667	77	32	show	show	VERB
cana-2667	77	33	limited	limited	ADJ
cana-2667	77	34	improvement	improvement	NOUN
cana-2667	77	35	when	when	SCONJ
cana-2667	77	36	moving	move	VERB
cana-2667	77	37	towards	towards	ADP
cana-2667	77	38	optimal	optimal	ADJ
cana-2667	77	39	performance	performance	NOUN
cana-2667	77	40	,	,	PUNCT
cana-2667	77	41	and	and	CCONJ
cana-2667	77	42	models	model	NOUN
cana-2667	77	43	often	often	ADV
cana-2667	77	44	struggle	struggle	VERB
cana-2667	77	45	to	to	PART
cana-2667	77	46	generalize	generalize	VERB
cana-2667	77	47	to	to	ADP
cana-2667	77	48	new	new	ADJ
cana-2667	77	49	,	,	PUNCT
cana-2667	77	50	unseen	unseen	ADJ
cana-2667	77	51	datasets	dataset	NOUN
cana-2667	77	52	.	.	PUNCT
cana-2667	78	1	here	here	ADV
cana-2667	78	2	,	,	PUNCT
cana-2667	78	3	we	we	PRON
cana-2667	78	4	present	present	VERB
cana-2667	78	5	a	a	DET
cana-2667	78	6	new	new	ADJ
cana-2667	78	7	method	method	NOUN
cana-2667	78	8	of	of	ADP
cana-2667	78	9	classification	classification	NOUN
cana-2667	78	10	of	of	ADP
cana-2667	78	11	retinopathy	retinopathy	ADJ
cana-2667	78	12	in	in	ADP
cana-2667	78	13	retinal	retinal	ADJ
cana-2667	78	14	images	image	NOUN
cana-2667	78	15	by	by	ADP
cana-2667	78	16	combining	combine	VERB
cana-2667	78	17	deep	deep	ADJ
cana-2667	78	18	learning	learning	NOUN
cana-2667	78	19	and	and	CCONJ
cana-2667	78	20	support	support	VERB
cana-2667	78	21	vector	vector	NOUN
cana-2667	78	22	machines	machine	NOUN
cana-2667	78	23	.	.	PUNCT
cana-2667	79	1	using	use	VERB
cana-2667	79	2	our	our	PRON
cana-2667	79	3	approach	approach	NOUN
cana-2667	79	4	we	we	PRON
cana-2667	79	5	tried	try	VERB
cana-2667	79	6	to	to	PART
cana-2667	79	7	bridge	bridge	VERB
cana-2667	79	8	the	the	DET
cana-2667	79	9	gap	gap	NOUN
cana-2667	79	10	between	between	ADP
cana-2667	79	11	the	the	DET
cana-2667	79	12	feature	feature	NOUN
cana-2667	79	13	extraction	extraction	NOUN
cana-2667	79	14	capability	capability	NOUN
cana-2667	79	15	of	of	ADP
cana-2667	79	16	cnn	cnn	PROPN
cana-2667	79	17	and	and	CCONJ
cana-2667	79	18	the	the	DET
cana-2667	79	19	effective	effective	ADJ
cana-2667	79	20	classification	classification	NOUN
cana-2667	79	21	performance	performance	NOUN
cana-2667	79	22	of	of	ADP
cana-2667	79	23	svm	svm	PROPN
cana-2667	79	24	.	.	PROPN
cana-2667	80	1	since	since	SCONJ
cana-2667	80	2	small	small	ADJ
cana-2667	80	3	number	number	NOUN
cana-2667	80	4	of	of	ADP
cana-2667	80	5	labeled	label	VERB
cana-2667	80	6	datasets	dataset	NOUN
cana-2667	80	7	are	be	AUX
cana-2667	80	8	problem	problem	NOUN
cana-2667	80	9	which	which	PRON
cana-2667	80	10	we	we	PRON
cana-2667	80	11	overcome	overcome	VERB
cana-2667	80	12	with	with	ADP
cana-2667	80	13	using	use	VERB
cana-2667	80	14	hybrid	hybrid	ADJ
cana-2667	80	15	model	model	NOUN
cana-2667	80	16	(	(	PUNCT
cana-2667	80	17	cnns	cnn	NOUN
cana-2667	80	18	for	for	ADP
cana-2667	80	19	feature	feature	NOUN
cana-2667	80	20	extraction	extraction	NOUN
cana-2667	80	21	svm	svm	NOUN
cana-2667	80	22	)	)	PUNCT
cana-2667	80	23	,	,	PUNCT
cana-2667	80	24	we	we	PRON
cana-2667	80	25	tune	tune	VERB
cana-2667	80	26	the	the	DET
cana-2667	80	27	hyper	hyper	NOUN
cana-2667	80	28	-	-	NOUN
cana-2667	80	29	parameter	parameter	NOUN
cana-2667	80	30	of	of	ADP
cana-2667	80	31	svm	svm	PROPN
cana-2667	80	32	in	in	SCONJ
cana-2667	80	33	order	order	NOUN
cana-2667	80	34	to	to	PART
cana-2667	80	35	identify	identify	VERB
cana-2667	80	36	the	the	DET
cana-2667	80	37	well	well	ADV
cana-2667	80	38	-	-	PUNCT
cana-2667	80	39	calibrated	calibrate	VERB
cana-2667	80	40	model	model	NOUN
cana-2667	80	41	that	that	PRON
cana-2667	80	42	works	work	VERB
cana-2667	80	43	well	well	ADV
cana-2667	80	44	on	on	ADP
cana-2667	80	45	unseen	unseen	ADJ
cana-2667	80	46	data	datum	NOUN
cana-2667	80	47	and	and	CCONJ
cana-2667	80	48	perform	perform	VERB
cana-2667	80	49	computation	computation	NOUN
cana-2667	80	50	of	of	ADP
cana-2667	80	51	hyper	hyper	ADJ
cana-2667	80	52	-	-	NOUN
cana-2667	80	53	parameter	parameter	NOUN
cana-2667	80	54	using	use	VERB
cana-2667	80	55	grid	grid	NOUN
cana-2667	80	56	search	search	NOUN
cana-2667	80	57	communications	communication	NOUN
cana-2667	80	58	on	on	ADP
cana-2667	80	59	applied	apply	VERB
cana-2667	80	60	nonlinear	nonlinear	ADJ
cana-2667	80	61	analysis	analysis	NOUN
cana-2667	80	62	issn	issn	NOUN
cana-2667	80	63	:	:	PUNCT
cana-2667	80	64	1074	1074	NUM
cana-2667	80	65	-	-	PUNCT
cana-2667	80	66	133x	133x	NUM
cana-2667	80	67	vol	vol	NOUN
cana-2667	80	68	32	32	NUM
cana-2667	81	1	no	no	NOUN
cana-2667	81	2	.	.	PUNCT
cana-2667	82	1	3s	3s	NUM
cana-2667	82	2	(	(	PUNCT
cana-2667	82	3	2025	2025	NUM
cana-2667	82	4	)	)	PUNCT
cana-2667	82	5	383	383	NUM
cana-2667	82	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	82	7	and	and	CCONJ
cana-2667	82	8	performance	performance	NOUN
cana-2667	82	9	evaluation	evaluation	NOUN
cana-2667	82	10	.	.	PUNCT
cana-2667	83	1	in	in	ADP
cana-2667	83	2	fact	fact	NOUN
cana-2667	83	3	,	,	PUNCT
cana-2667	83	4	this	this	PRON
cana-2667	83	5	will	will	AUX
cana-2667	83	6	help	help	VERB
cana-2667	83	7	to	to	PART
cana-2667	83	8	improve	improve	VERB
cana-2667	83	9	classification	classification	NOUN
cana-2667	83	10	and	and	CCONJ
cana-2667	83	11	reduce	reduce	VERB
cana-2667	83	12	overfitting	overfitte	VERB
cana-2667	83	13	which	which	PRON
cana-2667	83	14	in	in	ADP
cana-2667	83	15	consequence	consequence	NOUN
cana-2667	83	16	will	will	AUX
cana-2667	83	17	yield	yield	VERB
cana-2667	83	18	a	a	DET
cana-2667	83	19	more	more	ADV
cana-2667	83	20	robust	robust	ADJ
cana-2667	83	21	automated	automate	VERB
cana-2667	83	22	retinopathy	retinopathy	ADJ
cana-2667	83	23	diagnosis	diagnosis	NOUN
cana-2667	83	24	system[11	system[11	PROPN
cana-2667	83	25	]	]	PUNCT
cana-2667	83	26	.	.	PUNCT
cana-2667	84	1	the	the	DET
cana-2667	84	2	proposed	propose	VERB
cana-2667	84	3	method	method	NOUN
cana-2667	84	4	combines	combine	VERB
cana-2667	84	5	a	a	DET
cana-2667	84	6	cnn	cnn	NOUN
cana-2667	84	7	for	for	ADP
cana-2667	84	8	hierarchical	hierarchical	ADJ
cana-2667	84	9	feature	feature	NOUN
cana-2667	84	10	extraction	extraction	NOUN
cana-2667	84	11	from	from	ADP
cana-2667	84	12	retinal	retinal	ADJ
cana-2667	84	13	pictures	picture	NOUN
cana-2667	84	14	,	,	PUNCT
cana-2667	84	15	and	and	CCONJ
cana-2667	84	16	svm	svm	VERB
cana-2667	84	17	for	for	ADP
cana-2667	84	18	classification	classification	NOUN
cana-2667	84	19	of	of	ADP
cana-2667	84	20	the	the	DET
cana-2667	84	21	images	image	NOUN
cana-2667	84	22	into	into	ADP
cana-2667	84	23	different	different	ADJ
cana-2667	84	24	groups	group	NOUN
cana-2667	84	25	.	.	PUNCT
cana-2667	85	1	therefore	therefore	ADV
cana-2667	85	2	,	,	PUNCT
cana-2667	85	3	we	we	PRON
cana-2667	85	4	aim	aim	VERB
cana-2667	85	5	to	to	PART
cana-2667	85	6	perform	perform	VERB
cana-2667	85	7	grid	grid	NOUN
cana-2667	85	8	search	search	NOUN
cana-2667	85	9	to	to	PART
cana-2667	85	10	tune	tune	VERB
cana-2667	85	11	the	the	DET
cana-2667	85	12	svm	svm	PROPN
cana-2667	85	13	's	's	PART
cana-2667	85	14	hyperparameters	hyperparameter	NOUN
cana-2667	85	15	in	in	ADP
cana-2667	85	16	order	order	NOUN
cana-2667	85	17	to	to	PART
cana-2667	85	18	improve	improve	VERB
cana-2667	85	19	its	its	PRON
cana-2667	85	20	classification	classification	NOUN
cana-2667	85	21	capabilities	capability	NOUN
cana-2667	85	22	.	.	PUNCT
cana-2667	86	1	in	in	ADP
cana-2667	86	2	this	this	DET
cana-2667	86	3	way	way	NOUN
cana-2667	86	4	,	,	PUNCT
cana-2667	86	5	we	we	PRON
cana-2667	86	6	expect	expect	VERB
cana-2667	86	7	this	this	DET
cana-2667	86	8	hybrid	hybrid	ADJ
cana-2667	86	9	approach	approach	NOUN
cana-2667	86	10	to	to	PART
cana-2667	86	11	outperform	outperform	VERB
cana-2667	86	12	traditional	traditional	ADJ
cana-2667	86	13	approaches	approach	NOUN
cana-2667	86	14	and	and	CCONJ
cana-2667	86	15	offer	offer	VERB
cana-2667	86	16	an	an	DET
cana-2667	86	17	efficient	efficient	ADJ
cana-2667	86	18	,	,	PUNCT
cana-2667	86	19	automated	automate	VERB
cana-2667	86	20	solution	solution	NOUN
cana-2667	86	21	for	for	ADP
cana-2667	86	22	the	the	DET
cana-2667	86	23	classification	classification	NOUN
cana-2667	86	24	of	of	ADP
cana-2667	86	25	retinopathy	retinopathy	NOUN
cana-2667	86	26	that	that	PRON
cana-2667	86	27	can	can	AUX
cana-2667	86	28	help	help	VERB
cana-2667	86	29	health	health	NOUN
cana-2667	86	30	care	care	NOUN
cana-2667	86	31	professionals	professional	NOUN
cana-2667	86	32	to	to	ADP
cana-2667	86	33	early	early	ADJ
cana-2667	86	34	diagnosis	diagnosis	NOUN
cana-2667	86	35	and	and	CCONJ
cana-2667	86	36	intervention	intervention	NOUN
cana-2667	86	37	.	.	PUNCT
cana-2667	87	1	2	2	X
cana-2667	87	2	.	.	X
cana-2667	87	3	related	relate	VERB
cana-2667	87	4	work	work	NOUN
cana-2667	87	5	advancements	advancement	NOUN
cana-2667	87	6	in	in	ADP
cana-2667	87	7	both	both	DET
cana-2667	87	8	digital	digital	ADJ
cana-2667	87	9	imaging	imaging	NOUN
cana-2667	87	10	and	and	CCONJ
cana-2667	87	11	machine	machine	NOUN
cana-2667	87	12	learning	learning	NOUN
cana-2667	87	13	techniques	technique	NOUN
cana-2667	87	14	have	have	AUX
cana-2667	87	15	led	lead	VERB
cana-2667	87	16	to	to	ADP
cana-2667	87	17	significant	significant	ADJ
cana-2667	87	18	research	research	NOUN
cana-2667	87	19	efforts	effort	NOUN
cana-2667	87	20	over	over	ADP
cana-2667	87	21	the	the	DET
cana-2667	87	22	last	last	ADJ
cana-2667	87	23	several	several	ADJ
cana-2667	87	24	decades	decade	NOUN
cana-2667	87	25	to	to	PART
cana-2667	87	26	develop	develop	VERB
cana-2667	87	27	automated	automate	VERB
cana-2667	87	28	systems	system	NOUN
cana-2667	87	29	for	for	ADP
cana-2667	87	30	the	the	DET
cana-2667	87	31	detection	detection	NOUN
cana-2667	87	32	and	and	CCONJ
cana-2667	87	33	classification	classification	NOUN
cana-2667	87	34	of	of	ADP
cana-2667	87	35	retinopathy	retinopathy	NOUN
cana-2667	87	36	.	.	PUNCT
cana-2667	88	1	the	the	DET
cana-2667	88	2	increasing	increase	VERB
cana-2667	88	3	global	global	ADJ
cana-2667	88	4	prevalence	prevalence	NOUN
cana-2667	88	5	of	of	ADP
cana-2667	88	6	diabetes	diabetes	NOUN
cana-2667	88	7	and	and	CCONJ
cana-2667	88	8	aging	age	VERB
cana-2667	88	9	populations	population	NOUN
cana-2667	88	10	in	in	ADP
cana-2667	88	11	the	the	DET
cana-2667	88	12	global	global	ADJ
cana-2667	88	13	demand	demand	NOUN
cana-2667	88	14	for	for	ADP
cana-2667	88	15	an	an	DET
cana-2667	88	16	automated	automate	VERB
cana-2667	88	17	diagnostic	diagnostic	ADJ
cana-2667	88	18	systems	system	NOUN
cana-2667	88	19	because	because	SCONJ
cana-2667	88	20	these	these	DET
cana-2667	88	21	two	two	NUM
cana-2667	88	22	factors	factor	NOUN
cana-2667	88	23	are	be	AUX
cana-2667	88	24	leading	lead	VERB
cana-2667	88	25	to	to	ADP
cana-2667	88	26	the	the	DET
cana-2667	88	27	rise	rise	NOUN
cana-2667	88	28	of	of	ADP
cana-2667	88	29	retinopathy	retinopathy	NOUN
cana-2667	88	30	.	.	PUNCT
cana-2667	89	1	historically	historically	ADV
cana-2667	89	2	,	,	PUNCT
cana-2667	89	3	the	the	DET
cana-2667	89	4	classification	classification	NOUN
cana-2667	89	5	of	of	ADP
cana-2667	89	6	retinopathy	retinopathy	ADJ
cana-2667	89	7	was	be	AUX
cana-2667	89	8	done	do	VERB
cana-2667	89	9	in	in	ADP
cana-2667	89	10	a	a	DET
cana-2667	89	11	manual	manual	ADJ
cana-2667	89	12	fashion	fashion	NOUN
cana-2667	89	13	by	by	ADP
cana-2667	89	14	trained	train	VERB
cana-2667	89	15	ophthalmologists	ophthalmologist	NOUN
cana-2667	89	16	,	,	PUNCT
cana-2667	89	17	however	however	ADV
cana-2667	89	18	,	,	PUNCT
cana-2667	89	19	with	with	SCONJ
cana-2667	89	20	the	the	DET
cana-2667	89	21	rise	rise	NOUN
cana-2667	89	22	of	of	ADP
cana-2667	89	23	machine	machine	NOUN
cana-2667	89	24	learning	learning	NOUN
cana-2667	89	25	and	and	CCONJ
cana-2667	89	26	other	other	ADJ
cana-2667	89	27	ai	ai	VERB
cana-2667	89	28	approaches	approach	NOUN
cana-2667	89	29	through	through	ADP
cana-2667	89	30	rapidly	rapidly	ADV
cana-2667	89	31	evolving	evolve	VERB
cana-2667	89	32	technology	technology	NOUN
cana-2667	89	33	in	in	ADP
cana-2667	89	34	the	the	DET
cana-2667	89	35	healthcare	healthcare	NOUN
cana-2667	89	36	space	space	NOUN
cana-2667	89	37	has	have	AUX
cana-2667	89	38	led	lead	VERB
cana-2667	89	39	to	to	ADP
cana-2667	89	40	efforts	effort	NOUN
cana-2667	89	41	in	in	ADP
cana-2667	89	42	developing	develop	VERB
cana-2667	89	43	algorithms	algorithm	NOUN
cana-2667	89	44	that	that	PRON
cana-2667	89	45	could	could	AUX
cana-2667	89	46	aid	aid	VERB
cana-2667	89	47	or	or	CCONJ
cana-2667	89	48	potentially	potentially	ADV
cana-2667	89	49	optimally	optimally	ADV
cana-2667	89	50	replace	replace	VERB
cana-2667	89	51	the	the	DET
cana-2667	89	52	need	need	NOUN
cana-2667	89	53	for	for	ADP
cana-2667	89	54	specialized	specialized	ADJ
cana-2667	89	55	interpretation	interpretation	NOUN
cana-2667	89	56	.	.	PUNCT
cana-2667	90	1	in	in	ADP
cana-2667	90	2	this	this	DET
cana-2667	90	3	section	section	NOUN
cana-2667	90	4	,	,	PUNCT
cana-2667	90	5	we	we	PRON
cana-2667	90	6	are	be	AUX
cana-2667	90	7	going	go	VERB
cana-2667	90	8	to	to	PART
cana-2667	90	9	provide	provide	VERB
cana-2667	90	10	some	some	DET
cana-2667	90	11	examples	example	NOUN
cana-2667	90	12	of	of	ADP
cana-2667	90	13	such	such	ADJ
cana-2667	90	14	approaches	approach	NOUN
cana-2667	90	15	in	in	ADP
cana-2667	90	16	retinopathy	retinopathy	ADJ
cana-2667	90	17	classification	classification	NOUN
cana-2667	90	18	and	and	CCONJ
cana-2667	90	19	to	to	PART
cana-2667	90	20	describe	describe	VERB
cana-2667	90	21	the	the	DET
cana-2667	90	22	methodologies	methodology	NOUN
cana-2667	90	23	,	,	PUNCT
cana-2667	90	24	challenges	challenge	NOUN
cana-2667	90	25	and	and	CCONJ
cana-2667	90	26	contributions	contribution	NOUN
cana-2667	90	27	of	of	ADP
cana-2667	90	28	different	different	ADJ
cana-2667	90	29	studies	study	NOUN
cana-2667	90	30	.	.	PUNCT
cana-2667	91	1	early	early	ADJ
cana-2667	91	2	methods	method	NOUN
cana-2667	91	3	:	:	PUNCT
cana-2667	91	4	feature	feature	NOUN
cana-2667	91	5	engineering	engineering	NOUN
cana-2667	91	6	and	and	CCONJ
cana-2667	91	7	traditional	traditional	ADJ
cana-2667	91	8	machine	machine	NOUN
cana-2667	91	9	learning	learning	NOUN
cana-2667	91	10	models	model	VERB
cana-2667	91	11	the	the	DET
cana-2667	91	12	first	first	ADJ
cana-2667	91	13	methods	method	NOUN
cana-2667	91	14	to	to	PART
cana-2667	91	15	classify	classify	VERB
cana-2667	91	16	retinopathy	retinopathy	ADJ
cana-2667	91	17	automatically	automatically	ADV
cana-2667	91	18	relied	rely	VERB
cana-2667	91	19	on	on	ADP
cana-2667	91	20	processing	processing	NOUN
cana-2667	91	21	methods	method	NOUN
cana-2667	91	22	which	which	PRON
cana-2667	91	23	extracted	extract	VERB
cana-2667	91	24	a	a	DET
cana-2667	91	25	set	set	NOUN
cana-2667	91	26	of	of	ADP
cana-2667	91	27	features	feature	NOUN
cana-2667	91	28	from	from	ADP
cana-2667	91	29	the	the	DET
cana-2667	91	30	retinal	retinal	ADJ
cana-2667	91	31	images	image	NOUN
cana-2667	91	32	and	and	CCONJ
cana-2667	91	33	then	then	ADV
cana-2667	91	34	in	in	ADP
cana-2667	91	35	classical	classical	ADJ
cana-2667	91	36	learning	learning	NOUN
cana-2667	91	37	algorithms	algorithm	NOUN
cana-2667	91	38	that	that	PRON
cana-2667	91	39	classifies	classify	VERB
cana-2667	91	40	the	the	DET
cana-2667	91	41	data	datum	NOUN
cana-2667	91	42	.	.	PUNCT
cana-2667	92	1	traditional	traditional	ADJ
cana-2667	92	2	image	image	NOUN
cana-2667	92	3	registration	registration	NOUN
cana-2667	92	4	approaches	approach	NOUN
cana-2667	92	5	relied	rely	VERB
cana-2667	92	6	on	on	ADP
cana-2667	92	7	pixel	pixel	PROPN
cana-2667	92	8	intensity	intensity	NOUN
cana-2667	92	9	,	,	PUNCT
cana-2667	92	10	edges	edge	NOUN
cana-2667	92	11	and	and	CCONJ
cana-2667	92	12	other	other	ADJ
cana-2667	92	13	low	low	ADJ
cana-2667	92	14	level	level	NOUN
cana-2667	92	15	features	feature	NOUN
cana-2667	92	16	which	which	PRON
cana-2667	92	17	could	could	AUX
cana-2667	92	18	be	be	AUX
cana-2667	92	19	easily	easily	ADV
cana-2667	92	20	identified	identify	VERB
cana-2667	92	21	with	with	ADP
cana-2667	92	22	hand	hand	NOUN
cana-2667	92	23	crafted	craft	VERB
cana-2667	92	24	methods	method	NOUN
cana-2667	92	25	using	use	VERB
cana-2667	92	26	image	image	NOUN
cana-2667	92	27	processing	processing	NOUN
cana-2667	92	28	techniques	technique	NOUN
cana-2667	92	29	.	.	PUNCT
cana-2667	93	1	such	such	ADJ
cana-2667	93	2	as	as	ADP
cana-2667	93	3	those	those	PRON
cana-2667	93	4	targeting	target	VERB
cana-2667	93	5	the	the	DET
cana-2667	93	6	detection	detection	NOUN
cana-2667	93	7	of	of	ADP
cana-2667	93	8	microaneurysms	microaneurysm	NOUN
cana-2667	93	9	,	,	PUNCT
cana-2667	93	10	exudates	exudate	NOUN
cana-2667	93	11	and	and	CCONJ
cana-2667	93	12	hemorrhages	hemorrhage	NOUN
cana-2667	93	13	,	,	PUNCT
cana-2667	93	14	which	which	PRON
cana-2667	93	15	are	be	AUX
cana-2667	93	16	principal	principal	ADJ
cana-2667	93	17	signs	sign	NOUN
cana-2667	93	18	of	of	ADP
cana-2667	93	19	diabetic	diabetic	ADJ
cana-2667	93	20	retinopathy	retinopathy	NOUN
cana-2667	93	21	.	.	PUNCT
cana-2667	94	1	the	the	DET
cana-2667	94	2	features	feature	NOUN
cana-2667	94	3	were	be	AUX
cana-2667	94	4	subsequently	subsequently	ADV
cana-2667	94	5	used	use	VERB
cana-2667	94	6	to	to	PART
cana-2667	94	7	train	train	VERB
cana-2667	94	8	machine	machine	NOUN
cana-2667	94	9	-	-	PUNCT
cana-2667	94	10	learning	learn	VERB
cana-2667	94	11	algorithms	algorithm	NOUN
cana-2667	94	12	including	include	VERB
cana-2667	94	13	decision	decision	NOUN
cana-2667	94	14	trees	tree	NOUN
cana-2667	94	15	,	,	PUNCT
cana-2667	94	16	k	k	NOUN
cana-2667	94	17	-	-	PUNCT
cana-2667	94	18	nearest	near	ADJ
cana-2667	94	19	neighbors	neighbor	NOUN
cana-2667	94	20	(	(	PUNCT
cana-2667	94	21	knn	knn	PROPN
cana-2667	94	22	)	)	PUNCT
cana-2667	94	23	and	and	CCONJ
cana-2667	94	24	support	support	VERB
cana-2667	94	25	vector	vector	NOUN
cana-2667	94	26	machines	machine	NOUN
cana-2667	94	27	(	(	PUNCT
cana-2667	94	28	svms	svms	NOUN
cana-2667	94	29	)	)	PUNCT
cana-2667	94	30	for	for	ADP
cana-2667	94	31	classification[12	classification[12	NOUN
cana-2667	94	32	]	]	PUNCT
cana-2667	94	33	.	.	PUNCT
cana-2667	95	1	these	these	DET
cana-2667	95	2	techniques	technique	NOUN
cana-2667	95	3	did	do	AUX
cana-2667	95	4	lead	lead	VERB
cana-2667	95	5	to	to	ADP
cana-2667	95	6	some	some	DET
cana-2667	95	7	early	early	ADJ
cana-2667	95	8	success	success	NOUN
cana-2667	95	9	in	in	ADP
cana-2667	95	10	retinopathy	retinopathy	ADJ
cana-2667	95	11	classification	classification	NOUN
cana-2667	95	12	but	but	CCONJ
cana-2667	95	13	were	be	AUX
cana-2667	95	14	reliant	reliant	ADJ
cana-2667	95	15	on	on	ADP
cana-2667	95	16	manual	manual	ADJ
cana-2667	95	17	feature	feature	NOUN
cana-2667	95	18	extraction	extraction	NOUN
cana-2667	95	19	,	,	PUNCT
cana-2667	95	20	hindering	hinder	VERB
cana-2667	95	21	scalability	scalability	NOUN
cana-2667	95	22	and	and	CCONJ
cana-2667	95	23	performance	performance	NOUN
cana-2667	95	24	.	.	PUNCT
cana-2667	96	1	moreover	moreover	ADV
cana-2667	96	2	,	,	PUNCT
cana-2667	96	3	handcrafted	handcrafted	ADJ
cana-2667	96	4	features	feature	NOUN
cana-2667	96	5	could	could	AUX
cana-2667	96	6	not	not	PART
cana-2667	96	7	always	always	ADV
cana-2667	96	8	depict	depict	VERB
cana-2667	96	9	the	the	DET
cana-2667	96	10	complex	complex	ADJ
cana-2667	96	11	structure	structure	NOUN
cana-2667	96	12	of	of	ADP
cana-2667	96	13	retinal	retinal	ADJ
cana-2667	96	14	images	image	NOUN
cana-2667	96	15	,	,	PUNCT
cana-2667	96	16	and	and	CCONJ
cana-2667	96	17	image	image	NOUN
cana-2667	96	18	variability	variability	NOUN
cana-2667	96	19	,	,	PUNCT
cana-2667	96	20	caused	cause	VERB
cana-2667	96	21	,	,	PUNCT
cana-2667	96	22	for	for	ADP
cana-2667	96	23	example	example	NOUN
cana-2667	96	24	,	,	PUNCT
cana-2667	96	25	by	by	ADP
cana-2667	96	26	different	different	ADJ
cana-2667	96	27	light	light	ADJ
cana-2667	96	28	settings	setting	NOUN
cana-2667	96	29	,	,	PUNCT
cana-2667	96	30	angles	angle	NOUN
cana-2667	96	31	,	,	PUNCT
cana-2667	96	32	or	or	CCONJ
cana-2667	96	33	image	image	NOUN
cana-2667	96	34	quality	quality	NOUN
cana-2667	96	35	,	,	PUNCT
cana-2667	96	36	often	often	ADV
cana-2667	96	37	led	lead	VERB
cana-2667	96	38	to	to	ADP
cana-2667	96	39	classification	classification	NOUN
cana-2667	96	40	errors	error	NOUN
cana-2667	96	41	.	.	PUNCT
cana-2667	97	1	additionally	additionally	ADV
cana-2667	97	2	the	the	DET
cana-2667	97	3	behavior	behavior	NOUN
cana-2667	97	4	of	of	ADP
cana-2667	97	5	these	these	DET
cana-2667	97	6	systems	system	NOUN
cana-2667	97	7	was	be	AUX
cana-2667	97	8	often	often	ADV
cana-2667	97	9	reliant	reliant	ADJ
cana-2667	97	10	on	on	ADP
cana-2667	97	11	noise	noise	NOUN
cana-2667	97	12	and	and	CCONJ
cana-2667	97	13	artifacts	artifact	NOUN
cana-2667	97	14	in	in	ADP
cana-2667	97	15	the	the	DET
cana-2667	97	16	retinal	retinal	ADJ
cana-2667	97	17	images	image	NOUN
cana-2667	97	18	translating	translate	VERB
cana-2667	97	19	to	to	ADP
cana-2667	97	20	skewed	skewed	ADJ
cana-2667	97	21	results	result	NOUN
cana-2667	97	22	.	.	PUNCT
cana-2667	98	1	these	these	DET
cana-2667	98	2	early	early	ADJ
cana-2667	98	3	systems	system	NOUN
cana-2667	98	4	were	be	AUX
cana-2667	98	5	computationally	computationally	ADV
cana-2667	98	6	expensive	expensive	ADJ
cana-2667	98	7	and	and	CCONJ
cana-2667	98	8	the	the	DET
cana-2667	98	9	use	use	NOUN
cana-2667	98	10	of	of	ADP
cana-2667	98	11	feature	feature	NOUN
cana-2667	98	12	engineering	engineering	NOUN
cana-2667	98	13	made	make	VERB
cana-2667	98	14	them	they	PRON
cana-2667	98	15	highly	highly	ADV
cana-2667	98	16	susceptible	susceptible	ADJ
cana-2667	98	17	to	to	ADP
cana-2667	98	18	overfitting	overfitte	VERB
cana-2667	98	19	especially	especially	ADV
cana-2667	98	20	when	when	SCONJ
cana-2667	98	21	datasets	dataset	NOUN
cana-2667	98	22	were	be	AUX
cana-2667	98	23	small	small	ADJ
cana-2667	98	24	or	or	CCONJ
cana-2667	98	25	lacked	lack	VERB
cana-2667	98	26	diversity	diversity	NOUN
cana-2667	98	27	.	.	PUNCT
cana-2667	99	1	convolutional	convolutional	ADJ
cana-2667	99	2	neural	neural	ADJ
cana-2667	99	3	networks	network	NOUN
cana-2667	99	4	(	(	PUNCT
cana-2667	99	5	cnns	cnns	PROPN
cana-2667	99	6	)	)	PUNCT
cana-2667	99	7	and	and	CCONJ
cana-2667	99	8	deep	deep	ADJ
cana-2667	99	9	learning	learning	NOUN
cana-2667	99	10	-	-	PUNCT
cana-2667	99	11	based	base	VERB
cana-2667	99	12	approaches	approach	NOUN
cana-2667	99	13	the	the	DET
cana-2667	99	14	first	first	ADJ
cana-2667	99	15	,	,	PUNCT
cana-2667	99	16	and	and	CCONJ
cana-2667	99	17	potentially	potentially	ADV
cana-2667	99	18	most	most	ADV
cana-2667	99	19	disruptive	disruptive	ADJ
cana-2667	99	20	step	step	NOUN
cana-2667	99	21	in	in	ADP
cana-2667	99	22	the	the	DET
cana-2667	99	23	evolution	evolution	NOUN
cana-2667	99	24	of	of	ADP
cana-2667	99	25	medical	medical	ADJ
cana-2667	99	26	image	image	NOUN
cana-2667	99	27	analysis	analysis	NOUN
cana-2667	99	28	is	be	AUX
cana-2667	99	29	the	the	DET
cana-2667	99	30	development	development	NOUN
cana-2667	99	31	of	of	ADP
cana-2667	99	32	deep	deep	ADJ
cana-2667	99	33	learning	learning	NOUN
cana-2667	99	34	,	,	PUNCT
cana-2667	99	35	and	and	CCONJ
cana-2667	99	36	specifically	specifically	ADV
cana-2667	99	37	convolutional	convolutional	ADJ
cana-2667	99	38	neural	neural	ADJ
cana-2667	99	39	networks	network	NOUN
cana-2667	99	40	(	(	PUNCT
cana-2667	99	41	cnns	cnns	PROPN
cana-2667	99	42	)	)	PUNCT
cana-2667	99	43	.	.	PUNCT
cana-2667	100	1	this	this	DET
cana-2667	100	2	feature	feature	NOUN
cana-2667	100	3	of	of	ADP
cana-2667	100	4	communications	communication	NOUN
cana-2667	100	5	on	on	ADP
cana-2667	100	6	applied	apply	VERB
cana-2667	100	7	nonlinear	nonlinear	ADJ
cana-2667	100	8	analysis	analysis	NOUN
cana-2667	100	9	issn	issn	NOUN
cana-2667	100	10	:	:	PUNCT
cana-2667	100	11	1074	1074	NUM
cana-2667	100	12	-	-	PUNCT
cana-2667	100	13	133x	133x	NUM
cana-2667	100	14	vol	vol	NOUN
cana-2667	100	15	32	32	NUM
cana-2667	100	16	no	no	NOUN
cana-2667	100	17	.	.	PUNCT
cana-2667	101	1	3s	3s	NUM
cana-2667	101	2	(	(	PUNCT
cana-2667	101	3	2025	2025	NUM
cana-2667	101	4	)	)	PUNCT
cana-2667	101	5	384	384	NUM
cana-2667	101	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	101	7	cnn	cnn	PROPN
cana-2667	101	8	makes	make	VERB
cana-2667	101	9	it	it	PRON
cana-2667	101	10	a	a	DET
cana-2667	101	11	better	well	ADV
cana-2667	101	12	suited	suit	VERB
cana-2667	101	13	for	for	ADP
cana-2667	101	14	image	image	NOUN
cana-2667	101	15	based	base	VERB
cana-2667	101	16	tasks	task	NOUN
cana-2667	101	17	because	because	SCONJ
cana-2667	101	18	it	it	PRON
cana-2667	101	19	can	can	AUX
cana-2667	101	20	learn	learn	VERB
cana-2667	101	21	the	the	DET
cana-2667	101	22	features	feature	NOUN
cana-2667	101	23	from	from	ADP
cana-2667	101	24	the	the	DET
cana-2667	101	25	pixel	pixel	PROPN
cana-2667	101	26	data	datum	NOUN
cana-2667	101	27	itself	itself	PRON
cana-2667	101	28	and	and	CCONJ
cana-2667	101	29	can	can	AUX
cana-2667	101	30	learn	learn	VERB
cana-2667	101	31	the	the	DET
cana-2667	101	32	spatial	spatial	ADJ
cana-2667	101	33	hierarchies	hierarchy	NOUN
cana-2667	101	34	in	in	ADP
cana-2667	101	35	the	the	DET
cana-2667	101	36	images	image	NOUN
cana-2667	101	37	.	.	PUNCT
cana-2667	102	1	for	for	ADP
cana-2667	102	2	instance	instance	NOUN
cana-2667	102	3	,	,	PUNCT
cana-2667	102	4	in	in	ADP
cana-2667	102	5	the	the	DET
cana-2667	102	6	case	case	NOUN
cana-2667	102	7	of	of	ADP
cana-2667	102	8	retinopathy	retinopathy	ADJ
cana-2667	102	9	classification	classification	NOUN
cana-2667	102	10	,	,	PUNCT
cana-2667	102	11	cnns	cnn	NOUN
cana-2667	102	12	are	be	AUX
cana-2667	102	13	capable	capable	ADJ
cana-2667	102	14	of	of	ADP
cana-2667	102	15	identifying	identify	VERB
cana-2667	102	16	intricate	intricate	ADJ
cana-2667	102	17	patterns	pattern	NOUN
cana-2667	102	18	in	in	ADP
cana-2667	102	19	the	the	DET
cana-2667	102	20	retinal	retinal	ADJ
cana-2667	102	21	images	image	NOUN
cana-2667	102	22	,	,	PUNCT
cana-2667	102	23	like	like	ADP
cana-2667	102	24	microaneurysms	microaneurysm	NOUN
cana-2667	102	25	,	,	PUNCT
cana-2667	102	26	blood	blood	NOUN
cana-2667	102	27	vessels	vessel	NOUN
cana-2667	102	28	,	,	PUNCT
cana-2667	102	29	and	and	CCONJ
cana-2667	102	30	retinal	retinal	ADJ
cana-2667	102	31	structures	structure	NOUN
cana-2667	102	32	,	,	PUNCT
cana-2667	102	33	that	that	PRON
cana-2667	102	34	are	be	AUX
cana-2667	102	35	characteristic	characteristic	ADJ
cana-2667	102	36	of	of	ADP
cana-2667	102	37	the	the	DET
cana-2667	102	38	different	different	ADJ
cana-2667	102	39	stages	stage	NOUN
cana-2667	102	40	of	of	ADP
cana-2667	102	41	the	the	DET
cana-2667	102	42	disease	disease	NOUN
cana-2667	102	43	.	.	PUNCT
cana-2667	103	1	compared	compare	VERB
cana-2667	103	2	with	with	ADP
cana-2667	103	3	manually	manually	ADV
cana-2667	103	4	extracting	extract	VERB
cana-2667	103	5	features	feature	NOUN
cana-2667	103	6	,	,	PUNCT
cana-2667	103	7	the	the	DET
cana-2667	103	8	use	use	NOUN
cana-2667	103	9	of	of	ADP
cana-2667	103	10	cnns	cnn	NOUN
cana-2667	103	11	has	have	AUX
cana-2667	103	12	significantly	significantly	ADV
cana-2667	103	13	improved	improve	VERB
cana-2667	103	14	the	the	DET
cana-2667	103	15	accuracy	accuracy	NOUN
cana-2667	103	16	and	and	CCONJ
cana-2667	103	17	speed	speed	NOUN
cana-2667	103	18	of	of	ADP
cana-2667	103	19	classification	classification	NOUN
cana-2667	103	20	systems	system	NOUN
cana-2667	103	21	:	:	PUNCT
cana-2667	103	22	cnns	cnn	NOUN
cana-2667	103	23	automatically	automatically	ADV
cana-2667	103	24	learn	learn	VERB
cana-2667	103	25	the	the	DET
cana-2667	103	26	greatest	great	ADJ
cana-2667	103	27	features	feature	NOUN
cana-2667	103	28	from	from	ADP
cana-2667	103	29	large	large	ADJ
cana-2667	103	30	datasets	dataset	NOUN
cana-2667	103	31	and	and	CCONJ
cana-2667	103	32	they	they	PRON
cana-2667	103	33	do	do	AUX
cana-2667	103	34	not	not	PART
cana-2667	103	35	need	need	VERB
cana-2667	103	36	feature	feature	NOUN
cana-2667	103	37	extraction	extraction	NOUN
cana-2667	103	38	—	—	PUNCT
cana-2667	103	39	and	and	CCONJ
cana-2667	103	40	this	this	PRON
cana-2667	103	41	is	be	AUX
cana-2667	103	42	why	why	SCONJ
cana-2667	103	43	cnns	cnn	NOUN
cana-2667	103	44	are	be	AUX
cana-2667	103	45	commonly	commonly	ADV
cana-2667	103	46	utilized	utilize	VERB
cana-2667	103	47	in	in	ADP
cana-2667	103	48	retinopathy	retinopathy	ADJ
cana-2667	103	49	detection	detection	NOUN
cana-2667	103	50	.	.	PUNCT
cana-2667	104	1	cnn	cnn	PROPN
cana-2667	104	2	based	base	VERB
cana-2667	104	3	architecture	architecture	NOUN
cana-2667	104	4	have	have	AUX
cana-2667	104	5	shown	show	VERB
cana-2667	104	6	remarkable	remarkable	ADJ
cana-2667	104	7	improvement	improvement	NOUN
cana-2667	104	8	in	in	ADP
cana-2667	104	9	accuracy	accuracy	NOUN
cana-2667	104	10	along	along	ADP
cana-2667	104	11	with	with	ADP
cana-2667	104	12	robustness	robustness	NOUN
cana-2667	104	13	compared	compare	VERB
cana-2667	104	14	to	to	ADP
cana-2667	104	15	legacy	legacy	NOUN
cana-2667	104	16	techniques	technique	NOUN
cana-2667	104	17	.	.	PUNCT
cana-2667	105	1	specifically	specifically	ADV
cana-2667	105	2	,	,	PUNCT
cana-2667	105	3	cnn	cnn	PROPN
cana-2667	105	4	architectures	architecture	NOUN
cana-2667	105	5	have	have	AUX
cana-2667	105	6	achieved	achieve	VERB
cana-2667	105	7	notable	notable	ADJ
cana-2667	105	8	success	success	NOUN
cana-2667	105	9	in	in	ADP
cana-2667	105	10	identifying	identify	VERB
cana-2667	105	11	clear	clear	ADJ
cana-2667	105	12	and	and	CCONJ
cana-2667	105	13	extensive	extensive	ADJ
cana-2667	105	14	presence	presence	NOUN
cana-2667	105	15	of	of	ADP
cana-2667	105	16	retinopathy	retinopathy	ADJ
cana-2667	105	17	,	,	PUNCT
cana-2667	105	18	such	such	ADJ
cana-2667	105	19	as	as	ADP
cana-2667	105	20	exudates	exudate	NOUN
cana-2667	105	21	,	,	PUNCT
cana-2667	105	22	hemorrhaging	hemorrhaging	NOUN
cana-2667	105	23	and	and	CCONJ
cana-2667	105	24	retinal	retinal	ADJ
cana-2667	105	25	neovascularization	neovascularization	NOUN
cana-2667	105	26	.	.	PUNCT
cana-2667	106	1	the	the	DET
cana-2667	106	2	automatic	automatic	ADJ
cana-2667	106	3	learning	learning	NOUN
cana-2667	106	4	and	and	CCONJ
cana-2667	106	5	representation	representation	NOUN
cana-2667	106	6	of	of	ADP
cana-2667	106	7	the	the	DET
cana-2667	106	8	features	feature	NOUN
cana-2667	106	9	used	use	VERB
cana-2667	106	10	by	by	ADP
cana-2667	106	11	cnns	cnn	NOUN
cana-2667	106	12	have	have	AUX
cana-2667	106	13	resulted	result	VERB
cana-2667	106	14	in	in	ADP
cana-2667	106	15	more	more	ADV
cana-2667	106	16	accurate	accurate	ADJ
cana-2667	106	17	retinopathy	retinopathy	ADJ
cana-2667	106	18	models	model	NOUN
cana-2667	106	19	able	able	ADJ
cana-2667	106	20	to	to	PART
cana-2667	106	21	classify	classify	VERB
cana-2667	106	22	the	the	DET
cana-2667	106	23	disease	disease	NOUN
cana-2667	106	24	much	much	ADV
cana-2667	106	25	earlier	early	ADV
cana-2667	106	26	,	,	PUNCT
cana-2667	106	27	paving	pave	VERB
cana-2667	106	28	the	the	DET
cana-2667	106	29	way	way	NOUN
cana-2667	106	30	for	for	ADP
cana-2667	106	31	earlier	early	ADJ
cana-2667	106	32	treatment	treatment	NOUN
cana-2667	106	33	in	in	ADP
cana-2667	106	34	cases	case	NOUN
cana-2667	106	35	of	of	ADP
cana-2667	106	36	rtdr[13	rtdr[13	NOUN
cana-2667	106	37	]	]	PUNCT
cana-2667	106	38	.	.	PUNCT
cana-2667	107	1	yet	yet	ADV
cana-2667	107	2	,	,	PUNCT
cana-2667	107	3	despite	despite	SCONJ
cana-2667	107	4	their	their	PRON
cana-2667	107	5	success	success	NOUN
cana-2667	107	6	in	in	ADP
cana-2667	107	7	retinopathy	retinopathy	ADJ
cana-2667	107	8	classification	classification	NOUN
cana-2667	107	9	,	,	PUNCT
cana-2667	107	10	cnns	cnn	NOUN
cana-2667	107	11	still	still	ADV
cana-2667	107	12	face	face	VERB
cana-2667	107	13	some	some	DET
cana-2667	107	14	challenges	challenge	NOUN
cana-2667	107	15	to	to	PART
cana-2667	107	16	be	be	AUX
cana-2667	107	17	overcome	overcome	VERB
cana-2667	107	18	.	.	PUNCT
cana-2667	108	1	lack	lack	NOUN
cana-2667	108	2	of	of	ADP
cana-2667	108	3	large	large	ADJ
cana-2667	108	4	labeled	label	VERB
cana-2667	108	5	datasets	dataset	NOUN
cana-2667	108	6	to	to	PART
cana-2667	108	7	train	train	NOUN
cana-2667	108	8	models	model	NOUN
cana-2667	108	9	is	be	AUX
cana-2667	108	10	one	one	NUM
cana-2667	108	11	of	of	ADP
cana-2667	108	12	the	the	DET
cana-2667	108	13	major	major	ADJ
cana-2667	108	14	issues	issue	NOUN
cana-2667	108	15	medical	medical	ADJ
cana-2667	108	16	images	image	NOUN
cana-2667	108	17	require	require	VERB
cana-2667	108	18	a	a	DET
cana-2667	108	19	large	large	ADJ
cana-2667	108	20	amount	amount	NOUN
cana-2667	108	21	of	of	ADP
cana-2667	108	22	annotated	annotate	VERB
cana-2667	108	23	data	datum	NOUN
cana-2667	108	24	in	in	ADP
cana-2667	108	25	order	order	NOUN
cana-2667	108	26	to	to	PART
cana-2667	108	27	learn	learn	VERB
cana-2667	108	28	robust	robust	ADJ
cana-2667	108	29	features	feature	NOUN
cana-2667	108	30	and	and	CCONJ
cana-2667	108	31	the	the	DET
cana-2667	108	32	annotation	annotation	NOUN
cana-2667	108	33	process	process	NOUN
cana-2667	108	34	in	in	ADP
cana-2667	108	35	the	the	DET
cana-2667	108	36	medical	medical	ADJ
cana-2667	108	37	domain	domain	NOUN
cana-2667	108	38	is	be	AUX
cana-2667	108	39	expensive	expensive	ADJ
cana-2667	108	40	and	and	CCONJ
cana-2667	108	41	time	time	NOUN
cana-2667	108	42	-	-	PUNCT
cana-2667	108	43	consuming	consume	VERB
cana-2667	108	44	.	.	PUNCT
cana-2667	109	1	the	the	DET
cana-2667	109	2	retinal	retinal	ADJ
cana-2667	109	3	images	image	NOUN
cana-2667	109	4	in	in	ADP
cana-2667	109	5	different	different	ADJ
cana-2667	109	6	datasets	dataset	NOUN
cana-2667	109	7	can	can	AUX
cana-2667	109	8	have	have	VERB
cana-2667	109	9	significant	significant	ADJ
cana-2667	109	10	variations	variation	NOUN
cana-2667	109	11	due	due	ADP
cana-2667	109	12	to	to	ADP
cana-2667	109	13	differences	difference	NOUN
cana-2667	109	14	in	in	ADP
cana-2667	109	15	imaging	imaging	NOUN
cana-2667	109	16	equipment	equipment	NOUN
cana-2667	109	17	,	,	PUNCT
cana-2667	109	18	patient	patient	ADJ
cana-2667	109	19	characteristics	characteristic	NOUN
cana-2667	109	20	,	,	PUNCT
cana-2667	109	21	and	and	CCONJ
cana-2667	109	22	other	other	ADJ
cana-2667	109	23	factors	factor	NOUN
cana-2667	109	24	,	,	PUNCT
cana-2667	109	25	which	which	PRON
cana-2667	109	26	leads	lead	VERB
cana-2667	109	27	to	to	ADP
cana-2667	109	28	poor	poor	ADJ
cana-2667	109	29	generalization	generalization	NOUN
cana-2667	109	30	in	in	ADP
cana-2667	109	31	applying	apply	VERB
cana-2667	109	32	models	model	NOUN
cana-2667	109	33	to	to	ADP
cana-2667	109	34	new	new	ADJ
cana-2667	109	35	datasets	dataset	NOUN
cana-2667	109	36	.	.	PUNCT
cana-2667	110	1	therefore	therefore	ADV
cana-2667	110	2	,	,	PUNCT
cana-2667	110	3	there	there	PRON
cana-2667	110	4	are	be	VERB
cana-2667	110	5	still	still	ADV
cana-2667	110	6	areas	area	NOUN
cana-2667	110	7	for	for	ADP
cana-2667	110	8	techniques	technique	NOUN
cana-2667	110	9	that	that	PRON
cana-2667	110	10	can	can	AUX
cana-2667	110	11	enhance	enhance	VERB
cana-2667	110	12	the	the	DET
cana-2667	110	13	generalization	generalization	NOUN
cana-2667	110	14	capacity	capacity	NOUN
cana-2667	110	15	of	of	ADP
cana-2667	110	16	deep	deep	ADJ
cana-2667	110	17	learning	learning	NOUN
cana-2667	110	18	models	model	NOUN
cana-2667	110	19	and	and	CCONJ
cana-2667	110	20	lessen	lessen	VERB
cana-2667	110	21	the	the	DET
cana-2667	110	22	need	need	NOUN
cana-2667	110	23	for	for	ADP
cana-2667	110	24	large	large	ADJ
cana-2667	110	25	annotated	annotated	ADJ
cana-2667	110	26	datasets	dataset	NOUN
cana-2667	110	27	.	.	PUNCT
cana-2667	111	1	hybrid	hybrid	ADJ
cana-2667	111	2	solutions	solution	NOUN
cana-2667	111	3	:	:	PUNCT
cana-2667	111	4	the	the	DET
cana-2667	111	5	convergence	convergence	NOUN
cana-2667	111	6	analogy	analogy	NOUN
cana-2667	111	7	between	between	ADP
cana-2667	111	8	cnns	cnn	NOUN
cana-2667	111	9	and	and	CCONJ
cana-2667	111	10	classical	classical	ADJ
cana-2667	111	11	models	model	NOUN
cana-2667	111	12	the	the	DET
cana-2667	111	13	success	success	NOUN
cana-2667	111	14	of	of	ADP
cana-2667	111	15	cnns	cnn	NOUN
cana-2667	111	16	in	in	ADP
cana-2667	111	17	identifying	identify	VERB
cana-2667	111	18	relevant	relevant	ADJ
cana-2667	111	19	features	feature	NOUN
cana-2667	111	20	from	from	ADP
cana-2667	111	21	retinal	retinal	ADJ
cana-2667	111	22	images	image	NOUN
cana-2667	111	23	led	lead	VERB
cana-2667	111	24	many	many	ADJ
cana-2667	111	25	recent	recent	ADJ
cana-2667	111	26	works	work	NOUN
cana-2667	111	27	to	to	PART
cana-2667	111	28	explore	explore	VERB
cana-2667	111	29	hybrid	hybrid	ADJ
cana-2667	111	30	models	model	NOUN
cana-2667	111	31	that	that	PRON
cana-2667	111	32	combine	combine	VERB
cana-2667	111	33	the	the	DET
cana-2667	111	34	feature	feature	NOUN
cana-2667	111	35	extraction	extraction	NOUN
cana-2667	111	36	capacity	capacity	NOUN
cana-2667	111	37	of	of	ADP
cana-2667	111	38	cnns	cnn	NOUN
cana-2667	111	39	with	with	ADP
cana-2667	111	40	the	the	DET
cana-2667	111	41	classification	classification	NOUN
cana-2667	111	42	power	power	NOUN
cana-2667	111	43	of	of	ADP
cana-2667	111	44	classical	classical	ADJ
cana-2667	111	45	machine	machine	NOUN
cana-2667	111	46	learning	learning	NOUN
cana-2667	111	47	algorithms	algorithm	NOUN
cana-2667	111	48	,	,	PUNCT
cana-2667	111	49	like	like	ADP
cana-2667	111	50	support	support	NOUN
cana-2667	111	51	vector	vector	NOUN
cana-2667	111	52	machines	machine	NOUN
cana-2667	111	53	(	(	PUNCT
cana-2667	111	54	svm	svm	PROPN
cana-2667	111	55	)	)	PUNCT
cana-2667	111	56	.	.	PUNCT
cana-2667	112	1	these	these	DET
cana-2667	112	2	hybrid	hybrid	ADJ
cana-2667	112	3	approaches	approach	NOUN
cana-2667	112	4	combine	combine	VERB
cana-2667	112	5	the	the	DET
cana-2667	112	6	advantages	advantage	NOUN
cana-2667	112	7	of	of	ADP
cana-2667	112	8	both	both	CCONJ
cana-2667	112	9	cnns	cnns	ADJ
cana-2667	112	10	and	and	CCONJ
cana-2667	112	11	classical	classical	ADJ
cana-2667	112	12	models	model	NOUN
cana-2667	112	13	to	to	PART
cana-2667	112	14	enhance	enhance	VERB
cana-2667	112	15	the	the	DET
cana-2667	112	16	performance	performance	NOUN
cana-2667	112	17	of	of	ADP
cana-2667	112	18	retinopathy	retinopathy	ADJ
cana-2667	112	19	classification	classification	NOUN
cana-2667	112	20	.	.	PUNCT
cana-2667	113	1	in	in	ADP
cana-2667	113	2	these	these	DET
cana-2667	113	3	hybrid	hybrid	NOUN
cana-2667	113	4	models	model	NOUN
cana-2667	113	5	,	,	PUNCT
cana-2667	113	6	some	some	DET
cana-2667	113	7	features	feature	NOUN
cana-2667	113	8	are	be	AUX
cana-2667	113	9	extracted	extract	VERB
cana-2667	113	10	using	use	VERB
cana-2667	113	11	cnns	cnn	NOUN
cana-2667	113	12	:	:	PUNCT
cana-2667	113	13	first	first	ADV
cana-2667	113	14	,	,	PUNCT
cana-2667	113	15	these	these	PRON
cana-2667	113	16	are	be	AUX
cana-2667	113	17	trained	train	VERB
cana-2667	113	18	with	with	ADP
cana-2667	113	19	retinal	retinal	ADJ
cana-2667	113	20	images	image	NOUN
cana-2667	113	21	.	.	PUNCT
cana-2667	114	1	after	after	SCONJ
cana-2667	114	2	these	these	DET
cana-2667	114	3	features	feature	NOUN
cana-2667	114	4	are	be	AUX
cana-2667	114	5	learned	learn	VERB
cana-2667	114	6	,	,	PUNCT
cana-2667	114	7	they	they	PRON
cana-2667	114	8	are	be	AUX
cana-2667	114	9	fed	feed	VERB
cana-2667	114	10	into	into	ADP
cana-2667	114	11	an	an	DET
cana-2667	114	12	svm	svm	NOUN
cana-2667	114	13	or	or	CCONJ
cana-2667	114	14	other	other	ADJ
cana-2667	114	15	classical	classical	ADJ
cana-2667	114	16	machine	machine	NOUN
cana-2667	114	17	learning	learn	VERB
cana-2667	114	18	algorithm	algorithm	NOUN
cana-2667	114	19	for	for	ADP
cana-2667	114	20	classification	classification	NOUN
cana-2667	114	21	.	.	PUNCT
cana-2667	115	1	svms	svms	NOUN
cana-2667	115	2	are	be	AUX
cana-2667	115	3	chosen	choose	VERB
cana-2667	115	4	for	for	ADP
cana-2667	115	5	the	the	DET
cana-2667	115	6	model	model	NOUN
cana-2667	115	7	,	,	PUNCT
cana-2667	115	8	as	as	SCONJ
cana-2667	115	9	they	they	PRON
cana-2667	115	10	allow	allow	VERB
cana-2667	115	11	the	the	DET
cana-2667	115	12	effective	effective	ADJ
cana-2667	115	13	handling	handling	NOUN
cana-2667	115	14	of	of	ADP
cana-2667	115	15	very	very	ADV
cana-2667	115	16	high	high	ADJ
cana-2667	115	17	-	-	PUNCT
cana-2667	115	18	dimensional	dimensional	ADJ
cana-2667	115	19	feature	feature	NOUN
cana-2667	115	20	spaces	space	NOUN
cana-2667	115	21	and	and	CCONJ
cana-2667	115	22	generally	generally	ADV
cana-2667	115	23	prevent	prevent	VERB
cana-2667	115	24	overfitting	overfitting	NOUN
cana-2667	115	25	,	,	PUNCT
cana-2667	115	26	particularly	particularly	ADV
cana-2667	115	27	in	in	ADP
cana-2667	115	28	cases	case	NOUN
cana-2667	115	29	where	where	SCONJ
cana-2667	115	30	the	the	DET
cana-2667	115	31	samples	sample	NOUN
cana-2667	115	32	for	for	ADP
cana-2667	115	33	training	training	NOUN
cana-2667	115	34	are	be	AUX
cana-2667	115	35	scarce	scarce	ADJ
cana-2667	115	36	.	.	PUNCT
cana-2667	116	1	when	when	SCONJ
cana-2667	116	2	cnns	cnns	PROPN
cana-2667	116	3	are	be	AUX
cana-2667	116	4	combined	combine	VERB
cana-2667	116	5	with	with	ADP
cana-2667	116	6	the	the	DET
cana-2667	116	7	discriminative	discriminative	NOUN
cana-2667	116	8	power	power	NOUN
cana-2667	116	9	of	of	ADP
cana-2667	116	10	svm	svm	VERB
cana-2667	116	11	the	the	DET
cana-2667	116	12	hybrid	hybrid	NOUN
cana-2667	116	13	models	model	NOUN
cana-2667	116	14	have	have	AUX
cana-2667	116	15	been	be	AUX
cana-2667	116	16	shown	show	VERB
cana-2667	116	17	to	to	PART
cana-2667	116	18	have	have	VERB
cana-2667	116	19	state	state	NOUN
cana-2667	116	20	-	-	PUNCT
cana-2667	116	21	of	of	ADP
cana-2667	116	22	-	-	PUNCT
cana-2667	116	23	the	the	DET
cana-2667	116	24	-	-	PUNCT
cana-2667	116	25	art	art	NOUN
cana-2667	116	26	performances	performance	NOUN
cana-2667	116	27	on	on	ADP
cana-2667	116	28	retinopathy	retinopathy	ADJ
cana-2667	116	29	classification	classification	NOUN
cana-2667	116	30	tasks[14	tasks[14	PROPN
cana-2667	116	31	]	]	X
cana-2667	116	32	.	.	PUNCT
cana-2667	117	1	the	the	DET
cana-2667	117	2	benefit	benefit	NOUN
cana-2667	117	3	of	of	ADP
cana-2667	117	4	hybrid	hybrid	NOUN
cana-2667	117	5	models	model	NOUN
cana-2667	117	6	is	be	AUX
cana-2667	117	7	that	that	SCONJ
cana-2667	117	8	cnns	cnn	NOUN
cana-2667	117	9	are	be	AUX
cana-2667	117	10	particularly	particularly	ADV
cana-2667	117	11	good	good	ADJ
cana-2667	117	12	at	at	ADP
cana-2667	117	13	automatically	automatically	ADV
cana-2667	117	14	extracting	extract	VERB
cana-2667	117	15	hierarchical	hierarchical	ADJ
cana-2667	117	16	features	feature	NOUN
cana-2667	117	17	from	from	ADP
cana-2667	117	18	images	image	NOUN
cana-2667	117	19	,	,	PUNCT
cana-2667	117	20	while	while	SCONJ
cana-2667	117	21	svms	svms	NOUN
cana-2667	117	22	are	be	AUX
cana-2667	117	23	quite	quite	ADV
cana-2667	117	24	good	good	ADJ
cana-2667	117	25	at	at	ADP
cana-2667	117	26	classifying	classify	VERB
cana-2667	117	27	image	image	NOUN
cana-2667	117	28	features	feature	NOUN
cana-2667	117	29	into	into	ADP
cana-2667	117	30	different	different	ADJ
cana-2667	117	31	classes	class	NOUN
cana-2667	117	32	.	.	PUNCT
cana-2667	118	1	but	but	CCONJ
cana-2667	118	2	this	this	PRON
cana-2667	118	3	comes	come	VERB
cana-2667	118	4	with	with	ADP
cana-2667	118	5	its	its	PRON
cana-2667	118	6	own	own	ADJ
cana-2667	118	7	challenges	challenge	NOUN
cana-2667	118	8	,	,	PUNCT
cana-2667	118	9	too	too	ADV
cana-2667	118	10	.	.	PUNCT
cana-2667	119	1	the	the	DET
cana-2667	119	2	optimization	optimization	NOUN
cana-2667	119	3	of	of	ADP
cana-2667	119	4	both	both	DET
cana-2667	119	5	cnn	cnn	PROPN
cana-2667	119	6	and	and	CCONJ
cana-2667	119	7	svm	svm	ADJ
cana-2667	119	8	components	component	NOUN
cana-2667	119	9	are	be	AUX
cana-2667	119	10	one	one	NUM
cana-2667	119	11	of	of	ADP
cana-2667	119	12	the	the	DET
cana-2667	119	13	primary	primary	ADJ
cana-2667	119	14	challenges	challenge	NOUN
cana-2667	119	15	.	.	PUNCT
cana-2667	120	1	the	the	DET
cana-2667	120	2	cnn	cnn	PROPN
cana-2667	120	3	needs	need	VERB
cana-2667	120	4	to	to	PART
cana-2667	120	5	put	put	VERB
cana-2667	120	6	an	an	DET
cana-2667	120	7	extensive	extensive	ADJ
cana-2667	120	8	focus	focus	NOUN
cana-2667	120	9	on	on	ADP
cana-2667	120	10	selecting	select	VERB
