id	sid	tid	token	lemma	pos
cana-1016	1	1	communications	communication	NOUN
cana-1016	1	2	on	on	ADP
cana-1016	1	3	applied	apply	VERB
cana-1016	1	4	nonlinear	nonlinear	ADJ
cana-1016	1	5	analysis	analysis	NOUN
cana-1016	1	6	issn	issn	NOUN
cana-1016	1	7	:	:	PUNCT
cana-1016	1	8	1074	1074	NUM
cana-1016	1	9	-	-	PUNCT
cana-1016	1	10	133x	133x	NUM
cana-1016	1	11	vol	vol	NOUN
cana-1016	1	12	31	31	NUM
cana-1016	1	13	no	no	NOUN
cana-1016	1	14	.	.	PUNCT
cana-1016	2	1	5s	5s	NUM
cana-1016	2	2	(	(	PUNCT
cana-1016	2	3	2024	2024	NUM
cana-1016	2	4	)	)	PUNCT
cana-1016	2	5	213	213	NUM
cana-1016	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	2	7	skin	skin	NOUN
cana-1016	2	8	cancer	cancer	NOUN
cana-1016	2	9	diagnosis	diagnosis	NOUN
cana-1016	2	10	with	with	ADP
cana-1016	2	11	a	a	DET
cana-1016	2	12	customized	customize	VERB
cana-1016	2	13	cnn	cnn	PROPN
cana-1016	2	14	model	model	NOUN
cana-1016	2	15	using	use	VERB
cana-1016	2	16	deep	deep	ADJ
cana-1016	2	17	learning	learning	NOUN
cana-1016	2	18	approaches	approach	NOUN
cana-1016	2	19	kiran	kiran	PROPN
cana-1016	2	20	likhar1	likhar1	PROPN
cana-1016	2	21	,	,	PUNCT
cana-1016	2	22	dr	dr	PROPN
cana-1016	2	23	.	.	PROPN
cana-1016	2	24	sonali	sonali	PROPN
cana-1016	2	25	ridhorkar2	ridhorkar2	PROPN
cana-1016	3	1	1research	1research	NUM
cana-1016	3	2	scholar(ph.d	scholar(ph.d	NOUN
cana-1016	3	3	)	)	PUNCT
cana-1016	3	4	,	,	PUNCT
cana-1016	3	5	department	department	NOUN
cana-1016	3	6	of	of	ADP
cana-1016	3	7	cse	cse	PROPN
cana-1016	3	8	,	,	PUNCT
cana-1016	3	9	g	g	PROPN
cana-1016	3	10	h	h	PROPN
cana-1016	3	11	raisoni	raisoni	PROPN
cana-1016	3	12	university	university	PROPN
cana-1016	3	13	amravati	amravati	PROPN
cana-1016	3	14	,	,	PUNCT
cana-1016	3	15	india	india	PROPN
cana-1016	3	16	.	.	PUNCT
cana-1016	3	17	email	email	NOUN
cana-1016	3	18	:	:	PUNCT
cana-1016	3	19	kiran.likhar24@gmail.com	kiran.likhar24@gmail.com	X
cana-1016	3	20	2associate	2associate	NUM
cana-1016	3	21	professor	professor	NOUN
cana-1016	3	22	,	,	PUNCT
cana-1016	3	23	department	department	PROPN
cana-1016	3	24	of	of	ADP
cana-1016	3	25	cse	cse	PROPN
cana-1016	3	26	,	,	PUNCT
cana-1016	3	27	g	g	PROPN
cana-1016	3	28	h	h	PROPN
cana-1016	3	29	raisoni	raisoni	PROPN
cana-1016	3	30	institute	institute	PROPN
cana-1016	3	31	of	of	ADP
cana-1016	3	32	engineering	engineering	NOUN
cana-1016	3	33	and	and	CCONJ
cana-1016	3	34	technology	technology	NOUN
cana-1016	3	35	,	,	PUNCT
cana-1016	3	36	nagpur	nagpur	PROPN
cana-1016	3	37	,	,	PUNCT
cana-1016	3	38	india	india	PROPN
cana-1016	3	39	.	.	PUNCT
cana-1016	3	40	email	email	NOUN
cana-1016	3	41	:	:	PUNCT
cana-1016	4	1	sonaliridhorkar@gmail.com	sonaliridhorkar@gmail.com	X
cana-1016	4	2	article	article	NOUN
cana-1016	4	3	history	history	NOUN
cana-1016	4	4	:	:	PUNCT
cana-1016	4	5	received	receive	VERB
cana-1016	4	6	:	:	PUNCT
cana-1016	4	7	11	11	NUM
cana-1016	4	8	-	-	SYM
cana-1016	4	9	05	05	NUM
cana-1016	4	10	-	-	PUNCT
cana-1016	4	11	2024	2024	NUM
cana-1016	4	12	revised	revise	VERB
cana-1016	4	13	:	:	PUNCT
cana-1016	4	14	23	23	NUM
cana-1016	4	15	-	-	SYM
cana-1016	4	16	06	06	NUM
cana-1016	4	17	-	-	PUNCT
cana-1016	4	18	2024	2024	NUM
cana-1016	4	19	accepted	accept	VERB
cana-1016	4	20	:	:	PUNCT
cana-1016	4	21	05	05	NUM
cana-1016	4	22	-	-	PUNCT
cana-1016	4	23	07	07	NUM
cana-1016	4	24	-	-	PUNCT
cana-1016	4	25	2024	2024	NUM
cana-1016	4	26	abstract	abstract	NOUN
cana-1016	4	27	:	:	PUNCT
cana-1016	4	28	medical	medical	ADJ
cana-1016	4	29	imaging	imaging	NOUN
cana-1016	4	30	has	have	VERB
cana-1016	4	31	a	a	DET
cana-1016	4	32	significant	significant	ADJ
cana-1016	4	33	challenge	challenge	NOUN
cana-1016	4	34	in	in	ADP
cana-1016	4	35	accurately	accurately	ADV
cana-1016	4	36	classifying	classify	VERB
cana-1016	4	37	skin	skin	NOUN
cana-1016	4	38	lesions	lesion	NOUN
cana-1016	4	39	into	into	ADP
cana-1016	4	40	benign	benign	ADJ
cana-1016	4	41	and	and	CCONJ
cana-1016	4	42	malignant	malignant	ADJ
cana-1016	4	43	classifications	classification	NOUN
cana-1016	4	44	.	.	PUNCT
cana-1016	5	1	to	to	PART
cana-1016	5	2	solve	solve	VERB
cana-1016	5	3	this	this	DET
cana-1016	5	4	issue	issue	NOUN
cana-1016	5	5	,	,	PUNCT
cana-1016	5	6	we	we	PRON
cana-1016	5	7	have	have	AUX
cana-1016	5	8	developed	develop	VERB
cana-1016	5	9	a	a	DET
cana-1016	5	10	technique	technique	NOUN
cana-1016	5	11	that	that	PRON
cana-1016	5	12	utilizes	utilize	VERB
cana-1016	5	13	a	a	DET
cana-1016	5	14	custom	custom	NOUN
cana-1016	5	15	convolutional	convolutional	ADJ
cana-1016	5	16	neural	neural	ADJ
cana-1016	5	17	network	network	NOUN
cana-1016	5	18	classifier	classifier	NOUN
cana-1016	5	19	with	with	ADP
cana-1016	5	20	a	a	DET
cana-1016	5	21	support	support	NOUN
cana-1016	5	22	vector	vector	NOUN
cana-1016	5	23	machine	machine	NOUN
cana-1016	5	24	.	.	PUNCT
cana-1016	6	1	our	our	PRON
cana-1016	6	2	customized	customized	ADJ
cana-1016	6	3	cnn	cnn	PROPN
cana-1016	6	4	architecture	architecture	NOUN
cana-1016	6	5	is	be	AUX
cana-1016	6	6	designed	design	VERB
cana-1016	6	7	to	to	PART
cana-1016	6	8	address	address	VERB
cana-1016	6	9	the	the	DET
cana-1016	6	10	core	core	NOUN
cana-1016	6	11	issue	issue	NOUN
cana-1016	6	12	of	of	ADP
cana-1016	6	13	skin	skin	NOUN
cana-1016	6	14	cancer	cancer	NOUN
cana-1016	6	15	categorization	categorization	NOUN
cana-1016	6	16	.	.	PUNCT
cana-1016	7	1	densenet121	densenet121	PROPN
cana-1016	7	2	,	,	PUNCT
cana-1016	7	3	densenet201	densenet201	PROPN
cana-1016	7	4	,	,	PUNCT
cana-1016	7	5	inceptionv3	inceptionv3	NOUN
cana-1016	7	6	,	,	PUNCT
cana-1016	7	7	inceptionresnetv2	inceptionresnetv2	PROPN
cana-1016	7	8	,	,	PUNCT
cana-1016	7	9	mobilenet	mobilenet	NOUN
cana-1016	7	10	,	,	PUNCT
cana-1016	7	11	resnet50v2	resnet50v2	PROPN
cana-1016	7	12	,	,	PUNCT
cana-1016	7	13	resnet101	resnet101	PROPN
cana-1016	7	14	,	,	PUNCT
cana-1016	7	15	vgg16	vgg16	PROPN
cana-1016	7	16	,	,	PUNCT
cana-1016	7	17	vgg19	vgg19	PROPN
cana-1016	7	18	,	,	PUNCT
cana-1016	7	19	and	and	CCONJ
cana-1016	7	20	xception	xception	NOUN
cana-1016	7	21	are	be	AUX
cana-1016	7	22	among	among	ADP
cana-1016	7	23	the	the	DET
cana-1016	7	24	most	most	ADV
cana-1016	7	25	prominent	prominent	ADJ
cana-1016	7	26	pre	pre	ADJ
cana-1016	7	27	-	-	ADJ
cana-1016	7	28	trained	train	VERB
cana-1016	7	29	models	model	NOUN
cana-1016	7	30	evaluated	evaluate	VERB
cana-1016	7	31	in	in	ADP
cana-1016	7	32	our	our	PRON
cana-1016	7	33	study	study	NOUN
cana-1016	7	34	.	.	PUNCT
cana-1016	8	1	the	the	DET
cana-1016	8	2	customized	customize	VERB
cana-1016	8	3	cnn	cnn	PROPN
cana-1016	8	4	exceeds	exceed	VERB
cana-1016	8	5	existing	exist	VERB
cana-1016	8	6	models	model	NOUN
cana-1016	8	7	on	on	ADP
cana-1016	8	8	an	an	DET
cana-1016	8	9	average	average	ADJ
cana-1016	8	10	basis	basis	NOUN
cana-1016	8	11	,	,	PUNCT
cana-1016	8	12	displaying	display	VERB
cana-1016	8	13	greater	great	ADJ
cana-1016	8	14	accuracy	accuracy	NOUN
cana-1016	8	15	,	,	PUNCT
cana-1016	8	16	recall	recall	NOUN
cana-1016	8	17	,	,	PUNCT
cana-1016	8	18	precision	precision	NOUN
cana-1016	8	19	,	,	PUNCT
cana-1016	8	20	and	and	CCONJ
cana-1016	8	21	f1	f1	NOUN
cana-1016	8	22	-	-	PUNCT
cana-1016	8	23	score	score	NOUN
cana-1016	8	24	for	for	ADP
cana-1016	8	25	both	both	CCONJ
cana-1016	8	26	benign	benign	ADJ
cana-1016	8	27	and	and	CCONJ
cana-1016	8	28	malignant	malignant	ADJ
cana-1016	8	29	cases	case	NOUN
cana-1016	8	30	.	.	PUNCT
cana-1016	9	1	this	this	DET
cana-1016	9	2	technique	technique	NOUN
cana-1016	9	3	has	have	VERB
cana-1016	9	4	significant	significant	ADJ
cana-1016	9	5	prospects	prospect	NOUN
cana-1016	9	6	for	for	ADP
cana-1016	9	7	enhancing	enhance	VERB
cana-1016	9	8	early	early	ADJ
cana-1016	9	9	skin	skin	NOUN
cana-1016	9	10	cancer	cancer	NOUN
cana-1016	9	11	diagnosis	diagnosis	NOUN
cana-1016	9	12	,	,	PUNCT
cana-1016	9	13	perhaps	perhaps	ADV
cana-1016	9	14	leading	lead	VERB
cana-1016	9	15	to	to	ADP
cana-1016	9	16	better	well	ADJ
cana-1016	9	17	patient	patient	ADJ
cana-1016	9	18	results	result	NOUN
cana-1016	9	19	and	and	CCONJ
cana-1016	9	20	more	more	ADV
cana-1016	9	21	efficient	efficient	ADJ
cana-1016	9	22	medical	medical	ADJ
cana-1016	9	23	treatments	treatment	NOUN
cana-1016	9	24	.	.	PUNCT
cana-1016	10	1	keywords	keyword	NOUN
cana-1016	10	2	:	:	PUNCT
cana-1016	10	3	artificial	artificial	ADJ
cana-1016	10	4	intelligence	intelligence	NOUN
cana-1016	10	5	,	,	PUNCT
cana-1016	10	6	skin	skin	NOUN
cana-1016	10	7	cancer	cancer	NOUN
cana-1016	10	8	detection	detection	NOUN
cana-1016	10	9	,	,	PUNCT
cana-1016	10	10	deep	deep	ADJ
cana-1016	10	11	learning	learning	NOUN
cana-1016	10	12	,	,	PUNCT
cana-1016	10	13	pretrained	pretraine	VERB
cana-1016	10	14	models	model	NOUN
cana-1016	10	15	,	,	PUNCT
cana-1016	10	16	cnn	cnn	PROPN
cana-1016	10	17	.	.	PROPN
cana-1016	11	1	1	1	X
cana-1016	11	2	.	.	X
cana-1016	11	3	introduction	introduction	NOUN
cana-1016	11	4	skin	skin	NOUN
cana-1016	11	5	cancer	cancer	NOUN
cana-1016	11	6	detection	detection	NOUN
cana-1016	11	7	is	be	AUX
cana-1016	11	8	a	a	DET
cana-1016	11	9	critical	critical	ADJ
cana-1016	11	10	aspect	aspect	NOUN
cana-1016	11	11	of	of	ADP
cana-1016	11	12	healthcare	healthcare	NOUN
cana-1016	11	13	due	due	ADP
cana-1016	11	14	to	to	ADP
cana-1016	11	15	its	its	PRON
cana-1016	11	16	increasing	increase	VERB
cana-1016	11	17	prevalence	prevalence	NOUN
cana-1016	11	18	worldwide	worldwide	ADV
cana-1016	11	19	.	.	PUNCT
cana-1016	12	1	the	the	DET
cana-1016	12	2	conventional	conventional	ADJ
cana-1016	12	3	methods	method	NOUN
cana-1016	12	4	of	of	ADP
cana-1016	12	5	visual	visual	ADJ
cana-1016	12	6	examination	examination	NOUN
cana-1016	12	7	used	use	VERB
cana-1016	12	8	by	by	ADP
cana-1016	12	9	dermatologists	dermatologist	NOUN
cana-1016	12	10	for	for	ADP
cana-1016	12	11	detecting	detect	VERB
cana-1016	12	12	skin	skin	NOUN
cana-1016	12	13	cancer	cancer	NOUN
cana-1016	12	14	are	be	AUX
cana-1016	12	15	subjective	subjective	ADJ
cana-1016	12	16	.	.	PUNCT
cana-1016	13	1	the	the	DET
cana-1016	13	2	use	use	NOUN
cana-1016	13	3	of	of	ADP
cana-1016	13	4	dl	dl	PROPN
cana-1016	13	5	techniques	technique	NOUN
cana-1016	13	6	has	have	AUX
cana-1016	13	7	gained	gain	VERB
cana-1016	13	8	significant	significant	ADJ
cana-1016	13	9	attention	attention	NOUN
cana-1016	13	10	for	for	ADP
cana-1016	13	11	improving	improve	VERB
cana-1016	13	12	the	the	DET
cana-1016	13	13	accuracy	accuracy	NOUN
cana-1016	13	14	and	and	CCONJ
cana-1016	13	15	efficiency	efficiency	NOUN
cana-1016	13	16	of	of	ADP
cana-1016	13	17	skin	skin	NOUN
cana-1016	13	18	cancer	cancer	NOUN
cana-1016	13	19	detection	detection	NOUN
cana-1016	13	20	.	.	PUNCT
cana-1016	14	1	to	to	PART
cana-1016	14	2	offer	offer	VERB
cana-1016	14	3	an	an	DET
cana-1016	14	4	extensive	extensive	ADJ
cana-1016	14	5	analysis	analysis	NOUN
cana-1016	14	6	of	of	ADP
cana-1016	14	7	deep	deep	ADJ
cana-1016	14	8	learning	learning	NOUN
cana-1016	14	9	approaches	approach	NOUN
cana-1016	14	10	in	in	ADP
cana-1016	14	11	the	the	DET
cana-1016	14	12	identification	identification	NOUN
cana-1016	14	13	of	of	ADP
cana-1016	14	14	skin	skin	NOUN
cana-1016	14	15	cancer	cancer	NOUN
cana-1016	14	16	through	through	ADP
cana-1016	14	17	integrating	integrate	VERB
cana-1016	14	18	various	various	ADJ
cana-1016	14	19	datasets	dataset	NOUN
cana-1016	14	20	and	and	CCONJ
cana-1016	14	21	reviewing	review	VERB
cana-1016	14	22	relevant	relevant	ADJ
cana-1016	14	23	literature	literature	NOUN
cana-1016	14	24	[	[	X
cana-1016	14	25	1	1	NUM
cana-1016	14	26	]	]	PUNCT
cana-1016	14	27	.	.	PUNCT
cana-1016	15	1	by	by	ADP
cana-1016	15	2	examining	examine	VERB
cana-1016	15	3	existing	exist	VERB
cana-1016	15	4	study	study	NOUN
cana-1016	15	5	,	,	PUNCT
cana-1016	15	6	the	the	DET
cana-1016	15	7	objective	objective	NOUN
cana-1016	15	8	is	be	AUX
cana-1016	15	9	to	to	PART
cana-1016	15	10	identify	identify	VERB
cana-1016	15	11	the	the	DET
cana-1016	15	12	latest	late	ADJ
cana-1016	15	13	methodologies	methodology	NOUN
cana-1016	15	14	,	,	PUNCT
cana-1016	15	15	address	address	NOUN
cana-1016	15	16	challenges	challenge	NOUN
cana-1016	15	17	,	,	PUNCT
cana-1016	15	18	and	and	CCONJ
cana-1016	15	19	propose	propose	VERB
cana-1016	15	20	potential	potential	ADJ
cana-1016	15	21	solutions	solution	NOUN
cana-1016	15	22	to	to	PART
cana-1016	15	23	increase	increase	VERB
cana-1016	15	24	the	the	DET
cana-1016	15	25	accuracy	accuracy	NOUN
cana-1016	15	26	and	and	CCONJ
cana-1016	15	27	generalizability	generalizability	NOUN
cana-1016	15	28	of	of	ADP
cana-1016	15	29	skin	skin	NOUN
cana-1016	15	30	cancer	cancer	NOUN
cana-1016	15	31	models	model	NOUN
cana-1016	15	32	for	for	ADP
cana-1016	15	33	detection	detection	NOUN
cana-1016	15	34	.	.	PUNCT
cana-1016	16	1	to	to	PART
cana-1016	16	2	accomplish	accomplish	VERB
cana-1016	16	3	this	this	DET
cana-1016	16	4	goal	goal	NOUN
cana-1016	16	5	,	,	PUNCT
cana-1016	16	6	skin	skin	NOUN
cana-1016	16	7	lesion	lesion	NOUN
cana-1016	16	8	datasets	dataset	NOUN
cana-1016	16	9	containing	contain	VERB
cana-1016	16	10	dermoscopy	dermoscopy	NOUN
cana-1016	16	11	images	image	NOUN
cana-1016	16	12	,	,	PUNCT
cana-1016	16	13	clinical	clinical	ADJ
cana-1016	16	14	photographs	photograph	NOUN
cana-1016	16	15	,	,	PUNCT
cana-1016	16	16	and	and	CCONJ
cana-1016	16	17	histopathological	histopathological	ADJ
cana-1016	16	18	slides	slide	NOUN
cana-1016	16	19	will	will	AUX
cana-1016	16	20	be	be	AUX
cana-1016	16	21	collected	collect	VERB
cana-1016	16	22	and	and	CCONJ
cana-1016	16	23	curated	curate	VERB
cana-1016	16	24	.	.	PUNCT
cana-1016	17	1	these	these	DET
cana-1016	17	2	datasets	dataset	NOUN
cana-1016	17	3	will	will	AUX
cana-1016	17	4	be	be	AUX
cana-1016	17	5	utilized	utilize	VERB
cana-1016	17	6	in	in	ADP
cana-1016	17	7	dl	dl	PROPN
cana-1016	17	8	technique	technique	NOUN
cana-1016	17	9	training	training	NOUN
cana-1016	17	10	and	and	CCONJ
cana-1016	17	11	evaluation	evaluation	NOUN
cana-1016	17	12	across	across	ADP
cana-1016	17	13	different	different	ADJ
cana-1016	17	14	imaging	imaging	NOUN
cana-1016	17	15	techniques	technique	NOUN
cana-1016	17	16	and	and	CCONJ
cana-1016	17	17	patient	patient	ADJ
cana-1016	17	18	demographics	demographic	NOUN
cana-1016	17	19	.	.	PUNCT
cana-1016	18	1	the	the	DET
cana-1016	18	2	inclusion	inclusion	NOUN
cana-1016	18	3	of	of	ADP
cana-1016	18	4	a	a	DET
cana-1016	18	5	wide	wide	ADJ
cana-1016	18	6	range	range	NOUN
cana-1016	18	7	of	of	ADP
cana-1016	18	8	data	datum	NOUN
cana-1016	18	9	sources	source	NOUN
cana-1016	18	10	will	will	AUX
cana-1016	18	11	enhance	enhance	VERB
cana-1016	18	12	the	the	DET
cana-1016	18	13	reliability	reliability	NOUN
cana-1016	18	14	and	and	CCONJ
cana-1016	18	15	applicability	applicability	NOUN
cana-1016	18	16	of	of	ADP
cana-1016	18	17	the	the	DET
cana-1016	18	18	developed	develop	VERB
cana-1016	18	19	models	model	NOUN
cana-1016	18	20	[	[	X
cana-1016	18	21	2	2	NUM
cana-1016	18	22	]	]	PUNCT
cana-1016	18	23	.	.	PUNCT
cana-1016	19	1	moreover	moreover	ADV
cana-1016	19	2	,	,	PUNCT
cana-1016	19	3	an	an	DET
cana-1016	19	4	extensive	extensive	ADJ
cana-1016	19	5	literature	literature	NOUN
cana-1016	19	6	review	review	NOUN
cana-1016	19	7	will	will	AUX
cana-1016	19	8	be	be	AUX
cana-1016	19	9	conducted	conduct	VERB
cana-1016	19	10	to	to	PART
cana-1016	19	11	identify	identify	VERB
cana-1016	19	12	the	the	DET
cana-1016	19	13	advancements	advancement	NOUN
cana-1016	19	14	and	and	CCONJ
cana-1016	19	15	limitations	limitation	NOUN
cana-1016	19	16	of	of	ADP
cana-1016	19	17	existing	exist	VERB
cana-1016	19	18	deep	deep	ADJ
cana-1016	19	19	learning	learning	NOUN
cana-1016	19	20	approaches	approach	NOUN
cana-1016	19	21	in	in	ADP
cana-1016	19	22	skin	skin	NOUN
cana-1016	19	23	cancer	cancer	NOUN
cana-1016	19	24	detection	detection	NOUN
cana-1016	19	25	.	.	PUNCT
cana-1016	20	1	the	the	DET
cana-1016	20	2	analysis	analysis	NOUN
cana-1016	20	3	will	will	AUX
cana-1016	20	4	focus	focus	VERB
cana-1016	20	5	on	on	ADP
cana-1016	20	6	the	the	DET
cana-1016	20	7	methodologies	methodology	NOUN
cana-1016	20	8	employed	employ	VERB
cana-1016	20	9	,	,	PUNCT
cana-1016	20	10	such	such	ADJ
cana-1016	20	11	as	as	ADP
cana-1016	20	12	feature	feature	NOUN
cana-1016	20	13	extraction	extraction	NOUN
cana-1016	20	14	techniques	technique	NOUN
cana-1016	20	15	,	,	PUNCT
cana-1016	20	16	classification	classification	NOUN
cana-1016	20	17	algorithms	algorithm	NOUN
cana-1016	20	18	,	,	PUNCT
cana-1016	20	19	and	and	CCONJ
cana-1016	20	20	model	model	NOUN
cana-1016	20	21	evaluation	evaluation	NOUN
cana-1016	20	22	metrics	metric	NOUN
cana-1016	20	23	.	.	PUNCT
cana-1016	21	1	by	by	ADP
cana-1016	21	2	understanding	understand	VERB
cana-1016	21	3	the	the	DET
cana-1016	21	4	advantages	advantage	NOUN
cana-1016	21	5	and	and	CCONJ
cana-1016	21	6	disadvantages	disadvantage	NOUN
cana-1016	21	7	of	of	ADP
cana-1016	21	8	certain	certain	ADJ
cana-1016	21	9	strategies	strategy	NOUN
cana-1016	21	10	,	,	PUNCT
cana-1016	21	11	opportunities	opportunity	NOUN
cana-1016	21	12	for	for	ADP
cana-1016	21	13	improvement	improvement	NOUN
cana-1016	21	14	and	and	CCONJ
cana-1016	21	15	innovation	innovation	NOUN
cana-1016	21	16	can	can	AUX
cana-1016	21	17	be	be	AUX
cana-1016	21	18	identified	identify	VERB
cana-1016	21	19	[	[	PUNCT
cana-1016	21	20	3	3	NUM
cana-1016	21	21	]	]	PUNCT
cana-1016	21	22	.	.	PUNCT
cana-1016	22	1	mailto:kiran.likhar24@gmail.com	mailto:kiran.likhar24@gmail.com	X
cana-1016	22	2	communications	communication	NOUN
cana-1016	22	3	on	on	ADP
cana-1016	22	4	applied	apply	VERB
cana-1016	22	5	nonlinear	nonlinear	ADJ
cana-1016	22	6	analysis	analysis	NOUN
cana-1016	22	7	issn	issn	NOUN
cana-1016	22	8	:	:	PUNCT
cana-1016	22	9	1074	1074	NUM
cana-1016	22	10	-	-	PUNCT
cana-1016	22	11	133x	133x	NUM
cana-1016	22	12	vol	vol	NOUN
cana-1016	22	13	31	31	NUM
cana-1016	22	14	no	no	NOUN
cana-1016	22	15	.	.	PUNCT
cana-1016	23	1	5s	5s	NUM
cana-1016	23	2	(	(	PUNCT
cana-1016	23	3	2024	2024	NUM
cana-1016	23	4	)	)	PUNCT
cana-1016	23	5	214	214	NUM
cana-1016	23	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	23	7	1.1	1.1	NUM
cana-1016	23	8	review	review	NOUN
cana-1016	23	9	of	of	ADP
cana-1016	23	10	deep	deep	ADJ
cana-1016	23	11	learning	learning	NOUN
cana-1016	23	12	classifier	classifier	NOUN
cana-1016	23	13	for	for	ADP
cana-1016	23	14	skin	skin	NOUN
cana-1016	23	15	cancer	cancer	NOUN
cana-1016	23	16	detection	detection	NOUN
cana-1016	23	17	deep	deep	ADJ
cana-1016	23	18	learning	learning	NOUN
cana-1016	23	19	has	have	AUX
cana-1016	23	20	emerged	emerge	VERB
cana-1016	23	21	as	as	ADP
cana-1016	23	22	a	a	DET
cana-1016	23	23	revolutionary	revolutionary	ADJ
cana-1016	23	24	force	force	NOUN
cana-1016	23	25	within	within	ADP
cana-1016	23	26	the	the	DET
cana-1016	23	27	dl	dl	PROPN
cana-1016	23	28	sector	sector	NOUN
cana-1016	23	29	,	,	PUNCT
cana-1016	23	30	particularly	particularly	ADV
cana-1016	23	31	within	within	ADP
cana-1016	23	32	the	the	DET
cana-1016	23	33	last	last	ADJ
cana-1016	23	34	few	few	ADJ
cana-1016	23	35	decades	decade	NOUN
cana-1016	23	36	.	.	PUNCT
cana-1016	24	1	it	it	PRON
cana-1016	24	2	is	be	AUX
cana-1016	24	3	recognized	recognize	VERB
cana-1016	24	4	as	as	ADP
cana-1016	24	5	a	a	DET
cana-1016	24	6	sophisticated	sophisticated	ADJ
cana-1016	24	7	subfield	subfield	NOUN
cana-1016	24	8	that	that	PRON
cana-1016	24	9	focuses	focus	VERB
cana-1016	24	10	on	on	ADP
cana-1016	24	11	ann	ann	PROPN
cana-1016	24	12	methods	method	NOUN
cana-1016	24	13	,	,	PUNCT
cana-1016	24	14	drawing	draw	VERB
cana-1016	24	15	inspiration	inspiration	NOUN
cana-1016	24	16	from	from	ADP
cana-1016	24	17	the	the	DET
cana-1016	24	18	structure	structure	NOUN
cana-1016	24	19	and	and	CCONJ
cana-1016	24	20	functionality	functionality	NOUN
cana-1016	24	21	within	within	ADP
cana-1016	24	22	the	the	DET
cana-1016	24	23	human	human	ADJ
cana-1016	24	24	mind	mind	NOUN
cana-1016	24	25	.	.	PUNCT
cana-1016	25	1	dl	dl	PROPN
cana-1016	25	2	techniques	technique	NOUN
cana-1016	25	3	have	have	AUX
cana-1016	25	4	been	be	AUX
cana-1016	25	5	successfully	successfully	ADV
cana-1016	25	6	applied	apply	VERB
cana-1016	25	7	in	in	ADP
cana-1016	25	8	various	various	ADJ
cana-1016	25	9	domains	domain	NOUN
cana-1016	25	10	,	,	PUNCT
cana-1016	25	11	including	include	VERB
cana-1016	25	12	speech	speech	NOUN
cana-1016	25	13	recognition	recognition	NOUN
cana-1016	25	14	,	,	PUNCT
cana-1016	25	15	pattern	pattern	NOUN
cana-1016	25	16	recognition	recognition	NOUN
cana-1016	25	17	,	,	PUNCT
cana-1016	25	18	and	and	CCONJ
cana-1016	25	19	bioinformatics	bioinformatics	NOUN
cana-1016	25	20	,	,	PUNCT
cana-1016	25	21	producing	produce	VERB
cana-1016	25	22	impressive	impressive	ADJ
cana-1016	25	23	results	result	NOUN
cana-1016	25	24	when	when	SCONJ
cana-1016	25	25	compared	compare	VERB
cana-1016	25	26	to	to	ADP
cana-1016	25	27	traditional	traditional	ADJ
cana-1016	25	28	dl	dl	PROPN
cana-1016	25	29	approaches	approach	NOUN
cana-1016	25	30	[	[	X
cana-1016	25	31	4	4	NUM
cana-1016	25	32	]	]	PUNCT
cana-1016	25	33	.	.	PUNCT
cana-1016	26	1	in	in	ADP
cana-1016	26	2	recent	recent	ADJ
cana-1016	26	3	years	year	NOUN
cana-1016	26	4	,	,	PUNCT
cana-1016	26	5	dl	dl	PROPN
cana-1016	26	6	approaches	approach	NOUN
cana-1016	26	7	have	have	AUX
cana-1016	26	8	gained	gain	VERB
cana-1016	26	9	significant	significant	ADJ
cana-1016	26	10	traction	traction	NOUN
cana-1016	26	11	in	in	ADP
cana-1016	26	12	computer	computer	NOUN
cana-1016	26	13	-	-	PUNCT
cana-1016	26	14	based	base	VERB
cana-1016	26	15	skin	skin	NOUN
cana-1016	26	16	cancer	cancer	NOUN
cana-1016	26	17	detection	detection	NOUN
cana-1016	26	18	.	.	PUNCT
cana-1016	27	1	this	this	DET
cana-1016	27	2	research	research	NOUN
cana-1016	27	3	goal	goal	NOUN
cana-1016	27	4	is	be	AUX
cana-1016	27	5	to	to	PART
cana-1016	27	6	provide	provide	VERB
cana-1016	27	7	a	a	DET
cana-1016	27	8	thorough	thorough	ADJ
cana-1016	27	9	and	and	CCONJ
cana-1016	27	10	structured	structured	ADJ
cana-1016	27	11	survey	survey	NOUN
cana-1016	27	12	of	of	ADP
cana-1016	27	13	the	the	DET
cana-1016	27	14	literature	literature	NOUN
cana-1016	27	15	on	on	ADP
cana-1016	27	16	dl	dl	PROPN
cana-1016	27	17	techniques	technique	NOUN
cana-1016	27	18	employed	employ	VERB
cana-1016	27	19	in	in	ADP
cana-1016	27	20	skin	skin	NOUN
cana-1016	27	21	cancer	cancer	NOUN
cana-1016	27	22	detection	detection	NOUN
cana-1016	27	23	.	.	PUNCT
cana-1016	28	1	the	the	DET
cana-1016	28	2	focus	focus	NOUN
cana-1016	28	3	is	be	AUX
cana-1016	28	4	on	on	ADP
cana-1016	28	5	classical	classical	ADJ
cana-1016	28	6	dl	dl	PROPN
cana-1016	28	7	approaches	approach	NOUN
cana-1016	28	8	such	such	ADJ
cana-1016	28	9	as	as	ADP
cana-1016	28	10	cnn	cnn	PROPN
cana-1016	28	11	.	.	PUNCT
cana-1016	29	1	to	to	PART
cana-1016	29	2	ensure	ensure	VERB
cana-1016	29	3	a	a	DET
cana-1016	29	4	valuable	valuable	ADJ
cana-1016	29	5	systematic	systematic	ADJ
cana-1016	29	6	review	review	NOUN
cana-1016	29	7	of	of	ADP
cana-1016	29	8	neural	neural	ADJ
cana-1016	29	9	network	network	NOUN
cana-1016	29	10	-	-	PUNCT
cana-1016	29	11	based	base	VERB
cana-1016	29	12	classification	classification	NOUN
cana-1016	29	13	techniques	technique	NOUN
cana-1016	29	14	for	for	ADP
cana-1016	29	15	identifying	identify	VERB
cana-1016	29	16	skin	skin	NOUN
cana-1016	29	17	cancer	cancer	NOUN
cana-1016	29	18	,	,	PUNCT
cana-1016	29	19	a	a	DET
cana-1016	29	20	rigorous	rigorous	ADJ
cana-1016	29	21	strategy	strategy	NOUN
cana-1016	29	22	was	be	AUX
cana-1016	29	23	devised	devise	VERB
cana-1016	29	24	.	.	PUNCT
cana-1016	30	1	1.2	1.2	NUM
cana-1016	30	2	analyzing	analyze	VERB
cana-1016	30	3	deep	deep	ADJ
cana-1016	30	4	learning	learning	NOUN
cana-1016	30	5	methods	method	NOUN
cana-1016	30	6	for	for	ADP
cana-1016	30	7	the	the	DET
cana-1016	30	8	identification	identification	NOUN
cana-1016	30	9	of	of	ADP
cana-1016	30	10	skin	skin	NOUN
cana-1016	30	11	cancer	cancer	NOUN
cana-1016	30	12	dl	dl	PROPN
cana-1016	30	13	techniques	technique	NOUN
cana-1016	30	14	for	for	ADP
cana-1016	30	15	skin	skin	NOUN
cana-1016	30	16	cancer	cancer	NOUN
cana-1016	30	17	detection	detection	NOUN
cana-1016	30	18	were	be	AUX
cana-1016	30	19	explored	explore	VERB
cana-1016	30	20	.	.	PUNCT
cana-1016	31	1	skin	skin	NOUN
cana-1016	31	2	cancer	cancer	NOUN
cana-1016	31	3	datasets	dataset	NOUN
cana-1016	31	4	were	be	AUX
cana-1016	31	5	integrated	integrate	VERB
cana-1016	31	6	,	,	PUNCT
cana-1016	31	7	and	and	CCONJ
cana-1016	31	8	a	a	DET
cana-1016	31	9	comprehensive	comprehensive	ADJ
cana-1016	31	10	literature	literature	NOUN
cana-1016	31	11	review	review	NOUN
cana-1016	31	12	on	on	ADP
cana-1016	31	13	dl	dl	PROPN
cana-1016	31	14	methods	method	NOUN
cana-1016	31	15	was	be	AUX
cana-1016	31	16	conducted	conduct	VERB
cana-1016	31	17	[	[	X
cana-1016	31	18	5	5	NUM
cana-1016	31	19	]	]	PUNCT
cana-1016	31	20	.	.	PUNCT
cana-1016	32	1	various	various	ADJ
cana-1016	32	2	dl	dl	PROPN
cana-1016	32	3	models	model	NOUN
cana-1016	32	4	were	be	AUX
