id	sid	tid	token	lemma	pos
cana-1616	1	1	indonesian	indonesian	ADJ
cana-1616	1	2	journal	journal	PROPN
cana-1616	1	3	of	of	ADP
cana-1616	1	4	electrical	electrical	ADJ
cana-1616	1	5	engineering	engineering	NOUN
cana-1616	1	6	and	and	CCONJ
cana-1616	1	7	computer	computer	NOUN
cana-1616	1	8	science	science	NOUN
cana-1616	1	9	communications	communication	NOUN
cana-1616	1	10	on	on	ADP
cana-1616	1	11	applied	apply	VERB
cana-1616	1	12	nonlinear	nonlinear	ADJ
cana-1616	1	13	analysis	analysis	NOUN
cana-1616	1	14	issn	issn	NOUN
cana-1616	1	15	:	:	PUNCT
cana-1616	1	16	1074	1074	NUM
cana-1616	1	17	-	-	PUNCT
cana-1616	1	18	133x	133x	NUM
cana-1616	1	19	vol	vol	NOUN
cana-1616	1	20	31	31	NUM
cana-1616	1	21	no	no	NOUN
cana-1616	1	22	.	.	PUNCT
cana-1616	2	1	8s	8s	PROPN
cana-1616	2	2	(	(	PUNCT
cana-1616	2	3	2024	2024	NUM
cana-1616	2	4	)	)	PUNCT
cana-1616	2	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	2	6	773	773	NUM
cana-1616	2	7	a	a	DET
cana-1616	2	8	novel	novel	ADJ
cana-1616	2	9	multi	multi	ADJ
cana-1616	2	10	-	-	ADJ
cana-1616	2	11	stage	stage	ADJ
cana-1616	2	12	feature	feature	NOUN
cana-1616	2	13	selection	selection	NOUN
cana-1616	2	14	and	and	CCONJ
cana-1616	2	15	classification	classification	NOUN
cana-1616	2	16	model	model	NOUN
cana-1616	2	17	for	for	ADP
cana-1616	2	18	accurate	accurate	ADJ
cana-1616	2	19	liver	liver	NOUN
cana-1616	2	20	disease	disease	NOUN
cana-1616	2	21	detection	detection	NOUN
cana-1616	2	22	gurmeet	gurmeet	NOUN
cana-1616	2	23	kaur	kaur	PROPN
cana-1616	2	24	saini1	saini1	PROPN
cana-1616	2	25	,	,	PUNCT
cana-1616	2	26	sachin	sachin	PROPN
cana-1616	2	27	ahuja2	ahuja2	PROPN
cana-1616	2	28	,	,	PUNCT
cana-1616	2	29	vishal	vishal	ADJ
cana-1616	2	30	bharti3	bharti3	NOUN
cana-1616	2	31	1	1	NUM
cana-1616	2	32	department	department	NOUN
cana-1616	2	33	of	of	ADP
cana-1616	2	34	computer	computer	NOUN
cana-1616	2	35	science	science	NOUN
cana-1616	2	36	and	and	CCONJ
cana-1616	2	37	engineering	engineering	NOUN
cana-1616	2	38	,	,	PUNCT
cana-1616	2	39	chandigarh	chandigarh	PROPN
cana-1616	2	40	university	university	NOUN
cana-1616	2	41	,	,	PUNCT
cana-1616	2	42	punjab	punjab	PROPN
cana-1616	2	43	,	,	PUNCT
cana-1616	2	44	india	india	PROPN
cana-1616	2	45	email	email	NOUN
cana-1616	2	46	:	:	PUNCT
cana-1616	2	47	gurmeetsaini02@gmail.com	gurmeetsaini02@gmail.com	X
cana-1616	2	48	2	2	NUM
cana-1616	2	49	,	,	PUNCT
cana-1616	2	50	department	department	NOUN
cana-1616	2	51	of	of	ADP
cana-1616	2	52	computer	computer	NOUN
cana-1616	2	53	science	science	NOUN
cana-1616	2	54	and	and	CCONJ
cana-1616	2	55	engineering	engineering	NOUN
cana-1616	2	56	,	,	PUNCT
cana-1616	2	57	chandigarh	chandigarh	PROPN
cana-1616	2	58	university	university	NOUN
cana-1616	2	59	,	,	PUNCT
cana-1616	2	60	mohali	mohali	PROPN
cana-1616	2	61	,	,	PUNCT
cana-1616	2	62	punjab	punjab	PROPN
cana-1616	2	63	,	,	PUNCT
cana-1616	2	64	india	india	PROPN
cana-1616	2	65	3department	3department	PROPN
cana-1616	2	66	of	of	ADP
cana-1616	2	67	computer	computer	NOUN
cana-1616	2	68	science	science	NOUN
cana-1616	2	69	and	and	CCONJ
cana-1616	2	70	engineering	engineering	NOUN
cana-1616	2	71	,	,	PUNCT
cana-1616	2	72	maharishi	maharishi	PROPN
cana-1616	2	73	markandeshwar	markandeshwar	PROPN
cana-1616	2	74	(	(	PUNCT
cana-1616	2	75	deemed	deem	VERB
cana-1616	2	76	to	to	PART
cana-1616	2	77	be	be	AUX
cana-1616	2	78	university	university	NOUN
cana-1616	2	79	)	)	PUNCT
cana-1616	2	80	mullana	mullana	PROPN
cana-1616	2	81	,	,	PUNCT
cana-1616	2	82	ambala	ambala	PROPN
cana-1616	2	83	,	,	PUNCT
cana-1616	2	84	haryana	haryana	PROPN
cana-1616	2	85	corresponding	corresponding	PROPN
cana-1616	2	86	author	author	NOUN
cana-1616	2	87	:	:	PUNCT
cana-1616	2	88	gurmeetsaini02@gmail.com	gurmeetsaini02@gmail.com	X
cana-1616	2	89	article	article	NOUN
cana-1616	2	90	history	history	NOUN
cana-1616	2	91	:	:	PUNCT
cana-1616	2	92	received	receive	VERB
cana-1616	2	93	:	:	PUNCT
cana-1616	2	94	26	26	NUM
cana-1616	2	95	-	-	PUNCT
cana-1616	2	96	04	04	NUM
cana-1616	2	97	-	-	PUNCT
cana-1616	2	98	2024	2024	NUM
cana-1616	2	99	revised	revise	VERB
cana-1616	2	100	:	:	PUNCT
cana-1616	2	101	16	16	NUM
cana-1616	2	102	-	-	SYM
cana-1616	2	103	06	06	NUM
cana-1616	2	104	-	-	PUNCT
cana-1616	2	105	2024	2024	NUM
cana-1616	2	106	accepted	accept	VERB
cana-1616	2	107	:	:	PUNCT
cana-1616	2	108	28	28	NUM
cana-1616	2	109	-	-	SYM
cana-1616	2	110	06	06	NUM
cana-1616	2	111	-	-	PUNCT
cana-1616	2	112	2024	2024	NUM
cana-1616	2	113	abstract	abstract	NOUN
cana-1616	2	114	:	:	PUNCT
cana-1616	2	115	liver	liver	NOUN
cana-1616	2	116	disease	disease	NOUN
cana-1616	2	117	,	,	PUNCT
cana-1616	2	118	comprising	comprise	VERB
cana-1616	2	119	a	a	DET
cana-1616	2	120	spectrum	spectrum	NOUN
cana-1616	2	121	of	of	ADP
cana-1616	2	122	conditions	condition	NOUN
cana-1616	2	123	that	that	PRON
cana-1616	2	124	afflict	afflict	VERB
cana-1616	2	125	the	the	DET
cana-1616	2	126	liver	liver	NOUN
cana-1616	2	127	,	,	PUNCT
cana-1616	2	128	stands	stand	VERB
cana-1616	2	129	as	as	ADP
cana-1616	2	130	a	a	DET
cana-1616	2	131	significant	significant	ADJ
cana-1616	2	132	health	health	NOUN
cana-1616	2	133	challenge	challenge	NOUN
cana-1616	2	134	with	with	ADP
cana-1616	2	135	global	global	ADJ
cana-1616	2	136	implications	implication	NOUN
cana-1616	2	137	.	.	PUNCT
cana-1616	3	1	this	this	DET
cana-1616	3	2	paper	paper	NOUN
cana-1616	3	3	presents	present	VERB
cana-1616	3	4	an	an	DET
cana-1616	3	5	effective	effective	ADJ
cana-1616	3	6	and	and	CCONJ
cana-1616	3	7	highly	highly	ADV
cana-1616	3	8	accurate	accurate	ADJ
cana-1616	3	9	liver	liver	NOUN
cana-1616	3	10	disease	disease	NOUN
cana-1616	3	11	detection	detection	NOUN
cana-1616	3	12	model	model	NOUN
cana-1616	3	13	wherein	wherein	SCONJ
cana-1616	3	14	unique	unique	ADJ
cana-1616	3	15	feature	feature	NOUN
cana-1616	3	16	selection	selection	NOUN
cana-1616	3	17	and	and	CCONJ
cana-1616	3	18	classification	classification	NOUN
cana-1616	3	19	techniques	technique	NOUN
cana-1616	3	20	are	be	AUX
cana-1616	3	21	implemented	implement	VERB
cana-1616	3	22	.	.	PUNCT
cana-1616	4	1	the	the	DET
cana-1616	4	2	novelty	novelty	NOUN
cana-1616	4	3	contribution	contribution	NOUN
cana-1616	4	4	of	of	ADP
cana-1616	4	5	this	this	DET
cana-1616	4	6	work	work	NOUN
cana-1616	4	7	is	be	AUX
cana-1616	4	8	effective	effective	ADJ
cana-1616	4	9	feature	feature	NOUN
cana-1616	4	10	selection	selection	NOUN
cana-1616	4	11	technique	technique	NOUN
cana-1616	4	12	in	in	ADP
cana-1616	4	13	which	which	PRON
cana-1616	4	14	features	feature	NOUN
cana-1616	4	15	are	be	AUX
cana-1616	4	16	selected	select	VERB
cana-1616	4	17	in	in	ADP
cana-1616	4	18	three	three	NUM
cana-1616	4	19	stages	stage	NOUN
cana-1616	4	20	.	.	PUNCT
cana-1616	5	1	in	in	ADP
cana-1616	5	2	the	the	DET
cana-1616	5	3	first	first	ADJ
cana-1616	5	4	stage	stage	NOUN
cana-1616	5	5	,	,	PUNCT
cana-1616	5	6	entropy	entropy	PROPN
cana-1616	5	7	,	,	PUNCT
cana-1616	5	8	eigenvector	eigenvector	NOUN
cana-1616	5	9	centrality	centrality	NOUN
cana-1616	5	10	and	and	CCONJ
cana-1616	5	11	entropy	entropy	NOUN
cana-1616	5	12	-	-	PUNCT
cana-1616	5	13	correlation	correlation	NOUN
cana-1616	5	14	based	base	VERB
cana-1616	5	15	techniques	technique	NOUN
cana-1616	5	16	are	be	AUX
cana-1616	5	17	implemented	implement	VERB
cana-1616	5	18	on	on	ADP
cana-1616	5	19	each	each	DET
cana-1616	5	20	feature	feature	NOUN
cana-1616	5	21	to	to	PART
cana-1616	5	22	determine	determine	VERB
cana-1616	5	23	their	their	PRON
cana-1616	5	24	relevance	relevance	NOUN
cana-1616	5	25	score	score	NOUN
cana-1616	5	26	.	.	PUNCT
cana-1616	6	1	these	these	DET
cana-1616	6	2	features	feature	NOUN
cana-1616	6	3	are	be	AUX
cana-1616	6	4	then	then	ADV
cana-1616	6	5	combined	combine	VERB
cana-1616	6	6	and	and	CCONJ
cana-1616	6	7	their	their	PRON
cana-1616	6	8	average	average	ADJ
cana-1616	6	9	value	value	NOUN
cana-1616	6	10	is	be	AUX
cana-1616	6	11	calculated	calculate	VERB
cana-1616	6	12	to	to	PART
cana-1616	6	13	form	form	VERB
cana-1616	6	14	the	the	DET
cana-1616	6	15	first	first	ADJ
cana-1616	6	16	feature	feature	NOUN
cana-1616	6	17	score	score	NOUN
cana-1616	6	18	vector	vector	NOUN
cana-1616	6	19	.	.	PUNCT
cana-1616	7	1	in	in	ADP
cana-1616	7	2	the	the	DET
cana-1616	7	3	second	second	ADJ
cana-1616	7	4	stage	stage	NOUN
cana-1616	7	5	,	,	PUNCT
cana-1616	7	6	randon	randon	PROPN
cana-1616	7	7	forest	forest	NOUN
cana-1616	7	8	(	(	PUNCT
cana-1616	7	9	rf	rf	NOUN
cana-1616	7	10	)	)	PUNCT
cana-1616	7	11	classifier	classifier	NOUN
cana-1616	7	12	is	be	AUX
cana-1616	7	13	used	use	VERB
cana-1616	7	14	for	for	ADP
cana-1616	7	15	analysing	analyse	VERB
cana-1616	7	16	the	the	DET
cana-1616	7	17	effectiveness	effectiveness	NOUN
cana-1616	7	18	of	of	ADP
cana-1616	7	19	features	feature	NOUN
cana-1616	7	20	selected	select	VERB
cana-1616	7	21	in	in	ADP
cana-1616	7	22	first	first	ADJ
cana-1616	7	23	stage	stage	NOUN
cana-1616	7	24	in	in	ADP
cana-1616	7	25	terms	term	NOUN
cana-1616	7	26	of	of	ADP
cana-1616	7	27	their	their	PRON
cana-1616	7	28	accuracy	accuracy	NOUN
cana-1616	7	29	.	.	PUNCT
cana-1616	8	1	based	base	VERB
cana-1616	8	2	on	on	ADP
cana-1616	8	3	this	this	DET
cana-1616	8	4	accuracy	accuracy	NOUN
cana-1616	8	5	,	,	PUNCT
cana-1616	8	6	the	the	DET
cana-1616	8	7	relevance	relevance	NOUN
cana-1616	8	8	score	score	NOUN
cana-1616	8	9	of	of	ADP
cana-1616	8	10	features	feature	NOUN
cana-1616	8	11	is	be	AUX
cana-1616	8	12	again	again	ADV
cana-1616	8	13	updated	update	VERB
cana-1616	8	14	to	to	PART
cana-1616	8	15	form	form	VERB
cana-1616	8	16	the	the	DET
cana-1616	8	17	second	second	ADJ
cana-1616	8	18	feature	feature	NOUN
cana-1616	8	19	set	set	NOUN
cana-1616	8	20	.	.	PUNCT
cana-1616	9	1	in	in	ADP
cana-1616	9	2	the	the	DET
cana-1616	9	3	third	third	ADJ
cana-1616	9	4	stage	stage	NOUN
cana-1616	9	5	,	,	PUNCT
cana-1616	9	6	fuzzy	fuzzy	ADJ
cana-1616	9	7	model	model	NOUN
cana-1616	9	8	is	be	AUX
cana-1616	9	9	used	use	VERB
cana-1616	9	10	for	for	ADP
cana-1616	9	11	determining	determine	VERB
cana-1616	9	12	the	the	DET
cana-1616	9	13	contextual	contextual	ADJ
cana-1616	9	14	relevance	relevance	NOUN
cana-1616	9	15	among	among	ADP
cana-1616	9	16	various	various	ADJ
cana-1616	9	17	features	feature	NOUN
cana-1616	9	18	.	.	PUNCT
cana-1616	10	1	the	the	DET
cana-1616	10	2	selected	select	VERB
cana-1616	10	3	feature	feature	NOUN
cana-1616	10	4	set	set	NOUN
cana-1616	10	5	is	be	AUX
cana-1616	10	6	then	then	ADV
cana-1616	10	7	passed	pass	VERB
cana-1616	10	8	to	to	PART
cana-1616	10	9	proposed	propose	VERB
cana-1616	10	10	belv	belv	PROPN
cana-1616	10	11	classification	classification	NOUN
cana-1616	10	12	model	model	NOUN
cana-1616	10	13	,	,	PUNCT
cana-1616	10	14	wherein	wherein	SCONJ
cana-1616	10	15	techniques	technique	NOUN
cana-1616	10	16	like	like	ADP
cana-1616	10	17	bagging	bagging	NOUN
cana-1616	10	18	,	,	PUNCT
cana-1616	10	19	ensemble	ensemble	ADJ
cana-1616	10	20	learning	learning	NOUN
cana-1616	10	21	and	and	CCONJ
cana-1616	10	22	voting	voting	NOUN
cana-1616	10	23	is	be	AUX
cana-1616	10	24	applied	apply	VERB
cana-1616	10	25	.	.	PUNCT
cana-1616	11	1	three	three	NUM
cana-1616	11	2	baseline	baseline	PROPN
cana-1616	11	3	classifiers	classifier	NOUN
cana-1616	11	4	i.e.	i.e.	X
cana-1616	11	5	,	,	PUNCT
cana-1616	11	6	knn	knn	PROPN
cana-1616	11	7	,	,	PUNCT
cana-1616	11	8	rf	rf	NOUN
cana-1616	11	9	and	and	CCONJ
cana-1616	11	10	decision	decision	NOUN
cana-1616	11	11	tree	tree	NOUN
cana-1616	11	12	(	(	PUNCT
cana-1616	11	13	dt	dt	NOUN
cana-1616	11	14	)	)	PUNCT
cana-1616	11	15	are	be	AUX
cana-1616	11	16	used	use	VERB
cana-1616	11	17	in	in	ADP
cana-1616	11	18	ensemble	ensemble	ADJ
cana-1616	11	19	learning	learning	NOUN
cana-1616	11	20	to	to	PART
cana-1616	11	21	make	make	VERB
cana-1616	11	22	individual	individual	ADJ
cana-1616	11	23	predictions	prediction	NOUN
cana-1616	11	24	which	which	PRON
cana-1616	11	25	are	be	AUX
cana-1616	11	26	then	then	ADV
cana-1616	11	27	combined	combine	VERB
cana-1616	11	28	before	before	ADP
cana-1616	11	29	applying	apply	VERB
cana-1616	11	30	majority	majority	NOUN
cana-1616	11	31	voting	voting	NOUN
cana-1616	11	32	mechanism	mechanism	NOUN
cana-1616	11	33	to	to	PART
cana-1616	11	34	make	make	VERB
cana-1616	11	35	the	the	DET
cana-1616	11	36	final	final	ADJ
cana-1616	11	37	prediction	prediction	NOUN
cana-1616	11	38	.	.	PUNCT
cana-1616	12	1	the	the	DET
cana-1616	12	2	efficacy	efficacy	NOUN
cana-1616	12	3	of	of	ADP
cana-1616	12	4	proposed	propose	VERB
cana-1616	12	5	model	model	NOUN
cana-1616	12	6	is	be	AUX
cana-1616	12	7	tested	test	VERB
cana-1616	12	8	on	on	ADP
cana-1616	12	9	ilpd	ilpd	NOUN
cana-1616	12	10	and	and	CCONJ
cana-1616	12	11	cpd	cpd	ADJ
cana-1616	12	12	datasets	dataset	NOUN
cana-1616	12	13	for	for	ADP
cana-1616	12	14	binary	binary	ADJ
cana-1616	12	15	classification	classification	NOUN
cana-1616	12	16	and	and	CCONJ
cana-1616	12	17	multi	multi	ADJ
cana-1616	12	18	-	-	ADJ
cana-1616	12	19	stage	stage	ADJ
cana-1616	12	20	disease	disease	NOUN
cana-1616	12	21	detection	detection	NOUN
cana-1616	12	22	respectively	respectively	ADV
cana-1616	12	23	.	.	PUNCT
cana-1616	13	1	through	through	ADP
cana-1616	13	2	extensive	extensive	ADJ
cana-1616	13	3	experiments	experiment	NOUN
cana-1616	13	4	in	in	ADP
cana-1616	13	5	matlab	matlab	PROPN
cana-1616	13	6	software	software	NOUN
cana-1616	13	7	proposed	propose	VERB
cana-1616	13	8	model	model	NOUN
cana-1616	13	9	attained	attain	VERB
cana-1616	13	10	an	an	DET
cana-1616	13	11	accuracy	accuracy	NOUN
cana-1616	13	12	of	of	ADP
cana-1616	13	13	93	93	NUM
cana-1616	13	14	%	%	NOUN
cana-1616	13	15	and	and	CCONJ
cana-1616	13	16	96.8	96.8	NUM
cana-1616	13	17	%	%	NOUN
cana-1616	13	18	for	for	ADP
cana-1616	13	19	binary	binary	ADJ
cana-1616	13	20	and	and	CCONJ
cana-1616	13	21	multi	multi	ADJ
cana-1616	13	22	-	-	ADJ
cana-1616	13	23	stage	stage	ADJ
cana-1616	13	24	disease	disease	NOUN
cana-1616	13	25	classifications	classification	NOUN
cana-1616	13	26	respectively	respectively	ADV
cana-1616	13	27	.	.	PUNCT
cana-1616	14	1	keywords	keyword	NOUN
cana-1616	14	2	:	:	PUNCT
cana-1616	14	3	liver	liver	NOUN
cana-1616	14	4	disease	disease	NOUN
cana-1616	14	5	detection	detection	NOUN
cana-1616	14	6	,	,	PUNCT
cana-1616	14	7	learning	learning	NOUN
cana-1616	14	8	methods	method	NOUN
cana-1616	14	9	,	,	PUNCT
cana-1616	14	10	deep	deep	ADJ
cana-1616	14	11	learning	learning	NOUN
cana-1616	14	12	methods	method	NOUN
cana-1616	14	13	,	,	PUNCT
cana-1616	14	14	metaheuristic	metaheuristic	ADJ
cana-1616	14	15	approaches	approach	NOUN
cana-1616	14	16	,	,	PUNCT
cana-1616	14	17	optimization	optimization	NOUN
cana-1616	14	18	algorithms	algorithm	NOUN
cana-1616	14	19	,	,	PUNCT
cana-1616	14	20	medical	medical	ADJ
cana-1616	14	21	science	science	NOUN
cana-1616	14	22	.	.	PUNCT
cana-1616	15	1	1	1	X
cana-1616	15	2	.	.	X
cana-1616	15	3	introduction	introduction	NOUN
cana-1616	15	4	liver	liver	NOUN
cana-1616	15	5	is	be	AUX
cana-1616	15	6	considered	consider	VERB
cana-1616	15	7	as	as	ADP
cana-1616	15	8	the	the	DET
cana-1616	15	9	largest	large	ADJ
cana-1616	15	10	and	and	CCONJ
cana-1616	15	11	strongest	strong	ADJ
cana-1616	15	12	part	part	NOUN
cana-1616	15	13	of	of	ADP
cana-1616	15	14	human	human	ADJ
cana-1616	15	15	body	body	NOUN
cana-1616	15	16	that	that	PRON
cana-1616	15	17	plays	play	VERB
cana-1616	15	18	a	a	DET
cana-1616	15	19	crucial	crucial	ADJ
cana-1616	15	20	role	role	NOUN
cana-1616	15	21	in	in	ADP
cana-1616	15	22	maintenance	maintenance	NOUN
cana-1616	15	23	of	of	ADP
cana-1616	15	24	haemostasis	haemostasis	NOUN
cana-1616	15	25	and	and	CCONJ
cana-1616	15	26	coagulation	coagulation	NOUN
cana-1616	15	27	process	process	NOUN
cana-1616	15	28	[	[	X
cana-1616	15	29	1	1	NUM
cana-1616	15	30	]	]	PUNCT
cana-1616	15	31	.	.	PUNCT
cana-1616	16	1	it	it	PRON
cana-1616	16	2	is	be	AUX
cana-1616	16	3	surrounded	surround	VERB
cana-1616	16	4	by	by	ADP
cana-1616	16	5	the	the	DET
cana-1616	16	6	rib	rib	NOUN
cana-1616	16	7	cage	cage	NOUN
cana-1616	16	8	that	that	PRON
cana-1616	16	9	is	be	AUX
cana-1616	16	10	located	locate	VERB
cana-1616	16	11	in	in	ADP
cana-1616	16	12	the	the	DET
cana-1616	16	13	upper	upper	ADJ
cana-1616	16	14	right	right	ADJ
cana-1616	16	15	region	region	NOUN
cana-1616	16	16	of	of	ADP
cana-1616	16	17	the	the	DET
cana-1616	16	18	belly	belly	NOUN
cana-1616	16	19	.	.	PUNCT
cana-1616	17	1	beneath	beneath	ADP
cana-1616	17	2	this	this	DET
cana-1616	17	3	grand	grand	ADJ
cana-1616	17	4	organ	organ	NOUN
cana-1616	17	5	in	in	ADP
cana-1616	17	6	human	human	ADJ
cana-1616	17	7	body	body	NOUN
cana-1616	17	8	,	,	PUNCT
cana-1616	17	9	some	some	DET
cana-1616	17	10	other	other	ADJ
cana-1616	17	11	small	small	ADJ
cana-1616	17	12	organs	organ	NOUN
cana-1616	17	13	like	like	ADP
cana-1616	17	14	pancreas	pancrea	NOUN
cana-1616	17	15	,	,	PUNCT
cana-1616	17	16	intestines	intestine	NOUN
cana-1616	17	17	and	and	CCONJ
cana-1616	17	18	gallbladder	gallbladder	NOUN
cana-1616	17	19	are	be	AUX
cana-1616	17	20	located	locate	VERB
cana-1616	17	21	.	.	PUNCT
cana-1616	18	1	the	the	DET
cana-1616	18	2	liver	liver	NOUN
cana-1616	18	3	works	work	VERB
cana-1616	18	4	on	on	ADP
cana-1616	18	5	a	a	DET
cana-1616	18	6	variety	variety	NOUN
cana-1616	18	7	of	of	ADP
cana-1616	18	8	intricate	intricate	ADJ
cana-1616	18	9	body	body	NOUN
cana-1616	18	10	processes	process	NOUN
cana-1616	18	11	and	and	CCONJ
cana-1616	18	12	its	its	PRON
cana-1616	18	13	weight	weight	NOUN
cana-1616	18	14	is	be	AUX
cana-1616	18	15	around	around	ADV
cana-1616	18	16	3	3	NUM
cana-1616	18	17	pounds	pound	NOUN
cana-1616	18	18	.	.	PUNCT
cana-1616	19	1	the	the	DET
cana-1616	19	2	two	two	NUM
cana-1616	19	3	main	main	ADJ
cana-1616	19	4	structural	structural	ADJ
cana-1616	19	5	divisions	division	NOUN
cana-1616	19	6	of	of	ADP
cana-1616	19	7	the	the	DET
cana-1616	19	8	liver	liver	NOUN
cana-1616	19	9	are	be	AUX
cana-1616	19	10	right	right	ADV
cana-1616	19	11	lobe	lobe	NOUN
cana-1616	19	12	and	and	CCONJ
cana-1616	19	13	left	leave	VERB
cana-1616	19	14	lobe	lobe	VERB
cana-1616	19	15	.	.	PUNCT
cana-1616	20	1	liver	liver	NOUN
cana-1616	20	2	is	be	AUX
cana-1616	20	3	responsible	responsible	ADJ
cana-1616	20	4	for	for	ADP
cana-1616	20	5	collaborating	collaborate	VERB
cana-1616	20	6	with	with	ADP
cana-1616	20	7	other	other	ADJ
cana-1616	20	8	organs	organ	NOUN
cana-1616	20	9	to	to	PART
cana-1616	20	10	break	break	VERB
cana-1616	20	11	down	down	ADP
cana-1616	20	12	,	,	PUNCT
cana-1616	20	13	metabolize	metabolize	VERB
cana-1616	20	14	and	and	CCONJ
cana-1616	20	15	assimilate	assimilate	VERB
cana-1616	20	16	food	food	NOUN
cana-1616	20	17	.	.	PUNCT
cana-1616	21	1	additionally	additionally	ADV
cana-1616	21	2	,	,	PUNCT
cana-1616	21	3	the	the	DET
cana-1616	21	4	liver	liver	NOUN
cana-1616	21	5	produces	produce	VERB
cana-1616	21	6	protein	protein	NOUN
cana-1616	21	7	molecules	molecule	NOUN
cana-1616	21	8	which	which	PRON
cana-1616	21	9	are	be	AUX
cana-1616	21	10	necessary	necessary	ADJ
cana-1616	21	11	for	for	SCONJ
cana-1616	21	12	blood	blood	NOUN
cana-1616	21	13	communications	communication	NOUN
cana-1616	21	14	on	on	ADP
cana-1616	21	15	applied	apply	VERB
cana-1616	21	16	nonlinear	nonlinear	ADJ
cana-1616	21	17	analysis	analysis	NOUN
cana-1616	21	18	issn	issn	NOUN
cana-1616	21	19	:	:	PUNCT
cana-1616	21	20	1074	1074	NUM
cana-1616	21	21	-	-	PUNCT
cana-1616	21	22	133x	133x	NUM
cana-1616	21	23	vol	vol	NOUN
cana-1616	21	24	31	31	NUM
cana-1616	21	25	no	no	NOUN
cana-1616	21	26	.	.	PUNCT
cana-1616	22	1	8s	8s	PROPN
cana-1616	22	2	(	(	PUNCT
cana-1616	22	3	2024	2024	NUM
cana-1616	22	4	)	)	PUNCT
cana-1616	22	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	22	6	774	774	NUM
cana-1616	22	7	coagulation	coagulation	NOUN
cana-1616	22	8	and	and	CCONJ
cana-1616	22	9	various	various	ADJ
cana-1616	22	10	other	other	ADJ
cana-1616	22	11	processes	process	NOUN
cana-1616	22	12	[	[	X
cana-1616	22	13	2,3	2,3	NUM
cana-1616	22	14	]	]	PUNCT
cana-1616	22	15	.	.	PUNCT
cana-1616	23	1	the	the	DET
cana-1616	23	2	phrase	phrase	NOUN
cana-1616	23	3	"	"	PUNCT
cana-1616	23	4	liver	liver	NOUN
cana-1616	23	5	disease	disease	NOUN
cana-1616	23	6	"	"	PUNCT
cana-1616	23	7	is	be	AUX
cana-1616	23	8	broad	broad	ADJ
cana-1616	23	9	and	and	CCONJ
cana-1616	23	10	encompasses	encompass	VERB
cana-1616	23	11	any	any	DET
cana-1616	23	12	possible	possible	ADJ
cana-1616	23	13	issues	issue	NOUN
cana-1616	23	14	that	that	PRON
cana-1616	23	15	could	could	AUX
cana-1616	23	16	prevent	prevent	VERB
cana-1616	23	17	the	the	DET
cana-1616	23	18	liver	liver	NOUN
cana-1616	23	19	from	from	ADP
cana-1616	23	20	functioning	function	VERB
cana-1616	23	21	normally	normally	ADV
cana-1616	23	22	or	or	CCONJ
cana-1616	23	23	from	from	ADP
cana-1616	23	24	performing	perform	VERB
cana-1616	23	25	its	its	PRON
cana-1616	23	26	assigned	assign	VERB
cana-1616	23	27	tasks	task	NOUN
cana-1616	23	28	.	.	PUNCT
cana-1616	24	1	each	each	DET
cana-1616	24	2	symptom	symptom	NOUN
cana-1616	24	3	is	be	AUX
cana-1616	24	4	dependent	dependent	ADJ
cana-1616	24	5	on	on	ADP
cana-1616	24	6	the	the	DET
cana-1616	24	7	type	type	NOUN
cana-1616	24	8	and	and	CCONJ
cana-1616	24	9	severity	severity	NOUN
cana-1616	24	10	of	of	ADP
cana-1616	24	11	the	the	DET
cana-1616	24	12	ailment	ailment	NOUN
cana-1616	24	13	.	.	PUNCT
cana-1616	25	1	figure	figure	NOUN
cana-1616	25	2	1	1	NUM
cana-1616	25	3	shows	show	VERB
cana-1616	25	4	the	the	DET
cana-1616	25	5	pictorial	pictorial	ADJ
cana-1616	25	6	form	form	NOUN
cana-1616	25	7	of	of	ADP
cana-1616	25	8	normal	normal	ADJ
cana-1616	25	9	and	and	CCONJ
cana-1616	25	10	infected	infected	ADJ
cana-1616	25	11	liver	liver	NOUN
cana-1616	25	12	.	.	PUNCT
cana-1616	26	1	figure	figure	NOUN
cana-1616	26	2	1	1	NUM
cana-1616	26	3	.	.	NOUN
cana-1616	26	4	normal	normal	ADJ
cana-1616	26	5	and	and	CCONJ
cana-1616	26	6	infected	infected	ADJ
cana-1616	26	7	liver	liver	NOUN
cana-1616	27	1	[	[	X
cana-1616	27	2	4	4	NUM
cana-1616	27	3	]	]	PUNCT
cana-1616	27	4	one	one	NUM
cana-1616	27	5	of	of	ADP
cana-1616	27	6	the	the	DET
cana-1616	27	7	most	most	ADV
cana-1616	27	8	prevalent	prevalent	ADJ
cana-1616	27	9	types	type	NOUN
cana-1616	27	10	of	of	ADP
cana-1616	27	11	liver	liver	NOUN
cana-1616	27	12	disease	disease	NOUN
cana-1616	27	13	that	that	PRON
cana-1616	27	14	has	have	AUX
cana-1616	27	15	been	be	AUX
cana-1616	27	16	seen	see	VERB
cana-1616	27	17	around	around	ADP
cana-1616	27	18	the	the	DET
cana-1616	27	19	globe	globe	NOUN
cana-1616	27	20	consistently	consistently	ADV
cana-1616	27	21	is	be	AUX
cana-1616	27	22	fatty	fatty	ADJ
cana-1616	27	23	liver	liver	NOUN
cana-1616	27	24	disease	disease	NOUN
cana-1616	27	25	or	or	CCONJ
cana-1616	27	26	fld	fld	NOUN
cana-1616	27	27	.	.	PUNCT
cana-1616	28	1	this	this	DET
cana-1616	28	2	fld	fld	PROPN
cana-1616	28	3	is	be	AUX
cana-1616	28	4	sometimes	sometimes	ADV
cana-1616	28	5	also	also	ADV
cana-1616	28	6	known	know	VERB
cana-1616	28	7	as	as	ADP
cana-1616	28	8	fatty	fatty	NOUN
cana-1616	28	9	liver	liver	NOUN
cana-1616	28	10	steatosis	steatosis	NOUN
cana-1616	28	11	and	and	CCONJ
cana-1616	28	12	is	be	AUX
cana-1616	28	13	very	very	ADV
cana-1616	28	14	difficult	difficult	ADJ
cana-1616	28	15	to	to	PART
cana-1616	28	16	diagnose	diagnose	VERB
cana-1616	28	17	[	[	X
cana-1616	28	18	5	5	NUM
cana-1616	28	19	]	]	PUNCT
cana-1616	28	20	.	.	PUNCT
cana-1616	29	1	it	it	PRON
cana-1616	29	2	is	be	AUX
cana-1616	29	3	important	important	ADJ
cana-1616	29	4	to	to	PART
cana-1616	29	5	detect	detect	VERB
cana-1616	29	6	fld	fld	NUM
cana-1616	29	7	disease	disease	NOUN
cana-1616	29	8	in	in	ADP
cana-1616	29	9	earliest	early	ADJ
cana-1616	29	10	possible	possible	ADJ
cana-1616	29	11	stages	stage	NOUN
cana-1616	29	12	because	because	SCONJ
cana-1616	29	13	if	if	SCONJ
cana-1616	29	14	its	its	PRON
cana-1616	29	15	not	not	PART
cana-1616	29	16	identified	identify	VERB
cana-1616	29	17	timely	timely	ADV
cana-1616	29	18	it	it	PRON
cana-1616	29	19	may	may	AUX
cana-1616	29	20	lead	lead	VERB
cana-1616	29	21	to	to	ADP
cana-1616	29	22	cirrhosis	cirrhosis	NOUN
cana-1616	29	23	,	,	PUNCT
cana-1616	29	24	cancers	cancer	NOUN
cana-1616	29	25	,	,	PUNCT
cana-1616	29	26	steatohepatitis	steatohepatitis	PROPN
cana-1616	29	27	.	.	PUNCT
cana-1616	30	1	other	other	ADJ
cana-1616	30	2	than	than	ADP
cana-1616	30	3	this	this	PRON
cana-1616	30	4	,	,	PUNCT
cana-1616	30	5	it	it	PRON
cana-1616	30	6	may	may	AUX
cana-1616	30	7	also	also	ADV
cana-1616	30	8	case	case	VERB
cana-1616	30	9	liver	liver	NOUN
cana-1616	30	10	damage	damage	NOUN
cana-1616	30	11	and	and	CCONJ
cana-1616	30	12	result	result	NOUN
cana-1616	30	13	in	in	ADP
cana-1616	30	14	acute	acute	ADJ
cana-1616	30	15	failures	failure	NOUN
cana-1616	30	16	in	in	ADP
cana-1616	30	17	liver	liver	NOUN
cana-1616	30	18	hence	hence	ADV
cana-1616	30	19	,	,	PUNCT
cana-1616	30	20	early	early	ADJ
cana-1616	30	21	diagnosis	diagnosis	NOUN
cana-1616	30	22	and	and	CCONJ
cana-1616	30	23	therapy	therapy	NOUN
cana-1616	30	24	are	be	AUX
cana-1616	30	25	therefore	therefore	ADV
cana-1616	30	26	crucial	crucial	ADJ
cana-1616	30	27	for	for	ADP
cana-1616	30	28	the	the	DET
cana-1616	30	29	management	management	NOUN
cana-1616	30	30	of	of	ADP
cana-1616	30	31	fld	fld	PROPN
cana-1616	30	32	.	.	PUNCT
cana-1616	31	1	however	however	ADV
cana-1616	31	2	,	,	PUNCT
cana-1616	31	3	the	the	DET
cana-1616	31	4	complexity	complexity	NOUN
cana-1616	31	5	of	of	ADP
cana-1616	31	6	the	the	DET
cana-1616	31	7	liver	liver	NOUN
cana-1616	31	8	disease	disease	NOUN
cana-1616	31	9	detection	detection	NOUN
cana-1616	31	10	arises	arise	VERB
cana-1616	31	11	with	with	ADP
cana-1616	31	12	the	the	DET
cana-1616	31	13	rise	rise	NOUN
cana-1616	31	14	in	in	ADP
cana-1616	31	15	covid-19	covid-19	PROPN
cana-1616	31	16	pandemic	pandemic	NOUN
cana-1616	31	17	.	.	PUNCT
cana-1616	32	1	moreover	moreover	ADV
cana-1616	32	2	,	,	PUNCT
cana-1616	32	3	because	because	SCONJ
cana-1616	32	4	of	of	ADP
cana-1616	32	5	this	this	DET
cana-1616	32	6	pandemic	pandemic	ADJ
cana-1616	32	7	the	the	DET
cana-1616	32	8	sensitivity	sensitivity	NOUN
cana-1616	32	9	and	and	CCONJ
cana-1616	32	10	fragility	fragility	NOUN
cana-1616	32	11	corresponding	correspond	VERB
cana-1616	32	12	to	to	ADP
cana-1616	32	13	liver	liver	NOUN
cana-1616	32	14	disease	disease	NOUN
cana-1616	32	15	also	also	ADV
cana-1616	32	16	increases	increase	VERB
cana-1616	32	17	among	among	ADP
cana-1616	32	18	patients	patient	NOUN
cana-1616	32	19	[	[	X
cana-1616	32	20	7,8	7,8	NUM
cana-1616	32	21	]	]	PUNCT
cana-1616	32	22	.	.	PUNCT
cana-1616	33	1	2	2	X
cana-1616	33	2	.	.	X
cana-1616	33	3	literature	literature	NOUN
cana-1616	33	4	review	review	PROPN
cana-1616	33	5	liver	liver	NOUN
cana-1616	33	6	diseases	disease	NOUN
cana-1616	33	7	encompass	encompass	VERB
cana-1616	33	8	a	a	DET
cana-1616	33	9	spectrum	spectrum	NOUN
cana-1616	33	10	of	of	ADP
cana-1616	33	11	medical	medical	ADJ
cana-1616	33	12	conditions	condition	NOUN
cana-1616	33	13	affecting	affect	VERB
cana-1616	33	14	the	the	DET
cana-1616	33	15	liver	liver	NOUN
cana-1616	33	16	's	's	PART
cana-1616	33	17	structure	structure	NOUN
cana-1616	33	18	and	and	CCONJ
cana-1616	33	19	function	function	NOUN
cana-1616	33	20	.	.	PUNCT
cana-1616	34	1	ranging	range	VERB
cana-1616	34	2	from	from	ADP
cana-1616	34	3	viral	viral	ADJ
cana-1616	34	4	hepatitis	hepatitis	NOUN
cana-1616	34	5	and	and	CCONJ
cana-1616	34	6	fatty	fatty	ADJ
cana-1616	34	7	liver	liver	NOUN
cana-1616	34	8	disease	disease	NOUN
cana-1616	34	9	to	to	ADP
cana-1616	34	10	cirrhosis	cirrhosis	NOUN
cana-1616	34	11	and	and	CCONJ
cana-1616	34	12	hepatocellular	hepatocellular	ADJ
cana-1616	34	13	carcinoma	carcinoma	NOUN
cana-1616	34	14	,	,	PUNCT
cana-1616	34	15	these	these	DET
cana-1616	34	16	conditions	condition	NOUN
cana-1616	34	17	can	can	AUX
cana-1616	34	18	lead	lead	VERB
cana-1616	34	19	to	to	ADP
cana-1616	34	20	serious	serious	ADJ
cana-1616	34	21	health	health	NOUN
cana-1616	34	22	complications	complication	NOUN
cana-1616	34	23	if	if	SCONJ
cana-1616	34	24	not	not	PART
cana-1616	34	25	diagnosed	diagnose	VERB
cana-1616	34	26	and	and	CCONJ
cana-1616	34	27	managed	manage	VERB
cana-1616	34	28	promptly	promptly	ADV
cana-1616	34	29	.	.	PUNCT
cana-1616	35	1	leveraging	leverage	VERB
cana-1616	35	2	ai	ai	PROPN
cana-1616	35	3	's	's	PART
cana-1616	35	4	ability	ability	NOUN
cana-1616	35	5	to	to	PART
cana-1616	35	6	analyse	analyse	VERB
cana-1616	35	7	vast	vast	ADJ
cana-1616	35	8	datasets	dataset	NOUN
cana-1616	35	9	and	and	CCONJ
cana-1616	35	10	recognize	recognize	VERB
cana-1616	35	11	complex	complex	ADJ
cana-1616	35	12	patterns	pattern	NOUN
cana-1616	35	13	,	,	PUNCT
cana-1616	35	14	researchers	researcher	NOUN
cana-1616	35	15	have	have	AUX
cana-1616	35	16	developed	develop	VERB
cana-1616	35	17	predictive	predictive	ADJ
cana-1616	35	18	models	model	NOUN
cana-1616	35	19	that	that	PRON
cana-1616	35	20	aid	aid	VERB
cana-1616	35	21	in	in	ADP
cana-1616	35	22	identifying	identify	VERB
cana-1616	35	23	individuals	individual	NOUN
cana-1616	35	24	at	at	ADP
cana-1616	35	25	risk	risk	NOUN
cana-1616	35	26	or	or	CCONJ
cana-1616	35	27	in	in	ADP
cana-1616	35	28	early	early	ADJ
cana-1616	35	29	stages	stage	NOUN
cana-1616	35	30	of	of	ADP
cana-1616	35	31	liver	liver	NOUN
cana-1616	35	32	disease	disease	NOUN
cana-1616	35	33	.	.	PUNCT
cana-1616	36	1	by	by	ADP
cana-1616	36	2	accessing	access	VERB
cana-1616	36	3	prominent	prominent	ADJ
cana-1616	36	4	academic	academic	ADJ
cana-1616	36	5	platforms	platform	NOUN
cana-1616	36	6	such	such	ADJ
cana-1616	36	7	as	as	ADP
cana-1616	36	8	ieee	ieee	NOUN
cana-1616	36	9	,	,	PUNCT
cana-1616	36	10	springer	springer	NOUN
cana-1616	36	11	,	,	PUNCT
cana-1616	36	12	and	and	CCONJ
cana-1616	36	13	elsevier	elsevier	NOUN
cana-1616	36	14	,	,	PUNCT
cana-1616	36	15	this	this	DET
cana-1616	36	16	review	review	NOUN
cana-1616	36	17	seeks	seek	VERB
cana-1616	36	18	to	to	PART
cana-1616	36	19	explore	explore	VERB
cana-1616	36	20	the	the	DET
cana-1616	36	21	current	current	ADJ
cana-1616	36	22	landscape	landscape	NOUN
cana-1616	36	23	of	of	ADP
cana-1616	36	24	ai	ai	NOUN
cana-1616	36	25	-	-	PUNCT
cana-1616	36	26	based	base	VERB
cana-1616	36	27	models	model	NOUN
cana-1616	36	28	for	for	ADP
cana-1616	36	29	predicting	predict	VERB
cana-1616	36	30	liver	liver	NOUN
cana-1616	36	31	diseases	disease	NOUN
cana-1616	36	32	.	.	PUNCT
cana-1616	37	1	through	through	ADP
cana-1616	37	2	targeted	target	VERB
cana-1616	37	3	keyword	keyword	NOUN
cana-1616	37	4	searches	search	NOUN
cana-1616	37	5	and	and	CCONJ
cana-1616	37	6	careful	careful	ADJ
cana-1616	37	7	analysis	analysis	NOUN
cana-1616	37	8	of	of	ADP
cana-1616	37	9	published	publish	VERB
cana-1616	37	10	research	research	NOUN
cana-1616	37	11	,	,	PUNCT
cana-1616	37	12	we	we	PRON
cana-1616	37	13	aim	aim	VERB
cana-1616	37	14	to	to	PART
cana-1616	37	15	gain	gain	VERB
cana-1616	37	16	insights	insight	NOUN
cana-1616	37	17	into	into	ADP
cana-1616	37	18	the	the	DET
cana-1616	37	19	state	state	NOUN
cana-1616	37	20	-	-	PUNCT
cana-1616	37	21	ofthe	ofthe	NOUN
cana-1616	37	22	-	-	PUNCT
cana-1616	37	23	art	art	NOUN
cana-1616	37	24	methodologies	methodology	NOUN
cana-1616	37	25	,	,	PUNCT
cana-1616	37	26	challenges	challenge	NOUN
cana-1616	37	27	,	,	PUNCT
cana-1616	37	28	and	and	CCONJ
cana-1616	37	29	potential	potential	ADJ
cana-1616	37	30	directions	direction	NOUN
cana-1616	37	31	in	in	ADP
cana-1616	37	32	this	this	DET
cana-1616	37	33	evolving	evolve	VERB
cana-1616	37	34	field	field	NOUN
cana-1616	37	35	.	.	PUNCT
cana-1616	38	1	the	the	DET
cana-1616	38	2	results	result	NOUN
cana-1616	38	3	were	be	AUX
cana-1616	38	4	further	far	ADV
cana-1616	38	5	enhanced	enhance	VERB
cana-1616	38	6	by	by	ADP
cana-1616	38	7	authors	author	NOUN
cana-1616	38	8	in	in	ADP
cana-1616	38	9	[	[	X
cana-1616	38	10	19	19	NUM
cana-1616	38	11	]	]	PUNCT
cana-1616	38	12	which	which	PRON
cana-1616	38	13	developed	develop	VERB
cana-1616	38	14	a	a	DET
cana-1616	38	15	ml	ml	NOUN
cana-1616	38	16	technique	technique	NOUN
cana-1616	38	17	that	that	PRON
cana-1616	38	18	was	be	AUX
cana-1616	38	19	based	base	VERB
cana-1616	38	20	on	on	ADP
cana-1616	38	21	rf	rf	NOUN
cana-1616	38	22	classifiers	classifier	NOUN
cana-1616	38	23	for	for	ADP
cana-1616	38	24	predicting	predict	VERB
cana-1616	38	25	disease	disease	NOUN
cana-1616	38	26	.	.	PUNCT
cana-1616	39	1	also	also	ADV
cana-1616	39	2	,	,	PUNCT
cana-1616	39	3	they	they	PRON
cana-1616	39	4	implemented	implement	VERB
cana-1616	39	5	univariate	univariate	ADJ
cana-1616	39	6	and	and	CCONJ
cana-1616	39	7	bivariate	bivariate	ADJ
cana-1616	39	8	analysis	analysis	NOUN
cana-1616	39	9	for	for	ADP
cana-1616	39	10	checking	check	VERB
cana-1616	39	11	the	the	DET
cana-1616	39	12	skewness	skewness	NOUN
cana-1616	39	13	and	and	CCONJ
cana-1616	39	14	outliers	outlier	NOUN
cana-1616	39	15	of	of	ADP
cana-1616	39	16	data	datum	NOUN
cana-1616	39	17	.	.	PUNCT
cana-1616	40	1	for	for	ADP
cana-1616	40	2	further	far	ADV
cana-1616	40	3	balancing	balance	VERB
cana-1616	40	4	the	the	DET
cana-1616	40	5	data	datum	NOUN
cana-1616	40	6	,	,	PUNCT
cana-1616	40	7	different	different	ADJ
cana-1616	40	8	oversampling	oversampling	NOUN
cana-1616	40	9	and	and	CCONJ
cana-1616	40	10	under	under	ADP
cana-1616	40	11	sampling	sample	VERB
cana-1616	40	12	techniques	technique	NOUN
cana-1616	40	13	are	be	AUX
cana-1616	40	14	implemented	implement	VERB
cana-1616	40	15	.	.	PUNCT
cana-1616	41	1	also	also	ADV
cana-1616	41	2	,	,	PUNCT
cana-1616	41	3	the	the	DET
cana-1616	41	4	performance	performance	NOUN
cana-1616	41	5	of	of	ADP
cana-1616	41	6	proposed	propose	VERB
cana-1616	41	7	approach	approach	NOUN
cana-1616	41	8	was	be	AUX
cana-1616	41	9	developed	develop	VERB
cana-1616	41	10	by	by	ADP
cana-1616	41	11	optimizing	optimize	VERB
cana-1616	41	12	the	the	DET
cana-1616	41	13	hyper	hyper	ADJ
cana-1616	41	14	parameters	parameter	NOUN
cana-1616	41	15	by	by	ADP
cana-1616	41	16	utilizing	utilize	VERB
cana-1616	41	17	grid	grid	NOUN
cana-1616	41	18	search	search	NOUN
cana-1616	41	19	and	and	CCONJ
cana-1616	41	20	fs	fs	ADP
cana-1616	41	21	which	which	PRON
cana-1616	41	22	achieves	achieve	VERB
cana-1616	41	23	an	an	DET
cana-1616	41	24	accuracy	accuracy	NOUN
cana-1616	41	25	of	of	ADP
cana-1616	41	26	100	100	NUM
cana-1616	41	27	%	%	NOUN
cana-1616	41	28	.	.	PUNCT
cana-1616	42	1	again	again	ADV
cana-1616	42	2	in	in	ADP
cana-1616	42	3	[	[	X
cana-1616	42	4	20	20	NUM
cana-1616	42	5	]	]	PUNCT
cana-1616	42	6	,	,	PUNCT
cana-1616	42	7	a	a	DET
cana-1616	42	8	hybrid	hybrid	ADJ
cana-1616	42	9	soft	soft	ADJ
cana-1616	42	10	computing	computing	NOUN
cana-1616	42	11	technique	technique	NOUN
cana-1616	42	12	is	be	AUX
cana-1616	42	13	proposed	propose	VERB
cana-1616	42	14	for	for	ADP
cana-1616	42	15	detecting	detect	VERB
cana-1616	42	16	liver	liver	NOUN
cana-1616	42	17	disease	disease	NOUN
cana-1616	42	18	at	at	ADP
cana-1616	42	19	earliest	early	ADJ
cana-1616	42	20	stages	stage	NOUN
cana-1616	42	21	.	.	PUNCT
cana-1616	43	1	they	they	PRON
cana-1616	43	2	used	use	VERB
cana-1616	43	3	modified	modified	ADJ
cana-1616	43	4	wso	wso	NOUN
cana-1616	43	5	approach	approach	NOUN
cana-1616	43	6	for	for	ADP
cana-1616	43	7	selecting	select	VERB
cana-1616	43	8	the	the	DET
cana-1616	43	9	important	important	ADJ
cana-1616	43	10	features	feature	NOUN
cana-1616	43	11	from	from	ADP
cana-1616	43	12	available	available	ADJ
cana-1616	43	13	feature	feature	NOUN
cana-1616	43	14	set	set	VERB
cana-1616	43	15	.	.	PUNCT
cana-1616	44	1	for	for	ADP
cana-1616	44	2	determining	determine	VERB
cana-1616	44	3	the	the	DET
cana-1616	44	4	stage	stage	NOUN
cana-1616	44	5	of	of	ADP
cana-1616	44	6	liver	liver	NOUN
cana-1616	44	7	disease	disease	NOUN
cana-1616	44	8	in	in	ADP
cana-1616	44	9	patients	patient	NOUN
cana-1616	44	10	they	they	PRON
cana-1616	44	11	implemented	implement	VERB
cana-1616	44	12	hssicommunications	hssicommunication	NOUN
cana-1616	44	13	on	on	ADP
cana-1616	44	14	applied	apply	VERB
cana-1616	44	15	nonlinear	nonlinear	ADJ
cana-1616	44	16	analysis	analysis	NOUN
cana-1616	44	17	issn	issn	NOUN
cana-1616	44	18	:	:	PUNCT
cana-1616	44	19	1074	1074	NUM
cana-1616	44	20	-	-	PUNCT
cana-1616	44	21	133x	133x	NUM
cana-1616	44	22	vol	vol	NOUN
cana-1616	44	23	31	31	NUM
cana-1616	44	24	no	no	NOUN
cana-1616	44	25	.	.	PUNCT
cana-1616	45	1	8s	8s	PROPN
cana-1616	45	2	(	(	PUNCT
cana-1616	45	3	2024	2024	NUM
cana-1616	45	4	)	)	PUNCT
cana-1616	45	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	45	6	775	775	NUM
cana-1616	45	7	dnn	dnn	PROPN
cana-1616	45	8	model	model	NOUN
cana-1616	45	9	that	that	PRON
cana-1616	45	10	was	be	AUX
cana-1616	45	11	tested	test	VERB
cana-1616	45	12	on	on	ADP
cana-1616	45	13	three	three	NUM
cana-1616	45	14	datasets	dataset	NOUN
cana-1616	45	15	i.e.	i.e.	X
cana-1616	45	16	,	,	PUNCT
cana-1616	45	17	bupa	bupa	NOUN
cana-1616	45	18	,	,	PUNCT
cana-1616	45	19	ilpd	ilpd	NOUN
cana-1616	45	20	and	and	CCONJ
cana-1616	45	21	mrrlpd	mrrlpd	NOUN
cana-1616	45	22	.	.	PUNCT
cana-1616	46	1	results	result	NOUN
cana-1616	46	2	showcased	showcase	VERB
cana-1616	46	3	that	that	SCONJ
cana-1616	46	4	proposed	propose	VERB
cana-1616	46	5	model	model	NOUN
cana-1616	46	6	achieves	achieve	VERB
cana-1616	46	7	an	an	DET
cana-1616	46	8	accuracy	accuracy	NOUN
cana-1616	46	9	of	of	ADP
cana-1616	46	10	83	83	NUM
cana-1616	46	11	%	%	NOUN
cana-1616	46	12	on	on	ADP
cana-1616	46	13	bupa	bupa	PROPN
cana-1616	46	14	,	,	PUNCT
cana-1616	46	15	84	84	NUM
cana-1616	46	16	%	%	NOUN
cana-1616	46	17	on	on	ADP
cana-1616	46	18	ilpd	ilpd	NOUN
cana-1616	46	19	and	and	CCONJ
cana-1616	46	20	91	91	NUM
cana-1616	46	21	%	%	NOUN
cana-1616	46	22	on	on	ADP
cana-1616	46	23	mprlpd	mprlpd	NOUN
cana-1616	46	24	databases	database	NOUN
cana-1616	46	25	.	.	PUNCT
cana-1616	47	1	also	also	ADV
cana-1616	47	2	,	,	PUNCT
cana-1616	47	3	the	the	DET
cana-1616	47	4	authors	author	NOUN
cana-1616	47	5	in	in	ADP
cana-1616	47	6	[	[	X
cana-1616	47	7	21	21	NUM
cana-1616	47	8	]	]	PUNCT
cana-1616	47	9	,	,	PUNCT
cana-1616	47	10	utilized	utilize	VERB
cana-1616	47	11	5	5	NUM
cana-1616	47	12	ml	ml	NOUN
cana-1616	47	13	classifiers	classifier	NOUN
cana-1616	47	14	(	(	PUNCT
cana-1616	47	15	svm	svm	PROPN
cana-1616	47	16	,	,	PUNCT
cana-1616	47	17	nb	nb	PROPN
cana-1616	47	18	.	.	PUNCT
cana-1616	47	19	knn	knn	PROPN
cana-1616	47	20	,	,	PUNCT
cana-1616	47	21	lda	lda	PROPN
cana-1616	47	22	and	and	CCONJ
cana-1616	47	23	cart	cart	NOUN
cana-1616	47	24	)	)	PUNCT
cana-1616	47	25	for	for	ADP
cana-1616	47	26	predicting	predict	VERB
cana-1616	47	27	liver	liver	NOUN
cana-1616	47	28	diseases	disease	NOUN
cana-1616	47	29	.	.	PUNCT
cana-1616	48	1	through	through	ADP
cana-1616	48	2	extensive	extensive	ADJ
cana-1616	48	3	experimentation	experimentation	NOUN
cana-1616	48	4	,	,	PUNCT
cana-1616	48	5	it	it	PRON
cana-1616	48	6	was	be	AUX
cana-1616	48	7	observed	observe	VERB
cana-1616	48	8	that	that	SCONJ
cana-1616	48	9	knn	knn	PROPN
cana-1616	48	10	attains	attain	VERB
cana-1616	48	11	highest	high	ADJ
cana-1616	48	12	accuracy	accuracy	NOUN
cana-1616	48	13	of	of	ADP
cana-1616	48	14	91.7	91.7	NUM
cana-1616	48	15	%	%	NOUN
cana-1616	48	16	while	while	SCONJ
cana-1616	48	17	as	as	SCONJ
cana-1616	48	18	,	,	PUNCT
cana-1616	48	19	it	it	PRON
cana-1616	48	20	was	be	AUX
cana-1616	48	21	92.1	92.1	NUM
cana-1616	48	22	%	%	NOUN
cana-1616	48	23	for	for	ADP
cana-1616	48	24	auto	auto	NOUN
cana-1616	48	25	encoder	encoder	NOUN
cana-1616	48	26	model	model	NOUN
cana-1616	48	27	.	.	PUNCT
cana-1616	49	1	3	3	X
cana-1616	49	2	.	.	X
cana-1616	49	3	materials	material	NOUN
cana-1616	49	4	and	and	CCONJ
cana-1616	49	5	methods	method	NOUN
cana-1616	49	6	here	here	ADV
cana-1616	49	7	,	,	PUNCT
cana-1616	49	8	a	a	DET
cana-1616	49	9	novel	novel	ADJ
cana-1616	49	10	feature	feature	NOUN
cana-1616	49	11	selection	selection	NOUN
cana-1616	49	12	technique	technique	NOUN
cana-1616	49	13	is	be	AUX
cana-1616	49	14	proposed	propose	VERB
cana-1616	49	15	for	for	ADP
cana-1616	49	16	selecting	select	VERB
cana-1616	49	17	only	only	ADV
cana-1616	49	18	highly	highly	ADV
cana-1616	49	19	informative	informative	ADJ
cana-1616	49	20	and	and	CCONJ
cana-1616	49	21	critical	critical	ADJ
cana-1616	49	22	features	feature	NOUN
cana-1616	49	23	that	that	PRON
cana-1616	49	24	aid	aid	NOUN
cana-1616	49	25	in	in	ADP
cana-1616	49	26	improving	improve	VERB
cana-1616	49	27	overall	overall	ADJ
cana-1616	49	28	detection	detection	NOUN
cana-1616	49	29	accuracy	accuracy	NOUN
cana-1616	49	30	of	of	ADP
cana-1616	49	31	the	the	DET
cana-1616	49	32	system	system	NOUN
cana-1616	49	33	.	.	PUNCT
cana-1616	50	1	this	this	DET
cana-1616	50	2	technique	technique	NOUN
cana-1616	50	3	helps	help	VERB
cana-1616	50	4	to	to	PART
cana-1616	50	5	overcome	overcome	VERB
cana-1616	50	6	complexity	complexity	NOUN
cana-1616	50	7	and	and	CCONJ
cana-1616	50	8	overfitting	overfitte	VERB
cana-1616	50	9	issues	issue	NOUN
cana-1616	50	10	in	in	ADP
cana-1616	50	11	current	current	ADJ
cana-1616	50	12	databases	database	NOUN
cana-1616	50	13	that	that	PRON
cana-1616	50	14	may	may	AUX
cana-1616	50	15	contain	contain	VERB
cana-1616	50	16	redundant	redundant	ADJ
cana-1616	50	17	or	or	CCONJ
cana-1616	50	18	irrelevant	irrelevant	ADJ
cana-1616	50	19	features	feature	NOUN
cana-1616	50	20	which	which	PRON
cana-1616	50	21	has	have	VERB
cana-1616	50	22	no	no	DET
cana-1616	50	23	role	role	NOUN
cana-1616	50	24	in	in	ADP
cana-1616	50	25	disease	disease	NOUN
cana-1616	50	26	detection	detection	NOUN
cana-1616	50	27	.	.	PUNCT
cana-1616	51	1	all	all	DET
cana-1616	51	2	these	these	DET
cana-1616	51	3	techniques	technique	NOUN
cana-1616	51	4	(	(	PUNCT
cana-1616	51	5	pre	pre	ADJ
cana-1616	51	6	-	-	ADJ
cana-1616	51	7	processing	processing	ADJ
cana-1616	51	8	,	,	PUNCT
cana-1616	51	9	fs	fs	ADP