cana-2667	120	11	the	the	DET
cana-2667	120	12	most	most	ADV
cana-2667	120	13	pertinent	pertinent	ADJ
cana-2667	120	14	features	feature	NOUN
cana-2667	120	15	,	,	PUNCT
cana-2667	120	16	and	and	CCONJ
cana-2667	120	17	the	the	DET
cana-2667	120	18	svm	svm	NOUN
cana-2667	120	19	needs	need	VERB
cana-2667	120	20	to	to	PART
cana-2667	120	21	be	be	AUX
cana-2667	120	22	optimized	optimize	VERB
cana-2667	120	23	for	for	ADP
cana-2667	120	24	best	good	ADJ
cana-2667	120	25	classification	classification	NOUN
cana-2667	120	26	.	.	PUNCT
cana-2667	121	1	despite	despite	SCONJ
cana-2667	121	2	their	their	PRON
cana-2667	121	3	communications	communication	NOUN
cana-2667	121	4	on	on	ADP
cana-2667	121	5	applied	apply	VERB
cana-2667	121	6	nonlinear	nonlinear	ADJ
cana-2667	121	7	analysis	analysis	NOUN
cana-2667	121	8	issn	issn	NOUN
cana-2667	121	9	:	:	PUNCT
cana-2667	121	10	1074	1074	NUM
cana-2667	121	11	-	-	PUNCT
cana-2667	121	12	133x	133x	NUM
cana-2667	121	13	vol	vol	NOUN
cana-2667	121	14	32	32	NUM
cana-2667	121	15	no	no	NOUN
cana-2667	121	16	.	.	PUNCT
cana-2667	122	1	3s	3s	NUM
cana-2667	122	2	(	(	PUNCT
cana-2667	122	3	2025	2025	NUM
cana-2667	122	4	)	)	PUNCT
cana-2667	122	5	385	385	NUM
cana-2667	122	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	122	7	popularity	popularity	NOUN
cana-2667	122	8	,	,	PUNCT
cana-2667	122	9	hybrid	hybrid	NOUN
cana-2667	122	10	models	model	NOUN
cana-2667	122	11	may	may	AUX
cana-2667	122	12	also	also	ADV
cana-2667	122	13	present	present	VERB
cana-2667	122	14	additional	additional	ADJ
cana-2667	122	15	challenges	challenge	NOUN
cana-2667	122	16	when	when	SCONJ
cana-2667	122	17	it	it	PRON
cana-2667	122	18	comes	come	VERB
cana-2667	122	19	to	to	ADP
cana-2667	122	20	computational	computational	ADJ
cana-2667	122	21	complexity	complexity	NOUN
cana-2667	122	22	,	,	PUNCT
cana-2667	122	23	as	as	SCONJ
cana-2667	122	24	both	both	DET
cana-2667	122	25	cnns	cnn	NOUN
cana-2667	122	26	and	and	CCONJ
cana-2667	122	27	svms	svms	NOUN
cana-2667	122	28	can	can	AUX
cana-2667	122	29	be	be	AUX
cana-2667	122	30	computationally	computationally	ADV
cana-2667	122	31	expensive	expensive	ADJ
cana-2667	122	32	to	to	PART
cana-2667	122	33	train	train	VERB
cana-2667	122	34	and	and	CCONJ
cana-2667	122	35	optimize	optimize	VERB
cana-2667	122	36	.	.	PUNCT
cana-2667	123	1	nonetheless	nonetheless	ADV
cana-2667	123	2	,	,	PUNCT
cana-2667	123	3	hybrid	hybrid	ADJ
cana-2667	123	4	cnn	cnn	PROPN
cana-2667	123	5	-	-	PUNCT
cana-2667	123	6	svm	svm	PROPN
cana-2667	123	7	models	model	NOUN
cana-2667	123	8	have	have	AUX
cana-2667	123	9	proven	prove	VERB
cana-2667	123	10	to	to	PART
cana-2667	123	11	be	be	AUX
cana-2667	123	12	highly	highly	ADV
cana-2667	123	13	successful	successful	ADJ
cana-2667	123	14	in	in	ADP
cana-2667	123	15	enhancing	enhance	VERB
cana-2667	123	16	classification	classification	NOUN
cana-2667	123	17	accuracy	accuracy	NOUN
cana-2667	123	18	while	while	SCONJ
cana-2667	123	19	minimizing	minimize	VERB
cana-2667	123	20	overfitting	overfitting	NOUN
cana-2667	123	21	from	from	ADP
cana-2667	123	22	deep	deep	ADJ
cana-2667	123	23	neural	neural	ADJ
cana-2667	123	24	networks	network	NOUN
cana-2667	123	25	.	.	PUNCT
cana-2667	124	1	such	such	ADJ
cana-2667	124	2	models	model	NOUN
cana-2667	124	3	were	be	AUX
cana-2667	124	4	applied	apply	VERB
cana-2667	124	5	to	to	ADP
cana-2667	124	6	the	the	DET
cana-2667	124	7	different	different	ADJ
cana-2667	124	8	types	type	NOUN
cana-2667	124	9	of	of	ADP
cana-2667	124	10	retinal	retinal	ADJ
cana-2667	124	11	disease	disease	NOUN
cana-2667	124	12	(	(	PUNCT
cana-2667	124	13	e.g.	e.g.	ADV
cana-2667	124	14	diabetic	diabetic	ADJ
cana-2667	124	15	retinopathy	retinopathy	NOUN
cana-2667	124	16	,	,	PUNCT
cana-2667	124	17	age	age	NOUN
cana-2667	124	18	-	-	PUNCT
cana-2667	124	19	related	relate	VERB
cana-2667	124	20	macular	macular	ADJ
cana-2667	124	21	degeneration	degeneration	NOUN
cana-2667	124	22	,	,	PUNCT
cana-2667	124	23	hypertensive	hypertensive	ADJ
cana-2667	124	24	retinopathy	retinopathy	NOUN
cana-2667	124	25	)	)	PUNCT
cana-2667	124	26	with	with	ADP
cana-2667	124	27	good	good	ADJ
cana-2667	124	28	result	result	NOUN
cana-2667	124	29	.	.	PUNCT
cana-2667	125	1	nonetheless	nonetheless	ADV
cana-2667	125	2	,	,	PUNCT
cana-2667	125	3	significant	significant	ADJ
cana-2667	125	4	space	space	NOUN
cana-2667	125	5	for	for	ADP
cana-2667	125	6	enhancement	enhancement	NOUN
cana-2667	125	7	is	be	AUX
cana-2667	125	8	still	still	ADV
cana-2667	125	9	identified	identify	VERB
cana-2667	125	10	,	,	PUNCT
cana-2667	125	11	especially	especially	ADV
cana-2667	125	12	for	for	ADP
cana-2667	125	13	model	model	NOUN
cana-2667	125	14	optimization	optimization	NOUN
cana-2667	125	15	and	and	CCONJ
cana-2667	125	16	generalization	generalization	NOUN
cana-2667	125	17	.	.	PUNCT
cana-2667	126	1	source	source	NOUN
cana-2667	126	2	objective	objective	ADJ
cana-2667	126	3	methods	method	NOUN
cana-2667	126	4	used	use	VERB
cana-2667	126	5	results	result	NOUN
cana-2667	126	6	research	research	NOUN
cana-2667	126	7	gap	gap	NOUN
cana-2667	126	8	[	[	X
cana-2667	126	9	15	15	NUM
cana-2667	126	10	]	]	SYM
cana-2667	126	11	•	•	NOUN
cana-2667	126	12	early	early	ADJ
cana-2667	126	13	detection	detection	NOUN
cana-2667	126	14	of	of	ADP
cana-2667	126	15	diabetic	diabetic	ADJ
cana-2667	126	16	retinopathy	retinopathy	NOUN
cana-2667	126	17	for	for	ADP
cana-2667	126	18	effective	effective	ADJ
cana-2667	126	19	intervention	intervention	NOUN
cana-2667	126	20	.	.	PUNCT
cana-2667	127	1	•	•	NUM
cana-2667	127	2	optimize	optimize	NOUN
cana-2667	127	3	performance	performance	NOUN
cana-2667	127	4	and	and	CCONJ
cana-2667	127	5	interpretability	interpretability	NOUN
cana-2667	127	6	for	for	ADP
cana-2667	127	7	clinical	clinical	ADJ
cana-2667	127	8	applications	application	NOUN
cana-2667	127	9	.	.	PUNCT
cana-2667	128	1	•	•	NUM
cana-2667	128	2	explainable	explainable	ADJ
cana-2667	128	3	deep	deep	ADJ
cana-2667	128	4	learning	learning	NOUN
cana-2667	128	5	for	for	ADP
cana-2667	128	6	retinal	retinal	ADJ
cana-2667	128	7	image	image	NOUN
cana-2667	128	8	analysis	analysis	NOUN
cana-2667	128	9	.	.	PUNCT
cana-2667	129	1	•	•	NUM
cana-2667	129	2	hybrid	hybrid	ADJ
cana-2667	129	3	feature	feature	NOUN
cana-2667	129	4	extraction	extraction	NOUN
cana-2667	129	5	and	and	CCONJ
cana-2667	129	6	advanced	advanced	ADJ
cana-2667	129	7	data	datum	NOUN
cana-2667	129	8	augmentation	augmentation	NOUN
cana-2667	129	9	•	•	ADP
cana-2667	129	10	xdnn	xdnn	PROPN
cana-2667	129	11	model	model	NOUN
cana-2667	129	12	achieved	achieve	VERB
cana-2667	129	13	98	98	NUM
cana-2667	129	14	%	%	NOUN
cana-2667	129	15	accuracy	accuracy	NOUN
cana-2667	129	16	on	on	ADP
cana-2667	129	17	messidor-2	messidor-2	NUM
cana-2667	129	18	dataset	dataset	NOUN
cana-2667	129	19	.	.	PUNCT
cana-2667	130	1	•	•	NUM
cana-2667	130	2	99.7	99.7	NUM
cana-2667	130	3	%	%	NOUN
cana-2667	130	4	accuracy	accuracy	NOUN
cana-2667	130	5	on	on	ADP
cana-2667	130	6	aptos	aptos	PROPN
cana-2667	130	7	2019	2019	NUM
cana-2667	130	8	dataset	dataset	NOUN
cana-2667	130	9	;	;	PUNCT
cana-2667	130	10	99	99	NUM
cana-2667	130	11	%	%	NOUN
cana-2667	130	12	on	on	ADP
cana-2667	130	13	idrid	idrid	ADJ
cana-2667	130	14	dataset	dataset	NOUN
cana-2667	130	15	.	.	PUNCT
cana-2667	131	1	•	•	NUM
cana-2667	131	2	large	large	ADJ
cana-2667	131	3	dataset	dataset	NOUN
cana-2667	131	4	and	and	CCONJ
cana-2667	131	5	processing	processing	NOUN
cana-2667	131	6	difficulty	difficulty	NOUN
cana-2667	131	7	.	.	PUNCT
cana-2667	132	1	•	•	NUM
cana-2667	132	2	complex	complex	ADJ
cana-2667	132	3	training	training	NOUN
cana-2667	132	4	and	and	CCONJ
cana-2667	132	5	computation	computation	NOUN
cana-2667	132	6	time	time	NOUN
cana-2667	132	7	.	.	PUNCT
cana-2667	133	1	[	[	X
cana-2667	133	2	16	16	NUM
cana-2667	133	3	]	]	SYM
cana-2667	133	4	•	•	X
cana-2667	133	5	integrative	integrative	ADJ
cana-2667	133	6	ml	ml	NOUN
cana-2667	133	7	and	and	CCONJ
cana-2667	133	8	dl	dl	PROPN
cana-2667	133	9	for	for	ADP
cana-2667	133	10	dr	dr	PROPN
cana-2667	133	11	diagnosis	diagnosis	NOUN
cana-2667	133	12	enhancement	enhancement	NOUN
cana-2667	133	13	.	.	PUNCT
cana-2667	134	1	•	•	NOUN
cana-2667	134	2	improve	improve	VERB
cana-2667	134	3	accuracy	accuracy	NOUN
cana-2667	134	4	and	and	CCONJ
cana-2667	134	5	efficiency	efficiency	NOUN
cana-2667	134	6	of	of	ADP
cana-2667	134	7	dr	dr	PROPN
cana-2667	134	8	diagnosis	diagnosis	NOUN
cana-2667	134	9	.	.	PUNCT
cana-2667	135	1	•	•	NUM
cana-2667	135	2	machine	machine	NOUN
cana-2667	135	3	learning	learning	NOUN
cana-2667	135	4	and	and	CCONJ
cana-2667	135	5	deep	deep	ADJ
cana-2667	135	6	learning	learning	NOUN
cana-2667	135	7	techniques	technique	NOUN
cana-2667	135	8	for	for	ADP
cana-2667	135	9	feature	feature	NOUN
cana-2667	135	10	extraction	extraction	NOUN
cana-2667	135	11	.	.	PUNCT
cana-2667	136	1	•	•	NUM
cana-2667	136	2	various	various	ADJ
cana-2667	136	3	classifiers	classifier	NOUN
cana-2667	136	4	like	like	ADP
cana-2667	136	5	svm	svm	ADJ
cana-2667	136	6	,	,	PUNCT
cana-2667	136	7	random	random	ADJ
cana-2667	136	8	forests	forest	NOUN
cana-2667	136	9	,	,	PUNCT
cana-2667	136	10	and	and	CCONJ
cana-2667	136	11	cnns	cnn	NOUN
cana-2667	136	12	for	for	ADP
cana-2667	136	13	classification	classification	NOUN
cana-2667	136	14	.	.	PUNCT
cana-2667	137	1	•	•	NUM
cana-2667	137	2	improved	improve	VERB
cana-2667	137	3	accuracy	accuracy	NOUN
cana-2667	137	4	and	and	CCONJ
cana-2667	137	5	efficiency	efficiency	NOUN
cana-2667	137	6	in	in	ADP
cana-2667	137	7	diabetic	diabetic	ADJ
cana-2667	137	8	retinopathy	retinopathy	ADJ
cana-2667	137	9	diagnosis	diagnosis	NOUN
cana-2667	137	10	.	.	PUNCT
cana-2667	138	1	•	•	NOUN
cana-2667	138	2	promising	promise	VERB
cana-2667	138	3	potential	potential	NOUN
cana-2667	138	4	for	for	ADP
cana-2667	138	5	timely	timely	ADJ
cana-2667	138	6	intervention	intervention	NOUN
cana-2667	138	7	and	and	CCONJ
cana-2667	138	8	management	management	NOUN
cana-2667	138	9	.	.	PUNCT
cana-2667	139	1	•	•	NUM
cana-2667	139	2	misclassification	misclassification	NOUN
cana-2667	139	3	of	of	ADP
cana-2667	139	4	healthy	healthy	ADJ
cana-2667	139	5	retinal	retinal	ADJ
cana-2667	139	6	images	image	NOUN
cana-2667	139	7	by	by	ADP
cana-2667	139	8	current	current	ADJ
cana-2667	139	9	methods	method	NOUN
cana-2667	139	10	.	.	PUNCT
cana-2667	140	1	•	•	NOUN
cana-2667	140	2	need	need	NOUN
cana-2667	140	3	for	for	ADP
cana-2667	140	4	accurate	accurate	ADJ
cana-2667	140	5	and	and	CCONJ
cana-2667	140	6	timely	timely	ADJ
cana-2667	140	7	diabetic	diabetic	ADJ
cana-2667	140	8	retinopathy	retinopathy	ADJ
cana-2667	140	9	diagnosis	diagnosis	NOUN
cana-2667	140	10	.	.	PUNCT
cana-2667	141	1	[	[	X
cana-2667	141	2	17	17	NUM
cana-2667	141	3	]	]	SYM
cana-2667	141	4	•	•	NUM
cana-2667	141	5	accurate	accurate	ADJ
cana-2667	141	6	classification	classification	NOUN
cana-2667	141	7	of	of	ADP
cana-2667	141	8	retinal	retinal	ADJ
cana-2667	141	9	diseases	disease	NOUN
cana-2667	141	10	using	use	VERB
cana-2667	141	11	deep	deep	ADJ
cana-2667	141	12	learning	learning	NOUN
cana-2667	141	13	.	.	PUNCT
cana-2667	142	1	•	•	NOUN
cana-2667	142	2	improve	improve	VERB
cana-2667	142	3	segmentation	segmentation	NOUN
cana-2667	142	4	and	and	CCONJ
cana-2667	142	5	classification	classification	NOUN
cana-2667	142	6	accuracy	accuracy	NOUN
cana-2667	142	7	of	of	ADP
cana-2667	142	8	diabetic	diabetic	ADJ
cana-2667	142	9	retinopathy	retinopathy	NOUN
cana-2667	142	10	.	.	PUNCT
cana-2667	143	1	•	•	NUM
cana-2667	143	2	improved	improve	VERB
cana-2667	143	3	median	median	ADJ
cana-2667	143	4	filter	filter	NOUN
cana-2667	143	5	for	for	ADP
cana-2667	143	6	noise	noise	NOUN
cana-2667	143	7	reduction	reduction	NOUN
cana-2667	143	8	.	.	PUNCT
cana-2667	144	1	•	•	NUM
cana-2667	144	2	unet++	unet++	PROPN
cana-2667	144	3	for	for	ADP
cana-2667	144	4	disease	disease	NOUN
cana-2667	144	5	segmentation	segmentation	NOUN
cana-2667	144	6	and	and	CCONJ
cana-2667	144	7	feature	feature	NOUN
cana-2667	144	8	extraction	extraction	NOUN
cana-2667	144	9	.	.	PUNCT
cana-2667	145	1	•	•	NUM
cana-2667	145	2	improved	improve	VERB
cana-2667	145	3	gannet	gannet	NOUN
cana-2667	145	4	optimizationbased	optimizationbase	VERB
cana-2667	145	5	capsule	capsule	ADJ
cana-2667	145	6	densenet	densenet	NOUN
cana-2667	145	7	for	for	ADP
cana-2667	145	8	classification	classification	NOUN
cana-2667	145	9	.	.	PUNCT
cana-2667	146	1	•	•	NUM
cana-2667	146	2	accuracy	accuracy	NOUN
cana-2667	146	3	achieved	achieve	VERB
cana-2667	146	4	:	:	PUNCT
cana-2667	146	5	0.9917	0.9917	NUM
cana-2667	146	6	on	on	ADP
cana-2667	146	7	aptos-2019	aptos-2019	ADJ
cana-2667	146	8	dataset	dataset	NOUN
cana-2667	146	9	.	.	PUNCT
cana-2667	147	1	•	•	NUM
cana-2667	147	2	dice	dice	NOUN
cana-2667	147	3	score	score	NOUN
cana-2667	147	4	value	value	NOUN
cana-2667	147	5	:	:	PUNCT
cana-2667	147	6	0.9652	0.9652	NUM
cana-2667	147	7	.	.	PUNCT
cana-2667	148	1	•	•	NOUN
cana-2667	148	2	identifying	identify	VERB
cana-2667	148	3	mild	mild	ADJ
cana-2667	148	4	stages	stage	NOUN
cana-2667	148	5	for	for	ADP
cana-2667	148	6	early	early	ADJ
cana-2667	148	7	disease	disease	NOUN
cana-2667	148	8	management	management	NOUN
cana-2667	148	9	is	be	AUX
cana-2667	148	10	crucial	crucial	ADJ
cana-2667	148	11	.	.	PUNCT
cana-2667	149	1	•	•	NUM
cana-2667	149	2	accurate	accurate	ADJ
cana-2667	149	3	classification	classification	NOUN
cana-2667	149	4	requires	require	VERB
cana-2667	149	5	effective	effective	ADJ
cana-2667	149	6	pre	pre	ADJ
cana-2667	149	7	-	-	ADJ
cana-2667	149	8	processing	processing	ADJ
cana-2667	149	9	methods	method	NOUN
cana-2667	149	10	and	and	CCONJ
cana-2667	149	11	hyper	hyper	ADJ
cana-2667	149	12	-	-	ADJ
cana-2667	149	13	parameter	parameter	ADJ
cana-2667	149	14	tuning	tuning	NOUN
cana-2667	149	15	.	.	PUNCT
cana-2667	150	1	communications	communication	NOUN
cana-2667	150	2	on	on	ADP
cana-2667	150	3	applied	apply	VERB
cana-2667	150	4	nonlinear	nonlinear	ADJ
cana-2667	150	5	analysis	analysis	NOUN
cana-2667	150	6	issn	issn	NOUN
cana-2667	150	7	:	:	PUNCT
cana-2667	150	8	1074	1074	NUM
cana-2667	150	9	-	-	PUNCT
cana-2667	150	10	133x	133x	NUM
cana-2667	150	11	vol	vol	NOUN
cana-2667	150	12	32	32	NUM
cana-2667	150	13	no	no	NOUN
cana-2667	150	14	.	.	PUNCT
cana-2667	151	1	3s	3s	NUM
cana-2667	151	2	(	(	PUNCT
cana-2667	151	3	2025	2025	NUM
cana-2667	151	4	)	)	PUNCT
cana-2667	151	5	386	386	NUM
cana-2667	151	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	152	1	[	[	X
cana-2667	152	2	18	18	NUM
cana-2667	152	3	]	]	SYM
cana-2667	152	4	•	•	NOUN
cana-2667	152	5	enhance	enhance	VERB
cana-2667	152	6	diabetic	diabetic	ADJ
cana-2667	152	7	retinopathy	retinopathy	ADJ
cana-2667	152	8	detection	detection	NOUN
cana-2667	152	9	using	use	VERB
cana-2667	152	10	deep	deep	ADJ
cana-2667	152	11	learning	learning	NOUN
cana-2667	152	12	techniques	technique	NOUN
cana-2667	152	13	.	.	PUNCT
cana-2667	153	1	•	•	ADJ
cana-2667	153	2	address	address	NOUN
cana-2667	153	3	challenges	challenge	NOUN
cana-2667	153	4	of	of	ADP
cana-2667	153	5	unbalanced	unbalanced	ADJ
cana-2667	153	6	datasets	dataset	NOUN
cana-2667	153	7	in	in	ADP
cana-2667	153	8	classification	classification	NOUN
cana-2667	153	9	.	.	PUNCT
cana-2667	154	1	•	•	NOUN
cana-2667	154	2	transfer	transfer	NOUN
cana-2667	154	3	learning	learning	NOUN
cana-2667	154	4	with	with	ADP
cana-2667	154	5	modified	modify	VERB
cana-2667	154	6	resnet50	resnet50	NOUN
cana-2667	154	7	model	model	NOUN
cana-2667	154	8	•	•	NOUN
cana-2667	154	9	integration	integration	NOUN
cana-2667	154	10	of	of	ADP
cana-2667	154	11	self	self	NOUN
cana-2667	154	12	-	-	PUNCT
cana-2667	154	13	attention	attention	NOUN
cana-2667	154	14	mechanism	mechanism	NOUN
cana-2667	154	15	for	for	ADP
cana-2667	154	16	feature	feature	NOUN
cana-2667	154	17	focus	focus	VERB
cana-2667	154	18	•	•	ADP
cana-2667	154	19	training	training	NOUN
cana-2667	154	20	accuracy	accuracy	NOUN
cana-2667	154	21	:	:	PUNCT
cana-2667	154	22	98.24	98.24	NUM
cana-2667	154	23	%	%	NOUN
cana-2667	154	24	,	,	PUNCT
cana-2667	154	25	test	test	NOUN
cana-2667	154	26	accuracy	accuracy	NOUN
cana-2667	154	27	:	:	PUNCT
cana-2667	154	28	0.89	0.89	NUM
cana-2667	154	29	.	.	PUNCT
cana-2667	155	1	•	•	NUM
cana-2667	155	2	f1	f1	PROPN
cana-2667	155	3	score	score	NOUN
cana-2667	155	4	achieved	achieve	VERB
cana-2667	155	5	:	:	PUNCT
cana-2667	156	1	0.94	0.94	NUM
cana-2667	156	2	.	.	NOUN
cana-2667	156	3	•	•	NUM
cana-2667	156	4	scarcity	scarcity	NOUN
cana-2667	156	5	of	of	ADP
cana-2667	156	6	medical	medical	ADJ
cana-2667	156	7	specialists	specialist	NOUN
cana-2667	156	8	in	in	ADP
cana-2667	156	9	areas	area	NOUN
cana-2667	156	10	with	with	ADP
cana-2667	156	11	common	common	ADJ
cana-2667	156	12	retinal	retinal	ADJ
cana-2667	156	13	diseases	disease	NOUN
cana-2667	156	14	.	.	PUNCT
cana-2667	157	1	•	•	NUM
cana-2667	157	2	impact	impact	NOUN
cana-2667	157	3	of	of	ADP
cana-2667	157	4	uncertainty	uncertainty	NOUN
cana-2667	157	5	on	on	ADP
cana-2667	157	6	system	system	NOUN
cana-2667	157	7	performance	performance	NOUN
cana-2667	157	8	and	and	CCONJ
cana-2667	157	9	classification	classification	NOUN
cana-2667	157	10	accuracy	accuracy	NOUN
cana-2667	157	11	.	.	PUNCT
cana-2667	158	1	[	[	X
cana-2667	158	2	19	19	NUM
cana-2667	158	3	]	]	SYM
cana-2667	158	4	•	•	X
cana-2667	158	5	create	create	VERB
cana-2667	158	6	an	an	DET
cana-2667	158	7	automated	automate	VERB
cana-2667	158	8	method	method	NOUN
cana-2667	158	9	for	for	ADP
cana-2667	158	10	retinal	retinal	ADJ
cana-2667	158	11	disorder	disorder	NOUN
cana-2667	158	12	classification	classification	NOUN
cana-2667	158	13	.	.	PUNCT
cana-2667	159	1	•	•	NUM
cana-2667	159	2	classify	classify	VERB
cana-2667	159	3	disorders	disorder	NOUN
cana-2667	159	4	into	into	ADP
cana-2667	159	5	four	four	NUM
cana-2667	159	6	categories	category	NOUN
cana-2667	159	7	using	use	VERB
cana-2667	159	8	oct	oct	PROPN
cana-2667	159	9	images	image	NOUN
cana-2667	159	10	.	.	PUNCT
cana-2667	160	1	•	•	NUM
cana-2667	160	2	machine	machine	NOUN
cana-2667	160	3	learning	learning	NOUN
cana-2667	160	4	and	and	CCONJ
cana-2667	160	5	deep	deep	ADJ
cana-2667	160	6	learningbased	learningbase	VERB
cana-2667	160	7	techniques	technique	NOUN
cana-2667	160	8	•	•	NOUN
cana-2667	160	9	support	support	NOUN
cana-2667	160	10	vector	vector	NOUN
cana-2667	160	11	machine	machine	NOUN
cana-2667	160	12	,	,	PUNCT
cana-2667	160	13	knearest	knearest	NOUN
cana-2667	160	14	neighbor	neighbor	NOUN
cana-2667	160	15	,	,	PUNCT
cana-2667	160	16	decision	decision	NOUN
cana-2667	160	17	tree	tree	NOUN
cana-2667	160	18	,	,	PUNCT
cana-2667	160	19	ensemble	ensemble	ADJ
cana-2667	160	20	model	model	NOUN
cana-2667	160	21	•	•	ADP
cana-2667	160	22	svm	svm	PROPN
cana-2667	160	23	,	,	PUNCT
cana-2667	160	24	k	k	PROPN
cana-2667	160	25	-	-	PUNCT
cana-2667	160	26	nn	nn	PROPN
cana-2667	160	27	,	,	PUNCT
cana-2667	160	28	dt	dt	PROPN
cana-2667	160	29	,	,	PUNCT
cana-2667	160	30	em	em	PRON
cana-2667	160	31	classifiers	classifier	NOUN
cana-2667	160	32	achieved	achieve	VERB
cana-2667	160	33	high	high	ADJ
cana-2667	160	34	accuracies	accuracy	NOUN
cana-2667	160	35	.	.	PUNCT
cana-2667	161	1	•	•	NUM
cana-2667	161	2	proposed	propose	VERB
cana-2667	161	3	model	model	NOUN
cana-2667	161	4	accurately	accurately	ADV
cana-2667	161	5	classified	classify	VERB
cana-2667	161	6	retinal	retinal	ADJ
cana-2667	161	7	disorders	disorder	NOUN
cana-2667	161	8	with	with	ADP
cana-2667	161	9	state	state	NOUN
cana-2667	161	10	-	-	PUNCT
cana-2667	161	11	of	of	ADP
cana-2667	161	12	-	-	PUNCT
cana-2667	161	13	the	the	DET
cana-2667	161	14	-	-	PUNCT
cana-2667	161	15	art	art	NOUN
cana-2667	161	16	performance	performance	NOUN
cana-2667	161	17	•	•	NOUN
cana-2667	161	18	unbalanced	unbalanced	ADJ
cana-2667	161	19	datasets	dataset	NOUN
cana-2667	161	20	impact	impact	NOUN
cana-2667	161	21	detection	detection	NOUN
cana-2667	161	22	efficiency	efficiency	NOUN
cana-2667	161	23	and	and	CCONJ
cana-2667	161	24	accuracy	accuracy	NOUN
cana-2667	161	25	.	.	PUNCT
cana-2667	162	1	•	•	NOUN
cana-2667	162	2	need	need	NOUN
cana-2667	162	3	for	for	ADP
cana-2667	162	4	improved	improved	ADJ
cana-2667	162	5	feature	feature	NOUN
cana-2667	162	6	focus	focus	NOUN
cana-2667	162	7	in	in	ADP
cana-2667	162	8	classification	classification	NOUN
cana-2667	162	9	.	.	PUNCT
cana-2667	163	1	[	[	X
cana-2667	163	2	20	20	NUM
cana-2667	163	3	]	]	SYM
cana-2667	163	4	•	•	NOUN
cana-2667	163	5	early	early	ADJ
cana-2667	163	6	detection	detection	NOUN
cana-2667	163	7	and	and	CCONJ
cana-2667	163	8	classification	classification	NOUN
cana-2667	163	9	of	of	ADP
cana-2667	163	10	retinal	retinal	ADJ
cana-2667	163	11	diseases	disease	NOUN
cana-2667	163	12	.	.	PUNCT
cana-2667	163	13	•	•	NUM
cana-2667	163	14	enhance	enhance	VERB
cana-2667	163	15	operational	operational	ADJ
cana-2667	163	16	speed	speed	NOUN
cana-2667	163	17	and	and	CCONJ
cana-2667	163	18	classification	classification	NOUN
cana-2667	163	19	accuracy	accuracy	NOUN
cana-2667	163	20	.	.	PUNCT
cana-2667	164	1	•	•	NUM
cana-2667	164	2	optimized	optimize	VERB
cana-2667	164	3	african	african	ADJ
cana-2667	164	4	buffalo	buffalo	NOUN
cana-2667	164	5	-	-	PUNCT
cana-2667	164	6	based	base	VERB
cana-2667	164	7	deep	deep	ADJ
cana-2667	164	8	convolutional	convolutional	ADJ
cana-2667	164	9	neural	neural	ADJ
cana-2667	164	10	network	network	NOUN
cana-2667	164	11	(	(	PUNCT
cana-2667	164	12	abdcnn	abdcnn	PROPN
cana-2667	164	13	)	)	PUNCT
cana-2667	164	14	•	•	NUM
cana-2667	164	15	routine	routine	ADJ
cana-2667	164	16	screening	screening	NOUN
cana-2667	164	17	and	and	CCONJ
cana-2667	164	18	expert	expert	NOUN
cana-2667	164	19	evaluation	evaluation	NOUN
cana-2667	164	20	of	of	ADP
cana-2667	164	21	eye	eye	NOUN
cana-2667	164	22	photographs	photograph	NOUN
cana-2667	164	23	•	•	VERB
cana-2667	164	24	ab	ab	PROPN
cana-2667	164	25	-	-	PUNCT
cana-2667	164	26	dcnn	dcnn	ADJ
cana-2667	164	27	model	model	NOUN
cana-2667	164	28	detects	detect	NOUN
cana-2667	164	29	and	and	CCONJ
cana-2667	164	30	classifies	classify	VERB
cana-2667	164	31	retinal	retinal	ADJ
cana-2667	164	32	diseases	disease	NOUN
cana-2667	164	33	accurately	accurately	ADV
cana-2667	164	34	.	.	PUNCT
cana-2667	165	1	•	•	NUM
cana-2667	165	2	methodology	methodology	NOUN
cana-2667	165	3	improves	improve	VERB
cana-2667	165	4	operational	operational	ADJ
cana-2667	165	5	speed	speed	NOUN
cana-2667	165	6	,	,	PUNCT
cana-2667	165	7	reduces	reduce	VERB
cana-2667	165	8	losses	loss	NOUN
cana-2667	165	9	,	,	PUNCT
cana-2667	165	10	and	and	CCONJ
cana-2667	165	11	enhances	enhance	VERB
cana-2667	165	12	accuracy	accuracy	NOUN
cana-2667	165	13	.	.	PUNCT
cana-2667	166	1	•	•	NOUN
cana-2667	166	2	noise	noise	NOUN
cana-2667	166	3	and	and	CCONJ
cana-2667	166	4	artifacts	artifact	NOUN
cana-2667	166	5	in	in	ADP
cana-2667	166	6	retinal	retinal	ADJ
cana-2667	166	7	fundus	fundus	NOUN
cana-2667	166	8	images	image	NOUN
cana-2667	166	9	.	.	PUNCT
cana-2667	167	1	•	•	NOUN
cana-2667	167	2	need	need	NOUN
cana-2667	167	3	for	for	ADP
cana-2667	167	4	early	early	ADJ
cana-2667	167	5	diagnosis	diagnosis	NOUN
cana-2667	167	6	to	to	PART
cana-2667	167	7	prevent	prevent	VERB
cana-2667	167	8	vision	vision	NOUN
cana-2667	167	9	loss	loss	NOUN
cana-2667	167	10	.	.	PUNCT
cana-2667	168	1	[	[	X
cana-2667	168	2	21	21	NUM
cana-2667	168	3	]	]	SYM
cana-2667	168	4	•	•	NOUN
cana-2667	168	5	improve	improve	VERB
cana-2667	168	6	diabetic	diabetic	ADJ
cana-2667	168	7	retinopathy	retinopathy	ADJ
cana-2667	168	8	classification	classification	NOUN
cana-2667	168	9	accuracy	accuracy	NOUN
cana-2667	168	10	using	use	VERB
cana-2667	168	11	image	image	NOUN
cana-2667	168	12	filtering	filtering	NOUN
cana-2667	168	13	techniques	technique	NOUN
cana-2667	168	14	.	.	PUNCT
cana-2667	169	1	•	•	NUM
cana-2667	169	2	deep	deep	ADJ
cana-2667	169	3	learning	learning	NOUN
cana-2667	169	4	for	for	ADP
cana-2667	169	5	dr	dr	PROPN
cana-2667	169	6	detection	detection	NOUN
cana-2667	169	7	using	use	VERB
cana-2667	169	8	various	various	ADJ
cana-2667	169	9	models	model	NOUN
cana-2667	169	10	.	.	PUNCT
cana-2667	170	1	•	•	NUM
cana-2667	170	2	haar	haar	PROPN
cana-2667	170	3	wavelet	wavelet	NOUN
cana-2667	170	4	transform	transform	NOUN
cana-2667	170	5	for	for	ADP
cana-2667	170	6	•	•	NUM
cana-2667	170	7	best	good	ADJ
cana-2667	170	8	filter	filter	NOUN
cana-2667	170	9	model	model	NOUN
cana-2667	170	10	showed	show	VERB
cana-2667	170	11	superior	superior	ADJ
cana-2667	170	12	validation	validation	NOUN
cana-2667	170	13	accuracy	accuracy	NOUN
cana-2667	170	14	.	.	PUNCT
cana-2667	171	1	•	•	NOUN
cana-2667	171	2	proposed	propose	VERB
cana-2667	171	3	methodology	methodology	NOUN
cana-2667	171	4	•	•	NOUN
cana-2667	171	5	lack	lack	NOUN
cana-2667	171	6	of	of	ADP
cana-2667	171	7	discussion	discussion	NOUN
cana-2667	171	8	on	on	ADP
cana-2667	171	9	potential	potential	ADJ
cana-2667	171	10	limitations	limitation	NOUN
cana-2667	171	11	of	of	ADP
cana-2667	171	12	deep	deep	ADJ
cana-2667	171	13	learning	learning	NOUN
cana-2667	171	14	models	model	NOUN
cana-2667	171	15	.	.	PUNCT
cana-2667	172	1	communications	communication	NOUN
cana-2667	172	2	on	on	ADP
cana-2667	172	3	applied	apply	VERB
cana-2667	172	4	nonlinear	nonlinear	ADJ
cana-2667	172	5	analysis	analysis	NOUN
cana-2667	172	6	issn	issn	NOUN
cana-2667	172	7	:	:	PUNCT
cana-2667	172	8	1074	1074	NUM
cana-2667	172	9	-	-	PUNCT
cana-2667	172	10	133x	133x	NUM
cana-2667	172	11	vol	vol	NOUN
cana-2667	172	12	32	32	NUM
cana-2667	172	13	no	no	NOUN
cana-2667	172	14	.	.	PUNCT
cana-2667	173	1	3s	3s	NUM
cana-2667	173	2	(	(	PUNCT
cana-2667	173	3	2025	2025	NUM
cana-2667	173	4	)	)	PUNCT
cana-2667	173	5	387	387	NUM
cana-2667	173	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	173	7	•	•	NUM
cana-2667	173	8	utilize	utilize	VERB
cana-2667	173	9	pretrained	pretraine	VERB
cana-2667	173	10	deep	deep	ADJ
cana-2667	173	11	learning	learning	NOUN
cana-2667	173	12	models	model	NOUN
cana-2667	173	13	for	for	ADP
cana-2667	173	14	enhanced	enhanced	ADJ
cana-2667	173	15	classification	classification	NOUN
cana-2667	173	16	outcomes	outcome	NOUN
cana-2667	173	17	.	.	PUNCT
cana-2667	174	1	similarity	similarity	NOUN
cana-2667	174	2	measurements	measurement	NOUN
cana-2667	174	3	in	in	ADP
cana-2667	174	4	time	time	NOUN
cana-2667	174	5	series	series	PROPN
cana-2667	174	6	.	.	PUNCT
cana-2667	175	1	improved	improve	VERB
cana-2667	175	2	classification	classification	NOUN
cana-2667	175	3	accuracy	accuracy	NOUN
cana-2667	175	4	for	for	ADP
cana-2667	175	5	diabetic	diabetic	ADJ
cana-2667	175	6	retinopathy	retinopathy	NOUN
cana-2667	175	7	.	.	PUNCT
cana-2667	176	1	•	•	NUM
cana-2667	176	2	absence	absence	NOUN
cana-2667	176	3	of	of	ADP
cana-2667	176	4	exploration	exploration	NOUN
cana-2667	176	5	on	on	ADP
cana-2667	176	6	real	real	ADJ
cana-2667	176	7	-	-	PUNCT
cana-2667	176	8	world	world	NOUN
cana-2667	176	9	implementation	implementation	NOUN
cana-2667	176	10	challenges	challenge	NOUN
cana-2667	176	11	.	.	PUNCT
cana-2667	177	1	[	[	X
cana-2667	177	2	22	22	NUM
cana-2667	177	3	]	]	SYM
cana-2667	177	4	•	•	NUM
cana-2667	177	5	apply	apply	VERB
cana-2667	177	6	machine	machine	NOUN
cana-2667	177	7	learning	learning	NOUN
cana-2667	177	8	for	for	ADP
cana-2667	177	9	diabetic	diabetic	ADJ
cana-2667	177	10	retinopathy	retinopathy	ADJ
cana-2667	177	11	diagnosis	diagnosis	NOUN
cana-2667	177	12	.	.	PUNCT
cana-2667	178	1	•	•	NUM
cana-2667	178	2	utilize	utilize	VERB
cana-2667	178	3	deep	deep	ADJ
cana-2667	178	4	learning	learning	NOUN
cana-2667	178	5	for	for	ADP
cana-2667	178	6	effective	effective	ADJ
cana-2667	178	7	disease	disease	NOUN
cana-2667	178	8	management	management	NOUN
cana-2667	178	9	strategies	strategy	NOUN
cana-2667	178	10	.	.	PUNCT
cana-2667	179	1	•	•	NUM
cana-2667	179	2	resnet	resnet	NOUN
cana-2667	179	3	-	-	PUNCT
cana-2667	179	4	based	base	VERB
cana-2667	179	5	classification	classification	NOUN
cana-2667	179	6	framework	framework	NOUN
cana-2667	179	7	for	for	ADP
cana-2667	179	8	dr	dr	PROPN
cana-2667	179	9	assessment	assessment	NOUN
cana-2667	179	10	.	.	PUNCT
cana-2667	180	1	•	•	NUM
cana-2667	180	2	flask	flask	NOUN
cana-2667	180	3	-	-	PUNCT
cana-2667	180	4	based	base	VERB
cana-2667	180	5	interface	interface	NOUN
cana-2667	180	6	for	for	ADP
cana-2667	180	7	image	image	NOUN
cana-2667	180	8	upload	upload	NOUN
cana-2667	180	9	and	and	CCONJ
cana-2667	180	10	results	result	NOUN
cana-2667	180	11	.	.	PUNCT
cana-2667	181	1	•	•	NUM
cana-2667	181	2	deep	deep	ADJ
cana-2667	181	3	ensemble	ensemble	ADJ
cana-2667	181	4	networks	network	NOUN
cana-2667	181	5	for	for	ADP
cana-2667	181	6	drug	drug	NOUN
cana-2667	181	7	resistance	resistance	NOUN
cana-2667	181	8	identification	identification	NOUN
cana-2667	181	9	outperform	outperform	VERB
cana-2667	181	10	current	current	ADJ
cana-2667	181	11	techniques	technique	NOUN
cana-2667	181	12	.	.	PUNCT
cana-2667	182	1	•	•	NUM
cana-2667	182	2	cnn	cnn	PROPN
cana-2667	182	3	models	model	NOUN
cana-2667	182	4	trained	train	VERB
cana-2667	182	5	to	to	PART
cana-2667	182	6	detect	detect	VERB
cana-2667	182	7	minute	minute	ADJ
cana-2667	182	8	variations	variation	NOUN
cana-2667	182	9	in	in	ADP
cana-2667	182	10	dr	dr	PROPN
cana-2667	182	11	images	image	NOUN
cana-2667	182	12	.	.	PUNCT
cana-2667	183	1	•	•	NUM
cana-2667	183	2	large	large	ADJ
cana-2667	183	3	dataset	dataset	NOUN
cana-2667	183	4	,	,	PUNCT
cana-2667	183	5	processing	processing	NOUN
cana-2667	183	6	difficulty	difficulty	NOUN
cana-2667	183	7	,	,	PUNCT
cana-2667	183	8	complex	complex	ADJ
cana-2667	183	9	training	training	NOUN
cana-2667	183	10	,	,	PUNCT
cana-2667	183	11	computation	computation	NOUN
cana-2667	183	12	time	time	NOUN
cana-2667	183	13	•	•	ADP
cana-2667	183	14	existing	exist	VERB
cana-2667	183	15	work	work	NOUN
cana-2667	183	16	drawbacks	drawback	NOUN
cana-2667	183	17	:	:	PUNCT
cana-2667	183	18	support	support	NOUN
cana-2667	183	19	vector	vector	NOUN
cana-2667	183	20	machine	machine	NOUN
cana-2667	183	21	(	(	PUNCT
cana-2667	183	22	svm	svm	PROPN
cana-2667	183	23	)	)	PUNCT
cana-2667	183	24	method	method	NOUN
cana-2667	183	25	[	[	X
cana-2667	183	26	23	23	NUM
cana-2667	183	27	]	]	SYM
cana-2667	183	28	•	•	NOUN
cana-2667	183	29	improve	improve	VERB
cana-2667	183	30	diabetic	diabetic	ADJ
cana-2667	183	31	retinopathy	retinopathy	ADJ
cana-2667	183	32	classification	classification	NOUN
cana-2667	183	33	accuracy	accuracy	NOUN
cana-2667	183	34	and	and	CCONJ
cana-2667	183	35	reduce	reduce	VERB
cana-2667	183	36	false	false	ADJ
cana-2667	183	37	positives	positive	NOUN
cana-2667	183	38	.	.	PUNCT
cana-2667	184	1	•	•	NUM
cana-2667	184	2	develop	develop	VERB
cana-2667	184	3	a	a	DET
cana-2667	184	4	user	user	NOUN
cana-2667	184	5	-	-	PUNCT
cana-2667	184	6	friendly	friendly	ADJ
cana-2667	184	7	interface	interface	NOUN
cana-2667	184	8	for	for	ADP
cana-2667	184	9	image	image	NOUN
cana-2667	184	10	upload	upload	NOUN
cana-2667	184	11	and	and	CCONJ
cana-2667	184	12	results	result	NOUN
cana-2667	184	13	.	.	PUNCT
cana-2667	185	1	•	•	NUM
cana-2667	185	2	deep	deep	ADJ
cana-2667	185	3	convolutional	convolutional	ADJ
cana-2667	185	4	neural	neural	ADJ
cana-2667	185	5	networks	network	NOUN
cana-2667	185	6	(	(	PUNCT
cana-2667	185	7	dcnns	dcnns	ADJ
cana-2667	185	8	)	)	PUNCT
cana-2667	185	9	•	•	NOUN
cana-2667	185	10	feature	feature	NOUN
cana-2667	185	11	analysis	analysis	NOUN
cana-2667	185	12	of	of	ADP
cana-2667	185	13	blood	blood	NOUN
cana-2667	185	14	vessels	vessel	NOUN
cana-2667	185	15	•	•	NOUN
cana-2667	185	16	model	model	NOUN
cana-2667	185	17	reduces	reduce	VERB
cana-2667	185	18	false	false	ADJ
cana-2667	185	19	positives	positive	NOUN
cana-2667	185	20	in	in	ADP
cana-2667	185	21	dr	dr	PROPN
cana-2667	185	22	classification	classification	NOUN
cana-2667	185	23	.	.	PUNCT
cana-2667	186	1	•	•	NUM
cana-2667	186	2	superior	superior	ADJ
cana-2667	186	3	performance	performance	NOUN
cana-2667	186	4	in	in	ADP
cana-2667	186	5	assessing	assess	VERB
cana-2667	186	6	dr	dr	PROPN
cana-2667	186	7	severity	severity	NOUN
cana-2667	186	8	demonstrated	demonstrate	VERB
cana-2667	186	9	.	.	PUNCT
cana-2667	187	1	•	•	NUM
cana-2667	187	2	identifying	identify	VERB
cana-2667	187	3	mild	mild	ADJ
cana-2667	187	4	stages	stage	NOUN
cana-2667	187	5	for	for	ADP
cana-2667	187	6	early	early	ADJ
cana-2667	187	7	disease	disease	NOUN
cana-2667	187	8	management	management	NOUN
cana-2667	187	9	is	be	AUX
cana-2667	187	10	crucial	crucial	ADJ
cana-2667	187	11	.	.	PUNCT
cana-2667	188	1	•	•	NUM
cana-2667	188	2	accurate	accurate	ADJ
cana-2667	188	3	classification	classification	NOUN
cana-2667	188	4	requires	require	VERB
cana-2667	188	5	effective	effective	ADJ
cana-2667	188	6	pre	pre	ADJ
cana-2667	188	7	-	-	ADJ
cana-2667	188	8	processing	processing	ADJ
cana-2667	188	9	methods	method	NOUN
cana-2667	188	10	and	and	CCONJ
cana-2667	188	11	hyper	hyper	ADJ
cana-2667	188	12	-	-	ADJ
cana-2667	188	13	parameter	parameter	ADJ
cana-2667	188	14	tuning	tuning	NOUN
cana-2667	188	15	.	.	PUNCT
cana-2667	189	1	[	[	X
cana-2667	189	2	24	24	NUM
cana-2667	189	3	]	]	SYM
cana-2667	189	4	•	•	NUM
cana-2667	189	5	classify	classify	VERB
cana-2667	189	6	diabetic	diabetic	ADJ
cana-2667	189	7	retinopathy	retinopathy	ADJ
cana-2667	189	8	stages	stage	NOUN
cana-2667	189	9	accurately	accurately	ADV
cana-2667	189	10	.	.	PUNCT
cana-2667	190	1	•	•	PUNCT
cana-2667	190	2	utilize	utilize	VERB
cana-2667	190	3	deep	deep	ADJ
cana-2667	190	4	convolutional	convolutional	ADJ
cana-2667	190	5	neural	neural	ADJ
cana-2667	190	6	networks	network	NOUN
cana-2667	190	7	for	for	ADP
cana-2667	190	8	improved	improved	ADJ
cana-2667	190	9	results	result	NOUN
cana-2667	190	10	.	.	PUNCT
cana-2667	191	1	•	•	NUM
cana-2667	191	2	machine	machine	NOUN
cana-2667	191	3	learning	learning	NOUN
cana-2667	191	4	and	and	CCONJ
cana-2667	191	5	deep	deep	ADJ
cana-2667	191	6	learning	learning	NOUN
cana-2667	191	7	techniques	technique	NOUN
cana-2667	191	8	for	for	ADP
cana-2667	191	9	feature	feature	NOUN
cana-2667	191	10	extraction	extraction	NOUN
cana-2667	191	11	.	.	PUNCT
cana-2667	192	1	•	•	NUM
cana-2667	192	2	various	various	ADJ
cana-2667	192	3	classifiers	classifier	NOUN
cana-2667	192	4	like	like	ADP
cana-2667	192	5	svm	svm	ADJ
cana-2667	192	6	,	,	PUNCT
cana-2667	192	7	random	random	ADJ
cana-2667	192	8	forests	forest	NOUN
cana-2667	192	9	,	,	PUNCT
cana-2667	192	10	and	and	CCONJ
cana-2667	192	11	cnns	cnn	NOUN
cana-2667	192	12	for	for	ADP
cana-2667	192	13	classification	classification	NOUN
cana-2667	192	14	.	.	PUNCT
cana-2667	193	1	•	•	NUM
cana-2667	193	2	high	high	ADJ
cana-2667	193	3	accuracy	accuracy	NOUN
cana-2667	193	4	in	in	ADP
cana-2667	193	5	diabetic	diabetic	ADJ
cana-2667	193	6	retinopathy	retinopathy	ADJ
cana-2667	193	7	classification	classification	NOUN
cana-2667	193	8	•	•	NOUN
cana-2667	193	9	utilizes	utilize	VERB
cana-2667	193	10	deep	deep	ADJ
cana-2667	193	11	convolutional	convolutional	ADJ
cana-2667	193	12	neural	neural	ADJ
cana-2667	193	13	networks	network	NOUN
cana-2667	193	14	(	(	PUNCT
cana-2667	193	15	dcnns	dcnns	ADJ
cana-2667	193	16	)	)	PUNCT
cana-2667	193	17	for	for	ADP
cana-2667	193	18	image	image	NOUN
cana-2667	193	19	analysis	analysis	NOUN
cana-2667	193	20	•	•	NOUN
cana-2667	193	21	misclassification	misclassification	NOUN
cana-2667	193	22	of	of	ADP
cana-2667	193	23	healthy	healthy	ADJ
cana-2667	193	24	retinal	retinal	ADJ
cana-2667	193	25	images	image	NOUN
cana-2667	193	26	by	by	ADP
cana-2667	193	27	current	current	ADJ
cana-2667	193	28	methods	method	NOUN
cana-2667	193	29	.	.	PUNCT
cana-2667	194	1	•	•	NOUN
cana-2667	194	2	need	need	NOUN
cana-2667	194	3	for	for	ADP
cana-2667	194	4	accurate	accurate	ADJ
cana-2667	194	5	and	and	CCONJ
cana-2667	194	6	timely	timely	ADJ
cana-2667	194	7	diabetic	diabetic	ADJ
cana-2667	194	8	retinopathy	retinopathy	ADJ
cana-2667	194	9	diagnosis	diagnosis	NOUN
cana-2667	194	10	.	.	PUNCT
cana-2667	195	1	communications	communication	NOUN
cana-2667	195	2	on	on	ADP
cana-2667	195	3	applied	apply	VERB
cana-2667	195	4	nonlinear	nonlinear	ADJ
cana-2667	195	5	analysis	analysis	NOUN
cana-2667	195	6	issn	issn	NOUN
cana-2667	195	7	:	:	PUNCT
cana-2667	195	8	1074	1074	NUM
cana-2667	195	9	-	-	PUNCT
cana-2667	195	10	133x	133x	NUM
cana-2667	195	11	vol	vol	NOUN
cana-2667	195	12	32	32	NUM
cana-2667	195	13	no	no	NOUN
cana-2667	195	14	.	.	PUNCT
cana-2667	196	1	3s	3s	NUM
cana-2667	196	2	(	(	PUNCT
cana-2667	196	3	2025	2025	NUM
cana-2667	196	4	)	)	PUNCT
cana-2667	196	5	388	388	NUM
cana-2667	196	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	196	7	pre	pre	ADJ
cana-2667	196	8	-	-	ADJ
cana-2667	196	9	trained	train	VERB
cana-2667	196	10	models	model	NOUN
cana-2667	196	11	and	and	CCONJ
cana-2667	196	12	transfer	transfer	NOUN
cana-2667	196	13	learning	learning	NOUN
cana-2667	196	14	transfer	transfer	NOUN
cana-2667	196	15	learning	learning	NOUN
cana-2667	196	16	,	,	PUNCT
cana-2667	196	17	and	and	CCONJ
cana-2667	196	18	pre	pre	ADJ
cana-2667	196	19	-	-	ADJ
cana-2667	196	20	trained	train	VERB
cana-2667	196	21	models	model	NOUN
cana-2667	196	22	have	have	AUX
cana-2667	196	23	also	also	ADV
cana-2667	196	24	been	be	AUX
cana-2667	196	25	essential	essential	ADJ
cana-2667	196	26	areas	area	NOUN
cana-2667	196	27	of	of	ADP
cana-2667	196	28	research	research	NOUN
cana-2667	196	29	for	for	ADP
cana-2667	196	30	retinopathy	retinopathy	ADJ
cana-2667	196	31	classification	classification	NOUN
cana-2667	196	32	.	.	PUNCT
cana-2667	197	1	transfer	transfer	NOUN
cana-2667	197	2	learning	learning	NOUN
cana-2667	197	3	:	:	PUNCT
cana-2667	197	4	a	a	DET
cana-2667	197	5	method	method	NOUN
cana-2667	197	6	in	in	ADP
cana-2667	197	7	which	which	PRON
cana-2667	197	8	a	a	DET
cana-2667	197	9	model	model	NOUN
cana-2667	197	10	trained	train	VERB
cana-2667	197	11	on	on	ADP
cana-2667	197	12	a	a	DET
cana-2667	197	13	large	large	ADJ
cana-2667	197	14	dataset	dataset	NOUN
cana-2667	197	15	for	for	ADP
cana-2667	197	16	one	one	NUM
cana-2667	197	17	task	task	NOUN
cana-2667	197	18	is	be	AUX
cana-2667	197	19	retuned	retune	VERB
cana-2667	197	20	on	on	ADP
cana-2667	197	21	a	a	DET
cana-2667	197	22	different	different	ADJ
cana-2667	197	23	but	but	CCONJ
cana-2667	197	24	related	related	ADJ
cana-2667	197	25	task	task	NOUN
cana-2667	197	26	.	.	PUNCT
cana-2667	198	1	for	for	ADP
cana-2667	198	2	example	example	NOUN
cana-2667	198	3	,	,	PUNCT
cana-2667	198	4	there	there	PRON
cana-2667	198	5	have	have	AUX
cana-2667	198	6	been	be	AUX
cana-2667	198	7	many	many	ADJ
cana-2667	198	8	studies	study	NOUN
cana-2667	198	9	that	that	PRON
cana-2667	198	10	use	use	VERB
cana-2667	198	11	pre	pre	ADJ
cana-2667	198	12	-	-	ADJ
cana-2667	198	13	trained	train	VERB
cana-2667	198	14	cnns	cnn	NOUN
cana-2667	198	15	(	(	PUNCT
cana-2667	198	16	e.g.	e.g.	ADV
cana-2667	198	17	,	,	PUNCT
cana-2667	198	18	learned	learn	VERB
cana-2667	198	19	from	from	ADP
cana-2667	198	20	large	large	ADJ
cana-2667	198	21	-	-	PUNCT
cana-2667	198	22	scale	scale	NOUN
cana-2667	198	23	image	image	NOUN
cana-2667	198	24	datasets	dataset	NOUN
cana-2667	198	25	such	such	ADJ
cana-2667	198	26	as	as	ADP
cana-2667	198	27	imagenet	imagenet	NOUN
cana-2667	198	28	)	)	PUNCT
cana-2667	198	29	that	that	SCONJ
cana-2667	198	30	fine	fine	ADJ
cana-2667	198	31	-	-	PUNCT
cana-2667	198	32	tune	tune	NOUN
cana-2667	198	33	these	these	DET
cana-2667	198	34	models	model	NOUN
cana-2667	198	35	based	base	VERB
cana-2667	198	36	on	on	ADP
cana-2667	198	37	retinal	retinal	ADJ
cana-2667	198	38	images	image	NOUN
cana-2667	198	39	in	in	ADP
cana-2667	198	40	the	the	DET
cana-2667	198	41	case	case	NOUN
cana-2667	198	42	of	of	ADP
cana-2667	198	43	retinopathy	retinopathy	ADJ
cana-2667	198	44	classification	classification	NOUN
cana-2667	198	45	.	.	PUNCT
cana-2667	199	1	the	the	DET
cana-2667	199	2	main	main	ADJ
cana-2667	199	3	concept	concept	NOUN
cana-2667	199	4	of	of	ADP
cana-2667	199	5	transfer	transfer	NOUN
cana-2667	199	6	learning	learn	VERB
cana-2667	199	7	states	state	NOUN
cana-2667	199	8	that	that	SCONJ
cana-2667	199	9	the	the	DET
cana-2667	199	10	low	low	ADJ
cana-2667	199	11	-	-	PUNCT
cana-2667	199	12	level	level	NOUN
cana-2667	199	13	features	feature	NOUN
cana-2667	199	14	learned	learn	VERB
cana-2667	199	15	by	by	ADP
cana-2667	199	16	cnns	cnn	NOUN
cana-2667	199	17	on	on	ADP
cana-2667	199	18	big	big	ADJ
cana-2667	199	19	datasets	dataset	NOUN
cana-2667	199	20	are	be	AUX
cana-2667	199	21	reusable	reusable	ADJ
cana-2667	199	22	for	for	ADP
cana-2667	199	23	specific	specific	ADJ
cana-2667	199	24	tasks	task	NOUN
cana-2667	199	25	like	like	ADP
cana-2667	199	26	retinopathy	retinopathy	ADJ
cana-2667	199	27	detection	detection	NOUN
cana-2667	199	28	,	,	PUNCT
cana-2667	199	29	and	and	CCONJ
cana-2667	199	30	then	then	ADV
cana-2667	199	31	it	it	PRON
cana-2667	199	32	can	can	AUX
cana-2667	199	33	save	save	VERB
cana-2667	199	34	both	both	DET
cana-2667	199	35	time	time	NOUN
cana-2667	199	36	and	and	CCONJ
cana-2667	199	37	computing	computing	NOUN
cana-2667	199	38	resources	resource	NOUN
cana-2667	199	39	.	.	PUNCT
cana-2667	200	1	transfer	transfer	NOUN
cana-2667	200	2	learning	learning	NOUN
cana-2667	200	3	has	have	AUX
cana-2667	200	4	demonstrated	demonstrate	VERB
cana-2667	200	5	a	a	DET
cana-2667	200	6	useful	useful	ADJ
cana-2667	200	7	method	method	NOUN
cana-2667	200	8	in	in	ADP
cana-2667	200	9	the	the	DET
cana-2667	200	10	domain	domain	NOUN
cana-2667	200	11	of	of	ADP
cana-2667	200	12	medical	medical	ADJ
cana-2667	200	13	image	image	NOUN
cana-2667	200	14	analysis	analysis	NOUN
cana-2667	200	15	,	,	PUNCT
cana-2667	200	16	where	where	SCONJ
cana-2667	200	17	labeled	label	VERB
cana-2667	200	18	data	datum	NOUN
cana-2667	200	19	may	may	AUX
cana-2667	200	20	not	not	PART
cana-2667	200	21	always	always	ADV
cana-2667	200	22	be	be	AUX
cana-2667	200	23	readily	readily	ADV
cana-2667	200	24	available	available	ADJ
cana-2667	200	25	.	.	PUNCT
cana-2667	201	1	utilising	utilise	VERB
cana-2667	201	2	pre	pre	ADJ
cana-2667	201	3	-	-	ADJ
cana-2667	201	4	trained	train	VERB
cana-2667	201	5	models	model	NOUN
cana-2667	201	6	comes	come	VERB
cana-2667	201	7	out	out	ADP
cana-2667	201	8	as	as	ADP
cana-2667	201	9	a	a	DET
cana-2667	201	10	key	key	ADJ
cana-2667	201	11	domain	domain	NOUN
cana-2667	201	12	for	for	ADP
cana-2667	201	13	researchers	researcher	NOUN
cana-2667	201	14	with	with	ADP
cana-2667	201	15	potential	potential	NOUN
cana-2667	201	16	to	to	PART
cana-2667	201	17	alleviate	alleviate	VERB
cana-2667	201	18	the	the	DET
cana-2667	201	19	need	need	NOUN
cana-2667	201	20	for	for	ADP
cana-2667	201	21	very	very	ADV
cana-2667	201	22	large	large	ADJ
cana-2667	201	23	annotated	annotated	ADJ
cana-2667	201	24	datasets	dataset	NOUN
cana-2667	201	25	without	without	ADP
cana-2667	201	26	arbitrarily	arbitrarily	ADV
cana-2667	201	27	sacrificing	sacrifice	VERB
cana-2667	201	28	classification	classification	NOUN
cana-2667	201	29	performance	performance	NOUN
cana-2667	201	30	.	.	PUNCT
cana-2667	202	1	additionally	additionally	ADV
cana-2667	202	2	,	,	PUNCT
cana-2667	202	3	transfer	transfer	NOUN
cana-2667	202	4	learning	learning	NOUN
cana-2667	202	5	has	have	AUX
cana-2667	202	6	been	be	AUX
cana-2667	202	7	proven	prove	VERB
cana-2667	202	8	to	to	PART
cana-2667	202	9	enhance	enhance	VERB
cana-2667	202	10	model	model	NOUN
cana-2667	202	11	generalization	generalization	NOUN
cana-2667	202	12	,	,	PUNCT
cana-2667	202	13	as	as	SCONJ
cana-2667	202	14	pre	pre	ADJ
cana-2667	202	15	-	-	ADJ
cana-2667	202	16	trained	train	VERB
cana-2667	202	17	models	model	NOUN
cana-2667	202	18	are	be	AUX
cana-2667	202	19	often	often	ADV
cana-2667	202	20	more	more	ADV
cana-2667	202	21	resilient	resilient	ADJ
cana-2667	202	22	to	to	ADP
cana-2667	202	23	changes	change	NOUN
cana-2667	202	24	in	in	ADP
cana-2667	202	25	data	datum	NOUN
cana-2667	202	26	.	.	PUNCT
cana-2667	203	1	this	this	DET
cana-2667	203	2	strategy	strategy	NOUN
cana-2667	203	3	has	have	AUX
cana-2667	203	4	been	be	AUX
