id	sid	tid	token	lemma	pos
easat-10839	1	1	edelweiss	edelweiss	PROPN
easat-10839	1	2	applied	apply	VERB
easat-10839	1	3	science	science	NOUN
easat-10839	1	4	and	and	CCONJ
easat-10839	1	5	technology	technology	NOUN
easat-10839	1	6	issn	issn	PROPN
easat-10839	1	7	:	:	PUNCT
easat-10839	1	8	2576	2576	NUM
easat-10839	1	9	-	-	SYM
easat-10839	1	10	8484	8484	NUM
easat-10839	1	11	vol	vol	NOUN
easat-10839	1	12	.	.	PROPN
easat-10839	2	1	9	9	NUM
easat-10839	2	2	,	,	PUNCT
easat-10839	2	3	no	no	INTJ
easat-10839	2	4	.	.	NOUN
easat-10839	2	5	11	11	NUM
easat-10839	2	6	,	,	PUNCT
easat-10839	2	7	249	249	NUM
easat-10839	2	8	-	-	SYM
easat-10839	2	9	261	261	NUM
easat-10839	2	10	2025	2025	NUM
easat-10839	2	11	publisher	publisher	NOUN
easat-10839	2	12	:	:	PUNCT
easat-10839	2	13	learning	learn	VERB
easat-10839	2	14	gate	gate	NOUN
easat-10839	2	15	doi	doi	PROPN
easat-10839	2	16	:	:	PUNCT
easat-10839	2	17	10.55214/2576	10.55214/2576	NUM
easat-10839	2	18	-	-	SYM
easat-10839	2	19	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	2	20	©	©	ADP
easat-10839	2	21	2025	2025	NUM
easat-10839	2	22	by	by	ADP
easat-10839	2	23	the	the	DET
easat-10839	2	24	authors	author	NOUN
easat-10839	2	25	;	;	PUNCT
easat-10839	3	1	licensee	licensee	PROPN
easat-10839	3	2	learning	learning	NOUN
easat-10839	3	3	gate	gate	NOUN
easat-10839	3	4	©	©	PROPN
easat-10839	3	5	2025	2025	NUM
easat-10839	3	6	by	by	ADP
easat-10839	3	7	the	the	DET
easat-10839	3	8	authors	author	NOUN
easat-10839	3	9	;	;	PUNCT
easat-10839	3	10	licensee	licensee	PROPN
easat-10839	3	11	learning	learning	NOUN
easat-10839	3	12	gate	gate	NOUN
easat-10839	3	13	history	history	NOUN
easat-10839	3	14	:	:	PUNCT
easat-10839	3	15	received	receive	VERB
easat-10839	3	16	:	:	PUNCT
easat-10839	3	17	20	20	NUM
easat-10839	3	18	august	august	PROPN
easat-10839	3	19	2025	2025	NUM
easat-10839	3	20	;	;	PUNCT
easat-10839	3	21	revised	revise	VERB
easat-10839	3	22	:	:	PUNCT
easat-10839	3	23	8	8	NUM
easat-10839	3	24	october	october	NOUN
easat-10839	3	25	2025	2025	NUM
easat-10839	3	26	;	;	PUNCT
easat-10839	3	27	accepted	accept	VERB
easat-10839	3	28	:	:	PUNCT
easat-10839	3	29	13	13	NUM
easat-10839	3	30	october2025	october2025	PROPN
easat-10839	3	31	;	;	PUNCT
easat-10839	3	32	published	publish	VERB
easat-10839	3	33	:	:	PUNCT
easat-10839	3	34	3	3	NUM
easat-10839	3	35	november	november	PROPN
easat-10839	3	36	2025	2025	NUM
easat-10839	3	37	*	*	PUNCT
easat-10839	3	38	correspondence	correspondence	NOUN
easat-10839	3	39	:	:	PUNCT
easat-10839	3	40	ito.wasito@pradita.ac.id	ito.wasito@pradita.ac.id	PROPN
easat-10839	3	41	fully	fully	ADV
easat-10839	3	42	automated	automate	VERB
easat-10839	3	43	tumor	tumor	NOUN
easat-10839	3	44	-	-	PUNCT
easat-10839	3	45	stroma	stroma	NOUN
easat-10839	3	46	ratio	ratio	NOUN
easat-10839	3	47	prediction	prediction	NOUN
easat-10839	3	48	as	as	ADP
easat-10839	3	49	prognosis	prognosis	NOUN
easat-10839	3	50	factor	factor	NOUN
easat-10839	3	51	in	in	ADP
easat-10839	3	52	colorectal	colorectal	ADJ
easat-10839	3	53	cancer	cancer	NOUN
easat-10839	3	54	using	use	VERB
easat-10839	3	55	optimized	optimize	VERB
easat-10839	3	56	deep	deep	ADJ
easat-10839	3	57	transfer	transfer	NOUN
easat-10839	3	58	learning	learn	VERB
easat-10839	3	59	ito	ito	PROPN
easat-10839	3	60	wasito1	wasito1	PROPN
easat-10839	3	61	*	*	PROPN
easat-10839	3	62	,	,	PUNCT
easat-10839	3	63	handri	handri	PROPN
easat-10839	3	64	santoso2	santoso2	PROPN
easat-10839	3	65	,	,	PUNCT
easat-10839	3	66	denny	denny	PROPN
easat-10839	3	67	saptono	saptono	VERB
easat-10839	3	68	f2	f2	PROPN
easat-10839	3	69	,	,	PUNCT
easat-10839	3	70	ekan	ekan	ADJ
easat-10839	3	71	faozi3	faozi3	NOUN
easat-10839	3	72	1department	1department	NUM
easat-10839	3	73	of	of	ADP
easat-10839	3	74	information	information	NOUN
easat-10839	3	75	technology	technology	NOUN
easat-10839	3	76	,	,	PUNCT
easat-10839	3	77	pradita	pradita	NOUN
easat-10839	3	78	university	university	PROPN
easat-10839	3	79	,	,	PUNCT
easat-10839	3	80	banten	banten	PROPN
easat-10839	3	81	,	,	PUNCT
easat-10839	3	82	indonesia	indonesia	PROPN
easat-10839	3	83	;	;	PUNCT
easat-10839	3	84	ito.wasito@pradita.ac.id	ito.wasito@pradita.ac.id	PROPN
easat-10839	3	85	(	(	PUNCT
easat-10839	3	86	i.w	i.w	PROPN
easat-10839	3	87	.	.	PROPN
easat-10839	3	88	)	)	PUNCT
easat-10839	3	89	.	.	PUNCT
easat-10839	4	1	2department	2department	NUM
easat-10839	4	2	of	of	ADP
easat-10839	4	3	public	public	ADJ
easat-10839	4	4	health	health	NOUN
easat-10839	4	5	,	,	PUNCT
easat-10839	4	6	universitas	universita	NOUN
easat-10839	4	7	muhammadiyah	muhammadiyah	ADP
easat-10839	4	8	surakarta	surakarta	NOUN
easat-10839	4	9	,	,	PUNCT
easat-10839	4	10	surakarta	surakarta	NOUN
easat-10839	4	11	,	,	PUNCT
easat-10839	4	12	indonesia	indonesia	PROPN
easat-10839	4	13	;	;	PUNCT
easat-10839	4	14	handri.santoso@pradita.ac.id	handri.santoso@pradita.ac.id	PUNCT
easat-10839	4	15	(	(	PUNCT
easat-10839	4	16	h.s	h.s	PROPN
easat-10839	4	17	.	.	PROPN
easat-10839	4	18	)	)	PUNCT
easat-10839	5	1	dsf795@ums.ac.id	dsf795@ums.ac.id	NOUN
easat-10839	5	2	(	(	PUNCT
easat-10839	5	3	d.s.f	d.s.f	NOUN
easat-10839	5	4	.	.	PUNCT
easat-10839	5	5	)	)	PUNCT
easat-10839	5	6	.	.	PUNCT
easat-10839	6	1	3department	3department	NUM
easat-10839	6	2	of	of	ADP
easat-10839	6	3	nursing	nursing	NOUN
easat-10839	6	4	science	science	NOUN
easat-10839	6	5	,	,	PUNCT
easat-10839	6	6	universitas	universita	NOUN
easat-10839	6	7	muhammadiyah	muhammadiyah	ADP
easat-10839	6	8	surakarta	surakarta	NOUN
easat-10839	6	9	,	,	PUNCT
easat-10839	6	10	surakarta	surakarta	NOUN
easat-10839	6	11	,	,	PUNCT
easat-10839	6	12	indonesia	indonesia	PROPN
easat-10839	6	13	;	;	PUNCT
easat-10839	6	14	ef666@ums.ac.id	ef666@ums.ac.id	PROPN
easat-10839	6	15	(	(	PUNCT
easat-10839	6	16	e.f	e.f	PROPN
easat-10839	6	17	.	.	PROPN
easat-10839	6	18	)	)	PUNCT
easat-10839	6	19	.	.	PUNCT
easat-10839	7	1	abstract	abstract	ADV
easat-10839	7	2	:	:	PUNCT
easat-10839	7	3	the	the	DET
easat-10839	7	4	tumor	tumor	NOUN
easat-10839	7	5	-	-	PUNCT
easat-10839	7	6	stroma	stroma	NOUN
easat-10839	7	7	ratio	ratio	NOUN
easat-10839	7	8	(	(	PUNCT
easat-10839	7	9	tsr	tsr	PROPN
easat-10839	7	10	)	)	PUNCT
easat-10839	7	11	reflects	reflect	VERB
easat-10839	7	12	a	a	DET
easat-10839	7	13	higher	high	ADJ
easat-10839	7	14	ratio	ratio	NOUN
easat-10839	7	15	of	of	ADP
easat-10839	7	16	stromal	stromal	ADJ
easat-10839	7	17	cells	cell	NOUN
easat-10839	7	18	compared	compare	VERB
easat-10839	7	19	to	to	ADP
easat-10839	7	20	cancer	cancer	NOUN
easat-10839	7	21	cells	cell	NOUN
easat-10839	7	22	in	in	ADP
easat-10839	7	23	a	a	DET
easat-10839	7	24	tumor	tumor	NOUN
easat-10839	7	25	,	,	PUNCT
easat-10839	7	26	which	which	PRON
easat-10839	7	27	is	be	AUX
easat-10839	7	28	associated	associate	VERB
easat-10839	7	29	with	with	ADP
easat-10839	7	30	a	a	DET
easat-10839	7	31	worse	bad	ADJ
easat-10839	7	32	prognosis	prognosis	NOUN
easat-10839	7	33	,	,	PUNCT
easat-10839	7	34	increased	increase	VERB
easat-10839	7	35	risk	risk	NOUN
easat-10839	7	36	of	of	ADP
easat-10839	7	37	recurrence	recurrence	NOUN
easat-10839	7	38	,	,	PUNCT
easat-10839	7	39	and	and	CCONJ
easat-10839	7	40	reduced	reduce	VERB
easat-10839	7	41	overall	overall	ADJ
easat-10839	7	42	survival	survival	NOUN
easat-10839	7	43	in	in	ADP
easat-10839	7	44	colorectal	colorectal	ADJ
easat-10839	7	45	cancer	cancer	NOUN
easat-10839	7	46	.	.	PUNCT
easat-10839	8	1	this	this	DET
easat-10839	8	2	paper	paper	NOUN
easat-10839	8	3	reports	report	VERB
easat-10839	8	4	the	the	DET
easat-10839	8	5	application	application	NOUN
easat-10839	8	6	of	of	ADP
easat-10839	8	7	optimized	optimize	VERB
easat-10839	8	8	deep	deep	ADJ
easat-10839	8	9	transfer	transfer	NOUN
easat-10839	8	10	learning	learning	NOUN
easat-10839	8	11	for	for	ADP
easat-10839	8	12	fully	fully	ADV
easat-10839	8	13	automated	automate	VERB
easat-10839	8	14	tumor	tumor	NOUN
easat-10839	8	15	-	-	PUNCT
easat-10839	8	16	stroma	stroma	NOUN
easat-10839	8	17	ratio	ratio	NOUN
easat-10839	8	18	estimation	estimation	NOUN
easat-10839	8	19	and	and	CCONJ
easat-10839	8	20	its	its	PRON
easat-10839	8	21	significance	significance	NOUN
easat-10839	8	22	as	as	ADP
easat-10839	8	23	a	a	DET
easat-10839	8	24	prognostic	prognostic	ADJ
easat-10839	8	25	factor	factor	NOUN
easat-10839	8	26	in	in	ADP
easat-10839	8	27	patient	patient	ADJ
easat-10839	8	28	survival	survival	NOUN
easat-10839	8	29	prediction	prediction	NOUN
easat-10839	8	30	.	.	PUNCT
easat-10839	9	1	various	various	ADJ
easat-10839	9	2	base	base	NOUN
easat-10839	9	3	models	model	NOUN
easat-10839	9	4	of	of	ADP
easat-10839	9	5	transfer	transfer	NOUN
easat-10839	9	6	learning	learning	NOUN
easat-10839	9	7	,	,	PUNCT
easat-10839	9	8	including	include	VERB
easat-10839	9	9	resnet18	resnet18	NOUN
easat-10839	9	10	,	,	PUNCT
easat-10839	9	11	densenet201	densenet201	PROPN
easat-10839	9	12	,	,	PUNCT
easat-10839	9	13	mobilenet_v2	mobilenet_v2	NOUN
easat-10839	9	14	,	,	PUNCT
easat-10839	9	15	efficientnet_b2	efficientnet_b2	PROPN
easat-10839	9	16	,	,	PUNCT
easat-10839	9	17	and	and	CCONJ
easat-10839	9	18	inception_v3	inception_v3	NOUN
easat-10839	9	19	,	,	PUNCT
easat-10839	9	20	are	be	AUX
easat-10839	9	21	considered	consider	VERB
easat-10839	9	22	.	.	PUNCT
easat-10839	10	1	all	all	DET
easat-10839	10	2	base	base	NOUN
easat-10839	10	3	models	model	NOUN
easat-10839	10	4	were	be	AUX
easat-10839	10	5	trained	train	VERB
easat-10839	10	6	using	use	VERB
easat-10839	10	7	the	the	DET
easat-10839	10	8	optuna	optuna	ADJ
easat-10839	10	9	hyperparameter	hyperparameter	NOUN
easat-10839	10	10	optimization	optimization	NOUN
easat-10839	10	11	framework	framework	NOUN
easat-10839	10	12	,	,	PUNCT
easat-10839	10	13	which	which	PRON
easat-10839	10	14	is	be	AUX
easat-10839	10	15	flexible	flexible	ADJ
easat-10839	10	16	,	,	PUNCT
easat-10839	10	17	modular	modular	ADJ
easat-10839	10	18	,	,	PUNCT
easat-10839	10	19	and	and	CCONJ
easat-10839	10	20	easy	easy	ADJ
easat-10839	10	21	to	to	PART
easat-10839	10	22	combine	combine	VERB
easat-10839	10	23	with	with	ADP
easat-10839	10	24	transfer	transfer	NOUN
easat-10839	10	25	learning	learning	NOUN
easat-10839	10	26	.	.	PUNCT
easat-10839	11	1	after	after	ADP
easat-10839	11	2	determining	determine	VERB
easat-10839	11	3	the	the	DET
easat-10839	11	4	optimal	optimal	ADJ
easat-10839	11	5	deep	deep	ADJ
easat-10839	11	6	transfer	transfer	NOUN
easat-10839	11	7	learning	learning	NOUN
easat-10839	11	8	model	model	NOUN
easat-10839	11	9	,	,	PUNCT
easat-10839	11	10	it	it	PRON
easat-10839	11	11	was	be	AUX
easat-10839	11	12	implemented	implement	VERB
easat-10839	11	13	to	to	PART
easat-10839	11	14	predict	predict	VERB
easat-10839	11	15	the	the	DET
easat-10839	11	16	tumor	tumor	NOUN
easat-10839	11	17	-	-	PUNCT
easat-10839	11	18	stroma	stroma	NOUN
easat-10839	11	19	ratio	ratio	NOUN
easat-10839	11	20	(	(	PUNCT
easat-10839	11	21	tsr	tsr	PROPN
easat-10839	11	22	)	)	PUNCT
easat-10839	11	23	.	.	PUNCT
easat-10839	12	1	experimental	experimental	ADJ
easat-10839	12	2	comparisons	comparison	NOUN
easat-10839	12	3	indicate	indicate	VERB
easat-10839	12	4	that	that	DET
easat-10839	12	5	resnet18	resnet18	NOUN
easat-10839	12	6	is	be	AUX
easat-10839	12	7	the	the	DET
easat-10839	12	8	most	most	ADV
easat-10839	12	9	suitable	suitable	ADJ
easat-10839	12	10	base	base	NOUN
easat-10839	12	11	deep	deep	ADJ
easat-10839	12	12	transfer	transfer	NOUN
easat-10839	12	13	learning	learning	NOUN
easat-10839	12	14	model	model	NOUN
easat-10839	12	15	for	for	ADP
easat-10839	12	16	colorectal	colorectal	ADJ
easat-10839	12	17	cancer	cancer	NOUN
easat-10839	12	18	(	(	PUNCT
easat-10839	12	19	crc	crc	NOUN
easat-10839	12	20	)	)	PUNCT
easat-10839	12	21	classification	classification	NOUN
easat-10839	12	22	.	.	PUNCT
easat-10839	13	1	consequently	consequently	ADV
easat-10839	13	2	,	,	PUNCT
easat-10839	13	3	resnet18	resnet18	NOUN
easat-10839	13	4	was	be	AUX
easat-10839	13	5	used	use	VERB
easat-10839	13	6	to	to	PART
easat-10839	13	7	classify	classify	VERB
easat-10839	13	8	whole	whole	ADJ
easat-10839	13	9	slide	slide	NOUN
easat-10839	13	10	images	image	NOUN
easat-10839	13	11	of	of	ADP
easat-10839	13	12	colorectal	colorectal	ADJ
easat-10839	13	13	patients	patient	NOUN
easat-10839	13	14	.	.	PUNCT
easat-10839	14	1	finally	finally	ADV
easat-10839	14	2	,	,	PUNCT
easat-10839	14	3	the	the	DET
easat-10839	14	4	cox	cox	PROPN
easat-10839	14	5	proportional	proportional	PROPN
easat-10839	14	6	hazards	hazard	NOUN
easat-10839	14	7	model	model	NOUN
easat-10839	14	8	was	be	AUX
easat-10839	14	9	applied	apply	VERB
easat-10839	14	10	to	to	ADP
easat-10839	14	11	features	feature	NOUN
easat-10839	14	12	including	include	VERB
easat-10839	14	13	tsr	tsr	PROPN
easat-10839	14	14	and	and	CCONJ
easat-10839	14	15	other	other	ADJ
easat-10839	14	16	clinical	clinical	ADJ
easat-10839	14	17	parameters	parameter	NOUN
easat-10839	14	18	of	of	ADP
easat-10839	14	19	colorectal	colorectal	ADJ
easat-10839	14	20	cancer	cancer	NOUN
easat-10839	14	21	.	.	PUNCT
easat-10839	15	1	the	the	DET
easat-10839	15	2	results	result	NOUN
easat-10839	15	3	demonstrate	demonstrate	VERB
easat-10839	15	4	that	that	SCONJ
easat-10839	15	5	the	the	DET
easat-10839	15	6	tumor	tumor	NOUN
easat-10839	15	7	-	-	PUNCT
easat-10839	15	8	stroma	stroma	NOUN
easat-10839	15	9	ratio	ratio	NOUN
easat-10839	15	10	can	can	AUX
easat-10839	15	11	be	be	AUX
easat-10839	15	12	considered	consider	VERB
easat-10839	15	13	an	an	DET
easat-10839	15	14	important	important	ADJ
easat-10839	15	15	prognostic	prognostic	ADJ
easat-10839	15	16	factor	factor	NOUN
easat-10839	15	17	for	for	ADP
easat-10839	15	18	colorectal	colorectal	ADJ
easat-10839	15	19	cancer	cancer	NOUN
easat-10839	15	20	based	base	VERB
easat-10839	15	21	on	on	ADP
easat-10839	15	22	survival	survival	NOUN
easat-10839	15	23	analysis	analysis	NOUN
easat-10839	15	24	prediction	prediction	NOUN
easat-10839	15	25	.	.	PUNCT
easat-10839	16	1	keywords	keyword	NOUN
easat-10839	16	2	:	:	PUNCT
easat-10839	16	3	colorectal	colorectal	ADJ
easat-10839	16	4	cancer	cancer	NOUN
easat-10839	16	5	,	,	PUNCT
easat-10839	16	6	convolutional	convolutional	ADJ
easat-10839	16	7	neural	neural	ADJ
easat-10839	16	8	networks	network	NOUN
easat-10839	16	9	,	,	PUNCT
easat-10839	16	10	deep	deep	ADJ
easat-10839	16	11	transfer	transfer	NOUN
easat-10839	16	12	learning	learning	NOUN
easat-10839	16	13	,	,	PUNCT
easat-10839	16	14	patient	patient	ADJ
easat-10839	16	15	survival	survival	NOUN
easat-10839	16	16	,	,	PUNCT
easat-10839	16	17	tumor	tumor	NOUN
easat-10839	16	18	-	-	PUNCT
easat-10839	16	19	stroma	stroma	NOUN
easat-10839	16	20	ratio	ratio	NOUN
easat-10839	16	21	.	.	PUNCT
easat-10839	17	1	1	1	X
easat-10839	17	2	.	.	X
easat-10839	17	3	introduction	introduction	NOUN
easat-10839	17	4	as	as	ADP
easat-10839	17	5	widely	widely	ADV
easat-10839	17	6	known	know	VERB
easat-10839	17	7	,	,	PUNCT
easat-10839	17	8	colorectal	colorectal	ADJ
easat-10839	17	9	cancer	cancer	NOUN
easat-10839	17	10	(	(	PUNCT
easat-10839	17	11	crc	crc	NOUN
easat-10839	17	12	)	)	PUNCT
easat-10839	17	13	is	be	AUX
easat-10839	17	14	the	the	DET
easat-10839	17	15	fourth	fourth	ADJ
easat-10839	17	16	most	most	ADV
easat-10839	17	17	common	common	ADJ
easat-10839	17	18	form	form	NOUN
easat-10839	17	19	of	of	ADP
easat-10839	17	20	cancer	cancer	NOUN
easat-10839	17	21	and	and	CCONJ
easat-10839	17	22	the	the	DET
easat-10839	17	23	second	second	ADJ
easat-10839	17	24	deadliest	deadly	ADJ
easat-10839	17	25	disease	disease	NOUN
easat-10839	17	26	[	[	X
easat-10839	17	27	1	1	NUM
easat-10839	17	28	]	]	PUNCT
easat-10839	17	29	.	.	PUNCT
easat-10839	18	1	furthermore	furthermore	ADV
easat-10839	18	2	,	,	PUNCT
easat-10839	18	3	according	accord	VERB
easat-10839	18	4	to	to	ADP
easat-10839	18	5	the	the	DET
easat-10839	18	6	american	american	PROPN
easat-10839	18	7	institute	institute	PROPN
easat-10839	18	8	of	of	ADP
easat-10839	18	9	cancer	cancer	PROPN
easat-10839	18	10	research	research	NOUN
easat-10839	18	11	,	,	PUNCT
easat-10839	18	12	colorectal	colorectal	ADJ
easat-10839	18	13	cancer	cancer	NOUN
easat-10839	18	14	cases	case	NOUN
easat-10839	18	15	worldwide	worldwide	ADV
easat-10839	18	16	are	be	AUX
easat-10839	18	17	expected	expect	VERB
easat-10839	18	18	to	to	PART
easat-10839	18	19	increase	increase	VERB
easat-10839	18	20	by	by	ADP
easat-10839	18	21	60	60	NUM
easat-10839	18	22	percent	percent	NOUN
easat-10839	18	23	over	over	ADP
easat-10839	18	24	the	the	DET
easat-10839	18	25	next	next	ADJ
easat-10839	18	26	fifteen	fifteen	NUM
easat-10839	18	27	years	year	NOUN
easat-10839	18	28	.	.	PUNCT
easat-10839	19	1	therefore	therefore	ADV
easat-10839	19	2	,	,	PUNCT
easat-10839	19	3	the	the	DET
easat-10839	19	4	critical	critical	ADJ
easat-10839	19	5	steps	step	NOUN
easat-10839	19	6	for	for	ADP
easat-10839	19	7	diagnosis	diagnosis	NOUN
easat-10839	19	8	will	will	AUX
easat-10839	19	9	also	also	ADV
easat-10839	19	10	rise	rise	VERB
easat-10839	19	11	rapidly	rapidly	ADV
easat-10839	19	12	,	,	PUNCT
easat-10839	19	13	which	which	PRON
easat-10839	19	14	could	could	AUX
easat-10839	19	15	prove	prove	VERB
easat-10839	19	16	disastrous	disastrous	ADJ
easat-10839	19	17	if	if	SCONJ
easat-10839	19	18	pathologists	pathologist	NOUN
easat-10839	19	19	rely	rely	VERB
easat-10839	19	20	solely	solely	ADV
easat-10839	19	21	on	on	ADP
easat-10839	19	22	manual	manual	ADJ
easat-10839	19	23	examinations	examination	NOUN
easat-10839	19	24	[	[	X
easat-10839	19	25	2	2	NUM
easat-10839	19	26	]	]	PUNCT
easat-10839	19	27	.	.	PUNCT
easat-10839	20	1	with	with	ADP
easat-10839	20	2	the	the	DET
easat-10839	20	3	advancement	advancement	NOUN
easat-10839	20	4	in	in	ADP
easat-10839	20	5	the	the	DET
easat-10839	20	6	field	field	NOUN
easat-10839	20	7	of	of	ADP
easat-10839	20	8	artificial	artificial	ADJ
easat-10839	20	9	intelligence	intelligence	NOUN
easat-10839	20	10	,	,	PUNCT
easat-10839	20	11	including	include	VERB
easat-10839	20	12	several	several	ADJ
easat-10839	20	13	deep	deep	ADJ
easat-10839	20	14	learning	learning	NOUN
easat-10839	20	15	approaches	approach	NOUN
easat-10839	20	16	,	,	PUNCT
easat-10839	20	17	it	it	PRON
easat-10839	20	18	has	have	AUX
easat-10839	20	19	been	be	AUX
easat-10839	20	20	applied	apply	VERB
easat-10839	20	21	to	to	PART
easat-10839	20	22	identify	identify	VERB
easat-10839	20	23	biomarkers	biomarker	NOUN
easat-10839	20	24	in	in	ADP
easat-10839	20	25	colorectal	colorectal	ADJ
easat-10839	20	26	carcinoma	carcinoma	NOUN
easat-10839	20	27	cancer	cancer	NOUN
easat-10839	21	1	[	[	X
easat-10839	21	2	3	3	NUM
easat-10839	21	3	,	,	PUNCT
easat-10839	21	4	4	4	NUM
easat-10839	21	5	]	]	PUNCT
easat-10839	21	6	.	.	PUNCT
easat-10839	22	1	the	the	DET
easat-10839	22	2	advantages	advantage	NOUN
easat-10839	22	3	of	of	ADP
easat-10839	22	4	deep	deep	ADJ
easat-10839	22	5	learning	learning	NOUN
easat-10839	22	6	-	-	PUNCT
easat-10839	22	7	based	base	VERB
easat-10839	22	8	approaches	approach	NOUN
easat-10839	22	9	can	can	AUX
easat-10839	22	10	be	be	AUX
easat-10839	22	11	used	use	VERB
easat-10839	22	12	as	as	ADP
easat-10839	22	13	a	a	DET
easat-10839	22	14	solid	solid	ADJ
easat-10839	22	15	‘	'	PUNCT
easat-10839	22	16	feature	feature	NOUN
easat-10839	22	17	extractor	extractor	NOUN
easat-10839	22	18	’	'	PUNCT
easat-10839	22	19	for	for	ADP
easat-10839	22	20	slides	slide	NOUN
easat-10839	22	21	of	of	ADP
easat-10839	22	22	cancer	cancer	NOUN
easat-10839	22	23	composition	composition	NOUN
easat-10839	22	24	.	.	PUNCT
easat-10839	23	1	then	then	ADV
easat-10839	23	2	,	,	PUNCT
easat-10839	23	3	those	those	DET
easat-10839	23	4	extracted	extract	VERB
easat-10839	23	5	features	feature	NOUN
easat-10839	23	6	will	will	AUX
easat-10839	23	7	be	be	AUX
easat-10839	23	8	determined	determine	VERB
easat-10839	23	9	using	use	VERB
easat-10839	23	10	a	a	DET
easat-10839	23	11	well	well	ADV
easat-10839	23	12	-	-	PUNCT
easat-10839	23	13	defined	define	VERB
easat-10839	23	14	feature	feature	NOUN
easat-10839	23	15	selection	selection	NOUN
easat-10839	23	16	technique	technique	NOUN
easat-10839	23	17	.	.	PUNCT
easat-10839	24	1	finally	finally	ADV
easat-10839	24	2	,	,	PUNCT
easat-10839	24	3	a	a	DET
easat-10839	24	4	classifier	classifier	NOUN
easat-10839	24	5	technique	technique	NOUN
easat-10839	24	6	will	will	AUX
easat-10839	24	7	decompose	decompose	VERB
easat-10839	24	8	slide	slide	NOUN
easat-10839	24	9	images	image	NOUN
easat-10839	24	10	into	into	ADP
easat-10839	24	11	their	their	PRON
easat-10839	24	12	expected	expect	VERB
easat-10839	24	13	category	category	NOUN
easat-10839	24	14	of	of	ADP
easat-10839	24	15	colorectal	colorectal	ADJ
easat-10839	24	16	carcinoma	carcinoma	NOUN
easat-10839	24	17	(	(	PUNCT
easat-10839	24	18	crc	crc	NOUN
easat-10839	24	19	)	)	PUNCT
easat-10839	25	1	[	[	X
easat-10839	25	2	5	5	NUM
easat-10839	25	3	-	-	SYM
easat-10839	25	4	8	8	NUM
easat-10839	25	5	]	]	PUNCT
easat-10839	25	6	.	.	PUNCT
easat-10839	26	1	various	various	ADJ
easat-10839	26	2	architectures	architecture	NOUN
easat-10839	26	3	of	of	ADP
easat-10839	26	4	convolutional	convolutional	ADJ
easat-10839	26	5	neural	neural	ADJ
easat-10839	26	6	networks	network	NOUN
easat-10839	26	7	(	(	PUNCT
easat-10839	26	8	cnn	cnn	PROPN
easat-10839	26	9	)	)	PUNCT
easat-10839	26	10	have	have	AUX
easat-10839	26	11	been	be	AUX
easat-10839	26	12	developed	develop	VERB
easat-10839	26	13	,	,	PUNCT
easat-10839	26	14	such	such	ADJ
easat-10839	26	15	as	as	ADP
easat-10839	26	16	deep	deep	ADJ
easat-10839	26	17	residual	residual	ADJ
easat-10839	26	18	networks	network	NOUN
easat-10839	26	19	(	(	PUNCT
easat-10839	26	20	resnet	resnet	NOUN
easat-10839	26	21	)	)	PUNCT
easat-10839	26	22	,	,	PUNCT
easat-10839	26	23	inception	inception	NOUN
easat-10839	26	24	networks	network	NOUN
easat-10839	26	25	,	,	PUNCT
easat-10839	26	26	densely	densely	ADV
easat-10839	26	27	connected	connect	VERB
easat-10839	26	28	convolutional	convolutional	ADJ
easat-10839	26	29	networks	network	NOUN
easat-10839	26	30	(	(	PUNCT
easat-10839	26	31	densenet	densenet	NOUN
easat-10839	26	32	)	)	PUNCT
easat-10839	26	33	,	,	PUNCT
easat-10839	26	34	mobilenet	mobilenet	NOUN
easat-10839	26	35	,	,	PUNCT
easat-10839	26	36	and	and	CCONJ
easat-10839	26	37	efficientnet	efficientnet	NOUN
easat-10839	27	1	[	[	X
easat-10839	27	2	9	9	NUM
easat-10839	27	3	]	]	PUNCT
easat-10839	27	4	.	.	PUNCT
easat-10839	28	1	those	those	DET
easat-10839	28	2	architectures	architecture	NOUN
easat-10839	28	3	are	be	AUX
easat-10839	28	4	usually	usually	ADV
easat-10839	28	5	implemented	implement	VERB
easat-10839	28	6	in	in	ADP
easat-10839	28	7	image	image	NOUN
easat-10839	28	8	classification	classification	NOUN
easat-10839	28	9	within	within	ADP
easat-10839	28	10	the	the	DET
easat-10839	28	11	transfer	transfer	NOUN
easat-10839	28	12	learning	learn	VERB
easat-10839	28	13	framework	framework	NOUN
easat-10839	28	14	[	[	X
easat-10839	28	15	10	10	NUM
easat-10839	28	16	]	]	PUNCT
easat-10839	28	17	in	in	ADP
easat-10839	28	18	which	which	PRON
easat-10839	28	19	knowledge	knowledge	NOUN
easat-10839	28	20	learned	learn	VERB
easat-10839	28	21	from	from	ADP
easat-10839	28	22	a	a	DET
easat-10839	28	23	task	task	NOUN
easat-10839	28	24	is	be	AUX
easat-10839	28	25	reused	reuse	VERB
easat-10839	28	26	in	in	ADP
easat-10839	28	27	order	order	NOUN
easat-10839	28	28	to	to	PART
easat-10839	28	29	boost	boost	VERB
easat-10839	28	30	performance	performance	NOUN
easat-10839	28	31	on	on	ADP
easat-10839	28	32	a	a	DET
easat-10839	28	33	related	relate	VERB
easat-10839	28	34	task	task	NOUN
easat-10839	28	35	.	.	PUNCT
easat-10839	29	1	the	the	DET
easat-10839	29	2	transfer	transfer	NOUN
easat-10839	29	3	learning	learn	VERB
easat-10839	29	4	framework	framework	NOUN
easat-10839	29	5	simply	simply	ADV
easat-10839	29	6	uses	use	VERB
easat-10839	29	7	the	the	DET
easat-10839	29	8	“	"	PUNCT
easat-10839	29	9	pre	pre	ADJ
easat-10839	29	10	-	-	ADJ
easat-10839	29	11	trained	train	VERB
easat-10839	29	12	weight	weight	NOUN
easat-10839	29	13	”	"	PUNCT
easat-10839	29	14	cnn	cnn	PROPN
easat-10839	29	15	-	-	PUNCT
easat-10839	29	16	based	base	VERB
easat-10839	29	17	model	model	NOUN
easat-10839	29	18	architecture	architecture	NOUN
easat-10839	29	19	using	use	VERB
easat-10839	29	20	related	relate	VERB
easat-10839	29	21	image	image	NOUN
easat-10839	29	22	datasets	dataset	NOUN
easat-10839	29	23	.	.	PUNCT
easat-10839	30	1	all	all	DET
easat-10839	30	2	the	the	DET
easat-10839	30	3	base	base	NOUN
easat-10839	30	4	models	model	NOUN
easat-10839	30	5	were	be	AUX
easat-10839	30	6	https://orcid.org/0000-0002-3265-8179	https://orcid.org/0000-0002-3265-8179	NOUN
easat-10839	30	7	https://orcid.org/0009-0009-9592-6300	https://orcid.org/0009-0009-9592-6300	PROPN
easat-10839	30	8	https://orcid.org/0000-0002-0995-0913	https://orcid.org/0000-0002-0995-0913	PROPN
easat-10839	30	9	250	250	NUM
easat-10839	30	10	edelweiss	edelweiss	PROPN
easat-10839	30	11	applied	apply	VERB
easat-10839	30	12	science	science	NOUN
easat-10839	30	13	and	and	CCONJ
easat-10839	30	14	technology	technology	NOUN
easat-10839	30	15	issn	issn	PROPN
easat-10839	30	16	:	:	PUNCT
easat-10839	30	17	2576	2576	NUM
easat-10839	30	18	-	-	SYM
easat-10839	30	19	8484	8484	NUM
easat-10839	30	20	vol	vol	NOUN
easat-10839	30	21	.	.	PROPN
easat-10839	31	1	9	9	NUM
easat-10839	31	2	,	,	PUNCT
easat-10839	31	3	no	no	INTJ
easat-10839	31	4	.	.	NOUN
easat-10839	31	5	11	11	NUM
easat-10839	31	6	:	:	PUNCT
easat-10839	31	7	249	249	NUM
easat-10839	31	8	-	-	SYM
easat-10839	31	9	261	261	NUM
easat-10839	31	10	,	,	PUNCT
easat-10839	31	11	2025	2025	NUM
easat-10839	31	12	doi	doi	NOUN
easat-10839	31	13	:	:	PUNCT
easat-10839	31	14	10.55214/2576	10.55214/2576	NUM
easat-10839	31	15	-	-	SYM
easat-10839	31	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	31	17	©	©	ADP
easat-10839	31	18	2025	2025	NUM
easat-10839	31	19	by	by	ADP
easat-10839	31	20	the	the	DET
easat-10839	31	21	authors	author	NOUN
easat-10839	31	22	;	;	PUNCT
easat-10839	31	23	licensee	licensee	PROPN
easat-10839	31	24	learning	learning	NOUN
