id	sid	tid	token	lemma	pos
cana-2865	1	1	communications	communication	NOUN
cana-2865	1	2	on	on	ADP
cana-2865	1	3	applied	apply	VERB
cana-2865	1	4	nonlinear	nonlinear	ADJ
cana-2865	1	5	analysis	analysis	NOUN
cana-2865	1	6	issn	issn	NOUN
cana-2865	1	7	:	:	PUNCT
cana-2865	1	8	1074	1074	NUM
cana-2865	1	9	-	-	PUNCT
cana-2865	1	10	133x	133x	NUM
cana-2865	1	11	vol	vol	NOUN
cana-2865	1	12	32	32	NUM
cana-2865	1	13	no	no	NOUN
cana-2865	1	14	.	.	PUNCT
cana-2865	2	1	4s	4s	NUM
cana-2865	2	2	(	(	PUNCT
cana-2865	2	3	2025	2025	NUM
cana-2865	2	4	)	)	PUNCT
cana-2865	2	5	469	469	NUM
cana-2865	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	2	7	firefly	firefly	NOUN
cana-2865	2	8	algorithm	algorithm	NOUN
cana-2865	2	9	-	-	PUNCT
cana-2865	2	10	based	base	VERB
cana-2865	2	11	feature	feature	NOUN
cana-2865	2	12	selection	selection	NOUN
cana-2865	2	13	for	for	ADP
cana-2865	2	14	accurate	accurate	ADJ
cana-2865	2	15	prediction	prediction	NOUN
cana-2865	2	16	of	of	ADP
cana-2865	2	17	major	major	ADJ
cana-2865	2	18	depressive	depressive	ADJ
cana-2865	2	19	disorder	disorder	NOUN
cana-2865	2	20	from	from	ADP
cana-2865	2	21	eeg	eeg	NOUN
cana-2865	2	22	signals	signal	NOUN
cana-2865	2	23	k	k	PROPN
cana-2865	2	24	padmaleela1	padmaleela1	PROPN
cana-2865	2	25	,	,	PUNCT
cana-2865	2	26	dr	dr	PROPN
cana-2865	2	27	.	.	PROPN
cana-2865	2	28	s	s	PART
cana-2865	2	29	aruna2	aruna2	PROPN
cana-2865	2	30	,	,	PUNCT
cana-2865	2	31	dr	dr	PROPN
cana-2865	2	32	.	.	PROPN
cana-2865	2	33	p	p	PROPN
cana-2865	2	34	rajesh	rajesh	PROPN
cana-2865	2	35	kumar3	kumar3	PROPN
cana-2865	3	1	1research	1research	NUM
cana-2865	3	2	scholar	scholar	NOUN
cana-2865	3	3	,	,	PUNCT
cana-2865	3	4	dept	dept	NOUN
cana-2865	3	5	.	.	PROPN
cana-2865	3	6	of	of	ADP
cana-2865	3	7	ece	ece	PROPN
cana-2865	3	8	,	,	PUNCT
cana-2865	3	9	auce	auce	NOUN
cana-2865	3	10	(	(	PUNCT
cana-2865	3	11	a	a	NOUN
cana-2865	3	12	)	)	PUNCT
cana-2865	3	13	,	,	PUNCT
cana-2865	3	14	andhra	andhra	PROPN
cana-2865	3	15	university	university	PROPN
cana-2865	3	16	,	,	PUNCT
cana-2865	3	17	visakhapatnam	visakhapatnam	PROPN
cana-2865	3	18	,	,	PUNCT
cana-2865	3	19	india	india	PROPN
cana-2865	3	20	2associate	2associate	PROPN
cana-2865	3	21	professor	professor	NOUN
cana-2865	3	22	&	&	CCONJ
cana-2865	3	23	head	head	PROPN
cana-2865	3	24	,	,	PUNCT
cana-2865	3	25	dept	dept	NOUN
cana-2865	3	26	.	.	PROPN
cana-2865	3	27	of	of	ADP
cana-2865	3	28	ece	ece	PROPN
cana-2865	3	29	,	,	PUNCT
cana-2865	3	30	aucew	aucew	PROPN
cana-2865	3	31	,	,	PUNCT
cana-2865	3	32	andhra	andhra	PROPN
cana-2865	3	33	university	university	PROPN
cana-2865	3	34	,	,	PUNCT
cana-2865	3	35	visakhapatnam	visakhapatnam	PROPN
cana-2865	3	36	,	,	PUNCT
cana-2865	3	37	india	india	PROPN
cana-2865	3	38	3professor	3professor	NUM
cana-2865	3	39	,	,	PUNCT
cana-2865	3	40	dept	dept	NOUN
cana-2865	3	41	.	.	PROPN
cana-2865	3	42	of	of	ADP
cana-2865	3	43	ece	ece	PROPN
cana-2865	3	44	,	,	PUNCT
cana-2865	3	45	auce	auce	NOUN
cana-2865	3	46	(	(	PUNCT
cana-2865	3	47	a	a	NOUN
cana-2865	3	48	)	)	PUNCT
cana-2865	3	49	,	,	PUNCT
cana-2865	3	50	andhra	andhra	PROPN
cana-2865	3	51	university	university	PROPN
cana-2865	3	52	,	,	PUNCT
cana-2865	3	53	visakhapatnam	visakhapatnam	PROPN
cana-2865	3	54	,	,	PUNCT
cana-2865	3	55	india	india	PROPN
cana-2865	3	56	corresponding	corresponding	PROPN
cana-2865	3	57	author	author	NOUN
cana-2865	3	58	:	:	PUNCT
cana-2865	3	59	marypaddu@gmail.com	marypaddu@gmail.com	X
cana-2865	3	60	article	article	NOUN
cana-2865	3	61	history	history	NOUN
cana-2865	3	62	:	:	PUNCT
cana-2865	3	63	received	receive	VERB
cana-2865	3	64	:	:	PUNCT
cana-2865	3	65	29	29	NUM
cana-2865	3	66	-	-	SYM
cana-2865	3	67	09	09	NUM
cana-2865	3	68	-	-	PUNCT
cana-2865	3	69	2024	2024	NUM
cana-2865	3	70	revised	revise	VERB
cana-2865	3	71	:	:	PUNCT
cana-2865	3	72	27	27	NUM
cana-2865	3	73	-	-	SYM
cana-2865	3	74	11	11	NUM
cana-2865	3	75	-	-	PUNCT
cana-2865	3	76	2024	2024	NUM
cana-2865	3	77	accepted	accept	VERB
cana-2865	3	78	:	:	PUNCT
cana-2865	3	79	08	08	NUM
cana-2865	3	80	-	-	SYM
cana-2865	3	81	12	12	NUM
cana-2865	3	82	-	-	PUNCT
cana-2865	3	83	2024	2024	NUM
cana-2865	3	84	abstract	abstract	NOUN
cana-2865	3	85	:	:	PUNCT
cana-2865	3	86	around	around	ADP
cana-2865	3	87	the	the	DET
cana-2865	3	88	world	world	NOUN
cana-2865	3	89	,	,	PUNCT
cana-2865	3	90	billions	billion	NOUN
cana-2865	3	91	of	of	ADP
cana-2865	3	92	people	people	NOUN
cana-2865	3	93	suffer	suffer	VERB
cana-2865	3	94	from	from	ADP
cana-2865	3	95	major	major	ADJ
cana-2865	3	96	depressive	depressive	ADJ
cana-2865	3	97	disorder	disorder	NOUN
cana-2865	3	98	,	,	PUNCT
cana-2865	3	99	a	a	DET
cana-2865	3	100	complex	complex	ADJ
cana-2865	3	101	mental	mental	ADJ
cana-2865	3	102	health	health	NOUN
cana-2865	3	103	issue	issue	NOUN
cana-2865	3	104	.	.	PUNCT
cana-2865	4	1	most	most	ADJ
cana-2865	4	2	psychological	psychological	ADJ
cana-2865	4	3	assessments	assessment	NOUN
cana-2865	4	4	are	be	AUX
cana-2865	4	5	subjective	subjective	ADJ
cana-2865	4	6	,	,	PUNCT
cana-2865	4	7	and	and	CCONJ
cana-2865	4	8	symptoms	symptom	NOUN
cana-2865	4	9	can	can	AUX
cana-2865	4	10	fluctuate	fluctuate	VERB
cana-2865	4	11	widely	widely	ADV
cana-2865	4	12	,	,	PUNCT
cana-2865	4	13	making	make	VERB
cana-2865	4	14	the	the	DET
cana-2865	4	15	diagnosis	diagnosis	NOUN
cana-2865	4	16	of	of	ADP
cana-2865	4	17	major	major	ADJ
cana-2865	4	18	depressive	depressive	ADJ
cana-2865	4	19	disorder	disorder	NOUN
cana-2865	4	20	challenging	challenge	VERB
cana-2865	4	21	.	.	PUNCT
cana-2865	5	1	improved	improve	VERB
cana-2865	5	2	diagnostic	diagnostic	ADJ
cana-2865	5	3	accuracy	accuracy	NOUN
cana-2865	5	4	can	can	AUX
cana-2865	5	5	be	be	AUX
cana-2865	5	6	achieved	achieve	VERB
cana-2865	5	7	through	through	ADP
cana-2865	5	8	innovative	innovative	ADJ
cana-2865	5	9	approaches	approach	NOUN
cana-2865	5	10	like	like	ADP
cana-2865	5	11	machine	machine	NOUN
cana-2865	5	12	learning	learning	NOUN
cana-2865	5	13	and	and	CCONJ
cana-2865	5	14	optimization	optimization	NOUN
cana-2865	5	15	.	.	PUNCT
cana-2865	6	1	in	in	ADP
cana-2865	6	2	this	this	DET
cana-2865	6	3	study	study	NOUN
cana-2865	6	4	,	,	PUNCT
cana-2865	6	5	we	we	PRON
cana-2865	6	6	present	present	VERB
cana-2865	6	7	the	the	DET
cana-2865	6	8	firefly	firefly	NOUN
cana-2865	6	9	algorithm	algorithm	NOUN
cana-2865	6	10	,	,	PUNCT
cana-2865	6	11	a	a	DET
cana-2865	6	12	nature	nature	NOUN
cana-2865	6	13	-	-	PUNCT
cana-2865	6	14	inspired	inspire	VERB
cana-2865	6	15	metaheuristic	metaheuristic	ADJ
cana-2865	6	16	,	,	PUNCT
cana-2865	6	17	to	to	PART
cana-2865	6	18	enhance	enhance	VERB
cana-2865	6	19	feature	feature	NOUN
cana-2865	6	20	selection	selection	NOUN
cana-2865	6	21	and	and	CCONJ
cana-2865	6	22	classification	classification	NOUN
cana-2865	6	23	for	for	ADP
cana-2865	6	24	mdd	mdd	PROPN
cana-2865	6	25	diagnosis	diagnosis	NOUN
cana-2865	6	26	.	.	PUNCT
cana-2865	7	1	firefly	firefly	NOUN
cana-2865	7	2	-	-	PUNCT
cana-2865	7	3	adapted	adapt	VERB
cana-2865	7	4	artificial	artificial	ADJ
cana-2865	7	5	intelligence	intelligence	NOUN
cana-2865	7	6	identifies	identify	VERB
cana-2865	7	7	the	the	DET
cana-2865	7	8	most	most	ADV
cana-2865	7	9	relevant	relevant	ADJ
cana-2865	7	10	elements	element	NOUN
cana-2865	7	11	that	that	PRON
cana-2865	7	12	lead	lead	VERB
cana-2865	7	13	to	to	ADP
cana-2865	7	14	a	a	DET
cana-2865	7	15	correct	correct	ADJ
cana-2865	7	16	diagnosis	diagnosis	NOUN
cana-2865	7	17	,	,	PUNCT
cana-2865	7	18	adapting	adapt	VERB
cana-2865	7	19	to	to	ADP
cana-2865	7	20	the	the	DET
cana-2865	7	21	complexity	complexity	NOUN
cana-2865	7	22	of	of	ADP
cana-2865	7	23	mdd	mdd	PROPN
cana-2865	7	24	datasets	dataset	NOUN
cana-2865	7	25	.	.	PUNCT
cana-2865	8	1	using	use	VERB
cana-2865	8	2	real	real	ADJ
cana-2865	8	3	-	-	PUNCT
cana-2865	8	4	world	world	NOUN
cana-2865	8	5	mdd	mdd	PROPN
cana-2865	8	6	datasets	dataset	NOUN
cana-2865	8	7	,	,	PUNCT
cana-2865	8	8	we	we	PRON
cana-2865	8	9	evaluate	evaluate	VERB
cana-2865	8	10	the	the	DET
cana-2865	8	11	fa	fa	NOUN
cana-2865	8	12	's	's	PART
cana-2865	8	13	effectiveness	effectiveness	NOUN
cana-2865	8	14	compared	compare	VERB
cana-2865	8	15	to	to	ADP
cana-2865	8	16	conventional	conventional	ADJ
cana-2865	8	17	machine	machine	NOUN
cana-2865	8	18	learning	learning	NOUN
cana-2865	8	19	methods	method	NOUN
cana-2865	8	20	.	.	PUNCT
cana-2865	9	1	the	the	DET
cana-2865	9	2	results	result	NOUN
cana-2865	9	3	demonstrate	demonstrate	VERB
cana-2865	9	4	that	that	SCONJ
cana-2865	9	5	the	the	DET
cana-2865	9	6	firefly	firefly	NOUN
cana-2865	9	7	algorithm	algorithm	NOUN
cana-2865	9	8	is	be	AUX
cana-2865	9	9	a	a	DET
cana-2865	9	10	promising	promising	ADJ
cana-2865	9	11	approach	approach	NOUN
cana-2865	9	12	for	for	ADP
cana-2865	9	13	improved	improved	ADJ
cana-2865	9	14	mdd	mdd	PROPN
cana-2865	9	15	diagnosis	diagnosis	NOUN
cana-2865	9	16	,	,	PUNCT
cana-2865	9	17	as	as	SCONJ
cana-2865	9	18	it	it	PRON
cana-2865	9	19	reduces	reduce	VERB
cana-2865	9	20	computational	computational	ADJ
cana-2865	9	21	complexity	complexity	NOUN
cana-2865	9	22	and	and	CCONJ
cana-2865	9	23	boosts	boost	VERB
cana-2865	9	24	diagnostic	diagnostic	ADJ
cana-2865	9	25	accuracy	accuracy	NOUN
cana-2865	9	26	.	.	PUNCT
cana-2865	10	1	specifically	specifically	ADV
cana-2865	10	2	,	,	PUNCT
cana-2865	10	3	the	the	DET
cana-2865	10	4	fa	fa	NOUN
cana-2865	10	5	-	-	PUNCT
cana-2865	10	6	optimized	optimize	VERB
cana-2865	10	7	svm	svm	ADJ
cana-2865	10	8	model	model	NOUN
cana-2865	10	9	(	(	PUNCT
cana-2865	10	10	96.24	96.24	NUM
cana-2865	10	11	%	%	NOUN
cana-2865	10	12	)	)	PUNCT
cana-2865	10	13	achieved	achieve	VERB
cana-2865	10	14	the	the	DET
cana-2865	10	15	highest	high	ADJ
cana-2865	10	16	level	level	NOUN
cana-2865	10	17	of	of	ADP
cana-2865	10	18	diagnostic	diagnostic	ADJ
cana-2865	10	19	accuracy	accuracy	NOUN
cana-2865	10	20	,	,	PUNCT
cana-2865	10	21	followed	follow	VERB
cana-2865	10	22	by	by	ADP
cana-2865	10	23	knn	knn	PROPN
cana-2865	10	24	,	,	PUNCT
cana-2865	10	25	ann	ann	PROPN
cana-2865	10	26	,	,	PUNCT
cana-2865	10	27	qda	qda	PROPN
cana-2865	10	28	,	,	PUNCT
cana-2865	10	29	and	and	CCONJ
cana-2865	10	30	naïve	naïve	ADJ
cana-2865	10	31	bayes	bayes	NOUN
cana-2865	10	32	.	.	PUNCT
cana-2865	11	1	these	these	DET
cana-2865	11	2	findings	finding	NOUN
cana-2865	11	3	highlight	highlight	VERB
cana-2865	11	4	how	how	SCONJ
cana-2865	11	5	the	the	DET
cana-2865	11	6	fa	fa	NOUN
cana-2865	11	7	can	can	AUX
cana-2865	11	8	select	select	VERB
cana-2865	11	9	the	the	DET
cana-2865	11	10	most	most	ADV
cana-2865	11	11	suitable	suitable	ADJ
cana-2865	11	12	characteristics	characteristic	NOUN
cana-2865	11	13	to	to	PART
cana-2865	11	14	yield	yield	VERB
cana-2865	11	15	more	more	ADV
cana-2865	11	16	accurate	accurate	ADJ
cana-2865	11	17	and	and	CCONJ
cana-2865	11	18	efficient	efficient	ADJ
cana-2865	11	19	models	model	NOUN
cana-2865	11	20	,	,	PUNCT
cana-2865	11	21	potentially	potentially	ADV
cana-2865	11	22	enhancing	enhance	VERB
cana-2865	11	23	mdd	mdd	PROPN
cana-2865	11	24	diagnosis	diagnosis	NOUN
cana-2865	11	25	keywords	keyword	NOUN
cana-2865	11	26	:	:	PUNCT
cana-2865	11	27	major	major	ADJ
cana-2865	11	28	depressive	depressive	ADJ
cana-2865	11	29	disorder	disorder	NOUN
cana-2865	11	30	,	,	PUNCT
cana-2865	11	31	feature	feature	NOUN
cana-2865	11	32	selection	selection	NOUN
cana-2865	11	33	,	,	PUNCT
cana-2865	11	34	firefly	firefly	NOUN
cana-2865	11	35	algorithm	algorithm	NOUN
cana-2865	11	36	,	,	PUNCT
cana-2865	11	37	support	support	NOUN
cana-2865	11	38	vector	vector	NOUN
cana-2865	11	39	machine	machine	NOUN
cana-2865	11	40	,	,	PUNCT
cana-2865	11	41	eeg	eeg	PROPN
cana-2865	11	42	.	.	PROPN
cana-2865	12	1	1	1	NUM
cana-2865	12	2	.	.	X
cana-2865	12	3	introduction	introduction	NOUN
cana-2865	12	4	major	major	ADJ
cana-2865	12	5	depressive	depressive	ADJ
cana-2865	12	6	disorder	disorder	NOUN
cana-2865	12	7	is	be	AUX
cana-2865	12	8	a	a	DET
cana-2865	12	9	prevalent	prevalent	ADJ
cana-2865	12	10	and	and	CCONJ
cana-2865	12	11	debilitating	debilitate	VERB
cana-2865	12	12	mental	mental	ADJ
cana-2865	12	13	health	health	NOUN
cana-2865	12	14	condition	condition	NOUN
cana-2865	12	15	characterized	characterize	VERB
cana-2865	12	16	by	by	ADP
cana-2865	12	17	persistent	persistent	ADJ
cana-2865	12	18	low	low	ADJ
cana-2865	12	19	mood	mood	NOUN
cana-2865	12	20	,	,	PUNCT
cana-2865	12	21	loss	loss	NOUN
cana-2865	12	22	of	of	ADP
cana-2865	12	23	interest	interest	NOUN
cana-2865	12	24	in	in	ADP
cana-2865	12	25	daily	daily	ADJ
cana-2865	12	26	activities	activity	NOUN
cana-2865	12	27	,	,	PUNCT
cana-2865	12	28	and	and	CCONJ
cana-2865	12	29	a	a	DET
cana-2865	12	30	range	range	NOUN
cana-2865	12	31	of	of	ADP
cana-2865	12	32	physical	physical	ADJ
cana-2865	12	33	symptoms	symptom	NOUN
cana-2865	12	34	such	such	ADJ
cana-2865	12	35	as	as	ADP
cana-2865	12	36	changes	change	NOUN
cana-2865	12	37	in	in	ADP
cana-2865	12	38	appetite	appetite	NOUN
cana-2865	12	39	and	and	CCONJ
cana-2865	12	40	sleep	sleep	VERB
cana-2865	12	41	patterns	pattern	NOUN
cana-2865	12	42	.	.	PUNCT
cana-2865	13	1	it	it	PRON
cana-2865	13	2	is	be	AUX
cana-2865	13	3	a	a	DET
cana-2865	13	4	complex	complex	ADJ
cana-2865	13	5	disorder	disorder	NOUN
cana-2865	13	6	that	that	PRON
cana-2865	13	7	affects	affect	VERB
cana-2865	13	8	more	more	ADJ
cana-2865	13	9	than	than	ADP
cana-2865	13	10	264	264	NUM
cana-2865	13	11	million	million	NUM
cana-2865	13	12	people	people	NOUN
cana-2865	13	13	globally	globally	ADV
cana-2865	13	14	,	,	PUNCT
cana-2865	13	15	according	accord	VERB
cana-2865	13	16	to	to	ADP
cana-2865	13	17	the	the	DET
cana-2865	13	18	world	world	PROPN
cana-2865	13	19	health	health	NOUN
cana-2865	13	20	organization	organization	NOUN
cana-2865	13	21	[	[	X
cana-2865	13	22	1	1	NUM
cana-2865	13	23	]	]	PUNCT
cana-2865	13	24	,	,	PUNCT
cana-2865	13	25	making	make	VERB
cana-2865	13	26	it	it	PRON
cana-2865	13	27	a	a	DET
cana-2865	13	28	leading	lead	VERB
cana-2865	13	29	cause	cause	NOUN
cana-2865	13	30	of	of	ADP
cana-2865	13	31	disability	disability	NOUN
cana-2865	13	32	worldwide	worldwide	ADV
cana-2865	13	33	.	.	PUNCT
cana-2865	14	1	the	the	DET
cana-2865	14	2	profound	profound	ADJ
cana-2865	14	3	impact	impact	NOUN
cana-2865	14	4	of	of	ADP
cana-2865	14	5	major	major	ADJ
cana-2865	14	6	depressive	depressive	ADJ
cana-2865	14	7	disorder	disorder	NOUN
cana-2865	14	8	on	on	ADP
cana-2865	14	9	individuals	individual	NOUN
cana-2865	14	10	,	,	PUNCT
cana-2865	14	11	communities	community	NOUN
cana-2865	14	12	,	,	PUNCT
cana-2865	14	13	and	and	CCONJ
cana-2865	14	14	the	the	DET
cana-2865	14	15	community	community	NOUN
cana-2865	14	16	at	at	ADP
cana-2865	14	17	large	large	ADJ
cana-2865	14	18	emphasizes	emphasize	VERB
cana-2865	14	19	the	the	DET
cana-2865	14	20	crucial	crucial	ADJ
cana-2865	14	21	need	need	NOUN
cana-2865	14	22	for	for	ADP
cana-2865	14	23	correct	correct	ADJ
cana-2865	14	24	diagnosis	diagnosis	NOUN
cana-2865	14	25	and	and	CCONJ
cana-2865	14	26	successful	successful	ADJ
cana-2865	14	27	therapy	therapy	NOUN
cana-2865	14	28	approaches	approach	VERB
cana-2865	14	29	to	to	PART
cana-2865	14	30	address	address	VERB
cana-2865	14	31	this	this	DET
cana-2865	14	32	significant	significant	ADJ
cana-2865	14	33	public	public	ADJ
cana-2865	14	34	health	health	NOUN
cana-2865	14	35	challenge	challenge	NOUN
cana-2865	14	36	.	.	PUNCT
cana-2865	15	1	due	due	ADP
cana-2865	15	2	to	to	ADP
cana-2865	15	3	the	the	DET
cana-2865	15	4	diverse	diverse	ADJ
cana-2865	15	5	range	range	NOUN
cana-2865	15	6	of	of	ADP
cana-2865	15	7	signs	sign	NOUN
cana-2865	15	8	and	and	CCONJ
cana-2865	15	9	symptoms	symptom	NOUN
cana-2865	15	10	that	that	PRON
cana-2865	15	11	frequently	frequently	ADV
cana-2865	15	12	co	co	VERB
cana-2865	15	13	-	-	VERB
cana-2865	15	14	occur	occur	VERB
cana-2865	15	15	with	with	ADP
cana-2865	15	16	other	other	ADJ
cana-2865	15	17	mental	mental	ADJ
cana-2865	15	18	disorders	disorder	NOUN
cana-2865	15	19	,	,	PUNCT
cana-2865	15	20	accurately	accurately	ADV
cana-2865	15	21	and	and	CCONJ
cana-2865	15	22	promptly	promptly	ADV
cana-2865	15	23	diagnosing	diagnose	VERB
cana-2865	15	24	major	major	ADJ
cana-2865	15	25	depressive	depressive	ADJ
cana-2865	15	26	disorder	disorder	NOUN
cana-2865	15	27	is	be	AUX
cana-2865	15	28	crucial	crucial	ADJ
cana-2865	15	29	for	for	ADP
cana-2865	15	30	receiving	receive	VERB
cana-2865	15	31	effective	effective	ADJ
cana-2865	15	32	treatment	treatment	NOUN
cana-2865	15	33	.	.	PUNCT
cana-2865	16	1	machine	machine	NOUN
cana-2865	16	2	learning	learning	NOUN
cana-2865	16	3	-	-	PUNCT
cana-2865	16	4	based	base	VERB
cana-2865	16	5	approaches	approach	NOUN
cana-2865	16	6	have	have	AUX
cana-2865	16	7	become	become	VERB
cana-2865	16	8	invaluable	invaluable	ADJ
cana-2865	16	9	tools	tool	NOUN
cana-2865	16	10	in	in	ADP
cana-2865	16	11	mental	mental	ADJ
cana-2865	16	12	health	health	NOUN
cana-2865	16	13	diagnosis	diagnosis	NOUN
cana-2865	16	14	,	,	PUNCT
cana-2865	16	15	as	as	SCONJ
cana-2865	16	16	they	they	PRON
cana-2865	16	17	can	can	AUX
cana-2865	16	18	identify	identify	VERB
cana-2865	16	19	complex	complex	ADJ
cana-2865	16	20	patterns	pattern	NOUN
cana-2865	16	21	in	in	ADP
cana-2865	16	22	clinical	clinical	ADJ
cana-2865	16	23	trials	trial	NOUN
cana-2865	16	24	and	and	CCONJ
cana-2865	16	25	neuroimaging	neuroimaging	NOUN
cana-2865	16	26	data	datum	NOUN
cana-2865	17	1	[	[	X
cana-2865	17	2	2	2	NUM
cana-2865	17	3	-	-	SYM
cana-2865	17	4	3	3	NUM
cana-2865	17	5	]	]	PUNCT
cana-2865	17	6	.	.	PUNCT
cana-2865	18	1	communications	communication	NOUN
cana-2865	18	2	on	on	ADP
cana-2865	18	3	applied	apply	VERB
cana-2865	18	4	nonlinear	nonlinear	ADJ
cana-2865	18	5	analysis	analysis	NOUN
cana-2865	18	6	issn	issn	NOUN
cana-2865	18	7	:	:	PUNCT
cana-2865	18	8	1074	1074	NUM
cana-2865	18	9	-	-	PUNCT
cana-2865	18	10	133x	133x	NUM
cana-2865	18	11	vol	vol	NOUN
cana-2865	18	12	32	32	NUM
cana-2865	18	13	no	no	NOUN
cana-2865	18	14	.	.	PUNCT
cana-2865	19	1	4s	4s	NUM
cana-2865	19	2	(	(	PUNCT
cana-2865	19	3	2025	2025	NUM
cana-2865	19	4	)	)	PUNCT
cana-2865	19	5	470	470	NUM
cana-2865	19	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	19	7	the	the	DET
cana-2865	19	8	effectiveness	effectiveness	NOUN
cana-2865	19	9	of	of	ADP
cana-2865	19	10	applying	apply	VERB
cana-2865	19	11	classical	classical	ADJ
cana-2865	19	12	machine	machine	NOUN
cana-2865	19	13	learning	learn	VERB
cana-2865	19	14	techniques	technique	NOUN
cana-2865	19	15	,	,	PUNCT
cana-2865	19	16	such	such	ADJ
cana-2865	19	17	as	as	ADP
