id	sid	tid	token	lemma	pos
easat-1848	1	1	edelweiss	edelweiss	PROPN
easat-1848	1	2	applied	apply	VERB
easat-1848	1	3	science	science	NOUN
easat-1848	1	4	and	and	CCONJ
easat-1848	1	5	technology	technology	NOUN
easat-1848	1	6	issn	issn	PROPN
easat-1848	1	7	:	:	PUNCT
easat-1848	1	8	2576	2576	NUM
easat-1848	1	9	-	-	SYM
easat-1848	1	10	8484	8484	NUM
easat-1848	1	11	vol	vol	NOUN
easat-1848	1	12	.	.	PROPN
easat-1848	1	13	8	8	NUM
easat-1848	1	14	,	,	PUNCT
easat-1848	1	15	no	no	INTJ
easat-1848	1	16	.	.	NOUN
easat-1848	1	17	5	5	NUM
easat-1848	1	18	,	,	PUNCT
easat-1848	1	19	1454	1454	NUM
easat-1848	1	20	-	-	SYM
easat-1848	1	21	1471	1471	NUM
easat-1848	1	22	2024	2024	NUM
easat-1848	1	23	publisher	publisher	NOUN
easat-1848	1	24	:	:	PUNCT
easat-1848	1	25	learning	learn	VERB
easat-1848	1	26	gate	gate	NOUN
easat-1848	1	27	doi	doi	PROPN
easat-1848	1	28	:	:	PUNCT
easat-1848	1	29	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	1	30	©	©	PROPN
easat-1848	1	31	2024	2024	NUM
easat-1848	1	32	by	by	ADP
easat-1848	1	33	the	the	DET
easat-1848	1	34	authors	author	NOUN
easat-1848	1	35	;	;	PUNCT
easat-1848	1	36	licensee	licensee	PROPN
easat-1848	1	37	learning	learning	NOUN
easat-1848	1	38	gate	gate	NOUN
easat-1848	1	39	©	©	PROPN
easat-1848	1	40	2024	2024	NUM
easat-1848	1	41	by	by	ADP
easat-1848	1	42	the	the	DET
easat-1848	1	43	authors	author	NOUN
easat-1848	1	44	;	;	PUNCT
easat-1848	1	45	licensee	licensee	PROPN
easat-1848	1	46	learning	learn	VERB
easat-1848	1	47	gate	gate	NOUN
easat-1848	1	48	*	*	PUNCT
easat-1848	1	49	correspondence	correspondence	NOUN
easat-1848	1	50	:	:	PUNCT
easat-1848	1	51	lijethacjaffrin@veltech.edu.in	lijethacjaffrin@veltech.edu.in	ADJ
easat-1848	1	52	impact	impact	NOUN
easat-1848	1	53	of	of	ADP
easat-1848	1	54	feature	feature	NOUN
easat-1848	1	55	selection	selection	NOUN
easat-1848	1	56	techniques	technique	NOUN
easat-1848	1	57	on	on	ADP
easat-1848	1	58	machine	machine	NOUN
easat-1848	1	59	learning	learning	NOUN
easat-1848	1	60	and	and	CCONJ
easat-1848	1	61	deep	deep	ADJ
easat-1848	1	62	learning	learning	NOUN
easat-1848	1	63	techniques	technique	NOUN
easat-1848	1	64	for	for	ADP
easat-1848	1	65	cardiovascular	cardiovascular	ADJ
easat-1848	1	66	disease	disease	NOUN
easat-1848	1	67	prediction	prediction	NOUN
easat-1848	1	68	-	-	PUNCT
easat-1848	1	69	an	an	DET
easat-1848	1	70	analysis	analysis	NOUN
easat-1848	1	71	lijetha	lijetha	NOUN
easat-1848	1	72	.	.	PUNCT
easat-1848	2	1	c.	c.	PROPN
easat-1848	2	2	jaffrin1	jaffrin1	PROPN
easat-1848	3	1	*	*	PROPN
easat-1848	3	2	,	,	PUNCT
easat-1848	3	3	j.	j.	PROPN
easat-1848	3	4	visumathi2	visumathi2	PROPN
easat-1848	3	5	1,2vel	1,2vel	NUM
easat-1848	3	6	tech	tech	NOUN
easat-1848	3	7	rangarajan	rangarajan	NOUN
easat-1848	3	8	dr.sagunthala	dr.sagunthala	NOUN
easat-1848	3	9	r&d	r&d	PROPN
easat-1848	3	10	institute	institute	PROPN
easat-1848	3	11	of	of	ADP
easat-1848	3	12	science	science	NOUN
easat-1848	3	13	and	and	CCONJ
easat-1848	3	14	technology	technology	NOUN
easat-1848	3	15	;	;	PUNCT
easat-1848	3	16	lijethacjaffrin@veltech.edu.in	lijethacjaffrin@veltech.edu.in	NOUN
easat-1848	3	17	(	(	PUNCT
easat-1848	3	18	l.c.j	l.c.j	NOUN
easat-1848	3	19	.	.	PUNCT
easat-1848	3	20	)	)	PUNCT
easat-1848	4	1	drvisumathij@veltech.edu.in	drvisumathij@veltech.edu.in	INTJ
easat-1848	4	2	(	(	PUNCT
easat-1848	4	3	j.v	j.v	PROPN
easat-1848	4	4	.	.	PUNCT
easat-1848	4	5	)	)	PUNCT
easat-1848	4	6	.	.	PUNCT
easat-1848	5	1	abstract	abstract	ADJ
easat-1848	5	2	:	:	PUNCT
easat-1848	5	3	cardio	cardio	ADJ
easat-1848	5	4	vascular	vascular	NOUN
easat-1848	5	5	disease	disease	NOUN
easat-1848	5	6	is	be	AUX
easat-1848	5	7	one	one	NUM
easat-1848	5	8	of	of	ADP
easat-1848	5	9	the	the	DET
easat-1848	5	10	life	life	NOUN
easat-1848	5	11	-	-	PUNCT
easat-1848	5	12	threatening	threaten	VERB
easat-1848	5	13	diseases	disease	NOUN
easat-1848	5	14	which	which	PRON
easat-1848	5	15	affects	affect	VERB
easat-1848	5	16	individuals	individual	NOUN
easat-1848	5	17	worldwide	worldwide	ADV
easat-1848	5	18	.	.	PUNCT
easat-1848	6	1	early	early	ADJ
easat-1848	6	2	diagnosis	diagnosis	NOUN
easat-1848	6	3	may	may	AUX
easat-1848	6	4	allow	allow	VERB
easat-1848	6	5	for	for	ADP
easat-1848	6	6	the	the	DET
easat-1848	6	7	prevention	prevention	NOUN
easat-1848	6	8	or	or	CCONJ
easat-1848	6	9	mitigation	mitigation	NOUN
easat-1848	6	10	of	of	ADP
easat-1848	6	11	cardiovascular	cardiovascular	ADJ
easat-1848	6	12	diseases	disease	NOUN
easat-1848	6	13	,	,	PUNCT
easat-1848	6	14	which	which	PRON
easat-1848	6	15	may	may	AUX
easat-1848	6	16	minor	minor	ADJ
easat-1848	6	17	mortality	mortality	NOUN
easat-1848	6	18	rates	rate	NOUN
easat-1848	6	19	.	.	PUNCT
easat-1848	7	1	a	a	DET
easat-1848	7	2	feasible	feasible	ADJ
easat-1848	7	3	deep	deep	ADJ
easat-1848	7	4	learning	learning	NOUN
easat-1848	7	5	and	and	CCONJ
easat-1848	7	6	machine	machine	NOUN
easat-1848	7	7	learning	learning	NOUN
easat-1848	7	8	algorithms	algorithm	NOUN
easat-1848	7	9	are	be	AUX
easat-1848	7	10	used	use	VERB
easat-1848	7	11	to	to	PART
easat-1848	7	12	find	find	VERB
easat-1848	7	13	risk	risk	NOUN
easat-1848	7	14	variables	variable	NOUN
easat-1848	7	15	.	.	PUNCT
easat-1848	8	1	machine	machine	NOUN
easat-1848	8	2	learning	learning	NOUN
easat-1848	8	3	and	and	CCONJ
easat-1848	8	4	deep	deep	ADJ
easat-1848	8	5	learning	learning	NOUN
easat-1848	8	6	system	system	NOUN
easat-1848	8	7	anticipates	anticipate	VERB
easat-1848	8	8	heart	heart	NOUN
easat-1848	8	9	diseases	disease	NOUN
easat-1848	8	10	early	early	ADV
easat-1848	8	11	on	on	ADV
easat-1848	8	12	and	and	CCONJ
easat-1848	8	13	reduce	reduce	VERB
easat-1848	8	14	death	death	NOUN
easat-1848	8	15	rates	rate	NOUN
easat-1848	8	16	from	from	ADP
easat-1848	8	17	clinical	clinical	ADJ
easat-1848	8	18	data	datum	NOUN
easat-1848	8	19	.	.	PUNCT
easat-1848	9	1	to	to	PART
easat-1848	9	2	detect	detect	VERB
easat-1848	9	3	heart	heart	NOUN
easat-1848	9	4	diseases	disease	NOUN
easat-1848	9	5	or	or	CCONJ
easat-1848	9	6	determine	determine	VERB
easat-1848	9	7	the	the	DET
easat-1848	9	8	patient	patient	NOUN
easat-1848	9	9	's	's	PART
easat-1848	9	10	severity	severity	NOUN
easat-1848	9	11	level	level	NOUN
easat-1848	9	12	,	,	PUNCT
easat-1848	9	13	numerous	numerous	ADJ
easat-1848	9	14	research	research	NOUN
easat-1848	9	15	studies	study	NOUN
easat-1848	9	16	recently	recently	ADV
easat-1848	9	17	used	use	VERB
easat-1848	9	18	various	various	ADJ
easat-1848	9	19	machine	machine	NOUN
easat-1848	9	20	learning	learn	VERB
easat-1848	9	21	techniques	technique	NOUN
easat-1848	9	22	.	.	PUNCT
easat-1848	10	1	the	the	DET
easat-1848	10	2	volume	volume	NOUN
easat-1848	10	3	of	of	ADP
easat-1848	10	4	internationally	internationally	ADV
easat-1848	10	5	recognised	recognise	VERB
easat-1848	10	6	medical	medical	ADJ
easat-1848	10	7	data	datum	NOUN
easat-1848	10	8	sets	set	NOUN
easat-1848	10	9	is	be	AUX
easat-1848	10	10	growing	grow	VERB
easat-1848	10	11	in	in	ADP
easat-1848	10	12	terms	term	NOUN
easat-1848	10	13	of	of	ADP
easat-1848	10	14	both	both	DET
easat-1848	10	15	qualities	quality	NOUN
easat-1848	10	16	and	and	CCONJ
easat-1848	10	17	records	record	NOUN
easat-1848	10	18	.	.	PUNCT
easat-1848	11	1	this	this	DET
easat-1848	11	2	paper	paper	NOUN
easat-1848	11	3	delivers	deliver	VERB
easat-1848	11	4	brief	brief	ADJ
easat-1848	11	5	outline	outline	NOUN
easat-1848	11	6	of	of	ADP
easat-1848	11	7	various	various	ADJ
easat-1848	11	8	feature	feature	NOUN
easat-1848	11	9	extraction	extraction	NOUN
easat-1848	11	10	methods	method	NOUN
easat-1848	11	11	such	such	ADJ
easat-1848	11	12	as	as	ADP
easat-1848	11	13	lasso	lasso	NOUN
easat-1848	11	14	,	,	PUNCT
easat-1848	11	15	relief	relief	NOUN
easat-1848	11	16	,	,	PUNCT
easat-1848	11	17	rfe	rfe	NOUN
easat-1848	11	18	,	,	PUNCT
easat-1848	11	19	mrmr	mrmr	NOUN
easat-1848	11	20	and	and	CCONJ
easat-1848	11	21	relief	relief	NOUN
easat-1848	11	22	on	on	ADP
easat-1848	11	23	deep	deep	ADJ
easat-1848	11	24	learning	learning	NOUN
easat-1848	11	25	and	and	CCONJ
easat-1848	11	26	machine	machine	NOUN
easat-1848	11	27	learning	learn	VERB
easat-1848	11	28	techniques	technique	NOUN
easat-1848	11	29	for	for	ADP
easat-1848	11	30	diagnosing	diagnose	VERB
easat-1848	11	31	cardiac	cardiac	ADJ
easat-1848	11	32	disease	disease	NOUN
easat-1848	11	33	.	.	PUNCT
easat-1848	12	1	the	the	DET
easat-1848	12	2	performance	performance	NOUN
easat-1848	12	3	metrics	metric	NOUN
easat-1848	12	4	taken	take	VERB
easat-1848	12	5	into	into	ADP
easat-1848	12	6	consideration	consideration	NOUN
easat-1848	12	7	are	be	AUX
easat-1848	12	8	accuracy	accuracy	NOUN
easat-1848	12	9	,	,	PUNCT
easat-1848	12	10	precision	precision	NOUN
easat-1848	12	11	,	,	PUNCT
easat-1848	12	12	recall	recall	NOUN
easat-1848	12	13	,	,	PUNCT
easat-1848	12	14	f1score	f1score	NOUN
easat-1848	12	15	and	and	CCONJ
easat-1848	12	16	the	the	DET
easat-1848	12	17	error	error	NOUN
easat-1848	12	18	measures	measure	NOUN
easat-1848	12	19	are	be	AUX
easat-1848	12	20	least	least	ADJ
easat-1848	12	21	mean	mean	VERB
easat-1848	12	22	squared	square	VERB
easat-1848	12	23	error	error	NOUN
easat-1848	12	24	and	and	CCONJ
easat-1848	12	25	mean	mean	VERB
easat-1848	12	26	absolute	absolute	ADJ
easat-1848	12	27	error	error	NOUN
easat-1848	12	28	.	.	PUNCT
easat-1848	13	1	the	the	DET
easat-1848	13	2	feature	feature	NOUN
easat-1848	13	3	selection	selection	NOUN
easat-1848	13	4	methods	method	NOUN
easat-1848	13	5	with	with	ADP
easat-1848	13	6	more	more	ADJ
easat-1848	13	7	features	feature	NOUN
easat-1848	13	8	selected	select	VERB
easat-1848	13	9	outpaced	outpace	VERB
easat-1848	13	10	other	other	ADJ
easat-1848	13	11	approaches	approach	NOUN
easat-1848	13	12	.	.	PUNCT
easat-1848	14	1	finally	finally	ADV
easat-1848	14	2	,	,	PUNCT
easat-1848	14	3	crucial	crucial	ADJ
easat-1848	14	4	findings	finding	NOUN
easat-1848	14	5	from	from	ADP
easat-1848	14	6	the	the	DET
easat-1848	14	7	evaluated	evaluated	ADJ
easat-1848	14	8	studies	study	NOUN
easat-1848	14	9	are	be	AUX
easat-1848	14	10	outlined	outline	VERB
easat-1848	14	11	.	.	PUNCT
easat-1848	15	1	keywords	keyword	NOUN
easat-1848	15	2	:	:	PUNCT
easat-1848	15	3	deep	deep	ADJ
easat-1848	15	4	learning	learning	NOUN
easat-1848	15	5	,	,	PUNCT
easat-1848	15	6	features	feature	VERB
easat-1848	15	7	selection	selection	NOUN
easat-1848	15	8	,	,	PUNCT
easat-1848	15	9	heart	heart	NOUN
easat-1848	15	10	disease	disease	NOUN
easat-1848	15	11	,	,	PUNCT
easat-1848	15	12	intelligent	intelligent	ADJ
easat-1848	15	13	system	system	NOUN
easat-1848	15	14	,	,	PUNCT
easat-1848	15	15	machine	machine	NOUN
easat-1848	15	16	learning	learning	NOUN
easat-1848	15	17	.	.	PUNCT
easat-1848	16	1	1	1	X
easat-1848	16	2	.	.	X
easat-1848	16	3	introduction	introduction	NOUN
easat-1848	16	4	the	the	DET
easat-1848	16	5	largest	large	ADJ
easat-1848	16	6	reason	reason	NOUN
easat-1848	16	7	of	of	ADP
easat-1848	16	8	death	death	NOUN
easat-1848	16	9	worldwide	worldwide	ADV
easat-1848	16	10	is	be	AUX
easat-1848	16	11	heart	heart	NOUN
easat-1848	16	12	disease	disease	NOUN
easat-1848	16	13	,	,	PUNCT
easat-1848	16	14	usually	usually	ADV
easat-1848	16	15	referred	refer	VERB
easat-1848	16	16	to	to	ADP
easat-1848	16	17	as	as	ADP
easat-1848	16	18	cardiovascular	cardiovascular	ADJ
easat-1848	16	19	disease	disease	NOUN
easat-1848	16	20	(	(	PUNCT
easat-1848	16	21	cvd	cvd	PROPN
easat-1848	16	22	)	)	PUNCT
easat-1848	16	23	.	.	PUNCT
easat-1848	17	1	according	accord	VERB
easat-1848	17	2	to	to	ADP
easat-1848	17	3	the	the	DET
easat-1848	17	4	world	world	NOUN
easat-1848	17	5	heart	heart	PROPN
easat-1848	17	6	federation	federation	PROPN
easat-1848	17	7	's	's	PART
easat-1848	17	8	2023	2023	NUM
easat-1848	17	9	world	world	NOUN
easat-1848	17	10	heart	heart	NOUN
easat-1848	17	11	report	report	NOUN
easat-1848	17	12	,	,	PUNCT
easat-1848	17	13	nearly	nearly	ADV
easat-1848	17	14	one	one	NUM
easat-1848	17	15	-	-	PUNCT
easat-1848	17	16	third	third	NOUN
easat-1848	17	17	of	of	ADP
easat-1848	17	18	all	all	DET
easat-1848	17	19	fatalities	fatality	NOUN
easat-1848	17	20	worldwide	worldwide	ADV
easat-1848	17	21	were	be	AUX
easat-1848	17	22	caused	cause	VERB
easat-1848	17	23	by	by	ADP
easat-1848	17	24	cardiovascular	cardiovascular	ADJ
easat-1848	17	25	diseases	disease	NOUN
easat-1848	17	26	.	.	PUNCT
easat-1848	18	1	statistics	statistic	NOUN
easat-1848	18	2	from	from	ADP
easat-1848	18	3	world	world	NOUN
easat-1848	18	4	health	health	NOUN
easat-1848	18	5	organisation	organisation	NOUN
easat-1848	18	6	indicates	indicate	VERB
easat-1848	18	7	that	that	SCONJ
easat-1848	18	8	more	more	ADJ
easat-1848	18	9	than	than	ADP
easat-1848	18	10	23.6	23.6	NUM
easat-1848	18	11	million	million	NUM
easat-1848	18	12	people	people	NOUN
easat-1848	18	13	could	could	AUX
easat-1848	18	14	die	die	VERB
easat-1848	18	15	largely	largely	ADV
easat-1848	18	16	from	from	ADP
easat-1848	18	17	heart	heart	NOUN
easat-1848	18	18	disease	disease	NOUN
easat-1848	18	19	and	and	CCONJ
easat-1848	18	20	stroke	stroke	NOUN
easat-1848	18	21	in	in	ADP
easat-1848	18	22	2030	2030	NUM
easat-1848	18	23	[	[	X
easat-1848	18	24	1	1	NUM
easat-1848	18	25	]	]	PUNCT
easat-1848	18	26	.	.	PUNCT
easat-1848	19	1	stress	stress	NOUN
easat-1848	19	2	,	,	PUNCT
easat-1848	19	3	alcohol	alcohol	NOUN
easat-1848	19	4	,	,	PUNCT
easat-1848	19	5	smoking	smoking	NOUN
easat-1848	19	6	,	,	PUNCT
easat-1848	19	7	unhealthy	unhealthy	ADJ
easat-1848	19	8	eating	eating	NOUN
easat-1848	19	9	habits	habit	NOUN
easat-1848	19	10	,	,	PUNCT
easat-1848	19	11	sedentary	sedentary	ADJ
easat-1848	19	12	lifestyles	lifestyle	NOUN
easat-1848	19	13	,	,	PUNCT
easat-1848	19	14	and	and	CCONJ
easat-1848	19	15	other	other	ADJ
easat-1848	19	16	factors	factor	NOUN
easat-1848	19	17	like	like	ADP
easat-1848	19	18	diabetes	diabetes	NOUN
easat-1848	19	19	or	or	CCONJ
easat-1848	19	20	high	high	ADJ
easat-1848	19	21	blood	blood	NOUN
easat-1848	19	22	pressure	pressure	NOUN
easat-1848	19	23	are	be	AUX
easat-1848	19	24	few	few	ADJ
easat-1848	19	25	causes	cause	NOUN
easat-1848	19	26	of	of	ADP
easat-1848	19	27	cvd	cvd	PROPN
easat-1848	19	28	[	[	X
easat-1848	19	29	2	2	NUM
easat-1848	19	30	]	]	PUNCT
easat-1848	19	31	.	.	PUNCT
easat-1848	20	1	due	due	ADP
easat-1848	20	2	to	to	ADP
easat-1848	20	3	several	several	ADJ
easat-1848	20	4	factors	factor	NOUN
easat-1848	20	5	,	,	PUNCT
easat-1848	20	6	including	include	VERB
easat-1848	20	7	accuracy	accuracy	NOUN
easat-1848	20	8	and	and	CCONJ
easat-1848	20	9	execution	execution	NOUN
easat-1848	20	10	time	time	NOUN
easat-1848	20	11	,	,	PUNCT
easat-1848	20	12	current	current	ADJ
easat-1848	20	13	heart	heart	NOUN
easat-1848	20	14	disease	disease	NOUN
easat-1848	20	15	diagnosis	diagnosis	NOUN
easat-1848	20	16	procedures	procedure	NOUN
easat-1848	20	17	are	be	AUX
easat-1848	20	18	not	not	PART
easat-1848	20	19	very	very	ADV
easat-1848	20	20	effective	effective	ADJ
easat-1848	20	21	in	in	ADP
easat-1848	20	22	detecting	detect	VERB
easat-1848	20	23	the	the	DET
easat-1848	20	24	disease	disease	NOUN
easat-1848	20	25	in	in	ADP
easat-1848	20	26	its	its	PRON
easat-1848	20	27	early	early	ADJ
easat-1848	20	28	stages	stage	NOUN
easat-1848	20	29	.	.	PUNCT
easat-1848	21	1	as	as	ADP
easat-1848	21	2	a	a	DET
easat-1848	21	3	result	result	NOUN
easat-1848	21	4	,	,	PUNCT
easat-1848	21	5	researchers	researcher	NOUN
easat-1848	21	6	are	be	AUX
easat-1848	21	7	working	work	VERB
easat-1848	21	8	to	to	PART
easat-1848	21	9	develop	develop	VERB
easat-1848	21	10	an	an	DET
easat-1848	21	11	effective	effective	ADJ
easat-1848	21	12	method	method	NOUN
easat-1848	21	13	for	for	ADP
easat-1848	21	14	detecting	detect	VERB
easat-1848	21	15	the	the	DET
easat-1848	21	16	condition	condition	NOUN
easat-1848	21	17	.	.	PUNCT
easat-1848	22	1	when	when	SCONJ
easat-1848	22	2	contemporary	contemporary	ADJ
easat-1848	22	3	equipment	equipment	NOUN
easat-1848	22	4	and	and	CCONJ
easat-1848	22	5	qualified	qualified	ADJ
easat-1848	22	6	medical	medical	ADJ
easat-1848	22	7	personnel	personnel	NOUN
easat-1848	22	8	are	be	AUX
easat-1848	22	9	not	not	PART
easat-1848	22	10	available	available	ADJ
easat-1848	22	11	,	,	PUNCT
easat-1848	22	12	diagnosing	diagnose	VERB
easat-1848	22	13	and	and	CCONJ
easat-1848	22	14	treating	treat	VERB
easat-1848	22	15	heart	heart	NOUN
easat-1848	22	16	disease	disease	NOUN
easat-1848	22	17	is	be	AUX
easat-1848	22	18	really	really	ADV
easat-1848	22	19	challenging	challenging	ADJ
easat-1848	22	20	.	.	PUNCT
easat-1848	23	1	people	people	NOUN
easat-1848	23	2	’s	’s	PART
easat-1848	23	3	lives	life	NOUN
easat-1848	23	4	can	can	AUX
easat-1848	23	5	be	be	AUX
easat-1848	23	6	saved	save	VERB
easat-1848	23	7	by	by	ADP
easat-1848	23	8	earlier	early	ADJ
easat-1848	23	9	diagnosis	diagnosis	NOUN
easat-1848	23	10	and	and	CCONJ
easat-1848	23	11	appropriate	appropriate	ADJ
easat-1848	23	12	care	care	NOUN
easat-1848	23	13	.	.	PUNCT
easat-1848	24	1	the	the	DET
easat-1848	24	2	primary	primary	ADJ
easat-1848	24	3	goal	goal	NOUN
easat-1848	24	4	is	be	AUX
easat-1848	24	5	to	to	PART
easat-1848	24	6	provide	provide	VERB
easat-1848	24	7	succinct	succinct	ADJ
easat-1848	24	8	outline	outline	NOUN
easat-1848	24	9	of	of	ADP
easat-1848	24	10	feature	feature	NOUN
easat-1848	24	11	selection	selection	NOUN
easat-1848	24	12	methods	method	NOUN
easat-1848	24	13	on	on	ADP
easat-1848	24	14	current	current	ADJ
easat-1848	24	15	deep	deep	ADJ
easat-1848	24	16	learning	learning	NOUN
easat-1848	24	17	and	and	CCONJ
easat-1848	24	18	machine	machine	NOUN
easat-1848	24	19	learning	learn	VERB
easat-1848	24	20	to	to	ADP
easat-1848	24	21	foreknow	foreknow	PROPN
easat-1848	24	22	heart	heart	NOUN
easat-1848	24	23	disease	disease	NOUN
easat-1848	24	24	.	.	PUNCT
easat-1848	25	1	a.	a.	NOUN
easat-1848	25	2	background	background	NOUN
easat-1848	25	3	knowledge	knowledge	NOUN
easat-1848	25	4	on	on	ADP
easat-1848	25	5	ml	ml	NOUN
easat-1848	25	6	and	and	CCONJ
easat-1848	25	7	dl	dl	PROPN
easat-1848	25	8	artificial	artificial	ADJ
easat-1848	25	9	intelligence	intelligence	NOUN
easat-1848	25	10	(	(	PUNCT
easat-1848	25	11	ai	ai	PROPN
easat-1848	25	12	)	)	PUNCT
easat-1848	25	13	is	be	AUX
easat-1848	25	14	a	a	DET
easat-1848	25	15	technology	technology	NOUN
easat-1848	25	16	that	that	PRON
easat-1848	25	17	makes	make	VERB
easat-1848	25	18	it	it	PRON
easat-1848	25	19	possible	possible	ADJ
easat-1848	25	20	for	for	SCONJ
easat-1848	25	21	computers	computer	NOUN
easat-1848	25	22	and	and	CCONJ
easat-1848	25	23	other	other	ADJ
easat-1848	25	24	devices	device	NOUN
easat-1848	25	25	to	to	PART
easat-1848	25	26	simulate	simulate	VERB
easat-1848	25	27	decision	decision	NOUN
easat-1848	25	28	making	making	NOUN
easat-1848	25	29	,	,	PUNCT
easat-1848	25	30	human	human	ADJ
easat-1848	25	31	learning	learning	NOUN
easat-1848	25	32	,	,	PUNCT
easat-1848	25	33	conception	conception	NOUN
easat-1848	25	34	,	,	PUNCT
easat-1848	25	35	problem	problem	NOUN
easat-1848	25	36	solving	solving	NOUN
easat-1848	25	37	.	.	PUNCT
easat-1848	26	1	these	these	DET
easat-1848	26	2	tasks	task	NOUN
easat-1848	26	3	comprise	comprise	VERB
easat-1848	26	4	pattern	pattern	NOUN
easat-1848	26	5	recognition	recognition	NOUN
easat-1848	26	6	,	,	PUNCT
easat-1848	26	7	experience	experience	NOUN
easat-1848	26	8	-	-	PUNCT
easat-1848	26	9	based	base	VERB
easat-1848	26	10	learning	learning	NOUN
easat-1848	26	11	,	,	PUNCT
easat-1848	26	12	problem	problem	NOUN
easat-1848	26	13	-	-	PUNCT
easat-1848	26	14	solving	solving	NOUN
easat-1848	26	15	,	,	PUNCT
easat-1848	26	16	comprehension	comprehension	NOUN
easat-1848	26	17	of	of	ADP
easat-1848	26	18	natural	natural	ADJ
easat-1848	26	19	language	language	NOUN
easat-1848	26	20	and	and	CCONJ
easat-1848	26	21	decision	decision	NOUN
easat-1848	26	22	-	-	PUNCT
easat-1848	26	23	making	making	NOUN
easat-1848	26	24	.	.	PUNCT
easat-1848	27	1	to	to	PART
easat-1848	27	2	analyse	analyse	VERB
easat-1848	27	3	enormous	enormous	ADJ
easat-1848	27	4	volume	volume	NOUN
easat-1848	27	5	of	of	ADP
easat-1848	27	6	medical	medical	ADJ
easat-1848	27	7	data	datum	NOUN
easat-1848	27	8	and	and	CCONJ
easat-1848	27	9	find	find	VERB
easat-1848	27	10	patterns	pattern	NOUN
easat-1848	27	11	,	,	PUNCT
easat-1848	27	12	risk	risk	NOUN
easat-1848	27	13	factors	factor	NOUN
easat-1848	27	14	,	,	PUNCT
easat-1848	27	15	and	and	CCONJ
easat-1848	27	16	early	early	ADJ
easat-1848	27	17	indicators	indicator	NOUN
easat-1848	27	18	of	of	ADP
easat-1848	27	19	wide	wide	ADJ
easat-1848	27	20	range	range	NOUN
easat-1848	27	21	of	of	ADP
easat-1848	27	22	diseases	disease	NOUN
easat-1848	27	23	,	,	PUNCT
easat-1848	27	24	artificial	artificial	ADJ
easat-1848	27	25	intelligence	intelligence	NOUN
easat-1848	27	26	(	(	PUNCT
easat-1848	27	27	ai	ai	NOUN
easat-1848	27	28	)	)	PUNCT
easat-1848	27	29	is	be	AUX
easat-1848	27	30	revolutionizing	revolutionize	VERB
easat-1848	27	31	diagnosis	diagnosis	NOUN
easat-1848	27	32	and	and	CCONJ
easat-1848	27	33	treatment	treatment	NOUN
easat-1848	27	34	.	.	PUNCT
easat-1848	28	1	enhancing	enhance	VERB
easat-1848	28	2	early	early	ADJ
easat-1848	28	3	diagnosis	diagnosis	NOUN
easat-1848	28	4	,	,	PUNCT
easat-1848	28	5	tailoring	tailor	VERB
easat-1848	28	6	treatment	treatment	NOUN
easat-1848	28	7	regimens	regimen	NOUN
easat-1848	28	8	,	,	PUNCT
easat-1848	28	9	and	and	CCONJ
easat-1848	28	10	improving	improve	VERB
easat-1848	28	11	patient	patient	ADJ
easat-1848	28	12	outcomes	outcome	NOUN
easat-1848	28	13	1455	1455	NUM
easat-1848	28	14	edelweiss	edelweiss	PROPN
easat-1848	28	15	applied	apply	VERB
easat-1848	28	16	science	science	NOUN
easat-1848	28	17	and	and	CCONJ
easat-1848	28	18	technology	technology	NOUN
easat-1848	28	19	issn	issn	AUX
easat-1848	28	20	:	:	PUNCT
easat-1848	28	21	2576	2576	NUM
easat-1848	28	22	-	-	SYM
easat-1848	28	23	8484	8484	NUM
easat-1848	28	24	vol	vol	NOUN
easat-1848	28	25	.	.	PROPN
easat-1848	28	26	8	8	NUM
easat-1848	28	27	,	,	PUNCT
easat-1848	28	28	no	no	INTJ
easat-1848	28	29	.	.	NOUN
easat-1848	28	30	5	5	NUM
easat-1848	28	31	:	:	SYM
easat-1848	28	32	1445	1445	NUM
easat-1848	28	33	-	-	SYM
easat-1848	28	34	1471	1471	NUM
easat-1848	28	35	,	,	PUNCT
easat-1848	28	36	2024	2024	NUM
easat-1848	28	37	doi	doi	NOUN
easat-1848	28	38	:	:	PUNCT
easat-1848	28	39	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	28	40	©	©	PROPN
easat-1848	28	41	2024	2024	NUM
easat-1848	28	42	by	by	ADP
easat-1848	28	43	the	the	DET
easat-1848	28	44	authors	author	NOUN
easat-1848	28	45	;	;	PUNCT
easat-1848	28	46	licensee	licensee	PROPN
easat-1848	28	47	learning	learning	NOUN
easat-1848	28	48	gate	gate	NOUN
easat-1848	28	49	are	be	AUX
easat-1848	28	50	possible	possible	ADJ
easat-1848	28	51	benefits	benefit	NOUN
easat-1848	28	52	of	of	ADP
easat-1848	28	53	this	this	PRON
easat-1848	28	54	.	.	PUNCT
easat-1848	29	1	it	it	PRON
easat-1848	29	2	is	be	AUX
easat-1848	29	3	used	use	VERB
easat-1848	29	4	often	often	ADV
easat-1848	29	5	in	in	ADP
easat-1848	29	6	the	the	DET
easat-1848	29	7	medical	medical	ADJ
easat-1848	29	8	field	field	NOUN
easat-1848	29	9	to	to	PART
easat-1848	29	10	identify	identify	VERB
easat-1848	29	11	different	different	ADJ
easat-1848	29	12	diseases	disease	NOUN
easat-1848	29	13	,	,	PUNCT
easat-1848	29	14	including	include	VERB
easat-1848	29	15	heart	heart	NOUN
easat-1848	29	16	disease	disease	NOUN
easat-1848	29	17	,	,	PUNCT
easat-1848	29	18	cancer	cancer	NOUN
easat-1848	29	19	and	and	CCONJ
easat-1848	29	20	diabetes	diabetes	NOUN
easat-1848	29	21	.	.	PUNCT
easat-1848	30	1	the	the	DET
easat-1848	30	2	idiom	idiom	ADJ
easat-1848	30	3	"	"	PUNCT
easat-1848	30	4	artificial	artificial	ADJ
easat-1848	30	5	intelligence	intelligence	NOUN
easat-1848	30	6	"	"	PUNCT
easat-1848	30	7	(	(	PUNCT
easat-1848	30	8	ai	ai	NOUN
easat-1848	30	9	)	)	PUNCT
easat-1848	30	10	includes	include	VERB
easat-1848	30	11	analytical	analytical	ADJ
easat-1848	30	12	algorithms	algorithm	NOUN
easat-1848	30	13	that	that	PRON
easat-1848	30	14	repeatedly	repeatedly	ADV
easat-1848	30	15	acquire	acquire	VERB
easat-1848	30	16	from	from	ADP
easat-1848	30	17	data	datum	NOUN
easat-1848	30	18	,	,	PUNCT
easat-1848	30	19	permitting	permit	VERB
easat-1848	30	20	computers	computer	NOUN
easat-1848	30	21	to	to	PART
easat-1848	30	22	discover	discover	VERB
easat-1848	30	23	unobserved	unobserved	ADJ
easat-1848	30	24	intuitions	intuition	NOUN
easat-1848	30	25	.	.	PUNCT
easat-1848	31	1	when	when	SCONJ
easat-1848	31	2	conventional	conventional	ADJ
easat-1848	31	3	statistical	statistical	ADJ
easat-1848	31	4	methods	method	NOUN
easat-1848	31	5	fall	fall	VERB
easat-1848	31	6	short	short	ADJ
easat-1848	31	7	,	,	PUNCT
easat-1848	31	8	there	there	PRON
easat-1848	31	9	are	be	VERB
easat-1848	31	10	set	set	VERB
easat-1848	31	11	of	of	ADP
easat-1848	31	12	operations	operation	NOUN
easat-1848	31	13	that	that	PRON
easat-1848	31	14	include	include	VERB
easat-1848	31	15	reinforcement	reinforcement	NOUN
easat-1848	31	16	learning	learning	NOUN
easat-1848	31	17	,	,	PUNCT
easat-1848	31	18	deep	deep	ADJ
easat-1848	31	19	learning	learning	NOUN
easat-1848	31	20	,	,	PUNCT
easat-1848	31	21	cognitive	cognitive	ADJ
easat-1848	31	22	learning	learning	NOUN
easat-1848	31	23	and	and	CCONJ
easat-1848	31	24	machine	machine	NOUN
easat-1848	31	25	learning	learning	NOUN
easat-1848	31	26	-	-	PUNCT
easat-1848	31	27	based	base	VERB
easat-1848	31	28	methods	method	NOUN
easat-1848	31	29	for	for	ADP
easat-1848	31	30	combining	combine	VERB
easat-1848	31	31	and	and	CCONJ
easat-1848	31	32	analysing	analyse	VERB
easat-1848	31	33	complex	complex	ADJ
easat-1848	31	34	healthcare	healthcare	NOUN
easat-1848	31	35	and	and	CCONJ
easat-1848	31	36	biological	biological	ADJ
easat-1848	31	37	data	datum	NOUN
easat-1848	31	38	[	[	X
easat-1848	31	39	3	3	NUM
easat-1848	31	40	]	]	PUNCT
easat-1848	31	41	.	.	PUNCT
easat-1848	32	1	the	the	DET
easat-1848	32	2	below	below	ADJ
easat-1848	32	3	fig.1	fig.1	PROPN
easat-1848	32	4	describes	describe	VERB
easat-1848	32	5	the	the	DET
easat-1848	32	6	features	feature	NOUN
easat-1848	32	7	of	of	ADP
easat-1848	32	8	deep	deep	ADJ
easat-1848	32	9	learning	learning	NOUN
easat-1848	32	10	,	,	PUNCT
easat-1848	32	11	artificial	artificial	ADJ
easat-1848	32	12	intelligence	intelligence	NOUN
easat-1848	32	13	and	and	CCONJ
easat-1848	32	14	machine	machine	NOUN
easat-1848	32	15	learning	learning	NOUN
easat-1848	32	16	.	.	PUNCT
easat-1848	33	1	machine	machine	NOUN
easat-1848	33	2	learning	learning	NOUN
easat-1848	33	3	(	(	PUNCT
easat-1848	33	4	ml	ml	NOUN
easat-1848	33	5	)	)	PUNCT
easat-1848	33	6	is	be	AUX
easat-1848	33	7	a	a	DET
easat-1848	33	8	subdivision	subdivision	NOUN
easat-1848	33	9	of	of	ADP
easat-1848	33	10	artificial	artificial	ADJ
easat-1848	33	11	intelligence	intelligence	NOUN
easat-1848	33	12	that	that	PRON
easat-1848	33	13	practices	practice	VERB
easat-1848	33	14	mathematical	mathematical	ADJ
easat-1848	33	15	models	model	NOUN
easat-1848	33	16	for	for	ADP
easat-1848	33	17	aiding	aid	VERB
easat-1848	33	18	computer	computer	NOUN
easat-1848	33	19	learn	learn	VERB
easat-1848	33	20	without	without	ADP
easat-1848	33	21	being	be	AUX
easat-1848	33	22	overtly	overtly	ADV
easat-1848	33	23	trained	train	VERB
easat-1848	33	24	.	.	PUNCT
easat-1848	34	1	machine	machine	NOUN
easat-1848	34	2	learning	learning	NOUN
easat-1848	34	3	uses	use	VERB
easat-1848	34	4	algorithms	algorithm	NOUN
easat-1848	34	5	to	to	PART
easat-1848	34	6	discover	discover	VERB
easat-1848	34	7	patterns	pattern	NOUN
easat-1848	34	8	in	in	ADP
easat-1848	34	9	data	datum	NOUN
easat-1848	34	10	.	.	PUNCT
easat-1848	35	1	a	a	DET
easat-1848	35	2	data	data	NOUN
easat-1848	35	3	model	model	NOUN
easat-1848	35	4	that	that	PRON
easat-1848	35	5	forecasts	forecast	VERB
easat-1848	35	6	the	the	DET
easat-1848	35	7	future	future	NOUN
easat-1848	35	8	is	be	AUX
easat-1848	35	9	also	also	ADV
easat-1848	35	10	constructed	construct	VERB
easat-1848	35	11	using	use	VERB
easat-1848	35	12	these	these	DET
easat-1848	35	13	patterns	pattern	NOUN
easat-1848	35	14	.	.	PUNCT
easat-1848	36	1	with	with	ADP
easat-1848	36	2	the	the	DET
easat-1848	36	3	aim	aim	NOUN
easat-1848	36	4	of	of	ADP
easat-1848	36	5	delivering	deliver	VERB
easat-1848	36	6	accurate	accurate	ADJ
easat-1848	36	7	diagnostics	diagnostic	NOUN
easat-1848	36	8	,	,	PUNCT
easat-1848	36	9	risk	risk	NOUN
easat-1848	36	10	assessment	assessment	NOUN
easat-1848	36	11	,	,	PUNCT
easat-1848	36	12	and	and	CCONJ
easat-1848	36	13	personalised	personalised	ADJ
easat-1848	36	14	treatments	treatment	NOUN
easat-1848	36	15	,	,	PUNCT
easat-1848	36	16	machine	machine	NOUN
easat-1848	36	17	learning	learning	NOUN
easat-1848	36	18	algorithms	algorithm	NOUN
easat-1848	36	19	are	be	AUX
easat-1848	36	20	employed	employ	VERB
easat-1848	36	21	in	in	ADP
easat-1848	36	22	prospective	prospective	ADJ
easat-1848	36	23	clinical	clinical	ADJ
easat-1848	36	24	trials	trial	NOUN
easat-1848	36	25	[	[	X
easat-1848	36	26	3	3	NUM
easat-1848	36	27	]	]	PUNCT
easat-1848	36	28	.	.	PUNCT
easat-1848	37	1	the	the	DET
easat-1848	37	2	scope	scope	NOUN
easat-1848	37	3	of	of	ADP
easat-1848	37	4	machine	machine	NOUN
easat-1848	37	5	learning	learning	NOUN
easat-1848	37	6	(	(	PUNCT
easat-1848	37	7	ml	ml	NOUN
easat-1848	37	8	)	)	PUNCT
easat-1848	37	9	is	be	AUX
easat-1848	37	10	to	to	PART
easat-1848	37	11	impart	impart	VERB
easat-1848	37	12	computer	computer	NOUN
easat-1848	37	13	to	to	PART
easat-1848	37	14	utilize	utilize	VERB
easat-1848	37	15	its	its	PRON
easat-1848	37	16	prior	prior	ADJ
easat-1848	37	17	experience	experience	NOUN
easat-1848	37	18	to	to	PART
easat-1848	37	19	crack	crack	VERB
easat-1848	37	20	problems	problem	NOUN
easat-1848	37	21	.	.	PUNCT
easat-1848	38	1	the	the	DET
easat-1848	38	2	notion	notion	NOUN
easat-1848	38	3	of	of	ADP
easat-1848	38	4	using	use	VERB
easat-1848	38	5	machine	machine	NOUN
easat-1848	38	6	learning	learn	VERB
easat-1848	38	7	to	to	PART
easat-1848	38	8	solve	solve	VERB
easat-1848	38	9	issues	issue	NOUN
easat-1848	38	10	more	more	ADV
easat-1848	38	11	quickly	quickly	ADV
easat-1848	38	12	than	than	ADP
easat-1848	38	13	humans	human	NOUN
easat-1848	38	14	in	in	ADP
easat-1848	38	15	many	many	ADJ
easat-1848	38	16	fields	field	NOUN
easat-1848	38	17	.	.	PUNCT
easat-1848	39	1	perceptions	perception	NOUN
easat-1848	39	2	and	and	CCONJ
easat-1848	39	3	connections	connection	NOUN
easat-1848	39	4	between	between	ADP
easat-1848	39	5	data	datum	NOUN
easat-1848	39	6	that	that	PRON
easat-1848	39	7	are	be	AUX
easat-1848	39	8	hidden	hide	VERB
easat-1848	39	9	to	to	ADP
easat-1848	39	10	human	human	ADJ
easat-1848	39	11	eye	eye	NOUN
easat-1848	39	12	can	can	AUX
easat-1848	39	13	be	be	AUX
easat-1848	39	14	found	find	VERB
easat-1848	39	15	by	by	ADP
easat-1848	39	16	processing	processing	NOUN
easat-1848	39	17	and	and	CCONJ
easat-1848	39	18	analysing	analyse	VERB
easat-1848	39	19	very	very	ADV
easat-1848	39	20	large	large	ADJ
easat-1848	39	21	quantity	quantity	NOUN
easat-1848	39	22	of	of	ADP
easat-1848	39	23	data	datum	NOUN
easat-1848	39	24	.	.	PUNCT
easat-1848	40	1	its	its	PRON
easat-1848	40	2	smart	smart	ADJ
easat-1848	40	3	behaviour	behaviour	NOUN
easat-1848	40	4	is	be	AUX
easat-1848	40	5	utilised	utilise	VERB
easat-1848	40	6	in	in	ADP
easat-1848	40	7	various	various	ADJ
easat-1848	40	8	algorithms	algorithm	NOUN
easat-1848	40	9	that	that	PRON
easat-1848	40	10	permit	permit	VERB
easat-1848	40	11	computer	computer	NOUN
easat-1848	40	12	to	to	PART
easat-1848	40	13	make	make	VERB
easat-1848	40	14	relevant	relevant	ADJ
easat-1848	40	15	prediction	prediction	NOUN
easat-1848	40	16	by	by	ADP
easat-1848	40	17	conceptualizing	conceptualize	VERB
easat-1848	40	18	information	information	NOUN
easat-1848	40	19	from	from	ADP
easat-1848	40	20	experience	experience	NOUN
easat-1848	40	21	[	[	X
easat-1848	40	22	4	4	NUM
easat-1848	40	23	]	]	PUNCT
easat-1848	40	24	.	.	PUNCT
easat-1848	41	1	deep	deep	ADJ
easat-1848	41	2	learning	learning	NOUN
easat-1848	42	1	[	[	X
easat-1848	42	2	4	4	X
easat-1848	42	3	]	]	PUNCT
easat-1848	42	4	is	be	AUX
easat-1848	42	5	the	the	DET
easat-1848	42	6	division	division	NOUN
easat-1848	42	7	of	of	ADP
easat-1848	42	8	machine	machine	NOUN
easat-1848	42	9	learning	learning	NOUN
easat-1848	42	10	resembling	resemble	VERB
easat-1848	42	11	the	the	DET
easat-1848	42	12	function	function	NOUN
easat-1848	42	13	and	and	CCONJ
easat-1848	42	14	structure	structure	NOUN
easat-1848	42	15	of	of	ADP
easat-1848	42	16	human	human	ADJ
easat-1848	42	17	brain	brain	NOUN
easat-1848	42	18	.	.	PUNCT
easat-1848	43	1	by	by	ADP
easat-1848	43	2	automatically	automatically	ADV
easat-1848	43	3	extracting	extract	VERB
easat-1848	43	4	complex	complex	ADJ
easat-1848	43	5	patterns	pattern	NOUN
easat-1848	43	6	from	from	ADP
easat-1848	43	7	large	large	ADJ
easat-1848	43	8	and	and	CCONJ
easat-1848	43	9	complicated	complicated	ADJ
easat-1848	43	10	datasets	dataset	NOUN
easat-1848	43	11	,	,	PUNCT
easat-1848	43	12	deep	deep	ADJ
easat-1848	43	13	learning	learning	NOUN
easat-1848	43	14	has	have	AUX
easat-1848	43	15	revealed	reveal	VERB
easat-1848	43	16	great	great	ADJ
easat-1848	43	17	potential	potential	NOUN
easat-1848	43	18	in	in	ADP
easat-1848	43	19	improving	improve	VERB
easat-1848	43	20	the	the	DET
easat-1848	43	21	diagnosis	diagnosis	NOUN
easat-1848	43	22	of	of	ADP
easat-1848	43	23	cardiac	cardiac	ADJ
easat-1848	43	24	disorders	disorder	NOUN
easat-1848	43	25	.	.	PUNCT
easat-1848	44	1	multiple	multiple	ADJ
easat-1848	44	2	layers	layer	NOUN
easat-1848	44	3	in	in	ADP
easat-1848	44	4	deep	deep	ADJ
easat-1848	44	5	learning	learning	NOUN
easat-1848	44	6	models	model	NOUN
easat-1848	44	7	process	process	VERB
easat-1848	44	8	data	datum	NOUN
easat-1848	44	9	through	through	ADP
easat-1848	44	10	nonlinear	nonlinear	ADJ
easat-1848	44	11	transformations	transformation	NOUN
easat-1848	44	12	to	to	PART
easat-1848	44	13	obtain	obtain	VERB
easat-1848	44	14	highlevel	highlevel	ADJ
easat-1848	44	15	characteristics	characteristic	NOUN
easat-1848	44	16	.	.	PUNCT
easat-1848	45	1	these	these	DET
easat-1848	45	2	models	model	NOUN
easat-1848	45	3	have	have	AUX
easat-1848	45	4	revealed	reveal	VERB
easat-1848	45	5	great	great	ADJ
easat-1848	45	6	accomplishment	accomplishment	NOUN
easat-1848	45	7	in	in	ADP
easat-1848	45	8	various	various	ADJ
easat-1848	45	9	fields	field	NOUN
easat-1848	45	10	,	,	PUNCT
easat-1848	45	11	such	such	ADJ
easat-1848	45	12	as	as	ADP
easat-1848	45	13	picture	picture	NOUN
easat-1848	45	14	recognition	recognition	NOUN
easat-1848	45	15	,	,	PUNCT
easat-1848	45	16	speech	speech	NOUN
easat-1848	45	17	recognition	recognition	NOUN
easat-1848	45	18	and	and	CCONJ
easat-1848	45	19	natural	natural	ADJ
easat-1848	45	20	language	language	NOUN
easat-1848	45	21	processing	processing	NOUN
easat-1848	45	22	and	and	CCONJ
easat-1848	45	23	,	,	PUNCT
easat-1848	45	24	healthcare	healthcare	NOUN
easat-1848	45	25	for	for	ADP
easat-1848	45	26	applications	application	NOUN
easat-1848	45	27	like	like	ADP
easat-1848	45	28	disease	disease	NOUN
easat-1848	45	29	prediction	prediction	NOUN
easat-1848	45	30	,	,	PUNCT
easat-1848	45	31	medical	medical	ADJ
easat-1848	45	32	image	image	NOUN
easat-1848	45	33	analysis	analysis	NOUN
easat-1848	45	34	,	,	PUNCT
easat-1848	45	35	and	and	CCONJ
easat-1848	45	36	personalized	personalized	ADJ
easat-1848	45	37	treatment	treatment	NOUN
easat-1848	45	38	.	.	PUNCT
easat-1848	46	1	specifically	specifically	ADV
easat-1848	46	2	,	,	PUNCT
easat-1848	46	3	deep	deep	ADJ
easat-1848	46	4	learning	learning	NOUN
easat-1848	46	5	is	be	AUX
easat-1848	46	6	the	the	DET
easat-1848	46	7	collection	collection	NOUN
easat-1848	46	8	of	of	ADP
easat-1848	46	9	neural	neural	ADJ
easat-1848	46	10	data	datum	NOUN
easat-1848	46	11	driven	drive	VERB
easat-1848	46	12	techniques	technique	NOUN
easat-1848	46	13	built	build	VERB
easat-1848	46	14	using	use	VERB
easat-1848	46	15	automatic	automatic	ADJ
easat-1848	46	16	feature	feature	NOUN
easat-1848	46	17	engineering	engineering	NOUN
easat-1848	46	18	procedures	procedure	NOUN
easat-1848	46	19	;	;	PUNCT
easat-1848	46	20	its	its	PRON
easat-1848	46	21	remarkable	remarkable	ADJ
easat-1848	46	22	high	high	ADJ
easat-1848	46	23	-	-	PUNCT
easat-1848	46	24	performance	performance	NOUN
easat-1848	46	25	and	and	CCONJ
easat-1848	46	26	accuracy	accuracy	NOUN
easat-1848	46	27	stems	stem	VERB
easat-1848	46	28	from	from	ADP
easat-1848	46	29	the	the	DET
easat-1848	46	30	ability	ability	NOUN
easat-1848	46	31	to	to	PART
easat-1848	46	32	automatically	automatically	ADV
easat-1848	46	33	learn	learn	VERB
easat-1848	46	34	features	feature	NOUN
easat-1848	46	35	from	from	ADP
easat-1848	46	36	inputs	input	NOUN
easat-1848	46	37	.	.	PUNCT
easat-1848	47	1	figure	figure	NOUN
easat-1848	47	2	1	1	NUM
easat-1848	47	3	.	.	PUNCT
easat-1848	48	1	what	what	PRON
easat-1848	48	2	is	be	AUX
easat-1848	48	3	ai	ai	VERB
easat-1848	48	4	,	,	PUNCT
easat-1848	48	5	ml	ml	ADV
easat-1848	48	6	and	and	CCONJ
easat-1848	48	7	dl	dl	PROPN
easat-1848	48	8	?	?	PROPN
easat-1848	48	9	1456	1456	NUM
easat-1848	48	10	edelweiss	edelweiss	PROPN
easat-1848	48	11	applied	apply	VERB
easat-1848	48	12	science	science	NOUN
easat-1848	48	13	and	and	CCONJ
easat-1848	48	14	technology	technology	NOUN
easat-1848	48	15	issn	issn	PROPN
easat-1848	48	16	:	:	PUNCT
easat-1848	48	17	2576	2576	NUM
easat-1848	48	18	-	-	SYM
easat-1848	48	19	8484	8484	NUM
easat-1848	48	20	vol	vol	NOUN
easat-1848	48	21	.	.	PROPN
easat-1848	48	22	8	8	NUM
easat-1848	48	23	,	,	PUNCT
easat-1848	48	24	no	no	INTJ
easat-1848	48	25	.	.	NOUN
easat-1848	48	26	5	5	NUM
easat-1848	48	27	:	:	SYM
easat-1848	48	28	1445	1445	NUM
easat-1848	48	29	-	-	SYM
easat-1848	48	30	1471	1471	NUM
easat-1848	48	31	,	,	PUNCT
easat-1848	48	32	2024	2024	NUM
easat-1848	48	33	doi	doi	NOUN
easat-1848	48	34	:	:	PUNCT
easat-1848	48	35	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	48	36	©	©	PROPN
easat-1848	48	37	2024	2024	NUM
easat-1848	48	38	by	by	ADP
easat-1848	48	39	the	the	DET
easat-1848	48	40	authors	author	NOUN
easat-1848	48	41	;	;	PUNCT
easat-1848	48	42	licensee	licensee	PROPN
easat-1848	48	43	learning	learning	NOUN
easat-1848	48	44	gate	gate	NOUN
easat-1848	48	45	this	this	DET
easat-1848	48	46	paper	paper	NOUN
easat-1848	48	47	encompasses	encompass	VERB
easat-1848	48	48	the	the	DET
easat-1848	48	49	subsequent	subsequent	ADJ
easat-1848	48	50	significant	significant	ADJ
easat-1848	48	51	contributions	contribution	NOUN
easat-1848	48	52	:	:	PUNCT
easat-1848	48	53	•	•	ADP
easat-1848	48	54	the	the	DET
easat-1848	48	55	aim	aim	NOUN
easat-1848	48	56	was	be	AUX
easat-1848	48	57	to	to	PART
easat-1848	48	58	look	look	VERB
easat-1848	48	59	at	at	ADP
easat-1848	48	60	the	the	DET
easat-1848	48	61	contribution	contribution	NOUN
easat-1848	48	62	of	of	ADP
easat-1848	48	63	various	various	ADJ
easat-1848	48	64	feature	feature	NOUN
easat-1848	48	65	selection	selection	NOUN
easat-1848	48	66	methods	method	NOUN
easat-1848	48	67	,	,	PUNCT
easat-1848	48	68	such	such	ADJ
easat-1848	48	69	as	as	ADP
easat-1848	48	70	lasso	lasso	NOUN
easat-1848	48	71	,	,	PUNCT
easat-1848	48	72	relief	relief	NOUN
easat-1848	48	73	,	,	PUNCT
easat-1848	48	74	mr	mr	PROPN
easat-1848	48	75	-	-	PUNCT
easat-1848	48	76	mr	mr	PROPN
easat-1848	48	77	,	,	PUNCT
easat-1848	48	78	rfe	rfe	NOUN
easat-1848	48	79	,	,	PUNCT
easat-1848	48	80	and	and	CCONJ
easat-1848	48	81	pca	pca	NOUN
easat-1848	48	82	impact	impact	NOUN
easat-1848	48	83	deep	deep	ADJ
easat-1848	48	84	learning	learning	NOUN
easat-1848	48	85	and	and	CCONJ
easat-1848	48	86	machine	machine	NOUN
easat-1848	48	87	learning	learn	VERB
easat-1848	48	88	algorithms	algorithm	NOUN
easat-1848	48	89	for	for	ADP
easat-1848	48	90	prognosis	prognosis	NOUN
easat-1848	48	91	of	of	ADP
easat-1848	48	92	cardio	cardio	NOUN
easat-1848	48	93	vascular	vascular	ADJ
easat-1848	48	94	disease	disease	NOUN
easat-1848	48	95	.	.	PUNCT
easat-1848	49	1	•	•	NUM
easat-1848	49	2	different	different	ADJ
easat-1848	49	3	feature	feature	NOUN
easat-1848	49	4	selection	selection	NOUN
easat-1848	49	5	approaches	approach	NOUN
easat-1848	49	6	were	be	AUX
easat-1848	49	7	used	use	VERB
easat-1848	49	8	in	in	ADP
easat-1848	49	9	the	the	DET
easat-1848	49	10	next	next	ADJ
easat-1848	49	11	step	step	NOUN
easat-1848	49	12	,	,	PUNCT
easat-1848	49	13	including	include	VERB
easat-1848	49	14	random	random	ADJ
easat-1848	49	15	forest	forest	NOUN
easat-1848	49	16	,	,	PUNCT
easat-1848	49	17	support	support	NOUN
easat-1848	49	18	vector	vector	NOUN
easat-1848	49	19	machine	machine	NOUN
easat-1848	49	20	,	,	PUNCT
easat-1848	49	21	logistic	logistic	ADJ
easat-1848	49	22	regression	regression	NOUN
easat-1848	49	23	,	,	PUNCT
easat-1848	49	24	neural	neural	ADJ
easat-1848	49	25	network	network	NOUN
easat-1848	49	26	,	,	PUNCT
easat-1848	49	27	naïve	naïve	ADJ
easat-1848	49	28	bayes	bayes	NOUN
easat-1848	49	29	and	and	CCONJ
easat-1848	49	30	k	k	NOUN
easat-1848	49	31	-	-	PUNCT
easat-1848	49	32	nearest	near	ADJ
easat-1848	49	33	neighbour	neighbour	NOUN
easat-1848	49	34	.	.	PUNCT
easat-1848	50	1	the	the	DET
easat-1848	50	2	outcomes	outcome	NOUN
easat-1848	50	3	were	be	AUX
easat-1848	50	4	compared	compare	VERB
easat-1848	50	5	using	use	VERB
easat-1848	50	6	accuracy	accuracy	NOUN
easat-1848	50	7	,	,	PUNCT
easat-1848	50	8	precision	precision	NOUN
easat-1848	50	9	,	,	PUNCT
easat-1848	50	10	recall	recall	NOUN
easat-1848	50	11	,	,	PUNCT
easat-1848	50	12	f1score	f1score	NOUN
easat-1848	50	13	,	,	PUNCT
easat-1848	50	14	mse	mse	NOUN
easat-1848	50	15	,	,	PUNCT
easat-1848	50	16	and	and	CCONJ
easat-1848	50	17	mae	mae	PROPN
easat-1848	50	18	assessment	assessment	NOUN
easat-1848	50	19	criteria	criterion	NOUN
easat-1848	50	20	.	.	PUNCT
easat-1848	51	1	•	•	NUM
easat-1848	51	2	the	the	DET
easat-1848	51	3	primary	primary	ADJ
easat-1848	51	4	and	and	CCONJ
easat-1848	51	5	most	most	ADV
easat-1848	51	6	noteworthy	noteworthy	ADJ
easat-1848	51	7	outcome	outcome	NOUN
easat-1848	51	8	of	of	ADP
easat-1848	51	9	the	the	DET
easat-1848	51	10	current	current	ADJ
easat-1848	51	11	investigation	investigation	NOUN
easat-1848	51	12	is	be	AUX
easat-1848	51	13	thorough	thorough	ADJ
easat-1848	51	14	comparison	comparison	NOUN
easat-1848	51	15	of	of	ADP
easat-1848	51	16	several	several	ADJ
easat-1848	51	17	feature	feature	NOUN
easat-1848	51	18	selection	selection	NOUN
easat-1848	51	19	strategies	strategy	NOUN
easat-1848	51	20	on	on	ADP
easat-1848	51	21	deep	deep	ADJ
easat-1848	51	22	learning	learning	NOUN
easat-1848	51	23	and	and	CCONJ
easat-1848	51	24	machine	machine	NOUN
easat-1848	51	25	learning	learn	VERB
easat-1848	51	26	algorithms	algorithm	NOUN
easat-1848	51	27	for	for	ADP
easat-1848	51	28	forecasting	forecast	VERB
easat-1848	51	29	cardiac	cardiac	ADJ
easat-1848	51	30	illnesses	illness	NOUN
easat-1848	51	31	.	.	PUNCT
easat-1848	52	1	2	2	X
easat-1848	52	2	.	.	X
easat-1848	52	3	literature	literature	NOUN
easat-1848	52	4	review	review	VERB
easat-1848	52	5	the	the	DET
easat-1848	52	6	authors	author	NOUN
easat-1848	52	7	[	[	X
easat-1848	52	8	1	1	X
easat-1848	52	9	]	]	PUNCT
easat-1848	52	10	proposed	propose	VERB
easat-1848	52	11	an	an	DET
easat-1848	52	12	efficient	efficient	ADJ
easat-1848	52	13	decision	decision	NOUN
easat-1848	52	14	support	support	NOUN
easat-1848	52	15	system	system	NOUN
easat-1848	52	16	incorporating	incorporate	VERB
easat-1848	52	17	improved	improve	VERB
easat-1848	52	18	weighted	weight	VERB
easat-1848	52	19	random	random	ADJ
easat-1848	52	20	forest	forest	NOUN
easat-1848	52	21	(	(	PUNCT
easat-1848	52	22	iwrf	iwrf	VERB
easat-1848	52	23	)	)	PUNCT
easat-1848	52	24	is	be	AUX
easat-1848	52	25	used	use	VERB
easat-1848	52	26	to	to	PART
easat-1848	52	27	forecast	forecast	VERB
easat-1848	52	28	cardiac	cardiac	ADJ
easat-1848	52	29	disease	disease	NOUN
easat-1848	52	30	,	,	PUNCT
easat-1848	52	31	supervised	supervise	VERB
easat-1848	52	32	infinite	infinite	ADJ
easat-1848	52	33	feature	feature	NOUN
easat-1848	52	34	selection	selection	NOUN
easat-1848	52	35	(	(	PUNCT
easat-1848	52	36	inf	inf	NOUN
easat-1848	52	37	-	-	PUNCT
easat-1848	52	38	fss	fss	NOUN
easat-1848	52	39	)	)	PUNCT
easat-1848	52	40	to	to	PART
easat-1848	52	41	identify	identify	VERB
easat-1848	52	42	the	the	DET
easat-1848	52	43	most	most	ADV
easat-1848	52	44	important	important	ADJ
easat-1848	52	45	features	feature	NOUN
easat-1848	52	46	,	,	PUNCT
easat-1848	52	47	and	and	CCONJ
easat-1848	52	48	bayesian	bayesian	NOUN
easat-1848	52	49	optimization	optimization	NOUN
easat-1848	52	50	to	to	PART
easat-1848	52	51	adjust	adjust	VERB
easat-1848	52	52	the	the	DET
easat-1848	52	53	new	new	ADJ
easat-1848	52	54	hyperparameters	hyperparameter	NOUN
easat-1848	52	55	.	.	PUNCT
easat-1848	53	1	it	it	PRON
easat-1848	53	2	was	be	AUX
easat-1848	53	3	supposed	suppose	VERB
easat-1848	53	4	that	that	SCONJ
easat-1848	53	5	coalescing	coalesce	VERB
easat-1848	53	6	these	these	DET
easat-1848	53	7	approaches	approach	NOUN
easat-1848	53	8	would	would	AUX
easat-1848	53	9	improve	improve	VERB
easat-1848	53	10	efficacy	efficacy	NOUN
easat-1848	53	11	of	of	ADP
easat-1848	53	12	current	current	ADJ
easat-1848	53	13	methodologies	methodology	NOUN
easat-1848	53	14	for	for	ADP
easat-1848	53	15	predicting	predict	VERB
easat-1848	53	16	cvd	cvd	PROPN
easat-1848	53	17	using	use	VERB
easat-1848	53	18	medical	medical	ADJ
easat-1848	53	19	data	data	NOUN
easat-1848	53	20	sets	set	NOUN
easat-1848	53	21	.	.	PUNCT
easat-1848	54	1	an	an	DET
easat-1848	54	2	improved	improve	VERB
easat-1848	54	3	weighted	weight	VERB
easat-1848	54	4	random	random	ADJ
easat-1848	54	5	forest	forest	NOUN
easat-1848	54	6	was	be	AUX
easat-1848	54	7	established	establish	VERB
easat-1848	54	8	to	to	PART
easat-1848	54	9	resolve	resolve	VERB
easat-1848	54	10	class	class	NOUN
easat-1848	54	11	imbalance	imbalance	NOUN
easat-1848	54	12	.	.	PUNCT
easat-1848	55	1	the	the	DET
easat-1848	55	2	authors	author	NOUN
easat-1848	55	3	[	[	X
easat-1848	55	4	5	5	NUM
easat-1848	55	5	]	]	PUNCT
easat-1848	55	6	utilised	utilise	VERB
easat-1848	55	7	rank	rank	NOUN
easat-1848	55	8	values	value	NOUN
easat-1848	55	9	in	in	ADP
easat-1848	55	10	medical	medical	ADJ
easat-1848	55	11	references	reference	NOUN
easat-1848	55	12	and	and	CCONJ
easat-1848	55	13	the	the	DET
easat-1848	55	14	most	most	ADV
easat-1848	55	15	appropriate	appropriate	ADJ
easat-1848	55	16	features	feature	NOUN
easat-1848	55	17	were	be	AUX
easat-1848	55	18	extracted	extract	VERB
easat-1848	55	19	using	use	VERB
easat-1848	55	20	least	least	ADJ
easat-1848	55	21	absolute	absolute	ADJ
easat-1848	55	22	shrinkage	shrinkage	NOUN
easat-1848	55	23	and	and	CCONJ
easat-1848	55	24	selection	selection	NOUN
easat-1848	55	25	operator	operator	NOUN
easat-1848	55	26	and	and	CCONJ
easat-1848	55	27	relief	relief	NOUN
easat-1848	55	28	feature	feature	NOUN
easat-1848	55	29	selection	selection	NOUN
easat-1848	55	30	.	.	PUNCT
easat-1848	56	1	overfitting	overfitte	VERB
easat-1848	56	2	and	and	CCONJ
easat-1848	56	3	underfitting	underfitting	NOUN
easat-1848	56	4	issues	issue	NOUN
