id	sid	tid	token	lemma	pos
cana-1429	1	1	communications	communication	NOUN
cana-1429	1	2	on	on	ADP
cana-1429	1	3	applied	apply	VERB
cana-1429	1	4	nonlinear	nonlinear	ADJ
cana-1429	1	5	analysis	analysis	NOUN
cana-1429	1	6	issn	issn	NOUN
cana-1429	1	7	:	:	PUNCT
cana-1429	1	8	1074	1074	NUM
cana-1429	1	9	-	-	PUNCT
cana-1429	1	10	133x	133x	NUM
cana-1429	1	11	vol	vol	NOUN
cana-1429	1	12	31	31	NUM
cana-1429	1	13	no	no	NOUN
cana-1429	1	14	.	.	PUNCT
cana-1429	2	1	7s	7	NOUN
cana-1429	2	2	(	(	PUNCT
cana-1429	2	3	2024	2024	NUM
cana-1429	2	4	)	)	PUNCT
cana-1429	2	5	677	677	NUM
cana-1429	3	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1429	3	2	handling	handle	VERB
cana-1429	3	3	missing	miss	VERB
cana-1429	3	4	data	datum	NOUN
cana-1429	3	5	through	through	ADP
cana-1429	3	6	artificial	artificial	ADJ
cana-1429	3	7	neural	neural	ADJ
cana-1429	3	8	network	network	NOUN
cana-1429	3	9	geeta	geeta	PROPN
cana-1429	3	10	chhabra	chhabra	PROPN
cana-1429	3	11	data	data	PROPN
cana-1429	3	12	informatics	informatics	PROPN
cana-1429	3	13	&	&	CCONJ
cana-1429	3	14	innovation	innovation	PROPN
cana-1429	3	15	division	division	PROPN
cana-1429	3	16	,	,	PUNCT
cana-1429	3	17	ministry	ministry	PROPN
cana-1429	3	18	of	of	ADP
cana-1429	3	19	statistics	statistics	PROPN
cana-1429	3	20	&	&	CCONJ
cana-1429	3	21	pi	pi	PROPN
cana-1429	3	22	,	,	PUNCT
cana-1429	3	23	govt	govt	PROPN
cana-1429	3	24	.	.	PUNCT
cana-1429	4	1	of	of	ADP
cana-1429	4	2	india	india	PROPN
cana-1429	4	3	,	,	PUNCT
cana-1429	4	4	india	india	PROPN
cana-1429	4	5	,	,	PUNCT
cana-1429	4	6	geeta_chhabra@rediffmail.com	geeta_chhabra@rediffmail.com	PROPN
cana-1429	4	7	article	article	NOUN
cana-1429	4	8	history	history	NOUN
cana-1429	4	9	:	:	PUNCT
cana-1429	4	10	received	receive	VERB
cana-1429	4	11	:	:	PUNCT
cana-1429	4	12	07	07	NUM
cana-1429	4	13	-	-	PUNCT
cana-1429	4	14	06	06	NUM
cana-1429	4	15	-	-	PUNCT
cana-1429	4	16	2024	2024	NUM
cana-1429	4	17	revised	revise	VERB
cana-1429	4	18	:	:	PUNCT
cana-1429	4	19	07	07	NUM
cana-1429	4	20	-	-	PUNCT
cana-1429	4	21	07	07	NUM
cana-1429	4	22	-	-	PUNCT
cana-1429	4	23	2024	2024	NUM
cana-1429	4	24	accepted	accept	VERB
cana-1429	4	25	:	:	PUNCT
cana-1429	4	26	31	31	NUM
cana-1429	4	27	-	-	SYM
cana-1429	4	28	07	07	NUM
cana-1429	4	29	-	-	PUNCT
cana-1429	4	30	2024	2024	NUM
cana-1429	4	31	abstract	abstract	NOUN
cana-1429	4	32	:	:	PUNCT
cana-1429	4	33	missing	miss	VERB
cana-1429	4	34	data	data	NOUN
cana-1429	4	35	is	be	AUX
cana-1429	4	36	a	a	DET
cana-1429	4	37	difficult	difficult	ADJ
cana-1429	4	38	problem	problem	NOUN
cana-1429	4	39	to	to	PART
cana-1429	4	40	solve	solve	VERB
cana-1429	4	41	when	when	SCONJ
cana-1429	4	42	working	work	VERB
cana-1429	4	43	with	with	ADP
cana-1429	4	44	real	real	ADJ
cana-1429	4	45	-	-	PUNCT
cana-1429	4	46	world	world	NOUN
cana-1429	4	47	datasets	dataset	NOUN
cana-1429	4	48	.	.	PUNCT
cana-1429	5	1	it	it	PRON
cana-1429	5	2	is	be	AUX
cana-1429	5	3	vital	vital	ADJ
cana-1429	5	4	to	to	PART
cana-1429	5	5	improve	improve	VERB
cana-1429	5	6	data	datum	NOUN
cana-1429	5	7	quality	quality	NOUN
cana-1429	5	8	by	by	ADP
cana-1429	5	9	imputing	impute	VERB
cana-1429	5	10	missing	miss	VERB
cana-1429	5	11	values	value	NOUN
cana-1429	5	12	in	in	ADP
cana-1429	5	13	order	order	NOUN
cana-1429	5	14	to	to	PART
cana-1429	5	15	obtain	obtain	VERB
cana-1429	5	16	effective	effective	ADJ
cana-1429	5	17	data	datum	NOUN
cana-1429	5	18	learning	learning	NOUN
cana-1429	5	19	.	.	PUNCT
cana-1429	6	1	deep	deep	ADJ
cana-1429	6	2	learning	learning	NOUN
cana-1429	6	3	has	have	AUX
cana-1429	6	4	recently	recently	ADV
cana-1429	6	5	risen	rise	VERB
cana-1429	6	6	to	to	ADP
cana-1429	6	7	prominence	prominence	NOUN
cana-1429	6	8	as	as	ADP
cana-1429	6	9	the	the	DET
cana-1429	6	10	most	most	ADV
cana-1429	6	11	effective	effective	ADJ
cana-1429	6	12	sort	sort	NOUN
cana-1429	6	13	of	of	ADP
cana-1429	6	14	machine	machine	NOUN
cana-1429	6	15	learning	learning	NOUN
cana-1429	6	16	technique	technique	NOUN
cana-1429	6	17	for	for	ADP
cana-1429	6	18	uncovering	uncover	VERB
cana-1429	6	19	hidden	hidden	ADJ
cana-1429	6	20	knowledge	knowledge	NOUN
cana-1429	6	21	in	in	ADP
cana-1429	6	22	massive	massive	ADJ
cana-1429	6	23	datasets	dataset	NOUN
cana-1429	6	24	and	and	CCONJ
cana-1429	6	25	making	make	VERB
cana-1429	6	26	accurate	accurate	ADJ
cana-1429	6	27	predictions	prediction	NOUN
cana-1429	6	28	.	.	PUNCT
cana-1429	7	1	we	we	PRON
cana-1429	7	2	have	have	AUX
cana-1429	7	3	used	use	VERB
cana-1429	7	4	“	"	PUNCT
cana-1429	7	5	back	back	ADJ
cana-1429	7	6	-	-	PUNCT
cana-1429	7	7	propagation	propagation	NOUN
cana-1429	7	8	artificial	artificial	ADJ
cana-1429	7	9	neural	neural	ADJ
cana-1429	7	10	network	network	NOUN
cana-1429	7	11	”	"	PUNCT
cana-1429	7	12	to	to	PART
cana-1429	7	13	impute	impute	VERB
cana-1429	7	14	categorical	categorical	ADJ
cana-1429	7	15	missing	miss	VERB
cana-1429	7	16	data	datum	NOUN
cana-1429	7	17	.	.	PUNCT
cana-1429	8	1	the	the	DET
cana-1429	8	2	main	main	ADJ
cana-1429	8	3	goal	goal	NOUN
cana-1429	8	4	is	be	AUX
cana-1429	8	5	to	to	PART
cana-1429	8	6	see	see	VERB
cana-1429	8	7	how	how	SCONJ
cana-1429	8	8	well	well	ADV
cana-1429	8	9	“	"	PUNCT
cana-1429	8	10	neural	neural	ADJ
cana-1429	8	11	network	network	NOUN
cana-1429	8	12	”	"	PUNCT
cana-1429	8	13	compares	compare	VERB
cana-1429	8	14	to	to	ADP
cana-1429	8	15	statistics	statistic	NOUN
cana-1429	8	16	and	and	CCONJ
cana-1429	8	17	machine	machine	NOUN
cana-1429	8	18	learning	learning	NOUN
cana-1429	8	19	for	for	ADP
cana-1429	8	20	resolving	resolve	VERB
cana-1429	8	21	categorical	categorical	ADJ
cana-1429	8	22	missing	miss	VERB
cana-1429	8	23	data	datum	NOUN
cana-1429	8	24	.	.	PUNCT
cana-1429	9	1	the	the	DET
cana-1429	9	2	results	result	NOUN
cana-1429	9	3	of	of	ADP
cana-1429	9	4	“	"	PUNCT
cana-1429	9	5	back	back	ADJ
cana-1429	9	6	-	-	PUNCT
cana-1429	9	7	propagation	propagation	NOUN
cana-1429	9	8	”	"	PUNCT
cana-1429	9	9	are	be	AUX
cana-1429	9	10	compared	compare	VERB
cana-1429	9	11	with	with	ADP
cana-1429	9	12	multiple	multiple	ADJ
cana-1429	9	13	imputation	imputation	NOUN
cana-1429	9	14	and	and	CCONJ
cana-1429	9	15	random	random	ADJ
cana-1429	9	16	forest	forest	NOUN
cana-1429	9	17	.	.	PUNCT
cana-1429	10	1	it	it	PRON
cana-1429	10	2	consistently	consistently	ADV
cana-1429	10	3	outperforms	outperform	VERB
cana-1429	10	4	alternative	alternative	ADJ
cana-1429	10	5	methods	method	NOUN
cana-1429	10	6	both	both	CCONJ
cana-1429	10	7	in	in	ADP
cana-1429	10	8	“	"	PUNCT
cana-1429	10	9	training	training	NOUN
cana-1429	10	10	”	"	PUNCT
cana-1429	10	11	and	and	CCONJ
cana-1429	10	12	“	"	PUNCT
cana-1429	10	13	test	test	NOUN
cana-1429	10	14	”	"	PUNCT
cana-1429	10	15	data	datum	NOUN
cana-1429	10	16	sets	set	NOUN
cana-1429	10	17	,	,	PUNCT
cana-1429	10	18	showing	show	VERB
cana-1429	10	19	that	that	SCONJ
cana-1429	10	20	“	"	PUNCT
cana-1429	10	21	neural	neural	ADJ
cana-1429	10	22	network	network	NOUN
cana-1429	10	23	”	"	PUNCT
cana-1429	10	24	is	be	AUX
cana-1429	10	25	a	a	DET
cana-1429	10	26	suitable	suitable	ADJ
cana-1429	10	27	for	for	ADP
cana-1429	10	28	reconstructing	reconstruct	VERB
cana-1429	10	29	“	"	PUNCT
cana-1429	10	30	missing	miss	VERB
cana-1429	10	31	values	value	NOUN
cana-1429	10	32	”	"	PUNCT
cana-1429	10	33	in	in	ADP
cana-1429	10	34	“	"	PUNCT
cana-1429	10	35	multivariate	multivariate	NOUN
cana-1429	10	36	analysis	analysis	NOUN
cana-1429	10	37	”	"	PUNCT
cana-1429	10	38	.	.	PUNCT
cana-1429	11	1	keywords	keyword	NOUN
cana-1429	11	2	:	:	PUNCT
cana-1429	11	3	artificial	artificial	ADJ
cana-1429	11	4	neural	neural	ADJ
cana-1429	11	5	network	network	NOUN
cana-1429	11	6	,	,	PUNCT
cana-1429	11	7	multiple	multiple	ADJ
cana-1429	11	8	imputation	imputation	NOUN
cana-1429	11	9	,	,	PUNCT
cana-1429	11	10	random	random	ADJ
cana-1429	11	11	forest	forest	NOUN
cana-1429	11	12	,	,	PUNCT
cana-1429	11	13	backpropagation	backpropagation	NOUN
cana-1429	11	14	.	.	PUNCT
cana-1429	12	1	1	1	X
cana-1429	12	2	.	.	X
cana-1429	12	3	introduction	introduction	NOUN
cana-1429	12	4	in	in	ADP
cana-1429	12	5	the	the	DET
cana-1429	12	6	modern	modern	ADJ
cana-1429	12	7	era	era	NOUN
cana-1429	12	8	,	,	PUNCT
cana-1429	12	9	a	a	DET
cana-1429	12	10	great	great	ADJ
cana-1429	12	11	amount	amount	NOUN
cana-1429	12	12	of	of	ADP
cana-1429	12	13	data	datum	NOUN
cana-1429	12	14	is	be	AUX
cana-1429	12	15	gradually	gradually	ADV
cana-1429	12	16	generated	generate	VERB
cana-1429	12	17	in	in	ADP
cana-1429	12	18	various	various	ADJ
cana-1429	12	19	fields	field	NOUN
cana-1429	12	20	,	,	PUNCT
cana-1429	12	21	and	and	CCONJ
cana-1429	12	22	the	the	DET
cana-1429	12	23	quick	quick	ADJ
cana-1429	12	24	increase	increase	NOUN
cana-1429	12	25	in	in	ADP
cana-1429	12	26	data	data	NOUN
cana-1429	12	27	size	size	NOUN
cana-1429	12	28	has	have	AUX
cana-1429	12	29	demonstrated	demonstrate	VERB
cana-1429	12	30	the	the	DET
cana-1429	12	31	importance	importance	NOUN
cana-1429	12	32	of	of	ADP
cana-1429	12	33	big	big	ADJ
cana-1429	12	34	data	datum	NOUN
cana-1429	12	35	analysis	analysis	NOUN
cana-1429	12	36	.	.	PUNCT
cana-1429	13	1	because	because	SCONJ
cana-1429	13	2	low	low	ADJ
cana-1429	13	3	quality	quality	NOUN
cana-1429	13	4	data	datum	NOUN
cana-1429	13	5	can	can	AUX
cana-1429	13	6	not	not	PART
cana-1429	13	7	be	be	AUX
cana-1429	13	8	used	use	VERB
cana-1429	13	9	to	to	PART
cana-1429	13	10	construct	construct	VERB
cana-1429	13	11	credible	credible	ADJ
cana-1429	13	12	models	model	NOUN
cana-1429	13	13	,	,	PUNCT
cana-1429	13	14	it	it	PRON
cana-1429	13	15	is	be	AUX
cana-1429	13	16	vital	vital	ADJ
cana-1429	13	17	to	to	PART
cana-1429	13	18	ensure	ensure	VERB
cana-1429	13	19	that	that	SCONJ
cana-1429	13	20	the	the	DET
cana-1429	13	21	data	datum	NOUN
cana-1429	13	22	acquired	acquire	VERB
cana-1429	13	23	is	be	AUX
cana-1429	13	24	trustworthy	trustworthy	ADJ
cana-1429	13	25	and	and	CCONJ
cana-1429	13	26	valuable	valuable	ADJ
cana-1429	13	27	.	.	PUNCT
cana-1429	14	1	missing	miss	VERB
cana-1429	14	2	values	value	NOUN
cana-1429	14	3	in	in	ADP
cana-1429	14	4	the	the	DET
cana-1429	14	5	acquired	acquire	VERB
cana-1429	14	6	data	datum	NOUN
cana-1429	14	7	set	set	VERB
cana-1429	14	8	are	be	AUX
cana-1429	14	9	a	a	DET
cana-1429	14	10	regular	regular	ADJ
cana-1429	14	11	and	and	CCONJ
cana-1429	14	12	inevitable	inevitable	ADJ
cana-1429	14	13	issue	issue	NOUN
cana-1429	14	14	in	in	ADP
cana-1429	14	15	practise	practise	NOUN
cana-1429	14	16	,	,	PUNCT
cana-1429	14	17	and	and	CCONJ
cana-1429	14	18	they	they	PRON
cana-1429	14	19	can	can	AUX
cana-1429	14	20	lead	lead	VERB
cana-1429	14	21	to	to	ADP
cana-1429	14	22	uncertainty	uncertainty	NOUN
cana-1429	14	23	in	in	ADP
cana-1429	14	24	data	datum	NOUN
cana-1429	14	25	analysis	analysis	NOUN
cana-1429	14	26	.	.	PUNCT
cana-1429	15	1	missing	miss	VERB
cana-1429	15	2	data	datum	NOUN
cana-1429	15	3	can	can	AUX
cana-1429	15	4	be	be	AUX
cana-1429	15	5	found	find	VERB
cana-1429	15	6	in	in	ADP
cana-1429	15	7	a	a	DET
cana-1429	15	8	variety	variety	NOUN
cana-1429	15	9	of	of	ADP
cana-1429	15	10	areas	area	NOUN
cana-1429	15	11	,	,	PUNCT
cana-1429	15	12	including	include	VERB
cana-1429	15	13	gene	gene	NOUN
cana-1429	15	14	expression	expression	NOUN
cana-1429	15	15	,	,	PUNCT
cana-1429	15	16	traffic	traffic	NOUN
cana-1429	15	17	control	control	NOUN
cana-1429	15	18	,	,	PUNCT
cana-1429	15	19	industrial	industrial	ADJ
cana-1429	15	20	informatics	informatic	NOUN
cana-1429	15	21	,	,	PUNCT
cana-1429	15	22	image	image	NOUN
cana-1429	15	23	processing	processing	NOUN
cana-1429	15	24	,	,	PUNCT
cana-1429	15	25	and	and	CCONJ
cana-1429	15	26	software	software	NOUN
cana-1429	15	27	development	development	NOUN
cana-1429	15	28	.	.	PUNCT
cana-1429	16	1	without	without	ADP
cana-1429	16	2	addressing	address	VERB
cana-1429	16	3	the	the	DET
cana-1429	16	4	aforementioned	aforementioned	ADJ
cana-1429	16	5	issue	issue	NOUN
cana-1429	16	6	,	,	PUNCT
cana-1429	16	7	data	datum	NOUN
cana-1429	16	8	analysis	analysis	NOUN
cana-1429	16	9	can	can	AUX
cana-1429	16	10	yield	yield	VERB
cana-1429	16	11	deceptive	deceptive	ADJ
cana-1429	16	12	conclusions	conclusion	NOUN
cana-1429	16	13	.	.	PUNCT
cana-1429	17	1	as	as	ADP
cana-1429	17	2	a	a	DET
cana-1429	17	3	result	result	NOUN
cana-1429	17	4	,	,	PUNCT
cana-1429	17	5	it	it	PRON
cana-1429	17	6	is	be	AUX
cana-1429	17	7	vital	vital	ADJ
cana-1429	17	8	to	to	PART
cana-1429	17	9	improve	improve	VERB
cana-1429	17	10	the	the	DET
cana-1429	17	11	situation	situation	NOUN
cana-1429	17	12	.	.	PUNCT
cana-1429	18	1	missing	miss	VERB
cana-1429	18	2	data	datum	NOUN
cana-1429	18	3	could	could	AUX
cana-1429	18	4	be	be	AUX
cana-1429	18	5	due	due	ADJ
cana-1429	18	6	to	to	ADP
cana-1429	18	7	a	a	DET
cana-1429	18	8	variety	variety	NOUN
cana-1429	18	9	of	of	ADP
cana-1429	18	10	factors	factor	NOUN
cana-1429	18	11	,	,	PUNCT
cana-1429	18	12	including	include	VERB
cana-1429	18	13	questionnaire	questionnaire	NOUN
cana-1429	18	14	non	non	ADJ
cana-1429	18	15	-	-	NOUN
cana-1429	18	16	response	response	ADJ
cana-1429	18	17	,	,	PUNCT
cana-1429	18	18	failure	failure	NOUN
cana-1429	18	19	to	to	PART
cana-1429	18	20	follow	follow	VERB
cana-1429	18	21	up	up	ADP
cana-1429	18	22	on	on	ADP
cana-1429	18	23	research	research	NOUN
cana-1429	18	24	subjects	subject	NOUN
cana-1429	18	25	,	,	PUNCT
cana-1429	18	26	data	datum	NOUN
cana-1429	18	27	entry	entry	NOUN
cana-1429	18	28	errors	error	NOUN
cana-1429	18	29	,	,	PUNCT
cana-1429	18	30	equipment	equipment	NOUN
cana-1429	18	31	failure	failure	NOUN
cana-1429	18	32	,	,	PUNCT
cana-1429	18	33	or	or	CCONJ
cana-1429	18	34	incomplete	incomplete	ADJ
cana-1429	18	35	or	or	CCONJ
cana-1429	18	36	deleted	delete	VERB
cana-1429	18	37	records	record	NOUN
cana-1429	18	38	.	.	PUNCT
cana-1429	19	1	simply	simply	ADV
cana-1429	19	2	excluding	exclude	VERB
cana-1429	19	3	instances	instance	NOUN
cana-1429	19	4	of	of	ADP
cana-1429	19	5	“	"	PUNCT
cana-1429	19	6	missing	miss	VERB
cana-1429	19	7	data	datum	NOUN
cana-1429	19	8	”	"	PUNCT
cana-1429	19	9	could	could	AUX
cana-1429	19	10	lead	lead	VERB
cana-1429	19	11	to	to	ADP
cana-1429	19	12	“	"	PUNCT
cana-1429	19	13	biased	biased	ADJ
cana-1429	19	14	inference	inference	NOUN
cana-1429	19	15	”	"	PUNCT
cana-1429	19	16	,	,	PUNCT
cana-1429	19	17	lower	low	ADJ
cana-1429	19	18	“	"	PUNCT
cana-1429	19	19	statistical	statistical	ADJ
cana-1429	19	20	power	power	NOUN
cana-1429	19	21	”	"	PUNCT
cana-1429	19	22	and	and	CCONJ
cana-1429	19	23	outcomes	outcome	NOUN
cana-1429	19	24	,	,	PUNCT
cana-1429	19	25	that	that	PRON
cana-1429	19	26	are	be	AUX
cana-1429	19	27	less	less	ADV
cana-1429	19	28	generalizable	generalizable	ADJ
cana-1429	19	29	.	.	PUNCT
cana-1429	20	1	the	the	DET
cana-1429	20	2	issue	issue	NOUN
cana-1429	20	3	of	of	ADP
cana-1429	20	4	“	"	PUNCT
cana-1429	20	5	missing	missing	ADJ
cana-1429	20	6	data	datum	NOUN
cana-1429	20	7	”	"	PUNCT
cana-1429	20	8	can	can	AUX
cana-1429	20	9	be	be	AUX
cana-1429	20	10	categorised	categorise	VERB
cana-1429	20	11	in	in	ADP
cana-1429	20	12	three	three	NUM
cana-1429	20	13	groups	group	NOUN
cana-1429	20	14	based	base	VERB
cana-1429	20	15	on	on	ADP
cana-1429	20	16	missingness	missingness	ADJ
cana-1429	20	17	assumptions	assumption	NOUN
cana-1429	20	18	:	:	PUNCT
cana-1429	20	19	“	"	PUNCT
cana-1429	20	20	missing	miss	VERB
cana-1429	20	21	completely	completely	ADV
cana-1429	20	22	at	at	ADP
cana-1429	20	23	random	random	ADJ
cana-1429	20	24	(	(	PUNCT
cana-1429	20	25	“	"	PUNCT
cana-1429	20	26	mcar	mcar	NOUN
cana-1429	20	27	”	"	PUNCT
cana-1429	20	28	)	)	PUNCT
cana-1429	20	29	,	,	PUNCT
cana-1429	20	30	“	"	PUNCT
cana-1429	20	31	missing	miss	VERB
cana-1429	20	32	at	at	ADP
cana-1429	20	33	random	random	ADJ
cana-1429	20	34	”	"	PUNCT
cana-1429	20	35	(	(	PUNCT
cana-1429	20	36	“	"	PUNCT
cana-1429	20	37	mar	mar	PROPN
cana-1429	20	38	”	"	PUNCT
cana-1429	20	39	)	)	PUNCT
cana-1429	20	40	,	,	PUNCT
cana-1429	20	41	and	and	CCONJ
cana-1429	20	42	“	"	PUNCT