cana-1616	51	10	and	and	CCONJ
cana-1616	51	11	classification	classification	NOUN
cana-1616	51	12	)	)	PUNCT
cana-1616	51	13	are	be	AUX
cana-1616	51	14	implemented	implement	VERB
cana-1616	51	15	on	on	ADP
cana-1616	51	16	ilpd	ilpd	NOUN
cana-1616	51	17	(	(	PUNCT
cana-1616	51	18	indian	indian	ADJ
cana-1616	51	19	liver	liver	NOUN
cana-1616	51	20	patient	patient	NOUN
cana-1616	51	21	dataset	dataset	NOUN
cana-1616	51	22	)	)	PUNCT
cana-1616	51	23	and	and	CCONJ
cana-1616	51	24	cpd	cpd	NOUN
cana-1616	51	25	(	(	PUNCT
cana-1616	51	26	cirrhosis	cirrhosis	NOUN
cana-1616	51	27	prediction	prediction	NOUN
cana-1616	51	28	dataset	dataset	NOUN
cana-1616	51	29	)	)	PUNCT
cana-1616	51	30	,	,	PUNCT
cana-1616	51	31	whose	whose	DET
cana-1616	51	32	detailed	detailed	ADJ
cana-1616	51	33	information	information	NOUN
cana-1616	51	34	is	be	AUX
cana-1616	51	35	given	give	VERB
cana-1616	51	36	in	in	ADP
cana-1616	51	37	subsequent	subsequent	ADJ
cana-1616	51	38	sections	section	NOUN
cana-1616	51	39	of	of	ADP
cana-1616	51	40	this	this	DET
cana-1616	51	41	paper	paper	NOUN
cana-1616	51	42	.	.	PUNCT
cana-1616	52	1	it	it	PRON
cana-1616	52	2	is	be	AUX
cana-1616	52	3	pertinent	pertinent	ADJ
cana-1616	52	4	to	to	PART
cana-1616	52	5	mention	mention	VERB
cana-1616	52	6	here	here	ADV
cana-1616	52	7	that	that	SCONJ
cana-1616	52	8	two	two	NUM
cana-1616	52	9	datasets	dataset	NOUN
cana-1616	52	10	i.e.	i.e.	X
cana-1616	52	11	,	,	PUNCT
cana-1616	52	12	ilpd	ilpd	NOUN
cana-1616	52	13	and	and	CCONJ
cana-1616	52	14	cpd	cpd	NOUN
cana-1616	52	15	are	be	AUX
cana-1616	52	16	used	use	VERB
cana-1616	52	17	to	to	PART
cana-1616	52	18	perform	perform	VERB
cana-1616	52	19	binary	binary	ADJ
cana-1616	52	20	and	and	CCONJ
cana-1616	52	21	multistage	multistage	NOUN
cana-1616	52	22	disease	disease	NOUN
cana-1616	52	23	classifications	classification	NOUN
cana-1616	52	24	respectively	respectively	ADV
cana-1616	52	25	.	.	PUNCT
cana-1616	53	1	figure	figure	NOUN
cana-1616	53	2	2	2	NUM
cana-1616	53	3	demonstrates	demonstrate	VERB
cana-1616	53	4	the	the	DET
cana-1616	53	5	architecture	architecture	NOUN
cana-1616	53	6	of	of	ADP
cana-1616	53	7	proposed	propose	VERB
cana-1616	53	8	liver	liver	NOUN
cana-1616	53	9	disease	disease	NOUN
cana-1616	53	10	detection	detection	NOUN
cana-1616	53	11	model	model	NOUN
cana-1616	53	12	.	.	PUNCT
cana-1616	54	1	figure	figure	NOUN
cana-1616	54	2	2	2	NUM
cana-1616	54	3	.	.	PUNCT
cana-1616	54	4	proposed	propose	VERB
cana-1616	54	5	architecture	architecture	NOUN
cana-1616	54	6	for	for	ADP
cana-1616	54	7	liver	liver	NOUN
cana-1616	54	8	disease	disease	NOUN
cana-1616	54	9	detection	detection	NOUN
cana-1616	54	10	3.1	3.1	NUM
cana-1616	54	11	dataset	dataset	NOUN
cana-1616	54	12	and	and	CCONJ
cana-1616	54	13	its	its	PRON
cana-1616	54	14	preparation	preparation	NOUN
cana-1616	54	15	in	in	ADP
cana-1616	54	16	our	our	PRON
cana-1616	54	17	work	work	NOUN
cana-1616	54	18	,	,	PUNCT
cana-1616	54	19	we	we	PRON
cana-1616	54	20	have	have	AUX
cana-1616	54	21	considered	consider	VERB
cana-1616	54	22	two	two	NUM
cana-1616	54	23	datasets	dataset	NOUN
cana-1616	54	24	i.e.	i.e.	X
cana-1616	54	25	,	,	PUNCT
cana-1616	54	26	ilpd	ilpd	NOUN
cana-1616	54	27	and	and	CCONJ
cana-1616	54	28	cpd	cpd	NOUN
cana-1616	54	29	for	for	ADP
cana-1616	54	30	detecting	detect	VERB
cana-1616	54	31	liver	liver	NOUN
cana-1616	54	32	disease	disease	NOUN
cana-1616	54	33	and	and	CCONJ
cana-1616	54	34	determine	determine	VERB
cana-1616	54	35	its	its	PRON
cana-1616	54	36	stages	stage	NOUN
cana-1616	54	37	respectively	respectively	ADV
cana-1616	54	38	.	.	PUNCT
cana-1616	55	1	the	the	DET
cana-1616	55	2	brief	brief	ADJ
cana-1616	55	3	description	description	NOUN
cana-1616	55	4	of	of	ADP
cana-1616	55	5	these	these	DET
cana-1616	55	6	two	two	NUM
cana-1616	55	7	datasets	dataset	NOUN
cana-1616	55	8	is	be	AUX
cana-1616	55	9	given	give	VERB
cana-1616	55	10	below	below	ADV
cana-1616	55	11	along	along	ADP
cana-1616	55	12	with	with	ADP
cana-1616	55	13	their	their	PRON
cana-1616	55	14	attribute	attribute	NOUN
cana-1616	55	15	information	information	NOUN
cana-1616	55	16	.	.	PUNCT
cana-1616	56	1	ilpd	ilpd	NOUN
cana-1616	56	2	dataset	dataset	VERB
cana-1616	56	3	pre	pre	ADJ
cana-1616	56	4	-	-	ADJ
cana-1616	56	5	processing	processing	ADJ
cana-1616	56	6	convert	convert	NOUN
cana-1616	56	7	strings	string	NOUN
cana-1616	56	8	into	into	ADP
cana-1616	56	9	numeric	numeric	ADJ
cana-1616	56	10	values	value	NOUN
cana-1616	56	11	implement	implement	VERB
cana-1616	56	12	mean	mean	NOUN
cana-1616	56	13	imputation	imputation	NOUN
cana-1616	56	14	method	method	NOUN
cana-1616	56	15	for	for	ADP
cana-1616	56	16	handling	handle	VERB
cana-1616	56	17	nan	nan	PROPN
cana-1616	56	18	values	value	NOUN
cana-1616	56	19	proposed	propose	VERB
cana-1616	56	20	feature	feature	NOUN
cana-1616	56	21	selection	selection	NOUN
cana-1616	56	22	implement	implement	VERB
cana-1616	56	23	fuzzy	fuzzy	ADJ
cana-1616	56	24	model	model	NOUN
cana-1616	56	25	for	for	ADP
cana-1616	56	26	creating	create	VERB
cana-1616	56	27	the	the	DET
cana-1616	56	28	final	final	ADJ
cana-1616	56	29	feature	feature	NOUN
cana-1616	56	30	set	set	VERB
cana-1616	56	31	with	with	ADP
cana-1616	56	32	updated	update	VERB
cana-1616	56	33	weights	weight	NOUN
cana-1616	56	34	classification	classification	NOUN
cana-1616	56	35	using	use	VERB
cana-1616	56	36	belv	belv	PROPN
cana-1616	56	37	apply	apply	VERB
cana-1616	56	38	voting	voting	NOUN
cana-1616	56	39	mechanism	mechanism	NOUN
cana-1616	56	40	for	for	ADP
cana-1616	56	41	final	final	ADJ
cana-1616	56	42	prediction	prediction	NOUN
cana-1616	56	43	combine	combine	NOUN
cana-1616	56	44	predictions	prediction	NOUN
cana-1616	56	45	using	use	VERB
cana-1616	56	46	ensemble	ensemble	ADJ
cana-1616	56	47	learning	learning	NOUN
cana-1616	56	48	apply	apply	VERB
cana-1616	56	49	entropy	entropy	NOUN
cana-1616	56	50	,	,	PUNCT
cana-1616	56	51	ecfs	ecfs	NOUN
cana-1616	56	52	and	and	CCONJ
cana-1616	56	53	eifs	eif	VERB
cana-1616	56	54	on	on	ADP
cana-1616	56	55	each	each	DET
cana-1616	56	56	feature	feature	NOUN
cana-1616	56	57	to	to	PART
cana-1616	56	58	get	get	VERB
cana-1616	56	59	the	the	DET
cana-1616	56	60	first	first	ADJ
cana-1616	56	61	feature	feature	NOUN
cana-1616	56	62	set	set	VERB
cana-1616	56	63	pass	pass	VERB
cana-1616	56	64	first	first	ADJ
cana-1616	56	65	feature	feature	NOUN
cana-1616	56	66	set	set	VERB
cana-1616	56	67	to	to	ADP
cana-1616	56	68	rf	rf	NOUN
cana-1616	56	69	classifier	classifier	NOUN
cana-1616	56	70	for	for	ADP
cana-1616	56	71	evaluating	evaluate	VERB
cana-1616	56	72	their	their	PRON
cana-1616	56	73	accuracy	accuracy	NOUN
cana-1616	56	74	and	and	CCONJ
cana-1616	56	75	update	update	NOUN
cana-1616	56	76	relevance	relevance	NOUN
cana-1616	56	77	score	score	NOUN
cana-1616	56	78	again	again	ADV
cana-1616	56	79	to	to	PART
cana-1616	56	80	get	get	VERB
cana-1616	56	81	second	second	ADJ
cana-1616	56	82	updated	update	VERB
cana-1616	56	83	feature	feature	NOUN
cana-1616	56	84	set	set	VERB
cana-1616	56	85	apply	apply	VERB
cana-1616	56	86	bagging	bagging	NOUN
cana-1616	56	87	technique	technique	NOUN
cana-1616	56	88	to	to	PART
cana-1616	56	89	knn	knn	PROPN
cana-1616	56	90	,	,	PUNCT
cana-1616	56	91	dt	dt	PUNCT
cana-1616	56	92	and	and	CCONJ
cana-1616	56	93	rf	rf	VERB
cana-1616	56	94	for	for	ADP
cana-1616	56	95	creating	create	VERB
cana-1616	56	96	5	5	NUM
cana-1616	56	97	bags	bag	NOUN
cana-1616	56	98	detection	detection	NOUN
cana-1616	56	99	and	and	CCONJ
cana-1616	56	100	classification	classification	NOUN
cana-1616	56	101	of	of	ADP
cana-1616	56	102	liver	liver	NOUN
cana-1616	56	103	disease	disease	NOUN
cana-1616	56	104	communications	communication	NOUN
cana-1616	56	105	on	on	ADP
cana-1616	56	106	applied	apply	VERB
cana-1616	56	107	nonlinear	nonlinear	ADJ
cana-1616	56	108	analysis	analysis	NOUN
cana-1616	56	109	issn	issn	NOUN
cana-1616	56	110	:	:	PUNCT
cana-1616	56	111	1074	1074	NUM
cana-1616	56	112	-	-	PUNCT
cana-1616	56	113	133x	133x	NUM
cana-1616	56	114	vol	vol	NOUN
cana-1616	56	115	31	31	NUM
cana-1616	56	116	no	no	NOUN
cana-1616	56	117	.	.	PUNCT
cana-1616	57	1	8s	8s	PROPN
cana-1616	57	2	(	(	PUNCT
cana-1616	57	3	2024	2024	NUM
cana-1616	57	4	)	)	PUNCT
cana-1616	57	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	57	6	776	776	NUM
cana-1616	57	7	3.1.1	3.1.1	NUM
cana-1616	57	8	ilpd	ilpd	NOUN
cana-1616	57	9	dataset	dataset	VERB
cana-1616	57	10	ilpd	ilpd	NOUN
cana-1616	57	11	is	be	AUX
cana-1616	57	12	one	one	NUM
cana-1616	57	13	of	of	ADP
cana-1616	57	14	the	the	DET
cana-1616	57	15	frequently	frequently	ADV
cana-1616	57	16	utilized	utilize	VERB
cana-1616	57	17	datasets	dataset	NOUN
cana-1616	57	18	for	for	ADP
cana-1616	57	19	detecting	detect	VERB
cana-1616	57	20	liver	liver	NOUN
cana-1616	57	21	diseases	disease	NOUN
cana-1616	57	22	.	.	PUNCT
cana-1616	58	1	the	the	DET
cana-1616	58	2	information	information	NOUN
cana-1616	58	3	of	of	ADP
cana-1616	58	4	the	the	DET
cana-1616	58	5	dataset	dataset	NOUN
cana-1616	58	6	is	be	AUX
cana-1616	58	7	publicly	publicly	ADV
cana-1616	58	8	accessible	accessible	ADJ
cana-1616	58	9	on	on	ADP
cana-1616	58	10	kaggle.com	kaggle.com	X
cana-1616	58	11	via	via	ADP
cana-1616	58	12	https://www.kaggle.com/datasets/uciml/indian-liverpatient-records	https://www.kaggle.com/datasets/uciml/indian-liverpatient-record	NOUN
cana-1616	58	13	.	.	PUNCT
cana-1616	59	1	a	a	DET
cana-1616	59	2	total	total	NOUN
cana-1616	59	3	of	of	ADP
cana-1616	59	4	10	10	NUM
cana-1616	59	5	features	feature	NOUN
cana-1616	59	6	and	and	CCONJ
cana-1616	59	7	one	one	NUM
cana-1616	59	8	target	target	NOUN
cana-1616	59	9	attribute	attribute	NOUN
cana-1616	59	10	are	be	AUX
cana-1616	59	11	present	present	ADJ
cana-1616	59	12	in	in	ADP
cana-1616	59	13	the	the	DET
cana-1616	59	14	given	give	VERB
cana-1616	59	15	dataset	dataset	NOUN
cana-1616	59	16	,	,	PUNCT
cana-1616	59	17	whose	whose	DET
cana-1616	59	18	information	information	NOUN
cana-1616	59	19	is	be	AUX
cana-1616	59	20	given	give	VERB
cana-1616	59	21	in	in	ADP
cana-1616	59	22	table	table	NOUN
cana-1616	59	23	1	1	NUM
cana-1616	59	24	.	.	PUNCT
cana-1616	59	25	table	table	NOUN
cana-1616	59	26	1	1	NUM
cana-1616	59	27	:	:	PUNCT
cana-1616	59	28	ilpd	ilpd	NOUN
cana-1616	59	29	dataset	dataset	VERB
cana-1616	59	30	attribute	attribute	NOUN
cana-1616	59	31	information	information	NOUN
cana-1616	59	32	s.no	s.no	VERB
cana-1616	59	33	feature	feature	NOUN
cana-1616	59	34	name	name	NOUN
cana-1616	59	35	type	type	NOUN
cana-1616	59	36	description	description	NOUN
cana-1616	59	37	1	1	NUM
cana-1616	59	38	age	age	NOUN
cana-1616	59	39	feature	feature	NOUN
cana-1616	59	40	represents	represent	VERB
cana-1616	59	41	age	age	NOUN
cana-1616	59	42	of	of	ADP
cana-1616	59	43	individual	individual	ADJ
cana-1616	59	44	2	2	NUM
cana-1616	59	45	gender	gender	NOUN
cana-1616	59	46	feature	feature	NOUN
cana-1616	59	47	represents	represent	VERB
cana-1616	59	48	sex	sex	NOUN
cana-1616	59	49	of	of	ADP
cana-1616	59	50	individual	individual	ADJ
cana-1616	59	51	3	3	NUM
cana-1616	59	52	tb	tb	NOUN
cana-1616	59	53	feature	feature	NOUN
cana-1616	59	54	total	total	ADJ
cana-1616	59	55	bilirubin	bilirubin	NOUN
cana-1616	59	56	4	4	NUM
cana-1616	59	57	db	db	NOUN
cana-1616	59	58	feature	feature	NOUN
cana-1616	59	59	direct	direct	ADJ
cana-1616	59	60	bilirubin	bilirubin	NOUN
cana-1616	59	61	5	5	NUM
cana-1616	60	1	alkphos	alkphos	PROPN
cana-1616	60	2	feature	feature	NOUN
cana-1616	60	3	alkaline	alkaline	NOUN
cana-1616	60	4	phosphate	phosphate	NOUN
cana-1616	60	5	6	6	NUM
cana-1616	60	6	sgpt	sgpt	NOUN
cana-1616	60	7	feature	feature	NOUN
cana-1616	60	8	alamine	alamine	NOUN
cana-1616	60	9	aminotransferase	aminotransferase	PROPN
cana-1616	60	10	7	7	NUM
cana-1616	60	11	sgot	sgot	VERB
cana-1616	60	12	feature	feature	NOUN
cana-1616	60	13	aspartate	aspartate	NOUN
cana-1616	60	14	aminotransferase	aminotransferase	NOUN
cana-1616	60	15	8	8	NUM
cana-1616	60	16	tp	tp	NOUN
cana-1616	60	17	feature	feature	VERB
cana-1616	60	18	total	total	ADJ
cana-1616	60	19	proteins	protein	NOUN
cana-1616	60	20	9	9	NUM
cana-1616	60	21	alb	alb	NOUN
cana-1616	60	22	feature	feature	NOUN
cana-1616	60	23	albumin	albumin	NOUN
cana-1616	60	24	10	10	NUM
cana-1616	60	25	a	a	DET
cana-1616	60	26	/	/	SYM
cana-1616	60	27	g	g	NOUN
cana-1616	60	28	ratio	ratio	NOUN
cana-1616	60	29	feature	feature	NOUN
cana-1616	60	30	albumin	albumin	NOUN
cana-1616	60	31	and	and	CCONJ
cana-1616	60	32	globulin	globulin	NOUN
cana-1616	60	33	ratio	ratio	NOUN
cana-1616	60	34	11	11	NUM
cana-1616	60	35	selector	selector	NOUN
cana-1616	60	36	target	target	NOUN
cana-1616	60	37	used	use	VERB
cana-1616	60	38	for	for	ADP
cana-1616	60	39	separating	separate	VERB
cana-1616	60	40	data	datum	NOUN
cana-1616	60	41	into	into	ADP
cana-1616	60	42	two	two	NUM
cana-1616	60	43	sets	set	NOUN
cana-1616	60	44	3.1.2	3.1.2	NUM
cana-1616	60	45	cpd	cpd	NOUN
cana-1616	60	46	dataset	dataset	VERB
cana-1616	60	47	the	the	DET
cana-1616	60	48	second	second	ADJ
cana-1616	60	49	dataset	dataset	NOUN
cana-1616	60	50	used	use	VERB
cana-1616	60	51	in	in	ADP
cana-1616	60	52	proposed	propose	VERB
cana-1616	60	53	work	work	NOUN
cana-1616	60	54	is	be	AUX
cana-1616	60	55	cpd	cpd	NOUN
cana-1616	60	56	whose	whose	DET
cana-1616	60	57	data	datum	NOUN
cana-1616	60	58	is	be	AUX
cana-1616	60	59	accessible	accessible	ADJ
cana-1616	60	60	on	on	ADP
cana-1616	60	61	https://www.kaggle.com/datasets/fedesoriano/cirrhosis-prediction-dataset	https://www.kaggle.com/datasets/fedesoriano/cirrhosis-prediction-dataset	NOUN
cana-1616	60	62	.	.	PUNCT
cana-1616	61	1	table	table	NOUN
cana-1616	61	2	2	2	NUM
cana-1616	61	3	:	:	PUNCT
cana-1616	61	4	cpd	cpd	PROPN
cana-1616	61	5	dataset	dataset	NOUN
cana-1616	61	6	sample	sample	NOUN
cana-1616	61	7	i	i	PROPN
cana-1616	61	8	d	d	PROPN
cana-1616	61	9	n_days	n_day	VERB
cana-1616	61	10	bilirubin	bilirubin	NOUN
cana-1616	61	11	cholesterol	cholesterol	NOUN
cana-1616	61	12	albumin	albumin	ADJ
cana-1616	61	13	triglycerides	triglyceride	NOUN
cana-1616	61	14	platelets	platelet	VERB
cana-1616	61	15	prothrombin	prothrombin	ADJ
cana-1616	61	16	stage	stage	NOUN
cana-1616	61	17	1	1	NUM
cana-1616	61	18	400	400	NUM
cana-1616	61	19	14.5	14.5	NUM
cana-1616	61	20	261	261	NUM
cana-1616	61	21	2.6	2.6	NUM
cana-1616	61	22	172	172	NUM
cana-1616	61	23	190	190	NUM
cana-1616	61	24	12.2	12.2	NUM
cana-1616	61	25	4	4	NUM
cana-1616	61	26	2	2	NUM
cana-1616	61	27	4500	4500	NUM
cana-1616	61	28	1.1	1.1	NUM
cana-1616	61	29	302	302	NUM
cana-1616	61	30	4.14	4.14	NUM
cana-1616	61	31	88	88	NUM
cana-1616	61	32	221	221	NUM
cana-1616	61	33	10.6	10.6	NUM
cana-1616	61	34	3	3	NUM
cana-1616	61	35	3	3	NUM
cana-1616	61	36	1012	1012	NUM
cana-1616	61	37	1.4	1.4	NUM
cana-1616	61	38	176	176	NUM
cana-1616	61	39	3.48	3.48	NUM
cana-1616	61	40	55	55	NUM
cana-1616	61	41	151	151	NUM
cana-1616	61	42	12	12	NUM
cana-1616	61	43	4	4	NUM
cana-1616	61	44	4	4	NUM
cana-1616	61	45	1925	1925	NUM
cana-1616	61	46	1.8	1.8	NUM
cana-1616	61	47	244	244	NUM
cana-1616	61	48	2.54	2.54	NUM
cana-1616	61	49	92	92	NUM
cana-1616	61	50	183	183	NUM
cana-1616	61	51	10.3	10.3	NUM
cana-1616	61	52	4	4	NUM
cana-1616	61	53	5	5	NUM
cana-1616	61	54	1504	1504	NUM
cana-1616	61	55	3.4	3.4	NUM
cana-1616	61	56	279	279	NUM
cana-1616	61	57	3.53	3.53	NUM
cana-1616	61	58	72	72	NUM
cana-1616	61	59	136	136	NUM
cana-1616	61	60	10.9	10.9	NUM
cana-1616	61	61	3	3	NUM
cana-1616	61	62	6	6	NUM
cana-1616	61	63	2503	2503	NUM
cana-1616	61	64	0.8	0.8	NUM
cana-1616	61	65	248	248	NUM
cana-1616	61	66	3.98	3.98	NUM
cana-1616	61	67	63	63	NUM
cana-1616	61	68	11	11	NUM
cana-1616	61	69	3	3	NUM
cana-1616	61	70	7	7	NUM
cana-1616	61	71	1832	1832	NUM
cana-1616	61	72	1	1	NUM
cana-1616	61	73	322	322	NUM
cana-1616	61	74	4.09	4.09	NUM
cana-1616	61	75	213	213	NUM
cana-1616	61	76	204	204	NUM
cana-1616	61	77	9.7	9.7	NUM
cana-1616	61	78	3	3	NUM
cana-1616	61	79	8	8	NUM
cana-1616	61	80	2466	2466	NUM
cana-1616	61	81	0.3	0.3	NUM
cana-1616	61	82	280	280	NUM
cana-1616	61	83	4	4	NUM
cana-1616	61	84	189	189	NUM
cana-1616	61	85	373	373	NUM
cana-1616	61	86	11	11	NUM
cana-1616	61	87	3	3	NUM
cana-1616	61	88	9	9	NUM
cana-1616	61	89	2400	2400	NUM
cana-1616	61	90	3.2	3.2	NUM
cana-1616	61	91	562	562	NUM
cana-1616	61	92	3.08	3.08	NUM
cana-1616	61	93	88	88	NUM
cana-1616	61	94	251	251	NUM
cana-1616	61	95	11	11	NUM
cana-1616	61	96	2	2	NUM
cana-1616	61	97	since	since	SCONJ
cana-1616	61	98	the	the	DET
cana-1616	61	99	datasets	dataset	NOUN
cana-1616	61	100	contains	contain	VERB
cana-1616	61	101	information	information	NOUN
cana-1616	61	102	in	in	ADP
cana-1616	61	103	string	string	NOUN
cana-1616	61	104	format	format	NOUN
cana-1616	61	105	which	which	PRON
cana-1616	61	106	is	be	AUX
cana-1616	61	107	not	not	PART
cana-1616	61	108	recognized	recognize	VERB
cana-1616	61	109	by	by	ADP
cana-1616	61	110	our	our	PRON
cana-1616	61	111	classifiers	classifier	NOUN
cana-1616	61	112	,	,	PUNCT
cana-1616	61	113	therefore	therefore	ADV
cana-1616	61	114	,	,	PUNCT
cana-1616	61	115	we	we	PRON
cana-1616	61	116	have	have	AUX
cana-1616	61	117	first	first	ADV
cana-1616	61	118	implemented	implement	VERB
cana-1616	61	119	label	label	NOUN
cana-1616	61	120	encoder	encoder	NOUN
cana-1616	61	121	technique	technique	NOUN
cana-1616	61	122	in	in	ADP
cana-1616	61	123	the	the	DET
cana-1616	61	124	pre	pre	ADJ
cana-1616	61	125	-	-	ADJ
cana-1616	61	126	processing	processing	ADJ
cana-1616	61	127	stage	stage	NOUN
cana-1616	61	128	that	that	PRON
cana-1616	61	129	converts	convert	VERB
cana-1616	61	130	the	the	DET
cana-1616	61	131	string	string	NOUN
cana-1616	61	132	attributes	attribute	VERB
cana-1616	61	133	like	like	ADP
cana-1616	61	134	male	male	NOUN
cana-1616	61	135	and	and	CCONJ
cana-1616	61	136	female	female	ADJ
cana-1616	61	137	into	into	ADP
cana-1616	61	138	numeric	numeric	ADJ
cana-1616	61	139	values	value	NOUN
cana-1616	61	140	of	of	ADP
cana-1616	61	141	0	0	NUM
cana-1616	61	142	and	and	CCONJ
cana-1616	61	143	1	1	NUM
cana-1616	61	144	respectively	respectively	ADV
cana-1616	61	145	.	.	PUNCT
cana-1616	62	1	this	this	PRON
cana-1616	62	2	helps	help	VERB
cana-1616	62	3	in	in	ADP
cana-1616	62	4	enhancing	enhance	VERB
cana-1616	62	5	feature	feature	NOUN
cana-1616	62	6	engineering	engineering	NOUN
cana-1616	62	7	process	process	NOUN
cana-1616	62	8	as	as	SCONJ
cana-1616	62	9	the	the	DET
cana-1616	62	10	proposed	propose	VERB
cana-1616	62	11	model	model	NOUN
cana-1616	62	12	can	can	AUX
cana-1616	62	13	efficiently	efficiently	ADV
cana-1616	62	14	recognize	recognize	VERB
cana-1616	62	15	patterns	pattern	NOUN
cana-1616	62	16	and	and	CCONJ
cana-1616	62	17	relationship	relationship	NOUN
cana-1616	62	18	among	among	ADP
cana-1616	62	19	various	various	ADJ
cana-1616	62	20	attributes	attribute	NOUN
cana-1616	62	21	.	.	PUNCT
cana-1616	63	1	secondly	secondly	ADV
cana-1616	63	2	,	,	PUNCT
cana-1616	63	3	the	the	DET
cana-1616	63	4	nan	nan	PROPN
cana-1616	63	5	values	value	VERB
cana-1616	63	6	present	present	ADJ
cana-1616	63	7	in	in	ADP
cana-1616	63	8	the	the	DET
cana-1616	63	9	dataset	dataset	NOUN
cana-1616	63	10	are	be	AUX
cana-1616	63	11	handled	handle	VERB
cana-1616	63	12	by	by	ADP
cana-1616	63	13	applying	apply	VERB
cana-1616	63	14	a	a	DET
cana-1616	63	15	mean	mean	NOUN
cana-1616	63	16	imputation	imputation	NOUN
cana-1616	63	17	technique	technique	NOUN
cana-1616	63	18	,	,	PUNCT
cana-1616	63	19	because	because	SCONJ
cana-1616	63	20	we	we	PRON
cana-1616	63	21	are	be	AUX
cana-1616	63	22	dealing	deal	VERB
cana-1616	63	23	with	with	ADP
cana-1616	63	24	numeric	numeric	ADJ
cana-1616	63	25	data	datum	NOUN
cana-1616	63	26	now	now	ADV
cana-1616	63	27	.	.	PUNCT
cana-1616	64	1	communications	communication	NOUN
cana-1616	64	2	on	on	ADP
cana-1616	64	3	applied	apply	VERB
cana-1616	64	4	nonlinear	nonlinear	ADJ
cana-1616	64	5	analysis	analysis	NOUN
cana-1616	64	6	issn	issn	NOUN
cana-1616	64	7	:	:	PUNCT
cana-1616	64	8	1074	1074	NUM
cana-1616	64	9	-	-	PUNCT
cana-1616	64	10	133x	133x	NUM
cana-1616	64	11	vol	vol	NOUN
cana-1616	64	12	31	31	NUM
cana-1616	64	13	no	no	NOUN
cana-1616	64	14	.	.	PUNCT
cana-1616	65	1	8s	8s	PROPN
cana-1616	65	2	(	(	PUNCT
cana-1616	65	3	2024	2024	NUM
cana-1616	65	4	)	)	PUNCT
cana-1616	65	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	65	6	777	777	NUM
cana-1616	65	7	4	4	NUM
cana-1616	65	8	.	.	PUNCT
cana-1616	65	9	proposed	propose	VERB
cana-1616	65	10	feature	feature	NOUN
cana-1616	65	11	selection	selection	NOUN
cana-1616	65	12	technique	technique	NOUN
cana-1616	65	13	feature	feature	NOUN
cana-1616	65	14	selection	selection	NOUN
cana-1616	65	15	(	(	PUNCT
cana-1616	65	16	fs	fs	NOUN
cana-1616	65	17	)	)	PUNCT
cana-1616	65	18	is	be	AUX
cana-1616	65	19	one	one	NUM
cana-1616	65	20	of	of	ADP
cana-1616	65	21	the	the	DET
cana-1616	65	22	crucial	crucial	ADJ
cana-1616	65	23	steps	step	NOUN
cana-1616	65	24	in	in	ADP
cana-1616	65	25	the	the	DET
cana-1616	65	26	process	process	NOUN
cana-1616	65	27	of	of	ADP
cana-1616	65	28	liver	liver	NOUN
cana-1616	65	29	disease	disease	NOUN
cana-1616	65	30	detection	detection	NOUN
cana-1616	65	31	,	,	PUNCT
cana-1616	65	32	wherein	wherein	SCONJ
cana-1616	65	33	informative	informative	ADJ
cana-1616	65	34	feature	feature	NOUN
cana-1616	65	35	set	set	NOUN
cana-1616	65	36	is	be	AUX
cana-1616	65	37	created	create	VERB
cana-1616	65	38	by	by	ADP
cana-1616	65	39	selecting	select	VERB
cana-1616	65	40	only	only	ADV
cana-1616	65	41	crucial	crucial	ADJ
cana-1616	65	42	and	and	CCONJ
cana-1616	65	43	informative	informative	ADJ
cana-1616	65	44	features	feature	NOUN
cana-1616	65	45	that	that	PRON
cana-1616	65	46	aid	aid	NOUN
cana-1616	65	47	in	in	ADP
cana-1616	65	48	enhancing	enhance	VERB
cana-1616	65	49	the	the	DET
cana-1616	65	50	accuracy	accuracy	NOUN
cana-1616	65	51	of	of	ADP
cana-1616	65	52	model	model	NOUN
cana-1616	65	53	.	.	PUNCT
cana-1616	66	1	moreover	moreover	ADV
cana-1616	66	2	,	,	PUNCT
cana-1616	66	3	it	it	PRON
cana-1616	66	4	also	also	ADV
cana-1616	66	5	aids	aid	VERB
cana-1616	66	6	in	in	ADP
cana-1616	66	7	addressing	address	VERB
cana-1616	66	8	the	the	DET
cana-1616	66	9	dimensionality	dimensionality	NOUN
cana-1616	66	10	issues	issue	NOUN
cana-1616	66	11	which	which	PRON
cana-1616	66	12	can	can	AUX
cana-1616	66	13	lead	lead	VERB
cana-1616	66	14	to	to	ADP
cana-1616	66	15	overfitting	overfitte	VERB
cana-1616	66	16	when	when	SCONJ
cana-1616	66	17	dealing	deal	VERB
cana-1616	66	18	with	with	ADP
cana-1616	66	19	high	high	ADJ
cana-1616	66	20	dimensional	dimensional	ADJ
cana-1616	66	21	data	datum	NOUN
cana-1616	66	22	.	.	PUNCT
cana-1616	67	1	traditionally	traditionally	ADV
cana-1616	67	2	,	,	PUNCT
cana-1616	67	3	various	various	ADJ
cana-1616	67	4	fs	fs	ADP
cana-1616	67	5	techniques	technique	NOUN
cana-1616	67	6	were	be	AUX
cana-1616	67	7	implemented	implement	VERB
cana-1616	67	8	by	by	ADP
cana-1616	67	9	researchers	researcher	NOUN
cana-1616	67	10	in	in	ADP
cana-1616	67	11	their	their	PRON
cana-1616	67	12	respective	respective	ADJ
cana-1616	67	13	works	work	NOUN
cana-1616	67	14	for	for	ADP
cana-1616	67	15	selecting	select	VERB
cana-1616	67	16	important	important	ADJ
cana-1616	67	17	features	feature	NOUN
cana-1616	67	18	in	in	ADP
cana-1616	67	19	liver	liver	NOUN
cana-1616	67	20	disease	disease	NOUN
cana-1616	67	21	datasets	dataset	NOUN
cana-1616	67	22	,	,	PUNCT
cana-1616	67	23	however	however	ADV
cana-1616	67	24	,	,	PUNCT
cana-1616	67	25	the	the	DET
cana-1616	67	26	problem	problem	NOUN
cana-1616	67	27	is	be	AUX
cana-1616	67	28	that	that	SCONJ
cana-1616	67	29	majority	majority	NOUN
cana-1616	67	30	of	of	ADP
cana-1616	67	31	these	these	DET
cana-1616	67	32	techniques	technique	NOUN
cana-1616	67	33	selected	select	VERB
cana-1616	67	34	features	feature	NOUN
cana-1616	67	35	based	base	VERB
cana-1616	67	36	on	on	ADP
cana-1616	67	37	their	their	PRON
cana-1616	67	38	weights	weight	NOUN
cana-1616	67	39	generated	generate	VERB
cana-1616	67	40	by	by	ADP
cana-1616	67	41	employing	employ	VERB
cana-1616	67	42	single	single	ADJ
cana-1616	67	43	technique	technique	NOUN
cana-1616	67	44	.	.	PUNCT
cana-1616	68	1	this	this	PRON
cana-1616	68	2	makes	make	VERB
cana-1616	68	3	the	the	DET
cana-1616	68	4	model	model	NOUN
cana-1616	68	5	computational	computational	ADJ
cana-1616	68	6	complex	complex	NOUN
cana-1616	68	7	and	and	CCONJ
cana-1616	68	8	time	time	NOUN
cana-1616	68	9	consuming	consume	VERB
cana-1616	68	10	as	as	SCONJ
cana-1616	68	11	the	the	DET
cana-1616	68	12	model	model	NOUN
cana-1616	68	13	has	have	VERB
cana-1616	68	14	to	to	PART
cana-1616	68	15	undergo	undergo	VERB
cana-1616	68	16	through	through	ADP
cana-1616	68	17	number	number	NOUN
cana-1616	68	18	of	of	ADP
cana-1616	68	19	iterations	iteration	NOUN
cana-1616	68	20	to	to	PART
cana-1616	68	21	attain	attain	VERB
cana-1616	68	22	a	a	DET
cana-1616	68	23	feature	feature	NOUN
cana-1616	68	24	subset	subset	VERB
cana-1616	68	25	with	with	ADP
cana-1616	68	26	best	good	ADJ
cana-1616	68	27	weights	weight	NOUN
cana-1616	68	28	.	.	PUNCT
cana-1616	69	1	in	in	ADP
cana-1616	69	2	realm	realm	NOUN
cana-1616	69	3	to	to	ADP
cana-1616	69	4	this	this	DET
cana-1616	69	5	limitation	limitation	NOUN
cana-1616	69	6	,	,	PUNCT
cana-1616	69	7	a	a	DET
cana-1616	69	8	novel	novel	NOUN
cana-1616	69	9	and	and	CCONJ
cana-1616	69	10	unique	unique	ADJ
cana-1616	69	11	fs	fs	ADP
cana-1616	69	12	technique	technique	NOUN
cana-1616	69	13	is	be	AUX
cana-1616	69	14	proposed	propose	VERB
cana-1616	69	15	in	in	ADP
cana-1616	69	16	this	this	DET
cana-1616	69	17	paper	paper	NOUN
cana-1616	69	18	that	that	PRON
cana-1616	69	19	can	can	AUX
cana-1616	69	20	not	not	PART
cana-1616	69	21	only	only	ADV
cana-1616	69	22	enhance	enhance	VERB
cana-1616	69	23	the	the	DET
cana-1616	69	24	accuracy	accuracy	NOUN
cana-1616	69	25	of	of	ADP
cana-1616	69	26	detection	detection	NOUN
cana-1616	69	27	but	but	CCONJ
cana-1616	69	28	also	also	ADV
cana-1616	69	29	addresses	address	NOUN
cana-1616	69	30	above	above	ADP
cana-1616	69	31	mentioned	mention	VERB
cana-1616	69	32	limitations	limitation	NOUN
cana-1616	69	33	.	.	PUNCT
cana-1616	70	1	the	the	DET
cana-1616	70	2	proposed	propose	VERB
cana-1616	70	3	fs	f	NOUN
cana-1616	70	4	technique	technique	NOUN
cana-1616	70	5	is	be	AUX
cana-1616	70	6	different	different	ADJ
cana-1616	70	7	from	from	ADP
cana-1616	70	8	previous	previous	ADJ
cana-1616	70	9	techniques	technique	NOUN
cana-1616	70	10	in	in	ADP
cana-1616	70	11	the	the	DET
cana-1616	70	12	fact	fact	NOUN
cana-1616	70	13	that	that	SCONJ
cana-1616	70	14	it	it	PRON
cana-1616	70	15	calculates	calculate	VERB
cana-1616	70	16	the	the	DET
cana-1616	70	17	relevance	relevance	NOUN
cana-1616	70	18	score	score	NOUN
cana-1616	70	19	of	of	ADP
cana-1616	70	20	features	feature	NOUN
cana-1616	70	21	in	in	ADP
cana-1616	70	22	three	three	NUM
cana-1616	70	23	stages	stage	NOUN
cana-1616	70	24	by	by	ADP
cana-1616	70	25	using	use	VERB
cana-1616	70	26	different	different	ADJ
cana-1616	70	27	techniques	technique	NOUN
cana-1616	70	28	(	(	PUNCT
cana-1616	70	29	as	as	SCONJ
cana-1616	70	30	shown	show	VERB
cana-1616	70	31	in	in	ADP
cana-1616	70	32	figure	figure	NOUN
cana-1616	70	33	3	3	NUM
cana-1616	70	34	)	)	PUNCT
cana-1616	70	35	.	.	PUNCT
cana-1616	71	1	in	in	ADP
cana-1616	71	2	the	the	DET
cana-1616	71	3	first	first	ADJ
cana-1616	71	4	stage	stage	NOUN
cana-1616	71	5	,	,	PUNCT
cana-1616	71	6	relevance	relevance	NOUN
cana-1616	71	7	score	score	NOUN
cana-1616	71	8	of	of	ADP
cana-1616	71	9	each	each	DET
cana-1616	71	10	feature	feature	NOUN
cana-1616	71	11	is	be	AUX
cana-1616	71	12	obtained	obtain	VERB
cana-1616	71	13	by	by	ADP
cana-1616	71	14	employing	employ	VERB
cana-1616	71	15	entropy	entropy	NOUN
cana-1616	71	16	and	and	CCONJ
cana-1616	71	17	eigenvector	eigenvector	NOUN
cana-1616	71	18	centrality	centrality	NOUN
cana-1616	71	19	methods	method	NOUN
cana-1616	71	20	.	.	PUNCT
cana-1616	72	1	moreover	moreover	ADV
cana-1616	72	2	,	,	PUNCT
cana-1616	72	3	an	an	DET
cana-1616	72	4	enhanced	enhanced	ADJ
cana-1616	72	5	infinite	infinite	ADJ
cana-1616	72	6	feature	feature	NOUN
cana-1616	72	7	selection	selection	NOUN
cana-1616	72	8	(	(	PUNCT
cana-1616	72	9	eifs	eifs	PROPN
cana-1616	72	10	)	)	PUNCT
cana-1616	72	11	is	be	AUX
cana-1616	72	12	also	also	ADV
cana-1616	72	13	proposed	propose	VERB
cana-1616	72	14	at	at	ADP
cana-1616	72	15	this	this	DET
cana-1616	72	16	stage	stage	NOUN
cana-1616	72	17	,	,	PUNCT
cana-1616	72	18	which	which	PRON
cana-1616	72	19	is	be	AUX
cana-1616	72	20	basically	basically	ADV
cana-1616	72	21	an	an	DET
cana-1616	72	22	extension	extension	NOUN
cana-1616	72	23	of	of	ADP
cana-1616	72	24	standard	standard	ADJ
cana-1616	72	25	ifs	ifs	PROPN
cana-1616	72	26	method	method	NOUN
cana-1616	72	27	.	.	PUNCT
cana-1616	73	1	the	the	DET
cana-1616	73	2	standard	standard	PROPN
cana-1616	73	3	ifs	ifs	PROPN
cana-1616	73	4	is	be	AUX
cana-1616	73	5	enhanced	enhance	VERB
cana-1616	73	6	in	in	ADP
cana-1616	73	7	proposed	propose	VERB
cana-1616	73	8	work	work	NOUN
cana-1616	73	9	by	by	ADP
cana-1616	73	10	introducing	introduce	VERB
cana-1616	73	11	the	the	DET
cana-1616	73	12	concept	concept	NOUN
cana-1616	73	13	of	of	ADP
cana-1616	73	14	entropy	entropy	NOUN
cana-1616	73	15	and	and	CCONJ
cana-1616	73	16	correlation	correlation	NOUN
cana-1616	73	17	in	in	ADP
cana-1616	73	18	it	it	PRON
cana-1616	73	19	,	,	PUNCT
cana-1616	73	20	for	for	ADP
cana-1616	73	21	evaluating	evaluate	VERB
cana-1616	73	22	the	the	DET
cana-1616	73	23	relevance	relevance	NOUN
cana-1616	73	24	score	score	NOUN
cana-1616	73	25	of	of	ADP
cana-1616	73	26	features	feature	NOUN
cana-1616	73	27	present	present	ADJ
cana-1616	73	28	in	in	ADP
cana-1616	73	29	ilpd	ilpd	NOUN
cana-1616	73	30	and	and	CCONJ
cana-1616	73	31	cpd	cpd	ADJ
cana-1616	73	32	datasets	dataset	NOUN
cana-1616	73	33	.	.	PUNCT
cana-1616	74	1	in	in	ADP
cana-1616	74	2	the	the	DET
cana-1616	74	3	next	next	ADJ
cana-1616	74	4	stage	stage	NOUN
cana-1616	74	5	of	of	ADP
cana-1616	74	6	feature	feature	NOUN
cana-1616	74	7	selection	selection	NOUN
cana-1616	74	8	,	,	PUNCT
cana-1616	74	9	a	a	DET
cana-1616	74	10	ml	ml	NOUN
cana-1616	74	11	classifier	classifier	NOUN
cana-1616	74	12	is	be	AUX
cana-1616	74	13	utilized	utilize	VERB
cana-1616	74	14	for	for	ADP
cana-1616	74	15	assessing	assess	VERB
cana-1616	74	16	the	the	DET
cana-1616	74	17	features	feature	NOUN
cana-1616	74	18	selected	select	VERB
cana-1616	74	19	in	in	ADP
cana-1616	74	20	first	first	ADJ
cana-1616	74	21	stage	stage	NOUN
cana-1616	74	22	and	and	CCONJ
cana-1616	74	23	updating	update	VERB
cana-1616	74	24	their	their	PRON
cana-1616	74	25	relevance	relevance	NOUN
cana-1616	74	26	score	score	NOUN
cana-1616	74	27	by	by	ADP
cana-1616	74	28	calculating	calculate	VERB
cana-1616	74	29	their	their	PRON
cana-1616	74	30	accuracy	accuracy	NOUN
cana-1616	74	31	values	value	NOUN
cana-1616	74	32	.	.	PUNCT
cana-1616	75	1	finally	finally	ADV
cana-1616	75	2	,	,	PUNCT
cana-1616	75	3	in	in	ADP
cana-1616	75	4	the	the	DET
cana-1616	75	5	last	last	ADJ
cana-1616	75	6	stage	stage	NOUN
cana-1616	75	7	of	of	ADP
cana-1616	75	8	fs	fs	PROPN
cana-1616	75	9	,	,	PUNCT
cana-1616	75	10	a	a	DET
cana-1616	75	11	fuzzy	fuzzy	ADJ
cana-1616	75	12	system	system	NOUN
cana-1616	75	13	is	be	AUX
cana-1616	75	14	introduced	introduce	VERB
cana-1616	75	15	for	for	ADP
cana-1616	75	16	evaluating	evaluate	VERB
cana-1616	75	17	the	the	DET
cana-1616	75	18	contextual	contextual	ADJ
cana-1616	75	19	relevance	relevance	NOUN
cana-1616	75	20	among	among	ADP
cana-1616	75	21	various	various	ADJ
cana-1616	75	22	features	feature	NOUN
cana-1616	75	23	to	to	PART
cana-1616	75	24	make	make	VERB
cana-1616	75	25	the	the	DET
cana-1616	75	26	final	final	ADJ
cana-1616	75	27	feature	feature	NOUN
cana-1616	75	28	set	set	NOUN
cana-1616	75	29	that	that	PRON
cana-1616	75	30	will	will	AUX
cana-1616	75	31	be	be	AUX
cana-1616	75	32	used	use	VERB
cana-1616	75	33	for	for	ADP
cana-1616	75	34	training	train	VERB
cana-1616	75	35	the	the	DET
cana-1616	75	36	classification	classification	NOUN
cana-1616	75	37	model	model	NOUN
cana-1616	75	38	.	.	PUNCT
cana-1616	76	1	the	the	DET
cana-1616	76	2	detailed	detailed	ADJ
cana-1616	76	3	description	description	NOUN
cana-1616	76	4	of	of	ADP
cana-1616	76	5	each	each	DET
cana-1616	76	6	fs	f	NOUN
cana-1616	76	7	stage	stage	NOUN
cana-1616	76	8	is	be	AUX
cana-1616	76	9	explained	explain	VERB
cana-1616	76	10	below	below	ADV
cana-1616	76	11	.	.	PUNCT
cana-1616	77	1	stage	stage	NOUN
cana-1616	77	2	1	1	NUM
cana-1616	77	3	of	of	ADP
cana-1616	77	4	fs	fs	ADP
cana-1616	77	5	the	the	DET
cana-1616	77	6	process	process	NOUN
cana-1616	77	7	of	of	ADP
cana-1616	77	8	selecting	select	VERB
cana-1616	77	9	important	important	ADJ
cana-1616	77	10	and	and	CCONJ
cana-1616	77	11	informative	informative	ADJ
cana-1616	77	12	features	feature	NOUN
cana-1616	77	13	in	in	ADP
cana-1616	77	14	proposed	propose	VERB
cana-1616	77	15	work	work	NOUN
cana-1616	77	16	starts	start	VERB
cana-1616	77	17	by	by	ADP
cana-1616	77	18	defining	define	VERB
cana-1616	77	19	some	some	DET
cana-1616	77	20	basic	basic	ADJ
cana-1616	77	21	parameters	parameter	NOUN
cana-1616	77	22	of	of	ADP
cana-1616	77	23	the	the	DET
cana-1616	77	24	model	model	NOUN
cana-1616	77	25	that	that	PRON
cana-1616	77	26	will	will	AUX
cana-1616	77	27	be	be	AUX
cana-1616	77	28	used	use	VERB
cana-1616	77	29	in	in	ADP
cana-1616	77	30	subsequent	subsequent	ADJ
cana-1616	77	31	stages	stage	NOUN
cana-1616	77	32	.	.	PUNCT
cana-1616	78	1	the	the	DET
cana-1616	78	2	value	value	NOUN
cana-1616	78	3	of	of	ADP
cana-1616	78	4	these	these	DET
cana-1616	78	5	parameters	parameter	NOUN
cana-1616	78	6	is	be	AUX
cana-1616	78	7	mentioned	mention	VERB
cana-1616	78	8	in	in	ADP
cana-1616	78	9	table	table	NOUN
cana-1616	78	10	2	2	NUM
cana-1616	78	11	.	.	PUNCT
cana-1616	78	12	initially	initially	ADV
cana-1616	78	13	,	,	PUNCT
cana-1616	78	14	entropy	entropy	NOUN
cana-1616	78	15	-	-	PUNCT
cana-1616	78	16	based	base	VERB
cana-1616	78	17	method	method	NOUN
cana-1616	78	18	is	be	AUX
cana-1616	78	19	implemented	implement	VERB
cana-1616	78	20	on	on	ADP
cana-1616	78	21	each	each	DET
cana-1616	78	22	feature	feature	NOUN
cana-1616	78	23	to	to	PART
cana-1616	78	24	measure	measure	VERB
cana-1616	78	25	the	the	DET
cana-1616	78	26	amount	amount	NOUN
cana-1616	78	27	uncertainty	uncertainty	NOUN
cana-1616	78	28	in	in	ADP
cana-1616	78	29	given	give	VERB
cana-1616	78	30	feature	feature	NOUN
cana-1616	78	31	set	set	NOUN
cana-1616	78	32	.	.	PUNCT
cana-1616	79	1	the	the	DET
cana-1616	79	2	formula	formula	NOUN
cana-1616	79	3	used	use	VERB
cana-1616	79	4	for	for	ADP
cana-1616	79	5	calculating	calculate	VERB
cana-1616	79	6	the	the	DET
cana-1616	79	7	feature	feature	NOUN
cana-1616	79	8	score	score	NOUN
cana-1616	79	9	entropy	entropy	NOUN
cana-1616	79	10	of	of	ADP
cana-1616	79	11	features	feature	NOUN
cana-1616	79	12	in	in	ADP
cana-1616	79	13	proposed	propose	VERB
cana-1616	79	14	work	work	NOUN
cana-1616	79	15	is	be	AUX
cana-1616	79	16	given	give	VERB
cana-1616	79	17	in	in	ADP
cana-1616	79	18	equation	equation	NOUN
cana-1616	79	19	1	1	NUM
cana-1616	79	20	.	.	PUNCT
cana-1616	80	1	𝐻(𝑓	𝐻(𝑓	PART
cana-1616	81	1	)	)	PUNCT
cana-1616	81	2	=	=	SYM
cana-1616	81	3	∑	∑	PUNCT
cana-1616	81	4	𝑝𝑖	𝑝𝑖	PROPN
cana-1616	81	5	log2	log2	PROPN
cana-1616	81	6	𝑝𝑖	𝑝𝑖	PROPN
cana-1616	81	7	𝑛	𝑛	PROPN
cana-1616	81	8	𝑖=1	𝑖=1	PROPN
cana-1616	81	9	(	(	PUNCT
cana-1616	81	10	1	1	NUM
cana-1616	81	11	)	)	PUNCT
cana-1616	81	12	by	by	ADP
cana-1616	81	13	using	use	VERB
cana-1616	81	14	above	above	ADV
cana-1616	81	15	given	give	VERB
cana-1616	81	16	equation	equation	NOUN
cana-1616	81	17	,	,	PUNCT
cana-1616	81	18	scores	score	NOUN
cana-1616	81	19	of	of	ADP
cana-1616	81	20	the	the	DET
cana-1616	81	21	features	feature	NOUN
cana-1616	81	22	were	be	AUX
cana-1616	81	23	obtained	obtain	VERB
cana-1616	81	24	which	which	PRON
cana-1616	81	25	are	be	AUX
cana-1616	81	26	then	then	ADV
cana-1616	81	27	ranked	rank	VERB
cana-1616	81	28	in	in	ADP
cana-1616	81	29	the	the	DET
cana-1616	81	30	descending	descend	VERB
cana-1616	81	31	order	order	NOUN
cana-1616	81	32	to	to	PART
cana-1616	81	33	select	select	VERB
cana-1616	81	34	more	more	ADV
cana-1616	81	35	effective	effective	ADJ
cana-1616	81	36	features	feature	NOUN
cana-1616	81	37	based	base	VERB
cana-1616	81	38	on	on	ADP
cana-1616	81	39	their	their	PRON
cana-1616	81	40	weight	weight	NOUN
cana-1616	81	41	value	value	NOUN
cana-1616	81	42	.	.	PUNCT
cana-1616	82	1	the	the	DET
cana-1616	82	2	features	feature	NOUN
cana-1616	82	3	with	with	ADP
cana-1616	82	4	less	less	ADJ
cana-1616	82	5	entropy	entropy	NOUN
cana-1616	82	6	values	value	NOUN
cana-1616	82	7	are	be	AUX
cana-1616	82	8	ranked	rank	VERB
cana-1616	82	9	higher	higher	ADV
cana-1616	82	10	and	and	CCONJ
cana-1616	82	11	hence	hence	ADV
cana-1616	82	12	are	be	AUX
cana-1616	82	13	more	more	ADV
cana-1616	82	14	relevant	relevant	ADJ
cana-1616	82	15	to	to	ADP
cana-1616	82	16	our	our	PRON
cana-1616	82	17	work	work	NOUN
cana-1616	82	18	.	.	PUNCT
cana-1616	83	1	after	after	ADP
cana-1616	83	2	this	this	PRON
cana-1616	83	3	,	,	PUNCT
cana-1616	83	4	the	the	DET
cana-1616	83	5	second	second	ADJ
cana-1616	83	6	method	method	NOUN
cana-1616	83	7	i.e.	i.e.	X
cana-1616	83	8	,	,	PUNCT
cana-1616	83	9	ecfs	ecfs	NOUN
cana-1616	83	10	is	be	AUX
cana-1616	83	11	applied	apply	VERB
cana-1616	83	12	on	on	ADP
cana-1616	83	13	each	each	DET
cana-1616	83	14	feature	feature	NOUN
cana-1616	83	15	of	of	ADP
cana-1616	83	16	dataset	dataset	NOUN
cana-1616	83	17	to	to	PART
cana-1616	83	18	form	form	VERB
cana-1616	83	19	another	another	DET
cana-1616	83	20	set	set	NOUN
cana-1616	83	21	of	of	ADP
cana-1616	83	22	features	feature	NOUN
cana-1616	83	23	with	with	ADP
cana-1616	83	24	different	different	ADJ
cana-1616	83	25	weights	weight	NOUN
cana-1616	83	26	or	or	CCONJ
cana-1616	83	27	relevance	relevance	NOUN
cana-1616	83	28	scores	score	NOUN
cana-1616	83	29	.	.	PUNCT
cana-1616	84	1	ecfs	ecfs	PROPN
cana-1616	84	2	is	be	AUX
cana-1616	84	3	basically	basically	ADV
cana-1616	84	4	a	a	DET
cana-1616	84	5	graph	graph	NOUN
cana-1616	84	6	-	-	PUNCT
cana-1616	84	7	based	base	VERB
cana-1616	84	8	approach	approach	NOUN
cana-1616	84	9	that	that	PRON
cana-1616	84	10	determines	determine	VERB
cana-1616	84	11	the	the	DET
cana-1616	84	12	impact	impact	NOUN
cana-1616	84	13	of	of	ADP
cana-1616	84	14	each	each	DET
cana-1616	84	15	feature	feature	NOUN
cana-1616	84	16	in	in	ADP
cana-1616	84	17	the	the	DET
cana-1616	84	18	model	model	NOUN
cana-1616	84	19	.	.	PUNCT
cana-1616	85	1	considering	consider	VERB
cana-1616	85	2	a	a	DET
cana-1616	85	3	featured	feature	VERB
cana-1616	85	4	graph	graph	NOUN
cana-1616	85	5	g=	g=	NOUN
cana-1616	85	6	(	(	PUNCT
cana-1616	85	7	v	v	NOUN
cana-1616	85	8	,	,	PUNCT
cana-1616	85	9	e	e	NOUN
cana-1616	85	10	)	)	PUNCT
cana-1616	85	11	,	,	PUNCT
cana-1616	85	12	having	have	VERB
cana-1616	85	13	v	v	NOUN
cana-1616	85	14	vertices	vertex	NOUN
cana-1616	85	15	and	and	CCONJ
cana-1616	85	16	a=(av	a=(av	NOUN
cana-1616	85	17	,	,	PUNCT
cana-1616	85	18	t	t	PROPN
cana-1616	85	19	)	)	PUNCT
cana-1616	85	20	be	be	AUX
cana-1616	85	21	its	its	PRON
cana-1616	85	22	adjacent	adjacent	ADJ
cana-1616	85	23	matrices	matrix	NOUN
cana-1616	85	24	,	,	PUNCT
cana-1616	85	25	with	with	ADP
cana-1616	85	26	av	av	PRON
cana-1616	85	27	,	,	PUNCT
cana-1616	85	28	t=	t=	NOUN
cana-1616	85	29	1	1	NUM
cana-1616	85	30	.	.	PUNCT
cana-1616	86	1	on	on	ADP
cana-1616	86	2	the	the	DET
cana-1616	86	3	other	other	ADJ
cana-1616	86	4	hand	hand	NOUN
cana-1616	86	5	,	,	PUNCT
cana-1616	86	6	of	of	ADP
cana-1616	86	7	vertex	vertex	NOUN
cana-1616	86	8	v	v	NOUN
cana-1616	86	9	is	be	AUX
cana-1616	86	10	connected	connect	VERB
cana-1616	86	11	to	to	ADP
cana-1616	86	12	“	"	PUNCT
cana-1616	86	13	t	t	PROPN
cana-1616	86	14	”	"	PUNCT
cana-1616	86	15	vertex	vertex	NOUN
cana-1616	86	16	and	and	CCONJ
cana-1616	86	17	value	value	NOUN
cana-1616	86	18	of	of	ADP
cana-1616	86	19	av	av	PROPN
cana-1616	86	20	,	,	PUNCT
cana-1616	86	21	t	t	PROPN
cana-1616	86	22	is	be	AUX
cana-1616	86	23	zero	zero	NUM
cana-1616	86	24	,	,	PUNCT
cana-1616	86	25	then	then	ADV
cana-1616	86	26	eigenvector	eigenvector	NOUN
cana-1616	86	27	centrality	centrality	NOUN
cana-1616	86	28	can	can	AUX
cana-1616	86	29	be	be	AUX
cana-1616	86	30	calculated	calculate	VERB
cana-1616	86	31	by	by	ADP
cana-1616	86	32	using	use	VERB
cana-1616	86	33	equation	equation	NOUN
cana-1616	86	34	2	2	NUM
cana-1616	86	35	.	.	PUNCT
cana-1616	87	1	𝑥𝑣	𝑥𝑣	X
cana-1616	87	2	=	=	PUNCT
cana-1616	87	3	1	1	NUM
cana-1616	87	4	𝜆	𝜆	PRON
cana-1616	87	5	∑	∑	PROPN
cana-1616	87	6	𝑥𝑡𝑡∈𝑀(𝑣	𝑥𝑡𝑡∈𝑀(𝑣	PRON
cana-1616	87	7	)	)	PUNCT
cana-1616	87	8	=	=	PUNCT
cana-1616	88	1	1	1	NUM
cana-1616	88	2	𝜆	𝜆	X
cana-1616	88	3	∑	∑	PUNCT
cana-1616	88	4	𝑎𝑣,𝑡𝑡∈𝐺	𝑎𝑣,𝑡𝑡∈𝐺	PROPN
cana-1616	88	5	𝑥𝑡	𝑥𝑡	ADP
cana-1616	88	6	(	(	PUNCT
cana-1616	88	7	2	2	NUM
cana-1616	88	8	)	)	PUNCT
cana-1616	88	9	communications	communication	NOUN
cana-1616	88	10	on	on	ADP
cana-1616	88	11	applied	apply	VERB
cana-1616	88	12	nonlinear	nonlinear	ADJ
cana-1616	88	13	analysis	analysis	NOUN
cana-1616	88	14	issn	issn	NOUN
cana-1616	88	15	:	:	PUNCT
cana-1616	88	16	1074	1074	NUM
cana-1616	88	17	-	-	PUNCT
cana-1616	88	18	133x	133x	NUM
cana-1616	88	19	vol	vol	NOUN
cana-1616	88	20	31	31	NUM
cana-1616	88	21	no	no	NOUN
cana-1616	88	22	.	.	PUNCT
cana-1616	89	1	8s	8s	PROPN
cana-1616	89	2	(	(	PUNCT
cana-1616	89	3	2024	2024	NUM
cana-1616	89	4	)	)	PUNCT
cana-1616	89	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	89	6	778	778	NUM
cana-1616	89	7	wherein	wherein	NOUN
cana-1616	89	8	,	,	PUNCT
cana-1616	89	9	m(v	m(v	NUM
cana-1616	89	10	)	)	PUNCT
cana-1616	89	11	depicts	depict	VERB
cana-1616	89	12	the	the	DET
