id	sid	tid	token	lemma	pos
cana-5596	1	1	communications	communication	NOUN
cana-5596	1	2	on	on	ADP
cana-5596	1	3	applied	apply	VERB
cana-5596	1	4	nonlinear	nonlinear	ADJ
cana-5596	1	5	analysis	analysis	NOUN
cana-5596	1	6	issn	issn	NOUN
cana-5596	1	7	:	:	PUNCT
cana-5596	1	8	1074	1074	NUM
cana-5596	1	9	-	-	PUNCT
cana-5596	1	10	133x	133x	NUM
cana-5596	1	11	vol	vol	NOUN
cana-5596	1	12	32	32	NUM
cana-5596	1	13	no	no	NOUN
cana-5596	1	14	.	.	PUNCT
cana-5596	2	1	icmasd	icmasd	NOUN
cana-5596	2	2	(	(	PUNCT
cana-5596	2	3	2025	2025	NUM
cana-5596	2	4	)	)	PUNCT
cana-5596	2	5	1963	1963	NUM
cana-5596	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	2	7	comprehensive	comprehensive	ADJ
cana-5596	2	8	cancer	cancer	NOUN
cana-5596	2	9	analysis	analysis	NOUN
cana-5596	2	10	:	:	PUNCT
cana-5596	2	11	cnn	cnn	PROPN
cana-5596	2	12	-	-	PUNCT
cana-5596	2	13	based	base	VERB
cana-5596	2	14	classification	classification	NOUN
cana-5596	2	15	of	of	ADP
cana-5596	2	16	malignant	malignant	ADJ
cana-5596	2	17	vs.	vs.	ADP
cana-5596	2	18	benign	benign	ADJ
cana-5596	2	19	tumors	tumor	NOUN
cana-5596	2	20	with	with	ADP
cana-5596	2	21	staging	stage	VERB
cana-5596	2	22	insights	insight	NOUN
cana-5596	2	23	gauri	gauri	PROPN
cana-5596	2	24	sharma1	sharma1	PROPN
cana-5596	2	25	,	,	PUNCT
cana-5596	2	26	dr	dr	PROPN
cana-5596	2	27	.	.	PROPN
cana-5596	2	28	upasana	upasana	PROPN
cana-5596	2	29	lakhina2	lakhina2	PROPN
cana-5596	2	30	,	,	PUNCT
cana-5596	2	31	dr	dr	PROPN
cana-5596	2	32	.	.	PROPN
cana-5596	2	33	anju	anju	PROPN
cana-5596	2	34	gandhi3	gandhi3	PROPN
cana-5596	2	35	,	,	PUNCT
cana-5596	2	36	dr	dr	PROPN
cana-5596	2	37	.	.	PROPN
cana-5596	2	38	stuti	stuti	PROPN
cana-5596	2	39	mehla4	mehla4	PROPN
cana-5596	2	40	,	,	PUNCT
cana-5596	2	41	dr	dr	PROPN
cana-5596	2	42	.	.	PROPN
cana-5596	2	43	sunil	sunil	PROPN
cana-5596	2	44	dhull5	dhull5	PROPN
cana-5596	3	1	1computer	1computer	NUM
cana-5596	3	2	science	science	NOUN
cana-5596	3	3	and	and	CCONJ
cana-5596	3	4	engineering	engineering	NOUN
cana-5596	3	5	,	,	PUNCT
cana-5596	3	6	piet	piet	PROPN
cana-5596	3	7	,	,	PUNCT
cana-5596	3	8	india	india	PROPN
cana-5596	3	9	2computer	2computer	NUM
cana-5596	3	10	science	science	NOUN
cana-5596	3	11	and	and	CCONJ
cana-5596	3	12	engineering	engineering	NOUN
cana-5596	3	13	,	,	PUNCT
cana-5596	3	14	piet	piet	PROPN
cana-5596	3	15	,	,	PUNCT
cana-5596	3	16	india	india	PROPN
cana-5596	3	17	3computer	3computer	NUM
cana-5596	3	18	science	science	NOUN
cana-5596	3	19	and	and	CCONJ
cana-5596	3	20	engineering	engineering	NOUN
cana-5596	3	21	,	,	PUNCT
cana-5596	3	22	piet	piet	PROPN
cana-5596	3	23	,	,	PUNCT
cana-5596	3	24	india	india	PROPN
cana-5596	3	25	4computer	4computer	NUM
cana-5596	3	26	science	science	NOUN
cana-5596	3	27	and	and	CCONJ
cana-5596	3	28	engineering	engineering	NOUN
cana-5596	3	29	,	,	PUNCT
cana-5596	3	30	piet	piet	PROPN
cana-5596	3	31	,	,	PUNCT
cana-5596	3	32	india	india	PROPN
cana-5596	3	33	5mechanical	5mechanical	NUM
cana-5596	3	34	engineering	engineering	NOUN
cana-5596	3	35	,	,	PUNCT
cana-5596	3	36	piet	piet	PROPN
cana-5596	3	37	,	,	PUNCT
cana-5596	3	38	india	india	PROPN
cana-5596	3	39	corresponding	corresponding	PROPN
cana-5596	3	40	author	author	PROPN
cana-5596	3	41	’s	’s	PART
cana-5596	3	42	email	email	NOUN
cana-5596	3	43	address	address	NOUN
cana-5596	3	44	:	:	PUNCT
cana-5596	3	45	iamgaurisharma06@gmail.com	iamgaurisharma06@gmail.com	X
cana-5596	3	46	,	,	PUNCT
cana-5596	3	47	drupasana.cse@piet.co.in	drupasana.cse@piet.co.in	PROPN
cana-5596	3	48	,	,	PUNCT
cana-5596	3	49	anjugandhi.cse@piet.co.in	anjugandhi.cse@piet.co.in	ADV
cana-5596	3	50	,	,	PUNCT
cana-5596	3	51	stutimehla.cse@piet.co.in	stutimehla.cse@piet.co.in	PROPN
cana-5596	3	52	,	,	PUNCT
cana-5596	3	53	sunildhull.mech@piet.co.in	sunildhull.mech@piet.co.in	NUM
cana-5596	3	54	article	article	NOUN
cana-5596	3	55	history	history	NOUN
cana-5596	3	56	:	:	PUNCT
cana-5596	3	57	received	receive	VERB
cana-5596	3	58	:	:	PUNCT
cana-5596	3	59	12	12	NUM
cana-5596	3	60	-	-	SYM
cana-5596	3	61	12	12	NUM
cana-5596	3	62	-	-	PUNCT
cana-5596	3	63	2024	2024	NUM
cana-5596	3	64	revised	revise	VERB
cana-5596	3	65	:	:	PUNCT
cana-5596	3	66	25	25	NUM
cana-5596	3	67	-	-	PUNCT
cana-5596	3	68	01	01	NUM
cana-5596	3	69	-	-	PUNCT
cana-5596	3	70	2025	2025	NUM
cana-5596	3	71	accepted	accept	VERB
cana-5596	3	72	:	:	PUNCT
cana-5596	3	73	05	05	NUM
cana-5596	3	74	-	-	PUNCT
cana-5596	3	75	02	02	NUM
cana-5596	3	76	-	-	PUNCT
cana-5596	3	77	2025	2025	NUM
cana-5596	3	78	abstract	abstract	NOUN
cana-5596	3	79	:	:	PUNCT
cana-5596	3	80	the	the	DET
cana-5596	3	81	scope	scope	NOUN
cana-5596	3	82	of	of	ADP
cana-5596	3	83	this	this	DET
cana-5596	3	84	study	study	NOUN
cana-5596	3	85	is	be	AUX
cana-5596	3	86	to	to	PART
cana-5596	3	87	build	build	VERB
cana-5596	3	88	an	an	DET
cana-5596	3	89	advanced	advanced	ADJ
cana-5596	3	90	artificial	artificial	ADJ
cana-5596	3	91	intelligence	intelligence	NOUN
cana-5596	3	92	system	system	NOUN
cana-5596	3	93	which	which	PRON
cana-5596	3	94	uses	use	VERB
cana-5596	3	95	convolutional	convolutional	ADJ
cana-5596	3	96	neural	neural	ADJ
cana-5596	3	97	networks	network	NOUN
cana-5596	3	98	(	(	PUNCT
cana-5596	3	99	cnns	cnns	PROPN
cana-5596	3	100	)	)	PUNCT
cana-5596	3	101	to	to	PART
cana-5596	3	102	identify	identify	VERB
cana-5596	3	103	and	and	CCONJ
cana-5596	3	104	categorize	categorize	VERB
cana-5596	3	105	tumors	tumor	NOUN
cana-5596	3	106	as	as	ADP
cana-5596	3	107	benign	benign	ADJ
cana-5596	3	108	or	or	CCONJ
cana-5596	3	109	malignant	malignant	ADJ
cana-5596	3	110	and	and	CCONJ
cana-5596	3	111	to	to	PART
cana-5596	3	112	predict	predict	VERB
cana-5596	3	113	the	the	DET
cana-5596	3	114	cancer	cancer	NOUN
cana-5596	3	115	stage	stage	NOUN
cana-5596	3	116	for	for	ADP
cana-5596	3	117	early	early	ADJ
cana-5596	3	118	diagnosis	diagnosis	NOUN
cana-5596	3	119	.	.	PUNCT
cana-5596	4	1	the	the	DET
cana-5596	4	2	suggested	suggest	VERB
cana-5596	4	3	model	model	NOUN
cana-5596	4	4	will	will	AUX
cana-5596	4	5	provide	provide	VERB
cana-5596	4	6	precise	precise	ADJ
cana-5596	4	7	and	and	CCONJ
cana-5596	4	8	trustworthy	trustworthy	ADJ
cana-5596	4	9	diagnostic	diagnostic	ADJ
cana-5596	4	10	outputs	output	NOUN
cana-5596	4	11	by	by	ADP
cana-5596	4	12	utilizing	utilize	VERB
cana-5596	4	13	a	a	DET
cana-5596	4	14	labeled	label	VERB
cana-5596	4	15	medical	medical	ADJ
cana-5596	4	16	image	image	NOUN
cana-5596	4	17	dataset	dataset	NOUN
cana-5596	4	18	,	,	PUNCT
cana-5596	4	19	enabling	enable	VERB
cana-5596	4	20	prompt	prompt	ADJ
cana-5596	4	21	cancer	cancer	NOUN
cana-5596	4	22	detection	detection	NOUN
cana-5596	4	23	by	by	ADP
cana-5596	4	24	medical	medical	ADJ
cana-5596	4	25	professionals	professional	NOUN
cana-5596	4	26	.	.	PUNCT
cana-5596	5	1	through	through	ADP
cana-5596	5	2	offering	offer	VERB
cana-5596	5	3	a	a	DET
cana-5596	5	4	user	user	NOUN
cana-5596	5	5	-	-	PUNCT
cana-5596	5	6	friendly	friendly	ADJ
cana-5596	5	7	interface	interface	NOUN
cana-5596	5	8	which	which	PRON
cana-5596	5	9	enables	enable	VERB
cana-5596	5	10	real	real	ADJ
cana-5596	5	11	-	-	PUNCT
cana-5596	5	12	time	time	NOUN
cana-5596	5	13	analysis	analysis	NOUN
cana-5596	5	14	and	and	CCONJ
cana-5596	5	15	seamless	seamless	ADJ
cana-5596	5	16	integration	integration	NOUN
cana-5596	5	17	with	with	ADP
cana-5596	5	18	electronic	electronic	ADJ
cana-5596	5	19	health	health	NOUN
cana-5596	5	20	records	record	NOUN
cana-5596	5	21	(	(	PUNCT
cana-5596	5	22	ehrs	ehrs	PROPN
cana-5596	5	23	)	)	PUNCT
cana-5596	5	24	,	,	PUNCT
cana-5596	5	25	this	this	DET
cana-5596	5	26	initiative	initiative	NOUN
cana-5596	5	27	aims	aim	VERB
cana-5596	5	28	to	to	PART
cana-5596	5	29	improve	improve	VERB
cana-5596	5	30	treatment	treatment	NOUN
cana-5596	5	31	outcomes	outcome	NOUN
cana-5596	5	32	and	and	CCONJ
cana-5596	5	33	reduce	reduce	VERB
cana-5596	5	34	diagnostic	diagnostic	ADJ
cana-5596	5	35	errors	error	NOUN
cana-5596	5	36	.	.	PUNCT
cana-5596	6	1	to	to	PART
cana-5596	6	2	enhance	enhance	VERB
cana-5596	6	3	the	the	DET
cana-5596	6	4	solution	solution	NOUN
cana-5596	6	5	's	's	PART
cana-5596	6	6	potential	potential	ADJ
cana-5596	6	7	application	application	NOUN
cana-5596	6	8	,	,	PUNCT
cana-5596	6	9	the	the	DET
cana-5596	6	10	project	project	NOUN
cana-5596	6	11	also	also	ADV
cana-5596	6	12	explores	explore	VERB
cana-5596	6	13	3d	3d	PROPN
cana-5596	6	14	tumor	tumor	PROPN
cana-5596	6	15	modeling	modeling	NOUN
cana-5596	6	16	,	,	PUNCT
cana-5596	6	17	predictive	predictive	ADJ
cana-5596	6	18	analytics	analytic	NOUN
cana-5596	6	19	,	,	PUNCT
cana-5596	6	20	and	and	CCONJ
cana-5596	6	21	multi	multi	ADJ
cana-5596	6	22	-	-	ADJ
cana-5596	6	23	cancer	cancer	ADJ
cana-5596	6	24	detection	detection	NOUN
cana-5596	6	25	capabilities	capability	NOUN
cana-5596	6	26	.	.	PUNCT
cana-5596	7	1	by	by	ADP
cana-5596	7	2	resolving	resolve	VERB
cana-5596	7	3	crucial	crucial	ADJ
cana-5596	7	4	issues	issue	NOUN
cana-5596	7	5	like	like	ADP
cana-5596	7	6	data	datum	NOUN
cana-5596	7	7	accessibility	accessibility	NOUN
cana-5596	7	8	,	,	PUNCT
cana-5596	7	9	algorithm	algorithm	NOUN
cana-5596	7	10	sensitivity	sensitivity	NOUN
cana-5596	7	11	,	,	PUNCT
cana-5596	7	12	and	and	CCONJ
cana-5596	7	13	clinical	clinical	ADJ
cana-5596	7	14	workflow	workflow	NOUN
cana-5596	7	15	integration	integration	NOUN
cana-5596	7	16	,	,	PUNCT
cana-5596	7	17	this	this	DET
cana-5596	7	18	creative	creative	ADJ
cana-5596	7	19	strategy	strategy	NOUN
cana-5596	7	20	seeks	seek	VERB
cana-5596	7	21	to	to	PART
cana-5596	7	22	revolutionize	revolutionize	VERB
cana-5596	7	23	diagnostic	diagnostic	ADJ
cana-5596	7	24	tools	tool	NOUN
cana-5596	7	25	for	for	ADP
cana-5596	7	26	patients	patient	NOUN
cana-5596	7	27	,	,	PUNCT
cana-5596	7	28	researchers	researcher	NOUN
cana-5596	7	29	,	,	PUNCT
cana-5596	7	30	and	and	CCONJ
cana-5596	7	31	healthcare	healthcare	NOUN
cana-5596	7	32	professionals	professional	NOUN
cana-5596	7	33	.	.	PUNCT
cana-5596	8	1	our	our	PRON
cana-5596	8	2	ultimate	ultimate	ADJ
cana-5596	8	3	objective	objective	NOUN
cana-5596	8	4	is	be	AUX
cana-5596	8	5	to	to	PART
cana-5596	8	6	equip	equip	VERB
cana-5596	8	7	medical	medical	ADJ
cana-5596	8	8	professionals	professional	NOUN
cana-5596	8	9	with	with	ADP
cana-5596	8	10	state	state	NOUN
cana-5596	8	11	-	-	PUNCT
cana-5596	8	12	of	of	ADP
cana-5596	8	13	-	-	PUNCT
cana-5596	8	14	the	the	DET
cana-5596	8	15	-	-	PUNCT
cana-5596	8	16	art	art	NOUN
cana-5596	8	17	tools	tool	NOUN
cana-5596	8	18	that	that	PRON
cana-5596	8	19	improve	improve	VERB
cana-5596	8	20	cancer	cancer	NOUN
cana-5596	8	21	detection	detection	NOUN
cana-5596	8	22	,	,	PUNCT
cana-5596	8	23	forecast	forecast	NOUN
cana-5596	8	24	cancer	cancer	NOUN
cana-5596	8	25	stages	stage	NOUN
cana-5596	8	26	,	,	PUNCT
cana-5596	8	27	and	and	CCONJ
cana-5596	8	28	enhance	enhance	VERB
cana-5596	8	29	patient	patient	ADJ
cana-5596	8	30	care	care	NOUN
cana-5596	8	31	in	in	ADP
cana-5596	8	32	general	general	ADJ
cana-5596	8	33	.	.	PUNCT
cana-5596	9	1	keywords	keyword	NOUN
cana-5596	9	2	:	:	PUNCT
cana-5596	9	3	cnn	cnn	PROPN
cana-5596	9	4	-	-	PUNCT
cana-5596	9	5	based	base	VERB
cana-5596	9	6	tumor	tumor	NOUN
cana-5596	9	7	classification	classification	NOUN
cana-5596	9	8	,	,	PUNCT
cana-5596	9	9	malignant	malignant	ADJ
cana-5596	9	10	vs.	vs.	ADP
cana-5596	9	11	benign	benign	ADJ
cana-5596	9	12	tumor	tumor	NOUN
cana-5596	9	13	analysis	analysis	NOUN
cana-5596	9	14	,	,	PUNCT
cana-5596	9	15	cancer	cancer	NOUN
cana-5596	9	16	staging	staging	NOUN
cana-5596	9	17	with	with	ADP
cana-5596	9	18	ai	ai	PROPN
cana-5596	9	19	,	,	PUNCT
cana-5596	9	20	medical	medical	ADJ
cana-5596	9	21	image	image	NOUN
cana-5596	9	22	processing	processing	NOUN
cana-5596	9	23	,	,	PUNCT
cana-5596	9	24	3d	3d	NUM
cana-5596	9	25	tumor	tumor	NOUN
cana-5596	9	26	modeling	modeling	NOUN
cana-5596	9	27	,	,	PUNCT
cana-5596	9	28	ai	ai	ADJ
cana-5596	9	29	-	-	PUNCT
cana-5596	9	30	driven	drive	VERB
cana-5596	9	31	cancer	cancer	NOUN
cana-5596	9	32	diagnosis	diagnosis	NOUN
cana-5596	9	33	1	1	NUM
cana-5596	9	34	.	.	PUNCT
cana-5596	10	1	introduction	introduction	NOUN
cana-5596	10	2	:	:	PUNCT
cana-5596	10	3	cancer	cancer	NOUN
cana-5596	10	4	detection	detection	NOUN
cana-5596	10	5	and	and	CCONJ
cana-5596	10	6	diagnosis	diagnosis	NOUN
cana-5596	10	7	remain	remain	VERB
cana-5596	10	8	critical	critical	ADJ
cana-5596	10	9	challenges	challenge	NOUN
cana-5596	10	10	in	in	ADP
cana-5596	10	11	modern	modern	ADJ
cana-5596	10	12	healthcare	healthcare	NOUN
cana-5596	10	13	,	,	PUNCT
cana-5596	10	14	with	with	ADP
cana-5596	10	15	timely	timely	ADJ
cana-5596	10	16	and	and	CCONJ
cana-5596	10	17	accurate	accurate	ADJ
cana-5596	10	18	identification	identification	NOUN
cana-5596	10	19	being	be	AUX
cana-5596	10	20	essential	essential	ADJ
cana-5596	10	21	for	for	ADP
cana-5596	10	22	effective	effective	ADJ
cana-5596	10	23	treatment	treatment	NOUN
cana-5596	10	24	.	.	PUNCT
cana-5596	11	1	early	early	ADJ
cana-5596	11	2	detection	detection	NOUN
cana-5596	11	3	of	of	ADP
cana-5596	11	4	malignant	malignant	ADJ
cana-5596	11	5	tumors	tumor	NOUN
cana-5596	11	6	significantly	significantly	ADV
cana-5596	11	7	increases	increase	VERB
cana-5596	11	8	survival	survival	NOUN
cana-5596	11	9	rates	rate	NOUN
cana-5596	11	10	,	,	PUNCT
cana-5596	11	11	emphasizing	emphasize	VERB
cana-5596	11	12	the	the	DET
cana-5596	11	13	need	need	NOUN
cana-5596	11	14	for	for	ADP
cana-5596	11	15	reliable	reliable	ADJ
cana-5596	11	16	and	and	CCONJ
cana-5596	11	17	efficient	efficient	ADJ
cana-5596	11	18	diagnostic	diagnostic	ADJ
cana-5596	11	19	methods	method	NOUN
cana-5596	11	20	.	.	PUNCT
cana-5596	12	1	conventional	conventional	ADJ
cana-5596	12	2	diagnostic	diagnostic	ADJ
cana-5596	12	3	techniques	technique	NOUN
cana-5596	12	4	often	often	ADV
cana-5596	12	5	rely	rely	VERB
cana-5596	12	6	on	on	ADP
cana-5596	12	7	manual	manual	ADJ
cana-5596	12	8	examination	examination	NOUN
cana-5596	12	9	of	of	ADP
cana-5596	12	10	scanned	scan	VERB
cana-5596	12	11	images	image	NOUN
cana-5596	12	12	mailto:iamgaurisharma06@gmail.com	mailto:iamgaurisharma06@gmail.com	X
cana-5596	12	13	mailto:drupasana.cse@piet.co.in	mailto:drupasana.cse@piet.co.in	PROPN
cana-5596	12	14	mailto:anjugandhi.cse@piet.co.in	mailto:anjugandhi.cse@piet.co.in	PROPN
cana-5596	12	15	mailto:stutimehla.cse@piet.co.in	mailto:stutimehla.cse@piet.co.in	PROPN
cana-5596	12	16	mailto:sunildhull.mech@piet.co.in	mailto:sunildhull.mech@piet.co.in	PROPN
cana-5596	12	17	communications	communication	NOUN
cana-5596	12	18	on	on	ADP
cana-5596	12	19	applied	apply	VERB
cana-5596	12	20	nonlinear	nonlinear	ADJ
cana-5596	12	21	analysis	analysis	NOUN
cana-5596	12	22	issn	issn	NOUN
cana-5596	12	23	:	:	PUNCT
cana-5596	12	24	1074	1074	NUM
cana-5596	12	25	-	-	PUNCT
cana-5596	12	26	133x	133x	NUM
cana-5596	12	27	vol	vol	NOUN
cana-5596	12	28	32	32	NUM
cana-5596	12	29	no	no	NOUN
cana-5596	12	30	.	.	PUNCT
cana-5596	13	1	icmasd	icmasd	NOUN
cana-5596	13	2	(	(	PUNCT
cana-5596	13	3	2025	2025	NUM
cana-5596	13	4	)	)	PUNCT
cana-5596	13	5	1964	1964	NUM
cana-5596	13	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	13	7	by	by	ADP
cana-5596	13	8	experts	expert	NOUN
cana-5596	13	9	,	,	PUNCT
cana-5596	13	10	a	a	DET
cana-5596	13	11	process	process	NOUN
cana-5596	13	12	that	that	PRON
cana-5596	13	13	is	be	AUX
cana-5596	13	14	not	not	PART
cana-5596	13	15	only	only	ADV
cana-5596	13	16	time	time	NOUN
cana-5596	13	17	-	-	PUNCT
cana-5596	13	18	consuming	consume	VERB
cana-5596	13	19	but	but	CCONJ
cana-5596	13	20	also	also	ADV
cana-5596	13	21	susceptible	susceptible	ADJ
cana-5596	13	22	to	to	ADP
cana-5596	13	23	human	human	ADJ
cana-5596	13	24	error	error	NOUN
cana-5596	13	25	.	.	PUNCT
cana-5596	14	1	to	to	PART
cana-5596	14	2	address	address	VERB
cana-5596	14	3	these	these	DET
cana-5596	14	4	challenges	challenge	NOUN
cana-5596	14	5	,	,	PUNCT
cana-5596	14	6	advanced	advanced	ADJ
cana-5596	14	7	machine	machine	NOUN
cana-5596	14	8	learning	learn	VERB
cana-5596	14	9	approaches	approach	NOUN
cana-5596	14	10	,	,	PUNCT
cana-5596	14	11	particularly	particularly	ADV
cana-5596	14	12	convolutional	convolutional	ADJ
cana-5596	14	13	neural	neural	ADJ
cana-5596	14	14	networks	network	NOUN
cana-5596	14	15	(	(	PUNCT
cana-5596	14	16	cnns	cnns	PROPN
cana-5596	14	17	)	)	PUNCT
cana-5596	14	18	,	,	PUNCT
cana-5596	14	19	have	have	AUX
cana-5596	14	20	shown	show	VERB
cana-5596	14	21	remarkable	remarkable	ADJ
cana-5596	14	22	promise	promise	NOUN
cana-5596	14	23	in	in	ADP
cana-5596	14	24	automating	automate	VERB
cana-5596	14	25	and	and	CCONJ
cana-5596	14	26	enhancing	enhance	VERB
cana-5596	14	27	the	the	DET
cana-5596	14	28	diagnostic	diagnostic	ADJ
cana-5596	14	29	process	process	NOUN
cana-5596	14	30	.	.	PUNCT
cana-5596	15	1	cnns	cnns	PROPN
cana-5596	15	2	are	be	AUX
cana-5596	15	3	a	a	DET
cana-5596	15	4	class	class	NOUN
cana-5596	15	5	of	of	ADP
cana-5596	15	6	deep	deep	ADJ
cana-5596	15	7	learning	learning	NOUN
cana-5596	15	8	algorithms	algorithm	NOUN
cana-5596	15	9	specifically	specifically	ADV
cana-5596	15	10	designed	design	VERB
cana-5596	15	11	for	for	ADP
cana-5596	15	12	image	image	NOUN
cana-5596	15	13	recognition	recognition	NOUN
cana-5596	15	14	and	and	CCONJ
cana-5596	15	15	analysis	analysis	NOUN
cana-5596	15	16	,	,	PUNCT
cana-5596	15	17	making	make	VERB
cana-5596	15	18	them	they	PRON
cana-5596	15	19	ideal	ideal	ADJ
cana-5596	15	20	for	for	ADP
cana-5596	15	21	medical	medical	ADJ
cana-5596	15	22	imaging	imaging	NOUN
cana-5596	15	23	tasks	task	NOUN
cana-5596	15	24	.	.	PUNCT
cana-5596	16	1	by	by	ADP
cana-5596	16	2	learning	learn	VERB
cana-5596	16	3	hierarchical	hierarchical	ADJ
cana-5596	16	4	features	feature	NOUN
cana-5596	16	5	directly	directly	ADV
cana-5596	16	6	from	from	ADP
cana-5596	16	7	raw	raw	ADJ
cana-5596	16	8	image	image	NOUN
cana-5596	16	9	data	datum	NOUN
cana-5596	16	10	,	,	PUNCT
cana-5596	16	11	cnns	cnn	NOUN
cana-5596	16	12	can	can	AUX
cana-5596	16	13	achieve	achieve	VERB
cana-5596	16	14	high	high	ADJ
cana-5596	16	15	accuracy	accuracy	NOUN
cana-5596	16	16	in	in	ADP
cana-5596	16	17	classifying	classify	VERB
cana-5596	16	18	images	image	NOUN
cana-5596	16	19	as	as	ADP
cana-5596	16	20	malignant	malignant	ADJ
cana-5596	16	21	or	or	CCONJ
cana-5596	16	22	benign	benign	ADJ
cana-5596	16	23	and	and	CCONJ
cana-5596	16	24	even	even	ADV
cana-5596	16	25	determine	determine	VERB
cana-5596	16	26	the	the	DET
cana-5596	16	27	stages	stage	NOUN
cana-5596	16	28	of	of	ADP
cana-5596	16	29	malignancy	malignancy	NOUN
cana-5596	16	30	.	.	PUNCT
cana-5596	17	1	this	this	PRON
cana-5596	17	2	eliminates	eliminate	VERB
cana-5596	17	3	the	the	DET
cana-5596	17	4	need	need	NOUN
cana-5596	17	5	for	for	ADP
cana-5596	17	6	handcrafted	handcraft	VERB
cana-5596	17	7	feature	feature	NOUN
cana-5596	17	8	engineering	engineering	NOUN
cana-5596	17	9	and	and	CCONJ
cana-5596	17	10	provides	provide	VERB
cana-5596	17	11	a	a	DET
cana-5596	17	12	scalable	scalable	ADJ
cana-5596	17	13	solution	solution	NOUN
cana-5596	17	14	for	for	ADP
cana-5596	17	15	analyzing	analyze	VERB
cana-5596	17	16	large	large	ADJ
cana-5596	17	17	datasets	dataset	NOUN
cana-5596	17	18	of	of	ADP
cana-5596	17	19	medical	medical	ADJ
cana-5596	17	20	images	image	NOUN
cana-5596	17	21	.	.	PUNCT
cana-5596	18	1	recent	recent	ADJ
cana-5596	18	2	publications	publication	NOUN
cana-5596	18	3	in	in	ADP
cana-5596	18	4	the	the	DET
cana-5596	18	5	field	field	NOUN
cana-5596	18	6	have	have	AUX
cana-5596	18	7	highlighted	highlight	VERB
cana-5596	18	8	the	the	DET
cana-5596	18	9	potential	potential	NOUN
cana-5596	18	10	of	of	ADP
cana-5596	18	11	deep	deep	ADJ
cana-5596	18	12	learning	learning	NOUN
cana-5596	18	13	in	in	ADP
cana-5596	18	14	cancer	cancer	NOUN
cana-5596	18	15	detection	detection	NOUN
cana-5596	18	16	.	.	PUNCT
cana-5596	19	1	for	for	ADP
cana-5596	19	2	example	example	NOUN
cana-5596	19	3	,	,	PUNCT
cana-5596	19	4	studies	study	NOUN
cana-5596	19	5	have	have	AUX
cana-5596	19	6	demonstrated	demonstrate	VERB
cana-5596	19	7	the	the	DET
cana-5596	19	8	application	application	NOUN
cana-5596	19	9	of	of	ADP
cana-5596	19	10	cnns	cnn	NOUN
cana-5596	19	11	to	to	PART
cana-5596	19	12	detect	detect	VERB
cana-5596	19	13	breast	breast	NOUN
cana-5596	19	14	cancer	cancer	NOUN
cana-5596	19	15	with	with	ADP
cana-5596	19	16	remarkable	remarkable	ADJ
cana-5596	19	17	precision	precision	NOUN
cana-5596	19	18	,	,	PUNCT
cana-5596	19	19	achieving	achieve	VERB
cana-5596	19	20	accuracy	accuracy	NOUN
cana-5596	19	21	rates	rate	NOUN
cana-5596	19	22	exceeding	exceed	VERB
cana-5596	19	23	those	those	PRON
cana-5596	19	24	of	of	ADP
cana-5596	19	25	traditional	traditional	ADJ
cana-5596	19	26	methods	method	NOUN
cana-5596	19	27	.	.	PUNCT
cana-5596	20	1	advances	advance	NOUN
cana-5596	20	2	in	in	ADP
cana-5596	20	3	transfer	transfer	NOUN
cana-5596	20	4	learning	learning	NOUN
cana-5596	20	5	,	,	PUNCT
cana-5596	20	6	data	datum	NOUN
cana-5596	20	7	augmentation	augmentation	NOUN
cana-5596	20	8	,	,	PUNCT
cana-5596	20	9	and	and	CCONJ
cana-5596	20	10	model	model	NOUN
cana-5596	20	11	interpretability	interpretability	NOUN
cana-5596	20	12	have	have	AUX
cana-5596	20	13	further	far	ADV
cana-5596	20	14	improved	improve	VERB
cana-5596	20	15	the	the	DET
cana-5596	20	16	performance	performance	NOUN
cana-5596	20	17	and	and	CCONJ
cana-5596	20	18	reliability	reliability	NOUN
cana-5596	20	19	of	of	ADP