cana-1429	20	43	missing	miss	VERB
cana-1429	20	44	not	not	PART
cana-1429	20	45	at	at	ADP
cana-1429	20	46	random	random	ADJ
cana-1429	20	47	”	"	PUNCT
cana-1429	20	48	(	(	PUNCT
cana-1429	20	49	“	"	PUNCT
cana-1429	20	50	mnar	mnar	ADJ
cana-1429	20	51	”	"	PUNCT
cana-1429	20	52	)	)	PUNCT
cana-1429	20	53	.	.	PUNCT
cana-1429	21	1	the	the	DET
cana-1429	21	2	majority	majority	NOUN
cana-1429	21	3	of	of	ADP
cana-1429	21	4	“	"	PUNCT
cana-1429	21	5	missing	missing	ADJ
cana-1429	21	6	data	datum	NOUN
cana-1429	21	7	”	"	PUNCT
cana-1429	21	8	research	research	NOUN
cana-1429	21	9	is	be	AUX
cana-1429	21	10	presumed	presume	VERB
cana-1429	21	11	to	to	PART
cana-1429	21	12	be	be	AUX
cana-1429	21	13	mar	mar	PROPN
cana-1429	21	14	in	in	ADP
cana-1429	21	15	general	general	ADJ
cana-1429	21	16	.	.	PUNCT
cana-1429	22	1	mice	mouse	NOUN
cana-1429	22	2	(	(	PUNCT
cana-1429	22	3	“	"	PUNCT
cana-1429	22	4	multiple	multiple	ADJ
cana-1429	22	5	imputation	imputation	NOUN
cana-1429	22	6	by	by	ADP
cana-1429	22	7	chained	chain	VERB
cana-1429	22	8	equations	equation	NOUN
cana-1429	22	9	”	"	PUNCT
cana-1429	22	10	)	)	PUNCT
cana-1429	22	11	is	be	AUX
cana-1429	22	12	most	most	ADV
cana-1429	22	13	widely	widely	ADV
cana-1429	22	14	used	use	VERB
cana-1429	22	15	“	"	PUNCT
cana-1429	22	16	statistical	statistical	ADJ
cana-1429	22	17	”	"	PUNCT
cana-1429	22	18	approach	approach	NOUN
cana-1429	22	19	for	for	ADP
cana-1429	22	20	dealing	deal	VERB
cana-1429	22	21	with	with	ADP
cana-1429	22	22	“	"	PUNCT
cana-1429	22	23	missing	missing	ADJ
cana-1429	22	24	data	datum	NOUN
cana-1429	22	25	”	"	PUNCT
cana-1429	22	26	,	,	PUNCT
cana-1429	22	27	especially	especially	ADV
cana-1429	22	28	mar	mar	PROPN
cana-1429	22	29	data	data	PROPN
cana-1429	22	30	.	.	PUNCT
cana-1429	23	1	many	many	ADJ
cana-1429	23	2	statistical	statistical	ADJ
cana-1429	23	3	software	software	NOUN
cana-1429	23	4	packages	package	NOUN
cana-1429	23	5	,	,	PUNCT
cana-1429	23	6	such	such	ADJ
cana-1429	23	7	as	as	ADP
cana-1429	23	8	spss	spss	PROPN
cana-1429	23	9	,	,	PUNCT
cana-1429	23	10	stata	stata	NOUN
cana-1429	23	11	,	,	PUNCT
cana-1429	23	12	and	and	CCONJ
cana-1429	23	13	r	r	NOUN
cana-1429	23	14	,	,	PUNCT
cana-1429	23	15	have	have	VERB
cana-1429	23	16	mice	mouse	NOUN
cana-1429	23	17	.	.	PUNCT
cana-1429	24	1	because	because	SCONJ
cana-1429	24	2	mice	mouse	NOUN
cana-1429	24	3	defaults	default	NOUN
cana-1429	24	4	to	to	PART
cana-1429	24	5	"	"	PUNCT
cana-1429	24	6	predictive	predictive	ADJ
cana-1429	24	7	mean	mean	NOUN
cana-1429	24	8	matching	matching	NOUN
cana-1429	24	9	"	"	PUNCT
cana-1429	24	10	and	and	CCONJ
cana-1429	24	11	"	"	PUNCT
cana-1429	24	12	logistic	logistic	ADJ
cana-1429	24	13	communications	communication	NOUN
cana-1429	24	14	on	on	ADP
cana-1429	24	15	applied	apply	VERB
cana-1429	24	16	nonlinear	nonlinear	ADJ
cana-1429	24	17	analysis	analysis	NOUN
cana-1429	24	18	issn	issn	NOUN
cana-1429	24	19	:	:	PUNCT
cana-1429	24	20	1074	1074	NUM
cana-1429	24	21	-	-	PUNCT
cana-1429	24	22	133x	133x	NUM
cana-1429	24	23	vol	vol	NOUN
cana-1429	24	24	31	31	NUM
cana-1429	24	25	no	no	NOUN
cana-1429	24	26	.	.	PUNCT
cana-1429	25	1	7s	7	NOUN
cana-1429	25	2	(	(	PUNCT
cana-1429	25	3	2024	2024	NUM
cana-1429	25	4	)	)	PUNCT
cana-1429	25	5	678	678	NUM
cana-1429	25	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1429	25	7	regression	regression	NOUN
cana-1429	25	8	"	"	PUNCT
cana-1429	25	9	are	be	AUX
cana-1429	25	10	limited	limit	VERB
cana-1429	25	11	to	to	PART
cana-1429	25	12	handle	handle	VERB
cana-1429	25	13	non	non	ADJ
cana-1429	25	14	-	-	ADJ
cana-1429	25	15	linear	linear	ADJ
cana-1429	25	16	connections	connection	NOUN
cana-1429	25	17	and	and	CCONJ
cana-1429	25	18	interactions	interaction	NOUN
cana-1429	25	19	between	between	ADP
cana-1429	25	20	variables	variable	NOUN
cana-1429	25	21	and	and	CCONJ
cana-1429	25	22	may	may	AUX
cana-1429	25	23	produce	produce	VERB
cana-1429	25	24	biased	biased	ADJ
cana-1429	25	25	results	result	NOUN
cana-1429	25	26	.	.	PUNCT
cana-1429	26	1	“	"	PUNCT
cana-1429	26	2	random	random	ADJ
cana-1429	26	3	forest	forest	NOUN
cana-1429	26	4	”	"	PUNCT
cana-1429	26	5	,	,	PUNCT
cana-1429	26	6	an	an	DET
cana-1429	26	7	“	"	PUNCT
cana-1429	26	8	ensemble	ensemble	ADJ
cana-1429	26	9	machine	machine	NOUN
cana-1429	26	10	-	-	PUNCT
cana-1429	26	11	learning	learning	NOUN
cana-1429	26	12	”	"	PUNCT
cana-1429	26	13	technique	technique	NOUN
cana-1429	26	14	for	for	ADP
cana-1429	26	15	“	"	PUNCT
cana-1429	26	16	multi	multi	ADJ
cana-1429	26	17	-	-	ADJ
cana-1429	26	18	classification	classification	ADJ
cana-1429	26	19	”	"	PUNCT
cana-1429	26	20	or	or	CCONJ
cana-1429	26	21	“	"	PUNCT
cana-1429	26	22	decision	decision	NOUN
cana-1429	26	23	tree	tree	NOUN
cana-1429	26	24	regression	regression	NOUN
cana-1429	26	25	”	"	PUNCT
cana-1429	26	26	,	,	PUNCT
cana-1429	26	27	is	be	AUX
cana-1429	26	28	one	one	NUM
cana-1429	26	29	way	way	NOUN
cana-1429	26	30	to	to	PART
cana-1429	26	31	overcome	overcome	VERB
cana-1429	26	32	“	"	PUNCT
cana-1429	26	33	non	non	ADJ
cana-1429	26	34	-	-	ADJ
cana-1429	26	35	linearity	linearity	ADJ
cana-1429	26	36	”	"	PUNCT
cana-1429	26	37	.	.	PUNCT
cana-1429	27	1	“	"	PUNCT
cana-1429	27	2	random	random	ADJ
cana-1429	27	3	forest	forest	NOUN
cana-1429	27	4	”	"	PUNCT
cana-1429	27	5	beat	beat	VERB
cana-1429	27	6	“	"	PUNCT
cana-1429	27	7	mice	mouse	NOUN
cana-1429	27	8	”	"	PUNCT
cana-1429	27	9	in	in	ADP
cana-1429	27	10	both	both	CCONJ
cana-1429	27	11	realworld	realworld	PROPN
cana-1429	27	12	and	and	CCONJ
cana-1429	27	13	simulated	simulated	ADJ
cana-1429	27	14	datasets	dataset	NOUN
cana-1429	27	15	,	,	PUNCT
cana-1429	27	16	according	accord	VERB
cana-1429	27	17	to	to	ADP
cana-1429	27	18	subsequent	subsequent	ADJ
cana-1429	27	19	research	research	NOUN
cana-1429	27	20	(	(	PUNCT
cana-1429	27	21	shah	shah	PROPN
cana-1429	27	22	et	et	PROPN
cana-1429	27	23	al	al	PROPN
cana-1429	27	24	.	.	PROPN
cana-1429	27	25	,	,	PUNCT
cana-1429	27	26	2014	2014	NUM
cana-1429	27	27	)	)	PUNCT
cana-1429	27	28	.	.	PUNCT
cana-1429	28	1	back	back	ADJ
cana-1429	28	2	-	-	PUNCT
cana-1429	28	3	propagation	propagation	NOUN
cana-1429	28	4	“	"	PUNCT
cana-1429	28	5	artificial	artificial	ADJ
cana-1429	28	6	neural	neural	ADJ
cana-1429	28	7	network	network	NOUN
cana-1429	28	8	”	"	PUNCT
cana-1429	28	9	(	(	PUNCT
cana-1429	28	10	ann	ann	PROPN
cana-1429	28	11	)	)	PUNCT
cana-1429	28	12	is	be	AUX
cana-1429	28	13	a	a	DET
cana-1429	28	14	prominent	prominent	ADJ
cana-1429	28	15	“	"	PUNCT
cana-1429	28	16	deep	deep	ADJ
cana-1429	28	17	learning	learning	NOUN
cana-1429	28	18	”	"	PUNCT
cana-1429	28	19	method	method	NOUN
cana-1429	28	20	that	that	PRON
cana-1429	28	21	has	have	AUX
cana-1429	28	22	been	be	AUX
cana-1429	28	23	widely	widely	ADV
cana-1429	28	24	used	use	VERB
cana-1429	28	25	for	for	ADP
cana-1429	28	26	prediction	prediction	NOUN
cana-1429	28	27	,	,	PUNCT
cana-1429	28	28	classification	classification	NOUN
cana-1429	28	29	,	,	PUNCT
cana-1429	28	30	and	and	CCONJ
cana-1429	28	31	decision	decision	NOUN
cana-1429	28	32	-	-	PUNCT
cana-1429	28	33	making	making	NOUN
cana-1429	28	34	.	.	PUNCT
cana-1429	29	1	in	in	ADP
cana-1429	29	2	three	three	NUM
cana-1429	29	3	open	open	ADJ
cana-1429	29	4	-	-	PUNCT
cana-1429	29	5	source	source	NOUN
cana-1429	29	6	datasets	dataset	NOUN
cana-1429	29	7	,	,	PUNCT
cana-1429	29	8	it	it	PRON
cana-1429	29	9	outperformed	outperform	VERB
cana-1429	29	10	previous	previous	ADJ
cana-1429	29	11	approaches	approach	NOUN
cana-1429	29	12	in	in	ADP
cana-1429	29	13	terms	term	NOUN
cana-1429	29	14	of	of	ADP
cana-1429	29	15	imputation	imputation	NOUN
cana-1429	29	16	accuracy	accuracy	NOUN
cana-1429	29	17	while	while	SCONJ
cana-1429	29	18	replacing	replace	VERB
cana-1429	29	19	mar	mar	PROPN
cana-1429	29	20	data	datum	NOUN
cana-1429	29	21	.	.	PUNCT
cana-1429	30	1	the	the	DET
cana-1429	30	2	primary	primary	ADJ
cana-1429	30	3	goal	goal	NOUN
cana-1429	30	4	of	of	ADP
cana-1429	30	5	this	this	DET
cana-1429	30	6	research	research	NOUN
cana-1429	30	7	was	be	AUX
cana-1429	30	8	to	to	PART
cana-1429	30	9	see	see	VERB
cana-1429	30	10	how	how	SCONJ
cana-1429	30	11	accurate	accurate	ADJ
cana-1429	30	12	ann	ann	PROPN
cana-1429	30	13	was	be	AUX
cana-1429	30	14	in	in	ADP
cana-1429	30	15	imputing	impute	VERB
cana-1429	30	16	missing	miss	VERB
cana-1429	30	17	values	value	NOUN
cana-1429	30	18	in	in	ADP
cana-1429	30	19	categorical	categorical	ADJ
cana-1429	30	20	variables	variable	NOUN
cana-1429	30	21	.	.	PUNCT
cana-1429	31	1	this	this	DET
cana-1429	31	2	research	research	NOUN
cana-1429	31	3	also	also	ADV
cana-1429	31	4	sought	seek	VERB
cana-1429	31	5	to	to	PART
cana-1429	31	6	compare	compare	VERB
cana-1429	31	7	its	its	PRON
cana-1429	31	8	results	result	NOUN
cana-1429	31	9	to	to	ADP
cana-1429	31	10	those	those	PRON
cana-1429	31	11	of	of	ADP
cana-1429	31	12	mice	mouse	NOUN
cana-1429	31	13	and	and	CCONJ
cana-1429	31	14	random	random	ADJ
cana-1429	31	15	forest	forest	NOUN
cana-1429	31	16	.	.	PUNCT
cana-1429	32	1	2	2	X
cana-1429	32	2	.	.	X
cana-1429	32	3	related	relate	VERB
cana-1429	32	4	work	work	NOUN
cana-1429	32	5	this	this	DET
cana-1429	32	6	section	section	NOUN
cana-1429	32	7	examines	examine	VERB
cana-1429	32	8	few	few	ADJ
cana-1429	32	9	representative	representative	ADJ
cana-1429	32	10	works	work	NOUN
cana-1429	32	11	that	that	PRON
cana-1429	32	12	use	use	VERB
cana-1429	32	13	deep	deep	ADJ
cana-1429	32	14	learning	learning	NOUN
cana-1429	32	15	to	to	PART
cana-1429	32	16	handle	handle	VERB
cana-1429	32	17	missing	miss	VERB
cana-1429	32	18	data	datum	NOUN
cana-1429	32	19	.	.	PUNCT
cana-1429	33	1	many	many	ADJ
cana-1429	33	2	researches	research	NOUN
cana-1429	33	3	have	have	AUX
cana-1429	33	4	been	be	AUX
cana-1429	33	5	undertaken	undertake	VERB
cana-1429	33	6	to	to	PART
cana-1429	33	7	address	address	VERB
cana-1429	33	8	the	the	DET
cana-1429	33	9	issue	issue	NOUN
cana-1429	33	10	of	of	ADP
cana-1429	33	11	“	"	PUNCT
cana-1429	33	12	missing	missing	ADJ
cana-1429	33	13	data	datum	NOUN
cana-1429	33	14	”	"	PUNCT
cana-1429	33	15	,	,	PUNCT
cana-1429	33	16	which	which	PRON
cana-1429	33	17	is	be	AUX
cana-1429	33	18	a	a	DET
cana-1429	33	19	widespread	widespread	ADJ
cana-1429	33	20	problem	problem	NOUN
cana-1429	33	21	in	in	ADP
cana-1429	33	22	many	many	ADJ
cana-1429	33	23	data	data	NOUN
cana-1429	33	24	-	-	PUNCT
cana-1429	33	25	driven	drive	VERB
cana-1429	33	26	systems	system	NOUN
cana-1429	33	27	.	.	PUNCT
cana-1429	34	1	in	in	ADP
cana-1429	34	2	their	their	PRON
cana-1429	34	3	article	article	NOUN
cana-1429	34	4	“	"	PUNCT
cana-1429	34	5	analysis	analysis	NOUN
cana-1429	34	6	of	of	ADP
cana-1429	34	7	backpropagation	backpropagation	NOUN
cana-1429	34	8	neural	neural	ADJ
cana-1429	34	9	neural	neural	ADJ
cana-1429	34	10	network	network	NOUN
cana-1429	34	11	algorithm	algorithm	NOUN
cana-1429	34	12	on	on	ADP
cana-1429	34	13	student	student	NOUN
cana-1429	34	14	ability	ability	NOUN
cana-1429	34	15	based	base	VERB
cana-1429	34	16	cognitive	cognitive	ADJ
cana-1429	34	17	aspects	aspect	NOUN
cana-1429	34	18	”	"	PUNCT
cana-1429	34	19	,	,	PUNCT
cana-1429	34	20	izhari	izhari	VERB
cana-1429	34	21	et	et	PROPN
cana-1429	34	22	al	al	PROPN
cana-1429	34	23	.	.	PROPN
cana-1429	34	24	,	,	PUNCT
cana-1429	34	25	(	(	PUNCT
cana-1429	34	26	2020	2020	NUM
cana-1429	34	27	)	)	PUNCT
cana-1429	34	28	,	,	PUNCT
cana-1429	34	29	used	use	VERB
cana-1429	34	30	a	a	DET
cana-1429	34	31	dataset	dataset	NOUN
cana-1429	34	32	for	for	ADP
cana-1429	34	33	predictions	prediction	NOUN
cana-1429	34	34	using	use	VERB
cana-1429	34	35	"	"	PUNCT
cana-1429	34	36	artificial	artificial	ADJ
cana-1429	34	37	neural	neural	ADJ
cana-1429	34	38	networks	network	NOUN
cana-1429	34	39	"	"	PUNCT
cana-1429	34	40	with	with	ADP
cana-1429	34	41	"	"	PUNCT
cana-1429	34	42	back	back	ADJ
cana-1429	34	43	propagation	propagation	NOUN
cana-1429	34	44	"	"	PUNCT
cana-1429	34	45	for	for	ADP
cana-1429	34	46	the	the	DET
cana-1429	34	47	maximum	maximum	ADJ
cana-1429	34	48	accuracy	accuracy	NOUN
cana-1429	34	49	in	in	ADP
cana-1429	34	50	“	"	PUNCT
cana-1429	34	51	binary	binary	NOUN
cana-1429	34	52	”	"	PUNCT
cana-1429	34	53	and	and	CCONJ
cana-1429	34	54	“	"	PUNCT
cana-1429	34	55	bipolar	bipolar	ADJ
cana-1429	34	56	sigmoid	sigmoid	NOUN
cana-1429	34	57	”	"	PUNCT
cana-1429	34	58	to	to	PART
cana-1429	34	59	estimate	estimate	VERB
cana-1429	34	60	children	child	NOUN
cana-1429	34	61	's	's	PART
cana-1429	34	62	cognitive	cognitive	ADJ
cana-1429	34	63	abilities	ability	NOUN
cana-1429	34	64	.	.	PUNCT
cana-1429	35	1	with	with	ADP
cana-1429	35	2	considerable	considerable	ADJ
cana-1429	35	3	success	success	NOUN
cana-1429	35	4	,	,	PUNCT
cana-1429	35	5	the	the	DET
cana-1429	35	6	“	"	PUNCT
cana-1429	35	7	back	back	ADJ
cana-1429	35	8	propagation	propagation	NOUN
cana-1429	35	9	artificial	artificial	ADJ
cana-1429	35	10	neural	neural	ADJ
cana-1429	35	11	network	network	NOUN
cana-1429	35	12	”	"	PUNCT
cana-1429	35	13	technique	technique	NOUN
cana-1429	35	14	is	be	AUX
cana-1429	35	15	utilised	utilise	VERB
cana-1429	35	16	to	to	PART
cana-1429	35	17	predict	predict	VERB
cana-1429	35	18	students	student	NOUN
cana-1429	35	19	’	'	PUNCT
cana-1429	35	20	ability	ability	NOUN
cana-1429	35	21	on	on	ADP
cana-1429	35	22	cognitive	cognitive	ADJ
cana-1429	35	23	assessments	assessment	NOUN
cana-1429	35	24	.	.	PUNCT
cana-1429	36	1	cihan	cihan	INTJ
cana-1429	36	2	,	,	PUNCT
cana-1429	36	3	p.	p.	NOUN
cana-1429	36	4	(	(	PUNCT
cana-1429	36	5	2020	2020	NUM
cana-1429	36	6	)	)	PUNCT
cana-1429	36	7	in	in	ADP
cana-1429	36	8	his	his	PRON
cana-1429	36	9	article	article	NOUN
cana-1429	36	10	“	"	PUNCT
cana-1429	36	11	deep	deep	ADJ
cana-1429	36	12	learning	learning	NOUN
cana-1429	36	13	-	-	PUNCT
cana-1429	36	14	based	base	VERB
cana-1429	36	15	approach	approach	NOUN
cana-1429	36	16	for	for	ADP
cana-1429	36	17	missing	miss	VERB
cana-1429	36	18	data	data	NOUN
cana-1429	36	19	imputation	imputation	NOUN
cana-1429	36	20	”	"	PUNCT
cana-1429	36	21	used	use	VERB
cana-1429	36	22	denoising	denoise	VERB
cana-1429	36	23	autoencoder	autoencoder	NOUN
cana-1429	36	24	on	on	ADP
cana-1429	36	25	dna	dna	PROPN
cana-1429	36	26	,	,	PUNCT
cana-1429	36	27	wine	wine	NOUN
cana-1429	36	28	&	&	CCONJ
cana-1429	36	29	shuttle	shuttle	PROPN
cana-1429	36	30	data	datum	NOUN
cana-1429	36	31	and	and	CCONJ
cana-1429	36	32	compared	compare	VERB
cana-1429	36	33	the	the	DET
cana-1429	36	34	results	result	NOUN
cana-1429	36	35	with	with	ADP
cana-1429	36	36	knn	knn	PROPN
cana-1429	36	37	and	and	CCONJ
cana-1429	36	38	mice	mouse	NOUN
cana-1429	36	39	.	.	PUNCT
cana-1429	37	1	he	he	PRON
cana-1429	37	2	concluded	conclude	VERB
cana-1429	37	3	that	that	SCONJ
cana-1429	37	4	deep	deep	ADJ
cana-1429	37	5	learning	learning	NOUN
cana-1429	37	6	-	-	PUNCT
cana-1429	37	7	based	base	VERB
cana-1429	37	8	approach	approach	NOUN
cana-1429	37	9	outperforms	outperform	VERB
cana-1429	37	10	statistical	statistical	ADJ
cana-1429	37	11	methods	method	NOUN
cana-1429	37	12	.	.	PUNCT
cana-1429	38	1	phung	phung	PROPN
cana-1429	38	2	et	et	PROPN
cana-1429	38	3	(	(	PUNCT
cana-1429	38	4	2019	2019	NUM
cana-1429	38	5	)	)	PUNCT
cana-1429	38	6	in	in	ADP
cana-1429	38	7	their	their	PRON
cana-1429	38	8	manuscript	manuscript	NOUN
cana-1429	38	9	“	"	PUNCT
cana-1429	38	10	a	a	DET
cana-1429	38	11	deep	deep	ADJ
cana-1429	38	12	learning	learning	NOUN
cana-1429	38	13	technique	technique	NOUN
cana-1429	38	14	for	for	ADP
cana-1429	38	15	imputing	impute	VERB
cana-1429	38	16	missing	miss	VERB
cana-1429	38	17	healthcare	healthcare	NOUN
cana-1429	38	18	data	data	PROPN
cana-1429	38	19	”	"	PUNCT
cana-1429	38	20	used	use	VERB
cana-1429	38	21	denoising	denoise	VERB
cana-1429	38	22	autoencoder	autoencoder	NOUN
cana-1429	38	23	on	on	ADP
cana-1429	38	24	“	"	PUNCT
cana-1429	38	25	linked	link	VERB
cana-1429	38	26	birth	birth	NOUN
cana-1429	38	27	/	/	SYM
cana-1429	38	28	infant	infant	NOUN
cana-1429	38	29	death	death	NOUN