easat-1848	56	5	with	with	ADP
easat-1848	56	6	machine	machine	NOUN
easat-1848	56	7	learning	learning	NOUN
easat-1848	56	8	were	be	AUX
easat-1848	56	9	also	also	ADV
easat-1848	56	10	solved	solve	VERB
easat-1848	56	11	with	with	ADP
easat-1848	56	12	this	this	PRON
easat-1848	56	13	.	.	PUNCT
easat-1848	57	1	by	by	ADP
easat-1848	57	2	mingling	mingle	VERB
easat-1848	57	3	traditional	traditional	ADJ
easat-1848	57	4	classifiers	classifier	NOUN
easat-1848	57	5	with	with	ADP
easat-1848	57	6	boosting	boost	VERB
easat-1848	57	7	and	and	CCONJ
easat-1848	57	8	bagging	bagging	NOUN
easat-1848	57	9	methods	method	NOUN
easat-1848	57	10	,	,	PUNCT
easat-1848	57	11	novel	novel	ADJ
easat-1848	57	12	hybrid	hybrid	ADJ
easat-1848	57	13	classifiers	classifier	NOUN
easat-1848	57	14	like	like	VERB
easat-1848	57	15	,	,	PUNCT
easat-1848	57	16	gradient	gradient	ADJ
easat-1848	57	17	boosting	boosting	NOUN
easat-1848	57	18	method	method	NOUN
easat-1848	57	19	,	,	PUNCT
easat-1848	57	20	adaboost	adaboost	ADJ
easat-1848	57	21	method	method	NOUN
easat-1848	57	22	,	,	PUNCT
easat-1848	57	23	decision	decision	NOUN
easat-1848	57	24	tree	tree	NOUN
easat-1848	57	25	bagging	bagging	NOUN
easat-1848	57	26	method	method	NOUN
easat-1848	57	27	,	,	PUNCT
easat-1848	57	28	k	k	X
easat-1848	57	29	-	-	PUNCT
easat-1848	57	30	nearest	near	ADJ
easat-1848	57	31	neighbours	neighbour	NOUN
easat-1848	57	32	bagging	bagging	NOUN
easat-1848	57	33	method	method	NOUN
easat-1848	57	34	and	and	CCONJ
easat-1848	57	35	random	random	ADJ
easat-1848	57	36	forest	forest	NOUN
easat-1848	57	37	bagging	bagging	NOUN
easat-1848	57	38	method	method	NOUN
easat-1848	57	39	were	be	AUX
easat-1848	57	40	created	create	VERB
easat-1848	57	41	to	to	PART
easat-1848	57	42	increase	increase	VERB
easat-1848	57	43	testing	testing	NOUN
easat-1848	57	44	rate	rate	NOUN
easat-1848	57	45	and	and	CCONJ
easat-1848	57	46	shorten	shorten	VERB
easat-1848	57	47	implementation	implementation	NOUN
easat-1848	57	48	time	time	NOUN
easat-1848	57	49	[	[	X
easat-1848	57	50	5	5	NUM
easat-1848	57	51	]	]	PUNCT
easat-1848	57	52	.	.	PUNCT
easat-1848	58	1	the	the	DET
easat-1848	58	2	authors	author	NOUN
easat-1848	58	3	in	in	ADP
easat-1848	58	4	[	[	X
easat-1848	58	5	6	6	NUM
easat-1848	58	6	]	]	PUNCT
easat-1848	58	7	attempted	attempt	VERB
easat-1848	58	8	to	to	PART
easat-1848	58	9	resolve	resolve	VERB
easat-1848	58	10	the	the	DET
easat-1848	58	11	issue	issue	NOUN
easat-1848	58	12	of	of	ADP
easat-1848	58	13	feature	feature	NOUN
easat-1848	58	14	selection	selection	NOUN
easat-1848	58	15	by	by	ADP
easat-1848	58	16	utilising	utilise	VERB
easat-1848	58	17	pre	pre	ADJ
easat-1848	58	18	-	-	ADJ
easat-1848	58	19	processing	processing	ADJ
easat-1848	58	20	methods	method	NOUN
easat-1848	58	21	and	and	CCONJ
easat-1848	58	22	four	four	NUM
easat-1848	58	23	feature	feature	NOUN
easat-1848	58	24	selection	selection	NOUN
easat-1848	58	25	algorithms	algorithm	NOUN
easat-1848	58	26	,	,	PUNCT
easat-1848	58	27	including	include	VERB
easat-1848	58	28	lasso	lasso	NOUN
easat-1848	58	29	,	,	PUNCT
easat-1848	58	30	relief	relief	NOUN
easat-1848	58	31	,	,	PUNCT
easat-1848	58	32	llbfs	llbfs	NOUN
easat-1848	58	33	and	and	CCONJ
easat-1848	58	34	mrmr	mrmr	NOUN
easat-1848	58	35	for	for	ADP
easat-1848	58	36	the	the	DET
easat-1848	58	37	proper	proper	ADJ
easat-1848	58	38	subdivision	subdivision	NOUN
easat-1848	58	39	of	of	ADP
easat-1848	58	40	attributes	attribute	NOUN
easat-1848	58	41	.	.	PUNCT
easat-1848	59	1	these	these	DET
easat-1848	59	2	features	feature	NOUN
easat-1848	59	3	were	be	AUX
easat-1848	59	4	employed	employ	VERB
easat-1848	59	5	for	for	ADP
easat-1848	59	6	successful	successful	ADJ
easat-1848	59	7	classifier	classifier	NOUN
easat-1848	59	8	training	training	NOUN
easat-1848	59	9	and	and	CCONJ
easat-1848	59	10	testing	testing	NOUN
easat-1848	59	11	.	.	PUNCT
easat-1848	60	1	to	to	PART
easat-1848	60	2	choose	choose	VERB
easat-1848	60	3	features	feature	NOUN
easat-1848	60	4	,	,	PUNCT
easat-1848	60	5	the	the	DET
easat-1848	60	6	fast	fast	ADJ
easat-1848	60	7	-	-	PUNCT
easat-1848	60	8	conditional	conditional	ADJ
easat-1848	60	9	mutual	mutual	ADJ
easat-1848	60	10	information	information	NOUN
easat-1848	60	11	feature	feature	NOUN
easat-1848	60	12	selection	selection	NOUN
easat-1848	60	13	algorithm	algorithm	NOUN
easat-1848	60	14	was	be	AUX
easat-1848	60	15	secondly	secondly	ADV
easat-1848	60	16	proposed	propose	VERB
easat-1848	60	17	.	.	PUNCT
easat-1848	61	1	the	the	DET
easat-1848	61	2	authors	author	NOUN
easat-1848	61	3	[	[	X
easat-1848	61	4	7	7	X
easat-1848	61	5	]	]	PUNCT
easat-1848	61	6	suggested	suggest	VERB
easat-1848	61	7	a	a	DET
easat-1848	61	8	model	model	NOUN
easat-1848	61	9	for	for	ADP
easat-1848	61	10	predicting	predict	VERB
easat-1848	61	11	diabetes	diabetes	NOUN
easat-1848	61	12	using	use	VERB
easat-1848	61	13	combined	combined	ADJ
easat-1848	61	14	machine	machine	NOUN
easat-1848	61	15	learning	learning	NOUN
easat-1848	61	16	technique	technique	NOUN
easat-1848	61	17	.	.	PUNCT
easat-1848	62	1	the	the	DET
easat-1848	62	2	support	support	NOUN
easat-1848	62	3	vector	vector	NOUN
easat-1848	62	4	machine	machine	NOUN
easat-1848	62	5	and	and	CCONJ
easat-1848	62	6	artificial	artificial	ADJ
easat-1848	62	7	neural	neural	ADJ
easat-1848	62	8	network	network	NOUN
easat-1848	62	9	models	model	NOUN
easat-1848	62	10	brought	bring	VERB
easat-1848	62	11	up	up	ADP
easat-1848	62	12	conceptual	conceptual	ADJ
easat-1848	62	13	basis	basis	NOUN
easat-1848	62	14	.	.	PUNCT
easat-1848	63	1	the	the	DET
easat-1848	63	2	output	output	NOUN
easat-1848	63	3	of	of	ADP
easat-1848	63	4	these	these	DET
easat-1848	63	5	models	model	NOUN
easat-1848	63	6	served	serve	VERB
easat-1848	63	7	as	as	ADP
easat-1848	63	8	input	input	NOUN
easat-1848	63	9	membership	membership	NOUN
easat-1848	63	10	function	function	NOUN
easat-1848	63	11	of	of	ADP
easat-1848	63	12	fuzzy	fuzzy	ADJ
easat-1848	63	13	model	model	NOUN
easat-1848	63	14	and	and	CCONJ
easat-1848	63	15	fuzzy	fuzzy	ADJ
easat-1848	63	16	logic	logic	NOUN
easat-1848	63	17	concluded	conclude	VERB
easat-1848	63	18	whether	whether	SCONJ
easat-1848	63	19	diabetes	diabetes	NOUN
easat-1848	63	20	diagnosis	diagnosis	NOUN
easat-1848	63	21	was	be	AUX
easat-1848	63	22	positive	positive	ADJ
easat-1848	63	23	or	or	CCONJ
easat-1848	63	24	negative	negative	ADJ
easat-1848	63	25	.	.	PUNCT
easat-1848	64	1	the	the	DET
easat-1848	64	2	fused	fuse	VERB
easat-1848	64	3	models	model	NOUN
easat-1848	64	4	were	be	AUX
easat-1848	64	5	saved	save	VERB
easat-1848	64	6	for	for	ADP
easat-1848	64	7	later	later	ADJ
easat-1848	64	8	use	use	NOUN
easat-1848	64	9	in	in	ADP
easat-1848	64	10	a	a	DET
easat-1848	64	11	cloud	cloud	ADJ
easat-1848	64	12	storage	storage	NOUN
easat-1848	64	13	system	system	NOUN
easat-1848	64	14	.	.	PUNCT
easat-1848	65	1	a	a	DET
easat-1848	65	2	hybrid	hybrid	ADJ
easat-1848	65	3	intelligent	intelligent	ADJ
easat-1848	65	4	machine	machine	NOUN
easat-1848	65	5	learning	learning	NOUN
easat-1848	65	6	-	-	PUNCT
easat-1848	65	7	based	base	VERB
easat-1848	65	8	prediction	prediction	NOUN
easat-1848	65	9	technique	technique	NOUN
easat-1848	65	10	[	[	X
easat-1848	65	11	8	8	NUM
easat-1848	65	12	]	]	PUNCT
easat-1848	65	13	to	to	PART
easat-1848	65	14	forecast	forecast	VERB
easat-1848	65	15	cardiac	cardiac	ADJ
easat-1848	65	16	sickness	sickness	NOUN
easat-1848	65	17	used	use	VERB
easat-1848	65	18	different	different	ADJ
easat-1848	65	19	algorithms	algorithm	NOUN
easat-1848	65	20	,	,	PUNCT
easat-1848	65	21	including	include	VERB
easat-1848	65	22	k	k	NOUN
easat-1848	65	23	-	-	PUNCT
easat-1848	65	24	nearest	near	ADJ
easat-1848	65	25	neighbour	neighbour	NOUN
easat-1848	65	26	,	,	PUNCT
easat-1848	65	27	random	random	ADJ
easat-1848	65	28	forest	forest	NOUN
easat-1848	65	29	,	,	PUNCT
easat-1848	65	30	decision	decision	NOUN
easat-1848	65	31	tree	tree	NOUN
easat-1848	65	32	,	,	PUNCT
easat-1848	65	33	linear	linear	ADJ
easat-1848	65	34	discriminant	discriminant	ADJ
easat-1848	65	35	analysis	analysis	NOUN
easat-1848	65	36	,	,	PUNCT
easat-1848	65	37	support	support	NOUN
easat-1848	65	38	vector	vector	NOUN
easat-1848	65	39	machine	machine	NOUN
easat-1848	65	40	and	and	CCONJ
easat-1848	65	41	gradient	gradient	NOUN
easat-1848	65	42	boosting	boost	VERB
easat-1848	65	43	classifier	classifier	NOUN
easat-1848	65	44	as	as	ADV
easat-1848	65	45	well	well	ADV
easat-1848	65	46	as	as	ADP
easat-1848	65	47	feature	feature	NOUN
easat-1848	65	48	selection	selection	NOUN
easat-1848	65	49	approach	approach	NOUN
easat-1848	65	50	sequential	sequential	ADJ
easat-1848	65	51	feature	feature	NOUN
easat-1848	65	52	selection	selection	NOUN
easat-1848	65	53	.	.	PUNCT
easat-1848	66	1	by	by	ADP
easat-1848	66	2	implementing	implement	VERB
easat-1848	66	3	k	k	ADJ
easat-1848	66	4	-	-	ADJ
easat-1848	66	5	fold	fold	ADJ
easat-1848	66	6	cross	cross	ADJ
easat-1848	66	7	-	-	ADJ
easat-1848	66	8	validation	validation	ADJ
easat-1848	66	9	method	method	NOUN
easat-1848	66	10	,	,	PUNCT
easat-1848	66	11	sequential	sequential	ADJ
easat-1848	66	12	feature	feature	NOUN
easat-1848	66	13	selection	selection	NOUN
easat-1848	66	14	approach	approach	NOUN
easat-1848	66	15	can	can	AUX
easat-1848	66	16	reduce	reduce	VERB
easat-1848	66	17	calculation	calculation	NOUN
easat-1848	66	18	time	time	NOUN
easat-1848	66	19	while	while	SCONJ
easat-1848	66	20	increasing	increase	VERB
easat-1848	66	21	the	the	DET
easat-1848	66	22	classification	classification	NOUN
easat-1848	66	23	accuracy	accuracy	NOUN
easat-1848	66	24	of	of	ADP
easat-1848	66	25	classifiers	classifier	NOUN
easat-1848	66	26	.	.	PUNCT
easat-1848	67	1	the	the	DET
easat-1848	67	2	authors	author	NOUN
easat-1848	67	3	[	[	X
easat-1848	67	4	9	9	NUM
easat-1848	67	5	]	]	PUNCT
easat-1848	67	6	presented	present	VERB
easat-1848	67	7	an	an	DET
easat-1848	67	8	ensemble	ensemble	ADJ
easat-1848	67	9	model	model	NOUN
easat-1848	67	10	and	and	CCONJ
easat-1848	67	11	majority	majority	NOUN
easat-1848	67	12	voting	voting	NOUN
easat-1848	67	13	method	method	NOUN
easat-1848	67	14	to	to	PART
easat-1848	67	15	improve	improve	VERB
easat-1848	67	16	the	the	DET
easat-1848	67	17	accuracy	accuracy	NOUN
easat-1848	67	18	of	of	ADP
easat-1848	67	19	prediction	prediction	NOUN
easat-1848	67	20	of	of	ADP
easat-1848	67	21	heart	heart	NOUN
easat-1848	67	22	disease	disease	NOUN
easat-1848	67	23	.	.	PUNCT
easat-1848	68	1	additionally	additionally	ADV
easat-1848	68	2	,	,	PUNCT
easat-1848	68	3	feature	feature	NOUN
easat-1848	68	4	selection	selection	NOUN
easat-1848	68	5	based	base	VERB
easat-1848	68	6	genetic	genetic	ADJ
easat-1848	68	7	algorithm	algorithm	NOUN
easat-1848	68	8	and	and	CCONJ
easat-1848	68	9	pre	pre	ADJ
easat-1848	68	10	-	-	ADJ
easat-1848	68	11	processing	processing	ADJ
easat-1848	68	12	method	method	NOUN
easat-1848	68	13	were	be	AUX
easat-1848	68	14	proposed	propose	VERB
easat-1848	68	15	to	to	PART
easat-1848	68	16	improve	improve	VERB
easat-1848	68	17	prediction	prediction	NOUN
easat-1848	68	18	accuracy	accuracy	NOUN
easat-1848	68	19	.	.	PUNCT
easat-1848	69	1	for	for	ADP
easat-1848	69	2	predicting	predict	VERB
easat-1848	69	3	chd	chd	NOUN
easat-1848	69	4	using	use	VERB
easat-1848	69	5	an	an	DET
easat-1848	69	6	improved	improve	VERB
easat-1848	69	7	lightgbm	lightgbm	ADJ
easat-1848	69	8	classifier	classifier	NOUN
easat-1848	69	9	,	,	PUNCT
easat-1848	69	10	hy_optgbm	hy_optgbm	PRON
easat-1848	69	11	was	be	AUX
easat-1848	69	12	proposed	propose	VERB
easat-1848	69	13	as	as	ADP
easat-1848	69	14	prediction	prediction	NOUN
easat-1848	69	15	model	model	NOUN
easat-1848	69	16	[	[	X
easat-1848	69	17	10	10	NUM
easat-1848	69	18	]	]	PUNCT
easat-1848	69	19	.	.	PUNCT
easat-1848	70	1	the	the	DET
easat-1848	70	2	hyperparameters	hyperparameter	NOUN
easat-1848	70	3	of	of	ADP
easat-1848	70	4	the	the	DET
easat-1848	70	5	lightgbm	lightgbm	ADJ
easat-1848	70	6	model	model	NOUN
easat-1848	70	7	were	be	AUX
easat-1848	70	8	altered	alter	VERB
easat-1848	70	9	to	to	PART
easat-1848	70	10	improve	improve	VERB
easat-1848	70	11	the	the	DET
easat-1848	70	12	classifier	classifier	NOUN
easat-1848	70	13	's	's	PART
easat-1848	70	14	performance	performance	NOUN
easat-1848	70	15	.	.	PUNCT
easat-1848	71	1	the	the	DET
easat-1848	71	2	model	model	NOUN
easat-1848	71	3	was	be	AUX
easat-1848	71	4	trained	train	VERB
easat-1848	71	5	utilising	utilise	VERB
easat-1848	71	6	altered	alter	VERB
easat-1848	71	7	hyperparameters	hyperparameter	NOUN
easat-1848	71	8	,	,	PUNCT
easat-1848	71	9	and	and	CCONJ
easat-1848	71	10	its	its	PRON
easat-1848	71	11	loss	loss	NOUN
easat-1848	71	12	function	function	NOUN
easat-1848	71	13	was	be	AUX
easat-1848	71	14	enhanced	enhance	VERB
easat-1848	71	15	as	as	ADV
easat-1848	71	16	well	well	ADV
easat-1848	71	17	.	.	PUNCT
easat-1848	72	1	the	the	DET
easat-1848	72	2	most	most	ADV
easat-1848	72	3	cutting	cutting	NOUN
easat-1848	72	4	-	-	PUNCT
easat-1848	72	5	edge	edge	NOUN
easat-1848	72	6	hyperparameter	hyperparameter	NOUN
easat-1848	72	7	optimisation	optimisation	NOUN
easat-1848	72	8	framework	framework	NOUN
easat-1848	72	9	(	(	PUNCT
easat-1848	72	10	optuna	optuna	PROPN
easat-1848	72	11	)	)	PUNCT
easat-1848	72	12	was	be	AUX
easat-1848	72	13	used	use	VERB
easat-1848	72	14	to	to	PART
easat-1848	72	15	optimise	optimise	VERB
easat-1848	72	16	the	the	DET
easat-1848	72	17	prediction	prediction	NOUN
easat-1848	72	18	model	model	NOUN
easat-1848	72	19	's	's	PART
easat-1848	72	20	1457	1457	NUM
easat-1848	72	21	edelweiss	edelweiss	PROPN
easat-1848	72	22	applied	apply	VERB
easat-1848	72	23	science	science	NOUN
easat-1848	72	24	and	and	CCONJ
easat-1848	72	25	technology	technology	NOUN
easat-1848	72	26	issn	issn	PROPN
easat-1848	72	27	:	:	PUNCT
easat-1848	72	28	2576	2576	NUM
easat-1848	72	29	-	-	SYM
easat-1848	72	30	8484	8484	NUM
easat-1848	72	31	vol	vol	NOUN
easat-1848	72	32	.	.	PROPN
easat-1848	72	33	8	8	NUM
easat-1848	72	34	,	,	PUNCT
easat-1848	72	35	no	no	INTJ
easat-1848	72	36	.	.	NOUN
easat-1848	72	37	5	5	NUM
easat-1848	72	38	:	:	SYM
easat-1848	72	39	1445	1445	NUM
easat-1848	72	40	-	-	SYM
easat-1848	72	41	1471	1471	NUM
easat-1848	72	42	,	,	PUNCT
easat-1848	72	43	2024	2024	NUM
easat-1848	72	44	doi	doi	NOUN
easat-1848	72	45	:	:	PUNCT
easat-1848	72	46	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	72	47	©	©	PROPN
easat-1848	72	48	2024	2024	NUM
easat-1848	72	49	by	by	ADP
easat-1848	72	50	the	the	DET
easat-1848	72	51	authors	author	NOUN
easat-1848	72	52	;	;	PUNCT
easat-1848	72	53	licensee	licensee	PROPN
easat-1848	72	54	learning	learn	VERB
easat-1848	72	55	gate	gate	NOUN
easat-1848	72	56	hyperparameters	hyperparameter	NOUN
easat-1848	72	57	.	.	PUNCT
easat-1848	73	1	for	for	ADP
easat-1848	73	2	the	the	DET
easat-1848	73	3	purpose	purpose	NOUN
easat-1848	73	4	of	of	ADP
easat-1848	73	5	predicting	predict	VERB
easat-1848	73	6	cardiovascular	cardiovascular	ADJ
easat-1848	73	7	disorders	disorder	NOUN
easat-1848	73	8	utilising	utilise	VERB
easat-1848	73	9	12	12	NUM
easat-1848	73	10	lead	lead	NOUN
easat-1848	73	11	-	-	PUNCT
easat-1848	73	12	based	base	VERB
easat-1848	73	13	ecg	ecg	PROPN
easat-1848	73	14	images	image	NOUN
easat-1848	73	15	,	,	PUNCT
easat-1848	73	16	a	a	DET
easat-1848	73	17	new	new	ADJ
easat-1848	73	18	,	,	PUNCT
easat-1848	73	19	lightweight	lightweight	ADJ
easat-1848	73	20	deep	deep	ADJ
easat-1848	73	21	learning	learn	VERB
easat-1848	73	22	cnn	cnn	PROPN
easat-1848	73	23	architecture	architecture	NOUN
easat-1848	73	24	was	be	AUX
easat-1848	73	25	suggested	suggest	VERB
easat-1848	73	26	[	[	X
easat-1848	73	27	11	11	NUM
easat-1848	73	28	]	]	PUNCT
easat-1848	73	29	.	.	PUNCT
easat-1848	74	1	the	the	DET
easat-1848	74	2	suggested	suggest	VERB
easat-1848	74	3	cnn	cnn	PROPN
easat-1848	74	4	model	model	PROPN
easat-1848	74	5	outperformed	outperform	VERB
easat-1848	74	6	the	the	DET
easat-1848	74	7	cutting	cutting	NOUN
easat-1848	74	8	-	-	PUNCT
easat-1848	74	9	edge	edge	NOUN
easat-1848	74	10	low	low	ADJ
easat-1848	74	11	-	-	PUNCT
easat-1848	74	12	scale	scale	NOUN
easat-1848	74	13	squeeze	squeeze	NOUN
easat-1848	74	14	net	net	NOUN
easat-1848	74	15	and	and	CCONJ
easat-1848	74	16	alexnet	alexnet	NOUN
easat-1848	74	17	,	,	PUNCT
easat-1848	74	18	with	with	ADP
easat-1848	74	19	success	success	NOUN
easat-1848	74	20	rates	rate	NOUN
easat-1848	74	21	.	.	PUNCT
easat-1848	75	1	an	an	DET
easat-1848	75	2	effective	effective	ADJ
easat-1848	75	3	method	method	NOUN
easat-1848	75	4	for	for	ADP
easat-1848	75	5	foreseeing	foresee	VERB
easat-1848	75	6	risk	risk	NOUN
easat-1848	75	7	of	of	ADP
easat-1848	75	8	coronary	coronary	ADJ
easat-1848	75	9	heart	heart	NOUN
easat-1848	75	10	disease	disease	NOUN
easat-1848	75	11	was	be	AUX
easat-1848	75	12	proposed	propose	VERB
easat-1848	75	13	[	[	X
easat-1848	75	14	12	12	NUM
easat-1848	75	15	]	]	PUNCT
easat-1848	75	16	.	.	PUNCT
easat-1848	76	1	it	it	PRON
easat-1848	76	2	incorporated	incorporate	VERB
easat-1848	76	3	deep	deep	ADJ
easat-1848	76	4	neural	neural	ADJ
easat-1848	76	5	networks	network	NOUN
easat-1848	76	6	that	that	PRON
easat-1848	76	7	were	be	AUX
easat-1848	76	8	trained	train	VERB
easat-1848	76	9	on	on	ADP
easat-1848	76	10	well	well	ADV
easat-1848	76	11	-	-	PUNCT
easat-1848	76	12	organized	organize	VERB
easat-1848	76	13	training	training	NOUN
easat-1848	76	14	data	datum	NOUN
easat-1848	76	15	.	.	PUNCT
easat-1848	77	1	first	first	ADV
easat-1848	77	2	,	,	PUNCT
easat-1848	77	3	it	it	PRON
easat-1848	77	4	demonstrated	demonstrate	VERB
easat-1848	77	5	how	how	SCONJ
easat-1848	77	6	principal	principal	ADJ
easat-1848	77	7	component	component	NOUN
easat-1848	77	8	analysis	analysis	NOUN
easat-1848	77	9	and	and	CCONJ
easat-1848	77	10	variational	variational	ADJ
easat-1848	77	11	autoencoder	autoencoder	NOUN
easat-1848	77	12	models	model	NOUN
easat-1848	77	13	enhance	enhance	VERB
easat-1848	77	14	functionality	functionality	NOUN
easat-1848	77	15	of	of	ADP
easat-1848	77	16	deep	deep	ADJ
easat-1848	77	17	neural	neural	ADJ
easat-1848	77	18	network	network	NOUN
easat-1848	77	19	.	.	PUNCT
easat-1848	78	1	in	in	ADP
easat-1848	78	2	second	second	ADJ
easat-1848	78	3	experiment	experiment	NOUN
easat-1848	78	4	,	,	PUNCT
easat-1848	78	5	proposed	propose	VERB
easat-1848	78	6	approach	approach	NOUN
easat-1848	78	7	was	be	AUX
easat-1848	78	8	contrasted	contrast	VERB
easat-1848	78	9	with	with	ADP
easat-1848	78	10	adaptive	adaptive	ADJ
easat-1848	78	11	boosting	boosting	NOUN
easat-1848	78	12	,	,	PUNCT
easat-1848	78	13	support	support	NOUN
easat-1848	78	14	vector	vector	NOUN
easat-1848	78	15	machine	machine	NOUN
easat-1848	78	16	,	,	PUNCT
easat-1848	78	17	decision	decision	NOUN
easat-1848	78	18	tree	tree	NOUN
easat-1848	78	19	naive	naive	ADJ
easat-1848	78	20	bayes	bayes	NOUN
easat-1848	78	21	,	,	PUNCT
easat-1848	78	22	k	k	NOUN
easat-1848	78	23	-	-	PUNCT
easat-1848	78	24	nearest	near	ADJ
easat-1848	78	25	neighbour	neighbour	NOUN
easat-1848	78	26	,	,	PUNCT
easat-1848	78	27	and	and	CCONJ
easat-1848	78	28	random	random	ADJ
easat-1848	78	29	forest	forest	NOUN
easat-1848	78	30	.	.	PUNCT
easat-1848	79	1	experimental	experimental	ADJ
easat-1848	79	2	outcomes	outcome	NOUN
easat-1848	79	3	demonstrated	demonstrate	VERB
easat-1848	79	4	that	that	SCONJ
easat-1848	79	5	suggested	suggest	VERB
easat-1848	79	6	approach	approach	NOUN
easat-1848	79	7	beat	beat	VERB
easat-1848	79	8	traditional	traditional	ADJ
easat-1848	79	9	machine	machine	NOUN
easat-1848	79	10	learning	learn	VERB
easat-1848	79	11	methods	method	NOUN
easat-1848	79	12	by	by	ADP
easat-1848	79	13	providing	provide	VERB
easat-1848	79	14	better	well	ADJ
easat-1848	79	15	accuracy	accuracy	NOUN
easat-1848	79	16	.	.	PUNCT
easat-1848	80	1	using	use	VERB
easat-1848	80	2	the	the	DET
easat-1848	80	3	uci	uci	PROPN
easat-1848	80	4	heart	heart	PROPN
easat-1848	80	5	illness	illness	NOUN
easat-1848	80	6	dataset	dataset	PROPN
easat-1848	80	7	,	,	PUNCT
easat-1848	80	8	a	a	DET
easat-1848	80	9	novel	novel	ADJ
easat-1848	80	10	method	method	NOUN
easat-1848	80	11	[	[	X
easat-1848	80	12	13	13	NUM
easat-1848	80	13	]	]	PUNCT
easat-1848	80	14	for	for	ADP
easat-1848	80	15	ischemic	ischemic	ADJ
easat-1848	80	16	heart	heart	NOUN
easat-1848	80	17	illness	illness	NOUN
easat-1848	80	18	squirrel	squirrel	PROPN
easat-1848	80	19	search	search	NOUN
easat-1848	80	20	optimisation	optimisation	NOUN
easat-1848	80	21	feature	feature	NOUN
easat-1848	80	22	selection	selection	NOUN
easat-1848	80	23	technique	technique	NOUN
easat-1848	80	24	was	be	AUX
easat-1848	80	25	proposed	propose	VERB
easat-1848	80	26	.	.	PUNCT
easat-1848	81	1	in	in	ADP
easat-1848	81	2	the	the	DET
easat-1848	81	3	study	study	NOUN
easat-1848	81	4	,	,	PUNCT
easat-1848	81	5	characteristics	characteristic	NOUN
easat-1848	81	6	like	like	ADP
easat-1848	81	7	"	"	PUNCT
easat-1848	81	8	cp	cp	NOUN
easat-1848	81	9	,	,	PUNCT
easat-1848	81	10	"	"	PUNCT
easat-1848	81	11	"	"	PUNCT
easat-1848	81	12	restecg	restecg	PROPN
easat-1848	81	13	,	,	PUNCT
easat-1848	81	14	"	"	PUNCT
easat-1848	81	15	"	"	PUNCT
easat-1848	81	16	oldpeak	oldpeak	NOUN
easat-1848	81	17	,	,	PUNCT
easat-1848	81	18	"	"	PUNCT
easat-1848	81	19	"	"	PUNCT
easat-1848	81	20	ca	can	AUX
easat-1848	81	21	,	,	PUNCT
easat-1848	81	22	"	"	PUNCT
easat-1848	81	23	and	and	CCONJ
easat-1848	81	24	"	"	PUNCT
easat-1848	81	25	thal	thal	NOUN
easat-1848	81	26	"	"	PUNCT
easat-1848	81	27	were	be	AUX
easat-1848	81	28	identified	identify	VERB
easat-1848	81	29	for	for	ADP
easat-1848	81	30	prognosis	prognosis	NOUN
easat-1848	81	31	of	of	ADP
easat-1848	81	32	heart	heart	NOUN
easat-1848	81	33	disease	disease	NOUN
easat-1848	81	34	.	.	PUNCT
easat-1848	82	1	the	the	DET
easat-1848	82	2	suggested	suggest	VERB
easat-1848	82	3	ischemic	ischemic	ADJ
easat-1848	82	4	heart	heart	NOUN
easat-1848	82	5	disease	disease	NOUN
easat-1848	82	6	squirrel	squirrel	NOUN
easat-1848	82	7	search	search	NOUN
easat-1848	82	8	optimization	optimization	NOUN
easat-1848	82	9	model	model	NOUN
easat-1848	82	10	and	and	CCONJ
easat-1848	82	11	random	random	ADJ
easat-1848	82	12	forest	forest	NOUN
easat-1848	82	13	classifier	classifier	NOUN
easat-1848	82	14	provided	provide	VERB
easat-1848	82	15	enhanced	enhanced	ADJ
easat-1848	82	16	accuracy	accuracy	NOUN
easat-1848	82	17	for	for	ADP
easat-1848	82	18	heart	heart	NOUN
easat-1848	82	19	disease	disease	NOUN
easat-1848	82	20	prediction	prediction	NOUN
easat-1848	82	21	.	.	PUNCT
easat-1848	83	1	a	a	DET
easat-1848	83	2	fused	fuse	VERB
easat-1848	83	3	random	random	ADJ
easat-1848	83	4	forest	forest	NOUN
easat-1848	83	5	with	with	ADP
easat-1848	83	6	linear	linear	ADJ
easat-1848	83	7	model	model	NOUN
easat-1848	83	8	was	be	AUX
easat-1848	83	9	presented	present	VERB
easat-1848	83	10	[	[	X
easat-1848	83	11	14	14	NUM
easat-1848	83	12	]	]	PUNCT
easat-1848	83	13	.	.	PUNCT
easat-1848	84	1	its	its	PRON
easat-1848	84	2	major	major	ADJ
easat-1848	84	3	goal	goal	NOUN
easat-1848	84	4	was	be	AUX
easat-1848	84	5	to	to	PART
easat-1848	84	6	improve	improve	VERB
easat-1848	84	7	the	the	DET
easat-1848	84	8	predictability	predictability	NOUN
easat-1848	84	9	of	of	ADP
easat-1848	84	10	cardiac	cardiac	ADJ
easat-1848	84	11	disease	disease	NOUN
easat-1848	84	12	.	.	PUNCT
easat-1848	85	1	hrflm	hrflm	NOUN
easat-1848	85	2	approach	approach	NOUN
easat-1848	85	3	,	,	PUNCT
easat-1848	85	4	in	in	ADP
easat-1848	85	5	contrast	contrast	NOUN
easat-1848	85	6	,	,	PUNCT
easat-1848	85	7	had	have	AUX
easat-1848	85	8	been	be	AUX
easat-1848	85	9	an	an	DET
easat-1848	85	10	advantage	advantage	NOUN
easat-1848	85	11	of	of	ADP
easat-1848	85	12	every	every	DET
easat-1848	85	13	feature	feature	NOUN
easat-1848	85	14	without	without	ADP
easat-1848	85	15	any	any	DET
easat-1848	85	16	feature	feature	NOUN
easat-1848	85	17	selection	selection	NOUN
easat-1848	85	18	limitations	limitation	NOUN
easat-1848	85	19	and	and	CCONJ
easat-1848	85	20	had	have	VERB
easat-1848	85	21	higher	high	ADJ
easat-1848	85	22	ability	ability	NOUN
easat-1848	85	23	to	to	PART
easat-1848	85	24	predict	predict	VERB
easat-1848	85	25	heart	heart	NOUN
easat-1848	85	26	disease	disease	NOUN
easat-1848	85	27	than	than	ADP
easat-1848	85	28	existing	exist	VERB
easat-1848	85	29	methods	method	NOUN
easat-1848	85	30	.	.	PUNCT
easat-1848	86	1	recursion	recursion	NOUN
easat-1848	86	2	enhanced	enhance	VERB
easat-1848	86	3	random	random	ADJ
easat-1848	86	4	forest	forest	NOUN
easat-1848	86	5	with	with	ADP
easat-1848	86	6	improved	improve	VERB
easat-1848	86	7	linear	linear	NOUN
easat-1848	86	8	model	model	NOUN
easat-1848	86	9	was	be	AUX
easat-1848	86	10	suggested	suggest	VERB
easat-1848	86	11	[	[	X
easat-1848	86	12	15	15	NUM
easat-1848	86	13	]	]	PUNCT
easat-1848	86	14	for	for	ADP
easat-1848	86	15	predicting	predict	VERB
easat-1848	86	16	heart	heart	NOUN
easat-1848	86	17	disease	disease	NOUN
easat-1848	86	18	and	and	CCONJ
easat-1848	86	19	evaluating	evaluate	VERB
easat-1848	86	20	its	its	PRON
easat-1848	86	21	accuracy	accuracy	NOUN
easat-1848	86	22	.	.	PUNCT
easat-1848	87	1	it	it	PRON
easat-1848	87	2	was	be	AUX
easat-1848	87	3	additionally	additionally	ADV
easat-1848	87	4	suggested	suggest	VERB
easat-1848	87	5	to	to	PART
easat-1848	87	6	design	design	VERB
easat-1848	87	7	artificial	artificial	ADJ
easat-1848	87	8	neural	neural	ADJ
easat-1848	87	9	network	network	NOUN
easat-1848	87	10	with	with	ADP
easat-1848	87	11	feature	feature	NOUN
easat-1848	87	12	selection	selection	NOUN
easat-1848	87	13	and	and	CCONJ
easat-1848	87	14	backpropagation	backpropagation	NOUN
easat-1848	87	15	learning	learn	VERB
easat-1848	87	16	for	for	ADP
easat-1848	87	17	categorising	categorise	VERB
easat-1848	87	18	cardiovascular	cardiovascular	ADJ
easat-1848	87	19	illness	illness	NOUN
easat-1848	87	20	.	.	PUNCT
easat-1848	88	1	the	the	DET
easat-1848	88	2	authors	author	NOUN
easat-1848	88	3	in	in	ADP
easat-1848	88	4	[	[	X
easat-1848	88	5	16	16	NUM
easat-1848	88	6	]	]	PUNCT
easat-1848	88	7	suggested	suggest	VERB
easat-1848	88	8	to	to	PART
easat-1848	88	9	use	use	VERB
easat-1848	88	10	improved	improve	VERB
easat-1848	88	11	salp	salp	NOUN
easat-1848	88	12	swarm	swarm	NOUN
easat-1848	88	13	optimisation	optimisation	NOUN
easat-1848	88	14	and	and	CCONJ
easat-1848	88	15	an	an	DET
easat-1848	88	16	adaptive	adaptive	ADJ
easat-1848	88	17	neuro	neuro	NOUN
easat-1848	88	18	-	-	PUNCT
easat-1848	88	19	fuzzy	fuzzy	ADJ
easat-1848	88	20	inference	inference	NOUN
easat-1848	88	21	system	system	NOUN
easat-1848	88	22	framework	framework	NOUN
easat-1848	88	23	for	for	ADP
easat-1848	88	24	detection	detection	NOUN
easat-1848	88	25	of	of	ADP
easat-1848	88	26	cardiac	cardiac	ADJ
easat-1848	88	27	illness	illness	NOUN
easat-1848	88	28	in	in	ADP
easat-1848	88	29	order	order	NOUN
easat-1848	88	30	to	to	PART
easat-1848	88	31	improve	improve	VERB
easat-1848	88	32	prediction	prediction	NOUN
easat-1848	88	33	accuracy	accuracy	NOUN
easat-1848	88	34	.	.	PUNCT
easat-1848	89	1	utilising	utilise	VERB
easat-1848	89	2	levy	levy	NOUN
easat-1848	89	3	flight	flight	NOUN
easat-1848	89	4	algorithm	algorithm	NOUN
easat-1848	89	5	,	,	PUNCT
easat-1848	89	6	the	the	DET
easat-1848	89	7	suggested	suggest	VERB
easat-1848	89	8	model	model	NOUN
easat-1848	89	9	enhanced	enhance	VERB
easat-1848	89	10	search	search	NOUN
easat-1848	89	11	capability	capability	NOUN
easat-1848	89	12	.	.	PUNCT
easat-1848	90	1	consistent	consistent	ADJ
easat-1848	90	2	learning	learning	NOUN
easat-1848	90	3	in	in	ADP
easat-1848	90	4	adaptive	adaptive	ADJ
easat-1848	90	5	neuro	neuro	NOUN
easat-1848	90	6	-	-	PUNCT
easat-1848	90	7	fuzzy	fuzzy	ADJ
easat-1848	90	8	inference	inference	NOUN
easat-1848	90	9	system	system	NOUN
easat-1848	90	10	relied	rely	VERB
easat-1848	90	11	on	on	ADP
easat-1848	90	12	gradient	gradient	NOUN
easat-1848	90	13	-	-	PUNCT
easat-1848	90	14	based	base	VERB
easat-1848	90	15	learning	learning	NOUN
easat-1848	90	16	and	and	CCONJ
easat-1848	90	17	was	be	AUX
easat-1848	90	18	a	a	DET
easat-1848	90	19	prone	prone	NOUN
easat-1848	90	20	for	for	ADP
easat-1848	90	21	getting	get	VERB
easat-1848	90	22	jammed	jammed	ADJ
easat-1848	90	23	in	in	ADP
easat-1848	90	24	local	local	ADJ
easat-1848	90	25	minima	minima	PROPN
easat-1848	90	26	.	.	PUNCT
easat-1848	91	1	modified	modify	VERB
easat-1848	91	2	salp	salp	PROPN
easat-1848	91	3	swarm	swarm	PROPN
easat-1848	91	4	optimizationadaptive	optimizationadaptive	ADJ
easat-1848	91	5	neuro	neuro	NOUN
easat-1848	91	6	-	-	PUNCT
easat-1848	91	7	fuzzy	fuzzy	ADJ
easat-1848	91	8	inference	inference	NOUN
easat-1848	91	9	system	system	NOUN
easat-1848	91	10	performed	perform	VERB
easat-1848	91	11	well	well	ADV
easat-1848	91	12	in	in	ADP
easat-1848	91	13	terms	term	NOUN
easat-1848	91	14	of	of	ADP
easat-1848	91	15	disease	disease	NOUN
easat-1848	91	16	prediction	prediction	NOUN
easat-1848	91	17	,	,	PUNCT
easat-1848	91	18	as	as	SCONJ
easat-1848	91	19	demonstrated	demonstrate	VERB
easat-1848	91	20	by	by	ADP
easat-1848	91	21	a	a	DET
easat-1848	91	22	simulation	simulation	NOUN
easat-1848	91	23	and	and	CCONJ
easat-1848	91	24	analysis	analysis	NOUN
easat-1848	91	25	.	.	PUNCT
easat-1848	92	1	oci	oci	PROPN
easat-1848	92	2	-	-	PUNCT
easat-1848	92	3	dbn	dbn	PROPN
easat-1848	92	4	,	,	PUNCT
easat-1848	92	5	a	a	DET
easat-1848	92	6	unique	unique	ADJ
easat-1848	92	7	method	method	NOUN
easat-1848	92	8	that	that	PRON
easat-1848	92	9	did	do	AUX
easat-1848	92	10	not	not	PART
easat-1848	92	11	overfit	overfit	VERB
easat-1848	92	12	or	or	CCONJ
easat-1848	92	13	underfit	underfit	NOUN
easat-1848	92	14	,	,	PUNCT
easat-1848	92	15	was	be	AUX
easat-1848	92	16	suggested	suggest	VERB
easat-1848	92	17	[	[	X
easat-1848	92	18	17	17	NUM
easat-1848	92	19	]	]	PUNCT
easat-1848	92	20	for	for	ADP
easat-1848	92	21	categorization	categorization	NOUN
easat-1848	92	22	and	and	CCONJ
easat-1848	92	23	improvement	improvement	NOUN
easat-1848	92	24	in	in	ADP
easat-1848	92	25	heart	heart	NOUN
easat-1848	92	26	disease	disease	NOUN
easat-1848	92	27	prognosis	prognosis	NOUN
easat-1848	92	28	.	.	PUNCT
easat-1848	93	1	in	in	ADP
easat-1848	93	2	the	the	DET
easat-1848	93	3	suggested	suggest	VERB
easat-1848	93	4	oci	oci	PROPN
easat-1848	93	5	-	-	PUNCT
easat-1848	93	6	dbn	dbn	PROPN
easat-1848	93	7	strategy	strategy	NOUN
easat-1848	93	8	,	,	PUNCT
easat-1848	93	9	ruzzo	ruzzo	NOUN
easat-1848	93	10	-	-	PUNCT
easat-1848	93	11	tompa	tompa	NOUN
easat-1848	93	12	performed	perform	VERB
easat-1848	93	13	best	well	ADV
easat-1848	93	14	.	.	PUNCT
easat-1848	94	1	by	by	ADP
easat-1848	94	2	determining	determine	VERB
easat-1848	94	3	each	each	DET
easat-1848	94	4	hidden	hide	VERB
easat-1848	94	5	layer	layer	NOUN
easat-1848	94	6	in	in	ADP
easat-1848	94	7	dbn	dbn	PROPN
easat-1848	94	8	using	use	VERB
easat-1848	94	9	sga	sga	PROPN
easat-1848	94	10	,	,	PUNCT
easat-1848	94	11	proposed	propose	VERB
easat-1848	94	12	oci	oci	PROPN
easat-1848	94	13	-	-	PUNCT
easat-1848	94	14	dbn	dbn	NOUN
easat-1848	94	15	technique	technique	NOUN
easat-1848	94	16	resolved	resolve	VERB
easat-1848	94	17	network	network	NOUN
easat-1848	94	18	optimisation	optimisation	NOUN
easat-1848	94	19	and	and	CCONJ
easat-1848	94	20	setup	setup	NOUN
easat-1848	94	21	issue	issue	NOUN
easat-1848	94	22	.	.	PUNCT
easat-1848	95	1	in	in	ADP
easat-1848	95	2	this	this	DET
easat-1848	95	3	study	study	NOUN
easat-1848	95	4	[	[	X
easat-1848	95	5	18	18	NUM
easat-1848	95	6	]	]	PUNCT
easat-1848	95	7	,	,	PUNCT
easat-1848	95	8	the	the	DET
easat-1848	95	9	properties	property	NOUN
easat-1848	95	10	of	of	ADP
easat-1848	95	11	big	big	ADJ
easat-1848	95	12	data	datum	NOUN
easat-1848	95	13	and	and	CCONJ
easat-1848	95	14	machine	machine	NOUN
easat-1848	95	15	learning	learn	VERB
easat-1848	95	16	for	for	ADP
easat-1848	95	17	foreseeing	foresee	VERB
easat-1848	95	18	the	the	DET
easat-1848	95	19	risk	risk	NOUN
easat-1848	95	20	of	of	ADP
easat-1848	95	21	cvd	cvd	PROPN
easat-1848	95	22	were	be	AUX
easat-1848	95	23	investigated	investigate	VERB
easat-1848	95	24	using	use	VERB
easat-1848	95	25	korean	korean	ADJ
easat-1848	95	26	national	national	PROPN
easat-1848	95	27	health	health	PROPN
easat-1848	95	28	insurance	insurance	PROPN
easat-1848	95	29	service	service	PROPN
easat-1848	95	30	-	-	PUNCT
easat-1848	95	31	national	national	ADJ
easat-1848	95	32	health	health	NOUN
easat-1848	95	33	sample	sample	NOUN
easat-1848	95	34	cohort	cohort	NOUN
easat-1848	95	35	data	datum	NOUN
easat-1848	95	36	analysis	analysis	NOUN
easat-1848	95	37	.	.	PUNCT
easat-1848	96	1	more	more	ADV
easat-1848	96	2	particularly	particularly	ADV
easat-1848	96	3	,	,	PUNCT
easat-1848	96	4	accuracy	accuracy	NOUN
easat-1848	96	5	of	of	ADP
easat-1848	96	6	different	different	ADJ
easat-1848	96	7	machine	machine	NOUN
easat-1848	96	8	learning	learning	NOUN
easat-1848	96	9	(	(	PUNCT
easat-1848	96	10	ml	ml	NOUN
easat-1848	96	11	)	)	PUNCT
easat-1848	96	12	techniques	technique	NOUN
easat-1848	96	13	such	such	ADJ
easat-1848	96	14	as	as	ADP
easat-1848	96	15	lightgbm	lightgbm	ADJ
easat-1848	96	16	,	,	PUNCT
easat-1848	96	17	deep	deep	ADJ
easat-1848	96	18	neural	neural	ADJ
easat-1848	96	19	networks	network	NOUN
easat-1848	96	20	,	,	PUNCT
easat-1848	96	21	logistic	logistic	ADJ
easat-1848	96	22	regression	regression	NOUN
easat-1848	96	23	,	,	PUNCT
easat-1848	96	24	and	and	CCONJ
easat-1848	96	25	random	random	ADJ
easat-1848	96	26	forests	forest	NOUN
easat-1848	96	27	in	in	ADP
easat-1848	96	28	predicting	predict	VERB
easat-1848	96	29	2	2	NUM
easat-1848	96	30	-	-	PUNCT
easat-1848	96	31	years	year	NOUN
easat-1848	96	32	and	and	CCONJ
easat-1848	96	33	10	10	NUM
easat-1848	96	34	-	-	PUNCT
easat-1848	96	35	years	year	NOUN
easat-1848	96	36	risk	risk	NOUN
easat-1848	96	37	of	of	ADP
easat-1848	96	38	cvd	cvd	PROPN
easat-1848	96	39	,	,	PUNCT
easat-1848	96	40	including	include	VERB
easat-1848	96	41	heart	heart	NOUN
easat-1848	96	42	failure	failure	NOUN
easat-1848	96	43	,	,	PUNCT
easat-1848	96	44	atrial	atrial	ADJ
easat-1848	96	45	fibrillation	fibrillation	NOUN
easat-1848	96	46	,	,	PUNCT
easat-1848	96	47	strokes	stroke	NOUN
easat-1848	96	48	and	and	CCONJ
easat-1848	96	49	coronary	coronary	ADJ
easat-1848	96	50	artery	artery	NOUN
easat-1848	96	51	disease	disease	NOUN
easat-1848	96	52	was	be	AUX
easat-1848	96	53	evaluated	evaluate	VERB
easat-1848	96	54	.	.	PUNCT
easat-1848	97	1	a	a	DET
easat-1848	97	2	sophisticated	sophisticated	ADJ
easat-1848	97	3	learning	learning	NOUN
easat-1848	97	4	system	system	NOUN
easat-1848	97	5	random	random	ADJ
easat-1848	97	6	search	search	NOUN
easat-1848	97	7	algorithm	algorithm	NOUN
easat-1848	97	8	based	base	VERB
easat-1848	97	9	random	random	ADJ
easat-1848	97	10	forest	forest	NOUN
easat-1848	97	11	[	[	X
easat-1848	97	12	19	19	NUM
easat-1848	97	13	]	]	PUNCT
easat-1848	97	14	was	be	AUX
easat-1848	97	15	suggested	suggest	VERB
easat-1848	97	16	for	for	ADP
easat-1848	97	17	automatic	automatic	ADJ
easat-1848	97	18	recognition	recognition	NOUN
easat-1848	97	19	of	of	ADP
easat-1848	97	20	heart	heart	NOUN
easat-1848	97	21	failure	failure	NOUN
easat-1848	97	22	.	.	PUNCT
easat-1848	98	1	this	this	DET
easat-1848	98	2	model	model	NOUN
easat-1848	98	3	for	for	ADP
easat-1848	98	4	heart	heart	NOUN
easat-1848	98	5	failure	failure	NOUN
easat-1848	98	6	diagnosis	diagnosis	NOUN
easat-1848	98	7	was	be	AUX
easat-1848	98	8	put	put	VERB
easat-1848	98	9	forth	forth	ADV
easat-1848	98	10	and	and	CCONJ
easat-1848	98	11	developed	develop	VERB
easat-1848	98	12	.	.	PUNCT
easat-1848	99	1	in	in	ADP
easat-1848	99	2	proposed	propose	VERB
easat-1848	99	3	diagnostic	diagnostic	ADJ
easat-1848	99	4	system	system	NOUN
easat-1848	99	5	,	,	PUNCT
easat-1848	99	6	features	feature	NOUN
easat-1848	99	7	were	be	AUX
easat-1848	99	8	selected	select	VERB
easat-1848	99	9	using	use	VERB
easat-1848	99	10	random	random	ADJ
easat-1848	99	11	search	search	NOUN
easat-1848	99	12	algorithm	algorithm	NOUN
easat-1848	99	13	,	,	PUNCT
easat-1848	99	14	and	and	CCONJ
easat-1848	99	15	heart	heart	NOUN
easat-1848	99	16	failure	failure	NOUN
easat-1848	99	17	was	be	AUX
easat-1848	99	18	foreseen	foresee	VERB
easat-1848	99	19	using	use	VERB
easat-1848	99	20	random	random	ADJ
easat-1848	99	21	forest	forest	NOUN
easat-1848	99	22	model	model	NOUN
easat-1848	99	23	.	.	PUNCT
easat-1848	100	1	grid	grid	NOUN
easat-1848	100	2	search	search	NOUN
easat-1848	100	3	was	be	AUX
easat-1848	100	4	used	use	VERB
easat-1848	100	5	to	to	PART
easat-1848	100	6	optimise	optimise	VERB
easat-1848	100	7	suggested	suggest	VERB
easat-1848	100	8	diagnostic	diagnostic	ADJ
easat-1848	100	9	system	system	NOUN
easat-1848	100	10	.	.	PUNCT
easat-1848	101	1	in	in	ADP
easat-1848	101	2	order	order	NOUN
easat-1848	101	3	to	to	PART
easat-1848	101	4	effectively	effectively	ADV
easat-1848	101	5	predict	predict	VERB
easat-1848	101	6	heart	heart	NOUN
easat-1848	101	7	failure	failure	NOUN
easat-1848	101	8	,	,	PUNCT
easat-1848	101	9	an	an	DET
easat-1848	101	10	expert	expert	NOUN
easat-1848	101	11	system	system	NOUN
easat-1848	101	12	[	[	X
easat-1848	101	13	20	20	NUM
easat-1848	101	14	]	]	PUNCT
easat-1848	101	15	comprising	comprise	VERB
easat-1848	101	16	two	two	NUM
easat-1848	101	17	support	support	NOUN
easat-1848	101	18	vector	vector	NOUN
easat-1848	101	19	machine	machine	NOUN
easat-1848	101	20	models	model	NOUN
easat-1848	101	21	was	be	AUX
easat-1848	101	22	presented	present	VERB
easat-1848	101	23	.	.	PUNCT
easat-1848	102	1	linear	linear	PROPN
easat-1848	102	2	and	and	CCONJ
easat-1848	102	3	l1	l1	PROPN
easat-1848	102	4	regularised	regularise	VERB
easat-1848	102	5	described	describe	VERB
easat-1848	102	6	first	first	ADJ
easat-1848	102	7	svm	svm	PROPN
easat-1848	102	8	model	model	NOUN
easat-1848	102	9	.	.	PUNCT
easat-1848	103	1	l2	l2	NOUN
easat-1848	103	2	regularised	regularise	VERB
easat-1848	103	3	was	be	AUX
easat-1848	103	4	second	second	ADJ
easat-1848	103	5	svm	svm	ADJ
easat-1848	103	6	model	model	NOUN
easat-1848	103	7	.	.	PUNCT
easat-1848	104	1	it	it	PRON
easat-1848	104	2	served	serve	VERB
easat-1848	104	3	as	as	ADP
easat-1848	104	4	a	a	DET
easat-1848	104	5	predictive	predictive	ADJ
easat-1848	104	6	modelling	modelling	NOUN
easat-1848	104	7	tool	tool	NOUN
easat-1848	104	8	.	.	PUNCT
easat-1848	105	1	in	in	ADP
easat-1848	105	2	order	order	NOUN
easat-1848	105	3	to	to	PART
easat-1848	105	4	optimise	optimise	VERB
easat-1848	105	5	two	two	NUM
easat-1848	105	6	models	model	NOUN
easat-1848	105	7	,	,	PUNCT
easat-1848	105	8	hybrid	hybrid	ADJ
easat-1848	105	9	grid	grid	NOUN
easat-1848	105	10	search	search	NOUN
easat-1848	105	11	algorithm	algorithm	NOUN
easat-1848	105	12	was	be	AUX
easat-1848	105	13	suggested	suggest	VERB
easat-1848	105	14	that	that	SCONJ
easat-1848	105	15	instantaneously	instantaneously	ADV
easat-1848	105	16	optimised	optimise	VERB
easat-1848	105	17	two	two	NUM
easat-1848	105	18	models	model	NOUN
easat-1848	105	19	.	.	PUNCT
easat-1848	106	1	matthew	matthew	PROPN
easat-1848	106	2	’s	’s	PART
easat-1848	106	3	correlation	correlation	NOUN
easat-1848	106	4	coefficient	coefficient	NOUN
easat-1848	106	5	,	,	PUNCT
easat-1848	106	6	accuracy	accuracy	NOUN
easat-1848	106	7	,	,	PUNCT
easat-1848	106	8	specificity	specificity	NOUN
easat-1848	106	9	,	,	PUNCT
easat-1848	106	10	area	area	NOUN
easat-1848	106	11	under	under	ADP
easat-1848	106	12	the	the	DET
easat-1848	106	13	curve	curve	NOUN
easat-1848	106	14	,	,	PUNCT
easat-1848	106	15	receiver	receiver	ADV
easat-1848	106	16	operating	operate	VERB
easat-1848	106	17	characteristic	characteristic	ADJ
easat-1848	106	18	charts	chart	NOUN
easat-1848	106	19	,	,	PUNCT
easat-1848	106	20	and	and	CCONJ
easat-1848	106	21	sensitivity	sensitivity	NOUN
easat-1848	106	22	[	[	X
easat-1848	106	23	20	20	NUM
easat-1848	106	24	]	]	PUNCT
easat-1848	106	25	were	be	AUX
easat-1848	106	26	six	six	NUM
easat-1848	106	27	evaluation	evaluation	NOUN
easat-1848	106	28	metrics	metric	NOUN
easat-1848	106	29	that	that	PRON
easat-1848	106	30	evaluate	evaluate	VERB
easat-1848	106	31	effectiveness	effectiveness	NOUN
easat-1848	106	32	of	of	ADP
easat-1848	106	33	recommended	recommend	VERB
easat-1848	106	34	approach	approach	NOUN
easat-1848	106	35	.	.	PUNCT
easat-1848	107	1	to	to	PART
easat-1848	107	2	increase	increase	VERB
easat-1848	107	3	diagnosis	diagnosis	NOUN
easat-1848	107	4	efficiency	efficiency	NOUN
easat-1848	107	5	of	of	ADP
easat-1848	107	6	heart	heart	NOUN
easat-1848	107	7	illness	illness	NOUN
easat-1848	107	8	,	,	PUNCT
easat-1848	107	9	a	a	DET
easat-1848	107	10	smart	smart	ADJ
easat-1848	107	11	hybrid	hybrid	ADJ
easat-1848	107	12	system	system	NOUN
easat-1848	107	13	[	[	X
easat-1848	107	14	21	21	NUM
easat-1848	107	15	]	]	PUNCT
easat-1848	107	16	called	call	VERB
easat-1848	107	17	χ2	χ2	PROPN
easat-1848	107	18	-dnn	-dnn	PUNCT
easat-1848	107	19	had	have	AUX
easat-1848	107	20	been	be	AUX
easat-1848	107	21	created	create	VERB
easat-1848	107	22	.	.	PUNCT
easat-1848	108	1	this	this	DET
easat-1848	108	2	study	study	NOUN
easat-1848	108	3	examined	examine	VERB
easat-1848	108	4	the	the	DET
easat-1848	108	5	consequence	consequence	NOUN
easat-1848	108	6	of	of	ADP
easat-1848	108	7	neural	neural	ADJ
easat-1848	108	8	network	network	NOUN
easat-1848	108	9	depth	depth	NOUN
easat-1848	108	10	on	on	ADP
easat-1848	108	11	accuracy	accuracy	NOUN
easat-1848	108	12	.	.	PUNCT
easat-1848	109	1	deep	deep	ADJ
easat-1848	109	2	neural	neural	ADJ
easat-1848	109	3	networks	network	NOUN
easat-1848	109	4	are	be	AUX
easat-1848	109	5	generally	generally	ADV
easat-1848	109	6	achieved	achieve	VERB
easat-1848	109	7	better	well	ADV
easat-1848	109	8	on	on	ADP
easat-1848	109	9	tiny	tiny	ADJ
easat-1848	109	10	datasets	dataset	NOUN
easat-1848	109	11	.	.	PUNCT
easat-1848	110	1	however	however	ADV
easat-1848	110	2	,	,	PUNCT
easat-1848	110	3	dnn	dnn	PROPN
easat-1848	110	4	with	with	ADP
easat-1848	110	5	multiple	multiple	ADJ
easat-1848	110	6	hidden	hide	VERB
easat-1848	110	7	layers	layer	NOUN
easat-1848	110	8	performed	perform	VERB
easat-1848	110	9	better	well	ADV
easat-1848	110	10	than	than	ADP
easat-1848	110	11	ann	ann	PROPN
easat-1848	110	12	on	on	ADP
easat-1848	110	13	heart	heart	NOUN
easat-1848	110	14	disease	disease	NOUN
easat-1848	110	15	dataset	dataset	VERB
easat-1848	110	16	and	and	CCONJ
easat-1848	110	17	unnecessary	unnecessary	ADJ
easat-1848	110	18	characteristics	characteristic	NOUN
easat-1848	110	19	are	be	AUX
easat-1848	110	20	removed	remove	VERB
easat-1848	110	21	.	.	PUNCT
easat-1848	111	1	a	a	DET
easat-1848	111	2	two	two	NUM
easat-1848	111	3	-	-	PUNCT
easat-1848	111	4	level	level	NOUN
easat-1848	111	5	stack	stack	NOUN
easat-1848	111	6	model	model	NOUN
easat-1848	111	7	[	[	X
easat-1848	111	8	22	22	NUM
easat-1848	111	9	]	]	PUNCT
easat-1848	111	10	was	be	AUX
easat-1848	111	11	created	create	VERB
easat-1848	111	12	,	,	PUNCT
easat-1848	111	13	with	with	ADP
easat-1848	111	14	level-1	level-1	NUM
easat-1848	111	15	serving	serve	VERB
easat-1848	111	16	as	as	ADP
easat-1848	111	17	base	base	NOUN
easat-1848	111	18	level	level	NOUN
easat-1848	111	19	and	and	CCONJ
easat-1848	111	20	level-2	level-2	NUM
easat-1848	111	21	as	as	ADP
easat-1848	111	22	meta	meta	ADJ
easat-1848	111	23	level	level	NOUN
easat-1848	111	24	.	.	PUNCT
easat-1848	112	1	the	the	DET
easat-1848	112	2	1458	1458	NUM
easat-1848	112	3	edelweiss	edelweiss	PROPN
easat-1848	112	4	applied	apply	VERB
easat-1848	112	5	science	science	NOUN
easat-1848	112	6	and	and	CCONJ
easat-1848	112	7	technology	technology	NOUN
easat-1848	112	8	issn	issn	PROPN
easat-1848	112	9	:	:	PUNCT
easat-1848	112	10	2576	2576	NUM
easat-1848	112	11	-	-	SYM
easat-1848	112	12	8484	8484	NUM
easat-1848	112	13	vol	vol	NOUN
easat-1848	112	14	.	.	PROPN
easat-1848	113	1	8	8	NUM
easat-1848	113	2	,	,	PUNCT
easat-1848	113	3	no	no	INTJ
easat-1848	113	4	.	.	NOUN
easat-1848	113	5	5	5	NUM
easat-1848	113	6	:	:	SYM
easat-1848	113	7	1445	1445	NUM
easat-1848	113	8	-	-	SYM
easat-1848	113	9	1471	1471	NUM
easat-1848	113	10	,	,	PUNCT
easat-1848	113	11	2024	2024	NUM
easat-1848	113	12	doi	doi	NOUN
easat-1848	113	13	:	:	PUNCT
easat-1848	113	14	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	113	15	©	©	PROPN
easat-1848	113	16	2024	2024	NUM
easat-1848	113	17	by	by	ADP
easat-1848	113	18	the	the	DET
easat-1848	113	19	authors	author	NOUN
easat-1848	113	20	;	;	PUNCT
easat-1848	113	21	licensee	licensee	PROPN
easat-1848	113	22	learning	learn	VERB
easat-1848	113	23	gate	gate	NOUN
easat-1848	113	24	input	input	NOUN
easat-1848	113	25	for	for	ADP
easat-1848	113	26	meta	meta	ADJ
easat-1848	113	27	-	-	PUNCT
easat-1848	113	28	level	level	NOUN
easat-1848	113	29	classifiers	classifier	NOUN
easat-1848	113	30	was	be	AUX
easat-1848	113	31	preferred	prefer	VERB
easat-1848	113	32	from	from	ADP
easat-1848	113	33	predictions	prediction	NOUN
easat-1848	113	34	of	of	ADP
easat-1848	113	35	base	base	NOUN
easat-1848	113	36	-	-	PUNCT
easat-1848	113	37	level	level	NOUN
easat-1848	113	38	classifiers	classifier	NOUN
easat-1848	113	39	.	.	PUNCT
easat-1848	114	1	to	to	PART
easat-1848	114	2	identify	identify	VERB
easat-1848	114	3	lowest	low	ADJ
easat-1848	114	4	correlation	correlation	NOUN
easat-1848	114	5	classifier	classifier	NOUN
easat-1848	114	6	,	,	PUNCT
easat-1848	114	7	maximum	maximum	ADJ
easat-1848	114	8	information	information	NOUN
easat-1848	114	9	coefficient	coefficient	NOUN
easat-1848	114	10	and	and	CCONJ
easat-1848	114	11	pearson	pearson	PROPN
easat-1848	114	12	correlation	correlation	NOUN
easat-1848	114	13	coefficient	coefficient	NOUN
easat-1848	114	14	were	be	AUX
easat-1848	114	15	first	first	ADV
easat-1848	114	16	calculated	calculate	VERB
easat-1848	114	17	.	.	PUNCT
easat-1848	115	1	then	then	ADV
easat-1848	115	2	,	,	PUNCT
easat-1848	115	3	best	well	ADV
easat-1848	115	4	combining	combine	VERB
easat-1848	115	5	classifiers	classifier	NOUN
easat-1848	115	6	that	that	PRON
easat-1848	115	7	produced	produce	VERB
easat-1848	115	8	best	good	ADJ
easat-1848	115	9	result	result	NOUN
easat-1848	115	10	were	be	AUX
easat-1848	115	11	found	find	VERB
easat-1848	115	12	using	use	VERB
easat-1848	115	13	enumeration	enumeration	NOUN
easat-1848	115	14	approach	approach	NOUN
easat-1848	115	15	.	.	PUNCT
easat-1848	116	1	this	this	DET
easat-1848	116	2	study	study	NOUN
easat-1848	116	3	[	[	X
easat-1848	116	4	23	23	NUM
easat-1848	116	5	]	]	PUNCT
easat-1848	116	6	analyses	analyse	VERB
easat-1848	116	7	the	the	DET
easat-1848	116	8	299	299	NUM
easat-1848	116	9	hospitalised	hospitalise	VERB
easat-1848	116	10	patients	patient	NOUN
easat-1848	116	11	with	with	ADP
easat-1848	116	12	heart	heart	NOUN
easat-1848	116	13	failure	failure	NOUN
easat-1848	116	14	who	who	PRON
easat-1848	116	15	survived	survive	VERB
easat-1848	116	16	and	and	CCONJ
easat-1848	116	17	used	use	VERB
easat-1848	116	18	nine	nine	NUM
easat-1848	116	19	classification	classification	NOUN
easat-1848	116	20	models	model	NOUN
easat-1848	116	21	to	to	PART
easat-1848	116	22	predict	predict	VERB
easat-1848	116	23	patient	patient	ADJ
easat-1848	116	24	survival	survival	NOUN
easat-1848	116	25	:	:	PUNCT