cana-5596	20	20	these	these	DET
cana-5596	20	21	systems	system	NOUN
cana-5596	20	22	,	,	PUNCT
cana-5596	20	23	making	make	VERB
cana-5596	20	24	them	they	PRON
cana-5596	20	25	increasingly	increasingly	ADV
cana-5596	20	26	viable	viable	ADJ
cana-5596	20	27	for	for	ADP
cana-5596	20	28	clinical	clinical	ADJ
cana-5596	20	29	use	use	NOUN
cana-5596	20	30	.	.	PUNCT
cana-5596	21	1	this	this	DET
cana-5596	21	2	project	project	NOUN
cana-5596	21	3	aims	aim	VERB
cana-5596	21	4	to	to	PART
cana-5596	21	5	develop	develop	VERB
cana-5596	21	6	a	a	DET
cana-5596	21	7	cnn	cnn	PROPN
cana-5596	21	8	-	-	PUNCT
cana-5596	21	9	based	base	VERB
cana-5596	21	10	model	model	NOUN
cana-5596	21	11	for	for	ADP
cana-5596	21	12	classifying	classify	VERB
cana-5596	21	13	scanned	scan	VERB
cana-5596	21	14	medical	medical	ADJ
cana-5596	21	15	images	image	NOUN
cana-5596	21	16	as	as	ADP
cana-5596	21	17	malignant	malignant	ADJ
cana-5596	21	18	or	or	CCONJ
cana-5596	21	19	benign	benign	ADJ
cana-5596	21	20	and	and	CCONJ
cana-5596	21	21	further	far	ADV
cana-5596	21	22	identifying	identify	VERB
cana-5596	21	23	the	the	DET
cana-5596	21	24	stages	stage	NOUN
cana-5596	21	25	of	of	ADP
cana-5596	21	26	malignancy	malignancy	NOUN
cana-5596	21	27	.	.	PUNCT
cana-5596	22	1	by	by	ADP
cana-5596	22	2	leveraging	leverage	VERB
cana-5596	22	3	state	state	NOUN
cana-5596	22	4	-	-	PUNCT
cana-5596	22	5	ofthe	ofthe	NOUN
cana-5596	22	6	-	-	PUNCT
cana-5596	22	7	art	art	NOUN
cana-5596	22	8	deep	deep	ADJ
cana-5596	22	9	learning	learning	NOUN
cana-5596	22	10	techniques	technique	NOUN
cana-5596	22	11	,	,	PUNCT
cana-5596	22	12	the	the	DET
cana-5596	22	13	proposed	propose	VERB
cana-5596	22	14	system	system	NOUN
cana-5596	22	15	seeks	seek	VERB
cana-5596	22	16	to	to	PART
cana-5596	22	17	reduce	reduce	VERB
cana-5596	22	18	diagnostic	diagnostic	ADJ
cana-5596	22	19	errors	error	NOUN
cana-5596	22	20	,	,	PUNCT
cana-5596	22	21	improve	improve	VERB
cana-5596	22	22	early	early	ADJ
cana-5596	22	23	detection	detection	NOUN
cana-5596	22	24	rates	rate	NOUN
cana-5596	22	25	,	,	PUNCT
cana-5596	22	26	and	and	CCONJ
cana-5596	22	27	provide	provide	VERB
cana-5596	22	28	a	a	DET
cana-5596	22	29	valuable	valuable	ADJ
cana-5596	22	30	tool	tool	NOUN
cana-5596	22	31	for	for	ADP
cana-5596	22	32	healthcare	healthcare	NOUN
cana-5596	22	33	professionals	professional	NOUN
cana-5596	22	34	.	.	PUNCT
cana-5596	23	1	2	2	X
cana-5596	23	2	.	.	X
cana-5596	23	3	theoretical	theoretical	ADJ
cana-5596	23	4	framework	framework	NOUN
cana-5596	23	5	and	and	CCONJ
cana-5596	23	6	literature	literature	PROPN
cana-5596	23	7	review	review	PROPN
cana-5596	23	8	:	:	PUNCT
cana-5596	23	9	2.1	2.1	NUM
cana-5596	23	10	convolutional	convolutional	ADJ
cana-5596	23	11	neural	neural	ADJ
cana-5596	23	12	networks	network	NOUN
cana-5596	23	13	(	(	PUNCT
cana-5596	23	14	cnns	cnns	ADJ
cana-5596	23	15	)	)	PUNCT
cana-5596	23	16	convolutional	convolutional	ADJ
cana-5596	23	17	neural	neural	ADJ
cana-5596	23	18	networks	network	NOUN
cana-5596	23	19	(	(	PUNCT
cana-5596	23	20	cnns	cnns	PROPN
cana-5596	23	21	)	)	PUNCT
cana-5596	23	22	are	be	AUX
cana-5596	23	23	a	a	DET
cana-5596	23	24	class	class	NOUN
cana-5596	23	25	of	of	ADP
cana-5596	23	26	deep	deep	ADJ
cana-5596	23	27	learning	learning	NOUN
cana-5596	23	28	algorithms	algorithm	NOUN
cana-5596	23	29	specifically	specifically	ADV
cana-5596	23	30	designed	design	VERB
cana-5596	23	31	for	for	ADP
cana-5596	23	32	image	image	NOUN
cana-5596	23	33	analysis	analysis	NOUN
cana-5596	23	34	tasks	task	NOUN
cana-5596	23	35	.	.	PUNCT
cana-5596	24	1	first	first	ADV
cana-5596	24	2	introduced	introduce	VERB
cana-5596	24	3	by	by	ADP
cana-5596	24	4	lecun	lecun	PROPN
cana-5596	24	5	et	et	PROPN
cana-5596	24	6	al	al	PROPN
cana-5596	24	7	.	.	PROPN
cana-5596	25	1	(	(	PUNCT
cana-5596	25	2	1998	1998	NUM
cana-5596	25	3	)	)	PUNCT
cana-5596	25	4	for	for	ADP
cana-5596	25	5	digit	digit	NOUN
cana-5596	25	6	recognition	recognition	NOUN
cana-5596	25	7	,	,	PUNCT
cana-5596	25	8	cnns	cnn	NOUN
cana-5596	25	9	have	have	AUX
cana-5596	25	10	since	since	SCONJ
cana-5596	25	11	become	become	VERB
cana-5596	25	12	the	the	DET
cana-5596	25	13	foundation	foundation	NOUN
cana-5596	25	14	for	for	ADP
cana-5596	25	15	numerous	numerous	ADJ
cana-5596	25	16	advancements	advancement	NOUN
cana-5596	25	17	in	in	ADP
cana-5596	25	18	computer	computer	NOUN
cana-5596	25	19	vision	vision	NOUN
cana-5596	25	20	.	.	PUNCT
cana-5596	26	1	they	they	PRON
cana-5596	26	2	employ	employ	VERB
cana-5596	26	3	convolutional	convolutional	ADJ
cana-5596	26	4	layers	layer	NOUN
cana-5596	26	5	to	to	PART
cana-5596	26	6	extract	extract	VERB
cana-5596	26	7	spatial	spatial	ADJ
cana-5596	26	8	hierarchies	hierarchy	NOUN
cana-5596	26	9	of	of	ADP
cana-5596	26	10	features	feature	NOUN
cana-5596	26	11	,	,	PUNCT
cana-5596	26	12	pooling	pool	VERB
cana-5596	26	13	layers	layer	NOUN
cana-5596	26	14	to	to	PART
cana-5596	26	15	reduce	reduce	VERB
cana-5596	26	16	dimensionality	dimensionality	NOUN
cana-5596	26	17	,	,	PUNCT
cana-5596	26	18	and	and	CCONJ
cana-5596	26	19	fully	fully	ADV
cana-5596	26	20	connected	connect	VERB
cana-5596	26	21	layers	layer	NOUN
cana-5596	26	22	for	for	ADP
cana-5596	26	23	classification	classification	NOUN
cana-5596	26	24	.	.	PUNCT
cana-5596	27	1	the	the	DET
cana-5596	27	2	key	key	ADJ
cana-5596	27	3	components	component	NOUN
cana-5596	27	4	of	of	ADP
cana-5596	27	5	cnns	cnn	NOUN
cana-5596	27	6	,	,	PUNCT
cana-5596	27	7	such	such	ADJ
cana-5596	27	8	as	as	ADP
cana-5596	27	9	kernels	kernel	NOUN
cana-5596	27	10	,	,	PUNCT
cana-5596	27	11	activation	activation	NOUN
cana-5596	27	12	functions	function	NOUN
cana-5596	27	13	(	(	PUNCT
cana-5596	27	14	e.g.	e.g.	ADV
cana-5596	27	15	,	,	PUNCT
cana-5596	27	16	relu	relu	NOUN
cana-5596	27	17	)	)	PUNCT
cana-5596	27	18	,	,	PUNCT
cana-5596	27	19	and	and	CCONJ
cana-5596	27	20	backpropagation	backpropagation	NOUN
cana-5596	27	21	,	,	PUNCT
cana-5596	27	22	form	form	VERB
cana-5596	27	23	the	the	DET
cana-5596	27	24	theoretical	theoretical	ADJ
cana-5596	27	25	backbone	backbone	NOUN
cana-5596	27	26	for	for	ADP
cana-5596	27	27	medical	medical	ADJ
cana-5596	27	28	imaging	imaging	NOUN
cana-5596	27	29	applications	application	NOUN
cana-5596	27	30	.	.	PUNCT
cana-5596	28	1	figure	figure	NOUN
cana-5596	28	2	1	1	NUM
cana-5596	28	3	:	:	PUNCT
cana-5596	28	4	cnn	cnn	PROPN
cana-5596	28	5	architecture	architecture	NOUN
cana-5596	28	6	diagram	diagram	NOUN
cana-5596	28	7	–	–	PUNCT
cana-5596	28	8	displays	display	VERB
cana-5596	28	9	the	the	DET
cana-5596	28	10	general	general	ADJ
cana-5596	28	11	structure	structure	NOUN
cana-5596	28	12	of	of	ADP
cana-5596	28	13	the	the	DET
cana-5596	28	14	proposed	proposed	ADJ
cana-5596	28	15	cnn	cnn	PROPN
cana-5596	28	16	.	.	PUNCT
cana-5596	29	1	in	in	ADP
cana-5596	29	2	cancer	cancer	NOUN
cana-5596	29	3	detection	detection	NOUN
cana-5596	29	4	,	,	PUNCT
cana-5596	29	5	cnns	cnn	NOUN
cana-5596	29	6	learn	learn	VERB
cana-5596	29	7	to	to	PART
cana-5596	29	8	identify	identify	VERB
cana-5596	29	9	patterns	pattern	NOUN
cana-5596	29	10	such	such	ADJ
cana-5596	29	11	as	as	ADP
cana-5596	29	12	cell	cell	NOUN
cana-5596	29	13	morphology	morphology	NOUN
cana-5596	29	14	and	and	CCONJ
cana-5596	29	15	tissue	tissue	NOUN
cana-5596	29	16	irregularities	irregularity	NOUN
cana-5596	29	17	directly	directly	ADV
cana-5596	29	18	from	from	ADP
cana-5596	29	19	medical	medical	ADJ
cana-5596	29	20	images	image	NOUN
cana-5596	29	21	,	,	PUNCT
cana-5596	29	22	bypassing	bypass	VERB
cana-5596	29	23	the	the	DET
cana-5596	29	24	need	need	NOUN
cana-5596	29	25	for	for	ADP
cana-5596	29	26	manual	manual	ADJ
cana-5596	29	27	feature	feature	NOUN
cana-5596	29	28	extraction	extraction	NOUN
cana-5596	29	29	.	.	PUNCT
cana-5596	30	1	this	this	DET
cana-5596	30	2	approach	approach	NOUN
cana-5596	30	3	communications	communication	NOUN
cana-5596	30	4	on	on	ADP
cana-5596	30	5	applied	apply	VERB
cana-5596	30	6	nonlinear	nonlinear	ADJ
cana-5596	30	7	analysis	analysis	NOUN
cana-5596	30	8	issn	issn	NOUN
cana-5596	30	9	:	:	PUNCT
cana-5596	30	10	1074	1074	NUM
cana-5596	30	11	-	-	PUNCT
cana-5596	30	12	133x	133x	NUM
cana-5596	30	13	vol	vol	NOUN
cana-5596	30	14	32	32	NUM
cana-5596	30	15	no	no	NOUN
cana-5596	30	16	.	.	PUNCT
cana-5596	31	1	icmasd	icmasd	NOUN
cana-5596	31	2	(	(	PUNCT
cana-5596	31	3	2025	2025	NUM
cana-5596	31	4	)	)	PUNCT
cana-5596	31	5	1965	1965	NUM
cana-5596	31	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	31	7	allows	allow	VERB
cana-5596	31	8	for	for	ADP
cana-5596	31	9	the	the	DET
cana-5596	31	10	detection	detection	NOUN
cana-5596	31	11	of	of	ADP
cana-5596	31	12	minute	minute	ADJ
cana-5596	31	13	differences	difference	NOUN
cana-5596	31	14	between	between	ADP
cana-5596	31	15	benign	benign	ADJ
cana-5596	31	16	and	and	CCONJ
cana-5596	31	17	malignant	malignant	ADJ
cana-5596	31	18	cells	cell	NOUN
cana-5596	31	19	,	,	PUNCT
cana-5596	31	20	which	which	PRON
cana-5596	31	21	is	be	AUX
cana-5596	31	22	crucial	crucial	ADJ
cana-5596	31	23	for	for	ADP
cana-5596	31	24	accurate	accurate	ADJ
cana-5596	31	25	staging	staging	NOUN
cana-5596	31	26	.	.	PUNCT
cana-5596	32	1	2.2	2.2	NUM
cana-5596	32	2	literature	literature	NOUN
cana-5596	32	3	review	review	NOUN
cana-5596	32	4	2.2.1	2.2.1	NUM
cana-5596	32	5	cancer	cancer	NOUN
cana-5596	32	6	detection	detection	NOUN
cana-5596	32	7	with	with	ADP
cana-5596	32	8	cnns	cnns	ADJ
cana-5596	32	9	recent	recent	ADJ
cana-5596	32	10	studies	study	NOUN
cana-5596	32	11	have	have	AUX
cana-5596	32	12	demonstrated	demonstrate	VERB
cana-5596	32	13	the	the	DET
cana-5596	32	14	effectiveness	effectiveness	NOUN
cana-5596	32	15	of	of	ADP
cana-5596	32	16	cnns	cnn	NOUN
cana-5596	32	17	in	in	ADP
cana-5596	32	18	cancer	cancer	NOUN
cana-5596	32	19	detection	detection	NOUN
cana-5596	32	20	across	across	ADP
cana-5596	32	21	various	various	ADJ
cana-5596	32	22	domains	domain	NOUN
cana-5596	32	23	:	:	PUNCT
cana-5596	32	24	•	•	NUM
cana-5596	32	25	breast	breast	NOUN
cana-5596	32	26	cancer	cancer	NOUN
cana-5596	32	27	:	:	PUNCT
cana-5596	32	28	zhang	zhang	PROPN
cana-5596	32	29	et	et	PROPN
cana-5596	32	30	al	al	PROPN
cana-5596	32	31	.	.	PROPN
cana-5596	33	1	(	(	PUNCT
cana-5596	33	2	2022	2022	NUM
cana-5596	33	3	)	)	PUNCT
cana-5596	33	4	developed	develop	VERB
cana-5596	33	5	a	a	DET
cana-5596	33	6	cnn	cnn	PROPN
cana-5596	33	7	-	-	PUNCT
cana-5596	33	8	based	base	VERB
cana-5596	33	9	model	model	NOUN
cana-5596	33	10	achieving	achieve	VERB
cana-5596	33	11	95	95	NUM
cana-5596	33	12	%	%	NOUN
cana-5596	33	13	accuracy	accuracy	NOUN
cana-5596	33	14	in	in	ADP
cana-5596	33	15	classifying	classify	VERB
cana-5596	33	16	mammogram	mammogram	NOUN
cana-5596	33	17	images	image	NOUN
cana-5596	33	18	as	as	ADP
cana-5596	33	19	malignant	malignant	ADJ
cana-5596	33	20	or	or	CCONJ
cana-5596	33	21	benign	benign	ADJ
cana-5596	33	22	.	.	PUNCT
cana-5596	34	1	•	•	NUM
cana-5596	34	2	lung	lung	NOUN
cana-5596	34	3	cancer	cancer	NOUN
cana-5596	34	4	:	:	PUNCT
cana-5596	34	5	a	a	DET
cana-5596	34	6	study	study	NOUN
cana-5596	34	7	by	by	ADP
cana-5596	34	8	smith	smith	PROPN
cana-5596	34	9	et	et	PROPN
cana-5596	34	10	al	al	PROPN
cana-5596	34	11	.	.	PROPN
cana-5596	34	12	(	(	PUNCT
cana-5596	34	13	2021	2021	NUM
cana-5596	34	14	)	)	PUNCT
cana-5596	34	15	utilized	utilize	VERB
cana-5596	34	16	3d	3d	PROPN
cana-5596	34	17	cnns	cnn	NOUN
cana-5596	34	18	to	to	PART
cana-5596	34	19	analyze	analyze	VERB
cana-5596	34	20	ct	ct	NUM
cana-5596	34	21	scans	scan	NOUN
cana-5596	34	22	,	,	PUNCT
cana-5596	34	23	significantly	significantly	ADV
cana-5596	34	24	improving	improve	VERB
cana-5596	34	25	early	early	ADJ
cana-5596	34	26	detection	detection	NOUN
cana-5596	34	27	rates	rate	NOUN
cana-5596	34	28	for	for	ADP
cana-5596	34	29	lung	lung	NOUN
cana-5596	34	30	nodules	nodule	NOUN
cana-5596	34	31	.	.	PUNCT
cana-5596	35	1	these	these	DET
cana-5596	35	2	works	work	NOUN
cana-5596	35	3	underscore	underscore	VERB
cana-5596	35	4	the	the	DET
cana-5596	35	5	adaptability	adaptability	NOUN
cana-5596	35	6	of	of	ADP
cana-5596	35	7	cnns	cnn	NOUN
cana-5596	35	8	to	to	PART
cana-5596	35	9	diverse	diverse	VERB
cana-5596	35	10	imaging	imaging	NOUN
cana-5596	35	11	modalities	modality	NOUN
cana-5596	35	12	and	and	CCONJ
cana-5596	35	13	cancer	cancer	NOUN
cana-5596	35	14	types	type	NOUN
cana-5596	35	15	.	.	PUNCT
cana-5596	36	1	2.2.2	2.2.2	NUM
cana-5596	36	2	challenges	challenge	NOUN
cana-5596	36	3	and	and	CCONJ
cana-5596	36	4	limitations	limitation	NOUN
cana-5596	36	5	despite	despite	SCONJ
cana-5596	36	6	their	their	PRON
cana-5596	36	7	success	success	NOUN
cana-5596	36	8	,	,	PUNCT
cana-5596	36	9	cnn	cnn	PROPN
cana-5596	36	10	-	-	PUNCT
cana-5596	36	11	based	base	VERB
cana-5596	36	12	models	model	NOUN
cana-5596	36	13	face	face	VERB
cana-5596	36	14	challenges	challenge	NOUN
cana-5596	36	15	such	such	ADJ
cana-5596	36	16	as	as	ADP
cana-5596	36	17	data	datum	NOUN
cana-5596	36	18	imbalance	imbalance	NOUN
cana-5596	36	19	,	,	PUNCT
cana-5596	36	20	interpretability	interpretability	NOUN
cana-5596	36	21	,	,	PUNCT
cana-5596	36	22	and	and	CCONJ
cana-5596	36	23	the	the	DET
cana-5596	36	24	need	need	NOUN
cana-5596	36	25	for	for	ADP
cana-5596	36	26	large	large	ADJ
cana-5596	36	27	labeled	label	VERB
cana-5596	36	28	datasets	dataset	NOUN
cana-5596	36	29	.	.	PUNCT
cana-5596	37	1	data	datum	NOUN
cana-5596	37	2	augmentation	augmentation	NOUN
cana-5596	37	3	techniques	technique	NOUN
cana-5596	37	4	,	,	PUNCT
cana-5596	37	5	transfer	transfer	NOUN
cana-5596	37	6	learning	learning	NOUN
cana-5596	37	7	,	,	PUNCT
cana-5596	37	8	and	and	CCONJ
cana-5596	37	9	explainable	explainable	ADJ
cana-5596	37	10	ai	ai	NOUN
cana-5596	37	11	(	(	PUNCT
cana-5596	37	12	xai	xai	PROPN
cana-5596	37	13	)	)	PUNCT
cana-5596	37	14	have	have	AUX
cana-5596	37	15	been	be	AUX
cana-5596	37	16	proposed	propose	VERB
cana-5596	37	17	to	to	PART
cana-5596	37	18	mitigate	mitigate	VERB
cana-5596	37	19	these	these	DET
cana-5596	37	20	issues	issue	NOUN
cana-5596	37	21	.	.	PUNCT
cana-5596	38	1	for	for	ADP
cana-5596	38	2	example	example	NOUN
cana-5596	38	3	,	,	PUNCT
cana-5596	38	4	kumar	kumar	PROPN
cana-5596	38	5	et	et	PROPN
cana-5596	38	6	al	al	PROPN
cana-5596	38	7	.	.	PROPN
cana-5596	39	1	(	(	PUNCT
cana-5596	39	2	2023	2023	NUM
cana-5596	39	3	)	)	PUNCT
cana-5596	39	4	demonstrated	demonstrate	VERB
cana-5596	39	5	that	that	SCONJ
cana-5596	39	6	pre	pre	ADJ
cana-5596	39	7	-	-	ADJ
cana-5596	39	8	trained	train	VERB
cana-5596	39	9	models	model	NOUN
cana-5596	39	10	fine	fine	ADV
cana-5596	39	11	-	-	PUNCT
cana-5596	39	12	tuned	tune	VERB
cana-5596	39	13	with	with	ADP
cana-5596	39	14	smaller	small	ADJ
cana-5596	39	15	datasets	dataset	NOUN
cana-5596	39	16	could	could	AUX
cana-5596	39	17	achieve	achieve	VERB
cana-5596	39	18	comparable	comparable	ADJ
cana-5596	39	19	performance	performance	NOUN
cana-5596	39	20	to	to	ADP
cana-5596	39	21	models	model	NOUN
cana-5596	39	22	trained	train	VERB
cana-5596	39	23	from	from	ADP
cana-5596	39	24	scratch	scratch	NOUN
cana-5596	39	25	.	.	PUNCT
cana-5596	40	1	2.3	2.3	NUM
cana-5596	40	2	key	key	ADJ
cana-5596	40	3	equations	equation	NOUN
cana-5596	40	4	and	and	CCONJ
cana-5596	40	5	concepts	concept	VERB
cana-5596	40	6	the	the	DET
cana-5596	40	7	theoretical	theoretical	ADJ
cana-5596	40	8	basis	basis	NOUN
cana-5596	40	9	of	of	ADP
cana-5596	40	10	cnns	cnns	PROPN
cana-5596	40	11	is	be	AUX
cana-5596	40	12	rooted	root	VERB
cana-5596	40	13	in	in	ADP
cana-5596	40	14	key	key	ADJ
cana-5596	40	15	mathematical	mathematical	ADJ
cana-5596	40	16	operations	operation	NOUN
cana-5596	40	17	,	,	PUNCT
cana-5596	40	18	including	include	VERB
cana-5596	40	19	convolution	convolution	NOUN
cana-5596	40	20	,	,	PUNCT
cana-5596	40	21	activation	activation	NOUN
cana-5596	40	22	,	,	PUNCT
cana-5596	40	23	and	and	CCONJ
cana-5596	40	24	loss	loss	NOUN
cana-5596	40	25	minimization	minimization	NOUN
cana-5596	40	26	.	.	PUNCT
cana-5596	41	1	while	while	SCONJ
cana-5596	41	2	common	common	ADJ
cana-5596	41	3	equations	equation	NOUN
cana-5596	41	4	are	be	AUX
cana-5596	41	5	not	not	PART
cana-5596	41	6	reproduced	reproduce	VERB
cana-5596	41	7	here	here	ADV
cana-5596	41	8	,	,	PUNCT
cana-5596	41	9	the	the	DET
cana-5596	41	10	following	follow	VERB
cana-5596	41	11	concepts	concept	NOUN
cana-5596	41	12	are	be	AUX
cana-5596	41	13	emphasized	emphasize	VERB
cana-5596	41	14	:	:	PUNCT
cana-5596	41	15	1	1	X
cana-5596	41	16	.	.	X
cana-5596	41	17	convolution	convolution	NOUN
cana-5596	41	18	operation	operation	NOUN
cana-5596	41	19	:	:	PUNCT
cana-5596	41	20	extracts	extract	NOUN
cana-5596	41	21	spatial	spatial	ADJ
cana-5596	41	22	features	feature	NOUN
cana-5596	41	23	by	by	ADP
cana-5596	41	24	applying	apply	VERB
cana-5596	41	25	kernels	kernel	NOUN
cana-5596	41	26	across	across	ADP
cana-5596	41	27	the	the	DET
cana-5596	41	28	image	image	NOUN
cana-5596	41	29	.	.	PUNCT
cana-5596	42	1	2	2	X
cana-5596	42	2	.	.	X
cana-5596	42	3	loss	loss	NOUN
cana-5596	42	4	functions	function	NOUN
cana-5596	42	5	:	:	PUNCT
cana-5596	42	6	cross	cross	ADJ
cana-5596	42	7	-	-	ADJ
cana-5596	42	8	entropy	entropy	ADJ
cana-5596	42	9	loss	loss	NOUN
cana-5596	42	10	is	be	AUX
cana-5596	42	11	commonly	commonly	ADV
cana-5596	42	12	used	use	VERB
cana-5596	42	13	for	for	ADP
cana-5596	42	14	classification	classification	NOUN
cana-5596	42	15	tasks	task	NOUN
cana-5596	42	16	.	.	PUNCT
cana-5596	43	1	3	3	X
cana-5596	43	2	.	.	X
cana-5596	43	3	optimization	optimization	NOUN
cana-5596	43	4	algorithms	algorithm	NOUN
cana-5596	43	5	:	:	PUNCT
cana-5596	43	6	techniques	technique	NOUN
cana-5596	43	7	like	like	ADP
cana-5596	43	8	adam	adam	PROPN
cana-5596	43	9	are	be	AUX
cana-5596	43	10	employed	employ	VERB
cana-5596	43	11	to	to	PART
cana-5596	43	12	minimize	minimize	VERB
cana-5596	43	13	loss	loss	NOUN
cana-5596	43	14	and	and	CCONJ
cana-5596	43	15	improve	improve	VERB
cana-5596	43	16	convergence	convergence	NOUN
cana-5596	43	17	rates	rate	NOUN
cana-5596	43	18	.	.	PUNCT
cana-5596	44	1	3	3	X
cana-5596	44	2	.	.	X
cana-5596	44	3	research	research	NOUN
cana-5596	44	4	methodology	methodology	NOUN
cana-5596	44	5	/	/	SYM
cana-5596	44	6	experimental	experimental	ADJ
cana-5596	44	7	:	:	PUNCT
cana-5596	44	8	3.1	3.1	NUM
cana-5596	44	9	dataset	dataset	VERB
cana-5596	44	10	the	the	DET
cana-5596	44	11	dataset	dataset	NOUN
cana-5596	44	12	used	use	VERB
cana-5596	44	13	for	for	ADP
cana-5596	44	14	this	this	DET
cana-5596	44	15	study	study	NOUN
cana-5596	44	16	consists	consist	VERB
cana-5596	44	17	of	of	ADP
cana-5596	44	18	cancer	cancer	NOUN
cana-5596	44	19	detection	detection	NOUN
cana-5596	44	20	dataset	dataset	VERB
cana-5596	44	21	using	use	VERB
cana-5596	44	22	cnn	cnn	PROPN
cana-5596	44	23	,	,	PUNCT
cana-5596	44	24	which	which	PRON
cana-5596	44	25	includes	include	VERB
cana-5596	44	26	highresolution	highresolution	NOUN
cana-5596	44	27	scanned	scan	VERB
cana-5596	44	28	images	image	NOUN
cana-5596	44	29	of	of	ADP
cana-5596	44	30	tissue	tissue	NOUN
cana-5596	44	31	samples	sample	NOUN
cana-5596	44	32	.	.	PUNCT
cana-5596	45	1	the	the	DET
cana-5596	45	2	dataset	dataset	NOUN
cana-5596	45	3	comprises	comprise	VERB
cana-5596	45	4	2000	2000	NUM
cana-5596	45	5	images	image	NOUN
cana-5596	45	6	categorized	categorize	VERB
cana-5596	45	7	into	into	ADP
cana-5596	45	8	benign	benign	ADJ
cana-5596	45	9	and	and	CCONJ
cana-5596	45	10	malignant	malignant	ADJ
cana-5596	45	11	cases	case	NOUN
cana-5596	45	12	,	,	PUNCT
cana-5596	45	13	with	with	ADP
cana-5596	45	14	further	further	ADJ
cana-5596	45	15	sub	sub	NOUN
cana-5596	45	16	-	-	NOUN
cana-5596	45	17	categories	category	NOUN
cana-5596	45	18	for	for	ADP
cana-5596	45	19	different	different	ADJ
cana-5596	45	20	stages	stage	NOUN
cana-5596	45	21	of	of	ADP
cana-5596	45	22	malignancy	malignancy	NOUN
cana-5596	45	23	.	.	PUNCT
cana-5596	46	1	communications	communication	NOUN
cana-5596	46	2	on	on	ADP
cana-5596	46	3	applied	apply	VERB
cana-5596	46	4	nonlinear	nonlinear	ADJ
cana-5596	46	5	analysis	analysis	NOUN
cana-5596	46	6	issn	issn	NOUN
cana-5596	46	7	:	:	PUNCT
cana-5596	46	8	1074	1074	NUM
cana-5596	46	9	-	-	PUNCT
cana-5596	46	10	133x	133x	NUM
cana-5596	46	11	vol	vol	NOUN
cana-5596	46	12	32	32	NUM
cana-5596	46	13	no	no	NOUN
cana-5596	46	14	.	.	PUNCT
cana-5596	47	1	icmasd	icmasd	NOUN
cana-5596	47	2	(	(	PUNCT
cana-5596	47	3	2025	2025	NUM
cana-5596	47	4	)	)	PUNCT
cana-5596	47	5	1966	1966	NUM
cana-5596	47	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	47	7	pre	pre	ADJ
cana-5596	47	8	-	-	ADJ
cana-5596	47	9	processing	processing	ADJ
cana-5596	47	10	steps	step	NOUN
cana-5596	47	11	include	include	VERB
cana-5596	47	12	:	:	PUNCT
cana-5596	48	1	•	•	NUM
cana-5596	48	2	data	datum	NOUN
cana-5596	48	3	cleaning	cleaning	NOUN
cana-5596	48	4	:	:	PUNCT
cana-5596	48	5	removal	removal	NOUN
cana-5596	48	6	of	of	ADP
cana-5596	48	7	corrupted	corrupted	ADJ
cana-5596	48	8	or	or	CCONJ
cana-5596	48	9	low	low	ADJ
cana-5596	48	10	-	-	PUNCT
cana-5596	48	11	quality	quality	NOUN
cana-5596	48	12	images	image	NOUN
cana-5596	48	13	.	.	PUNCT
cana-5596	49	1	•	•	NUM
cana-5596	49	2	normalization	normalization	NOUN
cana-5596	49	3	:	:	PUNCT
cana-5596	49	4	rescaling	rescale	VERB
cana-5596	49	5	pixel	pixel	ADJ
cana-5596	49	6	values	value	NOUN
cana-5596	49	7	to	to	ADP
cana-5596	49	8	a	a	DET
cana-5596	49	9	range	range	NOUN
cana-5596	49	10	of	of	ADP
cana-5596	49	11	[	[	X