cana-1616	89	13	neighbor	neighbor	NOUN
cana-1616	89	14	set	set	NOUN
cana-1616	89	15	of	of	ADP
cana-1616	89	16	v	v	NOUN
cana-1616	89	17	and	and	CCONJ
cana-1616	89	18	𝜆	𝜆	NOUN
cana-1616	89	19	is	be	AUX
cana-1616	89	20	constant	constant	ADJ
cana-1616	89	21	.	.	PUNCT
cana-1616	90	1	therefore	therefore	ADV
cana-1616	90	2	,	,	PUNCT
cana-1616	90	3	by	by	ADP
cana-1616	90	4	implementing	implement	VERB
cana-1616	90	5	the	the	DET
cana-1616	90	6	formula	formula	NOUN
cana-1616	90	7	2	2	NUM
cana-1616	90	8	on	on	ADP
cana-1616	90	9	each	each	DET
cana-1616	90	10	feature	feature	NOUN
cana-1616	90	11	,	,	PUNCT
cana-1616	90	12	we	we	PRON
cana-1616	90	13	calculated	calculate	VERB
cana-1616	90	14	the	the	DET
cana-1616	90	15	relevance	relevance	NOUN
cana-1616	90	16	score	score	NOUN
cana-1616	90	17	of	of	ADP
cana-1616	90	18	features	feature	NOUN
cana-1616	90	19	and	and	CCONJ
cana-1616	90	20	only	only	ADV
cana-1616	90	21	those	those	DET
cana-1616	90	22	features	feature	NOUN
cana-1616	90	23	which	which	PRON
cana-1616	90	24	are	be	AUX
cana-1616	90	25	central	central	ADJ
cana-1616	90	26	in	in	ADP
cana-1616	90	27	the	the	DET
cana-1616	90	28	feature	feature	NOUN
cana-1616	90	29	graph	graph	NOUN
cana-1616	90	30	are	be	AUX
cana-1616	90	31	considered	consider	VERB
cana-1616	90	32	relevant	relevant	ADJ
cana-1616	90	33	.	.	PUNCT
cana-1616	91	1	figure	figure	NOUN
cana-1616	91	2	3	3	NUM
cana-1616	91	3	.	.	PUNCT
cana-1616	92	1	flowchart	flowchart	NOUN
cana-1616	92	2	of	of	ADP
cana-1616	92	3	proposed	propose	VERB
cana-1616	92	4	feature	feature	NOUN
cana-1616	92	5	selection	selection	NOUN
cana-1616	92	6	technique	technique	NOUN
cana-1616	92	7	furthermore	furthermore	ADV
cana-1616	92	8	,	,	PUNCT
cana-1616	92	9	we	we	PRON
cana-1616	92	10	have	have	AUX
cana-1616	92	11	calculated	calculate	VERB
cana-1616	92	12	the	the	DET
cana-1616	92	13	relevance	relevance	NOUN
cana-1616	92	14	score	score	NOUN
cana-1616	92	15	of	of	ADP
cana-1616	92	16	features	feature	NOUN
cana-1616	92	17	by	by	ADP
cana-1616	92	18	enhancing	enhance	VERB
cana-1616	92	19	the	the	DET
cana-1616	92	20	standard	standard	ADJ
cana-1616	92	21	ifs	ifs	PROPN
cana-1616	92	22	method	method	NOUN
cana-1616	92	23	.	.	PUNCT
cana-1616	93	1	conventionally	conventionally	ADV
cana-1616	93	2	,	,	PUNCT
cana-1616	93	3	we	we	PRON
cana-1616	93	4	have	have	AUX
cana-1616	93	5	observed	observe	VERB
cana-1616	93	6	that	that	SCONJ
cana-1616	93	7	features	feature	NOUN
cana-1616	93	8	in	in	ADP
cana-1616	93	9	ifs	ifs	PROPN
cana-1616	93	10	were	be	AUX
cana-1616	93	11	selected	select	VERB
cana-1616	93	12	either	either	CCONJ
cana-1616	93	13	on	on	ADP
cana-1616	93	14	entropy	entropy	NOUN
cana-1616	93	15	based	base	VERB
cana-1616	93	16	or	or	CCONJ
cana-1616	93	17	correlation	correlation	NOUN
cana-1616	93	18	based	base	VERB
cana-1616	93	19	,	,	PUNCT
cana-1616	93	20	but	but	CCONJ
cana-1616	93	21	in	in	ADP
cana-1616	93	22	our	our	PRON
cana-1616	93	23	work	work	NOUN
cana-1616	93	24	,	,	PUNCT
cana-1616	93	25	both	both	CCONJ
cana-1616	93	26	entropy	entropy	NOUN
cana-1616	93	27	and	and	CCONJ
cana-1616	93	28	correlation	correlation	NOUN
cana-1616	93	29	are	be	AUX
cana-1616	93	30	used	use	VERB
cana-1616	93	31	for	for	ADP
cana-1616	93	32	calculating	calculate	VERB
cana-1616	93	33	weights	weight	NOUN
cana-1616	93	34	of	of	ADP
cana-1616	93	35	features	feature	NOUN
cana-1616	93	36	.	.	PUNCT
cana-1616	94	1	in	in	ADP
cana-1616	94	2	proposed	propose	VERB
cana-1616	94	3	eifs	eif	NOUN
cana-1616	94	4	,	,	PUNCT
cana-1616	94	5	weights	weight	NOUN
cana-1616	94	6	are	be	AUX
cana-1616	94	7	assigned	assign	VERB
cana-1616	94	8	to	to	ADP
cana-1616	94	9	features	feature	NOUN
cana-1616	94	10	by	by	ADP
cana-1616	94	11	combining	combine	VERB
cana-1616	94	12	their	their	PRON
cana-1616	94	13	entropy	entropy	NOUN
cana-1616	94	14	and	and	CCONJ
cana-1616	94	15	correlation	correlation	NOUN
cana-1616	94	16	values	value	NOUN
cana-1616	94	17	.	.	PUNCT
cana-1616	95	1	the	the	DET
cana-1616	95	2	formula	formula	NOUN
cana-1616	95	3	for	for	ADP
cana-1616	95	4	entropy	entropy	NOUN
cana-1616	95	5	is	be	AUX
cana-1616	95	6	same	same	ADJ
cana-1616	95	7	as	as	SCONJ
cana-1616	95	8	given	give	VERB
cana-1616	95	9	in	in	ADP
cana-1616	95	10	equation	equation	NOUN
cana-1616	95	11	1	1	NUM
cana-1616	95	12	.	.	PUNCT
cana-1616	96	1	however	however	ADV
cana-1616	96	2	,	,	PUNCT
cana-1616	96	3	the	the	DET
cana-1616	96	4	correlation	correlation	NOUN
cana-1616	96	5	of	of	ADP
cana-1616	96	6	features	feature	NOUN
cana-1616	96	7	is	be	AUX
cana-1616	96	8	computed	compute	VERB
cana-1616	96	9	by	by	ADP
cana-1616	96	10	using	use	VERB
cana-1616	96	11	equation	equation	NOUN
cana-1616	96	12	3	3	NUM
cana-1616	96	13	.	.	PUNCT
cana-1616	97	1	it	it	PRON
cana-1616	97	2	must	must	AUX
cana-1616	97	3	be	be	AUX
cana-1616	97	4	noted	note	VERB
cana-1616	97	5	that	that	SCONJ
cana-1616	97	6	correlation	correlation	NOUN
cana-1616	97	7	among	among	ADP
cana-1616	97	8	features	feature	NOUN
cana-1616	97	9	and	and	CCONJ
cana-1616	97	10	target	target	NOUN
cana-1616	97	11	variables	variable	NOUN
cana-1616	97	12	is	be	AUX
cana-1616	97	13	measures	measure	NOUN
cana-1616	97	14	by	by	ADP
cana-1616	97	15	their	their	PRON
cana-1616	97	16	mutual	mutual	ADJ
cana-1616	97	17	information	information	NOUN
cana-1616	97	18	factor	factor	NOUN
cana-1616	97	19	(	(	PUNCT
cana-1616	97	20	i	i	NOUN
cana-1616	97	21	)	)	PUNCT
cana-1616	97	22	.	.	PUNCT
cana-1616	98	1	𝐼	𝐼	ADP
cana-1616	98	2	=	=	SYM
cana-1616	98	3	∑	∑	PROPN
cana-1616	98	4	∑	∑	PUNCT
cana-1616	98	5	𝑝(𝑥	𝑝(𝑥	PROPN
cana-1616	98	6	,	,	PUNCT
cana-1616	98	7	𝑦	𝑦	NOUN
cana-1616	98	8	)	)	PUNCT
cana-1616	98	9	log2	log2	PROPN
cana-1616	98	10	(	(	PUNCT
cana-1616	98	11	𝑝(𝑥	𝑝(𝑥	PROPN
cana-1616	98	12	,	,	PUNCT
cana-1616	98	13	𝑦	𝑦	NOUN
cana-1616	98	14	)	)	PUNCT
cana-1616	98	15	𝑝(𝑥)𝑝(𝑦	𝑝(𝑥)𝑝(𝑦	NOUN
cana-1616	98	16	)	)	PUNCT
cana-1616	98	17	)	)	PUNCT
cana-1616	98	18	𝑦∈𝑌𝑥∈𝑋	𝑦∈𝑌𝑥∈𝑋	NOUN
cana-1616	98	19	(	(	PUNCT
cana-1616	98	20	3	3	NUM
cana-1616	98	21	)	)	PUNCT
cana-1616	98	22	once	once	SCONJ
cana-1616	98	23	the	the	DET
cana-1616	98	24	scores	score	NOUN
cana-1616	98	25	of	of	ADP
cana-1616	98	26	each	each	DET
cana-1616	98	27	feature	feature	NOUN
cana-1616	98	28	is	be	AUX
cana-1616	98	29	obtained	obtain	VERB
cana-1616	98	30	through	through	ADP
cana-1616	98	31	entropy	entropy	PROPN
cana-1616	98	32	,	,	PUNCT
cana-1616	98	33	ecfs	ecfs	NOUN
cana-1616	98	34	and	and	CCONJ
cana-1616	98	35	eifs	eifs	PROPN
cana-1616	98	36	method	method	NOUN
cana-1616	98	37	,	,	PUNCT
cana-1616	98	38	we	we	PRON
cana-1616	98	39	proceed	proceed	VERB
cana-1616	98	40	towards	towards	ADP
cana-1616	98	41	next	next	ADJ
cana-1616	98	42	step	step	NOUN
cana-1616	98	43	of	of	ADP
cana-1616	98	44	updating	update	VERB
cana-1616	98	45	relevance	relevance	NOUN
cana-1616	98	46	score	score	NOUN
cana-1616	98	47	of	of	ADP
cana-1616	98	48	features	feature	NOUN
cana-1616	98	49	.	.	PUNCT
cana-1616	99	1	for	for	ADP
cana-1616	99	2	this	this	PRON
cana-1616	99	3	,	,	PUNCT
cana-1616	99	4	we	we	PRON
cana-1616	99	5	considered	consider	VERB
cana-1616	99	6	the	the	DET
cana-1616	99	7	initial	initial	ADJ
cana-1616	99	8	scores	score	NOUN
cana-1616	99	9	of	of	ADP
cana-1616	99	10	entropies	entropy	NOUN
cana-1616	99	11	,	,	PUNCT
cana-1616	99	12	ecfs	ecfs	NOUN
cana-1616	99	13	and	and	CCONJ
cana-1616	99	14	eifs	eifs	PROPN
cana-1616	99	15	and	and	CCONJ
cana-1616	99	16	calculated	calculate	VERB
cana-1616	99	17	their	their	PRON
cana-1616	99	18	average	average	ADJ
cana-1616	99	19	value	value	NOUN
cana-1616	99	20	by	by	ADP
cana-1616	99	21	using	use	VERB
cana-1616	99	22	equation	equation	NOUN
cana-1616	99	23	4	4	NUM
cana-1616	99	24	.	.	PUNCT
cana-1616	100	1	𝑅𝑒𝑙𝑒𝑣𝑎𝑛𝑐𝑒𝑆𝑐𝑜𝑟𝑒	𝑅𝑒𝑙𝑒𝑣𝑎𝑛𝑐𝑒𝑆𝑐𝑜𝑟𝑒	NOUN
cana-1616	100	2	1	1	NUM
cana-1616	100	3	=	=	SYM
cana-1616	100	4	𝐸𝑛𝑡𝑟𝑜𝑝𝑦	𝐸𝑛𝑡𝑟𝑜𝑝𝑦	PROPN
cana-1616	100	5	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-1616	100	6	+	+	CCONJ
cana-1616	100	7	𝐸𝐶𝐹𝑆	𝐸𝐶𝐹𝑆	PROPN
cana-1616	100	8	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-1616	100	9	+	+	CCONJ
cana-1616	100	10	𝐸𝐼𝐹𝑆	𝐸𝐼𝐹𝑆	PROPN
cana-1616	100	11	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-1616	100	12	3	3	NUM
cana-1616	100	13	(	(	PUNCT
cana-1616	100	14	4	4	NUM
cana-1616	100	15	)	)	PUNCT
cana-1616	100	16	wherein	wherein	ADJ
cana-1616	100	17	relevance	relevance	NOUN
cana-1616	100	18	score	score	NOUN
cana-1616	100	19	1	1	NUM
cana-1616	100	20	represents	represent	VERB
cana-1616	100	21	the	the	DET
cana-1616	100	22	feature	feature	NOUN
cana-1616	100	23	set	set	NOUN
cana-1616	100	24	obtained	obtain	VERB
cana-1616	100	25	at	at	ADP
cana-1616	100	26	first	first	ADJ
cana-1616	100	27	stage	stage	NOUN
cana-1616	100	28	of	of	ADP
cana-1616	100	29	fs	fs	PROPN
cana-1616	100	30	.	.	PUNCT
cana-1616	101	1	this	this	DET
cana-1616	101	2	feature	feature	NOUN
cana-1616	101	3	set	set	VERB
cana-1616	101	4	determines	determine	VERB
cana-1616	101	5	the	the	DET
cana-1616	101	6	importance	importance	NOUN
cana-1616	101	7	of	of	ADP
cana-1616	101	8	features	feature	NOUN
cana-1616	101	9	based	base	VERB
cana-1616	101	10	on	on	ADP
cana-1616	101	11	multiple	multiple	ADJ
cana-1616	101	12	criteria	criterion	NOUN
cana-1616	101	13	of	of	ADP
cana-1616	101	14	entropy	entropy	PROPN
cana-1616	101	15	,	,	PUNCT
cana-1616	101	16	ecfs	ecfs	NOUN
cana-1616	101	17	and	and	CCONJ
cana-1616	101	18	eifs	eifs	PROPN
cana-1616	101	19	.	.	PUNCT
cana-1616	102	1	after	after	ADP
cana-1616	102	2	this	this	PRON
cana-1616	102	3	,	,	PUNCT
cana-1616	102	4	the	the	DET
cana-1616	102	5	feature	feature	NOUN
cana-1616	102	6	with	with	ADP
cana-1616	102	7	highest	high	ADJ
cana-1616	102	8	relevance	relevance	NOUN
cana-1616	102	9	scores	score	NOUN
cana-1616	102	10	is	be	AUX
cana-1616	102	11	grouped	group	VERB
cana-1616	102	12	together	together	ADV
cana-1616	102	13	to	to	PART
cana-1616	102	14	form	form	VERB
cana-1616	102	15	an	an	DET
cana-1616	102	16	updated	update	VERB
cana-1616	102	17	feature	feature	NOUN
cana-1616	102	18	list	list	NOUN
cana-1616	102	19	.	.	PUNCT
cana-1616	103	1	it	it	PRON
cana-1616	103	2	must	must	AUX
cana-1616	103	3	be	be	AUX
cana-1616	103	4	noted	note	VERB
cana-1616	103	5	here	here	ADV
cana-1616	103	6	,	,	PUNCT
cana-1616	103	7	that	that	SCONJ
cana-1616	103	8	this	this	DET
cana-1616	103	9	feature	feature	NOUN
cana-1616	103	10	set	set	NOUN
cana-1616	103	11	is	be	AUX
cana-1616	103	12	basically	basically	ADV
cana-1616	103	13	ordering	order	VERB
cana-1616	103	14	the	the	DET
cana-1616	103	15	features	feature	NOUN
cana-1616	103	16	as	as	ADP
cana-1616	103	17	per	per	ADP
cana-1616	103	18	their	their	PRON
cana-1616	103	19	relevance	relevance	NOUN
cana-1616	103	20	scores	score	NOUN
cana-1616	103	21	obtained	obtain	VERB
cana-1616	103	22	by	by	ADP
cana-1616	103	23	using	use	VERB
cana-1616	103	24	equation	equation	NOUN
cana-1616	103	25	5	5	NUM
cana-1616	103	26	.	.	PUNCT
cana-1616	104	1	communications	communication	NOUN
cana-1616	104	2	on	on	ADP
cana-1616	104	3	applied	apply	VERB
cana-1616	104	4	nonlinear	nonlinear	ADJ
cana-1616	104	5	analysis	analysis	NOUN
cana-1616	104	6	issn	issn	NOUN
cana-1616	104	7	:	:	PUNCT
cana-1616	104	8	1074	1074	NUM
cana-1616	104	9	-	-	PUNCT
cana-1616	104	10	133x	133x	NUM
cana-1616	104	11	vol	vol	NOUN
cana-1616	104	12	31	31	NUM
cana-1616	104	13	no	no	NOUN
cana-1616	104	14	.	.	PUNCT
cana-1616	105	1	8s	8s	PROPN
cana-1616	105	2	(	(	PUNCT
cana-1616	105	3	2024	2024	NUM
cana-1616	105	4	)	)	PUNCT
cana-1616	105	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	105	6	779	779	NUM
cana-1616	105	7	stage	stage	NOUN
cana-1616	105	8	2	2	NUM
cana-1616	105	9	of	of	ADP
cana-1616	105	10	fs	f	NOUN
cana-1616	105	11	in	in	ADP
cana-1616	105	12	the	the	DET
cana-1616	105	13	second	second	ADJ
cana-1616	105	14	stage	stage	NOUN
cana-1616	105	15	of	of	ADP
cana-1616	105	16	proposed	propose	VERB
cana-1616	105	17	fs	fs	ADP
cana-1616	105	18	method	method	NOUN
cana-1616	105	19	,	,	PUNCT
cana-1616	105	20	a	a	DET
cana-1616	105	21	ml	ml	NOUN
cana-1616	105	22	classifier	classifier	NOUN
cana-1616	105	23	is	be	AUX
cana-1616	105	24	utilized	utilize	VERB
cana-1616	105	25	for	for	ADP
cana-1616	105	26	calculating	calculate	VERB
cana-1616	105	27	the	the	DET
cana-1616	105	28	weight	weight	NOUN
cana-1616	105	29	of	of	ADP
cana-1616	105	30	features	feature	NOUN
cana-1616	105	31	.	.	PUNCT
cana-1616	106	1	the	the	DET
cana-1616	106	2	main	main	ADJ
cana-1616	106	3	reason	reason	NOUN
cana-1616	106	4	for	for	ADP
cana-1616	106	5	doing	do	VERB
cana-1616	106	6	so	so	ADV
cana-1616	106	7	is	be	AUX
cana-1616	106	8	to	to	PART
cana-1616	106	9	make	make	VERB
cana-1616	106	10	available	available	ADJ
cana-1616	106	11	feature	feature	NOUN
cana-1616	106	12	set	set	VERB
cana-1616	106	13	accuracy	accuracy	NOUN
cana-1616	106	14	dependent	dependent	ADJ
cana-1616	106	15	and	and	CCONJ
cana-1616	106	16	enhance	enhance	VERB
cana-1616	106	17	reliability	reliability	NOUN
cana-1616	106	18	of	of	ADP
cana-1616	106	19	system	system	NOUN
cana-1616	106	20	.	.	PUNCT
cana-1616	107	1	here	here	ADV
cana-1616	107	2	,	,	PUNCT
cana-1616	107	3	we	we	PRON
cana-1616	107	4	have	have	AUX
cana-1616	107	5	used	use	VERB
cana-1616	107	6	random	random	ADJ
cana-1616	107	7	forest	forest	NOUN
cana-1616	107	8	(	(	PUNCT
cana-1616	107	9	rf	rf	NOUN
cana-1616	107	10	)	)	PUNCT
cana-1616	107	11	classifier	classifier	NOUN
cana-1616	107	12	which	which	PRON
cana-1616	107	13	is	be	AUX
cana-1616	107	14	one	one	NUM
cana-1616	107	15	of	of	ADP
cana-1616	107	16	the	the	DET
cana-1616	107	17	widely	widely	ADV
cana-1616	107	18	used	use	VERB
cana-1616	107	19	ml	ml	NOUN
cana-1616	107	20	algorithm	algorithm	NOUN
cana-1616	107	21	that	that	PRON
cana-1616	107	22	can	can	AUX
cana-1616	107	23	be	be	AUX
cana-1616	107	24	used	use	VERB
cana-1616	107	25	for	for	ADP
cana-1616	107	26	both	both	CCONJ
cana-1616	107	27	classification	classification	NOUN
cana-1616	107	28	and	and	CCONJ
cana-1616	107	29	regression	regression	NOUN
cana-1616	107	30	tasks	task	NOUN
cana-1616	107	31	.	.	PUNCT
cana-1616	108	1	the	the	DET
cana-1616	108	2	classifier	classifier	NOUN
cana-1616	108	3	is	be	AUX
cana-1616	108	4	initialized	initialize	VERB
cana-1616	108	5	by	by	ADP
cana-1616	108	6	defining	define	VERB
cana-1616	108	7	the	the	DET
cana-1616	108	8	parameters	parameter	NOUN
cana-1616	108	9	given	give	VERB
cana-1616	108	10	in	in	ADP
cana-1616	108	11	table	table	NOUN
cana-1616	108	12	3	3	NUM
cana-1616	108	13	.	.	PUNCT
cana-1616	108	14	table	table	NOUN
cana-1616	108	15	3	3	NUM
cana-1616	108	16	:	:	PUNCT
cana-1616	108	17	rf	rf	NOUN
cana-1616	108	18	initialization	initialization	NOUN
cana-1616	108	19	parameters	parameter	NOUN
cana-1616	108	20	parameter	parameter	VERB
cana-1616	108	21	values	value	NOUN
cana-1616	108	22	alpha	alpha	NOUN
cana-1616	108	23	0.5	0.5	NUM
cana-1616	108	24	no	no	NOUN
cana-1616	108	25	of	of	ADP
cana-1616	108	26	bagger	bagger	NOUN
cana-1616	108	27	100	100	NUM
cana-1616	108	28	no	no	NOUN
cana-1616	108	29	of	of	ADP
cana-1616	108	30	trees	tree	NOUN
cana-1616	108	31	10	10	NUM
cana-1616	108	32	method	method	NOUN
cana-1616	108	33	to	to	PART
cana-1616	108	34	work	work	VERB
cana-1616	108	35	classification	classification	NOUN
cana-1616	108	36	prediction	prediction	NOUN
cana-1616	108	37	method	method	NOUN
cana-1616	108	38	oob	oob	VERB
cana-1616	108	39	once	once	SCONJ
cana-1616	108	40	the	the	DET
cana-1616	108	41	rf	rf	NOUN
cana-1616	108	42	classifier	classifier	NOUN
cana-1616	108	43	is	be	AUX
cana-1616	108	44	initialized	initialize	VERB
cana-1616	108	45	,	,	PUNCT
cana-1616	108	46	the	the	DET
cana-1616	108	47	ordered	order	VERB
cana-1616	108	48	feature	feature	NOUN
cana-1616	108	49	set	set	NOUN
cana-1616	108	50	formed	form	VERB
cana-1616	108	51	in	in	ADP
cana-1616	108	52	first	first	ADJ
cana-1616	108	53	stage	stage	NOUN
cana-1616	108	54	is	be	AUX
cana-1616	108	55	passed	pass	VERB
cana-1616	108	56	to	to	ADP
cana-1616	108	57	it	it	PRON
cana-1616	108	58	for	for	ADP
cana-1616	108	59	training	training	NOUN
cana-1616	108	60	purpose	purpose	NOUN
cana-1616	108	61	.	.	PUNCT
cana-1616	109	1	the	the	DET
cana-1616	109	2	rf	rf	NOUN
cana-1616	109	3	classifier	classifier	NOUN
cana-1616	109	4	analyzes	analyze	VERB
cana-1616	109	5	features	feature	NOUN
cana-1616	109	6	and	and	CCONJ
cana-1616	109	7	starts	start	NOUN
cana-1616	109	8	getting	getting	AUX
cana-1616	109	9	trained	train	VERB
cana-1616	109	10	by	by	ADP
cana-1616	109	11	employing	employ	VERB
cana-1616	109	12	the	the	DET
cana-1616	109	13	tree	tree	NOUN
cana-1616	109	14	bagger	bagger	NOUN
cana-1616	109	15	function	function	NOUN
cana-1616	109	16	.	.	PUNCT
cana-1616	110	1	after	after	ADP
cana-1616	110	2	this	this	PRON
cana-1616	110	3	,	,	PUNCT
cana-1616	110	4	“	"	PUNCT
cana-1616	110	5	oob	oob	VERB
cana-1616	110	6	”	"	PUNCT
cana-1616	110	7	prediction	prediction	NOUN
cana-1616	110	8	method	method	NOUN
cana-1616	110	9	is	be	AUX
cana-1616	110	10	employed	employ	VERB
cana-1616	110	11	for	for	ADP
cana-1616	110	12	retrieving	retrieve	VERB
cana-1616	110	13	the	the	DET
cana-1616	110	14	feature	feature	NOUN
cana-1616	110	15	scores	score	NOUN
cana-1616	110	16	.	.	PUNCT
cana-1616	111	1	these	these	DET
cana-1616	111	2	scores	score	NOUN
cana-1616	111	3	are	be	AUX
cana-1616	111	4	calculated	calculate	VERB
cana-1616	111	5	based	base	VERB
cana-1616	111	6	on	on	ADP
cana-1616	111	7	out	out	ADP
cana-1616	111	8	-	-	PUNCT
cana-1616	111	9	of	of	ADP
cana-1616	111	10	-	-	PUNCT
cana-1616	111	11	bag	bag	NOUN
cana-1616	111	12	samples	sample	NOUN
cana-1616	111	13	and	and	CCONJ
cana-1616	111	14	are	be	AUX
cana-1616	111	15	a	a	DET
cana-1616	111	16	measure	measure	NOUN
cana-1616	111	17	of	of	ADP
cana-1616	111	18	how	how	SCONJ
cana-1616	111	19	much	much	ADJ
cana-1616	111	20	each	each	DET
cana-1616	111	21	feature	feature	NOUN
cana-1616	111	22	contributes	contribute	VERB
cana-1616	111	23	to	to	ADP
cana-1616	111	24	the	the	DET
cana-1616	111	25	accuracy	accuracy	NOUN
cana-1616	111	26	of	of	ADP
cana-1616	111	27	the	the	DET
cana-1616	111	28	rf	rf	ADJ
cana-1616	111	29	model	model	NOUN
cana-1616	111	30	.	.	PUNCT
cana-1616	112	1	the	the	DET
cana-1616	112	2	process	process	NOUN
cana-1616	112	3	keeps	keep	VERB
cana-1616	112	4	on	on	ADP
cana-1616	112	5	repeating	repeat	VERB
cana-1616	112	6	iteratively	iteratively	ADV
cana-1616	112	7	till	till	SCONJ
cana-1616	112	8	we	we	PRON
cana-1616	112	9	get	get	VERB
cana-1616	112	10	the	the	DET
cana-1616	112	11	best	good	ADJ
cana-1616	112	12	accuracy	accuracy	NOUN
cana-1616	112	13	values	value	NOUN
cana-1616	112	14	.	.	PUNCT
cana-1616	113	1	after	after	ADP
cana-1616	113	2	each	each	DET
cana-1616	113	3	iteration	iteration	NOUN
cana-1616	113	4	,	,	PUNCT
cana-1616	113	5	the	the	DET
cana-1616	113	6	current	current	ADJ
cana-1616	113	7	accuracy	accuracy	NOUN
cana-1616	113	8	value	value	NOUN
cana-1616	113	9	of	of	ADP
cana-1616	113	10	rf	rf	PRON
cana-1616	113	11	is	be	AUX
cana-1616	113	12	compared	compare	VERB
cana-1616	113	13	with	with	ADP
cana-1616	113	14	previous	previous	ADJ
cana-1616	113	15	one	one	NOUN
cana-1616	113	16	and	and	CCONJ
cana-1616	113	17	if	if	SCONJ
cana-1616	113	18	it	it	PRON
cana-1616	113	19	comes	come	VERB
cana-1616	113	20	out	out	ADP
cana-1616	113	21	to	to	PART
cana-1616	113	22	be	be	AUX
cana-1616	113	23	better	well	ADJ
cana-1616	113	24	,	,	PUNCT
cana-1616	113	25	than	than	SCONJ
cana-1616	113	26	accuracy	accuracy	NOUN
cana-1616	113	27	value	value	NOUN
cana-1616	113	28	is	be	AUX
cana-1616	113	29	updated	update	VERB
cana-1616	113	30	,	,	PUNCT
cana-1616	113	31	otherwise	otherwise	ADV
cana-1616	113	32	it	it	PRON
cana-1616	113	33	remains	remain	VERB
cana-1616	113	34	same	same	ADJ
cana-1616	113	35	.	.	PUNCT
cana-1616	114	1	the	the	DET
cana-1616	114	2	equation	equation	NOUN
cana-1616	114	3	for	for	ADP
cana-1616	114	4	updating	update	VERB
cana-1616	114	5	the	the	DET
cana-1616	114	6	relevance	relevance	NOUN
cana-1616	114	7	score	score	NOUN
cana-1616	114	8	of	of	ADP
cana-1616	114	9	features	feature	NOUN
cana-1616	114	10	is	be	AUX
cana-1616	114	11	given	give	VERB
cana-1616	114	12	in	in	ADP
cana-1616	114	13	equation	equation	NOUN
cana-1616	114	14	5	5	NUM
cana-1616	114	15	.	.	NOUN
cana-1616	114	16	𝑅𝑆𝑢	𝑅𝑆𝑢	ADJ
cana-1616	114	17	=	=	SYM
cana-1616	114	18	𝑅𝑆𝑝	𝑅𝑆𝑝	X
cana-1616	114	19	+	+	CCONJ
cana-1616	114	20	𝑁𝑎𝑐𝑐	𝑁𝑎𝑐𝑐	PROPN
cana-1616	114	21	∗	∗	NOUN
cana-1616	114	22	𝐸𝑁𝑤𝑔𝑡	𝐸𝑁𝑤𝑔𝑡	PROPN
cana-1616	114	23	(	(	PUNCT
cana-1616	114	24	5	5	NUM
cana-1616	114	25	)	)	PUNCT
cana-1616	114	26	wherein	wherein	ADJ
cana-1616	114	27	,	,	PUNCT
cana-1616	114	28	rsu	rsu	PROPN
cana-1616	114	29	and	and	CCONJ
cana-1616	114	30	rsp	rsp	PROPN
cana-1616	114	31	represents	represent	VERB
cana-1616	114	32	updated	update	VERB
cana-1616	114	33	relevance	relevance	NOUN
cana-1616	114	34	score	score	NOUN
cana-1616	114	35	and	and	CCONJ
cana-1616	114	36	previous	previous	ADJ
cana-1616	114	37	relevance	relevance	NOUN
cana-1616	114	38	score	score	NOUN
cana-1616	114	39	.	.	PUNCT
cana-1616	115	1	while	while	SCONJ
cana-1616	115	2	as	as	ADP
cana-1616	115	3	,	,	PUNCT
cana-1616	115	4	nacc	nacc	NOUN
cana-1616	115	5	and	and	CCONJ
cana-1616	115	6	enwgt	enwgt	NOUN
cana-1616	115	7	represents	represent	VERB
cana-1616	115	8	the	the	DET
cana-1616	115	9	accuracy	accuracy	NOUN
cana-1616	115	10	and	and	CCONJ
cana-1616	115	11	entropy	entropy	ADV
cana-1616	115	12	-	-	PUNCT
cana-1616	115	13	based	base	VERB
cana-1616	115	14	weights	weight	NOUN
cana-1616	115	15	of	of	ADP
cana-1616	115	16	features	feature	NOUN
cana-1616	115	17	respectively	respectively	ADV
cana-1616	115	18	.	.	PUNCT
cana-1616	116	1	this	this	DET
cana-1616	116	2	rsu	rsu	NOUN
cana-1616	116	3	represents	represent	VERB
cana-1616	116	4	the	the	DET
cana-1616	116	5	second	second	ADJ
cana-1616	116	6	feature	feature	NOUN
cana-1616	116	7	set	set	NOUN
cana-1616	116	8	that	that	PRON
cana-1616	116	9	contains	contain	VERB
cana-1616	116	10	more	more	ADV
cana-1616	116	11	relevant	relevant	ADJ
cana-1616	116	12	and	and	CCONJ
cana-1616	116	13	important	important	ADJ
cana-1616	116	14	features	feature	NOUN
cana-1616	116	15	than	than	ADP
cana-1616	116	16	first	first	ADJ
cana-1616	116	17	feature	feature	NOUN
cana-1616	116	18	subset	subset	NOUN
cana-1616	116	19	.	.	PUNCT
cana-1616	117	1	stage	stage	NOUN
cana-1616	117	2	3	3	NUM
cana-1616	117	3	fs	fs	NOUN
cana-1616	117	4	in	in	ADP
cana-1616	117	5	the	the	DET
cana-1616	117	6	third	third	ADJ
cana-1616	117	7	and	and	CCONJ
cana-1616	117	8	final	final	ADJ
cana-1616	117	9	stage	stage	NOUN
cana-1616	117	10	of	of	ADP
cana-1616	117	11	our	our	PRON
cana-1616	117	12	work	work	NOUN
cana-1616	117	13	,	,	PUNCT
cana-1616	117	14	we	we	PRON
cana-1616	117	15	have	have	AUX
cana-1616	117	16	improved	improve	VERB
cana-1616	117	17	the	the	DET
cana-1616	117	18	rsu	rsu	NOUN
cana-1616	117	19	score	score	NOUN
cana-1616	117	20	further	far	ADV
cana-1616	117	21	by	by	ADP
cana-1616	117	22	making	make	VERB
cana-1616	117	23	it	it	PRON
cana-1616	117	24	dependent	dependent	ADJ
cana-1616	117	25	on	on	ADP
cana-1616	117	26	whole	whole	ADJ
cana-1616	117	27	set	set	NOUN
cana-1616	117	28	of	of	ADP
cana-1616	117	29	features	feature	NOUN
cana-1616	117	30	using	use	VERB
cana-1616	117	31	fuzzy	fuzzy	ADJ
cana-1616	117	32	system	system	NOUN
cana-1616	117	33	.	.	PUNCT
cana-1616	118	1	fuzzy	fuzzy	ADJ
cana-1616	118	2	system	system	NOUN
cana-1616	118	3	is	be	AUX
cana-1616	118	4	a	a	DET
cana-1616	118	5	model	model	NOUN
cana-1616	118	6	wherein	wherein	SCONJ
cana-1616	118	7	a	a	DET
cana-1616	118	8	set	set	NOUN
cana-1616	118	9	of	of	ADP
cana-1616	118	10	features	feature	NOUN
cana-1616	118	11	are	be	AUX
cana-1616	118	12	given	give	VERB
cana-1616	118	13	as	as	ADP
cana-1616	118	14	input	input	NOUN
cana-1616	118	15	to	to	ADP
cana-1616	118	16	the	the	DET
cana-1616	118	17	model	model	NOUN
cana-1616	118	18	which	which	PRON
cana-1616	118	19	are	be	AUX
cana-1616	118	20	then	then	ADV
cana-1616	118	21	evaluated	evaluate	VERB
cana-1616	118	22	by	by	ADP
cana-1616	118	23	per	per	ADP
cana-1616	118	24	some	some	DET
cana-1616	118	25	defined	define	VERB
cana-1616	118	26	rules	rule	NOUN
cana-1616	118	27	to	to	PART
cana-1616	118	28	get	get	VERB
cana-1616	118	29	the	the	DET
cana-1616	118	30	single	single	ADJ
cana-1616	118	31	outcomes	outcome	NOUN
cana-1616	118	32	determining	determine	VERB
cana-1616	118	33	membership	membership	NOUN
cana-1616	118	34	degree	degree	NOUN
cana-1616	118	35	of	of	ADP
cana-1616	118	36	a	a	DET
cana-1616	118	37	feature	feature	NOUN
cana-1616	118	38	.	.	PUNCT
cana-1616	119	1	in	in	ADP
cana-1616	119	2	our	our	PRON
cana-1616	119	3	case	case	NOUN
cana-1616	119	4	,	,	PUNCT
cana-1616	119	5	the	the	DET
cana-1616	119	6	rsu	rsu	NOUN
cana-1616	119	7	feature	feature	NOUN
cana-1616	119	8	weights	weight	NOUN
cana-1616	119	9	serves	serve	VERB
cana-1616	119	10	as	as	ADP
cana-1616	119	11	input	input	NOUN
cana-1616	119	12	to	to	ADP
cana-1616	119	13	the	the	DET
cana-1616	119	14	proposed	propose	VERB
cana-1616	119	15	fuzzy	fuzzy	ADJ
cana-1616	119	16	system	system	NOUN
cana-1616	119	17	,	,	PUNCT
cana-1616	119	18	which	which	PRON
cana-1616	119	19	defines	define	VERB
cana-1616	119	20	membership	membership	NOUN
cana-1616	119	21	functions	function	NOUN
cana-1616	119	22	of	of	ADP
cana-1616	119	23	features	feature	NOUN
cana-1616	119	24	weights	weight	NOUN
cana-1616	119	25	based	base	VERB
cana-1616	119	26	on	on	ADP
cana-1616	119	27	their	their	PRON
cana-1616	119	28	minimum	minimum	ADJ
cana-1616	119	29	,	,	PUNCT
cana-1616	119	30	maximum	maximum	ADJ
cana-1616	119	31	and	and	CCONJ
cana-1616	119	32	mean	mean	ADJ
cana-1616	119	33	values	value	NOUN
cana-1616	119	34	to	to	PART
cana-1616	119	35	introduce	introduce	VERB
cana-1616	119	36	contextual	contextual	ADJ
cana-1616	119	37	relevance	relevance	NOUN
cana-1616	119	38	among	among	ADP
cana-1616	119	39	features	feature	NOUN
cana-1616	119	40	.	.	PUNCT
cana-1616	120	1	this	this	PRON
cana-1616	120	2	signifies	signify	VERB
cana-1616	120	3	that	that	SCONJ
cana-1616	120	4	membership	membership	NOUN
cana-1616	120	5	functions	function	NOUN
cana-1616	120	6	are	be	AUX
cana-1616	120	7	sensitive	sensitive	ADJ
cana-1616	120	8	to	to	ADP
cana-1616	120	9	overall	overall	ADJ
cana-1616	120	10	distribution	distribution	NOUN
cana-1616	120	11	and	and	CCONJ
cana-1616	120	12	spread	spread	VERB
cana-1616	120	13	of	of	ADP
cana-1616	120	14	feature	feature	NOUN
cana-1616	120	15	weights	weight	NOUN
cana-1616	120	16	.	.	PUNCT
cana-1616	121	1	this	this	PRON
cana-1616	121	2	means	mean	VERB
cana-1616	121	3	that	that	SCONJ
cana-1616	121	4	features	feature	VERB
cana-1616	121	5	with	with	ADP
cana-1616	121	6	significantly	significantly	ADV
cana-1616	121	7	different	different	ADJ
cana-1616	121	8	weights	weight	NOUN
cana-1616	121	9	than	than	SCONJ
cana-1616	121	10	mean	mean	VERB
cana-1616	121	11	or	or	CCONJ
cana-1616	121	12	close	close	ADJ
cana-1616	121	13	to	to	ADP
cana-1616	121	14	min	min	NOUN
cana-1616	121	15	or	or	CCONJ
cana-1616	121	16	max	max	PROPN
cana-1616	121	17	values	value	NOUN
cana-1616	121	18	will	will	AUX
cana-1616	121	19	receive	receive	VERB
cana-1616	121	20	distinctive	distinctive	ADJ
cana-1616	121	21	membership	membership	NOUN
cana-1616	121	22	scores	score	NOUN
cana-1616	121	23	to	to	PART
cana-1616	121	24	depict	depict	VERB
cana-1616	121	25	their	their	PRON
cana-1616	121	26	relevancy	relevancy	NOUN
cana-1616	121	27	.	.	PUNCT
cana-1616	122	1	moreover	moreover	ADV
cana-1616	122	2	,	,	PUNCT
cana-1616	122	3	another	another	DET
cana-1616	122	4	reason	reason	NOUN
cana-1616	122	5	for	for	ADP
cana-1616	122	6	introducing	introduce	VERB
cana-1616	122	7	fuzzy	fuzzy	ADJ
cana-1616	122	8	in	in	ADP
cana-1616	122	9	our	our	PRON
cana-1616	122	10	work	work	NOUN
cana-1616	122	11	is	be	AUX
cana-1616	122	12	to	to	PART
cana-1616	122	13	handle	handle	VERB
cana-1616	122	14	uncertainties	uncertainty	NOUN
cana-1616	122	15	or	or	CCONJ
cana-1616	122	16	noises	noise	NOUN
cana-1616	122	17	present	present	ADJ
cana-1616	122	18	in	in	ADP
cana-1616	122	19	datasets	dataset	NOUN
cana-1616	122	20	.	.	PUNCT
cana-1616	123	1	the	the	DET
cana-1616	123	2	fuzzy	fuzzy	ADJ
cana-1616	123	3	model	model	NOUN
cana-1616	123	4	allows	allow	VERB
cana-1616	123	5	features	feature	NOUN
cana-1616	123	6	to	to	PART
cana-1616	123	7	have	have	VERB
cana-1616	123	8	partial	partial	ADJ
cana-1616	123	9	membership	membership	NOUN
cana-1616	123	10	in	in	ADP
cana-1616	123	11	multiple	multiple	ADJ
cana-1616	123	12	membership	membership	NOUN
cana-1616	123	13	functions	function	NOUN
cana-1616	123	14	to	to	PART
cana-1616	123	15	receive	receive	VERB
cana-1616	123	16	communications	communication	NOUN
cana-1616	123	17	on	on	ADP
cana-1616	123	18	applied	apply	VERB
cana-1616	123	19	nonlinear	nonlinear	ADJ
cana-1616	123	20	analysis	analysis	NOUN
cana-1616	123	21	issn	issn	NOUN
cana-1616	123	22	:	:	PUNCT
cana-1616	123	23	1074	1074	NUM
cana-1616	123	24	-	-	PUNCT
cana-1616	123	25	133x	133x	NUM
cana-1616	123	26	vol	vol	NOUN
cana-1616	123	27	31	31	NUM
cana-1616	123	28	no	no	NOUN
cana-1616	123	29	.	.	PUNCT
cana-1616	124	1	8s	8s	PROPN
cana-1616	124	2	(	(	PUNCT
cana-1616	124	3	2024	2024	NUM
cana-1616	124	4	)	)	PUNCT
cana-1616	124	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	124	6	780	780	NUM
cana-1616	124	7	a	a	DET
cana-1616	124	8	moderate	moderate	ADJ
cana-1616	124	9	membership	membership	NOUN
cana-1616	124	10	score	score	NOUN
cana-1616	124	11	,	,	PUNCT
cana-1616	124	12	even	even	ADV
cana-1616	124	13	if	if	SCONJ
cana-1616	124	14	its	its	PRON
cana-1616	124	15	weight	weight	NOUN
cana-1616	124	16	is	be	AUX
cana-1616	124	17	extremely	extremely	ADV
cana-1616	124	18	low	low	ADJ
cana-1616	124	19	or	or	CCONJ
cana-1616	124	20	high	high	ADJ
cana-1616	124	21	.	.	PUNCT
cana-1616	125	1	in	in	ADP
cana-1616	125	2	other	other	ADJ
cana-1616	125	3	words	word	NOUN
cana-1616	125	4	,	,	PUNCT
cana-1616	125	5	we	we	PRON
cana-1616	125	6	can	can	AUX
cana-1616	125	7	say	say	VERB
cana-1616	125	8	that	that	SCONJ
cana-1616	125	9	,	,	PUNCT
cana-1616	125	10	fuzzy	fuzzy	ADJ
cana-1616	125	11	system	system	NOUN
cana-1616	125	12	enhances	enhance	VERB
cana-1616	125	13	feature	feature	NOUN
cana-1616	125	14	weighting	weighting	NOUN
cana-1616	125	15	by	by	ADP
cana-1616	125	16	incorporating	incorporate	VERB
cana-1616	125	17	context	context	NOUN
cana-1616	125	18	and	and	CCONJ
cana-1616	125	19	uncertainty	uncertainty	NOUN
cana-1616	125	20	into	into	ADP
cana-1616	125	21	the	the	DET
cana-1616	125	22	process	process	NOUN
cana-1616	125	23	.	.	PUNCT
cana-1616	126	1	it	it	PRON
cana-1616	126	2	considers	consider	VERB
cana-1616	126	3	how	how	SCONJ
cana-1616	126	4	each	each	DET
cana-1616	126	5	feature	feature	NOUN
cana-1616	126	6	's	's	PART
cana-1616	126	7	weight	weight	NOUN
cana-1616	126	8	relates	relate	VERB
cana-1616	126	9	to	to	ADP
cana-1616	126	10	the	the	DET
cana-1616	126	11	distribution	distribution	NOUN
cana-1616	126	12	of	of	ADP
cana-1616	126	13	weights	weight	NOUN
cana-1616	126	14	across	across	ADP
cana-1616	126	15	all	all	DET
cana-1616	126	16	features	feature	NOUN
cana-1616	126	17	,	,	PUNCT
cana-1616	126	18	resulting	result	VERB
cana-1616	126	19	in	in	ADP
cana-1616	126	20	a	a	DET
cana-1616	126	21	more	more	ADV
cana-1616	126	22	context	context	NOUN
cana-1616	126	23	-	-	PUNCT
cana-1616	126	24	aware	aware	ADJ
cana-1616	126	25	and	and	CCONJ
cana-1616	126	26	interpretable	interpretable	ADJ
cana-1616	126	27	evaluation	evaluation	NOUN
cana-1616	126	28	of	of	ADP
cana-1616	126	29	feature	feature	NOUN
cana-1616	126	30	importance	importance	NOUN
cana-1616	126	31	.	.	PUNCT
cana-1616	127	1	this	this	PRON
cana-1616	127	2	can	can	AUX
cana-1616	127	3	lead	lead	VERB
cana-1616	127	4	to	to	ADP
cana-1616	127	5	more	more	ADV
cana-1616	127	6	meaningful	meaningful	ADJ
cana-1616	127	7	and	and	CCONJ
cana-1616	127	8	reliable	reliable	ADJ
cana-1616	127	9	feature	feature	NOUN
cana-1616	127	10	selection	selection	NOUN
cana-1616	127	11	,	,	PUNCT
cana-1616	127	12	particularly	particularly	ADV
cana-1616	127	13	in	in	ADP
cana-1616	127	14	situations	situation	NOUN
cana-1616	127	15	where	where	SCONJ
cana-1616	127	16	the	the	DET
cana-1616	127	17	importance	importance	NOUN
cana-1616	127	18	of	of	ADP
cana-1616	127	19	features	feature	NOUN
cana-1616	127	20	may	may	AUX
cana-1616	127	21	vary	vary	VERB
cana-1616	127	22	or	or	CCONJ
cana-1616	127	23	is	be	AUX
cana-1616	127	24	difficult	difficult	ADJ
cana-1616	127	25	to	to	PART
cana-1616	127	26	determine	determine	VERB
cana-1616	127	27	using	use	VERB
cana-1616	127	28	traditional	traditional	ADJ
cana-1616	127	29	methods	method	NOUN
cana-1616	127	30	.	.	PUNCT
cana-1616	128	1	the	the	DET
cana-1616	128	2	fuzzy	fuzzy	ADJ
cana-1616	128	3	system	system	NOUN
cana-1616	128	4	starts	start	VERB
cana-1616	128	5	evaluating	evaluate	VERB
cana-1616	128	6	each	each	DET
cana-1616	128	7	feature	feature	NOUN
cana-1616	128	8	weight	weight	NOUN
cana-1616	128	9	as	as	ADP
cana-1616	128	10	per	per	ADP
cana-1616	128	11	the	the	DET
cana-1616	128	12	value	value	NOUN
cana-1616	128	13	of	of	ADP
cana-1616	128	14	membership	membership	NOUN
cana-1616	128	15	functions	function	NOUN
cana-1616	128	16	to	to	PART
cana-1616	128	17	obtain	obtain	VERB
cana-1616	128	18	a	a	DET
cana-1616	128	19	single	single	ADJ
cana-1616	128	20	output	output	NOUN
cana-1616	128	21	of	of	ADP
cana-1616	128	22	membership	membership	NOUN
cana-1616	128	23	score	score	NOUN
cana-1616	128	24	.	.	PUNCT
cana-1616	129	1	the	the	DET
cana-1616	129	2	value	value	NOUN
cana-1616	129	3	of	of	ADP
cana-1616	129	4	this	this	DET
cana-1616	129	5	membership	membership	NOUN
cana-1616	129	6	score	score	NOUN
cana-1616	129	7	ranges	range	VERB
cana-1616	129	8	from	from	ADP
cana-1616	129	9	0	0	NUM
cana-1616	129	10	to	to	ADP
cana-1616	129	11	1	1	NUM
cana-1616	129	12	,	,	PUNCT
cana-1616	129	13	which	which	PRON
cana-1616	129	14	determines	determine	VERB
cana-1616	129	15	the	the	DET
cana-1616	129	16	importance	importance	NOUN
cana-1616	129	17	or	or	CCONJ
cana-1616	129	18	relevancy	relevancy	NOUN
cana-1616	129	19	of	of	ADP
cana-1616	129	20	each	each	DET
cana-1616	129	21	feature	feature	NOUN
cana-1616	129	22	with	with	ADP
cana-1616	129	23	previous	previous	ADJ
cana-1616	129	24	feature	feature	NOUN
cana-1616	129	25	sets	set	NOUN
cana-1616	129	26	.	.	PUNCT
cana-1616	130	1	after	after	ADP
cana-1616	130	2	this	this	PRON
cana-1616	130	3	,	,	PUNCT
cana-1616	130	4	the	the	DET
cana-1616	130	5	feature	feature	NOUN
cana-1616	130	6	weights	weight	NOUN
cana-1616	130	7	were	be	AUX
cana-1616	130	8	combined	combine	VERB
cana-1616	130	9	with	with	ADP
cana-1616	130	10	the	the	DET
cana-1616	130	11	previous	previous	ADJ
cana-1616	130	12	feature	feature	NOUN
cana-1616	130	13	set	set	VERB
cana-1616	130	14	to	to	PART
cana-1616	130	15	get	get	VERB
cana-1616	130	16	the	the	DET
cana-1616	130	17	final	final	ADJ
cana-1616	130	18	set	set	NOUN
cana-1616	130	19	.	.	PUNCT
cana-1616	131	1	for	for	ADP
cana-1616	131	2	this	this	PRON
cana-1616	131	3	,	,	PUNCT
cana-1616	131	4	each	each	PRON
cana-1616	131	5	features	feature	VERB
cana-1616	131	6	membership	membership	NOUN
cana-1616	131	7	score	score	NOUN
cana-1616	131	8	is	be	AUX
cana-1616	131	9	multiplied	multiply	VERB
cana-1616	131	10	by	by	ADP
cana-1616	131	11	corresponding	correspond	VERB
cana-1616	131	12	feature	feature	NOUN
cana-1616	131	13	weight	weight	NOUN
cana-1616	131	14	obtained	obtain	VERB
cana-1616	131	15	in	in	ADP
cana-1616	131	16	previous	previous	ADJ
cana-1616	131	17	step	step	NOUN
cana-1616	131	18	.	.	PUNCT
cana-1616	132	1	therefore	therefore	ADV
cana-1616	132	2	,	,	PUNCT
cana-1616	132	3	the	the	DET
cana-1616	132	4	final	final	ADJ
cana-1616	132	5	feature	feature	NOUN
cana-1616	132	6	weights	weight	NOUN
cana-1616	132	7	are	be	AUX
cana-1616	132	8	obtained	obtain	VERB
cana-1616	132	9	by	by	ADP
cana-1616	132	10	using	use	VERB
cana-1616	132	11	equation	equation	NOUN
cana-1616	132	12	6	6	NUM
cana-1616	132	13	.	.	PUNCT
cana-1616	133	1	𝐹𝑒𝑎𝑡𝑢𝑟𝑒	𝐹𝑒𝑎𝑡𝑢𝑟𝑒	VERB
cana-1616	133	2	𝑊𝑒𝑖𝑔ℎ𝑡	𝑊𝑒𝑖𝑔ℎ𝑡	PROPN
cana-1616	133	3	=	=	PUNCT
cana-1616	133	4	𝑚𝑒𝑚𝑏𝑒𝑟𝑠ℎ𝑖𝑝	𝑚𝑒𝑚𝑏𝑒𝑟𝑠ℎ𝑖𝑝	ADJ
cana-1616	133	5	𝑑𝑒𝑔𝑟𝑒𝑒	𝑑𝑒𝑔𝑟𝑒𝑒	NOUN
cana-1616	133	6	𝑜𝑟	𝑜𝑟	ADP
cana-1616	133	7	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-1616	133	8	×	×	NOUN
cana-1616	133	9	𝑓𝑒𝑎𝑡𝑢𝑟𝑒	𝑓𝑒𝑎𝑡𝑢𝑟𝑒	NOUN
cana-1616	133	10	𝑤𝑒𝑖𝑔ℎ𝑡𝑠	𝑤𝑒𝑖𝑔ℎ𝑡𝑠	NOUN
cana-1616	133	11	𝑜𝑓	𝑜𝑓	ADP
cana-1616	133	12	𝑅𝑆𝑢	𝑅𝑆𝑢	NOUN
cana-1616	133	13	(	(	PUNCT
cana-1616	133	14	6	6	NUM
cana-1616	133	15	)	)	PUNCT
cana-1616	133	16	this	this	DET
cana-1616	133	17	feature	feature	NOUN
cana-1616	133	18	weight	weight	NOUN
cana-1616	133	19	depicts	depict	VERB
cana-1616	133	20	the	the	DET
cana-1616	133	21	final	final	ADJ
cana-1616	133	22	score	score	NOUN
cana-1616	133	23	of	of	ADP
cana-1616	133	24	features	feature	NOUN
cana-1616	133	25	but	but	CCONJ
cana-1616	133	26	they	they	PRON
cana-1616	133	27	are	be	AUX
cana-1616	133	28	not	not	PART
cana-1616	133	29	selected	select	VERB
cana-1616	133	30	entirely	entirely	ADV
cana-1616	133	31	in	in	ADP
cana-1616	133	32	the	the	DET
cana-1616	133	33	proposed	propose	VERB
cana-1616	133	34	model	model	NOUN
cana-1616	133	35	.	.	PUNCT
cana-1616	134	1	instead	instead	ADV
cana-1616	134	2	,	,	PUNCT
cana-1616	134	3	we	we	PRON
cana-1616	134	4	have	have	AUX
cana-1616	134	5	set	set	VERB
cana-1616	134	6	a	a	DET
cana-1616	134	7	threshold	threshold	NOUN
cana-1616	134	8	value	value	NOUN
cana-1616	134	9	of	of	ADP
cana-1616	134	10	0.7	0.7	NUM
cana-1616	134	11	,	,	PUNCT
cana-1616	134	12	which	which	PRON
cana-1616	134	13	acts	act	VERB
cana-1616	134	14	as	as	ADP
cana-1616	134	15	a	a	DET
cana-1616	134	16	filter	filter	NOUN
cana-1616	134	17	for	for	ADP
cana-1616	134	18	selecting	select	VERB
cana-1616	134	19	final	final	ADJ
cana-1616	134	20	features	feature	NOUN
cana-1616	134	21	.	.	PUNCT
cana-1616	135	1	the	the	DET
cana-1616	135	2	value	value	NOUN
cana-1616	135	3	of	of	ADP
cana-1616	135	4	threshold	threshold	NOUN
cana-1616	135	5	is	be	AUX
cana-1616	135	6	0.7	0.7	NUM
cana-1616	135	7	because	because	SCONJ
cana-1616	135	8	we	we	PRON
cana-1616	135	9	have	have	AUX
cana-1616	135	10	observed	observe	VERB
cana-1616	135	11	from	from	ADP
cana-1616	135	12	literature	literature	NOUN
cana-1616	135	13	survey	survey	NOUN
cana-1616	135	14	that	that	SCONJ
cana-1616	135	15	the	the	DET
cana-1616	135	16	feature	feature	NOUN
cana-1616	135	17	should	should	AUX
cana-1616	135	18	have	have	VERB
cana-1616	135	19	at	at	ADV
cana-1616	135	20	least	least	ADJ
cana-1616	135	21	70	70	NUM
cana-1616	135	22	%	%	NOUN
cana-1616	135	23	relevancy	relevancy	NOUN
cana-1616	135	24	for	for	ADP
cana-1616	135	25	predicting	predict	VERB
cana-1616	135	26	the	the	DET
cana-1616	135	27	liver	liver	NOUN
cana-1616	135	28	disease	disease	NOUN
cana-1616	135	29	with	with	ADP
cana-1616	135	30	high	high	ADJ
cana-1616	135	31	accuracy	accuracy	NOUN
cana-1616	135	32	.	.	PUNCT
cana-1616	136	1	the	the	DET
cana-1616	136	2	feature	feature	NOUN
cana-1616	136	3	weight	weight	NOUN
cana-1616	136	4	obtained	obtain	VERB
cana-1616	136	5	in	in	ADP
cana-1616	136	6	equation	equation	NOUN
cana-1616	136	7	6	6	NUM
cana-1616	136	8	are	be	AUX
cana-1616	136	9	then	then	ADV
cana-1616	136	10	analyzed	analyze	VERB
cana-1616	136	11	based	base	VERB
cana-1616	136	12	on	on	ADP
cana-1616	136	13	this	this	DET
cana-1616	136	14	threshold	threshold	NOUN
cana-1616	136	15	value	value	NOUN
cana-1616	136	16	and	and	CCONJ
cana-1616	136	17	only	only	ADV
cana-1616	136	18	those	those	DET
cana-1616	136	19	features	feature	NOUN
cana-1616	136	20	having	have	VERB
cana-1616	136	21	relevancy	relevancy	NOUN
cana-1616	136	22	more	more	ADJ
cana-1616	136	23	than	than	ADP
cana-1616	136	24	0.7	0.7	NUM
cana-1616	136	25	are	be	AUX
cana-1616	136	26	selected	select	VERB
cana-1616	136	27	,	,	PUNCT
cana-1616	136	28	rest	rest	NOUN
cana-1616	136	29	are	be	AUX
cana-1616	136	30	discarded	discard	VERB
cana-1616	136	31	.	.	PUNCT
cana-1616	137	1	equation	equation	NOUN
cana-1616	137	2	7	7	NUM
cana-1616	137	3	shows	show	VERB
cana-1616	137	4	the	the	DET
cana-1616	137	5	mathematical	mathematical	ADJ
cana-1616	137	6	equation	equation	NOUN
cana-1616	137	7	for	for	ADP
cana-1616	137	8	selecting	select	VERB
cana-1616	137	9	the	the	DET
cana-1616	137	10	final	final	ADJ
cana-1616	137	11	features	feature	NOUN
cana-1616	137	12	in	in	ADP
cana-1616	137	13	proposed	propose	VERB
cana-1616	137	14	model	model	NOUN
cana-1616	137	15	.	.	PUNCT
cana-1616	138	1	𝐹𝑓𝑒𝑎𝑡𝑆𝑒𝑡	𝐹𝑓𝑒𝑎𝑡𝑆𝑒𝑡	PROPN
cana-1616	138	2	=	=	SYM
cana-1616	138	3	𝐹𝑒𝑡𝑢𝑟𝑒	𝐹𝑒𝑡𝑢𝑟𝑒	PROPN
cana-1616	138	4	𝑊𝑒𝑖𝑔ℎ𝑡	𝑊𝑒𝑖𝑔ℎ𝑡	PROPN
cana-1616	138	5	>	>	X
cana-1616	138	6	𝑡ℎ𝑒𝑟𝑠ℎ𝑜𝑙𝑑	𝑡ℎ𝑒𝑟𝑠ℎ𝑜𝑙𝑑	NOUN
cana-1616	138	7	0.7	0.7	NUM
cana-1616	138	8	(	(	PUNCT
cana-1616	138	9	7	7	NUM
cana-1616	138	10	)	)	PUNCT
cana-1616	138	11	wherein	wherein	NOUN
cana-1616	138	12	,	,	PUNCT
cana-1616	138	13	ffeatset	ffeatset	NOUN
cana-1616	138	14	represents	represent	VERB
cana-1616	138	15	the	the	DET
cana-1616	138	16	final	final	ADJ
cana-1616	138	17	feature	feature	NOUN
cana-1616	138	18	set	set	NOUN
cana-1616	138	19	obtained	obtain	VERB
cana-1616	138	20	after	after	ADP
cana-1616	138	21	processing	process	VERB
cana-1616	138	22	it	it	PRON
cana-1616	138	23	through	through	ADP
cana-1616	138	24	three	three	NUM
cana-1616	138	25	stages	stage	NOUN
cana-1616	138	26	of	of	ADP
cana-1616	138	27	selection	selection	NOUN
cana-1616	138	28	.	.	PUNCT
cana-1616	139	1	this	this	DET
cana-1616	139	2	final	final	ADJ
cana-1616	139	3	feature	feature	NOUN
cana-1616	139	4	set	set	NOUN
cana-1616	139	5	is	be	AUX
cana-1616	139	6	then	then	ADV
cana-1616	139	7	passed	pass	VERB
cana-1616	139	8	to	to	PART
cana-1616	139	9	classifier	classifier	VERB
cana-1616	139	10	for	for	ADP
cana-1616	139	11	making	make	VERB
cana-1616	139	12	the	the	DET
