id	sid	tid	token	lemma	pos
cana-2493	1	1	communications	communication	NOUN
cana-2493	1	2	on	on	ADP
cana-2493	1	3	applied	apply	VERB
cana-2493	1	4	nonlinear	nonlinear	ADJ
cana-2493	1	5	analysis	analysis	NOUN
cana-2493	1	6	issn	issn	NOUN
cana-2493	1	7	:	:	PUNCT
cana-2493	1	8	1074	1074	NUM
cana-2493	1	9	-	-	PUNCT
cana-2493	1	10	133x	133x	NUM
cana-2493	1	11	vol	vol	NOUN
cana-2493	1	12	32	32	NUM
cana-2493	1	13	no	no	NOUN
cana-2493	1	14	.	.	PUNCT
cana-2493	2	1	2s	2s	NUM
cana-2493	2	2	(	(	PUNCT
cana-2493	2	3	2025	2025	NUM
cana-2493	2	4	)	)	PUNCT
cana-2493	2	5	545	545	NUM
cana-2493	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	2	7	implementing	implement	VERB
cana-2493	2	8	deep	deep	ADJ
cana-2493	2	9	learning	learning	NOUN
cana-2493	2	10	models	model	NOUN
cana-2493	2	11	for	for	ADP
cana-2493	2	12	early	early	ADJ
cana-2493	2	13	detection	detection	NOUN
cana-2493	2	14	and	and	CCONJ
cana-2493	2	15	segmentation	segmentation	NOUN
cana-2493	2	16	of	of	ADP
cana-2493	2	17	lung	lung	NOUN
cana-2493	2	18	cancer	cancer	NOUN
cana-2493	2	19	from	from	ADP
cana-2493	2	20	medical	medical	ADJ
cana-2493	2	21	imaging	imaging	PROPN
cana-2493	2	22	rajeev	rajeev	PROPN
cana-2493	2	23	dixit1	dixit1	PROPN
cana-2493	2	24	,	,	PUNCT
cana-2493	2	25	dr	dr	PROPN
cana-2493	2	26	.	.	PROPN
cana-2493	2	27	pankaj	pankaj	PROPN
cana-2493	2	28	kumar2	kumar2	PROPN
cana-2493	2	29	,	,	PUNCT
cana-2493	2	30	dr	dr	PROPN
cana-2493	2	31	.	.	PROPN
cana-2493	2	32	shashank	shashank	PROPN
cana-2493	2	33	ojha3	ojha3	PROPN
cana-2493	3	1	1department	1department	NUM
cana-2493	3	2	of	of	ADP
cana-2493	3	3	computer	computer	NOUN
cana-2493	3	4	science	science	PROPN
cana-2493	3	5	&	&	CCONJ
cana-2493	3	6	engineering	engineering	PROPN
cana-2493	3	7	,	,	PUNCT
cana-2493	3	8	united	united	PROPN
cana-2493	3	9	college	college	PROPN
cana-2493	3	10	of	of	ADP
cana-2493	3	11	engineering	engineering	PROPN
cana-2493	3	12	&	&	CCONJ
cana-2493	3	13	research	research	PROPN
cana-2493	3	14	,	,	PUNCT
cana-2493	3	15	prayagraj	prayagraj	PROPN
cana-2493	3	16	,	,	PUNCT
cana-2493	3	17	dr	dr	PROPN
cana-2493	3	18	.	.	PROPN
cana-2493	3	19	a.p.j	a.p.j	PROPN
cana-2493	3	20	.	.	PUNCT
cana-2493	4	1	abdul	abdul	PROPN
cana-2493	4	2	kalam	kalam	PROPN
cana-2493	4	3	technical	technical	PROPN
cana-2493	4	4	university	university	PROPN
cana-2493	4	5	,	,	PUNCT
cana-2493	4	6	lucknow	lucknow	PROPN
cana-2493	4	7	,	,	PUNCT
cana-2493	4	8	india	india	PROPN
cana-2493	4	9	.	.	PUNCT
cana-2493	5	1	dixitraj73@gmail.com	dixitraj73@gmail.com	PROPN
cana-2493	5	2	2department	2department	NUM
cana-2493	5	3	of	of	ADP
cana-2493	5	4	computer	computer	NOUN
cana-2493	5	5	science	science	PROPN
cana-2493	5	6	&	&	CCONJ
cana-2493	5	7	engineering	engineering	PROPN
cana-2493	5	8	,	,	PUNCT
cana-2493	5	9	sri	sri	PROPN
cana-2493	5	10	ramswaroop	ramswaroop	PROPN
cana-2493	5	11	memorial	memorial	ADJ
cana-2493	5	12	group	group	NOUN
cana-2493	5	13	of	of	ADP
cana-2493	5	14	professional	professional	ADJ
cana-2493	5	15	colleges	college	NOUN
cana-2493	5	16	lucknow	lucknow	PROPN
cana-2493	5	17	,	,	PUNCT
cana-2493	5	18	dr	dr	PROPN
cana-2493	5	19	.	.	PROPN
cana-2493	5	20	a.p.j	a.p.j	PROPN
cana-2493	5	21	.	.	PUNCT
cana-2493	6	1	abdul	abdul	PROPN
cana-2493	6	2	kalam	kalam	PROPN
cana-2493	6	3	technical	technical	PROPN
cana-2493	6	4	university	university	PROPN
cana-2493	6	5	,	,	PUNCT
cana-2493	6	6	uttar	uttar	PROPN
cana-2493	6	7	pradesh	pradesh	PROPN
cana-2493	6	8	,	,	PUNCT
cana-2493	6	9	lucknow	lucknow	PROPN
cana-2493	6	10	,	,	PUNCT
cana-2493	6	11	india	india	PROPN
cana-2493	6	12	.	.	PUNCT
cana-2493	6	13	pk79jan@gmail.com	pk79jan@gmail.com	PROPN
cana-2493	7	1	3chest	3chest	NUM
cana-2493	7	2	department	department	NOUN
cana-2493	7	3	,	,	PUNCT
cana-2493	7	4	guru	guru	NOUN
cana-2493	7	5	shri	shri	NOUN
cana-2493	7	6	gorakshnath	gorakshnath	ADP
cana-2493	7	7	chikitsalaya	chikitsalaya	PROPN
cana-2493	7	8	,	,	PUNCT
cana-2493	7	9	gorakhpur	gorakhpur	PROPN
cana-2493	7	10	,	,	PUNCT
cana-2493	7	11	india	india	PROPN
cana-2493	7	12	corresponding	corresponding	PROPN
cana-2493	7	13	author	author	NOUN
cana-2493	7	14	mail	mail	NOUN
cana-2493	7	15	:	:	PUNCT
cana-2493	8	1	dixitraj73@gmail.com	dixitraj73@gmail.com	PROPN
cana-2493	8	2	article	article	NOUN
cana-2493	8	3	history	history	NOUN
cana-2493	8	4	:	:	PUNCT
cana-2493	8	5	received	receive	VERB
cana-2493	8	6	:	:	PUNCT
cana-2493	8	7	26	26	NUM
cana-2493	8	8	-	-	SYM
cana-2493	8	9	09	09	NUM
cana-2493	8	10	-	-	PUNCT
cana-2493	8	11	2024	2024	NUM
cana-2493	8	12	revised	revise	VERB
cana-2493	8	13	:	:	PUNCT
cana-2493	8	14	01	01	NUM
cana-2493	8	15	-	-	SYM
cana-2493	8	16	11	11	NUM
cana-2493	8	17	-	-	PUNCT
cana-2493	8	18	2024	2024	NUM
cana-2493	8	19	accepted	accept	VERB
cana-2493	8	20	:	:	PUNCT
cana-2493	8	21	13	13	NUM
cana-2493	8	22	-	-	SYM
cana-2493	8	23	11	11	NUM
cana-2493	8	24	-	-	PUNCT
cana-2493	8	25	2024	2024	NUM
cana-2493	8	26	abstract	abstract	NOUN
cana-2493	8	27	:	:	PUNCT
cana-2493	8	28	once	once	ADV
cana-2493	8	29	surprisingly	surprisingly	ADV
cana-2493	8	30	,	,	PUNCT
cana-2493	8	31	lung	lung	NOUN
cana-2493	8	32	cancer	cancer	NOUN
cana-2493	8	33	still	still	ADV
cana-2493	8	34	ranks	rank	VERB
cana-2493	8	35	among	among	ADP
cana-2493	8	36	the	the	DET
cana-2493	8	37	top	top	ADJ
cana-2493	8	38	causes	cause	NOUN
cana-2493	8	39	of	of	ADP
cana-2493	8	40	cancer	cancer	NOUN
cana-2493	8	41	deaths	death	NOUN
cana-2493	8	42	globally	globally	ADV
cana-2493	8	43	,	,	PUNCT
cana-2493	8	44	early	early	ADJ
cana-2493	8	45	stage	stage	NOUN
cana-2493	8	46	diagnosis	diagnosis	NOUN
cana-2493	8	47	is	be	AUX
cana-2493	8	48	the	the	DET
cana-2493	8	49	key	key	NOUN
cana-2493	8	50	to	to	ADP
cana-2493	8	51	increasing	increase	VERB
cana-2493	8	52	the	the	DET
cana-2493	8	53	survival	survival	NOUN
cana-2493	8	54	benefits	benefit	NOUN
cana-2493	8	55	of	of	ADP
cana-2493	8	56	the	the	DET
cana-2493	8	57	patient	patient	NOUN
cana-2493	8	58	.	.	PUNCT
cana-2493	9	1	lung	lung	NOUN
cana-2493	9	2	cancer	cancer	NOUN
cana-2493	9	3	diagnosis	diagnosis	NOUN
cana-2493	9	4	using	use	VERB
cana-2493	9	5	classical	classical	ADJ
cana-2493	9	6	methods	method	NOUN
cana-2493	9	7	like	like	ADP
cana-2493	9	8	manual	manual	ADJ
cana-2493	9	9	image	image	NOUN
cana-2493	9	10	analysis	analysis	NOUN
cana-2493	9	11	and	and	CCONJ
cana-2493	9	12	histogram	histogram	NOUN
cana-2493	9	13	analysis	analysis	NOUN
cana-2493	9	14	is	be	AUX
cana-2493	9	15	time	time	NOUN
cana-2493	9	16	consuming	consume	VERB
cana-2493	9	17	and	and	CCONJ
cana-2493	9	18	has	have	VERB
cana-2493	9	19	high	high	ADJ
cana-2493	9	20	possibilities	possibility	NOUN
cana-2493	9	21	of	of	ADP
cana-2493	9	22	human	human	ADJ
cana-2493	9	23	errors	error	NOUN
cana-2493	9	24	.	.	PUNCT
cana-2493	10	1	lung	lung	NOUN
cana-2493	10	2	cancer	cancer	NOUN
cana-2493	10	3	detection	detection	NOUN
cana-2493	10	4	and	and	CCONJ
cana-2493	10	5	segmentation	segmentation	NOUN
cana-2493	10	6	with	with	ADP
cana-2493	10	7	deep	deep	ADJ
cana-2493	10	8	learning	learning	NOUN
cana-2493	10	9	are	be	AUX
cana-2493	10	10	promising	promise	VERB
cana-2493	10	11	,	,	PUNCT
cana-2493	10	12	but	but	CCONJ
cana-2493	10	13	they	they	PRON
cana-2493	10	14	still	still	ADV
cana-2493	10	15	encountered	encounter	VERB
cana-2493	10	16	challenges	challenge	NOUN
cana-2493	10	17	of	of	ADP
cana-2493	10	18	high	high	ADJ
cana-2493	10	19	accuracy	accuracy	NOUN
cana-2493	10	20	in	in	ADP
cana-2493	10	21	noisy	noisy	ADJ
cana-2493	10	22	or	or	CCONJ
cana-2493	10	23	low	low	ADJ
cana-2493	10	24	-	-	PUNCT
cana-2493	10	25	quality	quality	NOUN
cana-2493	10	26	medical	medical	ADJ
cana-2493	10	27	images	image	NOUN
cana-2493	10	28	.	.	PUNCT
cana-2493	11	1	this	this	DET
cana-2493	11	2	study	study	NOUN
cana-2493	11	3	proposes	propose	VERB
cana-2493	11	4	an	an	DET
cana-2493	11	5	advanced	advanced	ADJ
cana-2493	11	6	deep	deep	ADJ
cana-2493	11	7	learning	learning	NOUN
cana-2493	11	8	framework	framework	NOUN
cana-2493	11	9	articulated	articulate	VERB
cana-2493	11	10	by	by	ADP
cana-2493	11	11	cnns	cnn	NOUN
cana-2493	11	12	with	with	ADP
cana-2493	11	13	the	the	DET
cana-2493	11	14	integration	integration	NOUN
cana-2493	11	15	of	of	ADP
cana-2493	11	16	data	datum	NOUN
cana-2493	11	17	augmentation	augmentation	NOUN
cana-2493	11	18	methods	method	NOUN
cana-2493	11	19	and	and	CCONJ
cana-2493	11	20	multiple	multiple	ADJ
cana-2493	11	21	scale	scale	NOUN
cana-2493	11	22	segmentation	segmentation	NOUN
cana-2493	11	23	for	for	ADP
cana-2493	11	24	the	the	DET
cana-2493	11	25	automated	automate	VERB
cana-2493	11	26	detection	detection	NOUN
cana-2493	11	27	and	and	CCONJ
cana-2493	11	28	segmentation	segmentation	NOUN
cana-2493	11	29	of	of	ADP
cana-2493	11	30	lung	lung	NOUN
cana-2493	11	31	cancer	cancer	NOUN
cana-2493	11	32	,	,	PUNCT
cana-2493	11	33	on	on	ADP
cana-2493	11	34	a	a	DET
cana-2493	11	35	dataset	dataset	NOUN
cana-2493	11	36	of	of	ADP
cana-2493	11	37	ct	ct	PROPN
cana-2493	11	38	scans	scan	NOUN
cana-2493	11	39	.	.	PUNCT
cana-2493	12	1	more	more	ADV
cana-2493	12	2	importantly	importantly	ADV
cana-2493	12	3	,	,	PUNCT
cana-2493	12	4	when	when	SCONJ
cana-2493	12	5	compared	compare	VERB
cana-2493	12	6	with	with	ADP
cana-2493	12	7	existing	exist	VERB
cana-2493	12	8	techniques	technique	NOUN
cana-2493	12	9	,	,	PUNCT
cana-2493	12	10	it	it	PRON
cana-2493	12	11	has	have	VERB
cana-2493	12	12	a	a	DET
cana-2493	12	13	much	much	ADV
cana-2493	12	14	higher	high	ADJ
cana-2493	12	15	accuracy	accuracy	NOUN
cana-2493	12	16	in	in	ADP
cana-2493	12	17	detecting	detect	VERB
cana-2493	12	18	the	the	DET
cana-2493	12	19	tumour	tumour	NOUN
cana-2493	12	20	areas	area	NOUN
cana-2493	12	21	,	,	PUNCT
cana-2493	12	22	even	even	ADV
cana-2493	12	23	under	under	ADP
cana-2493	12	24	situations	situation	NOUN
cana-2493	12	25	of	of	ADP
cana-2493	12	26	varying	vary	VERB
cana-2493	12	27	quality	quality	NOUN
cana-2493	12	28	of	of	ADP
cana-2493	12	29	the	the	DET
cana-2493	12	30	images	image	NOUN
cana-2493	12	31	.	.	PUNCT
cana-2493	13	1	experimental	experimental	ADJ
cana-2493	13	2	data	datum	NOUN
cana-2493	13	3	shows	show	VERB
cana-2493	13	4	enhanced	enhance	VERB
cana-2493	13	5	sensitivity	sensitivity	NOUN
cana-2493	13	6	and	and	CCONJ
cana-2493	13	7	specificity	specificity	NOUN
cana-2493	13	8	over	over	ADP
cana-2493	13	9	conventional	conventional	ADJ
cana-2493	13	10	strategies	strategy	NOUN
cana-2493	13	11	.	.	PUNCT
cana-2493	14	1	this	this	DET
cana-2493	14	2	proposed	propose	VERB
cana-2493	14	3	model	model	NOUN
cana-2493	14	4	not	not	PART
cana-2493	14	5	only	only	ADV
cana-2493	14	6	shortens	shorten	VERB
cana-2493	14	7	the	the	DET
cana-2493	14	8	diagnostic	diagnostic	ADJ
cana-2493	14	9	time	time	NOUN
cana-2493	14	10	but	but	CCONJ
cana-2493	14	11	it	it	PRON
cana-2493	14	12	also	also	ADV
cana-2493	14	13	provides	provide	VERB
cana-2493	14	14	uniform	uniform	ADJ
cana-2493	14	15	,	,	PUNCT
cana-2493	14	16	trustful	trustful	ADJ
cana-2493	14	17	results	result	NOUN
cana-2493	14	18	which	which	PRON
cana-2493	14	19	reduce	reduce	VERB
cana-2493	14	20	the	the	DET
cana-2493	14	21	misdiagnosis	misdiagnosis	NOUN
cana-2493	14	22	occurrence	occurrence	NOUN
cana-2493	14	23	.	.	PUNCT
cana-2493	15	1	we	we	PRON
cana-2493	15	2	are	be	AUX
cana-2493	15	3	making	make	VERB
cana-2493	15	4	strides	stride	NOUN
cana-2493	15	5	that	that	PRON
cana-2493	15	6	further	far	ADV
cana-2493	15	7	advance	advance	NOUN
cana-2493	15	8	ai	ai	VERB
cana-2493	15	9	tools	tool	NOUN
cana-2493	15	10	to	to	PART
cana-2493	15	11	enhance	enhance	VERB
cana-2493	15	12	clinical	clinical	ADJ
cana-2493	15	13	practice	practice	NOUN
cana-2493	15	14	and	and	CCONJ
cana-2493	15	15	we	we	PRON
cana-2493	15	16	hope	hope	VERB
cana-2493	15	17	may	may	AUX
cana-2493	15	18	improve	improve	VERB
cana-2493	15	19	the	the	DET
cana-2493	15	20	early	early	ADJ
cana-2493	15	21	detection	detection	NOUN
cana-2493	15	22	of	of	ADP
cana-2493	15	23	lung	lung	NOUN
cana-2493	15	24	cancer	cancer	NOUN
cana-2493	15	25	and	and	CCONJ
cana-2493	15	26	save	save	VERB
cana-2493	15	27	lives	life	NOUN
cana-2493	15	28	.	.	PUNCT
cana-2493	16	1	keywords	keyword	NOUN
cana-2493	16	2	:	:	PUNCT
cana-2493	16	3	cancer	cancer	NOUN
cana-2493	16	4	,	,	PUNCT
cana-2493	16	5	diagnosis	diagnosis	NOUN
cana-2493	16	6	,	,	PUNCT
cana-2493	16	7	lung	lung	NOUN
cana-2493	16	8	,	,	PUNCT
cana-2493	16	9	clinical	clinical	ADJ
cana-2493	16	10	,	,	PUNCT
cana-2493	16	11	occurrence	occurrence	NOUN
cana-2493	16	12	,	,	PUNCT
cana-2493	16	13	detection	detection	NOUN
cana-2493	16	14	,	,	PUNCT
cana-2493	16	15	segmentation	segmentation	NOUN
cana-2493	16	16	,	,	PUNCT
cana-2493	16	17	imaging	imaging	NOUN
cana-2493	16	18	.	.	PUNCT
cana-2493	17	1	introduction	introduction	NOUN
cana-2493	17	2	lung	lung	NOUN
cana-2493	17	3	cancer	cancer	NOUN
cana-2493	17	4	,	,	PUNCT
cana-2493	17	5	a	a	DET
cana-2493	17	6	leading	lead	VERB
cana-2493	17	7	cause	cause	NOUN
cana-2493	17	8	of	of	ADP
cana-2493	17	9	cancer	cancer	NOUN
cana-2493	17	10	-	-	PUNCT
cana-2493	17	11	related	relate	VERB
cana-2493	17	12	mortalities	mortality	NOUN
cana-2493	17	13	around	around	ADP
cana-2493	17	14	the	the	DET
cana-2493	17	15	world	world	NOUN
cana-2493	17	16	,	,	PUNCT
cana-2493	17	17	presents	present	VERB
cana-2493	17	18	significant	significant	ADJ
cana-2493	17	19	difficulties	difficulty	NOUN
cana-2493	17	20	for	for	ADP
cana-2493	17	21	early	early	ADJ
cana-2493	17	22	diagnosis	diagnosis	NOUN
cana-2493	17	23	,	,	PUNCT
cana-2493	17	24	treatment	treatment	NOUN
cana-2493	17	25	,	,	PUNCT
cana-2493	17	26	and	and	CCONJ
cana-2493	17	27	survival	survival	NOUN
cana-2493	17	28	rates	rate	NOUN
cana-2493	17	29	.	.	PUNCT
cana-2493	18	1	according	accord	VERB
cana-2493	18	2	to	to	ADP
cana-2493	18	3	the	the	DET
cana-2493	18	4	world	world	PROPN
cana-2493	18	5	health	health	PROPN
cana-2493	18	6	organization	organization	NOUN
cana-2493	18	7	,	,	PUNCT
cana-2493	18	8	lung	lung	NOUN
cana-2493	18	9	cancer	cancer	NOUN
cana-2493	18	10	accounts	account	VERB
cana-2493	18	11	for	for	ADP
cana-2493	18	12	approximately	approximately	ADV
cana-2493	18	13	25	25	NUM
cana-2493	18	14	%	%	NOUN
cana-2493	18	15	of	of	ADP
cana-2493	18	16	all	all	DET
cana-2493	18	17	cancer	cancer	NOUN
cana-2493	18	18	-	-	PUNCT
cana-2493	18	19	related	relate	VERB
cana-2493	18	20	deaths	death	NOUN
cana-2493	18	21	globally	globally	ADV
cana-2493	18	22	with	with	ADP
cana-2493	18	23	an	an	DET
cana-2493	18	24	estimated	estimate	VERB
cana-2493	18	25	1.8	1.8	NUM
cana-2493	18	26	million	million	NUM
cana-2493	18	27	deaths	death	NOUN
cana-2493	18	28	annually	annually	ADV
cana-2493	18	29	.	.	PUNCT
cana-2493	19	1	the	the	DET
cana-2493	19	2	probability	probability	NOUN
cana-2493	19	3	of	of	ADP
cana-2493	19	4	patients	patient	NOUN
cana-2493	19	5	diagnosed	diagnose	VERB
cana-2493	19	6	with	with	ADP
cana-2493	19	7	lung	lung	NOUN
cana-2493	19	8	cancer	cancer	NOUN
cana-2493	19	9	surviving	surviving	NOUN
cana-2493	19	10	is	be	AUX
cana-2493	19	11	heavily	heavily	ADV
cana-2493	19	12	dependent	dependent	ADJ
cana-2493	19	13	on	on	ADP
cana-2493	19	14	when	when	SCONJ
cana-2493	19	15	the	the	DET
cana-2493	19	16	disease	disease	NOUN
cana-2493	19	17	is	be	AUX
cana-2493	19	18	detected	detect	VERB
cana-2493	19	19	,	,	PUNCT
cana-2493	19	20	with	with	ADP
cana-2493	19	21	survival	survival	NOUN
cana-2493	19	22	rates	rate	NOUN
cana-2493	19	23	drastically	drastically	ADV
cana-2493	19	24	improving	improve	VERB
cana-2493	19	25	if	if	SCONJ
cana-2493	19	26	identified	identify	VERB
cana-2493	19	27	at	at	ADP
cana-2493	19	28	its	its	PRON
cana-2493	19	29	initial	initial	ADJ
cana-2493	19	30	stages[5	stages[5	NOUN
cana-2493	19	31	]	]	PUNCT
cana-2493	19	32	.	.	PUNCT
cana-2493	20	1	regrettably	regrettably	ADV
cana-2493	20	2	,	,	PUNCT
cana-2493	20	3	most	most	ADJ
cana-2493	20	4	lung	lung	NOUN
cana-2493	20	5	cancer	cancer	NOUN
cana-2493	20	6	cases	case	NOUN
cana-2493	20	7	are	be	AUX
cana-2493	20	8	diagnosed	diagnose	VERB
cana-2493	20	9	at	at	ADP
cana-2493	20	10	an	an	DET
cana-2493	20	11	advanced	advanced	ADJ
cana-2493	20	12	stage	stage	NOUN
cana-2493	20	13	due	due	ADP
cana-2493	20	14	to	to	ADP
cana-2493	20	15	the	the	DET
cana-2493	20	16	subtle	subtle	ADJ
cana-2493	20	17	nature	nature	NOUN
cana-2493	20	18	of	of	ADP
cana-2493	20	19	early	early	ADJ
cana-2493	20	20	symptoms	symptom	NOUN
cana-2493	20	21	and	and	CCONJ
cana-2493	20	22	constraints	constraint	NOUN
cana-2493	20	23	of	of	ADP
cana-2493	20	24	traditional	traditional	ADJ
cana-2493	20	25	diagnostic	diagnostic	ADJ
cana-2493	20	26	methods	method	NOUN
cana-2493	20	27	.	.	PUNCT
cana-2493	21	1	consequently	consequently	ADV
cana-2493	21	2	,	,	PUNCT
cana-2493	21	3	there	there	PRON
cana-2493	21	4	is	be	VERB
cana-2493	21	5	a	a	DET
cana-2493	21	6	growing	grow	VERB
cana-2493	21	7	necessity	necessity	NOUN
cana-2493	21	8	for	for	ADP
cana-2493	21	9	more	more	ADV
cana-2493	21	10	efficient	efficient	ADJ
cana-2493	21	11	,	,	PUNCT
cana-2493	21	12	accurate	accurate	ADJ
cana-2493	21	13	,	,	PUNCT
cana-2493	21	14	and	and	CCONJ
cana-2493	21	15	automated	automate	VERB
cana-2493	21	16	techniques	technique	NOUN
cana-2493	21	17	for	for	ADP
cana-2493	21	18	lung	lung	NOUN
cana-2493	21	19	cancer	cancer	NOUN
cana-2493	21	20	detection	detection	NOUN
cana-2493	21	21	particularly	particularly	ADV
cana-2493	21	22	in	in	ADP
cana-2493	21	23	the	the	DET
cana-2493	21	24	early	early	ADJ
cana-2493	21	25	phases	phase	NOUN
cana-2493	21	26	of	of	ADP
cana-2493	21	27	the	the	DET
cana-2493	21	28	disease	disease	NOUN
cana-2493	21	29	.	.	PUNCT
cana-2493	22	1	mailto:dixitraj73@gmail.com	mailto:dixitraj73@gmail.com	X
cana-2493	22	2	mailto:pk79jan@gmail.com	mailto:pk79jan@gmail.com	X
cana-2493	22	3	mailto:dixitraj73@gmail.com	mailto:dixitraj73@gmail.com	X
cana-2493	22	4	communications	communication	NOUN
cana-2493	22	5	on	on	ADP
cana-2493	22	6	applied	apply	VERB
cana-2493	22	7	nonlinear	nonlinear	ADJ
cana-2493	22	8	analysis	analysis	NOUN
cana-2493	22	9	issn	issn	NOUN
cana-2493	22	10	:	:	PUNCT
cana-2493	22	11	1074	1074	NUM
cana-2493	22	12	-	-	PUNCT
cana-2493	22	13	133x	133x	NUM
cana-2493	22	14	vol	vol	NOUN
cana-2493	22	15	32	32	NUM
cana-2493	22	16	no	no	NOUN
cana-2493	22	17	.	.	PUNCT
cana-2493	23	1	2s	2s	NUM
cana-2493	23	2	(	(	PUNCT
cana-2493	23	3	2025	2025	NUM
cana-2493	23	4	)	)	PUNCT
cana-2493	23	5	546	546	NUM
cana-2493	23	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	23	7	historically	historically	ADV
cana-2493	23	8	,	,	PUNCT
cana-2493	23	9	lung	lung	NOUN
cana-2493	23	10	cancer	cancer	NOUN
cana-2493	23	11	detection	detection	NOUN
cana-2493	23	12	has	have	AUX
cana-2493	23	13	relied	rely	VERB
cana-2493	23	14	on	on	ADP
cana-2493	23	15	imaging	imaging	NOUN
cana-2493	23	16	approaches	approach	NOUN
cana-2493	23	17	including	include	VERB
cana-2493	23	18	chest	chest	NOUN
cana-2493	23	19	x	x	NOUN
cana-2493	23	20	-	-	NOUN
cana-2493	23	21	rays	ray	NOUN
cana-2493	23	22	,	,	PUNCT
cana-2493	23	23	computed	compute	VERB
cana-2493	23	24	tomography	tomography	NOUN
cana-2493	23	25	scans	scan	NOUN
cana-2493	23	26	,	,	PUNCT
cana-2493	23	27	and	and	CCONJ
cana-2493	23	28	positron	positron	NOUN
cana-2493	23	29	emission	emission	NOUN
cana-2493	23	30	tomography	tomography	NOUN
cana-2493	23	31	scans	scan	NOUN
cana-2493	23	32	.	.	PUNCT
cana-2493	24	1	these	these	DET
cana-2493	24	2	imaging	imaging	NOUN
cana-2493	24	3	modalities	modality	NOUN
cana-2493	24	4	enable	enable	VERB
cana-2493	24	5	healthcare	healthcare	NOUN
cana-2493	24	6	professionals	professional	NOUN
cana-2493	24	7	to	to	PART
cana-2493	24	8	observe	observe	VERB
cana-2493	24	9	lung	lung	NOUN
cana-2493	24	10	abnormalities	abnormality	NOUN
cana-2493	24	11	,	,	PUNCT
cana-2493	24	12	involving	involve	VERB
cana-2493	24	13	tumors	tumor	NOUN
cana-2493	24	14	,	,	PUNCT
cana-2493	24	15	lesions	lesion	NOUN
cana-2493	24	16	,	,	PUNCT
cana-2493	24	17	and	and	CCONJ
cana-2493	24	18	nodules	nodule	NOUN
cana-2493	24	19	.	.	PUNCT
cana-2493	25	1	however	however	ADV
cana-2493	25	2	,	,	PUNCT
cana-2493	25	3	the	the	DET
cana-2493	25	4	precision	precision	NOUN
cana-2493	25	5	of	of	ADP
cana-2493	25	6	these	these	DET
cana-2493	25	7	techniques	technique	NOUN
cana-2493	25	8	is	be	AUX
cana-2493	25	9	heavily	heavily	ADV
cana-2493	25	10	reliant	reliant	ADJ
cana-2493	25	11	on	on	ADP
cana-2493	25	12	the	the	DET
cana-2493	25	13	skill	skill	NOUN
cana-2493	25	14	and	and	CCONJ
cana-2493	25	15	experience	experience	NOUN
cana-2493	25	16	of	of	ADP
cana-2493	25	17	radiologists	radiologist	NOUN
cana-2493	25	18	and	and	CCONJ
cana-2493	25	19	clinicians	clinician	NOUN
cana-2493	25	20	who	who	PRON
cana-2493	25	21	interpret	interpret	VERB
cana-2493	25	22	the	the	DET
cana-2493	25	23	images	image	NOUN
cana-2493	25	24	.	.	PUNCT
cana-2493	26	1	manual	manual	ADJ
cana-2493	26	2	interpretation	interpretation	NOUN
cana-2493	26	3	is	be	AUX
cana-2493	26	4	a	a	DET
cana-2493	26	5	time	time	NOUN
cana-2493	26	6	-	-	PUNCT
cana-2493	26	7	consuming	consume	VERB
cana-2493	26	8	process	process	NOUN
cana-2493	26	9	,	,	PUNCT
cana-2493	26	10	and	and	CCONJ
cana-2493	26	11	the	the	DET
cana-2493	26	12	risk	risk	NOUN
cana-2493	26	13	of	of	ADP
cana-2493	26	14	human	human	ADJ
cana-2493	26	15	error	error	NOUN
cana-2493	26	16	can	can	AUX
cana-2493	26	17	lead	lead	VERB
cana-2493	26	18	to	to	ADP
cana-2493	26	19	misdiagnosis	misdiagnosis	NOUN
cana-2493	26	20	—	—	PUNCT
cana-2493	26	21	particularly	particularly	ADV
cana-2493	26	22	in	in	ADP
cana-2493	26	23	instances	instance	NOUN
cana-2493	26	24	of	of	ADP
cana-2493	26	25	subtle	subtle	ADJ
cana-2493	26	26	or	or	CCONJ
cana-2493	26	27	overlapping	overlap	VERB
cana-2493	26	28	abnormalities	abnormality	NOUN
cana-2493	26	29	.	.	PUNCT
cana-2493	27	1	furthermore	furthermore	ADV
cana-2493	27	2	,	,	PUNCT
cana-2493	27	3	the	the	DET
cana-2493	27	4	sheer	sheer	ADJ
cana-2493	27	5	quantity	quantity	NOUN
cana-2493	27	6	of	of	ADP
cana-2493	27	7	medical	medical	ADJ
cana-2493	27	8	imaging	imaging	NOUN
cana-2493	27	9	data	datum	NOUN
cana-2493	27	10	in	in	ADP
cana-2493	27	11	clinical	clinical	ADJ
cana-2493	27	12	practice	practice	NOUN
cana-2493	27	13	has	have	AUX
cana-2493	27	14	made	make	VERB
cana-2493	27	15	it	it	PRON
cana-2493	27	16	increasingly	increasingly	ADV
cana-2493	27	17	difficult	difficult	ADJ
cana-2493	27	18	for	for	SCONJ
cana-2493	27	19	healthcare	healthcare	NOUN
cana-2493	27	20	professionals	professional	NOUN
cana-2493	27	21	to	to	PART
cana-2493	27	22	keep	keep	VERB
cana-2493	27	23	pace	pace	NOUN
cana-2493	27	24	with	with	ADP
cana-2493	27	25	the	the	DET
cana-2493	27	26	ever	ever	ADV
cana-2493	27	27	-	-	PUNCT
cana-2493	27	28	growing	grow	VERB
cana-2493	27	29	number	number	NOUN
cana-2493	27	30	of	of	ADP
cana-2493	27	31	cases	case	NOUN
cana-2493	27	32	.	.	PUNCT
cana-2493	28	1	over	over	ADP
cana-2493	28	2	the	the	DET
cana-2493	28	3	past	past	ADJ
cana-2493	28	4	decade	decade	NOUN
cana-2493	28	5	,	,	PUNCT
cana-2493	28	6	noteworthy	noteworthy	ADJ
cana-2493	28	7	advances	advance	NOUN
cana-2493	28	8	have	have	AUX
cana-2493	28	9	been	be	AUX
cana-2493	28	10	made	make	VERB
cana-2493	28	11	applying	apply	VERB
cana-2493	28	12	deep	deep	ADJ
cana-2493	28	13	learning	learning	NOUN
cana-2493	28	14	approaches	approach	NOUN
cana-2493	28	15	to	to	ADP
cana-2493	28	16	medical	medical	ADJ
cana-2493	28	17	imaging	imaging	NOUN
cana-2493	28	18	,	,	PUNCT
cana-2493	28	19	offering	offer	VERB
cana-2493	28	20	promising	promise	VERB
cana-2493	28	21	remedies	remedy	NOUN
cana-2493	28	22	to	to	ADP
cana-2493	28	23	these	these	DET
cana-2493	28	24	issues	issue	NOUN
cana-2493	28	25	.	.	PUNCT
cana-2493	29	1	deep	deep	ADJ
cana-2493	29	2	learning	learning	NOUN
cana-2493	29	3	,	,	PUNCT
cana-2493	29	4	notably	notably	ADV
cana-2493	29	5	convolutional	convolutional	ADJ
cana-2493	29	6	neural	neural	ADJ
cana-2493	29	7	systems	system	NOUN
cana-2493	29	8	(	(	PUNCT
cana-2493	29	9	cnns	cnns	PROPN
cana-2493	29	10	)	)	PUNCT
cana-2493	29	11	,	,	PUNCT
cana-2493	29	12	has	have	AUX
cana-2493	29	13	revolutionized	revolutionize	VERB
cana-2493	29	14	the	the	DET
cana-2493	29	15	field	field	NOUN
cana-2493	29	16	of	of	ADP
cana-2493	29	17	medical	medical	ADJ
cana-2493	29	18	image	image	NOUN
cana-2493	29	19	examination	examination	NOUN
cana-2493	29	20	owing	owe	VERB
cana-2493	29	21	to	to	ADP
cana-2493	29	22	its	its	PRON
cana-2493	29	23	ability	ability	NOUN
cana-2493	29	24	to	to	PART
cana-2493	29	25	automatically	automatically	ADV
cana-2493	29	26	learn	learn	VERB
cana-2493	29	27	features	feature	NOUN
cana-2493	29	28	from	from	ADP
cana-2493	29	29	raw	raw	ADJ
cana-2493	29	30	image	image	NOUN
cana-2493	29	31	data	datum	NOUN
cana-2493	29	32	without	without	ADP
cana-2493	29	33	the	the	DET
cana-2493	29	34	necessity	necessity	NOUN
cana-2493	29	35	for	for	ADP
cana-2493	29	36	manual	manual	ADJ
cana-2493	29	37	feature	feature	NOUN
cana-2493	29	38	extraction	extraction	NOUN
cana-2493	29	39	.	.	PUNCT
cana-2493	30	1	cnns	cnns	PROPN
cana-2493	30	2	have	have	AUX
cana-2493	30	3	shown	show	VERB
cana-2493	30	4	striking	striking	ADJ
cana-2493	30	5	success	success	NOUN
cana-2493	30	6	in	in	ADP
cana-2493	30	7	a	a	DET
cana-2493	30	8	wide	wide	ADJ
cana-2493	30	9	range	range	NOUN
cana-2493	30	10	of	of	ADP
cana-2493	30	11	applications	application	NOUN
cana-2493	30	12	,	,	PUNCT
cana-2493	30	13	for	for	ADP
cana-2493	30	14	example	example	NOUN
cana-2493	30	15	image	image	NOUN
cana-2493	30	16	categorization	categorization	NOUN
cana-2493	30	17	,	,	PUNCT
cana-2493	30	18	object	object	NOUN
cana-2493	30	19	detection	detection	NOUN
cana-2493	30	20	,	,	PUNCT
cana-2493	30	21	and	and	CCONJ
cana-2493	30	22	segmentation	segmentation	NOUN
cana-2493	30	23	.	.	PUNCT
cana-2493	31	1	for	for	ADP
cana-2493	31	2	lung	lung	NOUN
cana-2493	31	3	cancer	cancer	NOUN
cana-2493	31	4	,	,	PUNCT
cana-2493	31	5	deep	deep	ADJ
cana-2493	31	6	learning	learning	NOUN
cana-2493	31	7	models	model	NOUN
cana-2493	31	8	hold	hold	VERB
cana-2493	31	9	the	the	DET
cana-2493	31	10	potential	potential	NOUN
cana-2493	31	11	to	to	PART
cana-2493	31	12	significantly	significantly	ADV
cana-2493	31	13	improve	improve	VERB
cana-2493	31	14	the	the	DET
cana-2493	31	15	precision	precision	NOUN
cana-2493	31	16	,	,	PUNCT
cana-2493	31	17	speed	speed	NOUN
cana-2493	31	18	,	,	PUNCT
cana-2493	31	19	and	and	CCONJ
cana-2493	31	20	consistency	consistency	NOUN
cana-2493	31	21	of	of	ADP
cana-2493	31	22	detection	detection	NOUN
cana-2493	31	23	and	and	CCONJ
cana-2493	31	24	segmentation	segmentation	NOUN
cana-2493	31	25	tasks	task	NOUN
cana-2493	31	26	,	,	PUNCT
cana-2493	31	27	addressing	address	VERB
cana-2493	31	28	the	the	DET
cana-2493	31	29	restrictions	restriction	NOUN
cana-2493	31	30	of	of	ADP
cana-2493	31	31	traditional	traditional	ADJ
cana-2493	31	32	techniques	technique	NOUN
cana-2493	31	33	.	.	PUNCT
cana-2493	32	1	despite	despite	SCONJ
cana-2493	32	2	the	the	DET
cana-2493	32	3	potential	potential	NOUN
cana-2493	32	4	of	of	ADP
cana-2493	32	5	deep	deep	ADJ
cana-2493	32	6	learning	learning	NOUN
cana-2493	32	7	,	,	PUNCT
cana-2493	32	8	difficulties	difficulty	NOUN
cana-2493	32	9	remain	remain	VERB
cana-2493	32	10	in	in	ADP
cana-2493	32	11	applying	apply	VERB
cana-2493	32	12	these	these	DET
cana-2493	32	13	models	model	NOUN
cana-2493	32	14	productively	productively	ADV
cana-2493	32	15	to	to	ADP
cana-2493	32	16	lung	lung	NOUN
cana-2493	32	17	cancer	cancer	NOUN
cana-2493	32	18	detection	detection	NOUN
cana-2493	32	19	and	and	CCONJ
cana-2493	32	20	segmentation	segmentation	NOUN
cana-2493	32	21	.	.	PUNCT
cana-2493	33	1	among	among	ADP
cana-2493	33	2	the	the	DET
cana-2493	33	3	key	key	ADJ
cana-2493	33	4	difficulties	difficulty	NOUN
cana-2493	33	5	is	be	AUX
cana-2493	33	6	the	the	DET
cana-2493	33	7	diversity	diversity	NOUN
cana-2493	33	8	in	in	ADP
cana-2493	33	9	medical	medical	ADJ
cana-2493	33	10	image	image	NOUN
cana-2493	33	11	quality	quality	NOUN
cana-2493	33	12	.	.	PUNCT
cana-2493	34	1	ct	ct	PROPN
cana-2493	34	2	scans	scan	NOUN
cana-2493	34	3	and	and	CCONJ
cana-2493	34	4	x	x	NOUN
cana-2493	34	5	-	-	NOUN
cana-2493	34	6	rays	ray	NOUN
cana-2493	34	7	can	can	AUX
cana-2493	34	8	vary	vary	VERB
cana-2493	34	9	regarding	regard	VERB
cana-2493	34	10	resolution	resolution	NOUN
cana-2493	34	11	,	,	PUNCT
cana-2493	34	12	contrast	contrast	NOUN
cana-2493	34	13	,	,	PUNCT
cana-2493	34	14	and	and	CCONJ
cana-2493	34	15	noise	noise	NOUN
cana-2493	34	16	,	,	PUNCT
cana-2493	34	17	rendering	render	VERB
cana-2493	34	18	it	it	PRON
cana-2493	34	19	tricky	tricky	ADJ
cana-2493	34	20	for	for	ADP
cana-2493	34	21	deep	deep	ADJ
cana-2493	34	22	learning	learning	NOUN
cana-2493	34	23	models	model	NOUN
cana-2493	34	24	to	to	PART
cana-2493	34	25	generalize	generalize	VERB
cana-2493	34	26	across	across	ADP
cana-2493	34	27	different	different	ADJ
cana-2493	34	28	datasets	dataset	NOUN
cana-2493	34	29	.	.	PUNCT
cana-2493	35	1	additionally	additionally	ADV
cana-2493	35	2	,	,	PUNCT
cana-2493	35	3	lung	lung	NOUN
cana-2493	35	4	cancer	cancer	NOUN
cana-2493	35	5	lesions	lesion	NOUN
cana-2493	35	6	and	and	CCONJ
cana-2493	35	7	nodules	nodule	NOUN
cana-2493	35	8	can	can	AUX
cana-2493	35	9	have	have	VERB
cana-2493	35	10	varying	vary	VERB
cana-2493	35	11	shapes	shape	NOUN
cana-2493	35	12	,	,	PUNCT
cana-2493	35	13	sizes	size	NOUN
cana-2493	35	14	,	,	PUNCT
cana-2493	35	15	and	and	CCONJ
cana-2493	35	16	places	place	NOUN
cana-2493	35	17	,	,	PUNCT
cana-2493	35	18	further	far	ADV
cana-2493	35	19	complicating	complicate	VERB
cana-2493	35	20	the	the	DET
cana-2493	35	21	endeavor	endeavor	NOUN
cana-2493	35	22	of	of	ADP
cana-2493	35	23	accurate	accurate	ADJ
cana-2493	35	24	segmentation	segmentation	NOUN
cana-2493	35	25	.	.	PUNCT
cana-2493	36	1	furthermore	furthermore	ADV
cana-2493	36	2	,	,	PUNCT
cana-2493	36	3	most	most	ADJ
cana-2493	36	4	existing	existing	ADJ
cana-2493	36	5	deep	deep	ADJ
cana-2493	36	6	learning	learning	NOUN
cana-2493	36	7	models	model	NOUN
cana-2493	36	8	for	for	ADP
cana-2493	36	9	lung	lung	NOUN
cana-2493	36	10	cancer	cancer	NOUN
cana-2493	36	11	detection	detection	NOUN
cana-2493	36	12	have	have	AUX
cana-2493	36	13	focused	focus	VERB
cana-2493	36	14	on	on	ADP
cana-2493	36	15	binary	binary	ADJ
cana-2493	36	16	classification	classification	NOUN
cana-2493	36	17	tasks	task	NOUN
cana-2493	36	18	(	(	PUNCT
cana-2493	36	19	e.g.	e.g.	ADV
cana-2493	36	20	,	,	PUNCT
cana-2493	36	21	detecting	detect	VERB
cana-2493	36	22	whether	whether	SCONJ
cana-2493	36	23	a	a	DET
cana-2493	36	24	lesion	lesion	NOUN
cana-2493	36	25	is	be	AUX
cana-2493	36	26	cancerous	cancerous	ADJ
cana-2493	36	27	or	or	CCONJ
cana-2493	36	28	benign	benign	ADJ
cana-2493	36	29	)	)	PUNCT
cana-2493	36	30	,	,	PUNCT
cana-2493	36	31	with	with	ADP
cana-2493	36	32	less	less	ADJ
cana-2493	36	33	emphasis	emphasis	NOUN
cana-2493	36	34	on	on	ADP
cana-2493	36	35	the	the	DET
cana-2493	36	36	finer	finer	ADV
cana-2493	36	37	-	-	PUNCT
cana-2493	36	38	grained	grain	VERB
cana-2493	36	39	task	task	NOUN
cana-2493	36	40	of	of	ADP
cana-2493	36	41	segmenting	segment	VERB
cana-2493	36	42	cancerous	cancerous	ADJ
cana-2493	36	43	regions	region	NOUN
cana-2493	36	44	from	from	ADP
cana-2493	36	45	the	the	DET
cana-2493	36	46	surrounding	surround	VERB
cana-2493	36	47	lung	lung	NOUN
cana-2493	36	48	tissue	tissue	NOUN
cana-2493	36	49	.	.	PUNCT
cana-2493	37	1	the	the	DET
cana-2493	37	2	focus	focus	NOUN
cana-2493	37	3	of	of	ADP
cana-2493	37	4	this	this	DET
cana-2493	37	5	research	research	NOUN
cana-2493	37	6	aims	aim	VERB
cana-2493	37	7	to	to	PART
cana-2493	37	8	address	address	VERB
cana-2493	37	9	current	current	ADJ
cana-2493	37	10	challenges	challenge	NOUN
cana-2493	37	11	by	by	ADP
cana-2493	37	12	putting	put	VERB
cana-2493	37	13	forth	forth	ADP
cana-2493	37	14	an	an	DET
cana-2493	37	15	innovative	innovative	ADJ
cana-2493	37	16	deep	deep	ADJ
cana-2493	37	17	learning	learning	NOUN
cana-2493	37	18	framework	framework	NOUN
cana-2493	37	19	for	for	ADP
cana-2493	37	20	lung	lung	NOUN
cana-2493	37	21	cancer	cancer	NOUN
cana-2493	37	22	identification	identification	NOUN
cana-2493	37	23	and	and	CCONJ
cana-2493	37	24	segmentation[4	segmentation[4	NOUN
cana-2493	37	25	]	]	PUNCT
cana-2493	37	26	.	.	PUNCT
cana-2493	38	1	unlike	unlike	ADP
cana-2493	38	2	past	past	ADJ
cana-2493	38	3	methods	method	NOUN
cana-2493	38	4	,	,	PUNCT
cana-2493	38	5	our	our	PRON
cana-2493	38	6	strategy	strategy	NOUN
cana-2493	38	7	combines	combine	VERB
cana-2493	38	8	the	the	DET
cana-2493	38	9	strengths	strength	NOUN
cana-2493	38	10	of	of	ADP
cana-2493	38	11	cnns	cnn	NOUN
cana-2493	38	12	with	with	ADP
cana-2493	38	13	data	datum	NOUN
cana-2493	38	14	augmentation	augmentation	NOUN
cana-2493	38	15	tactics	tactic	NOUN
cana-2493	38	16	and	and	CCONJ
cana-2493	38	17	multi	multi	ADJ
cana-2493	38	18	-	-	ADJ
cana-2493	38	19	scale	scale	ADJ
cana-2493	38	20	segmentation	segmentation	NOUN
cana-2493	38	21	strategies	strategy	NOUN
cana-2493	38	22	to	to	PART
cana-2493	38	23	boost	boost	VERB
cana-2493	38	24	robustness	robustness	NOUN
cana-2493	38	25	and	and	CCONJ
cana-2493	38	26	precision	precision	NOUN
cana-2493	38	27	.	.	PUNCT
cana-2493	39	1	data	datum	NOUN
cana-2493	39	2	augmentation	augmentation	NOUN
cana-2493	39	3	is	be	AUX
cana-2493	39	4	crucial	crucial	ADJ
cana-2493	39	5	for	for	ADP
cana-2493	39	6	overcoming	overcome	VERB
cana-2493	39	7	limited	limited	ADJ
cana-2493	39	8	annotated	annotate	VERB
cana-2493	39	9	data	datum	NOUN
cana-2493	39	10	,	,	PUNCT
cana-2493	39	11	a	a	DET
cana-2493	39	12	common	common	ADJ
cana-2493	39	13	issue	issue	NOUN
cana-2493	39	14	in	in	ADP
cana-2493	39	15	medical	medical	ADJ
cana-2493	39	16	imaging	imaging	NOUN
cana-2493	39	17	,	,	PUNCT
cana-2493	39	18	while	while	SCONJ
cana-2493	39	19	multi	multi	ADJ
cana-2493	39	20	-	-	ADJ
cana-2493	39	21	scale	scale	ADJ
cana-2493	39	22	segmentation	segmentation	NOUN
cana-2493	39	23	helps	helps	AUX
cana-2493	39	24	identify	identify	VERB
cana-2493	39	25	cancerous	cancerous	ADJ
cana-2493	39	26	regions	region	NOUN
cana-2493	39	27	of	of	ADP
cana-2493	39	28	varying	vary	VERB
cana-2493	39	29	sizes	size	NOUN
cana-2493	39	30	and	and	CCONJ
cana-2493	39	31	scales	scale	NOUN
cana-2493	39	32	.	.	PUNCT
cana-2493	40	1	by	by	ADP
cana-2493	40	2	integrating	integrate	VERB
cana-2493	40	3	these	these	DET
cana-2493	40	4	techniques	technique	NOUN
cana-2493	40	5	,	,	PUNCT
cana-2493	40	6	our	our	PRON
cana-2493	40	7	model	model	NOUN
cana-2493	40	8	strives	strive	VERB
cana-2493	40	9	to	to	PART
cana-2493	40	10	enhance	enhance	VERB
cana-2493	40	11	deep	deep	ADJ
cana-2493	40	12	learning	learning	NOUN
cana-2493	40	13	models	model	NOUN
cana-2493	40	14	'	'	PART
cana-2493	40	15	ability	ability	NOUN
cana-2493	40	16	to	to	PART
cana-2493	40	17	handle	handle	VERB
cana-2493	40	18	image	image	NOUN
cana-2493	40	19	quality	quality	NOUN
cana-2493	40	20	variances	variance	NOUN
cana-2493	40	21	,	,	PUNCT
cana-2493	40	22	advance	advance	VERB
cana-2493	40	23	the	the	DET
cana-2493	40	24	exactness	exactness	NOUN
cana-2493	40	25	of	of	ADP
cana-2493	40	26	lung	lung	NOUN
cana-2493	40	27	cancer	cancer	NOUN
cana-2493	40	28	segmentation	segmentation	NOUN
cana-2493	40	29	,	,	PUNCT
cana-2493	40	30	and	and	CCONJ
cana-2493	40	31	ultimately	ultimately	ADV
cana-2493	40	32	furnish	furnish	VERB
cana-2493	40	33	dependable	dependable	ADJ
cana-2493	40	34	diagnostic	diagnostic	ADJ
cana-2493	40	35	help	help	NOUN
cana-2493	40	36	for	for	ADP
cana-2493	40	37	clinicians	clinician	NOUN
cana-2493	40	38	.	.	PUNCT
cana-2493	41	1	the	the	DET
cana-2493	41	2	organization	organization	NOUN
cana-2493	41	3	of	of	ADP
cana-2493	41	4	this	this	DET
cana-2493	41	5	paper	paper	NOUN
cana-2493	41	6	is	be	AUX
cana-2493	41	7	as	as	SCONJ
cana-2493	41	8	follows	follow	VERB
cana-2493	41	9	:	:	PUNCT
cana-2493	41	10	we	we	PRON
cana-2493	41	11	first	first	ADV
cana-2493	41	12	examine	examine	VERB
cana-2493	41	13	related	related	ADJ
cana-2493	41	14	work	work	NOUN
cana-2493	41	15	in	in	ADP
cana-2493	41	16	the	the	DET
cana-2493	41	17	field	field	NOUN
cana-2493	41	18	of	of	ADP
cana-2493	41	19	lung	lung	NOUN
cana-2493	41	20	cancer	cancer	NOUN
cana-2493	41	21	detection	detection	NOUN
cana-2493	41	22	and	and	CCONJ
cana-2493	41	23	segmentation	segmentation	NOUN
cana-2493	41	24	using	use	VERB
cana-2493	41	25	deep	deep	ADJ
cana-2493	41	26	learning	learning	NOUN
cana-2493	41	27	,	,	PUNCT
cana-2493	41	28	highlighting	highlight	VERB
cana-2493	41	29	strengths	strength	NOUN
cana-2493	41	30	and	and	CCONJ
cana-2493	41	31	restrictions	restriction	NOUN
cana-2493	41	32	of	of	ADP
cana-2493	41	33	present	present	ADJ
cana-2493	41	34	approaches	approach	NOUN
cana-2493	41	35	.	.	PUNCT
cana-2493	42	1	we	we	PRON
cana-2493	42	2	then	then	ADV
cana-2493	42	3	unveil	unveil	VERB
cana-2493	42	4	our	our	PRON
cana-2493	42	5	proposed	propose	VERB
cana-2493	42	6	model	model	NOUN
cana-2493	42	7	,	,	PUNCT
cana-2493	42	8	detailing	detail	VERB
cana-2493	42	9	the	the	DET
cana-2493	42	10	architecture	architecture	NOUN
cana-2493	42	11	,	,	PUNCT
cana-2493	42	12	training	training	NOUN
cana-2493	42	13	methodology	methodology	NOUN
cana-2493	42	14	,	,	PUNCT
cana-2493	42	15	and	and	CCONJ
cana-2493	42	16	assessment	assessment	NOUN
cana-2493	42	17	measures	measure	NOUN
cana-2493	42	18	used	use	VERB
cana-2493	42	19	.	.	PUNCT
cana-2493	43	1	next	next	ADV
cana-2493	43	2	,	,	PUNCT
cana-2493	43	3	we	we	PRON
cana-2493	43	4	present	present	VERB
cana-2493	43	5	the	the	DET
cana-2493	43	6	experimental	experimental	ADJ
cana-2493	43	7	outcomes	outcome	NOUN
cana-2493	43	8	,	,	PUNCT
cana-2493	43	9	demonstrating	demonstrate	VERB
cana-2493	43	10	our	our	PRON
cana-2493	43	11	model	model	NOUN
cana-2493	43	12	's	's	PART
cana-2493	43	13	performance	performance	NOUN
cana-2493	43	14	compared	compare	VERB
cana-2493	43	15	to	to	ADP
cana-2493	43	16	state	state	NOUN
cana-2493	43	17	-	-	PUNCT
cana-2493	43	18	of	of	ADP
cana-2493	43	19	-	-	PUNCT
cana-2493	43	20	the	the	DET
cana-2493	43	21	-	-	PUNCT
cana-2493	43	22	art	art	NOUN
cana-2493	43	23	techniques	technique	NOUN
cana-2493	43	24	.	.	PUNCT
cana-2493	44	1	lastly	lastly	ADV
cana-2493	44	2	,	,	PUNCT
cana-2493	44	3	we	we	PRON
cana-2493	44	4	conclude	conclude	VERB
cana-2493	44	5	with	with	ADP
cana-2493	44	6	a	a	DET
cana-2493	44	7	discussion	discussion	NOUN
cana-2493	44	8	of	of	ADP
cana-2493	44	9	the	the	DET
cana-2493	44	10	implications	implication	NOUN
cana-2493	44	11	of	of	ADP
cana-2493	44	12	our	our	PRON
cana-2493	44	13	work	work	NOUN
cana-2493	44	14	,	,	PUNCT
cana-2493	44	15	potential	potential	ADJ
cana-2493	44	16	avenues	avenue	NOUN
cana-2493	44	17	for	for	ADP
cana-2493	44	18	future	future	ADJ
cana-2493	44	19	research	research	NOUN
cana-2493	44	20	,	,	PUNCT
cana-2493	44	21	and	and	CCONJ
cana-2493	44	22	the	the	DET
cana-2493	44	23	broader	broad	ADJ
cana-2493	44	24	impact	impact	NOUN
cana-2493	44	25	of	of	ADP
cana-2493	44	26	deep	deep	ADJ
cana-2493	44	27	learning	learning	NOUN
cana-2493	44	28	in	in	ADP
cana-2493	44	29	clinical	clinical	ADJ
cana-2493	44	30	practice	practice	NOUN
cana-2493	44	31	.	.	PUNCT
cana-2493	45	1	communications	communication	NOUN
cana-2493	45	2	on	on	ADP
cana-2493	45	3	applied	apply	VERB
cana-2493	45	4	nonlinear	nonlinear	ADJ
cana-2493	45	5	analysis	analysis	NOUN
cana-2493	45	6	issn	issn	NOUN
cana-2493	45	7	:	:	PUNCT
cana-2493	45	8	1074	1074	NUM
cana-2493	45	9	-	-	PUNCT
cana-2493	45	10	133x	133x	NUM
cana-2493	45	11	vol	vol	NOUN
cana-2493	45	12	32	32	NUM
cana-2493	45	13	no	no	NOUN
cana-2493	45	14	.	.	PUNCT
cana-2493	46	1	2s	2s	NUM
cana-2493	46	2	(	(	PUNCT
cana-2493	46	3	2025	2025	NUM
cana-2493	46	4	)	)	PUNCT
cana-2493	46	5	547	547	NUM
cana-2493	46	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	46	7	lung	lung	NOUN
cana-2493	46	8	cancer	cancer	NOUN
cana-2493	46	9	detection	detection	NOUN
cana-2493	46	10	has	have	AUX
cana-2493	46	11	traditionally	traditionally	ADV
cana-2493	46	12	been	be	AUX
cana-2493	46	13	a	a	DET
cana-2493	46	14	complex	complex	ADJ
cana-2493	46	15	task	task	NOUN
cana-2493	46	16	due	due	ADP
cana-2493	46	17	to	to	ADP
cana-2493	46	18	the	the	DET
cana-2493	46	19	inherent	inherent	ADJ
cana-2493	46	20	intricacy	intricacy	NOUN
cana-2493	46	21	of	of	ADP
cana-2493	46	22	medical	medical	ADJ
cana-2493	46	23	imagery	imagery	NOUN
cana-2493	46	24	and	and	CCONJ
cana-2493	46	25	the	the	DET
cana-2493	46	26	delicate	delicate	ADJ
cana-2493	46	27	nature	nature	NOUN
cana-2493	46	28	of	of	ADP
cana-2493	46	29	early	early	ADJ
cana-2493	46	30	developments	development	NOUN
cana-2493	46	31	of	of	ADP
cana-2493	46	32	cancerous	cancerous	ADJ
cana-2493	46	33	changes	change	NOUN
cana-2493	46	34	in	in	ADP
cana-2493	46	35	the	the	DET
cana-2493	46	36	lungs	lung	NOUN
cana-2493	46	37	.	.	PUNCT
cana-2493	47	1	the	the	DET
cana-2493	47	2	conventional	conventional	ADJ
cana-2493	47	3	approach	approach	NOUN
cana-2493	47	4	to	to	ADP
cana-2493	47	5	identifying	identify	VERB
cana-2493	47	6	lung	lung	NOUN
cana-2493	47	7	cancer	cancer	NOUN
cana-2493	47	8	involves	involve	VERB
cana-2493	47	9	using	use	VERB
cana-2493	47	10	radiological	radiological	ADJ
cana-2493	47	11	imaging	imaging	NOUN
cana-2493	47	12	,	,	PUNCT
cana-2493	47	13	primarily	primarily	ADV
cana-2493	47	14	ct	ct	NUM
cana-2493	47	15	scans	scan	NOUN
cana-2493	47	16	,	,	PUNCT
cana-2493	47	17	which	which	PRON
cana-2493	47	18	provide	provide	VERB
cana-2493	47	19	comprehensive	comprehensive	ADJ
cana-2493	47	20	cross	cross	ADJ
cana-2493	47	21	-	-	ADJ
cana-2493	47	22	sectional	sectional	ADJ
cana-2493	47	23	views	view	NOUN
cana-2493	47	24	of	of	ADP
cana-2493	47	25	the	the	DET
cana-2493	47	26	lungs	lung	NOUN
cana-2493	47	27	.	.	PUNCT
cana-2493	48	1	ct	ct	NUM
cana-2493	48	2	imaging	imaging	NOUN
cana-2493	48	3	can	can	AUX
cana-2493	48	4	expose	expose	VERB
cana-2493	48	5	tumors	tumor	NOUN
cana-2493	48	6	,	,	PUNCT
cana-2493	48	7	nodules	nodule	NOUN
cana-2493	48	8	,	,	PUNCT
cana-2493	48	9	and	and	CCONJ
cana-2493	48	10	other	other	ADJ
cana-2493	48	11	anomalies	anomaly	NOUN
cana-2493	48	12	,	,	PUNCT
cana-2493	48	13	but	but	CCONJ
cana-2493	48	14	its	its	PRON
cana-2493	48	15	interpretation	interpretation	NOUN
cana-2493	48	16	necessitates	necessitate	VERB
cana-2493	48	17	considerable	considerable	ADJ
cana-2493	48	18	proficiency[14][15	proficiency[14][15	PROPN
cana-2493	48	19	]	]	PUNCT
cana-2493	48	20	.	.	PUNCT
cana-2493	49	1	in	in	ADP
cana-2493	49	2	clinical	clinical	ADJ
cana-2493	49	3	routine	routine	NOUN
cana-2493	49	4	,	,	PUNCT
cana-2493	49	5	radiologists	radiologist	NOUN
cana-2493	49	6	visually	visually	ADV
cana-2493	49	7	inspect	inspect	VERB
cana-2493	49	8	ct	ct	NUM
cana-2493	49	9	scans	scan	NOUN
cana-2493	49	10	for	for	ADP
cana-2493	49	11	signs	sign	NOUN
cana-2493	49	12	of	of	ADP
cana-2493	49	13	lung	lung	NOUN
cana-2493	49	14	cancer	cancer	NOUN
cana-2493	49	15	,	,	PUNCT
cana-2493	49	16	but	but	CCONJ
cana-2493	49	17	the	the	DET
cana-2493	49	18	practice	practice	NOUN
cana-2493	49	19	is	be	AUX
cana-2493	49	20	time	time	NOUN
cana-2493	49	21	-	-	PUNCT
cana-2493	49	22	consuming	consume	VERB
cana-2493	49	23	and	and	CCONJ
cana-2493	49	24	prone	prone	ADJ
cana-2493	49	25	to	to	ADP
cana-2493	49	26	error	error	NOUN
cana-2493	49	27	,	,	PUNCT
cana-2493	49	28	particularly	particularly	ADV
cana-2493	49	29	when	when	SCONJ
cana-2493	49	30	abnormalities	abnormality	NOUN
cana-2493	49	31	are	be	AUX
cana-2493	49	32	small	small	ADJ
cana-2493	49	33	,	,	PUNCT
cana-2493	49	34	faint	faint	ADJ
cana-2493	49	35	,	,	PUNCT
cana-2493	49	36	or	or	CCONJ
cana-2493	49	37	overlapping	overlap	VERB
cana-2493	49	38	with	with	ADP
cana-2493	49	39	other	other	ADJ
cana-2493	49	40	structures	structure	NOUN
cana-2493	49	41	in	in	ADP
cana-2493	49	42	the	the	DET
cana-2493	49	43	chest	chest	NOUN
cana-2493	49	44	cavity	cavity	NOUN
cana-2493	49	45	.	.	PUNCT
cana-2493	50	1	figure	figure	NOUN
cana-2493	50	2	1	1	NUM
cana-2493	50	3	.	.	PUNCT
cana-2493	51	1	growth	growth	NOUN
cana-2493	51	2	of	of	ADP
cana-2493	51	3	deep	deep	ADJ
cana-2493	51	4	learning	learning	NOUN
cana-2493	51	5	research	research	NOUN
cana-2493	51	6	in	in	ADP
cana-2493	51	7	lung	lung	NOUN
cana-2493	51	8	cancer	cancer	NOUN
cana-2493	51	9	detection	detection	NOUN
cana-2493	51	10	(	(	PUNCT
cana-2493	51	11	2015	2015	NUM
cana-2493	51	12	-	-	SYM
cana-2493	51	13	2024	2024	NUM
cana-2493	51	14	)	)	PUNCT
cana-2493	51	15	to	to	PART
cana-2493	51	16	address	address	VERB
cana-2493	51	17	these	these	DET
cana-2493	51	18	issues	issue	NOUN
cana-2493	51	19	,	,	PUNCT
cana-2493	51	20	numerous	numerous	ADJ
cana-2493	51	21	automated	automate	VERB
cana-2493	51	22	methods	method	NOUN
cana-2493	51	23	have	have	AUX
cana-2493	51	24	been	be	AUX
cana-2493	51	25	put	put	VERB
cana-2493	51	26	forth	forth	ADP
cana-2493	51	27	for	for	ADP
cana-2493	51	28	lung	lung	NOUN
cana-2493	51	29	cancer	cancer	NOUN
cana-2493	51	30	identification	identification	NOUN
cana-2493	51	31	and	and	CCONJ
cana-2493	51	32	segmentation	segmentation	NOUN
cana-2493	51	33	,	,	PUNCT
cana-2493	51	34	relying	rely	VERB
cana-2493	51	35	on	on	ADP
cana-2493	51	36	machine	machine	NOUN
cana-2493	51	37	learning	learning	NOUN
cana-2493	51	38	and	and	CCONJ
cana-2493	51	39	,	,	PUNCT
cana-2493	51	40	more	more	ADV
cana-2493	51	41	recently	recently	ADV
cana-2493	51	42	,	,	PUNCT
cana-2493	51	43	deep	deep	ADJ
cana-2493	51	44	learning	learning	NOUN
cana-2493	51	45	.	.	PUNCT
cana-2493	52	1	machine	machine	NOUN
cana-2493	52	2	learning	learning	NOUN
cana-2493	52	3	-	-	PUNCT
cana-2493	52	4	based	base	VERB
cana-2493	52	5	strategies	strategy	NOUN
cana-2493	52	6	typically	typically	ADV
cana-2493	52	7	require	require	VERB
cana-2493	52	8	the	the	DET
cana-2493	52	9	manual	manual	ADJ
cana-2493	52	10	extraction	extraction	NOUN
cana-2493	52	11	of	of	ADP
cana-2493	52	12	features	feature	NOUN
cana-2493	52	13	from	from	ADP
cana-2493	52	14	medical	medical	ADJ
cana-2493	52	15	images	image	NOUN
cana-2493	52	16	,	,	PUNCT
cana-2493	52	17	which	which	PRON
cana-2493	52	18	are	be	AUX
cana-2493	52	19	then	then	ADV
cana-2493	52	20	fed	feed	VERB
cana-2493	52	21	into	into	ADP
cana-2493	52	22	algorithms	algorithm	NOUN
cana-2493	52	23	like	like	ADP
cana-2493	52	24	support	support	NOUN
cana-2493	52	25	vector	vector	NOUN
cana-2493	52	26	machines	machine	NOUN
cana-2493	52	27	(	(	PUNCT
cana-2493	52	28	svms	svms	NOUN
cana-2493	52	29	)	)	PUNCT
cana-2493	52	30	or	or	CCONJ
cana-2493	52	31	decision	decision	NOUN
cana-2493	52	32	trees	tree	NOUN
cana-2493	52	33	for	for	ADP
cana-2493	52	34	categorization	categorization	NOUN
cana-2493	52	35	.	.	PUNCT
cana-2493	53	1	while	while	SCONJ
cana-2493	53	2	these	these	DET
cana-2493	53	3	methods	method	NOUN
cana-2493	53	4	have	have	AUX
cana-2493	53	5	achieved	achieve	VERB
cana-2493	53	6	some	some	DET
cana-2493	53	7	accomplishment	accomplishment	NOUN
cana-2493	53	8	,	,	PUNCT
cana-2493	53	9	they	they	PRON
cana-2493	53	10	are	be	AUX
cana-2493	53	11	limited	limit	VERB
cana-2493	53	12	by	by	ADP
cana-2493	53	13	the	the	DET
cana-2493	53	14	need	need	NOUN
cana-2493	53	15	for	for	ADP
cana-2493	53	16	handcrafted	handcrafted	ADJ
cana-2493	53	17	features	feature	NOUN
cana-2493	53	18	,	,	PUNCT
cana-2493	53	19	which	which	PRON
cana-2493	53	20	may	may	AUX
cana-2493	53	21	not	not	PART
cana-2493	53	22	fully	fully	ADV
cana-2493	53	23	capture	capture	VERB
cana-2493	53	24	the	the	DET
cana-2493	53	25	intricate	intricate	ADJ
cana-2493	53	26	patterns	pattern	NOUN
cana-2493	53	27	inherent	inherent	ADJ
cana-2493	53	28	in	in	ADP
cana-2493	53	29	medical	medical	ADJ
cana-2493	53	30	images	image	NOUN
cana-2493	53	31	.	.	PUNCT
cana-2493	54	1	moreover	moreover	ADV
cana-2493	54	2	,	,	PUNCT
cana-2493	54	3	they	they	PRON
cana-2493	54	4	regularly	regularly	ADV
cana-2493	54	5	require	require	VERB
cana-2493	54	6	substantial	substantial	ADJ
cana-2493	54	7	domain	domain	NOUN
cana-2493	54	8	knowledge	knowledge	NOUN
cana-2493	54	9	to	to	PART
cana-2493	54	10	identify	identify	VERB
cana-2493	54	11	relevant	relevant	ADJ
cana-2493	54	12	features	feature	NOUN
cana-2493	54	13	and	and	CCONJ
cana-2493	54	14	may	may	AUX
cana-2493	54	15	struggle	struggle	VERB
cana-2493	54	16	with	with	ADP
cana-2493	54	17	high	high	ADJ
cana-2493	54	18	-	-	PUNCT
cana-2493	54	19	dimensional	dimensional	ADJ
cana-2493	54	20	data	datum	NOUN
cana-2493	54	21	,	,	PUNCT
cana-2493	54	22	such	such	ADJ
cana-2493	54	23	as	as	ADP
cana-2493	54	24	ct	ct	PROPN
cana-2493	54	25	scans	scan	NOUN
cana-2493	54	26	,	,	PUNCT
cana-2493	54	27	which	which	PRON
cana-2493	54	28	contain	contain	VERB
