id	sid	tid	token	lemma	pos
cana-3843	1	1	communications	communication	NOUN
cana-3843	1	2	on	on	ADP
cana-3843	1	3	applied	apply	VERB
cana-3843	1	4	nonlinear	nonlinear	ADJ
cana-3843	1	5	analysis	analysis	NOUN
cana-3843	1	6	issn	issn	NOUN
cana-3843	1	7	:	:	PUNCT
cana-3843	1	8	1074	1074	NUM
cana-3843	1	9	-	-	PUNCT
cana-3843	1	10	133x	133x	NUM
cana-3843	1	11	vol	vol	NOUN
cana-3843	1	12	32	32	NUM
cana-3843	1	13	no	no	NOUN
cana-3843	1	14	.	.	PUNCT
cana-3843	2	1	9s	9s	NUM
cana-3843	2	2	(	(	PUNCT
cana-3843	2	3	2025	2025	NUM
cana-3843	2	4	)	)	PUNCT
cana-3843	2	5	119	119	NUM
cana-3843	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	2	7	leukemia	leukemia	NOUN
cana-3843	2	8	cancer	cancer	NOUN
cana-3843	2	9	gene	gene	NOUN
cana-3843	2	10	identification	identification	NOUN
cana-3843	2	11	through	through	ADP
cana-3843	2	12	genetic	genetic	ADJ
cana-3843	2	13	optimization	optimization	NOUN
cana-3843	2	14	technique	technique	NOUN
cana-3843	2	15	and	and	CCONJ
cana-3843	2	16	prediction	prediction	NOUN
cana-3843	2	17	with	with	ADP
cana-3843	2	18	lstm	lstm	NOUN
cana-3843	2	19	m.kalaivani1	m.kalaivani1	NOUN
cana-3843	2	20	,	,	PUNCT
cana-3843	2	21	dr.k.abirami2	dr.k.abirami2	PROPN
cana-3843	2	22	and	and	CCONJ
cana-3843	2	23	dr.k.dharmarajan3	dr.k.dharmarajan3	PROPN
cana-3843	2	24	1,2,3vels	1,2,3vels	NUM
cana-3843	2	25	institute	institute	PROPN
cana-3843	2	26	of	of	ADP
cana-3843	2	27	science	science	NOUN
cana-3843	2	28	,	,	PUNCT
cana-3843	2	29	technology	technology	NOUN
cana-3843	2	30	&	&	CCONJ
cana-3843	2	31	advanced	advanced	ADJ
cana-3843	2	32	studies(vistas	studies(vista	NOUN
cana-3843	2	33	)	)	PUNCT
cana-3843	2	34	,	,	PUNCT
cana-3843	2	35	chennai	chennai	PROPN
cana-3843	2	36	,	,	PUNCT
cana-3843	2	37	india	india	PROPN
cana-3843	2	38	e	e	PROPN
cana-3843	2	39	-	-	NOUN
cana-3843	2	40	mail	mail	NOUN
cana-3843	2	41	:	:	PUNCT
cana-3843	2	42	mkvanimca@gmail.com	mkvanimca@gmail.com	X
cana-3843	2	43	article	article	NOUN
cana-3843	2	44	history	history	NOUN
cana-3843	2	45	:	:	PUNCT
cana-3843	2	46	received	receive	VERB
cana-3843	2	47	:	:	PUNCT
cana-3843	2	48	12	12	NUM
cana-3843	2	49	-	-	SYM
cana-3843	2	50	11	11	NUM
cana-3843	2	51	-	-	PUNCT
cana-3843	2	52	2024	2024	NUM
cana-3843	2	53	revised:24	revised:24	X
cana-3843	2	54	-	-	PUNCT
cana-3843	2	55	12	12	NUM
cana-3843	2	56	-	-	PUNCT
cana-3843	2	57	2024	2024	NUM
cana-3843	2	58	accepted:09	accepted:09	NOUN
cana-3843	2	59	-	-	PUNCT
cana-3843	2	60	01	01	NUM
cana-3843	2	61	-	-	PUNCT
cana-3843	2	62	2025	2025	NUM
cana-3843	2	63	abstract	abstract	NOUN
cana-3843	2	64	:	:	PUNCT
cana-3843	2	65	cancer	cancer	NOUN
cana-3843	2	66	disease	disease	NOUN
cana-3843	2	67	persists	persist	VERB
cana-3843	2	68	as	as	ADP
cana-3843	2	69	one	one	NUM
cana-3843	2	70	of	of	ADP
cana-3843	2	71	the	the	DET
cana-3843	2	72	major	major	ADJ
cana-3843	2	73	causes	cause	NOUN
cana-3843	2	74	of	of	ADP
cana-3843	2	75	mortality	mortality	NOUN
cana-3843	2	76	worldwide	worldwide	ADV
cana-3843	2	77	,	,	PUNCT
cana-3843	2	78	emphasizing	emphasize	VERB
cana-3843	2	79	the	the	DET
cana-3843	2	80	critical	critical	ADJ
cana-3843	2	81	necessity	necessity	NOUN
cana-3843	2	82	for	for	ADP
cana-3843	2	83	accurate	accurate	ADJ
cana-3843	2	84	and	and	CCONJ
cana-3843	2	85	early	early	ADJ
cana-3843	2	86	diagnosis	diagnosis	NOUN
cana-3843	2	87	.	.	PUNCT
cana-3843	3	1	identifying	identify	VERB
cana-3843	3	2	genes	gene	NOUN
cana-3843	3	3	associated	associate	VERB
cana-3843	3	4	with	with	ADP
cana-3843	3	5	cancer	cancer	NOUN
cana-3843	3	6	can	can	AUX
cana-3843	3	7	facilitate	facilitate	VERB
cana-3843	3	8	effective	effective	ADJ
cana-3843	3	9	early	early	ADJ
cana-3843	3	10	-	-	PUNCT
cana-3843	3	11	stage	stage	NOUN
cana-3843	3	12	treatment	treatment	NOUN
cana-3843	3	13	.	.	PUNCT
cana-3843	4	1	dna	dna	PROPN
cana-3843	4	2	microarray	microarray	PROPN
cana-3843	4	3	data	datum	NOUN
cana-3843	4	4	plays	play	VERB
cana-3843	4	5	a	a	DET
cana-3843	4	6	vital	vital	ADJ
cana-3843	4	7	role	role	NOUN
cana-3843	4	8	in	in	ADP
cana-3843	4	9	detecting	detect	VERB
cana-3843	4	10	and	and	CCONJ
cana-3843	4	11	diagnosing	diagnose	VERB
cana-3843	4	12	cancer	cancer	NOUN
cana-3843	4	13	.	.	PUNCT
cana-3843	5	1	microarray	microarray	NOUN
cana-3843	5	2	analysis	analysis	NOUN
cana-3843	5	3	allows	allow	VERB
cana-3843	5	4	the	the	DET
cana-3843	5	5	examination	examination	NOUN
cana-3843	5	6	of	of	ADP
cana-3843	5	7	gene	gene	NOUN
cana-3843	5	8	expression	expression	NOUN
cana-3843	5	9	levels	level	NOUN
cana-3843	5	10	in	in	ADP
cana-3843	5	11	specific	specific	ADJ
cana-3843	5	12	cell	cell	NOUN
cana-3843	5	13	samples	sample	NOUN
cana-3843	5	14	,	,	PUNCT
cana-3843	5	15	enabling	enable	VERB
cana-3843	5	16	the	the	DET
cana-3843	5	17	simultaneous	simultaneous	ADJ
cana-3843	5	18	analysis	analysis	NOUN
cana-3843	5	19	of	of	ADP
cana-3843	5	20	thousands	thousand	NOUN
cana-3843	5	21	of	of	ADP
cana-3843	5	22	genes	gene	NOUN
cana-3843	5	23	.	.	PUNCT
cana-3843	6	1	however	however	ADV
cana-3843	6	2	,	,	PUNCT
cana-3843	6	3	microarray	microarray	PROPN
cana-3843	6	4	gene	gene	NOUN
cana-3843	6	5	data	datum	NOUN
cana-3843	6	6	is	be	AUX
cana-3843	6	7	characterized	characterize	VERB
cana-3843	6	8	by	by	ADP
cana-3843	6	9	high	high	ADJ
cana-3843	6	10	dimensionality	dimensionality	NOUN
cana-3843	6	11	and	and	CCONJ
cana-3843	6	12	contains	contain	VERB
cana-3843	6	13	redundant	redundant	ADJ
cana-3843	6	14	genes	gene	NOUN
cana-3843	6	15	.	.	PUNCT
cana-3843	7	1	the	the	DET
cana-3843	7	2	gene	gene	NOUN
cana-3843	7	3	(	(	PUNCT
cana-3843	7	4	feature	feature	NOUN
cana-3843	7	5	)	)	PUNCT
cana-3843	7	6	selection	selection	NOUN
cana-3843	7	7	process	process	NOUN
cana-3843	7	8	is	be	AUX
cana-3843	7	9	essential	essential	ADJ
cana-3843	7	10	in	in	ADP
cana-3843	7	11	microarray	microarray	NOUN
cana-3843	7	12	gene	gene	NOUN
cana-3843	7	13	expression	expression	NOUN
cana-3843	7	14	data	datum	NOUN
cana-3843	7	15	analysis	analysis	NOUN
cana-3843	7	16	for	for	ADP
cana-3843	7	17	selecting	select	VERB
cana-3843	7	18	highly	highly	ADV
cana-3843	7	19	relevant	relevant	ADJ
cana-3843	7	20	genes	gene	NOUN
cana-3843	7	21	with	with	ADP
cana-3843	7	22	low	low	ADJ
cana-3843	7	23	redundancy	redundancy	NOUN
cana-3843	7	24	that	that	PRON
cana-3843	7	25	may	may	AUX
cana-3843	7	26	cause	cause	VERB
cana-3843	7	27	improved	improved	ADJ
cana-3843	7	28	prediction	prediction	NOUN
cana-3843	7	29	results	result	NOUN
cana-3843	7	30	.	.	PUNCT
cana-3843	8	1	this	this	DET
cana-3843	8	2	research	research	NOUN
cana-3843	8	3	article	article	NOUN
cana-3843	8	4	presents	present	VERB
cana-3843	8	5	a	a	DET
cana-3843	8	6	model	model	NOUN
cana-3843	8	7	designed	design	VERB
cana-3843	8	8	to	to	PART
cana-3843	8	9	reduce	reduce	VERB
cana-3843	8	10	the	the	DET
cana-3843	8	11	high	high	ADJ
cana-3843	8	12	-	-	PUNCT
cana-3843	8	13	dimensional	dimensional	ADJ
cana-3843	8	14	gene	gene	NOUN
cana-3843	8	15	data	datum	NOUN
cana-3843	8	16	to	to	ADP
cana-3843	8	17	low	low	ADJ
cana-3843	8	18	-	-	PUNCT
cana-3843	8	19	dimensional	dimensional	ADJ
cana-3843	8	20	space	space	NOUN
cana-3843	8	21	,	,	PUNCT
cana-3843	8	22	eliminate	eliminate	VERB
cana-3843	8	23	redundant	redundant	ADJ
cana-3843	8	24	genes	gene	NOUN
cana-3843	8	25	,	,	PUNCT
cana-3843	8	26	and	and	CCONJ
cana-3843	8	27	improve	improve	VERB
cana-3843	8	28	early	early	ADJ
cana-3843	8	29	-	-	PUNCT
cana-3843	8	30	stage	stage	NOUN
cana-3843	8	31	disease	disease	NOUN
cana-3843	8	32	prediction	prediction	NOUN
cana-3843	8	33	.	.	PUNCT
cana-3843	9	1	the	the	DET
cana-3843	9	2	proposed	propose	VERB
cana-3843	9	3	model	model	NOUN
cana-3843	9	4	is	be	AUX
cana-3843	9	5	implemented	implement	VERB
cana-3843	9	6	in	in	ADP
cana-3843	9	7	the	the	DET
cana-3843	9	8	following	follow	VERB
cana-3843	9	9	phases	phase	NOUN
cana-3843	9	10	.	.	PUNCT
cana-3843	10	1	the	the	DET
cana-3843	10	2	initial	initial	ADJ
cana-3843	10	3	process	process	NOUN
cana-3843	10	4	involves	involve	VERB
cana-3843	10	5	checking	check	VERB
cana-3843	10	6	the	the	DET
cana-3843	10	7	multicollinearity	multicollinearity	NOUN
cana-3843	10	8	between	between	ADP
cana-3843	10	9	genes	gene	NOUN
cana-3843	10	10	and	and	CCONJ
cana-3843	10	11	identifying	identify	VERB
cana-3843	10	12	the	the	DET
cana-3843	10	13	low	low	ADJ
cana-3843	10	14	intercorrelated	intercorrelate	VERB
cana-3843	10	15	genes	gene	NOUN
cana-3843	10	16	using	use	VERB
cana-3843	10	17	the	the	DET
cana-3843	10	18	karl	karl	PROPN
cana-3843	10	19	pearson	pearson	PROPN
cana-3843	10	20	correlation	correlation	PROPN
cana-3843	10	21	coefficient	coefficient	NOUN
cana-3843	10	22	on	on	ADP
cana-3843	10	23	the	the	DET
cana-3843	10	24	cancer	cancer	NOUN
cana-3843	10	25	dataset	dataset	NOUN
cana-3843	10	26	.	.	PUNCT
cana-3843	11	1	next	next	ADV
cana-3843	11	2	,	,	PUNCT
cana-3843	11	3	the	the	DET
cana-3843	11	4	genetic	genetic	ADJ
cana-3843	11	5	optimization	optimization	NOUN
cana-3843	11	6	algorithm	algorithm	NOUN
cana-3843	11	7	integrated	integrate	VERB
cana-3843	11	8	with	with	ADP
cana-3843	11	9	the	the	DET
cana-3843	11	10	signal	signal	NOUN
cana-3843	11	11	to	to	PART
cana-3843	11	12	noise	noise	VERB
cana-3843	11	13	ratio	ratio	NOUN
cana-3843	11	14	method	method	NOUN
cana-3843	11	15	is	be	AUX
cana-3843	11	16	applied	apply	VERB
cana-3843	11	17	to	to	PART
cana-3843	11	18	determine	determine	VERB
cana-3843	11	19	an	an	DET
cana-3843	11	20	optimal	optimal	ADJ
cana-3843	11	21	set	set	NOUN
cana-3843	11	22	of	of	ADP
cana-3843	11	23	genes	gene	NOUN
cana-3843	11	24	,	,	PUNCT
cana-3843	11	25	focusing	focus	VERB
cana-3843	11	26	on	on	ADP
cana-3843	11	27	reducing	reduce	VERB
cana-3843	11	28	dimensionality	dimensionality	NOUN
cana-3843	11	29	while	while	SCONJ
cana-3843	11	30	filtering	filter	VERB
cana-3843	11	31	out	out	ADP
cana-3843	11	32	noisy	noisy	ADJ
cana-3843	11	33	and	and	CCONJ
cana-3843	11	34	redundant	redundant	ADJ
cana-3843	11	35	genes	gene	NOUN
cana-3843	11	36	.	.	PUNCT
cana-3843	12	1	in	in	ADP
cana-3843	12	2	the	the	DET
cana-3843	12	3	final	final	ADJ
cana-3843	12	4	phase	phase	NOUN
cana-3843	12	5	,	,	PUNCT
cana-3843	12	6	the	the	DET
cana-3843	12	7	selected	select	VERB
cana-3843	12	8	genes	gene	NOUN
cana-3843	12	9	are	be	AUX
cana-3843	12	10	classified	classify	VERB
cana-3843	12	11	using	use	VERB
cana-3843	12	12	a	a	DET
cana-3843	12	13	deep	deep	ADJ
cana-3843	12	14	learning	learn	VERB
cana-3843	12	15	classification	classification	NOUN
cana-3843	12	16	method	method	NOUN
cana-3843	12	17	namely	namely	ADV
cana-3843	12	18	the	the	DET
cana-3843	12	19	long	long	ADJ
cana-3843	12	20	short	short	ADJ
cana-3843	12	21	term	term	NOUN
cana-3843	12	22	memory	memory	NOUN
cana-3843	12	23	classifier	classifier	NOUN
cana-3843	12	24	is	be	AUX
cana-3843	12	25	utilized	utilize	VERB
cana-3843	12	26	.	.	PUNCT
cana-3843	13	1	the	the	DET
cana-3843	13	2	model	model	NOUN
cana-3843	13	3	’s	’s	PART
cana-3843	13	4	performance	performance	NOUN
cana-3843	13	5	is	be	AUX
cana-3843	13	6	evaluated	evaluate	VERB
cana-3843	13	7	with	with	ADP
cana-3843	13	8	various	various	ADJ
cana-3843	13	9	optimizers	optimizer	NOUN
cana-3843	13	10	,	,	PUNCT
cana-3843	13	11	including	include	VERB
cana-3843	13	12	adam	adam	PROPN
cana-3843	13	13	,	,	PUNCT
cana-3843	13	14	adagrad	adagrad	ADJ
cana-3843	13	15	,	,	PUNCT
cana-3843	13	16	rmsprop	rmsprop	NOUN
cana-3843	13	17	,	,	PUNCT
cana-3843	13	18	and	and	CCONJ
cana-3843	13	19	sgd	sgd	VERB
cana-3843	13	20	by	by	ADP
cana-3843	13	21	comparing	compare	VERB
cana-3843	13	22	accuracy	accuracy	NOUN
cana-3843	13	23	and	and	CCONJ
cana-3843	13	24	loss	loss	NOUN
cana-3843	13	25	values	value	NOUN
cana-3843	13	26	.	.	PUNCT
cana-3843	14	1	also	also	ADV
cana-3843	14	2	calculate	calculate	VERB
cana-3843	14	3	the	the	DET
cana-3843	14	4	other	other	ADJ
cana-3843	14	5	classification	classification	NOUN
cana-3843	14	6	parameters	parameter	NOUN
cana-3843	14	7	such	such	ADJ
cana-3843	14	8	as	as	ADP
cana-3843	14	9	precision	precision	NOUN
cana-3843	14	10	,	,	PUNCT
cana-3843	14	11	recall	recall	NOUN
cana-3843	14	12	,	,	PUNCT
cana-3843	14	13	and	and	CCONJ
cana-3843	14	14	f1	f1	ADJ
cana-3843	14	15	-	-	PUNCT
cana-3843	14	16	score	score	NOUN
cana-3843	14	17	value	value	NOUN
cana-3843	14	18	.	.	PUNCT
cana-3843	15	1	finally	finally	ADV
cana-3843	15	2	,	,	PUNCT
cana-3843	15	3	comparative	comparative	ADJ
cana-3843	15	4	analyses	analysis	NOUN
cana-3843	15	5	of	of	ADP
cana-3843	15	6	these	these	DET
cana-3843	15	7	metrics	metric	NOUN
cana-3843	15	8	across	across	ADP
cana-3843	15	9	the	the	DET
cana-3843	15	10	different	different	ADJ
cana-3843	15	11	optimizers	optimizer	NOUN
cana-3843	15	12	are	be	AUX
cana-3843	15	13	performed	perform	VERB
cana-3843	15	14	.	.	PUNCT
cana-3843	16	1	the	the	DET
cana-3843	16	2	experimental	experimental	ADJ
cana-3843	16	3	results	result	NOUN
cana-3843	16	4	demonstrate	demonstrate	VERB
cana-3843	16	5	that	that	SCONJ
cana-3843	16	6	the	the	DET
cana-3843	16	7	research	research	NOUN
cana-3843	16	8	model	model	PROPN
cana-3843	16	9	cor	cor	PROPN
cana-3843	16	10	-	-	PROPN
cana-3843	16	11	ga_snr	ga_snr	PROPN
cana-3843	16	12	-	-	PUNCT
cana-3843	16	13	lstm	lstm	NOUN
cana-3843	16	14	significantly	significantly	ADV
cana-3843	16	15	improves	improve	VERB
cana-3843	16	16	the	the	DET
cana-3843	16	17	detection	detection	NOUN
cana-3843	16	18	analysis	analysis	NOUN
cana-3843	16	19	by	by	ADP
cana-3843	16	20	reducing	reduce	VERB
cana-3843	16	21	the	the	DET
cana-3843	16	22	number	number	NOUN
cana-3843	16	23	of	of	ADP
cana-3843	16	24	features	feature	NOUN
cana-3843	16	25	in	in	ADP
cana-3843	16	26	the	the	DET
cana-3843	16	27	gene	gene	NOUN
cana-3843	16	28	data	datum	NOUN
cana-3843	16	29	,	,	PUNCT
cana-3843	16	30	enhancing	enhance	VERB
cana-3843	16	31	the	the	DET
cana-3843	16	32	accuracy	accuracy	NOUN
cana-3843	16	33	value	value	NOUN
cana-3843	16	34	,	,	PUNCT
cana-3843	16	35	and	and	CCONJ
cana-3843	16	36	minimizing	minimize	VERB
cana-3843	16	37	the	the	DET
cana-3843	16	38	loss	loss	NOUN
cana-3843	16	39	value	value	NOUN
cana-3843	16	40	.	.	PUNCT
cana-3843	17	1	the	the	DET
cana-3843	17	2	adam	adam	PROPN
cana-3843	17	3	optimizer	optimizer	NOUN
cana-3843	17	4	yielded	yield	VERB
cana-3843	17	5	the	the	DET
cana-3843	17	6	optimal	optimal	ADJ
cana-3843	17	7	performance	performance	NOUN
cana-3843	17	8	with	with	ADP
cana-3843	17	9	an	an	DET
cana-3843	17	10	accuracy	accuracy	NOUN
cana-3843	17	11	of	of	ADP
cana-3843	17	12	88.45	88.45	NUM
cana-3843	17	13	%	%	NOUN
cana-3843	17	14	and	and	CCONJ
cana-3843	17	15	a	a	DET
cana-3843	17	16	loss	loss	NOUN
cana-3843	17	17	value	value	NOUN
cana-3843	17	18	of	of	ADP
cana-3843	17	19	0.1612	0.1612	NUM
cana-3843	17	20	.	.	PUNCT
cana-3843	18	1	the	the	DET
cana-3843	18	2	proposed	propose	VERB
cana-3843	18	3	method	method	NOUN
cana-3843	18	4	effectively	effectively	ADV
cana-3843	18	5	identifies	identify	VERB
cana-3843	18	6	the	the	DET
cana-3843	18	7	most	most	ADV
cana-3843	18	8	relevant	relevant	ADJ
cana-3843	18	9	genes	gene	NOUN
cana-3843	18	10	responsible	responsible	ADJ
cana-3843	18	11	for	for	ADP
cana-3843	18	12	detecting	detect	VERB
cana-3843	18	13	and	and	CCONJ
cana-3843	18	14	predicting	predict	VERB
cana-3843	18	15	leukemia	leukemia	NOUN
cana-3843	18	16	cancer	cancer	NOUN
cana-3843	18	17	disease	disease	NOUN
cana-3843	18	18	.	.	PUNCT
cana-3843	19	1	keywords	keyword	NOUN
cana-3843	19	2	:	:	PUNCT
cana-3843	19	3	classification	classification	NOUN
cana-3843	19	4	,	,	PUNCT
cana-3843	19	5	genetic	genetic	ADJ
cana-3843	19	6	optimization	optimization	NOUN
cana-3843	19	7	technique	technique	NOUN
cana-3843	19	8	,	,	PUNCT
cana-3843	19	9	long	long	ADJ
cana-3843	19	10	short	short	ADJ
cana-3843	19	11	term	term	NOUN
cana-3843	19	12	memory	memory	NOUN
cana-3843	19	13	,	,	PUNCT
cana-3843	19	14	microarray	microarray	VERB
cana-3843	19	15	analysis	analysis	NOUN
cana-3843	19	16	,	,	PUNCT
cana-3843	19	17	signal	signal	NOUN
cana-3843	19	18	-	-	PUNCT
cana-3843	19	19	to	to	ADP
cana-3843	19	20	-	-	PUNCT
cana-3843	19	21	noise	noise	NOUN
cana-3843	19	22	ratio	ratio	NOUN
cana-3843	19	23	.	.	PUNCT
cana-3843	20	1	1	1	X
cana-3843	20	2	.	.	X
cana-3843	20	3	introduction	introduction	NOUN
cana-3843	20	4	a	a	DET
cana-3843	20	5	key	key	ADJ
cana-3843	20	6	challenge	challenge	NOUN
cana-3843	20	7	in	in	ADP
cana-3843	20	8	the	the	DET
cana-3843	20	9	medical	medical	ADJ
cana-3843	20	10	industry	industry	NOUN
cana-3843	20	11	is	be	AUX
cana-3843	20	12	accurately	accurately	ADV
cana-3843	20	13	diagnosing	diagnose	VERB
cana-3843	20	14	cancer	cancer	NOUN
cana-3843	20	15	patients	patient	NOUN
cana-3843	20	16	at	at	ADP
cana-3843	20	17	an	an	DET
cana-3843	20	18	early	early	ADJ
cana-3843	20	19	stage	stage	NOUN
cana-3843	20	20	.	.	PUNCT
cana-3843	21	1	conventional	conventional	ADJ
cana-3843	21	2	diagnostic	diagnostic	ADJ
cana-3843	21	3	techniques	technique	NOUN
cana-3843	21	4	,	,	PUNCT
cana-3843	21	5	including	include	VERB
cana-3843	21	6	non	non	ADJ
cana-3843	21	7	-	-	ADJ
cana-3843	21	8	invasive	invasive	ADJ
cana-3843	21	9	methods	method	NOUN
cana-3843	21	10	,	,	PUNCT
cana-3843	21	11	invasive	invasive	ADJ
cana-3843	21	12	procedures	procedure	NOUN
cana-3843	21	13	,	,	PUNCT
cana-3843	21	14	and	and	CCONJ
cana-3843	21	15	fine	fine	ADJ
cana-3843	21	16	needle	needle	NOUN
cana-3843	21	17	aspiration	aspiration	NOUN
cana-3843	21	18	cytology	cytology	NOUN
cana-3843	21	19	may	may	AUX
cana-3843	21	20	sometimes	sometimes	ADV
cana-3843	21	21	misinterpret	misinterpret	VERB
cana-3843	21	22	the	the	DET
cana-3843	21	23	distinction	distinction	NOUN
cana-3843	21	24	between	between	ADP
cana-3843	21	25	normal	normal	ADJ
cana-3843	21	26	and	and	CCONJ
cana-3843	21	27	cancerous	cancerous	ADJ
cana-3843	21	28	genes	gene	NOUN
cana-3843	21	29	,	,	PUNCT
cana-3843	21	30	leading	lead	VERB
cana-3843	21	31	to	to	ADP
cana-3843	21	32	adverse	adverse	ADJ
cana-3843	21	33	effects	effect	NOUN
cana-3843	21	34	.	.	PUNCT
cana-3843	22	1	leukemia	leukemia	NOUN
cana-3843	22	2	is	be	AUX
cana-3843	22	3	a	a	DET
cana-3843	22	4	form	form	NOUN
cana-3843	22	5	of	of	ADP
cana-3843	22	6	cancer	cancer	NOUN
cana-3843	22	7	originating	originating	NOUN
cana-3843	22	8	in	in	ADP
cana-3843	22	9	the	the	DET
cana-3843	22	10	bone	bone	NOUN
cana-3843	22	11	marrow	marrow	NOUN
cana-3843	22	12	,	,	PUNCT
cana-3843	22	13	often	often	ADV
cana-3843	22	14	caused	cause	VERB
cana-3843	22	15	by	by	ADP
cana-3843	22	16	genetic	genetic	ADJ
cana-3843	22	17	abnormalities	abnormality	NOUN
cana-3843	22	18	[	[	X
cana-3843	22	19	1	1	NUM
cana-3843	22	20	]	]	PUNCT
cana-3843	22	21	.	.	PUNCT
cana-3843	23	1	the	the	DET
cana-3843	23	2	primary	primary	ADJ
cana-3843	23	3	cause	cause	NOUN
cana-3843	23	4	of	of	ADP
cana-3843	23	5	leukemia	leukemia	NOUN
cana-3843	23	6	is	be	AUX
cana-3843	23	7	the	the	DET
cana-3843	23	8	mutation	mutation	NOUN
cana-3843	23	9	of	of	ADP
cana-3843	23	10	cells	cell	NOUN
cana-3843	23	11	within	within	ADP
cana-3843	23	12	the	the	DET
cana-3843	23	13	bone	bone	NOUN
cana-3843	23	14	marrow	marrow	NOUN
cana-3843	23	15	which	which	PRON
cana-3843	23	16	can	can	AUX
cana-3843	23	17	sometimes	sometimes	ADV
cana-3843	23	18	obstruct	obstruct	VERB
cana-3843	23	19	the	the	DET
cana-3843	23	20	production	production	NOUN
cana-3843	23	21	of	of	ADP
cana-3843	23	22	healthy	healthy	ADJ
cana-3843	23	23	cells	cell	NOUN
cana-3843	23	24	.	.	PUNCT
cana-3843	24	1	detecting	detect	VERB
cana-3843	24	2	dna	dna	NOUN
cana-3843	24	3	mutations	mutation	NOUN
cana-3843	24	4	for	for	ADP
cana-3843	24	5	the	the	DET
cana-3843	24	6	early	early	ADJ
cana-3843	24	7	identification	identification	NOUN
cana-3843	24	8	of	of	ADP
cana-3843	24	9	genetic	genetic	ADJ
cana-3843	24	10	disorders	disorder	NOUN
cana-3843	24	11	is	be	AUX
cana-3843	24	12	a	a	DET
cana-3843	24	13	challenging	challenging	ADJ
cana-3843	24	14	process	process	NOUN
cana-3843	24	15	.	.	PUNCT
cana-3843	25	1	before	before	ADP
cana-3843	25	2	the	the	DET
cana-3843	25	3	development	development	NOUN
cana-3843	25	4	of	of	ADP
cana-3843	25	5	next	next	ADJ
cana-3843	25	6	-	-	PUNCT
cana-3843	25	7	generation	generation	NOUN
cana-3843	25	8	sequencing	sequencing	NOUN
cana-3843	25	9	,	,	PUNCT
cana-3843	25	10	microarray	microarray	NOUN
cana-3843	25	11	technology	technology	NOUN
cana-3843	25	12	had	have	VERB
cana-3843	25	13	a	a	DET
cana-3843	25	14	significant	significant	ADJ
cana-3843	25	15	impact	impact	NOUN
cana-3843	25	16	on	on	ADP
cana-3843	25	17	the	the	DET
cana-3843	25	18	domain	domain	NOUN
cana-3843	25	19	of	of	ADP
cana-3843	25	20	cancer	cancer	NOUN
cana-3843	25	21	biology[2	biology[2	PROPN
cana-3843	25	22	]	]	PUNCT
cana-3843	25	23	.	.	PUNCT
cana-3843	26	1	the	the	DET
cana-3843	26	2	communications	communication	NOUN
cana-3843	26	3	on	on	ADP
cana-3843	26	4	applied	apply	VERB
cana-3843	26	5	nonlinear	nonlinear	ADJ
cana-3843	26	6	analysis	analysis	NOUN
cana-3843	26	7	issn	issn	NOUN
cana-3843	26	8	:	:	PUNCT
cana-3843	26	9	1074	1074	NUM
cana-3843	26	10	-	-	PUNCT
cana-3843	26	11	133x	133x	NUM
cana-3843	26	12	vol	vol	NOUN
cana-3843	26	13	32	32	NUM
cana-3843	26	14	no	no	NOUN
cana-3843	26	15	.	.	PUNCT
cana-3843	27	1	9s	9s	NUM
cana-3843	27	2	(	(	PUNCT
cana-3843	27	3	2025	2025	NUM
cana-3843	27	4	)	)	PUNCT
cana-3843	27	5	120	120	NUM
cana-3843	27	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	27	7	technology	technology	NOUN
cana-3843	27	8	enabled	enable	VERB
cana-3843	27	9	thousands	thousand	NOUN
cana-3843	27	10	of	of	ADP
cana-3843	27	11	genes	gene	NOUN
cana-3843	27	12	to	to	PART
cana-3843	27	13	be	be	AUX
cana-3843	27	14	monitored	monitor	VERB
cana-3843	27	15	simultaneously	simultaneously	ADV
cana-3843	27	16	to	to	PART
cana-3843	27	17	detect	detect	VERB
cana-3843	27	18	complex	complex	ADJ
cana-3843	27	19	gene	gene	NOUN
cana-3843	27	20	expression	expression	NOUN
cana-3843	27	21	patterns	pattern	NOUN
cana-3843	27	22	[	[	X
cana-3843	27	23	3	3	NUM
cana-3843	27	24	]	]	PUNCT
cana-3843	27	25	.	.	PUNCT
cana-3843	28	1	dna	dna	PROPN
cana-3843	28	2	microarray	microarray	PROPN
cana-3843	28	3	data	data	PROPN
cana-3843	28	4	,	,	PUNCT
cana-3843	28	5	containing	contain	VERB
cana-3843	28	6	gene	gene	NOUN
cana-3843	28	7	expression	expression	NOUN
cana-3843	28	8	profiles	profile	NOUN
cana-3843	28	9	,	,	PUNCT
cana-3843	28	10	facilitate	facilitate	VERB
cana-3843	28	11	precise	precise	ADJ
cana-3843	28	12	cancer	cancer	NOUN
cana-3843	28	13	diagnoses	diagnosis	NOUN
cana-3843	28	14	in	in	ADP
cana-3843	28	15	the	the	DET
cana-3843	28	16	healthcare	healthcare	NOUN
cana-3843	28	17	sector	sector	NOUN
cana-3843	28	18	.	.	PUNCT
cana-3843	29	1	however	however	ADV
cana-3843	29	2	,	,	PUNCT
cana-3843	29	3	the	the	DET
cana-3843	29	4	nature	nature	NOUN
cana-3843	29	5	of	of	ADP
cana-3843	29	6	the	the	DET
cana-3843	29	7	microarray	microarray	NOUN
cana-3843	29	8	gene	gene	NOUN
cana-3843	29	9	dataset	dataset	VERB
cana-3843	29	10	is	be	AUX
cana-3843	29	11	high	high	ADV
cana-3843	29	12	-	-	PUNCT
cana-3843	29	13	dimensional	dimensional	ADJ
cana-3843	29	14	,	,	PUNCT
cana-3843	29	15	containing	contain	VERB
cana-3843	29	16	a	a	DET
cana-3843	29	17	large	large	ADJ
cana-3843	29	18	number	number	NOUN
cana-3843	29	19	of	of	ADP
cana-3843	29	20	genes	gene	NOUN
cana-3843	29	21	and	and	CCONJ
cana-3843	29	22	a	a	DET
cana-3843	29	23	small	small	ADJ
cana-3843	29	24	number	number	NOUN
cana-3843	29	25	of	of	ADP
cana-3843	29	26	patient	patient	ADJ
cana-3843	29	27	sample	sample	NOUN
cana-3843	29	28	instances	instance	NOUN
cana-3843	29	29	.	.	PUNCT
cana-3843	30	1	this	this	PRON
cana-3843	30	2	leads	lead	VERB
cana-3843	30	3	to	to	ADP
cana-3843	30	4	the	the	DET
cana-3843	30	5	curse	curse	NOUN
cana-3843	30	6	of	of	ADP
cana-3843	30	7	dimensionality	dimensionality	NOUN
cana-3843	30	8	that	that	PRON
cana-3843	30	9	affects	affect	VERB
cana-3843	30	10	the	the	DET
cana-3843	30	11	prediction	prediction	NOUN
cana-3843	30	12	rate	rate	NOUN
cana-3843	30	13	of	of	ADP
cana-3843	30	14	the	the	DET
cana-3843	30	15	cancer	cancer	NOUN
cana-3843	30	16	disease	disease	NOUN
cana-3843	30	17	[	[	X
cana-3843	30	18	4	4	NUM
cana-3843	30	19	]	]	PUNCT
cana-3843	30	20	.	.	PUNCT
cana-3843	31	1	also	also	ADV
cana-3843	31	2	,	,	PUNCT
cana-3843	31	3	the	the	DET
cana-3843	31	4	majority	majority	NOUN
cana-3843	31	5	of	of	ADP
cana-3843	31	6	genes	gene	NOUN
cana-3843	31	7	are	be	AUX
cana-3843	31	8	non	non	ADJ
cana-3843	31	9	-	-	ADJ
cana-3843	31	10	informative	informative	ADJ
cana-3843	31	11	and	and	CCONJ
cana-3843	31	12	redundant	redundant	ADJ
cana-3843	31	13	.	.	PUNCT
cana-3843	32	1	the	the	DET
cana-3843	32	2	dataset	dataset	NOUN
cana-3843	32	3	contains	contain	VERB
cana-3843	32	4	a	a	DET
cana-3843	32	5	1:10	1:10	NUM
cana-3843	32	6	ratio	ratio	NOUN
cana-3843	32	7	of	of	ADP
cana-3843	32	8	relevant	relevant	ADJ
cana-3843	32	9	to	to	ADP
cana-3843	32	10	noisy	noisy	ADJ
cana-3843	32	11	data	datum	NOUN
cana-3843	32	12	,	,	PUNCT
cana-3843	32	13	which	which	PRON
cana-3843	32	14	negatively	negatively	ADV
cana-3843	32	15	impacts	impact	VERB
cana-3843	32	16	the	the	DET
cana-3843	32	17	model	model	NOUN
cana-3843	32	18	’s	’s	PART
cana-3843	32	19	performance	performance	NOUN
cana-3843	32	20	when	when	SCONJ
cana-3843	32	21	conventional	conventional	ADJ
cana-3843	32	22	methods	method	NOUN
cana-3843	32	23	are	be	AUX
cana-3843	32	24	directly	directly	ADV
cana-3843	32	25	implemented	implement	VERB
cana-3843	32	26	[	[	PUNCT
cana-3843	32	27	5	5	NUM
cana-3843	32	28	]	]	PUNCT
cana-3843	32	29	.	.	PUNCT
cana-3843	33	1	to	to	PART
cana-3843	33	2	enhance	enhance	VERB
cana-3843	33	3	the	the	DET
cana-3843	33	4	effectiveness	effectiveness	NOUN
cana-3843	33	5	of	of	ADP
cana-3843	33	6	the	the	DET
cana-3843	33	7	microarray	microarray	NOUN
cana-3843	33	8	data	datum	NOUN
cana-3843	33	9	,	,	PUNCT
cana-3843	33	10	gene	gene	NOUN
cana-3843	33	11	/	/	SYM
cana-3843	33	12	attribute	attribute	NOUN
cana-3843	33	13	selection	selection	NOUN
cana-3843	33	14	techniques	technique	NOUN
cana-3843	33	15	perform	perform	VERB
cana-3843	33	16	an	an	DET
cana-3843	33	17	important	important	ADJ
cana-3843	33	18	role	role	NOUN
cana-3843	33	19	in	in	ADP
cana-3843	33	20	processing	process	VERB
cana-3843	33	21	the	the	DET
cana-3843	33	22	data	datum	NOUN
cana-3843	33	23	and	and	CCONJ
cana-3843	33	24	improving	improve	VERB
cana-3843	33	25	the	the	DET
cana-3843	33	26	accuracy	accuracy	NOUN
cana-3843	33	27	of	of	ADP
cana-3843	33	28	classifier	classifier	NOUN
cana-3843	33	29	models	model	NOUN
cana-3843	33	30	[	[	X
cana-3843	33	31	6	6	NUM
cana-3843	33	32	]	]	PUNCT
cana-3843	33	33	.	.	PUNCT
cana-3843	34	1	the	the	DET
cana-3843	34	2	main	main	ADJ
cana-3843	34	3	goals	goal	NOUN
cana-3843	34	4	of	of	ADP
cana-3843	34	5	the	the	DET
cana-3843	34	6	research	research	NOUN
cana-3843	34	7	are	be	AUX
cana-3843	34	8	to	to	PART
cana-3843	34	9	identify	identify	VERB
cana-3843	34	10	significant	significant	ADJ
cana-3843	34	11	biomarker	biomarker	NOUN
cana-3843	34	12	genes	gene	NOUN
cana-3843	34	13	in	in	ADP
cana-3843	34	14	gene	gene	NOUN
cana-3843	34	15	expression	expression	NOUN
cana-3843	34	16	data	datum	NOUN
cana-3843	34	17	using	use	VERB
cana-3843	34	18	gene	gene	NOUN
cana-3843	34	19	selection	selection	NOUN
cana-3843	34	20	techniques	technique	NOUN
cana-3843	34	21	and	and	CCONJ
cana-3843	34	22	to	to	PART
cana-3843	34	23	classify	classify	VERB
cana-3843	34	24	the	the	DET
cana-3843	34	25	data	datum	NOUN
cana-3843	34	26	through	through	ADP
cana-3843	34	27	deep	deep	ADJ
cana-3843	34	28	learning	learning	NOUN
cana-3843	34	29	techniques	technique	NOUN
cana-3843	34	30	.	.	PUNCT
cana-3843	35	1	initially	initially	ADV
cana-3843	35	2	,	,	PUNCT
cana-3843	35	3	the	the	DET
cana-3843	35	4	model	model	NOUN
cana-3843	35	5	checks	check	VERB
cana-3843	35	6	the	the	DET
cana-3843	35	7	multi	multi	NOUN
cana-3843	35	8	-	-	NOUN
cana-3843	35	9	collinearity	collinearity	NOUN
cana-3843	35	10	between	between	ADP
cana-3843	35	11	genes	gene	NOUN
cana-3843	35	12	using	use	VERB
cana-3843	35	13	correlation	correlation	NOUN
cana-3843	35	14	and	and	CCONJ
cana-3843	35	15	identifies	identify	VERB
cana-3843	35	16	the	the	DET
cana-3843	35	17	low	low	ADJ
cana-3843	35	18	inter	inter	ADJ
cana-3843	35	19	-	-	ADJ
cana-3843	35	20	correlated	correlate	VERB
cana-3843	35	21	features	feature	NOUN
cana-3843	35	22	.	.	PUNCT
cana-3843	36	1	an	an	DET
cana-3843	36	2	optimization	optimization	NOUN
cana-3843	36	3	technique	technique	NOUN
cana-3843	36	4	with	with	ADP
cana-3843	36	5	the	the	DET
cana-3843	36	6	rank	rank	NOUN
cana-3843	36	7	filter	filter	NOUN
cana-3843	36	8	method	method	NOUN
cana-3843	36	9	is	be	AUX
cana-3843	36	10	utilized	utilize	VERB
cana-3843	36	11	to	to	PART
cana-3843	36	12	identify	identify	VERB
cana-3843	36	13	key	key	ADJ
cana-3843	36	14	genes	gene	NOUN
cana-3843	36	15	from	from	ADP
cana-3843	36	16	cancer	cancer	NOUN
cana-3843	36	17	data	datum	NOUN
cana-3843	36	18	,	,	PUNCT
cana-3843	36	19	aiming	aim	VERB
cana-3843	36	20	to	to	PART
cana-3843	36	21	enhance	enhance	VERB
cana-3843	36	22	prediction	prediction	NOUN
cana-3843	36	23	accuracy	accuracy	NOUN
cana-3843	36	24	.	.	PUNCT
cana-3843	37	1	the	the	DET
cana-3843	37	2	designed	design	VERB
cana-3843	37	3	model	model	NOUN
cana-3843	37	4	utilized	utilize	VERB
cana-3843	37	5	the	the	DET
cana-3843	37	6	genetic	genetic	ADJ
cana-3843	37	7	optimization	optimization	NOUN
cana-3843	37	8	technique	technique	NOUN
cana-3843	37	9	with	with	ADP
cana-3843	37	10	signal	signal	NOUN
cana-3843	37	11	to	to	PART
cana-3843	37	12	noise	noise	VERB
cana-3843	37	13	ratio	ratio	NOUN
cana-3843	37	14	method	method	NOUN
cana-3843	37	15	to	to	PART
cana-3843	37	16	effectively	effectively	ADV
cana-3843	37	17	evaluate	evaluate	VERB
cana-3843	37	18	the	the	DET
cana-3843	37	19	gene	gene	NOUN
cana-3843	37	20	patterns	pattern	NOUN
cana-3843	37	21	and	and	CCONJ