cana-1429	38	30	cohort	cohort	NOUN
cana-1429	38	31	”	"	PUNCT
cana-1429	38	32	data	datum	NOUN
cana-1429	38	33	records	record	NOUN
cana-1429	38	34	and	and	CCONJ
cana-1429	38	35	compared	compare	VERB
cana-1429	38	36	the	the	DET
cana-1429	38	37	outcome	outcome	NOUN
cana-1429	38	38	with	with	ADP
cana-1429	38	39	matrix	matrix	NOUN
cana-1429	38	40	factorization	factorization	NOUN
cana-1429	38	41	,	,	PUNCT
cana-1429	38	42	knn	knn	PROPN
cana-1429	38	43	,	,	PUNCT
cana-1429	38	44	svd	svd	PROPN
cana-1429	38	45	mean	mean	VERB
cana-1429	38	46	,	,	PUNCT
cana-1429	38	47	median	median	NOUN
cana-1429	38	48	and	and	CCONJ
cana-1429	38	49	concluded	conclude	VERB
cana-1429	38	50	that	that	SCONJ
cana-1429	38	51	deep	deep	ADJ
cana-1429	38	52	learning	learning	NOUN
cana-1429	38	53	method	method	NOUN
cana-1429	38	54	has	have	VERB
cana-1429	38	55	better	well	ADJ
cana-1429	38	56	accuracy	accuracy	NOUN
cana-1429	38	57	.	.	PUNCT
cana-1429	39	1	experiments	experiment	NOUN
cana-1429	39	2	show	show	VERB
cana-1429	39	3	that	that	SCONJ
cana-1429	39	4	their	their	PRON
cana-1429	39	5	method	method	NOUN
cana-1429	39	6	produces	produce	VERB
cana-1429	39	7	lower	low	ADJ
cana-1429	39	8	imputation	imputation	NOUN
cana-1429	39	9	mean	mean	VERB
cana-1429	39	10	squared	square	VERB
cana-1429	39	11	error	error	NOUN
cana-1429	39	12	than	than	ADP
cana-1429	39	13	other	other	ADJ
cana-1429	39	14	imputation	imputation	NOUN
cana-1429	39	15	methods	method	NOUN
cana-1429	39	16	.	.	PUNCT
cana-1429	40	1	to	to	PART
cana-1429	40	2	deal	deal	VERB
cana-1429	40	3	with	with	ADP
cana-1429	40	4	attributes	attribute	NOUN
cana-1429	40	5	that	that	PRON
cana-1429	40	6	had	have	VERB
cana-1429	40	7	more	more	ADJ
cana-1429	40	8	than	than	ADP
cana-1429	40	9	1	1	NUM
cana-1429	40	10	%	%	NOUN
cana-1429	40	11	"	"	PUNCT
cana-1429	40	12	missing	miss	VERB
cana-1429	40	13	data	datum	NOUN
cana-1429	40	14	,	,	PUNCT
cana-1429	40	15	"	"	PUNCT
cana-1429	40	16	desiani	desiani	PROPN
cana-1429	40	17	et	et	PROPN
cana-1429	40	18	al	al	PROPN
cana-1429	40	19	.	.	PROPN
cana-1429	41	1	(	(	PUNCT
cana-1429	41	2	2021	2021	NUM
cana-1429	41	3	)	)	PUNCT
cana-1429	41	4	employed	employ	VERB
cana-1429	41	5	"	"	PUNCT
cana-1429	41	6	artificial	artificial	ADJ
cana-1429	41	7	neural	neural	ADJ
cana-1429	41	8	network	network	NOUN
cana-1429	41	9	"	"	PUNCT
cana-1429	41	10	in	in	ADP
cana-1429	41	11	their	their	PRON
cana-1429	41	12	manuscript	manuscript	NOUN
cana-1429	41	13	“	"	PUNCT
cana-1429	41	14	handling	handle	VERB
cana-1429	41	15	missing	miss	VERB
cana-1429	41	16	data	datum	NOUN
cana-1429	41	17	using	use	VERB
cana-1429	41	18	combination	combination	NOUN
cana-1429	41	19	of	of	ADP
cana-1429	41	20	deletion	deletion	NOUN
cana-1429	41	21	technique	technique	NOUN
cana-1429	41	22	,	,	PUNCT
cana-1429	41	23	mean	mean	VERB
cana-1429	41	24	,	,	PUNCT
cana-1429	41	25	mode	mode	NOUN
cana-1429	41	26	,	,	PUNCT
cana-1429	41	27	and	and	CCONJ
cana-1429	41	28	artificial	artificial	ADJ
cana-1429	41	29	neural	neural	ADJ
cana-1429	41	30	network	network	NOUN
cana-1429	41	31	imputation	imputation	NOUN
cana-1429	41	32	for	for	ADP
cana-1429	41	33	heart	heart	NOUN
cana-1429	41	34	disease	disease	NOUN
cana-1429	41	35	dataset	dataset	NOUN
cana-1429	41	36	”	"	PUNCT
cana-1429	41	37	.	.	PUNCT
cana-1429	42	1	the	the	DET
cana-1429	42	2	outcomes	outcome	NOUN
cana-1429	42	3	of	of	ADP
cana-1429	42	4	approaches	approach	NOUN
cana-1429	42	5	and	and	CCONJ
cana-1429	42	6	procedures	procedure	NOUN
cana-1429	42	7	used	use	VERB
cana-1429	42	8	to	to	PART
cana-1429	42	9	deal	deal	VERB
cana-1429	42	10	with	with	ADP
cana-1429	42	11	“	"	PUNCT
cana-1429	42	12	missing	missing	ADJ
cana-1429	42	13	data	datum	NOUN
cana-1429	42	14	”	"	PUNCT
cana-1429	42	15	were	be	AUX
cana-1429	42	16	evaluated	evaluate	VERB
cana-1429	42	17	using	use	VERB
cana-1429	42	18	the	the	DET
cana-1429	42	19	performance	performance	NOUN
cana-1429	42	20	of	of	ADP
cana-1429	42	21	classification	classification	NOUN
cana-1429	42	22	method	method	NOUN
cana-1429	42	23	.	.	PUNCT
cana-1429	43	1	“	"	PUNCT
cana-1429	43	2	artificial	artificial	ADJ
cana-1429	43	3	neural	neural	ADJ
cana-1429	43	4	networks	network	NOUN
cana-1429	43	5	”	"	PUNCT
cana-1429	43	6	,	,	PUNCT
cana-1429	43	7	“	"	PUNCT
cana-1429	43	8	nave	nave	NOUN
cana-1429	43	9	bayes	bayes	PROPN
cana-1429	43	10	”	"	PUNCT
cana-1429	43	11	,	,	PUNCT
cana-1429	43	12	“	"	PUNCT
cana-1429	43	13	support	support	NOUN
cana-1429	43	14	vector	vector	NOUN
cana-1429	43	15	machines	machine	NOUN
cana-1429	43	16	”	"	PUNCT
cana-1429	43	17	and	and	CCONJ
cana-1429	43	18	“	"	PUNCT
cana-1429	43	19	k	k	ADJ
cana-1429	43	20	-	-	PUNCT
cana-1429	43	21	nearest	near	ADJ
cana-1429	43	22	neighbor	neighbor	NOUN
cana-1429	43	23	”	"	PUNCT
cana-1429	43	24	are	be	AUX
cana-1429	43	25	some	some	PRON
cana-1429	43	26	of	of	ADP
cana-1429	43	27	the	the	DET
cana-1429	43	28	classification	classification	NOUN
cana-1429	43	29	techniques	technique	NOUN
cana-1429	43	30	employed	employ	VERB
cana-1429	43	31	in	in	ADP
cana-1429	43	32	this	this	DET
cana-1429	43	33	research	research	NOUN
cana-1429	43	34	.	.	PUNCT
cana-1429	44	1	the	the	DET
cana-1429	44	2	accuracy	accuracy	NOUN
cana-1429	44	3	,	,	PUNCT
cana-1429	44	4	sensitivity	sensitivity	NOUN
cana-1429	44	5	,	,	PUNCT
cana-1429	44	6	specificity	specificity	NOUN
cana-1429	44	7	,	,	PUNCT
cana-1429	44	8	and	and	CCONJ
cana-1429	44	9	recall	recall	NOUN
cana-1429	44	10	of	of	ADP
cana-1429	44	11	classification	classification	NOUN
cana-1429	44	12	without	without	ADP
cana-1429	44	13	missing	miss	VERB
cana-1429	44	14	data	datum	NOUN
cana-1429	44	15	were	be	AUX
cana-1429	44	16	compared	compare	VERB
cana-1429	44	17	to	to	ADP
cana-1429	44	18	the	the	DET
cana-1429	44	19	accuracy	accuracy	NOUN
cana-1429	44	20	,	,	PUNCT
cana-1429	44	21	sensitivity	sensitivity	NOUN
cana-1429	44	22	,	,	PUNCT
cana-1429	44	23	specificity	specificity	NOUN
cana-1429	44	24	,	,	PUNCT
cana-1429	44	25	and	and	CCONJ
cana-1429	44	26	recall	recall	NOUN
cana-1429	44	27	of	of	ADP
cana-1429	44	28	classification	classification	NOUN
cana-1429	44	29	after	after	ADP
cana-1429	44	30	“	"	PUNCT
cana-1429	44	31	imputation	imputation	NOUN
cana-1429	44	32	”	"	PUNCT
cana-1429	44	33	.	.	PUNCT
cana-1429	45	1	furthermore	furthermore	ADV
cana-1429	45	2	,	,	PUNCT
cana-1429	45	3	the	the	DET
cana-1429	45	4	mean	mean	NOUN
cana-1429	45	5	squared	square	VERB
cana-1429	45	6	error	error	NOUN
cana-1429	45	7	findings	finding	NOUN
cana-1429	45	8	were	be	AUX
cana-1429	45	9	compared	compare	VERB
cana-1429	45	10	to	to	PART
cana-1429	45	11	assess	assess	VERB
cana-1429	45	12	how	how	SCONJ
cana-1429	45	13	similar	similar	ADJ
cana-1429	45	14	was	be	AUX
cana-1429	45	15	the	the	DET
cana-1429	45	16	predicted	predict	VERB
cana-1429	45	17	label	label	NOUN
cana-1429	45	18	in	in	ADP
cana-1429	45	19	categorization	categorization	NOUN
cana-1429	45	20	with	with	ADP
cana-1429	45	21	the	the	DET
cana-1429	45	22	original	original	ADJ
cana-1429	45	23	label	label	NOUN
cana-1429	45	24	.	.	PUNCT
cana-1429	46	1	artificial	artificial	ADJ
cana-1429	46	2	neural	neural	ADJ
cana-1429	46	3	network	network	NOUN
cana-1429	46	4	had	have	VERB
cana-1429	46	5	the	the	DET
cana-1429	46	6	lowest	low	ADJ
cana-1429	46	7	mean	mean	NOUN
cana-1429	46	8	squared	square	VERB
cana-1429	46	9	error	error	NOUN
cana-1429	46	10	,	,	PUNCT
cana-1429	46	11	indicating	indicate	VERB
cana-1429	46	12	that	that	SCONJ
cana-1429	46	13	when	when	SCONJ
cana-1429	46	14	compared	compare	VERB
cana-1429	46	15	to	to	ADP
cana-1429	46	16	other	other	ADJ
cana-1429	46	17	approaches	approach	NOUN
cana-1429	46	18	,	,	PUNCT
cana-1429	46	19	the	the	DET
cana-1429	46	20	artificial	artificial	ADJ
cana-1429	46	21	neural	neural	ADJ
cana-1429	46	22	network	network	NOUN
cana-1429	46	23	performed	perform	VERB
cana-1429	46	24	communications	communication	NOUN
cana-1429	46	25	on	on	ADP
cana-1429	46	26	applied	apply	VERB
cana-1429	46	27	nonlinear	nonlinear	ADJ
cana-1429	46	28	analysis	analysis	NOUN
cana-1429	46	29	issn	issn	NOUN
cana-1429	46	30	:	:	PUNCT
cana-1429	46	31	1074	1074	NUM
cana-1429	46	32	-	-	PUNCT
cana-1429	46	33	133x	133x	NUM
cana-1429	46	34	vol	vol	NOUN
cana-1429	46	35	31	31	NUM
cana-1429	46	36	no	no	NOUN
cana-1429	46	37	.	.	PUNCT
cana-1429	47	1	7s	7	NOUN
cana-1429	47	2	(	(	PUNCT
cana-1429	47	3	2024	2024	NUM
cana-1429	47	4	)	)	PUNCT
cana-1429	47	5	679	679	NUM
cana-1429	47	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1429	47	7	exceptionally	exceptionally	ADV
cana-1429	47	8	well	well	ADV
cana-1429	47	9	on	on	ADP
cana-1429	47	10	datasets	dataset	NOUN
cana-1429	47	11	with	with	ADP
cana-1429	47	12	missing	miss	VERB
cana-1429	47	13	data	datum	NOUN
cana-1429	47	14	.	.	PUNCT
cana-1429	48	1	the	the	DET
cana-1429	48	2	accuracy	accuracy	NOUN
cana-1429	48	3	,	,	PUNCT
cana-1429	48	4	specificity	specificity	NOUN
cana-1429	48	5	,	,	PUNCT
cana-1429	48	6	and	and	CCONJ
cana-1429	48	7	sensitivity	sensitivity	NOUN
cana-1429	48	8	results	result	VERB
cana-1429	48	9	for	for	ADP
cana-1429	48	10	“	"	PUNCT
cana-1429	48	11	classification	classification	NOUN
cana-1429	48	12	”	"	PUNCT
cana-1429	48	13	revealed	reveal	VERB
cana-1429	48	14	that	that	SCONJ
cana-1429	48	15	“	"	PUNCT
cana-1429	48	16	imputation	imputation	NOUN
cana-1429	48	17	”	"	PUNCT
cana-1429	48	18	of	of	ADP
cana-1429	48	19	“	"	PUNCT
cana-1429	48	20	missing	miss	VERB
cana-1429	48	21	data	datum	NOUN
cana-1429	48	22	”	"	PUNCT
cana-1429	48	23	could	could	AUX
cana-1429	48	24	improve	improve	VERB
cana-1429	48	25	classification	classification	NOUN
cana-1429	48	26	performance	performance	NOUN
cana-1429	48	27	,	,	PUNCT
cana-1429	48	28	particularly	particularly	ADV
cana-1429	48	29	with	with	ADP
cana-1429	48	30	the	the	DET
cana-1429	48	31	artificial	artificial	ADJ
cana-1429	48	32	neural	neural	ADJ
cana-1429	48	33	network	network	NOUN
cana-1429	48	34	method	method	NOUN
cana-1429	48	35	.	.	PUNCT
cana-1429	49	1	yoon	yoon	PROPN
cana-1429	49	2	et	et	PROPN
cana-1429	49	3	al	al	PROPN
cana-1429	49	4	(	(	PUNCT
cana-1429	49	5	2018	2018	NUM
cana-1429	49	6	)	)	PUNCT
cana-1429	49	7	in	in	ADP
cana-1429	49	8	their	their	PRON
cana-1429	49	9	manuscript	manuscript	NOUN
cana-1429	49	10	“	"	PUNCT
cana-1429	49	11	gain	gain	NOUN
cana-1429	49	12	:	:	PUNCT
cana-1429	49	13	missing	miss	VERB
cana-1429	49	14	data	data	NOUN
cana-1429	49	15	imputation	imputation	NOUN
cana-1429	49	16	using	use	VERB
cana-1429	49	17	generative	generative	ADJ
cana-1429	49	18	adversarial	adversarial	ADJ
cana-1429	49	19	nets	net	NOUN
cana-1429	49	20	”	"	PUNCT
cana-1429	49	21	used	use	VERB
cana-1429	49	22	imputation	imputation	NOUN
cana-1429	49	23	nets	net	NOUN
cana-1429	49	24	(	(	PUNCT
cana-1429	49	25	gain	gain	NOUN
cana-1429	49	26	)	)	PUNCT
cana-1429	49	27	on	on	ADP
cana-1429	49	28	uci	uci	PROPN
cana-1429	49	29	machine	machine	NOUN
cana-1429	49	30	learning	learn	VERB
cana-1429	49	31	repository	repository	NOUN
cana-1429	49	32	dataset	dataset	VERB
cana-1429	49	33	namely	namely	ADV
cana-1429	49	34	breast	breast	NOUN
cana-1429	49	35	,	,	PUNCT
cana-1429	49	36	spam	spam	NOUN
cana-1429	49	37	,	,	PUNCT
cana-1429	49	38	letter	letter	NOUN
cana-1429	49	39	,	,	PUNCT
cana-1429	49	40	credit	credit	NOUN
cana-1429	49	41	,	,	PUNCT
cana-1429	49	42	and	and	CCONJ
cana-1429	49	43	news	news	NOUN
cana-1429	49	44	.	.	PUNCT
cana-1429	50	1	the	the	DET
cana-1429	50	2	results	result	NOUN
cana-1429	50	3	were	be	AUX
cana-1429	50	4	compared	compare	VERB
cana-1429	50	5	with	with	ADP
cana-1429	50	6	mice	mouse	NOUN
cana-1429	50	7	,	,	PUNCT
cana-1429	50	8	missforest	missfor	ADJ
cana-1429	50	9	,	,	PUNCT
cana-1429	50	10	auto	auto	NOUN
cana-1429	50	11	-	-	PUNCT
cana-1429	50	12	encoder	encoder	NOUN
cana-1429	50	13	and	and	CCONJ
cana-1429	50	14	expectation	expectation	NOUN
cana-1429	50	15	-	-	PUNCT
cana-1429	50	16	maximization	maximization	NOUN
cana-1429	50	17	.	.	PUNCT
cana-1429	51	1	gain	gain	NOUN
cana-1429	51	2	outperforms	outperform	VERB
cana-1429	51	3	other	other	ADJ
cana-1429	51	4	“	"	PUNCT
cana-1429	51	5	state	state	NOUN
cana-1429	51	6	-	-	PUNCT
cana-1429	51	7	of	of	ADP
cana-1429	51	8	-	-	PUNCT
cana-1429	51	9	the	the	DET
cana-1429	51	10	-	-	PUNCT
cana-1429	51	11	art	art	NOUN
cana-1429	51	12	”	"	PUNCT
cana-1429	51	13	imputation	imputation	NOUN
cana-1429	51	14	methods	method	NOUN
cana-1429	51	15	.	.	PUNCT
cana-1429	52	1	dong	dong	PROPN
cana-1429	52	2	et	et	PROPN
cana-1429	52	3	al	al	PROPN
cana-1429	52	4	(	(	PUNCT
cana-1429	52	5	2021	2021	NUM
cana-1429	52	6	)	)	PUNCT
cana-1429	52	7	in	in	ADP
cana-1429	52	8	their	their	PRON
cana-1429	52	9	manuscript	manuscript	NOUN
cana-1429	52	10	“	"	PUNCT
cana-1429	52	11	generative	generative	ADJ
cana-1429	52	12	adversarial	adversarial	ADJ
cana-1429	52	13	networks	network	NOUN
cana-1429	52	14	for	for	ADP
cana-1429	52	15	imputing	impute	VERB
cana-1429	52	16	missing	miss	VERB
cana-1429	52	17	data	datum	NOUN
cana-1429	52	18	for	for	ADP
cana-1429	52	19	big	big	ADJ
cana-1429	52	20	data	datum	NOUN
cana-1429	52	21	clinical	clinical	ADJ
cana-1429	52	22	research	research	NOUN
cana-1429	52	23	”	"	PUNCT
cana-1429	52	24	used	use	VERB
cana-1429	52	25	“	"	PUNCT
cana-1429	52	26	generative	generative	ADJ
cana-1429	52	27	adversarial	adversarial	ADJ
cana-1429	52	28	imputation	imputation	NOUN
cana-1429	52	29	(	(	PUNCT
cana-1429	52	30	gain	gain	NOUN
cana-1429	52	31	)	)	PUNCT
cana-1429	52	32	”	"	PUNCT
cana-1429	52	33	on	on	ADP
cana-1429	52	34	mixed	mixed	ADJ
cana-1429	52	35	type	type	NOUN
cana-1429	52	36	of	of	ADP
cana-1429	52	37	data	datum	NOUN
cana-1429	52	38	and	and	CCONJ
cana-1429	52	39	compared	compare	VERB
cana-1429	52	40	the	the	DET
cana-1429	52	41	results	result	NOUN
cana-1429	52	42	with	with	ADP
cana-1429	52	43	“	"	PUNCT
cana-1429	52	44	mice	mouse	NOUN
cana-1429	52	45	”	"	PUNCT
cana-1429	52	46	and	and	CCONJ
cana-1429	52	47	“	"	PUNCT
cana-1429	52	48	missforest	missfor	ADJ
cana-1429	52	49	”	"	PUNCT
cana-1429	52	50	.	.	PUNCT
cana-1429	53	1	in	in	ADP
cana-1429	53	2	large	large	ADJ
cana-1429	53	3	"	"	PUNCT
cana-1429	53	4	clinical	clinical	ADJ
cana-1429	53	5	datasets	dataset	NOUN
cana-1429	53	6	"	"	PUNCT
cana-1429	53	7	,	,	PUNCT
cana-1429	53	8	gain	gain	NOUN
cana-1429	53	9	outperformed	outperform	VERB
cana-1429	53	10	"	"	PUNCT
cana-1429	53	11	mice	mouse	NOUN
cana-1429	53	12	"	"	PUNCT
cana-1429	53	13	&	&	CCONJ
cana-1429	53	14	"	"	PUNCT
cana-1429	53	15	missforest	missfor	ADJ
cana-1429	53	16	"	"	PUNCT
cana-1429	53	17	as	as	ADP
cana-1429	53	18	an	an	DET
cana-1429	53	19	"	"	PUNCT
cana-1429	53	20	imputation	imputation	NOUN
cana-1429	53	21	"	"	PUNCT
cana-1429	53	22	strategy	strategy	NOUN
cana-1429	53	23	,	,	PUNCT
cana-1429	53	24	and	and	CCONJ
cana-1429	53	25	was	be	AUX
cana-1429	53	26	more	more	ADV
cana-1429	53	27	resilient	resilient	ADJ
cana-1429	53	28	to	to	ADP
cana-1429	53	29	high	high	ADJ
cana-1429	53	30	"	"	PUNCT
cana-1429	53	31	missingness	missingness	NOUN
cana-1429	53	32	"	"	PUNCT
cana-1429	53	33	rates	rate	NOUN
cana-1429	53	34	(	(	PUNCT
cana-1429	53	35	50	50	NUM
cana-1429	53	36	%	%	NOUN
cana-1429	53	37	)	)	PUNCT
cana-1429	53	38	.	.	PUNCT
cana-1429	54	1	3	3	X
cana-1429	54	2	.	.	X
cana-1429	54	3	methodology	methodology	NOUN
cana-1429	54	4	the	the	DET
cana-1429	54	5	traditional	traditional	ADJ
cana-1429	54	6	methods	method	NOUN
cana-1429	54	7	for	for	ADP
cana-1429	54	8	dealing	deal	VERB
cana-1429	54	9	with	with	ADP
cana-1429	54	10	“	"	PUNCT
cana-1429	54	11	missing	missing	ADJ
cana-1429	54	12	data	datum	NOUN
cana-1429	54	13	”	"	PUNCT
cana-1429	54	14	can	can	AUX
cana-1429	54	15	be	be	AUX
cana-1429	54	16	categorized	categorize	VERB
cana-1429	54	17	in	in	ADP
cana-1429	54	18	two	two	NUM
cana-1429	54	19	groups	group	NOUN
cana-1429	54	20	.	.	PUNCT
cana-1429	55	1	the	the	DET
cana-1429	55	2	first	first	ADJ
cana-1429	55	3	is	be	AUX
cana-1429	55	4	deletion	deletion	NOUN
cana-1429	55	5	,	,	PUNCT
