id	sid	tid	token	lemma	pos
cana-5024	1	1	communications	communication	NOUN
cana-5024	1	2	on	on	ADP
cana-5024	1	3	applied	apply	VERB
cana-5024	1	4	nonlinear	nonlinear	ADJ
cana-5024	1	5	analysis	analysis	NOUN
cana-5024	1	6	issn	issn	NOUN
cana-5024	1	7	:	:	PUNCT
cana-5024	1	8	1074	1074	NUM
cana-5024	1	9	-	-	PUNCT
cana-5024	1	10	133x	133x	NUM
cana-5024	1	11	vol	vol	VERB
cana-5024	1	12	32	32	NUM
cana-5024	1	13	no.1s	no.1s	PROPN
cana-5024	1	14	(	(	PUNCT
cana-5024	1	15	2025	2025	NUM
cana-5024	1	16	)	)	PUNCT
cana-5024	1	17	643	643	NUM
cana-5024	1	18	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	1	19	enhancing	enhance	VERB
cana-5024	1	20	the	the	DET
cana-5024	1	21	precision	precision	NOUN
cana-5024	1	22	of	of	ADP
cana-5024	1	23	skin	skin	NOUN
cana-5024	1	24	cancer	cancer	NOUN
cana-5024	1	25	diagnosis	diagnosis	NOUN
cana-5024	1	26	by	by	ADP
cana-5024	1	27	leveraging	leverage	VERB
cana-5024	1	28	advanced	advanced	ADJ
cana-5024	1	29	deep	deep	ADJ
cana-5024	1	30	learning	learning	NOUN
cana-5024	1	31	techniques	technique	NOUN
cana-5024	1	32	integrated	integrate	VERB
cana-5024	1	33	with	with	ADP
cana-5024	1	34	optimization	optimization	NOUN
cana-5024	1	35	strategies	strategy	NOUN
cana-5024	1	36	dr	dr	PROPN
cana-5024	1	37	.	.	PROPN
cana-5024	1	38	s.	s.	PROPN
cana-5024	1	39	senthamizhselvi	senthamizhselvi	VERB
cana-5024	1	40	1	1	NUM
cana-5024	1	41	,	,	PUNCT
cana-5024	1	42	dr	dr	PROPN
cana-5024	1	43	.	.	PROPN
cana-5024	1	44	r.	r.	PROPN
cana-5024	1	45	vijay	vijay	PROPN
cana-5024	1	46	arumugam2	arumugam2	PROPN
cana-5024	1	47	*	*	SYM
cana-5024	1	48	1	1	NUM
cana-5024	1	49	assistant	assistant	NOUN
cana-5024	1	50	professor	professor	NOUN
cana-5024	1	51	,	,	PUNCT
cana-5024	1	52	dept	dept	NOUN
cana-5024	1	53	.	.	PROPN
cana-5024	1	54	of	of	ADP
cana-5024	1	55	computer	computer	NOUN
cana-5024	1	56	science	science	NOUN
cana-5024	1	57	,	,	PUNCT
cana-5024	1	58	d.	d.	PROPN
cana-5024	1	59	g.	g.	PROPN
cana-5024	1	60	govt	govt	PROPN
cana-5024	1	61	.	.	PUNCT
cana-5024	2	1	arts	art	NOUN
cana-5024	2	2	college	college	PROPN
cana-5024	2	3	for	for	ADP
cana-5024	2	4	women	woman	NOUN
cana-5024	2	5	,	,	PUNCT
cana-5024	2	6	mayiladuthurai	mayiladuthurai	PROPN
cana-5024	2	7	,	,	PUNCT
cana-5024	2	8	tamil	tamil	PROPN
cana-5024	2	9	nadu	nadu	PROPN
cana-5024	2	10	,	,	PUNCT
cana-5024	2	11	india	india	PROPN
cana-5024	2	12	.	.	PUNCT
cana-5024	3	1	2assistant	2assistant	NUM
cana-5024	3	2	professor	professor	NOUN
cana-5024	3	3	,	,	PUNCT
cana-5024	3	4	department	department	NOUN
cana-5024	3	5	of	of	ADP
cana-5024	3	6	computer	computer	NOUN
cana-5024	3	7	science	science	NOUN
cana-5024	3	8	,	,	PUNCT
cana-5024	3	9	government	government	NOUN
cana-5024	3	10	arts	art	NOUN
cana-5024	3	11	and	and	CCONJ
cana-5024	3	12	science	science	PROPN
cana-5024	3	13	college	college	PROPN
cana-5024	3	14	,	,	PUNCT
cana-5024	3	15	manalmedu	manalmedu	PROPN
cana-5024	3	16	,	,	PUNCT
cana-5024	3	17	tamil	tamil	PROPN
cana-5024	3	18	nadu	nadu	PROPN
cana-5024	3	19	,	,	PUNCT
cana-5024	3	20	india	india	PROPN
cana-5024	3	21	.	.	PUNCT
cana-5024	3	22	email	email	NOUN
cana-5024	3	23	:	:	PUNCT
cana-5024	3	24	1selvikarthi2002@gmail.com	1selvikarthi2002@gmail.com	NUM
cana-5024	3	25	corresponding	corresponding	NOUN
cana-5024	3	26	email	email	NOUN
cana-5024	3	27	:	:	PUNCT
cana-5024	3	28	2*vijaynew@gmail.com	2*vijaynew@gmail.com	NUM
cana-5024	3	29	article	article	NOUN
cana-5024	3	30	history	history	NOUN
cana-5024	3	31	:	:	PUNCT
cana-5024	3	32	received	receive	VERB
cana-5024	3	33	:	:	PUNCT
cana-5024	3	34	09	09	NUM
cana-5024	3	35	-	-	SYM
cana-5024	3	36	11	11	NUM
cana-5024	3	37	-	-	PUNCT
cana-5024	3	38	2024	2024	NUM
cana-5024	3	39	revised	revise	VERB
cana-5024	3	40	:	:	PUNCT
cana-5024	3	41	10	10	NUM
cana-5024	3	42	-	-	SYM
cana-5024	3	43	01	01	NUM
cana-5024	3	44	-	-	PUNCT
cana-5024	3	45	2025	2025	NUM
cana-5024	3	46	accepted	accept	VERB
cana-5024	3	47	:	:	PUNCT
cana-5024	3	48	15	15	NUM
cana-5024	3	49	-	-	NUM
cana-5024	3	50	02	02	NUM
cana-5024	3	51	-	-	PUNCT
cana-5024	3	52	2025	2025	NUM
cana-5024	3	53	abstract	abstract	NOUN
cana-5024	3	54	:	:	PUNCT
cana-5024	4	1	melanoma	melanoma	NOUN
cana-5024	4	2	,	,	PUNCT
cana-5024	4	3	a	a	DET
cana-5024	4	4	particularly	particularly	ADV
cana-5024	4	5	aggressive	aggressive	ADJ
cana-5024	4	6	variant	variant	NOUN
cana-5024	4	7	of	of	ADP
cana-5024	4	8	skin	skin	NOUN
cana-5024	4	9	cancer	cancer	NOUN
cana-5024	4	10	,	,	PUNCT
cana-5024	4	11	continues	continue	VERB
cana-5024	4	12	to	to	PART
cana-5024	4	13	represent	represent	VERB
cana-5024	4	14	a	a	DET
cana-5024	4	15	significant	significant	ADJ
cana-5024	4	16	global	global	ADJ
cana-5024	4	17	health	health	NOUN
cana-5024	4	18	concern	concern	NOUN
cana-5024	4	19	due	due	ADP
cana-5024	4	20	to	to	ADP
cana-5024	4	21	its	its	PRON
cana-5024	4	22	high	high	ADJ
cana-5024	4	23	incidence	incidence	NOUN
cana-5024	4	24	and	and	CCONJ
cana-5024	4	25	mortality	mortality	NOUN
cana-5024	4	26	rates	rate	NOUN
cana-5024	4	27	.	.	PUNCT
cana-5024	5	1	early	early	ADJ
cana-5024	5	2	and	and	CCONJ
cana-5024	5	3	precise	precise	ADJ
cana-5024	5	4	diagnosis	diagnosis	NOUN
cana-5024	5	5	is	be	AUX
cana-5024	5	6	vital	vital	ADJ
cana-5024	5	7	for	for	ADP
cana-5024	5	8	improving	improve	VERB
cana-5024	5	9	patient	patient	ADJ
cana-5024	5	10	outcomes	outcome	NOUN
cana-5024	5	11	and	and	CCONJ
cana-5024	5	12	enabling	enable	VERB
cana-5024	5	13	timely	timely	ADJ
cana-5024	5	14	therapeutic	therapeutic	ADJ
cana-5024	5	15	intervention	intervention	NOUN
cana-5024	5	16	.	.	PUNCT
cana-5024	6	1	this	this	DET
cana-5024	6	2	study	study	NOUN
cana-5024	6	3	introduces	introduce	VERB
cana-5024	6	4	a	a	DET
cana-5024	6	5	sophisticated	sophisticated	ADJ
cana-5024	6	6	diagnostic	diagnostic	ADJ
cana-5024	6	7	architecture	architecture	NOUN
cana-5024	6	8	that	that	PRON
cana-5024	6	9	synergizes	synergize	VERB
cana-5024	6	10	deep	deep	ADJ
cana-5024	6	11	learning	learning	NOUN
cana-5024	6	12	methodologies	methodology	NOUN
cana-5024	6	13	with	with	ADP
cana-5024	6	14	optimization	optimization	NOUN
cana-5024	6	15	algorithms	algorithm	NOUN
cana-5024	6	16	to	to	PART
cana-5024	6	17	bolster	bolster	VERB
cana-5024	6	18	the	the	DET
cana-5024	6	19	accuracy	accuracy	NOUN
cana-5024	6	20	of	of	ADP
cana-5024	6	21	skin	skin	NOUN
cana-5024	6	22	cancer	cancer	NOUN
cana-5024	6	23	classification	classification	NOUN
cana-5024	6	24	.	.	PUNCT
cana-5024	7	1	specifically	specifically	ADV
cana-5024	7	2	,	,	PUNCT
cana-5024	7	3	we	we	PRON
cana-5024	7	4	implement	implement	VERB
cana-5024	7	5	convolutional	convolutional	ADJ
cana-5024	7	6	neural	neural	ADJ
cana-5024	7	7	networks	network	NOUN
cana-5024	7	8	(	(	PUNCT
cana-5024	7	9	cnns	cnns	PROPN
cana-5024	7	10	)	)	PUNCT
cana-5024	7	11	augmented	augment	VERB
cana-5024	7	12	by	by	ADP
cana-5024	7	13	systematic	systematic	ADJ
cana-5024	7	14	hyperparameter	hyperparameter	NOUN
cana-5024	7	15	optimization	optimization	NOUN
cana-5024	7	16	utilizing	utilize	VERB
cana-5024	7	17	evolutionary	evolutionary	ADJ
cana-5024	7	18	computation	computation	NOUN
cana-5024	7	19	and	and	CCONJ
cana-5024	7	20	related	related	ADJ
cana-5024	7	21	techniques	technique	NOUN
cana-5024	7	22	.	.	PUNCT
cana-5024	8	1	the	the	DET
cana-5024	8	2	proposed	propose	VERB
cana-5024	8	3	model	model	NOUN
cana-5024	8	4	is	be	AUX
cana-5024	8	5	trained	train	VERB
cana-5024	8	6	and	and	CCONJ
cana-5024	8	7	evaluated	evaluate	VERB
cana-5024	8	8	using	use	VERB
cana-5024	8	9	the	the	DET
cana-5024	8	10	ham10000	ham10000	PROPN
cana-5024	8	11	dataset	dataset	NOUN
cana-5024	8	12	,	,	PUNCT
cana-5024	8	13	which	which	PRON
cana-5024	8	14	contains	contain	VERB
cana-5024	8	15	a	a	DET
cana-5024	8	16	diverse	diverse	ADJ
cana-5024	8	17	array	array	NOUN
cana-5024	8	18	of	of	ADP
cana-5024	8	19	dermatoscopic	dermatoscopic	NOUN
cana-5024	8	20	images	image	NOUN
cana-5024	8	21	.	.	PUNCT
cana-5024	9	1	our	our	PRON
cana-5024	9	2	empirical	empirical	ADJ
cana-5024	9	3	findings	finding	NOUN
cana-5024	9	4	reveal	reveal	VERB
cana-5024	9	5	that	that	SCONJ
cana-5024	9	6	the	the	DET
cana-5024	9	7	integrated	integrate	VERB
cana-5024	9	8	framework	framework	NOUN
cana-5024	9	9	outperforms	outperform	VERB
cana-5024	9	10	conventional	conventional	ADJ
cana-5024	9	11	cnn	cnn	PROPN
cana-5024	9	12	-	-	PUNCT
cana-5024	9	13	based	base	VERB
cana-5024	9	14	approaches	approach	NOUN
cana-5024	9	15	,	,	PUNCT
cana-5024	9	16	yielding	yield	VERB
cana-5024	9	17	notable	notable	ADJ
cana-5024	9	18	enhancements	enhancement	NOUN
cana-5024	9	19	in	in	ADP
cana-5024	9	20	accuracy	accuracy	NOUN
cana-5024	9	21	,	,	PUNCT
cana-5024	9	22	sensitivity	sensitivity	NOUN
cana-5024	9	23	,	,	PUNCT
cana-5024	9	24	and	and	CCONJ
cana-5024	9	25	specificity	specificity	NOUN
cana-5024	9	26	.	.	PUNCT
cana-5024	10	1	these	these	DET
cana-5024	10	2	results	result	NOUN
cana-5024	10	3	underscore	underscore	VERB
cana-5024	10	4	the	the	DET
cana-5024	10	5	efficacy	efficacy	NOUN
cana-5024	10	6	of	of	ADP
cana-5024	10	7	combining	combine	VERB
cana-5024	10	8	deep	deep	ADJ
cana-5024	10	9	learning	learning	NOUN
cana-5024	10	10	with	with	ADP
cana-5024	10	11	optimization	optimization	NOUN
cana-5024	10	12	strategies	strategy	NOUN
cana-5024	10	13	to	to	PART
cana-5024	10	14	advance	advance	VERB
cana-5024	10	15	the	the	DET
cana-5024	10	16	early	early	ADJ
cana-5024	10	17	detection	detection	NOUN
cana-5024	10	18	and	and	CCONJ
cana-5024	10	19	reliable	reliable	ADJ
cana-5024	10	20	classification	classification	NOUN
cana-5024	10	21	of	of	ADP
cana-5024	10	22	skin	skin	NOUN
cana-5024	10	23	cancer	cancer	NOUN
cana-5024	10	24	.	.	PUNCT
cana-5024	11	1	keywords	keyword	NOUN
cana-5024	11	2	:	:	PUNCT
cana-5024	11	3	skin	skin	NOUN
cana-5024	11	4	cancer	cancer	NOUN
cana-5024	11	5	diagnosis	diagnosis	NOUN
cana-5024	11	6	,	,	PUNCT
cana-5024	11	7	deep	deep	ADJ
cana-5024	11	8	learning	learning	NOUN
cana-5024	11	9	,	,	PUNCT
cana-5024	11	10	convolutional	convolutional	ADJ
cana-5024	11	11	neural	neural	ADJ
cana-5024	11	12	networks	network	NOUN
cana-5024	11	13	(	(	PUNCT
cana-5024	11	14	cnns	cnns	PROPN
cana-5024	11	15	)	)	PUNCT
cana-5024	11	16	,	,	PUNCT
cana-5024	11	17	optimization	optimization	NOUN
cana-5024	11	18	techniques	technique	NOUN
cana-5024	11	19	,	,	PUNCT
cana-5024	11	20	and	and	CCONJ
cana-5024	11	21	medical	medical	ADJ
cana-5024	11	22	image	image	NOUN
cana-5024	11	23	classification	classification	NOUN
cana-5024	11	24	.	.	PUNCT
cana-5024	12	1	1	1	X
cana-5024	12	2	.	.	X
cana-5024	12	3	introduction	introduction	NOUN
cana-5024	12	4	skin	skin	NOUN
cana-5024	12	5	cancer	cancer	NOUN
cana-5024	12	6	continues	continue	VERB
cana-5024	12	7	to	to	PART
cana-5024	12	8	exhibit	exhibit	VERB
cana-5024	12	9	a	a	DET
cana-5024	12	10	sharp	sharp	ADJ
cana-5024	12	11	global	global	ADJ
cana-5024	12	12	rise	rise	NOUN
cana-5024	12	13	in	in	ADP
cana-5024	12	14	incidence	incidence	NOUN
cana-5024	12	15	,	,	PUNCT
cana-5024	12	16	with	with	ADP
cana-5024	12	17	millions	million	NOUN
cana-5024	12	18	of	of	ADP
cana-5024	12	19	new	new	ADJ
cana-5024	12	20	diagnoses	diagnosis	NOUN
cana-5024	12	21	emerging	emerge	VERB
cana-5024	12	22	annually	annually	ADV
cana-5024	12	23	.	.	PUNCT
cana-5024	13	1	among	among	ADP
cana-5024	13	2	its	its	PRON
cana-5024	13	3	various	various	ADJ
cana-5024	13	4	forms	form	NOUN
cana-5024	13	5	,	,	PUNCT
cana-5024	13	6	melanoma	melanoma	NOUN
cana-5024	13	7	remains	remain	VERB
cana-5024	13	8	the	the	DET
cana-5024	13	9	most	most	ADJ
cana-5024	13	10	life	life	NOUN
cana-5024	13	11	-	-	PUNCT
cana-5024	13	12	threatening	threaten	VERB
cana-5024	13	13	due	due	ADP
cana-5024	13	14	to	to	ADP
cana-5024	13	15	its	its	PRON
cana-5024	13	16	rapid	rapid	ADJ
cana-5024	13	17	metastatic	metastatic	ADJ
cana-5024	13	18	progression	progression	NOUN
cana-5024	13	19	.	.	PUNCT
cana-5024	14	1	conventional	conventional	ADJ
cana-5024	14	2	diagnostic	diagnostic	ADJ
cana-5024	14	3	practices	practice	NOUN
cana-5024	14	4	are	be	AUX
cana-5024	14	5	predominantly	predominantly	ADV
cana-5024	14	6	reliant	reliant	ADJ
cana-5024	14	7	on	on	ADP
cana-5024	14	8	clinical	clinical	ADJ
cana-5024	14	9	expertise	expertise	NOUN
cana-5024	14	10	,	,	PUNCT
cana-5024	14	11	which	which	PRON
cana-5024	14	12	may	may	AUX
cana-5024	14	13	introduce	introduce	VERB
cana-5024	14	14	subjectivity	subjectivity	NOUN
cana-5024	14	15	and	and	CCONJ
cana-5024	14	16	variability	variability	NOUN
cana-5024	14	17	in	in	ADP
cana-5024	14	18	assessments	assessment	NOUN
cana-5024	14	19	.	.	PUNCT
cana-5024	15	1	in	in	ADP
cana-5024	15	2	light	light	NOUN
cana-5024	15	3	of	of	ADP
cana-5024	15	4	recent	recent	ADJ
cana-5024	15	5	advancements	advancement	NOUN
cana-5024	15	6	in	in	ADP
cana-5024	15	7	artificial	artificial	ADJ
cana-5024	15	8	intelligence	intelligence	NOUN
cana-5024	15	9	particularly	particularly	ADV
cana-5024	15	10	deep	deep	ADJ
cana-5024	15	11	learning	learn	VERB
cana-5024	15	12	automated	automate	VERB
cana-5024	15	13	diagnostic	diagnostic	ADJ
cana-5024	15	14	systems	system	NOUN
cana-5024	15	15	have	have	AUX
cana-5024	15	16	emerged	emerge	VERB
cana-5024	15	17	as	as	ADP
cana-5024	15	18	a	a	DET
cana-5024	15	19	compelling	compelling	ADJ
cana-5024	15	20	alternative	alternative	NOUN
cana-5024	15	21	to	to	PART
cana-5024	15	22	support	support	VERB
cana-5024	15	23	more	more	ADV
cana-5024	15	24	consistent	consistent	ADJ
cana-5024	15	25	and	and	CCONJ
cana-5024	15	26	accurate	accurate	ADJ
cana-5024	15	27	evaluations	evaluation	NOUN
cana-5024	15	28	while	while	SCONJ
cana-5024	15	29	reducing	reduce	VERB
cana-5024	15	30	diagnostic	diagnostic	ADJ
cana-5024	15	31	latency	latency	NOUN
cana-5024	15	32	.	.	PUNCT
cana-5024	16	1	a	a	DET
cana-5024	16	2	growing	grow	VERB
cana-5024	16	3	body	body	NOUN
cana-5024	16	4	of	of	ADP
cana-5024	16	5	research	research	NOUN
cana-5024	16	6	has	have	AUX
cana-5024	16	7	demonstrated	demonstrate	VERB
cana-5024	16	8	the	the	DET
cana-5024	16	9	effectiveness	effectiveness	NOUN
cana-5024	16	10	of	of	ADP
cana-5024	16	11	convolutional	convolutional	ADJ
cana-5024	16	12	neural	neural	ADJ
cana-5024	16	13	networks	network	NOUN
cana-5024	16	14	(	(	PUNCT
cana-5024	16	15	cnns	cnns	PROPN
cana-5024	16	16	)	)	PUNCT
cana-5024	16	17	in	in	ADP
cana-5024	16	18	the	the	DET
cana-5024	16	19	classification	classification	NOUN
cana-5024	16	20	of	of	ADP
cana-5024	16	21	medical	medical	ADJ
cana-5024	16	22	imagery	imagery	NOUN
cana-5024	16	23	,	,	PUNCT
cana-5024	16	24	including	include	VERB
cana-5024	16	25	dermatological	dermatological	ADJ
cana-5024	16	26	conditions	condition	NOUN
cana-5024	16	27	.	.	PUNCT
cana-5024	17	1	nonetheless	nonetheless	ADV
cana-5024	17	2	,	,	PUNCT
cana-5024	17	3	the	the	DET
cana-5024	17	4	performance	performance	NOUN
cana-5024	17	5	of	of	ADP
cana-5024	17	6	cnns	cnns	PROPN
cana-5024	17	7	is	be	AUX
cana-5024	17	8	intricately	intricately	ADV
cana-5024	17	9	influenced	influence	VERB
cana-5024	17	10	by	by	ADP
cana-5024	17	11	the	the	DET
cana-5024	17	12	selection	selection	NOUN
cana-5024	17	13	of	of	ADP
cana-5024	17	14	hyperparameters	hyperparameter	NOUN
cana-5024	17	15	and	and	CCONJ
cana-5024	17	16	architectural	architectural	ADJ
cana-5024	17	17	configurations	configuration	NOUN
cana-5024	17	18	.	.	PUNCT
cana-5024	18	1	this	this	DET
cana-5024	18	2	study	study	NOUN
cana-5024	18	3	presents	present	VERB
cana-5024	18	4	an	an	DET
cana-5024	18	5	innovative	innovative	ADJ
cana-5024	18	6	mailto:selvikarthi2002@gmail.com	mailto:selvikarthi2002@gmail.com	NOUN
cana-5024	18	7	mailto:2*vijaynew@gmail.com	mailto:2*vijaynew@gmail.com	X
cana-5024	18	8	communications	communication	NOUN
cana-5024	18	9	on	on	ADP
cana-5024	18	10	applied	apply	VERB
cana-5024	18	11	nonlinear	nonlinear	ADJ
cana-5024	18	12	analysis	analysis	NOUN
cana-5024	18	13	issn	issn	NOUN
cana-5024	18	14	:	:	PUNCT
cana-5024	18	15	1074	1074	NUM
cana-5024	18	16	-	-	PUNCT
cana-5024	18	17	133x	133x	NUM
cana-5024	18	18	vol	vol	VERB
cana-5024	18	19	32	32	NUM
cana-5024	18	20	no.1s	no.1s	PROPN
cana-5024	18	21	(	(	PUNCT
cana-5024	18	22	2025	2025	NUM
cana-5024	18	23	)	)	PUNCT
cana-5024	18	24	644	644	NUM
cana-5024	18	25	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	18	26	diagnostic	diagnostic	ADJ
cana-5024	18	27	methodology	methodology	NOUN
cana-5024	18	28	that	that	PRON
cana-5024	18	29	integrates	integrate	VERB
cana-5024	18	30	deep	deep	ADJ
cana-5024	18	31	learning	learning	NOUN
cana-5024	18	32	with	with	ADP
cana-5024	18	33	optimization	optimization	NOUN
cana-5024	18	34	techniques	technique	NOUN
cana-5024	18	35	to	to	PART
cana-5024	18	36	systematically	systematically	ADV
cana-5024	18	37	fine	fine	ADJ
cana-5024	18	38	-	-	PUNCT
cana-5024	18	39	tune	tune	NOUN
cana-5024	18	40	model	model	NOUN
cana-5024	18	41	parameters	parameter	NOUN
cana-5024	18	42	,	,	PUNCT
cana-5024	18	43	thereby	thereby	ADV
cana-5024	18	44	enhancing	enhance	VERB
cana-5024	18	45	classification	classification	NOUN
cana-5024	18	46	accuracy	accuracy	NOUN
cana-5024	18	47	.	.	PUNCT
cana-5024	19	1	the	the	DET
cana-5024	19	2	ham10000	ham10000	PROPN
cana-5024	19	3	dataset	dataset	PROPN
cana-5024	19	4	,	,	PUNCT
cana-5024	19	5	a	a	DET
cana-5024	19	6	well	well	ADV
cana-5024	19	7	-	-	PUNCT
cana-5024	19	8	established	establish	VERB
cana-5024	19	9	benchmark	benchmark	NOUN
cana-5024	19	10	comprising	comprising	NOUN
cana-5024	19	11	a	a	DET
cana-5024	19	12	diverse	diverse	ADJ
cana-5024	19	13	range	range	NOUN
cana-5024	19	14	of	of	ADP
cana-5024	19	15	dermatoscopic	dermatoscopic	ADJ
cana-5024	19	16	images	image	NOUN
cana-5024	19	17	,	,	PUNCT
cana-5024	19	18	serves	serve	VERB
cana-5024	19	19	as	as	ADP
cana-5024	19	20	the	the	DET
cana-5024	19	21	foundation	foundation	NOUN
cana-5024	19	22	for	for	ADP
cana-5024	19	23	evaluating	evaluate	VERB
cana-5024	19	24	the	the	DET
cana-5024	19	25	proposed	propose	VERB
cana-5024	19	26	framework	framework	NOUN
cana-5024	19	27	’s	’s	PART
cana-5024	19	28	reliability	reliability	NOUN
cana-5024	19	29	and	and	CCONJ
cana-5024	19	30	effectiveness	effectiveness	NOUN
cana-5024	19	31	.	.	PUNCT
cana-5024	20	1	2	2	X
cana-5024	20	2	.	.	X
cana-5024	20	3	review	review	NOUN
cana-5024	20	4	of	of	ADP
cana-5024	20	5	literature	literature	PROPN
cana-5024	20	6	esteva	esteva	PROPN
cana-5024	20	7	et	et	PROPN
cana-5024	20	8	al	al	PROPN
cana-5024	20	9	.	.	PROPN
cana-5024	20	10	provided	provide	VERB
cana-5024	20	11	one	one	NUM
cana-5024	20	12	of	of	ADP
cana-5024	20	13	the	the	DET
cana-5024	20	14	first	first	ADJ
cana-5024	20	15	validations	validation	NOUN
cana-5024	20	16	of	of	ADP
cana-5024	20	17	deep	deep	ADJ
cana-5024	20	18	learning	learning	NOUN
cana-5024	20	19	in	in	ADP
cana-5024	20	20	skin	skin	NOUN
cana-5024	20	21	cancer	cancer	NOUN
cana-5024	20	22	detection	detection	NOUN
cana-5024	20	23	.	.	PUNCT
cana-5024	21	1	it	it	PRON
cana-5024	21	2	marked	mark	VERB
cana-5024	21	3	a	a	DET
cana-5024	21	4	significant	significant	ADJ
cana-5024	21	5	milestone	milestone	NOUN
cana-5024	21	6	in	in	ADP
cana-5024	21	7	applying	apply	VERB
cana-5024	21	8	ai	ai	NOUN
cana-5024	21	9	for	for	ADP
cana-5024	21	10	public	public	ADJ
cana-5024	21	11	health	health	NOUN
cana-5024	21	12	.	.	PUNCT
cana-5024	22	1	their	their	PRON
cana-5024	22	2	results	result	NOUN
cana-5024	22	3	emphasized	emphasize	VERB
cana-5024	22	4	the	the	DET
cana-5024	22	5	potential	potential	NOUN
cana-5024	22	6	for	for	ADP
cana-5024	22	7	scalable	scalable	ADJ
cana-5024	22	8	diagnostic	diagnostic	ADJ
cana-5024	22	9	tools	tool	NOUN
cana-5024	22	10	.	.	PUNCT
cana-5024	23	1	it	it	PRON
cana-5024	23	2	highlighted	highlight	VERB
cana-5024	23	3	cnns	cnn	NOUN
cana-5024	23	4	'	'	PART
cana-5024	23	5	strength	strength	NOUN
cana-5024	23	6	in	in	ADP
cana-5024	23	7	visual	visual	ADJ
cana-5024	23	8	recognition	recognition	NOUN
cana-5024	23	9	tasks	task	NOUN
cana-5024	23	10	.	.	PUNCT
cana-5024	24	1	haenssle	haenssle	NOUN
cana-5024	24	2	et	et	PROPN
cana-5024	24	3	al	al	PROPN
cana-5024	24	4	.	.	PROPN
cana-5024	24	5	compared	compare	VERB
cana-5024	24	6	deep	deep	ADJ
cana-5024	24	7	learning	learning	NOUN
cana-5024	24	8	models	model	NOUN
cana-5024	24	9	against	against	ADP
cana-5024	24	10	58	58	NUM
cana-5024	24	11	dermatologists	dermatologist	NOUN
cana-5024	24	12	in	in	ADP
cana-5024	24	13	melanoma	melanoma	NOUN
cana-5024	24	14	classification	classification	NOUN
cana-5024	24	15	.	.	PUNCT
cana-5024	25	1	they	they	PRON
cana-5024	25	2	found	find	VERB
cana-5024	25	3	cnns	cnns	PROPN
cana-5024	25	4	achieved	achieve	VERB
cana-5024	25	5	higher	high	ADJ
cana-5024	25	6	sensitivity	sensitivity	NOUN
cana-5024	25	7	and	and	CCONJ
cana-5024	25	8	specificity	specificity	NOUN
cana-5024	25	9	on	on	ADP
cana-5024	25	10	dermoscopic	dermoscopic	ADJ
cana-5024	25	11	images	image	NOUN
cana-5024	25	12	.	.	PUNCT
cana-5024	26	1	this	this	DET
cana-5024	26	2	study	study	NOUN
cana-5024	26	3	reinforced	reinforce	VERB
cana-5024	26	4	the	the	DET
cana-5024	26	5	reliability	reliability	NOUN
cana-5024	26	6	of	of	ADP
cana-5024	26	7	machine	machine	NOUN
cana-5024	26	8	learning	learning	NOUN
cana-5024	26	9	in	in	ADP
cana-5024	26	10	clinical	clinical	ADJ
cana-5024	26	11	settings	setting	NOUN
cana-5024	26	12	.	.	PUNCT
cana-5024	27	1	using	use	VERB
cana-5024	27	2	a	a	DET
cana-5024	27	3	standardized	standardized	ADJ
cana-5024	27	4	dataset	dataset	NOUN
cana-5024	27	5	helped	help	VERB
cana-5024	27	6	ensure	ensure	VERB
cana-5024	27	7	reproducibility	reproducibility	NOUN
cana-5024	27	8	and	and	CCONJ
cana-5024	27	9	fairness	fairness	NOUN
cana-5024	27	10	in	in	ADP
cana-5024	27	11	comparisons	comparison	NOUN
cana-5024	27	12	.	.	PUNCT
cana-5024	28	1	tschandl	tschandl	PROPN
cana-5024	28	2	et	et	PROPN
cana-5024	28	3	al	al	PROPN
cana-5024	28	4	.	.	PROPN
cana-5024	28	5	introduced	introduce	VERB
cana-5024	28	6	the	the	DET
cana-5024	28	7	ham10000	ham10000	PROPN
cana-5024	28	8	dataset	dataset	NOUN
cana-5024	28	9	,	,	PUNCT
cana-5024	28	10	which	which	PRON
cana-5024	28	11	contains	contain	VERB
cana-5024	28	12	over	over	ADP
cana-5024	28	13	10,000	10,000	NUM
cana-5024	28	14	dermatoscopic	dermatoscopic	NOUN
cana-5024	28	15	images	image	NOUN
cana-5024	28	16	.	.	PUNCT
cana-5024	29	1	the	the	DET
cana-5024	29	2	dataset	dataset	NOUN
cana-5024	29	3	supports	support	VERB
cana-5024	29	4	multi	multi	ADJ
cana-5024	29	5	-	-	ADJ
cana-5024	29	6	class	class	ADJ
cana-5024	29	7	classification	classification	NOUN
cana-5024	29	8	across	across	ADP
cana-5024	29	9	seven	seven	NUM
cana-5024	29	10	types	type	NOUN
cana-5024	29	11	of	of	ADP