easat-10839	31	25	gate	gate	NOUN
easat-10839	31	26	trained	train	VERB
easat-10839	31	27	using	use	VERB
easat-10839	31	28	the	the	DET
easat-10839	31	29	optuna	optuna	ADJ
easat-10839	31	30	hyperparameter	hyperparameter	NOUN
easat-10839	31	31	optimization	optimization	NOUN
easat-10839	31	32	framework	framework	NOUN
easat-10839	32	1	[	[	X
easat-10839	32	2	11	11	NUM
easat-10839	32	3	]	]	PUNCT
easat-10839	32	4	,	,	PUNCT
easat-10839	32	5	which	which	PRON
easat-10839	32	6	has	have	VERB
easat-10839	32	7	flexible	flexible	ADJ
easat-10839	32	8	,	,	PUNCT
easat-10839	32	9	modular	modular	ADJ
easat-10839	32	10	,	,	PUNCT
easat-10839	32	11	and	and	CCONJ
easat-10839	32	12	easy	easy	ADJ
easat-10839	32	13	-	-	PUNCT
easat-10839	32	14	to	to	PART
easat-10839	32	15	-	-	PUNCT
easat-10839	32	16	combine	combine	VERB
easat-10839	32	17	with	with	ADP
easat-10839	32	18	transfer	transfer	NOUN
easat-10839	32	19	learning	learning	NOUN
easat-10839	32	20	.	.	PUNCT
easat-10839	33	1	having	having	AUX
easat-10839	33	2	determined	determine	VERB
easat-10839	33	3	the	the	DET
easat-10839	33	4	optimized	optimize	VERB
easat-10839	33	5	deep	deep	ADJ
easat-10839	33	6	transfer	transfer	NOUN
easat-10839	33	7	learning	learning	NOUN
easat-10839	33	8	,	,	PUNCT
easat-10839	33	9	the	the	DET
easat-10839	33	10	model	model	NOUN
easat-10839	33	11	will	will	AUX
easat-10839	33	12	be	be	AUX
easat-10839	33	13	deployed	deploy	VERB
easat-10839	33	14	on	on	ADP
easat-10839	33	15	the	the	DET
easat-10839	33	16	training	training	NOUN
easat-10839	33	17	and	and	CCONJ
easat-10839	33	18	test	test	NOUN
easat-10839	33	19	data	datum	NOUN
easat-10839	33	20	sets	set	NOUN
easat-10839	33	21	to	to	PART
easat-10839	33	22	classify	classify	VERB
easat-10839	33	23	nine	nine	NUM
easat-10839	33	24	classes	class	NOUN
easat-10839	33	25	of	of	ADP
easat-10839	33	26	colorectal	colorectal	ADJ
easat-10839	33	27	carcinoma	carcinoma	NOUN
easat-10839	33	28	slide	slide	NOUN
easat-10839	33	29	images	image	NOUN
easat-10839	33	30	,	,	PUNCT
easat-10839	33	31	including	include	VERB
easat-10839	33	32	tumor	tumor	NOUN
easat-10839	33	33	and	and	CCONJ
easat-10839	33	34	stroma	stroma	ADJ
easat-10839	33	35	classes	class	NOUN
easat-10839	33	36	.	.	PUNCT
easat-10839	34	1	the	the	DET
easat-10839	34	2	best	good	ADJ
easat-10839	34	3	model	model	NOUN
easat-10839	34	4	will	will	AUX
easat-10839	34	5	be	be	AUX
easat-10839	34	6	applied	apply	VERB
easat-10839	34	7	to	to	ADP
easat-10839	34	8	whole	whole	ADJ
easat-10839	34	9	slide	slide	NOUN
easat-10839	34	10	images	image	NOUN
easat-10839	34	11	(	(	PUNCT
easat-10839	34	12	wsi	wsi	NOUN
easat-10839	34	13	)	)	PUNCT
easat-10839	34	14	to	to	PART
easat-10839	34	15	identify	identify	VERB
easat-10839	34	16	areas	area	NOUN
easat-10839	34	17	of	of	ADP
easat-10839	34	18	tumor	tumor	NOUN
easat-10839	34	19	and	and	CCONJ
easat-10839	34	20	stroma	stroma	NOUN
easat-10839	34	21	.	.	PUNCT
easat-10839	35	1	in	in	ADP
easat-10839	35	2	tumors	tumor	NOUN
easat-10839	35	3	,	,	PUNCT
easat-10839	35	4	the	the	DET
easat-10839	35	5	stroma	stroma	NOUN
easat-10839	35	6	is	be	AUX
easat-10839	35	7	non	non	ADJ
easat-10839	35	8	-	-	ADJ
easat-10839	35	9	cancerous	cancerous	ADJ
easat-10839	35	10	tissue	tissue	NOUN
easat-10839	35	11	,	,	PUNCT
easat-10839	35	12	which	which	PRON
easat-10839	35	13	includes	include	VERB
easat-10839	35	14	fibroblasts	fibroblast	NOUN
easat-10839	35	15	,	,	PUNCT
easat-10839	35	16	blood	blood	NOUN
easat-10839	35	17	vessels	vessel	NOUN
easat-10839	35	18	,	,	PUNCT
easat-10839	35	19	and	and	CCONJ
easat-10839	35	20	immune	immune	ADJ
easat-10839	35	21	cells	cell	NOUN
easat-10839	35	22	,	,	PUNCT
easat-10839	35	23	forming	form	VERB
easat-10839	35	24	the	the	DET
easat-10839	35	25	tumor	tumor	NOUN
easat-10839	35	26	microenvironment	microenvironment	NOUN
easat-10839	36	1	[	[	X
easat-10839	36	2	12	12	NUM
easat-10839	36	3	,	,	PUNCT
easat-10839	36	4	13	13	NUM
easat-10839	36	5	]	]	PUNCT
easat-10839	36	6	.	.	PUNCT
easat-10839	37	1	it	it	PRON
easat-10839	37	2	's	be	AUX
easat-10839	37	3	mostly	mostly	ADV
easat-10839	37	4	a	a	DET
easat-10839	37	5	product	product	NOUN
easat-10839	37	6	of	of	ADP
easat-10839	37	7	the	the	DET
easat-10839	37	8	host	host	NOUN
easat-10839	37	9	and	and	CCONJ
easat-10839	37	10	is	be	AUX
easat-10839	37	11	very	very	ADV
easat-10839	37	12	important	important	ADJ
easat-10839	37	13	for	for	ADP
easat-10839	37	14	tumor	tumor	NOUN
easat-10839	37	15	growth	growth	NOUN
easat-10839	37	16	,	,	PUNCT
easat-10839	37	17	development	development	NOUN
easat-10839	37	18	,	,	PUNCT
easat-10839	37	19	invasion	invasion	NOUN
easat-10839	37	20	,	,	PUNCT
easat-10839	37	21	and	and	CCONJ
easat-10839	37	22	metastasis	metastasis	NOUN
easat-10839	37	23	.	.	PUNCT
easat-10839	38	1	therefore	therefore	ADV
easat-10839	38	2	,	,	PUNCT
easat-10839	38	3	the	the	DET
easat-10839	38	4	tumor	tumor	NOUN
easat-10839	38	5	-	-	PUNCT
easat-10839	38	6	stroma	stroma	NOUN
easat-10839	38	7	ratio	ratio	NOUN
easat-10839	38	8	(	(	PUNCT
easat-10839	38	9	tsr	tsr	PROPN
easat-10839	38	10	)	)	PUNCT
easat-10839	38	11	is	be	AUX
easat-10839	38	12	a	a	DET
easat-10839	38	13	prognostic	prognostic	ADJ
easat-10839	38	14	indicator	indicator	NOUN
easat-10839	38	15	in	in	ADP
easat-10839	38	16	cancer	cancer	NOUN
easat-10839	38	17	,	,	PUNCT
easat-10839	38	18	defined	define	VERB
easat-10839	38	19	as	as	ADP
easat-10839	38	20	the	the	DET
easat-10839	38	21	proportion	proportion	NOUN
easat-10839	38	22	of	of	ADP
easat-10839	38	23	stroma	stroma	ADJ
easat-10839	38	24	(	(	PUNCT
easat-10839	38	25	non	non	ADJ
easat-10839	38	26	-	-	ADJ
easat-10839	38	27	cancerous	cancerous	ADJ
easat-10839	38	28	cells	cell	NOUN
easat-10839	38	29	and	and	CCONJ
easat-10839	38	30	extracellular	extracellular	ADJ
easat-10839	38	31	matrix	matrix	NOUN
easat-10839	38	32	)	)	PUNCT
easat-10839	38	33	to	to	ADP
easat-10839	38	34	cancer	cancer	NOUN
easat-10839	38	35	cells	cell	NOUN
easat-10839	38	36	within	within	ADP
easat-10839	38	37	a	a	DET
easat-10839	38	38	tumor	tumor	NOUN
easat-10839	38	39	[	[	X
easat-10839	38	40	13	13	NUM
easat-10839	38	41	,	,	PUNCT
easat-10839	38	42	14	14	NUM
easat-10839	38	43	]	]	PUNCT
easat-10839	38	44	.	.	PUNCT
easat-10839	39	1	a	a	DET
easat-10839	39	2	high	high	ADJ
easat-10839	39	3	tsr	tsr	PROPN
easat-10839	39	4	,	,	PUNCT
easat-10839	39	5	meaning	mean	VERB
easat-10839	39	6	higher	high	ADJ
easat-10839	39	7	percentages	percentage	NOUN
easat-10839	39	8	of	of	ADP
easat-10839	39	9	stroma	stroma	NOUN
easat-10839	39	10	,	,	PUNCT
easat-10839	39	11	is	be	AUX
easat-10839	39	12	generally	generally	ADV
easat-10839	39	13	associated	associate	VERB
easat-10839	39	14	with	with	ADP
easat-10839	39	15	a	a	DET
easat-10839	39	16	poorer	poor	ADJ
easat-10839	39	17	prognosis	prognosis	NOUN
easat-10839	39	18	,	,	PUNCT
easat-10839	39	19	shorter	short	ADJ
easat-10839	39	20	survival	survival	NOUN
easat-10839	39	21	,	,	PUNCT
easat-10839	39	22	and	and	CCONJ
easat-10839	39	23	increased	increase	VERB
easat-10839	39	24	risk	risk	NOUN
easat-10839	39	25	of	of	ADP
easat-10839	39	26	recurrence	recurrence	NOUN
easat-10839	39	27	and	and	CCONJ
easat-10839	39	28	metastasis	metastasis	NOUN
easat-10839	39	29	in	in	ADP
easat-10839	39	30	many	many	ADJ
easat-10839	39	31	cancers	cancer	NOUN
easat-10839	39	32	,	,	PUNCT
easat-10839	39	33	including	include	VERB
easat-10839	39	34	colorectal	colorectal	ADJ
easat-10839	39	35	cancer	cancer	NOUN
easat-10839	39	36	.	.	PUNCT
easat-10839	40	1	pathologists	pathologist	NOUN
easat-10839	40	2	determine	determine	VERB
easat-10839	40	3	tsr	tsr	PROPN
easat-10839	40	4	visually	visually	ADV
easat-10839	40	5	by	by	ADP
easat-10839	40	6	following	follow	VERB
easat-10839	40	7	a	a	DET
easat-10839	40	8	certain	certain	ADJ
easat-10839	40	9	scoring	scoring	NOUN
easat-10839	40	10	protocol	protocol	NOUN
easat-10839	40	11	.	.	PUNCT
easat-10839	41	1	the	the	DET
easat-10839	41	2	main	main	ADJ
easat-10839	41	3	problem	problem	NOUN
easat-10839	41	4	with	with	ADP
easat-10839	41	5	this	this	DET
easat-10839	41	6	approach	approach	NOUN
easat-10839	41	7	is	be	AUX
easat-10839	41	8	the	the	DET
easat-10839	41	9	reproducibility	reproducibility	NOUN
easat-10839	41	10	and	and	CCONJ
easat-10839	41	11	consistency	consistency	NOUN
easat-10839	41	12	of	of	ADP
easat-10839	41	13	the	the	DET
easat-10839	41	14	tsr	tsr	PROPN
easat-10839	41	15	scoring	scoring	NOUN
easat-10839	41	16	.	.	PUNCT
easat-10839	42	1	therefore	therefore	ADV
easat-10839	42	2	,	,	PUNCT
easat-10839	42	3	developing	develop	VERB
easat-10839	42	4	an	an	DET
easat-10839	42	5	automated	automate	VERB
easat-10839	42	6	tsr	tsr	PROPN
easat-10839	42	7	scoring	scoring	NOUN
easat-10839	42	8	system	system	NOUN
easat-10839	42	9	is	be	AUX
easat-10839	42	10	required	require	VERB
easat-10839	42	11	to	to	PART
easat-10839	42	12	ensure	ensure	VERB
easat-10839	42	13	that	that	SCONJ
easat-10839	42	14	the	the	DET
easat-10839	42	15	values	value	NOUN
easat-10839	42	16	are	be	AUX
easat-10839	42	17	reproducible	reproducible	ADJ
easat-10839	42	18	and	and	CCONJ
easat-10839	42	19	consistent	consistent	ADJ
easat-10839	42	20	[	[	X
easat-10839	42	21	12	12	NUM
easat-10839	42	22	,	,	PUNCT
easat-10839	42	23	14	14	NUM
easat-10839	42	24	-	-	SYM
easat-10839	42	25	16	16	NUM
easat-10839	42	26	]	]	PUNCT
easat-10839	42	27	.	.	PUNCT
easat-10839	43	1	the	the	DET
easat-10839	43	2	automated	automate	VERB
easat-10839	43	3	prediction	prediction	NOUN
easat-10839	43	4	of	of	ADP
easat-10839	43	5	tsr	tsr	PROPN
easat-10839	43	6	will	will	AUX
easat-10839	43	7	be	be	AUX
easat-10839	43	8	computed	compute	VERB
easat-10839	43	9	based	base	VERB
easat-10839	43	10	on	on	ADP
easat-10839	43	11	whole	whole	ADJ
easat-10839	43	12	slide	slide	NOUN
easat-10839	43	13	images	image	NOUN
easat-10839	43	14	for	for	ADP
easat-10839	43	15	each	each	DET
easat-10839	43	16	patient	patient	NOUN
easat-10839	43	17	using	use	VERB
easat-10839	43	18	the	the	DET
easat-10839	43	19	optimized	optimize	VERB
easat-10839	43	20	deep	deep	ADJ
easat-10839	43	21	transfer	transfer	NOUN
easat-10839	43	22	learning	learning	NOUN
easat-10839	43	23	methods	method	NOUN
easat-10839	43	24	identified	identify	VERB
easat-10839	43	25	in	in	ADP
easat-10839	43	26	the	the	DET
easat-10839	43	27	previous	previous	ADJ
easat-10839	43	28	steps	step	NOUN
easat-10839	43	29	.	.	PUNCT
easat-10839	44	1	those	those	DET
easat-10839	44	2	tsr	tsr	PROPN
easat-10839	44	3	values	value	NOUN
easat-10839	44	4	will	will	AUX
easat-10839	44	5	be	be	AUX
easat-10839	44	6	included	include	VERB
easat-10839	44	7	as	as	ADP
easat-10839	44	8	prognostic	prognostic	ADJ
easat-10839	44	9	factors	factor	NOUN
easat-10839	44	10	alongside	alongside	ADP
easat-10839	44	11	clinical	clinical	ADJ
easat-10839	44	12	factors	factor	NOUN
easat-10839	44	13	of	of	ADP
easat-10839	44	14	crc	crc	NOUN
easat-10839	44	15	,	,	PUNCT
easat-10839	44	16	such	such	ADJ
easat-10839	44	17	as	as	ADP
easat-10839	44	18	gender	gender	NOUN
easat-10839	44	19	,	,	PUNCT
easat-10839	44	20	age	age	NOUN
easat-10839	44	21	,	,	PUNCT
easat-10839	44	22	t	t	NOUN
easat-10839	44	23	-	-	PUNCT
easat-10839	44	24	stage	stage	NOUN
easat-10839	44	25	,	,	PUNCT
easat-10839	44	26	and	and	CCONJ
easat-10839	44	27	m	m	NOUN
easat-10839	44	28	-	-	NOUN
easat-10839	44	29	stage	stage	NOUN
easat-10839	44	30	.	.	PUNCT
easat-10839	45	1	finally	finally	ADV
easat-10839	45	2	,	,	PUNCT
easat-10839	45	3	a	a	DET
easat-10839	45	4	patient	patient	ADJ
easat-10839	45	5	survival	survival	NOUN
easat-10839	45	6	prediction	prediction	NOUN
easat-10839	45	7	model	model	NOUN
easat-10839	45	8	,	,	PUNCT
easat-10839	45	9	called	call	VERB
easat-10839	45	10	the	the	DET
easat-10839	45	11	cox	cox	PROPN
easat-10839	45	12	proportional	proportional	PROPN
easat-10839	45	13	hazards	hazard	NOUN
easat-10839	45	14	(	(	PUNCT
easat-10839	45	15	cox	cox	NOUN
easat-10839	45	16	-	-	PUNCT
easat-10839	45	17	ph	ph	ADJ
easat-10839	45	18	)	)	PUNCT
easat-10839	45	19	model	model	NOUN
easat-10839	45	20	,	,	PUNCT
easat-10839	45	21	will	will	AUX
easat-10839	45	22	be	be	AUX
easat-10839	45	23	developed	develop	VERB
easat-10839	45	24	.	.	PUNCT
easat-10839	46	1	from	from	ADP
easat-10839	46	2	the	the	DET
easat-10839	46	3	cox	cox	PROPN
easat-10839	46	4	-	-	PUNCT
easat-10839	46	5	ph	ph	ADJ
easat-10839	46	6	model	model	NOUN
easat-10839	46	7	,	,	PUNCT
easat-10839	46	8	the	the	DET
easat-10839	46	9	significance	significance	NOUN
easat-10839	46	10	of	of	ADP
easat-10839	46	11	tsr	tsr	PROPN
easat-10839	46	12	as	as	ADP
easat-10839	46	13	a	a	DET
easat-10839	46	14	prognostic	prognostic	ADJ
easat-10839	46	15	factor	factor	NOUN
easat-10839	46	16	will	will	AUX
easat-10839	46	17	be	be	AUX
easat-10839	46	18	analyzed	analyze	VERB
easat-10839	46	19	[	[	X
easat-10839	46	20	10	10	NUM
easat-10839	46	21	]	]	PUNCT
easat-10839	46	22	.	.	PUNCT
easat-10839	47	1	this	this	DET
easat-10839	47	2	study	study	NOUN
easat-10839	47	3	has	have	VERB
easat-10839	47	4	two	two	NUM
easat-10839	47	5	contributions	contribution	NOUN
easat-10839	47	6	:	:	PUNCT
easat-10839	47	7	first	first	ADV
easat-10839	47	8	,	,	PUNCT
easat-10839	47	9	this	this	DET
easat-10839	47	10	research	research	NOUN
easat-10839	47	11	can	can	AUX
easat-10839	47	12	provide	provide	VERB
easat-10839	47	13	insights	insight	NOUN
easat-10839	47	14	to	to	ADP
easat-10839	47	15	medical	medical	ADJ
easat-10839	47	16	experts	expert	NOUN
easat-10839	47	17	and	and	CCONJ
easat-10839	47	18	computer	computer	NOUN
easat-10839	47	19	scientists	scientist	NOUN
easat-10839	47	20	regarding	regard	VERB
easat-10839	47	21	the	the	DET
easat-10839	47	22	current	current	ADJ
easat-10839	47	23	state	state	NOUN
easat-10839	47	24	of	of	ADP
easat-10839	47	25	development	development	NOUN
easat-10839	47	26	of	of	ADP
easat-10839	47	27	deep	deep	ADJ
easat-10839	47	28	transfer	transfer	NOUN
easat-10839	47	29	learning	learning	NOUN
easat-10839	47	30	approaches	approach	NOUN
easat-10839	47	31	for	for	ADP
easat-10839	47	32	histopathological	histopathological	ADJ
easat-10839	47	33	image	image	NOUN
easat-10839	47	34	classification	classification	NOUN
easat-10839	47	35	,	,	PUNCT
easat-10839	47	36	especially	especially	ADV
easat-10839	47	37	in	in	ADP
easat-10839	47	38	colorectal	colorectal	ADJ
easat-10839	47	39	carcinoma	carcinoma	NOUN
easat-10839	47	40	(	(	PUNCT
easat-10839	47	41	crc	crc	NOUN
easat-10839	47	42	)	)	PUNCT
easat-10839	47	43	.	.	PUNCT
easat-10839	48	1	the	the	DET
easat-10839	48	2	second	second	ADJ
easat-10839	48	3	contribution	contribution	NOUN
easat-10839	48	4	of	of	ADP
easat-10839	48	5	this	this	DET
easat-10839	48	6	research	research	NOUN
easat-10839	48	7	is	be	AUX
easat-10839	48	8	to	to	PART
easat-10839	48	9	propose	propose	VERB
easat-10839	48	10	a	a	DET
easat-10839	48	11	fully	fully	ADV
easat-10839	48	12	automatic	automatic	ADJ
easat-10839	48	13	tumor	tumor	NOUN
easat-10839	48	14	-	-	PUNCT
easat-10839	48	15	stroma	stroma	NOUN
easat-10839	48	16	prediction	prediction	NOUN
easat-10839	48	17	as	as	ADP
easat-10839	48	18	a	a	DET
easat-10839	48	19	prognostic	prognostic	ADJ
easat-10839	48	20	factor	factor	NOUN
easat-10839	48	21	for	for	ADP
easat-10839	48	22	colorectal	colorectal	ADJ
easat-10839	48	23	cancer	cancer	NOUN
easat-10839	48	24	.	.	PUNCT
easat-10839	49	1	the	the	DET
easat-10839	49	2	goals	goal	NOUN
easat-10839	49	3	of	of	ADP
easat-10839	49	4	the	the	DET
easat-10839	49	5	paper	paper	NOUN
easat-10839	49	6	can	can	AUX
easat-10839	49	7	be	be	AUX
easat-10839	49	8	summarized	summarize	VERB
easat-10839	49	9	in	in	ADP
easat-10839	49	10	two	two	NUM
easat-10839	49	11	main	main	ADJ
easat-10839	49	12	points	point	NOUN
easat-10839	49	13	:	:	PUNCT
easat-10839	49	14	firstly	firstly	ADV
easat-10839	49	15	,	,	PUNCT
easat-10839	49	16	a	a	DET
easat-10839	49	17	fully	fully	ADV
easat-10839	49	18	automated	automate	VERB
easat-10839	49	19	scoring	scoring	NOUN
easat-10839	49	20	system	system	NOUN
easat-10839	49	21	for	for	ADP
easat-10839	49	22	tsr	tsr	PROPN
easat-10839	49	23	prediction	prediction	NOUN
easat-10839	49	24	will	will	AUX
easat-10839	49	25	be	be	AUX
easat-10839	49	26	proposed	propose	VERB
easat-10839	49	27	.	.	PUNCT
easat-10839	50	1	secondly	secondly	ADV
easat-10839	50	2	,	,	PUNCT
easat-10839	50	3	the	the	DET
easat-10839	50	4	significance	significance	NOUN
easat-10839	50	5	of	of	ADP
easat-10839	50	6	tsr	tsr	PROPN
easat-10839	50	7	as	as	ADP
easat-10839	50	8	a	a	DET
easat-10839	50	9	prognostic	prognostic	ADJ
easat-10839	50	10	factor	factor	NOUN
easat-10839	50	11	,	,	PUNCT
easat-10839	50	12	alongside	alongside	ADP
easat-10839	50	13	other	other	ADJ
easat-10839	50	14	clinical	clinical	ADJ
easat-10839	50	15	factors	factor	NOUN
easat-10839	50	16	such	such	ADJ
easat-10839	50	17	as	as	ADP
easat-10839	50	18	gender	gender	NOUN
easat-10839	50	19	,	,	PUNCT
easat-10839	50	20	age	age	NOUN
easat-10839	50	21	,	,	PUNCT
easat-10839	50	22	and	and	CCONJ
easat-10839	50	23	t	t	NOUN
easat-10839	50	24	-	-	PUNCT
easat-10839	50	25	stage	stage	NOUN
easat-10839	50	26	in	in	ADP
easat-10839	50	27	colorectal	colorectal	ADJ
easat-10839	50	28	cancer	cancer	NOUN
easat-10839	50	29	,	,	PUNCT
easat-10839	50	30	will	will	AUX
easat-10839	50	31	be	be	AUX
easat-10839	50	32	evaluated	evaluate	VERB
easat-10839	50	33	using	use	VERB
easat-10839	50	34	the	the	DET
easat-10839	50	35	cox	cox	PROPN
easat-10839	50	36	proportional	proportional	PROPN
easat-10839	50	37	hazards	hazard	NOUN
easat-10839	50	38	(	(	PUNCT
easat-10839	50	39	cox	cox	NOUN
easat-10839	50	40	-	-	PUNCT
easat-10839	50	41	ph	ph	ADJ
easat-10839	50	42	)	)	PUNCT
easat-10839	50	43	model	model	NOUN
easat-10839	50	44	.	.	PUNCT
easat-10839	51	1	to	to	PART
easat-10839	51	2	achieve	achieve	VERB
easat-10839	51	3	the	the	DET
easat-10839	51	4	goals	goal	NOUN
easat-10839	51	5	,	,	PUNCT
easat-10839	51	6	this	this	DET
easat-10839	51	7	paper	paper	NOUN
easat-10839	51	8	will	will	AUX
easat-10839	51	9	be	be	AUX
easat-10839	51	10	organized	organize	VERB
easat-10839	51	11	as	as	SCONJ
easat-10839	51	12	follows	follow	VERB
easat-10839	51	13	.	.	PUNCT
easat-10839	52	1	first	first	ADV
easat-10839	52	2	,	,	PUNCT
easat-10839	52	3	deep	deep	ADJ
easat-10839	52	4	transfer	transfer	NOUN
easat-10839	52	5	learning	learning	NOUN
easat-10839	52	6	of	of	ADP
easat-10839	52	7	the	the	DET
easat-10839	52	8	cnn	cnn	PROPN
easat-10839	52	9	-	-	PUNCT
easat-10839	52	10	based	base	VERB
easat-10839	52	11	model	model	NOUN
easat-10839	52	12	for	for	ADP
easat-10839	52	13	the	the	DET
easat-10839	52	14	classification	classification	NOUN
easat-10839	52	15	of	of	ADP
easat-10839	52	16	crc	crc	NOUN
easat-10839	52	17	will	will	AUX
easat-10839	52	18	be	be	AUX
easat-10839	52	19	explored	explore	VERB
easat-10839	52	20	.	.	PUNCT
easat-10839	53	1	the	the	DET
easat-10839	53	2	hyperparameter	hyperparameter	NOUN
easat-10839	53	3	optimization	optimization	NOUN
easat-10839	53	4	for	for	ADP
easat-10839	53	5	the	the	DET
easat-10839	53	6	transfer	transfer	NOUN
easat-10839	53	7	learning	learning	NOUN
easat-10839	53	8	model	model	NOUN
easat-10839	53	9	will	will	AUX
easat-10839	53	10	be	be	AUX
easat-10839	53	11	reviewed	review	VERB
easat-10839	53	12	.	.	PUNCT
easat-10839	54	1	then	then	ADV
easat-10839	54	2	,	,	PUNCT
easat-10839	54	3	the	the	DET
easat-10839	54	4	experimental	experimental	ADJ
easat-10839	54	5	settings	setting	NOUN
easat-10839	54	6	for	for	ADP
easat-10839	54	7	finding	find	VERB
easat-10839	54	8	the	the	DET
easat-10839	54	9	tumor	tumor	NOUN
easat-10839	54	10	-	-	PUNCT
easat-10839	54	11	stroma	stroma	NOUN
easat-10839	54	12	ratio	ratio	NOUN
easat-10839	54	13	will	will	AUX
easat-10839	54	14	be	be	AUX
easat-10839	54	15	described	describe	VERB
easat-10839	54	16	.	.	PUNCT
easat-10839	55	1	the	the	DET
easat-10839	55	2	results	result	NOUN
easat-10839	55	3	and	and	CCONJ
easat-10839	55	4	discussions	discussion	NOUN
easat-10839	55	5	will	will	AUX
easat-10839	55	6	present	present	VERB
easat-10839	55	7	some	some	DET
easat-10839	55	8	findings	finding	NOUN
easat-10839	55	9	of	of	ADP
easat-10839	55	10	the	the	DET
easat-10839	55	11	experiments	experiment	NOUN
easat-10839	55	12	.	.	PUNCT
easat-10839	56	1	the	the	DET
easat-10839	56	2	paper	paper	NOUN
easat-10839	56	3	will	will	AUX
easat-10839	56	4	be	be	AUX
easat-10839	56	5	concluded	conclude	VERB
easat-10839	56	6	by	by	ADP
easat-10839	56	7	summarizing	summarize	VERB
easat-10839	56	8	the	the	DET
easat-10839	56	9	findings	finding	NOUN
easat-10839	56	10	,	,	PUNCT
easat-10839	56	11	suggestions	suggestion	NOUN
easat-10839	56	12	,	,	PUNCT
easat-10839	56	13	and	and	CCONJ
easat-10839	56	14	further	further	ADJ
easat-10839	56	15	work	work	NOUN
easat-10839	56	16	.	.	PUNCT
easat-10839	57	1	2	2	X
easat-10839	57	2	.	.	NUM
easat-10839	57	3	optimized	optimize	VERB
easat-10839	57	4	deep	deep	ADJ
easat-10839	57	5	transfer	transfer	NOUN
easat-10839	57	6	learning	learning	NOUN
easat-10839	57	7	transfer	transfer	NOUN
easat-10839	57	8	learning	learning	NOUN
easat-10839	57	9	is	be	AUX
easat-10839	57	10	a	a	DET
easat-10839	57	11	machine	machine	NOUN
easat-10839	57	12	learning	learn	VERB
easat-10839	57	13	framework	framework	NOUN
easat-10839	57	14	in	in	ADP
easat-10839	57	15	which	which	PRON
easat-10839	57	16	knowledge	knowledge	NOUN
easat-10839	57	17	obtained	obtain	VERB
easat-10839	57	18	through	through	ADP
easat-10839	57	19	one	one	NUM
easat-10839	57	20	task	task	NOUN
easat-10839	57	21	or	or	CCONJ
easat-10839	57	22	dataset	dataset	NOUN
easat-10839	57	23	is	be	AUX
easat-10839	57	24	reused	reuse	VERB
easat-10839	57	25	to	to	PART
easat-10839	57	26	enhance	enhance	VERB
easat-10839	57	27	model	model	NOUN
easat-10839	57	28	performance	performance	NOUN
easat-10839	57	29	on	on	ADP
easat-10839	57	30	another	another	DET
easat-10839	57	31	related	relate	VERB
easat-10839	57	32	task	task	NOUN
easat-10839	57	33	and/or	and/or	CCONJ
easat-10839	57	34	a	a	DET
easat-10839	57	35	different	different	ADJ
easat-10839	57	36	dataset	dataset	NOUN
easat-10839	58	1	[	[	X
easat-10839	58	2	17	17	NUM
easat-10839	58	3	]	]	PUNCT
easat-10839	58	4	.	.	PUNCT
easat-10839	59	1	251	251	NUM
easat-10839	59	2	edelweiss	edelweiss	PROPN
easat-10839	59	3	applied	apply	VERB
easat-10839	59	4	science	science	NOUN
easat-10839	59	5	and	and	CCONJ
easat-10839	59	6	technology	technology	NOUN
easat-10839	59	7	issn	issn	PROPN
easat-10839	59	8	:	:	PUNCT
easat-10839	59	9	2576	2576	NUM
easat-10839	59	10	-	-	SYM
easat-10839	59	11	8484	8484	NUM
easat-10839	59	12	vol	vol	NOUN
easat-10839	59	13	.	.	PROPN
easat-10839	60	1	9	9	NUM
easat-10839	60	2	,	,	PUNCT
easat-10839	60	3	no	no	INTJ
easat-10839	60	4	.	.	NOUN
easat-10839	60	5	11	11	NUM
easat-10839	60	6	:	:	PUNCT
easat-10839	60	7	249	249	NUM
easat-10839	60	8	-	-	SYM
easat-10839	60	9	261	261	NUM
easat-10839	60	10	,	,	PUNCT
easat-10839	60	11	2025	2025	NUM
easat-10839	60	12	doi	doi	NOUN
easat-10839	60	13	:	:	PUNCT
easat-10839	60	14	10.55214/2576	10.55214/2576	NUM
easat-10839	60	15	-	-	SYM
easat-10839	60	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	60	17	©	©	ADP
easat-10839	60	18	2025	2025	NUM
easat-10839	60	19	by	by	ADP
easat-10839	60	20	the	the	DET
easat-10839	60	21	authors	author	NOUN
easat-10839	60	22	;	;	PUNCT
easat-10839	60	23	licensee	licensee	PROPN
easat-10839	60	24	learning	learn	VERB
easat-10839	60	25	gate	gate	NOUN
easat-10839	60	26	figure	figure	NOUN
easat-10839	60	27	1	1	NUM
easat-10839	60	28	.	.	PUNCT
easat-10839	61	1	a	a	DET
easat-10839	61	2	simple	simple	ADJ
easat-10839	61	3	cnn	cnn	NOUN
easat-10839	61	4	architecture	architecture	NOUN
easat-10839	61	5	.	.	PUNCT
easat-10839	62	1	deep	deep	ADJ
easat-10839	62	2	transfer	transfer	NOUN
easat-10839	62	3	learning	learning	NOUN
easat-10839	62	4	is	be	AUX
easat-10839	62	5	a	a	DET
easat-10839	62	6	type	type	NOUN
easat-10839	62	7	of	of	ADP
easat-10839	62	8	transfer	transfer	NOUN
easat-10839	62	9	learning	learning	NOUN
easat-10839	62	10	used	use	VERB
easat-10839	62	11	for	for	ADP
easat-10839	62	12	training	train	VERB
easat-10839	62	13	deep	deep	ADJ
easat-10839	62	14	learning	learning	NOUN
easat-10839	62	15	models	model	NOUN
easat-10839	62	16	.	.	PUNCT
easat-10839	63	1	in	in	ADP
easat-10839	63	2	this	this	DET
easat-10839	63	3	paper	paper	NOUN
easat-10839	63	4	,	,	PUNCT
easat-10839	63	5	the	the	DET
easat-10839	63	6	architecture	architecture	NOUN
easat-10839	63	7	of	of	ADP
easat-10839	63	8	convolutional	convolutional	ADJ
easat-10839	63	9	neural	neural	ADJ
easat-10839	63	10	networks	network	NOUN
easat-10839	63	11	(	(	PUNCT
easat-10839	63	12	cnn	cnn	PROPN
easat-10839	63	13	)	)	PUNCT
easat-10839	63	14	will	will	AUX
easat-10839	63	15	be	be	AUX
easat-10839	63	16	used	use	VERB
easat-10839	63	17	to	to	PART
easat-10839	63	18	extract	extract	VERB
easat-10839	63	19	image	image	NOUN
easat-10839	63	20	features	feature	NOUN
easat-10839	63	21	of	of	ADP
easat-10839	63	22	colorectal	colorectal	ADJ
easat-10839	63	23	cancer	cancer	NOUN
easat-10839	63	24	patients	patient	NOUN
easat-10839	63	25	,	,	PUNCT
easat-10839	63	26	as	as	SCONJ
easat-10839	63	27	shown	show	VERB
easat-10839	63	28	in	in	ADP
easat-10839	63	29	figure	figure	NOUN
easat-10839	63	30	2	2	NUM
easat-10839	63	31	.	.	PUNCT
easat-10839	63	32	figure	figure	NOUN
easat-10839	63	33	2	2	NUM
easat-10839	63	34	.	.	PUNCT
easat-10839	63	35	deep	deep	ADJ
easat-10839	63	36	transfer	transfer	NOUN
easat-10839	63	37	learning	learning	NOUN
easat-10839	63	38	for	for	ADP
easat-10839	63	39	patients	patient	NOUN
easat-10839	63	40	'	'	PART
easat-10839	63	41	cancer	cancer	NOUN
easat-10839	63	42	image	image	NOUN
easat-10839	63	43	classification	classification	NOUN
easat-10839	63	44	.	.	PUNCT
easat-10839	64	1	transfer	transfer	NOUN
easat-10839	64	2	learning	learning	NOUN
easat-10839	64	3	methods	method	NOUN
easat-10839	64	4	in	in	ADP
easat-10839	64	5	deep	deep	ADJ
easat-10839	64	6	learning	learning	NOUN
easat-10839	64	7	aim	aim	VERB
easat-10839	64	8	to	to	PART
easat-10839	64	9	reduce	reduce	VERB
easat-10839	64	10	the	the	DET
easat-10839	64	11	cost	cost	NOUN
easat-10839	64	12	and	and	CCONJ