cana-3843	37	22	identify	identify	VERB
cana-3843	37	23	an	an	DET
cana-3843	37	24	optimal	optimal	ADJ
cana-3843	37	25	set	set	NOUN
cana-3843	37	26	of	of	ADP
cana-3843	37	27	prominent	prominent	ADJ
cana-3843	37	28	biomarker	biomarker	NOUN
cana-3843	37	29	genes	gene	NOUN
cana-3843	37	30	.	.	PUNCT
cana-3843	38	1	the	the	DET
cana-3843	38	2	selected	select	VERB
cana-3843	38	3	genes	gene	NOUN
cana-3843	38	4	are	be	AUX
cana-3843	38	5	applied	apply	VERB
cana-3843	38	6	in	in	ADP
cana-3843	38	7	deep	deep	ADJ
cana-3843	38	8	learning	learn	VERB
cana-3843	38	9	classification	classification	NOUN
cana-3843	38	10	methods	method	NOUN
cana-3843	38	11	such	such	ADJ
cana-3843	38	12	as	as	ADP
cana-3843	38	13	the	the	DET
cana-3843	38	14	long	long	ADJ
cana-3843	38	15	shortterm	shortterm	NOUN
cana-3843	38	16	memory	memory	NOUN
cana-3843	38	17	model	model	NOUN
cana-3843	38	18	to	to	PART
cana-3843	38	19	accurately	accurately	ADV
cana-3843	38	20	recognize	recognize	VERB
cana-3843	38	21	the	the	DET
cana-3843	38	22	cancer	cancer	NOUN
cana-3843	38	23	subtype	subtype	NOUN
cana-3843	38	24	genes	gene	NOUN
cana-3843	38	25	.	.	PUNCT
cana-3843	39	1	the	the	DET
cana-3843	39	2	research	research	NOUN
cana-3843	39	3	paper	paper	NOUN
cana-3843	39	4	is	be	AUX
cana-3843	39	5	structured	structure	VERB
cana-3843	39	6	as	as	SCONJ
cana-3843	39	7	follows	follow	VERB
cana-3843	39	8	:	:	PUNCT
cana-3843	39	9	section	section	NOUN
cana-3843	39	10	2	2	NUM
cana-3843	39	11	presents	present	VERB
cana-3843	39	12	a	a	DET
cana-3843	39	13	review	review	NOUN
cana-3843	39	14	of	of	ADP
cana-3843	39	15	related	related	ADJ
cana-3843	39	16	literature	literature	NOUN
cana-3843	39	17	,	,	PUNCT
cana-3843	39	18	while	while	SCONJ
cana-3843	39	19	section	section	NOUN
cana-3843	39	20	3	3	NUM
cana-3843	39	21	outlines	outline	VERB
cana-3843	39	22	the	the	DET
cana-3843	39	23	research	research	NOUN
cana-3843	39	24	resources	resource	NOUN
cana-3843	39	25	and	and	CCONJ
cana-3843	39	26	methods	method	NOUN
cana-3843	39	27	,	,	PUNCT
cana-3843	39	28	including	include	VERB
cana-3843	39	29	details	detail	NOUN
cana-3843	39	30	of	of	ADP
cana-3843	39	31	the	the	DET
cana-3843	39	32	dataset	dataset	NOUN
cana-3843	39	33	,	,	PUNCT
cana-3843	39	34	an	an	DET
cana-3843	39	35	overview	overview	NOUN
cana-3843	39	36	of	of	ADP
cana-3843	39	37	the	the	DET
cana-3843	39	38	genetic	genetic	ADJ
cana-3843	39	39	optimization	optimization	NOUN
cana-3843	39	40	technique	technique	NOUN
cana-3843	39	41	with	with	ADP
cana-3843	39	42	signal	signal	NOUN
cana-3843	39	43	to	to	PART
cana-3843	39	44	noise	noise	VERB
cana-3843	39	45	ratio	ratio	NOUN
cana-3843	39	46	method	method	NOUN
cana-3843	39	47	,	,	PUNCT
cana-3843	39	48	and	and	CCONJ
cana-3843	39	49	long	long	ADJ
cana-3843	39	50	short	short	ADJ
cana-3843	39	51	term	term	NOUN
cana-3843	39	52	memory	memory	NOUN
cana-3843	39	53	classification	classification	NOUN
cana-3843	39	54	model	model	NOUN
cana-3843	39	55	.	.	PUNCT
cana-3843	40	1	section	section	NOUN
cana-3843	40	2	4	4	NUM
cana-3843	40	3	explores	explore	VERB
cana-3843	40	4	the	the	DET
cana-3843	40	5	details	detail	NOUN
cana-3843	40	6	of	of	ADP
cana-3843	40	7	the	the	DET
cana-3843	40	8	proposed	propose	VERB
cana-3843	40	9	model	model	NOUN
cana-3843	40	10	(	(	PUNCT
cana-3843	40	11	cor	cor	PROPN
cana-3843	40	12	-	-	PROPN
cana-3843	40	13	ga_snr	ga_snr	NOUN
cana-3843	40	14	-	-	PUNCT
cana-3843	40	15	lstm	lstm	NOUN
cana-3843	40	16	)	)	PUNCT
cana-3843	40	17	.	.	PUNCT
cana-3843	41	1	section	section	NOUN
cana-3843	41	2	5	5	NUM
cana-3843	41	3	discusses	discuss	VERB
cana-3843	41	4	the	the	DET
cana-3843	41	5	simulation	simulation	NOUN
cana-3843	41	6	analysis	analysis	NOUN
cana-3843	41	7	of	of	ADP
cana-3843	41	8	the	the	DET
cana-3843	41	9	research	research	NOUN
cana-3843	41	10	work	work	NOUN
cana-3843	41	11	and	and	CCONJ
cana-3843	41	12	comparative	comparative	ADJ
cana-3843	41	13	analysis	analysis	NOUN
cana-3843	41	14	with	with	ADP
cana-3843	41	15	existing	exist	VERB
cana-3843	41	16	techniques	technique	NOUN
cana-3843	41	17	.	.	PUNCT
cana-3843	42	1	finally	finally	ADV
cana-3843	42	2	,	,	PUNCT
cana-3843	42	3	the	the	DET
cana-3843	42	4	research	research	NOUN
cana-3843	42	5	findings	finding	NOUN
cana-3843	42	6	are	be	AUX
cana-3843	42	7	presented	present	VERB
cana-3843	42	8	in	in	ADP
cana-3843	42	9	the	the	DET
cana-3843	42	10	conclusion	conclusion	NOUN
cana-3843	42	11	part	part	NOUN
cana-3843	42	12	.	.	PUNCT
cana-3843	43	1	2	2	X
cana-3843	43	2	.	.	X
cana-3843	43	3	related	relate	VERB
cana-3843	43	4	work	work	NOUN
cana-3843	43	5	this	this	DET
cana-3843	43	6	section	section	NOUN
cana-3843	43	7	briefly	briefly	NOUN
cana-3843	43	8	overviews	overview	VERB
cana-3843	43	9	existing	exist	VERB
cana-3843	43	10	attribute	attribute	NOUN
cana-3843	43	11	/	/	SYM
cana-3843	43	12	gene	gene	NOUN
cana-3843	43	13	selection	selection	NOUN
cana-3843	43	14	methods	method	NOUN
cana-3843	43	15	for	for	ADP
cana-3843	43	16	identifying	identify	VERB
cana-3843	43	17	biomarker	biomarker	NOUN
cana-3843	43	18	genes	gene	NOUN
cana-3843	43	19	in	in	ADP
cana-3843	43	20	leukemia	leukemia	NOUN
cana-3843	43	21	cancer	cancer	NOUN
cana-3843	43	22	and	and	CCONJ
cana-3843	43	23	evaluating	evaluate	VERB
cana-3843	43	24	their	their	PRON
cana-3843	43	25	prediction	prediction	NOUN
cana-3843	43	26	performance	performance	NOUN
cana-3843	43	27	through	through	ADP
cana-3843	43	28	different	different	ADJ
cana-3843	43	29	classifiers	classifier	NOUN
cana-3843	43	30	.	.	PUNCT
cana-3843	44	1	waleed	waleed	PROPN
cana-3843	44	2	ali	ali	PROPN
cana-3843	44	3	et	et	PROPN
cana-3843	44	4	al	al	PROPN
cana-3843	44	5	.	.	PUNCT
cana-3843	45	1	[	[	X
cana-3843	45	2	7	7	X
cana-3843	45	3	]	]	PUNCT
cana-3843	45	4	presented	present	VERB
cana-3843	45	5	a	a	DET
cana-3843	45	6	hybrid	hybrid	ADJ
cana-3843	45	7	attribute	attribute	NOUN
cana-3843	45	8	selection	selection	NOUN
cana-3843	45	9	model	model	NOUN
cana-3843	45	10	that	that	PRON
cana-3843	45	11	integrates	integrate	VERB
cana-3843	45	12	filter	filter	NOUN
cana-3843	45	13	and	and	CCONJ
cana-3843	45	14	optimization	optimization	NOUN
cana-3843	45	15	techniques	technique	NOUN
cana-3843	45	16	.	.	PUNCT
cana-3843	46	1	in	in	ADP
cana-3843	46	2	the	the	DET
cana-3843	46	3	proposed	propose	VERB
cana-3843	46	4	method	method	NOUN
cana-3843	46	5	,	,	PUNCT
cana-3843	46	6	mutual	mutual	ADJ
cana-3843	46	7	information	information	NOUN
cana-3843	46	8	,	,	PUNCT
cana-3843	46	9	chi	chi	NOUN
cana-3843	46	10	-	-	PUNCT
cana-3843	46	11	square	square	NOUN
cana-3843	46	12	,	,	PUNCT
cana-3843	46	13	and	and	CCONJ
cana-3843	46	14	igr	igr	NOUN
cana-3843	46	15	filter	filter	NOUN
cana-3843	46	16	methods	method	NOUN
cana-3843	46	17	are	be	AUX
cana-3843	46	18	used	use	VERB
cana-3843	46	19	to	to	PART
cana-3843	46	20	eliminate	eliminate	VERB
cana-3843	46	21	irrelevant	irrelevant	ADJ
cana-3843	46	22	features	feature	NOUN
cana-3843	46	23	.	.	PUNCT
cana-3843	47	1	after	after	ADP
cana-3843	47	2	selecting	select	VERB
cana-3843	47	3	the	the	DET
cana-3843	47	4	relevant	relevant	ADJ
cana-3843	47	5	attributes	attribute	NOUN
cana-3843	47	6	,	,	PUNCT
cana-3843	47	7	a	a	DET
cana-3843	47	8	genetic	genetic	ADJ
cana-3843	47	9	algorithm	algorithm	NOUN
cana-3843	47	10	is	be	AUX
cana-3843	47	11	employed	employ	VERB
cana-3843	47	12	to	to	PART
cana-3843	47	13	select	select	VERB
cana-3843	47	14	optimal	optimal	ADJ
cana-3843	47	15	features	feature	NOUN
cana-3843	47	16	,	,	PUNCT
cana-3843	47	17	enhancing	enhance	VERB
cana-3843	47	18	the	the	DET
cana-3843	47	19	model	model	NOUN
cana-3843	47	20	's	's	PART
cana-3843	47	21	performance	performance	NOUN
cana-3843	47	22	for	for	ADP
cana-3843	47	23	cancer	cancer	NOUN
cana-3843	47	24	classification	classification	NOUN
cana-3843	47	25	.	.	PUNCT
cana-3843	48	1	mehrdad	mehrdad	PROPN
cana-3843	48	2	rostami	rostami	PROPN
cana-3843	48	3	et	et	PROPN
cana-3843	48	4	al	al	PROPN
cana-3843	48	5	.	.	PUNCT
cana-3843	49	1	[	[	X
cana-3843	49	2	8	8	NUM
cana-3843	49	3	]	]	PUNCT
cana-3843	49	4	proposed	propose	VERB
cana-3843	49	5	an	an	DET
cana-3843	49	6	innovative	innovative	ADJ
cana-3843	49	7	biomarker	biomarker	NOUN
cana-3843	49	8	gene	gene	NOUN
cana-3843	49	9	selection	selection	NOUN
cana-3843	49	10	model	model	NOUN
cana-3843	49	11	based	base	VERB
cana-3843	49	12	on	on	ADP
cana-3843	49	13	a	a	DET
cana-3843	49	14	community	community	NOUN
cana-3843	49	15	detection	detection	NOUN
cana-3843	49	16	cluster	cluster	NOUN
cana-3843	49	17	method	method	NOUN
cana-3843	49	18	with	with	ADP
cana-3843	49	19	a	a	DET
cana-3843	49	20	genetic	genetic	ADJ
cana-3843	49	21	algorithm	algorithm	NOUN
cana-3843	49	22	.	.	PUNCT
cana-3843	50	1	initially	initially	ADV
cana-3843	50	2	,	,	PUNCT
cana-3843	50	3	the	the	DET
cana-3843	50	4	similarities	similarity	NOUN
cana-3843	50	5	of	of	ADP
cana-3843	50	6	the	the	DET
cana-3843	50	7	features	feature	NOUN
cana-3843	50	8	are	be	AUX
cana-3843	50	9	calculated	calculate	VERB
cana-3843	50	10	and	and	CCONJ
cana-3843	50	11	the	the	DET
cana-3843	50	12	features	feature	NOUN
cana-3843	50	13	are	be	AUX
cana-3843	50	14	grouped	group	VERB
cana-3843	50	15	using	use	VERB
cana-3843	50	16	community	community	NOUN
cana-3843	50	17	detection	detection	NOUN
cana-3843	50	18	cluster	cluster	NOUN
cana-3843	50	19	methods	method	NOUN
cana-3843	50	20	.	.	PUNCT
cana-3843	51	1	a	a	DET
cana-3843	51	2	genetic	genetic	ADJ
cana-3843	51	3	algorithm	algorithm	NOUN
cana-3843	51	4	with	with	ADP
cana-3843	51	5	a	a	DET
cana-3843	51	6	repair	repair	NOUN
cana-3843	51	7	operation	operation	NOUN
cana-3843	51	8	was	be	AUX
cana-3843	51	9	applied	apply	VERB
cana-3843	51	10	to	to	ADP
cana-3843	51	11	each	each	DET
cana-3843	51	12	cluster	cluster	NOUN
cana-3843	51	13	to	to	PART
cana-3843	51	14	select	select	VERB
cana-3843	51	15	the	the	DET
cana-3843	51	16	significant	significant	ADJ
cana-3843	51	17	set	set	NOUN
cana-3843	51	18	of	of	ADP
cana-3843	51	19	features	feature	NOUN
cana-3843	51	20	and	and	CCONJ
cana-3843	51	21	perform	perform	VERB
cana-3843	51	22	the	the	DET
cana-3843	51	23	comparison	comparison	NOUN
cana-3843	51	24	analysis	analysis	NOUN
cana-3843	51	25	with	with	ADP
cana-3843	51	26	other	other	ADJ
cana-3843	51	27	optimization	optimization	NOUN
cana-3843	51	28	techniques	technique	NOUN
cana-3843	51	29	.	.	PUNCT
cana-3843	52	1	the	the	DET
cana-3843	52	2	proposed	propose	VERB
cana-3843	52	3	method	method	NOUN
cana-3843	52	4	produced	produce	VERB
cana-3843	52	5	higher	high	ADJ
cana-3843	52	6	accuracy	accuracy	NOUN
cana-3843	52	7	in	in	ADP
cana-3843	52	8	predicting	predict	VERB
cana-3843	52	9	communications	communication	NOUN
cana-3843	52	10	on	on	ADP
cana-3843	52	11	applied	apply	VERB
cana-3843	52	12	nonlinear	nonlinear	ADJ
cana-3843	52	13	analysis	analysis	NOUN
cana-3843	52	14	issn	issn	NOUN
cana-3843	52	15	:	:	PUNCT
cana-3843	52	16	1074	1074	NUM
cana-3843	52	17	-	-	PUNCT
cana-3843	52	18	133x	133x	NUM
cana-3843	52	19	vol	vol	NOUN
cana-3843	52	20	32	32	NUM
cana-3843	52	21	no	no	NOUN
cana-3843	52	22	.	.	PUNCT
cana-3843	53	1	9s	9s	NUM
cana-3843	53	2	(	(	PUNCT
cana-3843	53	3	2025	2025	NUM
cana-3843	53	4	)	)	PUNCT
cana-3843	53	5	121	121	NUM
cana-3843	53	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	53	7	the	the	DET
cana-3843	53	8	disease	disease	NOUN
cana-3843	53	9	using	use	VERB
cana-3843	53	10	the	the	DET
cana-3843	53	11	genetic	genetic	ADJ
cana-3843	53	12	process	process	NOUN
cana-3843	53	13	.	.	PUNCT
cana-3843	54	1	sabah	sabah	PROPN
cana-3843	54	2	sayed	say	VERB
cana-3843	54	3	et	et	PROPN
cana-3843	54	4	al	al	PROPN
cana-3843	54	5	.	.	PUNCT
cana-3843	55	1	[	[	X
cana-3843	55	2	9	9	NUM
cana-3843	55	3	]	]	PUNCT
cana-3843	55	4	developed	develop	VERB
cana-3843	55	5	an	an	DET
cana-3843	55	6	ensemble	ensemble	ADJ
cana-3843	55	7	-	-	PUNCT
cana-3843	55	8	based	base	VERB
cana-3843	55	9	attribute	attribute	NOUN
cana-3843	55	10	selection	selection	NOUN
cana-3843	55	11	approach	approach	NOUN
cana-3843	55	12	that	that	PRON
cana-3843	55	13	combines	combine	VERB
cana-3843	55	14	a	a	DET
cana-3843	55	15	t	t	NOUN
cana-3843	55	16	-	-	PUNCT
cana-3843	55	17	test	test	NOUN
cana-3843	55	18	and	and	CCONJ
cana-3843	55	19	a	a	DET
cana-3843	55	20	nested	nested	ADJ
cana-3843	55	21	genetic	genetic	ADJ
cana-3843	55	22	algorithm	algorithm	NOUN
cana-3843	55	23	to	to	PART
cana-3843	55	24	eliminate	eliminate	VERB
cana-3843	55	25	redundant	redundant	ADJ
cana-3843	55	26	features	feature	NOUN
cana-3843	55	27	.	.	PUNCT
cana-3843	56	1	an	an	DET
cana-3843	56	2	incremental	incremental	ADJ
cana-3843	56	3	fs	f	NOUN
cana-3843	56	4	method	method	NOUN
cana-3843	56	5	was	be	AUX
cana-3843	56	6	then	then	ADV
cana-3843	56	7	utilized	utilize	VERB
cana-3843	56	8	to	to	PART
cana-3843	56	9	identify	identify	VERB
cana-3843	56	10	a	a	DET
cana-3843	56	11	significant	significant	ADJ
cana-3843	56	12	subset	subset	NOUN
cana-3843	56	13	of	of	ADP
cana-3843	56	14	genes	gene	NOUN
cana-3843	56	15	.	.	PUNCT
cana-3843	57	1	finally	finally	ADV
cana-3843	57	2	,	,	PUNCT
cana-3843	57	3	the	the	DET
cana-3843	57	4	biological	biological	ADJ
cana-3843	57	5	relevance	relevance	NOUN
cana-3843	57	6	of	of	ADP
cana-3843	57	7	the	the	DET
cana-3843	57	8	selected	select	VERB
cana-3843	57	9	genes	gene	NOUN
cana-3843	57	10	was	be	AUX
cana-3843	57	11	validated	validate	VERB
cana-3843	57	12	through	through	ADP
cana-3843	57	13	enrichment	enrichment	NOUN
cana-3843	57	14	analysis	analysis	NOUN
cana-3843	57	15	,	,	PUNCT
cana-3843	57	16	achieving	achieve	VERB
cana-3843	57	17	a	a	DET
cana-3843	57	18	classification	classification	NOUN
cana-3843	57	19	accuracy	accuracy	NOUN
cana-3843	57	20	of	of	ADP
cana-3843	57	21	98.4	98.4	NUM
cana-3843	57	22	%	%	NOUN
cana-3843	57	23	.	.	PUNCT
cana-3843	58	1	lawrence	lawrence	PROPN
cana-3843	58	2	et	et	PROPN
cana-3843	58	3	al	al	PROPN
cana-3843	58	4	.	.	PUNCT
cana-3843	59	1	[	[	X
cana-3843	59	2	10	10	NUM
cana-3843	59	3	]	]	PUNCT
cana-3843	59	4	designed	design	VERB
cana-3843	59	5	a	a	DET
cana-3843	59	6	framework	framework	NOUN
cana-3843	59	7	that	that	PRON
cana-3843	59	8	combines	combine	VERB
cana-3843	59	9	ga	ga	PROPN
cana-3843	59	10	and	and	CCONJ
cana-3843	59	11	dbn	dbn	PROPN
cana-3843	59	12	for	for	ADP
cana-3843	59	13	the	the	DET
cana-3843	59	14	effective	effective	ADJ
cana-3843	59	15	selection	selection	NOUN
cana-3843	59	16	of	of	ADP
cana-3843	59	17	attributes	attribute	NOUN
cana-3843	59	18	and	and	CCONJ
cana-3843	59	19	classification	classification	NOUN
cana-3843	59	20	.	.	PUNCT
cana-3843	60	1	the	the	DET
cana-3843	60	2	research	research	NOUN
cana-3843	60	3	study	study	NOUN
cana-3843	60	4	utilized	utilize	VERB
cana-3843	60	5	ga	ga	PROPN
cana-3843	60	6	to	to	PART
cana-3843	60	7	remove	remove	VERB
cana-3843	60	8	the	the	DET
cana-3843	60	9	noisy	noisy	ADJ
cana-3843	60	10	attributes	attribute	NOUN
cana-3843	60	11	and	and	CCONJ
cana-3843	60	12	select	select	VERB
cana-3843	60	13	the	the	DET
cana-3843	60	14	most	most	ADV
cana-3843	60	15	prominent	prominent	ADJ
cana-3843	60	16	set	set	NOUN
cana-3843	60	17	of	of	ADP
cana-3843	60	18	attributes	attribute	NOUN
cana-3843	60	19	.	.	PUNCT
cana-3843	61	1	finally	finally	ADV
cana-3843	61	2	,	,	PUNCT
cana-3843	61	3	the	the	DET
cana-3843	61	4	dbn	dbn	PROPN
cana-3843	61	5	classifier	classifier	NOUN
cana-3843	61	6	was	be	AUX
cana-3843	61	7	applied	apply	VERB
cana-3843	61	8	to	to	PART
cana-3843	61	9	predict	predict	VERB
cana-3843	61	10	the	the	DET
cana-3843	61	11	disease	disease	NOUN
cana-3843	61	12	.	.	PUNCT
cana-3843	62	1	the	the	DET
cana-3843	62	2	presented	present	VERB
cana-3843	62	3	method	method	NOUN
cana-3843	62	4	accurately	accurately	ADV
cana-3843	62	5	identifies	identify	VERB
cana-3843	62	6	the	the	DET
cana-3843	62	7	cancer	cancer	NOUN
cana-3843	62	8	types	type	NOUN
cana-3843	62	9	.	.	PUNCT
cana-3843	63	1	pragadeesh	pragadeesh	ADJ
cana-3843	63	2	et	et	PROPN
cana-3843	63	3	al	al	PROPN
cana-3843	63	4	.	.	PUNCT
cana-3843	64	1	[	[	X
cana-3843	64	2	11	11	NUM
cana-3843	64	3	]	]	PUNCT
cana-3843	64	4	suggested	suggest	VERB
cana-3843	64	5	a	a	DET
cana-3843	64	6	compounded	compound	VERB
cana-3843	64	7	feature	feature	NOUN
cana-3843	64	8	selection	selection	NOUN
cana-3843	64	9	approach	approach	NOUN
cana-3843	64	10	for	for	ADP
cana-3843	64	11	classifying	classify	VERB
cana-3843	64	12	cancer	cancer	NOUN
cana-3843	64	13	gene	gene	NOUN
cana-3843	64	14	data	datum	NOUN
cana-3843	64	15	.	.	PUNCT
cana-3843	65	1	in	in	ADP
cana-3843	65	2	this	this	DET
cana-3843	65	3	approach	approach	NOUN
cana-3843	65	4	,	,	PUNCT
cana-3843	65	5	the	the	DET
cana-3843	65	6	information	information	NOUN
cana-3843	65	7	gain	gain	VERB
cana-3843	65	8	filtering	filtering	NOUN
cana-3843	65	9	technique	technique	NOUN
cana-3843	65	10	eliminates	eliminate	NOUN
cana-3843	65	11	redundant	redundant	ADJ
cana-3843	65	12	attributes	attribute	NOUN
cana-3843	65	13	,	,	PUNCT
cana-3843	65	14	and	and	CCONJ
cana-3843	65	15	a	a	DET
cana-3843	65	16	micro	micro	PROPN
cana-3843	65	17	ga	ga	PROPN
cana-3843	65	18	evolutionary	evolutionary	ADJ
cana-3843	65	19	computing	computing	NOUN
cana-3843	65	20	technique	technique	NOUN
cana-3843	65	21	is	be	AUX
cana-3843	65	22	applied	apply	VERB
cana-3843	65	23	to	to	PART
cana-3843	65	24	identify	identify	VERB
cana-3843	65	25	the	the	DET
cana-3843	65	26	prominent	prominent	ADJ
cana-3843	65	27	set	set	NOUN
cana-3843	65	28	of	of	ADP
cana-3843	65	29	features	feature	NOUN
cana-3843	65	30	.	.	PUNCT
cana-3843	66	1	finally	finally	ADV
cana-3843	66	2	,	,	PUNCT
cana-3843	66	3	the	the	DET
cana-3843	66	4	classification	classification	NOUN
cana-3843	66	5	accuracy	accuracy	NOUN
cana-3843	66	6	is	be	AUX
cana-3843	66	7	calculated	calculate	VERB
cana-3843	66	8	using	use	VERB
cana-3843	66	9	the	the	DET
cana-3843	66	10	svm	svm	PROPN
cana-3843	66	11	method.yuvaraj	method.yuvaraj	PROPN
cana-3843	66	12	et	et	NOUN
cana-3843	66	13	al[12	al[12	PROPN
cana-3843	66	14	]	]	PUNCT
cana-3843	66	15	developed	develop	VERB
cana-3843	66	16	an	an	DET
cana-3843	66	17	efficient	efficient	ADJ
cana-3843	66	18	attribute	attribute	NOUN
cana-3843	66	19	selection	selection	NOUN
cana-3843	66	20	model	model	NOUN
cana-3843	66	21	using	use	VERB
cana-3843	66	22	optimization	optimization	NOUN
cana-3843	66	23	techniques	technique	NOUN
cana-3843	66	24	such	such	ADJ
cana-3843	66	25	as	as	ADP
cana-3843	66	26	whale	whale	NOUN
cana-3843	66	27	optimization	optimization	NOUN
cana-3843	66	28	to	to	PART
cana-3843	66	29	select	select	VERB
cana-3843	66	30	biomarker	biomarker	NOUN
cana-3843	66	31	attributes	attribute	NOUN
cana-3843	66	32	.	.	PUNCT
cana-3843	67	1	then	then	ADV
cana-3843	67	2	,	,	PUNCT
cana-3843	67	3	a	a	DET
cana-3843	67	4	modified	modify	VERB
cana-3843	67	5	lstm	lstm	NOUN
cana-3843	67	6	network	network	NOUN
cana-3843	67	7	was	be	AUX
cana-3843	67	8	utilized	utilize	VERB
cana-3843	67	9	to	to	PART
cana-3843	67	10	classify	classify	VERB
cana-3843	67	11	the	the	DET
cana-3843	67	12	cancer	cancer	NOUN
cana-3843	67	13	types	type	NOUN
cana-3843	67	14	.	.	PUNCT
cana-3843	68	1	the	the	DET
cana-3843	68	2	suggested	suggest	VERB
cana-3843	68	3	model	model	NOUN
cana-3843	68	4	produced	produce	VERB
cana-3843	68	5	a	a	DET
cana-3843	68	6	significant	significant	ADJ
cana-3843	68	7	accuracy	accuracy	NOUN
cana-3843	68	8	rate	rate	NOUN
cana-3843	68	9	,	,	PUNCT
cana-3843	68	10	f	f	X
cana-3843	68	11	-	-	PUNCT
cana-3843	68	12	measure	measure	NOUN
cana-3843	68	13	,	,	PUNCT
cana-3843	68	14	and	and	CCONJ
cana-3843	68	15	recall	recall	VERB
cana-3843	68	16	values	value	NOUN
cana-3843	68	17	.	.	PUNCT
cana-3843	69	1	sergii	sergii	PROPN
cana-3843	69	2	babichev	babichev	PROPN
cana-3843	69	3	et	et	NOUN
cana-3843	69	4	al.[13	al.[13	NOUN
cana-3843	69	5	]	]	PUNCT
cana-3843	69	6	explored	explore	VERB
cana-3843	69	7	gene	gene	NOUN
cana-3843	69	8	data	datum	NOUN
cana-3843	69	9	classification	classification	NOUN
cana-3843	69	10	,	,	PUNCT
cana-3843	69	11	focusing	focus	VERB
cana-3843	69	12	on	on	ADP
cana-3843	69	13	the	the	DET
cana-3843	69	14	relationships	relationship	NOUN
cana-3843	69	15	within	within	ADP
cana-3843	69	16	genetic	genetic	ADJ
cana-3843	69	17	information	information	NOUN
cana-3843	69	18	,	,	PUNCT
cana-3843	69	19	gene	gene	NOUN
cana-3843	69	20	activity	activity	NOUN
cana-3843	69	21	patterns	pattern	NOUN
cana-3843	69	22	,	,	PUNCT
cana-3843	69	23	and	and	CCONJ
cana-3843	69	24	biological	biological	ADJ
cana-3843	69	25	processes	process	NOUN
cana-3843	69	26	.	.	PUNCT
cana-3843	70	1	the	the	DET
cana-3843	70	2	proposed	propose	VERB
cana-3843	70	3	work	work	NOUN
cana-3843	70	4	developed	develop	VERB
cana-3843	70	5	a	a	DET
cana-3843	70	6	model	model	NOUN
cana-3843	70	7	that	that	PRON
cana-3843	70	8	optimizes	optimize	VERB
cana-3843	70	9	the	the	DET
cana-3843	70	10	architecture	architecture	NOUN
cana-3843	70	11	and	and	CCONJ
cana-3843	70	12	hyperparameter	hyperparameter	NOUN
cana-3843	70	13	values	value	NOUN
cana-3843	70	14	of	of	ADP
cana-3843	70	15	recurrent	recurrent	ADJ
cana-3843	70	16	nn	nn	PROPN
cana-3843	70	17	specifically	specifically	ADV
cana-3843	70	18	gru	gru	PROPN
cana-3843	70	19	and	and	CCONJ
cana-3843	70	20	lstm	lstm	PROPN
cana-3843	70	21	,	,	PUNCT
cana-3843	70	22	based	base	VERB
cana-3843	70	23	on	on	ADP
cana-3843	70	24	the	the	DET
cana-3843	70	25	classification	classification	NOUN
cana-3843	70	26	accuracy	accuracy	NOUN
cana-3843	70	27	,	,	PUNCT
cana-3843	70	28	loss	loss	NOUN
cana-3843	70	29	function	function	NOUN
cana-3843	70	30	value	value	NOUN
cana-3843	70	31	,	,	PUNCT
cana-3843	70	32	training	training	NOUN
cana-3843	70	33	time	time	NOUN
cana-3843	70	34	,	,	PUNCT
cana-3843	70	35	and	and	CCONJ
cana-3843	70	36	the	the	DET
cana-3843	70	37	f1	f1	ADJ
cana-3843	70	38	-	-	PUNCT
cana-3843	70	39	score	score	NOUN
cana-3843	70	40	index	index	NOUN
cana-3843	70	41	using	use	VERB
cana-3843	70	42	the	the	DET
cana-3843	70	43	harrington	harrington	NOUN
cana-3843	70	44	desirability	desirability	NOUN
cana-3843	70	45	method	method	NOUN
cana-3843	70	46	.	.	PUNCT
cana-3843	71	1	finally	finally	ADV
cana-3843	71	2	,	,	PUNCT
cana-3843	71	3	the	the	DET
cana-3843	71	4	best	good	ADJ
cana-3843	71	5	hyperparameters	hyperparameter	NOUN
cana-3843	71	6	for	for	ADP
cana-3843	71	7	each	each	DET
cana-3843	71	8	network	network	NOUN
cana-3843	71	9	model	model	NOUN
cana-3843	71	10	are	be	AUX
cana-3843	71	11	identified	identify	VERB
cana-3843	71	12	to	to	PART
cana-3843	71	13	improve	improve	VERB
cana-3843	71	14	the	the	DET
cana-3843	71	15	accuracy	accuracy	NOUN
cana-3843	71	16	of	of	ADP
cana-3843	71	17	disease	disease	NOUN
cana-3843	71	18	prediction.zixuan	prediction.zixuan	PROPN
cana-3843	71	19	wang	wang	PROPN
cana-3843	71	20	et	et	PROPN
cana-3843	71	21	al	al	PROPN
cana-3843	72	1	[	[	X
cana-3843	72	2	14	14	NUM
cana-3843	72	3	]	]	PUNCT
cana-3843	72	4	introduced	introduce	VERB
cana-3843	72	5	a	a	DET
cana-3843	72	6	feature	feature	NOUN
cana-3843	72	7	selection	selection	NOUN
cana-3843	72	8	framework	framework	NOUN
cana-3843	72	9	that	that	PRON
cana-3843	72	10	combines	combine	VERB
cana-3843	72	11	isomap	isomap	NOUN
cana-3843	72	12	and	and	CCONJ
cana-3843	72	13	genetic	genetic	ADJ
cana-3843	72	14	search	search	NOUN
cana-3843	72	15	techniques	technique	NOUN
cana-3843	72	16	.	.	PUNCT
cana-3843	73	1	isomap	isomap	PROPN
cana-3843	73	2	is	be	AUX
cana-3843	73	3	used	use	VERB
cana-3843	73	4	to	to	PART
cana-3843	73	5	map	map	VERB
cana-3843	73	6	high	high	ADJ
cana-3843	73	7	-	-	PUNCT
cana-3843	73	8	dimensional	dimensional	ADJ
cana-3843	73	9	nonlinear	nonlinear	ADJ
cana-3843	73	10	data	datum	NOUN
cana-3843	73	11	into	into	ADP
cana-3843	73	12	a	a	DET
cana-3843	73	13	lower	lower	ADV
cana-3843	73	14	-	-	PUNCT
cana-3843	73	15	dimensional	dimensional	ADJ
cana-3843	73	16	linear	linear	ADJ
cana-3843	73	17	space	space	NOUN
cana-3843	73	18	,	,	PUNCT
cana-3843	73	19	while	while	SCONJ
cana-3843	73	20	the	the	DET
cana-3843	73	21	genetic	genetic	ADJ
cana-3843	73	22	search	search	NOUN
cana-3843	73	23	selects	select	NOUN
cana-3843	73	24	feature	feature	NOUN
cana-3843	73	25	subsets	subset	NOUN
cana-3843	73	26	and	and	CCONJ
cana-3843	73	27	enhances	enhance	VERB
cana-3843	73	28	the	the	DET
cana-3843	73	29	fitness	fitness	NOUN
cana-3843	73	30	function	function	NOUN
cana-3843	73	31	.	.	PUNCT
cana-3843	74	1	the	the	DET
cana-3843	74	2	final	final	ADJ
cana-3843	74	3	set	set	NOUN
cana-3843	74	4	of	of	ADP
cana-3843	74	5	features	feature	NOUN
cana-3843	74	6	is	be	AUX
cana-3843	74	7	selected	select	VERB
cana-3843	74	8	based	base	VERB
cana-3843	74	9	on	on	ADP
cana-3843	74	10	a	a	DET
cana-3843	74	11	threshold	threshold	NOUN
cana-3843	74	12	derived	derive	VERB
cana-3843	74	13	from	from	ADP
cana-3843	74	14	the	the	DET
cana-3843	74	15	binomial	binomial	ADJ
cana-3843	74	16	distribution	distribution	NOUN
cana-3843	74	17	.	.	PUNCT
cana-3843	75	1	the	the	DET
cana-3843	75	2	selected	select	VERB
cana-3843	75	3	features	feature	NOUN
cana-3843	75	4	are	be	AUX
cana-3843	75	5	expected	expect	VERB
cana-3843	75	6	to	to	PART
cana-3843	75	7	improve	improve	VERB
cana-3843	75	8	classification	classification	NOUN
cana-3843	75	9	accuracy	accuracy	NOUN
cana-3843	75	10	for	for	ADP
cana-3843	75	11	cancer	cancer	NOUN
cana-3843	75	12	gene	gene	NOUN
cana-3843	75	13	data.ebtisam	data.ebtisam	PROPN
cana-3843	75	14	abdullah	abdullah	PROPN
cana-3843	75	15	alabdulqader	alabdulqader	NOUN
cana-3843	75	16	et	et	PROPN
cana-3843	75	17	al	al	PROPN
cana-3843	76	1	[	[	X
cana-3843	76	2	15	15	NUM
cana-3843	76	3	]	]	PUNCT
cana-3843	76	4	presented	present	VERB
cana-3843	76	5	a	a	DET
cana-3843	76	6	diagnostic	diagnostic	ADJ
cana-3843	76	7	method	method	NOUN
cana-3843	76	8	utilizing	utilize	VERB
cana-3843	76	9	22,283	22,283	NUM
cana-3843	76	10	leukemia	leukemia	NOUN
cana-3843	76	11	gene	gene	NOUN
cana-3843	76	12	microarray	microarray	NOUN
cana-3843	76	13	data	datum	NOUN
cana-3843	76	14	.	.	PUNCT
cana-3843	77	1	the	the	DET
cana-3843	77	2	proposed	propose	VERB
cana-3843	77	3	model	model	NOUN
cana-3843	77	4	used	use	VERB
cana-3843	77	5	a	a	DET
cana-3843	77	6	chisquared	chisquare	VERB
cana-3843	77	7	filter	filter	NOUN
cana-3843	77	8	method	method	NOUN
cana-3843	77	9	to	to	PART
cana-3843	77	10	select	select	VERB
cana-3843	77	11	the	the	DET
cana-3843	77	12	top	top	ADJ
cana-3843	77	13	300	300	NUM
cana-3843	77	14	genes	gene	NOUN
cana-3843	77	15	,	,	PUNCT
cana-3843	77	16	and	and	CCONJ
cana-3843	77	17	the	the	DET
cana-3843	77	18	smote	smote	PROPN
cana-3843	77	19	-	-	PUNCT
cana-3843	77	20	tomek	tomek	PROPN
cana-3843	77	21	technique	technique	NOUN
cana-3843	77	22	was	be	AUX
cana-3843	77	23	applied	apply	VERB
cana-3843	77	24	to	to	PART
cana-3843	77	25	generate	generate	VERB
cana-3843	77	26	synthetic	synthetic	ADJ
cana-3843	77	27	data	datum	NOUN
cana-3843	77	28	.	.	PUNCT
cana-3843	78	1	a	a	DET
cana-3843	78	2	weighted	weight	VERB
cana-3843	78	3	cnn	cnn	PROPN
cana-3843	78	4	is	be	AUX
cana-3843	78	5	then	then	ADV
cana-3843	78	6	proposed	propose	VERB
cana-3843	78	7	for	for	ADP
cana-3843	78	8	disease	disease	NOUN
cana-3843	78	9	prediction	prediction	NOUN
cana-3843	78	10	and	and	CCONJ
cana-3843	78	11	achieving	achieve	VERB
cana-3843	78	12	an	an	DET
cana-3843	78	13	accuracy	accuracy	NOUN
cana-3843	78	14	of	of	ADP
cana-3843	78	15	99.9	99.9	NUM
cana-3843	78	16	%	%	NOUN
cana-3843	78	17	.	.	PUNCT
cana-3843	79	1	pradeep	pradeep	PROPN
cana-3843	79	2	kumar	kumar	PROPN
cana-3843	79	3	mallick	mallick	PROPN
cana-3843	79	4	et	et	PROPN
cana-3843	79	5	al	al	PROPN
cana-3843	79	6	.	.	PUNCT
cana-3843	80	1	[	[	X
cana-3843	80	2	16	16	NUM
cana-3843	80	3	]	]	PUNCT
cana-3843	80	4	introduced	introduce	VERB
cana-3843	80	5	a	a	DET
cana-3843	80	6	method	method	NOUN
cana-3843	80	7	designed	design	VERB
cana-3843	80	8	to	to	PART
cana-3843	80	9	enhance	enhance	VERB
cana-3843	80	10	the	the	DET
cana-3843	80	11	convergence	convergence	NOUN
cana-3843	80	12	of	of	ADP
cana-3843	80	13	dnn	dnn	PROPN
cana-3843	80	14	.	.	PUNCT
cana-3843	81	1	the	the	DET
cana-3843	81	2	model	model	NOUN
cana-3843	81	3	used	use	VERB
cana-3843	81	4	leukemia	leukemia	NOUN
cana-3843	81	5	cancer	cancer	NOUN
cana-3843	81	6	gene	gene	NOUN
cana-3843	81	7	data	datum	NOUN
cana-3843	81	8	and	and	CCONJ
cana-3843	81	9	implemented	implement	VERB
cana-3843	81	10	a	a	DET
cana-3843	81	11	five	five	NUM
cana-3843	81	12	-	-	PUNCT
cana-3843	81	13	layer	layer	NOUN
cana-3843	81	14	dnn	dnn	PROPN
cana-3843	81	15	to	to	PART
cana-3843	81	16	classify	classify	VERB
cana-3843	81	17	all	all	DET
cana-3843	81	18	and	and	CCONJ
cana-3843	81	19	aml	aml	NOUN
cana-3843	81	20	gene	gene	NOUN
cana-3843	81	21	expression	expression	NOUN
cana-3843	81	22	data	datum	NOUN
cana-3843	81	23	.	.	PUNCT
cana-3843	82	1	the	the	DET
cana-3843	82	2	proposed	propose	VERB
cana-3843	82	3	approach	approach	NOUN
cana-3843	82	4	achieved	achieve	VERB
cana-3843	82	5	an	an	DET
cana-3843	82	6	accuracy	accuracy	NOUN
cana-3843	82	7	rate	rate	NOUN
cana-3843	82	8	of	of	ADP
cana-3843	82	9	98.2	98.2	NUM
cana-3843	82	10	%	%	NOUN
cana-3843	82	11	and	and	CCONJ
cana-3843	82	12	a	a	DET
cana-3843	82	13	specificity	specificity	NOUN
cana-3843	82	14	value	value	NOUN
cana-3843	82	15	of	of	ADP
cana-3843	82	16	97.9	97.9	NUM
cana-3843	82	17	%	%	NOUN
cana-3843	82	18	.	.	PUNCT
cana-3843	83	1	bibhuprasad	bibhuprasad	ADP
cana-3843	83	2	sahu	sahu	PROPN
cana-3843	83	3	et	et	PROPN
cana-3843	83	4	al	al	PROPN
cana-3843	84	1	[	[	X
cana-3843	84	2	17	17	NUM
cana-3843	84	3	]	]	PUNCT
cana-3843	84	4	developed	develop	VERB
cana-3843	84	5	an	an	DET
cana-3843	84	6	ensemble	ensemble	ADJ
cana-3843	84	7	approach	approach	NOUN
cana-3843	84	8	for	for	ADP
cana-3843	84	9	classifying	classify	VERB
cana-3843	84	10	leukemia	leukemia	NOUN
cana-3843	84	11	cancer	cancer	NOUN
cana-3843	84	12	data	datum	NOUN
cana-3843	84	13	.	.	PUNCT