cana-5024	29	12	skin	skin	NOUN
cana-5024	29	13	lesions	lesion	NOUN
cana-5024	29	14	.	.	PUNCT
cana-5024	30	1	it	it	PRON
cana-5024	30	2	is	be	AUX
cana-5024	30	3	now	now	ADV
cana-5024	30	4	a	a	DET
cana-5024	30	5	benchmark	benchmark	NOUN
cana-5024	30	6	for	for	ADP
cana-5024	30	7	evaluating	evaluate	VERB
cana-5024	30	8	skin	skin	NOUN
cana-5024	30	9	lesion	lesion	NOUN
cana-5024	30	10	classifiers	classifier	NOUN
cana-5024	30	11	.	.	PUNCT
cana-5024	31	1	brinker	brinker	PROPN
cana-5024	31	2	et	et	PROPN
cana-5024	31	3	al	al	PROPN
cana-5024	31	4	.	.	PROPN
cana-5024	31	5	evaluated	evaluate	VERB
cana-5024	31	6	cnn	cnn	PROPN
cana-5024	31	7	generalizability	generalizability	NOUN
cana-5024	31	8	across	across	ADP
cana-5024	31	9	multiple	multiple	ADJ
cana-5024	31	10	clinical	clinical	ADJ
cana-5024	31	11	image	image	NOUN
cana-5024	31	12	repositories	repository	NOUN
cana-5024	31	13	.	.	PUNCT
cana-5024	32	1	they	they	PRON
cana-5024	32	2	found	find	VERB
cana-5024	32	3	significant	significant	ADJ
cana-5024	32	4	drops	drop	NOUN
cana-5024	32	5	in	in	ADP
cana-5024	32	6	performance	performance	NOUN
cana-5024	32	7	when	when	SCONJ
cana-5024	32	8	models	model	NOUN
cana-5024	32	9	were	be	AUX
cana-5024	32	10	tested	test	VERB
cana-5024	32	11	on	on	ADP
cana-5024	32	12	unseen	unseen	ADJ
cana-5024	32	13	datasets	dataset	NOUN
cana-5024	32	14	.	.	PUNCT
cana-5024	33	1	this	this	PRON
cana-5024	33	2	highlighted	highlight	VERB
cana-5024	33	3	the	the	DET
cana-5024	33	4	limitations	limitation	NOUN
cana-5024	33	5	of	of	ADP
cana-5024	33	6	training	training	NOUN
cana-5024	33	7	models	model	NOUN
cana-5024	33	8	on	on	ADP
cana-5024	33	9	narrow	narrow	ADJ
cana-5024	33	10	data	datum	NOUN
cana-5024	33	11	distributions	distribution	NOUN
cana-5024	33	12	.	.	PUNCT
cana-5024	34	1	their	their	PRON
cana-5024	34	2	work	work	NOUN
cana-5024	34	3	emphasizes	emphasize	VERB
cana-5024	34	4	the	the	DET
cana-5024	34	5	importance	importance	NOUN
cana-5024	34	6	of	of	ADP
cana-5024	34	7	cross	cross	ADJ
cana-5024	34	8	-	-	ADJ
cana-5024	34	9	dataset	dataset	ADJ
cana-5024	34	10	validation	validation	NOUN
cana-5024	34	11	.	.	PUNCT
cana-5024	35	1	kawahara	kawahara	PROPN
cana-5024	35	2	et	et	PROPN
cana-5024	35	3	al	al	PROPN
cana-5024	35	4	.	.	PROPN
cana-5024	35	5	explored	explore	VERB
cana-5024	35	6	transfer	transfer	NOUN
cana-5024	35	7	learning	learning	NOUN
cana-5024	35	8	using	use	VERB
cana-5024	35	9	pre	pre	ADJ
cana-5024	35	10	-	-	ADJ
cana-5024	35	11	trained	train	VERB
cana-5024	35	12	networks	network	NOUN
cana-5024	35	13	such	such	ADJ
cana-5024	35	14	as	as	ADP
cana-5024	35	15	vgg	vgg	NOUN
cana-5024	35	16	and	and	CCONJ
cana-5024	35	17	resnet	resnet	NOUN
cana-5024	35	18	.	.	PUNCT
cana-5024	36	1	they	they	PRON
cana-5024	36	2	demonstrated	demonstrate	VERB
cana-5024	36	3	that	that	SCONJ
cana-5024	36	4	models	model	NOUN
cana-5024	36	5	trained	train	VERB
cana-5024	36	6	on	on	ADP
cana-5024	36	7	imagenet	imagenet	NOUN
cana-5024	36	8	could	could	AUX
cana-5024	36	9	be	be	AUX
cana-5024	36	10	fine	fine	ADV
cana-5024	36	11	-	-	PUNCT
cana-5024	36	12	tuned	tune	VERB
cana-5024	36	13	for	for	ADP
cana-5024	36	14	dermoscopy	dermoscopy	NOUN
cana-5024	36	15	.	.	PUNCT
cana-5024	37	1	this	this	PRON
cana-5024	37	2	reduces	reduce	VERB
cana-5024	37	3	the	the	DET
cana-5024	37	4	need	need	NOUN
cana-5024	37	5	for	for	ADP
cana-5024	37	6	large	large	ADJ
cana-5024	37	7	,	,	PUNCT
cana-5024	37	8	labeled	label	VERB
cana-5024	37	9	medical	medical	ADJ
cana-5024	37	10	datasets	dataset	NOUN
cana-5024	37	11	.	.	PUNCT
cana-5024	38	1	yu	yu	PROPN
cana-5024	38	2	et	et	PROPN
cana-5024	38	3	al	al	PROPN
cana-5024	38	4	.	.	PROPN
cana-5024	38	5	proposed	propose	VERB
cana-5024	38	6	a	a	DET
cana-5024	38	7	multi	multi	ADJ
cana-5024	38	8	-	-	ADJ
cana-5024	38	9	scale	scale	ADJ
cana-5024	38	10	cnn	cnn	NOUN
cana-5024	38	11	architecture	architecture	NOUN
cana-5024	38	12	to	to	PART
cana-5024	38	13	handle	handle	VERB
cana-5024	38	14	lesion	lesion	NOUN
cana-5024	38	15	size	size	NOUN
cana-5024	38	16	variations	variation	NOUN
cana-5024	38	17	.	.	PUNCT
cana-5024	39	1	their	their	PRON
cana-5024	39	2	network	network	NOUN
cana-5024	39	3	incorporated	incorporate	VERB
cana-5024	39	4	varying	vary	VERB
cana-5024	39	5	image	image	NOUN
cana-5024	39	6	resolutions	resolution	NOUN
cana-5024	39	7	for	for	ADP
cana-5024	39	8	better	well	ADJ
cana-5024	39	9	feature	feature	NOUN
cana-5024	39	10	extraction	extraction	NOUN
cana-5024	39	11	.	.	PUNCT
cana-5024	40	1	they	they	PRON
cana-5024	40	2	reported	report	VERB
cana-5024	40	3	improved	improved	ADJ
cana-5024	40	4	classification	classification	NOUN
cana-5024	40	5	of	of	ADP
cana-5024	40	6	melanoma	melanoma	NOUN
cana-5024	40	7	and	and	CCONJ
cana-5024	40	8	other	other	ADJ
cana-5024	40	9	lesions	lesion	NOUN
cana-5024	40	10	.	.	PUNCT
cana-5024	41	1	harangi	harangi	PROPN
cana-5024	41	2	presented	present	VERB
cana-5024	41	3	an	an	DET
cana-5024	41	4	ensemble	ensemble	NOUN
cana-5024	41	5	of	of	ADP
cana-5024	41	6	cnns	cnn	NOUN
cana-5024	41	7	to	to	PART
cana-5024	41	8	enhance	enhance	VERB
cana-5024	41	9	diagnostic	diagnostic	ADJ
cana-5024	41	10	accuracy	accuracy	NOUN
cana-5024	41	11	.	.	PUNCT
cana-5024	42	1	each	each	DET
cana-5024	42	2	cnn	cnn	PROPN
cana-5024	42	3	in	in	ADP
cana-5024	42	4	the	the	DET
cana-5024	42	5	ensemble	ensemble	ADJ
cana-5024	42	6	specialized	specialized	NOUN
cana-5024	42	7	in	in	ADP
cana-5024	42	8	different	different	ADJ
cana-5024	42	9	feature	feature	NOUN
cana-5024	42	10	domains	domain	NOUN
cana-5024	42	11	.	.	PUNCT
cana-5024	43	1	the	the	DET
cana-5024	43	2	combined	combine	VERB
cana-5024	43	3	output	output	NOUN
cana-5024	43	4	provided	provide	VERB
cana-5024	43	5	superior	superior	ADJ
cana-5024	43	6	performance	performance	NOUN
cana-5024	43	7	compared	compare	VERB
cana-5024	43	8	to	to	ADP
cana-5024	43	9	individual	individual	ADJ
cana-5024	43	10	models	model	NOUN
cana-5024	43	11	.	.	PUNCT
cana-5024	44	1	it	it	PRON
cana-5024	44	2	highlighted	highlight	VERB
cana-5024	44	3	the	the	DET
cana-5024	44	4	power	power	NOUN
cana-5024	44	5	of	of	ADP
cana-5024	44	6	collaborative	collaborative	ADJ
cana-5024	44	7	learning	learning	NOUN
cana-5024	44	8	in	in	ADP
cana-5024	44	9	ai	ai	PROPN
cana-5024	44	10	.	.	PROPN
cana-5024	45	1	gómez	gómez	PROPN
cana-5024	45	2	et	et	PROPN
cana-5024	45	3	al	al	PROPN
cana-5024	45	4	.	.	PROPN
cana-5024	45	5	applied	apply	VERB
cana-5024	45	6	cnns	cnn	NOUN
cana-5024	45	7	to	to	PART
cana-5024	45	8	extract	extract	VERB
cana-5024	45	9	color	color	NOUN
cana-5024	45	10	and	and	CCONJ
cana-5024	45	11	texture	texture	NOUN
cana-5024	45	12	features	feature	NOUN
cana-5024	45	13	from	from	ADP
cana-5024	45	14	dermoscopic	dermoscopic	ADJ
cana-5024	45	15	images	image	NOUN
cana-5024	45	16	.	.	PUNCT
cana-5024	46	1	they	they	PRON
cana-5024	46	2	used	use	VERB
cana-5024	46	3	these	these	DET
cana-5024	46	4	features	feature	NOUN
cana-5024	46	5	to	to	PART
cana-5024	46	6	distinguish	distinguish	VERB
cana-5024	46	7	benign	benign	NOUN
cana-5024	46	8	from	from	ADP
cana-5024	46	9	malignant	malignant	ADJ
cana-5024	46	10	lesions	lesion	NOUN
cana-5024	46	11	.	.	PUNCT
cana-5024	47	1	their	their	PRON
cana-5024	47	2	model	model	NOUN
cana-5024	47	3	improved	improve	VERB
cana-5024	47	4	classification	classification	NOUN
cana-5024	47	5	precision	precision	NOUN
cana-5024	47	6	by	by	ADP
cana-5024	47	7	integrating	integrate	VERB
cana-5024	47	8	multiple	multiple	ADJ
cana-5024	47	9	modalities	modality	NOUN
cana-5024	47	10	.	.	PUNCT
cana-5024	48	1	xie	xie	PROPN
cana-5024	48	2	et	et	PROPN
cana-5024	48	3	al	al	PROPN
cana-5024	48	4	.	.	PROPN
cana-5024	48	5	introduced	introduce	VERB
cana-5024	48	6	attention	attention	NOUN
cana-5024	48	7	mechanisms	mechanism	NOUN
cana-5024	48	8	in	in	ADP
cana-5024	48	9	cnns	cnn	NOUN
cana-5024	48	10	for	for	ADP
cana-5024	48	11	skin	skin	NOUN
cana-5024	48	12	cancer	cancer	NOUN
cana-5024	48	13	classification	classification	NOUN
cana-5024	48	14	.	.	PUNCT
cana-5024	49	1	the	the	DET
cana-5024	49	2	attention	attention	NOUN
cana-5024	49	3	layer	layer	NOUN
cana-5024	49	4	focused	focus	VERB
cana-5024	49	5	the	the	DET
cana-5024	49	6	model	model	NOUN
cana-5024	49	7	on	on	ADP
cana-5024	49	8	lesion	lesion	NOUN
cana-5024	49	9	-	-	PUNCT
cana-5024	49	10	relevant	relevant	ADJ
cana-5024	49	11	regions	region	NOUN
cana-5024	49	12	.	.	PUNCT
cana-5024	50	1	this	this	DET
cana-5024	50	2	reduced	reduce	VERB
cana-5024	50	3	noise	noise	NOUN
cana-5024	50	4	from	from	ADP
cana-5024	50	5	surrounding	surround	VERB
cana-5024	50	6	skin	skin	NOUN
cana-5024	50	7	and	and	CCONJ
cana-5024	50	8	improved	improve	VERB
cana-5024	50	9	interpretability	interpretability	NOUN
cana-5024	50	10	.	.	PUNCT
cana-5024	51	1	zhang	zhang	PROPN
cana-5024	51	2	et	et	PROPN
cana-5024	51	3	al	al	PROPN
cana-5024	51	4	.	.	PROPN
cana-5024	51	5	demonstrated	demonstrate	VERB
cana-5024	51	6	the	the	DET
cana-5024	51	7	use	use	NOUN
cana-5024	51	8	of	of	ADP
cana-5024	51	9	data	datum	NOUN
cana-5024	51	10	augmentation	augmentation	NOUN
cana-5024	51	11	to	to	PART
cana-5024	51	12	address	address	VERB
cana-5024	51	13	dataset	dataset	ADJ
cana-5024	51	14	imbalance	imbalance	NOUN
cana-5024	51	15	.	.	PUNCT
cana-5024	52	1	they	they	PRON
cana-5024	52	2	introduced	introduce	VERB
cana-5024	52	3	rotation	rotation	NOUN
cana-5024	52	4	,	,	PUNCT
cana-5024	52	5	flipping	flipping	NOUN
cana-5024	52	6	,	,	PUNCT
cana-5024	52	7	and	and	CCONJ
cana-5024	52	8	color	color	NOUN
cana-5024	52	9	jittering	jittere	VERB
cana-5024	52	10	to	to	PART
cana-5024	52	11	expand	expand	VERB
cana-5024	52	12	training	training	NOUN
cana-5024	52	13	data	datum	NOUN
cana-5024	52	14	.	.	PUNCT
cana-5024	53	1	esteva	esteva	PROPN
cana-5024	53	2	et	et	PROPN
cana-5024	53	3	al	al	PROPN
cana-5024	53	4	.	.	PROPN
cana-5024	53	5	demonstrated	demonstrate	VERB
cana-5024	53	6	that	that	SCONJ
cana-5024	53	7	convolutional	convolutional	ADJ
cana-5024	53	8	neural	neural	ADJ
cana-5024	53	9	networks	network	NOUN
cana-5024	53	10	(	(	PUNCT
cana-5024	53	11	cnns	cnns	PROPN
cana-5024	53	12	)	)	PUNCT
cana-5024	53	13	can	can	AUX
cana-5024	53	14	match	match	VERB
cana-5024	53	15	dermatologist	dermatologist	NOUN
cana-5024	53	16	-	-	PUNCT
cana-5024	53	17	level	level	NOUN
cana-5024	53	18	performance	performance	NOUN
cana-5024	53	19	in	in	ADP
cana-5024	53	20	classifying	classify	VERB
cana-5024	53	21	skin	skin	NOUN
cana-5024	53	22	lesions	lesion	NOUN
cana-5024	53	23	.	.	PUNCT
cana-5024	54	1	their	their	PRON
cana-5024	54	2	work	work	NOUN
cana-5024	54	3	laid	lay	VERB
cana-5024	54	4	the	the	DET
cana-5024	54	5	foundation	foundation	NOUN
cana-5024	54	6	for	for	ADP
cana-5024	54	7	automated	automate	VERB
cana-5024	54	8	diagnostic	diagnostic	ADJ
cana-5024	54	9	systems	system	NOUN
cana-5024	54	10	in	in	ADP
cana-5024	54	11	dermatology	dermatology	NOUN
cana-5024	54	12	.	.	PUNCT
cana-5024	55	1	by	by	ADP
cana-5024	55	2	training	train	VERB
cana-5024	55	3	on	on	ADP
cana-5024	55	4	over	over	ADP
cana-5024	55	5	129,000	129,000	NUM
cana-5024	55	6	clinical	clinical	ADJ
cana-5024	55	7	images	image	NOUN
cana-5024	55	8	,	,	PUNCT
cana-5024	55	9	the	the	DET
cana-5024	55	10	model	model	NOUN
cana-5024	55	11	was	be	AUX
cana-5024	55	12	able	able	ADJ
cana-5024	55	13	to	to	PART
cana-5024	55	14	differentiate	differentiate	VERB
cana-5024	55	15	among	among	ADP
cana-5024	55	16	over	over	ADP
cana-5024	55	17	2,000	2,000	NUM
cana-5024	55	18	skin	skin	NOUN
cana-5024	55	19	diseases	disease	NOUN
cana-5024	55	20	.	.	PUNCT
cana-5024	56	1	haenssle	haenssle	NOUN
cana-5024	56	2	et	et	PROPN
cana-5024	56	3	al	al	PROPN
cana-5024	56	4	.	.	PROPN
cana-5024	56	5	compared	compare	VERB
cana-5024	56	6	deep	deep	ADJ
cana-5024	56	7	learning	learning	NOUN
cana-5024	56	8	models	model	NOUN
cana-5024	56	9	against	against	ADP
cana-5024	56	10	58	58	NUM
cana-5024	56	11	dermatologists	dermatologist	NOUN
cana-5024	56	12	in	in	ADP
cana-5024	56	13	melanoma	melanoma	NOUN
cana-5024	56	14	classification	classification	NOUN
cana-5024	56	15	.	.	PUNCT
cana-5024	57	1	they	they	PRON
cana-5024	57	2	found	find	VERB
cana-5024	57	3	cnns	cnns	PROPN
cana-5024	57	4	achieved	achieve	VERB
cana-5024	57	5	higher	high	ADJ
cana-5024	57	6	sensitivity	sensitivity	NOUN
cana-5024	57	7	and	and	CCONJ
cana-5024	57	8	specificity	specificity	NOUN
cana-5024	57	9	on	on	ADP
cana-5024	57	10	dermoscopic	dermoscopic	ADJ
cana-5024	57	11	images	image	NOUN
cana-5024	57	12	.	.	PUNCT
cana-5024	58	1	tschandl	tschandl	PROPN
cana-5024	58	2	et	et	PROPN
cana-5024	58	3	al	al	PROPN
cana-5024	58	4	.	.	PROPN
cana-5024	58	5	introduced	introduce	VERB
cana-5024	58	6	the	the	DET
cana-5024	58	7	ham10000	ham10000	PROPN
cana-5024	58	8	dataset	dataset	NOUN
cana-5024	58	9	,	,	PUNCT
cana-5024	58	10	which	which	PRON
cana-5024	58	11	contains	contain	VERB
cana-5024	58	12	over	over	ADP
cana-5024	58	13	10,000	10,000	NUM
cana-5024	58	14	dermatoscopic	dermatoscopic	NOUN
cana-5024	58	15	images	image	NOUN
cana-5024	58	16	.	.	PUNCT
cana-5024	59	1	brinker	brinker	NOUN
cana-5024	59	2	et	et	PROPN
cana-5024	59	3	al	al	PROPN
cana-5024	59	4	.	.	PROPN
cana-5024	59	5	evaluated	evaluate	VERB
cana-5024	59	6	cnn	cnn	PROPN
cana-5024	59	7	generalizability	generalizability	NOUN
cana-5024	59	8	across	across	ADP
cana-5024	59	9	multiple	multiple	ADJ
cana-5024	59	10	clinical	clinical	ADJ
cana-5024	59	11	image	image	NOUN
cana-5024	59	12	repositories	repository	NOUN
cana-5024	59	13	.	.	PUNCT
cana-5024	60	1	they	they	PRON
cana-5024	60	2	found	find	VERB
cana-5024	60	3	significant	significant	ADJ
cana-5024	60	4	drops	drop	NOUN
cana-5024	60	5	in	in	ADP
cana-5024	60	6	performance	performance	NOUN
cana-5024	60	7	when	when	SCONJ
cana-5024	60	8	models	model	NOUN
cana-5024	60	9	were	be	AUX
cana-5024	60	10	tested	test	VERB
cana-5024	60	11	on	on	ADP
cana-5024	60	12	communications	communication	NOUN
cana-5024	60	13	on	on	ADP
cana-5024	60	14	applied	apply	VERB
cana-5024	60	15	nonlinear	nonlinear	ADJ
cana-5024	60	16	analysis	analysis	NOUN
cana-5024	60	17	issn	issn	NOUN
cana-5024	60	18	:	:	PUNCT
cana-5024	60	19	1074	1074	NUM
cana-5024	60	20	-	-	PUNCT
cana-5024	60	21	133x	133x	NUM
cana-5024	60	22	vol	vol	VERB
cana-5024	60	23	32	32	NUM
cana-5024	60	24	no.1s	no.1s	PROPN
cana-5024	60	25	(	(	PUNCT
cana-5024	60	26	2025	2025	NUM
cana-5024	60	27	)	)	PUNCT
cana-5024	60	28	645	645	NUM
cana-5024	60	29	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	60	30	unseen	unseen	ADJ
cana-5024	60	31	datasets	dataset	NOUN
cana-5024	60	32	.	.	PUNCT
cana-5024	61	1	kawahara	kawahara	PROPN
cana-5024	61	2	et	et	PROPN
cana-5024	61	3	al	al	PROPN
cana-5024	61	4	.	.	PROPN
cana-5024	61	5	explored	explore	VERB
cana-5024	61	6	transfer	transfer	NOUN
cana-5024	61	7	learning	learning	NOUN
cana-5024	61	8	using	use	VERB
cana-5024	61	9	pre	pre	ADJ
cana-5024	61	10	-	-	ADJ
cana-5024	61	11	trained	train	VERB
cana-5024	61	12	networks	network	NOUN
cana-5024	61	13	such	such	ADJ
cana-5024	61	14	as	as	ADP
cana-5024	61	15	vgg	vgg	NOUN
cana-5024	61	16	and	and	CCONJ
cana-5024	61	17	resnet	resnet	NOUN
cana-5024	61	18	.	.	PUNCT
cana-5024	62	1	they	they	PRON
cana-5024	62	2	demonstrated	demonstrate	VERB
cana-5024	62	3	that	that	SCONJ
cana-5024	62	4	models	model	NOUN
cana-5024	62	5	trained	train	VERB
cana-5024	62	6	on	on	ADP
cana-5024	62	7	imagenet	imagenet	NOUN
cana-5024	62	8	could	could	AUX
cana-5024	62	9	be	be	AUX
cana-5024	62	10	fine	fine	ADV
cana-5024	62	11	-	-	PUNCT
cana-5024	62	12	tuned	tune	VERB
cana-5024	62	13	for	for	ADP
cana-5024	62	14	dermoscopy	dermoscopy	NOUN
cana-5024	62	15	.	.	PUNCT
cana-5024	63	1	this	this	PRON
cana-5024	63	2	reduces	reduce	VERB
cana-5024	63	3	the	the	DET
cana-5024	63	4	need	need	NOUN
cana-5024	63	5	for	for	ADP
cana-5024	63	6	large	large	ADJ
cana-5024	63	7	,	,	PUNCT
cana-5024	63	8	labeled	label	VERB
cana-5024	63	9	medical	medical	ADJ
cana-5024	63	10	datasets	dataset	NOUN
cana-5024	63	11	.	.	PUNCT
cana-5024	64	1	their	their	PRON
cana-5024	64	2	study	study	NOUN
cana-5024	64	3	showed	show	VERB
cana-5024	64	4	transfer	transfer	NOUN
cana-5024	64	5	learning	learning	NOUN
cana-5024	64	6	significantly	significantly	ADV
cana-5024	64	7	enhances	enhance	VERB
cana-5024	64	8	performance	performance	NOUN
cana-5024	64	9	.	.	PUNCT
cana-5024	65	1	yu	yu	PROPN
cana-5024	65	2	et	et	PROPN
cana-5024	65	3	al	al	PROPN
cana-5024	65	4	.	.	PROPN
cana-5024	65	5	proposed	propose	VERB
cana-5024	65	6	a	a	DET
cana-5024	65	7	multi	multi	ADJ
cana-5024	65	8	-	-	ADJ
cana-5024	65	9	scale	scale	ADJ
cana-5024	65	10	cnn	cnn	NOUN
cana-5024	65	11	architecture	architecture	NOUN
cana-5024	65	12	to	to	PART
cana-5024	65	13	handle	handle	VERB
cana-5024	65	14	lesion	lesion	NOUN
cana-5024	65	15	size	size	NOUN
cana-5024	65	16	variations	variation	NOUN
cana-5024	65	17	.	.	PUNCT
cana-5024	66	1	their	their	PRON
cana-5024	66	2	network	network	NOUN
cana-5024	66	3	incorporated	incorporate	VERB
cana-5024	66	4	varying	vary	VERB
cana-5024	66	5	image	image	NOUN
cana-5024	66	6	resolutions	resolution	NOUN
cana-5024	66	7	for	for	ADP
cana-5024	66	8	better	well	ADJ
cana-5024	66	9	feature	feature	NOUN
cana-5024	66	10	extraction	extraction	NOUN
cana-5024	66	11	.	.	PUNCT
cana-5024	67	1	harangi	harangi	PROPN
cana-5024	67	2	presented	present	VERB
cana-5024	67	3	an	an	DET
cana-5024	67	4	ensemble	ensemble	NOUN
cana-5024	67	5	of	of	ADP
cana-5024	67	6	cnns	cnn	NOUN
cana-5024	67	7	to	to	PART
cana-5024	67	8	enhance	enhance	VERB
cana-5024	67	9	diagnostic	diagnostic	ADJ
cana-5024	67	10	accuracy	accuracy	NOUN
cana-5024	67	11	.	.	PUNCT
cana-5024	68	1	each	each	DET
cana-5024	68	2	cnn	cnn	PROPN
cana-5024	68	3	in	in	ADP
cana-5024	68	4	the	the	DET
cana-5024	68	5	ensemble	ensemble	ADJ
cana-5024	68	6	specialized	specialized	NOUN
cana-5024	68	7	in	in	ADP
cana-5024	68	8	different	different	ADJ
cana-5024	68	9	feature	feature	NOUN
cana-5024	68	10	domains	domain	NOUN
cana-5024	68	11	.	.	PUNCT
cana-5024	69	1	the	the	DET
cana-5024	69	2	combined	combine	VERB
cana-5024	69	3	output	output	NOUN
cana-5024	69	4	provided	provide	VERB
cana-5024	69	5	superior	superior	ADJ
cana-5024	69	6	performance	performance	NOUN
cana-5024	69	7	compared	compare	VERB
cana-5024	69	8	to	to	ADP
cana-5024	69	9	individual	individual	ADJ
cana-5024	69	10	models	model	NOUN
cana-5024	69	11	.	.	PUNCT
cana-5024	70	1	this	this	DET
cana-5024	70	2	technique	technique	NOUN
cana-5024	70	3	minimized	minimized	ADJ
cana-5024	70	4	overfitting	overfitting	NOUN
cana-5024	70	5	and	and	CCONJ
cana-5024	70	6	improved	improved	ADJ
cana-5024	70	7	model	model	NOUN
cana-5024	70	8	reliability	reliability	NOUN
cana-5024	70	9	.	.	PUNCT
cana-5024	71	1	gómez	gómez	NOUN
cana-5024	71	2	et	et	PROPN
cana-5024	71	3	al	al	PROPN
cana-5024	71	4	.	.	PROPN
cana-5024	71	5	applied	apply	VERB
cana-5024	71	6	cnns	cnn	NOUN
cana-5024	71	7	to	to	PART
cana-5024	71	8	extract	extract	VERB
cana-5024	71	9	color	color	NOUN
cana-5024	71	10	and	and	CCONJ
cana-5024	71	11	texture	texture	NOUN
cana-5024	71	12	features	feature	NOUN
cana-5024	71	13	from	from	ADP
cana-5024	71	14	dermoscopic	dermoscopic	ADJ
cana-5024	71	15	images	image	NOUN
cana-5024	71	16	.	.	PUNCT
cana-5024	72	1	they	they	PRON
cana-5024	72	2	used	use	VERB
cana-5024	72	3	these	these	DET
cana-5024	72	4	features	feature	NOUN
cana-5024	72	5	to	to	PART
cana-5024	72	6	distinguish	distinguish	VERB
cana-5024	72	7	benign	benign	NOUN
cana-5024	72	8	from	from	ADP
cana-5024	72	9	malignant	malignant	ADJ
cana-5024	72	10	lesions	lesion	NOUN
cana-5024	72	11	.	.	PUNCT
cana-5024	73	1	their	their	PRON
cana-5024	73	2	model	model	NOUN
cana-5024	73	3	improved	improve	VERB
cana-5024	73	4	classification	classification	NOUN
cana-5024	73	5	precision	precision	NOUN
cana-5024	73	6	by	by	ADP
cana-5024	73	7	integrating	integrate	VERB
cana-5024	73	8	multiple	multiple	ADJ
cana-5024	73	9	modalities	modality	NOUN
cana-5024	73	10	.	.	PUNCT
cana-5024	74	1	xie	xie	PROPN
cana-5024	74	2	et	et	PROPN
cana-5024	74	3	al	al	PROPN
cana-5024	74	4	.	.	PROPN
cana-5024	74	5	introduced	introduce	VERB
cana-5024	74	6	attention	attention	NOUN
cana-5024	74	7	mechanisms	mechanism	NOUN
cana-5024	74	8	in	in	ADP
cana-5024	74	9	cnns	cnn	NOUN
cana-5024	74	10	for	for	ADP
cana-5024	74	11	skin	skin	NOUN
cana-5024	74	12	cancer	cancer	NOUN
cana-5024	74	13	classification	classification	NOUN
cana-5024	74	14	.	.	PUNCT
cana-5024	75	1	the	the	DET
cana-5024	75	2	attention	attention	NOUN
cana-5024	75	3	layer	layer	NOUN
cana-5024	75	4	focused	focus	VERB
cana-5024	75	5	the	the	DET
cana-5024	75	6	model	model	NOUN
cana-5024	75	7	on	on	ADP
cana-5024	75	8	lesion	lesion	NOUN
cana-5024	75	9	-	-	PUNCT
cana-5024	75	10	relevant	relevant	ADJ
cana-5024	75	11	regions	region	NOUN
cana-5024	75	12	.	.	PUNCT
cana-5024	76	1	this	this	DET
cana-5024	76	2	reduced	reduce	VERB
cana-5024	76	3	noise	noise	NOUN
cana-5024	76	4	from	from	ADP
cana-5024	76	5	surrounding	surround	VERB
cana-5024	76	6	skin	skin	NOUN
cana-5024	76	7	and	and	CCONJ
cana-5024	76	8	improved	improve	VERB
cana-5024	76	9	interpretability	interpretability	NOUN
cana-5024	76	10	.	.	PUNCT
cana-5024	77	1	their	their	PRON
cana-5024	77	2	model	model	NOUN
cana-5024	77	3	achieved	achieve	VERB
cana-5024	77	4	higher	high	ADJ
cana-5024	77	5	accuracy	accuracy	NOUN
cana-5024	77	6	than	than	ADP
cana-5024	77	7	baseline	baseline	NOUN
cana-5024	77	8	cnns	cnn	NOUN
cana-5024	77	9	.	.	PUNCT
cana-5024	78	1	zhang	zhang	PROPN
cana-5024	78	2	et	et	PROPN
cana-5024	78	3	al	al	PROPN
cana-5024	78	4	.	.	PROPN
cana-5024	78	5	demonstrated	demonstrate	VERB
cana-5024	78	6	the	the	DET
cana-5024	78	7	use	use	NOUN
cana-5024	78	8	of	of	ADP
cana-5024	78	9	data	datum	NOUN
cana-5024	78	10	augmentation	augmentation	NOUN
cana-5024	78	11	to	to	PART
cana-5024	78	12	address	address	VERB
cana-5024	78	13	dataset	dataset	ADJ
cana-5024	78	14	imbalance	imbalance	NOUN
cana-5024	78	15	.	.	PUNCT
cana-5024	79	1	they	they	PRON
cana-5024	79	2	introduced	introduce	VERB
cana-5024	79	3	rotation	rotation	NOUN
cana-5024	79	4	,	,	PUNCT
cana-5024	79	5	flipping	flipping	NOUN
cana-5024	79	6	,	,	PUNCT
cana-5024	79	7	and	and	CCONJ
cana-5024	79	8	color	color	NOUN
cana-5024	79	9	jittering	jittere	VERB
cana-5024	79	10	to	to	PART
cana-5024	79	11	expand	expand	VERB
cana-5024	79	12	training	training	NOUN
cana-5024	79	13	data	datum	NOUN
cana-5024	79	14	.	.	PUNCT
cana-5024	80	1	these	these	DET
cana-5024	80	2	augmentations	augmentation	NOUN
cana-5024	80	3	improved	improve	VERB
cana-5024	80	4	generalization	generalization	NOUN
cana-5024	80	5	and	and	CCONJ