easat-10839	64	13	training	training	NOUN
easat-10839	64	14	time	time	NOUN
easat-10839	64	15	,	,	PUNCT
easat-10839	64	16	as	as	ADV
easat-10839	64	17	well	well	ADV
easat-10839	64	18	as	as	ADP
easat-10839	64	19	the	the	DET
easat-10839	64	20	necessity	necessity	NOUN
easat-10839	64	21	of	of	ADP
easat-10839	64	22	extensive	extensive	ADJ
easat-10839	64	23	training	training	NOUN
easat-10839	64	24	datasets	dataset	NOUN
easat-10839	64	25	,	,	PUNCT
easat-10839	64	26	which	which	PRON
easat-10839	64	27	can	can	AUX
easat-10839	64	28	be	be	AUX
easat-10839	64	29	difficult	difficult	ADJ
easat-10839	64	30	to	to	PART
easat-10839	64	31	obtain	obtain	VERB
easat-10839	64	32	in	in	ADP
easat-10839	64	33	some	some	DET
easat-10839	64	34	areas	area	NOUN
easat-10839	64	35	,	,	PUNCT
easat-10839	64	36	such	such	ADJ
easat-10839	64	37	as	as	ADP
easat-10839	64	38	colorectal	colorectal	ADJ
easat-10839	64	39	carcinoma	carcinoma	NOUN
easat-10839	64	40	slide	slide	NOUN
easat-10839	64	41	images	image	NOUN
easat-10839	64	42	.	.	PUNCT
easat-10839	65	1	in	in	ADP
easat-10839	65	2	this	this	DET
easat-10839	65	3	work	work	NOUN
easat-10839	65	4	,	,	PUNCT
easat-10839	65	5	five	five	NUM
easat-10839	65	6	cnn	cnn	NOUN
easat-10839	65	7	-	-	PUNCT
easat-10839	65	8	based	base	VERB
easat-10839	65	9	models	model	NOUN
easat-10839	65	10	,	,	PUNCT
easat-10839	65	11	resnet50	resnet50	NOUN
easat-10839	65	12	,	,	PUNCT
easat-10839	65	13	inception_v3	inception_v3	NOUN
easat-10839	65	14	,	,	PUNCT
easat-10839	65	15	densenet201	densenet201	PROPN
easat-10839	65	16	,	,	PUNCT
easat-10839	65	17	efficientnet_b2	efficientnet_b2	PROPN
easat-10839	65	18	,	,	PUNCT
easat-10839	65	19	and	and	CCONJ
easat-10839	65	20	mobilenetv2	mobilenetv2	PROPN
easat-10839	65	21	,	,	PUNCT
easat-10839	65	22	will	will	AUX
easat-10839	65	23	be	be	AUX
easat-10839	65	24	explored	explore	VERB
easat-10839	65	25	and	and	CCONJ
easat-10839	65	26	their	their	PRON
easat-10839	65	27	performances	performance	NOUN
easat-10839	65	28	compared	compare	VERB
easat-10839	65	29	using	use	VERB
easat-10839	65	30	real	real	ADJ
easat-10839	65	31	252	252	NUM
easat-10839	65	32	edelweiss	edelweiss	PROPN
easat-10839	65	33	applied	apply	VERB
easat-10839	65	34	science	science	NOUN
easat-10839	65	35	and	and	CCONJ
easat-10839	65	36	technology	technology	NOUN
easat-10839	65	37	issn	issn	PROPN
easat-10839	65	38	:	:	PUNCT
easat-10839	65	39	2576	2576	NUM
easat-10839	65	40	-	-	SYM
easat-10839	65	41	8484	8484	NUM
easat-10839	65	42	vol	vol	NOUN
easat-10839	65	43	.	.	PROPN
easat-10839	66	1	9	9	NUM
easat-10839	66	2	,	,	PUNCT
easat-10839	66	3	no	no	INTJ
easat-10839	66	4	.	.	NOUN
easat-10839	66	5	11	11	NUM
easat-10839	66	6	:	:	PUNCT
easat-10839	66	7	249	249	NUM
easat-10839	66	8	-	-	SYM
easat-10839	66	9	261	261	NUM
easat-10839	66	10	,	,	PUNCT
easat-10839	66	11	2025	2025	NUM
easat-10839	66	12	doi	doi	NOUN
easat-10839	66	13	:	:	PUNCT
easat-10839	66	14	10.55214/2576	10.55214/2576	NUM
easat-10839	66	15	-	-	SYM
easat-10839	66	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	66	17	©	©	ADP
easat-10839	66	18	2025	2025	NUM
easat-10839	66	19	by	by	ADP
easat-10839	66	20	the	the	DET
easat-10839	66	21	authors	author	NOUN
easat-10839	66	22	;	;	PUNCT
easat-10839	66	23	licensee	licensee	PROPN
easat-10839	66	24	learning	learning	NOUN
easat-10839	66	25	gate	gate	VERB
easat-10839	66	26	colorectal	colorectal	ADJ
easat-10839	66	27	carcinoma	carcinoma	NOUN
easat-10839	66	28	image	image	NOUN
easat-10839	66	29	datasets	dataset	NOUN
easat-10839	66	30	.	.	PUNCT
easat-10839	67	1	the	the	DET
easat-10839	67	2	parameters	parameter	NOUN
easat-10839	67	3	of	of	ADP
easat-10839	67	4	the	the	DET
easat-10839	67	5	models	model	NOUN
easat-10839	67	6	will	will	AUX
easat-10839	67	7	be	be	AUX
easat-10839	67	8	optimized	optimize	VERB
easat-10839	67	9	using	use	VERB
easat-10839	67	10	the	the	DET
easat-10839	67	11	optuna	optuna	ADJ
easat-10839	67	12	algorithm	algorithm	NOUN
easat-10839	67	13	[	[	X
easat-10839	67	14	11	11	NUM
easat-10839	67	15	]	]	PUNCT
easat-10839	67	16	.	.	PUNCT
easat-10839	68	1	the	the	DET
easat-10839	68	2	transfer	transfer	NOUN
easat-10839	68	3	learning	learning	NOUN
easat-10839	68	4	usually	usually	ADV
easat-10839	68	5	uses	use	VERB
easat-10839	68	6	weights	weight	NOUN
easat-10839	68	7	from	from	ADP
easat-10839	68	8	the	the	DET
easat-10839	68	9	pretrained	pretraine	VERB
easat-10839	68	10	model	model	NOUN
easat-10839	68	11	on	on	ADP
easat-10839	68	12	the	the	DET
easat-10839	68	13	imagenet	imagenet	NOUN
easat-10839	68	14	data	data	NOUN
easat-10839	68	15	sets	set	VERB
easat-10839	68	16	[	[	X
easat-10839	68	17	10	10	NUM
easat-10839	68	18	,	,	PUNCT
easat-10839	68	19	15	15	NUM
easat-10839	68	20	]	]	PUNCT
easat-10839	68	21	.	.	PUNCT
easat-10839	69	1	3	3	X
easat-10839	69	2	.	.	X
easat-10839	69	3	hyperparameter	hyperparameter	NOUN
easat-10839	69	4	optimization	optimization	NOUN
easat-10839	69	5	(	(	PUNCT
easat-10839	69	6	hpo	hpo	PROPN
easat-10839	69	7	)	)	PUNCT
easat-10839	69	8	despite	despite	SCONJ
easat-10839	69	9	the	the	DET
easat-10839	69	10	achievements	achievement	NOUN
easat-10839	69	11	of	of	ADP
easat-10839	69	12	deep	deep	ADJ
easat-10839	69	13	learning	learning	NOUN
easat-10839	69	14	in	in	ADP
easat-10839	69	15	various	various	ADJ
easat-10839	69	16	applications	application	NOUN
easat-10839	69	17	,	,	PUNCT
easat-10839	69	18	the	the	DET
easat-10839	69	19	design	design	NOUN
easat-10839	69	20	and	and	CCONJ
easat-10839	69	21	training	training	NOUN
easat-10839	69	22	of	of	ADP
easat-10839	69	23	deep	deep	ADJ
easat-10839	69	24	learning	learning	NOUN
easat-10839	69	25	models	model	NOUN
easat-10839	69	26	remain	remain	VERB
easat-10839	69	27	challenging	challenging	ADJ
easat-10839	69	28	and	and	CCONJ
easat-10839	69	29	uncontrolled	uncontrolled	ADJ
easat-10839	69	30	processes	process	NOUN
easat-10839	69	31	that	that	PRON
easat-10839	69	32	are	be	AUX
easat-10839	69	33	often	often	ADV
easat-10839	69	34	associated	associate	VERB
easat-10839	69	35	with	with	ADP
easat-10839	69	36	uncertainty	uncertainty	NOUN
easat-10839	69	37	.	.	PUNCT
easat-10839	70	1	to	to	PART
easat-10839	70	2	reduce	reduce	VERB
easat-10839	70	3	the	the	DET
easat-10839	70	4	technical	technical	ADJ
easat-10839	70	5	barriers	barrier	NOUN
easat-10839	70	6	for	for	ADP
easat-10839	70	7	naive	naive	ADJ
easat-10839	70	8	users	user	NOUN
easat-10839	70	9	,	,	PUNCT
easat-10839	70	10	automated	automate	VERB
easat-10839	70	11	hyper	hyper	ADJ
easat-10839	70	12	-	-	ADJ
easat-10839	70	13	parameter	parameter	ADJ
easat-10839	70	14	optimization	optimization	NOUN
easat-10839	70	15	(	(	PUNCT
easat-10839	70	16	hpo	hpo	PROPN
easat-10839	70	17	)	)	PUNCT
easat-10839	70	18	has	have	AUX
easat-10839	70	19	become	become	VERB
easat-10839	70	20	a	a	DET
easat-10839	70	21	trending	trend	VERB
easat-10839	70	22	topic	topic	NOUN
easat-10839	70	23	in	in	ADP
easat-10839	70	24	both	both	CCONJ
easat-10839	70	25	academic	academic	ADJ
easat-10839	70	26	and	and	CCONJ
easat-10839	70	27	industrial	industrial	ADJ
easat-10839	70	28	sectors	sector	NOUN
easat-10839	70	29	.	.	PUNCT
easat-10839	71	1	currently	currently	ADV
easat-10839	71	2	,	,	PUNCT
easat-10839	71	3	there	there	PRON
easat-10839	71	4	are	be	VERB
easat-10839	71	5	four	four	NUM
easat-10839	71	6	main	main	ADJ
easat-10839	71	7	approaches	approach	NOUN
easat-10839	71	8	to	to	ADP
easat-10839	71	9	implementing	implement	VERB
easat-10839	71	10	hyper	hyper	ADJ
easat-10839	71	11	-	-	ADJ
easat-10839	71	12	parameter	parameter	NOUN
easat-10839	71	13	optimization	optimization	NOUN
easat-10839	71	14	,	,	PUNCT
easat-10839	71	15	including	include	VERB
easat-10839	71	16	[	[	X
easat-10839	71	17	18	18	NUM
easat-10839	71	18	]	]	NOUN
easat-10839	71	19	:	:	PUNCT
easat-10839	71	20	grid	grid	NOUN
easat-10839	71	21	search	search	NOUN
easat-10839	71	22	,	,	PUNCT
easat-10839	71	23	random	random	ADJ
easat-10839	71	24	search	search	NOUN
easat-10839	71	25	,	,	PUNCT
easat-10839	71	26	bayesian	bayesian	NOUN
easat-10839	71	27	optimization	optimization	NOUN
easat-10839	71	28	,	,	PUNCT
easat-10839	71	29	and	and	CCONJ
easat-10839	71	30	the	the	DET
easat-10839	71	31	optuna	optuna	ADJ
easat-10839	71	32	framework	framework	NOUN
easat-10839	71	33	.	.	PUNCT
easat-10839	72	1	the	the	DET
easat-10839	72	2	approaches	approach	NOUN
easat-10839	72	3	will	will	AUX
easat-10839	72	4	be	be	AUX
easat-10839	72	5	briefly	briefly	ADV
easat-10839	72	6	explored	explore	VERB
easat-10839	72	7	as	as	SCONJ
easat-10839	72	8	follows	follow	VERB
easat-10839	72	9	:	:	PUNCT
easat-10839	72	10	3.1	3.1	NUM
easat-10839	72	11	.	.	PUNCT
easat-10839	72	12	grid	grid	NOUN
easat-10839	72	13	search	search	NOUN
easat-10839	72	14	grid	grid	NOUN
easat-10839	72	15	search	search	NOUN
easat-10839	72	16	is	be	AUX
easat-10839	72	17	one	one	NUM
easat-10839	72	18	of	of	ADP
easat-10839	72	19	the	the	DET
easat-10839	72	20	most	most	ADV
easat-10839	72	21	widely	widely	ADV
easat-10839	72	22	implemented	implement	VERB
easat-10839	72	23	hyperparameter	hyperparameter	NOUN
easat-10839	72	24	optimization	optimization	NOUN
easat-10839	72	25	approaches	approach	NOUN
easat-10839	72	26	.	.	PUNCT
easat-10839	73	1	it	it	PRON
easat-10839	73	2	operates	operate	VERB
easat-10839	73	3	by	by	ADP
easat-10839	73	4	exhaustively	exhaustively	ADV
easat-10839	73	5	searching	search	VERB
easat-10839	73	6	through	through	ADP
easat-10839	73	7	all	all	DET
easat-10839	73	8	possible	possible	ADJ
easat-10839	73	9	combinations	combination	NOUN
easat-10839	73	10	of	of	ADP
easat-10839	73	11	hyperparameters	hyperparameter	NOUN
easat-10839	73	12	within	within	ADP
easat-10839	73	13	a	a	DET
easat-10839	73	14	specified	specified	ADJ
easat-10839	73	15	grid	grid	NOUN
easat-10839	73	16	.	.	PUNCT
easat-10839	74	1	this	this	DET
easat-10839	74	2	method	method	NOUN
easat-10839	74	3	guarantees	guarantee	VERB
easat-10839	74	4	that	that	SCONJ
easat-10839	74	5	every	every	DET
easat-10839	74	6	candidate	candidate	NOUN
easat-10839	74	7	combination	combination	NOUN
easat-10839	74	8	is	be	AUX
easat-10839	74	9	considered	consider	VERB
easat-10839	74	10	,	,	PUNCT
easat-10839	74	11	ensuring	ensure	VERB
easat-10839	74	12	that	that	SCONJ
easat-10839	74	13	the	the	DET
easat-10839	74	14	best	good	ADJ
easat-10839	74	15	set	set	NOUN
easat-10839	74	16	of	of	ADP
easat-10839	74	17	hyperparameters	hyperparameter	NOUN
easat-10839	74	18	within	within	ADP
easat-10839	74	19	the	the	DET
easat-10839	74	20	defined	define	VERB
easat-10839	74	21	grid	grid	NOUN
easat-10839	74	22	is	be	AUX
easat-10839	74	23	identified	identify	VERB
easat-10839	74	24	.	.	PUNCT
easat-10839	75	1	3.2	3.2	NUM
easat-10839	75	2	.	.	PUNCT
easat-10839	75	3	random	random	ADJ
easat-10839	75	4	search	search	NOUN
easat-10839	75	5	instead	instead	ADV
easat-10839	75	6	of	of	ADP
easat-10839	75	7	intensively	intensively	ADV
easat-10839	75	8	searching	search	VERB
easat-10839	75	9	through	through	ADP
easat-10839	75	10	every	every	DET
easat-10839	75	11	possible	possible	ADJ
easat-10839	75	12	combination	combination	NOUN
easat-10839	75	13	of	of	ADP
easat-10839	75	14	hyperparameters	hyperparameter	NOUN
easat-10839	75	15	,	,	PUNCT
easat-10839	75	16	random	random	ADJ
easat-10839	75	17	search	search	NOUN
easat-10839	75	18	collects	collect	VERB
easat-10839	75	19	a	a	DET
easat-10839	75	20	fixed	fix	VERB
easat-10839	75	21	number	number	NOUN
easat-10839	75	22	of	of	ADP
easat-10839	75	23	random	random	ADJ
easat-10839	75	24	combinations	combination	NOUN
easat-10839	75	25	from	from	ADP
easat-10839	75	26	the	the	DET
easat-10839	75	27	search	search	NOUN
easat-10839	75	28	space	space	NOUN
easat-10839	75	29	.	.	PUNCT
easat-10839	76	1	this	this	PRON
easat-10839	76	2	allows	allow	VERB
easat-10839	76	3	random	random	ADJ
easat-10839	76	4	search	search	NOUN
easat-10839	76	5	to	to	PART
easat-10839	76	6	explore	explore	VERB
easat-10839	76	7	the	the	DET
easat-10839	76	8	hyperparameter	hyperparameter	NOUN
easat-10839	76	9	space	space	NOUN
easat-10839	76	10	more	more	ADV
easat-10839	76	11	efficiently	efficiently	ADV
easat-10839	76	12	,	,	PUNCT
easat-10839	76	13	often	often	ADV
easat-10839	76	14	yielding	yield	VERB
easat-10839	76	15	good	good	ADJ
easat-10839	76	16	results	result	NOUN
easat-10839	76	17	with	with	ADP
easat-10839	76	18	fewer	few	ADJ
easat-10839	76	19	iterations	iteration	NOUN
easat-10839	76	20	.	.	PUNCT
easat-10839	77	1	3.3	3.3	NUM
easat-10839	77	2	.	.	PUNCT
easat-10839	78	1	bayes	bayes	PROPN
easat-10839	78	2	optimization	optimization	NOUN
easat-10839	78	3	bayesian	bayesian	NOUN
easat-10839	78	4	optimization	optimization	NOUN
easat-10839	78	5	is	be	AUX
easat-10839	78	6	an	an	DET
easat-10839	78	7	advanced	advanced	ADJ
easat-10839	78	8	and	and	CCONJ
easat-10839	78	9	efficient	efficient	ADJ
easat-10839	78	10	method	method	NOUN
easat-10839	78	11	that	that	PRON
easat-10839	78	12	determines	determine	VERB
easat-10839	78	13	the	the	DET
easat-10839	78	14	probabilistic	probabilistic	ADJ
easat-10839	78	15	relationship	relationship	NOUN
easat-10839	78	16	between	between	ADP
easat-10839	78	17	hyperparameters	hyperparameter	NOUN
easat-10839	78	18	and	and	CCONJ
easat-10839	78	19	the	the	DET
easat-10839	78	20	objective	objective	ADJ
easat-10839	78	21	function	function	NOUN
easat-10839	78	22	,	,	PUNCT
easat-10839	78	23	usually	usually	ADV
easat-10839	78	24	employing	employ	VERB
easat-10839	78	25	a	a	DET
easat-10839	78	26	gaussian	gaussian	ADJ
easat-10839	78	27	process	process	NOUN
easat-10839	78	28	(	(	PUNCT
easat-10839	78	29	gp	gp	NOUN
easat-10839	78	30	)	)	PUNCT
easat-10839	78	31	model	model	NOUN
easat-10839	78	32	.	.	PUNCT
easat-10839	79	1	the	the	DET
easat-10839	79	2	objective	objective	NOUN
easat-10839	79	3	is	be	AUX
easat-10839	79	4	to	to	PART
easat-10839	79	5	search	search	VERB
easat-10839	79	6	for	for	ADP
easat-10839	79	7	the	the	DET
easat-10839	79	8	optimal	optimal	ADJ
easat-10839	79	9	hyperparameters	hyperparameter	NOUN
easat-10839	79	10	by	by	ADP
easat-10839	79	11	selecting	select	VERB
easat-10839	79	12	the	the	DET
easat-10839	79	13	next	next	ADJ
easat-10839	79	14	set	set	NOUN
easat-10839	79	15	of	of	ADP
easat-10839	79	16	hyperparameters	hyperparameter	NOUN
easat-10839	79	17	to	to	PART
easat-10839	79	18	evaluate	evaluate	VERB
easat-10839	79	19	based	base	VERB
easat-10839	79	20	on	on	ADP
easat-10839	79	21	the	the	DET
easat-10839	79	22	results	result	NOUN
easat-10839	79	23	of	of	ADP
easat-10839	79	24	previous	previous	ADJ
easat-10839	79	25	evaluations	evaluation	NOUN
easat-10839	79	26	.	.	PUNCT
easat-10839	80	1	3.4	3.4	NUM
easat-10839	80	2	.	.	PUNCT
easat-10839	81	1	optuna	optuna	NOUN
easat-10839	81	2	:	:	PUNCT
easat-10839	81	3	a	a	DET
easat-10839	81	4	hyperparameter	hyperparameter	NOUN
easat-10839	81	5	optimization	optimization	NOUN
easat-10839	81	6	framework	framework	NOUN
easat-10839	81	7	more	more	ADV
easat-10839	81	8	recent	recent	ADJ
easat-10839	81	9	approaches	approach	NOUN
easat-10839	81	10	in	in	ADP
easat-10839	81	11	hyperparameter	hyperparameter	NOUN
easat-10839	81	12	optimization	optimization	NOUN
easat-10839	81	13	include	include	VERB
easat-10839	81	14	optuna	optuna	NOUN
easat-10839	81	15	,	,	PUNCT
easat-10839	81	16	which	which	PRON
easat-10839	81	17	is	be	AUX
easat-10839	81	18	defined	define	VERB
easat-10839	81	19	as	as	ADP
easat-10839	81	20	an	an	DET
easat-10839	81	21	automatic	automatic	ADJ
easat-10839	81	22	hyperparameter	hyperparameter	NOUN
easat-10839	81	23	optimization	optimization	NOUN
easat-10839	81	24	software	software	NOUN
easat-10839	81	25	framework	framework	NOUN
easat-10839	81	26	(	(	PUNCT
easat-10839	81	27	18	18	NUM
easat-10839	81	28	)	)	PUNCT
easat-10839	81	29	.	.	PUNCT
easat-10839	82	1	it	it	PRON
easat-10839	82	2	features	feature	VERB
easat-10839	82	3	an	an	DET
easat-10839	82	4	imperative	imperative	NOUN
easat-10839	82	5	,	,	PUNCT
easat-10839	82	6	define	define	NOUN
easat-10839	82	7	-	-	PUNCT
easat-10839	82	8	by	by	ADP
easat-10839	82	9	-	-	PUNCT
easat-10839	82	10	run	run	NOUN
easat-10839	82	11	style	style	NOUN
easat-10839	82	12	user	user	NOUN
easat-10839	82	13	application	application	NOUN
easat-10839	82	14	programming	programming	NOUN
easat-10839	82	15	interface	interface	NOUN
easat-10839	82	16	(	(	PUNCT
easat-10839	82	17	api	api	NOUN
easat-10839	82	18	)	)	PUNCT
easat-10839	82	19	.	.	PUNCT
easat-10839	83	1	the	the	DET
easat-10839	83	2	program	program	NOUN
easat-10839	83	3	written	write	VERB
easat-10839	83	4	with	with	ADP
easat-10839	83	5	optuna	optuna	ADJ
easat-10839	83	6	benefits	benefit	NOUN
easat-10839	83	7	from	from	ADP
easat-10839	83	8	high	high	ADJ
easat-10839	83	9	modularity	modularity	NOUN
easat-10839	83	10	,	,	PUNCT
easat-10839	83	11	and	and	CCONJ
easat-10839	83	12	the	the	DET
easat-10839	83	13	user	user	NOUN
easat-10839	83	14	can	can	AUX
easat-10839	83	15	dynamically	dynamically	ADV
easat-10839	83	16	develop	develop	VERB
easat-10839	83	17	the	the	DET
easat-10839	83	18	search	search	NOUN
easat-10839	83	19	spaces	space	NOUN
easat-10839	83	20	for	for	ADP
easat-10839	83	21	the	the	DET
easat-10839	83	22	hyperparameters	hyperparameter	NOUN
easat-10839	83	23	.	.	PUNCT
easat-10839	84	1	this	this	DET
easat-10839	84	2	paper	paper	NOUN
easat-10839	84	3	will	will	AUX
easat-10839	84	4	use	use	VERB
easat-10839	84	5	this	this	DET
easat-10839	84	6	approach	approach	NOUN
easat-10839	84	7	based	base	VERB
easat-10839	84	8	on	on	ADP
easat-10839	84	9	considerations	consideration	NOUN
easat-10839	84	10	of	of	ADP
easat-10839	84	11	flexibility	flexibility	NOUN
easat-10839	84	12	,	,	PUNCT
easat-10839	84	13	modularity	modularity	NOUN
easat-10839	84	14	,	,	PUNCT
easat-10839	84	15	and	and	CCONJ
easat-10839	84	16	ease	ease	NOUN
easat-10839	84	17	of	of	ADP
easat-10839	84	18	integration	integration	NOUN
easat-10839	84	19	with	with	ADP
easat-10839	84	20	transfer	transfer	NOUN
easat-10839	84	21	learning	learn	VERB
easat-10839	84	22	frameworks	framework	NOUN
easat-10839	84	23	[	[	X
easat-10839	84	24	11	11	NUM
easat-10839	84	25	,	,	PUNCT
easat-10839	84	26	18	18	NUM
easat-10839	84	27	,	,	PUNCT
easat-10839	84	28	19	19	NUM
easat-10839	84	29	]	]	PUNCT
easat-10839	84	30	.	.	PUNCT
easat-10839	85	1	4	4	X
easat-10839	85	2	.	.	X
easat-10839	85	3	prognostic	prognostic	ADJ
easat-10839	85	4	model	model	NOUN
easat-10839	85	5	prognostic	prognostic	ADJ
easat-10839	85	6	models	model	NOUN
easat-10839	85	7	are	be	AUX
easat-10839	85	8	defined	define	VERB
easat-10839	85	9	as	as	ADP
easat-10839	85	10	frameworks	framework	NOUN
easat-10839	85	11	that	that	PRON
easat-10839	85	12	use	use	VERB
easat-10839	85	13	clinical	clinical	ADJ
easat-10839	85	14	parameters	parameter	NOUN
easat-10839	85	15	,	,	PUNCT
easat-10839	85	16	such	such	ADJ
easat-10839	85	17	as	as	ADP
easat-10839	85	18	gender	gender	NOUN
easat-10839	85	19	,	,	PUNCT
easat-10839	85	20	gestational	gestational	ADJ
easat-10839	85	21	age	age	NOUN
easat-10839	85	22	,	,	PUNCT
easat-10839	85	23	and	and	CCONJ
easat-10839	85	24	stage	stage	NOUN
easat-10839	85	25	of	of	ADP
easat-10839	85	26	cancer	cancer	NOUN
easat-10839	85	27	,	,	PUNCT
easat-10839	85	28	to	to	PART
easat-10839	85	29	categorize	categorize	VERB
easat-10839	85	30	patients	patient	NOUN
easat-10839	85	31	into	into	ADP
easat-10839	85	32	different	different	ADJ
easat-10839	85	33	prognostic	prognostic	ADJ
easat-10839	85	34	categories	category	NOUN
easat-10839	85	35	.	.	PUNCT
easat-10839	86	1	it	it	PRON
easat-10839	86	2	would	would	AUX
easat-10839	86	3	be	be	AUX
easat-10839	86	4	useful	useful	ADJ
easat-10839	86	5	in	in	ADP
easat-10839	86	6	aiding	aid	VERB
easat-10839	86	7	decision	decision	NOUN
easat-10839	86	8	-	-	PUNCT
easat-10839	86	9	making	making	NOUN
easat-10839	86	10	regarding	regard	VERB
easat-10839	86	11	the	the	DET
easat-10839	86	12	level	level	NOUN
easat-10839	86	13	of	of	ADP
easat-10839	86	14	care	care	NOUN
easat-10839	86	15	,	,	PUNCT
easat-10839	86	16	especially	especially	ADV
easat-10839	86	17	in	in	ADP
easat-10839	86	18	contexts	context	NOUN
easat-10839	86	19	like	like	ADP
easat-10839	86	20	colorectal	colorectal	ADJ
easat-10839	86	21	cancer	cancer	NOUN
easat-10839	86	22	.	.	PUNCT
easat-10839	87	1	these	these	DET
easat-10839	87	2	models	model	NOUN
easat-10839	87	3	determine	determine	VERB
easat-10839	87	4	the	the	DET
easat-10839	87	5	probability	probability	NOUN
easat-10839	87	6	of	of	ADP
easat-10839	87	7	acceptable	acceptable	ADJ
easat-10839	87	8	outcomes	outcome	NOUN
easat-10839	87	9	,	,	PUNCT
easat-10839	87	10	highlighting	highlight	VERB
easat-10839	87	11	the	the	DET
easat-10839	87	12	importance	importance	NOUN
easat-10839	87	13	of	of	ADP
easat-10839	87	14	evaluating	evaluate	VERB
easat-10839	87	15	new	new	ADJ
easat-10839	87	16	models	model	NOUN
easat-10839	87	17	against	against	ADP
easat-10839	87	18	existing	exist	VERB
easat-10839	87	19	ones	one	NOUN
easat-10839	87	20	.	.	PUNCT
easat-10839	88	1	in	in	ADP
easat-10839	88	2	this	this	DET
easat-10839	88	3	paper	paper	NOUN
easat-10839	88	4	,	,	PUNCT
easat-10839	88	5	to	to	PART
easat-10839	88	6	determine	determine	VERB
easat-10839	88	7	the	the	DET
easat-10839	88	8	tumor	tumor	NOUN
easat-10839	88	9	-	-	PUNCT
easat-10839	88	10	stroma	stroma	NOUN
easat-10839	88	11	ratio	ratio	NOUN
easat-10839	88	12	as	as	ADP
easat-10839	88	13	a	a	DET
easat-10839	88	14	prognostic	prognostic	ADJ
easat-10839	88	15	factor	factor	NOUN
easat-10839	88	16	in	in	ADP
easat-10839	88	17	colorectal	colorectal	ADJ
easat-10839	88	18	cancer	cancer	NOUN
easat-10839	88	19	,	,	PUNCT
easat-10839	88	20	it	it	PRON
easat-10839	88	21	will	will	AUX
easat-10839	88	22	be	be	AUX
easat-10839	88	23	included	include	VERB
easat-10839	88	24	in	in	ADP
easat-10839	88	25	the	the	DET
easat-10839	88	26	prognostic	prognostic	ADJ
easat-10839	88	27	model	model	NOUN
easat-10839	88	28	,	,	PUNCT
easat-10839	88	29	especially	especially	ADV
easat-10839	88	30	in	in	ADP
easat-10839	88	31	the	the	DET
easat-10839	88	32	cox	cox	PROPN
easat-10839	88	33	proportional	proportional	ADJ
easat-10839	88	34	-	-	PUNCT
easat-10839	88	35	hazard	hazard	NOUN
easat-10839	88	36	model	model	NOUN
easat-10839	88	37	[	[	X
easat-10839	88	38	10	10	NUM
easat-10839	88	39	]	]	PUNCT
easat-10839	88	40	.	.	PUNCT
easat-10839	89	1	4.1	4.1	NUM
easat-10839	89	2	.	.	PUNCT
easat-10839	90	1	cox	cox	PROPN
easat-10839	90	2	proportional	proportional	ADJ
easat-10839	90	3	-	-	PUNCT
easat-10839	90	4	hazards	hazard	NOUN
easat-10839	90	5	model	model	NOUN
easat-10839	90	6	the	the	DET
easat-10839	90	7	cox	cox	PROPN
easat-10839	90	8	proportional	proportional	PROPN
easat-10839	90	9	-	-	PUNCT
easat-10839	90	10	hazards	hazard	NOUN
easat-10839	90	11	model	model	NOUN
easat-10839	90	12	is	be	AUX
easat-10839	90	13	essentially	essentially	ADV
easat-10839	90	14	a	a	DET
easat-10839	90	15	regression	regression	NOUN
easat-10839	90	16	model	model	NOUN
easat-10839	90	17	commonly	commonly	ADV
easat-10839	90	18	used	use	VERB
easat-10839	90	19	in	in	ADP
easat-10839	90	20	medical	medical	ADJ
easat-10839	90	21	research	research	NOUN
easat-10839	90	22	to	to	PART
easat-10839	90	23	determine	determine	VERB
easat-10839	90	24	the	the	DET
easat-10839	90	25	association	association	NOUN
easat-10839	90	26	between	between	ADP
easat-10839	90	27	patients	patient	NOUN
easat-10839	90	28	'	'	PART
easat-10839	90	29	survival	survival	NOUN
easat-10839	90	30	time	time	NOUN
easat-10839	90	31	and	and	CCONJ
easat-10839	90	32	one	one	NUM
easat-10839	90	33	or	or	CCONJ
easat-10839	90	34	more	more	ADJ
easat-10839	90	35	prognostic	prognostic	ADJ
easat-10839	90	36	factors	factor	NOUN
easat-10839	90	37	,	,	PUNCT
easat-10839	90	38	253	253	NUM
easat-10839	90	39	edelweiss	edelweiss	PROPN
easat-10839	90	40	applied	apply	VERB
easat-10839	90	41	science	science	NOUN
easat-10839	90	42	and	and	CCONJ
easat-10839	90	43	technology	technology	NOUN
easat-10839	90	44	issn	issn	PROPN
easat-10839	90	45	:	:	PUNCT
easat-10839	90	46	2576	2576	NUM
easat-10839	90	47	-	-	SYM
easat-10839	90	48	8484	8484	NUM
easat-10839	90	49	vol	vol	NOUN
easat-10839	90	50	.	.	PROPN
easat-10839	91	1	9	9	NUM
easat-10839	91	2	,	,	PUNCT
easat-10839	91	3	no	no	INTJ
easat-10839	91	4	.	.	NOUN
easat-10839	91	5	11	11	NUM
easat-10839	91	6	:	:	PUNCT
easat-10839	91	7	249	249	NUM
easat-10839	91	8	-	-	SYM
easat-10839	91	9	261	261	NUM
easat-10839	91	10	,	,	PUNCT
easat-10839	91	11	2025	2025	NUM
easat-10839	91	12	doi	doi	NOUN
easat-10839	91	13	:	:	PUNCT
easat-10839	91	14	10.55214/2576	10.55214/2576	NUM
easat-10839	91	15	-	-	SYM
easat-10839	91	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	91	17	©	©	ADP
easat-10839	91	18	2025	2025	NUM
easat-10839	91	19	by	by	ADP
easat-10839	91	20	the	the	DET
easat-10839	91	21	authors	author	NOUN
easat-10839	91	22	;	;	PUNCT
easat-10839	91	23	licensee	licensee	PROPN
easat-10839	91	24	learning	learning	NOUN
easat-10839	91	25	gate	gate	NOUN
easat-10839	91	26	such	such	ADJ
easat-10839	91	27	as	as	ADP
easat-10839	91	28	age	age	NOUN
easat-10839	91	29	,	,	PUNCT
easat-10839	91	30	gender	gender	NOUN
easat-10839	91	31	,	,	PUNCT
easat-10839	91	32	m	m	NOUN
easat-10839	91	33	-	-	NOUN
easat-10839	91	34	stage	stage	NOUN
easat-10839	91	35	,	,	PUNCT
easat-10839	91	36	and	and	CCONJ
easat-10839	91	37	t	t	NOUN
easat-10839	91	38	-	-	PUNCT
easat-10839	91	39	stage	stage	NOUN
easat-10839	91	40	in	in	ADP
easat-10839	91	41	colorectal	colorectal	ADJ
easat-10839	91	42	cancer	cancer	NOUN
easat-10839	92	1	[	[	X
easat-10839	92	2	5	5	NUM
easat-10839	92	3	,	,	PUNCT
easat-10839	92	4	10	10	NUM
easat-10839	92	5	,	,	PUNCT
easat-10839	92	6	15	15	NUM
easat-10839	92	7	]	]	PUNCT
easat-10839	92	8	.	.	PUNCT
easat-10839	93	1	in	in	ADP
easat-10839	93	2	this	this	DET
easat-10839	93	3	paper	paper	NOUN
easat-10839	93	4	,	,	PUNCT
easat-10839	93	5	the	the	DET
easat-10839	93	6	tumor	tumor	NOUN
easat-10839	93	7	-	-	PUNCT
easat-10839	93	8	stroma	stroma	NOUN
easat-10839	93	9	ratio	ratio	NOUN
easat-10839	93	10	(	(	PUNCT
easat-10839	93	11	tsr	tsr	PROPN
easat-10839	93	12	)	)	PUNCT