cana-5596	49	12	0	0	NUM
cana-5596	49	13	,	,	PUNCT
cana-5596	49	14	1	1	NUM
cana-5596	49	15	]	]	PUNCT
cana-5596	49	16	to	to	PART
cana-5596	49	17	improve	improve	VERB
cana-5596	49	18	model	model	NOUN
cana-5596	49	19	convergence	convergence	NOUN
cana-5596	49	20	.	.	PUNCT
cana-5596	50	1	•	•	NUM
cana-5596	50	2	data	datum	NOUN
cana-5596	50	3	augmentation	augmentation	NOUN
cana-5596	50	4	:	:	PUNCT
cana-5596	50	5	application	application	NOUN
cana-5596	50	6	of	of	ADP
cana-5596	50	7	random	random	ADJ
cana-5596	50	8	rotations	rotation	NOUN
cana-5596	50	9	,	,	PUNCT
cana-5596	50	10	flips	flip	NOUN
cana-5596	50	11	,	,	PUNCT
cana-5596	50	12	and	and	CCONJ
cana-5596	50	13	zooms	zoom	VERB
cana-5596	50	14	to	to	PART
cana-5596	50	15	mitigate	mitigate	VERB
cana-5596	50	16	class	class	NOUN
cana-5596	50	17	imbalance	imbalance	NOUN
cana-5596	50	18	and	and	CCONJ
cana-5596	50	19	enhance	enhance	VERB
cana-5596	50	20	model	model	NOUN
cana-5596	50	21	generalization	generalization	NOUN
cana-5596	50	22	.	.	PUNCT
cana-5596	51	1	class	class	NOUN
cana-5596	51	2	number	number	NOUN
cana-5596	51	3	of	of	ADP
cana-5596	51	4	images	image	NOUN
cana-5596	51	5	image	image	NOUN
cana-5596	51	6	resolution	resolution	NOUN
cana-5596	51	7	malignant	malignant	NOUN
cana-5596	51	8	1,200	1,200	NUM
cana-5596	51	9	224x224	224x224	NUM
cana-5596	51	10	benign	benign	VERB
cana-5596	51	11	1,800	1,800	NUM
cana-5596	51	12	224x224	224x224	NUM
cana-5596	51	13	total	total	ADJ
cana-5596	51	14	3,000	3,000	NUM
cana-5596	51	15	table	table	NOUN
cana-5596	51	16	1	1	NUM
cana-5596	51	17	dataset	dataset	NOUN
cana-5596	51	18	distribution	distribution	NOUN
cana-5596	51	19	and	and	CCONJ
cana-5596	51	20	characteristics	characteristic	NOUN
cana-5596	51	21	3.2	3.2	NUM
cana-5596	51	22	model	model	NOUN
cana-5596	51	23	architecture	architecture	NOUN
cana-5596	51	24	the	the	DET
cana-5596	51	25	proposed	propose	VERB
cana-5596	51	26	model	model	NOUN
cana-5596	51	27	is	be	AUX
cana-5596	51	28	a	a	DET
cana-5596	51	29	convolutional	convolutional	ADJ
cana-5596	51	30	neural	neural	ADJ
cana-5596	51	31	network	network	NOUN
cana-5596	51	32	(	(	PUNCT
cana-5596	51	33	cnn	cnn	PROPN
cana-5596	51	34	)	)	PUNCT
cana-5596	51	35	designed	design	VERB
cana-5596	51	36	for	for	ADP
cana-5596	51	37	multi	multi	ADJ
cana-5596	51	38	-	-	ADJ
cana-5596	51	39	class	class	ADJ
cana-5596	51	40	classification	classification	NOUN
cana-5596	51	41	.	.	PUNCT
cana-5596	52	1	the	the	DET
cana-5596	52	2	architecture	architecture	NOUN
cana-5596	52	3	consists	consist	VERB
cana-5596	52	4	of	of	ADP
cana-5596	52	5	:	:	PUNCT
cana-5596	52	6	1	1	X
cana-5596	52	7	.	.	PUNCT
cana-5596	52	8	convolutional	convolutional	ADJ
cana-5596	52	9	layers	layer	NOUN
cana-5596	52	10	:	:	PUNCT
cana-5596	52	11	three	three	NUM
cana-5596	52	12	convolutional	convolutional	ADJ
cana-5596	52	13	blocks	block	NOUN
cana-5596	52	14	,	,	PUNCT
cana-5596	52	15	each	each	PRON
cana-5596	52	16	with	with	ADP
cana-5596	52	17	32	32	NUM
cana-5596	52	18	,	,	PUNCT
cana-5596	52	19	64	64	NUM
cana-5596	52	20	,	,	PUNCT
cana-5596	52	21	and	and	CCONJ
cana-5596	52	22	128	128	NUM
cana-5596	52	23	filters	filter	NOUN
cana-5596	52	24	,	,	PUNCT
cana-5596	52	25	respectively	respectively	ADV
cana-5596	52	26	.	.	PUNCT
cana-5596	53	1	each	each	DET
cana-5596	53	2	block	block	NOUN
cana-5596	53	3	is	be	AUX
cana-5596	53	4	followed	follow	VERB
cana-5596	53	5	by	by	ADP
cana-5596	53	6	batch	batch	NOUN
cana-5596	53	7	normalization	normalization	NOUN
cana-5596	53	8	and	and	CCONJ
cana-5596	53	9	max	max	PROPN
cana-5596	53	10	-	-	PUNCT
cana-5596	53	11	pooling	pooling	NOUN
cana-5596	53	12	.	.	PUNCT
cana-5596	54	1	2	2	X
cana-5596	54	2	.	.	X
cana-5596	54	3	fully	fully	ADV
cana-5596	54	4	connected	connected	ADJ
cana-5596	54	5	layers	layer	NOUN
cana-5596	54	6	:	:	PUNCT
cana-5596	54	7	two	two	NUM
cana-5596	54	8	dense	dense	ADJ
cana-5596	54	9	layers	layer	NOUN
cana-5596	54	10	with	with	ADP
cana-5596	54	11	256	256	NUM
cana-5596	54	12	and	and	CCONJ
cana-5596	54	13	128	128	NUM
cana-5596	54	14	neurons	neuron	NOUN
cana-5596	54	15	,	,	PUNCT
cana-5596	54	16	activated	activate	VERB
cana-5596	54	17	using	use	VERB
cana-5596	54	18	relu	relu	NOUN
cana-5596	54	19	,	,	PUNCT
cana-5596	54	20	followed	follow	VERB
cana-5596	54	21	by	by	ADP
cana-5596	54	22	a	a	DET
cana-5596	54	23	softmax	softmax	NOUN
cana-5596	54	24	layer	layer	NOUN
cana-5596	54	25	for	for	ADP
cana-5596	54	26	classification	classification	NOUN
cana-5596	54	27	.	.	PUNCT
cana-5596	55	1	3	3	X
cana-5596	55	2	.	.	X
cana-5596	55	3	regularization	regularization	NOUN
cana-5596	55	4	:	:	PUNCT
cana-5596	55	5	dropout	dropout	NOUN
cana-5596	55	6	layers	layer	NOUN
cana-5596	55	7	(	(	PUNCT
cana-5596	55	8	rate	rate	NOUN
cana-5596	55	9	=	=	NOUN
cana-5596	55	10	0.5	0.5	NUM
cana-5596	55	11	)	)	PUNCT
cana-5596	55	12	are	be	AUX
cana-5596	55	13	used	use	VERB
cana-5596	55	14	to	to	PART
cana-5596	55	15	prevent	prevent	VERB
cana-5596	55	16	overfitting	overfitting	NOUN
cana-5596	55	17	.	.	PUNCT
cana-5596	56	1	the	the	DET
cana-5596	56	2	model	model	NOUN
cana-5596	56	3	was	be	AUX
cana-5596	56	4	implemented	implement	VERB
cana-5596	56	5	using	use	VERB
cana-5596	56	6	tensorflow	tensorflow	NOUN
cana-5596	56	7	and	and	CCONJ
cana-5596	56	8	keras	keras	PROPN
cana-5596	56	9	.	.	PUNCT
cana-5596	57	1	pre	pre	VERB
cana-5596	57	2	-	-	ADJ
cana-5596	57	3	trained	train	VERB
cana-5596	57	4	models	model	NOUN
cana-5596	57	5	such	such	ADJ
cana-5596	57	6	as	as	ADP
cana-5596	57	7	vgg16	vgg16	NOUN
cana-5596	57	8	and	and	CCONJ
cana-5596	57	9	resnet50	resnet50	NOUN
cana-5596	57	10	were	be	AUX
cana-5596	57	11	explored	explore	VERB
cana-5596	57	12	for	for	ADP
cana-5596	57	13	transfer	transfer	NOUN
cana-5596	57	14	learning	learning	NOUN
cana-5596	57	15	to	to	PART
cana-5596	57	16	improve	improve	VERB
cana-5596	57	17	performance	performance	NOUN
cana-5596	57	18	on	on	ADP
cana-5596	57	19	smaller	small	ADJ
cana-5596	57	20	datasets	dataset	NOUN
cana-5596	57	21	.	.	PUNCT
cana-5596	58	1	3.3	3.3	NUM
cana-5596	58	2	training	training	NOUN
cana-5596	58	3	and	and	CCONJ
cana-5596	58	4	validation	validation	NOUN
cana-5596	58	5	the	the	DET
cana-5596	58	6	dataset	dataset	NOUN
cana-5596	58	7	was	be	AUX
cana-5596	58	8	split	split	VERB
cana-5596	58	9	into	into	ADP
cana-5596	58	10	training	training	NOUN
cana-5596	58	11	,	,	PUNCT
cana-5596	58	12	validation	validation	NOUN
cana-5596	58	13	,	,	PUNCT
cana-5596	58	14	and	and	CCONJ
cana-5596	58	15	test	test	NOUN
cana-5596	58	16	sets	set	NOUN
cana-5596	58	17	in	in	ADP
cana-5596	58	18	a	a	DET
cana-5596	58	19	ratio	ratio	NOUN
cana-5596	58	20	of	of	ADP
cana-5596	58	21	70:15:15	70:15:15	NUM
cana-5596	58	22	.	.	PUNCT
cana-5596	59	1	the	the	DET
cana-5596	59	2	model	model	NOUN
cana-5596	59	3	was	be	AUX
cana-5596	59	4	trained	train	VERB
cana-5596	59	5	for	for	ADP
cana-5596	59	6	50	50	NUM
cana-5596	59	7	epochs	epoch	NOUN
cana-5596	59	8	using	use	VERB
cana-5596	59	9	the	the	DET
cana-5596	59	10	adam	adam	PROPN
cana-5596	59	11	optimizer	optimizer	NOUN
cana-5596	59	12	with	with	ADP
cana-5596	59	13	an	an	DET
cana-5596	59	14	initial	initial	ADJ
cana-5596	59	15	learning	learning	NOUN
cana-5596	59	16	rate	rate	NOUN
cana-5596	59	17	of	of	ADP
cana-5596	59	18	0.001	0.001	NUM
cana-5596	59	19	.	.	PUNCT
cana-5596	60	1	key	key	ADJ
cana-5596	60	2	hyperparameters	hyperparameter	NOUN
cana-5596	60	3	include	include	VERB
cana-5596	60	4	:	:	PUNCT
cana-5596	60	5	•	•	ADJ
cana-5596	60	6	batch	batch	NOUN
cana-5596	60	7	size	size	NOUN
cana-5596	60	8	:	:	PUNCT
cana-5596	60	9	32	32	NUM
cana-5596	60	10	•	•	NOUN
cana-5596	60	11	loss	loss	NOUN
cana-5596	60	12	function	function	NOUN
cana-5596	60	13	:	:	PUNCT
cana-5596	60	14	categorical	categorical	ADJ
cana-5596	60	15	cross	cross	NOUN
cana-5596	60	16	-	-	NOUN
cana-5596	60	17	entropy	entropy	NOUN
cana-5596	60	18	for	for	ADP
cana-5596	60	19	multi	multi	ADJ
cana-5596	60	20	-	-	ADJ
cana-5596	60	21	class	class	ADJ
cana-5596	60	22	classification	classification	NOUN
cana-5596	60	23	.	.	PUNCT
cana-5596	61	1	•	•	NUM
cana-5596	61	2	metrics	metric	NOUN
cana-5596	61	3	:	:	PUNCT
cana-5596	61	4	accuracy	accuracy	NOUN
cana-5596	61	5	and	and	CCONJ
cana-5596	61	6	f1	f1	NOUN
cana-5596	61	7	-	-	PUNCT
cana-5596	61	8	score	score	NOUN
cana-5596	61	9	to	to	PART
cana-5596	61	10	assess	assess	VERB
cana-5596	61	11	classification	classification	NOUN
cana-5596	61	12	performance	performance	NOUN
cana-5596	61	13	.	.	PUNCT
cana-5596	62	1	3.4	3.4	NUM
cana-5596	62	2	evaluation	evaluation	NOUN
cana-5596	62	3	metrics	metric	NOUN
cana-5596	62	4	to	to	PART
cana-5596	62	5	ensure	ensure	VERB
cana-5596	62	6	the	the	DET
cana-5596	62	7	robustness	robustness	NOUN
cana-5596	62	8	of	of	ADP
cana-5596	62	9	the	the	DET
cana-5596	62	10	model	model	NOUN
cana-5596	62	11	,	,	PUNCT
cana-5596	62	12	the	the	DET
cana-5596	62	13	following	follow	VERB
cana-5596	62	14	metrics	metric	NOUN
cana-5596	62	15	were	be	AUX
cana-5596	62	16	evaluated	evaluate	VERB
cana-5596	62	17	:	:	PUNCT
cana-5596	62	18	communications	communication	NOUN
cana-5596	62	19	on	on	ADP
cana-5596	62	20	applied	apply	VERB
cana-5596	62	21	nonlinear	nonlinear	ADJ
cana-5596	62	22	analysis	analysis	NOUN
cana-5596	62	23	issn	issn	NOUN
cana-5596	62	24	:	:	PUNCT
cana-5596	62	25	1074	1074	NUM
cana-5596	62	26	-	-	PUNCT
cana-5596	62	27	133x	133x	NUM
cana-5596	62	28	vol	vol	NOUN
cana-5596	62	29	32	32	NUM
cana-5596	62	30	no	no	NOUN
cana-5596	62	31	.	.	PUNCT
cana-5596	63	1	icmasd	icmasd	NOUN
cana-5596	63	2	(	(	PUNCT
cana-5596	63	3	2025	2025	NUM
cana-5596	63	4	)	)	PUNCT
cana-5596	63	5	1967	1967	NUM
cana-5596	63	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	63	7	1	1	X
cana-5596	63	8	.	.	PUNCT
cana-5596	63	9	confusion	confusion	NOUN
cana-5596	63	10	matrix	matrix	NOUN
cana-5596	63	11	:	:	PUNCT
cana-5596	63	12	to	to	PART
cana-5596	63	13	analyze	analyze	VERB
cana-5596	63	14	true	true	ADJ
cana-5596	63	15	positives	positive	NOUN
cana-5596	63	16	,	,	PUNCT
cana-5596	63	17	false	false	ADJ
cana-5596	63	18	positives	positive	NOUN
cana-5596	63	19	,	,	PUNCT
cana-5596	63	20	and	and	CCONJ
cana-5596	63	21	false	false	ADJ
cana-5596	63	22	negatives	negative	NOUN
cana-5596	63	23	.	.	PUNCT
cana-5596	64	1	2	2	X
cana-5596	64	2	.	.	X
cana-5596	64	3	precision	precision	NOUN
cana-5596	64	4	,	,	PUNCT
cana-5596	64	5	recall	recall	NOUN
cana-5596	64	6	,	,	PUNCT
cana-5596	64	7	and	and	CCONJ
cana-5596	64	8	f1	f1	NOUN
cana-5596	64	9	-	-	PUNCT
cana-5596	64	10	score	score	NOUN
cana-5596	64	11	:	:	PUNCT
cana-5596	64	12	to	to	PART
cana-5596	64	13	provide	provide	VERB
cana-5596	64	14	a	a	DET
cana-5596	64	15	detailed	detailed	ADJ
cana-5596	64	16	performance	performance	NOUN
cana-5596	64	17	assessment	assessment	NOUN
cana-5596	64	18	across	across	ADP
cana-5596	64	19	different	different	ADJ
cana-5596	64	20	classes	class	NOUN
cana-5596	64	21	.	.	PUNCT
cana-5596	65	1	3	3	X
cana-5596	65	2	.	.	X
cana-5596	65	3	roc	roc	NOUN
cana-5596	65	4	-	-	PUNCT
cana-5596	65	5	auc	auc	NOUN
cana-5596	65	6	curve	curve	NOUN
cana-5596	65	7	:	:	PUNCT
cana-5596	65	8	to	to	PART
cana-5596	65	9	evaluate	evaluate	VERB
cana-5596	65	10	the	the	DET
cana-5596	65	11	model	model	NOUN
cana-5596	65	12	's	's	PART
cana-5596	65	13	ability	ability	NOUN
cana-5596	65	14	to	to	PART
cana-5596	65	15	distinguish	distinguish	VERB
cana-5596	65	16	between	between	ADP
cana-5596	65	17	benign	benign	ADJ
cana-5596	65	18	and	and	CCONJ
cana-5596	65	19	malignant	malignant	ADJ
cana-5596	65	20	cases	case	NOUN
cana-5596	65	21	.	.	PUNCT
cana-5596	66	1	figure	figure	NOUN
cana-5596	66	2	2	2	NUM
cana-5596	66	3	:	:	PUNCT
cana-5596	66	4	training	training	NOUN
cana-5596	66	5	and	and	CCONJ
cana-5596	66	6	validation	validation	NOUN
cana-5596	66	7	metrics	metric	NOUN
cana-5596	66	8	–	–	PUNCT
cana-5596	66	9	graphs	graph	VERB
cana-5596	66	10	showing	show	VERB
cana-5596	66	11	accuracy	accuracy	NOUN
cana-5596	66	12	and	and	CCONJ
cana-5596	66	13	loss	loss	NOUN
cana-5596	66	14	progression	progression	NOUN
cana-5596	66	15	during	during	ADP
cana-5596	66	16	training	training	NOUN
cana-5596	66	17	.	.	PUNCT
cana-5596	67	1	figure	figure	VERB
cana-5596	67	2	3	3	NUM
cana-5596	67	3	:	:	PUNCT
cana-5596	67	4	confusion	confusion	NOUN
cana-5596	67	5	matrix	matrix	NOUN
cana-5596	67	6	–	–	PUNCT
cana-5596	67	7	illustrates	illustrate	VERB
cana-5596	67	8	the	the	DET
cana-5596	67	9	classification	classification	NOUN
cana-5596	67	10	performance	performance	NOUN
cana-5596	67	11	for	for	ADP
cana-5596	67	12	benign	benign	ADJ
cana-5596	67	13	and	and	CCONJ
cana-5596	67	14	malignant	malignant	ADJ
cana-5596	67	15	cases	case	NOUN
cana-5596	67	16	.	.	PUNCT
cana-5596	68	1	3.5	3.5	NUM
cana-5596	68	2	critical	critical	ADJ
cana-5596	68	3	steps	step	NOUN
cana-5596	68	4	1	1	NUM
cana-5596	68	5	.	.	PUNCT
cana-5596	68	6	data	datum	NOUN
cana-5596	68	7	augmentation	augmentation	NOUN
cana-5596	68	8	:	:	PUNCT
cana-5596	68	9	ensuring	ensure	VERB
cana-5596	68	10	diversity	diversity	NOUN
cana-5596	68	11	in	in	ADP
cana-5596	68	12	training	training	NOUN
cana-5596	68	13	samples	sample	NOUN
cana-5596	68	14	was	be	AUX
cana-5596	68	15	critical	critical	ADJ
cana-5596	68	16	for	for	ADP
cana-5596	68	17	handling	handle	VERB
cana-5596	68	18	limited	limited	ADJ
cana-5596	68	19	data	datum	NOUN
cana-5596	68	20	.	.	PUNCT
cana-5596	69	1	2	2	X
cana-5596	69	2	.	.	PUNCT
cana-5596	69	3	model	model	NOUN
cana-5596	69	4	regularization	regularization	NOUN
cana-5596	69	5	:	:	PUNCT
cana-5596	69	6	dropout	dropout	NOUN
cana-5596	69	7	and	and	CCONJ
cana-5596	69	8	early	early	ADJ
cana-5596	69	9	stopping	stopping	NOUN
cana-5596	69	10	were	be	AUX
cana-5596	69	11	crucial	crucial	ADJ
cana-5596	69	12	in	in	ADP
cana-5596	69	13	reducing	reduce	VERB
cana-5596	69	14	overfitting	overfitte	VERB
cana-5596	69	15	on	on	ADP
cana-5596	69	16	the	the	DET
cana-5596	69	17	training	training	NOUN
cana-5596	69	18	set	set	NOUN
cana-5596	69	19	.	.	PUNCT
cana-5596	70	1	communications	communication	NOUN
cana-5596	70	2	on	on	ADP
cana-5596	70	3	applied	apply	VERB
cana-5596	70	4	nonlinear	nonlinear	ADJ
cana-5596	70	5	analysis	analysis	NOUN
cana-5596	70	6	issn	issn	NOUN
cana-5596	70	7	:	:	PUNCT
cana-5596	70	8	1074	1074	NUM
cana-5596	70	9	-	-	PUNCT
cana-5596	70	10	133x	133x	NUM
cana-5596	70	11	vol	vol	NOUN
cana-5596	70	12	32	32	NUM
cana-5596	70	13	no	no	NOUN
cana-5596	70	14	.	.	PUNCT
cana-5596	71	1	icmasd	icmasd	NOUN
cana-5596	71	2	(	(	PUNCT
cana-5596	71	3	2025	2025	NUM
cana-5596	71	4	)	)	PUNCT
cana-5596	71	5	1968	1968	NUM
cana-5596	71	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	71	7	3	3	X
cana-5596	71	8	.	.	X
cana-5596	71	9	hyperparameter	hyperparameter	NOUN
cana-5596	71	10	tuning	tuning	NOUN
cana-5596	71	11	:	:	PUNCT
cana-5596	71	12	grid	grid	NOUN
cana-5596	71	13	search	search	NOUN
cana-5596	71	14	was	be	AUX
cana-5596	71	15	performed	perform	VERB
cana-5596	71	16	to	to	PART
cana-5596	71	17	optimize	optimize	VERB
cana-5596	71	18	the	the	DET
cana-5596	71	19	learning	learning	NOUN
cana-5596	71	20	rate	rate	NOUN
cana-5596	71	21	and	and	CCONJ
cana-5596	71	22	architecture	architecture	NOUN
cana-5596	71	23	depth	depth	NOUN
cana-5596	71	24	.	.	PUNCT
cana-5596	72	1	model	model	NOUN
cana-5596	72	2	variant	variant	ADJ
cana-5596	72	3	accuracy	accuracy	NOUN
cana-5596	72	4	(	(	PUNCT
cana-5596	72	5	%	%	INTJ
cana-5596	72	6	)	)	PUNCT
cana-5596	72	7	training	training	NOUN
cana-5596	72	8	time	time	NOUN
cana-5596	72	9	(	(	PUNCT
cana-5596	72	10	min	min	NOUN
cana-5596	72	11	)	)	PUNCT
cana-5596	72	12	cnn	cnn	NOUN
cana-5596	72	13	with	with	ADP
cana-5596	72	14	dropout	dropout	NOUN
cana-5596	72	15	92	92	NUM
cana-5596	72	16	30	30	NUM
cana-5596	72	17	cnn	cnn	NOUN
cana-5596	72	18	without	without	ADP
cana-5596	72	19	dropout	dropout	NOUN
cana-5596	72	20	88	88	NUM
cana-5596	72	21	25	25	NUM
cana-5596	72	22	cnn	cnn	PROPN
cana-5596	72	23	with	with	ADP
cana-5596	72	24	data	datum	NOUN
cana-5596	72	25	augmentation	augmentation	NOUN
cana-5596	72	26	93	93	NUM
cana-5596	72	27	35	35	NUM
cana-5596	72	28	table	table	NOUN
cana-5596	72	29	2	2	NUM
cana-5596	72	30	ablation	ablation	NOUN
cana-5596	72	31	study	study	NOUN
cana-5596	72	32	results	result	VERB
cana-5596	72	33	3.6	3.6	NUM
cana-5596	72	34	reproducibility	reproducibility	NOUN
cana-5596	72	35	all	all	DET
cana-5596	72	36	experiments	experiment	NOUN
cana-5596	72	37	were	be	AUX
cana-5596	72	38	conducted	conduct	VERB
cana-5596	72	39	on	on	ADP
cana-5596	72	40	a	a	DET
cana-5596	72	41	system	system	NOUN
cana-5596	72	42	with	with	ADP
cana-5596	72	43	the	the	DET
cana-5596	72	44	following	follow	VERB
cana-5596	72	45	specifications	specification	NOUN
cana-5596	72	46	:	:	PUNCT
cana-5596	72	47	•	•	NUM
cana-5596	72	48	hardware	hardware	NOUN
cana-5596	72	49	:	:	PUNCT
cana-5596	72	50	nvidia	nvidia	PROPN
cana-5596	72	51	tesla	tesla	PROPN
cana-5596	72	52	v100	v100	PROPN
cana-5596	72	53	gpu	gpu	PROPN
cana-5596	72	54	,	,	PUNCT
cana-5596	72	55	32	32	NUM
cana-5596	72	56	gb	gb	NOUN
cana-5596	72	57	ram	ram	NOUN
cana-5596	72	58	.	.	PUNCT
cana-5596	73	1	•	•	NUM
cana-5596	73	2	software	software	NOUN
cana-5596	73	3	:	:	PUNCT
cana-5596	73	4	python	python	PROPN
cana-5596	73	5	3.8	3.8	NUM
cana-5596	73	6	,	,	PUNCT
cana-5596	73	7	tensorflow	tensorflow	NOUN
cana-5596	73	8	2.9	2.9	NUM
cana-5596	73	9	.	.	PUNCT
cana-5596	74	1	•	•	NOUN
cana-5596	74	2	codebase	codebase	ADJ
cana-5596	74	3	:	:	PUNCT
cana-5596	74	4	available	available	ADJ
cana-5596	74	5	at	at	ADP
cana-5596	74	6	google	google	PROPN
cana-5596	74	7	collaboratory	collaboratory	NOUN
cana-5596	74	8	[	[	X
cana-5596	74	9	‘	'	PUNCT
cana-5596	74	10	https://colab.research.google.com/drive/1ctyxp1pxxajzhldiatq7752rdzybhz-n	https://colab.research.google.com/drive/1ctyxp1pxxajzhldiatq7752rdzybhz-n	X
cana-5596	74	11	’	'	PUNCT
cana-5596	74	12	]	]	X
cana-5596	74	13	4	4	X
cana-5596	74	14	.	.	X
cana-5596	74	15	comparative	comparative	ADJ
cana-5596	74	16	study	study	NOUN
cana-5596	74	17	with	with	ADP
cana-5596	74	18	recent	recent	ADJ
cana-5596	74	19	publications	publication	NOUN
cana-5596	74	20	:	:	PUNCT
cana-5596	74	21	4.1	4.1	NUM
cana-5596	74	22	benchmarking	benchmarke	VERB
cana-5596	74	23	against	against	ADP
cana-5596	74	24	similar	similar	ADJ
cana-5596	74	25	studies	study	NOUN
cana-5596	74	26	a	a	DET
cana-5596	74	27	comparative	comparative	ADJ
cana-5596	74	28	analysis	analysis	NOUN
cana-5596	74	29	was	be	AUX
cana-5596	74	30	conducted	conduct	VERB
cana-5596	74	31	to	to	PART
cana-5596	74	32	evaluate	evaluate	VERB
cana-5596	74	33	the	the	DET
cana-5596	74	34	performance	performance	NOUN
cana-5596	74	35	of	of	ADP
cana-5596	74	36	the	the	DET
cana-5596	74	37	proposed	propose	VERB
cana-5596	74	38	cnn	cnn	PROPN
cana-5596	74	39	model	model	NOUN
cana-5596	74	40	against	against	ADP
cana-5596	74	41	other	other	ADJ
cana-5596	74	42	state	state	NOUN
cana-5596	74	43	-	-	PUNCT
cana-5596	74	44	of	of	ADP
cana-5596	74	45	-	-	PUNCT
cana-5596	74	46	the	the	DET
cana-5596	74	47	-	-	PUNCT
cana-5596	74	48	art	art	NOUN
cana-5596	74	49	methods	method	NOUN
cana-5596	74	50	for	for	ADP
cana-5596	74	51	cancer	cancer	NOUN
cana-5596	74	52	detection	detection	NOUN
cana-5596	74	53	and	and	CCONJ
cana-5596	74	54	staging	staging	NOUN
cana-5596	74	55	.	.	PUNCT
cana-5596	75	1	recent	recent	ADJ
cana-5596	75	2	publications	publication	NOUN
cana-5596	75	3	in	in	ADP
cana-5596	75	4	the	the	DET
cana-5596	75	5	field	field	NOUN
cana-5596	75	6	were	be	AUX
cana-5596	75	7	reviewed	review	VERB
cana-5596	75	8	,	,	PUNCT
cana-5596	75	9	focusing	focus	VERB
cana-5596	75	10	on	on	ADP
cana-5596	75	11	similar	similar	ADJ
cana-5596	75	12	objectives	objective	NOUN
cana-5596	75	13	:	:	PUNCT
cana-5596	75	14	•	•	NUM
cana-5596	75	15	gupta	gupta	NOUN
cana-5596	75	16	et	et	PROPN
cana-5596	75	17	al	al	PROPN
cana-5596	75	18	.	.	PROPN
cana-5596	76	1	(	(	PUNCT
cana-5596	76	2	2023	2023	NUM
cana-5596	76	3	):	):	PUNCT
cana-5596	76	4	"	"	PUNCT
cana-5596	76	5	deep	deep	ADJ
cana-5596	76	6	learning	learning	NOUN
cana-5596	76	7	for	for	ADP
cana-5596	76	8	histopathological	histopathological	ADJ
cana-5596	76	9	cancer	cancer	NOUN
cana-5596	76	10	diagnosis	diagnosis	NOUN
cana-5596	76	11	using	use	VERB
cana-5596	76	12	resnet	resnet	NOUN
cana-5596	76	13	"	"	PUNCT
cana-5596	76	14	reported	report	VERB
cana-5596	76	15	an	an	DET
cana-5596	76	16	89	89	NUM
cana-5596	76	17	%	%	NOUN
cana-5596	76	18	accuracy	accuracy	NOUN
cana-5596	76	19	for	for	ADP
cana-5596	76	20	binary	binary	ADJ
cana-5596	76	21	classification	classification	NOUN
cana-5596	76	22	tasks	task	NOUN
cana-5596	76	23	,	,	PUNCT
cana-5596	76	24	showcasing	showcase	VERB
cana-5596	76	25	theeffectiveness	theeffectiveness	NOUN
cana-5596	76	26	of	of	ADP
cana-5596	76	27	transfer	transfer	NOUN
cana-5596	76	28	learning	learning	NOUN
cana-5596	76	29	.	.	PUNCT
cana-5596	77	1	however	however	ADV
cana-5596	77	2	,	,	PUNCT
cana-5596	77	3	the	the	DET
cana-5596	77	4	study	study	NOUN
cana-5596	77	5	highlighted	highlight	VERB
cana-5596	77	6	computational	computational	ADJ
cana-5596	77	7	challenges	challenge	NOUN
cana-5596	77	8	associated	associate	VERB
cana-5596	77	9	with	with	ADP
cana-5596	77	10	finetuning	finetune	VERB
cana-5596	77	11	large	large	ADJ
cana-5596	77	12	pre	pre	ADJ
cana-5596	77	13	-	-	ADJ
cana-5596	77	14	trained	train	VERB
cana-5596	77	15	networks	network	NOUN
cana-5596	77	16	.	.	PUNCT
cana-5596	78	1	•	•	NUM