cana-5024	80	6	reduced	reduced	ADJ
cana-5024	80	7	overfitting	overfitting	NOUN
cana-5024	80	8	.	.	PUNCT
cana-5024	81	1	jinnai	jinnai	PROPN
cana-5024	81	2	et	et	PROPN
cana-5024	81	3	al	al	PROPN
cana-5024	81	4	.	.	PROPN
cana-5024	81	5	proposed	propose	VERB
cana-5024	81	6	a	a	DET
cana-5024	81	7	two	two	NUM
cana-5024	81	8	-	-	PUNCT
cana-5024	81	9	stage	stage	NOUN
cana-5024	81	10	cnn	cnn	PROPN
cana-5024	81	11	model	model	NOUN
cana-5024	81	12	to	to	PART
cana-5024	81	13	classify	classify	VERB
cana-5024	81	14	skin	skin	NOUN
cana-5024	81	15	lesions	lesion	NOUN
cana-5024	81	16	.	.	PUNCT
cana-5024	82	1	the	the	DET
cana-5024	82	2	first	first	ADJ
cana-5024	82	3	stage	stage	NOUN
cana-5024	82	4	segmented	segment	VERB
cana-5024	82	5	lesions	lesion	NOUN
cana-5024	82	6	from	from	ADP
cana-5024	82	7	the	the	DET
cana-5024	82	8	surrounding	surround	VERB
cana-5024	82	9	skin	skin	NOUN
cana-5024	82	10	.	.	PUNCT
cana-5024	83	1	the	the	DET
cana-5024	83	2	second	second	ADJ
cana-5024	83	3	stage	stage	NOUN
cana-5024	83	4	classified	classify	VERB
cana-5024	83	5	the	the	DET
cana-5024	83	6	extracted	extract	VERB
cana-5024	83	7	lesion	lesion	NOUN
cana-5024	83	8	image	image	NOUN
cana-5024	83	9	.	.	PUNCT
cana-5024	84	1	liu	liu	PROPN
cana-5024	84	2	et	et	PROPN
cana-5024	84	3	al	al	PROPN
cana-5024	84	4	.	.	PROPN
cana-5024	84	5	investigated	investigate	VERB
cana-5024	84	6	the	the	DET
cana-5024	84	7	use	use	NOUN
cana-5024	84	8	of	of	ADP
cana-5024	84	9	generative	generative	ADJ
cana-5024	84	10	adversarial	adversarial	ADJ
cana-5024	84	11	networks	network	NOUN
cana-5024	84	12	(	(	PUNCT
cana-5024	84	13	gans	gan	NOUN
cana-5024	84	14	)	)	PUNCT
cana-5024	84	15	for	for	ADP
cana-5024	84	16	data	datum	NOUN
cana-5024	84	17	augmentation	augmentation	NOUN
cana-5024	84	18	.	.	PUNCT
cana-5024	85	1	they	they	PRON
cana-5024	85	2	created	create	VERB
cana-5024	85	3	synthetic	synthetic	ADJ
cana-5024	85	4	dermoscopic	dermoscopic	NOUN
cana-5024	85	5	images	image	NOUN
cana-5024	85	6	to	to	PART
cana-5024	85	7	balance	balance	VERB
cana-5024	85	8	underrepresented	underrepresented	ADJ
cana-5024	85	9	classes	class	NOUN
cana-5024	85	10	.	.	PUNCT
cana-5024	86	1	codella	codella	PROPN
cana-5024	86	2	et	et	PROPN
cana-5024	86	3	al	al	PROPN
cana-5024	86	4	.	.	PROPN
cana-5024	86	5	organized	organize	VERB
cana-5024	86	6	the	the	DET
cana-5024	86	7	isic	isic	PROPN
cana-5024	86	8	challenges	challenge	NOUN
cana-5024	86	9	to	to	PART
cana-5024	86	10	promote	promote	VERB
cana-5024	86	11	benchmarking	benchmarke	VERB
cana-5024	86	12	in	in	ADP
cana-5024	86	13	dermoscopic	dermoscopic	ADJ
cana-5024	86	14	image	image	NOUN
cana-5024	86	15	analysis	analysis	NOUN
cana-5024	86	16	.	.	PUNCT
cana-5024	87	1	these	these	DET
cana-5024	87	2	competitions	competition	NOUN
cana-5024	87	3	established	establish	VERB
cana-5024	87	4	standard	standard	ADJ
cana-5024	87	5	evaluation	evaluation	NOUN
cana-5024	87	6	protocols	protocol	NOUN
cana-5024	87	7	.	.	PUNCT
cana-5024	88	1	nasr	nasr	PROPN
cana-5024	88	2	-	-	PUNCT
cana-5024	88	3	esfahani	esfahani	PROPN
cana-5024	88	4	et	et	PROPN
cana-5024	88	5	al	al	PROPN
cana-5024	88	6	.	.	PROPN
cana-5024	88	7	developed	develop	VERB
cana-5024	88	8	a	a	DET
cana-5024	88	9	fully	fully	ADV
cana-5024	88	10	convolutional	convolutional	ADJ
cana-5024	88	11	network	network	NOUN
cana-5024	88	12	(	(	PUNCT
cana-5024	88	13	fcn	fcn	PROPN
cana-5024	88	14	)	)	PUNCT
cana-5024	88	15	for	for	ADP
cana-5024	88	16	lesion	lesion	NOUN
cana-5024	88	17	segmentation	segmentation	NOUN
cana-5024	88	18	.	.	PUNCT
cana-5024	89	1	their	their	PRON
cana-5024	89	2	model	model	NOUN
cana-5024	89	3	combined	combine	VERB
cana-5024	89	4	spatial	spatial	ADJ
cana-5024	89	5	and	and	CCONJ
cana-5024	89	6	texture	texture	ADJ
cana-5024	89	7	features	feature	NOUN
cana-5024	89	8	.	.	PUNCT
cana-5024	90	1	the	the	DET
cana-5024	90	2	segmentation	segmentation	NOUN
cana-5024	90	3	helped	help	VERB
cana-5024	90	4	downstream	downstream	VERB
cana-5024	90	5	classification	classification	NOUN
cana-5024	90	6	tasks	task	NOUN
cana-5024	90	7	.	.	PUNCT
cana-5024	91	1	al	al	PROPN
cana-5024	91	2	-	-	PUNCT
cana-5024	91	3	masni	masni	PROPN
cana-5024	91	4	et	et	PROPN
cana-5024	91	5	al	al	PROPN
cana-5024	91	6	.	.	PROPN
cana-5024	91	7	proposed	propose	VERB
cana-5024	91	8	a	a	DET
cana-5024	91	9	deep	deep	ADV
cana-5024	91	10	fully	fully	ADV
cana-5024	91	11	connected	connect	VERB
cana-5024	91	12	cnn	cnn	PROPN
cana-5024	91	13	for	for	ADP
cana-5024	91	14	end	end	NOUN
cana-5024	91	15	-	-	PUNCT
cana-5024	91	16	to	to	ADP
cana-5024	91	17	-	-	PUNCT
cana-5024	91	18	end	end	NOUN
cana-5024	91	19	skin	skin	NOUN
cana-5024	91	20	cancer	cancer	NOUN
cana-5024	91	21	detection	detection	NOUN
cana-5024	91	22	.	.	PUNCT
cana-5024	92	1	their	their	PRON
cana-5024	92	2	model	model	NOUN
cana-5024	92	3	integrated	integrate	VERB
cana-5024	92	4	lesion	lesion	NOUN
cana-5024	92	5	localization	localization	NOUN
cana-5024	92	6	and	and	CCONJ
cana-5024	92	7	classification	classification	NOUN
cana-5024	92	8	.	.	PUNCT
cana-5024	93	1	rehman	rehman	NOUN
cana-5024	93	2	et	et	PROPN
cana-5024	93	3	al	al	PROPN
cana-5024	93	4	.	.	PROPN
cana-5024	93	5	applied	apply	VERB
cana-5024	93	6	deep	deep	ADJ
cana-5024	93	7	learning	learning	NOUN
cana-5024	93	8	with	with	ADP
cana-5024	93	9	wavelet	wavelet	NOUN
cana-5024	93	10	transform	transform	NOUN
cana-5024	93	11	for	for	ADP
cana-5024	93	12	feature	feature	NOUN
cana-5024	93	13	extraction	extraction	NOUN
cana-5024	93	14	.	.	PUNCT
cana-5024	94	1	the	the	DET
cana-5024	94	2	hybrid	hybrid	NOUN
cana-5024	94	3	method	method	NOUN
cana-5024	94	4	combined	combine	VERB
cana-5024	94	5	spatial	spatial	ADJ
cana-5024	94	6	and	and	CCONJ
cana-5024	94	7	frequency	frequency	NOUN
cana-5024	94	8	features	feature	NOUN
cana-5024	94	9	.	.	PUNCT
cana-5024	95	1	their	their	PRON
cana-5024	95	2	model	model	NOUN
cana-5024	95	3	achieved	achieve	VERB
cana-5024	95	4	better	well	ADJ
cana-5024	95	5	accuracy	accuracy	NOUN
cana-5024	95	6	than	than	ADP
cana-5024	95	7	standard	standard	ADJ
cana-5024	95	8	cnns	cnn	NOUN
cana-5024	95	9	.	.	PUNCT
cana-5024	96	1	mahbod	mahbod	INTJ
cana-5024	96	2	et	et	PROPN
cana-5024	96	3	al	al	PROPN
cana-5024	96	4	.	.	PROPN
cana-5024	96	5	fused	fuse	VERB
cana-5024	96	6	features	feature	NOUN
cana-5024	96	7	from	from	ADP
cana-5024	96	8	multiple	multiple	ADJ
cana-5024	96	9	cnns	cnn	NOUN
cana-5024	96	10	to	to	PART
cana-5024	96	11	enhance	enhance	VERB
cana-5024	96	12	robustness	robustness	NOUN
cana-5024	96	13	.	.	PUNCT
cana-5024	97	1	they	they	PRON
cana-5024	97	2	concatenated	concatenate	VERB
cana-5024	97	3	deep	deep	ADJ
cana-5024	97	4	features	feature	NOUN
cana-5024	97	5	from	from	ADP
cana-5024	97	6	vgg	vgg	PROPN
cana-5024	97	7	,	,	PUNCT
cana-5024	97	8	resnet	resnet	NOUN
cana-5024	97	9	,	,	PUNCT
cana-5024	97	10	and	and	CCONJ
cana-5024	97	11	inception	inception	NOUN
cana-5024	97	12	.	.	PUNCT
cana-5024	98	1	the	the	DET
cana-5024	98	2	fusion	fusion	NOUN
cana-5024	98	3	approach	approach	NOUN
cana-5024	98	4	outperformed	outperform	VERB
cana-5024	98	5	single	single	ADJ
cana-5024	98	6	-	-	PUNCT
cana-5024	98	7	model	model	NOUN
cana-5024	98	8	baselines	baseline	NOUN
cana-5024	98	9	.	.	PUNCT
cana-5024	99	1	it	it	PRON
cana-5024	99	2	increased	increase	VERB
cana-5024	99	3	classification	classification	NOUN
cana-5024	99	4	precision	precision	NOUN
cana-5024	99	5	and	and	CCONJ
cana-5024	99	6	recall	recall	NOUN
cana-5024	99	7	.	.	PUNCT
cana-5024	100	1	their	their	PRON
cana-5024	100	2	method	method	NOUN
cana-5024	100	3	improved	improve	VERB
cana-5024	100	4	feature	feature	NOUN
cana-5024	100	5	richness	richness	NOUN
cana-5024	100	6	.	.	PUNCT
cana-5024	101	1	goyal	goyal	PROPN
cana-5024	101	2	et	et	PROPN
cana-5024	101	3	al	al	PROPN
cana-5024	101	4	.	.	PROPN
cana-5024	101	5	emphasized	emphasize	VERB
cana-5024	101	6	explainable	explainable	ADJ
cana-5024	101	7	ai	ai	NOUN
cana-5024	101	8	(	(	PUNCT
cana-5024	101	9	xai	xai	PROPN
cana-5024	101	10	)	)	PUNCT
cana-5024	101	11	in	in	ADP
cana-5024	101	12	medical	medical	ADJ
cana-5024	101	13	diagnostics	diagnostic	NOUN
cana-5024	101	14	.	.	PUNCT
cana-5024	102	1	they	they	PRON
cana-5024	102	2	used	use	VERB
cana-5024	102	3	grad	grad	NOUN
cana-5024	102	4	-	-	PUNCT
cana-5024	102	5	cam	cam	NOUN
cana-5024	102	6	to	to	PART
cana-5024	102	7	visualize	visualize	VERB
cana-5024	102	8	cnn	cnn	PROPN
cana-5024	102	9	decisions	decision	NOUN
cana-5024	102	10	.	.	PUNCT
cana-5024	103	1	the	the	DET
cana-5024	103	2	heatmaps	heatmap	NOUN
cana-5024	103	3	revealed	reveal	VERB
cana-5024	103	4	important	important	ADJ
cana-5024	103	5	lesion	lesion	NOUN
cana-5024	103	6	areas	area	NOUN
cana-5024	103	7	.	.	PUNCT
cana-5024	104	1	dermatologists	dermatologist	NOUN
cana-5024	104	2	used	use	VERB
cana-5024	104	3	these	these	DET
cana-5024	104	4	maps	map	NOUN
cana-5024	104	5	for	for	ADP
cana-5024	104	6	validation	validation	NOUN
cana-5024	104	7	.	.	PUNCT
cana-5024	105	1	yu	yu	PROPN
cana-5024	105	2	et	et	PROPN
cana-5024	105	3	al	al	PROPN
cana-5024	105	4	.	.	PROPN
cana-5024	105	5	introduced	introduce	VERB
cana-5024	105	6	a	a	DET
cana-5024	105	7	hierarchical	hierarchical	ADJ
cana-5024	105	8	classification	classification	NOUN
cana-5024	105	9	model	model	NOUN
cana-5024	105	10	for	for	ADP
cana-5024	105	11	multi	multi	ADJ
cana-5024	105	12	-	-	ADJ
cana-5024	105	13	class	class	ADJ
cana-5024	105	14	lesion	lesion	NOUN
cana-5024	105	15	detection	detection	NOUN
cana-5024	105	16	.	.	PUNCT
cana-5024	106	1	it	it	PRON
cana-5024	106	2	grouped	group	VERB
cana-5024	106	3	lesion	lesion	NOUN
cana-5024	106	4	types	type	NOUN
cana-5024	106	5	by	by	ADP
cana-5024	106	6	similarity	similarity	NOUN
cana-5024	106	7	.	.	PUNCT
cana-5024	107	1	each	each	DET
cana-5024	107	2	subgroup	subgroup	NOUN
cana-5024	107	3	was	be	AUX
cana-5024	107	4	handled	handle	VERB
cana-5024	107	5	by	by	ADP
cana-5024	107	6	a	a	DET
cana-5024	107	7	dedicated	dedicated	ADJ
cana-5024	107	8	classifier	classifier	NOUN
cana-5024	107	9	.	.	PUNCT
cana-5024	108	1	the	the	DET
cana-5024	108	2	system	system	NOUN
cana-5024	108	3	achieved	achieve	VERB
cana-5024	108	4	higher	high	ADJ
cana-5024	108	5	overall	overall	ADJ
cana-5024	108	6	accuracy	accuracy	NOUN
cana-5024	108	7	.	.	PUNCT
cana-5024	109	1	liu	liu	PROPN
cana-5024	109	2	et	et	PROPN
cana-5024	109	3	al	al	PROPN
cana-5024	109	4	.	.	PROPN
cana-5024	109	5	implemented	implement	VERB
cana-5024	109	6	residual	residual	ADJ
cana-5024	109	7	attention	attention	NOUN
cana-5024	109	8	networks	network	NOUN
cana-5024	109	9	for	for	ADP
cana-5024	109	10	skin	skin	NOUN
cana-5024	109	11	cancer	cancer	NOUN
cana-5024	109	12	recognition	recognition	NOUN
cana-5024	109	13	.	.	PUNCT
cana-5024	110	1	the	the	DET
cana-5024	110	2	residual	residual	ADJ
cana-5024	110	3	blocks	block	NOUN
cana-5024	110	4	preserved	preserve	VERB
cana-5024	110	5	feature	feature	NOUN
cana-5024	110	6	flow	flow	NOUN
cana-5024	110	7	.	.	PUNCT
cana-5024	111	1	attention	attention	NOUN
cana-5024	111	2	layers	layer	NOUN
cana-5024	111	3	focused	focus	VERB
cana-5024	111	4	on	on	ADP
cana-5024	111	5	critical	critical	ADJ
cana-5024	111	6	lesion	lesion	NOUN
cana-5024	111	7	areas	area	NOUN
cana-5024	111	8	.	.	PUNCT
cana-5024	112	1	han	han	PROPN
cana-5024	112	2	et	et	PROPN
cana-5024	112	3	al	al	PROPN
cana-5024	112	4	.	.	PROPN
cana-5024	112	5	developed	develop	VERB
cana-5024	112	6	a	a	DET
cana-5024	112	7	deep	deep	ADJ
cana-5024	112	8	neural	neural	ADJ
cana-5024	112	9	network	network	NOUN
cana-5024	112	10	capable	capable	ADJ
cana-5024	112	11	of	of	ADP
cana-5024	112	12	multi	multi	ADJ
cana-5024	112	13	-	-	ADJ
cana-5024	112	14	class	class	ADJ
cana-5024	112	15	classification	classification	NOUN
cana-5024	112	16	across	across	ADP
cana-5024	112	17	common	common	ADJ
cana-5024	112	18	skin	skin	NOUN
cana-5024	112	19	diseases	disease	NOUN
cana-5024	112	20	using	use	VERB
cana-5024	112	21	clinical	clinical	ADJ
cana-5024	112	22	images	image	NOUN
cana-5024	112	23	.	.	PUNCT
cana-5024	113	1	the	the	DET
cana-5024	113	2	model	model	NOUN
cana-5024	113	3	achieved	achieve	VERB
cana-5024	113	4	dermatologist	dermatologist	NOUN
cana-5024	113	5	-	-	PUNCT
cana-5024	113	6	level	level	NOUN
cana-5024	113	7	accuracy	accuracy	NOUN
cana-5024	113	8	in	in	ADP
cana-5024	113	9	identifying	identify	VERB
cana-5024	113	10	conditions	condition	NOUN
cana-5024	113	11	such	such	ADJ
cana-5024	113	12	as	as	ADP
cana-5024	113	13	melanoma	melanoma	NOUN
cana-5024	113	14	,	,	PUNCT
cana-5024	113	15	nevus	nevus	ADJ
cana-5024	113	16	,	,	PUNCT
cana-5024	113	17	and	and	CCONJ
cana-5024	113	18	seborrheic	seborrheic	ADJ
cana-5024	113	19	keratosis	keratosis	NOUN
cana-5024	113	20	.	.	PUNCT
cana-5024	114	1	rajesh	rajesh	PROPN
cana-5024	114	2	et	et	PROPN
cana-5024	114	3	al	al	PROPN
cana-5024	114	4	.	.	PROPN
cana-5024	114	5	discussed	discuss	VERB
cana-5024	114	6	various	various	ADJ
cana-5024	114	7	machine	machine	NOUN
cana-5024	114	8	learning	learn	VERB
cana-5024	114	9	approaches	approach	NOUN
cana-5024	114	10	for	for	ADP
cana-5024	114	11	data	datum	NOUN
cana-5024	114	12	analysis	analysis	NOUN
cana-5024	114	13	and	and	CCONJ
cana-5024	114	14	prediction	prediction	NOUN
cana-5024	114	15	using	use	VERB
cana-5024	114	16	j48	j48	PROPN
cana-5024	114	17	,	,	PUNCT
cana-5024	114	18	random	random	ADJ
cana-5024	114	19	tree	tree	NOUN
cana-5024	114	20	(	(	PUNCT
cana-5024	114	21	rt	rt	NOUN
cana-5024	114	22	)	)	PUNCT
cana-5024	114	23	,	,	PUNCT
cana-5024	114	24	decision	decision	NOUN
cana-5024	114	25	stump	stump	NOUN
cana-5024	114	26	(	(	PUNCT
cana-5024	114	27	ds	ds	NOUN
cana-5024	114	28	)	)	PUNCT
cana-5024	114	29	,	,	PUNCT
cana-5024	114	30	communications	communication	NOUN
cana-5024	114	31	on	on	ADP
cana-5024	114	32	applied	apply	VERB
cana-5024	114	33	nonlinear	nonlinear	ADJ
cana-5024	114	34	analysis	analysis	NOUN
cana-5024	114	35	issn	issn	NOUN
cana-5024	114	36	:	:	PUNCT
cana-5024	114	37	1074	1074	NUM
cana-5024	114	38	-	-	PUNCT
cana-5024	114	39	133x	133x	NUM
cana-5024	114	40	vol	vol	VERB
cana-5024	114	41	32	32	NUM
cana-5024	114	42	no.1s	no.1s	PROPN
cana-5024	114	43	(	(	PUNCT
cana-5024	114	44	2025	2025	NUM
cana-5024	114	45	)	)	PUNCT
cana-5024	114	46	646	646	NUM
cana-5024	114	47	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	114	48	logistic	logistic	ADJ
cana-5024	114	49	model	model	NOUN
cana-5024	114	50	tree	tree	NOUN
cana-5024	114	51	(	(	PUNCT
cana-5024	114	52	lmt	lmt	PROPN
cana-5024	114	53	)	)	PUNCT
cana-5024	114	54	,	,	PUNCT
cana-5024	114	55	hoeffding	hoeffde	VERB
cana-5024	114	56	tree	tree	NOUN
cana-5024	114	57	(	(	PUNCT
cana-5024	114	58	ht	ht	PROPN
cana-5024	114	59	)	)	PUNCT
cana-5024	114	60	,	,	PUNCT
cana-5024	114	61	reduce	reduce	VERB
cana-5024	114	62	error	error	NOUN
cana-5024	114	63	pruning	pruning	NOUN
cana-5024	114	64	(	(	PUNCT
cana-5024	114	65	rep	rep	NOUN
cana-5024	114	66	)	)	PUNCT
cana-5024	114	67	and	and	CCONJ
cana-5024	114	68	random	random	ADJ
cana-5024	114	69	forest	forest	NOUN
cana-5024	114	70	(	(	PUNCT
cana-5024	114	71	rf	rf	NOUN
cana-5024	114	72	)	)	PUNCT
cana-5024	114	73	.	.	PUNCT
cana-5024	115	1	performance	performance	NOUN
cana-5024	115	2	measurements	measurement	NOUN
cana-5024	115	3	also	also	ADV
cana-5024	115	4	used	use	VERB
cana-5024	115	5	to	to	PART
cana-5024	115	6	prove	prove	VERB
cana-5024	115	7	the	the	DET
cana-5024	115	8	proposed	propose	VERB
cana-5024	115	9	results	result	NOUN
cana-5024	115	10	.	.	PUNCT
cana-5024	116	1	menegola	menegola	PROPN
cana-5024	116	2	et	et	PROPN
cana-5024	116	3	al	al	PROPN
cana-5024	116	4	.	.	PUNCT
cana-5024	117	1	studies	study	NOUN
cana-5024	117	2	evaluated	evaluate	VERB
cana-5024	117	3	transfer	transfer	NOUN
cana-5024	117	4	learning	learn	VERB
cana-5024	117	5	techniques	technique	NOUN
cana-5024	117	6	using	use	VERB
cana-5024	117	7	various	various	ADJ
cana-5024	117	8	pre	pre	ADJ
cana-5024	117	9	-	-	ADJ
cana-5024	117	10	trained	train	VERB
cana-5024	117	11	models	model	NOUN
cana-5024	117	12	such	such	ADJ
cana-5024	117	13	as	as	ADP
cana-5024	117	14	inception	inception	NOUN
cana-5024	117	15	-	-	PUNCT
cana-5024	117	16	v4	v4	NOUN
cana-5024	117	17	,	,	PUNCT
cana-5024	117	18	resnet	resnet	NOUN
cana-5024	117	19	,	,	PUNCT
cana-5024	117	20	and	and	CCONJ
cana-5024	117	21	densenet	densenet	NOUN
cana-5024	117	22	for	for	ADP
cana-5024	117	23	dermoscopic	dermoscopic	ADJ
cana-5024	117	24	image	image	NOUN
cana-5024	117	25	classification	classification	NOUN
cana-5024	117	26	.	.	PUNCT
cana-5024	118	1	bi	bi	NOUN
cana-5024	118	2	et	et	PROPN
cana-5024	118	3	al	al	PROPN
cana-5024	118	4	.	.	PROPN
cana-5024	118	5	introduced	introduce	VERB
cana-5024	118	6	a	a	DET
cana-5024	118	7	deep	deep	ADJ
cana-5024	118	8	residual	residual	ADJ
cana-5024	118	9	cnn	cnn	NOUN
cana-5024	118	10	with	with	ADP
cana-5024	118	11	attention	attention	NOUN
cana-5024	118	12	modules	module	NOUN
cana-5024	118	13	to	to	PART
cana-5024	118	14	improve	improve	VERB
cana-5024	118	15	melanoma	melanoma	NOUN
cana-5024	118	16	detection	detection	NOUN
cana-5024	118	17	.	.	PUNCT
cana-5024	119	1	their	their	PRON
cana-5024	119	2	architecture	architecture	NOUN
cana-5024	119	3	integrated	integrate	VERB
cana-5024	119	4	residual	residual	ADJ
cana-5024	119	5	learning	learning	NOUN
cana-5024	119	6	to	to	PART
cana-5024	119	7	maintain	maintain	VERB
cana-5024	119	8	deep	deep	ADJ
cana-5024	119	9	feature	feature	NOUN
cana-5024	119	10	propagation	propagation	NOUN
cana-5024	119	11	and	and	CCONJ
cana-5024	119	12	incorporated	incorporate	VERB
cana-5024	119	13	attention	attention	NOUN
cana-5024	119	14	mechanisms	mechanism	NOUN
cana-5024	119	15	to	to	PART
cana-5024	119	16	focus	focus	VERB
cana-5024	119	17	on	on	ADP
cana-5024	119	18	critical	critical	ADJ
cana-5024	119	19	lesion	lesion	NOUN
cana-5024	119	20	areas	area	NOUN
cana-5024	119	21	.	.	PUNCT
cana-5024	120	1	li	li	PROPN
cana-5024	120	2	and	and	CCONJ
cana-5024	120	3	shen	shen	PROPN
cana-5024	120	4	proposed	propose	VERB
cana-5024	120	5	a	a	DET
cana-5024	120	6	dual	dual	ADJ
cana-5024	120	7	-	-	PUNCT
cana-5024	120	8	path	path	NOUN
cana-5024	120	9	network	network	NOUN
cana-5024	120	10	for	for	ADP
cana-5024	120	11	lesion	lesion	NOUN
cana-5024	120	12	classification	classification	NOUN
cana-5024	120	13	that	that	PRON
cana-5024	120	14	simultaneously	simultaneously	ADV
cana-5024	120	15	processed	process	VERB
cana-5024	120	16	global	global	ADJ
cana-5024	120	17	and	and	CCONJ
cana-5024	120	18	local	local	ADJ
cana-5024	120	19	views	view	NOUN
cana-5024	120	20	of	of	ADP
cana-5024	120	21	dermoscopic	dermoscopic	ADJ
cana-5024	120	22	images	image	NOUN
cana-5024	120	23	.	.	PUNCT
cana-5024	121	1	by	by	ADP
cana-5024	121	2	combining	combine	VERB
cana-5024	121	3	wide	wide	ADJ
cana-5024	121	4	context	context	NOUN
cana-5024	121	5	with	with	ADP
cana-5024	121	6	fine	fine	ADJ
cana-5024	121	7	lesion	lesion	NOUN
cana-5024	121	8	details	detail	NOUN
cana-5024	121	9	,	,	PUNCT
cana-5024	121	10	their	their	PRON
cana-5024	121	11	network	network	NOUN
cana-5024	121	12	captured	capture	VERB
cana-5024	121	13	complementary	complementary	ADJ
cana-5024	121	14	features	feature	NOUN
cana-5024	121	15	.	.	PUNCT
cana-5024	122	1	pandey	pandey	PROPN
cana-5024	122	2	and	and	CCONJ
cana-5024	122	3	sahu	sahu	PROPN
cana-5024	122	4	applied	apply	VERB
cana-5024	122	5	deep	deep	ADJ
cana-5024	122	6	cnns	cnn	NOUN
cana-5024	122	7	with	with	ADP
cana-5024	122	8	modified	modify	VERB
cana-5024	122	9	loss	loss	NOUN
cana-5024	122	10	functions	function	NOUN
cana-5024	122	11	to	to	PART
cana-5024	122	12	address	address	VERB
cana-5024	122	13	class	class	NOUN
cana-5024	122	14	imbalance	imbalance	NOUN
cana-5024	122	15	in	in	ADP
cana-5024	122	16	lesion	lesion	NOUN
cana-5024	122	17	classification	classification	NOUN
cana-5024	122	18	.	.	PUNCT
cana-5024	123	1	by	by	ADP
cana-5024	123	2	using	use	VERB
cana-5024	123	3	focal	focal	ADJ
cana-5024	123	4	loss	loss	NOUN
cana-5024	123	5	and	and	CCONJ
cana-5024	123	6	weighted	weight	VERB
cana-5024	123	7	cross	cross	NOUN
cana-5024	123	8	-	-	NOUN
cana-5024	123	9	entropy	entropy	ADJ
cana-5024	123	10	,	,	PUNCT
cana-5024	123	11	they	they	PRON
cana-5024	123	12	managed	manage	VERB
cana-5024	123	13	to	to	PART
cana-5024	123	14	reduce	reduce	VERB
cana-5024	123	15	the	the	DET
cana-5024	123	16	bias	bias	NOUN
cana-5024	123	17	toward	toward	ADP
cana-5024	123	18	majority	majority	NOUN
cana-5024	123	19	classes	class	NOUN
cana-5024	123	20	.	.	PUNCT
cana-5024	124	1	serte	serte	NOUN
cana-5024	124	2	and	and	CCONJ
cana-5024	124	3	demirel	demirel	NOUN
cana-5024	124	4	introduced	introduce	VERB
cana-5024	124	5	a	a	DET
cana-5024	124	6	compact	compact	ADJ
cana-5024	124	7	cnn	cnn	NOUN
cana-5024	124	8	model	model	NOUN
cana-5024	124	9	optimized	optimize	VERB
cana-5024	124	10	for	for	ADP
cana-5024	124	11	resourceconstrained	resourceconstraine	VERB
cana-5024	124	12	environments	environment	NOUN
cana-5024	124	13	.	.	PUNCT
cana-5024	125	1	despite	despite	SCONJ
cana-5024	125	2	having	have	VERB
cana-5024	125	3	fewer	few	ADJ
cana-5024	125	4	parameters	parameter	NOUN
cana-5024	125	5	,	,	PUNCT
cana-5024	125	6	the	the	DET
cana-5024	125	7	model	model	NOUN
cana-5024	125	8	maintained	maintain	VERB
cana-5024	125	9	high	high	ADJ
cana-5024	125	10	diagnostic	diagnostic	ADJ
cana-5024	125	11	accuracy	accuracy	NOUN
cana-5024	125	12	on	on	ADP
cana-5024	125	13	the	the	DET
cana-5024	125	14	isic	isic	PROPN
cana-5024	125	15	dataset	dataset	NOUN
cana-5024	125	16	.	.	PUNCT
cana-5024	126	1	their	their	PRON
cana-5024	126	2	work	work	NOUN
cana-5024	126	3	demonstrated	demonstrate	VERB
cana-5024	126	4	the	the	DET
cana-5024	126	5	feasibility	feasibility	NOUN
cana-5024	126	6	of	of	ADP
cana-5024	126	7	deploying	deploy	VERB
cana-5024	126	8	deep	deep	ADJ
cana-5024	126	9	learning	learning	NOUN
cana-5024	126	10	tools	tool	NOUN
cana-5024	126	11	on	on	ADP
cana-5024	126	12	mobile	mobile	ADJ
cana-5024	126	13	or	or	CCONJ
cana-5024	126	14	embedded	embed	VERB
cana-5024	126	15	devices	device	NOUN
cana-5024	126	16	for	for	ADP
cana-5024	126	17	remote	remote	ADJ
cana-5024	126	18	dermatological	dermatological	ADJ
cana-5024	126	19	screening	screening	NOUN
cana-5024	126	20	.	.	PUNCT
cana-5024	127	1	yu	yu	PROPN
cana-5024	127	2	et	et	PROPN
cana-5024	127	3	al	al	PROPN
cana-5024	127	4	.	.	PROPN
cana-5024	127	5	introduced	introduce	VERB
cana-5024	127	6	a	a	DET
cana-5024	127	7	3d	3d	NUM
cana-5024	127	8	cnn	cnn	PROPN
cana-5024	127	9	model	model	NOUN
cana-5024	127	10	that	that	PRON
cana-5024	127	11	processes	process	VERB