easat-10839	93	13	will	will	AUX
easat-10839	93	14	be	be	AUX
easat-10839	93	15	included	include	VERB
easat-10839	93	16	as	as	ADP
easat-10839	93	17	a	a	DET
easat-10839	93	18	new	new	ADJ
easat-10839	93	19	prognostic	prognostic	ADJ
easat-10839	93	20	factor	factor	NOUN
easat-10839	93	21	in	in	ADP
easat-10839	93	22	colorectal	colorectal	ADJ
easat-10839	93	23	cancer	cancer	NOUN
easat-10839	93	24	.	.	PUNCT
easat-10839	94	1	the	the	DET
easat-10839	94	2	importance	importance	NOUN
easat-10839	94	3	of	of	ADP
easat-10839	94	4	tsr	tsr	PROPN
easat-10839	94	5	can	can	AUX
easat-10839	94	6	be	be	AUX
easat-10839	94	7	determined	determine	VERB
easat-10839	94	8	from	from	ADP
easat-10839	94	9	the	the	DET
easat-10839	94	10	significance	significance	NOUN
easat-10839	94	11	of	of	ADP
easat-10839	94	12	the	the	DET
easat-10839	94	13	coefficients	coefficient	NOUN
easat-10839	94	14	of	of	ADP
easat-10839	94	15	the	the	DET
easat-10839	94	16	model	model	NOUN
easat-10839	94	17	.	.	PUNCT
easat-10839	95	1	4.2	4.2	NUM
easat-10839	95	2	.	.	PUNCT
easat-10839	96	1	kaplan	kaplan	PROPN
easat-10839	96	2	-	-	PUNCT
easat-10839	96	3	meier	meier	PROPN
easat-10839	96	4	survival	survival	PROPN
easat-10839	96	5	analysis	analysis	VERB
easat-10839	96	6	kaplan	kaplan	PROPN
easat-10839	96	7	-	-	PUNCT
easat-10839	96	8	meier	meier	PROPN
easat-10839	96	9	survival	survival	NOUN
easat-10839	96	10	analysis	analysis	NOUN
easat-10839	96	11	is	be	AUX
easat-10839	96	12	a	a	DET
easat-10839	96	13	statistical	statistical	ADJ
easat-10839	96	14	method	method	NOUN
easat-10839	96	15	for	for	ADP
easat-10839	96	16	estimating	estimate	VERB
easat-10839	96	17	survival	survival	NOUN
easat-10839	96	18	predictions	prediction	NOUN
easat-10839	96	19	from	from	ADP
easat-10839	96	20	lifetime	lifetime	NOUN
easat-10839	96	21	patient	patient	NOUN
easat-10839	96	22	data	datum	NOUN
easat-10839	96	23	and	and	CCONJ
easat-10839	96	24	is	be	AUX
easat-10839	96	25	represented	represent	VERB
easat-10839	96	26	by	by	ADP
easat-10839	96	27	a	a	DET
easat-10839	96	28	stepwise	stepwise	NOUN
easat-10839	96	29	decreasing	decrease	VERB
easat-10839	96	30	curve	curve	NOUN
easat-10839	96	31	,	,	PUNCT
easat-10839	96	32	plotting	plot	VERB
easat-10839	96	33	survival	survival	NOUN
easat-10839	96	34	probability	probability	NOUN
easat-10839	96	35	on	on	ADP
easat-10839	96	36	the	the	DET
easat-10839	96	37	y	y	NOUN
easat-10839	96	38	-	-	PUNCT
easat-10839	96	39	axis	axis	NOUN
easat-10839	96	40	against	against	ADP
easat-10839	96	41	time	time	NOUN
easat-10839	96	42	on	on	ADP
easat-10839	96	43	the	the	DET
easat-10839	96	44	x	x	NOUN
easat-10839	96	45	-	-	NOUN
easat-10839	96	46	axis	axis	ADJ
easat-10839	96	47	.	.	PUNCT
easat-10839	97	1	in	in	ADP
easat-10839	97	2	this	this	DET
easat-10839	97	3	paper	paper	NOUN
easat-10839	97	4	,	,	PUNCT
easat-10839	97	5	the	the	DET
easat-10839	97	6	high	high	ADJ
easat-10839	97	7	tumor	tumor	NOUN
easat-10839	97	8	-	-	PUNCT
easat-10839	97	9	stroma	stroma	NOUN
easat-10839	97	10	ratio	ratio	NOUN
easat-10839	97	11	(	(	PUNCT
easat-10839	97	12	high	high	ADJ
easat-10839	97	13	-	-	PUNCT
easat-10839	97	14	tsr	tsr	NOUN
easat-10839	97	15	)	)	PUNCT
easat-10839	97	16	and	and	CCONJ
easat-10839	97	17	low	low	ADJ
easat-10839	97	18	tumor	tumor	NOUN
easat-10839	97	19	-	-	PUNCT
easat-10839	97	20	stroma	stroma	NOUN
easat-10839	97	21	ratio	ratio	NOUN
easat-10839	97	22	(	(	PUNCT
easat-10839	97	23	low	low	ADJ
easat-10839	97	24	-	-	PUNCT
easat-10839	97	25	tsr	tsr	NOUN
easat-10839	97	26	)	)	PUNCT
easat-10839	97	27	will	will	AUX
easat-10839	97	28	be	be	AUX
easat-10839	97	29	shown	show	VERB
easat-10839	97	30	using	use	VERB
easat-10839	97	31	kaplan	kaplan	PROPN
easat-10839	97	32	-	-	PUNCT
easat-10839	97	33	meier	meier	PROPN
easat-10839	97	34	survival	survival	PROPN
easat-10839	97	35	analysis	analysis	NOUN
easat-10839	97	36	.	.	PUNCT
easat-10839	98	1	tumors	tumor	NOUN
easat-10839	98	2	with	with	ADP
easat-10839	98	3	a	a	DET
easat-10839	98	4	high	high	ADJ
easat-10839	98	5	proportion	proportion	NOUN
easat-10839	98	6	of	of	ADP
easat-10839	98	7	stroma	stroma	NOUN
easat-10839	98	8	(	(	PUNCT
easat-10839	98	9	often	often	ADV
easat-10839	98	10	defined	define	VERB
easat-10839	98	11	as	as	ADP
easat-10839	98	12	>	>	X
easat-10839	98	13	50	50	NUM
easat-10839	98	14	%	%	NOUN
easat-10839	98	15	)	)	PUNCT
easat-10839	98	16	are	be	AUX
easat-10839	98	17	considered	consider	VERB
easat-10839	98	18	"	"	PUNCT
easat-10839	98	19	high	high	ADJ
easat-10839	98	20	-	-	PUNCT
easat-10839	98	21	tsr	tsr	NOUN
easat-10839	98	22	,	,	PUNCT
easat-10839	98	23	"	"	PUNCT
easat-10839	98	24	while	while	SCONJ
easat-10839	98	25	those	those	PRON
easat-10839	98	26	with	with	ADP
easat-10839	98	27	abundant	abundant	ADJ
easat-10839	98	28	carcinoma	carcinoma	NOUN
easat-10839	98	29	tissue	tissue	NOUN
easat-10839	98	30	(	(	PUNCT
easat-10839	98	31	≤50	≤50	NOUN
easat-10839	98	32	%	%	NOUN
easat-10839	98	33	stroma	stroma	NOUN
easat-10839	98	34	)	)	PUNCT
easat-10839	98	35	are	be	AUX
easat-10839	98	36	"	"	PUNCT
easat-10839	98	37	low	low	ADJ
easat-10839	98	38	-	-	PUNCT
easat-10839	98	39	tsr	tsr	NOUN
easat-10839	98	40	.	.	PUNCT
easat-10839	98	41	"	"	PUNCT
easat-10839	99	1	the	the	DET
easat-10839	99	2	high	high	ADJ
easat-10839	99	3	-	-	PUNCT
easat-10839	99	4	tsr	tsr	PROPN
easat-10839	99	5	is	be	AUX
easat-10839	99	6	generally	generally	ADV
easat-10839	99	7	associated	associate	VERB
easat-10839	99	8	with	with	ADP
easat-10839	99	9	a	a	DET
easat-10839	99	10	poorer	poor	ADJ
easat-10839	99	11	prognosis	prognosis	NOUN
easat-10839	99	12	,	,	PUNCT
easat-10839	99	13	shorter	short	ADJ
easat-10839	99	14	survival	survival	NOUN
easat-10839	99	15	,	,	PUNCT
easat-10839	99	16	and	and	CCONJ
easat-10839	99	17	increased	increase	VERB
easat-10839	99	18	risk	risk	NOUN
easat-10839	99	19	of	of	ADP
easat-10839	99	20	recurrence	recurrence	NOUN
easat-10839	99	21	and	and	CCONJ
easat-10839	99	22	metastasis	metastasis	NOUN
easat-10839	99	23	in	in	ADP
easat-10839	99	24	many	many	ADJ
easat-10839	99	25	cancers	cancer	NOUN
easat-10839	99	26	,	,	PUNCT
easat-10839	99	27	including	include	VERB
easat-10839	99	28	colorectal	colorectal	ADJ
easat-10839	99	29	cancer	cancer	NOUN
easat-10839	99	30	.	.	PUNCT
easat-10839	100	1	5	5	X
easat-10839	100	2	.	.	X
easat-10839	100	3	experimental	experimental	ADJ
easat-10839	100	4	settings	setting	NOUN
easat-10839	100	5	5.1	5.1	NUM
easat-10839	100	6	.	.	PUNCT
easat-10839	101	1	data	datum	NOUN
easat-10839	101	2	description	description	NOUN
easat-10839	101	3	the	the	DET
easat-10839	101	4	training	training	NOUN
easat-10839	101	5	and	and	CCONJ
easat-10839	101	6	test	test	NOUN
easat-10839	101	7	data	datum	NOUN
easat-10839	101	8	set	set	VERB
easat-10839	101	9	can	can	AUX
easat-10839	101	10	be	be	AUX
easat-10839	101	11	downloaded	download	VERB
easat-10839	101	12	in	in	ADP
easat-10839	101	13	the	the	DET
easat-10839	101	14	following	follow	VERB
easat-10839	101	15	publicly	publicly	ADV
easat-10839	101	16	open	open	ADJ
easat-10839	101	17	website	website	NOUN
easat-10839	101	18	[	[	X
easat-10839	101	19	15	15	NUM
easat-10839	101	20	]	]	X
easat-10839	101	21	:	:	PUNCT
easat-10839	101	22	https://zenodo.org/records/4024676	https://zenodo.org/records/4024676	NOUN
easat-10839	101	23	this	this	PRON
easat-10839	101	24	downloaded	download	VERB
easat-10839	101	25	colorectal	colorectal	ADJ
easat-10839	101	26	carcinoma	carcinoma	NOUN
easat-10839	101	27	data	datum	NOUN
easat-10839	101	28	set	set	VERB
easat-10839	101	29	consists	consist	NOUN
easat-10839	101	30	of	of	ADP
easat-10839	101	31	the	the	DET
easat-10839	101	32	training	training	NOUN
easat-10839	101	33	set	set	NOUN
easat-10839	101	34	used	use	VERB
easat-10839	101	35	to	to	PART
easat-10839	101	36	train	train	VERB
easat-10839	101	37	the	the	DET
easat-10839	101	38	cnn	cnn	PROPN
easat-10839	101	39	model	model	NOUN
easat-10839	101	40	,	,	PUNCT
easat-10839	101	41	including	include	VERB
easat-10839	101	42	283,100	283,100	NUM
easat-10839	101	43	image	image	NOUN
easat-10839	101	44	patches	patch	NOUN
easat-10839	101	45	,	,	PUNCT
easat-10839	101	46	including	include	VERB
easat-10839	101	47	he	he	PRON
easat-10839	101	48	slides	slide	VERB
easat-10839	101	49	of	of	ADP
easat-10839	101	50	crc	crc	NOUN
easat-10839	101	51	tissue	tissue	NOUN
easat-10839	101	52	randomly	randomly	ADV
easat-10839	101	53	selected	select	VERB
easat-10839	101	54	from	from	ADP
easat-10839	101	55	those	those	PRON
easat-10839	101	56	retrieved	retrieve	VERB
easat-10839	101	57	from	from	ADP
easat-10839	101	58	the	the	DET
easat-10839	101	59	cancer	cancer	NOUN
easat-10839	101	60	genome	genome	NOUN
easat-10839	101	61	atlas	atlas	PROPN
easat-10839	101	62	.	.	PUNCT
easat-10839	102	1	two	two	NUM
easat-10839	102	2	independent	independent	ADJ
easat-10839	102	3	test	test	NOUN
easat-10839	102	4	sets	set	NOUN
easat-10839	102	5	(	(	PUNCT
easat-10839	102	6	test	test	NOUN
easat-10839	102	7	sets	set	VERB
easat-10839	102	8	1	1	NUM
easat-10839	102	9	and	and	CCONJ
easat-10839	102	10	2	2	NUM
easat-10839	102	11	)	)	PUNCT
easat-10839	102	12	were	be	AUX
easat-10839	102	13	used	use	VERB
easat-10839	102	14	to	to	PART
easat-10839	102	15	assess	assess	VERB
easat-10839	102	16	the	the	DET
easat-10839	102	17	classification	classification	NOUN
easat-10839	102	18	performance	performance	NOUN
easat-10839	102	19	of	of	ADP
easat-10839	102	20	the	the	DET
easat-10839	102	21	trained	train	VERB
easat-10839	102	22	cnn	cnn	PROPN
easat-10839	102	23	model	model	NOUN
easat-10839	102	24	.	.	PUNCT
easat-10839	103	1	non	non	ADJ
easat-10839	103	2	-	-	ADJ
easat-10839	103	3	overlapping	overlapping	ADJ
easat-10839	103	4	image	image	NOUN
easat-10839	103	5	patches	patch	NOUN
easat-10839	103	6	from	from	ADP
easat-10839	103	7	hematoxylin	hematoxylin	PROPN
easat-10839	103	8	&	&	CCONJ
easat-10839	103	9	eosin	eosin	PROPN
easat-10839	103	10	(	(	PUNCT
easat-10839	103	11	h&e	h&e	PROPN
easat-10839	103	12	)	)	PUNCT
easat-10839	103	13	stained	stain	VERB
easat-10839	103	14	histological	histological	ADJ
easat-10839	103	15	images	image	NOUN
easat-10839	103	16	of	of	ADP
easat-10839	103	17	human	human	ADJ
easat-10839	103	18	colorectal	colorectal	ADJ
easat-10839	103	19	cancer	cancer	NOUN
easat-10839	103	20	(	(	PUNCT
easat-10839	103	21	crc	crc	NOUN
easat-10839	103	22	)	)	PUNCT
easat-10839	103	23	and	and	CCONJ
easat-10839	103	24	normal	normal	ADJ
easat-10839	103	25	tissue	tissue	NOUN
easat-10839	103	26	were	be	AUX
easat-10839	103	27	included	include	VERB
easat-10839	103	28	[	[	X
easat-10839	103	29	20	20	NUM
easat-10839	103	30	]	]	PUNCT
easat-10839	103	31	.	.	PUNCT
easat-10839	104	1	there	there	PRON
easat-10839	104	2	are	be	VERB
easat-10839	104	3	9	9	NUM
easat-10839	104	4	tissue	tissue	NOUN
easat-10839	104	5	classes	class	NOUN
easat-10839	104	6	:	:	PUNCT
easat-10839	104	7	adipose	adipose	X
easat-10839	104	8	(	(	PUNCT
easat-10839	104	9	adi	adi	PROPN
easat-10839	104	10	)	)	PUNCT
easat-10839	104	11	,	,	PUNCT
easat-10839	104	12	background	background	NOUN
easat-10839	104	13	(	(	PUNCT
easat-10839	104	14	back	back	ADV
easat-10839	104	15	)	)	PUNCT
easat-10839	104	16	,	,	PUNCT
easat-10839	104	17	debris	debris	NOUN
easat-10839	104	18	(	(	PUNCT
easat-10839	104	19	deb	deb	PROPN
easat-10839	104	20	)	)	PUNCT
easat-10839	104	21	,	,	PUNCT
easat-10839	104	22	lymphocytes	lymphocyte	VERB
easat-10839	104	23	(	(	PUNCT
easat-10839	104	24	lym	lym	PROPN
easat-10839	104	25	)	)	PUNCT
easat-10839	104	26	,	,	PUNCT
easat-10839	104	27	mucus	mucus	NOUN
easat-10839	104	28	(	(	PUNCT
easat-10839	104	29	muc	muc	X
easat-10839	104	30	)	)	PUNCT
easat-10839	104	31	,	,	PUNCT
easat-10839	104	32	smooth	smooth	ADJ
easat-10839	104	33	muscle	muscle	NOUN
easat-10839	104	34	(	(	PUNCT
easat-10839	104	35	mus	mus	PROPN
easat-10839	104	36	)	)	PUNCT
easat-10839	104	37	,	,	PUNCT
easat-10839	104	38	normal	normal	ADJ
easat-10839	104	39	colon	colon	NOUN
easat-10839	104	40	mucosa	mucosa	NOUN
easat-10839	104	41	(	(	PUNCT
easat-10839	104	42	norm	norm	NOUN
easat-10839	104	43	)	)	PUNCT
easat-10839	104	44	,	,	PUNCT
easat-10839	104	45	cancerassociated	cancerassociate	VERB
easat-10839	104	46	stroma	stroma	NOUN
easat-10839	104	47	(	(	PUNCT
easat-10839	104	48	str	str	NOUN
easat-10839	104	49	)	)	PUNCT
easat-10839	104	50	,	,	PUNCT
easat-10839	104	51	colorectal	colorectal	ADJ
easat-10839	104	52	adenocarcinoma	adenocarcinoma	NOUN
easat-10839	104	53	epithelium	epithelium	NOUN
easat-10839	104	54	(	(	PUNCT
easat-10839	104	55	tum	tum	NOUN
easat-10839	104	56	)	)	PUNCT
easat-10839	104	57	.	.	PUNCT
easat-10839	105	1	lym	lym	PROPN
easat-10839	105	2	,	,	PUNCT
easat-10839	105	3	str	str	NOUN
easat-10839	105	4	,	,	PUNCT
easat-10839	105	5	and	and	CCONJ
easat-10839	105	6	tum	tum	PROPN
easat-10839	105	7	classes	class	NOUN
easat-10839	105	8	have	have	VERB
easat-10839	105	9	important	important	ADJ
easat-10839	105	10	roles	role	NOUN
easat-10839	105	11	in	in	ADP
easat-10839	105	12	colorectal	colorectal	ADJ
easat-10839	105	13	carcinoma	carcinoma	NOUN
easat-10839	105	14	.	.	PUNCT
easat-10839	106	1	especially	especially	ADV
easat-10839	106	2	,	,	PUNCT
easat-10839	106	3	tum	tum	PROPN
easat-10839	106	4	and	and	CCONJ
easat-10839	106	5	str	str	NOUN
easat-10839	106	6	are	be	AUX
easat-10839	106	7	used	use	VERB
easat-10839	106	8	to	to	PART
easat-10839	106	9	determine	determine	VERB
easat-10839	106	10	the	the	DET
easat-10839	106	11	tumor	tumor	NOUN
easat-10839	106	12	-	-	PUNCT
easat-10839	106	13	stroma	stroma	NOUN
easat-10839	106	14	ratio	ratio	NOUN
easat-10839	106	15	(	(	PUNCT
easat-10839	106	16	tsr	tsr	PROPN
easat-10839	106	17	)	)	PUNCT
easat-10839	106	18	.	.	PUNCT
easat-10839	107	1	5.2	5.2	NUM
easat-10839	107	2	.	.	PUNCT
easat-10839	107	3	optimized	optimize	VERB
easat-10839	107	4	deep	deep	ADJ
easat-10839	107	5	transfer	transfer	NOUN
easat-10839	107	6	learning	learning	NOUN
easat-10839	107	7	for	for	ADP
easat-10839	107	8	tumor	tumor	NOUN
easat-10839	107	9	-	-	PUNCT
easat-10839	107	10	stroma	stroma	NOUN
easat-10839	107	11	ratio	ratio	NOUN
easat-10839	107	12	prediction	prediction	NOUN
easat-10839	107	13	five	five	NUM
easat-10839	107	14	base	base	NOUN
easat-10839	107	15	cnn	cnn	PROPN
easat-10839	107	16	models	model	NOUN
easat-10839	107	17	,	,	PUNCT
easat-10839	107	18	including	include	VERB
easat-10839	107	19	resnet18	resnet18	NOUN
easat-10839	107	20	,	,	PUNCT
easat-10839	107	21	densenet201	densenet201	PROPN
easat-10839	107	22	,	,	PUNCT
easat-10839	107	23	inception_v3	inception_v3	NOUN
easat-10839	107	24	,	,	PUNCT
easat-10839	107	25	efficientb2	efficientb2	NOUN
easat-10839	107	26	,	,	PUNCT
easat-10839	107	27	and	and	CCONJ
easat-10839	107	28	mobilenetv2	mobilenetv2	PROPN
easat-10839	107	29	,	,	PUNCT
easat-10839	107	30	were	be	AUX
easat-10839	107	31	trained	train	VERB
easat-10839	107	32	on	on	ADP
easat-10839	107	33	training	training	NOUN
easat-10839	107	34	data	datum	NOUN
easat-10839	107	35	sets	set	NOUN
easat-10839	107	36	[	[	X
easat-10839	107	37	19	19	NUM
easat-10839	107	38	,	,	PUNCT
easat-10839	107	39	21	21	NUM
easat-10839	107	40	]	]	PUNCT
easat-10839	107	41	.	.	PUNCT
easat-10839	108	1	the	the	DET
easat-10839	108	2	training	training	NOUN
easat-10839	108	3	process	process	NOUN
easat-10839	108	4	used	use	VERB
easat-10839	108	5	optuna	optuna	PROPN
easat-10839	108	6	hyperparameter	hyperparameter	NOUN
easat-10839	108	7	optimization	optimization	NOUN
easat-10839	108	8	20	20	NUM
easat-10839	108	9	epochs	epoch	NOUN
easat-10839	108	10	and	and	CCONJ
easat-10839	108	11	3	3	NUM
easat-10839	108	12	trials	trial	NOUN
easat-10839	108	13	.	.	PUNCT
easat-10839	109	1	having	having	AUX
easat-10839	109	2	determined	determine	VERB
easat-10839	109	3	the	the	DET
easat-10839	109	4	best	good	ADJ
easat-10839	109	5	cnn	cnn	NOUN
easat-10839	109	6	model	model	NOUN
easat-10839	109	7	with	with	ADP
easat-10839	109	8	optuna	optuna	PROPN
easat-10839	109	9	hyperparameter	hyperparameter	PROPN
easat-10839	109	10	optimization	optimization	NOUN
easat-10839	109	11	,	,	PUNCT
easat-10839	109	12	the	the	DET
easat-10839	109	13	next	next	ADJ
easat-10839	109	14	step	step	NOUN
easat-10839	109	15	is	be	AUX
easat-10839	109	16	to	to	PART
easat-10839	109	17	apply	apply	VERB
easat-10839	109	18	the	the	DET
easat-10839	109	19	model	model	NOUN
easat-10839	109	20	to	to	PART
easat-10839	109	21	predict	predict	VERB
easat-10839	109	22	on	on	ADP
easat-10839	109	23	the	the	DET
easat-10839	109	24	whole	whole	ADJ
easat-10839	109	25	slide	slide	NOUN
easat-10839	109	26	images	image	NOUN
easat-10839	109	27	dataset	dataset	VERB
easat-10839	109	28	for	for	ADP
easat-10839	109	29	each	each	DET
easat-10839	109	30	colorectal	colorectal	ADJ
easat-10839	109	31	cancer	cancer	NOUN
easat-10839	109	32	patient	patient	NOUN
easat-10839	109	33	.	.	PUNCT
easat-10839	110	1	the	the	DET
easat-10839	110	2	outcome	outcome	NOUN
easat-10839	110	3	of	of	ADP
easat-10839	110	4	the	the	DET
easat-10839	110	5	prediction	prediction	NOUN
easat-10839	110	6	will	will	AUX
easat-10839	110	7	be	be	AUX
easat-10839	110	8	used	use	VERB
easat-10839	110	9	to	to	PART
easat-10839	110	10	calculate	calculate	VERB
easat-10839	110	11	the	the	DET
easat-10839	110	12	area	area	NOUN
easat-10839	110	13	of	of	ADP
easat-10839	110	14	tumor	tumor	NOUN
easat-10839	110	15	(	(	PUNCT
easat-10839	110	16	tum	tum	NOUN
easat-10839	110	17	)	)	PUNCT
easat-10839	110	18	and	and	CCONJ
easat-10839	110	19	stroma	stroma	NOUN
easat-10839	110	20	(	(	PUNCT
easat-10839	110	21	str	str	NOUN
easat-10839	110	22	)	)	PUNCT
easat-10839	110	23	.	.	PUNCT
easat-10839	111	1	finally	finally	ADV
easat-10839	111	2	,	,	PUNCT
easat-10839	111	3	the	the	DET
easat-10839	111	4	tumor	tumor	NOUN
easat-10839	111	5	-	-	PUNCT
easat-10839	111	6	stroma	stroma	NOUN
easat-10839	111	7	ratio	ratio	NOUN
easat-10839	111	8	in	in	ADP
easat-10839	111	9	colorectal	colorectal	ADJ
easat-10839	111	10	cancer	cancer	NOUN
easat-10839	111	11	can	can	AUX
easat-10839	111	12	be	be	AUX
easat-10839	111	13	predicted	predict	VERB
easat-10839	111	14	.	.	PUNCT
easat-10839	112	1	5.3	5.3	NUM
easat-10839	112	2	.	.	PUNCT
easat-10839	113	1	the	the	DET
easat-10839	113	2	evaluation	evaluation	NOUN
easat-10839	113	3	of	of	ADP
easat-10839	113	4	tumor	tumor	NOUN
easat-10839	113	5	-	-	PUNCT
easat-10839	113	6	stroma	stroma	NOUN
easat-10839	113	7	ratio	ratio	NOUN
easat-10839	113	8	(	(	PUNCT
easat-10839	113	9	tsr	tsr	PROPN
easat-10839	113	10	)	)	PUNCT
easat-10839	113	11	as	as	ADP
easat-10839	113	12	a	a	DET
easat-10839	113	13	prognosis	prognosis	NOUN
easat-10839	113	14	factor	factor	NOUN
easat-10839	113	15	in	in	ADP
easat-10839	113	16	colorectal	colorectal	ADJ
easat-10839	113	17	cancer	cancer	NOUN
easat-10839	113	18	the	the	DET
easat-10839	113	19	importance	importance	NOUN
easat-10839	113	20	of	of	ADP
easat-10839	113	21	tsr	tsr	PROPN
easat-10839	113	22	with	with	ADP
easat-10839	113	23	other	other	ADJ
easat-10839	113	24	clinical	clinical	ADJ
easat-10839	113	25	parameters	parameter	NOUN
easat-10839	113	26	,	,	PUNCT
easat-10839	113	27	such	such	ADJ
easat-10839	113	28	as	as	ADP
easat-10839	113	29	age	age	NOUN
easat-10839	113	30	,	,	PUNCT
easat-10839	113	31	gender	gender	NOUN
easat-10839	113	32	,	,	PUNCT
easat-10839	113	33	and	and	CCONJ
easat-10839	113	34	m	m	NOUN
easat-10839	113	35	-	-	NOUN
easat-10839	113	36	stage	stage	NOUN
easat-10839	113	37	as	as	SCONJ
easat-10839	113	38	prognostic	prognostic	ADJ
easat-10839	113	39	factors	factor	NOUN
easat-10839	113	40	in	in	ADP
easat-10839	113	41	colorectal	colorectal	ADJ
easat-10839	113	42	cancer	cancer	NOUN
easat-10839	113	43	and	and	CCONJ
easat-10839	113	44	others	other	NOUN
easat-10839	113	45	will	will	AUX
easat-10839	113	46	be	be	AUX
easat-10839	113	47	determined	determine	VERB
easat-10839	113	48	using	use	VERB
easat-10839	113	49	the	the	DET
easat-10839	113	50	cox	cox	PROPN
easat-10839	113	51	proportional	proportional	ADJ
easat-10839	113	52	-	-	PUNCT
easat-10839	113	53	hazards	hazard	NOUN
easat-10839	113	54	model	model	NOUN
easat-10839	113	55	.	.	PUNCT
easat-10839	114	1	then	then	ADV
easat-10839	114	2	,	,	PUNCT
easat-10839	114	3	patient	patient	ADJ
easat-10839	114	4	survival	survival	NOUN
easat-10839	114	5	prediction	prediction	NOUN
easat-10839	114	6	for	for	ADP
easat-10839	114	7	high	high	ADJ
easat-10839	114	8	-	-	PUNCT
easat-10839	114	9	tsr	tsr	NOUN
easat-10839	114	10	and	and	CCONJ
easat-10839	114	11	low	low	ADJ
easat-10839	114	12	-	-	PUNCT
easat-10839	114	13	tsr	tsr	NOUN
easat-10839	114	14	groups	group	NOUN
easat-10839	114	15	will	will	AUX
easat-10839	114	16	be	be	AUX
easat-10839	114	17	shown	show	VERB
easat-10839	114	18	by	by	ADP
easat-10839	114	19	the	the	DET
easat-10839	114	20	kaplan	kaplan	PROPN
easat-10839	114	21	-	-	PUNCT
easat-10839	114	22	meier	meier	PROPN
easat-10839	114	23	curve	curve	NOUN
easat-10839	114	24	.	.	PUNCT
easat-10839	115	1	overall	overall	ADJ
easat-10839	115	2	,	,	PUNCT
easat-10839	115	3	experimental	experimental	ADJ
easat-10839	115	4	settings	setting	NOUN
easat-10839	115	5	can	can	AUX
easat-10839	115	6	be	be	AUX
easat-10839	115	7	shown	show	VERB
easat-10839	115	8	in	in	ADP
easat-10839	115	9	the	the	DET
easat-10839	115	10	following	follow	VERB
easat-10839	115	11	figure	figure	NOUN
easat-10839	115	12	:	:	PUNCT
easat-10839	115	13	254	254	NUM
easat-10839	115	14	edelweiss	edelweiss	PROPN
easat-10839	115	15	applied	apply	VERB
easat-10839	115	16	science	science	NOUN
easat-10839	115	17	and	and	CCONJ
easat-10839	115	18	technology	technology	NOUN
easat-10839	115	19	issn	issn	PROPN
easat-10839	115	20	:	:	PUNCT
easat-10839	115	21	2576	2576	NUM
easat-10839	115	22	-	-	SYM
easat-10839	115	23	8484	8484	NUM
easat-10839	115	24	vol	vol	NOUN
easat-10839	115	25	.	.	PROPN
easat-10839	116	1	9	9	NUM
easat-10839	116	2	,	,	PUNCT
easat-10839	116	3	no	no	INTJ
easat-10839	116	4	.	.	NOUN
easat-10839	116	5	11	11	NUM
easat-10839	116	6	:	:	PUNCT
easat-10839	116	7	249	249	NUM
easat-10839	116	8	-	-	SYM
easat-10839	116	9	261	261	NUM
easat-10839	116	10	,	,	PUNCT
easat-10839	116	11	2025	2025	NUM
easat-10839	116	12	doi	doi	NOUN
easat-10839	116	13	:	:	PUNCT
easat-10839	116	14	10.55214/2576	10.55214/2576	NUM
easat-10839	116	15	-	-	SYM
easat-10839	116	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	116	17	©	©	ADP
easat-10839	116	18	2025	2025	NUM
easat-10839	116	19	by	by	ADP
easat-10839	116	20	the	the	DET
easat-10839	116	21	authors	author	NOUN
easat-10839	116	22	;	;	PUNCT
easat-10839	116	23	licensee	licensee	PROPN
easat-10839	116	24	learning	learn	VERB
easat-10839	116	25	gate	gate	PROPN
easat-10839	116	26	figure	figure	NOUN
easat-10839	116	27	3	3	NUM
easat-10839	116	28	.	.	PUNCT
easat-10839	116	29	flow	flow	NOUN
easat-10839	116	30	of	of	ADP
easat-10839	116	31	experimental	experimental	ADJ
easat-10839	116	32	settings	setting	NOUN
easat-10839	116	33	.	.	PUNCT
easat-10839	117	1	6	6	X
easat-10839	117	2	.	.	X
easat-10839	117	3	results	result	NOUN
easat-10839	117	4	and	and	CCONJ
easat-10839	117	5	discussions	discussion	NOUN
easat-10839	117	6	6.1	6.1	NUM
easat-10839	117	7	.	.	PUNCT
easat-10839	117	8	optimized	optimize	VERB
easat-10839	117	9	base	base	NOUN
easat-10839	117	10	model	model	NOUN
easat-10839	117	11	deep	deep	ADJ
easat-10839	117	12	transfer	transfer	NOUN
easat-10839	117	13	learning	learn	VERB
easat-10839	117	14	to	to	PART
easat-10839	117	15	achieve	achieve	VERB
easat-10839	117	16	high	high	ADJ
easat-10839	117	17	training	training	NOUN
easat-10839	117	18	accuracy	accuracy	NOUN
easat-10839	117	19	of	of	ADP
easat-10839	117	20	the	the	DET
easat-10839	117	21	base	base	NOUN
easat-10839	117	22	models	model	NOUN
easat-10839	117	23	,	,	PUNCT
easat-10839	117	24	optuna	optuna	X
easat-10839	117	25	hyperparameter	hyperparameter	NOUN
easat-10839	117	26	optimization	optimization	NOUN
easat-10839	117	27	will	will	AUX
easat-10839	117	28	be	be	AUX
easat-10839	117	29	implemented	implement	VERB
easat-10839	117	30	.	.	PUNCT
easat-10839	118	1	some	some	DET
easat-10839	118	2	hyperparameters	hyperparameter	NOUN
easat-10839	118	3	include	include	VERB
easat-10839	118	4	learning	learn	VERB
easat-10839	118	5	rate	rate	NOUN
easat-10839	118	6	(	(	PUNCT
easat-10839	118	7	lr	lr	NOUN
easat-10839	118	8	)	)	PUNCT
easat-10839	118	9	,	,	PUNCT
easat-10839	118	10	batch	batch	NOUN
easat-10839	118	11	size	size	NOUN
easat-10839	118	12	,	,	PUNCT
easat-10839	118	13	optimizer	optimizer	NOUN
easat-10839	118	14	types	type	NOUN
easat-10839	118	15	(	(	PUNCT
easat-10839	118	16	adam	adam	NOUN
easat-10839	118	17	or	or	CCONJ
easat-10839	118	18	stochastic	stochastic	ADJ
easat-10839	118	19	gradient	gradient	ADJ
easat-10839	118	20	descent	descent	NOUN
easat-10839	118	21	)	)	PUNCT
easat-10839	118	22	,	,	PUNCT
easat-10839	118	23	and	and	CCONJ
easat-10839	118	24	weight	weight	NOUN
easat-10839	118	25	decay	decay	NOUN
easat-10839	118	26	(	(	PUNCT
easat-10839	118	27	l2	l2	NOUN
easat-10839	118	28	regularization	regularization	NOUN
easat-10839	118	29	)	)	PUNCT
easat-10839	118	30	.	.	PUNCT
easat-10839	119	1	the	the	DET
easat-10839	119	2	optimal	optimal	ADJ
easat-10839	119	3	value	value	NOUN
easat-10839	119	4	of	of	ADP
easat-10839	119	5	the	the	DET
easat-10839	119	6	hyperparameter	hyperparameter	NOUN
easat-10839	119	7	combination	combination	NOUN
easat-10839	119	8	will	will	AUX
easat-10839	119	9	produce	produce	VERB
easat-10839	119	10	the	the	DET
easat-10839	119	11	highest	high	ADJ
easat-10839	119	12	accuracy	accuracy	NOUN
easat-10839	119	13	with	with	ADP
easat-10839	119	14	reasonable	reasonable	ADJ
easat-10839	119	15	speed	speed	NOUN
easat-10839	119	16	.	.	PUNCT
easat-10839	120	1	each	each	DET
easat-10839	120	2	base	base	NOUN
easat-10839	120	3	model	model	NOUN
easat-10839	120	4	has	have	VERB
easat-10839	120	5	a	a	DET
easat-10839	120	6	different	different	ADJ
easat-10839	120	7	combination	combination	NOUN
easat-10839	120	8	of	of	ADP
easat-10839	120	9	optimal	optimal	ADJ
easat-10839	120	10	hyperparameters	hyperparameter	NOUN
easat-10839	120	11	,	,	PUNCT
easat-10839	120	12	as	as	SCONJ