cana-1016	32	5	applied	apply	VERB
cana-1016	32	6	,	,	PUNCT
cana-1016	32	7	and	and	CCONJ
cana-1016	32	8	their	their	PRON
cana-1016	32	9	performances	performance	NOUN
cana-1016	32	10	were	be	AUX
cana-1016	32	11	compared	compare	VERB
cana-1016	32	12	.	.	PUNCT
cana-1016	33	1	the	the	DET
cana-1016	33	2	potential	potential	NOUN
cana-1016	33	3	of	of	ADP
cana-1016	33	4	dl	dl	PROPN
cana-1016	33	5	for	for	ADP
cana-1016	33	6	enhancing	enhance	VERB
cana-1016	33	7	skin	skin	NOUN
cana-1016	33	8	cancer	cancer	NOUN
cana-1016	33	9	detection	detection	NOUN
cana-1016	33	10	mechanisms	mechanism	NOUN
cana-1016	33	11	was	be	AUX
cana-1016	33	12	demonstrated	demonstrate	VERB
cana-1016	33	13	.	.	PUNCT
cana-1016	34	1	accurate	accurate	ADJ
cana-1016	34	2	detection	detection	NOUN
cana-1016	34	3	of	of	ADP
cana-1016	34	4	skin	skin	NOUN
cana-1016	34	5	cancer	cancer	NOUN
cana-1016	34	6	was	be	AUX
cana-1016	34	7	achieved	achieve	VERB
cana-1016	34	8	using	use	VERB
cana-1016	34	9	these	these	DET
cana-1016	34	10	techniques	technique	NOUN
cana-1016	34	11	.	.	PUNCT
cana-1016	35	1	the	the	DET
cana-1016	35	2	significance	significance	NOUN
cana-1016	35	3	of	of	ADP
cana-1016	35	4	early	early	ADJ
cana-1016	35	5	detection	detection	NOUN
cana-1016	35	6	in	in	ADP
cana-1016	35	7	improving	improve	VERB
cana-1016	35	8	patient	patient	ADJ
cana-1016	35	9	outcomes	outcome	NOUN
cana-1016	35	10	was	be	AUX
cana-1016	35	11	emphasised	emphasise	VERB
cana-1016	35	12	.	.	PUNCT
cana-1016	36	1	key	key	ADJ
cana-1016	36	2	factors	factor	NOUN
cana-1016	36	3	influencing	influence	VERB
cana-1016	36	4	accurate	accurate	ADJ
cana-1016	36	5	detection	detection	NOUN
cana-1016	36	6	were	be	AUX
cana-1016	36	7	identified	identify	VERB
cana-1016	36	8	and	and	CCONJ
cana-1016	36	9	analysed	analyse	VERB
cana-1016	36	10	.	.	PUNCT
cana-1016	37	1	the	the	DET
cana-1016	37	2	role	role	NOUN
cana-1016	37	3	of	of	ADP
cana-1016	37	4	dl	dl	PROPN
cana-1016	37	5	in	in	ADP
cana-1016	37	6	aiding	aid	VERB
cana-1016	37	7	medical	medical	ADJ
cana-1016	37	8	professionals	professional	NOUN
cana-1016	37	9	in	in	ADP
cana-1016	37	10	making	make	VERB
cana-1016	37	11	timely	timely	ADJ
cana-1016	37	12	diagnoses	diagnosis	NOUN
cana-1016	37	13	and	and	CCONJ
cana-1016	37	14	treatment	treatment	NOUN
cana-1016	37	15	decisions	decision	NOUN
cana-1016	37	16	was	be	AUX
cana-1016	37	17	highlighted	highlight	VERB
cana-1016	37	18	[	[	X
cana-1016	37	19	6	6	NUM
cana-1016	37	20	]	]	PUNCT
cana-1016	37	21	.	.	PUNCT
cana-1016	38	1	2	2	X
cana-1016	38	2	.	.	X
cana-1016	38	3	literature	literature	NOUN
cana-1016	38	4	review	review	PROPN
cana-1016	38	5	skin	skin	NOUN
cana-1016	38	6	cancer	cancer	NOUN
cana-1016	38	7	stands	stand	VERB
cana-1016	38	8	as	as	ADP
cana-1016	38	9	a	a	DET
cana-1016	38	10	prevalent	prevalent	ADJ
cana-1016	38	11	form	form	NOUN
cana-1016	38	12	of	of	ADP
cana-1016	38	13	cancer	cancer	NOUN
cana-1016	38	14	on	on	ADP
cana-1016	38	15	a	a	DET
cana-1016	38	16	global	global	ADJ
cana-1016	38	17	scale	scale	NOUN
cana-1016	38	18	,	,	PUNCT
cana-1016	38	19	posing	pose	VERB
cana-1016	38	20	a	a	DET
cana-1016	38	21	substantial	substantial	ADJ
cana-1016	38	22	concern	concern	NOUN
cana-1016	38	23	for	for	ADP
cana-1016	38	24	people	people	NOUN
cana-1016	38	25	annually	annually	ADV
cana-1016	38	26	.	.	PUNCT
cana-1016	39	1	early	early	ADJ
cana-1016	39	2	detection	detection	NOUN
cana-1016	39	3	and	and	CCONJ
cana-1016	39	4	accurate	accurate	ADJ
cana-1016	39	5	diagnosis	diagnosis	NOUN
cana-1016	39	6	play	play	VERB
cana-1016	39	7	pivotal	pivotal	ADJ
cana-1016	39	8	roles	role	NOUN
cana-1016	39	9	in	in	ADP
cana-1016	39	10	improving	improve	VERB
cana-1016	39	11	patient	patient	ADJ
cana-1016	39	12	outcomes	outcome	NOUN
cana-1016	39	13	and	and	CCONJ
cana-1016	39	14	reducing	reduce	VERB
cana-1016	39	15	the	the	DET
cana-1016	39	16	mortality	mortality	NOUN
cana-1016	39	17	and	and	CCONJ
cana-1016	39	18	morbidity	morbidity	NOUN
cana-1016	39	19	associated	associate	VERB
cana-1016	39	20	with	with	ADP
cana-1016	39	21	this	this	DET
cana-1016	39	22	disease	disease	NOUN
cana-1016	39	23	.	.	PUNCT
cana-1016	40	1	over	over	ADP
cana-1016	40	2	the	the	DET
cana-1016	40	3	years	year	NOUN
cana-1016	40	4	,	,	PUNCT
cana-1016	40	5	study	study	NOUN
cana-1016	40	6	and	and	CCONJ
cana-1016	40	7	healthcare	healthcare	NOUN
cana-1016	40	8	professionals	professional	NOUN
cana-1016	40	9	have	have	AUX
cana-1016	40	10	explored	explore	VERB
cana-1016	40	11	various	various	ADJ
cana-1016	40	12	innovative	innovative	ADJ
cana-1016	40	13	approaches	approach	NOUN
cana-1016	40	14	to	to	PART
cana-1016	40	15	enhance	enhance	VERB
cana-1016	40	16	skin	skin	NOUN
cana-1016	40	17	cancer	cancer	NOUN
cana-1016	40	18	detection	detection	NOUN
cana-1016	40	19	and	and	CCONJ
cana-1016	40	20	treatment	treatment	NOUN
cana-1016	40	21	.	.	PUNCT
cana-1016	41	1	in	in	ADP
cana-1016	41	2	their	their	PRON
cana-1016	41	3	study	study	NOUN
cana-1016	41	4	,	,	PUNCT
cana-1016	41	5	shi	shi	PROPN
cana-1016	41	6	wang	wang	PROPN
cana-1016	41	7	et	et	PROPN
cana-1016	41	8	al	al	PROPN
cana-1016	41	9	.	.	PUNCT
cana-1016	42	1	[	[	X
cana-1016	42	2	7	7	X
cana-1016	42	3	]	]	PUNCT
cana-1016	42	4	suggested	suggest	VERB
cana-1016	42	5	an	an	DET
cana-1016	42	6	innovative	innovative	ADJ
cana-1016	42	7	method	method	NOUN
cana-1016	42	8	for	for	ADP
cana-1016	42	9	skin	skin	NOUN
cana-1016	42	10	cancer	cancer	NOUN
cana-1016	42	11	detection	detection	NOUN
cana-1016	42	12	,	,	PUNCT
cana-1016	42	13	combining	combine	VERB
cana-1016	42	14	the	the	DET
cana-1016	42	15	extreme	extreme	ADJ
cana-1016	42	16	learning	learning	NOUN
cana-1016	42	17	machine	machine	NOUN
cana-1016	42	18	(	(	PUNCT
cana-1016	42	19	elm	elm	PROPN
cana-1016	42	20	)	)	PUNCT
cana-1016	42	21	with	with	ADP
cana-1016	42	22	an	an	DET
cana-1016	42	23	enhanced	enhanced	ADJ
cana-1016	42	24	version	version	NOUN
cana-1016	42	25	of	of	ADP
cana-1016	42	26	thermal	thermal	ADJ
cana-1016	42	27	exchange	exchange	NOUN
cana-1016	42	28	optimization	optimization	NOUN
cana-1016	42	29	(	(	PUNCT
cana-1016	42	30	teo	teo	PROPN
cana-1016	42	31	)	)	PUNCT
cana-1016	42	32	.	.	PUNCT
cana-1016	43	1	by	by	ADP
cana-1016	43	2	leveraging	leverage	VERB
cana-1016	43	3	elm	elm	PROPN
cana-1016	43	4	and	and	CCONJ
cana-1016	43	5	teo	teo	PROPN
cana-1016	43	6	,	,	PUNCT
cana-1016	43	7	they	they	PRON
cana-1016	43	8	achieved	achieve	VERB
cana-1016	43	9	improved	improved	ADJ
cana-1016	43	10	accuracy	accuracy	NOUN
cana-1016	43	11	,	,	PUNCT
cana-1016	43	12	sensitivity	sensitivity	NOUN
cana-1016	43	13	,	,	PUNCT
cana-1016	43	14	and	and	CCONJ
cana-1016	43	15	specificity	specificity	NOUN
cana-1016	43	16	in	in	ADP
cana-1016	43	17	identifying	identify	VERB
cana-1016	43	18	malignant	malignant	ADJ
cana-1016	43	19	skin	skin	NOUN
cana-1016	43	20	lesions	lesion	NOUN
cana-1016	43	21	,	,	PUNCT
cana-1016	43	22	leading	lead	VERB
cana-1016	43	23	to	to	ADP
cana-1016	43	24	reliable	reliable	ADJ
cana-1016	43	25	and	and	CCONJ
cana-1016	43	26	timely	timely	ADJ
cana-1016	43	27	diagnoses	diagnosis	NOUN
cana-1016	43	28	.	.	PUNCT
cana-1016	44	1	the	the	DET
cana-1016	44	2	elm	elm	PROPN
cana-1016	44	3	-	-	PUNCT
cana-1016	44	4	teo	teo	PROPN
cana-1016	44	5	system	system	NOUN
cana-1016	44	6	has	have	AUX
cana-1016	44	7	shown	show	VERB
cana-1016	44	8	great	great	ADJ
cana-1016	44	9	potential	potential	NOUN
cana-1016	44	10	for	for	ADP
cana-1016	44	11	lowering	lower	VERB
cana-1016	44	12	mortality	mortality	NOUN
cana-1016	44	13	and	and	CCONJ
cana-1016	44	14	morbidity	morbidity	NOUN
cana-1016	44	15	associated	associate	VERB
cana-1016	44	16	with	with	ADP
cana-1016	44	17	skin	skin	NOUN
cana-1016	44	18	cancer	cancer	NOUN
cana-1016	44	19	,	,	PUNCT
cana-1016	44	20	proving	prove	VERB
cana-1016	44	21	its	its	PRON
cana-1016	44	22	usefulness	usefulness	NOUN
cana-1016	44	23	within	within	ADP
cana-1016	44	24	the	the	DET
cana-1016	44	25	healthcare	healthcare	NOUN
cana-1016	44	26	industry	industry	NOUN
cana-1016	44	27	.	.	PUNCT
cana-1016	45	1	in	in	ADP
cana-1016	45	2	addressing	address	VERB
cana-1016	45	3	the	the	DET
cana-1016	45	4	problem	problem	NOUN
cana-1016	45	5	of	of	ADP
cana-1016	45	6	cervical	cervical	ADJ
cana-1016	45	7	cancer	cancer	NOUN
cana-1016	45	8	detection	detection	NOUN
cana-1016	45	9	,	,	PUNCT
cana-1016	45	10	umesh	umesh	PROPN
cana-1016	45	11	kumar	kumar	PROPN
cana-1016	45	12	lilhore	lilhore	PROPN
cana-1016	45	13	et	et	PROPN
cana-1016	45	14	al	al	PROPN
cana-1016	45	15	.	.	PUNCT
cana-1016	46	1	[	[	X
cana-1016	46	2	8	8	NUM
cana-1016	46	3	]	]	PUNCT
cana-1016	46	4	developed	develop	VERB
cana-1016	46	5	a	a	DET
cana-1016	46	6	model	model	NOUN
cana-1016	46	7	that	that	SCONJ
cana-1016	46	8	integrated	integrate	VERB
cana-1016	46	9	causal	causal	ADJ
cana-1016	46	10	analysis	analysis	NOUN
cana-1016	46	11	and	and	CCONJ
cana-1016	46	12	deep	deep	ADJ
cana-1016	46	13	learning	learning	NOUN
cana-1016	46	14	techniques	technique	NOUN
cana-1016	46	15	.	.	PUNCT
cana-1016	47	1	this	this	DET
cana-1016	47	2	novel	novel	ADJ
cana-1016	47	3	approach	approach	NOUN
cana-1016	47	4	allowed	allow	VERB
cana-1016	47	5	the	the	DET
cana-1016	47	6	identification	identification	NOUN
cana-1016	47	7	of	of	ADP
cana-1016	47	8	potential	potential	ADJ
cana-1016	47	9	risk	risk	NOUN
cana-1016	47	10	factors	factor	NOUN
cana-1016	47	11	and	and	CCONJ
cana-1016	47	12	their	their	PRON
cana-1016	47	13	relationships	relationship	NOUN
cana-1016	47	14	through	through	ADP
cana-1016	47	15	causal	causal	ADJ
cana-1016	47	16	analysis	analysis	NOUN
cana-1016	47	17	,	,	PUNCT
cana-1016	47	18	which	which	PRON
cana-1016	47	19	,	,	PUNCT
cana-1016	47	20	in	in	ADP
cana-1016	47	21	turn	turn	NOUN
cana-1016	47	22	,	,	PUNCT
cana-1016	47	23	contributed	contribute	VERB
cana-1016	47	24	to	to	ADP
cana-1016	47	25	building	build	VERB
cana-1016	47	26	a	a	DET
cana-1016	47	27	predictive	predictive	ADJ
cana-1016	47	28	model	model	NOUN
cana-1016	47	29	using	use	VERB
cana-1016	47	30	deep	deep	ADJ
cana-1016	47	31	learning	learning	NOUN
cana-1016	47	32	algorithms	algorithm	NOUN
cana-1016	47	33	.	.	PUNCT
cana-1016	48	1	the	the	DET
cana-1016	48	2	developed	develop	VERB
cana-1016	48	3	model	model	NOUN
cana-1016	48	4	showcased	showcase	VERB
cana-1016	48	5	substantial	substantial	ADJ
cana-1016	48	6	improvements	improvement	NOUN
cana-1016	48	7	in	in	ADP
cana-1016	48	8	accuracy	accuracy	NOUN
cana-1016	48	9	and	and	CCONJ
cana-1016	48	10	sensitivity	sensitivity	NOUN
cana-1016	48	11	for	for	ADP
cana-1016	48	12	cervical	cervical	ADJ
cana-1016	48	13	cancer	cancer	NOUN
cana-1016	48	14	detection	detection	NOUN
cana-1016	48	15	,	,	PUNCT
cana-1016	48	16	providing	provide	VERB
cana-1016	48	17	valuable	valuable	ADJ
cana-1016	48	18	insights	insight	NOUN
cana-1016	48	19	for	for	ADP
cana-1016	48	20	better	well	ADJ
cana-1016	48	21	healthcare	healthcare	NOUN
cana-1016	48	22	management	management	NOUN
cana-1016	48	23	and	and	CCONJ
cana-1016	48	24	improved	improve	VERB
cana-1016	48	25	patient	patient	ADJ
cana-1016	48	26	outcomes	outcome	NOUN
cana-1016	48	27	.	.	PUNCT
cana-1016	49	1	however	however	ADV
cana-1016	49	2	,	,	PUNCT
cana-1016	49	3	not	not	PART
cana-1016	49	4	all	all	DET
cana-1016	49	5	innovations	innovation	NOUN
cana-1016	49	6	in	in	ADP
cana-1016	49	7	skin	skin	NOUN
cana-1016	49	8	cancer	cancer	NOUN
cana-1016	49	9	detection	detection	NOUN
cana-1016	49	10	have	have	AUX
cana-1016	49	11	been	be	AUX
cana-1016	49	12	successful	successful	ADJ
cana-1016	49	13	.	.	PUNCT
cana-1016	50	1	ahmad	ahmad	PROPN
cana-1016	50	2	m.	m.	PROPN
cana-1016	50	3	khasawneh	khasawneh	PROPN
cana-1016	50	4	et	et	PROPN
cana-1016	50	5	al	al	PROPN
cana-1016	50	6	.	.	PUNCT
cana-1016	51	1	[	[	X
cana-1016	51	2	9	9	NUM
cana-1016	51	3	]	]	PUNCT
cana-1016	51	4	investigated	investigate	VERB
cana-1016	51	5	the	the	DET
cana-1016	51	6	problem	problem	NOUN
cana-1016	51	7	of	of	ADP
cana-1016	51	8	immediate	immediate	ADJ
cana-1016	51	9	identification	identification	NOUN
cana-1016	51	10	by	by	ADP
cana-1016	51	11	dl	dl	NOUN
cana-1016	51	12	-	-	PUNCT
cana-1016	51	13	based	base	VERB
cana-1016	51	14	medical	medical	ADJ
cana-1016	51	15	picture	picture	NOUN
cana-1016	51	16	communications	communication	NOUN
cana-1016	51	17	on	on	ADP
cana-1016	51	18	applied	apply	VERB
cana-1016	51	19	nonlinear	nonlinear	ADJ
cana-1016	51	20	analysis	analysis	NOUN
cana-1016	51	21	issn	issn	NOUN
cana-1016	51	22	:	:	PUNCT
cana-1016	51	23	1074	1074	NUM
cana-1016	51	24	-	-	PUNCT
cana-1016	51	25	133x	133x	NUM
cana-1016	51	26	vol	vol	NOUN
cana-1016	51	27	31	31	NUM
cana-1016	51	28	no	no	NOUN
cana-1016	51	29	.	.	PUNCT
cana-1016	52	1	5s	5s	NUM
cana-1016	52	2	(	(	PUNCT
cana-1016	52	3	2024	2024	NUM
cana-1016	52	4	)	)	PUNCT
cana-1016	52	5	215	215	NUM
cana-1016	52	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	52	7	evaluation	evaluation	NOUN
cana-1016	52	8	.	.	PUNCT
cana-1016	53	1	unfortunately	unfortunately	ADV
cana-1016	53	2	,	,	PUNCT
cana-1016	53	3	the	the	DET
cana-1016	53	4	study	study	NOUN
cana-1016	53	5	faced	face	VERB
cana-1016	53	6	challenges	challenge	NOUN
cana-1016	53	7	with	with	ADP
cana-1016	53	8	data	datum	NOUN
cana-1016	53	9	quality	quality	NOUN
cana-1016	53	10	,	,	PUNCT
cana-1016	53	11	algorithmic	algorithmic	ADJ
cana-1016	53	12	limitations	limitation	NOUN
cana-1016	53	13	,	,	PUNCT
cana-1016	53	14	and	and	CCONJ
cana-1016	53	15	potential	potential	ADJ
cana-1016	53	16	biases	bias	NOUN
cana-1016	53	17	,	,	PUNCT
cana-1016	53	18	leading	lead	VERB
cana-1016	53	19	to	to	ADP
cana-1016	53	20	the	the	DET
cana-1016	53	21	retraction	retraction	NOUN
cana-1016	53	22	of	of	ADP
cana-1016	53	23	the	the	DET
cana-1016	53	24	reported	report	VERB
cana-1016	53	25	results	result	NOUN
cana-1016	53	26	.	.	PUNCT
cana-1016	54	1	this	this	PRON
cana-1016	54	2	highlights	highlight	VERB
cana-1016	54	3	the	the	DET
cana-1016	54	4	importance	importance	NOUN
cana-1016	54	5	of	of	ADP
cana-1016	54	6	addressing	address	VERB
cana-1016	54	7	such	such	ADJ
cana-1016	54	8	issues	issue	NOUN
cana-1016	54	9	and	and	CCONJ
cana-1016	54	10	ensuring	ensure	VERB
cana-1016	54	11	the	the	DET
cana-1016	54	12	reliability	reliability	NOUN
cana-1016	54	13	and	and	CCONJ
cana-1016	54	14	validity	validity	NOUN
cana-1016	54	15	of	of	ADP
cana-1016	54	16	study	study	NOUN
cana-1016	54	17	outcomes	outcome	NOUN
cana-1016	54	18	in	in	ADP
cana-1016	54	19	the	the	DET
cana-1016	54	20	domain	domain	NOUN
cana-1016	54	21	of	of	ADP
cana-1016	54	22	medical	medical	ADJ
cana-1016	54	23	diagnostics	diagnostic	NOUN
cana-1016	54	24	.	.	PUNCT
cana-1016	55	1	on	on	ADP
cana-1016	55	2	a	a	DET
cana-1016	55	3	different	different	ADJ
cana-1016	55	4	note	note	NOUN
cana-1016	55	5	,	,	PUNCT
cana-1016	55	6	m.	m.	NOUN
cana-1016	55	7	shobana	shobana	PROPN
cana-1016	55	8	et	et	PROPN
cana-1016	55	9	al	al	PROPN
cana-1016	55	10	.	.	PUNCT
cana-1016	56	1	[	[	X
cana-1016	56	2	10	10	NUM
cana-1016	56	3	]	]	PUNCT
cana-1016	56	4	successfully	successfully	ADV
cana-1016	56	5	addressed	address	VERB
cana-1016	56	6	the	the	DET
cana-1016	56	7	challenge	challenge	NOUN
cana-1016	56	8	of	of	ADP
cana-1016	56	9	mesothelioma	mesothelioma	NOUN
cana-1016	56	10	cancer	cancer	NOUN
cana-1016	56	11	classification	classification	NOUN
cana-1016	56	12	and	and	CCONJ
cana-1016	56	13	detection	detection	NOUN
cana-1016	56	14	using	use	VERB
cana-1016	56	15	a	a	DET
cana-1016	56	16	feature	feature	NOUN
cana-1016	56	17	selection	selection	NOUN
cana-1016	56	18	-	-	PUNCT
cana-1016	56	19	enabled	enable	VERB
cana-1016	56	20	deep	deep	ADJ
cana-1016	56	21	learning	learning	NOUN
cana-1016	56	22	technique	technique	NOUN
cana-1016	56	23	.	.	PUNCT
cana-1016	57	1	by	by	ADP
cana-1016	57	2	identifying	identify	VERB
cana-1016	57	3	the	the	DET
cana-1016	57	4	most	most	ADV
cana-1016	57	5	informative	informative	ADJ
cana-1016	57	6	and	and	CCONJ
cana-1016	57	7	discriminative	discriminative	NOUN
cana-1016	57	8	features	feature	NOUN
cana-1016	57	9	from	from	ADP
cana-1016	57	10	the	the	DET
cana-1016	57	11	dataset	dataset	NOUN
cana-1016	57	12	,	,	PUNCT
cana-1016	57	13	their	their	PRON
cana-1016	57	14	method	method	NOUN
cana-1016	57	15	achieved	achieve	VERB
cana-1016	57	16	high	high	ADJ
cana-1016	57	17	-	-	PUNCT
cana-1016	57	18	performance	performance	NOUN
cana-1016	57	19	classification	classification	NOUN
cana-1016	57	20	and	and	CCONJ
cana-1016	57	21	early	early	ADJ
cana-1016	57	22	-	-	PUNCT
cana-1016	57	23	stage	stage	NOUN
cana-1016	57	24	detection	detection	NOUN
cana-1016	57	25	of	of	ADP
cana-1016	57	26	this	this	DET
cana-1016	57	27	aggressive	aggressive	ADJ
cana-1016	57	28	form	form	NOUN
cana-1016	57	29	of	of	ADP
cana-1016	57	30	cancer	cancer	NOUN
cana-1016	57	31	.	.	PUNCT
cana-1016	58	1	this	this	DET
cana-1016	58	2	development	development	NOUN
cana-1016	58	3	showed	show	VERB
cana-1016	58	4	greater	great	ADJ
cana-1016	58	5	sensitivity	sensitivity	NOUN
cana-1016	58	6	and	and	CCONJ
cana-1016	58	7	accuracy	accuracy	NOUN
cana-1016	58	8	in	in	ADP
cana-1016	58	9	detecting	detect	VERB
cana-1016	58	10	mesothelioma	mesothelioma	NOUN
cana-1016	58	11	malignancy	malignancy	NOUN
cana-1016	58	12	,	,	PUNCT
cana-1016	58	13	with	with	ADP
cana-1016	58	14	positive	positive	ADJ
cana-1016	58	15	implications	implication	NOUN
cana-1016	58	16	for	for	ADP
cana-1016	58	17	better	well	ADJ
cana-1016	58	18	patient	patient	ADJ
cana-1016	58	19	treatment	treatment	NOUN
cana-1016	58	20	and	and	CCONJ
cana-1016	58	21	healthier	healthy	ADJ
cana-1016	58	22	outcomes	outcome	NOUN
cana-1016	58	23	.	.	PUNCT
cana-1016	59	1	cnn	cnn	PROPN
cana-1016	59	2	has	have	AUX
cana-1016	59	3	displayed	display	VERB
cana-1016	59	4	known	known	ADJ
cana-1016	59	5	potential	potential	NOUN
cana-1016	59	6	in	in	ADP
cana-1016	59	7	various	various	ADJ
cana-1016	59	8	fields	field	NOUN
cana-1016	59	9	,	,	PUNCT
cana-1016	59	10	including	include	VERB
cana-1016	59	11	skin	skin	NOUN
cana-1016	59	12	cancer	cancer	NOUN
cana-1016	59	13	detection	detection	NOUN
cana-1016	59	14	.	.	PUNCT
cana-1016	60	1	mohammed	mohammed	PROPN
cana-1016	60	2	rakeibul	rakeibul	PROPN
cana-1016	60	3	hasan	hasan	PROPN
cana-1016	60	4	et	et	PROPN
cana-1016	60	5	al	al	PROPN
cana-1016	60	6	.	.	PUNCT
cana-1016	61	1	[	[	X
cana-1016	61	2	11	11	NUM
cana-1016	61	3	]	]	PUNCT
cana-1016	61	4	performed	perform	VERB
cana-1016	61	5	a	a	DET
cana-1016	61	6	comparative	comparative	ADJ
cana-1016	61	7	analysis	analysis	NOUN
cana-1016	61	8	using	use	VERB
cana-1016	61	9	cnns	cnn	NOUN
cana-1016	61	10	to	to	PART
cana-1016	61	11	separate	separate	VERB
cana-1016	61	12	equally	equally	ADV
cana-1016	61	13	benign	benign	ADJ
cana-1016	61	14	and	and	CCONJ
cana-1016	61	15	malignant	malignant	ADJ
cana-1016	61	16	skin	skin	NOUN
cana-1016	61	17	cancer	cancer	NOUN
cana-1016	61	18	cases	case	NOUN
cana-1016	61	19	.	.	PUNCT
cana-1016	62	1	their	their	PRON
cana-1016	62	2	approach	approach	NOUN
cana-1016	62	3	demonstrated	demonstrate	VERB
cana-1016	62	4	significantly	significantly	ADV
cana-1016	62	5	improved	improve	VERB
cana-1016	62	6	accuracy	accuracy	NOUN
cana-1016	62	7	,	,	PUNCT
cana-1016	62	8	sensitivity	sensitivity	NOUN
cana-1016	62	9	,	,	PUNCT
cana-1016	62	10	and	and	CCONJ
cana-1016	62	11	specificity	specificity	NOUN
cana-1016	62	12	compared	compare	VERB
cana-1016	62	13	to	to	ADP
cana-1016	62	14	conventional	conventional	ADJ
cana-1016	62	15	methods	method	NOUN
cana-1016	62	16	,	,	PUNCT
cana-1016	62	17	proving	prove	VERB
cana-1016	62	18	the	the	DET
cana-1016	62	19	efficacy	efficacy	NOUN
cana-1016	62	20	of	of	ADP
cana-1016	62	21	cnn	cnn	PROPN
cana-1016	62	22	-	-	PUNCT
cana-1016	62	23	based	base	VERB
cana-1016	62	24	techniques	technique	NOUN
cana-1016	62	25	in	in	ADP
cana-1016	62	26	analyzing	analyze	VERB
cana-1016	62	27	complex	complex	ADJ
cana-1016	62	28	image	image	NOUN
cana-1016	62	29	patterns	pattern	NOUN
cana-1016	62	30	and	and	CCONJ
cana-1016	62	31	identifying	identify	VERB
cana-1016	62	32	cancerous	cancerous	ADJ
cana-1016	62	33	conditions	condition	NOUN
cana-1016	62	34	.	.	PUNCT
cana-1016	63	1	beyond	beyond	ADP
cana-1016	63	2	diagnosis	diagnosis	NOUN
cana-1016	63	3	,	,	PUNCT
cana-1016	63	4	researchers	researcher	NOUN
cana-1016	63	5	have	have	AUX
cana-1016	63	6	explored	explore	VERB
cana-1016	63	7	the	the	DET
cana-1016	63	8	impact	impact	NOUN
cana-1016	63	9	of	of	ADP
cana-1016	63	10	diet	diet	NOUN
cana-1016	63	11	on	on	ADP
cana-1016	63	12	skin	skin	NOUN
cana-1016	63	13	cancer	cancer	NOUN
cana-1016	63	14	risk	risk	NOUN
cana-1016	63	15	.	.	PUNCT
cana-1016	64	1	sreevidya	sreevidya	PROPN
cana-1016	64	2	r.	r.	PROPN
cana-1016	64	3	c.	c.	PROPN
cana-1016	64	4	et	et	PROPN
cana-1016	64	5	al	al	PROPN
cana-1016	64	6	.	.	PUNCT
cana-1016	65	1	[	[	X
cana-1016	65	2	12	12	NUM
cana-1016	65	3	]	]	PUNCT
cana-1016	65	4	suggested	suggest	VERB
cana-1016	65	5	an	an	DET
cana-1016	65	6	innovative	innovative	ADJ
cana-1016	65	7	approach	approach	NOUN
cana-1016	65	8	to	to	PART
cana-1016	65	9	identify	identify	VERB
cana-1016	65	10	potential	potential	ADJ
cana-1016	65	11	correlations	correlation	NOUN
cana-1016	65	12	between	between	ADP
cana-1016	65	13	antioxidant	antioxidant	NOUN
cana-1016	65	14	-	-	PUNCT
cana-1016	65	15	rich	rich	ADJ
cana-1016	65	16	diets	diet	NOUN
cana-1016	65	17	and	and	CCONJ
cana-1016	65	18	their	their	PRON
cana-1016	65	19	impact	impact	NOUN
cana-1016	65	20	on	on	ADP
cana-1016	65	21	skin	skin	NOUN
cana-1016	65	22	cancer	cancer	NOUN
cana-1016	65	23	risk	risk	NOUN
cana-1016	65	24	.	.	PUNCT
cana-1016	66	1	by	by	ADP
cana-1016	66	2	utilizing	utilize	VERB
cana-1016	66	3	ai	ai	INTJ
cana-1016	66	4	and	and	CCONJ
cana-1016	66	5	deep	deep	ADJ
cana-1016	66	6	learning	learn	VERB
cana-1016	66	7	algorithms	algorithm	NOUN
cana-1016	66	8	to	to	PART
cana-1016	66	9	analyze	analyze	VERB
cana-1016	66	10	vast	vast	ADJ
cana-1016	66	11	datasets	dataset	NOUN
cana-1016	66	12	of	of	ADP
cana-1016	66	13	dietary	dietary	ADJ
cana-1016	66	14	information	information	NOUN
cana-1016	66	15	and	and	CCONJ
cana-1016	66	16	skin	skin	NOUN
cana-1016	66	17	cancer	cancer	NOUN
cana-1016	66	18	cases	case	NOUN
cana-1016	66	19	,	,	PUNCT
cana-1016	66	20	this	this	DET
cana-1016	66	21	method	method	NOUN
cana-1016	66	22	revealed	reveal	VERB
cana-1016	66	23	valuable	valuable	ADJ
cana-1016	66	24	insights	insight	NOUN
cana-1016	66	25	into	into	ADP
cana-1016	66	26	the	the	DET
cana-1016	66	27	potential	potential	ADJ
cana-1016	66	28	preventive	preventive	ADJ
cana-1016	66	29	properties	property	NOUN
cana-1016	66	30	of	of	ADP
cana-1016	66	31	antioxidants	antioxidant	NOUN
cana-1016	66	32	against	against	ADP
cana-1016	66	33	skin	skin	NOUN
cana-1016	66	34	cancer	cancer	NOUN
cana-1016	66	35	.	.	PUNCT
cana-1016	67	1	such	such	ADJ
cana-1016	67	2	ai	ai	PROPN
cana-1016	67	3	-	-	PUNCT
cana-1016	67	4	driven	drive	VERB
cana-1016	67	5	approaches	approach	NOUN
cana-1016	67	6	hold	hold	VERB
cana-1016	67	7	promise	promise	NOUN
cana-1016	67	8	in	in	ADP
cana-1016	67	9	supporting	support	VERB
cana-1016	67	10	healthcare	healthcare	NOUN
cana-1016	67	11	professionals	professional	NOUN
cana-1016	67	12	and	and	CCONJ
cana-1016	67	13	individuals	individual	NOUN
cana-1016	67	14	in	in	ADP
cana-1016	67	15	making	make	VERB
cana-1016	67	16	informed	informed	ADJ
cana-1016	67	17	dietary	dietary	ADJ
cana-1016	67	18	choices	choice	NOUN
cana-1016	67	19	to	to	PART
cana-1016	67	20	mitigate	mitigate	VERB
cana-1016	67	21	skin	skin	NOUN
cana-1016	67	22	cancer	cancer	NOUN
cana-1016	67	23	risks	risk	NOUN
cana-1016	67	24	and	and	CCONJ
cana-1016	67	25	enhance	enhance	VERB
cana-1016	67	26	overall	overall	ADJ
cana-1016	67	27	health	health	NOUN
cana-1016	67	28	outcomes	outcome	NOUN
cana-1016	67	29	.	.	PUNCT
cana-1016	68	1	hamza	hamza	PROPN
cana-1016	68	2	abu	abu	PROPN
cana-1016	68	3	owida	owida	PROPN
cana-1016	68	4	et	et	PROPN
cana-1016	68	5	al	al	PROPN
cana-1016	68	6	.	.	PUNCT
cana-1016	69	1	[	[	X
cana-1016	69	2	13	13	NUM
cana-1016	69	3	]	]	PUNCT
cana-1016	69	4	focused	focus	VERB
cana-1016	69	5	on	on	ADP
cana-1016	69	6	skin	skin	NOUN
cana-1016	69	7	cancer	cancer	NOUN
cana-1016	69	8	therapy	therapy	NOUN
cana-1016	69	9	and	and	CCONJ
cana-1016	69	10	detection	detection	NOUN
cana-1016	69	11	using	use	VERB
cana-1016	69	12	biomimetic	biomimetic	ADJ
cana-1016	69	13	nanoscale	nanoscale	NOUN
cana-1016	69	14	materials	material	NOUN
cana-1016	69	15	.	.	PUNCT
cana-1016	70	1	these	these	DET
cana-1016	70	2	nanomaterials	nanomaterial	NOUN
cana-1016	70	3	were	be	AUX
cana-1016	70	4	designed	design	VERB
cana-1016	70	5	to	to	PART
cana-1016	70	6	mimic	mimic	VERB
cana-1016	70	7	biological	biological	ADJ
cana-1016	70	8	processes	process	NOUN
cana-1016	70	9	,	,	PUNCT
cana-1016	70	10	effectively	effectively	ADV
cana-1016	70	11	targeting	target	VERB
cana-1016	70	12	and	and	CCONJ
cana-1016	70	13	treating	treat	VERB
cana-1016	70	14	skin	skin	NOUN
cana-1016	70	15	cancer	cancer	NOUN
cana-1016	70	16	cells	cell	NOUN