cana-1429	55	6	which	which	PRON
cana-1429	55	7	is	be	AUX
cana-1429	55	8	intended	intend	VERB
cana-1429	55	9	to	to	PART
cana-1429	55	10	erase	erase	VERB
cana-1429	55	11	all	all	DET
cana-1429	55	12	instances	instance	NOUN
cana-1429	55	13	with	with	ADP
cana-1429	55	14	missing	miss	VERB
cana-1429	55	15	values	value	NOUN
cana-1429	55	16	for	for	ADP
cana-1429	55	17	specified	specified	ADJ
cana-1429	55	18	features	feature	NOUN
cana-1429	55	19	.	.	PUNCT
cana-1429	56	1	imputation	imputation	NOUN
cana-1429	56	2	is	be	AUX
cana-1429	56	3	the	the	DET
cana-1429	56	4	second	second	ADJ
cana-1429	56	5	strategy	strategy	NOUN
cana-1429	56	6	,	,	PUNCT
cana-1429	56	7	which	which	PRON
cana-1429	56	8	seeks	seek	VERB
cana-1429	56	9	to	to	PART
cana-1429	56	10	replace	replace	VERB
cana-1429	56	11	missing	missing	ADJ
cana-1429	56	12	values	value	NOUN
cana-1429	56	13	with	with	ADP
cana-1429	56	14	some	some	DET
cana-1429	56	15	suitable	suitable	ADJ
cana-1429	56	16	ones	one	NOUN
cana-1429	56	17	(	(	PUNCT
cana-1429	56	18	cardoso	cardoso	PROPN
cana-1429	56	19	pereira	pereira	PROPN
cana-1429	56	20	et	et	PROPN
cana-1429	56	21	al	al	PROPN
cana-1429	56	22	.	.	PROPN
cana-1429	56	23	,	,	PUNCT
cana-1429	56	24	2020	2020	NUM
cana-1429	56	25	)	)	PUNCT
cana-1429	56	26	.	.	PUNCT
cana-1429	57	1	furthermore	furthermore	ADV
cana-1429	57	2	,	,	PUNCT
cana-1429	57	3	“	"	PUNCT
cana-1429	57	4	deep	deep	ADJ
cana-1429	57	5	learning	learning	NOUN
cana-1429	57	6	”	"	PUNCT
cana-1429	57	7	has	have	AUX
cana-1429	57	8	been	be	AUX
cana-1429	57	9	widely	widely	ADV
cana-1429	57	10	applied	apply	VERB
cana-1429	57	11	in	in	ADP
cana-1429	57	12	a	a	DET
cana-1429	57	13	variety	variety	NOUN
cana-1429	57	14	of	of	ADP
cana-1429	57	15	domains	domain	NOUN
cana-1429	57	16	in	in	ADP
cana-1429	57	17	recent	recent	ADJ
cana-1429	57	18	years	year	NOUN
cana-1429	57	19	,	,	PUNCT
cana-1429	57	20	including	include	VERB
cana-1429	57	21	missing	miss	VERB
cana-1429	57	22	data	data	NOUN
cana-1429	57	23	imputation	imputation	NOUN
cana-1429	57	24	,	,	PUNCT
cana-1429	57	25	resulting	result	VERB
cana-1429	57	26	in	in	ADP
cana-1429	57	27	a	a	DET
cana-1429	57	28	significant	significant	ADJ
cana-1429	57	29	improvement	improvement	NOUN
cana-1429	57	30	in	in	ADP
cana-1429	57	31	imputation	imputation	NOUN
cana-1429	57	32	performance	performance	NOUN
cana-1429	57	33	by	by	ADP
cana-1429	57	34	utilising	utilise	VERB
cana-1429	57	35	a	a	DET
cana-1429	57	36	vast	vast	ADJ
cana-1429	57	37	amount	amount	NOUN
cana-1429	57	38	of	of	ADP
cana-1429	57	39	training	training	NOUN
cana-1429	57	40	data	datum	NOUN
cana-1429	57	41	(	(	PUNCT
cana-1429	57	42	khare	khare	PROPN
cana-1429	57	43	et	et	PROPN
cana-1429	57	44	al	al	PROPN
cana-1429	57	45	.	.	PROPN
cana-1429	57	46	,	,	PUNCT
cana-1429	57	47	2021	2021	NUM
cana-1429	57	48	,	,	PUNCT
cana-1429	57	49	yang	yang	PROPN
cana-1429	57	50	et	et	PROPN
cana-1429	57	51	al	al	PROPN
cana-1429	57	52	.	.	PROPN
cana-1429	57	53	,	,	PUNCT
cana-1429	57	54	2019	2019	NUM
cana-1429	57	55	;	;	PUNCT
cana-1429	57	56	fei	fei	PROPN
cana-1429	57	57	et	et	PROPN
cana-1429	57	58	al	al	PROPN
cana-1429	57	59	.	.	PROPN
cana-1429	57	60	,	,	PUNCT
cana-1429	57	61	2017	2017	NUM
cana-1429	57	62	)	)	PUNCT
cana-1429	57	63	.	.	PUNCT
cana-1429	58	1	as	as	ADP
cana-1429	58	2	a	a	DET
cana-1429	58	3	result	result	NOUN
cana-1429	58	4	,	,	PUNCT
cana-1429	58	5	of	of	ADP
cana-1429	58	6	their	their	PRON
cana-1429	58	7	amazing	amazing	ADJ
cana-1429	58	8	success	success	NOUN
cana-1429	58	9	,	,	PUNCT
cana-1429	58	10	“	"	PUNCT
cana-1429	58	11	artificial	artificial	ADJ
cana-1429	58	12	neural	neural	ADJ
cana-1429	58	13	networks	network	NOUN
cana-1429	58	14	”	"	PUNCT
cana-1429	58	15	(	(	PUNCT
cana-1429	58	16	ann	ann	PROPN
cana-1429	58	17	)	)	PUNCT
cana-1429	58	18	have	have	AUX
cana-1429	58	19	received	receive	VERB
cana-1429	58	20	a	a	DET
cana-1429	58	21	lot	lot	NOUN
cana-1429	58	22	of	of	ADP
cana-1429	58	23	attention	attention	NOUN
cana-1429	58	24	in	in	ADP
cana-1429	58	25	recent	recent	ADJ
cana-1429	58	26	years	year	NOUN
cana-1429	58	27	.	.	PUNCT
cana-1429	59	1	(	(	PUNCT
cana-1429	59	2	wei	wei	PROPN
cana-1429	59	3	&	&	CCONJ
cana-1429	59	4	yang	yang	PROPN
cana-1429	59	5	,	,	PUNCT
cana-1429	59	6	2021	2021	NUM
cana-1429	59	7	;	;	PUNCT
cana-1429	59	8	özden	özden	VERB
cana-1429	59	9	et	et	PROPN
cana-1429	59	10	al	al	PROPN
cana-1429	59	11	.	.	PROPN
cana-1429	59	12	,	,	PUNCT
cana-1429	59	13	2017	2017	NUM
cana-1429	59	14	;	;	PUNCT
cana-1429	59	15	wang	wang	PROPN
cana-1429	59	16	et	et	PROPN
cana-1429	59	17	al	al	PROPN
cana-1429	59	18	.	.	PROPN
cana-1429	59	19	,	,	PUNCT
cana-1429	59	20	2016	2016	NUM
cana-1429	59	21	)	)	PUNCT
cana-1429	59	22	3.1	3.1	NUM
cana-1429	59	23	artificial	artificial	ADJ
cana-1429	59	24	neural	neural	ADJ
cana-1429	59	25	network	network	NOUN
cana-1429	59	26	it	it	PRON
cana-1429	59	27	is	be	AUX
cana-1429	59	28	made	make	VERB
cana-1429	59	29	up	up	ADP
cana-1429	59	30	of	of	ADP
cana-1429	59	31	artificial	artificial	ADJ
cana-1429	59	32	neurons	neuron	NOUN
cana-1429	59	33	that	that	PRON
cana-1429	59	34	look	look	VERB
cana-1429	59	35	like	like	ADP
cana-1429	59	36	human	human	ADJ
cana-1429	59	37	brain	brain	NOUN
cana-1429	59	38	neurons	neuron	NOUN
cana-1429	59	39	.	.	PUNCT
cana-1429	60	1	it	it	PRON
cana-1429	60	2	is	be	AUX
cana-1429	60	3	a	a	DET
cana-1429	60	4	collection	collection	NOUN
cana-1429	60	5	of	of	ADP
cana-1429	60	6	artificial	artificial	ADJ
cana-1429	60	7	neurons	neuron	NOUN
cana-1429	60	8	(	(	PUNCT
cana-1429	60	9	known	know	VERB
cana-1429	60	10	as	as	ADP
cana-1429	60	11	processing	processing	NOUN
cana-1429	60	12	units	unit	NOUN
cana-1429	60	13	)	)	PUNCT
cana-1429	60	14	that	that	PRON
cana-1429	60	15	are	be	AUX
cana-1429	60	16	linked	link	VERB
cana-1429	60	17	to	to	ADP
cana-1429	60	18	one	one	NUM
cana-1429	60	19	another	another	DET
cana-1429	60	20	.	.	PUNCT
cana-1429	61	1	a	a	DET
cana-1429	61	2	weight	weight	NOUN
cana-1429	61	3	is	be	AUX
cana-1429	61	4	assigned	assign	VERB
cana-1429	61	5	to	to	ADP
cana-1429	61	6	each	each	DET
cana-1429	61	7	link	link	NOUN
cana-1429	61	8	,	,	PUNCT
cana-1429	61	9	which	which	PRON
cana-1429	61	10	symbolises	symbolise	VERB
cana-1429	61	11	the	the	DET
cana-1429	61	12	influence	influence	NOUN
cana-1429	61	13	of	of	ADP
cana-1429	61	14	one	one	NUM
cana-1429	61	15	neuron	neuron	NOUN
cana-1429	61	16	on	on	ADP
cana-1429	61	17	the	the	DET
cana-1429	61	18	other	other	ADJ
cana-1429	61	19	.	.	PUNCT
cana-1429	62	1	the	the	DET
cana-1429	62	2	signals	signal	NOUN
cana-1429	62	3	to	to	PART
cana-1429	62	4	conduct	conduct	VERB
cana-1429	62	5	the	the	DET
cana-1429	62	6	activities	activity	NOUN
cana-1429	62	7	are	be	AUX
cana-1429	62	8	sent	send	VERB
cana-1429	62	9	by	by	ADP
cana-1429	62	10	neurons	neuron	NOUN
cana-1429	62	11	in	in	ADP
cana-1429	62	12	the	the	DET
cana-1429	62	13	brain	brain	NOUN
cana-1429	62	14	.	.	PUNCT
cana-1429	63	1	artificial	artificial	ADJ
cana-1429	63	2	neurons	neuron	NOUN
cana-1429	63	3	link	link	VERB
cana-1429	63	4	in	in	ADP
cana-1429	63	5	a	a	DET
cana-1429	63	6	neural	neural	ADJ
cana-1429	63	7	network	network	NOUN
cana-1429	63	8	to	to	PART
cana-1429	63	9	complete	complete	VERB
cana-1429	63	10	tasks	task	NOUN
cana-1429	63	11	in	in	ADP
cana-1429	63	12	a	a	DET
cana-1429	63	13	similar	similar	ADJ
cana-1429	63	14	way	way	NOUN
cana-1429	63	15	.	.	PUNCT
cana-1429	64	1	(	(	PUNCT
cana-1429	64	2	silva	silva	NOUN
cana-1429	64	3	-	-	PUNCT
cana-1429	64	4	ramrez	ramrez	NOUN
cana-1429	64	5	and	and	CCONJ
cana-1429	64	6	colleagues	colleague	NOUN
cana-1429	64	7	,	,	PUNCT
cana-1429	64	8	2015	2015	NUM
cana-1429	64	9	)	)	PUNCT
cana-1429	64	10	the	the	DET
cana-1429	64	11	term	term	NOUN
cana-1429	64	12	"	"	PUNCT
cana-1429	64	13	network	network	NOUN
cana-1429	64	14	"	"	PUNCT
cana-1429	64	15	refers	refer	VERB
cana-1429	64	16	to	to	ADP
cana-1429	64	17	the	the	DET
cana-1429	64	18	connections	connection	NOUN
cana-1429	64	19	between	between	ADP
cana-1429	64	20	"	"	PUNCT
cana-1429	64	21	neurons	neuron	NOUN
cana-1429	64	22	"	"	PUNCT
cana-1429	64	23	in	in	ADP
cana-1429	64	24	different	different	ADJ
cana-1429	64	25	layers	layer	NOUN
cana-1429	64	26	.	.	PUNCT
cana-1429	65	1	every	every	DET
cana-1429	65	2	system	system	NOUN
cana-1429	65	3	is	be	AUX
cana-1429	65	4	made	make	VERB
cana-1429	65	5	up	up	ADP
cana-1429	65	6	of	of	ADP
cana-1429	65	7	three	three	NUM
cana-1429	65	8	layers	layer	NOUN
cana-1429	65	9	:	:	PUNCT
cana-1429	65	10	an	an	DET
cana-1429	65	11	“	"	PUNCT
cana-1429	65	12	input	input	NOUN
cana-1429	65	13	layer	layer	NOUN
cana-1429	65	14	”	"	PUNCT
cana-1429	65	15	,	,	PUNCT
cana-1429	65	16	a	a	DET
cana-1429	65	17	“	"	PUNCT
cana-1429	65	18	hidden	hidden	ADJ
cana-1429	65	19	layer	layer	NOUN
cana-1429	65	20	”	"	PUNCT
cana-1429	65	21	and	and	CCONJ
cana-1429	65	22	an	an	DET
cana-1429	65	23	“	"	PUNCT
cana-1429	65	24	output	output	NOUN
cana-1429	65	25	layer	layer	NOUN
cana-1429	65	26	”	"	PUNCT
cana-1429	65	27	(	(	PUNCT
cana-1429	65	28	saputra	saputra	PROPN
cana-1429	65	29	et	et	PROPN
cana-1429	65	30	al	al	PROPN
cana-1429	65	31	.	.	PROPN
cana-1429	65	32	,	,	PUNCT
cana-1429	65	33	2017	2017	NUM
cana-1429	65	34	)	)	PUNCT
cana-1429	65	35	.	.	PUNCT
cana-1429	66	1	the	the	PRON
cana-1429	66	2	“	"	PUNCT
cana-1429	66	3	input	input	NOUN
cana-1429	66	4	layer	layer	NOUN
cana-1429	66	5	”	"	PUNCT
cana-1429	66	6	contains	contain	VERB
cana-1429	66	7	input	input	NOUN
cana-1429	66	8	“	"	PUNCT
cana-1429	66	9	neurons	neuron	NOUN
cana-1429	66	10	”	"	PUNCT
cana-1429	66	11	that	that	PRON
cana-1429	66	12	send	send	VERB
cana-1429	66	13	data	datum	NOUN
cana-1429	66	14	to	to	ADP
cana-1429	66	15	the	the	DET
cana-1429	66	16	“	"	PUNCT
cana-1429	66	17	output	output	NOUN
cana-1429	66	18	layer	layer	NOUN
cana-1429	66	19	”	"	PUNCT
cana-1429	66	20	via	via	ADP
cana-1429	66	21	“	"	PUNCT
cana-1429	66	22	synapses	synapsis	NOUN
cana-1429	66	23	”	"	PUNCT
cana-1429	66	24	.	.	PUNCT
cana-1429	67	1	communications	communication	NOUN
cana-1429	67	2	on	on	ADP
cana-1429	67	3	applied	apply	VERB
cana-1429	67	4	nonlinear	nonlinear	ADJ
cana-1429	67	5	analysis	analysis	NOUN
cana-1429	67	6	issn	issn	NOUN
cana-1429	67	7	:	:	PUNCT
cana-1429	67	8	1074	1074	NUM
cana-1429	67	9	-	-	PUNCT
cana-1429	67	10	133x	133x	NUM
cana-1429	67	11	vol	vol	NOUN
cana-1429	67	12	31	31	NUM
cana-1429	67	13	no	no	NOUN
cana-1429	67	14	.	.	PUNCT
cana-1429	68	1	7s	7	NOUN
cana-1429	68	2	(	(	PUNCT
cana-1429	68	3	2024	2024	NUM
cana-1429	68	4	)	)	PUNCT
cana-1429	68	5	680	680	NUM
cana-1429	68	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1429	68	7	figure	figure	NOUN
cana-1429	68	8	1	1	NUM
cana-1429	68	9	:	:	PUNCT
cana-1429	68	10	backpropagation	backpropagation	NOUN
cana-1429	68	11	neural	neural	ADJ
cana-1429	68	12	network	network	NOUN
cana-1429	68	13	the	the	DET
cana-1429	68	14	basic	basic	ADJ
cana-1429	68	15	concept	concept	NOUN
cana-1429	68	16	underlying	underlie	VERB
cana-1429	68	17	training	training	NOUN
cana-1429	68	18	is	be	AUX
cana-1429	68	19	to	to	PART
cana-1429	68	20	select	select	VERB
cana-1429	68	21	a	a	DET
cana-1429	68	22	set	set	NOUN
cana-1429	68	23	of	of	ADP
cana-1429	68	24	weights	weight	NOUN
cana-1429	68	25	at	at	ADP
cana-1429	68	26	random	random	ADJ
cana-1429	68	27	,	,	PUNCT
cana-1429	68	28	apply	apply	VERB
cana-1429	68	29	inputs	input	NOUN
cana-1429	68	30	to	to	ADP
cana-1429	68	31	“	"	PUNCT
cana-1429	68	32	neural	neural	ADJ
cana-1429	68	33	net	net	NOUN
cana-1429	68	34	”	"	PUNCT
cana-1429	68	35	and	and	CCONJ
cana-1429	68	36	compare	compare	VERB
cana-1429	68	37	output	output	NOUN
cana-1429	68	38	to	to	ADP
cana-1429	68	39	the	the	DET
cana-1429	68	40	weights	weight	NOUN
cana-1429	68	41	assigned	assign	VERB
cana-1429	68	42	.	.	PUNCT
cana-1429	69	1	the	the	DET
cana-1429	69	2	calculated	calculate	VERB
cana-1429	69	3	value	value	NOUN
cana-1429	69	4	is	be	AUX
cana-1429	69	5	compared	compare	VERB
cana-1429	69	6	with	with	ADP
cana-1429	69	7	real	real	ADJ
cana-1429	69	8	one	one	NUM
cana-1429	69	9	.	.	PUNCT
cana-1429	70	1	using	use	VERB
cana-1429	70	2	generalised	generalise	VERB
cana-1429	70	3	delta	delta	NOUN
cana-1429	70	4	rule	rule	NOUN
cana-1429	70	5	,	,	PUNCT
cana-1429	70	6	difference	difference	NOUN
cana-1429	70	7	is	be	AUX
cana-1429	70	8	used	use	VERB
cana-1429	70	9	to	to	PART
cana-1429	70	10	update	update	VERB
cana-1429	70	11	the	the	DET
cana-1429	70	12	weights	weight	NOUN
cana-1429	70	13	of	of	ADP
cana-1429	70	14	each	each	DET
cana-1429	70	15	layer	layer	NOUN
cana-1429	70	16	.	.	PUNCT
cana-1429	71	1	back	back	ADJ
cana-1429	71	2	propagation	propagation	NOUN
cana-1429	71	3	is	be	AUX
cana-1429	71	4	the	the	DET
cana-1429	71	5	name	name	NOUN
cana-1429	71	6	of	of	ADP
cana-1429	71	7	the	the	DET
cana-1429	71	8	training	training	NOUN
cana-1429	71	9	algorithm	algorithm	NOUN
cana-1429	71	10	.	.	PUNCT
cana-1429	72	1	when	when	SCONJ
cana-1429	72	2	the	the	DET
cana-1429	72	3	error	error	NOUN
cana-1429	72	4	between	between	ADP
cana-1429	72	5	actual	actual	ADJ
cana-1429	72	6	output	output	NOUN
cana-1429	72	7	and	and	CCONJ
cana-1429	72	8	computed	compute	VERB
cana-1429	72	9	output	output	NOUN
cana-1429	72	10	is	be	AUX
cana-1429	72	11	smaller	small	ADJ
cana-1429	72	12	than	than	ADP
cana-1429	72	13	previously	previously	ADV
cana-1429	72	14	determined	determine	VERB
cana-1429	72	15	number	number	NOUN
cana-1429	72	16	,	,	PUNCT
cana-1429	72	17	after	after	ADP
cana-1429	72	18	several	several	ADJ
cana-1429	72	19	training	training	NOUN
cana-1429	72	20	epochs	epoch	NOUN
cana-1429	72	21	,	,	PUNCT
cana-1429	72	22	the	the	DET
cana-1429	72	23	neural	neural	ADJ
cana-1429	72	24	net	net	NOUN
cana-1429	72	25	is	be	AUX
cana-1429	72	26	considered	consider	VERB
cana-1429	72	27	trained	train	VERB
cana-1429	72	28	.	.	PUNCT
cana-1429	73	1	after	after	ADP
cana-1429	73	2	being	be	AUX
cana-1429	73	3	trained	train	VERB
cana-1429	73	4	,	,	PUNCT
cana-1429	73	5	the	the	DET
cana-1429	73	6	“	"	PUNCT
cana-1429	73	7	neural	neural	ADJ
cana-1429	73	8	net	net	NOUN
cana-1429	73	9	”	"	PUNCT
cana-1429	73	10	can	can	AUX
cana-1429	73	11	be	be	AUX
cana-1429	73	12	used	use	VERB
cana-1429	73	13	to	to	PART
cana-1429	73	14	analyse	analyse	VERB
cana-1429	73	15	fresh	fresh	ADJ
cana-1429	73	16	data	datum	NOUN
cana-1429	73	17	and	and	CCONJ
cana-1429	73	18	classify	classify	VERB
cana-1429	73	19	it	it	PRON
cana-1429	73	20	according	accord	VERB
cana-1429	73	21	to	to	ADP
cana-1429	73	22	the	the	DET
cana-1429	73	23	information	information	NOUN
cana-1429	73	24	it	it	PRON
cana-1429	73	25	requires	require	VERB
cana-1429	73	26	.	.	PUNCT
cana-1429	74	1	the	the	DET
cana-1429	74	2	“	"	PUNCT
cana-1429	74	3	neuralnet	neuralnet	NOUN
cana-1429	74	4	”	"	PUNCT
cana-1429	74	5	library	library	NOUN
cana-1429	74	6	in	in	ADP
cana-1429	74	7	r	r	NOUN
cana-1429	74	8	makes	make	VERB
cana-1429	74	9	this	this	DET
cana-1429	74	10	simple	simple	NOUN
cana-1429	74	11	.	.	PUNCT
cana-1429	75	1	3.2	3.2	NUM
cana-1429	75	2	multiple	multiple	ADJ
cana-1429	75	3	imputation	imputation	NOUN
cana-1429	75	4	it	it	PRON
cana-1429	75	5	is	be	AUX
cana-1429	75	6	a	a	DET
cana-1429	75	7	three	three	NUM
cana-1429	75	8	-	-	PUNCT
cana-1429	75	9	stage	stage	NOUN
cana-1429	75	10	statistical	statistical	ADJ
cana-1429	75	11	strategy	strategy	NOUN
cana-1429	75	12	for	for	ADP
cana-1429	75	13	coping	cope	VERB
cana-1429	75	14	with	with	ADP
cana-1429	75	15	missing	miss	VERB
cana-1429	75	16	values	value	NOUN
cana-1429	75	17	,	,	PUNCT
cana-1429	75	18	i	i	NOUN
cana-1429	75	19	)	)	PUNCT
cana-1429	75	20	data	datum	NOUN
cana-1429	75	21	imputation	imputation	NOUN
cana-1429	75	22	,	,	PUNCT
cana-1429	75	23	which	which	PRON
cana-1429	75	24	generates	generate	VERB
cana-1429	75	25	m	m	VERB
cana-1429	75	26	imputed	impute	VERB
cana-1429	75	27	data	data	NOUN
cana-1429	75	28	sets	set	NOUN
cana-1429	75	29	from	from	ADP
cana-1429	75	30	a	a	DET
cana-1429	75	31	distribution	distribution	NOUN
cana-1429	75	32	that	that	PRON