easat-10839	120	13	shown	show	VERB
easat-10839	120	14	in	in	ADP
easat-10839	120	15	figure	figure	NOUN
easat-10839	120	16	4	4	NUM
easat-10839	120	17	.	.	PUNCT
easat-10839	121	1	the	the	DET
easat-10839	121	2	performance	performance	NOUN
easat-10839	121	3	of	of	ADP
easat-10839	121	4	resnet18	resnet18	NOUN
easat-10839	121	5	,	,	PUNCT
easat-10839	121	6	densenet201	densenet201	PROPN
easat-10839	121	7	,	,	PUNCT
easat-10839	121	8	and	and	CCONJ
easat-10839	121	9	efficientnet_b2	efficientnet_b2	PROPN
easat-10839	121	10	is	be	AUX
easat-10839	121	11	mainly	mainly	ADV
easat-10839	121	12	influenced	influence	VERB
easat-10839	121	13	by	by	ADP
easat-10839	121	14	weight	weight	NOUN
easat-10839	121	15	decay	decay	NOUN
easat-10839	121	16	(	(	PUNCT
easat-10839	121	17	l2	l2	NOUN
easat-10839	121	18	regularization	regularization	NOUN
easat-10839	121	19	)	)	PUNCT
easat-10839	121	20	,	,	PUNCT
easat-10839	121	21	whereas	whereas	SCONJ
easat-10839	121	22	inception_v3	inception_v3	ADJ
easat-10839	121	23	relies	relie	NOUN
easat-10839	121	24	on	on	ADP
easat-10839	121	25	the	the	DET
easat-10839	121	26	learning	learning	NOUN
easat-10839	121	27	rate	rate	NOUN
easat-10839	121	28	,	,	PUNCT
easat-10839	121	29	and	and	CCONJ
easat-10839	121	30	mobilenetv2	mobilenetv2	PROPN
easat-10839	121	31	depends	depend	VERB
easat-10839	121	32	on	on	ADP
easat-10839	121	33	batch	batch	NOUN
easat-10839	121	34	size	size	NOUN
easat-10839	121	35	.	.	PUNCT
easat-10839	122	1	255	255	NUM
easat-10839	122	2	edelweiss	edelweiss	PROPN
easat-10839	122	3	applied	apply	VERB
easat-10839	122	4	science	science	NOUN
easat-10839	122	5	and	and	CCONJ
easat-10839	122	6	technology	technology	NOUN
easat-10839	122	7	issn	issn	PROPN
easat-10839	122	8	:	:	PUNCT
easat-10839	122	9	2576	2576	NUM
easat-10839	122	10	-	-	SYM
easat-10839	122	11	8484	8484	NUM
easat-10839	122	12	vol	vol	NOUN
easat-10839	122	13	.	.	PROPN
easat-10839	123	1	9	9	NUM
easat-10839	123	2	,	,	PUNCT
easat-10839	123	3	no	no	INTJ
easat-10839	123	4	.	.	NOUN
easat-10839	123	5	11	11	NUM
easat-10839	123	6	:	:	PUNCT
easat-10839	123	7	249	249	NUM
easat-10839	123	8	-	-	SYM
easat-10839	123	9	261	261	NUM
easat-10839	123	10	,	,	PUNCT
easat-10839	123	11	2025	2025	NUM
easat-10839	123	12	doi	doi	NOUN
easat-10839	123	13	:	:	PUNCT
easat-10839	123	14	10.55214/2576	10.55214/2576	NUM
easat-10839	123	15	-	-	SYM
easat-10839	123	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	123	17	©	©	ADP
easat-10839	123	18	2025	2025	NUM
easat-10839	123	19	by	by	ADP
easat-10839	123	20	the	the	DET
easat-10839	123	21	authors	author	NOUN
easat-10839	123	22	;	;	PUNCT
easat-10839	123	23	licensee	licensee	PROPN
easat-10839	123	24	learning	learn	VERB
easat-10839	123	25	gate	gate	PROPN
easat-10839	123	26	hyperparameter	hyperparameter	NOUN
easat-10839	123	27	importance	importance	NOUN
easat-10839	123	28	of	of	ADP
easat-10839	123	29	resnet18	resnet18	NOUN
easat-10839	123	30	hyperparameter	hyperparameter	NOUN
easat-10839	123	31	importance	importance	NOUN
easat-10839	123	32	of	of	ADP
easat-10839	123	33	desnet201	desnet201	PROPN
easat-10839	123	34	hyperparameter	hyperparameter	NOUN
easat-10839	123	35	importance	importance	NOUN
easat-10839	123	36	of	of	ADP
easat-10839	123	37	inception_v3	inception_v3	ADJ
easat-10839	123	38	hyperparameter	hyperparameter	NOUN
easat-10839	123	39	importance	importance	NOUN
easat-10839	123	40	of	of	ADP
easat-10839	123	41	efficientnetb2	efficientnetb2	X
easat-10839	123	42	hyperparameter	hyperparameter	NOUN
easat-10839	123	43	importance	importance	NOUN
easat-10839	123	44	of	of	ADP
easat-10839	123	45	mobilenet_v2	mobilenet_v2	ADJ
easat-10839	123	46	figure	figure	NOUN
easat-10839	123	47	4	4	NUM
easat-10839	123	48	.	.	PUNCT
easat-10839	124	1	the	the	DET
easat-10839	124	2	hyperparameter	hyperparameter	NOUN
easat-10839	124	3	importance	importance	NOUN
easat-10839	124	4	on	on	ADP
easat-10839	124	5	base	base	NOUN
easat-10839	124	6	models	model	NOUN
easat-10839	124	7	resnet18	resnet18	NOUN
easat-10839	124	8	,	,	PUNCT
easat-10839	124	9	densenet	densenet	NOUN
easat-10839	124	10	201	201	NUM
easat-10839	124	11	,	,	PUNCT
easat-10839	124	12	inception	inception	PROPN
easat-10839	124	13	v3	v3	PROPN
easat-10839	124	14	,	,	PUNCT
easat-10839	124	15	efficientnet	efficientnet	NOUN
easat-10839	124	16	b2	b2	NOUN
easat-10839	124	17	,	,	PUNCT
easat-10839	124	18	and	and	CCONJ
easat-10839	124	19	mobilenet	mobilenet	NOUN
easat-10839	124	20	v2	v2	PROPN
easat-10839	124	21	.	.	PUNCT
easat-10839	125	1	256	256	NUM
easat-10839	125	2	edelweiss	edelweiss	PROPN
easat-10839	125	3	applied	apply	VERB
easat-10839	125	4	science	science	NOUN
easat-10839	125	5	and	and	CCONJ
easat-10839	125	6	technology	technology	NOUN
easat-10839	125	7	issn	issn	PROPN
easat-10839	125	8	:	:	PUNCT
easat-10839	125	9	2576	2576	NUM
easat-10839	125	10	-	-	SYM
easat-10839	125	11	8484	8484	NUM
easat-10839	125	12	vol	vol	NOUN
easat-10839	125	13	.	.	PROPN
easat-10839	126	1	9	9	NUM
easat-10839	126	2	,	,	PUNCT
easat-10839	126	3	no	no	INTJ
easat-10839	126	4	.	.	NOUN
easat-10839	126	5	11	11	NUM
easat-10839	126	6	:	:	PUNCT
easat-10839	126	7	249	249	NUM
easat-10839	126	8	-	-	SYM
easat-10839	126	9	261	261	NUM
easat-10839	126	10	,	,	PUNCT
easat-10839	126	11	2025	2025	NUM
easat-10839	126	12	doi	doi	NOUN
easat-10839	126	13	:	:	PUNCT
easat-10839	126	14	10.55214/2576	10.55214/2576	NUM
easat-10839	126	15	-	-	SYM
easat-10839	126	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	126	17	©	©	ADP
easat-10839	126	18	2025	2025	NUM
easat-10839	126	19	by	by	ADP
easat-10839	126	20	the	the	DET
easat-10839	126	21	authors	author	NOUN
easat-10839	126	22	;	;	PUNCT
easat-10839	126	23	licensee	licensee	PROPN
easat-10839	126	24	learning	learning	NOUN
easat-10839	126	25	gate	gate	VERB
easat-10839	126	26	the	the	DET
easat-10839	126	27	five	five	NUM
easat-10839	126	28	cnn	cnn	NOUN
easat-10839	126	29	base	base	NOUN
easat-10839	126	30	models	model	NOUN
easat-10839	126	31	will	will	AUX
easat-10839	126	32	be	be	AUX
easat-10839	126	33	evaluated	evaluate	VERB
easat-10839	126	34	on	on	ADP
easat-10839	126	35	the	the	DET
easat-10839	126	36	test-1	test-1	NUM
easat-10839	126	37	and	and	CCONJ
easat-10839	126	38	test-2	test-2	NUM
easat-10839	126	39	datasets	dataset	NOUN
easat-10839	126	40	.	.	PUNCT
easat-10839	127	1	the	the	DET
easat-10839	127	2	table	table	NOUN
easat-10839	127	3	shows	show	VERB
easat-10839	127	4	the	the	DET
easat-10839	127	5	results	result	NOUN
easat-10839	127	6	of	of	ADP
easat-10839	127	7	the	the	DET
easat-10839	127	8	experiments	experiment	NOUN
easat-10839	127	9	.	.	PUNCT
easat-10839	128	1	overall	overall	ADJ
easat-10839	128	2	,	,	PUNCT
easat-10839	128	3	resnet-18	resnet-18	PROPN
easat-10839	128	4	produced	produce	VERB
easat-10839	128	5	the	the	DET
easat-10839	128	6	highest	high	ADJ
easat-10839	128	7	accuracy	accuracy	NOUN
easat-10839	128	8	and	and	CCONJ
easat-10839	128	9	the	the	DET
easat-10839	128	10	fastest	fast	ADJ
easat-10839	128	11	computation	computation	NOUN
easat-10839	128	12	,	,	PUNCT
easat-10839	128	13	based	base	VERB
easat-10839	128	14	on	on	ADP
easat-10839	128	15	batch	batch	NOUN
easat-10839	128	16	size	size	NOUN
easat-10839	128	17	and	and	CCONJ
easat-10839	128	18	learning	learning	NOUN
easat-10839	128	19	rate	rate	NOUN
easat-10839	128	20	,	,	PUNCT
easat-10839	128	21	which	which	PRON
easat-10839	128	22	are	be	AUX
easat-10839	128	23	44	44	NUM
easat-10839	128	24	and	and	CCONJ
easat-10839	128	25	0.00004	0.00004	NUM
easat-10839	128	26	,	,	PUNCT
easat-10839	128	27	respectively	respectively	ADV
easat-10839	128	28	.	.	PUNCT
easat-10839	129	1	the	the	DET
easat-10839	129	2	second	second	ADJ
easat-10839	129	3	best	good	ADJ
easat-10839	129	4	was	be	AUX
easat-10839	129	5	achieved	achieve	VERB
easat-10839	129	6	by	by	ADP
easat-10839	129	7	efficientnet_b2	efficientnet_b2	PROPN
easat-10839	129	8	,	,	PUNCT
easat-10839	129	9	followed	follow	VERB
easat-10839	129	10	by	by	ADP
easat-10839	129	11	inception_v3	inception_v3	ADJ
easat-10839	129	12	and	and	CCONJ
easat-10839	129	13	densenet201	densenet201	PROPN
easat-10839	129	14	.	.	PUNCT
easat-10839	130	1	mobilenet_v2	mobilenet_v2	PROPN
easat-10839	130	2	is	be	AUX
easat-10839	130	3	the	the	DET
easat-10839	130	4	worst	bad	ADJ
easat-10839	130	5	base	base	ADJ
easat-10839	130	6	cnn	cnn	PROPN
easat-10839	130	7	model	model	PROPN
easat-10839	130	8	.	.	PUNCT
easat-10839	131	1	table	table	NOUN
easat-10839	131	2	1	1	NUM
easat-10839	131	3	.	.	PUNCT
easat-10839	131	4	test	test	VERB
easat-10839	131	5	the	the	DET
easat-10839	131	6	accuracy	accuracy	NOUN
easat-10839	131	7	of	of	ADP
easat-10839	131	8	base	base	NOUN
easat-10839	131	9	models	model	NOUN
easat-10839	131	10	of	of	ADP
easat-10839	131	11	resnet18	resnet18	NOUN
easat-10839	131	12	,	,	PUNCT
easat-10839	131	13	densenet-201	densenet-201	NOUN
easat-10839	131	14	,	,	PUNCT
easat-10839	131	15	inception_v3	inception_v3	NOUN
easat-10839	131	16	,	,	PUNCT
easat-10839	131	17	efficientnet_b2	efficientnet_b2	NOUN
easat-10839	131	18	,	,	PUNCT
easat-10839	131	19	and	and	CCONJ
easat-10839	131	20	mobilenet_v2	mobilenet_v2	NOUN
easat-10839	131	21	using	use	VERB
easat-10839	131	22	optuna	optuna	PROPN
easat-10839	131	23	hyperparameter	hyperparameter	NOUN
easat-10839	131	24	optimization	optimization	NOUN
easat-10839	131	25	.	.	PUNCT
easat-10839	132	1	base	base	NOUN
easat-10839	132	2	model	model	NOUN
easat-10839	132	3	test-1	test-1	NUM
easat-10839	132	4	acc	acc	PROPN
easat-10839	132	5	(	(	PUNCT
easat-10839	132	6	%	%	NOUN
easat-10839	132	7	)	)	PUNCT
easat-10839	132	8	test-2	test-2	NUM
easat-10839	132	9	learning	learning	NOUN
easat-10839	132	10	rate	rate	NOUN
easat-10839	132	11	batch	batch	NOUN
easat-10839	132	12	size	size	NOUN
easat-10839	132	13	weight	weight	NOUN
easat-10839	132	14	decay	decay	NOUN
easat-10839	132	15	optimizer	optimizer	NOUN
easat-10839	132	16	time	time	NOUN
easat-10839	132	17	(	(	PUNCT
easat-10839	132	18	min	min	NOUN
easat-10839	132	19	)	)	PUNCT
easat-10839	132	20	resnet18	resnet18	NOUN
easat-10839	132	21	99.99	99.99	NUM
easat-10839	132	22	98.16	98.16	NUM
easat-10839	132	23	0.00004	0.00004	NUM
easat-10839	132	24	44	44	NUM
easat-10839	132	25	0.000008	0.000008	NUM
easat-10839	132	26	adam	adam	PROPN
easat-10839	132	27	53.57	53.57	NUM
easat-10839	132	28	densenet201	densenet201	PROPN
easat-10839	132	29	99.99	99.99	NUM
easat-10839	132	30	97.23	97.23	NUM
easat-10839	132	31	0.00003	0.00003	NUM
easat-10839	132	32	27	27	NUM
easat-10839	132	33	0.000001	0.000001	NUM
easat-10839	132	34	adam	adam	PROPN
easat-10839	132	35	156.25	156.25	NUM
easat-10839	132	36	inception_v3	inception_v3	VERB
easat-10839	132	37	99.99	99.99	NUM
easat-10839	132	38	98.12	98.12	NUM
easat-10839	132	39	0.00002	0.00002	NUM
easat-10839	132	40	16	16	NUM
easat-10839	132	41	0.000002	0.000002	NUM
easat-10839	132	42	adam	adam	PROPN
easat-10839	132	43	79.38	79.38	NUM
easat-10839	132	44	efficientnet_b2	efficientnet_b2	PROPN
easat-10839	132	45	99.99	99.99	NUM
easat-10839	132	46	98.13	98.13	NUM
easat-10839	132	47	0.00008	0.00008	NUM
easat-10839	132	48	29	29	NUM
easat-10839	132	49	0.000003	0.000003	NUM
easat-10839	132	50	adam	adam	PROPN
easat-10839	132	51	67.57	67.57	NUM
easat-10839	132	52	mobilenetv2	mobilenetv2	NOUN
easat-10839	132	53	98.98	98.98	NUM
easat-10839	132	54	96.12	96.12	NUM
easat-10839	132	55	0.00006	0.00006	NUM
easat-10839	132	56	24	24	NUM
easat-10839	132	57	0.000003	0.000003	NUM
easat-10839	132	58	adam	adam	PROPN
easat-10839	132	59	61.67	61.67	NUM
easat-10839	132	60	based	base	VERB
easat-10839	132	61	on	on	ADP
easat-10839	132	62	the	the	DET
easat-10839	132	63	test	test	NOUN
easat-10839	132	64	accuracy	accuracy	NOUN
easat-10839	132	65	shown	show	VERB
easat-10839	132	66	in	in	ADP
easat-10839	132	67	table	table	NOUN
easat-10839	132	68	1	1	NUM
easat-10839	132	69	,	,	PUNCT
easat-10839	132	70	the	the	DET
easat-10839	132	71	base	base	PROPN
easat-10839	132	72	model	model	NOUN
easat-10839	132	73	cnn	cnn	PROPN
easat-10839	132	74	resnet18	resnet18	NOUN
easat-10839	132	75	provides	provide	VERB
easat-10839	132	76	the	the	DET
easat-10839	132	77	highest	high	ADJ
easat-10839	132	78	and	and	CCONJ
easat-10839	132	79	most	most	ADV
easat-10839	132	80	consistent	consistent	ADJ
easat-10839	132	81	accuracy	accuracy	NOUN
easat-10839	132	82	,	,	PUNCT
easat-10839	132	83	as	as	ADV
easat-10839	132	84	well	well	ADV
easat-10839	132	85	as	as	ADP
easat-10839	132	86	the	the	DET
easat-10839	132	87	fastest	fast	ADJ
easat-10839	132	88	computation	computation	NOUN
easat-10839	132	89	.	.	PUNCT
easat-10839	133	1	therefore	therefore	ADV
easat-10839	133	2	,	,	PUNCT
easat-10839	133	3	for	for	ADP
easat-10839	133	4	further	further	ADJ
easat-10839	133	5	analysis	analysis	NOUN
easat-10839	133	6	,	,	PUNCT
easat-10839	133	7	the	the	DET
easat-10839	133	8	resnet	resnet	NOUN
easat-10839	133	9	base	base	NOUN
easat-10839	133	10	models	model	NOUN
easat-10839	133	11	will	will	AUX
easat-10839	133	12	be	be	AUX
easat-10839	133	13	implemented	implement	VERB
easat-10839	133	14	in	in	ADP
easat-10839	133	15	subsequent	subsequent	ADJ
easat-10839	133	16	steps	step	NOUN
easat-10839	133	17	.	.	PUNCT
easat-10839	134	1	the	the	DET
easat-10839	134	2	model	model	NOUN
easat-10839	134	3	to	to	PART
easat-10839	134	4	be	be	AUX
easat-10839	134	5	identified	identify	VERB
easat-10839	134	6	through	through	ADP
easat-10839	134	7	optuna	optuna	ADJ
easat-10839	134	8	hyperparameter	hyperparameter	NOUN
easat-10839	134	9	optimization	optimization	NOUN
easat-10839	134	10	will	will	AUX
easat-10839	134	11	then	then	ADV
easat-10839	134	12	be	be	AUX
easat-10839	134	13	used	use	VERB
easat-10839	134	14	to	to	PART
easat-10839	134	15	classify	classify	VERB
easat-10839	134	16	external	external	ADJ
easat-10839	134	17	data	datum	NOUN
easat-10839	134	18	,	,	PUNCT
easat-10839	134	19	as	as	SCONJ
easat-10839	134	20	shown	show	VERB
easat-10839	134	21	in	in	ADP
easat-10839	134	22	figure	figure	NOUN
easat-10839	134	23	5	5	NUM
easat-10839	134	24	.	.	PUNCT
easat-10839	135	1	the	the	DET
easat-10839	135	2	probability	probability	NOUN
easat-10839	135	3	of	of	ADP
easat-10839	135	4	the	the	DET
easat-10839	135	5	model	model	NOUN
easat-10839	135	6	's	's	PART
easat-10839	135	7	classification	classification	NOUN
easat-10839	135	8	is	be	AUX
easat-10839	135	9	computed	compute	VERB
easat-10839	135	10	using	use	VERB
easat-10839	135	11	a	a	DET
easat-10839	135	12	softmax	softmax	NOUN
easat-10839	135	13	classifier	classifier	NOUN
easat-10839	135	14	.	.	PUNCT
easat-10839	136	1	figure	figure	NOUN
easat-10839	136	2	5	5	NUM
easat-10839	136	3	.	.	PUNCT
easat-10839	137	1	the	the	DET
easat-10839	137	2	probability	probability	NOUN
easat-10839	137	3	of	of	ADP
easat-10839	137	4	the	the	DET
easat-10839	137	5	resnet	resnet	NOUN
easat-10839	137	6	18	18	NUM
easat-10839	137	7	model	model	NOUN
easat-10839	137	8	to	to	PART
easat-10839	137	9	classify	classify	VERB
easat-10839	137	10	the	the	DET
easat-10839	137	11	test	test	NOUN
easat-10839	137	12	data	datum	NOUN
easat-10839	137	13	1	1	NUM
easat-10839	137	14	(	(	PUNCT
easat-10839	137	15	left	leave	VERB
easat-10839	137	16	)	)	PUNCT
easat-10839	137	17	and	and	CCONJ
easat-10839	137	18	test	test	NOUN
easat-10839	137	19	data	datum	NOUN
easat-10839	137	20	2	2	NUM
easat-10839	137	21	(	(	PUNCT
easat-10839	137	22	right	right	ADJ
easat-10839	137	23	)	)	PUNCT
easat-10839	137	24	in	in	ADP
easat-10839	137	25	the	the	DET
easat-10839	137	26	correct	correct	ADJ
easat-10839	137	27	classes	class	NOUN
easat-10839	137	28	.	.	PUNCT
easat-10839	138	1	as	as	SCONJ
easat-10839	138	2	shown	show	VERB
easat-10839	138	3	in	in	ADP
easat-10839	138	4	fig5	fig5	NOUN
easat-10839	138	5	,	,	PUNCT
easat-10839	138	6	the	the	DET
easat-10839	138	7	resnet18	resnet18	NOUN
easat-10839	138	8	performed	perform	VERB
easat-10839	138	9	well	well	ADV
easat-10839	138	10	on	on	ADP
easat-10839	138	11	both	both	DET
easat-10839	138	12	test	test	NOUN
easat-10839	138	13	datasets	dataset	NOUN
easat-10839	138	14	.	.	PUNCT
easat-10839	139	1	the	the	DET
easat-10839	139	2	model	model	NOUN
easat-10839	139	3	can	can	AUX
easat-10839	139	4	predict	predict	VERB
easat-10839	139	5	the	the	DET
easat-10839	139	6	class	class	NOUN
easat-10839	139	7	of	of	ADP
easat-10839	139	8	images	image	NOUN
easat-10839	139	9	with	with	ADP
easat-10839	139	10	a	a	DET
easat-10839	139	11	probability	probability	NOUN
easat-10839	139	12	higher	high	ADJ
easat-10839	139	13	than	than	ADP
easat-10839	139	14	98	98	NUM
easat-10839	139	15	%	%	NOUN
easat-10839	139	16	.	.	PUNCT
easat-10839	140	1	for	for	ADP
easat-10839	140	2	model	model	NOUN
easat-10839	140	3	deployment	deployment	NOUN
easat-10839	140	4	,	,	PUNCT
easat-10839	140	5	the	the	DET
easat-10839	140	6	newer	new	ADJ
easat-10839	140	7	versions	version	NOUN
easat-10839	140	8	of	of	ADP
easat-10839	140	9	resnet	resnet	NOUN
easat-10839	140	10	,	,	PUNCT
easat-10839	140	11	257	257	NUM
easat-10839	140	12	edelweiss	edelweiss	PROPN
easat-10839	140	13	applied	apply	VERB
easat-10839	140	14	science	science	NOUN
easat-10839	140	15	and	and	CCONJ
easat-10839	140	16	technology	technology	NOUN
easat-10839	140	17	issn	issn	PROPN
easat-10839	140	18	:	:	PUNCT
easat-10839	140	19	2576	2576	NUM
easat-10839	140	20	-	-	SYM
easat-10839	140	21	8484	8484	NUM
easat-10839	140	22	vol	vol	NOUN
easat-10839	140	23	.	.	PROPN
easat-10839	141	1	9	9	NUM
easat-10839	141	2	,	,	PUNCT
easat-10839	141	3	no	no	INTJ
easat-10839	141	4	.	.	NOUN
easat-10839	141	5	11	11	NUM
easat-10839	141	6	:	:	PUNCT
easat-10839	141	7	249	249	NUM
easat-10839	141	8	-	-	SYM
easat-10839	141	9	261	261	NUM
easat-10839	141	10	,	,	PUNCT
easat-10839	141	11	2025	2025	NUM
easat-10839	141	12	doi	doi	NOUN
easat-10839	141	13	:	:	PUNCT
easat-10839	141	14	10.55214/2576	10.55214/2576	NUM
easat-10839	141	15	-	-	SYM
easat-10839	141	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	141	17	©	©	ADP
easat-10839	141	18	2025	2025	NUM
easat-10839	141	19	by	by	ADP
easat-10839	141	20	the	the	DET
easat-10839	141	21	authors	author	NOUN
easat-10839	141	22	;	;	PUNCT
easat-10839	141	23	licensee	licensee	PROPN
easat-10839	141	24	learning	learn	VERB
easat-10839	141	25	gate	gate	PROPN
easat-10839	141	26	resnet50	resnet50	PROPN
easat-10839	141	27	,	,	PUNCT
easat-10839	141	28	will	will	AUX
easat-10839	141	29	be	be	AUX
easat-10839	141	30	used	use	VERB
easat-10839	141	31	.	.	PUNCT
easat-10839	142	1	it	it	PRON
easat-10839	142	2	is	be	AUX
easat-10839	142	3	evident	evident	ADJ
easat-10839	142	4	that	that	SCONJ
easat-10839	142	5	the	the	DET
easat-10839	142	6	newer	new	ADJ
easat-10839	142	7	model	model	NOUN
easat-10839	142	8	has	have	VERB
easat-10839	142	9	a	a	DET
easat-10839	142	10	more	more	ADV
easat-10839	142	11	complex	complex	ADJ
easat-10839	142	12	structure	structure	NOUN
easat-10839	142	13	than	than	ADP
easat-10839	142	14	resnet18	resnet18	NOUN
easat-10839	142	15	.	.	PUNCT
easat-10839	143	1	therefore	therefore	ADV
easat-10839	143	2	,	,	PUNCT
easat-10839	143	3	the	the	DET
easat-10839	143	4	performance	performance	NOUN
easat-10839	143	5	of	of	ADP
easat-10839	143	6	the	the	DET
easat-10839	143	7	resnet50	resnet50	NOUN
easat-10839	143	8	model	model	NOUN
easat-10839	143	9	is	be	AUX
easat-10839	143	10	expected	expect	VERB
easat-10839	143	11	to	to	PART
easat-10839	143	12	be	be	AUX
easat-10839	143	13	better	well	ADJ
easat-10839	143	14	than	than	ADP
easat-10839	143	15	that	that	PRON
easat-10839	143	16	of	of	ADP
easat-10839	143	17	resnet18	resnet18	NOUN
easat-10839	143	18	.	.	PUNCT
easat-10839	144	1	6.2	6.2	NUM
easat-10839	144	2	.	.	PUNCT
easat-10839	145	1	model	model	NOUN
easat-10839	145	2	deployment	deployment	PROPN
easat-10839	145	3	for	for	ADP
easat-10839	145	4	tsr	tsr	PROPN
easat-10839	145	5	prediction	prediction	NOUN
easat-10839	145	6	the	the	DET
easat-10839	145	7	resnet50	resnet50	NOUN
easat-10839	145	8	,	,	PUNCT
easat-10839	145	9	the	the	DET
easat-10839	145	10	updated	update	VERB
easat-10839	145	11	version	version	NOUN
easat-10839	145	12	of	of	ADP
easat-10839	145	13	resnet18	resnet18	NOUN
easat-10839	145	14	,	,	PUNCT
easat-10839	145	15	is	be	AUX
easat-10839	145	16	deployed	deploy	VERB
easat-10839	145	17	on	on	ADP
easat-10839	145	18	whole	whole	ADJ
easat-10839	145	19	slide	slide	NOUN
easat-10839	145	20	images	image	NOUN
easat-10839	145	21	(	(	PUNCT
easat-10839	145	22	wsi	wsi	NOUN
easat-10839	145	23	)	)	PUNCT
easat-10839	145	24	of	of	ADP
easat-10839	145	25	colorectal	colorectal	ADJ
easat-10839	145	26	cancer	cancer	NOUN
easat-10839	145	27	patients	patient	NOUN
easat-10839	145	28	.	.	PUNCT
easat-10839	146	1	the	the	DET
easat-10839	146	2	nine	nine	NUM
easat-10839	146	3	classes	class	NOUN
easat-10839	146	4	of	of	ADP
easat-10839	146	5	colorectal	colorectal	ADJ
easat-10839	146	6	carcinoma	carcinoma	NOUN
easat-10839	146	7	have	have	AUX
easat-10839	146	8	been	be	AUX
easat-10839	146	9	successfully	successfully	ADV
easat-10839	146	10	classified	classify	VERB
easat-10839	146	11	by	by	ADP
easat-10839	146	12	resnet	resnet	NOUN
easat-10839	146	13	50	50	NUM
easat-10839	146	14	.	.	PUNCT
easat-10839	147	1	the	the	DET
easat-10839	147	2	sample	sample	NOUN
easat-10839	147	3	heatmap	heatmap	NOUN
easat-10839	147	4	of	of	ADP
easat-10839	147	5	the	the	DET
easat-10839	147	6	classes	class	NOUN
easat-10839	147	7	is	be	AUX
easat-10839	147	8	shown	show	VERB
easat-10839	147	9	in	in	ADP
easat-10839	147	10	figure	figure	NOUN
easat-10839	147	11	5	5	NUM
easat-10839	147	12	.	.	PUNCT
easat-10839	148	1	the	the	DET
easat-10839	148	2	tum	tum	PROPN
easat-10839	148	3	class	class	NOUN
easat-10839	148	4	has	have	VERB
easat-10839	148	5	the	the	DET
easat-10839	148	6	highest	high	ADJ
easat-10839	148	7	proportion	proportion	NOUN
easat-10839	148	8	compared	compare	VERB
easat-10839	148	9	to	to	ADP
easat-10839	148	10	the	the	DET
easat-10839	148	11	other	other	ADJ
easat-10839	148	12	classes	class	NOUN
easat-10839	148	13	.	.	PUNCT
easat-10839	149	1	near	near	ADP
easat-10839	149	2	the	the	DET
easat-10839	149	3	tum	tum	NOUN
easat-10839	149	4	,	,	PUNCT
easat-10839	149	5	there	there	PRON
easat-10839	149	6	are	be	VERB
easat-10839	149	7	str	str	NOUN
easat-10839	149	8	classes	class	NOUN
easat-10839	149	9	.	.	PUNCT
easat-10839	150	1	these	these	DET
easat-10839	150	2	tum	tum	PROPN
easat-10839	150	3	and	and	CCONJ
easat-10839	150	4	str	str	NOUN
easat-10839	150	5	classes	class	NOUN
easat-10839	150	6	indicate	indicate	VERB
easat-10839	150	7	the	the	DET
easat-10839	150	8	level	level	NOUN
easat-10839	150	9	of	of	ADP
easat-10839	150	10	prognosis	prognosis	NOUN
easat-10839	150	11	of	of	ADP
easat-10839	150	12	colorectal	colorectal	ADJ
easat-10839	150	13	carcinoma	carcinoma	NOUN
easat-10839	150	14	.	.	PUNCT
easat-10839	151	1	if	if	SCONJ
easat-10839	151	2	the	the	DET
easat-10839	151	3	proportion	proportion	NOUN
easat-10839	151	4	of	of	ADP
easat-10839	151	5	tum	tum	NOUN
easat-10839	151	6	and	and	CCONJ
easat-10839	151	7	str	str	NOUN
easat-10839	151	8	exceeds	exceed	NOUN
easat-10839	151	9	0.5	0.5	NUM
easat-10839	151	10	,	,	PUNCT
easat-10839	151	11	this	this	DET
easat-10839	151	12	ratio	ratio	NOUN
easat-10839	151	13	is	be	AUX
easat-10839	151	14	considered	consider	VERB
easat-10839	151	15	a	a	DET
easat-10839	151	16	high	high	ADJ
easat-10839	151	17	tumor	tumor	NOUN
easat-10839	151	18	-	-	PUNCT
easat-10839	151	19	stroma	stroma	NOUN
easat-10839	151	20	ratio	ratio	NOUN
easat-10839	151	21	(	(	PUNCT
easat-10839	151	22	tsr	tsr	PROPN
easat-10839	151	23	)	)	PUNCT
easat-10839	151	24	,	,	PUNCT
easat-10839	151	25	which	which	PRON
easat-10839	151	26	indicates	indicate	VERB
easat-10839	151	27	a	a	DET
easat-10839	151	28	larger	large	ADJ
easat-10839	151	29	proportion	proportion	NOUN
easat-10839	151	30	of	of	ADP
easat-10839	151	31	stroma	stroma	NOUN
easat-10839	151	32	compared	compare	VERB
easat-10839	151	33	to	to	ADP
easat-10839	151	34	tumor	tumor	NOUN
easat-10839	151	35	cells	cell	NOUN
easat-10839	151	36	.	.	PUNCT
easat-10839	152	1	this	this	PRON
easat-10839	152	2	suggests	suggest	VERB
easat-10839	152	3	a	a	DET
easat-10839	152	4	more	more	ADV
easat-10839	152	5	aggressive	aggressive	ADJ
easat-10839	152	6	tumor	tumor	NOUN
easat-10839	152	7	biology	biology	NOUN
easat-10839	152	8	and	and	CCONJ
easat-10839	152	9	is	be	AUX
easat-10839	152	10	a	a	DET
easat-10839	152	11	potential	potential	ADJ
easat-10839	152	12	prognostic	prognostic	ADJ
easat-10839	152	13	factor	factor	NOUN
easat-10839	152	14	,	,	PUNCT
easat-10839	152	15	indicating	indicate	VERB
easat-10839	152	16	a	a	DET
easat-10839	152	17	need	need	NOUN
easat-10839	152	18	for	for	ADP
easat-10839	152	19	more	more	ADV
easat-10839	152	20	intensive	intensive	ADJ
easat-10839	152	21	treatment	treatment	NOUN
easat-10839	152	22	strategies	strategy	NOUN
easat-10839	152	23	.	.	PUNCT
easat-10839	153	1	figure	figure	NOUN
easat-10839	153	2	6	6	NUM
easat-10839	153	3	.	.	PUNCT
easat-10839	154	1	the	the	DET
easat-10839	154	2	heatmap	heatmap	NOUN
easat-10839	154	3	of	of	ADP
easat-10839	154	4	colorectal	colorectal	ADJ
easat-10839	154	5	carcinoma	carcinoma	NOUN
easat-10839	154	6	.	.	PUNCT
easat-10839	155	1	the	the	DET
easat-10839	155	2	example	example	NOUN
easat-10839	155	3	of	of	ADP
easat-10839	155	4	the	the	DET
easat-10839	155	5	proportion	proportion	NOUN
easat-10839	155	6	of	of	ADP
easat-10839	155	7	nine	nine	NUM
easat-10839	155	8	classes	class	NOUN
easat-10839	155	9	of	of	ADP
easat-10839	155	10	colorectal	colorectal	ADJ
easat-10839	155	11	carcinoma	carcinoma	NOUN
easat-10839	155	12	is	be	AUX
easat-10839	155	13	shown	show	VERB
easat-10839	155	14	in	in	ADP
easat-10839	155	15	figure	figure	NOUN
easat-10839	155	16	6	6	NUM
easat-10839	155	17	.	.	PUNCT
easat-10839	156	1	after	after	ADP
easat-10839	156	2	determining	determine	VERB
easat-10839	156	3	the	the	DET
easat-10839	156	4	classification	classification	NOUN
easat-10839	156	5	heatmap	heatmap	NOUN
easat-10839	156	6	,	,	PUNCT
easat-10839	156	7	the	the	DET
easat-10839	156	8	areas	area	NOUN
easat-10839	156	9	of	of	ADP