cana-5024	127	12	volumetric	volumetric	ADJ
cana-5024	127	13	skin	skin	NOUN
cana-5024	127	14	lesion	lesion	NOUN
cana-5024	127	15	data	datum	NOUN
cana-5024	127	16	acquired	acquire	VERB
cana-5024	127	17	through	through	ADP
cana-5024	127	18	dermoscopic	dermoscopic	ADJ
cana-5024	127	19	video	video	NOUN
cana-5024	127	20	frames	frame	NOUN
cana-5024	127	21	.	.	PUNCT
cana-5024	128	1	this	this	DET
cana-5024	128	2	approach	approach	NOUN
cana-5024	128	3	allowed	allow	VERB
cana-5024	128	4	for	for	ADP
cana-5024	128	5	temporal	temporal	ADJ
cana-5024	128	6	consistency	consistency	NOUN
cana-5024	128	7	in	in	ADP
cana-5024	128	8	lesion	lesion	NOUN
cana-5024	128	9	analysis	analysis	NOUN
cana-5024	128	10	,	,	PUNCT
cana-5024	128	11	enhancing	enhance	VERB
cana-5024	128	12	classification	classification	NOUN
cana-5024	128	13	robustness	robustness	NOUN
cana-5024	128	14	and	and	CCONJ
cana-5024	128	15	reducing	reduce	VERB
cana-5024	128	16	false	false	ADJ
cana-5024	128	17	positives	positive	NOUN
cana-5024	128	18	in	in	ADP
cana-5024	128	19	sequential	sequential	ADJ
cana-5024	128	20	image	image	NOUN
cana-5024	128	21	settings	setting	NOUN
cana-5024	128	22	.	.	PUNCT
cana-5024	129	1	abbas	abbas	PROPN
cana-5024	129	2	and	and	CCONJ
cana-5024	129	3	colleagues	colleague	NOUN
cana-5024	129	4	proposed	propose	VERB
cana-5024	129	5	a	a	DET
cana-5024	129	6	hybrid	hybrid	ADJ
cana-5024	129	7	deep	deep	ADJ
cana-5024	129	8	learning	learning	NOUN
cana-5024	129	9	model	model	NOUN
cana-5024	129	10	combining	combine	VERB
cana-5024	129	11	cnns	cnn	NOUN
cana-5024	129	12	with	with	ADP
cana-5024	129	13	recurrent	recurrent	ADJ
cana-5024	129	14	neural	neural	ADJ
cana-5024	129	15	networks	network	NOUN
cana-5024	129	16	(	(	PUNCT
cana-5024	129	17	rnns	rnns	PROPN
cana-5024	129	18	)	)	PUNCT
cana-5024	129	19	.	.	PUNCT
cana-5024	130	1	noor	noor	PROPN
cana-5024	130	2	et	et	PROPN
cana-5024	130	3	al	al	PROPN
cana-5024	130	4	.	.	PROPN
cana-5024	130	5	designed	design	VERB
cana-5024	130	6	a	a	DET
cana-5024	130	7	lightweight	lightweight	ADJ
cana-5024	130	8	cnn	cnn	PROPN
cana-5024	130	9	using	use	VERB
cana-5024	130	10	depth	depth	NOUN
cana-5024	130	11	wise	wise	ADJ
cana-5024	130	12	separable	separable	ADJ
cana-5024	130	13	convolutions	convolution	NOUN
cana-5024	130	14	to	to	PART
cana-5024	130	15	reduce	reduce	VERB
cana-5024	130	16	computational	computational	ADJ
cana-5024	130	17	complexity	complexity	NOUN
cana-5024	130	18	.	.	PUNCT
cana-5024	131	1	despite	despite	SCONJ
cana-5024	131	2	its	its	PRON
cana-5024	131	3	efficiency	efficiency	NOUN
cana-5024	131	4	,	,	PUNCT
cana-5024	131	5	the	the	DET
cana-5024	131	6	model	model	NOUN
cana-5024	131	7	achieved	achieve	VERB
cana-5024	131	8	competitive	competitive	ADJ
cana-5024	131	9	results	result	NOUN
cana-5024	131	10	on	on	ADP
cana-5024	131	11	the	the	DET
cana-5024	131	12	ham10000	ham10000	PROPN
cana-5024	131	13	dataset	dataset	PROPN
cana-5024	131	14	.	.	PUNCT
cana-5024	132	1	almarazdamian	almarazdamian	PROPN
cana-5024	132	2	et	et	PROPN
cana-5024	132	3	al	al	PROPN
cana-5024	132	4	.	.	PROPN
cana-5024	132	5	team	team	PROPN
cana-5024	132	6	developed	develop	VERB
cana-5024	132	7	an	an	DET
cana-5024	132	8	interpretable	interpretable	ADJ
cana-5024	132	9	cnn	cnn	NOUN
cana-5024	132	10	model	model	NOUN
cana-5024	132	11	for	for	ADP
cana-5024	132	12	lesion	lesion	NOUN
cana-5024	132	13	classification	classification	NOUN
cana-5024	132	14	by	by	ADP
cana-5024	132	15	integrating	integrate	VERB
cana-5024	132	16	saliency	saliency	NOUN
cana-5024	132	17	maps	map	NOUN
cana-5024	132	18	and	and	CCONJ
cana-5024	132	19	class	class	NOUN
cana-5024	132	20	activation	activation	NOUN
cana-5024	132	21	maps	map	NOUN
cana-5024	132	22	(	(	PUNCT
cana-5024	132	23	cams	cam	NOUN
cana-5024	132	24	)	)	PUNCT
cana-5024	132	25	.	.	PUNCT
cana-5024	133	1	dataset	dataset	VERB
cana-5024	133	2	the	the	DET
cana-5024	133	3	ham10000	ham10000	NOUN
cana-5024	133	4	(	(	PUNCT
cana-5024	133	5	"	"	PUNCT
cana-5024	133	6	human	human	ADJ
cana-5024	133	7	against	against	ADP
cana-5024	133	8	machine	machine	NOUN
cana-5024	133	9	with	with	ADP
cana-5024	133	10	10000	10000	NUM
cana-5024	133	11	training	training	NOUN
cana-5024	133	12	images	image	NOUN
cana-5024	133	13	"	"	PUNCT
cana-5024	133	14	)	)	PUNCT
cana-5024	133	15	dataset	dataset	NOUN
cana-5024	133	16	which	which	PRON
cana-5024	133	17	contains	contain	VERB
cana-5024	133	18	.	.	PUNCT
cana-5024	134	1	10,015	10,015	NUM
cana-5024	134	2	dermatoscopic	dermatoscopic	NOUN
cana-5024	134	3	images	image	NOUN
cana-5024	134	4	,	,	PUNCT
cana-5024	134	5	7	7	NUM
cana-5024	134	6	diagnostic	diagnostic	ADJ
cana-5024	134	7	categories	category	NOUN
cana-5024	134	8	namely	namely	ADV
cana-5024	134	9	melanoma	melanoma	VERB
cana-5024	134	10	,	,	PUNCT
cana-5024	134	11	melanocytic	melanocytic	ADJ
cana-5024	134	12	nevi	nevi	NOUN
cana-5024	134	13	,	,	PUNCT
cana-5024	134	14	basal	basal	ADJ
cana-5024	134	15	cell	cell	NOUN
cana-5024	134	16	carcinoma	carcinoma	NOUN
cana-5024	134	17	,	,	PUNCT
cana-5024	134	18	actinic	actinic	ADJ
cana-5024	134	19	keratoses	keratose	NOUN
cana-5024	134	20	,	,	PUNCT
cana-5024	134	21	benign	benign	ADJ
cana-5024	134	22	keratosis	keratosis	NOUN
cana-5024	134	23	-	-	PUNCT
cana-5024	134	24	like	like	ADJ
cana-5024	134	25	lesions	lesion	NOUN
cana-5024	134	26	,	,	PUNCT
cana-5024	134	27	dermatofibroma	dermatofibroma	ADJ
cana-5024	134	28	,	,	PUNCT
cana-5024	134	29	and	and	CCONJ
cana-5024	134	30	vascular	vascular	ADJ
cana-5024	134	31	lesions	lesion	NOUN
cana-5024	134	32	.	.	PUNCT
cana-5024	135	1	images	image	NOUN
cana-5024	135	2	are	be	AUX
cana-5024	135	3	labelled	label	VERB
cana-5024	135	4	and	and	CCONJ
cana-5024	135	5	verified	verify	VERB
cana-5024	135	6	by	by	ADP
cana-5024	135	7	expert	expert	NOUN
cana-5024	135	8	dermatologists	dermatologist	NOUN
cana-5024	135	9	.	.	PUNCT
cana-5024	136	1	the	the	DET
cana-5024	136	2	data	data	NOUN
cana-5024	136	3	preprocessing	preprocessing	NOUN
cana-5024	136	4	uses	use	VERB
cana-5024	136	5	various	various	ADJ
cana-5024	136	6	stages	stage	NOUN
cana-5024	136	7	namely	namely	ADV
cana-5024	136	8	images	image	NOUN
cana-5024	136	9	resized	resize	VERB
cana-5024	136	10	to	to	ADP
cana-5024	136	11	224x224	224x224	NUM
cana-5024	136	12	,	,	PUNCT
cana-5024	136	13	suitable	suitable	ADJ
cana-5024	136	14	augmentation	augmentation	NOUN
cana-5024	136	15	,	,	PUNCT
cana-5024	136	16	and	and	CCONJ
cana-5024	136	17	data	datum	NOUN
cana-5024	136	18	imbalance	imbalance	NOUN
cana-5024	136	19	addressed	address	VERB
cana-5024	136	20	using	use	VERB
cana-5024	136	21	oversampling	oversampling	NOUN
cana-5024	136	22	.	.	PUNCT
cana-5024	137	1	the	the	DET
cana-5024	137	2	process	process	NOUN
cana-5024	137	3	of	of	ADP
cana-5024	137	4	preparing	prepare	VERB
cana-5024	137	5	a	a	DET
cana-5024	137	6	dataset	dataset	NOUN
cana-5024	137	7	and	and	CCONJ
cana-5024	137	8	generating	generate	VERB
cana-5024	137	9	experimental	experimental	ADJ
cana-5024	137	10	results	result	NOUN
cana-5024	137	11	.	.	PUNCT
cana-5024	138	1	communications	communication	NOUN
cana-5024	138	2	on	on	ADP
cana-5024	138	3	applied	apply	VERB
cana-5024	138	4	nonlinear	nonlinear	ADJ
cana-5024	138	5	analysis	analysis	NOUN
cana-5024	138	6	issn	issn	NOUN
cana-5024	138	7	:	:	PUNCT
cana-5024	138	8	1074	1074	NUM
cana-5024	138	9	-	-	PUNCT
cana-5024	138	10	133x	133x	NUM
cana-5024	138	11	vol	vol	VERB
cana-5024	138	12	32	32	NUM
cana-5024	138	13	no.1s	no.1s	PROPN
cana-5024	138	14	(	(	PUNCT
cana-5024	138	15	2025	2025	NUM
cana-5024	138	16	)	)	PUNCT
cana-5024	138	17	647	647	NUM
cana-5024	138	18	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	138	19	fig	fig	NOUN
cana-5024	138	20	.	.	PUNCT
cana-5024	139	1	1	1	X
cana-5024	139	2	.	.	PUNCT
cana-5024	139	3	different	different	ADJ
cana-5024	139	4	types	type	NOUN
cana-5024	139	5	of	of	ADP
cana-5024	139	6	skin	skin	NOUN
cana-5024	139	7	cancer	cancer	NOUN
cana-5024	139	8	fig	fig	NOUN
cana-5024	139	9	.	.	PUNCT
cana-5024	140	1	2	2	X
cana-5024	140	2	.	.	NUM
cana-5024	140	3	images	image	NOUN
cana-5024	140	4	from	from	ADP
cana-5024	140	5	ham10000	ham10000	PROPN
cana-5024	140	6	fig	fig	PROPN
cana-5024	140	7	.	.	PUNCT
cana-5024	141	1	3	3	X
cana-5024	141	2	.	.	X
cana-5024	141	3	different	different	ADJ
cana-5024	141	4	stages	stage	NOUN
cana-5024	141	5	of	of	ADP
cana-5024	141	6	preprocessing	preprocesse	VERB
cana-5024	141	7	4	4	NUM
cana-5024	141	8	.	.	PUNCT
cana-5024	141	9	backgrounds	background	NOUN
cana-5024	141	10	and	and	CCONJ
cana-5024	141	11	methodologies	methodology	NOUN
cana-5024	141	12	deep	deep	ADJ
cana-5024	141	13	learning	learning	NOUN
cana-5024	141	14	,	,	PUNCT
cana-5024	141	15	especially	especially	ADV
cana-5024	141	16	cnns	cnn	NOUN
cana-5024	141	17	,	,	PUNCT
cana-5024	141	18	has	have	AUX
cana-5024	141	19	revolutionized	revolutionize	VERB
cana-5024	141	20	image	image	NOUN
cana-5024	141	21	classification	classification	NOUN
cana-5024	141	22	by	by	ADP
cana-5024	141	23	automatically	automatically	ADV
cana-5024	141	24	extracting	extract	VERB
cana-5024	141	25	spatial	spatial	ADJ
cana-5024	141	26	features	feature	NOUN
cana-5024	141	27	.	.	PUNCT
cana-5024	142	1	however	however	ADV
cana-5024	142	2	,	,	PUNCT
cana-5024	142	3	these	these	DET
cana-5024	142	4	models	model	NOUN
cana-5024	142	5	require	require	VERB
cana-5024	142	6	careful	careful	ADJ
cana-5024	142	7	tuning	tuning	NOUN
cana-5024	142	8	of	of	ADP
cana-5024	142	9	parameters	parameter	NOUN
cana-5024	142	10	such	such	ADJ
cana-5024	142	11	as	as	ADP
cana-5024	142	12	learning	learn	VERB
cana-5024	142	13	rate	rate	NOUN
cana-5024	142	14	,	,	PUNCT
cana-5024	142	15	batch	batch	NOUN
cana-5024	142	16	size	size	NOUN
cana-5024	142	17	,	,	PUNCT
cana-5024	142	18	number	number	NOUN
cana-5024	142	19	of	of	ADP
cana-5024	142	20	layers	layer	NOUN
cana-5024	142	21	,	,	PUNCT
cana-5024	142	22	and	and	CCONJ
cana-5024	142	23	filter	filter	NOUN
cana-5024	142	24	size	size	NOUN
cana-5024	142	25	.	.	PUNCT
cana-5024	143	1	manual	manual	ADJ
cana-5024	143	2	tuning	tuning	NOUN
cana-5024	143	3	is	be	AUX
cana-5024	143	4	time	time	NOUN
cana-5024	143	5	-	-	PUNCT
cana-5024	143	6	consuming	consume	VERB
cana-5024	143	7	and	and	CCONJ
cana-5024	143	8	may	may	AUX
cana-5024	143	9	not	not	PART
cana-5024	143	10	guarantee	guarantee	VERB
cana-5024	143	11	optimal	optimal	ADJ
cana-5024	143	12	performance	performance	NOUN
cana-5024	143	13	.	.	PUNCT
cana-5024	144	1	communications	communication	NOUN
cana-5024	144	2	on	on	ADP
cana-5024	144	3	applied	apply	VERB
cana-5024	144	4	nonlinear	nonlinear	ADJ
cana-5024	144	5	analysis	analysis	NOUN
cana-5024	144	6	issn	issn	NOUN
cana-5024	144	7	:	:	PUNCT
cana-5024	144	8	1074	1074	NUM
cana-5024	144	9	-	-	PUNCT
cana-5024	144	10	133x	133x	NUM
cana-5024	144	11	vol	vol	VERB
cana-5024	144	12	32	32	NUM
cana-5024	144	13	no.1s	no.1s	PROPN
cana-5024	144	14	(	(	PUNCT
cana-5024	144	15	2025	2025	NUM
cana-5024	144	16	)	)	PUNCT
cana-5024	144	17	648	648	NUM
cana-5024	144	18	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	144	19	3	3	X
cana-5024	144	20	.	.	X
cana-5024	144	21	methodology	methodology	NOUN
cana-5024	144	22	our	our	PRON
cana-5024	144	23	approach	approach	NOUN
cana-5024	144	24	includes	include	VERB
cana-5024	144	25	the	the	DET
cana-5024	144	26	following	follow	VERB
cana-5024	144	27	stages	stage	NOUN
cana-5024	144	28	with	with	ADP
cana-5024	144	29	metrics	metric	NOUN
cana-5024	144	30	include	include	VERB
cana-5024	144	31	accuracy	accuracy	NOUN
cana-5024	144	32	,	,	PUNCT
cana-5024	144	33	precision	precision	NOUN
cana-5024	144	34	,	,	PUNCT
cana-5024	144	35	recall	recall	NOUN
cana-5024	144	36	,	,	PUNCT
cana-5024	144	37	f1	f1	NOUN
cana-5024	144	38	-	-	PUNCT
cana-5024	144	39	score	score	NOUN
cana-5024	144	40	,	,	PUNCT
cana-5024	144	41	and	and	CCONJ
cana-5024	144	42	auc	auc	NOUN
cana-5024	144	43	.	.	PUNCT
cana-5024	145	1	based	base	VERB
cana-5024	145	2	on	on	ADP
cana-5024	145	3	your	your	PRON
cana-5024	145	4	research	research	NOUN
cana-5024	145	5	on	on	ADP
cana-5024	145	6	enhancing	enhance	VERB
cana-5024	145	7	skin	skin	NOUN
cana-5024	145	8	cancer	cancer	NOUN
cana-5024	145	9	diagnosis	diagnosis	NOUN
cana-5024	145	10	,	,	PUNCT
cana-5024	145	11	here	here	ADV
cana-5024	145	12	are	be	AUX
cana-5024	145	13	the	the	DET
cana-5024	145	14	structured	structure	VERB
cana-5024	145	15	algorithms	algorithm	NOUN
cana-5024	145	16	for	for	ADP
cana-5024	145	17	:	:	PUNCT
cana-5024	145	18	3.1	3.1	NUM
cana-5024	145	19	baseline	baseline	PROPN
cana-5024	145	20	cnn	cnn	NOUN
cana-5024	145	21	architecture	architecture	NOUN
cana-5024	145	22	for	for	ADP
cana-5024	145	23	skin	skin	NOUN
cana-5024	145	24	cancer	cancer	NOUN
cana-5024	145	25	classification	classification	NOUN
cana-5024	145	26	input	input	NOUN
cana-5024	145	27	:	:	PUNCT
cana-5024	145	28	pre	pre	ADJ
cana-5024	145	29	-	-	ADJ
cana-5024	145	30	processed	process	VERB
cana-5024	145	31	dermatoscopic	dermatoscopic	NOUN
cana-5024	145	32	images	image	NOUN
cana-5024	145	33	from	from	ADP
cana-5024	145	34	the	the	DET
cana-5024	145	35	ham10000	ham10000	PROPN
cana-5024	145	36	dataset	dataset	PROPN
cana-5024	145	37	output	output	NOUN
cana-5024	145	38	:	:	PUNCT
cana-5024	145	39	predicted	predict	VERB
cana-5024	145	40	skin	skin	NOUN
cana-5024	145	41	lesion	lesion	NOUN
cana-5024	145	42	class	class	NOUN
cana-5024	145	43	step	step	NOUN
cana-5024	145	44	1	1	NUM
cana-5024	145	45	:	:	PUNCT
cana-5024	145	46	load	load	NOUN
cana-5024	145	47	and	and	CCONJ
cana-5024	145	48	preprocess	preprocess	NOUN
cana-5024	145	49	the	the	DET
cana-5024	145	50	dataset	dataset	NOUN
cana-5024	145	51	:	:	PUNCT
cana-5024	145	52	resize	resize	VERB
cana-5024	145	53	images	image	NOUN
cana-5024	145	54	to	to	ADP
cana-5024	145	55	224x224	224x224	NUM
cana-5024	145	56	pixels	pixel	NOUN
cana-5024	145	57	,	,	PUNCT
cana-5024	145	58	normalize	normalize	VERB
cana-5024	145	59	pixel	pixel	ADJ
cana-5024	145	60	values	value	NOUN
cana-5024	145	61	to	to	ADP
cana-5024	145	62	[	[	X
cana-5024	145	63	0	0	NUM
cana-5024	145	64	,	,	PUNCT
cana-5024	145	65	1	1	NUM
cana-5024	145	66	]	]	PUNCT
cana-5024	145	67	,	,	PUNCT
cana-5024	145	68	and	and	CCONJ
cana-5024	145	69	perform	perform	VERB
cana-5024	145	70	data	data	NOUN
cana-5024	145	71	augmentation	augmentation	NOUN
cana-5024	145	72	(	(	PUNCT
cana-5024	145	73	rotation	rotation	NOUN
cana-5024	145	74	,	,	PUNCT
cana-5024	145	75	flips	flip	NOUN
cana-5024	145	76	,	,	PUNCT
cana-5024	145	77	zoom	zoom	NOUN
cana-5024	145	78	)	)	PUNCT
cana-5024	145	79	step	step	NOUN
cana-5024	145	80	2	2	NUM
cana-5024	145	81	:	:	PUNCT
cana-5024	145	82	initialize	initialize	VERB
cana-5024	145	83	a	a	DET
cana-5024	145	84	cnn	cnn	NOUN
cana-5024	145	85	architecture	architecture	NOUN
cana-5024	145	86	:	:	PUNCT
cana-5024	145	87	(	(	PUNCT
cana-5024	145	88	a	a	X
cana-5024	145	89	)	)	PUNCT
cana-5024	145	90	conv2d	conv2d	PROPN
cana-5024	145	91	→	→	SYM
cana-5024	145	92	relu	relu	NOUN
cana-5024	145	93	→	→	SYM
cana-5024	145	94	maxpooling	maxpoole	VERB
cana-5024	145	95	,	,	PUNCT
cana-5024	145	96	(	(	PUNCT
cana-5024	145	97	b	b	NOUN
cana-5024	145	98	)	)	PUNCT
cana-5024	145	99	flatten	flatten	ADJ
cana-5024	145	100	,	,	PUNCT
cana-5024	145	101	(	(	PUNCT
cana-5024	145	102	c	c	X
cana-5024	145	103	)	)	PUNCT
cana-5024	145	104	dense	dense	ADJ
cana-5024	145	105	→	→	SYM
cana-5024	145	106	relu	relu	NOUN
cana-5024	145	107	,	,	PUNCT
cana-5024	145	108	(	(	PUNCT
cana-5024	145	109	d	d	NOUN
cana-5024	145	110	)	)	PUNCT
cana-5024	145	111	dropout	dropout	NOUN
cana-5024	145	112	,	,	PUNCT
cana-5024	145	113	and	and	CCONJ
cana-5024	145	114	(	(	PUNCT
cana-5024	145	115	d	d	X
cana-5024	145	116	)	)	PUNCT
cana-5024	145	117	dense	dense	ADJ
cana-5024	145	118	(	(	PUNCT
cana-5024	145	119	softmax	softmax	NOUN
cana-5024	145	120	activation	activation	NOUN
cana-5024	145	121	)	)	PUNCT
cana-5024	145	122	step	step	NOUN
cana-5024	145	123	3	3	NUM
cana-5024	145	124	:	:	PUNCT
cana-5024	145	125	compile	compile	VERB
cana-5024	145	126	the	the	DET
cana-5024	145	127	model	model	NOUN
cana-5024	145	128	:	:	PUNCT
cana-5024	145	129	loss	loss	NOUN
cana-5024	145	130	function	function	NOUN
cana-5024	145	131	:	:	PUNCT
cana-5024	145	132	categorical	categorical	PROPN
cana-5024	145	133	cross	cross	NOUN
cana-5024	145	134	entropy	entropy	NOUN
cana-5024	145	135	,	,	PUNCT
cana-5024	145	136	optimizer	optimizer	NOUN
cana-5024	145	137	:	:	PUNCT
cana-5024	145	138	adam	adam	NOUN
cana-5024	145	139	,	,	PUNCT
cana-5024	145	140	and	and	CCONJ
cana-5024	145	141	metrics	metric	NOUN
cana-5024	145	142	:	:	PUNCT
cana-5024	145	143	accuracy	accuracy	NOUN
cana-5024	145	144	step	step	NOUN
cana-5024	145	145	4	4	NUM
cana-5024	145	146	:	:	PUNCT
cana-5024	145	147	train	train	VERB
cana-5024	145	148	the	the	DET
cana-5024	145	149	model	model	NOUN
cana-5024	145	150	:	:	PUNCT
cana-5024	145	151	set	set	ADJ
cana-5024	145	152	epochs	epoch	NOUN
cana-5024	145	153	and	and	CCONJ
cana-5024	145	154	batch	batch	NOUN
cana-5024	145	155	size	size	NOUN
cana-5024	145	156	(	(	PUNCT
cana-5024	145	157	25	25	NUM
cana-5024	145	158	epochs	epoch	NOUN
cana-5024	145	159	,	,	PUNCT
cana-5024	145	160	batch	batch	NOUN
cana-5024	145	161	size	size	NOUN
cana-5024	145	162	=	=	SYM
cana-5024	145	163	32	32	NUM
cana-5024	145	164	)	)	PUNCT
cana-5024	145	165	use	use	VERB
cana-5024	145	166	80	80	NUM
cana-5024	145	167	%	%	NOUN
cana-5024	145	168	training	training	NOUN
cana-5024	145	169	and	and	CCONJ
cana-5024	145	170	20	20	NUM
cana-5024	145	171	%	%	NOUN
cana-5024	145	172	validation	validation	NOUN
cana-5024	145	173	split	split	VERB
cana-5024	145	174	step	step	NOUN
cana-5024	145	175	5	5	NUM
cana-5024	145	176	:	:	PUNCT
cana-5024	145	177	evaluate	evaluate	VERB
cana-5024	145	178	model	model	NOUN
cana-5024	145	179	:	:	PUNCT
cana-5024	145	180	generate	generate	VERB
cana-5024	145	181	accuracy	accuracy	NOUN
cana-5024	145	182	,	,	PUNCT
cana-5024	145	183	precision	precision	NOUN
cana-5024	145	184	,	,	PUNCT
cana-5024	145	185	recall	recall	NOUN
cana-5024	145	186	,	,	PUNCT
cana-5024	145	187	f1	f1	NOUN
cana-5024	145	188	-	-	PUNCT
cana-5024	145	189	score	score	NOUN
cana-5024	145	190	3.2.2	3.2.2	NUM
cana-5024	145	191	hyperparameter	hyperparameter	NOUN
cana-5024	145	192	tuning	tune	VERB
cana-5024	145	193	with	with	ADP
cana-5024	145	194	genetic	genetic	ADJ
cana-5024	145	195	algorithm	algorithm	NOUN
cana-5024	145	196	(	(	PUNCT
cana-5024	145	197	ga	ga	NOUN
cana-5024	145	198	)	)	PUNCT
cana-5024	145	199	input	input	NOUN
cana-5024	145	200	:	:	PUNCT
cana-5024	145	201	cnn	cnn	PROPN
cana-5024	145	202	model	model	NOUN
cana-5024	145	203	,	,	PUNCT
cana-5024	145	204	search	search	NOUN
cana-5024	145	205	space	space	NOUN
cana-5024	145	206	for	for	ADP
cana-5024	145	207	hyperparameters	hyperparameter	NOUN
cana-5024	145	208	output	output	NOUN
cana-5024	145	209	:	:	PUNCT
cana-5024	145	210	optimal	optimal	ADJ
cana-5024	145	211	set	set	NOUN
cana-5024	145	212	of	of	ADP
cana-5024	145	213	hyperparameters	hyperparameter	NOUN
cana-5024	145	214	steps	step	NOUN
cana-5024	145	215	1	1	NUM
cana-5024	145	216	:	:	PUNCT
cana-5024	145	217	define	define	VERB
cana-5024	145	218	hyperparameter	hyperparameter	NOUN
cana-5024	145	219	chromosome	chromosome	NOUN
cana-5024	145	220	(	(	PUNCT
cana-5024	145	221	individual	individual	ADJ
cana-5024	145	222	):	):	PUNCT
cana-5024	145	223	learning	learn	VERB
cana-5024	145	224	rate	rate	NOUN
cana-5024	145	225	,	,	PUNCT
cana-5024	145	226	batch	batch	NOUN
cana-5024	145	227	size	size	NOUN
cana-5024	145	228	,	,	PUNCT
cana-5024	145	229	dropout	dropout	NOUN
cana-5024	145	230	rate	rate	NOUN
cana-5024	145	231	,	,	PUNCT
cana-5024	145	232	number	number	NOUN
cana-5024	145	233	of	of	ADP
cana-5024	145	234	filters	filter	NOUN
cana-5024	145	235	,	,	PUNCT
cana-5024	145	236	number	number	NOUN
cana-5024	145	237	of	of	ADP
cana-5024	145	238	layers	layer	NOUN
cana-5024	145	239	step	step	VERB
cana-5024	145	240	2	2	NUM
cana-5024	145	241	:	:	PUNCT
cana-5024	145	242	initialize	initialize	VERB
cana-5024	145	243	a	a	DET
cana-5024	145	244	population	population	NOUN
cana-5024	145	245	of	of	ADP
cana-5024	145	246	n	n	PRON
cana-5024	145	247	individuals	individual	NOUN
cana-5024	145	248	randomly	randomly	ADV
cana-5024	145	249	step	step	VERB
cana-5024	145	250	3	3	NUM
cana-5024	145	251	:	:	PUNCT
cana-5024	145	252	for	for	ADP
cana-5024	145	253	each	each	DET
cana-5024	145	254	generation	generation	NOUN
cana-5024	145	255	(	(	PUNCT
cana-5024	145	256	e.g.	e.g.	ADV
cana-5024	145	257	,	,	PUNCT
cana-5024	145	258	20	20	NUM
cana-5024	145	259	generations	generation	NOUN
cana-5024	145	260	):	):	PUNCT
cana-5024	145	261	a.	a.	NOUN
cana-5024	145	262	evaluate	evaluate	VERB
cana-5024	145	263	the	the	DET
cana-5024	145	264	fitness	fitness	NOUN
cana-5024	145	265	of	of	ADP
cana-5024	145	266	each	each	DET
cana-5024	145	267	individual	individual	NOUN
cana-5024	145	268	:	:	PUNCT
cana-5024	145	269	train	train	VERB
cana-5024	145	270	cnn	cnn	PROPN
cana-5024	145	271	with	with	ADP
cana-5024	145	272	that	that	DET
cana-5024	145	273	configuration	configuration	NOUN
cana-5024	145	274	on	on	ADP
cana-5024	145	275	a	a	DET
cana-5024	145	276	subset	subset	NOUN
cana-5024	145	277	use	use	NOUN
cana-5024	145	278	validation	validation	NOUN
cana-5024	145	279	accuracy	accuracy	NOUN
cana-5024	145	280	as	as	ADP
cana-5024	145	281	fitness	fitness	NOUN
cana-5024	145	282	(	(	PUNCT
cana-5024	145	283	a	a	X
cana-5024	145	284	)	)	PUNCT
cana-5024	145	285	select	select	ADJ
cana-5024	145	286	parents	parent	NOUN
cana-5024	145	287	using	use	VERB
cana-5024	145	288	tournament	tournament	NOUN
cana-5024	145	289	or	or	CCONJ
cana-5024	145	290	roulette	roulette	NOUN
cana-5024	145	291	selection	selection	NOUN
cana-5024	145	292	,	,	PUNCT
cana-5024	145	293	(	(	PUNCT
cana-5024	145	294	b	b	X
cana-5024	145	295	)	)	PUNCT
cana-5024	145	296	crossover	crossover	NOUN
cana-5024	145	297	to	to	PART
cana-5024	145	298	create	create	VERB
cana-5024	145	299	offspring	offspring	NOUN
cana-5024	145	300	(	(	PUNCT
cana-5024	145	301	c	c	NOUN
cana-5024	145	302	)	)	PUNCT
cana-5024	145	303	apply	apply	VERB
cana-5024	145	304	mutation	mutation	NOUN
cana-5024	145	305	(	(	PUNCT
cana-5024	145	306	d	d	NOUN
cana-5024	145	307	)	)	PUNCT
cana-5024	145	308	replace	replace	VERB
cana-5024	145	309	the	the	DET
cana-5024	145	310	worst	worst	ADV
cana-5024	145	311	-	-	PUNCT
cana-5024	145	312	performing	perform	VERB
cana-5024	145	313	individuals	individual	NOUN
cana-5024	145	314	with	with	ADP
cana-5024	145	315	offspring	offspring	NOUN