easat-1848	116	26	decision	decision	NOUN
easat-1848	116	27	tree	tree	NOUN
easat-1848	116	28	,	,	PUNCT
easat-1848	116	29	stochastic	stochastic	ADJ
easat-1848	116	30	gradient	gradient	NOUN
easat-1848	116	31	classifier	classifier	NOUN
easat-1848	116	32	,	,	PUNCT
easat-1848	116	33	adaptive	adaptive	ADJ
easat-1848	116	34	boosting	boost	VERB
easat-1848	116	35	classifier	classifier	NOUN
easat-1848	116	36	,	,	PUNCT
easat-1848	116	37	random	random	ADJ
easat-1848	116	38	forest	forest	NOUN
easat-1848	116	39	,	,	PUNCT
easat-1848	116	40	gradient	gradient	ADJ
easat-1848	116	41	boosting	boost	VERB
easat-1848	116	42	classifier	classifier	NOUN
easat-1848	116	43	,	,	PUNCT
easat-1848	116	44	logistic	logistic	ADJ
easat-1848	116	45	regression	regression	NOUN
easat-1848	116	46	,	,	PUNCT
easat-1848	116	47	gaussian	gaussian	ADJ
easat-1848	116	48	naive	naive	ADJ
easat-1848	116	49	bayes	bayes	PROPN
easat-1848	116	50	classifier	classifier	PROPN
easat-1848	116	51	support	support	VERB
easat-1848	116	52	vector	vector	NOUN
easat-1848	116	53	machine	machine	NOUN
easat-1848	116	54	and	and	CCONJ
easat-1848	116	55	extra	extra	ADJ
easat-1848	116	56	tree	tree	NOUN
easat-1848	116	57	classifier	classifier	NOUN
easat-1848	116	58	.	.	PUNCT
easat-1848	117	1	the	the	DET
easat-1848	117	2	class	class	NOUN
easat-1848	117	3	imbalance	imbalance	NOUN
easat-1848	117	4	issue	issue	NOUN
easat-1848	117	5	was	be	AUX
easat-1848	117	6	resolved	resolve	VERB
easat-1848	117	7	by	by	ADP
easat-1848	117	8	synthetic	synthetic	ADJ
easat-1848	117	9	minority	minority	NOUN
easat-1848	117	10	oversampling	oversample	VERB
easat-1848	117	11	technique	technique	NOUN
easat-1848	117	12	.	.	PUNCT
easat-1848	118	1	a	a	DET
easat-1848	118	2	highly	highly	ADV
easat-1848	118	3	accurate	accurate	ADJ
easat-1848	118	4	automated	automate	VERB
easat-1848	118	5	method	method	NOUN
easat-1848	118	6	[	[	X
easat-1848	118	7	24	24	NUM
easat-1848	118	8	]	]	PUNCT
easat-1848	118	9	for	for	ADP
easat-1848	118	10	predicting	predict	VERB
easat-1848	118	11	sudden	sudden	ADJ
easat-1848	118	12	cardiac	cardiac	ADJ
easat-1848	118	13	death	death	NOUN
easat-1848	118	14	utilising	utilise	VERB
easat-1848	118	15	quantifiable	quantifiable	ADJ
easat-1848	118	16	arrhythmic	arrhythmic	ADJ
easat-1848	118	17	signals	signal	NOUN
easat-1848	118	18	was	be	AUX
easat-1848	118	19	described	describe	VERB
easat-1848	118	20	.	.	PUNCT
easat-1848	119	1	three	three	NUM
easat-1848	119	2	repolarization	repolarization	NOUN
easat-1848	119	3	interval	interval	NOUN
easat-1848	119	4	ratios	ratio	NOUN
easat-1848	119	5	as	as	ADV
easat-1848	119	6	well	well	ADV
easat-1848	119	7	as	as	ADP
easat-1848	119	8	two	two	NUM
easat-1848	119	9	conductionrepolarization	conductionrepolarization	NOUN
easat-1848	119	10	indicators	indicator	NOUN
easat-1848	119	11	were	be	AUX
easat-1848	119	12	included	include	VERB
easat-1848	119	13	in	in	ADP
easat-1848	119	14	arrhythmic	arrhythmic	ADJ
easat-1848	119	15	parameters	parameter	NOUN
easat-1848	119	16	set	set	VERB
easat-1848	119	17	.	.	PUNCT
easat-1848	120	1	then	then	ADV
easat-1848	120	2	,	,	PUNCT
easat-1848	120	3	all	all	DET
easat-1848	120	4	determined	determined	ADJ
easat-1848	120	5	markers	marker	NOUN
easat-1848	120	6	were	be	AUX
easat-1848	120	7	applied	apply	VERB
easat-1848	120	8	to	to	ADP
easat-1848	120	9	automatic	automatic	ADJ
easat-1848	120	10	classification	classification	NOUN
easat-1848	120	11	of	of	ADP
easat-1848	120	12	normal	normal	ADJ
easat-1848	120	13	and	and	CCONJ
easat-1848	120	14	sudden	sudden	ADJ
easat-1848	120	15	cardiac	cardiac	ADJ
easat-1848	120	16	death	death	NOUN
easat-1848	120	17	risk	risk	NOUN
easat-1848	120	18	groups	group	NOUN
easat-1848	120	19	using	use	VERB
easat-1848	120	20	machine	machine	NOUN
easat-1848	120	21	learning	learn	VERB
easat-1848	120	22	classifiers	classifier	NOUN
easat-1848	120	23	such	such	ADJ
easat-1848	120	24	k	k	NOUN
easat-1848	120	25	-	-	PUNCT
easat-1848	120	26	nearest	near	ADJ
easat-1848	120	27	neighbour	neighbour	NOUN
easat-1848	120	28	,	,	PUNCT
easat-1848	120	29	random	random	ADJ
easat-1848	120	30	forest	forest	NOUN
easat-1848	120	31	,	,	PUNCT
easat-1848	120	32	naive	naive	ADJ
easat-1848	120	33	bayes	bayes	NOUN
easat-1848	120	34	,	,	PUNCT
easat-1848	120	35	support	support	VERB
easat-1848	120	36	vector	vector	NOUN
easat-1848	120	37	machine	machine	NOUN
easat-1848	120	38	and	and	CCONJ
easat-1848	120	39	decision	decision	NOUN
easat-1848	120	40	tree	tree	NOUN
easat-1848	120	41	.	.	PUNCT
easat-1848	121	1	the	the	DET
easat-1848	121	2	current	current	ADJ
easat-1848	121	3	findings	finding	NOUN
easat-1848	121	4	demonstrated	demonstrate	VERB
easat-1848	121	5	that	that	SCONJ
easat-1848	121	6	both	both	CCONJ
easat-1848	121	7	automatic	automatic	ADJ
easat-1848	121	8	classifier	classifier	NOUN
easat-1848	121	9	and	and	CCONJ
easat-1848	121	10	integrated	integrate	VERB
easat-1848	121	11	sudden	sudden	ADJ
easat-1848	121	12	cardiac	cardiac	ADJ
easat-1848	121	13	death	death	NOUN
easat-1848	121	14	index	index	NOUN
easat-1848	121	15	could	could	AUX
easat-1848	121	16	predict	predict	VERB
easat-1848	121	17	sudden	sudden	ADJ
easat-1848	121	18	cardiac	cardiac	ADJ
easat-1848	121	19	death	death	NOUN
easat-1848	121	20	up	up	ADP
easat-1848	121	21	to	to	PART
easat-1848	121	22	30	30	NUM
easat-1848	121	23	minutes	minute	NOUN
easat-1848	121	24	earlier	early	ADV
easat-1848	121	25	.	.	PUNCT
easat-1848	122	1	for	for	ADP
easat-1848	122	2	ensemble	ensemble	ADJ
easat-1848	122	3	voting	voting	NOUN
easat-1848	122	4	algorithms	algorithm	NOUN
easat-1848	122	5	to	to	PART
easat-1848	122	6	predict	predict	VERB
easat-1848	122	7	cardiac	cardiac	ADJ
easat-1848	122	8	disease	disease	NOUN
easat-1848	122	9	[	[	X
easat-1848	122	10	25	25	NUM
easat-1848	122	11	]	]	PUNCT
easat-1848	122	12	,	,	PUNCT
easat-1848	122	13	novel	novel	ADJ
easat-1848	122	14	grouping	grouping	NOUN
easat-1848	122	15	of	of	ADP
easat-1848	122	16	machine	machine	NOUN
easat-1848	122	17	learning	learn	VERB
easat-1848	122	18	classifiers	classifier	NOUN
easat-1848	122	19	is	be	AUX
easat-1848	122	20	presented	present	VERB
easat-1848	122	21	.	.	PUNCT
easat-1848	123	1	individual	individual	ADJ
easat-1848	123	2	classifiers	classifier	NOUN
easat-1848	123	3	are	be	AUX
easat-1848	123	4	first	first	ADV
easat-1848	123	5	empirically	empirically	ADV
easat-1848	123	6	evaluated	evaluate	VERB
easat-1848	123	7	for	for	ADP
easat-1848	123	8	their	their	PRON
easat-1848	123	9	ability	ability	NOUN
easat-1848	123	10	to	to	PART
easat-1848	123	11	forecast	forecast	VERB
easat-1848	123	12	heart	heart	NOUN
easat-1848	123	13	disease	disease	NOUN
easat-1848	123	14	,	,	PUNCT
easat-1848	123	15	and	and	CCONJ
easat-1848	123	16	then	then	ADV
easat-1848	123	17	are	be	AUX
easat-1848	123	18	chosen	choose	VERB
easat-1848	123	19	for	for	ADP
easat-1848	123	20	ensemble	ensemble	ADJ
easat-1848	123	21	voting	voting	NOUN
easat-1848	123	22	systems	system	NOUN
easat-1848	123	23	based	base	VERB
easat-1848	123	24	on	on	ADP
easat-1848	123	25	their	their	PRON
easat-1848	123	26	performance	performance	NOUN
easat-1848	123	27	.	.	PUNCT
easat-1848	124	1	four	four	NUM
easat-1848	124	2	heart	heart	NOUN
easat-1848	124	3	disease	disease	NOUN
easat-1848	124	4	datasets	dataset	NOUN
easat-1848	124	5	are	be	AUX
easat-1848	124	6	specifically	specifically	ADV
easat-1848	124	7	used	use	VERB
easat-1848	124	8	for	for	ADP
easat-1848	124	9	performance	performance	NOUN
easat-1848	124	10	evaluation	evaluation	NOUN
easat-1848	124	11	of	of	ADP
easat-1848	124	12	six	six	NUM
easat-1848	124	13	single	single	ADJ
easat-1848	124	14	classifiers	classifier	NOUN
easat-1848	124	15	and	and	CCONJ
easat-1848	124	16	five	five	NUM
easat-1848	124	17	ensemble	ensemble	ADJ
easat-1848	124	18	voting	voting	NOUN
easat-1848	124	19	schemes	scheme	NOUN
easat-1848	124	20	.	.	PUNCT
easat-1848	125	1	the	the	DET
easat-1848	125	2	proposed	propose	VERB
easat-1848	125	3	ensemble	ensemble	ADJ
easat-1848	125	4	approach	approach	NOUN
easat-1848	125	5	has	have	AUX
easat-1848	125	6	produced	produce	VERB
easat-1848	125	7	improved	improved	ADJ
easat-1848	125	8	outcomes	outcome	NOUN
easat-1848	125	9	than	than	ADP
easat-1848	125	10	other	other	ADJ
easat-1848	125	11	schemes	scheme	NOUN
easat-1848	125	12	.	.	PUNCT
easat-1848	126	1	an	an	DET
easat-1848	126	2	effective	effective	ADJ
easat-1848	126	3	and	and	CCONJ
easat-1848	126	4	highly	highly	ADV
easat-1848	126	5	accurate	accurate	ADJ
easat-1848	126	6	prediction	prediction	NOUN
easat-1848	126	7	of	of	ADP
easat-1848	126	8	cardiovascular	cardiovascular	ADJ
easat-1848	126	9	disorders	disorder	NOUN
easat-1848	126	10	was	be	AUX
easat-1848	126	11	made	make	VERB
easat-1848	126	12	possible	possible	ADJ
easat-1848	126	13	by	by	ADP
easat-1848	126	14	machine	machine	NOUN
easat-1848	126	15	learning	learning	NOUN
easat-1848	126	16	based	base	VERB
easat-1848	126	17	cardiovascular	cardiovascular	ADJ
easat-1848	126	18	disease	disease	NOUN
easat-1848	126	19	diagnosis	diagnosis	NOUN
easat-1848	126	20	architecture	architecture	NOUN
easat-1848	126	21	[	[	X
easat-1848	126	22	26	26	NUM
easat-1848	126	23	]	]	PUNCT
easat-1848	126	24	.	.	PUNCT
easat-1848	127	1	the	the	DET
easat-1848	127	2	framework	framework	NOUN
easat-1848	127	3	initially	initially	ADV
easat-1848	127	4	addressed	address	VERB
easat-1848	127	5	missing	missing	ADJ
easat-1848	127	6	values	value	NOUN
easat-1848	127	7	in	in	ADP
easat-1848	127	8	dataset	dataset	NOUN
easat-1848	127	9	using	use	VERB
easat-1848	127	10	mean	mean	ADJ
easat-1848	127	11	replacement	replacement	NOUN
easat-1848	127	12	technique	technique	NOUN
easat-1848	127	13	and	and	CCONJ
easat-1848	127	14	data	datum	NOUN
easat-1848	127	15	imbalance	imbalance	NOUN
easat-1848	127	16	using	use	VERB
easat-1848	127	17	smote	smote	NOUN
easat-1848	127	18	.	.	PUNCT
easat-1848	128	1	the	the	DET
easat-1848	128	2	comparison	comparison	NOUN
easat-1848	128	3	analysis	analysis	NOUN
easat-1848	128	4	concluded	conclude	VERB
easat-1848	128	5	that	that	SCONJ
easat-1848	128	6	malcadd	malcadd	NOUN
easat-1848	128	7	predictions	prediction	NOUN
easat-1848	128	8	were	be	AUX
easat-1848	128	9	more	more	ADV
easat-1848	128	10	accurate	accurate	ADJ
easat-1848	128	11	.	.	PUNCT
easat-1848	129	1	the	the	DET
easat-1848	129	2	authors	author	NOUN
easat-1848	129	3	[	[	X
easat-1848	129	4	27	27	NUM
easat-1848	129	5	]	]	X
easat-1848	129	6	[	[	X
easat-1848	129	7	28	28	NUM
easat-1848	129	8	]	]	PUNCT
easat-1848	129	9	evaluated	evaluate	VERB
easat-1848	129	10	and	and	CCONJ
easat-1848	129	11	provided	provide	VERB
easat-1848	129	12	an	an	DET
easat-1848	129	13	overview	overview	NOUN
easat-1848	129	14	of	of	ADP
easat-1848	129	15	the	the	DET
easat-1848	129	16	general	general	ADJ
easat-1848	129	17	prediction	prediction	NOUN
easat-1848	129	18	power	power	NOUN
easat-1848	129	19	of	of	ADP
easat-1848	129	20	ml	ml	ADP
easat-1848	129	21	algorithms	algorithm	NOUN
easat-1848	129	22	in	in	ADP
easat-1848	129	23	cardiovascular	cardiovascular	ADJ
easat-1848	129	24	disorders	disorder	NOUN
easat-1848	129	25	.	.	PUNCT
easat-1848	130	1	svm	svm	PROPN
easat-1848	130	2	might	might	AUX
easat-1848	130	3	perform	perform	VERB
easat-1848	130	4	better	well	ADJ
easat-1848	130	5	than	than	ADP
easat-1848	130	6	other	other	ADJ
easat-1848	130	7	algorithms	algorithm	NOUN
easat-1848	130	8	,	,	PUNCT
easat-1848	130	9	even	even	ADV
easat-1848	130	10	though	though	SCONJ
easat-1848	130	11	there	there	PRON
easat-1848	130	12	were	be	VERB
easat-1848	130	13	lack	lack	NOUN
easat-1848	130	14	of	of	ADP
easat-1848	130	15	studies	study	NOUN
easat-1848	130	16	in	in	ADP
easat-1848	130	17	metaanalytics	metaanalytic	NOUN
easat-1848	130	18	for	for	ADP
easat-1848	130	19	both	both	DET
easat-1848	130	20	heart	heart	NOUN
easat-1848	130	21	failure	failure	NOUN
easat-1848	130	22	and	and	CCONJ
easat-1848	130	23	cardiac	cardiac	ADJ
easat-1848	130	24	arrhythmias	arrhythmia	NOUN
easat-1848	130	25	.	.	PUNCT
easat-1848	131	1	the	the	DET
easat-1848	131	2	overall	overall	ADJ
easat-1848	131	3	objective	objective	NOUN
easat-1848	131	4	[	[	X
easat-1848	131	5	29	29	NUM
easat-1848	131	6	]	]	PUNCT
easat-1848	131	7	was	be	AUX
easat-1848	131	8	to	to	PART
easat-1848	131	9	predict	predict	VERB
easat-1848	131	10	precisely	precisely	ADV
easat-1848	131	11	the	the	DET
easat-1848	131	12	presence	presence	NOUN
easat-1848	131	13	of	of	ADP
easat-1848	131	14	heart	heart	NOUN
easat-1848	131	15	disease	disease	NOUN
easat-1848	131	16	.	.	PUNCT
easat-1848	132	1	simulation	simulation	NOUN
easat-1848	132	2	-	-	PUNCT
easat-1848	132	3	based	base	VERB
easat-1848	132	4	experimentations	experimentation	NOUN
easat-1848	132	5	were	be	AUX
easat-1848	132	6	shown	show	VERB
easat-1848	132	7	using	use	VERB
easat-1848	132	8	six	six	NUM
easat-1848	132	9	methodologies	methodology	NOUN
easat-1848	132	10	named	name	VERB
easat-1848	132	11	naive	naive	ADJ
easat-1848	132	12	bayes	bayes	NOUN
easat-1848	132	13	classifier	classifier	NOUN
easat-1848	132	14	,	,	PUNCT
easat-1848	132	15	k	k	X
easat-1848	132	16	-	-	PUNCT
easat-1848	132	17	nearest	near	ADJ
easat-1848	132	18	neighbour	neighbour	NOUN
easat-1848	132	19	,	,	PUNCT
easat-1848	132	20	logistic	logistic	ADJ
easat-1848	132	21	regression	regression	NOUN
easat-1848	132	22	,	,	PUNCT
easat-1848	132	23	decision	decision	NOUN
easat-1848	132	24	tree	tree	NOUN
easat-1848	132	25	classifier	classifier	NOUN
easat-1848	132	26	,	,	PUNCT
easat-1848	132	27	support	support	VERB
easat-1848	132	28	vector	vector	NOUN
easat-1848	132	29	machine	machine	NOUN
easat-1848	132	30	and	and	CCONJ
easat-1848	132	31	random	random	ADJ
easat-1848	132	32	forest	forest	NOUN
easat-1848	132	33	.	.	PUNCT
easat-1848	133	1	it	it	PRON
easat-1848	133	2	was	be	AUX
easat-1848	133	3	concluded	conclude	VERB
easat-1848	133	4	that	that	SCONJ
easat-1848	133	5	random	random	ADJ
easat-1848	133	6	forest	forest	NOUN
easat-1848	133	7	produced	produce	VERB
easat-1848	133	8	more	more	ADJ
easat-1848	133	9	accuracy	accuracy	NOUN
easat-1848	133	10	than	than	ADP
easat-1848	133	11	other	other	ADJ
easat-1848	133	12	techniques	technique	NOUN
easat-1848	133	13	.	.	PUNCT
easat-1848	134	1	this	this	DET
easat-1848	134	2	study	study	NOUN
easat-1848	134	3	[	[	X
easat-1848	134	4	30	30	NUM
easat-1848	134	5	]	]	PUNCT
easat-1848	134	6	sought	seek	VERB
easat-1848	134	7	to	to	PART
easat-1848	134	8	find	find	VERB
easat-1848	134	9	several	several	ADJ
easat-1848	134	10	supervised	supervised	ADJ
easat-1848	134	11	machine	machine	NOUN
easat-1848	134	12	-	-	PUNCT
easat-1848	134	13	learning	learn	VERB
easat-1848	134	14	algorithms	algorithm	NOUN
easat-1848	134	15	for	for	ADP
easat-1848	134	16	predicting	predict	VERB
easat-1848	134	17	cardiac	cardiac	ADJ
easat-1848	134	18	disease	disease	NOUN
easat-1848	134	19	.	.	PUNCT
easat-1848	135	1	the	the	DET
easat-1848	135	2	utility	utility	NOUN
easat-1848	135	3	of	of	ADP
easat-1848	135	4	machine	machine	NOUN
easat-1848	135	5	learning	learn	VERB
easat-1848	135	6	techniques	technique	NOUN
easat-1848	135	7	for	for	ADP
easat-1848	135	8	heart	heart	NOUN
easat-1848	135	9	illness	illness	NOUN
easat-1848	135	10	prediction	prediction	NOUN
easat-1848	135	11	were	be	AUX
easat-1848	135	12	tested	test	VERB
easat-1848	135	13	on	on	ADP
easat-1848	135	14	heart	heart	NOUN
easat-1848	135	15	disease	disease	NOUN
easat-1848	135	16	dataset	dataset	VERB
easat-1848	135	17	,	,	PUNCT
easat-1848	135	18	and	and	CCONJ
easat-1848	135	19	it	it	PRON
easat-1848	135	20	was	be	AUX
easat-1848	135	21	revealed	reveal	VERB
easat-1848	135	22	that	that	SCONJ
easat-1848	135	23	three	three	NUM
easat-1848	135	24	classification	classification	NOUN
easat-1848	135	25	algorithms	algorithm	NOUN
easat-1848	135	26	,	,	PUNCT
easat-1848	135	27	k	k	X
easat-1848	135	28	-	-	PUNCT
easat-1848	135	29	nearest	near	ADJ
easat-1848	135	30	neighbour	neighbour	NOUN
easat-1848	135	31	,	,	PUNCT
easat-1848	135	32	random	random	ADJ
easat-1848	135	33	forests	forest	NOUN
easat-1848	135	34	and	and	CCONJ
easat-1848	135	35	decision	decision	NOUN
easat-1848	135	36	tree	tree	NOUN
easat-1848	135	37	algorithms	algorithm	NOUN
easat-1848	135	38	performed	perform	VERB
easat-1848	135	39	flawlessly	flawlessly	ADV
easat-1848	135	40	,	,	PUNCT
easat-1848	135	41	achieving	achieve	VERB
easat-1848	135	42	an	an	DET
easat-1848	135	43	excellent	excellent	ADJ
easat-1848	135	44	performance	performance	NOUN
easat-1848	135	45	.	.	PUNCT
easat-1848	136	1	authors	author	NOUN
easat-1848	136	2	[	[	X
easat-1848	136	3	31	31	NUM
easat-1848	136	4	]	]	PUNCT
easat-1848	136	5	identified	identify	VERB
easat-1848	136	6	the	the	DET
easat-1848	136	7	most	most	ADV
easat-1848	136	8	effective	effective	ADJ
easat-1848	136	9	ml	ml	ADP
easat-1848	136	10	algorithm	algorithm	PROPN
easat-1848	136	11	naive	naive	ADJ
easat-1848	136	12	bayes	bayes	NOUN
easat-1848	136	13	and	and	CCONJ
easat-1848	136	14	decision	decision	NOUN
easat-1848	136	15	tree	tree	NOUN
easat-1848	136	16	algorithms	algorithm	NOUN
easat-1848	136	17	for	for	ADP
easat-1848	136	18	heart	heart	NOUN
easat-1848	136	19	disease	disease	NOUN
easat-1848	136	20	identification	identification	NOUN
easat-1848	136	21	.	.	PUNCT
easat-1848	137	1	the	the	DET
easat-1848	137	2	study	study	NOUN
easat-1848	137	3	's	's	PART
easat-1848	137	4	findings	finding	NOUN
easat-1848	137	5	presented	present	VERB
easat-1848	137	6	that	that	SCONJ
easat-1848	137	7	random	random	ADJ
easat-1848	137	8	forest	forest	NOUN
easat-1848	137	9	algorithm	algorithm	NOUN
easat-1848	137	10	was	be	AUX
easat-1848	137	11	effective	effective	ADJ
easat-1848	137	12	algorithm	algorithm	NOUN
easat-1848	137	13	for	for	ADP
easat-1848	137	14	predicting	predict	VERB
easat-1848	137	15	heart	heart	NOUN
easat-1848	137	16	disease	disease	NOUN
easat-1848	137	17	,	,	PUNCT
easat-1848	137	18	with	with	ADP
easat-1848	137	19	enhanced	enhanced	ADJ
easat-1848	137	20	accuracy	accuracy	NOUN
easat-1848	137	21	and	and	CCONJ
easat-1848	137	22	produced	produce	VERB
easat-1848	137	23	better	well	ADJ
easat-1848	137	24	results	result	NOUN
easat-1848	137	25	.	.	PUNCT
easat-1848	138	1	for	for	ADP
easat-1848	138	2	forecasting	forecast	VERB
easat-1848	138	3	the	the	DET
easat-1848	138	4	survival	survival	NOUN
easat-1848	138	5	of	of	ADP
easat-1848	138	6	heart	heart	NOUN
easat-1848	138	7	patients	patient	NOUN
easat-1848	138	8	,	,	PUNCT
easat-1848	138	9	the	the	DET
easat-1848	138	10	authors	author	NOUN
easat-1848	138	11	[	[	X
easat-1848	138	12	32	32	NUM
easat-1848	138	13	]	]	PUNCT
easat-1848	138	14	suggested	suggest	VERB
easat-1848	138	15	machine	machine	NOUN
easat-1848	138	16	learning	learning	NOUN
easat-1848	138	17	-	-	PUNCT
easat-1848	138	18	based	base	VERB
easat-1848	138	19	technique	technique	NOUN
easat-1848	138	20	to	to	PART
easat-1848	138	21	predict	predict	VERB
easat-1848	138	22	cardiac	cardiac	ADJ
easat-1848	138	23	disease	disease	NOUN
easat-1848	138	24	.	.	PUNCT
easat-1848	139	1	they	they	PRON
easat-1848	139	2	used	use	VERB
easat-1848	139	3	eight	eight	NUM
easat-1848	139	4	classification	classification	NOUN
easat-1848	139	5	models	model	NOUN
easat-1848	139	6	,	,	PUNCT
easat-1848	139	7	including	include	VERB
easat-1848	139	8	linear	linear	ADJ
easat-1848	139	9	discriminant	discriminant	ADJ
easat-1848	139	10	analysis	analysis	NOUN
easat-1848	139	11	,	,	PUNCT
easat-1848	139	12	decision	decision	NOUN
easat-1848	139	13	tree	tree	NOUN
easat-1848	139	14	,	,	PUNCT
easat-1848	139	15	adaptive	adaptive	ADJ
easat-1848	139	16	boosting	boosting	NOUN
easat-1848	139	17	,	,	PUNCT
easat-1848	139	18	extra	extra	ADJ
easat-1848	139	19	tree	tree	NOUN
easat-1848	139	20	,	,	PUNCT
easat-1848	139	21	ridge	ridge	NOUN
easat-1848	139	22	classifiers	classifier	NOUN
easat-1848	139	23	,	,	PUNCT
easat-1848	139	24	logistic	logistic	ADJ
easat-1848	139	25	regression	regression	NOUN
easat-1848	139	26	,	,	PUNCT
easat-1848	139	27	random	random	ADJ
easat-1848	139	28	forest	forest	NOUN
easat-1848	139	29	,	,	PUNCT
easat-1848	139	30	and	and	CCONJ
easat-1848	139	31	light	light	ADJ
easat-1848	139	32	gradient	gradient	NOUN
easat-1848	139	33	boosting	boost	VERB
easat-1848	139	34	machine	machine	NOUN
easat-1848	139	35	.	.	PUNCT
easat-1848	140	1	smote	smote	PROPN
easat-1848	140	2	was	be	AUX
easat-1848	140	3	utilised	utilise	VERB
easat-1848	140	4	to	to	PART
easat-1848	140	5	solve	solve	VERB
easat-1848	140	6	class	class	NOUN
easat-1848	140	7	inequality	inequality	NOUN
easat-1848	140	8	issue	issue	NOUN
easat-1848	140	9	.	.	PUNCT
easat-1848	141	1	the	the	DET
easat-1848	141	2	authors	author	NOUN
easat-1848	141	3	[	[	X
easat-1848	141	4	33	33	NUM
easat-1848	141	5	]	]	PUNCT
easat-1848	141	6	used	use	VERB
easat-1848	141	7	machine	machine	NOUN
easat-1848	141	8	learning	learn	VERB
easat-1848	141	9	techniques	technique	NOUN
easat-1848	141	10	like	like	ADP
easat-1848	141	11	support	support	NOUN
easat-1848	141	12	vector	vector	NOUN
easat-1848	141	13	machine	machine	NOUN
easat-1848	141	14	,	,	PUNCT
easat-1848	141	15	random	random	ADJ
easat-1848	141	16	forest	forest	NOUN
easat-1848	141	17	,	,	PUNCT
easat-1848	141	18	k	k	X
easat-1848	141	19	-	-	PUNCT
easat-1848	141	20	nearest	near	ADJ
easat-1848	141	21	neighbour	neighbour	NOUN
easat-1848	141	22	,	,	PUNCT
easat-1848	141	23	and	and	CCONJ
easat-1848	141	24	deep	deep	ADJ
easat-1848	141	25	learning	learning	NOUN
easat-1848	141	26	models	model	NOUN
easat-1848	141	27	like	like	ADP
easat-1848	141	28	gated	gate	VERB
easat-1848	141	29	-	-	PUNCT
easat-1848	141	30	recurrent	recurrent	NOUN
easat-1848	141	31	unit	unit	NOUN
easat-1848	141	32	neural	neural	ADJ
easat-1848	141	33	networks	network	NOUN
easat-1848	141	34	and	and	CCONJ
easat-1848	141	35	long	long	ADJ
easat-1848	141	36	short	short	ADJ
easat-1848	141	37	-	-	PUNCT
easat-1848	141	38	term	term	NOUN
easat-1848	141	39	memory	memory	NOUN
easat-1848	141	40	to	to	PART
easat-1848	141	41	deploy	deploy	VERB
easat-1848	141	42	on	on	ADP
easat-1848	141	43	uci	uci	PROPN
easat-1848	141	44	heart	heart	NOUN
easat-1848	141	45	disease	disease	NOUN
easat-1848	141	46	dataset	dataset	VERB
easat-1848	141	47	.	.	PUNCT
easat-1848	142	1	by	by	ADP
easat-1848	142	2	integrating	integrate	VERB
easat-1848	142	3	various	various	ADJ
easat-1848	142	4	classifiers	classifier	NOUN
easat-1848	142	5	,	,	PUNCT
easat-1848	142	6	ensemble	ensemble	ADJ
easat-1848	142	7	voting	voting	NOUN
easat-1848	142	8	-	-	PUNCT
easat-1848	142	9	based	base	VERB
easat-1848	142	10	models	model	NOUN
easat-1848	142	11	had	have	AUX
easat-1848	142	12	been	be	AUX
easat-1848	142	13	used	use	VERB
easat-1848	142	14	to	to	PART
easat-1848	142	15	enhance	enhance	VERB
easat-1848	142	16	the	the	DET
easat-1848	142	17	accuracy	accuracy	NOUN
easat-1848	142	18	of	of	ADP
easat-1848	142	19	weak	weak	ADJ
easat-1848	142	20	algorithms	algorithm	NOUN
easat-1848	142	21	.	.	PUNCT
easat-1848	143	1	to	to	PART
easat-1848	143	2	forecast	forecast	VERB
easat-1848	143	3	the	the	DET
easat-1848	143	4	presence	presence	NOUN
easat-1848	143	5	of	of	ADP
easat-1848	143	6	cardiac	cardiac	ADJ
easat-1848	143	7	disease	disease	NOUN
easat-1848	143	8	in	in	ADP
easat-1848	143	9	an	an	DET
easat-1848	143	10	individual	individual	NOUN
easat-1848	143	11	,	,	PUNCT
easat-1848	143	12	authors	author	NOUN
easat-1848	143	13	[	[	X
easat-1848	143	14	34	34	NUM
easat-1848	143	15	]	]	PUNCT
easat-1848	143	16	used	use	VERB
easat-1848	143	17	supervised	supervised	ADJ
easat-1848	143	18	machine	machine	NOUN
easat-1848	143	19	learning	learning	NOUN
easat-1848	143	20	methods	method	NOUN
easat-1848	143	21	.	.	PUNCT
easat-1848	144	1	the	the	DET
easat-1848	144	2	heart	heart	NOUN
easat-1848	144	3	illness	illness	NOUN
easat-1848	144	4	dataset	dataset	NOUN
easat-1848	144	5	was	be	AUX
easat-1848	144	6	subjected	subject	VERB
easat-1848	144	7	to	to	ADP
easat-1848	144	8	naive	naive	ADJ
easat-1848	144	9	bayes	bayes	NOUN
easat-1848	144	10	,	,	PUNCT
easat-1848	144	11	k	k	NOUN
easat-1848	144	12	-	-	PUNCT
easat-1848	144	13	nearest	near	ADJ
easat-1848	144	14	neighbours	neighbour	NOUN
easat-1848	144	15	and	and	CCONJ
easat-1848	144	16	random	random	ADJ
easat-1848	144	17	forest	forest	NOUN
easat-1848	144	18	in	in	ADP
easat-1848	144	19	order	order	NOUN
easat-1848	144	20	to	to	PART
easat-1848	144	21	determine	determine	VERB
easat-1848	144	22	prediction	prediction	NOUN
easat-1848	144	23	accuracy	accuracy	NOUN
easat-1848	144	24	.	.	PUNCT
easat-1848	145	1	accuracy	accuracy	NOUN
easat-1848	145	2	of	of	ADP
easat-1848	145	3	prediction	prediction	NOUN
easat-1848	145	4	models	model	NOUN
easat-1848	145	5	was	be	AUX
easat-1848	145	6	improved	improve	VERB
easat-1848	145	7	by	by	ADP
easat-1848	145	8	handling	handle	VERB
easat-1848	145	9	null	null	ADJ
easat-1848	145	10	values	value	NOUN
easat-1848	145	11	on	on	ADP
easat-1848	145	12	specific	specific	ADJ
easat-1848	145	13	column	column	NOUN
easat-1848	145	14	and	and	CCONJ
easat-1848	145	15	imputing	impute	VERB
easat-1848	145	16	mean	mean	NOUN
easat-1848	145	17	values	value	NOUN
easat-1848	145	18	for	for	ADP
easat-1848	145	19	that	that	DET
easat-1848	145	20	column	column	NOUN
easat-1848	145	21	with	with	ADP
easat-1848	145	22	information	information	NOUN
easat-1848	145	23	1459	1459	NUM
easat-1848	145	24	edelweiss	edelweiss	PROPN
easat-1848	145	25	applied	apply	VERB
easat-1848	145	26	science	science	NOUN
easat-1848	145	27	and	and	CCONJ
easat-1848	145	28	technology	technology	NOUN
easat-1848	145	29	issn	issn	PROPN
easat-1848	145	30	:	:	PUNCT
easat-1848	145	31	2576	2576	NUM
easat-1848	145	32	-	-	SYM
easat-1848	145	33	8484	8484	NUM
easat-1848	145	34	vol	vol	NOUN
easat-1848	145	35	.	.	PROPN
easat-1848	146	1	8	8	NUM
easat-1848	146	2	,	,	PUNCT
easat-1848	146	3	no	no	INTJ
easat-1848	146	4	.	.	NOUN
easat-1848	146	5	5	5	NUM
easat-1848	146	6	:	:	SYM
easat-1848	146	7	1445	1445	NUM
easat-1848	146	8	-	-	SYM
easat-1848	146	9	1471	1471	NUM
easat-1848	146	10	,	,	PUNCT
easat-1848	146	11	2024	2024	NUM
easat-1848	146	12	doi	doi	NOUN
easat-1848	146	13	:	:	PUNCT
easat-1848	146	14	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	146	15	©	©	PROPN
easat-1848	146	16	2024	2024	NUM
easat-1848	146	17	by	by	ADP
easat-1848	146	18	the	the	DET
easat-1848	146	19	authors	author	NOUN
easat-1848	146	20	;	;	PUNCT
easat-1848	146	21	licensee	licensee	PROPN
easat-1848	146	22	learning	learning	NOUN
easat-1848	146	23	gate	gate	NOUN
easat-1848	146	24	gain	gain	VERB
easat-1848	146	25	feature	feature	NOUN
easat-1848	146	26	selection	selection	NOUN
easat-1848	146	27	method	method	NOUN
easat-1848	146	28	.	.	PUNCT
easat-1848	147	1	exploratory	exploratory	ADJ
easat-1848	147	2	data	datum	NOUN
easat-1848	147	3	analysis	analysis	NOUN
easat-1848	147	4	was	be	AUX
easat-1848	147	5	conducted	conduct	VERB
easat-1848	147	6	on	on	ADP
easat-1848	147	7	heart	heart	NOUN
easat-1848	147	8	dataset	dataset	VERB
easat-1848	147	9	by	by	ADP
easat-1848	147	10	authors	author	NOUN
easat-1848	147	11	[	[	X
easat-1848	147	12	35	35	NUM
easat-1848	147	13	]	]	PUNCT
easat-1848	147	14	.	.	PUNCT
easat-1848	148	1	utilising	utilise	VERB
easat-1848	148	2	the	the	DET
easat-1848	148	3	python	python	NOUN
easat-1848	148	4	seaborn	seaborn	NOUN
easat-1848	148	5	modules	module	NOUN
easat-1848	148	6	and	and	CCONJ
easat-1848	148	7	spyder	spyder	NOUN
easat-1848	148	8	ide	ide	NOUN
easat-1848	148	9	,	,	PUNCT
easat-1848	148	10	exploratory	exploratory	ADJ
easat-1848	148	11	data	datum	NOUN
easat-1848	148	12	analysis	analysis	NOUN
easat-1848	148	13	had	have	AUX
easat-1848	148	14	been	be	AUX
easat-1848	148	15	done	do	VERB
easat-1848	148	16	.	.	PUNCT
easat-1848	149	1	distribution	distribution	NOUN
easat-1848	149	2	plots	plot	NOUN
easat-1848	149	3	,	,	PUNCT
easat-1848	149	4	matrix	matrix	NOUN
easat-1848	149	5	plots	plot	NOUN
easat-1848	149	6	,	,	PUNCT
easat-1848	149	7	categorical	categorical	ADJ
easat-1848	149	8	plots	plot	NOUN
easat-1848	149	9	,	,	PUNCT
easat-1848	149	10	regression	regression	NOUN
easat-1848	149	11	plots	plot	NOUN
easat-1848	149	12	,	,	PUNCT
easat-1848	149	13	grid	grid	NOUN
easat-1848	149	14	plots	plot	NOUN
easat-1848	149	15	and	and	CCONJ
easat-1848	149	16	advanced	advanced	ADJ
easat-1848	149	17	plots	plot	NOUN
easat-1848	149	18	have	have	AUX
easat-1848	149	19	been	be	AUX
easat-1848	149	20	created	create	VERB
easat-1848	149	21	for	for	ADP
easat-1848	149	22	heart	heart	NOUN
easat-1848	149	23	dataset	dataset	NOUN
easat-1848	149	24	.	.	PUNCT
easat-1848	150	1	the	the	DET
easat-1848	150	2	variables	variables	PROPN
easat-1848	150	3	prevalenthyp	prevalenthyp	PROPN
easat-1848	150	4	,	,	PUNCT
easat-1848	150	5	sysbp	sysbp	NOUN
easat-1848	150	6	,	,	PUNCT
easat-1848	150	7	diabp	diabp	NOUN
easat-1848	150	8	,	,	PUNCT
easat-1848	150	9	heartrate	heartrate	NOUN
easat-1848	150	10	,	,	PUNCT
easat-1848	150	11	totchol	totchol	NOUN
easat-1848	150	12	,	,	PUNCT
easat-1848	150	13	and	and	CCONJ
easat-1848	150	14	glucose	glucose	NOUN
easat-1848	150	15	were	be	AUX
easat-1848	150	16	chosen	choose	VERB
easat-1848	150	17	as	as	ADP
easat-1848	150	18	essential	essential	ADJ
easat-1848	150	19	subcategory	subcategory	NOUN
easat-1848	150	20	of	of	ADP
easat-1848	150	21	variables	variable	NOUN
easat-1848	150	22	from	from	ADP
easat-1848	150	23	dataset	dataset	PROPN
easat-1848	150	24	's	's	PART
easat-1848	150	25	16	16	NUM
easat-1848	150	26	variables	variable	NOUN
easat-1848	150	27	to	to	PART
easat-1848	150	28	predict	predict	VERB
easat-1848	150	29	progress	progress	NOUN
easat-1848	150	30	of	of	ADP
easat-1848	150	31	heart	heart	NOUN
easat-1848	150	32	disease	disease	NOUN
easat-1848	150	33	in	in	ADP
easat-1848	150	34	individuals	individual	NOUN
easat-1848	150	35	in	in	ADP
easat-1848	150	36	different	different	ADJ
easat-1848	150	37	age	age	NOUN
easat-1848	150	38	groups	group	NOUN
easat-1848	150	39	.	.	PUNCT
easat-1848	151	1	3	3	X
easat-1848	151	2	.	.	X
easat-1848	151	3	methodology	methodology	NOUN
easat-1848	151	4	the	the	DET
easat-1848	151	5	suggested	suggest	VERB
easat-1848	151	6	method	method	NOUN
easat-1848	151	7	began	begin	VERB
easat-1848	151	8	with	with	ADP
easat-1848	151	9	the	the	DET
easat-1848	151	10	collection	collection	NOUN
easat-1848	151	11	of	of	ADP
easat-1848	151	12	five	five	NUM
easat-1848	151	13	open	open	ADJ
easat-1848	151	14	-	-	PUNCT
easat-1848	151	15	source	source	NOUN
easat-1848	151	16	heart	heart	NOUN
easat-1848	151	17	datasets	dataset	NOUN
easat-1848	151	18	cleveland	cleveland	PROPN
easat-1848	151	19	,	,	PUNCT
easat-1848	151	20	statlog	statlog	NOUN
easat-1848	151	21	,	,	PUNCT
easat-1848	151	22	hungarian	hungarian	PROPN
easat-1848	151	23	,	,	PUNCT
easat-1848	151	24	switzerland	switzerland	PROPN
easat-1848	151	25	and	and	CCONJ
easat-1848	151	26	long	long	ADJ
easat-1848	151	27	beach	beach	NOUN
easat-1848	151	28	.	.	PUNCT
easat-1848	152	1	as	as	SCONJ
easat-1848	152	2	standard	standard	ADJ
easat-1848	152	3	bench	bench	NOUN
easat-1848	152	4	mark	mark	NOUN
easat-1848	152	5	datasets	dataset	NOUN
easat-1848	152	6	were	be	AUX
easat-1848	152	7	combined	combine	VERB
easat-1848	152	8	and	and	CCONJ
easat-1848	152	9	used	use	VERB
easat-1848	152	10	,	,	PUNCT
easat-1848	152	11	no	no	DET
easat-1848	152	12	pre	pre	ADJ
easat-1848	152	13	-	-	ADJ
easat-1848	152	14	processing	processing	NOUN
easat-1848	152	15	was	be	AUX
easat-1848	152	16	required	require	VERB
easat-1848	152	17	.	.	PUNCT
easat-1848	153	1	following	follow	VERB
easat-1848	153	2	the	the	DET
easat-1848	153	3	data	datum	NOUN
easat-1848	153	4	collection	collection	NOUN
easat-1848	153	5	,	,	PUNCT
easat-1848	153	6	five	five	NUM
easat-1848	153	7	feature	feature	NOUN
easat-1848	153	8	selection	selection	NOUN
easat-1848	153	9	strategies	strategy	NOUN
easat-1848	153	10	such	such	ADJ
easat-1848	153	11	as	as	ADP
easat-1848	153	12	lasso	lasso	NOUN
easat-1848	153	13	,	,	PUNCT
easat-1848	153	14	relief	relief	NOUN
easat-1848	153	15	,	,	PUNCT
easat-1848	153	16	mr	mr	PROPN
easat-1848	153	17	-	-	PUNCT
easat-1848	153	18	mr	mr	PROPN
easat-1848	153	19	,	,	PUNCT
easat-1848	153	20	rfe	rfe	PROPN
easat-1848	153	21	,	,	PUNCT
easat-1848	153	22	pca	pca	PROPN
easat-1848	153	23	were	be	AUX
easat-1848	153	24	used	use	VERB
easat-1848	153	25	.	.	PUNCT
easat-1848	154	1	the	the	DET
easat-1848	154	2	optimal	optimal	ADJ
easat-1848	154	3	subset	subset	NOUN
easat-1848	154	4	was	be	AUX
easat-1848	154	5	then	then	ADV
easat-1848	154	6	chosen	choose	VERB
easat-1848	154	7	,	,	PUNCT
easat-1848	154	8	and	and	CCONJ
easat-1848	154	9	six	six	NUM
easat-1848	154	10	machine	machine	NOUN
easat-1848	154	11	-	-	PUNCT
easat-1848	154	12	learning	learn	VERB
easat-1848	154	13	strategies	strategy	NOUN
easat-1848	154	14	were	be	AUX
easat-1848	154	15	used	use	VERB
easat-1848	154	16	.	.	PUNCT
easat-1848	155	1	the	the	DET
easat-1848	155	2	data	datum	NOUN
easat-1848	155	3	is	be	AUX
easat-1848	155	4	subjected	subject	VERB
easat-1848	155	5	to	to	ADP
easat-1848	155	6	following	follow	VERB
easat-1848	155	7	machine	machine	NOUN
easat-1848	155	8	learning	learning	NOUN
easat-1848	155	9	algorithms	algorithm	NOUN
easat-1848	155	10	:	:	PUNCT
easat-1848	155	11	random	random	ADJ
easat-1848	155	12	forest	forest	NOUN
easat-1848	155	13	,	,	PUNCT
easat-1848	155	14	k	k	X
easat-1848	155	15	-	-	PUNCT
easat-1848	155	16	nearest	near	ADJ
easat-1848	155	17	neighbour	neighbour	NOUN
easat-1848	155	18	,	,	PUNCT
easat-1848	155	19	neural	neural	ADJ
easat-1848	155	20	network	network	NOUN
easat-1848	155	21	,	,	PUNCT
easat-1848	155	22	support	support	NOUN
easat-1848	155	23	vector	vector	NOUN
easat-1848	155	24	machine	machine	NOUN
easat-1848	155	25	,	,	PUNCT
easat-1848	155	26	naïve	naïve	ADJ
easat-1848	155	27	bayes	baye	NOUN
easat-1848	155	28	and	and	CCONJ
easat-1848	155	29	logistic	logistic	ADJ
easat-1848	155	30	regression	regression	NOUN
easat-1848	155	31	.	.	PUNCT
easat-1848	156	1	the	the	DET
easat-1848	156	2	performance	performance	NOUN
easat-1848	156	3	of	of	ADP
easat-1848	156	4	algorithm	algorithm	NOUN
easat-1848	156	5	and	and	CCONJ
easat-1848	156	6	feature	feature	NOUN
easat-1848	156	7	selection	selection	NOUN
easat-1848	156	8	was	be	AUX
easat-1848	156	9	then	then	ADV
easat-1848	156	10	assessed	assess	VERB
easat-1848	156	11	using	use	VERB
easat-1848	156	12	a	a	DET
easat-1848	156	13	variety	variety	NOUN
easat-1848	156	14	of	of	ADP
easat-1848	156	15	evaluation	evaluation	NOUN
easat-1848	156	16	criteria	criterion	NOUN
easat-1848	156	17	.	.	PUNCT
easat-1848	157	1	information	information	NOUN
easat-1848	157	2	of	of	ADP
easat-1848	157	3	1190	1190	NUM
easat-1848	157	4	cardiac	cardiac	ADJ
easat-1848	157	5	patients	patient	NOUN
easat-1848	157	6	is	be	AUX
easat-1848	157	7	included	include	VERB
easat-1848	157	8	in	in	ADP
easat-1848	157	9	the	the	DET
easat-1848	157	10	combined	combined	ADJ
easat-1848	157	11	heart	heart	NOUN
easat-1848	157	12	disease	disease	NOUN
easat-1848	157	13	dataset	dataset	VERB
easat-1848	157	14	.	.	PUNCT
easat-1848	158	1	heart	heart	NOUN
easat-1848	158	2	disease	disease	NOUN
easat-1848	158	3	was	be	AUX
easat-1848	158	4	classified	classify	VERB
easat-1848	158	5	as	as	ADP
easat-1848	158	6	stage	stage	NOUN
easat-1848	158	7	1	1	NUM
easat-1848	158	8	,	,	PUNCT
easat-1848	158	9	2	2	NUM
easat-1848	158	10	,	,	PUNCT
easat-1848	158	11	3	3	NUM
easat-1848	158	12	,	,	PUNCT
easat-1848	158	13	4	4	NUM
easat-1848	158	14	,	,	PUNCT
easat-1848	158	15	or	or	CCONJ
easat-1848	158	16	no	no	DET
easat-1848	158	17	heart	heart	NOUN
easat-1848	158	18	disease	disease	NOUN
easat-1848	158	19	at	at	ADP
easat-1848	158	20	the	the	DET
easat-1848	158	21	time	time	NOUN
easat-1848	158	22	of	of	ADP
easat-1848	158	23	diagnosis	diagnosis	NOUN
easat-1848	158	24	for	for	ADP
easat-1848	158	25	each	each	DET
easat-1848	158	26	patient	patient	NOUN
easat-1848	158	27	.	.	PUNCT
easat-1848	159	1	the	the	DET
easat-1848	159	2	dataset	dataset	NOUN
easat-1848	159	3	contains	contain	VERB
easat-1848	159	4	1190	1190	NUM
easat-1848	159	5	data	datum	NOUN
easat-1848	159	6	records	record	NOUN
easat-1848	159	7	.	.	PUNCT
easat-1848	160	1	following	follow	VERB
easat-1848	160	2	are	be	AUX
easat-1848	160	3	the	the	DET
easat-1848	160	4	dataset	dataset	NOUN
easat-1848	160	5	's	's	PART
easat-1848	160	6	features	feature	NOUN
easat-1848	160	7	:	:	PUNCT
easat-1848	160	8	exercise	exercise	NOUN
easat-1848	160	9	angina	angina	NOUN
easat-1848	160	10	,	,	PUNCT
easat-1848	160	11	sex	sex	NOUN
easat-1848	160	12	,	,	PUNCT
easat-1848	160	13	fasting	fast	VERB
easat-1848	160	14	blood	blood	NOUN
easat-1848	160	15	sugar	sugar	NOUN
easat-1848	160	16	,	,	PUNCT
easat-1848	160	17	resting	rest	VERB
easat-1848	160	18	ecg	ecg	PROPN
easat-1848	160	19	resting	rest	VERB
easat-1848	160	20	bps	bps	PROPN
easat-1848	160	21	,	,	PUNCT
easat-1848	160	22	chest	chest	NOUN
easat-1848	160	23	pain	pain	NOUN
easat-1848	160	24	type	type	NOUN
easat-1848	160	25	,	,	PUNCT
easat-1848	160	26	max	max	PROPN
easat-1848	160	27	heart	heart	NOUN
easat-1848	160	28	rate	rate	NOUN
easat-1848	160	29	,	,	PUNCT
easat-1848	160	30	age	age	NOUN
easat-1848	160	31	,	,	PUNCT
easat-1848	160	32	cholesterol	cholesterol	NOUN
easat-1848	160	33	,	,	PUNCT
easat-1848	160	34	target	target	NOUN
easat-1848	160	35	,	,	PUNCT
easat-1848	160	36	st	st	PROPN
easat-1848	160	37	slope	slope	PROPN
easat-1848	160	38	,	,	PUNCT
easat-1848	160	39	oldpeak	oldpeak	PROPN
easat-1848	160	40	.	.	PUNCT
easat-1848	161	1	figure	figure	NOUN
easat-1848	161	2	2	2	NUM
easat-1848	161	3	.	.	PUNCT
easat-1848	162	1	different	different	ADJ
easat-1848	162	2	feature	feature	NOUN
easat-1848	162	3	selection	selection	NOUN
easat-1848	162	4	methods	method	NOUN
easat-1848	162	5	.	.	PUNCT
easat-1848	163	1	3.1	3.1	NUM
easat-1848	163	2	.	.	PUNCT
easat-1848	163	3	feature	feature	NOUN
easat-1848	163	4	selection	selection	NOUN
easat-1848	163	5	methods	method	NOUN
easat-1848	163	6	feature	feature	VERB
easat-1848	163	7	selection	selection	NOUN
easat-1848	163	8	[	[	X
easat-1848	163	9	36	36	NUM
easat-1848	163	10	]	]	PUNCT
easat-1848	163	11	means	mean	VERB
easat-1848	163	12	choosing	choose	VERB
easat-1848	163	13	subclass	subclass	NOUN
easat-1848	163	14	of	of	ADP
easat-1848	163	15	input	input	NOUN
easat-1848	163	16	features	feature	NOUN
easat-1848	163	17	from	from	ADP
easat-1848	163	18	data	datum	NOUN
easat-1848	163	19	to	to	PART
easat-1848	163	20	improve	improve	VERB
easat-1848	163	21	performance	performance	NOUN
easat-1848	163	22	of	of	ADP
easat-1848	163	23	prediction	prediction	NOUN
easat-1848	163	24	model	model	NOUN
easat-1848	163	25	and	and	CCONJ
easat-1848	163	26	minimize	minimize	VERB
easat-1848	163	27	noise	noise	NOUN
easat-1848	163	28	.	.	PUNCT
easat-1848	164	1	by	by	ADP
easat-1848	164	2	selecting	select	VERB
easat-1848	164	3	just	just	ADV
easat-1848	164	4	pertinent	pertinent	ADJ
easat-1848	164	5	data	datum	NOUN
easat-1848	164	6	and	and	CCONJ
easat-1848	164	7	eliminating	eliminate	VERB
easat-1848	164	8	noise	noise	NOUN
easat-1848	164	9	from	from	ADP
easat-1848	164	10	the	the	DET
easat-1848	164	11	data	datum	NOUN
easat-1848	164	12	,	,	PUNCT
easat-1848	164	13	it	it	PRON
easat-1848	164	14	is	be	AUX
easat-1848	164	15	a	a	DET
easat-1848	164	16	technique	technique	NOUN
easat-1848	164	17	for	for	ADP
easat-1848	164	18	lowering	lower	VERB
easat-1848	164	19	the	the	DET
easat-1848	164	20	input	input	NOUN
easat-1848	164	21	variable	variable	NOUN
easat-1848	164	22	of	of	ADP
easat-1848	164	23	your	your	PRON
easat-1848	164	24	model	model	NOUN
easat-1848	164	25	.	.	PUNCT
easat-1848	165	1	the	the	DET
easat-1848	165	2	objective	objective	NOUN
easat-1848	165	3	is	be	AUX
easat-1848	165	4	to	to	PART
easat-1848	165	5	optimize	optimize	VERB
easat-1848	165	6	model	model	NOUN
easat-1848	165	7	's	's	PART
easat-1848	165	8	performance	performance	NOUN
easat-1848	165	9	with	with	ADP
easat-1848	165	10	least	least	ADJ
easat-1848	165	11	amount	amount	NOUN
easat-1848	165	12	of	of	ADP
easat-1848	165	13	data	datum	NOUN
easat-1848	165	14	while	while	SCONJ
easat-1848	165	15	streamlining	streamline	VERB
easat-1848	165	16	and	and	CCONJ
easat-1848	165	17	clarifying	clarify	VERB
easat-1848	165	18	the	the	DET
easat-1848	165	19	model	model	NOUN
easat-1848	165	20	.	.	PUNCT
easat-1848	166	1	the	the	DET
easat-1848	166	2	process	process	NOUN
easat-1848	166	3	of	of	ADP
easat-1848	166	4	automatically	automatically	ADV
easat-1848	166	5	selecting	select	VERB
easat-1848	166	6	pertinent	pertinent	ADJ
easat-1848	166	7	characteristics	characteristic	NOUN
easat-1848	166	8	according	accord	VERB
easat-1848	166	9	to	to	ADP
easat-1848	166	10	the	the	DET
easat-1848	166	11	kind	kind	NOUN
easat-1848	166	12	of	of	ADP
easat-1848	166	13	problem	problem	NOUN
easat-1848	166	14	being	be	AUX
easat-1848	166	15	solved	solve	VERB
easat-1848	166	16	is	be	AUX
easat-1848	166	17	known	know	VERB
easat-1848	166	18	as	as	ADP
easat-1848	166	19	feature	feature	NOUN
easat-1848	166	20	selection	selection	NOUN
easat-1848	166	21	.	.	PUNCT
easat-1848	167	1	to	to	PART
easat-1848	167	2	achieve	achieve	VERB
easat-1848	167	3	this	this	PRON
easat-1848	167	4	,	,	PUNCT
easat-1848	167	5	choose	choose	VERB
easat-1848	167	6	which	which	DET
easat-1848	167	7	significant	significant	ADJ
easat-1848	167	8	characteristics	characteristic	NOUN
easat-1848	167	9	to	to	PART
easat-1848	167	10	include	include	VERB
easat-1848	167	11	or	or	CCONJ
easat-1848	167	12	remove	remove	VERB
easat-1848	167	13	without	without	ADP
easat-1848	167	14	altering	alter	VERB
easat-1848	167	15	them	they	PRON
easat-1848	167	16	.	.	PUNCT
easat-1848	168	1	reducing	reduce	VERB
easat-1848	168	2	the	the	DET
easat-1848	168	3	size	size	NOUN
easat-1848	168	4	of	of	ADP
easat-1848	168	5	the	the	DET
easat-1848	168	6	input	input	NOUN
easat-1848	168	7	dataset	dataset	VERB
easat-1848	168	8	and	and	CCONJ
easat-1848	168	9	removing	remove	VERB
easat-1848	168	10	unnecessary	unnecessary	ADJ
easat-1848	168	11	noise	noise	NOUN
easat-1848	168	12	from	from	ADP
easat-1848	168	13	the	the	DET
easat-1848	168	14	data	datum	NOUN
easat-1848	168	15	are	be	AUX
easat-1848	168	16	two	two	NUM
easat-1848	168	17	benefits	benefit	NOUN
easat-1848	168	18	of	of	ADP
easat-1848	168	19	the	the	DET
easat-1848	168	20	technique	technique	NOUN
easat-1848	168	21	.	.	PUNCT
easat-1848	169	1	the	the	DET
easat-1848	169	2	above	above	ADJ
easat-1848	169	3	fig	fig	NOUN
easat-1848	169	4	.	.	PUNCT
easat-1848	170	1	2	2	NUM
easat-1848	170	2	shows	show	VERB
easat-1848	170	3	different	different	ADJ
easat-1848	170	4	feature	feature	NOUN
easat-1848	170	5	selection	selection	NOUN
easat-1848	170	6	techniques	technique	NOUN
easat-1848	170	7	employed	employ	VERB
easat-1848	170	8	in	in	ADP
easat-1848	170	9	this	this	DET
easat-1848	170	10	work	work	NOUN
easat-1848	170	11	and	and	CCONJ
easat-1848	170	12	they	they	PRON
easat-1848	170	13	are	be	AUX
easat-1848	170	14	described	describe	VERB
easat-1848	170	15	below	below	ADV
easat-1848	170	16	.	.	PUNCT
easat-1848	171	1	3.1.1	3.1.1	X
easat-1848	171	2	.	.	PUNCT
easat-1848	172	1	least	least	ADJ
easat-1848	172	2	absolute	absolute	ADJ
easat-1848	172	3	shrinkage	shrinkage	NOUN
easat-1848	172	4	and	and	CCONJ
easat-1848	172	5	selection	selection	NOUN
easat-1848	172	6	operator	operator	NOUN
easat-1848	172	7	(	(	PUNCT
easat-1848	172	8	lasso	lasso	PROPN
easat-1848	172	9	)	)	PUNCT
easat-1848	172	10	least	least	ADJ
easat-1848	172	11	absolute	absolute	ADJ
easat-1848	172	12	shrinkage	shrinkage	NOUN
easat-1848	172	13	and	and	CCONJ
easat-1848	172	14	selection	selection	NOUN
easat-1848	172	15	operator	operator	NOUN
easat-1848	172	16	is	be	AUX
easat-1848	172	17	a	a	DET
easat-1848	172	18	statistical	statistical	ADJ
easat-1848	172	19	technique	technique	NOUN
easat-1848	172	20	used	use	VERB
easat-1848	172	21	in	in	ADP
easat-1848	172	22	statistics	statistic	NOUN
easat-1848	172	23	and	and	CCONJ
easat-1848	172	24	machine	machine	NOUN
easat-1848	172	25	learning	learn	VERB
easat-1848	172	26	[	[	X
easat-1848	172	27	37	37	NUM
easat-1848	172	28	]	]	PUNCT
easat-1848	172	29	.	.	PUNCT
easat-1848	173	1	this	this	DET
easat-1848	173	2	particular	particular	ADJ
easat-1848	173	3	kind	kind	NOUN
easat-1848	173	4	of	of	ADP
easat-1848	173	5	regression	regression	NOUN
easat-1848	173	6	analysis	analysis	NOUN
easat-1848	173	7	carries	carry	VERB
easat-1848	173	8	out	out	ADP
easat-1848	173	9	two	two	NUM
easat-1848	173	10	crucial	crucial	ADJ
easat-1848	173	11	tasks	task	NOUN
easat-1848	173	12	:	:	PUNCT
easat-1848	173	13	variable	variable	ADJ
easat-1848	173	14	selection	selection	NOUN
easat-1848	173	15	is	be	AUX
easat-1848	173	16	the	the	DET
easat-1848	173	17	process	process	NOUN
easat-1848	173	18	of	of	ADP
easat-1848	173	19	determining	determine	VERB
easat-1848	173	20	which	which	DET
easat-1848	173	21	characteristics	characteristic	NOUN
easat-1848	173	22	or	or	CCONJ
easat-1848	173	23	factors	factor	NOUN
easat-1848	173	24	are	be	AUX
easat-1848	173	25	most	most	ADV
easat-1848	173	26	crucial	crucial	ADJ
easat-1848	173	27	for	for	ADP
easat-1848	173	28	predicting	predict	VERB
easat-1848	173	29	an	an	DET
easat-1848	173	30	outcome	outcome	NOUN
easat-1848	173	31	variable	variable	NOUN
easat-1848	173	32	.	.	PUNCT
easat-1848	174	1	regularization	regularization	NOUN
easat-1848	174	2	:	:	PUNCT
easat-1848	174	3	it	it	PRON
easat-1848	174	4	lowers	lower	VERB
easat-1848	174	5	the	the	DET
easat-1848	174	6	model	model	NOUN
easat-1848	174	7	's	's	PART
easat-1848	174	8	variance	variance	NOUN
easat-1848	174	9	,	,	PUNCT
easat-1848	174	10	which	which	PRON
easat-1848	174	11	lessens	lessen	VERB
easat-1848	174	12	the	the	DET
easat-1848	174	13	likelihood	likelihood	NOUN
easat-1848	174	14	of	of	ADP
easat-1848	174	15	overfitting	overfitte	VERB
easat-1848	174	16	and	and	CCONJ
easat-1848	174	17	enhances	enhance	VERB
easat-1848	174	18	the	the	DET
easat-1848	174	19	model	model	NOUN
easat-1848	174	20	's	's	PART
easat-1848	174	21	applicability	applicability	NOUN
easat-1848	174	22	to	to	ADP
easat-1848	174	23	hypothetical	hypothetical	ADJ
easat-1848	174	24	data	datum	NOUN
easat-1848	174	25	.	.	PUNCT
easat-1848	175	1	lasso	lasso	NOUN
easat-1848	175	2	augments	augment	VERB
easat-1848	175	3	the	the	DET
easat-1848	175	4	conventional	conventional	ADJ
easat-1848	175	5	least	least	ADJ
easat-1848	175	6	squares	square	NOUN
easat-1848	175	7	objective	objective	ADJ
easat-1848	175	8	function	function	NOUN
easat-1848	175	9	with	with	ADP
easat-1848	175	10	a	a	DET
easat-1848	175	11	penalty	penalty	NOUN
easat-1848	175	12	term	term	NOUN
easat-1848	175	13	to	to	PART
easat-1848	175	14	accomplish	accomplish	VERB
easat-1848	175	15	these	these	DET
easat-1848	175	16	ends	end	NOUN
easat-1848	175	17	.	.	PUNCT
easat-1848	176	1	the	the	DET
easat-1848	176	2	absolute	absolute	ADJ
easat-1848	176	3	value	value	NOUN
easat-1848	176	4	of	of	ADP
easat-1848	176	5	the	the	DET
easat-1848	176	6	regression	regression	NOUN
easat-1848	176	7	coefficients	coefficient	NOUN
easat-1848	176	8	serves	serve	VERB
easat-1848	176	9	as	as	ADP
easat-1848	176	10	the	the	DET
easat-1848	176	11	basis	basis	NOUN
easat-1848	176	12	for	for	ADP
easat-1848	176	13	this	this	DET