cana-2865	19	18	support	support	NOUN
cana-2865	19	19	vector	vector	NOUN
cana-2865	19	20	machines	machine	NOUN
cana-2865	19	21	(	(	PUNCT
cana-2865	19	22	svm	svm	PROPN
cana-2865	19	23	)	)	PUNCT
cana-2865	19	24	,	,	PUNCT
cana-2865	19	25	naïve	naïve	ADJ
cana-2865	19	26	bayes	bayes	PROPN
cana-2865	19	27	(	(	PUNCT
cana-2865	19	28	nb	nb	PROPN
cana-2865	19	29	)	)	PUNCT
cana-2865	19	30	,	,	PUNCT
cana-2865	19	31	k	k	X
cana-2865	19	32	-	-	PUNCT
cana-2865	19	33	nearest	near	ADJ
cana-2865	19	34	neighbors	neighbor	NOUN
cana-2865	19	35	(	(	PUNCT
cana-2865	19	36	knn	knn	PROPN
cana-2865	19	37	)	)	PUNCT
cana-2865	19	38	,	,	PUNCT
cana-2865	19	39	artificial	artificial	ADJ
cana-2865	19	40	neural	neural	ADJ
cana-2865	19	41	networks	network	NOUN
cana-2865	19	42	(	(	PUNCT
cana-2865	19	43	ann	ann	PROPN
cana-2865	19	44	)	)	PUNCT
cana-2865	19	45	,	,	PUNCT
cana-2865	19	46	quadratic	quadratic	ADJ
cana-2865	19	47	discriminant	discriminant	ADJ
cana-2865	19	48	analysis	analysis	NOUN
cana-2865	19	49	(	(	PUNCT
cana-2865	19	50	qda	qda	NOUN
cana-2865	19	51	)	)	PUNCT
cana-2865	19	52	,	,	PUNCT
cana-2865	19	53	and	and	CCONJ
cana-2865	19	54	knn	knn	PROPN
cana-2865	19	55	,	,	PUNCT
cana-2865	19	56	to	to	ADP
cana-2865	19	57	mdd	mdd	PROPN
cana-2865	19	58	identification	identification	NOUN
cana-2865	19	59	has	have	AUX
cana-2865	19	60	been	be	AUX
cana-2865	19	61	observed	observe	VERB
cana-2865	19	62	to	to	ADP
cana-2865	19	63	varying	vary	VERB
cana-2865	19	64	degrees	degree	NOUN
cana-2865	19	65	[	[	X
cana-2865	19	66	4	4	NUM
cana-2865	19	67	-	-	SYM
cana-2865	19	68	6	6	NUM
cana-2865	19	69	]	]	PUNCT
cana-2865	19	70	.	.	PUNCT
cana-2865	20	1	on	on	ADP
cana-2865	20	2	the	the	DET
cana-2865	20	3	other	other	ADJ
cana-2865	20	4	hand	hand	NOUN
cana-2865	20	5	,	,	PUNCT
cana-2865	20	6	a	a	DET
cana-2865	20	7	lot	lot	NOUN
cana-2865	20	8	of	of	ADP
cana-2865	20	9	the	the	DET
cana-2865	20	10	way	way	NOUN
cana-2865	20	11	that	that	PRON
cana-2865	20	12	those	those	DET
cana-2865	20	13	designs	design	NOUN
cana-2865	20	14	work	work	NOUN
cana-2865	20	15	is	be	AUX
cana-2865	20	16	based	base	VERB
cana-2865	20	17	on	on	ADP
cana-2865	20	18	the	the	DET
cana-2865	20	19	caliber	caliber	NOUN
cana-2865	20	20	of	of	ADP
cana-2865	20	21	the	the	DET
cana-2865	20	22	features	feature	NOUN
cana-2865	20	23	that	that	PRON
cana-2865	20	24	are	be	AUX
cana-2865	20	25	utilized	utilize	VERB
cana-2865	20	26	,	,	PUNCT
cana-2865	20	27	and	and	CCONJ
cana-2865	20	28	working	work	VERB
cana-2865	20	29	with	with	ADP
cana-2865	20	30	high	high	ADJ
cana-2865	20	31	-	-	PUNCT
cana-2865	20	32	dimensional	dimensional	ADJ
cana-2865	20	33	datasets	dataset	NOUN
cana-2865	20	34	might	might	AUX
cana-2865	20	35	render	render	VERB
cana-2865	20	36	them	they	PRON
cana-2865	20	37	less	less	ADV
cana-2865	20	38	accurate	accurate	ADJ
cana-2865	20	39	.	.	PUNCT
cana-2865	21	1	in	in	ADP
cana-2865	21	2	this	this	DET
cana-2865	21	3	scenario	scenario	NOUN
cana-2865	21	4	,	,	PUNCT
cana-2865	21	5	feature	feature	NOUN
cana-2865	21	6	selection	selection	NOUN
cana-2865	21	7	methodologies	methodology	NOUN
cana-2865	21	8	that	that	PRON
cana-2865	21	9	goal	goal	NOUN
cana-2865	21	10	to	to	PART
cana-2865	21	11	lower	lower	VERB
cana-2865	21	12	the	the	DET
cana-2865	21	13	dimensionality	dimensionality	NOUN
cana-2865	21	14	of	of	ADP
cana-2865	21	15	the	the	DET
cana-2865	21	16	data	datum	NOUN
cana-2865	21	17	while	while	SCONJ
cana-2865	21	18	preserving	preserve	VERB
cana-2865	21	19	the	the	DET
cana-2865	21	20	most	most	ADV
cana-2865	21	21	valuable	valuable	ADJ
cana-2865	21	22	qualities	quality	NOUN
cana-2865	21	23	are	be	AUX
cana-2865	21	24	the	the	DET
cana-2865	21	25	only	only	ADJ
cana-2865	21	26	ways	way	NOUN
cana-2865	21	27	to	to	PART
cana-2865	21	28	increase	increase	VERB
cana-2865	21	29	the	the	DET
cana-2865	21	30	performance	performance	NOUN
cana-2865	21	31	of	of	ADP
cana-2865	21	32	machine	machine	NOUN
cana-2865	21	33	learning	learning	NOUN
cana-2865	21	34	models	model	NOUN
cana-2865	21	35	[	[	X
cana-2865	21	36	7	7	NUM
cana-2865	21	37	]	]	PUNCT
cana-2865	21	38	.	.	PUNCT
cana-2865	22	1	several	several	ADJ
cana-2865	22	2	industry	industry	NOUN
cana-2865	22	3	sectors	sector	NOUN
cana-2865	22	4	,	,	PUNCT
cana-2865	22	5	including	include	VERB
cana-2865	22	6	medical	medical	ADJ
cana-2865	22	7	diagnostics	diagnostic	NOUN
cana-2865	22	8	,	,	PUNCT
cana-2865	22	9	have	have	AUX
cana-2865	22	10	successfully	successfully	ADV
cana-2865	22	11	incorporated	incorporate	VERB
cana-2865	22	12	nature	nature	NOUN
cana-2865	22	13	-	-	PUNCT
cana-2865	22	14	inspired	inspire	VERB
cana-2865	22	15	optimization	optimization	NOUN
cana-2865	22	16	algorithms	algorithm	NOUN
cana-2865	22	17	for	for	ADP
cana-2865	22	18	feature	feature	NOUN
cana-2865	22	19	selection	selection	NOUN
cana-2865	22	20	,	,	PUNCT
cana-2865	22	21	involving	involve	VERB
cana-2865	22	22	genetic	genetic	ADJ
cana-2865	22	23	algorithms	algorithm	NOUN
cana-2865	22	24	(	(	PUNCT
cana-2865	22	25	ga	ga	NOUN
cana-2865	22	26	)	)	PUNCT
cana-2865	22	27	,	,	PUNCT
cana-2865	22	28	particle	particle	NOUN
cana-2865	22	29	swarm	swarm	NOUN
cana-2865	22	30	optimization	optimization	NOUN
cana-2865	22	31	(	(	PUNCT
cana-2865	22	32	pso	pso	NOUN
cana-2865	22	33	)	)	PUNCT
cana-2865	22	34	,	,	PUNCT
cana-2865	22	35	and	and	CCONJ
cana-2865	22	36	the	the	DET
cana-2865	22	37	firefly	firefly	NOUN
cana-2865	22	38	algorithm	algorithm	NOUN
cana-2865	22	39	(	(	PUNCT
cana-2865	22	40	fa	fa	NOUN
cana-2865	22	41	)	)	PUNCT
cana-2865	23	1	[	[	X
cana-2865	23	2	8	8	NUM
cana-2865	23	3	-	-	SYM
cana-2865	23	4	9	9	NUM
cana-2865	23	5	]	]	PUNCT
cana-2865	23	6	.	.	PUNCT
cana-2865	24	1	in	in	ADP
cana-2865	24	2	particular	particular	ADJ
cana-2865	24	3	,	,	PUNCT
cana-2865	24	4	fa	fa	PROPN
cana-2865	24	5	has	have	AUX
cana-2865	24	6	shown	show	VERB
cana-2865	24	7	a	a	DET
cana-2865	24	8	pledge	pledge	NOUN
cana-2865	24	9	because	because	SCONJ
cana-2865	24	10	of	of	ADP
cana-2865	24	11	its	its	PRON
cana-2865	24	12	robustness	robustness	NOUN
cana-2865	24	13	in	in	ADP
cana-2865	24	14	avoiding	avoid	VERB
cana-2865	24	15	local	local	ADJ
cana-2865	24	16	optima	optima	NOUN
cana-2865	24	17	and	and	CCONJ
cana-2865	24	18	its	its	PRON
cana-2865	24	19	capacity	capacity	NOUN
cana-2865	24	20	to	to	PART
cana-2865	24	21	strike	strike	VERB
cana-2865	24	22	a	a	DET
cana-2865	24	23	state	state	NOUN
cana-2865	24	24	of	of	ADP
cana-2865	24	25	equilibrium	equilibrium	NOUN
cana-2865	24	26	between	between	ADP
cana-2865	24	27	extraction	extraction	NOUN
cana-2865	24	28	and	and	CCONJ
cana-2865	24	29	innovation	innovation	NOUN
cana-2865	24	30	[	[	X
cana-2865	24	31	10	10	NUM
cana-2865	24	32	]	]	PUNCT
cana-2865	24	33	.	.	PUNCT
cana-2865	25	1	in	in	ADP
cana-2865	25	2	order	order	NOUN
cana-2865	25	3	to	to	PART
cana-2865	25	4	boost	boost	VERB
cana-2865	25	5	the	the	DET
cana-2865	25	6	performance	performance	NOUN
cana-2865	25	7	of	of	ADP
cana-2865	25	8	five	five	NUM
cana-2865	25	9	prominent	prominent	ADJ
cana-2865	25	10	machine	machine	NOUN
cana-2865	25	11	learning	learning	NOUN
cana-2865	25	12	models	model	NOUN
cana-2865	25	13	—	—	PUNCT
cana-2865	25	14	knn	knn	PROPN
cana-2865	25	15	,	,	PUNCT
cana-2865	25	16	ann	ann	PROPN
cana-2865	25	17	,	,	PUNCT
cana-2865	25	18	naïve	naïve	ADJ
cana-2865	25	19	bayes	bayes	PROPN
cana-2865	25	20	,	,	PUNCT
cana-2865	25	21	qda	qda	NOUN
cana-2865	25	22	,	,	PUNCT
cana-2865	25	23	and	and	CCONJ
cana-2865	25	24	svm	svm	ADJ
cana-2865	25	25	—	—	PUNCT
cana-2865	25	26	this	this	DET
cana-2865	25	27	work	work	NOUN
cana-2865	25	28	examines	examine	VERB
cana-2865	25	29	the	the	DET
cana-2865	25	30	use	use	NOUN
cana-2865	25	31	of	of	ADP
cana-2865	25	32	fa	fa	NOUN
cana-2865	25	33	to	to	PART
cana-2865	25	34	optimize	optimize	VERB
cana-2865	25	35	feature	feature	NOUN
cana-2865	25	36	selection	selection	NOUN
cana-2865	25	37	for	for	ADP
cana-2865	25	38	mdd	mdd	PROPN
cana-2865	25	39	diagnosis	diagnosis	NOUN
cana-2865	25	40	.	.	PUNCT
cana-2865	26	1	an	an	DET
cana-2865	26	2	increasing	increase	VERB
cana-2865	26	3	number	number	NOUN
cana-2865	26	4	of	of	ADP
cana-2865	26	5	mental	mental	ADJ
cana-2865	26	6	health	health	NOUN
cana-2865	26	7	diagnostics	diagnostic	NOUN
cana-2865	26	8	,	,	PUNCT
cana-2865	26	9	including	include	VERB
cana-2865	26	10	mdd	mdd	PROPN
cana-2865	26	11	,	,	PUNCT
cana-2865	26	12	are	be	AUX
cana-2865	26	13	employing	employ	VERB
cana-2865	26	14	machine	machine	NOUN
cana-2865	26	15	learning	learn	VERB
cana-2865	26	16	techniques	technique	NOUN
cana-2865	26	17	.	.	PUNCT
cana-2865	27	1	knn	knn	PROPN
cana-2865	27	2	,	,	PUNCT
cana-2865	27	3	a	a	DET
cana-2865	27	4	simple	simple	ADJ
cana-2865	27	5	but	but	CCONJ
cana-2865	27	6	effective	effective	ADJ
cana-2865	27	7	algorithm	algorithm	NOUN
cana-2865	27	8	,	,	PUNCT
cana-2865	27	9	categorizes	categorize	VERB
cana-2865	27	10	incidents	incident	NOUN
cana-2865	27	11	based	base	VERB
cana-2865	27	12	on	on	ADP
cana-2865	27	13	the	the	DET
cana-2865	27	14	majority	majority	NOUN
cana-2865	27	15	class	class	NOUN
cana-2865	27	16	of	of	ADP
cana-2865	27	17	their	their	PRON
cana-2865	27	18	nearest	near	ADJ
cana-2865	27	19	neighbors	neighbor	NOUN
cana-2865	27	20	.	.	PUNCT
cana-2865	28	1	it	it	PRON
cana-2865	28	2	has	have	AUX
cana-2865	28	3	been	be	AUX
cana-2865	28	4	widely	widely	ADV
cana-2865	28	5	used	use	VERB
cana-2865	28	6	in	in	ADP
cana-2865	28	7	medical	medical	ADJ
cana-2865	28	8	applications	application	NOUN
cana-2865	28	9	but	but	CCONJ
cana-2865	28	10	is	be	AUX
cana-2865	28	11	sensitive	sensitive	ADJ
cana-2865	28	12	to	to	ADP
cana-2865	28	13	irrelevant	irrelevant	ADJ
cana-2865	28	14	features	feature	NOUN
cana-2865	28	15	and	and	CCONJ
cana-2865	28	16	the	the	DET
cana-2865	28	17	selection	selection	NOUN
cana-2865	28	18	of	of	ADP
cana-2865	28	19	k	k	PROPN
cana-2865	29	1	[	[	X
cana-2865	29	2	11	11	NUM
cana-2865	29	3	-	-	SYM
cana-2865	29	4	12	12	NUM
cana-2865	29	5	]	]	PUNCT
cana-2865	29	6	.	.	PUNCT
cana-2865	30	1	ann	ann	PROPN
cana-2865	30	2	,	,	PUNCT
cana-2865	30	3	which	which	PRON
cana-2865	30	4	mimics	mimic	VERB
cana-2865	30	5	the	the	DET
cana-2865	30	6	structure	structure	NOUN
cana-2865	30	7	of	of	ADP
cana-2865	30	8	the	the	DET
cana-2865	30	9	human	human	ADJ
cana-2865	30	10	brain	brain	NOUN
cana-2865	30	11	,	,	PUNCT
cana-2865	30	12	can	can	AUX
cana-2865	30	13	model	model	VERB
cana-2865	30	14	complex	complex	ADJ
cana-2865	30	15	relationships	relationship	NOUN
cana-2865	30	16	between	between	ADP
cana-2865	30	17	inputs	input	NOUN
cana-2865	30	18	and	and	CCONJ
cana-2865	30	19	outputs	output	NOUN
cana-2865	30	20	but	but	CCONJ
cana-2865	30	21	requires	require	VERB
cana-2865	30	22	a	a	DET
cana-2865	30	23	large	large	ADJ
cana-2865	30	24	amount	amount	NOUN
cana-2865	30	25	of	of	ADP
cana-2865	30	26	data	datum	NOUN
cana-2865	30	27	and	and	CCONJ
cana-2865	30	28	can	can	AUX
cana-2865	30	29	suffer	suffer	VERB
cana-2865	30	30	from	from	ADP
cana-2865	30	31	overfitting	overfitte	VERB
cana-2865	30	32	[	[	X
cana-2865	30	33	13	13	NUM
cana-2865	30	34	]	]	PUNCT
cana-2865	30	35	.	.	PUNCT
cana-2865	31	1	naïve	naïve	ADJ
cana-2865	31	2	bayes	bayes	PROPN
cana-2865	31	3	,	,	PUNCT
cana-2865	31	4	despite	despite	SCONJ
cana-2865	31	5	being	be	AUX
cana-2865	31	6	made	make	VERB
cana-2865	31	7	computationally	computationally	ADV
cana-2865	31	8	efficient	efficient	ADJ
cana-2865	31	9	,	,	PUNCT
cana-2865	31	10	assumes	assume	VERB
cana-2865	31	11	feature	feature	NOUN
cana-2865	31	12	independence	independence	NOUN
cana-2865	31	13	,	,	PUNCT
cana-2865	31	14	which	which	PRON
cana-2865	31	15	is	be	AUX
cana-2865	31	16	rarely	rarely	ADV
cana-2865	31	17	the	the	DET
cana-2865	31	18	case	case	NOUN
cana-2865	31	19	in	in	ADP
cana-2865	31	20	complex	complex	ADJ
cana-2865	31	21	disorders	disorder	NOUN
cana-2865	31	22	as	as	ADP
cana-2865	31	23	mdd	mdd	PROPN
cana-2865	31	24	[	[	X
cana-2865	31	25	14	14	NUM
cana-2865	31	26	-	-	SYM
cana-2865	31	27	15	15	NUM
cana-2865	31	28	]	]	PUNCT
cana-2865	31	29	.	.	PUNCT
cana-2865	32	1	the	the	DET
cana-2865	32	2	quadratic	quadratic	ADJ
cana-2865	32	3	classifier	classifier	NOUN
cana-2865	32	4	,	,	PUNCT
cana-2865	32	5	or	or	CCONJ
cana-2865	32	6	qda	qda	PROPN
cana-2865	32	7	,	,	PUNCT
cana-2865	32	8	can	can	AUX
cana-2865	32	9	be	be	AUX
cana-2865	32	10	sensitive	sensitive	ADJ
cana-2865	32	11	to	to	ADP
cana-2865	32	12	noisy	noisy	ADJ
cana-2865	32	13	data	datum	NOUN
cana-2865	32	14	,	,	PUNCT
cana-2865	32	15	but	but	CCONJ
cana-2865	32	16	it	it	PRON
cana-2865	32	17	is	be	AUX
cana-2865	32	18	useful	useful	ADJ
cana-2865	32	19	in	in	ADP
cana-2865	32	20	differentiating	differentiate	VERB
cana-2865	32	21	among	among	ADP
cana-2865	32	22	classes	class	NOUN
cana-2865	32	23	with	with	ADP
cana-2865	32	24	various	various	ADJ
cana-2865	32	25	covariances	covariance	NOUN
cana-2865	33	1	[	[	X
cana-2865	33	2	16	16	NUM
cana-2865	33	3	]	]	PUNCT
cana-2865	33	4	.	.	PUNCT
cana-2865	34	1	the	the	DET
cana-2865	34	2	program	program	NOUN
cana-2865	34	3	has	have	AUX
cana-2865	34	4	demonstrated	demonstrate	VERB
cana-2865	34	5	that	that	SCONJ
cana-2865	34	6	svm	svm	PROPN
cana-2865	34	7	performs	perform	VERB
cana-2865	34	8	well	well	ADV
cana-2865	34	9	in	in	ADP
cana-2865	34	10	mental	mental	ADJ
cana-2865	34	11	diagnoses	diagnosis	NOUN
cana-2865	34	12	,	,	PUNCT
cana-2865	34	13	such	such	ADJ
cana-2865	34	14	as	as	ADP
cana-2865	34	15	mdd	mdd	PROPN
cana-2865	34	16	[	[	X
cana-2865	34	17	17	17	NUM
cana-2865	34	18	]	]	PUNCT
cana-2865	34	19	,	,	PUNCT
cana-2865	34	20	and	and	CCONJ
cana-2865	34	21	has	have	AUX
cana-2865	34	22	been	be	AUX
cana-2865	34	23	particularly	particularly	ADV
cana-2865	34	24	successful	successful	ADJ
cana-2865	34	25	in	in	ADP
cana-2865	34	26	high	high	ADJ
cana-2865	34	27	-	-	PUNCT
cana-2865	34	28	dimensional	dimensional	ADJ
cana-2865	34	29	fields	field	NOUN
cana-2865	34	30	.	.	PUNCT
cana-2865	35	1	in	in	ADP
cana-2865	35	2	order	order	NOUN
cana-2865	35	3	to	to	PART
cana-2865	35	4	reduce	reduce	VERB
cana-2865	35	5	the	the	DET
cana-2865	35	6	dimensionality	dimensionality	NOUN
cana-2865	35	7	of	of	ADP
cana-2865	35	8	data	datum	NOUN
cana-2865	35	9	,	,	PUNCT
cana-2865	35	10	methods	method	NOUN
cana-2865	35	11	for	for	ADP
cana-2865	35	12	selecting	select	VERB
cana-2865	35	13	features	feature	NOUN
cana-2865	35	14	such	such	ADJ
cana-2865	35	15	as	as	ADP
cana-2865	35	16	recursive	recursive	ADJ
cana-2865	35	17	feature	feature	NOUN
cana-2865	35	18	elimination	elimination	NOUN
cana-2865	35	19	(	(	PUNCT
cana-2865	35	20	rfe	rfe	NOUN
cana-2865	35	21	)	)	PUNCT
cana-2865	35	22	and	and	CCONJ
cana-2865	35	23	principal	principal	ADJ
cana-2865	35	24	component	component	NOUN
cana-2865	35	25	analysis	analysis	NOUN
cana-2865	35	26	(	(	PUNCT
cana-2865	35	27	pca	pca	NOUN
cana-2865	35	28	)	)	PUNCT
cana-2865	35	29	are	be	AUX
cana-2865	35	30	widely	widely	ADV
cana-2865	35	31	applied	apply	VERB
cana-2865	35	32	;	;	PUNCT
cana-2865	35	33	yet	yet	CCONJ
cana-2865	35	34	they	they	PRON
cana-2865	35	35	might	might	AUX
cana-2865	35	36	be	be	AUX
cana-2865	35	37	computationally	computationally	ADV
cana-2865	35	38	more	more	ADV
cana-2865	35	39	expensive	expensive	ADJ
cana-2865	35	40	and	and	CCONJ
cana-2865	35	41	may	may	AUX
cana-2865	35	42	fail	fail	VERB
cana-2865	35	43	to	to	PART
cana-2865	35	44	recognize	recognize	VERB
cana-2865	35	45	minor	minor	ADJ
cana-2865	35	46	interactions	interaction	NOUN
cana-2865	35	47	between	between	ADP
cana-2865	35	48	features	feature	NOUN
cana-2865	35	49	[	[	X
cana-2865	35	50	1819	1819	NUM
cana-2865	35	51	]	]	PUNCT
cana-2865	35	52	.	.	PUNCT
cana-2865	36	1	different	different	ADJ
cana-2865	36	2	approaches	approach	NOUN
cana-2865	36	3	to	to	PART
cana-2865	36	4	feature	feature	NOUN
cana-2865	36	5	selection	selection	NOUN
cana-2865	36	6	have	have	AUX
cana-2865	36	7	been	be	AUX
cana-2865	36	8	offered	offer	VERB
cana-2865	36	9	by	by	ADP
cana-2865	36	10	metaheuristic	metaheuristic	ADJ
cana-2865	36	11	algorithms	algorithm	NOUN
cana-2865	36	12	such	such	ADJ
cana-2865	36	13	as	as	ADP
cana-2865	36	14	pso	pso	NOUN
cana-2865	36	15	and	and	CCONJ
cana-2865	36	16	ga	ga	PROPN
cana-2865	36	17	.	.	PUNCT
cana-2865	36	18	by	by	ADP
cana-2865	36	19	choosing	choose	VERB
cana-2865	36	20	the	the	DET
cana-2865	36	21	most	most	ADV
cana-2865	36	22	essential	essential	ADJ
cana-2865	36	23	features	feature	NOUN
cana-2865	36	24	,	,	PUNCT
cana-2865	36	25	these	these	DET
cana-2865	36	26	techniques	technique	NOUN
cana-2865	36	27	optimize	optimize	VERB
cana-2865	36	28	model	model	NOUN
cana-2865	36	29	performance	performance	NOUN
cana-2865	36	30	by	by	ADP
cana-2865	36	31	exploring	explore	VERB
cana-2865	36	32	the	the	DET
cana-2865	36	33	solution	solution	NOUN
cana-2865	36	34	space	space	NOUN
cana-2865	36	35	for	for	ADP
cana-2865	36	36	the	the	DET
cana-2865	36	37	ideal	ideal	ADJ
cana-2865	36	38	feature	feature	NOUN
cana-2865	36	39	subset	subset	VERB
cana-2865	37	1	[	[	X
cana-2865	37	2	20	20	NUM
cana-2865	37	3	-	-	SYM
cana-2865	37	4	21	21	NUM
cana-2865	37	5	]	]	PUNCT
cana-2865	37	6	.	.	PUNCT
cana-2865	38	1	fa	fa	PROPN
cana-2865	38	2	is	be	AUX
cana-2865	38	3	a	a	DET
cana-2865	38	4	fairly	fairly	ADV
cana-2865	38	5	recent	recent	ADJ
cana-2865	38	6	metaheuristic	metaheuristic	ADJ
cana-2865	38	7	,	,	PUNCT
cana-2865	38	8	modeled	model	VERB
cana-2865	38	9	upon	upon	SCONJ
cana-2865	38	10	the	the	DET
cana-2865	38	11	flashing	flash	VERB
cana-2865	38	12	activity	activity	NOUN
cana-2865	38	13	observed	observe	VERB
cana-2865	38	14	in	in	ADP
cana-2865	38	15	fireflies	firefly	NOUN
cana-2865	38	16	.	.	PUNCT
cana-2865	39	1	fa	fa	X
cana-2865	39	2	's	's	PART
cana-2865	39	3	greatest	great	ADJ
cana-2865	39	4	benefit	benefit	NOUN
cana-2865	39	5	is	be	AUX
cana-2865	39	6	its	its	PRON
cana-2865	39	7	ability	ability	NOUN
cana-2865	39	8	to	to	PART
cana-2865	39	9	achieve	achieve	VERB
cana-2865	39	10	a	a	DET
cana-2865	39	11	balance	balance	NOUN
cana-2865	39	12	across	across	ADP
cana-2865	39	13	local	local	ADJ
cana-2865	39	14	search	search	NOUN
cana-2865	39	15	and	and	CCONJ
cana-2865	39	16	global	global	ADJ
cana-2865	39	17	exploration	exploration	NOUN
cana-2865	39	18	,	,	PUNCT
cana-2865	39	19	thereby	thereby	ADV
cana-2865	39	20	minimizing	minimize	VERB
cana-2865	39	21	the	the	DET
cana-2865	39	22	likelihood	likelihood	NOUN
cana-2865	39	23	of	of	ADP
cana-2865	39	24	it	it	PRON
cana-2865	39	25	becoming	become	VERB
cana-2865	39	26	stuck	stuck	ADJ
cana-2865	39	27	in	in	ADP
cana-2865	39	28	local	local	ADJ
cana-2865	39	29	optima	optima	NOUN