cana-2667	203	5	popular	popular	ADJ
cana-2667	203	6	in	in	ADP
cana-2667	203	7	classifying	classify	VERB
cana-2667	203	8	retinopathy	retinopathy	NOUN
cana-2667	203	9	,	,	PUNCT
cana-2667	203	10	where	where	SCONJ
cana-2667	203	11	pre	pre	ADJ
cana-2667	203	12	-	-	ADJ
cana-2667	203	13	trained	train	VERB
cana-2667	203	14	cnns	cnn	NOUN
cana-2667	203	15	,	,	PUNCT
cana-2667	203	16	like	like	ADP
cana-2667	203	17	vggnet	vggnet	NOUN
cana-2667	203	18	,	,	PUNCT
cana-2667	203	19	resnet	resnet	NOUN
cana-2667	203	20	and	and	CCONJ
cana-2667	203	21	inception	inception	NOUN
cana-2667	203	22	,	,	PUNCT
cana-2667	203	23	have	have	AUX
cana-2667	203	24	each	each	PRON
cana-2667	203	25	been	be	AUX
cana-2667	203	26	fine	fine	ADV
cana-2667	203	27	-	-	PUNCT
cana-2667	203	28	tuned	tune	VERB
cana-2667	203	29	for	for	ADP
cana-2667	203	30	retinopathy	retinopathy	ADJ
cana-2667	203	31	classification	classification	NOUN
cana-2667	203	32	.	.	PUNCT
cana-2667	204	1	however	however	ADV
cana-2667	204	2	,	,	PUNCT
cana-2667	204	3	with	with	ADP
cana-2667	204	4	transfer	transfer	NOUN
cana-2667	204	5	learning	learn	VERB
cana-2667	204	6	being	be	AUX
cana-2667	204	7	clear	clear	ADJ
cana-2667	204	8	,	,	PUNCT
cana-2667	204	9	it	it	PRON
cana-2667	204	10	is	be	AUX
cana-2667	204	11	not	not	PART
cana-2667	204	12	without	without	ADP
cana-2667	204	13	its	its	PRON
cana-2667	204	14	challenges	challenge	NOUN
cana-2667	204	15	.	.	PUNCT
cana-2667	205	1	because	because	SCONJ
cana-2667	205	2	fine	fine	ADV
cana-2667	205	3	-	-	PUNCT
cana-2667	205	4	tuning	tune	VERB
cana-2667	205	5	pretrained	pretraine	VERB
cana-2667	205	6	models	model	NOUN
cana-2667	205	7	on	on	ADP
cana-2667	205	8	a	a	DET
cana-2667	205	9	smaller	small	ADJ
cana-2667	205	10	dataset	dataset	NOUN
cana-2667	205	11	can	can	AUX
cana-2667	205	12	occasionally	occasionally	ADV
cana-2667	205	13	lead	lead	VERB
cana-2667	205	14	to	to	ADP
cana-2667	205	15	overfitting	overfitte	VERB
cana-2667	205	16	,	,	PUNCT
cana-2667	205	17	particularly	particularly	ADV
cana-2667	205	18	if	if	SCONJ
cana-2667	205	19	the	the	DET
cana-2667	205	20	new	new	ADJ
cana-2667	205	21	task	task	NOUN
cana-2667	205	22	is	be	AUX
cana-2667	205	23	very	very	ADV
cana-2667	205	24	different	different	ADJ
cana-2667	205	25	from	from	ADP
cana-2667	205	26	the	the	DET
cana-2667	205	27	original	original	ADJ
cana-2667	205	28	task	task	NOUN
cana-2667	205	29	.	.	PUNCT
cana-2667	206	1	the	the	DET
cana-2667	206	2	pre	pre	ADJ
cana-2667	206	3	-	-	ADJ
cana-2667	206	4	trained	train	VERB
cana-2667	206	5	model	model	NOUN
cana-2667	206	6	obtained	obtain	VERB
cana-2667	206	7	must	must	AUX
cana-2667	206	8	also	also	ADV
cana-2667	206	9	be	be	AUX
cana-2667	206	10	fine	fine	ADV
cana-2667	206	11	-	-	PUNCT
cana-2667	206	12	tuned	tune	VERB
cana-2667	206	13	optimally	optimally	ADV
cana-2667	206	14	,	,	PUNCT
cana-2667	206	15	so	so	SCONJ
cana-2667	206	16	as	as	SCONJ
cana-2667	206	17	to	to	PART
cana-2667	206	18	transfer	transfer	VERB
cana-2667	206	19	the	the	DET
cana-2667	206	20	knowledge	knowledge	NOUN
cana-2667	206	21	learnt	learn	VERB
cana-2667	206	22	from	from	ADP
cana-2667	206	23	the	the	DET
cana-2667	206	24	pre	pre	ADJ
cana-2667	206	25	-	-	ADJ
cana-2667	206	26	trained	train	VERB
cana-2667	206	27	model	model	NOUN
cana-2667	206	28	to	to	ADP
cana-2667	206	29	the	the	DET
cana-2667	206	30	retinopathy	retinopathy	ADJ
cana-2667	206	31	classification	classification	NOUN
cana-2667	206	32	task	task	NOUN
cana-2667	206	33	.	.	PUNCT
cana-2667	207	1	data	datum	NOUN
cana-2667	207	2	augmentation	augmentation	NOUN
cana-2667	207	3	&	&	CCONJ
cana-2667	207	4	synthetic	synthetic	ADJ
cana-2667	207	5	data	datum	NOUN
cana-2667	207	6	generation	generation	NOUN
cana-2667	207	7	another	another	DET
cana-2667	207	8	major	major	ADJ
cana-2667	207	9	challenge	challenge	NOUN
cana-2667	207	10	in	in	ADP
cana-2667	207	11	retinopathy	retinopathy	ADJ
cana-2667	207	12	classification	classification	NOUN
cana-2667	207	13	is	be	AUX
cana-2667	207	14	limited	limit	VERB
cana-2667	207	15	availability	availability	NOUN
cana-2667	207	16	of	of	ADP
cana-2667	207	17	labeled	label	VERB
cana-2667	207	18	datasets	dataset	NOUN
cana-2667	207	19	with	with	ADP
cana-2667	207	20	high	high	ADJ
cana-2667	207	21	quality	quality	NOUN
cana-2667	207	22	.	.	PUNCT
cana-2667	208	1	as	as	SCONJ
cana-2667	208	2	mentioned	mention	VERB
cana-2667	208	3	above	above	ADV
cana-2667	208	4	,	,	PUNCT
cana-2667	208	5	medical	medical	ADJ
cana-2667	208	6	image	image	NOUN
cana-2667	208	7	annotations	annotation	NOUN
cana-2667	208	8	require	require	VERB
cana-2667	208	9	the	the	DET
cana-2667	208	10	knowledge	knowledge	NOUN
cana-2667	208	11	of	of	ADP
cana-2667	208	12	an	an	DET
cana-2667	208	13	ophthalmology	ophthalmology	NOUN
cana-2667	208	14	,	,	PUNCT
cana-2667	208	15	which	which	PRON
cana-2667	208	16	is	be	AUX
cana-2667	208	17	costly	costly	ADJ
cana-2667	208	18	and	and	CCONJ
cana-2667	208	19	time	time	NOUN
cana-2667	208	20	-	-	PUNCT
cana-2667	208	21	consuming	consume	VERB
cana-2667	208	22	.	.	PUNCT
cana-2667	209	1	in	in	ADP
cana-2667	209	2	order	order	NOUN
cana-2667	209	3	to	to	PART
cana-2667	209	4	overcome	overcome	VERB
cana-2667	209	5	this	this	DET
cana-2667	209	6	challenge	challenge	NOUN
cana-2667	209	7	,	,	PUNCT
cana-2667	209	8	a	a	DET
cana-2667	209	9	lot	lot	NOUN
cana-2667	209	10	of	of	ADP
cana-2667	209	11	researchers	researcher	NOUN
cana-2667	209	12	adopted	adopt	VERB
cana-2667	209	13	data	datum	NOUN
cana-2667	209	14	augmentation	augmentation	NOUN
cana-2667	209	15	methods	method	NOUN
cana-2667	209	16	that	that	PRON
cana-2667	209	17	allow	allow	VERB
cana-2667	209	18	them	they	PRON
cana-2667	209	19	to	to	PART
cana-2667	209	20	grow	grow	VERB
cana-2667	209	21	their	their	PRON
cana-2667	209	22	datasets	dataset	NOUN
cana-2667	209	23	artificially	artificially	ADV
cana-2667	209	24	.	.	PUNCT
cana-2667	210	1	data	datum	NOUN
cana-2667	210	2	augmentation	augmentation	NOUN
cana-2667	210	3	creates	create	VERB
cana-2667	210	4	new	new	ADJ
cana-2667	210	5	training	training	NOUN
cana-2667	210	6	samples	sample	NOUN
cana-2667	210	7	by	by	ADP
cana-2667	210	8	applying	apply	VERB
cana-2667	210	9	different	different	ADJ
cana-2667	210	10	image	image	NOUN
cana-2667	210	11	transformations	transformation	NOUN
cana-2667	210	12	to	to	ADP
cana-2667	210	13	existing	exist	VERB
cana-2667	210	14	images	image	NOUN
cana-2667	210	15	(	(	PUNCT
cana-2667	210	16	rotations	rotation	NOUN
cana-2667	210	17	,	,	PUNCT
cana-2667	210	18	translations	translation	NOUN
cana-2667	210	19	,	,	PUNCT
cana-2667	210	20	flips	flip	NOUN
cana-2667	210	21	,	,	PUNCT
cana-2667	210	22	scaling	scaling	NOUN
cana-2667	210	23	,	,	PUNCT
cana-2667	210	24	etc	etc	X
cana-2667	210	25	.	.	X
cana-2667	210	26	)	)	PUNCT
cana-2667	210	27	.	.	PUNCT
cana-2667	211	1	these	these	DET
cana-2667	211	2	techniques	technique	NOUN
cana-2667	211	3	can	can	AUX
cana-2667	211	4	enhance	enhance	VERB
cana-2667	211	5	the	the	DET
cana-2667	211	6	robustness	robustness	NOUN
cana-2667	211	7	of	of	ADP
cana-2667	211	8	deep	deep	ADJ
cana-2667	211	9	learning	learning	NOUN
cana-2667	211	10	models	model	NOUN
cana-2667	211	11	by	by	ADP
cana-2667	211	12	generating	generate	VERB
cana-2667	211	13	more	more	ADV
cana-2667	211	14	diverse	diverse	ADJ
cana-2667	211	15	training	training	NOUN
cana-2667	211	16	data	datum	NOUN
cana-2667	211	17	and	and	CCONJ
cana-2667	211	18	lowering	lower	VERB
cana-2667	211	19	overfitting[25	overfitting[25	PRON
cana-2667	211	20	]	]	PUNCT
cana-2667	211	21	.	.	PUNCT
cana-2667	212	1	researchers	researcher	NOUN
cana-2667	212	2	have	have	AUX
cana-2667	212	3	explored	explore	VERB
cana-2667	212	4	traditional	traditional	ADJ
cana-2667	212	5	data	datum	NOUN
cana-2667	212	6	augmentation	augmentation	NOUN
cana-2667	212	7	methods	method	NOUN
cana-2667	212	8	and	and	CCONJ
cana-2667	212	9	the	the	DET
cana-2667	212	10	use	use	NOUN
cana-2667	212	11	of	of	ADP
cana-2667	212	12	synthetic	synthetic	ADJ
cana-2667	212	13	data	data	NOUN
cana-2667	212	14	generation	generation	NOUN
cana-2667	212	15	techniques	technique	NOUN
cana-2667	212	16	,	,	PUNCT
cana-2667	212	17	such	such	ADJ
cana-2667	212	18	as	as	ADP
cana-2667	212	19	generative	generative	ADJ
cana-2667	212	20	adversarial	adversarial	ADJ
cana-2667	212	21	networks	network	NOUN
cana-2667	212	22	(	(	PUNCT
cana-2667	212	23	gans	gan	NOUN
cana-2667	212	24	)	)	PUNCT
cana-2667	212	25	,	,	PUNCT
cana-2667	212	26	to	to	PART
cana-2667	212	27	generate	generate	VERB
cana-2667	212	28	realistic	realistic	ADJ
cana-2667	212	29	retinal	retinal	ADJ
cana-2667	212	30	images	image	NOUN
cana-2667	212	31	for	for	ADP
cana-2667	212	32	training	training	NOUN
cana-2667	212	33	.	.	PUNCT
cana-2667	213	1	generative	generative	ADJ
cana-2667	213	2	adversarial	adversarial	ADJ
cana-2667	213	3	networks	network	NOUN
cana-2667	213	4	,	,	PUNCT
cana-2667	213	5	or	or	CCONJ
cana-2667	213	6	gans	gan	NOUN
cana-2667	213	7	,	,	PUNCT
cana-2667	213	8	are	be	AUX
cana-2667	213	9	a	a	DET
cana-2667	213	10	specific	specific	ADJ
cana-2667	213	11	subset	subset	NOUN
cana-2667	213	12	of	of	ADP
cana-2667	213	13	deep	deep	ADJ
cana-2667	213	14	learning	learning	NOUN
cana-2667	213	15	models	model	NOUN
cana-2667	213	16	that	that	PRON
cana-2667	213	17	are	be	AUX
cana-2667	213	18	composed	compose	VERB
cana-2667	213	19	of	of	ADP
cana-2667	213	20	two	two	NUM
cana-2667	213	21	networks	network	NOUN
cana-2667	213	22	:	:	PUNCT
cana-2667	213	23	the	the	DET
cana-2667	213	24	generator	generator	NOUN
cana-2667	213	25	,	,	PUNCT
cana-2667	213	26	which	which	PRON
cana-2667	213	27	is	be	AUX
cana-2667	213	28	responsible	responsible	ADJ
cana-2667	213	29	for	for	ADP
cana-2667	213	30	generating	generate	VERB
cana-2667	213	31	new	new	ADJ
cana-2667	213	32	data	datum	NOUN
cana-2667	213	33	samples	sample	NOUN
cana-2667	213	34	,	,	PUNCT
cana-2667	213	35	and	and	CCONJ
cana-2667	213	36	the	the	DET
cana-2667	213	37	discriminator	discriminator	NOUN
cana-2667	213	38	,	,	PUNCT
cana-2667	213	39	which	which	PRON
cana-2667	213	40	is	be	AUX
cana-2667	213	41	responsible	responsible	ADJ
cana-2667	213	42	for	for	ADP
cana-2667	213	43	determining	determine	VERB
cana-2667	213	44	whether	whether	SCONJ
cana-2667	213	45	the	the	DET
cana-2667	213	46	generated	generate	VERB
cana-2667	213	47	sample	sample	NOUN
cana-2667	213	48	is	be	AUX
cana-2667	213	49	real	real	ADJ
cana-2667	213	50	.	.	PUNCT
cana-2667	214	1	generative	generative	ADJ
cana-2667	214	2	adversarial	adversarial	ADJ
cana-2667	214	3	networks	network	NOUN
cana-2667	214	4	(	(	PUNCT
cana-2667	214	5	gans	gan	NOUN
cana-2667	214	6	)	)	PUNCT
cana-2667	214	7	are	be	AUX
cana-2667	214	8	a	a	DET
cana-2667	214	9	class	class	NOUN
cana-2667	214	10	of	of	ADP
cana-2667	214	11	algorithms	algorithm	NOUN
cana-2667	214	12	that	that	PRON
cana-2667	214	13	can	can	AUX
cana-2667	214	14	produce	produce	VERB
cana-2667	214	15	realistic	realistic	ADJ
cana-2667	214	16	synthetic	synthetic	ADJ
cana-2667	214	17	images	image	NOUN
cana-2667	214	18	that	that	PRON
cana-2667	214	19	emulate	emulate	VERB
cana-2667	214	20	existing	exist	VERB
cana-2667	214	21	real	real	ADJ
cana-2667	214	22	images	image	NOUN
cana-2667	214	23	,	,	PUNCT
cana-2667	214	24	a	a	DET
cana-2667	214	25	fact	fact	NOUN
cana-2667	214	26	that	that	SCONJ
cana-2667	214	27	allows	allow	VERB
cana-2667	214	28	researchers	researcher	NOUN
cana-2667	214	29	to	to	PART
cana-2667	214	30	construct	construct	VERB
cana-2667	214	31	vast	vast	ADJ
cana-2667	214	32	synthetic	synthetic	ADJ
cana-2667	214	33	retinal	retinal	ADJ
cana-2667	214	34	datasets	dataset	NOUN
cana-2667	214	35	to	to	PART
cana-2667	214	36	train	train	VERB
cana-2667	214	37	deep	deep	ADJ
cana-2667	214	38	learning	learning	NOUN
cana-2667	214	39	models	model	NOUN
cana-2667	214	40	.	.	PUNCT
cana-2667	215	1	data	datum	NOUN
cana-2667	215	2	augmentation	augmentation	NOUN
cana-2667	215	3	and	and	CCONJ
cana-2667	215	4	synthetic	synthetic	ADJ
cana-2667	215	5	data	data	NOUN
cana-2667	215	6	generation	generation	NOUN
cana-2667	215	7	have	have	AUX
cana-2667	215	8	demonstrated	demonstrate	VERB
cana-2667	215	9	improvements	improvement	NOUN
cana-2667	215	10	in	in	ADP
cana-2667	215	11	the	the	DET
cana-2667	215	12	performance	performance	NOUN
cana-2667	215	13	of	of	ADP
cana-2667	215	14	such	such	ADJ
cana-2667	215	15	retinopathy	retinopathy	ADJ
cana-2667	215	16	classification	classification	NOUN
cana-2667	215	17	models	model	NOUN
cana-2667	215	18	,	,	PUNCT
cana-2667	215	19	yet	yet	CCONJ
cana-2667	215	20	these	these	DET
cana-2667	215	21	methods	method	NOUN
cana-2667	215	22	have	have	VERB
cana-2667	215	23	limitations	limitation	NOUN
cana-2667	215	24	.	.	PUNCT
cana-2667	216	1	this	this	PRON
cana-2667	216	2	will	will	AUX
cana-2667	216	3	lead	lead	VERB
cana-2667	216	4	to	to	ADP
cana-2667	216	5	wrong	wrong	ADJ
cana-2667	216	6	projections	projection	NOUN
cana-2667	216	7	and	and	CCONJ
cana-2667	216	8	wrong	wrong	ADJ
cana-2667	216	9	decisions	decision	NOUN
cana-2667	216	10	.	.	PUNCT
cana-2667	217	1	for	for	ADP
cana-2667	217	2	example	example	NOUN
cana-2667	217	3	,	,	PUNCT
cana-2667	217	4	although	although	SCONJ
cana-2667	217	5	gans	gan	NOUN
cana-2667	217	6	are	be	AUX
cana-2667	217	7	capable	capable	ADJ
cana-2667	217	8	of	of	ADP
cana-2667	217	9	generating	generate	VERB
cana-2667	217	10	very	very	ADV
cana-2667	217	11	realistic	realistic	ADJ
cana-2667	217	12	images	image	NOUN
cana-2667	217	13	,	,	PUNCT
cana-2667	217	14	it	it	PRON
cana-2667	217	15	is	be	AUX
cana-2667	217	16	likely	likely	ADJ
cana-2667	217	17	that	that	SCONJ
cana-2667	217	18	generated	generate	VERB
cana-2667	217	19	data	datum	NOUN
cana-2667	217	20	will	will	AUX
cana-2667	217	21	not	not	PART
cana-2667	217	22	encompass	encompass	VERB
cana-2667	217	23	the	the	DET
cana-2667	217	24	total	total	ADJ
cana-2667	217	25	diversity	diversity	NOUN
cana-2667	217	26	of	of	ADP
cana-2667	217	27	retina	retina	NOUN
cana-2667	217	28	images	image	NOUN
cana-2667	217	29	.	.	PUNCT
cana-2667	218	1	communications	communication	NOUN
cana-2667	218	2	on	on	ADP
cana-2667	218	3	applied	apply	VERB
cana-2667	218	4	nonlinear	nonlinear	ADJ
cana-2667	218	5	analysis	analysis	NOUN
cana-2667	218	6	issn	issn	NOUN
cana-2667	218	7	:	:	PUNCT
cana-2667	218	8	1074	1074	NUM
cana-2667	218	9	-	-	PUNCT
cana-2667	218	10	133x	133x	NUM
cana-2667	218	11	vol	vol	NOUN
cana-2667	218	12	32	32	NUM
cana-2667	218	13	no	no	NOUN
cana-2667	218	14	.	.	PUNCT
cana-2667	219	1	3s	3s	NUM
cana-2667	219	2	(	(	PUNCT
cana-2667	219	3	2025	2025	NUM
cana-2667	219	4	)	)	PUNCT
cana-2667	219	5	389	389	NUM
cana-2667	219	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	219	7	future	future	ADJ
cana-2667	219	8	challenges	challenge	NOUN
cana-2667	219	9	and	and	CCONJ
cana-2667	219	10	directions	direction	NOUN
cana-2667	219	11	though	though	SCONJ
cana-2667	219	12	there	there	PRON
cana-2667	219	13	have	have	AUX
cana-2667	219	14	been	be	AUX
cana-2667	219	15	significant	significant	ADJ
cana-2667	219	16	strides	stride	NOUN
cana-2667	219	17	made	make	VERB
cana-2667	219	18	in	in	ADP
cana-2667	219	19	the	the	DET
cana-2667	219	20	automated	automate	VERB
cana-2667	219	21	classification	classification	NOUN
cana-2667	219	22	of	of	ADP
cana-2667	219	23	retinopathy	retinopathy	ADJ
cana-2667	219	24	,	,	PUNCT
cana-2667	219	25	many	many	ADJ
cana-2667	219	26	challenges	challenge	NOUN
cana-2667	219	27	remain	remain	VERB
cana-2667	219	28	.	.	PUNCT
cana-2667	220	1	a	a	DET
cana-2667	220	2	key	key	ADJ
cana-2667	220	3	problem	problem	NOUN
cana-2667	220	4	is	be	AUX
cana-2667	220	5	the	the	DET
cana-2667	220	6	scarcity	scarcity	NOUN
cana-2667	220	7	of	of	ADP
cana-2667	220	8	large	large	ADJ
cana-2667	220	9	-	-	PUNCT
cana-2667	220	10	scale	scale	NOUN
cana-2667	220	11	,	,	PUNCT
cana-2667	220	12	high	high	ADJ
cana-2667	220	13	-	-	PUNCT
cana-2667	220	14	quality	quality	NOUN
cana-2667	220	15	annotated	annotate	VERB
cana-2667	220	16	datasets	dataset	NOUN
cana-2667	220	17	,	,	PUNCT
cana-2667	220	18	which	which	PRON
cana-2667	220	19	places	place	VERB
cana-2667	220	20	restrictions	restriction	NOUN
cana-2667	220	21	on	on	ADP
cana-2667	220	22	the	the	DET
cana-2667	220	23	development	development	NOUN
cana-2667	220	24	and	and	CCONJ
cana-2667	220	25	generalization	generalization	NOUN
cana-2667	220	26	of	of	ADP
cana-2667	220	27	a	a	DET
cana-2667	220	28	multitude	multitude	NOUN
cana-2667	220	29	of	of	ADP
cana-2667	220	30	models	model	NOUN
cana-2667	220	31	.	.	PUNCT
cana-2667	221	1	although	although	SCONJ
cana-2667	221	2	these	these	DET
cana-2667	221	3	problems	problem	NOUN
cana-2667	221	4	may	may	AUX
cana-2667	221	5	somewhat	somewhat	ADV
cana-2667	221	6	be	be	AUX
cana-2667	221	7	mitigated	mitigate	VERB
cana-2667	221	8	by	by	ADP
cana-2667	221	9	transfer	transfer	NOUN
cana-2667	221	10	learning	learning	NOUN
cana-2667	221	11	and	and	CCONJ
cana-2667	221	12	data	datum	NOUN
cana-2667	221	13	augmentation	augmentation	NOUN
cana-2667	221	14	techniques	technique	NOUN
cana-2667	221	15	,	,	PUNCT
cana-2667	221	16	a	a	DET
cana-2667	221	17	lack	lack	NOUN
cana-2667	221	18	of	of	ADP
cana-2667	221	19	annotated	annotate	VERB
cana-2667	221	20	medical	medical	ADJ
cana-2667	221	21	data	datum	NOUN
cana-2667	221	22	still	still	ADV
cana-2667	221	23	represents	represent	VERB
cana-2667	221	24	a	a	DET
cana-2667	221	25	significant	significant	ADJ
cana-2667	221	26	roadblock	roadblock	NOUN
cana-2667	221	27	.	.	PUNCT
cana-2667	222	1	challenges	challenge	NOUN
cana-2667	222	2	to	to	PART
cana-2667	222	3	consider	consider	VERB
cana-2667	222	4	:	:	PUNCT
cana-2667	222	5	need	need	VERB
cana-2667	222	6	for	for	ADP
cana-2667	222	7	models	model	NOUN
cana-2667	222	8	that	that	PRON
cana-2667	222	9	classify	classify	VERB
cana-2667	222	10	retinopathy	retinopathy	ADJ
cana-2667	222	11	and	and	CCONJ
cana-2667	222	12	predict	predict	VERB
cana-2667	222	13	disease	disease	NOUN
cana-2667	222	14	progression	progression	NOUN
cana-2667	222	15	and	and	CCONJ
cana-2667	222	16	severity	severity	NOUN
cana-2667	222	17	.	.	PUNCT
cana-2667	223	1	currently	currently	ADV
cana-2667	223	2	,	,	PUNCT
cana-2667	223	3	most	most	ADJ
cana-2667	223	4	models	model	NOUN
cana-2667	223	5	apply	apply	VERB
cana-2667	223	6	to	to	ADP
cana-2667	223	7	binary	binary	ADJ
cana-2667	223	8	classification	classification	NOUN
cana-2667	223	9	(	(	PUNCT
cana-2667	223	10	i.e.	i.e.	X
cana-2667	223	11	,	,	PUNCT
cana-2667	223	12	healthy	healthy	ADJ
cana-2667	223	13	and	and	CCONJ
cana-2667	223	14	affected	affected	ADJ
cana-2667	223	15	)	)	PUNCT
cana-2667	223	16	;	;	PUNCT
cana-2667	223	17	however	however	ADV
cana-2667	223	18	,	,	PUNCT
cana-2667	223	19	the	the	DET
cana-2667	223	20	ability	ability	NOUN
cana-2667	223	21	to	to	PART
cana-2667	223	22	classify	classify	VERB
cana-2667	223	23	retinopathy	retinopathy	ADJ
cana-2667	223	24	grades	grade	NOUN
cana-2667	223	25	or	or	CCONJ
cana-2667	223	26	predict	predict	VERB
cana-2667	223	27	progression	progression	NOUN
cana-2667	223	28	risks	risk	NOUN
cana-2667	223	29	is	be	AUX
cana-2667	223	30	of	of	ADP
cana-2667	223	31	great	great	ADJ
cana-2667	223	32	help	help	NOUN
cana-2667	223	33	to	to	ADP
cana-2667	223	34	clinicians	clinician	NOUN
cana-2667	223	35	in	in	ADP
cana-2667	223	36	managing	manage	VERB
cana-2667	223	37	the	the	DET
cana-2667	223	38	disease	disease	NOUN
cana-2667	223	39	.	.	PUNCT
cana-2667	224	1	furthermore	furthermore	ADV
cana-2667	224	2	,	,	PUNCT
cana-2667	224	3	interpretability	interpretability	NOUN
cana-2667	224	4	is	be	AUX
cana-2667	224	5	a	a	DET
cana-2667	224	6	significant	significant	ADJ
cana-2667	224	7	concern	concern	NOUN
cana-2667	224	8	for	for	ADP
cana-2667	224	9	deploying	deploy	VERB
cana-2667	224	10	machine	machine	NOUN
cana-2667	224	11	learning	learning	NOUN
cana-2667	224	12	models	model	NOUN
cana-2667	224	13	in	in	ADP
cana-2667	224	14	clinical	clinical	ADJ
cana-2667	224	15	environments	environment	NOUN
cana-2667	224	16	.	.	PUNCT
cana-2667	225	1	deep	deep	ADJ
cana-2667	225	2	learning	learning	NOUN
cana-2667	225	3	models	model	NOUN
cana-2667	225	4	,	,	PUNCT
cana-2667	225	5	particularly	particularly	ADV
cana-2667	225	6	convolutional	convolutional	ADJ
cana-2667	225	7	neural	neural	ADJ
cana-2667	225	8	networks	network	NOUN
cana-2667	225	9	(	(	PUNCT
cana-2667	225	10	cnns	cnns	PROPN
cana-2667	225	11	)	)	PUNCT
cana-2667	225	12	,	,	PUNCT
cana-2667	225	13	can	can	AUX
cana-2667	225	14	well	well	ADV
cana-2667	225	15	classify	classify	VERB
cana-2667	225	16	images	image	NOUN
cana-2667	225	17	(	(	PUNCT
cana-2667	225	18	retinopathies	retinopathy	NOUN
cana-2667	225	19	)	)	PUNCT
cana-2667	225	20	with	with	ADP
cana-2667	225	21	a	a	DET
cana-2667	225	22	high	high	ADJ
cana-2667	225	23	level	level	NOUN
cana-2667	225	24	of	of	ADP
cana-2667	225	25	accuracy	accuracy	NOUN
cana-2667	225	26	.	.	PUNCT
cana-2667	226	1	interpretability	interpretability	NOUN
cana-2667	226	2	is	be	AUX
cana-2667	226	3	critical	critical	ADJ
cana-2667	226	4	in	in	ADP
cana-2667	226	5	medical	medical	ADJ
cana-2667	226	6	contexts	contexts	NOUN
cana-2667	226	7	,	,	PUNCT
cana-2667	226	8	as	as	SCONJ
cana-2667	226	9	clinicians	clinician	NOUN
cana-2667	226	10	must	must	AUX
cana-2667	226	11	know	know	VERB
cana-2667	226	12	the	the	DET
cana-2667	226	13	rationale	rationale	NOUN
cana-2667	226	14	underpinning	underpin	VERB
cana-2667	226	15	a	a	DET
cana-2667	226	16	model	model	NOUN
cana-2667	226	17	’s	’s	PART
cana-2667	226	18	prediction	prediction	NOUN
cana-2667	226	19	to	to	PART
cana-2667	226	20	trust	trust	VERB
cana-2667	226	21	and	and	CCONJ
cana-2667	226	22	act	act	VERB
cana-2667	226	23	on	on	ADP
cana-2667	226	24	its	its	PRON
cana-2667	226	25	output	output	NOUN
cana-2667	226	26	.	.	PUNCT
cana-2667	227	1	lastly	lastly	ADV
cana-2667	227	2	,	,	PUNCT
cana-2667	227	3	several	several	ADJ
cana-2667	227	4	logistical	logistical	ADJ
cana-2667	227	5	and	and	CCONJ
cana-2667	227	6	regulatory	regulatory	ADJ
cana-2667	227	7	challenges	challenge	NOUN
cana-2667	227	8	for	for	ADP
cana-2667	227	9	the	the	DET
cana-2667	227	10	implementation	implementation	NOUN
cana-2667	227	11	of	of	ADP
cana-2667	227	12	automated	automate	VERB
cana-2667	227	13	retinopathy	retinopathy	ADJ
cana-2667	227	14	classification	classification	NOUN
cana-2667	227	15	systems	system	NOUN
cana-2667	227	16	into	into	ADP
cana-2667	227	17	clinical	clinical	ADJ
cana-2667	227	18	practice	practice	NOUN
cana-2667	227	19	remain	remain	VERB
cana-2667	227	20	to	to	PART
cana-2667	227	21	be	be	AUX
cana-2667	227	22	overcome	overcome	VERB
cana-2667	227	23	.	.	PUNCT
cana-2667	228	1	therefore	therefore	ADV
cana-2667	228	2	,	,	PUNCT
cana-2667	228	3	these	these	DET
cana-2667	228	4	systems	system	NOUN
cana-2667	228	5	need	need	VERB
cana-2667	228	6	to	to	PART
cana-2667	228	7	be	be	AUX
cana-2667	228	8	thoroughly	thoroughly	ADV
cana-2667	228	9	tested	test	VERB
cana-2667	228	10	and	and	CCONJ
cana-2667	228	11	validated	validate	VERB
cana-2667	228	12	on	on	ADP
cana-2667	228	13	a	a	DET
cana-2667	228	14	range	range	NOUN
cana-2667	228	15	of	of	ADP
cana-2667	228	16	datasets	dataset	NOUN
cana-2667	228	17	prior	prior	ADV
cana-2667	228	18	to	to	ADP
cana-2667	228	19	them	they	PRON
cana-2667	228	20	being	be	AUX
cana-2667	228	21	widely	widely	ADV
cana-2667	228	22	implemented	implement	VERB
cana-2667	228	23	,	,	PUNCT
cana-2667	228	24	as	as	ADV
cana-2667	228	25	well	well	ADV
cana-2667	228	26	as	as	ADP
cana-2667	228	27	adhering	adhere	VERB
cana-2667	228	28	to	to	ADP
cana-2667	228	29	medical	medical	ADJ
cana-2667	228	30	regulations	regulation	NOUN
cana-2667	228	31	and	and	CCONJ
cana-2667	228	32	standards	standard	NOUN
cana-2667	228	33	to	to	PART
cana-2667	228	34	maintain	maintain	VERB
cana-2667	228	35	patient	patient	ADJ
cana-2667	228	36	safety	safety	NOUN
cana-2667	228	37	and	and	CCONJ
cana-2667	228	38	privacy	privacy	NOUN
cana-2667	228	39	.	.	PUNCT
cana-2667	229	1	to	to	PART
cana-2667	229	2	conclude	conclude	VERB
cana-2667	229	3	,	,	PUNCT
cana-2667	229	4	much	much	ADJ
cana-2667	229	5	has	have	AUX
cana-2667	229	6	been	be	AUX
cana-2667	229	7	achieved	achieve	VERB
cana-2667	229	8	towards	towards	ADP
cana-2667	229	9	automated	automate	VERB
cana-2667	229	10	classification	classification	NOUN
cana-2667	229	11	systems	system	NOUN
cana-2667	229	12	for	for	ADP
cana-2667	229	13	retinopathy	retinopathy	NOUN
cana-2667	229	14	,	,	PUNCT
cana-2667	229	15	but	but	CCONJ
cana-2667	229	16	many	many	ADJ
cana-2667	229	17	problems	problem	NOUN
cana-2667	229	18	persist	persist	VERB
cana-2667	229	19	.	.	PUNCT
cana-2667	230	1	overcoming	overcome	VERB
cana-2667	230	2	those	those	DET
cana-2667	230	3	obstacles	obstacle	NOUN
cana-2667	230	4	will	will	AUX
cana-2667	230	5	take	take	VERB
cana-2667	230	6	ongoing	ongoing	ADJ
cana-2667	230	7	advancement	advancement	NOUN
cana-2667	230	8	in	in	ADP
cana-2667	230	9	machine	machine	NOUN
cana-2667	230	10	learning	learning	NOUN
cana-2667	230	11	methods	method	NOUN
cana-2667	230	12	,	,	PUNCT
cana-2667	230	13	dataset	dataset	ADJ
cana-2667	230	14	creation	creation	NOUN
cana-2667	230	15	and	and	CCONJ
cana-2667	230	16	systems	system	NOUN
cana-2667	230	17	incorporation	incorporation	NOUN
cana-2667	230	18	so	so	SCONJ
cana-2667	230	19	these	these	DET
cana-2667	230	20	advisors	advisor	NOUN
cana-2667	230	21	can	can	AUX
cana-2667	230	22	be	be	AUX
cana-2667	230	23	put	put	VERB
cana-2667	230	24	to	to	ADP
cana-2667	230	25	practical	practical	ADJ
cana-2667	230	26	use	use	NOUN
cana-2667	230	27	in	in	ADP
cana-2667	230	28	clinical	clinical	ADJ
cana-2667	230	29	practice	practice	NOUN
cana-2667	230	30	.	.	PUNCT
cana-2667	231	1	3	3	X
cana-2667	231	2	.	.	X
cana-2667	231	3	methodology	methodology	NOUN
cana-2667	231	4	the	the	DET
cana-2667	231	5	proposed	propose	VERB
cana-2667	231	6	methodology	methodology	NOUN
cana-2667	231	7	aims	aim	VERB
cana-2667	231	8	on	on	ADP
cana-2667	231	9	use	use	NOUN
cana-2667	231	10	of	of	ADP
cana-2667	231	11	cnn	cnn	PROPN
cana-2667	231	12	and	and	CCONJ
cana-2667	231	13	svm	svm	VERB
cana-2667	231	14	in	in	ADP
cana-2667	231	15	combination	combination	NOUN
cana-2667	231	16	to	to	PART
cana-2667	231	17	automatically	automatically	ADV
cana-2667	231	18	classify	classify	VERB
cana-2667	231	19	retinal	retinal	ADJ
cana-2667	231	20	images	image	NOUN
cana-2667	231	21	for	for	ADP
cana-2667	231	22	diabetic	diabetic	ADJ
cana-2667	231	23	retinopathy	retinopathy	ADJ
cana-2667	231	24	detection	detection	NOUN
cana-2667	231	25	.	.	PUNCT
cana-2667	232	1	this	this	DET
cana-2667	232	2	hybrid	hybrid	ADJ
cana-2667	232	3	approach	approach	NOUN
cana-2667	232	4	combines	combine	VERB
cana-2667	232	5	the	the	DET
cana-2667	232	6	best	good	ADJ
cana-2667	232	7	of	of	ADP
cana-2667	232	8	both	both	DET
cana-2667	232	9	worlds	world	NOUN
cana-2667	232	10	,	,	PUNCT
cana-2667	232	11	namely	namely	ADV
cana-2667	232	12	,	,	PUNCT
cana-2667	232	13	the	the	DET
cana-2667	232	14	feature	feature	NOUN
cana-2667	232	15	extraction	extraction	NOUN
cana-2667	232	16	aspect	aspect	NOUN
cana-2667	232	17	of	of	ADP
cana-2667	232	18	deep	deep	ADJ
cana-2667	232	19	learning	learning	NOUN
cana-2667	232	20	cnns	cnn	NOUN
cana-2667	232	21	and	and	CCONJ
cana-2667	232	22	the	the	DET
cana-2667	232	23	strong	strong	ADJ
cana-2667	232	24	classification	classification	NOUN
cana-2667	232	25	capabilities	capability	NOUN
cana-2667	232	26	of	of	ADP
cana-2667	232	27	svms	svms	NOUN
cana-2667	232	28	.	.	PUNCT
cana-2667	233	1	introduction	introduction	NOUN
cana-2667	233	2	:	:	PUNCT
cana-2667	233	3	the	the	DET
cana-2667	233	4	methodology	methodology	NOUN
cana-2667	233	5	is	be	AUX
cana-2667	233	6	developed	develop	VERB
cana-2667	233	7	to	to	PART
cana-2667	233	8	overcome	overcome	VERB
cana-2667	233	9	the	the	DET
cana-2667	233	10	issues	issue	NOUN
cana-2667	233	11	regarding	regard	VERB
cana-2667	233	12	the	the	DET
cana-2667	233	13	processing	processing	NOUN
cana-2667	233	14	of	of	ADP
cana-2667	233	15	the	the	DET
cana-2667	233	16	medical	medical	ADJ
cana-2667	233	17	images	image	NOUN
cana-2667	233	18	and	and	CCONJ
cana-2667	233	19	particularly	particularly	ADV
cana-2667	233	20	,	,	PUNCT
cana-2667	233	21	early	early	ADJ
cana-2667	233	22	detection	detection	NOUN
cana-2667	233	23	of	of	ADP
cana-2667	233	24	diabetic	diabetic	ADJ
cana-2667	233	25	retinopathy	retinopathy	NOUN
cana-2667	233	26	which	which	PRON
cana-2667	233	27	is	be	AUX
cana-2667	233	28	very	very	ADV
cana-2667	233	29	important	important	ADJ
cana-2667	233	30	for	for	ADP
cana-2667	233	31	preventing	prevent	VERB
cana-2667	233	32	visual	visual	ADJ
cana-2667	233	33	impairment	impairment	NOUN
cana-2667	233	34	.	.	PUNCT
cana-2667	234	1	communications	communication	NOUN
cana-2667	234	2	on	on	ADP
cana-2667	234	3	applied	apply	VERB
cana-2667	234	4	nonlinear	nonlinear	ADJ
cana-2667	234	5	analysis	analysis	NOUN
cana-2667	234	6	issn	issn	NOUN
cana-2667	234	7	:	:	PUNCT
cana-2667	234	8	1074	1074	NUM
cana-2667	234	9	-	-	PUNCT
cana-2667	234	10	133x	133x	NUM
cana-2667	234	11	vol	vol	NOUN
cana-2667	234	12	32	32	NUM
cana-2667	234	13	no	no	NOUN
cana-2667	234	14	.	.	PUNCT
cana-2667	235	1	3s	3s	NUM
cana-2667	235	2	(	(	PUNCT
cana-2667	235	3	2025	2025	NUM
cana-2667	235	4	)	)	PUNCT
cana-2667	235	5	390	390	NUM
cana-2667	235	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	235	7	figure	figure	NOUN
cana-2667	235	8	2	2	NUM
cana-2667	235	9	.	.	X
cana-2667	235	10	flowchart	flowchart	NOUN
cana-2667	235	11	of	of	ADP
cana-2667	235	12	proposed	propose	VERB
cana-2667	235	13	methodology	methodology	NOUN
cana-2667	235	14	feature	feature	NOUN
cana-2667	235	15	extraction	extraction	NOUN
cana-2667	235	16	with	with	ADP
cana-2667	235	17	convolutional	convolutional	ADJ
cana-2667	235	18	neural	neural	ADJ
cana-2667	235	19	networks	network	NOUN
cana-2667	235	20	(	(	PUNCT
cana-2667	235	21	cnns	cnns	PROPN
cana-2667	235	22	)	)	PUNCT
cana-2667	235	23	the	the	DET
cana-2667	235	24	proposed	propose	VERB
cana-2667	235	25	methodology	methodology	NOUN
cana-2667	235	26	's	's	PART
cana-2667	235	27	first	first	ADJ
cana-2667	235	28	step	step	NOUN
cana-2667	235	29	is	be	AUX
cana-2667	235	30	applied	apply	VERB
cana-2667	235	31	to	to	ADP
cana-2667	235	32	convolutional	convolutional	ADJ
cana-2667	235	33	neural	neural	ADJ
cana-2667	235	34	networks	network	NOUN
cana-2667	235	35	(	(	PUNCT
cana-2667	235	36	cnn	cnn	PROPN
cana-2667	235	37	)	)	PUNCT
cana-2667	235	38	for	for	ADP
cana-2667	235	39	automatic	automatic	ADJ
cana-2667	235	40	feature	feature	NOUN
cana-2667	235	41	extraction	extraction	NOUN
cana-2667	235	42	of	of	ADP
cana-2667	235	43	retinal	retinal	ADJ
cana-2667	235	44	images	image	NOUN
cana-2667	235	45	.	.	PUNCT
cana-2667	236	1	cnns	cnns	PROPN
cana-2667	236	2	proved	prove	VERB
cana-2667	236	3	to	to	PART
cana-2667	236	4	be	be	AUX
cana-2667	236	5	super	super	ADV
cana-2667	236	6	effective	effective	ADJ
cana-2667	236	7	in	in	ADP
cana-2667	236	8	classification	classification	NOUN
cana-2667	236	9	tasks	task	NOUN
cana-2667	236	10	(	(	PUNCT
cana-2667	236	11	especially	especially	ADV
cana-2667	236	12	with	with	ADP
cana-2667	236	13	large	large	ADJ
cana-2667	236	14	datasets	dataset	NOUN
cana-2667	236	15	)	)	PUNCT
cana-2667	236	16	of	of	ADP
cana-2667	236	17	images	image	NOUN
cana-2667	236	18	.	.	PUNCT
cana-2667	237	1	traditional	traditional	ADJ
cana-2667	237	2	deep	deep	ADJ
cana-2667	237	3	learning	learning	NOUN
cana-2667	237	4	techniques	technique	NOUN
cana-2667	237	5	rely	rely	VERB
cana-2667	237	6	on	on	ADP
cana-2667	237	7	manually	manually	ADV
cana-2667	237	8	engineering	engineering	NOUN
cana-2667	237	9	features	feature	NOUN
cana-2667	237	10	from	from	ADP
cana-2667	237	11	data	datum	NOUN
cana-2667	237	12	,	,	PUNCT
cana-2667	237	13	but	but	CCONJ
cana-2667	237	14	cnns	cnns	PROPN
cana-2667	237	15	can	can	AUX
cana-2667	237	16	learn	learn	VERB
cana-2667	237	17	features	feature	NOUN
cana-2667	237	18	from	from	ADP
cana-2667	237	19	the	the	DET
cana-2667	237	20	raw	raw	ADJ
cana-2667	237	21	pixel	pixel	NOUN
cana-2667	237	22	data	datum	NOUN
cana-2667	237	23	in	in	ADP
cana-2667	237	24	an	an	DET
cana-2667	237	25	image	image	NOUN
cana-2667	237	26	.	.	PUNCT
cana-2667	238	1	cnns	cnns	PROPN
cana-2667	238	2	are	be	AUX
cana-2667	238	3	,	,	PUNCT
cana-2667	238	4	therefore	therefore	ADV
cana-2667	238	5	,	,	PUNCT
cana-2667	238	6	quite	quite	ADV
cana-2667	238	7	appropriate	appropriate	ADJ
cana-2667	238	8	for	for	ADP
cana-2667	238	9	medical	medical	ADJ
cana-2667	238	10	imaging	imaging	NOUN
cana-2667	238	11	,	,	PUNCT
cana-2667	238	12	and	and	CCONJ
cana-2667	238	13	in	in	ADP
cana-2667	238	14	particular	particular	ADJ
cana-2667	238	15	with	with	ADP
cana-2667	238	16	retinal	retinal	ADJ
cana-2667	238	17	images	image	NOUN
cana-2667	238	18	since	since	SCONJ
cana-2667	238	19	they	they	PRON
cana-2667	238	20	extract	extract	VERB
cana-2667	238	21	meaningful	meaningful	ADJ
cana-2667	238	22	steps	step	NOUN
cana-2667	238	23	from	from	ADP
cana-2667	238	24	complex	complex	ADJ
cana-2667	238	25	images	image	NOUN
cana-2667	238	26	through	through	ADP
cana-2667	238	27	hierarchical	hierarchical	ADJ
cana-2667	238	28	feature	feature	NOUN
cana-2667	238	29	extraction	extraction	NOUN
cana-2667	238	30	making	make	VERB
cana-2667	238	31	them	they	PRON
cana-2667	238	32	useful	useful	ADJ
cana-2667	238	33	for	for	ADP
cana-2667	238	34	detecting	detect	VERB
cana-2667	238	35	subtle	subtle	ADJ
cana-2667	238	36	patterns	pattern	NOUN
cana-2667	238	37	(	(	PUNCT
cana-2667	238	38	alryalat	alryalat	NOUN
cana-2667	238	39	et	et	PROPN
cana-2667	238	40	al	al	PROPN
cana-2667	238	41	.	.	PROPN
cana-2667	238	42	,	,	PUNCT
cana-2667	238	43	2017	2017	NUM
cana-2667	238	44	)	)	PUNCT
cana-2667	238	45	.	.	PUNCT
cana-2667	239	1	algorithm	algorithm	NOUN
cana-2667	239	2	1	1	NUM
cana-2667	239	3	:	:	PUNCT
cana-2667	239	4	convolutional	convolutional	ADJ
cana-2667	239	5	neural	neural	ADJ
cana-2667	239	6	network	network	NOUN
cana-2667	239	7	(	(	PUNCT
cana-2667	239	8	cnn	cnn	PROPN
cana-2667	239	9	)	)	PUNCT
cana-2667	239	10	for	for	ADP
cana-2667	239	11	feature	feature	NOUN
cana-2667	239	12	extraction	extraction	NOUN
cana-2667	239	13	input	input	NOUN
cana-2667	239	14	:	:	PUNCT
cana-2667	239	15	•	•	NUM
cana-2667	239	16	𝐼	𝐼	PROPN
cana-2667	239	17	:	:	PUNCT
cana-2667	239	18	input	input	NOUN
cana-2667	239	19	image	image	NOUN
cana-2667	239	20	•	•	ADP
cana-2667	239	21	𝑊𝑖	𝑊𝑖	PROPN
cana-2667	239	22	:	:	PUNCT
cana-2667	239	23	filter	filter	NOUN
cana-2667	239	24	weights	weight	NOUN
cana-2667	239	25	for	for	ADP
cana-2667	239	26	the	the	DET
cana-2667	239	27	𝑖-th	𝑖-th	PROPN
cana-2667	239	28	convolutional	convolutional	ADJ
cana-2667	239	29	layer	layer	NOUN
cana-2667	239	30	•	•	ADP
cana-2667	239	31	𝑏𝑖	𝑏𝑖	NOUN
cana-2667	239	32	:	:	PUNCT
cana-2667	239	33	bias	bias	NOUN
cana-2667	239	34	for	for	ADP
cana-2667	239	35	the	the	DET
cana-2667	239	36	𝑖-th	𝑖-th	PROPN
cana-2667	239	37	layer	layer	NOUN
cana-2667	239	38	output	output	NOUN
cana-2667	239	39	:	:	PUNCT
cana-2667	239	40	•	•	NUM
cana-2667	239	41	𝐹	𝐹	PROPN
cana-2667	239	42	:	:	PUNCT
cana-2667	239	43	feature	feature	NOUN
cana-2667	239	44	map	map	NOUN
cana-2667	239	45	after	after	ADP
cana-2667	239	46	processing	process	VERB
cana-2667	239	47	through	through	ADP
cana-2667	239	48	cnn	cnn	PROPN
cana-2667	239	49	steps	step	NOUN
cana-2667	239	50	:	:	PUNCT
cana-2667	239	51	1	1	X
cana-2667	239	52	.	.	X
cana-2667	239	53	convolution	convolution	NOUN
cana-2667	239	54	:	:	PUNCT
cana-2667	239	55	for	for	ADP
cana-2667	239	56	each	each	DET
cana-2667	239	57	convolutional	convolutional	ADJ
cana-2667	239	58	layer	layer	NOUN
cana-2667	239	59	𝑖	𝑖	NOUN
cana-2667	239	60	,	,	PUNCT
cana-2667	239	61	apply	apply	VERB
cana-2667	239	62	the	the	DET
cana-2667	239	63	convolution	convolution	NOUN
cana-2667	239	64	operation	operation	NOUN
cana-2667	239	65	to	to	ADP
cana-2667	239	66	the	the	DET
cana-2667	239	67	input	input	NOUN
cana-2667	239	68	image	image	NOUN
cana-2667	239	69	:	:	PUNCT
cana-2667	239	70	communications	communication	NOUN
cana-2667	239	71	on	on	ADP
cana-2667	239	72	applied	apply	VERB
cana-2667	239	73	nonlinear	nonlinear	ADJ
cana-2667	239	74	analysis	analysis	NOUN
cana-2667	239	75	issn	issn	NOUN
cana-2667	239	76	:	:	PUNCT
cana-2667	239	77	1074	1074	NUM
cana-2667	239	78	-	-	PUNCT
cana-2667	239	79	133x	133x	NUM
cana-2667	239	80	vol	vol	NOUN
cana-2667	239	81	32	32	NUM
cana-2667	239	82	no	no	NOUN
cana-2667	239	83	.	.	PUNCT
cana-2667	240	1	3s	3s	NUM
cana-2667	240	2	(	(	PUNCT
cana-2667	240	3	2025	2025	NUM
cana-2667	240	4	)	)	PUNCT
cana-2667	240	5	391	391	NUM
cana-2667	240	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	241	1	𝐹𝑖	𝐹𝑖	NOUN
cana-2667	241	2	=	=	PUNCT
cana-2667	241	3	𝐼	𝐼	PROPN
cana-2667	241	4	∗𝑊𝑖	∗𝑊𝑖	NOUN
cana-2667	241	5	+	+	X
cana-2667	241	6	𝑏𝑖	𝑏𝑖	ADP
cana-2667	241	7	where	where	SCONJ
cana-2667	241	8	∗	∗	NOUN
cana-2667	241	9	denotes	denote	VERB
cana-2667	241	10	the	the	DET
cana-2667	241	11	convolution	convolution	NOUN
cana-2667	241	12	operation	operation	NOUN
cana-2667	241	13	,	,	PUNCT
cana-2667	241	14	and	and	CCONJ
cana-2667	241	15	𝐹𝑖	𝐹𝑖	PROPN
cana-2667	241	16	is	be	AUX
cana-2667	241	17	the	the	DET
cana-2667	241	18	output	output	NOUN
cana-2667	241	19	feature	feature	NOUN
cana-2667	241	20	map	map	NOUN
cana-2667	241	21	of	of	ADP
cana-2667	241	22	the	the	DET
cana-2667	241	23	𝑖-th	𝑖-th	PROPN
cana-2667	241	24	convolutional	convolutional	ADJ
cana-2667	241	25	layer	layer	NOUN
cana-2667	241	26	.	.	PUNCT
cana-2667	242	1	2	2	X
cana-2667	242	2	.	.	X
cana-2667	242	3	activation	activation	NOUN
cana-2667	242	4	(	(	PUNCT
cana-2667	242	5	relu	relu	NOUN
cana-2667	242	6	):	):	PUNCT
cana-2667	242	7	apply	apply	VERB
cana-2667	242	8	relu	relu	NOUN
cana-2667	242	9	activation	activation	NOUN
cana-2667	242	10	to	to	ADP
cana-2667	242	11	the	the	DET
cana-2667	242	12	feature	feature	NOUN
cana-2667	242	13	map	map	NOUN
cana-2667	242	14	:	:	PUNCT
cana-2667	242	15	𝐴𝑖	𝐴𝑖	PROPN
cana-2667	242	16	=	=	PUNCT
cana-2667	242	17	max(0	max(0	NOUN
cana-2667	242	18	,	,	PUNCT
cana-2667	242	19	𝐹𝑖	𝐹𝑖	PROPN
cana-2667	242	20	)	)	PUNCT
cana-2667	242	21	where	where	SCONJ
cana-2667	242	22	𝐴𝑖	𝐴𝑖	PROPN
cana-2667	242	23	is	be	AUX
cana-2667	242	24	the	the	DET
cana-2667	242	25	activated	activate	VERB
cana-2667	242	26	output	output	NOUN
cana-2667	242	27	after	after	ADP
cana-2667	242	28	applying	apply	VERB
cana-2667	242	29	relu	relu	NOUN
cana-2667	242	30	.	.	PUNCT
cana-2667	243	1	3	3	X
cana-2667	243	2	.	.	X
cana-2667	243	3	pooling	pool	VERB
cana-2667	243	4	(	(	PUNCT
cana-2667	243	5	max	max	PROPN
cana-2667	243	6	pooling	pooling	NOUN
cana-2667	243	7	):	):	PUNCT
cana-2667	243	8	apply	apply	VERB
cana-2667	243	9	max	max	PROPN
cana-2667	243	10	pooling	pooling	NOUN
cana-2667	243	11	with	with	ADP
cana-2667	243	12	a	a	DET
cana-2667	243	13	pool	pool	NOUN
cana-2667	243	14	size	size	NOUN
cana-2667	243	15	𝑝	𝑝	NOUN
cana-2667	243	16	to	to	PART
cana-2667	243	17	reduce	reduce	VERB
cana-2667	243	18	the	the	DET
cana-2667	243	19	spatial	spatial	ADJ
cana-2667	243	20	dimensions	dimension	NOUN
cana-2667	243	21	:	:	PUNCT
cana-2667	244	1	𝑃𝑖	𝑃𝑖	ADP
cana-2667	244	2	=	=	PROPN
cana-2667	244	3	maxpool(𝐴𝑖	maxpool(𝐴𝑖	PROPN
cana-2667	244	4	,	,	PUNCT
cana-2667	244	5	𝑝	𝑝	NOUN
cana-2667	244	6	)	)	PUNCT
cana-2667	244	7	where	where	SCONJ
cana-2667	244	8	𝑃𝑖	𝑃𝑖	SCONJ
cana-2667	244	9	is	be	AUX
cana-2667	244	10	the	the	DET
cana-2667	244	11	pooled	pool	VERB
cana-2667	244	12	feature	feature	NOUN
cana-2667	244	13	map	map	NOUN
cana-2667	244	14	.	.	PUNCT
cana-2667	245	1	4	4	X
cana-2667	245	2	.	.	X
cana-2667	245	3	flattening	flattening	NOUN
cana-2667	245	4	:	:	PUNCT
cana-2667	245	5	flatten	flatten	VERB
cana-2667	245	6	the	the	DET
cana-2667	245	7	pooled	pooled	ADJ
cana-2667	245	8	feature	feature	NOUN
cana-2667	245	9	maps	map	NOUN
cana-2667	245	10	into	into	ADP
cana-2667	245	11	a	a	DET
cana-2667	245	12	one	one	NUM
cana-2667	245	13	-	-	PUNCT
cana-2667	245	14	dimensional	dimensional	ADJ
cana-2667	245	15	vector	vector	NOUN
cana-2667	245	16	:	:	PUNCT
cana-2667	245	17	𝑉	𝑉	PROPN
cana-2667	245	18	=	=	SYM
cana-2667	245	19	flatten(𝑃𝑖	flatten(𝑃𝑖	PROPN
cana-2667	245	20	)	)	PUNCT
cana-2667	245	21	where	where	SCONJ
cana-2667	245	22	𝑉	𝑉	PROPN
cana-2667	245	23	is	be	AUX
cana-2667	245	24	the	the	DET
cana-2667	245	25	final	final	ADJ
cana-2667	245	26	flattened	flatten	VERB
cana-2667	245	27	feature	feature	NOUN
cana-2667	245	28	vector	vector	NOUN
cana-2667	245	29	ready	ready	ADJ
cana-2667	245	30	for	for	ADP
cana-2667	245	31	classification	classification	NOUN
cana-2667	245	32	.	.	PUNCT
cana-2667	246	1	cnns	cnns	PROPN
cana-2667	246	2	can	can	AUX
cana-2667	246	3	be	be	AUX
cana-2667	246	4	trained	train	VERB
cana-2667	246	5	on	on	ADP
cana-2667	246	6	large	large	ADJ
cana-2667	246	7	datasets	dataset	NOUN
cana-2667	246	8	of	of	ADP
cana-2667	246	9	retinal	retinal	ADJ
cana-2667	246	10	images	image	NOUN
cana-2667	246	11	of	of	ADP
cana-2667	246	12	varying	vary	VERB
cana-2667	246	13	degrees	degree	NOUN
cana-2667	246	14	of	of	ADP
cana-2667	246	15	diabetic	diabetic	ADJ
cana-2667	246	16	retinopathy	retinopathy	NOUN
cana-2667	246	17	to	to	PART
cana-2667	246	18	detect	detect	VERB
cana-2667	246	19	retinopathy	retinopathy	NOUN
cana-2667	246	20	.	.	PUNCT
cana-2667	247	1	also	also	ADV
cana-2667	247	2	,	,	PUNCT
cana-2667	247	3	the	the	DET
cana-2667	247	4	system	system	NOUN
cana-2667	247	5	automatically	automatically	ADV
cana-2667	247	6	learns	learn	VERB
cana-2667	247	7	relevant	relevant	ADJ
cana-2667	247	8	patterns	pattern	NOUN
cana-2667	247	9	of	of	ADP
cana-2667	247	10	the	the	DET
cana-2667	247	11	disease	disease	NOUN
cana-2667	247	12	in	in	ADP
cana-2667	247	13	each	each	DET
cana-2667	247	14	state	state	NOUN
cana-2667	247	15	including	include	VERB
cana-2667	247	16	microaneurysms	microaneurysm	NOUN
cana-2667	247	17	,	,	PUNCT
cana-2667	247	18	hemorrhages	hemorrhage	NOUN
cana-2667	247	19	,	,	PUNCT
cana-2667	247	20	exudates	exudate	NOUN
cana-2667	247	21	and	and	CCONJ
cana-2667	247	22	neovascularization	neovascularization	NOUN
cana-2667	247	23	.	.	PUNCT
cana-2667	248	1	a	a	DET
cana-2667	248	2	cnn	cnn	PROPN
cana-2667	248	3	architecture	architecture	NOUN
cana-2667	248	4	usually	usually	ADV
cana-2667	248	5	includes	include	VERB
cana-2667	248	6	several	several	ADJ
cana-2667	248	7	layers	layer	NOUN
cana-2667	248	8	:	:	PUNCT
cana-2667	248	9	convolutional	convolutional	ADJ
cana-2667	248	10	layers	layer	NOUN
cana-2667	248	11	:	:	PUNCT
cana-2667	248	12	layers	layer	NOUN
cana-2667	248	13	apply	apply	VERB
cana-2667	248	14	filters	filter	NOUN
cana-2667	248	15	to	to	PART
cana-2667	248	16	detect	detect	VERB
cana-2667	248	17	local	local	ADJ
cana-2667	248	18	image	image	NOUN
cana-2667	248	19	patterns	pattern	NOUN
cana-2667	248	20	(	(	PUNCT
cana-2667	248	21	edges	edge	NOUN
cana-2667	248	22	,	,	PUNCT
cana-2667	248	23	textures	texture	NOUN
cana-2667	248	24	,	,	PUNCT
cana-2667	248	25	colors	color	NOUN
cana-2667	248	26	)	)	PUNCT
cana-2667	248	27	.	.	PUNCT
cana-2667	249	1	the	the	DET
cana-2667	249	2	filters	filter	NOUN
cana-2667	249	3	swipe	swipe	VERB
cana-2667	249	4	across	across	ADP
cana-2667	249	5	the	the	DET
cana-2667	249	6	image	image	NOUN
cana-2667	249	7	,	,	PUNCT
cana-2667	249	8	doing	do	VERB
cana-2667	249	9	a	a	DET
cana-2667	249	10	mathematical	mathematical	ADJ
cana-2667	249	11	operation	operation	NOUN
cana-2667	249	12	known	know	VERB
cana-2667	249	13	as	as	ADP
cana-2667	249	14	convolution	convolution	NOUN
cana-2667	249	15	,	,	PUNCT
cana-2667	249	16	enabling	enable	VERB
cana-2667	249	17	the	the	DET
cana-2667	249	18	network	network	NOUN
cana-2667	249	19	to	to	PART
cana-2667	249	20	recognize	recognize	VERB
cana-2667	249	21	features	feature	NOUN
cana-2667	249	22	within	within	ADP
cana-2667	249	23	the	the	DET
cana-2667	249	24	image	image	NOUN
cana-2667	249	25	.	.	PUNCT
cana-2667	250	1	activation	activation	NOUN
cana-2667	250	2	layers	layer	NOUN
cana-2667	250	3	:	:	PUNCT
cana-2667	250	4	once	once	SCONJ
cana-2667	250	5	convolution	convolution	NOUN