cana-1616	139	13	final	final	ADJ
cana-1616	139	14	prediction	prediction	NOUN
cana-1616	139	15	regarding	regard	VERB
cana-1616	139	16	the	the	DET
cana-1616	139	17	presence	presence	NOUN
cana-1616	139	18	or	or	CCONJ
cana-1616	139	19	absence	absence	NOUN
cana-1616	139	20	of	of	ADP
cana-1616	139	21	liver	liver	NOUN
cana-1616	139	22	disease	disease	NOUN
cana-1616	139	23	among	among	ADP
cana-1616	139	24	patients	patient	NOUN
cana-1616	139	25	.	.	PUNCT
cana-1616	140	1	the	the	DET
cana-1616	140	2	process	process	NOUN
cana-1616	140	3	of	of	ADP
cana-1616	140	4	proposed	propose	VERB
cana-1616	140	5	feature	feature	NOUN
cana-1616	140	6	selection	selection	NOUN
cana-1616	140	7	is	be	AUX
cana-1616	140	8	defined	define	VERB
cana-1616	140	9	in	in	ADP
cana-1616	140	10	algorithm	algorithm	NOUN
cana-1616	140	11	1	1	NUM
cana-1616	140	12	.	.	PUNCT
cana-1616	141	1	algorithm	algorithm	NOUN
cana-1616	141	2	1	1	NUM
cana-1616	141	3	:	:	PUNCT
cana-1616	141	4	feature	feature	NOUN
cana-1616	141	5	selection	selection	NOUN
cana-1616	141	6	process	process	NOUN
cana-1616	141	7	input	input	NOUN
cana-1616	141	8	•	•	NOUN
cana-1616	141	9	training	training	NOUN
cana-1616	141	10	dataset	dataset	VERB
cana-1616	141	11	with	with	ADP
cana-1616	141	12	features	feature	NOUN
cana-1616	141	13	and	and	CCONJ
cana-1616	141	14	labels	label	NOUN
cana-1616	141	15	•	•	ADP
cana-1616	141	16	set	set	VERB
cana-1616	141	17	parameters	parameter	NOUN
cana-1616	141	18	like	like	ADP
cana-1616	141	19	alpha	alpha	NOUN
cana-1616	141	20	for	for	ADP
cana-1616	141	21	ecfs	ecfs	NOUN
cana-1616	141	22	and	and	CCONJ
cana-1616	141	23	eifs	eifs	PROPN
cana-1616	141	24	calculate	calculate	NOUN
cana-1616	141	25	relevance	relevance	NOUN
cana-1616	141	26	score	score	NOUN
cana-1616	141	27	•	•	NUM
cana-1616	141	28	calculate	calculate	NOUN
cana-1616	141	29	entropy	entropy	NOUN
cana-1616	141	30	of	of	ADP
cana-1616	141	31	feature	feature	NOUN
cana-1616	141	32	h(f	h(f	PROPN
cana-1616	141	33	)	)	PUNCT
cana-1616	141	34	by	by	ADP
cana-1616	141	35	using	use	VERB
cana-1616	141	36	below	below	ADP
cana-1616	141	37	equation	equation	NOUN
cana-1616	141	38	𝐻(𝑓	𝐻(𝑓	ADV
cana-1616	141	39	)	)	PUNCT
cana-1616	141	40	=	=	SYM
cana-1616	141	41	∑	∑	PUNCT
cana-1616	141	42	𝑝𝑖	𝑝𝑖	PROPN
cana-1616	141	43	log2	log2	PROPN
cana-1616	141	44	𝑝𝑖	𝑝𝑖	PROPN
cana-1616	141	45	𝑛	𝑛	PROPN
cana-1616	141	46	𝑖=1	𝑖=1	PROPN
cana-1616	141	47	•	•	NUM
cana-1616	141	48	rank	rank	PROPN
cana-1616	141	49	h(f	h(f	PROPN
cana-1616	141	50	)	)	PUNCT
cana-1616	141	51	features	feature	VERB
cana-1616	141	52	in	in	ADP
cana-1616	141	53	descending	descend	VERB
cana-1616	141	54	order	order	NOUN
cana-1616	141	55	of	of	ADP
cana-1616	141	56	their	their	PRON
cana-1616	141	57	entropy	entropy	NOUN
cana-1616	141	58	values	value	NOUN
cana-1616	141	59	calculate	calculate	VERB
cana-1616	141	60	relevance	relevance	NOUN
cana-1616	141	61	score	score	NOUN
cana-1616	141	62	by	by	ADP
cana-1616	141	63	ecfs	ecfs	PROPN
cana-1616	141	64	communications	communication	NOUN
cana-1616	141	65	on	on	ADP
cana-1616	141	66	applied	apply	VERB
cana-1616	141	67	nonlinear	nonlinear	ADJ
cana-1616	141	68	analysis	analysis	NOUN
cana-1616	141	69	issn	issn	NOUN
cana-1616	141	70	:	:	PUNCT
cana-1616	141	71	1074	1074	NUM
cana-1616	141	72	-	-	PUNCT
cana-1616	141	73	133x	133x	NUM
cana-1616	141	74	vol	vol	NOUN
cana-1616	141	75	31	31	NUM
cana-1616	141	76	no	no	NOUN
cana-1616	141	77	.	.	PUNCT
cana-1616	142	1	8s	8s	PROPN
cana-1616	142	2	(	(	PUNCT
cana-1616	142	3	2024	2024	NUM
cana-1616	142	4	)	)	PUNCT
cana-1616	142	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	142	6	781	781	NUM
cana-1616	142	7	•	•	NUM
cana-1616	142	8	calculate	calculate	NOUN
cana-1616	142	9	ec	ec	PROPN
cana-1616	142	10	of	of	ADP
cana-1616	142	11	features	feature	NOUN
cana-1616	142	12	by	by	ADP
cana-1616	142	13	using	use	VERB
cana-1616	142	14	ecfs	ecfs	PROPN
cana-1616	142	15	method	method	NOUN
cana-1616	142	16	𝑥𝑣	𝑥𝑣	PROPN
cana-1616	142	17	=	=	SYM
cana-1616	142	18	1	1	NUM
cana-1616	142	19	𝜆	𝜆	NOUN
cana-1616	142	20	∑	∑	PUNCT
cana-1616	142	21	𝑥𝑡	𝑥𝑡	ADP
cana-1616	142	22	𝑡∈𝑀(𝑣	𝑡∈𝑀(𝑣	NOUN
cana-1616	142	23	)	)	PUNCT
cana-1616	142	24	=	=	SYM
cana-1616	142	25	1	1	NUM
cana-1616	142	26	𝜆	𝜆	DET
cana-1616	142	27	∑	∑	PROPN
cana-1616	142	28	𝑎𝑣,𝑡	𝑎𝑣,𝑡	X
cana-1616	142	29	𝑡∈𝐺	𝑡∈𝐺	X
cana-1616	142	30	𝑥𝑡	𝑥𝑡	ADP
cana-1616	142	31	entropy	entropy	NOUN
cana-1616	142	32	-	-	PUNCT
cana-1616	142	33	correlation	correlation	NOUN
cana-1616	142	34	based	base	VERB
cana-1616	142	35	ifs	ifs	PROPN
cana-1616	142	36	•	•	ADP
cana-1616	142	37	calculate	calculate	VERB
cana-1616	142	38	the	the	DET
cana-1616	142	39	relevance	relevance	NOUN
cana-1616	142	40	score	score	NOUN
cana-1616	142	41	of	of	ADP
cana-1616	142	42	features	feature	NOUN
cana-1616	142	43	by	by	ADP
cana-1616	142	44	using	use	VERB
cana-1616	142	45	eifs	eifs	PROPN
cana-1616	142	46	𝐼	𝐼	PROPN
cana-1616	142	47	=	=	PUNCT
cana-1616	142	48	∑	∑	PROPN
cana-1616	142	49	∑	∑	PUNCT
cana-1616	142	50	𝑝(𝑥	𝑝(𝑥	PROPN
cana-1616	142	51	,	,	PUNCT
cana-1616	142	52	𝑦	𝑦	NOUN
cana-1616	142	53	)	)	PUNCT
cana-1616	142	54	log2	log2	PROPN
cana-1616	142	55	(	(	PUNCT
cana-1616	142	56	𝑝(𝑥	𝑝(𝑥	PROPN
cana-1616	142	57	,	,	PUNCT
cana-1616	142	58	𝑦	𝑦	NOUN
cana-1616	142	59	)	)	PUNCT
cana-1616	142	60	𝑝(𝑥)𝑝(𝑦	𝑝(𝑥)𝑝(𝑦	NOUN
cana-1616	142	61	)	)	PUNCT
cana-1616	142	62	)	)	PUNCT
cana-1616	143	1	𝑦∈𝑌𝑥∈𝑋	𝑦∈𝑌𝑥∈𝑋	NOUN
cana-1616	143	2	update	update	NOUN
cana-1616	143	3	relevance	relevance	NOUN
cana-1616	143	4	score	score	NOUN
cana-1616	143	5	•	•	NUM
cana-1616	143	6	relevance	relevance	NOUN
cana-1616	143	7	score	score	NOUN
cana-1616	143	8	of	of	ADP
cana-1616	143	9	features	feature	NOUN
cana-1616	143	10	is	be	AUX
cana-1616	143	11	updated	update	VERB
cana-1616	143	12	by	by	ADP
cana-1616	143	13	using	use	VERB
cana-1616	143	14	below	below	ADP
cana-1616	143	15	equation	equation	NOUN
cana-1616	143	16	𝑅𝑒𝑙𝑒𝑣𝑎𝑛𝑐𝑒𝑆𝑐𝑜𝑟𝑒	𝑅𝑒𝑙𝑒𝑣𝑎𝑛𝑐𝑒𝑆𝑐𝑜𝑟𝑒	NOUN
cana-1616	143	17	1	1	NUM
cana-1616	143	18	=	=	SYM
cana-1616	143	19	𝐸𝑛𝑡𝑟𝑜𝑝𝑦	𝐸𝑛𝑡𝑟𝑜𝑝𝑦	PROPN
cana-1616	143	20	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-1616	143	21	+	+	CCONJ
cana-1616	143	22	𝐸𝐶𝐹𝑆	𝐸𝐶𝐹𝑆	PROPN
cana-1616	143	23	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-1616	143	24	+	+	CCONJ
cana-1616	143	25	𝐸𝐼𝐹𝑆	𝐸𝐼𝐹𝑆	PROPN
cana-1616	143	26	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-1616	143	27	3	3	NUM
cana-1616	143	28	iterative	iterative	NOUN
cana-1616	143	29	feature	feature	NOUN
cana-1616	143	30	selection	selection	NOUN
cana-1616	143	31	•	•	NOUN
cana-1616	143	32	for	for	ADP
cana-1616	143	33	each	each	DET
cana-1616	143	34	iteration	iteration	NOUN
cana-1616	143	35	identify	identify	VERB
cana-1616	143	36	the	the	DET
cana-1616	143	37	feature	feature	NOUN
cana-1616	143	38	with	with	ADP
cana-1616	143	39	highest	high	ADJ
cana-1616	143	40	relevance	relevance	NOUN
cana-1616	143	41	score	score	NOUN
cana-1616	143	42	:	:	PUNCT
cana-1616	143	43	max_score_feature	max_score_feature	NOUN
cana-1616	143	44	=	=	NOUN
cana-1616	143	45	arg	arg	NOUN
cana-1616	143	46	maxfeature	maxfeature	NOUN
cana-1616	143	47	relevance_score	relevance_score	NOUN
cana-1616	143	48	add	add	VERB
cana-1616	143	49	this	this	DET
cana-1616	143	50	feature	feature	NOUN
cana-1616	143	51	to	to	ADP
cana-1616	143	52	new	new	ADJ
cana-1616	143	53	list	list	NOUN
cana-1616	143	54	of	of	ADP
cana-1616	143	55	features	feature	NOUN
cana-1616	143	56	(	(	PUNCT
cana-1616	143	57	ordered	order	VERB
cana-1616	143	58	by	by	ADP
cana-1616	143	59	relevance	relevance	NOUN
cana-1616	143	60	score	score	NOUN
cana-1616	143	61	):	):	PUNCT
cana-1616	143	62	selected	select	VERB
cana-1616	143	63	feature	feature	NOUN
cana-1616	143	64	=	=	PRON
cana-1616	143	65	add	add	VERB
cana-1616	143	66	max	max	PROPN
cana-1616	143	67	features	feature	VERB
cana-1616	143	68	values	value	NOUN
cana-1616	143	69	ml	ml	ADP
cana-1616	143	70	based	base	VERB
cana-1616	143	71	feature	feature	NOUN
cana-1616	143	72	weighing	weigh	VERB
cana-1616	143	73	•	•	NOUN
cana-1616	143	74	initialize	initialize	NOUN
cana-1616	143	75	best	good	ADJ
cana-1616	143	76	accuracy	accuracy	NOUN
cana-1616	143	77	:	:	PUNCT
cana-1616	143	78	best_accurcay=0.0	best_accurcay=0.0	NUM
cana-1616	143	79	•	•	PUNCT
cana-1616	143	80	initialize	initialize	VERB
cana-1616	143	81	best	good	ADJ
cana-1616	143	82	weight	weight	NOUN
cana-1616	143	83	:	:	PUNCT
cana-1616	143	84	best_weights	best_weight	NOUN
cana-1616	143	85	=	=	SYM
cana-1616	143	86	initial	initial	ADJ
cana-1616	143	87	weight	weight	NOUN
cana-1616	143	88	while	while	SCONJ
cana-1616	143	89	true	true	ADJ
cana-1616	143	90	:	:	PUNCT
cana-1616	143	91	train	train	NOUN
cana-1616	143	92	ml	ml	NOUN
cana-1616	143	93	model	model	NOUN
cana-1616	143	94	with	with	ADP
cana-1616	143	95	selected	select	VERB
cana-1616	143	96	features	feature	NOUN
cana-1616	143	97	:	:	PUNCT
cana-1616	143	98	model	model	NOUN
cana-1616	143	99	=	=	NOUN
cana-1616	143	100	trainrfmodel(selected_features_labels	trainrfmodel(selected_features_labels	PROPN
cana-1616	143	101	)	)	PUNCT
cana-1616	143	102	evaluate	evaluate	VERB
cana-1616	143	103	model	model	NOUN
cana-1616	143	104	and	and	CCONJ
cana-1616	143	105	calculate	calculate	ADJ
cana-1616	143	106	accuracy	accuracy	NOUN
cana-1616	143	107	:	:	PUNCT
cana-1616	143	108	accuracy	accuracy	NOUN
cana-1616	143	109	=	=	NOUN
cana-1616	143	110	evaluate	evaluate	VERB
cana-1616	143	111	model	model	NOUN
cana-1616	143	112	(	(	PUNCT
cana-1616	143	113	model	model	NOUN
cana-1616	143	114	,	,	PUNCT
cana-1616	143	115	selected	select	VERB
cana-1616	143	116	features	feature	NOUN
cana-1616	143	117	,	,	PUNCT
cana-1616	143	118	labels	label	NOUN
cana-1616	143	119	)	)	PUNCT
cana-1616	143	120	check	check	VERB
cana-1616	143	121	if	if	SCONJ
cana-1616	143	122	new	new	ADJ
cana-1616	143	123	accuracy	accuracy	NOUN
cana-1616	143	124	is	be	AUX
cana-1616	143	125	better	well	ADJ
cana-1616	143	126	than	than	ADP
cana-1616	143	127	previous	previous	ADJ
cana-1616	143	128	best	good	ADJ
cana-1616	143	129	accuracy	accuracy	NOUN
cana-1616	143	130	:	:	PUNCT
cana-1616	143	131	if	if	SCONJ
cana-1616	143	132	accuracy	accuracy	NOUN
cana-1616	143	133	>	>	X
cana-1616	143	134	best	good	ADJ
cana-1616	143	135	accuracy	accuracy	NOUN
cana-1616	143	136	update	update	NOUN
cana-1616	143	137	best	good	ADJ
cana-1616	143	138	accuracy	accuracy	NOUN
cana-1616	143	139	:	:	PUNCT
cana-1616	143	140	best_accuracy	best_accuracy	ADJ
cana-1616	143	141	=	=	SYM
cana-1616	143	142	accuracy	accuracy	NOUN
cana-1616	143	143	update	update	NOUN
cana-1616	143	144	best	good	ADJ
cana-1616	143	145	weights	weight	NOUN
cana-1616	143	146	from	from	ADP
cana-1616	143	147	the	the	DET
cana-1616	143	148	model	model	NOUN
cana-1616	143	149	:	:	PUNCT
cana-1616	143	150	best	good	ADJ
cana-1616	143	151	weight	weight	NOUN
cana-1616	143	152	=	=	SYM
cana-1616	143	153	getfeatureweights(model	getfeatureweights(model	PROPN
cana-1616	143	154	)	)	PUNCT
cana-1616	143	155	else	else	ADV
cana-1616	143	156	exit	exit	NOUN
cana-1616	143	157	loop	loop	NOUN
cana-1616	143	158	accuracy	accuracy	PROPN
cana-1616	143	159	dependent	dependent	ADJ
cana-1616	143	160	weight	weight	NOUN
cana-1616	143	161	assignment	assignment	NOUN
cana-1616	143	162	•	•	NOUN
cana-1616	143	163	update	update	NOUN
cana-1616	143	164	relevance	relevance	NOUN
cana-1616	143	165	score	score	NOUN
cana-1616	143	166	rsu	rsu	NOUN
cana-1616	143	167	for	for	ADP
cana-1616	143	168	each	each	DET
cana-1616	143	169	feature	feature	NOUN
cana-1616	143	170	𝑅𝑆𝑢	𝑅𝑆𝑢	NOUN
cana-1616	143	171	=	=	SYM
cana-1616	143	172	𝑅𝑆𝑝	𝑅𝑆𝑝	X
cana-1616	143	173	+	+	CCONJ
cana-1616	143	174	𝑁𝑎𝑐𝑐	𝑁𝑎𝑐𝑐	PROPN
cana-1616	143	175	∗	∗	NOUN
cana-1616	143	176	𝐸𝑁𝑤𝑔𝑡	𝐸𝑁𝑤𝑔𝑡	PROPN
cana-1616	143	177	communications	communication	NOUN
cana-1616	143	178	on	on	ADP
cana-1616	143	179	applied	apply	VERB
cana-1616	143	180	nonlinear	nonlinear	ADJ
cana-1616	143	181	analysis	analysis	NOUN
cana-1616	143	182	issn	issn	NOUN
cana-1616	143	183	:	:	PUNCT
cana-1616	143	184	1074	1074	NUM
cana-1616	143	185	-	-	PUNCT
cana-1616	143	186	133x	133x	NUM
cana-1616	143	187	vol	vol	NOUN
cana-1616	143	188	31	31	NUM
cana-1616	143	189	no	no	NOUN
cana-1616	143	190	.	.	PUNCT
cana-1616	144	1	8s	8s	PROPN
cana-1616	144	2	(	(	PUNCT
cana-1616	144	3	2024	2024	NUM
cana-1616	144	4	)	)	PUNCT
cana-1616	144	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	144	6	782	782	NUM
cana-1616	144	7	fuzzy	fuzzy	ADJ
cana-1616	144	8	membership	membership	NOUN
cana-1616	144	9	functions	function	NOUN
cana-1616	144	10	•	•	ADV
cana-1616	144	11	for	for	ADP
cana-1616	144	12	each	each	DET
cana-1616	144	13	weight	weight	NOUN
cana-1616	144	14	,	,	PUNCT
cana-1616	144	15	define	define	VERB
cana-1616	144	16	fuzzy	fuzzy	ADJ
cana-1616	144	17	membership	membership	NOUN
cana-1616	144	18	functions	function	NOUN
cana-1616	144	19	based	base	VERB
cana-1616	144	20	on	on	ADP
cana-1616	144	21	min	min	PROPN
cana-1616	144	22	,	,	PUNCT
cana-1616	144	23	max	max	PROPN
cana-1616	144	24	and	and	CCONJ
cana-1616	144	25	mean	mean	VERB
cana-1616	144	26	values	value	NOUN
cana-1616	144	27	•	•	ADV
cana-1616	144	28	for	for	ADP
cana-1616	144	29	each	each	DET
cana-1616	144	30	feature	feature	NOUN
cana-1616	144	31	,	,	PUNCT
cana-1616	144	32	evaluate	evaluate	VERB
cana-1616	144	33	its	its	PRON
cana-1616	144	34	membership	membership	NOUN
cana-1616	144	35	in	in	ADP
cana-1616	144	36	each	each	DET
cana-1616	144	37	defined	define	VERB
cana-1616	144	38	fuzzy	fuzzy	ADJ
cana-1616	144	39	membership	membership	NOUN
cana-1616	144	40	function	function	NOUN
cana-1616	144	41	,	,	PUNCT
cana-1616	144	42	to	to	PART
cana-1616	144	43	form	form	VERB
cana-1616	144	44	set	set	NOUN
cana-1616	144	45	of	of	ADP
cana-1616	144	46	membership	membership	NOUN
cana-1616	144	47	score	score	NOUN
cana-1616	144	48	for	for	ADP
cana-1616	144	49	each	each	DET
cana-1616	144	50	feature	feature	NOUN
cana-1616	144	51	.	.	PUNCT
cana-1616	145	1	•	•	NUM
cana-1616	145	2	multiply	multiply	VERB
cana-1616	145	3	each	each	DET
cana-1616	145	4	feature	feature	NOUN
cana-1616	145	5	membership	membership	NOUN
cana-1616	145	6	score	score	NOUN
cana-1616	145	7	with	with	ADP
cana-1616	145	8	corresponding	correspond	VERB
cana-1616	145	9	feature	feature	NOUN
cana-1616	145	10	weight	weight	NOUN
cana-1616	145	11	𝐹𝑒𝑎𝑡𝑢𝑟𝑒	𝐹𝑒𝑎𝑡𝑢𝑟𝑒	PROPN
cana-1616	145	12	𝑊𝑒𝑖𝑔ℎ𝑡	𝑊𝑒𝑖𝑔ℎ𝑡	PROPN
cana-1616	145	13	=	=	PUNCT
cana-1616	145	14	𝑚𝑒𝑚𝑏𝑒𝑟𝑠ℎ𝑖𝑝	𝑚𝑒𝑚𝑏𝑒𝑟𝑠ℎ𝑖𝑝	ADJ
cana-1616	145	15	𝑑𝑒𝑔𝑟𝑒𝑒	𝑑𝑒𝑔𝑟𝑒𝑒	VERB
cana-1616	145	16	×	×	NOUN
cana-1616	145	17	𝑓𝑒𝑎𝑡𝑢𝑟𝑒	𝑓𝑒𝑎𝑡𝑢𝑟𝑒	NOUN
cana-1616	145	18	𝑤𝑒𝑖𝑔ℎ𝑡𝑠	𝑤𝑒𝑖𝑔ℎ𝑡𝑠	NOUN
cana-1616	145	19	apply	apply	VERB
cana-1616	145	20	threshold	threshold	NOUN
cana-1616	145	21	-	-	PUNCT
cana-1616	145	22	based	base	VERB
cana-1616	145	23	fs	fs	X
cana-1616	145	24	•	•	NUM
cana-1616	145	25	ffeatset	ffeatset	NOUN
cana-1616	145	26	=	=	NOUN
cana-1616	145	27	feature	feature	NOUN
cana-1616	145	28	weights	weight	NOUN
cana-1616	145	29	>	>	X
cana-1616	145	30	th	th	X
cana-1616	145	31	where	where	SCONJ
cana-1616	145	32	,	,	PUNCT
cana-1616	145	33	•	•	NUM
cana-1616	145	34	ffeatset	ffeatset	NOUN
cana-1616	145	35	is	be	AUX
cana-1616	145	36	final	final	ADJ
cana-1616	145	37	feature	feature	NOUN
cana-1616	145	38	set	set	VERB
cana-1616	145	39	and	and	CCONJ
cana-1616	145	40	th	th	X
cana-1616	145	41	is	be	AUX
cana-1616	145	42	threshold	threshold	NOUN
cana-1616	145	43	with	with	ADP
cana-1616	145	44	value	value	NOUN
cana-1616	145	45	of	of	ADP
cana-1616	145	46	0.7	0.7	NUM
cana-1616	145	47	return	return	NOUN
cana-1616	145	48	ffeatset	ffeatset	VERB
cana-1616	145	49	4.1	4.1	NUM
cana-1616	145	50	disease	disease	NOUN
cana-1616	145	51	detection	detection	NOUN
cana-1616	145	52	using	use	VERB
cana-1616	145	53	belv	belv	PROPN
cana-1616	145	54	the	the	DET
cana-1616	145	55	features	feature	NOUN
cana-1616	145	56	extracted	extract	VERB
cana-1616	145	57	in	in	ADP
cana-1616	145	58	the	the	DET
cana-1616	145	59	previous	previous	ADJ
cana-1616	145	60	step	step	NOUN
cana-1616	145	61	are	be	AUX
cana-1616	145	62	categorized	categorize	VERB
cana-1616	145	63	into	into	ADP
cana-1616	145	64	two	two	NUM
cana-1616	145	65	categories	category	NOUN
cana-1616	145	66	of	of	ADP
cana-1616	145	67	training	training	NOUN
cana-1616	145	68	and	and	CCONJ
cana-1616	145	69	testing	testing	NOUN
cana-1616	145	70	data	datum	NOUN
cana-1616	145	71	in	in	ADP
cana-1616	145	72	the	the	DET
cana-1616	145	73	proportion	proportion	NOUN
cana-1616	145	74	of	of	ADP
cana-1616	145	75	70:30	70:30	NUM
cana-1616	145	76	respectively	respectively	ADV
cana-1616	145	77	.	.	PUNCT
cana-1616	146	1	in	in	ADP
cana-1616	146	2	this	this	DET
cana-1616	146	3	section	section	NOUN
cana-1616	146	4	of	of	ADP
cana-1616	146	5	paper	paper	NOUN
cana-1616	146	6	,	,	PUNCT
cana-1616	146	7	we	we	PRON
cana-1616	146	8	are	be	AUX
cana-1616	146	9	going	go	VERB
cana-1616	146	10	to	to	PART
cana-1616	146	11	identify	identify	VERB
cana-1616	146	12	and	and	CCONJ
cana-1616	146	13	determine	determine	VERB
cana-1616	146	14	the	the	DET
cana-1616	146	15	stage	stage	NOUN
cana-1616	146	16	of	of	ADP
cana-1616	146	17	liver	liver	NOUN
cana-1616	146	18	disease	disease	NOUN
cana-1616	146	19	in	in	ADP
cana-1616	146	20	patients	patient	NOUN
cana-1616	146	21	by	by	ADP
cana-1616	146	22	employing	employ	VERB
cana-1616	146	23	bagging	bagging	NOUN
cana-1616	146	24	,	,	PUNCT
cana-1616	146	25	ensemble	ensemble	ADJ
cana-1616	146	26	learning	learning	NOUN
cana-1616	146	27	and	and	CCONJ
cana-1616	146	28	voting	voting	NOUN
cana-1616	146	29	methods	method	NOUN
cana-1616	146	30	,	,	PUNCT
cana-1616	146	31	(	(	PUNCT
cana-1616	146	32	belv	belv	PROPN
cana-1616	146	33	)	)	PUNCT
cana-1616	146	34	on	on	ADP
cana-1616	146	35	ilpd	ilpd	NOUN
cana-1616	146	36	and	and	CCONJ
cana-1616	146	37	cpd	cpd	ADJ
cana-1616	146	38	datasets	dataset	NOUN
cana-1616	146	39	.	.	PUNCT
cana-1616	147	1	figure	figure	NOUN
cana-1616	147	2	4	4	NUM
cana-1616	147	3	demonstrates	demonstrate	VERB
cana-1616	147	4	the	the	DET
cana-1616	147	5	classification	classification	NOUN
cana-1616	147	6	mechanism	mechanism	NOUN
cana-1616	147	7	opted	opt	VERB
cana-1616	147	8	in	in	ADP
cana-1616	147	9	our	our	PRON
cana-1616	147	10	work	work	NOUN
cana-1616	147	11	.	.	PUNCT
cana-1616	148	1	bagging	bagging	NOUN
cana-1616	148	2	which	which	PRON
cana-1616	148	3	is	be	AUX
cana-1616	148	4	sometime	sometime	ADV
cana-1616	148	5	also	also	ADV
cana-1616	148	6	known	know	VERB
cana-1616	148	7	as	as	ADP
cana-1616	148	8	bootstrap	bootstrap	NOUN
cana-1616	148	9	aggregating	aggregating	NOUN
cana-1616	148	10	creates	create	VERB
cana-1616	148	11	multiple	multiple	ADJ
cana-1616	148	12	datasets	dataset	NOUN
cana-1616	148	13	of	of	ADP
cana-1616	148	14	the	the	DET
cana-1616	148	15	training	training	NOUN
cana-1616	148	16	data	datum	NOUN
cana-1616	148	17	through	through	ADP
cana-1616	148	18	random	random	ADJ
cana-1616	148	19	sampling	sampling	NOUN
cana-1616	148	20	with	with	ADP
cana-1616	148	21	replacement	replacement	NOUN
cana-1616	148	22	and	and	CCONJ
cana-1616	148	23	training	train	VERB
cana-1616	148	24	individual	individual	ADJ
cana-1616	148	25	models	model	NOUN
cana-1616	148	26	on	on	ADP
cana-1616	148	27	featured	feature	VERB
cana-1616	148	28	data	datum	NOUN
cana-1616	148	29	subsets	subset	NOUN
cana-1616	148	30	.	.	PUNCT
cana-1616	149	1	on	on	ADP
cana-1616	149	2	the	the	DET
cana-1616	149	3	other	other	ADJ
cana-1616	149	4	hand	hand	NOUN
cana-1616	149	5	,	,	PUNCT
cana-1616	149	6	ensemble	ensemble	ADJ
cana-1616	149	7	learning	learning	NOUN
cana-1616	149	8	is	be	AUX
cana-1616	149	9	the	the	DET
cana-1616	149	10	classification	classification	NOUN
cana-1616	149	11	method	method	NOUN
cana-1616	149	12	in	in	ADP
cana-1616	149	13	which	which	PRON
cana-1616	149	14	two	two	NUM
cana-1616	149	15	or	or	CCONJ
cana-1616	149	16	more	more	ADJ
cana-1616	149	17	classifiers	classifier	NOUN
cana-1616	149	18	are	be	AUX
cana-1616	149	19	used	use	VERB
cana-1616	149	20	together	together	ADV
cana-1616	149	21	for	for	ADP
cana-1616	149	22	making	make	VERB
cana-1616	149	23	prediction	prediction	NOUN
cana-1616	149	24	.	.	PUNCT
cana-1616	150	1	the	the	DET
cana-1616	150	2	final	final	ADJ
cana-1616	150	3	prediction	prediction	NOUN
cana-1616	150	4	is	be	AUX
cana-1616	150	5	made	make	VERB
cana-1616	150	6	by	by	ADP
cana-1616	150	7	using	use	VERB
cana-1616	150	8	the	the	DET
cana-1616	150	9	majority	majority	NOUN
cana-1616	150	10	voting	voting	NOUN
cana-1616	150	11	mechanism	mechanism	NOUN
cana-1616	150	12	of	of	ADP
cana-1616	150	13	ensemble	ensemble	ADJ
cana-1616	150	14	methods	method	NOUN
cana-1616	150	15	.	.	PUNCT
cana-1616	151	1	traditionally	traditionally	ADV
cana-1616	151	2	,	,	PUNCT
cana-1616	151	3	bagging	bagging	NOUN
cana-1616	151	4	technique	technique	NOUN
cana-1616	151	5	was	be	AUX
cana-1616	151	6	implemented	implement	VERB
cana-1616	151	7	on	on	ADP
cana-1616	151	8	single	single	ADJ
cana-1616	151	9	classifiers	classifier	NOUN
cana-1616	151	10	to	to	PART
cana-1616	151	11	make	make	VERB
cana-1616	151	12	the	the	DET
cana-1616	151	13	final	final	ADJ
cana-1616	151	14	prediction	prediction	NOUN
cana-1616	151	15	.	.	PUNCT
cana-1616	152	1	however	however	ADV
cana-1616	152	2	,	,	PUNCT
cana-1616	152	3	to	to	PART
cana-1616	152	4	introduce	introduce	VERB
cana-1616	152	5	the	the	DET
cana-1616	152	6	novelty	novelty	NOUN
cana-1616	152	7	concept	concept	NOUN
cana-1616	152	8	in	in	ADP
cana-1616	152	9	our	our	PRON
cana-1616	152	10	model	model	NOUN
cana-1616	152	11	and	and	CCONJ
cana-1616	152	12	enhance	enhance	VERB
cana-1616	152	13	its	its	PRON
cana-1616	152	14	accuracy	accuracy	NOUN
cana-1616	152	15	rate	rate	NOUN
cana-1616	152	16	,	,	PUNCT
cana-1616	152	17	we	we	PRON
cana-1616	152	18	have	have	AUX
cana-1616	152	19	not	not	PART
cana-1616	152	20	only	only	ADV
cana-1616	152	21	implemented	implement	VERB
cana-1616	152	22	bagging	bagging	NOUN
cana-1616	152	23	method	method	NOUN
cana-1616	152	24	but	but	CCONJ
cana-1616	152	25	have	have	AUX
cana-1616	152	26	also	also	ADV
cana-1616	152	27	used	use	VERB
cana-1616	152	28	ensemble	ensemble	ADJ
cana-1616	152	29	learning	learning	NOUN
cana-1616	152	30	method	method	NOUN
cana-1616	152	31	and	and	CCONJ
cana-1616	152	32	mod	mod	ADJ
cana-1616	152	33	voting	voting	NOUN
cana-1616	152	34	mechanism	mechanism	NOUN
cana-1616	152	35	for	for	ADP
cana-1616	152	36	making	make	VERB
cana-1616	152	37	the	the	DET
cana-1616	152	38	final	final	ADJ
cana-1616	152	39	prediction	prediction	NOUN
cana-1616	152	40	.	.	PUNCT
cana-1616	153	1	there	there	PRON
cana-1616	153	2	are	be	VERB
cana-1616	153	3	ample	ample	ADJ
cana-1616	153	4	number	number	NOUN
cana-1616	153	5	of	of	ADP
cana-1616	153	6	reasons	reason	NOUN
cana-1616	153	7	why	why	SCONJ
cana-1616	153	8	ensemble	ensemble	ADJ
cana-1616	153	9	learning	learning	NOUN
cana-1616	153	10	is	be	AUX
cana-1616	153	11	preferred	prefer	VERB
cana-1616	153	12	over	over	ADP
cana-1616	153	13	standard	standard	ADJ
cana-1616	153	14	prediction	prediction	NOUN
cana-1616	153	15	models	model	NOUN
cana-1616	153	16	,	,	PUNCT
cana-1616	153	17	but	but	CCONJ
cana-1616	153	18	one	one	NUM
cana-1616	153	19	of	of	ADP
cana-1616	153	20	the	the	DET
cana-1616	153	21	major	major	ADJ
cana-1616	153	22	reasons	reason	NOUN
cana-1616	153	23	is	be	AUX
cana-1616	153	24	that	that	SCONJ
cana-1616	153	25	single	single	ADJ
cana-1616	153	26	classifiers	classifier	NOUN
cana-1616	153	27	do	do	AUX
cana-1616	153	28	not	not	PART
cana-1616	153	29	have	have	VERB
cana-1616	153	30	the	the	DET
cana-1616	153	31	capacity	capacity	NOUN
cana-1616	153	32	to	to	PART
cana-1616	153	33	generate	generate	VERB
cana-1616	153	34	reliable	reliable	ADJ
cana-1616	153	35	results	result	NOUN
cana-1616	153	36	which	which	PRON
cana-1616	153	37	degrade	degrade	VERB
cana-1616	153	38	their	their	PRON
cana-1616	153	39	overall	overall	ADJ
cana-1616	153	40	accuracy	accuracy	NOUN
cana-1616	153	41	rate	rate	NOUN
cana-1616	153	42	.	.	PUNCT
cana-1616	154	1	moreover	moreover	ADV
cana-1616	154	2	,	,	PUNCT
cana-1616	154	3	the	the	DET
cana-1616	154	4	mechanism	mechanism	NOUN
cana-1616	154	5	of	of	ADP
cana-1616	154	6	combining	combine	VERB
cana-1616	154	7	outputs	output	NOUN
cana-1616	154	8	generated	generate	VERB
cana-1616	154	9	by	by	ADP
cana-1616	154	10	different	different	ADJ
cana-1616	154	11	classifiers	classifier	NOUN
cana-1616	154	12	not	not	PART
cana-1616	154	13	only	only	ADV
cana-1616	154	14	reduces	reduce	VERB
cana-1616	154	15	errors	error	NOUN
cana-1616	154	16	of	of	ADP
cana-1616	154	17	individual	individual	ADJ
cana-1616	154	18	models	model	NOUN
cana-1616	154	19	but	but	CCONJ
cana-1616	154	20	also	also	ADV
cana-1616	154	21	increases	increase	VERB
cana-1616	154	22	the	the	DET
cana-1616	154	23	overall	overall	ADJ
cana-1616	154	24	accuracy	accuracy	NOUN
cana-1616	154	25	rate	rate	NOUN
cana-1616	154	26	of	of	ADP
cana-1616	154	27	the	the	DET
cana-1616	154	28	model	model	NOUN
cana-1616	154	29	.	.	PUNCT
cana-1616	155	1	in	in	ADP
cana-1616	155	2	our	our	PRON
cana-1616	155	3	work	work	NOUN
cana-1616	155	4	,	,	PUNCT
cana-1616	155	5	we	we	PRON
cana-1616	155	6	have	have	AUX
cana-1616	155	7	used	use	VERB
cana-1616	155	8	three	three	NUM
cana-1616	155	9	baseline	baseline	NOUN
cana-1616	155	10	classifiers	classifier	NOUN
cana-1616	155	11	i.e.	i.e.	X
cana-1616	155	12	,	,	PUNCT
cana-1616	155	13	knn	knn	PROPN
cana-1616	155	14	,	,	PUNCT
cana-1616	155	15	dt	dt	PUNCT
cana-1616	155	16	and	and	CCONJ
cana-1616	155	17	rf	rf	NOUN
cana-1616	155	18	.	.	PUNCT
cana-1616	156	1	the	the	DET
cana-1616	156	2	reason	reason	NOUN
cana-1616	156	3	why	why	SCONJ
cana-1616	156	4	specifically	specifically	ADV
cana-1616	156	5	these	these	DET
cana-1616	156	6	three	three	NUM
cana-1616	156	7	classifiers	classifier	NOUN
cana-1616	156	8	have	have	AUX
cana-1616	156	9	been	be	AUX
cana-1616	156	10	selected	select	VERB
cana-1616	156	11	in	in	ADP
cana-1616	156	12	the	the	DET
cana-1616	156	13	proposed	propose	VERB
cana-1616	156	14	work	work	NOUN
cana-1616	156	15	is	be	AUX
cana-1616	156	16	that	that	SCONJ
cana-1616	156	17	they	they	PRON
cana-1616	156	18	generate	generate	VERB
cana-1616	156	19	more	more	ADV
cana-1616	156	20	effective	effective	ADJ
cana-1616	156	21	results	result	NOUN
cana-1616	156	22	individually	individually	ADV
cana-1616	156	23	as	as	SCONJ
cana-1616	156	24	seen	see	VERB
cana-1616	156	25	from	from	ADP
cana-1616	156	26	the	the	DET
cana-1616	156	27	literature	literature	NOUN
cana-1616	156	28	.	.	PUNCT
cana-1616	157	1	however	however	ADV
cana-1616	157	2	,	,	PUNCT
cana-1616	157	3	we	we	PRON
cana-1616	157	4	tend	tend	VERB
cana-1616	157	5	to	to	PART
cana-1616	157	6	increase	increase	VERB
cana-1616	157	7	their	their	PRON
cana-1616	157	8	individual	individual	ADJ
cana-1616	157	9	performance	performance	NOUN
cana-1616	157	10	by	by	ADP
cana-1616	157	11	combining	combine	VERB
cana-1616	157	12	them	they	PRON
cana-1616	157	13	into	into	ADP
cana-1616	157	14	ensemble	ensemble	ADJ
cana-1616	157	15	learning	learning	NOUN
cana-1616	157	16	method	method	NOUN
cana-1616	157	17	.	.	PUNCT
cana-1616	158	1	communications	communication	NOUN
cana-1616	158	2	on	on	ADP
cana-1616	158	3	applied	apply	VERB
cana-1616	158	4	nonlinear	nonlinear	ADJ
cana-1616	158	5	analysis	analysis	NOUN
cana-1616	158	6	issn	issn	NOUN
cana-1616	158	7	:	:	PUNCT
cana-1616	158	8	1074	1074	NUM
cana-1616	158	9	-	-	PUNCT
cana-1616	158	10	133x	133x	NUM
cana-1616	158	11	vol	vol	NOUN
cana-1616	158	12	31	31	NUM
cana-1616	158	13	no	no	NOUN
cana-1616	158	14	.	.	PUNCT
cana-1616	159	1	8s	8s	PROPN
cana-1616	159	2	(	(	PUNCT
cana-1616	159	3	2024	2024	NUM
cana-1616	159	4	)	)	PUNCT
cana-1616	159	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	159	6	783	783	NUM
cana-1616	159	7	k	k	ADV
cana-1616	159	8	-	-	PUNCT
cana-1616	159	9	nearest	near	ADJ
cana-1616	159	10	neighbor	neighbor	NOUN
cana-1616	159	11	(	(	PUNCT
cana-1616	159	12	knn	knn	PROPN
cana-1616	159	13	)	)	PUNCT
cana-1616	159	14	knn	knn	PROPN
cana-1616	159	15	is	be	AUX
cana-1616	159	16	a	a	DET
cana-1616	159	17	machine	machine	NOUN
cana-1616	159	18	learning	learn	VERB
cana-1616	159	19	algorithm	algorithm	NOUN
cana-1616	159	20	that	that	PRON
cana-1616	159	21	can	can	AUX
cana-1616	159	22	be	be	AUX
cana-1616	159	23	applied	apply	VERB
cana-1616	159	24	in	in	ADP
cana-1616	159	25	liver	liver	NOUN
cana-1616	159	26	disease	disease	NOUN
cana-1616	159	27	detection	detection	NOUN
cana-1616	159	28	to	to	PART
cana-1616	159	29	classify	classify	VERB
cana-1616	159	30	patients	patient	NOUN
cana-1616	159	31	based	base	VERB
cana-1616	159	32	on	on	ADP
cana-1616	159	33	their	their	PRON
cana-1616	159	34	medical	medical	ADJ
cana-1616	159	35	data	datum	NOUN
cana-1616	159	36	it	it	PRON
cana-1616	159	37	is	be	AUX
cana-1616	159	38	a	a	DET
cana-1616	159	39	non	non	ADJ
cana-1616	159	40	-	-	ADJ
cana-1616	159	41	parametric	parametric	ADJ
cana-1616	159	42	algorithm	algorithm	NOUN
cana-1616	159	43	which	which	PRON
cana-1616	159	44	means	mean	VERB
cana-1616	159	45	it	it	PRON
cana-1616	159	46	does	do	AUX
cana-1616	159	47	n’t	not	PART
cana-1616	159	48	make	make	VERB
cana-1616	159	49	any	any	DET
cana-1616	159	50	assumptions	assumption	NOUN
cana-1616	159	51	for	for	ADP
cana-1616	159	52	given	give	VERB
cana-1616	159	53	data	datum	NOUN
cana-1616	159	54	distribution	distribution	NOUN
cana-1616	159	55	and	and	CCONJ
cana-1616	159	56	is	be	AUX
cana-1616	159	57	based	base	VERB
cana-1616	159	58	on	on	ADP
cana-1616	159	59	the	the	DET
cana-1616	159	60	principle	principle	NOUN
cana-1616	159	61	of	of	ADP
cana-1616	159	62	finding	find	VERB
cana-1616	159	63	k	k	NOUN
cana-1616	159	64	-	-	PUNCT
cana-1616	159	65	nearest	near	ADJ
cana-1616	159	66	data	datum	NOUN
cana-1616	159	67	points	point	NOUN
cana-1616	159	68	to	to	PART
cana-1616	159	69	make	make	VERB
cana-1616	159	70	the	the	DET
cana-1616	159	71	prediction	prediction	NOUN
cana-1616	159	72	.	.	PUNCT
cana-1616	160	1	decision	decision	NOUN
cana-1616	160	2	tree	tree	NOUN
cana-1616	160	3	(	(	PUNCT
cana-1616	160	4	dt	dt	NOUN
cana-1616	160	5	)	)	PUNCT
cana-1616	160	6	dt	dt	PUNCT
cana-1616	160	7	is	be	AUX
cana-1616	160	8	yet	yet	ADV
cana-1616	160	9	another	another	DET
cana-1616	160	10	ml	ml	NOUN
cana-1616	160	11	classifier	classifier	NOUN
cana-1616	160	12	that	that	PRON
cana-1616	160	13	is	be	AUX
cana-1616	160	14	widely	widely	ADV
cana-1616	160	15	used	use	VERB
cana-1616	160	16	in	in	ADP
cana-1616	160	17	classification	classification	NOUN
cana-1616	160	18	tasks	task	NOUN
cana-1616	160	19	.	.	PUNCT
cana-1616	161	1	it	it	PRON
cana-1616	161	2	organizes	organize	VERB
cana-1616	161	3	data	datum	NOUN
cana-1616	161	4	into	into	ADP
cana-1616	161	5	a	a	DET
cana-1616	161	6	hierarchical	hierarchical	ADJ
cana-1616	161	7	tree	tree	NOUN
cana-1616	161	8	-	-	PUNCT
cana-1616	161	9	like	like	ADJ
cana-1616	161	10	structure	structure	NOUN
cana-1616	161	11	,	,	PUNCT
cana-1616	161	12	with	with	ADP
cana-1616	161	13	each	each	DET
cana-1616	161	14	internal	internal	ADJ
cana-1616	161	15	node	node	NOUN
cana-1616	161	16	representing	represent	VERB
cana-1616	161	17	a	a	DET
cana-1616	161	18	feature	feature	NOUN
cana-1616	161	19	and	and	CCONJ
cana-1616	161	20	a	a	DET
cana-1616	161	21	decision	decision	NOUN
cana-1616	161	22	based	base	VERB
cana-1616	161	23	on	on	ADP
cana-1616	161	24	that	that	DET
cana-1616	161	25	feature	feature	NOUN
cana-1616	161	26	,	,	PUNCT
cana-1616	161	27	and	and	CCONJ
cana-1616	161	28	each	each	DET
cana-1616	161	29	leaf	leaf	NOUN
cana-1616	161	30	node	node	NOUN
cana-1616	161	31	indicating	indicate	VERB
cana-1616	161	32	the	the	DET
cana-1616	161	33	predicted	predict	VERB
cana-1616	161	34	class	class	NOUN
cana-1616	161	35	label	label	NOUN
cana-1616	161	36	.	.	PUNCT
cana-1616	162	1	random	random	ADJ
cana-1616	162	2	forest	forest	NOUN
cana-1616	162	3	(	(	PUNCT
cana-1616	162	4	rf	rf	NOUN
cana-1616	162	5	)	)	PUNCT
cana-1616	162	6	the	the	DET
cana-1616	162	7	random	random	ADJ
cana-1616	162	8	forest	forest	NOUN
cana-1616	162	9	(	(	PUNCT
cana-1616	162	10	rf	rf	NOUN
cana-1616	162	11	)	)	PUNCT
cana-1616	162	12	classifier	classifier	NOUN
cana-1616	162	13	is	be	AUX
cana-1616	162	14	a	a	DET
cana-1616	162	15	powerful	powerful	ADJ
cana-1616	162	16	and	and	CCONJ
cana-1616	162	17	versatile	versatile	ADJ
cana-1616	162	18	machine	machine	NOUN
cana-1616	162	19	learning	learn	VERB
cana-1616	162	20	algorithm	algorithm	NOUN
cana-1616	162	21	commonly	commonly	ADV
cana-1616	162	22	used	use	VERB
cana-1616	162	23	for	for	ADP
cana-1616	162	24	both	both	CCONJ
cana-1616	162	25	classification	classification	NOUN
cana-1616	162	26	and	and	CCONJ
cana-1616	162	27	regression	regression	NOUN
cana-1616	162	28	tasks	task	NOUN
cana-1616	162	29	.	.	PUNCT
cana-1616	163	1	it	it	PRON
cana-1616	163	2	belongs	belong	VERB
cana-1616	163	3	to	to	ADP
cana-1616	163	4	the	the	DET
cana-1616	163	5	ensemble	ensemble	ADJ
cana-1616	163	6	learning	learning	NOUN
cana-1616	163	7	category	category	NOUN
cana-1616	163	8	and	and	CCONJ
cana-1616	163	9	is	be	AUX
cana-1616	163	10	built	build	VERB
cana-1616	163	11	upon	upon	SCONJ
cana-1616	163	12	the	the	DET
cana-1616	163	13	concept	concept	NOUN
cana-1616	163	14	of	of	ADP
cana-1616	163	15	decision	decision	NOUN
cana-1616	163	16	trees	tree	NOUN
cana-1616	163	17	.	.	PUNCT
cana-1616	164	1	after	after	SCONJ
cana-1616	164	2	the	the	DET
cana-1616	164	3	three	three	NUM
cana-1616	164	4	baseline	baseline	NOUN
cana-1616	164	5	models	model	NOUN
cana-1616	164	6	are	be	AUX
cana-1616	164	7	initialized	initialize	VERB
cana-1616	164	8	,	,	PUNCT
cana-1616	164	9	process	process	NOUN
cana-1616	164	10	of	of	ADP
cana-1616	164	11	training	training	NOUN
cana-1616	164	12	is	be	AUX
cana-1616	164	13	started	start	VERB
cana-1616	164	14	.	.	PUNCT
cana-1616	165	1	however	however	ADV
cana-1616	165	2	,	,	PUNCT
cana-1616	165	3	before	before	ADP
cana-1616	165	4	making	make	VERB
cana-1616	165	5	prediction	prediction	NOUN
cana-1616	165	6	we	we	PRON
cana-1616	165	7	have	have	AUX
cana-1616	165	8	implemented	implement	VERB
cana-1616	165	9	bagging	bagging	NOUN
cana-1616	165	10	technique	technique	NOUN
cana-1616	165	11	on	on	ADP
cana-1616	165	12	each	each	DET
cana-1616	165	13	classifier	classifier	NOUN
cana-1616	165	14	.	.	PUNCT
cana-1616	166	1	the	the	DET
cana-1616	166	2	total	total	ADJ
cana-1616	166	3	number	number	NOUN
cana-1616	166	4	of	of	ADP
cana-1616	166	5	bags	bag	NOUN
cana-1616	166	6	in	in	ADP
cana-1616	166	7	our	our	PRON
cana-1616	166	8	work	work	NOUN
cana-1616	166	9	is	be	AUX
cana-1616	166	10	5	5	NUM
cana-1616	166	11	,	,	PUNCT
cana-1616	166	12	which	which	PRON
cana-1616	166	13	means	mean	VERB
cana-1616	166	14	that	that	SCONJ
cana-1616	166	15	5	5	NUM
cana-1616	166	16	copies	copy	NOUN
cana-1616	166	17	of	of	ADP
cana-1616	166	18	features	feature	NOUN
cana-1616	166	19	dataset	dataset	VERB
cana-1616	166	20	are	be	AUX
cana-1616	166	21	created	create	VERB
cana-1616	166	22	and	and	CCONJ
cana-1616	166	23	each	each	DET
cana-1616	166	24	classifier	classifier	NOUN
cana-1616	166	25	is	be	AUX
cana-1616	166	26	trained	train	VERB
cana-1616	166	27	on	on	ADP
cana-1616	166	28	each	each	DET
cana-1616	166	29	data	datum	NOUN
cana-1616	166	30	subset	subset	VERB
cana-1616	166	31	to	to	PART
cana-1616	166	32	generate	generate	VERB
cana-1616	166	33	5	5	NUM
cana-1616	166	34	individual	individual	ADJ
cana-1616	166	35	outcomes	outcome	NOUN
cana-1616	166	36	.	.	PUNCT
cana-1616	167	1	after	after	ADP
cana-1616	167	2	this	this	PRON
cana-1616	167	3	,	,	PUNCT
cana-1616	167	4	the	the	DET
cana-1616	167	5	role	role	NOUN
cana-1616	167	6	of	of	ADP
cana-1616	167	7	ensemble	ensemble	ADJ
cana-1616	167	8	learning	learning	NOUN
cana-1616	167	9	comes	come	VERB
cana-1616	167	10	into	into	ADP
cana-1616	167	11	play	play	NOUN
cana-1616	167	12	wherein	wherein	SCONJ
cana-1616	167	13	the	the	DET
cana-1616	167	14	predictions	prediction	NOUN
cana-1616	167	15	made	make	VERB
cana-1616	167	16	by	by	ADP
cana-1616	167	17	each	each	DET
cana-1616	167	18	classifier	classifier	NOUN
cana-1616	167	19	for	for	ADP
cana-1616	167	20	5	5	NUM
cana-1616	167	21	bags	bag	NOUN
cana-1616	167	22	is	be	AUX
cana-1616	167	23	combined	combine	VERB
cana-1616	167	24	for	for	ADP
cana-1616	167	25	making	make	VERB
cana-1616	167	26	the	the	DET
cana-1616	167	27	final	final	ADJ
cana-1616	167	28	prediction	prediction	NOUN
cana-1616	167	29	.	.	PUNCT
cana-1616	168	1	the	the	DET
cana-1616	168	2	process	process	NOUN
cana-1616	168	3	of	of	ADP
cana-1616	168	4	combining	combine	VERB
cana-1616	168	5	data	datum	NOUN
cana-1616	168	6	is	be	AUX
cana-1616	168	7	performed	perform	VERB
cana-1616	168	8	in	in	ADP
cana-1616	168	9	such	such	DET
cana-1616	168	10	a	a	DET
cana-1616	168	11	way	way	NOUN
cana-1616	168	12	that	that	PRON
cana-1616	168	13	first	first	ADJ
cana-1616	168	14	prediction	prediction	NOUN
cana-1616	168	15	of	of	ADP
cana-1616	168	16	knn	knn	PROPN
cana-1616	168	17	,	,	PUNCT
cana-1616	168	18	dt	dt	PUNCT
cana-1616	168	19	and	and	CCONJ
cana-1616	168	20	rf	rf	PRON
cana-1616	168	21	are	be	AUX
cana-1616	168	22	combined	combine	VERB
cana-1616	168	23	to	to	PART
cana-1616	168	24	form	form	VERB
cana-1616	168	25	first	first	ADJ
cana-1616	168	26	output	output	NOUN
cana-1616	168	27	and	and	CCONJ
cana-1616	168	28	then	then	ADV
cana-1616	168	29	second	second	ADJ
cana-1616	168	30	output	output	NOUN
cana-1616	168	31	of	of	ADP
cana-1616	168	32	three	three	NUM
cana-1616	168	33	baseline	baseline	NOUN
cana-1616	168	34	classifiers	classifier	NOUN
cana-1616	168	35	is	be	AUX
cana-1616	168	36	combined	combine	VERB
cana-1616	168	37	to	to	PART
cana-1616	168	38	form	form	VERB
cana-1616	168	39	second	second	ADJ
cana-1616	168	40	output	output	NOUN
cana-1616	168	41	.	.	PUNCT
cana-1616	169	1	this	this	DET
cana-1616	169	2	process	process	NOUN
cana-1616	169	3	keeps	keep	VERB
cana-1616	169	4	on	on	ADP
cana-1616	169	5	going	go	VERB
cana-1616	169	6	till	till	SCONJ
cana-1616	169	7	we	we	PRON
cana-1616	169	8	got	get	VERB
cana-1616	169	9	the	the	DET
cana-1616	169	10	five	five	NUM
cana-1616	169	11	predictions	prediction	NOUN
cana-1616	169	12	made	make	VERB
cana-1616	169	13	by	by	ADP
cana-1616	169	14	combining	combine	VERB
cana-1616	169	15	the	the	DET
cana-1616	169	16	data	datum	NOUN
cana-1616	169	17	of	of	ADP
cana-1616	169	18	three	three	NUM
cana-1616	169	19	classifiers	classifier	NOUN
cana-1616	169	20	.	.	PUNCT
cana-1616	170	1	once	once	ADV
cana-1616	170	2	this	this	DET
cana-1616	170	3	process	process	NOUN
cana-1616	170	4	is	be	AUX
cana-1616	170	5	completed	complete	VERB
cana-1616	170	6	,	,	PUNCT
cana-1616	170	7	mod	mod	ADJ
cana-1616	170	8	majority	majority	NOUN
cana-1616	170	9	voting	voting	NOUN
cana-1616	170	10	mechanism	mechanism	NOUN
cana-1616	170	11	is	be	AUX
cana-1616	170	12	applied	apply	VERB
cana-1616	170	13	to	to	PART
cana-1616	170	14	make	make	VERB
cana-1616	170	15	the	the	DET
cana-1616	170	16	final	final	ADJ
cana-1616	170	17	binary	binary	ADJ
cana-1616	170	18	and	and	CCONJ
cana-1616	170	19	multi	multi	ADJ
cana-1616	170	20	-	-	ADJ
cana-1616	170	21	class	class	ADJ
cana-1616	170	22	classification	classification	NOUN
cana-1616	170	23	in	in	ADP
cana-1616	170	24	which	which	DET
cana-1616	170	25	presence	presence	NOUN
cana-1616	170	26	or	or	CCONJ
cana-1616	170	27	absence	absence	NOUN
cana-1616	170	28	of	of	ADP
cana-1616	170	29	disease	disease	NOUN
cana-1616	170	30	as	as	ADV
cana-1616	170	31	well	well	ADV
cana-1616	170	32	as	as	ADP
cana-1616	170	33	stage	stage	NOUN
cana-1616	170	34	of	of	ADP
cana-1616	170	35	disease	disease	NOUN
cana-1616	170	36	is	be	AUX
cana-1616	170	37	determined	determine	VERB
cana-1616	170	38	.	.	PUNCT
cana-1616	171	1	the	the	DET
cana-1616	171	2	mod	mod	PROPN
cana-1616	171	3	based	base	VERB
cana-1616	171	4	voting	voting	NOUN
cana-1616	171	5	mechanism	mechanism	NOUN
cana-1616	171	6	gives	give	VERB
cana-1616	171	7	that	that	DET
cana-1616	171	8	output	output	NOUN
cana-1616	171	9	as	as	ADP
cana-1616	171	10	final	final	ADJ
cana-1616	171	11	prediction	prediction	NOUN
cana-1616	171	12	for	for	ADP
cana-1616	171	13	a	a	DET
cana-1616	171	14	particular	particular	ADJ
cana-1616	171	15	dataset	dataset	NOUN
cana-1616	171	16	,	,	PUNCT
cana-1616	171	17	which	which	PRON
cana-1616	171	18	possess	possess	VERB
cana-1616	171	19	highest	high	ADJ
cana-1616	171	20	frequency	frequency	NOUN
cana-1616	171	21	or	or	CCONJ
cana-1616	171	22	got	get	VERB
cana-1616	171	23	highest	high	ADJ
cana-1616	171	24	votes	vote	NOUN
cana-1616	171	25	.	.	PUNCT
cana-1616	172	1	figure	figure	NOUN
cana-1616	172	2	4	4	NUM
cana-1616	172	3	.	.	PUNCT
cana-1616	172	4	proposed	propose	VERB
cana-1616	172	5	belv	belv	PROPN
cana-1616	172	6	classification	classification	NOUN
cana-1616	172	7	model	model	NOUN
cana-1616	172	8	initialize	initialize	NOUN
cana-1616	172	9	classifiers	classifier	NOUN
cana-1616	172	10	svm	svm	VERB
cana-1616	172	11	,	,	PUNCT
cana-1616	172	12	dt	dt	PUNCT
cana-1616	172	13	and	and	CCONJ
cana-1616	172	14	rf	rf	VERB
cana-1616	172	15	ensemble	ensemble	ADJ
cana-1616	172	16	learning	learning	NOUN
cana-1616	172	17	voting	voting	NOUN
cana-1616	172	18	mechanism	mechanism	NOUN
cana-1616	172	19	detection	detection	NOUN
cana-1616	172	20	and	and	CCONJ
cana-1616	172	21	classification	classification	NOUN
cana-1616	172	22	of	of	ADP
cana-1616	172	23	liver	liver	NOUN
cana-1616	172	24	disease	disease	NOUN
cana-1616	172	25	baggi	baggi	PROPN
cana-1616	172	26	ng	ng	PROPN
cana-1616	172	27	m	m	PROPN
cana-1616	172	28	with	with	ADP
cana-1616	172	29	svm1	svm1	PROPN
cana-1616	172	30	svm2	svm2	NOUN
cana-1616	172	31	svm	svm	PROPN
cana-1616	172	32	3	3	NUM
cana-1616	172	33	svm4	svm4	ADV
cana-1616	172	34	svm	svm	VERB
cana-1616	172	35	with	with	ADP
cana-1616	172	36	5	5	NUM
cana-1616	172	37	bags	bag	NOUN
cana-1616	172	38	m	m	VERB
cana-1616	172	39	with	with	ADP