cana-2493	54	29	thousands	thousand	NOUN
cana-2493	54	30	of	of	ADP
cana-2493	54	31	pixels	pixel	NOUN
cana-2493	54	32	.	.	PUNCT
cana-2493	55	1	the	the	DET
cana-2493	55	2	introduction	introduction	NOUN
cana-2493	55	3	of	of	ADP
cana-2493	55	4	deep	deep	ADJ
cana-2493	55	5	learning	learning	NOUN
cana-2493	55	6	revolutionized	revolutionize	VERB
cana-2493	55	7	medical	medical	ADJ
cana-2493	55	8	image	image	NOUN
cana-2493	55	9	analysis	analysis	NOUN
cana-2493	55	10	by	by	ADP
cana-2493	55	11	enabling	enable	VERB
cana-2493	55	12	models	model	NOUN
cana-2493	55	13	to	to	PART
cana-2493	55	14	automatically	automatically	ADV
cana-2493	55	15	extract	extract	VERB
cana-2493	55	16	meaningful	meaningful	ADJ
cana-2493	55	17	patterns	pattern	NOUN
cana-2493	55	18	from	from	ADP
cana-2493	55	19	raw	raw	ADJ
cana-2493	55	20	image	image	NOUN
cana-2493	55	21	data	datum	NOUN
cana-2493	55	22	without	without	ADP
cana-2493	55	23	human	human	ADJ
cana-2493	55	24	design	design	NOUN
cana-2493	55	25	of	of	ADP
cana-2493	55	26	features	feature	NOUN
cana-2493	55	27	.	.	PUNCT
cana-2493	56	1	convolutional	convolutional	ADJ
cana-2493	56	2	neural	neural	ADJ
cana-2493	56	3	networks	network	NOUN
cana-2493	56	4	are	be	AUX
cana-2493	56	5	the	the	DET
cana-2493	56	6	predominant	predominant	ADJ
cana-2493	56	7	deep	deep	ADJ
cana-2493	56	8	learning	learning	NOUN
cana-2493	56	9	approach	approach	NOUN
cana-2493	56	10	for	for	ADP
cana-2493	56	11	analyzing	analyze	VERB
cana-2493	56	12	images	image	NOUN
cana-2493	56	13	,	,	PUNCT
cana-2493	56	14	including	include	VERB
cana-2493	56	15	lung	lung	NOUN
cana-2493	56	16	cancer	cancer	NOUN
cana-2493	56	17	detection	detection	NOUN
cana-2493	56	18	.	.	PUNCT
cana-2493	57	1	cnns	cnns	PROPN
cana-2493	57	2	apply	apply	VERB
cana-2493	57	3	repeating	repeat	VERB
cana-2493	57	4	operations	operation	NOUN
cana-2493	57	5	of	of	ADP
cana-2493	57	6	filtering	filtering	NOUN
cana-2493	57	7	,	,	PUNCT
cana-2493	57	8	activation	activation	NOUN
cana-2493	57	9	,	,	PUNCT
cana-2493	57	10	and	and	CCONJ
cana-2493	57	11	pooling	pool	VERB
cana-2493	57	12	to	to	PART
cana-2493	57	13	extract	extract	VERB
cana-2493	57	14	increasingly	increasingly	ADV
cana-2493	57	15	complex	complex	ADJ
cana-2493	57	16	representations	representation	NOUN
cana-2493	57	17	of	of	ADP
cana-2493	57	18	images	image	NOUN
cana-2493	57	19	.	.	PUNCT
cana-2493	58	1	these	these	DET
cana-2493	58	2	networks	network	NOUN
cana-2493	58	3	are	be	AUX
cana-2493	58	4	trained	train	VERB
cana-2493	58	5	on	on	ADP
cana-2493	58	6	huge	huge	ADJ
cana-2493	58	7	datasets	dataset	NOUN
cana-2493	58	8	of	of	ADP
cana-2493	58	9	annotated	annotate	VERB
cana-2493	58	10	medical	medical	ADJ
cana-2493	58	11	scans	scan	NOUN
cana-2493	58	12	,	,	PUNCT
cana-2493	58	13	which	which	PRON
cana-2493	58	14	permits	permit	VERB
cana-2493	58	15	detection	detection	NOUN
cana-2493	58	16	of	of	ADP
cana-2493	58	17	visual	visual	ADJ
cana-2493	58	18	hallmarks	hallmark	NOUN
cana-2493	58	19	linked	link	VERB
cana-2493	58	20	to	to	ADP
cana-2493	58	21	cancerous	cancerous	ADJ
cana-2493	58	22	and	and	CCONJ
cana-2493	58	23	healthy	healthy	ADJ
cana-2493	58	24	lung	lung	NOUN
cana-2493	58	25	regions	region	NOUN
cana-2493	58	26	.	.	PUNCT
cana-2493	59	1	early	early	ADJ
cana-2493	59	2	deep	deep	ADJ
cana-2493	59	3	learning	learning	NOUN
cana-2493	59	4	research	research	NOUN
cana-2493	59	5	for	for	ADP
cana-2493	59	6	lung	lung	NOUN
cana-2493	59	7	cancer	cancer	NOUN
cana-2493	59	8	focused	focus	VERB
cana-2493	59	9	on	on	ADP
cana-2493	59	10	classifying	classify	VERB
cana-2493	59	11	nodules	nodule	NOUN
cana-2493	59	12	as	as	ADP
cana-2493	59	13	malignant	malignant	ADJ
cana-2493	59	14	or	or	CCONJ
cana-2493	59	15	benign	benign	ADJ
cana-2493	59	16	using	use	VERB
cana-2493	59	17	cnns	cnn	NOUN
cana-2493	59	18	trained	train	VERB
cana-2493	59	19	on	on	ADP
cana-2493	59	20	labeled	label	VERB
cana-2493	59	21	ct	ct	NUM
cana-2493	59	22	scans	scan	NOUN
cana-2493	59	23	.	.	PUNCT
cana-2493	60	1	such	such	ADJ
cana-2493	60	2	methods	method	NOUN
cana-2493	60	3	exhibited	exhibit	VERB
cana-2493	60	4	potential	potential	NOUN
cana-2493	60	5	for	for	ADP
cana-2493	60	6	finding	find	VERB
cana-2493	60	7	cancerous	cancerous	ADJ
cana-2493	60	8	nodules	nodule	NOUN
cana-2493	60	9	,	,	PUNCT
cana-2493	60	10	with	with	ADP
cana-2493	60	11	some	some	DET
cana-2493	60	12	models	model	NOUN
cana-2493	60	13	achieving	achieve	VERB
cana-2493	60	14	expert	expert	NOUN
cana-2493	60	15	-	-	PUNCT
cana-2493	60	16	level	level	NOUN
cana-2493	60	17	accuracy[3	accuracy[3	NOUN
cana-2493	60	18	]	]	PUNCT
cana-2493	60	19	.	.	PUNCT
cana-2493	61	1	yet	yet	CCONJ
cana-2493	61	2	segmentation	segmentation	NOUN
cana-2493	61	3	was	be	AUX
cana-2493	61	4	challenging	challenge	VERB
cana-2493	61	5	since	since	SCONJ
cana-2493	61	6	the	the	DET
cana-2493	61	7	models	model	NOUN
cana-2493	61	8	centered	center	VERB
cana-2493	61	9	on	on	ADP
cana-2493	61	10	categorization	categorization	NOUN
cana-2493	61	11	rather	rather	ADV
cana-2493	61	12	than	than	ADP
cana-2493	61	13	delineating	delineate	VERB
cana-2493	61	14	tumor	tumor	NOUN
cana-2493	61	15	perimeters	perimeter	NOUN
cana-2493	61	16	.	.	PUNCT
cana-2493	62	1	more	more	ADV
cana-2493	62	2	recent	recent	ADJ
cana-2493	62	3	work	work	NOUN
cana-2493	62	4	enhanced	enhance	VERB
cana-2493	62	5	cnns	cnn	NOUN
cana-2493	62	6	to	to	PART
cana-2493	62	7	output	output	VERB
cana-2493	62	8	pixel	pixel	ADJ
cana-2493	62	9	-	-	PUNCT
cana-2493	62	10	level	level	NOUN
cana-2493	62	11	labels	label	NOUN
cana-2493	62	12	through	through	ADP
cana-2493	62	13	adaptations	adaptation	NOUN
cana-2493	62	14	like	like	ADP
cana-2493	62	15	u	u	NOUN
cana-2493	62	16	-	-	NOUN
cana-2493	62	17	net	net	ADJ
cana-2493	62	18	and	and	CCONJ
cana-2493	62	19	mask	mask	NOUN
cana-2493	62	20	r	r	NOUN
cana-2493	62	21	-	-	PUNCT
cana-2493	62	22	cnn	cnn	NOUN
cana-2493	62	23	.	.	PUNCT
cana-2493	63	1	these	these	DET
cana-2493	63	2	models	model	NOUN
cana-2493	63	3	generate	generate	VERB
cana-2493	63	4	binary	binary	ADJ
cana-2493	63	5	maps	map	NOUN
cana-2493	63	6	separating	separate	VERB
cana-2493	63	7	lung	lung	NOUN
cana-2493	63	8	tissue	tissue	NOUN
cana-2493	63	9	from	from	ADP
cana-2493	63	10	surroundings	surrounding	NOUN
cana-2493	63	11	.	.	PUNCT
cana-2493	64	1	u	u	NOUN
cana-2493	64	2	-	-	NOUN
cana-2493	64	3	net	net	NOUN
cana-2493	64	4	particularly	particularly	ADV
cana-2493	64	5	shines	shine	VERB
cana-2493	64	6	at	at	ADP
cana-2493	64	7	medical	medical	ADJ
cana-2493	64	8	imaging	imaging	NOUN
cana-2493	64	9	segmentation	segmentation	NOUN
cana-2493	64	10	due	due	ADP
cana-2493	64	11	to	to	ADP
cana-2493	64	12	its	its	PRON
cana-2493	64	13	symmetrical	symmetrical	ADJ
cana-2493	64	14	design	design	NOUN
cana-2493	64	15	extracting	extract	VERB
cana-2493	64	16	multiscale	multiscale	NOUN
cana-2493	64	17	features	feature	NOUN
cana-2493	64	18	.	.	PUNCT
cana-2493	65	1	communications	communication	NOUN
cana-2493	65	2	on	on	ADP
cana-2493	65	3	applied	apply	VERB
cana-2493	65	4	nonlinear	nonlinear	ADJ
cana-2493	65	5	analysis	analysis	NOUN
cana-2493	65	6	issn	issn	NOUN
cana-2493	65	7	:	:	PUNCT
cana-2493	65	8	1074	1074	NUM
cana-2493	65	9	-	-	PUNCT
cana-2493	65	10	133x	133x	NUM
cana-2493	65	11	vol	vol	NOUN
cana-2493	65	12	32	32	NUM
cana-2493	65	13	no	no	NOUN
cana-2493	65	14	.	.	PUNCT
cana-2493	66	1	2s	2s	NUM
cana-2493	66	2	(	(	PUNCT
cana-2493	66	3	2025	2025	NUM
cana-2493	66	4	)	)	PUNCT
cana-2493	66	5	548	548	NUM
cana-2493	66	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	66	7	nevertheless	nevertheless	ADV
cana-2493	66	8	,	,	PUNCT
cana-2493	66	9	segmentation	segmentation	NOUN
cana-2493	66	10	remains	remain	VERB
cana-2493	66	11	difficult	difficult	ADJ
cana-2493	66	12	when	when	SCONJ
cana-2493	66	13	images	image	NOUN
cana-2493	66	14	exhibit	exhibit	VERB
cana-2493	66	15	quality	quality	NOUN
cana-2493	66	16	variations	variation	NOUN
cana-2493	66	17	in	in	ADP
cana-2493	66	18	noise	noise	NOUN
cana-2493	66	19	,	,	PUNCT
cana-2493	66	20	contrast	contrast	NOUN
cana-2493	66	21	,	,	PUNCT
cana-2493	66	22	or	or	CCONJ
cana-2493	66	23	resolution	resolution	NOUN
cana-2493	66	24	.	.	PUNCT
cana-2493	67	1	continued	continue	VERB
cana-2493	67	2	progress	progress	NOUN
cana-2493	67	3	requires	require	VERB
cana-2493	67	4	models	model	NOUN
cana-2493	67	5	robust	robust	ADJ
cana-2493	67	6	to	to	ADP
cana-2493	67	7	such	such	ADJ
cana-2493	67	8	real	real	ADJ
cana-2493	67	9	-	-	PUNCT
cana-2493	67	10	world	world	NOUN
cana-2493	67	11	imaging	imaging	NOUN
cana-2493	67	12	inconsistencies	inconsistency	NOUN
cana-2493	67	13	.	.	PUNCT
cana-2493	68	1	future	future	ADJ
cana-2493	68	2	work	work	NOUN
cana-2493	68	3	may	may	AUX
cana-2493	68	4	incorporate	incorporate	VERB
cana-2493	68	5	techniques	technique	NOUN
cana-2493	68	6	like	like	ADP
cana-2493	68	7	data	datum	NOUN
cana-2493	68	8	augmentation	augmentation	NOUN
cana-2493	68	9	or	or	CCONJ
cana-2493	68	10	multi	multi	ADJ
cana-2493	68	11	-	-	NOUN
cana-2493	68	12	task	task	ADJ
cana-2493	68	13	learning	learning	NOUN
cana-2493	68	14	to	to	PART
cana-2493	68	15	build	build	VERB
cana-2493	68	16	flexibility	flexibility	NOUN
cana-2493	68	17	across	across	ADP
cana-2493	68	18	diverse	diverse	ADJ
cana-2493	68	19	clinical	clinical	ADJ
cana-2493	68	20	scans	scan	NOUN
cana-2493	68	21	.	.	PUNCT
cana-2493	69	1	deep	deep	ADJ
cana-2493	69	2	learning	learning	NOUN
cana-2493	69	3	holds	hold	VERB
cana-2493	69	4	promise	promise	NOUN
cana-2493	69	5	for	for	ADP
cana-2493	69	6	advancing	advance	VERB
cana-2493	69	7	automated	automate	VERB
cana-2493	69	8	lung	lung	NOUN
cana-2493	69	9	cancer	cancer	NOUN
cana-2493	69	10	analysis	analysis	NOUN
cana-2493	69	11	,	,	PUNCT
cana-2493	69	12	but	but	CCONJ
cana-2493	69	13	challenges	challenge	NOUN
cana-2493	69	14	remain	remain	VERB
cana-2493	69	15	in	in	ADP
cana-2493	69	16	deploying	deploy	VERB
cana-2493	69	17	solutions	solution	NOUN
cana-2493	69	18	applicable	applicable	ADJ
cana-2493	69	19	to	to	ADP
cana-2493	69	20	the	the	DET
cana-2493	69	21	complexity	complexity	NOUN
cana-2493	69	22	of	of	ADP
cana-2493	69	23	real	real	ADJ
cana-2493	69	24	patient	patient	ADJ
cana-2493	69	25	populations	population	NOUN
cana-2493	69	26	and	and	CCONJ
cana-2493	69	27	medical	medical	ADJ
cana-2493	69	28	environments	environment	NOUN
cana-2493	69	29	.	.	PUNCT
cana-2493	70	1	the	the	DET
cana-2493	70	2	primary	primary	ADJ
cana-2493	70	3	challenges	challenge	NOUN
cana-2493	70	4	in	in	ADP
cana-2493	70	5	lung	lung	NOUN
cana-2493	70	6	cancer	cancer	NOUN
cana-2493	70	7	detection	detection	NOUN
cana-2493	70	8	and	and	CCONJ
cana-2493	70	9	segmentation	segmentation	NOUN
cana-2493	70	10	originate	originate	VERB
cana-2493	70	11	from	from	ADP
cana-2493	70	12	the	the	DET
cana-2493	70	13	variability	variability	NOUN
cana-2493	70	14	within	within	ADP
cana-2493	70	15	medical	medical	ADJ
cana-2493	70	16	imaging	imaging	NOUN
cana-2493	70	17	information	information	NOUN
cana-2493	70	18	,	,	PUNCT
cana-2493	70	19	the	the	DET
cana-2493	70	20	complexity	complexity	NOUN
cana-2493	70	21	of	of	ADP
cana-2493	70	22	lung	lung	NOUN
cana-2493	70	23	cancer	cancer	NOUN
cana-2493	70	24	lesions	lesion	NOUN
cana-2493	70	25	,	,	PUNCT
cana-2493	70	26	and	and	CCONJ
cana-2493	70	27	the	the	DET
cana-2493	70	28	necessity	necessity	NOUN
cana-2493	70	29	for	for	ADP
cana-2493	70	30	precise	precise	ADJ
cana-2493	70	31	delineation	delineation	NOUN
cana-2493	70	32	of	of	ADP
cana-2493	70	33	cancerous	cancerous	ADJ
cana-2493	70	34	regions	region	NOUN
cana-2493	70	35	.	.	PUNCT
cana-2493	71	1	first	first	ADV
cana-2493	71	2	,	,	PUNCT
cana-2493	71	3	medical	medical	ADJ
cana-2493	71	4	imaging	imaging	NOUN
cana-2493	71	5	data	datum	NOUN
cana-2493	71	6	can	can	AUX
cana-2493	71	7	be	be	AUX
cana-2493	71	8	murky	murky	ADJ
cana-2493	71	9	,	,	PUNCT
cana-2493	71	10	with	with	ADP
cana-2493	71	11	fluctuations	fluctuation	NOUN
cana-2493	71	12	in	in	ADP
cana-2493	71	13	contrast	contrast	NOUN
cana-2493	71	14	,	,	PUNCT
cana-2493	71	15	resolution	resolution	NOUN
cana-2493	71	16	,	,	PUNCT
cana-2493	71	17	and	and	CCONJ
cana-2493	71	18	artifacts	artifact	NOUN
cana-2493	71	19	that	that	PRON
cana-2493	71	20	can	can	AUX
cana-2493	71	21	perplex	perplex	VERB
cana-2493	71	22	machine	machine	NOUN
cana-2493	71	23	learning	learning	NOUN
cana-2493	71	24	models	model	NOUN
cana-2493	71	25	.	.	PUNCT
cana-2493	72	1	deep	deep	ADJ
cana-2493	72	2	learning	learning	NOUN
cana-2493	72	3	models	model	NOUN
cana-2493	72	4	that	that	PRON
cana-2493	72	5	are	be	AUX
cana-2493	72	6	not	not	PART
cana-2493	72	7	robust	robust	ADJ
cana-2493	72	8	to	to	ADP
cana-2493	72	9	such	such	ADJ
cana-2493	72	10	variations	variation	NOUN
cana-2493	72	11	may	may	AUX
cana-2493	72	12	carry	carry	VERB
cana-2493	72	13	out	out	ADP
cana-2493	72	14	inadequately	inadequately	ADV
cana-2493	72	15	when	when	SCONJ
cana-2493	72	16	faced	face	VERB
cana-2493	72	17	with	with	ADP
cana-2493	72	18	real	real	ADJ
cana-2493	72	19	-	-	PUNCT
cana-2493	72	20	world	world	NOUN
cana-2493	72	21	clinical	clinical	ADJ
cana-2493	72	22	evidence	evidence	NOUN
cana-2493	72	23	,	,	PUNCT
cana-2493	72	24	where	where	SCONJ
cana-2493	72	25	images	image	NOUN
cana-2493	72	26	may	may	AUX
cana-2493	72	27	not	not	PART
cana-2493	72	28	be	be	AUX
cana-2493	72	29	of	of	ADP
cana-2493	72	30	the	the	DET
cana-2493	72	31	equivalent	equivalent	ADJ
cana-2493	72	32	quality	quality	NOUN
cana-2493	72	33	as	as	ADP
cana-2493	72	34	those	those	PRON
cana-2493	72	35	in	in	ADP
cana-2493	72	36	training	training	NOUN
cana-2493	72	37	datasets	dataset	NOUN
cana-2493	72	38	.	.	PUNCT
cana-2493	73	1	second	second	ADJ
cana-2493	73	2	,	,	PUNCT
cana-2493	73	3	lung	lung	NOUN
cana-2493	73	4	cancer	cancer	NOUN
cana-2493	73	5	lesions	lesion	NOUN
cana-2493	73	6	can	can	AUX
cana-2493	73	7	differ	differ	VERB
cana-2493	73	8	significantly	significantly	ADV
cana-2493	73	9	in	in	ADP
cana-2493	73	10	size	size	NOUN
cana-2493	73	11	,	,	PUNCT
cana-2493	73	12	shape	shape	NOUN
cana-2493	73	13	,	,	PUNCT
cana-2493	73	14	and	and	CCONJ
cana-2493	73	15	place	place	NOUN
cana-2493	73	16	,	,	PUNCT
cana-2493	73	17	making	make	VERB
cana-2493	73	18	it	it	PRON
cana-2493	73	19	difficult	difficult	ADJ
cana-2493	73	20	to	to	PART
cana-2493	73	21	generate	generate	VERB
cana-2493	73	22	a	a	DET
cana-2493	73	23	onesize	onesize	NOUN
cana-2493	73	24	-	-	PUNCT
cana-2493	73	25	fits	fit	VERB
cana-2493	73	26	-	-	PUNCT
cana-2493	73	27	all	all	DET
cana-2493	73	28	segmentation	segmentation	NOUN
cana-2493	73	29	model[2	model[2	NOUN
cana-2493	73	30	]	]	PUNCT
cana-2493	73	31	.	.	PUNCT
cana-2493	74	1	for	for	ADP
cana-2493	74	2	instance	instance	NOUN
cana-2493	74	3	,	,	PUNCT
cana-2493	74	4	some	some	DET
cana-2493	74	5	tumors	tumor	NOUN
cana-2493	74	6	may	may	AUX
cana-2493	74	7	be	be	AUX
cana-2493	74	8	small	small	ADJ
cana-2493	74	9	and	and	CCONJ
cana-2493	74	10	located	locate	VERB
cana-2493	74	11	in	in	ADP
cana-2493	74	12	the	the	DET
cana-2493	74	13	outskirts	outskirt	NOUN
cana-2493	74	14	of	of	ADP
cana-2493	74	15	the	the	DET
cana-2493	74	16	lung	lung	NOUN
cana-2493	74	17	,	,	PUNCT
cana-2493	74	18	while	while	SCONJ
cana-2493	74	19	others	other	NOUN
cana-2493	74	20	may	may	AUX
cana-2493	74	21	be	be	AUX
cana-2493	74	22	large	large	ADJ
cana-2493	74	23	and	and	CCONJ
cana-2493	74	24	centrally	centrally	ADV
cana-2493	74	25	positioned	position	VERB
cana-2493	74	26	.	.	PUNCT
cana-2493	75	1	this	this	DET
cana-2493	75	2	variability	variability	NOUN
cana-2493	75	3	in	in	ADP
cana-2493	75	4	lesion	lesion	NOUN
cana-2493	75	5	characteristics	characteristic	NOUN
cana-2493	75	6	necessitates	necessitate	VERB
cana-2493	75	7	the	the	DET
cana-2493	75	8	employment	employment	NOUN
cana-2493	75	9	of	of	ADP
cana-2493	75	10	models	model	NOUN
cana-2493	75	11	that	that	PRON
cana-2493	75	12	can	can	AUX
cana-2493	75	13	seize	seize	VERB
cana-2493	75	14	features	feature	NOUN
cana-2493	75	15	at	at	ADP
cana-2493	75	16	multiple	multiple	ADJ
cana-2493	75	17	scales	scale	NOUN
cana-2493	75	18	and	and	CCONJ
cana-2493	75	19	offer	offer	VERB
cana-2493	75	20	accurate	accurate	ADJ
cana-2493	75	21	segmentation	segmentation	NOUN
cana-2493	75	22	irrespective	irrespective	ADV
cana-2493	75	23	of	of	ADP
cana-2493	75	24	the	the	DET
cana-2493	75	25	tumor	tumor	NOUN
cana-2493	75	26	's	's	PART
cana-2493	75	27	size	size	NOUN
cana-2493	75	28	or	or	CCONJ
cana-2493	75	29	location	location	NOUN
cana-2493	75	30	.	.	PUNCT
cana-2493	76	1	additionally	additionally	ADV
cana-2493	76	2	,	,	PUNCT
cana-2493	76	3	while	while	SCONJ
cana-2493	76	4	deep	deep	ADJ
cana-2493	76	5	learning	learning	NOUN
cana-2493	76	6	models	model	NOUN
cana-2493	76	7	have	have	AUX
cana-2493	76	8	accomplished	accomplish	VERB
cana-2493	76	9	achievement	achievement	NOUN
cana-2493	76	10	in	in	ADP
cana-2493	76	11	binary	binary	ADJ
cana-2493	76	12	categorization	categorization	NOUN
cana-2493	76	13	tasks	task	NOUN
cana-2493	76	14	(	(	PUNCT
cana-2493	76	15	i.e.	i.e.	X
cana-2493	76	16	,	,	PUNCT
cana-2493	76	17	discovering	discover	VERB
cana-2493	76	18	the	the	DET
cana-2493	76	19	appearance	appearance	NOUN
cana-2493	76	20	or	or	CCONJ
cana-2493	76	21	absence	absence	NOUN
cana-2493	76	22	of	of	ADP
cana-2493	76	23	lung	lung	NOUN
cana-2493	76	24	cancer	cancer	NOUN
cana-2493	76	25	)	)	PUNCT
cana-2493	76	26	,	,	PUNCT
cana-2493	76	27	there	there	PRON
cana-2493	76	28	remains	remain	VERB
cana-2493	76	29	a	a	DET
cana-2493	76	30	significant	significant	ADJ
cana-2493	76	31	gap	gap	NOUN
cana-2493	76	32	in	in	ADP
cana-2493	76	33	the	the	DET
cana-2493	76	34	precise	precise	ADJ
cana-2493	76	35	segmentation	segmentation	NOUN
cana-2493	76	36	of	of	ADP
cana-2493	76	37	cancerous	cancerous	ADJ
cana-2493	76	38	regions	region	NOUN
cana-2493	76	39	.	.	PUNCT
cana-2493	77	1	automated	automate	VERB
cana-2493	77	2	segmentation	segmentation	NOUN
cana-2493	77	3	can	can	AUX
cana-2493	77	4	furnish	furnish	VERB
cana-2493	77	5	more	more	ADJ
cana-2493	77	6	comprehensive	comprehensive	ADJ
cana-2493	77	7	insights	insight	NOUN
cana-2493	77	8	into	into	ADP
cana-2493	77	9	the	the	DET
cana-2493	77	10	size	size	NOUN
cana-2493	77	11	,	,	PUNCT
cana-2493	77	12	shape	shape	NOUN
cana-2493	77	13	,	,	PUNCT
cana-2493	77	14	and	and	CCONJ
cana-2493	77	15	place	place	NOUN
cana-2493	77	16	of	of	ADP
cana-2493	77	17	tumors	tumor	NOUN
cana-2493	77	18	,	,	PUNCT
cana-2493	77	19	which	which	PRON
cana-2493	77	20	is	be	AUX
cana-2493	77	21	crucial	crucial	ADJ
cana-2493	77	22	for	for	ADP
cana-2493	77	23	treatment	treatment	NOUN
cana-2493	77	24	planning	planning	NOUN
cana-2493	77	25	,	,	PUNCT
cana-2493	77	26	staging	staging	NOUN
cana-2493	77	27	,	,	PUNCT
cana-2493	77	28	and	and	CCONJ
cana-2493	77	29	tracking	tracking	NOUN
cana-2493	77	30	.	.	PUNCT
cana-2493	78	1	accurate	accurate	ADJ
cana-2493	78	2	segmentation	segmentation	NOUN
cana-2493	78	3	also	also	ADV
cana-2493	78	4	reduces	reduce	VERB
cana-2493	78	5	the	the	DET
cana-2493	78	6	reliance	reliance	NOUN
cana-2493	78	7	on	on	ADP
cana-2493	78	8	manual	manual	ADJ
cana-2493	78	9	annotation	annotation	NOUN
cana-2493	78	10	,	,	PUNCT
cana-2493	78	11	which	which	PRON
cana-2493	78	12	can	can	AUX
cana-2493	78	13	be	be	AUX
cana-2493	78	14	labor	labor	NOUN
cana-2493	78	15	-	-	PUNCT
cana-2493	78	16	intensive	intensive	ADJ
cana-2493	78	17	and	and	CCONJ
cana-2493	78	18	subject	subject	ADJ
cana-2493	78	19	to	to	ADP
cana-2493	78	20	inter	inter	ADJ
cana-2493	78	21	-	-	ADJ
cana-2493	78	22	rater	rater	ADJ
cana-2493	78	23	variability	variability	NOUN
cana-2493	78	24	.	.	PUNCT
cana-2493	79	1	our	our	PRON
cana-2493	79	2	deep	deep	ADJ
cana-2493	79	3	learning	learning	NOUN
cana-2493	79	4	framework	framework	NOUN
cana-2493	79	5	for	for	ADP
cana-2493	79	6	improved	improved	ADJ
cana-2493	79	7	lung	lung	NOUN
cana-2493	79	8	cancer	cancer	NOUN
cana-2493	79	9	identification	identification	NOUN
cana-2493	79	10	and	and	CCONJ
cana-2493	79	11	analysis	analysis	NOUN
cana-2493	79	12	presents	present	VERB
cana-2493	79	13	novel	novel	ADJ
cana-2493	79	14	segmentation	segmentation	NOUN
cana-2493	79	15	strategies	strategy	NOUN
cana-2493	79	16	and	and	CCONJ
cana-2493	79	17	data	datum	NOUN
cana-2493	79	18	augmentation	augmentation	NOUN
cana-2493	79	19	techniques	technique	NOUN
cana-2493	79	20	to	to	PART
cana-2493	79	21	surmount	surmount	VERB
cana-2493	79	22	current	current	ADJ
cana-2493	79	23	approaches	approach	NOUN
cana-2493	79	24	'	'	PART
cana-2493	79	25	limitations	limitation	NOUN
cana-2493	79	26	.	.	PUNCT
cana-2493	80	1	our	our	PRON
cana-2493	80	2	model	model	NOUN
cana-2493	80	3	fuses	fuse	VERB
cana-2493	80	4	convolutional	convolutional	ADJ
cana-2493	80	5	neural	neural	ADJ
cana-2493	80	6	networks	network	NOUN
cana-2493	80	7	with	with	ADP
cana-2493	80	8	multi	multi	ADJ
cana-2493	80	9	-	-	ADJ
cana-2493	80	10	scale	scale	ADJ
cana-2493	80	11	delineation	delineation	NOUN
cana-2493	80	12	and	and	CCONJ
cana-2493	80	13	diverse	diverse	ADJ
cana-2493	80	14	,	,	PUNCT
cana-2493	80	15	enhanced	enhanced	ADJ
cana-2493	80	16	training	training	NOUN
cana-2493	80	17	information	information	NOUN
cana-2493	80	18	.	.	PUNCT
cana-2493	81	1	key	key	ADJ
cana-2493	81	2	model	model	NOUN
cana-2493	81	3	facets	facet	NOUN
cana-2493	81	4	encompass	encompass	VERB
cana-2493	81	5	a	a	DET
cana-2493	81	6	cnn	cnn	NOUN
cana-2493	81	7	backbone	backbone	NOUN
cana-2493	81	8	extracting	extract	VERB
cana-2493	81	9	attributes	attribute	NOUN
cana-2493	81	10	,	,	PUNCT
cana-2493	81	11	a	a	DET
cana-2493	81	12	multi	multi	ADJ
cana-2493	81	13	-	-	ADJ
cana-2493	81	14	level	level	ADJ
cana-2493	81	15	segmentation	segmentation	NOUN
cana-2493	81	16	module	module	NOUN
cana-2493	81	17	capturing	capture	VERB
cana-2493	81	18	characteristics	characteristic	NOUN
cana-2493	81	19	at	at	ADP
cana-2493	81	20	varying	vary	VERB
cana-2493	81	21	magnitudes	magnitude	NOUN
cana-2493	81	22	,	,	PUNCT
cana-2493	81	23	and	and	CCONJ
cana-2493	81	24	an	an	DET
cana-2493	81	25	augmentation	augmentation	NOUN
cana-2493	81	26	pipeline	pipeline	NOUN
cana-2493	81	27	cultivating	cultivate	VERB
cana-2493	81	28	training	training	NOUN
cana-2493	81	29	data	datum	NOUN
cana-2493	81	30	's	's	PART
cana-2493	81	31	variety	variety	NOUN
cana-2493	81	32	and	and	CCONJ
cana-2493	81	33	quality[13	quality[13	NOUN
cana-2493	81	34	]	]	PUNCT
cana-2493	81	35	.	.	PUNCT
cana-2493	82	1	data	datum	NOUN
cana-2493	82	2	augmentation	augmentation	NOUN
cana-2493	82	3	proves	prove	VERB
cana-2493	82	4	pivotal	pivotal	ADJ
cana-2493	82	5	for	for	ADP
cana-2493	82	6	training	train	VERB
cana-2493	82	7	deep	deep	ADJ
cana-2493	82	8	models	model	NOUN
cana-2493	82	9	on	on	ADP
cana-2493	82	10	scarce	scarce	ADJ
cana-2493	82	11	,	,	PUNCT
cana-2493	82	12	annotated	annotate	VERB
cana-2493	82	13	medical	medical	ADJ
cana-2493	82	14	images	image	NOUN
cana-2493	82	15	.	.	PUNCT
cana-2493	83	1	here	here	ADV
cana-2493	83	2	,	,	PUNCT
cana-2493	83	3	rotations	rotation	NOUN
cana-2493	83	4	,	,	PUNCT
cana-2493	83	5	translations	translation	NOUN
cana-2493	83	6	,	,	PUNCT
cana-2493	83	7	scaling	scaling	NOUN
cana-2493	83	8	and	and	CCONJ
cana-2493	83	9	intensity	intensity	NOUN
cana-2493	83	10	shifts	shift	NOUN
cana-2493	83	11	simulate	simulate	VERB
cana-2493	83	12	diverse	diverse	ADJ
cana-2493	83	13	imaging	imaging	NOUN
cana-2493	83	14	states	state	NOUN
cana-2493	83	15	,	,	PUNCT
cana-2493	83	16	better	well	ADV
cana-2493	83	17	generalizing	generalize	VERB
cana-2493	83	18	the	the	DET
cana-2493	83	19	model	model	NOUN
cana-2493	83	20	to	to	PART
cana-2493	83	21	handle	handle	VERB
cana-2493	83	22	quality	quality	NOUN
cana-2493	83	23	deviations	deviation	NOUN
cana-2493	83	24	and	and	CCONJ
cana-2493	83	25	perform	perform	VERB
cana-2493	83	26	accurately	accurately	ADV
cana-2493	83	27	on	on	ADP
cana-2493	83	28	novel	novel	ADJ
cana-2493	83	29	data	datum	NOUN
cana-2493	83	30	.	.	PUNCT
cana-2493	84	1	the	the	DET
cana-2493	84	2	multi	multi	ADJ
cana-2493	84	3	-	-	ADJ
cana-2493	84	4	scale	scale	ADJ
cana-2493	84	5	segmentation	segmentation	NOUN
cana-2493	84	6	module	module	NOUN
cana-2493	84	7	enables	enable	VERB
cana-2493	84	8	processing	process	VERB
cana-2493	84	9	at	at	ADP
cana-2493	84	10	different	different	ADJ
cana-2493	84	11	scales	scale	NOUN
cana-2493	84	12	,	,	PUNCT
cana-2493	84	13	detecting	detect	VERB
cana-2493	84	14	small	small	ADJ
cana-2493	84	15	and	and	CCONJ
cana-2493	84	16	large	large	ADJ
cana-2493	84	17	lesions	lesion	NOUN
cana-2493	84	18	.	.	PUNCT
cana-2493	85	1	multiple	multiple	ADJ
cana-2493	85	2	extraction	extraction	NOUN
cana-2493	85	3	levels	level	NOUN
cana-2493	85	4	focus	focus	VERB
cana-2493	85	5	on	on	ADP
cana-2493	85	6	fine	fine	ADJ
cana-2493	85	7	subtleties	subtlety	NOUN
cana-2493	85	8	like	like	ADP
cana-2493	85	9	miniscule	miniscule	ADJ
cana-2493	85	10	nodules	nodule	NOUN
cana-2493	85	11	as	as	ADV
cana-2493	85	12	well	well	ADV
cana-2493	85	13	as	as	ADP
cana-2493	85	14	broader	broad	ADJ
cana-2493	85	15	configurations	configuration	NOUN
cana-2493	85	16	such	such	ADJ
cana-2493	85	17	as	as	ADP
cana-2493	85	18	growths	growth	NOUN
cana-2493	85	19	,	,	PUNCT
cana-2493	85	20	providing	provide	VERB
cana-2493	85	21	sharper	sharp	ADJ
cana-2493	85	22	segmentation	segmentation	NOUN
cana-2493	85	23	.	.	PUNCT
cana-2493	86	1	integrating	integrate	VERB
cana-2493	86	2	these	these	DET
cana-2493	86	3	methods	method	NOUN
cana-2493	86	4	outflanks	outflank	NOUN
cana-2493	86	5	prior	prior	ADV
cana-2493	86	6	techniques	technique	NOUN
cana-2493	86	7	frequently	frequently	ADV
cana-2493	86	8	struggling	struggle	VERB
cana-2493	86	9	with	with	ADP
cana-2493	86	10	noisy	noisy	ADJ
cana-2493	86	11	or	or	CCONJ
cana-2493	86	12	low	low	ADJ
cana-2493	86	13	-	-	PUNCT
cana-2493	86	14	resolution	resolution	NOUN
cana-2493	86	15	pictures	picture	NOUN
cana-2493	86	16	absent	absent	VERB
cana-2493	86	17	a	a	DET
cana-2493	86	18	wide	wide	ADJ
cana-2493	86	19	lesion	lesion	NOUN
cana-2493	86	20	spectrum	spectrum	NOUN
cana-2493	86	21	's	's	PART
cana-2493	86	22	depiction	depiction	NOUN
cana-2493	86	23	and	and	CCONJ
cana-2493	86	24	locations	location	NOUN
cana-2493	86	25	.	.	PUNCT
cana-2493	87	1	communications	communication	NOUN
cana-2493	87	2	on	on	ADP
cana-2493	87	3	applied	apply	VERB
cana-2493	87	4	nonlinear	nonlinear	ADJ
cana-2493	87	5	analysis	analysis	NOUN
cana-2493	87	6	issn	issn	NOUN
cana-2493	87	7	:	:	PUNCT
cana-2493	87	8	1074	1074	NUM
cana-2493	87	9	-	-	PUNCT
cana-2493	87	10	133x	133x	NUM
cana-2493	87	11	vol	vol	NOUN
cana-2493	87	12	32	32	NUM
cana-2493	87	13	no	no	NOUN
cana-2493	87	14	.	.	PUNCT
cana-2493	88	1	2s	2s	NUM
cana-2493	88	2	(	(	PUNCT
cana-2493	88	3	2025	2025	NUM
cana-2493	88	4	)	)	PUNCT
cana-2493	88	5	549	549	NUM
cana-2493	88	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	88	7	1	1	NUM
cana-2493	88	8	.	.	PUNCT
cana-2493	88	9	related	relate	VERB
cana-2493	88	10	work	work	NOUN
cana-2493	88	11	for	for	ADP
cana-2493	88	12	many	many	ADJ
cana-2493	88	13	years	year	NOUN
cana-2493	88	14	now	now	ADV
cana-2493	88	15	,	,	PUNCT
cana-2493	88	16	lung	lung	NOUN
cana-2493	88	17	cancer	cancer	NOUN
cana-2493	88	18	detection	detection	NOUN
cana-2493	88	19	and	and	CCONJ
cana-2493	88	20	segmentation	segmentation	NOUN
cana-2493	88	21	using	use	VERB
cana-2493	88	22	deep	deep	ADJ
cana-2493	88	23	learning	learning	NOUN
cana-2493	88	24	techniques	technique	NOUN
cana-2493	88	25	have	have	AUX
cana-2493	88	26	increasingly	increasingly	ADV
cana-2493	88	27	become	become	VERB
cana-2493	88	28	major	major	ADJ
cana-2493	88	29	areas	area	NOUN
cana-2493	88	30	of	of	ADP
cana-2493	88	31	focus	focus	NOUN
cana-2493	88	32	in	in	ADP
cana-2493	88	33	the	the	DET
cana-2493	88	34	medical	medical	ADJ
cana-2493	88	35	community	community	NOUN
cana-2493	88	36	due	due	ADP
cana-2493	88	37	to	to	ADP
cana-2493	88	38	their	their	PRON
cana-2493	88	39	prospect	prospect	NOUN
cana-2493	88	40	of	of	ADP
cana-2493	88	41	considerably	considerably	ADV
cana-2493	88	42	enhancing	enhance	VERB
cana-2493	88	43	the	the	DET
cana-2493	88	44	accuracy	accuracy	NOUN
cana-2493	88	45	and	and	CCONJ
cana-2493	88	46	efficiency	efficiency	NOUN
cana-2493	88	47	of	of	ADP
cana-2493	88	48	diagnostic	diagnostic	ADJ
cana-2493	88	49	processes	process	NOUN
cana-2493	88	50	.	.	PUNCT
cana-2493	89	1	this	this	DET
cana-2493	89	2	section	section	NOUN
cana-2493	89	3	aims	aim	VERB
cana-2493	89	4	to	to	PART
cana-2493	89	5	summarize	summarize	VERB
cana-2493	89	6	the	the	DET
cana-2493	89	7	various	various	ADJ
cana-2493	89	8	methodologies	methodology	NOUN
cana-2493	89	9	that	that	PRON
cana-2493	89	10	have	have	AUX
cana-2493	89	11	been	be	AUX
cana-2493	89	12	employed	employ	VERB
cana-2493	89	13	for	for	ADP
cana-2493	89	14	lung	lung	NOUN
cana-2493	89	15	cancer	cancer	NOUN
cana-2493	89	16	detection	detection	NOUN
cana-2493	89	17	,	,	PUNCT
cana-2493	89	18	specifically	specifically	ADV
cana-2493	89	19	concentrating	concentrate	VERB
cana-2493	89	20	on	on	ADP
cana-2493	89	21	deep	deep	ADJ
cana-2493	89	22	learning	learning	NOUN
cana-2493	89	23	strategies	strategy	NOUN
cana-2493	89	24	for	for	ADP
cana-2493	89	25	image	image	NOUN
cana-2493	89	26	classification	classification	NOUN
cana-2493	89	27	,	,	PUNCT
cana-2493	89	28	localization	localization	NOUN
cana-2493	89	29	,	,	PUNCT
cana-2493	89	30	and	and	CCONJ
cana-2493	89	31	segmentation[12	segmentation[12	PROPN
cana-2493	89	32	]	]	X
cana-2493	89	33	.	.	PUNCT
cana-2493	90	1	the	the	DET
cana-2493	90	2	field	field	NOUN
cana-2493	90	3	has	have	AUX
cana-2493	90	4	advanced	advance	VERB
cana-2493	90	5	from	from	ADP
cana-2493	90	6	conventional	conventional	ADJ
cana-2493	90	7	image	image	NOUN
cana-2493	90	8	analysis	analysis	NOUN
cana-2493	90	9	methods	method	NOUN
cana-2493	90	10	to	to	ADP
cana-2493	90	11	sophisticated	sophisticated	ADJ
cana-2493	90	12	neural	neural	ADJ
cana-2493	90	13	network	network	NOUN
cana-2493	90	14	models	model	NOUN
cana-2493	90	15	,	,	PUNCT
cana-2493	90	16	notably	notably	ADV
cana-2493	90	17	convolutional	convolutional	ADJ
cana-2493	90	18	neural	neural	ADJ
cana-2493	90	19	networks	network	NOUN
cana-2493	90	20	(	(	PUNCT
cana-2493	90	21	cnns	cnns	PROPN
cana-2493	90	22	)	)	PUNCT
cana-2493	90	23	,	,	PUNCT
cana-2493	90	24	which	which	PRON
cana-2493	90	25	have	have	AUX
cana-2493	90	26	demonstrated	demonstrate	VERB
cana-2493	90	27	massive	massive	ADJ
cana-2493	90	28	improvements	improvement	NOUN
cana-2493	90	29	for	for	ADP
cana-2493	90	30	medical	medical	ADJ
cana-2493	90	31	image	image	NOUN
cana-2493	90	32	interpretation	interpretation	NOUN
cana-2493	90	33	tasks	task	NOUN
cana-2493	90	34	.	.	PUNCT
cana-2493	91	1	in	in	ADP
cana-2493	91	2	the	the	DET
cana-2493	91	3	past	past	NOUN
cana-2493	91	4	,	,	PUNCT
cana-2493	91	5	the	the	DET
cana-2493	91	6	predominant	predominant	ADJ
cana-2493	91	7	lung	lung	NOUN
cana-2493	91	8	cancer	cancer	NOUN
cana-2493	91	9	detection	detection	NOUN
cana-2493	91	10	approaches	approach	VERB
cana-2493	91	11	heavily	heavily	ADV
cana-2493	91	12	relied	rely	VERB
cana-2493	91	13	on	on	ADP
cana-2493	91	14	hand	hand	NOUN
cana-2493	91	15	-	-	PUNCT
cana-2493	91	16	designed	design	VERB
cana-2493	91	17	features	feature	NOUN
cana-2493	91	18	and	and	CCONJ
cana-2493	91	19	classical	classical	ADJ
cana-2493	91	20	machine	machine	NOUN
cana-2493	91	21	learning	learn	VERB
cana-2493	91	22	algorithms	algorithm	NOUN
cana-2493	91	23	.	.	PUNCT
cana-2493	92	1	such	such	ADJ
cana-2493	92	2	strategies	strategy	NOUN
cana-2493	92	3	involved	involve	VERB
cana-2493	92	4	extracting	extract	VERB
cana-2493	92	5	specific	specific	ADJ
cana-2493	92	6	characteristics	characteristic	NOUN
cana-2493	92	7	from	from	ADP
cana-2493	92	8	healthcare	healthcare	NOUN
cana-2493	92	9	images	image	NOUN
cana-2493	92	10	,	,	PUNCT
cana-2493	92	11	such	such	ADJ
cana-2493	92	12	as	as	ADP
cana-2493	92	13	texture	texture	ADJ
cana-2493	92	14	,	,	PUNCT
cana-2493	92	15	form	form	NOUN
cana-2493	92	16	,	,	PUNCT
cana-2493	92	17	and	and	CCONJ
cana-2493	92	18	boundary	boundary	ADJ
cana-2493	92	19	information	information	NOUN
cana-2493	92	20	,	,	PUNCT
cana-2493	92	21	then	then	ADV
cana-2493	92	22	employing	employ	VERB
cana-2493	92	23	machine	machine	NOUN
cana-2493	92	24	learning	learn	VERB
cana-2493	92	25	classifiers	classifier	NOUN
cana-2493	92	26	like	like	ADP
cana-2493	92	27	support	support	NOUN
cana-2493	92	28	vector	vector	NOUN
cana-2493	92	29	machines	machine	NOUN
cana-2493	92	30	(	(	PUNCT
cana-2493	92	31	svms	svms	NOUN
cana-2493	92	32	)	)	PUNCT
cana-2493	92	33	or	or	CCONJ
cana-2493	92	34	decision	decision	NOUN
cana-2493	92	35	trees	tree	NOUN
cana-2493	92	36	.	.	PUNCT
cana-2493	93	1	while	while	SCONJ
cana-2493	93	2	achieving	achieve	VERB
cana-2493	93	3	some	some	DET
cana-2493	93	4	accomplishment	accomplishment	NOUN
cana-2493	93	5	,	,	PUNCT
cana-2493	93	6	these	these	PRON
cana-2493	93	7	were	be	AUX
cana-2493	93	8	confined	confine	VERB
cana-2493	93	9	by	by	ADP
cana-2493	93	10	their	their	PRON
cana-2493	93	11	dependence	dependence	NOUN
cana-2493	93	12	on	on	ADP
cana-2493	93	13	domain	domain	NOUN
cana-2493	93	14	-	-	PUNCT
cana-2493	93	15	specific	specific	ADJ
cana-2493	93	16	feature	feature	NOUN
cana-2493	93	17	extraction	extraction	NOUN
cana-2493	93	18	and	and	CCONJ
cana-2493	93	19	were	be	AUX
cana-2493	93	20	less	less	ADV
cana-2493	93	21	adaptive	adaptive	ADJ
cana-2493	93	22	to	to	ADP
cana-2493	93	23	the	the	DET
cana-2493	93	24	intricacy	intricacy	NOUN
cana-2493	93	25	and	and	CCONJ
cana-2493	93	26	variability	variability	NOUN
cana-2493	93	27	within	within	ADP
cana-2493	93	28	medical	medical	ADJ
cana-2493	93	29	images	image	NOUN
cana-2493	93	30	.	.	PUNCT
cana-2493	94	1	what	what	PRON
cana-2493	94	2	's	be	AUX
cana-2493	94	3	more	more	ADJ
cana-2493	94	4	,	,	PUNCT
cana-2493	94	5	they	they	PRON
cana-2493	94	6	regularly	regularly	ADV
cana-2493	94	7	necessitated	necessitate	VERB
cana-2493	94	8	expert	expert	NOUN
cana-2493	94	9	understanding	understanding	NOUN
cana-2493	94	10	to	to	PART
cana-2493	94	11	consciously	consciously	ADV
cana-2493	94	12	identify	identify	VERB
cana-2493	94	13	and	and	CCONJ
cana-2493	94	14	extract	extract	VERB
cana-2493	94	15	pertinent	pertinent	ADJ
cana-2493	94	16	features	feature	NOUN
cana-2493	94	17	,	,	PUNCT
cana-2493	94	18	a	a	DET
cana-2493	94	19	tedious	tedious	ADJ
cana-2493	94	20	and	and	CCONJ
cana-2493	94	21	error	error	NOUN
cana-2493	94	22	-	-	PUNCT
cana-2493	94	23	prone	prone	ADJ
cana-2493	94	24	process	process	NOUN
cana-2493	94	25	.	.	PUNCT
cana-2493	95	1	the	the	DET
cana-2493	95	2	emergence	emergence	NOUN
cana-2493	95	3	of	of	ADP
cana-2493	95	4	deep	deep	ADJ
cana-2493	95	5	learning	learning	NOUN
cana-2493	95	6	,	,	PUNCT
cana-2493	95	7	notably	notably	ADV
cana-2493	95	8	cnns	cnns	ADJ
cana-2493	95	9	,	,	PUNCT
cana-2493	95	10	ushered	usher	VERB
cana-2493	95	11	in	in	ADP
cana-2493	95	12	a	a	DET
cana-2493	95	13	change	change	NOUN
cana-2493	95	14	of	of	ADP
cana-2493	95	15	perspective	perspective	NOUN
cana-2493	95	16	in	in	ADP
cana-2493	95	17	how	how	SCONJ
cana-2493	95	18	lung	lung	NOUN
cana-2493	95	19	cancer	cancer	NOUN
cana-2493	95	20	detection	detection	NOUN
cana-2493	95	21	and	and	CCONJ
cana-2493	95	22	segmentation	segmentation	NOUN
cana-2493	95	23	challenges	challenge	NOUN
cana-2493	95	24	were	be	AUX
cana-2493	95	25	tackled	tackle	VERB
cana-2493	95	26	.	.	PUNCT
cana-2493	96	1	cnns	cnns	PROPN
cana-2493	96	2	automate	automate	VERB
cana-2493	96	3	the	the	DET
cana-2493	96	4	feature	feature	NOUN
cana-2493	96	5	extraction	extraction	NOUN
cana-2493	96	6	process	process	NOUN
cana-2493	96	7	by	by	ADP
cana-2493	96	8	learning	learn	VERB
cana-2493	96	9	hierarchical	hierarchical	ADJ
cana-2493	96	10	representations	representation	NOUN
cana-2493	96	11	of	of	ADP
cana-2493	96	12	raw	raw	ADJ
cana-2493	96	13	image	image	NOUN
cana-2493	96	14	information	information	NOUN
cana-2493	96	15	.	.	PUNCT
cana-2493	97	1	initial	initial	ADJ
cana-2493	97	2	research	research	NOUN
cana-2493	97	3	showcased	showcase	VERB
cana-2493	97	4	the	the	DET
cana-2493	97	5	prospective	prospective	ADJ
cana-2493	97	6	of	of	ADP
cana-2493	97	7	cnns	cnn	NOUN
cana-2493	97	8	for	for	ADP
cana-2493	97	9	finding	find	VERB
cana-2493	97	10	lung	lung	NOUN
cana-2493	97	11	nodules	nodule	NOUN
cana-2493	97	12	and	and	CCONJ
cana-2493	97	13	categorizing	categorize	VERB
cana-2493	97	14	them	they	PRON
cana-2493	97	15	as	as	ADV
cana-2493	97	16	malignant	malignant	ADJ
cana-2493	97	17	or	or	CCONJ
cana-2493	97	18	benign[1	benign[1	NUM
cana-2493	97	19	]	]	X
cana-2493	97	20	.	.	PUNCT
cana-2493	98	1	these	these	DET
cana-2493	98	2	models	model	NOUN
cana-2493	98	3	were	be	AUX
cana-2493	98	4	generally	generally	ADV
cana-2493	98	5	educated	educate	VERB
cana-2493	98	6	on	on	ADP
cana-2493	98	7	substantial	substantial	ADJ
cana-2493	98	8	datasets	dataset	NOUN
cana-2493	98	9	of	of	ADP
cana-2493	98	10	annotated	annotate	VERB
cana-2493	98	11	images	image	NOUN
cana-2493	98	12	and	and	CCONJ
cana-2493	98	13	were	be	AUX
cana-2493	98	14	demonstrated	demonstrate	VERB
cana-2493	98	15	to	to	PART
cana-2493	98	16	outperform	outperform	VERB
cana-2493	98	17	conventional	conventional	ADJ
cana-2493	98	18	machine	machine	NOUN
cana-2493	98	19	learning	learn	VERB
cana-2493	98	20	algorithms	algorithm	NOUN
cana-2493	98	21	regarding	regard	VERB
cana-2493	98	22	accuracy	accuracy	NOUN
cana-2493	98	23	and	and	CCONJ
cana-2493	98	24	robustness	robustness	NOUN
cana-2493	98	25	.	.	PUNCT
cana-2493	99	1	in	in	ADP
cana-2493	99	2	any	any	DET
cana-2493	99	3	case	case	NOUN
cana-2493	99	4	,	,	PUNCT
cana-2493	99	5	early	early	ADJ
cana-2493	99	6	cnn	cnn	PROPN
cana-2493	99	7	models	model	NOUN
cana-2493	99	8	for	for	ADP
cana-2493	99	9	lung	lung	NOUN
cana-2493	99	10	cancer	cancer	NOUN
cana-2493	99	11	detection	detection	NOUN
cana-2493	99	12	were	be	AUX
cana-2493	99	13	usually	usually	ADV
cana-2493	99	14	restricted	restrict	VERB
cana-2493	99	15	to	to	ADP
cana-2493	99	16	binary	binary	ADJ
cana-2493	99	17	classification	classification	NOUN
cana-2493	99	18	tasks	task	NOUN
cana-2493	99	19	and	and	CCONJ
cana-2493	99	20	lacked	lack	VERB
cana-2493	99	21	the	the	DET
cana-2493	99	22	ability	ability	NOUN
cana-2493	99	23	to	to	PART
cana-2493	99	24	finely	finely	ADV
cana-2493	99	25	segment	segment	VERB
cana-2493	99	26	cancerous	cancerous	ADJ
cana-2493	99	27	regions	region	NOUN
cana-2493	99	28	.	.	PUNCT
cana-2493	100	1	as	as	SCONJ
cana-2493	100	2	research	research	NOUN
cana-2493	100	3	into	into	ADP
cana-2493	100	4	cnns	cnns	PROPN
cana-2493	100	5	expanded	expand	VERB
cana-2493	100	6	,	,	PUNCT
cana-2493	100	7	scientists	scientist	NOUN
cana-2493	100	8	started	start	VERB
cana-2493	100	9	exploring	explore	VERB
cana-2493	100	10	their	their	PRON
cana-2493	100	11	use	use	NOUN
cana-2493	100	12	not	not	PART
cana-2493	100	13	only	only	ADV
cana-2493	100	14	for	for	ADP
cana-2493	100	15	classifying	classify	VERB
cana-2493	100	16	images	image	NOUN
cana-2493	100	17	but	but	CCONJ
cana-2493	100	18	also	also	ADV
cana-2493	100	19	segmenting	segment	VERB
cana-2493	100	20	them	they	PRON
cana-2493	100	21	,	,	PUNCT
cana-2493	100	22	a	a	DET
cana-2493	100	23	process	process	NOUN
cana-2493	100	24	of	of	ADP
cana-2493	100	25	outlining	outline	VERB
cana-2493	100	26	cancerous	cancerous	ADJ
cana-2493	100	27	regions	region	NOUN
cana-2493	100	28	in	in	ADP
cana-2493	100	29	medical	medical	ADJ
cana-2493	100	30	photographs	photograph	NOUN
cana-2493	100	31	.	.	PUNCT
cana-2493	101	1	segmentation	segmentation	NOUN
cana-2493	101	2	plays	play	VERB
cana-2493	101	3	a	a	DET
cana-2493	101	4	pivotal	pivotal	ADJ
cana-2493	101	5	role	role	NOUN
cana-2493	101	6	in	in	ADP
cana-2493	101	7	lung	lung	NOUN
cana-2493	101	8	cancer	cancer	NOUN
cana-2493	101	9	diagnoses	diagnosis	NOUN
cana-2493	101	10	since	since	SCONJ
cana-2493	101	11	delineating	delineate	VERB
cana-2493	101	12	tumor	tumor	NOUN
cana-2493	101	13	sizes	size	NOUN
cana-2493	101	14	,	,	PUNCT
cana-2493	101	15	shapes	shape	NOUN
cana-2493	101	16	,	,	PUNCT
cana-2493	101	17	and	and	CCONJ
cana-2493	101	18	areas	area	NOUN
cana-2493	101	19	aids	aid	VERB
cana-2493	101	20	clinicians	clinician	NOUN
cana-2493	101	21	in	in	ADP
cana-2493	101	22	treatment	treatment	NOUN
cana-2493	101	23	planning	planning	NOUN
cana-2493	101	24	and	and	CCONJ
cana-2493	101	25	staging	staging	NOUN
cana-2493	101	26	,	,	PUNCT
cana-2493	101	27	crucial	crucial	ADJ
cana-2493	101	28	steps	step	NOUN
cana-2493	101	29	for	for	ADP
cana-2493	101	30	care	care	NOUN
cana-2493	101	31	.	.	PUNCT
cana-2493	102	1	one	one	NUM
cana-2493	102	2	especially	especially	ADV
cana-2493	102	3	notable	notable	ADJ
cana-2493	102	4	deep	deep	ADJ
cana-2493	102	5	learning	learning	NOUN
cana-2493	102	6	model	model	NOUN
cana-2493	102	7	for	for	ADP
cana-2493	102	8	segmentation	segmentation	NOUN
cana-2493	102	9	is	be	AUX
cana-2493	102	10	u	u	NOUN
cana-2493	102	11	-	-	NOUN
cana-2493	102	12	net	net	ADJ
cana-2493	102	13	,	,	PUNCT
cana-2493	102	14	invented	invent	VERB
cana-2493	102	15	for	for	ADP
cana-2493	102	16	biomedical	biomedical	ADJ
cana-2493	102	17	image	image	NOUN
cana-2493	102	18	delineation	delineation	NOUN
cana-2493	102	19	.	.	PUNCT
cana-2493	103	1	the	the	DET
cana-2493	103	2	u	u	ADJ
cana-2493	103	3	-	-	ADJ
cana-2493	103	4	net	net	ADJ
cana-2493	103	5	architecture	architecture	NOUN
cana-2493	103	6	has	have	VERB
cana-2493	103	7	an	an	DET
cana-2493	103	8	encoder	encoder	NOUN
cana-2493	103	9	-	-	PUNCT
cana-2493	103	10	decoder	decoder	NOUN
cana-2493	103	11	structure	structure	NOUN
cana-2493	103	12	capturing	capture	VERB
cana-2493	103	13	both	both	CCONJ
cana-2493	103	14	high	high	ADJ
cana-2493	103	15	-	-	PUNCT
cana-2493	103	16	level	level	NOUN
cana-2493	103	17	and	and	CCONJ
cana-2493	103	18	low	low	ADJ
cana-2493	103	19	-	-	PUNCT
cana-2493	103	20	level	level	NOUN
cana-2493	103	21	qualities	quality	NOUN
cana-2493	103	22	,	,	PUNCT
cana-2493	103	23	suiting	suit	VERB
cana-2493	103	24	it	it	PRON
cana-2493	103	25	well	well	ADV
cana-2493	103	26	for	for	ADP
cana-2493	103	27	parsing	parse	VERB
cana-2493	103	28	anatomical	anatomical	ADJ
cana-2493	103	29	features	feature	NOUN
cana-2493	103	30	in	in	ADP
cana-2493	103	31	medical	medical	ADJ
cana-2493	103	32	snapshots[6][7	snapshots[6][7	PROPN
cana-2493	103	33	]	]	PUNCT
cana-2493	103	34	.	.	PUNCT
cana-2493	104	1	oncologists	oncologist	NOUN
cana-2493	104	2	have	have	AUX
cana-2493	104	3	widely	widely	ADV
cana-2493	104	4	adopted	adopt	VERB
cana-2493	104	5	this	this	DET
cana-2493	104	6	design	design	NOUN
cana-2493	104	7	for	for	ADP
cana-2493	104	8	lung	lung	NOUN
cana-2493	104	9	cancer	cancer	NOUN
cana-2493	104	10	segmentation	segmentation	NOUN
cana-2493	104	11	given	give	VERB
cana-2493	104	12	its	its	PRON
cana-2493	104	13	capacity	capacity	NOUN
cana-2493	104	14	for	for	ADP
cana-2493	104	15	precisely	precisely	ADV
cana-2493	104	16	defining	define	VERB
cana-2493	104	17	cancerous	cancerous	ADJ
cana-2493	104	18	territories	territory	NOUN
cana-2493	104	19	even	even	ADV
cana-2493	104	20	amidst	amidst	ADP
cana-2493	104	21	noise	noise	NOUN
cana-2493	104	22	and	and	CCONJ
cana-2493	104	23	defects	defect	NOUN
cana-2493	104	24	.	.	PUNCT
cana-2493	105	1	however	however	ADV
cana-2493	105	2	,	,	PUNCT
cana-2493	105	3	hurdles	hurdle	NOUN
cana-2493	105	4	remain	remain	VERB
cana-2493	105	5	in	in	ADP
cana-2493	105	6	achieving	achieve	VERB
cana-2493	105	7	strong	strong	ADJ
cana-2493	105	8	performance	performance	NOUN
cana-2493	105	9	across	across	ADP
cana-2493	105	10	diverse	diverse	ADJ
cana-2493	105	11	datasets	dataset	NOUN
cana-2493	105	12	.	.	PUNCT
cana-2493	106	1	photographs	photograph	NOUN
cana-2493	106	2	used	use	VERB
cana-2493	106	3	for	for	ADP
cana-2493	106	4	lung	lung	NOUN
cana-2493	106	5	cancer	cancer	NOUN
cana-2493	106	6	detection	detection	NOUN
cana-2493	106	7	,	,	PUNCT
cana-2493	106	8	especially	especially	ADV
cana-2493	106	9	,	,	PUNCT
cana-2493	106	10	often	often	ADV
cana-2493	106	11	contain	contain	VERB
cana-2493	106	12	distortions	distortion	NOUN
cana-2493	106	13	and	and	CCONJ
cana-2493	106	14	exhibit	exhibit	VERB
cana-2493	106	15	variability	variability	NOUN
cana-2493	106	16	in	in	ADP
cana-2493	106	17	resolution	resolution	NOUN
cana-2493	106	18	,	,	PUNCT
cana-2493	106	19	contrast	contrast	NOUN
cana-2493	106	20	,	,	PUNCT
cana-2493	106	21	and	and	CCONJ
cana-2493	106	22	illumination	illumination	NOUN
cana-2493	106	23	.	.	PUNCT
cana-2493	107	1	such	such	ADJ
cana-2493	107	2	inconsistencies	inconsistency	NOUN
cana-2493	107	3	can	can	AUX
cana-2493	107	4	decrease	decrease	VERB
cana-2493	107	5	how	how	SCONJ
cana-2493	107	6	well	well	ADV
cana-2493	107	7	deep	deep	ADJ
cana-2493	107	8	learning	learning	NOUN
cana-2493	107	9	models	model	NOUN
cana-2493	107	10	perform	perform	VERB
cana-2493	107	11	since	since	SCONJ
cana-2493	107	12	they	they	PRON
cana-2493	107	13	are	be	AUX
cana-2493	107	14	highly	highly	ADV
cana-2493	107	15	sensitive	sensitive	ADJ
cana-2493	107	16	to	to	ADP
cana-2493	107	17	input	input	NOUN
cana-2493	107	18	picture	picture	NOUN
cana-2493	107	19	quality	quality	NOUN
cana-2493	107	20	.	.	PUNCT
cana-2493	108	1	to	to	PART
cana-2493	108	2	address	address	VERB
cana-2493	108	3	these	these	DET
cana-2493	108	4	challenges	challenge	NOUN
cana-2493	108	5	,	,	PUNCT
cana-2493	108	6	data	datum	NOUN
cana-2493	108	7	augmentation	augmentation	NOUN
cana-2493	108	8	techniques	technique	NOUN
cana-2493	108	9	have	have	AUX
cana-2493	108	10	emerged	emerge	VERB
cana-2493	108	11	as	as	ADP
cana-2493	108	12	a	a	DET
cana-2493	108	13	means	means	NOUN
cana-2493	108	14	of	of	ADP
cana-2493	108	15	synthetically	synthetically	ADV
cana-2493	108	16	increasing	increase	VERB
cana-2493	108	17	training	training	NOUN
cana-2493	108	18	information	information	NOUN
cana-2493	108	19	diversity[8][9	diversity[8][9	PROPN
cana-2493	108	20	]	]	PUNCT
cana-2493	108	21	.	.	PUNCT
cana-2493	109	1	by	by	ADP
cana-2493	109	2	applying	apply	VERB
cana-2493	109	3	rotations	rotation	NOUN
cana-2493	109	4	,	,	PUNCT
cana-2493	109	5	resizing	resizing	NOUN
cana-2493	109	6	,	,	PUNCT
cana-2493	109	7	and	and	CCONJ
cana-2493	109	8	flipping	flip	VERB
cana-2493	109	9	transformations	transformation	NOUN
cana-2493	109	10	to	to	ADP
cana-2493	109	11	education	education	NOUN
cana-2493	109	12	images	image	NOUN
cana-2493	109	13	,	,	PUNCT
cana-2493	109	14	data	datum	NOUN
cana-2493	109	15	augmentation	augmentation	NOUN
cana-2493	109	16	communications	communication	NOUN
cana-2493	109	17	on	on	ADP
cana-2493	109	18	applied	apply	VERB
cana-2493	109	19	nonlinear	nonlinear	ADJ
cana-2493	109	20	analysis	analysis	NOUN
cana-2493	109	21	issn	issn	NOUN
cana-2493	109	22	:	:	PUNCT
cana-2493	109	23	1074	1074	NUM
cana-2493	109	24	-	-	PUNCT
cana-2493	109	25	133x	133x	NUM
cana-2493	109	26	vol	vol	NOUN
cana-2493	109	27	32	32	NUM
cana-2493	109	28	no	no	NOUN
cana-2493	109	29	.	.	PUNCT
cana-2493	110	1	2s	2s	NUM
cana-2493	110	2	(	(	PUNCT
cana-2493	110	3	2025	2025	NUM
cana-2493	110	4	)	)	PUNCT
cana-2493	110	5	550	550	NUM
cana-2493	110	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	110	7	helps	help	VERB
cana-2493	110	8	models	model	NOUN
cana-2493	110	9	generalize	generalize	VERB
cana-2493	110	10	better	well	ADV
cana-2493	110	11	to	to	ADP
cana-2493	110	12	new	new	ADJ
cana-2493	110	13	data	datum	NOUN
cana-2493	110	14	,	,	PUNCT
cana-2493	110	15	strengthening	strengthen	VERB
cana-2493	110	16	their	their	PRON
cana-2493	110	17	robustness	robustness	NOUN
cana-2493	110	18	and	and	CCONJ
cana-2493	110	19	abilities	ability	NOUN
cana-2493	110	20	on	on	ADP
cana-2493	110	21	real	real	ADJ
cana-2493	110	22	-	-	PUNCT
cana-2493	110	23	world	world	NOUN
cana-2493	110	24	clinical	clinical	ADJ
cana-2493	110	25	photographs	photograph	NOUN
cana-2493	110	26	.	.	PUNCT
cana-2493	111	1	in	in	ADP
cana-2493	111	2	addition	addition	NOUN
cana-2493	111	3	to	to	ADP
cana-2493	111	4	data	datum	NOUN
cana-2493	111	5	augmentation	augmentation	NOUN
cana-2493	111	6	,	,	PUNCT
cana-2493	111	7	other	other	ADJ
cana-2493	111	8	strategies	strategy	NOUN
cana-2493	111	9	have	have	AUX
cana-2493	111	10	been	be	AUX
cana-2493	111	11	employed	employ	VERB
cana-2493	111	12	to	to	PART
cana-2493	111	13	enhance	enhance	VERB
cana-2493	111	14	the	the	DET
cana-2493	111	15	performance	performance	NOUN
cana-2493	111	16	of	of	ADP
cana-2493	111	17	lung	lung	NOUN
cana-2493	111	18	cancer	cancer	NOUN
cana-2493	111	19	detection	detection	NOUN
cana-2493	111	20	and	and	CCONJ
cana-2493	111	21	segmentation	segmentation	NOUN
cana-2493	111	22	models	model	NOUN
cana-2493	111	23	.	.	PUNCT