cana-1016	70	17	.	.	PUNCT
cana-1016	71	1	additionally	additionally	ADV
cana-1016	71	2	,	,	PUNCT
cana-1016	71	3	they	they	PRON
cana-1016	71	4	were	be	AUX
cana-1016	71	5	utilized	utilize	VERB
cana-1016	71	6	in	in	ADP
cana-1016	71	7	the	the	DET
cana-1016	71	8	initial	initial	ADJ
cana-1016	71	9	identification	identification	NOUN
cana-1016	71	10	of	of	ADP
cana-1016	71	11	skin	skin	NOUN
cana-1016	71	12	cancer	cancer	NOUN
cana-1016	71	13	by	by	ADP
cana-1016	71	14	selectively	selectively	ADV
cana-1016	71	15	binding	bind	VERB
cana-1016	71	16	to	to	ADP
cana-1016	71	17	cancer	cancer	NOUN
cana-1016	71	18	-	-	PUNCT
cana-1016	71	19	specific	specific	ADJ
cana-1016	71	20	biomarkers	biomarker	NOUN
cana-1016	71	21	or	or	CCONJ
cana-1016	71	22	signaling	signal	VERB
cana-1016	71	23	molecules	molecule	NOUN
cana-1016	71	24	.	.	PUNCT
cana-1016	72	1	the	the	DET
cana-1016	72	2	data	datum	NOUN
cana-1016	72	3	proven	prove	VERB
cana-1016	72	4	important	important	ADJ
cana-1016	72	5	advancements	advancement	NOUN
cana-1016	72	6	in	in	ADP
cana-1016	72	7	the	the	DET
cana-1016	72	8	area	area	NOUN
cana-1016	72	9	of	of	ADP
cana-1016	72	10	skin	skin	NOUN
cana-1016	72	11	cancer	cancer	NOUN
cana-1016	72	12	diagnosis	diagnosis	NOUN
cana-1016	72	13	and	and	CCONJ
cana-1016	72	14	treatment	treatment	NOUN
cana-1016	72	15	,	,	PUNCT
cana-1016	72	16	showing	show	VERB
cana-1016	72	17	the	the	DET
cana-1016	72	18	potential	potential	NOUN
cana-1016	72	19	of	of	ADP
cana-1016	72	20	biomimetic	biomimetic	ADJ
cana-1016	72	21	nanoscale	nanoscale	NOUN
cana-1016	72	22	materials	material	NOUN
cana-1016	72	23	as	as	ADP
cana-1016	72	24	a	a	DET
cana-1016	72	25	viable	viable	ADJ
cana-1016	72	26	and	and	CCONJ
cana-1016	72	27	novel	novel	ADJ
cana-1016	72	28	strategy	strategy	NOUN
cana-1016	72	29	to	to	PART
cana-1016	72	30	improve	improve	VERB
cana-1016	72	31	therapeutic	therapeutic	ADJ
cana-1016	72	32	results	result	NOUN
cana-1016	72	33	and	and	CCONJ
cana-1016	72	34	boost	boost	VERB
cana-1016	72	35	skin	skin	NOUN
cana-1016	72	36	cancer	cancer	NOUN
cana-1016	72	37	early	early	ADJ
cana-1016	72	38	detection	detection	NOUN
cana-1016	72	39	rates	rate	NOUN
cana-1016	72	40	.	.	PUNCT
cana-1016	73	1	taher	taher	PROPN
cana-1016	73	2	m.	m.	PROPN
cana-1016	73	3	ghazal	ghazal	PROPN
cana-1016	73	4	et	et	PROPN
cana-1016	73	5	al	al	PROPN
cana-1016	73	6	.	.	PUNCT
cana-1016	74	1	[	[	X
cana-1016	74	2	14	14	NUM
cana-1016	74	3	]	]	SYM
cana-1016	74	4	employed	employ	VERB
cana-1016	74	5	transfer	transfer	NOUN
cana-1016	74	6	learning	learn	VERB
cana-1016	74	7	to	to	PART
cana-1016	74	8	address	address	VERB
cana-1016	74	9	the	the	DET
cana-1016	74	10	challenge	challenge	NOUN
cana-1016	74	11	of	of	ADP
cana-1016	74	12	detecting	detect	VERB
cana-1016	74	13	benign	benign	ADJ
cana-1016	74	14	and	and	CCONJ
cana-1016	74	15	malignant	malignant	ADJ
cana-1016	74	16	tumors	tumor	NOUN
cana-1016	74	17	in	in	ADP
cana-1016	74	18	the	the	DET
cana-1016	74	19	skin	skin	NOUN
cana-1016	74	20	.	.	PUNCT
cana-1016	75	1	their	their	PRON
cana-1016	75	2	approach	approach	NOUN
cana-1016	75	3	involved	involve	VERB
cana-1016	75	4	fine	fine	ADV
cana-1016	75	5	-	-	PUNCT
cana-1016	75	6	tuning	tune	VERB
cana-1016	75	7	pre	pre	ADJ
cana-1016	75	8	-	-	ADJ
cana-1016	75	9	trained	train	VERB
cana-1016	75	10	deep	deep	ADJ
cana-1016	75	11	learning	learning	NOUN
cana-1016	75	12	models	model	NOUN
cana-1016	75	13	on	on	ADP
cana-1016	75	14	large	large	ADJ
cana-1016	75	15	datasets	dataset	NOUN
cana-1016	75	16	from	from	ADP
cana-1016	75	17	unrelated	unrelated	ADJ
cana-1016	75	18	tasks	task	NOUN
cana-1016	75	19	,	,	PUNCT
cana-1016	75	20	leading	lead	VERB
cana-1016	75	21	to	to	ADP
cana-1016	75	22	significant	significant	ADJ
cana-1016	75	23	improvements	improvement	NOUN
cana-1016	75	24	in	in	ADP
cana-1016	75	25	accuracy	accuracy	NOUN
cana-1016	75	26	and	and	CCONJ
cana-1016	75	27	efficiency	efficiency	NOUN
cana-1016	75	28	for	for	ADP
cana-1016	75	29	skin	skin	NOUN
cana-1016	75	30	tumor	tumor	NOUN
cana-1016	75	31	classification	classification	NOUN
cana-1016	75	32	.	.	PUNCT
cana-1016	76	1	the	the	DET
cana-1016	76	2	use	use	NOUN
cana-1016	76	3	of	of	ADP
cana-1016	76	4	transfer	transfer	NOUN
cana-1016	76	5	learning	learning	NOUN
cana-1016	76	6	empowered	empower	VERB
cana-1016	76	7	the	the	DET
cana-1016	76	8	method	method	NOUN
cana-1016	76	9	with	with	ADP
cana-1016	76	10	valuable	valuable	ADJ
cana-1016	76	11	insights	insight	NOUN
cana-1016	76	12	from	from	ADP
cana-1016	76	13	unrelated	unrelated	ADJ
cana-1016	76	14	datasets	dataset	NOUN
cana-1016	76	15	,	,	PUNCT
cana-1016	76	16	offering	offer	VERB
cana-1016	76	17	a	a	DET
cana-1016	76	18	valuable	valuable	ADJ
cana-1016	76	19	tool	tool	NOUN
cana-1016	76	20	for	for	ADP
cana-1016	76	21	healthcare	healthcare	NOUN
cana-1016	76	22	professionals	professional	NOUN
cana-1016	76	23	in	in	ADP
cana-1016	76	24	early	early	ADJ
cana-1016	76	25	diagnosis	diagnosis	NOUN
cana-1016	76	26	and	and	CCONJ
cana-1016	76	27	effective	effective	ADJ
cana-1016	76	28	treatment	treatment	NOUN
cana-1016	76	29	planning	planning	NOUN
cana-1016	76	30	for	for	ADP
cana-1016	76	31	patients	patient	NOUN
cana-1016	76	32	with	with	ADP
cana-1016	76	33	skin	skin	NOUN
cana-1016	76	34	cancer	cancer	NOUN
cana-1016	76	35	.	.	PUNCT
cana-1016	77	1	machine	machine	NOUN
cana-1016	77	2	vision	vision	NOUN
cana-1016	77	3	with	with	ADP
cana-1016	77	4	texture	texture	ADJ
cana-1016	77	5	features	feature	NOUN
cana-1016	77	6	was	be	AUX
cana-1016	77	7	employed	employ	VERB
cana-1016	77	8	by	by	ADP
cana-1016	77	9	syeda	syeda	PROPN
cana-1016	77	10	shamaila	shamaila	PROPN
cana-1016	77	11	zareen	zareen	NUM
cana-1016	77	12	et	et	PROPN
cana-1016	77	13	al	al	PROPN
cana-1016	77	14	.	.	PUNCT
cana-1016	78	1	[	[	X
cana-1016	78	2	15	15	NUM
cana-1016	78	3	]	]	PUNCT
cana-1016	78	4	to	to	PART
cana-1016	78	5	address	address	VERB
cana-1016	78	6	skin	skin	NOUN
cana-1016	78	7	cancer	cancer	NOUN
cana-1016	78	8	classification	classification	NOUN
cana-1016	78	9	.	.	PUNCT
cana-1016	79	1	the	the	DET
cana-1016	79	2	extraction	extraction	NOUN
cana-1016	79	3	and	and	CCONJ
cana-1016	79	4	combination	combination	NOUN
cana-1016	79	5	of	of	ADP
cana-1016	79	6	various	various	ADJ
cana-1016	79	7	texture	texture	NOUN
cana-1016	79	8	features	feature	NOUN
cana-1016	79	9	from	from	ADP
cana-1016	79	10	dermatoscopic	dermatoscopic	ADJ
cana-1016	79	11	images	image	NOUN
cana-1016	79	12	of	of	ADP
cana-1016	79	13	skin	skin	NOUN
cana-1016	79	14	lesions	lesion	NOUN
cana-1016	79	15	significantly	significantly	ADV
cana-1016	79	16	enhanced	enhance	VERB
cana-1016	79	17	the	the	DET
cana-1016	79	18	accuracy	accuracy	NOUN
cana-1016	79	19	of	of	ADP
cana-1016	79	20	skin	skin	NOUN
cana-1016	79	21	cancer	cancer	NOUN
cana-1016	79	22	classification	classification	NOUN
cana-1016	79	23	.	.	PUNCT
cana-1016	80	1	this	this	DET
cana-1016	80	2	machine	machine	NOUN
cana-1016	80	3	vision	vision	NOUN
cana-1016	80	4	-	-	PUNCT
cana-1016	80	5	based	base	VERB
cana-1016	80	6	method	method	NOUN
cana-1016	80	7	demonstrated	demonstrate	VERB
cana-1016	80	8	notable	notable	ADJ
cana-1016	80	9	improvements	improvement	NOUN
cana-1016	80	10	in	in	ADP
cana-1016	80	11	differentiating	differentiate	VERB
cana-1016	80	12	benign	benign	ADJ
cana-1016	80	13	and	and	CCONJ
cana-1016	80	14	malignant	malignant	ADJ
cana-1016	80	15	skin	skin	NOUN
cana-1016	80	16	tumors	tumor	NOUN
cana-1016	80	17	,	,	PUNCT
cana-1016	80	18	indicating	indicate	VERB
cana-1016	80	19	its	its	PRON
cana-1016	80	20	potential	potential	NOUN
cana-1016	80	21	in	in	ADP
cana-1016	80	22	assisting	assist	VERB
cana-1016	80	23	healthcare	healthcare	NOUN
cana-1016	80	24	professionals	professional	NOUN
cana-1016	80	25	in	in	ADP
cana-1016	80	26	making	make	VERB
cana-1016	80	27	more	more	ADV
cana-1016	80	28	informed	informed	ADJ
cana-1016	80	29	and	and	CCONJ
cana-1016	80	30	timely	timely	ADJ
cana-1016	80	31	decisions	decision	NOUN
cana-1016	80	32	for	for	ADP
cana-1016	80	33	skin	skin	NOUN
cana-1016	80	34	cancer	cancer	NOUN
cana-1016	80	35	diagnosis	diagnosis	NOUN
cana-1016	80	36	and	and	CCONJ
cana-1016	80	37	treatment	treatment	NOUN
cana-1016	80	38	,	,	PUNCT
cana-1016	80	39	ultimately	ultimately	ADV
cana-1016	80	40	leading	lead	VERB
cana-1016	80	41	to	to	ADP
cana-1016	80	42	improved	improved	ADJ
cana-1016	80	43	patient	patient	ADJ
cana-1016	80	44	outcomes	outcome	NOUN
cana-1016	80	45	.	.	PUNCT
cana-1016	81	1	muhammad	muhammad	PROPN
cana-1016	81	2	arif	arif	PROPN
cana-1016	81	3	et	et	PROPN
cana-1016	81	4	al	al	PROPN
cana-1016	81	5	.	.	PUNCT
cana-1016	82	1	[	[	X
cana-1016	82	2	16	16	NUM
cana-1016	82	3	]	]	PUNCT
cana-1016	82	4	will	will	AUX
cana-1016	82	5	propose	propose	VERB
cana-1016	82	6	another	another	DET
cana-1016	82	7	notable	notable	ADJ
cana-1016	82	8	advancement	advancement	NOUN
cana-1016	82	9	in	in	ADP
cana-1016	82	10	skin	skin	NOUN
cana-1016	82	11	cancer	cancer	NOUN
cana-1016	82	12	communications	communication	NOUN
cana-1016	82	13	on	on	ADP
cana-1016	82	14	applied	apply	VERB
cana-1016	82	15	nonlinear	nonlinear	ADJ
cana-1016	82	16	analysis	analysis	NOUN
cana-1016	82	17	issn	issn	NOUN
cana-1016	82	18	:	:	PUNCT
cana-1016	82	19	1074	1074	NUM
cana-1016	82	20	-	-	PUNCT
cana-1016	82	21	133x	133x	NUM
cana-1016	82	22	vol	vol	NOUN
cana-1016	82	23	31	31	NUM
cana-1016	82	24	no	no	NOUN
cana-1016	82	25	.	.	PUNCT
cana-1016	83	1	5s	5s	NUM
cana-1016	83	2	(	(	PUNCT
cana-1016	83	3	2024	2024	NUM
cana-1016	83	4	)	)	PUNCT
cana-1016	83	5	216	216	NUM
cana-1016	83	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	83	7	evaluation	evaluation	NOUN
cana-1016	83	8	.	.	PUNCT
cana-1016	84	1	they	they	PRON
cana-1016	84	2	developed	develop	VERB
cana-1016	84	3	an	an	DET
cana-1016	84	4	automated	automate	VERB
cana-1016	84	5	system	system	NOUN
cana-1016	84	6	using	use	VERB
cana-1016	84	7	dcnn	dcnn	PROPN
cana-1016	84	8	to	to	PART
cana-1016	84	9	detect	detect	VERB
cana-1016	84	10	nonmelanoma	nonmelanoma	ADJ
cana-1016	84	11	skin	skin	NOUN
cana-1016	84	12	cancer	cancer	NOUN
cana-1016	84	13	.	.	PUNCT
cana-1016	85	1	a	a	DET
cana-1016	85	2	convolutional	convolutional	ADJ
cana-1016	85	3	neural	neural	ADJ
cana-1016	85	4	network	network	NOUN
cana-1016	85	5	has	have	AUX
cana-1016	85	6	learned	learn	VERB
cana-1016	85	7	from	from	ADP
cana-1016	85	8	an	an	DET
cana-1016	85	9	extensive	extensive	ADJ
cana-1016	85	10	dataset	dataset	NOUN
cana-1016	85	11	of	of	ADP
cana-1016	85	12	dermatoscopic	dermatoscopic	ADJ
cana-1016	85	13	pictures	picture	NOUN
cana-1016	85	14	,	,	PUNCT
cana-1016	85	15	enabling	enable	VERB
cana-1016	85	16	the	the	DET
cana-1016	85	17	automated	automate	VERB
cana-1016	85	18	identification	identification	NOUN
cana-1016	85	19	and	and	CCONJ
cana-1016	85	20	differentiation	differentiation	NOUN
cana-1016	85	21	of	of	ADP
cana-1016	85	22	nonmelanoma	nonmelanoma	ADJ
cana-1016	85	23	skin	skin	NOUN
cana-1016	85	24	cancer	cancer	NOUN
cana-1016	85	25	cases	case	NOUN
cana-1016	85	26	based	base	VERB
cana-1016	85	27	on	on	ADP
cana-1016	85	28	benign	benign	ADJ
cana-1016	85	29	lesions	lesion	NOUN
cana-1016	85	30	.	.	PUNCT
cana-1016	86	1	substantial	substantial	ADJ
cana-1016	86	2	advancements	advancement	NOUN
cana-1016	86	3	in	in	ADP
cana-1016	86	4	enhancing	enhance	VERB
cana-1016	86	5	the	the	DET
cana-1016	86	6	precision	precision	NOUN
cana-1016	86	7	and	and	CCONJ
cana-1016	86	8	reliability	reliability	NOUN
cana-1016	86	9	of	of	ADP
cana-1016	86	10	nonmelanoma	nonmelanoma	ADJ
cana-1016	86	11	skin	skin	NOUN
cana-1016	86	12	cancer	cancer	NOUN
cana-1016	86	13	detection	detection	NOUN
cana-1016	86	14	were	be	AUX
cana-1016	86	15	demonstrated	demonstrate	VERB
cana-1016	86	16	,	,	PUNCT
cana-1016	86	17	showcasing	showcase	VERB
cana-1016	86	18	the	the	DET
cana-1016	86	19	effectiveness	effectiveness	NOUN
cana-1016	86	20	of	of	ADP
cana-1016	86	21	deep	deep	ADJ
cana-1016	86	22	cnn	cnn	PROPN
cana-1016	86	23	in	in	ADP
cana-1016	86	24	analyzing	analyze	VERB
cana-1016	86	25	complex	complex	ADJ
cana-1016	86	26	image	image	NOUN
cana-1016	86	27	patterns	pattern	NOUN
cana-1016	86	28	and	and	CCONJ
cana-1016	86	29	identifying	identify	VERB
cana-1016	86	30	cancerous	cancerous	ADJ
cana-1016	86	31	conditions	condition	NOUN
cana-1016	86	32	.	.	PUNCT
cana-1016	87	1	automated	automate	VERB
cana-1016	87	2	detection	detection	NOUN
cana-1016	87	3	systems	system	NOUN
cana-1016	87	4	can	can	AUX
cana-1016	87	5	assist	assist	VERB
cana-1016	87	6	healthcare	healthcare	NOUN
cana-1016	87	7	professionals	professional	NOUN
cana-1016	87	8	in	in	ADP
cana-1016	87	9	the	the	DET
cana-1016	87	10	initial	initial	ADJ
cana-1016	87	11	stages	stage	NOUN
cana-1016	87	12	of	of	ADP
cana-1016	87	13	detection	detection	NOUN
cana-1016	87	14	and	and	CCONJ
cana-1016	87	15	timely	timely	ADJ
cana-1016	87	16	intervention	intervention	NOUN
cana-1016	87	17	,	,	PUNCT
cana-1016	87	18	thus	thus	ADV
cana-1016	87	19	contributing	contribute	VERB
cana-1016	87	20	to	to	ADP
cana-1016	87	21	improved	improve	VERB
cana-1016	87	22	patient	patient	ADJ
cana-1016	87	23	care	care	NOUN
cana-1016	87	24	and	and	CCONJ
cana-1016	87	25	better	well	ADJ
cana-1016	87	26	outcomes	outcome	NOUN
cana-1016	87	27	for	for	ADP
cana-1016	87	28	individuals	individual	NOUN
cana-1016	87	29	with	with	ADP
cana-1016	87	30	nonmelanoma	nonmelanoma	ADJ
cana-1016	87	31	skin	skin	NOUN
cana-1016	87	32	cancer	cancer	NOUN
cana-1016	87	33	.	.	PUNCT
cana-1016	88	1	3	3	X
cana-1016	88	2	.	.	X
cana-1016	88	3	methodology	methodology	NOUN
cana-1016	88	4	using	use	VERB
cana-1016	88	5	deep	deep	ADJ
cana-1016	88	6	learning	learning	NOUN
cana-1016	88	7	technology	technology	NOUN
cana-1016	88	8	,	,	PUNCT
cana-1016	88	9	our	our	PRON
cana-1016	88	10	study	study	NOUN
cana-1016	88	11	improves	improve	VERB
cana-1016	88	12	skin	skin	NOUN
cana-1016	88	13	cancer	cancer	NOUN
cana-1016	88	14	diagnosis	diagnosis	NOUN
cana-1016	88	15	by	by	ADP
cana-1016	88	16	combining	combine	VERB
cana-1016	88	17	pre	pre	ADJ
cana-1016	88	18	-	-	ADJ
cana-1016	88	19	trained	train	VERB
cana-1016	88	20	cnn	cnn	PROPN
cana-1016	88	21	models	model	NOUN
cana-1016	88	22	,	,	PUNCT
cana-1016	88	23	data	datum	NOUN
cana-1016	88	24	augmentation	augmentation	NOUN
cana-1016	88	25	,	,	PUNCT
cana-1016	88	26	and	and	CCONJ
cana-1016	88	27	image	image	NOUN
cana-1016	88	28	normalization	normalization	NOUN
cana-1016	88	29	.	.	PUNCT
cana-1016	89	1	relevant	relevant	ADJ
cana-1016	89	2	characteristics	characteristic	NOUN
cana-1016	89	3	are	be	AUX
cana-1016	89	4	extracted	extract	VERB
cana-1016	89	5	using	use	VERB
cana-1016	89	6	cnn	cnn	PROPN
cana-1016	89	7	models	model	NOUN
cana-1016	89	8	such	such	ADJ
cana-1016	89	9	as	as	ADP
cana-1016	89	10	densenet121	densenet121	PROPN
cana-1016	89	11	,	,	PUNCT
cana-1016	89	12	densenet201	densenet201	PROPN
cana-1016	89	13	,	,	PUNCT
cana-1016	89	14	inceptionv3	inceptionv3	NOUN
cana-1016	89	15	,	,	PUNCT
cana-1016	89	16	inceptionresnetv2	inceptionresnetv2	PROPN
cana-1016	89	17	,	,	PUNCT
cana-1016	89	18	mobilenet	mobilenet	NOUN
cana-1016	89	19	,	,	PUNCT
cana-1016	89	20	resnet50v2	resnet50v2	PROPN
cana-1016	89	21	,	,	PUNCT
cana-1016	89	22	resnet101	resnet101	PROPN
cana-1016	89	23	,	,	PUNCT
cana-1016	89	24	vgg16	vgg16	PROPN
cana-1016	89	25	,	,	PUNCT
cana-1016	89	26	vgg19	vgg19	PROPN
cana-1016	89	27	,	,	PUNCT
cana-1016	89	28	xception	xception	NOUN
cana-1016	89	29	,	,	PUNCT
cana-1016	89	30	and	and	CCONJ
cana-1016	89	31	bespoke	bespoke	NOUN
cana-1016	89	32	cnns	cnn	NOUN
cana-1016	89	33	.	.	PUNCT
cana-1016	90	1	these	these	DET
cana-1016	90	2	attributes	attribute	NOUN
cana-1016	90	3	are	be	AUX
cana-1016	90	4	then	then	ADV
cana-1016	90	5	used	use	VERB
cana-1016	90	6	to	to	PART
cana-1016	90	7	classify	classify	VERB
cana-1016	90	8	skin	skin	NOUN
cana-1016	90	9	cancers	cancer	NOUN
cana-1016	90	10	as	as	ADP
cana-1016	90	11	benign	benign	ADJ
cana-1016	90	12	or	or	CCONJ
cana-1016	90	13	malignant	malignant	ADJ
cana-1016	90	14	using	use	VERB
cana-1016	90	15	deep	deep	ADJ
cana-1016	90	16	learning	learning	NOUN
cana-1016	90	17	techniques	technique	NOUN
cana-1016	90	18	such	such	ADJ
cana-1016	90	19	as	as	ADP
cana-1016	90	20	svms	svms	NOUN
cana-1016	90	21	or	or	CCONJ
cana-1016	90	22	random	random	ADJ
cana-1016	90	23	forests	forest	NOUN
cana-1016	90	24	.	.	PUNCT
cana-1016	91	1	this	this	DET
cana-1016	91	2	complete	complete	ADJ
cana-1016	91	3	method	method	NOUN
cana-1016	91	4	creates	create	VERB
cana-1016	91	5	an	an	DET
cana-1016	91	6	effective	effective	ADJ
cana-1016	91	7	and	and	CCONJ
cana-1016	91	8	accurate	accurate	ADJ
cana-1016	91	9	structure	structure	NOUN
cana-1016	91	10	for	for	ADP
cana-1016	91	11	detecting	detect	VERB
cana-1016	91	12	skin	skin	NOUN
cana-1016	91	13	cancer	cancer	NOUN
cana-1016	91	14	.	.	PUNCT
cana-1016	92	1	3.1	3.1	NUM
cana-1016	92	2	summary	summary	NOUN
cana-1016	92	3	of	of	ADP
cana-1016	92	4	dataset	dataset	NOUN
cana-1016	92	5	table	table	NOUN
cana-1016	92	6	1	1	NUM
cana-1016	92	7	presents	present	VERB
cana-1016	92	8	a	a	DET
cana-1016	92	9	summary	summary	NOUN
cana-1016	92	10	of	of	ADP
cana-1016	92	11	the	the	DET
cana-1016	92	12	image	image	NOUN
cana-1016	92	13	distribution	distribution	NOUN
cana-1016	92	14	within	within	ADP
cana-1016	92	15	a	a	DET
cana-1016	92	16	medical	medical	ADJ
cana-1016	92	17	imaging	imaging	NOUN
cana-1016	92	18	dataset	dataset	NOUN
cana-1016	92	19	.	.	PUNCT
cana-1016	93	1	this	this	DET
cana-1016	93	2	dataset	dataset	NOUN
cana-1016	93	3	is	be	AUX
cana-1016	93	4	divided	divide	VERB
cana-1016	93	5	into	into	ADP
cana-1016	93	6	two	two	NUM
cana-1016	93	7	main	main	ADJ
cana-1016	93	8	folders	folder	NOUN
cana-1016	93	9	:	:	PUNCT
cana-1016	93	10	'	'	PUNCT
cana-1016	93	11	benign	benign	ADJ
cana-1016	93	12	'	'	PUNCT
cana-1016	93	13	and	and	CCONJ
cana-1016	93	14	'	'	PUNCT
cana-1016	93	15	malignant	malignant	ADJ
cana-1016	93	16	,	,	PUNCT
cana-1016	93	17	'	'	PUNCT
cana-1016	93	18	and	and	CCONJ
cana-1016	93	19	further	far	ADV
cana-1016	93	20	categorized	categorize	VERB
cana-1016	93	21	into	into	ADP
cana-1016	93	22	three	three	NUM
cana-1016	93	23	subfolders	subfolder	NOUN
cana-1016	93	24	:	:	PUNCT
cana-1016	93	25	'	'	PUNCT
cana-1016	93	26	training	training	NOUN
cana-1016	93	27	,	,	PUNCT
cana-1016	93	28	'	'	PUNCT
cana-1016	93	29	'	'	PUNCT
cana-1016	93	30	validation	validation	NOUN
cana-1016	93	31	,	,	PUNCT
cana-1016	93	32	'	'	PUNCT
cana-1016	93	33	and	and	CCONJ
cana-1016	93	34	'	'	PUNCT
cana-1016	93	35	testing	testing	NOUN
cana-1016	93	36	.	.	PUNCT
cana-1016	93	37	'	'	PUNCT
cana-1016	94	1	the	the	DET
cana-1016	94	2	'	'	PUNCT
cana-1016	94	3	training	training	NOUN
cana-1016	94	4	'	'	PUNCT
cana-1016	94	5	subfolder	subfolder	NOUN
cana-1016	94	6	is	be	AUX
cana-1016	94	7	dedicated	dedicate	VERB
cana-1016	94	8	to	to	ADP
cana-1016	94	9	images	image	NOUN
cana-1016	94	10	used	use	VERB
cana-1016	94	11	for	for	ADP
cana-1016	94	12	classifying	classify	VERB
cana-1016	94	13	them	they	PRON
cana-1016	94	14	as	as	ADP
cana-1016	94	15	benign	benign	ADJ
cana-1016	94	16	or	or	CCONJ
cana-1016	94	17	malignant	malignant	ADJ
cana-1016	94	18	.	.	PUNCT
cana-1016	95	1	model	model	NOUN
cana-1016	95	2	efficiency	efficiency	NOUN
cana-1016	95	3	is	be	AUX
cana-1016	95	4	analyzed	analyze	VERB
cana-1016	95	5	within	within	ADP
cana-1016	95	6	the	the	DET
cana-1016	95	7	"	"	PUNCT
cana-1016	95	8	validation	validation	NOUN
cana-1016	95	9	"	"	PUNCT
cana-1016	95	10	subfolder	subfolder	NOUN
cana-1016	95	11	during	during	ADP
cana-1016	95	12	the	the	DET
cana-1016	95	13	training	training	NOUN
cana-1016	95	14	process	process	NOUN
cana-1016	95	15	,	,	PUNCT
cana-1016	95	16	and	and	CCONJ
cana-1016	95	17	the	the	DET
cana-1016	95	18	model	model	NOUN
cana-1016	95	19	's	's	PART
cana-1016	95	20	effectiveness	effectiveness	NOUN
cana-1016	95	21	is	be	AUX
cana-1016	95	22	assessed	assess	VERB
cana-1016	95	23	using	use	VERB
cana-1016	95	24	previously	previously	ADV
cana-1016	95	25	unseen	unseen	ADJ
cana-1016	95	26	data	datum	NOUN
cana-1016	95	27	in	in	ADP
cana-1016	95	28	the	the	DET
cana-1016	95	29	'	'	PUNCT
cana-1016	95	30	testing	testing	NOUN
cana-1016	95	31	'	'	PUNCT
cana-1016	95	32	subfolder	subfolder	NOUN
cana-1016	95	33	.	.	PUNCT
cana-1016	96	1	the	the	DET
cana-1016	96	2	dataset	dataset	NOUN
cana-1016	96	3	comprises	comprise	VERB
cana-1016	96	4	a	a	DET
cana-1016	96	5	total	total	NOUN
cana-1016	96	6	of	of	ADP
cana-1016	96	7	2360	2360	NUM
cana-1016	96	8	images	image	NOUN
cana-1016	96	9	,	,	PUNCT
cana-1016	96	10	with	with	ADP
cana-1016	96	11	1180	1180	NUM
cana-1016	96	12	classified	classify	VERB
cana-1016	96	13	as	as	ADP
cana-1016	96	14	benign	benign	ADJ
cana-1016	96	15	and	and	CCONJ
cana-1016	96	16	1200	1200	NUM
cana-1016	96	17	as	as	ADP
cana-1016	96	18	malignant	malignant	ADJ
cana-1016	96	19	.	.	PUNCT
cana-1016	97	1	this	this	DET
cana-1016	97	2	medical	medical	ADJ
cana-1016	97	3	imaging	imaging	NOUN
cana-1016	97	4	data	datum	NOUN
cana-1016	97	5	set	set	VERB
cana-1016	97	6	is	be	AUX
cana-1016	97	7	organized	organize	VERB
cana-1016	97	8	according	accord	VERB
cana-1016	97	9	to	to	ADP
cana-1016	97	10	several	several	ADJ
cana-1016	97	11	subfolders	subfolder	NOUN
cana-1016	97	12	:	:	PUNCT
cana-1016	97	13	'	'	PUNCT
cana-1016	97	14	training	training	NOUN
cana-1016	97	15	,	,	PUNCT
cana-1016	97	16	'	'	PUNCT
cana-1016	97	17	'	'	PUNCT
cana-1016	97	18	validation	validation	NOUN
cana-1016	97	19	,	,	PUNCT
cana-1016	97	20	'	'	PUNCT
cana-1016	97	21	and	and	CCONJ
cana-1016	97	22	'	'	PUNCT
cana-1016	97	23	testing	testing	NOUN
cana-1016	97	24	,	,	PUNCT
cana-1016	97	25	'	'	PUNCT
cana-1016	97	26	with	with	ADP
cana-1016	97	27	each	each	DET
cana-1016	97	28	subfolder	subfolder	NOUN
cana-1016	97	29	containing	contain	VERB
cana-1016	97	30	300	300	NUM
cana-1016	97	31	images	image	NOUN
cana-1016	97	32	.	.	PUNCT
cana-1016	98	1	table	table	NOUN
cana-1016	98	2	1	1	NUM
cana-1016	98	3	.	.	PUNCT
cana-1016	98	4	medical	medical	ADJ
cana-1016	98	5	imaging	imaging	NOUN
cana-1016	98	6	dataset	dataset	VERB
cana-1016	98	7	label	label	NOUN
cana-1016	98	8	benign	benign	ADJ
cana-1016	98	9	malignant	malignant	ADJ
cana-1016	98	10	total	total	ADJ
cana-1016	98	11	images	image	NOUN
cana-1016	99	1	training	train	VERB
cana-1016	99	2	folder	folder	NOUN
cana-1016	99	3	1180	1180	NUM
cana-1016	99	4	1180	1180	NUM
cana-1016	99	5	2360	2360	NUM
cana-1016	99	6	validation	validation	NOUN
cana-1016	99	7	folder	folder	NOUN
cana-1016	99	8	1180	1180	NUM
cana-1016	99	9	1180	1180	NUM
cana-1016	99	10	2360	2360	NUM
cana-1016	99	11	test	test	NOUN
cana-1016	99	12	folder	folder	NOUN
cana-1016	99	13	300	300	NUM
cana-1016	99	14	300	300	NUM
cana-1016	99	15	600	600	NUM
cana-1016	99	16	3.2	3.2	NUM
cana-1016	99	17	balanced	balanced	ADJ
cana-1016	99	18	skin	skin	NOUN
cana-1016	99	19	lesion	lesion	NOUN
cana-1016	99	20	dataset	dataset	VERB
cana-1016	99	21	for	for	ADP
cana-1016	99	22	binary	binary	ADJ
cana-1016	99	23	classification	classification	NOUN
cana-1016	99	24	the	the	DET
cana-1016	99	25	data	datum	NOUN
cana-1016	99	26	appears	appear	VERB
cana-1016	99	27	to	to	PART
cana-1016	99	28	be	be	AUX
cana-1016	99	29	organized	organize	VERB
cana-1016	99	30	into	into	ADP
cana-1016	99	31	three	three	NUM
cana-1016	99	32	main	main	ADJ
cana-1016	99	33	categories	category	NOUN
cana-1016	99	34	:	:	PUNCT
cana-1016	99	35	training	training	NOUN
cana-1016	99	36	,	,	PUNCT
cana-1016	99	37	validation	validation	NOUN
cana-1016	99	38	,	,	PUNCT
cana-1016	99	39	and	and	CCONJ
cana-1016	99	40	test	test	NOUN
cana-1016	99	41	sets	set	NOUN
cana-1016	99	42	,	,	PUNCT
cana-1016	99	43	as	as	SCONJ
cana-1016	99	44	seen	see	VERB
cana-1016	99	45	in	in	ADP
cana-1016	99	46	figure	figure	NOUN
cana-1016	99	47	1	1	NUM
cana-1016	99	48	.	.	PUNCT
cana-1016	100	1	each	each	DET
cana-1016	100	2	folder	folder	NOUN
cana-1016	100	3	contains	contain	VERB
cana-1016	100	4	images	image	NOUN
cana-1016	100	5	of	of	ADP
cana-1016	100	6	skin	skin	NOUN
cana-1016	100	7	lesions	lesion	NOUN
cana-1016	100	8	,	,	PUNCT
cana-1016	100	9	which	which	PRON
cana-1016	100	10	have	have	AUX
cana-1016	100	11	been	be	AUX
cana-1016	100	12	classified	classify	VERB
cana-1016	100	13	into	into	ADP
cana-1016	100	14	two	two	NUM
cana-1016	100	15	categories	category	NOUN
cana-1016	100	16	:	:	PUNCT
cana-1016	100	17	benign	benign	ADJ
cana-1016	100	18	and	and	CCONJ
cana-1016	100	19	malignant	malignant	ADJ
cana-1016	100	20	.	.	PUNCT
cana-1016	101	1	in	in	ADP
cana-1016	101	2	each	each	PRON
cana-1016	101	3	of	of	ADP
cana-1016	101	4	the	the	DET
cana-1016	101	5	training	training	NOUN
cana-1016	101	6	and	and	CCONJ
cana-1016	101	7	validation	validation	NOUN
cana-1016	101	8	folders	folder	NOUN
cana-1016	101	9	,	,	PUNCT
cana-1016	101	10	there	there	PRON
cana-1016	101	11	are	be	VERB
cana-1016	101	12	1,180	1,180	NUM
cana-1016	101	13	pictures	picture	NOUN