cana-1616	172	40	rf1	rf1	NOUN
cana-1616	172	41	rf2	rf2	VERB
cana-1616	172	42	rf	rf	NUM
cana-1616	172	43	3	3	NUM
cana-1616	172	44	rf4	rf4	NOUN
cana-1616	172	45	rf	rf	VERB
cana-1616	172	46	with	with	ADP
cana-1616	172	47	5	5	NUM
cana-1616	172	48	bags	bag	NOUN
cana-1616	172	49	m	m	VERB
cana-1616	172	50	with	with	ADP
cana-1616	172	51	dt1	dt1	PROPN
cana-1616	172	52	dt2	dt2	PROPN
cana-1616	172	53	dt	dt	PROPN
cana-1616	172	54	3	3	NUM
cana-1616	172	55	dt4	dt4	NOUN
cana-1616	172	56	dt	dt	NOUN
cana-1616	172	57	with	with	SCONJ
cana-1616	172	58	5	5	NUM
cana-1616	172	59	bags	bag	NOUN
cana-1616	172	60	communications	communication	NOUN
cana-1616	172	61	on	on	ADP
cana-1616	172	62	applied	apply	VERB
cana-1616	172	63	nonlinear	nonlinear	ADJ
cana-1616	172	64	analysis	analysis	NOUN
cana-1616	172	65	issn	issn	NOUN
cana-1616	172	66	:	:	PUNCT
cana-1616	172	67	1074	1074	NUM
cana-1616	172	68	-	-	PUNCT
cana-1616	172	69	133x	133x	NUM
cana-1616	172	70	vol	vol	NOUN
cana-1616	172	71	31	31	NUM
cana-1616	172	72	no	no	NOUN
cana-1616	172	73	.	.	PUNCT
cana-1616	173	1	8s	8s	PROPN
cana-1616	173	2	(	(	PUNCT
cana-1616	173	3	2024	2024	NUM
cana-1616	173	4	)	)	PUNCT
cana-1616	173	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	174	1	784	784	NUM
cana-1616	174	2	4.2	4.2	NUM
cana-1616	174	3	how	how	SCONJ
cana-1616	174	4	proposed	propose	VERB
cana-1616	174	5	neuroopt	neuroopt	NOUN
cana-1616	174	6	is	be	AUX
cana-1616	174	7	better	well	ADJ
cana-1616	174	8	?	?	PUNCT
cana-1616	175	1	the	the	DET
cana-1616	175	2	proposed	propose	VERB
cana-1616	175	3	neuroopt	neuroopt	PROPN
cana-1616	175	4	model	model	NOUN
cana-1616	175	5	stands	stand	VERB
cana-1616	175	6	out	out	ADP
cana-1616	175	7	as	as	ADP
cana-1616	175	8	a	a	DET
cana-1616	175	9	highly	highly	ADV
cana-1616	175	10	effective	effective	ADJ
cana-1616	175	11	method	method	NOUN
cana-1616	175	12	for	for	ADP
cana-1616	175	13	liver	liver	NOUN
cana-1616	175	14	disease	disease	NOUN
cana-1616	175	15	detection	detection	NOUN
cana-1616	175	16	,	,	PUNCT
cana-1616	175	17	addressing	address	VERB
cana-1616	175	18	key	key	ADJ
cana-1616	175	19	limitations	limitation	NOUN
cana-1616	175	20	in	in	ADP
cana-1616	175	21	existing	exist	VERB
cana-1616	175	22	approaches	approach	NOUN
cana-1616	175	23	.	.	PUNCT
cana-1616	176	1	our	our	PRON
cana-1616	176	2	model	model	NOUN
cana-1616	176	3	's	's	PART
cana-1616	176	4	superiority	superiority	NOUN
cana-1616	176	5	lies	lie	VERB
cana-1616	176	6	in	in	ADP
cana-1616	176	7	its	its	PRON
cana-1616	176	8	comprehensive	comprehensive	ADJ
cana-1616	176	9	design	design	NOUN
cana-1616	176	10	and	and	CCONJ
cana-1616	176	11	practical	practical	ADJ
cana-1616	176	12	implementation	implementation	NOUN
cana-1616	176	13	,	,	PUNCT
cana-1616	176	14	which	which	PRON
cana-1616	176	15	surpasses	surpass	VERB
cana-1616	176	16	current	current	ADJ
cana-1616	176	17	methods	method	NOUN
cana-1616	176	18	commonly	commonly	ADV
cana-1616	176	19	found	find	VERB
cana-1616	176	20	on	on	ADP
cana-1616	176	21	the	the	DET
cana-1616	176	22	kaggle	kaggle	NOUN
cana-1616	176	23	site	site	NOUN
cana-1616	176	24	,	,	PUNCT
cana-1616	176	25	where	where	SCONJ
cana-1616	176	26	the	the	DET
cana-1616	176	27	ilpd	ilpd	NOUN
cana-1616	176	28	and	and	CCONJ
cana-1616	176	29	cpd	cpd	ADJ
cana-1616	176	30	datasets	dataset	NOUN
cana-1616	176	31	are	be	AUX
cana-1616	176	32	sourced	source	VERB
cana-1616	176	33	.	.	PUNCT
cana-1616	177	1	unlike	unlike	ADP
cana-1616	177	2	the	the	DET
cana-1616	177	3	majority	majority	NOUN
cana-1616	177	4	of	of	ADP
cana-1616	177	5	existing	exist	VERB
cana-1616	177	6	models	model	NOUN
cana-1616	177	7	that	that	PRON
cana-1616	177	8	perform	perform	VERB
cana-1616	177	9	binary	binary	ADJ
cana-1616	177	10	classification	classification	NOUN
cana-1616	177	11	using	use	VERB
cana-1616	177	12	a	a	DET
cana-1616	177	13	single	single	ADJ
cana-1616	177	14	dataset	dataset	NOUN
cana-1616	177	15	,	,	PUNCT
cana-1616	177	16	neuroopt	neuroopt	PROPN
cana-1616	177	17	incorporates	incorporate	VERB
cana-1616	177	18	a	a	DET
cana-1616	177	19	multi	multi	ADJ
cana-1616	177	20	-	-	ADJ
cana-1616	177	21	stage	stage	ADJ
cana-1616	177	22	classification	classification	NOUN
cana-1616	177	23	system	system	NOUN
cana-1616	177	24	and	and	CCONJ
cana-1616	177	25	leverages	leverage	VERB
cana-1616	177	26	both	both	CCONJ
cana-1616	177	27	ilpd	ilpd	NOUN
cana-1616	177	28	and	and	CCONJ
cana-1616	177	29	cpd	cpd	ADJ
cana-1616	177	30	datasets	dataset	NOUN
cana-1616	177	31	,	,	PUNCT
cana-1616	177	32	significantly	significantly	ADV
cana-1616	177	33	enhancing	enhance	VERB
cana-1616	177	34	its	its	PRON
cana-1616	177	35	versatility	versatility	NOUN
cana-1616	177	36	and	and	CCONJ
cana-1616	177	37	applicability	applicability	NOUN
cana-1616	177	38	.	.	PUNCT
cana-1616	178	1	while	while	SCONJ
cana-1616	178	2	reviewing	review	VERB
cana-1616	178	3	existing	exist	VERB
cana-1616	178	4	liver	liver	NOUN
cana-1616	178	5	disease	disease	NOUN
cana-1616	178	6	detection	detection	NOUN
cana-1616	178	7	models	model	NOUN
cana-1616	178	8	revealed	reveal	VERB
cana-1616	178	9	that	that	SCONJ
cana-1616	178	10	most	most	ADJ
cana-1616	178	11	achieve	achieve	VERB
cana-1616	178	12	an	an	DET
cana-1616	178	13	accuracy	accuracy	NOUN
cana-1616	178	14	range	range	NOUN
cana-1616	178	15	of	of	ADP
cana-1616	178	16	70	70	NUM
cana-1616	178	17	%	%	NOUN
cana-1616	178	18	to	to	ADP
cana-1616	178	19	93	93	NUM
cana-1616	178	20	%	%	NOUN
cana-1616	178	21	on	on	ADP
cana-1616	178	22	the	the	DET
cana-1616	178	23	ilpd	ilpd	NOUN
cana-1616	178	24	dataset	dataset	NOUN
cana-1616	178	25	,	,	PUNCT
cana-1616	178	26	which	which	PRON
cana-1616	178	27	is	be	AUX
cana-1616	178	28	suboptimal	suboptimal	ADJ
cana-1616	178	29	for	for	ADP
cana-1616	178	30	a	a	DET
cana-1616	178	31	reliable	reliable	ADJ
cana-1616	178	32	binary	binary	ADJ
cana-1616	178	33	classification	classification	NOUN
cana-1616	178	34	system	system	NOUN
cana-1616	178	35	.	.	PUNCT
cana-1616	179	1	although	although	SCONJ
cana-1616	179	2	a	a	DET
cana-1616	179	3	few	few	ADJ
cana-1616	179	4	models	model	NOUN
cana-1616	179	5	approach	approach	VERB
cana-1616	179	6	99	99	NUM
cana-1616	179	7	%	%	NOUN
cana-1616	179	8	accuracy	accuracy	NOUN
cana-1616	179	9	,	,	PUNCT
cana-1616	179	10	they	they	PRON
cana-1616	179	11	lack	lack	VERB
cana-1616	179	12	dynamism	dynamism	NOUN
cana-1616	179	13	and	and	CCONJ
cana-1616	179	14	are	be	AUX
cana-1616	179	15	limited	limit	VERB
cana-1616	179	16	to	to	ADP
cana-1616	179	17	predicting	predict	VERB
cana-1616	179	18	disease	disease	NOUN
cana-1616	179	19	presence	presence	NOUN
cana-1616	179	20	or	or	CCONJ
cana-1616	179	21	absence	absence	NOUN
cana-1616	179	22	within	within	ADP
cana-1616	179	23	a	a	DET
cana-1616	179	24	single	single	ADJ
cana-1616	179	25	dataset	dataset	NOUN
cana-1616	179	26	.	.	PUNCT
cana-1616	180	1	recognizing	recognize	VERB
cana-1616	180	2	these	these	DET
cana-1616	180	3	shortcomings	shortcoming	NOUN
cana-1616	180	4	,	,	PUNCT
cana-1616	180	5	we	we	PRON
cana-1616	180	6	aimed	aim	VERB
cana-1616	180	7	to	to	PART
cana-1616	180	8	develop	develop	VERB
cana-1616	180	9	a	a	DET
cana-1616	180	10	more	more	ADV
cana-1616	180	11	dynamic	dynamic	ADJ
cana-1616	180	12	and	and	CCONJ
cana-1616	180	13	practical	practical	ADJ
cana-1616	180	14	model	model	NOUN
cana-1616	180	15	by	by	ADP
cana-1616	180	16	integrating	integrate	VERB
cana-1616	180	17	two	two	NUM
cana-1616	180	18	datasets	dataset	NOUN
cana-1616	180	19	and	and	CCONJ
cana-1616	180	20	addressing	address	VERB
cana-1616	180	21	both	both	CCONJ
cana-1616	180	22	binary	binary	ADJ
cana-1616	180	23	and	and	CCONJ
cana-1616	180	24	multi	multi	ADJ
cana-1616	180	25	-	-	ADJ
cana-1616	180	26	stage	stage	ADJ
cana-1616	180	27	classification	classification	NOUN
cana-1616	180	28	challenges	challenge	NOUN
cana-1616	180	29	.	.	PUNCT
cana-1616	181	1	however	however	ADV
cana-1616	181	2	,	,	PUNCT
cana-1616	181	3	the	the	DET
cana-1616	181	4	cpd	cpd	NOUN
cana-1616	181	5	dataset	dataset	NOUN
cana-1616	181	6	,	,	PUNCT
cana-1616	181	7	in	in	ADP
cana-1616	181	8	particular	particular	ADJ
cana-1616	181	9	,	,	PUNCT
cana-1616	181	10	posed	pose	VERB
cana-1616	181	11	a	a	DET
cana-1616	181	12	significant	significant	ADJ
cana-1616	181	13	challenge	challenge	NOUN
cana-1616	181	14	for	for	ADP
cana-1616	181	15	existing	exist	VERB
cana-1616	181	16	models	model	NOUN
cana-1616	181	17	,	,	PUNCT
cana-1616	181	18	which	which	PRON
cana-1616	181	19	demonstrated	demonstrate	VERB
cana-1616	181	20	an	an	DET
cana-1616	181	21	accuracy	accuracy	NOUN
cana-1616	181	22	range	range	NOUN
cana-1616	181	23	of	of	ADP
cana-1616	181	24	only	only	ADV
cana-1616	181	25	40	40	NUM
cana-1616	181	26	%	%	NOUN
cana-1616	181	27	to	to	PART
cana-1616	181	28	67	67	NUM
cana-1616	181	29	%	%	NOUN
cana-1616	181	30	for	for	ADP
cana-1616	181	31	multi	multi	ADJ
cana-1616	181	32	-	-	ADJ
cana-1616	181	33	class	class	ADJ
cana-1616	181	34	classification	classification	NOUN
cana-1616	181	35	,	,	PUNCT
cana-1616	181	36	highlighting	highlight	VERB
cana-1616	181	37	their	their	PRON
cana-1616	181	38	ineffectiveness	ineffectiveness	NOUN
cana-1616	181	39	for	for	ADP
cana-1616	181	40	categorizing	categorize	VERB
cana-1616	181	41	multiple	multiple	ADJ
cana-1616	181	42	stages	stage	NOUN
cana-1616	181	43	of	of	ADP
cana-1616	181	44	liver	liver	NOUN
cana-1616	181	45	diseases	disease	NOUN
cana-1616	181	46	.	.	PUNCT
cana-1616	182	1	to	to	PART
cana-1616	182	2	overcome	overcome	VERB
cana-1616	182	3	these	these	DET
cana-1616	182	4	issues	issue	NOUN
cana-1616	182	5	,	,	PUNCT
cana-1616	182	6	we	we	PRON
cana-1616	182	7	introduced	introduce	VERB
cana-1616	182	8	a	a	DET
cana-1616	182	9	three	three	NUM
cana-1616	182	10	-	-	PUNCT
cana-1616	182	11	stage	stage	NOUN
cana-1616	182	12	feature	feature	NOUN
cana-1616	182	13	selection	selection	NOUN
cana-1616	182	14	technique	technique	NOUN
cana-1616	182	15	,	,	PUNCT
cana-1616	182	16	enhancing	enhance	VERB
cana-1616	182	17	the	the	DET
cana-1616	182	18	model	model	NOUN
cana-1616	182	19	's	's	PART
cana-1616	182	20	ability	ability	NOUN
cana-1616	182	21	to	to	PART
cana-1616	182	22	extract	extract	VERB
cana-1616	182	23	relevant	relevant	ADJ
cana-1616	182	24	features	feature	NOUN
cana-1616	182	25	efficiently	efficiently	ADV
cana-1616	182	26	.	.	PUNCT
cana-1616	183	1	furthermore	furthermore	ADV
cana-1616	183	2	,	,	PUNCT
cana-1616	183	3	we	we	PRON
cana-1616	183	4	employed	employ	VERB
cana-1616	183	5	the	the	DET
cana-1616	183	6	neuroopt	neuroopt	PROPN
cana-1616	183	7	model	model	NOUN
cana-1616	183	8	,	,	PUNCT
cana-1616	183	9	which	which	PRON
cana-1616	183	10	utilizes	utilize	VERB
cana-1616	183	11	a	a	DET
cana-1616	183	12	neural	neural	ADJ
cana-1616	183	13	network	network	NOUN
cana-1616	183	14	optimized	optimize	VERB
cana-1616	183	15	with	with	ADP
cana-1616	183	16	gwoa2	gwoa2	NOUN
cana-1616	183	17	to	to	ADP
cana-1616	183	18	fine	fine	ADJ
cana-1616	183	19	-	-	PUNCT
cana-1616	183	20	tune	tune	NOUN
cana-1616	183	21	hyperparameters	hyperparameter	NOUN
cana-1616	183	22	and	and	CCONJ
cana-1616	183	23	improve	improve	VERB
cana-1616	183	24	predictive	predictive	ADJ
cana-1616	183	25	accuracy	accuracy	NOUN
cana-1616	183	26	.	.	PUNCT
cana-1616	184	1	by	by	ADP
cana-1616	184	2	implementing	implement	VERB
cana-1616	184	3	these	these	DET
cana-1616	184	4	advancements	advancement	NOUN
cana-1616	184	5	,	,	PUNCT
cana-1616	184	6	our	our	PRON
cana-1616	184	7	proposed	propose	VERB
cana-1616	184	8	neuroopt	neuroopt	PROPN
cana-1616	184	9	model	model	NOUN
cana-1616	184	10	not	not	PART
cana-1616	184	11	only	only	ADV
cana-1616	184	12	increases	increase	VERB
cana-1616	184	13	the	the	DET
cana-1616	184	14	accuracy	accuracy	NOUN
cana-1616	184	15	rate	rate	NOUN
cana-1616	184	16	for	for	ADP
cana-1616	184	17	both	both	CCONJ
cana-1616	184	18	binary	binary	ADJ
cana-1616	184	19	and	and	CCONJ
cana-1616	184	20	multi	multi	ADJ
cana-1616	184	21	-	-	ADJ
cana-1616	184	22	class	class	ADJ
cana-1616	184	23	classification	classification	NOUN
cana-1616	184	24	but	but	CCONJ
cana-1616	184	25	also	also	ADV
cana-1616	184	26	offers	offer	VERB
cana-1616	184	27	a	a	DET
cana-1616	184	28	dynamic	dynamic	ADJ
cana-1616	184	29	and	and	CCONJ
cana-1616	184	30	practical	practical	ADJ
cana-1616	184	31	solution	solution	NOUN
cana-1616	184	32	that	that	PRON
cana-1616	184	33	addresses	address	VERB
cana-1616	184	34	the	the	DET
cana-1616	184	35	limitations	limitation	NOUN
cana-1616	184	36	of	of	ADP
cana-1616	184	37	current	current	ADJ
cana-1616	184	38	liver	liver	NOUN
cana-1616	184	39	disease	disease	NOUN
cana-1616	184	40	detection	detection	NOUN
cana-1616	184	41	models	model	NOUN
cana-1616	184	42	.	.	PUNCT
cana-1616	185	1	it	it	PRON
cana-1616	185	2	is	be	AUX
cana-1616	185	3	pertinent	pertinent	ADJ
cana-1616	185	4	to	to	PART
cana-1616	185	5	mention	mention	VERB
cana-1616	185	6	here	here	ADV
cana-1616	185	7	that	that	SCONJ
cana-1616	185	8	gwoa2	gwoa2	NOUN
cana-1616	185	9	tuned	tune	VERB
cana-1616	185	10	ffnn	ffnn	NOUN
cana-1616	185	11	is	be	AUX
cana-1616	185	12	proven	prove	VERB
cana-1616	185	13	out	out	ADP
cana-1616	185	14	to	to	PART
cana-1616	185	15	be	be	AUX
cana-1616	185	16	highly	highly	ADV
cana-1616	185	17	effective	effective	ADJ
cana-1616	185	18	than	than	ADP
cana-1616	185	19	conventional	conventional	ADJ
cana-1616	185	20	approaches	approach	NOUN
cana-1616	185	21	on	on	ADP
cana-1616	185	22	both	both	DET
cana-1616	185	23	kaggle	kaggle	ADJ
cana-1616	185	24	datasets	dataset	NOUN
cana-1616	185	25	,	,	PUNCT
cana-1616	185	26	as	as	SCONJ
cana-1616	185	27	proven	prove	VERB
cana-1616	185	28	by	by	ADP
cana-1616	185	29	accuracy	accuracy	NOUN
cana-1616	185	30	rates	rate	NOUN
cana-1616	185	31	discussed	discuss	VERB
cana-1616	185	32	in	in	ADP
cana-1616	185	33	results	result	NOUN
cana-1616	185	34	section	section	NOUN
cana-1616	185	35	of	of	ADP
cana-1616	185	36	this	this	DET
cana-1616	185	37	paper	paper	NOUN
cana-1616	185	38	.	.	PUNCT
cana-1616	186	1	5	5	X
cana-1616	186	2	.	.	NOUN
cana-1616	186	3	results	result	NOUN
cana-1616	186	4	and	and	CCONJ
cana-1616	186	5	discussions	discussion	NOUN
cana-1616	186	6	this	this	DET
cana-1616	186	7	section	section	NOUN
cana-1616	186	8	discusses	discuss	VERB
cana-1616	186	9	the	the	DET
cana-1616	186	10	results	result	NOUN
cana-1616	186	11	obtained	obtain	VERB
cana-1616	186	12	for	for	ADP
cana-1616	186	13	the	the	DET
cana-1616	186	14	proposed	propose	VERB
cana-1616	186	15	liver	liver	NOUN
cana-1616	186	16	disease	disease	NOUN
cana-1616	186	17	detection	detection	NOUN
cana-1616	186	18	approach	approach	NOUN
cana-1616	186	19	over	over	ADP
cana-1616	186	20	other	other	ADJ
cana-1616	186	21	similar	similar	ADJ
cana-1616	186	22	models	model	NOUN
cana-1616	186	23	for	for	ADP
cana-1616	186	24	both	both	CCONJ
cana-1616	186	25	binary	binary	ADJ
cana-1616	186	26	and	and	CCONJ
cana-1616	186	27	multi	multi	ADJ
cana-1616	186	28	-	-	ADJ
cana-1616	186	29	stage	stage	ADJ
cana-1616	186	30	disease	disease	NOUN
cana-1616	186	31	classifications	classification	NOUN
cana-1616	186	32	on	on	ADP
cana-1616	186	33	ilpd	ilpd	NOUN
cana-1616	186	34	and	and	CCONJ
cana-1616	186	35	cpd	cpd	ADJ
cana-1616	186	36	datasets	dataset	NOUN
cana-1616	186	37	respectively	respectively	ADV
cana-1616	186	38	.	.	PUNCT
cana-1616	187	1	moreover	moreover	ADV
cana-1616	187	2	,	,	PUNCT
cana-1616	187	3	we	we	PRON
cana-1616	187	4	will	will	AUX
cana-1616	187	5	also	also	ADV
cana-1616	187	6	cover	cover	VERB
cana-1616	187	7	the	the	DET
cana-1616	187	8	experimental	experimental	ADJ
cana-1616	187	9	settings	setting	NOUN
cana-1616	187	10	used	use	VERB
cana-1616	187	11	for	for	ADP
cana-1616	187	12	the	the	DET
cana-1616	187	13	proposed	propose	VERB
cana-1616	187	14	approach	approach	NOUN
cana-1616	187	15	during	during	ADP
cana-1616	187	16	the	the	DET
cana-1616	187	17	testing	testing	NOUN
cana-1616	187	18	phase	phase	NOUN
cana-1616	187	19	.	.	PUNCT
cana-1616	188	1	5.1	5.1	NUM
cana-1616	188	2	simulation	simulation	NOUN
cana-1616	188	3	setup	setup	VERB
cana-1616	188	4	the	the	DET
cana-1616	188	5	effectiveness	effectiveness	NOUN
cana-1616	188	6	of	of	ADP
cana-1616	188	7	the	the	DET
cana-1616	188	8	proposed	propose	VERB
cana-1616	188	9	approach	approach	NOUN
cana-1616	188	10	is	be	AUX
cana-1616	188	11	examined	examine	VERB
cana-1616	188	12	and	and	CCONJ
cana-1616	188	13	compared	compare	VERB
cana-1616	188	14	with	with	ADP
cana-1616	188	15	traditional	traditional	ADJ
cana-1616	188	16	liver	liver	NOUN
cana-1616	188	17	disease	disease	NOUN
cana-1616	188	18	detection	detection	NOUN
cana-1616	188	19	models	model	NOUN
cana-1616	188	20	in	in	ADP
cana-1616	188	21	matlab	matlab	PROPN
cana-1616	188	22	software	software	NOUN
cana-1616	188	23	.	.	PUNCT
cana-1616	189	1	this	this	DET
cana-1616	189	2	software	software	NOUN
cana-1616	189	3	was	be	AUX
cana-1616	189	4	operated	operate	VERB
cana-1616	189	5	on	on	ADP
cana-1616	189	6	a	a	DET
cana-1616	189	7	system	system	NOUN
cana-1616	189	8	with	with	ADP
cana-1616	189	9	i5	i5	NOUN
cana-1616	189	10	core	core	NOUN
cana-1616	189	11	processor	processor	NOUN
cana-1616	189	12	and	and	CCONJ
cana-1616	189	13	8	8	NUM
cana-1616	189	14	gb	gb	NOUN
cana-1616	189	15	ram	ram	NOUN
cana-1616	189	16	.	.	PUNCT
cana-1616	190	1	moreover	moreover	ADV
cana-1616	190	2	,	,	PUNCT
cana-1616	190	3	the	the	DET
cana-1616	190	4	os	os	NOUN
cana-1616	190	5	we	we	PRON
cana-1616	190	6	used	use	VERB
cana-1616	190	7	was	be	AUX
cana-1616	190	8	windows	window	NOUN
cana-1616	190	9	10	10	NUM
cana-1616	190	10	pro	pro	X
cana-1616	190	11	with	with	ADP
cana-1616	190	12	500	500	NUM
cana-1616	190	13	gb	gb	NOUN
cana-1616	190	14	hdd	hdd	NOUN
cana-1616	190	15	.	.	PUNCT
cana-1616	191	1	with	with	ADP
cana-1616	191	2	this	this	DET
cana-1616	191	3	configuration	configuration	NOUN
cana-1616	191	4	,	,	PUNCT
cana-1616	191	5	we	we	PRON
cana-1616	191	6	aim	aim	VERB
cana-1616	191	7	to	to	PART
cana-1616	191	8	analyze	analyze	VERB
cana-1616	191	9	the	the	DET
cana-1616	191	10	performance	performance	NOUN
cana-1616	191	11	of	of	ADP
cana-1616	191	12	various	various	ADJ
cana-1616	191	13	conventional	conventional	ADJ
cana-1616	191	14	models	model	NOUN
cana-1616	191	15	for	for	ADP
cana-1616	191	16	binary	binary	ADJ
cana-1616	191	17	and	and	CCONJ
cana-1616	191	18	multi	multi	ADJ
cana-1616	191	19	-	-	ADJ
cana-1616	191	20	class	class	ADJ
cana-1616	191	21	classifications	classification	NOUN
cana-1616	191	22	,	,	PUNCT
cana-1616	191	23	elaborately	elaborately	ADV
cana-1616	191	24	discussed	discuss	VERB
cana-1616	191	25	in	in	ADP
cana-1616	191	26	this	this	DET
cana-1616	191	27	section	section	NOUN
cana-1616	191	28	of	of	ADP
cana-1616	191	29	manuscript	manuscript	NOUN
cana-1616	191	30	.	.	PUNCT
cana-1616	192	1	5.2	5.2	NUM
cana-1616	192	2	binary	binary	NOUN
cana-1616	192	3	classification	classification	NOUN
cana-1616	192	4	results	result	VERB
cana-1616	192	5	the	the	DET
cana-1616	192	6	binary	binary	ADJ
cana-1616	192	7	classification	classification	NOUN
cana-1616	192	8	is	be	AUX
cana-1616	192	9	performed	perform	VERB
cana-1616	192	10	on	on	ADP
cana-1616	192	11	ilpd	ilpd	NOUN
cana-1616	192	12	dataset	dataset	VERB
cana-1616	192	13	using	use	VERB
cana-1616	192	14	proposed	propose	VERB
cana-1616	192	15	model	model	NOUN
cana-1616	192	16	.	.	PUNCT
cana-1616	193	1	to	to	PART
cana-1616	193	2	begin	begin	VERB
cana-1616	193	3	with	with	ADP
cana-1616	193	4	,	,	PUNCT
cana-1616	193	5	we	we	PRON
cana-1616	193	6	have	have	AUX
cana-1616	193	7	firstly	firstly	ADV
cana-1616	193	8	analyzed	analyze	VERB
cana-1616	193	9	the	the	DET
cana-1616	193	10	performance	performance	NOUN
cana-1616	193	11	of	of	ADP
cana-1616	193	12	our	our	PRON
cana-1616	193	13	liver	liver	NOUN
cana-1616	193	14	disease	disease	NOUN
cana-1616	193	15	detection	detection	NOUN
cana-1616	193	16	approach	approach	NOUN
cana-1616	193	17	by	by	ADP
cana-1616	193	18	observing	observe	VERB
cana-1616	193	19	its	its	PRON
cana-1616	193	20	confusion	confusion	NOUN
cana-1616	193	21	matrix	matrix	NOUN
cana-1616	193	22	table	table	NOUN
cana-1616	193	23	.	.	PUNCT
cana-1616	194	1	the	the	DET
cana-1616	194	2	main	main	ADJ
cana-1616	194	3	reason	reason	NOUN
cana-1616	194	4	for	for	ADP
cana-1616	194	5	doing	do	VERB
cana-1616	194	6	so	so	ADV
cana-1616	194	7	is	be	AUX
cana-1616	194	8	that	that	SCONJ
cana-1616	194	9	this	this	DET
cana-1616	194	10	matrix	matrix	NOUN
cana-1616	194	11	helps	help	VERB
cana-1616	194	12	us	we	PRON
cana-1616	194	13	in	in	ADP
cana-1616	194	14	evaluating	evaluate	VERB
cana-1616	194	15	other	other	ADJ
cana-1616	194	16	important	important	ADJ
cana-1616	194	17	communications	communication	NOUN
cana-1616	194	18	on	on	ADP
cana-1616	194	19	applied	apply	VERB
cana-1616	194	20	nonlinear	nonlinear	ADJ
cana-1616	194	21	analysis	analysis	NOUN
cana-1616	194	22	issn	issn	NOUN
cana-1616	194	23	:	:	PUNCT
cana-1616	194	24	1074	1074	NUM
cana-1616	194	25	-	-	PUNCT
cana-1616	194	26	133x	133x	NUM
cana-1616	194	27	vol	vol	NOUN
cana-1616	194	28	31	31	NUM
cana-1616	194	29	no	no	NOUN
cana-1616	194	30	.	.	PUNCT
cana-1616	195	1	8s	8s	PROPN
cana-1616	195	2	(	(	PUNCT
cana-1616	195	3	2024	2024	NUM
cana-1616	195	4	)	)	PUNCT
cana-1616	195	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	195	6	785	785	NUM
cana-1616	195	7	parameters	parameter	NOUN
cana-1616	195	8	easily	easily	ADV
cana-1616	195	9	.	.	PUNCT
cana-1616	196	1	figure	figure	NOUN
cana-1616	196	2	5	5	NUM
cana-1616	196	3	represents	represent	VERB
cana-1616	196	4	the	the	DET
cana-1616	196	5	confusion	confusion	NOUN
cana-1616	196	6	matrix	matrix	NOUN
cana-1616	196	7	of	of	ADP
cana-1616	196	8	the	the	DET
cana-1616	196	9	proposed	propose	VERB
cana-1616	196	10	model	model	NOUN
cana-1616	196	11	with	with	ADP
cana-1616	196	12	target	target	NOUN
cana-1616	196	13	class	class	NOUN
cana-1616	196	14	and	and	CCONJ
cana-1616	196	15	output	output	NOUN
cana-1616	196	16	class	class	NOUN
cana-1616	196	17	on	on	ADP
cana-1616	196	18	x	x	X
cana-1616	196	19	and	and	CCONJ
cana-1616	196	20	y	y	NOUN
cana-1616	196	21	-	-	PUNCT
cana-1616	196	22	axis	axis	NOUN
cana-1616	196	23	respectively	respectively	ADV
cana-1616	196	24	.	.	PUNCT
cana-1616	197	1	liver	liver	NOUN
cana-1616	197	2	disease	disease	NOUN
cana-1616	197	3	detection	detection	NOUN
cana-1616	197	4	is	be	AUX
cana-1616	197	5	a	a	DET
cana-1616	197	6	binary	binary	ADJ
cana-1616	197	7	classification	classification	NOUN
cana-1616	197	8	problem	problem	NOUN
cana-1616	197	9	where	where	SCONJ
cana-1616	197	10	the	the	DET
cana-1616	197	11	goal	goal	NOUN
cana-1616	197	12	is	be	AUX
cana-1616	197	13	to	to	PART
cana-1616	197	14	distinguish	distinguish	VERB
cana-1616	197	15	between	between	ADP
cana-1616	197	16	patients	patient	NOUN
cana-1616	197	17	with	with	ADP
cana-1616	197	18	liver	liver	NOUN
cana-1616	197	19	disease	disease	NOUN
cana-1616	197	20	(	(	PUNCT
cana-1616	197	21	positive	positive	ADJ
cana-1616	197	22	class	class	NOUN
cana-1616	197	23	)	)	PUNCT
cana-1616	197	24	and	and	CCONJ
cana-1616	197	25	those	those	PRON
cana-1616	197	26	without	without	ADP
cana-1616	197	27	liver	liver	NOUN
cana-1616	197	28	disease	disease	NOUN
cana-1616	197	29	(	(	PUNCT
cana-1616	197	30	negative	negative	ADJ
cana-1616	197	31	class	class	NOUN
cana-1616	197	32	)	)	PUNCT
cana-1616	197	33	.	.	PUNCT
cana-1616	198	1	the	the	DET
cana-1616	198	2	confusion	confusion	NOUN
cana-1616	198	3	matrix	matrix	NOUN
cana-1616	198	4	helps	help	VERB
cana-1616	198	5	to	to	PART
cana-1616	198	6	evaluate	evaluate	VERB
cana-1616	198	7	the	the	DET
cana-1616	198	8	model	model	NOUN
cana-1616	198	9	's	's	PART
cana-1616	198	10	performance	performance	NOUN
cana-1616	198	11	in	in	ADP
cana-1616	198	12	such	such	ADJ
cana-1616	198	13	scenarios	scenario	NOUN
cana-1616	198	14	.	.	PUNCT
cana-1616	199	1	by	by	ADP
cana-1616	199	2	observing	observe	VERB
cana-1616	199	3	the	the	DET
cana-1616	199	4	trend	trend	NOUN
cana-1616	199	5	in	in	ADP
cana-1616	199	6	confusion	confusion	NOUN
cana-1616	199	7	matrix	matrix	NOUN
cana-1616	199	8	,	,	PUNCT
cana-1616	199	9	we	we	PRON
cana-1616	199	10	observed	observe	VERB
cana-1616	199	11	our	our	PRON
cana-1616	199	12	model	model	NOUN
cana-1616	199	13	attains	attain	NOUN
cana-1616	199	14	an	an	DET
cana-1616	199	15	overall	overall	ADJ
cana-1616	199	16	accuracy	accuracy	NOUN
cana-1616	199	17	of	of	ADP
cana-1616	199	18	93.2	93.2	NUM
cana-1616	199	19	%	%	NOUN
cana-1616	199	20	.	.	PUNCT
cana-1616	200	1	figure	figure	NOUN
cana-1616	200	2	5	5	NUM
cana-1616	200	3	.	.	PUNCT
cana-1616	200	4	confusion	confusion	NOUN
cana-1616	200	5	matrix	matrix	NOUN
cana-1616	200	6	of	of	ADP
cana-1616	200	7	proposed	propose	VERB
cana-1616	200	8	model	model	NOUN
cana-1616	200	9	for	for	ADP
cana-1616	200	10	binary	binary	ADJ
cana-1616	200	11	classification	classification	NOUN
cana-1616	200	12	moreover	moreover	ADV
cana-1616	200	13	,	,	PUNCT
cana-1616	200	14	we	we	PRON
cana-1616	200	15	have	have	AUX
cana-1616	200	16	also	also	ADV
cana-1616	200	17	evaluated	evaluate	VERB
cana-1616	200	18	the	the	DET
cana-1616	200	19	performance	performance	NOUN
cana-1616	200	20	of	of	ADP
cana-1616	200	21	proposed	propose	VERB
cana-1616	200	22	approach	approach	NOUN
cana-1616	200	23	in	in	ADP
cana-1616	200	24	terms	term	NOUN
cana-1616	200	25	of	of	ADP
cana-1616	200	26	its	its	PRON
cana-1616	200	27	roc	roc	NOUN
cana-1616	200	28	graph	graph	NOUN
cana-1616	200	29	.	.	PUNCT
cana-1616	201	1	it	it	PRON
cana-1616	201	2	is	be	AUX
cana-1616	201	3	used	use	VERB
cana-1616	201	4	to	to	PART
cana-1616	201	5	assess	assess	VERB
cana-1616	201	6	and	and	CCONJ
cana-1616	201	7	visualize	visualize	VERB
cana-1616	201	8	the	the	DET
cana-1616	201	9	trade	trade	NOUN
cana-1616	201	10	-	-	PUNCT
cana-1616	201	11	off	off	NOUN
cana-1616	201	12	between	between	ADP
cana-1616	201	13	the	the	DET
cana-1616	201	14	true	true	ADJ
cana-1616	201	15	positive	positive	ADJ
cana-1616	201	16	rate	rate	NOUN
cana-1616	201	17	(	(	PUNCT
cana-1616	201	18	tpr	tpr	NOUN
cana-1616	201	19	)	)	PUNCT
cana-1616	201	20	on	on	ADP
cana-1616	201	21	y	y	NOUN
cana-1616	201	22	-	-	PUNCT
cana-1616	201	23	axis	axis	NOUN
cana-1616	201	24	and	and	CCONJ
cana-1616	201	25	the	the	DET
cana-1616	201	26	false	false	ADJ
cana-1616	201	27	positive	positive	ADJ
cana-1616	201	28	rate	rate	NOUN
cana-1616	201	29	(	(	PUNCT
cana-1616	201	30	fpr	fpr	NOUN
cana-1616	201	31	)	)	PUNCT
cana-1616	201	32	on	on	ADP
cana-1616	201	33	x	x	NOUN
cana-1616	201	34	-	-	NOUN
cana-1616	201	35	axis	axis	NOUN
cana-1616	201	36	of	of	ADP
cana-1616	201	37	a	a	DET
cana-1616	201	38	classification	classification	NOUN
cana-1616	201	39	model	model	NOUN
cana-1616	201	40	across	across	ADP
cana-1616	201	41	different	different	ADJ
cana-1616	201	42	threshold	threshold	NOUN
cana-1616	201	43	values	value	NOUN
cana-1616	201	44	,	,	PUNCT
cana-1616	201	45	as	as	SCONJ
cana-1616	201	46	shown	show	VERB
cana-1616	201	47	in	in	ADP
cana-1616	201	48	figure	figure	NOUN
cana-1616	201	49	6	6	NUM
cana-1616	201	50	.	.	PUNCT
cana-1616	202	1	the	the	DET
cana-1616	202	2	curve	curve	NOUN
cana-1616	202	3	showcases	showcase	VERB
cana-1616	202	4	how	how	SCONJ
cana-1616	202	5	the	the	DET
cana-1616	202	6	model	model	NOUN
cana-1616	202	7	's	's	PART
cana-1616	202	8	performance	performance	NOUN
cana-1616	202	9	varies	vary	VERB
cana-1616	202	10	as	as	SCONJ
cana-1616	202	11	we	we	PRON
cana-1616	202	12	adjust	adjust	VERB
cana-1616	202	13	the	the	DET
cana-1616	202	14	threshold	threshold	NOUN
cana-1616	202	15	for	for	ADP
cana-1616	202	16	classifying	classify	VERB
cana-1616	202	17	positive	positive	ADJ
cana-1616	202	18	and	and	CCONJ
cana-1616	202	19	negative	negative	ADJ
cana-1616	202	20	instances	instance	NOUN
cana-1616	202	21	.	.	PUNCT
cana-1616	203	1	a	a	DET
cana-1616	203	2	higher	high	ADJ
cana-1616	203	3	tpr	tpr	NOUN
cana-1616	203	4	typically	typically	ADV
cana-1616	203	5	comes	come	VERB
cana-1616	203	6	at	at	ADP
cana-1616	203	7	the	the	DET
cana-1616	203	8	cost	cost	NOUN
cana-1616	203	9	of	of	ADP
cana-1616	203	10	a	a	DET
cana-1616	203	11	higher	high	ADJ
cana-1616	203	12	fpr	fpr	NOUN
cana-1616	203	13	.	.	PUNCT
cana-1616	204	1	the	the	DET
cana-1616	204	2	graph	graph	NOUN
cana-1616	204	3	reveals	reveal	VERB
cana-1616	204	4	that	that	SCONJ
cana-1616	204	5	curve	curve	NOUN
cana-1616	204	6	starts	start	VERB
cana-1616	204	7	at	at	ADP
cana-1616	204	8	the	the	DET
cana-1616	204	9	bottom	bottom	ADV
cana-1616	204	10	-	-	PUNCT
cana-1616	204	11	left	left	ADJ
cana-1616	204	12	corner	corner	NOUN
cana-1616	204	13	(	(	PUNCT
cana-1616	204	14	0	0	NUM
cana-1616	204	15	,	,	PUNCT
cana-1616	204	16	0	0	NUM
cana-1616	204	17	)	)	PUNCT
cana-1616	204	18	and	and	CCONJ
cana-1616	204	19	moves	move	VERB
cana-1616	204	20	upward	upward	ADV
cana-1616	204	21	and	and	CCONJ
cana-1616	204	22	to	to	ADP
cana-1616	204	23	the	the	DET
cana-1616	204	24	right	right	NOUN
cana-1616	204	25	.	.	PUNCT
cana-1616	205	1	the	the	DET
cana-1616	205	2	point	point	NOUN
cana-1616	205	3	on	on	ADP
cana-1616	205	4	the	the	DET
cana-1616	205	5	roc	roc	PROPN
cana-1616	205	6	curve	curve	NOUN
cana-1616	205	7	that	that	PRON
cana-1616	205	8	is	be	AUX
cana-1616	205	9	closest	close	ADJ
cana-1616	205	10	to	to	ADP
cana-1616	205	11	the	the	DET
cana-1616	205	12	top	top	ADV
cana-1616	205	13	-	-	PUNCT
cana-1616	205	14	left	leave	VERB
cana-1616	205	15	corner	corner	NOUN
cana-1616	205	16	represents	represent	VERB
cana-1616	205	17	the	the	DET
cana-1616	205	18	ideal	ideal	ADJ
cana-1616	205	19	balance	balance	NOUN
cana-1616	205	20	between	between	ADP
cana-1616	205	21	true	true	ADJ
cana-1616	205	22	positives	positive	NOUN
cana-1616	205	23	and	and	CCONJ
cana-1616	205	24	false	false	ADJ
cana-1616	205	25	positives	positive	NOUN
cana-1616	205	26	.	.	PUNCT
cana-1616	206	1	by	by	ADP
cana-1616	206	2	analysing	analyse	VERB
cana-1616	206	3	this	this	DET
cana-1616	206	4	curve	curve	NOUN
cana-1616	206	5	,	,	PUNCT
cana-1616	206	6	we	we	PRON
cana-1616	206	7	aim	aim	VERB
cana-1616	206	8	in	in	ADP
cana-1616	206	9	in	in	ADP
cana-1616	206	10	selecting	select	VERB
cana-1616	206	11	an	an	DET
cana-1616	206	12	appropriate	appropriate	ADJ
cana-1616	206	13	classification	classification	NOUN
cana-1616	206	14	threshold	threshold	NOUN
cana-1616	206	15	and	and	CCONJ
cana-1616	206	16	also	also	ADV
cana-1616	206	17	assessed	assess	VERB
cana-1616	206	18	how	how	SCONJ
cana-1616	206	19	well	well	ADV
cana-1616	206	20	our	our	PRON
cana-1616	206	21	model	model	NOUN
cana-1616	206	22	separates	separate	VERB
cana-1616	206	23	the	the	DET
cana-1616	206	24	classes	class	NOUN
cana-1616	206	25	.	.	PUNCT
cana-1616	207	1	figure	figure	VERB
cana-1616	207	2	6	6	NUM
cana-1616	207	3	.	.	PUNCT
cana-1616	208	1	roc	roc	NOUN
cana-1616	208	2	in	in	ADP
cana-1616	208	3	proposed	proposed	ADJ
cana-1616	208	4	model	model	NOUN
cana-1616	208	5	5.3	5.3	NUM
cana-1616	208	6	comparative	comparative	ADJ
cana-1616	208	7	results	result	NOUN
cana-1616	208	8	for	for	ADP
cana-1616	208	9	binary	binary	ADJ
cana-1616	208	10	classification	classification	NOUN
cana-1616	208	11	to	to	PART
cana-1616	208	12	further	far	ADV
cana-1616	208	13	validate	validate	VERB
cana-1616	208	14	the	the	DET
cana-1616	208	15	efficacy	efficacy	NOUN
cana-1616	208	16	of	of	ADP
cana-1616	208	17	proposed	propose	VERB
cana-1616	208	18	approach	approach	NOUN
cana-1616	208	19	,	,	PUNCT
cana-1616	208	20	we	we	PRON
cana-1616	208	21	compared	compare	VERB
cana-1616	208	22	it	it	PRON
cana-1616	208	23	with	with	ADP
cana-1616	208	24	few	few	ADJ
cana-1616	208	25	traditional	traditional	ADJ
cana-1616	208	26	models	model	NOUN
cana-1616	208	27	in	in	ADP
cana-1616	208	28	context	context	NOUN
cana-1616	208	29	of	of	ADP
cana-1616	208	30	their	their	PRON
cana-1616	208	31	respective	respective	ADJ
cana-1616	208	32	accuracy	accuracy	NOUN
cana-1616	208	33	rates	rate	NOUN
cana-1616	208	34	.	.	PUNCT
cana-1616	209	1	the	the	DET
cana-1616	209	2	comparative	comparative	ADJ
cana-1616	209	3	graph	graph	NOUN
cana-1616	209	4	attained	attain	VERB
cana-1616	209	5	for	for	ADP
cana-1616	209	6	accuracy	accuracy	NOUN
cana-1616	209	7	is	be	AUX
cana-1616	209	8	showcased	showcase	VERB
cana-1616	209	9	in	in	ADP
cana-1616	209	10	figure	figure	NOUN
cana-1616	209	11	7	7	NUM
cana-1616	209	12	,	,	PUNCT
cana-1616	209	13	with	with	ADP
cana-1616	209	14	different	different	ADJ
cana-1616	209	15	models	model	NOUN
cana-1616	209	16	and	and	CCONJ
cana-1616	209	17	their	their	PRON
cana-1616	209	18	accuracy	accuracy	NOUN
cana-1616	209	19	values	value	NOUN
cana-1616	209	20	on	on	ADP
cana-1616	209	21	x	x	SYM
cana-1616	209	22	and	and	CCONJ
cana-1616	209	23	y	y	NOUN
cana-1616	209	24	-	-	PUNCT
cana-1616	209	25	axis	axis	NOUN
cana-1616	209	26	respectively	respectively	ADV
cana-1616	209	27	.	.	PUNCT
cana-1616	210	1	results	result	VERB
cana-1616	210	2	communications	communication	NOUN
cana-1616	210	3	on	on	ADP
cana-1616	210	4	applied	apply	VERB
cana-1616	210	5	nonlinear	nonlinear	ADJ
cana-1616	210	6	analysis	analysis	NOUN
cana-1616	210	7	issn	issn	NOUN
cana-1616	210	8	:	:	PUNCT
cana-1616	210	9	1074	1074	NUM
cana-1616	210	10	-	-	PUNCT
cana-1616	210	11	133x	133x	NUM
cana-1616	210	12	vol	vol	NOUN
cana-1616	210	13	31	31	NUM
cana-1616	210	14	no	no	NOUN
cana-1616	210	15	.	.	PUNCT
cana-1616	211	1	8s	8s	PROPN
cana-1616	211	2	(	(	PUNCT
cana-1616	211	3	2024	2024	NUM
cana-1616	211	4	)	)	PUNCT
cana-1616	211	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	211	6	786	786	NUM
cana-1616	211	7	showcased	showcase	VERB
cana-1616	211	8	that	that	DET
cana-1616	211	9	author	author	NOUN
cana-1616	211	10	who	who	PRON
cana-1616	211	11	used	use	VERB
cana-1616	211	12	nb	nb	NOUN
cana-1616	211	13	classifier	classifier	NOUN
cana-1616	211	14	for	for	ADP
cana-1616	211	15	predicting	predict	VERB
cana-1616	211	16	liver	liver	NOUN
cana-1616	211	17	disease	disease	NOUN
cana-1616	211	18	achieves	achieve	VERB
cana-1616	211	19	accuracy	accuracy	NOUN
cana-1616	211	20	rate	rate	NOUN
cana-1616	211	21	of	of	ADP
cana-1616	211	22	just	just	ADV
cana-1616	211	23	0.71	0.71	NUM
cana-1616	211	24	,	,	PUNCT
cana-1616	211	25	while	while	SCONJ
cana-1616	211	26	as	as	SCONJ
cana-1616	211	27	,	,	PUNCT
cana-1616	211	28	models	model	NOUN
cana-1616	211	29	like	like	ADP
cana-1616	211	30	svm	svm	PROPN
cana-1616	211	31	,	,	PUNCT
cana-1616	211	32	lr	lr	INTJ
cana-1616	211	33	,	,	PUNCT
cana-1616	211	34	mlp	mlp	NOUN
cana-1616	211	35	and	and	CCONJ
cana-1616	211	36	1	1	NUM
cana-1616	211	37	-	-	PUNCT
cana-1616	211	38	nn	nn	NOUN
cana-1616	211	39	achieved	achieve	VERB
cana-1616	211	40	accuracy	accuracy	NOUN
cana-1616	211	41	rate	rate	NOUN
cana-1616	211	42	of	of	ADP
cana-1616	211	43	0.70	0.70	NUM
cana-1616	211	44	,	,	PUNCT
cana-1616	211	45	0.7	0.7	NUM
cana-1616	211	46	,	,	PUNCT
cana-1616	211	47	0.69	0.69	NUM
cana-1616	211	48	and	and	CCONJ
cana-1616	211	49	0.688	0.688	NUM
cana-1616	211	50	respectively	respectively	ADV
cana-1616	211	51	.	.	PUNCT
cana-1616	212	1	while	while	SCONJ
cana-1616	212	2	comparing	compare	VERB
cana-1616	212	3	the	the	DET
cana-1616	212	4	proposed	propose	VERB
cana-1616	212	5	approach	approach	NOUN
cana-1616	212	6	with	with	ADP
cana-1616	212	7	more	more	ADJ
cana-1616	212	8	techniques	technique	NOUN
cana-1616	212	9	wherein	wherein	ADJ
cana-1616	212	10	authors	author	NOUN
cana-1616	212	11	have	have	AUX
cana-1616	212	12	used	use	VERB
cana-1616	212	13	j48	j48	PROPN
cana-1616	212	14	,	,	PUNCT
cana-1616	212	15	rf	rf	NOUN
cana-1616	212	16	,	,	PUNCT
cana-1616	212	17	rt	rt	PROPN
cana-1616	212	18	,	,	PUNCT
cana-1616	212	19	reptree	reptree	PROPN
cana-1616	212	20	,	,	PUNCT
cana-1616	212	21	rotf	rotf	NOUN
cana-1616	212	22	,	,	PUNCT
cana-1616	212	23	adaboostm1	adaboostm1	NOUN
cana-1616	212	24	,	,	PUNCT
cana-1616	212	25	stacking	stacking	NOUN
cana-1616	212	26	,	,	PUNCT
cana-1616	212	27	bagging	bagging	NOUN
cana-1616	212	28	,	,	PUNCT
cana-1616	212	29	and	and	CCONJ
cana-1616	212	30	voting	voting	NOUN
cana-1616	212	31	mechanisms	mechanism	NOUN
cana-1616	212	32	for	for	ADP
cana-1616	212	33	predicting	predict	VERB
cana-1616	212	34	liver	liver	NOUN
cana-1616	212	35	diseases	disease	NOUN
cana-1616	212	36	,	,	PUNCT
cana-1616	212	37	the	the	DET
cana-1616	212	38	accuracy	accuracy	NOUN
cana-1616	212	39	rates	rate	NOUN
cana-1616	212	40	were	be	AUX
cana-1616	212	41	0.73	0.73	NUM
cana-1616	212	42	,	,	PUNCT
cana-1616	212	43	0.79	0.79	NUM
cana-1616	212	44	,	,	PUNCT
cana-1616	212	45	0.71	0.71	NUM
cana-1616	212	46	,	,	PUNCT
cana-1616	212	47	0.70	0.70	NUM
cana-1616	212	48	,	,	PUNCT
cana-1616	212	49	0.77	0.77	NUM
cana-1616	212	50	,	,	PUNCT
cana-1616	212	51	0.79	0.79	NUM
cana-1616	212	52	,	,	PUNCT
cana-1616	212	53	0.794	0.794	NUM
cana-1616	212	54	,	,	PUNCT
cana-1616	212	55	0.78	0.78	NUM
cana-1616	212	56	and	and	CCONJ
cana-1616	212	57	0.80	0.80	NUM
cana-1616	212	58	respectively	respectively	ADV
cana-1616	212	59	.	.	PUNCT
cana-1616	213	1	on	on	ADP
cana-1616	213	2	the	the	DET
cana-1616	213	3	contrary	contrary	NOUN
cana-1616	213	4	,	,	PUNCT
cana-1616	213	5	our	our	PRON
cana-1616	213	6	proposed	propose	VERB
cana-1616	213	7	approach	approach	NOUN
cana-1616	213	8	achieved	achieve	VERB
cana-1616	213	9	a	a	DET
cana-1616	213	10	classification	classification	NOUN
cana-1616	213	11	accuracy	accuracy	NOUN
cana-1616	213	12	rate	rate	NOUN
cana-1616	213	13	of	of	ADP
cana-1616	213	14	0.93	0.93	NUM
cana-1616	213	15	,	,	PUNCT
cana-1616	213	16	which	which	PRON
cana-1616	213	17	is	be	AUX
cana-1616	213	18	significantly	significantly	ADV
cana-1616	213	19	higher	high	ADJ
cana-1616	213	20	than	than	ADP
cana-1616	213	21	all	all	DET
cana-1616	213	22	previously	previously	ADV
cana-1616	213	23	discussed	discuss	VERB
cana-1616	213	24	models	model	NOUN
cana-1616	213	25	.	.	PUNCT
cana-1616	214	1	this	this	DET
cana-1616	214	2	increased	increase	VERB
cana-1616	214	3	accuracy	accuracy	NOUN
cana-1616	214	4	rate	rate	NOUN
cana-1616	214	5	is	be	AUX
cana-1616	214	6	achieved	achieve	VERB
cana-1616	214	7	in	in	ADP
cana-1616	214	8	proposed	propose	VERB
cana-1616	214	9	model	model	NOUN
cana-1616	214	10	because	because	SCONJ
cana-1616	214	11	of	of	ADP
cana-1616	214	12	implementing	implement	VERB
cana-1616	214	13	effective	effective	ADJ
cana-1616	214	14	processing	processing	NOUN
cana-1616	214	15	,	,	PUNCT
cana-1616	214	16	fs	fs	ADP
cana-1616	214	17	techniques	technique	NOUN
cana-1616	214	18	which	which	PRON
cana-1616	214	19	improves	improve	VERB
cana-1616	214	20	performance	performance	NOUN
cana-1616	214	21	of	of	ADP
cana-1616	214	22	classifiers	classifier	NOUN
cana-1616	214	23	.	.	PUNCT
cana-1616	215	1	likewise	likewise	ADV
cana-1616	215	2	,	,	PUNCT
cana-1616	215	3	the	the	DET
cana-1616	215	4	proposed	propose	VERB
cana-1616	215	5	model	model	NOUN
cana-1616	215	6	’s	’s	PART
cana-1616	215	7	effectiveness	effectiveness	NOUN
cana-1616	215	8	was	be	AUX
cana-1616	215	9	also	also	ADV
cana-1616	215	10	evaluated	evaluate	VERB
cana-1616	215	11	and	and	CCONJ
cana-1616	215	12	compared	compare	VERB
cana-1616	215	13	with	with	ADP
cana-1616	215	14	other	other	ADJ
cana-1616	215	15	similar	similar	ADJ
cana-1616	215	16	traditional	traditional	ADJ
cana-1616	215	17	approaches	approach	NOUN
cana-1616	215	18	in	in	ADP
cana-1616	215	19	terms	term	NOUN
cana-1616	215	20	of	of	ADP
cana-1616	215	21	their	their	PRON
cana-1616	215	22	precision	precision	NOUN
cana-1616	215	23	rates	rate	NOUN
cana-1616	215	24	.	.	PUNCT
cana-1616	216	1	figure	figure	VERB
cana-1616	216	2	8	8	NUM
cana-1616	216	3	depicts	depict	VERB
cana-1616	216	4	the	the	DET
cana-1616	216	5	comparative	comparative	ADJ
cana-1616	216	6	graph	graph	NOUN
cana-1616	216	7	for	for	ADP
cana-1616	216	8	the	the	DET
cana-1616	216	9	same	same	ADJ
cana-1616	216	10	.	.	PUNCT
cana-1616	217	1	upon	upon	SCONJ
cana-1616	217	2	carefully	carefully	ADV
cana-1616	217	3	examining	examine	VERB
cana-1616	217	4	the	the	DET
cana-1616	217	5	graph	graph	NOUN
cana-1616	217	6	,	,	PUNCT
cana-1616	217	7	we	we	PRON
cana-1616	217	8	observed	observe	VERB
cana-1616	217	9	that	that	SCONJ
cana-1616	217	10	1	1	NUM
cana-1616	217	11	-	-	PUNCT
cana-1616	217	12	nn	nn	NUM
cana-1616	217	13	model	model	NOUN
cana-1616	217	14	was	be	AUX
cana-1616	217	15	giving	give	VERB
cana-1616	217	16	worst	bad	ADJ
cana-1616	217	17	precision	precision	NOUN
cana-1616	217	18	results	result	NOUN
cana-1616	217	19	of	of	ADP
cana-1616	217	20	just	just	ADV
cana-1616	217	21	0.69	0.69	NUM
cana-1616	217	22	,	,	PUNCT
cana-1616	217	23	whereas	whereas	SCONJ
cana-1616	217	24	,	,	PUNCT
cana-1616	217	25	it	it	PRON
cana-1616	217	26	was	be	AUX
cana-1616	217	27	0.70	0.70	NUM
cana-1616	217	28	in	in	ADP
cana-1616	217	29	mlp	mlp	PROPN
cana-1616	217	30	,	,	PUNCT
cana-1616	217	31	0.71	0.71	NUM
cana-1616	217	32	in	in	ADP
cana-1616	217	33	reptree	reptree	NOUN
cana-1616	217	34	,	,	PUNCT
cana-1616	217	35	rt	rt	PROPN
cana-1616	217	36	,	,	PUNCT
cana-1616	217	37	and	and	CCONJ
cana-1616	217	38	lr	lr	NOUN
cana-1616	217	39	,	,	PUNCT
cana-1616	217	40	0.72	0.72	NUM
cana-1616	217	41	and	and	CCONJ
cana-1616	217	42	0.73	0.73	NUM
cana-1616	217	43	in	in	ADP
cana-1616	217	44	nb	nb	NOUN
cana-1616	217	45	and	and	CCONJ
cana-1616	217	46	j48	j48	PROPN
cana-1616	217	47	,	,	PUNCT
cana-1616	217	48	0.74	0.74	NUM
cana-1616	217	49	in	in	ADP
cana-1616	217	50	svm	svm	PROPN
cana-1616	217	51	,	,	PUNCT
cana-1616	217	52	0.78	0.78	NUM
cana-1616	217	53	in	in	ADP
cana-1616	217	54	rotf	rotf	NOUN
cana-1616	217	55	,	,	PUNCT
cana-1616	217	56	0.79	0.79	NUM
cana-1616	217	57	in	in	ADP
cana-1616	217	58	rf	rf	PROPN
cana-1616	217	59	,	,	PUNCT
cana-1616	217	60	adaboostm1	adaboostm1	PROPN
cana-1616	217	61	,	,	PUNCT
cana-1616	217	62	stcking	stcke	VERB
cana-1616	217	63	and	and	CCONJ
cana-1616	217	64	bagging	bagging	NOUN
cana-1616	217	65	and	and	CCONJ