cana-3843	85	1	the	the	DET
cana-3843	85	2	research	research	NOUN
cana-3843	85	3	method	method	NOUN
cana-3843	85	4	integrates	integrate	VERB
cana-3843	85	5	various	various	ADJ
cana-3843	85	6	filter	filter	NOUN
cana-3843	85	7	techniques	technique	NOUN
cana-3843	85	8	,	,	PUNCT
cana-3843	85	9	including	include	VERB
cana-3843	85	10	mutual	mutual	ADJ
cana-3843	85	11	information	information	NOUN
cana-3843	85	12	,	,	PUNCT
cana-3843	85	13	chi	chi	NOUN
cana-3843	85	14	-	-	PUNCT
cana-3843	85	15	square	square	ADJ
cana-3843	85	16	,	,	PUNCT
cana-3843	85	17	correlation	correlation	NOUN
cana-3843	85	18	-	-	PUNCT
cana-3843	85	19	based	base	VERB
cana-3843	85	20	fs	f	NOUN
cana-3843	85	21	,	,	PUNCT
cana-3843	85	22	and	and	CCONJ
cana-3843	85	23	gain	gain	VERB
cana-3843	85	24	ratio	ratio	NOUN
cana-3843	85	25	,	,	PUNCT
cana-3843	85	26	to	to	PART
cana-3843	85	27	select	select	VERB
cana-3843	85	28	the	the	DET
cana-3843	85	29	relevant	relevant	ADJ
cana-3843	85	30	features	feature	NOUN
cana-3843	85	31	.	.	PUNCT
cana-3843	86	1	the	the	DET
cana-3843	86	2	selected	select	VERB
cana-3843	86	3	features	feature	NOUN
cana-3843	86	4	are	be	AUX
cana-3843	86	5	further	far	ADV
cana-3843	86	6	optimized	optimize	VERB
cana-3843	86	7	using	use	VERB
cana-3843	86	8	the	the	DET
cana-3843	86	9	grey	grey	ADJ
cana-3843	86	10	wolf	wolf	NOUN
cana-3843	86	11	optimizer	optimizer	NOUN
cana-3843	86	12	to	to	PART
cana-3843	86	13	generate	generate	VERB
cana-3843	86	14	an	an	DET
cana-3843	86	15	optimal	optimal	ADJ
cana-3843	86	16	subset	subset	NOUN
cana-3843	86	17	of	of	ADP
cana-3843	86	18	genes	gene	NOUN
cana-3843	86	19	.	.	PUNCT
cana-3843	87	1	recurrent	recurrent	PROPN
cana-3843	87	2	nn	nn	PROPN
cana-3843	87	3	and	and	CCONJ
cana-3843	87	4	lstm	lstm	PROPN
cana-3843	87	5	communications	communication	NOUN
cana-3843	87	6	on	on	ADP
cana-3843	87	7	applied	apply	VERB
cana-3843	87	8	nonlinear	nonlinear	ADJ
cana-3843	87	9	analysis	analysis	NOUN
cana-3843	87	10	issn	issn	NOUN
cana-3843	87	11	:	:	PUNCT
cana-3843	87	12	1074	1074	NUM
cana-3843	87	13	-	-	PUNCT
cana-3843	87	14	133x	133x	NUM
cana-3843	87	15	vol	vol	NOUN
cana-3843	87	16	32	32	NUM
cana-3843	87	17	no	no	NOUN
cana-3843	87	18	.	.	PUNCT
cana-3843	88	1	9s	9s	NUM
cana-3843	88	2	(	(	PUNCT
cana-3843	88	3	2025	2025	NUM
cana-3843	88	4	)	)	PUNCT
cana-3843	88	5	122	122	NUM
cana-3843	88	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	88	7	classifiers	classifier	NOUN
cana-3843	88	8	are	be	AUX
cana-3843	88	9	applied	apply	VERB
cana-3843	88	10	for	for	ADP
cana-3843	88	11	disease	disease	NOUN
cana-3843	88	12	prediction	prediction	NOUN
cana-3843	88	13	,	,	PUNCT
cana-3843	88	14	achieving	achieve	VERB
cana-3843	88	15	high	high	ADJ
cana-3843	88	16	accuracy	accuracy	NOUN
cana-3843	88	17	.	.	PUNCT
cana-3843	89	1	abdul	abdul	PROPN
cana-3843	89	2	karim	karim	PROPN
cana-3843	89	3	et	et	PROPN
cana-3843	89	4	al	al	PROPN
cana-3843	90	1	[	[	X
cana-3843	90	2	18	18	NUM
cana-3843	90	3	]	]	PUNCT
cana-3843	90	4	defined	define	VERB
cana-3843	90	5	four	four	NUM
cana-3843	90	6	distinct	distinct	ADJ
cana-3843	90	7	types	type	NOUN
cana-3843	90	8	of	of	ADP
cana-3843	90	9	leukemia	leukemia	NOUN
cana-3843	90	10	,	,	PUNCT
cana-3843	90	11	including	include	VERB
cana-3843	90	12	aml	aml	PROPN
cana-3843	90	13	,	,	PUNCT
cana-3843	90	14	cml	cml	PROPN
cana-3843	90	15	,	,	PUNCT
cana-3843	90	16	all	all	PRON
cana-3843	90	17	,	,	PUNCT
cana-3843	90	18	and	and	CCONJ
cana-3843	90	19	cll	cll	PROPN
cana-3843	90	20	.	.	PUNCT
cana-3843	91	1	the	the	DET
cana-3843	91	2	authors	author	NOUN
cana-3843	91	3	proposed	propose	VERB
cana-3843	91	4	ldsvm	ldsvm	NOUN
cana-3843	91	5	,	,	PUNCT
cana-3843	91	6	an	an	DET
cana-3843	91	7	ensemble	ensemble	ADJ
cana-3843	91	8	ml	ml	NOUN
cana-3843	91	9	algorithm	algorithm	NOUN
cana-3843	91	10	to	to	PART
cana-3843	91	11	enhance	enhance	VERB
cana-3843	91	12	performance	performance	NOUN
cana-3843	91	13	and	and	CCONJ
cana-3843	91	14	prediction	prediction	NOUN
cana-3843	91	15	accuracy	accuracy	NOUN
cana-3843	91	16	.	.	PUNCT
cana-3843	92	1	the	the	DET
cana-3843	92	2	research	research	NOUN
cana-3843	92	3	emphasizes	emphasize	VERB
cana-3843	92	4	the	the	DET
cana-3843	92	5	need	need	NOUN
cana-3843	92	6	for	for	ADP
cana-3843	92	7	a	a	DET
cana-3843	92	8	distinctive	distinctive	ADJ
cana-3843	92	9	methodology	methodology	NOUN
cana-3843	92	10	that	that	PRON
cana-3843	92	11	utilizes	utilize	VERB
cana-3843	92	12	optimization	optimization	NOUN
cana-3843	92	13	techniques	technique	NOUN
cana-3843	92	14	to	to	PART
cana-3843	92	15	identify	identify	VERB
cana-3843	92	16	leukemia	leukemia	NOUN
cana-3843	92	17	cancer	cancer	NOUN
cana-3843	92	18	genes	gene	NOUN
cana-3843	92	19	and	and	CCONJ
cana-3843	92	20	incorporates	incorporate	VERB
cana-3843	92	21	deep	deep	ADJ
cana-3843	92	22	learning	learn	VERB
cana-3843	92	23	classification	classification	NOUN
cana-3843	92	24	methods	method	NOUN
cana-3843	92	25	with	with	ADP
cana-3843	92	26	various	various	ADJ
cana-3843	92	27	optimizers	optimizer	NOUN
cana-3843	92	28	for	for	ADP
cana-3843	92	29	the	the	DET
cana-3843	92	30	prediction	prediction	NOUN
cana-3843	92	31	of	of	ADP
cana-3843	92	32	the	the	DET
cana-3843	92	33	disease	disease	NOUN
cana-3843	92	34	.	.	PUNCT
cana-3843	93	1	the	the	DET
cana-3843	93	2	current	current	ADJ
cana-3843	93	3	study	study	NOUN
cana-3843	93	4	aims	aim	VERB
cana-3843	93	5	to	to	PART
cana-3843	93	6	achieve	achieve	VERB
cana-3843	93	7	the	the	DET
cana-3843	93	8	expected	expect	VERB
cana-3843	93	9	results	result	NOUN
cana-3843	93	10	.	.	PUNCT
cana-3843	94	1	3	3	X
cana-3843	94	2	.	.	X
cana-3843	94	3	materials	material	NOUN
cana-3843	94	4	and	and	CCONJ
cana-3843	94	5	methods	method	NOUN
cana-3843	94	6	this	this	DET
cana-3843	94	7	section	section	NOUN
cana-3843	94	8	provides	provide	VERB
cana-3843	94	9	an	an	DET
cana-3843	94	10	overview	overview	NOUN
cana-3843	94	11	of	of	ADP
cana-3843	94	12	the	the	DET
cana-3843	94	13	dataset	dataset	NOUN
cana-3843	94	14	and	and	CCONJ
cana-3843	94	15	the	the	DET
cana-3843	94	16	essential	essential	ADJ
cana-3843	94	17	methods	method	NOUN
cana-3843	94	18	required	require	VERB
cana-3843	94	19	to	to	PART
cana-3843	94	20	obtain	obtain	VERB
cana-3843	94	21	the	the	DET
cana-3843	94	22	desired	desire	VERB
cana-3843	94	23	accuracy	accuracy	NOUN
cana-3843	94	24	in	in	ADP
cana-3843	94	25	predicting	predict	VERB
cana-3843	94	26	cancer	cancer	NOUN
cana-3843	94	27	disease	disease	NOUN
cana-3843	94	28	.	.	PUNCT
cana-3843	95	1	3.1	3.1	NUM
cana-3843	95	2	.	.	PUNCT
cana-3843	95	3	dataset	dataset	VERB
cana-3843	95	4	this	this	DET
cana-3843	95	5	section	section	NOUN
cana-3843	95	6	explores	explore	VERB
cana-3843	95	7	the	the	DET
cana-3843	95	8	outline	outline	NOUN
cana-3843	95	9	of	of	ADP
cana-3843	95	10	the	the	DET
cana-3843	95	11	dataset	dataset	NOUN
cana-3843	95	12	utilized	utilize	VERB
cana-3843	95	13	in	in	ADP
cana-3843	95	14	the	the	DET
cana-3843	95	15	research	research	NOUN
cana-3843	95	16	work	work	NOUN
cana-3843	95	17	.	.	PUNCT
cana-3843	96	1	the	the	DET
cana-3843	96	2	proposed	propose	VERB
cana-3843	96	3	system	system	NOUN
cana-3843	96	4	utilizes	utilize	VERB
cana-3843	96	5	the	the	DET
cana-3843	96	6	repositories	repository	NOUN
cana-3843	96	7	from	from	ADP
cana-3843	96	8	the	the	DET
cana-3843	96	9	kent	kent	PROPN
cana-3843	96	10	ridge	ridge	PROPN
cana-3843	96	11	biomedical	biomedical	PROPN
cana-3843	96	12	data	datum	NOUN
cana-3843	96	13	set	set	VERB
cana-3843	96	14	repository	repository	NOUN
cana-3843	96	15	[	[	X
cana-3843	96	16	19	19	NUM
cana-3843	96	17	]	]	PUNCT
cana-3843	96	18	.	.	PUNCT
cana-3843	97	1	the	the	DET
cana-3843	97	2	microarray	microarray	NOUN
cana-3843	97	3	cancer	cancer	NOUN
cana-3843	97	4	dataset	dataset	NOUN
cana-3843	97	5	is	be	AUX
cana-3843	97	6	structured	structure	VERB
cana-3843	97	7	as	as	ADP
cana-3843	97	8	a	a	DET
cana-3843	97	9	matrix	matrix	NOUN
cana-3843	97	10	,	,	PUNCT
cana-3843	97	11	with	with	ADP
cana-3843	97	12	columns	column	NOUN
cana-3843	97	13	representing	represent	VERB
cana-3843	97	14	the	the	DET
cana-3843	97	15	attributes	attribute	NOUN
cana-3843	97	16	or	or	CCONJ
cana-3843	97	17	features	feature	NOUN
cana-3843	97	18	and	and	CCONJ
cana-3843	97	19	rows	row	NOUN
cana-3843	97	20	expressed	express	VERB
cana-3843	97	21	as	as	ADP
cana-3843	97	22	the	the	DET
cana-3843	97	23	patient	patient	NOUN
cana-3843	97	24	's	's	PART
cana-3843	97	25	sample	sample	NOUN
cana-3843	97	26	instance	instance	NOUN
cana-3843	97	27	the	the	DET
cana-3843	97	28	dataset	dataset	NOUN
cana-3843	97	29	enables	enable	VERB
cana-3843	97	30	binary	binary	ADJ
cana-3843	97	31	classification	classification	NOUN
cana-3843	97	32	models	model	NOUN
cana-3843	97	33	since	since	SCONJ
cana-3843	97	34	it	it	PRON
cana-3843	97	35	has	have	VERB
cana-3843	97	36	only	only	ADV
cana-3843	97	37	two	two	NUM
cana-3843	97	38	output	output	NOUN
cana-3843	97	39	labels	label	NOUN
cana-3843	97	40	called	call	VERB
cana-3843	97	41	all	all	DET
cana-3843	97	42	and	and	CCONJ
cana-3843	97	43	aml	aml	NOUN
cana-3843	97	44	genes	gene	NOUN
cana-3843	97	45	.	.	PUNCT
cana-3843	98	1	table-1	table-1	PRON
cana-3843	98	2	shows	show	VERB
cana-3843	98	3	the	the	DET
cana-3843	98	4	properties	property	NOUN
cana-3843	98	5	of	of	ADP
cana-3843	98	6	the	the	DET
cana-3843	98	7	datasets	dataset	NOUN
cana-3843	98	8	utilized	utilize	VERB
cana-3843	98	9	in	in	ADP
cana-3843	98	10	the	the	DET
cana-3843	98	11	research	research	NOUN
cana-3843	98	12	work	work	NOUN
cana-3843	98	13	.	.	PUNCT
cana-3843	99	1	table-1	table-1	NUM
cana-3843	99	2	description	description	NOUN
cana-3843	99	3	of	of	ADP
cana-3843	99	4	leukemia	leukemia	NOUN
cana-3843	99	5	cancer	cancer	NOUN
cana-3843	99	6	gene	gene	NOUN
cana-3843	99	7	dataset	dataset	VERB
cana-3843	99	8	dataset	dataset	NOUN
cana-3843	99	9	leukemia	leukemia	NOUN
cana-3843	99	10	cancer	cancer	NOUN
cana-3843	99	11	gene	gene	NOUN
cana-3843	99	12	count	count	NOUN
cana-3843	99	13	7182	7182	NUM
cana-3843	99	14	class	class	NOUN
cana-3843	99	15	distribution	distribution	NOUN
cana-3843	99	16	2(all	2(all	ADJ
cana-3843	99	17	/	/	SYM
cana-3843	99	18	aml	aml	PROPN
cana-3843	99	19	)	)	PUNCT
cana-3843	99	20	sample	sample	NOUN
cana-3843	99	21	size	size	NOUN
cana-3843	99	22	72	72	NUM
cana-3843	99	23	49	49	NUM
cana-3843	99	24	samples	sample	NOUN
cana-3843	99	25	-	-	PUNCT
cana-3843	99	26	all	all	DET
cana-3843	99	27	23	23	NUM
cana-3843	99	28	samples	sample	NOUN
cana-3843	99	29	-	-	PUNCT
cana-3843	99	30	aml	aml	NOUN
cana-3843	99	31	3.2	3.2	NUM
cana-3843	99	32	.	.	PUNCT
cana-3843	100	1	genetic	genetic	ADJ
cana-3843	100	2	optimization	optimization	NOUN
cana-3843	100	3	algorithm	algorithm	NOUN
cana-3843	100	4	genetic	genetic	ADJ
cana-3843	100	5	optimization	optimization	NOUN
cana-3843	100	6	algorithm	algorithm	NOUN
cana-3843	100	7	is	be	AUX
cana-3843	100	8	a	a	DET
cana-3843	100	9	well	well	ADV
cana-3843	100	10	-	-	PUNCT
cana-3843	100	11	known	know	VERB
cana-3843	100	12	heuristic	heuristic	ADJ
cana-3843	100	13	method	method	NOUN
cana-3843	100	14	designed	design	VERB
cana-3843	100	15	to	to	PART
cana-3843	100	16	solve	solve	VERB
cana-3843	100	17	optimization	optimization	NOUN
cana-3843	100	18	problems	problem	NOUN
cana-3843	100	19	through	through	ADP
cana-3843	100	20	evolutionary	evolutionary	ADJ
cana-3843	100	21	techniques	technique	NOUN
cana-3843	100	22	.	.	PUNCT
cana-3843	101	1	the	the	DET
cana-3843	101	2	optimization	optimization	NOUN
cana-3843	101	3	technique	technique	NOUN
cana-3843	101	4	simultaneously	simultaneously	ADV
cana-3843	101	5	explores	explore	VERB
cana-3843	101	6	information	information	NOUN
cana-3843	101	7	from	from	ADP
cana-3843	101	8	multiple	multiple	ADJ
cana-3843	101	9	search	search	NOUN
cana-3843	101	10	points[20	points[20	NOUN
cana-3843	101	11	]	]	PUNCT
cana-3843	101	12	and	and	CCONJ
cana-3843	101	13	effectively	effectively	ADV
cana-3843	101	14	prevents	prevent	VERB
cana-3843	101	15	the	the	DET
cana-3843	101	16	iterative	iterative	NOUN
cana-3843	101	17	process	process	NOUN
cana-3843	101	18	from	from	ADP
cana-3843	101	19	converging	converge	VERB
cana-3843	101	20	on	on	ADP
cana-3843	101	21	local	local	ADJ
cana-3843	101	22	optimal	optimal	ADJ
cana-3843	101	23	solutions	solution	NOUN
cana-3843	101	24	and	and	CCONJ
cana-3843	101	25	producing	produce	VERB
cana-3843	101	26	a	a	DET
cana-3843	101	27	global	global	ADJ
cana-3843	101	28	optimal	optimal	ADJ
cana-3843	101	29	solution[21	solution[21	PROPN
cana-3843	101	30	]	]	PUNCT
cana-3843	101	31	.	.	PUNCT
cana-3843	102	1	the	the	DET
cana-3843	102	2	technique	technique	NOUN
cana-3843	102	3	operates	operate	VERB
cana-3843	102	4	based	base	VERB
cana-3843	102	5	on	on	ADP
cana-3843	102	6	a	a	DET
cana-3843	102	7	population	population	NOUN
cana-3843	102	8	of	of	ADP
cana-3843	102	9	chromosomes	chromosome	NOUN
cana-3843	102	10	.	.	PUNCT
cana-3843	103	1	the	the	DET
cana-3843	103	2	process	process	NOUN
cana-3843	103	3	begins	begin	VERB
cana-3843	103	4	with	with	ADP
cana-3843	103	5	initializing	initialize	VERB
cana-3843	103	6	the	the	DET
cana-3843	103	7	population	population	NOUN
cana-3843	103	8	,	,	PUNCT
cana-3843	103	9	with	with	ADP
cana-3843	103	10	a	a	DET
cana-3843	103	11	set	set	NOUN
cana-3843	103	12	of	of	ADP
cana-3843	103	13	randomly	randomly	ADV
cana-3843	103	14	generated	generate	VERB
cana-3843	103	15	chromosomes	chromosome	NOUN
cana-3843	103	16	.	.	PUNCT
cana-3843	104	1	each	each	DET
cana-3843	104	2	chromosome	chromosome	NOUN
cana-3843	104	3	,	,	PUNCT
cana-3843	104	4	composed	compose	VERB
cana-3843	104	5	of	of	ADP
cana-3843	104	6	multiple	multiple	ADJ
cana-3843	104	7	genes	gene	NOUN
cana-3843	104	8	,	,	PUNCT
cana-3843	104	9	functions	function	NOUN
cana-3843	104	10	as	as	ADP
cana-3843	104	11	a	a	DET
cana-3843	104	12	candidate	candidate	NOUN
cana-3843	104	13	solution	solution	NOUN
cana-3843	104	14	to	to	ADP
cana-3843	104	15	the	the	DET
cana-3843	104	16	problem	problem	NOUN
cana-3843	104	17	.	.	PUNCT
cana-3843	105	1	the	the	DET
cana-3843	105	2	ga	ga	PROPN
cana-3843	105	3	execution	execution	NOUN
cana-3843	105	4	process	process	NOUN
cana-3843	105	5	includes	include	VERB
cana-3843	105	6	several	several	ADJ
cana-3843	105	7	key	key	ADJ
cana-3843	105	8	steps	step	NOUN
cana-3843	105	9	,	,	PUNCT
cana-3843	105	10	including	include	VERB
cana-3843	105	11	selection	selection	NOUN
cana-3843	105	12	,	,	PUNCT
cana-3843	105	13	crossover	crossover	NOUN
cana-3843	105	14	,	,	PUNCT
cana-3843	105	15	and	and	CCONJ
cana-3843	105	16	mutation	mutation	NOUN
cana-3843	105	17	[	[	X
cana-3843	105	18	22	22	NUM
cana-3843	105	19	]	]	PUNCT
cana-3843	105	20	.	.	PUNCT
cana-3843	106	1	in	in	ADP
cana-3843	106	2	the	the	DET
cana-3843	106	3	selection	selection	NOUN
cana-3843	106	4	operation	operation	NOUN
cana-3843	106	5	,	,	PUNCT
cana-3843	106	6	two	two	NUM
cana-3843	106	7	parent	parent	NOUN
cana-3843	106	8	chromosomes	chromosome	NOUN
cana-3843	106	9	are	be	AUX
cana-3843	106	10	selected	select	VERB
cana-3843	106	11	using	use	VERB
cana-3843	106	12	various	various	ADJ
cana-3843	106	13	selection	selection	NOUN
cana-3843	106	14	methods	method	NOUN
cana-3843	106	15	like	like	ADP
cana-3843	106	16	roulette	roulette	NOUN
cana-3843	106	17	wheel	wheel	NOUN
cana-3843	106	18	,	,	PUNCT
cana-3843	106	19	tournament	tournament	NOUN
cana-3843	106	20	selection	selection	NOUN
cana-3843	106	21	,	,	PUNCT
cana-3843	106	22	and	and	CCONJ
cana-3843	106	23	random	random	ADJ
cana-3843	106	24	selection	selection	NOUN
cana-3843	106	25	.	.	PUNCT
cana-3843	107	1	after	after	ADP
cana-3843	107	2	the	the	DET
cana-3843	107	3	selection	selection	NOUN
cana-3843	107	4	process	process	NOUN
cana-3843	107	5	,	,	PUNCT
cana-3843	107	6	the	the	DET
cana-3843	107	7	selected	select	VERB
cana-3843	107	8	parent	parent	NOUN
cana-3843	107	9	chromosomes	chromosome	NOUN
cana-3843	107	10	are	be	AUX
cana-3843	107	11	applied	apply	VERB
cana-3843	107	12	to	to	ADP
cana-3843	107	13	the	the	DET
cana-3843	107	14	crossover	crossover	NOUN
cana-3843	107	15	operator	operator	NOUN
cana-3843	107	16	,	,	PUNCT
cana-3843	107	17	where	where	SCONJ
cana-3843	107	18	parts	part	NOUN
cana-3843	107	19	of	of	ADP
cana-3843	107	20	the	the	DET
cana-3843	107	21	genetic	genetic	ADJ
cana-3843	107	22	material	material	NOUN
cana-3843	107	23	are	be	AUX
cana-3843	107	24	combined	combine	VERB
cana-3843	107	25	according	accord	VERB
cana-3843	107	26	to	to	ADP
cana-3843	107	27	a	a	DET
cana-3843	107	28	specified	specify	VERB
cana-3843	107	29	crossover	crossover	NOUN
cana-3843	107	30	rate	rate	NOUN
cana-3843	107	31	to	to	PART
cana-3843	107	32	produce	produce	VERB
cana-3843	107	33	communications	communication	NOUN
cana-3843	107	34	on	on	ADP
cana-3843	107	35	applied	apply	VERB
cana-3843	107	36	nonlinear	nonlinear	ADJ
cana-3843	107	37	analysis	analysis	NOUN
cana-3843	107	38	issn	issn	NOUN
cana-3843	107	39	:	:	PUNCT
cana-3843	107	40	1074	1074	NUM
cana-3843	107	41	-	-	PUNCT
cana-3843	107	42	133x	133x	NUM
cana-3843	107	43	vol	vol	NOUN
cana-3843	107	44	32	32	NUM
cana-3843	107	45	no	no	NOUN
cana-3843	107	46	.	.	PUNCT
cana-3843	108	1	9s	9s	NUM
cana-3843	108	2	(	(	PUNCT
cana-3843	108	3	2025	2025	NUM
cana-3843	108	4	)	)	PUNCT
cana-3843	108	5	123	123	NUM
cana-3843	108	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	108	7	the	the	DET
cana-3843	108	8	offspring	offspring	NOUN
cana-3843	108	9	.	.	PUNCT
cana-3843	109	1	the	the	DET
cana-3843	109	2	next	next	ADJ
cana-3843	109	3	process	process	NOUN
cana-3843	109	4	executes	execute	VERB
cana-3843	109	5	the	the	DET
cana-3843	109	6	mutation	mutation	NOUN
cana-3843	109	7	operator	operator	NOUN
cana-3843	109	8	where	where	SCONJ
cana-3843	109	9	certain	certain	ADJ
cana-3843	109	10	genes	gene	NOUN
cana-3843	109	11	within	within	ADP
cana-3843	109	12	the	the	DET
cana-3843	109	13	offspring	offspring	NOUN
cana-3843	109	14	are	be	AUX
cana-3843	109	15	randomly	randomly	ADV
cana-3843	109	16	changed	change	VERB
cana-3843	109	17	.	.	PUNCT
cana-3843	110	1	the	the	DET
cana-3843	110	2	fitness	fitness	NOUN
cana-3843	110	3	of	of	ADP
cana-3843	110	4	the	the	DET
cana-3843	110	5	resulting	result	VERB
cana-3843	110	6	offspring	offspring	NOUN
cana-3843	110	7	is	be	AUX
cana-3843	110	8	evaluated	evaluate	VERB
cana-3843	110	9	,	,	PUNCT
cana-3843	110	10	and	and	CCONJ
cana-3843	110	11	if	if	SCONJ
cana-3843	110	12	it	it	PRON
cana-3843	110	13	demonstrates	demonstrate	VERB
cana-3843	110	14	better	well	ADJ
cana-3843	110	15	fitness	fitness	NOUN
cana-3843	110	16	than	than	ADP
cana-3843	110	17	the	the	DET
cana-3843	110	18	parent	parent	NOUN
cana-3843	110	19	,	,	PUNCT
cana-3843	110	20	the	the	DET
cana-3843	110	21	offspring	offspring	NOUN
cana-3843	110	22	replaces	replace	VERB
cana-3843	110	23	the	the	DET
cana-3843	110	24	parent	parent	NOUN
cana-3843	110	25	in	in	ADP
cana-3843	110	26	the	the	DET
cana-3843	110	27	population	population	NOUN
cana-3843	110	28	.	.	PUNCT
cana-3843	111	1	this	this	DET
cana-3843	111	2	execution	execution	NOUN
cana-3843	111	3	process	process	NOUN
cana-3843	111	4	continues	continue	VERB
cana-3843	111	5	until	until	SCONJ
cana-3843	111	6	a	a	DET
cana-3843	111	7	predetermined	predetermine	VERB
cana-3843	111	8	termination	termination	NOUN
cana-3843	111	9	condition	condition	NOUN
cana-3843	111	10	is	be	AUX
cana-3843	111	11	satisfied	satisfied	ADJ
cana-3843	111	12	and	and	CCONJ
cana-3843	111	13	the	the	DET
cana-3843	111	14	most	most	ADV
cana-3843	111	15	optimal	optimal	ADJ
cana-3843	111	16	chromosome	chromosome	NOUN
cana-3843	111	17	is	be	AUX
cana-3843	111	18	selected	select	VERB
cana-3843	111	19	as	as	ADP
cana-3843	111	20	the	the	DET
cana-3843	111	21	final	final	ADJ
cana-3843	111	22	solution	solution	NOUN
cana-3843	111	23	.	.	PUNCT
cana-3843	112	1	algorithm	algorithm	NOUN
cana-3843	112	2	-	-	PUNCT
cana-3843	112	3	i	i	PRON
cana-3843	112	4	outlines	outline	VERB
cana-3843	112	5	the	the	DET
cana-3843	112	6	steps	step	NOUN
cana-3843	112	7	for	for	ADP
cana-3843	112	8	determining	determine	VERB
cana-3843	112	9	the	the	DET
cana-3843	112	10	optimal	optimal	ADJ
cana-3843	112	11	number	number	NOUN
cana-3843	112	12	of	of	ADP
cana-3843	112	13	attributes	attribute	NOUN
cana-3843	112	14	in	in	ADP
cana-3843	112	15	the	the	DET
cana-3843	112	16	dataset	dataset	NOUN
cana-3843	112	17	.	.	PUNCT
cana-3843	113	1	algorithm	algorithm	PROPN
cana-3843	113	2	-	-	PUNCT
cana-3843	113	3	i	i	PRON
cana-3843	113	4	#	#	NOUN
cana-3843	113	5	attribute	attribute	NOUN
cana-3843	113	6	selection	selection	NOUN
cana-3843	113	7	using	use	VERB
cana-3843	113	8	genetic	genetic	ADJ
cana-3843	113	9	optimization	optimization	NOUN
cana-3843	113	10	technique	technique	NOUN
cana-3843	113	11	step	step	NOUN
cana-3843	113	12	1	1	NUM
cana-3843	113	13	:	:	PUNCT
cana-3843	113	14	initialize	initialize	VERB
cana-3843	113	15	i=0	i=0	PROPN
cana-3843	113	16	step	step	NOUN
cana-3843	113	17	2	2	NUM
cana-3843	113	18	:	:	PUNCT
cana-3843	113	19	generate	generate	VERB
cana-3843	113	20	the	the	DET
cana-3843	113	21	population	population	NOUN
cana-3843	113	22	of	of	ADP
cana-3843	113	23	individuals	individual	NOUN
cana-3843	113	24	p(i	p(i	PROPN
cana-3843	113	25	)	)	PUNCT
cana-3843	113	26	step	step	NOUN
cana-3843	113	27	3	3	NUM
cana-3843	113	28	:	:	PUNCT
cana-3843	113	29	determine	determine	VERB
cana-3843	113	30	the	the	DET
cana-3843	113	31	fitness	fitness	NOUN
cana-3843	113	32	of	of	ADP
cana-3843	113	33	each	each	DET
cana-3843	113	34	individual	individual	NOUN
cana-3843	113	35	in	in	ADP
cana-3843	113	36	the	the	DET
cana-3843	113	37	population	population	NOUN
cana-3843	113	38	.	.	PUNCT
cana-3843	114	1	step	step	VERB
cana-3843	114	2	4	4	NUM
cana-3843	114	3	:	:	PUNCT
cana-3843	114	4	while	while	SCONJ
cana-3843	114	5	(	(	PUNCT
cana-3843	114	6	termination	termination	NOUN
cana-3843	114	7	condition	condition	NOUN
cana-3843	114	8	is	be	AUX
cana-3843	114	9	not	not	PART
cana-3843	114	10	satisfied	satisfied	ADJ
cana-3843	114	11	)	)	PUNCT
cana-3843	114	12	step	step	NOUN
cana-3843	114	13	5	5	NUM
cana-3843	114	14	:	:	PUNCT
cana-3843	114	15	do	do	AUX
cana-3843	114	16	i	i	PRON
cana-3843	114	17	=	=	NOUN
cana-3843	114	18	i+1	i+1	PART
cana-3843	114	19	step	step	NOUN
cana-3843	114	20	6	6	NUM
cana-3843	114	21	:	:	PUNCT
cana-3843	114	22	apply	apply	VERB
cana-3843	114	23	the	the	DET
cana-3843	114	24	selection	selection	NOUN
cana-3843	114	25	operation	operation	NOUN
cana-3843	114	26	of	of	ADP
cana-3843	114	27	two	two	NUM
cana-3843	114	28	parent	parent	NOUN
cana-3843	114	29	chromosomes	chromosome	NOUN
cana-3843	114	30	based	base	VERB
cana-3843	114	31	on	on	ADP
cana-3843	114	32	fitness	fitness	NOUN
cana-3843	114	33	.	.	PUNCT
cana-3843	115	1	step	step	NOUN
cana-3843	115	2	7	7	NUM
cana-3843	115	3	:	:	PUNCT
cana-3843	115	4	perform	perform	VERB
cana-3843	115	5	crossover	crossover	NOUN
cana-3843	115	6	with	with	ADP
cana-3843	115	7	the	the	DET
cana-3843	115	8	specified	specify	VERB
cana-3843	115	9	crossover	crossover	NOUN
cana-3843	115	10	rate	rate	NOUN
cana-3843	115	11	to	to	PART
cana-3843	115	12	generate	generate	VERB
cana-3843	115	13	offspring	offspring	NOUN
cana-3843	115	14	step	step	NOUN
cana-3843	115	15	8	8	NUM
cana-3843	115	16	:	:	PUNCT
cana-3843	115	17	apply	apply	VERB
cana-3843	115	18	the	the	DET
cana-3843	115	19	mutation	mutation	NOUN
cana-3843	115	20	function	function	NOUN
cana-3843	115	21	to	to	ADP
cana-3843	115	22	the	the	DET
cana-3843	115	23	offspring	offspring	NOUN
cana-3843	115	24	step	step	NOUN
cana-3843	115	25	9	9	NUM
cana-3843	115	26	:	:	PUNCT
cana-3843	115	27	end	end	NOUN
cana-3843	115	28	while	while	SCONJ
cana-3843	115	29	step	step	NOUN
cana-3843	115	30	10	10	NUM
cana-3843	115	31	:	:	PUNCT
cana-3843	115	32	return	return	VERB
cana-3843	115	33	the	the	DET
cana-3843	115	34	fittest	fit	ADJ
cana-3843	115	35	individuals	individual	NOUN
cana-3843	115	36	in	in	ADP
cana-3843	115	37	the	the	DET
cana-3843	115	38	population	population	NOUN
cana-3843	115	39	.	.	PUNCT
cana-3843	116	1	3.3	3.3	NUM
cana-3843	116	2	.	.	PUNCT
cana-3843	117	1	long	long	ADJ
cana-3843	117	2	short	short	ADJ
cana-3843	117	3	term	term	NOUN
cana-3843	117	4	method	method	NOUN
cana-3843	117	5	(	(	PUNCT
cana-3843	117	6	lstm	lstm	NOUN
cana-3843	117	7	)	)	PUNCT
cana-3843	117	8	network	network	NOUN
cana-3843	117	9	lstm	lstm	NOUN
cana-3843	117	10	is	be	AUX
cana-3843	117	11	a	a	DET
cana-3843	117	12	type	type	NOUN
cana-3843	117	13	of	of	ADP
cana-3843	117	14	recurrent	recurrent	NOUN
cana-3843	117	15	nn	nn	PROPN
cana-3843	117	16	and	and	CCONJ
cana-3843	117	17	is	be	AUX
cana-3843	117	18	effective	effective	ADJ
cana-3843	117	19	in	in	ADP
cana-3843	117	20	processing	process	VERB
cana-3843	117	21	sequential	sequential	ADJ
cana-3843	117	22	data	datum	NOUN
cana-3843	117	23	.	.	PUNCT
cana-3843	118	1	the	the	DET
cana-3843	118	2	network	network	NOUN
cana-3843	118	3	incorporates	incorporate	VERB
cana-3843	118	4	a	a	DET
cana-3843	118	5	memory	memory	NOUN
cana-3843	118	6	cell	cell	NOUN
cana-3843	118	7	capable	capable	ADJ
cana-3843	118	8	of	of	ADP
cana-3843	118	9	holding	hold	VERB
cana-3843	118	10	information	information	NOUN
cana-3843	118	11	for	for	ADP
cana-3843	118	12	a	a	DET
cana-3843	118	13	long	long	ADJ
cana-3843	118	14	period	period	NOUN
cana-3843	118	15	and	and	CCONJ
cana-3843	118	16	enabling	enable	VERB
cana-3843	118	17	the	the	DET
cana-3843	118	18	model	model	NOUN
cana-3843	118	19	to	to	PART
cana-3843	118	20	retain	retain	VERB
cana-3843	118	21	the	the	DET
cana-3843	118	22	recently	recently	ADV
cana-3843	118	23	computed	compute	VERB
cana-3843	118	24	values	value	NOUN
cana-3843	118	25	[	[	X
cana-3843	118	26	23	23	NUM
cana-3843	118	27	]	]	PUNCT
cana-3843	118	28	.	.	PUNCT
cana-3843	119	1	the	the	DET
cana-3843	119	2	network	network	NOUN
cana-3843	119	3	consists	consist	VERB
cana-3843	119	4	of	of	ADP
cana-3843	119	5	three	three	NUM
cana-3843	119	6	kinds	kind	NOUN
cana-3843	119	7	of	of	ADP
cana-3843	119	8	gates	gate	NOUN
cana-3843	119	9	such	such	ADJ
cana-3843	119	10	as	as	ADP
cana-3843	119	11	input	input	NOUN
cana-3843	119	12	,	,	PUNCT
cana-3843	119	13	output	output	NOUN
cana-3843	119	14	,	,	PUNCT
cana-3843	119	15	and	and	CCONJ
cana-3843	119	16	forget	forget	VERB
cana-3843	119	17	gates	gate	NOUN
cana-3843	119	18	,	,	PUNCT
cana-3843	119	19	and	and	CCONJ
cana-3843	119	20	maintains	maintain	VERB
cana-3843	119	21	two	two	NUM
cana-3843	119	22	state	state	NOUN
cana-3843	119	23	units	unit	NOUN
cana-3843	119	24	such	such	ADJ
cana-3843	119	25	as	as	ADP
cana-3843	119	26	cell	cell	NOUN
cana-3843	119	27	and	and	CCONJ
cana-3843	119	28	hidden	hidden	ADJ
cana-3843	119	29	state	state	NOUN
cana-3843	119	30	.	.	PUNCT
cana-3843	120	1	the	the	DET
cana-3843	120	2	input	input	NOUN
cana-3843	120	3	gate	gate	NOUN
cana-3843	120	4	regulates	regulate	VERB
cana-3843	120	5	the	the	DET
cana-3843	120	6	flow	flow	NOUN
cana-3843	120	7	of	of	ADP
cana-3843	120	8	data	datum	NOUN
cana-3843	120	9	into	into	ADP
cana-3843	120	10	the	the	DET
cana-3843	120	11	cell	cell	NOUN
cana-3843	120	12	state	state	NOUN
cana-3843	120	13	,	,	PUNCT
cana-3843	120	14	while	while	SCONJ
cana-3843	120	15	the	the	DET
cana-3843	120	16	forget	forget	NOUN
cana-3843	120	17	gate	gate	NOUN
cana-3843	120	18	is	be	AUX
cana-3843	120	19	responsible	responsible	ADJ
cana-3843	120	20	for	for	ADP
cana-3843	120	21	determining	determine	VERB
cana-3843	120	22	the	the	DET
cana-3843	120	23	information	information	NOUN
cana-3843	120	24	from	from	ADP
cana-3843	120	25	the	the	DET
cana-3843	120	26	previous	previous	ADJ
cana-3843	120	27	cell	cell	NOUN
cana-3843	120	28	state	state	NOUN
cana-3843	120	29	,	,	PUNCT
cana-3843	120	30	and	and	CCONJ
cana-3843	120	31	the	the	DET
cana-3843	120	32	output	output	NOUN
cana-3843	120	33	gate	gate	NOUN
cana-3843	120	34	controls	control	VERB
cana-3843	120	35	the	the	DET
cana-3843	120	36	flow	flow	NOUN
cana-3843	120	37	of	of	ADP
cana-3843	120	38	data	datum	NOUN
cana-3843	120	39	out	out	ADP
cana-3843	120	40	of	of	ADP
cana-3843	120	41	the	the	DET
cana-3843	120	42	cell	cell	NOUN
cana-3843	120	43	state	state	NOUN
cana-3843	120	44	.	.	PUNCT
cana-3843	121	1	the	the	DET
cana-3843	121	2	sigmoid	sigmoid	NOUN
cana-3843	121	3	activation	activation	NOUN
cana-3843	121	4	function	function	NOUN
cana-3843	121	5	is	be	AUX
cana-3843	121	6	utilized	utilize	VERB
cana-3843	121	7	to	to	PART
cana-3843	121	8	produce	produce	VERB
cana-3843	121	9	the	the	DET
cana-3843	121	10	output	output	NOUN
cana-3843	121	11	values	value	NOUN
cana-3843	121	12	within	within	ADP
cana-3843	121	13	the	the	DET
cana-3843	121	14	range	range	NOUN
cana-3843	121	15	of	of	ADP
cana-3843	121	16	0	0	NUM
cana-3843	121	17	to	to	PART
cana-3843	121	18	1	1	NUM
cana-3843	121	19	.	.	PUNCT
cana-3843	122	1	the	the	DET
cana-3843	122	2	gates	gate	NOUN
cana-3843	122	3	are	be	AUX
cana-3843	122	4	trained	train	VERB
cana-3843	122	5	using	use	VERB
cana-3843	122	6	a	a	DET
cana-3843	122	7	backpropagation	backpropagation	NOUN
cana-3843	122	8	algorithm	algorithm	NOUN
cana-3843	122	9	through	through	ADP
cana-3843	122	10	the	the	DET
cana-3843	122	11	network	network	NOUN
cana-3843	122	12	.	.	PUNCT
cana-3843	123	1	the	the	DET
cana-3843	123	2	training	training	NOUN
cana-3843	123	3	process	process	NOUN
cana-3843	123	4	for	for	ADP
cana-3843	123	5	the	the	DET
cana-3843	123	6	gates	gate	NOUN
cana-3843	123	7	depends	depend	VERB
cana-3843	123	8	on	on	ADP
cana-3843	123	9	the	the	DET
cana-3843	123	10	input	input	NOUN
cana-3843	123	11	and	and	CCONJ
cana-3843	123	12	the	the	DET
cana-3843	123	13	previous	previous	ADJ
cana-3843	123	14	hidden	hidden	ADJ
cana-3843	123	15	state	state	NOUN
cana-3843	123	16	,	,	PUNCT
cana-3843	123	17	allowing	allow	VERB
cana-3843	123	18	the	the	DET
cana-3843	123	19	lstm	lstm	NOUN
cana-3843	123	20	to	to	PART