cana-1016	101	14	depicting	depict	VERB
cana-1016	101	15	benign	benign	ADJ
cana-1016	101	16	cancers	cancer	NOUN
cana-1016	101	17	and	and	CCONJ
cana-1016	101	18	1,180	1,180	NUM
cana-1016	101	19	pictures	picture	NOUN
cana-1016	101	20	depicting	depict	VERB
cana-1016	101	21	malignant	malignant	ADJ
cana-1016	101	22	cancer	cancer	NOUN
cana-1016	101	23	.	.	PUNCT
cana-1016	102	1	this	this	DET
cana-1016	102	2	balanced	balanced	ADJ
cana-1016	102	3	distribution	distribution	NOUN
cana-1016	102	4	is	be	AUX
cana-1016	102	5	important	important	ADJ
cana-1016	102	6	for	for	ADP
cana-1016	102	7	training	training	NOUN
cana-1016	102	8	and	and	CCONJ
cana-1016	102	9	evaluating	evaluate	VERB
cana-1016	102	10	deep	deep	ADJ
cana-1016	102	11	learning	learning	NOUN
cana-1016	102	12	models	model	NOUN
cana-1016	102	13	,	,	PUNCT
cana-1016	102	14	as	as	SCONJ
cana-1016	102	15	it	it	PRON
cana-1016	102	16	helps	help	VERB
cana-1016	102	17	prevent	prevent	VERB
cana-1016	102	18	bias	bias	NOUN
cana-1016	102	19	.	.	PUNCT
cana-1016	103	1	in	in	ADP
cana-1016	103	2	the	the	DET
cana-1016	103	3	test	test	NOUN
cana-1016	103	4	folder	folder	NOUN
cana-1016	103	5	,	,	PUNCT
cana-1016	103	6	300	300	NUM
cana-1016	103	7	pictures	picture	NOUN
cana-1016	103	8	of	of	ADP
cana-1016	103	9	benign	benign	ADJ
cana-1016	103	10	lesions	lesion	NOUN
cana-1016	103	11	and	and	CCONJ
cana-1016	103	12	300	300	NUM
cana-1016	103	13	pictures	picture	NOUN
cana-1016	103	14	of	of	ADP
cana-1016	103	15	malignant	malignant	ADJ
cana-1016	103	16	cancers	cancer	NOUN
cana-1016	103	17	are	be	AUX
cana-1016	103	18	maintained	maintain	VERB
cana-1016	103	19	in	in	ADP
cana-1016	103	20	a	a	DET
cana-1016	103	21	balanced	balanced	ADJ
cana-1016	103	22	distribution	distribution	NOUN
cana-1016	103	23	.	.	PUNCT
cana-1016	104	1	the	the	DET
cana-1016	104	2	maximum	maximum	ADJ
cana-1016	104	3	total	total	NOUN
cana-1016	104	4	of	of	ADP
cana-1016	104	5	pictures	picture	NOUN
cana-1016	104	6	in	in	ADP
cana-1016	104	7	the	the	DET
cana-1016	104	8	training	training	NOUN
cana-1016	104	9	and	and	CCONJ
cana-1016	104	10	validation	validation	NOUN
cana-1016	104	11	folders	folder	NOUN
cana-1016	104	12	is	be	AUX
cana-1016	104	13	communications	communication	NOUN
cana-1016	104	14	on	on	ADP
cana-1016	104	15	applied	apply	VERB
cana-1016	104	16	nonlinear	nonlinear	ADJ
cana-1016	104	17	analysis	analysis	NOUN
cana-1016	104	18	issn	issn	NOUN
cana-1016	104	19	:	:	PUNCT
cana-1016	104	20	1074	1074	NUM
cana-1016	104	21	-	-	PUNCT
cana-1016	104	22	133x	133x	NUM
cana-1016	104	23	vol	vol	NOUN
cana-1016	104	24	31	31	NUM
cana-1016	104	25	no	no	NOUN
cana-1016	104	26	.	.	PUNCT
cana-1016	105	1	5s	5s	NUM
cana-1016	105	2	(	(	PUNCT
cana-1016	105	3	2024	2024	NUM
cana-1016	105	4	)	)	PUNCT
cana-1016	105	5	217	217	NUM
cana-1016	105	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	105	7	2,360	2,360	NUM
cana-1016	105	8	each	each	DET
cana-1016	105	9	,	,	PUNCT
cana-1016	105	10	and	and	CCONJ
cana-1016	105	11	there	there	PRON
cana-1016	105	12	are	be	VERB
cana-1016	105	13	600	600	NUM
cana-1016	105	14	images	image	NOUN
cana-1016	105	15	in	in	ADP
cana-1016	105	16	the	the	DET
cana-1016	105	17	test	test	NOUN
cana-1016	105	18	folder	folder	NOUN
cana-1016	105	19	.	.	PUNCT
cana-1016	106	1	this	this	DET
cana-1016	106	2	dataset	dataset	NOUN
cana-1016	106	3	is	be	AUX
cana-1016	106	4	going	go	VERB
cana-1016	106	5	to	to	PART
cana-1016	106	6	be	be	AUX
cana-1016	106	7	used	use	VERB
cana-1016	106	8	for	for	ADP
cana-1016	106	9	skin	skin	NOUN
cana-1016	106	10	cancer	cancer	NOUN
cana-1016	106	11	binary	binary	NOUN
cana-1016	106	12	classification	classification	NOUN
cana-1016	106	13	.	.	PUNCT
cana-1016	107	1	figure	figure	NOUN
cana-1016	107	2	1	1	NUM
cana-1016	107	3	.	.	PUNCT
cana-1016	107	4	skin	skin	NOUN
cana-1016	107	5	cancer	cancer	NOUN
cana-1016	107	6	data	datum	NOUN
cana-1016	107	7	distribution	distribution	NOUN
cana-1016	107	8	3.3	3.3	NUM
cana-1016	107	9	comparative	comparative	ADJ
cana-1016	107	10	analysis	analysis	NOUN
cana-1016	107	11	of	of	ADP
cana-1016	107	12	pre	pre	ADJ
cana-1016	107	13	-	-	ADJ
cana-1016	107	14	trained	train	VERB
cana-1016	107	15	deep	deep	ADJ
cana-1016	107	16	learning	learning	NOUN
cana-1016	107	17	models	model	NOUN
cana-1016	107	18	by	by	ADP
cana-1016	107	19	model	model	NOUN
cana-1016	107	20	complexity	complexity	NOUN
cana-1016	107	21	and	and	CCONJ
cana-1016	107	22	parameters	parameter	NOUN
cana-1016	107	23	table	table	NOUN
cana-1016	107	24	2	2	NUM
cana-1016	107	25	provides	provide	VERB
cana-1016	107	26	a	a	DET
cana-1016	107	27	comprehensive	comprehensive	ADJ
cana-1016	107	28	analysis	analysis	NOUN
cana-1016	107	29	of	of	ADP
cana-1016	107	30	various	various	ADJ
cana-1016	107	31	pre	pre	ADJ
cana-1016	107	32	-	-	ADJ
cana-1016	107	33	trained	train	VERB
cana-1016	107	34	deep	deep	ADJ
cana-1016	107	35	learning	learning	NOUN
cana-1016	107	36	models	model	NOUN
cana-1016	107	37	,	,	PUNCT
cana-1016	107	38	highlighting	highlight	VERB
cana-1016	107	39	their	their	PRON
cana-1016	107	40	model	model	NOUN
cana-1016	107	41	complexity	complexity	NOUN
cana-1016	107	42	in	in	ADP
cana-1016	107	43	terms	term	NOUN
cana-1016	107	44	of	of	ADP
cana-1016	107	45	modifiable	modifiable	ADJ
cana-1016	107	46	and	and	CCONJ
cana-1016	107	47	fixed	fixed	ADJ
cana-1016	107	48	parameters	parameter	NOUN
cana-1016	107	49	.	.	PUNCT
cana-1016	108	1	trainable	trainable	ADJ
cana-1016	108	2	parameters	parameter	NOUN
cana-1016	108	3	represent	represent	VERB
cana-1016	108	4	those	those	DET
cana-1016	108	5	components	component	NOUN
cana-1016	108	6	that	that	PRON
cana-1016	108	7	are	be	AUX
cana-1016	108	8	fine	fine	ADV
cana-1016	108	9	-	-	PUNCT
cana-1016	108	10	tuned	tune	VERB
cana-1016	108	11	during	during	ADP
cana-1016	108	12	training	training	NOUN
cana-1016	108	13	,	,	PUNCT
cana-1016	108	14	while	while	SCONJ
cana-1016	108	15	non	non	ADJ
cana-1016	108	16	-	-	ADJ
cana-1016	108	17	trainable	trainable	ADJ
cana-1016	108	18	parameters	parameter	NOUN
cana-1016	108	19	are	be	AUX
cana-1016	108	20	fixed	fix	VERB
cana-1016	108	21	weights	weight	NOUN
cana-1016	108	22	that	that	PRON
cana-1016	108	23	are	be	AUX
cana-1016	108	24	usually	usually	ADV
cana-1016	108	25	pre	pre	ADJ
cana-1016	108	26	-	-	VERB
cana-1016	108	27	trained	train	VERB
cana-1016	108	28	on	on	ADP
cana-1016	108	29	large	large	ADJ
cana-1016	108	30	datasets	dataset	NOUN
cana-1016	108	31	.	.	PUNCT
cana-1016	109	1	the	the	DET
cana-1016	109	2	overall	overall	ADJ
cana-1016	109	3	parameter	parameter	NOUN
cana-1016	109	4	count	count	NOUN
cana-1016	109	5	in	in	ADP
cana-1016	109	6	a	a	DET
cana-1016	109	7	model	model	NOUN
cana-1016	109	8	equals	equal	VERB
cana-1016	109	9	the	the	DET
cana-1016	109	10	sum	sum	NOUN
cana-1016	109	11	of	of	ADP
cana-1016	109	12	these	these	DET
cana-1016	109	13	two	two	NUM
cana-1016	109	14	components	component	NOUN
cana-1016	109	15	.	.	PUNCT
cana-1016	110	1	densenet121	densenet121	PROPN
cana-1016	110	2	and	and	CCONJ
cana-1016	110	3	densenet201	densenet201	PROPN
cana-1016	110	4	demonstrate	demonstrate	VERB
cana-1016	110	5	relatively	relatively	ADV
cana-1016	110	6	compact	compact	ADJ
cana-1016	110	7	architectures	architecture	NOUN
cana-1016	110	8	with	with	ADP
cana-1016	110	9	lower	low	ADJ
cana-1016	110	10	trainable	trainable	ADJ
cana-1016	110	11	and	and	CCONJ
cana-1016	110	12	non	non	ADJ
cana-1016	110	13	-	-	ADJ
cana-1016	110	14	trainable	trainable	ADJ
cana-1016	110	15	parameters	parameter	NOUN
cana-1016	110	16	.	.	PUNCT
cana-1016	111	1	densenet121	densenet121	PROPN
cana-1016	111	2	features	feature	VERB
cana-1016	111	3	32,770	32,770	NUM
cana-1016	111	4	trainable	trainable	ADJ
cana-1016	111	5	parameters	parameter	NOUN
cana-1016	111	6	,	,	PUNCT
cana-1016	111	7	making	make	VERB
cana-1016	111	8	it	it	PRON
cana-1016	111	9	computationally	computationally	ADV
cana-1016	111	10	efficient	efficient	ADJ
cana-1016	111	11	.	.	PUNCT
cana-1016	112	1	inceptionv3	inceptionv3	NOUN
cana-1016	112	2	is	be	AUX
cana-1016	112	3	characterized	characterize	VERB
cana-1016	112	4	by	by	ADP
cana-1016	112	5	a	a	DET
cana-1016	112	6	moderate	moderate	ADJ
cana-1016	112	7	number	number	NOUN
cana-1016	112	8	of	of	ADP
cana-1016	112	9	trainable	trainable	ADJ
cana-1016	112	10	parameters	parameter	NOUN
cana-1016	112	11	(	(	PUNCT
cana-1016	112	12	16,386	16,386	NUM
cana-1016	112	13	)	)	PUNCT
cana-1016	112	14	and	and	CCONJ
cana-1016	112	15	a	a	DET
cana-1016	112	16	substantial	substantial	ADJ
cana-1016	112	17	number	number	NOUN
cana-1016	112	18	of	of	ADP
cana-1016	112	19	non	non	ADJ
cana-1016	112	20	-	-	ADJ
cana-1016	112	21	trainable	trainable	ADJ
cana-1016	112	22	parameters	parameter	NOUN
cana-1016	112	23	(	(	PUNCT
cana-1016	112	24	21,802,784	21,802,784	NUM
cana-1016	112	25	)	)	PUNCT
cana-1016	112	26	.	.	PUNCT
cana-1016	113	1	inceptionresnetv2	inceptionresnetv2	PROPN
cana-1016	113	2	features	feature	VERB
cana-1016	113	3	a	a	DET
cana-1016	113	4	comparatively	comparatively	ADV
cana-1016	113	5	low	low	ADJ
cana-1016	113	6	number	number	NOUN
cana-1016	113	7	of	of	ADP
cana-1016	113	8	trainable	trainable	ADJ
cana-1016	113	9	parameters	parameter	NOUN
cana-1016	113	10	(	(	PUNCT
cana-1016	113	11	12,290	12,290	NUM
cana-1016	113	12	)	)	PUNCT
cana-1016	113	13	but	but	CCONJ
cana-1016	113	14	possesses	possess	VERB
cana-1016	113	15	a	a	DET
cana-1016	113	16	significant	significant	ADJ
cana-1016	113	17	number	number	NOUN
cana-1016	113	18	of	of	ADP
cana-1016	113	19	non	non	ADJ
cana-1016	113	20	-	-	ADJ
cana-1016	113	21	trainable	trainable	ADJ
cana-1016	113	22	parameters	parameter	NOUN
cana-1016	113	23	(	(	PUNCT
cana-1016	113	24	54,336,736	54,336,736	NUM
cana-1016	113	25	)	)	PUNCT
cana-1016	113	26	.	.	PUNCT
cana-1016	114	1	this	this	PRON
cana-1016	114	2	points	point	VERB
cana-1016	114	3	to	to	ADP
cana-1016	114	4	its	its	PRON
cana-1016	114	5	complex	complex	ADJ
cana-1016	114	6	architecture	architecture	NOUN
cana-1016	114	7	.	.	PUNCT
cana-1016	115	1	mobilenet	mobilenet	NOUN
cana-1016	115	2	is	be	AUX
cana-1016	115	3	notable	notable	ADJ
cana-1016	115	4	for	for	ADP
cana-1016	115	5	having	have	VERB
cana-1016	115	6	no	no	DET
cana-1016	115	7	trainable	trainable	ADJ
cana-1016	115	8	parameters	parameter	NOUN
cana-1016	115	9	,	,	PUNCT
cana-1016	115	10	offering	offer	VERB
cana-1016	115	11	efficient	efficient	ADJ
cana-1016	115	12	inference	inference	NOUN
cana-1016	115	13	with	with	ADP
cana-1016	115	14	a	a	DET
cana-1016	115	15	smaller	small	ADJ
cana-1016	115	16	parameter	parameter	NOUN
cana-1016	115	17	footprint	footprint	NOUN
cana-1016	115	18	.	.	PUNCT
cana-1016	116	1	resnet50v2	resnet50v2	NOUN
cana-1016	116	2	and	and	CCONJ
cana-1016	116	3	resnet101	resnet101	PROPN
cana-1016	116	4	are	be	AUX
cana-1016	116	5	more	more	ADV
cana-1016	116	6	parameter	parameter	NOUN
cana-1016	116	7	-	-	PUNCT
cana-1016	116	8	heavy	heavy	ADJ
cana-1016	116	9	models	model	NOUN
cana-1016	116	10	,	,	PUNCT
cana-1016	116	11	boasting	boast	VERB
cana-1016	116	12	65,538	65,538	NUM
cana-1016	116	13	trainable	trainable	ADJ
cana-1016	116	14	parameters	parameter	NOUN
cana-1016	116	15	each	each	PRON
cana-1016	116	16	,	,	PUNCT
cana-1016	116	17	combined	combine	VERB
cana-1016	116	18	with	with	ADP
cana-1016	116	19	a	a	DET
cana-1016	116	20	substantial	substantial	ADJ
cana-1016	116	21	number	number	NOUN
cana-1016	116	22	of	of	ADP
cana-1016	116	23	non	non	ADJ
cana-1016	116	24	-	-	ADJ
cana-1016	116	25	trainable	trainable	ADJ
cana-1016	116	26	parameters	parameter	NOUN
cana-1016	116	27	.	.	PUNCT
cana-1016	117	1	vgg16	vgg16	NOUN
cana-1016	117	2	and	and	CCONJ
cana-1016	117	3	vgg19	vgg19	PROPN
cana-1016	117	4	exhibit	exhibit	NOUN
cana-1016	117	5	balance	balance	NOUN
cana-1016	117	6	with	with	ADP
cana-1016	117	7	moderate	moderate	ADJ
cana-1016	117	8	trainable	trainable	ADJ
cana-1016	117	9	and	and	CCONJ
cana-1016	117	10	non	non	ADJ
cana-1016	117	11	-	-	ADJ
cana-1016	117	12	trainable	trainable	ADJ
cana-1016	117	13	parameters	parameter	NOUN
cana-1016	117	14	,	,	PUNCT
cana-1016	117	15	offering	offer	VERB
cana-1016	117	16	a	a	DET
cana-1016	117	17	good	good	ADJ
cana-1016	117	18	trade	trade	NOUN
cana-1016	117	19	-	-	PUNCT
cana-1016	117	20	off	off	NOUN
cana-1016	117	21	between	between	ADP
cana-1016	117	22	model	model	NOUN
cana-1016	117	23	complexity	complexity	NOUN
cana-1016	117	24	and	and	CCONJ
cana-1016	117	25	computational	computational	ADJ
cana-1016	117	26	requirements	requirement	NOUN
cana-1016	117	27	.	.	PUNCT
cana-1016	118	1	xception	xception	PROPN
cana-1016	118	2	is	be	AUX
cana-1016	118	3	characterized	characterize	VERB
cana-1016	118	4	by	by	ADP
cana-1016	118	5	a	a	DET
cana-1016	118	6	considerable	considerable	ADJ
cana-1016	118	7	number	number	NOUN
cana-1016	118	8	of	of	ADP
cana-1016	118	9	trainable	trainable	ADJ
cana-1016	118	10	parameters	parameter	NOUN
cana-1016	118	11	(	(	PUNCT
cana-1016	118	12	65,538	65,538	NUM
cana-1016	118	13	)	)	PUNCT
cana-1016	118	14	and	and	CCONJ
cana-1016	118	15	non	non	ADJ
cana-1016	118	16	-	-	ADJ
cana-1016	118	17	trainable	trainable	ADJ
cana-1016	118	18	parameters	parameter	NOUN
cana-1016	118	19	(	(	PUNCT
cana-1016	118	20	20,861,480	20,861,480	NUM
cana-1016	118	21	)	)	PUNCT
cana-1016	118	22	,	,	PUNCT
cana-1016	118	23	reflecting	reflect	VERB
cana-1016	118	24	its	its	PRON
cana-1016	118	25	complex	complex	ADJ
cana-1016	118	26	architecture	architecture	NOUN
cana-1016	118	27	.	.	PUNCT
cana-1016	119	1	table	table	NOUN
cana-1016	119	2	2	2	NUM
cana-1016	119	3	.	.	PUNCT
cana-1016	119	4	comparison	comparison	NOUN
cana-1016	119	5	of	of	ADP
cana-1016	119	6	pre	pre	ADJ
cana-1016	119	7	-	-	ADJ
cana-1016	119	8	trained	train	VERB
cana-1016	119	9	deep	deep	ADJ
cana-1016	119	10	learning	learning	NOUN
cana-1016	119	11	models	model	NOUN
cana-1016	119	12	based	base	VERB
cana-1016	119	13	on	on	ADP
cana-1016	119	14	model	model	NOUN
cana-1016	119	15	complexity	complexity	NOUN
cana-1016	119	16	pre	pre	VERB
cana-1016	119	17	-	-	ADJ
cana-1016	119	18	trained	train	VERB
cana-1016	119	19	deep	deep	ADJ
cana-1016	119	20	learning	learning	NOUN
cana-1016	119	21	models	model	NOUN
cana-1016	119	22	trainable	trainable	ADJ
cana-1016	119	23	parameters	parameter	NOUN
cana-1016	119	24	non	non	ADJ
cana-1016	119	25	-	-	ADJ
cana-1016	119	26	trainable	trainable	ADJ
cana-1016	119	27	parameters	parameter	NOUN
cana-1016	119	28	total	total	ADJ
cana-1016	119	29	parameters	parameter	NOUN
cana-1016	119	30	densenet121	densenet121	PROPN
cana-1016	119	31	32,770	32,770	NUM
cana-1016	119	32	7,037,504	7,037,504	NUM
cana-1016	119	33	7,070,274	7,070,274	NUM
cana-1016	119	34	densenet201	densenet201	PROPN
cana-1016	120	1	61,442	61,442	NUM
cana-1016	120	2	18,321,984	18,321,984	NUM
cana-1016	120	3	18,383,426	18,383,426	NUM
cana-1016	120	4	inceptionv3	inceptionv3	NOUN
cana-1016	120	5	16,386	16,386	NUM
cana-1016	120	6	21,802,784	21,802,784	NUM
cana-1016	120	7	21,819,170	21,819,170	NUM
cana-1016	120	8	inceptionresnetv2	inceptionresnetv2	NOUN
cana-1016	120	9	12,290	12,290	NUM
cana-1016	120	10	54,336,736	54,336,736	NUM
cana-1016	120	11	54,349,026	54,349,026	NUM
cana-1016	120	12	mobilenet	mobilenet	NOUN
cana-1016	120	13	0	0	NUM
cana-1016	120	14	3,228,864	3,228,864	NUM
cana-1016	120	15	3,228,864	3,228,864	NUM
cana-1016	120	16	resnet50v2	resnet50v2	NOUN
cana-1016	120	17	65,538	65,538	NUM
cana-1016	120	18	23,564,800	23,564,800	NUM
cana-1016	120	19	23,630,338	23,630,338	NUM
cana-1016	120	20	resnet101	resnet101	PROPN
cana-1016	120	21	65,538	65,538	NUM
cana-1016	120	22	42,658,176	42,658,176	NOUN
cana-1016	120	23	42,723,714	42,723,714	NUM
cana-1016	120	24	vgg16	vgg16	VERB
cana-1016	120	25	16,386	16,386	NUM
cana-1016	120	26	14,714,688	14,714,688	NUM
cana-1016	120	27	14,731,074	14,731,074	NUM
cana-1016	120	28	vgg19	vgg19	NOUN
cana-1016	120	29	16,386	16,386	NUM
cana-1016	120	30	20,024,384	20,024,384	NUM
cana-1016	120	31	20,040,770	20,040,770	NUM
cana-1016	120	32	xception	xception	NOUN
cana-1016	120	33	65,538	65,538	NUM
cana-1016	120	34	20,861,480	20,861,480	NUM
cana-1016	120	35	20,927,018	20,927,018	NUM
cana-1016	120	36	communications	communication	NOUN
cana-1016	120	37	on	on	ADP
cana-1016	120	38	applied	apply	VERB
cana-1016	120	39	nonlinear	nonlinear	ADJ
cana-1016	120	40	analysis	analysis	NOUN
cana-1016	120	41	issn	issn	NOUN
cana-1016	120	42	:	:	PUNCT
cana-1016	120	43	1074	1074	NUM
cana-1016	120	44	-	-	PUNCT
cana-1016	120	45	133x	133x	NUM
cana-1016	120	46	vol	vol	NOUN
cana-1016	120	47	31	31	NUM
cana-1016	120	48	no	no	NOUN
cana-1016	120	49	.	.	PUNCT
cana-1016	121	1	5s	5s	NUM
cana-1016	121	2	(	(	PUNCT
cana-1016	121	3	2024	2024	NUM
cana-1016	121	4	)	)	PUNCT
cana-1016	121	5	218	218	NUM
cana-1016	121	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	121	7	deep	deep	ADJ
cana-1016	121	8	learning	learning	NOUN
cana-1016	121	9	approach	approach	NOUN
cana-1016	121	10	for	for	ADP
cana-1016	121	11	skin	skin	NOUN
cana-1016	121	12	cancer	cancer	NOUN
cana-1016	121	13	detection	detection	NOUN
cana-1016	121	14	technology	technology	NOUN
cana-1016	121	15	employs	employ	VERB
cana-1016	121	16	dl	dl	PROPN
cana-1016	121	17	to	to	PART
cana-1016	121	18	detect	detect	VERB
cana-1016	121	19	skin	skin	NOUN
cana-1016	121	20	cancer	cancer	NOUN
cana-1016	121	21	using	use	VERB
cana-1016	121	22	an	an	DET
cana-1016	121	23	advanced	advanced	ADJ
cana-1016	121	24	approach	approach	NOUN
cana-1016	121	25	.	.	PUNCT
cana-1016	122	1	it	it	PRON
cana-1016	122	2	leverages	leverage	VERB
cana-1016	122	3	pre	pre	ADJ
cana-1016	122	4	-	-	VERB
cana-1016	122	5	trained	train	VERB
cana-1016	122	6	weights	weight	NOUN
cana-1016	122	7	from	from	ADP
cana-1016	122	8	a	a	DET
cana-1016	122	9	cnn	cnn	PROPN
cana-1016	122	10	model	model	NOUN
cana-1016	122	11	recently	recently	ADV
cana-1016	122	12	adapted	adapt	VERB
cana-1016	122	13	for	for	ADP
cana-1016	122	14	image	image	NOUN
cana-1016	122	15	categorization	categorization	NOUN
cana-1016	122	16	tasks	task	NOUN
cana-1016	122	17	.	.	PUNCT
cana-1016	123	1	methods	method	NOUN
cana-1016	123	2	for	for	ADP
cana-1016	123	3	enhancing	enhance	VERB
cana-1016	123	4	data	datum	NOUN
cana-1016	123	5	,	,	PUNCT
cana-1016	123	6	including	include	VERB
cana-1016	123	7	techniques	technique	NOUN
cana-1016	123	8	like	like	ADP
cana-1016	123	9	resizing	resizing	NOUN
cana-1016	123	10	and	and	CCONJ
cana-1016	123	11	orientation	orientation	NOUN
cana-1016	123	12	adjustment	adjustment	NOUN
cana-1016	123	13	,	,	PUNCT
cana-1016	123	14	are	be	AUX
cana-1016	123	15	used	use	VERB
cana-1016	123	16	to	to	PART
cana-1016	123	17	augment	augment	VERB
cana-1016	123	18	the	the	DET
cana-1016	123	19	training	training	NOUN
cana-1016	123	20	dataset	dataset	VERB
cana-1016	123	21	with	with	ADP
cana-1016	123	22	skin	skin	NOUN
cana-1016	123	23	lesion	lesion	NOUN
cana-1016	123	24	images	image	NOUN
cana-1016	123	25	.	.	PUNCT
cana-1016	124	1	all	all	DET
cana-1016	124	2	images	image	NOUN
cana-1016	124	3	are	be	AUX
cana-1016	124	4	standardized	standardize	VERB
cana-1016	124	5	to	to	ADP
cana-1016	124	6	a	a	DET
cana-1016	124	7	uniform	uniform	ADJ
cana-1016	124	8	size	size	NOUN
cana-1016	124	9	of	of	ADP
cana-1016	124	10	224x224x4	224x224x4	NUM
cana-1016	124	11	pixels	pixel	NOUN
cana-1016	124	12	.	.	PUNCT
cana-1016	125	1	image	image	NOUN
cana-1016	125	2	normalization	normalization	NOUN
cana-1016	125	3	is	be	AUX
cana-1016	125	4	used	use	VERB
cana-1016	125	5	to	to	PART
cana-1016	125	6	ensure	ensure	VERB
cana-1016	125	7	consistent	consistent	ADJ
cana-1016	125	8	pixel	pixel	NOUN
cana-1016	125	9	values	value	NOUN
cana-1016	125	10	.	.	PUNCT
cana-1016	126	1	various	various	ADJ
cana-1016	126	2	convolutional	convolutional	ADJ
cana-1016	126	3	neural	neural	ADJ
cana-1016	126	4	network	network	NOUN
cana-1016	126	5	frameworks	framework	NOUN
cana-1016	126	6	,	,	PUNCT
cana-1016	126	7	including	include	VERB
cana-1016	126	8	densenet121	densenet121	PROPN
cana-1016	126	9	,	,	PUNCT
cana-1016	126	10	densenet201	densenet201	PROPN
cana-1016	126	11	,	,	PUNCT
cana-1016	126	12	inceptionv3	inceptionv3	NOUN
cana-1016	126	13	,	,	PUNCT
cana-1016	126	14	inceptionresnetv2	inceptionresnetv2	PROPN
cana-1016	126	15	,	,	PUNCT
cana-1016	126	16	mobilenet	mobilenet	NOUN
cana-1016	126	17	,	,	PUNCT
cana-1016	126	18	resnet50v2	resnet50v2	PROPN
cana-1016	126	19	,	,	PUNCT
cana-1016	126	20	resnet101	resnet101	PROPN
cana-1016	126	21	,	,	PUNCT
cana-1016	126	22	vgg16	vgg16	PROPN
cana-1016	126	23	,	,	PUNCT
cana-1016	126	24	vgg19	vgg19	PROPN
cana-1016	126	25	,	,	PUNCT
cana-1016	126	26	xception	xception	NOUN
cana-1016	126	27	,	,	PUNCT
cana-1016	126	28	and	and	CCONJ
cana-1016	126	29	custom	custom	NOUN
cana-1016	126	30	cnn	cnn	PROPN
cana-1016	126	31	models	model	NOUN
cana-1016	126	32	,	,	PUNCT
cana-1016	126	33	are	be	AUX
cana-1016	126	34	employed	employ	VERB
cana-1016	126	35	to	to	PART
cana-1016	126	36	extract	extract	VERB
cana-1016	126	37	features	feature	NOUN
cana-1016	126	38	relevant	relevant	ADJ
cana-1016	126	39	to	to	ADP
cana-1016	126	40	skin	skin	NOUN
cana-1016	126	41	cancer	cancer	NOUN
cana-1016	126	42	identification	identification	NOUN
cana-1016	126	43	.	.	PUNCT
cana-1016	127	1	these	these	DET
cana-1016	127	2	features	feature	NOUN
cana-1016	127	3	undergo	undergo	VERB
cana-1016	127	4	a	a	DET
cana-1016	127	5	decision	decision	NOUN
cana-1016	127	6	-	-	PUNCT
cana-1016	127	7	making	make	VERB
cana-1016	127	8	process	process	NOUN
cana-1016	127	9	,	,	PUNCT
cana-1016	127	10	typically	typically	ADV
cana-1016	127	11	implemented	implement	VERB
cana-1016	127	12	using	use	VERB
cana-1016	127	13	deep	deep	ADJ
cana-1016	127	14	learning	learning	NOUN
cana-1016	127	15	techniques	technique	NOUN
cana-1016	127	16	like	like	ADP
cana-1016	127	17	svms	svms	NOUN
cana-1016	127	18	or	or	CCONJ
cana-1016	127	19	random	random	ADJ
cana-1016	127	20	forests	forest	NOUN
cana-1016	127	21	,	,	PUNCT
cana-1016	127	22	to	to	PART
cana-1016	127	23	determine	determine	VERB
cana-1016	127	24	the	the	DET
cana-1016	127	25	category	category	NOUN
cana-1016	127	26	of	of	ADP
cana-1016	127	27	skin	skin	NOUN
cana-1016	127	28	lesions	lesion	NOUN
cana-1016	127	29	as	as	ADP
cana-1016	127	30	benign	benign	ADJ
cana-1016	127	31	or	or	CCONJ
cana-1016	127	32	malignant	malignant	ADJ
cana-1016	127	33	.	.	PUNCT
cana-1016	128	1	the	the	DET
cana-1016	128	2	use	use	NOUN
cana-1016	128	3	of	of	ADP
cana-1016	128	4	pre	pre	ADJ
cana-1016	128	5	-	-	ADJ
cana-1016	128	6	trained	trained	ADJ
cana-1016	128	7	weights	weight	NOUN
cana-1016	128	8	accelerates	accelerate	VERB
cana-1016	128	9	the	the	DET
cana-1016	128	10	process	process	NOUN
cana-1016	128	11	,	,	PUNCT
cana-1016	128	12	data	datum	NOUN
cana-1016	128	13	augmentation	augmentation	NOUN
cana-1016	128	14	mitigates	mitigates	AUX
cana-1016	128	15	overfitting	overfitte	VERB
cana-1016	128	16	,	,	PUNCT
cana-1016	128	17	image	image	NOUN
cana-1016	128	18	normalization	normalization	NOUN
cana-1016	128	19	ensures	ensure	VERB
cana-1016	128	20	consistency	consistency	NOUN
cana-1016	128	21	,	,	PUNCT
cana-1016	128	22	and	and	CCONJ
cana-1016	128	23	a	a	DET
cana-1016	128	24	robust	robust	ADJ
cana-1016	128	25	framework	framework	NOUN
cana-1016	128	26	for	for	ADP
cana-1016	128	27	accurate	accurate	ADJ
cana-1016	128	28	skin	skin	NOUN
cana-1016	128	29	cancer	cancer	NOUN
cana-1016	128	30	detection	detection	NOUN
cana-1016	128	31	is	be	AUX
cana-1016	128	32	established	establish	VERB
cana-1016	128	33	through	through	ADP
cana-1016	128	34	feature	feature	NOUN
cana-1016	128	35	extraction	extraction	NOUN
cana-1016	128	36	and	and	CCONJ
cana-1016	128	37	decision	decision	NOUN
cana-1016	128	38	-	-	PUNCT
cana-1016	128	39	making	making	NOUN
cana-1016	128	40	,	,	PUNCT
cana-1016	128	41	as	as	SCONJ
cana-1016	128	42	illustrated	illustrate	VERB
cana-1016	128	43	in	in	ADP
cana-1016	128	44	the	the	DET
cana-1016	128	45	figure	figure	NOUN
cana-1016	128	46	2	2	NUM
cana-1016	128	47	.	.	NOUN
cana-1016	128	48	3.4	3.4	NUM
cana-1016	128	49	convolutional	convolutional	ADJ
cana-1016	128	50	neural	neural	ADJ
cana-1016	128	51	network	network	NOUN
cana-1016	128	52	based	base	VERB
cana-1016	128	53	skin	skin	NOUN
cana-1016	128	54	cancer	cancer	NOUN
cana-1016	128	55	detection	detection	NOUN
cana-1016	128	56	cnns	cnn	NOUN
cana-1016	128	57	are	be	AUX
cana-1016	128	58	a	a	DET
cana-1016	128	59	vital	vital	ADJ
cana-1016	128	60	type	type	NOUN
cana-1016	128	61	of	of	ADP
cana-1016	128	62	deep	deep	ADJ
cana-1016	128	63	neural	neural	ADJ
cana-1016	128	64	network	network	NOUN
cana-1016	128	65	that	that	PRON
cana-1016	128	66	finds	find	VERB
cana-1016	128	67	effective	effective	ADJ
cana-1016	128	68	applications	application	NOUN
cana-1016	128	69	in	in	ADP
cana-1016	128	70	visual	visual	ADJ
cana-1016	128	71	recognition	recognition	NOUN
cana-1016	128	72	.	.	PUNCT
cana-1016	129	1	it	it	PRON
cana-1016	129	2	is	be	AUX
cana-1016	129	3	employed	employ	VERB
cana-1016	129	4	for	for	ADP