cana-1429	75	33	yields	yield	VERB
cana-1429	75	34	m	m	VERB
cana-1429	75	35	full	full	ADJ
cana-1429	75	36	data	data	NOUN
cana-1429	75	37	sets	set	NOUN
cana-1429	75	38	,	,	PUNCT
cana-1429	75	39	ii	ii	NOUN
cana-1429	75	40	)	)	PUNCT
cana-1429	75	41	complete	complete	ADJ
cana-1429	75	42	data	datum	NOUN
cana-1429	75	43	analysis	analysis	NOUN
cana-1429	75	44	,	,	PUNCT
cana-1429	75	45	which	which	PRON
cana-1429	75	46	is	be	AUX
cana-1429	75	47	done	do	VERB
cana-1429	75	48	on	on	ADP
cana-1429	75	49	each	each	PRON
cana-1429	75	50	of	of	ADP
cana-1429	75	51	the	the	DET
cana-1429	75	52	m	m	ADV
cana-1429	75	53	imputed	impute	VERB
cana-1429	75	54	data	data	NOUN
cana-1429	75	55	sets	set	NOUN
cana-1429	75	56	,	,	PUNCT
cana-1429	75	57	and	and	CCONJ
cana-1429	75	58	iii	iii	X
cana-1429	75	59	)	)	PUNCT
cana-1429	75	60	data	datum	NOUN
cana-1429	75	61	pooling	pooling	NOUN
cana-1429	75	62	,	,	PUNCT
cana-1429	75	63	which	which	PRON
cana-1429	75	64	uses	use	VERB
cana-1429	75	65	simple	simple	ADJ
cana-1429	75	66	principles	principle	NOUN
cana-1429	75	67	to	to	PART
cana-1429	75	68	pool	pool	VERB
cana-1429	75	69	the	the	DET
cana-1429	75	70	data	datum	NOUN
cana-1429	75	71	acquired	acquire	VERB
cana-1429	75	72	through	through	ADP
cana-1429	75	73	data	datum	NOUN
cana-1429	75	74	analysis	analysis	NOUN
cana-1429	75	75	.	.	PUNCT
cana-1429	76	1	multiple	multiple	ADJ
cana-1429	76	2	imputation	imputation	NOUN
cana-1429	76	3	is	be	AUX
cana-1429	76	4	a	a	DET
cana-1429	76	5	method	method	NOUN
cana-1429	76	6	for	for	ADP
cana-1429	76	7	replacing	replace	VERB
cana-1429	76	8	missing	miss	VERB
cana-1429	76	9	values	value	NOUN
cana-1429	76	10	with	with	ADP
cana-1429	76	11	potential	potential	ADJ
cana-1429	76	12	solutions	solution	NOUN
cana-1429	76	13	.	.	PUNCT
cana-1429	77	1	using	use	VERB
cana-1429	77	2	imputation	imputation	NOUN
cana-1429	77	3	methods	method	NOUN
cana-1429	77	4	,	,	PUNCT
cana-1429	77	5	the	the	DET
cana-1429	77	6	incomplete	incomplete	ADJ
cana-1429	77	7	dataset	dataset	NOUN
cana-1429	77	8	is	be	AUX
cana-1429	77	9	turned	turn	VERB
cana-1429	77	10	into	into	ADP
cana-1429	77	11	a	a	DET
cana-1429	77	12	complete	complete	ADJ
cana-1429	77	13	dataset	dataset	NOUN
cana-1429	77	14	that	that	PRON
cana-1429	77	15	may	may	AUX
cana-1429	77	16	then	then	ADV
cana-1429	77	17	be	be	AUX
cana-1429	77	18	analysed	analyse	VERB
cana-1429	77	19	using	use	VERB
cana-1429	77	20	any	any	DET
cana-1429	77	21	standard	standard	ADJ
cana-1429	77	22	analysis	analysis	NOUN
cana-1429	77	23	approach	approach	NOUN
cana-1429	77	24	.	.	PUNCT
cana-1429	78	1	as	as	ADP
cana-1429	78	2	a	a	DET
cana-1429	78	3	result	result	NOUN
cana-1429	78	4	,	,	PUNCT
cana-1429	78	5	multiple	multiple	ADJ
cana-1429	78	6	imputations	imputation	NOUN
cana-1429	78	7	have	have	AUX
cana-1429	78	8	become	become	VERB
cana-1429	78	9	popular	popular	ADJ
cana-1429	78	10	for	for	ADP
cana-1429	78	11	dealing	deal	VERB
cana-1429	78	12	with	with	ADP
cana-1429	78	13	missing	miss	VERB
cana-1429	78	14	data	datum	NOUN
cana-1429	78	15	.	.	PUNCT
cana-1429	79	1	the	the	DET
cana-1429	79	2	process	process	NOUN
cana-1429	79	3	is	be	AUX
cana-1429	79	4	done	do	VERB
cana-1429	79	5	numerous	numerous	ADJ
cana-1429	79	6	times	time	NOUN
cana-1429	79	7	for	for	ADP
cana-1429	79	8	all	all	DET
cana-1429	79	9	variables	variable	NOUN
cana-1429	79	10	with	with	ADP
cana-1429	79	11	missing	miss	VERB
cana-1429	79	12	values	value	NOUN
cana-1429	79	13	in	in	ADP
cana-1429	79	14	the	the	DET
cana-1429	79	15	multiple	multiple	ADJ
cana-1429	79	16	imputation	imputation	NOUN
cana-1429	79	17	technique	technique	NOUN
cana-1429	79	18	,	,	PUNCT
cana-1429	79	19	as	as	SCONJ
cana-1429	79	20	the	the	DET
cana-1429	79	21	name	name	NOUN
cana-1429	79	22	implies	imply	VERB
cana-1429	79	23	,	,	PUNCT
cana-1429	79	24	and	and	CCONJ
cana-1429	79	25	then	then	ADV
cana-1429	79	26	analysed	analyse	VERB
cana-1429	79	27	to	to	PART
cana-1429	79	28	aggregate	aggregate	VERB
cana-1429	79	29	m	m	NOUN
cana-1429	79	30	number	number	NOUN
cana-1429	79	31	of	of	ADP
cana-1429	79	32	imputed	impute	VERB
cana-1429	79	33	data	data	NOUN
cana-1429	79	34	sets	set	NOUN
cana-1429	79	35	into	into	ADP
cana-1429	79	36	one	one	NUM
cana-1429	79	37	imputed	impute	VERB
cana-1429	79	38	data	datum	NOUN
cana-1429	79	39	set	set	VERB
cana-1429	79	40	.	.	PUNCT
cana-1429	80	1	for	for	ADP
cana-1429	80	2	this	this	PRON
cana-1429	80	3	,	,	PUNCT
cana-1429	80	4	“	"	PUNCT
cana-1429	80	5	r	r	NOUN
cana-1429	80	6	”	"	PUNCT
cana-1429	80	7	supplies	supply	VERB
cana-1429	80	8	the	the	DET
cana-1429	80	9	mice	mouse	NOUN
cana-1429	80	10	package	package	NOUN
cana-1429	80	11	,	,	PUNCT
cana-1429	80	12	which	which	PRON
cana-1429	80	13	is	be	AUX
cana-1429	80	14	simple	simple	ADJ
cana-1429	80	15	to	to	AUX
cana-1429	80	16	use	use	VERB
cana-1429	80	17	.	.	PUNCT
cana-1429	81	1	figure	figure	NOUN
cana-1429	81	2	2	2	NUM
cana-1429	81	3	:	:	PUNCT
cana-1429	81	4	multiple	multiple	ADJ
cana-1429	81	5	imputation	imputation	NOUN
cana-1429	81	6	mechanism	mechanism	NOUN
cana-1429	81	7	communications	communication	NOUN
cana-1429	81	8	on	on	ADP
cana-1429	81	9	applied	apply	VERB
cana-1429	81	10	nonlinear	nonlinear	ADJ
cana-1429	81	11	analysis	analysis	NOUN
cana-1429	81	12	issn	issn	NOUN
cana-1429	81	13	:	:	PUNCT
cana-1429	81	14	1074	1074	NUM
cana-1429	81	15	-	-	PUNCT
cana-1429	81	16	133x	133x	NUM
cana-1429	81	17	vol	vol	NOUN
cana-1429	81	18	31	31	NUM
cana-1429	81	19	no	no	NOUN
cana-1429	81	20	.	.	PUNCT
cana-1429	82	1	7s	7	NOUN
cana-1429	82	2	(	(	PUNCT
cana-1429	82	3	2024	2024	NUM
cana-1429	82	4	)	)	PUNCT
cana-1429	82	5	681	681	NUM
cana-1429	82	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1429	82	7	in	in	ADP
cana-1429	82	8	the	the	DET
cana-1429	82	9	case	case	NOUN
cana-1429	82	10	of	of	ADP
cana-1429	82	11	quantitative	quantitative	ADJ
cana-1429	82	12	variables	variable	NOUN
cana-1429	82	13	,	,	PUNCT
cana-1429	82	14	“	"	PUNCT
cana-1429	82	15	predictive	predictive	ADJ
cana-1429	82	16	mean	mean	NOUN
cana-1429	82	17	matching	matching	NOUN
cana-1429	82	18	”	"	PUNCT
cana-1429	82	19	is	be	AUX
cana-1429	82	20	an	an	DET
cana-1429	82	21	appealing	appealing	ADJ
cana-1429	82	22	technique	technique	NOUN
cana-1429	82	23	for	for	ADP
cana-1429	82	24	“	"	PUNCT
cana-1429	82	25	missing	missing	ADJ
cana-1429	82	26	value	value	NOUN
cana-1429	82	27	”	"	PUNCT
cana-1429	82	28	substitution	substitution	NOUN
cana-1429	82	29	.	.	PUNCT
cana-1429	83	1	it	it	PRON
cana-1429	83	2	is	be	AUX
cana-1429	83	3	comparable	comparable	ADJ
cana-1429	83	4	to	to	ADP
cana-1429	83	5	“	"	PUNCT
cana-1429	83	6	regression	regression	NOUN
cana-1429	83	7	”	"	PUNCT
cana-1429	83	8	,	,	PUNCT
cana-1429	83	9	in	in	SCONJ
cana-1429	83	10	which	which	DET
cana-1429	83	11	“	"	PUNCT
cana-1429	83	12	observed	observed	ADJ
cana-1429	83	13	value	value	NOUN
cana-1429	83	14	”	"	PUNCT
cana-1429	83	15	is	be	AUX
cana-1429	83	16	equated	equate	VERB
cana-1429	83	17	with	with	ADP
cana-1429	83	18	“	"	PUNCT
cana-1429	83	19	missing	missing	ADJ
cana-1429	83	20	value	value	NOUN
cana-1429	83	21	”	"	PUNCT
cana-1429	83	22	to	to	PART
cana-1429	83	23	get	get	VERB
cana-1429	83	24	it	it	PRON
cana-1429	83	25	close	close	ADJ
cana-1429	83	26	to	to	PART
cana-1429	83	27	“	"	PUNCT
cana-1429	83	28	predicted	predict	VERB
cana-1429	83	29	mean	mean	ADJ
cana-1429	83	30	”	"	PUNCT
cana-1429	83	31	.	.	PUNCT
cana-1429	84	1	(	(	PUNCT
cana-1429	84	2	vink	vink	PROPN
cana-1429	84	3	et	et	PROPN
cana-1429	84	4	al	al	PROPN
cana-1429	84	5	,	,	PUNCT
cana-1429	84	6	2014	2014	NUM
cana-1429	84	7	)	)	PUNCT
cana-1429	84	8	.	.	PUNCT
cana-1429	85	1	the	the	DET
cana-1429	85	2	values	value	NOUN
cana-1429	85	3	are	be	AUX
cana-1429	85	4	estimated	estimate	VERB
cana-1429	85	5	using	use	VERB
cana-1429	85	6	a	a	DET
cana-1429	85	7	combination	combination	NOUN
cana-1429	85	8	of	of	ADP
cana-1429	85	9	“	"	PUNCT
cana-1429	85	10	linear	linear	ADJ
cana-1429	85	11	regression	regression	NOUN
cana-1429	85	12	”	"	PUNCT
cana-1429	85	13	and	and	CCONJ
cana-1429	85	14	closest	close	ADJ
cana-1429	85	15	“	"	PUNCT
cana-1429	85	16	neighbour	neighbour	NOUN
cana-1429	85	17	”	"	PUNCT
cana-1429	85	18	.	.	PUNCT
cana-1429	86	1	3.3	3.3	NUM
cana-1429	86	2	random	random	ADJ
cana-1429	86	3	forest	forest	NOUN
cana-1429	86	4	random	random	ADJ
cana-1429	86	5	forest	forest	NOUN
cana-1429	86	6	is	be	AUX
cana-1429	86	7	a	a	DET
cana-1429	86	8	frequently	frequently	ADV
cana-1429	86	9	used	use	VERB
cana-1429	86	10	“	"	PUNCT
cana-1429	86	11	supervised	supervised	ADJ
cana-1429	86	12	machine	machine	NOUN
cana-1429	86	13	-	-	PUNCT
cana-1429	86	14	learning	learning	NOUN
cana-1429	86	15	”	"	PUNCT
cana-1429	86	16	approach	approach	NOUN
cana-1429	86	17	for	for	ADP
cana-1429	86	18	“	"	PUNCT
cana-1429	86	19	classification	classification	NOUN
cana-1429	86	20	”	"	PUNCT
cana-1429	86	21	&	&	CCONJ
cana-1429	86	22	“	"	PUNCT
cana-1429	86	23	regression	regression	NOUN
cana-1429	86	24	”	"	PUNCT
cana-1429	86	25	.	.	PUNCT
cana-1429	87	1	it	it	PRON
cana-1429	87	2	uses	use	VERB
cana-1429	87	3	majority	majority	NOUN
cana-1429	87	4	vote	vote	NOUN
cana-1429	87	5	for	for	ADP
cana-1429	87	6	classification	classification	NOUN
cana-1429	87	7	&	&	CCONJ
cana-1429	87	8	average	average	NOUN
cana-1429	87	9	for	for	ADP
cana-1429	87	10	regression	regression	NOUN
cana-1429	87	11	to	to	PART
cana-1429	87	12	create	create	VERB
cana-1429	87	13	decision	decision	NOUN
cana-1429	87	14	trees	tree	NOUN
cana-1429	87	15	from	from	ADP
cana-1429	87	16	samples	sample	NOUN
cana-1429	87	17	.	.	PUNCT
cana-1429	88	1	it	it	PRON
cana-1429	88	2	can	can	AUX
cana-1429	88	3	handle	handle	VERB
cana-1429	88	4	data	data	NOUN
cana-1429	88	5	sets	set	NOUN
cana-1429	88	6	with	with	ADP
cana-1429	88	7	both	both	CCONJ
cana-1429	88	8	continuous	continuous	ADJ
cana-1429	88	9	and	and	CCONJ
cana-1429	88	10	categorical	categorical	ADJ
cana-1429	88	11	variables	variable	NOUN
cana-1429	88	12	,	,	PUNCT
cana-1429	88	13	as	as	ADP
cana-1429	88	14	in	in	ADP
cana-1429	88	15	“	"	PUNCT
cana-1429	88	16	regression	regression	NOUN
cana-1429	88	17	”	"	PUNCT
cana-1429	88	18	and	and	CCONJ
cana-1429	88	19	“	"	PUNCT
cana-1429	88	20	classification	classification	NOUN
cana-1429	88	21	”	"	PUNCT
cana-1429	88	22	.	.	PUNCT
cana-1429	89	1	when	when	SCONJ
cana-1429	89	2	it	it	PRON
cana-1429	89	3	comes	come	VERB
cana-1429	89	4	to	to	ADP
cana-1429	89	5	categorization	categorization	NOUN
cana-1429	89	6	difficulties	difficulty	NOUN
cana-1429	89	7	,	,	PUNCT
cana-1429	89	8	it	it	PRON
cana-1429	89	9	excels	excel	VERB
cana-1429	89	10	the	the	DET
cana-1429	89	11	competitors	competitor	NOUN
cana-1429	89	12	.	.	PUNCT
cana-1429	90	1	the	the	DET
cana-1429	90	2	problem	problem	NOUN
cana-1429	90	3	of	of	ADP
cana-1429	90	4	decision	decision	NOUN
cana-1429	90	5	trees	tree	NOUN
cana-1429	90	6	overfitting	overfitte	VERB
cana-1429	90	7	their	their	PRON
cana-1429	90	8	training	training	NOUN
cana-1429	90	9	set	set	NOUN
cana-1429	90	10	is	be	AUX
cana-1429	90	11	addressed	address	VERB
cana-1429	90	12	by	by	ADP
cana-1429	90	13	random	random	ADJ
cana-1429	90	14	decision	decision	NOUN
cana-1429	90	15	forests	forest	NOUN
cana-1429	90	16	.	.	PUNCT
cana-1429	91	1	the	the	DET
cana-1429	91	2	“	"	PUNCT
cana-1429	91	3	randomforest	randomfor	ADJ
cana-1429	91	4	”	"	PUNCT
cana-1429	91	5	library	library	NOUN
cana-1429	91	6	from	from	ADP
cana-1429	91	7	r	r	NOUN
cana-1429	91	8	makes	make	VERB
cana-1429	91	9	this	this	DET
cana-1429	91	10	simple	simple	NOUN
cana-1429	91	11	.	.	PUNCT
cana-1429	92	1	steps	step	NOUN
cana-1429	92	2	involved	involve	VERB
cana-1429	92	3	in	in	ADP
cana-1429	92	4	random	random	ADJ
cana-1429	92	5	forest	forest	NOUN
cana-1429	92	6	algorithm	algorithm	NOUN
cana-1429	92	7	:	:	PUNCT
cana-1429	92	8	•	•	ADV
cana-1429	92	9	from	from	ADP
cana-1429	92	10	data	datum	NOUN
cana-1429	92	11	set	set	VERB
cana-1429	92	12	of	of	ADP
cana-1429	92	13	k	k	PROPN
cana-1429	92	14	records	record	NOUN
cana-1429	92	15	,	,	PUNCT
cana-1429	92	16	it	it	PRON
cana-1429	92	17	selects	select	VERB
cana-1429	92	18	n	n	PRON
cana-1429	92	19	records	record	NOUN
cana-1429	92	20	at	at	ADP
cana-1429	92	21	random	random	ADJ
cana-1429	92	22	.	.	PUNCT
cana-1429	93	1	•	•	NUM
cana-1429	93	2	for	for	ADP
cana-1429	93	3	each	each	DET
cana-1429	93	4	sample	sample	NOUN
cana-1429	93	5	,	,	PUNCT
cana-1429	93	6	a	a	DET
cana-1429	93	7	decision	decision	NOUN
cana-1429	93	8	tree	tree	NOUN
cana-1429	93	9	is	be	AUX
cana-1429	93	10	built	build	VERB
cana-1429	93	11	.	.	PUNCT
cana-1429	94	1	•	•	NUM
cana-1429	94	2	result	result	NOUN
cana-1429	94	3	is	be	AUX
cana-1429	94	4	generated	generate	VERB
cana-1429	94	5	by	by	ADP
cana-1429	94	6	each	each	DET
cana-1429	94	7	decision	decision	NOUN
cana-1429	94	8	tree	tree	NOUN
cana-1429	94	9	.	.	PUNCT
cana-1429	95	1	•	•	NOUN
cana-1429	95	2	for	for	ADP
cana-1429	95	3	“	"	PUNCT
cana-1429	95	4	classification	classification	NOUN
cana-1429	95	5	”	"	PUNCT
cana-1429	95	6	and	and	CCONJ
cana-1429	95	7	“	"	PUNCT
cana-1429	95	8	regression	regression	NOUN
cana-1429	95	9	”	"	PUNCT
cana-1429	95	10	,	,	PUNCT
cana-1429	95	11	the	the	DET
cana-1429	95	12	final	final	ADJ
cana-1429	95	13	output	output	NOUN
cana-1429	95	14	is	be	AUX
cana-1429	95	15	based	base	VERB
cana-1429	95	16	on	on	ADP
cana-1429	95	17	majority	majority	NOUN
cana-1429	95	18	vote	vote	NOUN
cana-1429	95	19	or	or	CCONJ
cana-1429	95	20	averaging	averaging	NOUN
cana-1429	95	21	,	,	PUNCT
cana-1429	95	22	as	as	ADV
cana-1429	95	23	applicable	applicable	ADJ
cana-1429	95	24	.	.	PUNCT
cana-1429	96	1	figure	figure	VERB
cana-1429	96	2	3	3	NUM
cana-1429	96	3	:	:	PUNCT
cana-1429	96	4	random	random	ADJ
cana-1429	96	5	forest	forest	NOUN
cana-1429	96	6	mechanism	mechanism	NOUN
cana-1429	96	7	4	4	NUM
cana-1429	96	8	.	.	PUNCT
cana-1429	96	9	experimental	experimental	ADJ
cana-1429	96	10	framework	framework	NOUN
cana-1429	96	11	this	this	DET
cana-1429	96	12	manuscript	manuscript	NOUN
cana-1429	96	13	utilizes	utilize	VERB
cana-1429	96	14	data	datum	NOUN
cana-1429	96	15	sets	set	NOUN
cana-1429	96	16	from	from	ADP
cana-1429	96	17	the	the	DET
cana-1429	96	18	uci	uci	PROPN
cana-1429	96	19	machine	machine	NOUN
cana-1429	96	20	learning	learn	VERB
cana-1429	96	21	repository	repository	NOUN
cana-1429	96	22	1	1	NUM
cana-1429	96	23	)	)	PUNCT
cana-1429	96	24	iris	iris	NOUN
cana-1429	96	25	data	datum	NOUN
cana-1429	96	26	set	set	NOUN
cana-1429	96	27	includes	include	VERB
cana-1429	96	28	three	three	NUM
cana-1429	96	29	classes	class	NOUN
cana-1429	96	30	,	,	PUNCT
cana-1429	96	31	each	each	PRON
cana-1429	96	32	with	with	ADP
cana-1429	96	33	50	50	NUM
cana-1429	96	34	instances	instance	NOUN
cana-1429	96	35	,	,	PUNCT
cana-1429	96	36	each	each	DET
cana-1429	96	37	class	class	NOUN
cana-1429	96	38	is	be	AUX
cana-1429	96	39	related	relate	VERB
cana-1429	96	40	to	to	ADP
cana-1429	96	41	a	a	DET
cana-1429	96	42	different	different	ADJ
cana-1429	96	43	type	type	NOUN
cana-1429	96	44	of	of	ADP
cana-1429	96	45	iris	iris	NOUN
cana-1429	96	46	plant	plant	NOUN
cana-1429	96	47	.	.	PUNCT
cana-1429	97	1	this	this	PRON
cana-1429	97	2	is	be	AUX
cana-1429	97	3	multiclass	multiclass	ADJ
cana-1429	97	4	classification	classification	NOUN
cana-1429	97	5	to	to	PART
cana-1429	97	6	predict	predict	VERB
cana-1429	97	7	class	class	NOUN
cana-1429	97	8	of	of	ADP
cana-1429	97	9	iris	iris	NOUN
cana-1429	97	10	plant	plant	NOUN
cana-1429	97	11	,	,	PUNCT
cana-1429	97	12	2)seed	2)seed	NUM
cana-1429	97	13	dataset	dataset	NOUN
cana-1429	97	14	that	that	PRON
cana-1429	97	15	comprises	comprise	VERB
cana-1429	97	16	wheat	wheat	NOUN
cana-1429	97	17	kernels	kernel	NOUN
cana-1429	97	18	from	from	ADP
cana-1429	97	19	three	three	NUM
cana-1429	97	20	distinct	distinct	ADJ
cana-1429	97	21	wheat	wheat	NOUN
cana-1429	97	22	kinds	kind	NOUN
cana-1429	97	23	:	:	PUNCT
cana-1429	97	24	kama	kama	PROPN
cana-1429	97	25	,	,	PUNCT