easat-1848	176	14	penalty	penalty	NOUN
easat-1848	176	15	term	term	NOUN
easat-1848	176	16	.	.	PUNCT
easat-1848	177	1	certain	certain	ADJ
easat-1848	177	2	coefficients	coefficient	NOUN
easat-1848	177	3	can	can	AUX
easat-1848	177	4	be	be	AUX
easat-1848	177	5	1460	1460	NUM
easat-1848	177	6	edelweiss	edelweiss	PROPN
easat-1848	177	7	applied	apply	VERB
easat-1848	177	8	science	science	NOUN
easat-1848	177	9	and	and	CCONJ
easat-1848	177	10	technology	technology	NOUN
easat-1848	177	11	issn	issn	PROPN
easat-1848	177	12	:	:	PUNCT
easat-1848	177	13	2576	2576	NUM
easat-1848	177	14	-	-	SYM
easat-1848	177	15	8484	8484	NUM
easat-1848	177	16	vol	vol	NOUN
easat-1848	177	17	.	.	PROPN
easat-1848	177	18	8	8	NUM
easat-1848	177	19	,	,	PUNCT
easat-1848	177	20	no	no	INTJ
easat-1848	177	21	.	.	NOUN
easat-1848	178	1	5	5	NUM
easat-1848	178	2	:	:	SYM
easat-1848	178	3	1445	1445	NUM
easat-1848	178	4	-	-	SYM
easat-1848	178	5	1471	1471	NUM
easat-1848	178	6	,	,	PUNCT
easat-1848	178	7	2024	2024	NUM
easat-1848	178	8	doi	doi	NOUN
easat-1848	178	9	:	:	PUNCT
easat-1848	178	10	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	178	11	©	©	PROPN
easat-1848	178	12	2024	2024	NUM
easat-1848	178	13	by	by	ADP
easat-1848	178	14	the	the	DET
easat-1848	178	15	authors	author	NOUN
easat-1848	178	16	;	;	PUNCT
easat-1848	178	17	licensee	licensee	PROPN
easat-1848	178	18	learning	learn	VERB
easat-1848	178	19	gate	gate	NOUN
easat-1848	178	20	efficiently	efficiently	ADV
easat-1848	178	21	set	set	VERB
easat-1848	178	22	to	to	ADP
easat-1848	178	23	exactly	exactly	ADV
easat-1848	178	24	zero	zero	NUM
easat-1848	178	25	via	via	ADP
easat-1848	178	26	lasso	lasso	NOUN
easat-1848	178	27	by	by	ADP
easat-1848	178	28	reducing	reduce	VERB
easat-1848	178	29	the	the	DET
easat-1848	178	30	coefficients	coefficient	NOUN
easat-1848	178	31	towards	towards	ADP
easat-1848	178	32	zero	zero	NUM
easat-1848	178	33	.	.	PUNCT
easat-1848	179	1	this	this	PRON
easat-1848	179	2	leads	lead	VERB
easat-1848	179	3	to	to	ADP
easat-1848	179	4	variable	variable	ADJ
easat-1848	179	5	selection	selection	NOUN
easat-1848	179	6	since	since	SCONJ
easat-1848	179	7	the	the	DET
easat-1848	179	8	matching	matching	NOUN
easat-1848	179	9	variables	variable	NOUN
easat-1848	179	10	are	be	AUX
easat-1848	179	11	eliminated	eliminate	VERB
easat-1848	179	12	from	from	ADP
easat-1848	179	13	the	the	DET
easat-1848	179	14	model	model	NOUN
easat-1848	179	15	.	.	PUNCT
easat-1848	180	1	an	an	DET
easat-1848	180	2	additional	additional	ADJ
easat-1848	180	3	penalty	penalty	NOUN
easat-1848	180	4	term	term	NOUN
easat-1848	180	5	has	have	AUX
easat-1848	180	6	been	be	AUX
easat-1848	180	7	added	add	VERB
easat-1848	180	8	to	to	ADP
easat-1848	180	9	objective	objective	ADJ
easat-1848	180	10	function	function	NOUN
easat-1848	180	11	by	by	ADP
easat-1848	180	12	lasso	lasso	NOUN
easat-1848	180	13	.	.	PUNCT
easat-1848	181	1	the	the	DET
easat-1848	181	2	absolute	absolute	ADJ
easat-1848	181	3	value	value	NOUN
easat-1848	181	4	of	of	ADP
easat-1848	181	5	the	the	DET
easat-1848	181	6	coefficients	coefficient	NOUN
easat-1848	181	7	serves	serve	VERB
easat-1848	181	8	as	as	ADP
easat-1848	181	9	the	the	DET
easat-1848	181	10	foundation	foundation	NOUN
easat-1848	181	11	for	for	ADP
easat-1848	181	12	this	this	DET
easat-1848	181	13	penalty	penalty	NOUN
easat-1848	181	14	term	term	NOUN
easat-1848	181	15	.	.	PUNCT
easat-1848	182	1	a	a	DET
easat-1848	182	2	coefficient	coefficient	NOUN
easat-1848	182	3	's	's	PART
easat-1848	182	4	penalty	penalty	NOUN
easat-1848	182	5	increases	increase	VERB
easat-1848	182	6	with	with	ADP
easat-1848	182	7	its	its	PRON
easat-1848	182	8	absolute	absolute	ADJ
easat-1848	182	9	value	value	NOUN
easat-1848	182	10	.	.	PUNCT
easat-1848	183	1	lasso	lasso	NOUN
easat-1848	183	2	works	work	VERB
easat-1848	183	3	to	to	PART
easat-1848	183	4	reduce	reduce	VERB
easat-1848	183	5	the	the	DET
easat-1848	183	6	coefficients	coefficient	NOUN
easat-1848	183	7	to	to	ADP
easat-1848	183	8	zero	zero	NUM
easat-1848	183	9	by	by	ADP
easat-1848	183	10	minimizing	minimize	VERB
easat-1848	183	11	the	the	DET
easat-1848	183	12	combined	combine	VERB
easat-1848	183	13	objective	objective	ADJ
easat-1848	183	14	function	function	NOUN
easat-1848	183	15	,	,	PUNCT
easat-1848	183	16	which	which	PRON
easat-1848	183	17	considers	consider	VERB
easat-1848	183	18	both	both	CCONJ
easat-1848	183	19	the	the	DET
easat-1848	183	20	lasso	lasso	NOUN
easat-1848	183	21	penalty	penalty	NOUN
easat-1848	183	22	and	and	CCONJ
easat-1848	183	23	the	the	DET
easat-1848	183	24	squared	squared	ADJ
easat-1848	183	25	errors	error	NOUN
easat-1848	183	26	.	.	PUNCT
easat-1848	184	1	coefficients	coefficient	NOUN
easat-1848	184	2	may	may	AUX
easat-1848	184	3	occasionally	occasionally	ADV
easat-1848	184	4	be	be	AUX
easat-1848	184	5	driven	drive	VERB
easat-1848	184	6	all	all	DET
easat-1848	184	7	the	the	DET
easat-1848	184	8	way	way	NOUN
easat-1848	184	9	to	to	ADP
easat-1848	184	10	zero	zero	NUM
easat-1848	184	11	,	,	PUNCT
easat-1848	184	12	which	which	PRON
easat-1848	184	13	would	would	AUX
easat-1848	184	14	essentially	essentially	ADV
easat-1848	184	15	eliminate	eliminate	VERB
easat-1848	184	16	the	the	DET
easat-1848	184	17	associated	associated	ADJ
easat-1848	184	18	characteristics	characteristic	NOUN
easat-1848	184	19	from	from	ADP
easat-1848	184	20	the	the	DET
easat-1848	184	21	model	model	NOUN
easat-1848	184	22	.	.	PUNCT
easat-1848	185	1	better	well	ADJ
easat-1848	185	2	generalization	generalization	NOUN
easat-1848	185	3	performance	performance	NOUN
easat-1848	185	4	on	on	ADP
easat-1848	185	5	unobserved	unobserved	ADJ
easat-1848	185	6	data	datum	NOUN
easat-1848	185	7	results	result	NOUN
easat-1848	185	8	from	from	ADP
easat-1848	185	9	this	this	DET
easat-1848	185	10	shrinking	shrinking	NOUN
easat-1848	185	11	,	,	PUNCT
easat-1848	185	12	which	which	PRON
easat-1848	185	13	also	also	ADV
easat-1848	185	14	lowers	lower	VERB
easat-1848	185	15	the	the	DET
easat-1848	185	16	model	model	NOUN
easat-1848	185	17	's	's	PART
easat-1848	185	18	variance	variance	NOUN
easat-1848	185	19	.	.	PUNCT
easat-1848	186	1	furthermore	furthermore	ADV
easat-1848	186	2	,	,	PUNCT
easat-1848	186	3	lasso	lasso	NOUN
easat-1848	186	4	can	can	AUX
easat-1848	186	5	enhance	enhance	VERB
easat-1848	186	6	the	the	DET
easat-1848	186	7	model	model	NOUN
easat-1848	186	8	's	's	PART
easat-1848	186	9	interpretability	interpretability	NOUN
easat-1848	186	10	by	by	ADP
easat-1848	186	11	limiting	limit	VERB
easat-1848	186	12	the	the	DET
easat-1848	186	13	selection	selection	NOUN
easat-1848	186	14	to	to	ADP
easat-1848	186	15	the	the	DET
easat-1848	186	16	most	most	ADV
easat-1848	186	17	crucial	crucial	ADJ
easat-1848	186	18	elements	element	NOUN
easat-1848	186	19	.	.	PUNCT
easat-1848	187	1	the	the	DET
easat-1848	187	2	lasso	lasso	NOUN
easat-1848	187	3	optimization	optimization	NOUN
easat-1848	187	4	problem	problem	NOUN
easat-1848	187	5	can	can	AUX
easat-1848	187	6	be	be	AUX
easat-1848	187	7	expressed	express	VERB
easat-1848	187	8	as	as	ADP
easat-1848	187	9	min	min	NOUN
easat-1848	187	10	[	[	X
easat-1848	187	11	(	(	PUNCT
easat-1848	187	12	1	1	NUM
easat-1848	187	13	/	/	SYM
easat-1848	187	14	m	m	NOUN
easat-1848	187	15	)	)	PUNCT
easat-1848	187	16	*	*	PUNCT
easat-1848	188	1	σ(ci	σ(ci	PROPN
easat-1848	188	2	(	(	PUNCT
easat-1848	188	3	β₀	β₀	PROPN
easat-1848	188	4	+	+	X
easat-1848	188	5	σ(βk	σ(βk	X
easat-1848	188	6	*	*	PUNCT
easat-1848	188	7	ak)))2	ak)))2	NOUN
easat-1848	188	8	+	+	CCONJ
easat-1848	188	9	λ	λ	X
easat-1848	188	10	*	*	PUNCT
easat-1848	188	11	σ|βk|	σ|βk|	PROPN
easat-1848	188	12	]	]	X
easat-1848	189	1	[	[	X
easat-1848	189	2	1	1	X
easat-1848	189	3	]	]	PUNCT
easat-1848	189	4	where	where	SCONJ
easat-1848	189	5	m	m	NOUN
easat-1848	189	6	is	be	AUX
easat-1848	189	7	the	the	DET
easat-1848	189	8	count	count	NOUN
easat-1848	189	9	of	of	ADP
easat-1848	189	10	data	datum	NOUN
easat-1848	189	11	points	point	NOUN
easat-1848	189	12	,	,	PUNCT
easat-1848	189	13	ci	ci	PROPN
easat-1848	189	14	is	be	AUX
easat-1848	189	15	the	the	DET
easat-1848	189	16	real	real	ADJ
easat-1848	189	17	value	value	NOUN
easat-1848	189	18	of	of	ADP
easat-1848	189	19	i	i	PROPN
easat-1848	189	20	-	-	PUNCT
easat-1848	189	21	th	th	X
easat-1848	189	22	data	datum	NOUN
easat-1848	189	23	point	point	NOUN
easat-1848	189	24	for	for	ADP
easat-1848	189	25	target	target	NOUN
easat-1848	189	26	variable	variable	NOUN
easat-1848	189	27	,	,	PUNCT
easat-1848	189	28	β₀	β₀	PROPN
easat-1848	189	29	is	be	AUX
easat-1848	189	30	the	the	DET
easat-1848	189	31	intercept	intercept	NOUN
easat-1848	189	32	of	of	ADP
easat-1848	189	33	the	the	DET
easat-1848	189	34	model	model	NOUN
easat-1848	189	35	,	,	PUNCT
easat-1848	189	36	βk	βk	VERB
easat-1848	189	37	is	be	AUX
easat-1848	189	38	the	the	DET
easat-1848	189	39	coefficient	coefficient	NOUN
easat-1848	189	40	for	for	ADP
easat-1848	189	41	k	k	NOUN
easat-1848	189	42	-	-	PUNCT
easat-1848	189	43	th	th	VERB
easat-1848	189	44	feature	feature	NOUN
easat-1848	189	45	,	,	PUNCT
easat-1848	189	46	ak	ak	PROPN
easat-1848	189	47	is	be	AUX
easat-1848	189	48	the	the	DET
easat-1848	189	49	value	value	NOUN
easat-1848	189	50	of	of	ADP
easat-1848	189	51	k	k	NOUN
easat-1848	189	52	-	-	PUNCT
easat-1848	189	53	th	th	VERB
easat-1848	189	54	feature	feature	NOUN
easat-1848	189	55	for	for	ADP
easat-1848	189	56	i	i	PROPN
easat-1848	189	57	-	-	PUNCT
easat-1848	189	58	th	th	X
easat-1848	189	59	data	datum	NOUN
easat-1848	189	60	point	point	NOUN
easat-1848	189	61	,	,	PUNCT
easat-1848	189	62	σ	σ	PROPN
easat-1848	189	63	is	be	AUX
easat-1848	189	64	the	the	DET
easat-1848	189	65	summation	summation	NOUN
easat-1848	189	66	over	over	ADP
easat-1848	189	67	all	all	DET
easat-1848	189	68	features	feature	NOUN
easat-1848	189	69	(	(	PUNCT
easat-1848	189	70	k	k	NOUN
easat-1848	189	71	)	)	PUNCT
easat-1848	189	72	and	and	CCONJ
easat-1848	189	73	λ	λ	PROPN
easat-1848	189	74	is	be	AUX
easat-1848	189	75	the	the	DET
easat-1848	189	76	tuning	tuning	NOUN
easat-1848	189	77	parameter	parameter	NOUN
easat-1848	189	78	.	.	PUNCT
easat-1848	190	1	3.1.2	3.1.2	X
easat-1848	190	2	.	.	PUNCT
easat-1848	190	3	relief	relief	NOUN
easat-1848	190	4	relief	relief	NOUN
easat-1848	190	5	feature	feature	NOUN
easat-1848	190	6	selection	selection	NOUN
easat-1848	190	7	[	[	X
easat-1848	190	8	38	38	NUM
easat-1848	190	9	]	]	PUNCT
easat-1848	190	10	is	be	AUX
easat-1848	190	11	a	a	DET
easat-1848	190	12	filter	filter	NOUN
easat-1848	190	13	-	-	PUNCT
easat-1848	190	14	based	base	VERB
easat-1848	190	15	technique	technique	NOUN
easat-1848	190	16	that	that	PRON
easat-1848	190	17	extracts	extract	VERB
easat-1848	190	18	the	the	DET
easat-1848	190	19	most	most	ADV
easat-1848	190	20	appropriate	appropriate	ADJ
easat-1848	190	21	features	feature	NOUN
easat-1848	190	22	from	from	ADP
easat-1848	190	23	dataset	dataset	NOUN
easat-1848	190	24	.	.	PUNCT
easat-1848	191	1	it	it	PRON
easat-1848	191	2	concentrates	concentrate	VERB
easat-1848	191	3	on	on	ADP
easat-1848	191	4	choosing	choose	VERB
easat-1848	191	5	characteristics	characteristic	NOUN
easat-1848	191	6	that	that	PRON
easat-1848	191	7	are	be	AUX
easat-1848	191	8	most	most	ADV
easat-1848	191	9	important	important	ADJ
easat-1848	191	10	for	for	ADP
easat-1848	191	11	distinguishing	distinguish	VERB
easat-1848	191	12	between	between	ADP
easat-1848	191	13	examples	example	NOUN
easat-1848	191	14	that	that	PRON
easat-1848	191	15	belong	belong	VERB
easat-1848	191	16	to	to	ADP
easat-1848	191	17	various	various	ADJ
easat-1848	191	18	classes	class	NOUN
easat-1848	191	19	.	.	PUNCT
easat-1848	192	1	its	its	PRON
easat-1848	192	2	purpose	purpose	NOUN
easat-1848	192	3	is	be	AUX
easat-1848	192	4	to	to	PART
easat-1848	192	5	remove	remove	VERB
easat-1848	192	6	superfluous	superfluous	ADJ
easat-1848	192	7	or	or	CCONJ
easat-1848	192	8	unnecessary	unnecessary	ADJ
easat-1848	192	9	features	feature	NOUN
easat-1848	192	10	,	,	PUNCT
easat-1848	192	11	which	which	PRON
easat-1848	192	12	results	result	VERB
easat-1848	192	13	in	in	ADP
easat-1848	192	14	faster	fast	ADJ
easat-1848	192	15	training	training	NOUN
easat-1848	192	16	times	time	NOUN
easat-1848	192	17	because	because	SCONJ
easat-1848	192	18	fewer	few	ADJ
easat-1848	192	19	features	feature	NOUN
easat-1848	192	20	mean	mean	VERB
easat-1848	192	21	less	less	ADJ
easat-1848	192	22	computation	computation	NOUN
easat-1848	192	23	,	,	PUNCT
easat-1848	192	24	better	well	ADJ
easat-1848	192	25	interpretability	interpretability	NOUN
easat-1848	192	26	because	because	SCONJ
easat-1848	192	27	simpler	simple	ADJ
easat-1848	192	28	models	model	NOUN
easat-1848	192	29	are	be	AUX
easat-1848	192	30	easier	easy	ADJ
easat-1848	192	31	to	to	PART
easat-1848	192	32	understand	understand	VERB
easat-1848	192	33	,	,	PUNCT
easat-1848	192	34	and	and	CCONJ
easat-1848	192	35	improved	improved	ADJ
easat-1848	192	36	model	model	NOUN
easat-1848	192	37	performance	performance	NOUN
easat-1848	192	38	because	because	SCONJ
easat-1848	192	39	reduced	reduced	ADJ
easat-1848	192	40	complexity	complexity	NOUN
easat-1848	192	41	prevents	prevent	VERB
easat-1848	192	42	overfitting	overfitte	VERB
easat-1848	192	43	and	and	CCONJ
easat-1848	192	44	improves	improve	VERB
easat-1848	192	45	generalization	generalization	NOUN
easat-1848	192	46	.	.	PUNCT
easat-1848	193	1	relief	relief	NOUN
easat-1848	194	1	[	[	X
easat-1848	194	2	39	39	NUM
easat-1848	194	3	]	]	PUNCT
easat-1848	194	4	depends	depend	VERB
easat-1848	194	5	on	on	ADP
easat-1848	194	6	the	the	DET
easat-1848	194	7	idea	idea	NOUN
easat-1848	194	8	of	of	ADP
easat-1848	194	9	closest	close	ADJ
easat-1848	194	10	neighbours	neighbour	NOUN
easat-1848	194	11	.	.	PUNCT
easat-1848	195	1	it	it	PRON
easat-1848	195	2	determines	determine	VERB
easat-1848	195	3	the	the	DET
easat-1848	195	4	closest	close	ADJ
easat-1848	195	5	neighbours	neighbour	NOUN
easat-1848	195	6	from	from	ADP
easat-1848	195	7	several	several	ADJ
easat-1848	195	8	classes	class	NOUN
easat-1848	195	9	(	(	PUNCT
easat-1848	195	10	the	the	DET
easat-1848	195	11	most	most	ADV
easat-1848	195	12	comparable	comparable	ADJ
easat-1848	195	13	points	point	NOUN
easat-1848	195	14	falling	fall	VERB
easat-1848	195	15	into	into	ADP
easat-1848	195	16	various	various	ADJ
easat-1848	195	17	categories	category	NOUN
easat-1848	195	18	)	)	PUNCT
easat-1848	195	19	for	for	ADP
easat-1848	195	20	a	a	DET
easat-1848	195	21	given	give	VERB
easat-1848	195	22	data	data	NOUN
easat-1848	195	23	point	point	NOUN
easat-1848	195	24	.	.	PUNCT
easat-1848	196	1	each	each	DET
easat-1848	196	2	feature	feature	NOUN
easat-1848	196	3	is	be	AUX
easat-1848	196	4	examined	examine	VERB
easat-1848	196	5	,	,	PUNCT
easat-1848	196	6	and	and	CCONJ
easat-1848	196	7	the	the	DET
easat-1848	196	8	values	value	NOUN
easat-1848	196	9	of	of	ADP
easat-1848	196	10	the	the	DET
easat-1848	196	11	features	feature	NOUN
easat-1848	196	12	at	at	ADP
easat-1848	196	13	the	the	DET
easat-1848	196	14	original	original	ADJ
easat-1848	196	15	position	position	NOUN
easat-1848	196	16	and	and	CCONJ
easat-1848	196	17	their	their	PRON
easat-1848	196	18	closest	close	ADJ
easat-1848	196	19	neighbours	neighbour	NOUN
easat-1848	196	20	are	be	AUX
easat-1848	196	21	compared	compare	VERB
easat-1848	196	22	.	.	PUNCT
easat-1848	197	1	it	it	PRON
easat-1848	197	2	distinguishes	distinguish	VERB
easat-1848	197	3	between	between	ADP
easat-1848	197	4	two	two	NUM
easat-1848	197	5	situations	situation	NOUN
easat-1848	197	6	:	:	PUNCT
easat-1848	197	7	a	a	DET
easat-1848	197	8	"	"	PUNCT
easat-1848	197	9	hit	hit	NOUN
easat-1848	197	10	"	"	PUNCT
easat-1848	197	11	is	be	AUX
easat-1848	197	12	an	an	DET
easat-1848	197	13	unwanted	unwanted	ADJ
easat-1848	197	14	result	result	NOUN
easat-1848	197	15	that	that	PRON
easat-1848	197	16	occurs	occur	VERB
easat-1848	197	17	when	when	SCONJ
easat-1848	197	18	nearest	near	ADJ
easat-1848	197	19	neighbour	neighbour	NOUN
easat-1848	197	20	of	of	ADP
easat-1848	197	21	different	different	ADJ
easat-1848	197	22	class	class	NOUN
easat-1848	197	23	has	have	VERB
easat-1848	197	24	same	same	ADJ
easat-1848	197	25	feature	feature	NOUN
easat-1848	197	26	value	value	NOUN
easat-1848	197	27	.	.	PUNCT
easat-1848	198	1	miss	miss	VERB
easat-1848	198	2	:	:	PUNCT
easat-1848	199	1	a	a	DET
easat-1848	199	2	"	"	PUNCT
easat-1848	199	3	miss	miss	NOUN
easat-1848	199	4	"	"	PUNCT
easat-1848	199	5	(	(	PUNCT
easat-1848	199	6	desirable	desirable	ADJ
easat-1848	199	7	)	)	PUNCT
easat-1848	199	8	occurs	occur	VERB
easat-1848	199	9	when	when	SCONJ
easat-1848	199	10	the	the	DET
easat-1848	199	11	feature	feature	NOUN
easat-1848	199	12	value	value	NOUN
easat-1848	199	13	of	of	ADP
easat-1848	199	14	nearest	near	ADJ
easat-1848	199	15	neighbour	neighbour	NOUN
easat-1848	199	16	(	(	PUNCT
easat-1848	199	17	of	of	ADP
easat-1848	199	18	different	different	ADJ
easat-1848	199	19	class	class	NOUN
easat-1848	199	20	)	)	PUNCT
easat-1848	199	21	differs	differ	NOUN
easat-1848	199	22	.	.	PUNCT
easat-1848	200	1	relief	relief	NOUN
easat-1848	200	2	adjusts	adjust	VERB
easat-1848	200	3	a	a	DET
easat-1848	200	4	score	score	NOUN
easat-1848	200	5	according	accord	VERB
easat-1848	200	6	to	to	ADP
easat-1848	200	7	the	the	DET
easat-1848	200	8	quantity	quantity	NOUN
easat-1848	200	9	of	of	ADP
easat-1848	200	10	"	"	PUNCT
easat-1848	200	11	hits	hit	NOUN
easat-1848	200	12	"	"	PUNCT
easat-1848	200	13	and	and	CCONJ
easat-1848	200	14	"	"	PUNCT
easat-1848	200	15	misses	miss	NOUN
easat-1848	200	16	"	"	PUNCT
easat-1848	200	17	experienced	experience	VERB
easat-1848	200	18	for	for	ADP
easat-1848	200	19	every	every	DET
easat-1848	200	20	feature	feature	NOUN
easat-1848	200	21	.	.	PUNCT
easat-1848	201	1	high	high	ADJ
easat-1848	201	2	marks	mark	NOUN
easat-1848	201	3	are	be	AUX
easat-1848	201	4	awarded	award	VERB
easat-1848	201	5	to	to	ADP
easat-1848	201	6	features	feature	NOUN
easat-1848	201	7	that	that	PRON
easat-1848	201	8	have	have	VERB
easat-1848	201	9	a	a	DET
easat-1848	201	10	lot	lot	NOUN
easat-1848	201	11	of	of	ADP
easat-1848	201	12	"	"	PUNCT
easat-1848	201	13	misses	miss	NOUN
easat-1848	201	14	"	"	PUNCT
easat-1848	201	15	(	(	PUNCT
easat-1848	201	16	differentiate	differentiate	ADJ
easat-1848	201	17	classes	class	NOUN
easat-1848	201	18	)	)	PUNCT
easat-1848	201	19	and	and	CCONJ
easat-1848	201	20	few	few	ADJ
easat-1848	201	21	"	"	PUNCT
easat-1848	201	22	hits	hit	NOUN
easat-1848	201	23	"	"	PUNCT
easat-1848	201	24	(	(	PUNCT
easat-1848	201	25	constant	constant	ADJ
easat-1848	201	26	within	within	ADP
easat-1848	201	27	class	class	NOUN
easat-1848	201	28	)	)	PUNCT
easat-1848	201	29	.	.	PUNCT
easat-1848	202	1	let	let	VERB
easat-1848	202	2	d	d	PART
easat-1848	202	3	represent	represent	VERB
easat-1848	202	4	the	the	DET
easat-1848	202	5	dataset	dataset	NOUN
easat-1848	202	6	consisting	consisting	NOUN
easat-1848	202	7	of	of	ADP
easat-1848	202	8	n	n	DET
easat-1848	202	9	occurrences	occurrence	NOUN
easat-1848	202	10	and	and	CCONJ
easat-1848	202	11	p	p	NOUN
easat-1848	202	12	features	feature	NOUN
easat-1848	202	13	.	.	PUNCT
easat-1848	203	1	for	for	ADP
easat-1848	203	2	each	each	DET
easat-1848	203	3	feature	feature	NOUN
easat-1848	203	4	,	,	PUNCT
easat-1848	203	5	the	the	DET
easat-1848	203	6	relevance	relevance	NOUN
easat-1848	203	7	score	score	NOUN
easat-1848	203	8	is	be	AUX
easat-1848	203	9	stored	store	VERB
easat-1848	203	10	in	in	ADP
easat-1848	203	11	a	a	DET
easat-1848	203	12	weight	weight	NOUN
easat-1848	203	13	vector	vector	NOUN
easat-1848	203	14	w	w	PROPN
easat-1848	203	15	of	of	ADP
easat-1848	203	16	zeros	zero	NOUN
easat-1848	203	17	(	(	PUNCT
easat-1848	203	18	length	length	NOUN
easat-1848	203	19	p	p	PROPN
easat-1848	203	20	)	)	PUNCT
easat-1848	203	21	,	,	PUNCT
easat-1848	203	22	and	and	CCONJ
easat-1848	203	23	t	t	PROPN
easat-1848	203	24	is	be	AUX
easat-1848	203	25	the	the	DET
easat-1848	203	26	number	number	NOUN
easat-1848	203	27	of	of	ADP
easat-1848	203	28	iterations	iteration	NOUN
easat-1848	203	29	(	(	PUNCT
easat-1848	203	30	usually	usually	ADV
easat-1848	203	31	high	high	ADJ
easat-1848	203	32	for	for	ADP
easat-1848	203	33	better	well	ADJ
easat-1848	203	34	estimation	estimation	NOUN
easat-1848	203	35	)	)	PUNCT
easat-1848	203	36	.	.	PUNCT
easat-1848	204	1	for	for	ADP
easat-1848	204	2	every	every	DET
easat-1848	204	3	cycle	cycle	NOUN
easat-1848	204	4	(	(	PUNCT
easat-1848	204	5	t	t	NOUN
easat-1848	204	6	=	=	SYM
easat-1848	204	7	1	1	NUM
easat-1848	204	8	to	to	ADP
easat-1848	204	9	t	t	PROPN
easat-1848	204	10	)	)	PUNCT
easat-1848	204	11	,	,	PUNCT
easat-1848	204	12	as	as	SCONJ
easat-1848	204	13	follows	follow	VERB
easat-1848	204	14	:	:	PUNCT
easat-1848	204	15	1	1	X
easat-1848	204	16	.	.	X
easat-1848	204	17	one	one	NUM
easat-1848	204	18	instance	instance	NOUN
easat-1848	204	19	ra	ra	PROPN
easat-1848	204	20	should	should	AUX
easat-1848	204	21	be	be	AUX
easat-1848	204	22	chosen	choose	VERB
easat-1848	204	23	at	at	ADP
easat-1848	204	24	random	random	ADJ
easat-1848	204	25	from	from	ADP
easat-1848	204	26	d.	d.	PROPN
easat-1848	204	27	2	2	NUM
easat-1848	204	28	.	.	PUNCT
easat-1848	205	1	determine	determine	VERB
easat-1848	205	2	which	which	PRON
easat-1848	205	3	ra	ra	PROPN
easat-1848	205	4	feature	feature	NOUN
easat-1848	205	5	values	value	NOUN
easat-1848	205	6	correspond	correspond	VERB
easat-1848	205	7	to	to	ADP
easat-1848	205	8	the	the	DET
easat-1848	205	9	nearest	near	ADJ
easat-1848	205	10	hit	hit	VERB
easat-1848	205	11	(	(	PUNCT
easat-1848	205	12	h	h	NOUN
easat-1848	205	13	)	)	PUNCT
easat-1848	205	14	and	and	CCONJ
easat-1848	205	15	nearest	near	ADJ
easat-1848	205	16	miss	miss	PROPN
easat-1848	205	17	(	(	PUNCT
easat-1848	205	18	m	m	NOUN
easat-1848	205	19	)	)	PUNCT
easat-1848	205	20	(	(	PUNCT
easat-1848	205	21	same	same	ADJ
easat-1848	205	22	class	class	NOUN
easat-1848	205	23	for	for	ADP
easat-1848	205	24	h	h	NOUN
easat-1848	205	25	,	,	PUNCT
easat-1848	205	26	different	different	ADJ
easat-1848	205	27	class	class	NOUN
easat-1848	205	28	for	for	ADP
easat-1848	205	29	m	m	NOUN
easat-1848	205	30	)	)	PUNCT
easat-1848	205	31	.	.	PUNCT
easat-1848	206	1	3	3	X
easat-1848	206	2	.	.	X
easat-1848	206	3	modify	modify	VERB
easat-1848	206	4	each	each	DET
easat-1848	206	5	feature	feature	NOUN
easat-1848	206	6	b	b	PROPN
easat-1848	206	7	's	's	PART
easat-1848	206	8	weight	weight	NOUN
easat-1848	206	9	(	(	PUNCT
easat-1848	206	10	from	from	ADP
easat-1848	206	11	1	1	NUM
easat-1848	206	12	to	to	ADP
easat-1848	206	13	p	p	NOUN
easat-1848	206	14	):	):	PUNCT
easat-1848	206	15	w[b	w[b	NOUN
easat-1848	206	16	]	]	X
easat-1848	206	17	=	=	SYM
easat-1848	206	18	w[b	w[b	NOUN
easat-1848	206	19	]	]	X
easat-1848	206	20	diff(ra[b	diff(ra[b	NOUN
easat-1848	206	21	]	]	PUNCT
easat-1848	206	22	,	,	PUNCT
easat-1848	206	23	h[b	h[b	PROPN
easat-1848	206	24	]	]	PUNCT
easat-1848	206	25	)	)	PUNCT
easat-1848	206	26	/	/	PUNCT
easat-1848	206	27	(	(	PUNCT
easat-1848	206	28	t	t	NOUN
easat-1848	206	29	*	*	PUNCT
easat-1848	206	30	m	m	NOUN
easat-1848	206	31	)	)	PUNCT
easat-1848	207	1	+	+	NUM
easat-1848	207	2	diff(ra[b	diff(ra[b	NOUN
easat-1848	207	3	]	]	PUNCT
easat-1848	207	4	,	,	PUNCT
easat-1848	207	5	m[b	m[b	NOUN
easat-1848	207	6	]	]	X
easat-1848	207	7	)	)	PUNCT
easat-1848	207	8	/	/	PUNCT
easat-1848	207	9	(	(	PUNCT
easat-1848	207	10	t	t	NOUN
easat-1848	207	11	*	*	PUNCT
easat-1848	207	12	m	m	NOUN
easat-1848	207	13	)	)	PUNCT
easat-1848	208	1	[	[	X
easat-1848	208	2	2	2	X
easat-1848	208	3	]	]	PUNCT
easat-1848	208	4	now	now	ADV
easat-1848	208	5	,	,	PUNCT
easat-1848	208	6	diff(a	diff(a	INTJ
easat-1848	208	7	,	,	PUNCT
easat-1848	208	8	b	b	NOUN
easat-1848	208	9	)	)	PUNCT
easat-1848	208	10	determines	determine	VERB
easat-1848	208	11	how	how	SCONJ
easat-1848	208	12	feature	feature	NOUN
easat-1848	208	13	values	value	VERB
easat-1848	208	14	a	a	PRON
easat-1848	208	15	and	and	CCONJ
easat-1848	208	16	b	b	NOUN
easat-1848	208	17	differ	differ	VERB
easat-1848	208	18	from	from	ADP
easat-1848	208	19	each	each	DET
easat-1848	208	20	other	other	ADJ
easat-1848	208	21	.	.	PUNCT
easat-1848	209	1	the	the	DET
easat-1848	209	2	number	number	NOUN
easat-1848	209	3	of	of	ADP
easat-1848	209	4	nearest	near	ADJ
easat-1848	209	5	neighbours	neighbour	NOUN
easat-1848	209	6	(	(	PUNCT
easat-1848	209	7	usually	usually	ADV
easat-1848	209	8	fixed	fix	VERB
easat-1848	209	9	)	)	PUNCT
easat-1848	209	10	that	that	PRON
easat-1848	209	11	are	be	AUX
easat-1848	209	12	taken	take	VERB
easat-1848	209	13	into	into	ADP
easat-1848	209	14	consideration	consideration	NOUN
easat-1848	209	15	is	be	AUX
easat-1848	209	16	m.	m.	NOUN
easat-1848	209	17	the	the	DET
easat-1848	209	18	weight	weight	NOUN
easat-1848	209	19	vector	vector	NOUN
easat-1848	209	20	(	(	PUNCT
easat-1848	209	21	w	w	NOUN
easat-1848	209	22	)	)	PUNCT
easat-1848	209	23	,	,	PUNCT
easat-1848	209	24	which	which	PRON
easat-1848	209	25	shows	show	VERB
easat-1848	209	26	the	the	DET
easat-1848	209	27	significance	significance	NOUN
easat-1848	209	28	of	of	ADP
easat-1848	209	29	each	each	DET
easat-1848	209	30	feature	feature	NOUN
easat-1848	209	31	after	after	ADP
easat-1848	209	32	t	t	PROPN
easat-1848	209	33	iterations	iteration	NOUN
easat-1848	209	34	,	,	PUNCT
easat-1848	209	35	has	have	VERB
easat-1848	209	36	greater	great	ADJ
easat-1848	209	37	values	value	NOUN
easat-1848	209	38	that	that	PRON
easat-1848	209	39	correspond	correspond	VERB
easat-1848	209	40	to	to	ADP
easat-1848	209	41	better	well	ADJ
easat-1848	209	42	class	class	NOUN
easat-1848	209	43	separation	separation	NOUN
easat-1848	209	44	.	.	PUNCT
easat-1848	210	1	3.1.3	3.1.3	NUM
easat-1848	210	2	.	.	PUNCT
easat-1848	210	3	minimum	minimum	ADJ
easat-1848	210	4	redundancy	redundancy	NOUN
easat-1848	210	5	maximum	maximum	NOUN
easat-1848	210	6	relevance	relevance	NOUN
easat-1848	210	7	(	(	PUNCT
easat-1848	210	8	mr	mr	PROPN
easat-1848	210	9	-	-	PUNCT
easat-1848	210	10	mr	mr	PROPN
easat-1848	210	11	)	)	PUNCT
easat-1848	210	12	the	the	DET
easat-1848	210	13	goal	goal	NOUN
easat-1848	210	14	of	of	ADP
easat-1848	210	15	minimum	minimum	ADJ
easat-1848	210	16	redundancy	redundancy	NOUN
easat-1848	210	17	maximum	maximum	ADJ
easat-1848	210	18	relevance	relevance	NOUN
easat-1848	210	19	[	[	X
easat-1848	210	20	40	40	NUM
easat-1848	210	21	]	]	PUNCT
easat-1848	210	22	is	be	AUX
easat-1848	210	23	to	to	PART
easat-1848	210	24	categorize	categorize	VERB
easat-1848	210	25	subclass	subclass	NOUN
easat-1848	210	26	of	of	ADP
easat-1848	210	27	features	feature	NOUN
easat-1848	210	28	that	that	PRON
easat-1848	210	29	are	be	AUX
easat-1848	210	30	less	less	ADV
easat-1848	210	31	redundant	redundant	ADJ
easat-1848	210	32	with	with	ADP
easat-1848	210	33	one	one	NUM
easat-1848	210	34	another	another	DET
easat-1848	210	35	and	and	CCONJ
easat-1848	210	36	extremely	extremely	ADV
easat-1848	210	37	significant	significant	ADJ
easat-1848	210	38	to	to	ADP
easat-1848	210	39	the	the	DET
easat-1848	210	40	target	target	NOUN
easat-1848	210	41	variable	variable	NOUN
easat-1848	210	42	.	.	PUNCT
easat-1848	211	1	relevance	relevance	NOUN
easat-1848	211	2	:	:	PUNCT
easat-1848	211	3	mr	mr	PROPN
easat-1848	211	4	-	-	PUNCT
easat-1848	211	5	mr	mr	PROPN
easat-1848	211	6	measures	measure	VERB
easat-1848	211	7	the	the	DET
easat-1848	211	8	significance	significance	NOUN
easat-1848	211	9	of	of	ADP
easat-1848	211	10	a	a	DET
easat-1848	211	11	feature	feature	NOUN
easat-1848	211	12	xi	xi	PROPN
easat-1848	211	13	’s	’s	PART
easat-1848	211	14	relationship	relationship	NOUN
easat-1848	211	15	to	to	ADP
easat-1848	211	16	the	the	DET
easat-1848	211	17	target	target	NOUN
easat-1848	211	18	variable	variable	NOUN
easat-1848	211	19	y	y	PROPN
easat-1848	211	20	by	by	ADP
easat-1848	211	21	using	use	VERB
easat-1848	211	22	mutual	mutual	ADJ
easat-1848	211	23	information	information	NOUN
easat-1848	211	24	.	.	PUNCT
easat-1848	212	1	two	two	NUM
easat-1848	212	2	variables	variable	NOUN
easat-1848	212	3	are	be	AUX
easat-1848	212	4	dependent	dependent	ADJ
easat-1848	212	5	on	on	ADP
easat-1848	212	6	each	each	DET
easat-1848	212	7	other	other	ADJ
easat-1848	212	8	,	,	PUNCT
easat-1848	212	9	and	and	CCONJ
easat-1848	212	10	mutual	mutual	ADJ
easat-1848	212	11	information	information	NOUN
easat-1848	212	12	1461	1461	NUM
easat-1848	212	13	edelweiss	edelweiss	PROPN
easat-1848	212	14	applied	apply	VERB
easat-1848	212	15	science	science	NOUN
easat-1848	212	16	and	and	CCONJ
easat-1848	212	17	technology	technology	NOUN
easat-1848	212	18	issn	issn	PROPN
easat-1848	212	19	:	:	PUNCT
easat-1848	212	20	2576	2576	NUM
easat-1848	212	21	-	-	SYM
easat-1848	212	22	8484	8484	NUM
easat-1848	212	23	vol	vol	NOUN
easat-1848	212	24	.	.	PROPN
easat-1848	212	25	8	8	NUM
easat-1848	212	26	,	,	PUNCT
easat-1848	212	27	no	no	INTJ
easat-1848	212	28	.	.	NOUN
easat-1848	212	29	5	5	NUM
easat-1848	212	30	:	:	SYM
easat-1848	212	31	1445	1445	NUM
easat-1848	212	32	-	-	SYM
easat-1848	212	33	1471	1471	NUM
easat-1848	212	34	,	,	PUNCT
easat-1848	212	35	2024	2024	NUM
easat-1848	212	36	doi	doi	NOUN
easat-1848	212	37	:	:	PUNCT
easat-1848	212	38	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	212	39	©	©	PROPN
easat-1848	212	40	2024	2024	NUM
easat-1848	212	41	by	by	ADP
easat-1848	212	42	the	the	DET
easat-1848	212	43	authors	author	NOUN
easat-1848	212	44	;	;	PUNCT
easat-1848	212	45	licensee	licensee	PROPN
easat-1848	212	46	learning	learn	VERB
easat-1848	212	47	gate	gate	NOUN
easat-1848	212	48	quantifies	quantifie	NOUN
easat-1848	212	49	this	this	PRON
easat-1848	212	50	.	.	PUNCT
easat-1848	213	1	the	the	DET
easat-1848	213	2	association	association	NOUN
easat-1848	213	3	between	between	ADP
easat-1848	213	4	feature	feature	NOUN
easat-1848	213	5	and	and	CCONJ
easat-1848	213	6	goal	goal	NOUN
easat-1848	213	7	variable	variable	NOUN
easat-1848	213	8	is	be	AUX
easat-1848	213	9	stronger	strong	ADJ
easat-1848	213	10	when	when	SCONJ
easat-1848	213	11	there	there	PRON
easat-1848	213	12	is	be	VERB
easat-1848	213	13	a	a	DET
easat-1848	213	14	higher	high	ADJ
easat-1848	213	15	mutual	mutual	ADJ
easat-1848	213	16	information	information	NOUN
easat-1848	213	17	.	.	PUNCT
easat-1848	214	1	relevance	relevance	NOUN
easat-1848	214	2	(	(	PUNCT
easat-1848	214	3	xi	xi	PROPN
easat-1848	214	4	,	,	PUNCT
easat-1848	214	5	y	y	NOUN
easat-1848	214	6	)	)	PUNCT
easat-1848	215	1	=	=	NOUN
easat-1848	215	2	i	i	PROPN
easat-1848	215	3	(	(	PUNCT
easat-1848	215	4	xi	xi	PROPN
easat-1848	215	5	,	,	PUNCT
easat-1848	215	6	y	y	NOUN
easat-1848	215	7	)	)	PUNCT
easat-1848	215	8	redundancy	redundancy	NOUN
easat-1848	215	9	:	:	PUNCT
easat-1848	215	10	mr	mr	PROPN
easat-1848	215	11	-	-	PUNCT
easat-1848	215	12	mr	mr	PROPN
easat-1848	215	13	measures	measure	VERB
easat-1848	215	14	how	how	SCONJ
easat-1848	215	15	much	much	ADJ
easat-1848	215	16	information	information	NOUN
easat-1848	215	17	a	a	DET
easat-1848	215	18	feature	feature	NOUN
easat-1848	215	19	xi	xi	ADP
easat-1848	215	20	shares	share	NOUN
easat-1848	215	21	with	with	ADP
easat-1848	215	22	another	another	DET
easat-1848	215	23	feature	feature	NOUN
easat-1848	215	24	xj	xj	PROPN
easat-1848	215	25	.	.	PUNCT
easat-1848	216	1	the	the	DET
easat-1848	216	2	goal	goal	NOUN
easat-1848	216	3	is	be	AUX
easat-1848	216	4	to	to	PART
easat-1848	216	5	prevent	prevent	VERB
easat-1848	216	6	overfitting	overfitting	NOUN
easat-1848	216	7	in	in	ADP
easat-1848	216	8	machine	machine	NOUN
easat-1848	216	9	learning	learning	NOUN
easat-1848	216	10	models	model	NOUN
easat-1848	216	11	by	by	ADP
easat-1848	216	12	avoiding	avoid	VERB
easat-1848	216	13	using	use	VERB
easat-1848	216	14	features	feature	NOUN
easat-1848	216	15	that	that	PRON
easat-1848	216	16	represent	represent	VERB
easat-1848	216	17	the	the	DET
easat-1848	216	18	same	same	ADJ
easat-1848	216	19	information	information	NOUN
easat-1848	216	20	.	.	PUNCT
easat-1848	217	1	this	this	DET
easat-1848	217	2	instance	instance	NOUN
easat-1848	217	3	likewise	likewise	ADV
easat-1848	217	4	uses	use	VERB
easat-1848	217	5	mutual	mutual	ADJ
easat-1848	217	6	information	information	NOUN
easat-1848	217	7	,	,	PUNCT
easat-1848	217	8	but	but	CCONJ
easat-1848	217	9	it	it	PRON
easat-1848	217	10	does	do	VERB
easat-1848	217	11	so	so	ADV
easat-1848	217	12	to	to	PART
easat-1848	217	13	gauge	gauge	VERB
easat-1848	217	14	how	how	SCONJ
easat-1848	217	15	dependent	dependent	ADJ
easat-1848	217	16	two	two	NUM
easat-1848	217	17	sets	set	NOUN
easat-1848	217	18	of	of	ADP
easat-1848	217	19	features	feature	NOUN
easat-1848	217	20	are	be	AUX
easat-1848	217	21	on	on	ADP
easat-1848	217	22	one	one	NUM
easat-1848	217	23	another	another	DET
easat-1848	217	24	.	.	PUNCT
easat-1848	218	1	when	when	SCONJ
easat-1848	218	2	features	feature	NOUN
easat-1848	218	3	have	have	VERB
easat-1848	218	4	high	high	ADJ
easat-1848	218	5	redundancy	redundancy	NOUN
easat-1848	218	6	,	,	PUNCT
easat-1848	218	7	they	they	PRON
easat-1848	218	8	offer	offer	VERB
easat-1848	218	9	overlapping	overlap	VERB
easat-1848	218	10	information	information	NOUN
easat-1848	218	11	[	[	X
easat-1848	218	12	41	41	NUM
easat-1848	218	13	]	]	PUNCT
easat-1848	218	14	.	.	PUNCT
easat-1848	219	1	redundancy	redundancy	NOUN
easat-1848	219	2	(	(	PUNCT
easat-1848	219	3	xi	xi	PROPN
easat-1848	219	4	,	,	PUNCT
easat-1848	219	5	xj	xj	PROPN
easat-1848	219	6	)	)	PUNCT
easat-1848	220	1	=	=	NOUN
easat-1848	220	2	i	i	PROPN
easat-1848	220	3	(	(	PUNCT
easat-1848	220	4	xi	xi	PROPN
easat-1848	220	5	,	,	PUNCT
easat-1848	220	6	xj	xj	ADJ
easat-1848	220	7	)	)	PUNCT
easat-1848	220	8	average	average	ADJ
easat-1848	220	9	redundancy	redundancy	NOUN
easat-1848	220	10	:	:	PUNCT
easat-1848	220	11	the	the	DET
easat-1848	220	12	average	average	ADJ
easat-1848	220	13	redundancy	redundancy	NOUN
easat-1848	220	14	between	between	ADP
easat-1848	220	15	feature	feature	NOUN
easat-1848	220	16	xi	xi	ADP
easat-1848	220	17	and	and	CCONJ
easat-1848	220	18	every	every	DET
easat-1848	220	19	feature	feature	NOUN
easat-1848	220	20	in	in	ADP
easat-1848	220	21	the	the	DET
easat-1848	220	22	chosen	choose	VERB
easat-1848	220	23	set	set	NOUN
easat-1848	220	24	s	s	PART
easat-1848	220	25	is	be	AUX
easat-1848	220	26	the	the	DET
easat-1848	220	27	redundancy	redundancy	NOUN
easat-1848	220	28	term	term	NOUN
easat-1848	220	29	1	1	NUM
easat-1848	220	30	∑xj∈s	∑xj∈	NOUN
easat-1848	220	31	redundancy	redundancy	NOUN
easat-1848	220	32	(	(	PUNCT
easat-1848	220	33	xi	xi	PROPN
easat-1848	220	34	,	,	PUNCT
easat-1848	220	35	xj	xj	PROPN
easat-1848	220	36	)	)	PUNCT
easat-1848	220	37	|s|	|s|	VERB
easat-1848	220	38	mrmr	mrmr	PROPN
easat-1848	220	39	score	score	NOUN
easat-1848	220	40	combines	combine	VERB
easat-1848	220	41	redundancy	redundancy	NOUN
easat-1848	220	42	and	and	CCONJ
easat-1848	220	43	relevance	relevance	NOUN
easat-1848	220	44	to	to	PART
easat-1848	220	45	choose	choose	VERB
easat-1848	220	46	features	feature	NOUN
easat-1848	220	47	that	that	PRON
easat-1848	220	48	are	be	AUX
easat-1848	220	49	least	least	ADV
easat-1848	220	50	redundant	redundant	ADJ
easat-1848	220	51	with	with	ADP
easat-1848	220	52	one	one	NUM
easat-1848	220	53	another	another	DET
easat-1848	220	54	and	and	CCONJ
easat-1848	220	55	extremely	extremely	ADV
easat-1848	220	56	relevant	relevant	ADJ
easat-1848	220	57	to	to	ADP
easat-1848	220	58	the	the	DET
easat-1848	220	59	target	target	NOUN
easat-1848	220	60	variable	variable	NOUN
easat-1848	220	61	.	.	PUNCT
easat-1848	221	1	the	the	DET
easat-1848	221	2	following	follow	VERB
easat-1848	221	3	formula	formula	NOUN
easat-1848	221	4	can	can	AUX
easat-1848	221	5	be	be	AUX
easat-1848	221	6	used	use	VERB
easat-1848	221	7	to	to	PART
easat-1848	221	8	express	express	VERB
easat-1848	221	9	the	the	DET
easat-1848	221	10	mr	mr	PROPN
easat-1848	221	11	-	-	PUNCT
easat-1848	221	12	mr	mr	PROPN
easat-1848	221	13	(	(	PUNCT
easat-1848	221	14	minimum	minimum	ADJ
easat-1848	221	15	redundancy	redundancy	NOUN
easat-1848	221	16	maximum	maximum	NOUN
easat-1848	221	17	relevance	relevance	NOUN
easat-1848	221	18	)	)	PUNCT
easat-1848	221	19	feature	feature	NOUN
easat-1848	221	20	selection	selection	NOUN
easat-1848	221	21	score	score	NOUN
easat-1848	221	22	mathematically	mathematically	ADV
easat-1848	221	23	:	:	PUNCT
easat-1848	221	24	mrmr	mrmr	PROPN
easat-1848	221	25	score	score	NOUN
easat-1848	221	26	(	(	PUNCT
easat-1848	221	27	xi)=relevance	xi)=relevance	NOUN
easat-1848	221	28	(	(	PUNCT
easat-1848	221	29	xi	xi	PROPN
easat-1848	221	30	,	,	PUNCT
easat-1848	221	31	y	y	NOUN
easat-1848	221	32	)	)	PUNCT
easat-1848	221	33	−1	−1	NOUN
easat-1848	221	34	∑xj∈s	∑xj∈	NOUN
easat-1848	221	35	redundancy	redundancy	NOUN
easat-1848	221	36	(	(	PUNCT
easat-1848	221	37	xi	xi	PROPN
easat-1848	221	38	,	,	PUNCT
easat-1848	221	39	xj	xj	PROPN
easat-1848	221	40	)	)	PUNCT
easat-1848	222	1	[	[	X
easat-1848	222	2	3	3	NUM
easat-1848	222	3	]	]	SYM
easat-1848	222	4	|s|	|s|	PROPN
easat-1848	222	5	where	where	SCONJ
easat-1848	222	6	:	:	PUNCT
easat-1848	222	7	•	•	NUM
easat-1848	222	8	mrmr	mrmr	PROPN
easat-1848	222	9	score	score	NOUN
easat-1848	222	10	(	(	PUNCT
easat-1848	222	11	xi	xi	X
easat-1848	222	12	)	)	PUNCT
easat-1848	222	13	is	be	AUX
easat-1848	222	14	mr	mr	PROPN
easat-1848	222	15	-	-	PUNCT
easat-1848	222	16	mr	mr	PROPN
easat-1848	222	17	score	score	NOUN
easat-1848	222	18	for	for	ADP
easat-1848	222	19	feature	feature	NOUN
easat-1848	222	20	xi	xi	PROPN
easat-1848	222	21	.	.	PUNCT
easat-1848	223	1	•	•	NUM
easat-1848	223	2	relevance	relevance	NOUN
easat-1848	223	3	(	(	PUNCT
easat-1848	223	4	xi	xi	PROPN
easat-1848	223	5	,	,	PUNCT
easat-1848	223	6	y	y	NOUN
easat-1848	223	7	)	)	PUNCT
easat-1848	223	8	is	be	AUX
easat-1848	223	9	relevance	relevance	NOUN
easat-1848	223	10	of	of	ADP
easat-1848	223	11	feature	feature	NOUN
easat-1848	223	12	xi	xi	ADP
easat-1848	223	13	with	with	ADP
easat-1848	223	14	respect	respect	NOUN
easat-1848	223	15	to	to	ADP
easat-1848	223	16	the	the	DET
easat-1848	223	17	target	target	NOUN
easat-1848	223	18	variable	variable	NOUN
easat-1848	223	19	y.	y.	NOUN
easat-1848	223	20	•	•	PROPN
easat-1848	223	21	s	s	VERB
easat-1848	223	22	is	be	AUX
easat-1848	223	23	the	the	DET
easat-1848	223	24	subset	subset	NOUN
easat-1848	223	25	of	of	ADP
easat-1848	223	26	already	already	ADV
easat-1848	223	27	chosen	choose	VERB
easat-1848	223	28	features	feature	NOUN
easat-1848	223	29	.	.	PUNCT
easat-1848	224	1	•	•	NUM
easat-1848	224	2	∣s∣	∣s∣	NOUN
easat-1848	224	3	is	be	AUX
easat-1848	224	4	count	count	NOUN
easat-1848	224	5	of	of	ADP
easat-1848	224	6	features	feature	NOUN
easat-1848	224	7	in	in	ADP
easat-1848	224	8	subset	subset	ADJ
easat-1848	224	9	s.	s.	PROPN
easat-1848	224	10	•	•	ADV
easat-1848	224	11	redundancy	redundancy	NOUN
easat-1848	224	12	(	(	PUNCT
easat-1848	224	13	xi	xi	PROPN
easat-1848	224	14	,	,	PUNCT
easat-1848	224	15	xj	xj	NOUN
easat-1848	224	16	)	)	PUNCT
easat-1848	224	17	is	be	AUX
easat-1848	224	18	the	the	DET
easat-1848	224	19	redundancy	redundancy	NOUN
easat-1848	224	20	among	among	ADP
easat-1848	224	21	feature	feature	NOUN
easat-1848	224	22	xi	xi	X
easat-1848	225	1	and	and	CCONJ
easat-1848	225	2	each	each	DET
easat-1848	225	3	feature	feature	NOUN
easat-1848	225	4	xj	xj	PROPN
easat-1848	225	5	in	in	ADP
easat-1848	225	6	selected	select	VERB
easat-1848	225	7	set	set	VERB
easat-1848	225	8	s.	s.	PROPN
easat-1848	225	9	3.1.4	3.1.4	PROPN
easat-1848	225	10	.	.	PUNCT
easat-1848	226	1	recursive	recursive	ADJ
easat-1848	226	2	feature	feature	NOUN
easat-1848	226	3	elimination	elimination	NOUN
easat-1848	226	4	(	(	PUNCT
easat-1848	226	5	rfe	rfe	NOUN
easat-1848	226	6	)	)	PUNCT
easat-1848	226	7	recursive	recursive	ADJ
easat-1848	226	8	feature	feature	NOUN
easat-1848	226	9	elimination	elimination	NOUN
easat-1848	226	10	method	method	NOUN
easat-1848	227	1	[	[	X
easat-1848	227	2	41	41	NUM
easat-1848	227	3	]	]	PUNCT
easat-1848	227	4	helps	help	VERB
easat-1848	227	5	to	to	PART
easat-1848	227	6	identify	identify	VERB
easat-1848	227	7	characteristics	characteristic	NOUN
easat-1848	227	8	which	which	PRON
easat-1848	227	9	are	be	AUX
easat-1848	227	10	most	most	ADV
easat-1848	227	11	crucial	crucial	ADJ
easat-1848	227	12	to	to	PART
easat-1848	227	13	include	include	VERB
easat-1848	227	14	in	in	ADP
easat-1848	227	15	a	a	DET
easat-1848	227	16	model	model	NOUN
easat-1848	227	17	.	.	PUNCT
easat-1848	228	1	depending	depend	VERB
easat-1848	228	2	on	on	ADP
easat-1848	228	3	the	the	DET
easat-1848	228	4	model	model	NOUN
easat-1848	228	5	's	's	PART
easat-1848	228	6	coefficients	coefficient	NOUN
easat-1848	228	7	,	,	PUNCT
easat-1848	228	8	it	it	PRON
easat-1848	228	9	operates	operate	VERB
easat-1848	228	10	by	by	ADP
easat-1848	228	11	iteratively	iteratively	ADV
easat-1848	228	12	eliminating	eliminate	VERB
easat-1848	228	13	least	least	ADV
easat-1848	228	14	significant	significant	ADJ
easat-1848	228	15	features	feature	NOUN
easat-1848	228	16	until	until	SCONJ
easat-1848	228	17	predetermined	predetermine	VERB
easat-1848	228	18	number	number	NOUN
easat-1848	228	19	of	of	ADP
easat-1848	228	20	features	feature	NOUN
easat-1848	228	21	is	be	AUX
easat-1848	228	22	reached	reach	VERB
easat-1848	228	23	.	.	PUNCT
easat-1848	229	1	recursively	recursively	ADV
easat-1848	229	2	evaluating	evaluate	VERB
easat-1848	229	3	progressively	progressively	ADV
easat-1848	229	4	smaller	small	ADJ
easat-1848	229	5	subsets	subset	NOUN
easat-1848	229	6	of	of	ADP
easat-1848	229	7	features	feature	NOUN
easat-1848	229	8	is	be	AUX
easat-1848	229	9	how	how	SCONJ
easat-1848	229	10	rfe	rfe	ADJ
easat-1848	229	11	selects	select	NOUN
easat-1848	229	12	features	feature	NOUN
easat-1848	229	13	.	.	PUNCT
easat-1848	230	1	based	base	VERB
easat-1848	230	2	on	on	ADP
easat-1848	230	3	the	the	DET
easat-1848	230	4	feature	feature	NOUN
easat-1848	230	5	importance	importance	NOUN
easat-1848	230	6	or	or	CCONJ
easat-1848	230	7	coefficients	coefficient	NOUN
easat-1848	230	8	supplied	supply	VERB
easat-1848	230	9	by	by	ADP
easat-1848	230	10	the	the	DET
easat-1848	230	11	model	model	NOUN
easat-1848	230	12	,	,	PUNCT
easat-1848	230	13	it	it	PRON
easat-1848	230	14	trains	train	VERB
easat-1848	230	15	a	a	DET
easat-1848	230	16	model	model	NOUN
easat-1848	230	17	in	in	ADP
easat-1848	230	18	every	every	DET
easat-1848	230	19	iteration	iteration	NOUN
easat-1848	230	20	and	and	CCONJ
easat-1848	230	21	eradicates	eradicate	NOUN
easat-1848	230	22	least	least	ADV
easat-1848	230	23	significant	significant	ADJ
easat-1848	230	24	feature	feature	NOUN
easat-1848	230	25	.	.	PUNCT
easat-1848	231	1	the	the	DET
easat-1848	231	2	importance	importance	NOUN
easat-1848	231	3	of	of	ADP
easat-1848	231	4	each	each	DET
easat-1848	231	5	feature	feature	NOUN
easat-1848	231	6	is	be	AUX
easat-1848	231	7	computed	compute	VERB
easat-1848	231	8	using	use	VERB
easat-1848	231	9	linear	linear	PROPN
easat-1848	231	10	model	model	ADJ
easat-1848	231	11	-	-	PUNCT
easat-1848	231	12	specific	specific	ADJ
easat-1848	231	13	criteria	criterion	NOUN
easat-1848	231	14	as	as	SCONJ
easat-1848	231	15	follows	follow	VERB
easat-1848	231	16	:	:	PUNCT
easat-1848	231	17	use	use	VERB
easat-1848	231	18	absolute	absolute	ADJ
easat-1848	231	19	values	value	NOUN
easat-1848	231	20	of	of	ADP
easat-1848	231	21	coefficients	coefficient	NOUN
easat-1848	231	22	.	.	PUNCT
easat-1848	232	1	a	a	DET
easat-1848	232	2	linear	linear	ADJ
easat-1848	232	3	model	model	NOUN
easat-1848	232	4	y	y	PROPN
easat-1848	232	5	=	=	PROPN
easat-1848	233	1	q0	q0	PROPN
easat-1848	233	2	+	+	CCONJ
easat-1848	233	3	q1	q1	NOUN
easat-1848	233	4	x1	x1	PROPN
easat-1848	234	1	+	+	X
easat-1848	234	2	…	…	PUNCT
easat-1848	234	3	+	+	NUM
easat-1848	234	4	qp	qp	NOUN
easat-1848	234	5	xp	xp	INTJ
easat-1848	234	6	,	,	PUNCT
easat-1848	234	7	[	[	X
easat-1848	234	8	4	4	X
easat-1848	234	9	]	]	X
easat-1848	234	10	the	the	DET
easat-1848	234	11	importance	importance	NOUN
easat-1848	234	12	of	of	ADP
easat-1848	234	13	feature	feature	NOUN
easat-1848	234	14	j	j	PROPN
easat-1848	234	15	is	be	AUX
easat-1848	234	16	∣qj∣	∣qj∣	PROPN
easat-1848	234	17	with	with	ADP
easat-1848	234	18	rfe	rfe	NOUN
easat-1848	234	19	,	,	PUNCT
easat-1848	234	20	redundant	redundant	ADJ
easat-1848	234	21	or	or	CCONJ
easat-1848	234	22	unnecessary	unnecessary	ADJ
easat-1848	234	23	features	feature	NOUN
easat-1848	234	24	are	be	AUX
easat-1848	234	25	removed	remove	VERB
easat-1848	234	26	,	,	PUNCT
easat-1848	234	27	which	which	PRON
easat-1848	234	28	effectively	effectively	ADV
easat-1848	234	29	reduces	reduce	VERB
easat-1848	234	30	model	model	NOUN
easat-1848	234	31	complexity	complexity	NOUN
easat-1848	234	32	and	and	CCONJ
easat-1848	234	33	improves	improve	VERB
easat-1848	234	34	generalization	generalization	NOUN
easat-1848	234	35	.	.	PUNCT
easat-1848	235	1	3.1.5	3.1.5	X
easat-1848	235	2	.	.	PUNCT
easat-1848	235	3	principle	principle	ADJ
easat-1848	235	4	component	component	NOUN
easat-1848	235	5	analysis	analysis	NOUN
easat-1848	235	6	(	(	PUNCT
easat-1848	235	7	pca	pca	NOUN
easat-1848	235	8	)	)	PUNCT
easat-1848	235	9	to	to	PART
easat-1848	235	10	extract	extract	VERB
easat-1848	235	11	the	the	DET
easat-1848	235	12	most	most	ADJ
easat-1848	235	13	variance	variance	NOUN
easat-1848	235	14	from	from	ADP
easat-1848	235	15	a	a	DET
easat-1848	235	16	dataset	dataset	NOUN
easat-1848	235	17	,	,	PUNCT
easat-1848	235	18	principle	principle	ADJ
easat-1848	235	19	component	component	NOUN
easat-1848	235	20	analysis	analysis	NOUN
easat-1848	235	21	(	(	PUNCT
easat-1848	235	22	pca	pca	NOUN
easat-1848	235	23	)	)	PUNCT
easat-1848	236	1	[	[	X
easat-1848	236	2	40	40	NUM
easat-1848	236	3	]	]	PUNCT
easat-1848	237	1	[	[	X
easat-1848	237	2	41	41	NUM
easat-1848	237	3	]	]	PUNCT
easat-1848	237	4	divides	divide	VERB
easat-1848	237	5	the	the	DET
easat-1848	237	6	dataset	dataset	NOUN
easat-1848	237	7	into	into	ADP
easat-1848	237	8	a	a	DET
easat-1848	237	9	set	set	NOUN
easat-1848	237	10	of	of	ADP
easat-1848	237	11	orthogonal	orthogonal	ADJ
easat-1848	237	12	components	component	NOUN
easat-1848	237	13	,	,	PUNCT
easat-1848	237	14	or	or	CCONJ
easat-1848	237	15	principle	principle	ADJ
easat-1848	237	16	components	component	NOUN
easat-1848	237	17	.	.	PUNCT
easat-1848	238	1	pca	pca	PROPN
easat-1848	238	2	can	can	AUX
easat-1848	238	3	be	be	AUX
easat-1848	238	4	used	use	VERB
easat-1848	238	5	to	to	PART
easat-1848	238	6	determine	determine	VERB
easat-1848	238	7	the	the	DET
easat-1848	238	8	most	most	ADV
easat-1848	238	9	significant	significant	ADJ
easat-1848	238	10	features	feature	NOUN
easat-1848	238	11	by	by	ADP
easat-1848	238	12	examining	examine	VERB
easat-1848	238	13	the	the	DET
easat-1848	238	14	principle	principle	ADJ
easat-1848	238	15	components	component	NOUN
easat-1848	238	16	,	,	PUNCT
easat-1848	238	17	even	even	ADV
easat-1848	238	18	though	though	SCONJ
easat-1848	238	19	it	it	PRON
easat-1848	238	20	is	be	AUX
easat-1848	238	21	not	not	PART
easat-1848	238	22	a	a	DET
easat-1848	238	23	feature	feature	NOUN
easat-1848	238	24	selection	selection	NOUN
easat-1848	238	25	technique	technique	NOUN
easat-1848	238	26	per	per	ADP