cana-2493	112	1	multi	multi	ADJ
cana-2493	112	2	-	-	ADJ
cana-2493	112	3	scale	scale	ADJ
cana-2493	112	4	networks	network	NOUN
cana-2493	112	5	process	process	NOUN
cana-2493	112	6	images	image	NOUN
cana-2493	112	7	at	at	ADP
cana-2493	112	8	multiple	multiple	ADJ
cana-2493	112	9	resolutions	resolution	NOUN
cana-2493	112	10	,	,	PUNCT
cana-2493	112	11	allowing	allow	VERB
cana-2493	112	12	the	the	DET
cana-2493	112	13	model	model	NOUN
cana-2493	112	14	to	to	PART
cana-2493	112	15	capture	capture	VERB
cana-2493	112	16	fine	fine	ADV
cana-2493	112	17	-	-	PUNCT
cana-2493	112	18	grained	grain	VERB
cana-2493	112	19	features	feature	NOUN
cana-2493	112	20	as	as	ADV
cana-2493	112	21	well	well	ADV
cana-2493	112	22	as	as	ADP
cana-2493	112	23	broader	broad	ADJ
cana-2493	112	24	spatial	spatial	PROPN
cana-2493	112	25	data[24][25	data[24][25	PROPN
cana-2493	112	26	]	]	PUNCT
cana-2493	112	27	.	.	PUNCT
cana-2493	113	1	this	this	PRON
cana-2493	113	2	benefits	benefit	VERB
cana-2493	113	3	lung	lung	NOUN
cana-2493	113	4	cancer	cancer	NOUN
cana-2493	113	5	analysis	analysis	NOUN
cana-2493	113	6	immensely	immensely	ADV
cana-2493	113	7	,	,	PUNCT
cana-2493	113	8	as	as	SCONJ
cana-2493	113	9	lesions	lesion	NOUN
cana-2493	113	10	range	range	VERB
cana-2493	113	11	dramatically	dramatically	ADV
cana-2493	113	12	in	in	ADP
cana-2493	113	13	size	size	NOUN
cana-2493	113	14	.	.	PUNCT
cana-2493	114	1	models	model	NOUN
cana-2493	114	2	analyzing	analyze	VERB
cana-2493	114	3	images	image	NOUN
cana-2493	114	4	across	across	ADP
cana-2493	114	5	scales	scale	NOUN
cana-2493	114	6	can	can	AUX
cana-2493	114	7	spot	spot	VERB
cana-2493	114	8	both	both	DET
cana-2493	114	9	tiny	tiny	ADJ
cana-2493	114	10	nodules	nodule	NOUN
cana-2493	114	11	and	and	CCONJ
cana-2493	114	12	sizable	sizable	ADJ
cana-2493	114	13	masses	masse	NOUN
cana-2493	114	14	.	.	PUNCT
cana-2493	115	1	meanwhile	meanwhile	ADV
cana-2493	115	2	,	,	PUNCT
cana-2493	115	3	unified	unified	ADJ
cana-2493	115	4	frameworks	framework	NOUN
cana-2493	115	5	integrating	integrate	VERB
cana-2493	115	6	detection	detection	NOUN
cana-2493	115	7	and	and	CCONJ
cana-2493	115	8	segmentation	segmentation	NOUN
cana-2493	115	9	perform	perform	VERB
cana-2493	115	10	both	both	DET
cana-2493	115	11	tasks	task	NOUN
cana-2493	115	12	jointly	jointly	ADV
cana-2493	115	13	through	through	ADP
cana-2493	115	14	a	a	DET
cana-2493	115	15	single	single	ADJ
cana-2493	115	16	network	network	NOUN
cana-2493	115	17	.	.	PUNCT
cana-2493	116	1	previously	previously	ADV
cana-2493	116	2	,	,	PUNCT
cana-2493	116	3	detection	detection	NOUN
cana-2493	116	4	preceded	precede	VERB
cana-2493	116	5	segmentation	segmentation	NOUN
cana-2493	116	6	,	,	PUNCT
cana-2493	116	7	with	with	ADP
cana-2493	116	8	the	the	DET
cana-2493	116	9	detection	detection	NOUN
cana-2493	116	10	model	model	NOUN
cana-2493	116	11	finding	find	VERB
cana-2493	116	12	regions	region	NOUN
cana-2493	116	13	of	of	ADP
cana-2493	116	14	interest	interest	NOUN
cana-2493	116	15	that	that	PRON
cana-2493	116	16	the	the	DET
cana-2493	116	17	segmentation	segmentation	NOUN
cana-2493	116	18	model	model	NOUN
cana-2493	116	19	then	then	ADV
cana-2493	116	20	delineated	delineate	VERB
cana-2493	116	21	.	.	PUNCT
cana-2493	117	1	however	however	ADV
cana-2493	117	2	,	,	PUNCT
cana-2493	117	3	this	this	DET
cana-2493	117	4	sequential	sequential	ADJ
cana-2493	117	5	approach	approach	NOUN
cana-2493	117	6	risks	risk	VERB
cana-2493	117	7	inconsistencies	inconsistency	NOUN
cana-2493	117	8	,	,	PUNCT
cana-2493	117	9	especially	especially	ADV
cana-2493	117	10	around	around	ADP
cana-2493	117	11	blurry	blurry	NOUN
cana-2493	118	1	borders[10	borders[10	ADV
cana-2493	118	2	]	]	PUNCT
cana-2493	118	3	.	.	PUNCT
cana-2493	119	1	a	a	DET
cana-2493	119	2	unified	unified	ADJ
cana-2493	119	3	architecture	architecture	NOUN
cana-2493	119	4	jointly	jointly	ADV
cana-2493	119	5	learns	learn	VERB
cana-2493	119	6	to	to	PART
cana-2493	119	7	detect	detect	VERB
cana-2493	119	8	and	and	CCONJ
cana-2493	119	9	segment	segment	NOUN
cana-2493	119	10	,	,	PUNCT
cana-2493	119	11	generating	generate	VERB
cana-2493	119	12	more	more	ADV
cana-2493	119	13	accurate	accurate	ADJ
cana-2493	119	14	,	,	PUNCT
cana-2493	119	15	aligned	aligned	ADJ
cana-2493	119	16	results	result	NOUN
cana-2493	119	17	.	.	PUNCT
cana-2493	120	1	mask	mask	VERB
cana-2493	120	2	r	r	NOUN
cana-2493	120	3	-	-	PUNCT
cana-2493	120	4	cnn	cnn	PROPN
cana-2493	120	5	exemplifies	exemplify	VERB
cana-2493	120	6	this	this	DET
cana-2493	120	7	method	method	NOUN
cana-2493	120	8	,	,	PUNCT
cana-2493	120	9	extending	extend	VERB
cana-2493	120	10	faster	fast	ADJ
cana-2493	120	11	rcnn	rcnn	NOUN
cana-2493	120	12	object	object	VERB
cana-2493	120	13	detection	detection	NOUN
cana-2493	120	14	with	with	ADP
cana-2493	120	15	a	a	DET
cana-2493	120	16	segmentation	segmentation	NOUN
cana-2493	120	17	branch	branch	NOUN
cana-2493	120	18	predicting	predict	VERB
cana-2493	120	19	pixel	pixel	PROPN
cana-2493	120	20	masks	mask	NOUN
cana-2493	120	21	.	.	PUNCT
cana-2493	121	1	evaluations	evaluation	NOUN
cana-2493	121	2	show	show	VERB
cana-2493	121	3	this	this	DET
cana-2493	121	4	approach	approach	NOUN
cana-2493	121	5	yields	yield	VERB
cana-2493	121	6	promising	promise	VERB
cana-2493	121	7	detection	detection	NOUN
cana-2493	121	8	and	and	CCONJ
cana-2493	121	9	segmentation	segmentation	NOUN
cana-2493	121	10	of	of	ADP
cana-2493	121	11	lung	lung	NOUN
cana-2493	121	12	cancer	cancer	NOUN
cana-2493	121	13	lesions	lesion	NOUN
cana-2493	121	14	on	on	ADP
cana-2493	121	15	ct	ct	PROPN
cana-2493	121	16	scans	scan	NOUN
cana-2493	121	17	.	.	PUNCT
cana-2493	122	1	transfer	transfer	NOUN
cana-2493	122	2	learning	learning	NOUN
cana-2493	122	3	has	have	AUX
cana-2493	122	4	allowed	allow	VERB
cana-2493	122	5	deep	deep	ADJ
cana-2493	122	6	learning	learning	NOUN
cana-2493	122	7	models	model	NOUN
cana-2493	122	8	in	in	ADP
cana-2493	122	9	lung	lung	NOUN
cana-2493	122	10	cancer	cancer	NOUN
cana-2493	122	11	detection	detection	NOUN
cana-2493	122	12	and	and	CCONJ
cana-2493	122	13	segmentation	segmentation	NOUN
cana-2493	122	14	to	to	PART
cana-2493	122	15	leverage	leverage	NOUN
cana-2493	122	16	knowledge	knowledge	NOUN
cana-2493	122	17	gained	gain	VERB
cana-2493	122	18	from	from	ADP
cana-2493	122	19	natural	natural	ADJ
cana-2493	122	20	images	image	NOUN
cana-2493	122	21	and	and	CCONJ
cana-2493	122	22	apply	apply	VERB
cana-2493	122	23	it	it	PRON
cana-2493	122	24	to	to	ADP
cana-2493	122	25	medical	medical	ADJ
cana-2493	122	26	imagery	imagery	NOUN
cana-2493	122	27	.	.	PUNCT
cana-2493	123	1	this	this	PRON
cana-2493	123	2	proves	prove	VERB
cana-2493	123	3	particularly	particularly	ADV
cana-2493	123	4	useful	useful	ADJ
cana-2493	123	5	for	for	ADP
cana-2493	123	6	medical	medical	ADJ
cana-2493	123	7	imaging	imaging	NOUN
cana-2493	123	8	where	where	SCONJ
cana-2493	123	9	annotated	annotate	VERB
cana-2493	123	10	datasets	dataset	NOUN
cana-2493	123	11	are	be	AUX
cana-2493	123	12	often	often	ADV
cana-2493	123	13	small	small	ADJ
cana-2493	123	14	.	.	PUNCT
cana-2493	124	1	by	by	ADP
cana-2493	124	2	fine	fine	ADV
cana-2493	124	3	-	-	PUNCT
cana-2493	124	4	tuning	tune	VERB
cana-2493	124	5	pretrained	pretraine	VERB
cana-2493	124	6	models	model	NOUN
cana-2493	124	7	like	like	ADP
cana-2493	124	8	vggnet	vggnet	NOUN
cana-2493	124	9	,	,	PUNCT
cana-2493	124	10	resnet	resnet	NOUN
cana-2493	124	11	,	,	PUNCT
cana-2493	124	12	and	and	CCONJ
cana-2493	124	13	inceptionnet	inceptionnet	NOUN
cana-2493	124	14	on	on	ADP
cana-2493	124	15	medical	medical	ADJ
cana-2493	124	16	images	image	NOUN
cana-2493	124	17	,	,	PUNCT
cana-2493	124	18	researchers	researcher	NOUN
cana-2493	124	19	can	can	AUX
cana-2493	124	20	obtain	obtain	VERB
cana-2493	124	21	high	high	ADJ
cana-2493	124	22	performance	performance	NOUN
cana-2493	124	23	from	from	ADP
cana-2493	124	24	more	more	ADV
cana-2493	124	25	modestly	modestly	ADV
cana-2493	124	26	-	-	PUNCT
cana-2493	124	27	sized	sized	ADJ
cana-2493	124	28	datasets	dataset	NOUN
cana-2493	124	29	.	.	PUNCT
cana-2493	125	1	these	these	DET
cana-2493	125	2	models	model	NOUN
cana-2493	125	3	have	have	AUX
cana-2493	125	4	been	be	AUX
cana-2493	125	5	successfully	successfully	ADV
cana-2493	125	6	employed	employ	VERB
cana-2493	125	7	for	for	ADP
cana-2493	125	8	lung	lung	NOUN
cana-2493	125	9	cancer	cancer	NOUN
cana-2493	125	10	diagnosis	diagnosis	NOUN
cana-2493	125	11	,	,	PUNCT
cana-2493	125	12	delivering	deliver	VERB
cana-2493	125	13	strong	strong	ADJ
cana-2493	125	14	feature	feature	NOUN
cana-2493	125	15	extraction	extraction	NOUN
cana-2493	125	16	abilities	ability	NOUN
cana-2493	125	17	then	then	ADV
cana-2493	125	18	tuned	tune	VERB
cana-2493	125	19	specifically	specifically	ADV
cana-2493	125	20	for	for	ADP
cana-2493	125	21	that	that	DET
cana-2493	125	22	task	task	NOUN
cana-2493	125	23	.	.	PUNCT
cana-2493	126	1	models	model	NOUN
cana-2493	126	2	have	have	AUX
cana-2493	126	3	also	also	ADV
cana-2493	126	4	looked	look	VERB
cana-2493	126	5	at	at	ADP
cana-2493	126	6	incorporating	incorporate	VERB
cana-2493	126	7	multiple	multiple	ADJ
cana-2493	126	8	modalities	modality	NOUN
cana-2493	126	9	to	to	PART
cana-2493	126	10	enhance	enhance	VERB
cana-2493	126	11	lung	lung	NOUN
cana-2493	126	12	cancer	cancer	NOUN
cana-2493	126	13	identification	identification	NOUN
cana-2493	126	14	and	and	CCONJ
cana-2493	126	15	definition[16	definition[16	PROPN
cana-2493	126	16	]	]	PUNCT
cana-2493	126	17	.	.	PUNCT
cana-2493	127	1	ct	ct	PROPN
cana-2493	127	2	scans	scan	NOUN
cana-2493	127	3	are	be	AUX
cana-2493	127	4	standard	standard	ADJ
cana-2493	127	5	for	for	ADP
cana-2493	127	6	discovering	discover	VERB
cana-2493	127	7	lung	lung	NOUN
cana-2493	127	8	cancer	cancer	NOUN
cana-2493	127	9	,	,	PUNCT
cana-2493	127	10	yet	yet	CCONJ
cana-2493	127	11	other	other	ADJ
cana-2493	127	12	modalities	modality	NOUN
cana-2493	127	13	such	such	ADJ
cana-2493	127	14	as	as	ADP
cana-2493	127	15	mri	mri	NOUN
cana-2493	127	16	and	and	CCONJ
cana-2493	127	17	pet	pet	NOUN
cana-2493	127	18	can	can	AUX
cana-2493	127	19	offer	offer	VERB
cana-2493	127	20	complementary	complementary	ADJ
cana-2493	127	21	data	datum	NOUN
cana-2493	127	22	about	about	ADP
cana-2493	127	23	cancerous	cancerous	ADJ
cana-2493	127	24	tissue	tissue	NOUN
cana-2493	127	25	.	.	PUNCT
cana-2493	128	1	multi	multi	ADJ
cana-2493	128	2	-	-	ADJ
cana-2493	128	3	modal	modal	ADJ
cana-2493	128	4	imaging	imaging	NOUN
cana-2493	128	5	combines	combine	VERB
cana-2493	128	6	information	information	NOUN
cana-2493	128	7	from	from	ADP
cana-2493	128	8	different	different	ADJ
cana-2493	128	9	sources	source	NOUN
cana-2493	128	10	to	to	PART
cana-2493	128	11	generate	generate	VERB
cana-2493	128	12	a	a	DET
cana-2493	128	13	fuller	full	ADJ
cana-2493	128	14	representation	representation	NOUN
cana-2493	128	15	of	of	ADP
cana-2493	128	16	the	the	DET
cana-2493	128	17	affected	affected	ADJ
cana-2493	128	18	region	region	NOUN
cana-2493	128	19	.	.	PUNCT
cana-2493	129	1	deep	deep	ADJ
cana-2493	129	2	learning	learning	NOUN
cana-2493	129	3	architectures	architecture	NOUN
cana-2493	129	4	equipped	equip	VERB
cana-2493	129	5	to	to	PART
cana-2493	129	6	handle	handle	VERB
cana-2493	129	7	multi	multi	ADJ
cana-2493	129	8	-	-	ADJ
cana-2493	129	9	source	source	NOUN
cana-2493	129	10	data	datum	NOUN
cana-2493	129	11	may	may	AUX
cana-2493	129	12	achieve	achieve	VERB
cana-2493	129	13	better	well	ADJ
cana-2493	129	14	results	result	NOUN
cana-2493	129	15	by	by	ADP
cana-2493	129	16	including	include	VERB
cana-2493	129	17	insights	insight	NOUN
cana-2493	129	18	from	from	ADP
cana-2493	129	19	multiple	multiple	ADJ
cana-2493	129	20	areas	area	NOUN
cana-2493	129	21	.	.	PUNCT
cana-2493	130	1	for	for	ADP
cana-2493	130	2	example	example	NOUN
cana-2493	130	3	,	,	PUNCT
cana-2493	130	4	some	some	PRON
cana-2493	130	5	blend	blend	NOUN
cana-2493	130	6	ct	ct	NOUN
cana-2493	130	7	and	and	CCONJ
cana-2493	130	8	pet	pet	PROPN
cana-2493	130	9	scans	scan	NOUN
cana-2493	130	10	to	to	PART
cana-2493	130	11	increase	increase	VERB
cana-2493	130	12	tumor	tumor	NOUN
cana-2493	130	13	detection	detection	NOUN
cana-2493	130	14	accuracy	accuracy	NOUN
cana-2493	130	15	and	and	CCONJ
cana-2493	130	16	appraise	appraise	VERB
cana-2493	130	17	metastatic	metastatic	ADJ
cana-2493	130	18	activity	activity	NOUN
cana-2493	130	19	.	.	PUNCT
cana-2493	131	1	by	by	ADP
cana-2493	131	2	integrating	integrate	VERB
cana-2493	131	3	multi	multi	ADJ
cana-2493	131	4	-	-	ADJ
cana-2493	131	5	modal	modal	ADJ
cana-2493	131	6	inputs	input	NOUN
cana-2493	131	7	,	,	PUNCT
cana-2493	131	8	deep	deep	ADJ
cana-2493	131	9	learning	learning	NOUN
cana-2493	131	10	models	model	NOUN
cana-2493	131	11	can	can	AUX
cana-2493	131	12	offer	offer	VERB
cana-2493	131	13	more	more	ADV
cana-2493	131	14	reliable	reliable	ADJ
cana-2493	131	15	and	and	CCONJ
cana-2493	131	16	precise	precise	ADJ
cana-2493	131	17	predictions	prediction	NOUN
cana-2493	131	18	,	,	PUNCT
cana-2493	131	19	assisting	assist	VERB
cana-2493	131	20	clinicians	clinician	NOUN
cana-2493	131	21	in	in	ADP
cana-2493	131	22	more	more	ADV
cana-2493	131	23	informed	informed	ADJ
cana-2493	131	24	choices	choice	NOUN
cana-2493	131	25	.	.	PUNCT
cana-2493	132	1	source	source	NOUN
cana-2493	132	2	objective	objective	ADJ
cana-2493	132	3	methodology	methodology	NOUN
cana-2493	132	4	results	result	VERB
cana-2493	132	5	research	research	NOUN
cana-2493	132	6	gap	gap	NOUN
cana-2493	132	7	[	[	X
cana-2493	132	8	15	15	NUM
cana-2493	132	9	]	]	X
cana-2493	132	10	●	●	PUNCT
cana-2493	132	11	develop	develop	VERB
cana-2493	132	12	accurate	accurate	ADJ
cana-2493	132	13	lung	lung	NOUN
cana-2493	132	14	cancer	cancer	NOUN
cana-2493	132	15	detection	detection	NOUN
cana-2493	132	16	system	system	NOUN
cana-2493	132	17	using	use	VERB
cana-2493	132	18	deep	deep	ADJ
cana-2493	132	19	learning	learning	NOUN
cana-2493	132	20	.	.	PUNCT
cana-2493	133	1	●	●	PUNCT
cana-2493	133	2	improve	improve	VERB
cana-2493	133	3	segmentation	segmentation	NOUN
cana-2493	133	4	accuracy	accuracy	NOUN
cana-2493	133	5	and	and	CCONJ
cana-2493	133	6	classification	classification	NOUN
cana-2493	133	7	performance	performance	NOUN
cana-2493	133	8	for	for	ADP
cana-2493	133	9	●	●	NUM
cana-2493	133	10	adaptive	adaptive	ADJ
cana-2493	133	11	multi	multi	ADJ
cana-2493	133	12	-	-	ADJ
cana-2493	133	13	scale	scale	ADJ
cana-2493	133	14	dilated	dilated	ADJ
cana-2493	133	15	trans	tran	NOUN
cana-2493	133	16	-	-	ADJ
cana-2493	133	17	unet3	unet3	ADJ
cana-2493	133	18	+	+	ADJ
cana-2493	133	19	for	for	ADP
cana-2493	133	20	nodule	nodule	ADJ
cana-2493	133	21	segmentation	segmentation	NOUN
cana-2493	133	22	.	.	PUNCT
cana-2493	134	1	●	●	PUNCT
cana-2493	134	2	advanced	advanced	ADJ
cana-2493	134	3	dilated	dilate	VERB
cana-2493	134	4	ensemble	ensemble	ADJ
cana-2493	134	5	convolutional	convolutional	ADJ
cana-2493	134	6	neural	neural	ADJ
cana-2493	134	7	networks	network	NOUN
cana-2493	134	8	for	for	ADP
cana-2493	134	9	classification	classification	NOUN
cana-2493	134	10	.	.	PUNCT
cana-2493	135	1	●	●	PUNCT
cana-2493	135	2	efficient	efficient	ADJ
cana-2493	135	3	lung	lung	NOUN
cana-2493	135	4	cancer	cancer	NOUN
cana-2493	135	5	detection	detection	NOUN
cana-2493	135	6	system	system	NOUN
cana-2493	135	7	with	with	ADP
cana-2493	135	8	improved	improved	ADJ
cana-2493	135	9	segmentation	segmentation	NOUN
cana-2493	135	10	and	and	CCONJ
cana-2493	135	11	classification	classification	NOUN
cana-2493	135	12	.	.	PUNCT
cana-2493	136	1	●	●	PUNCT
cana-2493	136	2	demonstrated	demonstrate	VERB
cana-2493	136	3	high	high	ADJ
cana-2493	136	4	performance	performance	NOUN
cana-2493	136	5	in	in	ADP
cana-2493	136	6	detecting	detect	VERB
cana-2493	136	7	cancer	cancer	NOUN
cana-2493	136	8	using	use	VERB
cana-2493	136	9	ct	ct	NUM
cana-2493	136	10	images	image	NOUN
cana-2493	136	11	.	.	PUNCT
cana-2493	137	1	●	●	PUNCT
cana-2493	137	2	enhance	enhance	NOUN
cana-2493	137	3	presentation	presentation	NOUN
cana-2493	137	4	quality	quality	NOUN
cana-2493	137	5	and	and	CCONJ
cana-2493	137	6	detailed	detailed	ADJ
cana-2493	137	7	algorithm	algorithm	NOUN
cana-2493	137	8	explanations	explanation	NOUN
cana-2493	137	9	.	.	PUNCT
cana-2493	138	1	communications	communication	NOUN
cana-2493	138	2	on	on	ADP
cana-2493	138	3	applied	apply	VERB
cana-2493	138	4	nonlinear	nonlinear	ADJ
cana-2493	138	5	analysis	analysis	NOUN
cana-2493	138	6	issn	issn	NOUN
cana-2493	138	7	:	:	PUNCT
cana-2493	138	8	1074	1074	NUM
cana-2493	138	9	-	-	PUNCT
cana-2493	138	10	133x	133x	NUM
cana-2493	138	11	vol	vol	NOUN
cana-2493	138	12	32	32	NUM
cana-2493	138	13	no	no	NOUN
cana-2493	138	14	.	.	PUNCT
cana-2493	139	1	2s	2s	NUM
cana-2493	139	2	(	(	PUNCT
cana-2493	139	3	2025	2025	NUM
cana-2493	139	4	)	)	PUNCT
cana-2493	139	5	551	551	NUM
cana-2493	139	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	139	7	lung	lung	NOUN
cana-2493	139	8	cancer	cancer	NOUN
cana-2493	139	9	detection	detection	NOUN
cana-2493	139	10	.	.	PUNCT
cana-2493	140	1	[	[	X
cana-2493	140	2	16	16	NUM
cana-2493	140	3	]	]	SYM
cana-2493	140	4	●	●	PUNCT
cana-2493	140	5	enhance	enhance	NOUN
cana-2493	140	6	lung	lung	NOUN
cana-2493	140	7	cancer	cancer	NOUN
cana-2493	140	8	diagnosis	diagnosis	NOUN
cana-2493	140	9	using	use	VERB
cana-2493	140	10	deep	deep	ADJ
cana-2493	140	11	learning	learning	NOUN
cana-2493	140	12	models	model	NOUN
cana-2493	140	13	.	.	PUNCT
cana-2493	141	1	●	●	PUNCT
cana-2493	141	2	compare	compare	ADJ
cana-2493	141	3	effectiveness	effectiveness	NOUN
cana-2493	141	4	of	of	ADP
cana-2493	141	5	various	various	ADJ
cana-2493	141	6	deep	deep	ADJ
cana-2493	141	7	learning	learning	NOUN
cana-2493	141	8	strategies	strategy	NOUN
cana-2493	141	9	●	●	NUM
cana-2493	141	10	deep	deep	ADJ
cana-2493	141	11	learning	learning	NOUN
cana-2493	141	12	models	model	NOUN
cana-2493	141	13	:	:	PUNCT
cana-2493	141	14	resnet152v2	resnet152v2	NOUN
cana-2493	141	15	,	,	PUNCT
cana-2493	141	16	inception	inception	PROPN
cana-2493	141	17	v3	v3	PROPN
cana-2493	141	18	,	,	PUNCT
cana-2493	141	19	ann	ann	PROPN
cana-2493	141	20	,	,	PUNCT
cana-2493	141	21	fnn	fnn	PROPN
cana-2493	141	22	●	●	NUM
cana-2493	141	23	comparative	comparative	ADJ
cana-2493	141	24	study	study	NOUN
cana-2493	141	25	on	on	ADP
cana-2493	141	26	diagnostic	diagnostic	ADJ
cana-2493	141	27	accuracy	accuracy	NOUN
cana-2493	141	28	and	and	CCONJ
cana-2493	141	29	performance	performance	NOUN
cana-2493	141	30	measures	measure	NOUN
cana-2493	141	31	.	.	PUNCT
cana-2493	142	1	●	●	NUM
cana-2493	142	2	enhanced	enhance	VERB
cana-2493	142	3	lung	lung	NOUN
cana-2493	142	4	cancer	cancer	NOUN
cana-2493	142	5	diagnosis	diagnosis	NOUN
cana-2493	142	6	using	use	VERB
cana-2493	142	7	deep	deep	ADJ
cana-2493	142	8	learning	learning	NOUN
cana-2493	142	9	models	model	NOUN
cana-2493	142	10	.	.	PUNCT
cana-2493	143	1	●	●	PUNCT
cana-2493	143	2	compared	compare	VERB
cana-2493	143	3	models	model	NOUN
cana-2493	143	4	on	on	ADP
cana-2493	143	5	accuracy	accuracy	NOUN
cana-2493	143	6	,	,	PUNCT
cana-2493	143	7	precision	precision	NOUN
cana-2493	143	8	,	,	PUNCT
cana-2493	143	9	sensitivity	sensitivity	NOUN
cana-2493	143	10	,	,	PUNCT
cana-2493	143	11	and	and	CCONJ
cana-2493	143	12	specificity	specificity	NOUN
cana-2493	143	13	.	.	PUNCT
cana-2493	144	1	●	●	PUNCT
cana-2493	144	2	incorporate	incorporate	VERB
cana-2493	144	3	substantial	substantial	ADJ
cana-2493	144	4	results	result	NOUN
cana-2493	144	5	or	or	CCONJ
cana-2493	144	6	insights	insight	NOUN
cana-2493	144	7	for	for	ADP
cana-2493	144	8	future	future	ADJ
cana-2493	144	9	research	research	NOUN
cana-2493	144	10	.	.	PUNCT
cana-2493	145	1	[	[	X
cana-2493	145	2	17	17	NUM
cana-2493	145	3	]	]	SYM
cana-2493	145	4	●	●	NUM
cana-2493	145	5	analyze	analyze	NOUN
cana-2493	145	6	publications	publication	NOUN
cana-2493	145	7	for	for	ADP
cana-2493	145	8	lung	lung	NOUN
cana-2493	145	9	cancer	cancer	NOUN
cana-2493	145	10	recognition	recognition	NOUN
cana-2493	145	11	methods	method	NOUN
cana-2493	145	12	.	.	PUNCT
cana-2493	146	1	●	●	PUNCT
cana-2493	146	2	examine	examine	NOUN
cana-2493	146	3	performance	performance	NOUN
cana-2493	146	4	metrics	metric	NOUN
cana-2493	146	5	of	of	ADP
cana-2493	146	6	detection	detection	NOUN
cana-2493	146	7	strategies	strategy	NOUN
cana-2493	146	8	.	.	PUNCT
cana-2493	147	1	●	●	NUM
cana-2493	147	2	segmentation	segmentation	NOUN
cana-2493	147	3	models	model	NOUN
cana-2493	147	4	and	and	CCONJ
cana-2493	147	5	feature	feature	NOUN
cana-2493	147	6	extraction	extraction	NOUN
cana-2493	147	7	methods	method	NOUN
cana-2493	147	8	analyzed	analyze	VERB
cana-2493	147	9	●	●	NUM
cana-2493	147	10	cancer	cancer	NOUN
cana-2493	147	11	detection	detection	NOUN
cana-2493	147	12	strategies	strategy	NOUN
cana-2493	147	13	include	include	VERB
cana-2493	147	14	dl	dl	PROPN
cana-2493	147	15	and	and	CCONJ
cana-2493	147	16	ml	ml	PROPN
cana-2493	147	17	models	model	NOUN
cana-2493	147	18	discussed	discuss	VERB
cana-2493	147	19	●	●	NUM
cana-2493	147	20	analyzed	analyze	VERB
cana-2493	147	21	various	various	ADJ
cana-2493	147	22	lung	lung	NOUN
cana-2493	147	23	cancer	cancer	NOUN
cana-2493	147	24	detection	detection	NOUN
cana-2493	147	25	methods	method	NOUN
cana-2493	147	26	using	use	VERB
cana-2493	147	27	deep	deep	ADJ
cana-2493	147	28	learning	learning	NOUN
cana-2493	147	29	.	.	PUNCT
cana-2493	148	1	●	●	NUM
cana-2493	148	2	identified	identify	VERB
cana-2493	148	3	research	research	NOUN
cana-2493	148	4	gaps	gap	NOUN
cana-2493	148	5	for	for	ADP
cana-2493	148	6	further	further	ADJ
cana-2493	148	7	investigation	investigation	NOUN
cana-2493	148	8	in	in	ADP
cana-2493	148	9	lung	lung	NOUN
cana-2493	148	10	detection	detection	NOUN
cana-2493	148	11	models	model	NOUN
cana-2493	148	12	.	.	PUNCT
cana-2493	149	1	●	●	PUNCT
cana-2493	149	2	encourages	encourage	VERB
cana-2493	149	3	further	further	ADJ
cana-2493	149	4	investigation	investigation	NOUN
cana-2493	149	5	of	of	ADP
cana-2493	149	6	lung	lung	NOUN
cana-2493	149	7	detection	detection	NOUN
cana-2493	149	8	models	model	NOUN
cana-2493	149	9	.	.	PUNCT
cana-2493	150	1	[	[	X
cana-2493	150	2	18	18	NUM
cana-2493	150	3	]	]	SYM
cana-2493	150	4	●	●	PUNCT
cana-2493	150	5	enhance	enhance	VERB
cana-2493	150	6	early	early	ADJ
cana-2493	150	7	detection	detection	NOUN
cana-2493	150	8	of	of	ADP
cana-2493	150	9	lung	lung	NOUN
cana-2493	150	10	cancer	cancer	NOUN
cana-2493	150	11	types	type	NOUN
cana-2493	150	12	.	.	PUNCT
cana-2493	151	1	●	●	PUNCT
cana-2493	151	2	automate	automate	ADJ
cana-2493	151	3	categorization	categorization	NOUN
cana-2493	151	4	of	of	ADP
cana-2493	151	5	lung	lung	NOUN
cana-2493	151	6	cancer	cancer	NOUN
cana-2493	151	7	through	through	ADP
cana-2493	151	8	cnn	cnn	PROPN
cana-2493	151	9	analysis	analysis	NOUN
cana-2493	151	10	.	.	PUNCT
cana-2493	152	1	●	●	PUNCT
cana-2493	152	2	lung	lung	NOUN
cana-2493	152	3	x	x	ADJ
cana-2493	152	4	-	-	NOUN
cana-2493	152	5	ray	ray	NOUN
cana-2493	152	6	image	image	NOUN
cana-2493	152	7	preprocessing	preprocesse	VERB
cana-2493	152	8	●	●	NUM
cana-2493	152	9	classification	classification	NOUN
cana-2493	152	10	using	use	VERB
cana-2493	152	11	convolutional	convolutional	ADJ
cana-2493	152	12	neural	neural	ADJ
cana-2493	152	13	networks	network	NOUN
cana-2493	152	14	●	●	NOUN
cana-2493	152	15	model	model	NOUN
cana-2493	152	16	effectively	effectively	ADV
cana-2493	152	17	distinguishes	distinguish	VERB
cana-2493	152	18	lung	lung	NOUN
cana-2493	152	19	cancer	cancer	NOUN
cana-2493	152	20	types	type	NOUN
cana-2493	152	21	and	and	CCONJ
cana-2493	152	22	normal	normal	ADJ
cana-2493	152	23	cases	case	NOUN
cana-2493	152	24	.	.	PUNCT
cana-2493	153	1	●	●	PUNCT
cana-2493	153	2	comprehensive	comprehensive	ADJ
cana-2493	153	3	performance	performance	NOUN
cana-2493	153	4	metrics	metric	NOUN
cana-2493	153	5	include	include	VERB
cana-2493	153	6	accuracy	accuracy	NOUN
cana-2493	153	7	,	,	PUNCT
cana-2493	153	8	sensitivity	sensitivity	NOUN
cana-2493	153	9	,	,	PUNCT
cana-2493	153	10	specificity	specificity	NOUN
cana-2493	153	11	,	,	PUNCT
cana-2493	153	12	and	and	CCONJ
cana-2493	153	13	precision	precision	NOUN
cana-2493	153	14	.	.	PUNCT
cana-2493	154	1	●	●	PUNCT
cana-2493	154	2	identifies	identifie	NOUN
cana-2493	154	3	areas	area	NOUN
cana-2493	154	4	where	where	SCONJ
cana-2493	154	5	additional	additional	ADJ
cana-2493	154	6	research	research	NOUN
cana-2493	154	7	is	be	AUX
cana-2493	154	8	needed	need	VERB
cana-2493	154	9	.	.	PUNCT
cana-2493	155	1	[	[	X
cana-2493	155	2	19	19	NUM
cana-2493	155	3	]	]	X
cana-2493	155	4	●	●	PUNCT
cana-2493	155	5	investigate	investigate	VERB
cana-2493	155	6	deep	deep	ADJ
cana-2493	155	7	learning	learning	NOUN
cana-2493	155	8	techniques	technique	NOUN
cana-2493	155	9	for	for	ADP
cana-2493	155	10	lung	lung	NOUN
cana-2493	155	11	cancer	cancer	NOUN
cana-2493	155	12	diagnosis	diagnosis	NOUN
cana-2493	155	13	.	.	PUNCT
cana-2493	156	1	●	●	PUNCT
cana-2493	156	2	evaluate	evaluate	VERB
cana-2493	156	3	the	the	DET
cana-2493	156	4	effectiveness	effectiveness	NOUN
cana-2493	156	5	of	of	ADP
cana-2493	156	6	convolutional	convolutional	ADJ
cana-2493	156	7	neural	neural	ADJ
cana-2493	156	8	networks	network	NOUN
cana-2493	156	9	●	●	PUNCT
cana-2493	156	10	deep	deep	ADJ
cana-2493	156	11	convolutional	convolutional	ADJ
cana-2493	156	12	neural	neural	ADJ
cana-2493	156	13	networks	network	NOUN
cana-2493	156	14	(	(	PUNCT
cana-2493	156	15	dcnn	dcnn	ADJ
cana-2493	156	16	)	)	PUNCT
cana-2493	156	17	●	●	PUNCT
cana-2493	156	18	convolutional	convolutional	ADJ
cana-2493	156	19	neural	neural	ADJ
cana-2493	156	20	network	network	NOUN
cana-2493	156	21	(	(	PUNCT
cana-2493	156	22	cnn	cnn	PROPN
cana-2493	156	23	)	)	PUNCT
cana-2493	156	24	●	●	PUNCT
cana-2493	156	25	deep	deep	ADJ
cana-2493	156	26	learning	learning	NOUN
cana-2493	156	27	techniques	technique	NOUN
cana-2493	156	28	improve	improve	VERB
cana-2493	156	29	lung	lung	NOUN
cana-2493	156	30	cancer	cancer	NOUN
cana-2493	156	31	detection	detection	NOUN
cana-2493	156	32	.	.	PUNCT
cana-2493	157	1	●	●	PUNCT
cana-2493	157	2	cnn	cnn	PROPN
cana-2493	157	3	consistently	consistently	ADV
cana-2493	157	4	shows	show	VERB
cana-2493	157	5	highest	high	ADJ
cana-2493	157	6	accuracy	accuracy	NOUN
cana-2493	157	7	in	in	ADP
cana-2493	157	8	classification	classification	NOUN
cana-2493	157	9	.	.	PUNCT
cana-2493	158	1	●	●	PUNCT
cana-2493	158	2	lack	lack	NOUN
cana-2493	158	3	of	of	ADP
cana-2493	158	4	discussion	discussion	NOUN
cana-2493	158	5	on	on	ADP
cana-2493	158	6	challenges	challenge	NOUN
cana-2493	158	7	faced	face	VERB
cana-2493	158	8	in	in	ADP
cana-2493	158	9	implementation	implementation	NOUN
cana-2493	158	10	.	.	PUNCT
cana-2493	159	1	communications	communication	NOUN
cana-2493	159	2	on	on	ADP
cana-2493	159	3	applied	apply	VERB
cana-2493	159	4	nonlinear	nonlinear	ADJ
cana-2493	159	5	analysis	analysis	NOUN
cana-2493	159	6	issn	issn	NOUN
cana-2493	159	7	:	:	PUNCT
cana-2493	159	8	1074	1074	NUM
cana-2493	159	9	-	-	PUNCT
cana-2493	159	10	133x	133x	NUM
cana-2493	159	11	vol	vol	NOUN
cana-2493	159	12	32	32	NUM
cana-2493	159	13	no	no	NOUN
cana-2493	159	14	.	.	PUNCT
cana-2493	160	1	2s	2s	NUM
cana-2493	160	2	(	(	PUNCT
cana-2493	160	3	2025	2025	NUM
cana-2493	160	4	)	)	PUNCT
cana-2493	160	5	552	552	NUM
cana-2493	160	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	160	7	(	(	PUNCT
cana-2493	160	8	cnn	cnn	PROPN
cana-2493	160	9	)	)	PUNCT
cana-2493	160	10	in	in	ADP
cana-2493	160	11	classification	classification	NOUN
cana-2493	160	12	.	.	PUNCT
cana-2493	161	1	[	[	X
cana-2493	161	2	20	20	NUM
cana-2493	161	3	]	]	SYM
cana-2493	161	4	●	●	PUNCT
cana-2493	161	5	develop	develop	VERB
cana-2493	161	6	a	a	DET
cana-2493	161	7	customized	customized	ADJ
cana-2493	161	8	convolutional	convolutional	ADJ
cana-2493	161	9	neural	neural	ADJ
cana-2493	161	10	network	network	NOUN
cana-2493	161	11	for	for	ADP
cana-2493	161	12	nodule	nodule	NOUN
cana-2493	161	13	detection	detection	NOUN
cana-2493	161	14	.	.	PUNCT
cana-2493	162	1	●	●	PUNCT
cana-2493	162	2	achieve	achieve	VERB
cana-2493	162	3	precise	precise	ADJ
cana-2493	162	4	lung	lung	NOUN
cana-2493	162	5	nodule	nodule	NOUN
cana-2493	162	6	segmentation	segmentation	NOUN
cana-2493	162	7	and	and	CCONJ
cana-2493	162	8	characterization	characterization	NOUN
cana-2493	162	9	.	.	PUNCT
cana-2493	163	1	●	●	PUNCT
cana-2493	163	2	customized	customize	VERB
cana-2493	163	3	convolutional	convolutional	ADJ
cana-2493	163	4	neural	neural	ADJ
cana-2493	163	5	network	network	NOUN
cana-2493	163	6	model	model	NOUN
cana-2493	163	7	for	for	ADP
cana-2493	163	8	nodule	nodule	NOUN
cana-2493	163	9	identification	identification	NOUN
cana-2493	163	10	●	●	PUNCT
cana-2493	163	11	u	u	NOUN
cana-2493	163	12	-	-	ADJ
cana-2493	163	13	net	net	ADJ
cana-2493	163	14	model	model	NOUN
cana-2493	163	15	for	for	ADP
cana-2493	163	16	precise	precise	ADJ
cana-2493	163	17	lung	lung	NOUN
cana-2493	163	18	nodule	nodule	NOUN
cana-2493	163	19	segmentation	segmentation	NOUN
cana-2493	163	20	●	●	NUM
cana-2493	163	21	improved	improved	ADJ
cana-2493	163	22	accuracy	accuracy	NOUN
cana-2493	163	23	in	in	ADP
cana-2493	163	24	detecting	detect	VERB
cana-2493	163	25	lung	lung	NOUN
cana-2493	163	26	nodules	nodule	NOUN
cana-2493	163	27	on	on	ADP
cana-2493	163	28	ct	ct	PROPN
cana-2493	163	29	scans	scan	NOUN
cana-2493	163	30	.	.	PUNCT
cana-2493	164	1	●	●	PUNCT
cana-2493	164	2	focus	focus	NOUN
cana-2493	164	3	on	on	ADP
cana-2493	164	4	localizing	localize	VERB
cana-2493	164	5	nodules	nodule	NOUN
cana-2493	164	6	in	in	ADP
cana-2493	164	7	malignant	malignant	ADJ
cana-2493	164	8	cases	case	NOUN
cana-2493	164	9	for	for	ADP
cana-2493	164	10	diagnosis	diagnosis	NOUN
cana-2493	164	11	.	.	PUNCT
cana-2493	165	1	●	●	PUNCT
cana-2493	165	2	limited	limited	ADJ
cana-2493	165	3	focus	focus	NOUN
cana-2493	165	4	on	on	ADP
cana-2493	165	5	deep	deep	ADJ
cana-2493	165	6	learning	learning	NOUN
cana-2493	165	7	methods	method	NOUN
cana-2493	165	8	other	other	ADJ
cana-2493	165	9	than	than	ADP
cana-2493	165	10	cnn	cnn	PROPN
cana-2493	165	11	.	.	PUNCT
cana-2493	166	1	[	[	X
cana-2493	166	2	21	21	NUM
cana-2493	166	3	]	]	SYM
cana-2493	166	4	●	●	PUNCT
cana-2493	166	5	enhance	enhance	NOUN
cana-2493	166	6	lung	lung	NOUN
cana-2493	166	7	cancer	cancer	NOUN
cana-2493	166	8	detection	detection	NOUN
cana-2493	166	9	accuracy	accuracy	NOUN
cana-2493	166	10	using	use	VERB
cana-2493	166	11	hybrid	hybrid	ADJ
cana-2493	166	12	framework	framework	NOUN
cana-2493	166	13	.	.	PUNCT
cana-2493	167	1	●	●	PUNCT
cana-2493	167	2	combine	combine	VERB
cana-2493	167	3	deep	deep	ADJ
cana-2493	167	4	learning	learning	NOUN
cana-2493	167	5	with	with	ADP
cana-2493	167	6	quantum	quantum	NOUN
cana-2493	167	7	computing	computing	NOUN
cana-2493	167	8	for	for	ADP
cana-2493	167	9	improved	improved	ADJ
cana-2493	167	10	performance	performance	NOUN
cana-2493	167	11	.	.	PUNCT
cana-2493	168	1	●	●	PUNCT
cana-2493	168	2	deep	deep	ADJ
cana-2493	168	3	learning	learning	NOUN
cana-2493	168	4	for	for	ADP
cana-2493	168	5	feature	feature	NOUN
cana-2493	168	6	extraction	extraction	NOUN
cana-2493	168	7	.	.	PUNCT
cana-2493	169	1	●	●	PUNCT
cana-2493	169	2	quantum	quantum	ADJ
cana-2493	169	3	circuits	circuit	NOUN
cana-2493	169	4	for	for	ADP
cana-2493	169	5	classification	classification	NOUN
cana-2493	169	6	.	.	PUNCT
cana-2493	170	1	●	●	PUNCT
cana-2493	170	2	overall	overall	ADJ
cana-2493	170	3	accuracy	accuracy	NOUN
cana-2493	170	4	of	of	ADP
cana-2493	170	5	92.12	92.12	NUM
cana-2493	170	6	%	%	NOUN
cana-2493	170	7	achieved	achieve	VERB
cana-2493	170	8	.	.	PUNCT
cana-2493	171	1	●	●	PUNCT
cana-2493	171	2	sensitivity	sensitivity	NOUN
cana-2493	171	3	94	94	NUM
cana-2493	171	4	%	%	NOUN
cana-2493	171	5	,	,	PUNCT
cana-2493	171	6	specificity	specificity	NOUN
cana-2493	171	7	90	90	NUM
cana-2493	171	8	%	%	NOUN
cana-2493	171	9	,	,	PUNCT
cana-2493	171	10	f1	f1	NOUN
cana-2493	171	11	-	-	PUNCT
cana-2493	171	12	score	score	NOUN
cana-2493	171	13	93	93	NUM
cana-2493	171	14	%	%	NOUN
cana-2493	171	15	,	,	PUNCT
cana-2493	171	16	precision	precision	NOUN
cana-2493	171	17	92	92	NUM
cana-2493	171	18	%	%	NOUN
cana-2493	171	19	.	.	PUNCT
cana-2493	172	1	●	●	PUNCT
cana-2493	172	2	addressing	address	VERB
cana-2493	172	3	interpretability	interpretability	NOUN
cana-2493	172	4	and	and	CCONJ
cana-2493	172	5	trust	trust	NOUN
cana-2493	172	6	in	in	ADP
cana-2493	172	7	ai	ai	PROPN
cana-2493	172	8	models	model	NOUN
cana-2493	172	9	[	[	X
cana-2493	172	10	22	22	NUM
cana-2493	172	11	]	]	X
cana-2493	172	12	●	●	PUNCT
cana-2493	172	13	develop	develop	VERB
cana-2493	172	14	automated	automate	VERB
cana-2493	172	15	lung	lung	NOUN
cana-2493	172	16	cancer	cancer	NOUN
cana-2493	172	17	detection	detection	NOUN
cana-2493	172	18	using	use	VERB
cana-2493	172	19	cnns	cnn	NOUN
cana-2493	172	20	.	.	PUNCT
cana-2493	173	1	●	●	PUNCT
cana-2493	173	2	improve	improve	VERB
cana-2493	173	3	early	early	ADJ
cana-2493	173	4	detection	detection	NOUN
cana-2493	173	5	for	for	ADP
cana-2493	173	6	better	well	ADJ
cana-2493	173	7	treatment	treatment	NOUN
cana-2493	173	8	effectiveness	effectiveness	NOUN
cana-2493	173	9	.	.	PUNCT
cana-2493	174	1	●	●	PUNCT
cana-2493	174	2	augmentation	augmentation	NOUN
cana-2493	174	3	techniques	technique	NOUN
cana-2493	174	4	:	:	PUNCT
cana-2493	174	5	zooming	zoom	VERB
cana-2493	174	6	,	,	PUNCT
cana-2493	174	7	shearing	shearing	NOUN
cana-2493	174	8	,	,	PUNCT
cana-2493	174	9	flipping	flipping	NOUN
cana-2493	174	10	,	,	PUNCT
cana-2493	174	11	normalization	normalization	NOUN
cana-2493	174	12	●	●	NUM
cana-2493	174	13	cnn	cnn	NOUN
cana-2493	174	14	architecture	architecture	NOUN
cana-2493	174	15	:	:	PUNCT
cana-2493	174	16	convolutional	convolutional	ADJ
cana-2493	174	17	,	,	PUNCT
cana-2493	174	18	maxpooling	maxpooling	NOUN
cana-2493	174	19	,	,	PUNCT
cana-2493	174	20	dropout	dropout	NOUN
cana-2493	174	21	layers	layer	NOUN
cana-2493	174	22	for	for	ADP
cana-2493	174	23	detailed	detailed	ADJ
cana-2493	174	24	pattern	pattern	NOUN
cana-2493	174	25	detection	detection	NOUN
cana-2493	174	26	●	●	PUNCT
cana-2493	174	27	achieved	achieve	VERB
cana-2493	174	28	95	95	NUM
cana-2493	174	29	%	%	NOUN
cana-2493	174	30	accuracy	accuracy	NOUN
cana-2493	174	31	in	in	ADP
cana-2493	174	32	lung	lung	NOUN
cana-2493	174	33	cancer	cancer	NOUN
cana-2493	174	34	detection	detection	NOUN
cana-2493	174	35	.	.	PUNCT
cana-2493	175	1	●	●	NUM
cana-2493	175	2	demonstrated	demonstrate	VERB
cana-2493	175	3	cnns	cnn	NOUN
cana-2493	175	4	'	'	PART
cana-2493	175	5	potential	potential	NOUN
cana-2493	175	6	in	in	ADP
cana-2493	175	7	healthcare	healthcare	NOUN
cana-2493	175	8	applications	application	NOUN
cana-2493	175	9	.	.	PUNCT
cana-2493	176	1	●	●	PUNCT
cana-2493	176	2	advancing	advance	VERB
cana-2493	176	3	research	research	NOUN
cana-2493	176	4	for	for	ADP
cana-2493	176	5	integrating	integrate	VERB
cana-2493	176	6	findings	finding	NOUN
cana-2493	176	7	into	into	ADP
cana-2493	176	8	clinical	clinical	ADJ
cana-2493	176	9	applications	application	NOUN
cana-2493	176	10	[	[	X
cana-2493	176	11	23	23	NUM
cana-2493	176	12	]	]	PUNCT
cana-2493	176	13	●	●	NUM
cana-2493	176	14	predict	predict	VERB
cana-2493	176	15	lung	lung	NOUN
cana-2493	176	16	cancer	cancer	NOUN
cana-2493	176	17	using	use	VERB
cana-2493	176	18	dl	dl	PROPN
cana-2493	176	19	models	model	NOUN
cana-2493	176	20	●	●	PUNCT
cana-2493	176	21	compare	compare	VERB
cana-2493	176	22	sequential	sequential	ADJ
cana-2493	176	23	and	and	CCONJ
cana-2493	176	24	●	●	PRON
cana-2493	176	25	dl	dl	NOUN
cana-2493	176	26	models	model	NOUN
cana-2493	176	27	:	:	PUNCT
cana-2493	176	28	sequential	sequential	ADJ
cana-2493	176	29	and	and	CCONJ
cana-2493	176	30	densenet	densenet	NOUN
cana-2493	176	31	●	●	NUM
cana-2493	176	32	image	image	NOUN
cana-2493	176	33	preprocessing	preprocesse	VERB
cana-2493	176	34	with	with	ADP
cana-2493	176	35	●	●	NUM
cana-2493	176	36	densenet	densenet	NOUN
cana-2493	176	37	model	model	NOUN
cana-2493	176	38	outperformed	outperform	VERB
cana-2493	176	39	sequential	sequential	ADJ
cana-2493	176	40	model	model	NOUN
cana-2493	176	41	with	with	ADP
cana-2493	176	42	95.86	95.86	NUM
cana-2493	176	43	%	%	NOUN
cana-2493	176	44	accuracy	accuracy	NOUN
cana-2493	176	45	.	.	PUNCT
cana-2493	177	1	●	●	PUNCT
cana-2493	177	2	enhance	enhance	NOUN
cana-2493	177	3	presentation	presentation	NOUN
cana-2493	177	4	quality	quality	NOUN
cana-2493	177	5	and	and	CCONJ
cana-2493	177	6	detailed	detailed	ADJ
cana-2493	177	7	algorithm	algorithm	NOUN
cana-2493	177	8	explanations	explanation	NOUN
cana-2493	177	9	.	.	PUNCT
cana-2493	178	1	communications	communication	NOUN
cana-2493	178	2	on	on	ADP
cana-2493	178	3	applied	apply	VERB
cana-2493	178	4	nonlinear	nonlinear	ADJ
cana-2493	178	5	analysis	analysis	NOUN
cana-2493	178	6	issn	issn	NOUN
cana-2493	178	7	:	:	PUNCT
cana-2493	178	8	1074	1074	NUM
cana-2493	178	9	-	-	PUNCT
cana-2493	178	10	133x	133x	NUM
cana-2493	178	11	vol	vol	NOUN
cana-2493	178	12	32	32	NUM
cana-2493	178	13	no	no	NOUN
cana-2493	178	14	.	.	PUNCT
cana-2493	179	1	2s	2s	NUM
cana-2493	179	2	(	(	PUNCT
cana-2493	179	3	2025	2025	NUM
cana-2493	179	4	)	)	PUNCT
cana-2493	179	5	553	553	NUM
cana-2493	179	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-2493	179	7	densenet	densenet	NOUN
cana-2493	179	8	models	model	NOUN
cana-2493	179	9	for	for	ADP
cana-2493	179	10	accuracy	accuracy	NOUN
cana-2493	179	11	chest	chest	NOUN
cana-2493	179	12	x	x	NOUN
cana-2493	179	13	-	-	NOUN
cana-2493	179	14	ray	ray	NOUN
cana-2493	179	15	scans	scan	NOUN
cana-2493	179	16	for	for	ADP
cana-2493	179	17	feature	feature	NOUN
cana-2493	179	18	selection	selection	NOUN
cana-2493	179	19	●	●	PUNCT
cana-2493	179	20	chest	chest	NOUN
cana-2493	179	21	x	x	NOUN
cana-2493	179	22	-	-	NOUN
cana-2493	179	23	ray	ray	NOUN
cana-2493	179	24	scans	scan	NOUN
cana-2493	179	25	used	use	VERB
cana-2493	179	26	for	for	ADP
cana-2493	179	27	lung	lung	NOUN
cana-2493	179	28	cancer	cancer	NOUN
cana-2493	179	29	prediction	prediction	NOUN
cana-2493	179	30	.	.	PUNCT
cana-2493	180	1	●	●	PUNCT
cana-2493	180	2	incorporate	incorporate	VERB
cana-2493	180	3	substantial	substantial	ADJ
cana-2493	180	4	results	result	NOUN
cana-2493	180	5	or	or	CCONJ
cana-2493	180	6	insights	insight	NOUN
cana-2493	180	7	for	for	ADP
cana-2493	180	8	future	future	ADJ
cana-2493	180	9	research	research	NOUN
cana-2493	180	10	.	.	PUNCT
cana-2493	181	1	[	[	X
cana-2493	181	2	24	24	NUM
cana-2493	181	3	]	]	X
cana-2493	181	4	●	●	PUNCT
cana-2493	181	5	evaluate	evaluate	VERB
cana-2493	181	6	deep	deep	ADJ
cana-2493	181	7	learning	learning	NOUN
cana-2493	181	8	algorithms	algorithm	NOUN
cana-2493	181	9	for	for	ADP
cana-2493	181	10	lung	lung	NOUN
cana-2493	181	11	cancer	cancer	NOUN
cana-2493	181	12	detection	detection	NOUN
cana-2493	181	13	effectiveness	effectiveness	NOUN
cana-2493	181	14	.	.	PUNCT
cana-2493	182	1	●	●	PUNCT
cana-2493	182	2	provide	provide	VERB
cana-2493	182	3	suggestions	suggestion	NOUN
cana-2493	182	4	for	for	ADP
cana-2493	182	5	advancing	advance	VERB
cana-2493	182	6	research	research	NOUN
cana-2493	182	7	and	and	CCONJ
cana-2493	182	8	clinical	clinical	ADJ
cana-2493	182	9	integration	integration	NOUN
cana-2493	182	10	.	.	PUNCT
cana-2493	183	1	●	●	PUNCT
cana-2493	183	2	deep	deep	ADJ
cana-2493	183	3	learning	learning	NOUN
cana-2493	183	4	algorithms	algorithm	NOUN
cana-2493	183	5	,	,	PUNCT
cana-2493	183	6	specifically	specifically	ADV
cana-2493	183	7	convolutional	convolutional	ADJ
cana-2493	183	8	neural	neural	ADJ
cana-2493	183	9	networks	network	NOUN
cana-2493	183	10	(	(	PUNCT
cana-2493	183	11	cnns	cnns	PROPN
cana-2493	183	12	)	)	PUNCT
cana-2493	183	13	●	●	NUM
cana-2493	183	14	keras	keras	PROPN
cana-2493	183	15	development	development	NOUN
cana-2493	183	16	tool	tool	NOUN
cana-2493	183	17	for	for	ADP
cana-2493	183	18	efficient	efficient	ADJ
cana-2493	183	19	task	task	NOUN
cana-2493	183	20	execution	execution	NOUN
cana-2493	183	21	●	●	PUNCT
cana-2493	183	22	high	high	ADJ
cana-2493	183	23	sensitivity	sensitivity	NOUN
cana-2493	183	24	and	and	CCONJ
cana-2493	183	25	accuracy	accuracy	NOUN
cana-2493	183	26	achieved	achieve	VERB
cana-2493	183	27	using	use	VERB
cana-2493	183	28	convolutional	convolutional	ADJ
cana-2493	183	29	neural	neural	ADJ
cana-2493	183	30	networks	network	NOUN
cana-2493	183	31	(	(	PUNCT
cana-2493	183	32	cnns	cnns	PROPN
cana-2493	183	33	)	)	PUNCT
cana-2493	183	34	●	●	NUM
cana-2493	183	35	deep	deep	ADJ
cana-2493	183	36	learning	learning	NOUN
cana-2493	183	37	algorithms	algorithm	NOUN
cana-2493	183	38	show	show	VERB
cana-2493	183	39	potential	potential	NOUN
cana-2493	183	40	in	in	ADP
cana-2493	183	41	revolutionizing	revolutionize	VERB
cana-2493	183	42	lung	lung	NOUN
cana-2493	183	43	cancer	cancer	NOUN
cana-2493	183	44	detection	detection	NOUN
cana-2493	183	45	●	●	NUM
cana-2493	183	46	limited	limit	VERB
cana-2493	183	47	focus	focus	NOUN
cana-2493	183	48	on	on	ADP
cana-2493	183	49	deep	deep	ADJ
cana-2493	183	50	learning	learning	NOUN
cana-2493	183	51	methods	method	NOUN
cana-2493	183	52	other	other	ADJ
cana-2493	183	53	than	than	ADP
cana-2493	183	54	cnn	cnn	PROPN
cana-2493	183	55	.	.	PUNCT
cana-2493	184	1	●	●	PUNCT
cana-2493	184	2	lack	lack	NOUN
cana-2493	184	3	of	of	ADP
cana-2493	184	4	discussion	discussion	NOUN
cana-2493	184	5	on	on	ADP
cana-2493	184	6	challenges	challenge	NOUN
cana-2493	184	7	faced	face	VERB
cana-2493	184	8	in	in	ADP
cana-2493	184	9	implementation	implementation	NOUN
cana-2493	184	10	.	.	PUNCT
cana-2493	185	1	despite	despite	SCONJ
cana-2493	185	2	achieving	achieve	VERB
cana-2493	185	3	promising	promise	VERB
cana-2493	185	4	outcomes	outcome	NOUN
cana-2493	185	5	using	use	VERB
cana-2493	185	6	deep	deep	ADJ
cana-2493	185	7	learning	learning	NOUN
cana-2493	185	8	algorithms	algorithm	NOUN
cana-2493	185	9	to	to	PART
cana-2493	185	10	detect	detect	VERB
cana-2493	185	11	and	and	CCONJ
cana-2493	185	12	segment	segment	NOUN
cana-2493	185	13	lung	lung	NOUN
cana-2493	185	14	cancers	cancer	NOUN
cana-2493	185	15	,	,	PUNCT
cana-2493	185	16	critical	critical	ADJ
cana-2493	185	17	challenges	challenge	NOUN
cana-2493	185	18	still	still	ADV
cana-2493	185	19	need	need	VERB
cana-2493	185	20	addressing	address	VERB
cana-2493	185	21	.	.	PUNCT
cana-2493	186	1	one	one	NUM
cana-2493	186	2	primary	primary	ADJ
cana-2493	186	3	issue	issue	NOUN
cana-2493	186	4	lies	lie	VERB
cana-2493	186	5	in	in	ADP
cana-2493	186	6	the	the	DET
cana-2493	186	7	scarcity	scarcity	NOUN
cana-2493	186	8	of	of	ADP
cana-2493	186	9	large	large	ADJ
cana-2493	186	10	,	,	PUNCT
cana-2493	186	11	highquality	highquality	NOUN
cana-2493	186	12	annotated	annotate	VERB
cana-2493	186	13	datasets	dataset	NOUN
cana-2493	186	14	.	.	PUNCT
cana-2493	187	1	labeling	label	VERB
cana-2493	187	2	medical	medical	ADJ
cana-2493	187	3	images	image	NOUN
cana-2493	187	4	demands	demand	VERB
cana-2493	187	5	expert	expert	NOUN
cana-2493	187	6	time	time	NOUN
cana-2493	187	7	and	and	CCONJ
cana-2493	187	8	knowledge	knowledge	NOUN
cana-2493	187	9	,	,	PUNCT
cana-2493	187	10	limiting	limit	VERB
cana-2493	187	11	available	available	ADJ
cana-2493	187	12	archives	archive	NOUN
cana-2493	187	13	in	in	ADP
cana-2493	187	14	both	both	DET
cana-2493	187	15	breadth	breadth	NOUN
cana-2493	187	16	and	and	CCONJ
cana-2493	187	17	depth	depth	NOUN
cana-2493	187	18	.	.	PUNCT
cana-2493	188	1	this	this	PRON
cana-2493	188	2	holds	hold	VERB
cana-2493	188	3	particularly	particularly	ADV
cana-2493	188	4	true	true	ADJ
cana-2493	188	5	for	for	ADP
cana-2493	188	6	lung	lung	NOUN
cana-2493	188	7	cancer	cancer	NOUN
cana-2493	188	8	,	,	PUNCT
cana-2493	188	9	where	where	SCONJ
cana-2493	188	10	variations	variation	NOUN
cana-2493	188	11	in	in	ADP
cana-2493	188	12	appearance	appearance	NOUN
cana-2493	188	13	and	and	CCONJ
cana-2493	188	14	locale	locale	NOUN
cana-2493	188	15	make	make	AUX
cana-2493	188	16	comprehensively	comprehensively	ADV
cana-2493	188	17	representing	represent	VERB
cana-2493	188	18	all	all	DET
cana-2493	188	19	scenarios	scenario	NOUN
cana-2493	188	20	difficult	difficult	ADJ
cana-2493	188	21	.	.	PUNCT
cana-2493	189	1	moreover	moreover	ADV
cana-2493	189	2	,	,	PUNCT
cana-2493	189	3	sensitive	sensitive	ADJ
cana-2493	189	4	patient	patient	ADJ
cana-2493	189	5	data	datum	NOUN
cana-2493	189	6	complicates	complicate	VERB
cana-2493	189	7	sharing	sharing	NOUN
cana-2493	189	8	and	and	CCONJ
cana-2493	189	9	collaboration	collaboration	NOUN
cana-2493	189	10	.	.	PUNCT
cana-2493	190	1	to	to	PART
cana-2493	190	2	mitigate	mitigate	VERB
cana-2493	190	3	such	such	ADJ
cana-2493	190	4	restrictions	restriction	NOUN
cana-2493	190	5	,	,	PUNCT
cana-2493	190	6	synthetic	synthetic	ADJ
cana-2493	190	7	data	data	NOUN
cana-2493	190	8	generation	generation	NOUN
cana-2493	190	9	using	use	VERB
cana-2493	190	10	generative	generative	ADJ
cana-2493	190	11	adversarial	adversarial	ADJ
cana-2493	190	12	networks	network	NOUN
cana-2493	190	13	and	and	CCONJ
cana-2493	190	14	related	related	ADJ
cana-2493	190	15	techniques	technique	NOUN
cana-2493	190	16	helps	helps	AUX
cana-2493	190	17	augment	augment	VERB
cana-2493	190	18	training	training	NOUN
cana-2493	190	19	data	datum	NOUN
cana-2493	190	20	provided	provide	VERB
cana-2493	190	21	to	to	ADP
cana-2493	190	22	models	model	NOUN
cana-2493	190	23	by	by	ADP
cana-2493	190	24	realistically	realistically	ADV
cana-2493	190	25	modeling	model	VERB
cana-2493	190	26	additional	additional	ADJ
cana-2493	190	27	examples	example	NOUN
cana-2493	190	28	.	.	PUNCT
cana-2493	191	1	however	however	ADV
cana-2493	191	2	,	,	PUNCT
cana-2493	191	3	interpretability	interpretability	NOUN
cana-2493	191	4	issues	issue	NOUN
cana-2493	191	5	with	with	ADP
cana-2493	191	6	deep	deep	ADJ
cana-2493	191	7	learning	learning	NOUN
cana-2493	191	8	models	model	NOUN
cana-2493	191	9	,	,	PUNCT
cana-2493	191	10	notably	notably	ADV
cana-2493	191	11	convolutional	convolutional	ADJ
cana-2493	191	12	networks	network	NOUN
cana-2493	191	13	proven	prove	VERB
cana-2493	191	14	so	so	ADV
cana-2493	191	15	skillful	skillful	ADJ
cana-2493	191	16	in	in	ADP
cana-2493	191	17	lung	lung	NOUN
cana-2493	191	18	cancer	cancer	NOUN
cana-2493	191	19	tasks	task	NOUN
cana-2493	191	20	,	,	PUNCT
cana-2493	191	21	can	can	AUX
cana-2493	191	22	deter	deter	VERB
cana-2493	191	23	clinical	clinical	ADJ
cana-2493	191	24	acceptance	acceptance	NOUN
cana-2493	191	25	where	where	SCONJ
cana-2493	191	26	justification	justification	NOUN
cana-2493	191	27	is	be	AUX
cana-2493	191	28	paramount	paramount	ADJ
cana-2493	191	29	.	.	PUNCT
cana-2493	192	1	black	black	ADJ
cana-2493	192	2	-	-	PUNCT
cana-2493	192	3	box	box	NOUN
cana-2493	192	4	perceptions	perception	NOUN
cana-2493	192	5	of	of	ADP
cana-2493	192	6	such	such	ADJ
cana-2493	192	7	algorithms	algorithm	NOUN
cana-2493	192	8	pose	pose	VERB
cana-2493	192	9	barriers	barrier	NOUN
cana-2493	192	10	.	.	PUNCT
cana-2493	193	1	researchers	researcher	NOUN
cana-2493	193	2	actively	actively	ADV
cana-2493	193	3	seek	seek	VERB
cana-2493	193	4	transparency	transparency	NOUN
cana-2493	193	5	boosts	boost	NOUN
cana-2493	193	6	,	,	PUNCT
cana-2493	193	7	whether	whether	SCONJ
cana-2493	193	8	highlighting	highlight	VERB
cana-2493	193	9	input	input	NOUN
cana-2493	193	10	regions	region	NOUN
cana-2493	193	11	most	most	ADV
cana-2493	193	12	impacting	impact	VERB
cana-2493	193	13	predictions	prediction	NOUN
cana-2493	193	14	through	through	ADP
cana-2493	193	15	attention	attention	NOUN
cana-2493	193	16	mechanisms	mechanism	NOUN
cana-2493	193	17	or	or	CCONJ
cana-2493	193	18	visually	visually	ADV
cana-2493	193	19	mapping	mapping	NOUN
cana-2493	193	20	contribution	contribution	NOUN
cana-2493	193	21	strengths	strength	NOUN
cana-2493	193	22	with	with	ADP
cana-2493	193	23	saliency	saliency	NOUN
cana-2493	193	24	heat	heat	NOUN
cana-2493	193	25	maps	map	NOUN
cana-2493	193	26	.	.	PUNCT
cana-2493	194	1	such	such	ADJ
cana-2493	194	2	explainability	explainability	NOUN
cana-2493	194	3	aids	aid	VERB
cana-2493	194	4	reassure	reassure	VERB
cana-2493	194	5	practitioners	practitioner	NOUN
cana-2493	194	6	and	and	CCONJ
cana-2493	194	7	endorse	endorse	VERB
cana-2493	194	8	dependability	dependability	NOUN
cana-2493	194	9	in	in	ADP
cana-2493	194	10	automating	automate	VERB
cana-2493	194	11	vital	vital	ADJ
cana-2493	194	12	decisions	decision	NOUN
cana-2493	194	13	.	.	PUNCT
cana-2493	195	1	continued	continue	VERB
cana-2493	195	2	progress	progress	NOUN
cana-2493	195	3	moreover	moreover	ADV
cana-2493	195	4	advances	advance	VERB
cana-2493	195	5	knowledge	knowledge	NOUN