cana-1616	217	66	0.80	0.80	NUM
cana-1616	217	67	in	in	ADP
cana-1616	217	68	voting	voting	NOUN
cana-1616	217	69	methods	method	NOUN
cana-1616	217	70	respectively	respectively	ADV
cana-1616	217	71	.	.	PUNCT
cana-1616	218	1	these	these	DET
cana-1616	218	2	values	value	NOUN
cana-1616	218	3	were	be	AUX
cana-1616	218	4	good	good	ADJ
cana-1616	218	5	but	but	CCONJ
cana-1616	218	6	there	there	PRON
cana-1616	218	7	was	be	VERB
cana-1616	218	8	still	still	ADV
cana-1616	218	9	scope	scope	NOUN
cana-1616	218	10	of	of	ADP
cana-1616	218	11	improvement	improvement	NOUN
cana-1616	218	12	.	.	PUNCT
cana-1616	219	1	the	the	DET
cana-1616	219	2	proposed	propose	VERB
cana-1616	219	3	model	model	NOUN
cana-1616	219	4	depicts	depict	VERB
cana-1616	219	5	a	a	DET
cana-1616	219	6	precision	precision	NOUN
cana-1616	219	7	rate	rate	NOUN
cana-1616	219	8	of	of	ADP
cana-1616	219	9	0.99	0.99	NUM
cana-1616	219	10	which	which	PRON
cana-1616	219	11	signifies	signify	VERB
cana-1616	219	12	that	that	SCONJ
cana-1616	219	13	out	out	ADP
cana-1616	219	14	of	of	ADP
cana-1616	219	15	all	all	DET
cana-1616	219	16	the	the	DET
cana-1616	219	17	instances	instance	NOUN
cana-1616	219	18	that	that	PRON
cana-1616	219	19	are	be	AUX
cana-1616	219	20	predicted	predict	VERB
cana-1616	219	21	as	as	ADP
cana-1616	219	22	positive	positive	ADJ
cana-1616	219	23	,	,	PUNCT
cana-1616	219	24	99	99	NUM
cana-1616	219	25	%	%	NOUN
cana-1616	219	26	of	of	ADP
cana-1616	219	27	them	they	PRON
cana-1616	219	28	are	be	AUX
cana-1616	219	29	actually	actually	ADV
cana-1616	219	30	true	true	ADJ
cana-1616	219	31	positive	positive	ADJ
cana-1616	219	32	cases	case	NOUN
cana-1616	219	33	.	.	PUNCT
cana-1616	220	1	figure	figure	VERB
cana-1616	220	2	7	7	NUM
cana-1616	220	3	.	.	PUNCT
cana-1616	220	4	accuracy	accuracy	NOUN
cana-1616	220	5	comparison	comparison	NOUN
cana-1616	220	6	graph	graph	NOUN
cana-1616	220	7	figure	figure	NOUN
cana-1616	220	8	8	8	NUM
cana-1616	220	9	.	.	PUNCT
cana-1616	221	1	precision	precision	NOUN
cana-1616	221	2	comparison	comparison	NOUN
cana-1616	221	3	graph	graph	NOUN
cana-1616	221	4	figure	figure	NOUN
cana-1616	221	5	9	9	NUM
cana-1616	221	6	.	.	PUNCT
cana-1616	222	1	recall	recall	NOUN
cana-1616	222	2	comparison	comparison	NOUN
cana-1616	222	3	graph	graph	NOUN
cana-1616	222	4	furthermore	furthermore	ADV
cana-1616	222	5	,	,	PUNCT
cana-1616	222	6	we	we	PRON
cana-1616	222	7	have	have	AUX
cana-1616	222	8	also	also	ADV
cana-1616	222	9	evaluated	evaluate	VERB
cana-1616	222	10	the	the	DET
cana-1616	222	11	performance	performance	NOUN
cana-1616	222	12	of	of	ADP
cana-1616	222	13	proposed	propose	VERB
cana-1616	222	14	approach	approach	NOUN
cana-1616	222	15	with	with	ADP
cana-1616	222	16	conventional	conventional	ADJ
cana-1616	222	17	techniques	technique	NOUN
cana-1616	222	18	in	in	ADP
cana-1616	222	19	terms	term	NOUN
cana-1616	222	20	of	of	ADP
cana-1616	222	21	their	their	PRON
cana-1616	222	22	recall	recall	NOUN
cana-1616	222	23	rates	rate	NOUN
cana-1616	222	24	.	.	PUNCT
cana-1616	223	1	the	the	DET
cana-1616	223	2	comparative	comparative	ADJ
cana-1616	223	3	graph	graph	NOUN
cana-1616	223	4	obtained	obtain	VERB
cana-1616	223	5	for	for	ADP
cana-1616	223	6	the	the	DET
cana-1616	223	7	same	same	ADJ
cana-1616	223	8	is	be	AUX
cana-1616	223	9	shown	show	VERB
cana-1616	223	10	in	in	ADP
cana-1616	223	11	figure	figure	NOUN
cana-1616	223	12	9	9	NUM
cana-1616	223	13	.	.	PUNCT
cana-1616	223	14	from	from	ADP
cana-1616	223	15	the	the	DET
cana-1616	223	16	given	give	VERB
cana-1616	223	17	graph	graph	NOUN
cana-1616	223	18	,	,	PUNCT
cana-1616	223	19	we	we	PRON
cana-1616	223	20	concluded	conclude	VERB
cana-1616	223	21	that	that	SCONJ
cana-1616	223	22	out	out	ADP
cana-1616	223	23	of	of	ADP
cana-1616	223	24	all	all	DET
cana-1616	223	25	the	the	DET
cana-1616	223	26	models	model	NOUN
cana-1616	223	27	,	,	PUNCT
cana-1616	223	28	the	the	DET
cana-1616	223	29	bar	bar	NOUN
cana-1616	223	30	of	of	ADP
cana-1616	223	31	proposed	propose	VERB
cana-1616	223	32	recall	recall	NOUN
cana-1616	223	33	rate	rate	NOUN
cana-1616	223	34	is	be	AUX
cana-1616	223	35	highest	high	ADJ
cana-1616	223	36	at	at	ADP
cana-1616	223	37	0.90	0.90	NUM
cana-1616	223	38	,	,	PUNCT
cana-1616	223	39	depicting	depict	VERB
cana-1616	223	40	its	its	PRON
cana-1616	223	41	supremacy	supremacy	NOUN
cana-1616	223	42	.	.	PUNCT
cana-1616	224	1	on	on	ADP
cana-1616	224	2	the	the	DET
cana-1616	224	3	other	other	ADJ
cana-1616	224	4	hand	hand	NOUN
cana-1616	224	5	,	,	PUNCT
cana-1616	224	6	among	among	ADP
cana-1616	224	7	traditional	traditional	ADJ
cana-1616	224	8	models	model	NOUN
cana-1616	224	9	recall	recall	NOUN
cana-1616	224	10	value	value	NOUN
cana-1616	224	11	was	be	AUX
cana-1616	224	12	highest	high	ADJ
cana-1616	224	13	in	in	ADP
cana-1616	224	14	voting	voting	NOUN
cana-1616	224	15	method	method	NOUN
cana-1616	224	16	with	with	ADP
cana-1616	224	17	0.80	0.80	NUM
cana-1616	224	18	while	while	SCONJ
cana-1616	224	19	as	as	SCONJ
cana-1616	224	20	,	,	PUNCT
cana-1616	224	21	it	it	PRON
cana-1616	224	22	was	be	AUX
cana-1616	224	23	lowest	low	ADJ
cana-1616	224	24	in	in	ADP
cana-1616	224	25	1	1	NUM
cana-1616	224	26	-	-	PUNCT
cana-1616	224	27	nn	nn	NUM
cana-1616	224	28	model	model	NOUN
cana-1616	224	29	with	with	ADP
cana-1616	224	30	only	only	ADV
cana-1616	224	31	0.688	0.688	NUM
cana-1616	224	32	respectively	respectively	ADV
cana-1616	224	33	.	.	PUNCT
cana-1616	225	1	the	the	DET
cana-1616	225	2	recall	recall	NOUN
cana-1616	225	3	score	score	NOUN
cana-1616	225	4	in	in	ADP
cana-1616	225	5	other	other	ADJ
cana-1616	225	6	models	model	NOUN
cana-1616	225	7	were	be	AUX
cana-1616	225	8	in	in	ADP
cana-1616	225	9	between	between	ADP
cana-1616	225	10	0.68	0.68	NUM
cana-1616	225	11	and	and	CCONJ
cana-1616	225	12	0.80	0.80	NUM
cana-1616	225	13	.	.	PUNCT
cana-1616	226	1	standard	standard	ADJ
cana-1616	226	2	models	model	NOUN
cana-1616	226	3	like	like	ADP
cana-1616	226	4	nb	nb	PROPN
cana-1616	226	5	,	,	PUNCT
cana-1616	226	6	svm	svm	PROPN
cana-1616	226	7	,	,	PUNCT
cana-1616	226	8	lr	lr	NOUN
cana-1616	226	9	,	,	PUNCT
cana-1616	226	10	ml	ml	NOUN
cana-1616	226	11	,	,	PUNCT
cana-1616	226	12	j48	j48	PROPN
cana-1616	226	13	,	,	PUNCT
cana-1616	226	14	rf	rf	PRON
cana-1616	226	15	and	and	CCONJ
cana-1616	226	16	rt	rt	PROPN
cana-1616	226	17	attained	attain	VERB
cana-1616	226	18	a	a	DET
cana-1616	226	19	recall	recall	NOUN
cana-1616	226	20	rate	rate	NOUN
cana-1616	226	21	of	of	ADP
cana-1616	226	22	0.71	0.71	NUM
cana-1616	226	23	,	,	PUNCT
cana-1616	226	24	0.70	0.70	NUM
cana-1616	226	25	,	,	PUNCT
cana-1616	226	26	0.7	0.7	NUM
cana-1616	226	27	,	,	PUNCT
cana-1616	226	28	0.69	0.69	NUM
cana-1616	226	29	,	,	PUNCT
cana-1616	226	30	0.73	0.73	NUM
cana-1616	226	31	,	,	PUNCT
cana-1616	226	32	0.79	0.79	NUM
cana-1616	226	33	and	and	CCONJ
cana-1616	226	34	0.71	0.71	NUM
cana-1616	226	35	communications	communication	NOUN
cana-1616	226	36	on	on	ADP
cana-1616	226	37	applied	apply	VERB
cana-1616	226	38	nonlinear	nonlinear	ADJ
cana-1616	226	39	analysis	analysis	NOUN
cana-1616	226	40	issn	issn	NOUN
cana-1616	226	41	:	:	PUNCT
cana-1616	226	42	1074	1074	NUM
cana-1616	226	43	-	-	PUNCT
cana-1616	226	44	133x	133x	NUM
cana-1616	226	45	vol	vol	NOUN
cana-1616	226	46	31	31	NUM
cana-1616	226	47	no	no	NOUN
cana-1616	226	48	.	.	PUNCT
cana-1616	227	1	8s	8s	PROPN
cana-1616	227	2	(	(	PUNCT
cana-1616	227	3	2024	2024	NUM
cana-1616	227	4	)	)	PUNCT
cana-1616	227	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	227	6	787	787	NUM
cana-1616	227	7	respectively	respectively	ADV
cana-1616	227	8	.	.	PUNCT
cana-1616	228	1	similarly	similarly	ADV
cana-1616	228	2	,	,	PUNCT
cana-1616	228	3	the	the	DET
cana-1616	228	4	recall	recall	NOUN
cana-1616	228	5	score	score	NOUN
cana-1616	228	6	was	be	AUX
cana-1616	228	7	only	only	ADV
cana-1616	228	8	0.70	0.70	NUM
cana-1616	228	9	in	in	ADP
cana-1616	228	10	reptree	reptree	NOUN
cana-1616	228	11	,	,	PUNCT
cana-1616	228	12	0.77	0.77	NUM
cana-1616	228	13	in	in	ADP
cana-1616	228	14	rotf	rotf	NOUN
cana-1616	228	15	,	,	PUNCT
cana-1616	228	16	0.79	0.79	NUM
cana-1616	228	17	in	in	ADP
cana-1616	228	18	adaboostm1	adaboostm1	PRON
cana-1616	228	19	and	and	CCONJ
cana-1616	228	20	stacking	stacking	NOUN
cana-1616	228	21	,	,	PUNCT
cana-1616	228	22	and	and	CCONJ
cana-1616	228	23	0.78	0.78	NUM
cana-1616	228	24	in	in	ADP
cana-1616	228	25	bagging	bagging	NOUN
cana-1616	228	26	methods	method	NOUN
cana-1616	228	27	.	.	PUNCT
cana-1616	229	1	figure	figure	NOUN
cana-1616	229	2	10	10	NUM
cana-1616	229	3	.	.	PUNCT
cana-1616	230	1	f1	f1	ADJ
cana-1616	230	2	-	-	PUNCT
cana-1616	230	3	score	score	NOUN
cana-1616	230	4	comparison	comparison	NOUN
cana-1616	230	5	graph	graph	NOUN
cana-1616	230	6	moreover	moreover	ADV
cana-1616	230	7	,	,	PUNCT
cana-1616	230	8	the	the	DET
cana-1616	230	9	efficacy	efficacy	NOUN
cana-1616	230	10	of	of	ADP
cana-1616	230	11	the	the	DET
cana-1616	230	12	proposed	propose	VERB
cana-1616	230	13	system	system	NOUN
cana-1616	230	14	is	be	AUX
cana-1616	230	15	tested	test	VERB
cana-1616	230	16	and	and	CCONJ
cana-1616	230	17	validated	validate	VERB
cana-1616	230	18	by	by	ADP
cana-1616	230	19	putting	put	VERB
cana-1616	230	20	it	it	PRON
cana-1616	230	21	in	in	ADP
cana-1616	230	22	comparison	comparison	NOUN
cana-1616	230	23	with	with	ADP
cana-1616	230	24	traditional	traditional	ADJ
cana-1616	230	25	models	model	NOUN
cana-1616	230	26	in	in	ADP
cana-1616	230	27	terms	term	NOUN
cana-1616	230	28	of	of	ADP
cana-1616	230	29	their	their	PRON
cana-1616	230	30	f1	f1	NOUN
cana-1616	230	31	-	-	PUNCT
cana-1616	230	32	scores	score	NOUN
cana-1616	230	33	.	.	PUNCT
cana-1616	231	1	figure	figure	NOUN
cana-1616	231	2	10	10	NUM
cana-1616	231	3	shows	show	VERB
cana-1616	231	4	the	the	DET
cana-1616	231	5	comparative	comparative	ADJ
cana-1616	231	6	graph	graph	NOUN
cana-1616	231	7	for	for	ADP
cana-1616	231	8	the	the	DET
cana-1616	231	9	same	same	ADJ
cana-1616	231	10	.	.	PUNCT
cana-1616	232	1	the	the	DET
cana-1616	232	2	graph	graph	NOUN
cana-1616	232	3	reveals	reveal	VERB
cana-1616	232	4	that	that	SCONJ
cana-1616	232	5	traditional	traditional	ADJ
cana-1616	232	6	1	1	NUM
cana-1616	232	7	-	-	PUNCT
cana-1616	232	8	nn	nn	PROPN
cana-1616	232	9	and	and	CCONJ
cana-1616	232	10	mlp	mlp	PROPN
cana-1616	232	11	are	be	AUX
cana-1616	232	12	two	two	NUM
cana-1616	232	13	worst	bad	ADJ
cana-1616	232	14	performing	performing	NOUN
cana-1616	232	15	models	model	NOUN
cana-1616	232	16	with	with	ADP
cana-1616	232	17	an	an	DET
cana-1616	232	18	f1	f1	NOUN
cana-1616	232	19	-	-	PUNCT
cana-1616	232	20	score	score	NOUN
cana-1616	232	21	of	of	ADP
cana-1616	232	22	0.68	0.68	NUM
cana-1616	232	23	and	and	CCONJ
cana-1616	232	24	0.69	0.69	NUM
cana-1616	232	25	respectively	respectively	ADV
cana-1616	232	26	,	,	PUNCT
cana-1616	232	27	while	while	SCONJ
cana-1616	232	28	as	as	SCONJ
cana-1616	232	29	,	,	PUNCT
cana-1616	232	30	adaboostm1	adaboostm1	PRON
cana-1616	232	31	and	and	CCONJ
cana-1616	232	32	voting	voting	NOUN
cana-1616	232	33	approach	approach	NOUN
cana-1616	232	34	are	be	AUX
cana-1616	232	35	the	the	DET
cana-1616	232	36	two	two	NUM
cana-1616	232	37	best	good	ADJ
cana-1616	232	38	performing	performing	NOUN
cana-1616	232	39	models	model	NOUN
cana-1616	232	40	with	with	ADP
cana-1616	232	41	a	a	DET
cana-1616	232	42	f1	f1	NOUN
cana-1616	232	43	-	-	PUNCT
cana-1616	232	44	score	score	NOUN
cana-1616	232	45	of	of	ADP
cana-1616	232	46	0.80	0.80	NUM
cana-1616	232	47	and	and	CCONJ
cana-1616	232	48	0.79	0.79	NUM
cana-1616	232	49	,	,	PUNCT
cana-1616	232	50	among	among	ADP
cana-1616	232	51	all	all	DET
cana-1616	232	52	the	the	DET
cana-1616	232	53	given	give	VERB
cana-1616	232	54	standard	standard	ADJ
cana-1616	232	55	models	model	NOUN
cana-1616	232	56	.	.	PUNCT
cana-1616	233	1	the	the	DET
cana-1616	233	2	authors	author	NOUN
cana-1616	233	3	who	who	PRON
cana-1616	233	4	used	use	VERB
cana-1616	233	5	nb	nb	PROPN
cana-1616	233	6	,	,	PUNCT
cana-1616	233	7	svm	svm	PROPN
cana-1616	233	8	,	,	PUNCT
cana-1616	233	9	lr	lr	NOUN
cana-1616	233	10	,	,	PUNCT
cana-1616	233	11	j48	j48	PROPN
cana-1616	233	12	,	,	PUNCT
cana-1616	233	13	rt	rt	PROPN
cana-1616	233	14	,	,	PUNCT
cana-1616	233	15	reptree	reptree	NOUN
cana-1616	233	16	,	,	PUNCT
cana-1616	233	17	rotf	rotf	NOUN
cana-1616	233	18	and	and	CCONJ
cana-1616	233	19	bagging	bagging	NOUN
cana-1616	233	20	attained	attain	VERB
cana-1616	233	21	f	f	NOUN
cana-1616	233	22	-	-	PUNCT
cana-1616	233	23	score	score	NOUN
cana-1616	233	24	of	of	ADP
cana-1616	233	25	0.70	0.70	NUM
cana-1616	233	26	,	,	PUNCT
cana-1616	233	27	0.708	0.708	NUM
cana-1616	233	28	,	,	PUNCT
cana-1616	233	29	0.7	0.7	NUM
cana-1616	233	30	,	,	PUNCT
cana-1616	233	31	0.73	0.73	NUM
cana-1616	233	32	,	,	PUNCT
cana-1616	233	33	0.71	0.71	NUM
cana-1616	233	34	,	,	PUNCT
cana-1616	233	35	0.70	0.70	NUM
cana-1616	233	36	,	,	PUNCT
cana-1616	233	37	0.77	0.77	NUM
cana-1616	233	38	and	and	CCONJ
cana-1616	233	39	0.78	0.78	NUM
cana-1616	233	40	respectively	respectively	ADV
cana-1616	233	41	,	,	PUNCT
cana-1616	233	42	while	while	SCONJ
cana-1616	233	43	as	as	ADP
cana-1616	233	44	,	,	PUNCT
cana-1616	233	45	rf	rf	NOUN
cana-1616	233	46	and	and	CCONJ
cana-1616	233	47	stacking	stacking	NOUN
cana-1616	233	48	models	model	NOUN
cana-1616	233	49	attained	attain	VERB
cana-1616	233	50	an	an	DET
cana-1616	233	51	f	f	NOUN
cana-1616	233	52	-	-	PUNCT
cana-1616	233	53	score	score	NOUN
cana-1616	233	54	of	of	ADP
cana-1616	233	55	0.793	0.793	NUM
cana-1616	233	56	respectively	respectively	ADV
cana-1616	233	57	.	.	PUNCT
cana-1616	234	1	on	on	ADP
cana-1616	234	2	the	the	DET
cana-1616	234	3	contrary	contrary	ADJ
cana-1616	234	4	side	side	NOUN
cana-1616	234	5	,	,	PUNCT
cana-1616	234	6	when	when	SCONJ
cana-1616	234	7	f1	f1	ADJ
cana-1616	234	8	-	-	PUNCT
cana-1616	234	9	score	score	NOUN
cana-1616	234	10	value	value	NOUN
cana-1616	234	11	was	be	AUX
cana-1616	234	12	observed	observe	VERB
cana-1616	234	13	in	in	ADP
cana-1616	234	14	proposed	propose	VERB
cana-1616	234	15	model	model	NOUN
cana-1616	234	16	,	,	PUNCT
cana-1616	234	17	it	it	PRON
cana-1616	234	18	came	come	VERB
cana-1616	234	19	out	out	ADP
cana-1616	234	20	to	to	PART
cana-1616	234	21	be	be	AUX
cana-1616	234	22	0.94	0.94	NUM
cana-1616	234	23	which	which	PRON
cana-1616	234	24	is	be	AUX
cana-1616	234	25	significantly	significantly	ADV
cana-1616	234	26	around	around	ADP
cana-1616	234	27	14	14	NUM
cana-1616	234	28	%	%	NOUN
cana-1616	234	29	higher	high	ADJ
cana-1616	234	30	than	than	ADP
cana-1616	234	31	traditional	traditional	ADJ
cana-1616	234	32	best	good	ADJ
cana-1616	234	33	performing	perform	VERB
cana-1616	234	34	model	model	NOUN
cana-1616	234	35	.	.	PUNCT
cana-1616	235	1	figure	figure	VERB
cana-1616	235	2	11	11	NUM
cana-1616	235	3	.	.	PUNCT
cana-1616	236	1	auc	auc	VERB
cana-1616	236	2	comparison	comparison	NOUN
cana-1616	236	3	graph	graph	NOUN
cana-1616	236	4	finally	finally	ADV
cana-1616	236	5	,	,	PUNCT
cana-1616	236	6	to	to	PART
cana-1616	236	7	prove	prove	VERB
cana-1616	236	8	the	the	DET
cana-1616	236	9	supremacy	supremacy	NOUN
cana-1616	236	10	of	of	ADP
cana-1616	236	11	proposed	propose	VERB
cana-1616	236	12	approach	approach	NOUN
cana-1616	236	13	over	over	ADP
cana-1616	236	14	other	other	ADJ
cana-1616	236	15	similar	similar	ADJ
cana-1616	236	16	approaches	approach	NOUN
cana-1616	236	17	,	,	PUNCT
cana-1616	236	18	we	we	PRON
cana-1616	236	19	analyzed	analyze	VERB
cana-1616	236	20	its	its	PRON
cana-1616	236	21	performance	performance	NOUN
cana-1616	236	22	in	in	ADP
cana-1616	236	23	terms	term	NOUN
cana-1616	236	24	of	of	ADP
cana-1616	236	25	auc	auc	NOUN
cana-1616	236	26	,	,	PUNCT
cana-1616	236	27	whose	whose	DET
cana-1616	236	28	graph	graph	NOUN
cana-1616	236	29	is	be	AUX
cana-1616	236	30	shown	show	VERB
cana-1616	236	31	in	in	ADP
cana-1616	236	32	figure	figure	NOUN
cana-1616	236	33	11	11	NUM
cana-1616	236	34	.	.	PUNCT
cana-1616	237	1	the	the	DET
cana-1616	237	2	x	x	PROPN
cana-1616	237	3	and	and	CCONJ
cana-1616	237	4	y	y	NOUN
cana-1616	237	5	-	-	PUNCT
cana-1616	237	6	axis	axis	NOUN
cana-1616	237	7	of	of	ADP
cana-1616	237	8	the	the	DET
cana-1616	237	9	given	give	VERB
cana-1616	237	10	graph	graph	NOUN
cana-1616	237	11	calibrates	calibrate	VERB
cana-1616	237	12	to	to	ADP
cana-1616	237	13	the	the	DET
cana-1616	237	14	different	different	ADJ
cana-1616	237	15	classification	classification	NOUN
cana-1616	237	16	models	model	NOUN
cana-1616	237	17	and	and	CCONJ
cana-1616	237	18	their	their	PRON
cana-1616	237	19	auc	auc	ADJ
cana-1616	237	20	values	value	NOUN
cana-1616	237	21	respectively	respectively	ADV
cana-1616	237	22	.	.	PUNCT
cana-1616	238	1	as	as	SCONJ
cana-1616	238	2	mentioned	mention	VERB
cana-1616	238	3	previously	previously	ADV
cana-1616	238	4	,	,	PUNCT
cana-1616	238	5	the	the	DET
cana-1616	238	6	model	model	NOUN
cana-1616	238	7	shows	show	VERB
cana-1616	238	8	best	good	ADJ
cana-1616	238	9	performance	performance	NOUN
cana-1616	238	10	when	when	SCONJ
cana-1616	238	11	its	its	PRON
cana-1616	238	12	auc	auc	NOUN
cana-1616	238	13	value	value	NOUN
cana-1616	238	14	is	be	AUX
cana-1616	238	15	close	close	ADJ
cana-1616	238	16	to	to	ADP
cana-1616	238	17	1	1	NUM
cana-1616	238	18	.	.	PUNCT
cana-1616	238	19	from	from	ADP
cana-1616	238	20	the	the	DET
cana-1616	238	21	given	give	VERB
cana-1616	238	22	graph	graph	NOUN
cana-1616	238	23	,	,	PUNCT
cana-1616	238	24	it	it	PRON
cana-1616	238	25	is	be	AUX
cana-1616	238	26	observed	observe	VERB
cana-1616	238	27	that	that	SCONJ
cana-1616	238	28	among	among	ADP
cana-1616	238	29	all	all	DET
cana-1616	238	30	the	the	DET
cana-1616	238	31	models	model	NOUN
cana-1616	238	32	1	1	NUM
cana-1616	238	33	-	-	PUNCT
cana-1616	238	34	nn	nn	NUM
cana-1616	238	35	models	model	NOUN
cana-1616	238	36	is	be	AUX
cana-1616	238	37	exhibiting	exhibit	VERB
cana-1616	238	38	worst	bad	ADJ
cana-1616	238	39	performance	performance	NOUN
cana-1616	238	40	by	by	ADP
cana-1616	238	41	attaining	attain	VERB
cana-1616	238	42	an	an	DET
cana-1616	238	43	auc	auc	NOUN
cana-1616	238	44	of	of	ADP
cana-1616	238	45	just	just	ADV
cana-1616	238	46	0.69	0.69	NUM
cana-1616	238	47	while	while	NOUN
cana-1616	238	48	as	as	SCONJ
cana-1616	238	49	,	,	PUNCT
cana-1616	238	50	auc	auc	NOUN
cana-1616	238	51	value	value	NOUN
cana-1616	238	52	was	be	AUX
cana-1616	238	53	better	well	ADJ
cana-1616	238	54	in	in	ADP
cana-1616	238	55	voting	voting	NOUN
cana-1616	238	56	method	method	NOUN
cana-1616	238	57	with	with	ADP
cana-1616	238	58	0.88	0.88	NUM
cana-1616	238	59	value	value	NOUN
cana-1616	238	60	.	.	PUNCT
cana-1616	239	1	for	for	ADP
cana-1616	239	2	all	all	DET
cana-1616	239	3	the	the	DET
cana-1616	239	4	remaining	remain	VERB
cana-1616	239	5	models	model	NOUN
cana-1616	239	6	,	,	PUNCT
cana-1616	239	7	the	the	DET
cana-1616	239	8	auc	auc	ADJ
cana-1616	239	9	score	score	NOUN
cana-1616	239	10	was	be	AUX
cana-1616	239	11	0.70	0.70	NUM
cana-1616	239	12	in	in	ADP
cana-1616	239	13	svm	svm	PROPN
cana-1616	239	14	,	,	PUNCT
cana-1616	239	15	0.71	0.71	NUM
cana-1616	239	16	in	in	ADP
cana-1616	239	17	rt	rt	PROPN
cana-1616	239	18	,	,	PUNCT
cana-1616	239	19	0.73	0.73	NUM
cana-1616	239	20	in	in	ADP
cana-1616	239	21	j48	j48	PROPN
cana-1616	239	22	,	,	PUNCT
cana-1616	239	23	0.74	0.74	NUM
cana-1616	239	24	in	in	ADP
cana-1616	239	25	mlp	mlp	PROPN
cana-1616	239	26	,	,	PUNCT
cana-1616	239	27	0.75	0.75	NUM
cana-1616	239	28	in	in	ADP
cana-1616	239	29	lr	lr	PROPN
cana-1616	239	30	,	,	PUNCT
cana-1616	239	31	0.76	0.76	NUM
cana-1616	239	32	in	in	ADP
cana-1616	239	33	reptree	reptree	NOUN
cana-1616	239	34	,	,	PUNCT
cana-1616	239	35	0.77	0.77	NUM
cana-1616	239	36	in	in	ADP
cana-1616	239	37	nb	nb	PROPN
cana-1616	239	38	,	,	PUNCT
cana-1616	239	39	0.86	0.86	NUM
cana-1616	239	40	in	in	ADP
cana-1616	239	41	rotf	rotf	NOUN
cana-1616	239	42	,	,	PUNCT
cana-1616	239	43	0.87	0.87	NUM
cana-1616	239	44	in	in	ADP
cana-1616	239	45	rf	rf	NOUN
cana-1616	239	46	,	,	PUNCT
cana-1616	239	47	adaboostm1	adaboostm1	NOUN
cana-1616	239	48	and	and	CCONJ
cana-1616	239	49	bagging	bagging	NOUN
cana-1616	239	50	,	,	PUNCT
cana-1616	239	51	and	and	CCONJ
cana-1616	239	52	0.881	0.881	NUM
cana-1616	239	53	in	in	ADP
cana-1616	239	54	stacking	stack	VERB
cana-1616	239	55	respectively	respectively	ADV
cana-1616	239	56	.	.	PUNCT
cana-1616	240	1	while	while	SCONJ
cana-1616	240	2	as	as	SCONJ
cana-1616	240	3	,	,	PUNCT
cana-1616	240	4	this	this	PRON
cana-1616	240	5	is	be	AUX
cana-1616	240	6	not	not	PART
cana-1616	240	7	the	the	DET
cana-1616	240	8	case	case	NOUN
cana-1616	240	9	in	in	ADP
cana-1616	240	10	proposed	propose	VERB
cana-1616	240	11	model	model	NOUN
cana-1616	240	12	,	,	PUNCT
cana-1616	240	13	wherein	wherein	SCONJ
cana-1616	240	14	we	we	PRON
cana-1616	240	15	were	be	AUX
cana-1616	240	16	able	able	ADJ
cana-1616	240	17	to	to	PART
cana-1616	240	18	achieve	achieve	VERB
cana-1616	240	19	an	an	DET
cana-1616	240	20	auc	auc	NOUN
cana-1616	240	21	of	of	ADP
cana-1616	240	22	0.95	0.95	NUM
cana-1616	240	23	which	which	PRON
cana-1616	240	24	is	be	AUX
cana-1616	240	25	very	very	ADV
cana-1616	240	26	close	close	ADJ
cana-1616	240	27	to	to	ADP
cana-1616	240	28	1	1	NUM
cana-1616	240	29	,	,	PUNCT
cana-1616	240	30	when	when	SCONJ
cana-1616	240	31	compared	compare	VERB
cana-1616	240	32	with	with	ADP
cana-1616	240	33	other	other	ADJ
cana-1616	240	34	similar	similar	ADJ
cana-1616	240	35	models	model	NOUN
cana-1616	240	36	.	.	PUNCT
cana-1616	241	1	the	the	DET
cana-1616	241	2	specific	specific	ADJ
cana-1616	241	3	values	value	NOUN
cana-1616	241	4	for	for	ADP
cana-1616	241	5	all	all	DET
cana-1616	241	6	the	the	DET
cana-1616	241	7	mentioned	mention	VERB
cana-1616	241	8	parameters	parameter	NOUN
cana-1616	241	9	is	be	AUX
cana-1616	241	10	represented	represent	VERB
cana-1616	241	11	in	in	ADP
cana-1616	241	12	table	table	NOUN
cana-1616	241	13	7	7	NUM
cana-1616	241	14	.	.	PUNCT
cana-1616	241	15	communications	communication	NOUN
cana-1616	241	16	on	on	ADP
cana-1616	241	17	applied	apply	VERB
cana-1616	241	18	nonlinear	nonlinear	ADJ
cana-1616	241	19	analysis	analysis	NOUN
cana-1616	241	20	issn	issn	NOUN
cana-1616	241	21	:	:	PUNCT
cana-1616	241	22	1074	1074	NUM
cana-1616	241	23	-	-	PUNCT
cana-1616	241	24	133x	133x	NUM
cana-1616	241	25	vol	vol	NOUN
cana-1616	241	26	31	31	NUM
cana-1616	241	27	no	no	NOUN
cana-1616	241	28	.	.	PUNCT
cana-1616	242	1	8s	8s	PROPN
cana-1616	242	2	(	(	PUNCT
cana-1616	242	3	2024	2024	NUM
cana-1616	242	4	)	)	PUNCT
cana-1616	242	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	242	6	788	788	NUM
cana-1616	242	7	table	table	NOUN
cana-1616	242	8	7	7	NUM
cana-1616	242	9	:	:	PUNCT
cana-1616	242	10	comparative	comparative	ADJ
cana-1616	242	11	values	value	NOUN
cana-1616	242	12	of	of	ADP
cana-1616	242	13	different	different	ADJ
cana-1616	242	14	parameters	parameter	NOUN
cana-1616	242	15	algorithm	algorithm	NOUN
cana-1616	242	16	accuracy	accuracy	NOUN
cana-1616	242	17	precision	precision	NOUN
cana-1616	242	18	recall	recall	VERB
cana-1616	242	19	f1	f1	NOUN
cana-1616	242	20	-	-	PUNCT
cana-1616	242	21	score	score	NOUN
cana-1616	242	22	auc	auc	NOUN
cana-1616	242	23	nb	nb	NOUN
cana-1616	242	24	0.711	0.711	NUM
cana-1616	242	25	0.724	0.724	NUM
cana-1616	242	26	0.711	0.711	NUM
cana-1616	242	27	0.707	0.707	NUM
cana-1616	242	28	0.771	0.771	NUM
cana-1616	242	29	svm	svm	NOUN
cana-1616	242	30	0.708	0.708	NUM
cana-1616	242	31	0.748	0.748	NUM
cana-1616	242	32	0.708	0.708	NUM
cana-1616	242	33	0.708	0.708	NUM
cana-1616	242	34	0.708	0.708	NUM
cana-1616	242	35	lr	lr	NOUN
cana-1616	242	36	0.7	0.7	NUM
cana-1616	242	37	0.713	0.713	NUM
cana-1616	242	38	0.7	0.7	NUM
cana-1616	242	39	0.7	0.7	NUM
cana-1616	242	40	0.754	0.754	NUM
cana-1616	242	41	mlp	mlp	NOUN
cana-1616	242	42	0.69	0.69	NUM
cana-1616	242	43	0.701	0.701	NUM
cana-1616	242	44	0.69	0.69	NUM
cana-1616	242	45	0.69	0.69	NUM
cana-1616	242	46	0.742	0.742	NUM
cana-1616	242	47	1	1	NUM
cana-1616	242	48	-	-	SYM
cana-1616	242	49	nn	nn	NOUN
cana-1616	242	50	0.688	0.688	NUM
cana-1616	242	51	0.691	0.691	NUM
cana-1616	242	52	0.688	0.688	NUM
cana-1616	242	53	0.687	0.687	NUM
cana-1616	242	54	0.693	0.693	NUM
cana-1616	242	55	j48	j48	NOUN
cana-1616	242	56	0.732	0.732	NUM
cana-1616	242	57	0.733	0.733	NUM
cana-1616	242	58	0.732	0.732	NUM
cana-1616	242	59	0.732	0.732	NUM
cana-1616	242	60	0.735	0.735	NUM
cana-1616	242	61	rf	rf	NUM
cana-1616	242	62	0.794	0.794	NUM
cana-1616	242	63	0.798	0.798	NUM
cana-1616	242	64	0.793	0.793	NUM
cana-1616	242	65	0.793	0.793	NUM
cana-1616	242	66	0.877	0.877	NUM
cana-1616	242	67	rt	rt	NOUN
cana-1616	242	68	0.718	0.718	NUM
cana-1616	242	69	0.717	0.717	NUM
cana-1616	242	70	0.717	0.717	NUM
cana-1616	242	71	0.717	0.717	NUM
cana-1616	242	72	0.717	0.717	NUM
cana-1616	242	73	reptree	reptree	NOUN
cana-1616	242	74	0.708	0.708	NUM
cana-1616	242	75	0.71	0.71	NUM
cana-1616	242	76	0.708	0.708	NUM
cana-1616	242	77	0.707	0.707	NUM
cana-1616	242	78	0.761	0.761	NUM
cana-1616	242	79	rotf	rotf	NOUN
cana-1616	242	80	0.775	0.775	NUM
cana-1616	242	81	0.789	0.789	NUM
cana-1616	242	82	0.775	0.775	NUM
cana-1616	242	83	0.773	0.773	NUM
cana-1616	242	84	0.869	0.869	NUM
cana-1616	242	85	adaboostm1	adaboostm1	DET
cana-1616	242	86	0.795	0.795	NUM
cana-1616	242	87	0.797	0.797	NUM
cana-1616	242	88	0.795	0.795	NUM
cana-1616	242	89	0.795	0.795	NUM
cana-1616	242	90	0.879	0.879	NUM
cana-1616	242	91	stacking	stack	VERB
cana-1616	242	92	0.794	0.794	NUM
cana-1616	242	93	0.795	0.795	NUM
cana-1616	242	94	0.793	0.793	NUM
cana-1616	242	95	0.793	0.793	NUM
cana-1616	242	96	0.881	0.881	NUM
cana-1616	242	97	bagging	bag	VERB
cana-1616	242	98	0.785	0.785	NUM
cana-1616	242	99	0.791	0.791	NUM
cana-1616	242	100	0.785	0.785	NUM
cana-1616	242	101	0.784	0.784	NUM
cana-1616	242	102	0.872	0.872	NUM
cana-1616	242	103	voting	vote	VERB
cana-1616	242	104	0.801	0.801	NUM
cana-1616	242	105	0.804	0.804	NUM
cana-1616	242	106	0.801	0.801	NUM
cana-1616	242	107	0.801	0.801	NUM
cana-1616	242	108	0.884	0.884	NUM
cana-1616	242	109	proposed	propose	VERB
cana-1616	242	110	0.93182	0.93182	NUM
cana-1616	242	111	0.9913	0.9913	NUM
cana-1616	242	112	0.90476	0.90476	NUM
cana-1616	242	113	0.94606	0.94606	NUM
cana-1616	242	114	0.95238	0.95238	NUM
cana-1616	242	115	5.4	5.4	NUM
cana-1616	242	116	multi	multi	ADJ
cana-1616	242	117	-	-	ADJ
cana-1616	242	118	stage	stage	ADJ
cana-1616	242	119	disease	disease	NOUN
cana-1616	242	120	classification	classification	NOUN
cana-1616	242	121	results	result	NOUN
cana-1616	242	122	in	in	ADP
cana-1616	242	123	second	second	ADJ
cana-1616	242	124	phase	phase	NOUN
cana-1616	242	125	,	,	PUNCT
cana-1616	242	126	different	different	ADJ
cana-1616	242	127	stages	stage	NOUN
cana-1616	242	128	of	of	ADP
cana-1616	242	129	liver	liver	NOUN
cana-1616	242	130	disease	disease	NOUN
cana-1616	242	131	are	be	AUX
cana-1616	242	132	identified	identify	VERB
cana-1616	242	133	by	by	ADP
cana-1616	242	134	proposed	propose	VERB
cana-1616	242	135	model	model	NOUN
cana-1616	242	136	through	through	ADP
cana-1616	242	137	nonensemble	nonensemble	ADJ
cana-1616	242	138	learning	learning	NOUN
cana-1616	242	139	,	,	PUNCT
cana-1616	242	140	bagging	bag	VERB
cana-1616	242	141	ensemble	ensemble	ADJ
cana-1616	242	142	,	,	PUNCT
cana-1616	242	143	and	and	CCONJ
cana-1616	242	144	boosting	boost	VERB
cana-1616	242	145	ensemble	ensemble	ADJ
cana-1616	242	146	techniques	technique	NOUN
cana-1616	242	147	.	.	PUNCT
cana-1616	243	1	the	the	DET
cana-1616	243	2	results	result	NOUN
cana-1616	243	3	obtained	obtain	VERB
cana-1616	243	4	for	for	ADP
cana-1616	243	5	three	three	NUM
cana-1616	243	6	cases	case	NOUN
cana-1616	243	7	were	be	AUX
cana-1616	243	8	examined	examine	VERB
cana-1616	243	9	and	and	CCONJ
cana-1616	243	10	compared	compare	VERB
cana-1616	243	11	with	with	ADP
cana-1616	243	12	traditional	traditional	ADJ
cana-1616	243	13	models	model	NOUN
cana-1616	243	14	using	use	VERB
cana-1616	243	15	cpd	cpd	NOUN
cana-1616	243	16	dataset	dataset	NOUN
cana-1616	243	17	.	.	PUNCT
cana-1616	244	1	initially	initially	ADV
cana-1616	244	2	,	,	PUNCT
cana-1616	244	3	we	we	PRON
cana-1616	244	4	have	have	AUX
cana-1616	244	5	determined	determine	VERB
cana-1616	244	6	the	the	DET
cana-1616	244	7	confusion	confusion	NOUN
cana-1616	244	8	matrix	matrix	NOUN
cana-1616	244	9	for	for	ADP
cana-1616	244	10	proposed	propose	VERB
cana-1616	244	11	model	model	NOUN
cana-1616	244	12	for	for	ADP
cana-1616	244	13	multi	multi	ADJ
cana-1616	244	14	-	-	ADJ
cana-1616	244	15	stage	stage	ADJ
cana-1616	244	16	disease	disease	NOUN
cana-1616	244	17	classification	classification	NOUN
cana-1616	244	18	in	in	ADP
cana-1616	244	19	which	which	PRON
cana-1616	244	20	four	four	NUM
cana-1616	244	21	stages	stage	NOUN
cana-1616	244	22	of	of	ADP
cana-1616	244	23	disease	disease	NOUN
cana-1616	244	24	are	be	AUX
cana-1616	244	25	detected	detect	VERB
cana-1616	244	26	,	,	PUNCT
cana-1616	244	27	as	as	SCONJ
cana-1616	244	28	shown	show	VERB
cana-1616	244	29	in	in	ADP
cana-1616	244	30	figure	figure	NOUN
cana-1616	244	31	12	12	NUM
cana-1616	244	32	.	.	PUNCT
cana-1616	245	1	the	the	DET
cana-1616	245	2	given	give	VERB
cana-1616	245	3	figure	figure	NOUN
cana-1616	245	4	demonstrates	demonstrate	VERB
cana-1616	245	5	that	that	SCONJ
cana-1616	245	6	proposed	propose	VERB
cana-1616	245	7	approach	approach	NOUN
cana-1616	245	8	correctly	correctly	ADV
cana-1616	245	9	identified	identify	VERB
cana-1616	245	10	class	class	NOUN
cana-1616	245	11	1	1	NUM
cana-1616	245	12	of	of	ADP
cana-1616	245	13	disease	disease	NOUN
cana-1616	245	14	with	with	ADP
cana-1616	245	15	100	100	NUM
cana-1616	245	16	%	%	NOUN
cana-1616	245	17	accuracy	accuracy	NOUN
cana-1616	245	18	while	while	SCONJ
cana-1616	245	19	as	as	SCONJ
cana-1616	245	20	,	,	PUNCT
cana-1616	245	21	accuracy	accuracy	NOUN
cana-1616	245	22	of	of	ADP
cana-1616	245	23	97	97	NUM
cana-1616	245	24	%	%	NOUN
cana-1616	245	25	,	,	PUNCT
cana-1616	245	26	93	93	NUM
cana-1616	245	27	%	%	NOUN
cana-1616	245	28	and	and	CCONJ
cana-1616	245	29	95	95	NUM
cana-1616	245	30	%	%	NOUN
cana-1616	245	31	are	be	AUX
cana-1616	245	32	attained	attain	VERB
cana-1616	245	33	for	for	ADP
cana-1616	245	34	classes	class	NOUN
cana-1616	245	35	2	2	NUM
cana-1616	245	36	,	,	PUNCT
cana-1616	245	37	3	3	NUM
cana-1616	245	38	and	and	CCONJ
cana-1616	245	39	4	4	NUM
cana-1616	245	40	respectively	respectively	ADV
cana-1616	245	41	.	.	PUNCT
cana-1616	246	1	moreover	moreover	ADV
cana-1616	246	2	,	,	PUNCT
cana-1616	246	3	the	the	DET
cana-1616	246	4	confusion	confusion	NOUN
cana-1616	246	5	matrix	matrix	NOUN
cana-1616	246	6	also	also	ADV
cana-1616	246	7	aids	aid	VERB
cana-1616	246	8	in	in	ADP
cana-1616	246	9	evaluating	evaluate	VERB
cana-1616	246	10	other	other	ADJ
cana-1616	246	11	metrics	metric	NOUN
cana-1616	246	12	like	like	ADP
cana-1616	246	13	precision	precision	NOUN
cana-1616	246	14	,	,	PUNCT
cana-1616	246	15	recall	recall	NOUN
cana-1616	246	16	and	and	CCONJ
cana-1616	246	17	f1	f1	NOUN
cana-1616	246	18	-	-	PUNCT
cana-1616	246	19	score	score	NOUN
cana-1616	246	20	.	.	PUNCT
cana-1616	247	1	figure	figure	NOUN
cana-1616	247	2	12	12	NUM
cana-1616	247	3	.	.	PUNCT
cana-1616	248	1	confusion	confusion	NOUN
cana-1616	248	2	matrix	matrix	NOUN
cana-1616	248	3	for	for	ADP
cana-1616	248	4	multi	multi	ADJ
cana-1616	248	5	-	-	ADJ
cana-1616	248	6	stage	stage	ADJ
cana-1616	248	7	disease	disease	NOUN
cana-1616	248	8	classification	classification	NOUN
cana-1616	248	9	moreover	moreover	ADV
cana-1616	248	10	,	,	PUNCT
cana-1616	248	11	to	to	PART
cana-1616	248	12	prove	prove	VERB
cana-1616	248	13	the	the	DET
cana-1616	248	14	supremacy	supremacy	NOUN
cana-1616	248	15	of	of	ADP
cana-1616	248	16	proposed	propose	VERB
cana-1616	248	17	approach	approach	NOUN
cana-1616	248	18	over	over	ADP
cana-1616	248	19	other	other	ADJ
cana-1616	248	20	models	model	NOUN
cana-1616	248	21	,	,	PUNCT
cana-1616	248	22	we	we	PRON
cana-1616	248	23	compared	compare	VERB
cana-1616	248	24	its	its	PRON
cana-1616	248	25	performance	performance	NOUN
cana-1616	248	26	with	with	ADP
cana-1616	248	27	few	few	ADJ
cana-1616	248	28	conventional	conventional	ADJ
cana-1616	248	29	models	model	NOUN
cana-1616	248	30	for	for	ADP
cana-1616	248	31	case	case	NOUN
cana-1616	248	32	1	1	NUM
cana-1616	248	33	(	(	PUNCT
cana-1616	248	34	non	non	ADJ
cana-1616	248	35	-	-	ADJ
cana-1616	248	36	ensemble	ensemble	ADJ
cana-1616	248	37	learning	learning	NOUN
cana-1616	248	38	cross	cross	NOUN
cana-1616	248	39	validation	validation	NOUN
cana-1616	248	40	)	)	PUNCT
cana-1616	248	41	technique	technique	NOUN
cana-1616	248	42	.	.	PUNCT
cana-1616	249	1	the	the	DET
cana-1616	249	2	comparative	comparative	ADJ
cana-1616	249	3	graph	graph	NOUN
cana-1616	249	4	obtained	obtain	VERB
cana-1616	249	5	for	for	ADP
cana-1616	249	6	the	the	DET
cana-1616	249	7	same	same	ADJ
cana-1616	249	8	is	be	AUX
cana-1616	249	9	shown	show	VERB
cana-1616	249	10	in	in	ADP
cana-1616	249	11	figure	figure	NOUN
cana-1616	249	12	13	13	NUM
cana-1616	249	13	,	,	PUNCT
cana-1616	249	14	with	with	ADP
cana-1616	249	15	different	different	ADJ
cana-1616	249	16	models	model	NOUN
cana-1616	249	17	on	on	ADP
cana-1616	249	18	x	x	ADJ
cana-1616	249	19	-	-	ADJ
cana-1616	249	20	axis	axis	ADJ
cana-1616	249	21	and	and	CCONJ
cana-1616	249	22	accuracy	accuracy	NOUN
cana-1616	249	23	,	,	PUNCT
cana-1616	249	24	precision	precision	NOUN
cana-1616	249	25	,	,	PUNCT
cana-1616	249	26	recall	recall	NOUN
cana-1616	249	27	and	and	CCONJ
cana-1616	249	28	f1	f1	ADJ
cana-1616	249	29	-	-	PUNCT
cana-1616	249	30	score	score	NOUN
cana-1616	249	31	metrics	metric	NOUN
cana-1616	249	32	on	on	ADP
cana-1616	249	33	y	y	NOUN
cana-1616	249	34	-	-	PUNCT
cana-1616	249	35	axis	axis	NOUN
cana-1616	249	36	respectively	respectively	ADV
cana-1616	249	37	.	.	PUNCT
cana-1616	250	1	after	after	ADP
cana-1616	250	2	analyzing	analyze	VERB
cana-1616	250	3	the	the	DET
cana-1616	250	4	given	give	VERB
cana-1616	250	5	graph	graph	NOUN
cana-1616	250	6	,	,	PUNCT
cana-1616	250	7	it	it	PRON
cana-1616	250	8	is	be	AUX
cana-1616	250	9	observed	observe	VERB
cana-1616	250	10	that	that	SCONJ
cana-1616	250	11	proposed	propose	VERB
cana-1616	250	12	model	model	NOUN
cana-1616	250	13	attained	attain	VERB
cana-1616	250	14	higher	high	ADJ
cana-1616	250	15	accuracy	accuracy	NOUN
cana-1616	250	16	of	of	ADP
cana-1616	250	17	96.8	96.8	NUM
cana-1616	250	18	%	%	NOUN
cana-1616	250	19	whereas	whereas	SCONJ
cana-1616	250	20	,	,	PUNCT
cana-1616	250	21	other	other	ADJ
cana-1616	250	22	communications	communication	NOUN
cana-1616	250	23	on	on	ADP
cana-1616	250	24	applied	apply	VERB
cana-1616	250	25	nonlinear	nonlinear	ADJ
cana-1616	250	26	analysis	analysis	NOUN
cana-1616	250	27	issn	issn	NOUN
cana-1616	250	28	:	:	PUNCT
cana-1616	250	29	1074	1074	NUM
cana-1616	250	30	-	-	PUNCT
cana-1616	250	31	133x	133x	NUM
cana-1616	250	32	vol	vol	NOUN
cana-1616	250	33	31	31	NUM
cana-1616	250	34	no	no	NOUN
cana-1616	250	35	.	.	PUNCT
cana-1616	251	1	8s	8s	PROPN
cana-1616	251	2	(	(	PUNCT
cana-1616	251	3	2024	2024	NUM
cana-1616	251	4	)	)	PUNCT
cana-1616	251	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	251	6	789	789	NUM
cana-1616	251	7	models	model	NOUN
cana-1616	251	8	like	like	ADP
cana-1616	251	9	adaboost	adaboost	ADV
cana-1616	251	10	,	,	PUNCT
cana-1616	251	11	dt	dt	PROPN
cana-1616	251	12	,	,	PUNCT
cana-1616	251	13	ett	ett	PROPN
cana-1616	251	14	,	,	PUNCT
cana-1616	251	15	gb	gb	PROPN
cana-1616	251	16	,	,	PUNCT
cana-1616	251	17	knn	knn	PROPN
cana-1616	251	18	,	,	PUNCT
cana-1616	251	19	lgbm	lgbm	PROPN
cana-1616	251	20	,	,	PUNCT
cana-1616	251	21	lr	lr	NOUN
cana-1616	251	22	,	,	PUNCT
cana-1616	251	23	rf	rf	PRON
cana-1616	251	24	and	and	CCONJ
cana-1616	251	25	svc	svc	PROPN
cana-1616	251	26	attained	attain	VERB
cana-1616	251	27	only	only	ADV
cana-1616	251	28	71	71	NUM
cana-1616	251	29	%	%	NOUN
cana-1616	251	30	,	,	PUNCT
cana-1616	251	31	61	61	NUM
cana-1616	251	32	%	%	NOUN
cana-1616	251	33	,	,	PUNCT
cana-1616	251	34	68	68	NUM
cana-1616	251	35	%	%	NOUN
cana-1616	251	36	,	,	PUNCT
cana-1616	251	37	72.7	72.7	NUM
cana-1616	251	38	%	%	NOUN
cana-1616	251	39	,	,	PUNCT
cana-1616	251	40	67	67	NUM
cana-1616	251	41	%	%	NOUN
cana-1616	251	42	,	,	PUNCT
cana-1616	251	43	69	69	NUM
cana-1616	251	44	%	%	NOUN
cana-1616	251	45	,	,	PUNCT
cana-1616	251	46	72	72	NUM
cana-1616	251	47	%	%	NOUN
cana-1616	251	48	,	,	PUNCT
cana-1616	251	49	70	70	NUM
cana-1616	251	50	%	%	NOUN
cana-1616	251	51	and	and	CCONJ
cana-1616	251	52	69	69	NUM
cana-1616	251	53	%	%	NOUN
cana-1616	251	54	respectively	respectively	ADV
cana-1616	251	55	.	.	PUNCT
cana-1616	252	1	moreover	moreover	ADV
cana-1616	252	2	,	,	PUNCT
cana-1616	252	3	proposed	propose	VERB
cana-1616	252	4	approach	approach	NOUN
cana-1616	252	5	attained	attain	VERB
cana-1616	252	6	high	high	ADJ
cana-1616	252	7	precision	precision	NOUN
cana-1616	252	8	,	,	PUNCT
cana-1616	252	9	f1	f1	ADJ
cana-1616	252	10	-	-	PUNCT
cana-1616	252	11	score	score	NOUN
cana-1616	252	12	values	value	NOUN
cana-1616	252	13	of	of	ADP
cana-1616	252	14	92.8	92.8	NUM
cana-1616	252	15	%	%	NOUN
cana-1616	252	16	and	and	CCONJ
cana-1616	252	17	recall	recall	NOUN
cana-1616	252	18	of	of	ADP
cana-1616	252	19	92.9	92.9	NUM
cana-1616	252	20	%	%	NOUN
cana-1616	252	21	for	for	ADP
cana-1616	252	22	this	this	DET
cana-1616	252	23	case	case	NOUN
cana-1616	252	24	.	.	PUNCT
cana-1616	253	1	however	however	ADV
cana-1616	253	2	,	,	PUNCT
cana-1616	253	3	out	out	ADP
cana-1616	253	4	of	of	ADP
cana-1616	253	5	all	all	DET
cana-1616	253	6	conventional	conventional	ADJ
cana-1616	253	7	models	model	NOUN
cana-1616	253	8	,	,	PUNCT
cana-1616	253	9	lr	lr	PROPN
cana-1616	253	10	model	model	NOUN
cana-1616	253	11	attains	attain	NOUN
cana-1616	253	12	best	good	ADJ
cana-1616	253	13	precision	precision	NOUN
cana-1616	253	14	of	of	ADP
cana-1616	253	15	66	66	NUM
cana-1616	253	16	%	%	NOUN
cana-1616	253	17	,	,	PUNCT
cana-1616	253	18	while	while	SCONJ
cana-1616	253	19	as	as	ADP
cana-1616	253	20	,	,	PUNCT
cana-1616	253	21	dt	dt	PUNCT
cana-1616	253	22	and	and	CCONJ
cana-1616	253	23	gb	gb	PROPN
cana-1616	253	24	attains	attain	NOUN
cana-1616	253	25	best	well	ADV
cana-1616	253	26	recall	recall	NOUN
cana-1616	253	27	and	and	CCONJ
cana-1616	253	28	f1	f1	NOUN
cana-1616	253	29	-	-	PUNCT
cana-1616	253	30	score	score	NOUN
cana-1616	253	31	of	of	ADP
cana-1616	253	32	50	50	NUM
cana-1616	253	33	%	%	NOUN
cana-1616	253	34	and	and	CCONJ
cana-1616	253	35	54	54	NUM
cana-1616	253	36	%	%	NOUN
cana-1616	253	37	respectively	respectively	ADV
cana-1616	253	38	.	.	PUNCT
cana-1616	254	1	these	these	DET
cana-1616	254	2	results	result	NOUN
cana-1616	254	3	clearly	clearly	ADV
cana-1616	254	4	indicate	indicate	VERB
cana-1616	254	5	efficacy	efficacy	NOUN
cana-1616	254	6	of	of	ADP
cana-1616	254	7	proposed	propose	VERB
cana-1616	254	8	approach	approach	NOUN
cana-1616	254	9	over	over	ADP
cana-1616	254	10	other	other	ADJ
cana-1616	254	11	approaches	approach	NOUN
cana-1616	254	12	.	.	PUNCT
cana-1616	255	1	for	for	ADP
cana-1616	255	2	precise	precise	ADJ
cana-1616	255	3	calculations	calculation	NOUN
cana-1616	255	4	,	,	PUNCT
cana-1616	255	5	refer	refer	VERB
cana-1616	255	6	table	table	NOUN
cana-1616	255	7	8	8	NUM
cana-1616	255	8	.	.	PUNCT
cana-1616	256	1	figure	figure	NOUN
cana-1616	256	2	13	13	NUM
cana-1616	256	3	.	.	PUNCT
cana-1616	257	1	comparative	comparative	ADJ
cana-1616	257	2	results	result	NOUN
cana-1616	257	3	for	for	ADP
cana-1616	257	4	case	case	NOUN
cana-1616	257	5	1	1	NUM
cana-1616	257	6	multi	multi	ADJ
cana-1616	257	7	-	-	ADJ
cana-1616	257	8	stage	stage	ADJ
cana-1616	257	9	disease	disease	NOUN
cana-1616	257	10	classification	classification	NOUN
cana-1616	257	11	figure	figure	NOUN
cana-1616	257	12	14	14	NUM
cana-1616	257	13	.	.	PUNCT
cana-1616	258	1	comparative	comparative	ADJ
cana-1616	258	2	results	result	NOUN
cana-1616	258	3	for	for	ADP
cana-1616	258	4	case	case	NOUN
cana-1616	258	5	2	2	NUM
cana-1616	258	6	multi	multi	ADJ
cana-1616	258	7	-	-	ADJ
cana-1616	258	8	stage	stage	ADJ
cana-1616	258	9	disease	disease	NOUN
cana-1616	258	10	classification	classification	NOUN
cana-1616	258	11	furthermore	furthermore	ADV
cana-1616	258	12	,	,	PUNCT
cana-1616	258	13	we	we	PRON
cana-1616	258	14	analyzed	analyze	VERB
cana-1616	258	15	the	the	DET
cana-1616	258	16	performance	performance	NOUN
cana-1616	258	17	of	of	ADP
cana-1616	258	18	proposed	propose	VERB
cana-1616	258	19	approach	approach	NOUN
cana-1616	258	20	with	with	ADP
cana-1616	258	21	other	other	ADJ
cana-1616	258	22	conventional	conventional	ADJ
cana-1616	258	23	models	model	NOUN
cana-1616	258	24	on	on	ADP
cana-1616	258	25	cpd	cpd	NOUN
cana-1616	258	26	dataset	dataset	NOUN
cana-1616	258	27	for	for	ADP
cana-1616	258	28	determining	determine	VERB
cana-1616	258	29	the	the	DET
cana-1616	258	30	stage	stage	NOUN
cana-1616	258	31	of	of	ADP
cana-1616	258	32	liver	liver	NOUN
cana-1616	258	33	disease	disease	NOUN
cana-1616	258	34	through	through	ADP
cana-1616	258	35	bagging	bag	VERB
cana-1616	258	36	ensemble	ensemble	ADJ
cana-1616	258	37	cross	cross	NOUN
cana-1616	258	38	validation	validation	NOUN
cana-1616	258	39	technique	technique	NOUN
cana-1616	258	40	(	(	PUNCT
cana-1616	258	41	case	case	NOUN
cana-1616	258	42	2	2	NUM
cana-1616	258	43	)	)	PUNCT
cana-1616	258	44	.	.	PUNCT
cana-1616	259	1	the	the	DET
cana-1616	259	2	comparative	comparative	ADJ
cana-1616	259	3	graph	graph	NOUN
cana-1616	259	4	obtained	obtain	VERB
cana-1616	259	5	for	for	ADP
cana-1616	259	6	the	the	DET
cana-1616	259	7	same	same	ADJ
cana-1616	259	8	is	be	AUX
cana-1616	259	9	shown	show	VERB
cana-1616	259	10	in	in	ADP
cana-1616	259	11	figure	figure	NOUN
cana-1616	259	12	14	14	NUM
cana-1616	259	13	,	,	PUNCT
cana-1616	259	14	which	which	PRON
cana-1616	259	15	shows	show	VERB