easat-1848	238	27	se	se	X
easat-1848	238	28	.	.	PUNCT
easat-1848	239	1	in	in	ADP
easat-1848	239	2	order	order	NOUN
easat-1848	239	3	to	to	PART
easat-1848	239	4	recognize	recognize	VERB
easat-1848	239	5	the	the	DET
easat-1848	239	6	original	original	ADJ
easat-1848	239	7	features	feature	NOUN
easat-1848	239	8	which	which	PRON
easat-1848	239	9	contribute	contribute	VERB
easat-1848	239	10	the	the	DET
easat-1848	239	11	most	most	ADJ
easat-1848	239	12	to	to	PART
easat-1848	239	13	variance	variance	VERB
easat-1848	239	14	in	in	ADP
easat-1848	239	15	the	the	DET
easat-1848	239	16	dataset	dataset	NOUN
easat-1848	239	17	,	,	PUNCT
easat-1848	239	18	one	one	PRON
easat-1848	239	19	must	must	AUX
easat-1848	239	20	interpret	interpret	VERB
easat-1848	239	21	the	the	DET
easat-1848	239	22	principle	principle	ADJ
easat-1848	239	23	components	component	NOUN
easat-1848	239	24	when	when	SCONJ
easat-1848	239	25	using	use	VERB
easat-1848	239	26	pca	pca	NOUN
easat-1848	239	27	for	for	ADP
easat-1848	239	28	feature	feature	NOUN
easat-1848	239	29	selection	selection	NOUN
easat-1848	239	30	.	.	PUNCT
easat-1848	240	1	despite	despite	SCONJ
easat-1848	240	2	the	the	DET
easat-1848	240	3	fact	fact	NOUN
easat-1848	240	4	that	that	SCONJ
easat-1848	240	5	pca	pca	NOUN
easat-1848	240	6	generates	generate	VERB
easat-1848	240	7	new	new	ADJ
easat-1848	240	8	composite	composite	ADJ
easat-1848	240	9	features	feature	NOUN
easat-1848	240	10	(	(	PUNCT
easat-1848	240	11	principal	principal	ADJ
easat-1848	240	12	components	component	NOUN
easat-1848	240	13	)	)	PUNCT
easat-1848	240	14	instead	instead	ADV
easat-1848	240	15	of	of	ADP
easat-1848	240	16	choosing	choose	VERB
easat-1848	240	17	original	original	ADJ
easat-1848	240	18	features	feature	NOUN
easat-1848	240	19	,	,	PUNCT
easat-1848	240	20	it	it	PRON
easat-1848	240	21	can	can	AUX
easat-1848	240	22	still	still	ADV
easat-1848	240	23	influence	influence	VERB
easat-1848	240	24	feature	feature	NOUN
easat-1848	240	25	selection	selection	NOUN
easat-1848	240	26	by	by	ADP
easat-1848	240	27	evaluating	evaluate	VERB
easat-1848	240	28	how	how	SCONJ
easat-1848	240	29	important	important	ADJ
easat-1848	240	30	a	a	DET
easat-1848	240	31	feature	feature	NOUN
easat-1848	240	32	is	be	AUX
easat-1848	240	33	within	within	ADP
easat-1848	240	34	these	these	DET
easat-1848	240	35	components	component	NOUN
easat-1848	240	36	.	.	PUNCT
easat-1848	241	1	in	in	ADP
easat-1848	241	2	order	order	NOUN
easat-1848	241	3	to	to	PART
easat-1848	241	4	choose	choose	VERB
easat-1848	241	5	features	feature	NOUN
easat-1848	241	6	using	use	VERB
easat-1848	241	7	pca	pca	PROPN
easat-1848	241	8	,	,	PUNCT
easat-1848	241	9	the	the	DET
easat-1848	241	10	loadings	loading	NOUN
easat-1848	241	11	of	of	ADP
easat-1848	241	12	the	the	DET
easat-1848	241	13	principle	principle	ADJ
easat-1848	241	14	components	component	NOUN
easat-1848	241	15	are	be	AUX
easat-1848	241	16	examined	examine	VERB
easat-1848	241	17	.	.	PUNCT
easat-1848	242	1	the	the	DET
easat-1848	242	2	loadings	loading	NOUN
easat-1848	242	3	show	show	VERB
easat-1848	242	4	how	how	SCONJ
easat-1848	242	5	each	each	DET
easat-1848	242	6	original	original	ADJ
easat-1848	242	7	feature	feature	NOUN
easat-1848	242	8	contributed	contribute	VERB
easat-1848	242	9	to	to	ADP
easat-1848	242	10	a	a	DET
easat-1848	242	11	major	major	ADJ
easat-1848	242	12	1462	1462	NUM
easat-1848	242	13	edelweiss	edelweiss	PROPN
easat-1848	242	14	applied	apply	VERB
easat-1848	242	15	science	science	NOUN
easat-1848	242	16	and	and	CCONJ
easat-1848	242	17	technology	technology	NOUN
easat-1848	242	18	issn	issn	PROPN
easat-1848	242	19	:	:	PUNCT
easat-1848	242	20	2576	2576	NUM
easat-1848	242	21	-	-	SYM
easat-1848	242	22	8484	8484	NUM
easat-1848	242	23	vol	vol	NOUN
easat-1848	242	24	.	.	PROPN
easat-1848	243	1	8	8	NUM
easat-1848	243	2	,	,	PUNCT
easat-1848	243	3	no	no	INTJ
easat-1848	243	4	.	.	NOUN
easat-1848	243	5	5	5	NUM
easat-1848	243	6	:	:	SYM
easat-1848	243	7	1445	1445	NUM
easat-1848	243	8	-	-	SYM
easat-1848	243	9	1471	1471	NUM
easat-1848	243	10	,	,	PUNCT
easat-1848	243	11	2024	2024	NUM
easat-1848	243	12	doi	doi	NOUN
easat-1848	243	13	:	:	PUNCT
easat-1848	243	14	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	243	15	©	©	PROPN
easat-1848	243	16	2024	2024	NUM
easat-1848	243	17	by	by	ADP
easat-1848	243	18	the	the	DET
easat-1848	243	19	authors	author	NOUN
easat-1848	243	20	;	;	PUNCT
easat-1848	243	21	licensee	licensee	PROPN
easat-1848	243	22	learning	learning	PROPN
easat-1848	243	23	gate	gate	PROPN
easat-1848	243	24	component	component	NOUN
easat-1848	243	25	.	.	PUNCT
easat-1848	244	1	they	they	PRON
easat-1848	244	2	are	be	AUX
easat-1848	244	3	given	give	VERB
easat-1848	244	4	by	by	ADP
easat-1848	244	5	the	the	DET
easat-1848	244	6	matrix	matrix	NOUN
easat-1848	244	7	of	of	ADP
easat-1848	244	8	eigenvectors	eigenvector	NOUN
easat-1848	244	9	:	:	PUNCT
easat-1848	244	10	l	l	NOUN
easat-1848	244	11	=	=	SYM
easat-1848	244	12	v	v	NOUN
easat-1848	244	13	,	,	PUNCT
easat-1848	244	14	where	where	SCONJ
easat-1848	244	15	each	each	DET
easat-1848	244	16	element	element	NOUN
easat-1848	244	17	lij	lij	NOUN
easat-1848	244	18	in	in	ADP
easat-1848	244	19	the	the	DET
easat-1848	244	20	loading	loading	NOUN
easat-1848	244	21	matrix	matrix	NOUN
easat-1848	244	22	represents	represent	VERB
easat-1848	244	23	the	the	DET
easat-1848	244	24	contribution	contribution	NOUN
easat-1848	244	25	of	of	ADP
easat-1848	244	26	the	the	DET
easat-1848	244	27	jth	jth	PROPN
easat-1848	244	28	feature	feature	NOUN
easat-1848	244	29	to	to	ADP
easat-1848	244	30	the	the	DET
easat-1848	244	31	ith	ith	PROPN
easat-1848	244	32	principal	principal	ADJ
easat-1848	244	33	component	component	NOUN
easat-1848	244	34	.	.	PUNCT
easat-1848	245	1	4	4	X
easat-1848	245	2	.	.	NOUN
easat-1848	245	3	results	result	NOUN
easat-1848	245	4	and	and	CCONJ
easat-1848	245	5	discussion	discussion	NOUN
easat-1848	245	6	4.1	4.1	NUM
easat-1848	245	7	.	.	PUNCT
easat-1848	246	1	results	result	NOUN
easat-1848	246	2	computed	compute	VERB
easat-1848	246	3	with	with	ADP
easat-1848	246	4	lasso	lasso	ADJ
easat-1848	246	5	feature	feature	NOUN
easat-1848	246	6	selection	selection	NOUN
easat-1848	246	7	8	8	NUM
easat-1848	246	8	features	feature	NOUN
easat-1848	246	9	have	have	AUX
easat-1848	246	10	been	be	AUX
easat-1848	246	11	chosen	choose	VERB
easat-1848	246	12	with	with	ADP
easat-1848	246	13	lasso	lasso	NOUN
easat-1848	246	14	from	from	ADP
easat-1848	246	15	initial	initial	ADJ
easat-1848	246	16	features	feature	NOUN
easat-1848	246	17	set	set	VERB
easat-1848	246	18	of	of	ADP
easat-1848	246	19	12	12	NUM
easat-1848	246	20	features	feature	NOUN
easat-1848	246	21	from	from	ADP
easat-1848	246	22	combined	combine	VERB
easat-1848	246	23	dataset	dataset	NOUN
easat-1848	246	24	.	.	PUNCT
easat-1848	247	1	table	table	NOUN
easat-1848	247	2	i	i	PRON
easat-1848	247	3	depicts	depict	VERB
easat-1848	247	4	the	the	DET
easat-1848	247	5	performance	performance	NOUN
easat-1848	247	6	of	of	ADP
easat-1848	247	7	lasso	lasso	ADJ
easat-1848	247	8	feature	feature	NOUN
easat-1848	247	9	selection	selection	NOUN
easat-1848	247	10	with	with	ADP
easat-1848	247	11	six	six	NUM
easat-1848	247	12	implemented	implement	VERB
easat-1848	247	13	ml	ml	NOUN
easat-1848	247	14	and	and	CCONJ
easat-1848	247	15	neural	neural	ADJ
easat-1848	247	16	network	network	NOUN
easat-1848	247	17	classifiers	classifier	NOUN
easat-1848	247	18	in	in	ADP
easat-1848	247	19	terms	term	NOUN
easat-1848	247	20	of	of	ADP
easat-1848	247	21	six	six	NUM
easat-1848	247	22	vital	vital	ADJ
easat-1848	247	23	efficiency	efficiency	NOUN
easat-1848	247	24	measuring	measure	VERB
easat-1848	247	25	metrics	metric	NOUN
easat-1848	247	26	.	.	PUNCT
easat-1848	248	1	figure	figure	VERB
easat-1848	248	2	3	3	NUM
easat-1848	248	3	-	-	SYM
easat-1848	248	4	8	8	NUM
easat-1848	248	5	signifies	signify	VERB
easat-1848	248	6	the	the	DET
easat-1848	248	7	six	six	NUM
easat-1848	248	8	outcomes	outcome	NOUN
easat-1848	248	9	accuracy	accuracy	NOUN
easat-1848	248	10	,	,	PUNCT
easat-1848	248	11	precision	precision	NOUN
easat-1848	248	12	,	,	PUNCT
easat-1848	248	13	recall	recall	NOUN
easat-1848	248	14	,	,	PUNCT
easat-1848	248	15	f1score	f1score	NOUN
easat-1848	248	16	,	,	PUNCT
easat-1848	248	17	mse	mse	PROPN
easat-1848	248	18	,	,	PUNCT
easat-1848	248	19	mae	mae	PROPN
easat-1848	249	1	[	[	X
easat-1848	249	2	42	42	NUM
easat-1848	249	3	]	]	PUNCT
easat-1848	250	1	[	[	X
easat-1848	250	2	43	43	NUM
easat-1848	250	3	]	]	PUNCT
easat-1848	250	4	in	in	ADP
easat-1848	250	5	graphical	graphical	ADJ
easat-1848	250	6	format	format	NOUN
easat-1848	250	7	for	for	ADP
easat-1848	250	8	random	random	ADJ
easat-1848	250	9	forest	forest	NOUN
easat-1848	250	10	,	,	PUNCT
easat-1848	250	11	logistic	logistic	ADJ
easat-1848	250	12	regression	regression	NOUN
easat-1848	250	13	,	,	PUNCT
easat-1848	250	14	support	support	NOUN
easat-1848	250	15	vector	vector	NOUN
easat-1848	250	16	machine	machine	NOUN
easat-1848	250	17	,	,	PUNCT
easat-1848	250	18	naive	naive	ADJ
easat-1848	250	19	bayes	bayes	NOUN
easat-1848	250	20	,	,	PUNCT
easat-1848	250	21	k	k	NOUN
easat-1848	250	22	-	-	PUNCT
easat-1848	250	23	nearest	near	ADJ
easat-1848	250	24	neighbour	neighbour	ADJ
easat-1848	250	25	classifiers	classifier	NOUN
easat-1848	250	26	respectively	respectively	ADV
easat-1848	250	27	using	use	VERB
easat-1848	250	28	lasso	lasso	NOUN
easat-1848	250	29	feature	feature	NOUN
easat-1848	250	30	selection	selection	NOUN
easat-1848	250	31	.	.	PUNCT
easat-1848	251	1	table	table	NOUN
easat-1848	251	2	1	1	NUM
easat-1848	251	3	.	.	PUNCT
easat-1848	251	4	results	result	NOUN
easat-1848	251	5	with	with	ADP
easat-1848	251	6	lasso	lasso	ADJ
easat-1848	251	7	feature	feature	NOUN
easat-1848	251	8	selection	selection	NOUN
easat-1848	251	9	method	method	NOUN
easat-1848	251	10	.	.	PUNCT
easat-1848	252	1	lasso	lasso	NOUN
easat-1848	252	2	feature	feature	NOUN
easat-1848	252	3	extraction	extraction	NOUN
easat-1848	252	4	model	model	NOUN
easat-1848	252	5	accuracy	accuracy	NOUN
easat-1848	252	6	precision	precision	NOUN
easat-1848	252	7	recall	recall	PROPN
easat-1848	252	8	f1score	f1score	PROPN
easat-1848	252	9	mse	mse	PROPN
easat-1848	252	10	mae	mae	PROPN
easat-1848	252	11	logistic	logistic	ADJ
easat-1848	252	12	regression	regression	NOUN
easat-1848	252	13	86.13	86.13	NUM
easat-1848	252	14	87.12	87.12	NUM
easat-1848	252	15	87.78	87.78	NUM
easat-1848	252	16	87.45	87.45	NUM
easat-1848	252	17	13.86	13.86	NUM
easat-1848	252	18	13.86	13.86	NUM
easat-1848	252	19	knn	knn	X
easat-1848	252	20	88.65	88.65	NUM
easat-1848	252	21	87.14	87.14	NUM
easat-1848	252	22	93.12	93.12	NUM
easat-1848	252	23	90.03	90.03	NUM
easat-1848	252	24	11.34	11.34	NUM
easat-1848	252	25	11.34	11.34	NUM
easat-1848	252	26	random	random	ADJ
easat-1848	252	27	forest	forest	NOUN
easat-1848	252	28	95.37	95.37	NUM
easat-1848	252	29	94.77	94.77	NUM
easat-1848	252	30	96.94	96.94	NUM
easat-1848	252	31	95.84	95.84	NUM
easat-1848	252	32	4.62	4.62	NUM
easat-1848	252	33	4.62	4.62	NUM
easat-1848	252	34	svm	svm	PROPN
easat-1848	252	35	89.07	89.07	NUM
easat-1848	252	36	86.71	86.71	NUM
easat-1848	252	37	94.65	94.65	NUM
easat-1848	252	38	90.51	90.51	NUM
easat-1848	252	39	10.9	10.9	NUM
easat-1848	252	40	10.9	10.9	NUM
easat-1848	252	41	naive	naive	ADJ
easat-1848	252	42	bayes	baye	NOUN
easat-1848	252	43	85.71	85.71	NUM
easat-1848	252	44	86.46	86.46	NUM
easat-1848	252	45	87.78	87.78	NUM
easat-1848	252	46	87.12	87.12	NUM
easat-1848	252	47	14.28	14.28	NUM
easat-1848	252	48	14.28	14.28	NUM
easat-1848	252	49	neural	neural	ADJ
easat-1848	252	50	network	network	NOUN
easat-1848	252	51	95.92	95.92	NUM
easat-1848	252	52	96.35	96.35	NUM
easat-1848	252	53	97.45	97.45	NUM
easat-1848	252	54	95.21	95.21	NUM
easat-1848	252	55	4.02	4.02	NUM
easat-1848	252	56	4.02	4.02	NUM
easat-1848	252	57	4.2	4.2	NUM
easat-1848	252	58	.	.	PUNCT
easat-1848	253	1	results	result	NOUN
easat-1848	253	2	computed	compute	VERB
easat-1848	253	3	with	with	ADP
easat-1848	253	4	relief	relief	NOUN
easat-1848	253	5	feature	feature	NOUN
easat-1848	253	6	selection	selection	NOUN
easat-1848	253	7	using	use	VERB
easat-1848	253	8	the	the	DET
easat-1848	253	9	feature	feature	NOUN
easat-1848	253	10	selection	selection	NOUN
easat-1848	253	11	algorithm	algorithm	NOUN
easat-1848	253	12	relief	relief	NOUN
easat-1848	253	13	,	,	PUNCT
easat-1848	253	14	10	10	NUM
easat-1848	253	15	features	feature	NOUN
easat-1848	253	16	were	be	AUX
easat-1848	253	17	obtained	obtain	VERB
easat-1848	253	18	from	from	ADP
easat-1848	253	19	the	the	DET
easat-1848	253	20	original	original	ADJ
easat-1848	253	21	set	set	NOUN
easat-1848	253	22	of	of	ADP
easat-1848	253	23	12	12	NUM
easat-1848	253	24	features	feature	NOUN
easat-1848	253	25	in	in	ADP
easat-1848	253	26	combined	combine	VERB
easat-1848	253	27	dataset	dataset	NOUN
easat-1848	253	28	.	.	PUNCT
easat-1848	254	1	table	table	PROPN
easat-1848	254	2	ii	ii	PROPN
easat-1848	254	3	reveals	reveal	VERB
easat-1848	254	4	the	the	DET
easat-1848	254	5	outcome	outcome	NOUN
easat-1848	254	6	of	of	ADP
easat-1848	254	7	relief	relief	NOUN
easat-1848	254	8	feature	feature	NOUN
easat-1848	254	9	selection	selection	NOUN
easat-1848	254	10	using	use	VERB
easat-1848	254	11	six	six	NUM
easat-1848	254	12	different	different	ADJ
easat-1848	254	13	ml	ml	NOUN
easat-1848	254	14	classifiers	classifier	NOUN
easat-1848	254	15	,	,	PUNCT
easat-1848	254	16	broken	break	VERB
easat-1848	254	17	down	down	ADP
easat-1848	254	18	into	into	ADP
easat-1848	254	19	six	six	NUM
easat-1848	254	20	essential	essential	ADJ
easat-1848	254	21	efficiency	efficiency	NOUN
easat-1848	254	22	measurement	measurement	NOUN
easat-1848	254	23	criteria	criterion	NOUN
easat-1848	254	24	.	.	PUNCT
easat-1848	255	1	the	the	DET
easat-1848	255	2	six	six	NUM
easat-1848	255	3	outcomes	outcome	NOUN
easat-1848	255	4	accuracy	accuracy	NOUN
easat-1848	255	5	,	,	PUNCT
easat-1848	255	6	precision	precision	NOUN
easat-1848	255	7	,	,	PUNCT
easat-1848	255	8	recall	recall	NOUN
easat-1848	255	9	,	,	PUNCT
easat-1848	255	10	f1score	f1score	NOUN
easat-1848	255	11	,	,	PUNCT
easat-1848	255	12	mse	mse	NOUN
easat-1848	255	13	,	,	PUNCT
easat-1848	255	14	and	and	CCONJ
easat-1848	255	15	mae	mae	PROPN
easat-1848	256	1	[	[	X
easat-1848	256	2	42	42	NUM
easat-1848	256	3	]	]	PUNCT
easat-1848	257	1	[	[	X
easat-1848	257	2	43	43	NUM
easat-1848	257	3	]	]	PUNCT
easat-1848	257	4	are	be	AUX
easat-1848	257	5	shown	show	VERB
easat-1848	257	6	graphically	graphically	ADV
easat-1848	257	7	for	for	ADP
easat-1848	257	8	the	the	DET
easat-1848	257	9	classifiers	classifier	NOUN
easat-1848	257	10	of	of	ADP
easat-1848	257	11	random	random	ADJ
easat-1848	257	12	forest	forest	NOUN
easat-1848	257	13	,	,	PUNCT
easat-1848	257	14	support	support	NOUN
easat-1848	257	15	vector	vector	NOUN
easat-1848	257	16	machine	machine	NOUN
easat-1848	257	17	,	,	PUNCT
easat-1848	257	18	naive	naive	ADJ
easat-1848	257	19	bayes	bayes	NOUN
easat-1848	257	20	,	,	PUNCT
easat-1848	257	21	logistic	logistic	ADJ
easat-1848	257	22	regression	regression	NOUN
easat-1848	257	23	,	,	PUNCT
easat-1848	257	24	knearest	knearest	NOUN
easat-1848	257	25	neighbour	neighbour	NOUN
easat-1848	257	26	respectively	respectively	ADV
easat-1848	257	27	,	,	PUNCT
easat-1848	257	28	in	in	ADP
easat-1848	257	29	figure	figure	NOUN
easat-1848	257	30	3	3	NUM
easat-1848	257	31	-	-	SYM
easat-1848	257	32	8	8	NUM
easat-1848	257	33	.	.	PUNCT
easat-1848	257	34	table	table	NOUN
easat-1848	257	35	2	2	NUM
easat-1848	257	36	.	.	X
easat-1848	257	37	results	result	NOUN
easat-1848	257	38	with	with	ADP
easat-1848	257	39	relief	relief	NOUN
easat-1848	257	40	feature	feature	NOUN
easat-1848	257	41	selection	selection	NOUN
easat-1848	257	42	method	method	NOUN
easat-1848	257	43	.	.	PUNCT
easat-1848	258	1	relief	relief	NOUN
easat-1848	258	2	feature	feature	NOUN
easat-1848	258	3	extraction	extraction	NOUN
easat-1848	258	4	model	model	NOUN
easat-1848	258	5	accuracy	accuracy	NOUN
easat-1848	258	6	precision	precision	NOUN
easat-1848	258	7	recall	recall	PROPN
easat-1848	258	8	f1score	f1score	PROPN
easat-1848	258	9	mse	mse	PROPN
easat-1848	258	10	mae	mae	PROPN
easat-1848	258	11	logistic	logistic	ADJ
easat-1848	258	12	regression	regression	NOUN
easat-1848	258	13	77.31	77.31	NUM
easat-1848	258	14	81.81	81.81	NUM
easat-1848	258	15	75.57	75.57	NUM
easat-1848	258	16	78.57	78.57	NUM
easat-1848	258	17	22.68	22.68	NUM
easat-1848	258	18	22.68	22.68	NUM
easat-1848	258	19	knn	knn	PROPN
easat-1848	258	20	78.15	78.15	NUM
easat-1848	258	21	82.64	82.64	NUM
easat-1848	258	22	76.33	76.33	NUM
easat-1848	258	23	79.36	79.36	NUM
easat-1848	258	24	21.84	21.84	NUM
easat-1848	258	25	21.84	21.84	NUM
easat-1848	258	26	random	random	ADJ
easat-1848	258	27	forest	forest	NOUN
easat-1848	258	28	81.09	81.09	NUM
easat-1848	258	29	86.44	86.44	NUM
easat-1848	258	30	77.86	77.86	NUM
easat-1848	258	31	81.92	81.92	NUM
easat-1848	258	32	18.9	18.9	NUM
easat-1848	258	33	18.9	18.9	NUM
easat-1848	258	34	svm	svm	NOUN
easat-1848	258	35	77.31	77.31	NUM
easat-1848	258	36	81.81	81.81	NUM
easat-1848	258	37	75.57	75.57	NUM
easat-1848	258	38	78.57	78.57	NUM
easat-1848	258	39	22.68	22.68	NUM
easat-1848	258	40	22.68	22.68	NUM
easat-1848	258	41	naive	naive	ADJ
easat-1848	258	42	bayes	baye	NOUN
easat-1848	258	43	78.99	78.99	NUM
easat-1848	258	44	84.03	84.03	NUM
easat-1848	258	45	76.33	76.33	NUM
easat-1848	258	46	80	80	NUM
easat-1848	258	47	21.00	21.00	NUM
easat-1848	258	48	21.00	21.00	NUM
easat-1848	258	49	neural	neural	ADJ
easat-1848	258	50	network	network	NOUN
easat-1848	258	51	82.56	82.56	NUM
easat-1848	258	52	88.47	88.47	NUM
easat-1848	258	53	79.86	79.86	NUM
easat-1848	258	54	83.92	83.92	NUM
easat-1848	258	55	14.5	14.5	NUM
easat-1848	258	56	14.5	14.5	NUM
easat-1848	258	57	4.3	4.3	NUM
easat-1848	258	58	.	.	PUNCT
easat-1848	259	1	results	result	NOUN
easat-1848	259	2	computed	compute	VERB
easat-1848	259	3	with	with	ADP
easat-1848	259	4	pca	pca	NOUN
easat-1848	259	5	feature	feature	NOUN
easat-1848	259	6	selection	selection	NOUN
easat-1848	259	7	using	use	VERB
easat-1848	259	8	the	the	DET
easat-1848	259	9	feature	feature	NOUN
easat-1848	259	10	selection	selection	NOUN
easat-1848	259	11	technique	technique	NOUN
easat-1848	259	12	pca	pca	PROPN
easat-1848	259	13	,	,	PUNCT
easat-1848	259	14	nine	nine	NUM
easat-1848	259	15	features	feature	NOUN
easat-1848	259	16	were	be	AUX
easat-1848	259	17	obtained	obtain	VERB
easat-1848	259	18	from	from	ADP
easat-1848	259	19	the	the	DET
easat-1848	259	20	original	original	ADJ
easat-1848	259	21	set	set	NOUN
easat-1848	259	22	of	of	ADP
easat-1848	259	23	twelve	twelve	NUM
easat-1848	259	24	features	feature	NOUN
easat-1848	259	25	in	in	ADP
easat-1848	259	26	the	the	DET
easat-1848	259	27	combined	combine	VERB
easat-1848	259	28	dataset	dataset	NOUN
easat-1848	259	29	.	.	PUNCT
easat-1848	260	1	table	table	NOUN
easat-1848	260	2	iii	iii	PROPN
easat-1848	260	3	illustrates	illustrate	VERB
easat-1848	260	4	the	the	DET
easat-1848	260	5	result	result	NOUN
easat-1848	260	6	of	of	ADP
easat-1848	260	7	pca	pca	NOUN
easat-1848	260	8	feature	feature	NOUN
easat-1848	260	9	selection	selection	NOUN
easat-1848	260	10	using	use	VERB
easat-1848	260	11	six	six	NUM
easat-1848	260	12	different	different	ADJ
easat-1848	260	13	ml	ml	NOUN
easat-1848	260	14	classifiers	classifier	NOUN
easat-1848	260	15	,	,	PUNCT
easat-1848	260	16	broken	break	VERB
easat-1848	260	17	down	down	ADP
easat-1848	260	18	into	into	ADP
easat-1848	260	19	six	six	NUM
easat-1848	260	20	essential	essential	ADJ
easat-1848	260	21	efficiency	efficiency	NOUN
easat-1848	260	22	measurement	measurement	NOUN
easat-1848	260	23	criteria	criterion	NOUN
easat-1848	260	24	.	.	PUNCT
easat-1848	261	1	the	the	DET
easat-1848	261	2	six	six	NUM
easat-1848	261	3	outcomes	outcome	NOUN
easat-1848	261	4	such	such	ADJ
easat-1848	261	5	as	as	ADP
easat-1848	261	6	accuracy	accuracy	NOUN
easat-1848	261	7	,	,	PUNCT
easat-1848	261	8	precision	precision	NOUN
easat-1848	261	9	,	,	PUNCT
easat-1848	261	10	recall	recall	NOUN
easat-1848	261	11	,	,	PUNCT
easat-1848	261	12	f1score	f1score	NOUN
easat-1848	261	13	,	,	PUNCT
easat-1848	261	14	mse	mse	NOUN
easat-1848	261	15	,	,	PUNCT
easat-1848	261	16	and	and	CCONJ
easat-1848	261	17	mae	mae	PROPN
easat-1848	262	1	[	[	X
easat-1848	262	2	43	43	NUM
easat-1848	262	3	]	]	X
easat-1848	263	1	[	[	X
easat-1848	263	2	44	44	NUM
easat-1848	263	3	]	]	PUNCT
easat-1848	263	4	for	for	ADP
easat-1848	263	5	each	each	PRON
easat-1848	263	6	of	of	ADP
easat-1848	263	7	the	the	DET
easat-1848	263	8	following	follow	VERB
easat-1848	263	9	classifiers	classifier	NOUN
easat-1848	263	10	—	—	PUNCT
easat-1848	263	11	support	support	NOUN
easat-1848	263	12	vector	vector	NOUN
easat-1848	263	13	machine	machine	NOUN
easat-1848	263	14	,	,	PUNCT
easat-1848	263	15	naive	naive	ADJ
easat-1848	263	16	bayes	bayes	NOUN
easat-1848	263	17	,	,	PUNCT
easat-1848	263	18	random	random	ADJ
easat-1848	263	19	forest	forest	NOUN
easat-1848	263	20	,	,	PUNCT
easat-1848	263	21	k	k	X
easat-1848	263	22	-	-	PUNCT
easat-1848	263	23	nearest	near	ADJ
easat-1848	263	24	neighbour	neighbour	NOUN
easat-1848	263	25	,	,	PUNCT
easat-1848	263	26	logistic	logistic	ADJ
easat-1848	263	27	regression	regression	NOUN
easat-1848	263	28	,	,	PUNCT
easat-1848	263	29	neural	neural	ADJ
easat-1848	263	30	network	network	NOUN
easat-1848	263	31	are	be	AUX
easat-1848	263	32	shown	show	VERB
easat-1848	263	33	graphically	graphically	ADV
easat-1848	263	34	in	in	ADP
easat-1848	263	35	figures	figure	NOUN
easat-1848	263	36	3	3	NUM
easat-1848	263	37	-	-	SYM
easat-1848	263	38	8	8	NUM
easat-1848	263	39	.	.	NOUN
easat-1848	263	40	1463	1463	NUM
easat-1848	263	41	edelweiss	edelweiss	PROPN
easat-1848	263	42	applied	apply	VERB
easat-1848	263	43	science	science	NOUN
easat-1848	263	44	and	and	CCONJ
easat-1848	263	45	technology	technology	NOUN
easat-1848	263	46	issn	issn	PROPN
easat-1848	263	47	:	:	PUNCT
easat-1848	263	48	2576	2576	NUM
easat-1848	263	49	-	-	SYM
easat-1848	263	50	8484	8484	NUM
easat-1848	263	51	vol	vol	NOUN
easat-1848	263	52	.	.	PROPN
easat-1848	263	53	8	8	NUM
easat-1848	263	54	,	,	PUNCT
easat-1848	263	55	no	no	INTJ
easat-1848	263	56	.	.	NOUN
easat-1848	263	57	5	5	NUM
easat-1848	263	58	:	:	SYM
easat-1848	263	59	1445	1445	NUM
easat-1848	263	60	-	-	SYM
easat-1848	263	61	1471	1471	NUM
easat-1848	263	62	,	,	PUNCT
easat-1848	263	63	2024	2024	NUM
easat-1848	263	64	doi	doi	NOUN
easat-1848	263	65	:	:	PUNCT
easat-1848	263	66	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	263	67	©	©	PROPN
easat-1848	263	68	2024	2024	NUM
easat-1848	263	69	by	by	ADP
easat-1848	263	70	the	the	DET
easat-1848	263	71	authors	author	NOUN
easat-1848	263	72	;	;	PUNCT
easat-1848	263	73	licensee	licensee	PROPN
easat-1848	263	74	learning	learn	VERB
easat-1848	263	75	gate	gate	NOUN
easat-1848	263	76	table	table	NOUN
easat-1848	263	77	3	3	PROPN
easat-1848	263	78	.	.	PUNCT
easat-1848	263	79	results	result	NOUN
easat-1848	263	80	with	with	ADP
easat-1848	263	81	pca	pca	NOUN
easat-1848	263	82	feature	feature	NOUN
easat-1848	263	83	selection	selection	NOUN
easat-1848	263	84	method	method	NOUN
easat-1848	263	85	.	.	PUNCT
easat-1848	264	1	pca	pca	NOUN
easat-1848	264	2	feature	feature	NOUN
easat-1848	264	3	extraction	extraction	NOUN
easat-1848	264	4	model	model	NOUN
easat-1848	264	5	accuracy	accuracy	NOUN
easat-1848	264	6	precision	precision	NOUN
easat-1848	264	7	recall	recall	PROPN
easat-1848	264	8	f1score	f1score	PROPN
easat-1848	264	9	mse	mse	PROPN
easat-1848	264	10	mae	mae	PROPN
easat-1848	264	11	logistic	logistic	PROPN
easat-1848	264	12	regression	regression	NOUN
easat-1848	264	13	84.87	84.87	NUM
easat-1848	264	14	85.18	85.18	NUM
easat-1848	264	15	87.78	87.78	NUM
easat-1848	264	16	86.46	86.46	NUM
easat-1848	264	17	15.12	15.12	NUM
easat-1848	264	18	15.12	15.12	NUM
easat-1848	264	19	knn	knn	PROPN
easat-1848	264	20	82.77	82.77	NUM
easat-1848	264	21	84.09	84.09	NUM
easat-1848	264	22	84.73	84.73	NUM
easat-1848	264	23	84.41	84.41	NUM
easat-1848	264	24	17.22	17.22	NUM
easat-1848	264	25	17.22	17.22	NUM
easat-1848	264	26	random	random	ADJ
easat-1848	264	27	forest	forest	NOUN
easat-1848	264	28	90.33	90.33	NUM
easat-1848	264	29	89.70	89.70	NUM
easat-1848	264	30	93.12	93.12	NUM
easat-1848	264	31	91.38	91.38	NUM
easat-1848	264	32	9.66	9.66	NUM
easat-1848	264	33	9.66	9.66	NUM
easat-1848	264	34	svm	svm	PROPN
easat-1848	264	35	85.29	85.29	NUM
easat-1848	264	36	85.29	85.29	NUM
easat-1848	264	37	88.54	88.54	NUM
easat-1848	264	38	86.89	86.89	NUM
easat-1848	264	39	14.70	14.70	NUM
easat-1848	264	40	14.70	14.70	NUM
easat-1848	264	41	naive	naive	ADJ
easat-1848	264	42	bayes	baye	NOUN
easat-1848	264	43	83.61	83.61	NUM
easat-1848	264	44	84.32	84.32	NUM
easat-1848	264	45	86.25	86.25	NUM
easat-1848	264	46	85.28	85.28	NUM
easat-1848	264	47	16.38	16.38	NUM
easat-1848	264	48	16.38	16.38	NUM
easat-1848	264	49	neural	neural	ADJ
easat-1848	264	50	network	network	NOUN
easat-1848	264	51	91.37	91.37	NUM
easat-1848	264	52	90.45	90.45	NUM
easat-1848	264	53	95.62	95.62	NUM
easat-1848	264	54	90.27	90.27	NUM
easat-1848	264	55	8.46	8.46	NUM
easat-1848	264	56	8.46	8.46	NUM
easat-1848	264	57	4.4	4.4	NUM
easat-1848	264	58	.	.	PUNCT
easat-1848	265	1	results	result	NOUN
easat-1848	265	2	computed	compute	VERB
easat-1848	265	3	with	with	ADP
easat-1848	265	4	rfe	rfe	PROPN
easat-1848	265	5	feature	feature	NOUN
easat-1848	265	6	selection	selection	NOUN
easat-1848	265	7	after	after	ADP
easat-1848	265	8	deploying	deploy	VERB
easat-1848	265	9	feature	feature	NOUN
easat-1848	265	10	selection	selection	NOUN
easat-1848	265	11	technique	technique	NOUN
easat-1848	265	12	rfe	rfe	NOUN
easat-1848	265	13	,	,	PUNCT
easat-1848	265	14	ten	ten	NUM
easat-1848	265	15	features	feature	NOUN
easat-1848	265	16	were	be	AUX
easat-1848	265	17	derived	derive	VERB
easat-1848	265	18	from	from	ADP
easat-1848	265	19	the	the	DET
easat-1848	265	20	12	12	NUM
easat-1848	265	21	initial	initial	ADJ
easat-1848	265	22	features	feature	NOUN
easat-1848	265	23	from	from	ADP
easat-1848	265	24	the	the	DET
easat-1848	265	25	combined	combine	VERB
easat-1848	265	26	dataset	dataset	NOUN
easat-1848	265	27	.	.	PUNCT
easat-1848	266	1	table	table	NOUN
easat-1848	266	2	iv	iv	NUM
easat-1848	266	3	shows	show	VERB
easat-1848	266	4	the	the	DET
easat-1848	266	5	rfe	rfe	PROPN
easat-1848	266	6	feature	feature	NOUN
easat-1848	266	7	selection	selection	NOUN
easat-1848	266	8	performance	performance	NOUN
easat-1848	266	9	in	in	ADP
easat-1848	266	10	terms	term	NOUN
easat-1848	266	11	of	of	ADP
easat-1848	266	12	six	six	NUM
easat-1848	266	13	essential	essential	ADJ
easat-1848	266	14	efficiency	efficiency	NOUN
easat-1848	266	15	measurement	measurement	NOUN
easat-1848	266	16	parameters	parameter	NOUN
easat-1848	266	17	when	when	SCONJ
easat-1848	266	18	six	six	NUM
easat-1848	266	19	ml	ml	NOUN
easat-1848	266	20	classifiers	classifier	NOUN
easat-1848	266	21	are	be	AUX
easat-1848	266	22	employed	employ	VERB
easat-1848	266	23	.	.	PUNCT
easat-1848	267	1	for	for	ADP
easat-1848	267	2	the	the	DET
easat-1848	267	3	classifiers	classifier	NOUN
easat-1848	267	4	of	of	ADP
easat-1848	267	5	neural	neural	ADJ
easat-1848	267	6	network	network	NOUN
easat-1848	267	7	,	,	PUNCT
easat-1848	267	8	support	support	NOUN
easat-1848	267	9	vector	vector	NOUN
easat-1848	267	10	machine	machine	NOUN
easat-1848	267	11	,	,	PUNCT
easat-1848	267	12	naive	naive	ADJ
easat-1848	267	13	bayes	bayes	NOUN
easat-1848	267	14	,	,	PUNCT
easat-1848	267	15	random	random	ADJ
easat-1848	267	16	forest	forest	NOUN
easat-1848	267	17	,	,	PUNCT
easat-1848	267	18	logistic	logistic	ADJ
easat-1848	267	19	regression	regression	NOUN
easat-1848	267	20	,	,	PUNCT
easat-1848	267	21	k	k	X
easat-1848	267	22	-	-	PUNCT
easat-1848	267	23	nearest	near	ADJ
easat-1848	267	24	neighbour	neighbour	NOUN
easat-1848	267	25	,	,	PUNCT
easat-1848	267	26	respectively	respectively	ADV
easat-1848	267	27	,	,	PUNCT
easat-1848	267	28	the	the	DET
easat-1848	267	29	six	six	NUM
easat-1848	267	30	outcomes	outcome	NOUN
easat-1848	267	31	such	such	ADJ
easat-1848	267	32	as	as	ADP
easat-1848	267	33	recall	recall	NOUN
easat-1848	267	34	,	,	PUNCT
easat-1848	267	35	accuracy	accuracy	NOUN
easat-1848	267	36	,	,	PUNCT
easat-1848	267	37	precision	precision	NOUN
easat-1848	267	38	,	,	PUNCT
easat-1848	267	39	f1score	f1score	NOUN
easat-1848	267	40	,	,	PUNCT
easat-1848	267	41	mse	mse	NOUN
easat-1848	267	42	,	,	PUNCT
easat-1848	267	43	and	and	CCONJ
easat-1848	267	44	mae	mae	PROPN
easat-1848	268	1	[	[	X
easat-1848	268	2	44	44	NUM
easat-1848	268	3	]	]	PUNCT
easat-1848	269	1	[	[	X
easat-1848	269	2	45	45	NUM
easat-1848	269	3	]	]	PUNCT
easat-1848	269	4	are	be	AUX
easat-1848	269	5	shown	show	VERB
easat-1848	269	6	graphically	graphically	ADV
easat-1848	269	7	in	in	ADP
easat-1848	269	8	figure	figure	NOUN
easat-1848	269	9	3	3	NUM
easat-1848	269	10	-	-	SYM
easat-1848	269	11	8	8	NUM
easat-1848	269	12	.	.	PUNCT
easat-1848	269	13	table	table	NOUN
easat-1848	269	14	4	4	NUM
easat-1848	269	15	.	.	PUNCT
easat-1848	269	16	results	result	NOUN
easat-1848	269	17	with	with	ADP
easat-1848	269	18	rfe	rfe	PROPN
easat-1848	269	19	feature	feature	NOUN
easat-1848	269	20	selection	selection	NOUN
easat-1848	269	21	method	method	NOUN
easat-1848	269	22	.	.	PUNCT
easat-1848	270	1	rfe	rfe	NOUN
easat-1848	270	2	feature	feature	NOUN
easat-1848	270	3	extraction	extraction	NOUN
easat-1848	270	4	model	model	NOUN
easat-1848	270	5	accuracy	accuracy	NOUN
easat-1848	270	6	precision	precision	NOUN
easat-1848	270	7	recall	recall	PROPN
easat-1848	270	8	f1score	f1score	PROPN
easat-1848	270	9	mse	mse	PROPN
easat-1848	270	10	mae	mae	PROPN
easat-1848	270	11	logistic	logistic	ADJ
easat-1848	270	12	regression	regression	NOUN
easat-1848	270	13	85.71	85.71	NUM
easat-1848	270	14	87.59	87.59	NUM
easat-1848	270	15	86.25	86.25	NUM
easat-1848	270	16	86.92	86.92	NUM
easat-1848	270	17	14.28	14.28	NUM
easat-1848	270	18	14.28	14.28	NUM
easat-1848	270	19	knn	knn	PROPN
easat-1848	270	20	79.83	79.83	NUM
easat-1848	270	21	78.23	78.23	NUM
easat-1848	270	22	87.78	87.78	NUM
easat-1848	270	23	82.73	82.73	NUM
easat-1848	270	24	20.16	20.16	NUM
easat-1848	270	25	20.16	20.16	NUM
easat-1848	270	26	random	random	ADJ
easat-1848	270	27	forest	forest	NOUN
easat-1848	270	28	85.29	85.29	NUM
easat-1848	270	29	85.82	85.82	NUM
easat-1848	270	30	87.78	87.78	NUM
easat-1848	270	31	86.79	86.79	NUM
easat-1848	270	32	14.7	14.7	NUM
easat-1848	270	33	14.7	14.7	NUM
easat-1848	270	34	svm	svm	NOUN
easat-1848	270	35	86.55	86.55	NUM
easat-1848	270	36	86.13	86.13	NUM
easat-1848	270	37	90.07	90.07	NUM
easat-1848	270	38	88.05	88.05	NUM
easat-1848	270	39	13.44	13.44	NUM
easat-1848	270	40	13.44	13.44	NUM
easat-1848	270	41	naive	naive	ADJ
easat-1848	270	42	bayes	bayes	NOUN
easat-1848	270	43	83.19	83.19	NUM
easat-1848	270	44	86.4	86.4	NUM
easat-1848	270	45	82.44	82.44	NUM
easat-1848	270	46	84.37	84.37	NUM
easat-1848	270	47	16.8	16.8	NUM
easat-1848	270	48	16.8	16.8	NUM
easat-1848	270	49	neural	neural	ADJ
easat-1848	270	50	network	network	NOUN
easat-1848	270	51	87.77	87.77	NUM
easat-1848	270	52	87.82	87.82	NUM
easat-1848	270	53	89.78	89.78	NUM
easat-1848	270	54	88.34	88.34	NUM
easat-1848	270	55	13.2	13.2	NUM
easat-1848	270	56	13.2	13.2	NUM
easat-1848	270	57	4.5	4.5	NUM
easat-1848	270	58	.	.	PUNCT
easat-1848	271	1	results	result	NOUN
easat-1848	271	2	computed	compute	VERB
easat-1848	271	3	with	with	ADP
easat-1848	271	4	mr	mr	PROPN
easat-1848	271	5	-	-	PUNCT
easat-1848	271	6	mr	mr	PROPN
easat-1848	271	7	feature	feature	NOUN
easat-1848	271	8	selection	selection	NOUN
easat-1848	271	9	out	out	ADP
easat-1848	271	10	of	of	ADP
easat-1848	271	11	the	the	DET
easat-1848	271	12	original	original	ADJ
easat-1848	271	13	features	feature	NOUN
easat-1848	271	14	set	set	VERB
easat-1848	271	15	of	of	ADP
easat-1848	271	16	12	12	NUM
easat-1848	271	17	features	feature	NOUN
easat-1848	271	18	from	from	ADP
easat-1848	271	19	the	the	DET
easat-1848	271	20	combined	combine	VERB
easat-1848	271	21	dataset	dataset	NOUN
easat-1848	271	22	,	,	PUNCT
easat-1848	271	23	11	11	NUM
easat-1848	271	24	features	feature	NOUN
easat-1848	271	25	have	have	AUX
easat-1848	271	26	been	be	AUX
easat-1848	271	27	obtained	obtain	VERB
easat-1848	271	28	utilizing	utilize	VERB
easat-1848	271	29	the	the	DET
easat-1848	271	30	mr	mr	PROPN
easat-1848	271	31	-	-	PUNCT
easat-1848	271	32	mr	mr	PROPN
easat-1848	271	33	feature	feature	NOUN
easat-1848	271	34	selection	selection	NOUN
easat-1848	271	35	technique	technique	NOUN
easat-1848	271	36	.	.	PUNCT
easat-1848	272	1	table	table	NOUN
easat-1848	272	2	v	v	NOUN
easat-1848	272	3	illustrates	illustrate	VERB
easat-1848	272	4	the	the	DET
easat-1848	272	5	results	result	NOUN
easat-1848	272	6	of	of	ADP
easat-1848	272	7	mr	mr	PROPN
easat-1848	272	8	-	-	PUNCT
easat-1848	272	9	mr	mr	PROPN
easat-1848	272	10	feature	feature	NOUN
easat-1848	272	11	selection	selection	NOUN
easat-1848	272	12	method	method	NOUN
easat-1848	272	13	using	use	VERB
easat-1848	272	14	six	six	NUM
easat-1848	272	15	real	real	ADJ
easat-1848	272	16	-	-	PUNCT
easat-1848	272	17	world	world	NOUN
easat-1848	272	18	deep	deep	ADJ
easat-1848	272	19	learning	learning	NOUN
easat-1848	272	20	and	and	CCONJ
easat-1848	272	21	machine	machine	NOUN
easat-1848	272	22	learning	learn	VERB
easat-1848	272	23	classifiers	classifier	NOUN
easat-1848	272	24	,	,	PUNCT
easat-1848	272	25	broken	break	VERB
easat-1848	272	26	down	down	ADP
easat-1848	272	27	into	into	ADP
easat-1848	272	28	six	six	NUM
easat-1848	272	29	essential	essential	ADJ
easat-1848	272	30	efficiency	efficiency	NOUN
easat-1848	272	31	measures	measure	NOUN
easat-1848	272	32	.	.	PUNCT
easat-1848	273	1	the	the	DET
easat-1848	273	2	six	six	NUM
easat-1848	273	3	outcomes	outcome	NOUN
easat-1848	273	4	such	such	ADJ
easat-1848	273	5	as	as	ADP
easat-1848	273	6	accuracy	accuracy	NOUN
easat-1848	273	7	,	,	PUNCT
easat-1848	273	8	recall	recall	NOUN
easat-1848	273	9	,	,	PUNCT
easat-1848	273	10	precision	precision	NOUN
easat-1848	273	11	,	,	PUNCT
easat-1848	273	12	f1score	f1score	NOUN
easat-1848	273	13	,	,	PUNCT
easat-1848	273	14	mse	mse	NOUN
easat-1848	273	15	,	,	PUNCT
easat-1848	273	16	and	and	CCONJ
easat-1848	273	17	mae	mae	PROPN
easat-1848	274	1	[	[	X
easat-1848	274	2	44	44	NUM
easat-1848	274	3	]	]	PUNCT
easat-1848	275	1	[	[	X
easat-1848	275	2	45	45	NUM
easat-1848	275	3	]	]	PUNCT
easat-1848	275	4	for	for	ADP
easat-1848	275	5	k	k	NOUN
easat-1848	275	6	-	-	PUNCT
easat-1848	275	7	nearest	near	ADJ
easat-1848	275	8	neighbour	neighbour	NOUN
easat-1848	275	9	,	,	PUNCT
easat-1848	275	10	neural	neural	ADJ
easat-1848	275	11	network	network	NOUN
easat-1848	275	12	,	,	PUNCT
easat-1848	275	13	support	support	NOUN
easat-1848	275	14	vector	vector	NOUN
easat-1848	275	15	machine	machine	NOUN
easat-1848	275	16	,	,	PUNCT
easat-1848	275	17	random	random	ADJ
easat-1848	275	18	forest	forest	NOUN
easat-1848	275	19	,	,	PUNCT
easat-1848	275	20	naive	naive	ADJ
easat-1848	275	21	bayes	bayes	NOUN
easat-1848	275	22	,	,	PUNCT
easat-1848	275	23	logistic	logistic	ADJ
easat-1848	275	24	regression	regression	NOUN
easat-1848	275	25	classifiers	classifier	NOUN
easat-1848	275	26	are	be	AUX
easat-1848	275	27	shown	show	VERB
easat-1848	275	28	graphically	graphically	ADV
easat-1848	275	29	in	in	ADP
easat-1848	275	30	figure	figure	NOUN
easat-1848	275	31	3	3	NUM
easat-1848	275	32	.	.	PUNCT
easat-1848	275	33	table	table	NOUN
easat-1848	275	34	5	5	NUM
easat-1848	275	35	.	.	PUNCT
easat-1848	275	36	results	result	NOUN
easat-1848	275	37	with	with	ADP
easat-1848	275	38	mr	mr	PROPN
easat-1848	275	39	-	-	PUNCT
easat-1848	275	40	mr	mr	PROPN
easat-1848	275	41	feature	feature	NOUN
easat-1848	275	42	selection	selection	NOUN
easat-1848	275	43	method	method	NOUN
easat-1848	275	44	.	.	PUNCT
easat-1848	276	1	mr	mr	PROPN
easat-1848	276	2	-	-	PUNCT
easat-1848	276	3	mr	mr	PROPN
easat-1848	276	4	feature	feature	NOUN
easat-1848	276	5	extraction	extraction	NOUN
easat-1848	276	6	model	model	NOUN
easat-1848	276	7	accuracy	accuracy	NOUN
easat-1848	276	8	precision	precision	NOUN
easat-1848	276	9	recall	recall	PROPN
easat-1848	276	10	f1score	f1score	PROPN
easat-1848	276	11	mse	mse	PROPN
easat-1848	276	12	mae	mae	PROPN
easat-1848	276	13	logistic	logistic	ADJ
easat-1848	276	14	regression	regression	NOUN
easat-1848	276	15	80.25	80.25	NUM
easat-1848	276	16	80.43	80.43	NUM
easat-1848	276	17	84.73	84.73	NUM
easat-1848	276	18	82.52	82.52	NUM
easat-1848	276	19	19.74	19.74	NUM
easat-1848	276	20	19.74	19.74	NUM
easat-1848	276	21	knn	knn	NOUN
easat-1848	276	22	78.15	78.15	NUM
easat-1848	276	23	80.62	80.62	NUM
easat-1848	276	24	79.38	79.38	NUM
easat-1848	276	25	80	80	NUM
easat-1848	276	26	21.84	21.84	NUM
easat-1848	276	27	21.84	21.84	NUM
easat-1848	276	28	random	random	ADJ
easat-1848	276	29	forest	forest	NOUN
easat-1848	276	30	90.33	90.33	NUM
easat-1848	276	31	90.29	90.29	NUM
easat-1848	276	32	92.36	92.36	NUM
easat-1848	276	33	91.32	91.32	NUM
easat-1848	276	34	9.6	9.6	NUM
easat-1848	276	35	9.6	9.6	NUM
easat-1848	276	36	svm	svm	PROPN
easat-1848	276	37	84.87	84.87	NUM
easat-1848	276	38	86.82	86.82	NUM
easat-1848	276	39	85.49	85.49	NUM
easat-1848	276	40	86.15	86.15	NUM
easat-1848	276	41	15.12	15.12	NUM
easat-1848	276	42	15.12	15.12	NUM
easat-1848	276	43	naive	naive	ADJ
easat-1848	276	44	bayes	bayes	NOUN
easat-1848	276	45	79.41	79.41	NUM
easat-1848	276	46	81.53	81.53	NUM
easat-1848	276	47	80.91	80.91	NUM
easat-1848	276	48	81.22	81.22	NUM
easat-1848	276	49	20.58	20.58	NUM
easat-1848	276	50	20.58	20.58	NUM
easat-1848	276	51	neural	neural	ADJ
easat-1848	276	52	network	network	NOUN
easat-1848	276	53	91.24	91.24	NUM
easat-1848	276	54	91.12	91.12	NUM
easat-1848	276	55	93.16	93.16	NUM
easat-1848	276	56	92.62	92.62	NUM
easat-1848	276	57	8.11	8.11	NUM
easat-1848	276	58	8.11	8.11	NUM
easat-1848	276	59	1464	1464	NUM
easat-1848	276	60	edelweiss	edelweiss	PROPN
easat-1848	276	61	applied	apply	VERB
easat-1848	276	62	science	science	NOUN
easat-1848	276	63	and	and	CCONJ
easat-1848	276	64	technology	technology	NOUN
easat-1848	276	65	issn	issn	PROPN
easat-1848	276	66	:	:	PUNCT
easat-1848	276	67	2576	2576	NUM
easat-1848	276	68	-	-	SYM
easat-1848	276	69	8484	8484	NUM
easat-1848	276	70	vol	vol	NOUN
easat-1848	276	71	.	.	PROPN
easat-1848	276	72	8	8	NUM
easat-1848	276	73	,	,	PUNCT
easat-1848	276	74	no	no	INTJ
easat-1848	276	75	.	.	NOUN
easat-1848	277	1	5	5	NUM
easat-1848	277	2	:	:	SYM
easat-1848	277	3	1445	1445	NUM
easat-1848	277	4	-	-	SYM
easat-1848	277	5	1471	1471	NUM
easat-1848	277	6	,	,	PUNCT
easat-1848	277	7	2024	2024	NUM
easat-1848	277	8	doi	doi	NOUN
easat-1848	277	9	:	:	PUNCT
easat-1848	277	10	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	277	11	©	©	PROPN
easat-1848	277	12	2024	2024	NUM
easat-1848	277	13	by	by	ADP
easat-1848	277	14	the	the	DET
easat-1848	277	15	authors	author	NOUN
easat-1848	277	16	;	;	PUNCT
easat-1848	277	17	licensee	licensee	PROPN
easat-1848	277	18	learning	learning	NOUN
easat-1848	277	19	gate	gate	NOUN
easat-1848	277	20	figure.3	figure.3	PROPN
easat-1848	277	21	below	below	ADV
easat-1848	277	22	shows	show	VERB
easat-1848	277	23	the	the	DET
easat-1848	277	24	accuracy	accuracy	NOUN
easat-1848	277	25	of	of	ADP
easat-1848	277	26	deep	deep	ADJ
easat-1848	277	27	learning	learning	NOUN
easat-1848	277	28	and	and	CCONJ
easat-1848	277	29	machine	machine	NOUN
easat-1848	277	30	learning	learn	VERB
easat-1848	277	31	algorithms	algorithm	NOUN
easat-1848	277	32	after	after	ADP
easat-1848	277	33	each	each	DET
easat-1848	277	34	feature	feature	NOUN
easat-1848	277	35	selection	selection	NOUN
easat-1848	277	36	method	method	NOUN
easat-1848	277	37	.	.	PUNCT
easat-1848	278	1	after	after	ADP
easat-1848	278	2	deploying	deploy	VERB
easat-1848	278	3	feature	feature	NOUN
easat-1848	278	4	selection	selection	NOUN
easat-1848	278	5	method	method	NOUN
easat-1848	278	6	lasso	lasso	NOUN
easat-1848	278	7	,	,	PUNCT
easat-1848	278	8	accuracy	accuracy	NOUN
easat-1848	278	9	of	of	ADP
easat-1848	278	10	deep	deep	ADJ
easat-1848	278	11	learning	learning	NOUN
easat-1848	278	12	and	and	CCONJ
easat-1848	278	13	machine	machine	NOUN
easat-1848	278	14	learning	learn	VERB
easat-1848	278	15	classifiers	classifier	NOUN
easat-1848	278	16	such	such	ADJ
easat-1848	278	17	as	as	ADP
easat-1848	278	18	logistic	logistic	ADJ
easat-1848	278	19	regression	regression	NOUN
easat-1848	278	20	,	,	PUNCT
easat-1848	278	21	random	random	ADJ
easat-1848	278	22	forest	forest	NOUN
easat-1848	278	23	,	,	PUNCT
easat-1848	278	24	support	support	NOUN
easat-1848	278	25	vector	vector	NOUN
easat-1848	278	26	machine	machine	NOUN
easat-1848	278	27	,	,	PUNCT
easat-1848	278	28	naïve	naïve	ADJ
easat-1848	278	29	bayes	bayes	NOUN
easat-1848	278	30	,	,	PUNCT
easat-1848	278	31	k	k	NOUN
easat-1848	278	32	-	-	PUNCT
easat-1848	278	33	nearest	near	ADJ
easat-1848	278	34	neighbour	neighbour	NOUN
easat-1848	278	35	,	,	PUNCT
easat-1848	278	36	and	and	CCONJ
easat-1848	278	37	neural	neural	ADJ
easat-1848	278	38	network	network	NOUN
easat-1848	278	39	are	be	AUX
easat-1848	278	40	86.13	86.13	NUM
easat-1848	278	41	,	,	PUNCT
easat-1848	278	42	95.37	95.37	NUM
easat-1848	278	43	,	,	PUNCT
easat-1848	278	44	89.07	89.07	NUM
easat-1848	278	45	,	,	PUNCT
easat-1848	278	46	85.71	85.71	NUM
easat-1848	278	47	,	,	PUNCT
easat-1848	278	48	88.65	88.65	NUM
easat-1848	278	49	,	,	PUNCT
easat-1848	278	50	95.92	95.92	NUM
easat-1848	278	51	respectively	respectively	ADV
easat-1848	278	52	.	.	PUNCT
easat-1848	279	1	after	after	ADP
easat-1848	279	2	deploying	deploy	VERB
easat-1848	279	3	feature	feature	NOUN
easat-1848	279	4	selection	selection	NOUN
easat-1848	279	5	method	method	NOUN
easat-1848	279	6	relief	relief	NOUN
easat-1848	279	7	,	,	PUNCT
easat-1848	279	8	the	the	DET
easat-1848	279	9	accuracy	accuracy	NOUN
easat-1848	279	10	of	of	ADP
easat-1848	279	11	machine	machine	NOUN
easat-1848	279	12	learning	learn	VERB
easat-1848	279	13	classifiers	classifier	NOUN
easat-1848	279	14	such	such	ADJ
easat-1848	279	15	as	as	ADP
easat-1848	279	16	k	k	NOUN
easat-1848	279	17	-	-	PUNCT
easat-1848	279	18	nearest	near	ADJ
easat-1848	279	19	neighbour	neighbour	NOUN
easat-1848	279	20	,	,	PUNCT
easat-1848	279	21	random	random	ADJ
easat-1848	279	22	forest	forest	NOUN
easat-1848	279	23	,	,	PUNCT
easat-1848	279	24	support	support	NOUN
easat-1848	279	25	vector	vector	NOUN
easat-1848	279	26	machine	machine	NOUN
easat-1848	279	27	,	,	PUNCT
easat-1848	279	28	naïve	naïve	ADJ
easat-1848	279	29	bayes	bayes	NOUN
easat-1848	279	30	,	,	PUNCT
easat-1848	279	31	logistic	logistic	ADJ
easat-1848	279	32	regression	regression	NOUN
easat-1848	279	33	and	and	CCONJ
easat-1848	279	34	neural	neural	ADJ
easat-1848	279	35	network	network	NOUN
easat-1848	279	36	are	be	AUX
easat-1848	279	37	78.15	78.15	NUM
easat-1848	279	38	,	,	PUNCT
easat-1848	279	39	81.09	81.09	NUM
easat-1848	279	40	,	,	PUNCT
easat-1848	279	41	77.31	77.31	NUM
easat-1848	279	42	,	,	PUNCT
easat-1848	279	43	78.99	78.99	NUM
easat-1848	279	44	,	,	PUNCT
easat-1848	279	45	77.31	77.31	NUM
easat-1848	279	46	,	,	PUNCT
easat-1848	279	47	82.56	82.56	NUM
easat-1848	279	48	respectively	respectively	ADV
easat-1848	279	49	.	.	PUNCT
easat-1848	280	1	with	with	ADP
easat-1848	280	2	pca	pca	PROPN
easat-1848	280	3	,	,	PUNCT
easat-1848	280	4	the	the	DET
easat-1848	280	5	accuracy	accuracy	NOUN
easat-1848	280	6	of	of	ADP
easat-1848	280	7	various	various	ADJ
easat-1848	280	8	machine	machine	NOUN
easat-1848	280	9	learning	learning	NOUN
easat-1848	280	10	and	and	CCONJ
easat-1848	280	11	deep	deep	ADJ
easat-1848	280	12	learning	learning	NOUN
easat-1848	280	13	classifiers	classifier	NOUN
easat-1848	280	14	such	such	ADJ
easat-1848	280	15	as	as	ADP
easat-1848	280	16	logistic	logistic	ADJ
easat-1848	280	17	regression	regression	NOUN
easat-1848	280	18	,	,	PUNCT
easat-1848	280	19	random	random	ADJ
easat-1848	280	20	forest	forest	NOUN
easat-1848	280	21	,	,	PUNCT
easat-1848	280	22	k	k	X
easat-1848	280	23	-	-	PUNCT
easat-1848	280	24	nearest	near	ADJ
easat-1848	280	25	neighbour	neighbour	NOUN
easat-1848	280	26	,	,	PUNCT
easat-1848	280	27	naïve	naïve	ADJ
easat-1848	280	28	bayes	bayes	NOUN
easat-1848	280	29	,	,	PUNCT
easat-1848	280	30	support	support	VERB
easat-1848	280	31	vector	vector	NOUN
easat-1848	280	32	machine	machine	NOUN
easat-1848	280	33	,	,	PUNCT
easat-1848	280	34	and	and	CCONJ
easat-1848	280	35	neural	neural	ADJ
easat-1848	280	36	network	network	NOUN
easat-1848	280	37	are	be	AUX
easat-1848	280	38	84.87	84.87	NUM
easat-1848	280	39	,	,	PUNCT
easat-1848	280	40	90.33	90.33	NUM
easat-1848	280	41	,	,	PUNCT
easat-1848	280	42	82.77	82.77	NUM
easat-1848	280	43	,	,	PUNCT
easat-1848	280	44	85.29	85.29	NUM
easat-1848	280	45	,	,	PUNCT
easat-1848	280	46	83.61	83.61	NUM
easat-1848	280	47	,	,	PUNCT
easat-1848	280	48	91.37	91.37	NUM
easat-1848	280	49	respectively	respectively	ADV
easat-1848	280	50	.	.	PUNCT
easat-1848	281	1	using	use	VERB
easat-1848	281	2	rfe	rfe	PROPN
easat-1848	281	3	feature	feature	NOUN
easat-1848	281	4	selection	selection	NOUN
easat-1848	281	5	,	,	PUNCT
easat-1848	281	6	the	the	DET
easat-1848	281	7	accuracy	accuracy	NOUN
easat-1848	281	8	of	of	ADP
easat-1848	281	9	logistic	logistic	ADJ
easat-1848	281	10	regression	regression	NOUN
easat-1848	281	11	,	,	PUNCT
easat-1848	281	12	random	random	ADJ
easat-1848	281	13	forest	forest	NOUN
easat-1848	281	14	,	,	PUNCT
easat-1848	281	15	support	support	NOUN
easat-1848	281	16	vector	vector	NOUN
easat-1848	281	17	machine	machine	NOUN
easat-1848	281	18	,	,	PUNCT
easat-1848	281	19	naïve	naïve	ADJ
easat-1848	281	20	bayes	bayes	NOUN
easat-1848	281	21	,	,	PUNCT
easat-1848	281	22	k	k	NOUN
easat-1848	281	23	-	-	PUNCT
easat-1848	281	24	nearest	near	ADJ
easat-1848	281	25	neighbour	neighbour	NOUN
easat-1848	281	26	,	,	PUNCT
easat-1848	281	27	and	and	CCONJ
easat-1848	281	28	neural	neural	ADJ
easat-1848	281	29	network	network	NOUN
easat-1848	281	30	are	be	AUX
easat-1848	281	31	85.71	85.71	NUM
easat-1848	281	32	,	,	PUNCT
easat-1848	281	33	85.29	85.29	NUM
easat-1848	281	34	,	,	PUNCT
easat-1848	281	35	83.19	83.19	NUM
easat-1848	281	36	,	,	PUNCT
easat-1848	281	37	86.55	86.55	NUM
easat-1848	281	38	,	,	PUNCT
easat-1848	281	39	79.83	79.83	NUM
easat-1848	281	40	,	,	PUNCT
easat-1848	281	41	87.77	87.77	NUM
easat-1848	281	42	respectively	respectively	ADV
easat-1848	281	43	.	.	PUNCT
easat-1848	282	1	with	with	ADP
easat-1848	282	2	mr	mr	PROPN
easat-1848	282	3	-	-	PUNCT
easat-1848	282	4	mr	mr	PROPN
easat-1848	282	5	feature	feature	NOUN
easat-1848	282	6	selection	selection	NOUN
easat-1848	282	7	,	,	PUNCT
easat-1848	282	8	accuracy	accuracy	NOUN
easat-1848	282	9	of	of	ADP
easat-1848	282	10	k	k	NOUN
easat-1848	282	11	-	-	PUNCT
easat-1848	282	12	nearest	near	ADJ
easat-1848	282	13	neighbour	neighbour	NOUN
easat-1848	282	14	,	,	PUNCT
easat-1848	282	15	random	random	ADJ
easat-1848	282	16	forest	forest	NOUN