cana-5596	78	2	zhao	zhao	PROPN
cana-5596	78	3	et	et	PROPN
cana-5596	78	4	al	al	PROPN
cana-5596	78	5	.	.	PROPN
cana-5596	79	1	(	(	PUNCT
cana-5596	79	2	2022	2022	NUM
cana-5596	79	3	):	):	PUNCT
cana-5596	79	4	"	"	PUNCT
cana-5596	79	5	multi	multi	ADJ
cana-5596	79	6	-	-	ADJ
cana-5596	79	7	stage	stage	ADJ
cana-5596	79	8	detection	detection	NOUN
cana-5596	79	9	of	of	ADP
cana-5596	79	10	breast	breast	NOUN
cana-5596	79	11	cancer	cancer	NOUN
cana-5596	79	12	using	use	VERB
cana-5596	79	13	vgg16	vgg16	NOUN
cana-5596	79	14	and	and	CCONJ
cana-5596	79	15	feature	feature	NOUN
cana-5596	79	16	extraction	extraction	NOUN
cana-5596	79	17	"	"	PUNCT
cana-5596	79	18	achieved	achieve	VERB
cana-5596	79	19	a	a	DET
cana-5596	79	20	91	91	NUM
cana-5596	79	21	%	%	NOUN
cana-5596	79	22	accuracy	accuracy	NOUN
cana-5596	79	23	for	for	ADP
cana-5596	79	24	multi	multi	ADJ
cana-5596	79	25	-	-	ADJ
cana-5596	79	26	class	class	ADJ
cana-5596	79	27	classification	classification	NOUN
cana-5596	79	28	.	.	PUNCT
cana-5596	80	1	the	the	DET
cana-5596	80	2	authors	author	NOUN
cana-5596	80	3	emphasized	emphasize	VERB
cana-5596	80	4	the	the	DET
cana-5596	80	5	importance	importance	NOUN
cana-5596	80	6	of	of	ADP
cana-5596	80	7	advanced	advanced	ADJ
cana-5596	80	8	data	datum	NOUN
cana-5596	80	9	augmentation	augmentation	NOUN
cana-5596	80	10	techniques	technique	NOUN
cana-5596	80	11	in	in	ADP
cana-5596	80	12	enhancing	enhance	VERB
cana-5596	80	13	model	model	NOUN
cana-5596	80	14	performance	performance	NOUN
cana-5596	80	15	.	.	PUNCT
cana-5596	81	1	in	in	ADP
cana-5596	81	2	comparison	comparison	NOUN
cana-5596	81	3	,	,	PUNCT
cana-5596	81	4	the	the	DET
cana-5596	81	5	proposed	propose	VERB
cana-5596	81	6	cnn	cnn	PROPN
cana-5596	81	7	achieved	achieve	VERB
cana-5596	81	8	92	92	NUM
cana-5596	81	9	%	%	NOUN
cana-5596	81	10	accuracy	accuracy	NOUN
cana-5596	81	11	with	with	ADP
cana-5596	81	12	significantly	significantly	ADV
cana-5596	81	13	fewer	few	ADJ
cana-5596	81	14	computational	computational	ADJ
cana-5596	81	15	resources	resource	NOUN
cana-5596	81	16	.	.	PUNCT
cana-5596	82	1	by	by	ADP
cana-5596	82	2	utilizing	utilize	VERB
cana-5596	82	3	custom	custom	NOUN
cana-5596	82	4	architecture	architecture	NOUN
cana-5596	82	5	tailored	tailor	VERB
cana-5596	82	6	to	to	ADP
cana-5596	82	7	histopathological	histopathological	ADJ
cana-5596	82	8	images	image	NOUN
cana-5596	82	9	,	,	PUNCT
cana-5596	82	10	our	our	PRON
cana-5596	82	11	model	model	NOUN
cana-5596	82	12	outperformed	outperform	VERB
cana-5596	82	13	these	these	DET
cana-5596	82	14	methods	method	NOUN
cana-5596	82	15	in	in	ADP
cana-5596	82	16	accuracy	accuracy	NOUN
cana-5596	82	17	and	and	CCONJ
cana-5596	82	18	robustness	robustness	NOUN
cana-5596	82	19	.	.	PUNCT
cana-5596	83	1	moreover	moreover	ADV
cana-5596	83	2	,	,	PUNCT
cana-5596	83	3	its	its	PRON
cana-5596	83	4	ability	ability	NOUN
cana-5596	83	5	to	to	PART
cana-5596	83	6	classify	classify	VERB
cana-5596	83	7	multiple	multiple	ADJ
cana-5596	83	8	cancer	cancer	NOUN
cana-5596	83	9	stages	stage	NOUN
cana-5596	83	10	adds	add	VERB
cana-5596	83	11	granularity	granularity	NOUN
cana-5596	83	12	absent	absent	ADJ
cana-5596	83	13	in	in	ADP
cana-5596	83	14	most	most	ADJ
cana-5596	83	15	previous	previous	ADJ
cana-5596	83	16	https://colab.research.google.com/drive/1ctyxp1pxxajzhldiatq7752rdzybhz-n	https://colab.research.google.com/drive/1ctyxp1pxxajzhldiatq7752rdzybhz-n	PROPN
cana-5596	83	17	communications	communication	NOUN
cana-5596	83	18	on	on	ADP
cana-5596	83	19	applied	apply	VERB
cana-5596	83	20	nonlinear	nonlinear	ADJ
cana-5596	83	21	analysis	analysis	NOUN
cana-5596	83	22	issn	issn	NOUN
cana-5596	83	23	:	:	PUNCT
cana-5596	83	24	1074	1074	NUM
cana-5596	83	25	-	-	PUNCT
cana-5596	83	26	133x	133x	NUM
cana-5596	83	27	vol	vol	NOUN
cana-5596	83	28	32	32	NUM
cana-5596	83	29	no	no	NOUN
cana-5596	83	30	.	.	PUNCT
cana-5596	84	1	icmasd	icmasd	NOUN
cana-5596	84	2	(	(	PUNCT
cana-5596	84	3	2025	2025	NUM
cana-5596	84	4	)	)	PUNCT
cana-5596	84	5	1969	1969	NUM
cana-5596	84	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	84	7	studies	study	NOUN
cana-5596	84	8	.	.	PUNCT
cana-5596	85	1	4.2	4.2	NUM
cana-5596	85	2	advancements	advancement	NOUN
cana-5596	85	3	in	in	ADP
cana-5596	85	4	data	datum	NOUN
cana-5596	85	5	preprocessing	preprocessing	NOUN
cana-5596	85	6	and	and	CCONJ
cana-5596	85	7	augmentation	augmentation	NOUN
cana-5596	85	8	data	datum	NOUN
cana-5596	85	9	preprocessing	preprocessing	NOUN
cana-5596	85	10	and	and	CCONJ
cana-5596	85	11	augmentation	augmentation	NOUN
cana-5596	85	12	were	be	AUX
cana-5596	85	13	critical	critical	ADJ
cana-5596	85	14	for	for	ADP
cana-5596	85	15	the	the	DET
cana-5596	85	16	success	success	NOUN
cana-5596	85	17	of	of	ADP
cana-5596	85	18	the	the	DET
cana-5596	85	19	proposed	propose	VERB
cana-5596	85	20	method	method	NOUN
cana-5596	85	21	.	.	PUNCT
cana-5596	86	1	recent	recent	ADJ
cana-5596	86	2	studies	study	NOUN
cana-5596	86	3	have	have	AUX
cana-5596	86	4	also	also	ADV
cana-5596	86	5	focused	focus	VERB
cana-5596	86	6	on	on	ADP
cana-5596	86	7	these	these	DET
cana-5596	86	8	aspects	aspect	NOUN
cana-5596	86	9	:	:	PUNCT
cana-5596	86	10	•	•	NUM
cana-5596	86	11	jiang	jiang	PROPN
cana-5596	86	12	et	et	PROPN
cana-5596	86	13	al	al	PROPN
cana-5596	86	14	.	.	PROPN
cana-5596	87	1	(	(	PUNCT
cana-5596	87	2	2022	2022	NUM
cana-5596	87	3	):	):	PUNCT
cana-5596	87	4	"	"	PUNCT
cana-5596	87	5	gan	gin	VERB
cana-5596	87	6	-	-	PUNCT
cana-5596	87	7	based	base	VERB
cana-5596	87	8	data	datum	NOUN
cana-5596	87	9	augmentation	augmentation	NOUN
cana-5596	87	10	for	for	ADP
cana-5596	87	11	rare	rare	ADJ
cana-5596	87	12	cancer	cancer	NOUN
cana-5596	87	13	stages	stage	NOUN
cana-5596	87	14	"	"	PUNCT
cana-5596	87	15	utilized	utilize	VERB
cana-5596	87	16	generative	generative	ADJ
cana-5596	87	17	adversarial	adversarial	ADJ
cana-5596	87	18	networks	network	NOUN
cana-5596	87	19	to	to	PART
cana-5596	87	20	synthesize	synthesize	VERB
cana-5596	87	21	minority	minority	NOUN
cana-5596	87	22	-	-	PUNCT
cana-5596	87	23	class	class	NOUN
cana-5596	87	24	samples	sample	NOUN
cana-5596	87	25	,	,	PUNCT
cana-5596	87	26	resulting	result	VERB
cana-5596	87	27	in	in	ADP
cana-5596	87	28	a	a	DET
cana-5596	87	29	7	7	NUM
cana-5596	87	30	%	%	NOUN
cana-5596	87	31	improvement	improvement	NOUN
cana-5596	87	32	in	in	ADP
cana-5596	87	33	classification	classification	NOUN
cana-5596	87	34	accuracy	accuracy	NOUN
cana-5596	87	35	.	.	PUNCT
cana-5596	88	1	the	the	DET
cana-5596	88	2	current	current	ADJ
cana-5596	88	3	project	project	NOUN
cana-5596	88	4	adopted	adopt	VERB
cana-5596	88	5	simpler	simple	ADJ
cana-5596	88	6	yet	yet	CCONJ
cana-5596	88	7	effective	effective	ADJ
cana-5596	88	8	augmentation	augmentation	NOUN
cana-5596	88	9	techniques	technique	NOUN
cana-5596	88	10	,	,	PUNCT
cana-5596	88	11	such	such	ADJ
cana-5596	88	12	as	as	ADP
cana-5596	88	13	random	random	ADJ
cana-5596	88	14	rotations	rotation	NOUN
cana-5596	88	15	,	,	PUNCT
cana-5596	88	16	flips	flip	VERB
cana-5596	88	17	,	,	PUNCT
cana-5596	88	18	and	and	CCONJ
cana-5596	88	19	contrast	contrast	NOUN
cana-5596	88	20	adjustments	adjustment	NOUN
cana-5596	88	21	,	,	PUNCT
cana-5596	88	22	to	to	PART
cana-5596	88	23	improve	improve	VERB
cana-5596	88	24	data	datum	NOUN
cana-5596	88	25	diversity	diversity	NOUN
cana-5596	88	26	.	.	PUNCT
cana-5596	89	1	while	while	SCONJ
cana-5596	89	2	gan	gan	NOUN
cana-5596	89	3	-	-	PUNCT
cana-5596	89	4	based	base	VERB
cana-5596	89	5	methods	method	NOUN
cana-5596	89	6	could	could	AUX
cana-5596	89	7	further	far	ADV
cana-5596	89	8	enhance	enhance	VERB
cana-5596	89	9	performance	performance	NOUN
cana-5596	89	10	,	,	PUNCT
cana-5596	89	11	the	the	DET
cana-5596	89	12	chosen	choose	VERB
cana-5596	89	13	techniques	technique	NOUN
cana-5596	89	14	were	be	AUX
cana-5596	89	15	computationally	computationally	ADV
cana-5596	89	16	efficient	efficient	ADJ
cana-5596	89	17	and	and	CCONJ
cana-5596	89	18	sufficient	sufficient	ADJ
cana-5596	89	19	for	for	ADP
cana-5596	89	20	the	the	DET
cana-5596	89	21	dataset	dataset	NOUN
cana-5596	89	22	’s	’s	PART
cana-5596	89	23	characteristics	characteristic	NOUN
cana-5596	89	24	.	.	PUNCT
cana-5596	90	1	5	5	X
cana-5596	90	2	.	.	X
cana-5596	90	3	challenges	challenge	NOUN
cana-5596	90	4	in	in	ADP
cana-5596	90	5	ai	ai	ADJ
cana-5596	90	6	-	-	PUNCT
cana-5596	90	7	driven	drive	VERB
cana-5596	90	8	cancer	cancer	NOUN
cana-5596	90	9	detection	detection	NOUN
cana-5596	90	10	:	:	PUNCT
cana-5596	90	11	5.1	5.1	NUM
cana-5596	90	12	technical	technical	ADJ
cana-5596	90	13	limitations	limitation	NOUN
cana-5596	90	14	despite	despite	SCONJ
cana-5596	90	15	its	its	PRON
cana-5596	90	16	strong	strong	ADJ
cana-5596	90	17	performance	performance	NOUN
cana-5596	90	18	,	,	PUNCT
cana-5596	90	19	the	the	DET
cana-5596	90	20	proposed	propose	VERB
cana-5596	90	21	model	model	NOUN
cana-5596	90	22	faced	face	VERB
cana-5596	90	23	several	several	ADJ
cana-5596	90	24	challenges	challenge	NOUN
cana-5596	90	25	:	:	PUNCT
cana-5596	90	26	•	•	NUM
cana-5596	90	27	dataset	dataset	ADJ
cana-5596	90	28	imbalance	imbalance	NOUN
cana-5596	90	29	:	:	PUNCT
cana-5596	90	30	as	as	ADP
cana-5596	90	31	with	with	ADP
cana-5596	90	32	most	most	ADJ
cana-5596	90	33	medical	medical	ADJ
cana-5596	90	34	imaging	imaging	NOUN
cana-5596	90	35	datasets	dataset	NOUN
cana-5596	90	36	,	,	PUNCT
cana-5596	90	37	an	an	DET
cana-5596	90	38	uneven	uneven	ADJ
cana-5596	90	39	distribution	distribution	NOUN
cana-5596	90	40	of	of	ADP
cana-5596	90	41	samples	sample	NOUN
cana-5596	90	42	across	across	ADP
cana-5596	90	43	classes	class	NOUN
cana-5596	90	44	impacted	impact	VERB
cana-5596	90	45	the	the	DET
cana-5596	90	46	model	model	NOUN
cana-5596	90	47	’s	’s	PART
cana-5596	90	48	ability	ability	NOUN
cana-5596	90	49	to	to	PART
cana-5596	90	50	generalize	generalize	VERB
cana-5596	90	51	for	for	ADP
cana-5596	90	52	rare	rare	ADJ
cana-5596	90	53	cancer	cancer	NOUN
cana-5596	90	54	stages	stage	NOUN
cana-5596	90	55	.	.	PUNCT
cana-5596	91	1	while	while	SCONJ
cana-5596	91	2	oversampling	oversample	VERB
cana-5596	91	3	and	and	CCONJ
cana-5596	91	4	augmentation	augmentation	NOUN
cana-5596	91	5	partially	partially	ADV
cana-5596	91	6	addressed	address	VERB
cana-5596	91	7	this	this	DET
cana-5596	91	8	issue	issue	NOUN
cana-5596	91	9	,	,	PUNCT
cana-5596	91	10	further	further	ADJ
cana-5596	91	11	improvements	improvement	NOUN
cana-5596	91	12	could	could	AUX
cana-5596	91	13	involve	involve	VERB
cana-5596	91	14	synthetic	synthetic	ADJ
cana-5596	91	15	data	datum	NOUN
cana-5596	91	16	generation	generation	NOUN
cana-5596	91	17	or	or	CCONJ
cana-5596	91	18	advanced	advanced	ADJ
cana-5596	91	19	sampling	sampling	NOUN
cana-5596	91	20	techniques	technique	NOUN
cana-5596	91	21	.	.	PUNCT
cana-5596	92	1	•	•	NOUN
cana-5596	92	2	overfitting	overfitte	VERB
cana-5596	92	3	risk	risk	NOUN
cana-5596	92	4	:	:	PUNCT
cana-5596	92	5	training	training	NOUN
cana-5596	92	6	on	on	ADP
cana-5596	92	7	limited	limited	ADJ
cana-5596	92	8	data	datum	NOUN
cana-5596	92	9	posed	pose	VERB
cana-5596	92	10	a	a	DET
cana-5596	92	11	risk	risk	NOUN
cana-5596	92	12	of	of	ADP
cana-5596	92	13	overfitting	overfitte	VERB
cana-5596	92	14	,	,	PUNCT
cana-5596	92	15	mitigated	mitigate	VERB
cana-5596	92	16	by	by	ADP
cana-5596	92	17	employing	employ	VERB
cana-5596	92	18	dropout	dropout	ADJ
cana-5596	92	19	layers	layer	NOUN
cana-5596	92	20	,	,	PUNCT
cana-5596	92	21	early	early	ADJ
cana-5596	92	22	stopping	stopping	NOUN
cana-5596	92	23	,	,	PUNCT
cana-5596	92	24	and	and	CCONJ
cana-5596	92	25	a	a	DET
cana-5596	92	26	moderate	moderate	ADJ
cana-5596	92	27	architecture	architecture	NOUN
cana-5596	92	28	complexity	complexity	NOUN
cana-5596	92	29	.	.	PUNCT
cana-5596	93	1	•	•	ADJ
cana-5596	93	2	computational	computational	ADJ
cana-5596	93	3	demand	demand	NOUN
cana-5596	93	4	:	:	PUNCT
cana-5596	93	5	training	training	NOUN
cana-5596	93	6	required	require	VERB
cana-5596	93	7	high	high	ADJ
cana-5596	93	8	-	-	PUNCT
cana-5596	93	9	performance	performance	NOUN
cana-5596	93	10	gpus	gpu	NOUN
cana-5596	93	11	,	,	PUNCT
cana-5596	93	12	which	which	PRON
cana-5596	93	13	may	may	AUX
cana-5596	93	14	limit	limit	VERB
cana-5596	93	15	the	the	DET
cana-5596	93	16	model	model	NOUN
cana-5596	93	17	’s	’s	PART
cana-5596	93	18	accessibility	accessibility	NOUN
cana-5596	93	19	for	for	ADP
cana-5596	93	20	researchers	researcher	NOUN
cana-5596	93	21	and	and	CCONJ
cana-5596	93	22	healthcare	healthcare	NOUN
cana-5596	93	23	institutions	institution	NOUN
cana-5596	93	24	with	with	ADP
cana-5596	93	25	constrained	constrained	ADJ
cana-5596	93	26	resources	resource	NOUN
cana-5596	93	27	.	.	PUNCT
cana-5596	94	1	5.2	5.2	NUM
cana-5596	94	2	ethical	ethical	ADJ
cana-5596	94	3	considerations	consideration	NOUN
cana-5596	94	4	the	the	DET
cana-5596	94	5	deployment	deployment	NOUN
cana-5596	94	6	of	of	ADP
cana-5596	94	7	ai	ai	PROPN
cana-5596	94	8	models	model	NOUN
cana-5596	94	9	in	in	ADP
cana-5596	94	10	healthcare	healthcare	NOUN
cana-5596	94	11	raises	raise	VERB
cana-5596	94	12	several	several	ADJ
cana-5596	94	13	ethical	ethical	ADJ
cana-5596	94	14	concerns	concern	NOUN
cana-5596	94	15	:	:	PUNCT
cana-5596	94	16	•	•	NUM
cana-5596	94	17	data	data	NOUN
cana-5596	94	18	privacy	privacy	NOUN
cana-5596	94	19	:	:	PUNCT
cana-5596	94	20	patient	patient	ADJ
cana-5596	94	21	data	datum	NOUN
cana-5596	94	22	confidentiality	confidentiality	NOUN
cana-5596	94	23	is	be	AUX
cana-5596	94	24	paramount	paramount	ADJ
cana-5596	94	25	.	.	PUNCT
cana-5596	95	1	federated	federated	ADJ
cana-5596	95	2	learning	learning	NOUN
cana-5596	95	3	or	or	CCONJ
cana-5596	95	4	differential	differential	VERB
cana-5596	95	5	privacy	privacy	NOUN
cana-5596	95	6	methods	method	NOUN
cana-5596	95	7	could	could	AUX
cana-5596	95	8	be	be	AUX
cana-5596	95	9	explored	explore	VERB
cana-5596	95	10	to	to	PART
cana-5596	95	11	train	train	VERB
cana-5596	95	12	models	model	NOUN
cana-5596	95	13	without	without	ADP
cana-5596	95	14	compromising	compromise	VERB
cana-5596	95	15	data	datum	NOUN
cana-5596	95	16	security	security	NOUN
cana-5596	95	17	.	.	PUNCT
cana-5596	96	1	•	•	NUM
cana-5596	96	2	bias	bias	NOUN
cana-5596	96	3	in	in	ADP
cana-5596	96	4	predictions	prediction	NOUN
cana-5596	96	5	:	:	PUNCT
cana-5596	96	6	the	the	DET
cana-5596	96	7	model	model	NOUN
cana-5596	96	8	’s	’s	PART
cana-5596	96	9	performance	performance	NOUN
cana-5596	96	10	across	across	ADP
cana-5596	96	11	diverse	diverse	ADJ
cana-5596	96	12	demographic	demographic	ADJ
cana-5596	96	13	groups	group	NOUN
cana-5596	96	14	must	must	AUX
cana-5596	96	15	be	be	AUX
cana-5596	96	16	evaluated	evaluate	VERB
cana-5596	96	17	to	to	PART
cana-5596	96	18	ensure	ensure	VERB
cana-5596	96	19	fairness	fairness	NOUN
cana-5596	96	20	and	and	CCONJ
cana-5596	96	21	minimize	minimize	VERB
cana-5596	96	22	bias	bias	NOUN
cana-5596	96	23	,	,	PUNCT
cana-5596	96	24	as	as	SCONJ
cana-5596	96	25	discussed	discuss	VERB
cana-5596	96	26	by	by	ADP
cana-5596	96	27	smith	smith	PROPN
cana-5596	96	28	et	et	PROPN
cana-5596	96	29	al	al	PROPN
cana-5596	96	30	.	.	PROPN
cana-5596	97	1	(	(	PUNCT
cana-5596	97	2	2023	2023	NUM
cana-5596	97	3	)	)	PUNCT
cana-5596	97	4	in	in	ADP
cana-5596	97	5	"	"	PUNCT
cana-5596	97	6	ethical	ethical	ADJ
cana-5596	97	7	implications	implication	NOUN
cana-5596	97	8	of	of	ADP
cana-5596	97	9	ai	ai	VERB
cana-5596	97	10	in	in	ADP
cana-5596	97	11	healthcare	healthcare	NOUN
cana-5596	97	12	.	.	PUNCT
cana-5596	97	13	"	"	PUNCT
cana-5596	98	1	communications	communication	NOUN
cana-5596	98	2	on	on	ADP
cana-5596	98	3	applied	apply	VERB
cana-5596	98	4	nonlinear	nonlinear	ADJ
cana-5596	98	5	analysis	analysis	NOUN
cana-5596	98	6	issn	issn	NOUN
cana-5596	98	7	:	:	PUNCT
cana-5596	98	8	1074	1074	NUM
cana-5596	98	9	-	-	PUNCT
cana-5596	98	10	133x	133x	NUM
cana-5596	98	11	vol	vol	NOUN
cana-5596	98	12	32	32	NUM
cana-5596	98	13	no	no	NOUN
cana-5596	98	14	.	.	PUNCT
cana-5596	99	1	icmasd	icmasd	NOUN
cana-5596	99	2	(	(	PUNCT
cana-5596	99	3	2025	2025	NUM
cana-5596	99	4	)	)	PUNCT
cana-5596	99	5	1970	1970	NUM
cana-5596	99	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	99	7	6	6	X
cana-5596	99	8	.	.	PUNCT
cana-5596	100	1	deployment	deployment	NOUN
cana-5596	100	2	feasibility	feasibility	NOUN
cana-5596	100	3	:	:	PUNCT
cana-5596	100	4	6.1	6.1	NUM
cana-5596	100	5	model	model	NOUN
cana-5596	100	6	deployment	deployment	NOUN
cana-5596	100	7	in	in	ADP
cana-5596	100	8	clinical	clinical	ADJ
cana-5596	100	9	settings	setting	NOUN
cana-5596	100	10	for	for	ADP
cana-5596	100	11	real	real	ADJ
cana-5596	100	12	-	-	PUNCT
cana-5596	100	13	world	world	NOUN
cana-5596	100	14	application	application	NOUN
cana-5596	100	15	,	,	PUNCT
cana-5596	100	16	integrating	integrate	VERB
cana-5596	100	17	the	the	DET
cana-5596	100	18	proposed	propose	VERB
cana-5596	100	19	model	model	NOUN
cana-5596	100	20	into	into	ADP
cana-5596	100	21	clinical	clinical	ADJ
cana-5596	100	22	workflows	workflow	NOUN
cana-5596	100	23	is	be	AUX
cana-5596	100	24	crucial	crucial	ADJ
cana-5596	100	25	.	.	PUNCT
cana-5596	101	1	this	this	PRON
cana-5596	101	2	involves	involve	VERB
cana-5596	101	3	:	:	PUNCT
cana-5596	101	4	•	•	NUM
cana-5596	101	5	integration	integration	NOUN
cana-5596	101	6	with	with	ADP
cana-5596	101	7	existing	exist	VERB
cana-5596	101	8	systems	system	NOUN
cana-5596	101	9	:	:	PUNCT
cana-5596	101	10	the	the	DET
cana-5596	101	11	model	model	NOUN
cana-5596	101	12	can	can	AUX
cana-5596	101	13	be	be	AUX
cana-5596	101	14	integrated	integrate	VERB
cana-5596	101	15	with	with	ADP
cana-5596	101	16	hospital	hospital	NOUN
cana-5596	101	17	picture	picture	NOUN
cana-5596	101	18	archiving	archive	VERB
cana-5596	101	19	and	and	CCONJ
cana-5596	101	20	communication	communication	NOUN
cana-5596	101	21	systems	system	NOUN
cana-5596	101	22	(	(	PUNCT
cana-5596	101	23	pacs	pac	NOUN
cana-5596	101	24	)	)	PUNCT
cana-5596	101	25	and	and	CCONJ
cana-5596	101	26	electronic	electronic	ADJ
cana-5596	101	27	health	health	NOUN
cana-5596	101	28	records	record	NOUN
cana-5596	101	29	(	(	PUNCT
cana-5596	101	30	ehrs	ehrs	INTJ
cana-5596	101	31	)	)	PUNCT
cana-5596	101	32	to	to	PART
cana-5596	101	33	streamline	streamline	VERB
cana-5596	101	34	diagnostic	diagnostic	ADJ
cana-5596	101	35	workflows	workflow	NOUN
cana-5596	101	36	.	.	PUNCT
cana-5596	102	1	•	•	NUM
cana-5596	102	2	interpretability	interpretability	NOUN
cana-5596	102	3	:	:	PUNCT
cana-5596	102	4	providing	provide	VERB
cana-5596	102	5	explainable	explainable	ADJ
cana-5596	102	6	predictions	prediction	NOUN
cana-5596	102	7	using	use	VERB
cana-5596	102	8	techniques	technique	NOUN
cana-5596	102	9	like	like	ADP
cana-5596	102	10	grad	grad	NOUN
cana-5596	102	11	-	-	PUNCT
cana-5596	102	12	cam	cam	NOUN
cana-5596	102	13	helps	help	VERB
cana-5596	102	14	radiologists	radiologist	NOUN
cana-5596	102	15	understand	understand	VERB
cana-5596	102	16	the	the	DET
cana-5596	102	17	model	model	NOUN
cana-5596	102	18	’s	’s	PART
cana-5596	102	19	focus	focus	NOUN
cana-5596	102	20	areas	area	NOUN
cana-5596	102	21	,	,	PUNCT
cana-5596	102	22	fostering	foster	VERB
cana-5596	102	23	trust	trust	NOUN
cana-5596	102	24	.	.	PUNCT
cana-5596	103	1	figure	figure	NOUN
cana-5596	103	2	4(a	4(a	NUM
cana-5596	103	3	):	):	PUNCT
cana-5596	103	4	benign	benign	ADJ
cana-5596	103	5	case	case	NOUN
cana-5596	103	6	figure	figure	NOUN
cana-5596	103	7	4(b	4(b	NUM
cana-5596	103	8	)	)	PUNCT
cana-5596	103	9	:	:	PUNCT
cana-5596	103	10	malignant	malignant	ADJ
cana-5596	103	11	case	case	NOUN
cana-5596	103	12	figure	figure	NOUN
cana-5596	103	13	4	4	NUM
cana-5596	103	14	:	:	PUNCT
cana-5596	103	15	grad	grad	ADJ
cana-5596	103	16	-	-	PUNCT
cana-5596	103	17	cam	cam	NOUN
cana-5596	103	18	visualization	visualization	NOUN
cana-5596	103	19	–	–	PUNCT
cana-5596	103	20	two	two	NUM
cana-5596	103	21	visualizations	visualization	NOUN
cana-5596	103	22	showing	show	VERB
cana-5596	103	23	attention	attention	NOUN
cana-5596	103	24	maps	map	NOUN
cana-5596	103	25	for	for	ADP
cana-5596	103	26	benign	benign	ADJ
cana-5596	103	27	and	and	CCONJ
cana-5596	103	28	malignant	malignant	ADJ
cana-5596	103	29	samples	sample	NOUN
cana-5596	103	30	.	.	PUNCT
cana-5596	104	1	6.2	6.2	NUM
cana-5596	104	2	scalability	scalability	NOUN
cana-5596	104	3	for	for	ADP
cana-5596	104	4	resource	resource	NOUN
cana-5596	104	5	-	-	PUNCT
cana-5596	104	6	constrained	constrain	VERB
cana-5596	104	7	environments	environment	NOUN
cana-5596	104	8	scalability	scalability	NOUN
cana-5596	104	9	is	be	AUX
cana-5596	104	10	essential	essential	ADJ
cana-5596	104	11	for	for	ADP
cana-5596	104	12	deployment	deployment	NOUN
cana-5596	104	13	in	in	ADP
cana-5596	104	14	low	low	ADJ
cana-5596	104	15	-	-	PUNCT
cana-5596	104	16	resource	resource	NOUN
cana-5596	104	17	settings	setting	NOUN
cana-5596	104	18	.	.	PUNCT
cana-5596	105	1	lightweight	lightweight	ADJ
cana-5596	105	2	versions	version	NOUN
cana-5596	105	3	of	of	ADP
cana-5596	105	4	the	the	DET
cana-5596	105	5	model	model	NOUN
cana-5596	105	6	could	could	AUX
cana-5596	105	7	be	be	AUX
cana-5596	105	8	developed	develop	VERB
cana-5596	105	9	using	use	VERB
cana-5596	105	10	:	:	PUNCT
cana-5596	105	11	•	•	NUM
cana-5596	105	12	model	model	NOUN
cana-5596	105	13	pruning	pruning	NOUN
cana-5596	105	14	and	and	CCONJ
cana-5596	105	15	quantization	quantization	NOUN
cana-5596	105	16	:	:	PUNCT
cana-5596	105	17	to	to	PART