cana-2865	40	1	[	[	X
cana-2865	40	2	22	22	NUM
cana-2865	40	3	]	]	PUNCT
cana-2865	40	4	.	.	PUNCT
cana-2865	41	1	2	2	X
cana-2865	41	2	.	.	X
cana-2865	41	3	objectives	objective	NOUN
cana-2865	41	4	as	as	SCONJ
cana-2865	41	5	discussed	discuss	VERB
cana-2865	41	6	in	in	ADP
cana-2865	41	7	section	section	NOUN
cana-2865	41	8	1	1	NUM
cana-2865	41	9	,	,	PUNCT
cana-2865	41	10	recent	recent	ADJ
cana-2865	41	11	work	work	NOUN
cana-2865	41	12	has	have	AUX
cana-2865	41	13	proven	prove	VERB
cana-2865	41	14	that	that	SCONJ
cana-2865	41	15	fa	fa	PROPN
cana-2865	41	16	may	may	AUX
cana-2865	41	17	be	be	AUX
cana-2865	41	18	helpful	helpful	ADJ
cana-2865	41	19	for	for	ADP
cana-2865	41	20	improving	improve	VERB
cana-2865	41	21	feature	feature	NOUN
cana-2865	41	22	selection	selection	NOUN
cana-2865	41	23	in	in	ADP
cana-2865	41	24	several	several	ADJ
cana-2865	41	25	kinds	kind	NOUN
cana-2865	41	26	of	of	ADP
cana-2865	41	27	classification	classification	NOUN
cana-2865	41	28	applications	application	NOUN
cana-2865	41	29	,	,	PUNCT
cana-2865	41	30	such	such	ADJ
cana-2865	41	31	as	as	ADP
cana-2865	41	32	bioinformatics	bioinformatics	NOUN
cana-2865	41	33	,	,	PUNCT
cana-2865	41	34	medical	medical	ADJ
cana-2865	41	35	diagnosis	diagnosis	NOUN
cana-2865	41	36	,	,	PUNCT
cana-2865	41	37	and	and	CCONJ
cana-2865	41	38	images	image	NOUN
cana-2865	41	39	being	be	AUX
cana-2865	41	40	processed	process	VERB
cana-2865	41	41	[	[	X
cana-2865	41	42	23	23	NUM
cana-2865	41	43	]	]	PUNCT
cana-2865	42	1	[	[	X
cana-2865	42	2	24	24	NUM
cana-2865	42	3	]	]	PUNCT
cana-2865	42	4	.	.	PUNCT
cana-2865	43	1	its	its	PRON
cana-2865	43	2	usage	usage	NOUN
cana-2865	43	3	for	for	ADP
cana-2865	43	4	people	people	NOUN
cana-2865	43	5	with	with	ADP
cana-2865	43	6	mental	mental	ADJ
cana-2865	43	7	disorders	disorder	NOUN
cana-2865	43	8	,	,	PUNCT
cana-2865	43	9	especially	especially	ADV
cana-2865	43	10	those	those	PRON
cana-2865	43	11	characterized	characterize	VERB
cana-2865	43	12	by	by	ADP
cana-2865	43	13	major	major	ADJ
cana-2865	43	14	depression	depression	NOUN
cana-2865	43	15	(	(	PUNCT
cana-2865	43	16	mdd	mdd	PROPN
cana-2865	43	17	)	)	PUNCT
cana-2865	43	18	,	,	PUNCT
cana-2865	43	19	has	have	AUX
cana-2865	43	20	been	be	AUX
cana-2865	43	21	prohibited	prohibit	VERB
cana-2865	43	22	.	.	PUNCT
cana-2865	44	1	the	the	DET
cana-2865	44	2	present	present	ADJ
cana-2865	44	3	study	study	NOUN
cana-2865	44	4	fulfills	fulfill	VERB
cana-2865	44	5	this	this	DET
cana-2865	44	6	gap	gap	NOUN
cana-2865	44	7	by	by	ADP
cana-2865	44	8	optimizing	optimize	VERB
cana-2865	44	9	feature	feature	NOUN
cana-2865	44	10	selection	selection	NOUN
cana-2865	44	11	for	for	ADP
cana-2865	44	12	mdd	mdd	PROPN
cana-2865	44	13	diagnosis	diagnosis	NOUN
cana-2865	44	14	utilizing	utilize	VERB
cana-2865	44	15	fa	fa	PROPN
cana-2865	44	16	in	in	ADP
cana-2865	44	17	knn	knn	PROPN
cana-2865	44	18	,	,	PUNCT
cana-2865	44	19	ann	ann	PROPN
cana-2865	44	20	,	,	PUNCT
cana-2865	44	21	naïve	naïve	ADJ
cana-2865	44	22	bayes	bayes	PROPN
cana-2865	44	23	,	,	PUNCT
cana-2865	44	24	qda	qda	NOUN
cana-2865	44	25	,	,	PUNCT
cana-2865	44	26	and	and	CCONJ
cana-2865	44	27	communications	communication	NOUN
cana-2865	44	28	on	on	ADP
cana-2865	44	29	applied	apply	VERB
cana-2865	44	30	nonlinear	nonlinear	ADJ
cana-2865	44	31	analysis	analysis	NOUN
cana-2865	44	32	issn	issn	NOUN
cana-2865	44	33	:	:	PUNCT
cana-2865	44	34	1074	1074	NUM
cana-2865	44	35	-	-	PUNCT
cana-2865	44	36	133x	133x	NUM
cana-2865	44	37	vol	vol	NOUN
cana-2865	44	38	32	32	NUM
cana-2865	44	39	no	no	NOUN
cana-2865	44	40	.	.	PUNCT
cana-2865	45	1	4s	4s	NUM
cana-2865	45	2	(	(	PUNCT
cana-2865	45	3	2025	2025	NUM
cana-2865	45	4	)	)	PUNCT
cana-2865	45	5	471	471	NUM
cana-2865	45	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	45	7	svm	svm	ADJ
cana-2865	45	8	models	model	NOUN
cana-2865	45	9	.	.	PUNCT
cana-2865	46	1	3	3	X
cana-2865	46	2	.	.	X
cana-2865	46	3	materials	material	NOUN
cana-2865	46	4	&	&	CCONJ
cana-2865	46	5	methods	methods	PROPN
cana-2865	46	6	a.	a.	PROPN
cana-2865	46	7	data	data	PROPN
cana-2865	46	8	acquisition	acquisition	NOUN
cana-2865	46	9	and	and	CCONJ
cana-2865	46	10	pre	pre	ADJ
cana-2865	46	11	-	-	ADJ
cana-2865	46	12	processing	processing	NOUN
cana-2865	46	13	in	in	ADP
cana-2865	46	14	order	order	NOUN
cana-2865	46	15	to	to	PART
cana-2865	46	16	conduct	conduct	VERB
cana-2865	46	17	the	the	DET
cana-2865	46	18	study	study	NOUN
cana-2865	46	19	,	,	PUNCT
cana-2865	46	20	the	the	DET
cana-2865	46	21	researchers	researcher	NOUN
cana-2865	46	22	recruited	recruit	VERB
cana-2865	46	23	60	60	NUM
cana-2865	46	24	healthy	healthy	ADJ
cana-2865	46	25	control	control	NOUN
cana-2865	46	26	volunteers	volunteer	NOUN
cana-2865	46	27	,	,	PUNCT
cana-2865	46	28	which	which	PRON
cana-2865	46	29	included	include	VERB
cana-2865	46	30	34	34	NUM
cana-2865	46	31	people	people	NOUN
cana-2865	46	32	with	with	ADP
cana-2865	46	33	severe	severe	ADJ
cana-2865	46	34	depressive	depressive	ADJ
cana-2865	46	35	disorder	disorder	NOUN
cana-2865	46	36	(	(	PUNCT
cana-2865	46	37	17	17	NUM
cana-2865	46	38	women	woman	NOUN
cana-2865	46	39	and	and	CCONJ
cana-2865	46	40	17	17	NUM
cana-2865	46	41	males	male	NOUN
cana-2865	46	42	)	)	PUNCT
cana-2865	46	43	.	.	PUNCT
cana-2865	47	1	of	of	ADP
cana-2865	47	2	them	they	PRON
cana-2865	47	3	,	,	PUNCT
cana-2865	47	4	they	they	PRON
cana-2865	47	5	consisted	consist	VERB
cana-2865	47	6	of	of	ADP
cana-2865	47	7	21	21	NUM
cana-2865	47	8	men	man	NOUN
cana-2865	47	9	and	and	CCONJ
cana-2865	47	10	39	39	NUM
cana-2865	47	11	women	woman	NOUN
cana-2865	47	12	.	.	PUNCT
cana-2865	48	1	in	in	ADP
cana-2865	48	2	this	this	DET
cana-2865	48	3	experiment	experiment	NOUN
cana-2865	48	4	,	,	PUNCT
cana-2865	48	5	the	the	DET
cana-2865	48	6	eeg	eeg	NOUN
cana-2865	48	7	database	database	NOUN
cana-2865	48	8	constructed	construct	VERB
cana-2865	48	9	in	in	ADP
cana-2865	48	10	[	[	X
cana-2865	48	11	25	25	NUM
cana-2865	48	12	]	]	PUNCT
cana-2865	48	13	is	be	AUX
cana-2865	48	14	being	be	AUX
cana-2865	48	15	utilized	utilize	VERB
cana-2865	48	16	to	to	PART
cana-2865	48	17	figure	figure	VERB
cana-2865	48	18	out	out	ADP
cana-2865	48	19	the	the	DET
cana-2865	48	20	machine	machine	NOUN
cana-2865	48	21	learning	learn	VERB
cana-2865	48	22	techniques	technique	NOUN
cana-2865	48	23	.	.	PUNCT
cana-2865	49	1	the	the	DET
cana-2865	49	2	eeg	eeg	NOUN
cana-2865	49	3	recordings	recording	NOUN
cana-2865	49	4	are	be	AUX
cana-2865	49	5	displayed	display	VERB
cana-2865	49	6	in	in	ADP
cana-2865	49	7	figure	figure	NOUN
cana-2865	49	8	1	1	NUM
cana-2865	49	9	for	for	ADP
cana-2865	49	10	both	both	PRON
cana-2865	49	11	mdd	mdd	PROPN
cana-2865	49	12	subjects	subject	NOUN
cana-2865	49	13	&	&	CCONJ
cana-2865	49	14	healthy	healthy	ADJ
cana-2865	49	15	persons	person	NOUN
cana-2865	49	16	.	.	PUNCT
cana-2865	50	1	with	with	ADP
cana-2865	50	2	authorization	authorization	NOUN
cana-2865	50	3	from	from	ADP
cana-2865	50	4	malaysia	malaysia	PROPN
cana-2865	50	5	’s	’s	PART
cana-2865	50	6	hospital	hospital	PROPN
cana-2865	50	7	university	university	PROPN
cana-2865	50	8	ethics	ethic	NOUN
cana-2865	50	9	committee	committee	PROPN
cana-2865	50	10	,	,	PUNCT
cana-2865	50	11	the	the	DET
cana-2865	50	12	present	present	ADJ
cana-2865	50	13	investigation	investigation	NOUN
cana-2865	50	14	assures	assure	VERB
cana-2865	50	15	that	that	SCONJ
cana-2865	50	16	the	the	DET
cana-2865	50	17	research	research	NOUN
cana-2865	50	18	is	be	AUX
cana-2865	50	19	performed	perform	VERB
cana-2865	50	20	ethically	ethically	ADV
cana-2865	50	21	.	.	PUNCT
cana-2865	51	1	the	the	DET
cana-2865	51	2	donors	donor	NOUN
cana-2865	51	3	were	be	AUX
cana-2865	51	4	specifically	specifically	ADV
cana-2865	51	5	selected	select	VERB
cana-2865	51	6	based	base	VERB
cana-2865	51	7	on	on	ADP
cana-2865	51	8	their	their	PRON
cana-2865	51	9	lack	lack	NOUN
cana-2865	51	10	of	of	ADP
cana-2865	51	11	preceding	precede	VERB
cana-2865	51	12	medical	medical	ADJ
cana-2865	51	13	education	education	NOUN
cana-2865	51	14	,	,	PUNCT
cana-2865	51	15	history	history	NOUN
cana-2865	51	16	of	of	ADP
cana-2865	51	17	head	head	NOUN
cana-2865	51	18	trauma	trauma	NOUN
cana-2865	51	19	,	,	PUNCT
cana-2865	51	20	and	and	CCONJ
cana-2865	51	21	prescription	prescription	NOUN
cana-2865	51	22	medication	medication	NOUN
cana-2865	51	23	intake	intake	NOUN
cana-2865	51	24	in	in	ADP
cana-2865	51	25	order	order	NOUN
cana-2865	51	26	to	to	PART
cana-2865	51	27	greatly	greatly	ADV
cana-2865	51	28	reduce	reduce	VERB
cana-2865	51	29	the	the	DET
cana-2865	51	30	probability	probability	NOUN
cana-2865	51	31	for	for	ADP
cana-2865	51	32	confounding	confound	VERB
cana-2865	51	33	variables	variable	NOUN
cana-2865	51	34	.	.	PUNCT
cana-2865	52	1	in	in	ADP
cana-2865	52	2	an	an	DET
cana-2865	52	3	effort	effort	NOUN
cana-2865	52	4	to	to	PART
cana-2865	52	5	achieve	achieve	VERB
cana-2865	52	6	the	the	DET
cana-2865	52	7	greatest	great	ADJ
cana-2865	52	8	accuracy	accuracy	NOUN
cana-2865	52	9	of	of	ADP
cana-2865	52	10	physiological	physiological	ADJ
cana-2865	52	11	measurements	measurement	NOUN
cana-2865	52	12	,	,	PUNCT
cana-2865	52	13	the	the	DET
cana-2865	52	14	participants	participant	NOUN
cana-2865	52	15	were	be	AUX
cana-2865	52	16	advised	advise	VERB
cana-2865	52	17	to	to	PART
cana-2865	52	18	remain	remain	VERB
cana-2865	52	19	hydrated	hydrated	ADJ
cana-2865	52	20	for	for	ADP
cana-2865	52	21	a	a	DET
cana-2865	52	22	minimum	minimum	NOUN
cana-2865	52	23	of	of	ADP
cana-2865	52	24	two	two	NUM
cana-2865	52	25	hours	hour	NOUN
cana-2865	52	26	before	before	ADP
cana-2865	52	27	the	the	DET
cana-2865	52	28	experiment	experiment	NOUN
cana-2865	52	29	.	.	PUNCT
cana-2865	53	1	every	every	DET
cana-2865	53	2	participant	participant	NOUN
cana-2865	53	3	deliberately	deliberately	ADV
cana-2865	53	4	agreed	agree	VERB
cana-2865	53	5	to	to	PART
cana-2865	53	6	participate	participate	VERB
cana-2865	53	7	in	in	ADP
cana-2865	53	8	the	the	DET
cana-2865	53	9	research	research	NOUN
cana-2865	53	10	study	study	NOUN
cana-2865	53	11	by	by	ADP
cana-2865	53	12	writing	write	VERB
cana-2865	53	13	up	up	ADP
cana-2865	53	14	an	an	DET
cana-2865	53	15	informed	informed	ADJ
cana-2865	53	16	consent	consent	NOUN
cana-2865	53	17	form	form	NOUN
cana-2865	53	18	to	to	PART
cana-2865	53	19	receive	receive	VERB
cana-2865	53	20	an	an	DET
cana-2865	53	21	honorarium	honorarium	NOUN
cana-2865	53	22	of	of	ADP
cana-2865	53	23	rm	rm	PROPN
cana-2865	53	24	40	40	NUM
cana-2865	53	25	.	.	PUNCT
cana-2865	54	1	to	to	PART
cana-2865	54	2	ascertain	ascertain	VERB
cana-2865	54	3	the	the	DET
cana-2865	54	4	protection	protection	NOUN
cana-2865	54	5	of	of	ADP
cana-2865	54	6	the	the	DET
cana-2865	54	7	participant	participant	NOUN
cana-2865	54	8	's	's	PART
cana-2865	54	9	rights	right	NOUN
cana-2865	54	10	and	and	CCONJ
cana-2865	54	11	social	social	ADJ
cana-2865	54	12	services	service	NOUN
cana-2865	54	13	,	,	PUNCT
cana-2865	54	14	the	the	DET
cana-2865	54	15	study	study	NOUN
cana-2865	54	16	's	's	PART
cana-2865	54	17	design	design	NOUN
cana-2865	54	18	was	be	AUX
cana-2865	54	19	meticulously	meticulously	ADV
cana-2865	54	20	reviewed	review	VERB
cana-2865	54	21	and	and	CCONJ
cana-2865	54	22	approved	approve	VERB
cana-2865	54	23	by	by	ADP
cana-2865	54	24	the	the	DET
cana-2865	54	25	hospital	hospital	NOUN
cana-2865	54	26	university	university	PROPN
cana-2865	54	27	sains	sain	VERB
cana-2865	54	28	malaysia	malaysia	PROPN
cana-2865	54	29	's	's	PART
cana-2865	54	30	ethics	ethic	NOUN
cana-2865	54	31	council	council	PROPN
cana-2865	54	32	in	in	ADP
cana-2865	54	33	malaysia	malaysia	PROPN
cana-2865	54	34	.	.	PUNCT
cana-2865	55	1	b.	b.	PROPN
cana-2865	55	2	feature	feature	NOUN
cana-2865	55	3	extraction	extraction	NOUN
cana-2865	55	4	and	and	CCONJ
cana-2865	55	5	selection	selection	NOUN
cana-2865	55	6	eeg	eeg	NOUN
cana-2865	55	7	recordings	recording	NOUN
cana-2865	55	8	are	be	AUX
cana-2865	55	9	a	a	DET
cana-2865	55	10	broad	broad	ADJ
cana-2865	55	11	and	and	CCONJ
cana-2865	55	12	varied	varied	ADJ
cana-2865	55	13	resource	resource	NOUN
cana-2865	55	14	of	of	ADP
cana-2865	55	15	data	datum	NOUN
cana-2865	55	16	that	that	PRON
cana-2865	55	17	may	may	AUX
cana-2865	55	18	provide	provide	VERB
cana-2865	55	19	a	a	DET
cana-2865	55	20	significant	significant	ADJ
cana-2865	55	21	understanding	understanding	NOUN
cana-2865	55	22	of	of	ADP
cana-2865	55	23	the	the	DET
cana-2865	55	24	neurophysiological	neurophysiological	ADJ
cana-2865	55	25	features	feature	NOUN
cana-2865	55	26	of	of	ADP
cana-2865	55	27	serious	serious	ADJ
cana-2865	55	28	depressive	depressive	ADJ
cana-2865	55	29	disorder	disorder	NOUN
cana-2865	55	30	in	in	ADP
cana-2865	55	31	addition	addition	NOUN
cana-2865	55	32	to	to	ADP
cana-2865	55	33	related	related	ADJ
cana-2865	55	34	mental	mental	ADJ
cana-2865	55	35	and	and	CCONJ
cana-2865	55	36	neurological	neurological	ADJ
cana-2865	55	37	disorders	disorder	NOUN
cana-2865	55	38	.	.	PUNCT
cana-2865	56	1	in	in	ADP
cana-2865	56	2	order	order	NOUN
cana-2865	56	3	to	to	PART
cana-2865	56	4	use	use	VERB
cana-2865	56	5	this	this	DET
cana-2865	56	6	data	datum	NOUN
cana-2865	56	7	for	for	ADP
cana-2865	56	8	clinical	clinical	ADJ
cana-2865	56	9	and	and	CCONJ
cana-2865	56	10	diagnostic	diagnostic	ADJ
cana-2865	56	11	use	use	NOUN
cana-2865	56	12	,	,	PUNCT
cana-2865	56	13	it	it	PRON
cana-2865	56	14	is	be	AUX
cana-2865	56	15	critical	critical	ADJ
cana-2865	56	16	to	to	PART
cana-2865	56	17	extract	extract	VERB
cana-2865	56	18	an	an	DET
cana-2865	56	19	extensive	extensive	ADJ
cana-2865	56	20	variety	variety	NOUN
cana-2865	56	21	of	of	ADP
cana-2865	56	22	relevant	relevant	ADJ
cana-2865	56	23	traits	trait	NOUN
cana-2865	56	24	that	that	PRON
cana-2865	56	25	may	may	AUX
cana-2865	56	26	determine	determine	VERB
cana-2865	56	27	the	the	DET
cana-2865	56	28	complicated	complicated	ADJ
cana-2865	56	29	interactions	interaction	NOUN
cana-2865	56	30	and	and	CCONJ
cana-2865	56	31	underlying	underlie	VERB
cana-2865	56	32	patterns	pattern	NOUN
cana-2865	56	33	in	in	ADP
cana-2865	56	34	the	the	DET
cana-2865	56	35	eeg	eeg	PROPN
cana-2865	56	36	data	data	PROPN
cana-2865	56	37	.	.	PUNCT
cana-2865	57	1	figure	figure	VERB
cana-2865	57	2	1	1	NUM
cana-2865	57	3	:	:	PUNCT
cana-2865	57	4	patients	patient	NOUN
cana-2865	57	5	with	with	ADP
cana-2865	57	6	major	major	ADJ
cana-2865	57	7	depressive	depressive	ADJ
cana-2865	57	8	illness	illness	NOUN
cana-2865	57	9	and	and	CCONJ
cana-2865	57	10	healthy	healthy	ADJ
cana-2865	57	11	people	people	NOUN
cana-2865	57	12	(	(	PUNCT
cana-2865	57	13	hc	hc	NOUN
cana-2865	57	14	)	)	PUNCT
cana-2865	57	15	using	use	VERB
cana-2865	57	16	19	19	NUM
cana-2865	57	17	-	-	PUNCT
cana-2865	57	18	channel	channel	NOUN
cana-2865	57	19	eeg	eeg	NOUN
cana-2865	57	20	signals	signal	NOUN
cana-2865	57	21	.	.	PUNCT
cana-2865	58	1	a	a	DET
cana-2865	58	2	wide	wide	ADJ
cana-2865	58	3	range	range	NOUN
cana-2865	58	4	of	of	ADP
cana-2865	58	5	feature	feature	NOUN
cana-2865	58	6	extraction	extraction	NOUN
cana-2865	58	7	methods	method	NOUN
cana-2865	58	8	,	,	PUNCT
cana-2865	58	9	consisting	consist	VERB
cana-2865	58	10	of	of	ADP
cana-2865	58	11	statistical	statistical	ADJ
cana-2865	58	12	,	,	PUNCT
cana-2865	58	13	spectral	spectral	ADJ
cana-2865	58	14	,	,	PUNCT
cana-2865	58	15	and	and	CCONJ
cana-2865	58	16	wavelet	wavelet	NOUN
cana-2865	58	17	-	-	PUNCT
cana-2865	58	18	based	base	VERB
cana-2865	58	19	methodologies	methodology	NOUN
cana-2865	58	20	,	,	PUNCT
cana-2865	58	21	have	have	AUX
cana-2865	58	22	been	be	AUX
cana-2865	58	23	utilized	utilize	VERB
cana-2865	58	24	in	in	ADP
cana-2865	58	25	this	this	DET
cana-2865	58	26	investigation	investigation	NOUN
cana-2865	58	27	to	to	PART
cana-2865	58	28	accurately	accurately	ADV
cana-2865	58	29	represent	represent	VERB
cana-2865	58	30	the	the	DET
cana-2865	58	31	eeg	eeg	PROPN
cana-2865	58	32	data	datum	NOUN
cana-2865	58	33	.	.	PUNCT
cana-2865	59	1	the	the	DET
cana-2865	59	2	eeg	eeg	PROPN
cana-2865	59	3	signals	signal	NOUN
cana-2865	59	4	'	'	PART
cana-2865	59	5	variability	variability	NOUN
cana-2865	59	6	and	and	CCONJ
cana-2865	59	7	distributional	distributional	ADJ
cana-2865	59	8	properties	property	NOUN
cana-2865	59	9	are	be	AUX
cana-2865	59	10	shown	show	VERB
cana-2865	59	11	by	by	ADP
cana-2865	59	12	statistical	statistical	ADJ
cana-2865	59	13	metrics	metric	NOUN
cana-2865	59	14	which	which	PRON
cana-2865	59	15	comprise	comprise	VERB
cana-2865	59	16	the	the	DET
cana-2865	59	17	communications	communication	NOUN
cana-2865	59	18	on	on	ADP
cana-2865	59	19	applied	apply	VERB
cana-2865	59	20	nonlinear	nonlinear	ADJ
cana-2865	59	21	analysis	analysis	NOUN
cana-2865	59	22	issn	issn	NOUN
cana-2865	59	23	:	:	PUNCT
cana-2865	59	24	1074	1074	NUM
cana-2865	59	25	-	-	PUNCT
cana-2865	59	26	133x	133x	NUM
cana-2865	59	27	vol	vol	NOUN
cana-2865	59	28	32	32	NUM
cana-2865	59	29	no	no	NOUN
cana-2865	59	30	.	.	PUNCT
cana-2865	60	1	4s	4s	NUM
cana-2865	60	2	(	(	PUNCT
cana-2865	60	3	2025	2025	NUM
cana-2865	60	4	)	)	PUNCT
cana-2865	60	5	472	472	NUM
cana-2865	60	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	60	7	variance	variance	NOUN
cana-2865	60	8	,	,	PUNCT
cana-2865	60	9	mean	mean	INTJ
cana-2865	60	10	,	,	PUNCT
cana-2865	60	11	skewness	skewness	NOUN
cana-2865	60	12	,	,	PUNCT
cana-2865	60	13	and	and	CCONJ
cana-2865	60	14	kurtosis	kurtosis	NOUN
cana-2865	60	15	,	,	PUNCT
cana-2865	60	16	which	which	PRON
cana-2865	60	17	may	may	AUX
cana-2865	60	18	be	be	AUX
cana-2865	60	19	an	an	DET
cana-2865	60	20	indicator	indicator	NOUN
cana-2865	60	21	of	of	ADP
cana-2865	60	22	underlying	underlie	VERB
cana-2865	60	23	neurophysiological	neurophysiological	ADJ
cana-2865	60	24	abnormalities	abnormality	NOUN
cana-2865	60	25	linked	link	VERB
cana-2865	60	26	to	to	ADP
cana-2865	60	27	depression	depression	NOUN
cana-2865	60	28	[	[	X
cana-2865	60	29	26	26	NUM
cana-2865	60	30	]	]	PUNCT
cana-2865	60	31	.	.	PUNCT
cana-2865	61	1	the	the	DET
cana-2865	61	2	spectral	spectral	ADJ
cana-2865	61	3	properties	property	NOUN
cana-2865	61	4	,	,	PUNCT
cana-2865	61	5	such	such	ADJ
cana-2865	61	6	as	as	ADP
cana-2865	61	7	peak	peak	NOUN
cana-2865	61	8	and	and	CCONJ
cana-2865	61	9	median	median	ADJ
cana-2865	61	10	frequencies	frequency	NOUN
cana-2865	61	11	,	,	PUNCT
cana-2865	61	12	provide	provide	VERB
cana-2865	61	13	crucial	crucial	ADJ
cana-2865	61	14	information	information	NOUN
cana-2865	61	15	regarding	regard	VERB
cana-2865	61	16	the	the	DET