cana-5024	145	316	step	step	NOUN
cana-5024	145	317	4	4	NUM
cana-5024	145	318	:	:	PUNCT
cana-5024	145	319	select	select	VERB
cana-5024	145	320	the	the	DET
cana-5024	145	321	individual	individual	NOUN
cana-5024	145	322	with	with	ADP
cana-5024	145	323	the	the	DET
cana-5024	145	324	highest	high	ADJ
cana-5024	145	325	fitness	fitness	NOUN
cana-5024	145	326	as	as	ADP
cana-5024	145	327	the	the	DET
cana-5024	145	328	optimal	optimal	ADJ
cana-5024	145	329	configuration	configuration	NOUN
cana-5024	145	330	step	step	NOUN
cana-5024	145	331	5	5	NUM
cana-5024	145	332	:	:	PUNCT
cana-5024	145	333	train	train	VERB
cana-5024	145	334	the	the	DET
cana-5024	145	335	final	final	ADJ
cana-5024	145	336	cnn	cnn	PROPN
cana-5024	145	337	using	use	VERB
cana-5024	145	338	optimal	optimal	ADJ
cana-5024	145	339	hyperparameters	hyperparameter	NOUN
cana-5024	145	340	on	on	ADP
cana-5024	145	341	the	the	DET
cana-5024	145	342	full	full	ADJ
cana-5024	145	343	dataset	dataset	ADJ
cana-5024	145	344	3.2.3	3.2.3	NUM
cana-5024	145	345	hyperparameter	hyperparameter	NOUN
cana-5024	145	346	tuning	tune	VERB
cana-5024	145	347	with	with	ADP
cana-5024	145	348	bayesian	bayesian	NOUN
cana-5024	145	349	optimization	optimization	NOUN
cana-5024	145	350	input	input	NOUN
cana-5024	145	351	:	:	PUNCT
cana-5024	145	352	cnn	cnn	PROPN
cana-5024	145	353	model	model	NOUN
cana-5024	145	354	,	,	PUNCT
cana-5024	145	355	defined	define	VERB
cana-5024	145	356	hyperparameter	hyperparameter	NOUN
cana-5024	145	357	space	space	NOUN
cana-5024	145	358	output	output	NOUN
cana-5024	145	359	:	:	PUNCT
cana-5024	145	360	optimal	optimal	ADJ
cana-5024	145	361	hyperparameter	hyperparameter	NOUN
cana-5024	145	362	set	set	VERB
cana-5024	145	363	communications	communication	NOUN
cana-5024	145	364	on	on	ADP
cana-5024	145	365	applied	apply	VERB
cana-5024	145	366	nonlinear	nonlinear	ADJ
cana-5024	145	367	analysis	analysis	NOUN
cana-5024	145	368	issn	issn	NOUN
cana-5024	145	369	:	:	PUNCT
cana-5024	145	370	1074	1074	NUM
cana-5024	145	371	-	-	PUNCT
cana-5024	145	372	133x	133x	NUM
cana-5024	145	373	vol	vol	VERB
cana-5024	145	374	32	32	NUM
cana-5024	145	375	no.1s	no.1s	PROPN
cana-5024	145	376	(	(	PUNCT
cana-5024	145	377	2025	2025	NUM
cana-5024	145	378	)	)	PUNCT
cana-5024	145	379	649	649	NUM
cana-5024	145	380	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	145	381	step	step	NOUN
cana-5024	145	382	1	1	NUM
cana-5024	145	383	:	:	PUNCT
cana-5024	145	384	define	define	VERB
cana-5024	145	385	search	search	NOUN
cana-5024	145	386	space	space	NOUN
cana-5024	145	387	for	for	ADP
cana-5024	145	388	hyperparameters	hyperparameter	NOUN
cana-5024	145	389	:	:	PUNCT
cana-5024	145	390	(	(	PUNCT
cana-5024	145	391	a	a	X
cana-5024	145	392	)	)	PUNCT
cana-5024	145	393	learning	learn	VERB
cana-5024	145	394	rate	rate	NOUN
cana-5024	145	395	∈	∈	PROPN
cana-5024	146	1	[	[	X
cana-5024	146	2	0.0001	0.0001	NUM
cana-5024	146	3	,	,	PUNCT
cana-5024	146	4	0.01	0.01	NUM
cana-5024	146	5	]	]	PUNCT
cana-5024	146	6	,	,	PUNCT
cana-5024	146	7	(	(	PUNCT
cana-5024	146	8	b	b	NOUN
cana-5024	146	9	)	)	PUNCT
cana-5024	146	10	dropout	dropout	NOUN
cana-5024	146	11	rate	rate	NOUN
cana-5024	146	12	∈	∈	PROPN
cana-5024	146	13	[	[	X
cana-5024	146	14	0.2	0.2	NUM
cana-5024	146	15	,	,	PUNCT
cana-5024	146	16	0.5	0.5	NUM
cana-5024	146	17	]	]	PUNCT
cana-5024	146	18	,	,	PUNCT
cana-5024	146	19	(	(	PUNCT
cana-5024	146	20	c	c	X
cana-5024	146	21	)	)	PUNCT
cana-5024	146	22	number	number	NOUN
cana-5024	146	23	of	of	ADP
cana-5024	146	24	filters	filter	NOUN
cana-5024	146	25	∈	∈	PROPN
cana-5024	146	26	{	{	PUNCT
cana-5024	146	27	32	32	NUM
cana-5024	146	28	,	,	PUNCT
cana-5024	146	29	64	64	NUM
cana-5024	146	30	,	,	PUNCT
cana-5024	146	31	128	128	NUM
cana-5024	146	32	}	}	PUNCT
cana-5024	146	33	,	,	PUNCT
cana-5024	146	34	(	(	PUNCT
cana-5024	146	35	d	d	X
cana-5024	146	36	)	)	PUNCT
cana-5024	146	37	batch	batch	NOUN
cana-5024	146	38	size	size	NOUN
cana-5024	146	39	∈	∈	PROPN
cana-5024	146	40	{	{	PUNCT
cana-5024	146	41	16	16	NUM
cana-5024	146	42	,	,	PUNCT
cana-5024	146	43	32	32	NUM
cana-5024	146	44	,	,	PUNCT
cana-5024	146	45	64	64	NUM
cana-5024	146	46	}	}	PUNCT
cana-5024	146	47	step	step	NOUN
cana-5024	146	48	2	2	NUM
cana-5024	146	49	:	:	PUNCT
cana-5024	146	50	initialize	initialize	VERB
cana-5024	146	51	surrogate	surrogate	ADJ
cana-5024	146	52	model	model	NOUN
cana-5024	146	53	(	(	PUNCT
cana-5024	146	54	e.g.	e.g.	ADV
cana-5024	146	55	,	,	PUNCT
cana-5024	146	56	gaussian	gaussian	ADJ
cana-5024	146	57	process	process	NOUN
cana-5024	146	58	)	)	PUNCT
cana-5024	146	59	step	step	NOUN
cana-5024	146	60	3	3	NUM
cana-5024	146	61	:	:	PUNCT
cana-5024	146	62	for	for	ADP
cana-5024	146	63	each	each	DET
cana-5024	146	64	iteration	iteration	NOUN
cana-5024	146	65	:	:	PUNCT
cana-5024	146	66	(	(	PUNCT
cana-5024	146	67	a	a	X
cana-5024	146	68	)	)	PUNCT
cana-5024	146	69	use	use	VERB
cana-5024	146	70	the	the	DET
cana-5024	146	71	acquisition	acquisition	NOUN
cana-5024	146	72	function	function	NOUN
cana-5024	146	73	to	to	PART
cana-5024	146	74	select	select	VERB
cana-5024	146	75	the	the	DET
cana-5024	146	76	next	next	ADJ
cana-5024	146	77	set	set	NOUN
cana-5024	146	78	of	of	ADP
cana-5024	146	79	parameters	parameter	NOUN
cana-5024	146	80	(	(	PUNCT
cana-5024	146	81	b	b	NOUN
cana-5024	146	82	)	)	PUNCT
cana-5024	146	83	train	train	NOUN
cana-5024	146	84	cnn	cnn	PROPN
cana-5024	146	85	with	with	ADP
cana-5024	146	86	selected	select	VERB
cana-5024	146	87	hyperparameters	hyperparameter	NOUN
cana-5024	146	88	,	,	PUNCT
cana-5024	146	89	(	(	PUNCT
cana-5024	146	90	c	c	X
cana-5024	146	91	)	)	PUNCT
cana-5024	146	92	evaluate	evaluate	VERB
cana-5024	146	93	validation	validation	NOUN
cana-5024	146	94	performance	performance	NOUN
cana-5024	146	95	(	(	PUNCT
cana-5024	146	96	d	d	NOUN
cana-5024	146	97	)	)	PUNCT
cana-5024	146	98	update	update	NOUN
cana-5024	146	99	the	the	DET
cana-5024	146	100	surrogate	surrogate	ADJ
cana-5024	146	101	model	model	NOUN
cana-5024	146	102	with	with	ADP
cana-5024	146	103	the	the	DET
cana-5024	146	104	new	new	ADJ
cana-5024	146	105	observation	observation	NOUN
cana-5024	146	106	step	step	NOUN
cana-5024	146	107	4	4	NUM
cana-5024	146	108	:	:	PUNCT
cana-5024	146	109	repeat	repeat	VERB
cana-5024	146	110	for	for	ADP
cana-5024	146	111	k	k	PROPN
cana-5024	146	112	iterations	iteration	NOUN
cana-5024	146	113	step	step	VERB
cana-5024	146	114	5	5	NUM
cana-5024	146	115	:	:	PUNCT
cana-5024	146	116	select	select	VERB
cana-5024	146	117	the	the	DET
cana-5024	146	118	hyperparameter	hyperparameter	NOUN
cana-5024	146	119	set	set	VERB
cana-5024	146	120	with	with	ADP
cana-5024	146	121	the	the	DET
cana-5024	146	122	best	good	ADJ
cana-5024	146	123	validation	validation	NOUN
cana-5024	146	124	performance	performance	NOUN
cana-5024	146	125	step	step	NOUN
cana-5024	146	126	6	6	NUM
cana-5024	146	127	:	:	PUNCT
cana-5024	146	128	train	train	VERB
cana-5024	146	129	the	the	DET
cana-5024	146	130	final	final	ADJ
cana-5024	146	131	cnn	cnn	PROPN
cana-5024	146	132	with	with	ADP
cana-5024	146	133	these	these	DET
cana-5024	146	134	parameters	parameter	NOUN
cana-5024	146	135	experimental	experimental	ADJ
cana-5024	146	136	results	result	NOUN
cana-5024	146	137	and	and	CCONJ
cana-5024	146	138	comparisons	comparison	NOUN
cana-5024	146	139	fig	fig	NOUN
cana-5024	146	140	.	.	PUNCT
cana-5024	147	1	4	4	X
cana-5024	147	2	.	.	X
cana-5024	147	3	confusion	confusion	NOUN
cana-5024	147	4	matrix	matrix	NOUN
cana-5024	147	5	based	base	VERB
cana-5024	147	6	on	on	ADP
cana-5024	147	7	the	the	DET
cana-5024	147	8	model	model	NOUN
cana-5024	147	9	performance	performance	NOUN
cana-5024	147	10	fig	fig	NOUN
cana-5024	147	11	.	.	PUNCT
cana-5024	148	1	5	5	X
cana-5024	148	2	.	.	X
cana-5024	148	3	training	training	NOUN
cana-5024	148	4	and	and	CCONJ
cana-5024	148	5	validation	validation	NOUN
cana-5024	148	6	loss	loss	NOUN
cana-5024	148	7	communications	communication	NOUN
cana-5024	148	8	on	on	ADP
cana-5024	148	9	applied	apply	VERB
cana-5024	148	10	nonlinear	nonlinear	ADJ
cana-5024	148	11	analysis	analysis	NOUN
cana-5024	148	12	issn	issn	NOUN
cana-5024	148	13	:	:	PUNCT
cana-5024	148	14	1074	1074	NUM
cana-5024	148	15	-	-	PUNCT
cana-5024	148	16	133x	133x	NUM
cana-5024	148	17	vol	vol	VERB
cana-5024	148	18	32	32	NUM
cana-5024	148	19	no.1s	no.1s	PROPN
cana-5024	148	20	(	(	PUNCT
cana-5024	148	21	2025	2025	NUM
cana-5024	148	22	)	)	PUNCT
cana-5024	148	23	650	650	NUM
cana-5024	148	24	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	148	25	table	table	NOUN
cana-5024	148	26	1	1	NUM
cana-5024	148	27	.	.	PUNCT
cana-5024	149	1	deep	deep	ADJ
cana-5024	149	2	learning	learning	NOUN
cana-5024	149	3	models	model	NOUN
cana-5024	149	4	with	with	ADP
cana-5024	149	5	performance	performance	NOUN
cana-5024	149	6	metrics	metric	NOUN
cana-5024	149	7	model	model	NOUN
cana-5024	149	8	accuracy	accuracy	NOUN
cana-5024	149	9	precision	precision	NOUN
cana-5024	149	10	recall	recall	VERB
cana-5024	149	11	f1	f1	NOUN
cana-5024	149	12	-	-	PUNCT
cana-5024	149	13	score	score	NOUN
cana-5024	149	14	auc	auc	NOUN
cana-5024	149	15	baseline	baseline	PROPN
cana-5024	149	16	cnn	cnn	PROPN
cana-5024	149	17	86.1	86.1	NUM
cana-5024	149	18	%	%	NOUN
cana-5024	149	19	85.6	85.6	NUM
cana-5024	149	20	%	%	NOUN
cana-5024	149	21	83.1	83.1	NUM
cana-5024	149	22	%	%	NOUN
cana-5024	149	23	83.9	83.9	NUM
cana-5024	149	24	%	%	NOUN
cana-5024	149	25	0.901	0.901	NUM
cana-5024	149	26	cnn	cnn	NOUN
cana-5024	149	27	+	+	CCONJ
cana-5024	149	28	genetic	genetic	ADJ
cana-5024	149	29	algorithm	algorithm	NOUN
cana-5024	149	30	90.2	90.2	NUM
cana-5024	149	31	%	%	NOUN
cana-5024	149	32	89.8	89.8	NUM
cana-5024	149	33	%	%	NOUN
cana-5024	149	34	88.8	88.8	NUM
cana-5024	149	35	%	%	NOUN
cana-5024	149	36	89.1	89.1	NUM
cana-5024	149	37	%	%	NOUN
cana-5024	149	38	0.938	0.938	NUM
cana-5024	149	39	cnn	cnn	NOUN
cana-5024	149	40	+	+	CCONJ
cana-5024	149	41	bayesian	bayesian	NOUN
cana-5024	149	42	opt	opt	NOUN
cana-5024	149	43	.	.	PUNCT
cana-5024	150	1	92.7	92.7	NUM
cana-5024	150	2	%	%	NOUN
cana-5024	150	3	92.4	92.4	NUM
cana-5024	150	4	%	%	NOUN
cana-5024	150	5	91.7	91.7	NUM
cana-5024	150	6	%	%	NOUN
cana-5024	150	7	91.5	91.5	NUM
cana-5024	150	8	%	%	NOUN
cana-5024	150	9	0.956	0.956	NUM
cana-5024	150	10	fig	fig	NOUN
cana-5024	150	11	.	.	PUNCT
cana-5024	151	1	6	6	NUM
cana-5024	151	2	.	.	X
cana-5024	151	3	performance	performance	NOUN
cana-5024	151	4	using	use	VERB
cana-5024	151	5	accuracy	accuracy	NOUN
cana-5024	151	6	,	,	PUNCT
cana-5024	151	7	precision	precision	NOUN
cana-5024	151	8	,	,	PUNCT
cana-5024	151	9	recall	recall	NOUN
cana-5024	151	10	,	,	PUNCT
cana-5024	151	11	and	and	CCONJ
cana-5024	151	12	f1	f1	NOUN
cana-5024	151	13	-	-	PUNCT
cana-5024	151	14	score	score	NOUN
cana-5024	151	15	fig	fig	NOUN
cana-5024	151	16	.	.	PUNCT
cana-5024	152	1	7	7	X
cana-5024	152	2	.	.	X
cana-5024	152	3	performance	performance	NOUN
cana-5024	152	4	using	use	VERB
cana-5024	152	5	auc	auc	ADJ
cana-5024	152	6	comparison	comparison	NOUN
cana-5024	152	7	fig	fig	NOUN
cana-5024	152	8	.	.	PUNCT
cana-5024	153	1	8	8	X
cana-5024	153	2	.	.	PUNCT
cana-5024	153	3	performance	performance	NOUN
cana-5024	153	4	using	use	VERB
cana-5024	153	5	roc	roc	PROPN
cana-5024	153	6	comparison	comparison	NOUN
cana-5024	153	7	communications	communication	NOUN
cana-5024	153	8	on	on	ADP
cana-5024	153	9	applied	apply	VERB
cana-5024	153	10	nonlinear	nonlinear	ADJ
cana-5024	153	11	analysis	analysis	NOUN
cana-5024	153	12	issn	issn	NOUN
cana-5024	153	13	:	:	PUNCT
cana-5024	153	14	1074	1074	NUM
cana-5024	153	15	-	-	PUNCT
cana-5024	153	16	133x	133x	NUM
cana-5024	153	17	vol	vol	VERB
cana-5024	153	18	32	32	NUM
cana-5024	153	19	no.1s	no.1s	PROPN
cana-5024	153	20	(	(	PUNCT
cana-5024	153	21	2025	2025	NUM
cana-5024	153	22	)	)	PUNCT
cana-5024	153	23	651	651	NUM
cana-5024	153	24	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	153	25	4	4	NUM
cana-5024	153	26	.	.	NOUN
cana-5024	153	27	results	result	NOUN
cana-5024	153	28	and	and	CCONJ
cana-5024	153	29	discussions	discussion	NOUN
cana-5024	153	30	this	this	DET
cana-5024	153	31	section	section	NOUN
cana-5024	153	32	explains	explain	VERB
cana-5024	153	33	the	the	DET
cana-5024	153	34	results	result	NOUN
cana-5024	153	35	of	of	ADP
cana-5024	153	36	using	use	VERB
cana-5024	153	37	deep	deep	ADJ
cana-5024	153	38	learning	learning	NOUN
cana-5024	153	39	methods	method	NOUN
cana-5024	153	40	combined	combine	VERB
cana-5024	153	41	with	with	ADP
cana-5024	153	42	optimization	optimization	NOUN
cana-5024	153	43	techniques	technique	NOUN
cana-5024	153	44	to	to	PART
cana-5024	153	45	classify	classify	VERB
cana-5024	153	46	skin	skin	NOUN
cana-5024	153	47	cancer	cancer	NOUN
cana-5024	153	48	.	.	PUNCT
cana-5024	154	1	the	the	DET
cana-5024	154	2	model	model	NOUN
cana-5024	154	3	was	be	AUX
cana-5024	154	4	tested	test	VERB
cana-5024	154	5	on	on	ADP
cana-5024	154	6	the	the	DET
cana-5024	154	7	ham10000	ham10000	PROPN
cana-5024	154	8	dataset	dataset	NOUN
cana-5024	154	9	,	,	PUNCT
cana-5024	154	10	and	and	CCONJ
cana-5024	154	11	its	its	PRON
cana-5024	154	12	performance	performance	NOUN
cana-5024	154	13	was	be	AUX
cana-5024	154	14	measured	measure	VERB
cana-5024	154	15	using	using	NOUN
cana-5024	154	16	accuracy	accuracy	NOUN
cana-5024	154	17	,	,	PUNCT
cana-5024	154	18	precision	precision	NOUN
cana-5024	154	19	,	,	PUNCT
cana-5024	154	20	recall	recall	NOUN
cana-5024	154	21	,	,	PUNCT
cana-5024	154	22	f1	f1	NOUN
cana-5024	154	23	-	-	PUNCT
cana-5024	154	24	score	score	NOUN
cana-5024	154	25	,	,	PUNCT
cana-5024	154	26	and	and	CCONJ
cana-5024	154	27	auc	auc	NOUN
cana-5024	154	28	.	.	PUNCT
cana-5024	155	1	table	table	NOUN
cana-5024	155	2	1	1	NUM
cana-5024	155	3	presents	present	VERB
cana-5024	155	4	the	the	DET
cana-5024	155	5	performance	performance	NOUN
cana-5024	155	6	comparison	comparison	NOUN
cana-5024	155	7	of	of	ADP
cana-5024	155	8	three	three	NUM
cana-5024	155	9	models	model	NOUN
cana-5024	155	10	:	:	PUNCT
cana-5024	155	11	the	the	DET
cana-5024	155	12	basic	basic	ADJ
cana-5024	155	13	cnn	cnn	PROPN
cana-5024	155	14	,	,	PUNCT
cana-5024	155	15	cnn	cnn	PROPN
cana-5024	155	16	with	with	ADP
cana-5024	155	17	genetic	genetic	ADJ
cana-5024	155	18	algorithm	algorithm	NOUN
cana-5024	155	19	,	,	PUNCT
cana-5024	155	20	and	and	CCONJ
cana-5024	155	21	cnn	cnn	PROPN
cana-5024	155	22	with	with	ADP
cana-5024	155	23	bayesian	bayesian	NOUN
cana-5024	155	24	optimization	optimization	NOUN
cana-5024	155	25	.	.	PUNCT
cana-5024	156	1	figure	figure	NOUN
cana-5024	156	2	1	1	NUM
cana-5024	156	3	shows	show	VERB
cana-5024	156	4	the	the	DET
cana-5024	156	5	dataset	dataset	NOUN
cana-5024	156	6	with	with	ADP
cana-5024	156	7	different	different	ADJ
cana-5024	156	8	types	type	NOUN
cana-5024	156	9	of	of	ADP
cana-5024	156	10	skin	skin	NOUN
cana-5024	156	11	cancer	cancer	NOUN
cana-5024	156	12	,	,	PUNCT
cana-5024	156	13	while	while	SCONJ
cana-5024	156	14	figure	figure	NOUN
cana-5024	156	15	2	2	NUM
cana-5024	156	16	displays	display	VERB
cana-5024	156	17	sample	sample	NOUN
cana-5024	156	18	images	image	NOUN
cana-5024	156	19	from	from	ADP
cana-5024	156	20	ham10000	ham10000	NOUN
cana-5024	156	21	,	,	PUNCT
cana-5024	156	22	highlighting	highlight	VERB
cana-5024	156	23	the	the	DET
cana-5024	156	24	variety	variety	NOUN
cana-5024	156	25	in	in	ADP
cana-5024	156	26	skin	skin	NOUN
cana-5024	156	27	lesion	lesion	NOUN
cana-5024	156	28	appearances	appearance	NOUN
cana-5024	156	29	.	.	PUNCT
cana-5024	157	1	figure	figure	NOUN
cana-5024	157	2	3	3	NUM
cana-5024	157	3	illustrates	illustrate	VERB
cana-5024	157	4	the	the	DET
cana-5024	157	5	preprocessing	preprocessing	NOUN
cana-5024	157	6	steps	step	NOUN
cana-5024	157	7	like	like	ADP
cana-5024	157	8	normalization	normalization	NOUN
cana-5024	157	9	,	,	PUNCT
cana-5024	157	10	resizing	resizing	NOUN
cana-5024	157	11	,	,	PUNCT
cana-5024	157	12	and	and	CCONJ
cana-5024	157	13	data	datum	NOUN
cana-5024	157	14	augmentation	augmentation	NOUN
cana-5024	157	15	,	,	PUNCT
cana-5024	157	16	which	which	PRON
cana-5024	157	17	help	help	VERB
cana-5024	157	18	improve	improve	VERB
cana-5024	157	19	model	model	NOUN
cana-5024	157	20	training	training	NOUN
cana-5024	157	21	and	and	CCONJ
cana-5024	157	22	reduce	reduce	VERB
cana-5024	157	23	overfitting	overfitting	NOUN
cana-5024	157	24	.	.	PUNCT
cana-5024	158	1	as	as	SCONJ
cana-5024	158	2	shown	show	VERB
cana-5024	158	3	in	in	ADP
cana-5024	158	4	figure	figure	NOUN
cana-5024	158	5	4	4	NUM
cana-5024	158	6	,	,	PUNCT
cana-5024	158	7	the	the	DET
cana-5024	158	8	confusion	confusion	NOUN
cana-5024	158	9	matrix	matrix	NOUN
cana-5024	158	10	for	for	ADP
cana-5024	158	11	the	the	DET
cana-5024	158	12	cnn	cnn	PROPN
cana-5024	158	13	with	with	ADP
cana-5024	158	14	bayesian	bayesian	NOUN
cana-5024	158	15	optimization	optimization	NOUN
cana-5024	158	16	demonstrates	demonstrate	VERB
cana-5024	158	17	strong	strong	ADJ
cana-5024	158	18	performance	performance	NOUN
cana-5024	158	19	,	,	PUNCT
cana-5024	158	20	especially	especially	ADV
cana-5024	158	21	in	in	ADP
cana-5024	158	22	identifying	identify	VERB
cana-5024	158	23	lesions	lesion	NOUN
cana-5024	158	24	like	like	ADP
cana-5024	158	25	nevi	nevi	NOUN
cana-5024	158	26	and	and	CCONJ
cana-5024	158	27	melanomas	melanoma	NOUN
cana-5024	158	28	.	.	PUNCT
cana-5024	159	1	only	only	ADV
cana-5024	159	2	a	a	DET
cana-5024	159	3	few	few	ADJ
cana-5024	159	4	errors	error	NOUN
cana-5024	159	5	occurred	occur	VERB
cana-5024	159	6	,	,	PUNCT
cana-5024	159	7	mostly	mostly	ADV
cana-5024	159	8	between	between	ADP
cana-5024	159	9	similar	similar	ADJ
cana-5024	159	10	-	-	PUNCT
cana-5024	159	11	looking	look	VERB
cana-5024	159	12	types	type	NOUN
cana-5024	159	13	like	like	ADP
cana-5024	159	14	bkl	bkl	NOUN
cana-5024	159	15	and	and	CCONJ
cana-5024	159	16	ak	ak	PROPN
cana-5024	159	17	.	.	PROPN
cana-5024	159	18	figure	figure	NOUN
cana-5024	159	19	5	5	NUM
cana-5024	159	20	displays	display	VERB
cana-5024	159	21	the	the	DET
cana-5024	159	22	training	training	NOUN
cana-5024	159	23	and	and	CCONJ
cana-5024	159	24	validation	validation	NOUN
cana-5024	159	25	loss	loss	NOUN
cana-5024	159	26	curves	curve	NOUN
cana-5024	159	27	.	.	PUNCT
cana-5024	160	1	the	the	DET
cana-5024	160	2	results	result	NOUN
cana-5024	160	3	show	show	VERB
cana-5024	160	4	that	that	SCONJ
cana-5024	160	5	the	the	DET
cana-5024	160	6	models	model	NOUN
cana-5024	160	7	learned	learn	VERB
cana-5024	160	8	well	well	ADV
cana-5024	160	9	over	over	ADP
cana-5024	160	10	time	time	NOUN
cana-5024	160	11	,	,	PUNCT
cana-5024	160	12	with	with	ADP
cana-5024	160	13	the	the	DET
cana-5024	160	14	bayesian	bayesian	NOUN
cana-5024	160	15	-	-	PUNCT
cana-5024	160	16	optimized	optimize	VERB
cana-5024	160	17	model	model	NOUN
cana-5024	160	18	showing	show	VERB
cana-5024	160	19	the	the	DET
cana-5024	160	20	most	most	ADV
cana-5024	160	21	stable	stable	ADJ
cana-5024	160	22	and	and	CCONJ
cana-5024	160	23	smooth	smooth	ADJ
cana-5024	160	24	learning	learning	NOUN
cana-5024	160	25	.	.	PUNCT
cana-5024	161	1	figure	figure	NOUN
cana-5024	161	2	6	6	NUM
cana-5024	161	3	compares	compare	VERB
cana-5024	161	4	the	the	DET
cana-5024	161	5	performance	performance	NOUN
cana-5024	161	6	metrics	metric	NOUN
cana-5024	161	7	of	of	ADP
cana-5024	161	8	all	all	DET
cana-5024	161	9	models	model	NOUN
cana-5024	161	10	.	.	PUNCT
cana-5024	162	1	it	it	PRON
cana-5024	162	2	clearly	clearly	ADV
cana-5024	162	3	shows	show	VERB
cana-5024	162	4	that	that	SCONJ
cana-5024	162	5	adding	add	VERB
cana-5024	162	6	optimization	optimization	NOUN
cana-5024	162	7	techniques	technique	NOUN
cana-5024	162	8	improved	improve	VERB
cana-5024	162	9	results	result	NOUN
cana-5024	162	10	,	,	PUNCT
cana-5024	162	11	with	with	ADP
cana-5024	162	12	the	the	DET
cana-5024	162	13	bayesian	bayesian	NOUN
cana-5024	162	14	approach	approach	NOUN
cana-5024	162	15	performing	perform	VERB
cana-5024	162	16	best	well	ADV
cana-5024	162	17	in	in	ADP
cana-5024	162	18	all	all	DET
cana-5024	162	19	categories	category	NOUN
cana-5024	162	20	.	.	PUNCT
cana-5024	163	1	figure	figure	VERB
cana-5024	163	2	7	7	NUM
cana-5024	163	3	shows	show	VERB
cana-5024	163	4	auc	auc	NOUN
cana-5024	163	5	scores	score	NOUN
cana-5024	163	6	for	for	ADP
cana-5024	163	7	each	each	DET
cana-5024	163	8	model	model	NOUN
cana-5024	163	9	.	.	PUNCT
cana-5024	164	1	the	the	DET
cana-5024	164	2	cnn	cnn	PROPN
cana-5024	164	3	with	with	ADP
cana-5024	164	4	bayesian	bayesian	NOUN
cana-5024	164	5	optimization	optimization	NOUN
cana-5024	164	6	scored	score	VERB
cana-5024	164	7	the	the	DET
cana-5024	164	8	highest	high	ADJ
cana-5024	164	9	auc	auc	NOUN
cana-5024	164	10	of	of	ADP
cana-5024	164	11	0.956	0.956	NUM
cana-5024	164	12	,	,	PUNCT
cana-5024	164	13	meaning	mean	VERB
cana-5024	164	14	it	it	PRON
cana-5024	164	15	was	be	AUX
cana-5024	164	16	most	most	ADV
cana-5024	164	17	accurate	accurate	ADJ
cana-5024	164	18	in	in	ADP
cana-5024	164	19	distinguishing	distinguish	VERB
cana-5024	164	20	between	between	ADP
cana-5024	164	21	skin	skin	NOUN
cana-5024	164	22	lesion	lesion	NOUN
cana-5024	164	23	types	type	NOUN
cana-5024	164	24	.	.	PUNCT
cana-5024	165	1	finally	finally	ADV
cana-5024	165	2	,	,	PUNCT
cana-5024	165	3	figure	figure	VERB
cana-5024	165	4	8	8	NUM
cana-5024	165	5	presents	present	VERB
cana-5024	165	6	the	the	DET
cana-5024	165	7	roc	roc	PROPN
cana-5024	165	8	curves	curve	NOUN
cana-5024	165	9	for	for	ADP
cana-5024	165	10	all	all	DET
cana-5024	165	11	seven	seven	NUM
cana-5024	165	12	classes	class	NOUN
cana-5024	165	13	,	,	PUNCT
cana-5024	165	14	showing	show	VERB
cana-5024	165	15	that	that	SCONJ
cana-5024	165	16	the	the	DET
cana-5024	165	17	model	model	NOUN
cana-5024	165	18	maintained	maintain	VERB
cana-5024	165	19	high	high	ADJ
cana-5024	165	20	sensitivity	sensitivity	NOUN
cana-5024	165	21	and	and	CCONJ
cana-5024	165	22	specificity	specificity	NOUN
cana-5024	165	23	.	.	PUNCT
cana-5024	166	1	all	all	DET
cana-5024	166	2	auc	auc	ADJ
cana-5024	166	3	values	value	NOUN
cana-5024	166	4	were	be	AUX
cana-5024	166	5	above	above	ADP
cana-5024	166	6	0.90	0.90	NUM
cana-5024	166	7	,	,	PUNCT
cana-5024	166	8	confirming	confirm	VERB
cana-5024	166	9	the	the	DET
cana-5024	166	10	system	system	NOUN
cana-5024	166	11	's	's	PART
cana-5024	166	12	strong	strong	ADJ
cana-5024	166	13	classification	classification	NOUN
cana-5024	166	14	ability	ability	NOUN
cana-5024	166	15	.	.	PUNCT
cana-5024	167	1	5	5	X
cana-5024	167	2	.	.	X
cana-5024	167	3	conclusion	conclusion	NOUN
cana-5024	167	4	in	in	ADP