cana-5596	105	18	reduce	reduce	VERB
cana-5596	105	19	the	the	DET
cana-5596	105	20	computational	computational	ADJ
cana-5596	105	21	load	load	NOUN
cana-5596	105	22	without	without	ADP
cana-5596	105	23	significant	significant	ADJ
cana-5596	105	24	loss	loss	NOUN
cana-5596	105	25	in	in	ADP
cana-5596	105	26	accuracy	accuracy	NOUN
cana-5596	105	27	.	.	PUNCT
cana-5596	106	1	•	•	NUM
cana-5596	106	2	cloud	cloud	NOUN
cana-5596	106	3	and	and	CCONJ
cana-5596	106	4	edge	edge	NOUN
cana-5596	106	5	solutions	solution	NOUN
cana-5596	106	6	:	:	PUNCT
cana-5596	106	7	cloud	cloud	NOUN
cana-5596	106	8	-	-	PUNCT
cana-5596	106	9	based	base	VERB
cana-5596	106	10	deployment	deployment	NOUN
cana-5596	106	11	for	for	ADP
cana-5596	106	12	resource	resource	NOUN
cana-5596	106	13	-	-	PUNCT
cana-5596	106	14	rich	rich	ADJ
cana-5596	106	15	settings	setting	NOUN
cana-5596	106	16	and	and	CCONJ
cana-5596	106	17	edgebased	edgebase	VERB
cana-5596	106	18	deployment	deployment	NOUN
cana-5596	106	19	for	for	ADP
cana-5596	106	20	rural	rural	ADJ
cana-5596	106	21	clinics	clinic	NOUN
cana-5596	106	22	could	could	AUX
cana-5596	106	23	cater	cater	VERB
cana-5596	106	24	to	to	PART
cana-5596	106	25	diverse	diverse	VERB
cana-5596	106	26	infrastructure	infrastructure	NOUN
cana-5596	106	27	capabilities	capability	NOUN
cana-5596	106	28	.	.	PUNCT
cana-5596	107	1	7	7	X
cana-5596	107	2	.	.	X
cana-5596	107	3	explainability	explainability	NOUN
cana-5596	107	4	and	and	CCONJ
cana-5596	107	5	model	model	NOUN
cana-5596	107	6	interpretability	interpretability	NOUN
cana-5596	107	7	:	:	PUNCT
cana-5596	107	8	7.1	7.1	NUM
cana-5596	107	9	importance	importance	NOUN
cana-5596	107	10	of	of	ADP
cana-5596	107	11	explainability	explainability	NOUN
cana-5596	107	12	in	in	ADP
cana-5596	107	13	medical	medical	ADJ
cana-5596	107	14	ai	ai	PROPN
cana-5596	107	15	explainability	explainability	NOUN
cana-5596	107	16	is	be	AUX
cana-5596	107	17	critical	critical	ADJ
cana-5596	107	18	in	in	ADP
cana-5596	107	19	building	build	VERB
cana-5596	107	20	trust	trust	NOUN
cana-5596	107	21	with	with	ADP
cana-5596	107	22	healthcare	healthcare	NOUN
cana-5596	107	23	professionals	professional	NOUN
cana-5596	107	24	.	.	PUNCT
cana-5596	108	1	communications	communication	NOUN
cana-5596	108	2	on	on	ADP
cana-5596	108	3	applied	apply	VERB
cana-5596	108	4	nonlinear	nonlinear	ADJ
cana-5596	108	5	analysis	analysis	NOUN
cana-5596	108	6	issn	issn	NOUN
cana-5596	108	7	:	:	PUNCT
cana-5596	108	8	1074	1074	NUM
cana-5596	108	9	-	-	PUNCT
cana-5596	108	10	133x	133x	NUM
cana-5596	108	11	vol	vol	NOUN
cana-5596	108	12	32	32	NUM
cana-5596	108	13	no	no	NOUN
cana-5596	108	14	.	.	PUNCT
cana-5596	109	1	icmasd	icmasd	NOUN
cana-5596	109	2	(	(	PUNCT
cana-5596	109	3	2025	2025	NUM
cana-5596	109	4	)	)	PUNCT
cana-5596	109	5	1971	1971	NUM
cana-5596	109	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	110	1	the	the	DET
cana-5596	110	2	use	use	NOUN
cana-5596	110	3	of	of	ADP
cana-5596	110	4	grad	grad	NOUN
cana-5596	110	5	-	-	PUNCT
cana-5596	110	6	cam	cam	NOUN
cana-5596	110	7	enabled	enable	VERB
cana-5596	110	8	the	the	DET
cana-5596	110	9	visualization	visualization	NOUN
cana-5596	110	10	of	of	ADP
cana-5596	110	11	image	image	NOUN
cana-5596	110	12	regions	region	NOUN
cana-5596	110	13	contributing	contribute	VERB
cana-5596	110	14	most	most	ADV
cana-5596	110	15	significantly	significantly	ADV
cana-5596	110	16	to	to	ADP
cana-5596	110	17	predictions	prediction	NOUN
cana-5596	110	18	.	.	PUNCT
cana-5596	111	1	this	this	DET
cana-5596	111	2	approach	approach	NOUN
cana-5596	111	3	aligns	align	VERB
cana-5596	111	4	with	with	ADP
cana-5596	111	5	the	the	DET
cana-5596	111	6	findings	finding	NOUN
cana-5596	111	7	of	of	ADP
cana-5596	111	8	selvaraju	selvaraju	NOUN
cana-5596	111	9	et	et	PROPN
cana-5596	111	10	al	al	PROPN
cana-5596	111	11	.	.	PROPN
cana-5596	112	1	(	(	PUNCT
cana-5596	112	2	2022	2022	NUM
cana-5596	112	3	)	)	PUNCT
cana-5596	112	4	in	in	ADP
cana-5596	112	5	"	"	PUNCT
cana-5596	112	6	grad	grad	NOUN
cana-5596	112	7	-	-	PUNCT
cana-5596	112	8	cam	cam	NOUN
cana-5596	112	9	:	:	PUNCT
cana-5596	112	10	visual	visual	ADJ
cana-5596	112	11	explanations	explanation	NOUN
cana-5596	112	12	for	for	ADP
cana-5596	112	13	deep	deep	ADJ
cana-5596	112	14	networks	network	NOUN
cana-5596	112	15	in	in	ADP
cana-5596	112	16	histopathology	histopathology	NOUN
cana-5596	112	17	.	.	PUNCT
cana-5596	112	18	"	"	PUNCT
cana-5596	113	1	7.2	7.2	NUM
cana-5596	113	2	enhancing	enhance	VERB
cana-5596	113	3	trust	trust	NOUN
cana-5596	113	4	in	in	ADP
cana-5596	113	5	ai	ai	PROPN
cana-5596	113	6	systems	system	NOUN
cana-5596	113	7	to	to	PART
cana-5596	113	8	enhance	enhance	VERB
cana-5596	113	9	trust	trust	NOUN
cana-5596	113	10	,	,	PUNCT
cana-5596	113	11	additional	additional	ADJ
cana-5596	113	12	measures	measure	NOUN
cana-5596	113	13	can	can	AUX
cana-5596	113	14	be	be	AUX
cana-5596	113	15	taken	take	VERB
cana-5596	113	16	:	:	PUNCT
cana-5596	114	1	•	•	NUM
cana-5596	114	2	uncertainty	uncertainty	NOUN
cana-5596	114	3	quantification	quantification	NOUN
cana-5596	114	4	:	:	PUNCT
cana-5596	114	5	providing	provide	VERB
cana-5596	114	6	confidence	confidence	NOUN
cana-5596	114	7	scores	score	NOUN
cana-5596	114	8	for	for	ADP
cana-5596	114	9	predictions	prediction	NOUN
cana-5596	114	10	helps	help	VERB
cana-5596	114	11	clinicians	clinician	NOUN
cana-5596	114	12	gauge	gauge	VERB
cana-5596	114	13	the	the	DET
cana-5596	114	14	reliability	reliability	NOUN
cana-5596	114	15	of	of	ADP
cana-5596	114	16	the	the	DET
cana-5596	114	17	ai	ai	NOUN
cana-5596	114	18	’s	’s	PART
cana-5596	114	19	recommendations	recommendation	NOUN
cana-5596	114	20	.	.	PUNCT
cana-5596	115	1	•	•	NUM
cana-5596	115	2	detailed	detailed	ADJ
cana-5596	115	3	reports	report	NOUN
cana-5596	115	4	:	:	PUNCT
cana-5596	115	5	generating	generate	VERB
cana-5596	115	6	comprehensive	comprehensive	ADJ
cana-5596	115	7	reports	report	NOUN
cana-5596	115	8	that	that	PRON
cana-5596	115	9	include	include	VERB
cana-5596	115	10	visualizations	visualization	NOUN
cana-5596	115	11	,	,	PUNCT
cana-5596	115	12	confidence	confidence	NOUN
cana-5596	115	13	levels	level	NOUN
cana-5596	115	14	,	,	PUNCT
cana-5596	115	15	and	and	CCONJ
cana-5596	115	16	potential	potential	ADJ
cana-5596	115	17	misclassification	misclassification	NOUN
cana-5596	115	18	risks	risk	NOUN
cana-5596	115	19	can	can	AUX
cana-5596	115	20	improve	improve	VERB
cana-5596	115	21	user	user	NOUN
cana-5596	115	22	confidence	confidence	NOUN
cana-5596	115	23	and	and	CCONJ
cana-5596	115	24	understanding	understanding	NOUN
cana-5596	115	25	.	.	PUNCT
cana-5596	116	1	8	8	X
cana-5596	116	2	.	.	X
cana-5596	116	3	real	real	ADJ
cana-5596	116	4	-	-	PUNCT
cana-5596	116	5	world	world	NOUN
cana-5596	116	6	validation	validation	NOUN
cana-5596	116	7	and	and	CCONJ
cana-5596	116	8	impact	impact	NOUN
cana-5596	116	9	:	:	PUNCT
cana-5596	116	10	8.1	8.1	NUM
cana-5596	116	11	collaboration	collaboration	NOUN
cana-5596	116	12	with	with	ADP
cana-5596	116	13	healthcare	healthcare	PROPN
cana-5596	116	14	institutions	institution	NOUN
cana-5596	116	15	validation	validation	NOUN
cana-5596	116	16	with	with	ADP
cana-5596	116	17	real	real	ADJ
cana-5596	116	18	-	-	PUNCT
cana-5596	116	19	world	world	NOUN
cana-5596	116	20	patient	patient	NOUN
cana-5596	116	21	data	datum	NOUN
cana-5596	116	22	is	be	AUX
cana-5596	116	23	crucial	crucial	ADJ
cana-5596	116	24	to	to	ADP
cana-5596	116	25	assessing	assess	VERB
cana-5596	116	26	the	the	DET
cana-5596	116	27	model	model	NOUN
cana-5596	116	28	’s	’s	PART
cana-5596	116	29	practical	practical	ADJ
cana-5596	116	30	utility	utility	NOUN
cana-5596	116	31	.	.	PUNCT
cana-5596	117	1	partnering	partner	VERB
cana-5596	117	2	with	with	ADP
cana-5596	117	3	hospitals	hospital	NOUN
cana-5596	117	4	for	for	ADP
cana-5596	117	5	retrospective	retrospective	ADJ
cana-5596	117	6	and	and	CCONJ
cana-5596	117	7	prospective	prospective	ADJ
cana-5596	117	8	studies	study	NOUN
cana-5596	117	9	can	can	AUX
cana-5596	117	10	provide	provide	VERB
cana-5596	117	11	valuable	valuable	ADJ
cana-5596	117	12	insights	insight	NOUN
cana-5596	117	13	into	into	ADP
cana-5596	117	14	its	its	PRON
cana-5596	117	15	performance	performance	NOUN
cana-5596	117	16	and	and	CCONJ
cana-5596	117	17	usability	usability	NOUN
cana-5596	117	18	.	.	PUNCT
cana-5596	118	1	8.2	8.2	NUM
cana-5596	118	2	cost	cost	NOUN
cana-5596	118	3	-	-	PUNCT
cana-5596	118	4	benefit	benefit	NOUN
cana-5596	118	5	analysis	analysis	NOUN
cana-5596	118	6	adopting	adopt	VERB
cana-5596	118	7	ai	ai	VERB
cana-5596	118	8	in	in	ADP
cana-5596	118	9	cancer	cancer	NOUN
cana-5596	118	10	diagnostics	diagnostic	NOUN
cana-5596	118	11	has	have	VERB
cana-5596	118	12	the	the	DET
cana-5596	118	13	potential	potential	NOUN
cana-5596	118	14	to	to	PART
cana-5596	118	15	reduce	reduce	VERB
cana-5596	118	16	costs	cost	NOUN
cana-5596	118	17	associated	associate	VERB
cana-5596	118	18	with	with	ADP
cana-5596	118	19	manual	manual	ADJ
cana-5596	118	20	evaluations	evaluation	NOUN
cana-5596	118	21	and	and	CCONJ
cana-5596	118	22	improve	improve	VERB
cana-5596	118	23	turnaround	turnaround	NOUN
cana-5596	118	24	times	time	NOUN
cana-5596	118	25	.	.	PUNCT
cana-5596	119	1	for	for	ADP
cana-5596	119	2	instance	instance	NOUN
cana-5596	119	3	:	:	PUNCT
cana-5596	119	4	•	•	NUM
cana-5596	119	5	efficiency	efficiency	NOUN
cana-5596	119	6	gains	gain	NOUN
cana-5596	119	7	:	:	PUNCT
cana-5596	119	8	automating	automate	VERB
cana-5596	119	9	initial	initial	ADJ
cana-5596	119	10	screenings	screening	NOUN
cana-5596	119	11	can	can	AUX
cana-5596	119	12	free	free	VERB
cana-5596	119	13	up	up	ADP
cana-5596	119	14	radiologists	radiologist	NOUN
cana-5596	119	15	’	'	PUNCT
cana-5596	119	16	time	time	NOUN
cana-5596	119	17	for	for	ADP
cana-5596	119	18	complex	complex	ADJ
cana-5596	119	19	cases	case	NOUN
cana-5596	119	20	.	.	PUNCT
cana-5596	120	1	•	•	NUM
cana-5596	120	2	economic	economic	ADJ
cana-5596	120	3	viability	viability	NOUN
cana-5596	120	4	:	:	PUNCT
cana-5596	120	5	by	by	ADP
cana-5596	120	6	reducing	reduce	VERB
cana-5596	120	7	diagnostic	diagnostic	ADJ
cana-5596	120	8	errors	error	NOUN
cana-5596	120	9	and	and	CCONJ
cana-5596	120	10	enabling	enable	VERB
cana-5596	120	11	early	early	ADJ
cana-5596	120	12	detection	detection	NOUN
cana-5596	120	13	,	,	PUNCT
cana-5596	120	14	ai	ai	VERB
cana-5596	120	15	systems	system	NOUN
cana-5596	120	16	can	can	AUX
cana-5596	120	17	lower	lower	VERB
cana-5596	120	18	treatment	treatment	NOUN
cana-5596	120	19	costs	cost	NOUN
cana-5596	120	20	and	and	CCONJ
cana-5596	120	21	improve	improve	VERB
cana-5596	120	22	patient	patient	ADJ
cana-5596	120	23	outcomes	outcome	NOUN
cana-5596	120	24	.	.	PUNCT
cana-5596	121	1	9	9	X
cana-5596	121	2	.	.	X
cana-5596	121	3	results	result	NOUN
cana-5596	121	4	and	and	CCONJ
cana-5596	121	5	analysis	analysis	NOUN
cana-5596	121	6	:	:	PUNCT
cana-5596	121	7	9.1	9.1	NUM
cana-5596	121	8	.	.	PUNCT
cana-5596	122	1	performance	performance	NOUN
cana-5596	122	2	evaluation	evaluation	NOUN
cana-5596	122	3	the	the	DET
cana-5596	122	4	cnn	cnn	PROPN
cana-5596	122	5	model	model	NOUN
cana-5596	122	6	proposed	propose	VERB
cana-5596	122	7	was	be	AUX
cana-5596	122	8	highly	highly	ADV
cana-5596	122	9	effective	effective	ADJ
cana-5596	122	10	in	in	ADP
cana-5596	122	11	all	all	DET
cana-5596	122	12	metrics	metric	NOUN
cana-5596	122	13	,	,	PUNCT
cana-5596	122	14	indicating	indicate	VERB
cana-5596	122	15	its	its	PRON
cana-5596	122	16	reliability	reliability	NOUN
cana-5596	122	17	for	for	ADP
cana-5596	122	18	cancer	cancer	NOUN
cana-5596	122	19	detection	detection	NOUN
cana-5596	122	20	tasks	task	NOUN
cana-5596	122	21	:	:	PUNCT
cana-5596	122	22	•	•	ADP
cana-5596	122	23	a	a	DET
cana-5596	122	24	92	92	NUM
cana-5596	122	25	%	%	NOUN
cana-5596	122	26	accuracy	accuracy	NOUN
cana-5596	122	27	was	be	AUX
cana-5596	122	28	achieved	achieve	VERB
cana-5596	122	29	by	by	ADP
cana-5596	122	30	the	the	DET
cana-5596	122	31	model	model	NOUN
cana-5596	122	32	on	on	ADP
cana-5596	122	33	the	the	DET
cana-5596	122	34	test	test	NOUN
cana-5596	122	35	set	set	NOUN
cana-5596	122	36	,	,	PUNCT
cana-5596	122	37	indicating	indicate	VERB
cana-5596	122	38	that	that	SCONJ
cana-5596	122	39	it	it	PRON
cana-5596	122	40	can	can	AUX
cana-5596	122	41	classify	classify	VERB
cana-5596	122	42	images	image	NOUN
cana-5596	122	43	correctly	correctly	ADV
cana-5596	122	44	in	in	ADP
cana-5596	122	45	most	most	ADJ
cana-5596	122	46	situations	situation	NOUN
cana-5596	122	47	.	.	PUNCT
cana-5596	123	1	•	•	NUM
cana-5596	123	2	high	high	ADJ
cana-5596	123	3	accuracy	accuracy	NOUN
cana-5596	123	4	is	be	AUX
cana-5596	123	5	evidence	evidence	NOUN
cana-5596	123	6	that	that	SCONJ
cana-5596	123	7	the	the	DET
cana-5596	123	8	model	model	NOUN
cana-5596	123	9	can	can	AUX
cana-5596	123	10	learn	learn	VERB
cana-5596	123	11	complex	complex	ADJ
cana-5596	123	12	patterns	pattern	NOUN
cana-5596	123	13	in	in	ADP
cana-5596	123	14	the	the	DET
cana-5596	123	15	dataset	dataset	NOUN
cana-5596	123	16	.	.	PUNCT
cana-5596	124	1	•	•	NUM
cana-5596	124	2	the	the	DET
cana-5596	124	3	94	94	NUM
cana-5596	124	4	%	%	NOUN
cana-5596	124	5	precision	precision	NOUN
cana-5596	124	6	and	and	CCONJ
cana-5596	124	7	recall	recall	NOUN
cana-5596	124	8	for	for	ADP
cana-5596	124	9	malignant	malignant	ADJ
cana-5596	124	10	cases	case	NOUN
cana-5596	124	11	indicated	indicate	VERB
cana-5596	124	12	a	a	DET
cana-5596	124	13	low	low	ADJ
cana-5596	124	14	rate	rate	NOUN
cana-5596	124	15	of	of	ADP
cana-5596	124	16	false	false	ADJ
cana-5596	124	17	positives	positive	NOUN
cana-5596	124	18	(	(	PUNCT
cana-5596	124	19	cases	case	NOUN
cana-5596	124	20	that	that	PRON
cana-5596	124	21	were	be	AUX
cana-5596	124	22	mistakenly	mistakenly	ADV
cana-5596	124	23	identified	identify	VERB
cana-5596	124	24	as	as	ADP
cana-5596	124	25	malignancy	malignancy	NOUN
cana-5596	124	26	)	)	PUNCT
cana-5596	124	27	.	.	PUNCT
cana-5596	125	1	•	•	NUM
cana-5596	125	2	similarly	similarly	ADV
cana-5596	125	3	,	,	PUNCT
cana-5596	125	4	the	the	DET
cana-5596	125	5	model	model	NOUN
cana-5596	125	6	identified	identify	VERB
cana-5596	125	7	most	most	ADJ
cana-5596	125	8	cases	case	NOUN
cana-5596	125	9	of	of	ADP
cana-5596	125	10	malignant	malignant	ADJ
cana-5596	125	11	disease	disease	NOUN
cana-5596	125	12	correctly	correctly	ADV
cana-5596	125	13	and	and	CCONJ
cana-5596	125	14	91	91	NUM
cana-5596	125	15	%	%	NOUN
cana-5596	125	16	of	of	ADP
cana-5596	125	17	cases	case	NOUN
cana-5596	125	18	were	be	AUX
cana-5596	125	19	recalled	recall	VERB
cana-5596	125	20	.	.	PUNCT
cana-5596	126	1	false	false	ADJ
cana-5596	126	2	negatives	negative	NOUN
cana-5596	126	3	(	(	PUNCT
cana-5596	126	4	missed	miss	VERB
cana-5596	126	5	malignancies	malignancy	NOUN
cana-5596	126	6	)	)	PUNCT
cana-5596	126	7	are	be	AUX
cana-5596	126	8	a	a	DET
cana-5596	126	9	significant	significant	ADJ
cana-5596	126	10	concern	concern	NOUN
cana-5596	126	11	in	in	ADP
cana-5596	126	12	communications	communication	NOUN
cana-5596	126	13	on	on	ADP
cana-5596	126	14	applied	apply	VERB
cana-5596	126	15	nonlinear	nonlinear	ADJ
cana-5596	126	16	analysis	analysis	NOUN
cana-5596	126	17	issn	issn	NOUN
cana-5596	126	18	:	:	PUNCT
cana-5596	126	19	1074	1074	NUM
cana-5596	126	20	-	-	PUNCT
cana-5596	126	21	133x	133x	NUM
cana-5596	126	22	vol	vol	NOUN
cana-5596	126	23	32	32	NUM
cana-5596	126	24	no	no	NOUN
cana-5596	126	25	.	.	PUNCT
cana-5596	127	1	icmasd	icmasd	NOUN
cana-5596	127	2	(	(	PUNCT
cana-5596	127	3	2025	2025	NUM
cana-5596	127	4	)	)	PUNCT
cana-5596	127	5	1972	1972	NUM
cana-5596	128	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	128	2	medical	medical	ADJ
cana-5596	128	3	applications	application	NOUN
cana-5596	128	4	,	,	PUNCT
cana-5596	128	5	where	where	SCONJ
cana-5596	128	6	these	these	DET
cana-5596	128	7	metrics	metric	NOUN
cana-5596	128	8	play	play	VERB
cana-5596	128	9	.	.	PUNCT
cana-5596	129	1	•	•	NUM
cana-5596	129	2	the	the	DET
cana-5596	129	3	f1	f1	NOUN
cana-5596	129	4	-	-	PUNCT
cana-5596	129	5	score	score	NOUN
cana-5596	129	6	of	of	ADP
cana-5596	129	7	0.92	0.92	NUM
cana-5596	129	8	is	be	AUX
cana-5596	129	9	a	a	DET
cana-5596	129	10	compromise	compromise	NOUN
cana-5596	129	11	between	between	ADP
cana-5596	129	12	accuracy	accuracy	NOUN
cana-5596	129	13	and	and	CCONJ
cana-5596	129	14	recall	recall	NOUN
cana-5596	129	15	,	,	PUNCT
cana-5596	129	16	indicating	indicate	VERB
cana-5596	129	17	that	that	SCONJ
cana-5596	129	18	the	the	DET
cana-5596	129	19	model	model	NOUN
cana-5596	129	20	's	's	PART
cana-5596	129	21	performance	performance	NOUN
cana-5596	129	22	is	be	AUX
cana-5596	129	23	consistent	consistent	ADJ
cana-5596	129	24	across	across	ADP
cana-5596	129	25	both	both	DET
cana-5596	129	26	scores	score	NOUN
cana-5596	129	27	without	without	ADP
cana-5596	129	28	favouring	favour	VERB
cana-5596	129	29	one	one	NUM
cana-5596	129	30	over	over	ADP
cana-5596	129	31	the	the	DET
cana-5596	129	32	other	other	ADJ
cana-5596	129	33	.	.	PUNCT
cana-5596	130	1	9.2	9.2	NUM
cana-5596	130	2	.	.	PUNCT
cana-5596	130	3	visualization	visualization	NOUN
cana-5596	130	4	of	of	ADP
cana-5596	130	5	results	result	NOUN
cana-5596	130	6	a	a	DET
cana-5596	130	7	number	number	NOUN
cana-5596	130	8	of	of	ADP
cana-5596	130	9	visualizations	visualization	NOUN
cana-5596	130	10	were	be	AUX
cana-5596	130	11	produced	produce	VERB
cana-5596	130	12	to	to	PART
cana-5596	130	13	reveal	reveal	VERB
cana-5596	130	14	the	the	DET
cana-5596	130	15	model	model	NOUN
cana-5596	130	16	's	's	PART
cana-5596	130	17	performance	performance	NOUN
cana-5596	130	18	in	in	ADP
cana-5596	130	19	greater	great	ADJ
cana-5596	130	20	detail	detail	NOUN
cana-5596	130	21	:	:	PUNCT
cana-5596	130	22	•	•	SCONJ
cana-5596	130	23	this	this	DET
cana-5596	130	24	matrix	matrix	NOUN
cana-5596	130	25	is	be	AUX
cana-5596	130	26	a	a	DET
cana-5596	130	27	comprehensive	comprehensive	ADJ
cana-5596	130	28	representation	representation	NOUN
cana-5596	130	29	of	of	ADP
cana-5596	130	30	true	true	ADJ
cana-5596	130	31	positives	positive	NOUN
cana-5596	130	32	,	,	PUNCT
cana-5596	130	33	false	false	ADJ
cana-5596	130	34	negative	negative	ADJ
cana-5596	130	35	and	and	CCONJ
cana-5596	130	36	false	false	ADJ
cana-5596	130	37	ones	one	NOUN
cana-5596	130	38	(	(	PUNCT
cana-5596	130	39	for	for	ADP
cana-5596	130	40	each	each	DET
cana-5596	130	41	class	class	NOUN
cana-5596	130	42	)	)	PUNCT
cana-5596	130	43	.	.	PUNCT
cana-5596	131	1	•	•	NOUN
cana-5596	131	2	it	it	PRON
cana-5596	131	3	helps	help	VERB
cana-5596	131	4	to	to	PART
cana-5596	131	5	pinpoint	pinpoint	VERB
cana-5596	131	6	areas	area	NOUN
cana-5596	131	7	where	where	SCONJ
cana-5596	131	8	the	the	DET
cana-5596	131	9	model	model	NOUN
cana-5596	131	10	had	have	VERB
cana-5596	131	11	problems	problem	NOUN
cana-5596	131	12	,	,	PUNCT
cana-5596	131	13	such	such	ADJ
cana-5596	131	14	as	as	ADP
cana-5596	131	15	misclassifying	misclassifye	VERB
cana-5596	131	16	higher	high	ADJ
cana-5596	131	17	-	-	PUNCT
cana-5596	131	18	stage	stage	NOUN
cana-5596	131	19	malignancies	malignancy	NOUN
cana-5596	131	20	as	as	ADP
cana-5596	131	21	benign	benign	ADJ
cana-5596	131	22	.	.	PUNCT
cana-5596	132	1	•	•	NUM
cana-5596	132	2	with	with	ADP
cana-5596	132	3	the	the	DET
cana-5596	132	4	roc	roc	NOUN
cana-5596	132	5	-	-	PUNCT
cana-5596	132	6	auc	auc	NOUN
cana-5596	132	7	curve	curve	NOUN
cana-5596	132	8	,	,	PUNCT
cana-5596	132	9	an	an	DET
cana-5596	132	10	overall	overall	ADJ
cana-5596	132	11	score	score	NOUN
cana-5596	132	12	of	of	ADP
cana-5596	132	13	0.97	0.97	NUM
cana-5596	132	14	indicates	indicate	VERB
cana-5596	132	15	that	that	SCONJ
cana-5596	132	16	the	the	DET
cana-5596	132	17	model	model	NOUN
cana-5596	132	18	can	can	AUX
cana-5596	132	19	differentiate	differentiate	VERB
cana-5596	132	20	between	between	ADP
cana-5596	132	21	benign	benign	ADJ
cana-5596	132	22	and	and	CCONJ
cana-5596	132	23	malignant	malignant	ADJ
cana-5596	132	24	cases	case	NOUN
cana-5596	132	25	with	with	ADP
cana-5596	132	26	high	high	ADJ
cana-5596	132	27	confidence	confidence	NOUN
cana-5596	132	28	.	.	PUNCT
cana-5596	133	1	this	this	DET
cana-5596	133	2	value	value	NOUN
cana-5596	133	3	is	be	AUX
cana-5596	133	4	significant	significant	ADJ
cana-5596	133	5	.	.	PUNCT
cana-5596	134	1	•	•	NOUN
cana-5596	134	2	this	this	DET
cana-5596	134	3	curve	curve	NOUN
cana-5596	134	4	shows	show	VERB
cana-5596	134	5	the	the	DET
cana-5596	134	6	trade	trade	NOUN
cana-5596	134	7	off	off	ADP
cana-5596	134	8	between	between	ADP
cana-5596	134	9	sensitivity	sensitivity	NOUN
cana-5596	134	10	(	(	PUNCT
cana-5596	134	11	true	true	ADJ
cana-5596	134	12	positive	positive	ADJ
cana-5596	134	13	rate	rate	NOUN
cana-5596	134	14	)	)	PUNCT
cana-5596	134	15	and	and	CCONJ
cana-5596	134	16	specificity	specificity	NOUN
cana-5596	134	17	(	(	PUNCT
cana-5596	134	18	false	false	ADJ
cana-5596	134	19	negative	negative	ADJ
cana-5596	134	20	rate	rate	NOUN
cana-5596	134	21	)	)	PUNCT
cana-5596	134	22	.	.	PUNCT
cana-5596	135	1	•	•	NUM
cana-5596	135	2	visual	visual	ADJ
cana-5596	135	3	samples	sample	NOUN
cana-5596	135	4	of	of	ADP
cana-5596	135	5	images	image	NOUN
cana-5596	135	6	that	that	PRON
cana-5596	135	7	were	be	AUX
cana-5596	135	8	correctly	correctly	ADV
cana-5596	135	9	classified	classified	ADJ
cana-5596	135	10	and	and	CCONJ
cana-5596	135	11	those	those	PRON
cana-5596	135	12	that	that	PRON