cana-2493	195	6	in	in	ADP
cana-2493	195	7	medical	medical	ADJ
cana-2493	195	8	image	image	NOUN
cana-2493	195	9	analysis	analysis	NOUN
cana-2493	195	10	and	and	CCONJ
cana-2493	195	11	benefits	benefit	VERB
cana-2493	195	12	more	more	ADJ
cana-2493	195	13	patients	patient	NOUN
cana-2493	195	14	worldwide[25	worldwide[25	X
cana-2493	195	15	]	]	PUNCT
cana-2493	195	16	.	.	PUNCT
cana-2493	196	1	while	while	SCONJ
cana-2493	196	2	deep	deep	ADJ
cana-2493	196	3	learning	learning	NOUN
cana-2493	196	4	models	model	NOUN
cana-2493	196	5	have	have	AUX
cana-2493	196	6	achieved	achieve	VERB
cana-2493	196	7	impressive	impressive	ADJ
cana-2493	196	8	performance	performance	NOUN
cana-2493	196	9	in	in	ADP
cana-2493	196	10	detecting	detect	VERB
cana-2493	196	11	lung	lung	NOUN
cana-2493	196	12	cancer	cancer	NOUN
cana-2493	196	13	from	from	ADP
cana-2493	196	14	medical	medical	ADJ
cana-2493	196	15	scans	scan	NOUN
cana-2493	196	16	,	,	PUNCT
cana-2493	196	17	their	their	PRON
cana-2493	196	18	application	application	NOUN
cana-2493	196	19	in	in	ADP
cana-2493	196	20	real	real	ADJ
cana-2493	196	21	-	-	PUNCT
cana-2493	196	22	world	world	NOUN
cana-2493	196	23	clinical	clinical	ADJ
cana-2493	196	24	settings	setting	NOUN
cana-2493	196	25	faces	face	VERB
cana-2493	196	26	several	several	ADJ
cana-2493	196	27	unresolved	unresolved	ADJ
cana-2493	196	28	challenges	challenge	NOUN
cana-2493	196	29	.	.	PUNCT
cana-2493	197	1	models	model	NOUN
cana-2493	197	2	trained	train	VERB
cana-2493	197	3	exclusively	exclusively	ADV
cana-2493	197	4	on	on	ADP
cana-2493	197	5	curated	curate	VERB
cana-2493	197	6	datasets	dataset	NOUN
cana-2493	197	7	may	may	AUX
cana-2493	197	8	struggle	struggle	VERB
cana-2493	197	9	to	to	PART
cana-2493	197	10	generalize	generalize	VERB
cana-2493	197	11	to	to	ADP
cana-2493	197	12	the	the	DET
cana-2493	197	13	complexities	complexity	NOUN
cana-2493	197	14	of	of	ADP
cana-2493	197	15	real	real	ADJ
cana-2493	197	16	patient	patient	ADJ
cana-2493	197	17	data	datum	NOUN
cana-2493	197	18	,	,	PUNCT
cana-2493	197	19	which	which	PRON
cana-2493	197	20	is	be	AUX
cana-2493	197	21	often	often	ADV
cana-2493	197	22	marred	mar	VERB
cana-2493	197	23	by	by	ADP
cana-2493	197	24	artifacts	artifact	NOUN
cana-2493	197	25	and	and	CCONJ
cana-2493	197	26	inconsistencies	inconsistency	NOUN
cana-2493	197	27	that	that	PRON
cana-2493	197	28	degrade	degrade	VERB
cana-2493	197	29	diagnostic	diagnostic	ADJ
cana-2493	197	30	accuracy	accuracy	NOUN
cana-2493	197	31	.	.	PUNCT
cana-2493	198	1	researchers	researcher	NOUN
cana-2493	198	2	are	be	AUX
cana-2493	198	3	exploring	explore	VERB
cana-2493	198	4	techniques	technique	NOUN
cana-2493	198	5	like	like	ADP
cana-2493	198	6	adversarial	adversarial	ADJ
cana-2493	198	7	training	training	NOUN
cana-2493	198	8	to	to	PART
cana-2493	198	9	develop	develop	VERB
cana-2493	198	10	models	model	NOUN
cana-2493	198	11	that	that	PRON
cana-2493	198	12	are	be	AUX
cana-2493	198	13	resilient	resilient	ADJ
cana-2493	198	14	to	to	ADP
cana-2493	198	15	various	various	ADJ
cana-2493	198	16	image	image	NOUN
cana-2493	198	17	perturbations	perturbation	NOUN
cana-2493	198	18	,	,	PUNCT
cana-2493	198	19	ensuring	ensure	VERB
cana-2493	198	20	reliable	reliable	ADJ
cana-2493	198	21	outcomes	outcome	NOUN
cana-2493	198	22	across	across	ADP
cana-2493	198	23	diverse	diverse	ADJ
cana-2493	198	24	medical	medical	ADJ
cana-2493	198	25	imaging	imaging	NOUN
cana-2493	198	26	scenarios	scenario	NOUN
cana-2493	198	27	.	.	PUNCT
cana-2493	199	1	at	at	ADP
cana-2493	199	2	the	the	DET
cana-2493	199	3	same	same	ADJ
cana-2493	199	4	time	time	NOUN
cana-2493	199	5	,	,	PUNCT
cana-2493	199	6	simply	simply	ADV
cana-2493	199	7	validating	validate	VERB
cana-2493	199	8	performance	performance	NOUN
cana-2493	199	9	in	in	ADP
cana-2493	199	10	controlled	control	VERB
cana-2493	199	11	research	research	NOUN
cana-2493	199	12	environments	environment	NOUN
cana-2493	199	13	is	be	AUX
cana-2493	199	14	insufficient	insufficient	ADJ
cana-2493	199	15	.	.	PUNCT
cana-2493	200	1	true	true	ADJ
cana-2493	200	2	progress	progress	NOUN
cana-2493	200	3	requires	require	VERB
cana-2493	200	4	seamless	seamless	ADJ
cana-2493	200	5	integration	integration	NOUN
cana-2493	200	6	of	of	ADP
cana-2493	200	7	ai	ai	VERB
cana-2493	200	8	into	into	ADP
cana-2493	200	9	clinical	clinical	ADJ
cana-2493	200	10	workflows	workflow	NOUN
cana-2493	200	11	and	and	CCONJ
cana-2493	200	12	existing	exist	VERB
cana-2493	200	13	infrastructure[16	infrastructure[16	NOUN
cana-2493	200	14	]	]	PUNCT
cana-2493	200	15	.	.	PUNCT
cana-2493	201	1	before	before	ADP
cana-2493	201	2	widespread	widespread	ADJ
cana-2493	201	3	adoption	adoption	NOUN
cana-2493	201	4	,	,	PUNCT
cana-2493	201	5	scalability	scalability	NOUN
cana-2493	201	6	issues	issue	NOUN
cana-2493	201	7	and	and	CCONJ
cana-2493	201	8	obstacles	obstacle	NOUN
cana-2493	201	9	to	to	ADP
cana-2493	201	10	practical	practical	ADJ
cana-2493	201	11	communications	communication	NOUN
cana-2493	201	12	on	on	ADP
cana-2493	201	13	applied	apply	VERB
cana-2493	201	14	nonlinear	nonlinear	ADJ
cana-2493	201	15	analysis	analysis	NOUN
cana-2493	201	16	issn	issn	NOUN
cana-2493	201	17	:	:	PUNCT
cana-2493	201	18	1074	1074	NUM
cana-2493	201	19	-	-	PUNCT
cana-2493	201	20	133x	133x	NUM
cana-2493	201	21	vol	vol	NOUN
cana-2493	201	22	32	32	NUM
cana-2493	201	23	no	no	NOUN
cana-2493	201	24	.	.	PUNCT
cana-2493	202	1	2s	2s	NUM
cana-2493	202	2	(	(	PUNCT
cana-2493	202	3	2025	2025	NUM
cana-2493	202	4	)	)	PUNCT
cana-2493	202	5	554	554	NUM
cana-2493	202	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	202	7	deployment	deployment	NOUN
cana-2493	202	8	must	must	AUX
cana-2493	202	9	be	be	AUX
cana-2493	202	10	addressed	address	VERB
cana-2493	202	11	.	.	PUNCT
cana-2493	203	1	most	most	ADV
cana-2493	203	2	critically	critically	ADV
cana-2493	203	3	,	,	PUNCT
cana-2493	203	4	models	model	NOUN
cana-2493	203	5	need	need	VERB
cana-2493	203	6	rigorous	rigorous	ADJ
cana-2493	203	7	evaluation	evaluation	NOUN
cana-2493	203	8	in	in	ADP
cana-2493	203	9	authentic	authentic	ADJ
cana-2493	203	10	patient	patient	NOUN
cana-2493	203	11	care	care	NOUN
cana-2493	203	12	settings	setting	NOUN
cana-2493	203	13	to	to	PART
cana-2493	203	14	substantiate	substantiate	VERB
cana-2493	203	15	safety	safety	NOUN
cana-2493	203	16	and	and	CCONJ
cana-2493	203	17	efficacy	efficacy	NOUN
cana-2493	203	18	as	as	ADP
cana-2493	203	19	medical	medical	ADJ
cana-2493	203	20	tools	tool	NOUN
cana-2493	203	21	.	.	PUNCT
cana-2493	204	1	policymakers	policymaker	NOUN
cana-2493	204	2	as	as	ADV
cana-2493	204	3	well	well	ADV
cana-2493	204	4	are	be	AUX
cana-2493	204	5	working	work	VERB
cana-2493	204	6	to	to	PART
cana-2493	204	7	establish	establish	VERB
cana-2493	204	8	ethical	ethical	ADJ
cana-2493	204	9	and	and	CCONJ
cana-2493	204	10	regulatory	regulatory	ADJ
cana-2493	204	11	standards	standard	NOUN
cana-2493	204	12	governing	govern	VERB
cana-2493	204	13	ai	ai	VERB
cana-2493	204	14	/	/	SYM
cana-2493	204	15	ml	ml	NOUN
cana-2493	204	16	use	use	NOUN
cana-2493	204	17	in	in	ADP
cana-2493	204	18	healthcare	healthcare	NOUN
cana-2493	204	19	.	.	PUNCT
cana-2493	205	1	only	only	ADV
cana-2493	205	2	by	by	ADP
cana-2493	205	3	conquering	conquer	VERB
cana-2493	205	4	real	real	ADJ
cana-2493	205	5	-	-	PUNCT
cana-2493	205	6	world	world	NOUN
cana-2493	205	7	implementation	implementation	NOUN
cana-2493	205	8	hurdles	hurdle	NOUN
cana-2493	205	9	with	with	ADP
cana-2493	205	10	thorough	thorough	ADJ
cana-2493	205	11	clinical	clinical	ADJ
cana-2493	205	12	validation	validation	NOUN
cana-2493	205	13	will	will	AUX
cana-2493	205	14	the	the	DET
cana-2493	205	15	promise	promise	NOUN
cana-2493	205	16	of	of	ADP
cana-2493	205	17	deep	deep	ADJ
cana-2493	205	18	learning	learning	NOUN
cana-2493	205	19	for	for	ADP
cana-2493	205	20	lung	lung	NOUN
cana-2493	205	21	cancer	cancer	NOUN
cana-2493	205	22	be	be	AUX
cana-2493	205	23	realized	realize	VERB
cana-2493	205	24	to	to	PART
cana-2493	205	25	benefit	benefit	VERB
cana-2493	205	26	patients	patient	NOUN
cana-2493	205	27	.	.	PUNCT
cana-2493	206	1	in	in	ADP
cana-2493	206	2	summary	summary	NOUN
cana-2493	206	3	,	,	PUNCT
cana-2493	206	4	deep	deep	ADJ
cana-2493	206	5	learning	learning	NOUN
cana-2493	206	6	techniques	technique	NOUN
cana-2493	206	7	applied	apply	VERB
cana-2493	206	8	to	to	ADP
cana-2493	206	9	lung	lung	NOUN
cana-2493	206	10	cancer	cancer	NOUN
cana-2493	206	11	screening	screening	NOUN
cana-2493	206	12	have	have	AUX
cana-2493	206	13	advanced	advance	VERB
cana-2493	206	14	tremendously	tremendously	ADV
cana-2493	206	15	in	in	ADP
cana-2493	206	16	recent	recent	ADJ
cana-2493	206	17	years	year	NOUN
cana-2493	206	18	.	.	PUNCT
cana-2493	207	1	convolutional	convolutional	ADJ
cana-2493	207	2	neural	neural	ADJ
cana-2493	207	3	networks	network	NOUN
cana-2493	207	4	,	,	PUNCT
cana-2493	207	5	multi	multi	ADJ
cana-2493	207	6	-	-	ADJ
cana-2493	207	7	scale	scale	ADJ
cana-2493	207	8	architectures	architecture	NOUN
cana-2493	207	9	and	and	CCONJ
cana-2493	207	10	unified	unified	ADJ
cana-2493	207	11	detectionsegmentation	detectionsegmentation	NOUN
cana-2493	207	12	models	model	NOUN
cana-2493	207	13	exhibit	exhibit	VERB
cana-2493	207	14	substantial	substantial	ADJ
cana-2493	207	15	promise	promise	NOUN
cana-2493	207	16	.	.	PUNCT
cana-2493	208	1	notwithstanding	notwithstanding	ADP
cana-2493	208	2	such	such	ADJ
cana-2493	208	3	progress	progress	NOUN
cana-2493	208	4	,	,	PUNCT
cana-2493	208	5	difficulties	difficulty	NOUN
cana-2493	208	6	persist	persist	VERB
cana-2493	208	7	regarding	regard	VERB
cana-2493	208	8	data	data	NOUN
cana-2493	208	9	availability	availability	NOUN
cana-2493	208	10	,	,	PUNCT
cana-2493	208	11	interpretability	interpretability	NOUN
cana-2493	208	12	of	of	ADP
cana-2493	208	13	results	result	NOUN
cana-2493	208	14	,	,	PUNCT
cana-2493	208	15	robustness	robustness	NOUN
cana-2493	208	16	and	and	CCONJ
cana-2493	208	17	clinical	clinical	ADJ
cana-2493	208	18	integration	integration	NOUN
cana-2493	208	19	.	.	PUNCT
cana-2493	209	1	as	as	ADP
cana-2493	209	2	the	the	DET
cana-2493	209	3	discipline	discipline	NOUN
cana-2493	209	4	matures	mature	NOUN
cana-2493	209	5	,	,	PUNCT
cana-2493	209	6	deep	deep	ADJ
cana-2493	209	7	learning	learning	NOUN
cana-2493	209	8	may	may	AUX
cana-2493	209	9	radically	radically	ADV
cana-2493	209	10	transform	transform	VERB
cana-2493	209	11	lung	lung	NOUN
cana-2493	209	12	cancer	cancer	NOUN
cana-2493	209	13	diagnosis	diagnosis	NOUN
cana-2493	209	14	and	and	CCONJ
cana-2493	209	15	therapy	therapy	NOUN
cana-2493	209	16	.	.	PUNCT
cana-2493	210	1	powerful	powerful	ADJ
cana-2493	210	2	tools	tool	NOUN
cana-2493	210	3	could	could	AUX
cana-2493	210	4	empower	empower	VERB
cana-2493	210	5	doctors	doctor	NOUN
cana-2493	210	6	to	to	PART
cana-2493	210	7	more	more	ADV
cana-2493	210	8	accurately	accurately	ADV
cana-2493	210	9	identify	identify	VERB
cana-2493	210	10	small	small	ADJ
cana-2493	210	11	lesions	lesion	NOUN
cana-2493	210	12	,	,	PUNCT
cana-2493	210	13	differentiate	differentiate	VERB
cana-2493	210	14	suspicious	suspicious	ADJ
cana-2493	210	15	nodules	nodule	NOUN
cana-2493	210	16	and	and	CCONJ
cana-2493	210	17	track	track	VERB
cana-2493	210	18	tumor	tumor	NOUN
cana-2493	210	19	evolution	evolution	NOUN
cana-2493	210	20	with	with	ADP
cana-2493	210	21	scans	scan	NOUN
cana-2493	210	22	.	.	PUNCT
cana-2493	211	1	multidisciplinary	multidisciplinary	ADJ
cana-2493	211	2	teams	team	NOUN
cana-2493	211	3	may	may	AUX
cana-2493	211	4	then	then	ADV
cana-2493	211	5	collaborate	collaborate	VERB
cana-2493	211	6	using	use	VERB
cana-2493	211	7	such	such	ADJ
cana-2493	211	8	insights	insight	NOUN
cana-2493	211	9	to	to	PART
cana-2493	211	10	customize	customize	VERB
cana-2493	211	11	treatment	treatment	NOUN
cana-2493	211	12	plans	plan	NOUN
cana-2493	211	13	tailored	tailor	VERB
cana-2493	211	14	for	for	ADP
cana-2493	211	15	each	each	DET
cana-2493	211	16	unique	unique	ADJ
cana-2493	211	17	patient	patient	NOUN
cana-2493	211	18	,	,	PUNCT
cana-2493	211	19	maximizing	maximize	VERB
cana-2493	211	20	chances	chance	NOUN
cana-2493	211	21	of	of	ADP
cana-2493	211	22	favorable	favorable	ADJ
cana-2493	211	23	outcomes	outcome	NOUN
cana-2493	211	24	.	.	PUNCT
cana-2493	212	1	continued	continue	VERB
cana-2493	212	2	progress	progress	NOUN
cana-2493	212	3	depends	depend	VERB
cana-2493	212	4	on	on	ADP
cana-2493	212	5	collaborative	collaborative	ADJ
cana-2493	212	6	efforts	effort	NOUN
cana-2493	212	7	to	to	PART
cana-2493	212	8	address	address	VERB
cana-2493	212	9	present	present	ADJ
cana-2493	212	10	limitations	limitation	NOUN
cana-2493	212	11	and	and	CCONJ
cana-2493	212	12	fully	fully	ADV
cana-2493	212	13	realize	realize	VERB
cana-2493	212	14	the	the	DET
cana-2493	212	15	future	future	ADJ
cana-2493	212	16	potential	potential	NOUN
cana-2493	212	17	of	of	ADP
cana-2493	212	18	artificial	artificial	ADJ
cana-2493	212	19	intelligence	intelligence	NOUN
cana-2493	212	20	to	to	PART
cana-2493	212	21	benefit	benefit	VERB
cana-2493	212	22	humanity[17	humanity[17	PROPN
cana-2493	212	23	]	]	PUNCT
cana-2493	212	24	.	.	PUNCT
cana-2493	213	1	2	2	X
cana-2493	213	2	.	.	NUM
cana-2493	213	3	proposed	propose	VERB
cana-2493	213	4	methodology	methodology	NOUN
cana-2493	213	5	a	a	PRON
cana-2493	213	6	in	in	ADP
cana-2493	213	7	this	this	DET
cana-2493	213	8	paper	paper	NOUN
cana-2493	213	9	,	,	PUNCT
cana-2493	213	10	we	we	PRON
cana-2493	213	11	proposed	propose	VERB
cana-2493	213	12	an	an	DET
cana-2493	213	13	approach	approach	NOUN
cana-2493	213	14	to	to	ADP
cana-2493	213	15	lung	lung	NOUN
cana-2493	213	16	cancer	cancer	NOUN
cana-2493	213	17	identification	identification	NOUN
cana-2493	213	18	using	use	VERB
cana-2493	213	19	deep	deep	ADJ
cana-2493	213	20	attention	attention	NOUN
cana-2493	213	21	and	and	CCONJ
cana-2493	213	22	local	local	ADJ
cana-2493	213	23	average	average	ADJ
cana-2493	213	24	pooling	pooling	NOUN
cana-2493	213	25	in	in	ADP
cana-2493	213	26	a	a	DET
cana-2493	213	27	cascade	cascade	NOUN
cana-2493	213	28	framework	framework	NOUN
cana-2493	213	29	.	.	PUNCT
cana-2493	214	1	this	this	PRON
cana-2493	214	2	is	be	AUX
cana-2493	214	3	an	an	DET
cana-2493	214	4	attempt	attempt	NOUN
cana-2493	214	5	to	to	PART
cana-2493	214	6	overcome	overcome	VERB
cana-2493	214	7	the	the	DET
cana-2493	214	8	limitations	limitation	NOUN
cana-2493	214	9	of	of	ADP
cana-2493	214	10	classic	classic	ADJ
cana-2493	214	11	convolutional	convolutional	ADJ
cana-2493	214	12	neural	neural	ADJ
cana-2493	214	13	networks	network	NOUN
cana-2493	214	14	(	(	PUNCT
cana-2493	214	15	cnns	cnns	PROPN
cana-2493	214	16	)	)	PUNCT
cana-2493	214	17	when	when	SCONJ
cana-2493	214	18	facing	face	VERB
cana-2493	214	19	sophisticated	sophisticated	ADJ
cana-2493	214	20	patterns	pattern	NOUN
cana-2493	214	21	in	in	ADP
cana-2493	214	22	medical	medical	ADJ
cana-2493	214	23	images	image	NOUN
cana-2493	214	24	such	such	ADJ
cana-2493	214	25	as	as	ADP
cana-2493	214	26	lung	lung	NOUN
cana-2493	214	27	cancer	cancer	NOUN
cana-2493	214	28	imagery	imagery	NOUN
cana-2493	214	29	on	on	ADP
cana-2493	214	30	chest	chest	NOUN
cana-2493	214	31	x	x	NOUN
cana-2493	214	32	-	-	NOUN
cana-2493	214	33	ray	ray	NOUN
cana-2493	214	34	.	.	PUNCT
cana-2493	215	1	in	in	ADP
cana-2493	215	2	this	this	DET
cana-2493	215	3	section	section	NOUN
cana-2493	215	4	,	,	PUNCT
cana-2493	215	5	we	we	PRON
cana-2493	215	6	explain	explain	VERB
cana-2493	215	7	the	the	DET
cana-2493	215	8	different	different	ADJ
cana-2493	215	9	components	component	NOUN
cana-2493	215	10	of	of	ADP
cana-2493	215	11	the	the	DET
cana-2493	215	12	framework	framework	NOUN
cana-2493	215	13	which	which	PRON
cana-2493	215	14	will	will	AUX
cana-2493	215	15	contain	contain	VERB
cana-2493	215	16	using	use	VERB
cana-2493	215	17	the	the	DET
cana-2493	215	18	attention	attention	NOUN
cana-2493	215	19	mechanism	mechanism	NOUN
cana-2493	215	20	,	,	PUNCT
cana-2493	215	21	cross	cross	ADJ
cana-2493	215	22	-	-	ADJ
cana-2493	215	23	average	average	ADJ
cana-2493	215	24	pooling	pooling	NOUN
cana-2493	215	25	and	and	CCONJ
cana-2493	215	26	how	how	SCONJ
cana-2493	215	27	to	to	PART
cana-2493	215	28	insert	insert	VERB
cana-2493	215	29	them	they	PRON
cana-2493	215	30	in	in	ADP
cana-2493	215	31	a	a	DET
cana-2493	215	32	deep	deep	ADJ
cana-2493	215	33	learning	learning	NOUN
cana-2493	215	34	model	model	NOUN
cana-2493	215	35	as	as	ADV
cana-2493	215	36	well	well	ADV
cana-2493	215	37	as	as	ADP
cana-2493	215	38	the	the	DET
cana-2493	215	39	evaluation	evaluation	NOUN
cana-2493	215	40	approach	approach	NOUN
cana-2493	215	41	to	to	PART
cana-2493	215	42	prove	prove	VERB
cana-2493	215	43	its	its	PRON
cana-2493	215	44	robustness	robustness	NOUN
cana-2493	215	45	.	.	PUNCT
cana-2493	216	1	figure	figure	NOUN
cana-2493	216	2	2	2	NUM
cana-2493	216	3	.	.	X
cana-2493	217	1	flowchart	flowchart	NOUN
cana-2493	217	2	of	of	ADP
cana-2493	217	3	proposed	propose	VERB
cana-2493	217	4	method	method	NOUN
cana-2493	217	5	communications	communication	NOUN
cana-2493	217	6	on	on	ADP
cana-2493	217	7	applied	apply	VERB
cana-2493	217	8	nonlinear	nonlinear	ADJ
cana-2493	217	9	analysis	analysis	NOUN
cana-2493	217	10	issn	issn	NOUN
cana-2493	217	11	:	:	PUNCT
cana-2493	217	12	1074	1074	NUM
cana-2493	217	13	-	-	PUNCT
cana-2493	217	14	133x	133x	NUM
cana-2493	217	15	vol	vol	NOUN
cana-2493	217	16	32	32	NUM
cana-2493	217	17	no	no	NOUN
cana-2493	217	18	.	.	PUNCT
cana-2493	218	1	2s	2s	NUM
cana-2493	218	2	(	(	PUNCT
cana-2493	218	3	2025	2025	NUM
cana-2493	218	4	)	)	PUNCT
cana-2493	218	5	555	555	NUM
cana-2493	218	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	218	7	1	1	NUM
cana-2493	218	8	.	.	PUNCT
cana-2493	218	9	attention	attention	NOUN
cana-2493	218	10	-	-	PUNCT
cana-2493	218	11	based	base	VERB
cana-2493	218	12	feature	feature	NOUN
cana-2493	218	13	extraction	extraction	NOUN
cana-2493	218	14	summary	summary	NOUN
cana-2493	218	15	a	a	DET
cana-2493	218	16	majority	majority	NOUN
cana-2493	218	17	of	of	ADP
cana-2493	218	18	the	the	DET
cana-2493	218	19	state	state	NOUN
cana-2493	218	20	-	-	PUNCT
cana-2493	218	21	of	of	ADP
cana-2493	218	22	-	-	PUNCT
cana-2493	218	23	the	the	DET
cana-2493	218	24	-	-	PUNCT
cana-2493	218	25	art	art	NOUN
cana-2493	218	26	methods	method	NOUN
cana-2493	218	27	based	base	VERB
cana-2493	218	28	on	on	ADP
cana-2493	218	29	cnns	cnn	NOUN
cana-2493	218	30	have	have	AUX
cana-2493	218	31	been	be	AUX
cana-2493	218	32	applied	apply	VERB
cana-2493	218	33	to	to	ADP
cana-2493	218	34	medical	medical	ADJ
cana-2493	218	35	images	image	NOUN
cana-2493	218	36	,	,	PUNCT
cana-2493	218	37	including	include	VERB
cana-2493	218	38	lung	lung	NOUN
cana-2493	218	39	cancer	cancer	NOUN
cana-2493	218	40	images	image	NOUN
cana-2493	218	41	however	however	ADV
cana-2493	218	42	they	they	PRON
cana-2493	218	43	are	be	AUX
cana-2493	218	44	all	all	PRON
cana-2493	218	45	challenged	challenge	VERB
cana-2493	218	46	by	by	ADP
cana-2493	218	47	the	the	DET
cana-2493	218	48	subtleties	subtlety	NOUN
cana-2493	218	49	and	and	CCONJ
cana-2493	218	50	high	high	ADV
cana-2493	218	51	-	-	PUNCT
cana-2493	218	52	contextualized	contextualize	VERB
cana-2493	218	53	nature	nature	NOUN
cana-2493	218	54	of	of	ADP
cana-2493	218	55	patterns	pattern	NOUN
cana-2493	218	56	in	in	ADP
cana-2493	218	57	such	such	ADJ
cana-2493	218	58	medical	medical	ADJ
cana-2493	218	59	cases	case	NOUN
cana-2493	218	60	.	.	PUNCT
cana-2493	219	1	this	this	PRON
cana-2493	219	2	occurs	occur	VERB
cana-2493	219	3	because	because	SCONJ
cana-2493	219	4	traditional	traditional	ADJ
cana-2493	219	5	cnns	cnn	NOUN
cana-2493	219	6	have	have	VERB
cana-2493	219	7	a	a	DET
cana-2493	219	8	constant	constant	ADJ
cana-2493	219	9	tunnel	tunnel	NOUN
cana-2493	219	10	vision	vision	NOUN
cana-2493	219	11	for	for	ADP
cana-2493	219	12	entire	entire	ADJ
cana-2493	219	13	image	image	NOUN
cana-2493	219	14	,	,	PUNCT
cana-2493	219	15	where	where	SCONJ
cana-2493	219	16	much	much	ADJ
cana-2493	219	17	of	of	ADP
cana-2493	219	18	the	the	DET
cana-2493	219	19	image	image	NOUN
cana-2493	219	20	(	(	PUNCT
cana-2493	219	21	e.	e.	PROPN
cana-2493	219	22	g.	g.	PROPN
cana-2493	219	23	,	,	PUNCT
cana-2493	219	24	normal	normal	ADJ
cana-2493	219	25	lung	lung	NOUN
cana-2493	219	26	tissues	tissue	NOUN
cana-2493	219	27	)	)	PUNCT
cana-2493	219	28	can	can	AUX
cana-2493	219	29	be	be	AUX
cana-2493	219	30	many	many	ADJ
cana-2493	219	31	times	time	NOUN
cana-2493	219	32	larger	large	ADJ
cana-2493	219	33	than	than	ADP
cana-2493	219	34	subtle	subtle	ADJ
cana-2493	219	35	cancer	cancer	NOUN
cana-2493	219	36	traces	trace	NOUN
cana-2493	219	37	in	in	ADP
cana-2493	219	38	size	size	NOUN
cana-2493	219	39	in	in	ADP
cana-2493	219	40	this	this	DET
cana-2493	219	41	approach	approach	NOUN
cana-2493	219	42	we	we	PRON
cana-2493	219	43	introduce	introduce	VERB
cana-2493	219	44	an	an	DET
cana-2493	219	45	attention	attention	NOUN
cana-2493	219	46	mechanism	mechanism	NOUN
cana-2493	219	47	to	to	PART
cana-2493	219	48	address	address	VERB
cana-2493	219	49	the	the	DET
cana-2493	219	50	above	above	ADJ
cana-2493	219	51	problem	problem	NOUN
cana-2493	219	52	within	within	ADP
cana-2493	219	53	the	the	DET
cana-2493	219	54	deep	deep	ADJ
cana-2493	219	55	learning	learning	NOUN
cana-2493	219	56	framework	framework	NOUN
cana-2493	219	57	.	.	PUNCT
cana-2493	220	1	algorithm	algorithm	NOUN
cana-2493	220	2	1	1	NUM
cana-2493	220	3	:	:	PUNCT
cana-2493	220	4	attention	attention	NOUN
cana-2493	220	5	-	-	PUNCT
cana-2493	220	6	based	base	VERB
cana-2493	220	7	feature	feature	NOUN
cana-2493	220	8	extraction	extraction	NOUN
cana-2493	220	9	input	input	NOUN
cana-2493	220	10	:	:	PUNCT
cana-2493	220	11	input	input	NOUN
cana-2493	220	12	image	image	NOUN
cana-2493	220	13	𝐼	𝐼	PROPN
cana-2493	220	14	,	,	PUNCT
cana-2493	220	15	convolutional	convolutional	ADJ
cana-2493	220	16	layers	layer	NOUN
cana-2493	220	17	{	{	PUNCT
cana-2493	220	18	𝐾𝑖	𝐾𝑖	PROPN
cana-2493	220	19	,	,	PUNCT
cana-2493	220	20	𝑏𝑖	𝑏𝑖	ADP
cana-2493	220	21	}	}	PUNCT
cana-2493	220	22	,	,	PUNCT
cana-2493	220	23	attention	attention	NOUN
cana-2493	220	24	mechanism	mechanism	NOUN
cana-2493	220	25	parameters	parameter	NOUN
cana-2493	220	26	output	output	VERB
cana-2493	220	27	:	:	PUNCT
cana-2493	220	28	weighted	weight	VERB
cana-2493	220	29	feature	feature	NOUN
cana-2493	220	30	map	map	NOUN
cana-2493	220	31	𝐹′	𝐹′	X
cana-2493	220	32	1	1	X
cana-2493	220	33	.	.	X
cana-2493	221	1	initialize	initialize	NOUN
cana-2493	221	2	:	:	PUNCT
cana-2493	221	3	load	load	NOUN
cana-2493	221	4	input	input	NOUN
cana-2493	221	5	image	image	NOUN
cana-2493	221	6	𝐼.	𝐼.	PROPN
cana-2493	221	7	2	2	NUM
cana-2493	221	8	.	.	PUNCT
cana-2493	221	9	convolutional	convolutional	ADJ
cana-2493	221	10	layer	layer	NOUN
cana-2493	221	11	:	:	PUNCT
cana-2493	221	12	apply	apply	VERB
cana-2493	221	13	convolution	convolution	NOUN
cana-2493	221	14	operations	operation	NOUN
cana-2493	221	15	using	use	VERB
cana-2493	221	16	kernels	kernel	NOUN
cana-2493	221	17	𝐾𝑖	𝐾𝑖	PROPN
cana-2493	221	18	to	to	PART
cana-2493	221	19	extract	extract	VERB
cana-2493	221	20	feature	feature	NOUN
cana-2493	221	21	map	map	NOUN
cana-2493	221	22	𝐹𝑖	𝐹𝑖	NOUN
cana-2493	221	23	for	for	ADP
cana-2493	221	24	each	each	DET
cana-2493	221	25	layer	layer	NOUN
cana-2493	221	26	:	:	PUNCT
cana-2493	222	1	𝐹𝑖	𝐹𝑖	PROPN
cana-2493	222	2	=	=	PUNCT
cana-2493	222	3	𝐼	𝐼	PROPN
cana-2493	222	4	∗	∗	NOUN
cana-2493	222	5	𝐾𝑖	𝐾𝑖	PROPN
cana-2493	223	1	+	+	NUM
cana-2493	223	2	𝑏𝑖	𝑏𝑖	PROPN
cana-2493	223	3	3	3	NUM
cana-2493	223	4	.	.	PUNCT
cana-2493	223	5	attention	attention	NOUN
cana-2493	223	6	map	map	NOUN
cana-2493	223	7	:	:	PUNCT
cana-2493	223	8	generate	generate	VERB
cana-2493	223	9	attention	attention	NOUN
cana-2493	223	10	scores	score	NOUN
cana-2493	223	11	𝑠𝑖𝑗	𝑠𝑖𝑗	PROPN
cana-2493	223	12	for	for	ADP
cana-2493	223	13	each	each	DET
cana-2493	223	14	spatial	spatial	ADJ
cana-2493	223	15	location	location	NOUN
cana-2493	223	16	in	in	ADP
cana-2493	223	17	𝐹𝑖.	𝐹𝑖.	PROPN
cana-2493	223	18	4	4	NUM
cana-2493	223	19	.	.	PUNCT
cana-2493	223	20	softmax	softmax	NOUN
cana-2493	223	21	normalization	normalization	NOUN
cana-2493	223	22	:	:	PUNCT
cana-2493	223	23	compute	compute	NOUN
cana-2493	223	24	attention	attention	NOUN
cana-2493	223	25	map	map	NOUN
cana-2493	223	26	𝐴𝑖𝑗	𝐴𝑖𝑗	PROPN
cana-2493	223	27	using	use	VERB
cana-2493	223	28	:	:	PUNCT
cana-2493	223	29	𝐴𝑖𝑗	𝐴𝑖𝑗	PROPN
cana-2493	223	30	=	=	SYM
cana-2493	223	31	𝑒𝑥𝑝(𝑠𝑖𝑗	𝑒𝑥𝑝(𝑠𝑖𝑗	PROPN
cana-2493	223	32	)	)	PUNCT
cana-2493	224	1	∑𝑁	∑𝑁	PROPN
cana-2493	224	2	𝑘=1	𝑘=1	PUNCT
cana-2493	224	3	𝑒𝑥𝑝(𝑠𝑖𝑘	𝑒𝑥𝑝(𝑠𝑖𝑘	NOUN
cana-2493	224	4	)	)	PUNCT
cana-2493	224	5	5	5	NUM
cana-2493	224	6	.	.	PUNCT
cana-2493	224	7	weighted	weight	VERB
cana-2493	224	8	feature	feature	NOUN
cana-2493	224	9	map	map	NOUN
cana-2493	224	10	:	:	PUNCT
cana-2493	224	11	multiply	multiply	VERB
cana-2493	224	12	the	the	DET
cana-2493	224	13	attention	attention	NOUN
cana-2493	224	14	map	map	NOUN
cana-2493	224	15	𝐴	𝐴	PROPN
cana-2493	224	16	with	with	ADP
cana-2493	224	17	the	the	DET
cana-2493	224	18	feature	feature	NOUN
cana-2493	224	19	map	map	NOUN
cana-2493	224	20	𝐹	𝐹	PRON
cana-2493	224	21	to	to	PART
cana-2493	224	22	obtain	obtain	VERB
cana-2493	224	23	the	the	DET
cana-2493	224	24	weighted	weight	VERB
cana-2493	224	25	feature	feature	NOUN
cana-2493	224	26	map	map	NOUN
cana-2493	224	27	𝐹′	𝐹′	VERB
cana-2493	224	28	:	:	PUNCT
cana-2493	225	1	𝐹𝑖𝑗	𝐹𝑖𝑗	NOUN
cana-2493	225	2	′	′	NUM
cana-2493	225	3	=	=	PUNCT
cana-2493	226	1	𝐴𝑖𝑗	𝐴𝑖𝑗	NUM
cana-2493	226	2	×	×	NOUN
cana-2493	226	3	𝐹𝑖𝑗	𝐹𝑖𝑗	NUM
cana-2493	226	4	6	6	NUM
cana-2493	226	5	.	.	PUNCT
cana-2493	226	6	return	return	NOUN
cana-2493	226	7	:	:	PUNCT
cana-2493	226	8	the	the	DET
cana-2493	226	9	weighted	weight	VERB
cana-2493	226	10	feature	feature	NOUN
cana-2493	226	11	map	map	NOUN
cana-2493	226	12	𝐹′	𝐹′	X
cana-2493	226	13	for	for	ADP
cana-2493	226	14	further	further	ADJ
cana-2493	226	15	processing	processing	NOUN
cana-2493	226	16	in	in	ADP
cana-2493	226	17	the	the	DET
cana-2493	226	18	model	model	NOUN
cana-2493	226	19	.	.	PUNCT
cana-2493	227	1	attention	attention	NOUN
cana-2493	227	2	mechanism	mechanism	NOUN
cana-2493	227	3	:	:	PUNCT
cana-2493	227	4	the	the	DET
cana-2493	227	5	principle	principle	NOUN
cana-2493	227	6	of	of	ADP
cana-2493	227	7	attention	attention	NOUN
cana-2493	227	8	mechanism	mechanism	NOUN
cana-2493	227	9	originates	originate	NOUN
cana-2493	227	10	from	from	ADP
cana-2493	227	11	the	the	DET
cana-2493	227	12	behavior	behavior	NOUN
cana-2493	227	13	of	of	ADP
cana-2493	227	14	human	human	ADJ
cana-2493	227	15	visual	visual	ADJ
cana-2493	227	16	attention	attention	NOUN
cana-2493	227	17	as	as	SCONJ
cana-2493	227	18	it	it	PRON
cana-2493	227	19	helps	help	VERB
cana-2493	227	20	to	to	PART
cana-2493	227	21	focus	focus	VERB
cana-2493	227	22	on	on	ADP
cana-2493	227	23	useful	useful	ADJ
cana-2493	227	24	information	information	NOUN
cana-2493	227	25	parts	part	NOUN
cana-2493	227	26	(	(	PUNCT
cana-2493	227	27	in	in	ADP
cana-2493	227	28	this	this	DET
cana-2493	227	29	scenario	scenario	NOUN
cana-2493	227	30	,	,	PUNCT
cana-2493	227	31	a	a	DET
cana-2493	227	32	chest	chest	NOUN
cana-2493	227	33	x	x	NOUN
cana-2493	227	34	-	-	NOUN
cana-2493	227	35	ray	ray	NOUN
cana-2493	227	36	image	image	NOUN
cana-2493	227	37	)	)	PUNCT
cana-2493	227	38	and	and	CCONJ
cana-2493	227	39	thus	thus	ADV
cana-2493	227	40	reduces	reduce	VERB
cana-2493	227	41	the	the	DET
cana-2493	227	42	impact	impact	NOUN
cana-2493	227	43	of	of	ADP
cana-2493	227	44	irrelevant	irrelevant	ADJ
cana-2493	227	45	regions	region	NOUN
cana-2493	227	46	.	.	PUNCT
cana-2493	228	1	for	for	ADP
cana-2493	228	2	lung	lung	NOUN
cana-2493	228	3	cancer	cancer	NOUN
cana-2493	228	4	detection	detection	NOUN
cana-2493	228	5	,	,	PUNCT
cana-2493	228	6	the	the	DET
cana-2493	228	7	attention	attention	NOUN
cana-2493	228	8	mechanism	mechanism	NOUN
cana-2493	228	9	focuses	focus	VERB
cana-2493	228	10	on	on	ADP
cana-2493	228	11	those	those	DET
cana-2493	228	12	regions	region	NOUN
cana-2493	228	13	of	of	ADP
cana-2493	228	14	the	the	DET
cana-2493	228	15	lung	lung	NOUN
cana-2493	228	16	images	image	NOUN
cana-2493	228	17	that	that	PRON
cana-2493	228	18	are	be	AUX
cana-2493	228	19	important	important	ADJ
cana-2493	228	20	to	to	PART
cana-2493	228	21	highlight	highlight	VERB
cana-2493	228	22	in	in	ADP
cana-2493	228	23	infected	infected	ADJ
cana-2493	228	24	area	area	NOUN
cana-2493	228	25	only	only	ADV
cana-2493	228	26	and	and	CCONJ
cana-2493	228	27	separate	separate	VERB
cana-2493	228	28	them	they	PRON
cana-2493	228	29	from	from	ADP
cana-2493	228	30	other	other	ADJ
cana-2493	228	31	parts	part	NOUN
cana-2493	228	32	of	of	ADP
cana-2493	228	33	lungs	lung	NOUN
cana-2493	228	34	as	as	ADP
cana-2493	228	35	noise	noise	NOUN
cana-2493	228	36	.	.	PUNCT
cana-2493	229	1	this	this	DET
cana-2493	229	2	mechanism	mechanism	NOUN
cana-2493	229	3	allows	allow	VERB
cana-2493	229	4	the	the	DET
cana-2493	229	5	model	model	NOUN
cana-2493	229	6	to	to	ADP
cana-2493	229	7	:	:	PUNCT
cana-2493	229	8	𝐹𝑖	𝐹𝑖	PROPN
cana-2493	229	9	=	=	PUNCT
cana-2493	229	10	𝐼	𝐼	PROPN
cana-2493	229	11	∗	∗	NOUN
cana-2493	230	1	𝐾𝑖	𝐾𝑖	PRON
cana-2493	230	2	+	+	PUNCT
cana-2493	230	3	𝑏𝑖	𝑏𝑖	AUX
cana-2493	230	4	find	find	VERB
cana-2493	230	5	the	the	DET
cana-2493	230	6	characteristic	characteristic	ADJ
cana-2493	230	7	features	feature	NOUN
cana-2493	230	8	of	of	ADP
cana-2493	230	9	lung	lung	NOUN
cana-2493	230	10	cancer	cancer	NOUN
cana-2493	230	11	and	and	CCONJ
cana-2493	230	12	look	look	VERB
cana-2493	230	13	for	for	ADP
cana-2493	230	14	areas	area	NOUN
cana-2493	230	15	of	of	ADP
cana-2493	230	16	abnormal	abnormal	ADJ
cana-2493	230	17	opacities	opacity	NOUN
cana-2493	230	18	or	or	CCONJ
cana-2493	230	19	textures	texture	NOUN
cana-2493	230	20	.	.	PUNCT
cana-2493	231	1	lower	lower	VERB
cana-2493	231	2	the	the	DET
cana-2493	231	3	importance	importance	NOUN
cana-2493	231	4	of	of	ADP
cana-2493	231	5	irrelevant	irrelevant	ADJ
cana-2493	231	6	areas	area	NOUN
cana-2493	231	7	in	in	ADP
cana-2493	231	8	the	the	DET
cana-2493	231	9	image	image	NOUN
cana-2493	231	10	keeping	keep	VERB
cana-2493	231	11	distraction	distraction	NOUN
cana-2493	231	12	at	at	ADP
cana-2493	231	13	its	its	PRON
cana-2493	231	14	minimum	minimum	NOUN
cana-2493	231	15	and	and	CCONJ
cana-2493	231	16	allowing	allow	VERB
cana-2493	231	17	for	for	ADP
cana-2493	231	18	more	more	ADV
cana-2493	231	19	meaningful	meaningful	ADJ
cana-2493	231	20	patterns	pattern	NOUN
cana-2493	231	21	to	to	PART
cana-2493	231	22	be	be	AUX
cana-2493	231	23	detected	detect	VERB
cana-2493	231	24	by	by	ADP
cana-2493	231	25	the	the	DET
cana-2493	231	26	model	model	NOUN
cana-2493	231	27	on	on	ADP
cana-2493	231	28	input	input	NOUN
cana-2493	231	29	data[18	data[18	PROPN
cana-2493	231	30	]	]	PUNCT
cana-2493	231	31	.	.	PUNCT
cana-2493	232	1	identify	identify	VERB
cana-2493	232	2	points	point	NOUN
cana-2493	232	3	of	of	ADP
cana-2493	232	4	cancer	cancer	NOUN
cana-2493	232	5	(	(	PUNCT
cana-2493	232	6	key	key	ADJ
cana-2493	232	7	areas	area	NOUN
cana-2493	232	8	)	)	PUNCT
cana-2493	232	9	and	and	CCONJ
cana-2493	232	10	use	use	VERB
cana-2493	232	11	them	they	PRON
cana-2493	232	12	to	to	PART
cana-2493	232	13	inform	inform	VERB
cana-2493	232	14	better	well	ADJ
cana-2493	232	15	feature	feature	NOUN
cana-2493	232	16	extraction	extraction	NOUN
cana-2493	232	17	.	.	PUNCT
cana-2493	233	1	𝐴𝑖𝑗	𝐴𝑖𝑗	PROPN
cana-2493	233	2	=	=	SYM
cana-2493	233	3	𝑒𝑥𝑝(𝑠𝑖𝑗	𝑒𝑥𝑝(𝑠𝑖𝑗	PROPN
cana-2493	233	4	)	)	PUNCT
cana-2493	234	1	∑𝑁	∑𝑁	PROPN
cana-2493	234	2	𝑘=1	𝑘=1	PUNCT
cana-2493	234	3	𝑒𝑥𝑝(𝑠𝑖𝑘	𝑒𝑥𝑝(𝑠𝑖𝑘	NOUN
cana-2493	234	4	)	)	PUNCT
cana-2493	234	5	the	the	DET
cana-2493	234	6	attention	attention	NOUN
cana-2493	234	7	mechanism	mechanism	NOUN
cana-2493	234	8	is	be	AUX
cana-2493	234	9	utilized	utilize	VERB
cana-2493	234	10	as	as	ADP
cana-2493	234	11	a	a	DET
cana-2493	234	12	layer	layer	NOUN
cana-2493	234	13	inside	inside	ADP
cana-2493	234	14	of	of	ADP
cana-2493	234	15	the	the	DET
cana-2493	234	16	neural	neural	ADJ
cana-2493	234	17	network	network	NOUN
cana-2493	234	18	which	which	PRON
cana-2493	234	19	directs	direct	VERB
cana-2493	234	20	the	the	DET
cana-2493	234	21	learning	learning	NOUN
cana-2493	234	22	process	process	NOUN
cana-2493	234	23	to	to	PART
cana-2493	234	24	select	select	VERB
cana-2493	234	25	appropriate	appropriate	ADJ
cana-2493	234	26	regions	region	NOUN
cana-2493	234	27	from	from	ADP
cana-2493	234	28	the	the	DET
cana-2493	234	29	input	input	NOUN
cana-2493	234	30	image	image	NOUN
cana-2493	234	31	.	.	PUNCT
cana-2493	235	1	the	the	DET
cana-2493	235	2	attention	attention	NOUN
cana-2493	235	3	map	map	NOUN
cana-2493	235	4	is	be	AUX
cana-2493	235	5	calculated	calculate	VERB
cana-2493	235	6	by	by	ADP
cana-2493	235	7	this	this	DET
cana-2493	235	8	layer	layer	NOUN
cana-2493	235	9	and	and	CCONJ
cana-2493	235	10	applied	apply	VERB
cana-2493	235	11	to	to	ADP
cana-2493	235	12	the	the	DET
cana-2493	235	13	image	image	NOUN
cana-2493	235	14	in	in	ADP
cana-2493	235	15	such	such	DET
cana-2493	235	16	a	a	DET
cana-2493	235	17	way	way	NOUN
cana-2493	235	18	that	that	PRON
cana-2493	235	19	areas	area	NOUN
cana-2493	235	20	of	of	ADP
cana-2493	235	21	concern	concern	NOUN
cana-2493	235	22	are	be	AUX
cana-2493	235	23	highlighted	highlight	VERB
cana-2493	235	24	.	.	PUNCT
cana-2493	236	1	by	by	ADP
cana-2493	236	2	doing	do	VERB
cana-2493	236	3	this	this	DET
cana-2493	236	4	selective	selective	ADJ
cana-2493	236	5	communications	communication	NOUN
cana-2493	236	6	on	on	ADP
cana-2493	236	7	applied	apply	VERB
cana-2493	236	8	nonlinear	nonlinear	ADJ
cana-2493	236	9	analysis	analysis	NOUN
cana-2493	236	10	issn	issn	NOUN
cana-2493	236	11	:	:	PUNCT
cana-2493	236	12	1074	1074	NUM
cana-2493	236	13	-	-	PUNCT
cana-2493	236	14	133x	133x	NUM
cana-2493	236	15	vol	vol	NOUN
cana-2493	236	16	32	32	NUM
cana-2493	236	17	no	no	NOUN
cana-2493	236	18	.	.	PUNCT
cana-2493	237	1	2s	2s	NUM
cana-2493	237	2	(	(	PUNCT
cana-2493	237	3	2025	2025	NUM
cana-2493	237	4	)	)	PUNCT
cana-2493	237	5	556	556	NUM
cana-2493	237	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	237	7	weighting	weighting	NOUN
cana-2493	237	8	,	,	PUNCT
cana-2493	237	9	the	the	DET
cana-2493	237	10	network	network	NOUN
cana-2493	237	11	can	can	AUX
cana-2493	237	12	emphasize	emphasize	VERB
cana-2493	237	13	more	more	ADV
cana-2493	237	14	on	on	ADP
cana-2493	237	15	extracting	extract	VERB
cana-2493	237	16	important	important	ADJ
cana-2493	237	17	features	feature	NOUN
cana-2493	237	18	of	of	ADP
cana-2493	237	19	the	the	DET
cana-2493	237	20	input	input	NOUN
cana-2493	237	21	images	image	NOUN
cana-2493	237	22	which	which	PRON
cana-2493	237	23	helps	help	VERB
cana-2493	237	24	in	in	ADP
cana-2493	237	25	better	well	ADJ
cana-2493	237	26	performance	performance	NOUN
cana-2493	237	27	of	of	ADP
cana-2493	237	28	recognizing	recognize	VERB
cana-2493	237	29	infected	infected	ADJ
cana-2493	237	30	regions	region	NOUN
cana-2493	237	31	.	.	PUNCT
cana-2493	238	1	𝐹𝑖𝑗	𝐹𝑖𝑗	NUM
cana-2493	238	2	′	′	NUM
cana-2493	239	1	=	=	PUNCT
cana-2493	239	2	𝐴𝑖𝑗	𝐴𝑖𝑗	NUM
cana-2493	239	3	×	×	NOUN
cana-2493	240	1	𝐹𝑖𝑗	𝐹𝑖𝑗	NUM
cana-2493	240	2	then	then	ADV
cana-2493	240	3	the	the	DET
cana-2493	240	4	attention	attention	NOUN
cana-2493	240	5	map	map	NOUN
cana-2493	240	6	is	be	AUX
cana-2493	240	7	computed	compute	VERB
cana-2493	240	8	with	with	ADP
cana-2493	240	9	convolutional	convolutional	ADJ
cana-2493	240	10	functions	function	NOUN
cana-2493	240	11	followed	follow	VERB
cana-2493	240	12	by	by	ADP
cana-2493	240	13	softmax	softmax	NOUN
cana-2493	240	14	normalization	normalization	NOUN
cana-2493	240	15	.	.	PUNCT
cana-2493	241	1	when	when	SCONJ
cana-2493	241	2	training	train	VERB
cana-2493	241	3	the	the	DET
cana-2493	241	4	network	network	NOUN
cana-2493	241	5	,	,	PUNCT
cana-2493	241	6	it	it	PRON
cana-2493	241	7	learns	learn	VERB
cana-2493	241	8	to	to	PART
cana-2493	241	9	assign	assign	VERB
cana-2493	241	10	higher	high	ADJ
cana-2493	241	11	importance	importance	NOUN
cana-2493	241	12	weights	weight	NOUN
cana-2493	241	13	to	to	ADP
cana-2493	241	14	areas	area	NOUN
cana-2493	241	15	that	that	PRON
cana-2493	241	16	are	be	AUX
cana-2493	241	17	more	more	ADV
cana-2493	241	18	likely	likely	ADJ
cana-2493	241	19	to	to	PART
cana-2493	241	20	contain	contain	VERB
cana-2493	241	21	relevant	relevant	ADJ
cana-2493	241	22	features	feature	NOUN
cana-2493	241	23	(	(	PUNCT
cana-2493	241	24	such	such	ADJ
cana-2493	241	25	as	as	ADP
cana-2493	241	26	clear	clear	ADJ
cana-2493	241	27	signs	sign	NOUN
cana-2493	241	28	of	of	ADP
cana-2493	241	29	cancer	cancer	NOUN
cana-2493	241	30	)	)	PUNCT
cana-2493	241	31	and	and	CCONJ
cana-2493	241	32	lower	low	ADJ
cana-2493	241	33	importance	importance	NOUN
cana-2493	241	34	weights	weight	NOUN
cana-2493	241	35	for	for	ADP
cana-2493	241	36	regions	region	NOUN
cana-2493	241	37	without	without	ADP
cana-2493	241	38	relevant	relevant	ADJ
cana-2493	241	39	information	information	NOUN
cana-2493	241	40	(	(	PUNCT
cana-2493	241	41	e.g.	e.g.	ADV
cana-2493	241	42	,	,	PUNCT
cana-2493	241	43	non	non	ADJ
cana-2493	241	44	-	-	ADJ
cana-2493	241	45	infected	infected	ADJ
cana-2493	241	46	healthy	healthy	ADJ
cana-2493	241	47	lung	lung	NOUN
cana-2493	241	48	parenchyma	parenchyma	NOUN
cana-2493	241	49	)	)	PUNCT
cana-2493	241	50	.	.	PUNCT
cana-2493	242	1	boost	boost	VERB
cana-2493	242	2	in	in	ADP
cana-2493	242	3	recognition	recognition	NOUN
cana-2493	242	4	accuracy	accuracy	NOUN
cana-2493	242	5	,	,	PUNCT
cana-2493	242	6	while	while	SCONJ
cana-2493	242	7	attention	attention	NOUN
cana-2493	242	8	based	base	VERB
cana-2493	242	9	feature	feature	NOUN
cana-2493	242	10	extraction	extraction	NOUN
cana-2493	242	11	assists	assist	NOUN
cana-2493	242	12	localizing	localize	VERB
cana-2493	242	13	the	the	DET
cana-2493	242	14	effected	effect	VERB
cana-2493	242	15	regions	region	NOUN
cana-2493	242	16	on	on	ADP
cana-2493	242	17	images	image	NOUN
cana-2493	242	18	which	which	PRON
cana-2493	242	19	is	be	AUX
cana-2493	242	20	important	important	ADJ
cana-2493	242	21	for	for	ADP
cana-2493	242	22	interpret	interpret	NOUN
cana-2493	242	23	-	-	PUNCT
cana-2493	242	24	ability	ability	NOUN
cana-2493	242	25	in	in	ADP
cana-2493	242	26	medical	medical	ADJ
cana-2493	242	27	diagnosis[23	diagnosis[23	NOUN
cana-2493	242	28	]	]	X
cana-2493	242	29	.	.	PUNCT
cana-2493	243	1	2	2	X
cana-2493	243	2	.	.	NUM
cana-2493	243	3	improved	improve	VERB
cana-2493	243	4	feature	feature	NOUN
cana-2493	243	5	representation	representation	NOUN
cana-2493	243	6	by	by	ADP
cana-2493	243	7	cross	cross	ADJ
cana-2493	243	8	-	-	ADJ
cana-2493	243	9	average	average	ADJ
cana-2493	243	10	pooling	pooling	NOUN
cana-2493	243	11	pooling	pool	VERB
cana-2493	243	12	is	be	AUX
cana-2493	243	13	a	a	DET
cana-2493	243	14	very	very	ADV
cana-2493	243	15	important	important	ADJ
cana-2493	243	16	operation	operation	NOUN
cana-2493	243	17	on	on	ADP
cana-2493	243	18	networks	network	NOUN
cana-2493	243	19	that	that	PRON
cana-2493	243	20	are	be	AUX
cana-2493	243	21	targets	target	NOUN
cana-2493	243	22	to	to	PART
cana-2493	243	23	be	be	AUX
cana-2493	243	24	applied	apply	VERB
cana-2493	243	25	convolution	convolution	NOUN
cana-2493	243	26	because	because	SCONJ
cana-2493	243	27	it	it	PRON
cana-2493	243	28	reduces	reduce	VERB
cana-2493	243	29	the	the	DET
cana-2493	243	30	spatial	spatial	ADJ
cana-2493	243	31	dimension	dimension	NOUN
cana-2493	243	32	of	of	ADP
cana-2493	243	33	feature	feature	NOUN
cana-2493	243	34	maps	map	NOUN
cana-2493	243	35	,	,	PUNCT
cana-2493	243	36	thus	thus	ADV
cana-2493	243	37	avoiding	avoid	VERB
cana-2493	243	38	overfitting	overfitte	VERB
cana-2493	243	39	and	and	CCONJ
cana-2493	243	40	reducing	reduce	VERB
cana-2493	243	41	computation	computation	NOUN
cana-2493	243	42	volume	volume	NOUN
cana-2493	243	43	.	.	PUNCT
cana-2493	244	1	in	in	ADP
cana-2493	244	2	general	general	ADJ
cana-2493	244	3	,	,	PUNCT
cana-2493	244	4	pooling	pool	VERB
cana-2493	244	5	operations	operation	NOUN
cana-2493	244	6	are	be	AUX
cana-2493	244	7	crucial	crucial	ADJ
cana-2493	244	8	in	in	ADP
cana-2493	244	9	cnn	cnn	PROPN
cana-2493	244	10	-	-	PUNCT
cana-2493	244	11	based	base	VERB
cana-2493	244	12	methods	method	NOUN
cana-2493	244	13	for	for	ADP
cana-2493	244	14	down	down	ADV
cana-2493	244	15	-	-	PUNCT
cana-2493	244	16	sampling	sample	VERB
cana-2493	244	17	the	the	DET
cana-2493	244	18	feature	feature	NOUN
cana-2493	244	19	maps	map	NOUN
cana-2493	244	20	and	and	CCONJ
cana-2493	244	21	simplifying	simplify	VERB
cana-2493	244	22	learning	learning	NOUN
cana-2493	244	23	process	process	NOUN
cana-2493	244	24	,	,	PUNCT
cana-2493	244	25	traditionally	traditionally	ADV
cana-2493	244	26	including	include	VERB
cana-2493	244	27	max	max	PROPN
cana-2493	244	28	-	-	PUNCT
cana-2493	244	29	pooling	pooling	NOUN
cana-2493	244	30	and	and	CCONJ
cana-2493	244	31	averagepooling	averagepooling	NOUN
cana-2493	244	32	;	;	PUNCT
cana-2493	244	33	however	however	ADV
cana-2493	244	34	these	these	DET
cana-2493	244	35	methods	method	NOUN
cana-2493	244	36	are	be	AUX
cana-2493	244	37	not	not	PART
cana-2493	244	38	always	always	ADV
cana-2493	244	39	suitable	suitable	ADJ
cana-2493	244	40	to	to	PART
cana-2493	244	41	preserve	preserve	VERB
cana-2493	244	42	subtle	subtle	ADJ
cana-2493	244	43	and	and	CCONJ
cana-2493	244	44	sporadic	sporadic	ADJ
cana-2493	244	45	patterns	pattern	NOUN
cana-2493	244	46	appearing	appear	VERB
cana-2493	244	47	in	in	ADP
cana-2493	244	48	medical	medical	ADJ
cana-2493	244	49	images	image	NOUN
cana-2493	244	50	of	of	ADP
cana-2493	244	51	lung	lung	NOUN
cana-2493	244	52	cancers	cancer	NOUN
cana-2493	244	53	x	x	NOUN
cana-2493	244	54	-	-	NOUN
cana-2493	244	55	ray	ray	NOUN
cana-2493	244	56	echo	echo	NOUN
cana-2493	244	57	.	.	PUNCT
cana-2493	245	1	the	the	DET
cana-2493	245	2	proposed	propose	VERB
cana-2493	245	3	approach	approach	NOUN
cana-2493	245	4	tackles	tackle	VERB
cana-2493	245	5	the	the	DET
cana-2493	245	6	problem	problem	NOUN
cana-2493	245	7	by	by	ADP
cana-2493	245	8	using	use	VERB
cana-2493	245	9	cross	cross	ADJ
cana-2493	245	10	-	-	ADJ
cana-2493	245	11	average	average	ADJ
cana-2493	245	12	pooling	pooling	NOUN
cana-2493	245	13	,	,	PUNCT
cana-2493	245	14	a	a	DET
cana-2493	245	15	new	new	ADJ
cana-2493	245	16	technique	technique	NOUN
cana-2493	245	17	that	that	PRON
cana-2493	245	18	aims	aim	VERB
cana-2493	245	19	to	to	PART
cana-2493	245	20	improve	improve	VERB
cana-2493	245	21	pattern	pattern	NOUN
cana-2493	245	22	learning	learn	VERB
cana-2493	245	23	from	from	ADP
cana-2493	245	24	input	input	NOUN
cana-2493	245	25	data	datum	NOUN
cana-2493	245	26	.	.	PUNCT
cana-2493	246	1	𝑃𝑐	𝑃𝑐	NOUN
cana-2493	246	2	=	=	SYM
cana-2493	246	3	1	1	NUM
cana-2493	246	4	𝐻	𝐻	NOUN
cana-2493	246	5	×𝑊	×𝑊	NOUN
cana-2493	246	6	∑	∑	PROPN
cana-2493	246	7	𝐻	𝐻	PROPN
cana-2493	246	8	𝑖=1	𝑖=1	PUNCT
cana-2493	246	9	∑	∑	PUNCT
cana-2493	246	10	𝑊	𝑊	PROPN
cana-2493	246	11	𝑗=1	𝑗=1	PROPN
cana-2493	246	12	𝐹𝑖𝑗𝑐	𝐹𝑖𝑗𝑐	PROPN
cana-2493	246	13	the	the	DET
cana-2493	246	14	cross	cross	ADJ
cana-2493	246	15	-	-	ADJ
cana-2493	246	16	average	average	ADJ
cana-2493	246	17	pooling	pooling	NOUN
cana-2493	246	18	is	be	AUX
cana-2493	246	19	distinct	distinct	ADJ
cana-2493	246	20	from	from	ADP
cana-2493	246	21	typical	typical	ADJ
cana-2493	246	22	pooling	pool	VERB
cana-2493	246	23	techniques	technique	NOUN
cana-2493	246	24	by	by	ADP
cana-2493	246	25	not	not	PART
cana-2493	246	26	treating	treat	VERB
cana-2493	246	27	each	each	DET
cana-2493	246	28	region	region	NOUN
cana-2493	246	29	in	in	ADP
cana-2493	246	30	isolation	isolation	NOUN
cana-2493	246	31	when	when	SCONJ
cana-2493	246	32	applying	apply	VERB
cana-2493	246	33	the	the	DET
cana-2493	246	34	pooling	pooling	NOUN
cana-2493	246	35	,	,	PUNCT
cana-2493	246	36	but	but	CCONJ
cana-2493	246	37	aggregating	aggregate	VERB
cana-2493	246	38	information	information	NOUN
cana-2493	246	39	across	across	ADP
cana-2493	246	40	spatial	spatial	ADJ
cana-2493	246	41	regions	region	NOUN
cana-2493	246	42	and	and	CCONJ
cana-2493	246	43	channels	channel	NOUN
cana-2493	246	44	to	to	PART
cana-2493	246	45	provide	provide	VERB
cana-2493	246	46	a	a	DET
cana-2493	246	47	more	more	ADV
cana-2493	246	48	global	global	ADJ
cana-2493	246	49	representation	representation	NOUN
cana-2493	246	50	of	of	ADP
cana-2493	246	51	the	the	DET
cana-2493	246	52	input	input	NOUN
cana-2493	246	53	image	image	NOUN
cana-2493	246	54	.	.	PUNCT
cana-2493	247	1	in	in	ADP
cana-2493	247	2	order	order	NOUN
cana-2493	247	3	to	to	PART
cana-2493	247	4	enable	enable	VERB
cana-2493	247	5	the	the	DET
cana-2493	247	6	model	model	NOUN
cana-2493	247	7	with	with	ADP
cana-2493	247	8	:	:	PUNCT
cana-2493	247	9	learn	learn	VERB
cana-2493	247	10	intricate	intricate	ADJ
cana-2493	247	11	patterns	pattern	NOUN
cana-2493	247	12	:	:	PUNCT
cana-2493	247	13	cross	cross	ADJ
cana-2493	247	14	-	-	ADJ
cana-2493	247	15	average	average	ADJ
cana-2493	247	16	pooling	pooling	NOUN
cana-2493	247	17	can	can	AUX
cana-2493	247	18	capture	capture	VERB
cana-2493	247	19	complex	complex	ADJ
cana-2493	247	20	textures	texture	NOUN
cana-2493	247	21	,	,	PUNCT
cana-2493	247	22	opacities	opacity	NOUN
cana-2493	247	23	and	and	CCONJ
cana-2493	247	24	shapes	shape	NOUN
cana-2493	247	25	unique	unique	ADJ
cana-2493	247	26	to	to	ADP
cana-2493	247	27	lung	lung	NOUN
cana-2493	247	28	cancers	cancer	NOUN
cana-2493	247	29	by	by	ADP
cana-2493	247	30	synthesizing	synthesize	VERB
cana-2493	247	31	information	information	NOUN
cana-2493	247	32	from	from	ADP
cana-2493	247	33	various	various	ADJ
cana-2493	247	34	channels	channel	NOUN
cana-2493	247	35	in	in	ADP
cana-2493	247	36	different	different	ADJ
cana-2493	247	37	spatial	spatial	ADJ
cana-2493	247	38	regions	region	NOUN
cana-2493	247	39	.	.	PUNCT
cana-2493	248	1	𝐹𝑖𝑗	𝐹𝑖𝑗	NOUN
cana-2493	248	2	𝑙+1	𝑙+1	NUM
cana-2493	248	3	=	=	SYM
cana-2493	248	4	𝜎	𝜎	PROPN
cana-2493	248	5	(	(	PUNCT
cana-2493	248	6	∑	∑	PROPN
cana-2493	248	7	𝑀	𝑀	PROPN
cana-2493	248	8	𝑚=1	𝑚=1	VERB
cana-2493	248	9	𝐾𝑖𝑗	𝐾𝑖𝑗	PROPN
cana-2493	248	10	𝑚	𝑚	AUX
cana-2493	248	11	∗	∗	NOUN
cana-2493	248	12	𝐹𝑖𝑗	𝐹𝑖𝑗	PROPN
cana-2493	249	1	𝑙	𝑙	PROPN
cana-2493	249	2	+	+	CCONJ
cana-2493	249	3	𝑏𝑙	𝑏𝑙	PROPN
cana-2493	249	4	)	)	PUNCT
cana-2493	249	5	preserve	preserve	VERB
cana-2493	249	6	spatial	spatial	ADJ
cana-2493	249	7	dependencies	dependency	NOUN
cana-2493	249	8	:	:	PUNCT
cana-2493	249	9	cross	cross	ADJ
cana-2493	249	10	-	-	ADJ
cana-2493	249	11	average	average	ADJ
cana-2493	249	12	pooling	pooling	NOUN
cana-2493	249	13	respects	respect	VERB
cana-2493	249	14	the	the	DET
cana-2493	249	15	important	important	ADJ
cana-2493	249	16	spatial	spatial	ADJ
cana-2493	249	17	structure	structure	NOUN
cana-2493	249	18	and	and	CCONJ
cana-2493	249	19	does	do	AUX
cana-2493	249	20	not	not	PART
cana-2493	249	21	lose	lose	VERB
cana-2493	249	22	focus	focus	NOUN
cana-2493	249	23	on	on	ADP
cana-2493	249	24	the	the	DET
cana-2493	249	25	critical	critical	ADJ
cana-2493	249	26	disease	disease	NOUN
cana-2493	249	27	discrimination	discrimination	NOUN
cana-2493	249	28	details	detail	NOUN
cana-2493	249	29	.	.	PUNCT
cana-2493	250	1	augmented	augment	VERB
cana-2493	250	2	robustness	robustness	NOUN
cana-2493	250	3	:	:	PUNCT
cana-2493	250	4	this	this	DET
cana-2493	250	5	method	method	NOUN
cana-2493	250	6	pools	pool	NOUN
cana-2493	250	7	features	feature	VERB
cana-2493	250	8	across	across	ADP
cana-2493	250	9	channels	channel	NOUN
cana-2493	250	10	which	which	PRON
cana-2493	250	11	results	result	VERB
cana-2493	250	12	in	in	ADP
cana-2493	250	13	a	a	DET
cana-2493	250	14	more	more	ADV
cana-2493	250	15	robust	robust	ADJ
cana-2493	250	16	set	set	NOUN
cana-2493	250	17	of	of	ADP
cana-2493	250	18	features	feature	NOUN
cana-2493	250	19	which	which	PRON
cana-2493	250	20	can	can	AUX
cana-2493	250	21	account	account	VERB
cana-2493	250	22	for	for	ADP
cana-2493	250	23	differences	difference	NOUN
cana-2493	250	24	in	in	ADP
cana-2493	250	25	how	how	SCONJ
cana-2493	250	26	the	the	DET
cana-2493	250	27	cancer	cancer	NOUN
cana-2493	250	28	appears	appear	VERB
cana-2493	250	29	between	between	ADP
cana-2493	250	30	different	different	ADJ
cana-2493	250	31	images	image	NOUN
cana-2493	250	32	.	.	PUNCT
cana-2493	251	1	𝑃	𝑃	NOUN
cana-2493	251	2	=	=	SYM
cana-2493	251	3	𝑐𝑜𝑛𝑐𝑎𝑡(𝑃1	𝑐𝑜𝑛𝑐𝑎𝑡(𝑃1	X
cana-2493	251	4	,	,	PUNCT
cana-2493	251	5	𝑃2	𝑃2	PROPN
cana-2493	251	6	,	,	PUNCT
cana-2493	251	7	…	…	PUNCT
cana-2493	251	8	,	,	PUNCT
cana-2493	251	9	𝑃𝐶	𝑃𝐶	PROPN
cana-2493	251	10	)	)	PUNCT
cana-2493	251	11	the	the	DET