cana-3843	123	21	selectively	selectively	ADV
cana-3843	123	22	retain	retain	VERB
cana-3843	123	23	or	or	CCONJ
cana-3843	123	24	forget	forget	VERB
cana-3843	123	25	information	information	NOUN
cana-3843	123	26	,	,	PUNCT
cana-3843	123	27	and	and	CCONJ
cana-3843	123	28	effectively	effectively	ADV
cana-3843	123	29	manage	manage	VERB
cana-3843	123	30	long	long	ADJ
cana-3843	123	31	-	-	PUNCT
cana-3843	123	32	term	term	NOUN
cana-3843	123	33	dependencies	dependency	NOUN
cana-3843	123	34	[	[	X
cana-3843	123	35	24	24	NUM
cana-3843	123	36	]	]	PUNCT
cana-3843	123	37	.	.	PUNCT
cana-3843	124	1	the	the	DET
cana-3843	124	2	lstm	lstm	PROPN
cana-3843	124	3	model	model	NOUN
cana-3843	124	4	was	be	AUX
cana-3843	124	5	employed	employ	VERB
cana-3843	124	6	to	to	PART
cana-3843	124	7	identify	identify	VERB
cana-3843	124	8	patterns	pattern	NOUN
cana-3843	124	9	and	and	CCONJ
cana-3843	124	10	relationships	relationship	NOUN
cana-3843	124	11	in	in	ADP
cana-3843	124	12	genetic	genetic	ADJ
cana-3843	124	13	mutations	mutation	NOUN
cana-3843	124	14	over	over	ADP
cana-3843	124	15	sequential	sequential	ADJ
cana-3843	124	16	time	time	NOUN
cana-3843	124	17	intervals	interval	NOUN
cana-3843	124	18	.	.	PUNCT
cana-3843	125	1	4	4	X
cana-3843	125	2	.	.	X
cana-3843	125	3	research	research	NOUN
cana-3843	125	4	methodology	methodology	NOUN
cana-3843	125	5	this	this	DET
cana-3843	125	6	section	section	NOUN
cana-3843	125	7	explores	explore	VERB
cana-3843	125	8	the	the	DET
cana-3843	125	9	proposed	propose	VERB
cana-3843	125	10	system	system	NOUN
cana-3843	125	11	for	for	ADP
cana-3843	125	12	effectively	effectively	ADV
cana-3843	125	13	identifying	identify	VERB
cana-3843	125	14	biomarker	biomarker	NOUN
cana-3843	125	15	genes	gene	NOUN
cana-3843	125	16	with	with	ADP
cana-3843	125	17	high	high	ADJ
cana-3843	125	18	predictive	predictive	ADJ
cana-3843	125	19	value	value	NOUN
cana-3843	125	20	.	.	PUNCT
cana-3843	126	1	figure-1	figure-1	NOUN
cana-3843	126	2	presents	present	VERB
cana-3843	126	3	the	the	DET
cana-3843	126	4	design	design	NOUN
cana-3843	126	5	of	of	ADP
cana-3843	126	6	the	the	DET
cana-3843	126	7	proposed	propose	VERB
cana-3843	126	8	research	research	NOUN
cana-3843	126	9	model	model	NOUN
cana-3843	126	10	.	.	PUNCT
cana-3843	127	1	the	the	DET
cana-3843	127	2	process	process	NOUN
cana-3843	127	3	includes	include	VERB
cana-3843	127	4	the	the	DET
cana-3843	127	5	following	follow	VERB
cana-3843	127	6	phases	phase	NOUN
cana-3843	127	7	:	:	PUNCT
cana-3843	127	8	exploratory	exploratory	ADJ
cana-3843	127	9	data	datum	NOUN
cana-3843	127	10	analysis	analysis	NOUN
cana-3843	127	11	,	,	PUNCT
cana-3843	127	12	data	datum	NOUN
cana-3843	127	13	preprocessing	preprocessing	NOUN
cana-3843	127	14	,	,	PUNCT
cana-3843	127	15	optimal	optimal	ADJ
cana-3843	127	16	gene	gene	NOUN
cana-3843	127	17	selection	selection	NOUN
cana-3843	127	18	,	,	PUNCT
cana-3843	127	19	classification	classification	NOUN
cana-3843	127	20	,	,	PUNCT
cana-3843	127	21	and	and	CCONJ
cana-3843	127	22	evaluation	evaluation	NOUN
cana-3843	127	23	of	of	ADP
cana-3843	127	24	the	the	DET
cana-3843	127	25	model	model	NOUN
cana-3843	127	26	.	.	PUNCT
cana-3843	128	1	algorithm	algorithm	NOUN
cana-3843	128	2	-	-	PUNCT
cana-3843	128	3	ii	ii	PROPN
cana-3843	128	4	presents	present	VERB
cana-3843	128	5	the	the	DET
cana-3843	128	6	key	key	ADJ
cana-3843	128	7	steps	step	NOUN
cana-3843	128	8	of	of	ADP
cana-3843	128	9	communications	communication	NOUN
cana-3843	128	10	on	on	ADP
cana-3843	128	11	applied	apply	VERB
cana-3843	128	12	nonlinear	nonlinear	ADJ
cana-3843	128	13	analysis	analysis	NOUN
cana-3843	128	14	issn	issn	NOUN
cana-3843	128	15	:	:	PUNCT
cana-3843	128	16	1074	1074	NUM
cana-3843	128	17	-	-	PUNCT
cana-3843	128	18	133x	133x	NUM
cana-3843	128	19	vol	vol	NOUN
cana-3843	128	20	32	32	NUM
cana-3843	128	21	no	no	NOUN
cana-3843	128	22	.	.	PUNCT
cana-3843	129	1	9s	9s	NUM
cana-3843	129	2	(	(	PUNCT
cana-3843	129	3	2025	2025	NUM
cana-3843	129	4	)	)	PUNCT
cana-3843	129	5	124	124	NUM
cana-3843	130	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	130	2	the	the	DET
cana-3843	130	3	proposed	propose	VERB
cana-3843	130	4	methodology	methodology	NOUN
cana-3843	130	5	for	for	ADP
cana-3843	130	6	identifying	identify	VERB
cana-3843	130	7	the	the	DET
cana-3843	130	8	prominent	prominent	ADJ
cana-3843	130	9	set	set	NOUN
cana-3843	130	10	of	of	ADP
cana-3843	130	11	genes	gene	NOUN
cana-3843	130	12	associated	associate	VERB
cana-3843	130	13	with	with	ADP
cana-3843	130	14	leukemia	leukemia	NOUN
cana-3843	130	15	and	and	CCONJ
cana-3843	130	16	classifying	classify	VERB
cana-3843	130	17	the	the	DET
cana-3843	130	18	subtypes	subtype	NOUN
cana-3843	130	19	in	in	ADP
cana-3843	130	20	the	the	DET
cana-3843	130	21	dataset	dataset	NOUN
cana-3843	130	22	.	.	PUNCT
cana-3843	131	1	figure-1	figure-1	NOUN
cana-3843	131	2	framework	framework	NOUN
cana-3843	131	3	of	of	ADP
cana-3843	131	4	the	the	DET
cana-3843	131	5	research	research	NOUN
cana-3843	131	6	model	model	NOUN
cana-3843	131	7	algorithm	algorithm	PROPN
cana-3843	131	8	-	-	PUNCT
cana-3843	131	9	ii(cor	ii(cor	PROPN
cana-3843	131	10	-	-	PUNCT
cana-3843	131	11	ga_snr	ga_snr	NOUN
cana-3843	131	12	-	-	PUNCT
cana-3843	131	13	lstm	lstm	NOUN
cana-3843	131	14	)	)	PUNCT
cana-3843	131	15	1	1	NUM
cana-3843	131	16	.	.	X
cana-3843	131	17	load	load	VERB
cana-3843	131	18	the	the	DET
cana-3843	131	19	leukemia	leukemia	NOUN
cana-3843	131	20	cancer	cancer	NOUN
cana-3843	131	21	gene	gene	NOUN
cana-3843	131	22	data	datum	NOUN
cana-3843	131	23	set	set	VERB
cana-3843	131	24	.	.	PUNCT
cana-3843	132	1	2	2	X
cana-3843	132	2	.	.	X
cana-3843	132	3	perform	perform	VERB
cana-3843	132	4	exploratory	exploratory	ADJ
cana-3843	132	5	data	datum	NOUN
cana-3843	132	6	analysis	analysis	NOUN
cana-3843	132	7	:	:	PUNCT
cana-3843	132	8	2.1	2.1	NUM
cana-3843	132	9	identify	identify	VERB
cana-3843	132	10	the	the	DET
cana-3843	132	11	characteristics	characteristic	NOUN
cana-3843	132	12	and	and	CCONJ
cana-3843	132	13	patterns	pattern	NOUN
cana-3843	132	14	of	of	ADP
cana-3843	132	15	the	the	DET
cana-3843	132	16	gene	gene	NOUN
cana-3843	132	17	expression	expression	NOUN
cana-3843	132	18	data	datum	NOUN
cana-3843	132	19	.	.	PUNCT
cana-3843	133	1	2.2	2.2	NUM
cana-3843	133	2	calculate	calculate	VERB
cana-3843	133	3	the	the	DET
cana-3843	133	4	central	central	ADJ
cana-3843	133	5	tendency	tendency	NOUN
cana-3843	133	6	and	and	CCONJ
cana-3843	133	7	dispersion	dispersion	NOUN
cana-3843	133	8	of	of	ADP
cana-3843	133	9	the	the	DET
cana-3843	133	10	gene	gene	NOUN
cana-3843	133	11	values	value	NOUN
cana-3843	133	12	.	.	PUNCT
cana-3843	134	1	3	3	X
cana-3843	134	2	.	.	X
cana-3843	134	3	perform	perform	VERB
cana-3843	134	4	the	the	DET
cana-3843	134	5	preprocessing	preprocessing	NOUN
cana-3843	134	6	stage	stage	NOUN
cana-3843	134	7	:	:	PUNCT
cana-3843	134	8	3.1	3.1	NUM
cana-3843	134	9	handle	handle	NOUN
cana-3843	134	10	missing	miss	VERB
cana-3843	134	11	and	and	CCONJ
cana-3843	134	12	null	null	ADJ
cana-3843	134	13	values	value	NOUN
cana-3843	134	14	within	within	ADP
cana-3843	134	15	the	the	DET
cana-3843	134	16	dataset	dataset	NOUN
cana-3843	134	17	by	by	ADP
cana-3843	134	18	imputation	imputation	NOUN
cana-3843	134	19	method	method	NOUN
cana-3843	134	20	.	.	PUNCT
cana-3843	135	1	3.2	3.2	NUM
cana-3843	135	2	transform	transform	VERB
cana-3843	135	3	categorical	categorical	ADJ
cana-3843	135	4	gene	gene	NOUN
cana-3843	135	5	information	information	NOUN
cana-3843	135	6	into	into	ADP
cana-3843	135	7	numerical	numerical	ADJ
cana-3843	135	8	values	value	NOUN
cana-3843	135	9	using	use	VERB
cana-3843	135	10	label	label	NOUN
cana-3843	135	11	encoding	encoding	NOUN
cana-3843	135	12	.	.	PUNCT
cana-3843	136	1	3.3	3.3	NUM
cana-3843	136	2	apply	apply	VERB
cana-3843	136	3	feature	feature	NOUN
cana-3843	136	4	scaling	scaling	NOUN
cana-3843	136	5	using	use	VERB
cana-3843	136	6	min	min	ADJ
cana-3843	136	7	-	-	ADJ
cana-3843	136	8	max	max	PROPN
cana-3843	136	9	normalization	normalization	NOUN
cana-3843	136	10	to	to	PART
cana-3843	136	11	normalize	normalize	VERB
cana-3843	136	12	the	the	DET
cana-3843	136	13	data	datum	NOUN
cana-3843	136	14	in	in	ADP
cana-3843	136	15	the	the	DET
cana-3843	136	16	dataset	dataset	NOUN
cana-3843	136	17	.	.	PUNCT
cana-3843	137	1	3.4	3.4	NUM
cana-3843	137	2	evaluate	evaluate	VERB
cana-3843	137	3	multicollinearity	multicollinearity	NOUN
cana-3843	137	4	among	among	ADP
cana-3843	137	5	genes	gene	NOUN
cana-3843	137	6	using	use	VERB
cana-3843	137	7	a	a	DET
cana-3843	137	8	correlation	correlation	NOUN
cana-3843	137	9	matrix	matrix	NOUN
cana-3843	137	10	to	to	PART
cana-3843	137	11	identify	identify	VERB
cana-3843	137	12	and	and	CCONJ
cana-3843	137	13	measure	measure	VERB
cana-3843	137	14	low	low	ADJ
cana-3843	137	15	intercorrelated	intercorrelate	VERB
cana-3843	137	16	genes	gene	NOUN
cana-3843	137	17	using	use	VERB
cana-3843	137	18	the	the	DET
cana-3843	137	19	equation	equation	NOUN
cana-3843	137	20	(	(	PUNCT
cana-3843	137	21	1	1	NUM
cana-3843	137	22	)	)	PUNCT
cana-3843	137	23	and	and	CCONJ
cana-3843	137	24	(	(	PUNCT
cana-3843	137	25	2	2	X
cana-3843	137	26	)	)	PUNCT
cana-3843	137	27	3.5	3.5	NUM
cana-3843	137	28	remove	remove	VERB
cana-3843	137	29	redundant	redundant	ADJ
cana-3843	137	30	genes	gene	NOUN
cana-3843	137	31	and	and	CCONJ
cana-3843	137	32	store	store	VERB
cana-3843	137	33	the	the	DET
cana-3843	137	34	relevant	relevant	ADJ
cana-3843	137	35	genes	gene	NOUN
cana-3843	137	36	.	.	PUNCT
cana-3843	138	1	4	4	X
cana-3843	138	2	.	.	X
cana-3843	138	3	perform	perform	VERB
cana-3843	138	4	optimal	optimal	ADJ
cana-3843	138	5	gene	gene	NOUN
cana-3843	138	6	selection	selection	NOUN
cana-3843	138	7	:	:	PUNCT
cana-3843	138	8	4.1	4.1	NUM
cana-3843	138	9	apply	apply	VERB
cana-3843	138	10	a	a	DET
cana-3843	138	11	genetic	genetic	ADJ
cana-3843	138	12	optimization	optimization	NOUN
cana-3843	138	13	technique	technique	NOUN
cana-3843	138	14	with	with	ADP
cana-3843	138	15	signal	signal	NOUN
cana-3843	138	16	-	-	PUNCT
cana-3843	138	17	to	to	ADP
cana-3843	138	18	-	-	PUNCT
cana-3843	138	19	noise	noise	NOUN
cana-3843	138	20	ratio	ratio	NOUN
cana-3843	138	21	as	as	SCONJ
cana-3843	138	22	the	the	DET
cana-3843	138	23	fitness	fitness	NOUN
cana-3843	138	24	function	function	NOUN
cana-3843	138	25	to	to	PART
cana-3843	138	26	identify	identify	VERB
cana-3843	138	27	an	an	DET
cana-3843	138	28	optimized	optimize	VERB
cana-3843	138	29	subset	subset	NOUN
cana-3843	138	30	of	of	ADP
cana-3843	138	31	significant	significant	ADJ
cana-3843	138	32	genes	gene	NOUN
cana-3843	138	33	.	.	PUNCT
cana-3843	139	1	4.2	4.2	NUM
cana-3843	139	2	store	store	VERB
cana-3843	139	3	the	the	DET
cana-3843	139	4	optimized	optimize	VERB
cana-3843	139	5	set	set	NOUN
cana-3843	139	6	of	of	ADP
cana-3843	139	7	features	feature	NOUN
cana-3843	139	8	in	in	ADP
cana-3843	139	9	a	a	DET
cana-3843	139	10	.csv	.csv	ADJ
cana-3843	139	11	file	file	NOUN
cana-3843	139	12	.	.	PUNCT
cana-3843	140	1	5	5	X
cana-3843	140	2	.	.	X
cana-3843	140	3	perform	perform	VERB
cana-3843	140	4	the	the	DET
cana-3843	140	5	classification	classification	NOUN
cana-3843	140	6	process	process	NOUN
cana-3843	140	7	:	:	PUNCT
cana-3843	140	8	communications	communication	NOUN
cana-3843	140	9	on	on	ADP
cana-3843	140	10	applied	apply	VERB
cana-3843	140	11	nonlinear	nonlinear	ADJ
cana-3843	140	12	analysis	analysis	NOUN
cana-3843	140	13	issn	issn	NOUN
cana-3843	140	14	:	:	PUNCT
cana-3843	140	15	1074	1074	NUM
cana-3843	140	16	-	-	PUNCT
cana-3843	140	17	133x	133x	NUM
cana-3843	140	18	vol	vol	NOUN
cana-3843	140	19	32	32	NUM
cana-3843	140	20	no	no	NOUN
cana-3843	140	21	.	.	PUNCT
cana-3843	141	1	9s	9s	NUM
cana-3843	141	2	(	(	PUNCT
cana-3843	141	3	2025	2025	NUM
cana-3843	141	4	)	)	PUNCT
cana-3843	141	5	125	125	NUM
cana-3843	141	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	141	7	5.1	5.1	NUM
cana-3843	141	8	train	train	NOUN
cana-3843	141	9	the	the	DET
cana-3843	141	10	lstm	lstm	PROPN
cana-3843	141	11	model	model	NOUN
cana-3843	141	12	on	on	ADP
cana-3843	141	13	the	the	DET
cana-3843	141	14	optimized	optimize	VERB
cana-3843	141	15	gene	gene	NOUN
cana-3843	141	16	set	set	VERB
cana-3843	141	17	to	to	PART
cana-3843	141	18	classify	classify	VERB
cana-3843	141	19	the	the	DET
cana-3843	141	20	data	datum	NOUN
cana-3843	141	21	.	.	PUNCT
cana-3843	142	1	6	6	NUM
cana-3843	142	2	.	.	X
cana-3843	142	3	performance	performance	NOUN
cana-3843	142	4	evaluation	evaluation	NOUN
cana-3843	142	5	:	:	PUNCT
cana-3843	142	6	6.1	6.1	NUM
cana-3843	142	7	to	to	PART
cana-3843	142	8	evaluate	evaluate	VERB
cana-3843	142	9	the	the	DET
cana-3843	142	10	model	model	NOUN
cana-3843	142	11	performance	performance	NOUN
cana-3843	142	12	,	,	PUNCT
cana-3843	142	13	different	different	ADJ
cana-3843	142	14	optimizers	optimizer	NOUN
cana-3843	142	15	are	be	AUX
cana-3843	142	16	applied	apply	VERB
cana-3843	142	17	to	to	PART
cana-3843	142	18	measure	measure	VERB
cana-3843	142	19	and	and	CCONJ
cana-3843	142	20	analyze	analyze	VERB
cana-3843	142	21	accuracy	accuracy	NOUN
cana-3843	142	22	and	and	CCONJ
cana-3843	142	23	loss	loss	NOUN
cana-3843	142	24	values	value	NOUN
cana-3843	142	25	during	during	ADP
cana-3843	142	26	the	the	DET
cana-3843	142	27	training	training	NOUN
cana-3843	142	28	phase	phase	NOUN
cana-3843	142	29	and	and	CCONJ
cana-3843	142	30	testing	testing	NOUN
cana-3843	142	31	phase	phase	NOUN
cana-3843	142	32	,	,	PUNCT
cana-3843	142	33	along	along	ADP
cana-3843	142	34	with	with	ADP
cana-3843	142	35	precision	precision	NOUN
cana-3843	142	36	rate	rate	NOUN
cana-3843	142	37	,	,	PUNCT
cana-3843	142	38	recall	recall	NOUN
cana-3843	142	39	measure	measure	NOUN
cana-3843	142	40	,	,	PUNCT
cana-3843	142	41	and	and	CCONJ
cana-3843	142	42	f1	f1	ADJ
cana-3843	142	43	-	-	PUNCT
cana-3843	142	44	score	score	NOUN
cana-3843	142	45	value	value	NOUN
cana-3843	142	46	.	.	PUNCT
cana-3843	143	1	in	in	ADP
cana-3843	143	2	the	the	DET
cana-3843	143	3	first	first	ADJ
cana-3843	143	4	phase	phase	NOUN
cana-3843	143	5	,	,	PUNCT
cana-3843	143	6	read	read	VERB
cana-3843	143	7	the	the	DET
cana-3843	143	8	leukemia	leukemia	NOUN
cana-3843	143	9	cancer	cancer	NOUN
cana-3843	143	10	gene	gene	NOUN
cana-3843	143	11	dataset	dataset	VERB
cana-3843	143	12	from	from	ADP
cana-3843	143	13	the	the	DET
cana-3843	143	14	krbr	krbr	NOUN
cana-3843	143	15	repository	repository	NOUN
cana-3843	143	16	.	.	PUNCT
cana-3843	144	1	during	during	ADP
cana-3843	144	2	the	the	DET
cana-3843	144	3	exploratory	exploratory	ADJ
cana-3843	144	4	data	datum	NOUN
cana-3843	144	5	analysis	analysis	NOUN
cana-3843	144	6	,	,	PUNCT
cana-3843	144	7	the	the	DET
cana-3843	144	8	shape	shape	NOUN
cana-3843	144	9	and	and	CCONJ
cana-3843	144	10	size	size	NOUN
cana-3843	144	11	of	of	ADP
cana-3843	144	12	the	the	DET
cana-3843	144	13	genes	gene	NOUN
cana-3843	144	14	/	/	SYM
cana-3843	144	15	features	feature	NOUN
cana-3843	144	16	,	,	PUNCT
cana-3843	144	17	and	and	CCONJ
cana-3843	144	18	samples	sample	NOUN
cana-3843	144	19	are	be	AUX
cana-3843	144	20	examined	examine	VERB
cana-3843	144	21	.	.	PUNCT
cana-3843	145	1	identify	identify	VERB
cana-3843	145	2	each	each	DET
cana-3843	145	3	gene	gene	NOUN
cana-3843	145	4	datatype	datatype	NOUN
cana-3843	145	5	and	and	CCONJ
cana-3843	145	6	calculate	calculate	VERB
cana-3843	145	7	the	the	DET
cana-3843	145	8	mean	mean	ADJ
cana-3843	145	9	,	,	PUNCT
cana-3843	145	10	median	median	ADJ
cana-3843	145	11	,	,	PUNCT
cana-3843	145	12	min	min	PROPN
cana-3843	145	13	,	,	PUNCT
cana-3843	145	14	max	max	PROPN
cana-3843	145	15	,	,	PUNCT
cana-3843	145	16	standard	standard	ADJ
cana-3843	145	17	deviation	deviation	NOUN
cana-3843	145	18	,	,	PUNCT
cana-3843	145	19	and	and	CCONJ
cana-3843	145	20	percentile	percentile	ADJ
cana-3843	145	21	value	value	NOUN
cana-3843	145	22	of	of	ADP
cana-3843	145	23	all	all	DET
cana-3843	145	24	genes	gene	NOUN
cana-3843	145	25	in	in	ADP
cana-3843	145	26	the	the	DET
cana-3843	145	27	dataset	dataset	NOUN
cana-3843	145	28	.	.	PUNCT
cana-3843	146	1	this	this	DET
cana-3843	146	2	stage	stage	NOUN
cana-3843	146	3	acts	act	VERB
cana-3843	146	4	as	as	ADP
cana-3843	146	5	the	the	DET
cana-3843	146	6	initial	initial	ADJ
cana-3843	146	7	step	step	NOUN
cana-3843	146	8	in	in	ADP
cana-3843	146	9	investigating	investigate	VERB
cana-3843	146	10	the	the	DET
cana-3843	146	11	dataset	dataset	NOUN
cana-3843	146	12	to	to	PART
cana-3843	146	13	understand	understand	VERB
cana-3843	146	14	its	its	PRON
cana-3843	146	15	characteristics	characteristic	NOUN
cana-3843	146	16	,	,	PUNCT
cana-3843	146	17	patterns	pattern	NOUN
cana-3843	146	18	,	,	PUNCT
cana-3843	146	19	or	or	CCONJ
cana-3843	146	20	anomalies	anomaly	NOUN
cana-3843	146	21	for	for	ADP
cana-3843	146	22	later	later	ADJ
cana-3843	146	23	stages	stage	NOUN
cana-3843	146	24	of	of	ADP
cana-3843	146	25	analysis	analysis	NOUN
cana-3843	146	26	.	.	PUNCT
cana-3843	147	1	the	the	DET
cana-3843	147	2	data	datum	NOUN
cana-3843	147	3	preprocessing	preprocessing	NOUN
cana-3843	147	4	is	be	AUX
cana-3843	147	5	an	an	DET
cana-3843	147	6	important	important	ADJ
cana-3843	147	7	phase	phase	NOUN
cana-3843	147	8	for	for	ADP
cana-3843	147	9	cleaning	clean	VERB
cana-3843	147	10	the	the	DET
cana-3843	147	11	data	datum	NOUN
cana-3843	147	12	to	to	PART
cana-3843	147	13	achieve	achieve	VERB
cana-3843	147	14	suitability	suitability	NOUN
cana-3843	147	15	for	for	ADP
cana-3843	147	16	developing	develop	VERB
cana-3843	147	17	the	the	DET
cana-3843	147	18	deep	deep	ADJ
cana-3843	147	19	learning	learning	NOUN
cana-3843	147	20	model	model	NOUN
cana-3843	147	21	,	,	PUNCT
cana-3843	147	22	thereby	thereby	ADV
cana-3843	147	23	enhancing	enhance	VERB
cana-3843	147	24	the	the	DET
cana-3843	147	25	accuracy	accuracy	NOUN
cana-3843	147	26	of	of	ADP
cana-3843	147	27	the	the	DET
cana-3843	147	28	model	model	NOUN
cana-3843	147	29	.	.	PUNCT
cana-3843	148	1	this	this	DET
cana-3843	148	2	phase	phase	NOUN
cana-3843	148	3	includes	include	VERB
cana-3843	148	4	several	several	ADJ
cana-3843	148	5	key	key	ADJ
cana-3843	148	6	processes	process	NOUN
cana-3843	148	7	.	.	PUNCT
cana-3843	149	1	the	the	DET
cana-3843	149	2	initial	initial	ADJ
cana-3843	149	3	process	process	NOUN
cana-3843	149	4	involves	involve	VERB
cana-3843	149	5	handling	handle	VERB
cana-3843	149	6	missing	miss	VERB
cana-3843	149	7	data	datum	NOUN
cana-3843	149	8	and	and	CCONJ
cana-3843	149	9	null	null	ADJ
cana-3843	149	10	values	value	NOUN
cana-3843	149	11	present	present	ADJ
cana-3843	149	12	in	in	ADP
cana-3843	149	13	the	the	DET
cana-3843	149	14	given	give	VERB
cana-3843	149	15	data	datum	NOUN
cana-3843	149	16	.	.	PUNCT
cana-3843	150	1	replace	replace	VERB
cana-3843	150	2	each	each	DET
cana-3843	150	3	missing	miss	VERB
cana-3843	150	4	value	value	NOUN
cana-3843	150	5	with	with	ADP
cana-3843	150	6	the	the	DET
cana-3843	150	7	mean	mean	NOUN
cana-3843	150	8	of	of	ADP
cana-3843	150	9	the	the	DET
cana-3843	150	10	sample	sample	NOUN
cana-3843	150	11	values	value	NOUN
cana-3843	150	12	for	for	ADP
cana-3843	150	13	the	the	DET
cana-3843	150	14	respective	respective	ADJ
cana-3843	150	15	gene	gene	NOUN
cana-3843	150	16	.	.	PUNCT
cana-3843	151	1	in	in	ADP
cana-3843	151	2	the	the	DET
cana-3843	151	3	next	next	ADJ
cana-3843	151	4	process	process	NOUN
cana-3843	151	5	,	,	PUNCT
cana-3843	151	6	the	the	DET
cana-3843	151	7	label	label	NOUN
cana-3843	151	8	encoding	encoding	NOUN
cana-3843	151	9	technique	technique	NOUN
cana-3843	151	10	is	be	AUX
cana-3843	151	11	applied	apply	VERB
cana-3843	151	12	to	to	PART
cana-3843	151	13	convert	convert	VERB
cana-3843	151	14	the	the	DET
cana-3843	151	15	levels	level	NOUN
cana-3843	151	16	of	of	ADP
cana-3843	151	17	the	the	DET
cana-3843	151	18	categorical	categorical	ADJ
cana-3843	151	19	features	feature	NOUN
cana-3843	151	20	into	into	ADP
cana-3843	151	21	numeric	numeric	ADJ
cana-3843	151	22	values	value	NOUN
cana-3843	151	23	.	.	PUNCT
cana-3843	152	1	in	in	ADP
cana-3843	152	2	this	this	DET
cana-3843	152	3	study	study	NOUN
cana-3843	152	4	,	,	PUNCT
cana-3843	152	5	the	the	DET
cana-3843	152	6	class	class	NOUN
cana-3843	152	7	labels	label	VERB
cana-3843	152	8	all	all	PRON
cana-3843	152	9	and	and	CCONJ
cana-3843	152	10	aml	aml	PROPN
cana-3843	152	11	are	be	AUX
cana-3843	152	12	encoded	encode	VERB
cana-3843	152	13	as	as	ADP
cana-3843	152	14	0	0	NUM
cana-3843	152	15	and	and	CCONJ
cana-3843	152	16	1	1	NUM
cana-3843	152	17	respectively	respectively	ADV
cana-3843	152	18	.	.	PUNCT
cana-3843	153	1	finally	finally	ADV
cana-3843	153	2	,	,	PUNCT
cana-3843	153	3	the	the	DET
cana-3843	153	4	feature	feature	NOUN
cana-3843	153	5	scaling	scale	VERB
cana-3843	153	6	process	process	NOUN
cana-3843	153	7	is	be	AUX
cana-3843	153	8	performed	perform	VERB
cana-3843	153	9	,	,	PUNCT
cana-3843	153	10	through	through	ADP
cana-3843	153	11	the	the	DET
cana-3843	153	12	min	min	PROPN
cana-3843	153	13	-	-	ADJ
cana-3843	153	14	max	max	PROPN
cana-3843	153	15	normalization	normalization	NOUN
cana-3843	153	16	technique	technique	NOUN
cana-3843	153	17	,	,	PUNCT
cana-3843	153	18	which	which	PRON
cana-3843	153	19	maps	map	VERB
cana-3843	153	20	the	the	DET
cana-3843	153	21	values	value	NOUN
cana-3843	153	22	to	to	ADP
cana-3843	153	23	a	a	DET
cana-3843	153	24	range	range	NOUN
cana-3843	153	25	[	[	X
cana-3843	153	26	0,1	0,1	NUM
cana-3843	153	27	]	]	PUNCT
cana-3843	153	28	.	.	PUNCT
cana-3843	154	1	the	the	DET
cana-3843	154	2	highest	high	ADJ
cana-3843	154	3	feature	feature	NOUN
cana-3843	154	4	value	value	NOUN
cana-3843	154	5	in	in	ADP
cana-3843	154	6	the	the	DET
cana-3843	154	7	dataset	dataset	NOUN
cana-3843	154	8	is	be	AUX
cana-3843	154	9	transformed	transform	VERB
cana-3843	154	10	to	to	ADP
cana-3843	154	11	1	1	NUM
cana-3843	154	12	,	,	PUNCT
cana-3843	154	13	the	the	DET
cana-3843	154	14	lowest	low	ADJ
cana-3843	154	15	value	value	NOUN
cana-3843	154	16	is	be	AUX
cana-3843	154	17	changed	change	VERB
cana-3843	154	18	to	to	ADP
cana-3843	154	19	0	0	NUM
cana-3843	154	20	,	,	PUNCT
cana-3843	154	21	and	and	CCONJ
cana-3843	154	22	the	the	DET
cana-3843	154	23	remaining	remain	VERB
cana-3843	154	24	values	value	NOUN
cana-3843	154	25	are	be	AUX
cana-3843	154	26	rescaled	rescale	VERB
cana-3843	154	27	to	to	PART
cana-3843	154	28	fall	fall	VERB
cana-3843	154	29	within	within	ADP
cana-3843	154	30	the	the	DET
cana-3843	154	31	range	range	NOUN
cana-3843	154	32	of	of	ADP
cana-3843	154	33	0	0	NUM
cana-3843	154	34	to	to	PART
cana-3843	154	35	1	1	NUM
cana-3843	154	36	.	.	PUNCT
cana-3843	155	1	the	the	DET
cana-3843	155	2	next	next	ADJ
cana-3843	155	3	process	process	NOUN
cana-3843	155	4	is	be	AUX
cana-3843	155	5	to	to	PART
cana-3843	155	6	evaluate	evaluate	VERB
cana-3843	155	7	the	the	DET
cana-3843	155	8	multicollinearity	multicollinearity	NOUN
cana-3843	155	9	between	between	ADP
cana-3843	155	10	features	feature	NOUN
cana-3843	155	11	.	.	PUNCT
cana-3843	156	1	the	the	DET
cana-3843	156	2	correlation	correlation	NOUN
cana-3843	156	3	matrix	matrix	NOUN
cana-3843	156	4	evaluates	evaluate	VERB
cana-3843	156	5	the	the	DET
cana-3843	156	6	dependency	dependency	NOUN
cana-3843	156	7	between	between	ADP
cana-3843	156	8	features	feature	NOUN
cana-3843	156	9	,	,	PUNCT
cana-3843	156	10	identifies	identify	VERB
cana-3843	156	11	the	the	DET
cana-3843	156	12	low	low	ADJ
cana-3843	156	13	inter	inter	ADJ
cana-3843	156	14	-	-	ADJ
cana-3843	156	15	correlated	correlate	VERB
cana-3843	156	16	features	feature	NOUN
cana-3843	156	17	,	,	PUNCT
cana-3843	156	18	and	and	CCONJ
cana-3843	156	19	eliminates	eliminate	VERB
cana-3843	156	20	redundant	redundant	ADJ
cana-3843	156	21	genes	gene	NOUN
cana-3843	156	22	[	[	X
cana-3843	156	23	25	25	NUM
cana-3843	156	24	]	]	PUNCT
cana-3843	156	25	.	.	PUNCT
cana-3843	157	1	the	the	DET
cana-3843	157	2	correlation	correlation	NOUN
cana-3843	157	3	matrix	matrix	NOUN
cana-3843	157	4	is	be	AUX
cana-3843	157	5	calculated	calculate	VERB
cana-3843	157	6	using	use	VERB
cana-3843	157	7	the	the	DET
cana-3843	157	8	formula	formula	NOUN
cana-3843	157	9	rx	rx	NOUN
cana-3843	157	10	,	,	PUNCT
cana-3843	157	11	y	y	NOUN
cana-3843	157	12	=	=	SYM
cana-3843	157	13	co_variance(x	co_variance(x	PROPN
cana-3843	157	14	,	,	PUNCT
cana-3843	157	15	y	y	NOUN
cana-3843	157	16	)	)	PUNCT
cana-3843	157	17	σxσy	σxσy	NOUN
cana-3843	157	18	-------(1	-------(1	PROPN
cana-3843	157	19	)	)	PUNCT
cana-3843	157	20	co_variance(x	co_variance(x	PROPN
cana-3843	157	21	,	,	PUNCT
cana-3843	157	22	y	y	NOUN
cana-3843	157	23	)	)	PUNCT
cana-3843	157	24	=	=	SYM
cana-3843	157	25	1	1	NUM
cana-3843	157	26	(	(	PUNCT
cana-3843	157	27	n-1	n-1	NUM
cana-3843	157	28	)	)	PUNCT
cana-3843	157	29	∑	∑	PUNCT
cana-3843	157	30	(	(	PUNCT
cana-3843	157	31	xi	xi	PROPN
cana-3843	157	32	-	-	PUNCT
cana-3843	157	33	μx	μx	NOUN
cana-3843	157	34	)	)	PUNCT
cana-3843	157	35	(	(	PUNCT
cana-3843	157	36	yi	yi	PROPN
cana-3843	157	37	-	-	PUNCT
cana-3843	157	38	μy	μy	PROPN
cana-3843	157	39	)	)	PUNCT
cana-3843	157	40	n	n	CCONJ
cana-3843	157	41	i=1	i=1	PROPN
cana-3843	157	42	--------(2	--------(2	INTJ
cana-3843	157	43	)	)	PUNCT
cana-3843	157	44	where	where	SCONJ
cana-3843	157	45	rx	rx	VERB
cana-3843	157	46	,	,	PUNCT
cana-3843	157	47	y	y	PROPN
cana-3843	157	48	represents	represent	VERB
cana-3843	157	49	the	the	DET
cana-3843	157	50	pearson	pearson	PROPN
cana-3843	157	51	correlation	correlation	NOUN
cana-3843	157	52	coefficient	coefficient	NOUN
cana-3843	157	53	and	and	CCONJ
cana-3843	157	54	σx	σx	NOUN
cana-3843	157	55	,	,	PUNCT
cana-3843	157	56	σy	σy	PRON
cana-3843	157	57	represent	represent	VERB
cana-3843	157	58	the	the	DET
cana-3843	157	59	standard	standard	ADJ
cana-3843	157	60	deviation	deviation	NOUN
cana-3843	157	61	of	of	ADP
cana-3843	157	62	x	x	PUNCT
cana-3843	157	63	and	and	CCONJ
cana-3843	157	64	y	y	PROPN
cana-3843	157	65	respectively.μ	respectively.μ	PROPN
cana-3843	158	1	x	x	PUNCT
cana-3843	158	2	and	and	CCONJ
cana-3843	158	3	μ	μ	PROPN
cana-3843	158	4	y	y	PROPN
cana-3843	158	5	denote	denote	VERB
cana-3843	158	6	the	the	DET
cana-3843	158	7	means	mean	NOUN
cana-3843	158	8	of	of	ADP
cana-3843	158	9	x	x	X
cana-3843	158	10	and	and	CCONJ
cana-3843	158	11	y	y	PROPN
cana-3843	158	12	,	,	PUNCT
cana-3843	158	13	and	and	CCONJ
cana-3843	158	14	n	n	CCONJ
cana-3843	158	15	indicates	indicate	VERB
cana-3843	158	16	the	the	DET
cana-3843	158	17	number	number	NOUN
cana-3843	158	18	of	of	ADP
cana-3843	158	19	data	datum	NOUN
cana-3843	158	20	points	point	NOUN
cana-3843	158	21	.	.	PUNCT
cana-3843	159	1	the	the	DET
cana-3843	159	2	next	next	ADJ
cana-3843	159	3	phase	phase	NOUN
cana-3843	159	4	involves	involve	VERB
cana-3843	159	5	selecting	select	VERB
cana-3843	159	6	an	an	DET
cana-3843	159	7	optimal	optimal	ADJ
cana-3843	159	8	gene	gene	NOUN
cana-3843	159	9	subset	subset	VERB
cana-3843	159	10	for	for	ADP
cana-3843	159	11	predicting	predict	VERB
cana-3843	159	12	the	the	DET
cana-3843	159	13	disease	disease	NOUN
cana-3843	159	14	.	.	PUNCT
cana-3843	160	1	in	in	ADP
cana-3843	160	2	this	this	DET
cana-3843	160	3	approach	approach	NOUN
cana-3843	160	4	,	,	PUNCT
cana-3843	160	5	a	a	DET
cana-3843	160	6	genetic	genetic	ADJ
cana-3843	160	7	optimization	optimization	NOUN
cana-3843	160	8	algorithm	algorithm	NOUN
cana-3843	160	9	,	,	PUNCT
cana-3843	160	10	integrated	integrate	VERB
cana-3843	160	11	with	with	ADP
cana-3843	160	12	the	the	DET
cana-3843	160	13	snr	snr	NOUN
cana-3843	160	14	method	method	NOUN
cana-3843	160	15	is	be	AUX
cana-3843	160	16	utilized	utilize	VERB
cana-3843	160	17	to	to	PART
cana-3843	160	18	select	select	VERB
cana-3843	160	19	an	an	DET
cana-3843	160	20	important	important	ADJ
cana-3843	160	21	subset	subset	NOUN
cana-3843	160	22	of	of	ADP
cana-3843	160	23	biomarker	biomarker	NOUN
cana-3843	160	24	genes	gene	NOUN
cana-3843	160	25	.	.	PUNCT
cana-3843	161	1	the	the	DET
cana-3843	161	2	fitness	fitness	NOUN
cana-3843	161	3	function	function	NOUN
cana-3843	161	4	used	use	VERB
cana-3843	161	5	in	in	ADP
cana-3843	161	6	this	this	DET
cana-3843	161	7	process	process	NOUN
cana-3843	161	8	is	be	AUX
cana-3843	161	9	calculated	calculate	VERB
cana-3843	161	10	using	use	VERB
cana-3843	161	11	the	the	DET
cana-3843	161	12	formula	formula	NOUN
cana-3843	161	13	snr(f	snr(f	NOUN
cana-3843	161	14	)	)	PUNCT
cana-3843	162	1	=	=	PUNCT
cana-3843	163	1	|	|	ADV
cana-3843	163	2	1	1	NUM
cana-3843	163	3	n1	n1	NOUN
cana-3843	163	4	∑	∑	PUNCT
cana-3843	163	5	xi	xi	PROPN
cana-3843	163	6	1	1	NUM
cana-3843	163	7	n2	n2	PROPN
cana-3843	163	8	∑	∑	PUNCT
cana-3843	163	9	xii∈c2i∈c1	xii∈c2i∈c1	PROPN
cana-3843	163	10	|	|	ADV
cana-3843	163	11	√	√	PROPN
cana-3843	163	12	1	1	NUM
cana-3843	163	13	n1	n1	NOUN
cana-3843	163	14	∑	∑	PUNCT
cana-3843	163	15	(	(	PUNCT
cana-3843	163	16	xi	xi	ADP
cana-3843	163	17	μ1	μ1	PROPN
cana-3843	163	18	)	)	PUNCT
cana-3843	163	19	2	2	NUM
cana-3843	163	20	+	+	SYM
cana-3843	163	21	1	1	NUM
cana-3843	163	22	n2	n2	NOUN
cana-3843	163	23	∑	∑	PUNCT
cana-3843	163	24	(	(	PUNCT
cana-3843	163	25	xi	xi	PROPN
cana-3843	163	26	μ2	μ2	NOUN
cana-3843	163	27	)	)	PUNCT
cana-3843	163	28	2	2	NUM
cana-3843	163	29	iϵc2i∈c1	iϵc2i∈c1	PROPN
cana-3843	163	30	-------(3	-------(3	PROPN
cana-3843	163	31	)	)	PUNCT
cana-3843	163	32	where	where	SCONJ
cana-3843	163	33	μ	μ	PROPN
cana-3843	163	34	1	1	NUM
cana-3843	163	35	and	and	CCONJ
cana-3843	163	36	μ	μ	PROPN
cana-3843	163	37	2	2	NUM
cana-3843	163	38	are	be	AUX
cana-3843	163	39	the	the	DET
cana-3843	163	40	means	mean	NOUN
cana-3843	163	41	of	of	ADP
cana-3843	163	42	the	the	DET
cana-3843	163	43	class	class	NOUN
cana-3843	163	44	all	all	PRON
cana-3843	163	45	and	and	CCONJ
cana-3843	163	46	aml	aml	NOUN
cana-3843	163	47	respectively	respectively	ADV
cana-3843	163	48	.	.	PUNCT
cana-3843	164	1	in	in	ADP
cana-3843	164	2	this	this	DET