easat-10839	156	10	tum	tum	PROPN
easat-10839	156	11	and	and	CCONJ
easat-10839	156	12	str	str	NOUN
easat-10839	156	13	will	will	AUX
easat-10839	156	14	be	be	AUX
easat-10839	156	15	identified	identify	VERB
easat-10839	156	16	.	.	PUNCT
easat-10839	157	1	subsequently	subsequently	ADV
easat-10839	157	2	,	,	PUNCT
easat-10839	157	3	the	the	DET
easat-10839	157	4	tumor	tumor	NOUN
easat-10839	157	5	-	-	PUNCT
easat-10839	157	6	stroma	stroma	NOUN
easat-10839	157	7	ratio	ratio	NOUN
easat-10839	157	8	can	can	AUX
easat-10839	157	9	be	be	AUX
easat-10839	157	10	calculated	calculate	VERB
easat-10839	157	11	as	as	SCONJ
easat-10839	157	12	follows	follow	VERB
easat-10839	157	13	:	:	PUNCT
easat-10839	157	14	𝑇𝑆𝑅	𝑇𝑆𝑅	PROPN
easat-10839	157	15	=	=	SYM
easat-10839	157	16	𝐿𝑆𝑇𝑅	𝐿𝑆𝑇𝑅	PROPN
easat-10839	157	17	(	(	PUNCT
easat-10839	157	18	𝐿𝑆𝑇𝑅	𝐿𝑆𝑇𝑅	PROPN
easat-10839	157	19	+	+	CCONJ
easat-10839	157	20	𝐿𝑇𝑈𝑀	𝐿𝑇𝑈𝑀	PROPN
easat-10839	157	21	)	)	PUNCT
easat-10839	157	22	(	(	PUNCT
easat-10839	157	23	1	1	X
easat-10839	157	24	)	)	PUNCT
easat-10839	157	25	where	where	SCONJ
easat-10839	157	26	tsr	tsr	PROPN
easat-10839	157	27	,	,	PUNCT
easat-10839	157	28	lstr	lstr	NOUN
easat-10839	157	29	,	,	PUNCT
easat-10839	157	30	and	and	CCONJ
easat-10839	157	31	ltum	ltum	NOUN
easat-10839	157	32	are	be	AUX
easat-10839	157	33	the	the	DET
easat-10839	157	34	tumor	tumor	NOUN
easat-10839	157	35	-	-	PUNCT
easat-10839	157	36	stroma	stroma	NOUN
easat-10839	157	37	ratio	ratio	NOUN
easat-10839	157	38	,	,	PUNCT
easat-10839	157	39	area	area	NOUN
easat-10839	157	40	of	of	ADP
easat-10839	157	41	stroma	stroma	NOUN
easat-10839	157	42	,	,	PUNCT
easat-10839	157	43	and	and	CCONJ
easat-10839	157	44	area	area	NOUN
easat-10839	157	45	of	of	ADP
easat-10839	157	46	tumor	tumor	NOUN
easat-10839	157	47	,	,	PUNCT
easat-10839	157	48	respectively	respectively	ADV
easat-10839	157	49	.	.	PUNCT
easat-10839	158	1	if	if	SCONJ
easat-10839	158	2	the	the	DET
easat-10839	158	3	tsr	tsr	PROPN
easat-10839	158	4	>	>	X
easat-10839	158	5	0.5	0.5	NUM
easat-10839	158	6	,	,	PUNCT
easat-10839	158	7	it	it	PRON
easat-10839	158	8	is	be	AUX
easat-10839	158	9	called	call	VERB
easat-10839	158	10	a	a	DET
easat-10839	158	11	high	high	ADJ
easat-10839	158	12	tsr	tsr	NOUN
easat-10839	158	13	;	;	PUNCT
easat-10839	158	14	otherwise	otherwise	ADV
easat-10839	158	15	,	,	PUNCT
easat-10839	158	16	it	it	PRON
easat-10839	158	17	is	be	AUX
easat-10839	158	18	called	call	VERB
easat-10839	158	19	a	a	DET
easat-10839	158	20	low	low	ADJ
easat-10839	158	21	tsr	tsr	PROPN
easat-10839	158	22	.	.	PROPN
easat-10839	158	23	258	258	NUM
easat-10839	158	24	edelweiss	edelweiss	PROPN
easat-10839	158	25	applied	apply	VERB
easat-10839	158	26	science	science	NOUN
easat-10839	158	27	and	and	CCONJ
easat-10839	158	28	technology	technology	NOUN
easat-10839	158	29	issn	issn	PROPN
easat-10839	158	30	:	:	PUNCT
easat-10839	158	31	2576	2576	NUM
easat-10839	158	32	-	-	SYM
easat-10839	158	33	8484	8484	NUM
easat-10839	158	34	vol	vol	NOUN
easat-10839	158	35	.	.	PROPN
easat-10839	159	1	9	9	NUM
easat-10839	159	2	,	,	PUNCT
easat-10839	159	3	no	no	INTJ
easat-10839	159	4	.	.	NOUN
easat-10839	159	5	11	11	NUM
easat-10839	159	6	:	:	PUNCT
easat-10839	159	7	249	249	NUM
easat-10839	159	8	-	-	SYM
easat-10839	159	9	261	261	NUM
easat-10839	159	10	,	,	PUNCT
easat-10839	159	11	2025	2025	NUM
easat-10839	159	12	doi	doi	NOUN
easat-10839	159	13	:	:	PUNCT
easat-10839	159	14	10.55214/2576	10.55214/2576	NUM
easat-10839	159	15	-	-	SYM
easat-10839	159	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	159	17	©	©	ADP
easat-10839	159	18	2025	2025	NUM
easat-10839	159	19	by	by	ADP
easat-10839	159	20	the	the	DET
easat-10839	159	21	authors	author	NOUN
easat-10839	159	22	;	;	PUNCT
easat-10839	159	23	licensee	licensee	PROPN
easat-10839	159	24	learning	learn	VERB
easat-10839	159	25	gate	gate	NOUN
easat-10839	159	26	figure	figure	NOUN
easat-10839	159	27	7	7	NUM
easat-10839	159	28	.	.	PUNCT
easat-10839	160	1	the	the	DET
easat-10839	160	2	example	example	NOUN
easat-10839	160	3	of	of	ADP
easat-10839	160	4	the	the	DET
easat-10839	160	5	proportion	proportion	NOUN
easat-10839	160	6	of	of	ADP
easat-10839	160	7	nine	nine	NUM
easat-10839	160	8	classes	class	NOUN
easat-10839	160	9	of	of	ADP
easat-10839	160	10	colorectal	colorectal	ADJ
easat-10839	160	11	carcinoma	carcinoma	NOUN
easat-10839	160	12	and	and	CCONJ
easat-10839	160	13	the	the	DET
easat-10839	160	14	tsr	tsr	PROPN
easat-10839	160	15	prediction	prediction	NOUN
easat-10839	160	16	.	.	PUNCT
easat-10839	161	1	the	the	DET
easat-10839	161	2	sample	sample	NOUN
easat-10839	161	3	of	of	ADP
easat-10839	161	4	the	the	DET
easat-10839	161	5	tsr	tsr	PROPN
easat-10839	161	6	value	value	NOUN
easat-10839	161	7	is	be	AUX
easat-10839	161	8	shown	show	VERB
easat-10839	161	9	in	in	ADP
easat-10839	161	10	figure	figure	NOUN
easat-10839	161	11	7	7	NUM
easat-10839	161	12	.	.	PUNCT
easat-10839	162	1	first	first	ADV
easat-10839	162	2	,	,	PUNCT
easat-10839	162	3	the	the	DET
easat-10839	162	4	overall	overall	ADJ
easat-10839	162	5	prediction	prediction	NOUN
easat-10839	162	6	classes	class	NOUN
easat-10839	162	7	determined	determine	VERB
easat-10839	162	8	by	by	ADP
easat-10839	162	9	resnet50	resnet50	NOUN
easat-10839	162	10	are	be	AUX
easat-10839	162	11	shown	show	VERB
easat-10839	162	12	in	in	ADP
easat-10839	162	13	the	the	DET
easat-10839	162	14	figure	figure	NOUN
easat-10839	162	15	above	above	ADV
easat-10839	162	16	.	.	PUNCT
easat-10839	163	1	from	from	ADP
easat-10839	163	2	the	the	DET
easat-10839	163	3	overall	overall	ADJ
easat-10839	163	4	classes	class	NOUN
easat-10839	163	5	,	,	PUNCT
easat-10839	163	6	the	the	DET
easat-10839	163	7	tumor	tumor	NOUN
easat-10839	163	8	classes	class	NOUN
easat-10839	163	9	and	and	CCONJ
easat-10839	163	10	stroma	stroma	ADJ
easat-10839	163	11	classes	class	NOUN
easat-10839	163	12	will	will	AUX
easat-10839	163	13	be	be	AUX
easat-10839	163	14	extracted	extract	VERB
easat-10839	163	15	.	.	PUNCT
easat-10839	164	1	then	then	ADV
easat-10839	164	2	,	,	PUNCT
easat-10839	164	3	the	the	DET
easat-10839	164	4	areas	area	NOUN
easat-10839	164	5	of	of	ADP
easat-10839	164	6	tum	tum	PROPN
easat-10839	164	7	and	and	CCONJ
easat-10839	164	8	str	str	NOUN
easat-10839	164	9	will	will	AUX
easat-10839	164	10	be	be	AUX
easat-10839	164	11	determined	determine	VERB
easat-10839	164	12	.	.	PUNCT
easat-10839	165	1	finally	finally	ADV
easat-10839	165	2	,	,	PUNCT
easat-10839	165	3	the	the	DET
easat-10839	165	4	tsr	tsr	PROPN
easat-10839	165	5	value	value	NOUN
easat-10839	165	6	can	can	AUX
easat-10839	165	7	be	be	AUX
easat-10839	165	8	predicted	predict	VERB
easat-10839	165	9	using	use	VERB
easat-10839	165	10	equation	equation	NOUN
easat-10839	165	11	(	(	PUNCT
easat-10839	165	12	1	1	NUM
easat-10839	165	13	)	)	PUNCT
easat-10839	165	14	.	.	PUNCT
easat-10839	166	1	6.3	6.3	NUM
easat-10839	166	2	.	.	PUNCT
easat-10839	166	3	evaluation	evaluation	NOUN
easat-10839	166	4	of	of	ADP
easat-10839	166	5	tsr	tsr	PROPN
easat-10839	166	6	as	as	ADP
easat-10839	166	7	a	a	DET
easat-10839	166	8	prognosis	prognosis	NOUN
easat-10839	166	9	factor	factor	NOUN
easat-10839	166	10	in	in	ADP
easat-10839	166	11	crc	crc	NOUN
easat-10839	166	12	for	for	ADP
easat-10839	166	13	the	the	DET
easat-10839	166	14	evaluation	evaluation	NOUN
easat-10839	166	15	of	of	ADP
easat-10839	166	16	tsr	tsr	PROPN
easat-10839	166	17	as	as	ADP
easat-10839	166	18	a	a	DET
easat-10839	166	19	prognostic	prognostic	ADJ
easat-10839	166	20	factor	factor	NOUN
easat-10839	166	21	in	in	ADP
easat-10839	166	22	colorectal	colorectal	ADJ
easat-10839	166	23	cancer	cancer	NOUN
easat-10839	166	24	,	,	PUNCT
easat-10839	166	25	we	we	PRON
easat-10839	166	26	used	use	VERB
easat-10839	166	27	the	the	DET
easat-10839	166	28	cancer	cancer	NOUN
easat-10839	166	29	genome	genome	NOUN
easat-10839	166	30	atlas	atlas	PROPN
easat-10839	166	31	(	(	PUNCT
easat-10839	166	32	tcga	tcga	PROPN
easat-10839	166	33	)	)	PUNCT
easat-10839	166	34	colorectal	colorectal	ADJ
easat-10839	166	35	adenocarcinoma	adenocarcinoma	NOUN
easat-10839	166	36	(	(	PUNCT
easat-10839	166	37	coad	coad	NOUN
easat-10839	166	38	)	)	PUNCT
easat-10839	166	39	data	datum	NOUN
easat-10839	166	40	from	from	ADP
easat-10839	166	41	(	(	PUNCT
easat-10839	166	42	)	)	PUNCT
easat-10839	166	43	.	.	PUNCT
easat-10839	167	1	as	as	SCONJ
easat-10839	167	2	shown	show	VERB
easat-10839	167	3	in	in	ADP
easat-10839	167	4	table	table	NOUN
easat-10839	167	5	2	2	NUM
easat-10839	167	6	,	,	PUNCT
easat-10839	167	7	a	a	DET
easat-10839	167	8	sample	sample	NOUN
easat-10839	167	9	of	of	ADP
easat-10839	167	10	222	222	NUM
easat-10839	167	11	patients	patient	NOUN
easat-10839	167	12	'	'	PART
easat-10839	167	13	data	datum	NOUN
easat-10839	167	14	has	have	AUX
easat-10839	167	15	been	be	AUX
easat-10839	167	16	used	use	VERB
easat-10839	167	17	to	to	PART
easat-10839	167	18	determine	determine	VERB
easat-10839	167	19	the	the	DET
easat-10839	167	20	importance	importance	NOUN
easat-10839	167	21	of	of	ADP
easat-10839	167	22	tsr	tsr	PROPN
easat-10839	167	23	as	as	ADP
easat-10839	167	24	a	a	DET
easat-10839	167	25	prognostic	prognostic	ADJ
easat-10839	167	26	factor	factor	NOUN
easat-10839	167	27	in	in	ADP
easat-10839	167	28	colorectal	colorectal	ADJ
easat-10839	167	29	cancer	cancer	NOUN
easat-10839	167	30	using	use	VERB
easat-10839	167	31	the	the	DET
easat-10839	167	32	cox	cox	PROPN
easat-10839	167	33	proportional	proportional	ADJ
easat-10839	167	34	-	-	PUNCT
easat-10839	167	35	hazards	hazard	NOUN
easat-10839	167	36	model	model	NOUN
easat-10839	167	37	.	.	PUNCT
easat-10839	168	1	table	table	NOUN
easat-10839	168	2	2	2	NUM
easat-10839	168	3	.	.	PUNCT
easat-10839	168	4	sample	sample	NOUN
easat-10839	168	5	tgca	tgca	PROPN
easat-10839	168	6	colorectal	colorectal	ADJ
easat-10839	168	7	measurement	measurement	NOUN
easat-10839	168	8	data	datum	NOUN
easat-10839	168	9	.	.	PUNCT
easat-10839	169	1	years_to	years_to	PROPN
easat-10839	169	2	birth	birth	NOUN
easat-10839	169	3	event	event	NOUN
easat-10839	169	4	pathologic	pathologic	ADJ
easat-10839	169	5	stage	stage	NOUN
easat-10839	169	6	pathology	pathology	NOUN
easat-10839	169	7	t_stage	t_stage	NOUN
easat-10839	169	8	pathology	pathology	NOUN
easat-10839	169	9	m_stage	m_stage	NOUN
easat-10839	169	10	gender	gender	NOUN
easat-10839	169	11	time	time	NOUN
easat-10839	169	12	tsr	tsr	PROPN
easat-10839	169	13	74	74	NUM
easat-10839	169	14	true	true	ADJ
easat-10839	169	15	stage	stage	NOUN
easat-10839	169	16	iv	iv	NUM
easat-10839	169	17	t3	t3	PROPN
easat-10839	169	18	m1b	m1b	PROPN
easat-10839	169	19	male	male	NOUN
easat-10839	169	20	49	49	NUM
easat-10839	169	21	high	high	ADJ
easat-10839	169	22	40	40	NUM
easat-10839	169	23	true	true	ADJ
easat-10839	169	24	stage	stage	NOUN
easat-10839	169	25	iv	iv	NUM
easat-10839	169	26	t4a	t4a	ADJ
easat-10839	169	27	m1a	m1a	PROPN
easat-10839	169	28	female	female	ADJ
easat-10839	169	29	290	290	NUM
easat-10839	169	30	low	low	ADJ
easat-10839	169	31	85	85	NUM
easat-10839	169	32	true	true	ADJ
easat-10839	169	33	stage	stage	NOUN
easat-10839	169	34	iv	iv	NUM
easat-10839	169	35	t3	t3	PROPN
easat-10839	169	36	m1	m1	PROPN
easat-10839	169	37	male	male	NOUN
easat-10839	169	38	1331	1331	NUM
easat-10839	169	39	low	low	ADJ
easat-10839	169	40	70	70	NUM
easat-10839	169	41	true	true	ADJ
easat-10839	169	42	stage	stage	NOUN
easat-10839	169	43	iv	iv	ADP
easat-10839	169	44	t4b	t4b	NOUN
easat-10839	169	45	m1	m1	NOUN
easat-10839	169	46	male	male	NOUN
easat-10839	169	47	424	424	NUM
easat-10839	169	48	low	low	ADJ
easat-10839	169	49	53	53	NUM
easat-10839	169	50	false	false	ADJ
easat-10839	169	51	stage	stage	NOUN
easat-10839	169	52	iiic	iiic	PROPN
easat-10839	169	53	t3	t3	PROPN
easat-10839	169	54	m0	m0	PROPN
easat-10839	169	55	female	female	ADJ
easat-10839	169	56	1054	1054	NUM
easat-10839	169	57	low	low	ADJ
easat-10839	169	58	80	80	NUM
easat-10839	169	59	false	false	ADJ
easat-10839	169	60	stage	stage	NOUN
easat-10839	169	61	iiic	iiic	PROPN
easat-10839	169	62	t4a	t4a	PROPN
easat-10839	169	63	mx	mx	PROPN
easat-10839	169	64	male	male	NOUN
easat-10839	169	65	672	672	NUM
easat-10839	169	66	low	low	ADJ
easat-10839	169	67	60	60	NUM
easat-10839	169	68	false	false	ADJ
easat-10839	169	69	stage	stage	NOUN
easat-10839	169	70	iia	iia	PROPN
easat-10839	169	71	t3	t3	PROPN
easat-10839	169	72	m0	m0	PROPN
easat-10839	169	73	male	male	NOUN
easat-10839	169	74	1186	1186	NUM
easat-10839	169	75	low	low	ADJ
easat-10839	169	76	89	89	NUM
easat-10839	169	77	false	false	ADJ
easat-10839	169	78	stage	stage	NOUN
easat-10839	169	79	iiib	iiib	NOUN
easat-10839	169	80	t3	t3	PROPN
easat-10839	169	81	m0	m0	PROPN
easat-10839	169	82	male	male	NOUN
easat-10839	169	83	245	245	NUM
easat-10839	169	84	low	low	ADJ
easat-10839	169	85	57	57	NUM
easat-10839	169	86	false	false	ADJ
easat-10839	169	87	stage	stage	NOUN
easat-10839	169	88	i	i	PRON
easat-10839	169	89	t2	t2	VERB
easat-10839	169	90	m0	m0	NOUN
easat-10839	169	91	male	male	NOUN
easat-10839	169	92	580	580	NUM
easat-10839	169	93	low	low	ADJ
easat-10839	169	94	table	table	NOUN
easat-10839	169	95	3	3	NUM
easat-10839	169	96	.	.	PUNCT
easat-10839	170	1	the	the	DET
easat-10839	170	2	significance	significance	NOUN
easat-10839	170	3	of	of	ADP
easat-10839	170	4	prognosis	prognosis	NOUN
easat-10839	170	5	factor	factor	NOUN
easat-10839	170	6	model	model	NOUN
easat-10839	170	7	.	.	PUNCT
easat-10839	171	1	tsr	tsr	PROPN
easat-10839	171	2	1.02	1.02	NUM
easat-10839	171	3	2.774	2.774	NUM
easat-10839	171	4	0.464	0.464	NUM
easat-10839	171	5	2.199	2.199	NUM
easat-10839	171	6	0.028	0.028	NUM
easat-10839	171	7	0.028	0.028	NUM
easat-10839	171	8	pathology_t_stage_t2	pathology_t_stage_t2	ADP
easat-10839	171	9	15.991	15.991	NUM
easat-10839	171	10	8807620.074	8807620.074	NUM
easat-10839	171	11	3137.135	3137.135	NUM
easat-10839	171	12	0.005	0.005	NUM
easat-10839	171	13	0.996	0.996	NUM
easat-10839	171	14	0.996	0.996	NUM
easat-10839	171	15	pathology_t_stage_t3	pathology_t_stage_t3	NOUN
easat-10839	171	16	16.289	16.289	NUM
easat-10839	171	17	1858763.221	1858763.221	NUM
easat-10839	171	18	3137.135	3137.135	NUM
easat-10839	171	19	0.005	0.005	NUM
easat-10839	171	20	0.996	0.996	NUM
easat-10839	171	21	0.996	0.996	NUM
easat-10839	171	22	pathology_t_stage_t4	pathology_t_stage_t4	NOUN
easat-10839	171	23	15.778	15.778	NUM
easat-10839	171	24	7115416.985	7115416.985	NUM
easat-10839	171	25	3137.135	3137.135	NUM
easat-10839	171	26	0.005	0.005	NUM
easat-10839	171	27	0.996	0.996	NUM
easat-10839	171	28	0.996	0.996	NUM
easat-10839	171	29	pathology_t_stage_t4a	pathology_t_stage_t4a	NOUN
easat-10839	171	30	16.032	16.032	NUM
easat-10839	171	31	9174120.975	9174120.975	NUM
easat-10839	171	32	3137.135	3137.135	NUM
easat-10839	171	33	0.005	0.005	NUM
easat-10839	171	34	0.996	0.996	NUM
easat-10839	171	35	0.996	0.996	NUM
easat-10839	171	36	pathology_t_stage_t4b	pathology_t_stage_t4b	NOUN
easat-10839	171	37	17.827	17.827	NUM
easat-10839	171	38	55248235.93	55248235.93	NUM
easat-10839	171	39	3137.135	3137.135	NUM
easat-10839	171	40	0.006	0.006	NUM
easat-10839	171	41	0.995	0.995	NUM
easat-10839	171	42	0.996	0.996	NUM
easat-10839	171	43	pathology_m_stage_m1	pathology_m_stage_m1	NOUN
easat-10839	171	44	1.878	1.878	NUM
easat-10839	171	45	6.544	6.544	NUM
easat-10839	171	46	0.407	0.407	NUM
easat-10839	171	47	4.61	4.61	NUM
easat-10839	171	48	0	0	NUM
easat-10839	171	49	0	0	NUM
easat-10839	171	50	pathology_m_stage_m1a	pathology_m_stage_m1a	NOUN
easat-10839	171	51	1.489	1.489	NUM
easat-10839	171	52	4.433	4.433	NUM
easat-10839	171	53	1.186	1.186	NUM
easat-10839	171	54	1.255	1.255	NUM
easat-10839	171	55	0.209	0.209	NUM
easat-10839	171	56	0.209	0.209	NUM
easat-10839	171	57	pathology_m_stage_m1b	pathology_m_stage_m1b	PROPN
easat-10839	171	58	3.077	3.077	NUM
easat-10839	171	59	21.695	21.695	NUM
easat-10839	171	60	1.152	1.152	NUM
easat-10839	171	61	2.671	2.671	NUM
easat-10839	171	62	0.008	0.008	NUM
easat-10839	171	63	0.008	0.008	NUM
easat-10839	171	64	pathology_m_stage_mx	pathology_m_stage_mx	NOUN
easat-10839	171	65	-0.407	-0.407	PUNCT
easat-10839	171	66	0.666	0.666	NUM
easat-10839	171	67	1.053	1.053	NUM
easat-10839	171	68	-0.386	-0.386	NUM
easat-10839	171	69	0.699	0.699	NUM
easat-10839	171	70	0.699	0.699	NUM
easat-10839	171	71	the	the	DET
easat-10839	171	72	results	result	NOUN
easat-10839	171	73	are	be	AUX
easat-10839	171	74	shown	show	VERB
easat-10839	171	75	in	in	ADP
easat-10839	171	76	table	table	NOUN
easat-10839	171	77	3	3	NUM
easat-10839	171	78	.	.	PUNCT
easat-10839	172	1	there	there	PRON
easat-10839	172	2	are	be	VERB
easat-10839	172	3	four	four	NUM
easat-10839	172	4	main	main	ADJ
easat-10839	172	5	prognostic	prognostic	ADJ
easat-10839	172	6	factors	factor	NOUN
easat-10839	172	7	that	that	PRON
easat-10839	172	8	play	play	VERB
easat-10839	172	9	an	an	DET
easat-10839	172	10	important	important	ADJ
easat-10839	172	11	role	role	NOUN
easat-10839	172	12	in	in	ADP
easat-10839	172	13	patient	patient	ADJ
easat-10839	172	14	survival	survival	NOUN
easat-10839	172	15	prediction	prediction	NOUN
easat-10839	172	16	,	,	PUNCT
easat-10839	172	17	which	which	PRON
easat-10839	172	18	include	include	VERB
easat-10839	172	19	pathology_m_stage_m1	pathology_m_stage_m1	NOUN
easat-10839	172	20	,	,	PUNCT
easat-10839	172	21	tumor	tumor	NOUN
easat-10839	172	22	-	-	PUNCT
easat-10839	172	23	stroma	stroma	NOUN
easat-10839	172	24	ratio	ratio	NOUN
easat-10839	172	25	(	(	PUNCT
easat-10839	172	26	tsr	tsr	PROPN
easat-10839	172	27	)	)	PUNCT
easat-10839	172	28	,	,	PUNCT
easat-10839	172	29	259	259	NUM
easat-10839	172	30	edelweiss	edelweiss	PROPN
easat-10839	172	31	applied	apply	VERB
easat-10839	172	32	science	science	NOUN
easat-10839	172	33	and	and	CCONJ
easat-10839	172	34	technology	technology	NOUN
easat-10839	172	35	issn	issn	PROPN
easat-10839	172	36	:	:	PUNCT
easat-10839	172	37	2576	2576	NUM
easat-10839	172	38	-	-	SYM
easat-10839	172	39	8484	8484	NUM
easat-10839	172	40	vol	vol	NOUN
easat-10839	172	41	.	.	PROPN
easat-10839	173	1	9	9	NUM
easat-10839	173	2	,	,	PUNCT
easat-10839	173	3	no	no	INTJ
easat-10839	173	4	.	.	NOUN
easat-10839	173	5	11	11	NUM
easat-10839	173	6	:	:	PUNCT
easat-10839	173	7	249	249	NUM
easat-10839	173	8	-	-	SYM
easat-10839	173	9	261	261	NUM
easat-10839	173	10	,	,	PUNCT
easat-10839	173	11	2025	2025	NUM
easat-10839	173	12	doi	doi	NOUN
easat-10839	173	13	:	:	PUNCT
easat-10839	173	14	10.55214/2576	10.55214/2576	NUM
easat-10839	173	15	-	-	SYM
easat-10839	173	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	173	17	©	©	ADP
easat-10839	173	18	2025	2025	NUM
easat-10839	173	19	by	by	ADP
easat-10839	173	20	the	the	DET
easat-10839	173	21	authors	author	NOUN
easat-10839	173	22	;	;	PUNCT
easat-10839	173	23	licensee	licensee	PROPN
easat-10839	173	24	learning	learning	PROPN
easat-10839	173	25	gate	gate	NOUN
easat-10839	173	26	pathology_m_stage_m1b	pathology_m_stage_m1b	PROPN
easat-10839	173	27	,	,	PUNCT
easat-10839	173	28	and	and	CCONJ
easat-10839	173	29	gender	gender	NOUN
easat-10839	173	30	.	.	PUNCT
easat-10839	174	1	the	the	DET
easat-10839	174	2	model	model	NOUN
easat-10839	174	3	has	have	VERB
easat-10839	174	4	a	a	DET
easat-10839	174	5	concordance	concordance	NOUN
easat-10839	174	6	index	index	NOUN
easat-10839	174	7	of	of	ADP
easat-10839	174	8	0.79	0.79	NUM
easat-10839	174	9	.	.	PUNCT
easat-10839	175	1	as	as	SCONJ
easat-10839	175	2	expected	expect	VERB
easat-10839	175	3	,	,	PUNCT
easat-10839	175	4	tsr	tsr	PROPN
easat-10839	175	5	is	be	AUX
easat-10839	175	6	one	one	NUM
easat-10839	175	7	of	of	ADP
easat-10839	175	8	the	the	DET
easat-10839	175	9	significant	significant	ADJ
easat-10839	175	10	prognostic	prognostic	ADJ
easat-10839	175	11	factors	factor	NOUN
easat-10839	175	12	in	in	ADP
easat-10839	175	13	colorectal	colorectal	ADJ
easat-10839	175	14	cancer	cancer	NOUN
easat-10839	175	15	,	,	PUNCT
easat-10839	175	16	with	with	ADP
easat-10839	175	17	a	a	DET
easat-10839	175	18	p	p	NOUN
easat-10839	175	19	-	-	PUNCT
easat-10839	175	20	value	value	NOUN
easat-10839	175	21	of	of	ADP
easat-10839	175	22	0.028	0.028	NUM
easat-10839	175	23	.	.	PUNCT
easat-10839	176	1	for	for	ADP
easat-10839	176	2	further	further	ADJ
easat-10839	176	3	analysis	analysis	NOUN
easat-10839	176	4	,	,	PUNCT
easat-10839	176	5	the	the	DET
easat-10839	176	6	two	two	NUM
easat-10839	176	7	class	class	NOUN
easat-10839	176	8	categories	category	NOUN
easat-10839	176	9	,	,	PUNCT
easat-10839	176	10	low	low	ADJ
easat-10839	176	11	-	-	PUNCT
easat-10839	176	12	tsr	tsr	NOUN
easat-10839	176	13	and	and	CCONJ
easat-10839	176	14	high	high	ADJ
easat-10839	176	15	-	-	PUNCT
easat-10839	176	16	tsr	tsr	NOUN
easat-10839	176	17	,	,	PUNCT
easat-10839	176	18	will	will	AUX
easat-10839	176	19	be	be	AUX
easat-10839	176	20	determined	determine	VERB
easat-10839	176	21	to	to	PART
easat-10839	176	22	assess	assess	VERB
easat-10839	176	23	whether	whether	SCONJ
easat-10839	176	24	both	both	DET
easat-10839	176	25	categories	category	NOUN
easat-10839	176	26	have	have	VERB
easat-10839	176	27	a	a	DET
easat-10839	176	28	significant	significant	ADJ
easat-10839	176	29	difference	difference	NOUN
easat-10839	176	30	in	in	ADP
easat-10839	176	31	patient	patient	ADJ
easat-10839	176	32	survival	survival	NOUN
easat-10839	176	33	prediction	prediction	NOUN
easat-10839	176	34	,	,	PUNCT
easat-10839	176	35	as	as	SCONJ
easat-10839	176	36	shown	show	VERB
easat-10839	176	37	in	in	ADP
easat-10839	176	38	figure	figure	NOUN
easat-10839	176	39	8	8	NUM
easat-10839	176	40	.	.	PUNCT
easat-10839	177	1	the	the	DET
easat-10839	177	2	tsr=1	tsr=1	NOUN
easat-10839	177	3	and	and	CCONJ
easat-10839	177	4	tsr=0	tsr=0	NOUN
easat-10839	177	5	refer	refer	VERB
easat-10839	177	6	to	to	ADP
easat-10839	177	7	high	high	ADJ
easat-10839	177	8	tsr	tsr	PROPN
easat-10839	177	9	and	and	CCONJ
easat-10839	177	10	low	low	ADJ
easat-10839	177	11	tsr	tsr	PROPN
easat-10839	177	12	,	,	PUNCT
easat-10839	177	13	respectively	respectively	ADV
easat-10839	177	14	.	.	PUNCT
easat-10839	178	1	the	the	DET
easat-10839	178	2	results	result	NOUN
easat-10839	178	3	show	show	VERB
easat-10839	178	4	that	that	SCONJ
easat-10839	178	5	the	the	DET
easat-10839	178	6	two	two	NUM
easat-10839	178	7	classes	class	NOUN
easat-10839	178	8	have	have	VERB
easat-10839	178	9	very	very	ADV
easat-10839	178	10	different	different	ADJ
easat-10839	178	11	survival	survival	NOUN
easat-10839	178	12	probabilities	probability	NOUN
easat-10839	178	13	,	,	PUNCT
easat-10839	178	14	with	with	SCONJ
easat-10839	178	15	the	the	DET
easat-10839	178	16	low	low	ADJ
easat-10839	178	17	tsr	tsr	PROPN
easat-10839	178	18	tending	tending	NOUN
easat-10839	178	19	to	to	PART
easat-10839	178	20	have	have	VERB
easat-10839	178	21	a	a	DET
easat-10839	178	22	higher	high	ADJ
easat-10839	178	23	probability	probability	NOUN
easat-10839	178	24	than	than	ADP
easat-10839	178	25	the	the	DET
easat-10839	178	26	high	high	ADJ
easat-10839	178	27	tsr	tsr	PROPN
easat-10839	178	28	.	.	PUNCT
easat-10839	179	1	thus	thus	ADV
easat-10839	179	2	,	,	PUNCT
easat-10839	179	3	the	the	DET
easat-10839	179	4	tsr	tsr	PROPN
easat-10839	179	5	values	value	NOUN
easat-10839	179	6	identified	identify	VERB
easat-10839	179	7	by	by	ADP
easat-10839	179	8	deep	deep	ADJ
easat-10839	179	9	transfer	transfer	NOUN
easat-10839	179	10	learning	learning	NOUN
easat-10839	179	11	play	play	VERB
easat-10839	179	12	an	an	DET
easat-10839	179	13	important	important	ADJ
easat-10839	179	14	role	role	NOUN
easat-10839	179	15	in	in	ADP
easat-10839	179	16	patient	patient	ADJ
easat-10839	179	17	survival	survival	NOUN
easat-10839	179	18	prediction	prediction	NOUN
easat-10839	179	19	.	.	PUNCT
easat-10839	180	1	figure	figure	NOUN
easat-10839	180	2	8	8	NUM
easat-10839	180	3	.	.	PUNCT
easat-10839	181	1	patient	patient	ADJ
easat-10839	181	2	survival	survival	NOUN
easat-10839	181	3	prediction	prediction	NOUN
easat-10839	181	4	on	on	ADP
easat-10839	181	5	high	high	ADJ
easat-10839	181	6	-	-	PUNCT
easat-10839	181	7	tsr(1	tsr(1	VERB
easat-10839	181	8	)	)	PUNCT
easat-10839	181	9	and	and	CCONJ
easat-10839	181	10	low	low	ADJ
easat-10839	181	11	-	-	PUNCT
easat-10839	181	12	tsr	tsr	NOUN
easat-10839	181	13	(	(	PUNCT
easat-10839	181	14	0	0	NUM
easat-10839	181	15	)	)	PUNCT
easat-10839	181	16	.	.	PUNCT
easat-10839	182	1	7	7	X
easat-10839	182	2	.	.	X
easat-10839	182	3	conclusions	conclusion	NOUN
easat-10839	182	4	the	the	DET
easat-10839	182	5	applications	application	NOUN
easat-10839	182	6	of	of	ADP
easat-10839	182	7	various	various	ADJ
easat-10839	182	8	architectures	architecture	NOUN
easat-10839	182	9	of	of	ADP
easat-10839	182	10	convolutional	convolutional	ADJ
easat-10839	182	11	neural	neural	ADJ
easat-10839	182	12	networks	network	NOUN
easat-10839	182	13	(	(	PUNCT
easat-10839	182	14	cnn	cnn	PROPN
easat-10839	182	15	)	)	PUNCT
easat-10839	182	16	,	,	PUNCT
easat-10839	182	17	such	such	ADJ
easat-10839	182	18	as	as	ADP
easat-10839	182	19	deep	deep	ADJ
easat-10839	182	20	residual	residual	ADJ
easat-10839	182	21	networks	network	NOUN
easat-10839	182	22	(	(	PUNCT
easat-10839	182	23	resnet	resnet	NOUN
easat-10839	182	24	)	)	PUNCT
easat-10839	182	25	,	,	PUNCT
easat-10839	182	26	inception	inception	NOUN
easat-10839	182	27	networks	network	NOUN
easat-10839	182	28	,	,	PUNCT
easat-10839	182	29	densely	densely	ADV
easat-10839	182	30	connected	connect	VERB
easat-10839	182	31	convolutional	convolutional	ADJ
easat-10839	182	32	networks	network	NOUN
easat-10839	182	33	(	(	PUNCT
easat-10839	182	34	densenet	densenet	NOUN
easat-10839	182	35	)	)	PUNCT
easat-10839	182	36	,	,	PUNCT
easat-10839	182	37	mobilenet	mobilenet	NOUN
easat-10839	182	38	,	,	PUNCT
easat-10839	182	39	and	and	CCONJ
easat-10839	182	40	efficientnet	efficientnet	NOUN
easat-10839	182	41	,	,	PUNCT
easat-10839	182	42	for	for	ADP
easat-10839	182	43	colorectal	colorectal	ADJ
easat-10839	182	44	cancer	cancer	NOUN
easat-10839	182	45	image	image	NOUN
easat-10839	182	46	classification	classification	NOUN