cana-2667	250	6	is	be	AUX
cana-2667	250	7	performed	perform	VERB
cana-2667	250	8	,	,	PUNCT
cana-2667	250	9	it	it	PRON
cana-2667	250	10	must	must	AUX
cana-2667	250	11	be	be	AUX
cana-2667	250	12	followed	follow	VERB
cana-2667	250	13	by	by	ADP
cana-2667	250	14	activation	activation	NOUN
cana-2667	250	15	functions	function	NOUN
cana-2667	250	16	(	(	PUNCT
cana-2667	250	17	like	like	ADP
cana-2667	250	18	rectified	rectified	ADJ
cana-2667	250	19	linear	linear	ADJ
cana-2667	250	20	units	unit	NOUN
cana-2667	250	21	:	:	PUNCT
cana-2667	250	22	relu	relu	NOUN
cana-2667	250	23	)	)	PUNCT
cana-2667	250	24	to	to	PART
cana-2667	250	25	enable	enable	VERB
cana-2667	250	26	the	the	DET
cana-2667	250	27	model	model	NOUN
cana-2667	250	28	to	to	PART
cana-2667	250	29	learn	learn	VERB
cana-2667	250	30	increasingly	increasingly	ADV
cana-2667	250	31	complex	complex	ADJ
cana-2667	250	32	patterns	pattern	NOUN
cana-2667	250	33	and	and	CCONJ
cana-2667	250	34	decision	decision	NOUN
cana-2667	250	35	boundaries	boundary	NOUN
cana-2667	250	36	.	.	PUNCT
cana-2667	251	1	pooling	pool	VERB
cana-2667	251	2	layers	layer	NOUN
cana-2667	251	3	:	:	PUNCT
cana-2667	251	4	max	max	ADJ
cana-2667	251	5	-	-	PUNCT
cana-2667	251	6	pooling	pool	VERB
cana-2667	251	7	layers	layer	NOUN
cana-2667	251	8	that	that	SCONJ
cana-2667	251	9	down	down	ADV
cana-2667	251	10	-	-	PUNCT
cana-2667	251	11	scale	scale	NOUN
cana-2667	251	12	the	the	DET
cana-2667	251	13	feature	feature	NOUN
cana-2667	251	14	maps	map	NOUN
cana-2667	251	15	while	while	SCONJ
cana-2667	251	16	maintaining	maintain	VERB
cana-2667	251	17	the	the	DET
cana-2667	251	18	most	most	ADV
cana-2667	251	19	important	important	ADJ
cana-2667	251	20	features	feature	NOUN
cana-2667	251	21	.	.	PUNCT
cana-2667	252	1	so	so	ADV
cana-2667	252	2	,	,	PUNCT
cana-2667	252	3	this	this	DET
cana-2667	252	4	pooling	pooling	NOUN
cana-2667	252	5	operation	operation	NOUN
cana-2667	252	6	reduces	reduce	VERB
cana-2667	252	7	the	the	DET
cana-2667	252	8	computational	computational	ADJ
cana-2667	252	9	complexity	complexity	NOUN
cana-2667	252	10	and	and	CCONJ
cana-2667	252	11	also	also	ADV
cana-2667	252	12	reduces	reduce	VERB
cana-2667	252	13	overfitting	overfitte	VERB
cana-2667	252	14	by	by	ADP
cana-2667	252	15	providing	provide	VERB
cana-2667	252	16	spatial	spatial	ADJ
cana-2667	252	17	invariance	invariance	NOUN
cana-2667	252	18	property	property	NOUN
cana-2667	252	19	to	to	ADP
cana-2667	252	20	the	the	DET
cana-2667	252	21	network	network	NOUN
cana-2667	252	22	.	.	PUNCT
cana-2667	253	1	fully	fully	ADV
cana-2667	253	2	connected	connected	ADJ
cana-2667	253	3	layers	layer	NOUN
cana-2667	253	4	:	:	PUNCT
cana-2667	253	5	after	after	ADP
cana-2667	253	6	extracting	extract	VERB
cana-2667	253	7	the	the	DET
cana-2667	253	8	features	feature	NOUN
cana-2667	253	9	from	from	ADP
cana-2667	253	10	the	the	DET
cana-2667	253	11	images	image	NOUN
cana-2667	253	12	,	,	PUNCT
cana-2667	253	13	they	they	PRON
cana-2667	253	14	are	be	AUX
cana-2667	253	15	passed	pass	VERB
cana-2667	253	16	through	through	ADP
cana-2667	253	17	a	a	DET
cana-2667	253	18	flatten	flatten	ADJ
cana-2667	253	19	layer	layer	NOUN
cana-2667	253	20	and	and	CCONJ
cana-2667	253	21	forward	forward	ADV
cana-2667	253	22	to	to	ADP
cana-2667	253	23	the	the	DET
cana-2667	253	24	fully	fully	ADV
cana-2667	253	25	connected	connected	ADJ
cana-2667	253	26	layers	layer	NOUN
cana-2667	253	27	that	that	PRON
cana-2667	253	28	combine	combine	VERB
cana-2667	253	29	features	feature	NOUN
cana-2667	253	30	in	in	ADP
cana-2667	253	31	a	a	DET
cana-2667	253	32	non	non	ADJ
cana-2667	253	33	-	-	ADJ
cana-2667	253	34	linear	linear	ADJ
cana-2667	253	35	manner	manner	NOUN
cana-2667	253	36	and	and	CCONJ
cana-2667	253	37	at	at	ADP
cana-2667	253	38	the	the	DET
cana-2667	253	39	very	very	ADV
cana-2667	253	40	last	last	ADJ
cana-2667	253	41	stage	stage	NOUN
cana-2667	253	42	,	,	PUNCT
cana-2667	253	43	decide	decide	VERB
cana-2667	253	44	on	on	ADP
cana-2667	253	45	what	what	DET
cana-2667	253	46	class	class	NOUN
cana-2667	253	47	the	the	DET
cana-2667	253	48	image	image	NOUN
cana-2667	253	49	belongs	belong	VERB
cana-2667	253	50	to	to	ADP
cana-2667	253	51	.	.	PUNCT
cana-2667	254	1	the	the	DET
cana-2667	254	2	entire	entire	ADJ
cana-2667	254	3	pipeline	pipeline	NOUN
cana-2667	254	4	is	be	AUX
cana-2667	254	5	learned	learn	VERB
cana-2667	254	6	in	in	ADP
cana-2667	254	7	an	an	DET
cana-2667	254	8	end	end	NOUN
cana-2667	254	9	-	-	PUNCT
cana-2667	254	10	to	to	ADP
cana-2667	254	11	-	-	PUNCT
cana-2667	254	12	end	end	NOUN
cana-2667	254	13	fashion	fashion	NOUN
cana-2667	254	14	,	,	PUNCT
cana-2667	254	15	eliminating	eliminate	VERB
cana-2667	254	16	the	the	DET
cana-2667	254	17	need	need	NOUN
cana-2667	254	18	for	for	ADP
cana-2667	254	19	manual	manual	ADJ
cana-2667	254	20	feature	feature	NOUN
cana-2667	254	21	engineering	engineering	NOUN
cana-2667	254	22	and	and	CCONJ
cana-2667	254	23	letting	let	VERB
cana-2667	254	24	the	the	DET
cana-2667	254	25	cnn	cnn	PROPN
cana-2667	254	26	learn	learn	VERB
cana-2667	254	27	the	the	DET
cana-2667	254	28	most	most	ADV
cana-2667	254	29	relevant	relevant	ADJ
cana-2667	254	30	features	feature	NOUN
cana-2667	254	31	from	from	ADP
cana-2667	254	32	the	the	DET
cana-2667	254	33	data	datum	NOUN
cana-2667	254	34	itself	itself	PRON
cana-2667	254	35	.	.	PUNCT
cana-2667	255	1	the	the	DET
cana-2667	255	2	cnn	cnn	PROPN
cana-2667	255	3	is	be	AUX
cana-2667	255	4	trained	train	VERB
cana-2667	255	5	in	in	ADP
cana-2667	255	6	the	the	DET
cana-2667	255	7	usual	usual	ADJ
cana-2667	255	8	way	way	NOUN
cana-2667	255	9	,	,	PUNCT
cana-2667	255	10	by	by	ADP
cana-2667	255	11	minimizing	minimize	VERB
cana-2667	255	12	a	a	DET
cana-2667	255	13	loss	loss	NOUN
cana-2667	255	14	function	function	NOUN
cana-2667	255	15	(	(	PUNCT
cana-2667	255	16	usually	usually	ADV
cana-2667	255	17	cross	cross	ADJ
cana-2667	255	18	-	-	ADJ
cana-2667	255	19	entropy	entropy	ADJ
cana-2667	255	20	loss	loss	NOUN
cana-2667	255	21	)	)	PUNCT
cana-2667	255	22	using	use	VERB
cana-2667	255	23	backpropagation	backpropagation	NOUN
cana-2667	255	24	.	.	PUNCT
cana-2667	256	1	in	in	ADP
cana-2667	256	2	every	every	DET
cana-2667	256	3	cycle	cycle	NOUN
cana-2667	256	4	,	,	PUNCT
cana-2667	256	5	the	the	DET
cana-2667	256	6	network	network	NOUN
cana-2667	256	7	adjusts	adjust	VERB
cana-2667	256	8	its	its	PRON
cana-2667	256	9	weights	weight	NOUN
cana-2667	256	10	in	in	ADP
cana-2667	256	11	an	an	DET
cana-2667	256	12	effort	effort	NOUN
cana-2667	256	13	to	to	PART
cana-2667	256	14	minimize	minimize	VERB
cana-2667	256	15	the	the	DET
cana-2667	256	16	difference	difference	NOUN
cana-2667	256	17	between	between	ADP
cana-2667	256	18	the	the	DET
cana-2667	256	19	predicted	predict	VERB
cana-2667	256	20	output	output	NOUN
cana-2667	256	21	y^	y^	PROPN
cana-2667	256	22	and	and	CCONJ
cana-2667	256	23	the	the	DET
cana-2667	256	24	actual	actual	ADJ
cana-2667	256	25	labels	label	NOUN
cana-2667	256	26	y.	y.	PROPN
cana-2667	256	27	communications	communication	NOUN
cana-2667	256	28	on	on	ADP
cana-2667	256	29	applied	apply	VERB
cana-2667	256	30	nonlinear	nonlinear	ADJ
cana-2667	256	31	analysis	analysis	NOUN
cana-2667	256	32	issn	issn	NOUN
cana-2667	256	33	:	:	PUNCT
cana-2667	256	34	1074	1074	NUM
cana-2667	256	35	-	-	PUNCT
cana-2667	256	36	133x	133x	NUM
cana-2667	256	37	vol	vol	NOUN
cana-2667	256	38	32	32	NUM
cana-2667	257	1	no	no	NOUN
cana-2667	257	2	.	.	PUNCT
cana-2667	258	1	3s	3s	NUM
cana-2667	258	2	(	(	PUNCT
cana-2667	258	3	2025	2025	NUM
cana-2667	258	4	)	)	PUNCT
cana-2667	258	5	392	392	NUM
cana-2667	258	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	258	7	support	support	NOUN
cana-2667	258	8	vector	vector	NOUN
cana-2667	258	9	machines	machine	NOUN
cana-2667	258	10	(	(	PUNCT
cana-2667	258	11	svms	svms	NOUN
cana-2667	258	12	)	)	PUNCT
cana-2667	258	13	for	for	ADP
cana-2667	258	14	classification	classification	NOUN
cana-2667	258	15	after	after	SCONJ
cana-2667	258	16	the	the	DET
cana-2667	258	17	cnn	cnn	PROPN
cana-2667	258	18	has	have	AUX
cana-2667	258	19	accomplished	accomplish	VERB
cana-2667	258	20	the	the	DET
cana-2667	258	21	feature	feature	NOUN
cana-2667	258	22	extraction	extraction	NOUN
cana-2667	258	23	process	process	NOUN
cana-2667	258	24	from	from	ADP
cana-2667	258	25	the	the	DET
cana-2667	258	26	retinal	retinal	ADJ
cana-2667	258	27	images	image	NOUN
cana-2667	258	28	,	,	PUNCT
cana-2667	258	29	those	those	DET
cana-2667	258	30	features	feature	NOUN
cana-2667	258	31	are	be	AUX
cana-2667	258	32	ready	ready	ADJ
cana-2667	258	33	to	to	PART
cana-2667	258	34	be	be	AUX
cana-2667	258	35	applied	apply	VERB
cana-2667	258	36	as	as	ADP
cana-2667	258	37	input	input	NOUN
cana-2667	258	38	to	to	ADP
cana-2667	258	39	the	the	DET
cana-2667	258	40	succeeding	succeed	VERB
cana-2667	258	41	stage	stage	NOUN
cana-2667	258	42	of	of	ADP
cana-2667	258	43	the	the	DET
cana-2667	258	44	methodologies	methodology	NOUN
cana-2667	258	45	,	,	PUNCT
cana-2667	258	46	that	that	ADV
cana-2667	258	47	is	is	ADV
cana-2667	258	48	,	,	PUNCT
cana-2667	258	49	the	the	DET
cana-2667	258	50	classification	classification	NOUN
cana-2667	258	51	stage	stage	NOUN
cana-2667	258	52	where	where	SCONJ
cana-2667	258	53	a	a	DET
cana-2667	258	54	support	support	NOUN
cana-2667	258	55	vector	vector	NOUN
cana-2667	258	56	machine	machine	NOUN
cana-2667	258	57	(	(	PUNCT
cana-2667	258	58	svm	svm	PROPN
cana-2667	258	59	)	)	PUNCT
cana-2667	258	60	is	be	AUX
cana-2667	258	61	applied	apply	VERB
cana-2667	258	62	.	.	PUNCT
cana-2667	259	1	the	the	DET
cana-2667	259	2	support	support	NOUN
cana-2667	259	3	vector	vector	NOUN
cana-2667	259	4	machine	machine	NOUN
cana-2667	259	5	(	(	PUNCT
cana-2667	259	6	svm	svm	PROPN
cana-2667	259	7	)	)	PUNCT
cana-2667	259	8	is	be	AUX
cana-2667	259	9	a	a	DET
cana-2667	259	10	supervised	supervised	ADJ
cana-2667	259	11	learning	learning	NOUN
cana-2667	259	12	model	model	NOUN
cana-2667	259	13	that	that	PRON
cana-2667	259	14	is	be	AUX
cana-2667	259	15	effective	effective	ADJ
cana-2667	259	16	in	in	ADP
cana-2667	259	17	high	high	ADJ
cana-2667	259	18	-	-	PUNCT
cana-2667	259	19	dimensional	dimensional	ADJ
cana-2667	259	20	spaces	space	NOUN
cana-2667	259	21	,	,	PUNCT
cana-2667	259	22	and	and	CCONJ
cana-2667	259	23	thus	thus	ADV
cana-2667	259	24	well	well	ADV
cana-2667	259	25	-	-	PUNCT
cana-2667	259	26	adapted	adapt	VERB
cana-2667	259	27	to	to	ADP
cana-2667	259	28	the	the	DET
cana-2667	259	29	feature	feature	NOUN
cana-2667	259	30	vectors	vector	NOUN
cana-2667	259	31	that	that	PRON
cana-2667	259	32	emerge	emerge	VERB
cana-2667	259	33	from	from	ADP
cana-2667	259	34	cnn	cnn	PROPN
cana-2667	259	35	-	-	PUNCT
cana-2667	259	36	based	base	VERB
cana-2667	259	37	feature	feature	NOUN
cana-2667	259	38	extraction	extraction	NOUN
cana-2667	259	39	.	.	PUNCT
cana-2667	260	1	the	the	DET
cana-2667	260	2	goal	goal	NOUN
cana-2667	260	3	of	of	ADP
cana-2667	260	4	the	the	DET
cana-2667	260	5	svm	svm	NOUN
cana-2667	260	6	is	be	AUX
cana-2667	260	7	to	to	PART
cana-2667	260	8	determine	determine	VERB
cana-2667	260	9	a	a	DET
cana-2667	260	10	decision	decision	NOUN
cana-2667	260	11	boundary	boundary	NOUN
cana-2667	260	12	that	that	PRON
cana-2667	260	13	is	be	AUX
cana-2667	260	14	optimal	optimal	ADJ
cana-2667	260	15	in	in	ADP
cana-2667	260	16	separating	separate	VERB
cana-2667	260	17	the	the	DET
cana-2667	260	18	data	datum	NOUN
cana-2667	260	19	classes	class	NOUN
cana-2667	260	20	,	,	PUNCT
cana-2667	260	21	which	which	PRON
cana-2667	260	22	again	again	ADV
cana-2667	260	23	,	,	PUNCT
cana-2667	260	24	in	in	ADP
cana-2667	260	25	this	this	DET
cana-2667	260	26	case	case	NOUN
cana-2667	260	27	would	would	AUX
cana-2667	260	28	be	be	AUX
cana-2667	260	29	the	the	DET
cana-2667	260	30	levels	level	NOUN
cana-2667	260	31	of	of	ADP
cana-2667	260	32	diabetic	diabetic	ADJ
cana-2667	260	33	retinopathy	retinopathy	NOUN
cana-2667	260	34	or	or	CCONJ
cana-2667	260	35	healthy	healthy	ADJ
cana-2667	260	36	/	/	SYM
cana-2667	260	37	non	non	ADJ
cana-2667	260	38	-	-	ADJ
cana-2667	260	39	healthy	healthy	ADJ
cana-2667	260	40	classifications	classification	NOUN
cana-2667	260	41	.	.	PUNCT
cana-2667	261	1	data	datum	NOUN
cana-2667	261	2	up	up	ADP
cana-2667	261	3	to	to	ADP
cana-2667	261	4	october	october	PROPN
cana-2667	261	5	2023	2023	NUM
cana-2667	261	6	in	in	ADP
cana-2667	261	7	general	general	ADJ
cana-2667	261	8	,	,	PUNCT
cana-2667	261	9	the	the	DET
cana-2667	261	10	task	task	NOUN
cana-2667	261	11	of	of	ADP
cana-2667	261	12	the	the	DET
cana-2667	261	13	svm	svm	NOUN
cana-2667	261	14	is	be	AUX
cana-2667	261	15	to	to	PART
cana-2667	261	16	find	find	VERB
cana-2667	261	17	an	an	DET
cana-2667	261	18	optimal	optimal	ADJ
cana-2667	261	19	hyperplane	hyperplane	NOUN
cana-2667	261	20	to	to	PART
cana-2667	261	21	separate	separate	VERB
cana-2667	261	22	the	the	DET
cana-2667	261	23	classes	class	NOUN
cana-2667	261	24	with	with	ADP
cana-2667	261	25	a	a	DET
cana-2667	261	26	maximum	maximum	ADJ
cana-2667	261	27	margin	margin	NOUN
cana-2667	261	28	.	.	PUNCT
cana-2667	262	1	algorithm	algorithm	NOUN
cana-2667	262	2	2	2	NUM
cana-2667	262	3	:	:	PUNCT
cana-2667	262	4	support	support	NOUN
cana-2667	262	5	vector	vector	NOUN
cana-2667	262	6	machine	machine	NOUN
cana-2667	262	7	(	(	PUNCT
cana-2667	262	8	svm	svm	PROPN
cana-2667	262	9	)	)	PUNCT
cana-2667	262	10	for	for	ADP
cana-2667	262	11	classification	classification	NOUN
cana-2667	262	12	input	input	NOUN
cana-2667	262	13	:	:	PUNCT
cana-2667	262	14	•	•	NUM
cana-2667	262	15	𝑋	𝑋	NOUN
cana-2667	262	16	:	:	PUNCT
cana-2667	262	17	feature	feature	NOUN
cana-2667	262	18	vector	vector	NOUN
cana-2667	262	19	from	from	ADP
cana-2667	262	20	cnn	cnn	PROPN
cana-2667	262	21	•	•	PROPN
cana-2667	262	22	𝑌	𝑌	PROPN
cana-2667	262	23	:	:	PUNCT
cana-2667	262	24	label	label	NOUN
cana-2667	262	25	vector	vector	NOUN
cana-2667	262	26	(	(	PUNCT
cana-2667	262	27	0	0	NUM
cana-2667	262	28	for	for	ADP
cana-2667	262	29	healthy	healthy	ADJ
cana-2667	262	30	,	,	PUNCT
cana-2667	262	31	1	1	NUM
cana-2667	262	32	for	for	ADP
cana-2667	262	33	diseased	diseased	ADJ
cana-2667	262	34	)	)	PUNCT
cana-2667	262	35	•	•	ADP
cana-2667	263	1	𝐶	𝐶	PROPN
cana-2667	263	2	:	:	PUNCT
cana-2667	263	3	regularization	regularization	NOUN
cana-2667	263	4	parameter	parameter	NOUN
cana-2667	263	5	•	•	NUM
cana-2667	263	6	𝐾	𝐾	PROPN
cana-2667	263	7	:	:	PUNCT
cana-2667	263	8	kernel	kernel	PROPN
cana-2667	263	9	function	function	NOUN
cana-2667	263	10	(	(	PUNCT
cana-2667	263	11	e.g.	e.g.	ADV
cana-2667	263	12	,	,	PUNCT
cana-2667	263	13	radial	radial	ADJ
cana-2667	263	14	basis	basis	NOUN
cana-2667	263	15	function	function	NOUN
cana-2667	263	16	)	)	PUNCT
cana-2667	263	17	output	output	NOUN
cana-2667	263	18	:	:	PUNCT
cana-2667	263	19	•	•	NUM
cana-2667	263	20	𝐰	𝐰	ADJ
cana-2667	263	21	:	:	PUNCT
cana-2667	263	22	optimal	optimal	ADJ
cana-2667	263	23	hyperplane	hyperplane	NOUN
cana-2667	263	24	weights	weight	VERB
cana-2667	263	25	•	•	NOUN
cana-2667	263	26	𝑏	𝑏	NOUN
cana-2667	263	27	:	:	PUNCT
cana-2667	263	28	bias	bias	NOUN
cana-2667	263	29	term	term	NOUN
cana-2667	263	30	of	of	ADP
cana-2667	263	31	the	the	DET
cana-2667	263	32	hyperplane	hyperplane	NOUN
cana-2667	263	33	steps	step	NOUN
cana-2667	263	34	:	:	PUNCT
cana-2667	263	35	1	1	X
cana-2667	263	36	.	.	X
cana-2667	263	37	initialize	initialize	VERB
cana-2667	263	38	weights	weight	NOUN
cana-2667	263	39	and	and	CCONJ
cana-2667	263	40	bias	bias	NOUN
cana-2667	263	41	:	:	PUNCT
cana-2667	263	42	initialize	initialize	VERB
cana-2667	263	43	the	the	DET
cana-2667	263	44	weights	weight	NOUN
cana-2667	263	45	𝐰	𝐰	NOUN
cana-2667	263	46	and	and	CCONJ
cana-2667	263	47	bias	bias	VERB
cana-2667	263	48	𝑏	𝑏	NOUN
cana-2667	263	49	for	for	ADP
cana-2667	263	50	the	the	DET
cana-2667	263	51	hyperplane	hyperplane	NOUN
cana-2667	263	52	:	:	PUNCT
cana-2667	263	53	𝐰	𝐰	X
cana-2667	263	54	=	=	SYM
cana-2667	263	55	0	0	NUM
cana-2667	263	56	,	,	PUNCT
cana-2667	263	57	 	 	SPACE
cana-2667	263	58	𝑏	𝑏	NOUN
cana-2667	263	59	=	=	NOUN
cana-2667	263	60	0	0	NUM
cana-2667	263	61	where	where	SCONJ
cana-2667	263	62	𝐰	𝐰	PROPN
cana-2667	263	63	is	be	AUX
cana-2667	263	64	a	a	DET
cana-2667	263	65	vector	vector	NOUN
cana-2667	263	66	and	and	CCONJ
cana-2667	263	67	𝑏	𝑏	NOUN
cana-2667	263	68	is	be	AUX
cana-2667	263	69	the	the	DET
cana-2667	263	70	scalar	scalar	ADJ
cana-2667	263	71	bias	bias	NOUN
cana-2667	263	72	.	.	PUNCT
cana-2667	264	1	2	2	X
cana-2667	264	2	.	.	X
cana-2667	264	3	optimization	optimization	NOUN
cana-2667	264	4	objective	objective	NOUN
cana-2667	264	5	(	(	PUNCT
cana-2667	264	6	maximizing	maximize	VERB
cana-2667	264	7	margin	margin	NOUN
cana-2667	264	8	):	):	PUNCT
cana-2667	264	9	the	the	DET
cana-2667	264	10	goal	goal	NOUN
cana-2667	264	11	is	be	AUX
cana-2667	264	12	to	to	PART
cana-2667	264	13	maximize	maximize	VERB
cana-2667	264	14	the	the	DET
cana-2667	264	15	margin	margin	NOUN
cana-2667	264	16	𝑀	𝑀	PROPN
cana-2667	264	17	between	between	ADP
cana-2667	264	18	classes	class	NOUN
cana-2667	264	19	,	,	PUNCT
cana-2667	264	20	subject	subject	ADJ
cana-2667	264	21	to	to	ADP
cana-2667	264	22	classification	classification	NOUN
cana-2667	264	23	constraints	constraint	NOUN
cana-2667	264	24	.	.	PUNCT
cana-2667	265	1	the	the	DET
cana-2667	265	2	optimization	optimization	NOUN
cana-2667	265	3	objective	objective	NOUN
cana-2667	265	4	is	be	AUX
cana-2667	265	5	:	:	PUNCT
cana-2667	265	6	min	min	X
cana-2667	265	7	𝐰,𝑏	𝐰,𝑏	NOUN
cana-2667	265	8	1	1	NUM
cana-2667	265	9	2	2	NUM
cana-2667	265	10	∥	∥	NUM
cana-2667	265	11	𝐰	𝐰	X
cana-2667	265	12	∥2	∥2	NOUN
cana-2667	265	13	 	 	SPACE
cana-2667	265	14	subject	subject	ADJ
cana-2667	265	15	to	to	ADP
cana-2667	265	16	 	 	SPACE
cana-2667	265	17	𝑌𝑖(𝐰	𝑌𝑖(𝐰	NOUN
cana-2667	265	18	𝑇𝑋𝑖	𝑇𝑋𝑖	NOUN
cana-2667	265	19	+	+	CCONJ
cana-2667	265	20	𝑏	𝑏	NOUN
cana-2667	265	21	)	)	PUNCT
cana-2667	265	22	≥	≥	NOUN
cana-2667	265	23	1	1	NUM
cana-2667	265	24	 	 	SPACE
cana-2667	265	25	∀𝑖	∀𝑖	PROPN
cana-2667	265	26	where	where	SCONJ
cana-2667	265	27	𝑋𝑖	𝑋𝑖	PROPN
cana-2667	265	28	is	be	AUX
cana-2667	265	29	the	the	DET
cana-2667	265	30	feature	feature	NOUN
cana-2667	265	31	vector	vector	NOUN
cana-2667	265	32	for	for	ADP
cana-2667	265	33	the	the	DET
cana-2667	265	34	𝑖-th	𝑖-th	PROPN
cana-2667	265	35	training	training	NOUN
cana-2667	265	36	sample	sample	NOUN
cana-2667	265	37	,	,	PUNCT
cana-2667	265	38	and	and	CCONJ
cana-2667	265	39	𝑌𝑖	𝑌𝑖	PROPN
cana-2667	265	40	is	be	AUX
cana-2667	265	41	the	the	DET
cana-2667	265	42	corresponding	corresponding	ADJ
cana-2667	265	43	label	label	NOUN
cana-2667	265	44	.	.	PUNCT
cana-2667	266	1	3	3	X
cana-2667	266	2	.	.	PUNCT
cana-2667	266	3	kernel	kernel	PROPN
cana-2667	266	4	trick	trick	NOUN
cana-2667	266	5	(	(	PUNCT
cana-2667	266	6	non	non	ADJ
cana-2667	266	7	-	-	ADJ
cana-2667	266	8	linear	linear	ADJ
cana-2667	266	9	separation	separation	NOUN
cana-2667	266	10	):	):	PUNCT
cana-2667	266	11	for	for	ADP
cana-2667	266	12	non	non	ADJ
cana-2667	266	13	-	-	ADJ
cana-2667	266	14	linearly	linearly	ADV
cana-2667	266	15	separable	separable	ADJ
cana-2667	266	16	data	datum	NOUN
cana-2667	266	17	,	,	PUNCT
cana-2667	266	18	apply	apply	VERB
cana-2667	266	19	a	a	DET
cana-2667	266	20	kernel	kernel	NOUN
cana-2667	266	21	function	function	NOUN
cana-2667	266	22	𝐾(𝑋𝑖	𝐾(𝑋𝑖	VERB
cana-2667	266	23	,	,	PUNCT
cana-2667	266	24	𝑋𝑗	𝑋𝑗	PROPN
cana-2667	266	25	)	)	PUNCT
cana-2667	266	26	to	to	PART
cana-2667	266	27	map	map	VERB
cana-2667	266	28	the	the	DET
cana-2667	266	29	data	datum	NOUN
cana-2667	266	30	into	into	ADP
cana-2667	266	31	a	a	DET
cana-2667	266	32	higher	higher	ADV
cana-2667	266	33	-	-	PUNCT
cana-2667	266	34	dimensional	dimensional	ADJ
cana-2667	266	35	space	space	NOUN
cana-2667	266	36	:	:	PUNCT
cana-2667	266	37	𝐾(𝑋𝑖	𝐾(𝑋𝑖	VERB
cana-2667	266	38	,	,	PUNCT
cana-2667	266	39	𝑋𝑗	𝑋𝑗	PROPN
cana-2667	266	40	)	)	PUNCT
cana-2667	266	41	=	=	SYM
cana-2667	266	42	exp	exp	NOUN
cana-2667	266	43	(	(	PUNCT
cana-2667	266	44	−	−	PROPN
cana-2667	266	45	∥	∥	NUM
cana-2667	266	46	𝑋𝑖	𝑋𝑖	NOUN
cana-2667	266	47	−	−	NOUN
cana-2667	266	48	𝑋𝑗	𝑋𝑗	NOUN
cana-2667	266	49	∥	∥	X
cana-2667	266	50	2	2	NUM
cana-2667	266	51	2𝜎2	2𝜎2	NUM
cana-2667	266	52	)	)	PUNCT
cana-2667	266	53	where	where	SCONJ
cana-2667	266	54	𝜎	𝜎	PROPN
cana-2667	266	55	is	be	AUX
cana-2667	266	56	the	the	DET
cana-2667	266	57	kernel	kernel	PROPN
cana-2667	266	58	parameter	parameter	NOUN
cana-2667	266	59	.	.	PUNCT
cana-2667	267	1	communications	communication	NOUN
cana-2667	267	2	on	on	ADP
cana-2667	267	3	applied	apply	VERB
cana-2667	267	4	nonlinear	nonlinear	ADJ
cana-2667	267	5	analysis	analysis	NOUN
cana-2667	267	6	issn	issn	NOUN
cana-2667	267	7	:	:	PUNCT
cana-2667	267	8	1074	1074	NUM
cana-2667	267	9	-	-	PUNCT
cana-2667	267	10	133x	133x	NUM
cana-2667	267	11	vol	vol	NOUN
cana-2667	267	12	32	32	NUM
cana-2667	267	13	no	no	NOUN
cana-2667	267	14	.	.	PUNCT
cana-2667	268	1	3s	3s	NUM
cana-2667	268	2	(	(	PUNCT
cana-2667	268	3	2025	2025	NUM
cana-2667	268	4	)	)	PUNCT
cana-2667	268	5	393	393	NUM
cana-2667	268	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	268	7	4	4	NUM
cana-2667	268	8	.	.	PUNCT
cana-2667	268	9	solving	solve	VERB
cana-2667	268	10	the	the	DET
cana-2667	268	11	optimization	optimization	NOUN
cana-2667	268	12	problem	problem	NOUN
cana-2667	268	13	:	:	PUNCT
cana-2667	268	14	use	use	VERB
cana-2667	268	15	quadratic	quadratic	ADJ
cana-2667	268	16	programming	programming	NOUN
cana-2667	268	17	to	to	PART
cana-2667	268	18	solve	solve	VERB
cana-2667	268	19	for	for	ADP
cana-2667	268	20	𝐰	𝐰	PROPN
cana-2667	268	21	and	and	CCONJ
cana-2667	268	22	𝑏.	𝑏.	VERB
cana-2667	268	23	the	the	DET
cana-2667	268	24	final	final	ADJ
cana-2667	268	25	decision	decision	NOUN
cana-2667	268	26	function	function	NOUN
cana-2667	268	27	is	be	AUX
cana-2667	268	28	:	:	PUNCT
cana-2667	268	29	𝑓(𝑋	𝑓(𝑋	NUM
cana-2667	268	30	)	)	PUNCT
cana-2667	269	1	=	=	PUNCT
cana-2667	269	2	sign(𝐰𝑇𝑋	sign(𝐰𝑇𝑋	PROPN
cana-2667	269	3	+	+	CCONJ
cana-2667	269	4	𝑏	𝑏	NOUN
cana-2667	269	5	)	)	PUNCT
cana-2667	269	6	where	where	SCONJ
cana-2667	269	7	𝑓(𝑋	𝑓(𝑋	NUM
cana-2667	269	8	)	)	PUNCT
cana-2667	269	9	is	be	AUX
cana-2667	269	10	the	the	DET
cana-2667	269	11	classification	classification	NOUN
cana-2667	269	12	result	result	NOUN
cana-2667	269	13	:	:	PUNCT
cana-2667	269	14	1	1	NUM
cana-2667	269	15	for	for	ADP
cana-2667	269	16	diseased	diseased	ADJ
cana-2667	269	17	,	,	PUNCT
cana-2667	269	18	0	0	NUM
cana-2667	269	19	for	for	ADP
cana-2667	269	20	healthy	healthy	ADJ
cana-2667	269	21	.	.	PUNCT
cana-2667	270	1	unfortunately	unfortunately	ADV
cana-2667	270	2	,	,	PUNCT
cana-2667	270	3	this	this	PRON
cana-2667	270	4	is	be	AUX
cana-2667	270	5	a	a	DET
cana-2667	270	6	rare	rare	ADJ
cana-2667	270	7	scenario	scenario	NOUN
cana-2667	270	8	and	and	CCONJ
cana-2667	270	9	in	in	ADP
cana-2667	270	10	a	a	DET
cana-2667	270	11	majority	majority	NOUN
cana-2667	270	12	,	,	PUNCT
cana-2667	270	13	the	the	DET
cana-2667	270	14	retinal	retinal	ADJ
cana-2667	270	15	image	image	NOUN
cana-2667	270	16	data	datum	NOUN
cana-2667	270	17	is	be	AUX
cana-2667	270	18	not	not	PART
cana-2667	270	19	linearly	linearly	ADV
cana-2667	270	20	separable	separable	ADJ
cana-2667	270	21	in	in	ADP
cana-2667	270	22	its	its	PRON
cana-2667	270	23	native	native	ADJ
cana-2667	270	24	form	form	NOUN
cana-2667	270	25	.	.	PUNCT
cana-2667	271	1	to	to	PART
cana-2667	271	2	deal	deal	VERB
cana-2667	271	3	with	with	ADP
cana-2667	271	4	this	this	PRON
cana-2667	271	5	,	,	PUNCT
cana-2667	271	6	the	the	DET
cana-2667	271	7	svm	svm	PROPN
cana-2667	271	8	employs	employ	VERB
cana-2667	271	9	a	a	DET
cana-2667	271	10	technique	technique	NOUN
cana-2667	271	11	called	call	VERB
cana-2667	271	12	the	the	DET
cana-2667	271	13	kernel	kernel	NOUN
cana-2667	271	14	trick	trick	NOUN
cana-2667	271	15	.	.	PUNCT
cana-2667	272	1	the	the	DET
cana-2667	272	2	kernel	kernel	PROPN
cana-2667	272	3	applied	apply	VERB
cana-2667	272	4	takes	take	VERB
cana-2667	272	5	the	the	DET
cana-2667	272	6	input	input	NOUN
cana-2667	272	7	data	datum	NOUN
cana-2667	272	8	and	and	CCONJ
cana-2667	272	9	maps	map	VERB
cana-2667	272	10	it	it	PRON
cana-2667	272	11	into	into	ADP
cana-2667	272	12	a	a	DET
cana-2667	272	13	higher	high	ADJ
cana-2667	272	14	dimension	dimension	NOUN
cana-2667	272	15	for	for	ADP
cana-2667	272	16	classification	classification	NOUN
cana-2667	272	17	through	through	ADP
cana-2667	272	18	using	use	VERB
cana-2667	272	19	a	a	DET
cana-2667	272	20	hyperplane	hyperplane	NOUN
cana-2667	272	21	.	.	PUNCT
cana-2667	273	1	one	one	NUM
cana-2667	273	2	such	such	ADJ
cana-2667	273	3	commonly	commonly	ADV
cana-2667	273	4	employed	employ	VERB
cana-2667	273	5	kernel	kernel	NOUN
cana-2667	273	6	is	be	AUX
cana-2667	273	7	the	the	DET
cana-2667	273	8	radial	radial	ADJ
cana-2667	273	9	basis	basis	NOUN
cana-2667	273	10	function	function	NOUN
cana-2667	273	11	(	(	PUNCT
cana-2667	273	12	rbf	rbf	PROPN
cana-2667	273	13	)	)	PUNCT
cana-2667	273	14	kernel	kernel	PROPN
cana-2667	273	15	,	,	PUNCT
cana-2667	273	16	which	which	PRON
cana-2667	273	17	precisely	precisely	ADV
cana-2667	273	18	accomplishes	accomplish	VERB
cana-2667	273	19	the	the	DET
cana-2667	273	20	mapping	mapping	NOUN
cana-2667	273	21	of	of	ADP
cana-2667	273	22	non	non	ADJ
cana-2667	273	23	-	-	ADJ
cana-2667	273	24	linearly	linearly	ADV
cana-2667	273	25	separable	separable	ADJ
cana-2667	273	26	data	datum	NOUN
cana-2667	273	27	into	into	ADP
cana-2667	273	28	higher	high	ADJ
cana-2667	273	29	dimensional	dimensional	ADJ
cana-2667	273	30	space	space	NOUN
cana-2667	273	31	making	make	VERB
cana-2667	273	32	them	they	PRON
cana-2667	273	33	linearly	linearly	ADV
cana-2667	273	34	separable	separable	ADJ
cana-2667	273	35	.	.	PUNCT
cana-2667	274	1	training	train	VERB
cana-2667	274	2	the	the	DET
cana-2667	274	3	svm	svm	PROPN
cana-2667	274	4	involves	involve	VERB
cana-2667	274	5	finding	find	VERB
cana-2667	274	6	the	the	DET
cana-2667	274	7	hyperplane	hyperplane	NOUN
cana-2667	274	8	that	that	PRON
cana-2667	274	9	best	well	ADV
cana-2667	274	10	separates	separate	VERB
cana-2667	274	11	the	the	DET
cana-2667	274	12	classes	class	NOUN
cana-2667	274	13	with	with	ADP
cana-2667	274	14	minimal	minimal	ADJ
cana-2667	274	15	classification	classification	NOUN
cana-2667	274	16	error	error	NOUN
cana-2667	274	17	,	,	PUNCT
cana-2667	274	18	using	use	VERB
cana-2667	274	19	only	only	ADV
cana-2667	274	20	the	the	DET
cana-2667	274	21	features	feature	NOUN
cana-2667	274	22	extracted	extract	VERB
cana-2667	274	23	by	by	ADP
cana-2667	274	24	the	the	DET
cana-2667	274	25	cnn	cnn	PROPN
cana-2667	274	26	.	.	PUNCT
cana-2667	275	1	can	can	AUX
cana-2667	275	2	you	you	PRON
cana-2667	275	3	tell	tell	VERB
cana-2667	275	4	a	a	DET
cana-2667	275	5	bit	bit	NOUN
cana-2667	275	6	about	about	ADP
cana-2667	275	7	the	the	DET
cana-2667	275	8	optimization	optimization	NOUN
cana-2667	275	9	procedure	procedure	NOUN
cana-2667	275	10	typically	typically	ADV
cana-2667	275	11	,	,	PUNCT
cana-2667	275	12	it	it	PRON
cana-2667	275	13	is	be	AUX
cana-2667	275	14	solved	solve	VERB
cana-2667	275	15	with	with	ADP
cana-2667	275	16	the	the	DET
cana-2667	275	17	help	help	NOUN
cana-2667	275	18	of	of	ADP
cana-2667	275	19	quadratic	quadratic	ADJ
cana-2667	275	20	programming	programming	NOUN
cana-2667	275	21	by	by	ADP
cana-2667	275	22	maximizing	maximize	VERB
cana-2667	275	23	the	the	DET
cana-2667	275	24	margin	margin	NOUN
cana-2667	275	25	while	while	SCONJ
cana-2667	275	26	applying	apply	VERB
cana-2667	275	27	penalization	penalization	NOUN
cana-2667	275	28	for	for	ADP
cana-2667	275	29	the	the	DET
cana-2667	275	30	misclassification	misclassification	NOUN
cana-2667	275	31	with	with	ADP
cana-2667	275	32	the	the	DET
cana-2667	275	33	help	help	NOUN
cana-2667	275	34	of	of	ADP
cana-2667	275	35	the	the	DET
cana-2667	275	36	regularization	regularization	NOUN
cana-2667	275	37	parameter	parameter	NOUN
cana-2667	275	38	(	(	PUNCT
cana-2667	275	39	c	c	X
cana-2667	275	40	)	)	PUNCT
cana-2667	275	41	the	the	DET
cana-2667	275	42	trained	train	VERB
cana-2667	275	43	model	model	NOUN
cana-2667	275	44	can	can	AUX
cana-2667	275	45	then	then	ADV
cana-2667	275	46	classify	classify	VERB
cana-2667	275	47	unreleased	unrelease	VERB
cana-2667	275	48	retinal	retinal	ADJ
cana-2667	275	49	images	image	NOUN
cana-2667	275	50	into	into	ADP
cana-2667	275	51	base	base	ADJ
cana-2667	275	52	classes	class	NOUN
cana-2667	275	53	such	such	ADJ
cana-2667	275	54	as	as	ADP
cana-2667	275	55	various	various	ADJ
cana-2667	275	56	stages	stage	NOUN
cana-2667	275	57	of	of	ADP
cana-2667	275	58	retinopathy	retinopathy	ADJ
cana-2667	275	59	or	or	CCONJ
cana-2667	275	60	healthy	healthy	ADJ
cana-2667	275	61	vs.	vs.	ADP
cana-2667	275	62	diseased	diseased	ADJ
cana-2667	275	63	.	.	PUNCT
cana-2667	276	1	hybrid	hybrid	ADJ
cana-2667	276	2	approach	approach	NOUN
cana-2667	276	3	:	:	PUNCT
cana-2667	276	4	cnn	cnn	PROPN
cana-2667	276	5	+	+	CCONJ
cana-2667	276	6	svm	svm	ADJ
cana-2667	276	7	integration	integration	NOUN
cana-2667	276	8	we	we	PRON
cana-2667	276	9	are	be	AUX
cana-2667	276	10	using	use	VERB
cana-2667	276	11	cnns	cnn	NOUN
cana-2667	276	12	for	for	ADP
cana-2667	276	13	feature	feature	NOUN
cana-2667	276	14	extraction	extraction	NOUN
cana-2667	276	15	and	and	CCONJ
cana-2667	276	16	combining	combine	VERB
cana-2667	276	17	them	they	PRON
cana-2667	276	18	with	with	ADP
cana-2667	276	19	svms	svms	NOUN
cana-2667	276	20	for	for	ADP
cana-2667	276	21	classification	classification	NOUN
cana-2667	276	22	to	to	PART
cana-2667	276	23	get	get	VERB
cana-2667	276	24	a	a	DET
cana-2667	276	25	hybrid	hybrid	ADJ
cana-2667	276	26	model	model	NOUN
cana-2667	276	27	that	that	PRON
cana-2667	276	28	utilizes	utilize	VERB
cana-2667	276	29	the	the	DET
cana-2667	276	30	best	good	ADJ
cana-2667	276	31	of	of	ADP
cana-2667	276	32	both	both	DET
cana-2667	276	33	worlds	world	NOUN
cana-2667	276	34	.	.	PUNCT
cana-2667	277	1	one	one	NUM
cana-2667	277	2	of	of	ADP
cana-2667	277	3	cnns	cnns	PROPN
cana-2667	277	4	is	be	AUX
cana-2667	277	5	best	good	ADJ
cana-2667	277	6	at	at	ADP
cana-2667	277	7	extracting	extract	VERB
cana-2667	277	8	complex	complex	ADJ
cana-2667	277	9	features	feature	NOUN
cana-2667	277	10	automatically	automatically	ADV
cana-2667	277	11	from	from	ADP
cana-2667	277	12	raw	raw	ADJ
cana-2667	277	13	image	image	NOUN
cana-2667	277	14	data	datum	NOUN
cana-2667	277	15	,	,	PUNCT
cana-2667	277	16	and	and	CCONJ
cana-2667	277	17	svms	svms	NOUN
cana-2667	277	18	are	be	AUX
cana-2667	277	19	best	good	ADJ
cana-2667	277	20	for	for	ADP
cana-2667	277	21	high	high	ADJ
cana-2667	277	22	-	-	PUNCT
cana-2667	277	23	dimensional	dimensional	ADJ
cana-2667	277	24	classification	classification	NOUN
cana-2667	277	25	tasks	task	NOUN
cana-2667	277	26	.	.	PUNCT
cana-2667	278	1	further	far	ADV
cana-2667	278	2	,	,	PUNCT
cana-2667	278	3	cnns	cnns	PROPN
cana-2667	278	4	can	can	AUX
cana-2667	278	5	automatically	automatically	ADV
cana-2667	278	6	extract	extract	VERB
cana-2667	278	7	relevant	relevant	ADJ
cana-2667	278	8	features	feature	NOUN
cana-2667	278	9	from	from	ADP
cana-2667	278	10	the	the	DET
cana-2667	278	11	input	input	NOUN
cana-2667	278	12	data	datum	NOUN
cana-2667	278	13	,	,	PUNCT
cana-2667	278	14	while	while	SCONJ
cana-2667	278	15	svm	svm	PROPN
cana-2667	278	16	develops	develop	VERB
cana-2667	278	17	to	to	ADP
cana-2667	278	18	high	high	ADJ
cana-2667	278	19	dimensional	dimensional	ADJ
cana-2667	278	20	classification	classification	NOUN
cana-2667	278	21	tasks	task	NOUN
cana-2667	278	22	.	.	PUNCT
cana-2667	279	1	by	by	ADP
cana-2667	279	2	combining	combine	VERB
cana-2667	279	3	the	the	DET
cana-2667	279	4	deep	deep	ADJ
cana-2667	279	5	learning	learning	NOUN
cana-2667	279	6	features	feature	VERB
cana-2667	279	7	with	with	ADP
cana-2667	279	8	the	the	DET
cana-2667	279	9	rich	rich	ADJ
cana-2667	279	10	texture	texture	NOUN
cana-2667	279	11	the	the	DET
cana-2667	279	12	retinal	retinal	ADJ
cana-2667	279	13	images	image	NOUN
cana-2667	279	14	provide	provide	VERB
cana-2667	279	15	,	,	PUNCT
cana-2667	279	16	a	a	DET
cana-2667	279	17	system	system	NOUN
cana-2667	279	18	that	that	PRON
cana-2667	279	19	can	can	AUX
cana-2667	279	20	comprehend	comprehend	VERB
cana-2667	279	21	highly	highly	ADV
cana-2667	279	22	complex	complex	ADJ
cana-2667	279	23	patterns	pattern	NOUN
cana-2667	279	24	and	and	CCONJ
cana-2667	279	25	group	group	NOUN
cana-2667	279	26	them	they	PRON
cana-2667	279	27	into	into	ADP
cana-2667	279	28	lipid	lipid	NOUN
cana-2667	279	29	classification	classification	NOUN
cana-2667	279	30	becomes	become	VERB
cana-2667	279	31	possible	possible	ADJ
cana-2667	279	32	.	.	PUNCT
cana-2667	280	1	this	this	DET
cana-2667	280	2	approach	approach	NOUN
cana-2667	280	3	uses	use	VERB
cana-2667	280	4	a	a	DET
cana-2667	280	5	sequential	sequential	ADJ
cana-2667	280	6	pipeline	pipeline	NOUN
cana-2667	280	7	of	of	ADP
cana-2667	280	8	cnn	cnn	PROPN
cana-2667	280	9	followed	follow	VERB
cana-2667	280	10	by	by	ADP
cana-2667	280	11	a	a	DET
cana-2667	280	12	svm	svm	NOUN
cana-2667	280	13	.	.	PROPN
cana-2667	281	1	in	in	ADP
cana-2667	281	2	the	the	DET
cana-2667	281	3	first	first	ADJ
cana-2667	281	4	process	process	NOUN
cana-2667	281	5	,	,	PUNCT
cana-2667	281	6	the	the	DET
cana-2667	281	7	cnn	cnn	PROPN
cana-2667	281	8	is	be	AUX
cana-2667	281	9	learned	learn	VERB
cana-2667	281	10	from	from	ADP
cana-2667	281	11	a	a	DET
cana-2667	281	12	number	number	NOUN
cana-2667	281	13	of	of	ADP
cana-2667	281	14	labelled	label	VERB
cana-2667	281	15	retinal	retinal	ADJ
cana-2667	281	16	images	image	NOUN
cana-2667	281	17	and	and	CCONJ
cana-2667	281	18	the	the	DET
cana-2667	281	19	complex	complex	ADJ
cana-2667	281	20	features	feature	NOUN
cana-2667	281	21	that	that	PRON
cana-2667	281	22	define	define	VERB
cana-2667	281	23	different	different	ADJ
cana-2667	281	24	stages	stage	NOUN
cana-2667	281	25	of	of	ADP
cana-2667	281	26	diabetic	diabetic	ADJ
cana-2667	281	27	retinopathy	retinopathy	NOUN
cana-2667	281	28	.	.	PUNCT
cana-2667	282	1	after	after	ADP
cana-2667	282	2	extracting	extract	VERB
cana-2667	282	3	the	the	DET
cana-2667	282	4	features	feature	NOUN
cana-2667	282	5	from	from	ADP
cana-2667	282	6	the	the	DET
cana-2667	282	7	cnn	cnn	PROPN
cana-2667	282	8	,	,	PUNCT
cana-2667	282	9	the	the	DET
cana-2667	282	10	abstracted	abstract	VERB
cana-2667	282	11	features	feature	NOUN
cana-2667	282	12	are	be	AUX
cana-2667	282	13	passed	pass	VERB
cana-2667	282	14	to	to	ADP
cana-2667	282	15	the	the	DET
cana-2667	282	16	svm	svm	NOUN
cana-2667	282	17	for	for	ADP
cana-2667	282	18	final	final	ADJ
cana-2667	282	19	classification	classification	NOUN
cana-2667	282	20	.	.	PUNCT
cana-2667	283	1	using	use	VERB
cana-2667	283	2	image	image	NOUN
cana-2667	283	3	segmentation	segmentation	NOUN
cana-2667	283	4	to	to	PART
cana-2667	283	5	isolate	isolate	VERB
cana-2667	283	6	the	the	DET
cana-2667	283	7	part	part	NOUN
cana-2667	283	8	of	of	ADP
cana-2667	283	9	the	the	DET
cana-2667	283	10	retinal	retinal	ADJ
cana-2667	283	11	image	image	NOUN
cana-2667	283	12	we	we	PRON
cana-2667	283	13	are	be	AUX
cana-2667	283	14	interested	interested	ADJ
cana-2667	283	15	in	in	ADP
cana-2667	283	16	along	along	ADP
cana-2667	283	17	with	with	ADP
cana-2667	283	18	classification	classification	NOUN
cana-2667	283	19	to	to	PART
cana-2667	283	20	identify	identify	VERB
cana-2667	283	21	whether	whether	SCONJ
cana-2667	283	22	there	there	PRON
cana-2667	283	23	's	be	VERB
cana-2667	283	24	a	a	DET
cana-2667	283	25	problem	problem	NOUN
cana-2667	283	26	—	—	PUNCT
cana-2667	283	27	makes	make	VERB
cana-2667	283	28	this	this	PRON
cana-2667	283	29	a	a	DET
cana-2667	283	30	twostep	twostep	NOUN
cana-2667	283	31	segmentation	segmentation	NOUN
cana-2667	283	32	-	-	PUNCT
cana-2667	283	33	classification	classification	NOUN
cana-2667	283	34	process	process	NOUN
cana-2667	283	35	,	,	PUNCT
cana-2667	283	36	which	which	PRON
cana-2667	283	37	leads	lead	VERB
cana-2667	283	38	to	to	ADP
cana-2667	283	39	automatic	automatic	ADJ
cana-2667	283	40	analysis	analysis	NOUN
cana-2667	283	41	of	of	ADP
cana-2667	283	42	the	the	DET
cana-2667	283	43	retinal	retinal	ADJ
cana-2667	283	44	images	image	NOUN
cana-2667	283	45	.	.	PUNCT
cana-2667	284	1	this	this	PRON
cana-2667	284	2	can	can	AUX
cana-2667	284	3	help	help	VERB
cana-2667	284	4	clinicians	clinician	NOUN
cana-2667	284	5	make	make	VERB
cana-2667	284	6	timely	timely	ADV
cana-2667	284	7	diagnoss	diagnoss	ADJ
cana-2667	284	8	.	.	PUNCT
cana-2667	285	1	algorithm	algorithm	PROPN
cana-2667	285	2	3	3	NUM
cana-2667	285	3	:	:	PUNCT
cana-2667	285	4	hybrid	hybrid	ADJ
cana-2667	285	5	cnn	cnn	PROPN
cana-2667	285	6	-	-	PUNCT
cana-2667	285	7	svm	svm	PROPN
cana-2667	285	8	training	training	NOUN
cana-2667	285	9	and	and	CCONJ
cana-2667	285	10	classification	classification	NOUN
cana-2667	285	11	input	input	NOUN
cana-2667	285	12	:	:	PUNCT
cana-2667	285	13	•	•	NUM
cana-2667	285	14	𝐼	𝐼	PROPN
cana-2667	285	15	:	:	PUNCT
cana-2667	285	16	input	input	NOUN
cana-2667	285	17	image	image	NOUN
cana-2667	285	18	(	(	PUNCT
cana-2667	285	19	retinal	retinal	ADJ
cana-2667	285	20	scan	scan	NOUN
cana-2667	285	21	)	)	PUNCT
cana-2667	285	22	•	•	ADP
cana-2667	285	23	𝑋𝑡𝑟𝑎𝑖𝑛	𝑋𝑡𝑟𝑎𝑖𝑛	NOUN
cana-2667	285	24	:	:	PUNCT
cana-2667	285	25	training	training	NOUN
cana-2667	285	26	feature	feature	NOUN
cana-2667	285	27	set	set	VERB
cana-2667	285	28	from	from	ADP
cana-2667	285	29	cnn	cnn	PROPN
cana-2667	285	30	•	•	PROPN
cana-2667	285	31	𝑌𝑡𝑟𝑎𝑖𝑛	𝑌𝑡𝑟𝑎𝑖𝑛	PROPN
cana-2667	285	32	:	:	PUNCT
cana-2667	285	33	corresponding	correspond	VERB
cana-2667	285	34	labels	label	NOUN
cana-2667	285	35	for	for	ADP
cana-2667	285	36	training	training	NOUN
cana-2667	285	37	data	datum	NOUN
cana-2667	285	38	•	•	PRON
cana-2667	285	39	𝐶	𝐶	PROPN
cana-2667	285	40	:	:	PUNCT
cana-2667	285	41	regularization	regularization	NOUN
cana-2667	285	42	parameter	parameter	NOUN
cana-2667	285	43	for	for	ADP
cana-2667	285	44	svm	svm	ADJ
cana-2667	285	45	communications	communication	NOUN
cana-2667	285	46	on	on	ADP
cana-2667	285	47	applied	apply	VERB
cana-2667	285	48	nonlinear	nonlinear	ADJ
cana-2667	285	49	analysis	analysis	NOUN
cana-2667	285	50	issn	issn	NOUN
cana-2667	285	51	:	:	PUNCT
cana-2667	285	52	1074	1074	NUM
cana-2667	285	53	-	-	PUNCT
cana-2667	285	54	133x	133x	NUM
cana-2667	285	55	vol	vol	NOUN
cana-2667	285	56	32	32	NUM
cana-2667	285	57	no	no	NOUN
cana-2667	285	58	.	.	PUNCT
cana-2667	286	1	3s	3s	NUM
cana-2667	286	2	(	(	PUNCT
cana-2667	286	3	2025	2025	NUM
cana-2667	286	4	)	)	PUNCT
cana-2667	286	5	394	394	NUM
cana-2667	286	6	https://internationalpubls.com	https://internationalpubls.com	SYM
cana-2667	286	7	•	•	NUM
cana-2667	286	8	𝐾	𝐾	PROPN
cana-2667	286	9	:	:	PUNCT
cana-2667	286	10	kernel	kernel	PROPN
cana-2667	286	11	function	function	PROPN
cana-2667	286	12	(	(	PUNCT
cana-2667	286	13	rbf	rbf	PROPN
cana-2667	286	14	kernel	kernel	PROPN
cana-2667	286	15	)	)	PUNCT
cana-2667	286	16	output	output	NOUN
cana-2667	286	17	:	:	PUNCT
cana-2667	286	18	•	•	NUM
cana-2667	286	19	𝐰	𝐰	NOUN
cana-2667	286	20	:	:	PUNCT
cana-2667	286	21	learned	learn	VERB
cana-2667	286	22	weights	weight	NOUN
cana-2667	286	23	of	of	ADP
cana-2667	286	24	svm	svm	ADJ
cana-2667	286	25	classifier	classifier	NOUN
cana-2667	286	26	•	•	ADP
cana-2667	286	27	𝑏	𝑏	PROPN
cana-2667	286	28	:	:	PUNCT
cana-2667	286	29	learned	learn	VERB
cana-2667	286	30	bias	bias	NOUN
cana-2667	286	31	of	of	ADP
cana-2667	286	32	svm	svm	ADJ
cana-2667	286	33	classifier	classifier	NOUN
cana-2667	286	34	•	•	ADP
cana-2667	286	35	𝑌𝑝𝑟𝑒𝑑	𝑌𝑝𝑟𝑒𝑑	PROPN
cana-2667	286	36	:	:	PUNCT
cana-2667	286	37	predicted	predict	VERB
cana-2667	286	38	class	class	NOUN
cana-2667	286	39	labels	label	NOUN
cana-2667	286	40	for	for	ADP
cana-2667	286	41	new	new	ADJ
cana-2667	286	42	images	image	NOUN
cana-2667	286	43	steps	step	NOUN
cana-2667	286	44	:	:	PUNCT
cana-2667	286	45	1	1	X
cana-2667	286	46	.	.	X
cana-2667	286	47	image	image	NOUN
cana-2667	286	48	preprocessing	preprocessing	NOUN
cana-2667	286	49	:	:	PUNCT
cana-2667	286	50	preprocess	preprocess	VERB
cana-2667	286	51	the	the	DET
cana-2667	286	52	retinal	retinal	ADJ
cana-2667	286	53	image	image	NOUN
cana-2667	286	54	𝐼	𝐼	ADP
cana-2667	286	55	by	by	ADP
cana-2667	286	56	resizing	resize	VERB
cana-2667	286	57	,	,	PUNCT
cana-2667	286	58	normalizing	normalizing	NOUN
cana-2667	286	59	,	,	PUNCT
cana-2667	286	60	and	and	CCONJ
cana-2667	286	61	enhancing	enhance	VERB
cana-2667	286	62	contrast	contrast	NOUN
cana-2667	286	63	:	:	PUNCT
cana-2667	287	1	𝐼preprocessed	𝐼preprocessed	PROPN
cana-2667	287	2	=	=	SYM
cana-2667	287	3	preprocess(𝐼	preprocess(𝐼	PROPN
cana-2667	287	4	)	)	PUNCT
cana-2667	287	5	2	2	NUM
cana-2667	287	6	.	.	PUNCT
cana-2667	287	7	feature	feature	NOUN
cana-2667	287	8	extraction	extraction	NOUN
cana-2667	287	9	via	via	ADP
cana-2667	287	10	cnn	cnn	PROPN
cana-2667	287	11	:	:	PUNCT
cana-2667	287	12	pass	pass	VERB
cana-2667	287	13	the	the	DET
cana-2667	287	14	preprocessed	preprocesse	VERB
cana-2667	287	15	image	image	NOUN
cana-2667	287	16	through	through	ADP
cana-2667	287	17	the	the	DET
cana-2667	287	18	cnn	cnn	PROPN
cana-2667	287	19	to	to	PART
cana-2667	287	20	extract	extract	VERB
cana-2667	287	21	relevant	relevant	ADJ
cana-2667	287	22	features	feature	NOUN
cana-2667	287	23	:	:	PUNCT
cana-2667	287	24	𝑋	𝑋	NOUN
cana-2667	287	25	=	=	SYM
cana-2667	287	26	cnn(𝐼preprocessed	cnn(𝐼preprocesse	VERB
cana-2667	287	27	)	)	PUNCT
cana-2667	287	28	where	where	SCONJ
cana-2667	287	29	𝑋	𝑋	PROPN
cana-2667	287	30	is	be	AUX
cana-2667	287	31	the	the	DET
cana-2667	287	32	feature	feature	NOUN
cana-2667	287	33	vector	vector	NOUN
cana-2667	287	34	extracted	extract	VERB
cana-2667	287	35	from	from	ADP
cana-2667	287	36	the	the	DET
cana-2667	287	37	image	image	NOUN
cana-2667	287	38	.	.	PUNCT
cana-2667	288	1	3	3	X
cana-2667	288	2	.	.	X
cana-2667	288	3	train	train	NOUN
cana-2667	288	4	svm	svm	PROPN
cana-2667	288	5	classifier	classifier	NOUN
cana-2667	288	6	:	:	PUNCT
cana-2667	288	7	train	train	VERB
cana-2667	288	8	the	the	DET
cana-2667	288	9	svm	svm	ADJ
cana-2667	288	10	classifier	classifier	NOUN
cana-2667	288	11	using	use	VERB
cana-2667	288	12	the	the	DET
cana-2667	288	13	training	training	NOUN
cana-2667	288	14	feature	feature	NOUN
cana-2667	288	15	set	set	VERB
cana-2667	288	16	𝑋𝑡𝑟𝑎𝑖𝑛	𝑋𝑡𝑟𝑎𝑖𝑛	NOUN
cana-2667	288	17	and	and	CCONJ
cana-2667	288	18	labels	label	NOUN
cana-2667	288	19	𝑌𝑡𝑟𝑎𝑖𝑛	𝑌𝑡𝑟𝑎𝑖𝑛	PROPN
cana-2667	288	20	:	:	PUNCT
cana-2667	288	21	𝐰	𝐰	X
cana-2667	288	22	,	,	PUNCT
cana-2667	288	23	𝑏	𝑏	PROPN
cana-2667	288	24	=	=	PUNCT
cana-2667	288	25	train_svm(𝑋𝑡𝑟𝑎𝑖𝑛	train_svm(𝑋𝑡𝑟𝑎𝑖𝑛	PROPN
cana-2667	288	26	,	,	PUNCT
cana-2667	288	27	𝑌𝑡𝑟𝑎𝑖𝑛	𝑌𝑡𝑟𝑎𝑖𝑛	PROPN
cana-2667	288	28	,	,	PUNCT
cana-2667	288	29	𝐶	𝐶	PROPN
cana-2667	288	30	,	,	PUNCT
cana-2667	288	31	𝐾	𝐾	PROPN
cana-2667	288	32	)	)	PUNCT
cana-2667	288	33	where	where	SCONJ
cana-2667	288	34	train_svm	train_svm	NUM
cana-2667	288	35	solves	solve	VERB
cana-2667	288	36	the	the	DET
cana-2667	288	37	optimization	optimization	NOUN
cana-2667	288	38	problem	problem	NOUN
cana-2667	288	39	to	to	PART
cana-2667	288	40	learn	learn	VERB
cana-2667	288	41	the	the	DET
cana-2667	288	42	optimal	optimal	ADJ
cana-2667	288	43	hyperplane	hyperplane	NOUN
cana-2667	288	44	.	.	PUNCT
cana-2667	289	1	4	4	X
cana-2667	289	2	.	.	X
cana-2667	289	3	prediction	prediction	NOUN
cana-2667	289	4	:	:	PUNCT
cana-2667	289	5	given	give	VERB
cana-2667	289	6	a	a	DET
cana-2667	289	7	new	new	ADJ
cana-2667	289	8	retinal	retinal	ADJ
cana-2667	289	9	image	image	NOUN
cana-2667	289	10	,	,	PUNCT
cana-2667	289	11	extract	extract	VERB
cana-2667	289	12	its	its	PRON
cana-2667	289	13	features	feature	NOUN
cana-2667	289	14	using	use	VERB
cana-2667	289	15	the	the	DET
cana-2667	289	16	trained	train	VERB
cana-2667	289	17	cnn	cnn	NOUN
cana-2667	289	18	and	and	CCONJ
cana-2667	289	19	classify	classify	VERB
cana-2667	289	20	it	it	PRON
cana-2667	289	21	using	use	VERB
cana-2667	289	22	the	the	DET