cana-1429	97	26	rosa	rosa	PROPN
cana-1429	97	27	and	and	CCONJ
cana-1429	97	28	canadian	canadian	PROPN
cana-1429	97	29	,	,	PUNCT
cana-1429	97	30	70	70	NUM
cana-1429	97	31	elements	element	NOUN
cana-1429	97	32	each	each	PRON
cana-1429	97	33	,	,	PUNCT
cana-1429	97	34	selected	select	VERB
cana-1429	97	35	randomly	randomly	ADV
cana-1429	97	36	for	for	ADP
cana-1429	97	37	the	the	DET
cana-1429	97	38	experiment	experiment	NOUN
cana-1429	97	39	is	be	AUX
cana-1429	97	40	again	again	ADV
cana-1429	97	41	a	a	DET
cana-1429	97	42	multiclass	multiclass	ADJ
cana-1429	97	43	classification	classification	NOUN
cana-1429	97	44	3	3	NUM
cana-1429	97	45	)	)	PUNCT
cana-1429	97	46	infert	infert	NOUN
cana-1429	97	47	dataset	dataset	NOUN
cana-1429	97	48	that	that	PRON
cana-1429	97	49	is	be	AUX
cana-1429	97	50	about	about	ADP
cana-1429	97	51	infertility	infertility	NOUN
cana-1429	97	52	after	after	ADP
cana-1429	97	53	spontaneous	spontaneous	ADJ
cana-1429	97	54	and	and	CCONJ
cana-1429	97	55	induced	induce	VERB
cana-1429	97	56	abortion	abortion	NOUN
cana-1429	97	57	with	with	ADP
cana-1429	97	58	248	248	NUM
cana-1429	97	59	instances	instance	NOUN
cana-1429	97	60	of	of	ADP
cana-1429	97	61	matched	match	VERB
cana-1429	97	62	case	case	NOUN
cana-1429	97	63	-	-	PUNCT
cana-1429	97	64	control	control	NOUN
cana-1429	97	65	study	study	NOUN
cana-1429	97	66	with	with	ADP
cana-1429	97	67	83	83	NUM
cana-1429	97	68	elements	element	NOUN
cana-1429	97	69	of	of	ADP
cana-1429	97	70	case	case	NOUN
cana-1429	97	71	and	and	CCONJ
cana-1429	97	72	164	164	NUM
cana-1429	97	73	control	control	NOUN
cana-1429	97	74	,	,	PUNCT
cana-1429	97	75	a	a	DET
cana-1429	97	76	binary	binary	ADJ
cana-1429	97	77	classification	classification	NOUN
cana-1429	97	78	problem	problem	NOUN
cana-1429	97	79	having	have	VERB
cana-1429	97	80	imbalanced	imbalance	VERB
cana-1429	97	81	dataset.(dua	dataset.(dua	PROPN
cana-1429	97	82	&	&	CCONJ
cana-1429	97	83	graff	graff	PROPN
cana-1429	97	84	,	,	PUNCT
cana-1429	97	85	2019	2019	NUM
cana-1429	97	86	;	;	PUNCT
cana-1429	97	87	charytanowicz	charytanowicz	PROPN
cana-1429	97	88	et	et	PROPN
cana-1429	97	89	al	al	PROPN
cana-1429	97	90	,	,	PUNCT
cana-1429	97	91	2012	2012	NUM
cana-1429	97	92	;	;	PUNCT
cana-1429	97	93	trichopoulos	trichopoulos	PROPN
cana-1429	97	94	et	et	PROPN
cana-1429	97	95	al,1976	al,1976	PROPN
cana-1429	97	96	)	)	PUNCT
cana-1429	97	97	communications	communication	NOUN
cana-1429	97	98	on	on	ADP
cana-1429	97	99	applied	apply	VERB
cana-1429	97	100	nonlinear	nonlinear	ADJ
cana-1429	97	101	analysis	analysis	NOUN
cana-1429	97	102	issn	issn	NOUN
cana-1429	97	103	:	:	PUNCT
cana-1429	97	104	1074	1074	NUM
cana-1429	97	105	-	-	PUNCT
cana-1429	97	106	133x	133x	NUM
cana-1429	97	107	vol	vol	NOUN
cana-1429	97	108	31	31	NUM
cana-1429	97	109	no	no	NOUN
cana-1429	97	110	.	.	PUNCT
cana-1429	98	1	7s	7	NOUN
cana-1429	98	2	(	(	PUNCT
cana-1429	98	3	2024	2024	NUM
cana-1429	98	4	)	)	PUNCT
cana-1429	98	5	682	682	NUM
cana-1429	98	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1429	98	7	the	the	DET
cana-1429	98	8	data	datum	NOUN
cana-1429	98	9	was	be	AUX
cana-1429	98	10	divided	divide	VERB
cana-1429	98	11	equally	equally	ADV
cana-1429	98	12	i.e.	i.e.	X
cana-1429	98	13	50	50	NUM
cana-1429	98	14	%	%	NOUN
cana-1429	98	15	into	into	ADP
cana-1429	98	16	training	training	NOUN
cana-1429	98	17	and	and	CCONJ
cana-1429	98	18	testing	testing	NOUN
cana-1429	98	19	.	.	PUNCT
cana-1429	99	1	on	on	ADP
cana-1429	99	2	these	these	DET
cana-1429	99	3	data	datum	NOUN
cana-1429	99	4	set	set	VERB
cana-1429	99	5	back	back	ADJ
cana-1429	99	6	-	-	PUNCT
cana-1429	99	7	propagation	propagation	NOUN
cana-1429	99	8	artificial	artificial	ADJ
cana-1429	99	9	neural	neural	ADJ
cana-1429	99	10	network	network	NOUN
cana-1429	99	11	with	with	ADP
cana-1429	99	12	three	three	NUM
cana-1429	99	13	“	"	PUNCT
cana-1429	99	14	hidden	hidden	ADJ
cana-1429	99	15	layers	layer	NOUN
cana-1429	99	16	”	"	PUNCT
cana-1429	99	17	,	,	PUNCT
cana-1429	99	18	“	"	PUNCT
cana-1429	99	19	ensemble	ensemble	ADJ
cana-1429	99	20	learning	learning	NOUN
cana-1429	99	21	”	"	PUNCT
cana-1429	99	22	method	method	NOUN
cana-1429	99	23	“	"	PUNCT
cana-1429	99	24	random	random	ADJ
cana-1429	99	25	forest	forest	NOUN
cana-1429	99	26	”	"	PUNCT
cana-1429	99	27	and	and	CCONJ
cana-1429	99	28	“	"	PUNCT
cana-1429	99	29	statistical	statistical	ADJ
cana-1429	99	30	”	"	PUNCT
cana-1429	99	31	technique	technique	NOUN
cana-1429	99	32	“	"	PUNCT
cana-1429	99	33	multiple	multiple	ADJ
cana-1429	99	34	imputation	imputation	NOUN
cana-1429	99	35	”	"	PUNCT
cana-1429	99	36	with	with	ADP
cana-1429	99	37	“	"	PUNCT
cana-1429	99	38	predictive	predictive	ADJ
cana-1429	99	39	mean	mean	NOUN
cana-1429	99	40	matching	matching	NOUN
cana-1429	99	41	’	'	PUNCT
cana-1429	99	42	have	have	AUX
cana-1429	99	43	been	be	AUX
cana-1429	99	44	applied	apply	VERB
cana-1429	99	45	for	for	ADP
cana-1429	99	46	imputation	imputation	NOUN
cana-1429	99	47	of	of	ADP
cana-1429	99	48	categorical	categorical	ADJ
cana-1429	99	49	variables	variable	NOUN
cana-1429	99	50	which	which	PRON
cana-1429	99	51	is	be	AUX
cana-1429	99	52	binary	binary	ADJ
cana-1429	99	53	and	and	CCONJ
cana-1429	99	54	multiclass	multiclass	ADJ
cana-1429	99	55	the	the	DET
cana-1429	99	56	“	"	PUNCT
cana-1429	99	57	artificial	artificial	ADJ
cana-1429	99	58	neural	neural	ADJ
cana-1429	99	59	net	net	NOUN
cana-1429	99	60	”	"	PUNCT
cana-1429	99	61	performance	performance	NOUN
cana-1429	99	62	is	be	AUX
cana-1429	99	63	significant	significant	ADJ
cana-1429	99	64	better	well	ADJ
cana-1429	99	65	than	than	ADP
cana-1429	99	66	others	other	NOUN
cana-1429	99	67	in	in	ADP
cana-1429	99	68	terms	term	NOUN
cana-1429	99	69	of	of	ADP
cana-1429	99	70	accuracy	accuracy	NOUN
cana-1429	99	71	.	.	PUNCT
cana-1429	100	1	machine	machine	NOUN
cana-1429	100	2	learning	learning	NOUN
cana-1429	100	3	packages	package	NOUN
cana-1429	100	4	in	in	ADP
cana-1429	100	5	r	r	NOUN
cana-1429	100	6	/	/	SYM
cana-1429	100	7	revolution	revolution	NOUN
cana-1429	100	8	environment	environment	NOUN
cana-1429	100	9	like	like	ADP
cana-1429	100	10	caret	caret	PROPN
cana-1429	100	11	,	,	PUNCT
cana-1429	100	12	neuralnet	neuralnet	NOUN
cana-1429	100	13	,	,	PUNCT
cana-1429	100	14	mice	mouse	NOUN
cana-1429	100	15	and	and	CCONJ
cana-1429	100	16	randomforest	randomforest	NOUN
cana-1429	100	17	have	have	AUX
cana-1429	100	18	been	be	AUX
cana-1429	100	19	used	use	VERB
cana-1429	100	20	.	.	PUNCT
cana-1429	101	1	figure	figure	VERB
cana-1429	101	2	4.1	4.1	NUM
cana-1429	101	3	:	:	PUNCT
cana-1429	101	4	ann	ann	PROPN
cana-1429	101	5	with	with	ADP
cana-1429	101	6	iris	iris	NOUN
cana-1429	101	7	dataset	dataset	VERB
cana-1429	101	8	figure	figure	NOUN
cana-1429	101	9	4.2	4.2	NUM
cana-1429	101	10	.	.	PUNCT
cana-1429	102	1	ann	ann	PROPN
cana-1429	102	2	with	with	ADP
cana-1429	102	3	seed	seed	NOUN
cana-1429	102	4	dataset	dataset	NOUN
cana-1429	102	5	figure	figure	NOUN
cana-1429	102	6	4.3	4.3	NUM
cana-1429	102	7	:	:	PUNCT
cana-1429	102	8	ann	ann	PROPN
cana-1429	102	9	with	with	ADP
cana-1429	102	10	infert	infert	ADJ
cana-1429	102	11	dataset	dataset	NOUN
cana-1429	102	12	table	table	NOUN
cana-1429	102	13	1	1	NUM
cana-1429	102	14	:	:	PUNCT
cana-1429	102	15	comparison	comparison	NOUN
cana-1429	102	16	of	of	ADP
cana-1429	102	17	accuracy	accuracy	NOUN
cana-1429	102	18	on	on	ADP
cana-1429	102	19	different	different	ADJ
cana-1429	102	20	dataset	dataset	NOUN
cana-1429	102	21	with	with	ADP
cana-1429	102	22	different	different	ADJ
cana-1429	102	23	classifier	classifier	NOUN
cana-1429	102	24	dataset	dataset	VERB
cana-1429	102	25	multiple	multiple	ADJ
cana-1429	102	26	imputation	imputation	NOUN
cana-1429	102	27	random	random	ADJ
cana-1429	102	28	forest	forest	NOUN
cana-1429	102	29	artificial	artificial	ADJ
cana-1429	102	30	neural	neural	ADJ
cana-1429	102	31	net	net	ADJ
cana-1429	102	32	iris	iris	NOUN
cana-1429	102	33	90.67	90.67	NUM
cana-1429	102	34	94.67	94.67	NUM
cana-1429	102	35	96	96	NUM
cana-1429	102	36	infert	infert	NOUN
cana-1429	102	37	73.39	73.39	NUM
cana-1429	102	38	75	75	NUM
cana-1429	102	39	76.61	76.61	NUM
cana-1429	102	40	seed	seed	NOUN
cana-1429	102	41	73.3	73.3	NUM
cana-1429	102	42	86.67	86.67	NUM
cana-1429	102	43	94.29	94.29	NUM
cana-1429	102	44	communications	communication	NOUN
cana-1429	102	45	on	on	ADP
cana-1429	102	46	applied	apply	VERB
cana-1429	102	47	nonlinear	nonlinear	ADJ
cana-1429	102	48	analysis	analysis	NOUN
cana-1429	102	49	issn	issn	NOUN
cana-1429	102	50	:	:	PUNCT
cana-1429	102	51	1074	1074	NUM
cana-1429	102	52	-	-	PUNCT
cana-1429	102	53	133x	133x	NUM
cana-1429	102	54	vol	vol	NOUN
cana-1429	102	55	31	31	NUM
cana-1429	102	56	no	no	NOUN
cana-1429	102	57	.	.	PUNCT
cana-1429	103	1	7s	7	NOUN
cana-1429	103	2	(	(	PUNCT
cana-1429	103	3	2024	2024	NUM
cana-1429	103	4	)	)	PUNCT
cana-1429	103	5	683	683	NUM
cana-1429	103	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1429	103	7	5	5	NUM
cana-1429	103	8	.	.	PUNCT
cana-1429	103	9	conclusion	conclusion	NOUN
cana-1429	103	10	&	&	CCONJ
cana-1429	103	11	future	future	ADJ
cana-1429	103	12	work	work	NOUN
cana-1429	103	13	we	we	PRON
cana-1429	103	14	compared	compare	VERB
cana-1429	103	15	“	"	PUNCT
cana-1429	103	16	artificial	artificial	ADJ
cana-1429	103	17	neural	neural	ADJ
cana-1429	103	18	net	net	NOUN
cana-1429	103	19	-	-	PUNCT
cana-1429	103	20	based	base	VERB
cana-1429	103	21	”	"	PUNCT
cana-1429	103	22	missing	miss	VERB
cana-1429	103	23	data	data	NOUN
cana-1429	103	24	imputation	imputation	NOUN
cana-1429	103	25	approaches	approach	NOUN
cana-1429	103	26	in	in	ADP
cana-1429	103	27	this	this	DET
cana-1429	103	28	manuscript	manuscript	NOUN
cana-1429	103	29	,	,	PUNCT
cana-1429	103	30	with	with	ADP
cana-1429	103	31	the	the	DET
cana-1429	103	32	goal	goal	NOUN
cana-1429	103	33	of	of	ADP
cana-1429	103	34	transforming	transform	VERB
cana-1429	103	35	partial	partial	ADJ
cana-1429	103	36	data	datum	NOUN
cana-1429	103	37	into	into	ADP
cana-1429	103	38	complete	complete	ADJ
cana-1429	103	39	data	datum	NOUN
cana-1429	103	40	.	.	PUNCT
cana-1429	104	1	overall	overall	ADJ
cana-1429	104	2	,	,	PUNCT
cana-1429	104	3	“	"	PUNCT
cana-1429	104	4	artificial	artificial	ADJ
cana-1429	104	5	neural	neural	ADJ
cana-1429	104	6	networks	network	NOUN
cana-1429	104	7	”	"	PUNCT
cana-1429	104	8	outperformed	outperform	VERB
cana-1429	104	9	“	"	PUNCT
cana-1429	104	10	mice	mouse	NOUN
cana-1429	104	11	”	"	PUNCT
cana-1429	104	12	and	and	CCONJ
cana-1429	104	13	‘	'	PUNCT
cana-1429	104	14	random	random	ADJ
cana-1429	104	15	forests	forest	NOUN
cana-1429	104	16	”	"	PUNCT
cana-1429	104	17	in	in	ADP
cana-1429	104	18	imputation	imputation	NOUN
cana-1429	104	19	of	of	ADP
cana-1429	104	20	missing	miss	VERB
cana-1429	104	21	data	datum	NOUN
cana-1429	104	22	for	for	ADP
cana-1429	104	23	categorical	categorical	ADJ
cana-1429	104	24	variables	variable	NOUN
cana-1429	104	25	,	,	PUNCT
cana-1429	104	26	even	even	ADV
cana-1429	104	27	when	when	SCONJ
cana-1429	104	28	the	the	DET
cana-1429	104	29	data	datum	NOUN
cana-1429	104	30	was	be	AUX
cana-1429	104	31	imbalanced	imbalance	VERB
cana-1429	104	32	and	and	CCONJ
cana-1429	104	33	the	the	DET
cana-1429	104	34	missingness	missingness	ADJ
cana-1429	104	35	rate	rate	NOUN
cana-1429	104	36	was	be	AUX
cana-1429	104	37	high	high	ADJ
cana-1429	104	38	i.e.	i.e.	ADV
cana-1429	104	39	about	about	ADV
cana-1429	104	40	50	50	NUM
cana-1429	104	41	%	%	NOUN
cana-1429	104	42	.	.	PUNCT
cana-1429	105	1	there	there	PRON
cana-1429	105	2	is	be	VERB
cana-1429	105	3	no	no	DET
cana-1429	105	4	single	single	ADJ
cana-1429	105	5	ideal	ideal	ADJ
cana-1429	105	6	algorithm	algorithm	NOUN
cana-1429	105	7	for	for	ADP
cana-1429	105	8	dealing	deal	VERB
cana-1429	105	9	with	with	ADP
cana-1429	105	10	missing	miss	VERB
cana-1429	105	11	data	datum	NOUN
cana-1429	105	12	.	.	PUNCT
cana-1429	106	1	indeed	indeed	ADV
cana-1429	106	2	,	,	PUNCT
cana-1429	106	3	the	the	DET
cana-1429	106	4	approach	approach	NOUN
cana-1429	106	5	used	use	VERB
cana-1429	106	6	will	will	AUX
cana-1429	106	7	be	be	AUX
cana-1429	106	8	determined	determine	VERB
cana-1429	106	9	by	by	ADP
cana-1429	106	10	“	"	PUNCT
cana-1429	106	11	missingness	missingness	NOUN
cana-1429	106	12	”	"	PUNCT
cana-1429	106	13	assumption	assumption	NOUN
cana-1429	106	14	as	as	ADV
cana-1429	106	15	well	well	ADV
cana-1429	106	16	as	as	ADP
cana-1429	106	17	“	"	PUNCT
cana-1429	106	18	auxiliary	auxiliary	ADJ
cana-1429	106	19	factors	factor	NOUN
cana-1429	106	20	”	"	PUNCT
cana-1429	106	21	that	that	PRON
cana-1429	106	22	could	could	AUX
cana-1429	106	23	explain	explain	VERB
cana-1429	106	24	why	why	SCONJ
cana-1429	106	25	data	datum	NOUN
cana-1429	106	26	is	be	AUX
cana-1429	106	27	missing	miss	VERB
cana-1429	106	28	.	.	PUNCT
cana-1429	107	1	in	in	ADP
cana-1429	107	2	some	some	DET
cana-1429	107	3	cases	case	NOUN
cana-1429	107	4	,	,	PUNCT
cana-1429	107	5	for	for	ADP
cana-1429	107	6	example	example	NOUN
cana-1429	107	7	,	,	PUNCT
cana-1429	107	8	“	"	PUNCT
cana-1429	107	9	complete	complete	ADJ
cana-1429	107	10	case	case	NOUN
cana-1429	107	11	analysis	analysis	NOUN
cana-1429	107	12	”	"	PUNCT
cana-1429	107	13	may	may	AUX
cana-1429	107	14	be	be	AUX
cana-1429	107	15	preferable	preferable	ADJ
cana-1429	107	16	than	than	ADP
cana-1429	107	17	multiple	multiple	ADJ
cana-1429	107	18	imputation	imputation	NOUN
cana-1429	107	19	.	.	PUNCT
cana-1429	108	1	based	base	VERB
cana-1429	108	2	on	on	ADP
cana-1429	108	3	our	our	PRON
cana-1429	108	4	findings	finding	NOUN
cana-1429	108	5	,	,	PUNCT
cana-1429	108	6	we	we	PRON
cana-1429	108	7	recommend	recommend	VERB
cana-1429	108	8	that	that	SCONJ
cana-1429	108	9	while	while	SCONJ
cana-1429	108	10	selecting	select	VERB
cana-1429	108	11	an	an	DET
cana-1429	108	12	imputation	imputation	NOUN
cana-1429	108	13	method	method	NOUN
cana-1429	108	14	,	,	PUNCT
cana-1429	108	15	consider	consider	VERB
cana-1429	108	16	the	the	DET
cana-1429	108	17	“	"	PUNCT
cana-1429	108	18	missingness	missingness	ADJ
cana-1429	108	19	rate	rate	NOUN
cana-1429	108	20	”	"	PUNCT
cana-1429	108	21	,	,	PUNCT
cana-1429	108	22	“	"	PUNCT
cana-1429	108	23	variable	variable	ADJ
cana-1429	108	24	distribution	distribution	NOUN
cana-1429	108	25	”	"	PUNCT
cana-1429	108	26	,	,	PUNCT
cana-1429	108	27	and	and	CCONJ
cana-1429	108	28	“	"	PUNCT
cana-1429	108	29	expected	expect	VERB
cana-1429	108	30	computation	computation	NOUN
cana-1429	108	31	”	"	PUNCT
cana-1429	108	32	time	time	NOUN
cana-1429	108	33	.	.	PUNCT
cana-1429	109	1	furthermore	furthermore	ADV
cana-1429	109	2	,	,	PUNCT
cana-1429	109	3	the	the	DET
cana-1429	109	4	use	use	NOUN
cana-1429	109	5	of	of	ADP
cana-1429	109	6	“	"	PUNCT
cana-1429	109	7	multiple	multiple	ADJ
cana-1429	109	8	imputation	imputation	NOUN
cana-1429	109	9	”	"	PUNCT
cana-1429	109	10	methods	method	NOUN
cana-1429	109	11	and	and	CCONJ
cana-1429	109	12	“	"	PUNCT
cana-1429	109	13	sensitivity	sensitivity	NOUN
cana-1429	109	14	”	"	PUNCT
cana-1429	109	15	analysis	analysis	NOUN
cana-1429	109	16	may	may	AUX
cana-1429	109	17	improve	improve	VERB
cana-1429	109	18	the	the	DET
cana-1429	109	19	results	result	NOUN
cana-1429	109	20	'	'	PART
cana-1429	109	21	reliability	reliability	NOUN
cana-1429	109	22	.	.	PUNCT
cana-1429	110	1	references	reference	NOUN
cana-1429	110	2	[	[	X
cana-1429	110	3	1	1	NUM
cana-1429	110	4	]	]	X
cana-1429	110	5	shah	shah	NOUN
cana-1429	110	6	,	,	PUNCT
cana-1429	110	7	a.	a.	PROPN
cana-1429	110	8	,	,	PUNCT
cana-1429	110	9	bartlett	bartlett	PROPN
cana-1429	110	10	,	,	PUNCT
cana-1429	110	11	j.	j.	PROPN
cana-1429	110	12	,	,	PUNCT
cana-1429	110	13	carpenter	carpenter	PROPN
cana-1429	110	14	,	,	PUNCT
cana-1429	110	15	j.	j.	PROPN
cana-1429	110	16	,	,	PUNCT
cana-1429	110	17	nicholas	nicholas	PROPN
cana-1429	110	18	,	,	PUNCT
cana-1429	110	19	o.	o.	PROPN
cana-1429	110	20	,	,	PUNCT
cana-1429	110	21	&	&	CCONJ
cana-1429	110	22	hemingway	hemingway	PROPN