cana-3843	164	3	process	process	NOUN
cana-3843	164	4	,	,	PUNCT
cana-3843	164	5	the	the	DET
cana-3843	164	6	population	population	NOUN
cana-3843	164	7	p	p	NOUN
cana-3843	164	8	is	be	AUX
cana-3843	164	9	initialized	initialize	VERB
cana-3843	164	10	by	by	ADP
cana-3843	164	11	generating	generate	VERB
cana-3843	164	12	n	n	PRON
cana-3843	164	13	chromosomes	chromosome	NOUN
cana-3843	164	14	with	with	ADP
cana-3843	164	15	random	random	ADJ
cana-3843	164	16	values	value	NOUN
cana-3843	164	17	between	between	ADP
cana-3843	164	18	0	0	NUM
cana-3843	164	19	and	and	CCONJ
cana-3843	164	20	1	1	NUM
cana-3843	164	21	.	.	X
cana-3843	165	1	snr	snr	PROPN
cana-3843	165	2	rank	rank	NOUN
cana-3843	165	3	method	method	NOUN
cana-3843	165	4	is	be	AUX
cana-3843	165	5	applied	apply	VERB
cana-3843	165	6	to	to	PART
cana-3843	165	7	evaluate	evaluate	VERB
cana-3843	165	8	the	the	DET
cana-3843	165	9	fitness	fitness	NOUN
cana-3843	165	10	value	value	NOUN
cana-3843	165	11	of	of	ADP
cana-3843	165	12	individual	individual	ADJ
cana-3843	165	13	chromosome	chromosome	NOUN
cana-3843	165	14	and	and	CCONJ
cana-3843	165	15	enable	enable	VERB
cana-3843	165	16	the	the	DET
cana-3843	165	17	classification	classification	NOUN
cana-3843	165	18	of	of	ADP
cana-3843	165	19	microarray	microarray	NOUN
cana-3843	165	20	data	datum	NOUN
cana-3843	166	1	[	[	X
cana-3843	166	2	26	26	NUM
cana-3843	166	3	]	]	PUNCT
cana-3843	166	4	.	.	PUNCT
cana-3843	167	1	the	the	DET
cana-3843	167	2	roulette	roulette	NOUN
cana-3843	167	3	wheel	wheel	NOUN
cana-3843	167	4	method	method	NOUN
cana-3843	167	5	is	be	AUX
cana-3843	167	6	applied	apply	VERB
cana-3843	167	7	as	as	ADP
cana-3843	167	8	a	a	DET
cana-3843	167	9	selection	selection	NOUN
cana-3843	167	10	communications	communication	NOUN
cana-3843	167	11	on	on	ADP
cana-3843	167	12	applied	apply	VERB
cana-3843	167	13	nonlinear	nonlinear	ADJ
cana-3843	167	14	analysis	analysis	NOUN
cana-3843	167	15	issn	issn	NOUN
cana-3843	167	16	:	:	PUNCT
cana-3843	167	17	1074	1074	NUM
cana-3843	167	18	-	-	PUNCT
cana-3843	167	19	133x	133x	NUM
cana-3843	167	20	vol	vol	NOUN
cana-3843	167	21	32	32	NUM
cana-3843	167	22	no	no	NOUN
cana-3843	167	23	.	.	PUNCT
cana-3843	168	1	9s	9s	NUM
cana-3843	168	2	(	(	PUNCT
cana-3843	168	3	2025	2025	NUM
cana-3843	168	4	)	)	PUNCT
cana-3843	168	5	126	126	NUM
cana-3843	168	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	168	7	operation	operation	NOUN
cana-3843	168	8	to	to	PART
cana-3843	168	9	select	select	VERB
cana-3843	168	10	two	two	NUM
cana-3843	168	11	parent	parent	NOUN
cana-3843	168	12	chromosomes	chromosome	NOUN
cana-3843	168	13	with	with	ADP
cana-3843	168	14	higher	high	ADJ
cana-3843	168	15	fitness	fitness	NOUN
cana-3843	168	16	values	value	NOUN
cana-3843	168	17	.	.	PUNCT
cana-3843	169	1	after	after	ADP
cana-3843	169	2	selection	selection	NOUN
cana-3843	169	3	,	,	PUNCT
cana-3843	169	4	the	the	DET
cana-3843	169	5	selected	select	VERB
cana-3843	169	6	parent	parent	NOUN
cana-3843	169	7	chromosomes	chromosome	NOUN
cana-3843	169	8	are	be	AUX
cana-3843	169	9	applied	apply	VERB
cana-3843	169	10	to	to	ADP
cana-3843	169	11	the	the	DET
cana-3843	169	12	crossover	crossover	NOUN
cana-3843	169	13	operation	operation	NOUN
cana-3843	169	14	,	,	PUNCT
cana-3843	169	15	with	with	ADP
cana-3843	169	16	a	a	DET
cana-3843	169	17	specified	specify	VERB
cana-3843	169	18	crossover	crossover	NOUN
cana-3843	169	19	rate	rate	NOUN
cana-3843	169	20	to	to	PART
cana-3843	169	21	produce	produce	VERB
cana-3843	169	22	the	the	DET
cana-3843	169	23	offspring	offspring	NOUN
cana-3843	169	24	.	.	PUNCT
cana-3843	170	1	the	the	DET
cana-3843	170	2	next	next	ADJ
cana-3843	170	3	process	process	NOUN
cana-3843	170	4	executes	execute	VERB
cana-3843	170	5	the	the	DET
cana-3843	170	6	mutation	mutation	NOUN
cana-3843	170	7	operator	operator	NOUN
cana-3843	170	8	where	where	SCONJ
cana-3843	170	9	specific	specific	ADJ
cana-3843	170	10	genes	gene	NOUN
cana-3843	170	11	within	within	ADP
cana-3843	170	12	the	the	DET
cana-3843	170	13	offspring	offspring	NOUN
cana-3843	170	14	are	be	AUX
cana-3843	170	15	randomly	randomly	ADV
cana-3843	170	16	changed	change	VERB
cana-3843	170	17	.	.	PUNCT
cana-3843	171	1	the	the	DET
cana-3843	171	2	fitness	fitness	NOUN
cana-3843	171	3	of	of	ADP
cana-3843	171	4	the	the	DET
cana-3843	171	5	resulting	result	VERB
cana-3843	171	6	offspring	offspring	NOUN
cana-3843	171	7	is	be	AUX
cana-3843	171	8	evaluated	evaluate	VERB
cana-3843	171	9	,	,	PUNCT
cana-3843	171	10	and	and	CCONJ
cana-3843	171	11	represents	represent	VERB
cana-3843	171	12	better	well	ADJ
cana-3843	171	13	fitness	fitness	NOUN
cana-3843	171	14	than	than	ADP
cana-3843	171	15	the	the	DET
cana-3843	171	16	parent	parent	NOUN
cana-3843	171	17	,	,	PUNCT
cana-3843	171	18	the	the	DET
cana-3843	171	19	offspring	offspring	NOUN
cana-3843	171	20	replaces	replace	VERB
cana-3843	171	21	the	the	DET
cana-3843	171	22	parent	parent	NOUN
cana-3843	171	23	.	.	PUNCT
cana-3843	172	1	the	the	DET
cana-3843	172	2	procedure	procedure	NOUN
cana-3843	172	3	continues	continue	VERB
cana-3843	172	4	until	until	SCONJ
cana-3843	172	5	a	a	DET
cana-3843	172	6	specified	specify	VERB
cana-3843	172	7	termination	termination	NOUN
cana-3843	172	8	condition	condition	NOUN
cana-3843	172	9	is	be	AUX
cana-3843	172	10	satisfied	satisfied	ADJ
cana-3843	172	11	,	,	PUNCT
cana-3843	172	12	resulting	result	VERB
cana-3843	172	13	in	in	ADP
cana-3843	172	14	the	the	DET
cana-3843	172	15	selection	selection	NOUN
cana-3843	172	16	of	of	ADP
cana-3843	172	17	the	the	DET
cana-3843	172	18	most	most	ADV
cana-3843	172	19	optimal	optimal	ADJ
cana-3843	172	20	chromosome	chromosome	NOUN
cana-3843	172	21	as	as	ADP
cana-3843	172	22	the	the	DET
cana-3843	172	23	final	final	ADJ
cana-3843	172	24	solution	solution	NOUN
cana-3843	172	25	.	.	PUNCT
cana-3843	173	1	this	this	DET
cana-3843	173	2	technique	technique	NOUN
cana-3843	173	3	reduces	reduce	VERB
cana-3843	173	4	the	the	DET
cana-3843	173	5	number	number	NOUN
cana-3843	173	6	of	of	ADP
cana-3843	173	7	genes	gene	NOUN
cana-3843	173	8	by	by	ADP
cana-3843	173	9	eliminating	eliminate	VERB
cana-3843	173	10	irrelevant	irrelevant	ADJ
cana-3843	173	11	and	and	CCONJ
cana-3843	173	12	redundant	redundant	ADJ
cana-3843	173	13	genes	gene	NOUN
cana-3843	173	14	from	from	ADP
cana-3843	173	15	the	the	DET
cana-3843	173	16	dataset	dataset	NOUN
cana-3843	173	17	.	.	PUNCT
cana-3843	174	1	this	this	DET
cana-3843	174	2	stage	stage	NOUN
cana-3843	174	3	helps	helps	AUX
cana-3843	174	4	identify	identify	VERB
cana-3843	174	5	the	the	DET
cana-3843	174	6	optimal	optimal	ADJ
cana-3843	174	7	set	set	NOUN
cana-3843	174	8	of	of	ADP
cana-3843	174	9	genes	gene	NOUN
cana-3843	174	10	connected	connect	VERB
cana-3843	174	11	to	to	ADP
cana-3843	174	12	cancer	cancer	NOUN
cana-3843	174	13	disease	disease	NOUN
cana-3843	174	14	in	in	ADP
cana-3843	174	15	the	the	DET
cana-3843	174	16	dataset	dataset	NOUN
cana-3843	174	17	.	.	PUNCT
cana-3843	175	1	to	to	PART
cana-3843	175	2	predict	predict	VERB
cana-3843	175	3	the	the	DET
cana-3843	175	4	presence	presence	NOUN
cana-3843	175	5	of	of	ADP
cana-3843	175	6	all	all	DET
cana-3843	175	7	and	and	CCONJ
cana-3843	175	8	aml	aml	NOUN
cana-3843	175	9	genes	gene	NOUN
cana-3843	175	10	,	,	PUNCT
cana-3843	175	11	the	the	DET
cana-3843	175	12	selected	select	VERB
cana-3843	175	13	341	341	NUM
cana-3843	175	14	optimal	optimal	ADJ
cana-3843	175	15	genes	gene	NOUN
cana-3843	175	16	are	be	AUX
cana-3843	175	17	divided	divide	VERB
cana-3843	175	18	into	into	ADP
cana-3843	175	19	training	training	NOUN
cana-3843	175	20	and	and	CCONJ
cana-3843	175	21	testing	testing	NOUN
cana-3843	175	22	sets	set	NOUN
cana-3843	175	23	.	.	PUNCT
cana-3843	176	1	the	the	DET
cana-3843	176	2	training	training	NOUN
cana-3843	176	3	data	datum	NOUN
cana-3843	176	4	is	be	AUX
cana-3843	176	5	applied	apply	VERB
cana-3843	176	6	to	to	PART
cana-3843	176	7	train	train	VERB
cana-3843	176	8	the	the	DET
cana-3843	176	9	long	long	ADJ
cana-3843	176	10	short	short	ADJ
cana-3843	176	11	term	term	NOUN
cana-3843	176	12	memory	memory	NOUN
cana-3843	176	13	(	(	PUNCT
cana-3843	176	14	lstm	lstm	NOUN
cana-3843	176	15	)	)	PUNCT
cana-3843	176	16	classifier	classifier	NOUN
cana-3843	176	17	model	model	NOUN
cana-3843	176	18	.	.	PUNCT
cana-3843	177	1	in	in	ADP
cana-3843	177	2	this	this	DET
cana-3843	177	3	process	process	NOUN
cana-3843	177	4	,	,	PUNCT
cana-3843	177	5	the	the	DET
cana-3843	177	6	network	network	NOUN
cana-3843	177	7	is	be	AUX
cana-3843	177	8	structured	structure	VERB
cana-3843	177	9	with	with	ADP
cana-3843	177	10	six	six	NUM
cana-3843	177	11	hidden	hidden	ADJ
cana-3843	177	12	layers	layer	NOUN
cana-3843	177	13	,	,	PUNCT
cana-3843	177	14	each	each	PRON
cana-3843	177	15	containing	contain	VERB
cana-3843	177	16	50	50	NUM
cana-3843	177	17	neurons	neuron	NOUN
cana-3843	177	18	.	.	PUNCT
cana-3843	178	1	the	the	DET
cana-3843	178	2	sparse	sparse	ADJ
cana-3843	178	3	categorical	categorical	ADJ
cana-3843	178	4	cross	cross	ADJ
cana-3843	178	5	-	-	ADJ
cana-3843	178	6	entropy	entropy	ADJ
cana-3843	178	7	loss	loss	NOUN
cana-3843	178	8	function	function	NOUN
cana-3843	178	9	is	be	AUX
cana-3843	178	10	applied	apply	VERB
cana-3843	178	11	to	to	PART
cana-3843	178	12	determine	determine	VERB
cana-3843	178	13	the	the	DET
cana-3843	178	14	loss	loss	NOUN
cana-3843	178	15	value	value	NOUN
cana-3843	178	16	.	.	PUNCT
cana-3843	179	1	in	in	ADP
cana-3843	179	2	this	this	DET
cana-3843	179	3	model	model	NOUN
cana-3843	179	4	,	,	PUNCT
cana-3843	179	5	different	different	ADJ
cana-3843	179	6	optimizers	optimizer	NOUN
cana-3843	179	7	including	include	VERB
cana-3843	179	8	adam	adam	PROPN
cana-3843	179	9	,	,	PUNCT
cana-3843	179	10	adagrad	adagrad	ADJ
cana-3843	179	11	,	,	PUNCT
cana-3843	179	12	rmsprop	rmsprop	NOUN
cana-3843	179	13	and	and	CCONJ
cana-3843	179	14	sgd	sgd	PROPN
cana-3843	179	15	are	be	AUX
cana-3843	179	16	tested	test	VERB
cana-3843	179	17	to	to	PART
cana-3843	179	18	evaluate	evaluate	VERB
cana-3843	179	19	the	the	DET
cana-3843	179	20	efficiency	efficiency	NOUN
cana-3843	179	21	of	of	ADP
cana-3843	179	22	the	the	DET
cana-3843	179	23	model	model	NOUN
cana-3843	179	24	.	.	PUNCT
cana-3843	180	1	finally	finally	ADV
cana-3843	180	2	,	,	PUNCT
cana-3843	180	3	an	an	DET
cana-3843	180	4	evaluation	evaluation	NOUN
cana-3843	180	5	of	of	ADP
cana-3843	180	6	the	the	DET
cana-3843	180	7	metrics	metric	NOUN
cana-3843	180	8	for	for	ADP
cana-3843	180	9	different	different	ADJ
cana-3843	180	10	optimizers	optimizer	NOUN
cana-3843	180	11	is	be	AUX
cana-3843	180	12	performed	perform	VERB
cana-3843	180	13	.	.	PUNCT
cana-3843	181	1	5	5	X
cana-3843	181	2	.	.	X
cana-3843	181	3	experimental	experimental	ADJ
cana-3843	181	4	analysis	analysis	NOUN
cana-3843	181	5	the	the	DET
cana-3843	181	6	research	research	NOUN
cana-3843	181	7	methodology	methodology	NOUN
cana-3843	181	8	was	be	AUX
cana-3843	181	9	developed	develop	VERB
cana-3843	181	10	and	and	CCONJ
cana-3843	181	11	implemented	implement	VERB
cana-3843	181	12	in	in	ADP
cana-3843	181	13	python	python	NOUN
cana-3843	181	14	using	use	VERB
cana-3843	181	15	google	google	PROPN
cana-3843	181	16	colob	colob	ADJ
cana-3843	181	17	notebook	notebook	NOUN
cana-3843	181	18	,	,	PUNCT
cana-3843	181	19	with	with	ADP
cana-3843	181	20	the	the	DET
cana-3843	181	21	deap	deap	ADJ
cana-3843	181	22	package	package	NOUN
cana-3843	181	23	version	version	NOUN
cana-3843	181	24	1.4.1	1.4.1	NUM
cana-3843	181	25	configured	configure	VERB
cana-3843	181	26	for	for	ADP
cana-3843	181	27	the	the	DET
cana-3843	181	28	genetic	genetic	ADJ
cana-3843	181	29	optimization	optimization	NOUN
cana-3843	181	30	technique	technique	NOUN
cana-3843	181	31	.	.	PUNCT
cana-3843	182	1	table-2	table-2	NUM
cana-3843	182	2	presents	present	VERB
cana-3843	182	3	the	the	DET
cana-3843	182	4	parameters	parameter	NOUN
cana-3843	182	5	used	use	VERB
cana-3843	182	6	to	to	PART
cana-3843	182	7	identify	identify	VERB
cana-3843	182	8	an	an	DET
cana-3843	182	9	optimal	optimal	ADJ
cana-3843	182	10	set	set	NOUN
cana-3843	182	11	of	of	ADP
cana-3843	182	12	features	feature	NOUN
cana-3843	182	13	.	.	PUNCT
cana-3843	183	1	the	the	DET
cana-3843	183	2	keras	keras	PROPN
cana-3843	183	3	and	and	CCONJ
cana-3843	183	4	tensorflow	tensorflow	PROPN
cana-3843	183	5	api	api	NOUN
cana-3843	183	6	library	library	NOUN
cana-3843	183	7	functions	function	NOUN
cana-3843	183	8	were	be	AUX
cana-3843	183	9	utilized	utilize	VERB
cana-3843	183	10	to	to	PART
cana-3843	183	11	develop	develop	VERB
cana-3843	183	12	the	the	DET
cana-3843	183	13	lstm	lstm	PROPN
cana-3843	183	14	model	model	NOUN
cana-3843	183	15	.	.	PUNCT
cana-3843	184	1	the	the	DET
cana-3843	184	2	research	research	NOUN
cana-3843	184	3	methodology	methodology	NOUN
cana-3843	184	4	was	be	AUX
cana-3843	184	5	evaluated	evaluate	VERB
cana-3843	184	6	using	use	VERB
cana-3843	184	7	the	the	DET
cana-3843	184	8	leukemia	leukemia	NOUN
cana-3843	184	9	cancer	cancer	NOUN
cana-3843	184	10	gene	gene	NOUN
cana-3843	184	11	dataset	dataset	NOUN
cana-3843	184	12	,	,	PUNCT
cana-3843	184	13	which	which	PRON
cana-3843	184	14	consists	consist	VERB
cana-3843	184	15	of	of	ADP
cana-3843	184	16	7129	7129	NUM
cana-3843	184	17	genes	gene	NOUN
cana-3843	184	18	and	and	CCONJ
cana-3843	184	19	72	72	NUM
cana-3843	184	20	samples	sample	NOUN
cana-3843	184	21	.	.	PUNCT
cana-3843	185	1	this	this	DET
cana-3843	185	2	section	section	NOUN
cana-3843	185	3	presents	present	VERB
cana-3843	185	4	multiple	multiple	ADJ
cana-3843	185	5	experiments	experiment	NOUN
cana-3843	185	6	,	,	PUNCT
cana-3843	185	7	and	and	CCONJ
cana-3843	185	8	the	the	DET
cana-3843	185	9	network	network	NOUN
cana-3843	185	10	was	be	AUX
cana-3843	185	11	trained	train	VERB
cana-3843	185	12	on	on	ADP
cana-3843	185	13	70	70	NUM
cana-3843	185	14	percent	percent	NOUN
cana-3843	185	15	of	of	ADP
cana-3843	185	16	the	the	DET
cana-3843	185	17	data	datum	NOUN
cana-3843	185	18	and	and	CCONJ
cana-3843	185	19	validated	validate	VERB
cana-3843	185	20	on	on	ADP
cana-3843	185	21	the	the	DET
cana-3843	185	22	remaining	remain	VERB
cana-3843	185	23	30	30	NUM
cana-3843	185	24	percent	percent	NOUN
cana-3843	185	25	of	of	ADP
cana-3843	185	26	the	the	DET
cana-3843	185	27	data	datum	NOUN
cana-3843	185	28	.	.	PUNCT
cana-3843	186	1	table-2	table-2	NUM
cana-3843	187	1	parameter	parameter	NOUN
cana-3843	187	2	settings	setting	NOUN
cana-3843	187	3	for	for	ADP
cana-3843	187	4	genetic	genetic	ADJ
cana-3843	187	5	optimization	optimization	NOUN
cana-3843	187	6	technique	technique	NOUN
cana-3843	187	7	genetic	genetic	ADJ
cana-3843	187	8	optimization	optimization	NOUN
cana-3843	187	9	technique	technique	NOUN
cana-3843	187	10	parameter	parameter	NOUN
cana-3843	187	11	values	value	NOUN
cana-3843	187	12	selection	selection	NOUN
cana-3843	187	13	method	method	NOUN
cana-3843	187	14	roulette	roulette	NOUN
cana-3843	187	15	wheel	wheel	NOUN
cana-3843	187	16	selection	selection	NOUN
cana-3843	187	17	crossover	crossover	ADP
cana-3843	187	18	type	type	NOUN
cana-3843	187	19	single	single	ADJ
cana-3843	187	20	point	point	NOUN
cana-3843	187	21	crossover	crossover	ADP
cana-3843	187	22	mutation	mutation	NOUN
cana-3843	187	23	rate	rate	NOUN
cana-3843	187	24	0.5	0.5	NUM
cana-3843	187	25	number	number	NOUN
cana-3843	187	26	of	of	ADP
cana-3843	187	27	chromosomes	chromosome	NOUN
cana-3843	187	28	50	50	NUM
cana-3843	187	29	number	number	NOUN
cana-3843	187	30	of	of	ADP
cana-3843	187	31	populations	population	NOUN
cana-3843	187	32	50	50	NUM
cana-3843	187	33	table-3	table-3	NUM
cana-3843	187	34	presents	present	VERB
cana-3843	187	35	the	the	DET
cana-3843	187	36	performance	performance	NOUN
cana-3843	187	37	of	of	ADP
cana-3843	187	38	the	the	DET
cana-3843	187	39	research	research	NOUN
cana-3843	187	40	methodology	methodology	NOUN
cana-3843	187	41	using	use	VERB
cana-3843	187	42	the	the	DET
cana-3843	187	43	lstm	lstm	NOUN
cana-3843	187	44	classifier	classifier	NOUN
cana-3843	187	45	,	,	PUNCT
cana-3843	187	46	evaluating	evaluate	VERB
cana-3843	187	47	the	the	DET
cana-3843	187	48	accuracy	accuracy	NOUN
cana-3843	187	49	and	and	CCONJ
cana-3843	187	50	loss	loss	NOUN
cana-3843	187	51	values	value	NOUN
cana-3843	187	52	of	of	ADP
cana-3843	187	53	various	various	ADJ
cana-3843	187	54	optimizers	optimizer	NOUN
cana-3843	187	55	,	,	PUNCT
cana-3843	187	56	including	include	VERB
cana-3843	187	57	adam	adam	PROPN
cana-3843	187	58	,	,	PUNCT
cana-3843	187	59	adagrad	adagrad	ADJ
cana-3843	187	60	,	,	PUNCT
cana-3843	187	61	rmsprop	rmsprop	NOUN
cana-3843	187	62	,	,	PUNCT
cana-3843	187	63	and	and	CCONJ
cana-3843	187	64	sgd	sgd	NOUN
cana-3843	187	65	.	.	PUNCT
cana-3843	188	1	the	the	DET
cana-3843	188	2	results	result	NOUN
cana-3843	188	3	highlight	highlight	VERB
cana-3843	188	4	the	the	DET
cana-3843	188	5	model	model	NOUN
cana-3843	188	6	’s	’s	PART
cana-3843	188	7	learning	learn	VERB
cana-3843	188	8	efficiency	efficiency	NOUN
cana-3843	188	9	,	,	PUNCT
cana-3843	188	10	and	and	CCONJ
cana-3843	188	11	convergence	convergence	NOUN
cana-3843	188	12	stability	stability	NOUN
cana-3843	188	13	in	in	ADP
cana-3843	188	14	accurately	accurately	ADV
cana-3843	188	15	predicting	predict	VERB
cana-3843	188	16	the	the	DET
cana-3843	188	17	disease	disease	NOUN
cana-3843	188	18	at	at	ADP
cana-3843	188	19	an	an	DET
cana-3843	188	20	early	early	ADJ
cana-3843	188	21	stage	stage	NOUN
cana-3843	188	22	.	.	PUNCT
cana-3843	189	1	table-3	table-3	NUM
cana-3843	189	2	performance	performance	NOUN
cana-3843	189	3	metrics	metric	NOUN
cana-3843	189	4	of	of	ADP
cana-3843	189	5	accuracy	accuracy	NOUN
cana-3843	189	6	and	and	CCONJ
cana-3843	189	7	loss	loss	NOUN
cana-3843	189	8	value	value	NOUN
cana-3843	189	9	for	for	ADP
cana-3843	189	10	various	various	ADJ
cana-3843	189	11	optimizers	optimizer	NOUN
cana-3843	189	12	communications	communication	NOUN
cana-3843	189	13	on	on	ADP
cana-3843	189	14	applied	apply	VERB
cana-3843	189	15	nonlinear	nonlinear	ADJ
cana-3843	189	16	analysis	analysis	NOUN
cana-3843	189	17	issn	issn	NOUN
cana-3843	189	18	:	:	PUNCT
cana-3843	189	19	1074	1074	NUM
cana-3843	189	20	-	-	PUNCT
cana-3843	189	21	133x	133x	NUM
cana-3843	189	22	vol	vol	NOUN
cana-3843	189	23	32	32	NUM
cana-3843	189	24	no	no	NOUN
cana-3843	189	25	.	.	PUNCT
cana-3843	190	1	9s	9s	NUM
cana-3843	190	2	(	(	PUNCT
cana-3843	190	3	2025	2025	NUM
cana-3843	190	4	)	)	PUNCT
cana-3843	190	5	127	127	NUM
cana-3843	190	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	190	7	figure2	figure2	NOUN
cana-3843	190	8	indicates	indicate	VERB
cana-3843	190	9	the	the	DET
cana-3843	190	10	accuracy	accuracy	NOUN
cana-3843	190	11	metrics	metric	NOUN
cana-3843	190	12	obtained	obtain	VERB
cana-3843	190	13	through	through	ADP
cana-3843	190	14	different	different	ADJ
cana-3843	190	15	optimizers	optimizer	NOUN
cana-3843	190	16	during	during	ADP
cana-3843	190	17	the	the	DET
cana-3843	190	18	training	training	NOUN
cana-3843	190	19	and	and	CCONJ
cana-3843	190	20	testing	testing	NOUN
cana-3843	190	21	phases	phase	NOUN
cana-3843	190	22	.	.	PUNCT
cana-3843	191	1	the	the	DET
cana-3843	191	2	adam	adam	PROPN
cana-3843	191	3	optimizer	optimizer	NOUN
cana-3843	191	4	yielded	yield	VERB
cana-3843	191	5	an	an	DET
cana-3843	191	6	increased	increase	VERB
cana-3843	191	7	training	training	NOUN
cana-3843	191	8	accuracy	accuracy	NOUN
cana-3843	191	9	rate	rate	NOUN
cana-3843	191	10	of	of	ADP
cana-3843	191	11	the	the	DET
cana-3843	191	12	classification	classification	NOUN
cana-3843	191	13	by	by	ADP
cana-3843	191	14	1.92	1.92	NUM
cana-3843	191	15	%	%	NOUN
cana-3843	191	16	in	in	ADP
cana-3843	191	17	comparison	comparison	NOUN
cana-3843	191	18	to	to	ADP
cana-3843	191	19	the	the	DET
cana-3843	191	20	adagrad	adagrad	ADJ
cana-3843	191	21	optimizer	optimizer	NOUN
cana-3843	191	22	,	,	PUNCT
cana-3843	191	23	and	and	CCONJ
cana-3843	191	24	reduced	reduce	VERB
cana-3843	191	25	training	training	NOUN
cana-3843	191	26	accuracy	accuracy	NOUN
cana-3843	191	27	by	by	ADP
cana-3843	191	28	0.97	0.97	NUM
cana-3843	191	29	%	%	NOUN
cana-3843	191	30	than	than	ADP
cana-3843	191	31	the	the	DET
cana-3843	191	32	rmsprop	rmsprop	NOUN
cana-3843	191	33	and	and	CCONJ
cana-3843	191	34	the	the	DET
cana-3843	191	35	accuracy	accuracy	NOUN
cana-3843	191	36	by	by	ADP
cana-3843	191	37	0.88	0.88	NUM
cana-3843	191	38	%	%	NOUN
cana-3843	191	39	with	with	ADP
cana-3843	191	40	the	the	DET
cana-3843	191	41	sgd	sgd	PROPN
cana-3843	191	42	optimizer	optimizer	NOUN
cana-3843	191	43	.	.	PUNCT
cana-3843	192	1	comparing	compare	VERB
cana-3843	192	2	,	,	PUNCT
cana-3843	192	3	the	the	DET
cana-3843	192	4	testing	testing	NOUN
cana-3843	192	5	accuracy	accuracy	NOUN
cana-3843	192	6	of	of	ADP
cana-3843	192	7	the	the	DET
cana-3843	192	8	model	model	NOUN
cana-3843	192	9	indicates	indicate	VERB
cana-3843	192	10	that	that	SCONJ
cana-3843	192	11	the	the	DET
cana-3843	192	12	adam	adam	PROPN
cana-3843	192	13	optimizer	optimizer	NOUN
cana-3843	192	14	achieved	achieve	VERB
cana-3843	192	15	a	a	DET
cana-3843	192	16	higher	high	ADJ
cana-3843	192	17	testing	testing	NOUN
cana-3843	192	18	accuracy	accuracy	NOUN
cana-3843	192	19	rate	rate	NOUN
cana-3843	192	20	of	of	ADP
cana-3843	192	21	the	the	DET
cana-3843	192	22	classification	classification	NOUN
cana-3843	192	23	by	by	ADP
cana-3843	192	24	6.63	6.63	NUM
cana-3843	192	25	%	%	NOUN
cana-3843	192	26	in	in	ADP
cana-3843	192	27	comparison	comparison	NOUN
cana-3843	192	28	to	to	ADP
cana-3843	192	29	the	the	DET
cana-3843	192	30	adagrad	adagrad	ADJ
cana-3843	192	31	optimizer	optimizer	NOUN
cana-3843	192	32	,	,	PUNCT
cana-3843	192	33	achieved	achieve	VERB
cana-3843	192	34	an	an	DET
cana-3843	192	35	increased	increase	VERB
cana-3843	192	36	accuracy	accuracy	NOUN
cana-3843	192	37	rate	rate	NOUN
cana-3843	192	38	by	by	ADP
cana-3843	192	39	2.09	2.09	NUM
cana-3843	192	40	%	%	NOUN
cana-3843	192	41	than	than	ADP
cana-3843	192	42	the	the	DET
cana-3843	192	43	rmsprop	rmsprop	NOUN
cana-3843	192	44	optimizer	optimizer	NOUN
cana-3843	192	45	,	,	PUNCT
cana-3843	192	46	and	and	CCONJ
cana-3843	192	47	4.9	4.9	NUM
cana-3843	192	48	%	%	NOUN
cana-3843	192	49	than	than	ADP
cana-3843	192	50	the	the	DET
cana-3843	192	51	sgd	sgd	NOUN
cana-3843	192	52	optimizer	optimizer	NOUN
cana-3843	192	53	.	.	PUNCT
cana-3843	193	1	the	the	DET
cana-3843	193	2	outcomes	outcome	NOUN
cana-3843	193	3	demonstrate	demonstrate	VERB
cana-3843	193	4	that	that	SCONJ
cana-3843	193	5	the	the	DET
cana-3843	193	6	lstm	lstm	PROPN
cana-3843	193	7	model	model	NOUN
cana-3843	193	8	using	use	VERB
cana-3843	193	9	the	the	DET
cana-3843	193	10	adam	adam	PROPN
cana-3843	193	11	optimizer	optimizer	NOUN
cana-3843	193	12	predicted	predict	VERB
cana-3843	193	13	a	a	DET
cana-3843	193	14	strong	strong	ADJ
cana-3843	193	15	overall	overall	ADJ
cana-3843	193	16	performance	performance	NOUN
cana-3843	193	17	with	with	ADP
cana-3843	193	18	a	a	DET
cana-3843	193	19	testing	testing	NOUN
cana-3843	193	20	accuracy	accuracy	NOUN
cana-3843	193	21	rate	rate	NOUN
cana-3843	193	22	of	of	ADP
cana-3843	193	23	88.45	88.45	NUM
cana-3843	193	24	%	%	NOUN
cana-3843	193	25	and	and	CCONJ
cana-3843	193	26	a	a	DET
cana-3843	193	27	training	training	NOUN
cana-3843	193	28	accuracy	accuracy	NOUN
cana-3843	193	29	of	of	ADP
cana-3843	193	30	94.48	94.48	NUM
cana-3843	193	31	%	%	NOUN
cana-3843	193	32	for	for	ADP
cana-3843	193	33	predicting	predict	VERB
cana-3843	193	34	leukemia	leukemia	NOUN
cana-3843	193	35	cancer	cancer	NOUN
cana-3843	193	36	.	.	PUNCT
cana-3843	194	1	figure-2	figure-2	X
cana-3843	194	2	accuracy	accuracy	NOUN
cana-3843	194	3	analysis	analysis	NOUN
cana-3843	194	4	of	of	ADP
cana-3843	194	5	various	various	ADJ
cana-3843	194	6	optimizers	optimizer	NOUN
cana-3843	194	7	figure-3	figure-3	NUM
cana-3843	194	8	indicates	indicate	VERB
cana-3843	194	9	the	the	DET
cana-3843	194	10	loss	loss	NOUN
cana-3843	194	11	value	value	NOUN
cana-3843	194	12	obtained	obtain	VERB
cana-3843	194	13	through	through	ADP
cana-3843	194	14	different	different	ADJ
cana-3843	194	15	optimizers	optimizer	NOUN
cana-3843	194	16	during	during	ADP
cana-3843	194	17	the	the	DET
cana-3843	194	18	training	training	NOUN
cana-3843	194	19	and	and	CCONJ
cana-3843	194	20	testing	testing	NOUN
cana-3843	194	21	phases	phase	NOUN
cana-3843	194	22	.	.	PUNCT
cana-3843	195	1	the	the	DET
cana-3843	195	2	adam	adam	PROPN
cana-3843	195	3	optimizer	optimizer	NOUN
cana-3843	195	4	achieved	achieve	VERB
cana-3843	195	5	a	a	DET
cana-3843	195	6	testing	testing	NOUN
cana-3843	195	7	loss	loss	NOUN
cana-3843	195	8	of	of	ADP
cana-3843	195	9	0.1612	0.1612	NUM
cana-3843	195	10	,	,	PUNCT
cana-3843	195	11	indicating	indicate	VERB
cana-3843	195	12	to	to	PART
cana-3843	195	13	generalize	generalize	VERB
cana-3843	195	14	effectively	effectively	ADV
cana-3843	195	15	to	to	ADP
cana-3843	195	16	unseen	unseen	ADJ
cana-3843	195	17	data	datum	NOUN
cana-3843	195	18	,	,	PUNCT
cana-3843	195	19	and	and	CCONJ
cana-3843	195	20	a	a	DET
cana-3843	195	21	training	training	NOUN
cana-3843	195	22	loss	loss	NOUN
cana-3843	195	23	of	of	ADP
cana-3843	195	24	0.0726	0.0726	NUM
cana-3843	195	25	reflecting	reflect	VERB
cana-3843	195	26	efficient	efficient	ADJ
cana-3843	195	27	convergence	convergence	NOUN
cana-3843	195	28	.	.	PUNCT
cana-3843	196	1	the	the	DET
cana-3843	196	2	adagrad	adagrad	ADJ
cana-3843	196	3	optimizer	optimizer	NOUN
cana-3843	196	4	recorded	record	VERB
cana-3843	196	5	a	a	DET
cana-3843	196	6	testing	testing	NOUN
cana-3843	196	7	loss	loss	NOUN
cana-3843	196	8	of	of	ADP
cana-3843	196	9	0.6638	0.6638	NUM
cana-3843	196	10	and	and	CCONJ
cana-3843	196	11	a	a	DET
cana-3843	196	12	training	training	NOUN
cana-3843	196	13	loss	loss	NOUN
cana-3843	196	14	of	of	ADP
cana-3843	196	15	0.2019	0.2019	NUM
cana-3843	196	16	indicating	indicate	VERB
cana-3843	196	17	increased	increase	VERB
cana-3843	196	18	loss	loss	NOUN
cana-3843	196	19	value	value	NOUN
cana-3843	196	20	during	during	ADP
cana-3843	196	21	the	the	DET
cana-3843	196	22	training	training	NOUN
cana-3843	196	23	and	and	CCONJ
cana-3843	196	24	testing	testing	NOUN
cana-3843	196	25	phase	phase	NOUN
cana-3843	196	26	.	.	PUNCT
cana-3843	197	1	the	the	DET
cana-3843	197	2	rmsprop	rmsprop	NOUN
cana-3843	197	3	optimizer	optimizer	NOUN
cana-3843	197	4	showed	show	VERB
cana-3843	197	5	a	a	DET
cana-3843	197	6	testing	testing	NOUN
cana-3843	197	7	loss	loss	NOUN
cana-3843	197	8	of	of	ADP
cana-3843	197	9	0.3799	0.3799	NUM
cana-3843	197	10	which	which	PRON
cana-3843	197	11	was	be	AUX
cana-3843	197	12	higher	high	ADJ
cana-3843	197	13	than	than	ADP
cana-3843	197	14	the	the	DET
cana-3843	197	15	adam	adam	PROPN
cana-3843	197	16	optimizer	optimizer	NOUN
cana-3843	197	17	and	and	CCONJ
cana-3843	197	18	lower	low	ADJ
cana-3843	197	19	than	than	ADP
cana-3843	197	20	the	the	DET
cana-3843	197	21	adagrad	adagrad	ADJ
cana-3843	197	22	optimizer	optimizer	NOUN
cana-3843	197	23	.	.	PUNCT
cana-3843	198	1	the	the	DET
cana-3843	198	2	training	training	NOUN
cana-3843	198	3	loss	loss	NOUN
cana-3843	198	4	of	of	ADP
cana-3843	198	5	0.0785	0.0785	NUM
cana-3843	198	6	and	and	CCONJ
cana-3843	198	7	a	a	DET
cana-3843	198	8	testing	testing	NOUN
cana-3843	198	9	loss	loss	NOUN
cana-3843	198	10	of	of	ADP
cana-3843	198	11	0.1905	0.1905	NUM
cana-3843	198	12	obtained	obtain	VERB
cana-3843	198	13	for	for	ADP
cana-3843	198	14	using	use	VERB
cana-3843	198	15	sgd	sgd	NOUN
cana-3843	198	16	optimizer	optimizer	NOUN
cana-3843	198	17	indicate	indicate	VERB
cana-3843	198	18	the	the	DET
cana-3843	198	19	stability	stability	NOUN
cana-3843	198	20	in	in	ADP
cana-3843	198	21	convergence.the	convergence.the	DET
cana-3843	198	22	outcomes	outcome	NOUN
cana-3843	198	23	demonstrate	demonstrate	VERB
cana-3843	198	24	that	that	SCONJ
cana-3843	198	25	the	the	DET
cana-3843	198	26	lstm	lstm	PROPN
cana-3843	198	27	model	model	NOUN
cana-3843	198	28	using	use	VERB
cana-3843	198	29	the	the	DET
cana-3843	198	30	adam	adam	PROPN
cana-3843	198	31	optimizer	optimizer	NOUN
cana-3843	198	32	reduced	reduce	VERB
cana-3843	198	33	the	the	DET
cana-3843	198	34	loss	loss	NOUN
cana-3843	198	35	rate	rate	NOUN
cana-3843	198	36	to	to	ADP
cana-3843	198	37	0.5026	0.5026	NUM
cana-3843	198	38	compared	compare	VERB
cana-3843	198	39	with	with	ADP
cana-3843	198	40	the	the	DET
cana-3843	198	41	adagrad	adagrad	ADJ
cana-3843	198	42	optimizer	optimizer	NOUN
cana-3843	198	43	,	,	PUNCT
cana-3843	198	44	0.2187	0.2187	NUM
cana-3843	198	45	with	with	ADP
cana-3843	198	46	rmsprop	rmsprop	NOUN
cana-3843	198	47	,	,	PUNCT
cana-3843	198	48	and	and	CCONJ
cana-3843	198	49	0.0293	0.0293	NUM
cana-3843	198	50	with	with	ADP
cana-3843	198	51	the	the	DET
cana-3843	198	52	sgd	sgd	PROPN
cana-3843	198	53	optimizer	optimizer	NOUN
cana-3843	198	54	.	.	PUNCT
cana-3843	199	1	optimizers	optimizer	NOUN
cana-3843	199	2	training	train	VERB
cana-3843	199	3	_	_	PUNCT
cana-3843	199	4	accuracy(%	accuracy(%	ADJ
cana-3843	199	5	)	)	PUNCT
cana-3843	199	6	testing	testing	NOUN
cana-3843	199	7	_	_	PUNCT
cana-3843	199	8	accuracy(%	accuracy(%	ADJ
cana-3843	199	9	)	)	PUNCT
cana-3843	199	10	training	training	NOUN
cana-3843	199	11	_	_	PUNCT
cana-3843	199	12	loss(%	loss(%	NOUN
cana-3843	199	13	)	)	PUNCT
cana-3843	199	14	testing	testing	NOUN
cana-3843	199	15	_	_	PUNCT
cana-3843	199	16	loss(%	loss(%	NOUN
cana-3843	199	17	)	)	PUNCT
cana-3843	199	18	adam	adam	PROPN
cana-3843	199	19	94.48	94.48	NUM
cana-3843	199	20	88.45	88.45	NUM
cana-3843	199	21	7.26	7.26	NUM
cana-3843	199	22	16.12	16.12	NUM
cana-3843	199	23	adagrad	adagrad	NOUN
cana-3843	199	24	92.56	92.56	NUM
cana-3843	199	25	81.82	81.82	NUM
cana-3843	199	26	20.19	20.19	NUM
cana-3843	199	27	66.38	66.38	NUM
cana-3843	199	28	rmsprop	rmsprop	NOUN
cana-3843	199	29	95.45	95.45	NUM