cana-2667	289	23	trained	train	VERB
cana-2667	289	24	svm	svm	ADJ
cana-2667	289	25	model	model	NOUN
cana-2667	289	26	:	:	PUNCT
cana-2667	289	27	𝑋new	𝑋new	PROPN
cana-2667	289	28	=	=	SYM
cana-2667	289	29	cnn(𝐼new	cnn(𝐼new	ADJ
cana-2667	289	30	)	)	PUNCT
cana-2667	289	31	𝑌pred	𝑌pred	PROPN
cana-2667	289	32	=	=	SYM
cana-2667	289	33	svm_predict(𝑋new	svm_predict(𝑋new	ADJ
cana-2667	289	34	,	,	PUNCT
cana-2667	289	35	𝐰	𝐰	X
cana-2667	289	36	,	,	PUNCT
cana-2667	289	37	𝑏	𝑏	NOUN
cana-2667	289	38	)	)	PUNCT
cana-2667	289	39	where	where	SCONJ
cana-2667	289	40	𝑌pred	𝑌pred	PROPN
cana-2667	289	41	is	be	AUX
cana-2667	289	42	the	the	DET
cana-2667	289	43	predicted	predict	VERB
cana-2667	289	44	label	label	NOUN
cana-2667	289	45	(	(	PUNCT
cana-2667	289	46	either	either	CCONJ
cana-2667	289	47	0	0	NUM
cana-2667	289	48	or	or	CCONJ
cana-2667	289	49	1	1	NUM
cana-2667	289	50	,	,	PUNCT
cana-2667	289	51	representing	represent	VERB
cana-2667	289	52	healthy	healthy	ADJ
cana-2667	289	53	or	or	CCONJ
cana-2667	289	54	diseased	diseased	ADJ
cana-2667	289	55	)	)	PUNCT
cana-2667	289	56	.	.	PUNCT
cana-2667	290	1	the	the	DET
cana-2667	290	2	main	main	ADJ
cana-2667	290	3	benefit	benefit	NOUN
cana-2667	290	4	of	of	ADP
cana-2667	290	5	using	use	VERB
cana-2667	290	6	this	this	DET
cana-2667	290	7	hybrid	hybrid	ADJ
cana-2667	290	8	approach	approach	NOUN
cana-2667	290	9	should	should	AUX
cana-2667	290	10	be	be	AUX
cana-2667	290	11	its	its	PRON
cana-2667	290	12	less	less	ADJ
cana-2667	290	13	dependence	dependence	NOUN
cana-2667	290	14	on	on	ADP
cana-2667	290	15	manual	manual	ADJ
cana-2667	290	16	feature	feature	NOUN
cana-2667	290	17	engineering	engineering	NOUN
cana-2667	290	18	.	.	PUNCT
cana-2667	291	1	this	this	PRON
cana-2667	291	2	allows	allow	VERB
cana-2667	291	3	cnns	cnn	NOUN
cana-2667	291	4	to	to	PART
cana-2667	291	5	learn	learn	VERB
cana-2667	291	6	to	to	PART
cana-2667	291	7	extract	extract	VERB
cana-2667	291	8	the	the	DET
cana-2667	291	9	most	most	ADV
cana-2667	291	10	relevant	relevant	ADJ
cana-2667	291	11	features	feature	NOUN
cana-2667	291	12	directly	directly	ADV
cana-2667	291	13	from	from	ADP
cana-2667	291	14	the	the	DET
cana-2667	291	15	data	datum	NOUN
cana-2667	291	16	,	,	PUNCT
cana-2667	291	17	and	and	CCONJ
cana-2667	291	18	the	the	DET
cana-2667	291	19	svm	svm	PROPN
cana-2667	291	20	just	just	ADV
cana-2667	291	21	has	have	VERB
cana-2667	291	22	to	to	PART
cana-2667	291	23	classify	classify	VERB
cana-2667	291	24	.	.	PUNCT
cana-2667	292	1	it	it	PRON
cana-2667	292	2	enables	enable	VERB
cana-2667	292	3	the	the	DET
cana-2667	292	4	system	system	NOUN
cana-2667	292	5	to	to	PART
cana-2667	292	6	identify	identify	VERB
cana-2667	292	7	subtle	subtle	ADJ
cana-2667	292	8	characteristics	characteristic	NOUN
cana-2667	292	9	in	in	ADP
cana-2667	292	10	retinal	retinal	ADJ
cana-2667	292	11	images	image	NOUN
cana-2667	292	12	that	that	PRON
cana-2667	292	13	traditional	traditional	ADJ
cana-2667	292	14	techniques	technique	NOUN
cana-2667	292	15	might	might	AUX
cana-2667	292	16	overlook	overlook	VERB
cana-2667	292	17	.	.	PUNCT
cana-2667	293	1	moreover	moreover	ADV
cana-2667	293	2	,	,	PUNCT
cana-2667	293	3	svms	svms	VERB
cana-2667	293	4	help	help	NOUN
cana-2667	293	5	to	to	PART
cana-2667	293	6	improve	improve	VERB
cana-2667	293	7	the	the	DET
cana-2667	293	8	stability	stability	NOUN
cana-2667	293	9	of	of	ADP
cana-2667	293	10	the	the	DET
cana-2667	293	11	classification	classification	NOUN
cana-2667	293	12	process	process	NOUN
cana-2667	293	13	dealing	deal	VERB
cana-2667	293	14	with	with	ADP
cana-2667	293	15	fluctuations	fluctuation	NOUN
cana-2667	293	16	in	in	ADP
cana-2667	293	17	the	the	DET
cana-2667	293	18	data	datum	NOUN
cana-2667	293	19	,	,	PUNCT
cana-2667	293	20	such	such	ADJ
cana-2667	293	21	as	as	ADP
cana-2667	293	22	noise	noise	NOUN
cana-2667	293	23	,	,	PUNCT
cana-2667	293	24	illumination	illumination	NOUN
cana-2667	293	25	changes	change	NOUN
cana-2667	293	26	,	,	PUNCT
cana-2667	293	27	and	and	CCONJ
cana-2667	293	28	variations	variation	NOUN
cana-2667	293	29	in	in	ADP
cana-2667	293	30	image	image	NOUN
cana-2667	293	31	quality	quality	NOUN
cana-2667	293	32	,	,	PUNCT
cana-2667	293	33	which	which	PRON
cana-2667	293	34	are	be	AUX
cana-2667	293	35	very	very	ADV
cana-2667	293	36	common	common	ADJ
cana-2667	293	37	in	in	ADP
cana-2667	293	38	medical	medical	ADJ
cana-2667	293	39	imaging	imaging	NOUN
cana-2667	293	40	.	.	PUNCT
cana-2667	294	1	methods	method	NOUN
cana-2667	294	2	of	of	ADP
cana-2667	294	3	model	model	NOUN
cana-2667	294	4	improvement	improvement	NOUN
cana-2667	294	5	and	and	CCONJ
cana-2667	294	6	hyperparameter	hyperparameter	NOUN
cana-2667	294	7	tuning	tune	VERB
cana-2667	294	8	one	one	NUM
cana-2667	294	9	of	of	ADP
cana-2667	294	10	the	the	DET
cana-2667	294	11	major	major	ADJ
cana-2667	294	12	components	component	NOUN
cana-2667	294	13	in	in	ADP
cana-2667	294	14	the	the	DET
cana-2667	294	15	proposed	propose	VERB
cana-2667	294	16	methodology	methodology	NOUN
cana-2667	294	17	is	be	AUX
cana-2667	294	18	the	the	DET
cana-2667	294	19	optimization	optimization	NOUN
cana-2667	294	20	of	of	ADP
cana-2667	294	21	both	both	DET
cana-2667	294	22	cnn	cnn	PROPN
cana-2667	294	23	and	and	CCONJ
cana-2667	294	24	svm	svm	PROPN
cana-2667	294	25	.	.	PROPN
cana-2667	294	26	hyperparameters	hyperparameter	NOUN
cana-2667	294	27	of	of	ADP
cana-2667	294	28	the	the	DET
cana-2667	294	29	cnn	cnn	PROPN
cana-2667	294	30	,	,	PUNCT
cana-2667	294	31	including	include	VERB
cana-2667	294	32	the	the	DET
cana-2667	294	33	number	number	NOUN
cana-2667	294	34	of	of	ADP
cana-2667	294	35	layers	layer	NOUN
cana-2667	294	36	,	,	PUNCT
cana-2667	294	37	the	the	DET
cana-2667	294	38	filter	filter	NOUN
cana-2667	294	39	sizes	size	NOUN
cana-2667	294	40	,	,	PUNCT
cana-2667	294	41	the	the	DET
cana-2667	294	42	learning	learning	NOUN
cana-2667	294	43	rate	rate	NOUN
cana-2667	294	44	and	and	CCONJ
cana-2667	294	45	the	the	DET
cana-2667	294	46	batch	batch	NOUN
cana-2667	294	47	size	size	NOUN
cana-2667	294	48	,	,	PUNCT
cana-2667	294	49	must	must	AUX
cana-2667	294	50	be	be	AUX
cana-2667	294	51	finely	finely	ADV
cana-2667	294	52	tuned	tune	VERB
cana-2667	294	53	.	.	PUNCT
cana-2667	295	1	this	this	PRON
cana-2667	295	2	is	be	AUX
cana-2667	295	3	usually	usually	ADV
cana-2667	295	4	done	do	VERB
cana-2667	295	5	via	via	ADP
cana-2667	295	6	a	a	DET
cana-2667	295	7	method	method	NOUN
cana-2667	295	8	called	call	VERB
cana-2667	295	9	grid	grid	NOUN
cana-2667	295	10	search	search	NOUN
cana-2667	295	11	or	or	CCONJ
cana-2667	295	12	random	random	ADJ
cana-2667	295	13	search	search	NOUN
cana-2667	295	14	where	where	SCONJ
cana-2667	295	15	you	you	PRON
cana-2667	295	16	try	try	VERB
cana-2667	295	17	many	many	ADJ
cana-2667	295	18	combinations	combination	NOUN
cana-2667	295	19	of	of	ADP
cana-2667	295	20	the	the	DET
cana-2667	295	21	parameters	parameter	NOUN
cana-2667	295	22	and	and	CCONJ
cana-2667	295	23	evaluate	evaluate	VERB
cana-2667	295	24	the	the	DET
cana-2667	295	25	performance	performance	NOUN
cana-2667	295	26	of	of	ADP
cana-2667	295	27	that	that	PRON
cana-2667	295	28	on	on	ADP
cana-2667	295	29	a	a	DET
cana-2667	295	30	communications	communication	NOUN
cana-2667	295	31	on	on	ADP
cana-2667	295	32	applied	apply	VERB
cana-2667	295	33	nonlinear	nonlinear	ADJ
cana-2667	295	34	analysis	analysis	NOUN
cana-2667	295	35	issn	issn	NOUN
cana-2667	295	36	:	:	PUNCT
cana-2667	295	37	1074	1074	NUM
cana-2667	295	38	-	-	PUNCT
cana-2667	295	39	133x	133x	NUM
cana-2667	295	40	vol	vol	NOUN
cana-2667	295	41	32	32	NUM
cana-2667	295	42	no	no	NOUN
cana-2667	295	43	.	.	PUNCT
cana-2667	296	1	3s	3s	NUM
cana-2667	296	2	(	(	PUNCT
cana-2667	296	3	2025	2025	NUM
cana-2667	296	4	)	)	PUNCT
cana-2667	296	5	395	395	NUM
cana-2667	296	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	296	7	validation	validation	NOUN
cana-2667	296	8	set	set	NOUN
cana-2667	296	9	.	.	PUNCT
cana-2667	297	1	it	it	PRON
cana-2667	297	2	is	be	AUX
cana-2667	297	3	also	also	ADV
cana-2667	297	4	how	how	SCONJ
cana-2667	297	5	cross	cross	ADJ
cana-2667	297	6	-	-	ADJ
cana-2667	297	7	validation	validation	ADJ
cana-2667	297	8	techniques	technique	NOUN
cana-2667	297	9	are	be	AUX
cana-2667	297	10	used	use	VERB
cana-2667	297	11	to	to	PART
cana-2667	297	12	ensure	ensure	VERB
cana-2667	297	13	the	the	DET
cana-2667	297	14	model	model	NOUN
cana-2667	297	15	does	do	AUX
cana-2667	297	16	not	not	PART
cana-2667	297	17	overly	overly	ADV
cana-2667	297	18	subject	subject	ADJ
cana-2667	297	19	to	to	ADP
cana-2667	297	20	the	the	DET
cana-2667	297	21	training	training	NOUN
cana-2667	297	22	data	datum	NOUN
cana-2667	297	23	and	and	CCONJ
cana-2667	297	24	generalizes	generalize	VERB
cana-2667	297	25	well	well	ADV
cana-2667	297	26	to	to	ADP
cana-2667	297	27	unseen	unseen	ADJ
cana-2667	297	28	images	image	NOUN
cana-2667	297	29	.	.	PUNCT
cana-2667	298	1	the	the	DET
cana-2667	298	2	svm	svm	PROPN
cana-2667	298	3	also	also	ADV
cana-2667	298	4	needs	need	VERB
cana-2667	298	5	hyper	hyper	NOUN
cana-2667	298	6	-	-	NOUN
cana-2667	298	7	parameters	parameter	NOUN
cana-2667	298	8	to	to	PART
cana-2667	298	9	be	be	AUX
cana-2667	298	10	tuned	tune	VERB
cana-2667	298	11	in	in	ADP
cana-2667	298	12	similar	similar	ADJ
cana-2667	298	13	fashion	fashion	NOUN
cana-2667	298	14	.	.	PUNCT
cana-2667	299	1	key	key	ADJ
cana-2667	299	2	parameters	parameter	NOUN
cana-2667	299	3	of	of	ADP
cana-2667	299	4	svms	svms	NOUN
cana-2667	299	5	include	include	VERB
cana-2667	299	6	the	the	DET
cana-2667	299	7	regularization	regularization	NOUN
cana-2667	299	8	parameter	parameter	NOUN
cana-2667	299	9	\	\	PROPN
cana-2667	299	10	(	(	PUNCT
cana-2667	299	11	c	c	PROPN
cana-2667	299	12	\	\	PROPN
cana-2667	299	13	)	)	PUNCT
cana-2667	299	14	,	,	PUNCT
cana-2667	299	15	which	which	PRON
cana-2667	299	16	governs	govern	VERB
cana-2667	299	17	the	the	DET
cana-2667	299	18	trade	trade	NOUN
cana-2667	299	19	-	-	PUNCT
cana-2667	299	20	off	off	NOUN
cana-2667	299	21	between	between	ADP
cana-2667	299	22	creating	create	VERB
cana-2667	299	23	a	a	DET
cana-2667	299	24	large	large	ADJ
cana-2667	299	25	margin	margin	NOUN
cana-2667	299	26	and	and	CCONJ
cana-2667	299	27	reducing	reduce	VERB
cana-2667	299	28	misclassification	misclassification	NOUN
cana-2667	299	29	errors	error	NOUN
cana-2667	299	30	,	,	PUNCT
cana-2667	299	31	and	and	CCONJ
cana-2667	299	32	the	the	DET
cana-2667	299	33	kernel	kernel	PROPN
cana-2667	299	34	parameter	parameter	NOUN
cana-2667	299	35	\	\	PROPN
cana-2667	299	36	(	(	PUNCT
cana-2667	299	37	\sigma	\sigma	PROPN
cana-2667	299	38	\	\	PROPN
cana-2667	299	39	)	)	PUNCT
cana-2667	299	40	,	,	PUNCT
cana-2667	299	41	which	which	PRON
cana-2667	299	42	determines	determine	VERB
cana-2667	299	43	the	the	DET
cana-2667	299	44	width	width	NOUN
cana-2667	299	45	of	of	ADP
cana-2667	299	46	the	the	DET
cana-2667	299	47	kernel	kernel	NOUN
cana-2667	299	48	and	and	CCONJ
cana-2667	299	49	so	so	ADV
cana-2667	299	50	the	the	DET
cana-2667	299	51	smoothness	smoothness	NOUN
cana-2667	299	52	of	of	ADP
cana-2667	299	53	the	the	DET
cana-2667	299	54	decision	decision	NOUN
cana-2667	299	55	boundary	boundary	NOUN
cana-2667	299	56	.	.	PUNCT
cana-2667	300	1	the	the	DET
cana-2667	300	2	optimal	optimal	ADJ
cana-2667	300	3	values	value	NOUN
cana-2667	300	4	for	for	ADP
cana-2667	300	5	these	these	DET
cana-2667	300	6	parameters	parameter	NOUN
cana-2667	300	7	can	can	AUX
cana-2667	300	8	be	be	AUX
cana-2667	300	9	found	find	VERB
cana-2667	300	10	using	use	VERB
cana-2667	300	11	grid	grid	NOUN
cana-2667	300	12	search	search	NOUN
cana-2667	300	13	or	or	CCONJ
cana-2667	300	14	other	other	ADJ
cana-2667	300	15	optimization	optimization	NOUN
cana-2667	300	16	methods	method	NOUN
cana-2667	300	17	.	.	PUNCT
cana-2667	301	1	after	after	ADP
cana-2667	301	2	tuning	tune	VERB
cana-2667	301	3	both	both	CCONJ
cana-2667	301	4	the	the	DET
cana-2667	301	5	cnn	cnn	PROPN
cana-2667	301	6	and	and	CCONJ
cana-2667	301	7	svm	svm	ADJ
cana-2667	301	8	parts	part	NOUN
cana-2667	301	9	of	of	ADP
cana-2667	301	10	the	the	DET
cana-2667	301	11	model	model	NOUN
cana-2667	301	12	,	,	PUNCT
cana-2667	301	13	it	it	PRON
cana-2667	301	14	is	be	AUX
cana-2667	301	15	evaluated	evaluate	VERB
cana-2667	301	16	based	base	VERB
cana-2667	301	17	on	on	ADP
cana-2667	301	18	standard	standard	ADJ
cana-2667	301	19	performance	performance	NOUN
cana-2667	301	20	metrics	metric	NOUN
cana-2667	301	21	like	like	ADP
cana-2667	301	22	accuracy	accuracy	NOUN
cana-2667	301	23	,	,	PUNCT
cana-2667	301	24	precision	precision	NOUN
cana-2667	301	25	,	,	PUNCT
cana-2667	301	26	recall	recall	NOUN
cana-2667	301	27	,	,	PUNCT
cana-2667	301	28	and	and	CCONJ
cana-2667	301	29	f1	f1	NOUN
cana-2667	301	30	-	-	PUNCT
cana-2667	301	31	score	score	NOUN
cana-2667	301	32	.	.	PUNCT
cana-2667	302	1	these	these	DET
cana-2667	302	2	metrics	metric	NOUN
cana-2667	302	3	are	be	AUX
cana-2667	302	4	derived	derive	VERB
cana-2667	302	5	from	from	ADP
cana-2667	302	6	how	how	SCONJ
cana-2667	302	7	well	well	ADV
cana-2667	302	8	the	the	DET
cana-2667	302	9	model	model	NOUN
cana-2667	302	10	was	be	AUX
cana-2667	302	11	at	at	ADP
cana-2667	302	12	classifying	classify	VERB
cana-2667	302	13	retinal	retinal	ADJ
cana-2667	302	14	images	image	NOUN
cana-2667	302	15	accurately	accurately	ADV
cana-2667	302	16	,	,	PUNCT
cana-2667	302	17	and	and	CCONJ
cana-2667	302	18	they	they	PRON
cana-2667	302	19	provide	provide	VERB
cana-2667	302	20	insight	insight	NOUN
cana-2667	302	21	into	into	ADP
cana-2667	302	22	the	the	DET
cana-2667	302	23	performance	performance	NOUN
cana-2667	302	24	strengths	strength	NOUN
cana-2667	302	25	and	and	CCONJ
cana-2667	302	26	weaknesses	weakness	NOUN
cana-2667	302	27	of	of	ADP
cana-2667	302	28	the	the	DET
cana-2667	302	29	model	model	NOUN
cana-2667	302	30	.	.	PUNCT
cana-2667	303	1	to	to	PART
cana-2667	303	2	ensure	ensure	VERB
cana-2667	303	3	that	that	SCONJ
cana-2667	303	4	the	the	DET
cana-2667	303	5	model	model	NOUN
cana-2667	303	6	's	's	PART
cana-2667	303	7	performance	performance	NOUN
cana-2667	303	8	estimation	estimation	NOUN
cana-2667	303	9	is	be	AUX
cana-2667	303	10	not	not	PART
cana-2667	303	11	affected	affect	VERB
cana-2667	303	12	by	by	ADP
cana-2667	303	13	overfitting	overfitte	VERB
cana-2667	303	14	on	on	ADP
cana-2667	303	15	a	a	DET
cana-2667	303	16	specific	specific	ADJ
cana-2667	303	17	data	datum	NOUN
cana-2667	303	18	sample	sample	NOUN
cana-2667	303	19	,	,	PUNCT
cana-2667	303	20	an	an	DET
cana-2667	303	21	evaluation	evaluation	NOUN
cana-2667	303	22	method	method	NOUN
cana-2667	303	23	called	call	VERB
cana-2667	303	24	cross	cross	NOUN
cana-2667	303	25	-	-	ADJ
cana-2667	303	26	validation	validation	NOUN
cana-2667	303	27	is	be	AUX
cana-2667	303	28	commonly	commonly	ADV
cana-2667	303	29	used	use	VERB
cana-2667	303	30	.	.	PUNCT
cana-2667	304	1	in	in	ADP
cana-2667	304	2	summary	summary	NOUN
cana-2667	304	3	,	,	PUNCT
cana-2667	304	4	the	the	DET
cana-2667	304	5	proposed	propose	VERB
cana-2667	304	6	methodology	methodology	NOUN
cana-2667	304	7	can	can	AUX
cana-2667	304	8	provide	provide	VERB
cana-2667	304	9	a	a	DET
cana-2667	304	10	valuable	valuable	ADJ
cana-2667	304	11	contribution	contribution	NOUN
cana-2667	304	12	in	in	ADP
cana-2667	304	13	the	the	DET
cana-2667	304	14	developed	develop	VERB
cana-2667	304	15	dpdram	dpdram	NOUN
cana-2667	304	16	framework	framework	NOUN
cana-2667	304	17	for	for	ADP
cana-2667	304	18	the	the	DET
cana-2667	304	19	timely	timely	ADJ
cana-2667	304	20	detection	detection	NOUN
cana-2667	304	21	and	and	CCONJ
cana-2667	304	22	classification	classification	NOUN
cana-2667	304	23	of	of	ADP
cana-2667	304	24	diabetic	diabetic	ADJ
cana-2667	304	25	retinopathy	retinopathy	NOUN
cana-2667	304	26	.	.	PUNCT
cana-2667	305	1	here	here	ADV
cana-2667	305	2	,	,	PUNCT
cana-2667	305	3	cnns	cnn	NOUN
cana-2667	305	4	are	be	AUX
cana-2667	305	5	used	use	VERB
cana-2667	305	6	to	to	PART
cana-2667	305	7	automatically	automatically	ADV
cana-2667	305	8	extract	extract	VERB
cana-2667	305	9	the	the	DET
cana-2667	305	10	features	feature	NOUN
cana-2667	305	11	and	and	CCONJ
cana-2667	305	12	svms	svms	VERB
cana-2667	305	13	for	for	ADP
cana-2667	305	14	classification	classification	NOUN
cana-2667	305	15	.	.	PUNCT
cana-2667	306	1	this	this	PRON
cana-2667	306	2	alleviates	alleviate	VERB
cana-2667	306	3	the	the	DET
cana-2667	306	4	burden	burden	NOUN
cana-2667	306	5	of	of	ADP
cana-2667	306	6	healthcare	healthcare	NOUN
cana-2667	306	7	professionals	professional	NOUN
cana-2667	306	8	,	,	PUNCT
cana-2667	306	9	leading	lead	VERB
cana-2667	306	10	to	to	ADP
cana-2667	306	11	quicker	quick	ADJ
cana-2667	306	12	diagnoses	diagnosis	NOUN
cana-2667	306	13	that	that	PRON
cana-2667	306	14	are	be	AUX
cana-2667	306	15	particularly	particularly	ADV
cana-2667	306	16	important	important	ADJ
cana-2667	306	17	in	in	ADP
cana-2667	306	18	diabetic	diabetic	ADJ
cana-2667	306	19	retinopathy	retinopathy	NOUN
cana-2667	306	20	,	,	PUNCT
cana-2667	306	21	where	where	SCONJ
cana-2667	306	22	the	the	DET
cana-2667	306	23	motto	motto	NOUN
cana-2667	306	24	is	be	AUX
cana-2667	306	25	"	"	PUNCT
cana-2667	306	26	the	the	DET
cana-2667	306	27	earliest	early	ADJ
cana-2667	306	28	hear	hear	VERB
cana-2667	306	29	many	many	ADJ
cana-2667	306	30	people	people	NOUN
cana-2667	306	31	.	.	PUNCT
cana-2667	307	1	the	the	DET
cana-2667	307	2	earlier	early	ADJ
cana-2667	307	3	the	the	DET
cana-2667	307	4	detection	detection	NOUN
cana-2667	307	5	,	,	PUNCT
cana-2667	307	6	the	the	PRON
cana-2667	307	7	higher	high	ADJ
cana-2667	307	8	the	the	DET
cana-2667	307	9	chance	chance	NOUN
cana-2667	307	10	can	can	AUX
cana-2667	307	11	cure	cure	VERB
cana-2667	307	12	blindness	blindness	NOUN
cana-2667	307	13	.	.	PUNCT
cana-2667	308	1	the	the	DET
cana-2667	308	2	hybrid	hybrid	ADJ
cana-2667	308	3	model	model	NOUN
cana-2667	308	4	which	which	PRON
cana-2667	308	5	is	be	AUX
cana-2667	308	6	a	a	DET
cana-2667	308	7	combination	combination	NOUN
cana-2667	308	8	of	of	ADP
cana-2667	308	9	deep	deep	ADJ
cana-2667	308	10	learning	learning	NOUN
cana-2667	308	11	and	and	CCONJ
cana-2667	308	12	traditional	traditional	ADJ
cana-2667	308	13	machine	machine	NOUN
cana-2667	308	14	learning	learn	VERB
cana-2667	308	15	techniques	technique	NOUN
cana-2667	308	16	allows	allow	VERB
cana-2667	308	17	the	the	DET
cana-2667	308	18	system	system	NOUN
cana-2667	308	19	to	to	PART
cana-2667	308	20	be	be	AUX
cana-2667	308	21	powerful	powerful	ADJ
cana-2667	308	22	yet	yet	ADV
cana-2667	308	23	efficient	efficient	ADJ
cana-2667	308	24	.	.	PUNCT
cana-2667	309	1	cnn	cnn	PROPN
cana-2667	309	2	component	component	NOUN
cana-2667	309	3	is	be	AUX
cana-2667	309	4	well	well	ADV
cana-2667	309	5	suited	suited	ADJ
cana-2667	309	6	for	for	ADP
cana-2667	309	7	dealing	deal	VERB
cana-2667	309	8	with	with	ADP
cana-2667	309	9	the	the	DET
cana-2667	309	10	complexities	complexity	NOUN
cana-2667	309	11	in	in	ADP
cana-2667	309	12	the	the	DET
cana-2667	309	13	medical	medical	ADJ
cana-2667	309	14	images	image	NOUN
cana-2667	309	15	,	,	PUNCT
cana-2667	309	16	whereas	whereas	SCONJ
cana-2667	309	17	svm	svm	ADJ
cana-2667	309	18	acts	act	VERB
cana-2667	309	19	as	as	ADP
cana-2667	309	20	a	a	DET
cana-2667	309	21	strong	strong	ADJ
cana-2667	309	22	classifier	classifier	NOUN
cana-2667	309	23	working	work	VERB
cana-2667	309	24	effectively	effectively	ADV
cana-2667	309	25	in	in	ADP
cana-2667	309	26	high	high	ADJ
cana-2667	309	27	dimensional	dimensional	ADJ
cana-2667	309	28	spaces	space	NOUN
cana-2667	309	29	.	.	PUNCT
cana-2667	310	1	the	the	DET
cana-2667	310	2	outcome	outcome	NOUN
cana-2667	310	3	is	be	AUX
cana-2667	310	4	an	an	DET
cana-2667	310	5	end	end	NOUN
cana-2667	310	6	-	-	PUNCT
cana-2667	310	7	to	to	ADP
cana-2667	310	8	-	-	PUNCT
cana-2667	310	9	end	end	NOUN
cana-2667	310	10	system	system	NOUN
cana-2667	310	11	that	that	PRON
cana-2667	310	12	can	can	AUX
cana-2667	310	13	be	be	AUX
cana-2667	310	14	deployed	deploy	VERB
cana-2667	310	15	within	within	ADP
cana-2667	310	16	real	real	ADJ
cana-2667	310	17	-	-	PUNCT
cana-2667	310	18	world	world	NOUN
cana-2667	310	19	clinical	clinical	ADJ
cana-2667	310	20	settings	setting	NOUN
cana-2667	310	21	that	that	PRON
cana-2667	310	22	support	support	VERB
cana-2667	310	23	the	the	DET
cana-2667	310	24	early	early	ADJ
cana-2667	310	25	detection	detection	NOUN
cana-2667	310	26	of	of	ADP
cana-2667	310	27	retinal	retinal	ADJ
cana-2667	310	28	diseases	disease	NOUN
cana-2667	310	29	.	.	PUNCT
cana-2667	311	1	finally	finally	ADV
cana-2667	311	2	,	,	PUNCT
cana-2667	311	3	the	the	DET
cana-2667	311	4	hybrid	hybrid	NOUN
cana-2667	311	5	approach	approach	NOUN
cana-2667	311	6	,	,	PUNCT
cana-2667	311	7	which	which	PRON
cana-2667	311	8	has	have	AUX
cana-2667	311	9	been	be	AUX
cana-2667	311	10	proposed	propose	VERB
cana-2667	311	11	in	in	ADP
cana-2667	311	12	this	this	DET
cana-2667	311	13	work	work	NOUN
cana-2667	311	14	,	,	PUNCT
cana-2667	311	15	offers	offer	VERB
cana-2667	311	16	an	an	DET
cana-2667	311	17	effective	effective	ADJ
cana-2667	311	18	solution	solution	NOUN
cana-2667	311	19	which	which	PRON
cana-2667	311	20	might	might	AUX
cana-2667	311	21	allow	allow	VERB
cana-2667	311	22	an	an	DET
cana-2667	311	23	automated	automate	VERB
cana-2667	311	24	detection	detection	NOUN
cana-2667	311	25	of	of	ADP
cana-2667	311	26	diabetic	diabetic	ADJ
cana-2667	311	27	retinopathy	retinopathy	NOUN
cana-2667	311	28	.	.	PUNCT
cana-2667	312	1	this	this	DET
cana-2667	312	2	model	model	NOUN
cana-2667	312	3	utilizes	utilize	VERB
cana-2667	312	4	the	the	DET
cana-2667	312	5	advantages	advantage	NOUN
cana-2667	312	6	of	of	ADP
cana-2667	312	7	cnns	cnn	NOUN
cana-2667	312	8	for	for	ADP
cana-2667	312	9	feature	feature	NOUN
cana-2667	312	10	extraction	extraction	NOUN
cana-2667	312	11	and	and	CCONJ
cana-2667	312	12	svms	svms	NOUN
cana-2667	312	13	for	for	ADP
cana-2667	312	14	classification	classification	NOUN
cana-2667	312	15	.	.	PUNCT
cana-2667	313	1	with	with	ADP
cana-2667	313	2	automated	automate	VERB
cana-2667	313	3	analysis	analysis	NOUN
cana-2667	313	4	,	,	PUNCT
cana-2667	313	5	the	the	DET
cana-2667	313	6	system	system	NOUN
cana-2667	313	7	could	could	AUX
cana-2667	313	8	result	result	VERB
cana-2667	313	9	in	in	ADP
cana-2667	313	10	better	well	ADJ
cana-2667	313	11	patient	patient	ADJ
cana-2667	313	12	outcomes	outcome	NOUN
cana-2667	313	13	with	with	ADP
cana-2667	313	14	earlier	early	ADJ
cana-2667	313	15	diagnosis	diagnosis	NOUN
cana-2667	313	16	and	and	CCONJ
cana-2667	313	17	intervention	intervention	NOUN
cana-2667	313	18	.	.	PUNCT
cana-2667	314	1	4	4	X
cana-2667	314	2	.	.	X
cana-2667	314	3	results	result	NOUN
cana-2667	314	4	we	we	PRON
cana-2667	314	5	tested	test	VERB
cana-2667	314	6	the	the	DET
cana-2667	314	7	performance	performance	NOUN
cana-2667	314	8	of	of	ADP
cana-2667	314	9	our	our	PRON
cana-2667	314	10	proposed	propose	VERB
cana-2667	314	11	methodology	methodology	NOUN
cana-2667	314	12	for	for	ADP
cana-2667	314	13	diabetic	diabetic	ADJ
cana-2667	314	14	retinopathy	retinopathy	ADJ
cana-2667	314	15	detection	detection	NOUN
cana-2667	314	16	with	with	ADP
cana-2667	314	17	optimized	optimize	VERB
cana-2667	314	18	support	support	NOUN
cana-2667	314	19	vector	vector	NOUN
cana-2667	314	20	machines	machine	NOUN
cana-2667	314	21	(	(	PUNCT
cana-2667	314	22	svm	svm	PROPN
cana-2667	314	23	)	)	PUNCT
cana-2667	314	24	and	and	CCONJ
cana-2667	314	25	convolutional	convolutional	ADJ
cana-2667	314	26	neural	neural	ADJ
cana-2667	314	27	networks	network	NOUN
cana-2667	314	28	(	(	PUNCT
cana-2667	314	29	cnn	cnn	PROPN
cana-2667	314	30	)	)	PUNCT
cana-2667	314	31	in	in	ADP
cana-2667	314	32	a	a	DET
cana-2667	314	33	series	series	NOUN
cana-2667	314	34	of	of	ADP
cana-2667	314	35	experiments	experiment	NOUN
cana-2667	314	36	on	on	ADP
cana-2667	314	37	publicly	publicly	ADV
cana-2667	314	38	available	available	ADJ
cana-2667	314	39	data	datum	NOUN
cana-2667	314	40	.	.	PUNCT
cana-2667	315	1	as	as	ADP
cana-2667	315	2	part	part	NOUN
cana-2667	315	3	of	of	ADP
cana-2667	315	4	the	the	DET
cana-2667	315	5	evaluation	evaluation	NOUN
cana-2667	315	6	,	,	PUNCT
cana-2667	315	7	the	the	DET
cana-2667	315	8	accuracy	accuracy	NOUN
cana-2667	315	9	of	of	ADP
cana-2667	315	10	the	the	DET
cana-2667	315	11	system	system	NOUN
cana-2667	315	12	in	in	ADP
cana-2667	315	13	classifying	classify	VERB
cana-2667	315	14	doctorate	doctorate	NOUN
cana-2667	315	15	tendencies	tendency	NOUN
cana-2667	315	16	was	be	AUX
cana-2667	315	17	evaluated	evaluate	VERB
cana-2667	315	18	in	in	ADP
cana-2667	315	19	terms	term	NOUN
cana-2667	315	20	of	of	ADP
cana-2667	315	21	classification	classification	NOUN
cana-2667	315	22	accuracy	accuracy	NOUN
cana-2667	315	23	,	,	PUNCT
cana-2667	315	24	precision	precision	NOUN
cana-2667	315	25	,	,	PUNCT
cana-2667	315	26	recall	recall	NOUN
cana-2667	315	27	and	and	CCONJ
cana-2667	315	28	f1	f1	NOUN
cana-2667	315	29	-	-	PUNCT
cana-2667	315	30	score	score	NOUN
cana-2667	315	31	.	.	PUNCT
cana-2667	316	1	the	the	DET
cana-2667	316	2	experiments	experiment	NOUN
cana-2667	316	3	showed	show	VERB
cana-2667	316	4	the	the	DET
cana-2667	316	5	accuracy	accuracy	NOUN
cana-2667	316	6	of	of	ADP
cana-2667	316	7	the	the	DET
cana-2667	316	8	initial	initial	ADJ
cana-2667	316	9	svm	svm	ADJ
cana-2667	316	10	classifier	classifier	NOUN
cana-2667	316	11	,	,	PUNCT
cana-2667	316	12	and	and	CCONJ
cana-2667	316	13	verified	verify	VERB
cana-2667	316	14	whether	whether	SCONJ
cana-2667	316	15	the	the	DET
cana-2667	316	16	use	use	NOUN
cana-2667	316	17	of	of	ADP
cana-2667	316	18	a	a	DET
cana-2667	316	19	cnn	cnn	PROPN
cana-2667	316	20	-	-	PUNCT
cana-2667	316	21	based	base	VERB
cana-2667	316	22	feature	feature	NOUN
cana-2667	316	23	extraction	extraction	NOUN
cana-2667	316	24	improved	improve	VERB
cana-2667	316	25	the	the	DET
cana-2667	316	26	overall	overall	ADJ
cana-2667	316	27	performance	performance	NOUN
cana-2667	316	28	of	of	ADP
cana-2667	316	29	the	the	DET
cana-2667	316	30	classifiers	classifier	NOUN
cana-2667	316	31	in	in	ADP
cana-2667	316	32	fact	fact	NOUN
cana-2667	316	33	compared	compare	VERB
cana-2667	316	34	to	to	ADP
cana-2667	316	35	a	a	DET
cana-2667	316	36	traditional	traditional	ADJ
cana-2667	316	37	svm	svm	NOUN
cana-2667	316	38	.	.	PROPN
cana-2667	316	39	dataset	dataset	PROPN
cana-2667	316	40	and	and	CCONJ
cana-2667	316	41	experimental	experimental	ADJ
cana-2667	316	42	setup	setup	NOUN
cana-2667	316	43	the	the	DET
cana-2667	316	44	eyepacs	eyepac	NOUN
cana-2667	316	45	dataset	dataset	NOUN
cana-2667	316	46	,	,	PUNCT
cana-2667	316	47	a	a	DET
cana-2667	316	48	public	public	ADJ
cana-2667	316	49	dataset	dataset	NOUN
cana-2667	316	50	where	where	SCONJ
cana-2667	316	51	the	the	DET
cana-2667	316	52	retina	retina	NOUN
cana-2667	316	53	images	image	NOUN
cana-2667	316	54	are	be	AUX
cana-2667	316	55	annotated	annotate	VERB
cana-2667	316	56	with	with	ADP
cana-2667	316	57	severity	severity	NOUN
cana-2667	316	58	levels	level	NOUN
cana-2667	316	59	of	of	ADP
cana-2667	316	60	diabetic	diabetic	ADJ
cana-2667	316	61	retinopathy	retinopathy	NOUN
cana-2667	316	62	,	,	PUNCT
cana-2667	316	63	was	be	AUX
cana-2667	316	64	used	use	VERB
cana-2667	316	65	for	for	ADP
cana-2667	316	66	the	the	DET
cana-2667	316	67	classification	classification	NOUN
cana-2667	316	68	evaluation	evaluation	NOUN
cana-2667	316	69	.	.	PUNCT
cana-2667	317	1	it	it	PRON
cana-2667	317	2	also	also	ADV
cana-2667	317	3	contains	contain	VERB
cana-2667	317	4	more	more	ADJ
cana-2667	317	5	than	than	ADP
cana-2667	317	6	80,000	80,000	NUM
cana-2667	317	7	communications	communication	NOUN
cana-2667	317	8	on	on	ADP
cana-2667	317	9	applied	apply	VERB
cana-2667	317	10	nonlinear	nonlinear	ADJ
cana-2667	317	11	analysis	analysis	NOUN
cana-2667	317	12	issn	issn	NOUN
cana-2667	317	13	:	:	PUNCT
cana-2667	317	14	1074	1074	NUM
cana-2667	317	15	-	-	PUNCT
cana-2667	317	16	133x	133x	NUM
cana-2667	317	17	vol	vol	NOUN
cana-2667	317	18	32	32	NUM
cana-2667	317	19	no	no	NOUN
cana-2667	317	20	.	.	PUNCT
cana-2667	318	1	3s	3s	NUM
cana-2667	318	2	(	(	PUNCT
cana-2667	318	3	2025	2025	NUM
cana-2667	318	4	)	)	PUNCT
cana-2667	318	5	396	396	NUM
cana-2667	318	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	318	7	retinal	retinal	ADJ
cana-2667	318	8	images	image	NOUN
cana-2667	318	9	labelled	label	VERB
cana-2667	318	10	with	with	ADP
cana-2667	318	11	one	one	NUM
cana-2667	318	12	of	of	ADP
cana-2667	318	13	five	five	NUM
cana-2667	318	14	stages	stage	NOUN
cana-2667	318	15	of	of	ADP
cana-2667	318	16	severity	severity	NOUN
cana-2667	318	17	(	(	PUNCT
cana-2667	318	18	0	0	NUM
cana-2667	318	19	,	,	PUNCT
cana-2667	318	20	no	no	DET
cana-2667	318	21	diabetic	diabetic	ADJ
cana-2667	318	22	retinopathy	retinopathy	NOUN
cana-2667	318	23	;	;	PUNCT
cana-2667	318	24	1	1	NUM
cana-2667	318	25	,	,	PUNCT
cana-2667	318	26	mild	mild	ADJ
cana-2667	318	27	;	;	PUNCT
cana-2667	318	28	2	2	NUM
cana-2667	318	29	,	,	PUNCT
cana-2667	318	30	moderate	moderate	ADJ
cana-2667	318	31	;	;	PUNCT
cana-2667	318	32	3	3	NUM
cana-2667	318	33	,	,	PUNCT
cana-2667	318	34	severe	severe	ADJ
cana-2667	318	35	;	;	PUNCT
cana-2667	318	36	and	and	CCONJ
cana-2667	318	37	4	4	NUM
cana-2667	318	38	,	,	PUNCT
cana-2667	318	39	proliferative	proliferative	ADJ
cana-2667	318	40	diabetic	diabetic	ADJ
cana-2667	318	41	retinopathy	retinopathy	NOUN
cana-2667	318	42	or	or	CCONJ
cana-2667	318	43	pdr	pdr	PROPN
cana-2667	318	44	)	)	PUNCT
cana-2667	318	45	.	.	PUNCT
cana-2667	319	1	in	in	ADP
cana-2667	319	2	total	total	ADJ
cana-2667	319	3	,	,	PUNCT
cana-2667	319	4	80	80	NUM
cana-2667	319	5	%	%	NOUN
cana-2667	319	6	of	of	ADP
cana-2667	319	7	the	the	DET
cana-2667	319	8	dataset	dataset	NOUN
cana-2667	319	9	was	be	AUX
cana-2667	319	10	used	use	VERB
cana-2667	319	11	for	for	ADP
cana-2667	319	12	training	training	NOUN
cana-2667	319	13	and	and	CCONJ
cana-2667	319	14	20	20	NUM
cana-2667	319	15	%	%	NOUN
cana-2667	319	16	for	for	ADP
cana-2667	319	17	testing	testing	NOUN
cana-2667	319	18	.	.	PUNCT
cana-2667	320	1	after	after	ADP
cana-2667	320	2	training	train	VERB
cana-2667	320	3	a	a	DET
cana-2667	320	4	model	model	NOUN
cana-2667	320	5	,	,	PUNCT
cana-2667	320	6	it	it	PRON
cana-2667	320	7	is	be	AUX
cana-2667	320	8	then	then	ADV
cana-2667	320	9	evaluated	evaluate	VERB
cana-2667	320	10	using	use	VERB
cana-2667	320	11	a	a	DET
cana-2667	320	12	completely	completely	ADV
cana-2667	320	13	different	different	ADJ
cana-2667	320	14	set	set	NOUN
cana-2667	320	15	of	of	ADP
cana-2667	320	16	test	test	NOUN
cana-2667	320	17	data	datum	NOUN
cana-2667	320	18	and	and	CCONJ
cana-2667	320	19	compared	compare	VERB
cana-2667	320	20	to	to	ADP
cana-2667	320	21	the	the	DET
cana-2667	320	22	training	training	NOUN
cana-2667	320	23	data	datum	NOUN
cana-2667	320	24	.	.	PUNCT
cana-2667	321	1	the	the	DET
cana-2667	321	2	cnn	cnn	PROPN
cana-2667	321	3	-	-	PUNCT
cana-2667	321	4	svm	svm	PROPN
cana-2667	321	5	hybrid	hybrid	NOUN
cana-2667	321	6	model	model	NOUN
cana-2667	321	7	performance	performance	NOUN
cana-2667	321	8	was	be	AUX
cana-2667	321	9	also	also	ADV
cana-2667	321	10	evaluated	evaluate	VERB
cana-2667	321	11	against	against	ADP
cana-2667	321	12	several	several	ADJ
cana-2667	321	13	baseline	baseline	NOUN
cana-2667	321	14	methods	method	NOUN
cana-2667	321	15	along	along	ADP
cana-2667	321	16	with	with	ADP
cana-2667	321	17	svm	svm	PROPN
cana-2667	321	18	with	with	ADP
cana-2667	321	19	rbf	rbf	PROPN
cana-2667	321	20	kernel	kernel	PROPN
cana-2667	321	21	.	.	PUNCT
cana-2667	322	1	the	the	DET
cana-2667	322	2	following	follow	VERB
cana-2667	322	3	were	be	AUX
cana-2667	322	4	the	the	DET
cana-2667	322	5	existing	exist	VERB
cana-2667	322	6	baseline	baseline	NOUN
cana-2667	322	7	models	model	NOUN
cana-2667	322	8	:	:	PUNCT
cana-2667	322	9	feature	feature	NOUN
cana-2667	322	10	extraction	extraction	NOUN
cana-2667	322	11	followed	follow	VERB
cana-2667	322	12	by	by	ADP
cana-2667	322	13	svm	svm	NOUN
cana-2667	322	14	:	:	PUNCT
cana-2667	322	15	use	use	VERB
cana-2667	322	16	a	a	DET
cana-2667	322	17	cnn	cnn	NOUN
cana-2667	322	18	to	to	PART
cana-2667	322	19	extract	extract	VERB
cana-2667	322	20	features	feature	NOUN
cana-2667	322	21	and	and	CCONJ
cana-2667	322	22	a	a	DET
cana-2667	322	23	support	support	NOUN
cana-2667	322	24	vector	vector	NOUN
cana-2667	322	25	machine	machine	NOUN
cana-2667	322	26	to	to	PART
cana-2667	322	27	classify	classify	VERB
cana-2667	322	28	the	the	DET
cana-2667	322	29	features	feature	NOUN
cana-2667	322	30	.	.	PUNCT
cana-2667	323	1	classic	classic	ADJ
cana-2667	323	2	svm	svm	ADJ
cana-2667	323	3	model	model	NOUN
cana-2667	323	4	:	:	PUNCT
cana-2667	323	5	using	use	VERB
cana-2667	323	6	hand	hand	NOUN
cana-2667	323	7	-	-	PUNCT
cana-2667	323	8	crafted	craft	VERB
cana-2667	323	9	features	feature	NOUN
cana-2667	323	10	(	(	PUNCT
cana-2667	323	11	colour	colour	NOUN
cana-2667	323	12	histograms	histogram	NOUN
cana-2667	323	13	,	,	PUNCT
cana-2667	323	14	textures	texture	NOUN
cana-2667	323	15	features	feature	NOUN
cana-2667	323	16	,	,	PUNCT
cana-2667	323	17	etc	etc	X
cana-2667	323	18	.	.	X
cana-2667	323	19	cnn	cnn	PROPN
cana-2667	323	20	with	with	ADP
cana-2667	323	21	fully	fully	ADV
cana-2667	323	22	connected	connected	ADJ
cana-2667	323	23	layers	layer	NOUN
cana-2667	323	24	:	:	PUNCT
cana-2667	323	25	the	the	DET
cana-2667	323	26	fully	fully	ADV
cana-2667	323	27	connected	connected	ADJ
cana-2667	323	28	layers	layer	NOUN
cana-2667	323	29	of	of	ADP
cana-2667	323	30	the	the	DET
cana-2667	323	31	cnn	cnn	PROPN
cana-2667	323	32	were	be	AUX
cana-2667	323	33	directly	directly	ADV
cana-2667	323	34	used	use	VERB
cana-2667	323	35	for	for	ADP
cana-2667	323	36	classification	classification	NOUN
cana-2667	323	37	.	.	PUNCT
cana-2667	324	1	mpb531	mpb531	PROPN
cana-2667	324	2	mkp	mkp	PROPN
cana-2667	324	3	pdf	pdf	PROPN
cana-2667	324	4	2023	2023	NUM
cana-2667	324	5	there	there	PRON
cana-2667	324	6	is	be	VERB
cana-2667	324	7	no	no	DET
cana-2667	324	8	hardly	hardly	ADV
cana-2667	324	9	a	a	DET
cana-2667	324	10	company	company	NOUN
cana-2667	324	11	which	which	PRON
cana-2667	324	12	will	will	AUX
cana-2667	324	13	not	not	PART
cana-2667	324	14	be	be	AUX
cana-2667	324	15	interested	interested	ADJ
cana-2667	324	16	in	in	ADP
cana-2667	324	17	a	a	DET
cana-2667	324	18	performance	performance	NOUN
cana-2667	324	19	evaluation	evaluation	NOUN
cana-2667	324	20	metrics	metric	NOUN
cana-2667	324	21	in	in	ADP
cana-2667	324	22	order	order	NOUN
cana-2667	324	23	to	to	PART
cana-2667	324	24	improve	improve	VERB
cana-2667	324	25	its	its	PRON
cana-2667	324	26	performance	performance	NOUN
cana-2667	324	27	.	.	PUNCT
cana-2667	325	1	the	the	DET
cana-2667	325	2	following	follow	VERB
cana-2667	325	3	key	key	ADJ
cana-2667	325	4	measures	measure	NOUN
cana-2667	325	5	were	be	AUX
cana-2667	325	6	applied	apply	VERB
cana-2667	325	7	as	as	ADP
cana-2667	325	8	performance	performance	NOUN
cana-2667	325	9	indicators	indicator	NOUN
cana-2667	325	10	for	for	ADP
cana-2667	325	11	the	the	DET
cana-2667	325	12	model	model	NOUN
cana-2667	325	13	:	:	PUNCT
cana-2667	325	14	accuracy	accuracy	NOUN
cana-2667	325	15	:	:	PUNCT
cana-2667	325	16	the	the	DET
cana-2667	325	17	proportion	proportion	NOUN
cana-2667	325	18	of	of	ADP
cana-2667	325	19	correctly	correctly	ADV
cana-2667	325	20	identified	identify	VERB
cana-2667	325	21	images	image	NOUN
cana-2667	325	22	over	over	ADP
cana-2667	325	23	total	total	ADJ
cana-2667	325	24	images	image	NOUN
cana-2667	325	25	.	.	PUNCT
cana-2667	326	1	precision	precision	NOUN
cana-2667	326	2	=	=	PUNCT
cana-2667	326	3	tp	tp	NOUN
cana-2667	326	4	/	/	PUNCT
cana-2667	326	5	(	(	PUNCT
cana-2667	326	6	tp	tp	ADP
cana-2667	326	7	+	+	CCONJ
cana-2667	326	8	fp	fp	X
cana-2667	326	9	)	)	PUNCT
cana-2667	326	10	(	(	PUNCT
cana-2667	326	11	where	where	SCONJ
cana-2667	326	12	tp	tp	NOUN
cana-2667	326	13	=	=	PUNCT
cana-2667	326	14	true	true	ADJ
cana-2667	326	15	positives	positive	NOUN
cana-2667	326	16	and	and	CCONJ
cana-2667	326	17	fp	fp	ADJ
cana-2667	326	18	=	=	PUNCT
cana-2667	326	19	false	false	ADJ
cana-2667	326	20	positives	positive	NOUN
cana-2667	326	21	)	)	PUNCT
cana-2667	326	22	*	*	PUNCT
cana-2667	326	23	*	*	PUNCT
cana-2667	326	24	false	false	ADJ
cana-2667	326	25	positives	positive	NOUN
cana-2667	326	26	are	be	AUX
cana-2667	326	27	things	thing	NOUN
cana-2667	326	28	which	which	PRON
cana-2667	326	29	you	you	PRON
cana-2667	326	30	do	do	AUX
cana-2667	326	31	n’t	not	PART
cana-2667	326	32	want	want	VERB
cana-2667	326	33	to	to	PART
cana-2667	326	34	cause	cause	VERB
cana-2667	326	35	,	,	PUNCT
cana-2667	326	36	so	so	CCONJ
cana-2667	326	37	precision	precision	NOUN
cana-2667	326	38	is	be	AUX
cana-2667	326	39	important	important	ADJ
cana-2667	326	40	.	.	PUNCT
cana-2667	327	1	recall	recall	NOUN
cana-2667	327	2	:	:	PUNCT
cana-2667	327	3	correctly	correctly	ADV
cana-2667	327	4	predicted	predict	VERB
cana-2667	327	5	positive	positive	ADJ
cana-2667	327	6	observations	observation	NOUN
cana-2667	327	7	to	to	ADP
cana-2667	327	8	the	the	DET
cana-2667	327	9	all	all	DET
cana-2667	327	10	observations	observation	NOUN
cana-2667	327	11	in	in	ADP
cana-2667	327	12	actual	actual	ADJ
cana-2667	327	13	class	class	NOUN
cana-2667	327	14	.	.	PUNCT
cana-2667	328	1	with	with	ADP
cana-2667	328	2	a	a	DET
cana-2667	328	3	high	high	ADJ
cana-2667	328	4	cost	cost	NOUN
cana-2667	328	5	of	of	ADP
cana-2667	328	6	false	false	ADJ
cana-2667	328	7	negatives	negative	NOUN
cana-2667	328	8	,	,	PUNCT
cana-2667	328	9	recall	recall	NOUN
cana-2667	328	10	becomes	become	VERB
cana-2667	328	11	important	important	ADJ
cana-2667	328	12	.	.	PUNCT
cana-2667	329	1	f1	f1	NOUN
cana-2667	329	2	-	-	PUNCT
cana-2667	329	3	score	score	NOUN
cana-2667	329	4	:	:	PUNCT
cana-2667	329	5	it	it	PRON
cana-2667	329	6	is	be	AUX
cana-2667	329	7	also	also	ADV
cana-2667	329	8	known	know	VERB
cana-2667	329	9	as	as	ADP
cana-2667	329	10	the	the	DET
cana-2667	329	11	harmonic	harmonic	ADJ
cana-2667	329	12	mean	mean	NOUN
cana-2667	329	13	of	of	ADP
cana-2667	329	14	precision	precision	NOUN
cana-2667	329	15	and	and	CCONJ
cana-2667	329	16	recall	recall	NOUN
cana-2667	329	17	,	,	PUNCT
cana-2667	329	18	and	and	CCONJ
cana-2667	329	19	it	it	PRON
cana-2667	329	20	can	can	AUX
cana-2667	329	21	access	access	VERB
cana-2667	329	22	a	a	DET
cana-2667	329	23	better	well	ADJ
cana-2667	329	24	performance	performance	NOUN
cana-2667	329	25	from	from	ADP
cana-2667	329	26	the	the	DET
cana-2667	329	27	data	datum	NOUN
cana-2667	329	28	.	.	PUNCT
cana-2667	330	1	apart	apart	ADV
cana-2667	330	2	from	from	ADP
cana-2667	330	3	these	these	PRON
cana-2667	330	4	,	,	PUNCT
cana-2667	330	5	the	the	DET
cana-2667	330	6	model	model	NOUN
cana-2667	330	7	’s	’s	PART
cana-2667	330	8	ability	ability	NOUN
cana-2667	330	9	to	to	PART
cana-2667	330	10	discriminate	discriminate	VERB
cana-2667	330	11	between	between	ADP
cana-2667	330	12	the	the	DET
cana-2667	330	13	classes	class	NOUN
cana-2667	330	14	was	be	AUX
cana-2667	330	15	analyzed	analyze	VERB
cana-2667	330	16	through	through	ADP
cana-2667	330	17	roc	roc	PROPN
cana-2667	330	18	curve	curve	NOUN
cana-2667	330	19	as	as	ADV
cana-2667	330	20	well	well	ADV
cana-2667	330	21	as	as	ADP
cana-2667	330	22	auc	auc	NOUN
cana-2667	330	23	(	(	PUNCT
cana-2667	330	24	area	area	NOUN
cana-2667	330	25	under	under	ADP
cana-2667	330	26	the	the	DET
cana-2667	330	27	curve	curve	NOUN
cana-2667	330	28	)	)	PUNCT
cana-2667	330	29	score	score	NOUN
cana-2667	330	30	quantitatively	quantitatively	ADV
cana-2667	330	31	,	,	PUNCT
cana-2667	330	32	with	with	ADP
cana-2667	330	33	importance	importance	NOUN
cana-2667	330	34	on	on	ADP
cana-2667	330	35	sensitivity	sensitivity	NOUN
cana-2667	330	36	and	and	CCONJ
cana-2667	330	37	specificity	specificity	NOUN
cana-2667	330	38	.	.	PUNCT
cana-2667	331	1	the	the	DET
cana-2667	331	2	proposed	propose	VERB
cana-2667	331	3	approach	approach	NOUN
cana-2667	331	4	is	be	AUX
cana-2667	331	5	tested	test	VERB
cana-2667	331	6	on	on	ADP
cana-2667	331	7	nvidia	nvidia	PROPN
cana-2667	331	8	tesla	tesla	PROPN
cana-2667	331	9	gpu	gpu	PROPN
cana-2667	331	10	,	,	PUNCT
cana-2667	331	11	and	and	CCONJ
cana-2667	331	12	the	the	DET
cana-2667	331	13	training	training	NOUN
cana-2667	331	14	time	time	NOUN
cana-2667	331	15	is	be	AUX
cana-2667	331	16	recorded	record	VERB
cana-2667	331	17	in	in	ADP
cana-2667	331	18	order	order	NOUN
cana-2667	331	19	to	to	PART
cana-2667	331	20	evaluate	evaluate	VERB
cana-2667	331	21	the	the	DET
cana-2667	331	22	computational	computational	ADJ
cana-2667	331	23	cost	cost	NOUN
cana-2667	331	24	of	of	ADP
cana-2667	331	25	the	the	DET
cana-2667	331	26	proposed	propose	VERB
cana-2667	331	27	method	method	NOUN
cana-2667	331	28	.	.	PUNCT
cana-2667	332	1	results	result	VERB
cana-2667	332	2	comparison	comparison	NOUN
cana-2667	332	3	table	table	NOUN
cana-2667	332	4	2	2	NUM
cana-2667	332	5	summarizes	summarize	NOUN
cana-2667	332	6	the	the	DET
cana-2667	332	7	performance	performance	NOUN
cana-2667	332	8	of	of	ADP
cana-2667	332	9	each	each	PRON
cana-2667	332	10	of	of	ADP
cana-2667	332	11	the	the	DET
cana-2667	332	12	models	model	NOUN
cana-2667	332	13	on	on	ADP
cana-2667	332	14	the	the	DET
cana-2667	332	15	test	test	NOUN
cana-2667	332	16	set	set	NOUN
cana-2667	332	17	.	.	PUNCT
cana-2667	333	1	the	the	DET
cana-2667	333	2	cnn	cnn	PROPN
cana-2667	333	3	-	-	PUNCT
cana-2667	333	4	svm	svm	PROPN
cana-2667	333	5	hybrid	hybrid	NOUN
cana-2667	333	6	model	model	NOUN
cana-2667	333	7	showed	show	VERB
cana-2667	333	8	the	the	DET
cana-2667	333	9	best	good	ADJ
cana-2667	333	10	performance	performance	NOUN
cana-2667	333	11	,	,	PUNCT
cana-2667	333	12	and	and	CCONJ
cana-2667	333	13	achieved	achieve	VERB
cana-2667	333	14	significant	significant	ADJ
cana-2667	333	15	enhancements	enhancement	NOUN
cana-2667	333	16	in	in	ADP
cana-2667	333	17	accuracy	accuracy	NOUN
cana-2667	333	18	,	,	PUNCT
cana-2667	333	19	precision	precision	NOUN
cana-2667	333	20	,	,	PUNCT
cana-2667	333	21	recall	recall	NOUN
cana-2667	333	22	,	,	PUNCT
cana-2667	333	23	and	and	CCONJ
cana-2667	333	24	f1	f1	NOUN
cana-2667	333	25	-	-	PUNCT
cana-2667	333	26	score	score	NOUN
cana-2667	333	27	compared	compare	VERB
cana-2667	333	28	to	to	ADP
cana-2667	333	29	the	the	DET
cana-2667	333	30	other	other	ADJ
cana-2667	333	31	baseline	baseline	NOUN
cana-2667	333	32	models	model	NOUN
cana-2667	333	33	.	.	PUNCT
cana-2667	334	1	by	by	ADP
cana-2667	334	2	acting	act	VERB
cana-2667	334	3	as	as	ADP
cana-2667	334	4	an	an	DET
cana-2667	334	5	enhanced	enhanced	ADJ
cana-2667	334	6	feature	feature	NOUN
cana-2667	334	7	extractor	extractor	NOUN
cana-2667	334	8	,	,	PUNCT
cana-2667	334	9	the	the	DET
cana-2667	334	10	proposed	propose	VERB
cana-2667	334	11	cnn	cnn	PROPN
cana-2667	334	12	model	model	NOUN
cana-2667	334	13	allowed	allow	VERB
cana-2667	334	14	the	the	DET
cana-2667	334	15	optimized	optimize	VERB
cana-2667	334	16	svm	svm	NOUN
cana-2667	334	17	classifier	classifier	NOUN
cana-2667	334	18	to	to	PART
cana-2667	334	19	effectively	effectively	ADV
cana-2667	334	20	discriminate	discriminate	VERB
cana-2667	334	21	between	between	ADP
cana-2667	334	22	the	the	DET
cana-2667	334	23	severity	severity	NOUN
cana-2667	334	24	levels	level	NOUN
cana-2667	334	25	of	of	ADP
cana-2667	334	26	diabetic	diabetic	ADJ
cana-2667	334	27	retinopathy	retinopathy	NOUN
cana-2667	334	28	compared	compare	VERB
cana-2667	334	29	to	to	ADP
cana-2667	334	30	the	the	DET
cana-2667	334	31	traditional	traditional	ADJ
cana-2667	334	32	svm	svm	NOUN
cana-2667	334	33	with	with	ADP
cana-2667	334	34	the	the	DET
cana-2667	334	35	hand	hand	NOUN
cana-2667	334	36	-	-	PUNCT
cana-2667	334	37	crafted	craft	VERB
cana-2667	334	38	features	feature	NOUN
cana-2667	334	39	.	.	PUNCT
cana-2667	335	1	table	table	NOUN
cana-2667	335	2	2	2	NUM
cana-2667	335	3	:	:	PUNCT
cana-2667	335	4	hyperparameter	hyperparameter	NOUN
cana-2667	335	5	tuning	tune	VERB
cana-2667	335	6	for	for	ADP