cana-5024	167	5	this	this	DET
cana-5024	167	6	work	work	NOUN
cana-5024	167	7	,	,	PUNCT
cana-5024	167	8	we	we	PRON
cana-5024	167	9	created	create	VERB
cana-5024	167	10	and	and	CCONJ
cana-5024	167	11	tested	test	VERB
cana-5024	167	12	a	a	DET
cana-5024	167	13	deep	deep	ADJ
cana-5024	167	14	learning	learning	NOUN
cana-5024	167	15	model	model	NOUN
cana-5024	167	16	combined	combine	VERB
cana-5024	167	17	with	with	ADP
cana-5024	167	18	optimization	optimization	NOUN
cana-5024	167	19	methods	method	NOUN
cana-5024	167	20	to	to	PART
cana-5024	167	21	detect	detect	VERB
cana-5024	167	22	skin	skin	NOUN
cana-5024	167	23	cancer	cancer	NOUN
cana-5024	167	24	from	from	ADP
cana-5024	167	25	dermatoscopic	dermatoscopic	ADJ
cana-5024	167	26	images	image	NOUN
cana-5024	167	27	.	.	PUNCT
cana-5024	168	1	we	we	PRON
cana-5024	168	2	used	use	VERB
cana-5024	168	3	the	the	DET
cana-5024	168	4	ham10000	ham10000	PROPN
cana-5024	168	5	dataset	dataset	NOUN
cana-5024	168	6	to	to	PART
cana-5024	168	7	compare	compare	VERB
cana-5024	168	8	a	a	DET
cana-5024	168	9	basic	basic	ADJ
cana-5024	168	10	cnn	cnn	NOUN
cana-5024	168	11	with	with	ADP
cana-5024	168	12	two	two	NUM
cana-5024	168	13	improved	improved	ADJ
cana-5024	168	14	versions	version	NOUN
cana-5024	168	15	—	—	PUNCT
cana-5024	168	16	one	one	NUM
cana-5024	168	17	using	use	VERB
cana-5024	168	18	a	a	DET
cana-5024	168	19	genetic	genetic	ADJ
cana-5024	168	20	algorithm	algorithm	NOUN
cana-5024	168	21	and	and	CCONJ
cana-5024	168	22	the	the	DET
cana-5024	168	23	other	other	ADJ
cana-5024	168	24	using	use	VERB
cana-5024	168	25	bayesian	bayesian	NOUN
cana-5024	168	26	optimization	optimization	NOUN
cana-5024	168	27	.	.	PUNCT
cana-5024	169	1	the	the	DET
cana-5024	169	2	results	result	NOUN
cana-5024	169	3	showed	show	VERB
cana-5024	169	4	that	that	SCONJ
cana-5024	169	5	adding	add	VERB
cana-5024	169	6	optimization	optimization	NOUN
cana-5024	169	7	techniques	technique	NOUN
cana-5024	169	8	greatly	greatly	ADV
cana-5024	169	9	improved	improve	VERB
cana-5024	169	10	the	the	DET
cana-5024	169	11	model	model	NOUN
cana-5024	169	12	’s	’s	PART
cana-5024	169	13	performance	performance	NOUN
cana-5024	169	14	.	.	PUNCT
cana-5024	170	1	the	the	DET
cana-5024	170	2	cnn	cnn	PROPN
cana-5024	170	3	with	with	ADP
cana-5024	170	4	bayesian	bayesian	NOUN
cana-5024	170	5	optimization	optimization	NOUN
cana-5024	170	6	performed	perform	VERB
cana-5024	170	7	the	the	DET
cana-5024	170	8	best	good	ADJ
cana-5024	170	9	,	,	PUNCT
cana-5024	170	10	reaching	reach	VERB
cana-5024	170	11	an	an	DET
cana-5024	170	12	accuracy	accuracy	NOUN
cana-5024	170	13	of	of	ADP
cana-5024	170	14	92.7	92.7	NUM
cana-5024	170	15	%	%	NOUN
cana-5024	170	16	,	,	PUNCT
cana-5024	170	17	precision	precision	NOUN
cana-5024	170	18	of	of	ADP
cana-5024	170	19	92.4	92.4	NUM
cana-5024	170	20	%	%	NOUN
cana-5024	170	21	,	,	PUNCT
cana-5024	170	22	recall	recall	NOUN
cana-5024	170	23	of	of	ADP
cana-5024	170	24	91.7	91.7	NUM
cana-5024	170	25	%	%	NOUN
cana-5024	170	26	,	,	PUNCT
cana-5024	170	27	f1	f1	NOUN
cana-5024	170	28	-	-	PUNCT
cana-5024	170	29	score	score	NOUN
cana-5024	170	30	of	of	ADP
cana-5024	170	31	91.5	91.5	NUM
cana-5024	170	32	%	%	NOUN
cana-5024	170	33	,	,	PUNCT
cana-5024	170	34	and	and	CCONJ
cana-5024	170	35	an	an	DET
cana-5024	170	36	auc	auc	NOUN
cana-5024	170	37	of	of	ADP
cana-5024	170	38	0.956	0.956	NUM
cana-5024	170	39	.	.	PUNCT
cana-5024	171	1	further	further	ADJ
cana-5024	171	2	analysis	analysis	NOUN
cana-5024	171	3	using	use	VERB
cana-5024	171	4	confusion	confusion	NOUN
cana-5024	171	5	matrices	matrix	NOUN
cana-5024	171	6	and	and	CCONJ
cana-5024	171	7	roc	roc	PROPN
cana-5024	171	8	curves	curve	NOUN
cana-5024	171	9	confirmed	confirm	VERB
cana-5024	171	10	the	the	DET
cana-5024	171	11	model	model	NOUN
cana-5024	171	12	’s	’s	PART
cana-5024	171	13	strong	strong	ADJ
cana-5024	171	14	ability	ability	NOUN
cana-5024	171	15	to	to	PART
cana-5024	171	16	correctly	correctly	ADV
cana-5024	171	17	classify	classify	VERB
cana-5024	171	18	different	different	ADJ
cana-5024	171	19	types	type	NOUN
cana-5024	171	20	of	of	ADP
cana-5024	171	21	skin	skin	NOUN
cana-5024	171	22	lesions	lesion	NOUN
cana-5024	171	23	.	.	PUNCT
cana-5024	172	1	the	the	DET
cana-5024	172	2	training	training	NOUN
cana-5024	172	3	and	and	CCONJ
cana-5024	172	4	validation	validation	NOUN
cana-5024	172	5	loss	loss	NOUN
cana-5024	172	6	graphs	graph	NOUN
cana-5024	172	7	also	also	ADV
cana-5024	172	8	showed	show	VERB
cana-5024	172	9	that	that	SCONJ
cana-5024	172	10	the	the	DET
cana-5024	172	11	model	model	NOUN
cana-5024	172	12	learned	learn	VERB
cana-5024	172	13	effectively	effectively	ADV
cana-5024	172	14	with	with	ADP
cana-5024	172	15	little	little	ADJ
cana-5024	172	16	overfitting	overfitting	NOUN
cana-5024	172	17	.	.	PUNCT
cana-5024	173	1	in	in	ADP
cana-5024	173	2	conclusion	conclusion	NOUN
cana-5024	173	3	,	,	PUNCT
cana-5024	173	4	combining	combine	VERB
cana-5024	173	5	deep	deep	ADJ
cana-5024	173	6	learning	learning	NOUN
cana-5024	173	7	with	with	ADP
cana-5024	173	8	optimization	optimization	NOUN
cana-5024	173	9	—	—	PUNCT
cana-5024	173	10	especially	especially	ADV
cana-5024	173	11	bayesian	bayesian	ADJ
cana-5024	173	12	optimization	optimization	NOUN
cana-5024	173	13	—	—	PUNCT
cana-5024	173	14	can	can	AUX
cana-5024	173	15	significantly	significantly	ADV
cana-5024	173	16	boost	boost	VERB
cana-5024	173	17	performance	performance	NOUN
cana-5024	173	18	in	in	ADP
cana-5024	173	19	skin	skin	NOUN
cana-5024	173	20	cancer	cancer	NOUN
cana-5024	173	21	detection	detection	NOUN
cana-5024	173	22	.	.	PUNCT
cana-5024	174	1	this	this	DET
cana-5024	174	2	approach	approach	NOUN
cana-5024	174	3	can	can	AUX
cana-5024	174	4	help	help	VERB
cana-5024	174	5	dermatologists	dermatologist	NOUN
cana-5024	174	6	make	make	VERB
cana-5024	174	7	quicker	quick	ADV
cana-5024	174	8	and	and	CCONJ
cana-5024	174	9	more	more	ADV
cana-5024	174	10	reliable	reliable	ADJ
cana-5024	174	11	diagnoses	diagnosis	NOUN
cana-5024	174	12	.	.	PUNCT
cana-5024	175	1	further	further	ADJ
cana-5024	175	2	studies	study	NOUN
cana-5024	175	3	although	although	SCONJ
cana-5024	175	4	this	this	DET
cana-5024	175	5	study	study	NOUN
cana-5024	175	6	showed	show	VERB
cana-5024	175	7	that	that	SCONJ
cana-5024	175	8	combining	combine	VERB
cana-5024	175	9	deep	deep	ADJ
cana-5024	175	10	learning	learning	NOUN
cana-5024	175	11	with	with	ADP
cana-5024	175	12	optimization	optimization	NOUN
cana-5024	175	13	improves	improve	VERB
cana-5024	175	14	skin	skin	NOUN
cana-5024	175	15	cancer	cancer	NOUN
cana-5024	175	16	detection	detection	NOUN
cana-5024	175	17	,	,	PUNCT
cana-5024	175	18	there	there	PRON
cana-5024	175	19	’s	’	VERB
cana-5024	175	20	room	room	NOUN
cana-5024	175	21	for	for	ADP
cana-5024	175	22	further	further	ADJ
cana-5024	175	23	improvement	improvement	NOUN
cana-5024	175	24	.	.	PUNCT
cana-5024	176	1	future	future	ADJ
cana-5024	176	2	research	research	NOUN
cana-5024	176	3	could	could	AUX
cana-5024	176	4	include	include	VERB
cana-5024	176	5	clinical	clinical	ADJ
cana-5024	176	6	details	detail	NOUN
cana-5024	176	7	like	like	ADP
cana-5024	176	8	age	age	NOUN
cana-5024	176	9	,	,	PUNCT
cana-5024	176	10	gender	gender	NOUN
cana-5024	176	11	,	,	PUNCT
cana-5024	176	12	and	and	CCONJ
cana-5024	176	13	lesion	lesion	NOUN
cana-5024	176	14	location	location	NOUN
cana-5024	176	15	along	along	ADP
cana-5024	176	16	with	with	ADP
cana-5024	176	17	images	image	NOUN
cana-5024	176	18	to	to	PART
cana-5024	176	19	boost	boost	VERB
cana-5024	176	20	accuracy	accuracy	NOUN
cana-5024	176	21	.	.	PUNCT
cana-5024	177	1	using	use	VERB
cana-5024	177	2	more	more	ADV
cana-5024	177	3	diverse	diverse	ADJ
cana-5024	177	4	and	and	CCONJ
cana-5024	177	5	larger	large	ADJ
cana-5024	177	6	datasets	dataset	NOUN
cana-5024	177	7	,	,	PUNCT
cana-5024	177	8	especially	especially	ADV
cana-5024	177	9	those	those	PRON
cana-5024	177	10	representing	represent	VERB
cana-5024	177	11	different	different	ADJ
cana-5024	177	12	skin	skin	NOUN
cana-5024	177	13	tones	tone	NOUN
cana-5024	177	14	and	and	CCONJ
cana-5024	177	15	rare	rare	ADJ
cana-5024	177	16	conditions	condition	NOUN
cana-5024	177	17	,	,	PUNCT
cana-5024	177	18	would	would	AUX
cana-5024	177	19	make	make	VERB
cana-5024	177	20	the	the	DET
cana-5024	177	21	model	model	NOUN
cana-5024	177	22	more	more	ADV
cana-5024	177	23	reliable	reliable	ADJ
cana-5024	177	24	.	.	PUNCT
cana-5024	178	1	adding	add	VERB
cana-5024	178	2	explanation	explanation	NOUN
cana-5024	178	3	tools	tool	NOUN
cana-5024	178	4	like	like	ADP
cana-5024	178	5	grad	grad	NOUN
cana-5024	178	6	-	-	PUNCT
cana-5024	178	7	cam	cam	PROPN
cana-5024	178	8	,	,	PUNCT
cana-5024	178	9	shap	shap	NOUN
cana-5024	178	10	,	,	PUNCT
cana-5024	178	11	or	or	CCONJ
cana-5024	178	12	lime	lime	NOUN
cana-5024	178	13	can	can	AUX
cana-5024	178	14	help	help	VERB
cana-5024	178	15	doctors	doctor	NOUN
cana-5024	178	16	better	well	ADV
cana-5024	178	17	understand	understand	VERB
cana-5024	178	18	the	the	DET
cana-5024	178	19	model	model	NOUN
cana-5024	178	20	’s	’s	PART
cana-5024	178	21	decisions	decision	NOUN
cana-5024	178	22	.	.	PUNCT
cana-5024	179	1	also	also	ADV
cana-5024	179	2	,	,	PUNCT
cana-5024	179	3	making	make	VERB
cana-5024	179	4	the	the	DET
cana-5024	179	5	model	model	NOUN
cana-5024	179	6	work	work	NOUN
cana-5024	179	7	on	on	ADP
cana-5024	179	8	mobile	mobile	ADJ
cana-5024	179	9	or	or	CCONJ
cana-5024	179	10	edge	edge	NOUN
cana-5024	179	11	devices	device	NOUN
cana-5024	179	12	could	could	AUX
cana-5024	179	13	help	help	VERB
cana-5024	179	14	communications	communication	NOUN
cana-5024	179	15	on	on	ADP
cana-5024	179	16	applied	apply	VERB
cana-5024	179	17	nonlinear	nonlinear	ADJ
cana-5024	179	18	analysis	analysis	NOUN
cana-5024	179	19	issn	issn	NOUN
cana-5024	179	20	:	:	PUNCT
cana-5024	179	21	1074	1074	NUM
cana-5024	179	22	-	-	PUNCT
cana-5024	179	23	133x	133x	NUM
cana-5024	179	24	vol	vol	VERB
cana-5024	179	25	32	32	NUM
cana-5024	179	26	no.1s	no.1s	PROPN
cana-5024	179	27	(	(	PUNCT
cana-5024	179	28	2025	2025	NUM
cana-5024	179	29	)	)	PUNCT
cana-5024	179	30	652	652	NUM
cana-5024	179	31	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	179	32	bring	bring	VERB
cana-5024	179	33	skin	skin	NOUN
cana-5024	179	34	cancer	cancer	NOUN
cana-5024	179	35	screening	screen	VERB
cana-5024	179	36	to	to	ADP
cana-5024	179	37	remote	remote	ADJ
cana-5024	179	38	areas	area	NOUN
cana-5024	179	39	.	.	PUNCT
cana-5024	180	1	future	future	ADJ
cana-5024	180	2	versions	version	NOUN
cana-5024	180	3	could	could	AUX
cana-5024	180	4	also	also	ADV
cana-5024	180	5	detect	detect	VERB
cana-5024	180	6	other	other	ADJ
cana-5024	180	7	skin	skin	NOUN
cana-5024	180	8	issues	issue	NOUN
cana-5024	180	9	like	like	ADP
cana-5024	180	10	eczema	eczema	NOUN
cana-5024	180	11	or	or	CCONJ
cana-5024	180	12	infections	infection	NOUN
cana-5024	180	13	.	.	PUNCT
cana-5024	181	1	finally	finally	ADV
cana-5024	181	2	,	,	PUNCT
cana-5024	181	3	testing	test	VERB
cana-5024	181	4	the	the	DET
cana-5024	181	5	model	model	NOUN
cana-5024	181	6	in	in	ADP
cana-5024	181	7	real	real	ADJ
cana-5024	181	8	clinical	clinical	ADJ
cana-5024	181	9	environments	environment	NOUN
cana-5024	181	10	and	and	CCONJ
cana-5024	181	11	working	work	VERB
cana-5024	181	12	closely	closely	ADV
cana-5024	181	13	with	with	ADP
cana-5024	181	14	dermatologists	dermatologist	NOUN
cana-5024	181	15	will	will	AUX
cana-5024	181	16	be	be	AUX
cana-5024	181	17	key	key	ADJ
cana-5024	181	18	to	to	ADP
cana-5024	181	19	making	make	VERB
cana-5024	181	20	it	it	PRON
cana-5024	181	21	useful	useful	ADJ
cana-5024	181	22	in	in	ADP
cana-5024	181	23	real	real	ADJ
cana-5024	181	24	-	-	PUNCT
cana-5024	181	25	world	world	NOUN
cana-5024	181	26	practice	practice	NOUN
cana-5024	181	27	.	.	PUNCT
cana-5024	182	1	these	these	DET
cana-5024	182	2	steps	step	NOUN
cana-5024	182	3	can	can	AUX
cana-5024	182	4	help	help	VERB
cana-5024	182	5	turn	turn	VERB
cana-5024	182	6	this	this	DET
cana-5024	182	7	research	research	NOUN
cana-5024	182	8	into	into	ADP
cana-5024	182	9	a	a	DET
cana-5024	182	10	powerful	powerful	ADJ
cana-5024	182	11	tool	tool	NOUN
cana-5024	182	12	for	for	ADP
cana-5024	182	13	diagnosing	diagnose	VERB
cana-5024	182	14	various	various	ADJ
cana-5024	182	15	skin	skin	NOUN
cana-5024	182	16	diseases	disease	NOUN
cana-5024	182	17	.	.	PUNCT
cana-5024	183	1	6	6	X
cana-5024	183	2	.	.	NUM
cana-5024	183	3	references	reference	NOUN
cana-5024	183	4	[	[	X
cana-5024	183	5	1	1	NUM
cana-5024	183	6	]	]	X
cana-5024	183	7	abbas	abbas	PROPN
cana-5024	183	8	,	,	PUNCT
cana-5024	183	9	q.	q.	NOUN
cana-5024	183	10	,	,	PUNCT
cana-5024	183	11	celebi	celebi	NOUN
cana-5024	183	12	,	,	PUNCT
cana-5024	183	13	m.	m.	NOUN
cana-5024	183	14	e.	e.	PROPN
cana-5024	183	15	,	,	PUNCT
cana-5024	183	16	and	and	CCONJ
cana-5024	183	17	garcia	garcia	PROPN
cana-5024	183	18	,	,	PUNCT
cana-5024	183	19	m.	m.	NOUN
cana-5024	183	20	,	,	PUNCT
cana-5024	183	21	"	"	PUNCT
cana-5024	183	22	deep	deep	ADJ
cana-5024	183	23	belief	belief	NOUN
cana-5024	183	24	networks	network	NOUN
cana-5024	183	25	with	with	ADP
cana-5024	183	26	cnns	cnn	NOUN
cana-5024	183	27	for	for	ADP
cana-5024	183	28	dermoscopic	dermoscopic	ADJ
cana-5024	183	29	image	image	NOUN
cana-5024	183	30	analysis	analysis	NOUN
cana-5024	183	31	,	,	PUNCT
cana-5024	183	32	"	"	PUNCT
cana-5024	183	33	comput	comput	NOUN
cana-5024	183	34	.	.	PUNCT
cana-5024	184	1	methods	method	NOUN
cana-5024	184	2	programs	program	NOUN
cana-5024	184	3	biomed	biome	VERB
cana-5024	184	4	.	.	PUNCT
cana-5024	185	1	,	,	PUNCT
cana-5024	185	2	vol	vol	NOUN
cana-5024	185	3	.	.	PROPN
cana-5024	185	4	180	180	NUM
cana-5024	185	5	,	,	PUNCT
cana-5024	186	1	p.	p.	NOUN
cana-5024	186	2	105027	105027	NUM
cana-5024	186	3	,	,	PUNCT
cana-5024	186	4	2019	2019	NUM
cana-5024	186	5	.	.	PUNCT
cana-5024	187	1	[	[	X
cana-5024	187	2	2	2	NUM
cana-5024	187	3	]	]	X
cana-5024	187	4	ali	ali	PROPN
cana-5024	187	5	,	,	PUNCT
cana-5024	187	6	l.	l.	PROPN
cana-5024	187	7	,	,	PUNCT
cana-5024	187	8	javed	javed	PROPN
cana-5024	187	9	,	,	PUNCT
cana-5024	187	10	a.	a.	NOUN
cana-5024	187	11	m.	m.	NOUN
cana-5024	187	12	,	,	PUNCT
cana-5024	187	13	rauf	rauf	PROPN
cana-5024	187	14	,	,	PUNCT
cana-5024	187	15	a.	a.	PROPN
cana-5024	187	16	,	,	PUNCT
cana-5024	187	17	and	and	CCONJ
cana-5024	187	18	khan	khan	PROPN
cana-5024	187	19	,	,	PUNCT
cana-5024	187	20	m.	m.	NOUN
cana-5024	187	21	a.	a.	NOUN
cana-5024	187	22	,	,	PUNCT
cana-5024	187	23	"	"	PUNCT
cana-5024	187	24	skin	skin	NOUN
cana-5024	187	25	cancer	cancer	NOUN
cana-5024	187	26	detection	detection	NOUN
cana-5024	187	27	using	use	VERB
cana-5024	187	28	deep	deep	ADJ
cana-5024	187	29	learning	learning	NOUN
cana-5024	187	30	and	and	CCONJ
cana-5024	187	31	svm	svm	ADJ
cana-5024	187	32	,	,	PUNCT
cana-5024	187	33	"	"	PUNCT
cana-5024	187	34	comput	comput	NOUN
cana-5024	187	35	.	.	PUNCT
cana-5024	188	1	mater	mater	NOUN
cana-5024	188	2	.	.	PUNCT
cana-5024	189	1	contin	contin	AUX
cana-5024	189	2	.	.	PUNCT
cana-5024	190	1	,	,	PUNCT
cana-5024	190	2	vol	vol	NOUN
cana-5024	190	3	.	.	PROPN
cana-5024	191	1	66	66	NUM
cana-5024	191	2	,	,	PUNCT
cana-5024	191	3	no	no	INTJ
cana-5024	191	4	.	.	NOUN
cana-5024	191	5	2	2	NUM
cana-5024	191	6	,	,	PUNCT
cana-5024	191	7	pp	pp	ADJ
cana-5024	191	8	.	.	PUNCT
cana-5024	192	1	1299–1315	1299–1315	NUM
cana-5024	192	2	,	,	PUNCT
cana-5024	192	3	2021	2021	NUM
cana-5024	192	4	.	.	PUNCT
cana-5024	193	1	[	[	X
cana-5024	193	2	3	3	NUM
cana-5024	193	3	]	]	X
cana-5024	193	4	almansour	almansour	ADJ
cana-5024	193	5	,	,	PUNCT
cana-5024	193	6	n.	n.	PROPN
cana-5024	193	7	,	,	PUNCT
cana-5024	193	8	al	al	PROPN
cana-5024	193	9	-	-	PUNCT
cana-5024	193	10	mutairi	mutairi	PROPN
cana-5024	193	11	,	,	PUNCT
cana-5024	193	12	n.	n.	PROPN
cana-5024	193	13	,	,	PUNCT
cana-5024	193	14	alrashed	alrashe	VERB
cana-5024	193	15	,	,	PUNCT
cana-5024	193	16	s.	s.	PROPN
cana-5024	193	17	,	,	PUNCT
cana-5024	193	18	and	and	CCONJ
cana-5024	193	19	almotiri	almotiri	ADV
cana-5024	193	20	,	,	PUNCT
cana-5024	193	21	s.	s.	PROPN
cana-5024	193	22	,	,	PUNCT
cana-5024	193	23	"	"	PUNCT
cana-5024	193	24	explainable	explainable	ADJ
cana-5024	193	25	ai	ai	VERB
cana-5024	193	26	in	in	ADP
cana-5024	193	27	dermatology	dermatology	NOUN
cana-5024	193	28	:	:	PUNCT
cana-5024	193	29	interpreting	interpret	VERB
cana-5024	193	30	deep	deep	ADJ
cana-5024	193	31	learning	learning	NOUN
cana-5024	193	32	predictions	prediction	NOUN
cana-5024	193	33	in	in	ADP
cana-5024	193	34	skin	skin	NOUN
cana-5024	193	35	cancer	cancer	NOUN
cana-5024	193	36	diagnosis	diagnosis	NOUN
cana-5024	193	37	,	,	PUNCT
cana-5024	193	38	"	"	PUNCT
cana-5024	193	39	diagnostics	diagnostic	NOUN
cana-5024	193	40	,	,	PUNCT
cana-5024	193	41	vol	vol	NOUN
cana-5024	193	42	.	.	PROPN
cana-5024	193	43	11	11	NUM
cana-5024	193	44	,	,	PUNCT
cana-5024	193	45	no	no	INTJ
cana-5024	193	46	.	.	NOUN
cana-5024	193	47	8	8	NUM
cana-5024	193	48	,	,	PUNCT
cana-5024	193	49	p.	p.	NOUN
cana-5024	193	50	1343	1343	NUM
cana-5024	193	51	,	,	PUNCT
cana-5024	193	52	2021	2021	NUM
cana-5024	193	53	.	.	PUNCT
cana-5024	194	1	[	[	X
cana-5024	194	2	4	4	NUM
cana-5024	194	3	]	]	X
cana-5024	194	4	al	al	PROPN
cana-5024	194	5	-	-	PUNCT
cana-5024	194	6	waisy	waisy	ADJ
cana-5024	194	7	,	,	PUNCT
cana-5024	194	8	a.	a.	PROPN
cana-5024	194	9	s.	s.	PROPN
cana-5024	194	10	,	,	PUNCT
cana-5024	194	11	al	al	PROPN
cana-5024	194	12	-	-	PUNCT
cana-5024	194	13	fahdawi	fahdawi	PROPN
cana-5024	194	14	,	,	PUNCT
cana-5024	194	15	s.	s.	PROPN
cana-5024	194	16	,	,	PUNCT
cana-5024	194	17	mohammed	mohammed	PROPN
cana-5024	194	18	,	,	PUNCT
cana-5024	194	19	m.	m.	NOUN
cana-5024	194	20	a.	a.	PROPN
cana-5024	194	21	,	,	PUNCT
cana-5024	194	22	damaševičius	damaševičius	PROPN
cana-5024	194	23	,	,	PUNCT
cana-5024	194	24	r.	r.	PROPN
cana-5024	194	25	,	,	PUNCT
cana-5024	194	26	abdulkareem	abdulkareem	PROPN
cana-5024	194	27	,	,	PUNCT
cana-5024	194	28	k.	k.	PROPN
cana-5024	194	29	h.	h.	PROPN
cana-5024	194	30	,	,	PUNCT
cana-5024	194	31	and	and	CCONJ
cana-5024	194	32	ibrahim	ibrahim	PROPN
cana-5024	194	33	,	,	PUNCT
cana-5024	194	34	d.	d.	PROPN
cana-5024	194	35	a.	a.	PROPN
cana-5024	194	36	,	,	PUNCT
cana-5024	194	37	"	"	PUNCT
cana-5024	194	38	a	a	DET
cana-5024	194	39	multi	multi	ADJ
cana-5024	194	40	-	-	ADJ
cana-5024	194	41	domain	domain	ADJ
cana-5024	194	42	hybrid	hybrid	NOUN
cana-5024	194	43	model	model	NOUN
cana-5024	194	44	for	for	ADP
cana-5024	194	45	skin	skin	NOUN
cana-5024	194	46	lesion	lesion	NOUN
cana-5024	194	47	classification	classification	NOUN
cana-5024	194	48	using	use	VERB
cana-5024	194	49	deep	deep	ADJ
cana-5024	194	50	learning	learning	NOUN
cana-5024	194	51	and	and	CCONJ
cana-5024	194	52	optimization	optimization	NOUN
cana-5024	194	53	techniques	technique	NOUN
cana-5024	194	54	,	,	PUNCT
cana-5024	194	55	"	"	PUNCT
cana-5024	194	56	comput	comput	NOUN
cana-5024	194	57	.	.	PUNCT
cana-5024	195	1	biol	biol	PROPN
cana-5024	195	2	.	.	PUNCT
cana-5024	196	1	med	med	PROPN
cana-5024	196	2	.	.	PROPN
cana-5024	196	3	,	,	PUNCT
cana-5024	196	4	vol	vol	NOUN
cana-5024	196	5	.	.	PROPN
cana-5024	197	1	133	133	NUM
cana-5024	197	2	,	,	PUNCT
cana-5024	197	3	p.	p.	NOUN
cana-5024	197	4	104365	104365	NUM
cana-5024	197	5	,	,	PUNCT
cana-5024	197	6	2021	2021	NUM
cana-5024	197	7	.	.	PUNCT
cana-5024	198	1	[	[	X
cana-5024	198	2	5	5	NUM
cana-5024	198	3	]	]	PUNCT
cana-5024	198	4	bi	bi	NOUN
cana-5024	198	5	,	,	PUNCT
cana-5024	198	6	l.	l.	PROPN
cana-5024	198	7	,	,	PUNCT
cana-5024	198	8	kim	kim	PROPN
cana-5024	198	9	,	,	PUNCT
cana-5024	198	10	j.	j.	PROPN
cana-5024	198	11	,	,	PUNCT
cana-5024	198	12	ahn	ahn	PROPN
cana-5024	198	13	,	,	PUNCT
cana-5024	198	14	e.	e.	PROPN
cana-5024	198	15	,	,	PUNCT
cana-5024	198	16	kumar	kumar	PROPN
cana-5024	198	17	,	,	PUNCT
cana-5024	198	18	a.	a.	PROPN
cana-5024	198	19	,	,	PUNCT
cana-5024	198	20	feng	feng	PROPN
cana-5024	198	21	,	,	PUNCT
cana-5024	198	22	d.	d.	PROPN
cana-5024	198	23	,	,	PUNCT
cana-5024	198	24	and	and	CCONJ
cana-5024	198	25	fulham	fulham	PROPN
cana-5024	198	26	,	,	PUNCT
cana-5024	198	27	m.	m.	NOUN
cana-5024	198	28	,	,	PUNCT
cana-5024	198	29	"	"	PUNCT
cana-5024	198	30	dermoscopic	dermoscopic	ADJ
cana-5024	198	31	image	image	NOUN
cana-5024	198	32	classification	classification	NOUN
cana-5024	198	33	using	use	VERB
cana-5024	198	34	ensemble	ensemble	NOUN
cana-5024	198	35	of	of	ADP
cana-5024	198	36	deep	deep	ADJ
cana-5024	198	37	convolutional	convolutional	ADJ
cana-5024	198	38	neural	neural	ADJ
cana-5024	198	39	networks	network	NOUN
cana-5024	198	40	,	,	PUNCT
cana-5024	198	41	"	"	PUNCT
cana-5024	198	42	ieee	ieee	PROPN
cana-5024	198	43	j.	j.	PROPN
cana-5024	198	44	biomed	biome	VERB
cana-5024	198	45	.	.	PUNCT
cana-5024	199	1	health	health	NOUN
cana-5024	199	2	inform	inform	NOUN
cana-5024	199	3	.	.	PUNCT
cana-5024	199	4	,	,	PUNCT
cana-5024	199	5	vol	vol	NOUN
cana-5024	199	6	.	.	PROPN
cana-5024	199	7	23	23	NUM
cana-5024	199	8	,	,	PUNCT
cana-5024	199	9	no	no	INTJ
cana-5024	199	10	.	.	NOUN
cana-5024	199	11	3	3	NUM
cana-5024	199	12	,	,	PUNCT
cana-5024	199	13	pp	pp	ADJ
cana-5024	199	14	.	.	PUNCT
cana-5024	199	15	1156–1164	1156–1164	NUM
cana-5024	199	16	,	,	PUNCT
cana-5024	199	17	2019	2019	NUM
cana-5024	199	18	.	.	PUNCT
cana-5024	200	1	[	[	X
cana-5024	200	2	6	6	NUM
cana-5024	200	3	]	]	PUNCT
cana-5024	200	4	brinker	brinker	NOUN
cana-5024	200	5	,	,	PUNCT
cana-5024	200	6	t.	t.	PROPN
cana-5024	200	7	j.	j.	PROPN
cana-5024	200	8	,	,	PUNCT
cana-5024	200	9	hekler	hekler	PROPN
cana-5024	200	10	,	,	PUNCT
cana-5024	200	11	a.	a.	PROPN
cana-5024	200	12	,	,	PUNCT
cana-5024	200	13	enk	enk	PROPN
cana-5024	200	14	,	,	PUNCT
cana-5024	200	15	a.	a.	PROPN
cana-5024	200	16	h.	h.	PROPN
cana-5024	200	17	,	,	PUNCT
cana-5024	200	18	berking	berking	NOUN
cana-5024	200	19	,	,	PUNCT
cana-5024	200	20	c.	c.	PROPN
cana-5024	200	21	,	,	PUNCT
cana-5024	200	22	haferkamp	haferkamp	PROPN
cana-5024	200	23	,	,	PUNCT
cana-5024	200	24	s.	s.	PROPN
cana-5024	200	25	,	,	PUNCT
cana-5024	200	26	hauschild	hauschild	PROPN
cana-5024	200	27	,	,	PUNCT
cana-5024	200	28	a.	a.	NOUN
cana-5024	200	29	,	,	PUNCT
cana-5024	200	30	et	et	PROPN
cana-5024	200	31	al	al	PROPN
cana-5024	200	32	.	.	PROPN
cana-5024	200	33	,	,	PUNCT
cana-5024	200	34	"	"	PUNCT
cana-5024	200	35	a	a	DET
cana-5024	200	36	convolutional	convolutional	ADJ
cana-5024	200	37	neural	neural	ADJ
cana-5024	200	38	network	network	NOUN
cana-5024	200	39	trained	train	VERB
cana-5024	200	40	with	with	ADP
cana-5024	200	41	dermoscopic	dermoscopic	ADJ