cana-1429	110	23	,	,	PUNCT
cana-1429	110	24	h.	h.	PROPN
cana-1429	110	25	(	(	PUNCT
cana-1429	110	26	2014	2014	NUM
cana-1429	110	27	)	)	PUNCT
cana-1429	110	28	.	.	PUNCT
cana-1429	111	1	comparison	comparison	NOUN
cana-1429	111	2	of	of	ADP
cana-1429	111	3	random	random	ADJ
cana-1429	111	4	forest	forest	NOUN
cana-1429	111	5	and	and	CCONJ
cana-1429	111	6	parametric	parametric	ADJ
cana-1429	111	7	imputation	imputation	NOUN
cana-1429	111	8	models	model	NOUN
cana-1429	111	9	for	for	ADP
cana-1429	111	10	imputing	impute	VERB
cana-1429	111	11	missing	miss	VERB
cana-1429	111	12	data	datum	NOUN
cana-1429	111	13	using	use	VERB
cana-1429	111	14	mice	mouse	NOUN
cana-1429	111	15	:	:	PUNCT
cana-1429	111	16	a	a	DET
cana-1429	111	17	caliber	caliber	NOUN
cana-1429	111	18	study	study	NOUN
cana-1429	111	19	.	.	PUNCT
cana-1429	112	1	american	american	PROPN
cana-1429	112	2	journal	journal	PROPN
cana-1429	112	3	of	of	ADP
cana-1429	112	4	epidemiology	epidemiology	NOUN
cana-1429	112	5	,	,	PUNCT
cana-1429	112	6	179(6	179(6	NUM
cana-1429	112	7	)	)	PUNCT
cana-1429	112	8	,	,	PUNCT
cana-1429	112	9	764	764	NUM
cana-1429	112	10	-	-	SYM
cana-1429	112	11	774	774	NUM
cana-1429	112	12	.	.	PUNCT
cana-1429	113	1	https://doi.org/10.1093/aje/kwt312	https://doi.org/10.1093/aje/kwt312	PROPN
cana-1429	113	2	[	[	X
cana-1429	113	3	2	2	NUM
cana-1429	113	4	]	]	SYM
cana-1429	113	5	dong	dong	PROPN
cana-1429	113	6	,	,	PUNCT
cana-1429	113	7	w.	w.	PROPN
cana-1429	113	8	,	,	PUNCT
cana-1429	113	9	fong	fong	PROPN
cana-1429	113	10	,	,	PUNCT
cana-1429	113	11	d.	d.	PROPN
cana-1429	113	12	,	,	PUNCT
cana-1429	113	13	yoon	yoon	PROPN
cana-1429	113	14	,	,	PUNCT
cana-1429	113	15	j.	j.	PROPN
cana-1429	113	16	,	,	PUNCT
cana-1429	113	17	wan	wan	PROPN
cana-1429	113	18	,	,	PUNCT
cana-1429	113	19	e.	e.	PROPN
cana-1429	113	20	,	,	PUNCT
cana-1429	113	21	bedford	bedford	PROPN
cana-1429	113	22	,	,	PUNCT
cana-1429	113	23	l.	l.	PROPN
cana-1429	113	24	,	,	PUNCT
cana-1429	113	25	tang	tang	PROPN
cana-1429	113	26	,	,	PUNCT
cana-1429	113	27	e.	e.	PROPN
cana-1429	113	28	,	,	PUNCT
cana-1429	113	29	&	&	CCONJ
cana-1429	113	30	lam	lam	PROPN
cana-1429	113	31	,	,	PUNCT
cana-1429	113	32	c.	c.	PROPN
cana-1429	113	33	(	(	PUNCT
cana-1429	113	34	2021	2021	NUM
cana-1429	113	35	)	)	PUNCT
cana-1429	113	36	.	.	PUNCT
cana-1429	114	1	generative	generative	ADJ
cana-1429	114	2	adversarial	adversarial	ADJ
cana-1429	114	3	networks	network	NOUN
cana-1429	114	4	for	for	ADP
cana-1429	114	5	imputing	impute	VERB
cana-1429	114	6	missing	miss	VERB
cana-1429	114	7	data	datum	NOUN
cana-1429	114	8	for	for	ADP
cana-1429	114	9	big	big	ADJ
cana-1429	114	10	data	datum	NOUN
cana-1429	114	11	clinical	clinical	ADJ
cana-1429	114	12	research	research	NOUN
cana-1429	114	13	.	.	PUNCT
cana-1429	115	1	bmc	bmc	PROPN
cana-1429	115	2	medical	medical	ADJ
cana-1429	115	3	research	research	NOUN
cana-1429	115	4	methodology	methodology	NOUN
cana-1429	115	5	,	,	PUNCT
cana-1429	115	6	21(1	21(1	NUM
cana-1429	115	7	)	)	PUNCT
cana-1429	115	8	.	.	PUNCT
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cana-1429	117	2	3	3	X
cana-1429	117	3	]	]	PUNCT
cana-1429	117	4	cardoso	cardoso	PROPN
cana-1429	117	5	pereira	pereira	PROPN
cana-1429	117	6	,	,	PUNCT
cana-1429	117	7	r.	r.	PROPN
cana-1429	117	8	,	,	PUNCT
cana-1429	117	9	seoane	seoane	PROPN
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cana-1429	117	11	,	,	PUNCT
cana-1429	117	12	m.	m.	NOUN
cana-1429	117	13	,	,	PUNCT
cana-1429	117	14	pereira	pereira	PROPN
cana-1429	117	15	rodrigues	rodrigues	PROPN
cana-1429	117	16	,	,	PUNCT
cana-1429	117	17	p.	p.	NOUN
cana-1429	117	18	,	,	PUNCT
cana-1429	117	19	&	&	CCONJ
cana-1429	117	20	henriques	henrique	NOUN
cana-1429	117	21	abreu	abreu	PROPN
cana-1429	117	22	,	,	PUNCT
cana-1429	117	23	p.	p.	NOUN
cana-1429	117	24	(	(	PUNCT
cana-1429	117	25	2020	2020	NUM
cana-1429	117	26	)	)	PUNCT
cana-1429	117	27	.	.	PUNCT
cana-1429	118	1	reviewing	review	VERB
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cana-1429	118	3	for	for	ADP
cana-1429	118	4	missing	miss	VERB
cana-1429	118	5	data	data	NOUN
cana-1429	118	6	imputation	imputation	NOUN
cana-1429	118	7	:	:	PUNCT
cana-1429	118	8	technical	technical	ADJ
cana-1429	118	9	trends	trend	NOUN
cana-1429	118	10	,	,	PUNCT
cana-1429	118	11	applications	application	NOUN
cana-1429	118	12	and	and	CCONJ
cana-1429	118	13	outcomes	outcome	NOUN
cana-1429	118	14	.	.	PUNCT
cana-1429	119	1	journal	journal	PROPN
cana-1429	119	2	of	of	ADP
cana-1429	119	3	artificial	artificial	ADJ
cana-1429	119	4	intelligence	intelligence	NOUN
cana-1429	119	5	research	research	NOUN
cana-1429	119	6	,	,	PUNCT
cana-1429	119	7	69	69	NUM
cana-1429	119	8	,	,	PUNCT
cana-1429	119	9	1255	1255	NUM
cana-1429	119	10	-	-	SYM
cana-1429	119	11	1285	1285	NUM
cana-1429	119	12	.	.	PUNCT
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cana-1429	120	3	4	4	NUM
cana-1429	120	4	]	]	X
cana-1429	120	5	desiani	desiani	PROPN
cana-1429	120	6	,	,	PUNCT
cana-1429	120	7	a.	a.	PROPN
cana-1429	120	8	,	,	PUNCT
cana-1429	120	9	dewi	dewi	PROPN
cana-1429	120	10	,	,	PUNCT
cana-1429	120	11	n.	n.	PROPN
cana-1429	120	12	,	,	PUNCT
cana-1429	120	13	fauza	fauza	PROPN
cana-1429	120	14	,	,	PUNCT
cana-1429	120	15	a.	a.	NOUN
cana-1429	120	16	,	,	PUNCT
cana-1429	120	17	rachmatullah	rachmatullah	ADJ
cana-1429	120	18	,	,	PUNCT
cana-1429	120	19	n.	n.	NOUN
cana-1429	120	20	,	,	PUNCT
cana-1429	120	21	arhami	arhami	NOUN
cana-1429	120	22	,	,	PUNCT
cana-1429	120	23	m.	m.	NOUN
cana-1429	120	24	,	,	PUNCT
cana-1429	120	25	&	&	CCONJ
cana-1429	120	26	nawawi	nawawi	PROPN
cana-1429	120	27	,	,	PUNCT
cana-1429	120	28	m.	m.	NOUN
cana-1429	120	29	(	(	PUNCT
cana-1429	120	30	2021	2021	NUM
cana-1429	120	31	)	)	PUNCT
cana-1429	120	32	.	.	PUNCT
cana-1429	121	1	handling	handle	VERB
cana-1429	121	2	missing	miss	VERB
cana-1429	121	3	data	datum	NOUN
cana-1429	121	4	using	use	VERB
cana-1429	121	5	combination	combination	NOUN
cana-1429	121	6	of	of	ADP
cana-1429	121	7	deletion	deletion	NOUN
cana-1429	121	8	technique	technique	NOUN
cana-1429	121	9	,	,	PUNCT
cana-1429	121	10	mean	mean	VERB
cana-1429	121	11	,	,	PUNCT
cana-1429	121	12	mode	mode	NOUN
cana-1429	121	13	and	and	CCONJ
cana-1429	121	14	artificial	artificial	ADJ
cana-1429	121	15	neural	neural	ADJ
cana-1429	121	16	network	network	NOUN
cana-1429	121	17	imputation	imputation	NOUN
cana-1429	121	18	for	for	ADP
cana-1429	121	19	heart	heart	NOUN
cana-1429	121	20	disease	disease	NOUN
cana-1429	121	21	dataset	dataset	VERB
cana-1429	121	22	.	.	PUNCT
cana-1429	122	1	science	science	NOUN
cana-1429	122	2	and	and	CCONJ
cana-1429	122	3	technology	technology	PROPN
cana-1429	122	4	indonesia	indonesia	PROPN
cana-1429	122	5	,	,	PUNCT
cana-1429	122	6	6(4	6(4	NUM
cana-1429	122	7	)	)	PUNCT
cana-1429	122	8	.	.	PUNCT
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cana-1429	124	2	5	5	NUM
cana-1429	124	3	]	]	PUNCT
cana-1429	124	4	ci̇han	ci̇han	PROPN
cana-1429	124	5	,	,	PUNCT
cana-1429	124	6	p.	p.	NOUN
cana-1429	124	7	(	(	PUNCT
cana-1429	124	8	2020	2020	NUM
cana-1429	124	9	)	)	PUNCT
cana-1429	124	10	.	.	PUNCT
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cana-1429	125	2	veri̇leri̇	veri̇leri̇	PROPN
cana-1429	125	3	tamamlamada	tamamlamada	PROPN
cana-1429	125	4	deri̇n	deri̇n	PROPN
cana-1429	125	5	öğrenme	öğrenme	PROPN
cana-1429	125	6	temelli̇	temelli̇	PROPN
cana-1429	125	7	yaklaşim	yaklaşim	PROPN
cana-1429	125	8	.	.	PROPN
cana-1429	125	9	eskişehir	eskişehir	PROPN
cana-1429	125	10	teknik	teknik	PROPN
cana-1429	125	11	üniversitesi	üniversitesi	PROPN
cana-1429	125	12	bilim	bilim	PROPN
cana-1429	125	13	ve	ve	AUX
cana-1429	125	14	teknoloji	teknoloji	PROPN
cana-1429	125	15	dergisi	dergisi	ADJ
cana-1429	125	16	b	b	PROPN
cana-1429	125	17	teorik	teorik	NOUN
cana-1429	125	18	bilimler	bilimler	NOUN
cana-1429	125	19	,	,	PUNCT
cana-1429	125	20	8(2	8(2	NUM
cana-1429	125	21	)	)	PUNCT
cana-1429	125	22	,	,	PUNCT
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cana-1429	125	24	-	-	SYM
cana-1429	125	25	343	343	NUM
cana-1429	125	26	.	.	PUNCT
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cana-1429	127	2	6	6	NUM
cana-1429	127	3	]	]	X
cana-1429	127	4	phung	phung	PROPN
cana-1429	127	5	,	,	PUNCT
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cana-1429	127	7	,	,	PUNCT
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cana-1429	127	11	,	,	PUNCT
cana-1429	127	12	&	&	CCONJ
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cana-1429	127	15	j.	j.	PROPN
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cana-1429	127	18	)	)	PUNCT
cana-1429	127	19	.	.	PUNCT
cana-1429	128	1	a	a	DET
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cana-1429	128	4	technique	technique	NOUN
cana-1429	128	5	for	for	ADP
cana-1429	128	6	imputing	impute	VERB
cana-1429	128	7	missing	miss	VERB
cana-1429	128	8	healthcare	healthcare	NOUN
cana-1429	128	9	data	datum	NOUN
cana-1429	128	10	.	.	PUNCT
cana-1429	129	1	2019	2019	NUM
cana-1429	129	2	41st	41st	NOUN
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cana-1429	129	4	international	international	ADJ
cana-1429	129	5	conference	conference	NOUN
cana-1429	129	6	of	of	ADP
cana-1429	129	7	the	the	DET
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cana-1429	129	9	engineering	engineering	NOUN
cana-1429	129	10	in	in	ADP
cana-1429	129	11	medicine	medicine	NOUN
cana-1429	129	12	and	and	CCONJ
cana-1429	129	13	biology	biology	NOUN
cana-1429	129	14	society	society	NOUN
cana-1429	129	15	(	(	PUNCT
cana-1429	129	16	embc	embc	PROPN
cana-1429	129	17	)	)	PUNCT
cana-1429	129	18	.	.	PUNCT
cana-1429	130	1	https://doi.org/10.1109/embc.2019.8856760	https://doi.org/10.1109/embc.2019.8856760	PROPN
cana-1429	131	1	[	[	X
cana-1429	131	2	7	7	NUM
cana-1429	131	3	]	]	X
cana-1429	131	4	khare	khare	NOUN
cana-1429	131	5	,	,	PUNCT
cana-1429	131	6	p.	p.	PROPN
cana-1429	131	7	,	,	PUNCT
cana-1429	131	8	wadhvani	wadhvani	PROPN
cana-1429	131	9	,	,	PUNCT
cana-1429	131	10	r.	r.	PROPN
cana-1429	131	11	,	,	PUNCT
cana-1429	131	12	&	&	CCONJ
cana-1429	131	13	shukla	shukla	PROPN
cana-1429	131	14	,	,	PUNCT
cana-1429	131	15	s.	s.	PROPN
cana-1429	131	16	(	(	PUNCT
cana-1429	131	17	2021	2021	NUM
cana-1429	131	18	)	)	PUNCT
cana-1429	131	19	.	.	PUNCT
cana-1429	132	1	missing	miss	VERB
cana-1429	132	2	data	data	NOUN
cana-1429	132	3	imputation	imputation	NOUN
cana-1429	132	4	for	for	ADP
cana-1429	132	5	solar	solar	ADJ
cana-1429	132	6	radiation	radiation	NOUN
cana-1429	132	7	using	use	VERB
cana-1429	132	8	generative	generative	ADJ
cana-1429	132	9	adversarial	adversarial	ADJ
cana-1429	132	10	networks	network	NOUN
cana-1429	132	11	.	.	PUNCT
cana-1429	133	1	proceedings	proceeding	NOUN
cana-1429	133	2	of	of	ADP
cana-1429	133	3	international	international	ADJ
cana-1429	133	4	conference	conference	NOUN
cana-1429	133	5	on	on	ADP
cana-1429	133	6	computational	computational	ADJ
cana-1429	133	7	intelligence	intelligence	NOUN
cana-1429	133	8	,	,	PUNCT
cana-1429	133	9	1	1	NUM
cana-1429	133	10	-	-	SYM
cana-1429	133	11	14	14	NUM
cana-1429	133	12	.	.	PUNCT
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cana-1429	134	3	8	8	NUM
cana-1429	134	4	]	]	SYM
cana-1429	134	5	yang	yang	PROPN
cana-1429	134	6	,	,	PUNCT
cana-1429	134	7	y.	y.	PROPN
cana-1429	134	8	,	,	PUNCT
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cana-1429	134	10	,	,	PUNCT
cana-1429	134	11	z.	z.	PROPN
cana-1429	134	12	,	,	PUNCT
cana-1429	134	13	tresp	tresp	NOUN
cana-1429	134	14	,	,	PUNCT
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cana-1429	134	16	,	,	PUNCT
cana-1429	134	17	&	&	CCONJ
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cana-1429	134	19	,	,	PUNCT
cana-1429	134	20	p.	p.	NOUN
cana-1429	134	21	(	(	PUNCT
cana-1429	134	22	2019	2019	NUM
cana-1429	134	23	)	)	PUNCT
cana-1429	134	24	.	.	PUNCT
cana-1429	135	1	categorical	categorical	ADJ
cana-1429	135	2	ehr	ehr	NOUN
cana-1429	135	3	imputation	imputation	NOUN
cana-1429	135	4	with	with	ADP
cana-1429	135	5	generative	generative	ADJ
cana-1429	135	6	adversarial	adversarial	ADJ
cana-1429	135	7	nets	net	NOUN
cana-1429	135	8	.	.	PUNCT
cana-1429	136	1	2019	2019	NUM
cana-1429	136	2	ieee	ieee	PROPN
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cana-1429	136	4	conference	conference	NOUN
cana-1429	136	5	on	on	ADP
cana-1429	136	6	healthcare	healthcare	PROPN
cana-1429	136	7	informatics	informatic	NOUN
cana-1429	136	8	(	(	PUNCT
cana-1429	136	9	ichi	ichi	NOUN
cana-1429	136	10	)	)	PUNCT
cana-1429	136	11	.	.	PUNCT
cana-1429	137	1	https://doi.org/10.1109/ichi.2019.8904717	https://doi.org/10.1109/ichi.2019.8904717	PROPN
cana-1429	138	1	[	[	X
cana-1429	138	2	9	9	NUM
cana-1429	138	3	]	]	X
cana-1429	138	4	izhari	izhari	PROPN
cana-1429	138	5	,	,	PUNCT
cana-1429	138	6	f.	f.	PROPN
cana-1429	138	7	,	,	PUNCT
cana-1429	138	8	zarlis	zarli	NOUN
cana-1429	138	9	,	,	PUNCT
cana-1429	138	10	m.	m.	NOUN
cana-1429	138	11	,	,	PUNCT
cana-1429	138	12	&	&	CCONJ
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cana-1429	138	14	.	.	PUNCT
cana-1429	139	1	(	(	PUNCT
cana-1429	139	2	2020	2020	NUM
cana-1429	139	3	)	)	PUNCT
cana-1429	139	4	.	.	PUNCT
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cana-1429	140	2	of	of	ADP
cana-1429	140	3	backpropagation	backpropagation	NOUN
cana-1429	140	4	neural	neural	ADJ
cana-1429	140	5	neural	neural	ADJ
cana-1429	140	6	network	network	NOUN
cana-1429	140	7	algorithm	algorithm	NOUN
cana-1429	140	8	on	on	ADP
cana-1429	140	9	student	student	NOUN
cana-1429	140	10	ability	ability	NOUN
cana-1429	140	11	based	base	VERB
cana-1429	140	12	cognitive	cognitive	ADJ
cana-1429	140	13	aspects	aspect	NOUN
cana-1429	140	14	.	.	PUNCT
cana-1429	141	1	iop	iop	NOUN
cana-1429	141	2	conference	conference	PROPN
cana-1429	141	3	series	series	PROPN
cana-1429	141	4	:	:	PUNCT
cana-1429	141	5	materials	material	NOUN
cana-1429	141	6	science	science	NOUN
cana-1429	141	7	and	and	CCONJ
cana-1429	141	8	engineering	engineering	NOUN
cana-1429	141	9	,	,	PUNCT
cana-1429	141	10	725(1	725(1	NUM
cana-1429	141	11	)	)	PUNCT
cana-1429	141	12	,	,	PUNCT
cana-1429	141	13	012103	012103	NUM
cana-1429	141	14	.	.	PUNCT
cana-1429	142	1	https://doi.org/10.1088/1757-899x/725/1/012103	https://doi.org/10.1088/1757-899x/725/1/012103	NOUN
cana-1429	143	1	[	[	X
cana-1429	143	2	10	10	NUM
cana-1429	143	3	]	]	X
cana-1429	143	4	silva	silva	NOUN
cana-1429	143	5	-	-	PUNCT
cana-1429	143	6	ramírez	ramírez	NOUN
cana-1429	143	7	,	,	PUNCT
cana-1429	143	8	e.	e.	PROPN
cana-1429	143	9	,	,	PUNCT
cana-1429	143	10	pino	pino	ADJ
cana-1429	143	11	-	-	PUNCT
cana-1429	143	12	mejías	mejías	NOUN
cana-1429	143	13	,	,	PUNCT
cana-1429	143	14	r.	r.	PROPN
cana-1429	143	15	,	,	PUNCT
cana-1429	143	16	&	&	CCONJ
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cana-1429	143	18	-	-	PUNCT
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cana-1429	143	24	)	)	PUNCT
cana-1429	143	25	.	.	PUNCT
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cana-1429	144	5	perceptron	perceptron	NOUN
cana-1429	144	6	and	and	CCONJ
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cana-1429	144	8	imputation	imputation	NOUN
cana-1429	144	9	combining	combine	VERB
cana-1429	144	10	multilayer	multilayer	ADJ
cana-1429	144	11	perceptron	perceptron	NOUN
cana-1429	144	12	and	and	CCONJ
cana-1429	144	13	k	k	NOUN
cana-1429	144	14	-	-	PUNCT
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cana-1429	144	16	neighbours	neighbour	NOUN
cana-1429	144	17	for	for	ADP
cana-1429	144	18	monotone	monotone	ADJ
cana-1429	144	19	patterns	pattern	NOUN
cana-1429	144	20	.	.	PUNCT
cana-1429	145	1	applied	apply	VERB
cana-1429	145	2	soft	soft	ADJ
cana-1429	145	3	computing	computing	NOUN
cana-1429	145	4	,	,	PUNCT
cana-1429	145	5	29	29	NUM
cana-1429	145	6	,	,	PUNCT
cana-1429	145	7	65	65	NUM
cana-1429	145	8	-	-	SYM
cana-1429	145	9	74	74	NUM
cana-1429	145	10	.	.	PUNCT