cana-3843	199	30	86.36	86.36	NUM
cana-3843	199	31	26.40	26.40	NUM
cana-3843	199	32	37.99	37.99	NUM
cana-3843	199	33	sgd	sgd	X
cana-3843	199	34	95.36	95.36	NUM
cana-3843	199	35	84.45	84.45	NUM
cana-3843	199	36	7.85	7.85	NUM
cana-3843	199	37	19.05	19.05	NUM
cana-3843	199	38	communications	communication	NOUN
cana-3843	199	39	on	on	ADP
cana-3843	199	40	applied	apply	VERB
cana-3843	199	41	nonlinear	nonlinear	ADJ
cana-3843	199	42	analysis	analysis	NOUN
cana-3843	199	43	issn	issn	NOUN
cana-3843	199	44	:	:	PUNCT
cana-3843	199	45	1074	1074	NUM
cana-3843	199	46	-	-	PUNCT
cana-3843	199	47	133x	133x	NUM
cana-3843	199	48	vol	vol	NOUN
cana-3843	199	49	32	32	NUM
cana-3843	199	50	no	no	NOUN
cana-3843	199	51	.	.	PUNCT
cana-3843	200	1	9s	9s	NUM
cana-3843	200	2	(	(	PUNCT
cana-3843	200	3	2025	2025	NUM
cana-3843	200	4	)	)	PUNCT
cana-3843	200	5	128	128	NUM
cana-3843	200	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	200	7	figure-3	figure-3	NUM
cana-3843	200	8	loss	loss	NOUN
cana-3843	200	9	analysis	analysis	NOUN
cana-3843	200	10	of	of	ADP
cana-3843	200	11	various	various	ADJ
cana-3843	200	12	optimizers	optimizer	NOUN
cana-3843	200	13	table-4	table-4	NUM
cana-3843	200	14	depicts	depict	VERB
cana-3843	200	15	evaluation	evaluation	NOUN
cana-3843	200	16	metrics	metric	NOUN
cana-3843	200	17	,	,	PUNCT
cana-3843	200	18	including	include	VERB
cana-3843	200	19	precision	precision	NOUN
cana-3843	200	20	,	,	PUNCT
cana-3843	200	21	recall	recall	NOUN
cana-3843	200	22	,	,	PUNCT
cana-3843	200	23	and	and	CCONJ
cana-3843	200	24	f1	f1	NOUN
cana-3843	200	25	-	-	PUNCT
cana-3843	200	26	score	score	NOUN
cana-3843	200	27	for	for	ADP
cana-3843	200	28	class	class	NOUN
cana-3843	200	29	0	0	PUNCT
cana-3843	200	30	(	(	PUNCT
cana-3843	200	31	all	all	PRON
cana-3843	200	32	)	)	PUNCT
cana-3843	200	33	and	and	CCONJ
cana-3843	200	34	class1(aml	class1(aml	NOUN
cana-3843	200	35	)	)	PUNCT
cana-3843	200	36	using	use	VERB
cana-3843	200	37	various	various	ADJ
cana-3843	200	38	optimizers	optimizer	NOUN
cana-3843	200	39	such	such	ADJ
cana-3843	200	40	as	as	ADP
cana-3843	200	41	adam	adam	PROPN
cana-3843	200	42	,	,	PUNCT
cana-3843	200	43	adagrad	adagrad	ADJ
cana-3843	200	44	,	,	PUNCT
cana-3843	200	45	rmsprop	rmsprop	NOUN
cana-3843	200	46	,	,	PUNCT
cana-3843	200	47	and	and	CCONJ
cana-3843	200	48	sgd	sgd	PROPN
cana-3843	200	49	applied	apply	VERB
cana-3843	200	50	to	to	ADP
cana-3843	200	51	the	the	DET
cana-3843	200	52	lstm	lstm	NOUN
cana-3843	200	53	classifier	classifier	NOUN
cana-3843	200	54	.	.	PUNCT
cana-3843	201	1	table-4	table-4	NUM
cana-3843	201	2	classification	classification	NOUN
cana-3843	201	3	metrics	metric	NOUN
cana-3843	201	4	using	use	VERB
cana-3843	201	5	various	various	ADJ
cana-3843	201	6	optimizers	optimizer	NOUN
cana-3843	201	7	with	with	ADP
cana-3843	201	8	lstm	lstm	PROPN
cana-3843	201	9	adam	adam	PROPN
cana-3843	201	10	adagrad	adagrad	ADJ
cana-3843	201	11	rmsprop	rmsprop	NOUN
cana-3843	201	12	sgd	sgd	PROPN
cana-3843	201	13	metric	metric	NOUN
cana-3843	201	14	s	s	PROPN
cana-3843	201	15	(	(	PUNCT
cana-3843	201	16	%	%	INTJ
cana-3843	201	17	)	)	PUNCT
cana-3843	202	1	prec	prec	PROPN
cana-3843	203	1	i	i	PROPN
cana-3843	203	2	_	_	NOUN
cana-3843	203	3	valu	valu	PROPN
cana-3843	203	4	e	e	X
cana-3843	203	5	reca	reca	PROPN
cana-3843	203	6	ll_va	ll_va	PROPN
cana-3843	203	7	lue	lue	PROPN
cana-3843	203	8	f1scor	f1scor	PROPN
cana-3843	203	9	e_va	e_va	PROPN
cana-3843	203	10	lue	lue	PROPN
cana-3843	203	11	preci	preci	X
cana-3843	204	1	_	_	PUNCT
cana-3843	204	2	val	val	PROPN
cana-3843	205	1	ue	ue	PROPN
cana-3843	205	2	reca	reca	PROPN
cana-3843	205	3	ll_va	ll_va	PROPN
cana-3843	205	4	lue	lue	PROPN
cana-3843	205	5	f1scor	f1scor	PROPN
cana-3843	205	6	e_va	e_va	PROPN
cana-3843	205	7	lue	lue	PROPN
cana-3843	205	8	preci	preci	X
cana-3843	206	1	_	_	PUNCT
cana-3843	206	2	val	val	PROPN
cana-3843	207	1	ue	ue	PROPN
cana-3843	207	2	reca	reca	PROPN
cana-3843	207	3	ll_va	ll_va	PROPN
cana-3843	207	4	lue	lue	PROPN
cana-3843	207	5	f1scor	f1scor	PROPN
cana-3843	207	6	e_val	e_val	PROPN
cana-3843	207	7	ue	ue	PROPN
cana-3843	207	8	preci	preci	NOUN
cana-3843	207	9	_	_	PUNCT
cana-3843	208	1	val	val	PROPN
cana-3843	209	1	ue	ue	PROPN
cana-3843	209	2	recal	recal	PROPN
cana-3843	209	3	l_val	l_val	PROPN
cana-3843	209	4	ue	ue	PROPN
cana-3843	209	5	f1scor	f1scor	PROPN
cana-3843	209	6	e_val	e_val	PROPN
cana-3843	209	7	ue	ue	PROPN
cana-3843	209	8	class	class	NOUN
cana-3843	209	9	0	0	NUM
cana-3843	209	10	all	all	PRON
cana-3843	209	11	0.93	0.93	NUM
cana-3843	209	12	0.87	0.87	NUM
cana-3843	209	13	0.90	0.90	NUM
cana-3843	209	14	0.80	0.80	NUM
cana-3843	209	15	0.92	0.92	NUM
cana-3843	209	16	0.86	0.86	NUM
cana-3843	209	17	0.81	0.81	NUM
cana-3843	209	18	1.00	1.00	NUM
cana-3843	209	19	0.90	0.90	NUM
cana-3843	209	20	0.82	0.82	NUM
cana-3843	209	21	0.93	0.93	NUM
cana-3843	209	22	0.87	0.87	NUM
cana-3843	209	23	class	class	NOUN
cana-3843	209	24	1	1	NUM
cana-3843	209	25	aml	aml	NOUN
cana-3843	209	26	0.82	0.82	NUM
cana-3843	209	27	0.90	0.90	NUM
cana-3843	209	28	0.86	0.86	NUM
cana-3843	209	29	0.86	0.86	NUM
cana-3843	209	30	0.67	0.67	NUM
cana-3843	209	31	0.75	0.75	NUM
cana-3843	209	32	1.00	1.00	NUM
cana-3843	209	33	0.67	0.67	NUM
cana-3843	209	34	0.80	0.80	NUM
cana-3843	209	35	0.88	0.88	NUM
cana-3843	209	36	0.70	0.70	NUM
cana-3843	209	37	0.78	0.78	NUM
cana-3843	209	38	macro	macro	ADJ
cana-3843	209	39	averag	averag	NOUN
cana-3843	209	40	e	e	PROPN
cana-3843	209	41	0.87	0.87	NUM
cana-3843	209	42	0.88	0.88	NUM
cana-3843	209	43	0.88	0.88	NUM
cana-3843	209	44	0.83	0.83	NUM
cana-3843	209	45	0.79	0.79	NUM
cana-3843	209	46	0.80	0.80	NUM
cana-3843	209	47	0.91	0.91	NUM
cana-3843	209	48	0.83	0.83	NUM
cana-3843	209	49	0.85	0.85	NUM
cana-3843	209	50	0.85	0.85	NUM
cana-3843	209	51	0.82	0.82	NUM
cana-3843	209	52	0.83	0.83	NUM
cana-3843	209	53	weight	weight	NOUN
cana-3843	209	54	ed	ed	NOUN
cana-3843	209	55	averag	averag	PROPN
cana-3843	209	56	e	e	PROPN
cana-3843	209	57	0.89	0.89	NUM
cana-3843	209	58	0.88	0.88	NUM
cana-3843	209	59	0.89	0.89	NUM
cana-3843	209	60	0.82	0.82	NUM
cana-3843	209	61	0.82	0.82	NUM
cana-3843	209	62	0.81	0.81	NUM
cana-3843	209	63	0.89	0.89	NUM
cana-3843	209	64	0.86	0.86	NUM
cana-3843	209	65	0.86	0.86	NUM
cana-3843	209	66	0.85	0.85	NUM
cana-3843	209	67	0.85	0.85	NUM
cana-3843	209	68	0.84	0.84	NUM
cana-3843	209	69	communications	communication	NOUN
cana-3843	209	70	on	on	ADP
cana-3843	209	71	applied	apply	VERB
cana-3843	209	72	nonlinear	nonlinear	ADJ
cana-3843	209	73	analysis	analysis	NOUN
cana-3843	209	74	issn	issn	NOUN
cana-3843	209	75	:	:	PUNCT
cana-3843	209	76	1074	1074	NUM
cana-3843	209	77	-	-	PUNCT
cana-3843	209	78	133x	133x	NUM
cana-3843	209	79	vol	vol	NOUN
cana-3843	209	80	32	32	NUM
cana-3843	209	81	no	no	NOUN
cana-3843	209	82	.	.	PUNCT
cana-3843	210	1	9s	9s	NUM
cana-3843	210	2	(	(	PUNCT
cana-3843	210	3	2025	2025	NUM
cana-3843	210	4	)	)	PUNCT
cana-3843	210	5	129	129	NUM
cana-3843	210	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	210	7	figure-4	figure-4	NUM
cana-3843	210	8	illustrates	illustrate	VERB
cana-3843	210	9	the	the	DET
cana-3843	210	10	precision	precision	NOUN
cana-3843	210	11	metric	metric	ADJ
cana-3843	210	12	performance	performance	NOUN
cana-3843	210	13	,	,	PUNCT
cana-3843	210	14	showing	show	VERB
cana-3843	210	15	that	that	SCONJ
cana-3843	210	16	the	the	DET
cana-3843	210	17	proposed	propose	VERB
cana-3843	210	18	model	model	NOUN
cana-3843	210	19	achieved	achieve	VERB
cana-3843	210	20	a	a	DET
cana-3843	210	21	macro	macro	ADJ
cana-3843	210	22	average	average	ADJ
cana-3843	210	23	precision	precision	NOUN
cana-3843	210	24	of	of	ADP
cana-3843	210	25	87	87	NUM
cana-3843	210	26	%	%	NOUN
cana-3843	210	27	and	and	CCONJ
cana-3843	210	28	a	a	DET
cana-3843	210	29	weighted	weight	VERB
cana-3843	210	30	average	average	ADJ
cana-3843	210	31	precision	precision	NOUN
cana-3843	210	32	value	value	NOUN
cana-3843	210	33	of	of	ADP
cana-3843	210	34	88	88	NUM
cana-3843	210	35	%	%	NOUN
cana-3843	210	36	while	while	SCONJ
cana-3843	210	37	applying	apply	VERB
cana-3843	210	38	adam	adam	PROPN
cana-3843	210	39	optimizer	optimizer	NOUN
cana-3843	210	40	.	.	PUNCT
cana-3843	211	1	for	for	ADP
cana-3843	211	2	the	the	DET
cana-3843	211	3	adagrad	adagrad	ADJ
cana-3843	211	4	optimizer	optimizer	NOUN
cana-3843	211	5	,	,	PUNCT
cana-3843	211	6	the	the	DET
cana-3843	211	7	precision	precision	NOUN
cana-3843	211	8	rates	rate	NOUN
cana-3843	211	9	for	for	ADP
cana-3843	211	10	class	class	NOUN
cana-3843	211	11	0	0	NUM
cana-3843	211	12	(	(	PUNCT
cana-3843	211	13	all)and	all)and	CCONJ
cana-3843	211	14	class	class	NOUN
cana-3843	211	15	1	1	NUM
cana-3843	211	16	(	(	PUNCT
cana-3843	211	17	aml	aml	PROPN
cana-3843	211	18	)	)	PUNCT
cana-3843	211	19	are	be	AUX
cana-3843	211	20	80	80	NUM
cana-3843	211	21	%	%	NOUN
cana-3843	211	22	and	and	CCONJ
cana-3843	211	23	86	86	NUM
cana-3843	211	24	%	%	NOUN
cana-3843	211	25	respectively	respectively	ADV
cana-3843	211	26	.	.	PUNCT
cana-3843	212	1	the	the	DET
cana-3843	212	2	optimizer	optimizer	NOUN
cana-3843	212	3	obtained	obtain	VERB
cana-3843	212	4	a	a	DET
cana-3843	212	5	macro	macro	ADJ
cana-3843	212	6	average	average	ADJ
cana-3843	212	7	precision	precision	NOUN
cana-3843	212	8	rate	rate	NOUN
cana-3843	212	9	of	of	ADP
cana-3843	212	10	83	83	NUM
cana-3843	212	11	%	%	NOUN
cana-3843	212	12	to	to	PART
cana-3843	212	13	predict	predict	VERB
cana-3843	212	14	the	the	DET
cana-3843	212	15	disease	disease	NOUN
cana-3843	212	16	.	.	PUNCT
cana-3843	213	1	the	the	DET
cana-3843	213	2	rmsprop	rmsprop	NOUN
cana-3843	213	3	optimizer	optimizer	NOUN
cana-3843	213	4	received	receive	VERB
cana-3843	213	5	the	the	DET
cana-3843	213	6	precision	precision	NOUN
cana-3843	213	7	rate	rate	NOUN
cana-3843	213	8	in	in	ADP
cana-3843	213	9	terms	term	NOUN
cana-3843	213	10	of	of	ADP
cana-3843	213	11	weighted	weight	VERB
cana-3843	213	12	average	average	NOUN
cana-3843	213	13	is	be	AUX
cana-3843	213	14	89	89	NUM
cana-3843	213	15	%	%	NOUN
cana-3843	213	16	.	.	PUNCT
cana-3843	214	1	the	the	DET
cana-3843	214	2	sgd	sgd	PROPN
cana-3843	214	3	optimizer	optimizer	NOUN
cana-3843	214	4	recorded	record	VERB
cana-3843	214	5	a	a	DET
cana-3843	214	6	precision	precision	NOUN
cana-3843	214	7	rate	rate	NOUN
cana-3843	214	8	of	of	ADP
cana-3843	214	9	85	85	NUM
cana-3843	214	10	%	%	NOUN
cana-3843	214	11	for	for	ADP
cana-3843	214	12	both	both	PRON
cana-3843	214	13	macro	macro	ADJ
cana-3843	214	14	average	average	NOUN
cana-3843	214	15	and	and	CCONJ
cana-3843	214	16	weighted	weight	VERB
cana-3843	214	17	average	average	ADJ
cana-3843	214	18	values	value	NOUN
cana-3843	214	19	.	.	PUNCT
cana-3843	215	1	figure-4	figure-4	NUM
cana-3843	215	2	estimation	estimation	NOUN
cana-3843	215	3	of	of	ADP
cana-3843	215	4	precision	precision	NOUN
cana-3843	215	5	value	value	NOUN
cana-3843	215	6	using	use	VERB
cana-3843	215	7	various	various	ADJ
cana-3843	215	8	optimizers	optimizer	NOUN
cana-3843	215	9	figure-5	figure-5	NUM
cana-3843	215	10	presents	present	VERB
cana-3843	215	11	the	the	DET
cana-3843	215	12	performance	performance	NOUN
cana-3843	215	13	evaluation	evaluation	NOUN
cana-3843	215	14	based	base	VERB
cana-3843	215	15	on	on	ADP
cana-3843	215	16	recall	recall	NOUN
cana-3843	215	17	metrics	metric	NOUN
cana-3843	215	18	.	.	PUNCT
cana-3843	216	1	the	the	DET
cana-3843	216	2	model	model	NOUN
cana-3843	216	3	achieved	achieve	VERB
cana-3843	216	4	a	a	DET
cana-3843	216	5	weighted	weighted	ADJ
cana-3843	216	6	average	average	ADJ
cana-3843	216	7	recall	recall	NOUN
cana-3843	216	8	rate	rate	NOUN
cana-3843	216	9	of	of	ADP
cana-3843	216	10	82	82	NUM
cana-3843	216	11	%	%	NOUN
cana-3843	216	12	with	with	ADP
cana-3843	216	13	the	the	DET
cana-3843	216	14	adagrad	adagrad	ADJ
cana-3843	216	15	optimizer	optimizer	NOUN
cana-3843	216	16	,	,	PUNCT
cana-3843	216	17	86	86	NUM
cana-3843	216	18	%	%	NOUN
cana-3843	216	19	with	with	ADP
cana-3843	216	20	the	the	DET
cana-3843	216	21	rmsprop	rmsprop	NOUN
cana-3843	216	22	optimizer	optimizer	NOUN
cana-3843	216	23	and	and	CCONJ
cana-3843	216	24	85	85	NUM
cana-3843	216	25	%	%	NOUN
cana-3843	216	26	with	with	ADP
cana-3843	216	27	the	the	DET
cana-3843	216	28	sgd	sgd	PROPN
cana-3843	216	29	optimizer	optimizer	NOUN
cana-3843	216	30	.	.	PUNCT
cana-3843	217	1	the	the	DET
cana-3843	217	2	adam	adam	PROPN
cana-3843	217	3	optimizer	optimizer	NOUN
cana-3843	217	4	attained	attain	VERB
cana-3843	217	5	a	a	DET
cana-3843	217	6	higher	high	ADJ
cana-3843	217	7	recall	recall	NOUN
cana-3843	217	8	rate	rate	NOUN
cana-3843	217	9	of	of	ADP
cana-3843	217	10	88	88	NUM
cana-3843	217	11	%	%	NOUN
cana-3843	217	12	for	for	ADP
cana-3843	217	13	data	datum	NOUN
cana-3843	217	14	classification	classification	NOUN
cana-3843	217	15	.	.	PUNCT
cana-3843	218	1	figure-5	figure-5	NUM
cana-3843	218	2	estimation	estimation	NOUN
cana-3843	218	3	of	of	ADP
cana-3843	218	4	recall	recall	NOUN
cana-3843	218	5	value	value	NOUN
cana-3843	218	6	using	use	VERB
cana-3843	218	7	various	various	ADJ
cana-3843	218	8	optimizers	optimizer	NOUN
cana-3843	218	9	figure-6	figure-6	NUM
cana-3843	218	10	highlights	highlight	NOUN
cana-3843	218	11	the	the	DET
cana-3843	218	12	model	model	NOUN
cana-3843	218	13	’s	’s	PART
cana-3843	218	14	performance	performance	NOUN
cana-3843	218	15	based	base	VERB
cana-3843	218	16	on	on	ADP
cana-3843	218	17	f1	f1	ADJ
cana-3843	218	18	-	-	PUNCT
cana-3843	218	19	score	score	NOUN
cana-3843	218	20	metrics	metric	NOUN
cana-3843	218	21	.	.	PUNCT
cana-3843	219	1	the	the	DET
cana-3843	219	2	adam	adam	PROPN
cana-3843	219	3	optimizer	optimizer	NOUN
cana-3843	219	4	achieved	achieve	VERB
cana-3843	219	5	an	an	DET
cana-3843	219	6	f1	f1	NOUN
cana-3843	219	7	-	-	PUNCT
cana-3843	219	8	score	score	NOUN
cana-3843	219	9	of	of	ADP
cana-3843	219	10	88	88	NUM
cana-3843	219	11	%	%	NOUN
cana-3843	219	12	,	,	PUNCT
cana-3843	219	13	while	while	SCONJ
cana-3843	219	14	the	the	DET
cana-3843	219	15	adagrad	adagrad	ADJ
cana-3843	219	16	optimizer	optimizer	NOUN
cana-3843	219	17	recorded	record	VERB
cana-3843	219	18	an	an	DET
cana-3843	219	19	f1	f1	NOUN
cana-3843	219	20	-	-	PUNCT
cana-3843	219	21	score	score	NOUN
cana-3843	219	22	of	of	ADP
cana-3843	219	23	80	80	NUM
cana-3843	219	24	%	%	NOUN
cana-3843	219	25	compared	compare	VERB
cana-3843	219	26	to	to	ADP
cana-3843	219	27	the	the	DET
cana-3843	219	28	other	other	ADJ
cana-3843	219	29	optimizers	optimizer	NOUN
cana-3843	219	30	.	.	PUNCT
cana-3843	220	1	communications	communication	NOUN
cana-3843	220	2	on	on	ADP
cana-3843	220	3	applied	apply	VERB
cana-3843	220	4	nonlinear	nonlinear	ADJ
cana-3843	220	5	analysis	analysis	NOUN
cana-3843	220	6	issn	issn	NOUN
cana-3843	220	7	:	:	PUNCT
cana-3843	220	8	1074	1074	NUM
cana-3843	220	9	-	-	PUNCT
cana-3843	220	10	133x	133x	NUM
cana-3843	220	11	vol	vol	NOUN
cana-3843	220	12	32	32	NUM
cana-3843	220	13	no	no	NOUN
cana-3843	220	14	.	.	PUNCT
cana-3843	221	1	9s	9s	NUM
cana-3843	221	2	(	(	PUNCT
cana-3843	221	3	2025	2025	NUM
cana-3843	221	4	)	)	PUNCT
cana-3843	221	5	130	130	NUM
cana-3843	221	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	222	1	figure-6	figure-6	NUM
cana-3843	222	2	estimation	estimation	NOUN
cana-3843	222	3	of	of	ADP
cana-3843	222	4	f1	f1	ADJ
cana-3843	222	5	-	-	PUNCT
cana-3843	222	6	score	score	NOUN
cana-3843	222	7	value	value	NOUN
cana-3843	222	8	using	use	VERB
cana-3843	222	9	various	various	ADJ
cana-3843	222	10	optimizers	optimizer	NOUN
cana-3843	222	11	researchers	researcher	NOUN
cana-3843	222	12	have	have	AUX
cana-3843	222	13	explored	explore	VERB
cana-3843	222	14	different	different	ADJ
cana-3843	222	15	techniques	technique	NOUN
cana-3843	222	16	for	for	ADP
cana-3843	222	17	identifying	identify	VERB
cana-3843	222	18	leukemia	leukemia	NOUN
cana-3843	222	19	cancer	cancer	NOUN
cana-3843	222	20	disease	disease	NOUN
cana-3843	222	21	.	.	PUNCT
cana-3843	223	1	table-5	table-5	PROPN
cana-3843	223	2	presents	present	VERB
cana-3843	223	3	a	a	DET
cana-3843	223	4	comparison	comparison	NOUN
cana-3843	223	5	of	of	ADP
cana-3843	223	6	different	different	ADJ
cana-3843	223	7	methodologies	methodology	NOUN
cana-3843	223	8	used	use	VERB
cana-3843	223	9	for	for	ADP
cana-3843	223	10	cancer	cancer	NOUN
cana-3843	223	11	classification	classification	NOUN
cana-3843	223	12	along	along	ADP
cana-3843	223	13	with	with	ADP
cana-3843	223	14	their	their	PRON
cana-3843	223	15	accuracy	accuracy	NOUN
cana-3843	223	16	values	value	NOUN
cana-3843	223	17	.	.	PUNCT
cana-3843	224	1	figure-7	figure-7	NUM
cana-3843	224	2	depicts	depict	VERB
cana-3843	224	3	the	the	DET
cana-3843	224	4	computational	computational	ADJ
cana-3843	224	5	efficiency	efficiency	NOUN
cana-3843	224	6	of	of	ADP
cana-3843	224	7	the	the	DET
cana-3843	224	8	research	research	NOUN
cana-3843	224	9	model	model	NOUN
cana-3843	224	10	compared	compare	VERB
cana-3843	224	11	to	to	ADP
cana-3843	224	12	existing	exist	VERB
cana-3843	224	13	techniques	technique	NOUN
cana-3843	224	14	.	.	PUNCT
cana-3843	225	1	the	the	DET
cana-3843	225	2	proposed	propose	VERB
cana-3843	225	3	method	method	NOUN
cana-3843	225	4	achieves	achieve	VERB
cana-3843	225	5	the	the	DET
cana-3843	225	6	highest	high	ADJ
cana-3843	225	7	accuracy	accuracy	NOUN
cana-3843	225	8	of	of	ADP
cana-3843	225	9	88.45	88.45	NUM
cana-3843	225	10	%	%	NOUN
cana-3843	225	11	for	for	ADP
cana-3843	225	12	detecting	detect	VERB
cana-3843	225	13	the	the	DET
cana-3843	225	14	disease	disease	NOUN
cana-3843	225	15	.	.	PUNCT
cana-3843	226	1	table-5	table-5	NUM
cana-3843	226	2	comparison	comparison	NOUN
cana-3843	226	3	between	between	ADP
cana-3843	226	4	proposed	propose	VERB
cana-3843	226	5	approach	approach	NOUN
cana-3843	226	6	and	and	CCONJ
cana-3843	226	7	existing	exist	VERB
cana-3843	226	8	techniques	technique	NOUN
cana-3843	226	9	reference	reference	NOUN
cana-3843	226	10	methodology	methodology	NOUN
cana-3843	226	11	accuracy(%	accuracy(%	NOUN
cana-3843	226	12	)	)	PUNCT
cana-3843	227	1	[	[	X
cana-3843	227	2	27	27	NUM
cana-3843	227	3	]	]	X
cana-3843	227	4	bss	bss	NOUN
cana-3843	227	5	/	/	SYM
cana-3843	227	6	wss	wss	NOUN
cana-3843	227	7	-	-	PUNCT
cana-3843	227	8	based	base	VERB
cana-3843	227	9	cart	cart	NOUN
cana-3843	227	10	84.43	84.43	NUM
cana-3843	227	11	[	[	SYM
cana-3843	227	12	28	28	NUM
cana-3843	227	13	]	]	PUNCT
cana-3843	227	14	cart	cart	NOUN
cana-3843	227	15	85.29	85.29	NUM
cana-3843	227	16	[	[	X
cana-3843	227	17	29	29	NUM
cana-3843	227	18	]	]	X
cana-3843	227	19	snr	snr	NOUN
cana-3843	227	20	-	-	PUNCT
cana-3843	227	21	svm	svm	PROPN
cana-3843	227	22	75.6	75.6	NUM
cana-3843	227	23	[	[	SYM
cana-3843	227	24	30	30	NUM
cana-3843	227	25	]	]	X
cana-3843	227	26	pca	pca	PROPN
cana-3843	227	27	-	-	PUNCT
cana-3843	227	28	qda	qda	NOUN
cana-3843	227	29	82.4	82.4	NUM
cana-3843	227	30	[	[	X
cana-3843	227	31	31	31	NUM
cana-3843	227	32	]	]	SYM
cana-3843	227	33	mlp+mi	mlp+mi	X
cana-3843	227	34	67.6	67.6	NUM
cana-3843	227	35	[	[	X
cana-3843	227	36	32	32	NUM
cana-3843	227	37	]	]	PUNCT
cana-3843	227	38	lnndp	lnndp	NOUN
cana-3843	227	39	88.24	88.24	NUM
cana-3843	227	40	[	[	X
cana-3843	227	41	33	33	NUM
cana-3843	227	42	]	]	PUNCT
cana-3843	227	43	chi2_dt	chi2_dt	NOUN
cana-3843	227	44	74	74	NUM
cana-3843	227	45	[	[	SYM
cana-3843	227	46	34	34	NUM
cana-3843	227	47	]	]	PUNCT
cana-3843	227	48	dlfcc	dlfcc	PROPN
cana-3843	227	49	87	87	NUM
cana-3843	227	50	proposed	propose	VERB
cana-3843	227	51	method	method	PROPN
cana-3843	227	52	cor	cor	PROPN
cana-3843	227	53	-	-	PROPN
cana-3843	227	54	ga_snr	ga_snr	PROPN
cana-3843	227	55	-	-	PUNCT
cana-3843	227	56	lstm	lstm	PROPN
cana-3843	227	57	88.45	88.45	NUM
cana-3843	227	58	communications	communication	NOUN
cana-3843	227	59	on	on	ADP
cana-3843	227	60	applied	apply	VERB
cana-3843	227	61	nonlinear	nonlinear	ADJ
cana-3843	227	62	analysis	analysis	NOUN
cana-3843	227	63	issn	issn	NOUN
cana-3843	227	64	:	:	PUNCT
cana-3843	227	65	1074	1074	NUM
cana-3843	227	66	-	-	PUNCT
cana-3843	227	67	133x	133x	NUM
cana-3843	227	68	vol	vol	NOUN
cana-3843	227	69	32	32	NUM
cana-3843	227	70	no	no	NOUN
cana-3843	227	71	.	.	PUNCT
cana-3843	228	1	9s	9s	NUM
cana-3843	228	2	(	(	PUNCT
cana-3843	228	3	2025	2025	NUM
cana-3843	228	4	)	)	PUNCT
cana-3843	229	1	131	131	NUM
cana-3843	229	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	229	3	figure-7	figure-7	NUM
cana-3843	229	4	comparative	comparative	ADJ
cana-3843	229	5	analysis	analysis	NOUN
cana-3843	229	6	of	of	ADP
cana-3843	229	7	existing	exist	VERB
cana-3843	229	8	methods	method	NOUN
cana-3843	229	9	versus	versus	ADP
cana-3843	229	10	proposed	propose	VERB
cana-3843	229	11	method	method	NOUN
cana-3843	229	12	6	6	NUM
cana-3843	229	13	.	.	PUNCT
cana-3843	230	1	conclusions	conclusion	NOUN
cana-3843	230	2	leukemia	leukemia	NOUN
cana-3843	230	3	cancer	cancer	NOUN
cana-3843	230	4	is	be	AUX
cana-3843	230	5	one	one	NUM
cana-3843	230	6	of	of	ADP
cana-3843	230	7	the	the	DET
cana-3843	230	8	most	most	ADV
cana-3843	230	9	threatening	threatening	ADJ
cana-3843	230	10	and	and	CCONJ
cana-3843	230	11	devastating	devastating	ADJ
cana-3843	230	12	diseases	disease	NOUN
cana-3843	230	13	around	around	ADP
cana-3843	230	14	the	the	DET
cana-3843	230	15	world	world	NOUN
cana-3843	230	16	.	.	PUNCT
cana-3843	231	1	early	early	ADJ
cana-3843	231	2	and	and	CCONJ
cana-3843	231	3	accurate	accurate	ADJ
cana-3843	231	4	detection	detection	NOUN
cana-3843	231	5	of	of	ADP
cana-3843	231	6	leukemia	leukemia	NOUN
cana-3843	231	7	at	at	ADP
cana-3843	231	8	its	its	PRON
cana-3843	231	9	initial	initial	ADJ
cana-3843	231	10	stages	stage	NOUN
cana-3843	231	11	remains	remain	VERB
cana-3843	231	12	a	a	DET
cana-3843	231	13	significant	significant	ADJ
cana-3843	231	14	challenge	challenge	NOUN
cana-3843	231	15	in	in	ADP
cana-3843	231	16	the	the	DET
cana-3843	231	17	medical	medical	ADJ
cana-3843	231	18	field	field	NOUN
cana-3843	231	19	.	.	PUNCT
cana-3843	232	1	the	the	DET
cana-3843	232	2	research	research	NOUN
cana-3843	232	3	study	study	NOUN
cana-3843	232	4	proposes	propose	VERB
cana-3843	232	5	a	a	DET
cana-3843	232	6	method	method	NOUN
cana-3843	232	7	that	that	PRON
cana-3843	232	8	utilizes	utilize	VERB
cana-3843	232	9	microarray	microarray	NOUN
cana-3843	232	10	clinical	clinical	ADJ
cana-3843	232	11	gene	gene	NOUN
cana-3843	232	12	data	datum	NOUN
cana-3843	232	13	to	to	PART
cana-3843	232	14	identify	identify	VERB
cana-3843	232	15	leukemia	leukemia	NOUN
cana-3843	232	16	cancer	cancer	NOUN
cana-3843	232	17	.	.	PUNCT
cana-3843	233	1	in	in	ADP
cana-3843	233	2	the	the	DET
cana-3843	233	3	proposed	propose	VERB
cana-3843	233	4	method	method	NOUN
cana-3843	233	5	,	,	PUNCT
cana-3843	233	6	the	the	DET
cana-3843	233	7	gene	gene	NOUN
cana-3843	233	8	data	datum	NOUN
cana-3843	233	9	is	be	AUX
cana-3843	233	10	preprocessed	preprocesse	VERB
cana-3843	233	11	initially	initially	ADV
cana-3843	233	12	,	,	PUNCT
cana-3843	233	13	which	which	PRON
cana-3843	233	14	includes	include	VERB
cana-3843	233	15	handling	handle	VERB
cana-3843	233	16	missing	missing	ADJ
cana-3843	233	17	and	and	CCONJ
cana-3843	233	18	null	null	ADJ
cana-3843	233	19	values	value	NOUN
cana-3843	233	20	present	present	ADJ
cana-3843	233	21	in	in	ADP
cana-3843	233	22	the	the	DET
cana-3843	233	23	data	datum	NOUN
cana-3843	233	24	,	,	PUNCT
cana-3843	233	25	transforming	transform	VERB
cana-3843	233	26	categorical	categorical	ADJ
cana-3843	233	27	variables	variable	NOUN
cana-3843	233	28	into	into	ADP
cana-3843	233	29	numerical	numerical	ADJ
cana-3843	233	30	format	format	NOUN
cana-3843	233	31	through	through	ADP
cana-3843	233	32	the	the	DET
cana-3843	233	33	label	label	NOUN
cana-3843	233	34	encoding	encoding	NOUN
cana-3843	233	35	method	method	NOUN
cana-3843	233	36	,	,	PUNCT
cana-3843	233	37	and	and	CCONJ
cana-3843	233	38	applying	apply	VERB
cana-3843	233	39	min	min	PROPN
cana-3843	233	40	max	max	PROPN
cana-3843	233	41	normalization	normalization	NOUN
cana-3843	233	42	for	for	ADP
cana-3843	233	43	scaling	scale	VERB
cana-3843	233	44	the	the	DET
cana-3843	233	45	feature	feature	NOUN
cana-3843	233	46	transformation	transformation	NOUN
cana-3843	233	47	.	.	PUNCT
cana-3843	234	1	after	after	ADP
cana-3843	234	2	preprocessing	preprocesse	VERB
cana-3843	234	3	,	,	PUNCT
cana-3843	234	4	the	the	DET
cana-3843	234	5	multicollinearity	multicollinearity	NOUN
cana-3843	234	6	is	be	AUX
cana-3843	234	7	checked	check	VERB
cana-3843	234	8	,	,	PUNCT
cana-3843	234	9	and	and	CCONJ
cana-3843	234	10	genes	gene	NOUN
cana-3843	234	11	with	with	ADP
cana-3843	234	12	low	low	ADJ
cana-3843	234	13	intercorrelation	intercorrelation	NOUN
cana-3843	234	14	are	be	AUX
cana-3843	234	15	identified	identify	VERB
cana-3843	234	16	using	use	VERB
cana-3843	234	17	the	the	DET
cana-3843	234	18	karl	karl	PROPN
cana-3843	234	19	pearson	pearson	PROPN
cana-3843	234	20	correlation	correlation	PROPN
cana-3843	234	21	coefficient	coefficient	NOUN
cana-3843	234	22	.	.	PUNCT
cana-3843	235	1	after	after	ADP
cana-3843	235	2	that	that	PRON
cana-3843	235	3	,	,	PUNCT
cana-3843	235	4	the	the	DET
cana-3843	235	5	genetic	genetic	ADJ
cana-3843	235	6	optimization	optimization	NOUN
cana-3843	235	7	algorithm	algorithm	NOUN
cana-3843	235	8	combined	combine	VERB
cana-3843	235	9	with	with	ADP
cana-3843	235	10	the	the	DET
cana-3843	235	11	signal	signal	NOUN
cana-3843	235	12	to	to	PART
cana-3843	235	13	noise	noise	VERB
cana-3843	235	14	raio	raio	ADJ
cana-3843	235	15	method	method	NOUN
cana-3843	235	16	is	be	AUX
cana-3843	235	17	applied	apply	VERB
cana-3843	235	18	to	to	PART
cana-3843	235	19	select	select	VERB
cana-3843	235	20	an	an	DET
cana-3843	235	21	optimal	optimal	ADJ
cana-3843	235	22	set	set	NOUN
cana-3843	235	23	of	of	ADP
cana-3843	235	24	genes	gene	NOUN
cana-3843	235	25	in	in	ADP
cana-3843	235	26	the	the	DET
cana-3843	235	27	dataset	dataset	NOUN
cana-3843	235	28	while	while	SCONJ
cana-3843	235	29	eliminating	eliminate	VERB
cana-3843	235	30	noisy	noisy	ADJ
cana-3843	235	31	and	and	CCONJ
cana-3843	235	32	redundant	redundant	ADJ
cana-3843	235	33	genes	gene	NOUN
cana-3843	235	34	,	,	PUNCT
cana-3843	235	35	thereby	thereby	ADV
cana-3843	235	36	enhancing	enhance	VERB
cana-3843	235	37	classification	classification	NOUN
cana-3843	235	38	accuracy	accuracy	NOUN
cana-3843	235	39	.	.	PUNCT
cana-3843	236	1	in	in	ADP
cana-3843	236	2	the	the	DET
cana-3843	236	3	final	final	ADJ
cana-3843	236	4	phase	phase	NOUN
cana-3843	236	5	,	,	PUNCT
cana-3843	236	6	the	the	DET
cana-3843	236	7	selected	select	VERB
cana-3843	236	8	genes	gene	NOUN
cana-3843	236	9	are	be	AUX
cana-3843	236	10	classified	classify	VERB
cana-3843	236	11	using	use	VERB
cana-3843	236	12	a	a	DET
cana-3843	236	13	long	long	ADJ
cana-3843	236	14	short	short	ADJ
cana-3843	236	15	term	term	NOUN
cana-3843	236	16	memory	memory	NOUN
cana-3843	236	17	classifier	classifier	NOUN
cana-3843	236	18	.	.	PUNCT
cana-3843	237	1	the	the	DET
cana-3843	237	2	model	model	NOUN
cana-3843	237	3	's	's	PART
cana-3843	237	4	performance	performance	NOUN
cana-3843	237	5	is	be	AUX
cana-3843	237	6	evaluated	evaluate	VERB
cana-3843	237	7	using	use	VERB
cana-3843	237	8	various	various	ADJ
cana-3843	237	9	optimizers	optimizer	NOUN
cana-3843	237	10	,	,	PUNCT
cana-3843	237	11	including	include	VERB
cana-3843	237	12	adam	adam	PROPN
cana-3843	237	13	,	,	PUNCT
cana-3843	237	14	adagrad	adagrad	ADJ
cana-3843	237	15	,	,	PUNCT
cana-3843	237	16	rmsprop	rmsprop	NOUN
cana-3843	237	17	,	,	PUNCT
cana-3843	237	18	and	and	CCONJ
cana-3843	237	19	sgd	sgd	VERB
cana-3843	237	20	by	by	ADP
cana-3843	237	21	comparing	compare	VERB
cana-3843	237	22	accuracy	accuracy	NOUN
cana-3843	237	23	and	and	CCONJ
cana-3843	237	24	loss	loss	NOUN
cana-3843	237	25	values	value	NOUN
cana-3843	237	26	.	.	PUNCT
cana-3843	238	1	additionally	additionally	ADV
cana-3843	238	2	,	,	PUNCT
cana-3843	238	3	other	other	ADJ
cana-3843	238	4	classification	classification	NOUN
cana-3843	238	5	metrics	metric	NOUN
cana-3843	238	6	such	such	ADJ
cana-3843	238	7	as	as	ADP
cana-3843	238	8	precision	precision	NOUN
cana-3843	238	9	,	,	PUNCT
cana-3843	238	10	recall	recall	NOUN
cana-3843	238	11	,	,	PUNCT
cana-3843	238	12	and	and	CCONJ
cana-3843	238	13	f1	f1	ADJ
cana-3843	238	14	-	-	PUNCT
cana-3843	238	15	score	score	NOUN
cana-3843	238	16	value	value	NOUN
cana-3843	238	17	are	be	AUX
cana-3843	238	18	calculated	calculate	VERB
cana-3843	238	19	.	.	PUNCT
cana-3843	239	1	finally	finally	ADV
cana-3843	239	2	,	,	PUNCT
cana-3843	239	3	comparative	comparative	ADJ
cana-3843	239	4	analyses	analysis	NOUN
cana-3843	239	5	of	of	ADP
cana-3843	239	6	these	these	DET
cana-3843	239	7	metrics	metric	NOUN
cana-3843	239	8	across	across	ADP
cana-3843	239	9	the	the	DET
cana-3843	239	10	optimizers	optimizer	NOUN
cana-3843	239	11	are	be	AUX
cana-3843	239	12	performed	perform	VERB
cana-3843	239	13	.	.	PUNCT
cana-3843	240	1	the	the	DET
cana-3843	240	2	experimental	experimental	ADJ
cana-3843	240	3	results	result	NOUN
cana-3843	240	4	demonstrated	demonstrate	VERB
cana-3843	240	5	that	that	SCONJ
cana-3843	240	6	the	the	DET
cana-3843	240	7	cor	cor	PROPN
cana-3843	240	8	-	-	PROPN
cana-3843	240	9	ga_snr	ga_snr	PROPN
cana-3843	240	10	-	-	PUNCT
cana-3843	240	11	lstm	lstm	PROPN
cana-3843	240	12	model	model	NOUN
cana-3843	240	13	effectively	effectively	ADV
cana-3843	240	14	identifies	identify	VERB
cana-3843	240	15	a	a	DET
cana-3843	240	16	prominent	prominent	ADJ
cana-3843	240	17	subset	subset	NOUN
cana-3843	240	18	of	of	ADP
cana-3843	240	19	biomarker	biomarker	NOUN
cana-3843	240	20	genes	gene	NOUN
cana-3843	240	21	,	,	PUNCT
cana-3843	240	22	enabling	enable	VERB
cana-3843	240	23	the	the	DET
cana-3843	240	24	lstm	lstm	PROPN
cana-3843	240	25	model	model	NOUN
cana-3843	240	26	to	to	PART
cana-3843	240	27	accurately	accurately	ADV