easat-10839	182	47	and	and	CCONJ
easat-10839	182	48	automated	automate	VERB
easat-10839	182	49	tumor	tumor	NOUN
easat-10839	182	50	-	-	PUNCT
easat-10839	182	51	stroma	stroma	NOUN
easat-10839	182	52	ratio	ratio	NOUN
easat-10839	182	53	(	(	PUNCT
easat-10839	182	54	tsr	tsr	PROPN
easat-10839	182	55	)	)	PUNCT
easat-10839	182	56	prediction	prediction	NOUN
easat-10839	182	57	have	have	AUX
easat-10839	182	58	been	be	AUX
easat-10839	182	59	successfully	successfully	ADV
easat-10839	182	60	implemented	implement	VERB
easat-10839	182	61	.	.	PUNCT
easat-10839	183	1	in	in	ADP
easat-10839	183	2	the	the	DET
easat-10839	183	3	proposed	propose	VERB
easat-10839	183	4	framework	framework	NOUN
easat-10839	183	5	,	,	PUNCT
easat-10839	183	6	all	all	DET
easat-10839	183	7	the	the	DET
easat-10839	183	8	base	base	NOUN
easat-10839	183	9	models	model	NOUN
easat-10839	183	10	were	be	AUX
easat-10839	183	11	trained	train	VERB
easat-10839	183	12	using	use	VERB
easat-10839	183	13	the	the	DET
easat-10839	183	14	optuna	optuna	ADJ
easat-10839	183	15	hyperparameter	hyperparameter	NOUN
easat-10839	183	16	optimization	optimization	NOUN
easat-10839	183	17	framework	framework	NOUN
easat-10839	183	18	,	,	PUNCT
easat-10839	183	19	which	which	PRON
easat-10839	183	20	is	be	AUX
easat-10839	183	21	flexible	flexible	ADJ
easat-10839	183	22	,	,	PUNCT
easat-10839	183	23	modular	modular	ADJ
easat-10839	183	24	,	,	PUNCT
easat-10839	183	25	and	and	CCONJ
easat-10839	183	26	easy	easy	ADJ
easat-10839	183	27	to	to	PART
easat-10839	183	28	combine	combine	VERB
easat-10839	183	29	with	with	ADP
easat-10839	183	30	transfer	transfer	NOUN
easat-10839	183	31	learning	learning	NOUN
easat-10839	183	32	.	.	PUNCT
easat-10839	184	1	results	result	NOUN
easat-10839	184	2	show	show	VERB
easat-10839	184	3	that	that	SCONJ
easat-10839	184	4	the	the	DET
easat-10839	184	5	optimized	optimize	VERB
easat-10839	184	6	resnet	resnet	NOUN
easat-10839	184	7	base	base	NOUN
easat-10839	184	8	model	model	NOUN
easat-10839	184	9	outperformed	outperform	VERB
easat-10839	184	10	the	the	DET
easat-10839	184	11	other	other	ADJ
easat-10839	184	12	base	base	NOUN
easat-10839	184	13	models	model	NOUN
easat-10839	184	14	using	use	VERB
easat-10839	184	15	optuna	optuna	PROPN
easat-10839	184	16	hyperparameter	hyperparameter	NOUN
easat-10839	184	17	optimization	optimization	NOUN
easat-10839	184	18	.	.	PUNCT
easat-10839	185	1	the	the	DET
easat-10839	185	2	classification	classification	NOUN
easat-10839	185	3	accuracy	accuracy	NOUN
easat-10839	185	4	of	of	ADP
easat-10839	185	5	the	the	DET
easat-10839	185	6	optimized	optimize	VERB
easat-10839	185	7	resnet50	resnet50	NOUN
easat-10839	185	8	base	base	PROPN
easat-10839	185	9	model	model	NOUN
easat-10839	185	10	achieved	achieve	VERB
easat-10839	185	11	more	more	ADJ
easat-10839	185	12	than	than	ADP
easat-10839	185	13	98	98	NUM
easat-10839	185	14	%	%	NOUN
easat-10839	185	15	on	on	ADP
easat-10839	185	16	external	external	ADJ
easat-10839	185	17	test	test	NOUN
easat-10839	185	18	data	datum	NOUN
easat-10839	185	19	.	.	PUNCT
easat-10839	186	1	the	the	DET
easat-10839	186	2	optimized	optimize	VERB
easat-10839	186	3	resnet50	resnet50	NOUN
easat-10839	186	4	is	be	AUX
easat-10839	186	5	used	use	VERB
easat-10839	186	6	to	to	PART
easat-10839	186	7	classify	classify	VERB
easat-10839	186	8	whole	whole	ADJ
easat-10839	186	9	slide	slide	NOUN
easat-10839	186	10	images	image	NOUN
easat-10839	186	11	(	(	PUNCT
easat-10839	186	12	wsi	wsi	NOUN
easat-10839	186	13	)	)	PUNCT
easat-10839	186	14	of	of	ADP
easat-10839	186	15	colorectal	colorectal	ADJ
easat-10839	186	16	patients	patient	NOUN
easat-10839	186	17	,	,	PUNCT
easat-10839	186	18	which	which	PRON
easat-10839	186	19	allows	allow	VERB
easat-10839	186	20	for	for	ADP
easat-10839	186	21	the	the	DET
easat-10839	186	22	prediction	prediction	NOUN
easat-10839	186	23	of	of	ADP
easat-10839	186	24	the	the	DET
easat-10839	186	25	tumor	tumor	NOUN
easat-10839	186	26	-	-	PUNCT
easat-10839	186	27	stroma	stroma	NOUN
easat-10839	186	28	ratio	ratio	NOUN
easat-10839	186	29	(	(	PUNCT
easat-10839	186	30	tsr	tsr	PROPN
easat-10839	186	31	)	)	PUNCT
easat-10839	186	32	.	.	PUNCT
easat-10839	187	1	resnet50	resnet50	PROPN
easat-10839	187	2	was	be	AUX
easat-10839	187	3	applied	apply	VERB
easat-10839	187	4	to	to	ADP
easat-10839	187	5	222	222	NUM
easat-10839	187	6	wsi	wsi	NOUN
easat-10839	187	7	patients	patient	NOUN
easat-10839	187	8	,	,	PUNCT
easat-10839	187	9	resulting	result	VERB
easat-10839	187	10	in	in	ADP
easat-10839	187	11	222	222	NUM
easat-10839	187	12	tsr	tsr	PROPN
easat-10839	187	13	values	value	NOUN
easat-10839	187	14	.	.	PUNCT
easat-10839	188	1	these	these	DET
easat-10839	188	2	tsr	tsr	PROPN
easat-10839	188	3	values	value	NOUN
easat-10839	188	4	,	,	PUNCT
easat-10839	188	5	along	along	ADP
easat-10839	188	6	with	with	ADP
easat-10839	188	7	other	other	ADJ
easat-10839	188	8	clinical	clinical	ADJ
easat-10839	188	9	parameters	parameter	NOUN
easat-10839	188	10	such	such	ADJ
easat-10839	188	11	as	as	ADP
easat-10839	188	12	m	m	NOUN
easat-10839	188	13	-	-	NOUN
easat-10839	188	14	stage	stage	NOUN
easat-10839	188	15	,	,	PUNCT
easat-10839	188	16	tstage	tstage	NOUN
easat-10839	188	17	,	,	PUNCT
easat-10839	188	18	age	age	NOUN
easat-10839	188	19	,	,	PUNCT
easat-10839	188	20	and	and	CCONJ
easat-10839	188	21	gender	gender	NOUN
easat-10839	188	22	,	,	PUNCT
easat-10839	188	23	were	be	AUX
easat-10839	188	24	included	include	VERB
easat-10839	188	25	in	in	ADP
easat-10839	188	26	the	the	DET
easat-10839	188	27	cox	cox	PROPN
easat-10839	188	28	proportional	proportional	PROPN
easat-10839	188	29	hazards	hazard	NOUN
easat-10839	188	30	model	model	NOUN
easat-10839	188	31	to	to	PART
easat-10839	188	32	predict	predict	VERB
easat-10839	188	33	patient	patient	ADJ
easat-10839	188	34	survival	survival	NOUN
easat-10839	188	35	.	.	PUNCT
easat-10839	189	1	the	the	DET
easat-10839	189	2	results	result	NOUN
easat-10839	189	3	indicate	indicate	VERB
easat-10839	189	4	that	that	SCONJ
easat-10839	189	5	tsr	tsr	PROPN
easat-10839	189	6	is	be	AUX
easat-10839	189	7	a	a	DET
easat-10839	189	8	prognostic	prognostic	ADJ
easat-10839	189	9	factor	factor	NOUN
easat-10839	189	10	in	in	ADP
easat-10839	189	11	colorectal	colorectal	ADJ
easat-10839	189	12	cancer	cancer	NOUN
easat-10839	189	13	.	.	PUNCT
easat-10839	190	1	overall	overall	ADV
easat-10839	190	2	,	,	PUNCT
easat-10839	190	3	the	the	DET
easat-10839	190	4	tsr	tsr	PROPN
easat-10839	190	5	levels	level	NOUN
easat-10839	190	6	,	,	PUNCT
easat-10839	190	7	categorized	categorize	VERB
easat-10839	190	8	as	as	ADP
easat-10839	190	9	high	high	ADJ
easat-10839	190	10	-	-	PUNCT
easat-10839	190	11	tsr	tsr	NOUN
easat-10839	190	12	and	and	CCONJ
easat-10839	190	13	low	low	ADJ
easat-10839	190	14	-	-	PUNCT
easat-10839	190	15	tsr	tsr	NOUN
easat-10839	190	16	,	,	PUNCT
easat-10839	190	17	are	be	AUX
easat-10839	190	18	associated	associate	VERB
easat-10839	190	19	with	with	ADP
easat-10839	190	20	different	different	ADJ
easat-10839	190	21	probabilities	probability	NOUN
easat-10839	190	22	of	of	ADP
easat-10839	190	23	patient	patient	ADJ
easat-10839	190	24	survival	survival	NOUN
easat-10839	190	25	.	.	PUNCT
easat-10839	191	1	in	in	ADP
easat-10839	191	2	future	future	ADJ
easat-10839	191	3	works	work	NOUN
easat-10839	191	4	,	,	PUNCT
easat-10839	191	5	this	this	DET
easat-10839	191	6	automated	automate	VERB
easat-10839	191	7	tsr	tsr	PROPN
easat-10839	191	8	approach	approach	NOUN
easat-10839	191	9	can	can	AUX
easat-10839	191	10	be	be	AUX
easat-10839	191	11	compared	compare	VERB
easat-10839	191	12	using	use	VERB
easat-10839	191	13	the	the	DET
easat-10839	191	14	real	real	ADJ
easat-10839	191	15	data	data	NOUN
easat-10839	191	16	sets	set	NOUN
easat-10839	191	17	that	that	PRON
easat-10839	191	18	are	be	AUX
easat-10839	191	19	created	create	VERB
easat-10839	191	20	by	by	ADP
easat-10839	191	21	pathologists	pathologist	NOUN
easat-10839	191	22	.	.	PUNCT
easat-10839	192	1	those	those	DET
easat-10839	192	2	comparisons	comparison	NOUN
easat-10839	192	3	should	should	AUX
easat-10839	192	4	be	be	AUX
easat-10839	192	5	carried	carry	VERB
easat-10839	192	6	out	out	ADP
easat-10839	192	7	carefully	carefully	ADV
easat-10839	192	8	,	,	PUNCT
easat-10839	192	9	which	which	PRON
easat-10839	192	10	depend	depend	VERB
easat-10839	192	11	on	on	ADP
easat-10839	192	12	many	many	ADJ
easat-10839	192	13	considerations	consideration	NOUN
easat-10839	192	14	such	such	ADJ
easat-10839	192	15	as	as	ADP
easat-10839	192	16	the	the	DET
easat-10839	192	17	quality	quality	NOUN
easat-10839	192	18	of	of	ADP
easat-10839	192	19	images	image	NOUN
easat-10839	192	20	,	,	PUNCT
easat-10839	192	21	the	the	DET
easat-10839	192	22	structure	structure	NOUN
easat-10839	192	23	of	of	ADP
easat-10839	192	24	images	image	NOUN
easat-10839	192	25	,	,	PUNCT
easat-10839	192	26	and	and	CCONJ
easat-10839	192	27	the	the	DET
easat-10839	192	28	similarity	similarity	NOUN
easat-10839	192	29	of	of	ADP
easat-10839	192	30	the	the	DET
easat-10839	192	31	environment	environment	NOUN
easat-10839	192	32	when	when	SCONJ
easat-10839	192	33	the	the	DET
easat-10839	192	34	images	image	NOUN
easat-10839	192	35	are	be	AUX
easat-10839	192	36	obtained	obtain	VERB
easat-10839	192	37	.	.	PUNCT
easat-10839	192	38	260	260	NUM
easat-10839	192	39	edelweiss	edelweiss	PROPN
easat-10839	192	40	applied	apply	VERB
easat-10839	192	41	science	science	NOUN
easat-10839	192	42	and	and	CCONJ
easat-10839	192	43	technology	technology	NOUN
easat-10839	192	44	issn	issn	PROPN
easat-10839	192	45	:	:	PUNCT
easat-10839	192	46	2576	2576	NUM
easat-10839	192	47	-	-	SYM
easat-10839	192	48	8484	8484	NUM
easat-10839	192	49	vol	vol	NOUN
easat-10839	192	50	.	.	PROPN
easat-10839	193	1	9	9	NUM
easat-10839	193	2	,	,	PUNCT
easat-10839	193	3	no	no	INTJ
easat-10839	193	4	.	.	NOUN
easat-10839	193	5	11	11	NUM
easat-10839	193	6	:	:	PUNCT
easat-10839	193	7	249	249	NUM
easat-10839	193	8	-	-	SYM
easat-10839	193	9	261	261	NUM
easat-10839	193	10	,	,	PUNCT
easat-10839	193	11	2025	2025	NUM
easat-10839	193	12	doi	doi	NOUN
easat-10839	193	13	:	:	PUNCT
easat-10839	193	14	10.55214/2576	10.55214/2576	NUM
easat-10839	193	15	-	-	SYM
easat-10839	193	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	193	17	©	©	ADP
easat-10839	193	18	2025	2025	NUM
easat-10839	193	19	by	by	ADP
easat-10839	193	20	the	the	DET
easat-10839	193	21	authors	author	NOUN
easat-10839	193	22	;	;	PUNCT
easat-10839	194	1	licensee	licensee	PROPN
easat-10839	194	2	learning	learn	VERB
easat-10839	194	3	gate	gate	NOUN
easat-10839	194	4	transparency	transparency	NOUN
easat-10839	194	5	:	:	PUNCT
easat-10839	194	6	the	the	DET
easat-10839	194	7	authors	author	NOUN
easat-10839	194	8	confirm	confirm	VERB
easat-10839	194	9	that	that	SCONJ
easat-10839	194	10	the	the	DET
easat-10839	194	11	manuscript	manuscript	NOUN
easat-10839	194	12	is	be	AUX
easat-10839	194	13	an	an	DET
easat-10839	194	14	honest	honest	ADJ
easat-10839	194	15	,	,	PUNCT
easat-10839	194	16	accurate	accurate	ADJ
easat-10839	194	17	,	,	PUNCT
easat-10839	194	18	and	and	CCONJ
easat-10839	194	19	transparent	transparent	ADJ
easat-10839	194	20	account	account	NOUN
easat-10839	194	21	of	of	ADP
easat-10839	194	22	the	the	DET
easat-10839	194	23	study	study	NOUN
easat-10839	194	24	;	;	PUNCT
easat-10839	194	25	that	that	SCONJ
easat-10839	194	26	no	no	DET
easat-10839	194	27	vital	vital	ADJ
easat-10839	194	28	features	feature	NOUN
easat-10839	194	29	of	of	ADP
easat-10839	194	30	the	the	DET
easat-10839	194	31	study	study	NOUN
easat-10839	194	32	have	have	AUX
easat-10839	194	33	been	be	AUX
easat-10839	194	34	omitted	omit	VERB
easat-10839	194	35	;	;	PUNCT
easat-10839	194	36	and	and	CCONJ
easat-10839	194	37	that	that	SCONJ
easat-10839	194	38	any	any	DET
easat-10839	194	39	discrepancies	discrepancy	NOUN
easat-10839	194	40	from	from	ADP
easat-10839	194	41	the	the	DET
easat-10839	194	42	study	study	NOUN
easat-10839	194	43	as	as	SCONJ
easat-10839	194	44	planned	plan	VERB
easat-10839	194	45	have	have	AUX
easat-10839	194	46	been	be	AUX
easat-10839	194	47	explained	explain	VERB
easat-10839	194	48	.	.	PUNCT
easat-10839	195	1	this	this	DET
easat-10839	195	2	study	study	NOUN
easat-10839	195	3	followed	follow	VERB
easat-10839	195	4	all	all	DET
easat-10839	195	5	ethical	ethical	ADJ
easat-10839	195	6	practices	practice	NOUN
easat-10839	195	7	during	during	ADP
easat-10839	195	8	writing	writing	NOUN
easat-10839	195	9	.	.	PUNCT
easat-10839	196	1	acknowledgement	acknowledgement	NOUN
easat-10839	196	2	:	:	PUNCT
easat-10839	196	3	we	we	PRON
easat-10839	196	4	are	be	AUX
easat-10839	196	5	grateful	grateful	ADJ
easat-10839	196	6	to	to	ADP
easat-10839	196	7	the	the	DET
easat-10839	196	8	ministry	ministry	PROPN
easat-10839	196	9	of	of	ADP
easat-10839	196	10	education	education	PROPN
easat-10839	196	11	,	,	PUNCT
easat-10839	196	12	research	research	NOUN
easat-10839	196	13	,	,	PUNCT
easat-10839	196	14	and	and	CCONJ
easat-10839	196	15	culture	culture	NOUN
easat-10839	196	16	of	of	ADP
easat-10839	196	17	the	the	DET
easat-10839	196	18	republic	republic	NOUN
easat-10839	196	19	of	of	ADP
easat-10839	196	20	indonesia	indonesia	PROPN
easat-10839	196	21	for	for	ADP
easat-10839	196	22	providing	provide	VERB
easat-10839	196	23	financial	financial	ADJ
easat-10839	196	24	support	support	NOUN
easat-10839	196	25	using	use	VERB
easat-10839	196	26	fundamental	fundamental	ADJ
easat-10839	196	27	research	research	NOUN
easat-10839	196	28	grant	grant	NOUN
easat-10839	196	29	124	124	NUM
easat-10839	196	30	/	/	SYM
easat-10839	196	31	c3	c3	PROPN
easat-10839	196	32	/	/	SYM
easat-10839	196	33	dt.05.00	dt.05.00	PROPN
easat-10839	196	34	/	/	SYM
easat-10839	196	35	pl/2025	pl/2025	NOUN
easat-10839	196	36	.	.	PUNCT
easat-10839	197	1	copyright	copyright	NOUN
easat-10839	197	2	:	:	PUNCT
easat-10839	197	3	©	©	PROPN
easat-10839	197	4	2025	2025	NUM
easat-10839	197	5	by	by	ADP
easat-10839	197	6	the	the	DET
easat-10839	197	7	authors	author	NOUN
easat-10839	197	8	.	.	PUNCT
easat-10839	198	1	this	this	DET
easat-10839	198	2	article	article	NOUN
easat-10839	198	3	is	be	AUX
easat-10839	198	4	an	an	DET
easat-10839	198	5	open	open	ADJ
easat-10839	198	6	-	-	PUNCT
easat-10839	198	7	access	access	NOUN
easat-10839	198	8	article	article	NOUN
easat-10839	198	9	distributed	distribute	VERB
easat-10839	198	10	under	under	ADP
easat-10839	198	11	the	the	DET
easat-10839	198	12	terms	term	NOUN
easat-10839	198	13	and	and	CCONJ
easat-10839	198	14	conditions	condition	NOUN
easat-10839	198	15	of	of	ADP
easat-10839	198	16	the	the	DET
easat-10839	198	17	creative	creative	ADJ
easat-10839	198	18	commons	common	NOUN
easat-10839	198	19	attribution	attribution	NOUN
easat-10839	198	20	(	(	PUNCT
easat-10839	198	21	cc	cc	NOUN
easat-10839	198	22	by	by	ADP
easat-10839	198	23	)	)	PUNCT
easat-10839	198	24	license	license	NOUN
easat-10839	198	25	(	(	PUNCT
easat-10839	198	26	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-10839	198	27	)	)	PUNCT
easat-10839	198	28	.	.	PUNCT
easat-10839	199	1	references	reference	NOUN
easat-10839	199	2	[	[	X
easat-10839	199	3	1	1	NUM
easat-10839	199	4	]	]	X
easat-10839	199	5	colorectal	colorectal	ADJ
easat-10839	199	6	cancer	cancer	NOUN
easat-10839	199	7	alliance	alliance	NOUN
easat-10839	199	8	,	,	PUNCT
easat-10839	199	9	"	"	PUNCT
easat-10839	199	10	colorectal	colorectal	ADJ
easat-10839	199	11	cancer	cancer	NOUN
easat-10839	199	12	information	information	NOUN
easat-10839	199	13	,	,	PUNCT
easat-10839	199	14	"	"	PUNCT
easat-10839	199	15	2025	2025	NUM
easat-10839	199	16	.	.	PUNCT
easat-10839	200	1	https://colorectalcancer.org/	https://colorectalcancer.org/	PRON
easat-10839	200	2	[	[	X
easat-10839	200	3	2	2	NUM
easat-10839	200	4	]	]	PUNCT
easat-10839	200	5	world	world	NOUN
easat-10839	200	6	cancer	cancer	NOUN
easat-10839	200	7	research	research	PROPN
easat-10839	200	8	fund	fund	PROPN
easat-10839	200	9	/	/	SYM
easat-10839	200	10	american	american	PROPN
easat-10839	200	11	institute	institute	PROPN
easat-10839	200	12	for	for	ADP
easat-10839	200	13	cancer	cancer	NOUN
easat-10839	200	14	research	research	NOUN
easat-10839	200	15	,	,	PUNCT
easat-10839	200	16	"	"	PUNCT
easat-10839	200	17	diet	diet	NOUN
easat-10839	200	18	,	,	PUNCT
easat-10839	200	19	nutrition	nutrition	NOUN
easat-10839	200	20	,	,	PUNCT
easat-10839	200	21	physical	physical	ADJ
easat-10839	200	22	activity	activity	NOUN
easat-10839	200	23	and	and	CCONJ
easat-10839	200	24	cancer	cancer	NOUN
easat-10839	200	25	:	:	PUNCT
easat-10839	200	26	a	a	DET
easat-10839	200	27	global	global	ADJ
easat-10839	200	28	perspective	perspective	NOUN
easat-10839	200	29	.	.	PUNCT
easat-10839	201	1	continuous	continuous	ADJ
easat-10839	201	2	update	update	NOUN
easat-10839	201	3	project	project	NOUN
easat-10839	201	4	expert	expert	NOUN
easat-10839	201	5	report	report	NOUN
easat-10839	201	6	,	,	PUNCT
easat-10839	201	7	"	"	PUNCT
easat-10839	201	8	2018	2018	NUM
easat-10839	201	9	.	.	PUNCT
easat-10839	202	1	https://www.wcrf.org/diet-activity-andcancer/	https://www.wcrf.org/diet-activity-andcancer/	VERB
easat-10839	203	1	[	[	X
easat-10839	203	2	3	3	X
easat-10839	203	3	]	]	PUNCT
easat-10839	203	4	f.	f.	PROPN
easat-10839	203	5	prezja	prezja	PROPN
easat-10839	203	6	et	et	PROPN
easat-10839	203	7	al	al	PROPN
easat-10839	203	8	.	.	PROPN
easat-10839	203	9	,	,	PUNCT
easat-10839	203	10	"	"	PUNCT
easat-10839	203	11	improved	improved	ADJ
easat-10839	203	12	accuracy	accuracy	NOUN
easat-10839	203	13	in	in	ADP
easat-10839	203	14	colorectal	colorectal	ADJ
easat-10839	203	15	cancer	cancer	NOUN
easat-10839	203	16	tissue	tissue	NOUN
easat-10839	203	17	decomposition	decomposition	NOUN
easat-10839	203	18	through	through	ADP
easat-10839	203	19	refinement	refinement	NOUN
easat-10839	203	20	of	of	ADP
easat-10839	203	21	established	establish	VERB
easat-10839	203	22	deep	deep	ADJ
easat-10839	203	23	learning	learning	NOUN
easat-10839	203	24	solutions	solution	NOUN
easat-10839	203	25	,	,	PUNCT
easat-10839	203	26	"	"	PUNCT
easat-10839	203	27	scientific	scientific	ADJ
easat-10839	203	28	reports	report	NOUN
easat-10839	203	29	,	,	PUNCT
easat-10839	203	30	vol	vol	NOUN
easat-10839	203	31	.	.	PROPN
easat-10839	203	32	13	13	NUM
easat-10839	203	33	,	,	PUNCT
easat-10839	203	34	p.	p.	NOUN
easat-10839	203	35	15879	15879	NUM
easat-10839	203	36	,	,	PUNCT
easat-10839	203	37	2023	2023	NUM
easat-10839	203	38	.	.	PUNCT
easat-10839	204	1	https://doi.org/10.1038/s41598-023-42357-x	https://doi.org/10.1038/s41598-023-42357-x	NOUN
easat-10839	205	1	[	[	X
easat-10839	205	2	4	4	X
easat-10839	205	3	]	]	PUNCT
easat-10839	205	4	s.	s.	PROPN
easat-10839	205	5	h.	h.	PROPN
easat-10839	205	6	lee	lee	PROPN
easat-10839	205	7	and	and	CCONJ
easat-10839	205	8	h.-j	h.-j	PROPN
easat-10839	205	9	.	.	PUNCT
easat-10839	206	1	jang	jang	PROPN
easat-10839	206	2	,	,	PUNCT
easat-10839	206	3	"	"	PUNCT
easat-10839	206	4	deep	deep	ADJ
easat-10839	206	5	learning	learning	NOUN
easat-10839	206	6	-	-	PUNCT
easat-10839	206	7	based	base	VERB
easat-10839	206	8	prediction	prediction	NOUN
easat-10839	206	9	of	of	ADP
easat-10839	206	10	molecular	molecular	ADJ
easat-10839	206	11	cancer	cancer	NOUN
easat-10839	206	12	biomarkers	biomarker	NOUN
easat-10839	206	13	from	from	ADP
easat-10839	206	14	tissue	tissue	NOUN
easat-10839	206	15	slides	slide	NOUN
easat-10839	206	16	:	:	PUNCT
easat-10839	206	17	a	a	DET
easat-10839	206	18	new	new	ADJ
easat-10839	206	19	tool	tool	NOUN
easat-10839	206	20	for	for	ADP
easat-10839	206	21	precision	precision	NOUN
easat-10839	206	22	oncology	oncology	NOUN
easat-10839	206	23	,	,	PUNCT
easat-10839	206	24	"	"	PUNCT
easat-10839	206	25	clinical	clinical	ADJ
easat-10839	206	26	and	and	CCONJ
easat-10839	206	27	molecular	molecular	ADJ
easat-10839	206	28	hepatology	hepatology	NOUN
easat-10839	206	29	,	,	PUNCT
easat-10839	206	30	vol	vol	NOUN
easat-10839	206	31	.	.	PROPN
easat-10839	206	32	28	28	NUM
easat-10839	206	33	,	,	PUNCT
easat-10839	206	34	no	no	INTJ
easat-10839	206	35	.	.	NOUN
easat-10839	206	36	4	4	NUM
easat-10839	206	37	,	,	PUNCT
easat-10839	206	38	p.	p.	NOUN
easat-10839	206	39	754	754	NUM
easat-10839	206	40	,	,	PUNCT
easat-10839	206	41	2022	2022	NUM
easat-10839	206	42	.	.	PUNCT
easat-10839	207	1	https://doi.org/10.3350/cmh.2021.0394	https://doi.org/10.3350/cmh.2021.0394	NOUN
easat-10839	207	2	[	[	X
easat-10839	207	3	5	5	NUM
easat-10839	207	4	]	]	PUNCT
easat-10839	207	5	j.	j.	PROPN
easat-10839	207	6	n.	n.	PROPN
easat-10839	207	7	kather	kather	PROPN
easat-10839	207	8	et	et	PROPN
easat-10839	207	9	al	al	PROPN
easat-10839	207	10	.	.	PROPN
easat-10839	207	11	,	,	PUNCT
easat-10839	207	12	"	"	PUNCT
easat-10839	207	13	predicting	predict	VERB
easat-10839	207	14	survival	survival	NOUN
easat-10839	207	15	from	from	ADP
easat-10839	207	16	colorectal	colorectal	ADJ
easat-10839	207	17	cancer	cancer	NOUN
easat-10839	207	18	histology	histology	NOUN
easat-10839	207	19	slides	slide	VERB
easat-10839	207	20	using	use	VERB
easat-10839	207	21	deep	deep	ADJ
easat-10839	207	22	learning	learning	NOUN
easat-10839	207	23	:	:	PUNCT
easat-10839	207	24	a	a	DET
easat-10839	207	25	retrospective	retrospective	ADJ
easat-10839	207	26	multicenter	multicenter	NOUN
easat-10839	207	27	study	study	NOUN
easat-10839	207	28	,	,	PUNCT
easat-10839	207	29	"	"	PUNCT
easat-10839	207	30	plos	plos	PROPN
easat-10839	207	31	medicine	medicine	NOUN
easat-10839	207	32	,	,	PUNCT
easat-10839	207	33	vol	vol	NOUN
easat-10839	207	34	.	.	PROPN
easat-10839	207	35	16	16	NUM
easat-10839	207	36	,	,	PUNCT
easat-10839	207	37	no	no	INTJ
easat-10839	207	38	.	.	NOUN
easat-10839	207	39	1	1	NUM
easat-10839	207	40	,	,	PUNCT
easat-10839	207	41	p.	p.	NOUN
easat-10839	207	42	e1002730	e1002730	NOUN
easat-10839	207	43	,	,	PUNCT
easat-10839	207	44	2019	2019	NUM
easat-10839	207	45	.	.	PUNCT
easat-10839	208	1	https://doi.org/10.1371/journal.pmed.1002730	https://doi.org/10.1371/journal.pmed.1002730	X
easat-10839	208	2	[	[	X
easat-10839	208	3	6	6	NUM
easat-10839	208	4	]	]	PUNCT
easat-10839	208	5	m.	m.	PROPN
easat-10839	208	6	lee	lee	PROPN
easat-10839	208	7	,	,	PUNCT
easat-10839	208	8	"	"	PUNCT
easat-10839	208	9	recent	recent	ADJ
easat-10839	208	10	advancements	advancement	NOUN
easat-10839	208	11	in	in	ADP
easat-10839	208	12	deep	deep	ADJ
easat-10839	208	13	learning	learning	NOUN
easat-10839	208	14	using	use	VERB
easat-10839	208	15	whole	whole	ADJ
easat-10839	208	16	slide	slide	NOUN
easat-10839	208	17	imaging	imaging	NOUN
easat-10839	208	18	for	for	ADP
easat-10839	208	19	cancer	cancer	NOUN
easat-10839	208	20	prognosis	prognosis	NOUN
easat-10839	208	21	,	,	PUNCT
easat-10839	208	22	"	"	PUNCT
easat-10839	208	23	bioengineering	bioengineering	NOUN
easat-10839	208	24	,	,	PUNCT
easat-10839	208	25	vol	vol	NOUN
easat-10839	208	26	.	.	PROPN
easat-10839	209	1	10	10	NUM
easat-10839	209	2	,	,	PUNCT
easat-10839	209	3	no	no	INTJ
easat-10839	209	4	.	.	NOUN
easat-10839	209	5	8	8	NUM
easat-10839	209	6	,	,	PUNCT
easat-10839	209	7	p.	p.	NOUN
easat-10839	209	8	897	897	NUM
easat-10839	209	9	,	,	PUNCT
easat-10839	209	10	2023	2023	NUM
easat-10839	209	11	.	.	PUNCT
easat-10839	210	1	[	[	X
easat-10839	210	2	7	7	X
easat-10839	210	3	]	]	X
easat-10839	210	4	v.	v.	PROPN
easat-10839	210	5	b.	b.	PROPN
easat-10839	210	6	mathema	mathema	PROPN
easat-10839	210	7	,	,	PUNCT
easat-10839	210	8	p.	p.	PROPN
easat-10839	210	9	sen	sen	PROPN
easat-10839	210	10	,	,	PUNCT
easat-10839	210	11	s.	s.	PROPN
easat-10839	210	12	lamichhane	lamichhane	PROPN
easat-10839	210	13	,	,	PUNCT
easat-10839	210	14	m.	m.	NOUN
easat-10839	210	15	orešič	orešič	PROPN
easat-10839	210	16	,	,	PUNCT
easat-10839	210	17	and	and	CCONJ
easat-10839	210	18	s.	s.	PROPN
easat-10839	210	19	khoomrung	khoomrung	PROPN
easat-10839	210	20	,	,	PUNCT
easat-10839	210	21	"	"	PUNCT
easat-10839	210	22	deep	deep	ADJ
easat-10839	210	23	learning	learning	NOUN
easat-10839	210	24	facilitates	facilitate	VERB
easat-10839	210	25	multi	multi	ADJ
easat-10839	210	26	-	-	ADJ
easat-10839	210	27	data	data	ADJ
easat-10839	210	28	type	type	NOUN
easat-10839	210	29	analysis	analysis	NOUN
easat-10839	210	30	and	and	CCONJ
easat-10839	210	31	predictive	predictive	ADJ
easat-10839	210	32	biomarker	biomarker	NOUN
easat-10839	210	33	discovery	discovery	NOUN
easat-10839	210	34	in	in	ADP
easat-10839	210	35	cancer	cancer	NOUN
easat-10839	210	36	precision	precision	NOUN
easat-10839	210	37	medicine	medicine	NOUN
easat-10839	210	38	,	,	PUNCT
easat-10839	210	39	"	"	PUNCT
easat-10839	210	40	computational	computational	ADJ
easat-10839	210	41	and	and	CCONJ
easat-10839	210	42	structural	structural	ADJ
easat-10839	210	43	biotechnology	biotechnology	NOUN
easat-10839	210	44	journal	journal	NOUN
easat-10839	210	45	,	,	PUNCT
easat-10839	210	46	vol	vol	NOUN
easat-10839	210	47	.	.	PROPN
easat-10839	210	48	21	21	NUM
easat-10839	210	49	,	,	PUNCT
easat-10839	210	50	pp	pp	ADJ
easat-10839	210	51	.	.	PUNCT
easat-10839	211	1	1372	1372	NUM
easat-10839	211	2	-	-	SYM
easat-10839	211	3	1382	1382	NUM
easat-10839	211	4	,	,	PUNCT
easat-10839	211	5	2023	2023	NUM
easat-10839	211	6	.	.	PUNCT
easat-10839	212	1	https://doi.org/10.1016/j.csbj.2023.01.043	https://doi.org/10.1016/j.csbj.2023.01.043	ADJ
easat-10839	212	2	[	[	X
easat-10839	212	3	8	8	NUM
easat-10839	212	4	]	]	PUNCT
easat-10839	212	5	m.	m.	PROPN
easat-10839	212	6	f.	f.	PROPN
easat-10839	212	7	ijaz	ijaz	PROPN
easat-10839	212	8	and	and	CCONJ
easat-10839	212	9	m.	m.	PROPN
easat-10839	212	10	woźniak	woźniak	PROPN
easat-10839	212	11	,	,	PUNCT
easat-10839	212	12	"	"	PUNCT
easat-10839	212	13	recent	recent	ADJ
easat-10839	212	14	advances	advance	NOUN
easat-10839	212	15	in	in	ADP
easat-10839	212	16	deep	deep	ADJ
easat-10839	212	17	learning	learning	NOUN
easat-10839	212	18	and	and	CCONJ
easat-10839	212	19	medical	medical	ADJ
easat-10839	212	20	imaging	imaging	NOUN
easat-10839	212	21	for	for	ADP
easat-10839	212	22	cancer	cancer	NOUN
easat-10839	212	23	treatment	treatment	NOUN
easat-10839	212	24	,	,	PUNCT