easat-1848	282	17	,	,	PUNCT
easat-1848	282	18	logistic	logistic	ADJ
easat-1848	282	19	regression	regression	NOUN
easat-1848	282	20	,	,	PUNCT
easat-1848	282	21	support	support	NOUN
easat-1848	282	22	vector	vector	NOUN
easat-1848	282	23	machine	machine	NOUN
easat-1848	282	24	,	,	PUNCT
easat-1848	282	25	naïve	naïve	ADJ
easat-1848	282	26	bayes	baye	NOUN
easat-1848	282	27	and	and	CCONJ
easat-1848	282	28	neural	neural	ADJ
easat-1848	282	29	network	network	NOUN
easat-1848	282	30	are	be	AUX
easat-1848	282	31	78.15	78.15	NUM
easat-1848	282	32	,	,	PUNCT
easat-1848	282	33	90.33	90.33	NUM
easat-1848	282	34	,	,	PUNCT
easat-1848	282	35	80.25	80.25	NUM
easat-1848	282	36	,	,	PUNCT
easat-1848	282	37	84.87	84.87	NUM
easat-1848	282	38	,	,	PUNCT
easat-1848	282	39	79.41	79.41	NUM
easat-1848	282	40	,	,	PUNCT
easat-1848	282	41	91.24	91.24	NUM
easat-1848	282	42	respectively	respectively	ADV
easat-1848	282	43	.	.	PUNCT
easat-1848	283	1	the	the	DET
easat-1848	283	2	random	random	ADJ
easat-1848	283	3	forest	forest	NOUN
easat-1848	283	4	algorithm	algorithm	NOUN
easat-1848	283	5	and	and	CCONJ
easat-1848	283	6	neural	neural	ADJ
easat-1848	283	7	network	network	NOUN
easat-1848	283	8	classifier	classifier	NOUN
easat-1848	283	9	implemented	implement	VERB
easat-1848	283	10	using	use	VERB
easat-1848	283	11	lasso	lasso	NOUN
easat-1848	283	12	feature	feature	NOUN
easat-1848	283	13	selection	selection	NOUN
easat-1848	283	14	technique	technique	NOUN
easat-1848	283	15	achieved	achieve	VERB
easat-1848	283	16	high	high	ADJ
easat-1848	283	17	performance	performance	NOUN
easat-1848	283	18	compared	compare	VERB
easat-1848	283	19	with	with	ADP
easat-1848	283	20	other	other	ADJ
easat-1848	283	21	algorithms	algorithm	NOUN
easat-1848	283	22	.	.	PUNCT
easat-1848	284	1	random	random	ADJ
easat-1848	284	2	forest	forest	NOUN
easat-1848	284	3	and	and	CCONJ
easat-1848	284	4	neural	neural	ADJ
easat-1848	284	5	network	network	NOUN
easat-1848	284	6	classifiers	classifier	NOUN
easat-1848	284	7	achieved	achieve	VERB
easat-1848	284	8	an	an	DET
easat-1848	284	9	accuracy	accuracy	NOUN
easat-1848	284	10	[	[	X
easat-1848	284	11	46	46	NUM
easat-1848	284	12	]	]	PUNCT
easat-1848	284	13	of	of	ADP
easat-1848	284	14	95.37	95.37	NUM
easat-1848	284	15	and	and	CCONJ
easat-1848	284	16	95.92	95.92	NUM
easat-1848	284	17	respectively	respectively	ADV
easat-1848	284	18	.	.	PUNCT
easat-1848	285	1	figure	figure	NOUN
easat-1848	285	2	3	3	NUM
easat-1848	285	3	.	.	PUNCT
easat-1848	285	4	accuracy	accuracy	NOUN
easat-1848	285	5	of	of	ADP
easat-1848	285	6	different	different	ADJ
easat-1848	285	7	classifier	classifier	NOUN
easat-1848	285	8	with	with	ADP
easat-1848	285	9	feature	feature	NOUN
easat-1848	285	10	selection	selection	NOUN
easat-1848	285	11	method	method	NOUN
easat-1848	285	12	.	.	PUNCT
easat-1848	286	1	figure	figure	NOUN
easat-1848	286	2	4	4	NUM
easat-1848	286	3	below	below	ADV
easat-1848	286	4	illustrates	illustrate	VERB
easat-1848	286	5	the	the	DET
easat-1848	286	6	precision	precision	NOUN
easat-1848	286	7	of	of	ADP
easat-1848	286	8	machine	machine	NOUN
easat-1848	286	9	learning	learning	NOUN
easat-1848	286	10	and	and	CCONJ
easat-1848	286	11	deep	deep	ADJ
easat-1848	286	12	learning	learning	NOUN
easat-1848	286	13	algorithms	algorithm	NOUN
easat-1848	286	14	after	after	ADP
easat-1848	286	15	each	each	DET
easat-1848	286	16	feature	feature	NOUN
easat-1848	286	17	selection	selection	NOUN
easat-1848	286	18	method	method	NOUN
easat-1848	286	19	.	.	PUNCT
easat-1848	287	1	after	after	ADP
easat-1848	287	2	deployment	deployment	NOUN
easat-1848	287	3	of	of	ADP
easat-1848	287	4	feature	feature	NOUN
easat-1848	287	5	selection	selection	NOUN
easat-1848	287	6	method	method	NOUN
easat-1848	287	7	lasso	lasso	NOUN
easat-1848	287	8	,	,	PUNCT
easat-1848	287	9	the	the	DET
easat-1848	287	10	precision	precision	NOUN
easat-1848	287	11	of	of	ADP
easat-1848	287	12	random	random	ADJ
easat-1848	287	13	forest	forest	NOUN
easat-1848	287	14	,	,	PUNCT
easat-1848	287	15	logistic	logistic	ADJ
easat-1848	287	16	regression	regression	NOUN
easat-1848	287	17	,	,	PUNCT
easat-1848	287	18	k	k	X
easat-1848	287	19	-	-	PUNCT
easat-1848	287	20	nearest	near	ADJ
easat-1848	287	21	neighbour	neighbour	NOUN
easat-1848	287	22	,	,	PUNCT
easat-1848	287	23	support	support	NOUN
easat-1848	287	24	vector	vector	NOUN
easat-1848	287	25	machine	machine	NOUN
easat-1848	287	26	,	,	PUNCT
easat-1848	287	27	neural	neural	ADJ
easat-1848	287	28	network	network	NOUN
easat-1848	287	29	and	and	CCONJ
easat-1848	287	30	naïve	naïve	ADJ
easat-1848	287	31	bayes	baye	NOUN
easat-1848	287	32	are	be	AUX
easat-1848	287	33	94.77	94.77	NUM
easat-1848	287	34	,	,	PUNCT
easat-1848	287	35	87.12	87.12	NUM
easat-1848	287	36	,	,	PUNCT
easat-1848	287	37	87.14	87.14	NUM
easat-1848	287	38	,	,	PUNCT
easat-1848	287	39	86.71	86.71	NUM
easat-1848	287	40	,	,	PUNCT
easat-1848	287	41	96.35	96.35	NUM
easat-1848	287	42	,	,	PUNCT
easat-1848	287	43	86.46	86.46	NUM
easat-1848	287	44	respectively	respectively	ADV
easat-1848	287	45	.	.	PUNCT
easat-1848	288	1	with	with	ADP
easat-1848	288	2	feature	feature	NOUN
easat-1848	288	3	selection	selection	NOUN
easat-1848	288	4	method	method	NOUN
easat-1848	288	5	relief	relief	NOUN
easat-1848	288	6	,	,	PUNCT
easat-1848	288	7	the	the	DET
easat-1848	288	8	precision	precision	NOUN
easat-1848	288	9	of	of	ADP
easat-1848	288	10	logistic	logistic	ADJ
easat-1848	288	11	regression	regression	NOUN
easat-1848	288	12	,	,	PUNCT
easat-1848	288	13	neural	neural	ADJ
easat-1848	288	14	network	network	NOUN
easat-1848	288	15	,	,	PUNCT
easat-1848	288	16	k	k	NOUN
easat-1848	288	17	-	-	PUNCT
easat-1848	288	18	nearest	near	ADJ
easat-1848	288	19	neighbour	neighbour	NOUN
easat-1848	288	20	,	,	PUNCT
easat-1848	288	21	random	random	ADJ
easat-1848	288	22	forest	forest	NOUN
easat-1848	288	23	,	,	PUNCT
easat-1848	288	24	support	support	NOUN
easat-1848	288	25	vector	vector	NOUN
easat-1848	288	26	machine	machine	NOUN
easat-1848	288	27	,	,	PUNCT
easat-1848	288	28	naïve	naïve	ADJ
easat-1848	288	29	bayes	baye	NOUN
easat-1848	288	30	and	and	CCONJ
easat-1848	288	31	are	be	AUX
easat-1848	288	32	81.81	81.81	NUM
easat-1848	288	33	,	,	PUNCT
easat-1848	288	34	88.47	88.47	NUM
easat-1848	288	35	,	,	PUNCT
easat-1848	288	36	82.64	82.64	NUM
easat-1848	288	37	,	,	PUNCT
easat-1848	288	38	86.44	86.44	NUM
easat-1848	288	39	,	,	PUNCT
easat-1848	288	40	81.81	81.81	NUM
easat-1848	288	41	,	,	PUNCT
easat-1848	288	42	84.03	84.03	NUM
easat-1848	288	43	respectively	respectively	ADV
easat-1848	288	44	.	.	PUNCT
easat-1848	289	1	the	the	DET
easat-1848	289	2	precision	precision	NOUN
easat-1848	289	3	of	of	ADP
easat-1848	289	4	naïve	naïve	ADJ
easat-1848	289	5	bayes	bayes	NOUN
easat-1848	289	6	,	,	PUNCT
easat-1848	289	7	logistic	logistic	ADJ
easat-1848	289	8	regression	regression	NOUN
easat-1848	289	9	,	,	PUNCT
easat-1848	289	10	k	k	X
easat-1848	289	11	-	-	PUNCT
easat-1848	289	12	nearest	near	ADJ
easat-1848	289	13	neighbour	neighbour	NOUN
easat-1848	289	14	,	,	PUNCT
easat-1848	289	15	random	random	ADJ
easat-1848	289	16	forest	forest	NOUN
easat-1848	289	17	,	,	PUNCT
easat-1848	289	18	support	support	NOUN
easat-1848	289	19	vector	vector	NOUN
easat-1848	289	20	machine	machine	NOUN
easat-1848	289	21	,	,	PUNCT
easat-1848	289	22	and	and	CCONJ
easat-1848	289	23	neural	neural	ADJ
easat-1848	289	24	network	network	NOUN
easat-1848	289	25	after	after	SCONJ
easat-1848	289	26	pca	pca	PROPN
easat-1848	289	27	feature	feature	NOUN
easat-1848	289	28	selection	selection	NOUN
easat-1848	289	29	are	be	AUX
easat-1848	289	30	84.32	84.32	NUM
easat-1848	289	31	,	,	PUNCT
easat-1848	289	32	85.18	85.18	NUM
easat-1848	289	33	,	,	PUNCT
easat-1848	289	34	84.09	84.09	NUM
easat-1848	289	35	,	,	PUNCT
easat-1848	289	36	89.70	89.70	NUM
easat-1848	289	37	,	,	PUNCT
easat-1848	289	38	85.29	85.29	NUM
easat-1848	289	39	,	,	PUNCT
easat-1848	289	40	90.45	90.45	NUM
easat-1848	289	41	respectively	respectively	ADV
easat-1848	289	42	.	.	PUNCT
easat-1848	290	1	the	the	DET
easat-1848	290	2	precision	precision	NOUN
easat-1848	290	3	of	of	ADP
easat-1848	290	4	support	support	NOUN
easat-1848	290	5	vector	vector	NOUN
easat-1848	290	6	machine	machine	NOUN
easat-1848	290	7	,	,	PUNCT
easat-1848	290	8	logistic	logistic	ADJ
easat-1848	290	9	regression	regression	NOUN
easat-1848	290	10	,	,	PUNCT
easat-1848	290	11	k	k	X
easat-1848	290	12	-	-	PUNCT
easat-1848	290	13	nearest	near	ADJ
easat-1848	290	14	neighbour	neighbour	NOUN
easat-1848	290	15	,	,	PUNCT
easat-1848	290	16	random	random	ADJ
easat-1848	290	17	forest	forest	NOUN
easat-1848	290	18	,	,	PUNCT
easat-1848	290	19	naïve	naïve	ADJ
easat-1848	290	20	bayes	bayes	NOUN
easat-1848	290	21	and	and	CCONJ
easat-1848	290	22	neural	neural	ADJ
easat-1848	290	23	network	network	NOUN
easat-1848	290	24	after	after	SCONJ
easat-1848	290	25	rfe	rfe	NOUN
easat-1848	290	26	feature	feature	NOUN
easat-1848	290	27	selection	selection	NOUN
easat-1848	290	28	are	be	AUX
easat-1848	290	29	86.13	86.13	NUM
easat-1848	290	30	,	,	PUNCT
easat-1848	290	31	87.59	87.59	NUM
easat-1848	290	32	,	,	PUNCT
easat-1848	290	33	78.23	78.23	NUM
easat-1848	290	34	,	,	PUNCT
easat-1848	290	35	85.82	85.82	NUM
easat-1848	290	36	,	,	PUNCT
easat-1848	290	37	86.4	86.4	NUM
easat-1848	290	38	,	,	PUNCT
easat-1848	290	39	87.82	87.82	NUM
easat-1848	290	40	respectively	respectively	ADV
easat-1848	290	41	.	.	PUNCT
easat-1848	291	1	the	the	DET
easat-1848	291	2	precision	precision	NOUN
easat-1848	291	3	of	of	ADP
easat-1848	291	4	random	random	ADJ
easat-1848	291	5	forest	forest	NOUN
easat-1848	291	6	,	,	PUNCT
easat-1848	291	7	logistic	logistic	ADJ
easat-1848	291	8	regression	regression	NOUN
easat-1848	291	9	,	,	PUNCT
easat-1848	291	10	k	k	X
easat-1848	291	11	-	-	PUNCT
easat-1848	291	12	nearest	near	ADJ
easat-1848	291	13	neighbour	neighbour	NOUN
easat-1848	291	14	,	,	PUNCT
easat-1848	291	15	support	support	NOUN
easat-1848	291	16	vector	vector	NOUN
easat-1848	291	17	machine	machine	NOUN
easat-1848	291	18	,	,	PUNCT
easat-1848	291	19	naïve	naïve	ADJ
easat-1848	291	20	bayes	bayes	NOUN
easat-1848	291	21	and	and	CCONJ
easat-1848	291	22	neural	neural	ADJ
easat-1848	291	23	network	network	NOUN
easat-1848	291	24	after	after	SCONJ
easat-1848	291	25	mr	mr	PROPN
easat-1848	291	26	-	-	PUNCT
easat-1848	291	27	mr	mr	PROPN
easat-1848	291	28	feature	feature	NOUN
easat-1848	291	29	selection	selection	NOUN
easat-1848	291	30	are	be	AUX
easat-1848	291	31	90.29	90.29	NUM
easat-1848	291	32	,	,	PUNCT
easat-1848	291	33	80.43	80.43	NUM
easat-1848	291	34	,	,	PUNCT
easat-1848	291	35	80.62	80.62	NUM
easat-1848	291	36	,	,	PUNCT
easat-1848	291	37	86.82	86.82	NUM
easat-1848	291	38	,	,	PUNCT
easat-1848	291	39	81.53	81.53	NUM
easat-1848	291	40	,	,	PUNCT
easat-1848	291	41	91.12	91.12	NUM
easat-1848	291	42	respectively	respectively	ADV
easat-1848	291	43	.	.	PUNCT
easat-1848	292	1	the	the	DET
easat-1848	292	2	random	random	ADJ
easat-1848	292	3	forest	forest	NOUN
easat-1848	292	4	and	and	CCONJ
easat-1848	292	5	neural	neural	ADJ
easat-1848	292	6	network	network	NOUN
easat-1848	292	7	1465	1465	NUM
easat-1848	292	8	edelweiss	edelweiss	PROPN
easat-1848	292	9	applied	apply	VERB
easat-1848	292	10	science	science	NOUN
easat-1848	292	11	and	and	CCONJ
easat-1848	292	12	technology	technology	NOUN
easat-1848	292	13	issn	issn	PROPN
easat-1848	292	14	:	:	PUNCT
easat-1848	292	15	2576	2576	NUM
easat-1848	292	16	-	-	SYM
easat-1848	292	17	8484	8484	NUM
easat-1848	292	18	vol	vol	NOUN
easat-1848	292	19	.	.	PROPN
easat-1848	292	20	8	8	NUM
easat-1848	292	21	,	,	PUNCT
easat-1848	292	22	no	no	INTJ
easat-1848	292	23	.	.	NOUN
easat-1848	292	24	5	5	NUM
easat-1848	292	25	:	:	SYM
easat-1848	292	26	1445	1445	NUM
easat-1848	292	27	-	-	SYM
easat-1848	292	28	1471	1471	NUM
easat-1848	292	29	,	,	PUNCT
easat-1848	292	30	2024	2024	NUM
easat-1848	292	31	doi	doi	NOUN
easat-1848	292	32	:	:	PUNCT
easat-1848	292	33	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	292	34	©	©	PROPN
easat-1848	292	35	2024	2024	NUM
easat-1848	292	36	by	by	ADP
easat-1848	292	37	the	the	DET
easat-1848	292	38	authors	author	NOUN
easat-1848	292	39	;	;	PUNCT
easat-1848	292	40	licensee	licensee	PROPN
easat-1848	292	41	learning	learn	VERB
easat-1848	292	42	gate	gate	NOUN
easat-1848	292	43	classifier	classifier	PROPN
easat-1848	292	44	implemented	implement	VERB
easat-1848	292	45	using	use	VERB
easat-1848	292	46	lasso	lasso	NOUN
easat-1848	292	47	and	and	CCONJ
easat-1848	292	48	mr	mr	PROPN
easat-1848	292	49	-	-	PUNCT
easat-1848	292	50	mr	mr	PROPN
easat-1848	292	51	feature	feature	NOUN
easat-1848	292	52	selection	selection	NOUN
easat-1848	292	53	techniques	technique	NOUN
easat-1848	292	54	have	have	AUX
easat-1848	292	55	achieved	achieve	VERB
easat-1848	292	56	high	high	ADJ
easat-1848	292	57	precision	precision	NOUN
easat-1848	292	58	compared	compare	VERB
easat-1848	292	59	with	with	ADP
easat-1848	292	60	other	other	ADJ
easat-1848	292	61	algorithms	algorithm	NOUN
easat-1848	292	62	.	.	PUNCT
easat-1848	293	1	figure	figure	VERB
easat-1848	293	2	4	4	NUM
easat-1848	293	3	.	.	PUNCT
easat-1848	293	4	precision	precision	NOUN
easat-1848	293	5	of	of	ADP
easat-1848	293	6	different	different	ADJ
easat-1848	293	7	classifier	classifier	NOUN
easat-1848	293	8	with	with	ADP
easat-1848	293	9	feature	feature	NOUN
easat-1848	293	10	selection	selection	NOUN
easat-1848	293	11	methods	method	NOUN
easat-1848	293	12	.	.	PUNCT
easat-1848	294	1	figure	figure	NOUN
easat-1848	294	2	5	5	NUM
easat-1848	294	3	below	below	ADV
easat-1848	294	4	shows	show	VERB
easat-1848	294	5	the	the	DET
easat-1848	294	6	recall	recall	NOUN
easat-1848	294	7	measure	measure	NOUN
easat-1848	294	8	of	of	ADP
easat-1848	294	9	machine	machine	NOUN
easat-1848	294	10	learning	learning	NOUN
easat-1848	294	11	and	and	CCONJ
easat-1848	294	12	deep	deep	ADJ
easat-1848	294	13	learning	learning	NOUN
easat-1848	294	14	algorithms	algorithm	NOUN
easat-1848	294	15	after	after	ADP
easat-1848	294	16	each	each	DET
easat-1848	294	17	feature	feature	NOUN
easat-1848	294	18	selection	selection	NOUN
easat-1848	294	19	techniques	technique	NOUN
easat-1848	294	20	.	.	PUNCT
easat-1848	295	1	after	after	ADP
easat-1848	295	2	deployment	deployment	NOUN
easat-1848	295	3	of	of	ADP
easat-1848	295	4	feature	feature	NOUN
easat-1848	295	5	selection	selection	NOUN
easat-1848	295	6	method	method	NOUN
easat-1848	295	7	lasso	lasso	NOUN
easat-1848	295	8	,	,	PUNCT
easat-1848	295	9	the	the	DET
easat-1848	295	10	recall	recall	NOUN
easat-1848	295	11	measure	measure	NOUN
easat-1848	295	12	of	of	ADP
easat-1848	295	13	support	support	NOUN
easat-1848	295	14	vector	vector	NOUN
easat-1848	295	15	machine	machine	NOUN
easat-1848	295	16	,	,	PUNCT
easat-1848	295	17	logistic	logistic	ADJ
easat-1848	295	18	regression	regression	NOUN
easat-1848	295	19	,	,	PUNCT
easat-1848	295	20	naïve	naïve	ADJ
easat-1848	295	21	bayes	bayes	NOUN
easat-1848	295	22	,	,	PUNCT
easat-1848	295	23	k	k	NOUN
easat-1848	295	24	-	-	PUNCT
easat-1848	295	25	nearest	near	ADJ
easat-1848	295	26	neighbour	neighbour	NOUN
easat-1848	295	27	,	,	PUNCT
easat-1848	295	28	random	random	ADJ
easat-1848	295	29	forest	forest	NOUN
easat-1848	295	30	,	,	PUNCT
easat-1848	295	31	and	and	CCONJ
easat-1848	295	32	neural	neural	ADJ
easat-1848	295	33	network	network	NOUN
easat-1848	295	34	are	be	AUX
easat-1848	295	35	94.65	94.65	NUM
easat-1848	295	36	,	,	PUNCT
easat-1848	295	37	87.78	87.78	NUM
easat-1848	295	38	,	,	PUNCT
easat-1848	295	39	87.78	87.78	NUM
easat-1848	295	40	,	,	PUNCT
easat-1848	295	41	93.12	93.12	NUM
easat-1848	295	42	,	,	PUNCT
easat-1848	295	43	96.94	96.94	NUM
easat-1848	295	44	,	,	PUNCT
easat-1848	295	45	97.45	97.45	NUM
easat-1848	295	46	respectively	respectively	ADV
easat-1848	295	47	.	.	PUNCT
easat-1848	296	1	with	with	ADP
easat-1848	296	2	feature	feature	NOUN
easat-1848	296	3	selection	selection	NOUN
easat-1848	296	4	method	method	NOUN
easat-1848	296	5	relief	relief	NOUN
easat-1848	296	6	,	,	PUNCT
easat-1848	296	7	the	the	DET
easat-1848	296	8	recall	recall	NOUN
easat-1848	296	9	measure	measure	NOUN
easat-1848	296	10	of	of	ADP
easat-1848	296	11	logistic	logistic	ADJ
easat-1848	296	12	regression	regression	NOUN
easat-1848	296	13	,	,	PUNCT
easat-1848	296	14	k	k	X
easat-1848	296	15	-	-	PUNCT
easat-1848	296	16	nearest	near	ADJ
easat-1848	296	17	neighbour	neighbour	NOUN
easat-1848	296	18	,	,	PUNCT
easat-1848	296	19	neural	neural	ADJ
easat-1848	296	20	network	network	NOUN
easat-1848	296	21	,	,	PUNCT
easat-1848	296	22	random	random	ADJ
easat-1848	296	23	forest	forest	NOUN
easat-1848	296	24	,	,	PUNCT
easat-1848	296	25	support	support	NOUN
easat-1848	296	26	vector	vector	NOUN
easat-1848	296	27	machine	machine	NOUN
easat-1848	296	28	,	,	PUNCT
easat-1848	296	29	naïve	naïve	ADJ
easat-1848	296	30	bayes	baye	NOUN
easat-1848	296	31	are	be	AUX
easat-1848	296	32	75.57	75.57	NUM
easat-1848	296	33	,	,	PUNCT
easat-1848	296	34	76.33	76.33	NUM
easat-1848	296	35	,	,	PUNCT
easat-1848	296	36	79.86	79.86	NUM
easat-1848	296	37	,	,	PUNCT
easat-1848	296	38	77.86	77.86	NUM
easat-1848	296	39	,	,	PUNCT
easat-1848	296	40	75.57	75.57	NUM
easat-1848	296	41	,	,	PUNCT
easat-1848	296	42	76.33	76.33	NUM
easat-1848	296	43	,	,	PUNCT
easat-1848	296	44	respectively	respectively	ADV
easat-1848	296	45	.	.	PUNCT
easat-1848	297	1	the	the	DET
easat-1848	297	2	recall	recall	NOUN
easat-1848	297	3	measure	measure	NOUN
easat-1848	297	4	of	of	ADP
easat-1848	297	5	logistic	logistic	ADJ
easat-1848	297	6	regression	regression	NOUN
easat-1848	297	7	,	,	PUNCT
easat-1848	297	8	support	support	NOUN
easat-1848	297	9	vector	vector	NOUN
easat-1848	297	10	machine	machine	NOUN
easat-1848	297	11	,	,	PUNCT
easat-1848	297	12	k	k	X
easat-1848	297	13	-	-	PUNCT
easat-1848	297	14	nearest	near	ADJ
easat-1848	297	15	neighbour	neighbour	NOUN
easat-1848	297	16	,	,	PUNCT
easat-1848	297	17	random	random	ADJ
easat-1848	297	18	forest	forest	NOUN
easat-1848	297	19	,	,	PUNCT
easat-1848	297	20	support	support	NOUN
easat-1848	297	21	vector	vector	NOUN
easat-1848	297	22	machine	machine	NOUN
easat-1848	297	23	,	,	PUNCT
easat-1848	297	24	naïve	naïve	ADJ
easat-1848	297	25	bayes	bayes	NOUN
easat-1848	297	26	and	and	CCONJ
easat-1848	297	27	neural	neural	ADJ
easat-1848	297	28	network	network	NOUN
easat-1848	297	29	after	after	ADP
easat-1848	297	30	pca	pca	PROPN
easat-1848	297	31	feature	feature	NOUN
easat-1848	297	32	selection	selection	NOUN
easat-1848	297	33	are	be	AUX
easat-1848	297	34	87.78	87.78	NUM
easat-1848	297	35	,	,	PUNCT
easat-1848	297	36	88.54	88.54	NUM
easat-1848	297	37	,	,	PUNCT
easat-1848	297	38	84.73	84.73	NUM
easat-1848	297	39	,	,	PUNCT
easat-1848	297	40	93.1286.25	93.1286.25	NUM
easat-1848	297	41	,	,	PUNCT
easat-1848	297	42	95.62	95.62	NUM
easat-1848	297	43	respectively	respectively	ADV
easat-1848	297	44	.	.	PUNCT
easat-1848	298	1	the	the	DET
easat-1848	298	2	recall	recall	NOUN
easat-1848	298	3	measure	measure	NOUN
easat-1848	298	4	of	of	ADP
easat-1848	298	5	neural	neural	ADJ
easat-1848	298	6	network	network	NOUN
easat-1848	298	7	,	,	PUNCT
easat-1848	298	8	k	k	NOUN
easat-1848	298	9	-	-	PUNCT
easat-1848	298	10	nearest	near	ADJ
easat-1848	298	11	neighbour	neighbour	NOUN
easat-1848	298	12	,	,	PUNCT
easat-1848	298	13	random	random	ADJ
easat-1848	298	14	forest	forest	NOUN
easat-1848	298	15	,	,	PUNCT
easat-1848	298	16	support	support	NOUN
easat-1848	298	17	vector	vector	NOUN
easat-1848	298	18	machine	machine	NOUN
easat-1848	298	19	,	,	PUNCT
easat-1848	298	20	naïve	naïve	ADJ
easat-1848	298	21	bayes	baye	NOUN
easat-1848	298	22	and	and	CCONJ
easat-1848	298	23	logistic	logistic	ADJ
easat-1848	298	24	regression	regression	NOUN
easat-1848	298	25	,	,	PUNCT
easat-1848	298	26	after	after	SCONJ
easat-1848	298	27	rfe	rfe	NOUN
easat-1848	298	28	feature	feature	NOUN
easat-1848	298	29	selection	selection	NOUN
easat-1848	298	30	are	be	AUX
easat-1848	298	31	89.78	89.78	NUM
easat-1848	298	32	,	,	PUNCT
easat-1848	298	33	87.78	87.78	NUM
easat-1848	298	34	,	,	PUNCT
easat-1848	298	35	87.78	87.78	NUM
easat-1848	298	36	,	,	PUNCT
easat-1848	298	37	90.07	90.07	NUM
easat-1848	298	38	,	,	PUNCT
easat-1848	298	39	82.44	82.44	NUM
easat-1848	298	40	,	,	PUNCT
easat-1848	298	41	86.25	86.25	NUM
easat-1848	298	42	respectively	respectively	ADV
easat-1848	298	43	.	.	PUNCT
easat-1848	299	1	after	after	ADP
easat-1848	299	2	the	the	DET
easat-1848	299	3	deployment	deployment	NOUN
easat-1848	299	4	of	of	ADP
easat-1848	299	5	feature	feature	NOUN
easat-1848	299	6	selection	selection	NOUN
easat-1848	299	7	method	method	NOUN
easat-1848	299	8	mr	mr	PROPN
easat-1848	299	9	-	-	PUNCT
easat-1848	299	10	mr	mr	PROPN
easat-1848	299	11	,	,	PUNCT
easat-1848	299	12	the	the	DET
easat-1848	299	13	recall	recall	NOUN
easat-1848	299	14	measure	measure	NOUN
easat-1848	299	15	of	of	ADP
easat-1848	299	16	logistic	logistic	ADJ
easat-1848	299	17	regression	regression	NOUN
easat-1848	299	18	,	,	PUNCT
easat-1848	299	19	knearest	knearest	NOUN
easat-1848	299	20	neighbour	neighbour	NOUN
easat-1848	299	21	,	,	PUNCT
easat-1848	299	22	random	random	ADJ
easat-1848	299	23	forest	forest	NOUN
easat-1848	299	24	,	,	PUNCT
easat-1848	299	25	support	support	NOUN
easat-1848	299	26	vector	vector	NOUN
easat-1848	299	27	machine	machine	NOUN
easat-1848	299	28	,	,	PUNCT
easat-1848	299	29	naïve	naïve	ADJ
easat-1848	299	30	bayes	baye	NOUN
easat-1848	299	31	and	and	CCONJ
easat-1848	299	32	neural	neural	ADJ
easat-1848	299	33	network	network	NOUN
easat-1848	299	34	are	be	AUX
easat-1848	299	35	84.73	84.73	NUM
easat-1848	299	36	,	,	PUNCT
easat-1848	299	37	79.38	79.38	NUM
easat-1848	299	38	,	,	PUNCT
easat-1848	299	39	92.36	92.36	NUM
easat-1848	299	40	,	,	PUNCT
easat-1848	299	41	85.49	85.49	NUM
easat-1848	299	42	,	,	PUNCT
easat-1848	299	43	80.91	80.91	NUM
easat-1848	299	44	,	,	PUNCT
easat-1848	299	45	93.16	93.16	NUM
easat-1848	299	46	respectively	respectively	ADV
easat-1848	299	47	.	.	PUNCT
easat-1848	300	1	the	the	DET
easat-1848	300	2	random	random	ADJ
easat-1848	300	3	forest	forest	NOUN
easat-1848	300	4	and	and	CCONJ
easat-1848	300	5	neural	neural	ADJ
easat-1848	300	6	network	network	NOUN
easat-1848	300	7	classifier	classifier	NOUN
easat-1848	300	8	implemented	implement	VERB
easat-1848	300	9	using	use	VERB
easat-1848	300	10	lasso	lasso	NOUN
easat-1848	300	11	feature	feature	NOUN
easat-1848	300	12	selection	selection	NOUN
easat-1848	300	13	techniques	technique	NOUN
easat-1848	300	14	have	have	AUX
easat-1848	300	15	achieved	achieve	VERB
easat-1848	300	16	high	high	ADJ
easat-1848	300	17	recall	recall	NOUN
easat-1848	300	18	measure	measure	NOUN
easat-1848	300	19	compared	compare	VERB
easat-1848	300	20	with	with	ADP
easat-1848	300	21	other	other	ADJ
easat-1848	300	22	algorithms	algorithm	NOUN
easat-1848	300	23	.	.	PUNCT
easat-1848	301	1	1466	1466	NUM
easat-1848	301	2	edelweiss	edelweiss	PROPN
easat-1848	301	3	applied	apply	VERB
easat-1848	301	4	science	science	NOUN
easat-1848	301	5	and	and	CCONJ
easat-1848	301	6	technology	technology	NOUN
easat-1848	301	7	issn	issn	PROPN
easat-1848	301	8	:	:	PUNCT
easat-1848	301	9	2576	2576	NUM
easat-1848	301	10	-	-	SYM
easat-1848	301	11	8484	8484	NUM
easat-1848	301	12	vol	vol	NOUN
easat-1848	301	13	.	.	PROPN
easat-1848	301	14	8	8	NUM
easat-1848	301	15	,	,	PUNCT
easat-1848	301	16	no	no	INTJ
easat-1848	301	17	.	.	NOUN
easat-1848	301	18	5	5	NUM
easat-1848	301	19	:	:	SYM
easat-1848	301	20	1445	1445	NUM
easat-1848	301	21	-	-	SYM
easat-1848	301	22	1471	1471	NUM
easat-1848	301	23	,	,	PUNCT
easat-1848	301	24	2024	2024	NUM
easat-1848	301	25	doi	doi	NOUN
easat-1848	301	26	:	:	PUNCT
easat-1848	301	27	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	301	28	©	©	PROPN
easat-1848	301	29	2024	2024	NUM
easat-1848	301	30	by	by	ADP
easat-1848	301	31	the	the	DET
easat-1848	301	32	authors	author	NOUN
easat-1848	301	33	;	;	PUNCT
easat-1848	301	34	licensee	licensee	PROPN
easat-1848	301	35	learning	learn	VERB
easat-1848	301	36	gate	gate	PROPN
easat-1848	301	37	figure	figure	NOUN
easat-1848	301	38	5	5	NUM
easat-1848	301	39	.	.	PUNCT
easat-1848	301	40	recall	recall	NOUN
easat-1848	301	41	of	of	ADP
easat-1848	301	42	different	different	ADJ
easat-1848	301	43	classifier	classifier	NOUN
easat-1848	301	44	with	with	ADP
easat-1848	301	45	feature	feature	NOUN
easat-1848	301	46	selection	selection	NOUN
easat-1848	301	47	methods	method	NOUN
easat-1848	301	48	.	.	PUNCT
easat-1848	302	1	figure.6	figure.6	NOUN
easat-1848	302	2	below	below	ADP
easat-1848	302	3	displays	display	VERB
easat-1848	302	4	the	the	DET
easat-1848	302	5	f1	f1	ADJ
easat-1848	302	6	score	score	NOUN
easat-1848	302	7	of	of	ADP
easat-1848	302	8	deep	deep	ADJ
easat-1848	302	9	learning	learning	NOUN
easat-1848	302	10	and	and	CCONJ
easat-1848	302	11	machine	machine	NOUN
easat-1848	302	12	learning	learn	VERB
easat-1848	302	13	algorithms	algorithm	NOUN
easat-1848	302	14	after	after	ADP
easat-1848	302	15	each	each	DET
easat-1848	302	16	feature	feature	NOUN
easat-1848	302	17	selection	selection	NOUN
easat-1848	302	18	method	method	NOUN
easat-1848	302	19	.	.	PUNCT
easat-1848	303	1	after	after	ADP
easat-1848	303	2	application	application	NOUN
easat-1848	303	3	of	of	ADP
easat-1848	303	4	feature	feature	NOUN
easat-1848	303	5	selection	selection	NOUN
easat-1848	303	6	method	method	NOUN
easat-1848	303	7	lasso	lasso	NOUN
easat-1848	303	8	,	,	PUNCT
easat-1848	303	9	the	the	DET
easat-1848	303	10	f1	f1	ADJ
easat-1848	303	11	score	score	NOUN
easat-1848	303	12	of	of	ADP
easat-1848	303	13	knearest	knearest	NOUN
easat-1848	303	14	neighbour	neighbour	NOUN
easat-1848	303	15	,	,	PUNCT
easat-1848	303	16	logistic	logistic	ADJ
easat-1848	303	17	regression	regression	NOUN
easat-1848	303	18	,	,	PUNCT
easat-1848	303	19	random	random	ADJ
easat-1848	303	20	forest	forest	NOUN
easat-1848	303	21	,	,	PUNCT
easat-1848	303	22	support	support	NOUN
easat-1848	303	23	vector	vector	NOUN
easat-1848	303	24	machine	machine	NOUN
easat-1848	303	25	,	,	PUNCT
easat-1848	303	26	neural	neural	ADJ
easat-1848	303	27	network	network	NOUN
easat-1848	303	28	and	and	CCONJ
easat-1848	303	29	naïve	naïve	ADJ
easat-1848	303	30	bayes	baye	NOUN
easat-1848	303	31	are	be	AUX
easat-1848	303	32	90.03	90.03	NUM
easat-1848	303	33	,	,	PUNCT
easat-1848	303	34	87.45	87.45	NUM
easat-1848	303	35	,	,	PUNCT
easat-1848	303	36	95.84	95.84	NUM
easat-1848	303	37	,	,	PUNCT
easat-1848	303	38	90.51	90.51	NUM
easat-1848	303	39	,	,	PUNCT
easat-1848	303	40	95.21	95.21	NUM
easat-1848	303	41	,	,	PUNCT
easat-1848	303	42	87.12	87.12	NUM
easat-1848	303	43	respectively	respectively	ADV
easat-1848	303	44	.	.	PUNCT
easat-1848	304	1	with	with	ADP
easat-1848	304	2	feature	feature	NOUN
easat-1848	304	3	selection	selection	NOUN
easat-1848	304	4	method	method	NOUN
easat-1848	304	5	relief	relief	NOUN
easat-1848	304	6	,	,	PUNCT
easat-1848	304	7	the	the	DET
easat-1848	304	8	f1	f1	ADJ
easat-1848	304	9	score	score	NOUN
easat-1848	304	10	measure	measure	NOUN
easat-1848	304	11	of	of	ADP
easat-1848	304	12	logistic	logistic	ADJ
easat-1848	304	13	regression	regression	NOUN
easat-1848	304	14	,	,	PUNCT
easat-1848	304	15	k	k	X
easat-1848	304	16	-	-	PUNCT
easat-1848	304	17	nearest	near	ADJ
easat-1848	304	18	neighbour	neighbour	NOUN
easat-1848	304	19	,	,	PUNCT
easat-1848	304	20	support	support	NOUN
easat-1848	304	21	vector	vector	NOUN
easat-1848	304	22	machine	machine	NOUN
easat-1848	304	23	,	,	PUNCT
easat-1848	304	24	naïve	naïve	ADJ
easat-1848	304	25	bayes	bayes	NOUN
easat-1848	304	26	,	,	PUNCT
easat-1848	304	27	random	random	ADJ
easat-1848	304	28	forest	forest	NOUN
easat-1848	304	29	,	,	PUNCT
easat-1848	304	30	and	and	CCONJ
easat-1848	304	31	neural	neural	ADJ
easat-1848	304	32	network	network	NOUN
easat-1848	304	33	are	be	AUX
easat-1848	304	34	78.57	78.57	NUM
easat-1848	304	35	,	,	PUNCT
easat-1848	304	36	79.36	79.36	NUM
easat-1848	304	37	,	,	PUNCT
easat-1848	304	38	78.57	78.57	NUM
easat-1848	304	39	,	,	PUNCT
easat-1848	304	40	80	80	NUM
easat-1848	304	41	,	,	PUNCT
easat-1848	304	42	81.92	81.92	NUM
easat-1848	304	43	,	,	PUNCT
easat-1848	304	44	83.92	83.92	NUM
easat-1848	304	45	respectively	respectively	ADV
easat-1848	304	46	.	.	PUNCT
easat-1848	305	1	the	the	DET
easat-1848	305	2	f1	f1	PROPN
easat-1848	305	3	score	score	NOUN
easat-1848	305	4	measure	measure	NOUN
easat-1848	305	5	of	of	ADP
easat-1848	305	6	logistic	logistic	ADJ
easat-1848	305	7	regression	regression	NOUN
easat-1848	305	8	,	,	PUNCT
easat-1848	305	9	k	k	X
easat-1848	305	10	-	-	PUNCT
easat-1848	305	11	nearest	near	ADJ
easat-1848	305	12	neighbour	neighbour	NOUN
easat-1848	305	13	,	,	PUNCT
easat-1848	305	14	neural	neural	ADJ
easat-1848	305	15	network	network	NOUN
easat-1848	305	16	,	,	PUNCT
easat-1848	305	17	support	support	NOUN
easat-1848	305	18	vector	vector	NOUN
easat-1848	305	19	machine	machine	NOUN
easat-1848	305	20	,	,	PUNCT
easat-1848	305	21	naïve	naïve	ADJ
easat-1848	305	22	bayes	bayes	NOUN
easat-1848	305	23	and	and	CCONJ
easat-1848	305	24	random	random	ADJ
easat-1848	305	25	forest	forest	NOUN
easat-1848	305	26	after	after	SCONJ
easat-1848	305	27	pca	pca	PROPN
easat-1848	305	28	feature	feature	NOUN
easat-1848	305	29	selection	selection	NOUN
easat-1848	305	30	are	be	AUX
easat-1848	305	31	86.46	86.46	NUM
easat-1848	305	32	,	,	PUNCT
easat-1848	305	33	84.41	84.41	NUM
easat-1848	305	34	,	,	PUNCT
easat-1848	305	35	90.27	90.27	NUM
easat-1848	305	36	86.89	86.89	NUM
easat-1848	305	37	,	,	PUNCT
easat-1848	305	38	85.28	85.28	NUM
easat-1848	305	39	,	,	PUNCT
easat-1848	305	40	91.38	91.38	NUM
easat-1848	305	41	respectively	respectively	ADV
easat-1848	305	42	.	.	PUNCT
easat-1848	306	1	the	the	DET
easat-1848	306	2	f1	f1	PROPN
easat-1848	306	3	score	score	NOUN
easat-1848	306	4	of	of	ADP
easat-1848	306	5	logistic	logistic	ADJ
easat-1848	306	6	regression	regression	NOUN
easat-1848	306	7	,	,	PUNCT
easat-1848	306	8	k	k	X
easat-1848	306	9	-	-	PUNCT
easat-1848	306	10	nearest	near	ADJ
easat-1848	306	11	neighbour	neighbour	NOUN
easat-1848	306	12	,	,	PUNCT
easat-1848	306	13	random	random	ADJ
easat-1848	306	14	forest	forest	NOUN
easat-1848	306	15	,	,	PUNCT
easat-1848	306	16	support	support	NOUN
easat-1848	306	17	vector	vector	NOUN
easat-1848	306	18	machine	machine	NOUN
easat-1848	306	19	,	,	PUNCT
easat-1848	306	20	naïve	naïve	ADJ
easat-1848	306	21	bayes	bayes	NOUN
easat-1848	306	22	and	and	CCONJ
easat-1848	306	23	neural	neural	ADJ
easat-1848	306	24	network	network	NOUN
easat-1848	306	25	after	after	SCONJ
easat-1848	306	26	rfe	rfe	NOUN
easat-1848	306	27	feature	feature	NOUN
easat-1848	306	28	selection	selection	NOUN
easat-1848	306	29	are	be	AUX
easat-1848	306	30	86.92	86.92	NUM
easat-1848	306	31	,	,	PUNCT
easat-1848	306	32	82.73	82.73	NUM
easat-1848	306	33	,	,	PUNCT
easat-1848	306	34	86.79	86.79	NUM
easat-1848	306	35	,	,	PUNCT
easat-1848	306	36	88.05	88.05	NUM
easat-1848	306	37	,	,	PUNCT
easat-1848	306	38	84.37	84.37	NUM
easat-1848	306	39	,	,	PUNCT
easat-1848	306	40	88.34	88.34	NUM
easat-1848	306	41	respectively	respectively	ADV
easat-1848	306	42	.	.	PUNCT
easat-1848	307	1	after	after	ADP
easat-1848	307	2	the	the	DET
easat-1848	307	3	deployment	deployment	NOUN
easat-1848	307	4	of	of	ADP
easat-1848	307	5	feature	feature	NOUN
easat-1848	307	6	selection	selection	NOUN
easat-1848	307	7	method	method	NOUN
easat-1848	307	8	mr	mr	PROPN
easat-1848	307	9	-	-	PUNCT
easat-1848	307	10	mr	mr	PROPN
easat-1848	307	11	,	,	PUNCT
easat-1848	307	12	the	the	DET
easat-1848	307	13	f1	f1	ADJ
easat-1848	307	14	score	score	NOUN
easat-1848	307	15	measure	measure	NOUN
easat-1848	307	16	of	of	ADP
easat-1848	307	17	logistic	logistic	ADJ
easat-1848	307	18	regression	regression	NOUN
easat-1848	307	19	,	,	PUNCT
easat-1848	307	20	neural	neural	ADJ
easat-1848	307	21	network	network	NOUN
easat-1848	307	22	random	random	ADJ
easat-1848	307	23	forest	forest	NOUN
easat-1848	307	24	,	,	PUNCT
easat-1848	307	25	support	support	NOUN
easat-1848	307	26	vector	vector	NOUN
easat-1848	307	27	machine	machine	NOUN
easat-1848	307	28	,	,	PUNCT
easat-1848	307	29	naïve	naïve	ADJ
easat-1848	307	30	bayes	bayes	NOUN
easat-1848	307	31	and	and	CCONJ
easat-1848	307	32	k	k	NOUN
easat-1848	307	33	-	-	PUNCT
easat-1848	307	34	nearest	near	ADJ
easat-1848	307	35	neighbour	neighbour	NOUN
easat-1848	307	36	,	,	PUNCT
easat-1848	307	37	are	be	AUX
easat-1848	307	38	82.52	82.52	NUM
easat-1848	307	39	,	,	PUNCT
easat-1848	307	40	92.62	92.62	NUM
easat-1848	307	41	,	,	PUNCT
easat-1848	307	42	91.32	91.32	NUM
easat-1848	307	43	,	,	PUNCT
easat-1848	307	44	86.15	86.15	NUM
easat-1848	307	45	,	,	PUNCT
easat-1848	307	46	81.22	81.22	NUM
easat-1848	307	47	,	,	PUNCT
easat-1848	307	48	80	80	NUM
easat-1848	307	49	respectively	respectively	ADV
easat-1848	307	50	.	.	PUNCT
easat-1848	308	1	the	the	DET
easat-1848	308	2	random	random	ADJ
easat-1848	308	3	forest	forest	NOUN
easat-1848	308	4	and	and	CCONJ
easat-1848	308	5	neural	neural	ADJ
easat-1848	308	6	network	network	NOUN
easat-1848	308	7	classifier	classifier	NOUN
easat-1848	308	8	implemented	implement	VERB
easat-1848	308	9	using	use	VERB
easat-1848	308	10	lasso	lasso	NOUN
easat-1848	308	11	feature	feature	NOUN
easat-1848	308	12	selection	selection	NOUN
easat-1848	308	13	techniques	technique	NOUN
easat-1848	308	14	have	have	AUX
easat-1848	308	15	achieved	achieve	VERB
easat-1848	308	16	high	high	ADJ
easat-1848	308	17	f1	f1	NOUN
easat-1848	308	18	measure	measure	NOUN
easat-1848	308	19	than	than	ADP
easat-1848	308	20	other	other	ADJ
easat-1848	308	21	algorithms	algorithm	NOUN
easat-1848	308	22	.	.	PUNCT
easat-1848	309	1	figure	figure	VERB
easat-1848	309	2	6	6	NUM
easat-1848	309	3	.	.	PUNCT
easat-1848	310	1	fl	fl	NOUN
easat-1848	310	2	-	-	PUNCT
easat-1848	310	3	measure	measure	NOUN
easat-1848	310	4	of	of	ADP
easat-1848	310	5	different	different	ADJ
easat-1848	310	6	classifier	classifier	NOUN
easat-1848	310	7	with	with	ADP
easat-1848	310	8	feature	feature	NOUN
easat-1848	310	9	selection	selection	NOUN
easat-1848	310	10	methods	method	NOUN
easat-1848	310	11	.	.	PUNCT
easat-1848	311	1	1467	1467	NUM
easat-1848	311	2	edelweiss	edelweiss	PROPN
easat-1848	311	3	applied	apply	VERB
easat-1848	311	4	science	science	NOUN
easat-1848	311	5	and	and	CCONJ
easat-1848	311	6	technology	technology	NOUN
easat-1848	311	7	issn	issn	PROPN
easat-1848	311	8	:	:	PUNCT
easat-1848	311	9	2576	2576	NUM
easat-1848	311	10	-	-	SYM
easat-1848	311	11	8484	8484	NUM
easat-1848	311	12	vol	vol	NOUN
easat-1848	311	13	.	.	PROPN
easat-1848	311	14	8	8	NUM
easat-1848	311	15	,	,	PUNCT
easat-1848	311	16	no	no	INTJ
easat-1848	311	17	.	.	NOUN
easat-1848	311	18	5	5	NUM
easat-1848	311	19	:	:	SYM
easat-1848	311	20	1445	1445	NUM
easat-1848	311	21	-	-	SYM
easat-1848	311	22	1471	1471	NUM
easat-1848	311	23	,	,	PUNCT
easat-1848	311	24	2024	2024	NUM
easat-1848	311	25	doi	doi	NOUN
easat-1848	311	26	:	:	PUNCT
easat-1848	311	27	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	311	28	©	©	PROPN
easat-1848	311	29	2024	2024	NUM
easat-1848	311	30	by	by	ADP
easat-1848	311	31	the	the	DET
easat-1848	311	32	authors	author	NOUN
easat-1848	311	33	;	;	PUNCT
easat-1848	311	34	licensee	licensee	PROPN
easat-1848	311	35	learning	learn	VERB
easat-1848	311	36	gate	gate	NOUN
easat-1848	311	37	figure	figure	NOUN
easat-1848	311	38	7	7	NUM
easat-1848	311	39	below	below	ADV
easat-1848	311	40	shows	show	VERB
easat-1848	311	41	the	the	DET
easat-1848	311	42	mean	mean	ADJ
easat-1848	311	43	squared	square	VERB
easat-1848	311	44	error	error	NOUN
easat-1848	311	45	(	(	PUNCT
easat-1848	311	46	mse	mse	NOUN
easat-1848	311	47	)	)	PUNCT
easat-1848	311	48	of	of	ADP
easat-1848	311	49	deep	deep	ADJ
easat-1848	311	50	learning	learning	NOUN
easat-1848	311	51	algorithms	algorithm	NOUN
easat-1848	311	52	and	and	CCONJ
easat-1848	311	53	machine	machine	NOUN
easat-1848	311	54	learning	learn	VERB
easat-1848	311	55	after	after	ADP
easat-1848	311	56	each	each	DET
easat-1848	311	57	feature	feature	NOUN
easat-1848	311	58	selection	selection	NOUN
easat-1848	311	59	method	method	NOUN
easat-1848	311	60	.	.	PUNCT
easat-1848	312	1	after	after	ADP
easat-1848	312	2	implementing	implement	VERB
easat-1848	312	3	feature	feature	NOUN
easat-1848	312	4	selection	selection	NOUN
easat-1848	312	5	method	method	NOUN
easat-1848	312	6	lasso	lasso	NOUN
easat-1848	312	7	,	,	PUNCT
easat-1848	312	8	random	random	ADJ
easat-1848	312	9	forest	forest	NOUN
easat-1848	312	10	and	and	CCONJ
easat-1848	312	11	neural	neural	ADJ
easat-1848	312	12	network	network	NOUN
easat-1848	312	13	achieves	achieve	VERB
easat-1848	312	14	high	high	ADJ
easat-1848	312	15	performance	performance	NOUN
easat-1848	312	16	with	with	ADP
easat-1848	312	17	least	least	ADJ
easat-1848	312	18	mean	mean	VERB
easat-1848	312	19	squared	square	VERB
easat-1848	312	20	error	error	NOUN
easat-1848	312	21	of	of	ADP
easat-1848	312	22	4.62	4.62	NUM
easat-1848	312	23	and	and	CCONJ
easat-1848	312	24	4.02	4.02	NUM
easat-1848	312	25	respectively	respectively	ADV
easat-1848	312	26	compared	compare	VERB
easat-1848	312	27	to	to	ADP
easat-1848	312	28	other	other	ADJ
easat-1848	312	29	algorithms	algorithm	NOUN
easat-1848	312	30	.	.	PUNCT
easat-1848	313	1	figure	figure	VERB
easat-1848	313	2	7	7	NUM
easat-1848	313	3	.	.	PUNCT
easat-1848	314	1	mean	mean	VERB
easat-1848	314	2	squared	square	VERB
easat-1848	314	3	error	error	NOUN
easat-1848	314	4	of	of	ADP
easat-1848	314	5	different	different	ADJ
easat-1848	314	6	classifier	classifier	NOUN
easat-1848	314	7	with	with	ADP
easat-1848	314	8	feature	feature	NOUN
easat-1848	314	9	selection	selection	NOUN
easat-1848	314	10	methods	method	NOUN
easat-1848	314	11	.	.	PUNCT
easat-1848	315	1	figure	figure	NOUN
easat-1848	315	2	8	8	NUM
easat-1848	315	3	below	below	ADV
easat-1848	315	4	shows	show	VERB
easat-1848	315	5	the	the	DET
easat-1848	315	6	mean	mean	ADJ
easat-1848	315	7	absolute	absolute	ADJ
easat-1848	315	8	error	error	NOUN
easat-1848	315	9	(	(	PUNCT
easat-1848	315	10	mae	mae	PROPN
easat-1848	315	11	)	)	PUNCT
easat-1848	315	12	of	of	ADP
easat-1848	315	13	machine	machine	NOUN
easat-1848	315	14	learning	learning	NOUN
easat-1848	315	15	and	and	CCONJ
easat-1848	315	16	deep	deep	ADJ
easat-1848	315	17	learning	learning	NOUN
easat-1848	315	18	algorithms	algorithm	NOUN
easat-1848	315	19	after	after	ADP
easat-1848	315	20	each	each	DET
easat-1848	315	21	attribute	attribute	NOUN
easat-1848	315	22	selection	selection	NOUN
easat-1848	315	23	method	method	NOUN
easat-1848	315	24	.	.	PUNCT
easat-1848	316	1	after	after	ADP
easat-1848	316	2	implementing	implement	VERB
easat-1848	316	3	feature	feature	NOUN
easat-1848	316	4	selection	selection	NOUN
easat-1848	316	5	method	method	NOUN
easat-1848	316	6	lasso	lasso	NOUN
easat-1848	316	7	,	,	PUNCT
easat-1848	316	8	random	random	ADJ
easat-1848	316	9	forest	forest	NOUN
easat-1848	316	10	and	and	CCONJ
easat-1848	316	11	neural	neural	ADJ
easat-1848	316	12	network	network	NOUN
easat-1848	316	13	achieves	achieve	VERB
easat-1848	316	14	high	high	ADJ
easat-1848	316	15	performance	performance	NOUN
easat-1848	316	16	with	with	ADP
easat-1848	316	17	least	least	ADJ
easat-1848	316	18	mean	mean	VERB
easat-1848	316	19	absolute	absolute	ADJ
easat-1848	316	20	error	error	NOUN
easat-1848	316	21	of	of	ADP
easat-1848	316	22	4.62	4.62	NUM
easat-1848	316	23	and	and	CCONJ
easat-1848	316	24	4.02	4.02	NUM
easat-1848	316	25	respectively	respectively	ADV
easat-1848	316	26	compared	compare	VERB
easat-1848	316	27	to	to	ADP
easat-1848	316	28	other	other	ADJ
easat-1848	316	29	algorithms	algorithm	NOUN
easat-1848	316	30	.	.	PUNCT
easat-1848	317	1	figure	figure	VERB
easat-1848	317	2	8	8	NUM
easat-1848	317	3	.	.	PUNCT
easat-1848	318	1	mean	mean	VERB
easat-1848	318	2	absolute	absolute	ADJ
easat-1848	318	3	error	error	NOUN
easat-1848	318	4	of	of	ADP
easat-1848	318	5	different	different	ADJ
easat-1848	318	6	classifier	classifier	NOUN
easat-1848	318	7	with	with	ADP
easat-1848	318	8	feature	feature	NOUN
easat-1848	318	9	selection	selection	NOUN
easat-1848	318	10	methods	method	NOUN
easat-1848	318	11	.	.	PUNCT
easat-1848	319	1	1468	1468	NUM
easat-1848	319	2	edelweiss	edelweiss	PROPN
easat-1848	319	3	applied	apply	VERB
easat-1848	319	4	science	science	NOUN
easat-1848	319	5	and	and	CCONJ
easat-1848	319	6	technology	technology	NOUN
easat-1848	319	7	issn	issn	PROPN
easat-1848	319	8	:	:	PUNCT
easat-1848	319	9	2576	2576	NUM
easat-1848	319	10	-	-	SYM
easat-1848	319	11	8484	8484	NUM
easat-1848	319	12	vol	vol	NOUN
easat-1848	319	13	.	.	PROPN
easat-1848	319	14	8	8	NUM
easat-1848	319	15	,	,	PUNCT
easat-1848	319	16	no	no	INTJ
easat-1848	319	17	.	.	NOUN
easat-1848	319	18	5	5	NUM
easat-1848	319	19	:	:	SYM
easat-1848	319	20	1445	1445	NUM
easat-1848	319	21	-	-	SYM
easat-1848	319	22	1471	1471	NUM
easat-1848	319	23	,	,	PUNCT
easat-1848	319	24	2024	2024	NUM
easat-1848	319	25	doi	doi	NOUN
easat-1848	319	26	:	:	PUNCT
easat-1848	319	27	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	319	28	©	©	PROPN
easat-1848	319	29	2024	2024	NUM
easat-1848	319	30	by	by	ADP
easat-1848	319	31	the	the	DET
easat-1848	319	32	authors	author	NOUN
easat-1848	319	33	;	;	PUNCT
easat-1848	319	34	licensee	licensee	PROPN
easat-1848	319	35	learning	learn	VERB
easat-1848	319	36	gate	gate	NOUN
easat-1848	319	37	figure	figure	NOUN
easat-1848	319	38	9	9	NUM
easat-1848	319	39	.	.	PUNCT
easat-1848	320	1	different	different	ADJ
easat-1848	320	2	feature	feature	NOUN
easat-1848	320	3	selection	selection	NOUN
easat-1848	320	4	on	on	ADP
easat-1848	320	5	neural	neural	ADJ
easat-1848	320	6	network	network	NOUN
easat-1848	320	7	.	.	PUNCT
easat-1848	321	1	figure.9	figure.9	NOUN
easat-1848	321	2	above	above	ADV
easat-1848	321	3	shows	show	VERB
easat-1848	321	4	the	the	DET
easat-1848	321	5	accuracy	accuracy	NOUN
easat-1848	321	6	,	,	PUNCT
easat-1848	321	7	recall	recall	NOUN
easat-1848	321	8	,	,	PUNCT
easat-1848	321	9	precision	precision	NOUN
easat-1848	321	10	,	,	PUNCT
easat-1848	321	11	f1score	f1score	NOUN
easat-1848	321	12	,	,	PUNCT
easat-1848	321	13	mean	mean	VERB
easat-1848	321	14	squared	square	VERB
easat-1848	321	15	error	error	NOUN
easat-1848	321	16	and	and	CCONJ
easat-1848	321	17	mean	mean	VERB
easat-1848	321	18	absolute	absolute	ADJ
easat-1848	321	19	error	error	NOUN
easat-1848	321	20	of	of	ADP
easat-1848	321	21	neural	neural	ADJ
easat-1848	321	22	network	network	NOUN
easat-1848	321	23	after	after	ADP
easat-1848	321	24	deploying	deploy	VERB
easat-1848	321	25	different	different	ADJ
easat-1848	321	26	feature	feature	NOUN
easat-1848	321	27	selection	selection	NOUN
easat-1848	321	28	methods	method	NOUN
easat-1848	321	29	such	such	ADJ
easat-1848	321	30	as	as	ADP
easat-1848	321	31	lasso	lasso	NOUN
easat-1848	321	32	,	,	PUNCT
easat-1848	321	33	relief	relief	NOUN
easat-1848	321	34	,	,	PUNCT
easat-1848	321	35	mr	mr	PROPN
easat-1848	321	36	-	-	PUNCT
easat-1848	321	37	mr	mr	PROPN
easat-1848	321	38	,	,	PUNCT
easat-1848	321	39	rfe	rfe	NOUN
easat-1848	321	40	,	,	PUNCT
easat-1848	321	41	and	and	CCONJ
easat-1848	321	42	pca	pca	PROPN
easat-1848	321	43	.	.	PUNCT
easat-1848	322	1	after	after	ADP
easat-1848	322	2	implementing	implement	VERB
easat-1848	322	3	feature	feature	NOUN
easat-1848	322	4	selection	selection	NOUN
easat-1848	322	5	method	method	NOUN
easat-1848	322	6	lasso	lasso	NOUN
easat-1848	322	7	,	,	PUNCT
easat-1848	322	8	neural	neural	ADJ
easat-1848	322	9	network	network	NOUN
easat-1848	322	10	technique	technique	NOUN
easat-1848	322	11	achieved	achieve	VERB
easat-1848	322	12	high	high	ADJ
easat-1848	322	13	performance	performance	NOUN
easat-1848	322	14	with	with	ADP
easat-1848	322	15	accuracy	accuracy	NOUN
easat-1848	322	16	of	of	ADP
easat-1848	322	17	95.92	95.92	NUM
easat-1848	322	18	%	%	NOUN
easat-1848	322	19	,	,	PUNCT
easat-1848	322	20	precision	precision	NOUN
easat-1848	322	21	96.35	96.35	NUM
easat-1848	322	22	%	%	NOUN
easat-1848	322	23	,	,	PUNCT
easat-1848	322	24	recall	recall	VERB
easat-1848	322	25	97.45	97.45	NUM
easat-1848	322	26	%	%	NOUN
easat-1848	322	27	,	,	PUNCT
easat-1848	322	28	f1	f1	NOUN
easat-1848	322	29	measure	measure	NOUN
easat-1848	322	30	95.21	95.21	NUM
easat-1848	322	31	%	%	NOUN
easat-1848	322	32	with	with	ADP
easat-1848	322	33	least	least	ADJ
easat-1848	322	34	mean	mean	VERB
easat-1848	322	35	squared	square	VERB
easat-1848	322	36	error	error	NOUN
easat-1848	322	37	and	and	CCONJ
easat-1848	322	38	mean	mean	VERB
easat-1848	322	39	absolute	absolute	ADJ
easat-1848	322	40	error	error	NOUN
easat-1848	322	41	of	of	ADP
easat-1848	322	42	4.02	4.02	NUM
easat-1848	322	43	respectively	respectively	ADV
easat-1848	322	44	compared	compare	VERB
easat-1848	322	45	to	to	ADP
easat-1848	322	46	other	other	ADJ
easat-1848	322	47	algorithms	algorithm	NOUN
easat-1848	322	48	.	.	PUNCT
easat-1848	323	1	5	5	X
easat-1848	323	2	.	.	X
easat-1848	323	3	conclusion	conclusion	NOUN
easat-1848	323	4	cardiovascular	cardiovascular	ADJ
easat-1848	323	5	disease	disease	NOUN
easat-1848	323	6	has	have	AUX
easat-1848	323	7	emerged	emerge	VERB
easat-1848	323	8	in	in	ADP
easat-1848	323	9	the	the	DET
easat-1848	323	10	last	last	ADJ
easat-1848	323	11	ten	ten	NUM
easat-1848	323	12	years	year	NOUN
easat-1848	323	13	as	as	ADP
easat-1848	323	14	a	a	DET
easat-1848	323	15	major	major	ADJ
easat-1848	323	16	medical	medical	ADJ
easat-1848	323	17	problem	problem	NOUN
easat-1848	323	18	with	with	ADP
easat-1848	323	19	high	high	ADJ
easat-1848	323	20	death	death	NOUN
easat-1848	323	21	rate	rate	NOUN
easat-1848	323	22	.	.	PUNCT
easat-1848	324	1	for	for	ADP
easat-1848	324	2	the	the	DET
easat-1848	324	3	intelligent	intelligent	ADJ
easat-1848	324	4	prediction	prediction	NOUN
easat-1848	324	5	of	of	ADP
easat-1848	324	6	cardiovascular	cardiovascular	ADJ
easat-1848	324	7	disease	disease	NOUN
easat-1848	324	8	(	(	PUNCT
easat-1848	324	9	cvd	cvd	PROPN
easat-1848	324	10	)	)	PUNCT
easat-1848	324	11	,	,	PUNCT
easat-1848	324	12	combined	combine	VERB
easat-1848	324	13	standard	standard	ADJ
easat-1848	324	14	benchmark	benchmark	NOUN
easat-1848	324	15	dataset	dataset	NOUN
easat-1848	324	16	was	be	AUX
easat-1848	324	17	utilized	utilize	VERB
easat-1848	324	18	to	to	PART
easat-1848	324	19	evaluate	evaluate	VERB
easat-1848	324	20	the	the	DET
easat-1848	324	21	efficiency	efficiency	NOUN
easat-1848	324	22	of	of	ADP
easat-1848	324	23	suggested	suggest	VERB
easat-1848	324	24	strategy	strategy	NOUN
easat-1848	324	25	.	.	PUNCT
easat-1848	325	1	different	different	ADJ
easat-1848	325	2	feature	feature	NOUN
easat-1848	325	3	selection	selection	NOUN
easat-1848	325	4	methods	method	NOUN
easat-1848	325	5	,	,	PUNCT
easat-1848	325	6	such	such	ADJ
easat-1848	325	7	as	as	ADP
easat-1848	325	8	lasso	lasso	NOUN
easat-1848	325	9	,	,	PUNCT
easat-1848	325	10	relief	relief	NOUN
easat-1848	325	11	,	,	PUNCT
easat-1848	325	12	mr	mr	PROPN
easat-1848	325	13	-	-	PUNCT
easat-1848	325	14	mr	mr	PROPN
easat-1848	325	15	,	,	PUNCT
easat-1848	325	16	rfe	rfe	NOUN
easat-1848	325	17	,	,	PUNCT
easat-1848	325	18	and	and	CCONJ
easat-1848	325	19	pca	pca	NOUN