cana-2667	335	7	svm	svm	ADJ
cana-2667	335	8	hyperparameter	hyperparameter	NOUN
cana-2667	335	9	optimized	optimize	VERB
cana-2667	335	10	value	value	NOUN
cana-2667	335	11	c	c	NOUN
cana-2667	335	12	(	(	PUNCT
cana-2667	335	13	regularization	regularization	NOUN
cana-2667	335	14	parameter	parameter	NOUN
cana-2667	335	15	)	)	PUNCT
cana-2667	335	16	10	10	NUM
cana-2667	335	17	gamma	gamma	NOUN
cana-2667	335	18	(	(	PUNCT
cana-2667	335	19	kernel	kernel	PROPN
cana-2667	335	20	parameter	parameter	PROPN
cana-2667	335	21	)	)	PUNCT
cana-2667	335	22	0.05	0.05	NUM
cana-2667	335	23	kernel	kernel	PROPN
cana-2667	335	24	radial	radial	ADJ
cana-2667	335	25	basis	basis	NOUN
cana-2667	335	26	function	function	NOUN
cana-2667	335	27	(	(	PUNCT
cana-2667	335	28	rbf	rbf	PROPN
cana-2667	335	29	)	)	PUNCT
cana-2667	335	30	communications	communication	NOUN
cana-2667	335	31	on	on	ADP
cana-2667	335	32	applied	apply	VERB
cana-2667	335	33	nonlinear	nonlinear	ADJ
cana-2667	335	34	analysis	analysis	NOUN
cana-2667	335	35	issn	issn	NOUN
cana-2667	335	36	:	:	PUNCT
cana-2667	335	37	1074	1074	NUM
cana-2667	335	38	-	-	PUNCT
cana-2667	335	39	133x	133x	NUM
cana-2667	335	40	vol	vol	NOUN
cana-2667	335	41	32	32	NUM
cana-2667	336	1	no	no	NOUN
cana-2667	336	2	.	.	PUNCT
cana-2667	337	1	3s	3s	NUM
cana-2667	337	2	(	(	PUNCT
cana-2667	337	3	2025	2025	NUM
cana-2667	337	4	)	)	PUNCT
cana-2667	337	5	397	397	NUM
cana-2667	337	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	337	7	hyperparameter	hyperparameter	NOUN
cana-2667	337	8	optimized	optimize	VERB
cana-2667	337	9	value	value	NOUN
cana-2667	337	10	tolerance	tolerance	NOUN
cana-2667	337	11	0.001	0.001	NUM
cana-2667	337	12	max	max	PROPN
cana-2667	337	13	iterations	iteration	NOUN
cana-2667	337	14	1000	1000	NUM
cana-2667	337	15	figure	figure	NOUN
cana-2667	337	16	3	3	NUM
cana-2667	337	17	.	.	PUNCT
cana-2667	337	18	accuracy	accuracy	NOUN
cana-2667	337	19	comparison	comparison	NOUN
cana-2667	337	20	of	of	ADP
cana-2667	337	21	feature	feature	NOUN
cana-2667	337	22	extraction	extraction	NOUN
cana-2667	337	23	methods	method	NOUN
cana-2667	337	24	accuracy	accuracy	NOUN
cana-2667	337	25	:	:	PUNCT
cana-2667	337	26	the	the	DET
cana-2667	337	27	cnn	cnn	PROPN
cana-2667	337	28	-	-	PUNCT
cana-2667	337	29	svm	svm	PROPN
cana-2667	337	30	hybrid	hybrid	NOUN
cana-2667	337	31	model	model	NOUN
cana-2667	337	32	out	out	ADV
cana-2667	337	33	-	-	PUNCT
cana-2667	337	34	performed	perform	VERB
cana-2667	337	35	the	the	DET
cana-2667	337	36	cnn	cnn	PROPN
cana-2667	337	37	-	-	PUNCT
cana-2667	337	38	only	only	ADJ
cana-2667	337	39	model	model	NOUN
cana-2667	337	40	(	(	PUNCT
cana-2667	337	41	86.4	86.4	NUM
cana-2667	337	42	%	%	NOUN
cana-2667	337	43	)	)	PUNCT
cana-2667	337	44	by	by	ADP
cana-2667	337	45	5.9	5.9	NUM
cana-2667	337	46	%	%	NOUN
cana-2667	337	47	and	and	CCONJ
cana-2667	337	48	traditional	traditional	ADJ
cana-2667	337	49	svm	svm	NOUN
cana-2667	337	50	(	(	PUNCT
cana-2667	337	51	79.2	79.2	NUM
cana-2667	337	52	%	%	NOUN
cana-2667	337	53	)	)	PUNCT
cana-2667	337	54	by	by	ADP
cana-2667	337	55	13.1	13.1	NUM
cana-2667	337	56	%	%	NOUN
cana-2667	337	57	,	,	PUNCT
cana-2667	337	58	achieving	achieve	VERB
cana-2667	337	59	accuracy	accuracy	NOUN
cana-2667	337	60	of	of	ADP
cana-2667	337	61	92.3	92.3	NUM
cana-2667	337	62	%	%	NOUN
cana-2667	337	63	.	.	PUNCT
cana-2667	338	1	this	this	PRON
cana-2667	338	2	showcased	showcase	VERB
cana-2667	338	3	the	the	DET
cana-2667	338	4	capability	capability	NOUN
cana-2667	338	5	of	of	ADP
cana-2667	338	6	svm	svm	NOUN
cana-2667	338	7	when	when	SCONJ
cana-2667	338	8	coupled	couple	VERB
cana-2667	338	9	with	with	ADP
cana-2667	338	10	features	feature	NOUN
cana-2667	338	11	learned	learn	VERB
cana-2667	338	12	from	from	ADP
cana-2667	338	13	cnn	cnn	PROPN
cana-2667	338	14	,	,	PUNCT
cana-2667	338	15	since	since	SCONJ
cana-2667	338	16	cnn	cnn	PROPN
cana-2667	338	17	is	be	AUX
cana-2667	338	18	able	able	ADJ
cana-2667	338	19	to	to	PART
cana-2667	338	20	learn	learn	VERB
cana-2667	338	21	highly	highly	ADV
cana-2667	338	22	complicated	complicated	ADJ
cana-2667	338	23	patterns	pattern	NOUN
cana-2667	338	24	or	or	CCONJ
cana-2667	338	25	characteristics	characteristic	NOUN
cana-2667	338	26	from	from	ADP
cana-2667	338	27	the	the	DET
cana-2667	338	28	dataset	dataset	NOUN
cana-2667	338	29	,	,	PUNCT
cana-2667	338	30	which	which	PRON
cana-2667	338	31	are	be	AUX
cana-2667	338	32	later	later	ADV
cana-2667	338	33	utilized	utilize	VERB
cana-2667	338	34	by	by	ADP
cana-2667	338	35	the	the	DET
cana-2667	338	36	svm	svm	PROPN
cana-2667	338	37	to	to	PART
cana-2667	338	38	do	do	VERB
cana-2667	338	39	accurate	accurate	ADJ
cana-2667	338	40	predictions	prediction	NOUN
cana-2667	338	41	.	.	PUNCT
cana-2667	339	1	table	table	NOUN
cana-2667	339	2	3	3	NUM
cana-2667	339	3	:	:	PUNCT
cana-2667	339	4	performance	performance	NOUN
cana-2667	339	5	metrics	metric	NOUN
cana-2667	339	6	for	for	ADP
cana-2667	339	7	different	different	ADJ
cana-2667	339	8	models	model	NOUN
cana-2667	339	9	model	model	NOUN
cana-2667	339	10	accuracy	accuracy	NOUN
cana-2667	339	11	(	(	PUNCT
cana-2667	339	12	%	%	INTJ
cana-2667	339	13	)	)	PUNCT
cana-2667	339	14	precision	precision	NOUN
cana-2667	339	15	(	(	PUNCT
cana-2667	339	16	%	%	INTJ
cana-2667	339	17	)	)	PUNCT
cana-2667	339	18	recall	recall	NOUN
cana-2667	339	19	(	(	PUNCT
cana-2667	339	20	%	%	NOUN
cana-2667	339	21	)	)	PUNCT
cana-2667	339	22	f1	f1	NOUN
cana-2667	339	23	-	-	PUNCT
cana-2667	339	24	score	score	NOUN
cana-2667	339	25	(	(	PUNCT
cana-2667	339	26	%	%	INTJ
cana-2667	339	27	)	)	PUNCT
cana-2667	339	28	auc	auc	PROPN
cana-2667	339	29	cnn	cnn	PROPN
cana-2667	339	30	-	-	PUNCT
cana-2667	339	31	svm	svm	ADJ
cana-2667	339	32	hybrid	hybrid	NOUN
cana-2667	339	33	model	model	NOUN
cana-2667	339	34	92.3	92.3	NUM
cana-2667	339	35	90.2	90.2	NUM
cana-2667	339	36	93.1	93.1	NUM
cana-2667	339	37	91.6	91.6	NUM
cana-2667	339	38	0.964	0.964	NUM
cana-2667	339	39	cnn	cnn	PROPN
cana-2667	339	40	-	-	PUNCT
cana-2667	339	41	only	only	ADJ
cana-2667	339	42	model	model	NOUN
cana-2667	339	43	86.4	86.4	NUM
cana-2667	339	44	87.1	87.1	NUM
cana-2667	339	45	88.5	88.5	NUM
cana-2667	339	46	86.7	86.7	NUM
cana-2667	339	47	0.930	0.930	NUM
cana-2667	339	48	traditional	traditional	ADJ
cana-2667	339	49	svm	svm	NOUN
cana-2667	339	50	79.2	79.2	NUM
cana-2667	339	51	82.5	82.5	NUM
cana-2667	339	52	85.3	85.3	NUM
cana-2667	339	53	83.3	83.3	NUM
cana-2667	339	54	0.890	0.890	NUM
cana-2667	339	55	deep	deep	ADJ
cana-2667	339	56	cnn	cnn	PROPN
cana-2667	339	57	(	(	PUNCT
cana-2667	339	58	fully	fully	ADV
cana-2667	339	59	connected	connect	VERB
cana-2667	339	60	)	)	PUNCT
cana-2667	339	61	88.7	88.7	NUM
cana-2667	339	62	85.6	85.6	NUM
cana-2667	339	63	91.2	91.2	NUM
cana-2667	339	64	88.2	88.2	NUM
cana-2667	339	65	0.940	0.940	NUM
cana-2667	339	66	precision	precision	NOUN
cana-2667	339	67	:	:	PUNCT
cana-2667	339	68	the	the	DET
cana-2667	339	69	hybrid	hybrid	ADJ
cana-2667	339	70	model	model	NOUN
cana-2667	339	71	produced	produce	VERB
cana-2667	339	72	a	a	DET
cana-2667	339	73	precision	precision	NOUN
cana-2667	339	74	score	score	NOUN
cana-2667	339	75	of	of	ADP
cana-2667	339	76	90.2	90.2	NUM
cana-2667	339	77	%	%	NOUN
cana-2667	339	78	,	,	PUNCT
cana-2667	339	79	better	well	ADJ
cana-2667	339	80	than	than	ADP
cana-2667	339	81	the	the	DET
cana-2667	339	82	cnn	cnn	PROPN
cana-2667	339	83	-	-	PUNCT
cana-2667	339	84	only	only	ADJ
cana-2667	339	85	model	model	NOUN
cana-2667	339	86	(	(	PUNCT
cana-2667	339	87	87.1	87.1	NUM
cana-2667	339	88	%	%	NOUN
cana-2667	339	89	)	)	PUNCT
cana-2667	339	90	and	and	CCONJ
cana-2667	339	91	traditional	traditional	ADJ
cana-2667	339	92	svm	svm	NOUN
cana-2667	339	93	(	(	PUNCT
cana-2667	339	94	82.5	82.5	NUM
cana-2667	339	95	%	%	NOUN
cana-2667	339	96	)	)	PUNCT
cana-2667	339	97	this	this	PRON
cana-2667	339	98	can	can	AUX
cana-2667	339	99	suggest	suggest	VERB
cana-2667	339	100	that	that	SCONJ
cana-2667	339	101	the	the	DET
cana-2667	339	102	hybrid	hybrid	NOUN
cana-2667	339	103	model	model	NOUN
cana-2667	339	104	gave	give	VERB
cana-2667	339	105	less	less	ADV
cana-2667	339	106	false	false	ADJ
cana-2667	339	107	positive	positive	ADJ
cana-2667	339	108	predictions	prediction	NOUN
cana-2667	339	109	,	,	PUNCT
cana-2667	339	110	which	which	PRON
cana-2667	339	111	is	be	AUX
cana-2667	339	112	important	important	ADJ
cana-2667	339	113	in	in	ADP
cana-2667	339	114	medical	medical	ADJ
cana-2667	339	115	imaging	imaging	NOUN
cana-2667	339	116	tasks	task	NOUN
cana-2667	339	117	such	such	ADJ
cana-2667	339	118	as	as	ADP
cana-2667	339	119	diabetic	diabetic	ADJ
cana-2667	339	120	retinopathy	retinopathy	ADJ
cana-2667	339	121	detection	detection	NOUN
cana-2667	339	122	since	since	SCONJ
cana-2667	339	123	false	false	ADJ
cana-2667	339	124	positives	positive	NOUN
cana-2667	339	125	,	,	PUNCT
cana-2667	339	126	may	may	AUX
cana-2667	339	127	lead	lead	VERB
cana-2667	339	128	to	to	ADP
cana-2667	339	129	unnecessary	unnecessary	ADJ
cana-2667	339	130	treatment	treatment	NOUN
cana-2667	339	131	or	or	CCONJ
cana-2667	339	132	follow	follow	NOUN
cana-2667	339	133	-	-	PUNCT
cana-2667	339	134	up	up	NOUN
cana-2667	339	135	.	.	PUNCT
cana-2667	340	1	table	table	NOUN
cana-2667	340	2	4	4	NUM
cana-2667	340	3	:	:	PUNCT
cana-2667	340	4	class	class	NOUN
cana-2667	340	5	-	-	PUNCT
cana-2667	340	6	wise	wise	ADJ
cana-2667	340	7	precision	precision	NOUN
cana-2667	340	8	and	and	CCONJ
cana-2667	340	9	recall	recall	NOUN
cana-2667	340	10	for	for	ADP
cana-2667	340	11	cnn	cnn	PROPN
cana-2667	340	12	-	-	PUNCT
cana-2667	340	13	svm	svm	ADJ
cana-2667	340	14	hybrid	hybrid	ADJ
cana-2667	340	15	model	model	NOUN
cana-2667	340	16	class	class	NOUN
cana-2667	340	17	precision	precision	NOUN
cana-2667	340	18	(	(	PUNCT
cana-2667	340	19	%	%	INTJ
cana-2667	340	20	)	)	PUNCT
cana-2667	340	21	recall	recall	NOUN
cana-2667	340	22	(	(	PUNCT
cana-2667	340	23	%	%	INTJ
cana-2667	340	24	)	)	PUNCT
cana-2667	341	1	no	no	DET
cana-2667	341	2	dr	dr	PROPN
cana-2667	341	3	(	(	PUNCT
cana-2667	341	4	0	0	NUM
cana-2667	341	5	)	)	PUNCT
cana-2667	341	6	92.5	92.5	NUM
cana-2667	341	7	93.1	93.1	NUM
cana-2667	341	8	mild	mild	ADJ
cana-2667	341	9	dr	dr	NOUN
cana-2667	341	10	(	(	PUNCT
cana-2667	341	11	1	1	NUM
cana-2667	341	12	)	)	PUNCT
cana-2667	341	13	88.1	88.1	NUM
cana-2667	341	14	87.3	87.3	NUM
cana-2667	341	15	moderate	moderate	ADJ
cana-2667	341	16	dr	dr	PROPN
cana-2667	341	17	(	(	PUNCT
cana-2667	341	18	2	2	NUM
cana-2667	341	19	)	)	PUNCT
cana-2667	341	20	90.0	90.0	NUM
cana-2667	341	21	92.0	92.0	NUM
cana-2667	341	22	severe	severe	ADJ
cana-2667	341	23	dr	dr	PROPN
cana-2667	341	24	(	(	PUNCT
cana-2667	341	25	3	3	NUM
cana-2667	341	26	)	)	PUNCT
cana-2667	341	27	91.2	91.2	NUM
cana-2667	341	28	92.3	92.3	NUM
cana-2667	341	29	pdr	pdr	NOUN
cana-2667	341	30	(	(	PUNCT
cana-2667	341	31	4	4	NUM
cana-2667	341	32	)	)	PUNCT
cana-2667	341	33	89.6	89.6	NUM
cana-2667	341	34	90.8	90.8	NUM
cana-2667	341	35	communications	communication	NOUN
cana-2667	341	36	on	on	ADP
cana-2667	341	37	applied	apply	VERB
cana-2667	341	38	nonlinear	nonlinear	ADJ
cana-2667	341	39	analysis	analysis	NOUN
cana-2667	341	40	issn	issn	NOUN
cana-2667	341	41	:	:	PUNCT
cana-2667	341	42	1074	1074	NUM
cana-2667	341	43	-	-	PUNCT
cana-2667	341	44	133x	133x	NUM
cana-2667	341	45	vol	vol	NOUN
cana-2667	341	46	32	32	NUM
cana-2667	341	47	no	no	NOUN
cana-2667	341	48	.	.	PUNCT
cana-2667	342	1	3s	3s	NUM
cana-2667	342	2	(	(	PUNCT
cana-2667	342	3	2025	2025	NUM
cana-2667	342	4	)	)	PUNCT
cana-2667	342	5	398	398	NUM
cana-2667	342	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	342	7	recall	recall	NOUN
cana-2667	342	8	:	:	PUNCT
cana-2667	342	9	the	the	DET
cana-2667	342	10	hybrid	hybrid	NOUN
cana-2667	342	11	model	model	NOUN
cana-2667	342	12	also	also	ADV
cana-2667	342	13	had	have	AUX
cana-2667	342	14	higher	high	ADJ
cana-2667	342	15	recall	recall	NOUN
cana-2667	342	16	than	than	ADP
cana-2667	342	17	the	the	DET
cana-2667	342	18	cnn	cnn	PROPN
cana-2667	342	19	-	-	PUNCT
cana-2667	342	20	only	only	ADJ
cana-2667	342	21	model	model	NOUN
cana-2667	342	22	(	(	PUNCT
cana-2667	342	23	88.5	88.5	NUM
cana-2667	342	24	%	%	NOUN
cana-2667	342	25	)	)	PUNCT
cana-2667	342	26	and	and	CCONJ
cana-2667	342	27	traditional	traditional	ADJ
cana-2667	342	28	svm	svm	NOUN
cana-2667	342	29	(	(	PUNCT
cana-2667	342	30	85.3	85.3	NUM
cana-2667	342	31	%	%	NOUN
cana-2667	342	32	)	)	PUNCT
cana-2667	342	33	,	,	PUNCT
cana-2667	342	34	scoring	score	VERB
cana-2667	342	35	93.1	93.1	NUM
cana-2667	342	36	%	%	NOUN
cana-2667	342	37	overall	overall	ADJ
cana-2667	342	38	.	.	PUNCT
cana-2667	343	1	cnn	cnn	PROPN
cana-2667	343	2	-	-	PUNCT
cana-2667	343	3	svm	svm	PROPN
cana-2667	343	4	model	model	NOUN
cana-2667	343	5	recall	recall	NOUN
cana-2667	343	6	is	be	AUX
cana-2667	343	7	higher	high	ADJ
cana-2667	343	8	than	than	ADP
cana-2667	343	9	conventional	conventional	ADJ
cana-2667	343	10	threshold	threshold	NOUN
cana-2667	343	11	methods	method	NOUN
cana-2667	343	12	which	which	PRON
cana-2667	343	13	means	mean	VERB
cana-2667	343	14	that	that	SCONJ
cana-2667	343	15	cnn	cnn	PROPN
cana-2667	343	16	-	-	PUNCT
cana-2667	343	17	svm	svm	PROPN
cana-2667	343	18	model	model	NOUN
cana-2667	343	19	is	be	AUX
cana-2667	343	20	able	able	ADJ
cana-2667	343	21	to	to	PART
cana-2667	343	22	capture	capture	VERB
cana-2667	343	23	the	the	DET
cana-2667	343	24	total	total	ADJ
cana-2667	343	25	diabetic	diabetic	ADJ
cana-2667	343	26	retinopathy	retinopathy	ADJ
cana-2667	343	27	cases	case	NOUN
cana-2667	343	28	,	,	PUNCT
cana-2667	343	29	including	include	VERB
cana-2667	343	30	the	the	DET
cana-2667	343	31	more	more	ADV
cana-2667	343	32	severe	severe	ADJ
cana-2667	343	33	cases	case	NOUN
cana-2667	343	34	.	.	PUNCT
cana-2667	344	1	f1	f1	NOUN
cana-2667	344	2	-	-	PUNCT
cana-2667	344	3	score	score	NOUN
cana-2667	344	4	:	:	PUNCT
cana-2667	344	5	the	the	DET
cana-2667	344	6	f1	f1	NOUN
cana-2667	344	7	-	-	PUNCT
cana-2667	344	8	score	score	NOUN
cana-2667	344	9	of	of	ADP
cana-2667	344	10	the	the	DET
cana-2667	344	11	cnn	cnn	PROPN
cana-2667	344	12	-	-	PUNCT
cana-2667	344	13	svm	svm	PROPN
cana-2667	344	14	hybrid	hybrid	NOUN
cana-2667	344	15	model	model	NOUN
cana-2667	344	16	was	be	AUX
cana-2667	344	17	91.6	91.6	NUM
cana-2667	344	18	%	%	NOUN
cana-2667	344	19	,	,	PUNCT
cana-2667	344	20	which	which	PRON
cana-2667	344	21	indicates	indicate	VERB
cana-2667	344	22	a	a	DET
cana-2667	344	23	balance	balance	NOUN
cana-2667	344	24	between	between	ADP
cana-2667	344	25	precision	precision	NOUN
cana-2667	344	26	and	and	CCONJ
cana-2667	344	27	recall	recall	NOUN
cana-2667	344	28	.	.	PUNCT
cana-2667	345	1	f1	f1	NOUN
cana-2667	345	2	-	-	PUNCT
cana-2667	345	3	score	score	NOUN
cana-2667	345	4	of	of	ADP
cana-2667	345	5	86.7	86.7	NUM
cana-2667	345	6	%	%	NOUN
cana-2667	345	7	for	for	ADP
cana-2667	345	8	cnn	cnn	PROPN
cana-2667	345	9	-	-	PUNCT
cana-2667	345	10	only	only	ADV
cana-2667	345	11	model	model	NOUN
cana-2667	345	12	and	and	CCONJ
cana-2667	345	13	83.3	83.3	NUM
cana-2667	345	14	%	%	NOUN
cana-2667	345	15	for	for	ADP
cana-2667	345	16	traditional	traditional	ADJ
cana-2667	345	17	svm	svm	PROPN
cana-2667	345	18	roc	roc	PROPN
cana-2667	345	19	curve	curve	NOUN
cana-2667	345	20	and	and	CCONJ
cana-2667	345	21	auc	auc	NOUN
cana-2667	345	22	:	:	PUNCT
cana-2667	345	23	the	the	DET
cana-2667	345	24	auc	auc	NOUN
cana-2667	345	25	score	score	NOUN
cana-2667	345	26	obtained	obtain	VERB
cana-2667	345	27	by	by	ADP
cana-2667	345	28	the	the	DET
cana-2667	345	29	hybrid	hybrid	NOUN
cana-2667	345	30	model	model	NOUN
cana-2667	345	31	was	be	AUX
cana-2667	345	32	0.964	0.964	NUM
cana-2667	345	33	which	which	PRON
cana-2667	345	34	outperformed	outperform	VERB
cana-2667	345	35	the	the	DET
cana-2667	345	36	cnn	cnn	PROPN
cana-2667	345	37	only	only	ADV
cana-2667	345	38	model	model	NOUN
cana-2667	345	39	(	(	PUNCT
cana-2667	345	40	0.930	0.930	NUM
cana-2667	345	41	)	)	PUNCT
cana-2667	345	42	and	and	CCONJ
cana-2667	345	43	the	the	DET
cana-2667	345	44	traditional	traditional	ADJ
cana-2667	345	45	svm	svm	NOUN
cana-2667	345	46	(	(	PUNCT
cana-2667	345	47	0.890	0.890	NUM
cana-2667	345	48	)	)	PUNCT
cana-2667	345	49	.	.	PUNCT
cana-2667	346	1	also	also	ADV
cana-2667	346	2	,	,	PUNCT
cana-2667	346	3	a	a	DET
cana-2667	346	4	strong	strong	ADJ
cana-2667	346	5	auc	auc	NOUN
cana-2667	346	6	score	score	NOUN
cana-2667	346	7	reflects	reflect	VERB
cana-2667	346	8	that	that	SCONJ
cana-2667	346	9	the	the	DET
cana-2667	346	10	hybrid	hybrid	NOUN
cana-2667	346	11	model	model	NOUN
cana-2667	346	12	is	be	AUX
cana-2667	346	13	more	more	ADV
cana-2667	346	14	robust	robust	ADJ
cana-2667	346	15	for	for	ADP
cana-2667	346	16	the	the	DET
cana-2667	346	17	purpose	purpose	NOUN
cana-2667	346	18	of	of	ADP
cana-2667	346	19	distinguishing	distinguish	VERB
cana-2667	346	20	healthy	healthy	ADJ
cana-2667	346	21	from	from	ADP
cana-2667	346	22	diseased	diseased	ADJ
cana-2667	346	23	retinal	retinal	ADJ
cana-2667	346	24	image	image	NOUN
cana-2667	346	25	.	.	PUNCT
cana-2667	347	1	table	table	NOUN
cana-2667	347	2	5	5	NUM
cana-2667	347	3	:	:	PUNCT
cana-2667	347	4	comparison	comparison	NOUN
cana-2667	347	5	of	of	ADP
cana-2667	347	6	feature	feature	NOUN
cana-2667	347	7	extraction	extraction	NOUN
cana-2667	347	8	techniques	technique	NOUN
cana-2667	347	9	feature	feature	NOUN
cana-2667	347	10	extraction	extraction	NOUN
cana-2667	347	11	method	method	NOUN
cana-2667	347	12	accuracy	accuracy	NOUN
cana-2667	347	13	(	(	PUNCT
cana-2667	347	14	%	%	INTJ
cana-2667	347	15	)	)	PUNCT
cana-2667	347	16	precision	precision	NOUN
cana-2667	347	17	(	(	PUNCT
cana-2667	347	18	%	%	INTJ
cana-2667	347	19	)	)	PUNCT
cana-2667	347	20	recall	recall	NOUN
cana-2667	347	21	(	(	PUNCT
cana-2667	347	22	%	%	NOUN
cana-2667	347	23	)	)	PUNCT
cana-2667	347	24	f1	f1	NOUN
cana-2667	347	25	-	-	PUNCT
cana-2667	347	26	score	score	NOUN
cana-2667	347	27	(	(	PUNCT
cana-2667	347	28	%	%	INTJ
cana-2667	347	29	)	)	PUNCT
cana-2667	347	30	hand	hand	NOUN
cana-2667	347	31	-	-	PUNCT
cana-2667	347	32	crafted	craft	VERB
cana-2667	347	33	features	feature	VERB
cana-2667	347	34	74.5	74.5	NUM
cana-2667	347	35	75.3	75.3	NUM
cana-2667	347	36	70.8	70.8	NUM
cana-2667	347	37	72.9	72.9	NUM
cana-2667	347	38	cnn	cnn	PROPN
cana-2667	347	39	features	feature	NOUN
cana-2667	347	40	(	(	PUNCT
cana-2667	347	41	pre	pre	ADJ
cana-2667	347	42	-	-	ADJ
cana-2667	347	43	trained	trained	ADJ
cana-2667	347	44	)	)	PUNCT
cana-2667	347	45	86.4	86.4	NUM
cana-2667	347	46	87.1	87.1	NUM
cana-2667	347	47	88.5	88.5	NUM
cana-2667	347	48	86.7	86.7	NUM
cana-2667	347	49	hybrid	hybrid	ADJ
cana-2667	347	50	cnn	cnn	PROPN
cana-2667	347	51	-	-	PUNCT
cana-2667	347	52	svm	svm	PROPN
cana-2667	347	53	features	feature	VERB
cana-2667	347	54	92.3	92.3	NUM
cana-2667	347	55	90.2	90.2	NUM
cana-2667	347	56	93.1	93.1	NUM
cana-2667	347	57	91.6	91.6	NUM
cana-2667	347	58	figure	figure	NOUN
cana-2667	347	59	4	4	NUM
cana-2667	347	60	.	.	PUNCT
cana-2667	347	61	confusion	confusion	NOUN
cana-2667	347	62	matrix	matrix	NOUN
cana-2667	347	63	for	for	ADP
cana-2667	347	64	hybrid	hybrid	ADJ
cana-2667	347	65	model	model	NOUN
cana-2667	347	66	impact	impact	NOUN
cana-2667	347	67	of	of	ADP
cana-2667	347	68	optimized	optimize	VERB
cana-2667	347	69	svm	svm	NOUN
cana-2667	347	70	we	we	PRON
cana-2667	347	71	optimized	optimize	VERB
cana-2667	347	72	the	the	DET
cana-2667	347	73	svm	svm	ADJ
cana-2667	347	74	classifier	classifier	NOUN
cana-2667	347	75	which	which	PRON
cana-2667	347	76	is	be	AUX
cana-2667	347	77	one	one	NUM
cana-2667	347	78	of	of	ADP
cana-2667	347	79	the	the	DET
cana-2667	347	80	main	main	ADJ
cana-2667	347	81	contributions	contribution	NOUN
cana-2667	347	82	of	of	ADP
cana-2667	347	83	this	this	DET
cana-2667	347	84	work	work	NOUN
cana-2667	347	85	.	.	PUNCT
cana-2667	348	1	the	the	DET
cana-2667	348	2	svm	svm	PROPN
cana-2667	348	3	achieved	achieve	VERB
cana-2667	348	4	a	a	DET
cana-2667	348	5	better	well	ADJ
cana-2667	348	6	generalization	generalization	NOUN
cana-2667	348	7	on	on	ADP
cana-2667	348	8	unseen	unseen	ADJ
cana-2667	348	9	data	datum	NOUN
cana-2667	348	10	by	by	ADP
cana-2667	348	11	parameter	parameter	NOUN
cana-2667	348	12	tuning	tune	VERB
cana-2667	348	13	the	the	DET
cana-2667	348	14	regularization	regularization	NOUN
cana-2667	348	15	parameter	parameter	NOUN
cana-2667	348	16	cc	cc	PROPN
cana-2667	348	17	and	and	CCONJ
cana-2667	348	18	the	the	DET
cana-2667	348	19	kernel	kernel	PROPN
cana-2667	348	20	function	function	PROPN
cana-2667	348	21	parameters	parameter	NOUN
cana-2667	348	22	.	.	PUNCT
cana-2667	349	1	using	use	VERB
cana-2667	349	2	an	an	DET
cana-2667	349	3	rbf	rbf	PROPN
cana-2667	349	4	kernel	kernel	PROPN
cana-2667	349	5	allowed	allow	VERB
cana-2667	349	6	the	the	DET
cana-2667	349	7	model	model	NOUN
cana-2667	349	8	to	to	PART
cana-2667	349	9	capture	capture	VERB
cana-2667	349	10	truly	truly	ADV
cana-2667	349	11	nonlinear	nonlinear	ADJ
cana-2667	349	12	decision	decision	NOUN
cana-2667	349	13	boundaries	boundary	NOUN
cana-2667	349	14	between	between	ADP
cana-2667	349	15	the	the	DET
cana-2667	349	16	various	various	ADJ
cana-2667	349	17	classes	class	NOUN
cana-2667	349	18	of	of	ADP
cana-2667	349	19	diabetic	diabetic	ADJ
cana-2667	349	20	retinopathy	retinopathy	NOUN
cana-2667	349	21	.	.	PUNCT
cana-2667	350	1	communications	communication	NOUN
cana-2667	350	2	on	on	ADP
cana-2667	350	3	applied	apply	VERB
cana-2667	350	4	nonlinear	nonlinear	ADJ
cana-2667	350	5	analysis	analysis	NOUN
cana-2667	350	6	issn	issn	NOUN
cana-2667	350	7	:	:	PUNCT
cana-2667	350	8	1074	1074	NUM
cana-2667	350	9	-	-	PUNCT
cana-2667	350	10	133x	133x	NUM
cana-2667	350	11	vol	vol	NOUN
cana-2667	350	12	32	32	NUM
cana-2667	350	13	no	no	NOUN
cana-2667	350	14	.	.	PUNCT
cana-2667	351	1	3s	3s	NUM
cana-2667	351	2	(	(	PUNCT
cana-2667	351	3	2025	2025	NUM
cana-2667	351	4	)	)	PUNCT
cana-2667	351	5	399	399	NUM
cana-2667	351	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	351	7	table	table	NOUN
cana-2667	351	8	6	6	NUM
cana-2667	351	9	:	:	PUNCT
cana-2667	351	10	inference	inference	NOUN
cana-2667	351	11	time	time	PROPN
cana-2667	351	12	comparison	comparison	NOUN
cana-2667	351	13	model	model	NOUN
cana-2667	351	14	inference	inference	PROPN
cana-2667	351	15	time	time	NOUN
cana-2667	351	16	(	(	PUNCT
cana-2667	351	17	secs	secs	X
cana-2667	351	18	)	)	PUNCT
cana-2667	351	19	cnn	cnn	PROPN
cana-2667	351	20	-	-	PUNCT
cana-2667	351	21	svm	svm	PROPN
cana-2667	351	22	hybrid	hybrid	NOUN
cana-2667	351	23	model	model	NOUN
cana-2667	351	24	1.9	1.9	NUM
cana-2667	351	25	cnn	cnn	PROPN
cana-2667	351	26	-	-	PUNCT
cana-2667	351	27	only	only	ADV
cana-2667	351	28	model	model	NOUN
cana-2667	351	29	2.2	2.2	NUM
cana-2667	351	30	traditional	traditional	ADJ
cana-2667	351	31	svm	svm	PROPN
cana-2667	351	32	1.4	1.4	NUM
cana-2667	351	33	deep	deep	ADJ
cana-2667	351	34	cnn	cnn	PROPN
cana-2667	351	35	(	(	PUNCT
cana-2667	351	36	fully	fully	ADV
cana-2667	351	37	connected	connect	VERB
cana-2667	351	38	)	)	PUNCT
cana-2667	351	39	2.6	2.6	NUM
cana-2667	351	40	it	it	PRON
cana-2667	351	41	was	be	AUX
cana-2667	351	42	also	also	ADV
cana-2667	351	43	shown	show	VERB
cana-2667	351	44	in	in	ADP
cana-2667	351	45	the	the	DET
cana-2667	351	46	optimization	optimization	NOUN
cana-2667	351	47	of	of	ADP
cana-2667	351	48	the	the	DET
cana-2667	351	49	cnn	cnn	PROPN
cana-2667	351	50	-	-	PUNCT
cana-2667	351	51	svm	svm	PROPN
cana-2667	351	52	hybrid	hybrid	NOUN
cana-2667	351	53	model	model	NOUN
cana-2667	351	54	that	that	SCONJ
cana-2667	351	55	fine	fine	NOUN
cana-2667	351	56	-	-	PUNCT
cana-2667	351	57	tuning	tuning	NOUN
cana-2667	351	58	of	of	ADP
cana-2667	351	59	both	both	DET
cana-2667	351	60	cnn	cnn	PROPN
cana-2667	351	61	and	and	CCONJ
cana-2667	351	62	svm	svm	ADJ
cana-2667	351	63	models	model	NOUN
cana-2667	351	64	could	could	AUX
cana-2667	351	65	significantly	significantly	ADV
cana-2667	351	66	boost	boost	VERB
cana-2667	351	67	the	the	DET
cana-2667	351	68	classification	classification	NOUN
cana-2667	351	69	performance	performance	NOUN
cana-2667	351	70	.	.	PUNCT
cana-2667	352	1	in	in	ADP
cana-2667	352	2	our	our	PRON
cana-2667	352	3	implementation	implementation	NOUN
cana-2667	352	4	,	,	PUNCT
cana-2667	352	5	the	the	DET
cana-2667	352	6	cnn	cnn	PROPN
cana-2667	352	7	was	be	AUX
cana-2667	352	8	pre	pre	VERB
cana-2667	352	9	-	-	VERB
cana-2667	352	10	trained	train	VERB
cana-2667	352	11	over	over	ADP
cana-2667	352	12	a	a	DET
cana-2667	352	13	very	very	ADV
cana-2667	352	14	big	big	ADJ
cana-2667	352	15	dataset	dataset	NOUN
cana-2667	352	16	(	(	PUNCT
cana-2667	352	17	imagenet	imagenet	NOUN
cana-2667	352	18	)	)	PUNCT
cana-2667	352	19	giving	give	VERB
cana-2667	352	20	high	high	ADJ
cana-2667	352	21	initial	initial	ADJ
cana-2667	352	22	weights	weight	NOUN
cana-2667	352	23	.	.	PUNCT
cana-2667	353	1	next	next	ADV
cana-2667	353	2	,	,	PUNCT
cana-2667	353	3	we	we	PRON
cana-2667	353	4	finetuned	finetune	VERB
cana-2667	353	5	the	the	DET
cana-2667	353	6	cnn	cnn	NOUN
cana-2667	353	7	on	on	ADP
cana-2667	353	8	the	the	DET
cana-2667	353	9	diabetic	diabetic	ADJ
cana-2667	353	10	retinopathy	retinopathy	ADJ
cana-2667	353	11	dataset	dataset	VERB
cana-2667	353	12	for	for	ADP
cana-2667	353	13	better	well	ADJ
cana-2667	353	14	feature	feature	NOUN
cana-2667	353	15	extraction	extraction	NOUN
cana-2667	353	16	from	from	ADP
cana-2667	353	17	the	the	DET
cana-2667	353	18	images	image	NOUN
cana-2667	353	19	.	.	PUNCT
cana-2667	354	1	the	the	DET
cana-2667	354	2	svm	svm	PROPN
cana-2667	354	3	used	use	VERB
cana-2667	354	4	these	these	DET
cana-2667	354	5	features	feature	NOUN
cana-2667	354	6	as	as	ADP
cana-2667	354	7	input	input	NOUN
cana-2667	354	8	to	to	PART
cana-2667	354	9	classify	classify	VERB
cana-2667	354	10	the	the	DET
cana-2667	354	11	images	image	NOUN
cana-2667	354	12	,	,	PUNCT
cana-2667	354	13	which	which	PRON
cana-2667	354	14	resulted	result	VERB
cana-2667	354	15	in	in	ADP
cana-2667	354	16	improved	improved	ADJ
cana-2667	354	17	accuracy	accuracy	NOUN
cana-2667	354	18	and	and	CCONJ
cana-2667	354	19	efficiency	efficiency	NOUN
cana-2667	354	20	.	.	PUNCT
cana-2667	355	1	figure	figure	NOUN
cana-2667	355	2	5	5	NUM
cana-2667	355	3	.	.	PUNCT
cana-2667	355	4	comparison	comparison	NOUN
cana-2667	355	5	of	of	ADP
cana-2667	355	6	training	training	NOUN
cana-2667	355	7	time	time	NOUN
cana-2667	355	8	for	for	ADP
cana-2667	355	9	different	different	ADJ
cana-2667	355	10	models	model	NOUN
cana-2667	355	11	assessing	assess	VERB
cana-2667	355	12	the	the	DET
cana-2667	355	13	misclassifications	misclassification	NOUN
cana-2667	355	14	even	even	ADV
cana-2667	355	15	with	with	ADP
cana-2667	355	16	the	the	DET
cana-2667	355	17	high	high	ADJ
cana-2667	355	18	performance	performance	NOUN
cana-2667	355	19	,	,	PUNCT
cana-2667	355	20	the	the	DET
cana-2667	355	21	model	model	NOUN
cana-2667	355	22	showed	show	VERB
cana-2667	355	23	some	some	DET
cana-2667	355	24	misclassifications	misclassification	NOUN
cana-2667	355	25	around	around	ADP
cana-2667	355	26	the	the	DET
cana-2667	355	27	mild	mild	NOUN
cana-2667	355	28	to	to	ADP
cana-2667	355	29	moderate	moderate	ADJ
cana-2667	355	30	diabetic	diabetic	ADJ
cana-2667	355	31	retinopathy	retinopathy	NOUN
cana-2667	355	32	.	.	PUNCT
cana-2667	356	1	this	this	PRON
cana-2667	356	2	is	be	AUX
cana-2667	356	3	a	a	DET
cana-2667	356	4	notoriously	notoriously	ADV
cana-2667	356	5	difficult	difficult	ADJ
cana-2667	356	6	problem	problem	NOUN
cana-2667	356	7	in	in	ADP
cana-2667	356	8	the	the	DET
cana-2667	356	9	context	context	NOUN
cana-2667	356	10	of	of	ADP
cana-2667	356	11	medical	medical	ADJ
cana-2667	356	12	imaging	imaging	NOUN
cana-2667	356	13	,	,	PUNCT
cana-2667	356	14	as	as	SCONJ
cana-2667	356	15	the	the	DET
cana-2667	356	16	differences	difference	NOUN
cana-2667	356	17	between	between	ADP
cana-2667	356	18	between	between	ADP
cana-2667	356	19	visualizing	visualize	VERB
cana-2667	356	20	these	these	DET
cana-2667	356	21	two	two	NUM
cana-2667	356	22	severity	severity	NOUN
cana-2667	356	23	scores	score	NOUN
cana-2667	356	24	tend	tend	VERB
cana-2667	356	25	to	to	PART
cana-2667	356	26	be	be	AUX
cana-2667	356	27	small	small	ADJ
cana-2667	356	28	and	and	CCONJ
cana-2667	356	29	difficult	difficult	ADJ
cana-2667	356	30	to	to	PART
cana-2667	356	31	detect	detect	VERB
cana-2667	356	32	using	use	VERB
cana-2667	356	33	automated	automate	VERB
cana-2667	356	34	systems	system	NOUN
cana-2667	356	35	.	.	PUNCT
cana-2667	357	1	upon	upon	SCONJ
cana-2667	357	2	further	further	ADJ
cana-2667	357	3	analysis	analysis	NOUN
cana-2667	357	4	of	of	ADP
cana-2667	357	5	the	the	DET
cana-2667	357	6	misclassified	misclassifie	VERB
cana-2667	357	7	images	image	NOUN
cana-2667	357	8	,	,	PUNCT
cana-2667	357	9	it	it	PRON
cana-2667	357	10	was	be	AUX
cana-2667	357	11	found	find	VERB
cana-2667	357	12	that	that	SCONJ
cana-2667	357	13	wide	wide	ADJ
cana-2667	357	14	range	range	NOUN
cana-2667	357	15	of	of	ADP
cana-2667	357	16	artifacts	artifact	NOUN
cana-2667	357	17	,	,	PUNCT
cana-2667	357	18	like	like	ADP
cana-2667	357	19	glare	glare	NOUN
cana-2667	357	20	,	,	PUNCT
cana-2667	357	21	noise	noise	NOUN
cana-2667	357	22	,	,	PUNCT
cana-2667	357	23	image	image	NOUN
cana-2667	357	24	low	low	ADJ
cana-2667	357	25	resolution	resolution	NOUN
cana-2667	357	26	etc	etc	X
cana-2667	357	27	.	.	X
cana-2667	357	28	,	,	PUNCT
cana-2667	357	29	led	lead	VERB
cana-2667	357	30	to	to	ADP
cana-2667	357	31	the	the	DET
cana-2667	357	32	incorrect	incorrect	ADJ
cana-2667	357	33	classification	classification	NOUN
cana-2667	357	34	.	.	PUNCT
cana-2667	358	1	however	however	ADV
cana-2667	358	2	,	,	PUNCT
cana-2667	358	3	the	the	DET
cana-2667	358	4	overlapping	overlapping	NOUN
cana-2667	358	5	presented	present	VERB
cana-2667	358	6	in	in	ADP
cana-2667	358	7	the	the	DET
cana-2667	358	8	features	feature	NOUN
cana-2667	358	9	extracted	extract	VERB
cana-2667	358	10	from	from	ADP
cana-2667	358	11	the	the	DET
cana-2667	358	12	retinal	retinal	ADJ
cana-2667	358	13	images	image	NOUN
cana-2667	358	14	of	of	ADP
cana-2667	358	15	patients	patient	NOUN
cana-2667	358	16	with	with	ADP
cana-2667	358	17	mild	mild	ADJ
cana-2667	358	18	and	and	CCONJ
cana-2667	358	19	moderate	moderate	ADJ
cana-2667	358	20	diabetic	diabetic	ADJ
cana-2667	358	21	retinopathy	retinopathy	NOUN
cana-2667	358	22	were	be	AUX
cana-2667	358	23	also	also	ADV
cana-2667	358	24	difficult	difficult	ADJ
cana-2667	358	25	for	for	SCONJ
cana-2667	358	26	the	the	DET
cana-2667	358	27	model	model	NOUN
cana-2667	358	28	to	to	PART
cana-2667	358	29	predict	predict	VERB
cana-2667	358	30	.	.	PUNCT
cana-2667	359	1	communications	communication	NOUN
cana-2667	359	2	on	on	ADP
cana-2667	359	3	applied	apply	VERB
cana-2667	359	4	nonlinear	nonlinear	ADJ
cana-2667	359	5	analysis	analysis	NOUN
cana-2667	359	6	issn	issn	NOUN
cana-2667	359	7	:	:	PUNCT
cana-2667	359	8	1074	1074	NUM
cana-2667	359	9	-	-	PUNCT
cana-2667	359	10	133x	133x	NUM
cana-2667	359	11	vol	vol	NOUN
cana-2667	359	12	32	32	NUM
cana-2667	359	13	no	no	NOUN
cana-2667	359	14	.	.	PUNCT
cana-2667	360	1	3s	3s	NUM
cana-2667	360	2	(	(	PUNCT
cana-2667	360	3	2025	2025	NUM
cana-2667	360	4	)	)	PUNCT
cana-2667	360	5	400	400	NUM
cana-2667	360	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	360	7	figure	figure	NOUN
cana-2667	360	8	6	6	NUM
cana-2667	360	9	.	.	PUNCT
cana-2667	360	10	comparison	comparison	NOUN
cana-2667	360	11	of	of	ADP
cana-2667	360	12	inference	inference	NOUN
cana-2667	360	13	time	time	NOUN
cana-2667	360	14	for	for	ADP
cana-2667	360	15	different	different	ADJ
cana-2667	360	16	models	model	NOUN
cana-2667	360	17	table	table	VERB
cana-2667	360	18	7	7	NUM
cana-2667	360	19	:	:	PUNCT
cana-2667	360	20	misclassification	misclassification	NOUN
cana-2667	360	21	analysis	analysis	NOUN
cana-2667	360	22	predicted	predict	VERB
cana-2667	360	23	/	/	PUNCT
cana-2667	360	24	actual	actual	ADJ
cana-2667	360	25	no	no	DET
cana-2667	360	26	dr	dr	PROPN
cana-2667	360	27	(	(	PUNCT
cana-2667	360	28	0	0	NUM
cana-2667	360	29	)	)	PUNCT
cana-2667	360	30	mild	mild	ADJ
cana-2667	360	31	dr	dr	PROPN
cana-2667	360	32	(	(	PUNCT
cana-2667	360	33	1	1	NUM
cana-2667	360	34	)	)	PUNCT
cana-2667	360	35	moderate	moderate	ADJ
cana-2667	360	36	dr	dr	PROPN
cana-2667	360	37	(	(	PUNCT
cana-2667	360	38	2	2	NUM
cana-2667	360	39	)	)	PUNCT
cana-2667	360	40	severe	severe	ADJ
cana-2667	360	41	dr	dr	PROPN
cana-2667	360	42	(	(	PUNCT
cana-2667	360	43	3	3	NUM
cana-2667	360	44	)	)	PUNCT
cana-2667	360	45	pdr	pdr	PROPN
cana-2667	360	46	(	(	PUNCT
cana-2667	360	47	4	4	X
cana-2667	360	48	)	)	PUNCT
cana-2667	360	49	no	no	DET
cana-2667	360	50	dr	dr	PROPN
cana-2667	360	51	(	(	PUNCT
cana-2667	360	52	0	0	NUM
cana-2667	360	53	)	)	PUNCT
cana-2667	360	54	3500	3500	NUM
cana-2667	360	55	150	150	NUM
cana-2667	360	56	100	100	NUM
cana-2667	360	57	50	50	NUM
cana-2667	360	58	30	30	NUM
cana-2667	360	59	mild	mild	ADJ
cana-2667	360	60	dr	dr	NOUN
cana-2667	360	61	(	(	PUNCT
cana-2667	360	62	1	1	NUM
cana-2667	360	63	)	)	PUNCT
cana-2667	360	64	120	120	NUM
cana-2667	360	65	3400	3400	NUM
cana-2667	360	66	250	250	NUM
cana-2667	360	67	150	150	NUM
cana-2667	360	68	70	70	NUM
cana-2667	360	69	moderate	moderate	ADJ
cana-2667	360	70	dr	dr	PROPN
cana-2667	360	71	(	(	PUNCT
cana-2667	360	72	2	2	NUM
cana-2667	360	73	)	)	PUNCT
cana-2667	360	74	80	80	NUM
cana-2667	360	75	230	230	NUM
cana-2667	360	76	3300	3300	NUM
cana-2667	360	77	200	200	NUM
cana-2667	360	78	100	100	NUM
cana-2667	360	79	severe	severe	ADJ
cana-2667	360	80	dr	dr	PROPN
cana-2667	360	81	(	(	PUNCT
cana-2667	360	82	3	3	NUM
cana-2667	360	83	)	)	PUNCT
cana-2667	360	84	60	60	NUM
cana-2667	360	85	170	170	NUM
cana-2667	360	86	280	280	NUM
cana-2667	360	87	3200	3200	NUM
cana-2667	360	88	150	150	NUM
cana-2667	360	89	pdr	pdr	NOUN
cana-2667	360	90	(	(	PUNCT
cana-2667	360	91	4	4	NUM
cana-2667	360	92	)	)	PUNCT
cana-2667	360	93	50	50	NUM
cana-2667	360	94	100	100	NUM
cana-2667	360	95	120	120	NUM
cana-2667	360	96	200	200	NUM
cana-2667	360	97	3200	3200	NUM
cana-2667	360	98	computational	computational	ADJ
cana-2667	360	99	efficiency	efficiency	NOUN
cana-2667	360	100	training	training	NOUN
cana-2667	360	101	time	time	NOUN
cana-2667	360	102	and	and	CCONJ
cana-2667	360	103	inference	inference	NOUN
cana-2667	360	104	time	time	NOUN
cana-2667	360	105	were	be	AUX
cana-2667	360	106	measured	measure	VERB
cana-2667	360	107	for	for	ADP
cana-2667	360	108	each	each	DET
cana-2667	360	109	model	model	NOUN
cana-2667	360	110	,	,	PUNCT
cana-2667	360	111	and	and	CCONJ
cana-2667	360	112	the	the	DET
cana-2667	360	113	model	model	NOUN
cana-2667	360	114	's	's	PART
cana-2667	360	115	computational	computational	ADJ
cana-2667	360	116	efficiency	efficiency	NOUN
cana-2667	360	117	was	be	AUX
cana-2667	360	118	also	also	ADV
cana-2667	360	119	evaluated	evaluate	VERB
cana-2667	360	120	.	.	PUNCT
cana-2667	361	1	the	the	DET
cana-2667	361	2	results	result	NOUN
cana-2667	361	3	obtained	obtain	VERB
cana-2667	361	4	in	in	ADP
cana-2667	361	5	this	this	DET
cana-2667	361	6	study	study	NOUN
cana-2667	361	7	demonstrated	demonstrate	VERB
cana-2667	361	8	that	that	SCONJ
cana-2667	361	9	the	the	DET
cana-2667	361	10	cnn	cnn	PROPN
cana-2667	361	11	-	-	PUNCT
cana-2667	361	12	svm	svm	PROPN
cana-2667	361	13	hybrid	hybrid	NOUN
cana-2667	361	14	model	model	NOUN
cana-2667	361	15	required	require	VERB
cana-2667	361	16	2.5	2.5	NUM
cana-2667	361	17	hours	hour	NOUN
cana-2667	361	18	to	to	PART
cana-2667	361	19	train	train	VERB
cana-2667	361	20	on	on	ADP
cana-2667	361	21	the	the	DET
cana-2667	361	22	full	full	ADJ
cana-2667	361	23	training	training	NOUN
cana-2667	361	24	dataset	dataset	NOUN
cana-2667	361	25	,	,	PUNCT
cana-2667	361	26	which	which	PRON
cana-2667	361	27	was	be	AUX
cana-2667	361	28	much	much	ADV
cana-2667	361	29	faster	fast	ADJ
cana-2667	361	30	than	than	ADP
cana-2667	361	31	training	train	VERB
cana-2667	361	32	a	a	DET
cana-2667	361	33	deep	deep	ADJ
cana-2667	361	34	cnn	cnn	PROPN
cana-2667	361	35	model	model	NOUN
cana-2667	361	36	with	with	ADP
cana-2667	361	37	fully	fully	ADV
cana-2667	361	38	connected	connected	ADJ
cana-2667	361	39	layers	layer	NOUN
cana-2667	361	40	for	for	ADP
cana-2667	361	41	classification	classification	NOUN
cana-2667	361	42	(	(	PUNCT
cana-2667	361	43	6	6	NUM
cana-2667	361	44	hours	hour	NOUN
cana-2667	361	45	)	)	PUNCT
cana-2667	361	46	.	.	PUNCT
cana-2667	362	1	the	the	DET
cana-2667	362	2	hybrid	hybrid	NOUN
cana-2667	362	3	model	model	NOUN
cana-2667	362	4	was	be	AUX
cana-2667	362	5	also	also	ADV
cana-2667	362	6	found	find	VERB
cana-2667	362	7	to	to	PART
cana-2667	362	8	be	be	AUX
cana-2667	362	9	applicable	applicable	ADJ
cana-2667	362	10	in	in	ADP
cana-2667	362	11	real	real	ADJ
cana-2667	362	12	-	-	PUNCT
cana-2667	362	13	time	time	NOUN
cana-2667	362	14	clinical	clinical	ADJ
cana-2667	362	15	state	state	NOUN
cana-2667	362	16	as	as	ADP
cana-2667	362	17	the	the	DET
cana-2667	362	18	time	time	NOUN
cana-2667	362	19	for	for	ADP
cana-2667	362	20	inference	inference	NOUN
cana-2667	362	21	of	of	ADP
cana-2667	362	22	the	the	DET
cana-2667	362	23	new	new	ADJ
cana-2667	362	24	retinal	retinal	ADJ
cana-2667	362	25	image	image	NOUN
cana-2667	362	26	for	for	ADP
cana-2667	362	27	the	the	DET
cana-2667	362	28	classification	classification	NOUN
cana-2667	362	29	was	be	AUX
cana-2667	362	30	less	less	ADJ
cana-2667	362	31	than	than	ADP
cana-2667	362	32	2	2	NUM
cana-2667	362	33	seconds	second	NOUN
cana-2667	362	34	.	.	PUNCT
cana-2667	363	1	table	table	NOUN
cana-2667	363	2	8	8	NUM
cana-2667	363	3	:	:	PUNCT
cana-2667	363	4	training	training	NOUN
cana-2667	363	5	time	time	NOUN
cana-2667	363	6	comparison	comparison	NOUN
cana-2667	363	7	model	model	NOUN
cana-2667	363	8	training	training	NOUN
cana-2667	363	9	time	time	NOUN
cana-2667	363	10	(	(	PUNCT
cana-2667	363	11	hrs	hrs	NOUN
cana-2667	363	12	)	)	PUNCT
cana-2667	363	13	cnn	cnn	PROPN
cana-2667	363	14	-	-	PUNCT
cana-2667	363	15	svm	svm	PROPN
cana-2667	363	16	hybrid	hybrid	NOUN
cana-2667	363	17	model	model	NOUN
cana-2667	363	18	2.5	2.5	NUM
cana-2667	363	19	cnn	cnn	PROPN
cana-2667	363	20	-	-	PUNCT
cana-2667	363	21	only	only	ADV
cana-2667	363	22	model	model	NOUN
cana-2667	363	23	6.0	6.0	NUM
cana-2667	363	24	traditional	traditional	ADJ
cana-2667	363	25	svm	svm	PROPN
cana-2667	363	26	1.5	1.5	NUM
cana-2667	363	27	deep	deep	ADJ
cana-2667	363	28	cnn	cnn	PROPN
cana-2667	363	29	(	(	PUNCT
cana-2667	363	30	fully	fully	ADV
cana-2667	363	31	connected	connect	VERB
cana-2667	363	32	)	)	PUNCT
cana-2667	363	33	7.0	7.0	NUM
cana-2667	363	34	communications	communication	NOUN
cana-2667	363	35	on	on	ADP
cana-2667	363	36	applied	apply	VERB
cana-2667	363	37	nonlinear	nonlinear	ADJ
cana-2667	363	38	analysis	analysis	NOUN
cana-2667	363	39	issn	issn	NOUN
cana-2667	363	40	:	:	PUNCT
cana-2667	363	41	1074	1074	NUM
cana-2667	363	42	-	-	PUNCT
cana-2667	363	43	133x	133x	NUM
cana-2667	363	44	vol	vol	NOUN
cana-2667	363	45	32	32	NUM
cana-2667	363	46	no	no	NOUN
cana-2667	363	47	.	.	PUNCT
cana-2667	364	1	3s	3s	NUM
cana-2667	364	2	(	(	PUNCT
cana-2667	364	3	2025	2025	NUM
cana-2667	364	4	)	)	PUNCT
cana-2667	364	5	401	401	NUM
cana-2667	364	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	364	7	qualitative	qualitative	ADJ
cana-2667	364	8	analysis	analysis	NOUN
cana-2667	364	9	to	to	PART
cana-2667	364	10	confirm	confirm	VERB
cana-2667	364	11	the	the	DET
cana-2667	364	12	results	result	NOUN
cana-2667	364	13	,	,	PUNCT
cana-2667	364	14	qualitative	qualitative	ADJ
cana-2667	364	15	analysis	analysis	NOUN
cana-2667	364	16	was	be	AUX
cana-2667	364	17	conducted	conduct	VERB
cana-2667	364	18	by	by	ADP
cana-2667	364	19	assessing	assess	VERB
cana-2667	364	20	the	the	DET
cana-2667	364	21	activation	activation	NOUN
cana-2667	364	22	maps	map	NOUN
cana-2667	364	23	produced	produce	VERB
cana-2667	364	24	by	by	ADP
cana-2667	364	25	the	the	DET
cana-2667	364	26	cnn	cnn	PROPN
cana-2667	364	27	layers	layer	NOUN
cana-2667	364	28	for	for	ADP
cana-2667	364	29	the	the	DET
cana-2667	364	30	severity	severity	NOUN
cana-2667	364	31	of	of	ADP
cana-2667	364	32	dr	dr	PROPN
cana-2667	364	33	.	.	PROPN
cana-2667	364	34	such	such	ADJ
cana-2667	364	35	activation	activation	NOUN
cana-2667	364	36	maps	map	NOUN
cana-2667	364	37	indicate	indicate	VERB
cana-2667	364	38	the	the	DET
cana-2667	364	39	parts	part	NOUN
cana-2667	364	40	of	of	ADP
cana-2667	364	41	the	the	DET
cana-2667	364	42	retinal	retinal	ADJ
cana-2667	364	43	images	image	NOUN
cana-2667	364	44	that	that	PRON
cana-2667	364	45	the	the	DET
cana-2667	364	46	cnn	cnn	PROPN
cana-2667	364	47	was	be	AUX
cana-2667	364	48	attending	attend	VERB
cana-2667	364	49	to	to	PART
cana-2667	364	50	while	while	SCONJ
cana-2667	364	51	performing	perform	VERB
cana-2667	364	52	feature	feature	NOUN
cana-2667	364	53	extraction	extraction	NOUN
cana-2667	364	54	.	.	PUNCT
cana-2667	365	1	for	for	ADP
cana-2667	365	2	example	example	NOUN
cana-2667	365	3	,	,	PUNCT
cana-2667	365	4	when	when	SCONJ
cana-2667	365	5	detecting	detect	VERB
cana-2667	365	6	pdr	pdr	PROPN
cana-2667	365	7	,	,	PUNCT
cana-2667	365	8	the	the	DET
cana-2667	365	9	cnn	cnn	PROPN
cana-2667	365	10	was	be	AUX
cana-2667	365	11	seen	see	VERB
cana-2667	365	12	to	to	PART
cana-2667	365	13	focus	focus	VERB
cana-2667	365	14	on	on	ADP
cana-2667	365	15	regions	region	NOUN
cana-2667	365	16	of	of	ADP
cana-2667	365	17	the	the	DET
cana-2667	365	18	retina	retina	NOUN
cana-2667	365	19	corresponding	correspond	VERB
cana-2667	365	20	to	to	ADP
cana-2667	365	21	the	the	DET
cana-2667	365	22	fovea	fovea	NOUN
cana-2667	365	23	,	,	PUNCT
cana-2667	365	24	while	while	SCONJ
cana-2667	365	25	in	in	ADP
cana-2667	365	26	milder	mild	ADJ
cana-2667	365	27	forms	form	NOUN
cana-2667	365	28	it	it	PRON
cana-2667	365	29	was	be	AUX
cana-2667	365	30	emphasizing	emphasize	VERB
cana-2667	365	31	the	the	DET
cana-2667	365	32	detection	detection	NOUN
cana-2667	365	33	of	of	ADP
cana-2667	365	34	microaneurysms	microaneurysm	NOUN
cana-2667	365	35	and	and	CCONJ
cana-2667	365	36	exudates	exudate	NOUN
cana-2667	365	37	.	.	PUNCT
cana-2667	366	1	these	these	DET
cana-2667	366	2	visualizations	visualization	NOUN
cana-2667	366	3	confirmed	confirm	VERB
cana-2667	366	4	that	that	SCONJ
cana-2667	366	5	the	the	DET
cana-2667	366	6	cnn	cnn	PROPN
cana-2667	366	7	was	be	AUX
cana-2667	366	8	learning	learn	VERB
cana-2667	366	9	informative	informative	ADJ
cana-2667	366	10	features	feature	NOUN
cana-2667	366	11	suitable	suitable	ADJ
cana-2667	366	12	for	for	ADP
cana-2667	366	13	diabetic	diabetic	ADJ
cana-2667	366	14	retinopathy	retinopathy	ADJ
cana-2667	366	15	classification	classification	NOUN
cana-2667	366	16	,	,	PUNCT
cana-2667	366	17	and	and	CCONJ
cana-2667	366	18	the	the	DET
cana-2667	366	19	classifier(species	classifier(specie	NOUN
cana-2667	366	20	)	)	PUNCT
cana-2667	366	21	was	be	AUX
cana-2667	366	22	accurately	accurately	ADV
cana-2667	366	23	predicting	predict	VERB
cana-2667	366	24	using	use	VERB
cana-2667	366	25	the	the	DET
cana-2667	366	26	learned	learn	VERB
cana-2667	366	27	features	feature	NOUN
cana-2667	366	28	provided	provide	VERB
cana-2667	366	29	by	by	ADP
cana-2667	366	30	cnn	cnn	PROPN
cana-2667	366	31	.	.	PUNCT
cana-2667	367	1	figure	figure	VERB
cana-2667	367	2	7	7	NUM
cana-2667	367	3	.	.	PUNCT
cana-2667	367	4	performance	performance	NOUN
cana-2667	367	5	metrics	metric	NOUN
cana-2667	367	6	for	for	ADP
cana-2667	367	7	different	different	ADJ
cana-2667	367	8	models	model	NOUN
cana-2667	367	9	as	as	SCONJ
cana-2667	367	10	the	the	DET
cana-2667	367	11	results	result	NOUN
cana-2667	367	12	of	of	ADP
cana-2667	367	13	the	the	DET
cana-2667	367	14	experiments	experiment	NOUN
cana-2667	367	15	demonstrate	demonstrate	VERB
cana-2667	367	16	,	,	PUNCT
cana-2667	367	17	the	the	DET
cana-2667	367	18	proposed	propose	VERB
cana-2667	367	19	hybrid	hybrid	NOUN
cana-2667	367	20	model	model	NOUN
cana-2667	367	21	which	which	PRON
cana-2667	367	22	combines	combine	VERB
cana-2667	367	23	cnn	cnn	PROPN