easat-10839	212	25	"	"	PUNCT
easat-10839	212	26	vol	vol	NOUN
easat-10839	212	27	.	.	PROPN
easat-10839	212	28	16	16	NUM
easat-10839	212	29	,	,	PUNCT
easat-10839	212	30	ed	ed	NOUN
easat-10839	212	31	:	:	PUNCT
easat-10839	212	32	mdpi	mdpi	NOUN
easat-10839	212	33	,	,	PUNCT
easat-10839	212	34	2024	2024	NUM
easat-10839	212	35	,	,	PUNCT
easat-10839	212	36	p.	p.	NOUN
easat-10839	212	37	700	700	NUM
easat-10839	212	38	.	.	PUNCT
easat-10839	213	1	[	[	X
easat-10839	213	2	9	9	NUM
easat-10839	213	3	]	]	PUNCT
easat-10839	213	4	l.	l.	PROPN
easat-10839	213	5	alzubaidi	alzubaidi	PROPN
easat-10839	213	6	et	et	PROPN
easat-10839	213	7	al	al	PROPN
easat-10839	213	8	.	.	PROPN
easat-10839	213	9	,	,	PUNCT
easat-10839	213	10	"	"	PUNCT
easat-10839	213	11	review	review	NOUN
easat-10839	213	12	of	of	ADP
easat-10839	213	13	deep	deep	ADJ
easat-10839	213	14	learning	learning	NOUN
easat-10839	213	15	:	:	PUNCT
easat-10839	213	16	concepts	concept	NOUN
easat-10839	213	17	,	,	PUNCT
easat-10839	213	18	cnn	cnn	PROPN
easat-10839	213	19	architectures	architecture	NOUN
easat-10839	213	20	,	,	PUNCT
easat-10839	213	21	challenges	challenge	NOUN
easat-10839	213	22	,	,	PUNCT
easat-10839	213	23	applications	application	NOUN
easat-10839	213	24	,	,	PUNCT
easat-10839	213	25	future	future	ADJ
easat-10839	213	26	directions	direction	NOUN
easat-10839	213	27	,	,	PUNCT
easat-10839	213	28	"	"	PUNCT
easat-10839	213	29	journal	journal	NOUN
easat-10839	213	30	of	of	ADP
easat-10839	213	31	big	big	ADJ
easat-10839	213	32	data	datum	NOUN
easat-10839	213	33	,	,	PUNCT
easat-10839	213	34	vol	vol	NOUN
easat-10839	213	35	.	.	PROPN
easat-10839	213	36	8	8	NUM
easat-10839	213	37	,	,	PUNCT
easat-10839	213	38	p.	p.	NOUN
easat-10839	213	39	53	53	NUM
easat-10839	213	40	,	,	PUNCT
easat-10839	213	41	2021	2021	NUM
easat-10839	213	42	.	.	PUNCT
easat-10839	214	1	https://doi.org/10.1186/s40537-021-00444-8	https://doi.org/10.1186/s40537-021-00444-8	NOUN
easat-10839	215	1	[	[	X
easat-10839	215	2	10	10	NUM
easat-10839	215	3	]	]	X
easat-10839	215	4	j.	j.	PROPN
easat-10839	215	5	l.	l.	PROPN
easat-10839	215	6	katzman	katzman	PROPN
easat-10839	215	7	,	,	PUNCT
easat-10839	215	8	u.	u.	PROPN
easat-10839	215	9	shaham	shaham	PROPN
easat-10839	215	10	,	,	PUNCT
easat-10839	215	11	a.	a.	NOUN
easat-10839	215	12	cloninger	cloninger	PROPN
easat-10839	215	13	,	,	PUNCT
easat-10839	215	14	j.	j.	PROPN
easat-10839	215	15	bates	bates	PROPN
easat-10839	215	16	,	,	PUNCT
easat-10839	215	17	t.	t.	PROPN
easat-10839	215	18	jiang	jiang	PROPN
easat-10839	215	19	,	,	PUNCT
easat-10839	215	20	and	and	CCONJ
easat-10839	215	21	y.	y.	PROPN
easat-10839	215	22	kluger	kluger	PROPN
easat-10839	215	23	,	,	PUNCT
easat-10839	215	24	"	"	PUNCT
easat-10839	215	25	deepsurv	deepsurv	NOUN
easat-10839	215	26	:	:	PUNCT
easat-10839	215	27	personalized	personalize	VERB
easat-10839	215	28	treatment	treatment	NOUN
easat-10839	215	29	recommender	recommender	NOUN
easat-10839	215	30	system	system	NOUN
easat-10839	215	31	using	use	VERB
easat-10839	215	32	a	a	DET
easat-10839	215	33	cox	cox	PROPN
easat-10839	215	34	proportional	proportional	PROPN
easat-10839	215	35	hazards	hazard	NOUN
easat-10839	215	36	deep	deep	ADJ
easat-10839	215	37	neural	neural	ADJ
easat-10839	215	38	network	network	NOUN
easat-10839	215	39	,	,	PUNCT
easat-10839	215	40	"	"	PUNCT
easat-10839	215	41	bmc	bmc	PROPN
easat-10839	215	42	medical	medical	ADJ
easat-10839	215	43	research	research	NOUN
easat-10839	215	44	methodology	methodology	NOUN
easat-10839	215	45	,	,	PUNCT
easat-10839	215	46	vol	vol	NOUN
easat-10839	215	47	.	.	PROPN
easat-10839	215	48	18	18	NUM
easat-10839	215	49	,	,	PUNCT
easat-10839	215	50	p.	p.	NOUN
easat-10839	215	51	24	24	NUM
easat-10839	215	52	,	,	PUNCT
easat-10839	215	53	2018	2018	NUM
easat-10839	215	54	.	.	PUNCT
easat-10839	216	1	https://doi.org/10.1186/s12874-018-0482-1	https://doi.org/10.1186/s12874-018-0482-1	NUM
easat-10839	217	1	[	[	X
easat-10839	217	2	11	11	NUM
easat-10839	217	3	]	]	PUNCT
easat-10839	217	4	t.	t.	PROPN
easat-10839	217	5	akiba	akiba	PROPN
easat-10839	217	6	,	,	PUNCT
easat-10839	217	7	s.	s.	PROPN
easat-10839	217	8	sano	sano	PROPN
easat-10839	217	9	,	,	PUNCT
easat-10839	217	10	t.	t.	PROPN
easat-10839	217	11	yanase	yanase	PROPN
easat-10839	217	12	,	,	PUNCT
easat-10839	217	13	t.	t.	PROPN
easat-10839	217	14	ohta	ohta	PROPN
easat-10839	217	15	,	,	PUNCT
easat-10839	217	16	and	and	CCONJ
easat-10839	217	17	m.	m.	PROPN
easat-10839	217	18	koyama	koyama	PROPN
easat-10839	217	19	,	,	PUNCT
easat-10839	217	20	"	"	PUNCT
easat-10839	217	21	optuna	optuna	NOUN
easat-10839	217	22	:	:	PUNCT
easat-10839	217	23	a	a	DET
easat-10839	217	24	next	next	ADJ
easat-10839	217	25	-	-	PUNCT
easat-10839	217	26	generation	generation	NOUN
easat-10839	217	27	hyperparameter	hyperparameter	NOUN
easat-10839	217	28	optimization	optimization	NOUN
easat-10839	217	29	framework	framework	NOUN
easat-10839	217	30	,	,	PUNCT
easat-10839	217	31	"	"	PUNCT
easat-10839	217	32	in	in	ADP
easat-10839	217	33	proceedings	proceeding	NOUN
easat-10839	217	34	of	of	ADP
easat-10839	217	35	the	the	DET
easat-10839	217	36	25th	25th	ADJ
easat-10839	217	37	acm	acm	PROPN
easat-10839	217	38	sigkdd	sigkdd	NOUN
easat-10839	217	39	international	international	ADJ
easat-10839	217	40	conference	conference	NOUN
easat-10839	217	41	on	on	ADP
easat-10839	217	42	knowledge	knowledge	PROPN
easat-10839	217	43	discovery	discovery	PROPN
easat-10839	217	44	&	&	CCONJ
easat-10839	217	45	data	data	PROPN
easat-10839	217	46	mining	mining	NOUN
easat-10839	217	47	,	,	PUNCT
easat-10839	217	48	2019	2019	NUM
easat-10839	217	49	.	.	PUNCT
easat-10839	218	1	[	[	X
easat-10839	218	2	12	12	NUM
easat-10839	218	3	]	]	PUNCT
easat-10839	218	4	m.	m.	NOUN
easat-10839	218	5	a.	a.	PROPN
easat-10839	218	6	smit	smit	PROPN
easat-10839	218	7	et	et	PROPN
easat-10839	218	8	al	al	PROPN
easat-10839	218	9	.	.	PROPN
easat-10839	218	10	,	,	PUNCT
easat-10839	218	11	"	"	PUNCT
easat-10839	218	12	deep	deep	ADJ
easat-10839	218	13	learning	learning	NOUN
easat-10839	218	14	based	base	VERB
easat-10839	218	15	tumor	tumor	NOUN
easat-10839	218	16	–	–	PUNCT
easat-10839	218	17	stroma	stroma	ADJ
easat-10839	218	18	ratio	ratio	NOUN
easat-10839	218	19	scoring	score	VERB
easat-10839	218	20	in	in	ADP
easat-10839	218	21	colon	colon	NOUN
easat-10839	218	22	cancer	cancer	NOUN
easat-10839	218	23	correlates	correlate	VERB
easat-10839	218	24	with	with	ADP
easat-10839	218	25	microscopic	microscopic	ADJ
easat-10839	218	26	assessment	assessment	NOUN
easat-10839	218	27	,	,	PUNCT
easat-10839	218	28	"	"	PUNCT
easat-10839	218	29	journal	journal	NOUN
easat-10839	218	30	of	of	ADP
easat-10839	218	31	pathology	pathology	PROPN
easat-10839	218	32	informatics	informatic	NOUN
easat-10839	218	33	,	,	PUNCT
easat-10839	218	34	vol	vol	NOUN
easat-10839	218	35	.	.	PROPN
easat-10839	218	36	14	14	NUM
easat-10839	218	37	,	,	PUNCT
easat-10839	218	38	p.	p.	NOUN
easat-10839	218	39	100191	100191	NUM
easat-10839	218	40	,	,	PUNCT
easat-10839	218	41	2023	2023	NUM
easat-10839	218	42	.	.	PUNCT
easat-10839	219	1	https://doi.org/10.1016/j.jpi.2023.100191	https://doi.org/10.1016/j.jpi.2023.100191	PUNCT
easat-10839	220	1	[	[	X
easat-10839	220	2	13	13	NUM
easat-10839	220	3	]	]	PUNCT
easat-10839	220	4	j.	j.	PROPN
easat-10839	220	5	gao	gao	PROPN
easat-10839	220	6	,	,	PUNCT
easat-10839	220	7	z.	z.	PROPN
easat-10839	220	8	shen	shen	PROPN
easat-10839	220	9	,	,	PUNCT
easat-10839	220	10	z.	z.	PROPN
easat-10839	220	11	deng	deng	PROPN
easat-10839	220	12	,	,	PUNCT
easat-10839	220	13	and	and	CCONJ
easat-10839	220	14	l.	l.	PROPN
easat-10839	220	15	mei	mei	PROPN
easat-10839	220	16	,	,	PUNCT
easat-10839	220	17	"	"	PUNCT
easat-10839	220	18	impact	impact	NOUN
easat-10839	220	19	of	of	ADP
easat-10839	220	20	tumor	tumor	NOUN
easat-10839	220	21	–	–	PUNCT
easat-10839	220	22	stroma	stroma	ADJ
easat-10839	220	23	ratio	ratio	NOUN
easat-10839	220	24	on	on	ADP
easat-10839	220	25	the	the	DET
easat-10839	220	26	prognosis	prognosis	NOUN
easat-10839	220	27	of	of	ADP
easat-10839	220	28	colorectal	colorectal	ADJ
easat-10839	220	29	cancer	cancer	NOUN
easat-10839	220	30	:	:	PUNCT
easat-10839	220	31	a	a	DET
easat-10839	220	32	systematic	systematic	ADJ
easat-10839	220	33	review	review	NOUN
easat-10839	220	34	,	,	PUNCT
easat-10839	220	35	"	"	PUNCT
easat-10839	220	36	frontiers	frontier	NOUN
easat-10839	220	37	in	in	ADP
easat-10839	220	38	oncology	oncology	NOUN
easat-10839	220	39	,	,	PUNCT
easat-10839	220	40	vol	vol	NOUN
easat-10839	220	41	.	.	PROPN
easat-10839	220	42	11	11	NUM
easat-10839	220	43	,	,	PUNCT
easat-10839	220	44	p.	p.	NOUN
easat-10839	220	45	738080	738080	NUM
easat-10839	220	46	,	,	PUNCT
easat-10839	220	47	2021	2021	NUM
easat-10839	220	48	.	.	PUNCT
easat-10839	221	1	https://doi.org/10.3389/fonc.2021.738080	https://doi.org/10.3389/fonc.2021.738080	PROPN
easat-10839	221	2	[	[	X
easat-10839	221	3	14	14	NUM
easat-10839	221	4	]	]	X
easat-10839	221	5	l.	l.	PROPN
easat-10839	221	6	petäinen	petäinen	PROPN
easat-10839	221	7	,	,	PUNCT
easat-10839	221	8	j.	j.	PROPN
easat-10839	221	9	p.	p.	PROPN
easat-10839	221	10	väyrynen	väyrynen	PROPN
easat-10839	221	11	,	,	PUNCT
easat-10839	221	12	p.	p.	NOUN
easat-10839	221	13	ruusuvuori	ruusuvuori	PROPN
easat-10839	221	14	,	,	PUNCT
easat-10839	221	15	i.	i.	PROPN
easat-10839	221	16	pölönen	pölönen	PROPN
easat-10839	221	17	,	,	PUNCT
easat-10839	221	18	s.	s.	PROPN
easat-10839	221	19	äyrämö	äyrämö	PROPN
easat-10839	221	20	,	,	PUNCT
easat-10839	221	21	and	and	CCONJ
easat-10839	221	22	t.	t.	PROPN
easat-10839	221	23	kuopio	kuopio	NOUN
easat-10839	221	24	,	,	PUNCT
easat-10839	221	25	"	"	PUNCT
easat-10839	221	26	domain	domain	NOUN
easat-10839	221	27	-	-	PUNCT
easat-10839	221	28	specific	specific	ADJ
easat-10839	221	29	transfer	transfer	NOUN
easat-10839	221	30	learning	learning	NOUN
easat-10839	221	31	in	in	ADP
easat-10839	221	32	the	the	DET
easat-10839	221	33	automated	automate	VERB
easat-10839	221	34	scoring	scoring	NOUN
easat-10839	221	35	of	of	ADP
easat-10839	221	36	tumor	tumor	NOUN
easat-10839	221	37	-	-	PUNCT
easat-10839	221	38	stroma	stroma	NOUN
easat-10839	221	39	ratio	ratio	NOUN
easat-10839	221	40	from	from	ADP
easat-10839	221	41	histopathological	histopathological	ADJ
easat-10839	221	42	images	image	NOUN
easat-10839	221	43	of	of	ADP
easat-10839	221	44	colorectal	colorectal	ADJ
easat-10839	221	45	cancer	cancer	NOUN
easat-10839	221	46	,	,	PUNCT
easat-10839	221	47	"	"	PUNCT
easat-10839	221	48	plos	plos	PROPN
easat-10839	221	49	one	one	NUM
easat-10839	221	50	,	,	PUNCT
easat-10839	221	51	vol	vol	NOUN
easat-10839	221	52	.	.	PROPN
easat-10839	221	53	18	18	NUM
easat-10839	221	54	,	,	PUNCT
easat-10839	221	55	no	no	INTJ
easat-10839	221	56	.	.	NOUN
easat-10839	221	57	5	5	NUM
easat-10839	221	58	,	,	PUNCT
easat-10839	221	59	p.	p.	NOUN
easat-10839	221	60	e0286270	e0286270	PROPN
easat-10839	221	61	,	,	PUNCT
easat-10839	221	62	2023	2023	NUM
easat-10839	221	63	.	.	PUNCT
easat-10839	222	1	https://doi.org/10.1371/journal.pone.0286270	https://doi.org/10.1371/journal.pone.0286270	X
easat-10839	223	1	[	[	X
easat-10839	223	2	15	15	NUM
easat-10839	223	3	]	]	PUNCT
easat-10839	223	4	k.	k.	PROPN
easat-10839	223	5	zhao	zhao	PROPN
easat-10839	223	6	et	et	PROPN
easat-10839	223	7	al	al	PROPN
easat-10839	223	8	.	.	PROPN
easat-10839	223	9	,	,	PUNCT
easat-10839	223	10	"	"	PUNCT
easat-10839	223	11	artificial	artificial	ADJ
easat-10839	223	12	intelligence	intelligence	NOUN
easat-10839	223	13	quantified	quantify	VERB
easat-10839	223	14	tumour	tumour	ADJ
easat-10839	223	15	-	-	PUNCT
easat-10839	223	16	stroma	stroma	ADJ
easat-10839	223	17	ratio	ratio	NOUN
easat-10839	223	18	is	be	AUX
easat-10839	223	19	an	an	DET
easat-10839	223	20	independent	independent	ADJ
easat-10839	223	21	predictor	predictor	NOUN
easat-10839	223	22	for	for	ADP
easat-10839	223	23	overall	overall	ADJ
easat-10839	223	24	survival	survival	NOUN
easat-10839	223	25	in	in	ADP
easat-10839	223	26	resectable	resectable	ADJ
easat-10839	223	27	colorectal	colorectal	ADJ
easat-10839	223	28	cancer	cancer	NOUN
easat-10839	223	29	,	,	PUNCT
easat-10839	223	30	"	"	PUNCT
easat-10839	223	31	ebiomedicine	ebiomedicine	ADJ
easat-10839	223	32	,	,	PUNCT
easat-10839	223	33	vol	vol	NOUN
easat-10839	223	34	.	.	PROPN
easat-10839	223	35	61	61	NUM
easat-10839	223	36	,	,	PUNCT
easat-10839	223	37	p.	p.	NOUN
easat-10839	223	38	103054	103054	NUM
easat-10839	223	39	,	,	PUNCT
easat-10839	223	40	2020	2020	NUM
easat-10839	223	41	.	.	PUNCT
easat-10839	224	1	https://doi.org/10.1016/j.ebiom.2020.103054	https://doi.org/10.1016/j.ebiom.2020.103054	PROPN
easat-10839	225	1	[	[	X
easat-10839	225	2	16	16	NUM
easat-10839	225	3	]	]	X
easat-10839	225	4	d.	d.	PROPN
easat-10839	225	5	firmbach	firmbach	PROPN
easat-10839	225	6	et	et	PROPN
easat-10839	225	7	al	al	PROPN
easat-10839	225	8	.	.	PROPN
easat-10839	225	9	,	,	PUNCT
easat-10839	225	10	"	"	PUNCT
easat-10839	225	11	tumor	tumor	NOUN
easat-10839	225	12	–	–	PUNCT
easat-10839	225	13	stroma	stroma	ADJ
easat-10839	225	14	ratio	ratio	NOUN
easat-10839	225	15	in	in	ADP
easat-10839	225	16	colorectal	colorectal	ADJ
easat-10839	225	17	cancer	cancer	NOUN
easat-10839	225	18	—	—	PUNCT
easat-10839	225	19	comparison	comparison	NOUN
easat-10839	225	20	between	between	ADP
easat-10839	225	21	human	human	ADJ
easat-10839	225	22	estimation	estimation	NOUN
easat-10839	225	23	and	and	CCONJ
easat-10839	225	24	automated	automated	ADJ
easat-10839	225	25	assessment	assessment	NOUN
easat-10839	225	26	,	,	PUNCT
easat-10839	225	27	"	"	PUNCT
easat-10839	225	28	cancers	cancer	NOUN
easat-10839	225	29	,	,	PUNCT
easat-10839	225	30	vol	vol	NOUN
easat-10839	225	31	.	.	PROPN
easat-10839	225	32	15	15	NUM
easat-10839	225	33	,	,	PUNCT
easat-10839	225	34	no	no	INTJ
easat-10839	225	35	.	.	NOUN
easat-10839	225	36	10	10	NUM
easat-10839	225	37	,	,	PUNCT
easat-10839	225	38	p.	p.	NOUN
easat-10839	225	39	2675	2675	NUM
easat-10839	225	40	,	,	PUNCT
easat-10839	225	41	2023	2023	NUM
easat-10839	225	42	.	.	PUNCT
easat-10839	226	1	https://doi.org/10.3390/cancers15102675	https://doi.org/10.3390/cancers15102675	PROPN
easat-10839	227	1	[	[	X
easat-10839	227	2	17	17	NUM
easat-10839	227	3	]	]	PUNCT
easat-10839	227	4	h.	h.	PROPN
easat-10839	227	5	e.	e.	PROPN
easat-10839	227	6	kim	kim	PROPN
easat-10839	227	7	,	,	PUNCT
easat-10839	227	8	a.	a.	PROPN
easat-10839	227	9	cosa	cosa	PROPN
easat-10839	227	10	-	-	PUNCT
easat-10839	227	11	linan	linan	PROPN
easat-10839	227	12	,	,	PUNCT
easat-10839	227	13	n.	n.	NOUN
easat-10839	227	14	santhanam	santhanam	PROPN
easat-10839	227	15	,	,	PUNCT
easat-10839	227	16	m.	m.	NOUN
easat-10839	227	17	jannesari	jannesari	PROPN
easat-10839	227	18	,	,	PUNCT
easat-10839	227	19	m.	m.	PROPN
easat-10839	227	20	e.	e.	PROPN
easat-10839	227	21	maros	maros	PROPN
easat-10839	227	22	,	,	PUNCT
easat-10839	227	23	and	and	CCONJ
easat-10839	227	24	t.	t.	PROPN
easat-10839	227	25	ganslandt	ganslandt	NOUN
easat-10839	227	26	,	,	PUNCT
easat-10839	227	27	"	"	PUNCT
easat-10839	227	28	transfer	transfer	NOUN
easat-10839	227	29	learning	learning	NOUN
easat-10839	227	30	for	for	ADP
easat-10839	227	31	medical	medical	ADJ
easat-10839	227	32	image	image	NOUN
easat-10839	227	33	classification	classification	NOUN
easat-10839	227	34	:	:	PUNCT
easat-10839	227	35	a	a	DET
easat-10839	227	36	literature	literature	NOUN
easat-10839	227	37	review	review	NOUN
easat-10839	227	38	,	,	PUNCT
easat-10839	227	39	"	"	PUNCT
easat-10839	227	40	bmc	bmc	PROPN
easat-10839	227	41	medical	medical	ADJ
easat-10839	227	42	imaging	imaging	NOUN
easat-10839	227	43	,	,	PUNCT
easat-10839	227	44	vol	vol	NOUN
easat-10839	227	45	.	.	PROPN
easat-10839	227	46	22	22	NUM
easat-10839	227	47	,	,	PUNCT
easat-10839	227	48	p.	p.	NOUN
easat-10839	227	49	69	69	NUM
easat-10839	227	50	,	,	PUNCT
easat-10839	227	51	2022	2022	NUM
easat-10839	227	52	.	.	PUNCT
easat-10839	228	1	https://doi.org/10.1186/s12880022-00793-7	https://doi.org/10.1186/s12880022-00793-7	PROPN
easat-10839	228	2	[	[	X
easat-10839	228	3	18	18	NUM
easat-10839	228	4	]	]	PUNCT
easat-10839	228	5	m.	m.	NOUN
easat-10839	228	6	a.	a.	PROPN
easat-10839	228	7	k.	k.	PROPN
easat-10839	228	8	raiaan	raiaan	PROPN
easat-10839	228	9	et	et	PROPN
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easat-10839	228	11	.	.	PROPN
easat-10839	228	12	,	,	PUNCT
easat-10839	228	13	"	"	PUNCT
easat-10839	228	14	a	a	DET
easat-10839	228	15	systematic	systematic	ADJ
easat-10839	228	16	review	review	NOUN
easat-10839	228	17	of	of	ADP
easat-10839	228	18	hyperparameter	hyperparameter	NOUN
easat-10839	228	19	optimization	optimization	NOUN
easat-10839	228	20	techniques	technique	NOUN
easat-10839	228	21	in	in	ADP
easat-10839	228	22	convolutional	convolutional	ADJ
easat-10839	228	23	neural	neural	ADJ
easat-10839	228	24	networks	network	NOUN
easat-10839	228	25	,	,	PUNCT
easat-10839	228	26	"	"	PUNCT
easat-10839	228	27	decision	decision	NOUN
easat-10839	228	28	analytics	analytic	NOUN
easat-10839	228	29	journal	journal	NOUN
easat-10839	228	30	,	,	PUNCT
easat-10839	228	31	vol	vol	NOUN
easat-10839	228	32	.	.	PROPN
easat-10839	228	33	11	11	NUM
easat-10839	228	34	,	,	PUNCT
easat-10839	228	35	p.	p.	NOUN
easat-10839	228	36	100470	100470	NUM
easat-10839	228	37	,	,	PUNCT
easat-10839	228	38	2024	2024	NUM
easat-10839	228	39	.	.	PUNCT
easat-10839	229	1	https://doi.org/10.1016/j.dajour.2024.100470	https://doi.org/10.1016/j.dajour.2024.100470	PROPN
easat-10839	229	2	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-10839	229	3	https://colorectalcancer.org/	https://colorectalcancer.org/	PROPN
easat-10839	229	4	https://www.wcrf.org/diet-activity-and-cancer/	https://www.wcrf.org/diet-activity-and-cancer/	PROPN
easat-10839	230	1	https://www.wcrf.org/diet-activity-and-cancer/	https://www.wcrf.org/diet-activity-and-cancer/	PROPN
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easat-10839	230	3	https://doi.org/10.3350/cmh.2021.0394	https://doi.org/10.3350/cmh.2021.0394	NOUN
easat-10839	230	4	https://doi.org/10.1371/journal.pmed.1002730	https://doi.org/10.1371/journal.pmed.1002730	ADV
easat-10839	230	5	https://doi.org/10.1016/j.csbj.2023.01.043	https://doi.org/10.1016/j.csbj.2023.01.043	PROPN
easat-10839	230	6	https://doi.org/10.1186/s40537-021-00444-8	https://doi.org/10.1186/s40537-021-00444-8	VERB
easat-10839	230	7	https://doi.org/10.1186/s12874-018-0482-1	https://doi.org/10.1186/s12874-018-0482-1	NUM
easat-10839	230	8	https://doi.org/10.1016/j.jpi.2023.100191	https://doi.org/10.1016/j.jpi.2023.100191	PUNCT
easat-10839	231	1	https://doi.org/10.3389/fonc.2021.738080	https://doi.org/10.3389/fonc.2021.738080	PROPN
easat-10839	231	2	https://doi.org/10.1371/journal.pone.0286270	https://doi.org/10.1371/journal.pone.0286270	PROPN
easat-10839	231	3	https://doi.org/10.1016/j.ebiom.2020.103054	https://doi.org/10.1016/j.ebiom.2020.103054	PROPN
easat-10839	231	4	https://doi.org/10.3390/cancers15102675	https://doi.org/10.3390/cancers15102675	PROPN
easat-10839	231	5	https://doi.org/10.1186/s12880-022-00793-7	https://doi.org/10.1186/s12880-022-00793-7	PROPN
easat-10839	231	6	https://doi.org/10.1186/s12880-022-00793-7	https://doi.org/10.1186/s12880-022-00793-7	NUM
easat-10839	232	1	https://doi.org/10.1016/j.dajour.2024.100470	https://doi.org/10.1016/j.dajour.2024.100470	ADJ
easat-10839	232	2	261	261	NUM
easat-10839	232	3	edelweiss	edelweiss	PROPN
easat-10839	232	4	applied	apply	VERB
easat-10839	232	5	science	science	NOUN
easat-10839	232	6	and	and	CCONJ
easat-10839	232	7	technology	technology	NOUN
easat-10839	232	8	issn	issn	PROPN
easat-10839	232	9	:	:	PUNCT
easat-10839	232	10	2576	2576	NUM
easat-10839	232	11	-	-	SYM
easat-10839	232	12	8484	8484	NUM
easat-10839	232	13	vol	vol	NOUN
easat-10839	232	14	.	.	PROPN
easat-10839	233	1	9	9	NUM
easat-10839	233	2	,	,	PUNCT
easat-10839	233	3	no	no	INTJ
easat-10839	233	4	.	.	NOUN
easat-10839	233	5	11	11	NUM
easat-10839	233	6	:	:	PUNCT
easat-10839	233	7	249	249	NUM
easat-10839	233	8	-	-	SYM
easat-10839	233	9	261	261	NUM
easat-10839	233	10	,	,	PUNCT
easat-10839	233	11	2025	2025	NUM
easat-10839	233	12	doi	doi	NOUN
easat-10839	233	13	:	:	PUNCT
easat-10839	233	14	10.55214/2576	10.55214/2576	NUM
easat-10839	233	15	-	-	SYM
easat-10839	233	16	8484.v9i11.10839	8484.v9i11.10839	NUM
easat-10839	233	17	©	©	ADP
easat-10839	233	18	2025	2025	NUM
easat-10839	233	19	by	by	ADP
easat-10839	233	20	the	the	DET
easat-10839	233	21	authors	author	NOUN
easat-10839	233	22	;	;	PUNCT
easat-10839	233	23	licensee	licensee	PROPN
easat-10839	233	24	learning	learning	NOUN
easat-10839	233	25	gate	gate	NOUN
easat-10839	234	1	[	[	X
easat-10839	234	2	19	19	NUM
easat-10839	234	3	]	]	PUNCT
easat-10839	234	4	m.	m.	NOUN
easat-10839	234	5	iman	iman	PROPN
easat-10839	234	6	,	,	PUNCT
easat-10839	234	7	h.	h.	PROPN
easat-10839	234	8	r.	r.	PROPN
easat-10839	234	9	arabnia	arabnia	PROPN
easat-10839	234	10	,	,	PUNCT
easat-10839	234	11	and	and	CCONJ
easat-10839	234	12	k.	k.	PROPN
easat-10839	234	13	rasheed	rasheed	PROPN
easat-10839	234	14	,	,	PUNCT
easat-10839	234	15	"	"	PUNCT
easat-10839	234	16	a	a	DET
easat-10839	234	17	review	review	NOUN
easat-10839	234	18	of	of	ADP
easat-10839	234	19	deep	deep	ADJ
easat-10839	234	20	transfer	transfer	NOUN
easat-10839	234	21	learning	learning	NOUN
easat-10839	234	22	and	and	CCONJ
easat-10839	234	23	recent	recent	ADJ
easat-10839	234	24	advancements	advancement	NOUN
easat-10839	234	25	,	,	PUNCT
easat-10839	234	26	"	"	PUNCT
easat-10839	234	27	technologies	technology	NOUN
easat-10839	234	28	,	,	PUNCT
easat-10839	234	29	vol	vol	NOUN
easat-10839	234	30	.	.	PROPN
easat-10839	234	31	11	11	NUM
easat-10839	234	32	,	,	PUNCT
easat-10839	234	33	no	no	INTJ
easat-10839	234	34	.	.	NOUN
easat-10839	234	35	2	2	NUM
easat-10839	234	36	,	,	PUNCT
easat-10839	234	37	p.	p.	NOUN
easat-10839	234	38	40	40	NUM
easat-10839	234	39	,	,	PUNCT
easat-10839	234	40	2023	2023	NUM
easat-10839	234	41	.	.	PUNCT
easat-10839	235	1	[	[	X
easat-10839	235	2	20	20	NUM
easat-10839	235	3	]	]	PUNCT
easat-10839	235	4	m.	m.	NOUN
easat-10839	235	5	khazaee	khazaee	PROPN
easat-10839	235	6	fadafen	fadafen	PROPN
easat-10839	235	7	and	and	CCONJ
easat-10839	235	8	k.	k.	PROPN
easat-10839	235	9	rezaee	rezaee	PROPN
easat-10839	235	10	,	,	PUNCT
easat-10839	235	11	"	"	PUNCT
easat-10839	235	12	ensemble	ensemble	ADJ
easat-10839	235	13	-	-	PUNCT
easat-10839	235	14	based	base	VERB
easat-10839	235	15	multi	multi	ADJ
easat-10839	235	16	-	-	ADJ
easat-10839	235	17	tissue	tissue	ADJ
easat-10839	235	18	classification	classification	NOUN
easat-10839	235	19	approach	approach	NOUN
easat-10839	235	20	of	of	ADP
easat-10839	235	21	colorectal	colorectal	ADJ
easat-10839	235	22	cancer	cancer	NOUN
easat-10839	235	23	histology	histology	NOUN
easat-10839	235	24	images	image	NOUN
easat-10839	235	25	using	use	VERB
easat-10839	235	26	a	a	DET
easat-10839	235	27	novel	novel	ADJ
easat-10839	235	28	hybrid	hybrid	ADJ
easat-10839	235	29	deep	deep	ADJ
easat-10839	235	30	learning	learning	NOUN
easat-10839	235	31	framework	framework	NOUN
easat-10839	235	32	,	,	PUNCT
easat-10839	235	33	"	"	PUNCT
easat-10839	235	34	scientific	scientific	ADJ
easat-10839	235	35	reports	report	NOUN
easat-10839	235	36	,	,	PUNCT
easat-10839	235	37	vol	vol	NOUN
easat-10839	235	38	.	.	PROPN
easat-10839	235	39	13	13	NUM
easat-10839	235	40	,	,	PUNCT
easat-10839	235	41	no	no	INTJ
easat-10839	235	42	.	.	NOUN
easat-10839	235	43	1	1	NUM
easat-10839	235	44	,	,	PUNCT
easat-10839	235	45	p.	p.	NOUN
easat-10839	235	46	8823	8823	NUM
easat-10839	235	47	,	,	PUNCT
easat-10839	235	48	2023	2023	NUM
easat-10839	235	49	.	.	PUNCT
easat-10839	236	1	https://doi.org/10.1038/s41598-023-35431-x	https://doi.org/10.1038/s41598-023-35431-x	NOUN
easat-10839	236	2	[	[	X
easat-10839	236	3	21	21	NUM
easat-10839	236	4	]	]	PUNCT
easat-10839	236	5	m.	m.	NOUN
easat-10839	236	6	yildirim	yildirim	PROPN
easat-10839	236	7	and	and	CCONJ
easat-10839	236	8	a.	a.	PROPN
easat-10839	236	9	cinar	cinar	PROPN
easat-10839	236	10	,	,	PUNCT
easat-10839	236	11	"	"	PUNCT
easat-10839	236	12	classification	classification	NOUN
easat-10839	236	13	with	with	ADP
easat-10839	236	14	respect	respect	NOUN
easat-10839	236	15	to	to	ADP
easat-10839	236	16	colon	colon	NOUN
easat-10839	236	17	adenocarcinoma	adenocarcinoma	NOUN
easat-10839	236	18	and	and	CCONJ
easat-10839	236	19	colon	colon	NOUN
easat-10839	236	20	benign	benign	ADJ
easat-10839	236	21	tissue	tissue	NOUN
easat-10839	236	22	of	of	ADP
easat-10839	236	23	colon	colon	NOUN
easat-10839	236	24	histopathological	histopathological	ADJ
easat-10839	236	25	images	image	NOUN
easat-10839	236	26	with	with	ADP
easat-10839	236	27	a	a	DET
easat-10839	236	28	new	new	ADJ
easat-10839	236	29	cnn	cnn	PROPN
easat-10839	236	30	model	model	NOUN
easat-10839	236	31	:	:	PUNCT
easat-10839	236	32	ma_colonnet	ma_colonnet	NOUN
easat-10839	236	33	,	,	PUNCT
easat-10839	236	34	"	"	PUNCT
easat-10839	236	35	international	international	ADJ
easat-10839	236	36	journal	journal	NOUN
easat-10839	236	37	of	of	ADP
easat-10839	236	38	imaging	imaging	NOUN
easat-10839	236	39	systems	system	NOUN
easat-10839	236	40	and	and	CCONJ
easat-10839	236	41	technology	technology	NOUN
easat-10839	236	42	,	,	PUNCT
easat-10839	236	43	vol	vol	NOUN
easat-10839	236	44	.	.	PROPN
easat-10839	236	45	32	32	NUM
easat-10839	236	46	,	,	PUNCT
easat-10839	236	47	no	no	INTJ
easat-10839	236	48	.	.	NOUN
easat-10839	236	49	1	1	NUM
easat-10839	236	50	,	,	PUNCT
easat-10839	236	51	pp	pp	ADJ
easat-10839	236	52	.	.	PUNCT
easat-10839	237	1	155	155	NUM
easat-10839	237	2	-	-	SYM
easat-10839	237	3	162	162	NUM
easat-10839	237	4	,	,	PUNCT
easat-10839	237	5	2022	2022	NUM
easat-10839	237	6	.	.	PUNCT
easat-10839	238	1	https://doi.org/10.1002/ima.22623	https://doi.org/10.1002/ima.22623	VERB
easat-10839	238	2	https://doi.org/10.1038/s41598-023-35431-x	https://doi.org/10.1038/s41598-023-35431-x	NOUN
easat-10839	238	3	https://doi.org/10.1002/ima.22623	https://doi.org/10.1002/ima.22623	VERB