cana-1016	129	5	image	image	NOUN
cana-1016	129	6	categorization	categorization	NOUN
cana-1016	129	7	,	,	PUNCT
cana-1016	129	8	creating	create	VERB
cana-1016	129	9	a	a	DET
cana-1016	129	10	compilation	compilation	NOUN
cana-1016	129	11	of	of	ADP
cana-1016	129	12	the	the	DET
cana-1016	129	13	supplied	supply	VERB
cana-1016	129	14	images	image	NOUN
cana-1016	129	15	,	,	PUNCT
cana-1016	129	16	and	and	CCONJ
cana-1016	129	17	performing	perform	VERB
cana-1016	129	18	picture	picture	NOUN
cana-1016	129	19	identification	identification	NOUN
cana-1016	129	20	.	.	PUNCT
cana-1016	130	1	a	a	DET
cana-1016	130	2	convolutional	convolutional	ADJ
cana-1016	130	3	neural	neural	ADJ
cana-1016	130	4	network	network	NOUN
cana-1016	130	5	is	be	AUX
cana-1016	130	6	an	an	DET
cana-1016	130	7	excellent	excellent	ADJ
cana-1016	130	8	method	method	NOUN
cana-1016	130	9	of	of	ADP
cana-1016	130	10	collecting	collect	VERB
cana-1016	130	11	and	and	CCONJ
cana-1016	130	12	processing	process	VERB
cana-1016	130	13	local	local	ADJ
cana-1016	130	14	and	and	CCONJ
cana-1016	130	15	global	global	ADJ
cana-1016	130	16	data	datum	NOUN
cana-1016	130	17	because	because	SCONJ
cana-1016	130	18	it	it	PRON
cana-1016	130	19	combines	combine	VERB
cana-1016	130	20	basic	basic	ADJ
cana-1016	130	21	features	feature	NOUN
cana-1016	130	22	such	such	ADJ
cana-1016	130	23	as	as	ADP
cana-1016	130	24	curves	curve	NOUN
cana-1016	130	25	and	and	CCONJ
cana-1016	130	26	edges	edge	NOUN
cana-1016	130	27	to	to	PART
cana-1016	130	28	build	build	VERB
cana-1016	130	29	more	more	ADV
cana-1016	130	30	intricate	intricate	ADJ
cana-1016	130	31	elements	element	NOUN
cana-1016	130	32	such	such	ADJ
cana-1016	130	33	as	as	ADP
cana-1016	130	34	shapes	shape	NOUN
cana-1016	130	35	and	and	CCONJ
cana-1016	130	36	edges	edge	NOUN
cana-1016	130	37	.	.	PUNCT
cana-1016	131	1	convolutional	convolutional	ADJ
cana-1016	131	2	neural	neural	ADJ
cana-1016	131	3	network	network	NOUN
cana-1016	131	4	intermediate	intermediate	ADJ
cana-1016	131	5	layers	layer	NOUN
cana-1016	131	6	are	be	AUX
cana-1016	131	7	made	make	VERB
cana-1016	131	8	up	up	ADP
cana-1016	131	9	of	of	ADP
cana-1016	131	10	convolutional	convolutional	ADJ
cana-1016	131	11	,	,	PUNCT
cana-1016	131	12	fully	fully	ADV
cana-1016	131	13	connected	connect	VERB
cana-1016	131	14	,	,	PUNCT
cana-1016	131	15	and	and	CCONJ
cana-1016	131	16	nonlinear	nonlinear	ADJ
cana-1016	131	17	pooling	pool	VERB
cana-1016	131	18	layers	layer	NOUN
cana-1016	131	19	.	.	PUNCT
cana-1016	132	1	cnn	cnn	PROPN
cana-1016	132	2	may	may	AUX
cana-1016	132	3	contain	contain	VERB
cana-1016	132	4	several	several	ADJ
cana-1016	132	5	convolutional	convolutional	ADJ
cana-1016	132	6	layers	layer	NOUN
cana-1016	132	7	,	,	PUNCT
cana-1016	132	8	preceded	precede	VERB
cana-1016	132	9	by	by	ADP
cana-1016	132	10	several	several	ADJ
cana-1016	132	11	fully	fully	ADV
cana-1016	132	12	linked	link	VERB
cana-1016	132	13	layers	layer	NOUN
cana-1016	132	14	.	.	PUNCT
cana-1016	133	1	the	the	DET
cana-1016	133	2	three	three	NUM
cana-1016	133	3	primary	primary	ADJ
cana-1016	133	4	types	type	NOUN
cana-1016	133	5	of	of	ADP
cana-1016	133	6	layers	layer	NOUN
cana-1016	133	7	utilized	utilize	VERB
cana-1016	133	8	in	in	ADP
cana-1016	133	9	cnn	cnn	PROPN
cana-1016	133	10	are	be	AUX
cana-1016	133	11	convolution	convolution	NOUN
cana-1016	133	12	,	,	PUNCT
cana-1016	133	13	pooling	pooling	NOUN
cana-1016	133	14	,	,	PUNCT
cana-1016	133	15	and	and	CCONJ
cana-1016	133	16	full	full	ADV
cana-1016	133	17	-	-	PUNCT
cana-1016	133	18	connected	connected	ADJ
cana-1016	133	19	layers	layer	NOUN
cana-1016	133	20	.	.	PUNCT
cana-1016	134	1	fig	fig	NOUN
cana-1016	134	2	3	3	NUM
cana-1016	134	3	presents	present	VERB
cana-1016	134	4	cnn	cnn	PROPN
cana-1016	134	5	's	's	PART
cana-1016	134	6	fundamental	fundamental	ADJ
cana-1016	134	7	architecture	architecture	NOUN
cana-1016	134	8	[	[	X
cana-1016	134	9	19	19	NUM
cana-1016	134	10	]	]	PUNCT
cana-1016	134	11	.	.	PUNCT
cana-1016	135	1	figure	figure	NOUN
cana-1016	135	2	2	2	NUM
cana-1016	135	3	.	.	PUNCT
cana-1016	136	1	deep	deep	ADJ
cana-1016	136	2	learning	learning	NOUN
cana-1016	136	3	-	-	PUNCT
cana-1016	136	4	based	base	VERB
cana-1016	136	5	skin	skin	NOUN
cana-1016	136	6	cancer	cancer	NOUN
cana-1016	136	7	detection	detection	NOUN
cana-1016	136	8	pipeline	pipeline	NOUN
cana-1016	136	9	communications	communication	NOUN
cana-1016	136	10	on	on	ADP
cana-1016	136	11	applied	apply	VERB
cana-1016	136	12	nonlinear	nonlinear	ADJ
cana-1016	136	13	analysis	analysis	NOUN
cana-1016	136	14	issn	issn	NOUN
cana-1016	136	15	:	:	PUNCT
cana-1016	136	16	1074	1074	NUM
cana-1016	136	17	-	-	PUNCT
cana-1016	136	18	133x	133x	NUM
cana-1016	136	19	vol	vol	NOUN
cana-1016	136	20	31	31	NUM
cana-1016	136	21	no	no	NOUN
cana-1016	136	22	.	.	PUNCT
cana-1016	137	1	5s	5s	NUM
cana-1016	137	2	(	(	PUNCT
cana-1016	137	3	2024	2024	NUM
cana-1016	137	4	)	)	PUNCT
cana-1016	137	5	219	219	NUM
cana-1016	138	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	138	2	figure	figure	NOUN
cana-1016	138	3	3	3	NUM
cana-1016	138	4	.	.	PUNCT
cana-1016	138	5	skin	skin	NOUN
cana-1016	138	6	cancer	cancer	NOUN
cana-1016	138	7	detection	detection	PROPN
cana-1016	138	8	cnn	cnn	PROPN
cana-1016	138	9	architecture	architecture	NOUN
cana-1016	138	10	4	4	NUM
cana-1016	138	11	.	.	PUNCT
cana-1016	138	12	experimental	experimental	ADJ
cana-1016	138	13	results	result	NOUN
cana-1016	138	14	and	and	CCONJ
cana-1016	138	15	data	datum	NOUN
cana-1016	138	16	analysis	analysis	NOUN
cana-1016	138	17	4.1	4.1	NUM
cana-1016	138	18	model	model	NOUN
cana-1016	138	19	performance	performance	NOUN
cana-1016	138	20	in	in	ADP
cana-1016	138	21	skin	skin	NOUN
cana-1016	138	22	cancer	cancer	NOUN
cana-1016	138	23	classification	classification	NOUN
cana-1016	138	24	the	the	DET
cana-1016	138	25	utilization	utilization	NOUN
cana-1016	138	26	of	of	ADP
cana-1016	138	27	pre	pre	ADJ
cana-1016	138	28	-	-	ADJ
cana-1016	138	29	trained	train	VERB
cana-1016	138	30	deep	deep	ADJ
cana-1016	138	31	learning	learning	NOUN
cana-1016	138	32	models	model	NOUN
cana-1016	138	33	has	have	AUX
cana-1016	138	34	become	become	VERB
cana-1016	138	35	a	a	DET
cana-1016	138	36	prominent	prominent	ADJ
cana-1016	138	37	approach	approach	NOUN
cana-1016	138	38	in	in	ADP
cana-1016	138	39	various	various	ADJ
cana-1016	138	40	domains	domain	NOUN
cana-1016	138	41	,	,	PUNCT
cana-1016	138	42	particularly	particularly	ADV
cana-1016	138	43	in	in	ADP
cana-1016	138	44	the	the	DET
cana-1016	138	45	field	field	NOUN
cana-1016	138	46	of	of	ADP
cana-1016	138	47	computer	computer	NOUN
cana-1016	138	48	-	-	PUNCT
cana-1016	138	49	aided	aid	VERB
cana-1016	138	50	diagnosis	diagnosis	NOUN
cana-1016	138	51	for	for	ADP
cana-1016	138	52	skin	skin	NOUN
cana-1016	138	53	cancer	cancer	NOUN
cana-1016	138	54	.	.	PUNCT
cana-1016	139	1	this	this	DET
cana-1016	139	2	study	study	NOUN
cana-1016	139	3	offers	offer	VERB
cana-1016	139	4	a	a	DET
cana-1016	139	5	comprehensive	comprehensive	ADJ
cana-1016	139	6	performance	performance	NOUN
cana-1016	139	7	evaluation	evaluation	NOUN
cana-1016	139	8	of	of	ADP
cana-1016	139	9	several	several	ADJ
cana-1016	139	10	pre	pre	ADJ
cana-1016	139	11	-	-	ADJ
cana-1016	139	12	trained	train	VERB
cana-1016	139	13	models	model	NOUN
cana-1016	139	14	when	when	SCONJ
cana-1016	139	15	employed	employ	VERB
cana-1016	139	16	in	in	ADP
cana-1016	139	17	skin	skin	NOUN
cana-1016	139	18	cancer	cancer	NOUN
cana-1016	139	19	classification	classification	NOUN
cana-1016	139	20	.	.	PUNCT
cana-1016	140	1	the	the	DET
cana-1016	140	2	focus	focus	NOUN
cana-1016	140	3	lies	lie	VERB
cana-1016	140	4	on	on	ADP
cana-1016	140	5	five	five	NUM
cana-1016	140	6	different	different	ADJ
cana-1016	140	7	deep	deep	ADJ
cana-1016	140	8	learning	learning	NOUN
cana-1016	140	9	classifiers	classifier	NOUN
cana-1016	140	10	:	:	PUNCT
cana-1016	140	11	svm	svm	PROPN
cana-1016	140	12	,	,	PUNCT
cana-1016	140	13	knn	knn	PROPN
cana-1016	140	14	,	,	PUNCT
cana-1016	140	15	decision	decision	NOUN
cana-1016	140	16	tree	tree	NOUN
cana-1016	140	17	,	,	PUNCT
cana-1016	140	18	gradient	gradient	NOUN
cana-1016	140	19	boosting	boosting	NOUN
cana-1016	140	20	,	,	PUNCT
cana-1016	140	21	and	and	CCONJ
cana-1016	140	22	random	random	ADJ
cana-1016	140	23	forest	forest	NOUN
cana-1016	140	24	.	.	PUNCT
cana-1016	141	1	analyzing	analyze	VERB
cana-1016	141	2	the	the	DET
cana-1016	141	3	models	model	NOUN
cana-1016	141	4	mentioned	mention	VERB
cana-1016	141	5	as	as	ADP
cana-1016	141	6	follows	follow	VERB
cana-1016	141	7	:	:	PUNCT
cana-1016	141	8	densenet121	densenet121	ADJ
cana-1016	141	9	,	,	PUNCT
cana-1016	141	10	densenet201	densenet201	PROPN
cana-1016	141	11	,	,	PUNCT
cana-1016	141	12	vgg16	vgg16	PROPN
cana-1016	141	13	,	,	PUNCT
cana-1016	141	14	vgg19	vgg19	PROPN
cana-1016	141	15	,	,	PUNCT
cana-1016	141	16	xception	xception	PROPN
cana-1016	141	17	,	,	PUNCT
cana-1016	141	18	mobilenet	mobilenet	NOUN
cana-1016	141	19	,	,	PUNCT
cana-1016	141	20	resnet50v2	resnet50v2	PROPN
cana-1016	141	21	,	,	PUNCT
cana-1016	141	22	inceptionv3	inceptionv3	NOUN
cana-1016	141	23	,	,	PUNCT
cana-1016	141	24	and	and	CCONJ
cana-1016	141	25	inceptionresnetv2	inceptionresnetv2	NOUN
cana-1016	141	26	.	.	PUNCT
cana-1016	142	1	table	table	NOUN
cana-1016	142	2	3	3	NUM
cana-1016	142	3	further	far	ADV
cana-1016	142	4	shows	show	VERB
cana-1016	142	5	that	that	SCONJ
cana-1016	142	6	pre	pre	VERB
cana-1016	142	7	-	-	ADJ
cana-1016	142	8	trained	trained	ADJ
cana-1016	142	9	dl	dl	PROPN
cana-1016	142	10	algorithms	algorithm	NOUN
cana-1016	142	11	demonstrate	demonstrate	VERB
cana-1016	142	12	quite	quite	ADV
cana-1016	142	13	distinct	distinct	ADJ
cana-1016	142	14	when	when	SCONJ
cana-1016	142	15	applied	apply	VERB
cana-1016	142	16	to	to	ADP
cana-1016	142	17	the	the	DET
cana-1016	142	18	categorization	categorization	NOUN
cana-1016	142	19	of	of	ADP
cana-1016	142	20	skin	skin	NOUN
cana-1016	142	21	cancer	cancer	NOUN
cana-1016	142	22	.	.	PUNCT
cana-1016	143	1	the	the	DET
cana-1016	143	2	presented	present	VERB
cana-1016	143	3	table	table	NOUN
cana-1016	143	4	illustrates	illustrate	VERB
cana-1016	143	5	the	the	DET
cana-1016	143	6	classification	classification	NOUN
cana-1016	143	7	performance	performance	NOUN
cana-1016	143	8	of	of	ADP
cana-1016	143	9	each	each	DET
cana-1016	143	10	model	model	NOUN
cana-1016	143	11	using	use	VERB
cana-1016	143	12	the	the	DET
cana-1016	143	13	five	five	NUM
cana-1016	143	14	deep	deep	ADJ
cana-1016	143	15	learning	learning	NOUN
cana-1016	143	16	classifiers	classifier	NOUN
cana-1016	143	17	,	,	PUNCT
cana-1016	143	18	evaluated	evaluate	VERB
cana-1016	143	19	in	in	ADP
cana-1016	143	20	terms	term	NOUN
cana-1016	143	21	of	of	ADP
cana-1016	143	22	accuracy	accuracy	NOUN
cana-1016	143	23	.	.	PUNCT
cana-1016	144	1	densenet121	densenet121	PROPN
cana-1016	144	2	exhibits	exhibit	VERB
cana-1016	144	3	relatively	relatively	ADV
cana-1016	144	4	low	low	ADJ
cana-1016	144	5	performance	performance	NOUN
cana-1016	144	6	across	across	ADP
cana-1016	144	7	all	all	DET
cana-1016	144	8	classifiers	classifier	NOUN
cana-1016	144	9	.	.	PUNCT
cana-1016	145	1	it	it	PRON
cana-1016	145	2	struggles	struggle	VERB
cana-1016	145	3	to	to	PART
cana-1016	145	4	achieve	achieve	VERB
cana-1016	145	5	high	high	ADJ
cana-1016	145	6	accuracy	accuracy	NOUN
cana-1016	145	7	in	in	ADP
cana-1016	145	8	most	most	ADJ
cana-1016	145	9	cases	case	NOUN
cana-1016	145	10	.	.	PUNCT
cana-1016	146	1	densenet201	densenet201	PROPN
cana-1016	146	2	demonstrates	demonstrate	VERB
cana-1016	146	3	improved	improved	ADJ
cana-1016	146	4	performance	performance	NOUN
cana-1016	146	5	compared	compare	VERB
cana-1016	146	6	to	to	ADP
cana-1016	146	7	densenet121	densenet121	PROPN
cana-1016	146	8	,	,	PUNCT
cana-1016	146	9	especially	especially	ADV
cana-1016	146	10	with	with	ADP
cana-1016	146	11	the	the	DET
cana-1016	146	12	knn	knn	PROPN
cana-1016	146	13	and	and	CCONJ
cana-1016	146	14	decision	decision	NOUN
cana-1016	146	15	tree	tree	NOUN
cana-1016	146	16	classifiers	classifier	NOUN
cana-1016	146	17	.	.	PUNCT
cana-1016	147	1	inceptionv3	inceptionv3	NOUN
cana-1016	147	2	achieves	achieve	VERB
cana-1016	147	3	consistent	consistent	ADJ
cana-1016	147	4	performance	performance	NOUN
cana-1016	147	5	across	across	ADP
cana-1016	147	6	all	all	DET
cana-1016	147	7	classifiers	classifier	NOUN
cana-1016	147	8	,	,	PUNCT
cana-1016	147	9	indicating	indicate	VERB
cana-1016	147	10	its	its	PRON
cana-1016	147	11	robustness	robustness	NOUN
cana-1016	147	12	and	and	CCONJ
cana-1016	147	13	suitability	suitability	NOUN
cana-1016	147	14	for	for	ADP
cana-1016	147	15	various	various	ADJ
cana-1016	147	16	tasks	task	NOUN
cana-1016	147	17	.	.	PUNCT
cana-1016	148	1	inceptionresnetv2	inceptionresnetv2	NOUN
cana-1016	148	2	performs	perform	VERB
cana-1016	148	3	well	well	ADV
cana-1016	148	4	with	with	ADP
cana-1016	148	5	svm	svm	ADJ
cana-1016	148	6	and	and	CCONJ
cana-1016	148	7	decision	decision	NOUN
cana-1016	148	8	tree	tree	NOUN
cana-1016	148	9	,	,	PUNCT
cana-1016	148	10	showcasing	showcase	VERB
cana-1016	148	11	its	its	PRON
cana-1016	148	12	versatility	versatility	NOUN
cana-1016	148	13	.	.	PUNCT
cana-1016	149	1	mobilenet	mobilenet	PROPN
cana-1016	149	2	achieves	achieve	VERB
cana-1016	149	3	modest	modest	ADJ
cana-1016	149	4	accuracy	accuracy	NOUN
cana-1016	149	5	and	and	CCONJ
cana-1016	149	6	shows	show	VERB
cana-1016	149	7	potential	potential	NOUN
cana-1016	149	8	for	for	ADP
cana-1016	149	9	lightweight	lightweight	ADJ
cana-1016	149	10	applications	application	NOUN
cana-1016	149	11	due	due	ADP
cana-1016	149	12	to	to	ADP
cana-1016	149	13	its	its	PRON
cana-1016	149	14	efficient	efficient	ADJ
cana-1016	149	15	architecture	architecture	NOUN
cana-1016	149	16	.	.	PUNCT
cana-1016	150	1	resnet50v2	resnet50v2	NOUN
cana-1016	150	2	and	and	CCONJ
cana-1016	150	3	resnet101	resnet101	PROPN
cana-1016	150	4	deliver	deliver	VERB
cana-1016	150	5	strong	strong	ADJ
cana-1016	150	6	performance	performance	NOUN
cana-1016	150	7	,	,	PUNCT
cana-1016	150	8	especially	especially	ADV
cana-1016	150	9	with	with	ADP
cana-1016	150	10	the	the	DET
cana-1016	150	11	gradient	gradient	NOUN
cana-1016	150	12	boosting	boost	VERB
cana-1016	150	13	classifier	classifier	NOUN
cana-1016	150	14	.	.	PUNCT
cana-1016	151	1	xception	xception	PROPN
cana-1016	151	2	exhibits	exhibit	VERB
cana-1016	151	3	a	a	DET
cana-1016	151	4	moderate	moderate	ADJ
cana-1016	151	5	level	level	NOUN
cana-1016	151	6	of	of	ADP
cana-1016	151	7	performance	performance	NOUN
cana-1016	151	8	,	,	PUNCT
cana-1016	151	9	with	with	ADP
cana-1016	151	10	availability	availability	NOUN
cana-1016	151	11	for	for	ADP
cana-1016	151	12	higher	high	ADJ
cana-1016	151	13	-	-	PUNCT
cana-1016	151	14	level	level	NOUN
cana-1016	151	15	challenges	challenge	NOUN
cana-1016	151	16	.	.	PUNCT
cana-1016	152	1	vgg19	vgg19	VERB
cana-1016	152	2	and	and	CCONJ
cana-1016	152	3	vgg16	vgg16	PROPN
cana-1016	152	4	show	show	VERB
cana-1016	152	5	relatively	relatively	ADV
cana-1016	152	6	high	high	ADJ
cana-1016	152	7	accuracy	accuracy	NOUN
cana-1016	152	8	with	with	ADP
cana-1016	152	9	most	most	ADJ
cana-1016	152	10	classifiers	classifier	NOUN
cana-1016	152	11	,	,	PUNCT
cana-1016	152	12	particularly	particularly	ADV
cana-1016	152	13	with	with	ADP
cana-1016	152	14	gradient	gradient	ADJ
cana-1016	152	15	boosting	boosting	NOUN
cana-1016	152	16	.	.	PUNCT
cana-1016	153	1	this	this	DET
cana-1016	153	2	study	study	NOUN
cana-1016	153	3	highlights	highlight	VERB
cana-1016	153	4	the	the	DET
cana-1016	153	5	impact	impact	NOUN
cana-1016	153	6	of	of	ADP
cana-1016	153	7	model	model	NOUN
cana-1016	153	8	complexity	complexity	NOUN
cana-1016	153	9	on	on	ADP
cana-1016	153	10	classification	classification	NOUN
cana-1016	153	11	accuracy	accuracy	NOUN
cana-1016	153	12	,	,	PUNCT
cana-1016	153	13	illustrating	illustrate	VERB
cana-1016	153	14	the	the	DET
cana-1016	153	15	drawbacks	drawback	NOUN
cana-1016	153	16	between	between	ADP
cana-1016	153	17	model	model	NOUN
cana-1016	153	18	efficiency	efficiency	NOUN
cana-1016	153	19	and	and	CCONJ
cana-1016	153	20	performance	performance	NOUN
cana-1016	153	21	in	in	ADP
cana-1016	153	22	the	the	DET
cana-1016	153	23	context	context	NOUN
cana-1016	153	24	of	of	ADP
cana-1016	153	25	skin	skin	NOUN
cana-1016	153	26	cancer	cancer	NOUN
cana-1016	153	27	diagnosis	diagnosis	NOUN
cana-1016	153	28	.	.	PUNCT
cana-1016	154	1	table	table	NOUN
cana-1016	154	2	3	3	NUM
cana-1016	154	3	.	.	PUNCT
cana-1016	154	4	performance	performance	NOUN
cana-1016	154	5	evaluation	evaluation	NOUN
cana-1016	154	6	of	of	ADP
cana-1016	154	7	pre	pre	ADJ
cana-1016	154	8	-	-	ADJ
cana-1016	154	9	trained	train	VERB
cana-1016	154	10	deep	deep	ADJ
cana-1016	154	11	learning	learning	NOUN
cana-1016	154	12	models	model	NOUN
cana-1016	154	13	with	with	ADP
cana-1016	154	14	dl	dl	PROPN
cana-1016	154	15	classifiers	classifier	NOUN
cana-1016	154	16	in	in	ADP
cana-1016	154	17	skin	skin	NOUN
cana-1016	154	18	cancer	cancer	NOUN
cana-1016	154	19	classification	classification	NOUN
cana-1016	154	20	pre	pre	ADJ
cana-1016	154	21	-	-	ADJ
cana-1016	154	22	trained	train	VERB
cana-1016	154	23	model	model	NOUN
cana-1016	154	24	\	\	NOUN
cana-1016	154	25	names	name	NOUN
cana-1016	154	26	of	of	ADP
cana-1016	154	27	classifiers	classifier	NOUN
cana-1016	154	28	svm	svm	VERB
cana-1016	154	29	knn	knn	PROPN
cana-1016	154	30	decision	decision	NOUN
cana-1016	154	31	tree	tree	NOUN
cana-1016	154	32	gradient	gradient	NOUN
cana-1016	154	33	boosting	boost	VERB
cana-1016	154	34	random	random	ADJ
cana-1016	154	35	forest	forest	NOUN
cana-1016	154	36	densenet121	densenet121	PROPN
cana-1016	154	37	0.0144	0.0144	NUM
cana-1016	154	38	0.4766	0.4766	NUM
cana-1016	154	39	0.40084	0.40084	NUM
cana-1016	154	40	0.3203	0.3203	NUM
cana-1016	154	41	0.4245	0.4245	NUM
cana-1016	154	42	densenet201	densenet201	VERB
cana-1016	154	43	0.0427	0.0427	NUM
cana-1016	154	44	0.5152	0.5152	NUM
cana-1016	155	1	0.6644	0.6644	NUM
cana-1016	155	2	0.6072	0.6072	NUM
cana-1016	155	3	0.6453	0.6453	NUM
cana-1016	155	4	inceptionv3	inceptionv3	NOUN
cana-1016	155	5	0.4949	0.4949	NUM
cana-1016	155	6	0.5084	0.5084	NUM
cana-1016	155	7	0.4911	0.4911	NUM
cana-1016	155	8	0.5127	0.5127	NUM
cana-1016	155	9	0.4911	0.4911	NUM
cana-1016	155	10	inceptionresnetv2	inceptionresnetv2	NOUN
cana-1016	155	11	0.5419	0.5419	NUM
cana-1016	155	12	0.4991	0.4991	NUM
cana-1016	155	13	0.4949	0.4949	NUM
cana-1016	155	14	0.4974	0.4974	NUM
cana-1016	155	15	0.4949	0.4949	NUM
cana-1016	155	16	mobilenet	mobilenet	NOUN
cana-1016	155	17	0.0347	0.0347	NOUN
cana-1016	156	1	0.4355	0.4355	NUM
cana-1016	156	2	0.2457	0.2457	NUM
cana-1016	156	3	0.2042	0.2042	NUM
cana-1016	156	4	0.2487	0.2487	NUM
cana-1016	156	5	resnet50v2	resnet50v2	NOUN
cana-1016	156	6	0.5322	0.5322	NUM
cana-1016	156	7	0.4889	0.4889	NUM
cana-1016	156	8	0.4936	0.4936	NUM
cana-1016	156	9	0.5173	0.5173	NUM
cana-1016	156	10	0.4944	0.4944	NUM
cana-1016	156	11	resnet101	resnet101	PROPN
cana-1016	156	12	0.7402	0.7402	NUM
cana-1016	156	13	0.4699	0.4699	NUM
cana-1016	156	14	0.4966	0.4966	NUM
cana-1016	156	15	0.5245	0.5245	NUM
cana-1016	156	16	0.4966	0.4966	NUM
cana-1016	156	17	communications	communication	NOUN
cana-1016	156	18	on	on	ADP
cana-1016	156	19	applied	apply	VERB
cana-1016	156	20	nonlinear	nonlinear	ADJ
cana-1016	156	21	analysis	analysis	NOUN
cana-1016	156	22	issn	issn	NOUN
cana-1016	156	23	:	:	PUNCT
cana-1016	156	24	1074	1074	NUM
cana-1016	156	25	-	-	PUNCT
cana-1016	156	26	133x	133x	NUM
cana-1016	156	27	vol	vol	NOUN
cana-1016	156	28	31	31	NUM
cana-1016	156	29	no	no	NOUN
cana-1016	156	30	.	.	PUNCT
cana-1016	157	1	5s	5s	NUM
cana-1016	157	2	(	(	PUNCT
cana-1016	157	3	2024	2024	NUM
cana-1016	157	4	)	)	PUNCT
cana-1016	157	5	220	220	NUM
cana-1016	157	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	157	7	vgg19	vgg19	VERB
cana-1016	157	8	0.1038	0.1038	NUM
cana-1016	157	9	0.4762	0.4762	NUM
cana-1016	157	10	0.4838	0.4838	NUM
cana-1016	158	1	0.4101	0.4101	NUM
cana-1016	158	2	0.4838	0.4838	NUM
cana-1016	158	3	vgg16	vgg16	VERB
cana-1016	158	4	0.0919	0.0919	NUM
cana-1016	158	5	0.4635	0.4635	NUM
cana-1016	158	6	0.4877	0.4877	NUM
cana-1016	158	7	0.3292	0.3292	NUM
cana-1016	158	8	0.4868	0.4868	NUM
cana-1016	158	9	xception	xception	NOUN
cana-1016	158	10	0.0347	0.0347	NUM
cana-1016	158	11	0.4648	0.4648	NUM
cana-1016	158	12	0.2313	0.2313	NUM
cana-1016	158	13	0.2233	0.2233	NUM
cana-1016	158	14	0.2368	0.2368	NUM
cana-1016	158	15	4.2	4.2	NUM
cana-1016	158	16	evaluation	evaluation	NOUN
cana-1016	158	17	of	of	ADP
cana-1016	158	18	binary	binary	ADJ
cana-1016	158	19	skin	skin	NOUN
cana-1016	158	20	cancer	cancer	NOUN
cana-1016	158	21	classification	classification	NOUN
cana-1016	158	22	models	model	NOUN
cana-1016	158	23	the	the	DET
cana-1016	158	24	custom	custom	NOUN
cana-1016	158	25	cnn	cnn	PROPN
cana-1016	158	26	algorithm	algorithm	PROPN
cana-1016	158	27	outperformed	outperform	VERB
cana-1016	158	28	the	the	DET
cana-1016	158	29	trained	train	VERB
cana-1016	158	30	methods	method	NOUN
cana-1016	158	31	in	in	ADP
cana-1016	158	32	measures	measure	NOUN
cana-1016	158	33	of	of	ADP
cana-1016	158	34	accuracy	accuracy	NOUN
cana-1016	158	35	,	,	PUNCT
cana-1016	158	36	recall	recall	NOUN
cana-1016	158	37	,	,	PUNCT
cana-1016	158	38	precision	precision	NOUN
cana-1016	158	39	,	,	PUNCT
cana-1016	158	40	and	and	CCONJ
cana-1016	158	41	f1	f1	NOUN
cana-1016	158	42	-	-	PUNCT
cana-1016	158	43	score	score	NOUN
cana-1016	158	44	for	for	ADP
cana-1016	158	45	both	both	CCONJ
cana-1016	158	46	benign	benign	ADJ
cana-1016	158	47	and	and	CCONJ
cana-1016	158	48	malignant	malignant	ADJ
cana-1016	158	49	classes	class	NOUN
cana-1016	158	50	.	.	PUNCT
cana-1016	159	1	among	among	ADP
cana-1016	159	2	the	the	DET
cana-1016	159	3	pre	pre	ADJ
cana-1016	159	4	-	-	ADJ
cana-1016	159	5	trained	train	VERB
cana-1016	159	6	models	model	NOUN
cana-1016	159	7	,	,	PUNCT
cana-1016	159	8	densenet121	densenet121	PROPN
cana-1016	159	9	,	,	PUNCT
cana-1016	159	10	densenet201	densenet201	PROPN
cana-1016	159	11	,	,	PUNCT
cana-1016	159	12	mobilenet	mobilenet	NOUN
cana-1016	159	13	,	,	PUNCT
cana-1016	159	14	and	and	CCONJ
cana-1016	159	15	resnet50v2	resnet50v2	NOUN
cana-1016	159	16	showed	show	VERB
cana-1016	159	17	relatively	relatively	ADV
cana-1016	159	18	good	good	ADJ
cana-1016	159	19	performance	performance	NOUN
cana-1016	159	20	.	.	PUNCT
cana-1016	160	1	in	in	ADP
cana-1016	160	2	terms	term	NOUN
cana-1016	160	3	of	of	ADP
cana-1016	160	4	accuracy	accuracy	NOUN
cana-1016	160	5	,	,	PUNCT
cana-1016	160	6	the	the	DET
cana-1016	160	7	custom	custom	NOUN
cana-1016	160	8	cnn	cnn	PROPN
cana-1016	160	9	,	,	PUNCT
cana-1016	160	10	densenet121	densenet121	PROPN
cana-1016	160	11	,	,	PUNCT
cana-1016	160	12	vgg16	vgg16	NOUN
cana-1016	160	13	,	,	PUNCT
cana-1016	160	14	and	and	CCONJ
cana-1016	160	15	vgg19	vgg19	PROPN
cana-1016	160	16	models	model	NOUN
cana-1016	160	17	performed	perform	VERB
cana-1016	160	18	the	the	DET
cana-1016	160	19	best	good	ADJ
cana-1016	160	20	.	.	PUNCT
cana-1016	161	1	regarding	regard	VERB
cana-1016	161	2	recall	recall	NOUN
cana-1016	161	3	,	,	PUNCT
cana-1016	161	4	the	the	DET
cana-1016	161	5	mobilenet	mobilenet	NOUN
cana-1016	161	6	model	model	NOUN
cana-1016	161	7	performed	perform	VERB
cana-1016	161	8	exceptionally	exceptionally	ADV
cana-1016	161	9	well	well	ADV
cana-1016	161	10	for	for	ADP
cana-1016	161	11	malignant	malignant	ADJ
cana-1016	161	12	cases	case	NOUN
cana-1016	161	13	,	,	PUNCT
cana-1016	161	14	but	but	CCONJ
cana-1016	161	15	densenet121	densenet121	PROPN
cana-1016	161	16	,	,	PUNCT
cana-1016	161	17	vgg19	vgg19	NOUN
cana-1016	161	18	,	,	PUNCT
cana-1016	161	19	and	and	CCONJ
cana-1016	161	20	the	the	DET
cana-1016	161	21	custom	custom	NOUN
cana-1016	161	22	cnn	cnn	PROPN
cana-1016	161	23	also	also	ADV
cana-1016	161	24	had	have	VERB
cana-1016	161	25	high	high	ADJ
cana-1016	161	26	recall	recall	NOUN
cana-1016	161	27	values	value	NOUN
cana-1016	161	28	.	.	PUNCT
cana-1016	162	1	in	in	ADP
cana-1016	162	2	terms	term	NOUN
cana-1016	162	3	of	of	ADP
cana-1016	162	4	precision	precision	NOUN
cana-1016	162	5	,	,	PUNCT
cana-1016	162	6	the	the	DET
cana-1016	162	7	mobilenet	mobilenet	NOUN
cana-1016	162	8	model	model	NOUN
cana-1016	162	9	showed	show	VERB
cana-1016	162	10	high	high	ADJ
cana-1016	162	11	precision	precision	NOUN
cana-1016	162	12	for	for	ADP
cana-1016	162	13	benign	benign	ADJ
cana-1016	162	14	cases	case	NOUN
cana-1016	162	15	,	,	PUNCT
cana-1016	162	16	while	while	SCONJ
cana-1016	162	17	densenet121	densenet121	PROPN
cana-1016	162	18	,	,	PUNCT
cana-1016	162	19	vgg19	vgg19	NOUN
cana-1016	162	20	,	,	PUNCT
cana-1016	162	21	and	and	CCONJ
cana-1016	162	22	the	the	DET
cana-1016	162	23	custom	custom	NOUN
cana-1016	162	24	cnn	cnn	PROPN
cana-1016	162	25	had	have	VERB
cana-1016	162	26	good	good	ADJ