cana-2493	251	12	convolutional	convolutional	ADJ
cana-2493	251	13	layers	layer	NOUN
cana-2493	251	14	feature	feature	NOUN
cana-2493	251	15	maps	map	NOUN
cana-2493	251	16	are	be	AUX
cana-2493	251	17	processed	process	VERB
cana-2493	251	18	through	through	ADP
cana-2493	251	19	cross	cross	ADJ
cana-2493	251	20	-	-	ADJ
cana-2493	251	21	average	average	ADJ
cana-2493	251	22	pooling	pooling	NOUN
cana-2493	251	23	in	in	ADP
cana-2493	251	24	the	the	DET
cana-2493	251	25	proposed	propose	VERB
cana-2493	251	26	model	model	NOUN
cana-2493	251	27	.	.	PUNCT
cana-2493	252	1	the	the	DET
cana-2493	252	2	pooling	pooling	NOUN
cana-2493	252	3	is	be	AUX
cana-2493	252	4	done	do	VERB
cana-2493	252	5	by	by	ADP
cana-2493	252	6	separating	separate	VERB
cana-2493	252	7	the	the	DET
cana-2493	252	8	feature	feature	NOUN
cana-2493	252	9	maps	map	NOUN
cana-2493	252	10	into	into	ADP
cana-2493	252	11	disjoint	disjoint	NOUN
cana-2493	252	12	sections	section	NOUN
cana-2493	252	13	.	.	PUNCT
cana-2493	253	1	it	it	PRON
cana-2493	253	2	then	then	ADV
cana-2493	253	3	calculates	calculate	VERB
cana-2493	253	4	an	an	DET
cana-2493	253	5	average	average	NOUN
cana-2493	253	6	over	over	ADP
cana-2493	253	7	both	both	CCONJ
cana-2493	253	8	the	the	DET
cana-2493	253	9	spatial	spatial	ADJ
cana-2493	253	10	regions	region	NOUN
cana-2493	253	11	as	as	ADV
cana-2493	253	12	well	well	ADV
cana-2493	253	13	as	as	ADP
cana-2493	253	14	channels	channel	NOUN
cana-2493	253	15	,	,	PUNCT
cana-2493	253	16	giving	give	VERB
cana-2493	253	17	us	we	PRON
cana-2493	253	18	a	a	DET
cana-2493	253	19	pooled	pooled	ADJ
cana-2493	253	20	representation	representation	NOUN
cana-2493	253	21	that	that	PRON
cana-2493	253	22	combines	combine	VERB
cana-2493	253	23	information	information	NOUN
cana-2493	253	24	from	from	ADP
cana-2493	253	25	different	different	ADJ
cana-2493	253	26	parts	part	NOUN
cana-2493	253	27	of	of	ADP
cana-2493	253	28	the	the	DET
cana-2493	253	29	image	image	NOUN
cana-2493	253	30	.	.	PUNCT
cana-2493	254	1	this	this	PRON
cana-2493	254	2	yields	yield	VERB
cana-2493	254	3	a	a	DET
cana-2493	254	4	feature	feature	NOUN
cana-2493	254	5	vector	vector	NOUN
cana-2493	254	6	that	that	PRON
cana-2493	254	7	contains	contain	VERB
cana-2493	254	8	communications	communication	NOUN
cana-2493	254	9	on	on	ADP
cana-2493	254	10	applied	apply	VERB
cana-2493	254	11	nonlinear	nonlinear	ADJ
cana-2493	254	12	analysis	analysis	NOUN
cana-2493	254	13	issn	issn	NOUN
cana-2493	254	14	:	:	PUNCT
cana-2493	254	15	1074	1074	NUM
cana-2493	254	16	-	-	PUNCT
cana-2493	254	17	133x	133x	NUM
cana-2493	254	18	vol	vol	NOUN
cana-2493	254	19	32	32	NUM
cana-2493	254	20	no	no	NOUN
cana-2493	254	21	.	.	PUNCT
cana-2493	255	1	2s	2s	NUM
cana-2493	255	2	(	(	PUNCT
cana-2493	255	3	2025	2025	NUM
cana-2493	255	4	)	)	PUNCT
cana-2493	255	5	557	557	NUM
cana-2493	255	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	255	7	information	information	NOUN
cana-2493	255	8	about	about	ADP
cana-2493	255	9	both	both	DET
cana-2493	255	10	global	global	ADJ
cana-2493	255	11	patterns	pattern	NOUN
cana-2493	255	12	and	and	CCONJ
cana-2493	255	13	localized	localized	ADJ
cana-2493	255	14	details	detail	NOUN
cana-2493	255	15	of	of	ADP
cana-2493	255	16	different	different	ADJ
cana-2493	255	17	types	type	NOUN
cana-2493	255	18	of	of	ADP
cana-2493	255	19	lung	lung	NOUN
cana-2493	255	20	cancer	cancer	NOUN
cana-2493	255	21	,	,	PUNCT
cana-2493	255	22	which	which	PRON
cana-2493	255	23	is	be	AUX
cana-2493	255	24	essential	essential	ADJ
cana-2493	255	25	for	for	ADP
cana-2493	255	26	detecting	detect	VERB
cana-2493	255	27	various	various	ADJ
cana-2493	255	28	appearances	appearance	NOUN
cana-2493	255	29	of	of	ADP
cana-2493	255	30	lung	lung	NOUN
cana-2493	255	31	cancer[19	cancer[19	PRON
cana-2493	255	32	]	]	PUNCT
cana-2493	255	33	.	.	PUNCT
cana-2493	256	1	crossaverage	crossaverage	NOUN
cana-2493	256	2	pooling	pool	VERB
cana-2493	256	3	consists	consist	VERB
cana-2493	256	4	of	of	ADP
cana-2493	256	5	the	the	DET
cana-2493	256	6	following	follow	VERB
cana-2493	256	7	steps	step	NOUN
cana-2493	256	8	partitioning	partition	VERB
cana-2493	256	9	:	:	PUNCT
cana-2493	256	10	the	the	DET
cana-2493	256	11	convolutional	convolutional	ADJ
cana-2493	256	12	maps	map	NOUN
cana-2493	256	13	created	create	VERB
cana-2493	256	14	by	by	ADP
cana-2493	256	15	the	the	DET
cana-2493	256	16	convolutional	convolutional	ADJ
cana-2493	256	17	layers	layer	NOUN
cana-2493	256	18	is	be	AUX
cana-2493	256	19	partitioned	partition	VERB
cana-2493	256	20	into	into	ADP
cana-2493	256	21	a	a	DET
cana-2493	256	22	nonoverlapping	nonoverlapping	ADJ
cana-2493	256	23	regions	region	NOUN
cana-2493	256	24	.	.	PUNCT
cana-2493	257	1	averaging	average	VERB
cana-2493	257	2	:	:	PUNCT
cana-2493	257	3	average	average	ADJ
cana-2493	257	4	is	be	AUX
cana-2493	257	5	taken	take	VERB
cana-2493	257	6	across	across	ADP
cana-2493	257	7	both	both	CCONJ
cana-2493	257	8	the	the	DET
cana-2493	257	9	spatial	spatial	ADJ
cana-2493	257	10	dimensions	dimension	NOUN
cana-2493	257	11	and	and	CCONJ
cana-2493	257	12	channel	channel	NOUN
cana-2493	257	13	to	to	PART
cana-2493	257	14	compute	compute	VERB
cana-2493	257	15	a	a	DET
cana-2493	257	16	single	single	ADJ
cana-2493	257	17	pooled	pooled	ADJ
cana-2493	257	18	value	value	NOUN
cana-2493	257	19	for	for	ADP
cana-2493	257	20	a	a	DET
cana-2493	257	21	region	region	NOUN
cana-2493	257	22	in	in	ADP
cana-2493	257	23	a	a	DET
cana-2493	257	24	region	region	NOUN
cana-2493	257	25	.	.	PUNCT
cana-2493	258	1	�	�	PROPN
cana-2493	258	2	̂	̂	VERB
cana-2493	258	3	�	�	PROPN
cana-2493	258	4	=	=	SYM
cana-2493	258	5	𝐹	𝐹	PROPN
cana-2493	258	6	−	−	NOUN
cana-2493	258	7	𝜇	𝜇	ADP
cana-2493	258	8	√𝜎2	√𝜎2	PROPN
cana-2493	258	9	+	+	NUM
cana-2493	258	10	𝜖	𝜖	X
cana-2493	258	11	this	this	DET
cana-2493	258	12	pooling	pool	VERB
cana-2493	258	13	strategy	strategy	NOUN
cana-2493	258	14	could	could	AUX
cana-2493	258	15	effectively	effectively	ADV
cana-2493	258	16	improve	improve	VERB
cana-2493	258	17	the	the	DET
cana-2493	258	18	recognition	recognition	NOUN
cana-2493	258	19	ability	ability	NOUN
cana-2493	258	20	of	of	ADP
cana-2493	258	21	a	a	DET
cana-2493	258	22	broad	broad	ADJ
cana-2493	258	23	range	range	NOUN
cana-2493	258	24	of	of	ADP
cana-2493	258	25	lung	lung	NOUN
cana-2493	258	26	cancer	cancer	NOUN
cana-2493	258	27	cases	case	NOUN
cana-2493	258	28	by	by	ADP
cana-2493	258	29	promoting	promote	VERB
cana-2493	258	30	the	the	DET
cana-2493	258	31	model	model	NOUN
cana-2493	258	32	's	's	PART
cana-2493	258	33	capability	capability	NOUN
cana-2493	258	34	to	to	PART
cana-2493	258	35	learn	learn	VERB
cana-2493	258	36	universal	universal	ADJ
cana-2493	258	37	patterns	pattern	NOUN
cana-2493	258	38	from	from	ADP
cana-2493	258	39	chest	chest	NOUN
cana-2493	258	40	x	x	NOUN
cana-2493	258	41	-	-	NOUN
cana-2493	258	42	ray	ray	NOUN
cana-2493	258	43	images	image	NOUN
cana-2493	258	44	.	.	PUNCT
cana-2493	259	1	3	3	X
cana-2493	259	2	.	.	X
cana-2493	259	3	merge	merge	VERB
cana-2493	259	4	attention	attention	NOUN
cana-2493	259	5	and	and	CCONJ
cana-2493	259	6	cross	cross	ADJ
cana-2493	259	7	-	-	ADJ
cana-2493	259	8	average	average	ADJ
cana-2493	259	9	pooling	pooling	NOUN
cana-2493	259	10	into	into	ADP
cana-2493	259	11	the	the	DET
cana-2493	259	12	framework	framework	NOUN
cana-2493	259	13	in	in	ADP
cana-2493	259	14	this	this	DET
cana-2493	259	15	paper	paper	NOUN
cana-2493	259	16	,	,	PUNCT
cana-2493	259	17	we	we	PRON
cana-2493	259	18	proposed	propose	VERB
cana-2493	259	19	an	an	DET
cana-2493	259	20	end	end	NOUN
cana-2493	259	21	-	-	PUNCT
cana-2493	259	22	to	to	ADP
cana-2493	259	23	-	-	PUNCT
cana-2493	259	24	end	end	NOUN
cana-2493	259	25	deep	deep	ADJ
cana-2493	259	26	learning	learning	NOUN
cana-2493	259	27	model	model	NOUN
cana-2493	259	28	,	,	PUNCT
cana-2493	259	29	which	which	PRON
cana-2493	259	30	docked	dock	VERB
cana-2493	259	31	the	the	DET
cana-2493	259	32	attention	attention	NOUN
cana-2493	259	33	mechanism	mechanism	NOUN
cana-2493	259	34	as	as	ADV
cana-2493	259	35	well	well	ADV
cana-2493	259	36	as	as	ADP
cana-2493	259	37	cross	cross	ADJ
cana-2493	259	38	-	-	ADJ
cana-2493	259	39	average	average	ADJ
cana-2493	259	40	pooling	pooling	NOUN
cana-2493	259	41	to	to	PART
cana-2493	259	42	improve	improve	VERB
cana-2493	259	43	lung	lung	NOUN
cana-2493	259	44	cancer	cancer	NOUN
cana-2493	259	45	recognition	recognition	NOUN
cana-2493	259	46	performance	performance	NOUN
cana-2493	259	47	.	.	PUNCT
cana-2493	260	1	the	the	DET
cana-2493	260	2	main	main	ADJ
cana-2493	260	3	components	component	NOUN
cana-2493	260	4	of	of	ADP
cana-2493	260	5	the	the	DET
cana-2493	260	6	models	model	NOUN
cana-2493	260	7	architecture	architecture	NOUN
cana-2493	260	8	are	be	AUX
cana-2493	260	9	as	as	SCONJ
cana-2493	260	10	follows	follow	VERB
cana-2493	260	11	;	;	PUNCT
cana-2493	260	12	cnn	cnn	PROPN
cana-2493	260	13	base	base	NOUN
cana-2493	260	14	:	:	PUNCT
cana-2493	260	15	the	the	DET
cana-2493	260	16	first	first	ADJ
cana-2493	260	17	set	set	NOUN
cana-2493	260	18	of	of	ADP
cana-2493	260	19	layers	layer	NOUN
cana-2493	260	20	in	in	ADP
cana-2493	260	21	the	the	DET
cana-2493	260	22	model	model	NOUN
cana-2493	260	23	is	be	AUX
cana-2493	260	24	a	a	DET
cana-2493	260	25	stack	stack	NOUN
cana-2493	260	26	called	call	VERB
cana-2493	260	27	cnn	cnn	PROPN
cana-2493	260	28	(	(	PUNCT
cana-2493	260	29	convolution	convolution	NOUN
cana-2493	260	30	neural	neural	ADJ
cana-2493	260	31	network	network	NOUN
cana-2493	260	32	)	)	PUNCT
cana-2493	260	33	used	use	VERB
cana-2493	260	34	for	for	ADP
cana-2493	260	35	feature	feature	NOUN
cana-2493	260	36	extraction	extraction	NOUN
cana-2493	260	37	.	.	PUNCT
cana-2493	261	1	these	these	DET
cana-2493	261	2	layers	layer	NOUN
cana-2493	261	3	work	work	VERB
cana-2493	261	4	on	on	ADP
cana-2493	261	5	the	the	DET
cana-2493	261	6	input	input	NOUN
cana-2493	261	7	chest	chest	NOUN
cana-2493	261	8	x	x	NOUN
cana-2493	261	9	-	-	NOUN
cana-2493	261	10	ray	ray	NOUN
cana-2493	261	11	images	image	NOUN
cana-2493	261	12	to	to	PART
cana-2493	261	13	get	get	VERB
cana-2493	261	14	low	low	ADJ
cana-2493	261	15	level	level	NOUN
cana-2493	261	16	features	feature	NOUN
cana-2493	261	17	like	like	ADP
cana-2493	261	18	edges	edge	NOUN
cana-2493	261	19	,	,	PUNCT
cana-2493	261	20	texture	texture	NOUN
cana-2493	261	21	etc	etc	X
cana-2493	261	22	which	which	PRON
cana-2493	261	23	are	be	AUX
cana-2493	261	24	necessary	necessary	ADJ
cana-2493	261	25	for	for	ADP
cana-2493	261	26	identifying	identify	VERB
cana-2493	261	27	oppositive	oppositive	ADJ
cana-2493	261	28	cancer	cancer	NOUN
cana-2493	261	29	patterns[20	patterns[20	NOUN
cana-2493	261	30	]	]	PUNCT
cana-2493	261	31	.	.	PUNCT
cana-2493	262	1	attention	attention	NOUN
cana-2493	262	2	module	module	NOUN
cana-2493	262	3	:	:	PUNCT
cana-2493	262	4	we	we	PRON
cana-2493	262	5	use	use	VERB
cana-2493	262	6	the	the	DET
cana-2493	262	7	attention	attention	NOUN
cana-2493	262	8	mechanism	mechanism	NOUN
cana-2493	262	9	as	as	ADP
cana-2493	262	10	an	an	DET
cana-2493	262	11	intermediate	intermediate	ADJ
cana-2493	262	12	layer	layer	NOUN
cana-2493	262	13	which	which	PRON
cana-2493	262	14	takes	take	VERB
cana-2493	262	15	convolutional	convolutional	ADJ
cana-2493	262	16	feature	feature	NOUN
cana-2493	262	17	maps	map	NOUN
cana-2493	262	18	as	as	ADP
cana-2493	262	19	input	input	NOUN
cana-2493	262	20	of	of	ADP
cana-2493	262	21	our	our	PRON
cana-2493	262	22	network	network	NOUN
cana-2493	262	23	.	.	PUNCT
cana-2493	263	1	as	as	ADP
cana-2493	263	2	an	an	DET
cana-2493	263	3	appreciation	appreciation	NOUN
cana-2493	263	4	,	,	PUNCT
cana-2493	263	5	this	this	DET
cana-2493	263	6	module	module	NOUN
cana-2493	263	7	learns	learn	VERB
cana-2493	263	8	to	to	PART
cana-2493	263	9	create	create	VERB
cana-2493	263	10	its	its	PRON
cana-2493	263	11	own	own	ADJ
cana-2493	263	12	attention	attention	NOUN
cana-2493	263	13	map	map	NOUN
cana-2493	263	14	and	and	CCONJ
cana-2493	263	15	point	point	VERB
cana-2493	263	16	out	out	ADP
cana-2493	263	17	the	the	DET
cana-2493	263	18	most	most	ADV
cana-2493	263	19	informative	informative	ADJ
cana-2493	263	20	part	part	NOUN
cana-2493	263	21	in	in	ADP
cana-2493	263	22	the	the	DET
cana-2493	263	23	image	image	NOUN
cana-2493	263	24	.	.	PUNCT
cana-2493	264	1	notice	notice	VERB
cana-2493	264	2	that	that	SCONJ
cana-2493	264	3	this	this	DET
cana-2493	264	4	attention	attention	NOUN
cana-2493	264	5	map	map	NOUN
cana-2493	264	6	is	be	AUX
cana-2493	264	7	used	use	VERB
cana-2493	264	8	to	to	PART
cana-2493	264	9	multiply	multiply	VERB
cana-2493	264	10	some	some	DET
cana-2493	264	11	feature	feature	NOUN
cana-2493	264	12	maps	map	NOUN
cana-2493	264	13	,	,	PUNCT
cana-2493	264	14	highlighting	highlight	VERB
cana-2493	264	15	regions	region	NOUN
cana-2493	264	16	containing	contain	VERB
cana-2493	264	17	possible	possible	ADJ
cana-2493	264	18	lesions	lesion	NOUN
cana-2493	264	19	and	and	CCONJ
cana-2493	264	20	meanwhile	meanwhile	ADV
cana-2493	264	21	suppressing	suppress	VERB
cana-2493	264	22	irrelevant	irrelevant	ADJ
cana-2493	264	23	areas	area	NOUN
cana-2493	264	24	.	.	PUNCT
cana-2493	265	1	𝐿	𝐿	PROPN
cana-2493	265	2	=	=	SYM
cana-2493	265	3	−∑	−∑	PROPN
cana-2493	265	4	𝐶	𝐶	PROPN
cana-2493	265	5	𝑐=1	𝑐=1	PROPN
cana-2493	265	6	𝑦𝑐𝑙𝑜𝑔(𝑝𝑐	𝑦𝑐𝑙𝑜𝑔(𝑝𝑐	PROPN
cana-2493	265	7	)	)	PUNCT
cana-2493	265	8	following	follow	VERB
cana-2493	265	9	the	the	DET
cana-2493	265	10	attention	attention	NOUN
cana-2493	265	11	module	module	NOUN
cana-2493	265	12	,	,	PUNCT
cana-2493	265	13	we	we	PRON
cana-2493	265	14	apply	apply	VERB
cana-2493	265	15	a	a	DET
cana-2493	265	16	cross	cross	ADJ
cana-2493	265	17	-	-	ADJ
cana-2493	265	18	average	average	ADJ
cana-2493	265	19	pooling	pooling	NOUN
cana-2493	265	20	layer	layer	NOUN
cana-2493	265	21	.	.	PUNCT
cana-2493	266	1	algorithm	algorithm	NOUN
cana-2493	266	2	2	2	NUM
cana-2493	266	3	:	:	PUNCT
cana-2493	266	4	cross	cross	ADJ
cana-2493	266	5	-	-	ADJ
cana-2493	266	6	average	average	ADJ
cana-2493	266	7	pooling	pool	VERB
cana-2493	266	8	input	input	NOUN
cana-2493	266	9	:	:	PUNCT
cana-2493	266	10	weighted	weight	VERB
cana-2493	266	11	feature	feature	NOUN
cana-2493	266	12	map	map	NOUN
cana-2493	266	13	𝐹′	𝐹′	PUNCT
cana-2493	266	14	with	with	ADP
cana-2493	266	15	dimensions	dimension	NOUN
cana-2493	266	16	𝐻	𝐻	PROPN
cana-2493	266	17	×𝑊	×𝑊	VERB
cana-2493	266	18	×	×	PROPN
cana-2493	266	19	𝐶	𝐶	PROPN
cana-2493	266	20	output	output	NOUN
cana-2493	266	21	:	:	PUNCT
cana-2493	266	22	pooled	pool	VERB
cana-2493	266	23	feature	feature	NOUN
cana-2493	266	24	vector	vector	NOUN
cana-2493	266	25	𝑃	𝑃	NOUN
cana-2493	266	26	1	1	NUM
cana-2493	266	27	.	.	PUNCT
cana-2493	267	1	initialize	initialize	NOUN
cana-2493	267	2	:	:	PUNCT
cana-2493	267	3	take	take	VERB
cana-2493	267	4	the	the	DET
cana-2493	267	5	weighted	weight	VERB
cana-2493	267	6	feature	feature	NOUN
cana-2493	267	7	map	map	NOUN
cana-2493	267	8	𝐹′	𝐹′	PUNCT
cana-2493	267	9	with	with	ADP
cana-2493	267	10	spatial	spatial	ADJ
cana-2493	267	11	dimensions	dimension	NOUN
cana-2493	267	12	𝐻	𝐻	NOUN
cana-2493	267	13	×𝑊	×𝑊	NOUN
cana-2493	267	14	and	and	CCONJ
cana-2493	267	15	channel	channel	NOUN
cana-2493	267	16	dimension	dimension	NOUN
cana-2493	267	17	𝐶.	𝐶.	PROPN
cana-2493	267	18	2	2	NUM
cana-2493	267	19	.	.	PUNCT
cana-2493	268	1	for	for	ADP
cana-2493	268	2	each	each	DET
cana-2493	268	3	channel	channel	NOUN
cana-2493	268	4	𝑐	𝑐	PROPN
cana-2493	268	5	in	in	ADP
cana-2493	268	6	𝐹′	𝐹′	NUM
cana-2493	268	7	:	:	PUNCT
cana-2493	268	8	o	o	NOUN
cana-2493	268	9	compute	compute	VERB
cana-2493	268	10	the	the	DET
cana-2493	268	11	average	average	NOUN
cana-2493	268	12	across	across	ADP
cana-2493	268	13	all	all	DET
cana-2493	268	14	spatial	spatial	ADJ
cana-2493	268	15	locations	location	NOUN
cana-2493	268	16	:	:	PUNCT
cana-2493	269	1	𝑃𝑐	𝑃𝑐	NOUN
cana-2493	269	2	=	=	SYM
cana-2493	269	3	1	1	NUM
cana-2493	269	4	𝐻	𝐻	NOUN
cana-2493	269	5	×𝑊	×𝑊	NOUN
cana-2493	269	6	∑	∑	PROPN
cana-2493	269	7	𝐻	𝐻	PROPN
cana-2493	269	8	𝑖=1	𝑖=1	PUNCT
cana-2493	269	9	∑	∑	PUNCT
cana-2493	269	10	𝑊	𝑊	PROPN
cana-2493	269	11	𝑗=1	𝑗=1	PROPN
cana-2493	269	12	𝐹𝑖𝑗𝑐	𝐹𝑖𝑗𝑐	PROPN
cana-2493	269	13	′	′	NOUN
cana-2493	270	1	3	3	X
cana-2493	270	2	.	.	X
cana-2493	271	1	concatenate	concatenate	NOUN
cana-2493	271	2	:	:	PUNCT
cana-2493	271	3	concatenate	concatenate	VERB
cana-2493	271	4	the	the	DET
cana-2493	271	5	pooled	pool	VERB
cana-2493	271	6	features	feature	NOUN
cana-2493	271	7	across	across	ADP
cana-2493	271	8	all	all	DET
cana-2493	271	9	channels	channel	NOUN
cana-2493	271	10	:	:	PUNCT
cana-2493	271	11	communications	communication	NOUN
cana-2493	271	12	on	on	ADP
cana-2493	271	13	applied	apply	VERB
cana-2493	271	14	nonlinear	nonlinear	ADJ
cana-2493	271	15	analysis	analysis	NOUN
cana-2493	271	16	issn	issn	NOUN
cana-2493	271	17	:	:	PUNCT
cana-2493	271	18	1074	1074	NUM
cana-2493	271	19	-	-	PUNCT
cana-2493	271	20	133x	133x	NUM
cana-2493	271	21	vol	vol	NOUN
cana-2493	271	22	32	32	NUM
cana-2493	271	23	no	no	NOUN
cana-2493	271	24	.	.	PUNCT
cana-2493	272	1	2s	2s	NUM
cana-2493	272	2	(	(	PUNCT
cana-2493	272	3	2025	2025	NUM
cana-2493	272	4	)	)	PUNCT
cana-2493	272	5	558	558	NUM
cana-2493	272	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	272	7	𝑃	𝑃	NOUN
cana-2493	272	8	=	=	SYM
cana-2493	272	9	𝑐𝑜𝑛𝑐𝑎𝑡(𝑃1	𝑐𝑜𝑛𝑐𝑎𝑡(𝑃1	X
cana-2493	272	10	,	,	PUNCT
cana-2493	272	11	𝑃2	𝑃2	PROPN
cana-2493	272	12	,	,	PUNCT
cana-2493	272	13	…	…	PUNCT
cana-2493	272	14	,	,	PUNCT
cana-2493	272	15	𝑃𝐶	𝑃𝐶	PROPN
cana-2493	272	16	)	)	PUNCT
cana-2493	272	17	4	4	NUM
cana-2493	272	18	.	.	X
cana-2493	272	19	return	return	NOUN
cana-2493	272	20	:	:	PUNCT
cana-2493	272	21	the	the	DET
cana-2493	272	22	concatenated	concatenate	VERB
cana-2493	272	23	pooled	pool	VERB
cana-2493	272	24	feature	feature	NOUN
cana-2493	272	25	vector	vector	NOUN
cana-2493	272	26	𝑃	𝑃	NOUN
cana-2493	272	27	for	for	ADP
cana-2493	272	28	input	input	NOUN
cana-2493	272	29	to	to	ADP
cana-2493	272	30	the	the	DET
cana-2493	272	31	fully	fully	ADV
cana-2493	272	32	connected	connected	ADJ
cana-2493	272	33	layers	layer	NOUN
cana-2493	272	34	.	.	PUNCT
cana-2493	273	1	this	this	DET
cana-2493	273	2	approach	approach	NOUN
cana-2493	273	3	uses	use	VERB
cana-2493	273	4	a	a	DET
cana-2493	273	5	generic	generic	ADJ
cana-2493	273	6	sliding	sliding	NOUN
cana-2493	273	7	-	-	PUNCT
cana-2493	273	8	window	window	NOUN
cana-2493	273	9	to	to	PART
cana-2493	273	10	make	make	VERB
cana-2493	273	11	predictions	prediction	NOUN
cana-2493	273	12	at	at	ADP
cana-2493	273	13	different	different	ADJ
cana-2493	273	14	scales	scale	NOUN
cana-2493	273	15	on	on	ADP
cana-2493	273	16	input	input	NOUN
cana-2493	273	17	images	image	NOUN
cana-2493	273	18	and	and	CCONJ
cana-2493	273	19	then	then	ADV
cana-2493	273	20	extracts	extract	VERB
cana-2493	273	21	critical	critical	ADJ
cana-2493	273	22	features	feature	NOUN
cana-2493	273	23	from	from	ADP
cana-2493	273	24	each	each	DET
cana-2493	273	25	iteration	iteration	NOUN
cana-2493	273	26	using	use	VERB
cana-2493	273	27	a	a	DET
cana-2493	273	28	pooling	pooling	NOUN
cana-2493	273	29	mechanism	mechanism	NOUN
cana-2493	273	30	which	which	PRON
cana-2493	273	31	then	then	ADV
cana-2493	273	32	aggregates	aggregate	VERB
cana-2493	273	33	information	information	NOUN
cana-2493	273	34	across	across	ADP
cana-2493	273	35	multiple	multiple	ADJ
cana-2493	273	36	spatial	spatial	ADJ
cana-2493	273	37	regions	region	NOUN
cana-2493	273	38	or	or	CCONJ
cana-2493	273	39	depth	depth	NOUN
cana-2493	273	40	channels	channel	NOUN
cana-2493	273	41	by	by	ADP
cana-2493	273	42	producing	produce	VERB
cana-2493	273	43	feature	feature	NOUN
cana-2493	273	44	vectors	vector	NOUN
cana-2493	273	45	that	that	PRON
cana-2493	273	46	encompass	encompass	VERB
cana-2493	273	47	both	both	CCONJ
cana-2493	273	48	local	local	ADJ
cana-2493	273	49	and	and	CCONJ
cana-2493	273	50	global	global	ADJ
cana-2493	273	51	patterns	pattern	NOUN
cana-2493	273	52	of	of	ADP
cana-2493	273	53	lung	lung	NOUN
cana-2493	273	54	cancer[21	cancer[21	PROPN
cana-2493	273	55	]	]	PUNCT
cana-2493	273	56	.	.	PUNCT
cana-2493	274	1	dense	dense	ADJ
cana-2493	274	2	layers	layer	NOUN
cana-2493	274	3	:	:	PUNCT
cana-2493	274	4	the	the	DET
cana-2493	274	5	last	last	ADJ
cana-2493	274	6	few	few	ADJ
cana-2493	274	7	layers	layer	NOUN
cana-2493	274	8	of	of	ADP
cana-2493	274	9	the	the	DET
cana-2493	274	10	model	model	NOUN
cana-2493	274	11	are	be	AUX
cana-2493	274	12	dense	dense	ADJ
cana-2493	274	13	,	,	PUNCT
cana-2493	274	14	or	or	CCONJ
cana-2493	274	15	fully	fully	ADV
cana-2493	274	16	connected	connect	VERB
cana-2493	274	17	,	,	PUNCT
cana-2493	274	18	layers	layer	NOUN
cana-2493	274	19	to	to	PART
cana-2493	274	20	interpret	interpret	VERB
cana-2493	274	21	the	the	DET
cana-2493	274	22	pooled	pooled	ADJ
cana-2493	274	23	feature	feature	NOUN
cana-2493	274	24	vector	vector	NOUN
cana-2493	274	25	and	and	CCONJ
cana-2493	274	26	produce	produce	VERB
cana-2493	274	27	a	a	DET
cana-2493	274	28	final	final	ADJ
cana-2493	274	29	classification	classification	NOUN
cana-2493	274	30	.	.	PUNCT
cana-2493	275	1	specifically	specifically	ADV
cana-2493	275	2	,	,	PUNCT
cana-2493	275	3	these	these	DET
cana-2493	275	4	layers	layer	NOUN
cana-2493	275	5	learn	learn	VERB
cana-2493	275	6	to	to	PART
cana-2493	275	7	separate	separate	VERB
cana-2493	275	8	healthy	healthy	ADJ
cana-2493	275	9	and	and	CCONJ
cana-2493	275	10	infected	infected	ADJ
cana-2493	275	11	lung	lung	NOUN
cana-2493	275	12	regions	region	NOUN
cana-2493	275	13	by	by	ADP
cana-2493	275	14	absorbing	absorb	VERB
cana-2493	275	15	and	and	CCONJ
cana-2493	275	16	highlighting	highlight	VERB
cana-2493	275	17	information	information	NOUN
cana-2493	275	18	from	from	ADP
cana-2493	275	19	the	the	DET
cana-2493	275	20	attention	attention	NOUN
cana-2493	275	21	and	and	CCONJ
cana-2493	275	22	cross	cross	ADJ
cana-2493	275	23	-	-	ADJ
cana-2493	275	24	average	average	ADJ
cana-2493	275	25	pooling	pool	VERB
cana-2493	275	26	operations	operation	NOUN
cana-2493	275	27	.	.	PUNCT
cana-2493	276	1	output	output	NOUN
cana-2493	276	2	layer	layer	NOUN
cana-2493	276	3	:	:	PUNCT
cana-2493	276	4	the	the	DET
cana-2493	276	5	model	model	NOUN
cana-2493	276	6	will	will	AUX
cana-2493	276	7	end	end	VERB
cana-2493	276	8	with	with	ADP
cana-2493	276	9	an	an	DET
cana-2493	276	10	output	output	NOUN
cana-2493	276	11	layer	layer	NOUN
cana-2493	276	12	which	which	PRON
cana-2493	276	13	outputs	output	VERB
cana-2493	276	14	the	the	DET
cana-2493	276	15	probability	probability	NOUN
cana-2493	276	16	scores	score	NOUN
cana-2493	276	17	for	for	ADP
cana-2493	276	18	each	each	DET
cana-2493	276	19	class	class	NOUN
cana-2493	276	20	that	that	PRON
cana-2493	276	21	we	we	PRON
cana-2493	276	22	would	would	AUX
cana-2493	276	23	like	like	VERB
cana-2493	276	24	to	to	PART
cana-2493	276	25	predict	predict	VERB
cana-2493	276	26	,	,	PUNCT
cana-2493	276	27	for	for	ADP
cana-2493	276	28	example	example	NOUN
cana-2493	276	29	healthy	healthy	ADJ
cana-2493	276	30	,	,	PUNCT
cana-2493	276	31	pneumonia	pneumonia	NOUN
cana-2493	276	32	&	&	CCONJ
cana-2493	276	33	covid-19	covid-19	PROPN
cana-2493	276	34	.	.	PUNCT
cana-2493	277	1	in	in	ADP
cana-2493	277	2	the	the	DET
cana-2493	277	3	end	end	NOUN
cana-2493	277	4	,	,	PUNCT
cana-2493	277	5	a	a	DET
cana-2493	277	6	prediction	prediction	NOUN
cana-2493	277	7	is	be	AUX
cana-2493	277	8	made	make	VERB
cana-2493	277	9	for	for	ADP
cana-2493	277	10	the	the	DET
cana-2493	277	11	input	input	NOUN
cana-2493	277	12	image	image	NOUN
cana-2493	277	13	by	by	ADP
cana-2493	277	14	choosing	choose	VERB
cana-2493	277	15	class	class	NOUN
cana-2493	277	16	with	with	ADP
cana-2493	277	17	highest	high	ADJ
cana-2493	277	18	probability	probability	NOUN
cana-2493	277	19	score	score	NOUN
cana-2493	277	20	.	.	PUNCT
cana-2493	278	1	5	5	X
cana-2493	278	2	.	.	PUNCT
cana-2493	278	3	model	model	NOUN
cana-2493	278	4	training	training	NOUN
cana-2493	278	5	and	and	CCONJ
cana-2493	278	6	tuning	tune	VERB
cana-2493	278	7	it	it	PRON
cana-2493	278	8	is	be	AUX
cana-2493	278	9	trained	train	VERB
cana-2493	278	10	on	on	ADP
cana-2493	278	11	a	a	DET
cana-2493	278	12	real	real	ADJ
cana-2493	278	13	-	-	PUNCT
cana-2493	278	14	world	world	NOUN
cana-2493	278	15	data	datum	NOUN
cana-2493	278	16	:	:	PUNCT
cana-2493	278	17	a	a	DET
cana-2493	278	18	dataset	dataset	NOUN
cana-2493	278	19	of	of	ADP
cana-2493	278	20	chest	chest	NOUN
cana-2493	278	21	x	x	NOUN
cana-2493	278	22	-	-	NOUN
cana-2493	278	23	ray	ray	NOUN
cana-2493	278	24	images	image	NOUN
cana-2493	278	25	annotated	annotate	VERB
cana-2493	278	26	with	with	ADP
cana-2493	278	27	labeled	label	VERB
cana-2493	278	28	indicating	indicate	VERB
cana-2493	278	29	the	the	DET
cana-2493	278	30	existence	existence	NOUN
cana-2493	278	31	or	or	CCONJ
cana-2493	278	32	not	not	PART
cana-2493	278	33	for	for	ADP
cana-2493	278	34	lung	lung	NOUN
cana-2493	278	35	cancers	cancer	NOUN
cana-2493	278	36	.	.	PUNCT
cana-2493	279	1	while	while	SCONJ
cana-2493	279	2	training	training	NOUN
cana-2493	279	3	,	,	PUNCT
cana-2493	279	4	the	the	DET
cana-2493	279	5	attention	attention	NOUN
cana-2493	279	6	mechanism	mechanism	NOUN
cana-2493	279	7	learns	learn	VERB
cana-2493	279	8	to	to	PART
cana-2493	279	9	look	look	VERB
cana-2493	279	10	at	at	ADP
cana-2493	279	11	specific	specific	ADJ
cana-2493	279	12	regions	region	NOUN
cana-2493	279	13	of	of	ADP
cana-2493	279	14	interest	interest	NOUN
cana-2493	279	15	in	in	ADP
cana-2493	279	16	new	new	ADJ
cana-2493	279	17	input	input	NOUN
cana-2493	279	18	images	image	NOUN
cana-2493	279	19	,	,	PUNCT
cana-2493	279	20	and	and	CCONJ
cana-2493	279	21	the	the	DET
cana-2493	279	22	cross	cross	ADJ
cana-2493	279	23	-	-	ADJ
cana-2493	279	24	average	average	ADJ
cana-2493	279	25	pooling	pooling	NOUN
cana-2493	279	26	layer	layer	NOUN
cana-2493	279	27	captures	capture	VERB
cana-2493	279	28	complex	complex	ADJ
cana-2493	279	29	patterns	pattern	NOUN
cana-2493	279	30	that	that	PRON
cana-2493	279	31	promote	promote	VERB
cana-2493	279	32	different	different	ADJ
cana-2493	279	33	categories	category	NOUN
cana-2493	279	34	of	of	ADP
cana-2493	279	35	cancer	cancer	NOUN
cana-2493	279	36	.	.	PUNCT
cana-2493	280	1	a	a	DET
cana-2493	280	2	training	training	NOUN
cana-2493	280	3	process	process	NOUN
cana-2493	280	4	has	have	VERB
cana-2493	280	5	several	several	ADJ
cana-2493	280	6	key	key	ADJ
cana-2493	280	7	steps	step	NOUN
cana-2493	280	8	:	:	PUNCT
cana-2493	280	9	data	datum	NOUN
cana-2493	280	10	preprocessing	preprocessing	NOUN
cana-2493	280	11	:	:	PUNCT
cana-2493	280	12	the	the	DET
cana-2493	280	13	input	input	NOUN
cana-2493	280	14	images	image	NOUN
cana-2493	280	15	will	will	AUX
cana-2493	280	16	be	be	AUX
cana-2493	280	17	preprocessed	preprocesse	VERB
cana-2493	280	18	to	to	ADP
cana-2493	280	19	standardizing	standardize	VERB
cana-2493	280	20	the	the	DET
cana-2493	280	21	sizses	sizse	NOUN
cana-2493	280	22	and	and	CCONJ
cana-2493	280	23	intensity	intensity	NOUN
cana-2493	280	24	values	value	NOUN
cana-2493	280	25	of	of	ADP
cana-2493	280	26	the	the	DET
cana-2493	280	27	input	input	NOUN
cana-2493	280	28	images	image	NOUN
cana-2493	280	29	for	for	ADP
cana-2493	280	30	making	make	VERB
cana-2493	280	31	it	it	PRON
cana-2493	280	32	appear	appear	VERB
cana-2493	280	33	same	same	ADJ
cana-2493	280	34	across	across	ADP
cana-2493	280	35	the	the	DET
cana-2493	280	36	dataset	dataset	NOUN
cana-2493	280	37	.	.	PUNCT
cana-2493	281	1	rotation	rotation	NOUN
cana-2493	281	2	,	,	PUNCT
cana-2493	281	3	flipping	flip	VERB
cana-2493	281	4	,	,	PUNCT
cana-2493	281	5	scaling	scaling	NOUN
cana-2493	281	6	(	(	PUNCT
cana-2493	281	7	data	datum	NOUN
cana-2493	281	8	augmentation	augmentation	NOUN
cana-2493	281	9	)	)	PUNCT
cana-2493	281	10	are	be	AUX
cana-2493	281	11	more	more	ADV
cana-2493	281	12	commonly	commonly	ADV
cana-2493	281	13	rely	rely	ADJ
cana-2493	281	14	upon	upon	SCONJ
cana-2493	281	15	to	to	PART
cana-2493	281	16	make	make	VERB
cana-2493	281	17	the	the	DET
cana-2493	281	18	training	training	NOUN
cana-2493	281	19	data	datum	NOUN
cana-2493	281	20	much	much	ADV
cana-2493	281	21	robust	robust	ADJ
cana-2493	281	22	and	and	CCONJ
cana-2493	281	23	avoid	avoid	VERB
cana-2493	281	24	over	over	ADV
cana-2493	281	25	-	-	PUNCT
cana-2493	281	26	fitting	fitting	ADJ
cana-2493	281	27	.	.	PUNCT
cana-2493	282	1	a	a	DET
cana-2493	282	2	loss	loss	NOUN
cana-2493	282	3	function	function	NOUN
cana-2493	282	4	:	:	PUNCT
cana-2493	282	5	this	this	PRON
cana-2493	282	6	is	be	AUX
cana-2493	282	7	essentially	essentially	ADV
cana-2493	282	8	a	a	DET
cana-2493	282	9	way	way	NOUN
cana-2493	282	10	to	to	PART
cana-2493	282	11	measure	measure	VERB
cana-2493	282	12	how	how	SCONJ
cana-2493	282	13	incorrect	incorrect	ADJ
cana-2493	282	14	the	the	DET
cana-2493	282	15	neural	neural	ADJ
cana-2493	282	16	network	network	NOUN
cana-2493	282	17	is	be	AUX
cana-2493	282	18	compared	compare	VERB
cana-2493	282	19	to	to	ADP
cana-2493	282	20	ground	ground	NOUN
cana-2493	282	21	truth	truth	NOUN
cana-2493	282	22	labels	label	NOUN
cana-2493	282	23	e.g.	e.g.	ADV
cana-2493	282	24	,	,	PUNCT
cana-2493	282	25	categorical	categorical	ADJ
cana-2493	282	26	cross	cross	NOUN
cana-2493	282	27	-	-	NOUN
cana-2493	282	28	entropy	entropy	NOUN
cana-2493	282	29	.	.	PUNCT
cana-2493	283	1	it	it	PRON
cana-2493	283	2	updates	update	VERB
cana-2493	283	3	the	the	DET
cana-2493	283	4	model	model	NOUN
cana-2493	283	5	parameters	parameter	NOUN
cana-2493	283	6	by	by	ADP
cana-2493	283	7	backpropagation	backpropagation	NOUN
cana-2493	283	8	and	and	CCONJ
cana-2493	283	9	an	an	DET
cana-2493	283	10	optimization	optimization	NOUN
cana-2493	283	11	algorithm	algorithm	NOUN
cana-2493	283	12	such	such	ADJ
cana-2493	283	13	as	as	ADP
cana-2493	283	14	stochastic	stochastic	ADJ
cana-2493	283	15	gradient	gradient	ADJ
cana-2493	283	16	descent	descent	NOUN
cana-2493	283	17	(	(	PUNCT
cana-2493	283	18	sgd	sgd	NOUN
cana-2493	283	19	)	)	PUNCT
cana-2493	283	20	or	or	CCONJ
cana-2493	283	21	adam	adam	PROPN
cana-2493	283	22	to	to	PART
cana-2493	283	23	reduce	reduce	VERB
cana-2493	283	24	error	error	NOUN
cana-2493	283	25	.	.	PUNCT
cana-2493	284	1	attention	attention	NOUN
cana-2493	284	2	map	map	NOUN
cana-2493	284	3	generation	generation	NOUN
cana-2493	284	4	:	:	PUNCT
cana-2493	284	5	the	the	DET
cana-2493	284	6	attention	attention	NOUN
cana-2493	284	7	module	module	NOUN
cana-2493	284	8	is	be	AUX
cana-2493	284	9	a	a	DET
cana-2493	284	10	building	building	NOUN
cana-2493	284	11	block	block	NOUN
cana-2493	284	12	of	of	ADP
cana-2493	284	13	our	our	PRON
cana-2493	284	14	model	model	NOUN
cana-2493	284	15	and	and	CCONJ
cana-2493	284	16	is	be	AUX
cana-2493	284	17	responsible	responsible	ADJ
cana-2493	284	18	for	for	ADP
cana-2493	284	19	generating	generate	VERB
cana-2493	284	20	an	an	DET
cana-2493	284	21	attention	attention	NOUN
cana-2493	284	22	map	map	NOUN
cana-2493	284	23	for	for	ADP
cana-2493	284	24	the	the	DET
cana-2493	284	25	input	input	NOUN
cana-2493	284	26	image	image	NOUN
cana-2493	284	27	during	during	ADP
cana-2493	284	28	each	each	DET
cana-2493	284	29	forward	forward	ADJ
cana-2493	284	30	pass	pass	NOUN
cana-2493	284	31	,	,	PUNCT
cana-2493	284	32	where	where	SCONJ
cana-2493	284	33	regions	region	NOUN
cana-2493	284	34	contributing	contribute	VERB
cana-2493	284	35	to	to	ADP
cana-2493	284	36	the	the	DET
cana-2493	284	37	final	final	ADJ
cana-2493	284	38	classification	classification	NOUN
cana-2493	284	39	are	be	AUX
cana-2493	284	40	highlighted	highlight	VERB
cana-2493	284	41	.	.	PUNCT
cana-2493	285	1	this	this	DET
cana-2493	285	2	map	map	NOUN
cana-2493	285	3	is	be	AUX
cana-2493	285	4	then	then	ADV
cana-2493	285	5	utilized	utilize	VERB
cana-2493	285	6	to	to	PART
cana-2493	285	7	scale	scale	VERB
cana-2493	285	8	the	the	DET
cana-2493	285	9	feature	feature	NOUN
cana-2493	285	10	maps	map	NOUN
cana-2493	285	11	,	,	PUNCT
cana-2493	285	12	focusing	focus	VERB
cana-2493	285	13	on	on	ADP
cana-2493	285	14	the	the	DET
cana-2493	285	15	more	more	ADV
cana-2493	285	16	informative	informative	ADJ
cana-2493	285	17	regions	region	NOUN
cana-2493	285	18	.	.	PUNCT
cana-2493	286	1	pooling	pool	VERB
cana-2493	286	2	and	and	CCONJ
cana-2493	286	3	feature	feature	NOUN
cana-2493	286	4	aggregation	aggregation	NOUN
cana-2493	286	5	:	:	PUNCT
cana-2493	286	6	the	the	DET
cana-2493	286	7	cross	cross	ADJ
cana-2493	286	8	-	-	ADJ
cana-2493	286	9	average	average	ADJ
cana-2493	286	10	pooling	pooling	NOUN
cana-2493	286	11	layer	layer	NOUN
cana-2493	286	12	processes	process	VERB
cana-2493	286	13	the	the	DET
cana-2493	286	14	weighted	weight	VERB
cana-2493	286	15	feature	feature	NOUN
cana-2493	286	16	maps	map	NOUN
cana-2493	286	17	to	to	PART
cana-2493	286	18	output	output	VERB
cana-2493	286	19	a	a	DET
cana-2493	286	20	pooled	pooled	ADJ
cana-2493	286	21	representation	representation	NOUN
cana-2493	286	22	at	at	ADP
cana-2493	286	23	both	both	CCONJ
cana-2493	286	24	local	local	ADJ
cana-2493	286	25	and	and	CCONJ
cana-2493	286	26	global	global	ADJ
cana-2493	286	27	scales[22	scales[22	NOUN
cana-2493	286	28	]	]	PUNCT
cana-2493	286	29	.	.	PUNCT
cana-2493	287	1	classification	classification	NOUN
cana-2493	287	2	:	:	PUNCT
cana-2493	287	3	this	this	PRON
cana-2493	287	4	takes	take	VERB
cana-2493	287	5	the	the	DET
cana-2493	287	6	output	output	NOUN
cana-2493	287	7	of	of	ADP
cana-2493	287	8	300	300	NUM
cana-2493	287	9	pooled	pool	VERB
cana-2493	287	10	representation	representation	NOUN
cana-2493	287	11	and	and	CCONJ
cana-2493	287	12	produces	produce	VERB
cana-2493	287	13	final	final	ADJ
cana-2493	287	14	classification	classification	NOUN
cana-2493	287	15	scores	score	NOUN
cana-2493	287	16	,	,	PUNCT
cana-2493	287	17	which	which	PRON
cana-2493	287	18	we	we	PRON
cana-2493	287	19	compare	compare	VERB
cana-2493	287	20	to	to	ADP
cana-2493	287	21	true	true	ADJ
cana-2493	287	22	labels	label	NOUN
cana-2493	287	23	in	in	ADP
cana-2493	287	24	computing	computing	NOUN
cana-2493	287	25	losses	loss	NOUN
cana-2493	287	26	.	.	PUNCT
cana-2493	288	1	𝑝𝑐	𝑝𝑐	NOUN
cana-2493	288	2	=	=	PUNCT
cana-2493	288	3	𝑒𝑥𝑝(𝑧𝑐	𝑒𝑥𝑝(𝑧𝑐	PROPN
cana-2493	288	4	)	)	PUNCT
cana-2493	289	1	∑𝐶	∑𝐶	PROPN
cana-2493	289	2	𝑗=1	𝑗=1	PROPN
cana-2493	289	3	𝑒𝑥𝑝(𝑧𝑗	𝑒𝑥𝑝(𝑧𝑗	VERB
cana-2493	289	4	)	)	PUNCT
cana-2493	289	5	communications	communication	NOUN
cana-2493	289	6	on	on	ADP
cana-2493	289	7	applied	apply	VERB
cana-2493	289	8	nonlinear	nonlinear	ADJ
cana-2493	289	9	analysis	analysis	NOUN
cana-2493	289	10	issn	issn	NOUN
cana-2493	289	11	:	:	PUNCT
cana-2493	289	12	1074	1074	NUM
cana-2493	289	13	-	-	PUNCT
cana-2493	289	14	133x	133x	NUM
cana-2493	289	15	vol	vol	NOUN
cana-2493	289	16	32	32	NUM
cana-2493	289	17	no	no	NOUN
cana-2493	289	18	.	.	PUNCT
cana-2493	290	1	2s	2s	NUM
cana-2493	290	2	(	(	PUNCT
cana-2493	290	3	2025	2025	NUM
cana-2493	290	4	)	)	PUNCT
cana-2493	290	5	559	559	NUM
cana-2493	290	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	290	7	evaluation	evaluation	NOUN
cana-2493	290	8	:	:	PUNCT
cana-2493	290	9	performance	performance	NOUN
cana-2493	290	10	of	of	ADP
cana-2493	290	11	the	the	DET
cana-2493	290	12	model	model	NOUN
cana-2493	290	13	is	be	AUX
cana-2493	290	14	evaluated	evaluate	VERB
cana-2493	290	15	by	by	ADP
cana-2493	290	16	using	use	VERB
cana-2493	290	17	kpis	kpis	PROPN
cana-2493	290	18	like	like	ADP
cana-2493	290	19	accuracy	accuracy	NOUN
cana-2493	290	20	,	,	PUNCT
cana-2493	290	21	precision	precision	NOUN
cana-2493	290	22	,	,	PUNCT
cana-2493	290	23	recall	recall	NOUN
cana-2493	290	24	and	and	CCONJ
cana-2493	290	25	f1	f1	NOUN
cana-2493	290	26	-	-	PUNCT
cana-2493	290	27	score	score	NOUN
cana-2493	290	28	on	on	ADP
cana-2493	290	29	validation	validation	NOUN
cana-2493	290	30	set	set	NOUN
cana-2493	290	31	.	.	PUNCT
cana-2493	291	1	they	they	PRON
cana-2493	291	2	are	be	AUX
cana-2493	291	3	also	also	ADV
cana-2493	291	4	checked	check	VERB
cana-2493	291	5	to	to	PART
cana-2493	291	6	highlight	highlight	VERB
cana-2493	291	7	the	the	DET
cana-2493	291	8	responsible	responsible	ADJ
cana-2493	291	9	regions	region	NOUN
cana-2493	291	10	of	of	ADP
cana-2493	291	11	interest	interest	NOUN
cana-2493	291	12	for	for	ADP
cana-2493	291	13	model	model	NOUN
cana-2493	291	14	predictions	prediction	NOUN
cana-2493	291	15	in	in	ADP
cana-2493	291	16	input	input	NOUN
cana-2493	291	17	images	image	NOUN
cana-2493	291	18	.	.	PUNCT
cana-2493	292	1	5	5	X
cana-2493	292	2	.	.	X
cana-2493	292	3	experimental	experimental	ADJ
cana-2493	292	4	evaluation	evaluation	NOUN
cana-2493	292	5	and	and	CCONJ
cana-2493	292	6	results	result	VERB
cana-2493	292	7	the	the	DET
cana-2493	292	8	proposed	propose	VERB
cana-2493	292	9	framework	framework	NOUN
cana-2493	292	10	was	be	AUX
cana-2493	292	11	tested	test	VERB
cana-2493	292	12	on	on	ADP
cana-2493	292	13	publicly	publicly	ADV
cana-2493	292	14	used	use	VERB
cana-2493	292	15	lung	lung	NOUN
cana-2493	292	16	cancer	cancer	NOUN
cana-2493	292	17	datasets	dataset	NOUN
cana-2493	292	18	to	to	PART
cana-2493	292	19	verify	verify	VERB
cana-2493	292	20	its	its	PRON
cana-2493	292	21	performance	performance	NOUN
cana-2493	292	22	.	.	PUNCT
cana-2493	293	1	our	our	PRON
cana-2493	293	2	experimental	experimental	ADJ
cana-2493	293	3	results	result	NOUN
cana-2493	293	4	show	show	VERB
cana-2493	293	5	that	that	SCONJ
cana-2493	293	6	cross	cross	ADJ
cana-2493	293	7	-	-	ADJ
cana-2493	293	8	average	average	ADJ
cana-2493	293	9	pooling	pooling	NOUN
cana-2493	293	10	can	can	AUX
cana-2493	293	11	obviously	obviously	ADV
cana-2493	293	12	promote	promote	VERB
cana-2493	293	13	the	the	DET
cana-2493	293	14	recognition	recognition	NOUN
cana-2493	293	15	performance	performance	NOUN
cana-2493	293	16	of	of	ADP
cana-2493	293	17	the	the	DET
cana-2493	293	18	model	model	NOUN
cana-2493	293	19	is	be	AUX
cana-2493	293	20	lung	lung	NOUN
cana-2493	293	21	cancer	cancer	NOUN
cana-2493	293	22	diagnosis	diagnosis	NOUN
cana-2493	293	23	task	task	NOUN
cana-2493	293	24	for	for	ADP
cana-2493	293	25	attention	attention	NOUN
cana-2493	293	26	-	-	PUNCT
cana-2493	293	27	based	base	VERB
cana-2493	293	28	feature	feature	NOUN
cana-2493	293	29	extraction	extraction	NOUN
cana-2493	293	30	on	on	ADP
cana-2493	293	31	a	a	DET
cana-2493	293	32	typical	typical	ADJ
cana-2493	293	33	cnn	cnn	NOUN
cana-2493	293	34	architecture	architecture	NOUN
cana-2493	293	35	than	than	ADP
cana-2493	293	36	traditional	traditional	ADJ
cana-2493	293	37	cnn	cnn	PROPN
cana-2493	293	38	-	-	PUNCT
cana-2493	293	39	based	base	VERB
cana-2493	293	40	method	method	NOUN
cana-2493	293	41	.	.	PUNCT
cana-2493	294	1	they	they	PRON
cana-2493	294	2	test	test	VERB
cana-2493	294	3	their	their	PRON
cana-2493	294	4	model	model	NOUN
cana-2493	294	5	on	on	ADP
cana-2493	294	6	lidc	lidc	ADJ
cana-2493	294	7	-	-	PUNCT
cana-2493	294	8	idri	idri	ADJ
cana-2493	294	9	dataset	dataset	NOUN
cana-2493	294	10	,	,	PUNCT
cana-2493	294	11	and	and	CCONJ
cana-2493	294	12	observes	observe	VERB
cana-2493	294	13	that	that	SCONJ
cana-2493	294	14	the	the	DET
cana-2493	294	15	proposed	propose	VERB
cana-2493	294	16	model	model	NOUN
cana-2493	294	17	is	be	AUX
cana-2493	294	18	more	more	ADV
cana-2493	294	19	efficient	efficient	ADJ
cana-2493	294	20	in	in	ADP
cana-2493	294	21	identifying	identify	VERB
cana-2493	294	22	lung	lung	NOUN
cana-2493	294	23	cancer	cancer	NOUN
cana-2493	294	24	patterns	pattern	NOUN
cana-2493	294	25	with	with	ADP
cana-2493	294	26	improved	improve	VERB
cana-2493	294	27	both	both	PRON
cana-2493	294	28	accuracy	accuracy	NOUN
cana-2493	294	29	,	,	PUNCT
cana-2493	294	30	precision	precision	NOUN
cana-2493	294	31	and	and	CCONJ
cana-2493	294	32	recall	recall	NOUN
cana-2493	294	33	rates	rate	NOUN
cana-2493	294	34	across	across	ADP
cana-2493	294	35	difference	difference	NOUN
cana-2493	294	36	complexity	complexity	NOUN
cana-2493	294	37	levels	level	NOUN
cana-2493	294	38	of	of	ADP
cana-2493	294	39	cancer	cancer	NOUN
cana-2493	294	40	.	.	PUNCT
cana-2493	295	1	figure	figure	NOUN
cana-2493	295	2	3	3	NUM
cana-2493	295	3	.	.	PUNCT
cana-2493	295	4	model	model	NOUN
cana-2493	295	5	performance	performance	NOUN
cana-2493	295	6	comparison	comparison	NOUN
cana-2493	295	7	the	the	DET
cana-2493	295	8	implementation	implementation	NOUN
cana-2493	295	9	for	for	ADP
cana-2493	295	10	model	model	NOUN
cana-2493	295	11	attention	attention	NOUN
cana-2493	295	12	maps	map	NOUN
cana-2493	295	13	reveals	reveal	VERB
cana-2493	295	14	the	the	DET
cana-2493	295	15	important	important	ADJ
cana-2493	295	16	pieces	piece	NOUN
cana-2493	295	17	of	of	ADP
cana-2493	295	18	evidence	evidence	NOUN
cana-2493	295	19	,	,	PUNCT
cana-2493	295	20	assisting	assist	VERB
cana-2493	295	21	in	in	ADP
cana-2493	295	22	decision	decision	NOUN
cana-2493	295	23	making	make	VERB
cana-2493	295	24	to	to	PART
cana-2493	295	25	make	make	VERB
cana-2493	295	26	the	the	DET
cana-2493	295	27	predictions	prediction	NOUN
cana-2493	295	28	more	more	ADV
cana-2493	295	29	understandable	understandable	ADJ
cana-2493	295	30	by	by	ADP
cana-2493	295	31	clinicians	clinician	NOUN
cana-2493	295	32	.	.	PUNCT
cana-2493	296	1	and	and	CCONJ
cana-2493	296	2	since	since	SCONJ
cana-2493	296	3	in	in	ADP
cana-2493	296	4	medical	medical	ADJ
cana-2493	296	5	,	,	PUNCT
cana-2493	296	6	the	the	DET
cana-2493	296	7	interpretablity	interpretablity	NOUN
cana-2493	296	8	is	be	AUX
cana-2493	296	9	almost	almost	ADV
cana-2493	296	10	as	as	ADV
cana-2493	296	11	important	important	ADJ
cana-2493	296	12	as	as	ADP
cana-2493	296	13	performance	performance	NOUN
cana-2493	296	14	.	.	PUNCT
cana-2493	297	1	4	4	X
cana-2493	297	2	.	.	NOUN
cana-2493	297	3	results	result	VERB
cana-2493	297	4	the	the	DET
cana-2493	297	5	evaluation	evaluation	NOUN
cana-2493	297	6	results	result	NOUN
cana-2493	297	7	of	of	ADP
cana-2493	297	8	our	our	PRON
cana-2493	297	9	proposed	propose	VERB
cana-2493	297	10	mechanism	mechanism	NOUN
cana-2493	297	11	on	on	ADP
cana-2493	297	12	publicly	publicly	ADV
cana-2493	297	13	available	available	ADJ
cana-2493	297	14	datasets	dataset	NOUN
cana-2493	297	15	with	with	ADP
cana-2493	297	16	the	the	DET
cana-2493	297	17	purpose	purpose	NOUN
cana-2493	297	18	to	to	PART
cana-2493	297	19	detect	detect	VERB
cana-2493	297	20	lung	lung	NOUN
cana-2493	297	21	cancers	cancer	NOUN
cana-2493	297	22	were	be	AUX
cana-2493	297	23	assessed	assess	VERB
cana-2493	297	24	using	use	VERB
cana-2493	297	25	the	the	DET
cana-2493	297	26	experimental	experimental	ADJ
cana-2493	297	27	outcomes	outcome	NOUN
cana-2493	297	28	.	.	PUNCT
cana-2493	298	1	we	we	PRON
cana-2493	298	2	compared	compare	VERB
cana-2493	298	3	our	our	PRON
cana-2493	298	4	method	method	NOUN
cana-2493	298	5	to	to	ADP
cana-2493	298	6	a	a	DET
cana-2493	298	7	variety	variety	NOUN
cana-2493	298	8	of	of	ADP
cana-2493	298	9	convolutional	convolutional	ADJ
cana-2493	298	10	neural	neural	ADJ
cana-2493	298	11	network	network	NOUN
cana-2493	298	12	(	(	PUNCT
cana-2493	298	13	cnn	cnn	PROPN
cana-2493	298	14	)	)	PUNCT
cana-2493	298	15	models	model	NOUN
cana-2493	298	16	and	and	CCONJ
cana-2493	298	17	our	our	PRON
cana-2493	298	18	performance	performance	NOUN
cana-2493	298	19	was	be	AUX
cana-2493	298	20	higher	high	ADJ
cana-2493	298	21	across	across	ADP
cana-2493	298	22	all	all	DET
cana-2493	298	23	metrics	metric	NOUN
cana-2493	298	24	accuracy	accuracy	NOUN
cana-2493	298	25	,	,	PUNCT
cana-2493	298	26	precision	precision	NOUN
cana-2493	298	27	,	,	PUNCT
cana-2493	298	28	recall	recall	NOUN
cana-2493	298	29	and	and	CCONJ
cana-2493	298	30	f1	f1	NOUN
cana-2493	298	31	-	-	PUNCT
cana-2493	298	32	score	score	NOUN
cana-2493	298	33	.	.	PUNCT
cana-2493	299	1	the	the	DET
cana-2493	299	2	developed	develop	VERB
cana-2493	299	3	architecture	architecture	NOUN
cana-2493	299	4	was	be	AUX
cana-2493	299	5	specifically	specifically	ADV
cana-2493	299	6	meant	mean	VERB
cana-2493	299	7	to	to	PART
cana-2493	299	8	overcome	overcome	VERB
cana-2493	299	9	the	the	DET
cana-2493	299	10	inherent	inherent	ADJ
cana-2493	299	11	limitations	limitation	NOUN
cana-2493	299	12	in	in	ADP
cana-2493	299	13	terms	term	NOUN
cana-2493	299	14	of	of	ADP
cana-2493	299	15	feature	feature	NOUN
cana-2493	299	16	extraction	extraction	NOUN
cana-2493	299	17	from	from	ADP
cana-2493	299	18	noisy	noisy	ADJ
cana-2493	299	19	and	and	CCONJ
cana-2493	299	20	complex	complex	ADJ
cana-2493	299	21	medical	medical	ADJ
cana-2493	299	22	images	image	NOUN
cana-2493	299	23	which	which	PRON
cana-2493	299	24	hinder	hinder	AUX
cana-2493	299	25	cnns	cnn	NOUN
cana-2493	299	26	like	like	ADP
cana-2493	299	27	the	the	DET
cana-2493	299	28	chest	chest	NOUN
cana-2493	299	29	x	x	NOUN
cana-2493	299	30	-	-	NOUN
cana-2493	299	31	rays	ray	NOUN
cana-2493	299	32	.	.	PUNCT
cana-2493	300	1	the	the	DET
cana-2493	300	2	model	model	NOUN
cana-2493	300	3	was	be	AUX
cana-2493	300	4	even	even	ADV
cana-2493	300	5	able	able	ADJ
cana-2493	300	6	to	to	PART
cana-2493	300	7	fixate	fixate	VERB
cana-2493	300	8	on	on	ADP
cana-2493	300	9	the	the	DET
cana-2493	300	10	needful	needful	ADJ
cana-2493	300	11	regions	region	NOUN
cana-2493	300	12	in	in	ADP
cana-2493	300	13	an	an	DET
cana-2493	300	14	image	image	NOUN
cana-2493	300	15	,	,	PUNCT
cana-2493	300	16	mostly	mostly	ADV
cana-2493	300	17	corrupted	corrupt	VERB
cana-2493	300	18	by	by	ADP
cana-2493	300	19	cancers	cancer	NOUN
cana-2493	300	20	and	and	CCONJ
cana-2493	300	21	skip	skip	VERB
cana-2493	300	22	the	the	DET
cana-2493	300	23	irrelevant	irrelevant	ADJ
cana-2493	300	24	information	information	NOUN
cana-2493	300	25	from	from	ADP
cana-2493	300	26	normal	normal	ADJ
cana-2493	300	27	tissues	tissue	NOUN
cana-2493	300	28	or	or	CCONJ
cana-2493	300	29	from	from	ADP
cana-2493	300	30	the	the	DET
cana-2493	300	31	remaining	remain	VERB
cana-2493	300	32	parts	part	NOUN
cana-2493	300	33	of	of	ADP
cana-2493	300	34	the	the	DET
cana-2493	300	35	images	image	NOUN
cana-2493	300	36	''	''	PUNCT
cana-2493	300	37	by	by	ADP
cana-2493	300	38	using	use	VERB
cana-2493	300	39	attention	attention	NOUN
cana-2493	300	40	mechanisms	mechanism	NOUN
cana-2493	300	41	''	''	PUNCT
cana-2493	300	42	.	.	PUNCT
cana-2493	301	1	this	this	DET
cana-2493	301	2	attention	attention	NOUN
cana-2493	301	3	mechanism	mechanism	NOUN
cana-2493	301	4	improved	improve	VERB
cana-2493	301	5	essentially	essentially	ADV
cana-2493	301	6	the	the	DET
cana-2493	301	7	models	model	NOUN
cana-2493	301	8	discriminative	discriminative	VERB
cana-2493	301	9	power	power	NOUN
cana-2493	301	10	of	of	ADP
cana-2493	301	11	infected	infect	VERB
cana-2493	301	12	to	to	ADP
cana-2493	301	13	noninfected	noninfected	ADJ
cana-2493	301	14	regions	region	NOUN
cana-2493	301	15	,	,	PUNCT
cana-2493	301	16	ensuring	ensure	VERB
cana-2493	301	17	more	more	ADV
cana-2493	301	18	accurate	accurate	ADJ
cana-2493	301	19	and	and	CCONJ
cana-2493	301	20	reliable	reliable	ADJ
cana-2493	301	21	diagnoses	diagnosis	NOUN
cana-2493	301	22	.	.	PUNCT
cana-2493	302	1	table	table	NOUN
cana-2493	302	2	2	2	NUM
cana-2493	302	3	.	.	PUNCT
cana-2493	302	4	precision	precision	NOUN
cana-2493	302	5	,	,	PUNCT
cana-2493	302	6	recall	recall	NOUN
cana-2493	302	7	,	,	PUNCT
cana-2493	302	8	f1	f1	NOUN
cana-2493	302	9	-	-	PUNCT
cana-2493	302	10	score	score	NOUN
cana-2493	302	11	,	,	PUNCT
cana-2493	302	12	and	and	CCONJ
cana-2493	302	13	accuracy	accuracy	NOUN
cana-2493	302	14	comparison	comparison	NOUN
cana-2493	302	15	between	between	ADP
cana-2493	302	16	traditional	traditional	ADJ
cana-2493	302	17	cnn	cnn	PROPN
cana-2493	302	18	and	and	CCONJ
cana-2493	302	19	proposed	propose	VERB
cana-2493	302	20	model	model	NOUN
cana-2493	302	21	metric	metric	PROPN
cana-2493	302	22	traditional	traditional	ADJ
cana-2493	302	23	cnn	cnn	PROPN
cana-2493	302	24	proposed	propose	VERB
cana-2493	302	25	model	model	NOUN
cana-2493	302	26	(	(	PUNCT
cana-2493	302	27	attention	attention	NOUN
cana-2493	302	28	+	+	CCONJ
cana-2493	302	29	cross	cross	ADJ
cana-2493	302	30	-	-	ADJ
cana-2493	302	31	average	average	ADJ
cana-2493	302	32	pooling	pooling	NOUN
cana-2493	302	33	)	)	PUNCT
cana-2493	302	34	improvement	improvement	NOUN
cana-2493	302	35	(	(	PUNCT
cana-2493	302	36	%	%	INTJ
cana-2493	302	37	)	)	PUNCT
cana-2493	302	38	precision	precision	NOUN
cana-2493	302	39	(	(	PUNCT
cana-2493	302	40	%	%	INTJ
cana-2493	302	41	)	)	PUNCT
cana-2493	302	42	86.45	86.45	NUM
cana-2493	302	43	93.78	93.78	NUM
cana-2493	303	1	+8.47	+8.47	PROPN
cana-2493	303	2	communications	communication	NOUN
cana-2493	303	3	on	on	ADP
cana-2493	303	4	applied	apply	VERB
cana-2493	303	5	nonlinear	nonlinear	ADJ
cana-2493	303	6	analysis	analysis	NOUN
cana-2493	303	7	issn	issn	NOUN