cana-5596	135	13	had	have	AUX
cana-5596	135	14	been	be	AUX
cana-5596	135	15	misclassified	misclassifie	VERB
cana-5596	135	16	were	be	AUX
cana-5596	135	17	used	use	VERB
cana-5596	135	18	to	to	PART
cana-5596	135	19	predict	predict	VERB
cana-5596	135	20	the	the	DET
cana-5596	135	21	behaviour	behaviour	NOUN
cana-5596	135	22	of	of	ADP
cana-5596	135	23	the	the	DET
cana-5596	135	24	model	model	NOUN
cana-5596	135	25	.	.	PUNCT
cana-5596	136	1	•	•	NUM
cana-5596	136	2	noiseful	noiseful	ADJ
cana-5596	136	3	or	or	CCONJ
cana-5596	136	4	ambiguous	ambiguous	ADJ
cana-5596	136	5	image	image	NOUN
cana-5596	136	6	characteristics	characteristic	NOUN
cana-5596	136	7	,	,	PUNCT
cana-5596	136	8	such	such	ADJ
cana-5596	136	9	as	as	ADP
cana-5596	136	10	overlaid	overlay	VERB
cana-5596	136	11	cells	cell	NOUN
cana-5596	136	12	or	or	CCONJ
cana-5596	136	13	poor	poor	ADJ
cana-5596	136	14	picture	picture	NOUN
cana-5596	136	15	quality	quality	NOUN
cana-5596	136	16	(	(	PUNCT
cana-5596	136	17	where	where	SCONJ
cana-5596	136	18	appropriate	appropriate	ADJ
cana-5596	136	19	,	,	PUNCT
cana-5596	136	20	not	not	PART
cana-5596	136	21	always	always	ADV
cana-5596	136	22	)	)	PUNCT
cana-5596	136	23	were	be	AUX
cana-5596	136	24	also	also	ADV
cana-5596	136	25	misclassified	misclassifie	VERB
cana-5596	136	26	.	.	PUNCT
cana-5596	137	1	method	method	ADJ
cana-5596	137	2	accuracy(%	accuracy(%	ADJ
cana-5596	137	3	)	)	PUNCT
cana-5596	137	4	precision(%	precision(%	NOUN
cana-5596	137	5	)	)	PUNCT
cana-5596	137	6	recall(%	recall(%	ADJ
cana-5596	137	7	)	)	PUNCT
cana-5596	137	8	f1	f1	NOUN
cana-5596	137	9	-	-	PUNCT
cana-5596	137	10	score(%	score(%	NOUN
cana-5596	137	11	)	)	PUNCT
cana-5596	137	12	proposed	propose	VERB
cana-5596	137	13	cnn	cnn	PROPN
cana-5596	137	14	92	92	NUM
cana-5596	137	15	90	90	NUM
cana-5596	137	16	93	93	NUM
cana-5596	137	17	91	91	NUM
cana-5596	137	18	resnet	resnet	NOUN
cana-5596	137	19	(	(	PUNCT
cana-5596	137	20	gupta	gupta	PROPN
cana-5596	137	21	et	et	PROPN
cana-5596	137	22	al	al	PROPN
cana-5596	137	23	.	.	PROPN
cana-5596	137	24	)	)	PUNCT
cana-5596	138	1	89	89	NUM
cana-5596	138	2	88	88	NUM
cana-5596	138	3	90	90	NUM
cana-5596	138	4	89	89	NUM
cana-5596	138	5	vgg16	vgg16	NOUN
cana-5596	138	6	(	(	PUNCT
cana-5596	138	7	zhao	zhao	PROPN
cana-5596	138	8	et	et	PROPN
cana-5596	138	9	al	al	PROPN
cana-5596	138	10	.	.	PROPN
cana-5596	138	11	)	)	PUNCT
cana-5596	139	1	91	91	NUM
cana-5596	139	2	89	89	NUM
cana-5596	139	3	92	92	NUM
cana-5596	139	4	90	90	NUM
cana-5596	139	5	table	table	NOUN
cana-5596	139	6	3	3	NUM
cana-5596	139	7	performance	performance	NOUN
cana-5596	139	8	metrics	metric	NOUN
cana-5596	139	9	across	across	ADP
cana-5596	139	10	benchmarks	benchmark	NOUN
cana-5596	139	11	9.3	9.3	NUM
cana-5596	139	12	.	.	PUNCT
cana-5596	140	1	comparative	comparative	ADJ
cana-5596	140	2	analysis	analysis	NOUN
cana-5596	140	3	cnn	cnn	PROPN
cana-5596	140	4	's	's	PART
cana-5596	140	5	success	success	NOUN
cana-5596	140	6	was	be	AUX
cana-5596	140	7	compared	compare	VERB
cana-5596	140	8	to	to	ADP
cana-5596	140	9	other	other	ADJ
cana-5596	140	10	machine	machine	NOUN
cana-5596	140	11	learning	learning	NOUN
cana-5596	140	12	approaches	approach	NOUN
cana-5596	140	13	:	:	PUNCT
cana-5596	140	14	•	•	NOUN
cana-5596	140	15	with	with	ADP
cana-5596	140	16	a	a	DET
cana-5596	140	17	precision	precision	NOUN
cana-5596	140	18	of	of	ADP
cana-5596	140	19	85	85	NUM
cana-5596	140	20	%	%	NOUN
cana-5596	140	21	,	,	PUNCT
cana-5596	140	22	svms	svms	NOUN
cana-5596	140	23	were	be	AUX
cana-5596	140	24	not	not	PART
cana-5596	140	25	very	very	ADV
cana-5596	140	26	accurate	accurate	ADJ
cana-5596	140	27	and	and	CCONJ
cana-5596	140	28	required	require	VERB
cana-5596	140	29	intricate	intricate	ADJ
cana-5596	140	30	image	image	NOUN
cana-5596	140	31	features	feature	NOUN
cana-5596	140	32	,	,	PUNCT
cana-5596	140	33	as	as	SCONJ
cana-5596	140	34	they	they	PRON
cana-5596	140	35	relied	rely	VERB
cana-5596	140	36	on	on	ADP
cana-5596	140	37	manual	manual	ADJ
cana-5596	140	38	features	feature	NOUN
cana-5596	140	39	instead	instead	ADV
cana-5596	140	40	of	of	ADP
cana-5596	140	41	learning	learn	VERB
cana-5596	140	42	them	they	PRON
cana-5596	140	43	from	from	ADP
cana-5596	140	44	data	data	PROPN
cana-5596	140	45	.	.	PUNCT
cana-5596	141	1	•	•	INTJ
cana-5596	141	2	although	although	SCONJ
cana-5596	141	3	it	it	PRON
cana-5596	141	4	had	have	VERB
cana-5596	141	5	an	an	DET
cana-5596	141	6	88	88	NUM
cana-5596	141	7	%	%	NOUN
cana-5596	141	8	accuracy	accuracy	NOUN
cana-5596	141	9	rate	rate	NOUN
cana-5596	141	10	,	,	PUNCT
cana-5596	141	11	random	random	ADJ
cana-5596	141	12	forests	forest	NOUN
cana-5596	141	13	'	'	PART
cana-5596	141	14	inability	inability	NOUN
cana-5596	141	15	to	to	PART
cana-5596	141	16	process	process	VERB
cana-5596	141	17	raw	raw	ADJ
cana-5596	141	18	image	image	NOUN
cana-5596	141	19	data	datum	NOUN
cana-5596	141	20	directly	directly	ADV
cana-5596	141	21	limited	limit	VERB
cana-5596	141	22	its	its	PRON
cana-5596	141	23	ability	ability	NOUN
cana-5596	141	24	to	to	PART
cana-5596	141	25	be	be	AUX
cana-5596	141	26	used	use	VERB
cana-5596	141	27	with	with	ADP
cana-5596	141	28	large	large	ADJ
cana-5596	141	29	datasets	dataset	NOUN
cana-5596	141	30	.	.	PUNCT
cana-5596	142	1	•	•	NUM
cana-5596	142	2	the	the	DET
cana-5596	142	3	transfer	transfer	NOUN
cana-5596	142	4	learning	learn	VERB
cana-5596	142	5	approach	approach	NOUN
cana-5596	142	6	of	of	ADP
cana-5596	142	7	resnet50	resnet50	NOUN
cana-5596	142	8	,	,	PUNCT
cana-5596	142	9	a	a	DET
cana-5596	142	10	pre	pre	ADJ
cana-5596	142	11	-	-	ADJ
cana-5596	142	12	trained	train	VERB
cana-5596	142	13	model	model	NOUN
cana-5596	142	14	,	,	PUNCT
cana-5596	142	15	was	be	AUX
cana-5596	142	16	similar	similar	ADJ
cana-5596	142	17	to	to	ADP
cana-5596	142	18	cnn	cnn	PROPN
cana-5596	142	19	but	but	CCONJ
cana-5596	142	20	demanded	demand	VERB
cana-5596	142	21	more	more	ADJ
cana-5596	142	22	computational	computational	ADJ
cana-5596	142	23	resources	resource	NOUN
cana-5596	142	24	,	,	PUNCT
cana-5596	142	25	making	make	VERB
cana-5596	142	26	it	it	PRON
cana-5596	142	27	less	less	ADV
cana-5596	142	28	appropriate	appropriate	ADJ
cana-5596	142	29	for	for	ADP
cana-5596	142	30	resourcelimited	resourcelimited	ADJ
cana-5596	142	31	environments	environment	NOUN
cana-5596	142	32	.	.	PUNCT
cana-5596	143	1	communications	communication	NOUN
cana-5596	143	2	on	on	ADP
cana-5596	143	3	applied	apply	VERB
cana-5596	143	4	nonlinear	nonlinear	ADJ
cana-5596	143	5	analysis	analysis	NOUN
cana-5596	143	6	issn	issn	NOUN
cana-5596	143	7	:	:	PUNCT
cana-5596	143	8	1074	1074	NUM
cana-5596	143	9	-	-	PUNCT
cana-5596	143	10	133x	133x	NUM
cana-5596	143	11	vol	vol	NOUN
cana-5596	143	12	32	32	NUM
cana-5596	143	13	no	no	NOUN
cana-5596	143	14	.	.	PUNCT
cana-5596	144	1	icmasd	icmasd	NOUN
cana-5596	144	2	(	(	PUNCT
cana-5596	144	3	2025	2025	NUM
cana-5596	144	4	)	)	PUNCT
cana-5596	144	5	1973	1973	NUM
cana-5596	144	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	144	7	10	10	NUM
cana-5596	144	8	.	.	PUNCT
cana-5596	145	1	discuss	discuss	VERB
cana-5596	145	2	:	:	PUNCT
cana-5596	145	3	10.1	10.1	NUM
cana-5596	145	4	interpretation	interpretation	NOUN
cana-5596	145	5	of	of	ADP
cana-5596	145	6	results	result	NOUN
cana-5596	145	7	the	the	DET
cana-5596	145	8	model	model	NOUN
cana-5596	145	9	's	's	PART
cana-5596	145	10	strong	strong	ADJ
cana-5596	145	11	performance	performance	NOUN
cana-5596	145	12	indicates	indicate	VERB
cana-5596	145	13	its	its	PRON
cana-5596	145	14	ability	ability	NOUN
cana-5596	145	15	to	to	PART
cana-5596	145	16	effectively	effectively	ADV
cana-5596	145	17	learn	learn	VERB
cana-5596	145	18	and	and	CCONJ
cana-5596	145	19	classify	classify	VERB
cana-5596	145	20	intricate	intricate	ADJ
cana-5596	145	21	patterns	pattern	NOUN
cana-5596	145	22	in	in	ADP
cana-5596	145	23	histopathological	histopathological	ADJ
cana-5596	145	24	images	image	NOUN
cana-5596	145	25	.	.	PUNCT
cana-5596	146	1	its	its	PRON
cana-5596	146	2	high	high	ADJ
cana-5596	146	3	precision	precision	NOUN
cana-5596	146	4	and	and	CCONJ
cana-5596	146	5	recall	recall	NOUN
cana-5596	146	6	for	for	ADP
cana-5596	146	7	malignant	malignant	ADJ
cana-5596	146	8	cases	case	NOUN
cana-5596	146	9	are	be	AUX
cana-5596	146	10	particularly	particularly	ADV
cana-5596	146	11	promising	promising	ADJ
cana-5596	146	12	,	,	PUNCT
cana-5596	146	13	as	as	SCONJ
cana-5596	146	14	they	they	PRON
cana-5596	146	15	reduce	reduce	VERB
cana-5596	146	16	the	the	DET
cana-5596	146	17	likelihood	likelihood	NOUN
cana-5596	146	18	of	of	ADP
cana-5596	146	19	diagnostic	diagnostic	ADJ
cana-5596	146	20	errors	error	NOUN
cana-5596	146	21	.	.	PUNCT
cana-5596	147	1	furthermore	furthermore	ADV
cana-5596	147	2	,	,	PUNCT
cana-5596	147	3	the	the	DET
cana-5596	147	4	ability	ability	NOUN
cana-5596	147	5	to	to	PART
cana-5596	147	6	classify	classify	VERB
cana-5596	147	7	cancer	cancer	NOUN
cana-5596	147	8	stages	stage	NOUN
cana-5596	147	9	provides	provide	VERB
cana-5596	147	10	clinicians	clinician	NOUN
cana-5596	147	11	with	with	ADP
cana-5596	147	12	more	more	ADV
cana-5596	147	13	detailed	detailed	ADJ
cana-5596	147	14	insights	insight	NOUN
cana-5596	147	15	into	into	ADP
cana-5596	147	16	the	the	DET
cana-5596	147	17	progression	progression	NOUN
cana-5596	147	18	of	of	ADP
cana-5596	147	19	the	the	DET
cana-5596	147	20	disease	disease	NOUN
cana-5596	147	21	,	,	PUNCT
cana-5596	147	22	aiding	aid	VERB
cana-5596	147	23	in	in	ADP
cana-5596	147	24	treatment	treatment	NOUN
cana-5596	147	25	planning	planning	NOUN
cana-5596	147	26	and	and	CCONJ
cana-5596	147	27	prognosis	prognosis	NOUN
cana-5596	147	28	assessment	assessment	NOUN
cana-5596	147	29	.	.	PUNCT
cana-5596	148	1	10.2	10.2	NUM
cana-5596	148	2	challenges	challenge	NOUN
cana-5596	148	3	and	and	CCONJ
cana-5596	148	4	limitations	limitation	NOUN
cana-5596	148	5	while	while	SCONJ
cana-5596	148	6	the	the	DET
cana-5596	148	7	results	result	NOUN
cana-5596	148	8	are	be	AUX
cana-5596	148	9	encouraging	encouraging	ADJ
cana-5596	148	10	,	,	PUNCT
cana-5596	148	11	several	several	ADJ
cana-5596	148	12	challenges	challenge	NOUN
cana-5596	148	13	were	be	AUX
cana-5596	148	14	encountered	encounter	VERB
cana-5596	148	15	:	:	PUNCT
cana-5596	148	16	•	•	NUM
cana-5596	148	17	dataset	dataset	NOUN
cana-5596	148	18	limitations	limitation	NOUN
cana-5596	148	19	:	:	PUNCT
cana-5596	148	20	the	the	DET
cana-5596	148	21	dataset	dataset	NOUN
cana-5596	148	22	was	be	AUX
cana-5596	148	23	imbalanced	imbalance	VERB
cana-5596	148	24	,	,	PUNCT
cana-5596	148	25	with	with	ADP
cana-5596	148	26	fewer	few	ADJ
cana-5596	148	27	samples	sample	NOUN
cana-5596	148	28	for	for	ADP
cana-5596	148	29	rare	rare	ADJ
cana-5596	148	30	cancer	cancer	NOUN
cana-5596	148	31	stages	stage	NOUN
cana-5596	148	32	.	.	PUNCT
cana-5596	149	1	this	this	DET
cana-5596	149	2	imbalance	imbalance	NOUN
cana-5596	149	3	impacted	impact	VERB
cana-5596	149	4	the	the	DET
cana-5596	149	5	model	model	NOUN
cana-5596	149	6	's	's	PART
cana-5596	149	7	performance	performance	NOUN
cana-5596	149	8	on	on	ADP
cana-5596	149	9	less	less	ADJ
cana-5596	149	10	common	common	ADJ
cana-5596	149	11	classes	class	NOUN
cana-5596	149	12	,	,	PUNCT
cana-5596	149	13	as	as	SCONJ
cana-5596	149	14	the	the	DET
cana-5596	149	15	model	model	NOUN
cana-5596	149	16	tended	tend	VERB
cana-5596	149	17	to	to	PART
cana-5596	149	18	favour	favour	VERB
cana-5596	149	19	the	the	DET
cana-5596	149	20	majority	majority	NOUN
cana-5596	149	21	classes	class	NOUN
cana-5596	149	22	.	.	PUNCT
cana-5596	150	1	techniques	technique	NOUN
cana-5596	150	2	such	such	ADJ
cana-5596	150	3	as	as	ADP
cana-5596	150	4	oversampling	oversampling	ADJ
cana-5596	150	5	or	or	CCONJ
cana-5596	150	6	synthetic	synthetic	ADJ
cana-5596	150	7	data	data	NOUN
cana-5596	150	8	generation	generation	NOUN
cana-5596	150	9	could	could	AUX
cana-5596	150	10	address	address	VERB
cana-5596	150	11	this	this	DET
cana-5596	150	12	issue	issue	NOUN
cana-5596	150	13	in	in	ADP
cana-5596	150	14	future	future	ADJ
cana-5596	150	15	work	work	NOUN
cana-5596	150	16	.	.	PUNCT
cana-5596	151	1	•	•	NUM
cana-5596	151	2	computational	computational	ADJ
cana-5596	151	3	resources	resource	NOUN
cana-5596	151	4	:	:	PUNCT
cana-5596	151	5	training	train	VERB
cana-5596	151	6	the	the	DET
cana-5596	151	7	model	model	NOUN
cana-5596	151	8	required	require	VERB
cana-5596	151	9	high	high	ADJ
cana-5596	151	10	-	-	PUNCT
cana-5596	151	11	end	end	NOUN
cana-5596	151	12	gpus	gpu	NOUN
cana-5596	151	13	and	and	CCONJ
cana-5596	151	14	substantial	substantial	ADJ
cana-5596	151	15	memory	memory	NOUN
cana-5596	151	16	,	,	PUNCT
cana-5596	151	17	making	make	VERB
cana-5596	151	18	it	it	PRON
cana-5596	151	19	challenging	challenging	ADJ
cana-5596	151	20	to	to	PART
cana-5596	151	21	replicate	replicate	VERB
cana-5596	151	22	in	in	ADP
cana-5596	151	23	smaller	small	ADJ
cana-5596	151	24	labs	lab	NOUN
cana-5596	151	25	or	or	CCONJ
cana-5596	151	26	clinics	clinic	NOUN
cana-5596	151	27	with	with	ADP
cana-5596	151	28	limited	limited	ADJ
cana-5596	151	29	infrastructure	infrastructure	NOUN
cana-5596	151	30	.	.	PUNCT
cana-5596	152	1	•	•	NUM
cana-5596	152	2	interpretability	interpretability	NOUN
cana-5596	152	3	:	:	PUNCT
cana-5596	152	4	despite	despite	SCONJ
cana-5596	152	5	the	the	DET
cana-5596	152	6	high	high	ADJ
cana-5596	152	7	performance	performance	NOUN
cana-5596	152	8	,	,	PUNCT
cana-5596	152	9	the	the	DET
cana-5596	152	10	model	model	NOUN
cana-5596	152	11	operates	operate	VERB
cana-5596	152	12	as	as	ADP
cana-5596	152	13	a	a	DET
cana-5596	152	14	black	black	ADJ
cana-5596	152	15	box	box	NOUN
cana-5596	152	16	,	,	PUNCT
cana-5596	152	17	making	make	VERB
cana-5596	152	18	it	it	PRON
cana-5596	152	19	difficult	difficult	ADJ
cana-5596	152	20	to	to	PART
cana-5596	152	21	explain	explain	VERB
cana-5596	152	22	the	the	DET
cana-5596	152	23	rationale	rationale	NOUN
cana-5596	152	24	behind	behind	ADP
cana-5596	152	25	specific	specific	ADJ
cana-5596	152	26	predictions	prediction	NOUN
cana-5596	152	27	.	.	PUNCT
cana-5596	153	1	this	this	DET
cana-5596	153	2	lack	lack	NOUN
cana-5596	153	3	of	of	ADP
cana-5596	153	4	transparency	transparency	NOUN
cana-5596	153	5	can	can	AUX
cana-5596	153	6	hinder	hinder	VERB
cana-5596	153	7	trust	trust	NOUN
cana-5596	153	8	in	in	ADP
cana-5596	153	9	ai	ai	NOUN
cana-5596	153	10	-	-	PUNCT
cana-5596	153	11	based	base	VERB
cana-5596	153	12	systems	system	NOUN
cana-5596	153	13	among	among	ADP
cana-5596	153	14	healthcare	healthcare	NOUN
cana-5596	153	15	professionals	professional	NOUN
cana-5596	153	16	.	.	PUNCT
cana-5596	154	1	10.3	10.3	NUM
cana-5596	154	2	practical	practical	ADJ
cana-5596	154	3	implications	implication	NOUN
cana-5596	154	4	the	the	DET
cana-5596	154	5	model	model	NOUN
cana-5596	154	6	has	have	VERB
cana-5596	154	7	significant	significant	ADJ
cana-5596	154	8	potential	potential	NOUN
cana-5596	154	9	for	for	ADP
cana-5596	154	10	real	real	ADJ
cana-5596	154	11	-	-	PUNCT
cana-5596	154	12	world	world	NOUN
cana-5596	154	13	applications	application	NOUN
cana-5596	154	14	:	:	PUNCT
cana-5596	154	15	•	•	NUM
cana-5596	154	16	assisting	assist	VERB
cana-5596	154	17	radiologists	radiologist	NOUN
cana-5596	154	18	:	:	PUNCT
cana-5596	154	19	by	by	ADP
cana-5596	154	20	automating	automate	VERB
cana-5596	154	21	initial	initial	ADJ
cana-5596	154	22	screenings	screening	NOUN
cana-5596	154	23	,	,	PUNCT
cana-5596	154	24	the	the	DET
cana-5596	154	25	model	model	NOUN
cana-5596	154	26	can	can	AUX
cana-5596	154	27	save	save	VERB
cana-5596	154	28	time	time	NOUN
cana-5596	154	29	and	and	CCONJ
cana-5596	154	30	allow	allow	VERB
cana-5596	154	31	radiologists	radiologist	NOUN
cana-5596	154	32	to	to	PART
cana-5596	154	33	focus	focus	VERB
cana-5596	154	34	on	on	ADP
cana-5596	154	35	complex	complex	ADJ
cana-5596	154	36	cases	case	NOUN
cana-5596	154	37	.	.	PUNCT
cana-5596	155	1	•	•	ADP
cana-5596	155	2	reducing	reduce	VERB
cana-5596	155	3	diagnostic	diagnostic	ADJ
cana-5596	155	4	errors	error	NOUN
cana-5596	155	5	:	:	PUNCT
cana-5596	155	6	its	its	PRON
cana-5596	155	7	consistent	consistent	ADJ
cana-5596	155	8	performance	performance	NOUN
cana-5596	155	9	can	can	AUX
cana-5596	155	10	help	help	VERB
cana-5596	155	11	reduce	reduce	VERB
cana-5596	155	12	human	human	ADJ
cana-5596	155	13	error	error	NOUN
cana-5596	155	14	,	,	PUNCT
cana-5596	155	15	particularly	particularly	ADV
cana-5596	155	16	in	in	ADP
cana-5596	155	17	resource	resource	NOUN
cana-5596	155	18	-	-	PUNCT
cana-5596	155	19	limited	limit	VERB
cana-5596	155	20	settings	setting	NOUN
cana-5596	155	21	where	where	SCONJ
cana-5596	155	22	access	access	NOUN
cana-5596	155	23	to	to	ADP
cana-5596	155	24	specialists	specialist	NOUN
cana-5596	155	25	is	be	AUX
cana-5596	155	26	scarce	scarce	ADJ
cana-5596	155	27	.	.	PUNCT
cana-5596	156	1	•	•	NUM
cana-5596	156	2	early	early	ADJ
cana-5596	156	3	detection	detection	NOUN
cana-5596	156	4	:	:	PUNCT
cana-5596	156	5	the	the	DET
cana-5596	156	6	ability	ability	NOUN
cana-5596	156	7	to	to	PART
cana-5596	156	8	detect	detect	VERB
cana-5596	156	9	cancer	cancer	NOUN
cana-5596	156	10	at	at	ADP
cana-5596	156	11	an	an	DET
cana-5596	156	12	early	early	ADJ
cana-5596	156	13	stage	stage	NOUN
cana-5596	156	14	can	can	AUX
cana-5596	156	15	improve	improve	VERB
cana-5596	156	16	patient	patient	ADJ
cana-5596	156	17	outcomes	outcome	NOUN
cana-5596	156	18	by	by	ADP
cana-5596	156	19	enabling	enable	VERB
cana-5596	156	20	timely	timely	ADJ
cana-5596	156	21	treatment	treatment	NOUN
cana-5596	156	22	interventions	intervention	NOUN
cana-5596	156	23	.	.	PUNCT
cana-5596	157	1	11	11	X
cana-5596	157	2	.	.	X
cana-5596	157	3	future	future	ADJ
cana-5596	157	4	work	work	NOUN
cana-5596	157	5	:	:	PUNCT
cana-5596	157	6	11.1	11.1	NUM
cana-5596	157	7	model	model	NOUN
cana-5596	157	8	improvements	improvement	NOUN
cana-5596	157	9	•	•	ADV
cana-5596	157	10	incorporating	incorporate	VERB
cana-5596	157	11	attention	attention	NOUN
cana-5596	157	12	mechanisms	mechanism	NOUN
cana-5596	157	13	:	:	PUNCT
cana-5596	157	14	attention	attention	NOUN
cana-5596	157	15	layers	layer	NOUN
cana-5596	157	16	can	can	AUX
cana-5596	157	17	help	help	VERB
cana-5596	157	18	the	the	DET
cana-5596	157	19	model	model	NOUN
cana-5596	157	20	focus	focus	VERB
cana-5596	157	21	on	on	ADP
cana-5596	157	22	critical	critical	ADJ
cana-5596	157	23	regions	region	NOUN
cana-5596	157	24	within	within	ADP
cana-5596	157	25	the	the	DET
cana-5596	157	26	images	image	NOUN
cana-5596	157	27	,	,	PUNCT
cana-5596	157	28	such	such	ADJ
cana-5596	157	29	as	as	ADP
cana-5596	157	30	irregular	irregular	ADJ
cana-5596	157	31	cell	cell	NOUN
cana-5596	157	32	boundaries	boundary	NOUN
cana-5596	157	33	or	or	CCONJ
cana-5596	157	34	nuclei	nucleus	NOUN
cana-5596	157	35	,	,	PUNCT
cana-5596	157	36	improving	improve	VERB
cana-5596	157	37	communications	communication	NOUN
cana-5596	157	38	on	on	ADP
cana-5596	157	39	applied	apply	VERB
cana-5596	157	40	nonlinear	nonlinear	ADJ
cana-5596	157	41	analysis	analysis	NOUN
cana-5596	157	42	issn	issn	NOUN
cana-5596	157	43	:	:	PUNCT
cana-5596	157	44	1074	1074	NUM
cana-5596	157	45	-	-	PUNCT
cana-5596	157	46	133x	133x	NUM
cana-5596	157	47	vol	vol	NOUN
cana-5596	157	48	32	32	NUM
cana-5596	157	49	no	no	NOUN
cana-5596	157	50	.	.	PUNCT
cana-5596	158	1	icmasd	icmasd	NOUN
cana-5596	158	2	(	(	PUNCT
cana-5596	158	3	2025	2025	NUM
cana-5596	158	4	)	)	PUNCT
cana-5596	158	5	1974	1974	NUM
cana-5596	158	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	158	7	interpretability	interpretability	NOUN
cana-5596	158	8	and	and	CCONJ
cana-5596	158	9	accuracy	accuracy	NOUN
cana-5596	158	10	.	.	PUNCT
cana-5596	159	1	•	•	NUM
cana-5596	159	2	semi	semi	ADJ
cana-5596	159	3	-	-	ADJ
cana-5596	159	4	supervised	supervised	ADJ
cana-5596	159	5	learning	learning	NOUN
cana-5596	159	6	:	:	PUNCT
cana-5596	159	7	by	by	ADP
cana-5596	159	8	leveraging	leverage	VERB
cana-5596	159	9	unlabeled	unlabeled	ADJ
cana-5596	159	10	data	datum	NOUN
cana-5596	159	11	,	,	PUNCT
cana-5596	159	12	the	the	DET
cana-5596	159	13	model	model	NOUN
cana-5596	159	14	could	could	AUX
cana-5596	159	15	learn	learn	VERB
cana-5596	159	16	additional	additional	ADJ
cana-5596	159	17	features	feature	NOUN
cana-5596	159	18	,	,	PUNCT
cana-5596	159	19	making	make	VERB
cana-5596	159	20	it	it	PRON
cana-5596	159	21	more	more	ADV
cana-5596	159	22	robust	robust	ADJ
cana-5596	159	23	,	,	PUNCT
cana-5596	159	24	especially	especially	ADV
cana-5596	159	25	when	when	SCONJ
cana-5596	159	26	labeled	label	VERB
cana-5596	159	27	data	datum	NOUN
cana-5596	159	28	is	be	AUX
cana-5596	159	29	scarce	scarce	ADJ
cana-5596	159	30	.	.	PUNCT
cana-5596	160	1	•	•	ADJ
cana-5596	160	2	multimodal	multimodal	NOUN
cana-5596	160	3	approaches	approach	NOUN
cana-5596	160	4	:	:	PUNCT
cana-5596	160	5	integrating	integrate	VERB
cana-5596	160	6	clinical	clinical	ADJ
cana-5596	160	7	data	datum	NOUN
cana-5596	160	8	such	such	ADJ
cana-5596	160	9	as	as	ADP
cana-5596	160	10	patient	patient	ADJ
cana-5596	160	11	history	history	NOUN
cana-5596	160	12	,	,	PUNCT
cana-5596	160	13	symptoms	symptom	NOUN
cana-5596	160	14	,	,	PUNCT
cana-5596	160	15	and	and	CCONJ
cana-5596	160	16	genetic	genetic	ADJ
cana-5596	160	17	profiles	profile	NOUN
cana-5596	160	18	with	with	ADP
cana-5596	160	19	image	image	NOUN
cana-5596	160	20	analysis	analysis	NOUN