cana-2865	61	17	frequency	frequency	NOUN
cana-2865	61	18	-	-	PUNCT
cana-2865	61	19	domain	domain	NOUN
cana-2865	61	20	aspects	aspect	NOUN
cana-2865	61	21	of	of	ADP
cana-2865	61	22	the	the	DET
cana-2865	61	23	eeg	eeg	NOUN
cana-2865	61	24	readings	reading	NOUN
cana-2865	61	25	and	and	CCONJ
cana-2865	61	26	were	be	AUX
cana-2865	61	27	previously	previously	ADV
cana-2865	61	28	thought	think	VERB
cana-2865	61	29	to	to	PART
cana-2865	61	30	be	be	AUX
cana-2865	61	31	helpful	helpful	ADJ
cana-2865	61	32	biomarkers	biomarker	NOUN
cana-2865	61	33	for	for	ADP
cana-2865	61	34	the	the	DET
cana-2865	61	35	identification	identification	NOUN
cana-2865	61	36	of	of	ADP
cana-2865	61	37	major	major	ADJ
cana-2865	61	38	depressive	depressive	ADJ
cana-2865	61	39	illness	illness	NOUN
cana-2865	62	1	[	[	X
cana-2865	62	2	27–28	27–28	NUM
cana-2865	62	3	]	]	PUNCT
cana-2865	62	4	.	.	PUNCT
cana-2865	63	1	additionally	additionally	ADV
cana-2865	63	2	,	,	PUNCT
cana-2865	63	3	we	we	PRON
cana-2865	63	4	made	make	VERB
cana-2865	63	5	use	use	NOUN
cana-2865	63	6	of	of	ADP
cana-2865	63	7	wavelet	wavelet	NOUN
cana-2865	63	8	analysis	analysis	NOUN
cana-2865	63	9	,	,	PUNCT
cana-2865	63	10	a	a	DET
cana-2865	63	11	well	well	ADV
cana-2865	63	12	-	-	PUNCT
cana-2865	63	13	known	know	VERB
cana-2865	63	14	method	method	NOUN
cana-2865	63	15	for	for	ADP
cana-2865	63	16	obtaining	obtain	VERB
cana-2865	63	17	time	time	NOUN
cana-2865	63	18	-	-	PUNCT
cana-2865	63	19	frequency	frequency	NOUN
cana-2865	63	20	data	datum	NOUN
cana-2865	63	21	from	from	ADP
cana-2865	63	22	non	non	ADJ
cana-2865	63	23	-	-	ADJ
cana-2865	63	24	stationary	stationary	ADJ
cana-2865	63	25	signals	signal	NOUN
cana-2865	63	26	such	such	ADJ
cana-2865	63	27	as	as	ADP
cana-2865	63	28	eeg	eeg	NOUN
cana-2865	63	29	[	[	X
cana-2865	63	30	29	29	NUM
cana-2865	63	31	]	]	PUNCT
cana-2865	63	32	.	.	PUNCT
cana-2865	64	1	the	the	DET
cana-2865	64	2	researchers	researcher	NOUN
cana-2865	64	3	were	be	AUX
cana-2865	64	4	able	able	ADJ
cana-2865	64	5	to	to	PART
cana-2865	64	6	capture	capture	VERB
cana-2865	64	7	the	the	DET
cana-2865	64	8	complex	complex	ADJ
cana-2865	64	9	temporal	temporal	ADJ
cana-2865	64	10	and	and	CCONJ
cana-2865	64	11	spectral	spectral	ADJ
cana-2865	64	12	dynamics	dynamic	NOUN
cana-2865	64	13	of	of	ADP
cana-2865	64	14	the	the	DET
cana-2865	64	15	eeg	eeg	NOUN
cana-2865	64	16	data	datum	NOUN
cana-2865	64	17	by	by	ADP
cana-2865	64	18	breaking	break	VERB
cana-2865	64	19	them	they	PRON
cana-2865	64	20	down	down	ADP
cana-2865	64	21	into	into	ADP
cana-2865	64	22	several	several	ADJ
cana-2865	64	23	sub	sub	NOUN
cana-2865	64	24	-	-	NOUN
cana-2865	64	25	bands	band	NOUN
cana-2865	64	26	using	use	VERB
cana-2865	64	27	a	a	DET
cana-2865	64	28	six	six	NUM
cana-2865	64	29	-	-	PUNCT
cana-2865	64	30	level	level	NOUN
cana-2865	64	31	discrete	discrete	ADJ
cana-2865	64	32	wavelet	wavelet	NOUN
cana-2865	64	33	transform	transform	NOUN
cana-2865	64	34	with	with	ADP
cana-2865	64	35	the	the	DET
cana-2865	64	36	coif5	coif5	NOUN
cana-2865	64	37	mother	mother	NOUN
cana-2865	64	38	wavelet	wavelet	PROPN
cana-2865	64	39	.	.	PUNCT
cana-2865	65	1	energy	energy	NOUN
cana-2865	65	2	,	,	PUNCT
cana-2865	65	3	variance	variance	NOUN
cana-2865	65	4	,	,	PUNCT
cana-2865	65	5	wavelength	wavelength	NOUN
cana-2865	65	6	,	,	PUNCT
cana-2865	65	7	entropy	entropy	PROPN
cana-2865	65	8	,	,	PUNCT
cana-2865	65	9	standard	standard	ADJ
cana-2865	65	10	deviation	deviation	NOUN
cana-2865	65	11	,	,	PUNCT
cana-2865	65	12	and	and	CCONJ
cana-2865	65	13	other	other	ADJ
cana-2865	65	14	wavelet	wavelet	NOUN
cana-2865	65	15	-	-	PUNCT
cana-2865	65	16	derived	derive	VERB
cana-2865	65	17	characteristics	characteristic	NOUN
cana-2865	65	18	were	be	AUX
cana-2865	65	19	rich	rich	ADJ
cana-2865	65	20	and	and	CCONJ
cana-2865	65	21	relevant	relevant	ADJ
cana-2865	65	22	descriptors	descriptor	NOUN
cana-2865	65	23	of	of	ADP
cana-2865	65	24	the	the	DET
cana-2865	65	25	eeg	eeg	PROPN
cana-2865	65	26	data	datum	NOUN
cana-2865	65	27	that	that	PRON
cana-2865	65	28	may	may	AUX
cana-2865	65	29	help	help	VERB
cana-2865	65	30	with	with	ADP
cana-2865	65	31	the	the	DET
cana-2865	65	32	precise	precise	ADJ
cana-2865	65	33	diagnosis	diagnosis	NOUN
cana-2865	65	34	and	and	CCONJ
cana-2865	65	35	identification	identification	NOUN
cana-2865	65	36	of	of	ADP
cana-2865	65	37	severe	severe	ADJ
cana-2865	65	38	depression	depression	NOUN
cana-2865	65	39	.	.	PUNCT
cana-2865	66	1	a	a	DET
cana-2865	66	2	form	form	NOUN
cana-2865	66	3	of	of	ADP
cana-2865	66	4	metaheuristic	metaheuristic	ADJ
cana-2865	66	5	effective	effective	ADJ
cana-2865	66	6	optimization	optimization	NOUN
cana-2865	66	7	method	method	NOUN
cana-2865	66	8	called	call	VERB
cana-2865	66	9	the	the	DET
cana-2865	66	10	"	"	PUNCT
cana-2865	66	11	firefly	firefly	NOUN
cana-2865	66	12	algorithm	algorithm	NOUN
cana-2865	66	13	"	"	PUNCT
cana-2865	66	14	imitates	imitate	VERB
cana-2865	66	15	the	the	DET
cana-2865	66	16	flashing	flash	VERB
cana-2865	66	17	patterns	pattern	NOUN
cana-2865	66	18	of	of	ADP
cana-2865	66	19	firefly	firefly	NOUN
cana-2865	66	20	[	[	X
cana-2865	66	21	30	30	NUM
cana-2865	66	22	]	]	PUNCT
cana-2865	66	23	.	.	PUNCT
cana-2865	67	1	in	in	ADP
cana-2865	67	2	2009	2009	NUM
cana-2865	67	3	,	,	PUNCT
cana-2865	67	4	xin	xin	PROPN
cana-2865	67	5	-	-	PROPN
cana-2865	67	6	she	she	PRON
cana-2865	67	7	yang	yang	PROPN
cana-2865	67	8	created	create	VERB
cana-2865	67	9	an	an	DET
cana-2865	67	10	unconventional	unconventional	ADJ
cana-2865	67	11	optimization	optimization	NOUN
cana-2865	67	12	method	method	NOUN
cana-2865	67	13	called	call	VERB
cana-2865	67	14	the	the	DET
cana-2865	67	15	firefly	firefly	NOUN
cana-2865	67	16	algorithm	algorithm	NOUN
cana-2865	67	17	,	,	PUNCT
cana-2865	67	18	which	which	PRON
cana-2865	67	19	draws	draw	VERB
cana-2865	67	20	inspiration	inspiration	NOUN
cana-2865	67	21	from	from	ADP
cana-2865	67	22	the	the	DET
cana-2865	67	23	environment	environment	NOUN
cana-2865	67	24	.	.	PUNCT
cana-2865	68	1	it	it	PRON
cana-2865	68	2	draws	draw	VERB
cana-2865	68	3	inspiration	inspiration	NOUN
cana-2865	68	4	from	from	ADP
cana-2865	68	5	the	the	DET
cana-2865	68	6	natural	natural	ADJ
cana-2865	68	7	fireflies	firefly	NOUN
cana-2865	68	8	'	'	PART
cana-2865	68	9	flashing	flashing	NOUN
cana-2865	68	10	activity	activity	NOUN
cana-2865	68	11	.	.	PUNCT
cana-2865	69	1	the	the	DET
cana-2865	69	2	key	key	ADJ
cana-2865	69	3	principles	principle	NOUN
cana-2865	69	4	underlying	underlie	VERB
cana-2865	69	5	the	the	DET
cana-2865	69	6	firefly	firefly	NOUN
cana-2865	69	7	algorithm	algorithm	NOUN
cana-2865	69	8	are	be	AUX
cana-2865	69	9	:	:	PUNCT
cana-2865	69	10	all	all	DET
cana-2865	69	11	fireflies	firefly	NOUN
cana-2865	69	12	are	be	AUX
cana-2865	69	13	attracted	attract	VERB
cana-2865	69	14	to	to	ADP
cana-2865	69	15	one	one	NUM
cana-2865	69	16	another	another	DET
cana-2865	69	17	,	,	PUNCT
cana-2865	69	18	regardless	regardless	ADV
cana-2865	69	19	of	of	ADP
cana-2865	69	20	their	their	PRON
cana-2865	69	21	sex	sex	NOUN
cana-2865	69	22	.	.	PUNCT
cana-2865	70	1	the	the	DET
cana-2865	70	2	attractiveness	attractiveness	NOUN
cana-2865	70	3	between	between	ADP
cana-2865	70	4	two	two	NUM
cana-2865	70	5	fireflies	firefly	NOUN
cana-2865	70	6	is	be	AUX
cana-2865	70	7	proportional	proportional	ADJ
cana-2865	70	8	to	to	ADP
cana-2865	70	9	their	their	PRON
cana-2865	70	10	brightness	brightness	NOUN
cana-2865	70	11	,	,	PUNCT
cana-2865	70	12	which	which	PRON
cana-2865	70	13	represents	represent	VERB
cana-2865	70	14	the	the	DET
cana-2865	70	15	objective	objective	ADJ
cana-2865	70	16	function	function	NOUN
cana-2865	70	17	value	value	NOUN
cana-2865	70	18	being	be	AUX
cana-2865	70	19	optimized	optimize	VERB
cana-2865	70	20	.	.	PUNCT
cana-2865	71	1	a	a	DET
cana-2865	71	2	firefly	firefly	NOUN
cana-2865	71	3	with	with	ADP
cana-2865	71	4	lower	low	ADJ
cana-2865	71	5	brightness	brightness	NOUN
cana-2865	71	6	will	will	AUX
cana-2865	71	7	be	be	AUX
cana-2865	71	8	attracted	attract	VERB
cana-2865	71	9	towards	towards	ADP
cana-2865	71	10	a	a	DET
cana-2865	71	11	firefly	firefly	NOUN
cana-2865	71	12	with	with	ADP
cana-2865	71	13	higher	high	ADJ
cana-2865	71	14	brightness	brightness	NOUN
cana-2865	71	15	.	.	PUNCT
cana-2865	72	1	the	the	DET
cana-2865	72	2	attractiveness	attractiveness	NOUN
cana-2865	72	3	between	between	ADP
cana-2865	72	4	fireflies	firefly	NOUN
cana-2865	72	5	decreases	decrease	VERB
cana-2865	72	6	as	as	SCONJ
cana-2865	72	7	the	the	DET
cana-2865	72	8	distance	distance	NOUN
cana-2865	72	9	between	between	ADP
cana-2865	72	10	them	they	PRON
cana-2865	72	11	increases	increase	VERB
cana-2865	72	12	.	.	PUNCT
cana-2865	73	1	if	if	SCONJ
cana-2865	73	2	a	a	DET
cana-2865	73	3	firefly	firefly	NOUN
cana-2865	73	4	can	can	AUX
cana-2865	73	5	not	not	PART
cana-2865	73	6	find	find	VERB
cana-2865	73	7	a	a	DET
cana-2865	73	8	brighter	bright	ADJ
cana-2865	73	9	neighbor	neighbor	NOUN
cana-2865	73	10	,	,	PUNCT
cana-2865	73	11	it	it	PRON
cana-2865	73	12	will	will	AUX
cana-2865	73	13	move	move	VERB
cana-2865	73	14	randomly	randomly	ADV
cana-2865	73	15	.	.	PUNCT
cana-2865	74	1	the	the	DET
cana-2865	74	2	brightness	brightness	NOUN
cana-2865	74	3	of	of	ADP
cana-2865	74	4	a	a	DET
cana-2865	74	5	firefly	firefly	NOUN
cana-2865	74	6	is	be	AUX
cana-2865	74	7	determined	determine	VERB
cana-2865	74	8	by	by	ADP
cana-2865	74	9	the	the	DET
cana-2865	74	10	value	value	NOUN
cana-2865	74	11	of	of	ADP
cana-2865	74	12	the	the	DET
cana-2865	74	13	objective	objective	ADJ
cana-2865	74	14	function	function	NOUN
cana-2865	74	15	being	be	AUX
cana-2865	74	16	optimized	optimize	VERB
cana-2865	74	17	,	,	PUNCT
cana-2865	74	18	which	which	PRON
cana-2865	74	19	is	be	AUX
cana-2865	74	20	the	the	DET
cana-2865	74	21	fitness	fitness	NOUN
cana-2865	74	22	function	function	NOUN
cana-2865	74	23	in	in	ADP
cana-2865	74	24	the	the	DET
cana-2865	74	25	context	context	NOUN
cana-2865	74	26	of	of	ADP
cana-2865	74	27	the	the	DET
cana-2865	74	28	algorithm	algorithm	NOUN
cana-2865	74	29	.	.	PUNCT
cana-2865	75	1	the	the	DET
cana-2865	75	2	firefly	firefly	NOUN
cana-2865	75	3	algorithm	algorithm	NOUN
cana-2865	75	4	is	be	AUX
cana-2865	75	5	known	know	VERB
cana-2865	75	6	for	for	ADP
cana-2865	75	7	its	its	PRON
cana-2865	75	8	strong	strong	ADJ
cana-2865	75	9	exploration	exploration	NOUN
cana-2865	75	10	capabilities	capability	NOUN
cana-2865	75	11	and	and	CCONJ
cana-2865	75	12	ability	ability	NOUN
cana-2865	75	13	to	to	PART
cana-2865	75	14	efficiently	efficiently	ADV
cana-2865	75	15	search	search	VERB
cana-2865	75	16	complex	complex	ADJ
cana-2865	75	17	,	,	PUNCT
cana-2865	75	18	high	high	ADJ
cana-2865	75	19	-	-	PUNCT
cana-2865	75	20	dimensional	dimensional	ADJ
cana-2865	75	21	optimization	optimization	NOUN
cana-2865	75	22	spaces	space	NOUN
cana-2865	75	23	.	.	PUNCT
cana-2865	76	1	it	it	PRON
cana-2865	76	2	has	have	AUX
cana-2865	76	3	been	be	AUX
cana-2865	76	4	successfully	successfully	ADV
cana-2865	76	5	applied	apply	VERB
cana-2865	76	6	to	to	ADP
cana-2865	76	7	a	a	DET
cana-2865	76	8	wide	wide	ADJ
cana-2865	76	9	range	range	NOUN
cana-2865	76	10	of	of	ADP
cana-2865	76	11	optimization	optimization	NOUN
cana-2865	76	12	problems	problem	NOUN
cana-2865	76	13	,	,	PUNCT
cana-2865	76	14	including	include	VERB
cana-2865	76	15	feature	feature	NOUN
cana-2865	76	16	selection	selection	NOUN
cana-2865	76	17	,	,	PUNCT
cana-2865	76	18	which	which	PRON
cana-2865	76	19	is	be	AUX
cana-2865	76	20	a	a	DET
cana-2865	76	21	critical	critical	ADJ
cana-2865	76	22	step	step	NOUN
cana-2865	76	23	in	in	ADP
cana-2865	76	24	building	build	VERB
cana-2865	76	25	accurate	accurate	ADJ
cana-2865	76	26	predictive	predictive	ADJ
cana-2865	76	27	models	model	NOUN
cana-2865	76	28	,	,	PUNCT
cana-2865	76	29	such	such	ADJ
cana-2865	76	30	as	as	ADP
cana-2865	76	31	for	for	ADP
cana-2865	76	32	major	major	ADJ
cana-2865	76	33	depressive	depressive	ADJ
cana-2865	76	34	disorder	disorder	NOUN
cana-2865	76	35	diagnosis	diagnosis	NOUN
cana-2865	76	36	from	from	ADP
cana-2865	76	37	eeg	eeg	NOUN
cana-2865	76	38	signals	signal	NOUN
cana-2865	76	39	.	.	PUNCT
cana-2865	77	1	the	the	DET
cana-2865	77	2	results	result	NOUN
cana-2865	77	3	obtained	obtain	VERB
cana-2865	77	4	from	from	ADP
cana-2865	77	5	the	the	DET
cana-2865	77	6	firefly	firefly	NOUN
cana-2865	77	7	algorithm	algorithm	NOUN
cana-2865	77	8	were	be	AUX
cana-2865	77	9	compared	compare	VERB
cana-2865	77	10	against	against	ADP
cana-2865	77	11	genetic	genetic	ADJ
cana-2865	77	12	algorithm	algorithm	NOUN
cana-2865	77	13	and	and	CCONJ
cana-2865	77	14	direct	direct	ADJ
cana-2865	77	15	classification	classification	NOUN
cana-2865	77	16	.	.	PUNCT
cana-2865	78	1	the	the	DET
cana-2865	78	2	mutual	mutual	ADJ
cana-2865	78	3	information	information	NOUN
cana-2865	78	4	between	between	ADP
cana-2865	78	5	the	the	DET
cana-2865	78	6	features	feature	NOUN
cana-2865	78	7	and	and	CCONJ
cana-2865	78	8	the	the	DET
cana-2865	78	9	class	class	NOUN
cana-2865	78	10	labels	label	NOUN
cana-2865	78	11	was	be	AUX
cana-2865	78	12	used	use	VERB
cana-2865	78	13	as	as	ADP
cana-2865	78	14	the	the	DET
cana-2865	78	15	fitness	fitness	NOUN
cana-2865	78	16	function	function	NOUN
cana-2865	78	17	for	for	ADP
cana-2865	78	18	the	the	DET
cana-2865	78	19	optimization	optimization	NOUN
cana-2865	78	20	algorithms	algorithm	NOUN
cana-2865	78	21	.	.	PUNCT
cana-2865	79	1	the	the	DET
cana-2865	79	2	maximum	maximum	ADJ
cana-2865	79	3	number	number	NOUN
cana-2865	79	4	of	of	ADP
cana-2865	79	5	generations	generation	NOUN
cana-2865	79	6	/	/	SYM
cana-2865	79	7	iterations	iteration	NOUN
cana-2865	79	8	was	be	AUX
cana-2865	79	9	set	set	VERB
cana-2865	79	10	to	to	ADP
cana-2865	79	11	100	100	NUM
cana-2865	79	12	for	for	ADP
cana-2865	79	13	this	this	DET
cana-2865	79	14	research	research	NOUN
cana-2865	79	15	.	.	PUNCT
cana-2865	80	1	the	the	DET
cana-2865	80	2	ga	ga	PROPN
cana-2865	80	3	implementation	implementation	NOUN
cana-2865	80	4	utilized	utilize	VERB
cana-2865	80	5	a	a	DET
cana-2865	80	6	pressure	pressure	NOUN
cana-2865	80	7	parameter	parameter	NOUN
cana-2865	80	8	of	of	ADP
cana-2865	80	9	6	6	NUM
cana-2865	80	10	and	and	CCONJ
cana-2865	80	11	an	an	DET
cana-2865	80	12	elite	elite	ADJ
cana-2865	80	13	count	count	NOUN
cana-2865	80	14	of	of	ADP
cana-2865	80	15	2	2	NUM
cana-2865	80	16	.	.	PUNCT
cana-2865	81	1	the	the	DET
cana-2865	81	2	ffa	ffa	PROPN
cana-2865	81	3	was	be	AUX
cana-2865	81	4	implemented	implement	VERB
cana-2865	81	5	with	with	ADP
cana-2865	81	6	a	a	DET
cana-2865	81	7	fixed	fix	VERB
cana-2865	81	8	step	step	NOUN
cana-2865	81	9	size	size	NOUN
cana-2865	81	10	,	,	PUNCT
cana-2865	81	11	a	a	DET
cana-2865	81	12	light	light	ADJ
cana-2865	81	13	absorption	absorption	NOUN
cana-2865	81	14	coefficient	coefficient	NOUN
cana-2865	81	15	of	of	ADP
cana-2865	81	16	1	1	NUM
cana-2865	81	17	,	,	PUNCT
cana-2865	81	18	and	and	CCONJ
cana-2865	81	19	the	the	DET
cana-2865	81	20	number	number	NOUN
cana-2865	81	21	of	of	ADP
cana-2865	81	22	fireflies	firefly	NOUN
cana-2865	81	23	was	be	AUX
cana-2865	81	24	set	set	VERB
cana-2865	81	25	to	to	ADP
cana-2865	81	26	25	25	NUM
cana-2865	81	27	.	.	PUNCT
cana-2865	82	1	these	these	DET
cana-2865	82	2	parameter	parameter	NOUN
cana-2865	82	3	settings	setting	NOUN
cana-2865	82	4	were	be	AUX
cana-2865	82	5	chosen	choose	VERB
cana-2865	82	6	to	to	PART
cana-2865	82	7	leverage	leverage	VERB
cana-2865	82	8	the	the	DET
cana-2865	82	9	inherent	inherent	ADJ
cana-2865	82	10	strengths	strength	NOUN
cana-2865	82	11	of	of	ADP
cana-2865	82	12	each	each	DET
cana-2865	82	13	algorithm	algorithm	NOUN
cana-2865	82	14	and	and	CCONJ
cana-2865	82	15	facilitate	facilitate	VERB
cana-2865	82	16	a	a	DET
cana-2865	82	17	comprehensive	comprehensive	ADJ
cana-2865	82	18	comparison	comparison	NOUN
cana-2865	82	19	of	of	ADP
cana-2865	82	20	their	their	PRON
cana-2865	82	21	performance	performance	NOUN
cana-2865	82	22	in	in	ADP
cana-2865	82	23	the	the	DET
cana-2865	82	24	context	context	NOUN
cana-2865	82	25	of	of	ADP
cana-2865	82	26	feature	feature	NOUN
cana-2865	82	27	selection	selection	NOUN
cana-2865	82	28	for	for	ADP
cana-2865	82	29	major	major	ADJ
cana-2865	82	30	depressive	depressive	ADJ
cana-2865	82	31	disorder	disorder	NOUN
cana-2865	82	32	diagnosis	diagnosis	NOUN
cana-2865	82	33	from	from	ADP
cana-2865	82	34	eeg	eeg	NOUN
cana-2865	82	35	signals	signal	NOUN
cana-2865	82	36	.	.	PUNCT
cana-2865	83	1	c.	c.	PROPN
cana-2865	83	2	classification	classification	PROPN
cana-2865	83	3	another	another	DET
cana-2865	83	4	method	method	NOUN
cana-2865	83	5	for	for	ADP
cana-2865	83	6	classification	classification	NOUN
cana-2865	83	7	under	under	ADP
cana-2865	83	8	supervision	supervision	NOUN
cana-2865	83	9	is	be	AUX
cana-2865	83	10	a	a	DET
cana-2865	83	11	quadratic	quadratic	ADJ
cana-2865	83	12	discriminant	discriminant	ADJ
cana-2865	83	13	analysis	analysis	NOUN
cana-2865	83	14	that	that	PRON
cana-2865	83	15	provides	provide	VERB
cana-2865	83	16	a	a	DET
cana-2865	83	17	versatile	versatile	ADJ
cana-2865	83	18	,	,	PUNCT
cana-2865	83	19	limit	limit	NOUN
cana-2865	83	20	for	for	ADP
cana-2865	83	21	cubic	cubic	ADJ
cana-2865	83	22	decisions	decision	NOUN
cana-2865	83	23	.	.	PUNCT
cana-2865	84	1	unlike	unlike	ADP
cana-2865	84	2	linear	linear	PROPN
cana-2865	84	3	discriminant	discriminant	ADJ
cana-2865	84	4	analysis	analysis	NOUN
cana-2865	84	5	,	,	PUNCT
cana-2865	84	6	it	it	PRON
cana-2865	84	7	may	may	AUX
cana-2865	84	8	better	well	ADV
cana-2865	84	9	capture	capture	VERB
cana-2865	84	10	intricate	intricate	ADJ
cana-2865	84	11	communications	communication	NOUN
cana-2865	84	12	on	on	ADP
cana-2865	84	13	applied	apply	VERB
cana-2865	84	14	nonlinear	nonlinear	ADJ
cana-2865	84	15	analysis	analysis	NOUN
cana-2865	84	16	issn	issn	NOUN
cana-2865	84	17	:	:	PUNCT
cana-2865	84	18	1074	1074	NUM
cana-2865	84	19	-	-	PUNCT
cana-2865	84	20	133x	133x	NUM
cana-2865	84	21	vol	vol	NOUN
cana-2865	84	22	32	32	NUM
cana-2865	84	23	no	no	NOUN
cana-2865	84	24	.	.	PUNCT
cana-2865	85	1	4s	4s	NUM
cana-2865	85	2	(	(	PUNCT
cana-2865	85	3	2025	2025	NUM
cana-2865	85	4	)	)	PUNCT
cana-2865	85	5	473	473	NUM
cana-2865	85	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	85	7	data	data	NOUN
cana-2865	85	8	structures	structure	NOUN
cana-2865	85	9	and	and	CCONJ
cana-2865	85	10	potentially	potentially	ADV
cana-2865	85	11	achieve	achieve	VERB
cana-2865	85	12	higher	high	ADJ
cana-2865	85	13	accuracy	accuracy	NOUN