cana-2493	303	8	:	:	PUNCT
cana-2493	303	9	1074	1074	NUM
cana-2493	303	10	-	-	PUNCT
cana-2493	303	11	133x	133x	NUM
cana-2493	303	12	vol	vol	NOUN
cana-2493	303	13	32	32	NUM
cana-2493	303	14	no	no	NOUN
cana-2493	303	15	.	.	PUNCT
cana-2493	304	1	2s	2s	NUM
cana-2493	304	2	(	(	PUNCT
cana-2493	304	3	2025	2025	NUM
cana-2493	304	4	)	)	PUNCT
cana-2493	304	5	560	560	NUM
cana-2493	304	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	304	7	metric	metric	ADJ
cana-2493	304	8	traditional	traditional	ADJ
cana-2493	304	9	cnn	cnn	PROPN
cana-2493	304	10	proposed	propose	VERB
cana-2493	304	11	model	model	NOUN
cana-2493	304	12	(	(	PUNCT
cana-2493	304	13	attention	attention	NOUN
cana-2493	304	14	+	+	CCONJ
cana-2493	304	15	cross	cross	ADJ
cana-2493	304	16	-	-	ADJ
cana-2493	304	17	average	average	ADJ
cana-2493	304	18	pooling	pooling	NOUN
cana-2493	304	19	)	)	PUNCT
cana-2493	304	20	improvement	improvement	NOUN
cana-2493	304	21	(	(	PUNCT
cana-2493	304	22	%	%	INTJ
cana-2493	304	23	)	)	PUNCT
cana-2493	304	24	recall	recall	NOUN
cana-2493	304	25	(	(	PUNCT
cana-2493	304	26	%	%	INTJ
cana-2493	304	27	)	)	PUNCT
cana-2493	304	28	81.32	81.32	NUM
cana-2493	304	29	92.54	92.54	NUM
cana-2493	304	30	+13.82	+13.82	ADJ
cana-2493	304	31	f1	f1	ADJ
cana-2493	304	32	-	-	PUNCT
cana-2493	304	33	score	score	NOUN
cana-2493	304	34	(	(	PUNCT
cana-2493	304	35	%	%	INTJ
cana-2493	304	36	)	)	PUNCT
cana-2493	304	37	83.72	83.72	NUM
cana-2493	304	38	93.15	93.15	NUM
cana-2493	304	39	+11.25	+11.25	ADJ
cana-2493	304	40	accuracy	accuracy	NOUN
cana-2493	304	41	(	(	PUNCT
cana-2493	304	42	%	%	NOUN
cana-2493	304	43	)	)	PUNCT
cana-2493	304	44	84.50	84.50	NUM
cana-2493	304	45	94.26	94.26	NUM
cana-2493	304	46	+11.55	+11.55	NOUN
cana-2493	304	47	furthermore	furthermore	ADV
cana-2493	304	48	,	,	PUNCT
cana-2493	304	49	with	with	ADP
cana-2493	304	50	the	the	DET
cana-2493	304	51	cross	cross	ADJ
cana-2493	304	52	-	-	ADJ
cana-2493	304	53	average	average	ADJ
cana-2493	304	54	pooling	pooling	NOUN
cana-2493	304	55	method	method	NOUN
cana-2493	304	56	incorporated	incorporate	VERB
cana-2493	304	57	in	in	ADP
cana-2493	304	58	the	the	DET
cana-2493	304	59	model	model	NOUN
cana-2493	304	60	,	,	PUNCT
cana-2493	304	61	this	this	PRON
cana-2493	304	62	also	also	ADV
cana-2493	304	63	boosted	boost	VERB
cana-2493	304	64	its	its	PRON
cana-2493	304	65	potential	potential	NOUN
cana-2493	304	66	to	to	PART
cana-2493	304	67	learn	learn	VERB
cana-2493	304	68	deeper	deep	ADJ
cana-2493	304	69	cancer	cancer	NOUN
cana-2493	304	70	behaviour	behaviour	NOUN
cana-2493	304	71	.	.	PUNCT
cana-2493	305	1	in	in	ADP
cana-2493	305	2	response	response	NOUN
cana-2493	305	3	,	,	PUNCT
cana-2493	305	4	conventional	conventional	ADJ
cana-2493	305	5	pooling	pooling	NOUN
cana-2493	305	6	strategies	strategy	NOUN
cana-2493	305	7	like	like	ADP
cana-2493	305	8	maxpooling	maxpooling	NOUN
cana-2493	305	9	and	and	CCONJ
cana-2493	305	10	average	average	ADJ
cana-2493	305	11	-	-	PUNCT
cana-2493	305	12	pooling	pooling	NOUN
cana-2493	305	13	have	have	AUX
cana-2493	305	14	been	be	AUX
cana-2493	305	15	employed	employ	VERB
cana-2493	305	16	in	in	ADP
cana-2493	305	17	cnns	cnn	NOUN
cana-2493	305	18	for	for	ADP
cana-2493	305	19	eons	eon	NOUN
cana-2493	305	20	to	to	PART
cana-2493	305	21	down	down	VERB
cana-2493	305	22	sample	sample	NOUN
cana-2493	305	23	feature	feature	NOUN
cana-2493	305	24	maps	map	NOUN
cana-2493	305	25	spatially	spatially	ADV
cana-2493	305	26	to	to	PART
cana-2493	305	27	guard	guard	VERB
cana-2493	305	28	against	against	ADP
cana-2493	305	29	overfitting	overfitte	VERB
cana-2493	305	30	as	as	ADV
cana-2493	305	31	well	well	ADV
cana-2493	305	32	as	as	ADP
cana-2493	305	33	restricting	restrict	VERB
cana-2493	305	34	computational	computational	ADJ
cana-2493	305	35	complexity	complexity	NOUN
cana-2493	305	36	.	.	PUNCT
cana-2493	306	1	these	these	DET
cana-2493	306	2	traditional	traditional	ADJ
cana-2493	306	3	approaches	approach	NOUN
cana-2493	306	4	,	,	PUNCT
cana-2493	306	5	however	however	ADV
cana-2493	306	6	,	,	PUNCT
cana-2493	306	7	have	have	VERB
cana-2493	306	8	the	the	DET
cana-2493	306	9	disadvantage	disadvantage	NOUN
cana-2493	306	10	of	of	ADP
cana-2493	306	11	oversimplifying	oversimplify	VERB
cana-2493	306	12	the	the	DET
cana-2493	306	13	data	datum	NOUN
cana-2493	306	14	and	and	CCONJ
cana-2493	306	15	sacrificing	sacrifice	VERB
cana-2493	306	16	rich	rich	ADJ
cana-2493	306	17	finegrained	finegrained	ADJ
cana-2493	306	18	information	information	NOUN
cana-2493	306	19	needed	need	VERB
cana-2493	306	20	in	in	ADP
cana-2493	306	21	many	many	ADJ
cana-2493	306	22	medical	medical	ADJ
cana-2493	306	23	image	image	NOUN
cana-2493	306	24	analysis	analysis	NOUN
cana-2493	306	25	problems	problem	NOUN
cana-2493	306	26	such	such	ADJ
cana-2493	306	27	as	as	ADP
cana-2493	306	28	that	that	PRON
cana-2493	306	29	of	of	ADP
cana-2493	306	30	distinguishing	distinguish	VERB
cana-2493	306	31	subtle	subtle	ADJ
cana-2493	306	32	cancer	cancer	NOUN
cana-2493	306	33	signals	signal	NOUN
cana-2493	306	34	in	in	ADP
cana-2493	306	35	lung	lung	NOUN
cana-2493	306	36	tissue	tissue	NOUN
cana-2493	306	37	.	.	PUNCT
cana-2493	307	1	by	by	ADP
cana-2493	307	2	contrast	contrast	NOUN
cana-2493	307	3	,	,	PUNCT
cana-2493	307	4	cross	cross	ADJ
cana-2493	307	5	-	-	ADJ
cana-2493	307	6	average	average	ADJ
cana-2493	307	7	pooling	pooling	NOUN
cana-2493	307	8	consolidates	consolidate	VERB
cana-2493	307	9	knowledge	knowledge	NOUN
cana-2493	307	10	from	from	ADP
cana-2493	307	11	diverse	diverse	ADJ
cana-2493	307	12	spatial	spatial	ADJ
cana-2493	307	13	regions	region	NOUN
cana-2493	307	14	and	and	CCONJ
cana-2493	307	15	channels	channel	NOUN
cana-2493	307	16	which	which	PRON
cana-2493	307	17	allows	allow	VERB
cana-2493	307	18	the	the	DET
cana-2493	307	19	model	model	NOUN
cana-2493	307	20	to	to	PART
cana-2493	307	21	learn	learn	VERB
cana-2493	307	22	a	a	DET
cana-2493	307	23	wider	wide	ADJ
cana-2493	307	24	range	range	NOUN
cana-2493	307	25	of	of	ADP
cana-2493	307	26	lung	lung	NOUN
cana-2493	307	27	cancer	cancer	NOUN
cana-2493	307	28	patterns	pattern	NOUN
cana-2493	307	29	such	such	ADJ
cana-2493	307	30	as	as	ADP
cana-2493	307	31	opacity	opacity	NOUN
cana-2493	307	32	distributions	distribution	NOUN
cana-2493	307	33	,	,	PUNCT
cana-2493	307	34	surface	surface	NOUN
cana-2493	307	35	textures	texture	NOUN
cana-2493	307	36	,	,	PUNCT
cana-2493	307	37	and	and	CCONJ
cana-2493	307	38	dangerous	dangerous	ADJ
cana-2493	307	39	shapes	shape	NOUN
cana-2493	307	40	.	.	PUNCT
cana-2493	308	1	figure	figure	VERB
cana-2493	308	2	4	4	NUM
cana-2493	308	3	.	.	PUNCT
cana-2493	309	1	performance	performance	NOUN
cana-2493	309	2	comparison	comparison	NOUN
cana-2493	309	3	between	between	ADP
cana-2493	309	4	proposed	propose	VERB
cana-2493	309	5	model	model	NOUN
cana-2493	309	6	with	with	ADP
cana-2493	309	7	traditional	traditional	ADJ
cana-2493	309	8	cnn	cnn	PROPN
cana-2493	309	9	table	table	NOUN
cana-2493	309	10	3	3	NUM
cana-2493	309	11	.	.	PUNCT
cana-2493	309	12	accuracy	accuracy	NOUN
cana-2493	309	13	breakdown	breakdown	NOUN
cana-2493	309	14	by	by	ADP
cana-2493	309	15	type	type	NOUN
cana-2493	309	16	of	of	ADP
cana-2493	309	17	lung	lung	NOUN
cana-2493	309	18	cancer	cancer	NOUN
cana-2493	309	19	(	(	PUNCT
cana-2493	309	20	pneumonia	pneumonia	NOUN
cana-2493	309	21	,	,	PUNCT
cana-2493	309	22	covid-19	covid-19	PROPN
cana-2493	309	23	,	,	PUNCT
cana-2493	309	24	tuberculosis	tuberculosis	NOUN
cana-2493	309	25	)	)	PUNCT
cana-2493	309	26	lung	lung	NOUN
cana-2493	309	27	cancer	cancer	NOUN
cana-2493	309	28	type	type	NOUN
cana-2493	309	29	traditional	traditional	ADJ
cana-2493	309	30	cnn	cnn	PROPN
cana-2493	309	31	accuracy	accuracy	NOUN
cana-2493	309	32	(	(	PUNCT
cana-2493	309	33	%	%	INTJ
cana-2493	309	34	)	)	PUNCT
cana-2493	309	35	proposed	propose	VERB
cana-2493	309	36	model	model	NOUN
cana-2493	309	37	accuracy	accuracy	NOUN
cana-2493	309	38	(	(	PUNCT
cana-2493	309	39	%	%	INTJ
cana-2493	309	40	)	)	PUNCT
cana-2493	309	41	improvement	improvement	NOUN
cana-2493	309	42	(	(	PUNCT
cana-2493	309	43	%	%	NOUN
cana-2493	309	44	)	)	PUNCT
cana-2493	309	45	pneumonia	pneumonia	NOUN
cana-2493	309	46	85.12	85.12	NUM
cana-2493	309	47	93.21	93.21	NUM
cana-2493	310	1	+9.51	+9.51	PROPN
cana-2493	310	2	covid-19	covid-19	PROPN
cana-2493	310	3	88.33	88.33	NUM
cana-2493	310	4	96.12	96.12	NUM
cana-2493	310	5	+8.79	+8.79	NUM
cana-2493	310	6	tuberculosis	tuberculosis	NOUN
cana-2493	310	7	82.47	82.47	NUM
cana-2493	310	8	92.98	92.98	NUM
cana-2493	310	9	+12.74	+12.74	PROPN
cana-2493	310	10	average	average	ADJ
cana-2493	310	11	85.31	85.31	NUM
cana-2493	310	12	94.10	94.10	NUM
cana-2493	310	13	+10.32	+10.32	PROPN
cana-2493	310	14	in	in	ADP
cana-2493	310	15	the	the	DET
cana-2493	310	16	evaluation	evaluation	NOUN
cana-2493	310	17	,	,	PUNCT
cana-2493	310	18	datasets	dataset	NOUN
cana-2493	310	19	contained	contain	VERB
cana-2493	310	20	chest	chest	NOUN
cana-2493	310	21	x	x	NOUN
cana-2493	310	22	-	-	NOUN
cana-2493	310	23	rays	ray	NOUN
cana-2493	310	24	presenting	present	VERB
cana-2493	310	25	different	different	ADJ
cana-2493	310	26	stages	stage	NOUN
cana-2493	310	27	of	of	ADP
cana-2493	310	28	lung	lung	NOUN
cana-2493	310	29	cancers	cancer	NOUN
cana-2493	310	30	ranging	range	VERB
cana-2493	310	31	from	from	ADP
cana-2493	310	32	early	early	ADJ
cana-2493	310	33	-	-	PUNCT
cana-2493	310	34	stage	stage	NOUN
cana-2493	310	35	to	to	ADP
cana-2493	310	36	severe	severe	ADJ
cana-2493	310	37	conditions	condition	NOUN
cana-2493	310	38	.	.	PUNCT
cana-2493	311	1	the	the	DET
cana-2493	311	2	metrics	metric	NOUN
cana-2493	311	3	used	use	VERB
cana-2493	311	4	in	in	ADP
cana-2493	311	5	the	the	DET
cana-2493	311	6	evaluation	evaluation	NOUN
cana-2493	311	7	of	of	ADP
cana-2493	311	8	model	model	NOUN
cana-2493	311	9	performance	performance	NOUN
cana-2493	311	10	are	be	AUX
cana-2493	311	11	:	:	PUNCT
cana-2493	311	12	accuracy	accuracy	NOUN
cana-2493	311	13	precision	precision	NOUN
cana-2493	311	14	recall	recall	VERB
cana-2493	311	15	f1	f1	NOUN
cana-2493	311	16	-	-	PUNCT
cana-2493	311	17	score	score	NOUN
cana-2493	311	18	precision	precision	NOUN
cana-2493	311	19	is	be	AUX
cana-2493	311	20	the	the	DET
cana-2493	311	21	algorithms	algorithms	NOUN
cana-2493	311	22	ability	ability	NOUN
cana-2493	311	23	to	to	PART
cana-2493	311	24	correctly	correctly	ADV
cana-2493	311	25	identify	identify	VERB
cana-2493	311	26	positive	positive	ADJ
cana-2493	311	27	covid	covid	NOUN
cana-2493	311	28	cases	case	NOUN
cana-2493	311	29	and	and	CCONJ
cana-2493	311	30	recall	recall	VERB
cana-2493	311	31	too	too	ADV
cana-2493	311	32	gives	give	VERB
cana-2493	311	33	us	we	PRON
cana-2493	311	34	the	the	DET
cana-2493	311	35	understanding	understanding	NOUN
cana-2493	311	36	of	of	ADP
cana-2493	311	37	how	how	SCONJ
cana-2493	311	38	good	good	ADJ
cana-2493	311	39	it	it	PRON
cana-2493	311	40	performed	perform	VERB
cana-2493	311	41	in	in	ADP
cana-2493	311	42	identifying	identify	VERB
cana-2493	311	43	all	all	DET
cana-2493	311	44	true	true	ADJ
cana-2493	311	45	positive	positive	ADJ
cana-2493	311	46	cases	case	NOUN
cana-2493	311	47	.	.	PUNCT
cana-2493	312	1	the	the	DET
cana-2493	312	2	f1	f1	NOUN
cana-2493	312	3	-	-	PUNCT
cana-2493	312	4	score	score	NOUN
cana-2493	312	5	,	,	PUNCT
cana-2493	312	6	which	which	PRON
cana-2493	312	7	is	be	AUX
cana-2493	312	8	the	the	DET
cana-2493	312	9	harmonic	harmonic	ADJ
cana-2493	312	10	mean	mean	NOUN
cana-2493	312	11	of	of	ADP
cana-2493	312	12	precision	precision	NOUN
cana-2493	312	13	and	and	CCONJ
cana-2493	312	14	recall	recall	NOUN
cana-2493	312	15	,	,	PUNCT
cana-2493	312	16	gives	give	VERB
cana-2493	312	17	a	a	DET
cana-2493	312	18	balance	balance	NOUN
cana-2493	312	19	or	or	CCONJ
cana-2493	312	20	an	an	DET
cana-2493	312	21	overall	overall	ADJ
cana-2493	312	22	performance	performance	NOUN
cana-2493	312	23	measure	measure	NOUN
cana-2493	312	24	how	how	SCONJ
cana-2493	312	25	well	well	ADV
cana-2493	312	26	our	our	PRON
cana-2493	312	27	model	model	NOUN
cana-2493	312	28	did	do	VERB
cana-2493	312	29	.	.	PUNCT
cana-2493	313	1	thus	thus	ADV
cana-2493	313	2	,	,	PUNCT
cana-2493	313	3	based	base	VERB
cana-2493	313	4	on	on	ADP
cana-2493	313	5	our	our	PRON
cana-2493	313	6	metrics	metric	NOUN
cana-2493	313	7	improvements	improvement	NOUN
cana-2493	313	8	communications	communication	NOUN
cana-2493	313	9	on	on	ADP
cana-2493	313	10	applied	apply	VERB
cana-2493	313	11	nonlinear	nonlinear	ADJ
cana-2493	313	12	analysis	analysis	NOUN
cana-2493	313	13	issn	issn	NOUN
cana-2493	313	14	:	:	PUNCT
cana-2493	313	15	1074	1074	NUM
cana-2493	313	16	-	-	PUNCT
cana-2493	313	17	133x	133x	NUM
cana-2493	313	18	vol	vol	NOUN
cana-2493	313	19	32	32	NUM
cana-2493	313	20	no	no	NOUN
cana-2493	313	21	.	.	PUNCT
cana-2493	314	1	2s	2s	NUM
cana-2493	314	2	(	(	PUNCT
cana-2493	314	3	2025	2025	NUM
cana-2493	314	4	)	)	PUNCT
cana-2493	314	5	561	561	NUM
cana-2493	314	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	315	1	we	we	PRON
cana-2493	315	2	conclude	conclude	VERB
cana-2493	315	3	that	that	SCONJ
cana-2493	315	4	the	the	DET
cana-2493	315	5	model	model	NOUN
cana-2493	315	6	has	have	VERB
cana-2493	315	7	high	high	ADJ
cana-2493	315	8	potential	potential	NOUN
cana-2493	315	9	to	to	PART
cana-2493	315	10	be	be	AUX
cana-2493	315	11	able	able	ADJ
cana-2493	315	12	to	to	PART
cana-2493	315	13	identify	identify	VERB
cana-2493	315	14	lung	lung	NOUN
cana-2493	315	15	cancers	cancer	NOUN
cana-2493	315	16	across	across	ADP
cana-2493	315	17	heterogenous	heterogenous	ADJ
cana-2493	315	18	clinical	clinical	ADJ
cana-2493	315	19	settings	setting	NOUN
cana-2493	315	20	.	.	PUNCT
cana-2493	316	1	table	table	NOUN
cana-2493	316	2	4	4	NUM
cana-2493	316	3	.	.	PUNCT
cana-2493	316	4	comparison	comparison	NOUN
cana-2493	316	5	of	of	ADP
cana-2493	316	6	precision	precision	NOUN
cana-2493	316	7	,	,	PUNCT
cana-2493	316	8	recall	recall	NOUN
cana-2493	316	9	,	,	PUNCT
cana-2493	316	10	and	and	CCONJ
cana-2493	316	11	f1	f1	NOUN
cana-2493	316	12	-	-	PUNCT
cana-2493	316	13	score	score	NOUN
cana-2493	316	14	across	across	ADP
cana-2493	316	15	different	different	ADJ
cana-2493	316	16	datasets	dataset	NOUN
cana-2493	317	1	dataset	dataset	NOUN
cana-2493	317	2	precision	precision	NOUN
cana-2493	317	3	(	(	PUNCT
cana-2493	317	4	%	%	INTJ
cana-2493	317	5	)	)	PUNCT
cana-2493	317	6	recall	recall	NOUN
cana-2493	317	7	(	(	PUNCT
cana-2493	317	8	%	%	NOUN
cana-2493	317	9	)	)	PUNCT
cana-2493	317	10	f1	f1	NOUN
cana-2493	317	11	-	-	PUNCT
cana-2493	317	12	score	score	NOUN
cana-2493	317	13	(	(	PUNCT
cana-2493	317	14	%	%	INTJ
cana-2493	317	15	)	)	PUNCT
cana-2493	317	16	accuracy	accuracy	NOUN
cana-2493	317	17	(	(	PUNCT
cana-2493	317	18	%	%	INTJ
cana-2493	317	19	)	)	PUNCT
cana-2493	317	20	lidc	lidc	ADJ
cana-2493	317	21	-	-	PUNCT
cana-2493	317	22	idri	idri	NOUN
cana-2493	317	23	92.34	92.34	NUM
cana-2493	317	24	91.82	91.82	NUM
cana-2493	317	25	92.08	92.08	NUM
cana-2493	317	26	93.75	93.75	NUM
cana-2493	317	27	covid-19	covid-19	PROPN
cana-2493	317	28	radiography	radiography	NOUN
cana-2493	317	29	database	database	NOUN
cana-2493	317	30	95.21	95.21	NUM
cana-2493	317	31	94.79	94.79	NUM
cana-2493	317	32	95.00	95.00	NUM
cana-2493	317	33	96.45	96.45	NUM
cana-2493	317	34	rsna	rsna	NOUN
cana-2493	317	35	pneumonia	pneumonia	NOUN
cana-2493	317	36	detection	detection	NOUN
cana-2493	317	37	90.41	90.41	NUM
cana-2493	317	38	89.73	89.73	NUM
cana-2493	317	39	90.06	90.06	NUM
cana-2493	317	40	91.84	91.84	NUM
cana-2493	317	41	nih	nih	PROPN
cana-2493	317	42	chest	chest	PROPN
cana-2493	317	43	x	x	PROPN
cana-2493	317	44	-	-	NOUN
cana-2493	317	45	ray	ray	NOUN
cana-2493	317	46	dataset	dataset	VERB
cana-2493	317	47	91.67	91.67	NUM
cana-2493	317	48	91.10	91.10	NUM
cana-2493	317	49	91.38	91.38	NUM
cana-2493	317	50	92.55	92.55	NUM
cana-2493	317	51	average	average	NOUN
cana-2493	317	52	92.41	92.41	NUM
cana-2493	317	53	91.86	91.86	NUM
cana-2493	317	54	92.13	92.13	NUM
cana-2493	317	55	93.65	93.65	NUM
cana-2493	317	56	our	our	PRON
cana-2493	317	57	model	model	NOUN
cana-2493	317	58	achieves	achieve	VERB
cana-2493	317	59	much	much	ADV
cana-2493	317	60	higher	high	ADJ
cana-2493	317	61	precision	precision	NOUN
cana-2493	317	62	than	than	ADP
cana-2493	317	63	conventional	conventional	ADJ
cana-2493	317	64	cnn	cnn	PROPN
cana-2493	317	65	approaches	approach	NOUN
cana-2493	317	66	,	,	PUNCT
cana-2493	317	67	which	which	PRON
cana-2493	317	68	implies	imply	VERB
cana-2493	317	69	the	the	DET
cana-2493	317	70	model	model	NOUN
cana-2493	317	71	could	could	AUX
cana-2493	317	72	utilize	utilize	VERB
cana-2493	317	73	attention	attention	NOUN
cana-2493	317	74	mechanism	mechanism	NOUN
cana-2493	317	75	and	and	CCONJ
cana-2493	317	76	cross	cross	ADJ
cana-2493	317	77	-	-	ADJ
cana-2493	317	78	average	average	ADJ
cana-2493	317	79	pooling	pooling	NOUN
cana-2493	317	80	to	to	PART
cana-2493	317	81	highlight	highlight	VERB
cana-2493	317	82	the	the	DET
cana-2493	317	83	crucial	crucial	ADJ
cana-2493	317	84	areas	area	NOUN
cana-2493	317	85	of	of	ADP
cana-2493	317	86	the	the	DET
cana-2493	317	87	image	image	NOUN
cana-2493	317	88	that	that	PRON
cana-2493	317	89	matter	matter	ADV
cana-2493	317	90	(	(	PUNCT
cana-2493	317	91	decrease	decrease	VERB
cana-2493	317	92	false	false	ADJ
cana-2493	317	93	positives	positive	NOUN
cana-2493	317	94	)	)	PUNCT
cana-2493	317	95	.	.	PUNCT
cana-2493	318	1	this	this	PRON
cana-2493	318	2	is	be	AUX
cana-2493	318	3	especially	especially	ADV
cana-2493	318	4	crucial	crucial	ADJ
cana-2493	318	5	in	in	ADP
cana-2493	318	6	clinical	clinical	ADJ
cana-2493	318	7	practice	practice	NOUN
cana-2493	318	8	where	where	SCONJ
cana-2493	318	9	a	a	DET
cana-2493	318	10	misstep	misstep	NOUN
cana-2493	318	11	can	can	AUX
cana-2493	318	12	result	result	VERB
cana-2493	318	13	in	in	ADP
cana-2493	318	14	treatments	treatment	NOUN
cana-2493	318	15	that	that	PRON
cana-2493	318	16	are	be	AUX
cana-2493	318	17	not	not	PART
cana-2493	318	18	warranted	warrant	VERB
cana-2493	318	19	or	or	CCONJ
cana-2493	318	20	the	the	DET
cana-2493	318	21	increase	increase	NOUN
cana-2493	318	22	of	of	ADP
cana-2493	318	23	patient	patient	ADJ
cana-2493	318	24	anxiety	anxiety	NOUN
cana-2493	318	25	.	.	PUNCT
cana-2493	319	1	the	the	DET
cana-2493	319	2	accuracy	accuracy	NOUN
cana-2493	319	3	was	be	AUX
cana-2493	319	4	again	again	ADV
cana-2493	319	5	improved	improve	VERB
cana-2493	319	6	with	with	ADP
cana-2493	319	7	a	a	DET
cana-2493	319	8	higher	high	ADJ
cana-2493	319	9	recall	recall	NOUN
cana-2493	319	10	rate	rate	NOUN
cana-2493	319	11	,	,	PUNCT
cana-2493	319	12	meaning	mean	VERB
cana-2493	319	13	the	the	DET
cana-2493	319	14	model	model	NOUN
cana-2493	319	15	was	be	AUX
cana-2493	319	16	able	able	ADJ
cana-2493	319	17	to	to	PART
cana-2493	319	18	identify	identify	VERB
cana-2493	319	19	more	more	ADV
cana-2493	319	20	true	true	ADJ
cana-2493	319	21	positive	positive	ADJ
cana-2493	319	22	cases	case	NOUN
cana-2493	319	23	of	of	ADP
cana-2493	319	24	lung	lung	NOUN
cana-2493	319	25	cancers	cancer	NOUN
cana-2493	319	26	–	–	PUNCT
cana-2493	319	27	which	which	PRON
cana-2493	319	28	is	be	AUX
cana-2493	319	29	vital	vital	ADJ
cana-2493	319	30	for	for	ADP
cana-2493	319	31	timely	timely	ADJ
cana-2493	319	32	diagnosis	diagnosis	NOUN
cana-2493	319	33	and	and	CCONJ
cana-2493	319	34	treatment	treatment	NOUN
cana-2493	319	35	in	in	ADP
cana-2493	319	36	these	these	DET
cana-2493	319	37	patients	patient	NOUN
cana-2493	319	38	.	.	PUNCT
cana-2493	320	1	figure	figure	VERB
cana-2493	320	2	5	5	NUM
cana-2493	320	3	.	.	PUNCT
cana-2493	320	4	impact	impact	NOUN
cana-2493	320	5	of	of	ADP
cana-2493	320	6	attention	attention	NOUN
cana-2493	320	7	mechanism	mechanism	NOUN
cana-2493	320	8	and	and	CCONJ
cana-2493	320	9	multi	multi	ADJ
cana-2493	320	10	scale	scale	NOUN
cana-2493	320	11	network	network	NOUN
cana-2493	320	12	table	table	NOUN
cana-2493	320	13	5	5	NUM
cana-2493	320	14	.	.	PUNCT
cana-2493	320	15	model	model	NOUN
cana-2493	320	16	performance	performance	NOUN
cana-2493	320	17	on	on	ADP
cana-2493	320	18	different	different	ADJ
cana-2493	320	19	image	image	NOUN
cana-2493	320	20	quality	quality	NOUN
cana-2493	320	21	levels	level	NOUN
cana-2493	320	22	(	(	PUNCT
cana-2493	320	23	high	high	ADJ
cana-2493	320	24	,	,	PUNCT
cana-2493	320	25	medium	medium	ADJ
cana-2493	320	26	,	,	PUNCT
cana-2493	320	27	low	low	ADJ
cana-2493	320	28	)	)	PUNCT
cana-2493	320	29	image	image	NOUN
cana-2493	320	30	quality	quality	NOUN
cana-2493	320	31	traditional	traditional	ADJ
cana-2493	320	32	cnn	cnn	PROPN
cana-2493	320	33	precision	precision	NOUN
cana-2493	320	34	(	(	PUNCT
cana-2493	320	35	%	%	INTJ
cana-2493	320	36	)	)	PUNCT
cana-2493	320	37	proposed	propose	VERB
cana-2493	320	38	model	model	NOUN
cana-2493	320	39	precision	precision	NOUN
cana-2493	320	40	(	(	PUNCT
cana-2493	320	41	%	%	INTJ
cana-2493	320	42	)	)	PUNCT
cana-2493	320	43	traditional	traditional	ADJ
cana-2493	320	44	cnn	cnn	PROPN
cana-2493	320	45	recall	recall	NOUN
cana-2493	320	46	(	(	PUNCT
cana-2493	320	47	%	%	NOUN
cana-2493	320	48	)	)	PUNCT
cana-2493	320	49	proposed	propose	VERB
cana-2493	320	50	model	model	NOUN
cana-2493	320	51	recall	recall	PROPN
cana-2493	320	52	(	(	PUNCT
cana-2493	320	53	%	%	INTJ
cana-2493	320	54	)	)	PUNCT
cana-2493	320	55	traditional	traditional	ADJ
cana-2493	320	56	cnn	cnn	PROPN
cana-2493	320	57	accuracy	accuracy	NOUN
cana-2493	320	58	(	(	PUNCT
cana-2493	320	59	%	%	INTJ
cana-2493	320	60	)	)	PUNCT
cana-2493	320	61	proposed	propose	VERB
cana-2493	320	62	model	model	NOUN
cana-2493	320	63	accuracy	accuracy	NOUN
cana-2493	320	64	(	(	PUNCT
cana-2493	320	65	%	%	INTJ
cana-2493	320	66	)	)	PUNCT
cana-2493	320	67	high	high	ADJ
cana-2493	320	68	90.22	90.22	NUM
cana-2493	320	69	95.68	95.68	NUM
cana-2493	320	70	88.95	88.95	NUM
cana-2493	320	71	94.85	94.85	NUM
cana-2493	320	72	89.47	89.47	NUM
cana-2493	320	73	95.25	95.25	NUM
cana-2493	320	74	medium	medium	NOUN
cana-2493	320	75	83.47	83.47	NUM
cana-2493	320	76	91.32	91.32	NUM
cana-2493	320	77	81.29	81.29	NUM
cana-2493	320	78	90.14	90.14	NUM
cana-2493	320	79	82.38	82.38	NUM
cana-2493	320	80	91.12	91.12	NUM
cana-2493	320	81	low	low	ADJ
cana-2493	320	82	74.55	74.55	NUM
cana-2493	320	83	86.23	86.23	NUM
cana-2493	320	84	71.34	71.34	NUM
cana-2493	320	85	85.49	85.49	NUM
cana-2493	320	86	72.89	72.89	NUM
cana-2493	320	87	86.09	86.09	NUM
cana-2493	320	88	one	one	NUM
cana-2493	320	89	of	of	ADP
cana-2493	320	90	the	the	DET
cana-2493	320	91	main	main	ADJ
cana-2493	320	92	strong	strong	ADJ
cana-2493	320	93	points	point	NOUN
cana-2493	320	94	of	of	ADP
cana-2493	320	95	our	our	PRON
cana-2493	320	96	model	model	NOUN
cana-2493	320	97	is	be	AUX
cana-2493	320	98	its	its	PRON
cana-2493	320	99	luxury	luxury	NOUN
cana-2493	320	100	to	to	PART
cana-2493	320	101	work	work	VERB
cana-2493	320	102	with	with	ADP
cana-2493	320	103	other	other	ADJ
cana-2493	320	104	datasets	dataset	NOUN
cana-2493	320	105	and	and	CCONJ
cana-2493	320	106	cancer	cancer	NOUN
cana-2493	320	107	types	type	NOUN
cana-2493	320	108	as	as	ADV
cana-2493	320	109	well	well	ADV
cana-2493	320	110	.	.	PUNCT
cana-2493	321	1	the	the	DET
cana-2493	321	2	cross	cross	ADJ
cana-2493	321	3	-	-	ADJ
cana-2493	321	4	average	average	ADJ
cana-2493	321	5	pooling	pooling	NOUN
cana-2493	321	6	enables	enable	VERB
cana-2493	321	7	the	the	DET
cana-2493	321	8	model	model	NOUN
cana-2493	321	9	to	to	PART
cana-2493	321	10	generalize	generalize	VERB
cana-2493	321	11	for	for	ADP
cana-2493	321	12	from	from	ADP
cana-2493	321	13	one	one	NUM
cana-2493	321	14	cancer	cancer	NOUN
cana-2493	321	15	presentation	presentation	NOUN
cana-2493	321	16	(	(	PUNCT
cana-2493	321	17	bacterial	bacterial	ADJ
cana-2493	321	18	pneumonia	pneumonia	NOUN
cana-2493	321	19	,	,	PUNCT
cana-2493	321	20	viral	viral	ADJ
cana-2493	321	21	pneumonia	pneumonia	NOUN
cana-2493	321	22	or	or	CCONJ
cana-2493	321	23	covid-19	covid-19	PROPN
cana-2493	321	24	)	)	PUNCT
cana-2493	321	25	to	to	ADP
cana-2493	321	26	another	another	PRON
cana-2493	321	27	it	it	PRON
cana-2493	321	28	does	do	VERB
cana-2493	321	29	so	so	ADV
cana-2493	321	30	as	as	SCONJ
cana-2493	321	31	each	each	PRON
cana-2493	321	32	usually	usually	ADV
cana-2493	321	33	have	have	AUX
cana-2493	321	34	averaged	average	VERB
cana-2493	321	35	partner	partner	NOUN
cana-2493	321	36	in	in	ADP
cana-2493	321	37	different	different	ADJ
cana-2493	321	38	pattern	pattern	NOUN
cana-2493	321	39	on	on	ADP
cana-2493	321	40	the	the	DET
cana-2493	321	41	chest	chest	NOUN
cana-2493	321	42	x	x	NOUN
cana-2493	321	43	-	-	NOUN
cana-2493	321	44	ray	ray	NOUN
cana-2493	321	45	images	image	NOUN
cana-2493	321	46	.	.	PUNCT
cana-2493	322	1	for	for	ADP
cana-2493	322	2	instance	instance	NOUN
cana-2493	322	3	,	,	PUNCT
cana-2493	322	4	bacterial	bacterial	ADJ
cana-2493	322	5	pneumonia	pneumonia	NOUN
cana-2493	322	6	can	can	AUX
cana-2493	322	7	show	show	VERB
cana-2493	322	8	up	up	ADP
cana-2493	322	9	with	with	ADP
cana-2493	322	10	focal	focal	ADJ
cana-2493	322	11	consolidation	consolidation	NOUN
cana-2493	322	12	,	,	PUNCT
cana-2493	322	13	however	however	ADV
cana-2493	322	14	viral	viral	ADJ
cana-2493	322	15	cancers	cancer	NOUN
cana-2493	322	16	,	,	PUNCT
cana-2493	322	17	for	for	ADP
cana-2493	322	18	example	example	NOUN
cana-2493	322	19	covid-19	covid-19	PROPN
cana-2493	322	20	may	may	AUX
cana-2493	322	21	look	look	VERB
cana-2493	322	22	like	like	ADP
cana-2493	322	23	communications	communication	NOUN
cana-2493	322	24	on	on	ADP
cana-2493	322	25	applied	apply	VERB
cana-2493	322	26	nonlinear	nonlinear	ADJ
cana-2493	322	27	analysis	analysis	NOUN
cana-2493	322	28	issn	issn	NOUN
cana-2493	322	29	:	:	PUNCT
cana-2493	322	30	1074	1074	NUM
cana-2493	322	31	-	-	PUNCT
cana-2493	322	32	133x	133x	NUM
cana-2493	322	33	vol	vol	NOUN
cana-2493	322	34	32	32	NUM
cana-2493	322	35	no	no	NOUN
cana-2493	322	36	.	.	PUNCT
cana-2493	323	1	2s	2s	NUM
cana-2493	323	2	(	(	PUNCT
cana-2493	323	3	2025	2025	NUM
cana-2493	323	4	)	)	PUNCT
cana-2493	323	5	562	562	NUM
cana-2493	323	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-2493	323	7	diffused	diffused	ADJ
cana-2493	323	8	ground	ground	NOUN
cana-2493	323	9	glass	glass	NOUN
cana-2493	323	10	opacities	opacity	NOUN
cana-2493	323	11	.	.	PUNCT
cana-2493	324	1	performance	performance	NOUN
cana-2493	324	2	in	in	ADP
cana-2493	324	3	terms	term	NOUN
cana-2493	324	4	of	of	ADP
cana-2493	324	5	accuracy	accuracy	NOUN
cana-2493	324	6	was	be	AUX
cana-2493	324	7	better	well	ADJ
cana-2493	324	8	overall	overall	ADV
cana-2493	324	9	using	use	VERB
cana-2493	324	10	our	our	PRON
cana-2493	324	11	model	model	NOUN
cana-2493	324	12	for	for	ADP
cana-2493	324	13	all	all	DET
cana-2493	324	14	groups	group	NOUN
cana-2493	324	15	of	of	ADP
cana-2493	324	16	cancers	cancer	NOUN
cana-2493	324	17	due	due	ADP
cana-2493	324	18	to	to	ADP
cana-2493	324	19	the	the	DET
cana-2493	324	20	successful	successful	ADJ
cana-2493	324	21	differentiation	differentiation	NOUN
cana-2493	324	22	between	between	ADP
cana-2493	324	23	these	these	DET
cana-2493	324	24	cancer	cancer	NOUN
cana-2493	324	25	claims	claim	NOUN
cana-2493	324	26	in	in	ADP
cana-2493	324	27	those	those	DET
cana-2493	324	28	3	3	NUM
cana-2493	324	29	error	error	NOUN
cana-2493	324	30	cases	case	NOUN
cana-2493	324	31	.	.	PUNCT
cana-2493	325	1	figure	figure	VERB
cana-2493	325	2	6	6	NUM
cana-2493	325	3	.	.	PUNCT
cana-2493	325	4	sensitivity	sensitivity	NOUN
cana-2493	325	5	and	and	CCONJ
cana-2493	325	6	specificity	specificity	NOUN
cana-2493	325	7	comparison	comparison	NOUN
cana-2493	325	8	table	table	NOUN
cana-2493	325	9	6	6	NUM
cana-2493	325	10	.	.	PUNCT
cana-2493	325	11	performance	performance	NOUN
cana-2493	325	12	on	on	ADP
cana-2493	325	13	early	early	ADJ
cana-2493	325	14	-	-	PUNCT
cana-2493	325	15	stage	stage	NOUN
cana-2493	325	16	vs.	vs.	ADP
cana-2493	325	17	late	late	ADJ
cana-2493	325	18	-	-	PUNCT
cana-2493	325	19	stage	stage	NOUN
cana-2493	325	20	cancers	cancer	NOUN
cana-2493	325	21	cancer	cancer	NOUN
cana-2493	325	22	stage	stage	NOUN
cana-2493	325	23	traditional	traditional	ADJ
cana-2493	325	24	cnn	cnn	PROPN
cana-2493	325	25	precision	precision	NOUN
cana-2493	325	26	(	(	PUNCT
cana-2493	325	27	%	%	INTJ
cana-2493	325	28	)	)	PUNCT
cana-2493	325	29	proposed	propose	VERB
cana-2493	325	30	model	model	NOUN
cana-2493	325	31	precision	precision	NOUN
cana-2493	325	32	(	(	PUNCT
cana-2493	325	33	%	%	INTJ
cana-2493	325	34	)	)	PUNCT
cana-2493	325	35	traditional	traditional	ADJ
cana-2493	325	36	cnn	cnn	PROPN
cana-2493	325	37	recall	recall	NOUN
cana-2493	325	38	(	(	PUNCT
cana-2493	325	39	%	%	NOUN
cana-2493	325	40	)	)	PUNCT
cana-2493	325	41	proposed	propose	VERB
cana-2493	325	42	model	model	NOUN
cana-2493	325	43	recall	recall	PROPN
cana-2493	325	44	(	(	PUNCT
cana-2493	325	45	%	%	INTJ
cana-2493	325	46	)	)	PUNCT
cana-2493	325	47	traditional	traditional	ADJ
cana-2493	325	48	cnn	cnn	PROPN
cana-2493	325	49	accuracy	accuracy	NOUN
cana-2493	325	50	(	(	PUNCT
cana-2493	325	51	%	%	INTJ
cana-2493	325	52	)	)	PUNCT
cana-2493	325	53	proposed	propose	VERB
cana-2493	325	54	model	model	NOUN
cana-2493	325	55	accuracy	accuracy	NOUN
cana-2493	325	56	(	(	PUNCT
cana-2493	325	57	%	%	INTJ
cana-2493	325	58	)	)	PUNCT
cana-2493	325	59	early	early	ADJ
cana-2493	325	60	-	-	PUNCT
cana-2493	325	61	stage	stage	NOUN
cana-2493	325	62	80.12	80.12	NUM
cana-2493	325	63	90.45	90.45	NUM
cana-2493	325	64	78.45	78.45	NUM
cana-2493	325	65	89.32	89.32	NUM
cana-2493	325	66	79.28	79.28	NUM
cana-2493	325	67	90.01	90.01	NUM
cana-2493	325	68	late	late	ADJ
cana-2493	325	69	-	-	PUNCT
cana-2493	325	70	stage	stage	NOUN
cana-2493	325	71	88.67	88.67	NUM
cana-2493	325	72	95.11	95.11	NUM
cana-2493	325	73	85.54	85.54	NUM
cana-2493	325	74	94.34	94.34	NUM
cana-2493	325	75	87.12	87.12	NUM
cana-2493	325	76	94.82	94.82	NUM
cana-2493	325	77	in	in	ADP
cana-2493	325	78	addition	addition	NOUN
cana-2493	325	79	to	to	ADP
cana-2493	325	80	this	this	PRON
cana-2493	325	81	,	,	PUNCT
cana-2493	325	82	we	we	PRON
cana-2493	325	83	ran	run	VERB
cana-2493	325	84	more	more	ADJ
cana-2493	325	85	experiments	experiment	NOUN
cana-2493	325	86	on	on	ADP
cana-2493	325	87	multiple	multiple	ADJ
cana-2493	325	88	datasets	dataset	NOUN
cana-2493	325	89	using	use	VERB
cana-2493	325	90	images	image	NOUN
cana-2493	325	91	of	of	ADP
cana-2493	325	92	different	different	ADJ
cana-2493	325	93	qualities	quality	NOUN
cana-2493	325	94	and	and	CCONJ
cana-2493	325	95	cancer	cancer	NOUN
cana-2493	325	96	severity	severity	NOUN
cana-2493	325	97	levels	level	NOUN
cana-2493	325	98	to	to	PART
cana-2493	325	99	illustrate	illustrate	VERB
cana-2493	325	100	just	just	ADV
cana-2493	325	101	how	how	SCONJ
cana-2493	325	102	robust	robust	ADJ
cana-2493	325	103	the	the	DET
cana-2493	325	104	model	model	NOUN
cana-2493	325	105	is	be	AUX
cana-2493	325	106	.	.	PUNCT
cana-2493	326	1	across	across	ADP
cana-2493	326	2	all	all	DET
cana-2493	326	3	results	result	NOUN
cana-2493	326	4	,	,	PUNCT
cana-2493	326	5	the	the	DET
cana-2493	326	6	proposed	propose	VERB
cana-2493	326	7	approach	approach	NOUN
cana-2493	326	8	performed	perform	VERB
cana-2493	326	9	remarkably	remarkably	ADV
cana-2493	326	10	well	well	ADV
cana-2493	326	11	compared	compare	VERB
cana-2493	326	12	to	to	ADP
cana-2493	326	13	conventional	conventional	ADJ
cana-2493	326	14	cnn	cnn	PROPN
cana-2493	326	15	models	model	NOUN
cana-2493	326	16	(	(	PUNCT
cana-2493	326	17	figure	figure	NOUN
cana-2493	326	18	3	3	NUM
cana-2493	326	19	)	)	PUNCT
cana-2493	326	20	,	,	PUNCT
cana-2493	326	21	with	with	ADP
cana-2493	326	22	evident	evident	ADJ
cana-2493	326	23	superiority	superiority	NOUN
cana-2493	326	24	in	in	ADP
cana-2493	326	25	a	a	DET
cana-2493	326	26	number	number	NOUN
cana-2493	326	27	of	of	ADP
cana-2493	326	28	experiments	experiment	NOUN
cana-2493	326	29	that	that	PRON
cana-2493	326	30	featured	feature	VERB
cana-2493	326	31	subtle	subtle	ADJ
cana-2493	326	32	or	or	CCONJ
cana-2493	326	33	overlapped	overlapped	ADJ
cana-2493	326	34	cancer	cancer	NOUN
cana-2493	326	35	features	feature	NOUN
cana-2493	326	36	.	.	PUNCT
cana-2493	327	1	the	the	DET
cana-2493	327	2	attention	attention	NOUN
cana-2493	327	3	mean	mean	VERB
cana-2493	327	4	that	that	SCONJ
cana-2493	327	5	the	the	DET
cana-2493	327	6	model	model	NOUN
cana-2493	327	7	was	be	AUX
cana-2493	327	8	put	put	VERB
cana-2493	327	9	more	more	ADJ
cana-2493	327	10	congruity	congruity	NOUN
cana-2493	327	11	into	into	ADP
cana-2493	327	12	the	the	DET
cana-2493	327	13	most	most	ADV
cana-2493	327	14	probable	probable	ADJ
cana-2493	327	15	cancer	cancer	NOUN
cana-2493	327	16	-	-	PUNCT
cana-2493	327	17	related	relate	VERB
cana-2493	327	18	locations	location	NOUN
cana-2493	327	19	where	where	SCONJ
cana-2493	327	20	they	they	PRON
cana-2493	327	21	were	be	AUX
cana-2493	327	22	hardly	hardly	ADV
cana-2493	327	23	observed	observe	VERB
cana-2493	327	24	visually	visually	ADV
cana-2493	327	25	.	.	PUNCT
cana-2493	328	1	table	table	NOUN
cana-2493	328	2	7	7	NUM
cana-2493	328	3	.	.	PUNCT
cana-2493	328	4	execution	execution	NOUN
cana-2493	328	5	time	time	NOUN
cana-2493	328	6	and	and	CCONJ
cana-2493	328	7	resource	resource	NOUN
cana-2493	328	8	utilization	utilization	NOUN
cana-2493	328	9	for	for	ADP
cana-2493	328	10	traditional	traditional	ADJ
cana-2493	328	11	cnn	cnn	PROPN
cana-2493	328	12	vs.	vs.	ADP
cana-2493	328	13	proposed	propose	VERB
cana-2493	328	14	model	model	NOUN
cana-2493	328	15	model	model	NOUN
cana-2493	328	16	training	training	NOUN
cana-2493	328	17	time	time	NOUN
cana-2493	328	18	(	(	PUNCT
cana-2493	328	19	hrs	hrs	NOUN
cana-2493	328	20	)	)	PUNCT
cana-2493	328	21	inference	inference	NOUN
cana-2493	328	22	time	time	NOUN
cana-2493	328	23	(	(	PUNCT
cana-2493	328	24	ms	ms	PROPN
cana-2493	328	25	)	)	PUNCT
cana-2493	328	26	gpu	gpu	NOUN
cana-2493	328	27	memory	memory	NOUN
cana-2493	328	28	usage	usage	NOUN
cana-2493	328	29	(	(	PUNCT
cana-2493	328	30	gb	gb	NOUN
cana-2493	328	31	)	)	PUNCT
cana-2493	328	32	cpu	cpu	NOUN
cana-2493	328	33	utilization	utilization	NOUN
cana-2493	328	34	(	(	PUNCT
cana-2493	328	35	%	%	INTJ
cana-2493	328	36	)	)	PUNCT
cana-2493	328	37	traditional	traditional	ADJ
cana-2493	328	38	cnn	cnn	PROPN
cana-2493	328	39	6.4	6.4	NUM
cana-2493	328	40	128	128	NUM
cana-2493	328	41	12.5	12.5	NUM
cana-2493	328	42	70	70	NUM
cana-2493	328	43	proposed	propose	VERB
cana-2493	328	44	model	model	NOUN
cana-2493	328	45	5.3	5.3	NUM
cana-2493	328	46	102	102	NUM
cana-2493	328	47	15.8	15.8	NUM
cana-2493	328	48	78	78	NUM
cana-2493	328	49	improvement	improvement	NOUN
cana-2493	328	50	-17.19	-17.19	NOUN
cana-2493	328	51	%	%	NOUN
cana-2493	328	52	-20.31	-20.31	NOUN
cana-2493	328	53	%	%	NOUN
cana-2493	328	54	+26.4	+26.4	NUM
cana-2493	328	55	%	%	NOUN
cana-2493	328	56	+11.43	+11.43	ADJ
cana-2493	328	57	%	%	NOUN
cana-2493	328	58	our	our	PRON
cana-2493	328	59	model	model	NOUN
cana-2493	328	60	not	not	PART
cana-2493	328	61	only	only	ADV
cana-2493	328	62	enhances	enhance	VERB
cana-2493	328	63	diagnostic	diagnostic	ADJ
cana-2493	328	64	precision	precision	NOUN
cana-2493	328	65	but	but	CCONJ
cana-2493	328	66	also	also	ADV
cana-2493	328	67	carries	carry	VERB
cana-2493	328	68	major	major	ADJ
cana-2493	328	69	repercussions	repercussion	NOUN
cana-2493	328	70	in	in	ADP
cana-2493	328	71	daily	daily	ADJ
cana-2493	328	72	clinical	clinical	ADJ
cana-2493	328	73	practice	practice	NOUN
cana-2493	328	74	.	.	PUNCT
cana-2493	329	1	automating	automate	VERB
cana-2493	329	2	this	this	DET
cana-2493	329	3	process	process	NOUN
cana-2493	329	4	would	would	AUX
cana-2493	329	5	be	be	AUX
cana-2493	329	6	a	a	DET
cana-2493	329	7	boon	boon	NOUN
cana-2493	329	8	to	to	ADP
cana-2493	329	9	radiologists	radiologist	NOUN
cana-2493	329	10	and	and	CCONJ
cana-2493	329	11	also	also	ADV
cana-2493	329	12	free	free	VERB
cana-2493	329	13	up	up	ADP
cana-2493	329	14	massive	massive	ADJ
cana-2493	329	15	amount	amount	NOUN
cana-2493	329	16	of	of	ADP
cana-2493	329	17	workload	workload	NOUN
cana-2493	329	18	,	,	PUNCT
cana-2493	329	19	especially	especially	ADV
cana-2493	329	20	in	in	ADP
cana-2493	329	21	low	low	ADJ
cana-2493	329	22	-	-	PUNCT
cana-2493	329	23	resource	resource	NOUN
cana-2493	329	24	settings	setting	NOUN
cana-2493	329	25	where	where	SCONJ
cana-2493	329	26	presence	presence	NOUN
cana-2493	329	27	of	of	ADP
cana-2493	329	28	expert	expert	NOUN
cana-2493	329	29	clinicians	clinician	NOUN
cana-2493	329	30	can	can	AUX
cana-2493	329	31	often	often	ADV
cana-2493	329	32	be	be	AUX
cana-2493	329	33	nonexistent	nonexistent	ADJ
cana-2493	329	34	.	.	PUNCT
cana-2493	330	1	in	in	ADP
cana-2493	330	2	addition	addition	NOUN
cana-2493	330	3	,	,	PUNCT
cana-2493	330	4	it	it	PRON
cana-2493	330	5	also	also	ADV
cana-2493	330	6	helps	help	VERB
cana-2493	330	7	in	in	ADP
cana-2493	330	8	the	the	DET
cana-2493	330	9	interpretability	interpretability	NOUN
cana-2493	330	10	of	of	ADP
cana-2493	330	11	the	the	DET
cana-2493	330	12	model	model	NOUN
cana-2493	330	13	's	's	PART
cana-2493	330	14	predictions	prediction	NOUN
cana-2493	330	15	by	by	ADP
cana-2493	330	16	visualizing	visualize	VERB
cana-2493	330	17	them	they	PRON
cana-2493	330	18	as	as	ADP
cana-2493	330	19	attention	attention	NOUN
cana-2493	330	20	map	map	NOUN
cana-2493	330	21	which	which	PRON
cana-2493	330	22	gives	give	VERB
cana-2493	330	23	clinicians	clinician	NOUN
cana-2493	330	24	their	their	PRON
cana-2493	330	25	much	much	ADV
cana-2493	330	26	-	-	PUNCT
cana-2493	330	27	needed	need	VERB
cana-2493	330	28	explanation	explanation	NOUN
cana-2493	330	29	for	for	ADP
cana-2493	330	30	what	what	PRON
cana-2493	330	31	the	the	DET
cana-2493	330	32	model	model	NOUN
cana-2493	330	33	is	be	AUX
cana-2493	330	34	doing	do	VERB
cana-2493	330	35	and	and	CCONJ
cana-2493	330	36	therefore	therefore	ADV
cana-2493	330	37	easy	easy	ADJ
cana-2493	330	38	to	to	PART
cana-2493	330	39	trust	trust	VERB
cana-2493	330	40	and	and	CCONJ
cana-2493	330	41	validate	validate	VERB
cana-2493	330	42	its	its	PRON
cana-2493	330	43	results	result	NOUN
cana-2493	330	44	.	.	PUNCT
cana-2493	331	1	specifically	specifically	ADV
cana-2493	331	2	,	,	PUNCT
cana-2493	331	3	by	by	ADP
cana-2493	331	4	far	far	ADV
cana-2493	331	5	the	the	DET
cana-2493	331	6	coolest	cool	ADJ
cana-2493	331	7	use	use	NOUN
cana-2493	331	8	case	case	NOUN
cana-2493	331	9	imo	imo	ADV
cana-2493	331	10	is	be	AUX
cana-2493	331	11	communications	communication	NOUN
cana-2493	331	12	on	on	ADP
cana-2493	331	13	applied	apply	VERB
cana-2493	331	14	nonlinear	nonlinear	ADJ
cana-2493	331	15	analysis	analysis	NOUN
cana-2493	331	16	issn	issn	NOUN
cana-2493	331	17	:	:	PUNCT
cana-2493	331	18	1074	1074	NUM
cana-2493	331	19	-	-	PUNCT
cana-2493	331	20	133x	133x	NUM
cana-2493	331	21	vol	vol	NOUN
cana-2493	331	22	32	32	NUM
cana-2493	331	23	no	no	NOUN
cana-2493	331	24	.	.	PUNCT
cana-2493	332	1	2s	2s	NUM
cana-2493	332	2	(	(	PUNCT
cana-2493	332	3	2025	2025	NUM
cana-2493	332	4	)	)	PUNCT
cana-2493	332	5	563	563	NUM
cana-2493	332	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	332	7	where	where	SCONJ
cana-2493	332	8	attention	attention	NOUN
cana-2493	332	9	maps	map	NOUN
cana-2493	332	10	in	in	ADP
cana-2493	332	11	the	the	DET
cana-2493	332	12	model	model	NOUN
cana-2493	332	13	can	can	AUX
cana-2493	332	14	be	be	AUX
cana-2493	332	15	compared	compare	VERB
cana-2493	332	16	with	with	ADP
cana-2493	332	17	a	a	DET
cana-2493	332	18	subjective	subjective	ADJ
cana-2493	332	19	impression	impression	NOUN
cana-2493	332	20	of	of	ADP
cana-2493	332	21	what	what	PRON
cana-2493	332	22	you	you	PRON
cana-2493	332	23	(	(	PUNCT
cana-2493	332	24	or	or	CCONJ
cana-2493	332	25	better	well	ADJ
cana-2493	332	26	yet	yet	ADV
cana-2493	332	27	,	,	PUNCT
cana-2493	332	28	the	the	DET
cana-2493	332	29	neuroradiologist	neuroradiologist	NOUN
cana-2493	332	30	)	)	PUNCT
cana-2493	332	31	thought	think	VERB
cana-2493	332	32	was	be	AUX
cana-2493	332	33	important	important	ADJ
cana-2493	332	34	on	on	ADP
cana-2493	332	35	those	those	DET
cana-2493	332	36	images	image	NOUN
cana-2493	332	37	.	.	PUNCT
cana-2493	333	1	table	table	NOUN
cana-2493	333	2	8	8	NUM
cana-2493	333	3	.	.	PUNCT
cana-2493	334	1	generalization	generalization	NOUN
cana-2493	334	2	capability	capability	NOUN
cana-2493	334	3	on	on	ADP
cana-2493	334	4	different	different	ADJ
cana-2493	334	5	datasets	dataset	NOUN
cana-2493	334	6	(	(	PUNCT
cana-2493	334	7	accuracy	accuracy	NOUN
cana-2493	334	8	across	across	ADP
cana-2493	334	9	multiple	multiple	ADJ
cana-2493	334	10	datasets	dataset	NOUN
cana-2493	334	11	)	)	PUNCT
cana-2493	334	12	dataset	dataset	NOUN
cana-2493	334	13	name	name	NOUN
cana-2493	334	14	traditional	traditional	ADJ
cana-2493	334	15	cnn	cnn	PROPN
cana-2493	334	16	accuracy	accuracy	NOUN
cana-2493	334	17	(	(	PUNCT
cana-2493	334	18	%	%	INTJ
cana-2493	334	19	)	)	PUNCT
cana-2493	334	20	proposed	propose	VERB
cana-2493	334	21	model	model	NOUN
cana-2493	334	22	accuracy	accuracy	NOUN
cana-2493	334	23	(	(	PUNCT
cana-2493	334	24	%	%	INTJ
cana-2493	334	25	)	)	PUNCT
cana-2493	334	26	improvement	improvement	NOUN
cana-2493	334	27	(	(	PUNCT
cana-2493	334	28	%	%	INTJ
cana-2493	334	29	)	)	PUNCT
cana-2493	334	30	lidc	lidc	ADJ
cana-2493	334	31	-	-	PUNCT
cana-2493	334	32	idri	idri	NOUN
cana-2493	334	33	87.52	87.52	NUM
cana-2493	334	34	93.41	93.41	NUM
cana-2493	334	35	+6.73	+6.73	PROPN
cana-2493	334	36	covid-19	covid-19	PROPN
cana-2493	334	37	radiography	radiography	NOUN
cana-2493	334	38	database	database	NOUN
cana-2493	334	39	89.15	89.15	NUM
cana-2493	334	40	95.56	95.56	NUM
cana-2493	334	41	+7.19	+7.19	NUM
cana-2493	334	42	rsna	rsna	NOUN
cana-2493	334	43	pneumonia	pneumonia	NOUN
cana-2493	334	44	detection	detection	NOUN
cana-2493	334	45	85.03	85.03	NUM
cana-2493	334	46	91.82	91.82	NUM
cana-2493	335	1	+7.97	+7.97	PROPN
cana-2493	335	2	nih	nih	PROPN
cana-2493	335	3	chest	chest	PROPN
cana-2493	335	4	x	x	PROPN
cana-2493	335	5	-	-	NOUN
cana-2493	335	6	ray	ray	NOUN
cana-2493	335	7	dataset	dataset	VERB
cana-2493	335	8	86.44	86.44	NUM
cana-2493	335	9	93.22	93.22	NUM
cana-2493	336	1	+7.83	+7.83	ADJ
cana-2493	336	2	average	average	ADJ
cana-2493	336	3	87.03	87.03	NUM
cana-2493	336	4	93.00	93.00	NUM
cana-2493	336	5	+6.87	+6.87	PRON
cana-2493	336	6	the	the	DET
cana-2493	336	7	results	result	NOUN
cana-2493	336	8	of	of	ADP
cana-2493	336	9	experiments	experiment	NOUN
cana-2493	336	10	also	also	ADV
cana-2493	336	11	indicated	indicate	VERB
cana-2493	336	12	that	that	SCONJ
cana-2493	336	13	the	the	DET
cana-2493	336	14	model	model	NOUN
cana-2493	336	15	had	have	VERB
cana-2493	336	16	a	a	DET
cana-2493	336	17	capability	capability	NOUN
cana-2493	336	18	for	for	ADP
cana-2493	336	19	integration	integration	NOUN
cana-2493	336	20	an	an	DET
cana-2493	336	21	online	online	ADJ
cana-2493	336	22	diagnostic	diagnostic	ADJ
cana-2493	336	23	support	support	NOUN
cana-2493	336	24	systems	system	NOUN
cana-2493	336	25	.	.	PUNCT
cana-2493	337	1	its	its	PRON
cana-2493	337	2	high	high	ADJ
cana-2493	337	3	accuracy	accuracy	NOUN
cana-2493	337	4	and	and	CCONJ
cana-2493	337	5	the	the	DET
cana-2493	337	6	speed	speed	NOUN
cana-2493	337	7	at	at	ADP
cana-2493	337	8	which	which	PRON
cana-2493	337	9	it	it	PRON
cana-2493	337	10	can	can	AUX
cana-2493	337	11	process	process	VERB
cana-2493	337	12	images	image	NOUN
cana-2493	337	13	further	far	ADV
cana-2493	337	14	enable	enable	ADJ
cana-2493	337	15	integration	integration	NOUN
cana-2493	337	16	into	into	ADP
cana-2493	337	17	clinical	clinical	ADJ
cana-2493	337	18	workflows	workflow	NOUN
cana-2493	337	19	,	,	PUNCT
cana-2493	337	20	when	when	SCONJ
cana-2493	337	21	an	an	DET
cana-2493	337	22	urgent	urgent	ADJ
cana-2493	337	23	diagnosis	diagnosis	NOUN
cana-2493	337	24	is	be	AUX
cana-2493	337	25	essential	essential	ADJ
cana-2493	337	26	.	.	PUNCT
cana-2493	338	1	needing	need	VERB
cana-2493	338	2	rapid	rapid	ADJ
cana-2493	338	3	and	and	CCONJ
cana-2493	338	4	accurate	accurate	ADJ
cana-2493	338	5	diagnosis	diagnosis	NOUN
cana-2493	338	6	of	of	ADP
cana-2493	338	7	lung	lung	NOUN
cana-2493	338	8	cancers	cancer	NOUN
cana-2493	338	9	to	to	PART
cana-2493	338	10	control	control	VERB
cana-2493	338	11	the	the	DET
cana-2493	338	12	spread	spread	NOUN
cana-2493	338	13	of	of	ADP
cana-2493	338	14	the	the	DET
cana-2493	338	15	virus	virus	NOUN
cana-2493	338	16	and	and	CCONJ
cana-2493	338	17	treat	treat	VERB
cana-2493	338	18	patients	patient	NOUN
cana-2493	338	19	appropriately	appropriately	ADV
cana-2493	338	20	during	during	ADP
cana-2493	338	21	the	the	DET
cana-2493	338	22	covid-19	covid-19	PROPN
cana-2493	338	23	pandemic	pandemic	NOUN
cana-2493	338	24	,	,	PUNCT
cana-2493	338	25	for	for	ADP
cana-2493	338	26	example	example	NOUN
cana-2493	338	27	.	.	PUNCT
cana-2493	339	1	given	give	VERB
cana-2493	339	2	that	that	SCONJ
cana-2493	339	3	our	our	PRON
cana-2493	339	4	model	model	NOUN
cana-2493	339	5	outperformed	outperform	VERB
cana-2493	339	6	comparisons	comparison	NOUN
cana-2493	339	7	in	in	ADP
cana-2493	339	8	detecting	detect	VERB
cana-2493	339	9	covid-19	covid-19	PROPN
cana-2493	339	10	related	related	ADJ
cana-2493	339	11	lung	lung	NOUN
cana-2493	339	12	abnormalities	abnormality	NOUN
cana-2493	339	13	,	,	PUNCT
cana-2493	339	14	it	it	PRON
cana-2493	339	15	can	can	AUX
cana-2493	339	16	be	be	AUX
cana-2493	339	17	a	a	DET
cana-2493	339	18	useful	useful	ADJ
cana-2493	339	19	tool	tool	NOUN
cana-2493	339	20	for	for	ADP
cana-2493	339	21	such	such	ADJ
cana-2493	339	22	situations	situation	NOUN
cana-2493	339	23	.	.	PUNCT
cana-2493	340	1	judging	judge	VERB
cana-2493	340	2	from	from	ADP
cana-2493	340	3	the	the	DET
cana-2493	340	4	experiments	experiment	NOUN
cana-2493	340	5	,	,	PUNCT
cana-2493	340	6	the	the	DET
cana-2493	340	7	experimental	experimental	ADJ
cana-2493	340	8	evaluation	evaluation	NOUN
cana-2493	340	9	illustrated	illustrate	VERB
cana-2493	340	10	that	that	SCONJ
cana-2493	340	11	our	our	PRON
cana-2493	340	12	model	model	NOUN
cana-2493	340	13	was	be	AUX
cana-2493	340	14	a	a	DET
cana-2493	340	15	significant	significant	ADJ
cana-2493	340	16	step	step	NOUN
cana-2493	340	17	forward	forward	ADV
cana-2493	340	18	in	in	ADP
cana-2493	340	19	automatic	automatic	ADJ
cana-2493	340	20	detection	detection	NOUN
cana-2493	340	21	of	of	ADP
cana-2493	340	22	lung	lung	NOUN
cana-2493	340	23	cancer	cancer	NOUN
cana-2493	340	24	.	.	PUNCT
cana-2493	341	1	using	use	VERB
cana-2493	341	2	attention	attention	NOUN
cana-2493	341	3	-	-	PUNCT
cana-2493	341	4	based	base	VERB
cana-2493	341	5	feature	feature	NOUN
cana-2493	341	6	extraction	extraction	NOUN
cana-2493	341	7	enhances	enhance	VERB
cana-2493	341	8	the	the	DET
cana-2493	341	9	residual	residual	ADJ
cana-2493	341	10	network	network	NOUN
cana-2493	341	11	,	,	PUNCT
cana-2493	341	12	and	and	CCONJ
cana-2493	341	13	the	the	DET
cana-2493	341	14	cross	cross	ADJ
cana-2493	341	15	-	-	ADJ
cana-2493	341	16	average	average	ADJ
cana-2493	341	17	pooling	pooling	NOUN
cana-2493	341	18	operator	operator	NOUN
cana-2493	341	19	helps	help	VERB
cana-2493	341	20	to	to	PART
cana-2493	341	21	improve	improve	VERB
cana-2493	341	22	accuracy	accuracy	NOUN
cana-2493	341	23	and	and	CCONJ
cana-2493	341	24	robustness	robustness	NOUN
cana-2493	341	25	compared	compare	VERB
cana-2493	341	26	with	with	ADP
cana-2493	341	27	existing	exist	VERB
cana-2493	341	28	methods	method	NOUN
cana-2493	341	29	.	.	PUNCT
cana-2493	342	1	these	these	DET
cana-2493	342	2	upgrades	upgrade	NOUN
cana-2493	342	3	are	be	AUX
cana-2493	342	4	vital	vital	ADJ
cana-2493	342	5	for	for	ADP
cana-2493	342	6	their	their	PRON
cana-2493	342	7	use	use	NOUN
cana-2493	342	8	as	as	ADP
cana-2493	342	9	accurate	accurate	ADJ
cana-2493	342	10	diagnostic	diagnostic	ADJ
cana-2493	342	11	tools	tool	NOUN
cana-2493	342	12	and	and	CCONJ
cana-2493	342	13	especially	especially	ADV
cana-2493	342	14	in	in	ADP
cana-2493	342	15	areas	area	NOUN
cana-2493	342	16	where	where	SCONJ
cana-2493	342	17	expert	expert	NOUN
cana-2493	342	18	radiologists	radiologist	NOUN
cana-2493	342	19	may	may	AUX
cana-2493	342	20	be	be	AUX
cana-2493	342	21	scarce	scarce	ADJ
cana-2493	342	22	.	.	PUNCT
cana-2493	343	1	the	the	DET
cana-2493	343	2	researchers	researcher	NOUN
cana-2493	343	3	plan	plan	VERB
cana-2493	343	4	to	to	PART
cana-2493	343	5	continue	continue	VERB
cana-2493	343	6	improving	improve	VERB
cana-2493	343	7	the	the	DET
cana-2493	343	8	architecture	architecture	NOUN
cana-2493	343	9	of	of	ADP
cana-2493	343	10	their	their	PRON
cana-2493	343	11	model	model	NOUN
cana-2493	343	12	,	,	PUNCT