cana-1016	162	27	precision	precision	NOUN
cana-1016	162	28	values	value	NOUN
cana-1016	162	29	for	for	ADP
cana-1016	162	30	malignant	malignant	ADJ
cana-1016	162	31	cases	case	NOUN
cana-1016	162	32	.	.	PUNCT
cana-1016	163	1	the	the	DET
cana-1016	163	2	f1	f1	NOUN
cana-1016	163	3	-	-	PUNCT
cana-1016	163	4	score	score	NOUN
cana-1016	163	5	,	,	PUNCT
cana-1016	163	6	which	which	PRON
cana-1016	163	7	balances	balance	VERB
cana-1016	163	8	precision	precision	NOUN
cana-1016	163	9	and	and	CCONJ
cana-1016	163	10	recall	recall	NOUN
cana-1016	163	11	,	,	PUNCT
cana-1016	163	12	demonstrated	demonstrate	VERB
cana-1016	163	13	that	that	SCONJ
cana-1016	163	14	the	the	DET
cana-1016	163	15	custom	custom	NOUN
cana-1016	163	16	cnn	cnn	PROPN
cana-1016	163	17	and	and	CCONJ
cana-1016	163	18	densenet121	densenet121	PROPN
cana-1016	163	19	performed	perform	VERB
cana-1016	163	20	well	well	ADV
cana-1016	163	21	for	for	ADP
cana-1016	163	22	both	both	CCONJ
cana-1016	163	23	benign	benign	ADJ
cana-1016	163	24	and	and	CCONJ
cana-1016	163	25	malignant	malignant	ADJ
cana-1016	163	26	cases	case	NOUN
cana-1016	163	27	.	.	PUNCT
cana-1016	164	1	table	table	NOUN
cana-1016	164	2	4	4	NUM
cana-1016	164	3	.	.	PUNCT
cana-1016	165	1	testing	test	VERB
cana-1016	165	2	for	for	ADP
cana-1016	165	3	evaluation	evaluation	NOUN
cana-1016	165	4	metric	metric	NOUN
cana-1016	165	5	based	base	VERB
cana-1016	165	6	on	on	ADP
cana-1016	165	7	deep	deep	ADJ
cana-1016	165	8	learning	learning	NOUN
cana-1016	165	9	models	model	NOUN
cana-1016	165	10	in	in	ADP
cana-1016	165	11	skin	skin	NOUN
cana-1016	165	12	cancer	cancer	NOUN
cana-1016	165	13	binary	binary	PROPN
cana-1016	165	14	classification	classification	PROPN
cana-1016	165	15	sr	sr	PROPN
cana-1016	165	16	.	.	PUNCT
cana-1016	166	1	no	no	DET
cana-1016	166	2	model	model	NOUN
cana-1016	166	3	name	name	NOUN
cana-1016	166	4	metric	metric	ADJ
cana-1016	166	5	class	class	NOUN
cana-1016	166	6	benign	benign	ADJ
cana-1016	166	7	class	class	NOUN
cana-1016	166	8	malignant	malignant	NOUN
cana-1016	166	9	1	1	NUM
cana-1016	166	10	densenet121	densenet121	PROPN
cana-1016	166	11	accuracy	accuracy	NOUN
cana-1016	166	12	0.8400	0.8400	NUM
cana-1016	166	13	0.8400	0.8400	NUM
cana-1016	166	14	recall	recall	VERB
cana-1016	166	15	0.8033	0.8033	NUM
cana-1016	166	16	0.8767	0.8767	NUM
cana-1016	166	17	precision	precision	NOUN
cana-1016	166	18	0.8669	0.8669	NUM
cana-1016	166	19	0.8168	0.8168	NUM
cana-1016	166	20	f1	f1	NOUN
cana-1016	166	21	-	-	PUNCT
cana-1016	166	22	score	score	NOUN
cana-1016	166	23	0.8339	0.8339	NUM
cana-1016	166	24	0.8457	0.8457	NUM
cana-1016	166	25	2	2	NUM
cana-1016	166	26	densenet201	densenet201	NOUN
cana-1016	166	27	accuracy	accuracy	NOUN
cana-1016	166	28	0.8217	0.8217	NUM
cana-1016	166	29	0.8217	0.8217	NUM
cana-1016	166	30	recall	recall	NOUN
cana-1016	166	31	0.9167	0.9167	NUM
cana-1016	166	32	0.7267	0.7267	NUM
cana-1016	166	33	precision	precision	NOUN
cana-1016	166	34	0.7703	0.7703	NUM
cana-1016	166	35	0.8971	0.8971	NUM
cana-1016	166	36	f1	f1	NOUN
cana-1016	166	37	-	-	PUNCT
cana-1016	166	38	score	score	NOUN
cana-1016	166	39	0.8371	0.8371	NUM
cana-1016	166	40	0.8029	0.8029	NUM
cana-1016	166	41	3	3	NUM
cana-1016	166	42	inceptionresnetv2	inceptionresnetv2	NOUN
cana-1016	166	43	accuracy	accuracy	NOUN
cana-1016	166	44	0.7783	0.7783	NUM
cana-1016	166	45	0.7783	0.7783	NUM
cana-1016	166	46	recall	recall	VERB
cana-1016	166	47	0.7033	0.7033	NUM
cana-1016	166	48	0.8533	0.8533	NUM
cana-1016	166	49	precision	precision	NOUN
cana-1016	166	50	0.8275	0.8275	NUM
cana-1016	166	51	0.7420	0.7420	NUM
cana-1016	166	52	f1	f1	NOUN
cana-1016	166	53	-	-	PUNCT
cana-1016	166	54	score	score	NOUN
cana-1016	166	55	0.7604	0.7604	NUM
cana-1016	166	56	0.7938	0.7938	NUM
cana-1016	166	57	4	4	NUM
cana-1016	166	58	inceptionv3	inceptionv3	NOUN
cana-1016	166	59	accuracy	accuracy	NOUN
cana-1016	166	60	0.7933	0.7933	NUM
cana-1016	166	61	0.7933	0.7933	PRON
cana-1016	166	62	recall	recall	VERB
cana-1016	166	63	0.7867	0.7867	NUM
cana-1016	166	64	0.8000	0.8000	NUM
cana-1016	166	65	precision	precision	NOUN
cana-1016	166	66	0.7973	0.7973	NUM
cana-1016	166	67	0.7895	0.7895	NUM
cana-1016	166	68	f1	f1	NOUN
cana-1016	166	69	-	-	PUNCT
cana-1016	166	70	score	score	NOUN
cana-1016	166	71	0.7919	0.7919	NUM
cana-1016	166	72	0.7947	0.7947	NUM
cana-1016	166	73	5	5	NUM
cana-1016	166	74	mobilenet	mobilenet	NOUN
cana-1016	166	75	accuracy	accuracy	NOUN
cana-1016	166	76	0.8217	0.8217	NUM
cana-1016	166	77	0.8217	0.8217	NUM
cana-1016	166	78	recall	recall	NOUN
cana-1016	166	79	0.6667	0.6667	NUM
cana-1016	166	80	0.9767	0.9767	NUM
cana-1016	166	81	precision	precision	NOUN
cana-1016	166	82	0.9662	0.9662	NUM
cana-1016	166	83	0.7455	0.7455	NUM
cana-1016	166	84	f1	f1	NOUN
cana-1016	166	85	-	-	PUNCT
cana-1016	166	86	score	score	NOUN
cana-1016	166	87	0.7890	0.7890	NUM
cana-1016	166	88	0.8456	0.8456	NUM
cana-1016	166	89	6	6	NUM
cana-1016	166	90	resnet50v2	resnet50v2	NOUN
cana-1016	166	91	accuracy	accuracy	NOUN
cana-1016	166	92	0.8217	0.8217	NUM
cana-1016	166	93	0.8217	0.8217	NUM
cana-1016	166	94	recall	recall	NOUN
cana-1016	166	95	0.8733	0.8733	NUM
cana-1016	166	96	0.7700	0.7700	NUM
cana-1016	166	97	precision	precision	VERB
cana-1016	166	98	0.7915	0.7915	NUM
cana-1016	166	99	0.8587	0.8587	NUM
cana-1016	166	100	f1	f1	NOUN
cana-1016	166	101	-	-	PUNCT
cana-1016	166	102	score	score	NOUN
cana-1016	166	103	0.8304	0.8304	NUM
cana-1016	166	104	0.8120	0.8120	NUM
cana-1016	166	105	7	7	NUM
cana-1016	166	106	resnet101	resnet101	PROPN
cana-1016	166	107	accuracy	accuracy	NOUN
cana-1016	166	108	0.7450	0.7450	NUM
cana-1016	166	109	0.7450	0.7450	NUM
cana-1016	166	110	recall	recall	VERB
cana-1016	166	111	0.8300	0.8300	NUM
cana-1016	166	112	0.6600	0.6600	NUM
cana-1016	166	113	precision	precision	NOUN
cana-1016	166	114	0.7094	0.7094	NUM
cana-1016	166	115	0.7952	0.7952	NUM
cana-1016	166	116	f1	f1	NOUN
cana-1016	166	117	-	-	PUNCT
cana-1016	166	118	score	score	NOUN
cana-1016	166	119	0.7650	0.7650	NUM
cana-1016	166	120	0.7213	0.7213	NUM
cana-1016	166	121	8	8	NUM
cana-1016	166	122	vgg16	vgg16	NOUN
cana-1016	166	123	accuracy	accuracy	NOUN
cana-1016	166	124	0.8250	0.8250	NUM
cana-1016	166	125	0.8250	0.8250	NUM
cana-1016	166	126	communications	communication	NOUN
cana-1016	166	127	on	on	ADP
cana-1016	166	128	applied	apply	VERB
cana-1016	166	129	nonlinear	nonlinear	ADJ
cana-1016	166	130	analysis	analysis	NOUN
cana-1016	166	131	issn	issn	NOUN
cana-1016	166	132	:	:	PUNCT
cana-1016	166	133	1074	1074	NUM
cana-1016	166	134	-	-	PUNCT
cana-1016	166	135	133x	133x	NUM
cana-1016	166	136	vol	vol	NOUN
cana-1016	166	137	31	31	NUM
cana-1016	166	138	no	no	NOUN
cana-1016	166	139	.	.	PUNCT
cana-1016	167	1	5s	5s	NUM
cana-1016	167	2	(	(	PUNCT
cana-1016	167	3	2024	2024	NUM
cana-1016	167	4	)	)	PUNCT
cana-1016	167	5	221	221	NUM
cana-1016	167	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	167	7	recall	recall	VERB
cana-1016	167	8	0.8867	0.8867	NUM
cana-1016	167	9	0.7633	0.7633	NUM
cana-1016	167	10	precision	precision	NOUN
cana-1016	167	11	0.7893	0.7893	NUM
cana-1016	167	12	0.8707	0.8707	NUM
cana-1016	167	13	f1	f1	NOUN
cana-1016	167	14	-	-	PUNCT
cana-1016	167	15	score	score	NOUN
cana-1016	167	16	0.8352	0.8352	NUM
cana-1016	167	17	0.8135	0.8135	NUM
cana-1016	167	18	9	9	NUM
cana-1016	167	19	vgg19	vgg19	NOUN
cana-1016	167	20	accuracy	accuracy	NOUN
cana-1016	167	21	0.8367	0.8367	NUM
cana-1016	167	22	0.8367	0.8367	NUM
cana-1016	167	23	recall	recall	VERB
cana-1016	167	24	0.7467	0.7467	NUM
cana-1016	167	25	0.9267	0.9267	NUM
cana-1016	167	26	precision	precision	NOUN
cana-1016	167	27	0.9106	0.9106	NUM
cana-1016	167	28	0.7853	0.7853	NUM
cana-1016	167	29	f1	f1	NOUN
cana-1016	167	30	-	-	PUNCT
cana-1016	167	31	score	score	NOUN
cana-1016	168	1	0.8205	0.8205	NUM
cana-1016	168	2	0.8502	0.8502	NUM
cana-1016	168	3	10	10	NUM
cana-1016	168	4	xception	xception	PROPN
cana-1016	168	5	accuracy	accuracy	NOUN
cana-1016	168	6	0.7833	0.7833	NUM
cana-1016	168	7	0.7833	0.7833	NUM
cana-1016	168	8	recall	recall	VERB
cana-1016	168	9	0.8233	0.8233	NUM
cana-1016	168	10	0.7433	0.7433	NUM
cana-1016	168	11	precision	precision	NOUN
cana-1016	168	12	0.7623	0.7623	NUM
cana-1016	168	13	0.8080	0.8080	NUM
cana-1016	168	14	f1	f1	NOUN
cana-1016	168	15	-	-	PUNCT
cana-1016	168	16	score	score	NOUN
cana-1016	168	17	0.7917	0.7917	NUM
cana-1016	168	18	0.7743	0.7743	NUM
cana-1016	168	19	11	11	NUM
cana-1016	168	20	custom	custom	NOUN
cana-1016	168	21	cnn	cnn	PROPN
cana-1016	168	22	accuracy	accuracy	NOUN
cana-1016	168	23	0.8617	0.8617	NUM
cana-1016	168	24	0.8617	0.8617	NUM
cana-1016	168	25	recall	recall	VERB
cana-1016	168	26	0.8533	0.8533	NUM
cana-1016	168	27	0.8700	0.8700	NUM
cana-1016	168	28	precision	precision	NOUN
cana-1016	168	29	0.8678	0.8678	NUM
cana-1016	168	30	0.8557	0.8557	NUM
cana-1016	168	31	f1	f1	NOUN
cana-1016	168	32	-	-	PUNCT
cana-1016	168	33	score	score	NOUN
cana-1016	168	34	0.8605	0.8605	NUM
cana-1016	168	35	0.8628	0.8628	NUM
cana-1016	168	36	4.3	4.3	NUM
cana-1016	168	37	comparative	comparative	ADJ
cana-1016	168	38	analysis	analysis	NOUN
cana-1016	168	39	the	the	DET
cana-1016	168	40	confusion	confusion	NOUN
cana-1016	168	41	matrices	matrix	NOUN
cana-1016	168	42	for	for	ADP
cana-1016	168	43	several	several	ADJ
cana-1016	168	44	dl	dl	PROPN
cana-1016	168	45	algorithms	algorithm	NOUN
cana-1016	168	46	with	with	ADP
cana-1016	168	47	the	the	DET
cana-1016	168	48	task	task	NOUN
cana-1016	168	49	of	of	ADP
cana-1016	168	50	categorizing	categorize	VERB
cana-1016	168	51	skin	skin	NOUN
cana-1016	168	52	lesions	lesion	NOUN
cana-1016	168	53	as	as	ADP
cana-1016	168	54	benign	benign	ADJ
cana-1016	168	55	or	or	CCONJ
cana-1016	168	56	malignant	malignant	ADJ
cana-1016	168	57	give	give	VERB
cana-1016	168	58	fascinating	fascinating	ADJ
cana-1016	168	59	perspective	perspective	NOUN
cana-1016	168	60	into	into	ADP
cana-1016	168	61	their	their	PRON
cana-1016	168	62	performance	performance	NOUN
cana-1016	168	63	.	.	PUNCT
cana-1016	169	1	communications	communication	NOUN
cana-1016	169	2	on	on	ADP
cana-1016	169	3	applied	apply	VERB
cana-1016	169	4	nonlinear	nonlinear	ADJ
cana-1016	169	5	analysis	analysis	NOUN
cana-1016	169	6	issn	issn	NOUN
cana-1016	169	7	:	:	PUNCT
cana-1016	169	8	1074	1074	NUM
cana-1016	169	9	-	-	PUNCT
cana-1016	169	10	133x	133x	NUM
cana-1016	169	11	vol	vol	NOUN
cana-1016	169	12	31	31	NUM
cana-1016	169	13	no	no	NOUN
cana-1016	169	14	.	.	PUNCT
cana-1016	170	1	5s	5s	NUM
cana-1016	170	2	(	(	PUNCT
cana-1016	170	3	2024	2024	NUM
cana-1016	170	4	)	)	PUNCT
cana-1016	170	5	222	222	NUM
cana-1016	170	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	170	7	figure	figure	NOUN
cana-1016	170	8	4	4	NUM
cana-1016	170	9	.	.	PUNCT
cana-1016	170	10	performance	performance	NOUN
cana-1016	170	11	comparison	comparison	NOUN
cana-1016	170	12	of	of	ADP
cana-1016	170	13	deep	deep	ADJ
cana-1016	170	14	learning	learning	NOUN
cana-1016	170	15	models	model	NOUN
cana-1016	170	16	for	for	ADP
cana-1016	170	17	skin	skin	NOUN
cana-1016	170	18	cancer	cancer	NOUN
cana-1016	170	19	categorization	categorization	NOUN
cana-1016	170	20	xception	xception	NOUN
cana-1016	170	21	produced	produce	VERB
cana-1016	170	22	a	a	DET
cana-1016	170	23	moderately	moderately	ADV
cana-1016	170	24	satisfactory	satisfactory	ADJ
cana-1016	170	25	categorization	categorization	NOUN
cana-1016	170	26	,	,	PUNCT
cana-1016	170	27	properly	properly	ADV
cana-1016	170	28	detecting	detect	VERB
cana-1016	170	29	225	225	NUM
cana-1016	170	30	benign	benign	ADJ
cana-1016	170	31	and	and	CCONJ
cana-1016	170	32	223	223	NUM
cana-1016	170	33	malignant	malignant	ADJ
cana-1016	170	34	lesions	lesion	NOUN
cana-1016	170	35	,	,	PUNCT
cana-1016	170	36	with	with	ADP
cana-1016	170	37	a	a	DET
cana-1016	170	38	few	few	ADJ
cana-1016	170	39	misclassifications	misclassification	NOUN
cana-1016	170	40	in	in	ADP
cana-1016	170	41	each	each	DET
cana-1016	170	42	group	group	NOUN
cana-1016	170	43	.	.	PUNCT
cana-1016	171	1	densenet201	densenet201	PROPN
cana-1016	171	2	,	,	PUNCT
cana-1016	171	3	exhibited	exhibit	VERB
cana-1016	171	4	a	a	DET
cana-1016	171	5	greater	great	ADJ
cana-1016	171	6	percentage	percentage	NOUN
cana-1016	171	7	of	of	ADP
cana-1016	171	8	misclassification	misclassification	NOUN
cana-1016	171	9	,	,	PUNCT
cana-1016	171	10	notably	notably	ADV
cana-1016	171	11	for	for	ADP
cana-1016	171	12	benign	benign	ADJ
cana-1016	171	13	lesions	lesion	NOUN
cana-1016	171	14	,	,	PUNCT
cana-1016	171	15	where	where	SCONJ
cana-1016	171	16	200	200	NUM
cana-1016	171	17	were	be	AUX
cana-1016	171	18	correctly	correctly	ADV
cana-1016	171	19	recognized	recognize	VERB
cana-1016	171	20	.	.	PUNCT
cana-1016	172	1	the	the	DET
cana-1016	172	2	frequency	frequency	NOUN
cana-1016	172	3	of	of	ADP
cana-1016	172	4	misclassifications	misclassification	NOUN
cana-1016	172	5	was	be	AUX
cana-1016	172	6	much	much	ADV
cana-1016	172	7	greater	great	ADJ
cana-1016	172	8	for	for	ADP
cana-1016	172	9	vgg19	vgg19	PROPN
cana-1016	172	10	and	and	CCONJ
cana-1016	172	11	vgg16	vgg16	PROPN
cana-1016	172	12	,	,	PUNCT
cana-1016	172	13	suggesting	suggest	VERB
cana-1016	172	14	a	a	DET
cana-1016	172	15	less	less	ADV
cana-1016	172	16	accurate	accurate	ADJ
cana-1016	172	17	performance	performance	NOUN
cana-1016	172	18	in	in	ADP
cana-1016	172	19	discriminating	discriminate	VERB
cana-1016	172	20	between	between	ADP
cana-1016	172	21	benign	benign	ADJ
cana-1016	172	22	and	and	CCONJ
cana-1016	172	23	malignant	malignant	ADJ
cana-1016	172	24	cases	case	NOUN
cana-1016	172	25	.	.	PUNCT
cana-1016	173	1	densenet121	densenet121	ADJ
cana-1016	173	2	and	and	CCONJ
cana-1016	173	3	mobilenet	mobilenet	NOUN
cana-1016	173	4	produced	produce	VERB
cana-1016	173	5	a	a	DET
cana-1016	173	6	significantly	significantly	ADV
cana-1016	173	7	improved	improved	ADJ
cana-1016	173	8	misclassifications	misclassification	NOUN
cana-1016	173	9	,	,	PUNCT
cana-1016	173	10	particularly	particularly	ADV
cana-1016	173	11	densenet121	densenet121	PROPN
cana-1016	173	12	,	,	PUNCT
cana-1016	173	13	which	which	PRON
cana-1016	173	14	showed	show	VERB
cana-1016	173	15	a	a	DET
cana-1016	173	16	high	high	ADJ
cana-1016	173	17	accuracy	accuracy	NOUN
cana-1016	173	18	in	in	ADP
cana-1016	173	19	properly	properly	ADV
cana-1016	173	20	diagnosing	diagnose	VERB
cana-1016	173	21	benign	benign	ADJ
cana-1016	173	22	lesions	lesion	NOUN
cana-1016	173	23	.	.	PUNCT
cana-1016	174	1	inceptionv3	inceptionv3	NOUN
cana-1016	174	2	and	and	CCONJ
cana-1016	174	3	inceptionresnetv2	inceptionresnetv2	PROPN
cana-1016	174	4	performed	perform	VERB
cana-1016	174	5	well	well	ADV
cana-1016	174	6	,	,	PUNCT
cana-1016	174	7	with	with	ADP
cana-1016	174	8	a	a	DET
cana-1016	174	9	very	very	ADV
cana-1016	174	10	even	even	ADJ
cana-1016	174	11	distribution	distribution	NOUN
cana-1016	174	12	of	of	ADP
cana-1016	174	13	properly	properly	ADV
cana-1016	174	14	and	and	CCONJ
cana-1016	174	15	wrongly	wrongly	ADV
cana-1016	174	16	categorized	categorize	VERB
cana-1016	174	17	lesions	lesion	NOUN
cana-1016	174	18	in	in	ADP
cana-1016	174	19	both	both	DET
cana-1016	174	20	categories	category	NOUN
cana-1016	174	21	.	.	PUNCT
cana-1016	175	1	resnet-101	resnet-101	PROPN
cana-1016	175	2	had	have	VERB
cana-1016	175	3	more	more	ADJ
cana-1016	175	4	difficulty	difficulty	NOUN
cana-1016	175	5	with	with	ADP
cana-1016	175	6	benign	benign	ADJ
cana-1016	175	7	lesions	lesion	NOUN
cana-1016	175	8	,	,	PUNCT
cana-1016	175	9	misclassifying	misclassifye	VERB
cana-1016	175	10	a	a	DET
cana-1016	175	11	significant	significant	ADJ
cana-1016	175	12	communications	communication	NOUN
cana-1016	175	13	on	on	ADP
cana-1016	175	14	applied	apply	VERB
cana-1016	175	15	nonlinear	nonlinear	ADJ
cana-1016	175	16	analysis	analysis	NOUN
cana-1016	175	17	issn	issn	NOUN
cana-1016	175	18	:	:	PUNCT
cana-1016	175	19	1074	1074	NUM
cana-1016	175	20	-	-	PUNCT
cana-1016	175	21	133x	133x	NUM
cana-1016	175	22	vol	vol	NOUN
cana-1016	175	23	31	31	NUM
cana-1016	175	24	no	no	NOUN
cana-1016	175	25	.	.	PUNCT
cana-1016	176	1	5s	5s	NUM
cana-1016	176	2	(	(	PUNCT
cana-1016	176	3	2024	2024	NUM
cana-1016	176	4	)	)	PUNCT
cana-1016	176	5	223	223	NUM
cana-1016	176	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	176	7	percentage	percentage	NOUN
cana-1016	176	8	of	of	ADP
cana-1016	176	9	them	they	PRON
cana-1016	176	10	as	as	ADP
cana-1016	176	11	malignant	malignant	ADJ
cana-1016	176	12	.	.	PUNCT
cana-1016	177	1	resnet50v2	resnet50v2	NOUN
cana-1016	177	2	also	also	ADV
cana-1016	177	3	had	have	VERB
cana-1016	177	4	difficulty	difficulty	NOUN
cana-1016	177	5	identifying	identify	VERB
cana-1016	177	6	benign	benign	ADJ
cana-1016	177	7	instances	instance	NOUN
cana-1016	177	8	.	.	PUNCT
cana-1016	178	1	finally	finally	ADV
cana-1016	178	2	,	,	PUNCT
cana-1016	178	3	the	the	DET
cana-1016	178	4	custom	custom	NOUN
cana-1016	178	5	cnn	cnn	PROPN
cana-1016	178	6	model	model	NOUN
cana-1016	178	7	produced	produce	VERB
cana-1016	178	8	mixed	mixed	ADJ
cana-1016	178	9	results	result	NOUN
cana-1016	178	10	,	,	PUNCT
cana-1016	178	11	with	with	ADP
cana-1016	178	12	a	a	DET
cana-1016	178	13	large	large	ADJ
cana-1016	178	14	number	number	NOUN
cana-1016	178	15	of	of	ADP
cana-1016	178	16	misclassifications	misclassification	NOUN
cana-1016	178	17	,	,	PUNCT
cana-1016	178	18	particularly	particularly	ADV
cana-1016	178	19	in	in	ADP
cana-1016	178	20	the	the	DET
cana-1016	178	21	case	case	NOUN
cana-1016	178	22	of	of	ADP
cana-1016	178	23	malignant	malignant	ADJ
cana-1016	178	24	lesions	lesion	NOUN
cana-1016	178	25	.	.	PUNCT
cana-1016	179	1	these	these	DET
cana-1016	179	2	findings	finding	NOUN
cana-1016	179	3	imply	imply	VERB
cana-1016	179	4	that	that	SCONJ
cana-1016	179	5	the	the	DET
cana-1016	179	6	deep	deep	ADJ
cana-1016	179	7	learning	learning	NOUN
cana-1016	179	8	algorithm	algorithm	NOUN
cana-1016	179	9	used	use	VERB
cana-1016	179	10	has	have	VERB
cana-1016	179	11	a	a	DET
cana-1016	179	12	considerable	considerable	ADJ
cana-1016	179	13	impact	impact	NOUN
cana-1016	179	14	on	on	ADP
cana-1016	179	15	the	the	DET
cana-1016	179	16	precision	precision	NOUN
cana-1016	179	17	of	of	ADP
cana-1016	179	18	skin	skin	NOUN
cana-1016	179	19	cancer	cancer	NOUN
cana-1016	179	20	lesion	lesion	NOUN
cana-1016	179	21	classification	classification	NOUN
cana-1016	179	22	,	,	PUNCT
cana-1016	179	23	with	with	ADP
cana-1016	179	24	certain	certain	ADJ
cana-1016	179	25	models	model	NOUN
cana-1016	179	26	outperforming	outperform	VERB
cana-1016	179	27	others	other	NOUN
cana-1016	179	28	in	in	ADP
cana-1016	179	29	this	this	DET
cana-1016	179	30	task	task	NOUN
cana-1016	179	31	.	.	PUNCT
cana-1016	180	1	5	5	NUM
cana-1016	180	2	.	.	X
cana-1016	180	3	conclusion	conclusion	NOUN
cana-1016	180	4	this	this	DET
cana-1016	180	5	research	research	NOUN
cana-1016	180	6	findings	finding	NOUN
cana-1016	180	7	present	present	VERB
cana-1016	180	8	a	a	DET
cana-1016	180	9	unique	unique	ADJ
cana-1016	180	10	and	and	CCONJ
cana-1016	180	11	accurate	accurate	ADJ
cana-1016	180	12	mechanism	mechanism	NOUN
cana-1016	180	13	for	for	ADP
cana-1016	180	14	accurately	accurately	ADV
cana-1016	180	15	classifying	classify	VERB
cana-1016	180	16	skin	skin	NOUN
cana-1016	180	17	cancer	cancer	NOUN
cana-1016	180	18	lesions	lesion	NOUN
cana-1016	180	19	into	into	ADP
cana-1016	180	20	benign	benign	ADJ
cana-1016	180	21	and	and	CCONJ
cana-1016	180	22	malignant	malignant	ADJ
cana-1016	180	23	categories	category	NOUN
cana-1016	180	24	.	.	PUNCT
cana-1016	181	1	our	our	PRON
cana-1016	181	2	technique	technique	NOUN
cana-1016	181	3	consistently	consistently	ADV
cana-1016	181	4	outperforms	outperform	VERB
cana-1016	181	5	renowned	renowned	ADJ
cana-1016	181	6	pre	pre	ADJ
cana-1016	181	7	-	-	ADJ
cana-1016	181	8	trained	train	VERB
cana-1016	181	9	models	model	NOUN
cana-1016	181	10	by	by	ADP
cana-1016	181	11	merging	merge	VERB
cana-1016	181	12	a	a	DET
cana-1016	181	13	custom	custom	NOUN
cana-1016	181	14	cnn	cnn	NOUN
cana-1016	181	15	with	with	ADP
cana-1016	181	16	a	a	DET
cana-1016	181	17	svm	svm	ADJ
cana-1016	181	18	model	model	NOUN
cana-1016	181	19	.	.	PUNCT
cana-1016	182	1	for	for	ADP
cana-1016	182	2	both	both	CCONJ
cana-1016	182	3	benign	benign	ADJ
cana-1016	182	4	and	and	CCONJ
cana-1016	182	5	malignant	malignant	ADJ
cana-1016	182	6	instances	instance	NOUN
cana-1016	182	7	,	,	PUNCT
cana-1016	182	8	the	the	DET
cana-1016	182	9	custom	custom	NOUN
cana-1016	182	10	cnn	cnn	PROPN
cana-1016	182	11	outperforms	outperform	NOUN
cana-1016	182	12	in	in	ADP
cana-1016	182	13	terms	term	NOUN
cana-1016	182	14	of	of	ADP
cana-1016	182	15	accuracy	accuracy	NOUN
cana-1016	182	16	,	,	PUNCT
cana-1016	182	17	recall	recall	NOUN
cana-1016	182	18	,	,	PUNCT
cana-1016	182	19	precision	precision	NOUN
cana-1016	182	20	,	,	PUNCT
cana-1016	182	21	and	and	CCONJ
cana-1016	182	22	f1score	f1score	NOUN
cana-1016	182	23	.	.	PUNCT
cana-1016	183	1	models	model	NOUN
cana-1016	183	2	such	such	ADJ
cana-1016	183	3	as	as	ADP
cana-1016	183	4	densenet121	densenet121	PROPN
cana-1016	183	5	,	,	PUNCT
cana-1016	183	6	densenet201	densenet201	PROPN
cana-1016	183	7	,	,	PUNCT
cana-1016	183	8	mobilenet	mobilenet	NOUN
cana-1016	183	9	,	,	PUNCT
cana-1016	183	10	and	and	CCONJ
cana-1016	183	11	resnet50v2	resnet50v2	PROPN
cana-1016	183	12	also	also	ADV
cana-1016	183	13	performed	perform	VERB
cana-1016	183	14	well	well	ADV
cana-1016	183	15	,	,	PUNCT
cana-1016	183	16	with	with	ADP
cana-1016	183	17	the	the	DET
cana-1016	183	18	custom	custom	NOUN
cana-1016	183	19	cnn	cnn	PROPN
cana-1016	183	20	,	,	PUNCT
cana-1016	183	21	densenet121	densenet121	PROPN
cana-1016	183	22	,	,	PUNCT
cana-1016	183	23	vgg16	vgg16	NOUN
cana-1016	183	24	,	,	PUNCT
cana-1016	183	25	and	and	CCONJ
cana-1016	183	26	vgg19	vgg19	INTJ
cana-1016	183	27	dominating	dominate	VERB
cana-1016	183	28	in	in	ADP
cana-1016	183	29	accuracy	accuracy	NOUN
cana-1016	183	30	.	.	PUNCT
cana-1016	184	1	for	for	ADP
cana-1016	184	2	malignant	malignant	ADJ
cana-1016	184	3	cases	case	NOUN
cana-1016	184	4	,	,	PUNCT
cana-1016	184	5	the	the	DET
cana-1016	184	6	mobilenet	mobilenet	NOUN
cana-1016	184	7	model	model	NOUN
cana-1016	184	8	offers	offer	VERB
cana-1016	184	9	the	the	DET
cana-1016	184	10	best	good	ADJ
cana-1016	184	11	recall	recall	NOUN
cana-1016	184	12	,	,	PUNCT
cana-1016	184	13	but	but	CCONJ
cana-1016	184	14	densenet121	densenet121	PROPN
cana-1016	184	15	,	,	PUNCT
cana-1016	184	16	vgg19	vgg19	NOUN
cana-1016	184	17	,	,	PUNCT
cana-1016	184	18	and	and	CCONJ
cana-1016	184	19	the	the	DET
cana-1016	184	20	custom	custom	NOUN
cana-1016	184	21	cnn	cnn	PROPN
cana-1016	184	22	also	also	ADV
cana-1016	184	23	offer	offer	VERB
cana-1016	184	24	excellent	excellent	ADJ
cana-1016	184	25	recall	recall	NOUN
cana-1016	184	26	scores	score	NOUN
cana-1016	184	27	.	.	PUNCT
cana-1016	185	1	in	in	ADP
cana-1016	185	2	terms	term	NOUN
cana-1016	185	3	of	of	ADP
cana-1016	185	4	accuracy	accuracy	NOUN
cana-1016	185	5	,	,	PUNCT
cana-1016	185	6	mobilenet	mobilenet	NOUN
cana-1016	185	7	performs	perform	VERB
cana-1016	185	8	in	in	ADP
cana-1016	185	9	benign	benign	ADJ
cana-1016	185	10	situations	situation	NOUN
cana-1016	185	11	,	,	PUNCT
cana-1016	185	12	whereas	whereas	SCONJ
cana-1016	185	13	densenet121	densenet121	PROPN
cana-1016	185	14	,	,	PUNCT
cana-1016	185	15	vgg19	vgg19	NOUN
cana-1016	185	16	,	,	PUNCT
cana-1016	185	17	and	and	CCONJ
cana-1016	185	18	the	the	DET
cana-1016	185	19	custom	custom	NOUN
cana-1016	185	20	cnn	cnn	PROPN
cana-1016	185	21	excel	excel	VERB
cana-1016	185	22	in	in	ADP
cana-1016	185	23	malignant	malignant	ADJ
cana-1016	185	24	ones	one	NOUN
cana-1016	185	25	.	.	PUNCT
cana-1016	186	1	the	the	DET
cana-1016	186	2	custom	custom	NOUN
cana-1016	186	3	cnn	cnn	PROPN
cana-1016	186	4	's	's	PART
cana-1016	186	5	and	and	CCONJ
cana-1016	186	6	densenet121	densenet121	PROPN
cana-1016	186	7	's	's	PART
cana-1016	186	8	outstanding	outstanding	ADJ
cana-1016	186	9	f1	f1	ADJ
cana-1016	186	10	-	-	PUNCT
cana-1016	186	11	score	score	NOUN
cana-1016	186	12	performance	performance	NOUN
cana-1016	186	13	demonstrates	demonstrate	VERB
cana-1016	186	14	the	the	DET
cana-1016	186	15	dependability	dependability	NOUN
cana-1016	186	16	of	of	ADP
cana-1016	186	17	our	our	PRON
cana-1016	186	18	technique	technique	NOUN
cana-1016	186	19	.	.	PUNCT
cana-1016	187	1	this	this	DET
cana-1016	187	2	novel	novel	ADJ
cana-1016	187	3	technology	technology	NOUN
cana-1016	187	4	has	have	VERB
cana-1016	187	5	the	the	DET
cana-1016	187	6	potential	potential	NOUN
cana-1016	187	7	to	to	PART
cana-1016	187	8	enhance	enhance	VERB
cana-1016	187	9	patient	patient	ADJ
cana-1016	187	10	outcomes	outcome	NOUN
cana-1016	187	11	and	and	CCONJ
cana-1016	187	12	medical	medical	ADJ
cana-1016	187	13	treatment	treatment	NOUN
cana-1016	187	14	efficiency	efficiency	NOUN
cana-1016	187	15	,	,	PUNCT