cana-2865	85	14	when	when	SCONJ
cana-2865	85	15	it	it	PRON
cana-2865	85	16	assumes	assume	VERB
cana-2865	85	17	gaussian	gaussian	ADJ
cana-2865	85	18	-	-	PUNCT
cana-2865	85	19	distributed	distribute	VERB
cana-2865	85	20	features	feature	NOUN
cana-2865	85	21	with	with	ADP
cana-2865	85	22	distinct	distinct	ADJ
cana-2865	85	23	attributes	attribute	NOUN
cana-2865	85	24	and	and	CCONJ
cana-2865	85	25	covariances	covariance	NOUN
cana-2865	85	26	for	for	ADP
cana-2865	85	27	each	each	DET
cana-2865	85	28	class	class	NOUN
cana-2865	86	1	[	[	X
cana-2865	86	2	31	31	NUM
cana-2865	86	3	]	]	PUNCT
cana-2865	86	4	.	.	PUNCT
cana-2865	87	1	naïve	naïve	ADJ
cana-2865	87	2	bayes	bayes	PROPN
cana-2865	87	3	,	,	PUNCT
cana-2865	87	4	a	a	DET
cana-2865	87	5	computationally	computationally	ADV
cana-2865	87	6	efficient	efficient	ADJ
cana-2865	87	7	probabilistic	probabilistic	ADJ
cana-2865	87	8	classifier	classifier	NOUN
cana-2865	87	9	,	,	PUNCT
cana-2865	87	10	is	be	AUX
cana-2865	87	11	employed	employ	VERB
cana-2865	87	12	in	in	ADP
cana-2865	87	13	our	our	PRON
cana-2865	87	14	research	research	NOUN
cana-2865	87	15	for	for	ADP
cana-2865	87	16	issues	issue	NOUN
cana-2865	87	17	related	relate	VERB
cana-2865	87	18	to	to	ADP
cana-2865	87	19	classifications	classification	NOUN
cana-2865	87	20	that	that	PRON
cana-2865	87	21	are	be	AUX
cana-2865	87	22	binary	binary	ADJ
cana-2865	87	23	and	and	CCONJ
cana-2865	87	24	multi	multi	ADJ
cana-2865	87	25	-	-	NOUN
cana-2865	87	26	class	class	NOUN
cana-2865	87	27	,	,	PUNCT
cana-2865	87	28	with	with	SCONJ
cana-2865	87	29	the	the	DET
cana-2865	87	30	gaussian	gaussian	ADJ
cana-2865	87	31	nb	nb	PROPN
cana-2865	87	32	algorithm	algorithm	PROPN
cana-2865	87	33	used	use	VERB
cana-2865	87	34	to	to	PART
cana-2865	87	35	instantiate	instantiate	VERB
cana-2865	87	36	a	a	DET
cana-2865	87	37	classifier	classifier	ADJ
cana-2865	87	38	object	object	NOUN
cana-2865	88	1	[	[	X
cana-2865	88	2	32	32	NUM
cana-2865	88	3	]	]	PUNCT
cana-2865	88	4	.	.	PUNCT
cana-2865	89	1	k	k	X
cana-2865	89	2	-	-	PUNCT
cana-2865	89	3	nearest	near	ADJ
cana-2865	89	4	neighbor	neighbor	NOUN
cana-2865	89	5	is	be	AUX
cana-2865	89	6	a	a	DET
cana-2865	89	7	fundamental	fundamental	ADJ
cana-2865	89	8	machine	machine	NOUN
cana-2865	89	9	learning	learn	VERB
cana-2865	89	10	algorithm	algorithm	NOUN
cana-2865	89	11	based	base	VERB
cana-2865	89	12	on	on	ADP
cana-2865	89	13	supervised	supervised	ADJ
cana-2865	89	14	learning	learning	NOUN
cana-2865	89	15	,	,	PUNCT
cana-2865	89	16	which	which	PRON
cana-2865	89	17	stores	store	VERB
cana-2865	89	18	all	all	DET
cana-2865	89	19	available	available	ADJ
cana-2865	89	20	data	datum	NOUN
cana-2865	89	21	and	and	CCONJ
cana-2865	89	22	uses	use	VERB
cana-2865	89	23	similarity	similarity	NOUN
cana-2865	89	24	to	to	PART
cana-2865	89	25	classify	classify	VERB
cana-2865	89	26	new	new	ADJ
cana-2865	89	27	data	datum	NOUN
cana-2865	89	28	points	point	NOUN
cana-2865	89	29	,	,	PUNCT
cana-2865	89	30	instead	instead	ADV
cana-2865	89	31	of	of	ADP
cana-2865	89	32	learning	learn	VERB
cana-2865	89	33	directly	directly	ADV
cana-2865	89	34	from	from	ADP
cana-2865	89	35	the	the	DET
cana-2865	89	36	training	training	NOUN
cana-2865	89	37	set	set	NOUN
cana-2865	89	38	,	,	PUNCT
cana-2865	89	39	and	and	CCONJ
cana-2865	89	40	leverages	leverage	VERB
cana-2865	89	41	the	the	DET
cana-2865	89	42	preserved	preserve	VERB
cana-2865	89	43	dataset	dataset	NOUN
cana-2865	89	44	as	as	ADP
cana-2865	89	45	needed	need	VERB
cana-2865	89	46	[	[	X
cana-2865	89	47	33	33	NUM
cana-2865	89	48	]	]	PUNCT
cana-2865	89	49	.	.	PUNCT
cana-2865	90	1	support	support	NOUN
cana-2865	90	2	vector	vector	NOUN
cana-2865	90	3	machines	machine	NOUN
cana-2865	90	4	are	be	AUX
cana-2865	90	5	a	a	DET
cana-2865	90	6	supervised	supervised	ADJ
cana-2865	90	7	learning	learning	NOUN
cana-2865	90	8	method	method	NOUN
cana-2865	90	9	for	for	ADP
cana-2865	90	10	classification	classification	NOUN
cana-2865	90	11	.	.	PUNCT
cana-2865	91	1	they	they	PRON
cana-2865	91	2	emphasize	emphasize	VERB
cana-2865	91	3	establishing	establish	VERB
cana-2865	91	4	the	the	DET
cana-2865	91	5	optimal	optimal	ADJ
cana-2865	91	6	decision	decision	NOUN
cana-2865	91	7	boundary	boundary	ADJ
cana-2865	91	8	for	for	ADP
cana-2865	91	9	data	datum	NOUN
cana-2865	91	10	points	point	NOUN
cana-2865	92	1	[	[	X
cana-2865	92	2	34	34	NUM
cana-2865	92	3	]	]	PUNCT
cana-2865	92	4	.	.	PUNCT
cana-2865	93	1	artificial	artificial	ADJ
cana-2865	93	2	neural	neural	ADJ
cana-2865	93	3	networks	network	NOUN
cana-2865	93	4	,	,	PUNCT
cana-2865	93	5	inspired	inspire	VERB
cana-2865	93	6	by	by	ADP
cana-2865	93	7	the	the	DET
cana-2865	93	8	human	human	ADJ
cana-2865	93	9	brain	brain	NOUN
cana-2865	93	10	,	,	PUNCT
cana-2865	93	11	can	can	AUX
cana-2865	93	12	learn	learn	VERB
cana-2865	93	13	from	from	ADP
cana-2865	93	14	data	datum	NOUN
cana-2865	93	15	by	by	ADP
cana-2865	93	16	modifying	modify	VERB
cana-2865	93	17	the	the	DET
cana-2865	93	18	strengths	strength	NOUN
cana-2865	93	19	of	of	ADP
cana-2865	93	20	connected	connected	ADJ
cana-2865	93	21	nodes	node	NOUN
cana-2865	93	22	or	or	CCONJ
cana-2865	93	23	"	"	PUNCT
cana-2865	93	24	neurons	neuron	NOUN
cana-2865	93	25	.	.	PUNCT
cana-2865	93	26	"	"	PUNCT
cana-2865	94	1	their	their	PRON
cana-2865	94	2	ability	ability	NOUN
cana-2865	94	3	to	to	PART
cana-2865	94	4	learn	learn	VERB
cana-2865	94	5	complex	complex	ADJ
cana-2865	94	6	information	information	NOUN
cana-2865	94	7	and	and	CCONJ
cana-2865	94	8	detect	detect	VERB
cana-2865	94	9	nonlinear	nonlinear	ADJ
cana-2865	94	10	patterns	pattern	NOUN
cana-2865	94	11	in	in	ADP
cana-2865	94	12	high	high	ADJ
cana-2865	94	13	-	-	PUNCT
cana-2865	94	14	dimensional	dimensional	ADJ
cana-2865	94	15	data	datum	NOUN
cana-2865	94	16	makes	make	VERB
cana-2865	94	17	them	they	PRON
cana-2865	94	18	valuable	valuable	ADJ
cana-2865	94	19	for	for	ADP
cana-2865	94	20	classifying	classify	VERB
cana-2865	94	21	major	major	ADJ
cana-2865	94	22	depressive	depressive	ADJ
cana-2865	94	23	disorder	disorder	NOUN
cana-2865	94	24	from	from	ADP
cana-2865	94	25	eeg	eeg	PROPN
cana-2865	94	26	data	datum	NOUN
cana-2865	94	27	[	[	X
cana-2865	94	28	35	35	NUM
cana-2865	94	29	]	]	PUNCT
cana-2865	94	30	.	.	PUNCT
cana-2865	95	1	the	the	DET
cana-2865	95	2	levenbergmarquardt	levenbergmarquardt	ADJ
cana-2865	95	3	backpropagation	backpropagation	NOUN
cana-2865	95	4	technique	technique	NOUN
cana-2865	95	5	can	can	AUX
cana-2865	95	6	enhance	enhance	VERB
cana-2865	95	7	the	the	DET
cana-2865	95	8	neural	neural	ADJ
cana-2865	95	9	network	network	NOUN
cana-2865	95	10	's	's	PART
cana-2865	95	11	classification	classification	NOUN
cana-2865	95	12	performance	performance	NOUN
cana-2865	95	13	.	.	PUNCT
cana-2865	96	1	this	this	DET
cana-2865	96	2	research	research	NOUN
cana-2865	96	3	reviewed	review	VERB
cana-2865	96	4	that	that	SCONJ
cana-2865	96	5	multiple	multiple	ADJ
cana-2865	96	6	methods	method	NOUN
cana-2865	96	7	of	of	ADP
cana-2865	96	8	machine	machine	NOUN
cana-2865	96	9	learning	learning	NOUN
cana-2865	96	10	may	may	AUX
cana-2865	96	11	be	be	AUX
cana-2865	96	12	utilized	utilize	VERB
cana-2865	96	13	for	for	ADP
cana-2865	96	14	categorizing	categorize	VERB
cana-2865	96	15	eeg	eeg	NOUN
cana-2865	96	16	recordings	recording	NOUN
cana-2865	96	17	for	for	ADP
cana-2865	96	18	mdd	mdd	PROPN
cana-2865	96	19	identification	identification	NOUN
cana-2865	96	20	.	.	PUNCT
cana-2865	97	1	the	the	DET
cana-2865	97	2	benefits	benefit	NOUN
cana-2865	97	3	and	and	CCONJ
cana-2865	97	4	limitations	limitation	NOUN
cana-2865	97	5	of	of	ADP
cana-2865	97	6	each	each	DET
cana-2865	97	7	algorithm	algorithm	NOUN
cana-2865	97	8	were	be	AUX
cana-2865	97	9	completely	completely	ADV
cana-2865	97	10	examined	examine	VERB
cana-2865	97	11	in	in	ADP
cana-2865	97	12	the	the	DET
cana-2865	97	13	brightness	brightness	NOUN
cana-2865	97	14	of	of	ADP
cana-2865	97	15	this	this	DET
cana-2865	97	16	application	application	NOUN
cana-2865	97	17	.	.	PUNCT
cana-2865	98	1	they	they	PRON
cana-2865	98	2	worked	work	VERB
cana-2865	98	3	with	with	ADP
cana-2865	98	4	a	a	DET
cana-2865	98	5	30	30	NUM
cana-2865	98	6	%	%	NOUN
cana-2865	98	7	test	test	NOUN
cana-2865	98	8	set	set	VERB
cana-2865	98	9	and	and	CCONJ
cana-2865	98	10	a	a	DET
cana-2865	98	11	70	70	NUM
cana-2865	98	12	%	%	NOUN
cana-2865	98	13	training	training	NOUN
cana-2865	98	14	set	set	VERB
cana-2865	98	15	to	to	PART
cana-2865	98	16	determine	determine	VERB
cana-2865	98	17	every	every	DET
cana-2865	98	18	classifier	classifier	NOUN
cana-2865	98	19	's	's	PART
cana-2865	98	20	activity	activity	NOUN
cana-2865	98	21	inappropriately	inappropriately	ADV
cana-2865	98	22	decoding	decode	VERB
cana-2865	98	23	serious	serious	ADJ
cana-2865	98	24	depressive	depressive	ADJ
cana-2865	98	25	conditions	condition	NOUN
cana-2865	98	26	from	from	ADP
cana-2865	98	27	the	the	DET
cana-2865	98	28	electroencephalogram	electroencephalogram	NOUN
cana-2865	98	29	(	(	PUNCT
cana-2865	98	30	eeg	eeg	NOUN
cana-2865	98	31	)	)	PUNCT
cana-2865	98	32	signals	signal	NOUN
cana-2865	98	33	.	.	PUNCT
cana-2865	99	1	4	4	X
cana-2865	99	2	.	.	X
cana-2865	99	3	results	result	NOUN
cana-2865	99	4	throughout	throughout	ADP
cana-2865	99	5	this	this	DET
cana-2865	99	6	section	section	NOUN
cana-2865	99	7	,	,	PUNCT
cana-2865	99	8	we	we	PRON
cana-2865	99	9	provide	provide	VERB
cana-2865	99	10	the	the	DET
cana-2865	99	11	comprehensive	comprehensive	ADJ
cana-2865	99	12	experimentation	experimentation	NOUN
cana-2865	99	13	findings	finding	NOUN
cana-2865	99	14	for	for	ADP
cana-2865	99	15	assessing	assess	VERB
cana-2865	99	16	the	the	DET
cana-2865	99	17	models	model	NOUN
cana-2865	99	18	knn	knn	PROPN
cana-2865	99	19	,	,	PUNCT
cana-2865	99	20	ann	ann	PROPN
cana-2865	99	21	,	,	PUNCT
cana-2865	99	22	svm	svm	PROPN
cana-2865	99	23	,	,	PUNCT
cana-2865	99	24	nb	nb	INTJ
cana-2865	99	25	,	,	PUNCT
cana-2865	99	26	and	and	CCONJ
cana-2865	99	27	qda	qda	NOUN
cana-2865	99	28	that	that	PRON
cana-2865	99	29	are	be	AUX
cana-2865	99	30	recommended	recommend	VERB
cana-2865	99	31	classification	classification	NOUN
cana-2865	99	32	performance	performance	NOUN
cana-2865	99	33	utilizing	utilize	VERB
cana-2865	99	34	the	the	DET
cana-2865	99	35	characteristics	characteristic	NOUN
cana-2865	99	36	chosen	choose	VERB
cana-2865	99	37	by	by	ADP
cana-2865	99	38	the	the	DET
cana-2865	99	39	genetic	genetic	ADJ
cana-2865	99	40	algorithm	algorithm	NOUN
cana-2865	99	41	.	.	PUNCT
cana-2865	100	1	rigorous	rigorous	ADJ
cana-2865	100	2	ablation	ablation	NOUN
cana-2865	100	3	experiments	experiment	NOUN
cana-2865	100	4	were	be	AUX
cana-2865	100	5	carried	carry	VERB
cana-2865	100	6	out	out	ADP
cana-2865	100	7	to	to	PART
cana-2865	100	8	thoroughly	thoroughly	ADV
cana-2865	100	9	evaluate	evaluate	VERB
cana-2865	100	10	the	the	DET
cana-2865	100	11	feasibility	feasibility	NOUN
cana-2865	100	12	and	and	CCONJ
cana-2865	100	13	effectiveness	effectiveness	NOUN
cana-2865	100	14	of	of	ADP
cana-2865	100	15	the	the	DET
cana-2865	100	16	proposed	propose	VERB
cana-2865	100	17	model	model	NOUN
cana-2865	100	18	design	design	NOUN
cana-2865	100	19	.	.	PUNCT
cana-2865	101	1	the	the	DET
cana-2865	101	2	eeg	eeg	PROPN
cana-2865	101	3	data	datum	NOUN
cana-2865	101	4	from	from	ADP
cana-2865	101	5	34	34	NUM
cana-2865	101	6	people	people	NOUN
cana-2865	101	7	with	with	ADP
cana-2865	101	8	severe	severe	ADJ
cana-2865	101	9	depressive	depressive	ADJ
cana-2865	101	10	disorder	disorder	NOUN
cana-2865	101	11	diagnosis	diagnosis	NOUN
cana-2865	101	12	and	and	CCONJ
cana-2865	101	13	60	60	NUM
cana-2865	101	14	health	health	NOUN
cana-2865	101	15	control	control	NOUN
cana-2865	101	16	subjects	subject	NOUN
cana-2865	101	17	were	be	AUX
cana-2865	101	18	utilized	utilize	VERB
cana-2865	101	19	in	in	ADP
cana-2865	101	20	this	this	DET
cana-2865	101	21	comprehensive	comprehensive	ADJ
cana-2865	101	22	investigation	investigation	NOUN
cana-2865	101	23	to	to	PART
cana-2865	101	24	distinguish	distinguish	VERB
cana-2865	101	25	between	between	ADP
cana-2865	101	26	those	those	PRON
cana-2865	101	27	with	with	ADP
cana-2865	101	28	the	the	DET
cana-2865	101	29	mental	mental	ADJ
cana-2865	101	30	health	health	NOUN
cana-2865	101	31	condition	condition	NOUN
cana-2865	101	32	and	and	CCONJ
cana-2865	101	33	their	their	PRON
cana-2865	101	34	neurotypical	neurotypical	ADJ
cana-2865	101	35	counterparts	counterpart	NOUN
cana-2865	101	36	.	.	PUNCT
cana-2865	102	1	the	the	DET
cana-2865	102	2	five	five	NUM
cana-2865	102	3	categorization	categorization	NOUN
cana-2865	102	4	techniques	technique	NOUN
cana-2865	102	5	and	and	CCONJ
cana-2865	102	6	the	the	DET
cana-2865	102	7	suggested	suggest	VERB
cana-2865	102	8	methodology	methodology	NOUN
cana-2865	102	9	were	be	AUX
cana-2865	102	10	meticulously	meticulously	ADV
cana-2865	102	11	evaluated	evaluate	VERB
cana-2865	102	12	using	use	VERB
cana-2865	102	13	a	a	DET
cana-2865	102	14	70	70	NUM
cana-2865	102	15	%	%	NOUN
cana-2865	102	16	train	train	NOUN
cana-2865	102	17	and	and	CCONJ
cana-2865	102	18	30	30	NUM
cana-2865	102	19	%	%	NOUN
cana-2865	102	20	test	test	NOUN
cana-2865	102	21	data	datum	NOUN
cana-2865	102	22	split	split	NOUN
cana-2865	102	23	.	.	PUNCT
cana-2865	103	1	four	four	NUM
cana-2865	103	2	key	key	ADJ
cana-2865	103	3	performance	performance	NOUN
cana-2865	103	4	metrics	metric	NOUN
cana-2865	103	5	were	be	AUX
cana-2865	103	6	employed	employ	VERB
cana-2865	103	7	in	in	ADP
cana-2865	103	8	this	this	DET
cana-2865	103	9	study	study	NOUN
cana-2865	103	10	to	to	PART
cana-2865	103	11	provide	provide	VERB
cana-2865	103	12	an	an	DET
cana-2865	103	13	extensive	extensive	ADJ
cana-2865	103	14	examination	examination	NOUN
cana-2865	103	15	of	of	ADP
cana-2865	103	16	the	the	DET
cana-2865	103	17	categorization	categorization	NOUN
cana-2865	103	18	achievement	achievement	NOUN
cana-2865	103	19	:	:	PUNCT
cana-2865	103	20	accuracy	accuracy	NOUN
cana-2865	103	21	,	,	PUNCT
cana-2865	103	22	recall	recall	NOUN
cana-2865	103	23	,	,	PUNCT
cana-2865	103	24	precision	precision	NOUN
cana-2865	103	25	,	,	PUNCT
cana-2865	103	26	and	and	CCONJ
cana-2865	103	27	f1_score	f1_score	ADJ
cana-2865	103	28	.	.	PUNCT
cana-2865	104	1	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	PROPN
cana-2865	104	2	=	=	SYM
cana-2865	104	3	𝑇𝑃	𝑇𝑃	PROPN
cana-2865	104	4	+	+	CCONJ
cana-2865	104	5	𝑇𝑁	𝑇𝑁	PROPN
cana-2865	104	6	𝑇𝑃	𝑇𝑃	PROPN
cana-2865	104	7	+	+	CCONJ
cana-2865	104	8	𝐹𝑃	𝐹𝑃	PROPN
cana-2865	105	1	+	+	CCONJ
cana-2865	105	2	𝑇𝑁	𝑇𝑁	PROPN
cana-2865	106	1	+	+	X
cana-2865	106	2	𝐹𝑁	𝐹𝑁	PROPN
cana-2865	106	3	(	(	PUNCT
cana-2865	106	4	1	1	NUM
cana-2865	106	5	)	)	PUNCT
cana-2865	106	6	𝑅𝑒𝑐𝑎𝑙𝑙	𝑅𝑒𝑐𝑎𝑙𝑙	PROPN
cana-2865	106	7	=	=	SYM
cana-2865	106	8	𝑇𝑃	𝑇𝑃	PROPN
cana-2865	106	9	𝑇𝑃	𝑇𝑃	PROPN
cana-2865	106	10	+	+	CCONJ
cana-2865	106	11	𝐹𝑁	𝐹𝑁	PROPN
cana-2865	106	12	(	(	PUNCT
cana-2865	106	13	2	2	NUM
cana-2865	106	14	)	)	PUNCT
cana-2865	106	15	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
cana-2865	106	16	=	=	SYM
cana-2865	106	17	𝑇𝑃	𝑇𝑃	PROPN
cana-2865	106	18	𝑇𝑃	𝑇𝑃	PROPN
cana-2865	106	19	+	+	CCONJ
cana-2865	106	20	𝐹𝑃	𝐹𝑃	PROPN
cana-2865	106	21	(	(	PUNCT
cana-2865	106	22	3	3	NUM
cana-2865	106	23	)	)	PUNCT
cana-2865	106	24	f1_score	f1_score	ADJ
cana-2865	106	25	=	=	SYM
cana-2865	106	26	2	2	NUM
cana-2865	106	27	∗	∗	NOUN
cana-2865	106	28	𝑇𝑃	𝑇𝑃	NOUN
cana-2865	106	29	2	2	NUM
cana-2865	106	30	∗	∗	NOUN
cana-2865	106	31	𝑇𝑃	𝑇𝑃	NOUN
cana-2865	106	32	+	+	CCONJ
cana-2865	106	33	𝐹𝑃	𝐹𝑃	PROPN
cana-2865	107	1	+	+	CCONJ
cana-2865	107	2	𝐹𝑁	𝐹𝑁	PROPN
cana-2865	107	3	(	(	PUNCT
cana-2865	107	4	4	4	NUM
cana-2865	107	5	)	)	PUNCT
cana-2865	107	6	for	for	ADP
cana-2865	107	7	the	the	DET
cana-2865	107	8	appropriate	appropriate	ADJ
cana-2865	107	9	sample	sample	NOUN
cana-2865	107	10	categories	category	NOUN
cana-2865	107	11	,	,	PUNCT
cana-2865	107	12	the	the	DET
cana-2865	107	13	number	number	NOUN
cana-2865	107	14	of	of	ADP
cana-2865	107	15	samples	sample	NOUN
cana-2865	107	16	is	be	AUX
cana-2865	107	17	denoted	denote	VERB
cana-2865	107	18	by	by	ADP
cana-2865	107	19	the	the	DET
cana-2865	107	20	words	word	NOUN
cana-2865	107	21	true	true	ADJ
cana-2865	107	22	positive	positive	ADJ
cana-2865	107	23	(	(	PUNCT
cana-2865	107	24	tp	tp	NOUN
cana-2865	107	25	)	)	PUNCT
cana-2865	107	26	,	,	PUNCT
cana-2865	107	27	false	false	ADJ
cana-2865	107	28	negative	negative	ADJ
cana-2865	107	29	(	(	PUNCT
cana-2865	107	30	fn	fn	NOUN
cana-2865	107	31	)	)	PUNCT
cana-2865	107	32	,	,	PUNCT
cana-2865	107	33	true	true	ADJ
cana-2865	107	34	negative	negative	ADJ
cana-2865	107	35	(	(	PUNCT
cana-2865	107	36	tn	tn	NOUN
cana-2865	107	37	)	)	PUNCT
cana-2865	107	38	,	,	PUNCT
cana-2865	107	39	and	and	CCONJ
cana-2865	107	40	false	false	ADJ
cana-2865	107	41	positive	positive	ADJ
cana-2865	107	42	(	(	PUNCT
cana-2865	107	43	fp	fp	NOUN
cana-2865	107	44	)	)	PUNCT
cana-2865	107	45	.	.	PUNCT
cana-2865	108	1	communications	communication	NOUN
cana-2865	108	2	on	on	ADP
cana-2865	108	3	applied	apply	VERB
cana-2865	108	4	nonlinear	nonlinear	ADJ
cana-2865	108	5	analysis	analysis	NOUN
cana-2865	108	6	issn	issn	NOUN
cana-2865	108	7	:	:	PUNCT
cana-2865	108	8	1074	1074	NUM
cana-2865	108	9	-	-	PUNCT
cana-2865	108	10	133x	133x	NUM
cana-2865	108	11	vol	vol	NOUN
cana-2865	108	12	32	32	NUM
cana-2865	108	13	no	no	NOUN
cana-2865	108	14	.	.	PUNCT
cana-2865	109	1	4s	4s	NUM
cana-2865	109	2	(	(	PUNCT
cana-2865	109	3	2025	2025	NUM
cana-2865	109	4	)	)	PUNCT
cana-2865	109	5	474	474	NUM
cana-2865	109	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	109	7	table	table	NOUN
cana-2865	109	8	1	1	NUM
cana-2865	109	9	presents	present	VERB
cana-2865	109	10	the	the	DET
cana-2865	109	11	categorization	categorization	NOUN
cana-2865	109	12	outcomes	outcome	NOUN
cana-2865	109	13	derived	derive	VERB
cana-2865	109	14	from	from	ADP
cana-2865	109	15	the	the	DET
cana-2865	109	16	various	various	ADJ
cana-2865	109	17	classifiers	classifier	NOUN
cana-2865	109	18	.	.	PUNCT
cana-2865	110	1	42	42	NUM
cana-2865	110	2	characteristics	characteristic	NOUN
cana-2865	110	3	that	that	PRON
cana-2865	110	4	were	be	AUX
cana-2865	110	5	taken	take	VERB
cana-2865	110	6	from	from	ADP
cana-2865	110	7	the	the	DET
cana-2865	110	8	eeg	eeg	NOUN
cana-2865	110	9	data	datum	NOUN
cana-2865	110	10	made	make	VERB
cana-2865	110	11	up	up	ADP
cana-2865	110	12	the	the	DET
cana-2865	110	13	initial	initial	ADJ
cana-2865	110	14	feature	feature	NOUN
cana-2865	110	15	set	set	VERB
cana-2865	110	16	employed	employ	VERB