cana-2493	343	13	as	as	ADV
cana-2493	343	14	well	well	ADV
cana-2493	343	15	as	as	ADP
cana-2493	343	16	examining	examine	VERB
cana-2493	343	17	its	its	PRON
cana-2493	343	18	application	application	NOUN
cana-2493	343	19	to	to	ADP
cana-2493	343	20	additional	additional	ADJ
cana-2493	343	21	medical	medical	ADJ
cana-2493	343	22	imaging	imaging	NOUN
cana-2493	343	23	tasks	task	NOUN
cana-2493	343	24	,	,	PUNCT
cana-2493	343	25	such	such	ADJ
cana-2493	343	26	as	as	ADP
cana-2493	343	27	tumor	tumor	NOUN
cana-2493	343	28	detection	detection	NOUN
cana-2493	343	29	and	and	CCONJ
cana-2493	343	30	other	other	ADJ
cana-2493	343	31	types	type	NOUN
cana-2493	343	32	of	of	ADP
cana-2493	343	33	respiratory	respiratory	ADJ
cana-2493	343	34	diseases	disease	NOUN
cana-2493	343	35	.	.	PUNCT
cana-2493	344	1	5	5	X
cana-2493	344	2	.	.	X
cana-2493	344	3	conclusion	conclusion	NOUN
cana-2493	344	4	and	and	CCONJ
cana-2493	344	5	future	future	ADJ
cana-2493	344	6	work	work	NOUN
cana-2493	344	7	this	this	DET
cana-2493	344	8	paper	paper	NOUN
cana-2493	344	9	presents	present	VERB
cana-2493	344	10	a	a	DET
cana-2493	344	11	novel	novel	NOUN
cana-2493	344	12	and	and	CCONJ
cana-2493	344	13	powerful	powerful	ADJ
cana-2493	344	14	scheme	scheme	NOUN
cana-2493	344	15	on	on	ADP
cana-2493	344	16	implementing	implement	VERB
cana-2493	344	17	an	an	DET
cana-2493	344	18	end	end	NOUN
cana-2493	344	19	-	-	PUNCT
cana-2493	344	20	to	to	ADP
cana-2493	344	21	-	-	PUNCT
cana-2493	344	22	end	end	NOUN
cana-2493	344	23	deep	deep	ADJ
cana-2493	344	24	learning	learning	NOUN
cana-2493	344	25	framework	framework	NOUN
cana-2493	344	26	augmented	augment	VERB
cana-2493	344	27	with	with	ADP
cana-2493	344	28	attention	attention	NOUN
cana-2493	344	29	-	-	PUNCT
cana-2493	344	30	guided	guide	VERB
cana-2493	344	31	feature	feature	NOUN
cana-2493	344	32	extraction	extraction	NOUN
cana-2493	344	33	as	as	ADV
cana-2493	344	34	well	well	ADV
cana-2493	344	35	as	as	ADP
cana-2493	344	36	cross	cross	ADJ
cana-2493	344	37	-	-	ADJ
cana-2493	344	38	average	average	ADJ
cana-2493	344	39	pooling	pooling	NOUN
cana-2493	344	40	in	in	ADP
cana-2493	344	41	the	the	DET
cana-2493	344	42	detection	detection	NOUN
cana-2493	344	43	and	and	CCONJ
cana-2493	344	44	classification	classification	NOUN
cana-2493	344	45	of	of	ADP
cana-2493	344	46	lung	lung	NOUN
cana-2493	344	47	cancers	cancer	NOUN
cana-2493	344	48	.	.	PUNCT
cana-2493	345	1	the	the	DET
cana-2493	345	2	model	model	NOUN
cana-2493	345	3	improved	improve	VERB
cana-2493	345	4	test	test	NOUN
cana-2493	345	5	accuracy	accuracy	NOUN
cana-2493	345	6	,	,	PUNCT
cana-2493	345	7	precision	precision	NOUN
cana-2493	345	8	,	,	PUNCT
cana-2493	345	9	recall	recall	NOUN
cana-2493	345	10	,	,	PUNCT
cana-2493	345	11	and	and	CCONJ
cana-2493	345	12	overall	overall	ADJ
cana-2493	345	13	diagnostic	diagnostic	ADJ
cana-2493	345	14	performance	performance	NOUN
cana-2493	345	15	while	while	SCONJ
cana-2493	345	16	providing	provide	VERB
cana-2493	345	17	the	the	DET
cana-2493	345	18	rational	rational	ADJ
cana-2493	345	19	for	for	ADP
cana-2493	345	20	overcoming	overcome	VERB
cana-2493	345	21	certain	certain	ADJ
cana-2493	345	22	constraints	constraint	NOUN
cana-2493	345	23	with	with	ADP
cana-2493	345	24	traditional	traditional	ADJ
cana-2493	345	25	cnns	cnn	NOUN
cana-2493	345	26	.	.	PUNCT
cana-2493	346	1	the	the	DET
cana-2493	346	2	architecture	architecture	NOUN
cana-2493	346	3	of	of	ADP
cana-2493	346	4	this	this	DET
cana-2493	346	5	model	model	NOUN
cana-2493	346	6	is	be	AUX
cana-2493	346	7	particularly	particularly	ADV
cana-2493	346	8	well	well	ADV
cana-2493	346	9	suited	suited	ADJ
cana-2493	346	10	to	to	PART
cana-2493	346	11	take	take	VERB
cana-2493	346	12	on	on	ADP
cana-2493	346	13	lung	lung	NOUN
cana-2493	346	14	cancer	cancer	NOUN
cana-2493	346	15	imaging	imaging	NOUN
cana-2493	346	16	,	,	PUNCT
cana-2493	346	17	most	most	ADV
cana-2493	346	18	notably	notably	ADV
cana-2493	346	19	chest	ch	ADJ
cana-2493	346	20	x	x	NOUN
cana-2493	346	21	-	-	NOUN
cana-2493	346	22	ray	ray	NOUN
cana-2493	346	23	(	(	PUNCT
cana-2493	346	24	cxr	cxr	NOUN
cana-2493	346	25	)	)	PUNCT
cana-2493	346	26	images	image	NOUN
cana-2493	346	27	where	where	SCONJ
cana-2493	346	28	the	the	DET
cana-2493	346	29	presence	presence	NOUN
cana-2493	346	30	of	of	ADP
cana-2493	346	31	cancer	cancer	NOUN
cana-2493	346	32	may	may	AUX
cana-2493	346	33	manifest	manifest	VERB
cana-2493	346	34	in	in	ADP
cana-2493	346	35	an	an	DET
cana-2493	346	36	intricate	intricate	ADJ
cana-2493	346	37	fashion	fashion	NOUN
cana-2493	346	38	such	such	ADJ
cana-2493	346	39	as	as	ADP
cana-2493	346	40	being	be	AUX
cana-2493	346	41	subtle	subtle	ADJ
cana-2493	346	42	,	,	PUNCT
cana-2493	346	43	diffuse	diffuse	ADJ
cana-2493	346	44	or	or	CCONJ
cana-2493	346	45	coinciding	coincide	VERB
cana-2493	346	46	with	with	ADP
cana-2493	346	47	normal	normal	ADJ
cana-2493	346	48	anatomical	anatomical	ADJ
cana-2493	346	49	structures	structure	NOUN
cana-2493	346	50	.	.	PUNCT
cana-2493	347	1	these	these	DET
cana-2493	347	2	developments	development	NOUN
cana-2493	347	3	set	set	VERB
cana-2493	347	4	the	the	DET
cana-2493	347	5	stage	stage	NOUN
cana-2493	347	6	for	for	ADP
cana-2493	347	7	new	new	ADJ
cana-2493	347	8	,	,	PUNCT
cana-2493	347	9	clinically	clinically	ADV
cana-2493	347	10	pragmatic	pragmatic	ADJ
cana-2493	347	11	and	and	CCONJ
cana-2493	347	12	robust	robust	ADJ
cana-2493	347	13	diagnostic	diagnostic	ADJ
cana-2493	347	14	systems	system	NOUN
cana-2493	347	15	especially	especially	ADV
cana-2493	347	16	in	in	ADP
cana-2493	347	17	infectious	infectious	ADJ
cana-2493	347	18	diseases	disease	NOUN
cana-2493	347	19	(	(	PUNCT
cana-2493	347	20	like	like	ADP
cana-2493	347	21	pneumonia	pneumonia	NOUN
cana-2493	347	22	,	,	PUNCT
cana-2493	347	23	tuberculosis	tuberculosis	NOUN
cana-2493	347	24	,	,	PUNCT
cana-2493	347	25	covid-19	covid-19	PROPN
cana-2493	347	26	)	)	PUNCT
cana-2493	347	27	,	,	PUNCT
cana-2493	347	28	which	which	PRON
cana-2493	347	29	are	be	AUX
cana-2493	347	30	predominant	predominant	ADJ
cana-2493	347	31	issues	issue	NOUN
cana-2493	347	32	in	in	ADP
cana-2493	347	33	global	global	ADJ
cana-2493	347	34	health	health	NOUN
cana-2493	347	35	.	.	PUNCT
cana-2493	348	1	the	the	DET
cana-2493	348	2	attention	attention	NOUN
cana-2493	348	3	of	of	ADP
cana-2493	348	4	the	the	DET
cana-2493	348	5	research	research	NOUN
cana-2493	348	6	in	in	ADP
cana-2493	348	7	this	this	DET
cana-2493	348	8	regard	regard	NOUN
cana-2493	348	9	is	be	AUX
cana-2493	348	10	to	to	PART
cana-2493	348	11	implant	implant	VERB
cana-2493	348	12	an	an	DET
cana-2493	348	13	attention	attention	NOUN
cana-2493	348	14	mechanism	mechanism	NOUN
cana-2493	348	15	that	that	PRON
cana-2493	348	16	enables	enable	VERB
cana-2493	348	17	the	the	DET
cana-2493	348	18	model	model	NOUN
cana-2493	348	19	to	to	PART
cana-2493	348	20	attend	attend	VERB
cana-2493	348	21	(	(	PUNCT
cana-2493	348	22	focus	focus	NOUN
cana-2493	348	23	)	)	PUNCT
cana-2493	348	24	selectively	selectively	ADV
cana-2493	348	25	on	on	ADP
cana-2493	348	26	specific	specific	ADJ
cana-2493	348	27	regions	region	NOUN
cana-2493	348	28	of	of	ADP
cana-2493	348	29	the	the	DET
cana-2493	348	30	image	image	NOUN
cana-2493	348	31	which	which	PRON
cana-2493	348	32	are	be	AUX
cana-2493	348	33	more	more	ADV
cana-2493	348	34	informative	informative	ADJ
cana-2493	348	35	.	.	PUNCT
cana-2493	349	1	in	in	ADP
cana-2493	349	2	lung	lung	NOUN
cana-2493	349	3	cancers	cancer	NOUN
cana-2493	349	4	,	,	PUNCT
cana-2493	349	5	these	these	PRON
cana-2493	349	6	are	be	AUX
cana-2493	349	7	the	the	DET
cana-2493	349	8	regions	region	NOUN
cana-2493	349	9	that	that	PRON
cana-2493	349	10	demonstrate	demonstrate	VERB
cana-2493	349	11	the	the	DET
cana-2493	349	12	abnormal	abnormal	ADJ
cana-2493	349	13	opacities	opacity	NOUN
cana-2493	349	14	,	,	PUNCT
cana-2493	349	15	consolidations	consolidation	NOUN
cana-2493	349	16	,	,	PUNCT
cana-2493	349	17	or	or	CCONJ
cana-2493	349	18	any	any	DET
cana-2493	349	19	other	other	ADJ
cana-2493	349	20	patterns	pattern	NOUN
cana-2493	349	21	of	of	ADP
cana-2493	349	22	disease	disease	NOUN
cana-2493	349	23	.	.	PUNCT
cana-2493	350	1	this	this	PRON
cana-2493	350	2	has	have	AUX
cana-2493	350	3	been	be	AUX
cana-2493	350	4	one	one	NUM
cana-2493	350	5	of	of	ADP
cana-2493	350	6	the	the	DET
cana-2493	350	7	long	long	ADJ
cana-2493	350	8	standing	standing	ADJ
cana-2493	350	9	issues	issue	NOUN
cana-2493	350	10	with	with	ADP
cana-2493	350	11	traditional	traditional	ADJ
cana-2493	350	12	cnns	cnn	NOUN
cana-2493	350	13	as	as	SCONJ
cana-2493	350	14	it	it	PRON
cana-2493	350	15	treats	treat	VERB
cana-2493	350	16	all	all	DET
cana-2493	350	17	communications	communication	NOUN
cana-2493	350	18	on	on	ADP
cana-2493	350	19	applied	apply	VERB
cana-2493	350	20	nonlinear	nonlinear	ADJ
cana-2493	350	21	analysis	analysis	NOUN
cana-2493	350	22	issn	issn	NOUN
cana-2493	350	23	:	:	PUNCT
cana-2493	350	24	1074	1074	NUM
cana-2493	350	25	-	-	PUNCT
cana-2493	350	26	133x	133x	NUM
cana-2493	350	27	vol	vol	NOUN
cana-2493	350	28	32	32	NUM
cana-2493	350	29	no	no	NOUN
cana-2493	350	30	.	.	PUNCT
cana-2493	351	1	2s	2s	NUM
cana-2493	351	2	(	(	PUNCT
cana-2493	351	3	2025	2025	NUM
cana-2493	351	4	)	)	PUNCT
cana-2493	351	5	564	564	NUM
cana-2493	351	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	351	7	parts	part	NOUN
cana-2493	351	8	of	of	ADP
cana-2493	351	9	the	the	DET
cana-2493	351	10	image	image	NOUN
cana-2493	351	11	equally	equally	ADV
cana-2493	351	12	and	and	CCONJ
cana-2493	351	13	ends	end	VERB
cana-2493	351	14	up	up	ADP
cana-2493	351	15	learning	learn	VERB
cana-2493	351	16	from	from	ADP
cana-2493	351	17	irrelevant	irrelevant	ADJ
cana-2493	351	18	or	or	CCONJ
cana-2493	351	19	noisy	noisy	ADJ
cana-2493	351	20	information	information	NOUN
cana-2493	351	21	such	such	ADJ
cana-2493	351	22	as	as	ADP
cana-2493	351	23	healthy	healthy	ADJ
cana-2493	351	24	tissue	tissue	NOUN
cana-2493	351	25	or	or	CCONJ
cana-2493	351	26	background	background	NOUN
cana-2493	351	27	features	feature	NOUN
cana-2493	351	28	.	.	PUNCT
cana-2493	352	1	with	with	ADP
cana-2493	352	2	attention	attention	NOUN
cana-2493	352	3	-	-	PUNCT
cana-2493	352	4	based	base	VERB
cana-2493	352	5	feature	feature	NOUN
cana-2493	352	6	extraction	extraction	NOUN
cana-2493	352	7	,	,	PUNCT
cana-2493	352	8	our	our	PRON
cana-2493	352	9	model	model	NOUN
cana-2493	352	10	is	be	AUX
cana-2493	352	11	able	able	ADJ
cana-2493	352	12	to	to	PART
cana-2493	352	13	close	close	VERB
cana-2493	352	14	in	in	ADP
cana-2493	352	15	on	on	ADP
cana-2493	352	16	these	these	DET
cana-2493	352	17	regions	region	NOUN
cana-2493	352	18	and	and	CCONJ
cana-2493	352	19	give	give	VERB
cana-2493	352	20	higher	high	ADJ
cana-2493	352	21	weights	weight	NOUN
cana-2493	352	22	to	to	PART
cana-2493	352	23	features	feature	NOUN
cana-2493	352	24	which	which	PRON
cana-2493	352	25	are	be	AUX
cana-2493	352	26	most	most	ADV
cana-2493	352	27	critical	critical	ADJ
cana-2493	352	28	for	for	ADP
cana-2493	352	29	the	the	DET
cana-2493	352	30	diagnosis	diagnosis	NOUN
cana-2493	352	31	.	.	PUNCT
cana-2493	353	1	attention	attention	NOUN
cana-2493	353	2	improves	improve	VERB
cana-2493	353	3	accuracy	accuracy	NOUN
cana-2493	353	4	of	of	ADP
cana-2493	353	5	the	the	DET
cana-2493	353	6	model	model	NOUN
cana-2493	353	7	by	by	ADP
cana-2493	353	8	directing	direct	VERB
cana-2493	353	9	it	it	PRON
cana-2493	353	10	towards	towards	ADP
cana-2493	353	11	specific	specific	ADJ
cana-2493	353	12	parts	part	NOUN
cana-2493	353	13	in	in	ADP
cana-2493	353	14	the	the	DET
cana-2493	353	15	input	input	NOUN
cana-2493	353	16	image	image	NOUN
cana-2493	353	17	(	(	PUNCT
cana-2493	353	18	semantic	semantic	ADJ
cana-2493	353	19	meaning	meaning	NOUN
cana-2493	353	20	)	)	PUNCT
cana-2493	353	21	while	while	SCONJ
cana-2493	353	22	also	also	ADV
cana-2493	353	23	enhancing	enhance	VERB
cana-2493	353	24	interpretability	interpretability	NOUN
cana-2493	353	25	of	of	ADP
cana-2493	353	26	the	the	DET
cana-2493	353	27	same	same	ADJ
cana-2493	353	28	,	,	PUNCT
cana-2493	353	29	where	where	SCONJ
cana-2493	353	30	attention	attention	NOUN
cana-2493	353	31	maps	map	NOUN
cana-2493	353	32	serve	serve	VERB
cana-2493	353	33	as	as	ADP
cana-2493	353	34	a	a	DET
cana-2493	353	35	visual	visual	ADJ
cana-2493	353	36	reference	reference	NOUN
cana-2493	353	37	to	to	PART
cana-2493	353	38	understand	understand	VERB
cana-2493	353	39	where	where	SCONJ
cana-2493	353	40	exactly	exactly	ADV
cana-2493	353	41	was	be	AUX
cana-2493	353	42	the	the	DET
cana-2493	353	43	focussed	focusse	VERB
cana-2493	353	44	area	area	NOUN
cana-2493	353	45	which	which	PRON
cana-2493	353	46	helped	help	VERB
cana-2493	353	47	or	or	CCONJ
cana-2493	353	48	did	do	AUX
cana-2493	353	49	n't	not	PART
cana-2493	353	50	help	help	VERB
cana-2493	353	51	for	for	ADP
cana-2493	353	52	making	make	VERB
cana-2493	353	53	a	a	DET
cana-2493	353	54	decision	decision	NOUN
cana-2493	353	55	which	which	PRON
cana-2493	353	56	makes	make	VERB
cana-2493	353	57	it	it	PRON
cana-2493	353	58	more	more	ADV
cana-2493	353	59	transparent	transparent	ADJ
cana-2493	353	60	and	and	CCONJ
cana-2493	353	61	interpretable	interpretable	ADJ
cana-2493	353	62	from	from	ADP
cana-2493	353	63	formulation	formulation	NOUN
cana-2493	353	64	aspect	aspect	NOUN
cana-2493	353	65	with	with	ADP
cana-2493	353	66	specialists	specialist	NOUN
cana-2493	353	67	.	.	PUNCT
cana-2493	354	1	moreover	moreover	ADV
cana-2493	354	2	,	,	PUNCT
cana-2493	354	3	with	with	ADP
cana-2493	354	4	the	the	DET
cana-2493	354	5	recent	recent	ADJ
cana-2493	354	6	introduction	introduction	NOUN
cana-2493	354	7	of	of	ADP
cana-2493	354	8	cross	cross	ADJ
cana-2493	354	9	-	-	ADJ
cana-2493	354	10	average	average	ADJ
cana-2493	354	11	pooling	pooling	NOUN
cana-2493	354	12	it	it	PRON
cana-2493	354	13	constitutes	constitute	VERB
cana-2493	354	14	a	a	DET
cana-2493	354	15	great	great	ADJ
cana-2493	354	16	improvement	improvement	NOUN
cana-2493	354	17	in	in	ADP
cana-2493	354	18	how	how	SCONJ
cana-2493	354	19	deep	deep	ADJ
cana-2493	354	20	learning	learning	NOUN
cana-2493	354	21	models	model	NOUN
cana-2493	354	22	process	process	VERB
cana-2493	354	23	and	and	CCONJ
cana-2493	354	24	aggregate	aggregate	VERB
cana-2493	354	25	over	over	ADP
cana-2493	354	26	feature	feature	NOUN
cana-2493	354	27	map	map	NOUN
cana-2493	354	28	.	.	PUNCT
cana-2493	355	1	max	max	PROPN
cana-2493	355	2	pooling	pooling	NOUN
cana-2493	355	3	and	and	CCONJ
cana-2493	355	4	average	average	ADJ
cana-2493	355	5	pooling	pooling	NOUN
cana-2493	355	6	are	be	AUX
cana-2493	355	7	present	present	ADJ
cana-2493	355	8	in	in	ADP
cana-2493	355	9	traditional	traditional	ADJ
cana-2493	355	10	cnns	cnn	NOUN
cana-2493	355	11	to	to	AUX
cana-2493	355	12	down	down	VERB
cana-2493	355	13	sample	sample	NOUN
cana-2493	355	14	feature	feature	NOUN
cana-2493	355	15	maps	map	NOUN
cana-2493	355	16	for	for	ADP
cana-2493	355	17	reducing	reduce	VERB
cana-2493	355	18	the	the	DET
cana-2493	355	19	computation	computation	NOUN
cana-2493	355	20	cost	cost	NOUN
cana-2493	355	21	and	and	CCONJ
cana-2493	355	22	avoiding	avoid	VERB
cana-2493	355	23	overfitting	overfitte	VERB
cana-2493	355	24	.	.	PUNCT
cana-2493	356	1	but	but	CCONJ
cana-2493	356	2	these	these	DET
cana-2493	356	3	methods	method	NOUN
cana-2493	356	4	oversimplify	oversimplify	VERB
cana-2493	356	5	the	the	DET
cana-2493	356	6	data	datum	NOUN
cana-2493	356	7	,	,	PUNCT
cana-2493	356	8	removing	remove	VERB
cana-2493	356	9	crucial	crucial	ADJ
cana-2493	356	10	spatial	spatial	ADJ
cana-2493	356	11	information	information	NOUN
cana-2493	356	12	necessary	necessary	ADJ
cana-2493	356	13	to	to	PART
cana-2493	356	14	recognize	recognize	VERB
cana-2493	356	15	subtle	subtle	ADJ
cana-2493	356	16	patterns	pattern	NOUN
cana-2493	356	17	in	in	ADP
cana-2493	356	18	medical	medical	ADJ
cana-2493	356	19	images	image	NOUN
cana-2493	356	20	.	.	PUNCT
cana-2493	357	1	lung	lung	NOUN
cana-2493	357	2	inflammatory	inflammatory	ADJ
cana-2493	357	3	lesions	lesion	NOUN
cana-2493	357	4	can	can	AUX
cana-2493	357	5	have	have	VERB
cana-2493	357	6	small	small	ADJ
cana-2493	357	7	differences	difference	NOUN
cana-2493	357	8	on	on	ADP
cana-2493	357	9	their	their	PRON
cana-2493	357	10	texture	texture	ADJ
cana-2493	357	11	,	,	PUNCT
cana-2493	357	12	opacity	opacity	NOUN
cana-2493	357	13	and	and	CCONJ
cana-2493	357	14	shape	shape	NOUN
cana-2493	357	15	especially	especially	ADV
cana-2493	357	16	in	in	ADP
cana-2493	357	17	lung	lung	NOUN
cana-2493	357	18	specific	specific	ADJ
cana-2493	357	19	diseases	disease	NOUN
cana-2493	357	20	like	like	ADP
cana-2493	357	21	cancers	cancer	NOUN
cana-2493	357	22	,	,	PUNCT
cana-2493	357	23	which	which	PRON
cana-2493	357	24	conventional	conventional	ADJ
cana-2493	357	25	pooling	pooling	NOUN
cana-2493	357	26	strategies	strategy	NOUN
cana-2493	357	27	may	may	AUX
cana-2493	357	28	not	not	PART
cana-2493	357	29	suffice	suffice	VERB
cana-2493	357	30	.	.	PUNCT
cana-2493	358	1	cross	cross	VERB
cana-2493	358	2	average	average	ADJ
cana-2493	358	3	pooling	pool	VERB
cana-2493	358	4	solves	solve	NOUN
cana-2493	358	5	this	this	DET
cana-2493	358	6	problem	problem	NOUN
cana-2493	358	7	by	by	ADP
cana-2493	358	8	accumulating	accumulate	VERB
cana-2493	358	9	information	information	NOUN
cana-2493	358	10	in	in	ADP
cana-2493	358	11	various	various	ADJ
cana-2493	358	12	spatial	spatial	ADJ
cana-2493	358	13	regions	region	NOUN
cana-2493	358	14	and	and	CCONJ
cana-2493	358	15	channels	channel	NOUN
cana-2493	358	16	,	,	PUNCT
cana-2493	358	17	making	make	VERB
cana-2493	358	18	it	it	PRON
cana-2493	358	19	possible	possible	ADJ
cana-2493	358	20	for	for	SCONJ
cana-2493	358	21	the	the	DET
cana-2493	358	22	model	model	NOUN
cana-2493	358	23	to	to	PART
cana-2493	358	24	capture	capture	VERB
cana-2493	358	25	a	a	DET
cana-2493	358	26	comprehensive	comprehensive	ADJ
cana-2493	358	27	and	and	CCONJ
cana-2493	358	28	detailed	detailed	ADJ
cana-2493	358	29	representation	representation	NOUN
cana-2493	358	30	of	of	ADP
cana-2493	358	31	the	the	DET
cana-2493	358	32	cancer	cancer	NOUN
cana-2493	358	33	patterns	pattern	NOUN
cana-2493	358	34	.	.	PUNCT
cana-2493	359	1	this	this	DET
cana-2493	359	2	technique	technique	NOUN
cana-2493	359	3	retains	retain	VERB
cana-2493	359	4	crucial	crucial	ADJ
cana-2493	359	5	spatial	spatial	ADJ
cana-2493	359	6	dependencies	dependency	NOUN
cana-2493	359	7	and	and	CCONJ
cana-2493	359	8	improves	improve	VERB
cana-2493	359	9	the	the	DET
cana-2493	359	10	model	model	NOUN
cana-2493	359	11	generalisation	generalisation	NOUN
cana-2493	359	12	abilities	ability	NOUN
cana-2493	359	13	,	,	PUNCT
cana-2493	359	14	enabling	enable	VERB
cana-2493	359	15	it	it	PRON
cana-2493	359	16	to	to	PART
cana-2493	359	17	perform	perform	VERB
cana-2493	359	18	well	well	ADV
cana-2493	359	19	across	across	ADP
cana-2493	359	20	different	different	ADJ
cana-2493	359	21	lung	lung	NOUN
cana-2493	359	22	cancers	cancer	NOUN
cana-2493	359	23	as	as	ADV
cana-2493	359	24	well	well	ADV
cana-2493	359	25	as	as	ADP
cana-2493	359	26	for	for	ADP
cana-2493	359	27	unseen	unseen	ADJ
cana-2493	359	28	image	image	NOUN
cana-2493	359	29	datasets	dataset	NOUN
cana-2493	359	30	.	.	PUNCT
cana-2493	360	1	experimental	experimental	ADJ
cana-2493	360	2	results	result	NOUN
cana-2493	360	3	on	on	ADP
cana-2493	360	4	publicly	publicly	ADV
cana-2493	360	5	available	available	ADJ
cana-2493	360	6	lung	lung	NOUN
cana-2493	360	7	cancer	cancer	NOUN
cana-2493	360	8	datasets	dataset	NOUN
cana-2493	360	9	indicate	indicate	VERB
cana-2493	360	10	that	that	SCONJ
cana-2493	360	11	the	the	DET
cana-2493	360	12	proposed	propose	VERB
cana-2493	360	13	model	model	NOUN
cana-2493	360	14	is	be	AUX
cana-2493	360	15	able	able	ADJ
cana-2493	360	16	to	to	PART
cana-2493	360	17	detect	detect	VERB
cana-2493	360	18	cases	case	NOUN
cana-2493	360	19	of	of	ADP
cana-2493	360	20	cancer	cancer	NOUN
cana-2493	360	21	accurately	accurately	ADV
cana-2493	360	22	.	.	PUNCT
cana-2493	361	1	the	the	DET
cana-2493	361	2	model	model	NOUN
cana-2493	361	3	introduced	introduce	VERB
cana-2493	361	4	significantly	significantly	ADV
cana-2493	361	5	outperformed	outperform	VERB
cana-2493	361	6	traditional	traditional	ADJ
cana-2493	361	7	cnn	cnn	PROPN
cana-2493	361	8	based	base	VERB
cana-2493	361	9	methods	method	NOUN
cana-2493	361	10	on	on	ADP
cana-2493	361	11	important	important	ADJ
cana-2493	361	12	metrics	metric	NOUN
cana-2493	361	13	like	like	ADP
cana-2493	361	14	accuracy	accuracy	NOUN
cana-2493	361	15	,	,	PUNCT
cana-2493	361	16	precision	precision	NOUN
cana-2493	361	17	,	,	PUNCT
cana-2493	361	18	recall	recall	NOUN
cana-2493	361	19	and	and	CCONJ
cana-2493	361	20	f1	f1	NOUN
cana-2493	361	21	-	-	PUNCT
cana-2493	361	22	score	score	NOUN
cana-2493	361	23	.	.	PUNCT
cana-2493	362	1	improvements	improvement	NOUN
cana-2493	362	2	are	be	AUX
cana-2493	362	3	particularly	particularly	ADV
cana-2493	362	4	important	important	ADJ
cana-2493	362	5	in	in	ADP
cana-2493	362	6	cases	case	NOUN
cana-2493	362	7	where	where	SCONJ
cana-2493	362	8	cancers	cancer	NOUN
cana-2493	362	9	present	present	VERB
cana-2493	362	10	with	with	ADP
cana-2493	362	11	few	few	ADJ
cana-2493	362	12	or	or	CCONJ
cana-2493	362	13	overlapping	overlap	VERB
cana-2493	362	14	features	feature	NOUN
cana-2493	362	15	(	(	PUNCT
cana-2493	362	16	e.g.	e.g.	ADV
cana-2493	362	17	earlystage	earlystage	NOUN
cana-2493	362	18	cancer	cancer	NOUN
cana-2493	362	19	or	or	CCONJ
cana-2493	362	20	viral	viral	ADJ
cana-2493	362	21	pneumonia	pneumonia	NOUN
cana-2493	362	22	)	)	PUNCT
cana-2493	362	23	,	,	PUNCT
cana-2493	362	24	traditional	traditional	ADJ
cana-2493	362	25	models	model	NOUN
cana-2493	362	26	struggle	struggle	VERB
cana-2493	362	27	due	due	ADP
cana-2493	362	28	to	to	ADP
cana-2493	362	29	the	the	DET
cana-2493	362	30	lack	lack	NOUN
cana-2493	362	31	of	of	ADP
cana-2493	362	32	any	any	DET
cana-2493	362	33	single	single	ADJ
cana-2493	362	34	stand	stand	VERB
cana-2493	362	35	-	-	PUNCT
cana-2493	362	36	out	out	ADP
cana-2493	362	37	feature	feature	NOUN
cana-2493	362	38	.	.	PUNCT
cana-2493	363	1	our	our	PRON
cana-2493	363	2	results	result	NOUN
cana-2493	363	3	demonstrate	demonstrate	VERB
cana-2493	363	4	the	the	DET
cana-2493	363	5	critical	critical	ADJ
cana-2493	363	6	role	role	NOUN
cana-2493	363	7	of	of	ADP
cana-2493	363	8	attention	attention	NOUN
cana-2493	363	9	-	-	PUNCT
cana-2493	363	10	based	base	VERB
cana-2493	363	11	mechanisms	mechanism	NOUN
cana-2493	363	12	in	in	ADP
cana-2493	363	13	medical	medical	ADJ
cana-2493	363	14	image	image	NOUN
cana-2493	363	15	analysis	analysis	NOUN
cana-2493	363	16	,	,	PUNCT
cana-2493	363	17	especially	especially	ADV
cana-2493	363	18	when	when	SCONJ
cana-2493	363	19	identifying	identify	VERB
cana-2493	363	20	between	between	ADP
cana-2493	363	21	healthy	healthy	ADJ
cana-2493	363	22	and	and	CCONJ
cana-2493	363	23	infected	infected	ADJ
cana-2493	363	24	tissue	tissue	NOUN
cana-2493	363	25	is	be	AUX
cana-2493	363	26	challenging	challenge	VERB
cana-2493	363	27	or	or	CCONJ
cana-2493	363	28	non	non	ADJ
cana-2493	363	29	-	-	ADJ
cana-2493	363	30	trivial	trivial	ADJ
cana-2493	363	31	.	.	PUNCT
cana-2493	364	1	moreover	moreover	ADV
cana-2493	364	2	,	,	PUNCT
cana-2493	364	3	the	the	DET
cana-2493	364	4	one	one	NUM
cana-2493	364	5	cross	cross	ADJ
cana-2493	364	6	-	-	ADJ
cana-2493	364	7	region	region	ADJ
cana-2493	364	8	average	average	ADJ
cana-2493	364	9	pooling	pooling	NOUN
cana-2493	364	10	was	be	AUX
cana-2493	364	11	found	find	VERB
cana-2493	364	12	to	to	PART
cana-2493	364	13	improve	improve	VERB
cana-2493	364	14	the	the	DET
cana-2493	364	15	overall	overall	ADJ
cana-2493	364	16	detection	detection	NOUN
cana-2493	364	17	performance	performance	NOUN
cana-2493	364	18	for	for	ADP
cana-2493	364	19	various	various	ADJ
cana-2493	364	20	and	and	CCONJ
cana-2493	364	21	complex	complex	ADJ
cana-2493	364	22	cancer	cancer	NOUN
cana-2493	364	23	patterns	pattern	NOUN
cana-2493	364	24	over	over	ADP
cana-2493	364	25	all	all	DET
cana-2493	364	26	cancer	cancer	NOUN
cana-2493	364	27	types	type	NOUN
cana-2493	364	28	,	,	PUNCT
cana-2493	364	29	such	such	ADJ
cana-2493	364	30	as	as	ADP
cana-2493	364	31	bacterial	bacterial	ADJ
cana-2493	364	32	pneumonia	pneumonia	NOUN
cana-2493	364	33	or	or	CCONJ
cana-2493	364	34	only	only	ADV
cana-2493	364	35	viral	viral	ADJ
cana-2493	364	36	pneumonia	pneumonia	NOUN
cana-2493	364	37	;	;	PUNCT
cana-2493	364	38	covid-19	covid-19	PROPN
cana-2493	364	39	.	.	PUNCT
cana-2493	365	1	the	the	DET
cana-2493	365	2	flexibility	flexibility	NOUN
cana-2493	365	3	and	and	CCONJ
cana-2493	365	4	adaptability	adaptability	NOUN
cana-2493	365	5	of	of	ADP
cana-2493	365	6	the	the	DET
cana-2493	365	7	proposed	propose	VERB
cana-2493	365	8	model	model	NOUN
cana-2493	365	9	are	be	AUX
cana-2493	365	10	among	among	ADP
cana-2493	365	11	its	its	PRON
cana-2493	365	12	greatest	great	ADJ
cana-2493	365	13	strengths	strength	NOUN
cana-2493	365	14	.	.	PUNCT
cana-2493	366	1	the	the	DET
cana-2493	366	2	clinical	clinical	ADJ
cana-2493	366	3	presentation	presentation	NOUN
cana-2493	366	4	in	in	ADP
cana-2493	366	5	lung	lung	NOUN
cana-2493	366	6	cancers	cancer	NOUN
cana-2493	366	7	can	can	AUX
cana-2493	366	8	range	range	VERB
cana-2493	366	9	from	from	ADP
cana-2493	366	10	one	one	NUM
cana-2493	366	11	end	end	NOUN
cana-2493	366	12	to	to	ADP
cana-2493	366	13	the	the	DET
cana-2493	366	14	other	other	ADJ
cana-2493	366	15	according	accord	VERB
cana-2493	366	16	type	type	NOUN
cana-2493	366	17	and	and	CCONJ
cana-2493	366	18	stage	stage	NOUN
cana-2493	366	19	of	of	ADP
cana-2493	366	20	cancer	cancer	NOUN
cana-2493	366	21	and	and	CCONJ
cana-2493	366	22	patient	patient	ADJ
cana-2493	366	23	health	health	NOUN
cana-2493	366	24	status	status	NOUN
cana-2493	366	25	.	.	PUNCT
cana-2493	367	1	bacterial	bacterial	ADJ
cana-2493	367	2	pneumonia	pneumonia	NOUN
cana-2493	367	3	,	,	PUNCT
cana-2493	367	4	for	for	ADP
cana-2493	367	5	instance	instance	NOUN
cana-2493	367	6	,	,	PUNCT
cana-2493	367	7	tends	tend	VERB
cana-2493	367	8	to	to	PART
cana-2493	367	9	show	show	VERB
cana-2493	367	10	a	a	DET
cana-2493	367	11	more	more	ADV
cana-2493	367	12	focal	focal	ADJ
cana-2493	367	13	consolidation	consolidation	NOUN
cana-2493	367	14	distribution	distribution	NOUN
cana-2493	367	15	;	;	PUNCT
cana-2493	367	16	viral	viral	ADJ
cana-2493	367	17	illnesses	illness	NOUN
cana-2493	367	18	like	like	ADP
cana-2493	367	19	covid-19	covid-19	PROPN
cana-2493	367	20	tend	tend	VERB
cana-2493	367	21	to	to	PART
cana-2493	367	22	have	have	VERB
cana-2493	367	23	diffuse	diffuse	ADJ
cana-2493	367	24	ground	ground	NOUN
cana-2493	367	25	-	-	PUNCT
cana-2493	367	26	glass	glass	NOUN
cana-2493	367	27	opacities	opacity	NOUN
cana-2493	367	28	across	across	ADP
cana-2493	367	29	all	all	DET
cana-2493	367	30	lobes	lobe	NOUN
cana-2493	367	31	of	of	ADP
cana-2493	367	32	the	the	DET
cana-2493	367	33	lungs	lung	NOUN
cana-2493	367	34	.	.	PUNCT
cana-2493	368	1	the	the	DET
cana-2493	368	2	generalizability	generalizability	NOUN
cana-2493	368	3	across	across	ADP
cana-2493	368	4	these	these	DET
cana-2493	368	5	various	various	ADJ
cana-2493	368	6	cancer	cancer	NOUN
cana-2493	368	7	types	type	NOUN
cana-2493	368	8	is	be	AUX
cana-2493	368	9	key	key	ADJ
cana-2493	368	10	for	for	SCONJ
cana-2493	368	11	any	any	DET
cana-2493	368	12	diagnostic	diagnostic	ADJ
cana-2493	368	13	tool	tool	NOUN
cana-2493	368	14	to	to	PART
cana-2493	368	15	succeed	succeed	VERB
cana-2493	368	16	in	in	ADP
cana-2493	368	17	the	the	DET
cana-2493	368	18	real	real	ADJ
cana-2493	368	19	-	-	PUNCT
cana-2493	368	20	world	world	NOUN
cana-2493	368	21	clinical	clinical	ADJ
cana-2493	368	22	workflow	workflow	NOUN
cana-2493	368	23	.	.	PUNCT
cana-2493	369	1	with	with	ADP
cana-2493	369	2	attention	attention	NOUN
cana-2493	369	3	-	-	PUNCT
cana-2493	369	4	based	base	VERB
cana-2493	369	5	feature	feature	NOUN
cana-2493	369	6	extraction	extraction	NOUN
cana-2493	369	7	and	and	CCONJ
cana-2493	369	8	cross	cross	ADJ
cana-2493	369	9	-	-	ADJ
cana-2493	369	10	average	average	ADJ
cana-2493	369	11	pooling	pooling	NOUN
cana-2493	369	12	,	,	PUNCT
cana-2493	369	13	the	the	DET
cana-2493	369	14	model	model	NOUN
cana-2493	369	15	we	we	PRON
cana-2493	369	16	have	have	AUX
cana-2493	369	17	proposed	propose	VERB
cana-2493	369	18	has	have	AUX
cana-2493	369	19	shown	show	VERB
cana-2493	369	20	its	its	PRON
cana-2493	369	21	ability	ability	NOUN
cana-2493	369	22	to	to	PART
cana-2493	369	23	generalize	generalize	VERB
cana-2493	369	24	well	well	ADV
cana-2493	369	25	across	across	ADP
cana-2493	369	26	several	several	ADJ
cana-2493	369	27	datasets	dataset	NOUN
cana-2493	369	28	showing	show	VERB
cana-2493	369	29	high	high	ADJ
cana-2493	369	30	accuracy	accuracy	NOUN
cana-2493	369	31	in	in	ADP
cana-2493	369	32	comparison	comparison	NOUN
cana-2493	369	33	with	with	ADP
cana-2493	369	34	existing	exist	VERB
cana-2493	369	35	methods	method	NOUN
cana-2493	369	36	.	.	PUNCT
cana-2493	370	1	this	this	DET
cana-2493	370	2	generalization	generalization	NOUN
cana-2493	370	3	ability	ability	NOUN
cana-2493	370	4	is	be	AUX
cana-2493	370	5	crucial	crucial	ADJ
cana-2493	370	6	in	in	ADP
cana-2493	370	7	order	order	NOUN
cana-2493	370	8	to	to	PART
cana-2493	370	9	deploy	deploy	VERB
cana-2493	370	10	the	the	DET
cana-2493	370	11	model	model	NOUN
cana-2493	370	12	on	on	ADP
cana-2493	370	13	a	a	DET
cana-2493	370	14	broad	broad	ADJ
cana-2493	370	15	spectrum	spectrum	NOUN
cana-2493	370	16	of	of	ADP
cana-2493	370	17	clinical	clinical	ADJ
cana-2493	370	18	settings	setting	NOUN
cana-2493	370	19	,	,	PUNCT
cana-2493	370	20	with	with	ADP
cana-2493	370	21	patients	patient	NOUN
cana-2493	370	22	suffering	suffer	VERB
cana-2493	370	23	from	from	ADP
cana-2493	370	24	cancer	cancer	NOUN
cana-2493	370	25	types	type	NOUN
cana-2493	370	26	and	and	CCONJ
cana-2493	370	27	severity	severity	NOUN
cana-2493	370	28	levels	level	NOUN
cana-2493	370	29	.	.	PUNCT
cana-2493	371	1	besides	besides	SCONJ
cana-2493	371	2	the	the	DET
cana-2493	371	3	model	model	NOUN
cana-2493	371	4	having	have	VERB
cana-2493	371	5	high	high	ADJ
cana-2493	371	6	diagnostic	diagnostic	ADJ
cana-2493	371	7	accuracy	accuracy	NOUN
cana-2493	371	8	,	,	PUNCT
cana-2493	371	9	it	it	PRON
cana-2493	371	10	possesses	possess	VERB
cana-2493	371	11	several	several	ADJ
cana-2493	371	12	inherent	inherent	ADJ
cana-2493	371	13	practicularly	practicularly	ADJ
cana-2493	371	14	advantages	advantage	NOUN
cana-2493	371	15	that	that	PRON
cana-2493	371	16	are	be	AUX
cana-2493	371	17	advantageous	advantageous	ADJ
cana-2493	371	18	for	for	ADP
cana-2493	371	19	its	its	PRON
cana-2493	371	20	clinical	clinical	ADJ
cana-2493	371	21	workflow	workflow	NOUN
cana-2493	371	22	integration	integration	NOUN
cana-2493	371	23	.	.	PUNCT
cana-2493	372	1	one	one	NUM
cana-2493	372	2	of	of	ADP
cana-2493	372	3	the	the	DET
cana-2493	372	4	most	most	ADV
cana-2493	372	5	important	important	ADJ
cana-2493	372	6	communications	communication	NOUN
cana-2493	372	7	on	on	ADP
cana-2493	372	8	applied	apply	VERB
cana-2493	372	9	nonlinear	nonlinear	ADJ
cana-2493	372	10	analysis	analysis	NOUN
cana-2493	372	11	issn	issn	NOUN
cana-2493	372	12	:	:	PUNCT
cana-2493	372	13	1074	1074	NUM
cana-2493	372	14	-	-	PUNCT
cana-2493	372	15	133x	133x	NUM
cana-2493	372	16	vol	vol	NOUN
cana-2493	372	17	32	32	NUM
cana-2493	372	18	no	no	NOUN
cana-2493	372	19	.	.	PUNCT
cana-2493	373	1	2s	2s	NUM
cana-2493	373	2	(	(	PUNCT
cana-2493	373	3	2025	2025	NUM
cana-2493	373	4	)	)	PUNCT
cana-2493	373	5	565	565	NUM
cana-2493	373	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	373	7	among	among	ADP
cana-2493	373	8	these	these	PRON
cana-2493	373	9	is	be	AUX
cana-2493	373	10	its	its	PRON
cana-2493	373	11	interpretability	interpretability	NOUN
cana-2493	373	12	.	.	PUNCT
cana-2493	374	1	in	in	ADP
cana-2493	374	2	the	the	DET
cana-2493	374	3	medical	medical	ADJ
cana-2493	374	4	domain	domain	NOUN
cana-2493	374	5	,	,	PUNCT
cana-2493	374	6	especially	especially	ADV
cana-2493	374	7	in	in	ADP
cana-2493	374	8	radiology	radiology	NOUN
cana-2493	374	9	,	,	PUNCT
cana-2493	374	10	having	have	VERB
cana-2493	374	11	a	a	DET
cana-2493	374	12	model	model	NOUN
cana-2493	374	13	that	that	PRON
cana-2493	374	14	only	only	ADV
cana-2493	374	15	achieves	achieve	VERB
cana-2493	374	16	good	good	ADJ
cana-2493	374	17	performance	performance	NOUN
cana-2493	374	18	is	be	AUX
cana-2493	374	19	not	not	PART
cana-2493	374	20	enough	enough	ADJ
cana-2493	374	21	;	;	PUNCT
cana-2493	374	22	it	it	PRON
cana-2493	374	23	is	be	AUX
cana-2493	374	24	essential	essential	ADJ
cana-2493	374	25	as	as	ADV
cana-2493	374	26	well	well	ADV
cana-2493	374	27	to	to	PART
cana-2493	374	28	explain	explain	VERB
cana-2493	374	29	why	why	SCONJ
cana-2493	374	30	it	it	PRON
cana-2493	374	31	arrived	arrive	VERB
cana-2493	374	32	at	at	ADP
cana-2493	374	33	the	the	DET
cana-2493	374	34	prediction	prediction	NOUN
cana-2493	374	35	it	it	PRON
cana-2493	374	36	was	be	AUX
cana-2493	374	37	made	make	VERB
cana-2493	374	38	.	.	PUNCT
cana-2493	375	1	it	it	PRON
cana-2493	375	2	is	be	AUX
cana-2493	375	3	essential	essential	ADJ
cana-2493	375	4	,	,	PUNCT
cana-2493	375	5	particularly	particularly	ADV
cana-2493	375	6	when	when	SCONJ
cana-2493	375	7	the	the	DET
cana-2493	375	8	model	model	NOUN
cana-2493	375	9	is	be	AUX
cana-2493	375	10	making	make	VERB
cana-2493	375	11	a	a	DET
cana-2493	375	12	prediction	prediction	NOUN
cana-2493	375	13	that	that	PRON
cana-2493	375	14	may	may	AUX
cana-2493	375	15	conflict	conflict	VERB
cana-2493	375	16	with	with	ADP
cana-2493	375	17	the	the	DET
cana-2493	375	18	original	original	ADJ
cana-2493	375	19	judgment	judgment	NOUN
cana-2493	375	20	of	of	ADP
cana-2493	375	21	a	a	DET
cana-2493	375	22	rater	rater	NOUN
cana-2493	375	23	.	.	PUNCT
cana-2493	376	1	our	our	PRON
cana-2493	376	2	model	model	NOUN
cana-2493	376	3	based	base	VERB
cana-2493	376	4	on	on	ADP
cana-2493	376	5	the	the	DET
cana-2493	376	6	attention	attention	NOUN
cana-2493	376	7	mechanism	mechanism	NOUN
cana-2493	376	8	,	,	PUNCT
cana-2493	376	9	is	be	AUX
cana-2493	376	10	able	able	ADJ
cana-2493	376	11	to	to	PART
cana-2493	376	12	fill	fill	VERB
cana-2493	376	13	this	this	DET
cana-2493	376	14	gap	gap	NOUN
cana-2493	376	15	with	with	ADP
cana-2493	376	16	a	a	DET
cana-2493	376	17	useful	useful	ADJ
cana-2493	376	18	tool	tool	NOUN
cana-2493	376	19	:	:	PUNCT
cana-2493	376	20	we	we	PRON
cana-2493	376	21	are	be	AUX
cana-2493	376	22	able	able	ADJ
cana-2493	376	23	to	to	PART
cana-2493	376	24	generate	generate	VERB
cana-2493	376	25	attention	attention	NOUN
cana-2493	376	26	maps	map	NOUN
cana-2493	376	27	showing	show	VERB
cana-2493	376	28	which	which	DET
cana-2493	376	29	regions	region	NOUN
cana-2493	376	30	of	of	ADP
cana-2493	376	31	the	the	DET
cana-2493	376	32	image	image	NOUN
cana-2493	376	33	did	do	AUX
cana-2493	376	34	our	our	PRON
cana-2493	376	35	model	model	NOUN
cana-2493	376	36	attended	attend	VERB
cana-2493	376	37	to	to	ADP
cana-2493	376	38	when	when	SCONJ
cana-2493	376	39	it	it	PRON
cana-2493	376	40	was	be	AUX
cana-2493	376	41	making	make	VERB
cana-2493	376	42	its	its	PRON
cana-2493	376	43	decision	decision	NOUN
cana-2493	376	44	.	.	PUNCT
cana-2493	377	1	clinicians	clinician	NOUN
cana-2493	377	2	can	can	AUX
cana-2493	377	3	use	use	VERB
cana-2493	377	4	these	these	DET
cana-2493	377	5	maps	map	NOUN
cana-2493	377	6	to	to	PART
cana-2493	377	7	validate	validate	VERB
cana-2493	377	8	the	the	DET
cana-2493	377	9	model	model	NOUN
cana-2493	377	10	detections	detection	NOUN
cana-2493	377	11	and	and	CCONJ
cana-2493	377	12	as	as	SCONJ
cana-2493	377	13	visual	visual	ADJ
cana-2493	377	14	aids	aid	NOUN
cana-2493	377	15	to	to	PART
cana-2493	377	16	understand	understand	VERB
cana-2493	377	17	the	the	DET
cana-2493	377	18	relevant	relevant	ADJ
cana-2493	377	19	features	feature	NOUN
cana-2493	377	20	for	for	ADP
cana-2493	377	21	diagnosis	diagnosis	NOUN
cana-2493	377	22	.	.	PUNCT
cana-2493	378	1	this	this	DET
cana-2493	378	2	type	type	NOUN
cana-2493	378	3	of	of	ADP
cana-2493	378	4	clarity	clarity	NOUN
cana-2493	378	5	is	be	AUX
cana-2493	378	6	paramount	paramount	ADJ
cana-2493	378	7	to	to	PART
cana-2493	378	8	establish	establish	VERB
cana-2493	378	9	confidence	confidence	NOUN
cana-2493	378	10	clinical	clinical	ADJ
cana-2493	378	11	use	use	NOUN
cana-2493	378	12	of	of	ADP
cana-2493	378	13	automated	automate	VERB
cana-2493	378	14	diagnostic	diagnostic	ADJ
cana-2493	378	15	annotations	annotation	NOUN
cana-2493	378	16	.	.	PUNCT
cana-2493	379	1	in	in	ADP
cana-2493	379	2	addition	addition	NOUN
cana-2493	379	3	,	,	PUNCT
cana-2493	379	4	the	the	DET
cana-2493	379	5	proposed	propose	VERB
cana-2493	379	6	model	model	NOUN
cana-2493	379	7	can	can	AUX
cana-2493	379	8	potentially	potentially	ADV
cana-2493	379	9	alleviate	alleviate	VERB
cana-2493	379	10	the	the	DET
cana-2493	379	11	heavy	heavy	ADJ
cana-2493	379	12	workload	workload	NOUN
cana-2493	379	13	of	of	ADP
cana-2493	379	14	healthcare	healthcare	NOUN
cana-2493	379	15	professionals	professional	NOUN
cana-2493	379	16	,	,	PUNCT
cana-2493	379	17	especially	especially	ADV
cana-2493	379	18	in	in	ADP
cana-2493	379	19	resource	resource	NOUN
cana-2493	379	20	constrained	constrain	VERB
cana-2493	379	21	settings	setting	NOUN
cana-2493	379	22	where	where	SCONJ
cana-2493	379	23	expert	expert	ADJ
cana-2493	379	24	radiologists	radiologist	NOUN
cana-2493	379	25	are	be	AUX
cana-2493	379	26	few	few	ADJ
cana-2493	379	27	.	.	PUNCT
cana-2493	380	1	for	for	ADP
cana-2493	380	2	example	example	NOUN
cana-2493	380	3	,	,	PUNCT
cana-2493	380	4	lung	lung	NOUN
cana-2493	380	5	cancers	cancer	NOUN
cana-2493	380	6	such	such	ADJ
cana-2493	380	7	as	as	ADP
cana-2493	380	8	pneumonia	pneumonia	NOUN
cana-2493	380	9	and	and	CCONJ
cana-2493	380	10	covid-19	covid-19	PROPN
cana-2493	380	11	are	be	AUX
cana-2493	380	12	endemic	endemic	ADJ
cana-2493	380	13	to	to	ADP
cana-2493	380	14	many	many	ADJ
cana-2493	380	15	countries	country	NOUN
cana-2493	380	16	of	of	ADP
cana-2493	380	17	low	low	ADJ
cana-2493	380	18	-	-	PUNCT
cana-2493	380	19	and	and	CCONJ
cana-2493	380	20	middle	middle	ADJ
cana-2493	380	21	-	-	PUNCT
cana-2493	380	22	income	income	NOUN
cana-2493	380	23	,	,	PUNCT
cana-2493	380	24	contributing	contribute	VERB
cana-2493	380	25	to	to	ADP
cana-2493	380	26	respiratory	respiratory	ADJ
cana-2493	380	27	diagnostics	diagnostic	NOUN
cana-2493	380	28	being	be	AUX
cana-2493	380	29	a	a	DET
cana-2493	380	30	particularly	particularly	ADV
cana-2493	380	31	overburdened	overburden	VERB
cana-2493	380	32	area	area	NOUN
cana-2493	380	33	.	.	PUNCT
cana-2493	381	1	automation	automation	NOUN
cana-2493	381	2	of	of	ADP
cana-2493	381	3	identifying	identify	VERB
cana-2493	381	4	these	these	DET
cana-2493	381	5	cancers	cancer	NOUN
cana-2493	381	6	accurately	accurately	ADV
cana-2493	381	7	and	and	CCONJ
cana-2493	381	8	reliably	reliably	ADV
cana-2493	381	9	by	by	ADP
cana-2493	381	10	a	a	DET
cana-2493	381	11	deep	deep	ADJ
cana-2493	381	12	learning	learning	NOUN
cana-2493	381	13	model	model	NOUN
cana-2493	381	14	would	would	AUX
cana-2493	381	15	therefore	therefore	ADV
cana-2493	381	16	relieve	relieve	VERB
cana-2493	381	17	some	some	DET
cana-2493	381	18	part	part	NOUN
cana-2493	381	19	of	of	ADP
cana-2493	381	20	this	this	DET
cana-2493	381	21	burden	burden	NOUN
cana-2493	381	22	off	off	ADP
cana-2493	381	23	healthcare	healthcare	NOUN
cana-2493	381	24	workers	worker	NOUN
cana-2493	381	25	,	,	PUNCT
cana-2493	381	26	letting	let	VERB
cana-2493	381	27	them	they	PRON
cana-2493	381	28	to	to	PART
cana-2493	381	29	concentrate	concentrate	VERB
cana-2493	381	30	on	on	ADP
cana-2493	381	31	other	other	ADJ
cana-2493	381	32	important	important	ADJ
cana-2493	381	33	aspects	aspect	NOUN
cana-2493	381	34	of	of	ADP
cana-2493	381	35	patient	patient	ADJ
cana-2493	381	36	care	care	NOUN
cana-2493	381	37	.	.	PUNCT
cana-2493	382	1	the	the	DET
cana-2493	382	2	proposed	propose	VERB
cana-2493	382	3	model	model	NOUN
cana-2493	382	4	in	in	ADP
cana-2493	382	5	this	this	DET
cana-2493	382	6	context	context	NOUN
cana-2493	382	7	may	may	AUX
cana-2493	382	8	be	be	AUX
cana-2493	382	9	a	a	DET
cana-2493	382	10	diagnostic	diagnostic	ADJ
cana-2493	382	11	aid	aid	NOUN
cana-2493	382	12	as	as	SCONJ
cana-2493	382	13	it	it	PRON
cana-2493	382	14	can	can	AUX
cana-2493	382	15	help	help	VERB
cana-2493	382	16	predict	predict	VERB
cana-2493	382	17	the	the	DET
cana-2493	382	18	chest	ch	ADJ
cana-2493	382	19	x	x	NOUN
cana-2493	382	20	-	-	NOUN
cana-2493	382	21	ray	ray	NOUN
cana-2493	382	22	quickly	quickly	ADV
cana-2493	382	23	and	and	CCONJ
cana-2493	382	24	accurately	accurately	ADV
cana-2493	382	25	and	and	CCONJ
cana-2493	382	26	therefore	therefore	ADV
cana-2493	382	27	,	,	PUNCT
cana-2493	382	28	guide	guide	VERB
cana-2493	382	29	the	the	DET
cana-2493	382	30	clinicians	clinician	NOUN
cana-2493	382	31	to	to	ADP
cana-2493	382	32	treatment	treatment	NOUN
cana-2493	382	33	outcome	outcome	NOUN
cana-2493	382	34	.	.	PUNCT
cana-2493	383	1	the	the	DET
cana-2493	383	2	only	only	ADJ
cana-2493	383	3	other	other	ADJ
cana-2493	383	4	consideration	consideration	NOUN
cana-2493	383	5	for	for	ADP
cana-2493	383	6	future	future	ADJ
cana-2493	383	7	work	work	NOUN
cana-2493	383	8	on	on	ADP
cana-2493	383	9	this	this	DET
cana-2493	383	10	model	model	NOUN
cana-2493	383	11	is	be	AUX
cana-2493	383	12	its	its	PRON
cana-2493	383	13	portability	portability	NOUN
cana-2493	383	14	to	to	ADP
cana-2493	383	15	clinical	clinical	ADJ
cana-2493	383	16	imaging	imaging	NOUN
cana-2493	383	17	tasks	task	NOUN
cana-2493	383	18	.	.	PUNCT
cana-2493	384	1	although	although	SCONJ
cana-2493	384	2	we	we	PRON
cana-2493	384	3	have	have	AUX
cana-2493	384	4	focused	focus	VERB
cana-2493	384	5	on	on	ADP
cana-2493	384	6	lung	lung	NOUN
cana-2493	384	7	cancers	cancer	NOUN
cana-2493	384	8	in	in	ADP
cana-2493	384	9	this	this	DET
cana-2493	384	10	study	study	NOUN
cana-2493	384	11	,	,	PUNCT
cana-2493	384	12	the	the	DET
cana-2493	384	13	idea	idea	NOUN
cana-2493	384	14	of	of	ADP
cana-2493	384	15	attention	attention	NOUN
cana-2493	384	16	based	base	VERB
cana-2493	384	17	feature	feature	NOUN
cana-2493	384	18	extraction	extraction	NOUN
cana-2493	384	19	and	and	CCONJ
cana-2493	384	20	the	the	DET
cana-2493	384	21	cross	cross	ADJ
cana-2493	384	22	-	-	ADJ
cana-2493	384	23	average	average	ADJ
cana-2493	384	24	pooling	pooling	NOUN
cana-2493	384	25	can	can	AUX
cana-2493	384	26	be	be	AUX
cana-2493	384	27	widely	widely	ADV
cana-2493	384	28	applied	apply	VERB
cana-2493	384	29	to	to	ADP
cana-2493	384	30	other	other	ADJ
cana-2493	384	31	medical	medical	ADJ
cana-2493	384	32	image	image	NOUN
cana-2493	384	33	analysis	analysis	NOUN
cana-2493	384	34	tasks	task	NOUN
cana-2493	384	35	.	.	PUNCT
cana-2493	385	1	for	for	ADP
cana-2493	385	2	instance	instance	NOUN
cana-2493	385	3	,	,	PUNCT
cana-2493	385	4	these	these	DET
cana-2493	385	5	methodologies	methodology	NOUN
cana-2493	385	6	may	may	AUX
cana-2493	385	7	be	be	AUX
cana-2493	385	8	employed	employ	VERB
cana-2493	385	9	to	to	PART
cana-2493	385	10	enhance	enhance	VERB
cana-2493	385	11	the	the	DET
cana-2493	385	12	identification	identification	NOUN
cana-2493	385	13	of	of	ADP
cana-2493	385	14	tumors	tumor	NOUN
cana-2493	385	15	,	,	PUNCT
cana-2493	385	16	organ	organ	NOUN
cana-2493	385	17	diseases	disease	NOUN
cana-2493	385	18	or	or	CCONJ
cana-2493	385	19	to	to	PART
cana-2493	385	20	detect	detect	VERB
cana-2493	385	21	any	any	DET
cana-2493	385	22	other	other	ADJ
cana-2493	385	23	variety	variety	NOUN
cana-2493	385	24	of	of	ADP
cana-2493	385	25	pathologies	pathology	NOUN
cana-2493	385	26	that	that	PRON
cana-2493	385	27	manifest	manifest	VERB
cana-2493	385	28	through	through	ADP
cana-2493	385	29	fine	fine	ADJ
cana-2493	385	30	adaptations	adaptation	NOUN
cana-2493	385	31	in	in	ADP
cana-2493	385	32	the	the	DET
cana-2493	385	33	visual	visual	ADJ
cana-2493	385	34	dimension	dimension	NOUN
cana-2493	385	35	.	.	PUNCT
cana-2493	386	1	the	the	DET
cana-2493	386	2	model	model	NOUN
cana-2493	386	3	's	's	PART
cana-2493	386	4	architecture	architecture	NOUN
cana-2493	386	5	is	be	AUX
cana-2493	386	6	generalizable	generalizable	ADJ
cana-2493	386	7	,	,	PUNCT
cana-2493	386	8	capable	capable	ADJ
cana-2493	386	9	of	of	ADP
cana-2493	386	10	being	be	AUX
cana-2493	386	11	customized	customize	VERB
cana-2493	386	12	for	for	ADP
cana-2493	386	13	diagnostic	diagnostic	ADJ
cana-2493	386	14	applications	application	NOUN
cana-2493	386	15	across	across	ADP
cana-2493	386	16	diverse	diverse	ADJ
cana-2493	386	17	subspecialties	subspecialtie	NOUN
cana-2493	386	18	in	in	ADP
cana-2493	386	19	medicine	medicine	NOUN
cana-2493	386	20	,	,	PUNCT
cana-2493	386	21	which	which	PRON
cana-2493	386	22	could	could	AUX
cana-2493	386	23	change	change	VERB
cana-2493	386	24	how	how	SCONJ
cana-2493	386	25	medical	medical	ADJ
cana-2493	386	26	images	image	NOUN
cana-2493	386	27	are	be	AUX
cana-2493	386	28	interpreted	interpret	VERB
cana-2493	386	29	among	among	ADP
cana-2493	386	30	multiple	multiple	ADJ
cana-2493	386	31	specialties	specialty	NOUN
cana-2493	386	32	.	.	PUNCT
cana-2493	387	1	to	to	PART
cana-2493	387	2	sum	sum	VERB
cana-2493	387	3	up	up	ADP
cana-2493	387	4	,	,	PUNCT
cana-2493	387	5	this	this	DET
cana-2493	387	6	paper	paper	NOUN
cana-2493	387	7	contributes	contribute	VERB
cana-2493	387	8	a	a	DET
cana-2493	387	9	valuable	valuable	ADJ
cana-2493	387	10	research	research	NOUN
cana-2493	387	11	work	work	NOUN
cana-2493	387	12	to	to	PART
cana-2493	387	13	improve	improve	VERB
cana-2493	387	14	the	the	DET
cana-2493	387	15	existing	exist	VERB
cana-2493	387	16	mechanism	mechanism	NOUN
cana-2493	387	17	in	in	ADP
cana-2493	387	18	the	the	DET
cana-2493	387	19	lung	lung	NOUN
cana-2493	387	20	cancer	cancer	NOUN
cana-2493	387	21	detection	detection	NOUN
cana-2493	387	22	which	which	PRON
cana-2493	387	23	outperforms	outperform	VERB
cana-2493	387	24	traditional	traditional	ADJ
cana-2493	387	25	cnn	cnn	PROPN
cana-2493	387	26	-	-	PUNCT
cana-2493	387	27	based	base	VERB
cana-2493	387	28	methods	method	NOUN
cana-2493	387	29	.	.	PUNCT
cana-2493	388	1	up	up	ADP
cana-2493	388	2	using	use	VERB
cana-2493	388	3	fused	fuse	VERB
cana-2493	388	4	attentionbased	attentionbase	VERB
cana-2493	388	5	feature	feature	NOUN
cana-2493	388	6	extraction	extraction	NOUN
cana-2493	388	7	and	and	CCONJ
cana-2493	388	8	cross	cross	VERB
cana-2493	388	9	average	average	ADJ
cana-2493	388	10	pooling	pooling	NOUN
cana-2493	388	11	,	,	PUNCT
cana-2493	388	12	which	which	PRON
cana-2493	388	13	can	can	AUX
cana-2493	388	14	capture	capture	VERB
cana-2493	388	15	the	the	DET
cana-2493	388	16	most	most	ADV
cana-2493	388	17	discriminative	discriminative	ADJ
cana-2493	388	18	region	region	NOUN
cana-2493	388	19	from	from	ADP
cana-2493	388	20	an	an	DET
cana-2493	388	21	image	image	NOUN
cana-2493	388	22	to	to	PART
cana-2493	388	23	make	make	VERB
cana-2493	388	24	more	more	ADV
cana-2493	388	25	precise	precise	ADJ
cana-2493	388	26	discriminations	discrimination	NOUN
cana-2493	388	27	while	while	SCONJ
cana-2493	388	28	keeping	keep	VERB
cana-2493	388	29	enough	enough	ADJ
cana-2493	388	30	spatial	spatial	ADJ
cana-2493	388	31	information	information	NOUN
cana-2493	388	32	for	for	ADP
cana-2493	388	33	interpretability	interpretability	NOUN
cana-2493	388	34	.	.	PUNCT
cana-2493	389	1	experimental	experimental	ADJ
cana-2493	389	2	results	result	NOUN
cana-2493	389	3	show	show	VERB
cana-2493	389	4	the	the	DET
cana-2493	389	5	model	model	NOUN
cana-2493	389	6	outperforms	outperform	VERB
cana-2493	389	7	traditional	traditional	ADJ
cana-2493	389	8	approaches	approach	NOUN
cana-2493	389	9	,	,	PUNCT
cana-2493	389	10	especially	especially	ADV
cana-2493	389	11	when	when	SCONJ
cana-2493	389	12	cancer	cancer	NOUN
cana-2493	389	13	patterns	pattern	NOUN
cana-2493	389	14	are	be	AUX
cana-2493	389	15	subtle	subtle	ADJ
cana-2493	389	16	or	or	CCONJ
cana-2493	389	17	overlap	overlap	NOUN
cana-2493	389	18	.	.	PUNCT
cana-2493	390	1	in	in	ADP
cana-2493	390	2	addition	addition	NOUN
cana-2493	390	3	,	,	PUNCT
cana-2493	390	4	the	the	DET
cana-2493	390	5	model	model	NOUN
cana-2493	390	6	can	can	AUX
cana-2493	390	7	be	be	AUX
cana-2493	390	8	easily	easily	ADV
cana-2493	390	9	deployed	deploy	VERB
cana-2493	390	10	in	in	ADP
cana-2493	390	11	wideranging	widerange	VERB
cana-2493	390	12	clinical	clinical	ADJ
cana-2493	390	13	settings	setting	NOUN
cana-2493	390	14	due	due	ADP
cana-2493	390	15	to	to	ADP