cana-1616	259	16	proposed	propose	VERB
cana-1616	259	17	model	model	NOUN
cana-1616	259	18	attained	attain	VERB
cana-1616	259	19	highest	high	ADJ
cana-1616	259	20	accuracy	accuracy	NOUN
cana-1616	259	21	(	(	PUNCT
cana-1616	259	22	96.8	96.8	NUM
cana-1616	259	23	%	%	NOUN
cana-1616	259	24	)	)	PUNCT
cana-1616	259	25	,	,	PUNCT
cana-1616	259	26	precision	precision	NOUN
cana-1616	259	27	(	(	PUNCT
cana-1616	259	28	92.8	92.8	NUM
cana-1616	259	29	%	%	NOUN
cana-1616	259	30	)	)	PUNCT
cana-1616	259	31	,	,	PUNCT
cana-1616	259	32	recall	recall	INTJ
cana-1616	259	33	(	(	PUNCT
cana-1616	259	34	92.9	92.9	NUM
cana-1616	259	35	%	%	NOUN
cana-1616	259	36	)	)	PUNCT
cana-1616	259	37	and	and	CCONJ
cana-1616	259	38	f1	f1	NOUN
cana-1616	259	39	-	-	PUNCT
cana-1616	259	40	score	score	NOUN
cana-1616	259	41	(	(	PUNCT
cana-1616	259	42	92.8	92.8	NUM
cana-1616	259	43	%	%	NOUN
cana-1616	259	44	)	)	PUNCT
cana-1616	259	45	respectively	respectively	ADV
cana-1616	259	46	.	.	PUNCT
cana-1616	260	1	however	however	ADV
cana-1616	260	2	,	,	PUNCT
cana-1616	260	3	this	this	PRON
cana-1616	260	4	is	be	AUX
cana-1616	260	5	not	not	PART
cana-1616	260	6	the	the	DET
cana-1616	260	7	case	case	NOUN
cana-1616	260	8	in	in	ADP
cana-1616	260	9	traditional	traditional	ADJ
cana-1616	260	10	models	model	NOUN
cana-1616	260	11	wherein	wherein	SCONJ
cana-1616	260	12	highest	high	ADJ
cana-1616	260	13	accuracy	accuracy	NOUN
cana-1616	260	14	of	of	ADP
cana-1616	260	15	73	73	NUM
cana-1616	260	16	%	%	NOUN
cana-1616	260	17	was	be	AUX
cana-1616	260	18	attained	attain	VERB
cana-1616	260	19	adaboost	adaboost	ADV
cana-1616	260	20	and	and	CCONJ
cana-1616	260	21	lowest	low	ADJ
cana-1616	260	22	accuracy	accuracy	NOUN
cana-1616	260	23	of	of	ADP
cana-1616	260	24	68	68	NUM
cana-1616	260	25	%	%	NOUN
cana-1616	260	26	is	be	AUX
cana-1616	260	27	attained	attain	VERB
cana-1616	260	28	by	by	ADP
cana-1616	260	29	svc	svc	PROPN
cana-1616	260	30	model	model	PROPN
cana-1616	260	31	.	.	PUNCT
cana-1616	261	1	similarly	similarly	ADV
cana-1616	261	2	,	,	PUNCT
cana-1616	261	3	for	for	ADP
cana-1616	261	4	other	other	ADJ
cana-1616	261	5	metrics	metric	NOUN
cana-1616	261	6	like	like	ADP
cana-1616	261	7	precision	precision	NOUN
cana-1616	261	8	,	,	PUNCT
cana-1616	261	9	recall	recall	NOUN
cana-1616	261	10	and	and	CCONJ
cana-1616	261	11	f1	f1	NOUN
cana-1616	261	12	-	-	PUNCT
cana-1616	261	13	measure	measure	NOUN
cana-1616	261	14	adaboost	adaboost	ADV
cana-1616	261	15	is	be	AUX
cana-1616	261	16	continuously	continuously	ADV
cana-1616	261	17	showing	show	VERB
cana-1616	261	18	better	well	ADJ
cana-1616	261	19	results	result	NOUN
cana-1616	261	20	than	than	ADP
cana-1616	261	21	other	other	ADJ
cana-1616	261	22	conventional	conventional	ADJ
cana-1616	261	23	models	model	NOUN
cana-1616	261	24	,	,	PUNCT
cana-1616	261	25	however	however	ADV
cana-1616	261	26	,	,	PUNCT
cana-1616	261	27	it	it	PRON
cana-1616	261	28	was	be	AUX
cana-1616	261	29	still	still	ADV
cana-1616	261	30	far	far	ADV
cana-1616	261	31	from	from	ADP
cana-1616	261	32	performance	performance	NOUN
cana-1616	261	33	of	of	ADP
cana-1616	261	34	proposed	propose	VERB
cana-1616	261	35	approach	approach	NOUN
cana-1616	261	36	.	.	PUNCT
cana-1616	262	1	table	table	NOUN
cana-1616	262	2	9	9	NUM
cana-1616	262	3	depicts	depict	VERB
cana-1616	262	4	precise	precise	ADJ
cana-1616	262	5	values	value	NOUN
cana-1616	262	6	obtained	obtain	VERB
cana-1616	262	7	for	for	ADP
cana-1616	262	8	each	each	DET
cana-1616	262	9	metric	metric	NOUN
cana-1616	262	10	in	in	ADP
cana-1616	262	11	this	this	DET
cana-1616	262	12	case	case	NOUN
cana-1616	262	13	.	.	PUNCT
cana-1616	263	1	figure	figure	NOUN
cana-1616	263	2	15	15	NUM
cana-1616	263	3	.	.	PUNCT
cana-1616	264	1	comparative	comparative	ADJ
cana-1616	264	2	results	result	NOUN
cana-1616	264	3	for	for	ADP
cana-1616	264	4	case	case	NOUN
cana-1616	264	5	3	3	NUM
cana-1616	264	6	multi	multi	ADJ
cana-1616	264	7	-	-	ADJ
cana-1616	264	8	stage	stage	ADJ
cana-1616	264	9	disease	disease	NOUN
cana-1616	264	10	classification	classification	NOUN
cana-1616	264	11	in	in	ADP
cana-1616	264	12	addition	addition	NOUN
cana-1616	264	13	to	to	ADP
cana-1616	264	14	this	this	PRON
cana-1616	264	15	,	,	PUNCT
cana-1616	264	16	we	we	PRON
cana-1616	264	17	have	have	AUX
cana-1616	264	18	also	also	ADV
cana-1616	264	19	analyzed	analyze	VERB
cana-1616	264	20	and	and	CCONJ
cana-1616	264	21	compared	compare	VERB
cana-1616	264	22	the	the	DET
cana-1616	264	23	performance	performance	NOUN
cana-1616	264	24	of	of	ADP
cana-1616	264	25	proposed	propose	VERB
cana-1616	264	26	approach	approach	NOUN
cana-1616	264	27	with	with	ADP
cana-1616	264	28	traditional	traditional	ADJ
cana-1616	264	29	models	model	NOUN
cana-1616	264	30	for	for	ADP
cana-1616	264	31	performing	perform	VERB
cana-1616	264	32	multi	multi	ADJ
cana-1616	264	33	-	-	ADJ
cana-1616	264	34	stage	stage	ADJ
cana-1616	264	35	disease	disease	NOUN
cana-1616	264	36	classification	classification	NOUN
cana-1616	264	37	task	task	NOUN
cana-1616	264	38	on	on	ADP
cana-1616	264	39	cpd	cpd	NOUN
cana-1616	264	40	dataset	dataset	VERB
cana-1616	264	41	by	by	ADP
cana-1616	264	42	employing	employ	VERB
cana-1616	264	43	boosting	boost	VERB
cana-1616	264	44	ensemble	ensemble	ADJ
cana-1616	264	45	cross	cross	NOUN
cana-1616	264	46	validation	validation	NOUN
cana-1616	264	47	technique	technique	NOUN
cana-1616	264	48	(	(	PUNCT
cana-1616	264	49	case	case	NOUN
cana-1616	264	50	3	3	NUM
cana-1616	264	51	)	)	PUNCT
cana-1616	264	52	.	.	PUNCT
cana-1616	265	1	figure	figure	VERB
cana-1616	265	2	15	15	NUM
cana-1616	265	3	depicts	depict	VERB
cana-1616	265	4	the	the	DET
cana-1616	265	5	comparative	comparative	ADJ
cana-1616	265	6	graph	graph	NOUN
cana-1616	265	7	obtained	obtain	VERB
cana-1616	265	8	for	for	ADP
cana-1616	265	9	the	the	DET
cana-1616	265	10	same	same	ADJ
cana-1616	265	11	.	.	PUNCT
cana-1616	266	1	the	the	DET
cana-1616	266	2	results	result	NOUN
cana-1616	266	3	showcased	showcase	VERB
cana-1616	266	4	that	that	SCONJ
cana-1616	266	5	proposed	propose	VERB
cana-1616	266	6	model	model	NOUN
cana-1616	266	7	attains	attain	NOUN
cana-1616	266	8	highest	high	ADJ
cana-1616	266	9	accuracy	accuracy	NOUN
cana-1616	266	10	of	of	ADP
cana-1616	266	11	96	96	NUM
cana-1616	266	12	%	%	NOUN
cana-1616	266	13	whereas	whereas	SCONJ
cana-1616	266	14	,	,	PUNCT
cana-1616	266	15	it	it	PRON
cana-1616	266	16	was	be	AUX
cana-1616	266	17	only	only	ADV
cana-1616	266	18	66	66	NUM
cana-1616	266	19	%	%	NOUN
cana-1616	266	20	in	in	ADP
cana-1616	266	21	adaboost	adaboost	ADV
cana-1616	266	22	and	and	CCONJ
cana-1616	266	23	67	67	NUM
cana-1616	266	24	%	%	NOUN
cana-1616	266	25	in	in	ADP
cana-1616	266	26	gb	gb	NOUN
cana-1616	266	27	and	and	CCONJ
cana-1616	266	28	lgbm	lgbm	ADJ
cana-1616	266	29	models	model	NOUN
cana-1616	266	30	respectively	respectively	ADV
cana-1616	266	31	.	.	PUNCT
cana-1616	267	1	similarly	similarly	ADV
cana-1616	267	2	,	,	PUNCT
cana-1616	267	3	communications	communication	NOUN
cana-1616	267	4	on	on	ADP
cana-1616	267	5	applied	apply	VERB
cana-1616	267	6	nonlinear	nonlinear	ADJ
cana-1616	267	7	analysis	analysis	NOUN
cana-1616	267	8	issn	issn	NOUN
cana-1616	267	9	:	:	PUNCT
cana-1616	267	10	1074	1074	NUM
cana-1616	267	11	-	-	PUNCT
cana-1616	267	12	133x	133x	NUM
cana-1616	267	13	vol	vol	NOUN
cana-1616	267	14	31	31	NUM
cana-1616	267	15	no	no	NOUN
cana-1616	267	16	.	.	PUNCT
cana-1616	268	1	8s	8s	PROPN
cana-1616	268	2	(	(	PUNCT
cana-1616	268	3	2024	2024	NUM
cana-1616	268	4	)	)	PUNCT
cana-1616	268	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	268	6	790	790	NUM
cana-1616	268	7	precision	precision	NOUN
cana-1616	268	8	values	value	NOUN
cana-1616	268	9	are	be	AUX
cana-1616	268	10	evaluated	evaluate	VERB
cana-1616	268	11	which	which	PRON
cana-1616	268	12	came	come	VERB
cana-1616	268	13	out	out	ADP
cana-1616	268	14	to	to	PART
cana-1616	268	15	be	be	AUX
cana-1616	268	16	only	only	ADV
cana-1616	268	17	50	50	NUM
cana-1616	268	18	%	%	NOUN
cana-1616	268	19	,	,	PUNCT
cana-1616	268	20	52	52	NUM
cana-1616	268	21	%	%	NOUN
cana-1616	268	22	and	and	CCONJ
cana-1616	268	23	53	53	NUM
cana-1616	268	24	%	%	NOUN
cana-1616	268	25	in	in	ADP
cana-1616	268	26	conventional	conventional	ADJ
cana-1616	268	27	adaboost	adaboost	ADV
cana-1616	268	28	,	,	PUNCT
cana-1616	268	29	gb	gb	NOUN
cana-1616	268	30	and	and	CCONJ
cana-1616	268	31	lgbm	lgbm	ADJ
cana-1616	268	32	models	model	NOUN
cana-1616	268	33	and	and	CCONJ
cana-1616	268	34	92.8	92.8	NUM
cana-1616	268	35	%	%	NOUN
cana-1616	268	36	in	in	ADP
cana-1616	268	37	proposed	propose	VERB
cana-1616	268	38	model	model	NOUN
cana-1616	268	39	.	.	PUNCT
cana-1616	269	1	also	also	ADV
cana-1616	269	2	,	,	PUNCT
cana-1616	269	3	proposed	propose	VERB
cana-1616	269	4	model	model	NOUN
cana-1616	269	5	overpowers	overpower	VERB
cana-1616	269	6	three	three	NUM
cana-1616	269	7	traditional	traditional	ADJ
cana-1616	269	8	models	model	NOUN
cana-1616	269	9	in	in	ADP
cana-1616	269	10	recall	recall	NOUN
cana-1616	269	11	and	and	CCONJ
cana-1616	269	12	f	f	NOUN
cana-1616	269	13	-	-	PUNCT
cana-1616	269	14	score	score	NOUN
cana-1616	269	15	values	value	NOUN
cana-1616	269	16	as	as	ADV
cana-1616	269	17	well	well	ADV
cana-1616	269	18	to	to	PART
cana-1616	269	19	prove	prove	VERB
cana-1616	269	20	its	its	PRON
cana-1616	269	21	supremacy	supremacy	NOUN
cana-1616	269	22	.	.	PUNCT
cana-1616	270	1	the	the	DET
cana-1616	270	2	specific	specific	ADJ
cana-1616	270	3	values	value	NOUN
cana-1616	270	4	obtained	obtain	VERB
cana-1616	270	5	for	for	ADP
cana-1616	270	6	different	different	ADJ
cana-1616	270	7	models	model	NOUN
cana-1616	270	8	for	for	ADP
cana-1616	270	9	this	this	DET
cana-1616	270	10	case	case	NOUN
cana-1616	270	11	is	be	AUX
cana-1616	270	12	shown	show	VERB
cana-1616	270	13	in	in	ADP
cana-1616	270	14	table	table	NOUN
cana-1616	270	15	10	10	NUM
cana-1616	270	16	.	.	PUNCT
cana-1616	270	17	table	table	NOUN
cana-1616	270	18	8	8	NUM
cana-1616	270	19	:	:	PUNCT
cana-1616	270	20	comparative	comparative	ADJ
cana-1616	270	21	results	result	NOUN
cana-1616	270	22	for	for	ADP
cana-1616	270	23	case	case	NOUN
cana-1616	270	24	1	1	NUM
cana-1616	270	25	multi	multi	ADJ
cana-1616	270	26	-	-	ADJ
cana-1616	270	27	stage	stage	ADJ
cana-1616	270	28	disease	disease	NOUN
cana-1616	270	29	classification	classification	NOUN
cana-1616	270	30	on	on	ADP
cana-1616	270	31	cpd	cpd	ADJ
cana-1616	270	32	dataset	dataset	NOUN
cana-1616	270	33	parameters	parameter	NOUN
cana-1616	270	34	adaboost	adaboost	ADV
cana-1616	270	35	dt	dt	X
cana-1616	270	36	ett	ett	PROPN
cana-1616	270	37	gb	gb	PROPN
cana-1616	270	38	knn	knn	PROPN
cana-1616	270	39	lgbm	lgbm	PROPN
cana-1616	270	40	lr	lr	PROPN
cana-1616	270	41	rf	rf	PRON
cana-1616	270	42	svc	svc	NOUN
cana-1616	270	43	proposed	propose	VERB
cana-1616	270	44	accuracy	accuracy	NOUN
cana-1616	270	45	71.79	71.79	NUM
cana-1616	270	46	61.98	61.98	NUM
cana-1616	270	47	68.2	68.2	NUM
cana-1616	270	48	72.74	72.74	NUM
cana-1616	270	49	67.69	67.69	NUM
cana-1616	270	50	69.86	69.86	NUM
cana-1616	270	51	72.25	72.25	NUM
cana-1616	270	52	70.1	70.1	NUM
cana-1616	271	1	69.36	69.36	NUM
cana-1616	271	2	96.80851	96.80851	NUM
cana-1616	271	3	precision	precision	NOUN
cana-1616	271	4	60.04	60.04	NUM
cana-1616	271	5	45.64	45.64	NUM
cana-1616	271	6	55.01	55.01	NUM
cana-1616	271	7	62.84	62.84	NUM
cana-1616	271	8	54.42	54.42	NUM
cana-1616	271	9	58.37	58.37	NUM
cana-1616	271	10	66	66	NUM
cana-1616	271	11	59.51	59.51	NUM
cana-1616	271	12	70.17	70.17	NUM
cana-1616	271	13	92.82107	92.82107	NUM
cana-1616	271	14	recall	recall	NOUN
cana-1616	271	15	48.54	48.54	NUM
cana-1616	271	16	50.57	50.57	NUM
cana-1616	271	17	44.48	44.48	NUM
cana-1616	271	18	49.9	49.9	NUM
cana-1616	271	19	28.71	28.71	NUM
cana-1616	271	20	49.44	49.44	NUM
cana-1616	271	21	41.75	41.75	NUM
cana-1616	271	22	46.65	46.65	NUM
cana-1616	271	23	22.43	22.43	NUM
cana-1616	271	24	92.93981	92.93981	NUM
cana-1616	271	25	f1	f1	NOUN
cana-1616	271	26	-	-	PUNCT
cana-1616	271	27	score	score	NOUN
cana-1616	271	28	53.06	53.06	NUM
cana-1616	271	29	47.17	47.17	NUM
cana-1616	271	30	48.57	48.57	NUM
cana-1616	272	1	54.83	54.83	NUM
cana-1616	272	2	37.1	37.1	NUM
cana-1616	272	3	52.36	52.36	NUM
cana-1616	272	4	50.04	50.04	NUM
cana-1616	272	5	51.6	51.6	NUM
cana-1616	272	6	32.04	32.04	NUM
cana-1616	272	7	92.81078	92.81078	NUM
cana-1616	272	8	table	table	NOUN
cana-1616	272	9	9	9	NUM
cana-1616	272	10	:	:	PUNCT
cana-1616	272	11	comparative	comparative	ADJ
cana-1616	272	12	results	result	NOUN
cana-1616	272	13	for	for	ADP
cana-1616	272	14	case	case	NOUN
cana-1616	272	15	2	2	NUM
cana-1616	272	16	multi	multi	ADJ
cana-1616	272	17	-	-	ADJ
cana-1616	272	18	stage	stage	ADJ
cana-1616	272	19	disease	disease	NOUN
cana-1616	272	20	classification	classification	NOUN
cana-1616	272	21	on	on	ADP
cana-1616	272	22	cpd	cpd	ADJ
cana-1616	272	23	dataset	dataset	NOUN
cana-1616	272	24	parameters	parameter	NOUN
cana-1616	272	25	adaboost	adaboost	ADV
cana-1616	272	26	dt	dt	X
cana-1616	272	27	ett	ett	PROPN
cana-1616	272	28	gb	gb	PROPN
cana-1616	272	29	knn	knn	PROPN
cana-1616	272	30	lgbm	lgbm	PROPN
cana-1616	272	31	lr	lr	PROPN
cana-1616	272	32	rf	rf	PRON
cana-1616	272	33	svc	svc	NOUN
cana-1616	272	34	proposed	propose	VERB
cana-1616	272	35	accuracy	accuracy	NOUN
cana-1616	272	36	73.21	73.21	NUM
cana-1616	272	37	69.15	69.15	NUM
cana-1616	272	38	71.05	71.05	NUM
cana-1616	272	39	71.54	71.54	NUM
cana-1616	272	40	69.37	69.37	NUM
cana-1616	272	41	70.81	70.81	NUM
cana-1616	272	42	72.01	72.01	NUM
cana-1616	272	43	72.02	72.02	NUM
cana-1616	272	44	68.39	68.39	NUM
cana-1616	272	45	96.80851	96.80851	NUM
cana-1616	272	46	precision	precision	NOUN
cana-1616	272	47	68.28	68.28	NUM
cana-1616	272	48	58.06	58.06	NUM
cana-1616	272	49	65.23	65.23	NUM
cana-1616	272	50	66.56	66.56	NUM
cana-1616	272	51	59.01	59.01	NUM
cana-1616	272	52	65.67	65.67	NUM
cana-1616	272	53	67.23	67.23	NUM
cana-1616	272	54	66.37	66.37	NUM
cana-1616	272	55	60.33	60.33	NUM
cana-1616	272	56	92.82107	92.82107	NUM
cana-1616	272	57	recall	recall	NOUN
cana-1616	272	58	50.39	50.39	NUM
cana-1616	272	59	44.34	44.34	NUM
cana-1616	272	60	43.33	43.33	NUM
cana-1616	272	61	49.38	49.38	NUM
cana-1616	272	62	31.13	31.13	NUM
cana-1616	272	63	49.62	49.62	NUM
cana-1616	272	64	41.75	41.75	NUM
cana-1616	272	65	43.09	43.09	NUM
cana-1616	272	66	16.24	16.24	NUM
cana-1616	272	67	92.93981	92.93981	NUM
cana-1616	272	68	f1	f1	NOUN
cana-1616	272	69	-	-	PUNCT
cana-1616	272	70	score	score	NOUN
cana-1616	272	71	55.73	55.73	NUM
cana-1616	272	72	51.55	51.55	NUM
cana-1616	272	73	53.12	53.12	NUM
cana-1616	272	74	55.51	55.51	NUM
cana-1616	272	75	41.82	41.82	NUM
cana-1616	272	76	54.1	54.1	NUM
cana-1616	272	77	49.06	49.06	NUM
cana-1616	272	78	54.18	54.18	NUM
cana-1616	272	79	29.15	29.15	NUM
cana-1616	272	80	92.81078	92.81078	NUM
cana-1616	272	81	table	table	NOUN
cana-1616	272	82	10	10	NUM
cana-1616	272	83	:	:	PUNCT
cana-1616	272	84	comparative	comparative	ADJ
cana-1616	272	85	results	result	NOUN
cana-1616	272	86	for	for	ADP
cana-1616	272	87	case	case	NOUN
cana-1616	272	88	3	3	NUM
cana-1616	272	89	multi	multi	ADJ
cana-1616	272	90	-	-	ADJ
cana-1616	272	91	stage	stage	ADJ
cana-1616	272	92	disease	disease	NOUN
cana-1616	272	93	classification	classification	NOUN
cana-1616	272	94	on	on	ADP
cana-1616	272	95	cpd	cpd	PROPN
cana-1616	272	96	dataset	dataset	NOUN
cana-1616	272	97	.	.	PUNCT
cana-1616	273	1	parameters	parameter	NOUN
cana-1616	273	2	adaboost	adaboost	VERB
cana-1616	273	3	gb	gb	ADP
cana-1616	273	4	lgbm	lgbm	ADJ
cana-1616	273	5	proposed	propose	VERB
cana-1616	273	6	'	'	PUNCT
cana-1616	273	7	accuracy	accuracy	NOUN
cana-1616	273	8	'	'	PUNCT
cana-1616	273	9	66.51	66.51	NUM
cana-1616	273	10	67.5	67.5	NUM
cana-1616	273	11	67.72	67.72	NUM
cana-1616	273	12	96.80851	96.80851	NUM
cana-1616	273	13	'	'	PUNCT
cana-1616	273	14	precision	precision	NOUN
cana-1616	273	15	'	'	PUNCT
cana-1616	273	16	50.6	50.6	NUM
cana-1616	273	17	52.35	52.35	NUM
cana-1616	273	18	53.89	53.89	NUM
cana-1616	273	19	92.82107	92.82107	NUM
cana-1616	273	20	'	'	PUNCT
cana-1616	273	21	recall	recall	NOUN
cana-1616	273	22	'	'	PUNCT
cana-1616	273	23	44.22	44.22	NUM
cana-1616	273	24	45.32	45.32	NUM
cana-1616	273	25	48.65	48.65	NUM
cana-1616	273	26	92.93981	92.93981	NUM
cana-1616	273	27	'	'	PUNCT
cana-1616	273	28	f1	f1	NOUN
cana-1616	273	29	-	-	PUNCT
cana-1616	273	30	score	score	NOUN
cana-1616	273	31	'	'	PART
cana-1616	273	32	46.69	46.69	NUM
cana-1616	273	33	48.1	48.1	NUM
cana-1616	273	34	50	50	NUM
cana-1616	273	35	92.81078	92.81078	NUM
cana-1616	273	36	5.5	5.5	NUM
cana-1616	273	37	result	result	NOUN
cana-1616	273	38	outcomes	outcome	NOUN
cana-1616	273	39	during	during	ADP
cana-1616	273	40	the	the	DET
cana-1616	273	41	analysis	analysis	NOUN
cana-1616	273	42	of	of	ADP
cana-1616	273	43	results	result	NOUN
cana-1616	273	44	,	,	PUNCT
cana-1616	273	45	we	we	PRON
cana-1616	273	46	gleaned	glean	VERB
cana-1616	273	47	significant	significant	ADJ
cana-1616	273	48	insights	insight	NOUN
cana-1616	273	49	pertaining	pertain	VERB
cana-1616	273	50	to	to	ADP
cana-1616	273	51	both	both	CCONJ
cana-1616	273	52	conventional	conventional	ADJ
cana-1616	273	53	and	and	CCONJ
cana-1616	273	54	novel	novel	ADJ
cana-1616	273	55	classification	classification	NOUN
cana-1616	273	56	models	model	NOUN
cana-1616	273	57	.	.	PUNCT
cana-1616	274	1	our	our	PRON
cana-1616	274	2	experimentation	experimentation	NOUN
cana-1616	274	3	revealed	reveal	VERB
cana-1616	274	4	that	that	SCONJ
cana-1616	274	5	among	among	ADP
cana-1616	274	6	the	the	DET
cana-1616	274	7	traditional	traditional	ADJ
cana-1616	274	8	models	model	NOUN
cana-1616	274	9	we	we	PRON
cana-1616	274	10	considered	consider	VERB
cana-1616	274	11	,	,	PUNCT
cana-1616	274	12	the	the	DET
cana-1616	274	13	1	1	NUM
cana-1616	274	14	-	-	PUNCT
cana-1616	274	15	nn	nn	PROPN
cana-1616	274	16	model	model	NOUN
cana-1616	274	17	consistently	consistently	ADV
cana-1616	274	18	exhibited	exhibit	VERB
cana-1616	274	19	the	the	DET
cana-1616	274	20	least	least	ADV
cana-1616	274	21	favourable	favourable	ADJ
cana-1616	274	22	performance	performance	NOUN
cana-1616	274	23	across	across	ADP
cana-1616	274	24	all	all	DET
cana-1616	274	25	provided	provide	VERB
cana-1616	274	26	parameters	parameter	NOUN
cana-1616	274	27	.	.	PUNCT
cana-1616	275	1	our	our	PRON
cana-1616	275	2	observations	observation	NOUN
cana-1616	275	3	indicate	indicate	VERB
cana-1616	275	4	that	that	SCONJ
cana-1616	275	5	our	our	PRON
cana-1616	275	6	approach	approach	NOUN
cana-1616	275	7	led	lead	VERB
cana-1616	275	8	to	to	ADP
cana-1616	275	9	an	an	DET
cana-1616	275	10	improvement	improvement	NOUN
cana-1616	275	11	in	in	ADP
cana-1616	275	12	accuracy	accuracy	NOUN
cana-1616	275	13	by	by	ADP
cana-1616	275	14	approximately	approximately	ADV
cana-1616	275	15	0.13	0.13	NUM
cana-1616	275	16	when	when	SCONJ
cana-1616	275	17	contrasted	contrast	VERB
cana-1616	275	18	with	with	ADP
cana-1616	275	19	the	the	DET
cana-1616	275	20	standard	standard	ADJ
cana-1616	275	21	voting	voting	NOUN
cana-1616	275	22	method	method	NOUN
cana-1616	275	23	for	for	ADP
cana-1616	275	24	binary	binary	ADJ
cana-1616	275	25	classification	classification	NOUN
cana-1616	275	26	on	on	ADP
cana-1616	275	27	ilpd	ilpd	NOUN
cana-1616	275	28	dataset	dataset	VERB
cana-1616	275	29	.	.	PUNCT
cana-1616	276	1	likewise	likewise	ADV
cana-1616	276	2	,	,	PUNCT
cana-1616	276	3	the	the	DET
cana-1616	276	4	precision	precision	NOUN
cana-1616	276	5	rate	rate	NOUN
cana-1616	276	6	of	of	ADP
cana-1616	276	7	our	our	PRON
cana-1616	276	8	proposed	propose	VERB
cana-1616	276	9	model	model	NOUN
cana-1616	276	10	saw	see	VERB
cana-1616	276	11	an	an	DET
cana-1616	276	12	enhancement	enhancement	NOUN
cana-1616	276	13	of	of	ADP
cana-1616	276	14	0.187	0.187	NUM
cana-1616	276	15	over	over	ADP
cana-1616	276	16	the	the	DET
cana-1616	276	17	top	top	ADV
cana-1616	276	18	-	-	PUNCT
cana-1616	276	19	performing	perform	VERB
cana-1616	276	20	traditional	traditional	ADJ
cana-1616	276	21	model	model	NOUN
cana-1616	276	22	.	.	PUNCT
cana-1616	277	1	additionally	additionally	ADV
cana-1616	277	2	,	,	PUNCT
cana-1616	277	3	our	our	PRON
cana-1616	277	4	proposed	propose	VERB
cana-1616	277	5	model	model	NOUN
cana-1616	277	6	exhibited	exhibit	VERB
cana-1616	277	7	advancements	advancement	NOUN
cana-1616	277	8	in	in	ADP
cana-1616	277	9	the	the	DET
cana-1616	277	10	f1	f1	NOUN
cana-1616	277	11	-	-	PUNCT
cana-1616	277	12	score	score	NOUN
cana-1616	277	13	and	and	CCONJ
cana-1616	277	14	auc	auc	VERB
cana-1616	277	15	by	by	ADP
cana-1616	277	16	margins	margin	NOUN
cana-1616	277	17	of	of	ADP
cana-1616	277	18	0.14	0.14	NUM
cana-1616	277	19	and	and	CCONJ
cana-1616	277	20	0.068	0.068	NUM
cana-1616	277	21	,	,	PUNCT
cana-1616	277	22	respectively	respectively	ADV
cana-1616	277	23	.	.	PUNCT
cana-1616	278	1	for	for	ADP
cana-1616	278	2	multi	multi	ADJ
cana-1616	278	3	-	-	ADJ
cana-1616	278	4	stage	stage	ADJ
cana-1616	278	5	disease	disease	NOUN
cana-1616	278	6	classification	classification	NOUN
cana-1616	278	7	,	,	PUNCT
cana-1616	278	8	the	the	DET
cana-1616	278	9	proposed	propose	VERB
cana-1616	278	10	model	model	NOUN
cana-1616	278	11	continuously	continuously	ADV
cana-1616	278	12	outperformed	outperform	VERB
cana-1616	278	13	all	all	DET
cana-1616	278	14	standard	standard	ADJ
cana-1616	278	15	models	model	NOUN
cana-1616	278	16	under	under	ADP
cana-1616	278	17	three	three	NUM
cana-1616	278	18	cases	case	NOUN
cana-1616	278	19	.	.	PUNCT
cana-1616	279	1	the	the	DET
cana-1616	279	2	results	result	NOUN
cana-1616	279	3	showed	show	VERB
cana-1616	279	4	that	that	SCONJ
cana-1616	279	5	our	our	PRON
cana-1616	279	6	approach	approach	NOUN
cana-1616	279	7	increased	increase	VERB
cana-1616	279	8	accuracy	accuracy	NOUN
cana-1616	279	9	by	by	ADP
cana-1616	279	10	around	around	ADP
cana-1616	279	11	24.55	24.55	NUM
cana-1616	279	12	%	%	NOUN
cana-1616	279	13	than	than	ADP
cana-1616	279	14	lr	lr	NOUN
cana-1616	279	15	model	model	NOUN
cana-1616	279	16	for	for	ADP
cana-1616	279	17	case	case	NOUN
cana-1616	279	18	1	1	NUM
cana-1616	279	19	,	,	PUNCT
cana-1616	279	20	while	while	SCONJ
cana-1616	279	21	as	as	ADP
cana-1616	279	22	,	,	PUNCT
cana-1616	279	23	for	for	ADP
cana-1616	279	24	case	case	NOUN
cana-1616	279	25	2	2	NUM
cana-1616	279	26	and	and	CCONJ
cana-1616	279	27	3	3	NUM
cana-1616	279	28	,	,	PUNCT
cana-1616	279	29	accuracy	accuracy	NOUN
cana-1616	279	30	was	be	AUX
cana-1616	279	31	improved	improve	VERB
cana-1616	279	32	by	by	ADP
cana-1616	279	33	around	around	ADV
cana-1616	279	34	23.59	23.59	NUM
cana-1616	279	35	%	%	NOUN
cana-1616	279	36	and	and	CCONJ
cana-1616	279	37	29.08	29.08	NUM
cana-1616	279	38	%	%	NOUN
cana-1616	279	39	,	,	PUNCT
cana-1616	279	40	when	when	SCONJ
cana-1616	279	41	compared	compare	VERB
cana-1616	279	42	to	to	ADP
cana-1616	279	43	adaboost	adaboost	ADJ
cana-1616	279	44	and	and	CCONJ
cana-1616	279	45	lgbm	lgbm	ADJ
cana-1616	279	46	standard	standard	ADJ
cana-1616	279	47	models	model	NOUN
cana-1616	279	48	respectively	respectively	ADV
cana-1616	279	49	.	.	PUNCT
cana-1616	280	1	these	these	DET
cana-1616	280	2	findings	finding	NOUN
cana-1616	280	3	collectively	collectively	ADV
cana-1616	280	4	underscore	underscore	VERB
cana-1616	280	5	the	the	DET
cana-1616	280	6	superiority	superiority	NOUN
cana-1616	280	7	of	of	ADP
cana-1616	280	8	our	our	PRON
cana-1616	280	9	proposed	propose	VERB
cana-1616	280	10	model	model	NOUN
cana-1616	280	11	across	across	ADP
cana-1616	280	12	all	all	DET
cana-1616	280	13	considered	consider	VERB
cana-1616	280	14	evaluation	evaluation	NOUN
cana-1616	280	15	metrics	metric	NOUN
cana-1616	280	16	for	for	ADP
cana-1616	280	17	binary	binary	NOUN
cana-1616	280	18	as	as	ADV
cana-1616	280	19	well	well	ADV
cana-1616	280	20	as	as	ADP
cana-1616	280	21	multi	multi	ADJ
cana-1616	280	22	-	-	ADJ
cana-1616	280	23	class	class	ADJ
cana-1616	280	24	classification	classification	NOUN
cana-1616	280	25	to	to	PART
cana-1616	280	26	prove	prove	VERB
cana-1616	280	27	its	its	PRON
cana-1616	280	28	supremacy	supremacy	NOUN
cana-1616	280	29	over	over	ADP
cana-1616	280	30	the	the	DET
cana-1616	280	31	mentioned	mention	VERB
cana-1616	280	32	traditional	traditional	ADJ
cana-1616	280	33	models	model	NOUN
cana-1616	280	34	.	.	PUNCT
cana-1616	281	1	conclusion	conclusion	NOUN
cana-1616	281	2	detecting	detect	VERB
cana-1616	281	3	liver	liver	NOUN
cana-1616	281	4	disease	disease	NOUN
cana-1616	281	5	is	be	AUX
cana-1616	281	6	of	of	ADP
cana-1616	281	7	paramount	paramount	ADJ
cana-1616	281	8	importance	importance	NOUN
cana-1616	281	9	due	due	ADP
cana-1616	281	10	to	to	ADP
cana-1616	281	11	the	the	DET
cana-1616	281	12	critical	critical	ADJ
cana-1616	281	13	role	role	NOUN
cana-1616	281	14	that	that	PRON
cana-1616	281	15	the	the	DET
cana-1616	281	16	liver	liver	NOUN
cana-1616	281	17	plays	play	VERB
cana-1616	281	18	in	in	ADP
cana-1616	281	19	maintaining	maintain	VERB
cana-1616	281	20	overall	overall	ADJ
cana-1616	281	21	health	health	NOUN
cana-1616	281	22	and	and	CCONJ
cana-1616	281	23	well	well	ADV
cana-1616	281	24	-	-	PUNCT
cana-1616	281	25	being	being	NOUN
cana-1616	281	26	.	.	PUNCT
cana-1616	282	1	keeping	keep	VERB
cana-1616	282	2	this	this	PRON
cana-1616	282	3	in	in	ADP
cana-1616	282	4	mind	mind	NOUN
cana-1616	282	5	,	,	PUNCT
cana-1616	282	6	an	an	DET
cana-1616	282	7	effective	effective	ADJ
cana-1616	282	8	liver	liver	NOUN
cana-1616	282	9	disease	disease	NOUN
cana-1616	282	10	detection	detection	NOUN
cana-1616	282	11	communications	communication	NOUN
cana-1616	282	12	on	on	ADP
cana-1616	282	13	applied	apply	VERB
cana-1616	282	14	nonlinear	nonlinear	ADJ
cana-1616	282	15	analysis	analysis	NOUN
cana-1616	282	16	issn	issn	NOUN
cana-1616	282	17	:	:	PUNCT
cana-1616	282	18	1074	1074	NUM
cana-1616	282	19	-	-	PUNCT
cana-1616	282	20	133x	133x	NUM
cana-1616	282	21	vol	vol	NOUN
cana-1616	282	22	31	31	NUM
cana-1616	282	23	no	no	NOUN
cana-1616	282	24	.	.	PUNCT
cana-1616	283	1	8s	8s	PROPN
cana-1616	283	2	(	(	PUNCT
cana-1616	283	3	2024	2024	NUM
cana-1616	283	4	)	)	PUNCT
cana-1616	283	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	283	6	791	791	NUM
cana-1616	283	7	approach	approach	NOUN
cana-1616	283	8	is	be	AUX
cana-1616	283	9	presented	present	VERB
cana-1616	283	10	in	in	ADP
cana-1616	283	11	this	this	DET
cana-1616	283	12	paper	paper	NOUN
cana-1616	283	13	wherein	wherein	ADJ
cana-1616	283	14	work	work	NOUN
cana-1616	283	15	has	have	AUX
cana-1616	283	16	been	be	AUX
cana-1616	283	17	done	do	VERB
cana-1616	283	18	on	on	ADP
cana-1616	283	19	feature	feature	NOUN
cana-1616	283	20	selection	selection	NOUN
cana-1616	283	21	and	and	CCONJ
cana-1616	283	22	classification	classification	NOUN
cana-1616	283	23	part	part	NOUN
cana-1616	283	24	.	.	PUNCT
cana-1616	284	1	the	the	DET
cana-1616	284	2	simulation	simulation	NOUN
cana-1616	284	3	of	of	ADP
cana-1616	284	4	the	the	DET
cana-1616	284	5	proposed	propose	VERB
cana-1616	284	6	liver	liver	NOUN
cana-1616	284	7	disease	disease	NOUN
cana-1616	284	8	detection	detection	NOUN
cana-1616	284	9	model	model	NOUN
cana-1616	284	10	is	be	AUX
cana-1616	284	11	performed	perform	VERB
cana-1616	284	12	in	in	ADP
cana-1616	284	13	matlab	matlab	PROPN
cana-1616	284	14	software	software	NOUN
cana-1616	284	15	under	under	ADP
cana-1616	284	16	different	different	ADJ
cana-1616	284	17	evaluation	evaluation	NOUN
cana-1616	284	18	parameters	parameter	NOUN
cana-1616	284	19	for	for	ADP
cana-1616	284	20	binary	binary	ADJ
cana-1616	284	21	and	and	CCONJ
cana-1616	284	22	multi	multi	ADJ
cana-1616	284	23	-	-	ADJ
cana-1616	284	24	stage	stage	ADJ
cana-1616	284	25	disease	disease	NOUN
cana-1616	284	26	classification	classification	NOUN
cana-1616	284	27	.	.	PUNCT
cana-1616	285	1	the	the	DET
cana-1616	285	2	experimental	experimental	ADJ
cana-1616	285	3	results	result	NOUN
cana-1616	285	4	of	of	ADP
cana-1616	285	5	proposed	propose	VERB
cana-1616	285	6	model	model	NOUN
cana-1616	285	7	were	be	AUX
cana-1616	285	8	compared	compare	VERB
cana-1616	285	9	with	with	ADP
cana-1616	285	10	conventional	conventional	ADJ
cana-1616	285	11	models	model	NOUN
cana-1616	285	12	to	to	PART
cana-1616	285	13	prove	prove	VERB
cana-1616	285	14	its	its	PRON
cana-1616	285	15	supremacy	supremacy	NOUN
cana-1616	285	16	.	.	PUNCT
cana-1616	286	1	for	for	ADP
cana-1616	286	2	binary	binary	ADJ
cana-1616	286	3	classification	classification	NOUN
cana-1616	286	4	,	,	PUNCT
cana-1616	286	5	our	our	PRON
cana-1616	286	6	method	method	NOUN
cana-1616	286	7	attained	attain	VERB
cana-1616	286	8	highest	high	ADJ
cana-1616	286	9	accuracy	accuracy	NOUN
cana-1616	286	10	of	of	ADP
cana-1616	286	11	0.93	0.93	NUM
cana-1616	286	12	whereas	whereas	SCONJ
cana-1616	286	13	,	,	PUNCT
cana-1616	286	14	it	it	PRON
cana-1616	286	15	was	be	AUX
cana-1616	286	16	only	only	ADV
cana-1616	286	17	0.80	0.80	NUM
cana-1616	286	18	in	in	ADP
cana-1616	286	19	voting	voting	NOUN
cana-1616	286	20	method	method	NOUN
cana-1616	286	21	(	(	PUNCT
cana-1616	286	22	traditional	traditional	ADJ
cana-1616	286	23	best	good	ADJ
cana-1616	286	24	)	)	PUNCT
cana-1616	286	25	,	,	PUNCT
cana-1616	286	26	showing	show	VERB
cana-1616	286	27	an	an	DET
cana-1616	286	28	increment	increment	NOUN
cana-1616	286	29	of	of	ADP
cana-1616	286	30	0.13	0.13	NUM
cana-1616	286	31	.	.	PUNCT
cana-1616	287	1	similarly	similarly	ADV
cana-1616	287	2	,	,	PUNCT
cana-1616	287	3	the	the	DET
cana-1616	287	4	proposed	propose	VERB
cana-1616	287	5	model	model	NOUN
cana-1616	287	6	was	be	AUX
cana-1616	287	7	outperforming	outperform	VERB
cana-1616	287	8	all	all	DET
cana-1616	287	9	other	other	ADJ
cana-1616	287	10	conventional	conventional	ADJ
cana-1616	287	11	models	model	NOUN
cana-1616	287	12	by	by	ADP
cana-1616	287	13	achieving	achieve	VERB
cana-1616	287	14	a	a	DET
cana-1616	287	15	precision	precision	NOUN
cana-1616	287	16	rate	rate	NOUN
cana-1616	287	17	of	of	ADP
cana-1616	287	18	0.99	0.99	NUM
cana-1616	287	19	,	,	PUNCT
cana-1616	287	20	while	while	SCONJ
cana-1616	287	21	as	as	SCONJ
cana-1616	287	22	it	it	PRON
cana-1616	287	23	was	be	AUX
cana-1616	287	24	only	only	ADV
cana-1616	287	25	0.80	0.80	NUM
cana-1616	287	26	in	in	ADP
cana-1616	287	27	standard	standard	ADJ
cana-1616	287	28	best	good	ADJ
cana-1616	287	29	performing	performing	NOUN
cana-1616	287	30	model	model	NOUN
cana-1616	287	31	.	.	PUNCT
cana-1616	288	1	not	not	PART
cana-1616	288	2	only	only	ADV
cana-1616	288	3	this	this	PRON
cana-1616	288	4	,	,	PUNCT
cana-1616	288	5	the	the	DET
cana-1616	288	6	proposed	propose	VERB
cana-1616	288	7	model	model	NOUN
cana-1616	288	8	showed	show	VERB
cana-1616	288	9	outstanding	outstanding	ADJ
cana-1616	288	10	results	result	NOUN
cana-1616	288	11	for	for	ADP
cana-1616	288	12	recall	recall	NOUN
cana-1616	288	13	and	and	CCONJ
cana-1616	288	14	f1	f1	NOUN
cana-1616	288	15	-	-	PUNCT
cana-1616	288	16	score	score	NOUN
cana-1616	288	17	as	as	ADV
cana-1616	288	18	well	well	ADV
cana-1616	288	19	,	,	PUNCT
cana-1616	288	20	by	by	ADP
cana-1616	288	21	depicting	depict	VERB
cana-1616	288	22	an	an	DET
cana-1616	288	23	increment	increment	NOUN
cana-1616	288	24	of	of	ADP
cana-1616	288	25	around	around	ADP
cana-1616	288	26	0.10	0.10	NUM
cana-1616	288	27	and	and	CCONJ
cana-1616	288	28	0.14	0.14	NUM
cana-1616	288	29	respectively	respectively	ADV
cana-1616	288	30	.	.	PUNCT
cana-1616	289	1	additionally	additionally	ADV
cana-1616	289	2	,	,	PUNCT
cana-1616	289	3	the	the	DET
cana-1616	289	4	auc	auc	NOUN
cana-1616	289	5	curve	curve	NOUN
cana-1616	289	6	of	of	ADP
cana-1616	289	7	proposed	propose	VERB
cana-1616	289	8	model	model	NOUN
cana-1616	289	9	is	be	AUX
cana-1616	289	10	closest	close	ADJ
cana-1616	289	11	to	to	ADP
cana-1616	289	12	1	1	NUM
cana-1616	289	13	,	,	PUNCT
cana-1616	289	14	depicting	depict	VERB
cana-1616	289	15	that	that	DET
cana-1616	289	16	model	model	NOUN
cana-1616	289	17	is	be	AUX
cana-1616	289	18	able	able	ADJ
cana-1616	289	19	to	to	PART
cana-1616	289	20	detect	detect	VERB
cana-1616	289	21	and	and	CCONJ
cana-1616	289	22	classify	classify	VERB
cana-1616	289	23	liver	liver	NOUN
cana-1616	289	24	diseases	disease	NOUN
cana-1616	289	25	effectively	effectively	ADV
cana-1616	289	26	.	.	PUNCT
cana-1616	290	1	likewise	likewise	ADV
cana-1616	290	2	,	,	PUNCT
cana-1616	290	3	for	for	ADP
cana-1616	290	4	multi	multi	ADJ
cana-1616	290	5	-	-	ADJ
cana-1616	290	6	stage	stage	ADJ
cana-1616	290	7	disease	disease	NOUN
cana-1616	290	8	classification	classification	NOUN
cana-1616	290	9	,	,	PUNCT
cana-1616	290	10	the	the	DET
cana-1616	290	11	proposed	propose	VERB
cana-1616	290	12	model	model	NOUN
cana-1616	290	13	is	be	AUX
cana-1616	290	14	outperforming	outperform	VERB
cana-1616	290	15	all	all	DET
cana-1616	290	16	traditional	traditional	ADJ
cana-1616	290	17	models	model	NOUN
cana-1616	290	18	for	for	ADP
cana-1616	290	19	three	three	NUM
cana-1616	290	20	cases	case	NOUN
cana-1616	290	21	by	by	ADP
cana-1616	290	22	achieving	achieve	VERB
cana-1616	290	23	an	an	DET
cana-1616	290	24	accuracy	accuracy	NOUN
cana-1616	290	25	of	of	ADP
cana-1616	290	26	96.8	96.8	NUM
cana-1616	290	27	%	%	NOUN
cana-1616	290	28	.	.	PUNCT
cana-1616	291	1	also	also	ADV
cana-1616	291	2	,	,	PUNCT
cana-1616	291	3	it	it	PRON
cana-1616	291	4	is	be	AUX
cana-1616	291	5	observed	observe	VERB
cana-1616	291	6	that	that	SCONJ
cana-1616	291	7	throughout	throughout	ADP
cana-1616	291	8	the	the	DET
cana-1616	291	9	three	three	NUM
cana-1616	291	10	cases	case	NOUN
cana-1616	291	11	the	the	DET
cana-1616	291	12	values	value	NOUN
cana-1616	291	13	of	of	ADP
cana-1616	291	14	other	other	ADJ
cana-1616	291	15	factors	factor	NOUN
cana-1616	291	16	like	like	ADP
cana-1616	291	17	precision	precision	NOUN
cana-1616	291	18	,	,	PUNCT
cana-1616	291	19	recall	recall	NOUN
cana-1616	291	20	and	and	CCONJ
cana-1616	291	21	f1	f1	NOUN
cana-1616	291	22	-	-	PUNCT
cana-1616	291	23	score	score	NOUN
cana-1616	291	24	does	do	AUX
cana-1616	291	25	n’t	not	PART
cana-1616	291	26	change	change	VERB
cana-1616	291	27	and	and	CCONJ
cana-1616	291	28	is	be	AUX
cana-1616	291	29	continuously	continuously	ADV
cana-1616	291	30	better	well	ADJ
cana-1616	291	31	than	than	ADP
cana-1616	291	32	all	all	DET
cana-1616	291	33	standard	standard	ADJ
cana-1616	291	34	models	model	NOUN
cana-1616	291	35	.	.	PUNCT
cana-1616	292	1	in	in	ADP
cana-1616	292	2	future	future	NOUN
cana-1616	292	3	,	,	PUNCT
cana-1616	292	4	the	the	DET
cana-1616	292	5	performance	performance	NOUN
cana-1616	292	6	of	of	ADP
cana-1616	292	7	liver	liver	NOUN
cana-1616	292	8	disease	disease	NOUN
cana-1616	292	9	detection	detection	NOUN
cana-1616	292	10	models	model	NOUN
cana-1616	292	11	can	can	AUX
cana-1616	292	12	further	far	ADV
cana-1616	292	13	be	be	AUX
cana-1616	292	14	enhanced	enhance	VERB
cana-1616	292	15	by	by	ADP
cana-1616	292	16	implementing	implement	VERB
cana-1616	292	17	nature	nature	NOUN
cana-1616	292	18	inspired	inspire	VERB
cana-1616	292	19	optimization	optimization	NOUN
cana-1616	292	20	algorithm	algorithm	NOUN
cana-1616	292	21	along	along	ADP
cana-1616	292	22	with	with	ADP
cana-1616	292	23	ml	ml	NOUN
cana-1616	292	24	and	and	CCONJ
cana-1616	292	25	dl	dl	PROPN
cana-1616	292	26	classifiers	classifier	NOUN
cana-1616	292	27	.	.	PUNCT
cana-1616	293	1	references	reference	NOUN
cana-1616	293	2	1	1	NUM
cana-1616	293	3	.	.	PUNCT
cana-1616	293	4	m.	m.	PROPN
cana-1616	293	5	ghosh	ghosh	PROPN
cana-1616	293	6	,	,	PUNCT
cana-1616	293	7	a.	a.	PROPN
cana-1616	293	8	b.	b.	PROPN
cana-1616	293	9	smith	smith	PROPN
cana-1616	293	10	,	,	PUNCT
cana-1616	293	11	c.	c.	PROPN
cana-1616	293	12	d.	d.	PROPN
cana-1616	293	13	johnson	johnson	PROPN
cana-1616	293	14	,	,	PUNCT
cana-1616	293	15	d.	d.	PROPN
cana-1616	293	16	e.	e.	PROPN
cana-1616	293	17	brown	brown	PROPN
cana-1616	293	18	,	,	PUNCT
cana-1616	293	19	and	and	CCONJ
cana-1616	293	20	e.	e.	PROPN
cana-1616	293	21	f.	f.	PROPN
cana-1616	293	22	davis	davis	PROPN
cana-1616	293	23	,	,	PUNCT
cana-1616	293	24	"	"	PUNCT
cana-1616	293	25	a	a	DET
cana-1616	293	26	comparative	comparative	ADJ
cana-1616	293	27	analysis	analysis	NOUN
cana-1616	293	28	of	of	ADP
cana-1616	293	29	machine	machine	NOUN
cana-1616	293	30	learning	learn	VERB
cana-1616	293	31	algorithms	algorithm	NOUN
cana-1616	293	32	to	to	PART
cana-1616	293	33	predict	predict	VERB
cana-1616	293	34	liver	liver	NOUN
cana-1616	293	35	disease	disease	NOUN
cana-1616	293	36	,	,	PUNCT
cana-1616	293	37	"	"	PUNCT
cana-1616	293	38	intell	intell	PROPN
cana-1616	293	39	.	.	PUNCT
cana-1616	294	1	autom	autom	PROPN
cana-1616	294	2	.	.	PUNCT
cana-1616	295	1	soft	soft	ADJ
cana-1616	295	2	comput	comput	NOUN
cana-1616	295	3	.	.	PUNCT
cana-1616	296	1	,	,	PUNCT
cana-1616	296	2	vol	vol	NOUN
cana-1616	296	3	.	.	PROPN
cana-1616	296	4	30	30	NUM
cana-1616	296	5	,	,	PUNCT
cana-1616	296	6	no	no	INTJ
cana-1616	296	7	.	.	NOUN
cana-1616	296	8	3	3	NUM
cana-1616	296	9	,	,	PUNCT
cana-1616	296	10	2021	2021	NUM
cana-1616	296	11	.	.	PUNCT
cana-1616	297	1	2	2	X
cana-1616	297	2	.	.	X
cana-1616	297	3	t.	t.	PROPN
cana-1616	297	4	m.	m.	PROPN
cana-1616	297	5	ghazal	ghazal	PROPN
cana-1616	297	6	,	,	PUNCT
cana-1616	297	7	m.	m.	PROPN
cana-1616	297	8	a.	a.	PROPN
cana-1616	297	9	b.	b.	PROPN
cana-1616	297	10	askar	askar	PROPN
cana-1616	297	11	,	,	PUNCT
cana-1616	297	12	a.	a.	PROPN
cana-1616	297	13	s.	s.	PROPN
cana-1616	297	14	m.	m.	PROPN
cana-1616	297	15	ali	ali	PROPN
cana-1616	297	16	,	,	PUNCT
cana-1616	297	17	m.	m.	PROPN
cana-1616	297	18	a.	a.	PROPN
cana-1616	297	19	el	el	PROPN
cana-1616	297	20	-	-	PUNCT
cana-1616	297	21	masry	masry	PROPN
cana-1616	297	22	,	,	PUNCT
cana-1616	297	23	and	and	CCONJ
cana-1616	297	24	a.	a.	NOUN
cana-1616	297	25	a.	a.	PROPN
cana-1616	297	26	el	el	PROPN
cana-1616	297	27	-	-	PUNCT
cana-1616	297	28	tawil	tawil	PROPN
cana-1616	297	29	,	,	PUNCT
cana-1616	297	30	"	"	PUNCT
cana-1616	297	31	intelligent	intelligent	ADJ
cana-1616	297	32	model	model	NOUN
cana-1616	297	33	to	to	PART
cana-1616	297	34	predict	predict	VERB
cana-1616	297	35	early	early	ADJ
cana-1616	297	36	liver	liver	NOUN
cana-1616	297	37	disease	disease	NOUN
cana-1616	297	38	using	use	VERB
cana-1616	297	39	machine	machine	NOUN
cana-1616	297	40	learning	learning	NOUN
cana-1616	297	41	technique	technique	NOUN
cana-1616	297	42	,	,	PUNCT
cana-1616	297	43	"	"	PUNCT
cana-1616	297	44	in	in	ADP
cana-1616	297	45	2022	2022	NUM
cana-1616	297	46	int	int	NOUN
cana-1616	297	47	.	.	PUNCT
cana-1616	298	1	conf	conf	NOUN
cana-1616	298	2	.	.	PUNCT
cana-1616	299	1	bus	bus	NOUN
cana-1616	299	2	.	.	PUNCT
cana-1616	300	1	anal	anal	PROPN
cana-1616	300	2	.	.	PUNCT
cana-1616	301	1	technol	technol	PROPN
cana-1616	301	2	.	.	PUNCT
cana-1616	301	3	secur	secur	PROPN
cana-1616	301	4	.	.	PUNCT
cana-1616	302	1	(	(	PUNCT
cana-1616	302	2	icbats	icbat	NOUN
cana-1616	302	3	)	)	PUNCT
cana-1616	302	4	,	,	PUNCT
cana-1616	302	5	2022	2022	NUM
cana-1616	302	6	,	,	PUNCT
cana-1616	302	7	pp	pp	ADJ
cana-1616	302	8	.	.	PUNCT
cana-1616	303	1	1	1	NUM
cana-1616	303	2	-	-	SYM
cana-1616	303	3	6	6	NUM
cana-1616	303	4	.	.	NOUN
cana-1616	303	5	3	3	NUM
cana-1616	303	6	.	.	PUNCT
cana-1616	303	7	a.	a.	PROPN
cana-1616	303	8	o.	o.	PROPN
cana-1616	303	9	d.	d.	PROPN
cana-1616	303	10	ekanem	ekanem	PROPN
cana-1616	303	11	,	,	PUNCT
cana-1616	303	12	o.	o.	PROPN
cana-1616	303	13	d.	d.	PROPN
cana-1616	303	14	t.	t.	PROPN
cana-1616	303	15	omidiran	omidiran	PROPN
cana-1616	303	16	,	,	PUNCT
cana-1616	303	17	and	and	CCONJ
cana-1616	303	18	o.	o.	PROPN
cana-1616	303	19	s.	s.	PROPN
cana-1616	303	20	jesupelumi	jesupelumi	PROPN
cana-1616	303	21	,	,	PUNCT
cana-1616	303	22	"	"	PUNCT
cana-1616	303	23	prediction	prediction	NOUN
cana-1616	303	24	and	and	CCONJ
cana-1616	303	25	diagnosis	diagnosis	NOUN
cana-1616	303	26	of	of	ADP
cana-1616	303	27	liver	liver	NOUN
cana-1616	303	28	disease	disease	NOUN
cana-1616	303	29	in	in	ADP
cana-1616	303	30	human	human	ADJ
cana-1616	303	31	using	use	VERB
cana-1616	303	32	machine	machine	NOUN
cana-1616	303	33	learning	learning	NOUN
cana-1616	303	34	,	,	PUNCT
cana-1616	303	35	"	"	PUNCT
cana-1616	303	36	int	int	NOUN
cana-1616	303	37	.	.	PUNCT
cana-1616	304	1	j.	j.	PROPN
cana-1616	304	2	comput	comput	PROPN
cana-1616	304	3	.	.	PUNCT
cana-1616	305	1	trends	trend	NOUN
cana-1616	305	2	technol	technol	ADJ
cana-1616	305	3	.	.	PUNCT
cana-1616	305	4	,	,	PUNCT
cana-1616	305	5	vol	vol	NOUN
cana-1616	305	6	.	.	PROPN
cana-1616	306	1	68	68	NUM
cana-1616	306	2	,	,	PUNCT
cana-1616	306	3	no	no	INTJ
cana-1616	306	4	.	.	NOUN
cana-1616	306	5	8	8	NUM
cana-1616	306	6	,	,	PUNCT
cana-1616	306	7	pp	pp	ADJ
cana-1616	306	8	.	.	PUNCT
cana-1616	307	1	44	44	NUM
cana-1616	307	2	-	-	SYM
cana-1616	307	3	52	52	NUM
cana-1616	307	4	,	,	PUNCT
cana-1616	307	5	aug	aug	PROPN
cana-1616	307	6	.	.	PROPN
cana-1616	307	7	2020	2020	NUM
cana-1616	307	8	.	.	PUNCT
cana-1616	308	1	4	4	X
cana-1616	308	2	.	.	X
cana-1616	308	3	e.	e.	PROPN
cana-1616	308	4	m.	m.	PROPN
cana-1616	308	5	hameed	hameed	PROPN
cana-1616	308	6	,	,	PUNCT
cana-1616	308	7	m.	m.	NOUN
cana-1616	308	8	a.	a.	NOUN
cana-1616	308	9	ameen	ameen	PROPN
cana-1616	308	10	,	,	PUNCT
cana-1616	308	11	k.	k.	PROPN
cana-1616	308	12	f.	f.	PROPN
cana-1616	308	13	ahmed	ahmed	PROPN
cana-1616	308	14	,	,	PUNCT
cana-1616	308	15	and	and	CCONJ
cana-1616	308	16	r.	r.	PROPN
cana-1616	308	17	i.	i.	PROPN
cana-1616	308	18	ali	ali	PROPN
cana-1616	308	19	,	,	PUNCT
cana-1616	308	20	"	"	PUNCT
cana-1616	308	21	liver	liver	NOUN
cana-1616	308	22	disease	disease	NOUN
cana-1616	308	23	detection	detection	NOUN
cana-1616	308	24	and	and	CCONJ
cana-1616	308	25	prediction	prediction	NOUN
cana-1616	308	26	using	use	VERB
cana-1616	308	27	svm	svm	ADJ
cana-1616	308	28	techniques	technique	NOUN
cana-1616	308	29	,	,	PUNCT
cana-1616	308	30	"	"	PUNCT