cana-5024	200	42	images	image	NOUN
cana-5024	200	43	performed	perform	VERB
cana-5024	200	44	on	on	ADP
cana-5024	200	45	par	par	NOUN
cana-5024	200	46	with	with	ADP
cana-5024	200	47	145	145	NUM
cana-5024	200	48	dermatologists	dermatologist	NOUN
cana-5024	200	49	in	in	ADP
cana-5024	200	50	a	a	DET
cana-5024	200	51	classification	classification	NOUN
cana-5024	200	52	task	task	NOUN
cana-5024	200	53	,	,	PUNCT
cana-5024	200	54	"	"	PUNCT
cana-5024	200	55	eur	eur	PROPN
cana-5024	200	56	.	.	PUNCT
cana-5024	201	1	j.	j.	PROPN
cana-5024	201	2	cancer	cancer	PROPN
cana-5024	201	3	,	,	PUNCT
cana-5024	201	4	vol	vol	NOUN
cana-5024	201	5	.	.	NOUN
cana-5024	201	6	111	111	NUM
cana-5024	201	7	,	,	PUNCT
cana-5024	201	8	pp	pp	ADJ
cana-5024	201	9	.	.	PUNCT
cana-5024	202	1	148–154	148–154	NUM
cana-5024	202	2	,	,	PUNCT
cana-5024	202	3	2019	2019	NUM
cana-5024	202	4	.	.	PUNCT
cana-5024	203	1	[	[	X
cana-5024	203	2	7	7	NUM
cana-5024	203	3	]	]	PUNCT
cana-5024	203	4	codella	codella	NOUN
cana-5024	203	5	,	,	PUNCT
cana-5024	203	6	n.	n.	NOUN
cana-5024	203	7	,	,	PUNCT
cana-5024	203	8	gutman	gutman	PROPN
cana-5024	203	9	,	,	PUNCT
cana-5024	203	10	d.	d.	PROPN
cana-5024	203	11	,	,	PUNCT
cana-5024	203	12	celebi	celebi	NOUN
cana-5024	203	13	,	,	PUNCT
cana-5024	203	14	m.	m.	PROPN
cana-5024	203	15	e.	e.	PROPN
cana-5024	203	16	,	,	PUNCT
cana-5024	203	17	helba	helba	PROPN
cana-5024	203	18	,	,	PUNCT
cana-5024	203	19	b.	b.	PROPN
cana-5024	203	20	,	,	PUNCT
cana-5024	203	21	marchetti	marchetti	PROPN
cana-5024	203	22	,	,	PUNCT
cana-5024	203	23	m.	m.	NOUN
cana-5024	203	24	a.	a.	PROPN
cana-5024	203	25	,	,	PUNCT
cana-5024	203	26	dusza	dusza	NOUN
cana-5024	203	27	,	,	PUNCT
cana-5024	203	28	s.	s.	PROPN
cana-5024	203	29	w.	w.	PROPN
cana-5024	203	30	,	,	PUNCT
cana-5024	203	31	et	et	PROPN
cana-5024	203	32	al	al	PROPN
cana-5024	203	33	.	.	PROPN
cana-5024	203	34	,	,	PUNCT
cana-5024	203	35	"	"	PUNCT
cana-5024	203	36	skin	skin	NOUN
cana-5024	203	37	lesion	lesion	NOUN
cana-5024	203	38	analysis	analysis	NOUN
cana-5024	203	39	toward	toward	ADP
cana-5024	203	40	melanoma	melanoma	NOUN
cana-5024	203	41	detection	detection	NOUN
cana-5024	203	42	:	:	PUNCT
cana-5024	203	43	a	a	DET
cana-5024	203	44	challenge	challenge	NOUN
cana-5024	203	45	at	at	ADP
cana-5024	203	46	the	the	DET
cana-5024	203	47	2017	2017	NUM
cana-5024	203	48	isic	isic	PROPN
cana-5024	203	49	workshop	workshop	NOUN
cana-5024	203	50	,	,	PUNCT
cana-5024	203	51	"	"	PUNCT
cana-5024	203	52	in	in	ADP
cana-5024	203	53	proc	proc	NOUN
cana-5024	203	54	.	.	PUNCT
cana-5024	204	1	ieee	ieee	PROPN
cana-5024	204	2	int	int	PROPN
cana-5024	204	3	.	.	PUNCT
cana-5024	205	1	symp	symp	PROPN
cana-5024	205	2	.	.	PUNCT
cana-5024	205	3	biomed	biome	VERB
cana-5024	205	4	.	.	PUNCT
cana-5024	206	1	imaging	imaging	NOUN
cana-5024	206	2	(	(	PUNCT
cana-5024	206	3	isbi	isbi	NOUN
cana-5024	206	4	)	)	PUNCT
cana-5024	206	5	,	,	PUNCT
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cana-5024	206	7	,	,	PUNCT
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cana-5024	206	9	.	.	PUNCT
cana-5024	207	1	168–172	168–172	NUM
cana-5024	207	2	.	.	PUNCT
cana-5024	208	1	[	[	X
cana-5024	208	2	8	8	NUM
cana-5024	208	3	]	]	X
cana-5024	208	4	esteva	esteva	PROPN
cana-5024	208	5	,	,	PUNCT
cana-5024	208	6	a.	a.	PROPN
cana-5024	208	7	,	,	PUNCT
cana-5024	208	8	kuprel	kuprel	PROPN
cana-5024	208	9	,	,	PUNCT
cana-5024	208	10	b.	b.	PROPN
cana-5024	208	11	,	,	PUNCT
cana-5024	208	12	novoa	novoa	NOUN
cana-5024	208	13	,	,	PUNCT
cana-5024	208	14	r.	r.	PROPN
cana-5024	208	15	a.	a.	PROPN
cana-5024	208	16	,	,	PUNCT
cana-5024	208	17	ko	ko	PROPN
cana-5024	208	18	,	,	PUNCT
cana-5024	208	19	j.	j.	PROPN
cana-5024	208	20	,	,	PUNCT
cana-5024	208	21	swetter	swetter	PROPN
cana-5024	208	22	,	,	PUNCT
cana-5024	208	23	s.	s.	PROPN
cana-5024	208	24	m.	m.	PROPN
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cana-5024	208	26	blau	blau	PROPN
cana-5024	208	27	,	,	PUNCT
cana-5024	208	28	h.	h.	PROPN
cana-5024	208	29	m.	m.	PROPN
cana-5024	208	30	,	,	PUNCT
cana-5024	208	31	and	and	CCONJ
cana-5024	208	32	thrun	thrun	NOUN
cana-5024	208	33	,	,	PUNCT
cana-5024	208	34	s.	s.	PROPN
cana-5024	208	35	,	,	PUNCT
cana-5024	208	36	"	"	PUNCT
cana-5024	208	37	dermatologist	dermatologist	NOUN
cana-5024	208	38	-	-	PUNCT
cana-5024	208	39	level	level	NOUN
cana-5024	208	40	classification	classification	NOUN
cana-5024	208	41	of	of	ADP
cana-5024	208	42	skin	skin	NOUN
cana-5024	208	43	cancer	cancer	NOUN
cana-5024	208	44	with	with	ADP
cana-5024	208	45	deep	deep	ADJ
cana-5024	208	46	neural	neural	ADJ
cana-5024	208	47	networks	network	NOUN
cana-5024	208	48	,	,	PUNCT
cana-5024	208	49	"	"	PUNCT
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cana-5024	208	54	542	542	NUM
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cana-5024	208	57	.	.	NOUN
cana-5024	208	58	7639	7639	NUM
cana-5024	208	59	,	,	PUNCT
cana-5024	208	60	pp	pp	ADV
cana-5024	208	61	.	.	PUNCT
cana-5024	209	1	115–118	115–118	NUM
cana-5024	209	2	,	,	PUNCT
cana-5024	209	3	2017	2017	NUM
cana-5024	209	4	.	.	PUNCT
cana-5024	210	1	[	[	X
cana-5024	210	2	9	9	NUM
cana-5024	210	3	]	]	SYM
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cana-5024	210	5	,	,	PUNCT
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cana-5024	210	7	,	,	PUNCT
cana-5024	210	8	asadi	asadi	PROPN
cana-5024	210	9	,	,	PUNCT
cana-5024	210	10	f.	f.	PROPN
cana-5024	210	11	,	,	PUNCT
cana-5024	210	12	hosseini	hosseini	PROPN
cana-5024	210	13	,	,	PUNCT
cana-5024	210	14	a.	a.	NOUN
cana-5024	210	15	,	,	PUNCT
cana-5024	210	16	bashash	bashash	NOUN
cana-5024	210	17	,	,	PUNCT
cana-5024	210	18	d.	d.	PROPN
cana-5024	210	19	,	,	PUNCT
cana-5024	210	20	abolghasemi	abolghasemi	PROPN
cana-5024	210	21	,	,	PUNCT
cana-5024	210	22	h.	h.	NOUN
cana-5024	210	23	,	,	PUNCT
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cana-5024	210	28	,	,	PUNCT
cana-5024	210	29	"	"	PUNCT
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cana-5024	210	31	learning	learning	NOUN
cana-5024	210	32	in	in	ADP
cana-5024	210	33	the	the	DET
cana-5024	210	34	detection	detection	NOUN
cana-5024	210	35	and	and	CCONJ
cana-5024	210	36	diagnosis	diagnosis	NOUN
cana-5024	210	37	of	of	ADP
cana-5024	210	38	covid-19	covid-19	PROPN
cana-5024	210	39	using	use	VERB
cana-5024	210	40	radiology	radiology	NOUN
cana-5024	210	41	modalities	modality	NOUN
cana-5024	210	42	:	:	PUNCT
cana-5024	210	43	a	a	DET
cana-5024	210	44	systematic	systematic	ADJ
cana-5024	210	45	review	review	NOUN
cana-5024	210	46	,	,	PUNCT
cana-5024	210	47	"	"	PUNCT
cana-5024	210	48	j.	j.	PROPN
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cana-5024	210	50	.	.	PUNCT
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cana-5024	211	5	.	.	PROPN
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cana-5024	211	7	,	,	PUNCT
cana-5024	211	8	pp	pp	ADJ
cana-5024	211	9	.	.	PUNCT
cana-5024	212	1	1–13	1–13	NOUN
cana-5024	212	2	,	,	PUNCT
cana-5024	212	3	2021	2021	NUM
cana-5024	212	4	.	.	PUNCT
cana-5024	213	1	[	[	X
cana-5024	213	2	10	10	NUM
cana-5024	213	3	]	]	PUNCT
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cana-5024	213	5	,	,	PUNCT
cana-5024	213	6	d.	d.	PROPN
cana-5024	213	7	d.	d.	PROPN
cana-5024	213	8	,	,	PUNCT
cana-5024	213	9	butakoff	butakoff	PROPN
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cana-5024	213	11	c.	c.	PROPN
cana-5024	213	12	,	,	PUNCT
cana-5024	213	13	ersbøll	ersbøll	PROPN
cana-5024	213	14	,	,	PUNCT
cana-5024	213	15	a.	a.	NOUN
cana-5024	213	16	,	,	PUNCT
cana-5024	213	17	and	and	CCONJ
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cana-5024	213	21	,	,	PUNCT
cana-5024	213	22	"	"	PUNCT
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cana-5024	213	24	histogram	histogram	NOUN
cana-5024	213	25	pursuit	pursuit	NOUN
cana-5024	213	26	for	for	ADP
cana-5024	213	27	segmentation	segmentation	NOUN
cana-5024	213	28	of	of	ADP
cana-5024	213	29	skin	skin	NOUN
cana-5024	213	30	lesions	lesion	NOUN
cana-5024	213	31	,	,	PUNCT
cana-5024	213	32	"	"	PUNCT
cana-5024	213	33	ieee	ieee	NOUN
cana-5024	213	34	trans	tran	NOUN
cana-5024	213	35	.	.	PROPN
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cana-5024	213	37	.	.	PUNCT
cana-5024	214	1	eng	eng	PROPN
cana-5024	214	2	.	.	PROPN
cana-5024	214	3	,	,	PUNCT
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cana-5024	215	1	55	55	NUM
cana-5024	215	2	,	,	PUNCT
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cana-5024	215	5	1	1	NUM
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cana-5024	215	8	.	.	PUNCT
cana-5024	216	1	157–162	157–162	NUM
cana-5024	216	2	,	,	PUNCT
cana-5024	216	3	2008	2008	NUM
cana-5024	216	4	.	.	PUNCT
cana-5024	217	1	[	[	X
cana-5024	217	2	11	11	NUM
cana-5024	217	3	]	]	PUNCT
cana-5024	217	4	haenssle	haenssle	NOUN
cana-5024	217	5	,	,	PUNCT
cana-5024	217	6	h.	h.	PROPN
cana-5024	217	7	a.	a.	PROPN
cana-5024	217	8	,	,	PUNCT
cana-5024	217	9	fink	fink	PROPN
cana-5024	217	10	,	,	PUNCT
cana-5024	217	11	c.	c.	PROPN
cana-5024	217	12	,	,	PUNCT
cana-5024	217	13	schneiderbauer	schneiderbauer	PROPN
cana-5024	217	14	,	,	PUNCT
cana-5024	217	15	r.	r.	PROPN
cana-5024	217	16	,	,	PUNCT
cana-5024	217	17	toberer	toberer	NOUN
cana-5024	217	18	,	,	PUNCT
cana-5024	217	19	f.	f.	PROPN
cana-5024	217	20	,	,	PUNCT
cana-5024	217	21	buhl	buhl	PROPN
cana-5024	217	22	,	,	PUNCT
cana-5024	217	23	t.	t.	PROPN
cana-5024	217	24	,	,	PUNCT
cana-5024	217	25	blum	blum	PROPN
cana-5024	217	26	,	,	PUNCT
cana-5024	217	27	a.	a.	PROPN
cana-5024	217	28	,	,	PUNCT
cana-5024	217	29	et	et	PROPN
cana-5024	217	30	al	al	PROPN
cana-5024	217	31	.	.	PROPN
cana-5024	217	32	,	,	PUNCT
cana-5024	217	33	"	"	PUNCT
cana-5024	217	34	man	man	NOUN
cana-5024	217	35	against	against	ADP
cana-5024	217	36	machine	machine	NOUN
cana-5024	217	37	:	:	PUNCT
cana-5024	217	38	diagnostic	diagnostic	ADJ
cana-5024	217	39	performance	performance	NOUN
cana-5024	217	40	of	of	ADP
cana-5024	217	41	a	a	DET
cana-5024	217	42	deep	deep	ADJ
cana-5024	217	43	learning	learn	VERB
cana-5024	217	44	cnn	cnn	PROPN
cana-5024	217	45	for	for	ADP
cana-5024	217	46	dermoscopic	dermoscopic	ADJ
cana-5024	217	47	melanoma	melanoma	PROPN
cana-5024	217	48	recognition	recognition	NOUN
cana-5024	217	49	in	in	ADP
cana-5024	217	50	comparison	comparison	NOUN
cana-5024	217	51	to	to	ADP
cana-5024	217	52	58	58	NUM
cana-5024	217	53	dermatologists	dermatologist	NOUN
cana-5024	217	54	,	,	PUNCT
cana-5024	217	55	"	"	PUNCT
cana-5024	217	56	ann	ann	PROPN
cana-5024	217	57	.	.	PUNCT
cana-5024	217	58	oncol	oncol	PROPN
cana-5024	217	59	.	.	PUNCT
cana-5024	217	60	,	,	PUNCT
cana-5024	217	61	vol	vol	NOUN
cana-5024	217	62	.	.	PROPN
cana-5024	217	63	29	29	NUM
cana-5024	217	64	,	,	PUNCT
cana-5024	217	65	no	no	INTJ
cana-5024	217	66	.	.	NOUN
cana-5024	217	67	8	8	NUM
cana-5024	217	68	,	,	PUNCT
cana-5024	217	69	pp	pp	ADJ
cana-5024	217	70	.	.	PUNCT
cana-5024	217	71	1836–1842	1836–1842	NUM
cana-5024	217	72	,	,	PUNCT
cana-5024	217	73	2018	2018	NUM
cana-5024	217	74	.	.	PUNCT
cana-5024	218	1	[	[	X
cana-5024	218	2	12	12	NUM
cana-5024	218	3	]	]	X
cana-5024	218	4	han	han	PROPN
cana-5024	218	5	,	,	PUNCT
cana-5024	218	6	s.	s.	PROPN
cana-5024	218	7	s.	s.	PROPN
cana-5024	218	8	,	,	PUNCT
cana-5024	218	9	park	park	PROPN
cana-5024	218	10	,	,	PUNCT
cana-5024	218	11	i.	i.	PROPN
cana-5024	218	12	,	,	PUNCT
cana-5024	218	13	chang	chang	PROPN
cana-5024	218	14	,	,	PUNCT
cana-5024	218	15	w.	w.	PROPN
cana-5024	218	16	y.	y.	PROPN
cana-5024	218	17	,	,	PUNCT
cana-5024	218	18	and	and	CCONJ
cana-5024	218	19	lim	lim	PROPN
cana-5024	218	20	,	,	PUNCT
cana-5024	218	21	h.	h.	PROPN
cana-5024	218	22	s.	s.	PROPN
cana-5024	218	23	,	,	PUNCT
cana-5024	218	24	"	"	PUNCT
cana-5024	218	25	augmented	augment	VERB
cana-5024	218	26	intelligence	intelligence	NOUN
cana-5024	218	27	dermatology	dermatology	NOUN
cana-5024	218	28	:	:	PUNCT
cana-5024	218	29	deep	deep	ADJ
cana-5024	218	30	neural	neural	ADJ
cana-5024	218	31	networks	network	NOUN
cana-5024	218	32	empower	empower	PROPN
cana-5024	218	33	medical	medical	ADJ
cana-5024	218	34	professionals	professional	NOUN
cana-5024	218	35	in	in	ADP
cana-5024	218	36	diagnosing	diagnose	VERB
cana-5024	218	37	skin	skin	NOUN
cana-5024	218	38	cancer	cancer	NOUN
cana-5024	218	39	and	and	CCONJ
cana-5024	218	40	predicting	predict	VERB
cana-5024	218	41	treatment	treatment	NOUN
cana-5024	218	42	options	option	NOUN
cana-5024	218	43	,	,	PUNCT
cana-5024	218	44	"	"	PUNCT
cana-5024	218	45	j.	j.	PROPN
cana-5024	218	46	invest	invest	PROPN
cana-5024	218	47	.	.	PUNCT
cana-5024	219	1	dermatol	dermatol	NOUN
cana-5024	219	2	.	.	PUNCT
cana-5024	219	3	,	,	PUNCT
cana-5024	220	1	vol	vol	NOUN
cana-5024	220	2	.	.	PROPN
cana-5024	221	1	140	140	NUM
cana-5024	221	2	,	,	PUNCT
cana-5024	221	3	no	no	INTJ
cana-5024	221	4	.	.	NOUN
cana-5024	221	5	9	9	NUM
cana-5024	221	6	,	,	PUNCT
cana-5024	221	7	pp	pp	ADJ
cana-5024	221	8	.	.	PUNCT
cana-5024	222	1	1754–1762.e3	1754–1762.e3	NUM
cana-5024	222	2	,	,	PUNCT
cana-5024	222	3	2020	2020	NUM
cana-5024	222	4	.	.	PUNCT
cana-5024	223	1	[	[	X
cana-5024	223	2	13	13	NUM
cana-5024	223	3	]	]	SYM
cana-5024	223	4	harangi	harangi	PROPN
cana-5024	223	5	,	,	PUNCT
cana-5024	223	6	b.	b.	PROPN
cana-5024	223	7	,	,	PUNCT
cana-5024	223	8	"	"	PUNCT
cana-5024	223	9	skin	skin	NOUN
cana-5024	223	10	lesion	lesion	NOUN
cana-5024	223	11	classification	classification	NOUN
cana-5024	223	12	with	with	ADP
cana-5024	223	13	ensembles	ensemble	NOUN
cana-5024	223	14	of	of	ADP
cana-5024	223	15	deep	deep	ADJ
cana-5024	223	16	convolutional	convolutional	ADJ
cana-5024	223	17	neural	neural	ADJ
cana-5024	223	18	networks	network	NOUN
cana-5024	223	19	,	,	PUNCT
cana-5024	223	20	"	"	PUNCT
cana-5024	223	21	j.	j.	PROPN
cana-5024	223	22	biomed	biome	VERB
cana-5024	223	23	.	.	PUNCT
cana-5024	224	1	inform	inform	NOUN
cana-5024	224	2	.	.	PUNCT
cana-5024	224	3	,	,	PUNCT
cana-5024	224	4	vol	vol	NOUN
cana-5024	224	5	.	.	PROPN
cana-5024	224	6	86	86	NUM
cana-5024	224	7	,	,	PUNCT
cana-5024	224	8	pp	pp	ADJ
cana-5024	224	9	.	.	PUNCT
cana-5024	225	1	25–32	25–32	NUM
cana-5024	225	2	,	,	PUNCT
cana-5024	225	3	2018	2018	NUM
cana-5024	225	4	.	.	PUNCT
cana-5024	226	1	communications	communication	NOUN
cana-5024	226	2	on	on	ADP
cana-5024	226	3	applied	apply	VERB
cana-5024	226	4	nonlinear	nonlinear	ADJ
cana-5024	226	5	analysis	analysis	NOUN
cana-5024	226	6	issn	issn	NOUN
cana-5024	226	7	:	:	PUNCT
cana-5024	226	8	1074	1074	NUM
cana-5024	226	9	-	-	PUNCT
cana-5024	226	10	133x	133x	NUM
cana-5024	226	11	vol	vol	VERB
cana-5024	226	12	32	32	NUM
cana-5024	226	13	no.1s	no.1s	PROPN
cana-5024	226	14	(	(	PUNCT
cana-5024	226	15	2025	2025	NUM
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cana-5024	226	17	653	653	NUM
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cana-5024	227	1	[	[	X
cana-5024	227	2	14	14	NUM
cana-5024	227	3	]	]	X
cana-5024	227	4	kawahara	kawahara	PROPN
cana-5024	227	5	,	,	PUNCT
cana-5024	227	6	j.	j.	PROPN
cana-5024	227	7	,	,	PUNCT
cana-5024	227	8	bentaieb	bentaieb	PROPN
cana-5024	227	9	,	,	PUNCT
cana-5024	227	10	a.	a.	PROPN
cana-5024	227	11	,	,	PUNCT
cana-5024	227	12	and	and	CCONJ
cana-5024	227	13	hamarneh	hamarneh	PROPN
cana-5024	227	14	,	,	PUNCT
cana-5024	227	15	g.	g.	PROPN
cana-5024	227	16	,	,	PUNCT
cana-5024	227	17	"	"	PUNCT
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cana-5024	227	19	features	feature	NOUN
cana-5024	227	20	to	to	PART
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cana-5024	227	22	skin	skin	NOUN
cana-5024	227	23	lesions	lesion	NOUN
cana-5024	227	24	,	,	PUNCT
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cana-5024	227	28	.	.	PROPN
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cana-5024	228	4	,	,	PUNCT
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cana-5024	228	6	.	.	PROPN
cana-5024	228	7	35	35	NUM
cana-5024	228	8	,	,	PUNCT
cana-5024	228	9	no	no	INTJ
cana-5024	228	10	.	.	NOUN
cana-5024	228	11	8	8	NUM
cana-5024	228	12	,	,	PUNCT
cana-5024	228	13	pp	pp	ADJ
cana-5024	228	14	.	.	PUNCT
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cana-5024	229	2	,	,	PUNCT
cana-5024	229	3	2016	2016	NUM
cana-5024	229	4	.	.	PUNCT
cana-5024	230	1	[	[	X
cana-5024	230	2	15	15	NUM
cana-5024	230	3	]	]	X
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cana-5024	230	9	sharif	sharif	PROPN
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cana-5024	230	12	,	,	PUNCT
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cana-5024	230	16	t.	t.	PROPN
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cana-5024	230	18	"	"	PUNCT
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cana-5024	230	21	cnn	cnn	PROPN
cana-5024	230	22	framework	framework	NOUN
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cana-5024	230	24	skin	skin	NOUN
cana-5024	230	25	lesion	lesion	NOUN
cana-5024	230	26	classification	classification	NOUN
cana-5024	230	27	using	use	VERB
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cana-5024	230	29	and	and	CCONJ
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cana-5024	230	32	,	,	PUNCT
cana-5024	230	33	"	"	PUNCT
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cana-5024	230	38	.	.	PUNCT
cana-5024	231	1	,	,	PUNCT
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cana-5024	232	2	,	,	PUNCT
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cana-5024	232	5	,	,	PUNCT
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cana-5024	232	7	.	.	PUNCT
cana-5024	233	1	[	[	X
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cana-5024	233	3	]	]	SYM
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cana-5024	233	7	,	,	PUNCT
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cana-5024	233	9	,	,	PUNCT
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cana-5024	233	33	features	feature	NOUN
cana-5024	233	34	for	for	ADP
cana-5024	233	35	skin	skin	NOUN
cana-5024	233	36	lesion	lesion	NOUN
cana-5024	233	37	classification	classification	NOUN
cana-5024	233	38	,	,	PUNCT
cana-5024	233	39	"	"	PUNCT
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cana-5024	237	2	,	,	PUNCT
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cana-5024	237	4	.	.	PUNCT
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cana-5024	238	3	]	]	X
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cana-5024	238	5	,	,	PUNCT
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cana-5024	238	8	"	"	PUNCT
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cana-5024	241	1	,	,	PUNCT
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cana-5024	243	1	51–67	51–67	NUM
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cana-5024	244	1	[	[	X
cana-5024	244	2	18	18	NUM
cana-5024	244	3	]	]	X
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cana-5024	244	7	,	,	PUNCT
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cana-5024	244	31	,	,	PUNCT
cana-5024	244	32	"	"	PUNCT
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cana-5024	244	34	.	.	PUNCT
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cana-5024	246	10	,	,	PUNCT
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cana-5024	247	1	[	[	X
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cana-5024	247	3	]	]	X
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cana-5024	247	13	,	,	PUNCT
cana-5024	247	14	karimi	karimi	PROPN
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cana-5024	247	16	n.	n.	NOUN
cana-5024	247	17	,	,	PUNCT
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cana-5024	247	20	s.	s.	PROPN
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cana-5024	247	29	and	and	CCONJ
cana-5024	247	30	najarian	najarian	PROPN
cana-5024	247	31	,	,	PUNCT
cana-5024	247	32	k.	k.	PROPN
cana-5024	247	33	,	,	PUNCT
cana-5024	247	34	"	"	PUNCT
cana-5024	247	35	melanoma	melanoma	NOUN
cana-5024	247	36	detection	detection	NOUN
cana-5024	247	37	by	by	ADP
cana-5024	247	38	analysis	analysis	NOUN
cana-5024	247	39	of	of	ADP
cana-5024	247	40	clinical	clinical	ADJ
cana-5024	247	41	images	image	NOUN
cana-5024	247	42	using	use	VERB
cana-5024	247	43	convolutional	convolutional	ADJ
cana-5024	247	44	neural	neural	ADJ
cana-5024	247	45	network	network	NOUN
cana-5024	247	46	,	,	PUNCT
cana-5024	247	47	"	"	PUNCT
cana-5024	247	48	int	int	NOUN
cana-5024	247	49	.	.	PUNCT
cana-5024	248	1	j.	j.	PROPN
cana-5024	248	2	comput	comput	PROPN
cana-5024	248	3	.	.	PUNCT
cana-5024	249	1	assist	assist	VERB
cana-5024	249	2	.	.	PUNCT
cana-5024	250	1	radiol	radiol	NOUN
cana-5024	250	2	.	.	PUNCT
cana-5024	251	1	surg	surg	PROPN
cana-5024	251	2	.	.	PUNCT
cana-5024	252	1	,	,	PUNCT
cana-5024	252	2	vol	vol	NOUN
cana-5024	252	3	.	.	PROPN
cana-5024	253	1	11	11	NUM
cana-5024	253	2	,	,	PUNCT
cana-5024	253	3	no	no	INTJ
cana-5024	253	4	.	.	NOUN
cana-5024	253	5	6	6	NUM
cana-5024	253	6	,	,	PUNCT
cana-5024	253	7	pp	pp	ADJ
cana-5024	253	8	.	.	PUNCT
cana-5024	254	1	993–1001	993–1001	NUM
cana-5024	254	2	,	,	PUNCT
cana-5024	254	3	2016	2016	NUM
cana-5024	254	4	.	.	PUNCT
cana-5024	255	1	[	[	X
cana-5024	255	2	20	20	NUM
cana-5024	255	3	]	]	X
cana-5024	255	4	pham	pham	PROPN
cana-5024	255	5	,	,	PUNCT
cana-5024	255	6	t.	t.	PROPN
cana-5024	255	7	d.	d.	PROPN
cana-5024	255	8	,	,	PUNCT
cana-5024	255	9	hussain	hussain	PROPN
cana-5024	255	10	,	,	PUNCT
cana-5024	255	11	a.	a.	PROPN
cana-5024	255	12	,	,	PUNCT
cana-5024	255	13	al	al	PROPN
cana-5024	255	14	-	-	PUNCT
cana-5024	255	15	makhadmeh	makhadmeh	PROPN
cana-5024	255	16	,	,	PUNCT
cana-5024	255	17	z.	z.	PROPN
cana-5024	255	18	,	,	PUNCT
cana-5024	255	19	and	and	CCONJ
cana-5024	255	20	fernandes	fernande	NOUN
cana-5024	255	21	,	,	PUNCT
cana-5024	255	22	s.	s.	PROPN
cana-5024	255	23	l.	l.	PROPN
cana-5024	255	24	,	,	PUNCT
cana-5024	255	25	"	"	PUNCT
cana-5024	255	26	skin	skin	NOUN
cana-5024	255	27	lesion	lesion	NOUN
cana-5024	255	28	image	image	NOUN
cana-5024	255	29	synthesis	synthesis	NOUN
cana-5024	255	30	for	for	ADP
cana-5024	255	31	improving	improve	VERB
cana-5024	255	32	classification	classification	NOUN
cana-5024	255	33	performance	performance	NOUN
cana-5024	255	34	using	use	VERB
cana-5024	255	35	gans	gan	NOUN
cana-5024	255	36	,	,	PUNCT
cana-5024	255	37	"	"	PUNCT
cana-5024	255	38	comput	comput	NOUN
cana-5024	255	39	.	.	PUNCT
cana-5024	256	1	methods	method	NOUN
cana-5024	256	2	programs	program	NOUN
cana-5024	256	3	biomed	biome	VERB
cana-5024	256	4	.	.	PUNCT
cana-5024	257	1	,	,	PUNCT
cana-5024	257	2	vol	vol	NOUN
cana-5024	257	3	.	.	PROPN
cana-5024	257	4	196	196	NUM
cana-5024	257	5	,	,	PUNCT