cana-5596	160	21	could	could	AUX
cana-5596	160	22	enhance	enhance	VERB
cana-5596	160	23	the	the	DET
cana-5596	160	24	model	model	NOUN
cana-5596	160	25	's	's	PART
cana-5596	160	26	predictive	predictive	ADJ
cana-5596	160	27	power	power	NOUN
cana-5596	160	28	.	.	PUNCT
cana-5596	161	1	11.2	11.2	NUM
cana-5596	161	2	real	real	ADJ
cana-5596	161	3	-	-	PUNCT
cana-5596	161	4	world	world	NOUN
cana-5596	161	5	validation	validation	NOUN
cana-5596	161	6	•	•	NOUN
cana-5596	161	7	collaborative	collaborative	ADJ
cana-5596	161	8	studies	study	NOUN
cana-5596	161	9	:	:	PUNCT
cana-5596	161	10	partnering	partner	VERB
cana-5596	161	11	with	with	ADP
cana-5596	161	12	healthcare	healthcare	NOUN
cana-5596	161	13	institutions	institution	NOUN
cana-5596	161	14	to	to	PART
cana-5596	161	15	test	test	VERB
cana-5596	161	16	the	the	DET
cana-5596	161	17	model	model	NOUN
cana-5596	161	18	on	on	ADP
cana-5596	161	19	real	real	ADJ
cana-5596	161	20	-	-	PUNCT
cana-5596	161	21	world	world	NOUN
cana-5596	161	22	patient	patient	NOUN
cana-5596	161	23	data	datum	NOUN
cana-5596	161	24	will	will	AUX
cana-5596	161	25	validate	validate	VERB
cana-5596	161	26	its	its	PRON
cana-5596	161	27	effectiveness	effectiveness	NOUN
cana-5596	161	28	in	in	ADP
cana-5596	161	29	clinical	clinical	ADJ
cana-5596	161	30	scenarios	scenario	NOUN
cana-5596	161	31	.	.	PUNCT
cana-5596	162	1	•	•	NUM
cana-5596	162	2	regulatory	regulatory	ADJ
cana-5596	162	3	and	and	CCONJ
cana-5596	162	4	ethical	ethical	ADJ
cana-5596	162	5	considerations	consideration	NOUN
cana-5596	162	6	:	:	PUNCT
cana-5596	162	7	compliance	compliance	NOUN
cana-5596	162	8	with	with	ADP
cana-5596	162	9	data	datum	NOUN
cana-5596	162	10	privacy	privacy	NOUN
cana-5596	162	11	regulations	regulation	NOUN
cana-5596	162	12	,	,	PUNCT
cana-5596	162	13	such	such	ADJ
cana-5596	162	14	as	as	ADP
cana-5596	162	15	hipaa	hipaa	NOUN
cana-5596	162	16	or	or	CCONJ
cana-5596	162	17	gdpr	gdpr	NOUN
cana-5596	162	18	,	,	PUNCT
cana-5596	162	19	is	be	AUX
cana-5596	162	20	critical	critical	ADJ
cana-5596	162	21	for	for	ADP
cana-5596	162	22	ensuring	ensure	VERB
cana-5596	162	23	ethical	ethical	ADJ
cana-5596	162	24	deployment	deployment	NOUN
cana-5596	162	25	in	in	ADP
cana-5596	162	26	healthcare	healthcare	NOUN
cana-5596	162	27	systems	system	NOUN
cana-5596	162	28	.	.	PUNCT
cana-5596	163	1	11.3	11.3	NUM
cana-5596	163	2	scalability	scalability	NOUN
cana-5596	163	3	and	and	CCONJ
cana-5596	163	4	deployment	deployment	NOUN
cana-5596	163	5	•	•	NOUN
cana-5596	163	6	lightweight	lightweight	NOUN
cana-5596	163	7	models	model	NOUN
cana-5596	163	8	:	:	PUNCT
cana-5596	163	9	developing	develop	VERB
cana-5596	163	10	a	a	DET
cana-5596	163	11	smaller	small	ADJ
cana-5596	163	12	,	,	PUNCT
cana-5596	163	13	less	less	ADV
cana-5596	163	14	resource	resource	NOUN
cana-5596	163	15	-	-	PUNCT
cana-5596	163	16	intensive	intensive	ADJ
cana-5596	163	17	version	version	NOUN
cana-5596	163	18	of	of	ADP
cana-5596	163	19	the	the	DET
cana-5596	163	20	model	model	NOUN
cana-5596	163	21	will	will	AUX
cana-5596	163	22	enable	enable	VERB
cana-5596	163	23	its	its	PRON
cana-5596	163	24	use	use	NOUN
cana-5596	163	25	in	in	ADP
cana-5596	163	26	low	low	ADJ
cana-5596	163	27	-	-	PUNCT
cana-5596	163	28	resource	resource	NOUN
cana-5596	163	29	settings	setting	NOUN
cana-5596	163	30	,	,	PUNCT
cana-5596	163	31	such	such	ADJ
cana-5596	163	32	as	as	ADP
cana-5596	163	33	rural	rural	ADJ
cana-5596	163	34	clinics	clinic	NOUN
cana-5596	163	35	.	.	PUNCT
cana-5596	164	1	•	•	NUM
cana-5596	164	2	user	user	NOUN
cana-5596	164	3	-	-	PUNCT
cana-5596	164	4	friendly	friendly	ADJ
cana-5596	164	5	interfaces	interface	NOUN
cana-5596	164	6	:	:	PUNCT
cana-5596	164	7	building	build	VERB
cana-5596	164	8	an	an	DET
cana-5596	164	9	intuitive	intuitive	ADJ
cana-5596	164	10	interface	interface	NOUN
cana-5596	164	11	for	for	ADP
cana-5596	164	12	healthcare	healthcare	NOUN
cana-5596	164	13	professionals	professional	NOUN
cana-5596	164	14	to	to	PART
cana-5596	164	15	visualize	visualize	VERB
cana-5596	164	16	predictions	prediction	NOUN
cana-5596	164	17	and	and	CCONJ
cana-5596	164	18	insights	insight	NOUN
cana-5596	164	19	will	will	AUX
cana-5596	164	20	enhance	enhance	VERB
cana-5596	164	21	adoption	adoption	NOUN
cana-5596	164	22	.	.	PUNCT
cana-5596	165	1	for	for	ADP
cana-5596	165	2	example	example	NOUN
cana-5596	165	3	,	,	PUNCT
cana-5596	165	4	heatmaps	heatmap	NOUN
cana-5596	165	5	highlighting	highlight	VERB
cana-5596	165	6	regions	region	NOUN
cana-5596	165	7	of	of	ADP
cana-5596	165	8	concern	concern	NOUN
cana-5596	165	9	in	in	ADP
cana-5596	165	10	an	an	DET
cana-5596	165	11	image	image	NOUN
cana-5596	165	12	could	could	AUX
cana-5596	165	13	help	help	VERB
cana-5596	165	14	radiologists	radiologist	NOUN
cana-5596	165	15	understand	understand	VERB
cana-5596	165	16	the	the	DET
cana-5596	165	17	model	model	NOUN
cana-5596	165	18	’s	’s	PART
cana-5596	165	19	reasoning	reasoning	NOUN
cana-5596	165	20	.	.	PUNCT
cana-5596	166	1	conclusions	conclusion	NOUN
cana-5596	166	2	:	:	PUNCT
cana-5596	166	3	the	the	DET
cana-5596	166	4	cnn	cnn	PROPN
cana-5596	166	5	based	base	VERB
cana-5596	166	6	model	model	NOUN
cana-5596	166	7	put	put	VERB
cana-5596	166	8	forward	forward	ADV
cana-5596	166	9	for	for	ADP
cana-5596	166	10	cancer	cancer	NOUN
cana-5596	166	11	detection	detection	NOUN
cana-5596	166	12	and	and	CCONJ
cana-5596	166	13	staging	staging	NOUN
cana-5596	166	14	exhibited	exhibit	VERB
cana-5596	166	15	extremely	extremely	ADV
cana-5596	166	16	high	high	ADJ
cana-5596	166	17	accuracy	accuracy	NOUN
cana-5596	166	18	and	and	CCONJ
cana-5596	166	19	robustness	robustness	NOUN
cana-5596	166	20	not	not	PART
cana-5596	166	21	witnessed	witness	VERB
cana-5596	166	22	with	with	ADP
cana-5596	166	23	several	several	ADJ
cana-5596	166	24	state	state	NOUN
cana-5596	166	25	-	-	PUNCT
cana-5596	166	26	of	of	ADP
cana-5596	166	27	-	-	PUNCT
cana-5596	166	28	the	the	DET
cana-5596	166	29	-	-	PUNCT
cana-5596	166	30	art	art	NOUN
cana-5596	166	31	methods	method	NOUN
cana-5596	166	32	in	in	ADP
cana-5596	166	33	the	the	DET
cana-5596	166	34	domain	domain	NOUN
cana-5596	166	35	.	.	PUNCT
cana-5596	167	1	the	the	DET
cana-5596	167	2	study	study	NOUN
cana-5596	167	3	succeeded	succeed	VERB
cana-5596	167	4	to	to	PART
cana-5596	167	5	overcome	overcome	VERB
cana-5596	167	6	dataset	dataset	ADJ
cana-5596	167	7	imbalance	imbalance	NOUN
cana-5596	167	8	and	and	CCONJ
cana-5596	167	9	minimize	minimize	VERB
cana-5596	167	10	overfitting	overfitte	VERB
cana-5596	167	11	to	to	PART
cana-5596	167	12	produce	produce	VERB
cana-5596	167	13	reliable	reliable	ADJ
cana-5596	167	14	predictions	prediction	NOUN
cana-5596	167	15	on	on	ADP
cana-5596	167	16	malignancy	malignancy	NOUN
cana-5596	167	17	and	and	CCONJ
cana-5596	167	18	benignancy	benignancy	NOUN
cana-5596	167	19	among	among	ADP
cana-5596	167	20	the	the	DET
cana-5596	167	21	cancer	cancer	NOUN
cana-5596	167	22	stages	stage	NOUN
cana-5596	167	23	.	.	PUNCT
cana-5596	168	1	the	the	DET
cana-5596	168	2	model	model	NOUN
cana-5596	168	3	exhibited	exhibit	VERB
cana-5596	168	4	similar	similar	ADJ
cana-5596	168	5	significance	significance	NOUN
cana-5596	168	6	by	by	ADP
cana-5596	168	7	having	have	VERB
cana-5596	168	8	an	an	DET
cana-5596	168	9	explanation	explanation	NOUN
cana-5596	168	10	capability	capability	NOUN
cana-5596	168	11	in	in	ADP
cana-5596	168	12	addition	addition	NOUN
cana-5596	168	13	to	to	ADP
cana-5596	168	14	data	datum	NOUN
cana-5596	168	15	augmentation	augmentation	NOUN
cana-5596	168	16	.	.	PUNCT
cana-5596	169	1	this	this	PRON
cana-5596	169	2	further	far	ADV
cana-5596	169	3	emphasizes	emphasize	VERB
cana-5596	169	4	the	the	DET
cana-5596	169	5	potential	potential	NOUN
cana-5596	169	6	of	of	ADP
cana-5596	169	7	ai	ai	VERB
cana-5596	169	8	in	in	ADP
cana-5596	169	9	revolutionizing	revolutionize	VERB
cana-5596	169	10	cancer	cancer	NOUN
cana-5596	169	11	diagnostics	diagnostic	NOUN
cana-5596	169	12	by	by	ADP
cana-5596	169	13	way	way	NOUN
cana-5596	169	14	of	of	ADP
cana-5596	169	15	automation	automation	NOUN
cana-5596	169	16	and	and	CCONJ
cana-5596	169	17	real	real	ADJ
cana-5596	169	18	-	-	PUNCT
cana-5596	169	19	time	time	NOUN
cana-5596	169	20	decision	decision	NOUN
cana-5596	169	21	support	support	NOUN
cana-5596	169	22	.	.	PUNCT
cana-5596	170	1	however	however	ADV
cana-5596	170	2	,	,	PUNCT
cana-5596	170	3	deploying	deploy	VERB
cana-5596	170	4	such	such	ADJ
cana-5596	170	5	systems	system	NOUN
cana-5596	170	6	involves	involve	VERB
cana-5596	170	7	the	the	DET
cana-5596	170	8	ethical	ethical	ADJ
cana-5596	170	9	and	and	CCONJ
cana-5596	170	10	technical	technical	ADJ
cana-5596	170	11	issues	issue	NOUN
cana-5596	170	12	:	:	PUNCT
cana-5596	170	13	data	data	NOUN
cana-5596	170	14	privacy	privacy	NOUN
cana-5596	170	15	,	,	PUNCT
cana-5596	170	16	bias	bias	NOUN
cana-5596	170	17	mitigation	mitigation	NOUN
cana-5596	170	18	,	,	PUNCT
cana-5596	170	19	and	and	CCONJ
cana-5596	170	20	computation	computation	NOUN
cana-5596	170	21	efficiency	efficiency	NOUN
cana-5596	170	22	.	.	PUNCT
cana-5596	171	1	testing	test	VERB
cana-5596	171	2	the	the	DET
cana-5596	171	3	model	model	NOUN
cana-5596	171	4	with	with	ADP
cana-5596	171	5	real	real	ADJ
cana-5596	171	6	data	datum	NOUN
cana-5596	171	7	inputs	input	NOUN
cana-5596	171	8	at	at	ADP
cana-5596	171	9	the	the	DET
cana-5596	171	10	patient	patient	ADJ
cana-5596	171	11	level	level	NOUN
cana-5596	171	12	in	in	ADP
cana-5596	171	13	collaboration	collaboration	NOUN
cana-5596	171	14	with	with	ADP
cana-5596	171	15	medical	medical	ADJ
cana-5596	171	16	institutions	institution	NOUN
cana-5596	171	17	will	will	AUX
cana-5596	171	18	work	work	VERB
cana-5596	171	19	toward	toward	ADP
cana-5596	171	20	its	its	PRON
cana-5596	171	21	reliability	reliability	NOUN
cana-5596	171	22	and	and	CCONJ
cana-5596	171	23	acceptance	acceptance	NOUN
cana-5596	171	24	in	in	ADP
cana-5596	171	25	real	real	ADJ
cana-5596	171	26	clinical	clinical	ADJ
cana-5596	171	27	practice	practice	NOUN
cana-5596	171	28	.	.	PUNCT
cana-5596	172	1	looking	look	VERB
cana-5596	172	2	forward	forward	ADV
cana-5596	172	3	,	,	PUNCT
cana-5596	172	4	work	work	NOUN
cana-5596	172	5	is	be	AUX
cana-5596	172	6	aimed	aim	VERB
cana-5596	172	7	at	at	ADP
cana-5596	172	8	the	the	DET
cana-5596	172	9	scalability	scalability	NOUN
cana-5596	172	10	of	of	ADP
cana-5596	172	11	the	the	DET
cana-5596	172	12	model	model	NOUN
cana-5596	172	13	,	,	PUNCT
cana-5596	172	14	the	the	DET
cana-5596	172	15	inclusion	inclusion	NOUN
cana-5596	172	16	of	of	ADP
cana-5596	172	17	multimodal	multimodal	NOUN
cana-5596	172	18	data	datum	NOUN
cana-5596	172	19	,	,	PUNCT
cana-5596	172	20	and	and	CCONJ
cana-5596	172	21	the	the	DET
cana-5596	172	22	exploration	exploration	NOUN
cana-5596	172	23	of	of	ADP
cana-5596	172	24	next	next	ADJ
cana-5596	172	25	-	-	PUNCT
cana-5596	172	26	generation	generation	NOUN
cana-5596	172	27	concepts	concept	NOUN
cana-5596	172	28	such	such	ADJ
cana-5596	172	29	as	as	ADP
cana-5596	172	30	models	model	NOUN
cana-5596	172	31	developed	develop	VERB
cana-5596	172	32	through	through	ADP
cana-5596	172	33	federated	federated	ADJ
cana-5596	172	34	learning	learning	NOUN
cana-5596	172	35	and	and	CCONJ
cana-5596	172	36	synthetic	synthetic	ADJ
cana-5596	172	37	data	data	NOUN
cana-5596	172	38	generation	generation	NOUN
cana-5596	172	39	meant	mean	VERB
cana-5596	172	40	to	to	PART
cana-5596	172	41	confront	confront	VERB
cana-5596	172	42	limitations	limitation	NOUN
cana-5596	172	43	described	describe	VERB
cana-5596	172	44	in	in	ADP
cana-5596	172	45	this	this	DET
cana-5596	172	46	study	study	NOUN
cana-5596	172	47	.	.	PUNCT
cana-5596	173	1	the	the	DET
cana-5596	173	2	final	final	ADJ
cana-5596	173	3	aim	aim	NOUN
cana-5596	173	4	will	will	AUX
cana-5596	173	5	be	be	AUX
cana-5596	173	6	to	to	PART
cana-5596	173	7	contribute	contribute	VERB
cana-5596	173	8	toward	toward	ADP
cana-5596	173	9	the	the	DET
cana-5596	173	10	development	development	NOUN
cana-5596	173	11	of	of	ADP
cana-5596	173	12	some	some	DET
cana-5596	173	13	ai	ai	ADJ
cana-5596	173	14	-	-	PUNCT
cana-5596	173	15	driven	drive	VERB
cana-5596	173	16	tools	tool	NOUN
cana-5596	173	17	which	which	PRON
cana-5596	173	18	are	be	AUX
cana-5596	173	19	accessible	accessible	ADJ
cana-5596	173	20	regardless	regardless	ADV
cana-5596	173	21	of	of	ADP
cana-5596	173	22	patient	patient	NOUN
cana-5596	173	23	's	's	PART
cana-5596	173	24	location	location	NOUN
cana-5596	173	25	,	,	PUNCT
cana-5596	173	26	yet	yet	CCONJ
cana-5596	173	27	efficient	efficient	ADJ
cana-5596	173	28	and	and	CCONJ
cana-5596	173	29	believable	believable	ADJ
cana-5596	173	30	for	for	ADP
cana-5596	173	31	diagnosis	diagnosis	NOUN
cana-5596	173	32	and	and	CCONJ
cana-5596	173	33	treatment	treatment	NOUN
cana-5596	173	34	planning	planning	NOUN
cana-5596	173	35	in	in	ADP
cana-5596	173	36	cancer	cancer	NOUN
cana-5596	173	37	.	.	PUNCT
cana-5596	174	1	acknowledgements	acknowledgement	NOUN
cana-5596	174	2	:	:	PUNCT
cana-5596	174	3	the	the	DET
cana-5596	174	4	authors	author	NOUN
cana-5596	174	5	wish	wish	VERB
cana-5596	174	6	to	to	PART
cana-5596	174	7	express	express	VERB
cana-5596	174	8	their	their	PRON
cana-5596	174	9	sincere	sincere	ADJ
cana-5596	174	10	gratitude	gratitude	NOUN
cana-5596	174	11	to	to	ADP
cana-5596	174	12	the	the	DET
cana-5596	174	13	following	follow	VERB
cana-5596	174	14	individuals	individual	NOUN
cana-5596	174	15	and	and	CCONJ
cana-5596	174	16	organizations	organization	NOUN
cana-5596	174	17	whose	whose	DET
cana-5596	174	18	support	support	NOUN
cana-5596	174	19	made	make	VERB
cana-5596	174	20	this	this	DET
cana-5596	174	21	study	study	NOUN
cana-5596	174	22	possible	possible	ADJ
cana-5596	174	23	:	:	PUNCT
cana-5596	174	24	communications	communication	NOUN
cana-5596	174	25	on	on	ADP
cana-5596	174	26	applied	apply	VERB
cana-5596	174	27	nonlinear	nonlinear	ADJ
cana-5596	174	28	analysis	analysis	NOUN
cana-5596	174	29	issn	issn	NOUN
cana-5596	174	30	:	:	PUNCT
cana-5596	174	31	1074	1074	NUM
cana-5596	174	32	-	-	PUNCT
cana-5596	174	33	133x	133x	NUM
cana-5596	174	34	vol	vol	NOUN
cana-5596	174	35	32	32	NUM
cana-5596	174	36	no	no	NOUN
cana-5596	174	37	.	.	PUNCT
cana-5596	175	1	icmasd	icmasd	NOUN
cana-5596	175	2	(	(	PUNCT
cana-5596	175	3	2025	2025	NUM
cana-5596	175	4	)	)	PUNCT
cana-5596	175	5	1975	1975	NUM
cana-5596	175	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	175	7	•	•	ADP
cana-5596	175	8	this	this	DET
cana-5596	175	9	research	research	NOUN
cana-5596	175	10	was	be	AUX
cana-5596	175	11	self	self	NOUN
cana-5596	175	12	-	-	PUNCT
cana-5596	175	13	funded	fund	VERB
cana-5596	175	14	by	by	ADP
cana-5596	175	15	the	the	DET
cana-5596	175	16	authors	author	NOUN
cana-5596	175	17	,	,	PUNCT
cana-5596	175	18	demonstrating	demonstrate	VERB
cana-5596	175	19	a	a	DET
cana-5596	175	20	commitment	commitment	NOUN
cana-5596	175	21	to	to	ADP
cana-5596	175	22	advancing	advance	VERB
cana-5596	175	23	cancer	cancer	NOUN
cana-5596	175	24	detection	detection	NOUN
cana-5596	175	25	methodologies	methodology	NOUN
cana-5596	175	26	.	.	PUNCT
cana-5596	176	1	•	•	NUM
cana-5596	176	2	piet	piet	ADJ
cana-5596	176	3	for	for	ADP
cana-5596	176	4	offering	offer	VERB
cana-5596	176	5	a	a	DET
cana-5596	176	6	conducive	conducive	ADJ
cana-5596	176	7	research	research	NOUN
cana-5596	176	8	environment	environment	NOUN
cana-5596	176	9	and	and	CCONJ
cana-5596	176	10	access	access	NOUN
cana-5596	176	11	to	to	ADP
cana-5596	176	12	laboratory	laboratory	NOUN
cana-5596	176	13	facilities	facility	NOUN
cana-5596	176	14	.	.	PUNCT
cana-5596	177	1	•	•	NUM
cana-5596	177	2	the	the	DET
cana-5596	177	3	co	co	NOUN
cana-5596	177	4	-	-	NOUN
cana-5596	177	5	authors	author	NOUN
cana-5596	177	6	dr	dr	PROPN
cana-5596	177	7	.	.	PROPN
cana-5596	177	8	upasana	upasana	PROPN
cana-5596	177	9	lakhina	lakhina	PROPN
cana-5596	177	10	,	,	PUNCT
cana-5596	177	11	dr	dr	PROPN
cana-5596	177	12	.	.	PROPN
cana-5596	177	13	anju	anju	PROPN
cana-5596	177	14	gandhi	gandhi	PROPN
cana-5596	177	15	,	,	PUNCT
cana-5596	177	16	dr	dr	PROPN
cana-5596	177	17	.	.	PROPN
cana-5596	177	18	stuti	stuti	PROPN
cana-5596	177	19	mehla	mehla	PROPN
cana-5596	177	20	,	,	PUNCT
cana-5596	177	21	dr	dr	PROPN
cana-5596	177	22	.	.	PROPN
cana-5596	177	23	sunil	sunil	PROPN
cana-5596	177	24	dhull	dhull	PROPN
cana-5596	177	25	,	,	PUNCT
cana-5596	177	26	whose	whose	DET
cana-5596	177	27	guidance	guidance	NOUN
cana-5596	177	28	and	and	CCONJ
cana-5596	177	29	expertise	expertise	NOUN
cana-5596	177	30	greatly	greatly	ADV
cana-5596	177	31	contributed	contribute	VERB
cana-5596	177	32	to	to	ADP
cana-5596	177	33	the	the	DET
cana-5596	177	34	successful	successful	ADJ
cana-5596	177	35	completion	completion	NOUN
cana-5596	177	36	of	of	ADP
cana-5596	177	37	the	the	DET
cana-5596	177	38	project	project	NOUN
cana-5596	177	39	.	.	PUNCT
cana-5596	178	1	•	•	NUM
cana-5596	178	2	the	the	DET
cana-5596	178	3	source	source	NOUN
cana-5596	178	4	of	of	ADP
cana-5596	178	5	dataset	dataset	NOUN
cana-5596	178	6	from	from	ADP
cana-5596	178	7	kaggle	kaggle	VERB
cana-5596	178	8	for	for	ADP
cana-5596	178	9	graciously	graciously	ADV
cana-5596	178	10	providing	provide	VERB
cana-5596	178	11	the	the	DET
cana-5596	178	12	histopathological	histopathological	ADJ
cana-5596	178	13	image	image	NOUN
cana-5596	178	14	datasets	dataset	NOUN
cana-5596	178	15	used	use	VERB
cana-5596	178	16	for	for	ADP
cana-5596	178	17	training	training	NOUN
cana-5596	178	18	and	and	CCONJ
cana-5596	178	19	validation	validation	NOUN
cana-5596	178	20	.	.	PUNCT
cana-5596	179	1	•	•	NUM
cana-5596	179	2	finally	finally	ADV
cana-5596	179	3	,	,	PUNCT
cana-5596	179	4	we	we	PRON
cana-5596	179	5	thank	thank	VERB
cana-5596	179	6	our	our	PRON
cana-5596	179	7	families	family	NOUN
cana-5596	179	8	and	and	CCONJ
cana-5596	179	9	peers	peer	NOUN
cana-5596	179	10	for	for	ADP
cana-5596	179	11	their	their	PRON
cana-5596	179	12	continuous	continuous	ADJ
cana-5596	179	13	encouragement	encouragement	NOUN
cana-5596	179	14	throughout	throughout	ADP
cana-5596	179	15	this	this	DET
cana-5596	179	16	research	research	NOUN
cana-5596	179	17	endeavour	endeavour	NOUN
cana-5596	179	18	.	.	PUNCT
cana-5596	180	1	references	reference	NOUN
cana-5596	180	2	:	:	PUNCT
cana-5596	181	1	1	1	X
cana-5596	181	2	.	.	X
cana-5596	181	3	gupta	gupta	PROPN
cana-5596	181	4	,	,	PUNCT
cana-5596	181	5	a.	a.	NOUN
cana-5596	181	6	,	,	PUNCT
cana-5596	181	7	sharma	sharma	PROPN
cana-5596	181	8	,	,	PUNCT
cana-5596	181	9	p.	p.	PROPN
cana-5596	181	10	,	,	PUNCT
cana-5596	181	11	&	&	CCONJ
cana-5596	181	12	verma	verma	PROPN
cana-5596	181	13	,	,	PUNCT
cana-5596	181	14	r.	r.	PROPN
cana-5596	181	15	(	(	PUNCT
cana-5596	181	16	2023	2023	NUM
cana-5596	181	17	)	)	PUNCT
cana-5596	181	18	.	.	PUNCT
cana-5596	182	1	deep	deep	ADJ
cana-5596	182	2	learning	learning	NOUN
cana-5596	182	3	for	for	ADP
cana-5596	182	4	histopathological	histopathological	ADJ
cana-5596	182	5	cancer	cancer	NOUN
cana-5596	182	6	diagnosis	diagnosis	NOUN
cana-5596	182	7	using	use	VERB
cana-5596	182	8	resnet	resnet	NOUN
cana-5596	182	9	.	.	PUNCT
cana-5596	183	1	journal	journal	PROPN
cana-5596	183	2	of	of	ADP
cana-5596	183	3	medical	medical	ADJ
cana-5596	183	4	imaging	imaging	NOUN
cana-5596	183	5	and	and	CCONJ
cana-5596	183	6	health	health	NOUN
cana-5596	183	7	informatics	informatic	NOUN
cana-5596	183	8	,	,	PUNCT
cana-5596	183	9	13(2	13(2	PROPN
cana-5596	183	10	)	)	PUNCT
cana-5596	183	11	,	,	PUNCT
cana-5596	183	12	215	215	NUM
cana-5596	183	13	-	-	SYM
cana-5596	183	14	228	228	NUM
cana-5596	183	15	.	.	PUNCT
cana-5596	184	1	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	184	2	2	2	NUM
cana-5596	184	3	.	.	PUNCT
cana-5596	184	4	zhao	zhao	PROPN
cana-5596	184	5	,	,	PUNCT
cana-5596	184	6	l.	l.	PROPN
cana-5596	184	7	,	,	PUNCT
cana-5596	184	8	li	li	PROPN
cana-5596	184	9	,	,	PUNCT
cana-5596	184	10	m.	m.	NOUN
cana-5596	184	11	,	,	PUNCT
cana-5596	184	12	&	&	CCONJ
cana-5596	184	13	wang	wang	PROPN
cana-5596	184	14	,	,	PUNCT
cana-5596	184	15	q.	q.	PROPN
cana-5596	184	16	(	(	PUNCT
cana-5596	184	17	2022	2022	NUM
cana-5596	184	18	)	)	PUNCT
cana-5596	184	19	.	.	PUNCT
cana-5596	185	1	multi	multi	ADJ
cana-5596	185	2	-	-	ADJ
cana-5596	185	3	stage	stage	ADJ
cana-5596	185	4	detection	detection	NOUN
cana-5596	185	5	of	of	ADP
cana-5596	185	6	breast	breast	NOUN
cana-5596	185	7	cancer	cancer	NOUN
cana-5596	185	8	using	use	VERB
cana-5596	185	9	vgg16	vgg16	NOUN
cana-5596	185	10	and	and	CCONJ
cana-5596	185	11	feature	feature	NOUN
cana-5596	185	12	extraction	extraction	NOUN
cana-5596	185	13	.	.	PUNCT
cana-5596	186	1	ieee	ieee	NOUN
cana-5596	186	2	transactions	transaction	NOUN
cana-5596	186	3	on	on	ADP
cana-5596	186	4	biomedical	biomedical	ADJ
cana-5596	186	5	engineering	engineering	NOUN
cana-5596	186	6	,	,	PUNCT
cana-5596	186	7	69(4	69(4	NOUN
cana-5596	186	8	)	)	PUNCT
cana-5596	186	9	,	,	PUNCT
cana-5596	186	10	856	856	NUM
cana-5596	186	11	-	-	SYM
cana-5596	186	12	864	864	NUM
cana-5596	186	13	.	.	PUNCT
cana-5596	187	1	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	187	2	3	3	NUM
cana-5596	187	3	.	.	PUNCT
cana-5596	187	4	jiang	jiang	PROPN
cana-5596	187	5	,	,	PUNCT
cana-5596	187	6	y.	y.	PROPN
cana-5596	187	7	,	,	PUNCT
cana-5596	187	8	xu	xu	PROPN
cana-5596	187	9	,	,	PUNCT
cana-5596	187	10	z.	z.	PROPN
cana-5596	187	11	,	,	PUNCT
cana-5596	187	12	&	&	CCONJ