cana-1429	146	1	https://doi.org/10.1016/j.asoc.2014.09.052	https://doi.org/10.1016/j.asoc.2014.09.052	PROPN
cana-1429	147	1	[	[	X
cana-1429	147	2	11	11	NUM
cana-1429	147	3	]	]	X
cana-1429	147	4	saputra	saputra	PROPN
cana-1429	147	5	,	,	PUNCT
cana-1429	147	6	w.	w.	PROPN
cana-1429	147	7	,	,	PUNCT
cana-1429	147	8	tulus	tulus	ADV
cana-1429	147	9	,	,	PUNCT
cana-1429	147	10	zarlis	zarli	NOUN
cana-1429	147	11	,	,	PUNCT
cana-1429	147	12	m.	m.	NOUN
cana-1429	147	13	,	,	PUNCT
cana-1429	147	14	sembiring	sembiring	PROPN
cana-1429	147	15	,	,	PUNCT
cana-1429	147	16	r.	r.	PROPN
cana-1429	147	17	,	,	PUNCT
cana-1429	147	18	&	&	CCONJ
cana-1429	147	19	hartama	hartama	PROPN
cana-1429	147	20	,	,	PUNCT
cana-1429	147	21	d.	d.	PROPN
cana-1429	147	22	(	(	PUNCT
cana-1429	147	23	2017	2017	NUM
cana-1429	147	24	)	)	PUNCT
cana-1429	147	25	.	.	PUNCT
cana-1429	148	1	analysis	analysis	NOUN
cana-1429	148	2	resilient	resilient	ADJ
cana-1429	148	3	algorithm	algorithm	NOUN
cana-1429	148	4	on	on	ADP
cana-1429	148	5	artificial	artificial	ADJ
cana-1429	148	6	neural	neural	ADJ
cana-1429	148	7	network	network	NOUN
cana-1429	148	8	backpropagation	backpropagation	NOUN
cana-1429	148	9	.	.	PUNCT
cana-1429	149	1	journal	journal	PROPN
cana-1429	149	2	of	of	ADP
cana-1429	149	3	physics	physics	PROPN
cana-1429	149	4	:	:	PUNCT
cana-1429	149	5	conference	conference	NOUN
cana-1429	149	6	series	series	NOUN
cana-1429	149	7	,	,	PUNCT
cana-1429	149	8	930	930	NUM
cana-1429	149	9	,	,	PUNCT
cana-1429	149	10	012035	012035	NUM
cana-1429	149	11	.	.	PUNCT
cana-1429	150	1	https://doi.org/10.1088/1742-6596/930/1/012035	https://doi.org/10.1088/1742-6596/930/1/012035	PROPN
cana-1429	150	2	https://doi.org/10.1093/aje/kwt312	https://doi.org/10.1093/aje/kwt312	PROPN
cana-1429	150	3	https://doi.org/10.1186/s12874-021-01272-3	https://doi.org/10.1186/s12874-021-01272-3	NUM
cana-1429	151	1	https://doi.org/10.26554/sti.2021.6.4.303-312	https://doi.org/10.26554/sti.2021.6.4.303-312	PROPN
cana-1429	151	2	https://doi.org/10.20290/estubtdb.747821	https://doi.org/10.20290/estubtdb.747821	NOUN
cana-1429	151	3	https://doi.org/10.1109/embc.2019.8856760	https://doi.org/10.1109/embc.2019.8856760	PROPN
cana-1429	151	4	https://doi.org/10.1007/978-981-16-3802-2_1	https://doi.org/10.1007/978-981-16-3802-2_1	VERB
cana-1429	151	5	https://doi.org/10.1109/ichi.2019.8904717	https://doi.org/10.1109/ichi.2019.8904717	PROPN
cana-1429	151	6	https://doi.org/10.1016/j.asoc.2014.09.052	https://doi.org/10.1016/j.asoc.2014.09.052	PROPN
cana-1429	151	7	https://doi.org/10.1088/1742-6596/930/1/012035	https://doi.org/10.1088/1742-6596/930/1/012035	PROPN
cana-1429	151	8	communications	communication	NOUN
cana-1429	151	9	on	on	ADP
cana-1429	151	10	applied	apply	VERB
cana-1429	151	11	nonlinear	nonlinear	ADJ
cana-1429	151	12	analysis	analysis	NOUN
cana-1429	151	13	issn	issn	NOUN
cana-1429	151	14	:	:	PUNCT
cana-1429	151	15	1074	1074	NUM
cana-1429	151	16	-	-	PUNCT
cana-1429	151	17	133x	133x	NUM
cana-1429	151	18	vol	vol	NOUN
cana-1429	151	19	31	31	NUM
cana-1429	151	20	no	no	NOUN
cana-1429	151	21	.	.	PUNCT
cana-1429	152	1	7s	7	NOUN
cana-1429	152	2	(	(	PUNCT
cana-1429	152	3	2024	2024	NUM
cana-1429	152	4	)	)	PUNCT
cana-1429	152	5	684	684	NUM
cana-1429	152	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1429	153	1	[	[	X
cana-1429	153	2	12	12	NUM
cana-1429	153	3	]	]	X
cana-1429	153	4	wei	wei	PROPN
cana-1429	153	5	,	,	PUNCT
cana-1429	153	6	w.	w.	PROPN
cana-1429	153	7	,	,	PUNCT
cana-1429	153	8	&	&	CCONJ
cana-1429	153	9	yang	yang	PROPN
cana-1429	153	10	,	,	PUNCT
cana-1429	153	11	x.	x.	NOUN
cana-1429	153	12	(	(	PUNCT
cana-1429	153	13	2021	2021	NUM
cana-1429	153	14	)	)	PUNCT
cana-1429	153	15	.	.	PUNCT
cana-1429	154	1	comparison	comparison	NOUN
cana-1429	154	2	of	of	ADP
cana-1429	154	3	diagnosis	diagnosis	NOUN
cana-1429	154	4	accuracy	accuracy	NOUN
cana-1429	154	5	between	between	ADP
cana-1429	154	6	a	a	DET
cana-1429	154	7	backpropagation	backpropagation	NOUN
cana-1429	154	8	artificial	artificial	ADJ
cana-1429	154	9	neural	neural	ADJ
cana-1429	154	10	network	network	NOUN
cana-1429	154	11	model	model	NOUN
cana-1429	154	12	and	and	CCONJ
cana-1429	154	13	linear	linear	ADJ
cana-1429	154	14	regression	regression	NOUN
cana-1429	154	15	in	in	ADP
cana-1429	154	16	digestive	digestive	ADJ
cana-1429	154	17	disease	disease	NOUN
cana-1429	154	18	patients	patient	NOUN
cana-1429	154	19	:	:	PUNCT
cana-1429	154	20	an	an	DET
cana-1429	154	21	empirical	empirical	ADJ
cana-1429	154	22	research	research	NOUN
cana-1429	154	23	.	.	PUNCT
cana-1429	155	1	computational	computational	ADJ
cana-1429	155	2	and	and	CCONJ
cana-1429	155	3	mathematical	mathematical	ADJ
cana-1429	155	4	methods	method	NOUN
cana-1429	155	5	in	in	ADP
cana-1429	155	6	medicine	medicine	NOUN
cana-1429	155	7	,	,	PUNCT
cana-1429	155	8	2021	2021	NUM
cana-1429	155	9	,	,	PUNCT
cana-1429	155	10	1	1	NUM
cana-1429	155	11	-	-	SYM
cana-1429	155	12	10	10	NUM
cana-1429	155	13	.	.	PUNCT
cana-1429	156	1	https://doi.org/10.1155/2021/6662779	https://doi.org/10.1155/2021/6662779	NOUN
cana-1429	157	1	[	[	X
cana-1429	157	2	13	13	NUM
cana-1429	157	3	]	]	SYM
cana-1429	157	4	özden	özden	PROPN
cana-1429	157	5	,	,	PUNCT
cana-1429	157	6	s.	s.	PROPN
cana-1429	157	7	,	,	PUNCT
cana-1429	157	8	saylam	saylam	PROPN
cana-1429	157	9	,	,	PUNCT
cana-1429	157	10	b.	b.	PROPN
cana-1429	157	11	,	,	PUNCT
cana-1429	157	12	&	&	CCONJ
cana-1429	157	13	tez	tez	PROPN
cana-1429	157	14	,	,	PUNCT
cana-1429	157	15	m.	m.	NOUN
cana-1429	157	16	(	(	PUNCT
cana-1429	157	17	2017	2017	NUM
cana-1429	157	18	)	)	PUNCT
cana-1429	157	19	.	.	PUNCT
cana-1429	158	1	is	be	AUX
cana-1429	158	2	artificial	artificial	ADJ
cana-1429	158	3	neural	neural	ADJ
cana-1429	158	4	network	network	NOUN
cana-1429	158	5	an	an	DET
cana-1429	158	6	ideal	ideal	ADJ
cana-1429	158	7	modelling	modelling	NOUN
cana-1429	158	8	technique	technique	NOUN
cana-1429	158	9	?	?	PUNCT
cana-1429	158	10	.	.	PUNCT
cana-1429	159	1	journal	journal	PROPN
cana-1429	159	2	of	of	ADP
cana-1429	159	3	critical	critical	ADJ
cana-1429	159	4	care	care	NOUN
cana-1429	159	5	,	,	PUNCT
cana-1429	159	6	40	40	NUM
cana-1429	159	7	,	,	PUNCT
cana-1429	159	8	292	292	NUM
cana-1429	159	9	.	.	PUNCT
cana-1429	160	1	https://doi.org/10.1016/j.jcrc.2017.06.011	https://doi.org/10.1016/j.jcrc.2017.06.011	PROPN
cana-1429	160	2	[	[	X
cana-1429	160	3	14	14	NUM
cana-1429	160	4	]	]	X
cana-1429	160	5	wang	wang	PROPN
cana-1429	160	6	,	,	PUNCT
cana-1429	160	7	j.	j.	PROPN
cana-1429	160	8	,	,	PUNCT
cana-1429	160	9	wang	wang	PROPN
cana-1429	160	10	,	,	PUNCT
cana-1429	160	11	f.	f.	PROPN
cana-1429	160	12	,	,	PUNCT
cana-1429	160	13	liu	liu	PROPN
cana-1429	160	14	,	,	PUNCT
cana-1429	160	15	y.	y.	PROPN
cana-1429	160	16	,	,	PUNCT
cana-1429	160	17	xu	xu	PROPN
cana-1429	160	18	,	,	PUNCT
cana-1429	160	19	j.	j.	PROPN
cana-1429	160	20	,	,	PUNCT
cana-1429	160	21	lin	lin	PROPN
cana-1429	160	22	,	,	PUNCT
cana-1429	160	23	h.	h.	PROPN
cana-1429	160	24	,	,	PUNCT
cana-1429	160	25	&	&	CCONJ
cana-1429	160	26	jia	jia	PROPN
cana-1429	160	27	,	,	PUNCT
cana-1429	160	28	b.	b.	PROPN
cana-1429	160	29	et	et	PROPN
cana-1429	160	30	al	al	PROPN
cana-1429	160	31	.	.	PROPN
cana-1429	161	1	(	(	PUNCT
cana-1429	161	2	2016	2016	NUM
cana-1429	161	3	)	)	PUNCT
cana-1429	161	4	.	.	PUNCT
cana-1429	162	1	multiple	multiple	ADJ
cana-1429	162	2	linear	linear	ADJ
cana-1429	162	3	regression	regression	NOUN
cana-1429	162	4	and	and	CCONJ
cana-1429	162	5	artificial	artificial	ADJ
cana-1429	162	6	neural	neural	ADJ
cana-1429	162	7	network	network	NOUN
cana-1429	162	8	to	to	PART
cana-1429	162	9	predict	predict	VERB
cana-1429	162	10	blood	blood	NOUN
cana-1429	162	11	glucose	glucose	NOUN
cana-1429	162	12	in	in	ADP
cana-1429	162	13	overweight	overweight	ADJ
cana-1429	162	14	patients	patient	NOUN
cana-1429	162	15	.	.	PUNCT
cana-1429	163	1	experimental	experimental	ADJ
cana-1429	163	2	and	and	CCONJ
cana-1429	163	3	clinical	clinical	ADJ
cana-1429	163	4	endocrinology	endocrinology	NOUN
cana-1429	163	5	&	&	CCONJ
cana-1429	163	6	diabetes	diabetes	NOUN
cana-1429	163	7	,	,	PUNCT
cana-1429	163	8	124(01	124(01	NUM
cana-1429	163	9	)	)	PUNCT
cana-1429	163	10	,	,	PUNCT
cana-1429	163	11	34	34	NUM
cana-1429	163	12	-	-	SYM
cana-1429	163	13	38	38	NUM
cana-1429	163	14	.	.	PUNCT
cana-1429	164	1	https://doi.org/10.1055/s-0035-1565175	https://doi.org/10.1055/s-0035-1565175	PROPN
cana-1429	165	1	[	[	X
cana-1429	165	2	15	15	NUM
cana-1429	165	3	]	]	X
cana-1429	165	4	fei	fei	PROPN
cana-1429	165	5	,	,	PUNCT
cana-1429	165	6	y.	y.	PROPN
cana-1429	165	7	,	,	PUNCT
cana-1429	165	8	hu	hu	PROPN
cana-1429	165	9	,	,	PUNCT
cana-1429	165	10	j.	j.	PROPN
cana-1429	165	11	,	,	PUNCT
cana-1429	165	12	li	li	PROPN
cana-1429	165	13	,	,	PUNCT
cana-1429	165	14	w.	w.	PROPN
cana-1429	165	15	,	,	PUNCT
cana-1429	165	16	wang	wang	PROPN
cana-1429	165	17	,	,	PUNCT
cana-1429	165	18	w.	w.	PROPN
cana-1429	165	19	,	,	PUNCT
cana-1429	165	20	&	&	CCONJ
cana-1429	165	21	zong	zong	PROPN
cana-1429	165	22	,	,	PUNCT
cana-1429	165	23	g.	g.	PROPN
cana-1429	165	24	(	(	PUNCT
cana-1429	165	25	2017	2017	NUM
cana-1429	165	26	)	)	PUNCT
cana-1429	165	27	.	.	PUNCT
cana-1429	166	1	artificial	artificial	ADJ
cana-1429	166	2	neural	neural	ADJ
cana-1429	166	3	networks	network	NOUN
cana-1429	166	4	predict	predict	VERB
cana-1429	166	5	the	the	DET
cana-1429	166	6	incidence	incidence	NOUN
cana-1429	166	7	of	of	ADP
cana-1429	166	8	portosplenomesenteric	portosplenomesenteric	ADJ
cana-1429	166	9	venous	venous	ADJ
cana-1429	166	10	thrombosis	thrombosis	NOUN
cana-1429	166	11	in	in	ADP
cana-1429	166	12	patients	patient	NOUN
cana-1429	166	13	with	with	ADP
cana-1429	166	14	acute	acute	PROPN
cana-1429	166	15	pancreatitis	pancreatitis	PROPN
cana-1429	166	16	.	.	PUNCT
cana-1429	167	1	journal	journal	PROPN
cana-1429	167	2	of	of	ADP
cana-1429	167	3	thrombosis	thrombosis	NOUN
cana-1429	167	4	and	and	CCONJ
cana-1429	167	5	haemostasis	haemostasis	NOUN
cana-1429	167	6	,	,	PUNCT
cana-1429	167	7	15(3	15(3	NUM
cana-1429	167	8	)	)	PUNCT
cana-1429	167	9	,	,	PUNCT
cana-1429	167	10	439	439	NUM
cana-1429	167	11	-	-	SYM
cana-1429	167	12	445	445	NUM
cana-1429	167	13	.	.	PUNCT
cana-1429	168	1	https://doi.org/10.1111/jth.13588	https://doi.org/10.1111/jth.13588	PROPN
cana-1429	169	1	[	[	X
cana-1429	169	2	16	16	NUM
cana-1429	169	3	]	]	X
cana-1429	169	4	yoon	yoon	PROPN
cana-1429	169	5	,	,	PUNCT
cana-1429	169	6	j.	j.	PROPN
cana-1429	169	7	,	,	PUNCT
cana-1429	169	8	jordon	jordon	PROPN
cana-1429	169	9	,	,	PUNCT
cana-1429	169	10	j.	j.	PROPN
cana-1429	169	11	,	,	PUNCT
cana-1429	169	12	and	and	CCONJ
cana-1429	169	13	van	van	PROPN
cana-1429	169	14	der	der	ADJ
cana-1429	169	15	schaar	schaar	NOUN
cana-1429	169	16	,	,	PUNCT
cana-1429	169	17	m.	m.	NOUN
cana-1429	169	18	(	(	PUNCT
cana-1429	169	19	2018	2018	NUM
cana-1429	169	20	)	)	PUNCT
cana-1429	169	21	.	.	PUNCT
cana-1429	170	1	gain	gain	NOUN
cana-1429	170	2	:	:	PUNCT
cana-1429	170	3	missing	miss	VERB
cana-1429	170	4	data	data	NOUN
cana-1429	170	5	imputation	imputation	NOUN
cana-1429	170	6	using	use	VERB
cana-1429	170	7	generative	generative	ADJ
cana-1429	170	8	adversarial	adversarial	ADJ
cana-1429	170	9	nets	net	NOUN
cana-1429	170	10	.	.	PUNCT
cana-1429	171	1	proceedings	proceeding	NOUN
cana-1429	171	2	of	of	ADP
cana-1429	171	3	the	the	DET
cana-1429	171	4	35th	35th	ADJ
cana-1429	171	5	international	international	ADJ
cana-1429	171	6	conference	conference	NOUN
cana-1429	171	7	on	on	ADP
cana-1429	171	8	machine	machine	NOUN
cana-1429	171	9	learning	learning	NOUN
cana-1429	171	10	.	.	PUNCT
cana-1429	172	1	https://proceedings.mlr.press/v80/yoon18a.html	https://proceedings.mlr.press/v80/yoon18a.html	X
cana-1429	172	2	.	.	PUNCT
cana-1429	173	1	[	[	X
cana-1429	173	2	17	17	NUM
cana-1429	173	3	]	]	X
cana-1429	173	4	vink	vink	PROPN
cana-1429	173	5	g	g	PROPN
cana-1429	173	6	,	,	PUNCT
cana-1429	173	7	frank	frank	PROPN
cana-1429	173	8	le	le	PROPN
cana-1429	173	9	,	,	PUNCT
cana-1429	173	10	pannekoek	pannekoek	PROPN
cana-1429	173	11	j	j	PROPN
cana-1429	173	12	,	,	PUNCT
cana-1429	173	13	buuren	buuren	PROPN
cana-1429	173	14	sv.(2014).predictive	sv.(2014).predictive	PROPN
cana-1429	173	15	mean	mean	VERB
cana-1429	173	16	matching	matching	NOUN
cana-1429	173	17	imputation	imputation	NOUN
cana-1429	173	18	of	of	ADP
cana-1429	173	19	semicontinuous	semicontinuous	ADJ
cana-1429	173	20	variables	variable	NOUN
cana-1429	173	21	.	.	PUNCT
cana-1429	174	1	statistica	statistica	PROPN
cana-1429	174	2	neerlandica	neerlandica	PROPN
cana-1429	174	3	,	,	PUNCT
cana-1429	174	4	68(1	68(1	NOUN
cana-1429	174	5	)	)	PUNCT
cana-1429	174	6	,	,	PUNCT
cana-1429	174	7	61–90	61–90	NOUN
cana-1429	174	8	.	.	PUNCT
cana-1429	175	1	[	[	X
cana-1429	175	2	18	18	NUM
cana-1429	175	3	]	]	X
cana-1429	175	4	dua	dua	PROPN
cana-1429	175	5	,	,	PUNCT
cana-1429	175	6	d.	d.	PROPN
cana-1429	175	7	and	and	CCONJ
cana-1429	175	8	graff	graff	PROPN
cana-1429	175	9	,	,	PUNCT
cana-1429	175	10	c.	c.	PROPN
cana-1429	175	11	(	(	PUNCT
cana-1429	175	12	2019	2019	NUM
cana-1429	175	13	)	)	PUNCT
cana-1429	175	14	.	.	PUNCT
cana-1429	176	1	uci	uci	PROPN
cana-1429	176	2	machine	machine	NOUN
cana-1429	176	3	learning	learn	VERB
cana-1429	176	4	repository	repository	NOUN
cana-1429	177	1	[	[	X
cana-1429	177	2	http://archive.ics.uci.edu/ml	http://archive.ics.uci.edu/ml	X
cana-1429	177	3	]	]	X
cana-1429	177	4	.	.	PUNCT
cana-1429	178	1	irvine	irvine	PROPN
cana-1429	178	2	,	,	PUNCT
cana-1429	178	3	ca	ca	PROPN
cana-1429	178	4	:	:	PUNCT
cana-1429	178	5	university	university	PROPN
cana-1429	178	6	of	of	ADP
cana-1429	178	7	california	california	PROPN
cana-1429	178	8	,	,	PUNCT
cana-1429	178	9	school	school	NOUN
cana-1429	178	10	of	of	ADP
cana-1429	178	11	information	information	NOUN
cana-1429	178	12	and	and	CCONJ
cana-1429	178	13	computer	computer	NOUN
cana-1429	178	14	science	science	NOUN
cana-1429	178	15	.	.	PUNCT
cana-1429	179	1	[	[	X
cana-1429	179	2	19	19	NUM
cana-1429	179	3	]	]	X
cana-1429	179	4	charytanowicz	charytanowicz	NOUN
cana-1429	179	5	,	,	PUNCT
cana-1429	179	6	magorzata	magorzata	PROPN
cana-1429	179	7	,	,	PUNCT
cana-1429	179	8	niewczas	niewcza	NOUN
cana-1429	179	9	,	,	PUNCT
cana-1429	179	10	jerzy	jerzy	NOUN
cana-1429	179	11	,	,	PUNCT
cana-1429	179	12	kulczycki	kulczycki	PROPN
cana-1429	179	13	,	,	PUNCT
cana-1429	179	14	piotr	piotr	PROPN
cana-1429	179	15	,	,	PUNCT
cana-1429	179	16	kowalski	kowalski	PROPN
cana-1429	179	17	,	,	PUNCT
cana-1429	179	18	piotr	piotr	PROPN
cana-1429	179	19	&	&	CCONJ
cana-1429	179	20	lukasik	lukasik	PROPN
cana-1429	179	21	,	,	PUNCT
cana-1429	179	22	szymon	szymon	NOUN
cana-1429	179	23	.	.	PUNCT
cana-1429	180	1	(	(	PUNCT
cana-1429	180	2	2012	2012	NUM
cana-1429	180	3	)	)	PUNCT
cana-1429	180	4	.	.	PUNCT
cana-1429	181	1	seeds	seed	NOUN
cana-1429	181	2	.	.	PUNCT
cana-1429	182	1	uci	uci	PROPN
cana-1429	182	2	machine	machine	NOUN
cana-1429	182	3	learning	learn	VERB
cana-1429	182	4	repository	repository	NOUN
cana-1429	182	5	.	.	PUNCT
cana-1429	183	1	[	[	X
cana-1429	183	2	20	20	NUM
cana-1429	183	3	]	]	X
cana-1429	183	4	trichopoulos	trichopoulos	PROPN
cana-1429	183	5	et	et	PROPN
cana-1429	183	6	al	al	PROPN
cana-1429	183	7	(	(	PUNCT
cana-1429	183	8	1976	1976	NUM
cana-1429	183	9	)	)	PUNCT
cana-1429	183	10	br	br	PROPN
cana-1429	183	11	.	.	PUNCT
cana-1429	184	1	j.	j.	PROPN
cana-1429	184	2	of	of	ADP
cana-1429	184	3	obst	obst	PROPN
cana-1429	184	4	.	.	PROPN
cana-1429	185	1	and	and	CCONJ
cana-1429	185	2	gynaec	gynaec	PROPN
cana-1429	185	3	.	.	PUNCT
cana-1429	186	1	83	83	NUM
cana-1429	186	2	,	,	PUNCT
cana-1429	186	3	645–650	645–650	NUM
cana-1429	186	4	https://doi.org/10.1016/j.jcrc.2017.06.011	https://doi.org/10.1016/j.jcrc.2017.06.011	PROPN
cana-1429	186	5	https://doi.org/10.1111/jth.13588	https://doi.org/10.1111/jth.13588	PROPN
cana-1429	186	6	https://proceedings.mlr.press/v80/yoon18a.html	https://proceedings.mlr.press/v80/yoon18a.html	NOUN