cana-2865	110	17	in	in	ADP
cana-2865	110	18	this	this	DET
cana-2865	110	19	investigation	investigation	NOUN
cana-2865	110	20	.	.	PUNCT
cana-2865	111	1	nevertheless	nevertheless	ADV
cana-2865	111	2	,	,	PUNCT
cana-2865	111	3	by	by	ADP
cana-2865	111	4	using	use	VERB
cana-2865	111	5	the	the	DET
cana-2865	111	6	firefly	firefly	NOUN
cana-2865	111	7	method	method	NOUN
cana-2865	111	8	,	,	PUNCT
cana-2865	111	9	the	the	DET
cana-2865	111	10	researchers	researcher	NOUN
cana-2865	111	11	were	be	AUX
cana-2865	111	12	able	able	ADJ
cana-2865	111	13	to	to	PART
cana-2865	111	14	choose	choose	VERB
cana-2865	111	15	30	30	NUM
cana-2865	111	16	features	feature	NOUN
cana-2865	111	17	that	that	PRON
cana-2865	111	18	were	be	AUX
cana-2865	111	19	the	the	DET
cana-2865	111	20	most	most	ADV
cana-2865	111	21	discriminative	discriminative	NOUN
cana-2865	111	22	and	and	CCONJ
cana-2865	111	23	instructive	instructive	ADJ
cana-2865	111	24	for	for	ADP
cana-2865	111	25	the	the	DET
cana-2865	111	26	depression	depression	NOUN
cana-2865	111	27	detection	detection	NOUN
cana-2865	111	28	job	job	NOUN
cana-2865	111	29	.	.	PUNCT
cana-2865	112	1	an	an	DET
cana-2865	112	2	essential	essential	ADJ
cana-2865	112	3	stage	stage	NOUN
cana-2865	112	4	to	to	ADP
cana-2865	112	5	enhancing	enhance	VERB
cana-2865	112	6	the	the	DET
cana-2865	112	7	performance	performance	NOUN
cana-2865	112	8	of	of	ADP
cana-2865	112	9	the	the	DET
cana-2865	112	10	classification	classification	NOUN
cana-2865	112	11	models	model	NOUN
cana-2865	112	12	was	be	AUX
cana-2865	112	13	the	the	DET
cana-2865	112	14	process	process	NOUN
cana-2865	112	15	of	of	ADP
cana-2865	112	16	choosing	choose	VERB
cana-2865	112	17	features	feature	NOUN
cana-2865	112	18	implementing	implement	VERB
cana-2865	112	19	the	the	DET
cana-2865	112	20	firefly	firefly	NOUN
cana-2865	112	21	algorithm	algorithm	NOUN
cana-2865	112	22	,	,	PUNCT
cana-2865	112	23	which	which	PRON
cana-2865	112	24	allowed	allow	VERB
cana-2865	112	25	the	the	DET
cana-2865	112	26	models	model	NOUN
cana-2865	112	27	to	to	PART
cana-2865	112	28	specialize	specialize	VERB
cana-2865	112	29	on	on	ADP
cana-2865	112	30	the	the	DET
cana-2865	112	31	most	most	ADV
cana-2865	112	32	critical	critical	ADJ
cana-2865	112	33	features	feature	NOUN
cana-2865	112	34	of	of	ADP
cana-2865	112	35	the	the	DET
cana-2865	112	36	eeg	eeg	PROPN
cana-2865	112	37	data	datum	NOUN
cana-2865	112	38	,	,	PUNCT
cana-2865	112	39	strengthening	strengthen	VERB
cana-2865	112	40	their	their	PRON
cana-2865	112	41	capacity	capacity	NOUN
cana-2865	112	42	to	to	PART
cana-2865	112	43	discriminate	discriminate	VERB
cana-2865	112	44	between	between	ADP
cana-2865	112	45	people	people	NOUN
cana-2865	112	46	with	with	ADP
cana-2865	112	47	normal	normal	ADJ
cana-2865	112	48	boundaries	boundary	NOUN
cana-2865	112	49	and	and	CCONJ
cana-2865	112	50	those	those	PRON
cana-2865	112	51	suffering	suffer	VERB
cana-2865	112	52	from	from	ADP
cana-2865	112	53	severe	severe	ADJ
cana-2865	112	54	depression	depression	NOUN
cana-2865	112	55	.	.	PUNCT
cana-2865	113	1	when	when	SCONJ
cana-2865	113	2	applied	apply	VERB
cana-2865	113	3	to	to	ADP
cana-2865	113	4	the	the	DET
cana-2865	113	5	finest	fine	ADJ
cana-2865	113	6	feature	feature	NOUN
cana-2865	113	7	subset	subset	NOUN
cana-2865	113	8	assigned	assign	VERB
cana-2865	113	9	by	by	ADP
cana-2865	113	10	the	the	DET
cana-2865	113	11	firefly	firefly	NOUN
cana-2865	113	12	algorithm	algorithm	NOUN
cana-2865	113	13	,	,	PUNCT
cana-2865	113	14	the	the	DET
cana-2865	113	15	svm	svm	PROPN
cana-2865	113	16	classifier	classifier	NOUN
cana-2865	113	17	achieved	achieve	VERB
cana-2865	113	18	the	the	DET
cana-2865	113	19	greatest	great	ADJ
cana-2865	113	20	overall	overall	ADJ
cana-2865	113	21	score	score	NOUN
cana-2865	113	22	in	in	ADP
cana-2865	113	23	the	the	DET
cana-2865	113	24	division	division	NOUN
cana-2865	113	25	,	,	PUNCT
cana-2865	113	26	according	accord	VERB
cana-2865	113	27	to	to	ADP
cana-2865	113	28	the	the	DET
cana-2865	113	29	results	result	NOUN
cana-2865	113	30	.	.	PUNCT
cana-2865	114	1	as	as	SCONJ
cana-2865	114	2	illustrated	illustrate	VERB
cana-2865	114	3	by	by	ADP
cana-2865	114	4	the	the	DET
cana-2865	114	5	svm	svm	PROPN
cana-2865	114	6	model	model	NOUN
cana-2865	114	7	's	's	PART
cana-2865	114	8	incredible	incredible	ADJ
cana-2865	114	9	96.23	96.23	NUM
cana-2865	114	10	%	%	NOUN
cana-2865	114	11	accuracy	accuracy	NOUN
cana-2865	114	12	,	,	PUNCT
cana-2865	114	13	nearly	nearly	ADV
cana-2865	114	14	all	all	PRON
cana-2865	114	15	people	people	NOUN
cana-2865	114	16	were	be	AUX
cana-2865	114	17	properly	properly	ADV
cana-2865	114	18	classified	classify	VERB
cana-2865	114	19	as	as	ADP
cana-2865	114	20	either	either	CCONJ
cana-2865	114	21	majorly	majorly	ADV
cana-2865	114	22	depressed	depressed	ADJ
cana-2865	114	23	or	or	CCONJ
cana-2865	114	24	healthy	healthy	ADJ
cana-2865	114	25	controls	control	NOUN
cana-2865	114	26	.	.	PUNCT
cana-2865	115	1	a	a	DET
cana-2865	115	2	precision	precision	NOUN
cana-2865	115	3	score	score	NOUN
cana-2865	115	4	of	of	ADP
cana-2865	115	5	95.94	95.94	NUM
cana-2865	115	6	%	%	NOUN
cana-2865	115	7	proved	prove	VERB
cana-2865	115	8	the	the	DET
cana-2865	115	9	model	model	NOUN
cana-2865	115	10	's	's	PART
cana-2865	115	11	ability	ability	NOUN
cana-2865	115	12	to	to	PART
cana-2865	115	13	find	find	VERB
cana-2865	115	14	people	people	NOUN
cana-2865	115	15	with	with	ADP
cana-2865	115	16	depression	depression	NOUN
cana-2865	115	17	,	,	PUNCT
cana-2865	115	18	and	and	CCONJ
cana-2865	115	19	a	a	DET
cana-2865	115	20	recall	recall	NOUN
cana-2865	115	21	of	of	ADP
cana-2865	115	22	96.39	96.39	NUM
cana-2865	115	23	%	%	NOUN
cana-2865	115	24	proved	prove	VERB
cana-2865	115	25	it	it	PRON
cana-2865	115	26	was	be	AUX
cana-2865	115	27	successful	successful	ADJ
cana-2865	115	28	in	in	ADP
cana-2865	115	29	identifying	identify	VERB
cana-2865	115	30	instances	instance	NOUN
cana-2865	115	31	of	of	ADP
cana-2865	115	32	optimism	optimism	NOUN
cana-2865	115	33	.	.	PUNCT
cana-2865	116	1	further	far	ADV
cana-2865	116	2	supporting	support	VERB
cana-2865	116	3	the	the	DET
cana-2865	116	4	model	model	NOUN
cana-2865	116	5	's	's	PART
cana-2865	116	6	balanced	balanced	ADJ
cana-2865	116	7	and	and	CCONJ
cana-2865	116	8	reliable	reliable	ADJ
cana-2865	116	9	outcome	outcome	NOUN
cana-2865	116	10	is	be	AUX
cana-2865	116	11	its	its	PRON
cana-2865	116	12	f1	f1	NOUN
cana-2865	116	13	-	-	PUNCT
cana-2865	116	14	score	score	NOUN
cana-2865	116	15	of	of	ADP
cana-2865	116	16	96.14	96.14	NUM
cana-2865	116	17	%	%	NOUN
cana-2865	116	18	,	,	PUNCT
cana-2865	116	19	which	which	PRON
cana-2865	116	20	aggregates	aggregate	VERB
cana-2865	116	21	precision	precision	NOUN
cana-2865	116	22	and	and	CCONJ
cana-2865	116	23	recall	recall	VERB
cana-2865	116	24	into	into	ADP
cana-2865	116	25	a	a	DET
cana-2865	116	26	single	single	ADJ
cana-2865	116	27	amount	amount	NOUN
cana-2865	116	28	.	.	PUNCT
cana-2865	117	1	these	these	DET
cana-2865	117	2	excellent	excellent	ADJ
cana-2865	117	3	findings	finding	NOUN
cana-2865	117	4	point	point	VERB
cana-2865	117	5	out	out	ADP
cana-2865	117	6	the	the	DET
cana-2865	117	7	firefly	firefly	NOUN
cana-2865	117	8	algorithm	algorithm	NOUN
cana-2865	117	9	's	's	PART
cana-2865	117	10	ability	ability	NOUN
cana-2865	117	11	to	to	PART
cana-2865	117	12	extract	extract	VERB
cana-2865	117	13	the	the	DET
cana-2865	117	14	most	most	ADV
cana-2865	117	15	exposing	exposing	ADJ
cana-2865	117	16	and	and	CCONJ
cana-2865	117	17	unique	unique	ADJ
cana-2865	117	18	features	feature	NOUN
cana-2865	117	19	from	from	ADP
cana-2865	117	20	the	the	DET
cana-2865	117	21	eeg	eeg	PROPN
cana-2865	117	22	data	datum	NOUN
cana-2865	117	23	.	.	PUNCT
cana-2865	118	1	when	when	SCONJ
cana-2865	118	2	mixed	mix	VERB
cana-2865	118	3	with	with	ADP
cana-2865	118	4	the	the	DET
cana-2865	118	5	svm	svm	PROPN
cana-2865	118	6	classifier	classifier	NOUN
cana-2865	118	7	's	's	PART
cana-2865	118	8	integrated	integrate	VERB
cana-2865	118	9	capabilities	capability	NOUN
cana-2865	118	10	,	,	PUNCT
cana-2865	118	11	this	this	DET
cana-2865	118	12	approach	approach	NOUN
cana-2865	118	13	developed	develop	VERB
cana-2865	118	14	a	a	DET
cana-2865	118	15	highly	highly	ADV
cana-2865	118	16	accurate	accurate	ADJ
cana-2865	118	17	and	and	CCONJ
cana-2865	118	18	faithful	faithful	ADJ
cana-2865	118	19	system	system	NOUN
cana-2865	118	20	for	for	ADP
cana-2865	118	21	noticing	notice	VERB
cana-2865	118	22	severe	severe	ADJ
cana-2865	118	23	depression	depression	NOUN
cana-2865	118	24	.	.	PUNCT
cana-2865	119	1	table	table	NOUN
cana-2865	119	2	1	1	NUM
cana-2865	119	3	.	.	PUNCT
cana-2865	120	1	classification	classification	NOUN
cana-2865	120	2	results	result	NOUN
cana-2865	120	3	(	(	PUNCT
cana-2865	120	4	%	%	INTJ
cana-2865	120	5	)	)	PUNCT
cana-2865	120	6	after	after	ADP
cana-2865	120	7	feature	feature	NOUN
cana-2865	120	8	selection	selection	NOUN
cana-2865	120	9	by	by	ADP
cana-2865	120	10	firefly	firefly	NOUN
cana-2865	120	11	algorithm	algorithm	PROPN
cana-2865	120	12	classifier	classifier	PROPN
cana-2865	120	13	accuracy	accuracy	PROPN
cana-2865	120	14	precision	precision	NOUN
cana-2865	120	15	recall	recall	VERB
cana-2865	120	16	f1_score	f1_score	ADV
cana-2865	120	17	knn	knn	PROPN
cana-2865	120	18	94.7368	94.7368	NUM
cana-2865	120	19	94.2982	94.2982	NUM
cana-2865	120	20	94.9836	94.9836	NUM
cana-2865	120	21	94.5888	94.5888	NUM
cana-2865	120	22	ann	ann	PROPN
cana-2865	120	23	75.9398	75.9398	NUM
cana-2865	120	24	76.2061	76.2061	NUM
cana-2865	120	25	75.7077	75.7077	NUM
cana-2865	120	26	75.7424	75.7424	NUM
cana-2865	120	27	nb	nb	NOUN
cana-2865	120	28	73.3083	73.3083	NUM
cana-2865	120	29	72.9167	72.9167	NUM
cana-2865	120	30	76.1523	76.1523	NUM
cana-2865	120	31	72.8380	72.8380	NUM
cana-2865	120	32	qda	qda	NOUN
cana-2865	120	33	75.5639	75.5639	NUM
cana-2865	120	34	75.7675	75.7675	NUM
cana-2865	120	35	75.2932	75.2932	NUM
cana-2865	120	36	75.3461	75.3461	NUM
cana-2865	120	37	svm	svm	PROPN
cana-2865	120	38	96.2406	96.2406	NUM
cana-2865	120	39	95.9430	95.9430	NUM
cana-2865	120	40	96.3928	96.3928	NUM
cana-2865	120	41	96.1445	96.1445	NUM
cana-2865	120	42	additionally	additionally	ADV
cana-2865	120	43	,	,	PUNCT
cana-2865	120	44	the	the	DET
cana-2865	120	45	knn	knn	PROPN
cana-2865	120	46	classifier	classifier	PROPN
cana-2865	120	47	performed	perform	VERB
cana-2865	120	48	exceptionally	exceptionally	ADV
cana-2865	120	49	well	well	ADV
cana-2865	120	50	,	,	PUNCT
cana-2865	120	51	achieving	achieve	VERB
cana-2865	120	52	an	an	DET
cana-2865	120	53	impressive	impressive	ADJ
cana-2865	120	54	94.73	94.73	NUM
cana-2865	120	55	%	%	NOUN
cana-2865	120	56	accuracy	accuracy	NOUN
cana-2865	120	57	,	,	PUNCT
cana-2865	120	58	a	a	DET
cana-2865	120	59	precision	precision	NOUN
cana-2865	120	60	of	of	ADP
cana-2865	120	61	94.29	94.29	NUM
cana-2865	120	62	%	%	NOUN
cana-2865	120	63	that	that	PRON
cana-2865	120	64	demonstrated	demonstrate	VERB
cana-2865	120	65	a	a	DET
cana-2865	120	66	strong	strong	ADJ
cana-2865	120	67	ability	ability	NOUN
cana-2865	120	68	to	to	PART
cana-2865	120	69	correctly	correctly	ADV
cana-2865	120	70	identify	identify	VERB
cana-2865	120	71	individuals	individual	NOUN
cana-2865	120	72	with	with	ADP
cana-2865	120	73	depression	depression	NOUN
cana-2865	120	74	,	,	PUNCT
cana-2865	120	75	a	a	DET
cana-2865	120	76	recall	recall	NOUN
cana-2865	120	77	of	of	ADP
cana-2865	120	78	94.98	94.98	NUM
cana-2865	120	79	%	%	NOUN
cana-2865	120	80	that	that	PRON
cana-2865	120	81	demonstrated	demonstrate	VERB
cana-2865	120	82	its	its	PRON
cana-2865	120	83	effectiveness	effectiveness	NOUN
cana-2865	120	84	in	in	ADP
cana-2865	120	85	detecting	detect	VERB
cana-2865	120	86	positive	positive	ADJ
cana-2865	120	87	cases	case	NOUN
cana-2865	120	88	,	,	PUNCT
cana-2865	120	89	and	and	CCONJ
cana-2865	120	90	an	an	DET
cana-2865	120	91	f1	f1	NOUN
cana-2865	120	92	-	-	PUNCT
cana-2865	120	93	score	score	NOUN
cana-2865	120	94	of	of	ADP
cana-2865	120	95	94.58	94.58	NUM
cana-2865	120	96	%	%	NOUN
cana-2865	120	97	that	that	PRON
cana-2865	120	98	further	far	ADV
cana-2865	120	99	highlighted	highlight	VERB
cana-2865	120	100	the	the	DET
cana-2865	120	101	model	model	NOUN
cana-2865	120	102	's	's	PART
cana-2865	120	103	balanced	balanced	ADJ
cana-2865	120	104	and	and	CCONJ
cana-2865	120	105	robust	robust	ADJ
cana-2865	120	106	performance	performance	NOUN
cana-2865	120	107	by	by	ADP
cana-2865	120	108	combining	combine	VERB
cana-2865	120	109	precision	precision	NOUN
cana-2865	120	110	and	and	CCONJ
cana-2865	120	111	recall	recall	VERB
cana-2865	120	112	into	into	ADP
cana-2865	120	113	a	a	DET
cana-2865	120	114	single	single	ADJ
cana-2865	120	115	metric	metric	NOUN
cana-2865	120	116	.	.	PUNCT
cana-2865	121	1	these	these	DET
cana-2865	121	2	amazing	amazing	ADJ
cana-2865	121	3	results	result	NOUN
cana-2865	121	4	for	for	ADP
cana-2865	121	5	the	the	DET
cana-2865	121	6	knn	knn	PROPN
cana-2865	121	7	classifier	classifier	PROPN
cana-2865	121	8	,	,	PUNCT
cana-2865	121	9	when	when	SCONJ
cana-2865	121	10	teamed	team	VERB
cana-2865	121	11	with	with	ADP
cana-2865	121	12	the	the	DET
cana-2865	121	13	built	build	VERB
cana-2865	121	14	-	-	PUNCT
cana-2865	121	15	in	in	ADP
cana-2865	121	16	abilities	ability	NOUN
cana-2865	121	17	of	of	ADP
cana-2865	121	18	the	the	DET
cana-2865	121	19	knn	knn	PROPN
cana-2865	121	20	model	model	PROPN
cana-2865	121	21	,	,	PUNCT
cana-2865	121	22	suggest	suggest	VERB
cana-2865	121	23	that	that	SCONJ
cana-2865	121	24	the	the	DET
cana-2865	121	25	firefly	firefly	NOUN
cana-2865	121	26	algorithm	algorithm	NOUN
cana-2865	121	27	may	may	AUX
cana-2865	121	28	extract	extract	VERB
cana-2865	121	29	the	the	DET
cana-2865	121	30	most	most	ADV
cana-2865	121	31	unique	unique	ADJ
cana-2865	121	32	and	and	CCONJ
cana-2865	121	33	explaining	explain	VERB
cana-2865	121	34	features	feature	NOUN
cana-2865	121	35	from	from	ADP
cana-2865	121	36	the	the	DET
cana-2865	121	37	eeg	eeg	PROPN
cana-2865	121	38	data	datum	NOUN
cana-2865	121	39	,	,	PUNCT
cana-2865	121	40	developing	develop	VERB
cana-2865	121	41	a	a	DET
cana-2865	121	42	highly	highly	ADV
cana-2865	121	43	reliable	reliable	ADJ
cana-2865	121	44	and	and	CCONJ
cana-2865	121	45	accurate	accurate	ADJ
cana-2865	121	46	system	system	NOUN
cana-2865	121	47	for	for	ADP
cana-2865	121	48	discovering	discover	VERB
cana-2865	121	49	serious	serious	ADJ
cana-2865	121	50	mood	mood	NOUN
cana-2865	121	51	disorders	disorder	NOUN
cana-2865	121	52	.	.	PUNCT
cana-2865	122	1	in	in	ADP
cana-2865	122	2	addition	addition	NOUN
cana-2865	122	3	,	,	PUNCT
cana-2865	122	4	they	they	PRON
cana-2865	122	5	presented	present	VERB
cana-2865	122	6	good	good	ADJ
cana-2865	122	7	outcomes	outcome	NOUN
cana-2865	122	8	,	,	PUNCT
cana-2865	122	9	the	the	DET
cana-2865	122	10	ann	ann	PROPN
cana-2865	122	11	,	,	PUNCT
cana-2865	122	12	naïve	naïve	PROPN
cana-2865	122	13	-	-	PUNCT
cana-2865	122	14	bayes	bayes	NOUN
cana-2865	122	15	,	,	PUNCT
cana-2865	122	16	and	and	CCONJ
cana-2865	122	17	qda	qda	PROPN
cana-2865	122	18	classifiers	classifier	NOUN
cana-2865	122	19	have	have	AUX
cana-2865	122	20	not	not	PART
cana-2865	122	21	been	be	AUX
cana-2865	122	22	as	as	ADV
cana-2865	122	23	successful	successful	ADJ
cana-2865	122	24	as	as	ADP
cana-2865	122	25	the	the	DET
cana-2865	122	26	svm	svm	PROPN
cana-2865	122	27	and	and	CCONJ
cana-2865	122	28	knn	knn	PROPN
cana-2865	122	29	models	model	NOUN
cana-2865	122	30	.	.	PUNCT
cana-2865	123	1	75.93	75.93	NUM
cana-2865	123	2	%	%	NOUN
cana-2865	123	3	accuracy	accuracy	NOUN
cana-2865	123	4	,	,	PUNCT
cana-2865	123	5	76.20	76.20	NUM
cana-2865	123	6	%	%	NOUN
cana-2865	123	7	precision	precision	NOUN
cana-2865	123	8	,	,	PUNCT
cana-2865	123	9	75.70	75.70	NUM
cana-2865	123	10	%	%	NOUN
cana-2865	123	11	recall	recall	NOUN
cana-2865	123	12	,	,	PUNCT
cana-2865	123	13	and	and	CCONJ
cana-2865	123	14	75.74	75.74	NUM
cana-2865	123	15	%	%	NOUN
cana-2865	123	16	f1	f1	NOUN
cana-2865	123	17	-	-	PUNCT
cana-2865	123	18	score	score	NOUN
cana-2865	123	19	were	be	AUX
cana-2865	123	20	achieved	achieve	VERB
cana-2865	123	21	by	by	ADP
cana-2865	123	22	the	the	DET
cana-2865	123	23	ann	ann	PROPN
cana-2865	123	24	model	model	NOUN
cana-2865	123	25	.	.	PUNCT
cana-2865	124	1	the	the	DET
cana-2865	124	2	accuracy	accuracy	NOUN
cana-2865	124	3	,	,	PUNCT
cana-2865	124	4	precision	precision	NOUN
cana-2865	124	5	,	,	PUNCT
cana-2865	124	6	recall	recall	NOUN
cana-2865	124	7	,	,	PUNCT
cana-2865	124	8	and	and	CCONJ
cana-2865	124	9	f1	f1	NOUN
cana-2865	124	10	-	-	PUNCT
cana-2865	124	11	score	score	NOUN
cana-2865	124	12	of	of	ADP
cana-2865	124	13	the	the	DET
cana-2865	124	14	naïve	naïve	ADJ
cana-2865	124	15	-	-	PUNCT
cana-2865	124	16	bayes	bayes	PROPN
cana-2865	124	17	model	model	NOUN
cana-2865	124	18	reached	reach	VERB
cana-2865	124	19	73.30	73.30	NUM
cana-2865	124	20	%	%	NOUN
cana-2865	124	21	,	,	PUNCT
cana-2865	124	22	72.91	72.91	NUM
cana-2865	124	23	%	%	NOUN
cana-2865	124	24	,	,	PUNCT
cana-2865	124	25	and	and	CCONJ
cana-2865	124	26	76.15	76.15	NUM
cana-2865	124	27	%	%	NOUN
cana-2865	124	28	,	,	PUNCT
cana-2865	124	29	respectively	respectively	ADV
cana-2865	124	30	.	.	PUNCT
cana-2865	125	1	the	the	DET
cana-2865	125	2	qda	qda	PROPN
cana-2865	125	3	model	model	NOUN
cana-2865	125	4	achieved	achieve	VERB
cana-2865	125	5	75.56	75.56	NUM
cana-2865	125	6	%	%	NOUN
cana-2865	125	7	accuracy	accuracy	NOUN
cana-2865	125	8	,	,	PUNCT
cana-2865	125	9	75.76	75.76	NUM
cana-2865	125	10	%	%	NOUN
cana-2865	125	11	precision	precision	NOUN
cana-2865	125	12	,	,	PUNCT
cana-2865	125	13	75.29	75.29	NUM
cana-2865	125	14	%	%	NOUN
cana-2865	125	15	recall	recall	NOUN
cana-2865	125	16	,	,	PUNCT
cana-2865	125	17	and	and	CCONJ
cana-2865	125	18	70.34	70.34	NUM
cana-2865	125	19	%	%	NOUN
cana-2865	125	20	f1	f1	NOUN
cana-2865	125	21	-	-	PUNCT
cana-2865	125	22	score	score	NOUN
cana-2865	125	23	.	.	PUNCT
cana-2865	126	1	the	the	DET
cana-2865	126	2	results	result	NOUN
cana-2865	126	3	shown	show	VERB
cana-2865	126	4	in	in	ADP
cana-2865	126	5	[	[	X
cana-2865	126	6	36	36	NUM
cana-2865	126	7	]	]	PUNCT
cana-2865	126	8	demonstrate	demonstrate	VERB
cana-2865	126	9	that	that	SCONJ
cana-2865	126	10	the	the	DET
cana-2865	126	11	firefly	firefly	NOUN
cana-2865	126	12	algorithm	algorithm	NOUN
cana-2865	126	13	-	-	PUNCT
cana-2865	126	14	based	base	VERB
cana-2865	126	15	feature	feature	NOUN
cana-2865	126	16	selection	selection	NOUN
cana-2865	126	17	method	method	NOUN