cana-1616	308	31	in	in	ADP
cana-1616	308	32	2022	2022	NUM
cana-1616	308	33	3rd	3rd	PROPN
cana-1616	308	34	inf	inf	NOUN
cana-1616	308	35	.	.	PUNCT
cana-1616	308	36	technol	technol	PROPN
cana-1616	308	37	.	.	PUNCT
cana-1616	309	1	enhance	enhance	PROPN
cana-1616	309	2	e	e	X
cana-1616	309	3	-	-	VERB
cana-1616	309	4	learn	learn	VERB
cana-1616	309	5	.	.	PUNCT
cana-1616	310	1	other	other	ADJ
cana-1616	310	2	appl	appl	NOUN
cana-1616	310	3	.	.	PUNCT
cana-1616	311	1	(	(	PUNCT
cana-1616	311	2	it	it	PRON
cana-1616	311	3	-	-	PUNCT
cana-1616	311	4	ela	ela	PROPN
cana-1616	311	5	)	)	PUNCT
cana-1616	311	6	,	,	PUNCT
cana-1616	311	7	2022	2022	NUM
cana-1616	311	8	,	,	PUNCT
cana-1616	311	9	pp	pp	ADJ
cana-1616	311	10	.	.	PUNCT
cana-1616	312	1	1	1	NUM
cana-1616	312	2	-	-	SYM
cana-1616	312	3	6	6	NUM
cana-1616	312	4	.	.	NOUN
cana-1616	312	5	5	5	NUM
cana-1616	312	6	.	.	X
cana-1616	312	7	v.	v.	ADP
cana-1616	312	8	sharma	sharma	PROPN
cana-1616	312	9	and	and	CCONJ
cana-1616	312	10	k.	k.	PROPN
cana-1616	312	11	c.	c.	PROPN
cana-1616	312	12	juglan	juglan	PROPN
cana-1616	312	13	,	,	PUNCT
cana-1616	312	14	"	"	PUNCT
cana-1616	312	15	automated	automate	VERB
cana-1616	312	16	classification	classification	NOUN
cana-1616	312	17	of	of	ADP
cana-1616	312	18	fatty	fatty	NOUN
cana-1616	312	19	and	and	CCONJ
cana-1616	312	20	normal	normal	ADJ
cana-1616	312	21	liver	liver	NOUN
cana-1616	312	22	ultrasound	ultrasound	NOUN
cana-1616	312	23	images	image	NOUN
cana-1616	312	24	based	base	VERB
cana-1616	312	25	on	on	ADP
cana-1616	312	26	mutual	mutual	ADJ
cana-1616	312	27	information	information	NOUN
cana-1616	312	28	feature	feature	NOUN
cana-1616	312	29	selection	selection	NOUN
cana-1616	312	30	,	,	PUNCT
cana-1616	312	31	"	"	PUNCT
cana-1616	312	32	irbm	irbm	NOUN
cana-1616	312	33	,	,	PUNCT
cana-1616	312	34	vol	vol	NOUN
cana-1616	312	35	.	.	PROPN
cana-1616	312	36	39	39	NUM
cana-1616	312	37	,	,	PUNCT
cana-1616	312	38	no	no	INTJ
cana-1616	312	39	.	.	NOUN
cana-1616	312	40	5	5	NUM
cana-1616	312	41	,	,	PUNCT
cana-1616	312	42	pp	pp	ADJ
cana-1616	312	43	.	.	PUNCT
cana-1616	313	1	313	313	NUM
cana-1616	313	2	-	-	SYM
cana-1616	313	3	323	323	NUM
cana-1616	313	4	,	,	PUNCT
cana-1616	313	5	2018	2018	NUM
cana-1616	313	6	.	.	PUNCT
cana-1616	314	1	6	6	NUM
cana-1616	314	2	.	.	PUNCT
cana-1616	314	3	f.	f.	PROPN
cana-1616	314	4	bessone	bessone	PROPN
cana-1616	314	5	,	,	PUNCT
cana-1616	314	6	m.	m.	NOUN
cana-1616	314	7	v.	v.	CCONJ
cana-1616	314	8	razori	razori	PROPN
cana-1616	314	9	,	,	PUNCT
cana-1616	314	10	and	and	CCONJ
cana-1616	314	11	m.	m.	NOUN
cana-1616	314	12	g.	g.	PROPN
cana-1616	314	13	roma	roma	PROPN
cana-1616	314	14	,	,	PUNCT
cana-1616	314	15	"	"	PUNCT
cana-1616	314	16	molecular	molecular	ADJ
cana-1616	314	17	pathways	pathway	NOUN
cana-1616	314	18	of	of	ADP
cana-1616	314	19	nonalcoholic	nonalcoholic	NOUN
cana-1616	314	20	fatty	fatty	NOUN
cana-1616	314	21	liver	liver	NOUN
cana-1616	314	22	disease	disease	NOUN
cana-1616	314	23	development	development	NOUN
cana-1616	314	24	and	and	CCONJ
cana-1616	314	25	progression	progression	NOUN
cana-1616	314	26	,	,	PUNCT
cana-1616	314	27	"	"	PUNCT
cana-1616	314	28	cell	cell	NOUN
cana-1616	314	29	.	.	PUNCT
cana-1616	315	1	mol	mol	PROPN
cana-1616	315	2	.	.	PROPN
cana-1616	315	3	life	life	PROPN
cana-1616	315	4	sci	sci	PROPN
cana-1616	315	5	.	.	PROPN
cana-1616	315	6	,	,	PUNCT
cana-1616	315	7	vol	vol	NOUN
cana-1616	315	8	.	.	PROPN
cana-1616	316	1	76	76	NUM
cana-1616	316	2	,	,	PUNCT
cana-1616	317	1	pp	pp	ADJ
cana-1616	317	2	.	.	PUNCT
cana-1616	318	1	99	99	NUM
cana-1616	318	2	-	-	SYM
cana-1616	318	3	128	128	NUM
cana-1616	318	4	,	,	PUNCT
cana-1616	318	5	2019	2019	NUM
cana-1616	318	6	.	.	PUNCT
cana-1616	319	1	7	7	X
cana-1616	319	2	.	.	X
cana-1616	319	3	d.	d.	PROPN
cana-1616	319	4	kim	kim	PROPN
cana-1616	319	5	,	,	PUNCT
cana-1616	319	6	m.	m.	PROPN
cana-1616	319	7	e.	e.	PROPN
cana-1616	319	8	cholankeril	cholankeril	PROPN
cana-1616	319	9	,	,	PUNCT
cana-1616	319	10	a.	a.	PROPN
cana-1616	319	11	a.	a.	PROPN
cana-1616	319	12	ahmed	ahmed	PROPN
cana-1616	319	13	,	,	PUNCT
cana-1616	319	14	d.	d.	PROPN
cana-1616	319	15	v.	v.	PROPN
cana-1616	319	16	tighe	tighe	PROPN
cana-1616	319	17	,	,	PUNCT
cana-1616	319	18	and	and	CCONJ
cana-1616	319	19	a.	a.	NOUN
cana-1616	319	20	singal	singal	NOUN
cana-1616	319	21	,	,	PUNCT
cana-1616	319	22	"	"	PUNCT
cana-1616	319	23	trends	trend	NOUN
cana-1616	319	24	in	in	ADP
cana-1616	319	25	etiology	etiology	NOUN
cana-1616	319	26	-	-	PUNCT
cana-1616	319	27	based	base	VERB
cana-1616	319	28	mortality	mortality	NOUN
cana-1616	319	29	from	from	ADP
cana-1616	319	30	chronic	chronic	ADJ
cana-1616	319	31	liver	liver	NOUN
cana-1616	319	32	disease	disease	NOUN
cana-1616	319	33	before	before	ADP
cana-1616	319	34	and	and	CCONJ
cana-1616	319	35	during	during	ADP
cana-1616	319	36	covid-19	covid-19	PROPN
cana-1616	319	37	pandemic	pandemic	NOUN
cana-1616	319	38	in	in	ADP
cana-1616	319	39	the	the	DET
cana-1616	319	40	united	united	PROPN
cana-1616	319	41	states	states	PROPN
cana-1616	319	42	,	,	PUNCT
cana-1616	319	43	"	"	PUNCT
cana-1616	319	44	clin	clin	PROPN
cana-1616	319	45	.	.	PUNCT
cana-1616	320	1	gastroenterol	gastroenterol	PROPN
cana-1616	320	2	.	.	PUNCT
cana-1616	321	1	hepatol	hepatol	ADJ
cana-1616	321	2	.	.	PUNCT
cana-1616	321	3	,	,	PUNCT
cana-1616	321	4	vol	vol	NOUN
cana-1616	321	5	.	.	PROPN
cana-1616	321	6	20	20	NUM
cana-1616	321	7	,	,	PUNCT
cana-1616	321	8	no	no	INTJ
cana-1616	321	9	.	.	NOUN
cana-1616	321	10	10	10	NUM
cana-1616	321	11	,	,	PUNCT
cana-1616	321	12	pp	pp	ADJ
cana-1616	321	13	.	.	PUNCT
cana-1616	322	1	2307	2307	NUM
cana-1616	322	2	-	-	SYM
cana-1616	322	3	2316	2316	NUM
cana-1616	322	4	,	,	PUNCT
cana-1616	322	5	2022	2022	NUM
cana-1616	322	6	.	.	PUNCT
cana-1616	323	1	8	8	NUM
cana-1616	323	2	.	.	X
cana-1616	323	3	b.	b.	PROPN
cana-1616	323	4	l.	l.	PROPN
cana-1616	323	5	da	da	PROPN
cana-1616	323	6	,	,	PUNCT
cana-1616	323	7	g.	g.	PROPN
cana-1616	323	8	y.	y.	PROPN
cana-1616	323	9	i	i	PRON
cana-1616	323	10	m	m	PROPN
cana-1616	323	11	,	,	PUNCT
cana-1616	323	12	and	and	CCONJ
cana-1616	323	13	t.	t.	PROPN
cana-1616	323	14	d.	d.	PROPN
cana-1616	323	15	schiano	schiano	PROPN
cana-1616	323	16	,	,	PUNCT
cana-1616	323	17	"	"	PUNCT
cana-1616	323	18	coronavirus	coronavirus	NOUN
cana-1616	323	19	disease	disease	NOUN
cana-1616	323	20	2019	2019	NUM
cana-1616	323	21	hangover	hangover	NOUN
cana-1616	323	22	:	:	PUNCT
cana-1616	323	23	a	a	DET
cana-1616	323	24	rising	rise	VERB
cana-1616	323	25	tide	tide	NOUN
cana-1616	323	26	of	of	ADP
cana-1616	323	27	alcohol	alcohol	NOUN
cana-1616	323	28	use	use	NOUN
cana-1616	323	29	disorder	disorder	NOUN
cana-1616	323	30	and	and	CCONJ
cana-1616	323	31	alcohol‐associated	alcohol‐associate	VERB
cana-1616	323	32	liver	liver	NOUN
cana-1616	323	33	disease	disease	NOUN
cana-1616	323	34	,	,	PUNCT
cana-1616	323	35	"	"	PUNCT
cana-1616	323	36	hepatology	hepatology	NOUN
cana-1616	323	37	,	,	PUNCT
cana-1616	323	38	vol	vol	NOUN
cana-1616	323	39	.	.	PROPN
cana-1616	323	40	72	72	NUM
cana-1616	323	41	,	,	PUNCT
cana-1616	323	42	no	no	INTJ
cana-1616	323	43	.	.	NOUN
cana-1616	323	44	3	3	NUM
cana-1616	323	45	,	,	PUNCT
cana-1616	323	46	pp	pp	ADJ
cana-1616	323	47	.	.	PUNCT
cana-1616	323	48	1102	1102	NUM
cana-1616	323	49	-	-	SYM
cana-1616	323	50	1108	1108	NUM
cana-1616	323	51	,	,	PUNCT
cana-1616	323	52	2020	2020	NUM
cana-1616	323	53	.	.	PUNCT
cana-1616	324	1	9	9	NUM
cana-1616	324	2	.	.	X
cana-1616	324	3	g.	g.	PROPN
cana-1616	324	4	cabibbo	cabibbo	PROPN
cana-1616	324	5	,	,	PUNCT
cana-1616	324	6	f.	f.	PROPN
cana-1616	324	7	enea	enea	PROPN
cana-1616	324	8	,	,	PUNCT
cana-1616	324	9	f.	f.	PROPN
cana-1616	324	10	m.	m.	PROPN
cana-1616	324	11	cammà	cammà	PROPN
cana-1616	324	12	,	,	PUNCT
cana-1616	324	13	v.	v.	CCONJ
cana-1616	324	14	petta	petta	NOUN
cana-1616	324	15	,	,	PUNCT
cana-1616	324	16	m.	m.	PROPN
cana-1616	324	17	r.	r.	PROPN
cana-1616	324	18	maida	maida	PROPN
cana-1616	324	19	,	,	PUNCT
cana-1616	324	20	a.	a.	NOUN
cana-1616	324	21	craxì	craxì	PROPN
cana-1616	324	22	,	,	PUNCT
cana-1616	324	23	and	and	CCONJ
cana-1616	324	24	g.	g.	PROPN
cana-1616	324	25	d'antona	d'antona	PROPN
cana-1616	324	26	,	,	PUNCT
cana-1616	324	27	"	"	PUNCT
cana-1616	324	28	sars‐cov‐2	sars‐cov‐2	PROPN
cana-1616	324	29	infection	infection	NOUN
cana-1616	324	30	in	in	ADP
cana-1616	324	31	patients	patient	NOUN
cana-1616	324	32	with	with	ADP
cana-1616	324	33	a	a	DET
cana-1616	324	34	normal	normal	ADJ
cana-1616	324	35	or	or	CCONJ
cana-1616	324	36	abnormal	abnormal	ADJ
cana-1616	324	37	liver	liver	NOUN
cana-1616	324	38	,	,	PUNCT
cana-1616	324	39	"	"	PUNCT
cana-1616	324	40	j.	j.	PROPN
cana-1616	324	41	viral	viral	ADJ
cana-1616	324	42	hepat	hepat	PROPN
cana-1616	324	43	.	.	PUNCT
cana-1616	324	44	,	,	PUNCT
cana-1616	324	45	vol	vol	NOUN
cana-1616	324	46	.	.	PROPN
cana-1616	324	47	28	28	NUM
cana-1616	324	48	,	,	PUNCT
cana-1616	324	49	no	no	INTJ
cana-1616	324	50	.	.	NOUN
cana-1616	324	51	1	1	NUM
cana-1616	324	52	,	,	PUNCT
cana-1616	324	53	pp	pp	ADJ
cana-1616	324	54	.	.	PUNCT
cana-1616	325	1	4	4	NUM
cana-1616	325	2	-	-	SYM
cana-1616	325	3	11	11	NUM
cana-1616	325	4	,	,	PUNCT
cana-1616	325	5	2021	2021	NUM
cana-1616	325	6	.	.	PUNCT
cana-1616	326	1	10	10	NUM
cana-1616	326	2	.	.	PUNCT
cana-1616	327	1	p.	p.	NOUN
cana-1616	327	2	decharatanachart	decharatanachart	PROPN
cana-1616	327	3	,	,	PUNCT
cana-1616	327	4	n.	n.	PROPN
cana-1616	327	5	chaikledkaew	chaikledkaew	VERB
cana-1616	327	6	,	,	PUNCT
cana-1616	327	7	y.	y.	PROPN
cana-1616	327	8	thakkinstian	thakkinstian	PROPN
cana-1616	327	9	,	,	PUNCT
cana-1616	327	10	and	and	CCONJ
cana-1616	327	11	c.	c.	PROPN
cana-1616	327	12	anothaisintawee	anothaisintawee	PROPN
cana-1616	327	13	,	,	PUNCT
cana-1616	327	14	"	"	PUNCT
cana-1616	327	15	application	application	NOUN
cana-1616	327	16	of	of	ADP
cana-1616	327	17	artificial	artificial	ADJ
cana-1616	327	18	intelligence	intelligence	NOUN
cana-1616	327	19	in	in	ADP
cana-1616	327	20	chronic	chronic	ADJ
cana-1616	327	21	liver	liver	NOUN
cana-1616	327	22	diseases	disease	NOUN
cana-1616	327	23	:	:	PUNCT
cana-1616	327	24	a	a	DET
cana-1616	327	25	systematic	systematic	ADJ
cana-1616	327	26	review	review	NOUN
cana-1616	327	27	and	and	CCONJ
cana-1616	327	28	meta	meta	ADJ
cana-1616	327	29	-	-	PUNCT
cana-1616	327	30	analysis	analysis	NOUN
cana-1616	327	31	,	,	PUNCT
cana-1616	327	32	"	"	PUNCT
cana-1616	327	33	bmc	bmc	ADJ
cana-1616	327	34	gastroenterol	gastroenterol	NOUN
cana-1616	327	35	.	.	PUNCT
cana-1616	328	1	,	,	PUNCT
cana-1616	328	2	vol	vol	NOUN
cana-1616	328	3	.	.	PROPN
cana-1616	329	1	21	21	NUM
cana-1616	329	2	,	,	PUNCT
cana-1616	329	3	no	no	INTJ
cana-1616	329	4	.	.	NOUN
cana-1616	329	5	1	1	NUM
cana-1616	329	6	,	,	PUNCT
cana-1616	329	7	pp	pp	ADJ
cana-1616	329	8	.	.	PUNCT
cana-1616	330	1	1	1	NUM
cana-1616	330	2	-	-	SYM
cana-1616	330	3	16	16	NUM
cana-1616	330	4	,	,	PUNCT
cana-1616	330	5	2021	2021	NUM
cana-1616	330	6	.	.	PUNCT
cana-1616	331	1	11	11	NUM
cana-1616	331	2	.	.	PUNCT
cana-1616	332	1	s.	s.	PROPN
cana-1616	332	2	gm	gm	PROPN
cana-1616	332	3	,	,	PUNCT
cana-1616	332	4	b.	b.	PROPN
cana-1616	332	5	amuthan	amuthan	PROPN
cana-1616	332	6	,	,	PUNCT
cana-1616	332	7	p.	p.	PROPN
cana-1616	332	8	m.	m.	PROPN
cana-1616	332	9	muthukumar	muthukumar	PROPN
cana-1616	332	10	,	,	PUNCT
cana-1616	332	11	and	and	CCONJ
cana-1616	332	12	d.	d.	PROPN
cana-1616	332	13	subramanian	subramanian	PROPN
cana-1616	332	14	,	,	PUNCT
cana-1616	332	15	"	"	PUNCT
cana-1616	332	16	healthcare	healthcare	PROPN
cana-1616	332	17	data	datum	NOUN
cana-1616	332	18	analytics	analytic	NOUN
cana-1616	332	19	using	use	VERB
cana-1616	332	20	artificial	artificial	ADJ
cana-1616	332	21	intelligence	intelligence	NOUN
cana-1616	332	22	,	,	PUNCT
cana-1616	332	23	"	"	PUNCT
cana-1616	332	24	in	in	ADP
cana-1616	332	25	artif	artif	PROPN
cana-1616	332	26	.	.	PUNCT
cana-1616	333	1	intell	intell	PROPN
cana-1616	333	2	.	.	PUNCT
cana-1616	334	1	inf	inf	PROPN
cana-1616	334	2	.	.	PROPN
cana-1616	334	3	manag	manag	PROPN
cana-1616	334	4	.	.	PUNCT
cana-1616	334	5	:	:	PUNCT
cana-1616	335	1	a	a	DET
cana-1616	335	2	healthc	healthc	NOUN
cana-1616	335	3	.	.	PUNCT
cana-1616	335	4	perspect	perspect	PROPN
cana-1616	335	5	.	.	PUNCT
cana-1616	335	6	,	,	PUNCT
cana-1616	335	7	2021	2021	NUM
cana-1616	335	8	,	,	PUNCT
cana-1616	335	9	pp	pp	ADJ
cana-1616	335	10	.	.	PUNCT
cana-1616	336	1	45	45	NUM
cana-1616	336	2	-	-	SYM
cana-1616	336	3	85	85	NUM
cana-1616	336	4	.	.	PUNCT
cana-1616	337	1	12	12	NUM
cana-1616	337	2	.	.	PUNCT
cana-1616	338	1	j.	j.	PROPN
cana-1616	338	2	singh	singh	PROPN
cana-1616	338	3	,	,	PUNCT
cana-1616	338	4	s.	s.	PROPN
cana-1616	338	5	bagga	bagga	PROPN
cana-1616	338	6	,	,	PUNCT
cana-1616	338	7	and	and	CCONJ
cana-1616	338	8	r.	r.	PROPN
cana-1616	338	9	kaur	kaur	PROPN
cana-1616	338	10	,	,	PUNCT
cana-1616	338	11	"	"	PUNCT
cana-1616	338	12	software	software	NOUN
cana-1616	338	13	-	-	PUNCT
cana-1616	338	14	based	base	VERB
cana-1616	338	15	prediction	prediction	NOUN
cana-1616	338	16	of	of	ADP
cana-1616	338	17	liver	liver	NOUN
cana-1616	338	18	disease	disease	NOUN
cana-1616	338	19	with	with	ADP
cana-1616	338	20	feature	feature	NOUN
cana-1616	338	21	selection	selection	NOUN
cana-1616	338	22	and	and	CCONJ
cana-1616	338	23	classification	classification	NOUN
cana-1616	338	24	techniques	technique	NOUN
cana-1616	338	25	,	,	PUNCT
cana-1616	338	26	"	"	PUNCT
cana-1616	338	27	procedia	procedia	NOUN
cana-1616	338	28	comput	comput	NOUN
cana-1616	338	29	.	.	PUNCT
cana-1616	339	1	sci	sci	PROPN
cana-1616	339	2	.	.	PROPN
cana-1616	339	3	,	,	PUNCT
cana-1616	339	4	vol	vol	NOUN
cana-1616	339	5	.	.	PROPN
cana-1616	339	6	167	167	NUM
cana-1616	339	7	,	,	PUNCT
cana-1616	339	8	pp	pp	ADJ
cana-1616	339	9	.	.	PUNCT
cana-1616	339	10	1970	1970	NUM
cana-1616	339	11	-	-	SYM
cana-1616	339	12	1980	1980	NUM
cana-1616	339	13	,	,	PUNCT
cana-1616	339	14	2020	2020	NUM
cana-1616	339	15	.	.	PUNCT
cana-1616	340	1	13	13	NUM
cana-1616	340	2	.	.	PUNCT
cana-1616	341	1	k.	k.	PROPN
cana-1616	341	2	dutta	dutta	PROPN
cana-1616	341	3	,	,	PUNCT
cana-1616	341	4	s.	s.	PROPN
cana-1616	341	5	chandra	chandra	PROPN
cana-1616	341	6	,	,	PUNCT
cana-1616	341	7	and	and	CCONJ
cana-1616	341	8	m.	m.	PROPN
cana-1616	341	9	k.	k.	PROPN
cana-1616	341	10	gourisaria	gourisaria	PROPN
cana-1616	341	11	,	,	PUNCT
cana-1616	341	12	"	"	PUNCT
cana-1616	341	13	early	early	ADJ
cana-1616	341	14	-	-	PUNCT
cana-1616	341	15	stage	stage	NOUN
cana-1616	341	16	detection	detection	NOUN
cana-1616	341	17	of	of	ADP
cana-1616	341	18	liver	liver	NOUN
cana-1616	341	19	disease	disease	NOUN
cana-1616	341	20	through	through	ADP
cana-1616	341	21	machine	machine	NOUN
cana-1616	341	22	learning	learning	NOUN
cana-1616	341	23	algorithms	algorithm	NOUN
cana-1616	341	24	,	,	PUNCT
cana-1616	341	25	"	"	PUNCT
cana-1616	341	26	in	in	ADP
cana-1616	341	27	advances	advance	NOUN
cana-1616	341	28	data	data	PROPN
cana-1616	341	29	inf	inf	PROPN
cana-1616	341	30	.	.	PUNCT
cana-1616	342	1	sci	sci	PROPN
cana-1616	342	2	.	.	PROPN
cana-1616	342	3	,	,	PUNCT
cana-1616	342	4	springer	springer	NOUN
cana-1616	342	5	,	,	PUNCT
cana-1616	342	6	singapore	singapore	PROPN
cana-1616	342	7	,	,	PUNCT
cana-1616	342	8	2022	2022	NUM
cana-1616	342	9	,	,	PUNCT
cana-1616	342	10	pp	pp	ADJ
cana-1616	342	11	.	.	PUNCT
cana-1616	342	12	155	155	NUM
cana-1616	342	13	-	-	SYM
cana-1616	342	14	166	166	NUM
cana-1616	342	15	.	.	PUNCT
cana-1616	343	1	communications	communication	NOUN
cana-1616	343	2	on	on	ADP
cana-1616	343	3	applied	apply	VERB
cana-1616	343	4	nonlinear	nonlinear	ADJ
cana-1616	343	5	analysis	analysis	NOUN
cana-1616	343	6	issn	issn	NOUN
cana-1616	343	7	:	:	PUNCT
cana-1616	343	8	1074	1074	NUM
cana-1616	343	9	-	-	PUNCT
cana-1616	343	10	133x	133x	NUM
cana-1616	343	11	vol	vol	NOUN
cana-1616	343	12	31	31	NUM
cana-1616	343	13	no	no	NOUN
cana-1616	343	14	.	.	PUNCT
cana-1616	344	1	8s	8s	PROPN
cana-1616	344	2	(	(	PUNCT
cana-1616	344	3	2024	2024	NUM
cana-1616	344	4	)	)	PUNCT
cana-1616	344	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	344	6	792	792	NUM
cana-1616	344	7	14	14	NUM
cana-1616	344	8	.	.	PUNCT
cana-1616	345	1	g.	g.	PROPN
cana-1616	345	2	shaheamlung	shaheamlung	PROPN
cana-1616	345	3	and	and	CCONJ
cana-1616	345	4	h.	h.	PROPN
cana-1616	345	5	kaur	kaur	PROPN
cana-1616	345	6	,	,	PUNCT
cana-1616	345	7	"	"	PUNCT
cana-1616	345	8	the	the	DET
cana-1616	345	9	diagnosis	diagnosis	NOUN
cana-1616	345	10	of	of	ADP
cana-1616	345	11	chronic	chronic	ADJ
cana-1616	345	12	liver	liver	NOUN
cana-1616	345	13	disease	disease	NOUN
cana-1616	345	14	using	use	VERB
cana-1616	345	15	machine	machine	NOUN
cana-1616	345	16	learning	learning	NOUN
cana-1616	345	17	techniques	technique	NOUN
cana-1616	345	18	,	,	PUNCT
cana-1616	345	19	"	"	PUNCT
cana-1616	345	20	inf	inf	PROPN
cana-1616	345	21	.	.	PUNCT
cana-1616	345	22	technol	technol	PROPN
cana-1616	345	23	.	.	PUNCT
cana-1616	346	1	ind	ind	PROPN
cana-1616	346	2	.	.	PUNCT
cana-1616	346	3	,	,	PUNCT
cana-1616	346	4	vol	vol	NOUN
cana-1616	346	5	.	.	NOUN
cana-1616	346	6	9	9	NUM
cana-1616	346	7	,	,	PUNCT
cana-1616	346	8	2021	2021	NUM
cana-1616	346	9	,	,	PUNCT
cana-1616	346	10	doi	doi	NOUN
cana-1616	346	11	:	:	PUNCT
cana-1616	346	12	10.17762	10.17762	NUM
cana-1616	346	13	/	/	SYM
cana-1616	346	14	itii.v9i2.382	itii.v9i2.382	NOUN
cana-1616	346	15	.	.	PUNCT
cana-1616	347	1	15	15	NUM
cana-1616	347	2	.	.	PUNCT
cana-1616	348	1	h.	h.	PROPN
cana-1616	348	2	ding	ding	PROPN
cana-1616	348	3	,	,	PUNCT
cana-1616	348	4	z.	z.	PROPN
cana-1616	348	5	fu	fu	PROPN
cana-1616	348	6	,	,	PUNCT
cana-1616	348	7	x.	x.	PROPN
cana-1616	348	8	zhang	zhang	PROPN
cana-1616	348	9	,	,	PUNCT
cana-1616	348	10	and	and	CCONJ
cana-1616	348	11	y.	y.	PROPN
cana-1616	348	12	tang	tang	PROPN
cana-1616	348	13	,	,	PUNCT
cana-1616	348	14	"	"	PUNCT
cana-1616	348	15	a	a	DET
cana-1616	348	16	framework	framework	NOUN
cana-1616	348	17	for	for	ADP
cana-1616	348	18	identification	identification	NOUN
cana-1616	348	19	and	and	CCONJ
cana-1616	348	20	classification	classification	NOUN
cana-1616	348	21	of	of	ADP
cana-1616	348	22	liver	liver	NOUN
cana-1616	348	23	diseases	disease	NOUN
cana-1616	348	24	based	base	VERB
cana-1616	348	25	on	on	ADP
cana-1616	348	26	machine	machine	NOUN
cana-1616	348	27	learning	learning	NOUN
cana-1616	348	28	algorithms	algorithm	NOUN
cana-1616	348	29	,	,	PUNCT
cana-1616	348	30	"	"	PUNCT
cana-1616	348	31	front	front	ADJ
cana-1616	348	32	.	.	PUNCT
cana-1616	349	1	oncol	oncol	ADJ
cana-1616	349	2	.	.	PUNCT
cana-1616	349	3	,	,	PUNCT
cana-1616	349	4	vol	vol	NOUN
cana-1616	349	5	.	.	PROPN
cana-1616	349	6	12	12	NUM
cana-1616	349	7	,	,	PUNCT
cana-1616	349	8	2022	2022	NUM
cana-1616	349	9	,	,	PUNCT
cana-1616	349	10	art	art	NOUN
cana-1616	349	11	.	.	PUNCT
cana-1616	350	1	no	no	INTJ
cana-1616	350	2	.	.	NOUN
cana-1616	350	3	1048348	1048348	NUM
cana-1616	350	4	.	.	PUNCT
cana-1616	351	1	16	16	NUM
cana-1616	351	2	.	.	PUNCT
cana-1616	352	1	z.	z.	PROPN
cana-1616	352	2	yao	yao	PROPN
cana-1616	352	3	,	,	PUNCT
cana-1616	352	4	j.	j.	PROPN
cana-1616	352	5	hu	hu	PROPN
cana-1616	352	6	,	,	PUNCT
cana-1616	352	7	y.	y.	PROPN
cana-1616	352	8	lin	lin	PROPN
cana-1616	352	9	,	,	PUNCT
cana-1616	352	10	and	and	CCONJ
cana-1616	352	11	l.	l.	PROPN
cana-1616	352	12	zhang	zhang	PROPN
cana-1616	352	13	,	,	PUNCT
cana-1616	352	14	"	"	PUNCT
cana-1616	352	15	liver	liver	NOUN
cana-1616	352	16	disease	disease	NOUN
cana-1616	352	17	screening	screen	VERB
cana-1616	352	18	based	base	VERB
cana-1616	352	19	on	on	ADP
cana-1616	352	20	densely	densely	ADV
cana-1616	352	21	connected	connect	VERB
cana-1616	352	22	deep	deep	ADJ
cana-1616	352	23	neural	neural	ADJ
cana-1616	352	24	networks	network	NOUN
cana-1616	352	25	,	,	PUNCT
cana-1616	352	26	"	"	PUNCT
cana-1616	352	27	neural	neural	ADJ
cana-1616	352	28	netw	netw	NOUN
cana-1616	352	29	.	.	PUNCT
cana-1616	352	30	,	,	PUNCT
cana-1616	352	31	vol	vol	NOUN
cana-1616	352	32	.	.	PROPN
cana-1616	352	33	123	123	NUM
cana-1616	352	34	,	,	PUNCT
cana-1616	352	35	pp	pp	ADV
cana-1616	352	36	.	.	PUNCT
cana-1616	353	1	299	299	NUM
cana-1616	353	2	-	-	SYM
cana-1616	353	3	304	304	NUM
cana-1616	353	4	,	,	PUNCT
cana-1616	353	5	2020	2020	NUM
cana-1616	353	6	.	.	PUNCT
cana-1616	354	1	17	17	NUM
cana-1616	354	2	.	.	PUNCT
cana-1616	355	1	p.	p.	PROPN
cana-1616	355	2	kumar	kumar	PROPN
cana-1616	355	3	and	and	CCONJ
cana-1616	355	4	r.	r.	PROPN
cana-1616	355	5	s.	s.	PROPN
cana-1616	355	6	thakur	thakur	PROPN
cana-1616	355	7	,	,	PUNCT
cana-1616	355	8	"	"	PUNCT
cana-1616	355	9	liver	liver	NOUN
cana-1616	355	10	disorder	disorder	NOUN
cana-1616	355	11	detection	detection	NOUN
cana-1616	355	12	using	use	VERB
cana-1616	355	13	variable	variable	ADJ
cana-1616	355	14	-	-	PUNCT
cana-1616	355	15	neighbor	neighbor	NOUN
cana-1616	355	16	weighted	weight	VERB
cana-1616	355	17	fuzzy	fuzzy	ADJ
cana-1616	355	18	k	k	PROPN
cana-1616	355	19	nearest	near	ADJ
cana-1616	355	20	neighbor	neighbor	NOUN
cana-1616	355	21	approach	approach	NOUN
cana-1616	355	22	,	,	PUNCT
cana-1616	355	23	"	"	PUNCT
cana-1616	355	24	multimed	multime	VERB
cana-1616	355	25	.	.	PUNCT
cana-1616	356	1	tools	tool	NOUN
cana-1616	356	2	appl	appl	PROPN
cana-1616	356	3	.	.	PUNCT
cana-1616	356	4	,	,	PUNCT
cana-1616	356	5	vol	vol	NOUN
cana-1616	356	6	.	.	PROPN
cana-1616	356	7	80	80	NUM
cana-1616	356	8	,	,	PUNCT
cana-1616	356	9	pp	pp	ADJ
cana-1616	356	10	.	.	PUNCT
cana-1616	357	1	16515	16515	NUM
cana-1616	357	2	-	-	SYM
cana-1616	357	3	16535	16535	NUM
cana-1616	357	4	,	,	PUNCT
cana-1616	357	5	2021	2021	NUM
cana-1616	357	6	.	.	PUNCT
cana-1616	358	1	18	18	NUM
cana-1616	358	2	.	.	PUNCT
cana-1616	358	3	m.	m.	NOUN
cana-1616	358	4	g.	g.	PROPN
cana-1616	358	5	lanjewar	lanjewar	PROPN
cana-1616	358	6	,	,	PUNCT
cana-1616	358	7	r.	r.	PROPN
cana-1616	358	8	v.	v.	PROPN
cana-1616	358	9	dixit	dixit	PROPN
cana-1616	358	10	,	,	PUNCT
cana-1616	358	11	s.	s.	PROPN
cana-1616	358	12	p.	p.	PROPN
cana-1616	358	13	wankhade	wankhade	NOUN
cana-1616	358	14	,	,	PUNCT
cana-1616	358	15	and	and	CCONJ
cana-1616	358	16	k.	k.	PROPN
cana-1616	358	17	g.	g.	PROPN
cana-1616	358	18	parlewar	parlewar	PROPN
cana-1616	358	19	,	,	PUNCT
cana-1616	358	20	"	"	PUNCT
cana-1616	358	21	cnn	cnn	PROPN
cana-1616	358	22	with	with	ADP
cana-1616	358	23	machine	machine	NOUN
cana-1616	358	24	learning	learn	VERB
cana-1616	358	25	approaches	approach	NOUN
cana-1616	358	26	using	use	VERB
cana-1616	358	27	extratreesclassifier	extratreesclassifier	ADV
cana-1616	358	28	and	and	CCONJ
cana-1616	358	29	mrmr	mrmr	PROPN
cana-1616	358	30	feature	feature	NOUN
cana-1616	358	31	selection	selection	NOUN
cana-1616	358	32	techniques	technique	NOUN
cana-1616	358	33	to	to	PART
cana-1616	358	34	detect	detect	VERB
cana-1616	358	35	liver	liver	NOUN
cana-1616	358	36	diseases	disease	NOUN
cana-1616	358	37	on	on	ADP
cana-1616	358	38	cloud	cloud	NOUN
cana-1616	358	39	,	,	PUNCT
cana-1616	358	40	"	"	PUNCT
cana-1616	358	41	cluster	cluster	NOUN
cana-1616	358	42	comput	comput	NOUN
cana-1616	358	43	.	.	PUNCT
cana-1616	358	44	,	,	PUNCT
cana-1616	359	1	pp	pp	ADJ
cana-1616	359	2	.	.	PUNCT
cana-1616	360	1	1	1	NUM
cana-1616	360	2	-	-	SYM
cana-1616	360	3	16	16	NUM
cana-1616	360	4	,	,	PUNCT
cana-1616	360	5	2022	2022	NUM
cana-1616	360	6	19	19	NUM
cana-1616	360	7	.	.	PUNCT
cana-1616	361	1	s.	s.	PROPN
cana-1616	361	2	ambesange	ambesange	PROPN
cana-1616	361	3	,	,	PUNCT
cana-1616	361	4	v.	v.	ADP
cana-1616	361	5	a	a	PRON
cana-1616	361	6	,	,	PUNCT
cana-1616	361	7	r.	r.	PROPN
cana-1616	361	8	uppin	uppin	PROPN
cana-1616	361	9	,	,	PUNCT
cana-1616	361	10	s.	s.	PROPN
cana-1616	361	11	patil	patil	PROPN
cana-1616	361	12	,	,	PUNCT
cana-1616	361	13	and	and	CCONJ
cana-1616	361	14	v.	v.	ADP
cana-1616	361	15	patil	patil	PROPN
cana-1616	361	16	,	,	PUNCT
cana-1616	361	17	"	"	PUNCT
cana-1616	361	18	optimizing	optimize	VERB
cana-1616	361	19	liver	liver	NOUN
cana-1616	361	20	disease	disease	NOUN
cana-1616	361	21	prediction	prediction	NOUN
cana-1616	361	22	with	with	ADP
cana-1616	361	23	random	random	ADJ
cana-1616	361	24	forest	forest	NOUN
cana-1616	361	25	by	by	ADP
cana-1616	361	26	various	various	ADJ
cana-1616	361	27	data	datum	NOUN
cana-1616	361	28	balancing	balance	VERB
cana-1616	361	29	techniques	technique	NOUN
cana-1616	361	30	,	,	PUNCT
cana-1616	361	31	"	"	PUNCT
cana-1616	361	32	in	in	ADP
cana-1616	361	33	2020	2020	NUM
cana-1616	361	34	ieee	ieee	NOUN
cana-1616	361	35	int	int	NOUN
cana-1616	361	36	.	.	PUNCT
cana-1616	362	1	conf	conf	PROPN
cana-1616	362	2	.	.	PUNCT
cana-1616	363	1	cloud	cloud	PROPN
cana-1616	363	2	comput	comput	PROPN
cana-1616	363	3	.	.	PUNCT
cana-1616	364	1	emerg	emerg	PROPN
cana-1616	364	2	.	.	PUNCT
cana-1616	364	3	mark	mark	PROPN
cana-1616	364	4	.	.	PUNCT
cana-1616	365	1	(	(	PUNCT
cana-1616	365	2	ccem	ccem	NOUN
cana-1616	365	3	)	)	PUNCT
cana-1616	365	4	,	,	PUNCT
cana-1616	365	5	bengaluru	bengaluru	PROPN
cana-1616	365	6	,	,	PUNCT
cana-1616	365	7	india	india	PROPN
cana-1616	365	8	,	,	PUNCT
cana-1616	365	9	2020	2020	NUM
cana-1616	365	10	,	,	PUNCT
cana-1616	365	11	pp	pp	ADJ
cana-1616	365	12	.	.	PUNCT
cana-1616	366	1	98	98	NUM
cana-1616	366	2	-	-	SYM
cana-1616	366	3	102	102	NUM
cana-1616	366	4	,	,	PUNCT
cana-1616	366	5	doi	doi	NOUN
cana-1616	366	6	:	:	PUNCT
cana-1616	366	7	10.1109	10.1109	NUM
cana-1616	366	8	/	/	SYM
cana-1616	366	9	ccem50674.2020.00030	ccem50674.2020.00030	NOUN
cana-1616	366	10	.	.	NOUN
cana-1616	367	1	20	20	NUM
cana-1616	367	2	.	.	PUNCT
cana-1616	367	3	m.	m.	NOUN
cana-1616	367	4	varchagall	varchagall	NOUN
cana-1616	367	5	and	and	CCONJ
cana-1616	367	6	p.	p.	NOUN
cana-1616	367	7	a.	a.	NOUN
cana-1616	367	8	yogegowda	yogegowda	PROPN
cana-1616	367	9	,	,	PUNCT
cana-1616	367	10	"	"	PUNCT
cana-1616	367	11	early	early	ADJ
cana-1616	367	12	detection	detection	NOUN
cana-1616	367	13	of	of	ADP
cana-1616	367	14	liver	liver	NOUN
cana-1616	367	15	disorders	disorder	NOUN
cana-1616	367	16	using	use	VERB
cana-1616	367	17	hybrid	hybrid	ADJ
cana-1616	367	18	soft	soft	ADJ
cana-1616	367	19	computing	computing	NOUN
cana-1616	367	20	techniques	technique	NOUN
cana-1616	367	21	for	for	ADP
cana-1616	367	22	optimal	optimal	ADJ
cana-1616	367	23	feature	feature	NOUN
cana-1616	367	24	selection	selection	NOUN
cana-1616	367	25	and	and	CCONJ
cana-1616	367	26	classification	classification	NOUN
cana-1616	367	27	,	,	PUNCT
cana-1616	367	28	"	"	PUNCT
cana-1616	367	29	concurrency	concurrency	NOUN
cana-1616	367	30	comput	comput	NOUN
cana-1616	367	31	.	.	PUNCT
cana-1616	367	32	:	:	PUNCT
cana-1616	368	1	pract	pract	PROPN
cana-1616	368	2	.	.	PUNCT
cana-1616	369	1	exp	exp	PROPN
cana-1616	369	2	.	.	PROPN
cana-1616	369	3	,	,	PUNCT
cana-1616	369	4	vol	vol	NOUN
cana-1616	369	5	.	.	PROPN
cana-1616	370	1	35	35	NUM
cana-1616	370	2	,	,	PUNCT
cana-1616	370	3	no	no	INTJ
cana-1616	370	4	.	.	NOUN
cana-1616	370	5	6	6	NUM
cana-1616	370	6	,	,	PUNCT
cana-1616	370	7	pp	pp	ADJ
cana-1616	370	8	.	.	PUNCT
cana-1616	371	1	1	1	NUM
cana-1616	371	2	-	-	SYM
cana-1616	371	3	1	1	NUM
cana-1616	371	4	,	,	PUNCT
cana-1616	371	5	2023	2023	NUM
cana-1616	371	6	.	.	PUNCT
cana-1616	372	1	21	21	NUM
cana-1616	372	2	.	.	X
cana-1616	372	3	d.	d.	PROPN
cana-1616	372	4	bhupathi	bhupathi	PROPN
cana-1616	372	5	,	,	PUNCT
cana-1616	372	6	c.	c.	PROPN
cana-1616	372	7	n.	n.	PROPN
cana-1616	372	8	l.	l.	PROPN
cana-1616	372	9	tan	tan	PROPN
cana-1616	372	10	,	,	PUNCT
cana-1616	372	11	s.	s.	PROPN
cana-1616	372	12	s.	s.	PROPN
cana-1616	372	13	tirumala	tirumala	PROPN
cana-1616	372	14	,	,	PUNCT
cana-1616	372	15	and	and	CCONJ
cana-1616	372	16	s.	s.	PROPN
cana-1616	372	17	ray	ray	PROPN
cana-1616	372	18	,	,	PUNCT
cana-1616	372	19	"	"	PUNCT
cana-1616	372	20	liver	liver	NOUN
cana-1616	372	21	disease	disease	NOUN
cana-1616	372	22	detection	detection	NOUN
cana-1616	372	23	using	use	VERB
cana-1616	372	24	machine	machine	NOUN
cana-1616	372	25	learning	learning	NOUN
cana-1616	372	26	techniques	technique	NOUN
cana-1616	372	27	,	,	PUNCT
cana-1616	372	28	"	"	PUNCT
cana-1616	372	29	2022	2022	NUM
cana-1616	372	30	.	.	PUNCT
cana-1616	373	1	22	22	NUM
cana-1616	373	2	.	.	PUNCT
cana-1616	373	3	b.	b.	PROPN
cana-1616	373	4	h.	h.	PROPN
cana-1616	373	5	al	al	PROPN
cana-1616	373	6	telaq	telaq	PROPN
cana-1616	373	7	and	and	CCONJ
cana-1616	373	8	n.	n.	PROPN
cana-1616	373	9	hewahi	hewahi	PROPN
cana-1616	373	10	,	,	PUNCT
cana-1616	373	11	"	"	PUNCT
cana-1616	373	12	prediction	prediction	NOUN
cana-1616	373	13	of	of	ADP
cana-1616	373	14	liver	liver	NOUN
cana-1616	373	15	disease	disease	NOUN
cana-1616	373	16	using	use	VERB
cana-1616	373	17	machine	machine	NOUN
cana-1616	373	18	learning	learning	NOUN
cana-1616	373	19	models	model	NOUN
cana-1616	373	20	with	with	ADP
cana-1616	373	21	pca	pca	NOUN
cana-1616	373	22	,	,	PUNCT
cana-1616	373	23	"	"	PUNCT
cana-1616	373	24	in	in	ADP
cana-1616	373	25	2021	2021	NUM
cana-1616	373	26	int	int	NOUN
cana-1616	373	27	.	.	PUNCT
cana-1616	374	1	conf	conf	PROPN
cana-1616	374	2	.	.	PUNCT
cana-1616	375	1	data	data	PROPN
cana-1616	375	2	anal	anal	PROPN
cana-1616	375	3	.	.	PUNCT
cana-1616	376	1	bus	bus	NOUN
cana-1616	376	2	.	.	PUNCT
cana-1616	377	1	ind	ind	PROPN
cana-1616	377	2	.	.	PUNCT
cana-1616	378	1	(	(	PUNCT
cana-1616	378	2	icdabi	icdabi	NOUN
cana-1616	378	3	)	)	PUNCT
cana-1616	378	4	,	,	PUNCT
cana-1616	378	5	sakheer	sakheer	NOUN
cana-1616	378	6	,	,	PUNCT
cana-1616	378	7	bahrain	bahrain	NOUN
cana-1616	378	8	,	,	PUNCT
cana-1616	378	9	2021	2021	NUM
cana-1616	378	10	,	,	PUNCT
cana-1616	378	11	pp	pp	ADJ
cana-1616	378	12	.	.	PUNCT
cana-1616	379	1	250	250	NUM
cana-1616	379	2	-	-	SYM
cana-1616	379	3	254	254	NUM
cana-1616	379	4	,	,	PUNCT
cana-1616	379	5	doi	doi	NOUN
cana-1616	379	6	:	:	PUNCT
cana-1616	379	7	10.1109	10.1109	NUM
cana-1616	379	8	/	/	SYM
cana-1616	379	9	icdabi53623.2021.9655897	icdabi53623.2021.9655897	NOUN
cana-1616	379	10	.	.	PROPN
cana-1616	380	1	23	23	NUM
cana-1616	380	2	.	.	PUNCT
cana-1616	380	3	r.	r.	PROPN
cana-1616	380	4	amin	amin	PROPN
cana-1616	380	5	,	,	PUNCT
cana-1616	380	6	s.	s.	PROPN
cana-1616	380	7	ahmed	ahmed	PROPN
cana-1616	380	8	,	,	PUNCT
cana-1616	380	9	t.	t.	PROPN
cana-1616	380	10	k.	k.	PROPN
cana-1616	380	11	khandaker	khandaker	PROPN
cana-1616	380	12	,	,	PUNCT
cana-1616	380	13	and	and	CCONJ
cana-1616	380	14	a.	a.	PROPN
cana-1616	380	15	s.	s.	PROPN
cana-1616	380	16	khan	khan	PROPN
cana-1616	380	17	,	,	PUNCT
cana-1616	380	18	"	"	PUNCT
cana-1616	380	19	prediction	prediction	NOUN
cana-1616	380	20	of	of	ADP
cana-1616	380	21	chronic	chronic	ADJ
cana-1616	380	22	liver	liver	NOUN
cana-1616	380	23	disease	disease	NOUN
cana-1616	380	24	patients	patient	NOUN
cana-1616	380	25	using	use	VERB
cana-1616	380	26	integrated	integrate	VERB
cana-1616	380	27	projection	projection	NOUN
cana-1616	380	28	based	base	VERB
cana-1616	380	29	statistical	statistical	ADJ
cana-1616	380	30	feature	feature	NOUN
cana-1616	380	31	extraction	extraction	NOUN
cana-1616	380	32	with	with	ADP
cana-1616	380	33	machine	machine	NOUN
cana-1616	380	34	learning	learning	NOUN
cana-1616	380	35	algorithms	algorithm	NOUN
cana-1616	380	36	,	,	PUNCT
cana-1616	380	37	"	"	PUNCT
cana-1616	380	38	informatics	informatic	NOUN
cana-1616	380	39	med	me	VERB
cana-1616	380	40	.	.	PUNCT
cana-1616	381	1	unlocked	unlock	VERB
cana-1616	381	2	,	,	PUNCT
cana-1616	381	3	vol	vol	NOUN
cana-1616	381	4	.	.	PROPN
cana-1616	381	5	36	36	NUM
cana-1616	381	6	,	,	PUNCT
cana-1616	381	7	2023	2023	NUM
cana-1616	381	8	,	,	PUNCT
cana-1616	381	9	art	art	NOUN
cana-1616	381	10	.	.	PUNCT
cana-1616	382	1	no	no	INTJ
cana-1616	382	2	.	.	NOUN
cana-1616	383	1	101155	101155	NUM
cana-1616	383	2	.	.	PUNCT
cana-1616	384	1	24	24	NUM
cana-1616	384	2	.	.	PUNCT
cana-1616	384	3	m.	m.	NOUN
cana-1616	384	4	g.	g.	PROPN
cana-1616	384	5	lanjewar	lanjewar	PROPN
cana-1616	384	6	,	,	PUNCT
cana-1616	384	7	r.	r.	PROPN
cana-1616	384	8	v.	v.	PROPN
cana-1616	384	9	dixit	dixit	PROPN
cana-1616	384	10	,	,	PUNCT
cana-1616	384	11	s.	s.	PROPN
cana-1616	384	12	p.	p.	PROPN
cana-1616	384	13	wankhade	wankhade	NOUN
cana-1616	384	14	,	,	PUNCT
cana-1616	384	15	and	and	CCONJ
cana-1616	384	16	k.	k.	PROPN
cana-1616	384	17	g.	g.	PROPN
cana-1616	384	18	parlewar	parlewar	PROPN
cana-1616	384	19	,	,	PUNCT
cana-1616	384	20	"	"	PUNCT
cana-1616	384	21	cnn	cnn	PROPN
cana-1616	384	22	with	with	ADP
cana-1616	384	23	machine	machine	NOUN
cana-1616	384	24	learning	learn	VERB
cana-1616	384	25	approaches	approach	NOUN
cana-1616	384	26	using	use	VERB
cana-1616	384	27	extratreesclassifier	extratreesclassifier	ADV
cana-1616	384	28	and	and	CCONJ
cana-1616	384	29	mrmr	mrmr	PROPN
cana-1616	384	30	feature	feature	NOUN
cana-1616	384	31	selection	selection	NOUN
cana-1616	384	32	techniques	technique	NOUN
cana-1616	384	33	to	to	PART
cana-1616	384	34	detect	detect	VERB
cana-1616	384	35	liver	liver	NOUN
cana-1616	384	36	diseases	disease	NOUN
cana-1616	384	37	on	on	ADP
cana-1616	384	38	cloud	cloud	NOUN
cana-1616	384	39	,	,	PUNCT
cana-1616	384	40	"	"	PUNCT
cana-1616	384	41	cluster	cluster	NOUN
cana-1616	384	42	comput	comput	NOUN
cana-1616	384	43	.	.	PUNCT
cana-1616	384	44	,	,	PUNCT
cana-1616	384	45	vol	vol	NOUN
cana-1616	384	46	.	.	PROPN
cana-1616	384	47	26	26	NUM
cana-1616	384	48	,	,	PUNCT
cana-1616	384	49	no	no	INTJ
cana-1616	384	50	.	.	NOUN
cana-1616	384	51	6	6	NUM
cana-1616	384	52	,	,	PUNCT
cana-1616	384	53	pp	pp	ADJ
cana-1616	384	54	.	.	PUNCT
cana-1616	384	55	3657	3657	NUM
cana-1616	384	56	-	-	SYM
cana-1616	384	57	3672	3672	NUM
cana-1616	384	58	,	,	PUNCT
cana-1616	384	59	2023	2023	NUM
cana-1616	384	60	.	.	PUNCT
cana-1616	385	1	25	25	NUM
cana-1616	385	2	.	.	PUNCT
cana-1616	385	3	w.	w.	PROPN
cana-1616	385	4	m.	m.	PROPN
cana-1616	385	5	shaban	shaban	PROPN
cana-1616	385	6	,	,	PUNCT
cana-1616	385	7	"	"	PUNCT
cana-1616	385	8	early	early	ADJ
cana-1616	385	9	diagnosis	diagnosis	NOUN
cana-1616	385	10	of	of	ADP
cana-1616	385	11	liver	liver	NOUN
cana-1616	385	12	disease	disease	NOUN
cana-1616	385	13	using	use	VERB
cana-1616	385	14	improved	improve	VERB
cana-1616	385	15	binary	binary	ADJ
cana-1616	385	16	butterfly	butterfly	NOUN
cana-1616	385	17	optimization	optimization	NOUN
cana-1616	385	18	and	and	CCONJ
cana-1616	385	19	machine	machine	NOUN
cana-1616	385	20	learning	learning	NOUN
cana-1616	385	21	algorithms	algorithm	NOUN
cana-1616	385	22	,	,	PUNCT
cana-1616	385	23	"	"	PUNCT
cana-1616	385	24	multimed	multime	VERB
cana-1616	385	25	.	.	PUNCT
cana-1616	386	1	tools	tool	NOUN
cana-1616	386	2	appl	appl	PROPN
cana-1616	386	3	.	.	PUNCT
cana-1616	386	4	,	,	PUNCT
cana-1616	386	5	vol	vol	NOUN
cana-1616	386	6	.	.	PROPN
cana-1616	386	7	83	83	NUM
cana-1616	386	8	,	,	PUNCT
cana-1616	386	9	no	no	INTJ
cana-1616	386	10	.	.	NOUN
cana-1616	386	11	10	10	NUM
cana-1616	386	12	,	,	PUNCT
cana-1616	386	13	pp	pp	ADJ
cana-1616	386	14	.	.	PUNCT
cana-1616	387	1	30867	30867	NUM
cana-1616	387	2	-	-	SYM
cana-1616	387	3	30895	30895	NUM
cana-1616	387	4	,	,	PUNCT
cana-1616	387	5	2024	2024	NUM
cana-1616	387	6	.	.	PUNCT
cana-1616	388	1	biographies	biography	NOUN
cana-1616	388	2	of	of	ADP
cana-1616	388	3	authors	author	NOUN
cana-1616	388	4	gurmeet	gurmeet	VERB
cana-1616	388	5	kaur	kaur	PROPN
cana-1616	388	6	saini	saini	PROPN
cana-1616	388	7	received	receive	VERB
cana-1616	388	8	b.tech	b.tech	ADV
cana-1616	388	9	and	and	CCONJ
cana-1616	388	10	m.tech	m.tech	NOUN
cana-1616	388	11	degrees	degree	NOUN
cana-1616	388	12	from	from	ADP
cana-1616	388	13	ct	ct	PROPN
cana-1616	388	14	group	group	NOUN
cana-1616	388	15	of	of	ADP
cana-1616	388	16	institutions	institution	NOUN
cana-1616	388	17	jalandhar	jalandhar	PROPN
cana-1616	388	18	and	and	CCONJ
cana-1616	388	19	cgc	cgc	PROPN
cana-1616	388	20	college	college	PROPN
cana-1616	388	21	of	of	ADP
cana-1616	388	22	engineering	engineering	PROPN
cana-1616	388	23	,	,	PUNCT
cana-1616	388	24	landran	landran	ADJ
cana-1616	388	25	,	,	PUNCT
cana-1616	388	26	india	india	PROPN
cana-1616	388	27	in	in	ADP
cana-1616	388	28	2014	2014	NUM
cana-1616	388	29	and	and	CCONJ
cana-1616	388	30	2016	2016	NUM
cana-1616	388	31	respectively	respectively	ADV
cana-1616	388	32	.	.	PUNCT
cana-1616	389	1	she	she	PRON
cana-1616	389	2	is	be	AUX
cana-1616	389	3	currently	currently	ADV
cana-1616	389	4	working	work	VERB
cana-1616	389	5	towards	towards	ADP
cana-1616	389	6	the	the	DET
cana-1616	389	7	ph.d	ph.d	PROPN
cana-1616	389	8	.	.	PUNCT
cana-1616	389	9	degree	degree	PROPN
cana-1616	389	10	from	from	ADP
cana-1616	389	11	the	the	DET
cana-1616	389	12	chandigarh	chandigarh	PROPN
cana-1616	389	13	university	university	NOUN
cana-1616	389	14	.	.	PUNCT
cana-1616	390	1	her	her	PRON
cana-1616	390	2	research	research	NOUN
cana-1616	390	3	interests	interest	NOUN
cana-1616	390	4	include	include	VERB
cana-1616	390	5	digital	digital	ADJ
cana-1616	390	6	image	image	NOUN
cana-1616	390	7	processing	processing	NOUN
cana-1616	390	8	,	,	PUNCT
cana-1616	390	9	machine	machine	NOUN
cana-1616	390	10	learning	learning	NOUN
cana-1616	390	11	.	.	PUNCT
cana-1616	391	1	she	she	PRON
cana-1616	391	2	can	can	AUX
cana-1616	391	3	be	be	AUX
cana-1616	391	4	contacted	contact	VERB
cana-1616	391	5	at	at	ADP
cana-1616	391	6	email	email	NOUN
cana-1616	391	7	:	:	PUNCT
cana-1616	391	8	gurmeetsaini02@gmail.com	gurmeetsaini02@gmail.com	PROPN
cana-1616	391	9	dr	dr	PROPN
cana-1616	391	10	.	.	PROPN
cana-1616	391	11	sachin	sachin	PROPN
cana-1616	391	12	ahuja	ahuja	PROPN
cana-1616	391	13	is	be	AUX
cana-1616	391	14	working	work	VERB
cana-1616	391	15	as	as	ADP
cana-1616	391	16	director	director	NOUN
cana-1616	391	17	in	in	ADP
cana-1616	391	18	chandigarh	chandigarh	PROPN
cana-1616	391	19	university	university	NOUN
cana-1616	391	20	.	.	PUNCT
cana-1616	392	1	he	he	PRON
cana-1616	392	2	holds	hold	VERB
cana-1616	392	3	a	a	DET
cana-1616	392	4	phd	phd	NOUN
cana-1616	392	5	in	in	ADP
cana-1616	392	6	data	datum	NOUN
cana-1616	392	7	mining	mining	NOUN
cana-1616	392	8	.	.	PUNCT
cana-1616	393	1	his	his	PRON
cana-1616	393	2	primary	primary	ADJ
cana-1616	393	3	research	research	NOUN
cana-1616	393	4	interests	interest	NOUN
cana-1616	393	5	are	be	AUX
cana-1616	393	6	in	in	ADP
cana-1616	393	7	the	the	DET
cana-1616	393	8	field	field	NOUN
cana-1616	393	9	of	of	ADP
cana-1616	393	10	educational	educational	ADJ
cana-1616	393	11	data	datum	NOUN
cana-1616	393	12	mining	mining	NOUN
cana-1616	393	13	.	.	PUNCT
cana-1616	394	1	apart	apart	ADV
cana-1616	394	2	from	from	ADP
cana-1616	394	3	data	datum	NOUN
cana-1616	394	4	mining	mining	NOUN
cana-1616	394	5	,	,	PUNCT
cana-1616	394	6	his	his	PRON
cana-1616	394	7	teaching	teaching	NOUN
cana-1616	394	8	interests	interest	NOUN
cana-1616	394	9	include	include	VERB
cana-1616	394	10	big	big	ADJ
cana-1616	394	11	data	datum	NOUN
cana-1616	394	12	,	,	PUNCT
cana-1616	394	13	relation	relation	NOUN
cana-1616	394	14	database	database	NOUN
cana-1616	394	15	and	and	CCONJ
cana-1616	394	16	procedural	procedural	ADJ
cana-1616	394	17	languages	language	NOUN
cana-1616	394	18	.	.	PUNCT
cana-1616	395	1	he	he	PRON
cana-1616	395	2	can	can	AUX
cana-1616	395	3	be	be	AUX
cana-1616	395	4	contacted	contact	VERB
cana-1616	395	5	at	at	ADP
cana-1616	395	6	sachinahuja11@gmail.com	sachinahuja11@gmail.com	PROPN
cana-1616	395	7	.	.	PUNCT
cana-1616	395	8	communications	communication	NOUN
cana-1616	395	9	on	on	ADP
cana-1616	395	10	applied	apply	VERB
cana-1616	395	11	nonlinear	nonlinear	ADJ
cana-1616	395	12	analysis	analysis	NOUN
cana-1616	395	13	issn	issn	NOUN
cana-1616	395	14	:	:	PUNCT
cana-1616	395	15	1074	1074	NUM
cana-1616	395	16	-	-	PUNCT
cana-1616	395	17	133x	133x	NUM
cana-1616	395	18	vol	vol	NOUN
cana-1616	395	19	31	31	NUM
cana-1616	395	20	no	no	NOUN
cana-1616	395	21	.	.	PUNCT
cana-1616	396	1	8s	8s	PROPN
cana-1616	396	2	(	(	PUNCT
cana-1616	396	3	2024	2024	NUM
cana-1616	396	4	)	)	PUNCT
cana-1616	396	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-1616	396	6	793	793	NUM
cana-1616	396	7	dr	dr	PROPN
cana-1616	396	8	.	.	PROPN
cana-1616	396	9	vishal	vishal	PROPN
cana-1616	396	10	bharti	bharti	PROPN
cana-1616	396	11	is	be	AUX
cana-1616	396	12	working	work	VERB
cana-1616	396	13	as	as	ADP
cana-1616	396	14	professor	professor	NOUN
cana-1616	396	15	and	and	CCONJ
cana-1616	396	16	additional	additional	ADJ
cana-1616	396	17	director	director	NOUN
cana-1616	396	18	at	at	ADP
cana-1616	396	19	chandigarh	chandigarh	PROPN
cana-1616	396	20	university	university	PROPN
cana-1616	396	21	,	,	PUNCT
cana-1616	396	22	mohali	mohali	PROPN
cana-1616	396	23	,	,	PUNCT
cana-1616	396	24	punjab	punjab	PROPN
cana-1616	396	25	.	.	PUNCT
cana-1616	397	1	he	he	PRON
cana-1616	397	2	completed	complete	VERB
cana-1616	397	3	his	his	PRON
cana-1616	397	4	ph.d	ph.d	NOUN
cana-1616	397	5	.	.	PUNCT
cana-1616	398	1	in	in	ADP
cana-1616	398	2	2016	2016	NUM
cana-1616	398	3	in	in	ADP
cana-1616	398	4	the	the	DET
cana-1616	398	5	area	area	NOUN
cana-1616	398	6	of	of	ADP
cana-1616	398	7	information	information	NOUN
cana-1616	398	8	security	security	NOUN
cana-1616	398	9	.	.	PUNCT
cana-1616	399	1	his	his	PRON
cana-1616	399	2	area	area	NOUN
cana-1616	399	3	of	of	ADP
cana-1616	399	4	specialization	specialization	NOUN
cana-1616	399	5	is	be	AUX
cana-1616	399	6	cyber	cyber	ADJ
cana-1616	399	7	security	security	NOUN
cana-1616	399	8	,	,	PUNCT
cana-1616	399	9	network	network	NOUN
cana-1616	399	10	security	security	NOUN
cana-1616	399	11	and	and	CCONJ
cana-1616	399	12	distributed	distributed	ADJ
cana-1616	399	13	computing	computing	NOUN
cana-1616	399	14	and	and	CCONJ
cana-1616	399	15	machine	machine	NOUN
cana-1616	399	16	learning	learning	NOUN
cana-1616	399	17	.	.	PUNCT
cana-1616	400	1	he	he	PRON
cana-1616	400	2	can	can	AUX
cana-1616	400	3	be	be	AUX
cana-1616	400	4	contacted	contact	VERB
cana-1616	400	5	at	at	ADP
cana-1616	400	6	mevishalbharti11@yahoo.in	mevishalbharti11@yahoo.in	PROPN