cana-3843	240	28	classify	classify	VERB
cana-3843	240	29	the	the	DET
cana-3843	240	30	gene	gene	NOUN
cana-3843	240	31	expressions	expression	NOUN
cana-3843	240	32	.	.	PUNCT
cana-3843	241	1	the	the	DET
cana-3843	241	2	research	research	NOUN
cana-3843	241	3	model	model	NOUN
cana-3843	241	4	obtained	obtain	VERB
cana-3843	241	5	an	an	DET
cana-3843	241	6	accuracy	accuracy	NOUN
cana-3843	241	7	of	of	ADP
cana-3843	241	8	88.45	88.45	NUM
cana-3843	241	9	%	%	NOUN
cana-3843	241	10	,	,	PUNCT
cana-3843	241	11	a	a	DET
cana-3843	241	12	precision	precision	NOUN
cana-3843	241	13	score	score	NOUN
cana-3843	241	14	of	of	ADP
cana-3843	241	15	87	87	NUM
cana-3843	241	16	%	%	NOUN
cana-3843	241	17	,	,	PUNCT
cana-3843	241	18	and	and	CCONJ
cana-3843	241	19	a	a	DET
cana-3843	241	20	loss	loss	NOUN
cana-3843	241	21	rate	rate	NOUN
cana-3843	241	22	of	of	ADP
cana-3843	241	23	0.1612	0.1612	NUM
cana-3843	241	24	using	use	VERB
cana-3843	241	25	the	the	DET
cana-3843	241	26	adam	adam	PROPN
cana-3843	241	27	optimizer	optimizer	NOUN
cana-3843	241	28	.	.	PUNCT
cana-3843	242	1	in	in	ADP
cana-3843	242	2	future	future	ADJ
cana-3843	242	3	research	research	NOUN
cana-3843	242	4	,	,	PUNCT
cana-3843	242	5	different	different	ADJ
cana-3843	242	6	optimization	optimization	NOUN
cana-3843	242	7	techniques	technique	NOUN
cana-3843	242	8	can	can	AUX
cana-3843	242	9	be	be	AUX
cana-3843	242	10	implemented	implement	VERB
cana-3843	242	11	to	to	PART
cana-3843	242	12	further	far	ADV
cana-3843	242	13	enhance	enhance	VERB
cana-3843	242	14	the	the	DET
cana-3843	242	15	classification	classification	NOUN
cana-3843	242	16	outcomes	outcome	NOUN
cana-3843	242	17	.	.	PUNCT
cana-3843	243	1	references	reference	NOUN
cana-3843	243	2	[	[	X
cana-3843	243	3	1	1	NUM
cana-3843	243	4	]	]	X
cana-3843	243	5	kubota	kubota	PROPN
cana-3843	243	6	,	,	PUNCT
cana-3843	243	7	yasuo	yasuo	PROPN
cana-3843	243	8	,	,	PUNCT
cana-3843	243	9	misam	misam	PROPN
cana-3843	243	10	zawit	zawit	PROPN
cana-3843	243	11	,	,	PUNCT
cana-3843	243	12	jibran	jibran	PROPN
cana-3843	243	13	durrani	durrani	PROPN
cana-3843	243	14	,	,	PUNCT
cana-3843	243	15	wenyi	wenyi	PROPN
cana-3843	243	16	shen	shen	PROPN
cana-3843	243	17	,	,	PUNCT
cana-3843	243	18	waled	waled	PROPN
cana-3843	243	19	bahaj	bahaj	PROPN
cana-3843	243	20	,	,	PUNCT
cana-3843	243	21	tariq	tariq	PROPN
cana-3843	243	22	kewan	kewan	PROPN
cana-3843	243	23	,	,	PUNCT
cana-3843	243	24	ben	ben	PROPN
cana-3843	243	25	ponvilawan	ponvilawan	PROPN
cana-3843	243	26	et	et	PROPN
cana-3843	243	27	al	al	PROPN
cana-3843	243	28	.	.	PUNCT
cana-3843	244	1	"	"	PUNCT
cana-3843	244	2	significance	significance	NOUN
cana-3843	244	3	of	of	ADP
cana-3843	244	4	hereditary	hereditary	ADJ
cana-3843	244	5	gene	gene	NOUN
cana-3843	244	6	alterations	alteration	NOUN
cana-3843	244	7	for	for	ADP
cana-3843	244	8	the	the	DET
cana-3843	244	9	pathogenesis	pathogenesis	NOUN
cana-3843	244	10	of	of	ADP
cana-3843	244	11	adult	adult	NOUN
cana-3843	244	12	bone	bone	NOUN
cana-3843	244	13	marrow	marrow	NOUN
cana-3843	244	14	failure	failure	NOUN
cana-3843	244	15	versus	versus	ADP
cana-3843	244	16	myeloid	myeloid	ADJ
cana-3843	244	17	neoplasia	neoplasia	NOUN
cana-3843	244	18	.	.	PUNCT
cana-3843	244	19	"	"	PUNCT
cana-3843	245	1	leukemia	leukemia	NOUN
cana-3843	245	2	36	36	NUM
cana-3843	245	3	,	,	PUNCT
cana-3843	245	4	no	no	INTJ
cana-3843	245	5	.	.	PROPN
cana-3843	245	6	12	12	NUM
cana-3843	245	7	(	(	PUNCT
cana-3843	245	8	2022	2022	NUM
cana-3843	245	9	):	):	PUNCT
cana-3843	245	10	2827	2827	NUM
cana-3843	245	11	-	-	SYM
cana-3843	245	12	2834	2834	NUM
cana-3843	245	13	.	.	PUNCT
cana-3843	246	1	[	[	X
cana-3843	246	2	2	2	NUM
cana-3843	246	3	]	]	X
cana-3843	246	4	liu	liu	PROPN
cana-3843	246	5	,	,	PUNCT
cana-3843	246	6	li	li	PROPN
cana-3843	246	7	,	,	PUNCT
cana-3843	246	8	alex	alex	PROPN
cana-3843	246	9	yick	yick	PROPN
cana-3843	246	10	-	-	PUNCT
cana-3843	246	11	lun	lun	PROPN
cana-3843	247	1	so	so	ADV
cana-3843	247	2	,	,	PUNCT
cana-3843	247	3	and	and	CCONJ
cana-3843	247	4	jian	jian	ADJ
cana-3843	247	5	-	-	PUNCT
cana-3843	247	6	bing	bing	VERB
cana-3843	247	7	fan	fan	NOUN
cana-3843	247	8	.	.	PUNCT
cana-3843	248	1	"	"	PUNCT
cana-3843	248	2	analysis	analysis	NOUN
cana-3843	248	3	of	of	ADP
cana-3843	248	4	cancer	cancer	NOUN
cana-3843	248	5	genomes	genome	NOUN
cana-3843	248	6	through	through	ADP
cana-3843	248	7	microarrays	microarray	NOUN
cana-3843	248	8	and	and	CCONJ
cana-3843	248	9	next	next	ADJ
cana-3843	248	10	-	-	PUNCT
cana-3843	248	11	generation	generation	NOUN
cana-3843	248	12	sequencing	sequencing	NOUN
cana-3843	248	13	.	.	PUNCT
cana-3843	248	14	"	"	PUNCT
cana-3843	249	1	translational	translational	ADJ
cana-3843	249	2	cancer	cancer	NOUN
cana-3843	249	3	research	research	NOUN
cana-3843	249	4	4	4	NUM
cana-3843	249	5	,	,	PUNCT
cana-3843	249	6	no	no	INTJ
cana-3843	249	7	.	.	NOUN
cana-3843	249	8	3	3	NUM
cana-3843	249	9	(	(	PUNCT
cana-3843	249	10	2015	2015	NUM
cana-3843	249	11	)	)	PUNCT
cana-3843	249	12	.	.	PUNCT
cana-3843	250	1	communications	communication	NOUN
cana-3843	250	2	on	on	ADP
cana-3843	250	3	applied	apply	VERB
cana-3843	250	4	nonlinear	nonlinear	ADJ
cana-3843	250	5	analysis	analysis	NOUN
cana-3843	250	6	issn	issn	NOUN
cana-3843	250	7	:	:	PUNCT
cana-3843	250	8	1074	1074	NUM
cana-3843	250	9	-	-	PUNCT
cana-3843	250	10	133x	133x	NUM
cana-3843	250	11	vol	vol	NOUN
cana-3843	250	12	32	32	NUM
cana-3843	250	13	no	no	NOUN
cana-3843	250	14	.	.	PUNCT
cana-3843	251	1	9s	9s	NUM
cana-3843	251	2	(	(	PUNCT
cana-3843	251	3	2025	2025	NUM
cana-3843	251	4	)	)	PUNCT
cana-3843	251	5	132	132	NUM
cana-3843	251	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	252	1	[	[	X
cana-3843	252	2	3	3	NUM
cana-3843	252	3	]	]	PUNCT
cana-3843	252	4	ehigie	ehigie	NOUN
cana-3843	252	5	,	,	PUNCT
cana-3843	252	6	adeola	adeola	PROPN
cana-3843	252	7	folashade	folashade	PROPN
cana-3843	252	8	,	,	PUNCT
cana-3843	252	9	fiyinfoluwa	fiyinfoluwa	ADJ
cana-3843	252	10	demilade	demilade	NOUN
cana-3843	252	11	ojeniyi	ojeniyi	PROPN
cana-3843	252	12	,	,	PUNCT
cana-3843	252	13	adetayo	adetayo	PROPN
cana-3843	252	14	aborisade	aborisade	PROPN
cana-3843	252	15	,	,	PUNCT
cana-3843	252	16	james	james	PROPN
cana-3843	252	17	busayo	busayo	PROPN
cana-3843	252	18	agboola	agboola	PROPN
cana-3843	252	19	,	,	PUNCT
cana-3843	252	20	and	and	CCONJ
cana-3843	252	21	leonard	leonard	PROPN
cana-3843	252	22	ehigie	ehigie	PROPN
cana-3843	252	23	.	.	PUNCT
cana-3843	253	1	"	"	PUNCT
cana-3843	253	2	transcriptomic	transcriptomic	ADJ
cana-3843	253	3	analysis	analysis	NOUN
cana-3843	253	4	of	of	ADP
cana-3843	253	5	differential	differential	ADJ
cana-3843	253	6	gene	gene	NOUN
cana-3843	253	7	expression	expression	NOUN
cana-3843	253	8	in	in	ADP
cana-3843	253	9	staphylococcus	staphylococcus	NOUN
cana-3843	253	10	aureus	aureus	NOUN
cana-3843	253	11	-	-	PUNCT
cana-3843	253	12	induced	induce	VERB
cana-3843	253	13	pneumonia	pneumonia	NOUN
cana-3843	253	14	in	in	ADP
cana-3843	253	15	pediatrics	pediatric	NOUN
cana-3843	253	16	based	base	VERB
cana-3843	253	17	on	on	ADP
cana-3843	253	18	microarray	microarray	NOUN
cana-3843	253	19	analysis	analysis	NOUN
cana-3843	253	20	.	.	PUNCT
cana-3843	253	21	"	"	PUNCT
cana-3843	254	1	(	(	PUNCT
cana-3843	254	2	2022	2022	NUM
cana-3843	254	3	)	)	PUNCT
cana-3843	254	4	.	.	PUNCT
cana-3843	255	1	[	[	X
cana-3843	255	2	4	4	NUM
cana-3843	255	3	]	]	SYM
cana-3843	255	4	hambali	hambali	PROPN
cana-3843	255	5	,	,	PUNCT
cana-3843	255	6	moshood	moshood	NOUN
cana-3843	255	7	a.	a.	PROPN
cana-3843	255	8	,	,	PUNCT
cana-3843	255	9	tinuke	tinuke	PROPN
cana-3843	255	10	o.	o.	PROPN
cana-3843	255	11	oladele	oladele	PROPN
cana-3843	255	12	,	,	PUNCT
cana-3843	255	13	and	and	CCONJ
cana-3843	255	14	kayode	kayode	PROPN
cana-3843	255	15	s.	s.	PROPN
cana-3843	255	16	adewole	adewole	PROPN
cana-3843	255	17	.	.	PUNCT
cana-3843	256	1	"	"	PUNCT
cana-3843	256	2	microarray	microarray	NOUN
cana-3843	256	3	cancer	cancer	NOUN
cana-3843	256	4	feature	feature	NOUN
cana-3843	256	5	selection	selection	NOUN
cana-3843	256	6	:	:	PUNCT
cana-3843	256	7	review	review	NOUN
cana-3843	256	8	,	,	PUNCT
cana-3843	256	9	challenges	challenge	NOUN
cana-3843	256	10	and	and	CCONJ
cana-3843	256	11	research	research	NOUN
cana-3843	256	12	directions	direction	NOUN
cana-3843	256	13	.	.	PUNCT
cana-3843	256	14	"	"	PUNCT
cana-3843	257	1	international	international	ADJ
cana-3843	257	2	journal	journal	NOUN
cana-3843	257	3	of	of	ADP
cana-3843	257	4	cognitive	cognitive	ADJ
cana-3843	257	5	computing	computing	NOUN
cana-3843	257	6	in	in	ADP
cana-3843	257	7	engineering	engineering	NOUN
cana-3843	257	8	1	1	NUM
cana-3843	257	9	(	(	PUNCT
cana-3843	257	10	2020	2020	NUM
cana-3843	257	11	):	):	PUNCT
cana-3843	257	12	78	78	NUM
cana-3843	257	13	-	-	SYM
cana-3843	257	14	97	97	NUM
cana-3843	257	15	.	.	PUNCT
cana-3843	258	1	[	[	X
cana-3843	258	2	5	5	NUM
cana-3843	258	3	]	]	PUNCT
cana-3843	258	4	alshareef	alshareef	VERB
cana-3843	258	5	,	,	PUNCT
cana-3843	258	6	abdulrhman	abdulrhman	NOUN
cana-3843	258	7	m.	m.	NOUN
cana-3843	258	8	,	,	PUNCT
cana-3843	258	9	raed	raed	PROPN
cana-3843	258	10	alsini	alsini	PROPN
cana-3843	258	11	,	,	PUNCT
cana-3843	258	12	mohammed	mohammed	PROPN
cana-3843	258	13	alsieni	alsieni	PROPN
cana-3843	258	14	,	,	PUNCT
cana-3843	258	15	fadwa	fadwa	NOUN
cana-3843	258	16	alrowais	alrowais	PROPN
cana-3843	258	17	,	,	PUNCT
cana-3843	258	18	radwa	radwa	VERB
cana-3843	258	19	marzouk	marzouk	ADV
cana-3843	258	20	,	,	PUNCT
cana-3843	258	21	ibrahim	ibrahim	PROPN
cana-3843	258	22	abunadi	abunadi	NOUN
cana-3843	258	23	,	,	PUNCT
cana-3843	258	24	and	and	CCONJ
cana-3843	258	25	nadhem	nadhem	NOUN
cana-3843	258	26	nemri	nemri	ADJ
cana-3843	258	27	.	.	PUNCT
cana-3843	259	1	"	"	PUNCT
cana-3843	259	2	optimal	optimal	ADJ
cana-3843	259	3	deep	deep	ADJ
cana-3843	259	4	learning	learning	NOUN
cana-3843	259	5	enabled	enable	VERB
cana-3843	259	6	prostate	prostate	NOUN
cana-3843	259	7	cancer	cancer	NOUN
cana-3843	259	8	detection	detection	NOUN
cana-3843	259	9	using	use	VERB
cana-3843	259	10	microarray	microarray	NOUN
cana-3843	259	11	gene	gene	NOUN
cana-3843	259	12	expression	expression	NOUN
cana-3843	259	13	.	.	PUNCT
cana-3843	259	14	"	"	PUNCT
cana-3843	260	1	journal	journal	NOUN
cana-3843	260	2	of	of	ADP
cana-3843	260	3	healthcare	healthcare	PROPN
cana-3843	260	4	engineering	engineer	VERB
cana-3843	260	5	2022	2022	NUM
cana-3843	260	6	,	,	PUNCT
cana-3843	260	7	no	no	INTJ
cana-3843	260	8	.	.	NOUN
cana-3843	260	9	1	1	NUM
cana-3843	260	10	(	(	PUNCT
cana-3843	260	11	2022	2022	NUM
cana-3843	260	12	):	):	PUNCT
cana-3843	260	13	7364704	7364704	NUM
cana-3843	260	14	.	.	PUNCT
cana-3843	261	1	[	[	X
cana-3843	261	2	6	6	NUM
cana-3843	261	3	]	]	SYM
cana-3843	261	4	ogunbiyi	ogunbiyi	PROPN
cana-3843	261	5	,	,	PUNCT
cana-3843	261	6	temitope	temitope	NOUN
cana-3843	261	7	,	,	PUNCT
cana-3843	261	8	michael	michael	PROPN
cana-3843	261	9	adegoke	adegoke	VERB
cana-3843	261	10	,	,	PUNCT
cana-3843	261	11	adebisi	adebisi	ADJ
cana-3843	261	12	oluwatosin	oluwatosin	NOUN
cana-3843	261	13	,	,	PUNCT
cana-3843	261	14	bamidele	bamidele	PROPN
cana-3843	261	15	aremo	aremo	PROPN
cana-3843	261	16	,	,	PUNCT
cana-3843	261	17	olufemi	olufemi	ADJ
cana-3843	261	18	adekunle	adekunle	NOUN
cana-3843	261	19	,	,	PUNCT
cana-3843	261	20	emmanuel	emmanuel	PROPN
cana-3843	261	21	ayoariyo	ayoariyo	PROPN
cana-3843	261	22	,	,	PUNCT
cana-3843	261	23	and	and	CCONJ
cana-3843	261	24	austin	austin	PROPN
cana-3843	261	25	udemba	udemba	NOUN
cana-3843	261	26	.	.	PUNCT
cana-3843	262	1	"	"	PUNCT
cana-3843	262	2	improving	improve	VERB
cana-3843	262	3	acute	acute	ADJ
cana-3843	262	4	leukemia	leukemia	NOUN
cana-3843	262	5	classification	classification	NOUN
cana-3843	262	6	through	through	ADP
cana-3843	262	7	recursive	recursive	ADJ
cana-3843	262	8	feature	feature	NOUN
cana-3843	262	9	elimination	elimination	NOUN
cana-3843	262	10	and	and	CCONJ
cana-3843	262	11	multilayer	multilayer	ADJ
cana-3843	262	12	perceptron	perceptron	PROPN
cana-3843	262	13	analysis	analysis	NOUN
cana-3843	262	14	of	of	ADP
cana-3843	262	15	gene	gene	NOUN
cana-3843	262	16	expression	expression	NOUN
cana-3843	262	17	data	datum	NOUN
cana-3843	262	18	.	.	PUNCT
cana-3843	262	19	"	"	PUNCT
cana-3843	263	1	international	international	ADJ
cana-3843	263	2	journal	journal	NOUN
cana-3843	263	3	of	of	ADP
cana-3843	263	4	data	datum	NOUN
cana-3843	263	5	science	science	NOUN
cana-3843	263	6	5	5	NUM
cana-3843	263	7	,	,	PUNCT
cana-3843	263	8	no	no	INTJ
cana-3843	263	9	.	.	NOUN
cana-3843	263	10	1	1	NUM
cana-3843	263	11	(	(	PUNCT
cana-3843	263	12	2024	2024	NUM
cana-3843	263	13	):	):	PUNCT
cana-3843	263	14	33	33	NUM
cana-3843	263	15	-	-	SYM
cana-3843	263	16	49	49	NUM
cana-3843	263	17	.	.	PUNCT
cana-3843	264	1	[	[	X
cana-3843	264	2	7	7	NUM
cana-3843	264	3	]	]	X
cana-3843	264	4	ali	ali	PROPN
cana-3843	264	5	,	,	PUNCT
cana-3843	264	6	waleed	waleed	PROPN
cana-3843	264	7	,	,	PUNCT
cana-3843	264	8	and	and	CCONJ
cana-3843	264	9	faisal	faisal	PROPN
cana-3843	264	10	saeed	saeed	PROPN
cana-3843	264	11	.	.	PUNCT
cana-3843	265	1	"	"	PUNCT
cana-3843	265	2	hybrid	hybrid	ADJ
cana-3843	265	3	filter	filter	NOUN
cana-3843	265	4	and	and	CCONJ
cana-3843	265	5	genetic	genetic	ADJ
cana-3843	265	6	algorithm	algorithm	NOUN
cana-3843	265	7	-	-	PUNCT
cana-3843	265	8	based	base	VERB
cana-3843	265	9	feature	feature	NOUN
cana-3843	265	10	selection	selection	NOUN
cana-3843	265	11	for	for	ADP
cana-3843	265	12	improving	improve	VERB
cana-3843	265	13	cancer	cancer	NOUN
cana-3843	265	14	classification	classification	NOUN
cana-3843	265	15	in	in	ADP
cana-3843	265	16	high	high	ADJ
cana-3843	265	17	-	-	PUNCT
cana-3843	265	18	dimensional	dimensional	ADJ
cana-3843	265	19	microarray	microarray	NOUN
cana-3843	265	20	data	datum	NOUN
cana-3843	265	21	.	.	PUNCT
cana-3843	265	22	"	"	PUNCT
cana-3843	266	1	processes	process	VERB
cana-3843	266	2	11	11	NUM
cana-3843	266	3	,	,	PUNCT
cana-3843	266	4	no	no	INTJ
cana-3843	266	5	.	.	NOUN
cana-3843	266	6	2	2	NUM
cana-3843	266	7	(	(	PUNCT
cana-3843	266	8	2023	2023	NUM
cana-3843	266	9	):	):	PUNCT
cana-3843	266	10	562	562	NUM
cana-3843	266	11	.	.	PUNCT
cana-3843	267	1	[	[	X
cana-3843	267	2	8	8	NUM
cana-3843	267	3	]	]	SYM
cana-3843	267	4	rostami	rostami	NOUN
cana-3843	267	5	,	,	PUNCT
cana-3843	267	6	mehrdad	mehrdad	PROPN
cana-3843	267	7	,	,	PUNCT
cana-3843	267	8	kamal	kamal	PROPN
cana-3843	267	9	berahmand	berahmand	PROPN
cana-3843	267	10	,	,	PUNCT
cana-3843	267	11	and	and	CCONJ
cana-3843	267	12	saman	saman	PROPN
cana-3843	267	13	forouzandeh	forouzandeh	PROPN
cana-3843	267	14	.	.	PUNCT
cana-3843	268	1	"	"	PUNCT
cana-3843	268	2	a	a	DET
cana-3843	268	3	novel	novel	ADJ
cana-3843	268	4	community	community	NOUN
cana-3843	268	5	detection	detection	NOUN
cana-3843	268	6	based	base	VERB
cana-3843	268	7	genetic	genetic	ADJ
cana-3843	268	8	algorithm	algorithm	NOUN
cana-3843	268	9	for	for	ADP
cana-3843	268	10	feature	feature	NOUN
cana-3843	268	11	selection	selection	NOUN
cana-3843	268	12	.	.	PUNCT
cana-3843	268	13	"	"	PUNCT
cana-3843	269	1	journal	journal	NOUN
cana-3843	269	2	of	of	ADP
cana-3843	269	3	big	big	ADJ
cana-3843	269	4	data	datum	NOUN
cana-3843	269	5	8	8	NUM
cana-3843	269	6	,	,	PUNCT
cana-3843	269	7	no	no	INTJ
cana-3843	269	8	.	.	NOUN
cana-3843	269	9	1	1	NUM
cana-3843	269	10	(	(	PUNCT
cana-3843	269	11	2021	2021	NUM
cana-3843	269	12	):	):	PUNCT
cana-3843	269	13	2	2	NUM
cana-3843	269	14	.	.	PUNCT
cana-3843	270	1	[	[	X
cana-3843	270	2	9	9	NUM
cana-3843	270	3	]	]	PUNCT
cana-3843	270	4	sayed	say	VERB
cana-3843	270	5	,	,	PUNCT
cana-3843	270	6	sabah	sabah	PROPN
cana-3843	270	7	,	,	PUNCT
cana-3843	270	8	mohammad	mohammad	PROPN
cana-3843	270	9	nassef	nassef	PROPN
cana-3843	270	10	,	,	PUNCT
cana-3843	270	11	amr	amr	PROPN
cana-3843	270	12	badr	badr	PROPN
cana-3843	270	13	,	,	PUNCT
cana-3843	270	14	and	and	CCONJ
cana-3843	270	15	ibrahim	ibrahim	PROPN
cana-3843	270	16	farag	farag	PROPN
cana-3843	270	17	.	.	PUNCT
cana-3843	271	1	"	"	PUNCT
cana-3843	271	2	a	a	DET
cana-3843	271	3	nested	nested	ADJ
cana-3843	271	4	genetic	genetic	ADJ
cana-3843	271	5	algorithm	algorithm	NOUN
cana-3843	271	6	for	for	ADP
cana-3843	271	7	feature	feature	NOUN
cana-3843	271	8	selection	selection	NOUN
cana-3843	271	9	in	in	ADP
cana-3843	271	10	high	high	ADJ
cana-3843	271	11	-	-	PUNCT
cana-3843	271	12	dimensional	dimensional	ADJ
cana-3843	271	13	cancer	cancer	NOUN
cana-3843	271	14	microarray	microarray	NOUN
cana-3843	271	15	datasets	dataset	NOUN
cana-3843	271	16	.	.	PUNCT
cana-3843	271	17	"	"	PUNCT
cana-3843	272	1	expert	expert	ADJ
cana-3843	272	2	systems	system	NOUN
cana-3843	272	3	with	with	ADP
cana-3843	272	4	applications	application	NOUN
cana-3843	272	5	121	121	NUM
cana-3843	272	6	(	(	PUNCT
cana-3843	272	7	2019	2019	NUM
cana-3843	272	8	):	):	PUNCT
cana-3843	272	9	233	233	NUM
cana-3843	272	10	-	-	SYM
cana-3843	272	11	243	243	NUM
cana-3843	272	12	.	.	PUNCT
cana-3843	273	1	[	[	X
cana-3843	273	2	10	10	NUM
cana-3843	273	3	]	]	X
cana-3843	273	4	lawrence	lawrence	PROPN
cana-3843	273	5	,	,	PUNCT
cana-3843	273	6	morolake	morolake	ADJ
cana-3843	273	7	oladayo	oladayo	NOUN
cana-3843	273	8	,	,	PUNCT
cana-3843	273	9	rasheed	rasheed	NOUN
cana-3843	273	10	gbenga	gbenga	PROPN
cana-3843	273	11	jimoh	jimoh	NOUN
cana-3843	273	12	,	,	PUNCT
cana-3843	273	13	and	and	CCONJ
cana-3843	273	14	waheed	waheed	PROPN
cana-3843	273	15	babatunde	babatunde	PROPN
cana-3843	273	16	yahya	yahya	PROPN
cana-3843	273	17	.	.	PUNCT
cana-3843	274	1	"	"	PUNCT
cana-3843	274	2	an	an	DET
cana-3843	274	3	efficient	efficient	ADJ
cana-3843	274	4	feature	feature	NOUN
cana-3843	274	5	selection	selection	NOUN
cana-3843	274	6	and	and	CCONJ
cana-3843	274	7	classification	classification	NOUN
cana-3843	274	8	system	system	NOUN
cana-3843	274	9	for	for	ADP
cana-3843	274	10	microarray	microarray	NOUN
cana-3843	274	11	cancer	cancer	NOUN
cana-3843	274	12	data	datum	NOUN
cana-3843	274	13	using	use	VERB
cana-3843	274	14	genetic	genetic	ADJ
cana-3843	274	15	algorithm	algorithm	NOUN
cana-3843	274	16	and	and	CCONJ
cana-3843	274	17	deep	deep	ADJ
cana-3843	274	18	belief	belief	NOUN
cana-3843	274	19	networks	network	NOUN
cana-3843	274	20	.	.	PUNCT
cana-3843	274	21	"	"	PUNCT
cana-3843	274	22	multimedia	multimedia	NOUN
cana-3843	274	23	tools	tool	NOUN
cana-3843	274	24	and	and	CCONJ
cana-3843	274	25	applications	application	NOUN
cana-3843	274	26	(	(	PUNCT
cana-3843	274	27	2024	2024	NUM
cana-3843	274	28	):	):	PUNCT
cana-3843	274	29	1	1	NUM
cana-3843	274	30	-	-	SYM
cana-3843	274	31	42	42	NUM
cana-3843	274	32	.	.	PUNCT
cana-3843	275	1	[	[	X
cana-3843	275	2	11	11	NUM
cana-3843	275	3	]	]	X
cana-3843	275	4	pragadeesh	pragadeesh	ADJ
cana-3843	275	5	,	,	PUNCT
cana-3843	275	6	c.	c.	PROPN
cana-3843	275	7	,	,	PUNCT
cana-3843	275	8	rohana	rohana	PROPN
cana-3843	275	9	jeyaraj	jeyaraj	PROPN
cana-3843	275	10	,	,	PUNCT
cana-3843	275	11	k.	k.	PROPN
cana-3843	275	12	siranjeevi	siranjeevi	PROPN
cana-3843	275	13	,	,	PUNCT
cana-3843	275	14	r.	r.	PROPN
cana-3843	275	15	abishek	abishek	PROPN
cana-3843	275	16	,	,	PUNCT
cana-3843	275	17	and	and	CCONJ
cana-3843	275	18	g.	g.	PROPN
cana-3843	275	19	jeyakumar	jeyakumar	PROPN
cana-3843	275	20	.	.	PUNCT
cana-3843	276	1	"	"	PUNCT
cana-3843	276	2	hybrid	hybrid	ADJ
cana-3843	276	3	feature	feature	NOUN
cana-3843	276	4	selection	selection	NOUN
cana-3843	276	5	using	use	VERB
cana-3843	276	6	micro	micro	ADJ
cana-3843	276	7	genetic	genetic	ADJ
cana-3843	276	8	algorithm	algorithm	NOUN
cana-3843	276	9	on	on	ADP
cana-3843	276	10	microarray	microarray	NOUN
cana-3843	276	11	gene	gene	NOUN
cana-3843	276	12	expression	expression	NOUN
cana-3843	276	13	data	datum	NOUN
cana-3843	276	14	.	.	PUNCT
cana-3843	276	15	"	"	PUNCT
cana-3843	277	1	journal	journal	NOUN
cana-3843	277	2	of	of	ADP
cana-3843	277	3	intelligent	intelligent	ADJ
cana-3843	277	4	&	&	CCONJ
cana-3843	277	5	fuzzy	fuzzy	ADJ
cana-3843	277	6	systems	system	NOUN
cana-3843	277	7	36	36	NUM
cana-3843	277	8	,	,	PUNCT
cana-3843	277	9	no	no	INTJ
cana-3843	277	10	.	.	NOUN
cana-3843	277	11	3	3	NUM
cana-3843	277	12	(	(	PUNCT
cana-3843	277	13	2019	2019	NUM
cana-3843	277	14	):	):	PUNCT
cana-3843	277	15	2241	2241	NUM
cana-3843	277	16	-	-	SYM
cana-3843	277	17	2246	2246	NUM
cana-3843	277	18	.	.	PUNCT
cana-3843	278	1	[	[	X
cana-3843	278	2	12	12	NUM
cana-3843	278	3	]	]	X
cana-3843	278	4	yuvaraj	yuvaraj	PROPN
cana-3843	278	5	,	,	PUNCT
cana-3843	278	6	v.	v.	PROPN
cana-3843	278	7	,	,	PUNCT
cana-3843	278	8	g.	g.	PROPN
cana-3843	278	9	pandiyan	pandiyan	PROPN
cana-3843	278	10	,	,	PUNCT
cana-3843	278	11	and	and	CCONJ
cana-3843	278	12	g.	g.	PROPN
cana-3843	278	13	purusothaman	purusothaman	NOUN
cana-3843	278	14	.	.	PUNCT
cana-3843	279	1	"	"	PUNCT
cana-3843	279	2	gene	gene	NOUN
cana-3843	279	3	selection	selection	NOUN
cana-3843	279	4	and	and	CCONJ
cana-3843	279	5	modified	modify	VERB
cana-3843	279	6	long	long	ADJ
cana-3843	279	7	short	short	ADJ
cana-3843	279	8	term	term	NOUN
cana-3843	279	9	memory	memory	NOUN
cana-3843	279	10	network	network	NOUN
cana-3843	279	11	based	base	VERB
cana-3843	279	12	lung	lung	NOUN
cana-3843	279	13	cancer	cancer	NOUN
cana-3843	279	14	classification	classification	NOUN
cana-3843	279	15	using	use	VERB
cana-3843	279	16	gene	gene	NOUN
cana-3843	279	17	expression	expression	NOUN
cana-3843	279	18	data	datum	NOUN
cana-3843	279	19	.	.	PUNCT
cana-3843	279	20	"	"	PUNCT
cana-3843	280	1	ictact	ictact	ADJ
cana-3843	280	2	journal	journal	NOUN
cana-3843	280	3	on	on	ADP
cana-3843	280	4	soft	soft	ADJ
cana-3843	280	5	computing	computing	NOUN
cana-3843	280	6	12	12	NUM
cana-3843	280	7	,	,	PUNCT
cana-3843	280	8	no	no	INTJ
cana-3843	280	9	.	.	NOUN
cana-3843	280	10	2	2	NUM
cana-3843	280	11	(	(	PUNCT
cana-3843	280	12	2022	2022	NUM
cana-3843	280	13	)	)	PUNCT
cana-3843	280	14	.	.	PUNCT
cana-3843	281	1	[	[	X
cana-3843	281	2	13	13	NUM
cana-3843	281	3	]	]	SYM
cana-3843	281	4	babichev	babichev	NOUN
cana-3843	281	5	,	,	PUNCT
cana-3843	281	6	sergii	sergii	NOUN
cana-3843	281	7	,	,	PUNCT
cana-3843	281	8	igor	igor	PROPN
cana-3843	281	9	liakh	liakh	PROPN
cana-3843	281	10	,	,	PUNCT
cana-3843	281	11	and	and	CCONJ
cana-3843	281	12	irina	irina	PROPN
cana-3843	281	13	kalinina	kalinina	PROPN
cana-3843	281	14	.	.	PUNCT
cana-3843	282	1	"	"	PUNCT
cana-3843	282	2	applying	apply	VERB
cana-3843	282	3	a	a	DET
cana-3843	282	4	recurrent	recurrent	ADJ
cana-3843	282	5	neural	neural	ADJ
cana-3843	282	6	network	network	NOUN
cana-3843	282	7	-	-	PUNCT
cana-3843	282	8	based	base	VERB
cana-3843	282	9	deep	deep	ADJ
cana-3843	282	10	learning	learning	NOUN
cana-3843	282	11	model	model	NOUN
cana-3843	282	12	for	for	ADP
cana-3843	282	13	gene	gene	NOUN
cana-3843	282	14	expression	expression	NOUN
cana-3843	282	15	data	datum	NOUN
cana-3843	282	16	classification	classification	NOUN
cana-3843	282	17	.	.	PUNCT
cana-3843	282	18	"	"	PUNCT
cana-3843	283	1	applied	apply	VERB
cana-3843	283	2	sciences	science	NOUN
cana-3843	283	3	13	13	NUM
cana-3843	283	4	,	,	PUNCT
cana-3843	283	5	no	no	INTJ
cana-3843	283	6	.	.	NOUN
cana-3843	283	7	21	21	NUM
cana-3843	283	8	(	(	PUNCT
cana-3843	283	9	2023	2023	NUM
cana-3843	283	10	):	):	PUNCT
cana-3843	283	11	11823	11823	NUM
cana-3843	283	12	.	.	PUNCT
cana-3843	284	1	[	[	X
cana-3843	284	2	14	14	NUM
cana-3843	284	3	]	]	X
cana-3843	284	4	wang	wang	PROPN
cana-3843	284	5	,	,	PUNCT
cana-3843	284	6	zixuan	zixuan	PROPN
cana-3843	284	7	,	,	PUNCT
cana-3843	284	8	yi	yi	PROPN
cana-3843	284	9	zhou	zhou	PROPN
cana-3843	284	10	,	,	PUNCT
cana-3843	284	11	tatsuya	tatsuya	PROPN
cana-3843	284	12	takagi	takagi	PROPN
cana-3843	284	13	,	,	PUNCT
cana-3843	284	14	jiangning	jiangning	NOUN
cana-3843	284	15	song	song	NOUN
cana-3843	284	16	,	,	PUNCT
cana-3843	284	17	yu	yu	PROPN
cana-3843	284	18	-	-	PROPN
cana-3843	284	19	shi	shi	PROPN
cana-3843	284	20	tian	tian	PROPN
cana-3843	284	21	,	,	PUNCT
cana-3843	284	22	and	and	CCONJ
cana-3843	284	23	tetsuo	tetsuo	PROPN
cana-3843	284	24	shibuya	shibuya	PROPN
cana-3843	284	25	.	.	PUNCT
cana-3843	285	1	"	"	PUNCT
cana-3843	285	2	genetic	genetic	ADJ
cana-3843	285	3	algorithm	algorithm	NOUN
cana-3843	285	4	-	-	PUNCT
cana-3843	285	5	based	base	VERB
cana-3843	285	6	feature	feature	NOUN
cana-3843	285	7	selection	selection	NOUN
cana-3843	285	8	with	with	ADP
cana-3843	285	9	manifold	manifold	ADJ
cana-3843	285	10	learning	learning	NOUN
cana-3843	285	11	for	for	ADP
cana-3843	285	12	cancer	cancer	NOUN
cana-3843	285	13	classification	classification	NOUN
cana-3843	285	14	using	use	VERB
cana-3843	285	15	microarray	microarray	NOUN
cana-3843	285	16	data	datum	NOUN
cana-3843	285	17	.	.	PUNCT
cana-3843	285	18	"	"	PUNCT
cana-3843	286	1	bmc	bmc	ADJ
cana-3843	286	2	bioinformatics	bioinformatic	NOUN
cana-3843	286	3	24	24	NUM
cana-3843	286	4	,	,	PUNCT
cana-3843	286	5	no	no	INTJ
cana-3843	286	6	.	.	NOUN
cana-3843	286	7	1	1	NUM
cana-3843	286	8	(	(	PUNCT
cana-3843	286	9	2023	2023	NUM
cana-3843	286	10	):	):	PUNCT
cana-3843	286	11	139	139	NUM
cana-3843	286	12	.	.	PUNCT
cana-3843	287	1	[	[	X
cana-3843	287	2	15	15	NUM
cana-3843	287	3	]	]	X
cana-3843	287	4	alabdulqader	alabdulqader	NOUN
cana-3843	287	5	,	,	PUNCT
cana-3843	287	6	ebtisam	ebtisam	PROPN
cana-3843	287	7	abdullah	abdullah	PROPN
cana-3843	287	8	,	,	PUNCT
cana-3843	287	9	aisha	aisha	PROPN
cana-3843	287	10	ahmed	ahmed	PROPN
cana-3843	287	11	alarfaj	alarfaj	PROPN
cana-3843	287	12	,	,	PUNCT
cana-3843	287	13	muhammad	muhammad	PROPN
cana-3843	287	14	umer	umer	PROPN
cana-3843	287	15	,	,	PUNCT
cana-3843	287	16	ala’abdulmajid	ala’abdulmajid	PROPN
cana-3843	287	17	eshmawi	eshmawi	PROPN
cana-3843	287	18	,	,	PUNCT
cana-3843	287	19	shtwai	shtwai	PROPN
cana-3843	287	20	alsubai	alsubai	PROPN
cana-3843	287	21	,	,	PUNCT
cana-3843	287	22	tai	tai	PROPN
cana-3843	287	23	-	-	PUNCT
cana-3843	287	24	hoon	hoon	NOUN
cana-3843	287	25	kim	kim	PROPN
cana-3843	287	26	,	,	PUNCT
cana-3843	287	27	and	and	CCONJ
cana-3843	287	28	imran	imran	PROPN
cana-3843	287	29	ashraf	ashraf	PROPN
cana-3843	287	30	.	.	PUNCT
cana-3843	288	1	"	"	PUNCT
cana-3843	288	2	improving	improve	VERB
cana-3843	288	3	prediction	prediction	NOUN
cana-3843	288	4	of	of	ADP
cana-3843	288	5	blood	blood	NOUN
cana-3843	288	6	cancer	cancer	NOUN
cana-3843	288	7	using	use	VERB
cana-3843	288	8	leukemia	leukemia	NOUN
cana-3843	288	9	microarray	microarray	NOUN
cana-3843	288	10	gene	gene	NOUN
cana-3843	288	11	data	datum	NOUN
cana-3843	288	12	and	and	CCONJ
cana-3843	288	13	chi2	chi2	NOUN
cana-3843	288	14	features	feature	NOUN
cana-3843	288	15	with	with	ADP
cana-3843	288	16	weighted	weight	VERB
cana-3843	288	17	convolutional	convolutional	ADJ
cana-3843	288	18	neural	neural	ADJ
cana-3843	288	19	network	network	NOUN
cana-3843	288	20	.	.	PUNCT
cana-3843	288	21	"	"	PUNCT
cana-3843	289	1	scientific	scientific	ADJ
cana-3843	289	2	reports	report	NOUN
cana-3843	289	3	14	14	NUM
cana-3843	289	4	,	,	PUNCT
cana-3843	289	5	no	no	INTJ
cana-3843	289	6	.	.	NOUN
cana-3843	289	7	1	1	NUM
cana-3843	289	8	(	(	PUNCT
cana-3843	289	9	2024	2024	NUM
cana-3843	289	10	):	):	PUNCT
cana-3843	289	11	15625	15625	NUM
cana-3843	289	12	.	.	PUNCT
cana-3843	290	1	communications	communication	NOUN
cana-3843	290	2	on	on	ADP
cana-3843	290	3	applied	apply	VERB
cana-3843	290	4	nonlinear	nonlinear	ADJ
cana-3843	290	5	analysis	analysis	NOUN
cana-3843	290	6	issn	issn	NOUN
cana-3843	290	7	:	:	PUNCT
cana-3843	290	8	1074	1074	NUM
cana-3843	290	9	-	-	PUNCT
cana-3843	290	10	133x	133x	NUM
cana-3843	290	11	vol	vol	NOUN
cana-3843	290	12	32	32	NUM
cana-3843	290	13	no	no	NOUN
cana-3843	290	14	.	.	PUNCT
cana-3843	291	1	9s	9s	NUM
cana-3843	291	2	(	(	PUNCT
cana-3843	291	3	2025	2025	NUM
cana-3843	291	4	)	)	PUNCT
cana-3843	291	5	133	133	NUM
cana-3843	291	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	292	1	[	[	X
cana-3843	292	2	16	16	NUM
cana-3843	292	3	]	]	X
cana-3843	292	4	mallick	mallick	PROPN
cana-3843	292	5	,	,	PUNCT
cana-3843	292	6	pradeep	pradeep	PROPN
cana-3843	292	7	kumar	kumar	PROPN
cana-3843	292	8	,	,	PUNCT
cana-3843	292	9	saumendra	saumendra	PROPN
cana-3843	292	10	kumar	kumar	PROPN
cana-3843	292	11	mohapatra	mohapatra	PROPN
cana-3843	292	12	,	,	PUNCT
cana-3843	292	13	gyoo	gyoo	NOUN
cana-3843	292	14	-	-	PUNCT
cana-3843	292	15	soo	soo	PROPN
cana-3843	292	16	chae	chae	PROPN
cana-3843	292	17	,	,	PUNCT
cana-3843	292	18	and	and	CCONJ
cana-3843	292	19	mihir	mihir	PROPN
cana-3843	292	20	narayan	narayan	PROPN
cana-3843	292	21	mohanty	mohanty	PROPN
cana-3843	292	22	.	.	PUNCT
cana-3843	293	1	"	"	PUNCT
cana-3843	293	2	convergent	convergent	ADJ
cana-3843	293	3	learning	learning	NOUN
cana-3843	293	4	–	–	PUNCT
cana-3843	293	5	based	base	VERB
cana-3843	293	6	model	model	NOUN
cana-3843	293	7	for	for	ADP
cana-3843	293	8	leukemia	leukemia	NOUN
cana-3843	293	9	classification	classification	NOUN
cana-3843	293	10	from	from	ADP
cana-3843	293	11	gene	gene	NOUN
cana-3843	293	12	expression	expression	NOUN
cana-3843	293	13	.	.	PUNCT
cana-3843	293	14	"	"	PUNCT
cana-3843	294	1	personal	personal	ADJ
cana-3843	294	2	and	and	CCONJ
cana-3843	294	3	ubiquitous	ubiquitous	ADJ
cana-3843	294	4	computing	computing	NOUN
cana-3843	294	5	27	27	NUM
cana-3843	294	6	,	,	PUNCT
cana-3843	294	7	no	no	INTJ
cana-3843	294	8	.	.	NOUN
cana-3843	294	9	3	3	NUM
cana-3843	294	10	(	(	PUNCT
cana-3843	294	11	2023	2023	NUM
cana-3843	294	12	):	):	PUNCT
cana-3843	294	13	1103	1103	NUM
cana-3843	294	14	-	-	SYM
cana-3843	294	15	1110	1110	NUM
cana-3843	294	16	.	.	PUNCT
cana-3843	295	1	[	[	X
cana-3843	295	2	17	17	NUM
cana-3843	295	3	]	]	X
cana-3843	295	4	sahu	sahu	PROPN
cana-3843	295	5	,	,	PUNCT
cana-3843	295	6	bibhuprasad	bibhuprasad	ADJ
cana-3843	295	7	,	,	PUNCT
cana-3843	295	8	and	and	CCONJ
cana-3843	295	9	sujata	sujata	ADJ
cana-3843	295	10	dash	dash	NOUN
cana-3843	295	11	.	.	PUNCT
cana-3843	296	1	"	"	PUNCT