cana-2493	390	16	its	its	PRON
cana-2493	390	17	versatility	versatility	NOUN
cana-2493	390	18	and	and	CCONJ
cana-2493	390	19	generalization	generalization	NOUN
cana-2493	390	20	performance	performance	NOUN
cana-2493	390	21	that	that	PRON
cana-2493	390	22	enables	enable	VERB
cana-2493	390	23	high	high	ADJ
cana-2493	390	24	diagnostic	diagnostic	ADJ
cana-2493	390	25	accuracy	accuracy	NOUN
cana-2493	390	26	as	as	ADV
cana-2493	390	27	well	well	ADV
cana-2493	390	28	as	as	ADP
cana-2493	390	29	saving	save	VERB
cana-2493	390	30	of	of	ADP
cana-2493	390	31	time	time	NOUN
cana-2493	390	32	required	require	VERB
cana-2493	390	33	by	by	ADP
cana-2493	390	34	healthcare	healthcare	NOUN
cana-2493	390	35	personnel	personnel	NOUN
cana-2493	390	36	.	.	PUNCT
cana-2493	391	1	given	give	VERB
cana-2493	391	2	the	the	DET
cana-2493	391	3	everincreasing	everincrease	VERB
cana-2493	391	4	need	need	NOUN
cana-2493	391	5	of	of	ADP
cana-2493	391	6	automated	automate	VERB
cana-2493	391	7	diagnostic	diagnostic	ADJ
cana-2493	391	8	tools	tool	NOUN
cana-2493	391	9	particularly	particularly	ADV
cana-2493	391	10	highlighted	highlight	VERB
cana-2493	391	11	during	during	ADP
cana-2493	391	12	global	global	ADJ
cana-2493	391	13	health	health	NOUN
cana-2493	391	14	emergencies	emergency	NOUN
cana-2493	391	15	like	like	ADP
cana-2493	391	16	covid-19	covid-19	PROPN
cana-2493	391	17	,	,	PUNCT
cana-2493	391	18	our	our	PRON
cana-2493	391	19	model	model	NOUN
cana-2493	391	20	holds	hold	VERB
cana-2493	391	21	great	great	ADJ
cana-2493	391	22	promise	promise	NOUN
cana-2493	391	23	in	in	ADP
cana-2493	391	24	improving	improve	VERB
cana-2493	391	25	the	the	DET
cana-2493	391	26	diagnosis	diagnosis	NOUN
cana-2493	391	27	and	and	CCONJ
cana-2493	391	28	management	management	NOUN
cana-2493	391	29	of	of	ADP
cana-2493	391	30	lung	lung	NOUN
cana-2493	391	31	cancers	cancer	NOUN
cana-2493	391	32	along	along	ADP
cana-2493	391	33	with	with	ADP
cana-2493	391	34	various	various	ADJ
cana-2493	391	35	other	other	ADJ
cana-2493	391	36	medical	medical	ADJ
cana-2493	391	37	conditions	condition	NOUN
cana-2493	391	38	.	.	PUNCT
cana-2493	392	1	in	in	ADP
cana-2493	392	2	the	the	DET
cana-2493	392	3	future	future	ADJ
cana-2493	392	4	research	research	NOUN
cana-2493	392	5	,	,	PUNCT
cana-2493	392	6	we	we	PRON
cana-2493	392	7	will	will	AUX
cana-2493	392	8	improve	improve	VERB
cana-2493	392	9	the	the	DET
cana-2493	392	10	model	model	NOUN
cana-2493	392	11	architecture	architecture	NOUN
cana-2493	392	12	and	and	CCONJ
cana-2493	392	13	test	test	NOUN
cana-2493	392	14	on	on	ADP
cana-2493	392	15	other	other	ADJ
cana-2493	392	16	medical	medical	ADJ
cana-2493	392	17	imaging	imaging	NOUN
cana-2493	392	18	applications	application	NOUN
cana-2493	392	19	,	,	PUNCT
cana-2493	392	20	in	in	ADP
cana-2493	392	21	order	order	NOUN
cana-2493	392	22	to	to	PART
cana-2493	392	23	achieve	achieve	VERB
cana-2493	392	24	a	a	DET
cana-2493	392	25	more	more	ADV
cana-2493	392	26	universal	universal	ADJ
cana-2493	392	27	and	and	CCONJ
cana-2493	392	28	reliable	reliable	ADJ
cana-2493	392	29	diagnostic	diagnostic	ADJ
cana-2493	392	30	assistance	assistance	NOUN
cana-2493	392	31	tool	tool	NOUN
cana-2493	392	32	for	for	ADP
cana-2493	392	33	daily	daily	ADJ
cana-2493	392	34	clinical	clinical	ADJ
cana-2493	392	35	diagnosis	diagnosis	NOUN
cana-2493	392	36	.	.	PUNCT
cana-2493	393	1	communications	communication	NOUN
cana-2493	393	2	on	on	ADP
cana-2493	393	3	applied	apply	VERB
cana-2493	393	4	nonlinear	nonlinear	ADJ
cana-2493	393	5	analysis	analysis	NOUN
cana-2493	393	6	issn	issn	NOUN
cana-2493	393	7	:	:	PUNCT
cana-2493	393	8	1074	1074	NUM
cana-2493	393	9	-	-	PUNCT
cana-2493	393	10	133x	133x	NUM
cana-2493	393	11	vol	vol	NOUN
cana-2493	393	12	32	32	NUM
cana-2493	393	13	no	no	NOUN
cana-2493	393	14	.	.	PUNCT
cana-2493	394	1	2s	2s	NUM
cana-2493	394	2	(	(	PUNCT
cana-2493	394	3	2025	2025	NUM
cana-2493	394	4	)	)	PUNCT
cana-2493	394	5	566	566	NUM
cana-2493	394	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	394	7	references	reference	NOUN
cana-2493	394	8	:	:	PUNCT
cana-2493	395	1	[	[	X
cana-2493	395	2	1	1	NUM
cana-2493	395	3	]	]	X
cana-2493	395	4	sabry	sabry	PROPN
cana-2493	395	5	,	,	PUNCT
cana-2493	395	6	a.	a.	PROPN
cana-2493	395	7	h.	h.	PROPN
cana-2493	395	8	,	,	PUNCT
cana-2493	395	9	bashi	bashi	PROPN
cana-2493	395	10	,	,	PUNCT
cana-2493	395	11	o.	o.	PROPN
cana-2493	395	12	i.	i.	PROPN
cana-2493	395	13	d.	d.	PROPN
cana-2493	395	14	,	,	PUNCT
cana-2493	395	15	ali	ali	PROPN
cana-2493	395	16	,	,	PUNCT
cana-2493	395	17	n.	n.	PROPN
cana-2493	395	18	n.	n.	PROPN
cana-2493	395	19	,	,	PUNCT
cana-2493	395	20	&	&	CCONJ
cana-2493	395	21	al	al	PROPN
cana-2493	395	22	kubaisi	kubaisi	PROPN
cana-2493	395	23	,	,	PUNCT
cana-2493	395	24	y.	y.	PROPN
cana-2493	395	25	m.	m.	NOUN
cana-2493	395	26	(	(	PUNCT
cana-2493	395	27	2024	2024	NUM
cana-2493	395	28	)	)	PUNCT
cana-2493	395	29	.	.	PUNCT
cana-2493	396	1	lung	lung	NOUN
cana-2493	396	2	disease	disease	NOUN
cana-2493	396	3	recognition	recognition	NOUN
cana-2493	396	4	methods	method	NOUN
cana-2493	396	5	using	use	VERB
cana-2493	396	6	audiobased	audiobase	VERB
cana-2493	396	7	analysis	analysis	NOUN
cana-2493	396	8	with	with	ADP
cana-2493	396	9	machine	machine	NOUN
cana-2493	396	10	learning	learning	NOUN
cana-2493	396	11	.	.	PUNCT
cana-2493	397	1	heliyon	heliyon	NOUN
cana-2493	397	2	.	.	PUNCT
cana-2493	398	1	[	[	X
cana-2493	398	2	2	2	NUM
cana-2493	398	3	]	]	X
cana-2493	398	4	alam	alam	PROPN
cana-2493	398	5	,	,	PUNCT
cana-2493	398	6	s.	s.	PROPN
cana-2493	398	7	s.	s.	PROPN
cana-2493	398	8	,	,	PUNCT
cana-2493	398	9	anwar	anwar	PROPN
cana-2493	398	10	,	,	PUNCT
cana-2493	398	11	a.	a.	PROPN
cana-2493	398	12	s.	s.	PROPN
cana-2493	398	13	,	,	PUNCT
cana-2493	398	14	ashraf	ashraf	PROPN
cana-2493	398	15	,	,	PUNCT
cana-2493	398	16	m.	m.	NOUN
cana-2493	398	17	s.	s.	PROPN
cana-2493	398	18	,	,	PUNCT
cana-2493	398	19	ayrin	ayrin	PROPN
cana-2493	398	20	,	,	PUNCT
cana-2493	398	21	f.	f.	PROPN
cana-2493	398	22	j.	j.	PROPN
cana-2493	398	23	,	,	PUNCT
cana-2493	398	24	roy	roy	PROPN
cana-2493	398	25	,	,	PUNCT
cana-2493	398	26	p.	p.	PROPN
cana-2493	398	27	,	,	PUNCT
cana-2493	398	28	quader	quader	NOUN
cana-2493	398	29	,	,	PUNCT
cana-2493	398	30	m.	m.	NOUN
cana-2493	398	31	a.	a.	PROPN
cana-2493	398	32	,	,	PUNCT
cana-2493	398	33	&	&	CCONJ
cana-2493	398	34	quader	quader	NOUN
cana-2493	398	35	,	,	PUNCT
cana-2493	398	36	m.	m.	NOUN
cana-2493	398	37	a.	a.	NOUN
cana-2493	398	38	(	(	PUNCT
cana-2493	398	39	2024	2024	NUM
cana-2493	398	40	,	,	PUNCT
cana-2493	398	41	may	may	AUX
cana-2493	398	42	)	)	PUNCT
cana-2493	398	43	.	.	PUNCT
cana-2493	399	1	deep	deep	ADJ
cana-2493	399	2	learning	learn	VERB
cana-2493	399	3	analysis	analysis	NOUN
cana-2493	399	4	of	of	ADP
cana-2493	399	5	covid-19	covid-19	PROPN
cana-2493	399	6	lung	lung	NOUN
cana-2493	399	7	cancers	cancer	NOUN
cana-2493	399	8	in	in	ADP
cana-2493	399	9	ct	ct	NUM
cana-2493	399	10	scans	scan	NOUN
cana-2493	399	11	.	.	PUNCT
cana-2493	400	1	in	in	ADP
cana-2493	400	2	2024	2024	NUM
cana-2493	400	3	international	international	ADJ
cana-2493	400	4	conference	conference	NOUN
cana-2493	400	5	on	on	ADP
cana-2493	400	6	advances	advance	NOUN
cana-2493	400	7	in	in	ADP
cana-2493	400	8	modern	modern	ADJ
cana-2493	400	9	age	age	NOUN
cana-2493	400	10	technologies	technology	NOUN
cana-2493	400	11	for	for	ADP
cana-2493	400	12	health	health	NOUN
cana-2493	400	13	and	and	CCONJ
cana-2493	400	14	engineering	engineering	NOUN
cana-2493	400	15	science	science	NOUN
cana-2493	400	16	(	(	PUNCT
cana-2493	400	17	amathe	amathe	PROPN
cana-2493	400	18	)	)	PUNCT
cana-2493	400	19	(	(	PUNCT
cana-2493	400	20	pp	pp	X
cana-2493	400	21	.	.	PUNCT
cana-2493	401	1	1	1	NUM
cana-2493	401	2	-	-	SYM
cana-2493	401	3	5	5	NUM
cana-2493	401	4	)	)	PUNCT
cana-2493	401	5	.	.	PUNCT
cana-2493	402	1	ieee	ieee	NOUN
cana-2493	402	2	.	.	PUNCT
cana-2493	403	1	[	[	X
cana-2493	403	2	3	3	NUM
cana-2493	403	3	]	]	X
cana-2493	403	4	patil	patil	PROPN
cana-2493	403	5	,	,	PUNCT
cana-2493	403	6	prita	prita	PROPN
cana-2493	403	7	,	,	PUNCT
cana-2493	403	8	and	and	CCONJ
cana-2493	403	9	vaibhav	vaibhav	NOUN
cana-2493	403	10	narawade	narawade	NOUN
cana-2493	403	11	.	.	PUNCT
cana-2493	404	1	"	"	PUNCT
cana-2493	404	2	resp	resp	VERB
cana-2493	404	3	dataset	dataset	ADJ
cana-2493	404	4	construction	construction	NOUN
cana-2493	404	5	with	with	ADP
cana-2493	404	6	multiclass	multiclass	ADJ
cana-2493	404	7	classification	classification	NOUN
cana-2493	404	8	in	in	ADP
cana-2493	404	9	respiratory	respiratory	ADJ
cana-2493	404	10	disease	disease	NOUN
cana-2493	404	11	cancer	cancer	NOUN
cana-2493	404	12	detection	detection	NOUN
cana-2493	404	13	using	use	VERB
cana-2493	404	14	machine	machine	NOUN
cana-2493	404	15	learning	learning	NOUN
cana-2493	404	16	approach	approach	NOUN
cana-2493	404	17	.	.	PUNCT
cana-2493	404	18	"	"	PUNCT
cana-2493	405	1	international	international	ADJ
cana-2493	405	2	journal	journal	NOUN
cana-2493	405	3	of	of	ADP
cana-2493	405	4	information	information	NOUN
cana-2493	405	5	technology	technology	NOUN
cana-2493	405	6	(	(	PUNCT
cana-2493	405	7	2024	2024	NUM
cana-2493	405	8	):	):	PUNCT
cana-2493	405	9	1	1	NUM
cana-2493	405	10	-	-	SYM
cana-2493	405	11	18	18	NUM
cana-2493	405	12	.	.	PUNCT
cana-2493	406	1	[	[	X
cana-2493	406	2	4	4	NUM
cana-2493	406	3	]	]	X
cana-2493	406	4	pan	pan	PROPN
cana-2493	406	5	,	,	PUNCT
cana-2493	406	6	c.	c.	PROPN
cana-2493	406	7	t.	t.	PROPN
cana-2493	406	8	,	,	PUNCT
cana-2493	406	9	kumar	kumar	PROPN
cana-2493	406	10	,	,	PUNCT
cana-2493	406	11	r.	r.	PROPN
cana-2493	406	12	,	,	PUNCT
cana-2493	406	13	wen	wen	PROPN
cana-2493	406	14	,	,	PUNCT
cana-2493	406	15	z.	z.	PROPN
cana-2493	406	16	h.	h.	PROPN
cana-2493	406	17	,	,	PUNCT
cana-2493	406	18	wang	wang	PROPN
cana-2493	406	19	,	,	PUNCT
cana-2493	406	20	c.	c.	PROPN
cana-2493	406	21	h.	h.	PROPN
cana-2493	406	22	,	,	PUNCT
cana-2493	406	23	chang	chang	PROPN
cana-2493	406	24	,	,	PUNCT
cana-2493	406	25	c.	c.	PROPN
cana-2493	406	26	y.	y.	PROPN
cana-2493	406	27	,	,	PUNCT
cana-2493	406	28	&	&	CCONJ
cana-2493	406	29	shiue	shiue	PROPN
cana-2493	406	30	,	,	PUNCT
cana-2493	406	31	y.	y.	PROPN
cana-2493	406	32	l.	l.	PROPN
cana-2493	406	33	(	(	PUNCT
cana-2493	406	34	2024	2024	NUM
cana-2493	406	35	)	)	PUNCT
cana-2493	406	36	.	.	PUNCT
cana-2493	407	1	improving	improve	VERB
cana-2493	407	2	respiratory	respiratory	ADJ
cana-2493	407	3	cancer	cancer	NOUN
cana-2493	407	4	diagnosis	diagnosis	NOUN
cana-2493	407	5	with	with	ADP
cana-2493	407	6	deep	deep	ADJ
cana-2493	407	7	learning	learning	NOUN
cana-2493	407	8	and	and	CCONJ
cana-2493	407	9	combinatorial	combinatorial	ADJ
cana-2493	407	10	fusion	fusion	NOUN
cana-2493	407	11	:	:	PUNCT
cana-2493	407	12	a	a	DET
cana-2493	407	13	two	two	NUM
cana-2493	407	14	-	-	PUNCT
cana-2493	407	15	stage	stage	NOUN
cana-2493	407	16	approach	approach	NOUN
cana-2493	407	17	using	use	VERB
cana-2493	407	18	chest	chest	NOUN
cana-2493	407	19	x	x	NOUN
cana-2493	407	20	-	-	NOUN
cana-2493	407	21	ray	ray	NOUN
cana-2493	407	22	imaging	imaging	NOUN
cana-2493	407	23	.	.	PUNCT
cana-2493	408	1	diagnostics	diagnostic	NOUN
cana-2493	408	2	,	,	PUNCT
cana-2493	408	3	14(5	14(5	NUM
cana-2493	408	4	)	)	PUNCT
cana-2493	408	5	,	,	PUNCT
cana-2493	408	6	500	500	NUM
cana-2493	408	7	.	.	PUNCT
cana-2493	409	1	[	[	X
cana-2493	409	2	5	5	NUM
cana-2493	409	3	]	]	X
cana-2493	409	4	santhoosh	santhoosh	NOUN
cana-2493	409	5	,	,	PUNCT
cana-2493	409	6	m.	m.	NOUN
cana-2493	409	7	r.	r.	PROPN
cana-2493	409	8	,	,	PUNCT
cana-2493	409	9	praveen	praveen	PROPN
cana-2493	409	10	,	,	PUNCT
cana-2493	409	11	v.	v.	PROPN
cana-2493	409	12	,	,	PUNCT
cana-2493	409	13	riyaz	riyaz	PROPN
cana-2493	409	14	,	,	PUNCT
cana-2493	409	15	a.	a.	NOUN
cana-2493	409	16	m.	m.	NOUN
cana-2493	409	17	,	,	PUNCT
cana-2493	409	18	narendiran	narendiran	NOUN
cana-2493	409	19	,	,	PUNCT
cana-2493	409	20	m.	m.	NOUN
cana-2493	409	21	s.	s.	PROPN
cana-2493	409	22	,	,	PUNCT
cana-2493	409	23	vibhinarayanan	vibhinarayanan	PROPN
cana-2493	409	24	,	,	PUNCT
cana-2493	409	25	r.	r.	PROPN
cana-2493	409	26	v.	v.	PROPN
cana-2493	409	27	,	,	PUNCT
cana-2493	409	28	&	&	CCONJ
cana-2493	409	29	prabha	prabha	PROPN
cana-2493	409	30	,	,	PUNCT
cana-2493	409	31	b.	b.	PROPN
cana-2493	409	32	(	(	PUNCT
cana-2493	409	33	2024	2024	NUM
cana-2493	409	34	,	,	PUNCT
cana-2493	409	35	april	april	PROPN
cana-2493	409	36	)	)	PUNCT
cana-2493	409	37	.	.	PUNCT
cana-2493	410	1	classification	classification	NOUN
cana-2493	410	2	of	of	ADP
cana-2493	410	3	lung	lung	NOUN
cana-2493	410	4	disease	disease	NOUN
cana-2493	410	5	with	with	ADP
cana-2493	410	6	recommendation	recommendation	NOUN
cana-2493	410	7	using	use	VERB
cana-2493	410	8	deep	deep	ADJ
cana-2493	410	9	learning	learning	NOUN
cana-2493	410	10	.	.	PUNCT
cana-2493	411	1	in	in	ADP
cana-2493	411	2	2024	2024	NUM
cana-2493	411	3	international	international	ADJ
cana-2493	411	4	conference	conference	NOUN
cana-2493	411	5	on	on	ADP
cana-2493	411	6	cognitive	cognitive	ADJ
cana-2493	411	7	robotics	robotic	NOUN
cana-2493	411	8	and	and	CCONJ
cana-2493	411	9	intelligent	intelligent	ADJ
cana-2493	411	10	systems	system	NOUN
cana-2493	411	11	(	(	PUNCT
cana-2493	411	12	icc	icc	NOUN
cana-2493	411	13	-	-	PUNCT
cana-2493	411	14	robins	robin	NOUN
cana-2493	411	15	)	)	PUNCT
cana-2493	411	16	(	(	PUNCT
cana-2493	411	17	pp	pp	X
cana-2493	411	18	.	.	PUNCT
cana-2493	412	1	120	120	NUM
cana-2493	412	2	-	-	SYM
cana-2493	412	3	126	126	NUM
cana-2493	412	4	)	)	PUNCT
cana-2493	412	5	.	.	PUNCT
cana-2493	413	1	ieee	ieee	NOUN
cana-2493	413	2	.	.	PUNCT
cana-2493	414	1	[	[	X
cana-2493	414	2	6	6	NUM
cana-2493	414	3	]	]	SYM
cana-2493	414	4	li	li	PROPN
cana-2493	414	5	,	,	PUNCT
cana-2493	414	6	j.	j.	PROPN
cana-2493	414	7	,	,	PUNCT
cana-2493	414	8	xiong	xiong	PROPN
cana-2493	414	9	,	,	PUNCT
cana-2493	414	10	a.	a.	PROPN
cana-2493	414	11	,	,	PUNCT
cana-2493	414	12	wang	wang	PROPN
cana-2493	414	13	,	,	PUNCT
cana-2493	414	14	j.	j.	PROPN
cana-2493	414	15	,	,	PUNCT
cana-2493	414	16	wu	wu	PROPN
cana-2493	414	17	,	,	PUNCT
cana-2493	414	18	x.	x.	PROPN
cana-2493	414	19	,	,	PUNCT
cana-2493	414	20	bai	bai	PROPN
cana-2493	414	21	,	,	PUNCT
cana-2493	414	22	l.	l.	PROPN
cana-2493	414	23	,	,	PUNCT
cana-2493	414	24	zhang	zhang	PROPN
cana-2493	414	25	,	,	PUNCT
cana-2493	414	26	l.	l.	PROPN
cana-2493	414	27	,	,	PUNCT
cana-2493	414	28	...	...	PUNCT
cana-2493	414	29	&	&	CCONJ
cana-2493	414	30	li	li	PROPN
cana-2493	414	31	,	,	PUNCT
cana-2493	414	32	g.	g.	PROPN
cana-2493	414	33	(	(	PUNCT
cana-2493	414	34	2024	2024	NUM
cana-2493	414	35	)	)	PUNCT
cana-2493	414	36	.	.	PUNCT
cana-2493	415	1	deciphering	decipher	VERB
cana-2493	415	2	the	the	DET
cana-2493	415	3	microbial	microbial	ADJ
cana-2493	415	4	landscape	landscape	NOUN
cana-2493	415	5	of	of	ADP
cana-2493	415	6	lower	low	ADJ
cana-2493	415	7	respiratory	respiratory	ADJ
cana-2493	415	8	tract	tract	NOUN
cana-2493	415	9	cancers	cancer	NOUN
cana-2493	415	10	:	:	PUNCT
cana-2493	415	11	insights	insight	NOUN
cana-2493	415	12	from	from	ADP
cana-2493	415	13	metagenomics	metagenomic	NOUN
cana-2493	415	14	and	and	CCONJ
cana-2493	415	15	machine	machine	NOUN
cana-2493	415	16	learning	learning	NOUN
cana-2493	415	17	.	.	PUNCT
cana-2493	416	1	frontiers	frontier	NOUN
cana-2493	416	2	in	in	ADP
cana-2493	416	3	cellular	cellular	ADJ
cana-2493	416	4	and	and	CCONJ
cana-2493	416	5	cancer	cancer	NOUN
cana-2493	416	6	microbiology	microbiology	NOUN
cana-2493	416	7	,	,	PUNCT
cana-2493	416	8	14	14	NUM
cana-2493	416	9	,	,	PUNCT
cana-2493	416	10	1385562	1385562	NUM
cana-2493	416	11	.	.	PUNCT
cana-2493	417	1	[	[	X
cana-2493	417	2	7	7	NUM
cana-2493	417	3	]	]	X
cana-2493	417	4	shao	shao	PROPN
cana-2493	417	5	,	,	PUNCT
cana-2493	417	6	j.	j.	PROPN
cana-2493	417	7	,	,	PUNCT
cana-2493	417	8	ma	ma	PROPN
cana-2493	417	9	,	,	PUNCT
cana-2493	417	10	j.	j.	PROPN
cana-2493	417	11	,	,	PUNCT
cana-2493	417	12	yu	yu	PROPN
cana-2493	417	13	,	,	PUNCT
cana-2493	417	14	y.	y.	PROPN
cana-2493	417	15	,	,	PUNCT
cana-2493	417	16	zhang	zhang	PROPN
cana-2493	417	17	,	,	PUNCT
cana-2493	417	18	s.	s.	PROPN
cana-2493	417	19	,	,	PUNCT
cana-2493	417	20	wang	wang	PROPN
cana-2493	417	21	,	,	PUNCT
cana-2493	417	22	w.	w.	PROPN
cana-2493	417	23	,	,	PUNCT
cana-2493	417	24	li	li	PROPN
cana-2493	417	25	,	,	PUNCT
cana-2493	417	26	w.	w.	PROPN
cana-2493	417	27	,	,	PUNCT
cana-2493	417	28	&	&	CCONJ
cana-2493	417	29	wang	wang	PROPN
cana-2493	417	30	,	,	PUNCT
cana-2493	417	31	c.	c.	PROPN
cana-2493	417	32	(	(	PUNCT
cana-2493	417	33	2024	2024	NUM
cana-2493	417	34	)	)	PUNCT
cana-2493	417	35	.	.	PUNCT
cana-2493	418	1	a	a	DET
cana-2493	418	2	multimodal	multimodal	ADJ
cana-2493	418	3	integration	integration	NOUN
cana-2493	418	4	pipeline	pipeline	NOUN
cana-2493	418	5	for	for	ADP
cana-2493	418	6	accurate	accurate	ADJ
cana-2493	418	7	diagnosis	diagnosis	NOUN
cana-2493	418	8	,	,	PUNCT
cana-2493	418	9	pathogen	pathogen	NOUN
cana-2493	418	10	identification	identification	NOUN
cana-2493	418	11	,	,	PUNCT
cana-2493	418	12	and	and	CCONJ
cana-2493	418	13	prognosis	prognosis	NOUN
cana-2493	418	14	prediction	prediction	NOUN
cana-2493	418	15	of	of	ADP
cana-2493	418	16	pulmonary	pulmonary	ADJ
cana-2493	418	17	cancers	cancer	NOUN
cana-2493	418	18	.	.	PUNCT
cana-2493	419	1	the	the	DET
cana-2493	419	2	innovation	innovation	NOUN
cana-2493	419	3	,	,	PUNCT
cana-2493	419	4	5(4	5(4	NUM
cana-2493	419	5	)	)	PUNCT
cana-2493	419	6	.	.	PUNCT
cana-2493	420	1	[	[	X
cana-2493	420	2	8	8	NUM
cana-2493	420	3	]	]	X
cana-2493	420	4	kumar	kumar	PROPN
cana-2493	420	5	,	,	PUNCT
cana-2493	420	6	s.	s.	PROPN
cana-2493	420	7	,	,	PUNCT
cana-2493	420	8	kumar	kumar	PROPN
cana-2493	420	9	,	,	PUNCT
cana-2493	420	10	h.	h.	PROPN
cana-2493	420	11	,	,	PUNCT
cana-2493	420	12	kumar	kumar	PROPN
cana-2493	420	13	,	,	PUNCT
cana-2493	420	14	g.	g.	PROPN
cana-2493	420	15	,	,	PUNCT
cana-2493	420	16	singh	singh	PROPN
cana-2493	420	17	,	,	PUNCT
cana-2493	420	18	s.	s.	PROPN
cana-2493	420	19	p.	p.	PROPN
cana-2493	420	20	,	,	PUNCT
cana-2493	420	21	bijalwan	bijalwan	PROPN
cana-2493	420	22	,	,	PUNCT
cana-2493	420	23	a.	a.	NOUN
cana-2493	420	24	,	,	PUNCT
cana-2493	420	25	&	&	CCONJ
cana-2493	420	26	diwakar	diwakar	PROPN
cana-2493	420	27	,	,	PUNCT
cana-2493	420	28	m.	m.	NOUN
cana-2493	420	29	(	(	PUNCT
cana-2493	420	30	2024	2024	NUM
cana-2493	420	31	)	)	PUNCT
cana-2493	420	32	.	.	PUNCT
cana-2493	421	1	a	a	DET
cana-2493	421	2	methodical	methodical	ADJ
cana-2493	421	3	exploration	exploration	NOUN
cana-2493	421	4	of	of	ADP
cana-2493	421	5	imaging	imaging	NOUN
cana-2493	421	6	modalities	modality	NOUN
cana-2493	421	7	from	from	ADP
cana-2493	421	8	dataset	dataset	NOUN
cana-2493	421	9	to	to	ADP
cana-2493	421	10	detection	detection	NOUN
cana-2493	421	11	through	through	ADP
cana-2493	421	12	machine	machine	NOUN
cana-2493	421	13	learning	learning	NOUN
cana-2493	421	14	paradigms	paradigm	NOUN
cana-2493	421	15	in	in	ADP
cana-2493	421	16	prominent	prominent	ADJ
cana-2493	421	17	lung	lung	NOUN
cana-2493	421	18	disease	disease	NOUN
cana-2493	421	19	diagnosis	diagnosis	NOUN
cana-2493	421	20	:	:	PUNCT
cana-2493	421	21	a	a	DET
cana-2493	421	22	review	review	NOUN
cana-2493	421	23	.	.	PUNCT
cana-2493	422	1	bmc	bmc	PROPN
cana-2493	422	2	medical	medical	ADJ
cana-2493	422	3	imaging	imaging	NOUN
cana-2493	422	4	,	,	PUNCT
cana-2493	422	5	24(1	24(1	NUM
cana-2493	422	6	)	)	PUNCT
cana-2493	422	7	,	,	PUNCT
cana-2493	422	8	30	30	NUM
cana-2493	422	9	.	.	PUNCT
cana-2493	423	1	[	[	X
cana-2493	423	2	9	9	NUM
cana-2493	423	3	]	]	X
cana-2493	423	4	chandre	chandre	PROPN
cana-2493	423	5	,	,	PUNCT
cana-2493	423	6	d.	d.	PROPN
cana-2493	423	7	,	,	PUNCT
cana-2493	423	8	bhosale	bhosale	NOUN
cana-2493	423	9	,	,	PUNCT
cana-2493	423	10	n.	n.	NOUN
cana-2493	423	11	,	,	PUNCT
cana-2493	423	12	darode	darode	PROPN
cana-2493	423	13	,	,	PUNCT
cana-2493	423	14	r.	r.	PROPN
cana-2493	423	15	,	,	PUNCT
cana-2493	423	16	rokade	rokade	PROPN
cana-2493	423	17	,	,	PUNCT
cana-2493	423	18	l.	l.	PROPN
cana-2493	423	19	,	,	PUNCT
cana-2493	423	20	bhavsar	bhavsar	ADJ
cana-2493	423	21	,	,	PUNCT
cana-2493	423	22	s.	s.	PROPN
cana-2493	423	23	,	,	PUNCT
cana-2493	423	24	&	&	CCONJ
cana-2493	423	25	jadhav	jadhav	PROPN
cana-2493	423	26	,	,	PUNCT
cana-2493	423	27	d.	d.	PROPN
cana-2493	423	28	s.	s.	PROPN
cana-2493	423	29	(	(	PUNCT
cana-2493	423	30	2024	2024	NUM
cana-2493	423	31	,	,	PUNCT
cana-2493	423	32	january	january	PROPN
cana-2493	423	33	)	)	PUNCT
cana-2493	423	34	.	.	PUNCT
cana-2493	424	1	using	use	VERB
cana-2493	424	2	deep	deep	ADJ
cana-2493	424	3	learning	learning	NOUN
cana-2493	424	4	to	to	PART
cana-2493	424	5	identify	identify	VERB
cana-2493	424	6	types	type	NOUN
cana-2493	424	7	of	of	ADP
cana-2493	424	8	lung	lung	NOUN
cana-2493	424	9	diseases	disease	NOUN
cana-2493	424	10	from	from	ADP
cana-2493	424	11	x	x	NOUN
cana-2493	424	12	-	-	NOUN
cana-2493	424	13	ray	ray	NOUN
cana-2493	424	14	images	image	NOUN
cana-2493	424	15	.	.	PUNCT
cana-2493	425	1	in	in	ADP
cana-2493	425	2	international	international	ADJ
cana-2493	425	3	conference	conference	NOUN
cana-2493	425	4	on	on	ADP
cana-2493	425	5	multi	multi	ADJ
cana-2493	425	6	-	-	ADJ
cana-2493	425	7	strategy	strategy	ADJ
cana-2493	425	8	learning	learn	VERB
cana-2493	425	9	environment	environment	NOUN
cana-2493	425	10	(	(	PUNCT
cana-2493	425	11	pp	pp	ADJ
cana-2493	425	12	.	.	PUNCT
cana-2493	426	1	189	189	NUM
cana-2493	426	2	-	-	SYM
cana-2493	426	3	198	198	NUM
cana-2493	426	4	)	)	PUNCT
cana-2493	426	5	.	.	PUNCT
cana-2493	427	1	singapore	singapore	PROPN
cana-2493	427	2	:	:	PUNCT
cana-2493	427	3	springer	springer	NOUN
cana-2493	427	4	nature	nature	PROPN
cana-2493	427	5	singapore	singapore	PROPN
cana-2493	427	6	.	.	PUNCT
cana-2493	428	1	[	[	X
cana-2493	428	2	10	10	NUM
cana-2493	428	3	]	]	PUNCT
cana-2493	428	4	vats	vat	NOUN
cana-2493	428	5	,	,	PUNCT
cana-2493	428	6	s.	s.	PROPN
cana-2493	428	7	,	,	PUNCT
cana-2493	428	8	sharma	sharma	PROPN
cana-2493	428	9	,	,	PUNCT
cana-2493	428	10	v.	v.	PROPN
cana-2493	428	11	,	,	PUNCT
cana-2493	428	12	singh	singh	PROPN
cana-2493	428	13	,	,	PUNCT
cana-2493	428	14	k.	k.	PROPN
cana-2493	428	15	,	,	PUNCT
cana-2493	428	16	katti	katti	PROPN
cana-2493	428	17	,	,	PUNCT
cana-2493	428	18	a.	a.	NOUN
cana-2493	428	19	,	,	PUNCT
cana-2493	428	20	ariffin	ariffin	NOUN
cana-2493	428	21	,	,	PUNCT
cana-2493	428	22	m.	m.	NOUN
cana-2493	428	23	m.	m.	NOUN
cana-2493	428	24	,	,	PUNCT
cana-2493	428	25	ahmad	ahmad	PROPN
cana-2493	428	26	,	,	PUNCT
cana-2493	428	27	m.	m.	NOUN
cana-2493	428	28	n.	n.	PROPN
cana-2493	428	29	,	,	PUNCT
cana-2493	428	30	...	...	PUNCT
cana-2493	428	31	&	&	CCONJ
cana-2493	428	32	salahshour	salahshour	PROPN
cana-2493	428	33	,	,	PUNCT
cana-2493	428	34	s.	s.	PROPN
cana-2493	428	35	(	(	PUNCT
cana-2493	428	36	2024	2024	NUM
cana-2493	428	37	)	)	PUNCT
cana-2493	428	38	.	.	PUNCT
cana-2493	429	1	incremental	incremental	ADJ
cana-2493	429	2	learning	learning	NOUN
cana-2493	429	3	-	-	PUNCT
cana-2493	429	4	based	base	VERB
cana-2493	429	5	cascaded	cascade	VERB
cana-2493	429	6	model	model	NOUN
cana-2493	429	7	for	for	ADP
cana-2493	429	8	detection	detection	NOUN
cana-2493	429	9	and	and	CCONJ
cana-2493	429	10	localization	localization	NOUN
cana-2493	429	11	of	of	ADP
cana-2493	429	12	tuberculosis	tuberculosis	NOUN
cana-2493	429	13	from	from	ADP
cana-2493	429	14	chest	chest	NOUN
cana-2493	429	15	x	x	NOUN
cana-2493	429	16	-	-	NOUN
cana-2493	429	17	ray	ray	NOUN
cana-2493	429	18	images	image	NOUN
cana-2493	429	19	.	.	PUNCT
cana-2493	430	1	expert	expert	NOUN
cana-2493	430	2	systems	system	NOUN
cana-2493	430	3	with	with	ADP
cana-2493	430	4	applications	application	NOUN
cana-2493	430	5	,	,	PUNCT
cana-2493	430	6	238	238	NUM
cana-2493	430	7	,	,	PUNCT
cana-2493	430	8	122129	122129	NUM
cana-2493	430	9	.	.	PUNCT
cana-2493	431	1	[	[	X
cana-2493	431	2	11	11	NUM
cana-2493	431	3	]	]	SYM
cana-2493	431	4	ye	ye	PROPN
cana-2493	431	5	,	,	PUNCT
cana-2493	431	6	r.	r.	PROPN
cana-2493	431	7	z.	z.	PROPN
cana-2493	431	8	,	,	PUNCT
cana-2493	431	9	lipatov	lipatov	PROPN
cana-2493	431	10	,	,	PUNCT
cana-2493	431	11	k.	k.	PROPN
cana-2493	431	12	,	,	PUNCT
cana-2493	431	13	diedrich	diedrich	PROPN
cana-2493	431	14	,	,	PUNCT
cana-2493	431	15	d.	d.	PROPN
cana-2493	431	16	,	,	PUNCT
cana-2493	431	17	bhattacharyya	bhattacharyya	PROPN
cana-2493	431	18	,	,	PUNCT
cana-2493	431	19	a.	a.	PROPN
cana-2493	431	20	,	,	PUNCT
cana-2493	431	21	erickson	erickson	PROPN
cana-2493	431	22	,	,	PUNCT
cana-2493	431	23	b.	b.	PROPN
cana-2493	431	24	j.	j.	PROPN
cana-2493	431	25	,	,	PUNCT
cana-2493	431	26	pickering	pickering	PROPN
cana-2493	431	27	,	,	PUNCT
cana-2493	431	28	b.	b.	PROPN
cana-2493	431	29	w.	w.	PROPN
cana-2493	431	30	,	,	PUNCT
cana-2493	431	31	&	&	CCONJ
cana-2493	431	32	herasevich	herasevich	PROPN
cana-2493	431	33	,	,	PUNCT
cana-2493	431	34	v.	v.	PROPN
cana-2493	431	35	(	(	PUNCT
cana-2493	431	36	2024	2024	NUM
cana-2493	431	37	)	)	PUNCT
cana-2493	431	38	.	.	PUNCT
cana-2493	432	1	automatic	automatic	ADJ
cana-2493	432	2	ards	ard	NOUN
cana-2493	432	3	surveillance	surveillance	VERB
cana-2493	432	4	with	with	ADP
cana-2493	432	5	chest	chest	NOUN
cana-2493	432	6	x	x	NOUN
cana-2493	432	7	-	-	NOUN
cana-2493	432	8	ray	ray	NOUN
cana-2493	432	9	recognition	recognition	NOUN
cana-2493	432	10	using	use	VERB
cana-2493	432	11	convolutional	convolutional	ADJ
cana-2493	432	12	neural	neural	ADJ
cana-2493	432	13	networks	network	NOUN
cana-2493	432	14	.	.	PUNCT
cana-2493	433	1	journal	journal	NOUN
cana-2493	433	2	of	of	ADP
cana-2493	433	3	critical	critical	ADJ
cana-2493	433	4	care	care	NOUN
cana-2493	433	5	,	,	PUNCT
cana-2493	433	6	82	82	NUM
cana-2493	433	7	,	,	PUNCT
cana-2493	433	8	154794	154794	NUM
cana-2493	433	9	.	.	PUNCT
cana-2493	434	1	[	[	X
cana-2493	434	2	12	12	NUM
cana-2493	434	3	]	]	X
cana-2493	434	4	vijaya	vijaya	PROPN
cana-2493	434	5	,	,	PUNCT
cana-2493	434	6	p.	p.	PROPN
cana-2493	434	7	,	,	PUNCT
cana-2493	434	8	chander	chander	PROPN
cana-2493	434	9	,	,	PUNCT
cana-2493	434	10	s.	s.	PROPN
cana-2493	434	11	,	,	PUNCT
cana-2493	434	12	fernandes	fernandes	PROPN
cana-2493	434	13	,	,	PUNCT
cana-2493	434	14	r.	r.	PROPN
cana-2493	434	15	,	,	PUNCT
cana-2493	434	16	rodrigues	rodrigues	PROPN
cana-2493	434	17	,	,	PUNCT
cana-2493	434	18	a.	a.	NOUN
cana-2493	434	19	p.	p.	PROPN
cana-2493	434	20	,	,	PUNCT
cana-2493	434	21	&	&	CCONJ
cana-2493	434	22	maheswari	maheswari	PROPN
cana-2493	434	23	,	,	PUNCT
cana-2493	434	24	r.	r.	PROPN
cana-2493	434	25	(	(	PUNCT
cana-2493	434	26	2024	2024	NUM
cana-2493	434	27	)	)	PUNCT
cana-2493	434	28	.	.	PUNCT
cana-2493	435	1	severity	severity	NOUN
cana-2493	435	2	of	of	ADP
cana-2493	435	3	lung	lung	NOUN
cana-2493	435	4	cancer	cancer	NOUN
cana-2493	435	5	identification	identification	NOUN
cana-2493	435	6	and	and	CCONJ
cana-2493	435	7	classification	classification	NOUN
cana-2493	435	8	using	use	VERB
cana-2493	435	9	optimization	optimization	NOUN
cana-2493	435	10	-	-	PUNCT
cana-2493	435	11	enabled	enable	VERB
cana-2493	435	12	deep	deep	ADJ
cana-2493	435	13	learning	learning	NOUN
cana-2493	435	14	with	with	ADP
cana-2493	435	15	iot	iot	PROPN
cana-2493	435	16	.	.	PROPN
cana-2493	435	17	multimedia	multimedia	NOUN
cana-2493	435	18	systems	system	NOUN
cana-2493	435	19	,	,	PUNCT
cana-2493	435	20	30(2	30(2	NUM
cana-2493	435	21	)	)	PUNCT
cana-2493	435	22	,	,	PUNCT
cana-2493	435	23	107	107	NUM
cana-2493	435	24	.	.	PUNCT
cana-2493	436	1	[	[	X
cana-2493	436	2	13	13	NUM
cana-2493	436	3	]	]	SYM
cana-2493	436	4	koul	koul	PROPN
cana-2493	436	5	,	,	PUNCT
cana-2493	436	6	apeksha	apeksha	PROPN
cana-2493	436	7	,	,	PUNCT
cana-2493	436	8	rajesh	rajesh	PROPN
cana-2493	436	9	k.	k.	PROPN
cana-2493	436	10	bawa	bawa	PROPN
cana-2493	436	11	,	,	PUNCT
cana-2493	436	12	and	and	CCONJ
cana-2493	436	13	yogesh	yogesh	PROPN
cana-2493	436	14	kumar	kumar	PROPN
cana-2493	436	15	.	.	PUNCT
cana-2493	437	1	"	"	PUNCT
cana-2493	437	2	an	an	DET
cana-2493	437	3	analysis	analysis	NOUN
cana-2493	437	4	of	of	ADP
cana-2493	437	5	deep	deep	ADJ
cana-2493	437	6	transfer	transfer	NOUN
cana-2493	437	7	learning	learning	NOUN
cana-2493	437	8	-	-	PUNCT
cana-2493	437	9	based	base	VERB
cana-2493	437	10	approaches	approach	NOUN
cana-2493	437	11	for	for	ADP
cana-2493	437	12	prediction	prediction	NOUN
cana-2493	437	13	and	and	CCONJ
cana-2493	437	14	prognosis	prognosis	NOUN
cana-2493	437	15	of	of	ADP
cana-2493	437	16	multiple	multiple	ADJ
cana-2493	437	17	respiratory	respiratory	ADJ
cana-2493	437	18	diseases	disease	NOUN
cana-2493	437	19	using	use	VERB
cana-2493	437	20	pulmonary	pulmonary	ADJ
cana-2493	437	21	images	image	NOUN
cana-2493	437	22	.	.	PUNCT
cana-2493	437	23	"	"	PUNCT
cana-2493	438	1	archives	archive	NOUN
cana-2493	438	2	of	of	ADP
cana-2493	438	3	computational	computational	ADJ
cana-2493	438	4	methods	method	NOUN
cana-2493	438	5	in	in	ADP
cana-2493	438	6	engineering	engineering	NOUN
cana-2493	438	7	31.2	31.2	NUM
cana-2493	438	8	(	(	PUNCT
cana-2493	438	9	2024	2024	NUM
cana-2493	438	10	):	):	PUNCT
cana-2493	438	11	1023	1023	NUM
cana-2493	438	12	-	-	SYM
cana-2493	438	13	1049	1049	NUM
cana-2493	438	14	.	.	PUNCT
cana-2493	439	1	[	[	X
cana-2493	439	2	14	14	NUM
cana-2493	439	3	]	]	X
cana-2493	439	4	kakarla	kakarla	NOUN
cana-2493	439	5	,	,	PUNCT
cana-2493	439	6	praveena	praveena	NOUN
cana-2493	439	7	,	,	PUNCT
cana-2493	439	8	c.	c.	PROPN
cana-2493	439	9	vimala	vimala	PROPN
cana-2493	439	10	,	,	PUNCT
cana-2493	439	11	and	and	CCONJ
cana-2493	439	12	s.	s.	PROPN
cana-2493	439	13	hemachandra	hemachandra	PROPN
cana-2493	439	14	.	.	PUNCT
cana-2493	440	1	"	"	PUNCT
cana-2493	440	2	an	an	DET
cana-2493	440	3	automatic	automatic	ADJ
cana-2493	440	4	multi	multi	ADJ
cana-2493	440	5	-	-	ADJ
cana-2493	440	6	class	class	ADJ
cana-2493	440	7	lung	lung	NOUN
cana-2493	440	8	disease	disease	NOUN
cana-2493	440	9	classification	classification	NOUN
cana-2493	440	10	using	use	VERB
cana-2493	440	11	deep	deep	ADJ
cana-2493	440	12	learning	learning	NOUN
cana-2493	440	13	based	base	VERB
cana-2493	440	14	bidirectional	bidirectional	ADJ
cana-2493	440	15	long	long	ADJ
cana-2493	440	16	short	short	ADJ
cana-2493	440	17	term	term	NOUN
cana-2493	440	18	memory	memory	NOUN
cana-2493	440	19	with	with	ADP
cana-2493	440	20	spiking	spike	VERB
cana-2493	440	21	neural	neural	ADJ
cana-2493	440	22	network	network	NOUN
cana-2493	440	23	.	.	PUNCT
cana-2493	440	24	"	"	PUNCT
cana-2493	440	25	multimedia	multimedia	NOUN
cana-2493	440	26	tools	tool	NOUN
cana-2493	440	27	and	and	CCONJ
cana-2493	440	28	applications	application	NOUN
cana-2493	440	29	83.16	83.16	NUM
cana-2493	440	30	(	(	PUNCT
cana-2493	440	31	2024	2024	NUM
cana-2493	440	32	):	):	PUNCT
cana-2493	440	33	49091	49091	NUM
cana-2493	440	34	-	-	SYM
cana-2493	440	35	49119	49119	NUM
cana-2493	440	36	.	.	PUNCT
cana-2493	441	1	[	[	X
cana-2493	441	2	15	15	NUM
cana-2493	441	3	]	]	X
cana-2493	441	4	neshat	neshat	PROPN
cana-2493	441	5	,	,	PUNCT
cana-2493	441	6	m.	m.	NOUN
cana-2493	441	7	,	,	PUNCT
cana-2493	441	8	ahmed	ahmed	PROPN
cana-2493	441	9	,	,	PUNCT
cana-2493	441	10	m.	m.	NOUN
cana-2493	441	11	,	,	PUNCT
cana-2493	441	12	askari	askari	PROPN
cana-2493	441	13	,	,	PUNCT
cana-2493	441	14	h.	h.	PROPN
cana-2493	441	15	,	,	PUNCT
cana-2493	441	16	thilakaratne	thilakaratne	NOUN
cana-2493	441	17	,	,	PUNCT
cana-2493	441	18	m.	m.	NOUN
cana-2493	441	19	,	,	PUNCT
cana-2493	441	20	&	&	CCONJ
cana-2493	441	21	mirjalili	mirjalili	PROPN
cana-2493	441	22	,	,	PUNCT
cana-2493	441	23	s.	s.	PROPN
cana-2493	441	24	(	(	PUNCT
cana-2493	441	25	2024	2024	NUM
cana-2493	441	26	)	)	PUNCT
cana-2493	441	27	.	.	PUNCT
cana-2493	442	1	hybrid	hybrid	ADJ
cana-2493	442	2	inception	inception	NOUN
cana-2493	442	3	architecture	architecture	NOUN
cana-2493	442	4	with	with	ADP
cana-2493	442	5	residual	residual	ADJ
cana-2493	442	6	connection	connection	NOUN
cana-2493	442	7	:	:	PUNCT
cana-2493	442	8	fine	fine	ADJ
cana-2493	442	9	-	-	PUNCT
cana-2493	442	10	tuned	tune	VERB
cana-2493	442	11	inception	inception	NOUN
cana-2493	442	12	-	-	PUNCT
cana-2493	442	13	resnet	resnet	NOUN
cana-2493	442	14	deep	deep	ADJ
cana-2493	442	15	learning	learning	NOUN
cana-2493	442	16	model	model	NOUN
cana-2493	442	17	for	for	ADP
cana-2493	442	18	lung	lung	NOUN
cana-2493	442	19	inflammation	inflammation	NOUN
cana-2493	442	20	diagnosis	diagnosis	NOUN
cana-2493	442	21	from	from	ADP
cana-2493	442	22	chest	chest	NOUN
cana-2493	442	23	radiographs	radiograph	NOUN
cana-2493	442	24	.	.	PUNCT
cana-2493	443	1	procedia	procedia	PROPN
cana-2493	443	2	computer	computer	NOUN
cana-2493	443	3	science	science	NOUN
cana-2493	443	4	,	,	PUNCT
cana-2493	443	5	235	235	NUM
cana-2493	443	6	,	,	PUNCT
cana-2493	443	7	1841	1841	NUM
cana-2493	443	8	-	-	SYM
cana-2493	443	9	1850	1850	NUM
cana-2493	443	10	.	.	PUNCT
cana-2493	444	1	communications	communication	NOUN
cana-2493	444	2	on	on	ADP
cana-2493	444	3	applied	apply	VERB
cana-2493	444	4	nonlinear	nonlinear	ADJ
cana-2493	444	5	analysis	analysis	NOUN
cana-2493	444	6	issn	issn	NOUN
cana-2493	444	7	:	:	PUNCT
cana-2493	444	8	1074	1074	NUM
cana-2493	444	9	-	-	PUNCT
cana-2493	444	10	133x	133x	NUM
cana-2493	444	11	vol	vol	NOUN
cana-2493	444	12	32	32	NUM
cana-2493	444	13	no	no	NOUN
cana-2493	444	14	.	.	PUNCT
cana-2493	445	1	2s	2s	NUM
cana-2493	445	2	(	(	PUNCT
cana-2493	445	3	2025	2025	NUM
cana-2493	445	4	)	)	PUNCT
cana-2493	445	5	567	567	NUM
cana-2493	445	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2493	446	1	[	[	X
cana-2493	446	2	16	16	NUM
cana-2493	446	3	]	]	X
cana-2493	446	4	suganyadevi	suganyadevi	PROPN
cana-2493	446	5	,	,	PUNCT
cana-2493	446	6	s.	s.	PROPN
cana-2493	446	7	,	,	PUNCT
cana-2493	446	8	and	and	CCONJ
cana-2493	446	9	v.	v.	ADP
cana-2493	446	10	seethalakshmi	seethalakshmi	NOUN
cana-2493	446	11	.	.	PUNCT
cana-2493	447	1	"	"	PUNCT
cana-2493	447	2	deep	deep	ADJ
cana-2493	447	3	recurrent	recurrent	ADJ
cana-2493	447	4	learning	learning	NOUN
cana-2493	447	5	based	base	VERB
cana-2493	447	6	qualified	qualified	ADJ
cana-2493	447	7	sequence	sequence	NOUN
cana-2493	447	8	segment	segment	NOUN
cana-2493	447	9	analytical	analytical	ADJ
cana-2493	447	10	model	model	NOUN
cana-2493	447	11	(	(	PUNCT
cana-2493	447	12	qs2am	qs2am	NOUN
cana-2493	447	13	)	)	PUNCT
cana-2493	447	14	for	for	ADP
cana-2493	447	15	infectious	infectious	ADJ
cana-2493	447	16	disease	disease	NOUN
cana-2493	447	17	detection	detection	NOUN
cana-2493	447	18	using	use	VERB
cana-2493	447	19	ct	ct	NUM
cana-2493	447	20	images	image	NOUN
cana-2493	447	21	.	.	PUNCT
cana-2493	447	22	"	"	PUNCT
cana-2493	448	1	evolving	evolve	VERB
cana-2493	448	2	systems	system	NOUN
cana-2493	448	3	15.2	15.2	NUM
cana-2493	448	4	(	(	PUNCT
cana-2493	448	5	2024	2024	NUM
cana-2493	448	6	):	):	PUNCT
cana-2493	448	7	505	505	NUM
cana-2493	448	8	-	-	SYM
cana-2493	448	9	521	521	NUM
cana-2493	448	10	.	.	PUNCT
cana-2493	449	1	[	[	X
cana-2493	449	2	17	17	NUM
cana-2493	449	3	]	]	PUNCT
cana-2493	449	4	abdulahi	abdulahi	ADV
cana-2493	449	5	,	,	PUNCT
cana-2493	449	6	a.	a.	NOUN
cana-2493	449	7	t.	t.	PROPN
cana-2493	449	8	,	,	PUNCT
cana-2493	449	9	ogundokun	ogundokun	PROPN
cana-2493	449	10	,	,	PUNCT
cana-2493	449	11	r.	r.	PROPN
cana-2493	449	12	o.	o.	PROPN
cana-2493	449	13	,	,	PUNCT
cana-2493	449	14	adenike	adenike	ADJ
cana-2493	449	15	,	,	PUNCT
cana-2493	449	16	a.	a.	PROPN
cana-2493	449	17	r.	r.	PROPN
cana-2493	449	18	,	,	PUNCT
cana-2493	449	19	shah	shah	NOUN
cana-2493	449	20	,	,	PUNCT
cana-2493	449	21	m.	m.	NOUN
cana-2493	449	22	a.	a.	PROPN
cana-2493	449	23	,	,	PUNCT
cana-2493	449	24	&	&	CCONJ
cana-2493	449	25	ahmed	ahmed	PROPN
cana-2493	449	26	,	,	PUNCT
cana-2493	449	27	y.	y.	PROPN
cana-2493	449	28	k.	k.	PROPN
cana-2493	450	1	(	(	PUNCT
cana-2493	450	2	2024	2024	NUM
cana-2493	450	3	)	)	PUNCT
cana-2493	450	4	.	.	PUNCT
cana-2493	451	1	pulmonet	pulmonet	NOUN
cana-2493	451	2	:	:	PUNCT
cana-2493	451	3	a	a	DET
cana-2493	451	4	novel	novel	ADJ
cana-2493	451	5	deep	deep	ADJ
cana-2493	451	6	learning	learning	NOUN
cana-2493	451	7	based	base	VERB
cana-2493	451	8	pulmonary	pulmonary	ADJ
cana-2493	451	9	diseases	disease	NOUN
cana-2493	451	10	detection	detection	NOUN
cana-2493	451	11	model	model	NOUN
cana-2493	451	12	.	.	PUNCT
cana-2493	452	1	bmc	bmc	PROPN
cana-2493	452	2	medical	medical	ADJ
cana-2493	452	3	imaging	imaging	NOUN
cana-2493	452	4	,	,	PUNCT
cana-2493	452	5	24(1	24(1	NUM
cana-2493	452	6	)	)	PUNCT
cana-2493	452	7	,	,	PUNCT
cana-2493	452	8	51	51	NUM
cana-2493	452	9	.	.	PUNCT
cana-2493	453	1	[	[	X
cana-2493	453	2	18	18	NUM
cana-2493	453	3	]	]	X
cana-2493	453	4	wang	wang	PROPN
cana-2493	453	5	,	,	PUNCT
cana-2493	453	6	y.	y.	PROPN
cana-2493	453	7	,	,	PUNCT
cana-2493	453	8	liu	liu	PROPN
cana-2493	453	9	,	,	PUNCT
cana-2493	453	10	z.	z.	PROPN
cana-2493	453	11	l.	l.	PROPN
cana-2493	453	12	,	,	PUNCT
cana-2493	453	13	yang	yang	PROPN
cana-2493	453	14	,	,	PUNCT
cana-2493	453	15	h.	h.	PROPN
cana-2493	453	16	,	,	PUNCT
cana-2493	453	17	li	li	PROPN
cana-2493	453	18	,	,	PUNCT
cana-2493	453	19	r.	r.	PROPN
cana-2493	453	20	,	,	PUNCT
cana-2493	453	21	liao	liao	PROPN
cana-2493	453	22	,	,	PUNCT
cana-2493	453	23	s.	s.	PROPN
cana-2493	453	24	j.	j.	PROPN
cana-2493	453	25	,	,	PUNCT
cana-2493	453	26	huang	huang	PROPN
cana-2493	453	27	,	,	PUNCT
cana-2493	453	28	y.	y.	PROPN
cana-2493	453	29	,	,	PUNCT
cana-2493	453	30	...	...	PUNCT
cana-2493	453	31	&	&	CCONJ
cana-2493	453	32	zhang	zhang	PROPN
cana-2493	453	33	,	,	PUNCT
cana-2493	453	34	y.	y.	PROPN
cana-2493	453	35	(	(	PUNCT
cana-2493	453	36	2024	2024	NUM
cana-2493	453	37	)	)	PUNCT
cana-2493	453	38	.	.	PUNCT
cana-2493	454	1	prediction	prediction	NOUN
cana-2493	454	2	of	of	ADP
cana-2493	454	3	viral	viral	ADJ
cana-2493	454	4	pneumonia	pneumonia	NOUN
cana-2493	454	5	based	base	VERB
cana-2493	454	6	on	on	ADP
cana-2493	454	7	machine	machine	NOUN
cana-2493	454	8	learning	learning	NOUN
cana-2493	454	9	models	model	NOUN
cana-2493	454	10	analyzing	analyze	VERB
cana-2493	454	11	pulmonary	pulmonary	ADJ
cana-2493	454	12	inflammation	inflammation	NOUN
cana-2493	454	13	index	index	NOUN
cana-2493	454	14	scores	score	NOUN
cana-2493	454	15	.	.	PUNCT
cana-2493	455	1	computers	computer	NOUN
cana-2493	455	2	in	in	ADP
cana-2493	455	3	biology	biology	NOUN
cana-2493	455	4	and	and	CCONJ
cana-2493	455	5	medicine	medicine	NOUN
cana-2493	455	6	,	,	PUNCT
cana-2493	455	7	169	169	NUM
cana-2493	455	8	,	,	PUNCT
cana-2493	455	9	107905	107905	NUM
cana-2493	455	10	.	.	PUNCT
cana-2493	456	1	[	[	X
cana-2493	456	2	19	19	NUM
cana-2493	456	3	]	]	X
cana-2493	456	4	shyni	shyni	NOUN
cana-2493	456	5	,	,	PUNCT
cana-2493	456	6	h.	h.	PROPN
cana-2493	456	7	mary	mary	PROPN
cana-2493	456	8	,	,	PUNCT
cana-2493	456	9	and	and	CCONJ
cana-2493	456	10	chitra	chitra	PROPN
cana-2493	456	11	e.	e.	PROPN
cana-2493	456	12	"	"	PUNCT
cana-2493	456	13	pulmonu	pulmonu	NOUN
cana-2493	456	14	-	-	PUNCT
cana-2493	456	15	net	net	NOUN
cana-2493	456	16	:	:	PUNCT
cana-2493	456	17	a	a	DET
cana-2493	456	18	semantic	semantic	ADJ
cana-2493	456	19	lung	lung	NOUN
cana-2493	456	20	disease	disease	NOUN
cana-2493	456	21	segmentation	segmentation	NOUN
cana-2493	456	22	model	model	NOUN
cana-2493	456	23	leveraging	leverage	VERB
cana-2493	456	24	the	the	DET
cana-2493	456	25	benefit	benefit	NOUN
cana-2493	456	26	of	of	ADP
cana-2493	456	27	multiscale	multiscale	ADJ
cana-2493	456	28	feature	feature	NOUN
cana-2493	456	29	concatenation	concatenation	NOUN
cana-2493	456	30	and	and	CCONJ
cana-2493	456	31	leaky	leaky	ADJ
cana-2493	456	32	relu	relu	NOUN
cana-2493	456	33	.	.	PUNCT
cana-2493	456	34	"	"	PUNCT
cana-2493	457	1	automatika	automatika	PROPN
cana-2493	457	2	65.2	65.2	NUM
cana-2493	457	3	(	(	PUNCT
cana-2493	457	4	2024	2024	NUM
cana-2493	457	5	):	):	PUNCT
cana-2493	457	6	641	641	NUM
cana-2493	457	7	-	-	SYM
cana-2493	457	8	651	651	NUM
cana-2493	457	9	.	.	PUNCT
cana-2493	458	1	[	[	X
cana-2493	458	2	20	20	NUM
cana-2493	458	3	]	]	X
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cana-2493	458	5	,	,	PUNCT
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cana-2493	458	10	,	,	PUNCT
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cana-2493	459	12	cancer	cancer	NOUN
cana-2493	459	13	using	use	VERB
cana-2493	459	14	cough	cough	NOUN
cana-2493	459	15	and	and	CCONJ
cana-2493	459	16	breath	breath	NOUN
cana-2493	459	17	sounds	sound	NOUN
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cana-2493	460	7	.	.	PUNCT
cana-2493	461	1	crc	crc	PROPN
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cana-2493	461	5	.	.	PUNCT
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cana-2493	462	2	-	-	SYM
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cana-2493	462	4	.	.	PUNCT
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cana-2493	463	3	]	]	SYM
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cana-2493	463	9	s.	s.	PROPN
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cana-2493	463	11	.	.	PUNCT
cana-2493	464	1	"	"	PUNCT
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cana-2493	464	8	learning	learning	NOUN
cana-2493	464	9	model	model	NOUN
cana-2493	464	10	for	for	ADP
cana-2493	464	11	lung	lung	NOUN
cana-2493	464	12	disease	disease	NOUN
cana-2493	464	13	pneumonia	pneumonia	NOUN
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cana-2493	464	15	and	and	CCONJ
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cana-2493	464	18	chest	chest	NOUN
cana-2493	464	19	x	x	NOUN
cana-2493	464	20	-	-	NOUN
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cana-2493	464	22	images	image	NOUN
cana-2493	464	23	.	.	PUNCT
cana-2493	464	24	"	"	PUNCT
cana-2493	464	25	multimedia	multimedia	NOUN
cana-2493	464	26	tools	tool	NOUN
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cana-2493	464	28	applications	application	NOUN
cana-2493	464	29	(	(	PUNCT
cana-2493	464	30	2024	2024	NUM
cana-2493	464	31	):	):	PUNCT
cana-2493	464	32	1	1	NUM
cana-2493	464	33	-	-	SYM
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cana-2493	464	35	.	.	PUNCT
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cana-2493	465	5	-	-	PUNCT
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cana-2493	465	10	,	,	PUNCT
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cana-2493	465	12	,	,	PUNCT
cana-2493	465	13	j.	j.	PROPN
cana-2493	465	14	,	,	PUNCT
cana-2493	465	15	al	al	PROPN
cana-2493	465	16	-	-	PUNCT
cana-2493	465	17	alimi	alimi	PROPN
cana-2493	465	18	,	,	PUNCT
cana-2493	465	19	d.	d.	PROPN
cana-2493	465	20	,	,	PUNCT
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cana-2493	465	22	,	,	PUNCT
cana-2493	465	23	a.	a.	NOUN
cana-2493	465	24	,	,	PUNCT
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cana-2493	465	41	2024	2024	NUM
cana-2493	465	42	)	)	PUNCT
cana-2493	465	43	.	.	PUNCT
cana-2493	466	1	chest	chest	NOUN
cana-2493	466	2	x	x	NOUN
cana-2493	466	3	-	-	NOUN
cana-2493	466	4	ray	ray	NOUN
cana-2493	466	5	images	image	NOUN
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cana-2493	466	14	:	:	PUNCT
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cana-2493	466	17	survey	survey	NOUN
cana-2493	466	18	.	.	PUNCT
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cana-2493	467	2	of	of	ADP
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cana-2493	467	4	methods	method	NOUN
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cana-2493	467	7	,	,	PUNCT
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cana-2493	467	9	-	-	SYM
cana-2493	467	10	35	35	NUM
cana-2493	467	11	.	.	PUNCT
cana-2493	468	1	[	[	X
cana-2493	468	2	23	23	NUM
cana-2493	468	3	]	]	X
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cana-2493	468	5	,	,	PUNCT
cana-2493	468	6	s.	s.	PROPN
cana-2493	468	7	,	,	PUNCT
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cana-2493	468	9	,	,	PUNCT
cana-2493	468	10	v.	v.	PROPN
cana-2493	468	11	,	,	PUNCT
cana-2493	468	12	sahu	sahu	PROPN
cana-2493	468	13	,	,	PUNCT
cana-2493	468	14	p.	p.	NOUN
cana-2493	468	15	,	,	PUNCT
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cana-2493	468	17	,	,	PUNCT
cana-2493	468	18	m.	m.	NOUN
cana-2493	468	19	k.	k.	PROPN
cana-2493	468	20	,	,	PUNCT
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cana-2493	468	22	,	,	PUNCT
cana-2493	468	23	a.	a.	PROPN
cana-2493	468	24	k.	k.	PROPN
cana-2493	468	25	,	,	PUNCT
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cana-2493	468	27	,	,	PUNCT
cana-2493	468	28	m.	m.	NOUN
cana-2493	468	29	,	,	PUNCT
cana-2493	468	30	...	...	PUNCT
cana-2493	468	31	&	&	CCONJ
cana-2493	468	32	alsamhi	alsamhi	PROPN
cana-2493	468	33	,	,	PUNCT
cana-2493	468	34	s.	s.	PROPN
cana-2493	468	35	h.	h.	PROPN
cana-2493	468	36	(	(	PUNCT
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cana-2493	468	38	)	)	PUNCT
cana-2493	468	39	.	.	PUNCT
cana-2493	469	1	a	a	DET
cana-2493	469	2	novel	novel	ADJ
cana-2493	469	3	multimodal	multimodal	NOUN
cana-2493	469	4	framework	framework	NOUN
cana-2493	469	5	for	for	ADP
cana-2493	469	6	early	early	ADJ
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cana-2493	469	8	and	and	CCONJ
cana-2493	469	9	classification	classification	NOUN
cana-2493	469	10	of	of	ADP
cana-2493	469	11	copd	copd	PROPN
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cana-2493	469	15	scan	scan	NOUN
cana-2493	469	16	images	image	NOUN
cana-2493	469	17	and	and	CCONJ
cana-2493	469	18	multivariate	multivariate	VERB
cana-2493	469	19	pulmonary	pulmonary	ADJ
cana-2493	469	20	respiratory	respiratory	ADJ
cana-2493	469	21	diseases	disease	NOUN
cana-2493	469	22	.	.	PUNCT
cana-2493	470	1	computer	computer	NOUN
cana-2493	470	2	methods	method	NOUN
cana-2493	470	3	and	and	CCONJ
cana-2493	470	4	programs	program	NOUN
cana-2493	470	5	in	in	ADP
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cana-2493	470	7	,	,	PUNCT
cana-2493	470	8	243	243	NUM
cana-2493	470	9	,	,	PUNCT
cana-2493	470	10	107911	107911	NUM
cana-2493	470	11	.	.	PUNCT
cana-2493	471	1	[	[	X
cana-2493	471	2	24	24	NUM
cana-2493	471	3	]	]	PUNCT
cana-2493	471	4	sharma	sharma	PROPN
cana-2493	471	5	,	,	PUNCT
cana-2493	471	6	vinayak	vinayak	PROPN
cana-2493	471	7	,	,	PUNCT
cana-2493	471	8	sachin	sachin	PROPN
cana-2493	471	9	kumar	kumar	PROPN
cana-2493	471	10	gupta	gupta	PROPN
cana-2493	471	11	,	,	PUNCT
cana-2493	471	12	and	and	CCONJ
cana-2493	471	13	kaushal	kaushal	PROPN
cana-2493	471	14	kumar	kumar	PROPN
cana-2493	471	15	shukla	shukla	PROPN
cana-2493	471	16	.	.	PUNCT
cana-2493	472	1	"	"	PUNCT
cana-2493	472	2	deep	deep	ADJ
cana-2493	472	3	learning	learning	NOUN
cana-2493	472	4	models	model	NOUN
cana-2493	472	5	for	for	ADP
cana-2493	472	6	tuberculosis	tuberculosis	NOUN
cana-2493	472	7	detection	detection	NOUN
cana-2493	472	8	and	and	CCONJ
cana-2493	472	9	infected	infected	ADJ
cana-2493	472	10	region	region	NOUN
cana-2493	472	11	visualization	visualization	NOUN
cana-2493	472	12	in	in	ADP
cana-2493	472	13	chest	chest	NOUN
cana-2493	472	14	x	x	NOUN
cana-2493	472	15	-	-	NOUN
cana-2493	472	16	ray	ray	NOUN
cana-2493	472	17	images	image	NOUN
cana-2493	472	18	.	.	PUNCT
cana-2493	472	19	"	"	PUNCT
cana-2493	473	1	intelligent	intelligent	ADJ
cana-2493	473	2	medicine	medicine	NOUN
cana-2493	473	3	4.2	4.2	NUM
cana-2493	473	4	(	(	PUNCT
cana-2493	473	5	2024	2024	NUM
cana-2493	473	6	):	):	PUNCT
cana-2493	473	7	104	104	NUM
cana-2493	473	8	-	-	SYM
cana-2493	473	9	113	113	NUM
cana-2493	473	10	.	.	PUNCT
cana-2493	474	1	[	[	X
cana-2493	474	2	25	25	NUM
cana-2493	474	3	]	]	PUNCT
cana-2493	474	4	shames	shame	VERB
cana-2493	474	5	,	,	PUNCT
cana-2493	474	6	marwa	marwa	PROPN
cana-2493	474	7	a.	a.	PROPN
cana-2493	474	8	,	,	PUNCT
cana-2493	474	9	and	and	CCONJ
cana-2493	474	10	mohammed	mohammed	PROPN
cana-2493	474	11	y.	y.	PROPN
cana-2493	474	12	kamil	kamil	PROPN
cana-2493	474	13	.	.	PUNCT
cana-2493	475	1	"	"	PUNCT
cana-2493	475	2	early	early	ADJ
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cana-2493	475	4	of	of	ADP
cana-2493	475	5	lung	lung	NOUN
cana-2493	475	6	cancer	cancer	NOUN
cana-2493	475	7	via	via	ADP
cana-2493	475	8	deep	deep	ADJ
cana-2493	475	9	learning	learning	NOUN
cana-2493	475	10	approach	approach	NOUN
cana-2493	475	11	.	.	PUNCT
cana-2493	475	12	"	"	PUNCT
cana-2493	476	1	international	international	ADJ
cana-2493	476	2	research	research	NOUN
cana-2493	476	3	journal	journal	NOUN
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cana-2493	476	7	6.3	6.3	NUM
cana-2493	476	8	(	(	PUNCT
cana-2493	476	9	2024	2024	NUM
cana-2493	476	10	):	):	PUNCT
cana-2493	476	11	216	216	NUM
cana-2493	476	12	-	-	SYM
cana-2493	476	13	224	224	NUM
cana-2493	476	14	.	.	PUNCT