cana-2865	126	18	may	may	AUX
cana-2865	126	19	successfully	successfully	ADV
cana-2865	126	20	uncover	uncover	VERB
cana-2865	126	21	the	the	DET
cana-2865	126	22	communications	communication	NOUN
cana-2865	126	23	on	on	ADP
cana-2865	126	24	applied	apply	VERB
cana-2865	126	25	nonlinear	nonlinear	ADJ
cana-2865	126	26	analysis	analysis	NOUN
cana-2865	126	27	issn	issn	NOUN
cana-2865	126	28	:	:	PUNCT
cana-2865	126	29	1074	1074	NUM
cana-2865	126	30	-	-	PUNCT
cana-2865	126	31	133x	133x	NUM
cana-2865	126	32	vol	vol	NOUN
cana-2865	126	33	32	32	NUM
cana-2865	126	34	no	no	NOUN
cana-2865	126	35	.	.	PUNCT
cana-2865	127	1	4s	4s	NUM
cana-2865	127	2	(	(	PUNCT
cana-2865	127	3	2025	2025	NUM
cana-2865	127	4	)	)	PUNCT
cana-2865	127	5	475	475	NUM
cana-2865	127	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	127	7	most	most	ADJ
cana-2865	127	8	discriminant	discriminant	ADJ
cana-2865	127	9	eeg	eeg	PROPN
cana-2865	127	10	features	feature	NOUN
cana-2865	127	11	,	,	PUNCT
cana-2865	127	12	resulting	result	VERB
cana-2865	127	13	in	in	ADP
cana-2865	127	14	a	a	DET
cana-2865	127	15	notable	notable	ADJ
cana-2865	127	16	increase	increase	NOUN
cana-2865	127	17	in	in	ADP
cana-2865	127	18	the	the	DET
cana-2865	127	19	classification	classification	NOUN
cana-2865	127	20	accuracy	accuracy	NOUN
cana-2865	127	21	for	for	ADP
cana-2865	127	22	diagnosing	diagnose	VERB
cana-2865	127	23	melancholy	melancholy	ADJ
cana-2865	127	24	.	.	PUNCT
cana-2865	128	1	table	table	NOUN
cana-2865	128	2	2	2	NUM
cana-2865	128	3	.	.	PUNCT
cana-2865	128	4	comparison	comparison	NOUN
cana-2865	128	5	of	of	ADP
cana-2865	128	6	metrics	metric	NOUN
cana-2865	128	7	for	for	ADP
cana-2865	128	8	ffa	ffa	PROPN
cana-2865	128	9	,	,	PUNCT
cana-2865	128	10	ga	ga	PROPN
cana-2865	128	11	selection	selection	NOUN
cana-2865	128	12	,	,	PUNCT
cana-2865	128	13	and	and	CCONJ
cana-2865	128	14	without	without	ADP
cana-2865	128	15	feature	feature	NOUN
cana-2865	128	16	selection	selection	NOUN
cana-2865	128	17	classifier	classifier	NOUN
cana-2865	128	18	feature	feature	NOUN
cana-2865	128	19	selection	selection	NOUN
cana-2865	128	20	accuracy	accuracy	NOUN
cana-2865	128	21	precision	precision	NOUN
cana-2865	128	22	recall	recall	VERB
cana-2865	128	23	f1_score	f1_score	ADV
cana-2865	128	24	knn	knn	VERB
cana-2865	129	1	none	none	NOUN
cana-2865	129	2	86.4662	86.4662	NUM
cana-2865	129	3	86.6228	86.6228	NUM
cana-2865	129	4	86.1225	86.1225	NUM
cana-2865	129	5	86.2918	86.2918	NUM
cana-2865	129	6	ga	ga	NOUN
cana-2865	129	7	90.6015	90.6015	NUM
cana-2865	129	8	91.1184	91.1184	NUM
cana-2865	129	9	90.3614	90.3614	NUM
cana-2865	129	10	90.5177	90.5177	NUM
cana-2865	129	11	fa	fa	NOUN
cana-2865	129	12	94.7368	94.7368	NUM
cana-2865	129	13	94.2982	94.2982	NUM
cana-2865	129	14	94.9836	94.9836	NUM
cana-2865	129	15	94.5888	94.5888	NUM
cana-2865	129	16	ann	ann	PROPN
cana-2865	129	17	none	none	NOUN
cana-2865	129	18	75.5639	75.5639	NUM
cana-2865	129	19	75.2193	75.2193	NUM
cana-2865	129	20	75.2193	75.2193	NUM
cana-2865	129	21	75.1334	75.1334	NUM
cana-2865	129	22	ga	ga	PROPN
cana-2865	129	23	78.5714	78.5714	NUM
cana-2865	129	24	79.8246	79.8246	NUM
cana-2865	129	25	79.4557	79.4557	NUM
cana-2865	129	26	78.5566	78.5566	NUM
cana-2865	129	27	fa	fa	NOUN
cana-2865	129	28	75.9398	75.9398	NUM
cana-2865	129	29	76.2061	76.2061	NUM
cana-2865	129	30	75.7077	75.7077	NUM
cana-2865	129	31	75.7424	75.7424	NUM
cana-2865	129	32	nb	nb	ADP
cana-2865	129	33	none	none	NOUN
cana-2865	129	34	71.0526	71.0526	NUM
cana-2865	129	35	70.2851	70.2851	NUM
cana-2865	129	36	72.3164	72.3164	NUM
cana-2865	129	37	70.3482	70.3482	NUM
cana-2865	129	38	ga	ga	PROPN
cana-2865	129	39	72.9323	72.9323	NUM
cana-2865	129	40	70.9430	70.9430	NUM
cana-2865	129	41	73.8883	73.8883	NUM
cana-2865	129	42	71.2691	71.2691	NUM
cana-2865	129	43	fa	fa	NOUN
cana-2865	129	44	73.3083	73.3083	NUM
cana-2865	129	45	72.9167	72.9167	NUM
cana-2865	129	46	76.1523	76.1523	NUM
cana-2865	129	47	72.8380	72.8380	NUM
cana-2865	129	48	qda	qda	NOUN
cana-2865	129	49	none	none	NOUN
cana-2865	129	50	68.4211	68.4211	NUM
cana-2865	129	51	69.2982	69.2982	NUM
cana-2865	129	52	68.9914	68.9914	NUM
cana-2865	129	53	68.3764	68.3764	NUM
cana-2865	129	54	ga	ga	PROPN
cana-2865	129	55	70.6767	70.6767	NUM
cana-2865	129	56	71.6009	71.6009	NUM
cana-2865	129	57	71.2574	71.2574	NUM
cana-2865	129	58	70.6352	70.6352	NUM
cana-2865	129	59	fa	fa	NOUN
cana-2865	129	60	75.5639	75.5639	NUM
cana-2865	129	61	75.7675	75.7675	NUM
cana-2865	129	62	75.2932	75.2932	NUM
cana-2865	129	63	75.3461	75.3461	NUM
cana-2865	129	64	svm	svm	NOUN
cana-2865	129	65	none	none	NOUN
cana-2865	129	66	87.5940	87.5940	NUM
cana-2865	129	67	86.0746	86.0746	NUM
cana-2865	129	68	89.2527	89.2527	NUM
cana-2865	129	69	86.9053	86.9053	NUM
cana-2865	129	70	ga	ga	NOUN
cana-2865	129	71	91.7293	91.7293	NUM
cana-2865	129	72	91.0088	91.0088	NUM
cana-2865	129	73	92.1771	92.1771	NUM
cana-2865	129	74	91.4509	91.4509	NUM
cana-2865	129	75	fa	fa	NOUN
cana-2865	129	76	96.2406	96.2406	NUM
cana-2865	129	77	95.9430	95.9430	NUM
cana-2865	129	78	96.3928	96.3928	NUM
cana-2865	129	79	96.1445	96.1445	NUM
cana-2865	129	80	table	table	NOUN
cana-2865	129	81	2	2	NUM
cana-2865	129	82	reports	report	VERB
cana-2865	129	83	the	the	DET
cana-2865	129	84	comparison	comparison	NOUN
cana-2865	129	85	of	of	ADP
cana-2865	129	86	three	three	NUM
cana-2865	129	87	approaches	approach	NOUN
cana-2865	129	88	where	where	SCONJ
cana-2865	129	89	none	none	NOUN
cana-2865	129	90	means	mean	VERB
cana-2865	129	91	without	without	ADP
cana-2865	129	92	feature	feature	NOUN
cana-2865	129	93	selection	selection	NOUN
cana-2865	129	94	.	.	PUNCT
cana-2865	130	1	the	the	DET
cana-2865	130	2	firefly	firefly	NOUN
cana-2865	130	3	algorithm	algorithm	NOUN
cana-2865	130	4	(	(	PUNCT
cana-2865	130	5	fa	fa	NOUN
cana-2865	130	6	)	)	PUNCT
cana-2865	130	7	significantly	significantly	ADV
cana-2865	130	8	raised	raise	VERB
cana-2865	130	9	all	all	DET
cana-2865	130	10	algorithms	algorithm	NOUN
cana-2865	130	11	'	'	PART
cana-2865	130	12	classification	classification	NOUN
cana-2865	130	13	accuracy	accuracy	NOUN
cana-2865	130	14	by	by	ADP
cana-2865	130	15	picking	pick	VERB
cana-2865	130	16	the	the	DET
cana-2865	130	17	feature	feature	NOUN
cana-2865	130	18	subsets	subset	NOUN
cana-2865	130	19	with	with	ADP
cana-2865	130	20	greater	great	ADJ
cana-2865	130	21	efficiency	efficiency	NOUN
cana-2865	130	22	.	.	PUNCT
cana-2865	131	1	the	the	DET
cana-2865	131	2	outcomes	outcome	NOUN
cana-2865	131	3	of	of	ADP
cana-2865	131	4	every	every	DET
cana-2865	131	5	model	model	NOUN
cana-2865	131	6	are	be	AUX
cana-2865	131	7	summarized	summarize	VERB
cana-2865	131	8	in	in	ADP
cana-2865	131	9	table	table	NOUN
cana-2865	131	10	1	1	NUM
cana-2865	131	11	.	.	PUNCT
cana-2865	132	1	svm	svm	PROPN
cana-2865	132	2	(	(	PUNCT
cana-2865	132	3	96.24	96.24	NUM
cana-2865	132	4	%	%	NOUN
cana-2865	132	5	)	)	PUNCT
cana-2865	132	6	and	and	CCONJ
cana-2865	132	7	knn	knn	X
cana-2865	132	8	(	(	PUNCT
cana-2865	132	9	94.74	94.74	NUM
cana-2865	132	10	%	%	NOUN
cana-2865	132	11	)	)	PUNCT
cana-2865	132	12	had	have	VERB
cana-2865	132	13	the	the	DET
cana-2865	132	14	best	good	ADJ
cana-2865	132	15	diagnostic	diagnostic	ADJ
cana-2865	132	16	accuracy	accuracy	NOUN
cana-2865	132	17	when	when	SCONJ
cana-2865	132	18	applying	apply	VERB
cana-2865	132	19	fa	fa	NOUN
cana-2865	132	20	-	-	PUNCT
cana-2865	132	21	optimized	optimize	VERB
cana-2865	132	22	feature	feature	NOUN
cana-2865	132	23	selection	selection	NOUN
cana-2865	132	24	.	.	PUNCT
cana-2865	133	1	svm	svm	PROPN
cana-2865	133	2	(	(	PUNCT
cana-2865	133	3	96.24	96.24	NUM
cana-2865	133	4	%	%	NOUN
cana-2865	133	5	)	)	PUNCT
cana-2865	133	6	and	and	CCONJ
cana-2865	133	7	knn	knn	X
cana-2865	133	8	(	(	PUNCT
cana-2865	133	9	94.74	94.74	NUM
cana-2865	133	10	%	%	NOUN
cana-2865	133	11	)	)	PUNCT
cana-2865	133	12	have	have	AUX
cana-2865	133	13	demonstrated	demonstrate	VERB
cana-2865	133	14	the	the	DET
cana-2865	133	15	highest	high	ADJ
cana-2865	133	16	diagnostic	diagnostic	ADJ
cana-2865	133	17	accuracy	accuracy	NOUN
cana-2865	133	18	when	when	SCONJ
cana-2865	133	19	using	use	VERB
cana-2865	133	20	fa	fa	NOUN
cana-2865	133	21	-	-	PUNCT
cana-2865	133	22	optimized	optimize	VERB
cana-2865	133	23	feature	feature	NOUN
cana-2865	133	24	selection	selection	NOUN
cana-2865	133	25	.	.	PUNCT
cana-2865	134	1	an	an	DET
cana-2865	134	2	adequate	adequate	ADJ
cana-2865	134	3	level	level	NOUN
cana-2865	134	4	of	of	ADP
cana-2865	134	5	performance	performance	NOUN
cana-2865	134	6	was	be	AUX
cana-2865	134	7	demonstrated	demonstrate	VERB
cana-2865	134	8	by	by	ADP
cana-2865	134	9	the	the	DET
cana-2865	134	10	qda	qda	NOUN
cana-2865	134	11	and	and	CCONJ
cana-2865	134	12	ann	ann	PROPN
cana-2865	134	13	accuracy	accuracy	NOUN
cana-2865	134	14	achievements	achievement	NOUN
cana-2865	134	15	,	,	PUNCT
cana-2865	134	16	with	with	ADP
cana-2865	134	17	scores	score	NOUN
cana-2865	134	18	of	of	ADP
cana-2865	134	19	75.56	75.56	NUM
cana-2865	134	20	%	%	NOUN
cana-2865	134	21	and	and	CCONJ
cana-2865	134	22	75.94	75.94	NUM
cana-2865	134	23	%	%	NOUN
cana-2865	134	24	,	,	PUNCT
cana-2865	134	25	respectively	respectively	ADV
cana-2865	134	26	.	.	PUNCT
cana-2865	135	1	the	the	DET
cana-2865	135	2	naïve	naïve	ADJ
cana-2865	135	3	bayes	bayes	PROPN
cana-2865	135	4	algorithm	algorithm	PROPN
cana-2865	135	5	produced	produce	VERB
cana-2865	135	6	the	the	DET
cana-2865	135	7	worst	bad	ADJ
cana-2865	135	8	results	result	NOUN
cana-2865	135	9	,	,	PUNCT
cana-2865	135	10	scoring	score	VERB
cana-2865	135	11	73.31	73.31	NUM
cana-2865	135	12	%	%	NOUN
cana-2865	135	13	,	,	PUNCT
cana-2865	135	14	since	since	SCONJ
cana-2865	135	15	it	it	PRON
cana-2865	135	16	heavily	heavily	ADV
cana-2865	135	17	relies	rely	VERB
cana-2865	135	18	on	on	ADP
cana-2865	135	19	the	the	DET
cana-2865	135	20	idea	idea	NOUN
cana-2865	135	21	of	of	ADP
cana-2865	135	22	feature	feature	NOUN
cana-2865	135	23	independence	independence	NOUN
cana-2865	135	24	.	.	PUNCT
cana-2865	136	1	fa	fa	PROPN
cana-2865	136	2	predicted	predict	VERB
cana-2865	136	3	the	the	DET
cana-2865	136	4	number	number	NOUN
cana-2865	136	5	of	of	ADP
cana-2865	136	6	features	feature	NOUN
cana-2865	136	7	required	require	VERB
cana-2865	136	8	in	in	ADP
cana-2865	136	9	each	each	DET
cana-2865	136	10	technique	technique	NOUN
cana-2865	136	11	without	without	ADP
cana-2865	136	12	sacrificing	sacrifice	VERB
cana-2865	136	13	accuracy	accuracy	NOUN
cana-2865	136	14	,	,	PUNCT
cana-2865	136	15	leading	lead	VERB
cana-2865	136	16	to	to	ADP
cana-2865	136	17	the	the	DET
cana-2865	136	18	development	development	NOUN
cana-2865	136	19	of	of	ADP
cana-2865	136	20	smaller	small	ADJ
cana-2865	136	21	,	,	PUNCT
cana-2865	136	22	more	more	ADV
cana-2865	136	23	comprehensible	comprehensible	ADJ
cana-2865	136	24	models	model	NOUN
cana-2865	136	25	.	.	PUNCT
cana-2865	137	1	the	the	DET
cana-2865	137	2	models	model	NOUN
cana-2865	137	3	'	'	PART
cana-2865	137	4	feature	feature	NOUN
cana-2865	137	5	reduction	reduction	NOUN
cana-2865	137	6	rates	rate	NOUN
cana-2865	137	7	varied	vary	VERB
cana-2865	137	8	,	,	PUNCT
cana-2865	137	9	ranging	range	VERB
cana-2865	137	10	from	from	ADP
cana-2865	137	11	30	30	NUM
cana-2865	137	12	%	%	NOUN
cana-2865	137	13	to	to	PART
cana-2865	137	14	40	40	NUM
cana-2865	137	15	%	%	NOUN
cana-2865	137	16	.	.	PUNCT
cana-2865	138	1	in	in	ADP
cana-2865	138	2	medical	medical	ADJ
cana-2865	138	3	diagnostics	diagnostic	NOUN
cana-2865	138	4	,	,	PUNCT
cana-2865	138	5	computational	computational	ADJ
cana-2865	138	6	efficiency	efficiency	NOUN
cana-2865	138	7	and	and	CCONJ
cana-2865	138	8	interpretability	interpretability	NOUN
cana-2865	138	9	are	be	AUX
cana-2865	138	10	crucial	crucial	ADJ
cana-2865	138	11	,	,	PUNCT
cana-2865	138	12	and	and	CCONJ
cana-2865	138	13	this	this	DET
cana-2865	138	14	reduction	reduction	NOUN
cana-2865	138	15	is	be	AUX
cana-2865	138	16	particularly	particularly	ADV
cana-2865	138	17	noteworthy	noteworthy	ADJ
cana-2865	138	18	[	[	X
cana-2865	138	19	37	37	NUM
cana-2865	138	20	-	-	SYM
cana-2865	138	21	38	38	NUM
cana-2865	138	22	]	]	PUNCT
cana-2865	138	23	.	.	PUNCT
cana-2865	139	1	communications	communication	NOUN
cana-2865	139	2	on	on	ADP
cana-2865	139	3	applied	apply	VERB
cana-2865	139	4	nonlinear	nonlinear	ADJ
cana-2865	139	5	analysis	analysis	NOUN
cana-2865	139	6	issn	issn	NOUN
cana-2865	139	7	:	:	PUNCT
cana-2865	139	8	1074	1074	NUM
cana-2865	139	9	-	-	PUNCT
cana-2865	139	10	133x	133x	NUM
cana-2865	139	11	vol	vol	NOUN
cana-2865	139	12	32	32	NUM
cana-2865	139	13	no	no	NOUN
cana-2865	139	14	.	.	PUNCT
cana-2865	140	1	4s	4s	NUM
cana-2865	140	2	(	(	PUNCT
cana-2865	140	3	2025	2025	NUM
cana-2865	140	4	)	)	PUNCT
cana-2865	140	5	476	476	NUM
cana-2865	140	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	140	7	figure	figure	NOUN
cana-2865	140	8	2	2	NUM
cana-2865	140	9	-	-	SYM
cana-2865	140	10	6	6	NUM
cana-2865	140	11	:	:	PUNCT
cana-2865	140	12	improvement	improvement	NOUN
cana-2865	140	13	in	in	ADP
cana-2865	140	14	performance	performance	NOUN
cana-2865	140	15	metrics	metric	NOUN
cana-2865	140	16	of	of	ADP
cana-2865	140	17	knn	knn	PROPN
cana-2865	140	18	,	,	PUNCT
cana-2865	140	19	ann	ann	PROPN
cana-2865	140	20	,	,	PUNCT
cana-2865	140	21	nb	nb	PROPN
cana-2865	140	22	,	,	PUNCT
cana-2865	140	23	qda	qda	PROPN
cana-2865	140	24	,	,	PUNCT
cana-2865	140	25	and	and	CCONJ
cana-2865	140	26	svm	svm	PROPN
cana-2865	140	27	.	.	PROPN
cana-2865	141	1	in	in	ADP
cana-2865	141	2	particular	particular	ADJ
cana-2865	141	3	,	,	PUNCT
cana-2865	141	4	for	for	ADP
cana-2865	141	5	svm	svm	NOUN
cana-2865	141	6	and	and	CCONJ
cana-2865	141	7	knn	knn	PROPN
cana-2865	141	8	models	model	NOUN
cana-2865	141	9	,	,	PUNCT
cana-2865	141	10	observations	observation	NOUN
cana-2865	141	11	demonstrate	demonstrate	VERB
cana-2865	141	12	that	that	SCONJ
cana-2865	141	13	the	the	DET
cana-2865	141	14	firefly	firefly	NOUN
cana-2865	141	15	algorithm	algorithm	NOUN
cana-2865	141	16	is	be	AUX
cana-2865	141	17	highly	highly	ADV
cana-2865	141	18	flourishing	flourishing	ADJ
cana-2865	141	19	at	at	ADP
cana-2865	141	20	optimizing	optimize	VERB
cana-2865	141	21	feature	feature	NOUN
cana-2865	141	22	selection	selection	NOUN
cana-2865	141	23	for	for	ADP
cana-2865	141	24	mdd	mdd	PROPN
cana-2865	141	25	diagnosis	diagnosis	NOUN
cana-2865	141	26	.	.	PUNCT
cana-2865	142	1	in	in	ADP
cana-2865	142	2	addition	addition	NOUN
cana-2865	142	3	to	to	ADP
cana-2865	142	4	fa	fa	PROPN
cana-2865	142	5	,	,	PUNCT
cana-2865	142	6	medical	medical	ADJ
cana-2865	142	7	diagnosis	diagnosis	NOUN
cana-2865	142	8	can	can	AUX
cana-2865	142	9	be	be	AUX
cana-2865	142	10	further	far	ADV
cana-2865	142	11	improved	improve	VERB
cana-2865	142	12	by	by	ADP
cana-2865	142	13	identifying	identify	VERB
cana-2865	142	14	the	the	DET
cana-2865	142	15	most	most	ADV
cana-2865	142	16	pertinent	pertinent	ADJ
cana-2865	142	17	characteristics	characteristic	NOUN
cana-2865	142	18	,	,	PUNCT
cana-2865	142	19	as	as	SCONJ
cana-2865	142	20	evidenced	evidence	VERB
cana-2865	142	21	by	by	ADP
cana-2865	142	22	the	the	DET
cana-2865	142	23	notable	notable	ADJ
cana-2865	142	24	improvement	improvement	NOUN
cana-2865	142	25	in	in	ADP
cana-2865	142	26	classification	classification	NOUN
cana-2865	142	27	accuracy	accuracy	NOUN
cana-2865	142	28	.	.	PUNCT
cana-2865	143	1	another	another	DET
cana-2865	143	2	factor	factor	NOUN
cana-2865	143	3	that	that	PRON
cana-2865	143	4	suggests	suggest	VERB
cana-2865	143	5	that	that	SCONJ
cana-2865	143	6	fa	fa	PROPN
cana-2865	143	7	is	be	AUX
cana-2865	143	8	an	an	DET
cana-2865	143	9	adequate	adequate	ADJ
cana-2865	143	10	match	match	NOUN
cana-2865	143	11	for	for	ADP
cana-2865	143	12	medical	medical	ADJ
cana-2865	143	13	applications	application	NOUN
cana-2865	143	14	—	—	PUNCT
cana-2865	143	15	where	where	SCONJ
cana-2865	143	16	extremely	extremely	ADV
cana-2865	143	17	dimensional	dimensional	ADJ
cana-2865	143	18	data	datum	NOUN
cana-2865	143	19	is	be	AUX
cana-2865	143	20	more	more	ADV
cana-2865	143	21	often	often	ADV
cana-2865	143	22	encountered	encounter	VERB
cana-2865	143	23	—	—	PUNCT
cana-2865	143	24	is	be	AUX
cana-2865	143	25	its	its	PRON
cana-2865	143	26	capability	capability	NOUN
cana-2865	143	27	to	to	PART
cana-2865	143	28	reduce	reduce	VERB
cana-2865	143	29	dataset	dataset	ADJ
cana-2865	143	30	dimensionality	dimensionality	NOUN
cana-2865	143	31	without	without	ADP
cana-2865	143	32	affecting	affect	VERB
cana-2865	143	33	accuracy	accuracy	NOUN
cana-2865	143	34	[	[	X
cana-2865	143	35	39	39	NUM
cana-2865	143	36	-	-	SYM
cana-2865	143	37	40	40	NUM
cana-2865	143	38	]	]	PUNCT
cana-2865	143	39	.	.	PUNCT
cana-2865	144	1	features	feature	VERB
cana-2865	144	2	augmentation	augmentation	NOUN
cana-2865	144	3	(	(	PUNCT
cana-2865	144	4	fa	fa	NOUN
cana-2865	144	5	)	)	PUNCT
cana-2865	144	6	presents	present	VERB
cana-2865	144	7	a	a	DET
cana-2865	144	8	more	more	ADV
cana-2865	144	9	flexible	flexible	ADJ
cana-2865	144	10	and	and	CCONJ
cana-2865	144	11	successful	successful	ADJ
cana-2865	144	12	feature	feature	NOUN
cana-2865	144	13	optimization	optimization	NOUN
cana-2865	144	14	approach	approach	NOUN
cana-2865	144	15	compared	compare	VERB
cana-2865	144	16	to	to	ADP
cana-2865	144	17	previous	previous	ADJ
cana-2865	144	18	feature	feature	NOUN
cana-2865	144	19	selection	selection	NOUN
cana-2865	144	20	techniques	technique	NOUN
cana-2865	144	21	.	.	PUNCT
cana-2865	145	1	it	it	PRON
cana-2865	145	2	can	can	AUX
cana-2865	145	3	avoid	avoid	VERB
cana-2865	145	4	the	the	DET
cana-2865	145	5	traps	trap	NOUN
cana-2865	145	6	of	of	ADP
cana-2865	145	7	local	local	ADJ
cana-2865	145	8	optima	optima	NOUN
cana-2865	145	9	,	,	PUNCT
cana-2865	145	10	which	which	PRON
cana-2865	145	11	may	may	AUX
cana-2865	145	12	decrease	decrease	VERB
cana-2865	145	13	the	the	DET
cana-2865	145	14	performance	performance	NOUN
cana-2865	145	15	of	of	ADP
cana-2865	145	16	other	other	ADJ
cana-2865	145	17	metaheuristics	metaheuristic	NOUN
cana-2865	145	18	such	such	ADJ
cana-2865	145	19	as	as	ADP
cana-2865	145	20	ga	ga	PROPN
cana-2865	145	21	and	and	CCONJ
cana-2865	145	22	pso	pso	NOUN
cana-2865	145	23	,	,	PUNCT
cana-2865	145	24	owing	owe	VERB
cana-2865	145	25	to	to	ADP
cana-2865	145	26	its	its	PRON
cana-2865	145	27	dynamic	dynamic	ADJ
cana-2865	145	28	balance	balance	NOUN
cana-2865	145	29	between	between	ADP
cana-2865	145	30	exploration	exploration	NOUN
cana-2865	145	31	and	and	CCONJ