cana-3843	296	2	hybrid	hybrid	ADJ
cana-3843	296	3	multifilter	multifilter	NOUN
cana-3843	296	4	ensemble	ensemble	ADJ
cana-3843	296	5	based	base	VERB
cana-3843	296	6	feature	feature	NOUN
cana-3843	296	7	selection	selection	NOUN
cana-3843	296	8	model	model	NOUN
cana-3843	296	9	from	from	ADP
cana-3843	296	10	microarray	microarray	NOUN
cana-3843	296	11	cancer	cancer	NOUN
cana-3843	296	12	datasets	dataset	NOUN
cana-3843	296	13	using	use	VERB
cana-3843	296	14	gwo	gwo	NOUN
cana-3843	296	15	with	with	ADP
cana-3843	296	16	deep	deep	ADJ
cana-3843	296	17	learning	learning	NOUN
cana-3843	296	18	.	.	PUNCT
cana-3843	296	19	"	"	PUNCT
cana-3843	297	1	in	in	ADP
cana-3843	297	2	2023	2023	NUM
cana-3843	297	3	3rd	3rd	ADJ
cana-3843	297	4	international	international	ADJ
cana-3843	297	5	conference	conference	NOUN
cana-3843	297	6	on	on	ADP
cana-3843	297	7	intelligent	intelligent	ADJ
cana-3843	297	8	technologies	technology	NOUN
cana-3843	297	9	(	(	PUNCT
cana-3843	297	10	conit	conit	NOUN
cana-3843	297	11	)	)	PUNCT
cana-3843	297	12	,	,	PUNCT
cana-3843	297	13	pp	pp	PROPN
cana-3843	297	14	.	.	PUNCT
cana-3843	297	15	1	1	NUM
cana-3843	297	16	-	-	SYM
cana-3843	297	17	6	6	NUM
cana-3843	297	18	.	.	PUNCT
cana-3843	297	19	ieee	ieee	NOUN
cana-3843	297	20	,	,	PUNCT
cana-3843	297	21	2023	2023	NUM
cana-3843	297	22	.	.	PUNCT
cana-3843	298	1	[	[	X
cana-3843	298	2	18	18	NUM
cana-3843	298	3	]	]	X
cana-3843	298	4	karim	karim	PROPN
cana-3843	298	5	,	,	PUNCT
cana-3843	298	6	abdul	abdul	PROPN
cana-3843	298	7	,	,	PUNCT
cana-3843	298	8	azhari	azhari	PROPN
cana-3843	298	9	azhari	azhari	PROPN
cana-3843	298	10	,	,	PUNCT
cana-3843	298	11	mobeen	mobeen	PROPN
cana-3843	298	12	shahroz	shahroz	PROPN
cana-3843	298	13	,	,	PUNCT
cana-3843	298	14	samir	samir	PROPN
cana-3843	298	15	brahim	brahim	PROPN
cana-3843	298	16	belhaouri	belhaouri	PROPN
cana-3843	298	17	,	,	PUNCT
cana-3843	298	18	and	and	CCONJ
cana-3843	298	19	khabib	khabib	PROPN
cana-3843	298	20	mustofa	mustofa	PROPN
cana-3843	298	21	.	.	PUNCT
cana-3843	299	1	"	"	PUNCT
cana-3843	299	2	ldsvm	ldsvm	NOUN
cana-3843	299	3	:	:	PUNCT
cana-3843	299	4	leukemia	leukemia	NOUN
cana-3843	299	5	cancer	cancer	NOUN
cana-3843	299	6	classification	classification	NOUN
cana-3843	299	7	using	use	VERB
cana-3843	299	8	machine	machine	NOUN
cana-3843	299	9	learning	learning	NOUN
cana-3843	299	10	.	.	PUNCT
cana-3843	299	11	"	"	PUNCT
cana-3843	300	1	(	(	PUNCT
cana-3843	300	2	2022	2022	NUM
cana-3843	300	3	)	)	PUNCT
cana-3843	300	4	.	.	PUNCT
cana-3843	301	1	[	[	X
cana-3843	301	2	19	19	NUM
cana-3843	301	3	]	]	SYM
cana-3843	301	4	ma’ruf	ma’ruf	NOUN
cana-3843	301	5	,	,	PUNCT
cana-3843	301	6	firda	firda	NOUN
cana-3843	301	7	aminy	aminy	NOUN
cana-3843	301	8	,	,	PUNCT
cana-3843	301	9	and	and	CCONJ
cana-3843	301	10	untari	untari	ADJ
cana-3843	301	11	novia	novia	PROPN
cana-3843	301	12	wisesty	wisesty	PROPN
cana-3843	301	13	.	.	PUNCT
cana-3843	302	1	"	"	PUNCT
cana-3843	302	2	analysis	analysis	NOUN
cana-3843	302	3	of	of	ADP
cana-3843	302	4	the	the	DET
cana-3843	302	5	influence	influence	NOUN
cana-3843	302	6	of	of	ADP
cana-3843	302	7	minimum	minimum	ADJ
cana-3843	302	8	redundancy	redundancy	NOUN
cana-3843	302	9	maximum	maximum	ADJ
cana-3843	302	10	relevance	relevance	NOUN
cana-3843	302	11	as	as	ADP
cana-3843	302	12	dimensionality	dimensionality	NOUN
cana-3843	302	13	reduction	reduction	NOUN
cana-3843	302	14	method	method	NOUN
cana-3843	302	15	on	on	ADP
cana-3843	302	16	cancer	cancer	NOUN
cana-3843	302	17	classification	classification	NOUN
cana-3843	302	18	based	base	VERB
cana-3843	302	19	on	on	ADP
cana-3843	302	20	microarray	microarray	NOUN
cana-3843	302	21	data	datum	NOUN
cana-3843	302	22	using	use	VERB
cana-3843	302	23	support	support	NOUN
cana-3843	302	24	vector	vector	NOUN
cana-3843	302	25	machine	machine	NOUN
cana-3843	302	26	classifier	classifier	NOUN
cana-3843	302	27	.	.	PUNCT
cana-3843	302	28	"	"	PUNCT
cana-3843	303	1	in	in	ADP
cana-3843	303	2	journal	journal	PROPN
cana-3843	303	3	of	of	ADP
cana-3843	303	4	physics	physics	PROPN
cana-3843	303	5	:	:	PUNCT
cana-3843	303	6	conference	conference	NOUN
cana-3843	303	7	series	series	NOUN
cana-3843	303	8	,	,	PUNCT
cana-3843	303	9	vol	vol	NOUN
cana-3843	303	10	.	.	PROPN
cana-3843	303	11	1192	1192	NUM
cana-3843	303	12	,	,	PUNCT
cana-3843	303	13	no	no	INTJ
cana-3843	303	14	.	.	NOUN
cana-3843	303	15	1	1	NUM
cana-3843	303	16	,	,	PUNCT
cana-3843	303	17	p.	p.	NOUN
cana-3843	303	18	012011	012011	NUM
cana-3843	303	19	.	.	PUNCT
cana-3843	304	1	iop	iop	NOUN
cana-3843	304	2	publishing	publishing	NOUN
cana-3843	304	3	,	,	PUNCT
cana-3843	304	4	2019	2019	NUM
cana-3843	304	5	.	.	PUNCT
cana-3843	305	1	[	[	X
cana-3843	305	2	20	20	NUM
cana-3843	305	3	]	]	SYM
cana-3843	305	4	tabassum	tabassum	NOUN
cana-3843	305	5	,	,	PUNCT
cana-3843	305	6	mujahid	mujahid	NOUN
cana-3843	305	7	,	,	PUNCT
cana-3843	305	8	and	and	CCONJ
cana-3843	305	9	kuruvilla	kuruvilla	PROPN
cana-3843	305	10	mathew	mathew	PROPN
cana-3843	305	11	.	.	PUNCT
cana-3843	306	1	"	"	PUNCT
cana-3843	306	2	a	a	DET
cana-3843	306	3	genetic	genetic	ADJ
cana-3843	306	4	algorithm	algorithm	NOUN
cana-3843	306	5	analysis	analysis	NOUN
cana-3843	306	6	towards	towards	ADP
cana-3843	306	7	optimization	optimization	NOUN
cana-3843	306	8	solutions	solution	NOUN
cana-3843	306	9	.	.	PUNCT
cana-3843	306	10	"	"	PUNCT
cana-3843	307	1	international	international	ADJ
cana-3843	307	2	journal	journal	NOUN
cana-3843	307	3	of	of	ADP
cana-3843	307	4	digital	digital	ADJ
cana-3843	307	5	information	information	NOUN
cana-3843	307	6	and	and	CCONJ
cana-3843	307	7	wireless	wireless	ADJ
cana-3843	307	8	communications	communication	NOUN
cana-3843	307	9	(	(	PUNCT
cana-3843	307	10	ijdiwc	ijdiwc	PROPN
cana-3843	307	11	)	)	PUNCT
cana-3843	307	12	4	4	NUM
cana-3843	307	13	,	,	PUNCT
cana-3843	307	14	no	no	INTJ
cana-3843	307	15	.	.	NOUN
cana-3843	307	16	1	1	NUM
cana-3843	307	17	(	(	PUNCT
cana-3843	307	18	2014	2014	NUM
cana-3843	307	19	):	):	PUNCT
cana-3843	307	20	124	124	NUM
cana-3843	307	21	-	-	SYM
cana-3843	307	22	142	142	NUM
cana-3843	307	23	.	.	PUNCT
cana-3843	308	1	[	[	X
cana-3843	308	2	21	21	NUM
cana-3843	308	3	]	]	X
cana-3843	308	4	deng	deng	PROPN
cana-3843	308	5	,	,	PUNCT
cana-3843	308	6	xiongshi	xiongshi	PROPN
cana-3843	308	7	,	,	PUNCT
cana-3843	308	8	min	min	PROPN
cana-3843	308	9	li	li	PROPN
cana-3843	308	10	,	,	PUNCT
cana-3843	308	11	shaobo	shaobo	PROPN
cana-3843	308	12	deng	deng	PROPN
cana-3843	308	13	,	,	PUNCT
cana-3843	308	14	and	and	CCONJ
cana-3843	308	15	lei	lei	PROPN
cana-3843	308	16	wang	wang	PROPN
cana-3843	308	17	.	.	PUNCT
cana-3843	309	1	"	"	PUNCT
cana-3843	309	2	hybrid	hybrid	ADJ
cana-3843	309	3	gene	gene	NOUN
cana-3843	309	4	selection	selection	NOUN
cana-3843	309	5	approach	approach	NOUN
cana-3843	309	6	using	use	VERB
cana-3843	309	7	xgboost	xgboost	ADV
cana-3843	309	8	and	and	CCONJ
cana-3843	309	9	multi	multi	ADJ
cana-3843	309	10	-	-	ADJ
cana-3843	309	11	objective	objective	ADJ
cana-3843	309	12	genetic	genetic	ADJ
cana-3843	309	13	algorithm	algorithm	NOUN
cana-3843	309	14	for	for	ADP
cana-3843	309	15	cancer	cancer	NOUN
cana-3843	309	16	classification	classification	NOUN
cana-3843	309	17	.	.	PUNCT
cana-3843	309	18	"	"	PUNCT
cana-3843	310	1	medical	medical	ADJ
cana-3843	310	2	&	&	CCONJ
cana-3843	310	3	biological	biological	ADJ
cana-3843	310	4	engineering	engineering	PROPN
cana-3843	310	5	&	&	CCONJ
cana-3843	310	6	computing	computing	PROPN
cana-3843	310	7	60	60	NUM
cana-3843	310	8	,	,	PUNCT
cana-3843	310	9	no	no	INTJ
cana-3843	310	10	.	.	NOUN
cana-3843	310	11	3	3	NUM
cana-3843	310	12	(	(	PUNCT
cana-3843	310	13	2022	2022	NUM
cana-3843	310	14	):	):	PUNCT
cana-3843	310	15	663	663	NUM
cana-3843	310	16	-	-	SYM
cana-3843	310	17	681	681	NUM
cana-3843	310	18	.	.	PUNCT
cana-3843	311	1	[	[	X
cana-3843	311	2	22	22	NUM
cana-3843	311	3	]	]	X
cana-3843	311	4	shukla	shukla	NOUN
cana-3843	311	5	,	,	PUNCT
cana-3843	311	6	alok	alok	PROPN
cana-3843	311	7	kumar	kumar	PROPN
cana-3843	311	8	,	,	PUNCT
cana-3843	311	9	pradeep	pradeep	PROPN
cana-3843	311	10	singh	singh	PROPN
cana-3843	311	11	,	,	PUNCT
cana-3843	311	12	and	and	CCONJ
cana-3843	311	13	manu	manu	PROPN
cana-3843	311	14	vardhan	vardhan	PROPN
cana-3843	311	15	.	.	PUNCT
cana-3843	312	1	"	"	PUNCT
cana-3843	312	2	a	a	DET
cana-3843	312	3	new	new	ADJ
cana-3843	312	4	hybrid	hybrid	ADJ
cana-3843	312	5	feature	feature	NOUN
cana-3843	312	6	subset	subset	VERB
cana-3843	312	7	selection	selection	NOUN
cana-3843	312	8	framework	framework	NOUN
cana-3843	312	9	based	base	VERB
cana-3843	312	10	on	on	ADP
cana-3843	312	11	binary	binary	ADJ
cana-3843	312	12	genetic	genetic	ADJ
cana-3843	312	13	algorithm	algorithm	NOUN
cana-3843	312	14	and	and	CCONJ
cana-3843	312	15	information	information	NOUN
cana-3843	312	16	theory	theory	NOUN
cana-3843	312	17	.	.	PUNCT
cana-3843	312	18	"	"	PUNCT
cana-3843	313	1	international	international	ADJ
cana-3843	313	2	journal	journal	NOUN
cana-3843	313	3	of	of	ADP
cana-3843	313	4	computational	computational	ADJ
cana-3843	313	5	intelligence	intelligence	NOUN
cana-3843	313	6	and	and	CCONJ
cana-3843	313	7	applications	application	NOUN
cana-3843	313	8	18	18	NUM
cana-3843	313	9	,	,	PUNCT
cana-3843	313	10	no	no	INTJ
cana-3843	313	11	.	.	NOUN
cana-3843	313	12	03	03	NUM
cana-3843	313	13	(	(	PUNCT
cana-3843	313	14	2019	2019	NUM
cana-3843	313	15	):	):	PUNCT
cana-3843	313	16	1950020	1950020	NUM
cana-3843	313	17	.	.	PUNCT
cana-3843	314	1	[	[	X
cana-3843	314	2	23	23	NUM
cana-3843	314	3	]	]	X
cana-3843	314	4	gupta	gupta	PROPN
cana-3843	314	5	,	,	PUNCT
cana-3843	314	6	surbhi	surbhi	NOUN
cana-3843	314	7	,	,	PUNCT
cana-3843	314	8	manoj	manoj	PROPN
cana-3843	314	9	k.	k.	PROPN
cana-3843	314	10	gupta	gupta	PROPN
cana-3843	314	11	,	,	PUNCT
cana-3843	314	12	mohammad	mohammad	PROPN
cana-3843	314	13	shabaz	shabaz	PROPN
cana-3843	314	14	,	,	PUNCT
cana-3843	314	15	and	and	CCONJ
cana-3843	314	16	ashutosh	ashutosh	PROPN
cana-3843	314	17	sharma	sharma	PROPN
cana-3843	314	18	.	.	PUNCT
cana-3843	315	1	"	"	PUNCT
cana-3843	315	2	deep	deep	ADJ
cana-3843	315	3	learning	learning	NOUN
cana-3843	315	4	techniques	technique	NOUN
cana-3843	315	5	for	for	ADP
cana-3843	315	6	cancer	cancer	NOUN
cana-3843	315	7	classification	classification	NOUN
cana-3843	315	8	using	use	VERB
cana-3843	315	9	microarray	microarray	NOUN
cana-3843	315	10	gene	gene	NOUN
cana-3843	315	11	expression	expression	NOUN
cana-3843	315	12	data	datum	NOUN
cana-3843	315	13	.	.	PUNCT
cana-3843	315	14	"	"	PUNCT
cana-3843	315	15	frontiers	frontier	NOUN
cana-3843	315	16	in	in	ADP
cana-3843	315	17	physiology	physiology	NOUN
cana-3843	315	18	13	13	NUM
cana-3843	315	19	(	(	PUNCT
cana-3843	315	20	2022	2022	NUM
cana-3843	315	21	):	):	PUNCT
cana-3843	315	22	952709	952709	NUM
cana-3843	315	23	.	.	PUNCT
cana-3843	316	1	[	[	X
cana-3843	316	2	24	24	NUM
cana-3843	316	3	]	]	SYM
cana-3843	316	4	aburass	aburass	NOUN
cana-3843	316	5	,	,	PUNCT
cana-3843	316	6	sanad	sanad	NOUN
cana-3843	316	7	,	,	PUNCT
cana-3843	316	8	osama	osama	NOUN
cana-3843	316	9	dorgham	dorgham	NOUN
cana-3843	316	10	,	,	PUNCT
cana-3843	316	11	and	and	CCONJ
cana-3843	316	12	jamil	jamil	PROPN
cana-3843	316	13	al	al	PROPN
cana-3843	316	14	shaqsi	shaqsi	PROPN
cana-3843	316	15	.	.	PUNCT
cana-3843	317	1	"	"	PUNCT
cana-3843	317	2	a	a	DET
cana-3843	317	3	hybrid	hybrid	ADJ
cana-3843	317	4	machine	machine	NOUN
cana-3843	317	5	learning	learning	NOUN
cana-3843	317	6	model	model	NOUN
cana-3843	317	7	for	for	ADP
cana-3843	317	8	classifying	classify	VERB
cana-3843	317	9	gene	gene	NOUN
cana-3843	317	10	mutations	mutation	NOUN
cana-3843	317	11	in	in	ADP
cana-3843	317	12	cancer	cancer	NOUN
cana-3843	317	13	using	use	VERB
cana-3843	317	14	lstm	lstm	NOUN
cana-3843	317	15	,	,	PUNCT
cana-3843	317	16	bilstm	bilstm	NOUN
cana-3843	317	17	,	,	PUNCT
cana-3843	317	18	cnn	cnn	PROPN
cana-3843	317	19	,	,	PUNCT
cana-3843	317	20	gru	gru	PROPN
cana-3843	317	21	,	,	PUNCT
cana-3843	317	22	and	and	CCONJ
cana-3843	317	23	glove	glove	NOUN
cana-3843	317	24	.	.	PUNCT
cana-3843	317	25	"	"	PUNCT
cana-3843	318	1	systems	system	NOUN
cana-3843	318	2	and	and	CCONJ
cana-3843	318	3	soft	soft	ADJ
cana-3843	318	4	computing	computing	NOUN
cana-3843	318	5	6	6	NUM
cana-3843	318	6	(	(	PUNCT
cana-3843	318	7	2024	2024	NUM
cana-3843	318	8	):	):	PUNCT
cana-3843	318	9	200110	200110	NUM
cana-3843	318	10	.	.	PUNCT
cana-3843	319	1	[	[	X
cana-3843	319	2	25	25	NUM
cana-3843	319	3	]	]	X
cana-3843	319	4	hasan	hasan	PROPN
cana-3843	319	5	,	,	PUNCT
cana-3843	319	6	abid	abid	PROPN
cana-3843	319	7	,	,	PUNCT
cana-3843	319	8	and	and	CCONJ
cana-3843	319	9	md	md	PROPN
cana-3843	319	10	akhtaruzzaman	akhtaruzzaman	PROPN
cana-3843	319	11	adnan	adnan	PROPN
cana-3843	319	12	.	.	PUNCT
cana-3843	320	1	"	"	PUNCT
cana-3843	320	2	high	high	ADJ
cana-3843	320	3	dimensional	dimensional	ADJ
cana-3843	320	4	microarray	microarray	NOUN
cana-3843	320	5	data	data	NOUN
cana-3843	320	6	classification	classification	NOUN
cana-3843	320	7	using	use	VERB
cana-3843	320	8	correlation	correlation	NOUN
cana-3843	320	9	based	base	VERB
cana-3843	320	10	feature	feature	NOUN
cana-3843	320	11	selection	selection	NOUN
cana-3843	320	12	.	.	PUNCT
cana-3843	320	13	"	"	PUNCT
cana-3843	321	1	in	in	ADP
cana-3843	321	2	2012	2012	NUM
cana-3843	321	3	international	international	ADJ
cana-3843	321	4	conference	conference	NOUN
cana-3843	321	5	on	on	ADP
cana-3843	321	6	biomedical	biomedical	ADJ
cana-3843	321	7	engineering	engineering	NOUN
cana-3843	321	8	(	(	PUNCT
cana-3843	321	9	icobe	icobe	PROPN
cana-3843	321	10	)	)	PUNCT
cana-3843	321	11	,	,	PUNCT
cana-3843	321	12	pp	pp	ADP
cana-3843	321	13	.	.	PUNCT
cana-3843	322	1	319	319	NUM
cana-3843	322	2	-	-	SYM
cana-3843	322	3	321	321	NUM
cana-3843	322	4	.	.	PUNCT
cana-3843	323	1	ieee	ieee	NOUN
cana-3843	323	2	,	,	PUNCT
cana-3843	323	3	2012	2012	NUM
cana-3843	323	4	.	.	PUNCT
cana-3843	324	1	[	[	X
cana-3843	324	2	26	26	NUM
cana-3843	324	3	]	]	X
cana-3843	324	4	rezaee	rezaee	PROPN
cana-3843	324	5	,	,	PUNCT
cana-3843	324	6	khosro	khosro	PROPN
cana-3843	324	7	,	,	PUNCT
cana-3843	324	8	gwanggil	gwanggil	PROPN
cana-3843	324	9	jeon	jeon	PROPN
cana-3843	324	10	,	,	PUNCT
cana-3843	324	11	mohammad	mohammad	PROPN
cana-3843	324	12	r.	r.	PROPN
cana-3843	324	13	khosravi	khosravi	PROPN
cana-3843	324	14	,	,	PUNCT
cana-3843	324	15	hani	hani	PROPN
cana-3843	324	16	h.	h.	PROPN
cana-3843	324	17	attar	attar	PROPN
cana-3843	324	18	,	,	PUNCT
cana-3843	324	19	and	and	CCONJ
cana-3843	324	20	alireza	alireza	PROPN
cana-3843	324	21	sabzevari	sabzevari	PROPN
cana-3843	324	22	.	.	PUNCT
cana-3843	325	1	"	"	PUNCT
cana-3843	325	2	deep	deep	ADJ
cana-3843	325	3	learning‐based	learning‐based	ADJ
cana-3843	325	4	microarray	microarray	NOUN
cana-3843	325	5	cancer	cancer	NOUN
cana-3843	325	6	classification	classification	NOUN
cana-3843	325	7	and	and	CCONJ
cana-3843	325	8	ensemble	ensemble	ADJ
cana-3843	325	9	gene	gene	NOUN
cana-3843	325	10	selection	selection	NOUN
cana-3843	325	11	approach	approach	NOUN
cana-3843	325	12	.	.	PUNCT
cana-3843	325	13	"	"	PUNCT
cana-3843	326	1	iet	iet	PROPN
cana-3843	326	2	systems	systems	PROPN
cana-3843	326	3	biology	biology	NOUN
cana-3843	326	4	16	16	NUM
cana-3843	326	5	,	,	PUNCT
cana-3843	326	6	no	no	INTJ
cana-3843	326	7	.	.	NOUN
cana-3843	327	1	3	3	NUM
cana-3843	327	2	-	-	SYM
cana-3843	327	3	4	4	NUM
cana-3843	327	4	(	(	PUNCT
cana-3843	327	5	2022	2022	NUM
cana-3843	327	6	):	):	PUNCT
cana-3843	327	7	120	120	NUM
cana-3843	327	8	-	-	SYM
cana-3843	327	9	131	131	NUM
cana-3843	327	10	.	.	PUNCT
cana-3843	328	1	[	[	X
cana-3843	328	2	27	27	NUM
cana-3843	328	3	]	]	SYM
cana-3843	328	4	du	du	X
cana-3843	328	5	,	,	PUNCT
cana-3843	328	6	wen	wen	PROPN
cana-3843	328	7	,	,	PUNCT
cana-3843	328	8	ting	ting	PROPN
cana-3843	328	9	gu	gu	PROPN
cana-3843	328	10	,	,	PUNCT
cana-3843	328	11	li	li	PROPN
cana-3843	328	12	-	-	PROPN
cana-3843	328	13	juan	juan	PROPN
cana-3843	328	14	tang	tang	PROPN
cana-3843	328	15	,	,	PUNCT
cana-3843	328	16	jian	jian	PROPN
cana-3843	328	17	-	-	PUNCT
cana-3843	328	18	hui	hui	PROPN
cana-3843	328	19	jiang	jiang	PROPN
cana-3843	328	20	,	,	PUNCT
cana-3843	328	21	hai	hai	NOUN
cana-3843	328	22	-	-	PUNCT
cana-3843	328	23	long	long	ADJ
cana-3843	328	24	wu	wu	PROPN
cana-3843	328	25	,	,	PUNCT
cana-3843	328	26	guo	guo	PROPN
cana-3843	328	27	-	-	PUNCT
cana-3843	328	28	li	li	PROPN
cana-3843	328	29	shen	shen	PROPN
cana-3843	328	30	,	,	PUNCT
cana-3843	328	31	and	and	CCONJ
cana-3843	328	32	ru	ru	PROPN
cana-3843	328	33	-	-	PUNCT
cana-3843	328	34	qin	qin	PROPN
cana-3843	328	35	yu	yu	PROPN
cana-3843	328	36	.	.	PUNCT
cana-3843	329	1	"	"	PUNCT
cana-3843	329	2	unimodal	unimodal	ADJ
cana-3843	329	3	transform	transform	NOUN
cana-3843	329	4	of	of	ADP
cana-3843	329	5	variables	variable	NOUN
cana-3843	329	6	selected	select	VERB
cana-3843	329	7	by	by	ADP
cana-3843	329	8	interval	interval	NOUN
cana-3843	329	9	segmentation	segmentation	NOUN
cana-3843	329	10	purity	purity	NOUN
cana-3843	329	11	for	for	ADP
cana-3843	329	12	classification	classification	NOUN
cana-3843	329	13	tree	tree	NOUN
cana-3843	329	14	modeling	modeling	NOUN
cana-3843	329	15	of	of	ADP
cana-3843	329	16	high	high	ADJ
cana-3843	329	17	-	-	PUNCT
cana-3843	329	18	dimensional	dimensional	ADJ
cana-3843	329	19	microarray	microarray	NOUN
cana-3843	329	20	data	datum	NOUN
cana-3843	329	21	.	.	PUNCT
cana-3843	329	22	"	"	PUNCT
cana-3843	329	23	talanta	talanta	VERB
cana-3843	329	24	85	85	NUM
cana-3843	329	25	,	,	PUNCT
cana-3843	329	26	no	no	INTJ
cana-3843	329	27	.	.	NOUN
cana-3843	329	28	3	3	NUM
cana-3843	329	29	(	(	PUNCT
cana-3843	329	30	2011	2011	NUM
cana-3843	329	31	):	):	PUNCT
cana-3843	329	32	1689	1689	NUM
cana-3843	329	33	-	-	SYM
cana-3843	329	34	1694	1694	NUM
cana-3843	329	35	.	.	PUNCT
cana-3843	330	1	[	[	X
cana-3843	330	2	28	28	NUM
cana-3843	330	3	]	]	X
cana-3843	330	4	karimi	karimi	PROPN
cana-3843	330	5	,	,	PUNCT
cana-3843	330	6	sadegh	sadegh	VERB
cana-3843	330	7	,	,	PUNCT
cana-3843	330	8	and	and	CCONJ
cana-3843	330	9	maryam	maryam	PROPN
cana-3843	330	10	farrokhnia	farrokhnia	PROPN
cana-3843	330	11	.	.	PUNCT
cana-3843	331	1	"	"	PUNCT
cana-3843	331	2	leukemia	leukemia	NOUN
cana-3843	331	3	and	and	CCONJ
cana-3843	331	4	small	small	ADJ
cana-3843	331	5	round	round	ADJ
cana-3843	331	6	blue	blue	ADJ
cana-3843	331	7	-	-	PUNCT
cana-3843	331	8	cell	cell	NOUN
cana-3843	331	9	tumor	tumor	NOUN
cana-3843	331	10	cancer	cancer	NOUN
cana-3843	331	11	detection	detection	NOUN
cana-3843	331	12	using	use	VERB
cana-3843	331	13	microarray	microarray	NOUN
cana-3843	331	14	gene	gene	NOUN
cana-3843	331	15	expression	expression	NOUN
cana-3843	331	16	data	datum	NOUN
cana-3843	331	17	set	set	VERB
cana-3843	331	18	:	:	PUNCT
cana-3843	331	19	combining	combine	VERB
cana-3843	331	20	data	datum	NOUN
cana-3843	331	21	dimension	dimension	NOUN
cana-3843	331	22	reduction	reduction	NOUN
cana-3843	331	23	and	and	CCONJ
cana-3843	331	24	variable	variable	ADJ
cana-3843	331	25	selection	selection	NOUN
cana-3843	331	26	technique	technique	NOUN
cana-3843	331	27	.	.	PUNCT
cana-3843	331	28	"	"	PUNCT
cana-3843	332	1	chemometrics	chemometric	NOUN
cana-3843	332	2	and	and	CCONJ
cana-3843	332	3	intelligent	intelligent	ADJ
cana-3843	332	4	laboratory	laboratory	NOUN
cana-3843	332	5	systems	system	NOUN
cana-3843	332	6	139	139	NUM
cana-3843	332	7	(	(	PUNCT
cana-3843	332	8	2014	2014	NUM
cana-3843	332	9	):	):	PUNCT
cana-3843	332	10	6	6	NUM
cana-3843	332	11	-	-	SYM
cana-3843	332	12	14	14	NUM
cana-3843	332	13	.	.	PUNCT
cana-3843	333	1	communications	communication	NOUN
cana-3843	333	2	on	on	ADP
cana-3843	333	3	applied	apply	VERB
cana-3843	333	4	nonlinear	nonlinear	ADJ
cana-3843	333	5	analysis	analysis	NOUN
cana-3843	333	6	issn	issn	NOUN
cana-3843	333	7	:	:	PUNCT
cana-3843	333	8	1074	1074	NUM
cana-3843	333	9	-	-	PUNCT
cana-3843	333	10	133x	133x	NUM
cana-3843	333	11	vol	vol	NOUN
cana-3843	333	12	32	32	NUM
cana-3843	333	13	no	no	NOUN
cana-3843	333	14	.	.	PUNCT
cana-3843	334	1	9s	9s	NUM
cana-3843	334	2	(	(	PUNCT
cana-3843	334	3	2025	2025	NUM
cana-3843	334	4	)	)	PUNCT
cana-3843	334	5	134	134	NUM
cana-3843	334	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3843	335	1	[	[	X
cana-3843	335	2	29	29	NUM
cana-3843	335	3	]	]	X
cana-3843	335	4	furey	furey	PROPN
cana-3843	335	5	,	,	PUNCT
cana-3843	335	6	terrence	terrence	PROPN
cana-3843	335	7	s.	s.	PROPN
cana-3843	335	8	,	,	PUNCT
cana-3843	335	9	nello	nello	PROPN
cana-3843	335	10	cristianini	cristianini	PROPN
cana-3843	335	11	,	,	PUNCT
cana-3843	335	12	nigel	nigel	PROPN
cana-3843	335	13	duffy	duffy	PROPN
cana-3843	335	14	,	,	PUNCT
cana-3843	335	15	david	david	PROPN
cana-3843	335	16	w.	w.	PROPN
cana-3843	335	17	bednarski	bednarski	PROPN
cana-3843	335	18	,	,	PUNCT
cana-3843	335	19	michel	michel	PROPN
cana-3843	335	20	schummer	schummer	PROPN
cana-3843	335	21	,	,	PUNCT
cana-3843	335	22	and	and	CCONJ
cana-3843	335	23	david	david	PROPN
cana-3843	335	24	haussler	haussler	PROPN
cana-3843	335	25	.	.	PUNCT
cana-3843	336	1	"	"	PUNCT
cana-3843	336	2	support	support	VERB
cana-3843	336	3	vector	vector	NOUN
cana-3843	336	4	machine	machine	NOUN
cana-3843	336	5	classification	classification	NOUN
cana-3843	336	6	and	and	CCONJ
cana-3843	336	7	validation	validation	NOUN
cana-3843	336	8	of	of	ADP
cana-3843	336	9	cancer	cancer	NOUN
cana-3843	336	10	tissue	tissue	NOUN
cana-3843	336	11	samples	sample	NOUN
cana-3843	336	12	using	use	VERB
cana-3843	336	13	microarray	microarray	NOUN
cana-3843	336	14	expression	expression	NOUN
cana-3843	336	15	data	datum	NOUN
cana-3843	336	16	.	.	PUNCT
cana-3843	336	17	"	"	PUNCT
cana-3843	337	1	bioinformatics	bioinformatics	NOUN
cana-3843	337	2	16	16	NUM
cana-3843	337	3	,	,	PUNCT
cana-3843	337	4	no	no	INTJ
cana-3843	337	5	.	.	NOUN
cana-3843	337	6	10	10	NUM
cana-3843	337	7	(	(	PUNCT
cana-3843	337	8	2000	2000	NUM
cana-3843	337	9	):	):	PUNCT
cana-3843	337	10	906	906	NUM
cana-3843	337	11	-	-	SYM
cana-3843	337	12	914	914	NUM
cana-3843	337	13	.	.	PUNCT
cana-3843	338	1	[	[	X
cana-3843	338	2	30	30	NUM
cana-3843	338	3	]	]	X
cana-3843	338	4	nguyen	nguyen	NOUN
cana-3843	338	5	,	,	PUNCT
cana-3843	338	6	danh	danh	NOUN
cana-3843	338	7	v.	v.	ADV
cana-3843	338	8	,	,	PUNCT
cana-3843	338	9	and	and	CCONJ
cana-3843	338	10	david	david	PROPN
cana-3843	338	11	m.	m.	PROPN
cana-3843	338	12	rocke	rocke	PROPN
cana-3843	338	13	.	.	PUNCT
cana-3843	339	1	"	"	PUNCT
cana-3843	339	2	tumor	tumor	NOUN
cana-3843	339	3	classification	classification	NOUN
cana-3843	339	4	by	by	ADP
cana-3843	339	5	partial	partial	ADJ
cana-3843	339	6	least	least	ADJ
cana-3843	339	7	squares	square	NOUN
cana-3843	339	8	using	use	VERB
cana-3843	339	9	microarray	microarray	NOUN
cana-3843	339	10	gene	gene	NOUN
cana-3843	339	11	expression	expression	NOUN
cana-3843	339	12	data	datum	NOUN
cana-3843	339	13	.	.	PUNCT
cana-3843	339	14	"	"	PUNCT
cana-3843	340	1	bioinformatics	bioinformatics	NOUN
cana-3843	340	2	18	18	NUM
cana-3843	340	3	,	,	PUNCT
cana-3843	340	4	no	no	INTJ
cana-3843	340	5	.	.	NOUN
cana-3843	340	6	1	1	NUM
cana-3843	340	7	(	(	PUNCT
cana-3843	340	8	2002	2002	NUM
cana-3843	340	9	):	):	PUNCT
cana-3843	340	10	39	39	NUM
cana-3843	340	11	-	-	SYM
cana-3843	340	12	50	50	NUM
cana-3843	340	13	.	.	PUNCT
cana-3843	341	1	[	[	X
cana-3843	341	2	31	31	NUM
cana-3843	341	3	]	]	X
cana-3843	341	4	cho	cho	PROPN
cana-3843	341	5	,	,	PUNCT
cana-3843	341	6	sung	sung	NOUN
cana-3843	341	7	-	-	PUNCT
cana-3843	341	8	bae	bae	NOUN
cana-3843	341	9	.	.	PUNCT
cana-3843	342	1	"	"	PUNCT
cana-3843	342	2	exploring	explore	VERB
cana-3843	342	3	features	feature	NOUN
cana-3843	342	4	and	and	CCONJ
cana-3843	342	5	classifiers	classifier	NOUN
cana-3843	342	6	to	to	PART
cana-3843	342	7	classify	classify	VERB
cana-3843	342	8	gene	gene	NOUN
cana-3843	342	9	expression	expression	NOUN
cana-3843	342	10	profiles	profile	NOUN
cana-3843	342	11	of	of	ADP
cana-3843	342	12	acute	acute	ADJ
cana-3843	342	13	leukemia	leukemia	NOUN
cana-3843	342	14	.	.	PUNCT
cana-3843	342	15	"	"	PUNCT
cana-3843	343	1	international	international	ADJ
cana-3843	343	2	journal	journal	NOUN
cana-3843	343	3	of	of	ADP
cana-3843	343	4	pattern	pattern	NOUN
cana-3843	343	5	recognition	recognition	NOUN
cana-3843	343	6	and	and	CCONJ
cana-3843	343	7	artificial	artificial	ADJ
cana-3843	343	8	intelligence	intelligence	NOUN
cana-3843	343	9	16	16	NUM
cana-3843	343	10	,	,	PUNCT
cana-3843	343	11	no	no	INTJ
cana-3843	343	12	.	.	NOUN
cana-3843	343	13	07	07	NUM
cana-3843	343	14	(	(	PUNCT
cana-3843	343	15	2002	2002	NUM
cana-3843	343	16	):	):	PUNCT
cana-3843	343	17	831	831	NUM
cana-3843	343	18	-	-	SYM
cana-3843	343	19	844	844	NUM
cana-3843	343	20	.	.	PUNCT
cana-3843	344	1	[	[	X
cana-3843	344	2	32	32	NUM
cana-3843	344	3	]	]	X
cana-3843	344	4	ocampo	ocampo	PROPN
cana-3843	344	5	-	-	PUNCT
cana-3843	344	6	vega	vega	PROPN
cana-3843	344	7	,	,	PUNCT
cana-3843	344	8	ricardo	ricardo	PROPN
cana-3843	344	9	,	,	PUNCT
cana-3843	344	10	gildardo	gildardo	PROPN
cana-3843	344	11	sanchez	sanchez	PROPN
cana-3843	344	12	-	-	PUNCT
cana-3843	344	13	ante	ante	PROPN
cana-3843	344	14	,	,	PUNCT
cana-3843	344	15	marco	marco	PROPN
cana-3843	344	16	a.	a.	PROPN
cana-3843	344	17	de	de	PROPN
cana-3843	344	18	luna	luna	PROPN
cana-3843	344	19	,	,	PUNCT
cana-3843	344	20	roberto	roberto	PROPN
cana-3843	344	21	vega	vega	PROPN
cana-3843	344	22	,	,	PUNCT
cana-3843	344	23	luis	luis	PROPN
cana-3843	344	24	e.	e.	PROPN
cana-3843	344	25	falcón	falcón	PROPN
cana-3843	344	26	-	-	PUNCT
cana-3843	344	27	morales	morale	NOUN
cana-3843	344	28	,	,	PUNCT
cana-3843	344	29	and	and	CCONJ
cana-3843	344	30	humberto	humberto	PROPN
cana-3843	344	31	sossa	sossa	VERB
cana-3843	344	32	.	.	PUNCT
cana-3843	345	1	"	"	PUNCT
cana-3843	345	2	improving	improve	VERB
cana-3843	345	3	pattern	pattern	NOUN
cana-3843	345	4	classification	classification	NOUN
cana-3843	345	5	of	of	ADP
cana-3843	345	6	dna	dna	PROPN
cana-3843	345	7	microarray	microarray	NOUN
cana-3843	345	8	data	datum	NOUN
cana-3843	345	9	by	by	ADP
cana-3843	345	10	using	use	VERB
cana-3843	345	11	pca	pca	NOUN
cana-3843	345	12	and	and	CCONJ
cana-3843	345	13	logistic	logistic	ADJ
cana-3843	345	14	regression	regression	NOUN
cana-3843	345	15	.	.	PUNCT
cana-3843	345	16	"	"	PUNCT
cana-3843	346	1	intelligent	intelligent	ADJ
cana-3843	346	2	data	datum	NOUN
cana-3843	346	3	analysis	analysis	NOUN
cana-3843	346	4	20	20	NUM
cana-3843	346	5	,	,	PUNCT
cana-3843	346	6	no	no	INTJ
cana-3843	346	7	.	.	PUNCT
cana-3843	347	1	s1	s1	NOUN
cana-3843	347	2	(	(	PUNCT
cana-3843	347	3	2016	2016	NUM
cana-3843	347	4	):	):	PUNCT
cana-3843	347	5	s53s67	s53s67	NOUN
cana-3843	347	6	.	.	PUNCT
cana-3843	348	1	[	[	X
cana-3843	348	2	33	33	NUM
cana-3843	348	3	]	]	PUNCT
cana-3843	348	4	rupapara	rupapara	NOUN
cana-3843	348	5	,	,	PUNCT
cana-3843	348	6	vaibhav	vaibhav	PROPN
cana-3843	348	7	,	,	PUNCT
cana-3843	348	8	furqan	furqan	PROPN
cana-3843	348	9	rustam	rustam	PROPN
cana-3843	348	10	,	,	PUNCT
cana-3843	348	11	wajdi	wajdi	ADJ
cana-3843	348	12	aljedaani	aljedaani	PROPN
cana-3843	348	13	,	,	PUNCT
cana-3843	348	14	hina	hina	PROPN
cana-3843	348	15	fatima	fatima	PROPN
cana-3843	348	16	shahzad	shahzad	PROPN
cana-3843	348	17	,	,	PUNCT
cana-3843	348	18	ernesto	ernesto	PROPN
cana-3843	348	19	lee	lee	PROPN
cana-3843	348	20	,	,	PUNCT
cana-3843	348	21	and	and	CCONJ
cana-3843	348	22	imran	imran	PROPN
cana-3843	348	23	ashraf	ashraf	PROPN
cana-3843	348	24	.	.	PUNCT
cana-3843	349	1	"	"	PUNCT
cana-3843	349	2	blood	blood	NOUN
cana-3843	349	3	cancer	cancer	NOUN
cana-3843	349	4	prediction	prediction	NOUN
cana-3843	349	5	using	use	VERB
cana-3843	349	6	leukemia	leukemia	NOUN
cana-3843	349	7	microarray	microarray	NOUN
cana-3843	349	8	gene	gene	NOUN
cana-3843	349	9	data	datum	NOUN
cana-3843	349	10	and	and	CCONJ
cana-3843	349	11	hybrid	hybrid	ADJ
cana-3843	349	12	logistic	logistic	ADJ
cana-3843	349	13	vector	vector	NOUN
cana-3843	349	14	trees	tree	NOUN
cana-3843	349	15	model	model	NOUN
cana-3843	349	16	.	.	PUNCT
cana-3843	349	17	"	"	PUNCT
cana-3843	350	1	scientific	scientific	ADJ
cana-3843	350	2	reports	report	NOUN
cana-3843	350	3	12	12	NUM
cana-3843	350	4	,	,	PUNCT
cana-3843	350	5	no	no	INTJ
cana-3843	350	6	.	.	NOUN
cana-3843	350	7	1	1	NUM
cana-3843	350	8	(	(	PUNCT
cana-3843	350	9	2022	2022	NUM
cana-3843	350	10	):	):	PUNCT
cana-3843	350	11	1000	1000	NUM
cana-3843	350	12	.	.	PUNCT
cana-3843	351	1	[	[	X
cana-3843	351	2	34	34	NUM
cana-3843	351	3	]	]	PUNCT
cana-3843	351	4	sharma	sharma	PROPN
cana-3843	351	5	,	,	PUNCT
cana-3843	351	6	aman	aman	NOUN
cana-3843	351	7	,	,	PUNCT
cana-3843	351	8	and	and	CCONJ
cana-3843	351	9	rinkle	rinkle	ADJ
cana-3843	351	10	rani	rani	NOUN
cana-3843	351	11	.	.	PUNCT
cana-3843	352	1	"	"	PUNCT
cana-3843	352	2	an	an	DET
cana-3843	352	3	optimized	optimize	VERB
cana-3843	352	4	framework	framework	NOUN
cana-3843	352	5	for	for	ADP
cana-3843	352	6	cancer	cancer	NOUN
cana-3843	352	7	classification	classification	NOUN
cana-3843	352	8	using	use	VERB
cana-3843	352	9	deep	deep	ADJ
cana-3843	352	10	learning	learning	NOUN
cana-3843	352	11	and	and	CCONJ
cana-3843	352	12	genetic	genetic	ADJ
cana-3843	352	13	algorithm	algorithm	NOUN
cana-3843	352	14	.	.	PUNCT
cana-3843	352	15	"	"	PUNCT
cana-3843	353	1	journal	journal	NOUN
cana-3843	353	2	of	of	ADP
cana-3843	353	3	medical	medical	ADJ
cana-3843	353	4	imaging	imaging	NOUN
cana-3843	353	5	and	and	CCONJ
cana-3843	353	6	health	health	NOUN
cana-3843	353	7	informatics	informatic	NOUN
cana-3843	353	8	7	7	NUM
cana-3843	353	9	,	,	PUNCT
cana-3843	353	10	no	no	INTJ
cana-3843	353	11	.	.	NOUN
cana-3843	353	12	8	8	NUM
cana-3843	353	13	(	(	PUNCT
cana-3843	353	14	2017	2017	NUM
cana-3843	353	15	):	):	PUNCT
cana-3843	353	16	1851	1851	NUM
cana-3843	353	17	-	-	SYM
cana-3843	353	18	1856	1856	NUM
cana-3843	353	19	.	.	PUNCT