easat-1848	325	20	were	be	AUX
easat-1848	325	21	contributed	contribute	VERB
easat-1848	325	22	on	on	ADP
easat-1848	325	23	machine	machine	NOUN
easat-1848	325	24	learning	learn	VERB
easat-1848	325	25	algorithms	algorithm	NOUN
easat-1848	325	26	such	such	ADJ
easat-1848	325	27	as	as	ADP
easat-1848	325	28	random	random	ADJ
easat-1848	325	29	forest	forest	NOUN
easat-1848	325	30	,	,	PUNCT
easat-1848	325	31	logistic	logistic	ADJ
easat-1848	325	32	regression	regression	NOUN
easat-1848	325	33	,	,	PUNCT
easat-1848	325	34	k	k	X
easat-1848	325	35	-	-	PUNCT
easat-1848	325	36	nearest	near	ADJ
easat-1848	325	37	neighbour	neighbour	NOUN
easat-1848	325	38	,	,	PUNCT
easat-1848	325	39	naïve	naïve	ADJ
easat-1848	325	40	bayes	bayes	NOUN
easat-1848	325	41	,	,	PUNCT
easat-1848	325	42	support	support	VERB
easat-1848	325	43	vector	vector	NOUN
easat-1848	325	44	machine	machine	NOUN
easat-1848	325	45	,	,	PUNCT
easat-1848	325	46	and	and	CCONJ
easat-1848	325	47	neural	neural	ADJ
easat-1848	325	48	network	network	NOUN
easat-1848	325	49	for	for	ADP
easat-1848	325	50	prediction	prediction	NOUN
easat-1848	325	51	of	of	ADP
easat-1848	325	52	heart	heart	NOUN
easat-1848	325	53	disease	disease	NOUN
easat-1848	325	54	.	.	PUNCT
easat-1848	326	1	the	the	DET
easat-1848	326	2	outcomes	outcome	NOUN
easat-1848	326	3	were	be	AUX
easat-1848	326	4	then	then	ADV
easat-1848	326	5	compared	compare	VERB
easat-1848	326	6	using	use	VERB
easat-1848	326	7	assessment	assessment	NOUN
easat-1848	326	8	criteria	criterion	NOUN
easat-1848	326	9	such	such	ADJ
easat-1848	326	10	as	as	ADP
easat-1848	326	11	accuracy	accuracy	NOUN
easat-1848	326	12	,	,	PUNCT
easat-1848	326	13	precision	precision	NOUN
easat-1848	326	14	,	,	PUNCT
easat-1848	326	15	recall	recall	NOUN
easat-1848	326	16	,	,	PUNCT
easat-1848	326	17	f1score	f1score	NOUN
easat-1848	326	18	,	,	PUNCT
easat-1848	326	19	mse	mse	NOUN
easat-1848	326	20	,	,	PUNCT
easat-1848	326	21	and	and	CCONJ
easat-1848	326	22	mae	mae	PROPN
easat-1848	326	23	.	.	PUNCT
easat-1848	327	1	the	the	DET
easat-1848	327	2	primary	primary	ADJ
easat-1848	327	3	outcome	outcome	NOUN
easat-1848	327	4	was	be	AUX
easat-1848	327	5	thorough	thorough	ADJ
easat-1848	327	6	comparison	comparison	NOUN
easat-1848	327	7	of	of	ADP
easat-1848	327	8	several	several	ADJ
easat-1848	327	9	feature	feature	NOUN
easat-1848	327	10	selection	selection	NOUN
easat-1848	327	11	strategies	strategy	NOUN
easat-1848	327	12	on	on	ADP
easat-1848	327	13	machine	machine	NOUN
easat-1848	327	14	algorithms	algorithm	NOUN
easat-1848	327	15	for	for	ADP
easat-1848	327	16	prediction	prediction	NOUN
easat-1848	327	17	of	of	ADP
easat-1848	327	18	cardiac	cardiac	ADJ
easat-1848	327	19	illnesses	illness	NOUN
easat-1848	327	20	.	.	PUNCT
easat-1848	328	1	the	the	DET
easat-1848	328	2	findings	finding	NOUN
easat-1848	328	3	revealed	reveal	VERB
easat-1848	328	4	that	that	SCONJ
easat-1848	328	5	the	the	DET
easat-1848	328	6	suggested	suggest	VERB
easat-1848	328	7	method	method	NOUN
easat-1848	328	8	computes	compute	VERB
easat-1848	328	9	extremely	extremely	ADV
easat-1848	328	10	favourable	favourable	ADJ
easat-1848	328	11	outcomes	outcome	NOUN
easat-1848	328	12	for	for	ADP
easat-1848	328	13	numerous	numerous	ADJ
easat-1848	328	14	statistically	statistically	ADV
easat-1848	328	15	relevant	relevant	ADJ
easat-1848	328	16	measurement	measurement	NOUN
easat-1848	328	17	parameters	parameter	NOUN
easat-1848	328	18	,	,	PUNCT
easat-1848	328	19	including	include	VERB
easat-1848	328	20	f1score	f1score	NOUN
easat-1848	328	21	,	,	PUNCT
easat-1848	328	22	mean	mean	NOUN
easat-1848	328	23	squared	square	VERB
easat-1848	328	24	error	error	NOUN
easat-1848	328	25	,	,	PUNCT
easat-1848	328	26	mean	mean	ADJ
easat-1848	328	27	absolute	absolute	ADJ
easat-1848	328	28	error	error	NOUN
easat-1848	328	29	accuracy	accuracy	NOUN
easat-1848	328	30	,	,	PUNCT
easat-1848	328	31	precision	precision	NOUN
easat-1848	328	32	,	,	PUNCT
easat-1848	328	33	and	and	CCONJ
easat-1848	328	34	recall	recall	NOUN
easat-1848	328	35	.	.	PUNCT
easat-1848	329	1	the	the	DET
easat-1848	329	2	random	random	ADJ
easat-1848	329	3	forest	forest	NOUN
easat-1848	329	4	and	and	CCONJ
easat-1848	329	5	neural	neural	ADJ
easat-1848	329	6	network	network	NOUN
easat-1848	329	7	classifier	classifier	NOUN
easat-1848	329	8	implemented	implement	VERB
easat-1848	329	9	using	use	VERB
easat-1848	329	10	lasso	lasso	NOUN
easat-1848	329	11	and	and	CCONJ
easat-1848	329	12	mr	mr	PROPN
easat-1848	329	13	-	-	PUNCT
easat-1848	329	14	mr	mr	PROPN
easat-1848	329	15	feature	feature	NOUN
easat-1848	329	16	selection	selection	NOUN
easat-1848	329	17	techniques	technique	NOUN
easat-1848	329	18	have	have	AUX
easat-1848	329	19	achieved	achieve	VERB
easat-1848	329	20	high	high	ADJ
easat-1848	329	21	accuracy	accuracy	NOUN
easat-1848	329	22	,	,	PUNCT
easat-1848	329	23	precision	precision	NOUN
easat-1848	329	24	,	,	PUNCT
easat-1848	329	25	recall	recall	NOUN
easat-1848	329	26	,	,	PUNCT
easat-1848	329	27	f1score	f1score	NOUN
easat-1848	329	28	[	[	X
easat-1848	329	29	43	43	NUM
easat-1848	329	30	]	]	X
easat-1848	330	1	[	[	X
easat-1848	330	2	44	44	NUM
easat-1848	330	3	]	]	PUNCT
easat-1848	331	1	[	[	X
easat-1848	331	2	45	45	NUM
easat-1848	331	3	]	]	PUNCT
easat-1848	331	4	with	with	ADP
easat-1848	331	5	least	least	ADJ
easat-1848	331	6	mean	mean	VERB
easat-1848	331	7	squared	square	VERB
easat-1848	331	8	error	error	NOUN
easat-1848	331	9	and	and	CCONJ
easat-1848	331	10	mean	mean	VERB
easat-1848	331	11	absolute	absolute	ADJ
easat-1848	331	12	error	error	NOUN
easat-1848	331	13	compared	compare	VERB
easat-1848	331	14	with	with	ADP
easat-1848	331	15	other	other	ADJ
easat-1848	331	16	algorithms	algorithm	NOUN
easat-1848	331	17	.	.	PUNCT
easat-1848	332	1	significant	significant	ADJ
easat-1848	332	2	improvements	improvement	NOUN
easat-1848	332	3	have	have	AUX
easat-1848	332	4	been	be	AUX
easat-1848	332	5	made	make	VERB
easat-1848	332	6	in	in	ADP
easat-1848	332	7	classification	classification	NOUN
easat-1848	332	8	performance	performance	NOUN
easat-1848	332	9	.	.	PUNCT
easat-1848	333	1	many	many	ADJ
easat-1848	333	2	real	real	ADJ
easat-1848	333	3	-	-	PUNCT
easat-1848	333	4	world	world	NOUN
easat-1848	333	5	applications	application	NOUN
easat-1848	333	6	,	,	PUNCT
easat-1848	333	7	such	such	ADJ
easat-1848	333	8	as	as	ADP
easat-1848	333	9	disease	disease	NOUN
easat-1848	333	10	diagnosis	diagnosis	NOUN
easat-1848	333	11	,	,	PUNCT
easat-1848	333	12	prediction	prediction	NOUN
easat-1848	333	13	,	,	PUNCT
easat-1848	333	14	and	and	CCONJ
easat-1848	333	15	engineering	engineering	NOUN
easat-1848	333	16	optimization	optimization	NOUN
easat-1848	333	17	issues	issue	NOUN
easat-1848	333	18	,	,	PUNCT
easat-1848	333	19	may	may	AUX
easat-1848	333	20	benefit	benefit	VERB
easat-1848	333	21	from	from	ADP
easat-1848	333	22	the	the	DET
easat-1848	333	23	use	use	NOUN
easat-1848	333	24	of	of	ADP
easat-1848	333	25	the	the	DET
easat-1848	333	26	suggested	suggest	VERB
easat-1848	333	27	approach	approach	NOUN
easat-1848	333	28	.	.	PUNCT
easat-1848	334	1	this	this	PRON
easat-1848	334	2	could	could	AUX
easat-1848	334	3	assist	assist	VERB
easat-1848	334	4	in	in	ADP
easat-1848	334	5	addressing	address	VERB
easat-1848	334	6	problems	problem	NOUN
easat-1848	334	7	in	in	ADP
easat-1848	334	8	real	real	ADJ
easat-1848	334	9	life	life	NOUN
easat-1848	334	10	.	.	PUNCT
easat-1848	335	1	copyright	copyright	NOUN
easat-1848	335	2	:	:	PUNCT
easat-1848	335	3	©	©	PROPN
easat-1848	335	4	2024	2024	NUM
easat-1848	335	5	by	by	ADP
easat-1848	335	6	the	the	DET
easat-1848	335	7	authors	author	NOUN
easat-1848	335	8	.	.	PUNCT
easat-1848	336	1	this	this	DET
easat-1848	336	2	article	article	NOUN
easat-1848	336	3	is	be	AUX
easat-1848	336	4	an	an	DET
easat-1848	336	5	open	open	ADJ
easat-1848	336	6	access	access	NOUN
easat-1848	336	7	article	article	NOUN
easat-1848	336	8	distributed	distribute	VERB
easat-1848	336	9	under	under	ADP
easat-1848	336	10	the	the	DET
easat-1848	336	11	terms	term	NOUN
easat-1848	336	12	and	and	CCONJ
easat-1848	336	13	conditions	condition	NOUN
easat-1848	336	14	of	of	ADP
easat-1848	336	15	the	the	DET
easat-1848	336	16	creative	creative	ADJ
easat-1848	336	17	commons	common	NOUN
easat-1848	336	18	attribution	attribution	NOUN
easat-1848	336	19	(	(	PUNCT
easat-1848	336	20	cc	cc	NOUN
easat-1848	336	21	by	by	ADP
easat-1848	336	22	)	)	PUNCT
easat-1848	336	23	license	license	NOUN
easat-1848	336	24	(	(	PUNCT
easat-1848	336	25	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-1848	336	26	)	)	PUNCT
easat-1848	336	27	.	.	PUNCT
easat-1848	337	1	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-1848	337	2	1469	1469	NUM
easat-1848	337	3	edelweiss	edelweiss	PROPN
easat-1848	337	4	applied	apply	VERB
easat-1848	337	5	science	science	NOUN
easat-1848	337	6	and	and	CCONJ
easat-1848	337	7	technology	technology	NOUN
easat-1848	337	8	issn	issn	PROPN
easat-1848	337	9	:	:	PUNCT
easat-1848	337	10	2576	2576	NUM
easat-1848	337	11	-	-	SYM
easat-1848	337	12	8484	8484	NUM
easat-1848	337	13	vol	vol	NOUN
easat-1848	337	14	.	.	PROPN
easat-1848	337	15	8	8	NUM
easat-1848	337	16	,	,	PUNCT
easat-1848	337	17	no	no	INTJ
easat-1848	337	18	.	.	NOUN
easat-1848	337	19	5	5	NUM
easat-1848	337	20	:	:	SYM
easat-1848	337	21	1445	1445	NUM
easat-1848	337	22	-	-	SYM
easat-1848	337	23	1471	1471	NUM
easat-1848	337	24	,	,	PUNCT
easat-1848	337	25	2024	2024	NUM
easat-1848	337	26	doi	doi	NOUN
easat-1848	337	27	:	:	PUNCT
easat-1848	337	28	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	337	29	©	©	PROPN
easat-1848	337	30	2024	2024	NUM
easat-1848	337	31	by	by	ADP
easat-1848	337	32	the	the	DET
easat-1848	337	33	authors	author	NOUN
easat-1848	337	34	;	;	PUNCT
easat-1848	337	35	licensee	licensee	PROPN
easat-1848	337	36	learning	learn	VERB
easat-1848	337	37	gate	gate	NOUN
easat-1848	337	38	references	reference	NOUN
easat-1848	337	39	[	[	X
easat-1848	337	40	1	1	NUM
easat-1848	337	41	]	]	PUNCT
easat-1848	337	42	abdallah	abdallah	PROPN
easat-1848	337	43	abdellatif	abdellatif	PROPN
easat-1848	337	44	,	,	PUNCT
easat-1848	337	45	hamdan	hamdan	PROPN
easat-1848	337	46	abdellatef	abdellatef	PROPN
easat-1848	337	47	,	,	PUNCT
easat-1848	337	48	jeevan	jeevan	PROPN
easat-1848	337	49	kanesan	kanesan	NOUN
easat-1848	337	50	,	,	PUNCT
easat-1848	337	51	chee	chee	NOUN
easat-1848	337	52	-	-	PUNCT
easat-1848	337	53	onn	onn	NOUN
easat-1848	337	54	chow	chow	NOUN
easat-1848	337	55	,	,	PUNCT
easat-1848	337	56	joon	joon	PROPN
easat-1848	337	57	huang	huang	PROPN
easat-1848	337	58	chuah	chuah	PROPN
easat-1848	337	59	and	and	CCONJ
easat-1848	337	60	hassan	hassan	PROPN
easat-1848	337	61	muwafaq	muwafaq	PROPN
easat-1848	337	62	gheni	gheni	NOUN
easat-1848	337	63	,	,	PUNCT
easat-1848	337	64	an	an	DET
easat-1848	337	65	effective	effective	ADJ
easat-1848	337	66	heart	heart	NOUN
easat-1848	337	67	disease	disease	NOUN
easat-1848	337	68	detection	detection	NOUN
easat-1848	337	69	and	and	CCONJ
easat-1848	337	70	severity	severity	NOUN
easat-1848	337	71	level	level	NOUN
easat-1848	337	72	classification	classification	NOUN
easat-1848	337	73	model	model	NOUN
easat-1848	337	74	using	use	VERB
easat-1848	337	75	machine	machine	NOUN
easat-1848	337	76	learning	learning	NOUN
easat-1848	337	77	and	and	CCONJ
easat-1848	337	78	hyperparameter	hyperparameter	NOUN
easat-1848	337	79	optimization	optimization	NOUN
easat-1848	337	80	methods	method	NOUN
easat-1848	337	81	,	,	PUNCT
easat-1848	337	82	ieee	ieee	NOUN
easat-1848	337	83	access	access	NOUN
easat-1848	337	84	,	,	PUNCT
easat-1848	337	85	volume	volume	NOUN
easat-1848	337	86	10	10	NUM
easat-1848	337	87	,	,	PUNCT
easat-1848	337	88	2022	2022	NUM
easat-1848	338	1	[	[	X
easat-1848	338	2	2	2	NUM
easat-1848	338	3	]	]	PUNCT
easat-1848	338	4	g.	g.	PROPN
easat-1848	338	5	bazoukis	bazoukis	PROPN
easat-1848	338	6	,	,	PUNCT
easat-1848	338	7	s.	s.	PROPN
easat-1848	338	8	stavrakis	stavrakis	PROPN
easat-1848	338	9	,	,	PUNCT
easat-1848	338	10	j.	j.	PROPN
easat-1848	338	11	zhou	zhou	PROPN
easat-1848	338	12	,	,	PUNCT
easat-1848	338	13	s.	s.	PROPN
easat-1848	338	14	c.	c.	PROPN
easat-1848	338	15	bollepalli	bollepalli	PROPN
easat-1848	338	16	,	,	PUNCT
easat-1848	338	17	g.	g.	PROPN
easat-1848	338	18	tse	tse	PROPN
easat-1848	338	19	,	,	PUNCT
easat-1848	338	20	q.	q.	PROPN
easat-1848	338	21	zhang	zhang	PROPN
easat-1848	338	22	,	,	PUNCT
easat-1848	338	23	j.	j.	PROPN
easat-1848	338	24	p.	p.	PROPN
easat-1848	338	25	singh	singh	PROPN
easat-1848	338	26	,	,	PUNCT
easat-1848	338	27	and	and	CCONJ
easat-1848	338	28	a.	a.	NOUN
easat-1848	338	29	a.	a.	NOUN
easat-1848	338	30	armoundas	armoundas	PROPN
easat-1848	338	31	,	,	PUNCT
easat-1848	338	32	‘	'	PUNCT
easat-1848	338	33	‘	'	PUNCT
easat-1848	338	34	machine	machine	NOUN
easat-1848	338	35	learning	learning	NOUN
easat-1848	338	36	versus	versus	ADP
easat-1848	338	37	conventional	conventional	ADJ
easat-1848	338	38	clinical	clinical	ADJ
easat-1848	338	39	methods	method	NOUN
easat-1848	338	40	in	in	ADP
easat-1848	338	41	guiding	guide	VERB
easat-1848	338	42	management	management	NOUN
easat-1848	338	43	of	of	ADP
easat-1848	338	44	heart	heart	NOUN
easat-1848	338	45	failure	failure	NOUN
easat-1848	338	46	patients	patient	NOUN
easat-1848	338	47	—	—	PUNCT
easat-1848	338	48	a	a	DET
easat-1848	338	49	systematic	systematic	ADJ
easat-1848	338	50	review	review	NOUN
easat-1848	338	51	,	,	PUNCT
easat-1848	338	52	’’	’'	PUNCT
easat-1848	338	53	heart	heart	NOUN
easat-1848	338	54	failure	failure	NOUN
easat-1848	338	55	rev	rev	VERB
easat-1848	338	56	.	.	PROPN
easat-1848	338	57	,	,	PUNCT
easat-1848	338	58	vol	vol	NOUN
easat-1848	338	59	.	.	PROPN
easat-1848	338	60	26	26	NUM
easat-1848	338	61	,	,	PUNCT
easat-1848	338	62	no	no	INTJ
easat-1848	338	63	.	.	NOUN
easat-1848	338	64	1	1	NUM
easat-1848	338	65	,	,	PUNCT
easat-1848	338	66	pp	pp	ADJ
easat-1848	338	67	.	.	PUNCT
easat-1848	339	1	23–34	23–34	NUM
easat-1848	339	2	,	,	PUNCT
easat-1848	339	3	jan	jan	PROPN
easat-1848	339	4	.	.	PROPN
easat-1848	339	5	2021	2021	NUM
easat-1848	339	6	[	[	X
easat-1848	339	7	3	3	X
easat-1848	339	8	]	]	X
easat-1848	339	9	yilmaz	yilmaz	PROPN
easat-1848	339	10	r	r	PROPN
easat-1848	339	11	,	,	PUNCT
easat-1848	339	12	yagin	yagin	NOUN
easat-1848	339	13	fh	fh	PROPN
easat-1848	339	14	.	.	PROPN
easat-1848	339	15	,	,	PUNCT
easat-1848	339	16	“	"	PUNCT
easat-1848	339	17	early	early	ADJ
easat-1848	339	18	detection	detection	NOUN
easat-1848	339	19	of	of	ADP
easat-1848	339	20	coronary	coronary	ADJ
easat-1848	339	21	heart	heart	NOUN
easat-1848	339	22	disease	disease	NOUN
easat-1848	339	23	based	base	VERB
easat-1848	339	24	on	on	ADP
easat-1848	339	25	machine	machine	NOUN
easat-1848	339	26	learning	learning	NOUN
easat-1848	339	27	methods	method	NOUN
easat-1848	339	28	”	"	PUNCT
easat-1848	339	29	,	,	PUNCT
easat-1848	339	30	international	international	ADJ
easat-1848	339	31	medical	medical	ADJ
easat-1848	339	32	journal	journal	NOUN
easat-1848	339	33	,	,	PUNCT
easat-1848	339	34	2022	2022	NUM
easat-1848	339	35	jan	jan	PROPN
easat-1848	339	36	1	1	NUM
easat-1848	339	37	;	;	PUNCT
easat-1848	339	38	4(1	4(1	NOUN
easat-1848	339	39	):	):	PUNCT
easat-1848	340	1	1–6	1–6	X
easat-1848	340	2	.	.	PUNCT
easat-1848	340	3	doi	doi	NOUN
easat-1848	340	4	:	:	PUNCT
easat-1848	340	5	10.37990	10.37990	NUM
easat-1848	340	6	/	/	SYM
easat-1848	340	7	medr.1011924	medr.1011924	NOUN
easat-1848	340	8	.	.	PUNCT
easat-1848	341	1	[	[	X
easat-1848	341	2	4	4	NUM
easat-1848	341	3	]	]	X
easat-1848	341	4	protima	protima	PROPN
easat-1848	341	5	khan	khan	PROPN
easat-1848	341	6	,	,	PUNCT
easat-1848	341	7	md	md	PROPN
easat-1848	341	8	.	.	PROPN
easat-1848	341	9	fazlul	fazlul	PROPN
easat-1848	341	10	kader	kader	PROPN
easat-1848	341	11	,	,	PUNCT
easat-1848	341	12	s.	s.	PROPN
easat-1848	341	13	m.	m.	PROPN
easat-1848	341	14	riazul	riazul	PROPN
easat-1848	341	15	islam	islam	PROPN
easat-1848	341	16	,	,	PUNCT
easat-1848	341	17	aisha	aisha	PROPN
easat-1848	341	18	b.	b.	PROPN
easat-1848	341	19	rahman	rahman	PROPN
easat-1848	341	20	,	,	PUNCT
easat-1848	341	21	md	md	PROPN
easat-1848	341	22	.	.	PROPN
easat-1848	341	23	shahriar	shahriar	PROPN
easat-1848	341	24	kamal	kamal	PROPN
easat-1848	341	25	,	,	PUNCT
easat-1848	341	26	masbah	masbah	ADJ
easat-1848	341	27	uddin	uddin	PROPN
easat-1848	341	28	toha	toha	PROPN
easat-1848	341	29	,	,	PUNCT
easat-1848	341	30	and	and	CCONJ
easat-1848	341	31	kyung	kyung	PROPN
easat-1848	341	32	-	-	PUNCT
easat-1848	341	33	sup	sup	PROPN
easat-1848	341	34	kwak	kwak	PROPN
easat-1848	341	35	,	,	PUNCT
easat-1848	341	36	“	"	PUNCT
easat-1848	341	37	machine	machine	NOUN
easat-1848	341	38	learning	learning	NOUN
easat-1848	341	39	and	and	CCONJ
easat-1848	341	40	deep	deep	ADJ
easat-1848	341	41	learning	learning	NOUN
easat-1848	341	42	approaches	approach	NOUN
easat-1848	341	43	for	for	ADP
easat-1848	341	44	brain	brain	NOUN
easat-1848	341	45	disease	disease	NOUN
easat-1848	341	46	diagnosis	diagnosis	NOUN
easat-1848	341	47	:	:	PUNCT
easat-1848	341	48	principles	principle	NOUN
easat-1848	341	49	and	and	CCONJ
easat-1848	341	50	recent	recent	ADJ
easat-1848	341	51	advances	advance	NOUN
easat-1848	341	52	”	"	PUNCT
easat-1848	341	53	,	,	PUNCT
easat-1848	341	54	ieee	ieee	NOUN
easat-1848	341	55	access	access	NOUN
easat-1848	341	56	,	,	PUNCT
easat-1848	341	57	volume	volume	NOUN
easat-1848	341	58	9	9	NUM
easat-1848	341	59	,	,	PUNCT
easat-1848	341	60	2021	2021	NUM
easat-1848	341	61	,	,	PUNCT
easat-1848	341	62	digital	digital	ADJ
easat-1848	341	63	object	object	NOUN
easat-1848	341	64	identifier	identifier	NOUN
easat-1848	341	65	10.1109	10.1109	NUM
easat-1848	341	66	/	/	SYM
easat-1848	341	67	access.2021.3062484	access.2021.3062484	X
easat-1848	342	1	[	[	X
easat-1848	342	2	5	5	NUM
easat-1848	342	3	]	]	X
easat-1848	342	4	pronab	pronab	PROPN
easat-1848	342	5	ghosh	ghosh	PROPN
easat-1848	342	6	,	,	PUNCT
easat-1848	342	7	sami	sami	PROPN
easat-1848	342	8	azam	azam	PROPN
easat-1848	342	9	,	,	PUNCT
easat-1848	342	10	mirjam	mirjam	PROPN
easat-1848	342	11	jonkman	jonkman	NOUN
easat-1848	342	12	,	,	PUNCT
easat-1848	342	13	asif	asif	PROPN
easat-1848	342	14	karim	karim	PROPN
easat-1848	342	15	,	,	PUNCT
easat-1848	342	16	f.	f.	PROPN
easat-1848	342	17	m.	m.	PROPN
easat-1848	342	18	javed	javed	PROPN
easat-1848	343	1	mehedi	mehedi	PROPN
easat-1848	343	2	shamrat	shamrat	PROPN
easat-1848	343	3	,	,	PUNCT
easat-1848	343	4	eva	eva	PROPN
easat-1848	343	5	ignatious	ignatious	NOUN
easat-1848	343	6	,	,	PUNCT
easat-1848	343	7	shahana	shahana	PROPN
easat-1848	343	8	shultana	shultana	PROPN
easat-1848	343	9	,	,	PUNCT
easat-1848	343	10	abhijith	abhijith	ADP
easat-1848	343	11	reddy	reddy	PROPN
easat-1848	343	12	beeravolu	beeravolu	PROPN
easat-1848	343	13	,	,	PUNCT
easat-1848	343	14	friso	friso	PROPN
easat-1848	343	15	de	de	PROPN
easat-1848	343	16	boer	boer	PROPN
easat-1848	343	17	(	(	PUNCT
easat-1848	343	18	2021	2021	NUM
easat-1848	343	19	)	)	PUNCT
easat-1848	343	20	.	.	PUNCT
easat-1848	344	1	efficient	efficient	ADJ
easat-1848	344	2	prediction	prediction	NOUN
easat-1848	344	3	of	of	ADP
easat-1848	344	4	cardiovascular	cardiovascular	ADJ
easat-1848	344	5	disease	disease	NOUN
easat-1848	344	6	using	use	VERB
easat-1848	344	7	machine	machine	NOUN
easat-1848	344	8	learning	learn	VERB
easat-1848	344	9	algorithms	algorithm	NOUN
easat-1848	344	10	with	with	ADP
easat-1848	344	11	relief	relief	NOUN
easat-1848	344	12	and	and	CCONJ
easat-1848	344	13	lasso	lasso	NOUN
easat-1848	344	14	feature	feature	NOUN
easat-1848	344	15	selection	selection	NOUN
easat-1848	344	16	techniques	technique	NOUN
easat-1848	344	17	.	.	PUNCT
easat-1848	345	1	ieee	ieee	NOUN
easat-1848	345	2	access	access	NOUN
easat-1848	345	3	,	,	PUNCT
easat-1848	345	4	vol9	vol9	PROPN
easat-1848	345	5	.	.	PUNCT
easat-1848	346	1	doi:10.1109	doi:10.1109	VERB
easat-1848	346	2	/	/	SYM
easat-1848	346	3	access.2021.3053759	access.2021.3053759	PROPN
easat-1848	346	4	[	[	X
easat-1848	346	5	6	6	NUM
easat-1848	346	6	]	]	X
easat-1848	346	7	jian	jian	PROPN
easat-1848	346	8	ping	ping	PROPN
easat-1848	346	9	li	li	PROPN
easat-1848	346	10	,	,	PUNCT
easat-1848	346	11	amin	amin	PROPN
easat-1848	346	12	ul	ul	PROPN
easat-1848	346	13	haq	haq	PROPN
easat-1848	346	14	,	,	PUNCT
easat-1848	346	15	salah	salah	PROPN
easat-1848	346	16	ud	ud	INTJ
easat-1848	346	17	din	din	PROPN
easat-1848	346	18	,	,	PUNCT
easat-1848	346	19	jalaluddin	jalaluddin	PROPN
easat-1848	346	20	khan	khan	PROPN
easat-1848	346	21	,	,	PUNCT
easat-1848	346	22	asif	asif	PROPN
easat-1848	346	23	khan	khan	PROPN
easat-1848	346	24	and	and	CCONJ
easat-1848	346	25	abdus	abdus	PROPN
easat-1848	346	26	saboor	saboor	PROPN
easat-1848	346	27	(	(	PUNCT
easat-1848	346	28	2020	2020	NUM
easat-1848	346	29	)	)	PUNCT
easat-1848	346	30	,	,	PUNCT
easat-1848	346	31	heart	heart	NOUN
easat-1848	346	32	disease	disease	NOUN
easat-1848	346	33	identification	identification	NOUN
easat-1848	346	34	method	method	NOUN
easat-1848	346	35	using	use	VERB
easat-1848	346	36	machine	machine	NOUN
easat-1848	346	37	learning	learn	VERB
easat-1848	346	38	classification	classification	NOUN
easat-1848	346	39	in	in	ADP
easat-1848	346	40	e	e	NOUN
easat-1848	346	41	-	-	NOUN
easat-1848	346	42	healthcare	healthcare	NOUN
easat-1848	346	43	.	.	PUNCT
easat-1848	347	1	ieee	ieee	NOUN
easat-1848	347	2	access	access	NOUN
easat-1848	347	3	,	,	PUNCT
easat-1848	347	4	8	8	NUM
easat-1848	347	5	(	(	PUNCT
easat-1848	347	6	)	)	PUNCT
easat-1848	347	7	,	,	PUNCT
easat-1848	347	8	107562–107582	107562–107582	NUM
easat-1848	347	9	.	.	PUNCT
easat-1848	348	1	doi:10.1109	doi:10.1109	VERB
easat-1848	348	2	/	/	SYM
easat-1848	348	3	access.2020.3001149	access.2020.3001149	VERB
easat-1848	348	4	[	[	X
easat-1848	348	5	7	7	X
easat-1848	348	6	]	]	X
easat-1848	348	7	usama	usama	PROPN
easat-1848	348	8	ahmed	ahmed	PROPN
easat-1848	348	9	,	,	PUNCT
easat-1848	348	10	ghassan	ghassan	PROPN
easat-1848	348	11	f.	f.	PROPN
easat-1848	348	12	issa	issa	PROPN
easat-1848	348	13	,	,	PUNCT
easat-1848	348	14	muhammad	muhammad	PROPN
easat-1848	348	15	adnan	adnan	PROPN
easat-1848	348	16	khan	khan	PROPN
easat-1848	348	17	,	,	PUNCT
easat-1848	348	18	shabib	shabib	PROPN
easat-1848	348	19	aftab	aftab	PROPN
easat-1848	348	20	,	,	PUNCT
easat-1848	348	21	muhammad	muhammad	PROPN
easat-1848	348	22	farhan	farhan	PROPN
easat-1848	348	23	khan	khan	PROPN
easat-1848	348	24	,	,	PUNCT
easat-1848	348	25	raed	raed	PROPN
easat-1848	348	26	a.	a.	PROPN
easat-1848	348	27	t.	t.	PROPN
easat-1848	348	28	said	say	VERB
easat-1848	348	29	,	,	PUNCT
easat-1848	348	30	taher	taher	PROPN
easat-1848	348	31	m.	m.	NOUN
easat-1848	348	32	ghazal	ghazal	PROPN
easat-1848	348	33	and	and	CCONJ
easat-1848	348	34	munir	munir	PROPN
easat-1848	348	35	ahmad	ahmad	PROPN
easat-1848	348	36	,	,	PUNCT
easat-1848	348	37	prediction	prediction	NOUN
easat-1848	348	38	of	of	ADP
easat-1848	348	39	diabetes	diabete	NOUN
easat-1848	348	40	empowered	empower	VERB
easat-1848	348	41	with	with	ADP
easat-1848	348	42	fused	fuse	VERB
easat-1848	348	43	machine	machine	NOUN
easat-1848	348	44	learning	learning	NOUN
easat-1848	348	45	,	,	PUNCT
easat-1848	348	46	ieee	ieee	NOUN
easat-1848	348	47	access	access	NOUN
easat-1848	348	48	,	,	PUNCT
easat-1848	348	49	volume	volume	NOUN
easat-1848	348	50	10	10	NUM
easat-1848	348	51	,	,	PUNCT
easat-1848	348	52	2022	2022	NUM
easat-1848	349	1	[	[	X
easat-1848	349	2	8	8	NUM
easat-1848	349	3	]	]	X
easat-1848	349	4	ghulab	ghulab	PROPN
easat-1848	349	5	nabi	nabi	PROPN
easat-1848	349	6	ahmad	ahmad	PROPN
easat-1848	349	7	,	,	PUNCT
easat-1848	349	8	shafiullah	shafiullah	PROPN
easat-1848	349	9	,	,	PUNCT
easat-1848	349	10	abdullah	abdullah	PROPN
easat-1848	349	11	algethami	algethami	PROPN
easat-1848	349	12	,	,	PUNCT
easat-1848	349	13	hira	hira	PROPN
easat-1848	349	14	fatima	fatima	PROPN
easat-1848	349	15	,	,	PUNCT
easat-1848	349	16	and	and	CCONJ
easat-1848	349	17	syed	syed	PROPN
easat-1848	349	18	md	md	PROPN
easat-1848	349	19	.	.	PROPN
easat-1848	349	20	humayun	humayun	PROPN
easat-1848	349	21	akhter	akhter	PROPN
easat-1848	349	22	,	,	PUNCT
easat-1848	349	23	comparative	comparative	ADJ
easat-1848	349	24	study	study	NOUN
easat-1848	349	25	of	of	ADP
easat-1848	349	26	optimum	optimum	ADJ
easat-1848	349	27	medical	medical	ADJ
easat-1848	349	28	diagnosis	diagnosis	NOUN
easat-1848	349	29	of	of	ADP
easat-1848	349	30	human	human	ADJ
easat-1848	349	31	heart	heart	NOUN
easat-1848	349	32	disease	disease	NOUN
easat-1848	349	33	using	use	VERB
easat-1848	349	34	machine	machine	NOUN
easat-1848	349	35	learning	learning	NOUN
easat-1848	349	36	technique	technique	NOUN
easat-1848	349	37	with	with	ADP
easat-1848	349	38	and	and	CCONJ
easat-1848	349	39	without	without	ADP
easat-1848	349	40	sequential	sequential	ADJ
easat-1848	349	41	feature	feature	NOUN
easat-1848	349	42	selection	selection	NOUN
easat-1848	349	43	,	,	PUNCT
easat-1848	349	44	ieee	ieee	NOUN
easat-1848	349	45	access	access	NOUN
easat-1848	349	46	,	,	PUNCT
easat-1848	349	47	volume	volume	NOUN
easat-1848	349	48	10	10	NUM
easat-1848	349	49	,	,	PUNCT
easat-1848	349	50	2022	2022	NUM
easat-1848	349	51	[	[	X
easat-1848	349	52	9	9	NUM
easat-1848	349	53	]	]	X
easat-1848	349	54	sarria	sarria	PROPN
easat-1848	349	55	e.	e.	PROPN
easat-1848	349	56	a.	a.	PROPN
easat-1848	349	57	ashri	ashri	PROPN
easat-1848	349	58	,	,	PUNCT
easat-1848	349	59	m.	m.	NOUN
easat-1848	349	60	m.	m.	PROPN
easat-1848	349	61	el	el	PROPN
easat-1848	349	62	-	-	PROPN
easat-1848	349	63	gayar	gayar	NOUN
easat-1848	349	64	,	,	PUNCT
easat-1848	349	65	and	and	CCONJ
easat-1848	349	66	eman	eman	PROPN
easat-1848	349	67	m.	m.	PROPN
easat-1848	349	68	el	el	PROPN
easat-1848	349	69	-	-	PUNCT
easat-1848	349	70	daydamony	daydamony	ADJ
easat-1848	349	71	,	,	PUNCT
easat-1848	349	72	heart	heart	NOUN
easat-1848	349	73	disease	disease	NOUN
easat-1848	349	74	prediction	prediction	NOUN
easat-1848	349	75	framework	framework	NOUN
easat-1848	349	76	based	base	VERB
easat-1848	349	77	on	on	ADP
easat-1848	349	78	hybrid	hybrid	ADJ
easat-1848	349	79	classifiers	classifier	NOUN
easat-1848	349	80	and	and	CCONJ
easat-1848	349	81	genetic	genetic	ADJ
easat-1848	349	82	algorithm	algorithm	NOUN
easat-1848	349	83	,	,	PUNCT
easat-1848	349	84	ieee	ieee	NOUN
easat-1848	349	85	access	access	NOUN
easat-1848	349	86	,	,	PUNCT
easat-1848	349	87	volume	volume	NOUN
easat-1848	349	88	9	9	NUM
easat-1848	349	89	,	,	PUNCT
easat-1848	349	90	2021	2021	NUM
easat-1848	349	91	[	[	X
easat-1848	349	92	10	10	NUM
easat-1848	349	93	]	]	X
easat-1848	349	94	huazhong	huazhong	PROPN
easat-1848	349	95	yang	yang	PROPN
easat-1848	349	96	,	,	PUNCT
easat-1848	349	97	zhongju	zhongju	PROPN
easat-1848	349	98	chen	chen	PROPN
easat-1848	349	99	,	,	PUNCT
easat-1848	349	100	huajian	huajian	PROPN
easat-1848	349	101	yang	yang	PROPN
easat-1848	349	102	,	,	PUNCT
easat-1848	349	103	and	and	CCONJ
easat-1848	349	104	maojin	maojin	VERB
easat-1848	349	105	tian	tian	PROPN
easat-1848	349	106	,	,	PUNCT
easat-1848	349	107	predicting	predict	VERB
easat-1848	349	108	coronary	coronary	ADJ
easat-1848	349	109	heart	heart	NOUN
easat-1848	349	110	disease	disease	NOUN
easat-1848	349	111	using	use	VERB
easat-1848	349	112	an	an	DET
easat-1848	349	113	improved	improve	VERB
easat-1848	349	114	lightgbm	lightgbm	ADJ
easat-1848	349	115	model	model	NOUN
easat-1848	349	116	:	:	PUNCT
easat-1848	349	117	performance	performance	NOUN
easat-1848	349	118	analysis	analysis	NOUN
easat-1848	349	119	and	and	CCONJ
easat-1848	349	120	comparison	comparison	NOUN
easat-1848	349	121	,	,	PUNCT
easat-1848	349	122	ieee	ieee	NOUN
easat-1848	349	123	access	access	NOUN
easat-1848	349	124	,	,	PUNCT
easat-1848	349	125	volume	volume	NOUN
easat-1848	349	126	11	11	NUM
easat-1848	349	127	,	,	PUNCT
easat-1848	349	128	2023	2023	NUM
easat-1848	350	1	[	[	X
easat-1848	350	2	11	11	NUM
easat-1848	350	3	]	]	PUNCT
easat-1848	350	4	mohammed	mohammed	PROPN
easat-1848	350	5	b.	b.	PROPN
easat-1848	350	6	abubaker	abubaker	PROPN
easat-1848	350	7	and	and	CCONJ
easat-1848	350	8	bilal	bilal	PROPN
easat-1848	350	9	babayigit	babayigit	PROPN
easat-1848	350	10	,	,	PUNCT
easat-1848	350	11	detection	detection	NOUN
easat-1848	350	12	of	of	ADP
easat-1848	350	13	cardiovascular	cardiovascular	ADJ
easat-1848	350	14	diseases	disease	NOUN
easat-1848	350	15	in	in	ADP
easat-1848	350	16	ecg	ecg	PROPN
easat-1848	350	17	images	image	NOUN
easat-1848	350	18	using	use	VERB
easat-1848	350	19	machine	machine	NOUN
easat-1848	350	20	learning	learning	NOUN
easat-1848	350	21	and	and	CCONJ
easat-1848	350	22	deep	deep	ADJ
easat-1848	350	23	learning	learning	NOUN
easat-1848	350	24	methods	method	NOUN
easat-1848	350	25	,	,	PUNCT
easat-1848	350	26	ieee	ieee	NOUN
easat-1848	350	27	transactions	transaction	NOUN
easat-1848	350	28	on	on	ADP
easat-1848	350	29	artificial	artificial	ADJ
easat-1848	350	30	intelligence	intelligence	NOUN
easat-1848	350	31	,	,	PUNCT
easat-1848	350	32	vol	vol	NOUN
easat-1848	350	33	.	.	PROPN
easat-1848	350	34	4	4	NUM
easat-1848	350	35	,	,	PUNCT
easat-1848	350	36	no	no	INTJ
easat-1848	350	37	.	.	NOUN
easat-1848	350	38	2	2	NUM
easat-1848	350	39	,	,	PUNCT
easat-1848	350	40	april	april	PROPN
easat-1848	350	41	2023	2023	NUM
easat-1848	350	42	[	[	X
easat-1848	350	43	12	12	NUM
easat-1848	350	44	]	]	X
easat-1848	350	45	tsatsral	tsatsral	ADJ
easat-1848	350	46	amarbayasgalan	amarbayasgalan	ADJ
easat-1848	350	47	,	,	PUNCT
easat-1848	350	48	van	van	PROPN
easat-1848	350	49	-	-	PUNCT
easat-1848	350	50	huy	huy	PROPN
easat-1848	350	51	pham	pham	PROPN
easat-1848	350	52	,	,	PUNCT
easat-1848	350	53	nipon	nipon	PROPN
easat-1848	350	54	theera	theera	NOUN
easat-1848	350	55	-	-	PUNCT
easat-1848	350	56	umpon	umpon	PROPN
easat-1848	350	57	,	,	PUNCT
easat-1848	350	58	yongjun	yongjun	NOUN
easat-1848	350	59	piao	piao	NOUN
easat-1848	350	60	and	and	CCONJ
easat-1848	350	61	keun	keun	PROPN
easat-1848	350	62	ho	ho	PROPN
easat-1848	350	63	ryu	ryu	PROPN
easat-1848	350	64	,	,	PUNCT
easat-1848	350	65	an	an	DET
easat-1848	350	66	efficient	efficient	ADJ
easat-1848	350	67	prediction	prediction	NOUN
easat-1848	350	68	method	method	NOUN
easat-1848	350	69	for	for	ADP
easat-1848	350	70	coronary	coronary	ADJ
easat-1848	350	71	heart	heart	NOUN
easat-1848	350	72	disease	disease	NOUN
easat-1848	350	73	risk	risk	NOUN
easat-1848	350	74	based	base	VERB
easat-1848	350	75	on	on	ADP
easat-1848	350	76	two	two	NUM
easat-1848	350	77	deep	deep	ADJ
easat-1848	350	78	neural	neural	ADJ
easat-1848	350	79	networks	network	NOUN
easat-1848	350	80	trained	train	VERB
easat-1848	350	81	on	on	ADP
easat-1848	350	82	well	well	ADV
easat-1848	350	83	-	-	PUNCT
easat-1848	350	84	ordered	order	VERB
easat-1848	350	85	training	training	NOUN
easat-1848	350	86	datasets	dataset	NOUN
easat-1848	350	87	,	,	PUNCT
easat-1848	350	88	ieee	ieee	NOUN
easat-1848	350	89	access	access	NOUN
easat-1848	350	90	,	,	PUNCT
easat-1848	350	91	volume	volume	NOUN
easat-1848	350	92	9	9	NUM
easat-1848	350	93	,	,	PUNCT
easat-1848	350	94	2021	2021	NUM
easat-1848	350	95	[	[	X
easat-1848	350	96	13	13	NUM
easat-1848	350	97	]	]	X
easat-1848	350	98	d.	d.	PROPN
easat-1848	350	99	cenitta	cenitta	PROPN
easat-1848	350	100	,	,	PUNCT
easat-1848	350	101	r.	r.	PROPN
easat-1848	350	102	vijaya	vijaya	PROPN
easat-1848	350	103	arjunan	arjunan	PROPN
easat-1848	350	104	and	and	CCONJ
easat-1848	350	105	k.	k.	PROPN
easat-1848	351	1	v.	v.	PROPN
easat-1848	351	2	prema	prema	PROPN
easat-1848	351	3	,	,	PUNCT
easat-1848	351	4	ischemic	ischemic	ADJ
easat-1848	351	5	heart	heart	NOUN
easat-1848	351	6	disease	disease	NOUN
easat-1848	351	7	prediction	prediction	NOUN
easat-1848	351	8	using	use	VERB
easat-1848	351	9	optimized	optimize	VERB
easat-1848	351	10	squirrel	squirrel	NOUN
easat-1848	351	11	search	search	NOUN
easat-1848	351	12	feature	feature	NOUN
easat-1848	351	13	selection	selection	NOUN
easat-1848	351	14	algorithm	algorithm	NOUN
easat-1848	351	15	,	,	PUNCT
easat-1848	351	16	ieee	ieee	NOUN
easat-1848	351	17	access	access	NOUN
easat-1848	351	18	,	,	PUNCT
easat-1848	351	19	volume	volume	NOUN
easat-1848	351	20	10	10	NUM
easat-1848	351	21	,	,	PUNCT
easat-1848	351	22	2022	2022	NUM
easat-1848	351	23	,	,	PUNCT
easat-1848	351	24	digital	digital	ADJ
easat-1848	351	25	object	object	NOUN
easat-1848	351	26	identifier	identifier	NOUN
easat-1848	351	27	10.1109	10.1109	NUM
easat-1848	351	28	/	/	SYM
easat-1848	351	29	access.2022.3223429	access.2022.3223429	NOUN
easat-1848	351	30	[	[	X
easat-1848	351	31	14	14	NUM
easat-1848	351	32	]	]	X
easat-1848	351	33	senthilkumar	senthilkumar	PROPN
easat-1848	351	34	mohan	mohan	PROPN
easat-1848	351	35	,	,	PUNCT
easat-1848	351	36	chandrasegar	chandrasegar	NOUN
easat-1848	351	37	thirumalai	thirumalai	NOUN
easat-1848	351	38	and	and	CCONJ
easat-1848	351	39	gautam	gautam	PROPN
easat-1848	351	40	srivastava	srivastava	PROPN
easat-1848	351	41	,	,	PUNCT
easat-1848	351	42	effective	effective	ADJ
easat-1848	351	43	heart	heart	NOUN
easat-1848	351	44	disease	disease	NOUN
easat-1848	351	45	prediction	prediction	NOUN
easat-1848	351	46	using	use	VERB
easat-1848	351	47	hybrid	hybrid	ADJ
easat-1848	351	48	machine	machine	NOUN
easat-1848	351	49	learning	learn	VERB
easat-1848	351	50	techniques	technique	NOUN
easat-1848	351	51	,	,	PUNCT
easat-1848	351	52	ieee	ieee	NOUN
easat-1848	351	53	access	access	NOUN
easat-1848	351	54	,	,	PUNCT
easat-1848	351	55	volume	volume	NOUN
easat-1848	351	56	7	7	NUM
easat-1848	351	57	,	,	PUNCT
easat-1848	351	58	2019	2019	NUM
easat-1848	351	59	,	,	PUNCT
easat-1848	351	60	digital	digital	ADJ
easat-1848	351	61	object	object	NOUN
easat-1848	351	62	identifier	identifier	NOUN
easat-1848	351	63	10.1109	10.1109	NUM
easat-1848	351	64	/	/	SYM
easat-1848	351	65	access.2019.2923707	access.2019.2923707	NOUN
easat-1848	351	66	[	[	X
easat-1848	351	67	15	15	NUM
easat-1848	351	68	]	]	PUNCT
easat-1848	351	69	chunyan	chunyan	NOUN
easat-1848	351	70	guo	guo	PROPN
easat-1848	351	71	,	,	PUNCT
easat-1848	351	72	jiabing	jiabe	VERB
easat-1848	351	73	zhang	zhang	PROPN
easat-1848	351	74	,	,	PUNCT
easat-1848	351	75	yang	yang	PROPN
easat-1848	351	76	liu	liu	PROPN
easat-1848	351	77	,	,	PUNCT
easat-1848	351	78	yaying	yaying	PROPN
easat-1848	351	79	xie	xie	PROPN
easat-1848	351	80	,	,	PUNCT
easat-1848	351	81	zhiqiang	zhiqiang	PROPN
easat-1848	351	82	han	han	PROPN
easat-1848	351	83	and	and	CCONJ
easat-1848	351	84	jianshe	jianshe	PROPN
easat-1848	351	85	yu	yu	PROPN
easat-1848	351	86	,	,	PUNCT
easat-1848	351	87	recursion	recursion	NOUN
easat-1848	351	88	enhanced	enhance	VERB
easat-1848	351	89	random	random	ADJ
easat-1848	351	90	forest	forest	NOUN
easat-1848	351	91	with	with	ADP
easat-1848	351	92	an	an	DET
easat-1848	351	93	improved	improve	VERB
easat-1848	351	94	linear	linear	NOUN
easat-1848	351	95	model	model	NOUN
easat-1848	351	96	(	(	PUNCT
easat-1848	351	97	rerf	rerf	NOUN
easat-1848	351	98	-	-	PUNCT
easat-1848	351	99	ilm	ilm	NOUN
easat-1848	351	100	)	)	PUNCT
easat-1848	351	101	for	for	ADP
easat-1848	351	102	heart	heart	NOUN
easat-1848	351	103	disease	disease	NOUN
easat-1848	351	104	detection	detection	NOUN
easat-1848	351	105	on	on	ADP
easat-1848	351	106	the	the	DET
easat-1848	351	107	internet	internet	NOUN
easat-1848	351	108	of	of	ADP
easat-1848	351	109	medical	medical	ADJ
easat-1848	351	110	things	thing	NOUN
easat-1848	351	111	platform	platform	NOUN
easat-1848	351	112	,	,	PUNCT
easat-1848	351	113	ieee	ieee	NOUN
easat-1848	351	114	access	access	NOUN
easat-1848	351	115	,	,	PUNCT
easat-1848	351	116	volume	volume	NOUN
easat-1848	351	117	8	8	NUM
easat-1848	351	118	,	,	PUNCT
easat-1848	351	119	2020	2020	NUM
easat-1848	351	120	,	,	PUNCT
easat-1848	351	121	digital	digital	ADJ
easat-1848	351	122	object	object	NOUN
easat-1848	351	123	identifier	identifier	NOUN
easat-1848	351	124	10.1109	10.1109	NUM
easat-1848	351	125	/	/	SYM
easat-1848	351	126	access.2020.2981159	access.2020.2981159	NOUN
easat-1848	351	127	[	[	X
easat-1848	351	128	16	16	NUM
easat-1848	351	129	]	]	X
easat-1848	351	130	mohammad	mohammad	PROPN
easat-1848	351	131	ayoub	ayoub	PROPN
easat-1848	351	132	khan	khan	PROPN
easat-1848	351	133	and	and	CCONJ
easat-1848	351	134	fahad	fahad	PROPN
easat-1848	351	135	algarnia	algarnia	PROPN
easat-1848	351	136	,	,	PUNCT
easat-1848	351	137	healthcare	healthcare	NOUN
easat-1848	351	138	monitoring	monitoring	NOUN
easat-1848	351	139	system	system	NOUN
easat-1848	351	140	for	for	ADP
easat-1848	351	141	the	the	DET
easat-1848	351	142	diagnosis	diagnosis	NOUN
easat-1848	351	143	of	of	ADP
easat-1848	351	144	heart	heart	NOUN
easat-1848	351	145	disease	disease	NOUN
easat-1848	351	146	in	in	ADP
easat-1848	351	147	the	the	DET
easat-1848	351	148	iomt	iomt	PROPN
easat-1848	351	149	cloud	cloud	NOUN
easat-1848	351	150	environment	environment	NOUN
easat-1848	351	151	using	use	VERB
easat-1848	351	152	msso	msso	NOUN
easat-1848	351	153	-	-	PUNCT
easat-1848	351	154	anfis	anfis	PROPN
easat-1848	351	155	,	,	PUNCT
easat-1848	351	156	ieee	ieee	NOUN
easat-1848	351	157	access	access	NOUN
easat-1848	351	158	,	,	PUNCT
easat-1848	351	159	volume	volume	NOUN
easat-1848	351	160	8	8	NUM
easat-1848	351	161	,	,	PUNCT
easat-1848	351	162	2020	2020	NUM
easat-1848	351	163	,	,	PUNCT
easat-1848	351	164	digital	digital	ADJ
easat-1848	351	165	object	object	NOUN
easat-1848	351	166	identifier	identifier	NOUN
easat-1848	351	167	10.1109	10.1109	NUM
easat-1848	351	168	/	/	SYM
easat-1848	351	169	access.2020.3006424	access.2020.3006424	NUM
easat-1848	351	170	[	[	X
easat-1848	351	171	17	17	NUM
easat-1848	351	172	]	]	X
easat-1848	351	173	syed	syed	PROPN
easat-1848	351	174	arslan	arslan	PROPN
easat-1848	351	175	ali	ali	PROPN
easat-1848	351	176	,	,	PUNCT
easat-1848	351	177	basit	basit	PROPN
easat-1848	351	178	raza	raza	PROPN
easat-1848	351	179	,	,	PUNCT
easat-1848	351	180	ahmad	ahmad	PROPN
easat-1848	351	181	kamran	kamran	PROPN
easat-1848	351	182	malik	malik	PROPN
easat-1848	351	183	,	,	PUNCT
easat-1848	351	184	ahmad	ahmad	PROPN
easat-1848	351	185	raza	raza	PROPN
easat-1848	351	186	shahid	shahid	PROPN
easat-1848	351	187	,	,	PUNCT
easat-1848	351	188	muhammad	muhammad	PROPN
easat-1848	351	189	faheem	faheem	PROPN
easat-1848	351	190	,	,	PUNCT
easat-1848	351	191	hani	hani	PROPN
easat-1848	351	192	alquhayz	alquhayz	PROPN
easat-1848	351	193	and	and	CCONJ
easat-1848	351	194	yogan	yogan	PROPN
easat-1848	351	195	jaya	jaya	PROPN
easat-1848	351	196	kumar	kumar	PROPN
easat-1848	351	197	,	,	PUNCT
easat-1848	351	198	an	an	DET
easat-1848	351	199	optimally	optimally	ADV
easat-1848	351	200	configured	configure	VERB
easat-1848	351	201	and	and	CCONJ
easat-1848	351	202	improved	improve	VERB
easat-1848	351	203	deep	deep	ADJ
easat-1848	351	204	belief	belief	NOUN
easat-1848	351	205	network	network	NOUN
easat-1848	351	206	(	(	PUNCT
easat-1848	351	207	oci	oci	PROPN
easat-1848	351	208	-	-	PUNCT
easat-1848	351	209	dbn	dbn	NOUN
easat-1848	351	210	)	)	PUNCT
easat-1848	351	211	approach	approach	NOUN
easat-1848	351	212	for	for	ADP
easat-1848	351	213	heart	heart	NOUN
easat-1848	351	214	disease	disease	NOUN
easat-1848	351	215	prediction	prediction	NOUN
easat-1848	351	216	based	base	VERB
easat-1848	351	217	on	on	ADP
easat-1848	351	218	ruzzo	ruzzo	PROPN
easat-1848	351	219	–	–	PUNCT
easat-1848	351	220	tompa	tompa	NOUN
easat-1848	351	221	and	and	CCONJ
easat-1848	351	222	stacked	stack	VERB
easat-1848	351	223	genetic	genetic	ADJ
easat-1848	351	224	algorithm	algorithm	NOUN
easat-1848	351	225	,	,	PUNCT
easat-1848	351	226	ieee	ieee	NOUN
easat-1848	351	227	access	access	NOUN
easat-1848	351	228	,	,	PUNCT
easat-1848	351	229	volume	volume	NOUN
easat-1848	351	230	8	8	NUM
easat-1848	351	231	,	,	PUNCT
easat-1848	351	232	2020	2020	NUM
easat-1848	351	233	,	,	PUNCT
easat-1848	351	234	digital	digital	ADJ
easat-1848	351	235	object	object	NOUN
easat-1848	351	236	identifier	identifier	NOUN
easat-1848	351	237	10.1109	10.1109	NUM
easat-1848	351	238	/	/	SYM
easat-1848	351	239	access.2020.2985646	access.2020.2985646	PRON
easat-1848	352	1	[	[	X
easat-1848	352	2	18	18	NUM
easat-1848	352	3	]	]	X
easat-1848	352	4	gihun	gihun	PROPN
easat-1848	352	5	joo	joo	PROPN
easat-1848	352	6	,	,	PUNCT
easat-1848	352	7	yeongjin	yeongjin	NOUN
easat-1848	352	8	song	song	NOUN
easat-1848	352	9	,	,	PUNCT
easat-1848	352	10	hyeonseung	hyeonseung	VERB
easat-1848	352	11	i	i	PRON
easat-1848	352	12	m	m	PROPN
easat-1848	352	13	,	,	PUNCT
easat-1848	352	14	and	and	CCONJ
easat-1848	352	15	junbeom	junbeom	PROPN
easat-1848	352	16	park	park	NOUN
easat-1848	352	17	,	,	PUNCT
easat-1848	352	18	clinical	clinical	ADJ
easat-1848	352	19	implication	implication	NOUN
easat-1848	352	20	of	of	ADP
easat-1848	352	21	machine	machine	NOUN
easat-1848	352	22	learning	learn	VERB
easat-1848	352	23	in	in	ADP
easat-1848	352	24	predicting	predict	VERB
easat-1848	352	25	the	the	DET
easat-1848	352	26	occurrence	occurrence	NOUN
easat-1848	352	27	of	of	ADP
easat-1848	352	28	cardiovascular	cardiovascular	ADJ
easat-1848	352	29	disease	disease	NOUN
easat-1848	352	30	using	use	VERB
easat-1848	352	31	big	big	ADJ
easat-1848	352	32	data	datum	NOUN
easat-1848	352	33	(	(	PUNCT
easat-1848	352	34	nationwide	nationwide	ADJ
easat-1848	352	35	cohort	cohort	NOUN
easat-1848	352	36	data	datum	NOUN
easat-1848	352	37	in	in	ADP
easat-1848	352	38	korea	korea	PROPN
easat-1848	352	39	)	)	PUNCT
easat-1848	352	40	,	,	PUNCT
easat-1848	352	41	ieee	ieee	NOUN
easat-1848	352	42	access	access	NOUN
easat-1848	352	43	,	,	PUNCT
easat-1848	352	44	volume	volume	NOUN
easat-1848	352	45	8	8	NUM
easat-1848	352	46	,	,	PUNCT
easat-1848	352	47	2020	2020	NUM
easat-1848	352	48	,	,	PUNCT
easat-1848	352	49	digital	digital	ADJ
easat-1848	352	50	object	object	NOUN
easat-1848	352	51	identifier	identifier	NOUN
easat-1848	352	52	10.1109	10.1109	NUM
easat-1848	352	53	/	/	SYM
easat-1848	352	54	access.2020.3015757	access.2020.3015757	NOUN
easat-1848	353	1	[	[	X
easat-1848	353	2	19	19	NUM
easat-1848	353	3	]	]	PUNCT
easat-1848	353	4	ashir	ashir	ADJ
easat-1848	353	5	javeed	javeed	NOUN
easat-1848	353	6	,	,	PUNCT
easat-1848	353	7	shijie	shijie	PROPN
easat-1848	353	8	zhou	zhou	PROPN
easat-1848	353	9	,	,	PUNCT
easat-1848	353	10	liao	liao	PROPN
easat-1848	353	11	yongjian	yongjian	PROPN
easat-1848	353	12	,	,	PUNCT
easat-1848	353	13	iqbal	iqbal	PROPN
easat-1848	353	14	qasim	qasim	PROPN
easat-1848	353	15	,	,	PUNCT
easat-1848	353	16	adeeb	adeeb	PROPN
easat-1848	353	17	noor	noor	PROPN
easat-1848	353	18	and	and	CCONJ
easat-1848	353	19	redhwan	redhwan	PROPN
easat-1848	353	20	nour	nour	PROPN
easat-1848	353	21	,	,	PUNCT
easat-1848	353	22	an	an	DET
easat-1848	353	23	intelligent	intelligent	ADJ
easat-1848	353	24	learning	learning	NOUN
easat-1848	353	25	system	system	NOUN
easat-1848	353	26	based	base	VERB
easat-1848	353	27	on	on	ADP
easat-1848	353	28	random	random	ADJ
easat-1848	353	29	search	search	NOUN
easat-1848	353	30	algorithm	algorithm	NOUN
easat-1848	353	31	and	and	CCONJ
easat-1848	353	32	optimized	optimize	VERB
easat-1848	353	33	random	random	ADJ
easat-1848	353	34	forest	forest	NOUN
easat-1848	353	35	model	model	NOUN
easat-1848	353	36	for	for	ADP
easat-1848	353	37	improved	improved	ADJ
easat-1848	353	38	heart	heart	NOUN
easat-1848	353	39	disease	disease	NOUN
easat-1848	353	40	detection	detection	NOUN
easat-1848	353	41	,	,	PUNCT
easat-1848	353	42	ieee	ieee	NOUN
easat-1848	353	43	access	access	NOUN
easat-1848	353	44	,	,	PUNCT
easat-1848	353	45	volume	volume	NOUN
easat-1848	353	46	7	7	NUM
easat-1848	353	47	,	,	PUNCT
easat-1848	353	48	2019	2019	NUM
easat-1848	353	49	,	,	PUNCT
easat-1848	353	50	digital	digital	ADJ
easat-1848	353	51	object	object	NOUN
easat-1848	353	52	identifier	identifier	NOUN
easat-1848	353	53	10.1109	10.1109	NUM
easat-1848	353	54	/	/	SYM
easat-1848	353	55	access.2019.2952107	access.2019.2952107	NOUN
easat-1848	354	1	[	[	X
easat-1848	354	2	20	20	NUM
easat-1848	354	3	]	]	X
easat-1848	354	4	liaqat	liaqat	PROPN
easat-1848	354	5	ali	ali	PROPN
easat-1848	354	6	,	,	PUNCT
easat-1848	354	7	awais	awais	PROPN
easat-1848	354	8	niamat	niamat	PROPN
easat-1848	354	9	,	,	PUNCT
easat-1848	354	10	javed	javed	PROPN
easat-1848	354	11	ali	ali	PROPN
easat-1848	354	12	khan	khan	PROPN
easat-1848	354	13	,	,	PUNCT
easat-1848	354	14	noorbakhsh	noorbakhsh	PROPN
easat-1848	354	15	amiri	amiri	PROPN
easat-1848	354	16	golilarz	golilarz	PROPN
easat-1848	354	17	,	,	PUNCT
easat-1848	354	18	xiong	xiong	PROPN
easat-1848	354	19	xingzhong	xingzhong	PROPN
easat-1848	354	20	,	,	PUNCT
easat-1848	354	21	adeeb	adeeb	PROPN
easat-1848	354	22	noor	noor	PROPN
easat-1848	354	23	,	,	PUNCT
easat-1848	354	24	redhwan	redhwan	PROPN
easat-1848	354	25	nour	nour	PROPN
easat-1848	354	26	and	and	CCONJ
easat-1848	354	27	syed	syed	PROPN
easat-1848	354	28	ahmad	ahmad	PROPN
easat-1848	354	29	chan	chan	PROPN
easat-1848	354	30	bukhari	bukhari	PROPN
easat-1848	354	31	,	,	PUNCT
easat-1848	354	32	an	an	DET
easat-1848	354	33	optimized	optimize	VERB
easat-1848	354	34	stacked	stack	VERB
easat-1848	354	35	support	support	NOUN
easat-1848	354	36	vector	vector	NOUN
easat-1848	354	37	machines	machine	NOUN
easat-1848	354	38	based	base	VERB
easat-1848	354	39	expert	expert	NOUN
easat-1848	354	40	system	system	NOUN
easat-1848	354	41	for	for	ADP
easat-1848	354	42	the	the	DET
easat-1848	354	43	effective	effective	ADJ
easat-1848	354	44	prediction	prediction	NOUN
easat-1848	354	45	of	of	ADP
easat-1848	354	46	heart	heart	NOUN
easat-1848	354	47	failure	failure	NOUN
easat-1848	354	48	,	,	PUNCT
easat-1848	354	49	ieee	ieee	NOUN
easat-1848	354	50	access	access	NOUN
easat-1848	354	51	,	,	PUNCT
easat-1848	354	52	volume	volume	NOUN
easat-1848	354	53	7	7	NUM
easat-1848	354	54	,	,	PUNCT
easat-1848	354	55	2019	2019	NUM
easat-1848	354	56	,	,	PUNCT
easat-1848	354	57	digital	digital	ADJ
easat-1848	354	58	object	object	NOUN
easat-1848	354	59	identifier	identifier	NOUN
easat-1848	354	60	10.1109	10.1109	NUM
easat-1848	354	61	/	/	SYM
easat-1848	354	62	access.2019.2909969	access.2019.2909969	PROPN
easat-1848	354	63	1470	1470	NUM
easat-1848	354	64	edelweiss	edelweiss	PROPN
easat-1848	354	65	applied	apply	VERB
easat-1848	354	66	science	science	NOUN
easat-1848	354	67	and	and	CCONJ
easat-1848	354	68	technology	technology	NOUN
easat-1848	354	69	issn	issn	PROPN
easat-1848	354	70	:	:	PUNCT
easat-1848	354	71	2576	2576	NUM
easat-1848	354	72	-	-	SYM
easat-1848	354	73	8484	8484	NUM
easat-1848	354	74	vol	vol	NOUN
easat-1848	354	75	.	.	PROPN
easat-1848	354	76	8	8	NUM
easat-1848	354	77	,	,	PUNCT
easat-1848	354	78	no	no	INTJ
easat-1848	354	79	.	.	NOUN
easat-1848	354	80	5	5	NUM
easat-1848	354	81	:	:	SYM
easat-1848	354	82	1445	1445	NUM
easat-1848	354	83	-	-	SYM
easat-1848	354	84	1471	1471	NUM
easat-1848	354	85	,	,	PUNCT
easat-1848	354	86	2024	2024	NUM
easat-1848	354	87	doi	doi	NOUN
easat-1848	354	88	:	:	PUNCT
easat-1848	354	89	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	354	90	©	©	PROPN
easat-1848	354	91	2024	2024	NUM
easat-1848	354	92	by	by	ADP
easat-1848	354	93	the	the	DET
easat-1848	354	94	authors	author	NOUN