cana-5024	257	6	p.	p.	NOUN
cana-5024	257	7	105645	105645	NUM
cana-5024	257	8	,	,	PUNCT
cana-5024	257	9	2020	2020	NUM
cana-5024	257	10	.	.	PUNCT
cana-5024	258	1	[	[	X
cana-5024	258	2	21	21	NUM
cana-5024	258	3	]	]	X
cana-5024	258	4	rajesh	rajesh	PROPN
cana-5024	258	5	,	,	PUNCT
cana-5024	258	6	p.	p.	NOUN
cana-5024	258	7	,	,	PUNCT
cana-5024	258	8	and	and	CCONJ
cana-5024	258	9	m.	m.	PROPN
cana-5024	258	10	karthikeyan	karthikeyan	PROPN
cana-5024	258	11	.	.	PUNCT
cana-5024	259	1	"	"	PUNCT
cana-5024	259	2	a	a	DET
cana-5024	259	3	comparative	comparative	ADJ
cana-5024	259	4	study	study	NOUN
cana-5024	259	5	of	of	ADP
cana-5024	259	6	data	datum	NOUN
cana-5024	259	7	mining	mining	NOUN
cana-5024	259	8	algorithms	algorithm	NOUN
cana-5024	259	9	for	for	ADP
cana-5024	259	10	decision	decision	NOUN
cana-5024	259	11	tree	tree	NOUN
cana-5024	259	12	approaches	approach	NOUN
cana-5024	259	13	using	use	VERB
cana-5024	259	14	weka	weka	PROPN
cana-5024	259	15	tool	tool	NOUN
cana-5024	259	16	,	,	PUNCT
cana-5024	259	17	"	"	PUNCT
cana-5024	259	18	advances	advance	NOUN
cana-5024	259	19	in	in	ADP
cana-5024	259	20	natural	natural	ADJ
cana-5024	259	21	and	and	CCONJ
cana-5024	259	22	applied	applied	ADJ
cana-5024	259	23	sciences	science	NOUN
cana-5024	259	24	,	,	PUNCT
cana-5024	259	25	vol	vol	NOUN
cana-5024	259	26	.	.	PROPN
cana-5024	259	27	11	11	NUM
cana-5024	259	28	,	,	PUNCT
cana-5024	259	29	no	no	INTJ
cana-5024	259	30	.	.	NOUN
cana-5024	259	31	9	9	NUM
cana-5024	259	32	,	,	PUNCT
cana-5024	259	33	p.	p.	NOUN
cana-5024	259	34	230	230	NUM
cana-5024	259	35	-	-	SYM
cana-5024	259	36	243	243	NUM
cana-5024	259	37	,	,	PUNCT
cana-5024	259	38	2017	2017	NUM
cana-5024	259	39	.	.	PUNCT
cana-5024	260	1	[	[	X
cana-5024	260	2	22	22	NUM
cana-5024	260	3	]	]	X
cana-5024	260	4	rajesh	rajesh	PROPN
cana-5024	260	5	,	,	PUNCT
cana-5024	260	6	p.	p.	NOUN
cana-5024	260	7	,	,	PUNCT
cana-5024	260	8	and	and	CCONJ
cana-5024	260	9	m.	m.	PROPN
cana-5024	260	10	karthikeyan	karthikeyan	PROPN
cana-5024	260	11	.	.	PUNCT
cana-5024	261	1	"	"	PUNCT
cana-5024	261	2	data	datum	NOUN
cana-5024	261	3	assimilation	assimilation	NOUN
cana-5024	261	4	of	of	ADP
cana-5024	261	5	gross	gross	ADJ
cana-5024	261	6	domestic	domestic	ADJ
cana-5024	261	7	product	product	NOUN
cana-5024	261	8	(	(	PUNCT
cana-5024	261	9	gdp	gdp	NOUN
cana-5024	261	10	)	)	PUNCT
cana-5024	261	11	in	in	ADP
cana-5024	261	12	india	india	PROPN
cana-5024	261	13	using	use	VERB
cana-5024	261	14	stochastic	stochastic	ADJ
cana-5024	261	15	data	datum	NOUN
cana-5024	261	16	mining	mining	NOUN
cana-5024	261	17	approach	approach	NOUN
cana-5024	261	18	,	,	PUNCT
cana-5024	261	19	"	"	PUNCT
cana-5024	261	20	journal	journal	NOUN
cana-5024	261	21	of	of	ADP
cana-5024	261	22	computational	computational	ADJ
cana-5024	261	23	and	and	CCONJ
cana-5024	261	24	theoretical	theoretical	ADJ
cana-5024	261	25	nanoscience	nanoscience	NOUN
cana-5024	261	26	16	16	NUM
cana-5024	261	27	,	,	PUNCT
cana-5024	261	28	no	no	INTJ
cana-5024	261	29	.	.	NOUN
cana-5024	261	30	4	4	NUM
cana-5024	261	31	,	,	PUNCT
cana-5024	261	32	p.	p.	NOUN
cana-5024	261	33	1478	1478	NUM
cana-5024	261	34	-	-	SYM
cana-5024	261	35	1484	1484	NUM
cana-5024	261	36	,	,	PUNCT
cana-5024	261	37	2019	2019	NUM
cana-5024	261	38	.	.	PUNCT
cana-5024	262	1	[	[	X
cana-5024	262	2	23	23	NUM
cana-5024	262	3	]	]	X
cana-5024	262	4	rajesh	rajesh	PROPN
cana-5024	262	5	,	,	PUNCT
cana-5024	262	6	p.	p.	PROPN
cana-5024	262	7	,	,	PUNCT
cana-5024	262	8	m.	m.	NOUN
cana-5024	262	9	karthikeyan	karthikeyan	PROPN
cana-5024	262	10	,	,	PUNCT
cana-5024	262	11	b.	b.	PROPN
cana-5024	262	12	santhosh	santhosh	PROPN
cana-5024	262	13	kumar	kumar	PROPN
cana-5024	262	14	,	,	PUNCT
cana-5024	262	15	and	and	CCONJ
cana-5024	262	16	m.	m.	PROPN
cana-5024	262	17	y.	y.	PROPN
cana-5024	262	18	mohamed	mohamed	PROPN
cana-5024	262	19	parvees	parvees	PROPN
cana-5024	262	20	.	.	PUNCT
cana-5024	263	1	"	"	PUNCT
cana-5024	263	2	comparative	comparative	ADJ
cana-5024	263	3	study	study	NOUN
cana-5024	263	4	of	of	ADP
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cana-5024	263	6	tree	tree	NOUN
cana-5024	263	7	approaches	approach	VERB
cana-5024	263	8	in	in	ADP
cana-5024	263	9	data	datum	NOUN
cana-5024	263	10	mining	mining	NOUN
cana-5024	263	11	using	use	VERB
cana-5024	263	12	chronic	chronic	ADJ
cana-5024	263	13	disease	disease	NOUN
cana-5024	263	14	indicators	indicator	NOUN
cana-5024	263	15	(	(	PUNCT
cana-5024	263	16	cdi	cdi	PROPN
cana-5024	263	17	)	)	PUNCT
cana-5024	263	18	data	datum	NOUN
cana-5024	263	19	,	,	PUNCT
cana-5024	263	20	"	"	PUNCT
cana-5024	263	21	journal	journal	NOUN
cana-5024	263	22	of	of	ADP
cana-5024	263	23	computational	computational	ADJ
cana-5024	263	24	and	and	CCONJ
cana-5024	263	25	theoretical	theoretical	ADJ
cana-5024	263	26	nanoscience	nanoscience	NOUN
cana-5024	263	27	16	16	NUM
cana-5024	263	28	,	,	PUNCT
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cana-5024	263	30	.	.	NOUN
cana-5024	263	31	4	4	NUM
cana-5024	263	32	,	,	PUNCT
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cana-5024	263	34	1472	1472	NUM
cana-5024	263	35	-	-	SYM
cana-5024	263	36	1477	1477	NUM
cana-5024	263	37	,	,	PUNCT
cana-5024	263	38	2019	2019	NUM
cana-5024	263	39	.	.	PUNCT
cana-5024	264	1	[	[	X
cana-5024	264	2	24	24	NUM
cana-5024	264	3	]	]	PUNCT
cana-5024	264	4	rasti	rasti	PROPN
cana-5024	264	5	,	,	PUNCT
cana-5024	264	6	r.	r.	PROPN
cana-5024	264	7	,	,	PUNCT
cana-5024	264	8	teshnehlab	teshnehlab	NOUN
cana-5024	264	9	,	,	PUNCT
cana-5024	264	10	a.	a.	NOUN
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cana-5024	264	13	phung	phung	PROPN
cana-5024	264	14	,	,	PUNCT
cana-5024	264	15	s.	s.	PROPN
cana-5024	264	16	,	,	PUNCT
cana-5024	264	17	"	"	PUNCT
cana-5024	264	18	skin	skin	NOUN
cana-5024	264	19	lesion	lesion	NOUN
cana-5024	264	20	classification	classification	NOUN
cana-5024	264	21	using	use	VERB
cana-5024	264	22	hybrid	hybrid	ADJ
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cana-5024	264	24	methods	method	NOUN
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cana-5024	264	26	"	"	PUNCT
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cana-5024	264	28	syst	syst	NOUN
cana-5024	264	29	.	.	PUNCT
cana-5024	265	1	appl	appl	PROPN
cana-5024	265	2	.	.	PROPN
cana-5024	265	3	,	,	PUNCT
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cana-5024	265	5	.	.	PROPN
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cana-5024	265	7	,	,	PUNCT
cana-5024	265	8	p.	p.	NOUN
cana-5024	265	9	115331	115331	NUM
cana-5024	265	10	,	,	PUNCT
cana-5024	265	11	2021	2021	NUM
cana-5024	265	12	.	.	PUNCT
cana-5024	266	1	[	[	X
cana-5024	266	2	25	25	NUM
cana-5024	266	3	]	]	X
cana-5024	266	4	thurnhofer	thurnhofer	NOUN
cana-5024	266	5	-	-	PUNCT
cana-5024	266	6	hemsi	hemsi	NOUN
cana-5024	266	7	,	,	PUNCT
cana-5024	266	8	p.	p.	PROPN
cana-5024	266	9	,	,	PUNCT
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cana-5024	266	11	-	-	PUNCT
cana-5024	266	12	garcía	garcía	PROPN
cana-5024	266	13	,	,	PUNCT
cana-5024	266	14	c.	c.	PROPN
cana-5024	266	15	f.	f.	PROPN
cana-5024	266	16	,	,	PUNCT
cana-5024	266	17	and	and	CCONJ
cana-5024	266	18	garcía	garcía	ADJ
cana-5024	266	19	-	-	PUNCT
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cana-5024	266	22	b.	b.	PROPN
cana-5024	266	23	,	,	PUNCT
cana-5024	266	24	"	"	PUNCT
cana-5024	266	25	improving	improve	VERB
cana-5024	266	26	skin	skin	NOUN
cana-5024	266	27	lesion	lesion	NOUN
cana-5024	266	28	classification	classification	NOUN
cana-5024	266	29	using	use	VERB
cana-5024	266	30	deep	deep	ADJ
cana-5024	266	31	ensembles	ensemble	NOUN
cana-5024	266	32	and	and	CCONJ
cana-5024	266	33	cross	cross	ADJ
cana-5024	266	34	-	-	ADJ
cana-5024	266	35	dataset	dataset	ADJ
cana-5024	266	36	generalization	generalization	NOUN
cana-5024	266	37	,	,	PUNCT
cana-5024	266	38	"	"	PUNCT
cana-5024	266	39	sensors	sensor	NOUN
cana-5024	266	40	,	,	PUNCT
cana-5024	266	41	vol	vol	NOUN
cana-5024	266	42	.	.	PROPN
cana-5024	266	43	21	21	NUM
cana-5024	266	44	,	,	PUNCT
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cana-5024	266	47	14	14	NUM
cana-5024	266	48	,	,	PUNCT
cana-5024	266	49	p.	p.	NOUN
cana-5024	266	50	4897	4897	NUM
cana-5024	266	51	,	,	PUNCT
cana-5024	266	52	2021	2021	NUM
cana-5024	266	53	.	.	PUNCT
cana-5024	267	1	[	[	X
cana-5024	267	2	26	26	NUM
cana-5024	267	3	]	]	PUNCT
cana-5024	267	4	tschandl	tschandl	NOUN
cana-5024	267	5	,	,	PUNCT
cana-5024	267	6	p.	p.	PROPN
cana-5024	267	7	,	,	PUNCT
cana-5024	267	8	rosendahl	rosendahl	PROPN
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cana-5024	267	11	,	,	PUNCT
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cana-5024	267	14	,	,	PUNCT
cana-5024	267	15	h.	h.	PROPN
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cana-5024	267	17	"	"	PUNCT
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cana-5024	267	19	ham10000	ham10000	PROPN
cana-5024	267	20	dataset	dataset	PROPN
cana-5024	267	21	,	,	PUNCT
cana-5024	267	22	a	a	DET
cana-5024	267	23	large	large	ADJ
cana-5024	267	24	collection	collection	NOUN
cana-5024	267	25	of	of	ADP
cana-5024	267	26	multisource	multisource	ADJ
cana-5024	267	27	dermatoscopic	dermatoscopic	NOUN
cana-5024	267	28	images	image	NOUN
cana-5024	267	29	of	of	ADP
cana-5024	267	30	common	common	ADJ
cana-5024	267	31	pigmented	pigmented	ADJ
cana-5024	267	32	skin	skin	NOUN
cana-5024	267	33	lesions	lesion	NOUN
cana-5024	267	34	,	,	PUNCT
cana-5024	267	35	"	"	PUNCT
cana-5024	267	36	sci	sci	PROPN
cana-5024	267	37	.	.	PROPN
cana-5024	267	38	data	data	PROPN
cana-5024	267	39	,	,	PUNCT
cana-5024	267	40	vol	vol	NOUN
cana-5024	267	41	.	.	PROPN
cana-5024	267	42	5	5	NUM
cana-5024	267	43	,	,	PUNCT
cana-5024	267	44	p.	p.	NOUN
cana-5024	267	45	180161	180161	NUM
cana-5024	267	46	,	,	PUNCT
cana-5024	267	47	2018	2018	NUM
cana-5024	267	48	.	.	PUNCT
cana-5024	268	1	[	[	X
cana-5024	268	2	27	27	NUM
cana-5024	268	3	]	]	SYM
cana-5024	268	4	wahab	wahab	PROPN
cana-5024	268	5	,	,	PUNCT
cana-5024	268	6	a.	a.	PROPN
cana-5024	268	7	,	,	PUNCT
cana-5024	268	8	khan	khan	PROPN
cana-5024	268	9	,	,	PUNCT
cana-5024	268	10	a.	a.	PROPN
cana-5024	268	11	,	,	PUNCT
cana-5024	268	12	and	and	CCONJ
cana-5024	268	13	khan	khan	PROPN
cana-5024	268	14	,	,	PUNCT
cana-5024	268	15	m.	m.	NOUN
cana-5024	268	16	,	,	PUNCT
cana-5024	268	17	"	"	PUNCT
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cana-5024	268	19	learning	learning	NOUN
cana-5024	268	20	and	and	CCONJ
cana-5024	268	21	optimization	optimization	NOUN
cana-5024	268	22	-	-	PUNCT
cana-5024	268	23	based	base	VERB
cana-5024	268	24	approach	approach	NOUN
cana-5024	268	25	for	for	ADP
cana-5024	268	26	classification	classification	NOUN
cana-5024	268	27	of	of	ADP
cana-5024	268	28	skin	skin	NOUN
cana-5024	268	29	cancer	cancer	NOUN
cana-5024	268	30	using	use	VERB
cana-5024	268	31	dermoscopy	dermoscopy	NOUN
cana-5024	268	32	images	image	NOUN
cana-5024	268	33	,	,	PUNCT
cana-5024	268	34	"	"	PUNCT
cana-5024	268	35	biomed	biome	VERB
cana-5024	268	36	.	.	PUNCT
cana-5024	269	1	signal	signal	ADJ
cana-5024	269	2	process	process	NOUN
cana-5024	269	3	.	.	PUNCT
cana-5024	270	1	control	control	NOUN
cana-5024	270	2	,	,	PUNCT
cana-5024	270	3	vol	vol	NOUN
cana-5024	270	4	.	.	PROPN
cana-5024	270	5	68	68	NUM
cana-5024	270	6	,	,	PUNCT
cana-5024	270	7	p.	p.	NOUN
cana-5024	270	8	102833	102833	NUM
cana-5024	270	9	,	,	PUNCT
cana-5024	270	10	2021	2021	NUM
cana-5024	270	11	.	.	PUNCT
cana-5024	271	1	[	[	X
cana-5024	271	2	28	28	NUM
cana-5024	271	3	]	]	X
cana-5024	271	4	xie	xie	PROPN
cana-5024	271	5	,	,	PUNCT
cana-5024	271	6	f.	f.	PROPN
cana-5024	271	7	,	,	PUNCT
cana-5024	271	8	fan	fan	PROPN
cana-5024	271	9	,	,	PUNCT
cana-5024	271	10	y.	y.	PROPN
cana-5024	271	11	,	,	PUNCT
cana-5024	271	12	li	li	PROPN
cana-5024	271	13	,	,	PUNCT
cana-5024	271	14	z.	z.	PROPN
cana-5024	271	15	,	,	PUNCT
cana-5024	271	16	jiang	jiang	PROPN
cana-5024	271	17	,	,	PUNCT
cana-5024	271	18	z.	z.	PROPN
cana-5024	271	19	,	,	PUNCT
cana-5024	271	20	meng	meng	PROPN
cana-5024	271	21	,	,	PUNCT
cana-5024	271	22	r.	r.	PROPN
cana-5024	271	23	,	,	PUNCT
cana-5024	271	24	and	and	CCONJ
cana-5024	271	25	bovik	bovik	ADV
cana-5024	271	26	,	,	PUNCT
cana-5024	271	27	a.	a.	PROPN
cana-5024	271	28	c.	c.	PROPN
cana-5024	271	29	,	,	PUNCT
cana-5024	271	30	"	"	PUNCT
cana-5024	271	31	melanoma	melanoma	NOUN
cana-5024	271	32	classification	classification	NOUN
cana-5024	271	33	on	on	ADP
cana-5024	271	34	dermoscopy	dermoscopy	NOUN
cana-5024	271	35	images	image	NOUN
cana-5024	271	36	using	use	VERB
cana-5024	271	37	a	a	DET
cana-5024	271	38	neural	neural	ADJ
cana-5024	271	39	network	network	NOUN
cana-5024	271	40	ensemble	ensemble	ADJ
cana-5024	271	41	model	model	NOUN
cana-5024	271	42	,	,	PUNCT
cana-5024	271	43	"	"	PUNCT
cana-5024	271	44	ieee	ieee	NOUN
cana-5024	271	45	trans	tran	NOUN
cana-5024	271	46	.	.	PROPN
cana-5024	271	47	med	med	PROPN
cana-5024	271	48	.	.	PUNCT
cana-5024	271	49	imaging	imaging	PROPN
cana-5024	271	50	,	,	PUNCT
cana-5024	271	51	vol	vol	NOUN
cana-5024	271	52	.	.	PROPN
cana-5024	271	53	36	36	NUM
cana-5024	271	54	,	,	PUNCT
cana-5024	271	55	no	no	INTJ
cana-5024	271	56	.	.	NOUN
cana-5024	271	57	3	3	NUM
cana-5024	271	58	,	,	PUNCT
cana-5024	271	59	pp	pp	ADJ
cana-5024	271	60	.	.	PUNCT
cana-5024	272	1	849–858	849–858	NUM
cana-5024	272	2	,	,	PUNCT
cana-5024	272	3	2017	2017	NUM
cana-5024	272	4	.	.	PUNCT
cana-5024	273	1	[	[	X
cana-5024	273	2	29	29	NUM
cana-5024	273	3	]	]	X
cana-5024	273	4	yousuf	yousuf	PROPN
cana-5024	273	5	,	,	PUNCT
cana-5024	273	6	m.	m.	NOUN
cana-5024	273	7	,	,	PUNCT
cana-5024	273	8	asghar	asghar	PROPN
cana-5024	273	9	,	,	PUNCT
cana-5024	273	10	s.	s.	PROPN
cana-5024	273	11	,	,	PUNCT
cana-5024	273	12	ramzan	ramzan	PROPN
cana-5024	273	13	,	,	PUNCT
cana-5024	273	14	m.	m.	NOUN
cana-5024	273	15	,	,	PUNCT
cana-5024	273	16	and	and	CCONJ
cana-5024	273	17	jamil	jamil	PROPN
cana-5024	273	18	,	,	PUNCT
cana-5024	273	19	m.	m.	NOUN
cana-5024	273	20	,	,	PUNCT
cana-5024	273	21	"	"	PUNCT
cana-5024	273	22	a	a	DET
cana-5024	273	23	novel	novel	ADJ
cana-5024	273	24	particle	particle	NOUN
cana-5024	273	25	swarm	swarm	NOUN
cana-5024	273	26	optimization	optimization	NOUN
cana-5024	273	27	-	-	PUNCT
cana-5024	273	28	based	base	VERB
cana-5024	273	29	deep	deep	ADJ
cana-5024	273	30	learning	learning	NOUN
cana-5024	273	31	system	system	NOUN
cana-5024	273	32	for	for	ADP
cana-5024	273	33	covid-19	covid-19	PROPN
cana-5024	273	34	diagnosis	diagnosis	NOUN
cana-5024	273	35	using	use	VERB
cana-5024	273	36	chest	chest	NOUN
cana-5024	273	37	x	x	NOUN
cana-5024	273	38	-	-	NOUN
cana-5024	273	39	ray	ray	NOUN
cana-5024	273	40	images	image	NOUN
cana-5024	273	41	,	,	PUNCT
cana-5024	273	42	"	"	PUNCT
cana-5024	273	43	comput	comput	NOUN
cana-5024	273	44	.	.	PUNCT
cana-5024	274	1	biol	biol	PROPN
cana-5024	274	2	.	.	PUNCT
cana-5024	275	1	med	med	PROPN
cana-5024	275	2	.	.	PROPN
cana-5024	275	3	,	,	PUNCT
cana-5024	275	4	vol	vol	NOUN
cana-5024	275	5	.	.	PUNCT
cana-5024	276	1	143	143	NUM
cana-5024	276	2	,	,	PUNCT
cana-5024	276	3	p.	p.	NOUN
cana-5024	276	4	105198	105198	NUM
cana-5024	276	5	,	,	PUNCT
cana-5024	276	6	2022	2022	NUM
cana-5024	276	7	.	.	PUNCT
cana-5024	277	1	communications	communication	NOUN
cana-5024	277	2	on	on	ADP
cana-5024	277	3	applied	apply	VERB
cana-5024	277	4	nonlinear	nonlinear	ADJ
cana-5024	277	5	analysis	analysis	NOUN
cana-5024	277	6	issn	issn	NOUN
cana-5024	277	7	:	:	PUNCT
cana-5024	277	8	1074	1074	NUM
cana-5024	277	9	-	-	PUNCT
cana-5024	277	10	133x	133x	NUM
cana-5024	277	11	vol	vol	VERB
cana-5024	277	12	32	32	NUM
cana-5024	277	13	no.1s	no.1s	PROPN
cana-5024	277	14	(	(	PUNCT
cana-5024	277	15	2025	2025	NUM
cana-5024	277	16	)	)	PUNCT
cana-5024	277	17	654	654	NUM
cana-5024	277	18	https://internationalpubls.com	https://internationalpubls.com	X
cana-5024	278	1	[	[	X
cana-5024	278	2	30	30	NUM
cana-5024	278	3	]	]	X
cana-5024	278	4	yu	yu	PROPN
cana-5024	278	5	,	,	PUNCT
cana-5024	278	6	l.	l.	PROPN
cana-5024	278	7	,	,	PUNCT
cana-5024	278	8	chen	chen	PROPN
cana-5024	278	9	,	,	PUNCT
cana-5024	278	10	h.	h.	PROPN
cana-5024	278	11	,	,	PUNCT
cana-5024	278	12	dou	dou	PROPN
cana-5024	278	13	,	,	PUNCT
cana-5024	278	14	q.	q.	PROPN
cana-5024	278	15	,	,	PUNCT
cana-5024	278	16	qin	qin	PROPN
cana-5024	278	17	,	,	PUNCT
cana-5024	278	18	j.	j.	PROPN
cana-5024	278	19	,	,	PUNCT
cana-5024	278	20	and	and	CCONJ
cana-5024	278	21	heng	heng	PROPN
cana-5024	278	22	,	,	PUNCT
cana-5024	278	23	p.	p.	NOUN
cana-5024	278	24	a.	a.	NOUN
cana-5024	278	25	,	,	PUNCT
cana-5024	278	26	"	"	PUNCT
cana-5024	278	27	automated	automate	VERB
cana-5024	278	28	melanoma	melanoma	NOUN
cana-5024	278	29	recognition	recognition	NOUN
cana-5024	278	30	in	in	ADP
cana-5024	278	31	dermoscopy	dermoscopy	NOUN
cana-5024	278	32	images	image	NOUN
cana-5024	278	33	via	via	ADP
cana-5024	278	34	very	very	ADV
cana-5024	278	35	deep	deep	ADJ
cana-5024	278	36	residual	residual	ADJ
cana-5024	278	37	networks	network	NOUN
cana-5024	278	38	,	,	PUNCT
cana-5024	278	39	"	"	PUNCT
cana-5024	278	40	ieee	ieee	NOUN
cana-5024	278	41	trans	tran	NOUN
cana-5024	278	42	.	.	PROPN
cana-5024	279	1	med	med	PROPN
cana-5024	279	2	.	.	PUNCT
cana-5024	279	3	imaging	imaging	PROPN
cana-5024	279	4	,	,	PUNCT
cana-5024	279	5	vol	vol	NOUN
cana-5024	279	6	.	.	PROPN
cana-5024	279	7	36	36	NUM
cana-5024	279	8	,	,	PUNCT
cana-5024	279	9	no	no	INTJ
cana-5024	279	10	.	.	NOUN
cana-5024	279	11	4	4	NUM
cana-5024	279	12	,	,	PUNCT
cana-5024	279	13	pp	pp	ADJ
cana-5024	279	14	.	.	PUNCT
cana-5024	279	15	994–1004	994–1004	NUM
cana-5024	279	16	,	,	PUNCT
cana-5024	279	17	2017	2017	NUM
cana-5024	279	18	.	.	PUNCT
cana-5024	280	1	[	[	X
cana-5024	280	2	31	31	NUM
cana-5024	280	3	]	]	SYM
cana-5024	280	4	yu	yu	PROPN
cana-5024	280	5	,	,	PUNCT
cana-5024	280	6	z.	z.	PROPN
cana-5024	280	7	,	,	PUNCT
cana-5024	280	8	jiang	jiang	PROPN
cana-5024	280	9	,	,	PUNCT
cana-5024	280	10	x.	x.	PROPN
cana-5024	280	11	,	,	PUNCT
cana-5024	280	12	zhou	zhou	PROPN
cana-5024	280	13	,	,	PUNCT
cana-5024	280	14	f.	f.	PROPN
cana-5024	280	15	,	,	PUNCT
cana-5024	280	16	qin	qin	PROPN
cana-5024	280	17	,	,	PUNCT
cana-5024	280	18	j.	j.	PROPN
cana-5024	280	19	,	,	PUNCT
cana-5024	280	20	ni	ni	PROPN
cana-5024	280	21	,	,	PUNCT
cana-5024	280	22	d.	d.	PROPN
cana-5024	280	23	,	,	PUNCT
cana-5024	280	24	chen	chen	PROPN
cana-5024	280	25	,	,	PUNCT
cana-5024	280	26	s.	s.	PROPN
cana-5024	280	27	,	,	PUNCT
cana-5024	280	28	et	et	PROPN
cana-5024	280	29	al	al	PROPN
cana-5024	280	30	.	.	PROPN
cana-5024	280	31	,	,	PUNCT
cana-5024	280	32	"	"	PUNCT
cana-5024	280	33	melanoma	melanoma	NOUN
cana-5024	280	34	recognition	recognition	NOUN
cana-5024	280	35	in	in	ADP
cana-5024	280	36	dermoscopy	dermoscopy	NOUN
cana-5024	280	37	images	image	NOUN
cana-5024	280	38	via	via	ADP
cana-5024	280	39	a	a	DET
cana-5024	280	40	deep	deep	ADJ
cana-5024	280	41	residual	residual	ADJ
cana-5024	280	42	network	network	NOUN
cana-5024	280	43	,	,	PUNCT
cana-5024	280	44	"	"	PUNCT
cana-5024	280	45	ieee	ieee	NOUN
cana-5024	280	46	access	access	NOUN
cana-5024	280	47	,	,	PUNCT
cana-5024	280	48	vol	vol	NOUN
cana-5024	280	49	.	.	PROPN
cana-5024	280	50	8	8	NUM
cana-5024	280	51	,	,	PUNCT
cana-5024	280	52	pp	pp	ADJ
cana-5024	280	53	.	.	PUNCT
cana-5024	280	54	89674–89685	89674–89685	NUM
cana-5024	280	55	,	,	PUNCT
cana-5024	280	56	2020	2020	NUM
cana-5024	280	57	.	.	PUNCT
cana-5024	281	1	[	[	X
cana-5024	281	2	32	32	NUM
cana-5024	281	3	]	]	PUNCT
cana-5024	281	4	zawbaa	zawbaa	PROPN
cana-5024	281	5	,	,	PUNCT
cana-5024	281	6	h.	h.	PROPN
cana-5024	281	7	,	,	PUNCT
cana-5024	281	8	ahmed	ahmed	PROPN
cana-5024	281	9	,	,	PUNCT
cana-5024	281	10	m.	m.	NOUN
cana-5024	281	11	s.	s.	PROPN
cana-5024	281	12	,	,	PUNCT
cana-5024	281	13	anter	anter	ADV
cana-5024	281	14	,	,	PUNCT
cana-5024	281	15	a.	a.	NOUN
cana-5024	281	16	m.	m.	NOUN
cana-5024	281	17	,	,	PUNCT
cana-5024	281	18	and	and	CCONJ
cana-5024	281	19	hassanien	hassanien	NOUN
cana-5024	281	20	,	,	PUNCT
cana-5024	281	21	a.	a.	PROPN
cana-5024	281	22	e.	e.	PROPN
cana-5024	281	23	,	,	PUNCT
cana-5024	281	24	"	"	PUNCT
cana-5024	281	25	skin	skin	NOUN
cana-5024	281	26	lesion	lesion	NOUN
cana-5024	281	27	detection	detection	NOUN
cana-5024	281	28	using	use	VERB
cana-5024	281	29	cnn	cnn	PROPN
cana-5024	281	30	with	with	ADP
cana-5024	281	31	genetic	genetic	ADJ
cana-5024	281	32	algorithm	algorithm	NOUN
cana-5024	281	33	-	-	PUNCT
cana-5024	281	34	based	base	VERB
cana-5024	281	35	hyperparameter	hyperparameter	NOUN
cana-5024	281	36	tuning	tuning	NOUN
cana-5024	281	37	,	,	PUNCT
cana-5024	281	38	"	"	PUNCT
cana-5024	281	39	comput	comput	NOUN
cana-5024	281	40	.	.	PUNCT
cana-5024	282	1	biol	biol	PROPN
cana-5024	282	2	.	.	PUNCT
cana-5024	283	1	med	med	PROPN
cana-5024	283	2	.	.	PROPN
cana-5024	283	3	,	,	PUNCT
cana-5024	283	4	vol	vol	NOUN
cana-5024	283	5	.	.	PROPN
cana-5024	283	6	145	145	NUM
cana-5024	283	7	,	,	PUNCT
cana-5024	283	8	p.	p.	NOUN
cana-5024	283	9	105402	105402	NUM
cana-5024	283	10	,	,	PUNCT
cana-5024	283	11	2022	2022	NUM
cana-5024	283	12	.	.	PUNCT
cana-5024	284	1	[	[	X
cana-5024	284	2	33	33	NUM
cana-5024	284	3	]	]	X
cana-5024	284	4	zhang	zhang	PROPN
cana-5024	284	5	,	,	PUNCT
cana-5024	284	6	y.	y.	PROPN
cana-5024	284	7	,	,	PUNCT
cana-5024	284	8	yang	yang	PROPN
cana-5024	284	9	,	,	PUNCT
cana-5024	284	10	l.	l.	PROPN
cana-5024	284	11	,	,	PUNCT
cana-5024	284	12	zheng	zheng	PROPN
cana-5024	284	13	,	,	PUNCT
cana-5024	284	14	y.	y.	PROPN
cana-5024	284	15	,	,	PUNCT
cana-5024	284	16	and	and	CCONJ
cana-5024	284	17	wang	wang	PROPN
cana-5024	284	18	,	,	PUNCT
cana-5024	284	19	s.	s.	PROPN
cana-5024	284	20	,	,	PUNCT
cana-5024	284	21	"	"	PUNCT
cana-5024	284	22	skin	skin	NOUN
cana-5024	284	23	lesion	lesion	NOUN
cana-5024	284	24	classification	classification	NOUN
cana-5024	284	25	in	in	ADP
cana-5024	284	26	dermoscopy	dermoscopy	NOUN
cana-5024	284	27	images	image	NOUN
cana-5024	284	28	using	use	VERB
cana-5024	284	29	ensemble	ensemble	ADJ
cana-5024	284	30	of	of	ADP
cana-5024	284	31	deep	deep	ADJ
cana-5024	284	32	learning	learning	NOUN
cana-5024	284	33	models	model	NOUN
cana-5024	284	34	,	,	PUNCT
cana-5024	284	35	"	"	PUNCT
cana-5024	284	36	ieee	ieee	NOUN
cana-5024	284	37	access	access	NOUN
cana-5024	284	38	,	,	PUNCT
cana-5024	284	39	vol	vol	NOUN
cana-5024	284	40	.	.	PROPN
cana-5024	284	41	8	8	NUM
cana-5024	284	42	,	,	PUNCT
cana-5024	284	43	pp	pp	ADJ
cana-5024	284	44	.	.	PUNCT
cana-5024	285	1	11285–11292	11285–11292	NUM
cana-5024	285	2	,	,	PUNCT
cana-5024	285	3	2020	2020	NUM
cana-5024	285	4	.	.	PUNCT