cana-2667	367	24	for	for	ADP
cana-2667	367	25	the	the	DET
cana-2667	367	26	feature	feature	NOUN
cana-2667	367	27	extraction	extraction	NOUN
cana-2667	367	28	and	and	CCONJ
cana-2667	367	29	svm	svm	NOUN
cana-2667	367	30	for	for	ADP
cana-2667	367	31	the	the	DET
cana-2667	367	32	classification	classification	NOUN
cana-2667	367	33	,	,	PUNCT
cana-2667	367	34	proves	prove	VERB
cana-2667	367	35	to	to	PART
cana-2667	367	36	be	be	AUX
cana-2667	367	37	a	a	DET
cana-2667	367	38	highly	highly	ADV
cana-2667	367	39	effective	effective	ADJ
cana-2667	367	40	tool	tool	NOUN
cana-2667	367	41	for	for	ADP
cana-2667	367	42	diabetic	diabetic	ADJ
cana-2667	367	43	retinopathy	retinopathy	ADJ
cana-2667	367	44	detection	detection	NOUN
cana-2667	367	45	.	.	PUNCT
cana-2667	368	1	the	the	DET
cana-2667	368	2	tuned	tuned	ADJ
cana-2667	368	3	svm	svm	PROPN
cana-2667	368	4	enhanced	enhance	VERB
cana-2667	368	5	model	model	NOUN
cana-2667	368	6	's	's	PART
cana-2667	368	7	generalization	generalization	NOUN
cana-2667	368	8	ability	ability	NOUN
cana-2667	368	9	and	and	CCONJ
cana-2667	368	10	obtained	obtain	VERB
cana-2667	368	11	high	high	ADJ
cana-2667	368	12	classification	classification	NOUN
cana-2667	368	13	scores	score	NOUN
cana-2667	368	14	of	of	ADP
cana-2667	368	15	accuracy	accuracy	NOUN
cana-2667	368	16	,	,	PUNCT
cana-2667	368	17	precision	precision	NOUN
cana-2667	368	18	,	,	PUNCT
cana-2667	368	19	recall	recall	NOUN
cana-2667	368	20	,	,	PUNCT
cana-2667	368	21	and	and	CCONJ
cana-2667	368	22	f1	f1	NOUN
cana-2667	368	23	.	.	PUNCT
cana-2667	369	1	the	the	DET
cana-2667	369	2	hybrid	hybrid	NOUN
cana-2667	369	3	model	model	NOUN
cana-2667	369	4	also	also	ADV
cana-2667	369	5	achieved	achieve	VERB
cana-2667	369	6	superior	superior	ADJ
cana-2667	369	7	accuracy	accuracy	NOUN
cana-2667	369	8	and	and	CCONJ
cana-2667	369	9	efficiency	efficiency	NOUN
cana-2667	369	10	compared	compare	VERB
cana-2667	369	11	to	to	ADP
cana-2667	369	12	individual	individual	ADJ
cana-2667	369	13	cnn	cnn	PROPN
cana-2667	369	14	or	or	CCONJ
cana-2667	369	15	traditional	traditional	ADJ
cana-2667	369	16	machine	machine	NOUN
cana-2667	369	17	learning	learning	NOUN
cana-2667	369	18	models	model	NOUN
cana-2667	369	19	.	.	PUNCT
cana-2667	370	1	this	this	DET
cana-2667	370	2	methodology	methodology	NOUN
cana-2667	370	3	can	can	AUX
cana-2667	370	4	be	be	AUX
cana-2667	370	5	translated	translate	VERB
cana-2667	370	6	into	into	ADP
cana-2667	370	7	the	the	DET
cana-2667	370	8	clinical	clinical	ADJ
cana-2667	370	9	environment	environment	NOUN
cana-2667	370	10	for	for	ADP
cana-2667	370	11	early	early	ADJ
cana-2667	370	12	diagnosis	diagnosis	NOUN
cana-2667	370	13	and	and	CCONJ
cana-2667	370	14	monitoring	monitoring	NOUN
cana-2667	370	15	of	of	ADP
cana-2667	370	16	diabetic	diabetic	ADJ
cana-2667	370	17	retinopathy	retinopathy	NOUN
cana-2667	370	18	,	,	PUNCT
cana-2667	370	19	which	which	PRON
cana-2667	370	20	in	in	ADP
cana-2667	370	21	turn	turn	NOUN
cana-2667	370	22	can	can	AUX
cana-2667	370	23	greatly	greatly	ADV
cana-2667	370	24	enhance	enhance	VERB
cana-2667	370	25	patient	patient	ADJ
cana-2667	370	26	outcomes	outcome	NOUN
cana-2667	370	27	by	by	ADP
cana-2667	370	28	providing	provide	VERB
cana-2667	370	29	treatment	treatment	NOUN
cana-2667	370	30	during	during	ADP
cana-2667	370	31	the	the	DET
cana-2667	370	32	early	early	ADJ
cana-2667	370	33	stages	stage	NOUN
cana-2667	370	34	.	.	PUNCT
cana-2667	371	1	we	we	PRON
cana-2667	371	2	show	show	VERB
cana-2667	371	3	different	different	ADJ
cana-2667	371	4	tables	table	NOUN
cana-2667	371	5	with	with	ADP
cana-2667	371	6	detailed	detailed	ADJ
cana-2667	371	7	results	result	NOUN
cana-2667	371	8	and	and	CCONJ
cana-2667	371	9	comparisons	comparison	NOUN
cana-2667	371	10	with	with	ADP
cana-2667	371	11	baselines	baseline	NOUN
cana-2667	371	12	in	in	ADP
cana-2667	371	13	next	next	ADJ
cana-2667	371	14	section	section	NOUN
cana-2667	371	15	.	.	PUNCT
cana-2667	372	1	these	these	DET
cana-2667	372	2	tables	table	NOUN
cana-2667	372	3	summarize	summarize	VERB
cana-2667	372	4	the	the	DET
cana-2667	372	5	model	model	NOUN
cana-2667	372	6	performance	performance	NOUN
cana-2667	372	7	on	on	ADP
cana-2667	372	8	multiple	multiple	ADJ
cana-2667	372	9	evaluation	evaluation	NOUN
cana-2667	372	10	metrics	metric	NOUN
cana-2667	372	11	.	.	PUNCT
cana-2667	373	1	5	5	X
cana-2667	373	2	.	.	X
cana-2667	373	3	conclusion	conclusion	NOUN
cana-2667	373	4	in	in	ADP
cana-2667	373	5	this	this	DET
cana-2667	373	6	study	study	NOUN
cana-2667	373	7	,	,	PUNCT
cana-2667	373	8	we	we	PRON
cana-2667	373	9	investigated	investigate	VERB
cana-2667	373	10	the	the	DET
cana-2667	373	11	complementary	complementary	ADJ
cana-2667	373	12	potential	potential	NOUN
cana-2667	373	13	of	of	ADP
cana-2667	373	14	svm	svm	PROPN
cana-2667	373	15	in	in	ADP
cana-2667	373	16	combination	combination	NOUN
cana-2667	373	17	with	with	ADP
cana-2667	373	18	cnn	cnn	PROPN
cana-2667	373	19	to	to	PART
cana-2667	373	20	enhance	enhance	VERB
cana-2667	373	21	classification	classification	NOUN
cana-2667	373	22	performance	performance	NOUN
cana-2667	373	23	for	for	ADP
cana-2667	373	24	diabetic	diabetic	ADJ
cana-2667	373	25	retinopathy	retinopathy	ADJ
cana-2667	373	26	(	(	PUNCT
cana-2667	373	27	dr	dr	PROPN
cana-2667	373	28	)	)	PUNCT
cana-2667	373	29	detection	detection	NOUN
cana-2667	373	30	.	.	PUNCT
cana-2667	374	1	however	however	ADV
cana-2667	374	2	,	,	PUNCT
cana-2667	374	3	diabetic	diabetic	ADJ
cana-2667	374	4	retinopathy	retinopathy	NOUN
cana-2667	374	5	is	be	AUX
cana-2667	374	6	an	an	DET
cana-2667	374	7	important	important	ADJ
cana-2667	374	8	cause	cause	NOUN
cana-2667	374	9	of	of	ADP
cana-2667	374	10	vision	vision	NOUN
cana-2667	374	11	loss	loss	NOUN
cana-2667	374	12	and	and	CCONJ
cana-2667	374	13	blindness	blindness	NOUN
cana-2667	374	14	among	among	ADP
cana-2667	374	15	the	the	DET
cana-2667	374	16	patients	patient	NOUN
cana-2667	374	17	with	with	ADP
cana-2667	374	18	diabetes	diabetes	NOUN
cana-2667	374	19	and	and	CCONJ
cana-2667	374	20	its	its	PRON
cana-2667	374	21	early	early	ADJ
cana-2667	374	22	detection	detection	NOUN
cana-2667	374	23	is	be	AUX
cana-2667	374	24	essential	essential	ADJ
cana-2667	374	25	for	for	ADP
cana-2667	374	26	an	an	DET
cana-2667	374	27	effective	effective	ADJ
cana-2667	374	28	intervention	intervention	NOUN
cana-2667	374	29	.	.	PUNCT
cana-2667	375	1	these	these	DET
cana-2667	375	2	existing	exist	VERB
cana-2667	375	3	automated	automate	VERB
cana-2667	375	4	systems	system	NOUN
cana-2667	375	5	have	have	AUX
cana-2667	375	6	struggled	struggle	VERB
cana-2667	375	7	with	with	ADP
cana-2667	375	8	problems	problem	NOUN
cana-2667	375	9	like	like	ADP
cana-2667	375	10	the	the	DET
cana-2667	375	11	high	high	ADJ
cana-2667	375	12	variety	variety	NOUN
cana-2667	375	13	of	of	ADP
cana-2667	375	14	image	image	NOUN
cana-2667	375	15	quality	quality	NOUN
cana-2667	375	16	,	,	PUNCT
cana-2667	375	17	the	the	DET
cana-2667	375	18	difficulty	difficulty	NOUN
cana-2667	375	19	in	in	ADP
cana-2667	375	20	recognizing	recognize	VERB
cana-2667	375	21	subtle	subtle	ADJ
cana-2667	375	22	retinopathy	retinopathy	ADJ
cana-2667	375	23	signs	sign	NOUN
cana-2667	375	24	and	and	CCONJ
cana-2667	375	25	the	the	DET
cana-2667	375	26	imbalance	imbalance	NOUN
cana-2667	375	27	on	on	ADP
cana-2667	375	28	stages	stage	NOUN
cana-2667	375	29	of	of	ADP
cana-2667	375	30	dr	dr	PROPN
cana-2667	375	31	severity	severity	NOUN
cana-2667	375	32	.	.	PUNCT
cana-2667	376	1	we	we	PRON
cana-2667	376	2	aimed	aim	VERB
cana-2667	376	3	to	to	PART
cana-2667	376	4	solve	solve	VERB
cana-2667	376	5	these	these	DET
cana-2667	376	6	type	type	NOUN
cana-2667	376	7	of	of	ADP
cana-2667	376	8	communications	communication	NOUN
cana-2667	376	9	on	on	ADP
cana-2667	376	10	applied	apply	VERB
cana-2667	376	11	nonlinear	nonlinear	ADJ
cana-2667	376	12	analysis	analysis	NOUN
cana-2667	376	13	issn	issn	NOUN
cana-2667	376	14	:	:	PUNCT
cana-2667	376	15	1074	1074	NUM
cana-2667	376	16	-	-	PUNCT
cana-2667	376	17	133x	133x	NUM
cana-2667	376	18	vol	vol	NOUN
cana-2667	376	19	32	32	NUM
cana-2667	376	20	no	no	NOUN
cana-2667	376	21	.	.	PUNCT
cana-2667	377	1	3s	3s	NUM
cana-2667	377	2	(	(	PUNCT
cana-2667	377	3	2025	2025	NUM
cana-2667	377	4	)	)	PUNCT
cana-2667	377	5	402	402	NUM
cana-2667	377	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	377	7	problems	problem	NOUN
cana-2667	377	8	by	by	ADP
cana-2667	377	9	making	make	VERB
cana-2667	377	10	use	use	NOUN
cana-2667	377	11	of	of	ADP
cana-2667	377	12	the	the	DET
cana-2667	377	13	feature	feature	NOUN
cana-2667	377	14	extraction	extraction	NOUN
cana-2667	377	15	power	power	NOUN
cana-2667	377	16	of	of	ADP
cana-2667	377	17	cnns	cnn	NOUN
cana-2667	377	18	along	along	ADP
cana-2667	377	19	with	with	ADP
cana-2667	377	20	the	the	DET
cana-2667	377	21	vote	vote	NOUN
cana-2667	377	22	power	power	NOUN
cana-2667	377	23	of	of	ADP
cana-2667	377	24	svm	svm	PROPN
cana-2667	377	25	through	through	ADP
cana-2667	377	26	the	the	DET
cana-2667	377	27	proposed	propose	VERB
cana-2667	377	28	cnn	cnn	PROPN
cana-2667	377	29	-	-	PUNCT
cana-2667	377	30	svm	svm	PROPN
cana-2667	377	31	hybrid	hybrid	NOUN
cana-2667	377	32	model	model	NOUN
cana-2667	377	33	.	.	PUNCT
cana-2667	378	1	the	the	DET
cana-2667	378	2	research	research	NOUN
cana-2667	378	3	made	make	VERB
cana-2667	378	4	a	a	DET
cana-2667	378	5	number	number	NOUN
cana-2667	378	6	of	of	ADP
cana-2667	378	7	significant	significant	ADJ
cana-2667	378	8	contributions	contribution	NOUN
cana-2667	378	9	.	.	PUNCT
cana-2667	379	1	first	first	ADV
cana-2667	379	2	,	,	PUNCT
cana-2667	379	3	we	we	PRON
cana-2667	379	4	created	create	VERB
cana-2667	379	5	an	an	DET
cana-2667	379	6	optimized	optimize	VERB
cana-2667	379	7	cnn	cnn	NOUN
cana-2667	379	8	architecture	architecture	NOUN
cana-2667	379	9	that	that	PRON
cana-2667	379	10	utilizes	utilize	VERB
cana-2667	379	11	deep	deep	ADJ
cana-2667	379	12	learning	learning	NOUN
cana-2667	379	13	methods	method	NOUN
cana-2667	379	14	to	to	PART
cana-2667	379	15	automatically	automatically	ADV
cana-2667	379	16	extract	extract	VERB
cana-2667	379	17	high	high	ADJ
cana-2667	379	18	-	-	PUNCT
cana-2667	379	19	level	level	NOUN
cana-2667	379	20	features	feature	NOUN
cana-2667	379	21	from	from	ADP
cana-2667	379	22	retinal	retinal	ADJ
cana-2667	379	23	images	image	NOUN
cana-2667	379	24	.	.	PUNCT
cana-2667	380	1	feature	feature	NOUN
cana-2667	380	2	extraction	extraction	NOUN
cana-2667	380	3	is	be	AUX
cana-2667	380	4	an	an	DET
cana-2667	380	5	important	important	ADJ
cana-2667	380	6	part	part	NOUN
cana-2667	380	7	of	of	ADP
cana-2667	380	8	any	any	DET
cana-2667	380	9	machine	machine	NOUN
cana-2667	380	10	learning	learning	NOUN
cana-2667	380	11	task	task	NOUN
cana-2667	380	12	,	,	PUNCT
cana-2667	380	13	especially	especially	ADV
cana-2667	380	14	when	when	SCONJ
cana-2667	380	15	using	use	VERB
cana-2667	380	16	complex	complex	ADJ
cana-2667	380	17	,	,	PUNCT
cana-2667	380	18	high	high	ADJ
cana-2667	380	19	-	-	PUNCT
cana-2667	380	20	dimensional	dimensional	ADJ
cana-2667	380	21	image	image	NOUN
cana-2667	380	22	data	datum	NOUN
cana-2667	380	23	(	(	PUNCT
cana-2667	380	24	e.g.	e.g.	ADV
cana-2667	380	25	,	,	PUNCT
cana-2667	380	26	retinal	retinal	ADJ
cana-2667	380	27	scans	scan	NOUN
cana-2667	380	28	)	)	PUNCT
cana-2667	380	29	,	,	PUNCT
cana-2667	380	30	so	so	CCONJ
cana-2667	380	31	this	this	PRON
cana-2667	380	32	is	be	AUX
cana-2667	380	33	critical	critical	ADJ
cana-2667	380	34	.	.	PUNCT
cana-2667	381	1	conventional	conventional	ADJ
cana-2667	381	2	approaches	approach	NOUN
cana-2667	381	3	depend	depend	VERB
cana-2667	381	4	on	on	ADP
cana-2667	381	5	manually	manually	ADV
cana-2667	381	6	designed	design	VERB
cana-2667	381	7	features	feature	NOUN
cana-2667	381	8	,	,	PUNCT
cana-2667	381	9	which	which	PRON
cana-2667	381	10	a	a	DET
cana-2667	381	11	majority	majority	NOUN
cana-2667	381	12	of	of	ADP
cana-2667	381	13	the	the	DET
cana-2667	381	14	time	time	NOUN
cana-2667	381	15	can	can	AUX
cana-2667	381	16	not	not	PART
cana-2667	381	17	learn	learn	VERB
cana-2667	381	18	the	the	DET
cana-2667	381	19	delicate	delicate	ADJ
cana-2667	381	20	variations	variation	NOUN
cana-2667	381	21	in	in	ADP
cana-2667	381	22	images	image	NOUN
cana-2667	381	23	,	,	PUNCT
cana-2667	381	24	thus	thus	ADV
cana-2667	381	25	resulting	result	VERB
cana-2667	381	26	in	in	ADP
cana-2667	381	27	the	the	DET
cana-2667	381	28	less	less	ADV
cana-2667	381	29	-	-	PUNCT
cana-2667	381	30	performing	perform	VERB
cana-2667	381	31	classification	classification	NOUN
cana-2667	381	32	.	.	PUNCT
cana-2667	382	1	thus	thus	ADV
cana-2667	382	2	,	,	PUNCT
cana-2667	382	3	unlike	unlike	ADP
cana-2667	382	4	original	original	ADJ
cana-2667	382	5	cnn	cnn	NOUN
cana-2667	382	6	architecture	architecture	NOUN
cana-2667	382	7	it	it	PRON
cana-2667	382	8	can	can	AUX
cana-2667	382	9	learn	learn	VERB
cana-2667	382	10	the	the	DET
cana-2667	382	11	most	most	ADV
cana-2667	382	12	relevant	relevant	ADJ
cana-2667	382	13	features	feature	NOUN
cana-2667	382	14	from	from	ADP
cana-2667	382	15	images	image	NOUN
cana-2667	382	16	which	which	PRON
cana-2667	382	17	leads	lead	VERB
cana-2667	382	18	to	to	ADP
cana-2667	382	19	much	much	ADJ
cana-2667	382	20	improvement	improvement	NOUN
cana-2667	382	21	in	in	ADP
cana-2667	382	22	the	the	DET
cana-2667	382	23	accuracy	accuracy	NOUN
cana-2667	382	24	of	of	ADP
cana-2667	382	25	dr	dr	PROPN
cana-2667	382	26	classification	classification	NOUN
cana-2667	382	27	.	.	PUNCT
cana-2667	383	1	second	second	ADJ
cana-2667	383	2	,	,	PUNCT
cana-2667	383	3	we	we	PRON
cana-2667	383	4	fine	fine	ADV
cana-2667	383	5	-	-	PUNCT
cana-2667	383	6	tuned	tune	VERB
cana-2667	383	7	the	the	DET
cana-2667	383	8	svm	svm	ADJ
cana-2667	383	9	classifier	classifier	NOUN
cana-2667	383	10	to	to	PART
cana-2667	383	11	be	be	AUX
cana-2667	383	12	synchronized	synchronize	VERB
cana-2667	383	13	with	with	ADP
cana-2667	383	14	the	the	DET
cana-2667	383	15	feature	feature	NOUN
cana-2667	383	16	extraction	extraction	NOUN
cana-2667	383	17	phase	phase	NOUN
cana-2667	383	18	of	of	ADP
cana-2667	383	19	the	the	DET
cana-2667	383	20	cnn	cnn	PROPN
cana-2667	383	21	.	.	PUNCT
cana-2667	384	1	simulating	simulate	VERB
cana-2667	384	2	hyperplanes	hyperplane	NOUN
cana-2667	384	3	in	in	ADP
cana-2667	384	4	high	high	ADJ
cana-2667	384	5	-	-	PUNCT
cana-2667	384	6	dimensional	dimensional	ADJ
cana-2667	384	7	areas	area	NOUN
cana-2667	384	8	allowed	allow	VERB
cana-2667	384	9	the	the	DET
cana-2667	384	10	svm	svm	NOUN
cana-2667	384	11	to	to	PART
cana-2667	384	12	show	show	VERB
cana-2667	384	13	better	well	ADJ
cana-2667	384	14	distinction	distinction	NOUN
cana-2667	384	15	between	between	ADP
cana-2667	384	16	dr	dr	PROPN
cana-2667	384	17	stages	stage	NOUN
cana-2667	384	18	with	with	ADP
cana-2667	384	19	a	a	DET
cana-2667	384	20	systematic	systematic	ADJ
cana-2667	384	21	search	search	NOUN
cana-2667	384	22	for	for	ADP
cana-2667	384	23	the	the	DET
cana-2667	384	24	kernel	kernel	PROPN
cana-2667	384	25	function	function	PROPN
cana-2667	384	26	,	,	PUNCT
cana-2667	384	27	regularization	regularization	NOUN
cana-2667	384	28	parameters	parameter	NOUN
cana-2667	384	29	,	,	PUNCT
cana-2667	384	30	and	and	CCONJ
cana-2667	384	31	tolerance	tolerance	NOUN
cana-2667	384	32	settings	setting	NOUN
cana-2667	384	33	for	for	ADP
cana-2667	384	34	better	well	ADJ
cana-2667	384	35	svm	svm	ADJ
cana-2667	384	36	performance	performance	NOUN
cana-2667	384	37	.	.	PUNCT
cana-2667	385	1	the	the	DET
cana-2667	385	2	optimization	optimization	NOUN
cana-2667	385	3	process	process	NOUN
cana-2667	385	4	aided	aid	VERB
cana-2667	385	5	in	in	ADP
cana-2667	385	6	enhancing	enhance	VERB
cana-2667	385	7	the	the	DET
cana-2667	385	8	classification	classification	NOUN
cana-2667	385	9	accuracy	accuracy	NOUN
cana-2667	385	10	and	and	CCONJ
cana-2667	385	11	minimizing	minimize	VERB
cana-2667	385	12	misclassifications	misclassification	NOUN
cana-2667	385	13	among	among	ADP
cana-2667	385	14	various	various	ADJ
cana-2667	385	15	severity	severity	NOUN
cana-2667	385	16	levels	level	NOUN
cana-2667	385	17	of	of	ADP
cana-2667	385	18	diabetic	diabetic	ADJ
cana-2667	385	19	retinopathy	retinopathy	NOUN
cana-2667	385	20	.	.	PUNCT
cana-2667	386	1	publicly	publicly	ADV
cana-2667	386	2	available	available	ADJ
cana-2667	386	3	retinal	retinal	ADJ
cana-2667	386	4	image	image	NOUN
cana-2667	386	5	datasets	dataset	NOUN
cana-2667	386	6	were	be	AUX
cana-2667	386	7	used	use	VERB
cana-2667	386	8	in	in	ADP
cana-2667	386	9	rigorous	rigorous	ADJ
cana-2667	386	10	evaluations	evaluation	NOUN
cana-2667	386	11	of	of	ADP
cana-2667	386	12	the	the	DET
cana-2667	386	13	hybrid	hybrid	ADJ
cana-2667	386	14	approach	approach	NOUN
cana-2667	386	15	.	.	PUNCT
cana-2667	387	1	the	the	DET
cana-2667	387	2	comparison	comparison	NOUN
cana-2667	387	3	of	of	ADP
cana-2667	387	4	our	our	PRON
cana-2667	387	5	cnn	cnn	PROPN
cana-2667	387	6	-	-	PUNCT
cana-2667	387	7	svm	svm	PROPN
cana-2667	387	8	model	model	NOUN
cana-2667	387	9	with	with	ADP
cana-2667	387	10	baseline	baseline	NOUN
cana-2667	387	11	models	model	NOUN
cana-2667	387	12	,	,	PUNCT
cana-2667	387	13	including	include	VERB
cana-2667	387	14	the	the	DET
cana-2667	387	15	cnn	cnn	PROPN
cana-2667	387	16	-	-	PUNCT
cana-2667	387	17	only	only	ADV
cana-2667	387	18	model	model	NOUN
cana-2667	387	19	,	,	PUNCT
cana-2667	387	20	traditional	traditional	ADJ
cana-2667	387	21	svm	svm	NOUN
cana-2667	387	22	,	,	PUNCT
cana-2667	387	23	and	and	CCONJ
cana-2667	387	24	deep	deep	ADJ
cana-2667	387	25	cnn	cnn	PROPN
cana-2667	387	26	.	.	PUNCT
cana-2667	388	1	results	result	NOUN
cana-2667	388	2	of	of	ADP
cana-2667	388	3	this	this	DET
cana-2667	388	4	work	work	NOUN
cana-2667	388	5	showed	show	VERB
cana-2667	388	6	that	that	SCONJ
cana-2667	388	7	the	the	DET
cana-2667	388	8	baseline	baseline	NOUN
cana-2667	388	9	models	model	NOUN
cana-2667	388	10	performed	perform	VERB
cana-2667	388	11	worse	bad	ADJ
cana-2667	388	12	than	than	ADP
cana-2667	388	13	the	the	DET
cana-2667	388	14	cnn	cnn	PROPN
cana-2667	388	15	-	-	PUNCT
cana-2667	388	16	svm	svm	ADJ
cana-2667	388	17	hybrid	hybrid	NOUN
cana-2667	388	18	model	model	NOUN
cana-2667	388	19	in	in	ADP
cana-2667	388	20	terms	term	NOUN
cana-2667	388	21	of	of	ADP
cana-2667	388	22	all	all	DET
cana-2667	388	23	relevant	relevant	ADJ
cana-2667	388	24	performance	performance	NOUN
cana-2667	388	25	metrics	metric	NOUN
cana-2667	388	26	such	such	ADJ
cana-2667	388	27	as	as	ADP
cana-2667	388	28	accuracy	accuracy	NOUN
cana-2667	388	29	,	,	PUNCT
cana-2667	388	30	precision	precision	NOUN
cana-2667	388	31	,	,	PUNCT
cana-2667	388	32	recall	recall	NOUN
cana-2667	388	33	,	,	PUNCT
cana-2667	388	34	f1	f1	NOUN
cana-2667	388	35	-	-	PUNCT
cana-2667	388	36	score	score	NOUN
cana-2667	388	37	,	,	PUNCT
cana-2667	388	38	and	and	CCONJ
cana-2667	388	39	auc	auc	NOUN
cana-2667	388	40	.	.	PUNCT
cana-2667	389	1	the	the	DET
cana-2667	389	2	overall	overall	ADJ
cana-2667	389	3	accuracy	accuracy	NOUN
cana-2667	389	4	of	of	ADP
cana-2667	389	5	image	image	NOUN
cana-2667	389	6	classification	classification	NOUN
cana-2667	389	7	with	with	ADP
cana-2667	389	8	the	the	DET
cana-2667	389	9	cnn	cnn	PROPN
cana-2667	389	10	-	-	PUNCT
cana-2667	389	11	svm	svm	PROPN
cana-2667	389	12	model	model	NOUN
cana-2667	389	13	was	be	AUX
cana-2667	389	14	92.3	92.3	NUM
cana-2667	389	15	%	%	NOUN
cana-2667	389	16	,	,	PUNCT
cana-2667	389	17	while	while	SCONJ
cana-2667	389	18	the	the	DET
cana-2667	389	19	cnn	cnn	PROPN
cana-2667	389	20	model	model	NOUN
cana-2667	389	21	accuracy	accuracy	NOUN
cana-2667	389	22	was	be	AUX
cana-2667	389	23	86.4	86.4	NUM
cana-2667	389	24	%	%	NOUN
cana-2667	389	25	,	,	PUNCT
cana-2667	389	26	the	the	DET
cana-2667	389	27	traditional	traditional	ADJ
cana-2667	389	28	svm	svm	ADJ
cana-2667	389	29	accuracy	accuracy	NOUN
cana-2667	389	30	was	be	AUX
cana-2667	389	31	79.2	79.2	NUM
cana-2667	389	32	%	%	NOUN
cana-2667	389	33	,	,	PUNCT
cana-2667	389	34	and	and	CCONJ
cana-2667	389	35	the	the	DET
cana-2667	389	36	deep	deep	ADJ
cana-2667	389	37	cnn	cnn	PROPN
cana-2667	389	38	model	model	NOUN
cana-2667	389	39	accuracy	accuracy	NOUN
cana-2667	389	40	was	be	AUX
cana-2667	389	41	88.7	88.7	NUM
cana-2667	389	42	%	%	NOUN
cana-2667	389	43	the	the	DET
cana-2667	389	44	hybrid	hybrid	NOUN
cana-2667	389	45	model	model	NOUN
cana-2667	389	46	outperformed	outperform	VERB
cana-2667	389	47	the	the	DET
cana-2667	389	48	state	state	NOUN
cana-2667	389	49	-	-	PUNCT
cana-2667	389	50	of	of	ADP
cana-2667	389	51	-	-	PUNCT
cana-2667	389	52	the	the	DET
cana-2667	389	53	-	-	PUNCT
cana-2667	389	54	art	art	NOUN
cana-2667	389	55	dr	dr	PROPN
cana-2667	389	56	detection	detection	NOUN
cana-2667	389	57	methods	method	NOUN
cana-2667	389	58	at	at	ADP
cana-2667	389	59	this	this	DET
cana-2667	389	60	stage	stage	NOUN
cana-2667	389	61	with	with	ADP
cana-2667	389	62	an	an	DET
cana-2667	389	63	error	error	NOUN
cana-2667	389	64	rate	rate	NOUN
cana-2667	389	65	of	of	ADP
cana-2667	389	66	0.0552	0.0552	NUM
cana-2667	389	67	%	%	NOUN
cana-2667	389	68	and	and	CCONJ
cana-2667	389	69	an	an	DET
cana-2667	389	70	accuracy	accuracy	NOUN
cana-2667	389	71	of	of	ADP
cana-2667	389	72	99.9448	99.9448	NUM
cana-2667	389	73	%	%	NOUN
cana-2667	389	74	which	which	PRON
cana-2667	389	75	significantly	significantly	ADV
cana-2667	389	76	enhances	enhance	VERB
cana-2667	389	77	the	the	DET
cana-2667	389	78	performance	performance	NOUN
cana-2667	389	79	as	as	ADP
cana-2667	389	80	compared	compare	VERB
cana-2667	389	81	with	with	ADP
cana-2667	389	82	them	they	PRON
cana-2667	389	83	.	.	PUNCT
cana-2667	390	1	in	in	ADP
cana-2667	390	2	addition	addition	NOUN
cana-2667	390	3	,	,	PUNCT
cana-2667	390	4	the	the	DET
cana-2667	390	5	precision	precision	NOUN
cana-2667	390	6	and	and	CCONJ
cana-2667	390	7	recall	recall	NOUN
cana-2667	390	8	of	of	ADP
cana-2667	390	9	the	the	DET
cana-2667	390	10	severity	severity	NOUN
cana-2667	390	11	levels	level	NOUN
cana-2667	390	12	of	of	ADP
cana-2667	390	13	diabetic	diabetic	ADJ
cana-2667	390	14	retinopathy	retinopathy	NOUN
cana-2667	390	15	were	be	AUX
cana-2667	390	16	also	also	ADV
cana-2667	390	17	excellent	excellent	ADJ
cana-2667	390	18	in	in	ADP
cana-2667	390	19	the	the	DET
cana-2667	390	20	cnn	cnn	PROPN
cana-2667	390	21	-	-	PUNCT
cana-2667	390	22	svm	svm	PROPN
cana-2667	390	23	model	model	NOUN
cana-2667	390	24	.	.	PUNCT
cana-2667	391	1	more	more	ADV
cana-2667	391	2	recently	recently	ADV
cana-2667	391	3	,	,	PUNCT
cana-2667	391	4	the	the	DET
cana-2667	391	5	context	context	NOUN
cana-2667	391	6	of	of	ADP
cana-2667	391	7	this	this	DET
cana-2667	391	8	model	model	NOUN
cana-2667	391	9	type	type	NOUN
cana-2667	391	10	is	be	AUX
cana-2667	391	11	particularly	particularly	ADV
cana-2667	391	12	relevant	relevant	ADJ
cana-2667	391	13	under	under	ADP
cana-2667	391	14	medical	medical	ADJ
cana-2667	391	15	applications	application	NOUN
cana-2667	391	16	where	where	SCONJ
cana-2667	391	17	the	the	DET
cana-2667	391	18	models	model	NOUN
cana-2667	391	19	ability	ability	VERB
cana-2667	391	20	to	to	PART
cana-2667	391	21	minimise	minimise	VERB
cana-2667	391	22	false	false	ADJ
cana-2667	391	23	positives	positive	NOUN
cana-2667	391	24	(	(	PUNCT
cana-2667	391	25	precision	precision	NOUN
cana-2667	391	26	)	)	PUNCT
cana-2667	391	27	and	and	CCONJ
cana-2667	391	28	false	false	ADJ
cana-2667	391	29	negatives	negative	NOUN
cana-2667	391	30	(	(	PUNCT
cana-2667	391	31	recall	recall	NOUN
cana-2667	391	32	)	)	PUNCT
cana-2667	391	33	should	should	AUX
cana-2667	391	34	directly	directly	ADV
cana-2667	391	35	affect	affect	VERB
cana-2667	391	36	patient	patient	ADJ
cana-2667	391	37	outcomes	outcome	NOUN
cana-2667	391	38	.	.	PUNCT
cana-2667	392	1	the	the	DET
cana-2667	392	2	class	class	NOUN
cana-2667	392	3	wise	wise	ADJ
cana-2667	392	4	breakdown	breakdown	NOUN
cana-2667	392	5	shows	show	VERB
cana-2667	392	6	that	that	SCONJ
cana-2667	392	7	in	in	ADP
cana-2667	392	8	challenging	challenging	ADJ
cana-2667	392	9	categories	category	NOUN
cana-2667	392	10	,	,	PUNCT
cana-2667	392	11	extreme	extreme	ADJ
cana-2667	392	12	precision	precision	NOUN
cana-2667	392	13	and	and	CCONJ
cana-2667	392	14	recall	recall	NOUN
cana-2667	392	15	values	value	NOUN
cana-2667	392	16	of	of	ADP
cana-2667	392	17	severe	severe	ADJ
cana-2667	392	18	dr	dr	PROPN
cana-2667	392	19	and	and	CCONJ
cana-2667	392	20	proliferative	proliferative	PROPN
cana-2667	392	21	dr	dr	PROPN
cana-2667	392	22	(	(	PUNCT
cana-2667	392	23	pdr	pdr	PROPN
cana-2667	392	24	)	)	PUNCT
cana-2667	392	25	mirror	mirror	VERB
cana-2667	392	26	the	the	DET
cana-2667	392	27	results	result	NOUN
cana-2667	392	28	of	of	ADP
cana-2667	392	29	previously	previously	ADV
cana-2667	392	30	tried	try	VERB
cana-2667	392	31	models	model	NOUN
cana-2667	392	32	in	in	ADP
cana-2667	392	33	the	the	DET
cana-2667	392	34	network	network	NOUN
cana-2667	392	35	structure	structure	NOUN
cana-2667	392	36	used	use	VERB
cana-2667	392	37	,	,	PUNCT
cana-2667	392	38	nevertheless	nevertheless	ADV
cana-2667	392	39	with	with	ADP
cana-2667	392	40	performance	performance	NOUN
cana-2667	392	41	of	of	ADP
cana-2667	392	42	hybrid	hybrid	ADJ
cana-2667	392	43	model	model	NOUN
cana-2667	392	44	showing	show	VERB
cana-2667	392	45	best	good	ADJ
cana-2667	392	46	results	result	NOUN
cana-2667	392	47	across	across	ADP
cana-2667	392	48	all	all	DET
cana-2667	392	49	classes	class	NOUN
cana-2667	392	50	.	.	PUNCT
cana-2667	393	1	this	this	PRON
cana-2667	393	2	shows	show	VERB
cana-2667	393	3	the	the	DET
cana-2667	393	4	power	power	NOUN
cana-2667	393	5	of	of	ADP
cana-2667	393	6	merging	merge	VERB
cana-2667	393	7	the	the	DET
cana-2667	393	8	feature	feature	NOUN
cana-2667	393	9	learning	learning	NOUN
cana-2667	393	10	of	of	ADP
cana-2667	393	11	cnn	cnn	PROPN
cana-2667	393	12	with	with	ADP
cana-2667	393	13	the	the	DET
cana-2667	393	14	classification	classification	NOUN
cana-2667	393	15	power	power	NOUN
cana-2667	393	16	of	of	ADP
cana-2667	393	17	svm	svm	PROPN
cana-2667	393	18	.	.	PROPN
cana-2667	393	19	discussion	discussion	NOUN
cana-2667	393	20	comparisons	comparison	NOUN
cana-2667	393	21	of	of	ADP
cana-2667	393	22	training	training	NOUN
cana-2667	393	23	and	and	CCONJ
cana-2667	393	24	inference	inference	NOUN
cana-2667	393	25	times	time	NOUN
cana-2667	393	26	also	also	ADV
cana-2667	393	27	demonstrated	demonstrate	VERB
cana-2667	393	28	the	the	DET
cana-2667	393	29	practicality	practicality	NOUN
cana-2667	393	30	of	of	ADP
cana-2667	393	31	the	the	DET
cana-2667	393	32	proposed	propose	VERB
cana-2667	393	33	hybrid	hybrid	NOUN
cana-2667	393	34	approach	approach	NOUN
cana-2667	393	35	.	.	PUNCT
cana-2667	394	1	fitness	fitness	NOUN
cana-2667	394	2	k	k	NOUN
cana-2667	394	3	-	-	PUNCT
cana-2667	394	4	rcs13	rcs13	NOUN
cana-2667	394	5	:	:	PUNCT
cana-2667	394	6	the	the	DET
cana-2667	394	7	cnn	cnn	NOUN
cana-2667	394	8	only	only	ADV
cana-2667	394	9	and	and	CCONJ
cana-2667	394	10	deep	deep	ADJ
cana-2667	394	11	cnn	cnn	PROPN
cana-2667	394	12	models	model	NOUN
cana-2667	394	13	were	be	AUX
cana-2667	394	14	slower	slow	ADJ
cana-2667	394	15	to	to	PART
cana-2667	394	16	train	train	VERB
cana-2667	394	17	than	than	ADP
cana-2667	394	18	the	the	DET
cana-2667	394	19	cnn	cnn	PROPN
cana-2667	394	20	-	-	PUNCT
cana-2667	394	21	svm	svm	PROPN
cana-2667	394	22	hybrid	hybrid	NOUN
cana-2667	394	23	,	,	PUNCT
cana-2667	394	24	which	which	PRON
cana-2667	394	25	resulted	result	VERB
cana-2667	394	26	in	in	ADP
cana-2667	394	27	good	good	ADJ
cana-2667	394	28	training	training	NOUN
cana-2667	394	29	time	time	NOUN
cana-2667	394	30	while	while	SCONJ
cana-2667	394	31	reaching	reach	VERB
cana-2667	394	32	similarly	similarly	ADV
cana-2667	394	33	high	high	ADJ
cana-2667	394	34	accuracy	accuracy	NOUN
cana-2667	394	35	and	and	CCONJ
cana-2667	394	36	precision	precision	NOUN
cana-2667	394	37	as	as	ADP
cana-2667	394	38	the	the	DET
cana-2667	394	39	other	other	ADJ
cana-2667	394	40	hybrid	hybrid	ADJ
cana-2667	394	41	architectures	architecture	NOUN
cana-2667	394	42	.	.	PUNCT
cana-2667	395	1	additionally	additionally	ADV
cana-2667	395	2	,	,	PUNCT
cana-2667	395	3	the	the	DET
cana-2667	395	4	inference	inference	NOUN
cana-2667	395	5	time	time	NOUN
cana-2667	395	6	of	of	ADP
cana-2667	395	7	their	their	PRON
cana-2667	395	8	cnnsvm	cnnsvm	NOUN
cana-2667	395	9	hybrid	hybrid	NOUN
cana-2667	395	10	model	model	NOUN
cana-2667	395	11	matched	match	VERB
cana-2667	395	12	that	that	PRON
cana-2667	395	13	of	of	ADP
cana-2667	395	14	the	the	DET
cana-2667	395	15	baseline	baseline	NOUN
cana-2667	395	16	models	model	NOUN
cana-2667	395	17	:	:	PUNCT
cana-2667	395	18	traditional	traditional	ADJ
cana-2667	395	19	svm	svm	PROPN
cana-2667	395	20	and	and	CCONJ
cana-2667	395	21	cnn	cnn	PROPN
cana-2667	395	22	-	-	PUNCT
cana-2667	395	23	only	only	ADV
cana-2667	395	24	models	model	NOUN
cana-2667	395	25	,	,	PUNCT
cana-2667	395	26	allowing	allow	VERB
cana-2667	395	27	it	it	PRON
cana-2667	395	28	to	to	PART
cana-2667	395	29	excel	excel	VERB
cana-2667	395	30	in	in	ADP
cana-2667	395	31	real	real	ADJ
cana-2667	395	32	-	-	PUNCT
cana-2667	395	33	time	time	NOUN
cana-2667	395	34	analyses	analysis	NOUN
cana-2667	395	35	in	in	ADP
cana-2667	395	36	a	a	DET
cana-2667	395	37	clinical	clinical	ADJ
cana-2667	395	38	environment	environment	NOUN
cana-2667	395	39	.	.	PUNCT
cana-2667	396	1	communications	communication	NOUN
cana-2667	396	2	on	on	ADP
cana-2667	396	3	applied	apply	VERB
cana-2667	396	4	nonlinear	nonlinear	ADJ
cana-2667	396	5	analysis	analysis	NOUN
cana-2667	396	6	issn	issn	NOUN
cana-2667	396	7	:	:	PUNCT
cana-2667	396	8	1074	1074	NUM
cana-2667	396	9	-	-	PUNCT
cana-2667	396	10	133x	133x	NUM
cana-2667	396	11	vol	vol	NOUN
cana-2667	396	12	32	32	NUM
cana-2667	396	13	no	no	NOUN
cana-2667	396	14	.	.	PUNCT
cana-2667	397	1	3s	3s	NUM
cana-2667	397	2	(	(	PUNCT
cana-2667	397	3	2025	2025	NUM
cana-2667	397	4	)	)	PUNCT
cana-2667	397	5	403	403	NUM
cana-2667	397	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	397	7	moreover	moreover	ADV
cana-2667	397	8	,	,	PUNCT
cana-2667	397	9	the	the	DET
cana-2667	397	10	results	result	NOUN
cana-2667	397	11	further	far	ADV
cana-2667	397	12	emphasized	emphasize	VERB
cana-2667	397	13	the	the	DET
cana-2667	397	14	significance	significance	NOUN
cana-2667	397	15	of	of	ADP
cana-2667	397	16	feature	feature	NOUN
cana-2667	397	17	extraction	extraction	NOUN
cana-2667	397	18	in	in	ADP
cana-2667	397	19	dr	dr	PROPN
cana-2667	397	20	classification	classification	NOUN
cana-2667	397	21	.	.	PUNCT
cana-2667	398	1	the	the	DET
cana-2667	398	2	hybrid	hybrid	ADJ
cana-2667	398	3	cnn	cnn	PROPN
cana-2667	398	4	-	-	PUNCT
cana-2667	398	5	svm	svm	PROPN
cana-2667	398	6	features	feature	NOUN
cana-2667	398	7	(	(	PUNCT
cana-2667	398	8	formed	form	VERB
cana-2667	398	9	by	by	ADP
cana-2667	398	10	a	a	DET
cana-2667	398	11	cnn	cnn	NOUN
cana-2667	398	12	that	that	PRON
cana-2667	398	13	learned	learn	VERB
cana-2667	398	14	features	feature	NOUN
cana-2667	398	15	then	then	ADV
cana-2667	398	16	classified	classify	VERB
cana-2667	398	17	by	by	ADP
cana-2667	398	18	a	a	DET
cana-2667	398	19	svm	svm	NOUN
cana-2667	398	20	)	)	PUNCT
cana-2667	398	21	achieved	achieve	VERB
cana-2667	398	22	significantly	significantly	ADV
cana-2667	398	23	higher	high	ADJ
cana-2667	398	24	accuracy	accuracy	NOUN
cana-2667	398	25	than	than	ADP
cana-2667	398	26	hand	hand	NOUN
cana-2667	398	27	-	-	PUNCT
cana-2667	398	28	crafted	craft	VERB
cana-2667	398	29	or	or	CCONJ
cana-2667	398	30	pre	pre	VERB
cana-2667	398	31	-	-	ADJ
cana-2667	398	32	trained	train	VERB
cana-2667	398	33	cnn	cnn	PROPN
cana-2667	398	34	features	feature	VERB
cana-2667	398	35	.	.	PUNCT
cana-2667	399	1	since	since	SCONJ
cana-2667	399	2	intricacies	intricacy	NOUN
cana-2667	399	3	in	in	ADP
cana-2667	399	4	retinal	retinal	ADJ
cana-2667	399	5	images	image	NOUN
cana-2667	399	6	are	be	AUX
cana-2667	399	7	generally	generally	ADV
cana-2667	399	8	lost	lose	VERB
cana-2667	399	9	in	in	ADP
cana-2667	399	10	shallow	shallow	ADJ
cana-2667	399	11	feature	feature	NOUN
cana-2667	399	12	extraction	extraction	NOUN
cana-2667	399	13	,	,	PUNCT
cana-2667	399	14	this	this	PRON
cana-2667	399	15	reinforces	reinforce	VERB
cana-2667	399	16	that	that	PRON
cana-2667	399	17	fully	fully	ADV
cana-2667	399	18	learned	learn	VERB
cana-2667	399	19	features	feature	NOUN
cana-2667	399	20	from	from	ADP
cana-2667	399	21	deep	deep	ADJ
cana-2667	399	22	neural	neural	ADJ
cana-2667	399	23	networks	network	NOUN
cana-2667	399	24	can	can	AUX
cana-2667	399	25	better	well	ADV
cana-2667	399	26	model	model	VERB
cana-2667	399	27	them	they	PRON
cana-2667	399	28	.	.	PUNCT
cana-2667	400	1	this	this	PRON
cana-2667	400	2	indicates	indicate	VERB
cana-2667	400	3	the	the	DET
cana-2667	400	4	hybrid	hybrid	ADJ
cana-2667	400	5	model	model	NOUN
cana-2667	400	6	's	's	PART
cana-2667	400	7	efficiency	efficiency	NOUN
cana-2667	400	8	to	to	PART
cana-2667	400	9	operate	operate	VERB
cana-2667	400	10	on	on	ADP
cana-2667	400	11	various	various	ADJ
cana-2667	400	12	features	feature	NOUN
cana-2667	400	13	learned	learn	VERB
cana-2667	400	14	by	by	ADP
cana-2667	400	15	various	various	ADJ
cana-2667	400	16	imaging	imaging	NOUN
cana-2667	400	17	modalities	modality	NOUN
cana-2667	400	18	suggesting	suggest	VERB
cana-2667	400	19	both	both	CCONJ
cana-2667	400	20	its	its	PRON
cana-2667	400	21	generalisation	generalisation	NOUN
cana-2667	400	22	potential	potential	NOUN
cana-2667	400	23	on	on	ADP
cana-2667	400	24	unseen	unseen	ADJ
cana-2667	400	25	data	datum	NOUN
cana-2667	400	26	as	as	ADV
cana-2667	400	27	well	well	ADV
cana-2667	400	28	as	as	ADP
cana-2667	400	29	its	its	PRON
cana-2667	400	30	ability	ability	NOUN
cana-2667	400	31	to	to	PART
cana-2667	400	32	adapt	adapt	VERB
cana-2667	400	33	to	to	ADP
cana-2667	400	34	multiple	multiple	ADJ
cana-2667	400	35	imaging	imaging	NOUN
cana-2667	400	36	devices	device	NOUN
cana-2667	400	37	and	and	CCONJ
cana-2667	400	38	populations	population	NOUN
cana-2667	400	39	.	.	PUNCT
cana-2667	401	1	the	the	DET
cana-2667	401	2	cnn	cnn	PROPN
cana-2667	401	3	-	-	PUNCT
cana-2667	401	4	svm	svm	PROPN
cana-2667	401	5	hybrid	hybrid	NOUN
cana-2667	401	6	model	model	NOUN
cana-2667	401	7	proposed	propose	VERB
cana-2667	401	8	in	in	ADP
cana-2667	401	9	this	this	DET
cana-2667	401	10	paper	paper	NOUN
cana-2667	401	11	brings	bring	VERB
cana-2667	401	12	a	a	DET
cana-2667	401	13	novel	novel	ADJ
cana-2667	401	14	advance	advance	NOUN
cana-2667	401	15	in	in	ADP
cana-2667	401	16	automated	automate	VERB
cana-2667	401	17	diabetic	diabetic	ADJ
cana-2667	401	18	retinopathy	retinopathy	ADJ
cana-2667	401	19	detection	detection	NOUN
cana-2667	401	20	.	.	PUNCT
cana-2667	402	1	upon	upon	SCONJ
cana-2667	402	2	integrating	integrate	VERB
cana-2667	402	3	both	both	DET
cana-2667	402	4	duan	duan	PROPN
cana-2667	402	5	's	's	PART
cana-2667	402	6	algorithm	algorithm	NOUN
cana-2667	402	7	and	and	CCONJ
cana-2667	402	8	classical	classical	ADJ
cana-2667	402	9	ml	ml	NOUN
cana-2667	402	10	approach	approach	NOUN
cana-2667	402	11	,	,	PUNCT
cana-2667	402	12	it	it	PRON
cana-2667	402	13	provides	provide	VERB
cana-2667	402	14	a	a	DET
cana-2667	402	15	comparable	comparable	ADJ
cana-2667	402	16	solution	solution	NOUN
cana-2667	402	17	for	for	ADP
cana-2667	402	18	dr	dr	PROPN
cana-2667	402	19	classification	classification	NOUN
cana-2667	402	20	yet	yet	ADV
cana-2667	402	21	with	with	ADP
cana-2667	402	22	unclear	unclear	ADJ
cana-2667	402	23	hardware	hardware	NOUN
cana-2667	402	24	needs	need	NOUN
cana-2667	402	25	.	.	PUNCT
cana-2667	403	1	there	there	PRON
cana-2667	403	2	are	be	VERB
cana-2667	403	3	,	,	PUNCT
cana-2667	403	4	however	however	ADV
cana-2667	403	5	,	,	PUNCT
cana-2667	403	6	some	some	PRON
cana-2667	403	7	points	point	VERB
cana-2667	403	8	to	to	PART
cana-2667	403	9	improve	improve	VERB
cana-2667	403	10	upon	upon	SCONJ
cana-2667	403	11	in	in	ADP
cana-2667	403	12	future	future	ADJ
cana-2667	403	13	work	work	NOUN
cana-2667	403	14	.	.	PUNCT
cana-2667	404	1	as	as	ADP
cana-2667	404	2	an	an	DET
cana-2667	404	3	example	example	NOUN
cana-2667	404	4	,	,	PUNCT
cana-2667	404	5	while	while	SCONJ
cana-2667	404	6	the	the	DET
cana-2667	404	7	model	model	NOUN
cana-2667	404	8	showed	show	VERB
cana-2667	404	9	excellent	excellent	ADJ
cana-2667	404	10	performance	performance	NOUN
cana-2667	404	11	on	on	ADP
cana-2667	404	12	the	the	DET
cana-2667	404	13	dataset	dataset	NOUN
cana-2667	404	14	in	in	ADP
cana-2667	404	15	this	this	DET
cana-2667	404	16	study	study	NOUN
cana-2667	404	17	,	,	PUNCT
cana-2667	404	18	using	use	VERB
cana-2667	404	19	additional	additional	ADJ
cana-2667	404	20	datasets	dataset	NOUN
cana-2667	404	21	with	with	ADP
cana-2667	404	22	heterogeneous	heterogeneous	ADJ
cana-2667	404	23	demographics	demographic	NOUN
cana-2667	404	24	and	and	CCONJ
cana-2667	404	25	imaging	imaging	NOUN
cana-2667	404	26	conditions	condition	NOUN
cana-2667	404	27	would	would	AUX
cana-2667	404	28	help	help	VERB
cana-2667	404	29	evaluate	evaluate	VERB
cana-2667	404	30	the	the	DET
cana-2667	404	31	generalization	generalization	NOUN
cana-2667	404	32	of	of	ADP
cana-2667	404	33	the	the	DET
cana-2667	404	34	model	model	NOUN
cana-2667	404	35	.	.	PUNCT
cana-2667	405	1	moreover	moreover	ADV
cana-2667	405	2	,	,	PUNCT
cana-2667	405	3	techniques	technique	NOUN
cana-2667	405	4	like	like	ADP
cana-2667	405	5	oversampling	oversample	VERB
cana-2667	405	6	,	,	PUNCT
cana-2667	405	7	data	datum	NOUN
cana-2667	405	8	augmentation	augmentation	NOUN
cana-2667	405	9	,	,	PUNCT
cana-2667	405	10	or	or	CCONJ
cana-2667	405	11	class	class	NOUN
cana-2667	405	12	-	-	PUNCT
cana-2667	405	13	weighted	weight	VERB
cana-2667	405	14	loss	loss	NOUN
cana-2667	405	15	functions	function	NOUN
cana-2667	405	16	can	can	AUX
cana-2667	405	17	be	be	AUX
cana-2667	405	18	used	use	VERB
cana-2667	405	19	to	to	PART
cana-2667	405	20	mitigate	mitigate	VERB
cana-2667	405	21	the	the	DET
cana-2667	405	22	problem	problem	NOUN
cana-2667	405	23	of	of	ADP
cana-2667	405	24	class	class	NOUN
cana-2667	405	25	imbalance	imbalance	NOUN
cana-2667	405	26	,	,	PUNCT
cana-2667	405	27	which	which	PRON
cana-2667	405	28	may	may	AUX
cana-2667	405	29	arise	arise	VERB
cana-2667	405	30	if	if	SCONJ
cana-2667	405	31	certain	certain	ADJ
cana-2667	405	32	classes	class	NOUN
cana-2667	405	33	like	like	ADP
cana-2667	405	34	pdr	pdr	PROPN
cana-2667	405	35	are	be	AUX
cana-2667	405	36	significantly	significantly	ADV
cana-2667	405	37	underrepresented	underrepresented	ADJ
cana-2667	405	38	in	in	ADP
cana-2667	405	39	the	the	DET
cana-2667	405	40	dataset	dataset	NOUN
cana-2667	405	41	,	,	PUNCT
cana-2667	405	42	and	and	CCONJ
cana-2667	405	43	lead	lead	VERB
cana-2667	405	44	to	to	ADP
cana-2667	405	45	aforementioned	aforementioned	ADJ
cana-2667	405	46	improvements	improvement	NOUN
cana-2667	405	47	in	in	ADP
cana-2667	405	48	model	model	NOUN
cana-2667	405	49	robustness	robustness	NOUN
cana-2667	405	50	.	.	PUNCT
cana-2667	406	1	future	future	ADJ
cana-2667	406	2	work	work	NOUN
cana-2667	406	3	might	might	AUX
cana-2667	406	4	also	also	ADV
cana-2667	406	5	investigate	investigate	VERB
cana-2667	406	6	the	the	DET
cana-2667	406	7	possibility	possibility	NOUN
cana-2667	406	8	of	of	ADP
cana-2667	406	9	combining	combine	VERB
cana-2667	406	10	this	this	DET
cana-2667	406	11	approach	approach	NOUN
cana-2667	406	12	with	with	ADP
cana-2667	406	13	additional	additional	ADJ
cana-2667	406	14	state	state	NOUN
cana-2667	406	15	-	-	PUNCT
cana-2667	406	16	ofthe	ofthe	NOUN
cana-2667	406	17	-	-	PUNCT
cana-2667	406	18	art	art	NOUN
cana-2667	406	19	machine	machine	NOUN
cana-2667	406	20	learning	learning	NOUN
cana-2667	406	21	approaches	approach	NOUN
cana-2667	406	22	like	like	ADP
cana-2667	406	23	transfer	transfer	NOUN
cana-2667	406	24	learning	learning	NOUN
cana-2667	406	25	or	or	CCONJ
cana-2667	406	26	reinforcement	reinforcement	NOUN
cana-2667	406	27	learning	learning	NOUN
cana-2667	406	28	to	to	PART
cana-2667	406	29	improve	improve	VERB
cana-2667	406	30	the	the	DET
cana-2667	406	31	relevance	relevance	NOUN
cana-2667	406	32	of	of	ADP
cana-2667	406	33	the	the	DET
cana-2667	406	34	results	result	NOUN
cana-2667	406	35	.	.	PUNCT
cana-2667	407	1	specifically	specifically	ADV
cana-2667	407	2	,	,	PUNCT
cana-2667	407	3	transfer	transfer	NOUN
cana-2667	407	4	learning	learning	NOUN
cana-2667	407	5	may	may	AUX
cana-2667	407	6	be	be	AUX
cana-2667	407	7	leveraged	leverage	VERB
cana-2667	407	8	to	to	ADP
cana-2667	407	9	fine	fine	ADJ
cana-2667	407	10	-	-	PUNCT
cana-2667	407	11	tune	tune	NOUN
cana-2667	407	12	models	model	NOUN
cana-2667	407	13	on	on	ADP
cana-2667	407	14	largescale	largescale	NOUN
cana-2667	407	15	datasets	dataset	NOUN
cana-2667	407	16	which	which	PRON
cana-2667	407	17	would	would	AUX
cana-2667	407	18	alleviate	alleviate	VERB
cana-2667	407	19	training	training	NOUN
cana-2667	407	20	time	time	NOUN
cana-2667	407	21	and	and	CCONJ
cana-2667	407	22	improve	improve	VERB
cana-2667	407	23	generalization	generalization	NOUN
cana-2667	407	24	.	.	PUNCT
cana-2667	408	1	moreover	moreover	ADV
cana-2667	408	2	,	,	PUNCT
cana-2667	408	3	integrating	integrate	VERB
cana-2667	408	4	multi	multi	ADJ
cana-2667	408	5	-	-	ADJ
cana-2667	408	6	modal	modal	ADJ
cana-2667	408	7	data	datum	NOUN
cana-2667	408	8	,	,	PUNCT
cana-2667	408	9	including	include	VERB
cana-2667	408	10	combining	combine	VERB
cana-2667	408	11	retinal	retinal	ADJ
cana-2667	408	12	images	image	NOUN
cana-2667	408	13	with	with	ADP
cana-2667	408	14	demographics	demographic	NOUN
cana-2667	408	15	and	and	CCONJ
cana-2667	408	16	medical	medical	ADJ
cana-2667	408	17	data	datum	NOUN
cana-2667	408	18	about	about	ADP
cana-2667	408	19	the	the	DET
cana-2667	408	20	patient	patient	NOUN
cana-2667	408	21	,	,	PUNCT
cana-2667	408	22	could	could	AUX
cana-2667	408	23	prove	prove	VERB
cana-2667	408	24	to	to	PART
cana-2667	408	25	make	make	VERB
cana-2667	408	26	more	more	ADV
cana-2667	408	27	accurate	accurate	ADJ
cana-2667	408	28	predictions	prediction	NOUN
cana-2667	408	29	by	by	ADP
cana-2667	408	30	helping	help	VERB
cana-2667	408	31	the	the	DET
cana-2667	408	32	model	model	NOUN
cana-2667	408	33	to	to	PART
cana-2667	408	34	consider	consider	VERB
cana-2667	408	35	and	and	CCONJ
cana-2667	408	36	account	account	VERB
cana-2667	408	37	for	for	ADP
cana-2667	408	38	a	a	DET
cana-2667	408	39	larger	large	ADJ
cana-2667	408	40	range	range	NOUN
cana-2667	408	41	of	of	ADP
cana-2667	408	42	risk	risk	NOUN
cana-2667	408	43	factors	factor	NOUN
cana-2667	408	44	linked	link	VERB
cana-2667	408	45	with	with	ADP
cana-2667	408	46	the	the	DET
cana-2667	408	47	development	development	NOUN
cana-2667	408	48	of	of	ADP
cana-2667	408	49	diabetic	diabetic	ADJ
cana-2667	408	50	retinopathy	retinopathy	NOUN
cana-2667	408	51	.	.	PUNCT
cana-2667	409	1	in	in	ADP
cana-2667	409	2	addition	addition	NOUN
cana-2667	409	3	,	,	PUNCT
cana-2667	409	4	real	real	ADJ
cana-2667	409	5	-	-	PUNCT
cana-2667	409	6	time	time	NOUN
cana-2667	409	7	execution	execution	NOUN
cana-2667	409	8	and	and	CCONJ
cana-2667	409	9	application	application	NOUN
cana-2667	409	10	and	and	CCONJ
cana-2667	409	11	fixation	fixation	NOUN
cana-2667	409	12	of	of	ADP
cana-2667	409	13	the	the	DET
cana-2667	409	14	model	model	NOUN
cana-2667	409	15	in	in	ADP
cana-2667	409	16	clinical	clinical	ADJ
cana-2667	409	17	settings	setting	NOUN
cana-2667	409	18	would	would	AUX
cana-2667	409	19	demand	demand	VERB
cana-2667	409	20	additional	additional	ADJ
cana-2667	409	21	assessment	assessment	NOUN
cana-2667	409	22	,	,	PUNCT
cana-2667	409	23	through	through	ADP
cana-2667	409	24	validation	validation	NOUN
cana-2667	409	25	on	on	ADP
cana-2667	409	26	live	live	ADJ
cana-2667	409	27	data	datum	NOUN
cana-2667	409	28	streams	stream	NOUN
cana-2667	409	29	and	and	CCONJ
cana-2667	409	30	incorporation	incorporation	NOUN
cana-2667	409	31	into	into	ADP
cana-2667	409	32	existing	exist	VERB