easat-1848	354	95	;	;	PUNCT
easat-1848	354	96	licensee	licensee	PROPN
easat-1848	354	97	learning	learning	NOUN
easat-1848	354	98	gate	gate	NOUN
easat-1848	355	1	[	[	X
easat-1848	355	2	21	21	NUM
easat-1848	355	3	]	]	X
easat-1848	355	4	liaqat	liaqat	PROPN
easat-1848	355	5	ali	ali	PROPN
easat-1848	355	6	,	,	PUNCT
easat-1848	355	7	atiqur	atiqur	PROPN
easat-1848	355	8	rahman	rahman	PROPN
easat-1848	355	9	,	,	PUNCT
easat-1848	355	10	aurangzeb	aurangzeb	PROPN
easat-1848	355	11	khan	khan	PROPN
easat-1848	355	12	,	,	PUNCT
easat-1848	355	13	mingyi	mingyi	PROPN
easat-1848	355	14	zhou	zhou	PROPN
easat-1848	355	15	,	,	PUNCT
easat-1848	355	16	ashir	ashir	ADJ
easat-1848	355	17	javeed	javeed	NOUN
easat-1848	355	18	and	and	CCONJ
easat-1848	355	19	javed	javed	PROPN
easat-1848	355	20	ali	ali	PROPN
easat-1848	355	21	khan	khan	PROPN
easat-1848	355	22	,	,	PUNCT
easat-1848	355	23	an	an	DET
easat-1848	355	24	automated	automate	VERB
easat-1848	355	25	diagnostic	diagnostic	ADJ
easat-1848	355	26	system	system	NOUN
easat-1848	355	27	for	for	ADP
easat-1848	355	28	heart	heart	NOUN
easat-1848	355	29	disease	disease	NOUN
easat-1848	355	30	prediction	prediction	NOUN
easat-1848	355	31	based	base	VERB
easat-1848	355	32	on	on	ADP
easat-1848	355	33	χ	χ	DET
easat-1848	355	34	2	2	NUM
easat-1848	355	35	statistical	statistical	ADJ
easat-1848	355	36	model	model	NOUN
easat-1848	355	37	and	and	CCONJ
easat-1848	355	38	optimally	optimally	ADV
easat-1848	355	39	configured	configure	VERB
easat-1848	355	40	deep	deep	ADJ
easat-1848	355	41	neural	neural	ADJ
easat-1848	355	42	network	network	NOUN
easat-1848	355	43	,	,	PUNCT
easat-1848	355	44	ieee	ieee	NOUN
easat-1848	355	45	access	access	NOUN
easat-1848	355	46	,	,	PUNCT
easat-1848	355	47	volume	volume	NOUN
easat-1848	355	48	7	7	NUM
easat-1848	355	49	,	,	PUNCT
easat-1848	355	50	2019	2019	NUM
easat-1848	355	51	,	,	PUNCT
easat-1848	355	52	digital	digital	ADJ
easat-1848	355	53	object	object	NOUN
easat-1848	355	54	identifier	identifier	NOUN
easat-1848	355	55	10.1109	10.1109	NUM
easat-1848	355	56	/	/	SYM
easat-1848	355	57	access.2019.2904800	access.2019.2904800	PRON
easat-1848	355	58	[	[	X
easat-1848	355	59	22	22	NUM
easat-1848	355	60	]	]	X
easat-1848	355	61	jikuo	jikuo	PROPN
easat-1848	355	62	wang	wang	PROPN
easat-1848	355	63	,	,	PUNCT
easat-1848	355	64	changchun	changchun	PROPN
easat-1848	355	65	liu	liu	PROPN
easat-1848	355	66	,	,	PUNCT
easat-1848	355	67	liping	liping	PROPN
easat-1848	355	68	li	li	PROPN
easat-1848	355	69	,	,	PUNCT
easat-1848	355	70	wang	wang	PROPN
easat-1848	355	71	li	li	PROPN
easat-1848	355	72	,	,	PUNCT
easat-1848	355	73	lianke	lianke	PROPN
easat-1848	355	74	yao	yao	PROPN
easat-1848	355	75	,	,	PUNCT
easat-1848	355	76	han	han	PROPN
easat-1848	355	77	li	li	PROPN
easat-1848	355	78	and	and	CCONJ
easat-1848	355	79	huan	huan	PROPN
easat-1848	355	80	zhang	zhang	PROPN
easat-1848	355	81	,	,	PUNCT
easat-1848	355	82	a	a	DET
easat-1848	355	83	stacking	stacking	NOUN
easat-1848	355	84	-	-	PUNCT
easat-1848	355	85	based	base	VERB
easat-1848	355	86	model	model	NOUN
easat-1848	355	87	for	for	ADP
easat-1848	355	88	non	non	ADJ
easat-1848	355	89	-	-	ADJ
easat-1848	355	90	invasive	invasive	ADJ
easat-1848	355	91	detection	detection	NOUN
easat-1848	355	92	of	of	ADP
easat-1848	355	93	coronary	coronary	ADJ
easat-1848	355	94	heart	heart	NOUN
easat-1848	355	95	disease	disease	NOUN
easat-1848	355	96	,	,	PUNCT
easat-1848	355	97	ieee	ieee	NOUN
easat-1848	355	98	access	access	NOUN
easat-1848	355	99	,	,	PUNCT
easat-1848	355	100	volume	volume	NOUN
easat-1848	355	101	8	8	NUM
easat-1848	355	102	,	,	PUNCT
easat-1848	355	103	2020	2020	NUM
easat-1848	355	104	,	,	PUNCT
easat-1848	355	105	digital	digital	ADJ
easat-1848	355	106	object	object	NOUN
easat-1848	355	107	identifier	identifier	NOUN
easat-1848	355	108	10.1109	10.1109	NUM
easat-1848	355	109	/	/	SYM
easat-1848	355	110	access.2020.2975377	access.2020.2975377	NOUN
easat-1848	356	1	[	[	X
easat-1848	356	2	23	23	NUM
easat-1848	356	3	]	]	X
easat-1848	356	4	abid	abid	PROPN
easat-1848	356	5	ishaq	ishaq	PROPN
easat-1848	356	6	,	,	PUNCT
easat-1848	356	7	saima	saima	PROPN
easat-1848	356	8	sadiq	sadiq	PROPN
easat-1848	356	9	,	,	PUNCT
easat-1848	356	10	muhammad	muhammad	PROPN
easat-1848	356	11	umer	umer	PROPN
easat-1848	356	12	,	,	PUNCT
easat-1848	356	13	saleem	saleem	PROPN
easat-1848	356	14	ullah	ullah	PROPN
easat-1848	356	15	,	,	PUNCT
easat-1848	356	16	seyedali	seyedali	PROPN
easat-1848	356	17	mirjalili	mirjalili	NOUN
easat-1848	356	18	,	,	PUNCT
easat-1848	356	19	vaibhav	vaibhav	VERB
easat-1848	356	20	rupapara	rupapara	NOUN
easat-1848	356	21	and	and	CCONJ
easat-1848	356	22	michele	michele	PROPN
easat-1848	356	23	nappi	nappi	PROPN
easat-1848	356	24	,	,	PUNCT
easat-1848	356	25	improving	improve	VERB
easat-1848	356	26	the	the	DET
easat-1848	356	27	prediction	prediction	NOUN
easat-1848	356	28	of	of	ADP
easat-1848	356	29	heart	heart	NOUN
easat-1848	356	30	failure	failure	NOUN
easat-1848	356	31	patients	patient	NOUN
easat-1848	356	32	’	'	PUNCT
easat-1848	356	33	survival	survival	NOUN
easat-1848	356	34	using	use	VERB
easat-1848	356	35	smote	smote	ADJ
easat-1848	356	36	and	and	CCONJ
easat-1848	356	37	effective	effective	ADJ
easat-1848	356	38	data	datum	NOUN
easat-1848	356	39	mining	mining	NOUN
easat-1848	356	40	techniques	technique	NOUN
easat-1848	356	41	,	,	PUNCT
easat-1848	356	42	ieee	ieee	NOUN
easat-1848	356	43	access	access	NOUN
easat-1848	356	44	,	,	PUNCT
easat-1848	356	45	volume	volume	NOUN
easat-1848	356	46	9	9	NUM
easat-1848	356	47	,	,	PUNCT
easat-1848	356	48	2021	2021	NUM
easat-1848	356	49	,	,	PUNCT
easat-1848	356	50	digital	digital	ADJ
easat-1848	356	51	object	object	NOUN
easat-1848	356	52	identifier	identifier	NOUN
easat-1848	356	53	10.1109	10.1109	NUM
easat-1848	356	54	/	/	SYM
easat-1848	356	55	access.2021.3064084	access.2021.3064084	PROPN
easat-1848	357	1	[	[	X
easat-1848	357	2	24	24	NUM
easat-1848	357	3	]	]	PUNCT
easat-1848	357	4	dakun	dakun	PROPN
easat-1848	357	5	lai	lai	PROPN
easat-1848	357	6	,	,	PUNCT
easat-1848	357	7	yifei	yifei	PROPN
easat-1848	357	8	zhang	zhang	PROPN
easat-1848	357	9	,	,	PUNCT
easat-1848	357	10	xinshu	xinshu	PROPN
easat-1848	357	11	zhang	zhang	PROPN
easat-1848	357	12	,	,	PUNCT
easat-1848	357	13	ye	ye	PROPN
easat-1848	357	14	su	su	PROPN
easat-1848	357	15	and	and	CCONJ
easat-1848	357	16	md	md	PROPN
easat-1848	357	17	belal	belal	PROPN
easat-1848	357	18	bin	bin	PROPN
easat-1848	357	19	heyat	heyat	PROPN
easat-1848	357	20	,	,	PUNCT
easat-1848	357	21	an	an	DET
easat-1848	357	22	automated	automate	VERB
easat-1848	357	23	strategy	strategy	NOUN
easat-1848	357	24	for	for	ADP
easat-1848	357	25	early	early	ADJ
easat-1848	357	26	risk	risk	NOUN
easat-1848	357	27	identification	identification	NOUN
easat-1848	357	28	of	of	ADP
easat-1848	357	29	sudden	sudden	ADJ
easat-1848	357	30	cardiac	cardiac	ADJ
easat-1848	357	31	death	death	NOUN
easat-1848	357	32	by	by	ADP
easat-1848	357	33	using	use	VERB
easat-1848	357	34	machine	machine	NOUN
easat-1848	357	35	learning	learn	VERB
easat-1848	357	36	approach	approach	NOUN
easat-1848	357	37	on	on	ADP
easat-1848	357	38	measurable	measurable	ADJ
easat-1848	357	39	arrhythmic	arrhythmic	ADJ
easat-1848	357	40	risk	risk	NOUN
easat-1848	357	41	markers	marker	NOUN
easat-1848	357	42	,	,	PUNCT
easat-1848	357	43	ieee	ieee	NOUN
easat-1848	357	44	access	access	NOUN
easat-1848	357	45	,	,	PUNCT
easat-1848	357	46	volume	volume	NOUN
easat-1848	357	47	7	7	NUM
easat-1848	357	48	,	,	PUNCT
easat-1848	357	49	2019	2019	NUM
easat-1848	357	50	,	,	PUNCT
easat-1848	357	51	digital	digital	ADJ
easat-1848	357	52	object	object	NOUN
easat-1848	357	53	identifier	identifier	NOUN
easat-1848	357	54	10.1109	10.1109	NUM
easat-1848	357	55	/	/	SYM
easat-1848	357	56	access.2019.2925847	access.2019.2925847	X
easat-1848	357	57	[	[	X
easat-1848	357	58	25	25	NUM
easat-1848	357	59	]	]	PUNCT
easat-1848	357	60	saba	saba	PROPN
easat-1848	357	61	bashir	bashir	PROPN
easat-1848	357	62	,	,	PUNCT
easat-1848	357	63	abdulwahab	abdulwahab	PROPN
easat-1848	357	64	ali	ali	PROPN
easat-1848	357	65	almazroi	almazroi	PROPN
easat-1848	357	66	,	,	PUNCT
easat-1848	357	67	sufyan	sufyan	PROPN
easat-1848	357	68	ashfaq	ashfaq	NOUN
easat-1848	357	69	,	,	PUNCT
easat-1848	357	70	abdulaleem	abdulaleem	VERB
easat-1848	357	71	ali	ali	PROPN
easat-1848	357	72	almazroi	almazroi	PROPN
easat-1848	357	73	and	and	CCONJ
easat-1848	357	74	farhan	farhan	PROPN
easat-1848	357	75	hassan	hassan	PROPN
easat-1848	357	76	khan	khan	PROPN
easat-1848	357	77	,	,	PUNCT
easat-1848	357	78	a	a	DET
easat-1848	357	79	knowledge	knowledge	NOUN
easat-1848	357	80	-	-	PUNCT
easat-1848	357	81	based	base	VERB
easat-1848	357	82	clinical	clinical	ADJ
easat-1848	357	83	decision	decision	NOUN
easat-1848	357	84	support	support	NOUN
easat-1848	357	85	system	system	NOUN
easat-1848	357	86	utilizing	utilize	VERB
easat-1848	357	87	an	an	DET
easat-1848	357	88	intelligent	intelligent	ADJ
easat-1848	357	89	ensemble	ensemble	ADJ
easat-1848	357	90	voting	voting	NOUN
easat-1848	357	91	scheme	scheme	NOUN
easat-1848	357	92	for	for	ADP
easat-1848	357	93	improved	improve	VERB
easat-1848	357	94	cardiovascular	cardiovascular	ADJ
easat-1848	357	95	disease	disease	NOUN
easat-1848	357	96	prediction	prediction	NOUN
easat-1848	357	97	,	,	PUNCT
easat-1848	357	98	ieee	ieee	NOUN
easat-1848	357	99	access	access	NOUN
easat-1848	357	100	,	,	PUNCT
easat-1848	357	101	volume	volume	NOUN
easat-1848	357	102	9	9	NUM
easat-1848	357	103	,	,	PUNCT
easat-1848	357	104	2021	2021	NUM
easat-1848	357	105	,	,	PUNCT
easat-1848	357	106	digital	digital	ADJ
easat-1848	357	107	object	object	NOUN
easat-1848	357	108	identifier	identifier	NOUN
easat-1848	357	109	10.1109	10.1109	NUM
easat-1848	357	110	/	/	SYM
easat-1848	357	111	access.2021.3110604	access.2021.3110604	PROPN
easat-1848	358	1	[	[	X
easat-1848	358	2	26	26	NUM
easat-1848	358	3	]	]	X
easat-1848	358	4	aqsa	aqsa	PROPN
easat-1848	358	5	rahim	rahim	PROPN
easat-1848	358	6	,	,	PUNCT
easat-1848	358	7	yawar	yawar	PROPN
easat-1848	358	8	rasheed	rasheed	NOUN
easat-1848	358	9	,	,	PUNCT
easat-1848	358	10	farooque	farooque	ADJ
easat-1848	358	11	azam	azam	PROPN
easat-1848	358	12	,	,	PUNCT
easat-1848	358	13	muhammad	muhammad	PROPN
easat-1848	358	14	waseem	waseem	PROPN
easat-1848	358	15	anwar	anwar	PROPN
easat-1848	358	16	,	,	PUNCT
easat-1848	358	17	muhammad	muhammad	PROPN
easat-1848	358	18	abdul	abdul	PROPN
easat-1848	358	19	rahim	rahim	PROPN
easat-1848	358	20	and	and	CCONJ
easat-1848	358	21	abdul	abdul	PROPN
easat-1848	358	22	wahab	wahab	PROPN
easat-1848	358	23	muzaffar	muzaffar	PROPN
easat-1848	358	24	,	,	PUNCT
easat-1848	358	25	“	"	PUNCT
easat-1848	358	26	an	an	DET
easat-1848	358	27	integrated	integrated	ADJ
easat-1848	358	28	machine	machine	NOUN
easat-1848	358	29	learning	learn	VERB
easat-1848	358	30	framework	framework	NOUN
easat-1848	358	31	for	for	ADP
easat-1848	358	32	effective	effective	ADJ
easat-1848	358	33	prediction	prediction	NOUN
easat-1848	358	34	of	of	ADP
easat-1848	358	35	cardiovascular	cardiovascular	ADJ
easat-1848	358	36	diseases	disease	NOUN
easat-1848	358	37	”	"	PUNCT
easat-1848	358	38	,	,	PUNCT
easat-1848	358	39	ieee	ieee	NOUN
easat-1848	358	40	access	access	NOUN
easat-1848	358	41	,	,	PUNCT
easat-1848	358	42	volume	volume	NOUN
easat-1848	358	43	9	9	NUM
easat-1848	358	44	,	,	PUNCT
easat-1848	358	45	2021	2021	NUM
easat-1848	358	46	,	,	PUNCT
easat-1848	358	47	digital	digital	ADJ
easat-1848	358	48	object	object	NOUN
easat-1848	358	49	identifier	identifier	NOUN
easat-1848	358	50	10.1109	10.1109	NUM
easat-1848	358	51	/	/	SYM
easat-1848	358	52	access.2021.3098688	access.2021.3098688	NOUN
easat-1848	358	53	[	[	X
easat-1848	358	54	27	27	NUM
easat-1848	358	55	]	]	SYM
easat-1848	358	56	shishir	shishir	PROPN
easat-1848	358	57	rao	rao	PROPN
easat-1848	358	58	,	,	PUNCT
easat-1848	358	59	yikuan	yikuan	PROPN
easat-1848	358	60	li	li	PROPN
easat-1848	358	61	,	,	PUNCT
easat-1848	358	62	rema	rema	PROPN
easat-1848	358	63	ramakrishnan	ramakrishnan	PROPN
easat-1848	358	64	,	,	PUNCT
easat-1848	358	65	abdelaali	abdelaali	PROPN
easat-1848	358	66	hassaine	hassaine	PROPN
easat-1848	358	67	,	,	PUNCT
easat-1848	358	68	dexter	dexter	PROPN
easat-1848	358	69	canoy	canoy	PROPN
easat-1848	358	70	,	,	PUNCT
easat-1848	358	71	john	john	PROPN
easat-1848	358	72	cleland	cleland	PROPN
easat-1848	358	73	,	,	PUNCT
easat-1848	358	74	thomas	thomas	PROPN
easat-1848	358	75	lukasiewicz	lukasiewicz	PROPN
easat-1848	358	76	,	,	PUNCT
easat-1848	358	77	gholamreza	gholamreza	PROPN
easat-1848	358	78	salimi	salimi	NOUN
easat-1848	358	79	-	-	PUNCT
easat-1848	358	80	khorshidi	khorshidi	NOUN
easat-1848	358	81	,	,	PUNCT
easat-1848	358	82	and	and	CCONJ
easat-1848	358	83	kazem	kazem	PROPN
easat-1848	358	84	rahimi	rahimi	NOUN
easat-1848	358	85	,	,	PUNCT
easat-1848	358	86	“	"	PUNCT
easat-1848	358	87	an	an	DET
easat-1848	358	88	explainable	explainable	ADJ
easat-1848	358	89	transformer	transformer	NOUN
easat-1848	358	90	-	-	PUNCT
easat-1848	358	91	based	base	VERB
easat-1848	358	92	deep	deep	ADJ
easat-1848	358	93	learning	learning	NOUN
easat-1848	358	94	model	model	NOUN
easat-1848	358	95	for	for	ADP
easat-1848	358	96	the	the	DET
easat-1848	358	97	prediction	prediction	NOUN
easat-1848	358	98	of	of	ADP
easat-1848	358	99	incident	incident	NOUN
easat-1848	358	100	heart	heart	NOUN
easat-1848	358	101	failure	failure	NOUN
easat-1848	358	102	”	"	PUNCT
easat-1848	358	103	,	,	PUNCT
easat-1848	358	104	ieee	ieee	NOUN
easat-1848	358	105	journal	journal	NOUN
easat-1848	358	106	of	of	ADP
easat-1848	358	107	biomedical	biomedical	ADJ
easat-1848	358	108	and	and	CCONJ
easat-1848	358	109	health	health	NOUN
easat-1848	358	110	informatics	informatic	NOUN
easat-1848	358	111	,	,	PUNCT
easat-1848	358	112	vol	vol	NOUN
easat-1848	358	113	.	.	PROPN
easat-1848	358	114	26	26	NUM
easat-1848	358	115	,	,	PUNCT
easat-1848	358	116	no	no	INTJ
easat-1848	358	117	.	.	NOUN
easat-1848	358	118	7	7	NUM
easat-1848	358	119	,	,	PUNCT
easat-1848	358	120	july	july	NOUN
easat-1848	358	121	2022	2022	NUM
easat-1848	359	1	[	[	X
easat-1848	359	2	28	28	NUM
easat-1848	359	3	]	]	X
easat-1848	359	4	chayakrit	chayakrit	PROPN
easat-1848	359	5	krittanawong	krittanawong	PROPN
easat-1848	359	6	,	,	PUNCT
easat-1848	359	7	hafeez	hafeez	PROPN
easat-1848	359	8	ul	ul	PROPN
easat-1848	359	9	hassan	hassan	PROPN
easat-1848	359	10	virk	virk	PROPN
easat-1848	359	11	,	,	PUNCT
easat-1848	359	12	sripal	sripal	PROPN
easat-1848	359	13	bangalore	bangalore	PROPN
easat-1848	359	14	,	,	PUNCT
easat-1848	359	15	zhen	zhen	PROPN
easat-1848	359	16	wang	wang	PROPN
easat-1848	359	17	,	,	PUNCT
easat-1848	359	18	kipp	kipp	PROPN
easat-1848	359	19	w.	w.	PROPN
easat-1848	359	20	johnson	johnson	PROPN
easat-1848	359	21	,	,	PUNCT
easat-1848	359	22	rachel	rachel	PROPN
easat-1848	359	23	pinotti	pinotti	PROPN
easat-1848	359	24	,	,	PUNCT
easat-1848	359	25	hongju	hongju	PROPN
easat-1848	359	26	zhang	zhang	PROPN
easat-1848	359	27	,	,	PUNCT
easat-1848	359	28	scott	scott	PROPN
easat-1848	359	29	kaplin	kaplin	PROPN
easat-1848	359	30	,	,	PUNCT
easat-1848	359	31	bharat	bharat	PROPN
easat-1848	359	32	narasimhan	narasimhan	PROPN
easat-1848	359	33	,	,	PUNCT
easat-1848	359	34	takeshi	takeshi	NOUN
easat-1848	359	35	kitai	kitai	PROPN
easat-1848	359	36	,	,	PUNCT
easat-1848	359	37	usman	usman	PROPN
easat-1848	359	38	baber	baber	PROPN
easat-1848	359	39	,	,	PUNCT
easat-1848	359	40	jonathan	jonathan	PROPN
easat-1848	359	41	l.	l.	PROPN
easat-1848	359	42	halperin	halperin	PROPN
easat-1848	359	43	&	&	CCONJ
easat-1848	359	44	w.	w.	PROPN
easat-1848	359	45	h.	h.	PROPN
easat-1848	359	46	wilson	wilson	PROPN
easat-1848	359	47	tang	tang	PROPN
easat-1848	359	48	,	,	PUNCT
easat-1848	359	49	”	"	PUNCT
easat-1848	359	50	machine	machine	NOUN
easat-1848	359	51	learning	learning	NOUN
easat-1848	359	52	prediction	prediction	NOUN
easat-1848	359	53	in	in	ADP
easat-1848	359	54	cardiovascular	cardiovascular	ADJ
easat-1848	359	55	diseases	disease	NOUN
easat-1848	359	56	:	:	PUNCT
easat-1848	359	57	a	a	DET
easat-1848	359	58	meta	meta	ADJ
easat-1848	359	59	-	-	PUNCT
easat-1848	359	60	analysis	analysis	NOUN
easat-1848	359	61	”	"	PUNCT
easat-1848	359	62	,	,	PUNCT
easat-1848	359	63	sci	sci	PROPN
easat-1848	359	64	rep	rep	PROPN
easat-1848	359	65	10	10	NUM
easat-1848	359	66	,	,	PUNCT
easat-1848	359	67	16057	16057	NUM
easat-1848	359	68	(	(	PUNCT
easat-1848	359	69	2020	2020	NUM
easat-1848	359	70	)	)	PUNCT
easat-1848	359	71	.	.	PUNCT
easat-1848	360	1	https://doi.org/10.1038/s41598-020-72685-1	https://doi.org/10.1038/s41598-020-72685-1	PRON
easat-1848	361	1	[	[	X
easat-1848	361	2	29	29	NUM
easat-1848	361	3	]	]	X
easat-1848	361	4	malavika	malavika	PROPN
easat-1848	361	5	g	g	PROPN
easat-1848	361	6	,	,	PUNCT
easat-1848	361	7	rajathi	rajathi	NOUN
easat-1848	361	8	n	n	CCONJ
easat-1848	361	9	,	,	PUNCT
easat-1848	361	10	vanitha	vanitha	ADV
easat-1848	361	11	v	v	NOUN
easat-1848	361	12	and	and	CCONJ
easat-1848	361	13	parameswari	parameswari	PROPN
easat-1848	361	14	p	p	X
easat-1848	361	15	,	,	PUNCT
easat-1848	361	16	“	"	PUNCT
easat-1848	361	17	heart	heart	NOUN
easat-1848	361	18	disease	disease	NOUN
easat-1848	361	19	prediction	prediction	NOUN
easat-1848	361	20	using	use	VERB
easat-1848	361	21	machine	machine	NOUN
easat-1848	361	22	learning	learn	VERB
easat-1848	361	23	algorithms	algorithm	NOUN
easat-1848	361	24	”	"	PUNCT
easat-1848	361	25	,	,	PUNCT
easat-1848	361	26	bioscience	bioscience	NOUN
easat-1848	361	27	biotechnology	biotechnology	NOUN
easat-1848	361	28	research	research	NOUN
easat-1848	361	29	communication	communication	NOUN
easat-1848	361	30	,	,	PUNCT
easat-1848	361	31	special	special	ADJ
easat-1848	361	32	issue	issue	NOUN
easat-1848	361	33	vol	vol	NOUN
easat-1848	361	34	13	13	NUM
easat-1848	361	35	no	no	DET
easat-1848	361	36	11	11	NUM
easat-1848	361	37	(	(	PUNCT
easat-1848	361	38	2020	2020	NUM
easat-1848	361	39	)	)	PUNCT
easat-1848	361	40	pp-24	pp-24	NOUN
easat-1848	361	41	-	-	SYM
easat-1848	361	42	27	27	NUM
easat-1848	361	43	.	.	PUNCT
easat-1848	362	1	[	[	X
easat-1848	362	2	30	30	NUM
easat-1848	362	3	]	]	X
easat-1848	362	4	md	md	PROPN
easat-1848	362	5	mamun	mamun	PROPN
easat-1848	362	6	ali	ali	PROPN
easat-1848	362	7	,	,	PUNCT
easat-1848	362	8	bikash	bikash	PROPN
easat-1848	362	9	kumar	kumar	PROPN
easat-1848	362	10	paul	paul	PROPN
easat-1848	362	11	,	,	PUNCT
easat-1848	362	12	kawsar	kawsar	PROPN
easat-1848	362	13	ahmed	ahmed	PROPN
easat-1848	362	14	,	,	PUNCT
easat-1848	362	15	francis	francis	PROPN
easat-1848	362	16	m.	m.	PROPN
easat-1848	362	17	bui	bui	PROPN
easat-1848	362	18	,	,	PUNCT
easat-1848	362	19	julian	julian	PROPN
easat-1848	362	20	m.	m.	PROPN
easat-1848	362	21	w.	w.	PROPN
easat-1848	362	22	quinn	quinn	PROPN
easat-1848	362	23	,	,	PUNCT
easat-1848	362	24	mohammad	mohammad	PROPN
easat-1848	362	25	ali	ali	PROPN
easat-1848	362	26	moni	moni	PROPN
easat-1848	362	27	,	,	PUNCT
easat-1848	362	28	“	"	PUNCT
easat-1848	362	29	heart	heart	NOUN
easat-1848	362	30	disease	disease	NOUN
easat-1848	362	31	prediction	prediction	NOUN
easat-1848	362	32	using	use	VERB
easat-1848	362	33	supervised	supervised	ADJ
easat-1848	362	34	machine	machine	NOUN
easat-1848	362	35	learning	learning	NOUN
easat-1848	362	36	algorithms	algorithm	NOUN
easat-1848	362	37	:	:	PUNCT
easat-1848	362	38	performance	performance	NOUN
easat-1848	362	39	analysis	analysis	NOUN
easat-1848	362	40	and	and	CCONJ
easat-1848	362	41	comparison	comparison	NOUN
easat-1848	362	42	”	"	PUNCT
easat-1848	362	43	,	,	PUNCT
easat-1848	362	44	computers	computer	NOUN
easat-1848	362	45	in	in	ADP
easat-1848	362	46	biology	biology	NOUN
easat-1848	362	47	and	and	CCONJ
easat-1848	362	48	medicine	medicine	NOUN
easat-1848	362	49	,	,	PUNCT
easat-1848	362	50	volume	volume	NOUN
easat-1848	362	51	136	136	NUM
easat-1848	362	52	,	,	PUNCT
easat-1848	362	53	september	september	PROPN
easat-1848	362	54	2021	2021	NUM
easat-1848	362	55	,	,	PUNCT
easat-1848	362	56	104672	104672	NUM
easat-1848	362	57	.	.	PUNCT
easat-1848	363	1	[	[	X
easat-1848	363	2	31	31	NUM
easat-1848	363	3	]	]	PUNCT
easat-1848	363	4	p.	p.	NOUN
easat-1848	363	5	shashwith	shashwith	NOUN
easat-1848	363	6	,	,	PUNCT
easat-1848	363	7	b.	b.	PROPN
easat-1848	363	8	sai	sai	PROPN
easat-1848	363	9	prasad	prasad	PROPN
easat-1848	363	10	,	,	PUNCT
easat-1848	363	11	ch	ch	PROPN
easat-1848	363	12	.	.	PROPN
easat-1848	363	13	shashi	shashi	PROPN
easat-1848	363	14	kumar	kumar	PROPN
easat-1848	363	15	reddy	reddy	PROPN
easat-1848	363	16	,	,	PUNCT
easat-1848	363	17	n.	n.	PROPN
easat-1848	363	18	abhinav	abhinav	PROPN
easat-1848	363	19	krishna	krishna	PROPN
easat-1848	363	20	,	,	PUNCT
easat-1848	363	21	k.	k.	PROPN
easat-1848	363	22	ramesh	ramesh	PROPN
easat-1848	363	23	,	,	PUNCT
easat-1848	363	24	“	"	PUNCT
easat-1848	363	25	heart	heart	NOUN
easat-1848	363	26	disease	disease	NOUN
easat-1848	363	27	prediction	prediction	NOUN
easat-1848	363	28	by	by	ADP
easat-1848	363	29	using	use	VERB
easat-1848	363	30	machine	machine	NOUN
easat-1848	363	31	learning	learn	VERB
easat-1848	363	32	algorithms	algorithm	NOUN
easat-1848	363	33	”	"	PUNCT
easat-1848	363	34	,	,	PUNCT
easat-1848	363	35	international	international	ADJ
easat-1848	363	36	research	research	NOUN
easat-1848	363	37	journal	journal	NOUN
easat-1848	363	38	of	of	ADP
easat-1848	363	39	modernization	modernization	NOUN
easat-1848	363	40	in	in	ADP
easat-1848	363	41	engineering	engineering	NOUN
easat-1848	363	42	technology	technology	NOUN
easat-1848	363	43	and	and	CCONJ
easat-1848	363	44	science	science	NOUN
easat-1848	363	45	,	,	PUNCT
easat-1848	363	46	volume:04	volume:04	AUX
easat-1848	363	47	/	/	SYM
easat-1848	363	48	issue:06	issue:06	ADJ
easat-1848	363	49	/	/	SYM
easat-1848	363	50	june-2022	june-2022	NOUN
easat-1848	363	51	.	.	PUNCT
easat-1848	364	1	[	[	X
easat-1848	364	2	32	32	NUM
easat-1848	364	3	]	]	X
easat-1848	364	4	sudipta	sudipta	NOUN
easat-1848	364	5	priyadarshinee	priyadarshinee	PROPN
easat-1848	364	6	and	and	CCONJ
easat-1848	364	7	madhumita	madhumita	PROPN
easat-1848	364	8	panda	panda	NOUN
easat-1848	364	9	,	,	PUNCT
easat-1848	364	10	“	"	PUNCT
easat-1848	364	11	cardiac	cardiac	ADJ
easat-1848	364	12	disease	disease	NOUN
easat-1848	364	13	prediction	prediction	NOUN
easat-1848	364	14	using	use	VERB
easat-1848	364	15	smote	smote	NOUN
easat-1848	364	16	and	and	CCONJ
easat-1848	364	17	machine	machine	NOUN
easat-1848	364	18	learning	learn	VERB
easat-1848	364	19	classifiers	classifier	NOUN
easat-1848	364	20	”	"	PUNCT
easat-1848	364	21	,	,	PUNCT
easat-1848	364	22	journal	journal	NOUN
easat-1848	364	23	of	of	ADP
easat-1848	364	24	pharmaceutical	pharmaceutical	ADJ
easat-1848	364	25	negative	negative	ADJ
easat-1848	364	26	results	result	NOUN
easat-1848	364	27	¦	¦	PROPN
easat-1848	364	28	volume	volume	NOUN
easat-1848	364	29	13	13	NUM
easat-1848	364	30	¦	¦	PROPN
easat-1848	364	31	special	special	ADJ
easat-1848	364	32	issue	issue	NOUN
easat-1848	364	33	8	8	NUM
easat-1848	364	34	¦	¦	NOUN
easat-1848	364	35	2022	2022	NUM
easat-1848	364	36	.	.	PUNCT
easat-1848	365	1	[	[	X
easat-1848	365	2	33	33	NUM
easat-1848	365	3	]	]	X
easat-1848	365	4	irfan	irfan	PROPN
easat-1848	365	5	javid	javid	PROPN
easat-1848	365	6	,	,	PUNCT
easat-1848	365	7	ahmed	ahmed	PROPN
easat-1848	365	8	khalaf	khalaf	PROPN
easat-1848	365	9	zager	zager	PROPN
easat-1848	365	10	alsaedi	alsaedi	PROPN
easat-1848	365	11	and	and	CCONJ
easat-1848	365	12	rozaida	rozaida	PROPN
easat-1848	365	13	ghazali	ghazali	PROPN
easat-1848	365	14	,	,	PUNCT
easat-1848	365	15	“	"	PUNCT
easat-1848	365	16	enhanced	enhanced	ADJ
easat-1848	365	17	accuracy	accuracy	NOUN
easat-1848	365	18	of	of	ADP
easat-1848	365	19	heart	heart	NOUN
easat-1848	365	20	disease	disease	NOUN
easat-1848	365	21	prediction	prediction	NOUN
easat-1848	365	22	using	use	VERB
easat-1848	365	23	machine	machine	NOUN
easat-1848	365	24	learning	learning	NOUN
easat-1848	365	25	and	and	CCONJ
easat-1848	365	26	recurrent	recurrent	ADJ
easat-1848	365	27	neural	neural	ADJ
easat-1848	365	28	networks	network	NOUN
easat-1848	365	29	ensemble	ensemble	ADJ
easat-1848	365	30	majority	majority	NOUN
easat-1848	365	31	voting	voting	NOUN
easat-1848	365	32	method	method	NOUN
easat-1848	365	33	”	"	PUNCT
easat-1848	365	34	international	international	ADJ
easat-1848	365	35	journal	journal	NOUN
easat-1848	365	36	of	of	ADP
easat-1848	365	37	advanced	advanced	ADJ
easat-1848	365	38	computer	computer	NOUN
easat-1848	365	39	science	science	NOUN
easat-1848	365	40	and	and	CCONJ
easat-1848	365	41	applications(ijacsa),volume11,issue3,2020	applications(ijacsa),volume11,issue3,2020	PROPN
easat-1848	365	42	.	.	PUNCT
easat-1848	365	43	http://dx.doi.org/10.14569/ijacsa.2020.0110369	http://dx.doi.org/10.14569/ijacsa.2020.0110369	PROPN
easat-1848	366	1	[	[	X
easat-1848	366	2	34	34	NUM
easat-1848	366	3	]	]	X
easat-1848	366	4	md	md	PROPN
easat-1848	366	5	.	.	PROPN
easat-1848	366	6	julker	julker	PROPN
easat-1848	366	7	nayeem	nayeem	PROPN
easat-1848	366	8	,	,	PUNCT
easat-1848	366	9	sohel	sohel	PROPN
easat-1848	366	10	rana	rana	PROPN
easat-1848	366	11	,	,	PUNCT
easat-1848	366	12	and	and	CCONJ
easat-1848	366	13	md	md	PROPN
easat-1848	366	14	.	.	PROPN
easat-1848	366	15	rabiul	rabiul	PROPN
easat-1848	366	16	islam	islam	PROPN
easat-1848	366	17	,	,	PUNCT
easat-1848	366	18	“	"	PUNCT
easat-1848	366	19	prediction	prediction	NOUN
easat-1848	366	20	of	of	ADP
easat-1848	366	21	heart	heart	NOUN
easat-1848	366	22	disease	disease	NOUN
easat-1848	366	23	using	use	VERB
easat-1848	366	24	machine	machine	NOUN
easat-1848	366	25	learning	learn	VERB
easat-1848	366	26	algorithms	algorithm	NOUN
easat-1848	366	27	”	"	PUNCT
easat-1848	366	28	,	,	PUNCT
easat-1848	366	29	european	european	PROPN
easat-1848	366	30	journal	journal	PROPN
easat-1848	366	31	of	of	ADP
easat-1848	366	32	artificial	artificial	ADJ
easat-1848	366	33	intelligence	intelligence	NOUN
easat-1848	366	34	and	and	CCONJ
easat-1848	366	35	machine	machine	NOUN
easat-1848	366	36	learning	learning	NOUN
easat-1848	366	37	,	,	PUNCT
easat-1848	366	38	vol	vol	NOUN
easat-1848	366	39	1	1	NUM
easat-1848	366	40	|	|	NOUN
easat-1848	366	41	issue	issue	VERB
easat-1848	366	42	3	3	NUM
easat-1848	366	43	|	|	CCONJ
easat-1848	366	44	november	november	PROPN
easat-1848	366	45	2022	2022	NUM
easat-1848	366	46	.	.	PUNCT
easat-1848	367	1	[	[	X
easat-1848	367	2	35	35	NUM
easat-1848	367	3	]	]	SYM
easat-1848	367	4	lijetha.c	lijetha.c	PROPN
easat-1848	367	5	.	.	PUNCT
easat-1848	367	6	jaffrin	jaffrin	PROPN
easat-1848	367	7	,	,	PUNCT
easat-1848	367	8	dr.j	dr.j	NOUN
easat-1848	367	9	.	.	PUNCT
easat-1848	367	10	visumathi	visumathi	PROPN
easat-1848	367	11	,	,	PUNCT
easat-1848	367	12	dr.g.umarani	dr.g.umarani	PROPN
easat-1848	367	13	srikanth	srikanth	NOUN
easat-1848	367	14	,	,	PUNCT
easat-1848	367	15	“	"	PUNCT
easat-1848	367	16	role	role	NOUN
easat-1848	367	17	of	of	ADP
easat-1848	367	18	exploratory	exploratory	ADJ
easat-1848	367	19	analytics	analytic	NOUN
easat-1848	367	20	and	and	CCONJ
easat-1848	367	21	visualization	visualization	NOUN
easat-1848	367	22	in	in	ADP
easat-1848	367	23	heart	heart	NOUN
easat-1848	367	24	disease	disease	NOUN
easat-1848	367	25	prediction	prediction	NOUN
easat-1848	367	26	”	"	PUNCT
easat-1848	367	27	,	,	PUNCT
easat-1848	367	28	international	international	ADJ
easat-1848	367	29	journal	journal	NOUN
easat-1848	367	30	of	of	ADP
easat-1848	367	31	engineering	engineering	NOUN
easat-1848	367	32	trends	trend	NOUN
easat-1848	367	33	and	and	CCONJ
easat-1848	367	34	technology	technology	NOUN
easat-1848	367	35	volume	volume	NOUN
easat-1848	367	36	70	70	NUM
easat-1848	367	37	issue	issue	NOUN
easat-1848	367	38	1	1	NUM
easat-1848	367	39	,	,	PUNCT
easat-1848	367	40	24	24	NUM
easat-1848	367	41	-	-	SYM
easat-1848	367	42	34	34	NUM
easat-1848	367	43	,	,	PUNCT
easat-1848	367	44	january	january	PROPN
easat-1848	367	45	,	,	PUNCT
easat-1848	367	46	2022	2022	NUM
easat-1848	367	47	.	.	PUNCT
easat-1848	368	1	[	[	X
easat-1848	368	2	36	36	NUM
easat-1848	368	3	]	]	X
easat-1848	368	4	noroozi	noroozi	PROPN
easat-1848	368	5	,	,	PUNCT
easat-1848	368	6	z.	z.	PROPN
easat-1848	368	7	,	,	PUNCT
easat-1848	368	8	orooji	orooji	NOUN
easat-1848	368	9	,	,	PUNCT
easat-1848	368	10	a.	a.	NOUN
easat-1848	368	11	&	&	CCONJ
easat-1848	368	12	erfannia	erfannia	PROPN
easat-1848	368	13	,	,	PUNCT
easat-1848	368	14	l.	l.	PROPN
easat-1848	368	15	,	,	PUNCT
easat-1848	368	16	“	"	PUNCT
easat-1848	368	17	analyzing	analyze	VERB
easat-1848	368	18	the	the	DET
easat-1848	368	19	impact	impact	NOUN
easat-1848	368	20	of	of	ADP
easat-1848	368	21	feature	feature	NOUN
easat-1848	368	22	selection	selection	NOUN
easat-1848	368	23	methods	method	NOUN
easat-1848	368	24	on	on	ADP
easat-1848	368	25	machine	machine	NOUN
easat-1848	368	26	learning	learn	VERB
easat-1848	368	27	algorithms	algorithm	NOUN
easat-1848	368	28	for	for	ADP
easat-1848	368	29	heart	heart	NOUN
easat-1848	368	30	disease	disease	NOUN
easat-1848	368	31	prediction	prediction	NOUN
easat-1848	368	32	”	"	PUNCT
easat-1848	368	33	,	,	PUNCT
easat-1848	368	34	sci	sci	PROPN
easat-1848	368	35	rep	rep	PROPN
easat-1848	368	36	13	13	NUM
easat-1848	368	37	,	,	PUNCT
easat-1848	368	38	22588	22588	NUM
easat-1848	368	39	(	(	PUNCT
easat-1848	368	40	2023	2023	NUM
easat-1848	368	41	)	)	PUNCT
easat-1848	368	42	.	.	PUNCT
easat-1848	369	1	https://doi.org/10.1038/s41598-023-49962-w	https://doi.org/10.1038/s41598-023-49962-w	PROPN
easat-1848	369	2	.	.	PUNCT
easat-1848	370	1	[	[	X
easat-1848	370	2	37	37	NUM
easat-1848	370	3	]	]	X
easat-1848	370	4	kaushalya	kaushalya	PROPN
easat-1848	370	5	dissanayake	dissanayake	PROPN
easat-1848	370	6	,	,	PUNCT
easat-1848	370	7	md	md	PROPN
easat-1848	370	8	gapar	gapar	PROPN
easat-1848	370	9	md	md	PROPN
easat-1848	370	10	johar	johar	PROPN
easat-1848	370	11	,	,	PUNCT
easat-1848	370	12	“	"	PUNCT
easat-1848	370	13	comparative	comparative	ADJ
easat-1848	370	14	study	study	NOUN
easat-1848	370	15	on	on	ADP
easat-1848	370	16	heart	heart	NOUN
easat-1848	370	17	disease	disease	NOUN
easat-1848	370	18	prediction	prediction	NOUN
easat-1848	370	19	using	use	VERB
easat-1848	370	20	feature	feature	NOUN
easat-1848	370	21	selection	selection	NOUN
easat-1848	370	22	techniques	technique	NOUN
easat-1848	370	23	on	on	ADP
easat-1848	370	24	classification	classification	NOUN
easat-1848	370	25	algorithms	algorithm	NOUN
easat-1848	370	26	”	"	PUNCT
easat-1848	370	27	,	,	PUNCT
easat-1848	370	28	applied	apply	VERB
easat-1848	370	29	computational	computational	ADJ
easat-1848	370	30	intelliegence	intelliegence	NOUN
easat-1848	370	31	and	and	CCONJ
easat-1848	370	32	soft	soft	ADJ
easat-1848	370	33	computing	computing	NOUN
easat-1848	370	34	,	,	PUNCT
easat-1848	370	35	volume	volume	NOUN
easat-1848	370	36	2021	2021	NUM
easat-1848	370	37	,	,	PUNCT
easat-1848	370	38	article	article	NOUN
easat-1848	370	39	i	i	PROPN
easat-1848	370	40	d	d	PROPN
easat-1848	370	41	5581806	5581806	NUM
easat-1848	370	42	,	,	PUNCT
easat-1848	370	43	https://doi.org/10.1155/2021/5581806	https://doi.org/10.1155/2021/5581806	PROPN
easat-1848	370	44	.	.	PUNCT
easat-1848	371	1	[	[	X
easat-1848	371	2	38	38	NUM
easat-1848	371	3	]	]	PUNCT
easat-1848	371	4	bharti	bharti	PROPN
easat-1848	371	5	r	r	PROPN
easat-1848	371	6	,	,	PUNCT
easat-1848	371	7	khamparia	khamparia	PROPN
easat-1848	371	8	a	a	PRON
easat-1848	371	9	,	,	PUNCT
easat-1848	371	10	shabaz	shabaz	PROPN
easat-1848	371	11	m	m	PROPN
easat-1848	371	12	,	,	PUNCT
easat-1848	371	13	dhiman	dhiman	NOUN
easat-1848	371	14	g	g	NOUN
easat-1848	371	15	,	,	PUNCT
easat-1848	371	16	pande	pande	NOUN
easat-1848	371	17	s	s	PROPN
easat-1848	371	18	,	,	PUNCT
easat-1848	371	19	singh	singh	PROPN
easat-1848	371	20	p.	p.	NOUN
easat-1848	371	21	,	,	PUNCT
easat-1848	371	22	“	"	PUNCT
easat-1848	371	23	prediction	prediction	NOUN
easat-1848	371	24	of	of	ADP
easat-1848	371	25	heart	heart	NOUN
easat-1848	371	26	disease	disease	NOUN
easat-1848	371	27	using	use	VERB
easat-1848	371	28	a	a	DET
easat-1848	371	29	combination	combination	NOUN
easat-1848	371	30	of	of	ADP
easat-1848	371	31	machine	machine	NOUN
easat-1848	371	32	learning	learning	NOUN
easat-1848	371	33	and	and	CCONJ
easat-1848	371	34	deep	deep	ADJ
easat-1848	371	35	learning	learning	NOUN
easat-1848	371	36	”	"	PUNCT
easat-1848	371	37	,	,	PUNCT
easat-1848	371	38	computational	computational	ADJ
easat-1848	371	39	intelligence	intelligence	NOUN
easat-1848	371	40	and	and	CCONJ
easat-1848	371	41	neuroscience	neuroscience	NOUN
easat-1848	371	42	.	.	PUNCT
easat-1848	372	1	2021	2021	NUM
easat-1848	372	2	jul	jul	PROPN
easat-1848	372	3	1	1	NUM
easat-1848	372	4	;	;	PUNCT
easat-1848	372	5	2021:8387680	2021:8387680	NUM
easat-1848	372	6	.	.	X
easat-1848	372	7	doi	doi	NOUN
easat-1848	372	8	:	:	PUNCT
easat-1848	372	9	10.1155/2021/8387680	10.1155/2021/8387680	NUM
easat-1848	372	10	.	.	PUNCT
easat-1848	373	1	pmid	pmid	NOUN
easat-1848	373	2	:	:	PUNCT
easat-1848	373	3	34306056	34306056	NUM
easat-1848	373	4	;	;	PUNCT
easat-1848	373	5	pmcid	pmcid	ADJ
easat-1848	373	6	:	:	PUNCT
easat-1848	373	7	pmc8266441	pmc8266441	ADJ
easat-1848	373	8	.	.	PUNCT
easat-1848	374	1	[	[	X
easat-1848	374	2	39	39	NUM
easat-1848	374	3	]	]	X
easat-1848	374	4	xiao	xiao	PROPN
easat-1848	374	5	-	-	PUNCT
easat-1848	374	6	yan	yan	PROPN
easat-1848	374	7	gao	gao	PROPN
easat-1848	374	8	,	,	PUNCT
easat-1848	374	9	abdelmegeid	abdelmegeid	PROPN
easat-1848	374	10	amin	amin	PROPN
easat-1848	374	11	ali	ali	PROPN
easat-1848	374	12	,	,	PUNCT
easat-1848	374	13	hassan	hassan	PROPN
easat-1848	374	14	shaban	shaban	PROPN
easat-1848	374	15	hassan	hassan	PROPN
easat-1848	374	16	,	,	PUNCT
easat-1848	374	17	eman	eman	PROPN
easat-1848	374	18	m.	m.	PROPN
easat-1848	374	19	anwar	anwar	PROPN
easat-1848	374	20	,	,	PUNCT
easat-1848	374	21	“	"	PUNCT
easat-1848	374	22	improving	improve	VERB
easat-1848	374	23	the	the	DET
easat-1848	374	24	accuracy	accuracy	NOUN
easat-1848	374	25	for	for	ADP
easat-1848	374	26	analyzing	analyze	VERB
easat-1848	374	27	heart	heart	NOUN
easat-1848	374	28	diseases	disease	NOUN
easat-1848	374	29	prediction	prediction	NOUN
easat-1848	374	30	based	base	VERB
easat-1848	374	31	on	on	ADP
easat-1848	374	32	the	the	DET
easat-1848	374	33	ensemble	ensemble	ADJ
easat-1848	374	34	method	method	NOUN
easat-1848	374	35	”	"	PUNCT
easat-1848	374	36	,	,	PUNCT
easat-1848	374	37	complexity	complexity	NOUN
easat-1848	374	38	,	,	PUNCT
easat-1848	374	39	2021	2021	NUM
easat-1848	374	40	https://doi.org/10.1155/2021/6663455	https://doi.org/10.1155/2021/6663455	PROPN
easat-1848	374	41	.	.	PUNCT
easat-1848	375	1	[	[	X
easat-1848	375	2	40	40	NUM
easat-1848	375	3	]	]	SYM
easat-1848	375	4	mienye	mienye	PROPN
easat-1848	375	5	,	,	PUNCT
easat-1848	375	6	i.d	i.d	PROPN
easat-1848	375	7	.	.	PROPN
easat-1848	375	8	;	;	PUNCT
easat-1848	375	9	jere	jere	PROPN
easat-1848	375	10	,	,	PUNCT
easat-1848	375	11	n.	n.	NOUN
easat-1848	375	12	,	,	PUNCT
easat-1848	375	13	“	"	PUNCT
easat-1848	375	14	optimized	optimize	VERB
easat-1848	375	15	ensemble	ensemble	ADJ
easat-1848	375	16	learning	learning	NOUN
easat-1848	375	17	approach	approach	NOUN
easat-1848	375	18	with	with	ADP
easat-1848	375	19	explainable	explainable	ADJ
easat-1848	375	20	ai	ai	NOUN
easat-1848	375	21	for	for	ADP
easat-1848	375	22	improved	improved	ADJ
easat-1848	375	23	heart	heart	NOUN
easat-1848	375	24	disease	disease	NOUN
easat-1848	375	25	prediction	prediction	NOUN
easat-1848	375	26	”	"	PUNCT
easat-1848	375	27	,	,	PUNCT
easat-1848	375	28	information	information	NOUN
easat-1848	375	29	2024	2024	NUM
easat-1848	375	30	,	,	PUNCT
easat-1848	375	31	15	15	NUM
easat-1848	375	32	,	,	PUNCT
easat-1848	375	33	394	394	NUM
easat-1848	375	34	.	.	PUNCT
easat-1848	375	35	https://doi.org/10.3390/info15070394	https://doi.org/10.3390/info15070394	NOUN
easat-1848	375	36	.	.	PUNCT
easat-1848	376	1	[	[	X
easat-1848	376	2	41	41	NUM
easat-1848	376	3	]	]	X
easat-1848	376	4	khan	khan	PROPN
easat-1848	376	5	mamun	mamun	PROPN
easat-1848	376	6	,	,	PUNCT
easat-1848	376	7	m.m.r	m.m.r	ADJ
easat-1848	376	8	.	.	PUNCT
easat-1848	376	9	elfouly	elfouly	ADV
easat-1848	376	10	.	.	PUNCT
easat-1848	377	1	t.	t.	NOUN
easat-1848	377	2	,	,	PUNCT
easat-1848	377	3	“	"	PUNCT
easat-1848	377	4	detection	detection	NOUN
easat-1848	377	5	of	of	ADP
easat-1848	377	6	cardiovascular	cardiovascular	ADJ
easat-1848	377	7	disease	disease	NOUN
easat-1848	377	8	from	from	ADP
easat-1848	377	9	clinical	clinical	ADJ
easat-1848	377	10	parameters	parameter	NOUN
easat-1848	377	11	using	use	VERB
easat-1848	377	12	a	a	DET
easat-1848	377	13	onedimensional	onedimensional	ADJ
easat-1848	377	14	convolutional	convolutional	ADJ
easat-1848	377	15	neural	neural	ADJ
easat-1848	377	16	network	network	NOUN
easat-1848	377	17	”	"	PUNCT
easat-1848	377	18	,	,	PUNCT
easat-1848	377	19	bioengineering	bioengineering	NOUN
easat-1848	377	20	,	,	PUNCT
easat-1848	377	21	2023	2023	NUM
easat-1848	377	22	,	,	PUNCT
easat-1848	377	23	10	10	NUM
easat-1848	377	24	,	,	PUNCT
easat-1848	377	25	796	796	NUM
easat-1848	377	26	.	.	PUNCT
easat-1848	377	27	https://doi.org/10.3390/bioengineering10070796	https://doi.org/10.3390/bioengineering10070796	PROPN
easat-1848	377	28	.	.	PUNCT
easat-1848	378	1	https://doi.org/10.1038/s41598-020-72685-1	https://doi.org/10.1038/s41598-020-72685-1	PROPN
easat-1848	378	2	https://dx.doi.org/10.14569/ijacsa.2020.0110369	https://dx.doi.org/10.14569/ijacsa.2020.0110369	PROPN
easat-1848	378	3	https://doi.org/10.1038/s41598-023-49962-w	https://doi.org/10.1038/s41598-023-49962-w	PROPN
easat-1848	378	4	https://doi.org/10.3390/info15070394	https://doi.org/10.3390/info15070394	PROPN
easat-1848	378	5	1471	1471	NUM
easat-1848	378	6	edelweiss	edelweiss	PROPN
easat-1848	378	7	applied	apply	VERB
easat-1848	378	8	science	science	NOUN
easat-1848	378	9	and	and	CCONJ
easat-1848	378	10	technology	technology	NOUN
easat-1848	378	11	issn	issn	PROPN
easat-1848	378	12	:	:	PUNCT
easat-1848	378	13	2576	2576	NUM
easat-1848	378	14	-	-	SYM
easat-1848	378	15	8484	8484	NUM
easat-1848	378	16	vol	vol	NOUN
easat-1848	378	17	.	.	PROPN
easat-1848	378	18	8	8	NUM
easat-1848	378	19	,	,	PUNCT
easat-1848	378	20	no	no	INTJ
easat-1848	378	21	.	.	NOUN
easat-1848	378	22	5	5	NUM
easat-1848	378	23	:	:	SYM
easat-1848	378	24	1445	1445	NUM
easat-1848	378	25	-	-	SYM
easat-1848	378	26	1471	1471	NUM
easat-1848	378	27	,	,	PUNCT
easat-1848	378	28	2024	2024	NUM
easat-1848	378	29	doi	doi	NOUN
easat-1848	378	30	:	:	PUNCT
easat-1848	378	31	10.55214/25768484.v8i5.1848	10.55214/25768484.v8i5.1848	PROPN
easat-1848	378	32	©	©	PROPN
easat-1848	378	33	2024	2024	NUM
easat-1848	378	34	by	by	ADP
easat-1848	378	35	the	the	DET
easat-1848	378	36	authors	author	NOUN
easat-1848	378	37	;	;	PUNCT
easat-1848	378	38	licensee	licensee	PROPN
easat-1848	378	39	learning	learning	NOUN
easat-1848	378	40	gate	gate	NOUN
easat-1848	379	1	[	[	X
easat-1848	379	2	42	42	NUM
easat-1848	379	3	]	]	PUNCT
easat-1848	379	4	arkadip	arkadip	PROPN
easat-1848	379	5	ray	ray	PROPN
easat-1848	379	6	,	,	PUNCT
easat-1848	379	7	avijit	avijit	PROPN
easat-1848	379	8	kumar	kumar	PROPN
easat-1848	379	9	chaudhuri	chaudhuri	PROPN
easat-1848	379	10	,	,	PUNCT
easat-1848	379	11	“	"	PUNCT
easat-1848	379	12	smart	smart	ADJ
easat-1848	379	13	healthcare	healthcare	NOUN
easat-1848	379	14	disease	disease	NOUN
easat-1848	379	15	diagnosis	diagnosis	NOUN
easat-1848	379	16	and	and	CCONJ
easat-1848	379	17	patient	patient	ADJ
easat-1848	379	18	management	management	NOUN
easat-1848	379	19	:	:	PUNCT
easat-1848	379	20	innovation	innovation	NOUN
easat-1848	379	21	,	,	PUNCT
easat-1848	379	22	improvement	improvement	NOUN
easat-1848	379	23	and	and	CCONJ
easat-1848	379	24	skill	skill	NOUN
easat-1848	379	25	development	development	NOUN
easat-1848	379	26	”	"	PUNCT
easat-1848	379	27	,	,	PUNCT
easat-1848	379	28	machine	machine	NOUN
easat-1848	379	29	learning	learning	NOUN
easat-1848	379	30	with	with	ADP
easat-1848	379	31	applications	application	NOUN
easat-1848	379	32	,	,	PUNCT
easat-1848	379	33	volume	volume	NOUN
easat-1848	379	34	3	3	NUM
easat-1848	379	35	,	,	PUNCT
easat-1848	379	36	2021	2021	NUM
easat-1848	379	37	,	,	PUNCT
easat-1848	379	38	100011	100011	NUM
easat-1848	379	39	,	,	PUNCT
easat-1848	379	40	issn	issn	PROPN
easat-1848	379	41	26668270	26668270	NUM
easat-1848	379	42	,	,	PUNCT
easat-1848	379	43	https://doi.org/10.1016/j.mlwa.2020.100011	https://doi.org/10.1016/j.mlwa.2020.100011	ADJ
easat-1848	379	44	.	.	PUNCT
easat-1848	380	1	[	[	X
easat-1848	380	2	43	43	NUM
easat-1848	380	3	]	]	X
easat-1848	380	4	oleiwi	oleiwi	NOUN
easat-1848	380	5	,	,	PUNCT
easat-1848	380	6	zahraa	zahraa	PROPN
easat-1848	380	7	ch	ch	PROPN
easat-1848	380	8	.	.	PROPN
easat-1848	380	9	,	,	PUNCT
easat-1848	380	10	ebtesam	ebtesam	PROPN
easat-1848	380	11	n.	n.	PROPN
easat-1848	380	12	alshemmary	alshemmary	PROPN
easat-1848	380	13	,	,	PUNCT
easat-1848	380	14	and	and	CCONJ
easat-1848	380	15	salam	salam	PROPN
easat-1848	380	16	al	al	PROPN
easat-1848	380	17	-	-	PUNCT
easat-1848	380	18	augby	augby	PROPN
easat-1848	380	19	.	.	PUNCT
easat-1848	381	1	“	"	PUNCT
easat-1848	381	2	adaptive	adaptive	ADJ
easat-1848	381	3	features	feature	VERB
easat-1848	381	4	selection	selection	NOUN
easat-1848	381	5	technique	technique	NOUN
easat-1848	381	6	for	for	ADP
easat-1848	381	7	efficient	efficient	ADJ
easat-1848	381	8	heart	heart	NOUN
easat-1848	381	9	disease	disease	NOUN
easat-1848	381	10	prediction	prediction	NOUN
easat-1848	381	11	”	"	PUNCT
easat-1848	381	12	,	,	PUNCT
easat-1848	381	13	journal	journal	NOUN
easat-1848	381	14	of	of	ADP
easat-1848	381	15	al	al	PROPN
easat-1848	381	16	-	-	PUNCT
easat-1848	381	17	qadisiyah	qadisiyah	NOUN
easat-1848	381	18	for	for	ADP
easat-1848	381	19	computer	computer	NOUN
easat-1848	381	20	science	science	NOUN
easat-1848	381	21	and	and	CCONJ
easat-1848	381	22	mathematics	mathematic	NOUN
easat-1848	381	23	,	,	PUNCT
easat-1848	381	24	vol	vol	NOUN
easat-1848	381	25	.	.	PROPN
easat-1848	381	26	15(1	15(1	NUM
easat-1848	381	27	)	)	PUNCT
easat-1848	381	28	2023	2023	NUM
easat-1848	381	29	,	,	PUNCT
easat-1848	381	30	ppcomp.1–18	ppcomp.1–18	ADJ
easat-1848	381	31	https://	https://	PROPN
easat-1848	381	32	doi.org/10.29304/jqcm.2023.15.1.1137	doi.org/10.29304/jqcm.2023.15.1.1137	NUM
easat-1848	381	33	[	[	X
easat-1848	381	34	44	44	NUM
easat-1848	381	35	]	]	PUNCT
easat-1848	381	36	veena	veena	PROPN
easat-1848	381	37	s	s	PROPN
easat-1848	381	38	t	t	PROPN
easat-1848	381	39	,	,	PUNCT
easat-1848	381	40	jeevetha	jeevetha	PROPN
easat-1848	381	41	r	r	PROPN
easat-1848	381	42	,	,	PUNCT
easat-1848	381	43	abirami	abirami	NOUN
easat-1848	381	44	n	n	NUM
easat-1848	381	45	,	,	PUNCT
easat-1848	381	46	“	"	PUNCT
easat-1848	381	47	prediction	prediction	NOUN
easat-1848	381	48	of	of	ADP
easat-1848	381	49	heart	heart	NOUN
easat-1848	381	50	disease	disease	NOUN
easat-1848	381	51	using	use	VERB
easat-1848	381	52	hybrid	hybrid	ADJ
easat-1848	381	53	feature	feature	NOUN
easat-1848	381	54	selection	selection	NOUN
easat-1848	381	55	”	"	PUNCT
easat-1848	381	56	,	,	PUNCT
easat-1848	381	57	journal	journal	NOUN
easat-1848	381	58	of	of	ADP
easat-1848	381	59	positive	positive	ADJ
easat-1848	381	60	school	school	NOUN
easat-1848	381	61	psychology	psychology	NOUN
easat-1848	381	62	,	,	PUNCT
easat-1848	381	63	2022	2022	NUM
easat-1848	381	64	,	,	PUNCT
easat-1848	381	65	vol	vol	NOUN
easat-1848	381	66	.	.	PROPN
easat-1848	381	67	6	6	NUM
easat-1848	381	68	,	,	PUNCT
easat-1848	381	69	no	no	INTJ
easat-1848	381	70	.	.	NOUN
easat-1848	381	71	4	4	NUM
easat-1848	381	72	,	,	PUNCT
easat-1848	381	73	10454–10469	10454–10469	NUM
easat-1848	381	74	.	.	PUNCT
easat-1848	382	1	[	[	X
easat-1848	382	2	45	45	NUM
easat-1848	382	3	]	]	X
easat-1848	382	4	n.	n.	NOUN
easat-1848	382	5	ghaniaviyanto	ghaniaviyanto	NOUN
easat-1848	382	6	ramadhan	ramadhan	PROPN
easat-1848	382	7	,	,	PUNCT
easat-1848	382	8	adiwijaya	adiwijaya	PROPN
easat-1848	382	9	,	,	PUNCT
easat-1848	382	10	w.	w.	PROPN
easat-1848	382	11	maharani	maharani	PROPN
easat-1848	382	12	and	and	CCONJ
easat-1848	382	13	a.	a.	NOUN
easat-1848	382	14	akbar	akbar	NOUN
easat-1848	382	15	gozali	gozali	VERB
easat-1848	382	16	,	,	PUNCT
easat-1848	382	17	"	"	PUNCT
easat-1848	382	18	chronic	chronic	ADJ
easat-1848	382	19	diseases	disease	NOUN
easat-1848	382	20	prediction	prediction	NOUN
easat-1848	382	21	using	use	VERB
easat-1848	382	22	machine	machine	NOUN
easat-1848	382	23	learning	learn	VERB
easat-1848	382	24	with	with	ADP
easat-1848	382	25	data	datum	NOUN
easat-1848	382	26	preprocessing	preprocesse	VERB
easat-1848	382	27	handling	handling	NOUN
easat-1848	382	28	:	:	PUNCT
easat-1848	382	29	a	a	DET
easat-1848	382	30	critical	critical	ADJ
easat-1848	382	31	review	review	NOUN
easat-1848	382	32	,	,	PUNCT
easat-1848	382	33	"	"	PUNCT
easat-1848	382	34	ieee	ieee	NOUN
easat-1848	382	35	access	access	NOUN
easat-1848	382	36	,	,	PUNCT
easat-1848	382	37	vol	vol	NOUN
easat-1848	382	38	.	.	PROPN
easat-1848	382	39	12	12	NUM
easat-1848	382	40	,	,	PUNCT
easat-1848	382	41	pp	pp	ADJ
easat-1848	382	42	.	.	PUNCT
easat-1848	383	1	80698	80698	NUM
easat-1848	383	2	-	-	SYM
easat-1848	383	3	80730	80730	NUM
easat-1848	383	4	,	,	PUNCT
easat-1848	383	5	2024	2024	NUM
easat-1848	383	6	,	,	PUNCT
easat-1848	383	7	doi	doi	NOUN
easat-1848	383	8	:	:	PUNCT
easat-1848	383	9	10.1109	10.1109	NUM
easat-1848	383	10	/	/	SYM
easat-1848	383	11	access.2024.3406748	access.2024.3406748	NOUN
easat-1848	383	12	.	.	PUNCT
easat-1848	384	1	[	[	X
easat-1848	384	2	46	46	NUM
easat-1848	384	3	]	]	X
easat-1848	384	4	kim	kim	PROPN
easat-1848	384	5	,	,	PUNCT
easat-1848	384	6	k.	k.	PROPN
easat-1848	384	7	.	.	PUNCT
easat-1848	384	8	,	,	PUNCT
easat-1848	384	9	&	&	CCONJ
easat-1848	384	10	park	park	PROPN
easat-1848	384	11	,	,	PUNCT
easat-1848	384	12	h.	h.	PROPN
easat-1848	384	13	,	,	PUNCT
easat-1848	384	14	“	"	PUNCT
easat-1848	384	15	neural	neural	ADJ
easat-1848	384	16	network	network	NOUN
easat-1848	384	17	approach	approach	NOUN
easat-1848	384	18	to	to	PART
easat-1848	384	19	predict	predict	VERB
easat-1848	384	20	the	the	DET
easat-1848	384	21	association	association	NOUN
easat-1848	384	22	between	between	ADP
easat-1848	384	23	blood	blood	NOUN
easat-1848	384	24	cadmium	cadmium	NOUN
easat-1848	384	25	levels	level	NOUN
easat-1848	384	26	and	and	CCONJ
easat-1848	384	27	hypertension	hypertension	NOUN
easat-1848	384	28	”	"	PUNCT
easat-1848	384	29	,	,	PUNCT
easat-1848	384	30	edelweiss	edelweiss	PROPN
easat-1848	384	31	applied	apply	VERB
easat-1848	384	32	science	science	NOUN
easat-1848	384	33	and	and	CCONJ
easat-1848	384	34	technology	technology	NOUN
easat-1848	384	35	,	,	PUNCT
easat-1848	384	36	2024	2024	NUM
easat-1848	384	37	,	,	PUNCT
easat-1848	384	38	8(4	8(4	NUM
easat-1848	384	39	)	)	PUNCT
easat-1848	384	40	,	,	PUNCT
easat-1848	384	41	336–344	336–344	NUM
easat-1848	384	42	.	.	PUNCT
easat-1848	384	43	https://doi.org/10.55214/25768484.v8i4.978	https://doi.org/10.55214/25768484.v8i4.978	X