cana-1016	187	16	consequently	consequently	ADV
cana-1016	187	17	contributing	contribute	VERB
cana-1016	187	18	to	to	ADP
cana-1016	187	19	the	the	DET
cana-1016	187	20	evolution	evolution	NOUN
cana-1016	187	21	of	of	ADP
cana-1016	187	22	healthcare	healthcare	NOUN
cana-1016	187	23	imagery	imagery	NOUN
cana-1016	187	24	and	and	CCONJ
cana-1016	187	25	improving	improve	VERB
cana-1016	187	26	skin	skin	NOUN
cana-1016	187	27	cancer	cancer	NOUN
cana-1016	187	28	detection	detection	NOUN
cana-1016	187	29	and	and	CCONJ
cana-1016	187	30	treatment	treatment	NOUN
cana-1016	187	31	quality	quality	NOUN
cana-1016	187	32	.	.	PUNCT
cana-1016	188	1	references	reference	NOUN
cana-1016	188	2	[	[	X
cana-1016	188	3	1	1	NUM
cana-1016	188	4	]	]	X
cana-1016	188	5	dhatri	dhatri	PROPN
cana-1016	188	6	raval	raval	PROPN
cana-1016	188	7	,	,	PUNCT
cana-1016	188	8	jaimin	jaimin	PROPN
cana-1016	188	9	n.	n.	PROPN
cana-1016	188	10	undavia	undavia	PROPN
cana-1016	188	11	,	,	PUNCT
cana-1016	188	12	a	a	DET
cana-1016	188	13	comprehensive	comprehensive	ADJ
cana-1016	188	14	assessment	assessment	NOUN
cana-1016	188	15	of	of	ADP
cana-1016	188	16	convolutional	convolutional	ADJ
cana-1016	188	17	neural	neural	ADJ
cana-1016	188	18	networks	network	NOUN
cana-1016	188	19	for	for	ADP
cana-1016	188	20	skin	skin	NOUN
cana-1016	188	21	and	and	CCONJ
cana-1016	188	22	oral	oral	ADJ
cana-1016	188	23	cancer	cancer	NOUN
cana-1016	188	24	detection	detection	NOUN
cana-1016	188	25	using	use	VERB
cana-1016	188	26	medical	medical	ADJ
cana-1016	188	27	images	image	NOUN
cana-1016	188	28	,	,	PUNCT
cana-1016	188	29	healthcare	healthcare	NOUN
cana-1016	188	30	analytics	analytic	NOUN
cana-1016	188	31	,	,	PUNCT
cana-1016	188	32	volume	volume	NOUN
cana-1016	188	33	3	3	NUM
cana-1016	188	34	,	,	PUNCT
cana-1016	188	35	2023	2023	NUM
cana-1016	188	36	,	,	PUNCT
cana-1016	188	37	100199	100199	NUM
cana-1016	188	38	,	,	PUNCT
cana-1016	188	39	issn	issn	PROPN
cana-1016	188	40	2772	2772	NUM
cana-1016	188	41	-	-	SYM
cana-1016	188	42	4425	4425	NUM
cana-1016	188	43	,	,	PUNCT
cana-1016	188	44	https://doi.org/10.1016/j.health.2023.100199	https://doi.org/10.1016/j.health.2023.100199	NOUN
cana-1016	188	45	.	.	PUNCT
cana-1016	189	1	[	[	X
cana-1016	189	2	2	2	X
cana-1016	189	3	]	]	X
cana-1016	189	4	vipin	vipin	PROPN
cana-1016	189	5	venugopal	venugopal	NOUN
cana-1016	189	6	,	,	PUNCT
cana-1016	189	7	navin	navin	PROPN
cana-1016	189	8	infant	infant	PROPN
cana-1016	189	9	raj	raj	PROPN
cana-1016	189	10	,	,	PUNCT
cana-1016	189	11	malaya	malaya	PROPN
cana-1016	189	12	kumar	kumar	PROPN
cana-1016	189	13	nath	nath	PROPN
cana-1016	189	14	,	,	PUNCT
cana-1016	189	15	norton	norton	PROPN
cana-1016	189	16	stephen	stephen	PROPN
cana-1016	189	17	,	,	PUNCT
cana-1016	189	18	a	a	DET
cana-1016	189	19	deep	deep	ADJ
cana-1016	189	20	neural	neural	ADJ
cana-1016	189	21	network	network	NOUN
cana-1016	189	22	using	use	VERB
cana-1016	189	23	modified	modify	VERB
cana-1016	189	24	efficientnet	efficientnet	NOUN
cana-1016	189	25	for	for	ADP
cana-1016	189	26	skin	skin	NOUN
cana-1016	189	27	cancer	cancer	NOUN
cana-1016	189	28	detection	detection	NOUN
cana-1016	189	29	in	in	ADP
cana-1016	189	30	dermoscopic	dermoscopic	ADJ
cana-1016	189	31	images	image	NOUN
cana-1016	189	32	,	,	PUNCT
cana-1016	189	33	decision	decision	NOUN
cana-1016	189	34	analytics	analytic	NOUN
cana-1016	189	35	journal	journal	NOUN
cana-1016	189	36	,	,	PUNCT
cana-1016	189	37	volume	volume	NOUN
cana-1016	189	38	8	8	NUM
cana-1016	189	39	,	,	PUNCT
cana-1016	189	40	2023	2023	NUM
cana-1016	189	41	,	,	PUNCT
cana-1016	189	42	100278	100278	NUM
cana-1016	189	43	,	,	PUNCT
cana-1016	189	44	issn	issn	PROPN
cana-1016	189	45	2772	2772	NUM
cana-1016	189	46	-	-	SYM
cana-1016	189	47	6622	6622	NUM
cana-1016	189	48	,	,	PUNCT
cana-1016	189	49	https://doi.org/10.1016/j.dajour.2023.100278	https://doi.org/10.1016/j.dajour.2023.100278	ADJ
cana-1016	189	50	.	.	PUNCT
cana-1016	190	1	[	[	X
cana-1016	190	2	3	3	NUM
cana-1016	190	3	]	]	X
cana-1016	190	4	devakishan	devakishan	NOUN
cana-1016	190	5	adla	adla	NOUN
cana-1016	190	6	,	,	PUNCT
cana-1016	190	7	g.	g.	PROPN
cana-1016	190	8	venkata	venkata	PROPN
cana-1016	190	9	rami	rami	PROPN
cana-1016	190	10	reddy	reddy	PROPN
cana-1016	190	11	,	,	PUNCT
cana-1016	190	12	padmalaya	padmalaya	PROPN
cana-1016	190	13	nayak	nayak	PROPN
cana-1016	190	14	,	,	PUNCT
cana-1016	190	15	g.	g.	PROPN
cana-1016	190	16	karuna	karuna	PROPN
cana-1016	190	17	,	,	PUNCT
cana-1016	190	18	a	a	DET
cana-1016	190	19	full	full	ADJ
cana-1016	190	20	-	-	PUNCT
cana-1016	190	21	resolution	resolution	NOUN
cana-1016	190	22	convolutional	convolutional	ADJ
cana-1016	190	23	network	network	NOUN
cana-1016	190	24	with	with	ADP
cana-1016	190	25	a	a	DET
cana-1016	190	26	dynamic	dynamic	ADJ
cana-1016	190	27	graph	graph	NOUN
cana-1016	190	28	cut	cut	VERB
cana-1016	190	29	algorithm	algorithm	NOUN
cana-1016	190	30	for	for	ADP
cana-1016	190	31	skin	skin	NOUN
cana-1016	190	32	cancer	cancer	NOUN
cana-1016	190	33	classification	classification	NOUN
cana-1016	190	34	and	and	CCONJ
cana-1016	190	35	detection	detection	NOUN
cana-1016	190	36	,	,	PUNCT
cana-1016	190	37	healthcare	healthcare	PROPN
cana-1016	190	38	analytics	analytic	NOUN
cana-1016	190	39	,	,	PUNCT
cana-1016	190	40	volume	volume	NOUN
cana-1016	190	41	3	3	NUM
cana-1016	190	42	,	,	PUNCT
cana-1016	190	43	2023	2023	NUM
cana-1016	190	44	,	,	PUNCT
cana-1016	190	45	100154	100154	NUM
cana-1016	190	46	,	,	PUNCT
cana-1016	190	47	issn	issn	PROPN
cana-1016	190	48	2772	2772	NUM
cana-1016	190	49	-	-	SYM
cana-1016	190	50	4425	4425	NUM
cana-1016	190	51	,	,	PUNCT
cana-1016	190	52	https://doi.org/10.1016/j.health.2023.100154	https://doi.org/10.1016/j.health.2023.100154	NOUN
cana-1016	190	53	.	.	PUNCT
cana-1016	191	1	[	[	X
cana-1016	191	2	4	4	NUM
cana-1016	191	3	]	]	X
cana-1016	191	4	harsh	harsh	PROPN
cana-1016	191	5	bhatt	bhatt	PROPN
cana-1016	191	6	,	,	PUNCT
cana-1016	191	7	vrunda	vrunda	NOUN
cana-1016	191	8	shah	shah	PROPN
cana-1016	191	9	,	,	PUNCT
cana-1016	191	10	krish	krish	PROPN
cana-1016	191	11	shah	shah	PROPN
cana-1016	191	12	,	,	PUNCT
cana-1016	191	13	ruju	ruju	NOUN
cana-1016	191	14	shah	shah	NOUN
cana-1016	191	15	,	,	PUNCT
cana-1016	191	16	manan	manan	PROPN
cana-1016	191	17	shah	shah	PROPN
cana-1016	191	18	,	,	PUNCT
cana-1016	191	19	state	state	NOUN
cana-1016	191	20	-	-	PUNCT
cana-1016	191	21	of	of	ADP
cana-1016	191	22	-	-	PUNCT
cana-1016	191	23	the	the	DET
cana-1016	191	24	-	-	PUNCT
cana-1016	191	25	art	art	NOUN
cana-1016	191	26	machine	machine	NOUN
cana-1016	191	27	learning	learn	VERB
cana-1016	191	28	techniques	technique	NOUN
cana-1016	191	29	for	for	ADP
cana-1016	191	30	melanoma	melanoma	NOUN
cana-1016	191	31	skin	skin	NOUN
cana-1016	191	32	cancer	cancer	NOUN
cana-1016	191	33	detection	detection	NOUN
cana-1016	191	34	and	and	CCONJ
cana-1016	191	35	classification	classification	NOUN
cana-1016	191	36	:	:	PUNCT
cana-1016	191	37	a	a	DET
cana-1016	191	38	comprehensive	comprehensive	ADJ
cana-1016	191	39	review	review	NOUN
cana-1016	191	40	,	,	PUNCT
cana-1016	191	41	intelligent	intelligent	ADJ
cana-1016	191	42	medicine	medicine	NOUN
cana-1016	191	43	,	,	PUNCT
cana-1016	191	44	2022	2022	NUM
cana-1016	191	45	,	,	PUNCT
cana-1016	191	46	issn	issn	PROPN
cana-1016	191	47	2667	2667	NUM
cana-1016	191	48	-	-	SYM
cana-1016	191	49	1026	1026	NUM
cana-1016	191	50	,	,	PUNCT
cana-1016	191	51	https://doi.org/10.1016/j.imed.2022.08.004	https://doi.org/10.1016/j.imed.2022.08.004	NOUN
cana-1016	191	52	.	.	PUNCT
cana-1016	192	1	[	[	X
cana-1016	192	2	5	5	NUM
cana-1016	192	3	]	]	PUNCT
cana-1016	192	4	ashutosh	ashutosh	PROPN
cana-1016	192	5	lembhe	lembhe	PROPN
cana-1016	192	6	,	,	PUNCT
cana-1016	192	7	pranav	pranav	PROPN
cana-1016	192	8	motarwar	motarwar	PROPN
cana-1016	192	9	,	,	PUNCT
cana-1016	192	10	rudra	rudra	PROPN
cana-1016	192	11	patil	patil	PROPN
cana-1016	192	12	,	,	PUNCT
cana-1016	192	13	susan	susan	PROPN
cana-1016	192	14	elias	elias	PROPN
cana-1016	192	15	,	,	PUNCT
cana-1016	192	16	enhancement	enhancement	NOUN
cana-1016	192	17	in	in	ADP
cana-1016	192	18	skin	skin	NOUN
cana-1016	192	19	cancer	cancer	NOUN
cana-1016	192	20	detection	detection	NOUN
cana-1016	192	21	using	use	VERB
cana-1016	192	22	image	image	NOUN
cana-1016	192	23	super	super	ADJ
cana-1016	192	24	resolution	resolution	NOUN
cana-1016	192	25	and	and	CCONJ
cana-1016	192	26	convolutional	convolutional	ADJ
cana-1016	192	27	neural	neural	ADJ
cana-1016	192	28	network	network	NOUN
cana-1016	192	29	,	,	PUNCT
cana-1016	192	30	procedia	procedia	NOUN
cana-1016	192	31	computer	computer	NOUN
cana-1016	192	32	science	science	NOUN
cana-1016	192	33	,	,	PUNCT
cana-1016	192	34	volume	volume	NOUN
cana-1016	192	35	218	218	NUM
cana-1016	192	36	,	,	PUNCT
cana-1016	192	37	2023	2023	NUM
cana-1016	192	38	,	,	PUNCT
cana-1016	192	39	pages	page	NOUN
cana-1016	192	40	164173	164173	NUM
cana-1016	192	41	,	,	PUNCT
cana-1016	192	42	issn	issn	PROPN
cana-1016	192	43	1877	1877	NUM
cana-1016	192	44	-	-	SYM
cana-1016	192	45	0509	0509	NUM
cana-1016	192	46	,	,	PUNCT
cana-1016	192	47	https://doi.org/10.1016/j.procs.2022.12.412	https://doi.org/10.1016/j.procs.2022.12.412	NOUN
cana-1016	192	48	.	.	PUNCT
cana-1016	193	1	[	[	X
cana-1016	193	2	6	6	NUM
cana-1016	193	3	]	]	PUNCT
cana-1016	193	4	k.	k.	NOUN
cana-1016	193	5	mridha	mridha	PROPN
cana-1016	193	6	,	,	PUNCT
cana-1016	193	7	m.	m.	NOUN
cana-1016	193	8	m.	m.	NOUN
cana-1016	193	9	uddin	uddin	PROPN
cana-1016	193	10	,	,	PUNCT
cana-1016	193	11	j.	j.	PROPN
cana-1016	193	12	shin	shin	PROPN
cana-1016	193	13	,	,	PUNCT
cana-1016	193	14	s.	s.	PROPN
cana-1016	193	15	khadka	khadka	PROPN
cana-1016	193	16	and	and	CCONJ
cana-1016	193	17	m.	m.	PROPN
cana-1016	193	18	f.	f.	PROPN
cana-1016	193	19	mridha	mridha	PROPN
cana-1016	193	20	,	,	PUNCT
cana-1016	193	21	"	"	PUNCT
cana-1016	193	22	an	an	DET
cana-1016	193	23	interpretable	interpretable	ADJ
cana-1016	193	24	skin	skin	NOUN
cana-1016	193	25	cancer	cancer	NOUN
cana-1016	193	26	classification	classification	NOUN
cana-1016	193	27	using	use	VERB
cana-1016	193	28	optimized	optimize	VERB
cana-1016	193	29	convolutional	convolutional	ADJ
cana-1016	193	30	neural	neural	ADJ
cana-1016	193	31	network	network	NOUN
cana-1016	193	32	for	for	ADP
cana-1016	193	33	a	a	DET
cana-1016	193	34	smart	smart	ADJ
cana-1016	193	35	healthcare	healthcare	NOUN
cana-1016	193	36	system	system	NOUN
cana-1016	193	37	,	,	PUNCT
cana-1016	193	38	"	"	PUNCT
cana-1016	193	39	in	in	ADP
cana-1016	193	40	ieee	ieee	NOUN
cana-1016	193	41	access	access	NOUN
cana-1016	193	42	,	,	PUNCT
cana-1016	193	43	vol	vol	NOUN
cana-1016	193	44	.	.	PROPN
cana-1016	193	45	11	11	NUM
cana-1016	193	46	,	,	PUNCT
cana-1016	193	47	pp	pp	ADJ
cana-1016	193	48	.	.	PUNCT
cana-1016	193	49	4100341018	4100341018	NUM
cana-1016	193	50	,	,	PUNCT
cana-1016	193	51	2023	2023	NUM
cana-1016	193	52	,	,	PUNCT
cana-1016	193	53	doi	doi	NOUN
cana-1016	193	54	:	:	PUNCT
cana-1016	193	55	10.1109	10.1109	NUM
cana-1016	193	56	/	/	SYM
cana-1016	193	57	access.2023.3269694	access.2023.3269694	PROPN
cana-1016	193	58	.	.	PUNCT
cana-1016	194	1	[	[	X
cana-1016	194	2	7	7	X
cana-1016	194	3	]	]	X
cana-1016	194	4	shi	shi	PROPN
cana-1016	194	5	wang	wang	PROPN
cana-1016	194	6	,	,	PUNCT
cana-1016	194	7	melika	melika	PROPN
cana-1016	194	8	hamian	hamian	NOUN
cana-1016	194	9	,	,	PUNCT
cana-1016	194	10	"	"	PUNCT
cana-1016	194	11	skin	skin	NOUN
cana-1016	194	12	cancer	cancer	NOUN
cana-1016	194	13	detection	detection	NOUN
cana-1016	194	14	based	base	VERB
cana-1016	194	15	on	on	ADP
cana-1016	194	16	extreme	extreme	ADJ
cana-1016	194	17	learning	learning	NOUN
cana-1016	194	18	machine	machine	NOUN
cana-1016	194	19	and	and	CCONJ
cana-1016	194	20	a	a	DET
cana-1016	194	21	developed	develop	VERB
cana-1016	194	22	version	version	NOUN
cana-1016	194	23	of	of	ADP
cana-1016	194	24	thermal	thermal	ADJ
cana-1016	194	25	exchange	exchange	NOUN
cana-1016	194	26	optimization	optimization	NOUN
cana-1016	194	27	"	"	PUNCT
cana-1016	194	28	,	,	PUNCT
cana-1016	194	29	computational	computational	ADJ
cana-1016	194	30	intelligence	intelligence	NOUN
cana-1016	194	31	and	and	CCONJ
cana-1016	194	32	neuroscience	neuroscience	NOUN
cana-1016	194	33	,	,	PUNCT
cana-1016	194	34	vol	vol	NOUN
cana-1016	194	35	.	.	NOUN
cana-1016	194	36	2021	2021	NUM
cana-1016	194	37	,	,	PUNCT
cana-1016	194	38	article	article	NOUN
cana-1016	194	39	i	i	PROPN
cana-1016	194	40	d	d	PROPN
cana-1016	194	41	9528664	9528664	NUM
cana-1016	194	42	,	,	PUNCT
cana-1016	194	43	13	13	NUM
cana-1016	194	44	pages	page	NOUN
cana-1016	194	45	,	,	PUNCT
cana-1016	194	46	2021	2021	NUM
cana-1016	194	47	.	.	PUNCT
cana-1016	195	1	https://doi.org/10.1155/2021/9528664	https://doi.org/10.1155/2021/9528664	PROPN
cana-1016	195	2	[	[	X
cana-1016	195	3	8	8	NUM
cana-1016	195	4	]	]	X
cana-1016	195	5	umesh	umesh	PROPN
cana-1016	195	6	kumar	kumar	PROPN
cana-1016	195	7	lilhore	lilhore	PROPN
cana-1016	195	8	,	,	PUNCT
cana-1016	195	9	m.	m.	NOUN
cana-1016	195	10	poongodi	poongodi	PROPN
cana-1016	195	11	,	,	PUNCT
cana-1016	195	12	amandeep	amandeep	PROPN
cana-1016	195	13	kaur	kaur	PROPN
cana-1016	195	14	,	,	PUNCT
cana-1016	195	15	sarita	sarita	PROPN
cana-1016	195	16	simaiya	simaiya	PROPN
cana-1016	195	17	,	,	PUNCT
cana-1016	195	18	abeer	abeer	PROPN
cana-1016	195	19	d.	d.	PROPN
cana-1016	195	20	algarni	algarni	PROPN
cana-1016	195	21	,	,	PUNCT
cana-1016	195	22	hela	hela	ADJ
cana-1016	195	23	elmannai	elmannai	NOUN
cana-1016	195	24	,	,	PUNCT
cana-1016	195	25	v.	v.	PROPN
cana-1016	195	26	vijayakumar	vijayakumar	PROPN
cana-1016	195	27	,	,	PUNCT
cana-1016	195	28	godwin	godwin	PROPN
cana-1016	195	29	brown	brown	PROPN
cana-1016	195	30	tunze	tunze	PROPN
cana-1016	195	31	,	,	PUNCT
cana-1016	195	32	mounir	mounir	PROPN
cana-1016	195	33	hamdi	hamdi	PROPN
cana-1016	195	34	,	,	PUNCT
cana-1016	195	35	"	"	PUNCT
cana-1016	195	36	hybrid	hybrid	ADJ
cana-1016	195	37	model	model	NOUN
cana-1016	195	38	for	for	ADP
cana-1016	195	39	detection	detection	NOUN
cana-1016	195	40	of	of	ADP
cana-1016	195	41	cervical	cervical	ADJ
cana-1016	195	42	cancer	cancer	NOUN
cana-1016	195	43	using	use	VERB
cana-1016	195	44	causal	causal	ADJ
cana-1016	195	45	analysis	analysis	NOUN
cana-1016	195	46	and	and	CCONJ
cana-1016	195	47	machine	machine	NOUN
cana-1016	195	48	learning	learn	VERB
cana-1016	195	49	techniques	technique	NOUN
cana-1016	195	50	"	"	PUNCT
cana-1016	195	51	,	,	PUNCT
cana-1016	195	52	computational	computational	ADJ
cana-1016	195	53	and	and	CCONJ
cana-1016	195	54	mathematical	mathematical	ADJ
cana-1016	195	55	methods	method	NOUN
cana-1016	195	56	in	in	ADP
cana-1016	195	57	medicine	medicine	NOUN
cana-1016	195	58	,	,	PUNCT
cana-1016	195	59	vol	vol	NOUN
cana-1016	195	60	.	.	NOUN
cana-1016	195	61	2022	2022	NUM
cana-1016	195	62	,	,	PUNCT
cana-1016	195	63	article	article	NOUN
cana-1016	195	64	i	i	PROPN
cana-1016	195	65	d	d	PROPN
cana-1016	195	66	4688327	4688327	NUM
cana-1016	195	67	,	,	PUNCT
cana-1016	195	68	17	17	NUM
cana-1016	195	69	pages	page	NOUN
cana-1016	195	70	,	,	PUNCT
cana-1016	195	71	2022	2022	NUM
cana-1016	195	72	.	.	PUNCT
cana-1016	196	1	https://doi.org/10.1155/2022/4688327	https://doi.org/10.1155/2022/4688327	NOUN
cana-1016	197	1	[	[	X
cana-1016	197	2	9	9	NUM
cana-1016	197	3	]	]	X
cana-1016	197	4	ahmad	ahmad	PROPN
cana-1016	197	5	m.	m.	PROPN
cana-1016	197	6	khasawneh	khasawneh	PROPN
cana-1016	197	7	,	,	PUNCT
cana-1016	197	8	amal	amal	PROPN
cana-1016	197	9	bukhari	bukhari	PROPN
cana-1016	197	10	,	,	PUNCT
cana-1016	197	11	mahmoud	mahmoud	PROPN
cana-1016	197	12	ahmad	ahmad	PROPN
cana-1016	197	13	al	al	PROPN
cana-1016	197	14	-	-	PUNCT
cana-1016	197	15	khasawneh	khasawneh	PROPN
cana-1016	197	16	,	,	PUNCT
cana-1016	197	17	"	"	PUNCT
cana-1016	197	18	early	early	ADJ
cana-1016	197	19	detection	detection	NOUN
cana-1016	197	20	of	of	ADP
cana-1016	197	21	medical	medical	ADJ
cana-1016	197	22	image	image	NOUN
cana-1016	197	23	analysis	analysis	NOUN
cana-1016	197	24	by	by	ADP
cana-1016	197	25	using	use	VERB
cana-1016	197	26	machine	machine	NOUN
cana-1016	197	27	learning	learning	NOUN
cana-1016	197	28	method	method	NOUN
cana-1016	197	29	"	"	PUNCT
cana-1016	197	30	,	,	PUNCT
cana-1016	197	31	computational	computational	ADJ
cana-1016	197	32	and	and	CCONJ
cana-1016	197	33	mathematical	mathematical	ADJ
cana-1016	197	34	methods	method	NOUN
cana-1016	197	35	in	in	ADP
cana-1016	197	36	medicine	medicine	NOUN
cana-1016	197	37	,	,	PUNCT
cana-1016	197	38	vol	vol	NOUN
cana-1016	197	39	.	.	NOUN
cana-1016	197	40	2022	2022	NUM
cana-1016	197	41	,	,	PUNCT
cana-1016	197	42	article	article	NOUN
cana-1016	197	43	i	i	PROPN
cana-1016	197	44	d	d	PROPN
cana-1016	197	45	3041811	3041811	NUM
cana-1016	197	46	,	,	PUNCT
cana-1016	197	47	11	11	NUM
cana-1016	197	48	pages	page	NOUN
cana-1016	197	49	,	,	PUNCT
cana-1016	197	50	2022	2022	NUM
cana-1016	197	51	.	.	PUNCT
cana-1016	198	1	https://doi.org/10.1155/2022/3041811	https://doi.org/10.1155/2022/3041811	PROPN
cana-1016	198	2	https://doi.org/10.1016/j.health.2023.100199	https://doi.org/10.1016/j.health.2023.100199	PROPN
cana-1016	198	3	https://doi.org/10.1016/j.dajour.2023.100278	https://doi.org/10.1016/j.dajour.2023.100278	ADJ
cana-1016	198	4	https://doi.org/10.1016/j.health.2023.100154	https://doi.org/10.1016/j.health.2023.100154	NOUN
cana-1016	198	5	https://doi.org/10.1016/j.imed.2022.08.004	https://doi.org/10.1016/j.imed.2022.08.004	VERB
cana-1016	198	6	https://doi.org/10.1016/j.procs.2022.12.412	https://doi.org/10.1016/j.procs.2022.12.412	NOUN
cana-1016	198	7	https://doi.org/10.1155/2021/9528664	https://doi.org/10.1155/2021/9528664	PROPN
cana-1016	198	8	https://doi.org/10.1155/2022/4688327	https://doi.org/10.1155/2022/4688327	PROPN
cana-1016	198	9	https://doi.org/10.1155/2022/3041811	https://doi.org/10.1155/2022/3041811	PROPN
cana-1016	198	10	communications	communication	NOUN
cana-1016	198	11	on	on	ADP
cana-1016	198	12	applied	apply	VERB
cana-1016	198	13	nonlinear	nonlinear	ADJ
cana-1016	198	14	analysis	analysis	NOUN
cana-1016	198	15	issn	issn	NOUN
cana-1016	198	16	:	:	PUNCT
cana-1016	198	17	1074	1074	NUM
cana-1016	198	18	-	-	PUNCT
cana-1016	198	19	133x	133x	NUM
cana-1016	198	20	vol	vol	NOUN
cana-1016	198	21	31	31	NUM
cana-1016	198	22	no	no	NOUN
cana-1016	198	23	.	.	PUNCT
cana-1016	199	1	5s	5s	NUM
cana-1016	199	2	(	(	PUNCT
cana-1016	199	3	2024	2024	NUM
cana-1016	199	4	)	)	PUNCT
cana-1016	199	5	224	224	NUM
cana-1016	199	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1016	200	1	[	[	X
cana-1016	200	2	10	10	NUM
cana-1016	200	3	]	]	PUNCT
cana-1016	200	4	m.	m.	NOUN
cana-1016	200	5	shobana	shobana	PROPN
cana-1016	200	6	,	,	PUNCT
cana-1016	200	7	v.	v.	PROPN
cana-1016	200	8	r.	r.	PROPN
cana-1016	200	9	balasraswathi	balasraswathi	PROPN
cana-1016	200	10	,	,	PUNCT
cana-1016	200	11	r.	r.	PROPN
cana-1016	200	12	radhika	radhika	PROPN
cana-1016	200	13	,	,	PUNCT
cana-1016	200	14	ahmed	ahmed	PROPN
cana-1016	200	15	kareem	kareem	PROPN
cana-1016	200	16	oleiwi	oleiwi	PROPN
cana-1016	200	17	,	,	PUNCT
cana-1016	200	18	sushovan	sushovan	ADJ
cana-1016	200	19	chaudhury	chaudhury	PROPN
cana-1016	200	20	,	,	PUNCT
cana-1016	200	21	ajay	ajay	PROPN
cana-1016	200	22	s.	s.	PROPN
cana-1016	200	23	ladkat	ladkat	PROPN
cana-1016	200	24	,	,	PUNCT
cana-1016	200	25	mohd	mohd	PROPN
cana-1016	200	26	naved	naved	ADJ
cana-1016	200	27	,	,	PUNCT
cana-1016	200	28	abdul	abdul	PROPN
cana-1016	200	29	wahab	wahab	PROPN
cana-1016	200	30	rahmani	rahmani	PROPN
cana-1016	200	31	,	,	PUNCT
cana-1016	200	32	"	"	PUNCT
cana-1016	200	33	classification	classification	NOUN
cana-1016	200	34	and	and	CCONJ
cana-1016	200	35	detection	detection	NOUN
cana-1016	200	36	of	of	ADP
cana-1016	200	37	mesothelioma	mesothelioma	NOUN
cana-1016	200	38	cancer	cancer	NOUN
cana-1016	200	39	using	use	VERB
cana-1016	200	40	feature	feature	NOUN
cana-1016	200	41	selection	selection	NOUN
cana-1016	200	42	-	-	PUNCT
cana-1016	200	43	enabled	enable	VERB
cana-1016	200	44	machine	machine	NOUN
cana-1016	200	45	learning	learning	NOUN
cana-1016	200	46	technique	technique	NOUN
cana-1016	200	47	"	"	PUNCT
cana-1016	200	48	,	,	PUNCT
cana-1016	200	49	biomed	biome	VERB
cana-1016	200	50	research	research	NOUN
cana-1016	200	51	international	international	ADJ
cana-1016	200	52	,	,	PUNCT
cana-1016	200	53	vol	vol	NOUN
cana-1016	200	54	.	.	NOUN
cana-1016	200	55	2022	2022	NUM
cana-1016	200	56	,	,	PUNCT
cana-1016	200	57	article	article	NOUN
cana-1016	200	58	i	i	PROPN
cana-1016	200	59	d	d	PROPN
cana-1016	200	60	9900668	9900668	NUM
cana-1016	200	61	,	,	PUNCT
cana-1016	200	62	6	6	NUM
cana-1016	200	63	pages	page	NOUN
cana-1016	200	64	,	,	PUNCT
cana-1016	200	65	2022	2022	NUM
cana-1016	200	66	.	.	PUNCT
cana-1016	201	1	https://doi.org/10.1155/2022/9900668	https://doi.org/10.1155/2022/9900668	VERB
cana-1016	202	1	[	[	X
cana-1016	202	2	11	11	NUM
cana-1016	202	3	]	]	X
cana-1016	202	4	mohammed	mohammed	PROPN
cana-1016	202	5	rakeibul	rakeibul	PROPN
cana-1016	202	6	hasan	hasan	PROPN
cana-1016	202	7	,	,	PUNCT
cana-1016	202	8	mohammed	mohammed	PROPN
cana-1016	202	9	ishraaf	ishraaf	PROPN
cana-1016	202	10	fatemi	fatemi	PROPN
cana-1016	202	11	,	,	PUNCT
cana-1016	202	12	mohammad	mohammad	PROPN
cana-1016	202	13	monirujjaman	monirujjaman	PROPN
cana-1016	202	14	khan	khan	PROPN
cana-1016	202	15	,	,	PUNCT
cana-1016	202	16	manjit	manjit	PROPN
cana-1016	202	17	kaur	kaur	PROPN
cana-1016	202	18	,	,	PUNCT
cana-1016	202	19	atef	atef	PROPN
cana-1016	202	20	zaguia	zaguia	PROPN
cana-1016	202	21	,	,	PUNCT
cana-1016	202	22	"	"	PUNCT
cana-1016	202	23	comparative	comparative	ADJ
cana-1016	202	24	analysis	analysis	NOUN
cana-1016	202	25	of	of	ADP
cana-1016	202	26	skin	skin	NOUN
cana-1016	202	27	cancer	cancer	NOUN
cana-1016	202	28	(	(	PUNCT
cana-1016	202	29	benign	benign	ADJ
cana-1016	202	30	vs.	vs.	X
cana-1016	202	31	malignant	malignant	ADJ
cana-1016	202	32	)	)	PUNCT
cana-1016	202	33	detection	detection	NOUN
cana-1016	202	34	using	use	VERB
cana-1016	202	35	convolutional	convolutional	ADJ
cana-1016	202	36	neural	neural	ADJ
cana-1016	202	37	networks	network	NOUN
cana-1016	202	38	"	"	PUNCT
cana-1016	202	39	,	,	PUNCT
cana-1016	202	40	journal	journal	NOUN
cana-1016	202	41	of	of	ADP
cana-1016	202	42	healthcare	healthcare	PROPN
cana-1016	202	43	engineering	engineering	PROPN
cana-1016	202	44	,	,	PUNCT
cana-1016	202	45	vol	vol	NOUN
cana-1016	202	46	.	.	PROPN
cana-1016	202	47	2021	2021	NUM
cana-1016	202	48	,	,	PUNCT
cana-1016	202	49	article	article	NOUN
cana-1016	202	50	i	i	PROPN
cana-1016	202	51	d	d	PROPN
cana-1016	202	52	5895156	5895156	NUM
cana-1016	202	53	,	,	PUNCT
cana-1016	202	54	17	17	NUM
cana-1016	202	55	pages	page	NOUN
cana-1016	202	56	,	,	PUNCT
cana-1016	202	57	2021	2021	NUM
cana-1016	202	58	.	.	PUNCT
cana-1016	203	1	https://doi.org/10.1155/2021/5895156	https://doi.org/10.1155/2021/5895156	PROPN
cana-1016	204	1	[	[	X
cana-1016	204	2	12	12	NUM
cana-1016	204	3	]	]	X
cana-1016	204	4	sreevidya	sreevidya	PROPN
cana-1016	204	5	r.	r.	PROPN
cana-1016	204	6	c.	c.	PROPN
cana-1016	204	7	,	,	PUNCT
cana-1016	204	8	jalaja	jalaja	PROPN
cana-1016	204	9	g	g	PROPN
cana-1016	204	10	,	,	PUNCT
cana-1016	204	11	sajitha	sajitha	NOUN
cana-1016	204	12	n	n	CCONJ
cana-1016	204	13	,	,	PUNCT
cana-1016	204	14	d.	d.	PROPN
cana-1016	204	15	lakshmi	lakshmi	PROPN
cana-1016	204	16	padmaja	padmaja	PROPN
cana-1016	204	17	,	,	PUNCT
cana-1016	204	18	s.	s.	PROPN
cana-1016	204	19	nagaprasad	nagaprasad	PROPN
cana-1016	204	20	,	,	PUNCT
cana-1016	204	21	kumud	kumud	NOUN
cana-1016	204	22	pant	pant	NOUN
cana-1016	204	23	,	,	PUNCT
cana-1016	204	24	yekula	yekula	PROPN
cana-1016	204	25	prasanna	prasanna	PROPN
cana-1016	204	26	kumar	kumar	PROPN
cana-1016	204	27	,	,	PUNCT
cana-1016	204	28	"	"	PUNCT
cana-1016	204	29	role	role	NOUN
cana-1016	204	30	of	of	ADP
cana-1016	204	31	artificial	artificial	ADJ
cana-1016	204	32	intelligence	intelligence	NOUN
cana-1016	204	33	and	and	CCONJ
cana-1016	204	34	deep	deep	ADJ
cana-1016	204	35	learning	learning	NOUN
cana-1016	204	36	in	in	ADP
cana-1016	204	37	easier	easy	ADJ
cana-1016	204	38	skin	skin	NOUN
cana-1016	204	39	cancer	cancer	NOUN
cana-1016	204	40	detection	detection	NOUN
cana-1016	204	41	through	through	ADP
cana-1016	204	42	antioxidants	antioxidant	NOUN
cana-1016	204	43	present	present	ADJ
cana-1016	204	44	in	in	ADP
cana-1016	204	45	food	food	NOUN
cana-1016	204	46	"	"	PUNCT
cana-1016	204	47	,	,	PUNCT
cana-1016	204	48	journal	journal	NOUN
cana-1016	204	49	of	of	ADP
cana-1016	204	50	food	food	NOUN
cana-1016	204	51	quality	quality	NOUN
cana-1016	204	52	,	,	PUNCT
cana-1016	204	53	vol	vol	NOUN
cana-1016	204	54	.	.	NOUN
cana-1016	204	55	2022	2022	NUM
cana-1016	204	56	,	,	PUNCT
cana-1016	204	57	article	article	NOUN
cana-1016	204	58	i	i	PROPN
cana-1016	204	59	d	d	PROPN
cana-1016	204	60	5890666	5890666	NUM
cana-1016	204	61	,	,	PUNCT