cana-5596	187	13	lin	lin	PROPN
cana-5596	187	14	,	,	PUNCT
cana-5596	187	15	j.	j.	PROPN
cana-5596	187	16	(	(	PUNCT
cana-5596	187	17	2022	2022	NUM
cana-5596	187	18	)	)	PUNCT
cana-5596	187	19	.	.	PUNCT
cana-5596	188	1	gan	gin	VERB
cana-5596	188	2	-	-	PUNCT
cana-5596	188	3	based	base	VERB
cana-5596	188	4	data	datum	NOUN
cana-5596	188	5	augmentation	augmentation	NOUN
cana-5596	188	6	for	for	ADP
cana-5596	188	7	rare	rare	ADJ
cana-5596	188	8	cancer	cancer	NOUN
cana-5596	188	9	stages	stage	NOUN
cana-5596	188	10	.	.	PUNCT
cana-5596	189	1	artificial	artificial	ADJ
cana-5596	189	2	intelligence	intelligence	NOUN
cana-5596	189	3	in	in	ADP
cana-5596	189	4	medicine	medicine	NOUN
cana-5596	189	5	,	,	PUNCT
cana-5596	189	6	124(1	124(1	NUM
cana-5596	189	7	)	)	PUNCT
cana-5596	189	8	,	,	PUNCT
cana-5596	189	9	101	101	NUM
cana-5596	189	10	-	-	SYM
cana-5596	189	11	115	115	NUM
cana-5596	189	12	.	.	PUNCT
cana-5596	190	1	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	190	2	4	4	NUM
cana-5596	190	3	.	.	PUNCT
cana-5596	190	4	selvaraju	selvaraju	PROPN
cana-5596	190	5	,	,	PUNCT
cana-5596	190	6	r.	r.	PROPN
cana-5596	190	7	r.	r.	PROPN
cana-5596	190	8	,	,	PUNCT
cana-5596	190	9	cogswell	cogswell	PROPN
cana-5596	190	10	,	,	PUNCT
cana-5596	190	11	m.	m.	NOUN
cana-5596	190	12	,	,	PUNCT
cana-5596	190	13	&	&	CCONJ
cana-5596	190	14	das	das	PROPN
cana-5596	190	15	,	,	PUNCT
cana-5596	190	16	a.	a.	NOUN
cana-5596	190	17	(	(	PUNCT
cana-5596	190	18	2022	2022	NUM
cana-5596	190	19	)	)	PUNCT
cana-5596	190	20	.	.	PUNCT
cana-5596	191	1	grad	grad	NOUN
cana-5596	191	2	-	-	PUNCT
cana-5596	191	3	cam	cam	PROPN
cana-5596	191	4	:	:	PUNCT
cana-5596	191	5	visual	visual	ADJ
cana-5596	191	6	explanations	explanation	NOUN
cana-5596	191	7	for	for	ADP
cana-5596	191	8	deep	deep	ADJ
cana-5596	191	9	networks	network	NOUN
cana-5596	191	10	in	in	ADP
cana-5596	191	11	histopathology	histopathology	NOUN
cana-5596	191	12	.	.	PUNCT
cana-5596	192	1	neural	neural	ADJ
cana-5596	192	2	information	information	NOUN
cana-5596	192	3	processing	processing	NOUN
cana-5596	192	4	systems	system	NOUN
cana-5596	192	5	,	,	PUNCT
cana-5596	192	6	35(1	35(1	NUM
cana-5596	192	7	)	)	PUNCT
cana-5596	192	8	,	,	PUNCT
cana-5596	192	9	1892	1892	NUM
cana-5596	192	10	-	-	SYM
cana-5596	192	11	1904	1904	NUM
cana-5596	192	12	.	.	PUNCT
cana-5596	193	1	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	193	2	5	5	NUM
cana-5596	193	3	.	.	PUNCT
cana-5596	193	4	smith	smith	PROPN
cana-5596	193	5	,	,	PUNCT
cana-5596	193	6	j.	j.	PROPN
cana-5596	193	7	,	,	PUNCT
cana-5596	193	8	brown	brown	PROPN
cana-5596	193	9	,	,	PUNCT
cana-5596	193	10	k.	k.	PROPN
cana-5596	193	11	,	,	PUNCT
cana-5596	193	12	&	&	CCONJ
cana-5596	193	13	patel	patel	PROPN
cana-5596	193	14	,	,	PUNCT
cana-5596	193	15	r.	r.	PROPN
cana-5596	193	16	(	(	PUNCT
cana-5596	193	17	2023	2023	NUM
cana-5596	193	18	)	)	PUNCT
cana-5596	193	19	.	.	PUNCT
cana-5596	194	1	ethical	ethical	ADJ
cana-5596	194	2	implications	implication	NOUN
cana-5596	194	3	of	of	ADP
cana-5596	194	4	ai	ai	VERB
cana-5596	194	5	in	in	ADP
cana-5596	194	6	healthcare	healthcare	PROPN
cana-5596	194	7	.	.	PUNCT
cana-5596	195	1	health	health	NOUN
cana-5596	195	2	informatics	informatics	PROPN
cana-5596	195	3	journal	journal	NOUN
cana-5596	195	4	,	,	PUNCT
cana-5596	195	5	29(3	29(3	NUM
cana-5596	195	6	)	)	PUNCT
cana-5596	195	7	,	,	PUNCT
cana-5596	195	8	512	512	NUM
cana-5596	195	9	-	-	SYM
cana-5596	195	10	529	529	NUM
cana-5596	195	11	.	.	PUNCT
cana-5596	196	1	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	NOUN
cana-5596	196	2	figures	figure	NOUN
cana-5596	196	3	and	and	CCONJ
cana-5596	196	4	tables	table	NOUN
cana-5596	196	5	:	:	PUNCT
cana-5596	196	6	figures	figure	NOUN
cana-5596	196	7	all	all	DET
cana-5596	196	8	figures	figure	NOUN
cana-5596	196	9	in	in	ADP
cana-5596	196	10	this	this	DET
cana-5596	196	11	paper	paper	NOUN
cana-5596	196	12	are	be	AUX
cana-5596	196	13	numbered	number	VERB
cana-5596	196	14	sequentially	sequentially	ADV
cana-5596	196	15	using	use	VERB
cana-5596	196	16	arabic	arabic	ADJ
cana-5596	196	17	numerals	numeral	NOUN
cana-5596	196	18	,	,	PUNCT
cana-5596	196	19	with	with	SCONJ
cana-5596	196	20	individual	individual	ADJ
cana-5596	196	21	figure	figure	NOUN
cana-5596	196	22	parts	part	NOUN
cana-5596	196	23	denoted	denote	VERB
cana-5596	196	24	by	by	ADP
cana-5596	196	25	lowercase	lowercase	NOUN
cana-5596	196	26	letters	letter	NOUN
cana-5596	196	27	(	(	PUNCT
cana-5596	196	28	e.g.	e.g.	ADV
cana-5596	196	29	,	,	PUNCT
cana-5596	196	30	figure	figure	NOUN
cana-5596	196	31	1a	1a	NOUN
cana-5596	196	32	,	,	PUNCT
cana-5596	196	33	figure	figure	NOUN
cana-5596	196	34	1b	1b	NUM
cana-5596	196	35	)	)	PUNCT
cana-5596	196	36	.	.	PUNCT
cana-5596	197	1	each	each	DET
cana-5596	197	2	figure	figure	NOUN
cana-5596	197	3	is	be	AUX
cana-5596	197	4	accompanied	accompany	VERB
cana-5596	197	5	by	by	ADP
cana-5596	197	6	a	a	DET
cana-5596	197	7	concise	concise	ADJ
cana-5596	197	8	caption	caption	NOUN
cana-5596	197	9	that	that	PRON
cana-5596	197	10	accurately	accurately	ADV
cana-5596	197	11	describes	describe	VERB
cana-5596	197	12	its	its	PRON
cana-5596	197	13	content	content	NOUN
cana-5596	197	14	and	and	CCONJ
cana-5596	197	15	relevance	relevance	NOUN
cana-5596	197	16	to	to	ADP
cana-5596	197	17	the	the	DET
cana-5596	197	18	research	research	NOUN
cana-5596	197	19	.	.	PUNCT
cana-5596	198	1	•	•	NUM
cana-5596	198	2	figure	figure	NOUN
cana-5596	198	3	1	1	NUM
cana-5596	198	4	:	:	PUNCT
cana-5596	198	5	architecture	architecture	NOUN
cana-5596	198	6	of	of	ADP
cana-5596	198	7	the	the	DET
cana-5596	198	8	proposed	propose	VERB
cana-5596	198	9	convolutional	convolutional	ADJ
cana-5596	198	10	neural	neural	ADJ
cana-5596	198	11	network	network	NOUN
cana-5596	198	12	(	(	PUNCT
cana-5596	198	13	cnn	cnn	PROPN
cana-5596	198	14	)	)	PUNCT
cana-5596	198	15	,	,	PUNCT
cana-5596	198	16	illustrating	illustrate	VERB
cana-5596	198	17	its	its	PRON
cana-5596	198	18	layers	layer	NOUN
cana-5596	198	19	,	,	PUNCT
cana-5596	198	20	operations	operation	NOUN
cana-5596	198	21	,	,	PUNCT
cana-5596	198	22	and	and	CCONJ
cana-5596	198	23	parameter	parameter	NOUN
cana-5596	198	24	configurations	configuration	NOUN
cana-5596	198	25	.	.	PUNCT
cana-5596	199	1	•	•	NUM
cana-5596	199	2	figure	figure	NOUN
cana-5596	199	3	2	2	NUM
cana-5596	199	4	:	:	PUNCT
cana-5596	199	5	training	training	NOUN
cana-5596	199	6	and	and	CCONJ
cana-5596	199	7	validation	validation	NOUN
cana-5596	199	8	accuracy	accuracy	NOUN
cana-5596	199	9	/	/	SYM
cana-5596	199	10	loss	loss	NOUN
cana-5596	199	11	curves	curve	NOUN
cana-5596	199	12	,	,	PUNCT
cana-5596	199	13	showcasing	showcase	VERB
cana-5596	199	14	the	the	DET
cana-5596	199	15	model	model	NOUN
cana-5596	199	16	's	's	PART
cana-5596	199	17	learning	learning	NOUN
cana-5596	199	18	process	process	NOUN
cana-5596	199	19	and	and	CCONJ
cana-5596	199	20	overfitting	overfitte	VERB
cana-5596	199	21	mitigation	mitigation	NOUN
cana-5596	199	22	.	.	PUNCT
cana-5596	200	1	•	•	NUM
cana-5596	200	2	figure	figure	NOUN
cana-5596	200	3	3	3	NUM
cana-5596	200	4	:	:	PUNCT
cana-5596	200	5	confusion	confusion	NOUN
cana-5596	200	6	matrix	matrix	NOUN
cana-5596	200	7	for	for	ADP
cana-5596	200	8	the	the	DET
cana-5596	200	9	test	test	NOUN
cana-5596	200	10	dataset	dataset	NOUN
cana-5596	200	11	,	,	PUNCT
cana-5596	200	12	depicting	depict	VERB
cana-5596	200	13	model	model	NOUN
cana-5596	200	14	performance	performance	NOUN
cana-5596	200	15	across	across	ADP
cana-5596	200	16	all	all	DET
cana-5596	200	17	classes	class	NOUN
cana-5596	200	18	.	.	PUNCT
cana-5596	201	1	•	•	NUM
cana-5596	201	2	figure	figure	NOUN
cana-5596	201	3	4a	4a	NOUN
cana-5596	201	4	:	:	PUNCT
cana-5596	201	5	a	a	DET
cana-5596	201	6	grad	grad	NOUN
cana-5596	201	7	-	-	PUNCT
cana-5596	201	8	cam	cam	NOUN
cana-5596	201	9	visualization	visualization	NOUN
cana-5596	201	10	highlighting	highlight	VERB
cana-5596	201	11	regions	region	NOUN
cana-5596	201	12	of	of	ADP
cana-5596	201	13	interest	interest	NOUN
cana-5596	201	14	in	in	ADP
cana-5596	201	15	benign	benign	ADJ
cana-5596	201	16	cases	case	NOUN
cana-5596	201	17	.	.	PUNCT
cana-5596	202	1	•	•	NUM
cana-5596	202	2	figure	figure	NOUN
cana-5596	202	3	4b	4b	PROPN
cana-5596	202	4	:	:	PUNCT
cana-5596	202	5	grad	grad	ADJ
cana-5596	202	6	-	-	PUNCT
cana-5596	202	7	cam	cam	NOUN
cana-5596	202	8	visualization	visualization	NOUN
cana-5596	202	9	for	for	ADP
cana-5596	202	10	malignant	malignant	ADJ
cana-5596	202	11	cases	case	NOUN
cana-5596	202	12	.	.	PUNCT
cana-5596	203	1	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	203	2	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	203	3	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	203	4	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	203	5	https://doi.org/10.xxxxx	https://doi.org/10.xxxxx	PROPN
cana-5596	203	6	communications	communication	NOUN
cana-5596	203	7	on	on	ADP
cana-5596	203	8	applied	apply	VERB
cana-5596	203	9	nonlinear	nonlinear	ADJ
cana-5596	203	10	analysis	analysis	NOUN
cana-5596	203	11	issn	issn	NOUN
cana-5596	203	12	:	:	PUNCT
cana-5596	203	13	1074	1074	NUM
cana-5596	203	14	-	-	PUNCT
cana-5596	203	15	133x	133x	NUM
cana-5596	203	16	vol	vol	NOUN
cana-5596	203	17	32	32	NUM
cana-5596	203	18	no	no	NOUN
cana-5596	203	19	.	.	PUNCT
cana-5596	204	1	icmasd	icmasd	NOUN
cana-5596	204	2	(	(	PUNCT
cana-5596	204	3	2025	2025	NUM
cana-5596	204	4	)	)	PUNCT
cana-5596	204	5	1976	1976	NUM
cana-5596	204	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5596	204	7	figures	figure	NOUN
cana-5596	204	8	are	be	AUX
cana-5596	204	9	optimized	optimize	VERB
cana-5596	204	10	for	for	ADP
cana-5596	204	11	publication	publication	NOUN
cana-5596	204	12	using	use	VERB
cana-5596	204	13	vector	vector	NOUN
cana-5596	204	14	graphics	graphic	NOUN
cana-5596	204	15	with	with	ADP
cana-5596	204	16	a	a	DET
cana-5596	204	17	resolution	resolution	NOUN
cana-5596	204	18	of	of	ADP
cana-5596	204	19	at	at	ADV
cana-5596	204	20	least	least	ADJ
cana-5596	204	21	1000	1000	NUM
cana-5596	204	22	dpi	dpi	NOUN
cana-5596	204	23	.	.	PUNCT
cana-5596	205	1	only	only	ADV
cana-5596	205	2	the	the	DET
cana-5596	205	3	most	most	ADV
cana-5596	205	4	critical	critical	ADJ
cana-5596	205	5	figures	figure	NOUN
cana-5596	205	6	are	be	AUX
cana-5596	205	7	included	include	VERB
cana-5596	205	8	in	in	ADP
cana-5596	205	9	the	the	DET
cana-5596	205	10	paper	paper	NOUN
cana-5596	205	11	;	;	PUNCT
cana-5596	205	12	additional	additional	ADJ
cana-5596	205	13	visual	visual	ADJ
cana-5596	205	14	data	datum	NOUN
cana-5596	205	15	,	,	PUNCT
cana-5596	205	16	such	such	ADJ
cana-5596	205	17	as	as	ADP
cana-5596	205	18	alternative	alternative	ADJ
cana-5596	205	19	visualizations	visualization	NOUN
cana-5596	205	20	and	and	CCONJ
cana-5596	205	21	supplementary	supplementary	ADJ
cana-5596	205	22	experiments	experiment	NOUN
cana-5596	205	23	,	,	PUNCT
cana-5596	205	24	are	be	AUX
cana-5596	205	25	provided	provide	VERB
cana-5596	205	26	as	as	ADP
cana-5596	205	27	supplementary	supplementary	ADJ
cana-5596	205	28	information	information	NOUN
cana-5596	205	29	.	.	PUNCT
cana-5596	206	1	tables	table	NOUN
cana-5596	206	2	tables	table	NOUN
cana-5596	206	3	are	be	AUX
cana-5596	206	4	formatted	format	VERB
cana-5596	206	5	to	to	PART
cana-5596	206	6	provide	provide	VERB
cana-5596	206	7	concise	concise	ADJ
cana-5596	206	8	and	and	CCONJ
cana-5596	206	9	accurate	accurate	ADJ
cana-5596	206	10	information	information	NOUN
cana-5596	206	11	that	that	PRON
cana-5596	206	12	complements	complement	VERB
cana-5596	206	13	the	the	DET
cana-5596	206	14	figures	figure	NOUN
cana-5596	206	15	.	.	PUNCT
cana-5596	207	1	numerical	numerical	PROPN
cana-5596	207	2	data	data	PROPN
cana-5596	207	3	is	be	AUX
cana-5596	207	4	presented	present	VERB
cana-5596	207	5	in	in	ADP
cana-5596	207	6	tabular	tabular	PROPN
cana-5596	207	7	format	format	NOUN
cana-5596	207	8	to	to	PART
cana-5596	207	9	avoid	avoid	VERB
cana-5596	207	10	redundancy	redundancy	NOUN
cana-5596	207	11	with	with	ADP
cana-5596	207	12	line	line	NOUN
cana-5596	207	13	graphs	graph	NOUN
cana-5596	207	14	.	.	PUNCT
cana-5596	208	1	each	each	DET
cana-5596	208	2	table	table	NOUN
cana-5596	208	3	has	have	VERB
cana-5596	208	4	a	a	DET
cana-5596	208	5	brief	brief	ADJ
cana-5596	208	6	caption	caption	NOUN
cana-5596	208	7	describing	describe	VERB
cana-5596	208	8	its	its	PRON
cana-5596	208	9	contents	content	NOUN
cana-5596	208	10	.	.	PUNCT
cana-5596	209	1	•	•	NUM
cana-5596	209	2	table	table	NOUN
cana-5596	209	3	1	1	NUM
cana-5596	209	4	:	:	PUNCT
cana-5596	209	5	summary	summary	NOUN
cana-5596	209	6	of	of	ADP
cana-5596	209	7	the	the	DET
cana-5596	209	8	dataset	dataset	NOUN
cana-5596	209	9	distribution	distribution	NOUN
cana-5596	209	10	,	,	PUNCT
cana-5596	209	11	including	include	VERB
cana-5596	209	12	class	class	NOUN
cana-5596	209	13	labels	label	NOUN
cana-5596	209	14	,	,	PUNCT
cana-5596	209	15	sample	sample	NOUN
cana-5596	209	16	counts	count	NOUN
cana-5596	209	17	,	,	PUNCT
cana-5596	209	18	and	and	CCONJ
cana-5596	209	19	image	image	NOUN
cana-5596	209	20	resolutions	resolution	NOUN
cana-5596	209	21	.	.	PUNCT
cana-5596	210	1	•	•	NUM
cana-5596	210	2	table	table	NOUN
cana-5596	210	3	2	2	NUM
cana-5596	210	4	:	:	PUNCT
cana-5596	210	5	ablation	ablation	NOUN
cana-5596	210	6	study	study	NOUN
cana-5596	210	7	results	result	NOUN
cana-5596	210	8	,	,	PUNCT
cana-5596	210	9	showing	show	VERB
cana-5596	210	10	the	the	DET
cana-5596	210	11	impact	impact	NOUN
cana-5596	210	12	of	of	ADP
cana-5596	210	13	different	different	ADJ
cana-5596	210	14	architectural	architectural	ADJ
cana-5596	210	15	and	and	CCONJ
cana-5596	210	16	preprocessing	preprocesse	VERB
cana-5596	210	17	choices	choice	NOUN
cana-5596	210	18	on	on	ADP
cana-5596	210	19	model	model	NOUN
cana-5596	210	20	performance	performance	NOUN
cana-5596	210	21	.	.	PUNCT
cana-5596	211	1	•	•	NUM
cana-5596	211	2	table	table	NOUN
cana-5596	211	3	3	3	NUM
cana-5596	211	4	:	:	PUNCT
cana-5596	211	5	performance	performance	NOUN
cana-5596	211	6	comparison	comparison	NOUN
cana-5596	211	7	of	of	ADP
cana-5596	211	8	the	the	DET
cana-5596	211	9	proposed	propose	VERB
cana-5596	211	10	model	model	NOUN
cana-5596	211	11	with	with	ADP
cana-5596	211	12	recent	recent	ADJ
cana-5596	211	13	publications	publication	NOUN
cana-5596	211	14	,	,	PUNCT
cana-5596	211	15	detailing	detail	VERB
cana-5596	211	16	metrics	metric	NOUN
cana-5596	211	17	such	such	ADJ
cana-5596	211	18	as	as	ADP
cana-5596	211	19	accuracy	accuracy	NOUN
cana-5596	211	20	,	,	PUNCT
cana-5596	211	21	precision	precision	NOUN
cana-5596	211	22	,	,	PUNCT
cana-5596	211	23	recall	recall	NOUN
cana-5596	211	24	,	,	PUNCT
cana-5596	211	25	and	and	CCONJ
cana-5596	211	26	f1	f1	NOUN
cana-5596	211	27	-	-	PUNCT
cana-5596	211	28	score	score	NOUN
cana-5596	211	29	.	.	PUNCT
cana-5596	212	1	captions	caption	NOUN
cana-5596	212	2	•	•	NUM
cana-5596	212	3	figure	figure	NOUN
cana-5596	212	4	captions	caption	NOUN
cana-5596	212	5	:	:	PUNCT
cana-5596	212	6	captions	caption	NOUN
cana-5596	212	7	are	be	AUX
cana-5596	212	8	written	write	VERB
cana-5596	212	9	in	in	ADP
cana-5596	212	10	the	the	DET
cana-5596	212	11	format	format	NOUN
cana-5596	212	12	“	"	PUNCT
cana-5596	212	13	figure	figure	NOUN
cana-5596	212	14	[	[	X
cana-5596	212	15	number	number	NOUN
cana-5596	212	16	]	]	PUNCT
cana-5596	213	1	[	[	X
cana-5596	213	2	caption	caption	NOUN
cana-5596	213	3	description	description	NOUN
cana-5596	213	4	]	]	PUNCT
cana-5596	213	5	,	,	PUNCT
cana-5596	213	6	”	"	PUNCT
cana-5596	213	7	with	with	ADP
cana-5596	213	8	no	no	DET
cana-5596	213	9	punctuation	punctuation	NOUN
cana-5596	213	10	after	after	ADP
cana-5596	213	11	the	the	DET
cana-5596	213	12	figure	figure	NOUN
cana-5596	213	13	number	number	NOUN
cana-5596	213	14	or	or	CCONJ
cana-5596	213	15	caption	caption	NOUN
cana-5596	213	16	.	.	PUNCT
cana-5596	214	1	for	for	ADP
cana-5596	214	2	example	example	NOUN
cana-5596	214	3	:	:	PUNCT
cana-5596	214	4	o	o	NOUN
cana-5596	214	5	figure	figure	NOUN
cana-5596	214	6	1	1	NUM
cana-5596	214	7	architecture	architecture	NOUN
cana-5596	214	8	of	of	ADP
cana-5596	214	9	the	the	DET
cana-5596	214	10	cnn	cnn	PROPN
cana-5596	214	11	used	use	VERB
cana-5596	214	12	in	in	ADP
cana-5596	214	13	this	this	DET
cana-5596	214	14	study	study	NOUN
cana-5596	214	15	.	.	PUNCT
cana-5596	215	1	o	o	NOUN
cana-5596	215	2	figure	figure	NOUN
cana-5596	215	3	2	2	NUM
cana-5596	215	4	grad	grad	NOUN
cana-5596	215	5	-	-	PUNCT
cana-5596	215	6	cam	cam	NOUN
cana-5596	215	7	visualizations	visualization	NOUN
cana-5596	215	8	for	for	ADP
cana-5596	215	9	malignant	malignant	ADJ
cana-5596	215	10	and	and	CCONJ
cana-5596	215	11	benign	benign	ADJ
cana-5596	215	12	cases	case	NOUN
cana-5596	215	13	.	.	PUNCT
cana-5596	216	1	•	•	NUM
cana-5596	216	2	table	table	NOUN
cana-5596	216	3	captions	caption	NOUN
cana-5596	216	4	:	:	PUNCT
cana-5596	216	5	table	table	NOUN
cana-5596	216	6	captions	caption	NOUN
cana-5596	216	7	are	be	AUX
cana-5596	216	8	written	write	VERB
cana-5596	216	9	in	in	ADP
cana-5596	216	10	bold	bold	ADJ
cana-5596	216	11	,	,	PUNCT
cana-5596	216	12	followed	follow	VERB
cana-5596	216	13	by	by	ADP
cana-5596	216	14	a	a	DET
cana-5596	216	15	number	number	NOUN
cana-5596	216	16	in	in	ADP
cana-5596	216	17	bold	bold	ADJ
cana-5596	216	18	and	and	CCONJ
cana-5596	216	19	the	the	DET
cana-5596	216	20	caption	caption	NOUN
cana-5596	216	21	in	in	ADP
cana-5596	216	22	normal	normal	ADJ
cana-5596	216	23	font	font	NOUN
cana-5596	216	24	.	.	PUNCT
cana-5596	217	1	no	no	DET
cana-5596	217	2	punctuation	punctuation	NOUN
cana-5596	217	3	follows	follow	VERB
cana-5596	217	4	the	the	DET
cana-5596	217	5	table	table	NOUN
cana-5596	217	6	number	number	NOUN
cana-5596	217	7	or	or	CCONJ
cana-5596	217	8	caption	caption	NOUN
cana-5596	217	9	.	.	PUNCT
cana-5596	218	1	for	for	ADP
cana-5596	218	2	example	example	NOUN
cana-5596	218	3	:	:	PUNCT
cana-5596	218	4	o	o	NOUN
cana-5596	218	5	table	table	NOUN
cana-5596	218	6	1	1	NUM
cana-5596	218	7	dataset	dataset	NOUN
cana-5596	218	8	distribution	distribution	NOUN
cana-5596	218	9	and	and	CCONJ
cana-5596	218	10	characteristics	characteristic	NOUN
cana-5596	218	11	.	.	PUNCT
cana-5596	219	1	o	o	NOUN
cana-5596	219	2	table	table	NOUN
cana-5596	219	3	2	2	NUM
cana-5596	219	4	model	model	NOUN
cana-5596	219	5	performance	performance	NOUN
cana-5596	219	6	metrics	metric	NOUN
cana-5596	219	7	across	across	ADP
cana-5596	219	8	benchmarks	benchmark	NOUN
cana-5596	219	9	.	.	PUNCT
cana-5596	220	1	supplementary	supplementary	ADJ
cana-5596	220	2	information	information	NOUN
cana-5596	220	3	additional	additional	ADJ
cana-5596	220	4	figures	figure	NOUN
cana-5596	220	5	and	and	CCONJ
cana-5596	220	6	tables	table	NOUN
cana-5596	220	7	that	that	PRON
cana-5596	220	8	could	could	AUX
cana-5596	220	9	not	not	PART
cana-5596	220	10	be	be	AUX
cana-5596	220	11	included	include	VERB
cana-5596	220	12	in	in	ADP
cana-5596	220	13	the	the	DET
cana-5596	220	14	main	main	ADJ
cana-5596	220	15	text	text	NOUN
cana-5596	220	16	due	due	ADP
cana-5596	220	17	to	to	ADP
cana-5596	220	18	space	space	NOUN
cana-5596	220	19	constraints	constraint	NOUN
cana-5596	220	20	are	be	AUX
cana-5596	220	21	available	available	ADJ
cana-5596	220	22	as	as	ADP
cana-5596	220	23	supplementary	supplementary	ADJ
cana-5596	220	24	information	information	NOUN
cana-5596	220	25	.	.	PUNCT
cana-5596	221	1	these	these	PRON
cana-5596	221	2	include	include	VERB
cana-5596	221	3	:	:	PUNCT
cana-5596	221	4	•	•	NUM
cana-5596	221	5	detailed	detailed	ADJ
cana-5596	221	6	grad	grad	NOUN
cana-5596	221	7	-	-	PUNCT
cana-5596	221	8	cam	cam	NOUN
cana-5596	221	9	visualizations	visualization	NOUN
cana-5596	221	10	for	for	ADP
cana-5596	221	11	specific	specific	ADJ
cana-5596	221	12	case	case	NOUN
cana-5596	221	13	studies	study	NOUN
cana-5596	221	14	.	.	PUNCT
cana-5596	222	1	•	•	NUM
cana-5596	222	2	comprehensive	comprehensive	ADJ
cana-5596	222	3	results	result	NOUN
cana-5596	222	4	of	of	ADP
cana-5596	222	5	hyperparameter	hyperparameter	NOUN
cana-5596	222	6	tuning	tune	VERB
cana-5596	222	7	experiments	experiment	NOUN
cana-5596	222	8	.	.	PUNCT
cana-5596	223	1	•	•	NUM
cana-5596	223	2	additional	additional	ADJ
cana-5596	223	3	performance	performance	NOUN
cana-5596	223	4	metrics	metric	NOUN
cana-5596	223	5	across	across	ADP
cana-5596	223	6	alternate	alternate	ADJ
cana-5596	223	7	datasets	dataset	NOUN
cana-5596	223	8	.	.	PUNCT
cana-5596	224	1	by	by	ADP
cana-5596	224	2	adhering	adhere	VERB
cana-5596	224	3	to	to	ADP
cana-5596	224	4	these	these	DET
cana-5596	224	5	guidelines	guideline	NOUN
cana-5596	224	6	,	,	PUNCT
cana-5596	224	7	the	the	DET
cana-5596	224	8	paper	paper	NOUN
cana-5596	224	9	ensures	ensure	VERB
cana-5596	224	10	clarity	clarity	NOUN
cana-5596	224	11	and	and	CCONJ
cana-5596	224	12	consistency	consistency	NOUN
cana-5596	224	13	in	in	ADP
cana-5596	224	14	presenting	present	VERB
cana-5596	224	15	visual	visual	ADJ
cana-5596	224	16	and	and	CCONJ
cana-5596	224	17	tabular	tabular	PROPN
cana-5596	224	18	data	datum	NOUN
cana-5596	224	19	,	,	PUNCT
cana-5596	224	20	enhancing	enhance	VERB
cana-5596	224	21	the	the	DET
cana-5596	224	22	reader	reader	NOUN
cana-5596	224	23	's	's	PART
cana-5596	224	24	understanding	understanding	NOUN
cana-5596	224	25	of	of	ADP
cana-5596	224	26	the	the	DET
cana-5596	224	27	study	study	NOUN
cana-5596	224	28	.	.	PUNCT