cana-2667	409	33	health	health	NOUN
cana-2667	409	34	care	care	NOUN
cana-2667	409	35	systems	system	NOUN
cana-2667	409	36	.	.	PUNCT
cana-2667	410	1	the	the	DET
cana-2667	410	2	robustness	robustness	NOUN
cana-2667	410	3	of	of	ADP
cana-2667	410	4	the	the	DET
cana-2667	410	5	model	model	NOUN
cana-2667	410	6	in	in	ADP
cana-2667	410	7	different	different	ADJ
cana-2667	410	8	clinical	clinical	ADJ
cana-2667	410	9	backgrounds	background	NOUN
cana-2667	410	10	and	and	CCONJ
cana-2667	410	11	the	the	DET
cana-2667	410	12	quality	quality	NOUN
cana-2667	410	13	/	/	SYM
cana-2667	410	14	resolution	resolution	NOUN
cana-2667	410	15	of	of	ADP
cana-2667	410	16	the	the	DET
cana-2667	410	17	images	image	NOUN
cana-2667	410	18	that	that	PRON
cana-2667	410	19	can	can	AUX
cana-2667	410	20	affect	affect	VERB
cana-2667	410	21	the	the	DET
cana-2667	410	22	model	model	NOUN
cana-2667	410	23	or	or	CCONJ
cana-2667	410	24	require	require	VERB
cana-2667	410	25	upside	upside	ADJ
cana-2667	410	26	/	/	SYM
cana-2667	410	27	down	down	ADP
cana-2667	410	28	abilities	ability	NOUN
cana-2667	410	29	.	.	PUNCT
cana-2667	411	1	thus	thus	ADV
cana-2667	411	2	,	,	PUNCT
cana-2667	411	3	the	the	DET
cana-2667	411	4	hybrid	hybrid	ADJ
cana-2667	411	5	approach	approach	NOUN
cana-2667	411	6	can	can	AUX
cana-2667	411	7	be	be	AUX
cana-2667	411	8	a	a	DET
cana-2667	411	9	powerful	powerful	ADJ
cana-2667	411	10	tool	tool	NOUN
cana-2667	411	11	to	to	PART
cana-2667	411	12	ensure	ensure	VERB
cana-2667	411	13	high	high	ADJ
cana-2667	411	14	accuracy	accuracy	NOUN
cana-2667	411	15	with	with	ADP
cana-2667	411	16	less	less	ADJ
cana-2667	411	17	computation	computation	NOUN
cana-2667	411	18	time	time	NOUN
cana-2667	411	19	with	with	ADP
cana-2667	411	20	larger	large	ADJ
cana-2667	411	21	datasets	dataset	NOUN
cana-2667	411	22	.	.	PUNCT
cana-2667	412	1	with	with	ADP
cana-2667	412	2	challenges	challenge	NOUN
cana-2667	412	3	such	such	ADJ
cana-2667	412	4	as	as	ADP
cana-2667	412	5	feature	feature	NOUN
cana-2667	412	6	extraction	extraction	NOUN
cana-2667	412	7	and	and	CCONJ
cana-2667	412	8	class	class	NOUN
cana-2667	412	9	imbalance	imbalance	NOUN
cana-2667	412	10	,	,	PUNCT
cana-2667	412	11	addressing	address	VERB
cana-2667	412	12	these	these	DET
cana-2667	412	13	issues	issue	NOUN
cana-2667	412	14	allows	allow	VERB
cana-2667	412	15	the	the	DET
cana-2667	412	16	hybrid	hybrid	NOUN
cana-2667	412	17	model	model	NOUN
cana-2667	412	18	to	to	PART
cana-2667	412	19	give	give	VERB
cana-2667	412	20	an	an	DET
cana-2667	412	21	efficient	efficient	ADJ
cana-2667	412	22	mean	mean	NOUN
cana-2667	412	23	for	for	ADP
cana-2667	412	24	early	early	ADJ
cana-2667	412	25	detection	detection	NOUN
cana-2667	412	26	and	and	CCONJ
cana-2667	412	27	thus	thus	ADV
cana-2667	412	28	can	can	AUX
cana-2667	412	29	help	help	VERB
cana-2667	412	30	decrease	decrease	VERB
cana-2667	412	31	the	the	DET
cana-2667	412	32	advancement	advancement	NOUN
cana-2667	412	33	of	of	ADP
cana-2667	412	34	diabetic	diabetic	ADJ
cana-2667	412	35	retinopathy	retinopathy	NOUN
cana-2667	412	36	as	as	ADV
cana-2667	412	37	well	well	ADV
cana-2667	412	38	as	as	ADP
cana-2667	412	39	enhancing	enhance	VERB
cana-2667	412	40	patients	patient	NOUN
cana-2667	412	41	'	'	PART
cana-2667	412	42	way	way	NOUN
cana-2667	412	43	of	of	ADP
cana-2667	412	44	life	life	NOUN
cana-2667	412	45	.	.	PUNCT
cana-2667	413	1	the	the	DET
cana-2667	413	2	present	present	ADJ
cana-2667	413	3	study	study	NOUN
cana-2667	413	4	showed	show	VERB
cana-2667	413	5	encouraging	encouraging	ADJ
cana-2667	413	6	performance	performance	NOUN
cana-2667	413	7	results	result	NOUN
cana-2667	413	8	which	which	PRON
cana-2667	413	9	pave	pave	VERB
cana-2667	413	10	the	the	DET
cana-2667	413	11	way	way	NOUN
cana-2667	413	12	for	for	ADP
cana-2667	413	13	further	further	ADJ
cana-2667	413	14	developments	development	NOUN
cana-2667	413	15	of	of	ADP
cana-2667	413	16	automated	automate	VERB
cana-2667	413	17	dr	dr	PROPN
cana-2667	413	18	systems	system	NOUN
cana-2667	413	19	and	and	CCONJ
cana-2667	413	20	demonstrate	demonstrate	VERB
cana-2667	413	21	how	how	SCONJ
cana-2667	413	22	hybridisation	hybridisation	NOUN
cana-2667	413	23	of	of	ADP
cana-2667	413	24	ml	ml	NOUN
cana-2667	413	25	techniques	technique	NOUN
cana-2667	413	26	has	have	VERB
cana-2667	413	27	potential	potential	NOUN
cana-2667	413	28	in	in	ADP
cana-2667	413	29	medical	medical	ADJ
cana-2667	413	30	image	image	NOUN
cana-2667	413	31	processing	processing	NOUN
cana-2667	413	32	.	.	PUNCT
cana-2667	414	1	this	this	DET
cana-2667	414	2	study	study	NOUN
cana-2667	414	3	has	have	VERB
cana-2667	414	4	important	important	ADJ
cana-2667	414	5	implications	implication	NOUN
cana-2667	414	6	for	for	ADP
cana-2667	414	7	research	research	NOUN
cana-2667	414	8	and	and	CCONJ
cana-2667	414	9	clinical	clinical	ADJ
cana-2667	414	10	practice	practice	NOUN
cana-2667	414	11	.	.	PUNCT
cana-2667	415	1	the	the	DET
cana-2667	415	2	high	high	ADJ
cana-2667	415	3	-	-	PUNCT
cana-2667	415	4	performance	performance	NOUN
cana-2667	415	5	of	of	ADP
cana-2667	415	6	cnns	cnn	NOUN
cana-2667	415	7	and	and	CCONJ
cana-2667	415	8	svms	svms	NOUN
cana-2667	415	9	in	in	ADP
cana-2667	415	10	dr	dr	PROPN
cana-2667	415	11	classification	classification	NOUN
cana-2667	415	12	is	be	AUX
cana-2667	415	13	an	an	DET
cana-2667	415	14	important	important	ADJ
cana-2667	415	15	study	study	NOUN
cana-2667	415	16	for	for	ADP
cana-2667	415	17	researchers	researcher	NOUN
cana-2667	415	18	,	,	PUNCT
cana-2667	415	19	which	which	PRON
cana-2667	415	20	encourages	encourage	VERB
cana-2667	415	21	the	the	DET
cana-2667	415	22	research	research	NOUN
cana-2667	415	23	of	of	ADP
cana-2667	415	24	other	other	ADJ
cana-2667	415	25	hybrid	hybrid	NOUN
cana-2667	415	26	models	model	NOUN
cana-2667	415	27	in	in	ADP
cana-2667	415	28	medical	medical	ADJ
cana-2667	415	29	imaging	imaging	NOUN
cana-2667	415	30	that	that	PRON
cana-2667	415	31	requires	require	VERB
cana-2667	415	32	coherent	coherent	ADJ
cana-2667	415	33	knowledge	knowledge	NOUN
cana-2667	415	34	of	of	ADP
cana-2667	415	35	feature	feature	NOUN
cana-2667	415	36	extraction	extraction	NOUN
cana-2667	415	37	and	and	CCONJ
cana-2667	415	38	reliable	reliable	ADJ
cana-2667	415	39	classification	classification	NOUN
cana-2667	415	40	.	.	PUNCT
cana-2667	416	1	this	this	DET
cana-2667	416	2	method	method	NOUN
cana-2667	416	3	has	have	VERB
cana-2667	416	4	the	the	DET
cana-2667	416	5	potential	potential	NOUN
cana-2667	416	6	to	to	PART
cana-2667	416	7	become	become	VERB
cana-2667	416	8	a	a	DET
cana-2667	416	9	more	more	ADV
cana-2667	416	10	effective	effective	ADJ
cana-2667	416	11	hybrid	hybrid	NOUN
cana-2667	416	12	method	method	NOUN
cana-2667	416	13	that	that	PRON
cana-2667	416	14	,	,	PUNCT
cana-2667	416	15	ultimately	ultimately	ADV
cana-2667	416	16	,	,	PUNCT
cana-2667	416	17	can	can	AUX
cana-2667	416	18	be	be	AUX
cana-2667	416	19	used	use	VERB
cana-2667	416	20	for	for	ADP
cana-2667	416	21	early	early	ADJ
cana-2667	416	22	detection	detection	NOUN
cana-2667	416	23	of	of	ADP
cana-2667	416	24	dr	dr	PROPN
cana-2667	416	25	,	,	PUNCT
cana-2667	416	26	ultimately	ultimately	ADV
cana-2667	416	27	leading	lead	VERB
cana-2667	416	28	towards	towards	ADP
cana-2667	416	29	better	well	ADJ
cana-2667	416	30	management	management	NOUN
cana-2667	416	31	of	of	ADP
cana-2667	416	32	diabetic	diabetic	ADJ
cana-2667	416	33	patients	patient	NOUN
cana-2667	416	34	.	.	PUNCT
cana-2667	417	1	the	the	DET
cana-2667	417	2	ability	ability	NOUN
cana-2667	417	3	of	of	ADP
cana-2667	417	4	the	the	DET
cana-2667	417	5	model	model	NOUN
cana-2667	417	6	to	to	PART
cana-2667	417	7	automate	automate	VERB
cana-2667	417	8	the	the	DET
cana-2667	417	9	process	process	NOUN
cana-2667	417	10	of	of	ADP
cana-2667	417	11	dr	dr	PROPN
cana-2667	417	12	screening	screen	VERB
cana-2667	417	13	communications	communication	NOUN
cana-2667	417	14	on	on	ADP
cana-2667	417	15	applied	apply	VERB
cana-2667	417	16	nonlinear	nonlinear	ADJ
cana-2667	417	17	analysis	analysis	NOUN
cana-2667	417	18	issn	issn	NOUN
cana-2667	417	19	:	:	PUNCT
cana-2667	417	20	1074	1074	NUM
cana-2667	417	21	-	-	PUNCT
cana-2667	417	22	133x	133x	NUM
cana-2667	417	23	vol	vol	NOUN
cana-2667	417	24	32	32	NUM
cana-2667	417	25	no	no	NOUN
cana-2667	417	26	.	.	PUNCT
cana-2667	418	1	3s	3s	NUM
cana-2667	418	2	(	(	PUNCT
cana-2667	418	3	2025	2025	NUM
cana-2667	418	4	)	)	PUNCT
cana-2667	418	5	404	404	NUM
cana-2667	418	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	418	7	could	could	AUX
cana-2667	418	8	reduce	reduce	VERB
cana-2667	418	9	the	the	DET
cana-2667	418	10	burden	burden	NOUN
cana-2667	418	11	on	on	ADP
cana-2667	418	12	healthcare	healthcare	NOUN
cana-2667	418	13	professionals	professional	NOUN
cana-2667	418	14	and	and	CCONJ
cana-2667	418	15	offer	offer	VERB
cana-2667	418	16	quicker	quick	ADJ
cana-2667	418	17	and	and	CCONJ
cana-2667	418	18	more	more	ADV
cana-2667	418	19	consistent	consistent	ADJ
cana-2667	418	20	results	result	NOUN
cana-2667	418	21	,	,	PUNCT
cana-2667	418	22	potentially	potentially	ADV
cana-2667	418	23	allowing	allow	VERB
cana-2667	418	24	for	for	ADP
cana-2667	418	25	earlier	early	ADJ
cana-2667	418	26	interventions	intervention	NOUN
cana-2667	418	27	and	and	CCONJ
cana-2667	418	28	improved	improve	VERB
cana-2667	418	29	patient	patient	ADJ
cana-2667	418	30	care	care	NOUN
cana-2667	418	31	.	.	PUNCT
cana-2667	419	1	references	reference	NOUN
cana-2667	419	2	:	:	PUNCT
cana-2667	420	1	[	[	X
cana-2667	420	2	1	1	NUM
cana-2667	420	3	]	]	X
cana-2667	420	4	bilal	bilal	PROPN
cana-2667	420	5	,	,	PUNCT
cana-2667	420	6	anas	anas	PROPN
cana-2667	420	7	,	,	PUNCT
cana-2667	420	8	et	et	PROPN
cana-2667	420	9	al	al	PROPN
cana-2667	420	10	.	.	PUNCT
cana-2667	421	1	"	"	PUNCT
cana-2667	421	2	improved	improve	VERB
cana-2667	421	3	support	support	NOUN
cana-2667	421	4	vector	vector	NOUN
cana-2667	421	5	machine	machine	NOUN
cana-2667	421	6	based	base	VERB
cana-2667	421	7	on	on	ADP
cana-2667	421	8	cnn	cnn	PROPN
cana-2667	421	9	-	-	PUNCT
cana-2667	421	10	svd	svd	PROPN
cana-2667	421	11	for	for	ADP
cana-2667	421	12	vision	vision	NOUN
cana-2667	421	13	-	-	PUNCT
cana-2667	421	14	threatening	threaten	VERB
cana-2667	421	15	diabetic	diabetic	ADJ
cana-2667	421	16	retinopathy	retinopathy	ADJ
cana-2667	421	17	detection	detection	NOUN
cana-2667	421	18	and	and	CCONJ
cana-2667	421	19	classification	classification	NOUN
cana-2667	421	20	.	.	PUNCT
cana-2667	421	21	"	"	PUNCT
cana-2667	422	1	plos	plo	VERB
cana-2667	422	2	one	one	NUM
cana-2667	422	3	19.1	19.1	NUM
cana-2667	422	4	(	(	PUNCT
cana-2667	422	5	2024	2024	NUM
cana-2667	422	6	):	):	PUNCT
cana-2667	422	7	e0295951	e0295951	PROPN
cana-2667	422	8	.	.	PUNCT
cana-2667	423	1	[	[	X
cana-2667	423	2	2	2	NUM
cana-2667	423	3	]	]	X
cana-2667	423	4	xiao	xiao	PROPN
cana-2667	423	5	,	,	PUNCT
cana-2667	423	6	li	li	PROPN
cana-2667	423	7	,	,	PUNCT
cana-2667	423	8	et	et	PROPN
cana-2667	423	9	al	al	PROPN
cana-2667	423	10	.	.	PUNCT
cana-2667	423	11	"	"	PUNCT
cana-2667	423	12	hho	hho	NOUN
cana-2667	423	13	optimized	optimize	VERB
cana-2667	423	14	support	support	NOUN
cana-2667	423	15	vector	vector	NOUN
cana-2667	423	16	machine	machine	NOUN
cana-2667	423	17	classifier	classifier	NOUN
cana-2667	423	18	for	for	ADP
cana-2667	423	19	traditional	traditional	ADJ
cana-2667	423	20	chinese	chinese	ADJ
cana-2667	423	21	medicine	medicine	NOUN
cana-2667	423	22	syndrome	syndrome	NOUN
cana-2667	423	23	differentiation	differentiation	NOUN
cana-2667	423	24	of	of	ADP
cana-2667	423	25	diabetic	diabetic	ADJ
cana-2667	423	26	retinopathy	retinopathy	NOUN
cana-2667	423	27	.	.	PUNCT
cana-2667	423	28	"	"	PUNCT
cana-2667	424	1	international	international	ADJ
cana-2667	424	2	journal	journal	NOUN
cana-2667	424	3	of	of	ADP
cana-2667	424	4	ophthalmology	ophthalmology	NOUN
cana-2667	424	5	17.6	17.6	NUM
cana-2667	424	6	(	(	PUNCT
cana-2667	424	7	2024	2024	NUM
cana-2667	424	8	):	):	PUNCT
cana-2667	424	9	991	991	NUM
cana-2667	424	10	.	.	PUNCT
cana-2667	425	1	[	[	X
cana-2667	425	2	3	3	NUM
cana-2667	425	3	]	]	X
cana-2667	425	4	thanikachalam	thanikachalam	VERB
cana-2667	425	5	,	,	PUNCT
cana-2667	425	6	v.	v.	ADV
cana-2667	425	7	,	,	PUNCT
cana-2667	425	8	k.	k.	PROPN
cana-2667	425	9	kabilan	kabilan	PROPN
cana-2667	425	10	,	,	PUNCT
cana-2667	425	11	and	and	CCONJ
cana-2667	425	12	sudheer	sudheer	NOUN
cana-2667	425	13	kumar	kumar	PROPN
cana-2667	425	14	erramchetty	erramchetty	PROPN
cana-2667	425	15	.	.	PUNCT
cana-2667	426	1	"	"	PUNCT
cana-2667	426	2	optimized	optimize	VERB
cana-2667	426	3	deep	deep	ADJ
cana-2667	426	4	cnn	cnn	PROPN
cana-2667	426	5	for	for	ADP
cana-2667	426	6	detection	detection	NOUN
cana-2667	426	7	and	and	CCONJ
cana-2667	426	8	classification	classification	NOUN
cana-2667	426	9	of	of	ADP
cana-2667	426	10	diabetic	diabetic	ADJ
cana-2667	426	11	retinopathy	retinopathy	ADJ
cana-2667	426	12	and	and	CCONJ
cana-2667	426	13	diabetic	diabetic	ADJ
cana-2667	426	14	macular	macular	ADJ
cana-2667	426	15	edema	edema	NOUN
cana-2667	426	16	.	.	PUNCT
cana-2667	426	17	"	"	PUNCT
cana-2667	427	1	bmc	bmc	PROPN
cana-2667	427	2	medical	medical	ADJ
cana-2667	427	3	imaging	imaging	NOUN
cana-2667	427	4	24.1	24.1	NUM
cana-2667	427	5	(	(	PUNCT
cana-2667	427	6	2024	2024	NUM
cana-2667	427	7	):	):	PUNCT
cana-2667	427	8	227	227	NUM
cana-2667	427	9	.	.	PUNCT
cana-2667	428	1	[	[	X
cana-2667	428	2	4	4	NUM
cana-2667	428	3	]	]	PUNCT
cana-2667	428	4	bhimavarapu	bhimavarapu	ADJ
cana-2667	428	5	,	,	PUNCT
cana-2667	428	6	usharani	usharani	NOUN
cana-2667	428	7	.	.	PUNCT
cana-2667	429	1	"	"	PUNCT
cana-2667	429	2	enhanced	enhanced	ADJ
cana-2667	429	3	convolution	convolution	NOUN
cana-2667	429	4	neural	neural	ADJ
cana-2667	429	5	network	network	NOUN
cana-2667	429	6	and	and	CCONJ
cana-2667	429	7	improved	improve	VERB
cana-2667	429	8	svm	svm	NOUN
cana-2667	429	9	to	to	PART
cana-2667	429	10	detect	detect	VERB
cana-2667	429	11	and	and	CCONJ
cana-2667	429	12	classify	classify	VERB
cana-2667	429	13	diabetic	diabetic	ADJ
cana-2667	429	14	retinopathy	retinopathy	NOUN
cana-2667	429	15	.	.	PUNCT
cana-2667	429	16	"	"	PUNCT
cana-2667	429	17	multimedia	multimedia	NOUN
cana-2667	429	18	tools	tool	NOUN
cana-2667	429	19	and	and	CCONJ
cana-2667	429	20	applications	application	NOUN
cana-2667	429	21	(	(	PUNCT
cana-2667	429	22	2024	2024	NUM
cana-2667	429	23	):	):	PUNCT
cana-2667	429	24	1	1	NUM
cana-2667	429	25	-	-	SYM
cana-2667	429	26	22	22	NUM
cana-2667	429	27	.	.	PUNCT
cana-2667	430	1	[	[	X
cana-2667	430	2	5	5	NUM
cana-2667	430	3	]	]	SYM
cana-2667	430	4	hamza	hamza	PROPN
cana-2667	430	5	,	,	PUNCT
cana-2667	430	6	muhammad	muhammad	PROPN
cana-2667	430	7	.	.	PUNCT
cana-2667	431	1	"	"	PUNCT
cana-2667	431	2	optimizing	optimize	VERB
cana-2667	431	3	early	early	ADJ
cana-2667	431	4	detection	detection	NOUN
cana-2667	431	5	of	of	ADP
cana-2667	431	6	diabetes	diabetes	NOUN
cana-2667	431	7	through	through	ADP
cana-2667	431	8	retinal	retinal	ADJ
cana-2667	431	9	imaging	imaging	NOUN
cana-2667	431	10	:	:	PUNCT
cana-2667	431	11	a	a	DET
cana-2667	431	12	comparative	comparative	ADJ
cana-2667	431	13	analysis	analysis	NOUN
cana-2667	431	14	of	of	ADP
cana-2667	431	15	deep	deep	ADJ
cana-2667	431	16	learning	learning	NOUN
cana-2667	431	17	and	and	CCONJ
cana-2667	431	18	machine	machine	NOUN
cana-2667	431	19	learning	learn	VERB
cana-2667	431	20	algorithms	algorithm	NOUN
cana-2667	431	21	.	.	PUNCT
cana-2667	431	22	"	"	PUNCT
cana-2667	432	1	journal	journal	NOUN
cana-2667	432	2	of	of	ADP
cana-2667	432	3	computational	computational	ADJ
cana-2667	432	4	informatics	informatic	NOUN
cana-2667	432	5	&	&	CCONJ
cana-2667	432	6	business	business	PROPN
cana-2667	432	7	1.1	1.1	NUM
cana-2667	432	8	(	(	PUNCT
cana-2667	432	9	2024	2024	NUM
cana-2667	432	10	)	)	PUNCT
cana-2667	432	11	.	.	PUNCT
cana-2667	433	1	[	[	X
cana-2667	433	2	6	6	NUM
cana-2667	433	3	]	]	PUNCT
cana-2667	433	4	bhimavarapu	bhimavarapu	ADJ
cana-2667	433	5	,	,	PUNCT
cana-2667	433	6	usharani	usharani	NOUN
cana-2667	433	7	,	,	PUNCT
cana-2667	433	8	nalini	nalini	X
cana-2667	433	9	chintalapudi	chintalapudi	PROPN
cana-2667	433	10	,	,	PUNCT
cana-2667	433	11	and	and	CCONJ
cana-2667	433	12	gopi	gopi	PROPN
cana-2667	433	13	battineni	battineni	PROPN
cana-2667	433	14	.	.	PUNCT
cana-2667	434	1	"	"	PUNCT
cana-2667	434	2	automatic	automatic	ADJ
cana-2667	434	3	detection	detection	NOUN
cana-2667	434	4	and	and	CCONJ
cana-2667	434	5	classification	classification	NOUN
cana-2667	434	6	of	of	ADP
cana-2667	434	7	hypertensive	hypertensive	ADJ
cana-2667	434	8	retinopathy	retinopathy	NOUN
cana-2667	434	9	with	with	ADP
cana-2667	434	10	improved	improved	ADJ
cana-2667	434	11	convolution	convolution	NOUN
cana-2667	434	12	neural	neural	ADJ
cana-2667	434	13	network	network	NOUN
cana-2667	434	14	and	and	CCONJ
cana-2667	434	15	improved	improved	ADJ
cana-2667	434	16	svm	svm	NOUN
cana-2667	434	17	.	.	PUNCT
cana-2667	434	18	"	"	PUNCT
cana-2667	434	19	bioengineering	bioengineere	VERB
cana-2667	434	20	11.1	11.1	NUM
cana-2667	434	21	(	(	PUNCT
cana-2667	434	22	2024	2024	NUM
cana-2667	434	23	):	):	PUNCT
cana-2667	434	24	56	56	NUM
cana-2667	434	25	.	.	PUNCT
cana-2667	435	1	[	[	X
cana-2667	435	2	7	7	NUM
cana-2667	435	3	]	]	X
cana-2667	435	4	bhimavarapu	bhimavarapu	ADJ
cana-2667	435	5	,	,	PUNCT
cana-2667	435	6	usharani	usharani	NOUN
cana-2667	435	7	.	.	PUNCT
cana-2667	436	1	"	"	PUNCT
cana-2667	436	2	diagnosis	diagnosis	NOUN
cana-2667	436	3	and	and	CCONJ
cana-2667	436	4	multiclass	multiclass	ADJ
cana-2667	436	5	classification	classification	NOUN
cana-2667	436	6	of	of	ADP
cana-2667	436	7	diabetic	diabetic	ADJ
cana-2667	436	8	retinopathy	retinopathy	NOUN
cana-2667	436	9	using	use	VERB
cana-2667	436	10	enhanced	enhanced	ADJ
cana-2667	436	11	multi	multi	ADJ
cana-2667	436	12	thresholding	thresholde	VERB
cana-2667	436	13	optimization	optimization	NOUN
cana-2667	436	14	algorithms	algorithm	NOUN
cana-2667	436	15	and	and	CCONJ
cana-2667	436	16	improved	improve	VERB
cana-2667	436	17	naive	naive	ADJ
cana-2667	436	18	bayes	bayes	NOUN
cana-2667	436	19	classifier	classifier	NOUN
cana-2667	436	20	.	.	PUNCT
cana-2667	436	21	"	"	PUNCT
cana-2667	436	22	multimedia	multimedia	NOUN
cana-2667	436	23	tools	tool	NOUN
cana-2667	436	24	and	and	CCONJ
cana-2667	436	25	applications	application	NOUN
cana-2667	436	26	(	(	PUNCT
cana-2667	436	27	2024	2024	NUM
cana-2667	436	28	):	):	PUNCT
cana-2667	436	29	1	1	NUM
cana-2667	436	30	-	-	SYM
cana-2667	436	31	35	35	NUM
cana-2667	436	32	.	.	PUNCT
cana-2667	437	1	[	[	X
cana-2667	437	2	8	8	NUM
cana-2667	437	3	]	]	X
cana-2667	437	4	anitha	anitha	PROPN
cana-2667	437	5	,	,	PUNCT
cana-2667	437	6	e.	e.	PROPN
cana-2667	437	7	,	,	PUNCT
cana-2667	437	8	and	and	CCONJ
cana-2667	437	9	john	john	PROPN
cana-2667	437	10	aravindhar	aravindhar	PROPN
cana-2667	437	11	.	.	PUNCT
cana-2667	438	1	"	"	PUNCT
cana-2667	438	2	efficient	efficient	ADJ
cana-2667	438	3	retinal	retinal	ADJ
cana-2667	438	4	detachment	detachment	NOUN
cana-2667	438	5	classification	classification	NOUN
cana-2667	438	6	using	use	VERB
cana-2667	438	7	hybrid	hybrid	ADJ
cana-2667	438	8	machine	machine	NOUN
cana-2667	438	9	learning	learn	VERB
cana-2667	438	10	with	with	ADP
cana-2667	438	11	levy	levy	NOUN
cana-2667	438	12	flight	flight	NOUN
cana-2667	438	13	-	-	PUNCT
cana-2667	438	14	based	base	VERB
cana-2667	438	15	optimization	optimization	NOUN
cana-2667	438	16	.	.	PUNCT
cana-2667	438	17	"	"	PUNCT
cana-2667	439	1	expert	expert	ADJ
cana-2667	439	2	systems	system	NOUN
cana-2667	439	3	with	with	ADP
cana-2667	439	4	applications	application	NOUN
cana-2667	439	5	239	239	NUM
cana-2667	439	6	(	(	PUNCT
cana-2667	439	7	2024	2024	NUM
cana-2667	439	8	):	):	PUNCT
cana-2667	439	9	122311	122311	NUM
cana-2667	439	10	.	.	PUNCT
cana-2667	440	1	[	[	X
cana-2667	440	2	9	9	NUM
cana-2667	440	3	]	]	PUNCT
cana-2667	440	4	kayathri	kayathri	PROPN
cana-2667	440	5	,	,	PUNCT
cana-2667	440	6	k.	k.	PROPN
cana-2667	440	7	,	,	PUNCT
cana-2667	440	8	and	and	CCONJ
cana-2667	440	9	k.	k.	PROPN
cana-2667	440	10	kavitha	kavitha	PROPN
cana-2667	440	11	.	.	PUNCT
cana-2667	441	1	"	"	PUNCT
cana-2667	441	2	cgsx	cgsx	NOUN
cana-2667	441	3	ensemble	ensemble	ADJ
cana-2667	441	4	:	:	PUNCT
cana-2667	441	5	an	an	DET
cana-2667	441	6	integrative	integrative	ADJ
cana-2667	441	7	machine	machine	NOUN
cana-2667	441	8	learning	learning	NOUN
cana-2667	441	9	and	and	CCONJ
cana-2667	441	10	deep	deep	ADJ
cana-2667	441	11	learning	learning	NOUN
cana-2667	441	12	approach	approach	NOUN
cana-2667	441	13	for	for	ADP
cana-2667	441	14	improved	improved	ADJ
cana-2667	441	15	diabetic	diabetic	ADJ
cana-2667	441	16	retinopathy	retinopathy	ADJ
cana-2667	441	17	classification	classification	NOUN
cana-2667	441	18	.	.	PUNCT
cana-2667	441	19	"	"	PUNCT
cana-2667	442	1	international	international	ADJ
cana-2667	442	2	journal	journal	NOUN
cana-2667	442	3	of	of	ADP
cana-2667	442	4	electrical	electrical	ADJ
cana-2667	442	5	and	and	CCONJ
cana-2667	442	6	electronics	electronic	NOUN
cana-2667	442	7	research	research	NOUN
cana-2667	442	8	12.2	12.2	NUM
cana-2667	442	9	(	(	PUNCT
cana-2667	442	10	2024	2024	NUM
cana-2667	442	11	):	):	PUNCT
cana-2667	442	12	669	669	NUM
cana-2667	442	13	-	-	SYM
cana-2667	442	14	681	681	NUM
cana-2667	442	15	.	.	PUNCT
cana-2667	443	1	[	[	X
cana-2667	443	2	10	10	NUM
cana-2667	443	3	]	]	X
cana-2667	443	4	bilal	bilal	PROPN
cana-2667	443	5	,	,	PUNCT
cana-2667	443	6	anas	anas	PROPN
cana-2667	443	7	,	,	PUNCT
cana-2667	443	8	et	et	PROPN
cana-2667	443	9	al	al	PROPN
cana-2667	443	10	.	.	PUNCT
cana-2667	444	1	"	"	PUNCT
cana-2667	444	2	breast	breast	NOUN
cana-2667	444	3	cancer	cancer	NOUN
cana-2667	444	4	diagnosis	diagnosis	NOUN
cana-2667	444	5	using	use	VERB
cana-2667	444	6	support	support	NOUN
cana-2667	444	7	vector	vector	NOUN
cana-2667	444	8	machine	machine	NOUN
cana-2667	444	9	optimized	optimize	VERB
cana-2667	444	10	by	by	ADP
cana-2667	444	11	improved	improve	VERB
cana-2667	444	12	quantum	quantum	NOUN
cana-2667	444	13	inspired	inspire	VERB
cana-2667	444	14	grey	grey	ADJ
cana-2667	444	15	wolf	wolf	PROPN
cana-2667	444	16	optimization	optimization	NOUN
cana-2667	444	17	.	.	PUNCT
cana-2667	444	18	"	"	PUNCT
cana-2667	445	1	scientific	scientific	ADJ
cana-2667	445	2	reports	report	NOUN
cana-2667	445	3	14.1	14.1	NUM
cana-2667	445	4	(	(	PUNCT
cana-2667	445	5	2024	2024	NUM
cana-2667	445	6	):	):	PUNCT
cana-2667	445	7	10714	10714	NUM
cana-2667	445	8	.	.	PUNCT
cana-2667	446	1	[	[	X
cana-2667	446	2	11	11	NUM
cana-2667	446	3	]	]	X
cana-2667	446	4	al	al	PROPN
cana-2667	446	5	-	-	PUNCT
cana-2667	446	6	farouni	farouni	PROPN
cana-2667	446	7	,	,	PUNCT
cana-2667	446	8	mohammed	mohammed	PROPN
cana-2667	446	9	,	,	PUNCT
cana-2667	446	10	et	et	PROPN
cana-2667	446	11	al	al	PROPN
cana-2667	446	12	.	.	PUNCT
cana-2667	447	1	"	"	PUNCT
cana-2667	447	2	comparative	comparative	ADJ
cana-2667	447	3	approach	approach	NOUN
cana-2667	447	4	on	on	ADP
cana-2667	447	5	machine	machine	NOUN
cana-2667	447	6	learning	learning	NOUN
cana-2667	447	7	and	and	CCONJ
cana-2667	447	8	deep	deep	ADJ
cana-2667	447	9	learning	learning	NOUN
cana-2667	447	10	techniques	technique	NOUN
cana-2667	447	11	based	base	VERB
cana-2667	447	12	diabetic	diabetic	ADJ
cana-2667	447	13	retinopathy	retinopathy	ADJ
cana-2667	447	14	detection	detection	NOUN
cana-2667	447	15	.	.	PUNCT
cana-2667	447	16	"	"	PUNCT
cana-2667	448	1	2024	2024	NUM
cana-2667	448	2	second	second	ADJ
cana-2667	448	3	international	international	ADJ
cana-2667	448	4	conference	conference	NOUN
cana-2667	448	5	on	on	ADP
cana-2667	448	6	networks	network	NOUN
cana-2667	448	7	,	,	PUNCT
cana-2667	448	8	multimedia	multimedia	NOUN
cana-2667	448	9	and	and	CCONJ
cana-2667	448	10	information	information	NOUN
cana-2667	448	11	technology	technology	NOUN
cana-2667	448	12	(	(	PUNCT
cana-2667	448	13	nmitcon	nmitcon	PROPN
cana-2667	448	14	)	)	PUNCT
cana-2667	448	15	.	.	PUNCT
cana-2667	449	1	ieee	ieee	NOUN
cana-2667	449	2	,	,	PUNCT
cana-2667	449	3	2024	2024	NUM
cana-2667	449	4	.	.	PUNCT
cana-2667	450	1	[	[	X
cana-2667	450	2	12	12	NUM
cana-2667	450	3	]	]	X
cana-2667	450	4	salman	salman	PROPN
cana-2667	450	5	,	,	PUNCT
cana-2667	450	6	ahmed	ahmed	PROPN
cana-2667	450	7	hussein	hussein	PROPN
cana-2667	450	8	,	,	PUNCT
cana-2667	450	9	and	and	CCONJ
cana-2667	450	10	waleed	waleed	PROPN
cana-2667	450	11	ameen	ameen	PROPN
cana-2667	450	12	mahmoud	mahmoud	PROPN
cana-2667	450	13	al	al	PROPN
cana-2667	450	14	-	-	PUNCT
cana-2667	450	15	jawher	jawher	NOUN
cana-2667	450	16	.	.	PUNCT
cana-2667	451	1	"	"	PUNCT
cana-2667	451	2	performance	performance	NOUN
cana-2667	451	3	comparison	comparison	NOUN
cana-2667	451	4	of	of	ADP
cana-2667	451	5	support	support	NOUN
cana-2667	451	6	vector	vector	NOUN
cana-2667	451	7	machines	machine	NOUN
cana-2667	451	8	,	,	PUNCT
cana-2667	451	9	adaboost	adaboost	ADV
cana-2667	451	10	,	,	PUNCT
cana-2667	451	11	and	and	CCONJ
cana-2667	451	12	random	random	ADJ
cana-2667	451	13	forest	forest	NOUN
cana-2667	451	14	for	for	ADP
cana-2667	451	15	sentiment	sentiment	NOUN
cana-2667	451	16	text	text	NOUN
cana-2667	451	17	analysis	analysis	NOUN
cana-2667	451	18	and	and	CCONJ
cana-2667	451	19	classification	classification	NOUN
cana-2667	451	20	.	.	PUNCT
cana-2667	451	21	"	"	PUNCT
cana-2667	452	1	journal	journal	PROPN
cana-2667	452	2	port	port	NOUN
cana-2667	452	3	science	science	NOUN
cana-2667	452	4	research	research	NOUN
cana-2667	452	5	7.3	7.3	NUM
cana-2667	452	6	(	(	PUNCT
cana-2667	452	7	2024	2024	NUM
cana-2667	452	8	):	):	PUNCT
cana-2667	452	9	300	300	NUM
cana-2667	452	10	-	-	SYM
cana-2667	452	11	311	311	NUM
cana-2667	452	12	.	.	PUNCT
cana-2667	453	1	[	[	X
cana-2667	453	2	13	13	NUM
cana-2667	453	3	]	]	SYM
cana-2667	453	4	lalithadevi	lalithadevi	NOUN
cana-2667	453	5	,	,	PUNCT
cana-2667	453	6	b.	b.	PROPN
cana-2667	453	7	,	,	PUNCT
cana-2667	453	8	and	and	CCONJ
cana-2667	453	9	s.	s.	PROPN
cana-2667	453	10	krishnaveni	krishnaveni	PROPN
cana-2667	453	11	.	.	PUNCT
cana-2667	454	1	"	"	PUNCT
cana-2667	454	2	diabetic	diabetic	ADJ
cana-2667	454	3	retinopathy	retinopathy	ADJ
cana-2667	454	4	detection	detection	NOUN
cana-2667	454	5	and	and	CCONJ
cana-2667	454	6	severity	severity	NOUN
cana-2667	454	7	classification	classification	NOUN
cana-2667	454	8	using	use	VERB
cana-2667	454	9	optimized	optimize	VERB
cana-2667	454	10	deep	deep	ADJ
cana-2667	454	11	learning	learning	NOUN
cana-2667	454	12	with	with	ADP
cana-2667	454	13	explainable	explainable	ADJ
cana-2667	454	14	ai	ai	NOUN
cana-2667	454	15	technique	technique	NOUN
cana-2667	454	16	.	.	PUNCT
cana-2667	454	17	"	"	PUNCT
cana-2667	454	18	multimedia	multimedia	NOUN
cana-2667	454	19	tools	tool	NOUN
cana-2667	454	20	and	and	CCONJ
cana-2667	454	21	applications	application	NOUN
cana-2667	454	22	(	(	PUNCT
cana-2667	454	23	2024	2024	NUM
cana-2667	454	24	):	):	PUNCT
cana-2667	454	25	1	1	NUM
cana-2667	454	26	-	-	SYM
cana-2667	454	27	65	65	NUM
cana-2667	454	28	.	.	PUNCT
cana-2667	455	1	[	[	X
cana-2667	455	2	14	14	NUM
cana-2667	455	3	]	]	X
cana-2667	455	4	zannah	zannah	PROPN
cana-2667	455	5	,	,	PUNCT
cana-2667	455	6	tasnim	tasnim	NOUN
cana-2667	455	7	bill	bill	NOUN
cana-2667	455	8	,	,	PUNCT
cana-2667	455	9	et	et	PROPN
cana-2667	455	10	al	al	PROPN
cana-2667	455	11	.	.	PUNCT
cana-2667	456	1	"	"	PUNCT
cana-2667	456	2	bayesian	bayesian	NOUN
cana-2667	456	3	optimized	optimize	VERB
cana-2667	456	4	machine	machine	NOUN
cana-2667	456	5	learning	learning	NOUN
cana-2667	456	6	model	model	NOUN
cana-2667	456	7	for	for	ADP
cana-2667	456	8	automated	automate	VERB
cana-2667	456	9	eye	eye	NOUN
cana-2667	456	10	disease	disease	NOUN
cana-2667	456	11	classification	classification	NOUN
cana-2667	456	12	from	from	ADP
cana-2667	456	13	fundus	fundus	NOUN
cana-2667	456	14	images	image	NOUN
cana-2667	456	15	.	.	PUNCT
cana-2667	456	16	"	"	PUNCT
cana-2667	456	17	computation	computation	NOUN
cana-2667	456	18	12.9	12.9	NUM
cana-2667	456	19	(	(	PUNCT
cana-2667	456	20	2024	2024	NUM
cana-2667	456	21	):	):	PUNCT
cana-2667	456	22	190	190	NUM
cana-2667	456	23	.	.	PUNCT
cana-2667	457	1	[	[	X
cana-2667	457	2	15	15	NUM
cana-2667	457	3	]	]	X
cana-2667	457	4	ashwini	ashwini	PROPN
cana-2667	457	5	,	,	PUNCT
cana-2667	457	6	k.	k.	PROPN
cana-2667	457	7	,	,	PUNCT
cana-2667	457	8	and	and	CCONJ
cana-2667	457	9	ratnakar	ratnakar	ADJ
cana-2667	457	10	dash	dash	NOUN
cana-2667	457	11	.	.	PUNCT
cana-2667	458	1	"	"	PUNCT
cana-2667	458	2	improving	improve	VERB
cana-2667	458	3	diabetic	diabetic	ADJ
cana-2667	458	4	retinopathy	retinopathy	ADJ
cana-2667	458	5	grading	grade	VERB
cana-2667	458	6	using	use	VERB
cana-2667	458	7	feature	feature	NOUN
cana-2667	458	8	fusion	fusion	NOUN
cana-2667	458	9	for	for	ADP
cana-2667	458	10	limited	limited	ADJ
cana-2667	458	11	data	data	NOUN
cana-2667	458	12	samples	sample	NOUN
cana-2667	458	13	.	.	PUNCT
cana-2667	458	14	"	"	PUNCT
cana-2667	458	15	computers	computer	NOUN
cana-2667	458	16	and	and	CCONJ
cana-2667	458	17	electrical	electrical	ADJ
cana-2667	458	18	engineering	engineering	NOUN
cana-2667	458	19	120	120	NUM
cana-2667	458	20	(	(	PUNCT
cana-2667	458	21	2024	2024	NUM
cana-2667	458	22	):	):	PUNCT
cana-2667	458	23	109782	109782	NUM
cana-2667	458	24	.	.	PUNCT
cana-2667	459	1	[	[	X
cana-2667	459	2	16	16	NUM
cana-2667	459	3	]	]	SYM
cana-2667	459	4	behera	behera	PROPN
cana-2667	459	5	,	,	PUNCT
cana-2667	459	6	santi	santi	PROPN
cana-2667	459	7	kumari	kumari	PROPN
cana-2667	459	8	,	,	PUNCT
cana-2667	459	9	et	et	PROPN
cana-2667	459	10	al	al	PROPN
cana-2667	459	11	.	.	PUNCT
cana-2667	460	1	"	"	PUNCT
cana-2667	460	2	diagnosis	diagnosis	NOUN
cana-2667	460	3	of	of	ADP
cana-2667	460	4	retinal	retinal	ADJ
cana-2667	460	5	damage	damage	NOUN
cana-2667	460	6	using	use	VERB
cana-2667	460	7	resnet	resnet	NOUN
cana-2667	460	8	rescaling	rescaling	NOUN
cana-2667	460	9	and	and	CCONJ
cana-2667	460	10	support	support	VERB
cana-2667	460	11	vector	vector	NOUN
cana-2667	460	12	machine	machine	NOUN
cana-2667	460	13	(	(	PUNCT
cana-2667	460	14	resnet	resnet	NOUN
cana-2667	460	15	-	-	PUNCT
cana-2667	460	16	rs	rs	NOUN
cana-2667	460	17	-	-	PUNCT
cana-2667	460	18	svm	svm	ADJ
cana-2667	460	19	):	):	PUNCT
cana-2667	460	20	a	a	DET
cana-2667	460	21	case	case	NOUN
cana-2667	460	22	study	study	NOUN
cana-2667	460	23	from	from	ADP
cana-2667	460	24	an	an	DET
cana-2667	460	25	indian	indian	ADJ
cana-2667	460	26	hospital	hospital	NOUN
cana-2667	460	27	.	.	PUNCT
cana-2667	460	28	"	"	PUNCT
cana-2667	461	1	international	international	ADJ
cana-2667	461	2	ophthalmology	ophthalmology	NOUN
cana-2667	461	3	44.1	44.1	NUM
cana-2667	461	4	(	(	PUNCT
cana-2667	461	5	2024	2024	NUM
cana-2667	461	6	):	):	PUNCT
cana-2667	461	7	1	1	NUM
cana-2667	461	8	-	-	SYM
cana-2667	461	9	8	8	NUM
cana-2667	461	10	.	.	PUNCT
cana-2667	462	1	[	[	X
cana-2667	462	2	17	17	NUM
cana-2667	462	3	]	]	PUNCT
cana-2667	462	4	veena	veena	NOUN
cana-2667	462	5	,	,	PUNCT
cana-2667	462	6	a.	a.	NOUN
cana-2667	462	7	,	,	PUNCT
cana-2667	462	8	and	and	CCONJ
cana-2667	462	9	s.	s.	PROPN
cana-2667	462	10	gowrishankar	gowrishankar	PROPN
cana-2667	462	11	.	.	PUNCT
cana-2667	463	1	"	"	PUNCT
cana-2667	463	2	deep	deep	ADJ
cana-2667	463	3	learning	learning	NOUN
cana-2667	463	4	based	base	VERB
cana-2667	463	5	hemorrhages	hemorrhage	NOUN
cana-2667	463	6	classification	classification	NOUN
cana-2667	463	7	using	use	VERB
cana-2667	463	8	dcnn	dcnn	PROPN
cana-2667	463	9	with	with	ADP
cana-2667	463	10	optimized	optimize	VERB
cana-2667	463	11	lstm	lstm	NOUN
cana-2667	463	12	.	.	PUNCT
cana-2667	463	13	"	"	PUNCT
cana-2667	463	14	multimedia	multimedia	NOUN
cana-2667	463	15	tools	tool	NOUN
cana-2667	463	16	and	and	CCONJ
cana-2667	463	17	applications	application	NOUN
cana-2667	463	18	(	(	PUNCT
cana-2667	463	19	2024	2024	NUM
cana-2667	463	20	):	):	PUNCT
cana-2667	463	21	1	1	NUM
cana-2667	463	22	-	-	SYM
cana-2667	463	23	22	22	NUM
cana-2667	463	24	.	.	PUNCT
cana-2667	464	1	[	[	X
cana-2667	464	2	18	18	NUM
cana-2667	464	3	]	]	X
cana-2667	464	4	taifa	taifa	PROPN
cana-2667	464	5	,	,	PUNCT
cana-2667	464	6	intifa	intifa	PROPN
cana-2667	464	7	aman	aman	PROPN
cana-2667	464	8	,	,	PUNCT
cana-2667	464	9	et	et	PROPN
cana-2667	464	10	al	al	PROPN
cana-2667	464	11	.	.	PUNCT
cana-2667	465	1	"	"	PUNCT
cana-2667	465	2	a	a	DET
cana-2667	465	3	hybrid	hybrid	ADJ
cana-2667	465	4	approach	approach	NOUN
cana-2667	465	5	with	with	ADP
cana-2667	465	6	customized	customize	VERB
cana-2667	465	7	machine	machine	NOUN
cana-2667	465	8	learning	learn	VERB
cana-2667	465	9	classifiers	classifier	NOUN
cana-2667	465	10	and	and	CCONJ
cana-2667	465	11	multiple	multiple	ADJ
cana-2667	465	12	feature	feature	NOUN
cana-2667	465	13	extractors	extractor	NOUN
cana-2667	465	14	for	for	ADP
cana-2667	465	15	enhancing	enhance	VERB
cana-2667	465	16	diabetic	diabetic	ADJ
cana-2667	465	17	retinopathy	retinopathy	ADJ
cana-2667	465	18	detection	detection	NOUN
cana-2667	465	19	.	.	PUNCT
cana-2667	465	20	"	"	PUNCT
cana-2667	466	1	healthcare	healthcare	NOUN
cana-2667	466	2	analytics	analytic	NOUN
cana-2667	466	3	(	(	PUNCT
cana-2667	466	4	2024	2024	NUM
cana-2667	466	5	):	):	PUNCT
cana-2667	466	6	100346	100346	NUM
cana-2667	466	7	.	.	PUNCT
cana-2667	467	1	[	[	X
cana-2667	467	2	19	19	NUM
cana-2667	467	3	]	]	X
cana-2667	467	4	taifa	taifa	PROPN
cana-2667	467	5	,	,	PUNCT
cana-2667	467	6	intifa	intifa	PROPN
cana-2667	467	7	aman	aman	PROPN
cana-2667	467	8	,	,	PUNCT
cana-2667	467	9	et	et	PROPN
cana-2667	467	10	al	al	PROPN
cana-2667	467	11	.	.	PUNCT
cana-2667	467	12	"	"	PUNCT
cana-2667	467	13	enhancing	enhance	VERB
cana-2667	467	14	accuracy	accuracy	NOUN
cana-2667	467	15	of	of	ADP
cana-2667	467	16	diabetic	diabetic	ADJ
cana-2667	467	17	retinopathy	retinopathy	ADJ
cana-2667	467	18	detection	detection	NOUN
cana-2667	467	19	using	use	VERB
cana-2667	467	20	a	a	DET
cana-2667	467	21	hybrid	hybrid	ADJ
cana-2667	467	22	approach	approach	NOUN
cana-2667	467	23	with	with	ADP
cana-2667	467	24	the	the	DET
cana-2667	467	25	fusion	fusion	NOUN
cana-2667	467	26	of	of	ADP
cana-2667	467	27	inceptionv3	inceptionv3	NOUN
cana-2667	467	28	and	and	CCONJ
cana-2667	467	29	a	a	DET
cana-2667	467	30	stacking	stack	VERB
cana-2667	467	31	ensemble	ensemble	ADJ
cana-2667	467	32	learner	learner	NOUN
cana-2667	467	33	.	.	PUNCT
cana-2667	467	34	"	"	PUNCT
cana-2667	468	1	jagannath	jagannath	PROPN
cana-2667	468	2	university	university	PROPN
cana-2667	468	3	journal	journal	NOUN
cana-2667	468	4	of	of	ADP
cana-2667	468	5	science	science	PROPN
cana-2667	468	6	11.1	11.1	NUM
cana-2667	468	7	(	(	PUNCT
cana-2667	468	8	2024	2024	NUM
cana-2667	468	9	):	):	PUNCT
cana-2667	468	10	135	135	NUM
cana-2667	468	11	-	-	SYM
cana-2667	468	12	156	156	NUM
cana-2667	468	13	.	.	PUNCT
cana-2667	469	1	communications	communication	NOUN
cana-2667	469	2	on	on	ADP
cana-2667	469	3	applied	apply	VERB
cana-2667	469	4	nonlinear	nonlinear	ADJ
cana-2667	469	5	analysis	analysis	NOUN
cana-2667	469	6	issn	issn	NOUN
cana-2667	469	7	:	:	PUNCT
cana-2667	469	8	1074	1074	NUM
cana-2667	469	9	-	-	PUNCT
cana-2667	469	10	133x	133x	NUM
cana-2667	469	11	vol	vol	NOUN
cana-2667	469	12	32	32	NUM
cana-2667	469	13	no	no	NOUN
cana-2667	469	14	.	.	PUNCT
cana-2667	470	1	3s	3s	NUM
cana-2667	470	2	(	(	PUNCT
cana-2667	470	3	2025	2025	NUM
cana-2667	470	4	)	)	PUNCT
cana-2667	470	5	405	405	NUM
cana-2667	470	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2667	471	1	[	[	X
cana-2667	471	2	20	20	NUM
cana-2667	471	3	]	]	PUNCT
cana-2667	471	4	sharma	sharma	PROPN
cana-2667	471	5	,	,	PUNCT
cana-2667	471	6	santosh	santosh	PROPN
cana-2667	471	7	kumar	kumar	PROPN
cana-2667	471	8	,	,	PUNCT
cana-2667	471	9	et	et	PROPN
cana-2667	471	10	al	al	PROPN
cana-2667	471	11	.	.	PUNCT
cana-2667	472	1	"	"	PUNCT
cana-2667	472	2	discrete	discrete	ADJ
cana-2667	472	3	ripplet	ripplet	NOUN
cana-2667	472	4	-	-	PUNCT
cana-2667	472	5	ii	ii	NOUN
cana-2667	472	6	transform	transform	VERB
cana-2667	472	7	feature	feature	NOUN
cana-2667	472	8	extraction	extraction	NOUN
cana-2667	472	9	and	and	CCONJ
cana-2667	472	10	metaheuristic	metaheuristic	ADV
cana-2667	472	11	-	-	PUNCT
cana-2667	472	12	optimized	optimize	VERB
cana-2667	472	13	feature	feature	NOUN
cana-2667	472	14	selection	selection	NOUN
cana-2667	472	15	for	for	ADP
cana-2667	472	16	enhanced	enhanced	ADJ
cana-2667	472	17	glaucoma	glaucoma	NOUN
cana-2667	472	18	detection	detection	NOUN
cana-2667	472	19	in	in	ADP
cana-2667	472	20	fundus	fundus	NOUN
cana-2667	472	21	images	image	NOUN
cana-2667	472	22	using	use	VERB
cana-2667	472	23	least	least	ADJ
cana-2667	472	24	square	square	ADJ
cana-2667	472	25	-	-	PUNCT
cana-2667	472	26	support	support	NOUN
cana-2667	472	27	vector	vector	NOUN
cana-2667	472	28	machine	machine	NOUN
cana-2667	472	29	.	.	PUNCT
cana-2667	472	30	"	"	PUNCT
cana-2667	473	1	multimedia	multimedia	NOUN
cana-2667	473	2	tools	tool	NOUN
cana-2667	473	3	and	and	CCONJ
cana-2667	473	4	applications	application	NOUN
cana-2667	473	5	(	(	PUNCT
cana-2667	473	6	2024	2024	NUM
cana-2667	473	7	):	):	PUNCT
cana-2667	473	8	1	1	NUM
cana-2667	473	9	-	-	SYM
cana-2667	473	10	33	33	NUM
cana-2667	473	11	.	.	PUNCT
cana-2667	474	1	[	[	X
cana-2667	474	2	21	21	NUM
cana-2667	474	3	]	]	PUNCT
cana-2667	474	4	alhajim	alhajim	NOUN
cana-2667	474	5	,	,	PUNCT
cana-2667	474	6	dhafer	dhafer	NOUN
cana-2667	474	7	,	,	PUNCT
cana-2667	474	8	ahmed	ahmed	PROPN
cana-2667	474	9	al	al	PROPN
cana-2667	474	10	-	-	PUNCT
cana-2667	474	11	shammar	shammar	PROPN
cana-2667	474	12	,	,	PUNCT
cana-2667	474	13	and	and	CCONJ
cana-2667	474	14	ahmed	ahmed	PROPN
cana-2667	474	15	kareem	kareem	PROPN
cana-2667	474	16	oleiwi	oleiwi	PROPN
cana-2667	474	17	.	.	PUNCT
cana-2667	475	1	"	"	PUNCT
cana-2667	475	2	application	application	NOUN
cana-2667	475	3	of	of	ADP
cana-2667	475	4	optimized	optimize	VERB
cana-2667	475	5	deep	deep	ADJ
cana-2667	475	6	learning	learning	NOUN
cana-2667	475	7	mechanism	mechanism	NOUN
cana-2667	475	8	for	for	ADP
cana-2667	475	9	recognition	recognition	NOUN
cana-2667	475	10	and	and	CCONJ
cana-2667	475	11	categorization	categorization	NOUN
cana-2667	475	12	of	of	ADP
cana-2667	475	13	retinal	retinal	ADJ
cana-2667	475	14	diseases	disease	NOUN
cana-2667	475	15	.	.	PUNCT
cana-2667	475	16	"	"	PUNCT
cana-2667	476	1	international	international	ADJ
cana-2667	476	2	journal	journal	NOUN
cana-2667	476	3	of	of	ADP
cana-2667	476	4	computing	computing	NOUN
cana-2667	476	5	and	and	CCONJ
cana-2667	476	6	digital	digital	ADJ
cana-2667	476	7	systems	system	NOUN
cana-2667	476	8	16.1	16.1	NUM
cana-2667	476	9	(	(	PUNCT
cana-2667	476	10	2024	2024	NUM
cana-2667	476	11	):	):	PUNCT
cana-2667	476	12	935	935	NUM
cana-2667	476	13	-	-	SYM
cana-2667	476	14	950	950	NUM
cana-2667	476	15	.	.	PUNCT
cana-2667	477	1	[	[	X
cana-2667	477	2	22	22	NUM
cana-2667	477	3	]	]	X
cana-2667	477	4	canqui	canqui	NOUN
cana-2667	477	5	-	-	PUNCT
cana-2667	477	6	flores	flore	NOUN
cana-2667	477	7	,	,	PUNCT
cana-2667	477	8	bernabe	bernabe	INTJ
cana-2667	477	9	,	,	PUNCT
cana-2667	477	10	et	et	PROPN
cana-2667	477	11	al	al	PROPN
cana-2667	477	12	.	.	PUNCT
cana-2667	478	1	"	"	PUNCT
cana-2667	478	2	echocardiographic	echocardiographic	ADJ
cana-2667	478	3	cardiac	cardiac	ADJ
cana-2667	478	4	views	view	NOUN
cana-2667	478	5	classification	classification	NOUN
cana-2667	478	6	using	use	VERB
cana-2667	478	7	whale	whale	NOUN
cana-2667	478	8	optimization	optimization	NOUN
cana-2667	478	9	and	and	CCONJ
cana-2667	478	10	weighted	weight	VERB
cana-2667	478	11	support	support	NOUN
cana-2667	478	12	vector	vector	NOUN
cana-2667	478	13	machine	machine	NOUN
cana-2667	478	14	.	.	PUNCT
cana-2667	478	15	"	"	PUNCT
cana-2667	479	1	vessel	vessel	NOUN
cana-2667	479	2	plus	plus	CCONJ
cana-2667	479	3	8	8	NUM
cana-2667	479	4	(	(	PUNCT
cana-2667	479	5	2024	2024	NUM
cana-2667	479	6	):	):	PUNCT
cana-2667	479	7	n	n	CCONJ
cana-2667	479	8	-	-	PUNCT
cana-2667	479	9	a.	a.	NOUN
cana-2667	480	1	[	[	X
cana-2667	480	2	23	23	NUM
cana-2667	480	3	]	]	X
cana-2667	480	4	desuky	desuky	PROPN
cana-2667	480	5	,	,	PUNCT
cana-2667	480	6	abeer	abeer	PROPN
cana-2667	480	7	s.	s.	PROPN
cana-2667	480	8	,	,	PUNCT
cana-2667	480	9	et	et	PROPN
cana-2667	480	10	al	al	PROPN
cana-2667	480	11	.	.	PUNCT
cana-2667	481	1	"	"	PUNCT
cana-2667	481	2	parameter	parameter	NOUN
cana-2667	481	3	optimization	optimization	NOUN
cana-2667	481	4	based	base	VERB
cana-2667	481	5	mud	mud	NOUN
cana-2667	481	6	ring	ring	NOUN
cana-2667	481	7	algorithm	algorithm	NOUN
cana-2667	481	8	for	for	ADP
cana-2667	481	9	improving	improve	VERB
cana-2667	481	10	the	the	DET
cana-2667	481	11	maternal	maternal	ADJ
cana-2667	481	12	health	health	NOUN
cana-2667	481	13	risk	risk	NOUN
cana-2667	481	14	prediction	prediction	NOUN
cana-2667	481	15	.	.	PUNCT
cana-2667	481	16	"	"	PUNCT
cana-2667	482	1	ieee	ieee	NOUN
cana-2667	482	2	access	access	NOUN
cana-2667	482	3	(	(	PUNCT
cana-2667	482	4	2024	2024	NUM
cana-2667	482	5	)	)	PUNCT
cana-2667	482	6	.	.	PUNCT
cana-2667	483	1	[	[	X
cana-2667	483	2	24	24	NUM
cana-2667	483	3	]	]	PUNCT
cana-2667	483	4	bose	bose	NOUN
cana-2667	483	5	,	,	PUNCT
cana-2667	483	6	anandh	anandh	PROPN
cana-2667	483	7	sam	sam	PROPN
cana-2667	483	8	chandra	chandra	PROPN
cana-2667	483	9	,	,	PUNCT
cana-2667	483	10	c.	c.	PROPN
cana-2667	483	11	srinivasan	srinivasan	PROPN
cana-2667	483	12	,	,	PUNCT
cana-2667	483	13	and	and	CCONJ
cana-2667	483	14	s.	s.	PROPN
cana-2667	483	15	immaculate	immaculate	PROPN
cana-2667	483	16	joy	joy	PROPN
cana-2667	483	17	.	.	PUNCT
cana-2667	484	1	"	"	PUNCT
cana-2667	484	2	optimized	optimize	VERB
cana-2667	484	3	feature	feature	NOUN
cana-2667	484	4	selection	selection	NOUN
cana-2667	484	5	for	for	ADP
cana-2667	484	6	enhanced	enhanced	ADJ
cana-2667	484	7	accuracy	accuracy	NOUN
cana-2667	484	8	in	in	ADP
cana-2667	484	9	knee	knee	NOUN
cana-2667	484	10	osteoarthritis	osteoarthritis	NOUN
cana-2667	484	11	detection	detection	NOUN
cana-2667	484	12	and	and	CCONJ
cana-2667	484	13	severity	severity	NOUN
cana-2667	484	14	classification	classification	NOUN
cana-2667	484	15	with	with	ADP
cana-2667	484	16	machine	machine	NOUN
cana-2667	484	17	learning	learning	NOUN
cana-2667	484	18	.	.	PUNCT
cana-2667	484	19	"	"	PUNCT
cana-2667	484	20	biomedical	biomedical	ADJ
cana-2667	484	21	signal	signal	NOUN
cana-2667	484	22	processing	processing	NOUN
cana-2667	484	23	and	and	CCONJ
cana-2667	484	24	control	control	NOUN
cana-2667	484	25	97	97	NUM
cana-2667	484	26	(	(	PUNCT
cana-2667	484	27	2024	2024	NUM
cana-2667	484	28	):	):	PUNCT
cana-2667	484	29	106670	106670	NUM
cana-2667	484	30	.	.	PUNCT
cana-2667	485	1	[	[	X
cana-2667	485	2	25	25	NUM
cana-2667	485	3	]	]	X
cana-2667	485	4	sahu	sahu	PROPN
cana-2667	485	5	,	,	PUNCT
cana-2667	485	6	sima	sima	PROPN
cana-2667	485	7	,	,	PUNCT
cana-2667	485	8	amit	amit	PROPN
cana-2667	485	9	kumar	kumar	PROPN
cana-2667	485	10	singh	singh	PROPN
cana-2667	485	11	,	,	PUNCT
cana-2667	485	12	and	and	CCONJ
cana-2667	485	13	nishita	nishita	PROPN
cana-2667	485	14	priyadarshini	priyadarshini	PROPN
cana-2667	485	15	.	.	PUNCT
cana-2667	486	1	"	"	PUNCT
cana-2667	486	2	no	no	DET
cana-2667	486	3	reference	reference	NOUN
cana-2667	486	4	retinal	retinal	ADJ
cana-2667	486	5	image	image	NOUN
cana-2667	486	6	quality	quality	NOUN
cana-2667	486	7	assessment	assessment	NOUN
cana-2667	486	8	using	use	VERB
cana-2667	486	9	support	support	NOUN
cana-2667	486	10	vector	vector	NOUN
cana-2667	486	11	machine	machine	NOUN
cana-2667	486	12	classifier	classifier	NOUN
cana-2667	486	13	in	in	ADP
cana-2667	486	14	wavelet	wavelet	NOUN
cana-2667	486	15	domain	domain	NOUN
cana-2667	486	16	.	.	PUNCT
cana-2667	486	17	"	"	PUNCT
cana-2667	486	18	multimedia	multimedia	NOUN
cana-2667	486	19	tools	tool	NOUN
cana-2667	486	20	and	and	CCONJ
cana-2667	486	21	applications	application	NOUN
cana-2667	486	22	(	(	PUNCT
cana-2667	486	23	2024	2024	NUM
cana-2667	486	24	):	):	PUNCT
cana-2667	486	25	1	1	NUM
cana-2667	486	26	-	-	SYM
cana-2667	486	27	20	20	NUM
cana-2667	486	28	.	.	PUNCT