cana-1016	204	62	12	12	NUM
cana-1016	204	63	pages	page	NOUN
cana-1016	204	64	,	,	PUNCT
cana-1016	204	65	2022	2022	NUM
cana-1016	204	66	.	.	PUNCT
cana-1016	205	1	https://doi.org/10.1155/2022/5890666	https://doi.org/10.1155/2022/5890666	PROPN
cana-1016	206	1	[	[	X
cana-1016	206	2	13	13	NUM
cana-1016	206	3	]	]	SYM
cana-1016	206	4	hamza	hamza	PROPN
cana-1016	206	5	abu	abu	PROPN
cana-1016	206	6	owida	owida	PROPN
cana-1016	206	7	,	,	PUNCT
cana-1016	206	8	"	"	PUNCT
cana-1016	206	9	biomimetic	biomimetic	ADJ
cana-1016	206	10	nanoscale	nanoscale	NOUN
cana-1016	206	11	materials	material	NOUN
cana-1016	206	12	for	for	ADP
cana-1016	206	13	skin	skin	NOUN
cana-1016	206	14	cancer	cancer	NOUN
cana-1016	206	15	therapy	therapy	NOUN
cana-1016	206	16	and	and	CCONJ
cana-1016	206	17	detection	detection	NOUN
cana-1016	206	18	"	"	PUNCT
cana-1016	206	19	,	,	PUNCT
cana-1016	206	20	journal	journal	NOUN
cana-1016	206	21	of	of	ADP
cana-1016	206	22	skin	skin	NOUN
cana-1016	206	23	cancer	cancer	NOUN
cana-1016	206	24	,	,	PUNCT
cana-1016	206	25	vol	vol	NOUN
cana-1016	206	26	.	.	NOUN
cana-1016	206	27	2022	2022	NUM
cana-1016	206	28	,	,	PUNCT
cana-1016	206	29	article	article	NOUN
cana-1016	206	30	i	i	PROPN
cana-1016	206	31	d	d	PROPN
cana-1016	206	32	2961996	2961996	NUM
cana-1016	206	33	,	,	PUNCT
cana-1016	206	34	12	12	NUM
cana-1016	206	35	pages	page	NOUN
cana-1016	206	36	,	,	PUNCT
cana-1016	206	37	2022	2022	NUM
cana-1016	206	38	.	.	PUNCT
cana-1016	207	1	https://doi.org/10.1155/2022/2961996	https://doi.org/10.1155/2022/2961996	NOUN
cana-1016	207	2	[	[	X
cana-1016	207	3	14	14	NUM
cana-1016	207	4	]	]	PUNCT
cana-1016	207	5	taher	taher	PROPN
cana-1016	207	6	m.	m.	PROPN
cana-1016	207	7	ghazal	ghazal	PROPN
cana-1016	207	8	,	,	PUNCT
cana-1016	207	9	sajid	sajid	PROPN
cana-1016	207	10	hussain	hussain	PROPN
cana-1016	207	11	,	,	PUNCT
cana-1016	207	12	muhammad	muhammad	PROPN
cana-1016	207	13	farhan	farhan	PROPN
cana-1016	207	14	khan	khan	PROPN
cana-1016	207	15	,	,	PUNCT
cana-1016	207	16	muhammad	muhammad	PROPN
cana-1016	207	17	adnan	adnan	PROPN
cana-1016	207	18	khan	khan	PROPN
cana-1016	207	19	,	,	PUNCT
cana-1016	207	20	raed	raed	PROPN
cana-1016	207	21	a.	a.	PROPN
cana-1016	207	22	t.	t.	PROPN
cana-1016	207	23	said	say	VERB
cana-1016	207	24	,	,	PUNCT
cana-1016	207	25	munir	munir	PROPN
cana-1016	207	26	ahmad	ahmad	PROPN
cana-1016	207	27	,	,	PUNCT
cana-1016	207	28	"	"	PUNCT
cana-1016	207	29	detection	detection	NOUN
cana-1016	207	30	of	of	ADP
cana-1016	207	31	benign	benign	ADJ
cana-1016	207	32	and	and	CCONJ
cana-1016	207	33	malignant	malignant	ADJ
cana-1016	207	34	tumors	tumor	NOUN
cana-1016	207	35	in	in	ADP
cana-1016	207	36	skin	skin	NOUN
cana-1016	207	37	empowered	empower	VERB
cana-1016	207	38	with	with	ADP
cana-1016	207	39	transfer	transfer	NOUN
cana-1016	207	40	learning	learning	NOUN
cana-1016	207	41	"	"	PUNCT
cana-1016	207	42	,	,	PUNCT
cana-1016	207	43	computational	computational	ADJ
cana-1016	207	44	intelligence	intelligence	NOUN
cana-1016	207	45	and	and	CCONJ
cana-1016	207	46	neuroscience	neuroscience	NOUN
cana-1016	207	47	,	,	PUNCT
cana-1016	207	48	vol	vol	NOUN
cana-1016	207	49	.	.	NOUN
cana-1016	207	50	2022	2022	NUM
cana-1016	207	51	,	,	PUNCT
cana-1016	207	52	article	article	NOUN
cana-1016	207	53	i	i	PROPN
cana-1016	207	54	d	d	PROPN
cana-1016	207	55	4826892	4826892	NUM
cana-1016	207	56	,	,	PUNCT
cana-1016	207	57	9	9	NUM
cana-1016	207	58	pages	page	NOUN
cana-1016	207	59	,	,	PUNCT
cana-1016	207	60	2022	2022	NUM
cana-1016	207	61	.	.	PUNCT
cana-1016	208	1	https://doi.org/10.1155/2022/4826892	https://doi.org/10.1155/2022/4826892	PROPN
cana-1016	208	2	[	[	X
cana-1016	208	3	15	15	NUM
cana-1016	208	4	]	]	X
cana-1016	208	5	syeda	syeda	PROPN
cana-1016	208	6	shamaila	shamaila	PROPN
cana-1016	208	7	zareen	zareen	PROPN
cana-1016	208	8	,	,	PUNCT
cana-1016	208	9	sun	sun	NOUN
cana-1016	208	10	guangmin	guangmin	PROPN
cana-1016	208	11	,	,	PUNCT
cana-1016	208	12	yu	yu	PROPN
cana-1016	208	13	li	li	PROPN
cana-1016	208	14	,	,	PUNCT
cana-1016	208	15	mahwish	mahwish	PROPN
cana-1016	208	16	kundi	kundi	PROPN
cana-1016	208	17	,	,	PUNCT
cana-1016	208	18	salman	salman	PROPN
cana-1016	208	19	qadri	qadri	PROPN
cana-1016	208	20	,	,	PUNCT
cana-1016	208	21	syed	syed	PROPN
cana-1016	208	22	furqan	furqan	PROPN
cana-1016	208	23	qadri	qadri	PROPN
cana-1016	208	24	,	,	PUNCT
cana-1016	208	25	mubashir	mubashir	PROPN
cana-1016	208	26	ahmad	ahmad	PROPN
cana-1016	208	27	,	,	PUNCT
cana-1016	208	28	ali	ali	PROPN
cana-1016	208	29	haider	haider	PROPN
cana-1016	208	30	khan	khan	PROPN
cana-1016	208	31	,	,	PUNCT
cana-1016	208	32	"	"	PUNCT
cana-1016	208	33	a	a	DET
cana-1016	208	34	machine	machine	NOUN
cana-1016	208	35	vision	vision	NOUN
cana-1016	208	36	approach	approach	NOUN
cana-1016	208	37	for	for	ADP
cana-1016	208	38	classification	classification	NOUN
cana-1016	208	39	of	of	ADP
cana-1016	208	40	skin	skin	NOUN
cana-1016	208	41	cancer	cancer	NOUN
cana-1016	208	42	using	use	VERB
cana-1016	208	43	hybrid	hybrid	ADJ
cana-1016	208	44	texture	texture	NOUN
cana-1016	208	45	features	feature	NOUN
cana-1016	208	46	"	"	PUNCT
cana-1016	208	47	,	,	PUNCT
cana-1016	208	48	computational	computational	ADJ
cana-1016	208	49	intelligence	intelligence	NOUN
cana-1016	208	50	and	and	CCONJ
cana-1016	208	51	neuroscience	neuroscience	NOUN
cana-1016	208	52	,	,	PUNCT
cana-1016	208	53	vol	vol	NOUN
cana-1016	208	54	.	.	NOUN
cana-1016	208	55	2022	2022	NUM
cana-1016	208	56	,	,	PUNCT
cana-1016	208	57	article	article	NOUN
cana-1016	208	58	i	i	PROPN
cana-1016	208	59	d	d	PROPN
cana-1016	208	60	4942637	4942637	NUM
cana-1016	208	61	,	,	PUNCT
cana-1016	208	62	11	11	NUM
cana-1016	208	63	pages	page	NOUN
cana-1016	208	64	,	,	PUNCT
cana-1016	208	65	2022	2022	NUM
cana-1016	208	66	.	.	PUNCT
cana-1016	209	1	https://doi.org/10.1155/2022/4942637	https://doi.org/10.1155/2022/4942637	PROPN
cana-1016	210	1	[	[	X
cana-1016	210	2	16	16	NUM
cana-1016	210	3	]	]	X
cana-1016	210	4	muhammad	muhammad	PROPN
cana-1016	210	5	arif	arif	PROPN
cana-1016	210	6	,	,	PUNCT
cana-1016	210	7	felix	felix	PROPN
cana-1016	210	8	m.	m.	PROPN
cana-1016	210	9	philip	philip	PROPN
cana-1016	210	10	,	,	PUNCT
cana-1016	210	11	f.	f.	PROPN
cana-1016	210	12	ajesh	ajesh	PROPN
cana-1016	210	13	,	,	PUNCT
cana-1016	210	14	diana	diana	PROPN
cana-1016	210	15	izdrui	izdrui	PROPN
cana-1016	210	16	,	,	PUNCT
cana-1016	210	17	maria	maria	PROPN
cana-1016	210	18	daniela	daniela	PROPN
cana-1016	210	19	craciun	craciun	PROPN
cana-1016	210	20	,	,	PUNCT
cana-1016	210	21	oana	oana	PROPN
cana-1016	210	22	geman	geman	PROPN
cana-1016	210	23	,	,	PUNCT
cana-1016	210	24	"	"	PUNCT
cana-1016	210	25	automated	automated	ADJ
cana-1016	210	26	detection	detection	NOUN
cana-1016	210	27	of	of	ADP
cana-1016	210	28	nonmelanoma	nonmelanoma	ADJ
cana-1016	210	29	skin	skin	NOUN
cana-1016	210	30	cancer	cancer	NOUN
cana-1016	210	31	based	base	VERB
cana-1016	210	32	on	on	ADP
cana-1016	210	33	deep	deep	ADJ
cana-1016	210	34	convolutional	convolutional	ADJ
cana-1016	210	35	neural	neural	ADJ
cana-1016	210	36	network	network	NOUN
cana-1016	210	37	"	"	PUNCT
cana-1016	210	38	,	,	PUNCT
cana-1016	210	39	journal	journal	NOUN
cana-1016	210	40	of	of	ADP
cana-1016	210	41	healthcare	healthcare	PROPN
cana-1016	210	42	engineering	engineering	PROPN
cana-1016	210	43	,	,	PUNCT
cana-1016	210	44	vol	vol	NOUN
cana-1016	210	45	.	.	NOUN
cana-1016	210	46	2022	2022	NUM
cana-1016	210	47	,	,	PUNCT
cana-1016	210	48	article	article	NOUN
cana-1016	210	49	i	i	PROPN
cana-1016	210	50	d	d	PROPN
cana-1016	210	51	6952304	6952304	NUM
cana-1016	210	52	,	,	PUNCT
cana-1016	210	53	15	15	NUM
cana-1016	210	54	pages	page	NOUN
cana-1016	210	55	,	,	PUNCT
cana-1016	210	56	2022	2022	NUM
cana-1016	210	57	.	.	PUNCT
cana-1016	211	1	https://doi.org/10.1155/2022/6952304	https://doi.org/10.1155/2022/6952304	PROPN
cana-1016	211	2	.	.	PUNCT
cana-1016	212	1	[	[	X
cana-1016	212	2	17	17	NUM
cana-1016	212	3	]	]	X
cana-1016	212	4	r.	r.	PROPN
cana-1016	212	5	schiavoni	schiavoni	PROPN
cana-1016	212	6	,	,	PUNCT
cana-1016	212	7	g.	g.	PROPN
cana-1016	212	8	maietta	maietta	PROPN
cana-1016	212	9	,	,	PUNCT
cana-1016	212	10	e.	e.	PROPN
cana-1016	212	11	filieri	filieri	PROPN
cana-1016	212	12	,	,	PUNCT
cana-1016	212	13	a.	a.	NOUN
cana-1016	212	14	masciullo	masciullo	PROPN
cana-1016	212	15	and	and	CCONJ
cana-1016	212	16	a.	a.	PROPN
cana-1016	212	17	cataldo	cataldo	PROPN
cana-1016	212	18	,	,	PUNCT
cana-1016	212	19	"	"	PUNCT
cana-1016	212	20	microwave	microwave	NOUN
cana-1016	212	21	reflectometry	reflectometry	NOUN
cana-1016	212	22	sensing	sense	VERB
cana-1016	212	23	system	system	NOUN
cana-1016	212	24	for	for	ADP
cana-1016	212	25	low	low	ADJ
cana-1016	212	26	-	-	PUNCT
cana-1016	212	27	cost	cost	NOUN
cana-1016	212	28	in	in	ADP
cana-1016	212	29	-	-	PUNCT
cana-1016	212	30	vivo	vivo	NOUN
cana-1016	212	31	skin	skin	NOUN
cana-1016	212	32	cancer	cancer	NOUN
cana-1016	212	33	diagnostics	diagnostic	NOUN
cana-1016	212	34	,	,	PUNCT
cana-1016	212	35	"	"	PUNCT
cana-1016	212	36	in	in	ADP
cana-1016	212	37	ieee	ieee	NOUN
cana-1016	212	38	access	access	NOUN
cana-1016	212	39	,	,	PUNCT
cana-1016	212	40	vol	vol	NOUN
cana-1016	212	41	.	.	PROPN
cana-1016	212	42	11	11	NUM
cana-1016	212	43	,	,	PUNCT
cana-1016	212	44	pp	pp	ADJ
cana-1016	212	45	.	.	PUNCT
cana-1016	212	46	13918	13918	NUM
cana-1016	212	47	-	-	SYM
cana-1016	212	48	13928	13928	NUM
cana-1016	212	49	,	,	PUNCT
cana-1016	212	50	2023	2023	NUM
cana-1016	212	51	,	,	PUNCT
cana-1016	212	52	doi	doi	NOUN
cana-1016	212	53	:	:	PUNCT
cana-1016	212	54	10.1109	10.1109	NUM
cana-1016	212	55	/	/	SYM
cana-1016	212	56	access.2023.3243843	access.2023.3243843	NOUN
cana-1016	212	57	.	.	PUNCT
cana-1016	213	1	[	[	X
cana-1016	213	2	18	18	NUM
cana-1016	213	3	]	]	X
cana-1016	213	4	n.	n.	NOUN
cana-1016	213	5	andreasen	andreasen	NOUN
cana-1016	213	6	et	et	PROPN
cana-1016	213	7	al	al	PROPN
cana-1016	213	8	.	.	PROPN
cana-1016	213	9	,	,	PUNCT
cana-1016	213	10	"	"	PUNCT
cana-1016	213	11	skin	skin	NOUN
cana-1016	213	12	electrical	electrical	ADJ
cana-1016	213	13	resistance	resistance	NOUN
cana-1016	213	14	as	as	ADP
cana-1016	213	15	a	a	DET
cana-1016	213	16	diagnostic	diagnostic	ADJ
cana-1016	213	17	and	and	CCONJ
cana-1016	213	18	therapeutic	therapeutic	ADJ
cana-1016	213	19	biomarker	biomarker	NOUN
cana-1016	213	20	of	of	ADP
cana-1016	213	21	breast	breast	NOUN
cana-1016	213	22	cancer	cancer	NOUN
cana-1016	213	23	measuring	measure	VERB
cana-1016	213	24	lymphatic	lymphatic	ADJ
cana-1016	213	25	regions	region	NOUN
cana-1016	213	26	,	,	PUNCT
cana-1016	213	27	"	"	PUNCT
cana-1016	213	28	in	in	ADP
cana-1016	213	29	ieee	ieee	NOUN
cana-1016	213	30	access	access	NOUN
cana-1016	213	31	,	,	PUNCT
cana-1016	213	32	vol	vol	NOUN
cana-1016	213	33	.	.	NOUN
cana-1016	213	34	9	9	NUM
cana-1016	213	35	,	,	PUNCT
cana-1016	213	36	pp	pp	ADJ
cana-1016	213	37	.	.	PUNCT
cana-1016	213	38	152322	152322	NUM
cana-1016	213	39	-	-	SYM
cana-1016	213	40	152332	152332	NUM
cana-1016	213	41	,	,	PUNCT
cana-1016	213	42	2021	2021	NUM
cana-1016	213	43	,	,	PUNCT
cana-1016	213	44	doi	doi	NOUN
cana-1016	213	45	:	:	PUNCT
cana-1016	213	46	10.1109	10.1109	NUM
cana-1016	213	47	/	/	SYM
cana-1016	213	48	access.2021.3123569	access.2021.3123569	NOUN
cana-1016	213	49	.	.	PUNCT
cana-1016	214	1	[	[	X
cana-1016	214	2	19	19	NUM
cana-1016	214	3	]	]	X
cana-1016	214	4	h.	h.	PROPN
cana-1016	214	5	l.	l.	PROPN
cana-1016	214	6	gururaj	gururaj	PROPN
cana-1016	214	7	,	,	PUNCT
cana-1016	214	8	n.	n.	PROPN
cana-1016	214	9	manju	manju	PROPN
cana-1016	214	10	,	,	PUNCT
cana-1016	214	11	a.	a.	NOUN
cana-1016	214	12	nagarjun	nagarjun	PROPN
cana-1016	214	13	,	,	PUNCT
cana-1016	214	14	v.	v.	ADP
cana-1016	214	15	n.	n.	PROPN
cana-1016	214	16	m.	m.	NOUN
cana-1016	214	17	aradhya	aradhya	PROPN
cana-1016	214	18	and	and	CCONJ
cana-1016	214	19	f.	f.	PROPN
cana-1016	214	20	flammini	flammini	PROPN
cana-1016	214	21	,	,	PUNCT
cana-1016	214	22	"	"	PUNCT
cana-1016	214	23	deepskin	deepskin	NOUN
cana-1016	214	24	:	:	PUNCT
cana-1016	214	25	a	a	DET
cana-1016	214	26	deep	deep	ADJ
cana-1016	214	27	learning	learning	NOUN
cana-1016	214	28	approach	approach	NOUN
cana-1016	214	29	for	for	ADP
cana-1016	214	30	skin	skin	NOUN
cana-1016	214	31	cancer	cancer	NOUN
cana-1016	214	32	classification	classification	NOUN
cana-1016	214	33	,	,	PUNCT
cana-1016	214	34	"	"	PUNCT
cana-1016	214	35	in	in	ADP
cana-1016	214	36	ieee	ieee	NOUN
cana-1016	214	37	access	access	NOUN
cana-1016	214	38	,	,	PUNCT
cana-1016	214	39	vol	vol	NOUN
cana-1016	214	40	.	.	PROPN
cana-1016	214	41	11	11	NUM
cana-1016	214	42	,	,	PUNCT
cana-1016	214	43	pp	pp	ADJ
cana-1016	214	44	.	.	PUNCT
cana-1016	215	1	50205	50205	NUM
cana-1016	215	2	-	-	SYM
cana-1016	215	3	50214	50214	NUM
cana-1016	215	4	,	,	PUNCT
cana-1016	215	5	2023	2023	NUM
cana-1016	215	6	,	,	PUNCT
cana-1016	215	7	doi	doi	NOUN
cana-1016	215	8	:	:	PUNCT
cana-1016	215	9	10.1109	10.1109	NUM
cana-1016	215	10	/	/	SYM
cana-1016	215	11	access.2023.3274848	access.2023.3274848	PROPN
cana-1016	215	12	.	.	PUNCT
cana-1016	216	1	[	[	X
cana-1016	216	2	20	20	NUM
cana-1016	216	3	]	]	SYM
cana-1016	216	4	imran	imran	PROPN
cana-1016	216	5	,	,	PUNCT
cana-1016	216	6	a.	a.	PROPN
cana-1016	216	7	nasir	nasir	PROPN
cana-1016	216	8	,	,	PUNCT
cana-1016	216	9	m.	m.	NOUN
cana-1016	216	10	bilal	bilal	PROPN
cana-1016	216	11	,	,	PUNCT
cana-1016	216	12	g.	g.	PROPN
cana-1016	216	13	sun	sun	PROPN
cana-1016	216	14	,	,	PUNCT
cana-1016	216	15	a.	a.	NOUN
cana-1016	216	16	alzahrani	alzahrani	PROPN
cana-1016	216	17	and	and	CCONJ
cana-1016	216	18	a.	a.	NOUN
cana-1016	216	19	almuhaimeed	almuhaimeed	NOUN
cana-1016	216	20	,	,	PUNCT
cana-1016	216	21	"	"	PUNCT
cana-1016	216	22	skin	skin	NOUN
cana-1016	216	23	cancer	cancer	NOUN
cana-1016	216	24	detection	detection	NOUN
cana-1016	216	25	using	use	VERB
cana-1016	216	26	combined	combined	ADJ
cana-1016	216	27	decision	decision	NOUN
cana-1016	216	28	of	of	ADP
cana-1016	216	29	deep	deep	ADJ
cana-1016	216	30	learners	learner	NOUN
cana-1016	216	31	,	,	PUNCT
cana-1016	216	32	"	"	PUNCT
cana-1016	216	33	in	in	ADP
cana-1016	216	34	ieee	ieee	NOUN
cana-1016	216	35	access	access	NOUN
cana-1016	216	36	,	,	PUNCT
cana-1016	216	37	vol	vol	NOUN
cana-1016	216	38	.	.	PROPN
cana-1016	216	39	10	10	NUM
cana-1016	216	40	,	,	PUNCT
cana-1016	216	41	pp	pp	ADJ
cana-1016	216	42	.	.	PUNCT
cana-1016	217	1	118198	118198	NUM
cana-1016	217	2	-	-	SYM
cana-1016	217	3	118212	118212	NUM
cana-1016	217	4	,	,	PUNCT
cana-1016	217	5	2022	2022	NUM
cana-1016	217	6	,	,	PUNCT
cana-1016	217	7	doi	doi	NOUN
cana-1016	217	8	:	:	PUNCT
cana-1016	217	9	10.1109	10.1109	NUM
cana-1016	217	10	/	/	SYM
cana-1016	217	11	access.2022.3220329	access.2022.3220329	NOUN
cana-1016	217	12	.	.	PUNCT
cana-1016	218	1	[	[	X
cana-1016	218	2	21	21	NUM
cana-1016	218	3	]	]	PUNCT
cana-1016	218	4	z.	z.	PROPN
cana-1016	218	5	lan	lan	PROPN
cana-1016	218	6	,	,	PUNCT
cana-1016	218	7	s.	s.	PROPN
cana-1016	218	8	cai	cai	PROPN
cana-1016	218	9	,	,	PUNCT
cana-1016	218	10	x.	x.	PROPN
cana-1016	218	11	he	he	PRON
cana-1016	218	12	and	and	CCONJ
cana-1016	218	13	x.	x.	PROPN
cana-1016	218	14	wen	wen	PROPN
cana-1016	218	15	,	,	PUNCT
cana-1016	218	16	"	"	PUNCT
cana-1016	218	17	fixcaps	fixcap	NOUN
cana-1016	218	18	:	:	PUNCT
cana-1016	218	19	an	an	DET
cana-1016	218	20	improved	improve	VERB
cana-1016	218	21	capsules	capsule	NOUN
cana-1016	218	22	network	network	NOUN
cana-1016	218	23	for	for	ADP
cana-1016	218	24	diagnosis	diagnosis	NOUN
cana-1016	218	25	of	of	ADP
cana-1016	218	26	skin	skin	NOUN
cana-1016	218	27	cancer	cancer	NOUN
cana-1016	218	28	,	,	PUNCT
cana-1016	218	29	"	"	PUNCT
cana-1016	218	30	in	in	ADP
cana-1016	218	31	ieee	ieee	NOUN
cana-1016	218	32	access	access	NOUN
cana-1016	218	33	,	,	PUNCT
cana-1016	218	34	vol	vol	NOUN
cana-1016	218	35	.	.	PROPN
cana-1016	218	36	10	10	NUM
cana-1016	218	37	,	,	PUNCT
cana-1016	218	38	pp	pp	ADJ
cana-1016	218	39	.	.	PUNCT
cana-1016	219	1	76261	76261	NUM
cana-1016	219	2	-	-	SYM
cana-1016	219	3	76267	76267	NUM
cana-1016	219	4	,	,	PUNCT
cana-1016	219	5	2022	2022	NUM
cana-1016	219	6	,	,	PUNCT
cana-1016	219	7	doi	doi	NOUN
cana-1016	219	8	:	:	PUNCT
cana-1016	219	9	10.1109	10.1109	NUM
cana-1016	219	10	/	/	SYM
cana-1016	219	11	access.2022.3181225	access.2022.3181225	NOUN
cana-1016	219	12	.	.	PUNCT
cana-1016	220	1	[	[	X
cana-1016	220	2	22	22	NUM
cana-1016	220	3	]	]	X
cana-1016	220	4	y.	y.	PROPN
cana-1016	220	5	tian	tian	PROPN
cana-1016	220	6	,	,	PUNCT
cana-1016	220	7	z.	z.	PROPN
cana-1016	220	8	wu	wu	PROPN
cana-1016	220	9	,	,	PUNCT
cana-1016	220	10	j.	j.	PROPN
cana-1016	220	11	zhao	zhao	PROPN
cana-1016	220	12	,	,	PUNCT
cana-1016	220	13	h.	h.	PROPN
cana-1016	220	14	lui	lui	PROPN
cana-1016	220	15	and	and	CCONJ
cana-1016	220	16	h.	h.	PROPN
cana-1016	220	17	zeng	zeng	PROPN
cana-1016	220	18	,	,	PUNCT
cana-1016	220	19	"	"	PUNCT
cana-1016	220	20	cutaneous	cutaneous	ADJ
cana-1016	220	21	porphyrin	porphyrin	NOUN
cana-1016	220	22	exhibits	exhibit	VERB
cana-1016	220	23	anti	anti	ADJ
cana-1016	220	24	-	-	ADJ
cana-1016	220	25	stokes	stokes	ADJ
cana-1016	220	26	fluorescence	fluorescence	NOUN
cana-1016	220	27	emission	emission	NOUN
cana-1016	220	28	under	under	ADP
cana-1016	220	29	continuous	continuous	ADJ
cana-1016	220	30	wave	wave	NOUN
cana-1016	220	31	laser	laser	NOUN
cana-1016	220	32	excitation	excitation	NOUN
cana-1016	220	33	,	,	PUNCT
cana-1016	220	34	"	"	PUNCT
cana-1016	220	35	in	in	ADP
cana-1016	220	36	ieee	ieee	PROPN
cana-1016	220	37	journal	journal	NOUN
cana-1016	220	38	of	of	ADP
cana-1016	220	39	selected	select	VERB
cana-1016	220	40	topics	topic	NOUN
cana-1016	220	41	in	in	ADP
cana-1016	220	42	quantum	quantum	ADJ
cana-1016	220	43	electronics	electronic	NOUN
cana-1016	220	44	,	,	PUNCT
cana-1016	220	45	vol	vol	NOUN
cana-1016	220	46	.	.	PROPN
cana-1016	220	47	29	29	NUM
cana-1016	220	48	,	,	PUNCT
cana-1016	220	49	no	no	INTJ
cana-1016	220	50	.	.	NOUN
cana-1016	220	51	4	4	NUM
cana-1016	220	52	:	:	PUNCT
cana-1016	220	53	biophotonics	biophotonic	NOUN
cana-1016	220	54	,	,	PUNCT
cana-1016	220	55	pp	pp	ADJ
cana-1016	220	56	.	.	PUNCT
cana-1016	221	1	1	1	NUM
cana-1016	221	2	-	-	SYM
cana-1016	221	3	6	6	NUM
cana-1016	221	4	,	,	PUNCT
cana-1016	221	5	july	july	PROPN
cana-1016	221	6	-	-	PUNCT
cana-1016	221	7	aug	aug	PROPN
cana-1016	221	8	.	.	PROPN
cana-1016	221	9	2023	2023	NUM
cana-1016	221	10	,	,	PUNCT
cana-1016	221	11	art	art	NOUN
cana-1016	221	12	no	no	NOUN
cana-1016	221	13	.	.	PUNCT
cana-1016	222	1	7000206	7000206	NUM
cana-1016	222	2	,	,	PUNCT
cana-1016	222	3	doi	doi	NOUN
cana-1016	222	4	:	:	PUNCT
cana-1016	222	5	10.1109	10.1109	NUM
cana-1016	222	6	/	/	SYM
cana-1016	222	7	jstqe.2022.3227557	jstqe.2022.3227557	PROPN
cana-1016	222	8	.	.	PUNCT
cana-1016	223	1	[	[	X
cana-1016	223	2	23	23	NUM
cana-1016	223	3	]	]	X
cana-1016	223	4	n.	n.	PROPN
cana-1016	223	5	shafi	shafi	PROPN
cana-1016	223	6	et	et	PROPN
cana-1016	223	7	al	al	PROPN
cana-1016	223	8	.	.	PROPN
cana-1016	223	9	,	,	PUNCT
cana-1016	223	10	"	"	PUNCT
cana-1016	223	11	a	a	DET
cana-1016	223	12	portable	portable	ADJ
cana-1016	223	13	non	non	ADJ
cana-1016	223	14	-	-	ADJ
cana-1016	223	15	invasive	invasive	ADJ
cana-1016	223	16	electromagnetic	electromagnetic	ADJ
cana-1016	223	17	lesion	lesion	NOUN
cana-1016	223	18	-	-	PUNCT
cana-1016	223	19	optimized	optimize	VERB
cana-1016	223	20	sensing	sense	VERB
cana-1016	223	21	device	device	NOUN
cana-1016	223	22	for	for	ADP
cana-1016	223	23	the	the	DET
cana-1016	223	24	diagnosis	diagnosis	NOUN
cana-1016	223	25	of	of	ADP
cana-1016	223	26	skin	skin	NOUN
cana-1016	223	27	cancer	cancer	NOUN
cana-1016	223	28	(	(	PUNCT
cana-1016	223	29	skanmd	skanmd	ADV
cana-1016	223	30	)	)	PUNCT
cana-1016	223	31	,	,	PUNCT
cana-1016	223	32	"	"	PUNCT
cana-1016	223	33	in	in	ADP
cana-1016	223	34	ieee	ieee	NOUN
cana-1016	223	35	transactions	transaction	NOUN
cana-1016	223	36	on	on	ADP
cana-1016	223	37	biomedical	biomedical	ADJ
cana-1016	223	38	circuits	circuit	NOUN
cana-1016	223	39	and	and	CCONJ
cana-1016	223	40	systems	system	NOUN
cana-1016	223	41	,	,	PUNCT
cana-1016	223	42	vol	vol	NOUN
cana-1016	223	43	.	.	PROPN
cana-1016	223	44	17	17	NUM
cana-1016	223	45	,	,	PUNCT
cana-1016	223	46	no	no	INTJ
cana-1016	223	47	.	.	NOUN
cana-1016	223	48	3	3	NUM
cana-1016	223	49	,	,	PUNCT
cana-1016	223	50	pp	pp	ADJ
cana-1016	223	51	.	.	PUNCT
cana-1016	224	1	558	558	NUM
cana-1016	224	2	-	-	SYM
cana-1016	224	3	573	573	NUM
cana-1016	224	4	,	,	PUNCT
cana-1016	224	5	june	june	PROPN
cana-1016	224	6	2023	2023	NUM
cana-1016	224	7	,	,	PUNCT
cana-1016	224	8	doi	doi	NOUN
cana-1016	224	9	:	:	PUNCT
cana-1016	224	10	10.1109	10.1109	NUM
cana-1016	224	11	/	/	SYM
cana-1016	224	12	tbcas.2023.3260581	tbcas.2023.3260581	PROPN
cana-1016	224	13	.	.	PUNCT
cana-1016	225	1	[	[	X
cana-1016	225	2	24	24	NUM
cana-1016	225	3	]	]	PUNCT
cana-1016	225	4	k.	k.	PROPN
cana-1016	225	5	sharma	sharma	PROPN
cana-1016	225	6	et	et	PROPN
cana-1016	225	7	al	al	PROPN
cana-1016	225	8	.	.	PROPN
cana-1016	225	9	,	,	PUNCT
cana-1016	225	10	"	"	PUNCT
cana-1016	225	11	dermatologist	dermatologist	NOUN
cana-1016	225	12	-	-	PUNCT
cana-1016	225	13	level	level	NOUN
cana-1016	225	14	classification	classification	NOUN
cana-1016	225	15	of	of	ADP
cana-1016	225	16	skin	skin	NOUN
cana-1016	225	17	cancer	cancer	NOUN
cana-1016	225	18	using	use	VERB
cana-1016	225	19	cascaded	cascade	VERB
cana-1016	225	20	ensembling	ensembling	NOUN
cana-1016	225	21	of	of	ADP
cana-1016	225	22	convolutional	convolutional	ADJ
cana-1016	225	23	neural	neural	ADJ
cana-1016	225	24	network	network	NOUN
cana-1016	225	25	and	and	CCONJ
cana-1016	225	26	handcrafted	handcrafted	ADJ
cana-1016	225	27	features	feature	NOUN
cana-1016	225	28	based	base	VERB
cana-1016	225	29	deep	deep	ADJ
cana-1016	225	30	neural	neural	ADJ
cana-1016	225	31	network	network	NOUN
cana-1016	225	32	,	,	PUNCT
cana-1016	225	33	"	"	PUNCT
cana-1016	225	34	in	in	ADP
cana-1016	225	35	ieee	ieee	NOUN
cana-1016	225	36	access	access	NOUN
cana-1016	225	37	,	,	PUNCT
cana-1016	225	38	vol	vol	NOUN
cana-1016	225	39	.	.	PROPN
cana-1016	225	40	10	10	NUM
cana-1016	225	41	,	,	PUNCT
cana-1016	225	42	pp	pp	ADJ
cana-1016	225	43	.	.	PUNCT
cana-1016	226	1	1792017932	1792017932	NUM
cana-1016	226	2	,	,	PUNCT
cana-1016	226	3	2022	2022	NUM
cana-1016	226	4	,	,	PUNCT
cana-1016	226	5	doi	doi	NOUN
cana-1016	226	6	:	:	PUNCT
cana-1016	226	7	10.1109	10.1109	NUM
cana-1016	226	8	/	/	SYM
cana-1016	226	9	access.2022.3149824	access.2022.3149824	NOUN
cana-1016	226	10	.	.	PUNCT
cana-1016	227	1	[	[	X
cana-1016	227	2	25	25	NUM
cana-1016	227	3	]	]	X
cana-1016	227	4	y.	y.	PROPN
cana-1016	227	5	tang	tang	PROPN
cana-1016	227	6	,	,	PUNCT
cana-1016	227	7	l.	l.	PROPN
cana-1016	227	8	-y	-y	PROPN
cana-1016	227	9	.	.	PUNCT
cana-1016	228	1	chen	chen	PROPN
cana-1016	228	2	,	,	PUNCT
cana-1016	228	3	a.	a.	PROPN
cana-1016	228	4	zhang	zhang	PROPN
cana-1016	228	5	,	,	PUNCT
cana-1016	228	6	c.	c.	PROPN
cana-1016	228	7	-p	-p	PROPN
cana-1016	228	8	.	.	PROPN
cana-1016	228	9	liao	liao	PROPN
cana-1016	228	10	,	,	PUNCT
cana-1016	228	11	m.	m.	PROPN
cana-1016	228	12	e.	e.	PROPN
cana-1016	228	13	gross	gross	PROPN
cana-1016	228	14	and	and	CCONJ
cana-1016	228	15	e.	e.	PROPN
cana-1016	228	16	s.	s.	PROPN
cana-1016	228	17	kim	kim	PROPN
cana-1016	228	18	,	,	PUNCT
cana-1016	228	19	"	"	PUNCT
cana-1016	228	20	in	in	ADP
cana-1016	228	21	vivo	vivo	ADJ
cana-1016	228	22	non	non	ADJ
cana-1016	228	23	-	-	ADJ
cana-1016	228	24	thermal	thermal	ADJ
cana-1016	228	25	,	,	PUNCT
cana-1016	228	26	selective	selective	ADJ
cana-1016	228	27	cancer	cancer	NOUN
cana-1016	228	28	treatment	treatment	NOUN
cana-1016	228	29	with	with	ADP
cana-1016	228	30	high	high	ADJ
cana-1016	228	31	-	-	PUNCT
cana-1016	228	32	frequency	frequency	NOUN
cana-1016	228	33	medium	medium	ADJ
cana-1016	228	34	-	-	PUNCT
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cana-1016	228	51	,	,	PUNCT
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cana-1016	228	53	,	,	PUNCT
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cana-1016	228	55	:	:	PUNCT
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cana-1016	228	58	access.2021.3108548	access.2021.3108548	NOUN
cana-1016	228	59	.	.	PUNCT
cana-1016	229	1	https://doi.org/10.1155/2022/9900668	https://doi.org/10.1155/2022/9900668	PROPN
cana-1016	229	2	https://doi.org/10.1155/2021/5895156	https://doi.org/10.1155/2021/5895156	PROPN
cana-1016	229	3	https://doi.org/10.1155/2022/5890666	https://doi.org/10.1155/2022/5890666	PROPN
cana-1016	229	4	https://doi.org/10.1155/2022/2961996	https://doi.org/10.1155/2022/2961996	PROPN
cana-1016	229	5	https://doi.org/10.1155/2022/4826892	https://doi.org/10.1155/2022/4826892	NOUN
cana-1016	229	6	https://doi.org/10.1155/2022/4942637	https://doi.org/10.1155/2022/4942637	PROPN
cana-1016	229	7	https://doi.org/10.1155/2022/6952304	https://doi.org/10.1155/2022/6952304	PROPN