cana-2865	145	32	exploitation	exploitation	NOUN
cana-2865	145	33	[	[	X
cana-2865	145	34	41	41	NUM
cana-2865	145	35	-	-	SYM
cana-2865	145	36	42	42	NUM
cana-2865	145	37	]	]	PUNCT
cana-2865	145	38	.	.	PUNCT
cana-2865	146	1	in	in	ADP
cana-2865	146	2	particular	particular	ADJ
cana-2865	146	3	,	,	PUNCT
cana-2865	146	4	the	the	DET
cana-2865	146	5	fa	fa	NOUN
cana-2865	146	6	-	-	PUNCT
cana-2865	146	7	optimized	optimize	VERB
cana-2865	146	8	svm	svm	PROPN
cana-2865	146	9	model	model	NOUN
cana-2865	146	10	exhibits	exhibit	VERB
cana-2865	146	11	promise	promise	NOUN
cana-2865	146	12	for	for	ADP
cana-2865	146	13	practical	practical	ADJ
cana-2865	146	14	clinical	clinical	ADJ
cana-2865	146	15	applications	application	NOUN
cana-2865	146	16	where	where	SCONJ
cana-2865	146	17	diagnostic	diagnostic	ADJ
cana-2865	146	18	precision	precision	NOUN
cana-2865	146	19	is	be	AUX
cana-2865	146	20	crucial	crucial	ADJ
cana-2865	146	21	[	[	X
cana-2865	146	22	43	43	NUM
cana-2865	146	23	]	]	PUNCT
cana-2865	146	24	.	.	PUNCT
cana-2865	147	1	communications	communication	NOUN
cana-2865	147	2	on	on	ADP
cana-2865	147	3	applied	apply	VERB
cana-2865	147	4	nonlinear	nonlinear	ADJ
cana-2865	147	5	analysis	analysis	NOUN
cana-2865	147	6	issn	issn	NOUN
cana-2865	147	7	:	:	PUNCT
cana-2865	147	8	1074	1074	NUM
cana-2865	147	9	-	-	PUNCT
cana-2865	147	10	133x	133x	NUM
cana-2865	147	11	vol	vol	NOUN
cana-2865	147	12	32	32	NUM
cana-2865	147	13	no	no	NOUN
cana-2865	147	14	.	.	PUNCT
cana-2865	148	1	4s	4s	NUM
cana-2865	148	2	(	(	PUNCT
cana-2865	148	3	2025	2025	NUM
cana-2865	148	4	)	)	PUNCT
cana-2865	148	5	477	477	NUM
cana-2865	148	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	149	1	the	the	DET
cana-2865	149	2	principal	principal	ADJ
cana-2865	149	3	contributions	contribution	NOUN
cana-2865	149	4	to	to	ADP
cana-2865	149	5	this	this	DET
cana-2865	149	6	work	work	NOUN
cana-2865	149	7	are	be	AUX
cana-2865	149	8	as	as	SCONJ
cana-2865	149	9	follows	follow	VERB
cana-2865	149	10	:	:	PUNCT
cana-2865	149	11	we	we	PRON
cana-2865	149	12	encourage	encourage	VERB
cana-2865	149	13	a	a	DET
cana-2865	149	14	novel	novel	ADJ
cana-2865	149	15	firefly	firefly	NOUN
cana-2865	149	16	algorithm	algorithm	NOUN
cana-2865	149	17	-	-	PUNCT
cana-2865	149	18	based	base	VERB
cana-2865	149	19	feature	feature	NOUN
cana-2865	149	20	selection	selection	NOUN
cana-2865	149	21	method	method	NOUN
cana-2865	149	22	for	for	ADP
cana-2865	149	23	accurately	accurately	ADV
cana-2865	149	24	diagnosing	diagnose	VERB
cana-2865	149	25	major	major	ADJ
cana-2865	149	26	depressive	depressive	ADJ
cana-2865	149	27	disorder	disorder	NOUN
cana-2865	149	28	from	from	ADP
cana-2865	149	29	eeg	eeg	NOUN
cana-2865	149	30	signals	signal	NOUN
cana-2865	149	31	.	.	PUNCT
cana-2865	150	1	the	the	DET
cana-2865	150	2	fa	fa	NOUN
cana-2865	150	3	-	-	PUNCT
cana-2865	150	4	based	base	VERB
cana-2865	150	5	feature	feature	NOUN
cana-2865	150	6	selection	selection	NOUN
cana-2865	150	7	approach	approach	NOUN
cana-2865	150	8	is	be	AUX
cana-2865	150	9	shown	show	VERB
cana-2865	150	10	to	to	PART
cana-2865	150	11	be	be	AUX
cana-2865	150	12	more	more	ADV
cana-2865	150	13	effective	effective	ADJ
cana-2865	150	14	than	than	ADP
cana-2865	150	15	conventional	conventional	ADJ
cana-2865	150	16	techniques	technique	NOUN
cana-2865	150	17	like	like	ADP
cana-2865	150	18	ga	ga	PROPN
cana-2865	150	19	,	,	PUNCT
cana-2865	150	20	as	as	SCONJ
cana-2865	150	21	demonstrated	demonstrate	VERB
cana-2865	150	22	by	by	ADP
cana-2865	150	23	the	the	DET
cana-2865	150	24	higher	high	ADJ
cana-2865	150	25	classification	classification	NOUN
cana-2865	150	26	accuracy	accuracy	NOUN
cana-2865	150	27	,	,	PUNCT
cana-2865	150	28	precision	precision	NOUN
cana-2865	150	29	,	,	PUNCT
cana-2865	150	30	recall	recall	NOUN
cana-2865	150	31	,	,	PUNCT
cana-2865	150	32	and	and	CCONJ
cana-2865	150	33	f1	f1	NOUN
cana-2865	150	34	score	score	NOUN
cana-2865	150	35	achieved	achieve	VERB
cana-2865	150	36	by	by	ADP
cana-2865	150	37	svm	svm	PROPN
cana-2865	150	38	and	and	CCONJ
cana-2865	150	39	knn	knn	PROPN
cana-2865	150	40	classifiers	classifier	NOUN
cana-2865	150	41	.	.	PUNCT
cana-2865	151	1	the	the	DET
cana-2865	151	2	reduction	reduction	NOUN
cana-2865	151	3	in	in	ADP
cana-2865	151	4	the	the	DET
cana-2865	151	5	number	number	NOUN
cana-2865	151	6	of	of	ADP
cana-2865	151	7	features	feature	NOUN
cana-2865	151	8	without	without	ADP
cana-2865	151	9	sacrificing	sacrifice	VERB
cana-2865	151	10	accuracy	accuracy	NOUN
cana-2865	151	11	is	be	AUX
cana-2865	151	12	particularly	particularly	ADV
cana-2865	151	13	beneficial	beneficial	ADJ
cana-2865	151	14	in	in	ADP
cana-2865	151	15	medical	medical	ADJ
cana-2865	151	16	applications	application	NOUN
cana-2865	151	17	where	where	SCONJ
cana-2865	151	18	interpretability	interpretability	NOUN
cana-2865	151	19	and	and	CCONJ
cana-2865	151	20	computational	computational	ADJ
cana-2865	151	21	efficiency	efficiency	NOUN
cana-2865	151	22	are	be	AUX
cana-2865	151	23	important	important	ADJ
cana-2865	151	24	.	.	PUNCT
cana-2865	152	1	future	future	ADJ
cana-2865	152	2	work	work	NOUN
cana-2865	152	3	could	could	AUX
cana-2865	152	4	explore	explore	VERB
cana-2865	152	5	using	use	VERB
cana-2865	152	6	deep	deep	ADJ
cana-2865	152	7	learning	learning	NOUN
cana-2865	152	8	for	for	ADP
cana-2865	152	9	feature	feature	NOUN
cana-2865	152	10	extraction	extraction	NOUN
cana-2865	152	11	and	and	CCONJ
cana-2865	152	12	classification	classification	NOUN
cana-2865	152	13	,	,	PUNCT
cana-2865	152	14	test	test	VERB
cana-2865	152	15	different	different	ADJ
cana-2865	152	16	eeg	eeg	NOUN
cana-2865	152	17	electrode	electrode	NOUN
cana-2865	152	18	placements	placement	NOUN
cana-2865	152	19	,	,	PUNCT
cana-2865	152	20	and	and	CCONJ
cana-2865	152	21	track	track	VERB
cana-2865	152	22	how	how	SCONJ
cana-2865	152	23	these	these	DET
cana-2865	152	24	models	model	NOUN
cana-2865	152	25	perform	perform	VERB
cana-2865	152	26	over	over	ADP
cana-2865	152	27	time	time	NOUN
cana-2865	152	28	in	in	ADP
cana-2865	152	29	detecting	detect	VERB
cana-2865	152	30	changes	change	NOUN
cana-2865	152	31	in	in	ADP
cana-2865	152	32	major	major	ADJ
cana-2865	152	33	depressive	depressive	ADJ
cana-2865	152	34	disorder	disorder	NOUN
cana-2865	152	35	.	.	PUNCT
cana-2865	153	1	incorporating	incorporate	VERB
cana-2865	153	2	other	other	ADJ
cana-2865	153	3	data	datum	NOUN
cana-2865	153	4	types	type	NOUN
cana-2865	153	5	,	,	PUNCT
cana-2865	153	6	like	like	ADP
cana-2865	153	7	behavior	behavior	NOUN
cana-2865	153	8	and	and	CCONJ
cana-2865	153	9	demographics	demographic	NOUN
cana-2865	153	10	,	,	PUNCT
cana-2865	153	11	may	may	AUX
cana-2865	153	12	also	also	ADV
cana-2865	153	13	improve	improve	VERB
cana-2865	153	14	classification	classification	NOUN
cana-2865	153	15	and	and	CCONJ
cana-2865	153	16	provide	provide	VERB
cana-2865	153	17	more	more	ADJ
cana-2865	153	18	insights	insight	NOUN
cana-2865	153	19	into	into	ADP
cana-2865	153	20	the	the	DET
cana-2865	153	21	disorder	disorder	NOUN
cana-2865	153	22	.	.	PUNCT
cana-2865	154	1	using	use	VERB
cana-2865	154	2	eeg	eeg	PROPN
cana-2865	154	3	data	datum	NOUN
cana-2865	154	4	,	,	PUNCT
cana-2865	154	5	this	this	DET
cana-2865	154	6	work	work	NOUN
cana-2865	154	7	demonstrates	demonstrate	VERB
cana-2865	154	8	the	the	DET
cana-2865	154	9	potential	potential	NOUN
cana-2865	154	10	of	of	ADP
cana-2865	154	11	machine	machine	NOUN
cana-2865	154	12	learning	learning	NOUN
cana-2865	154	13	methods	method	NOUN
cana-2865	154	14	,	,	PUNCT
cana-2865	154	15	particularly	particularly	ADV
cana-2865	154	16	svm	svm	ADJ
cana-2865	154	17	and	and	CCONJ
cana-2865	154	18	knn	knn	PROPN
cana-2865	154	19	,	,	PUNCT
cana-2865	154	20	for	for	ADP
cana-2865	154	21	the	the	DET
cana-2865	154	22	classification	classification	NOUN
cana-2865	154	23	of	of	ADP
cana-2865	154	24	major	major	ADJ
cana-2865	154	25	depressive	depressive	ADJ
cana-2865	154	26	disorder	disorder	NOUN
cana-2865	154	27	.	.	PUNCT
cana-2865	155	1	5	5	X
cana-2865	155	2	.	.	X
cana-2865	155	3	discussion	discussion	NOUN
cana-2865	155	4	this	this	DET
cana-2865	155	5	study	study	NOUN
cana-2865	155	6	demonstrates	demonstrate	VERB
cana-2865	155	7	the	the	DET
cana-2865	155	8	effectiveness	effectiveness	NOUN
cana-2865	155	9	of	of	ADP
cana-2865	155	10	the	the	DET
cana-2865	155	11	firefly	firefly	NOUN
cana-2865	155	12	algorithm	algorithm	NOUN
cana-2865	155	13	in	in	ADP
cana-2865	155	14	enhancing	enhance	VERB
cana-2865	155	15	feature	feature	NOUN
cana-2865	155	16	selection	selection	NOUN
cana-2865	155	17	for	for	ADP
cana-2865	155	18	the	the	DET
cana-2865	155	19	diagnosis	diagnosis	NOUN
cana-2865	155	20	of	of	ADP
cana-2865	155	21	major	major	ADJ
cana-2865	155	22	depressive	depressive	ADJ
cana-2865	155	23	disorder	disorder	NOUN
cana-2865	155	24	across	across	ADP
cana-2865	155	25	multiple	multiple	ADJ
cana-2865	155	26	machine	machine	NOUN
cana-2865	155	27	learning	learning	NOUN
cana-2865	155	28	models	model	NOUN
cana-2865	155	29	.	.	PUNCT
cana-2865	156	1	the	the	DET
cana-2865	156	2	results	result	NOUN
cana-2865	156	3	indicate	indicate	VERB
cana-2865	156	4	that	that	SCONJ
cana-2865	156	5	the	the	DET
cana-2865	156	6	firefly	firefly	NOUN
cana-2865	156	7	algorithm	algorithm	NOUN
cana-2865	156	8	has	have	VERB
cana-2865	156	9	great	great	ADJ
cana-2865	156	10	potential	potential	NOUN
cana-2865	156	11	to	to	PART
cana-2865	156	12	improve	improve	VERB
cana-2865	156	13	the	the	DET
cana-2865	156	14	diagnostic	diagnostic	ADJ
cana-2865	156	15	capabilities	capability	NOUN
cana-2865	156	16	of	of	ADP
cana-2865	156	17	machine	machine	NOUN
cana-2865	156	18	learning	learn	VERB
cana-2865	156	19	techniques	technique	NOUN
cana-2865	156	20	in	in	ADP
cana-2865	156	21	the	the	DET
cana-2865	156	22	field	field	NOUN
cana-2865	156	23	of	of	ADP
cana-2865	156	24	psychiatry	psychiatry	NOUN
cana-2865	156	25	.	.	PUNCT
cana-2865	157	1	the	the	DET
cana-2865	157	2	fa	fa	NOUN
cana-2865	157	3	-	-	PUNCT
cana-2865	157	4	optimized	optimize	VERB
cana-2865	157	5	support	support	NOUN
cana-2865	157	6	vector	vector	NOUN
cana-2865	157	7	machine	machine	NOUN
cana-2865	157	8	model	model	NOUN
cana-2865	157	9	achieved	achieve	VERB
cana-2865	157	10	the	the	DET
cana-2865	157	11	greatest	great	ADJ
cana-2865	157	12	degree	degree	NOUN
cana-2865	157	13	of	of	ADP
cana-2865	157	14	accuracy	accuracy	NOUN
cana-2865	157	15	,	,	PUNCT
cana-2865	157	16	followed	follow	VERB
cana-2865	157	17	closely	closely	ADV
cana-2865	157	18	by	by	ADP
cana-2865	157	19	the	the	DET
cana-2865	157	20	k	k	PROPN
cana-2865	157	21	-	-	PUNCT
cana-2865	157	22	nearest	near	ADJ
cana-2865	157	23	neighbors	neighbor	NOUN
cana-2865	157	24	model	model	NOUN
cana-2865	157	25	.	.	PUNCT
cana-2865	158	1	to	to	PART
cana-2865	158	2	further	far	ADV
cana-2865	158	3	enhance	enhance	VERB
cana-2865	158	4	patient	patient	ADJ
cana-2865	158	5	outcomes	outcome	NOUN
cana-2865	158	6	and	and	CCONJ
cana-2865	158	7	diagnostic	diagnostic	ADJ
cana-2865	158	8	accuracy	accuracy	NOUN
cana-2865	158	9	,	,	PUNCT
cana-2865	158	10	future	future	ADJ
cana-2865	158	11	research	research	NOUN
cana-2865	158	12	should	should	AUX
cana-2865	158	13	focus	focus	VERB
cana-2865	158	14	on	on	ADP
cana-2865	158	15	integrating	integrate	VERB
cana-2865	158	16	the	the	DET
cana-2865	158	17	firefly	firefly	NOUN
cana-2865	158	18	algorithm	algorithm	NOUN
cana-2865	158	19	with	with	ADP
cana-2865	158	20	deep	deep	ADJ
cana-2865	158	21	learning	learning	NOUN
cana-2865	158	22	approaches	approach	NOUN
cana-2865	158	23	.	.	PUNCT
cana-2865	159	1	this	this	DET
cana-2865	159	2	integration	integration	NOUN
cana-2865	159	3	could	could	AUX
cana-2865	159	4	lead	lead	VERB
cana-2865	159	5	to	to	ADP
cana-2865	159	6	even	even	ADV
cana-2865	159	7	more	more	ADV
cana-2865	159	8	powerful	powerful	ADJ
cana-2865	159	9	and	and	CCONJ
cana-2865	159	10	robust	robust	ADJ
cana-2865	159	11	models	model	NOUN
cana-2865	159	12	for	for	ADP
cana-2865	159	13	the	the	DET
cana-2865	159	14	detection	detection	NOUN
cana-2865	159	15	and	and	CCONJ
cana-2865	159	16	management	management	NOUN
cana-2865	159	17	of	of	ADP
cana-2865	159	18	mdd	mdd	PROPN
cana-2865	159	19	.	.	PUNCT
cana-2865	159	20	additionally	additionally	ADV
cana-2865	159	21	,	,	PUNCT
cana-2865	159	22	exploring	explore	VERB
cana-2865	159	23	the	the	DET
cana-2865	159	24	application	application	NOUN
cana-2865	159	25	of	of	ADP
cana-2865	159	26	the	the	DET
cana-2865	159	27	firefly	firefly	NOUN
cana-2865	159	28	algorithm	algorithm	NOUN
cana-2865	159	29	-	-	PUNCT
cana-2865	159	30	based	base	VERB
cana-2865	159	31	feature	feature	NOUN
cana-2865	159	32	selection	selection	NOUN
cana-2865	159	33	method	method	NOUN
cana-2865	159	34	to	to	ADP
cana-2865	159	35	other	other	ADJ
cana-2865	159	36	psychiatric	psychiatric	ADJ
cana-2865	159	37	disorders	disorder	NOUN
cana-2865	159	38	could	could	AUX
cana-2865	159	39	yield	yield	VERB
cana-2865	159	40	valuable	valuable	ADJ
cana-2865	159	41	insights	insight	NOUN
cana-2865	159	42	and	and	CCONJ
cana-2865	159	43	advancements	advancement	NOUN
cana-2865	159	44	in	in	ADP
cana-2865	159	45	the	the	DET
cana-2865	159	46	field	field	NOUN
cana-2865	159	47	of	of	ADP
cana-2865	159	48	mental	mental	ADJ
cana-2865	159	49	health	health	NOUN
cana-2865	159	50	diagnostics	diagnostic	NOUN
cana-2865	159	51	and	and	CCONJ
cana-2865	159	52	treatment	treatment	NOUN
cana-2865	159	53	.	.	PUNCT
cana-2865	160	1	references	reference	NOUN
cana-2865	160	2	[	[	X
cana-2865	160	3	1	1	NUM
cana-2865	160	4	]	]	PUNCT
cana-2865	160	5	world	world	NOUN
cana-2865	160	6	health	health	NOUN
cana-2865	160	7	organization	organization	NOUN
cana-2865	160	8	.	.	PUNCT
cana-2865	161	1	(	(	PUNCT
cana-2865	161	2	2021	2021	NUM
cana-2865	161	3	)	)	PUNCT
cana-2865	161	4	.	.	PUNCT
cana-2865	162	1	"	"	PUNCT
cana-2865	162	2	depression	depression	NOUN
cana-2865	162	3	.	.	PUNCT
cana-2865	162	4	"	"	PUNCT
cana-2865	163	1	[	[	X
cana-2865	163	2	online	online	X
cana-2865	163	3	]	]	X
cana-2865	163	4	.	.	PUNCT
cana-2865	164	1	available	available	ADJ
cana-2865	164	2	:	:	PUNCT
cana-2865	164	3	https://www.who.int/news-room/factsheets/detail/depression	https://www.who.int/news-room/factsheets/detail/depression	X
cana-2865	164	4	.	.	PUNCT
cana-2865	165	1	[	[	X
cana-2865	165	2	2	2	NUM
cana-2865	165	3	]	]	X
cana-2865	165	4	kessler	kessler	PROPN
cana-2865	165	5	,	,	PUNCT
cana-2865	165	6	r.	r.	PROPN
cana-2865	165	7	c.	c.	PROPN
cana-2865	165	8	,	,	PUNCT
cana-2865	165	9	et	et	PROPN
cana-2865	165	10	al	al	PROPN
cana-2865	165	11	.	.	PUNCT
cana-2865	165	12	(	(	PUNCT
cana-2865	165	13	2003	2003	NUM
cana-2865	165	14	)	)	PUNCT
cana-2865	165	15	.	.	PUNCT
cana-2865	166	1	"	"	PUNCT
cana-2865	166	2	the	the	DET
cana-2865	166	3	epidemiology	epidemiology	NOUN
cana-2865	166	4	of	of	ADP
cana-2865	166	5	major	major	ADJ
cana-2865	166	6	depressive	depressive	ADJ
cana-2865	166	7	disorder	disorder	NOUN
cana-2865	166	8	:	:	PUNCT
cana-2865	166	9	results	result	NOUN
cana-2865	166	10	from	from	ADP
cana-2865	166	11	the	the	DET
cana-2865	166	12	national	national	ADJ
cana-2865	166	13	comorbidity	comorbidity	NOUN
cana-2865	166	14	survey	survey	NOUN
cana-2865	166	15	replication	replication	NOUN
cana-2865	166	16	(	(	PUNCT
cana-2865	166	17	ncs	ncs	NOUN
cana-2865	166	18	-	-	PUNCT
cana-2865	166	19	r	r	NOUN
cana-2865	166	20	)	)	PUNCT
cana-2865	166	21	.	.	PUNCT
cana-2865	166	22	"	"	PUNCT
cana-2865	167	1	jama	jama	PROPN
cana-2865	167	2	psychiatry	psychiatry	NOUN
cana-2865	167	3	,	,	PUNCT
cana-2865	167	4	289(23	289(23	NUM
cana-2865	167	5	)	)	PUNCT
cana-2865	167	6	,	,	PUNCT
cana-2865	167	7	3095	3095	NUM
cana-2865	167	8	-	-	SYM
cana-2865	167	9	3105	3105	NUM
cana-2865	167	10	.	.	PUNCT
cana-2865	168	1	https://doi.org/10.1001/jama.289.23.3095	https://doi.org/10.1001/jama.289.23.3095	PROPN
cana-2865	169	1	[	[	X
cana-2865	169	2	3	3	NUM
cana-2865	169	3	]	]	X
cana-2865	169	4	american	american	PROPN
cana-2865	169	5	psychiatric	psychiatric	PROPN
cana-2865	169	6	association	association	PROPN
cana-2865	169	7	.	.	PUNCT
cana-2865	170	1	(	(	PUNCT
cana-2865	170	2	2013	2013	NUM
cana-2865	170	3	)	)	PUNCT
cana-2865	170	4	.	.	PUNCT
cana-2865	171	1	"	"	PUNCT
cana-2865	171	2	diagnostic	diagnostic	ADJ
cana-2865	171	3	and	and	CCONJ
cana-2865	171	4	statistical	statistical	ADJ
cana-2865	171	5	manual	manual	NOUN
cana-2865	171	6	of	of	ADP
cana-2865	171	7	mental	mental	ADJ
cana-2865	171	8	disorders	disorder	NOUN
cana-2865	171	9	(	(	PUNCT
cana-2865	171	10	5th	5th	ADJ
cana-2865	171	11	ed	ed	NOUN
cana-2865	171	12	.	.	PUNCT
cana-2865	171	13	)	)	PUNCT
cana-2865	171	14	.	.	PUNCT
cana-2865	171	15	"	"	PUNCT
cana-2865	172	1	arlington	arlington	PROPN
cana-2865	172	2	,	,	PUNCT
cana-2865	172	3	va	va	PROPN
cana-2865	172	4	:	:	PUNCT
cana-2865	172	5	american	american	PROPN
cana-2865	172	6	psychiatric	psychiatric	PROPN
cana-2865	172	7	publishing	publishing	NOUN
cana-2865	172	8	.	.	PUNCT
cana-2865	173	1	[	[	X
cana-2865	173	2	4	4	NUM
cana-2865	173	3	]	]	X
cana-2865	173	4	yoon	yoon	PROPN
cana-2865	173	5	,	,	PUNCT
cana-2865	173	6	h.	h.	PROPN
cana-2865	173	7	,	,	PUNCT
cana-2865	173	8	et	et	PROPN
cana-2865	173	9	al	al	PROPN
cana-2865	173	10	.	.	PUNCT
cana-2865	173	11	(	(	PUNCT
cana-2865	173	12	2015	2015	NUM
cana-2865	173	13	)	)	PUNCT
cana-2865	173	14	.	.	PUNCT
cana-2865	174	1	"	"	PUNCT
cana-2865	174	2	classification	classification	NOUN
cana-2865	174	3	of	of	ADP
cana-2865	174	4	major	major	ADJ
cana-2865	174	5	depressive	depressive	ADJ
cana-2865	174	6	disorder	disorder	NOUN
cana-2865	174	7	based	base	VERB
cana-2865	174	8	on	on	ADP
cana-2865	174	9	brain	brain	NOUN
cana-2865	174	10	structural	structural	ADJ
cana-2865	174	11	mri	mri	NOUN
cana-2865	174	12	data	datum	NOUN
cana-2865	174	13	.	.	PUNCT
cana-2865	175	1	"	"	PUNCT
cana-2865	175	2	,	,	PUNCT
cana-2865	175	3	frontiers	frontier	NOUN
cana-2865	175	4	in	in	ADP
cana-2865	175	5	human	human	ADJ
cana-2865	175	6	neuroscience	neuroscience	NOUN
cana-2865	175	7	,	,	PUNCT
cana-2865	175	8	9	9	NUM
cana-2865	175	9	,	,	PUNCT
cana-2865	175	10	167	167	NUM
cana-2865	175	11	.	.	PUNCT
cana-2865	176	1	[	[	X
cana-2865	176	2	5	5	NUM
cana-2865	176	3	]	]	X
cana-2865	176	4	salvatore	salvatore	NOUN
cana-2865	176	5	,	,	PUNCT
cana-2865	176	6	p.	p.	PROPN
cana-2865	176	7	,	,	PUNCT
cana-2865	176	8	et	et	PROPN
cana-2865	176	9	al	al	PROPN
cana-2865	176	10	.	.	PUNCT
cana-2865	177	1	(	(	PUNCT
cana-2865	177	2	2014	2014	NUM
cana-2865	177	3	)	)	PUNCT
cana-2865	177	4	.	.	PUNCT
cana-2865	178	1	"	"	PUNCT
cana-2865	178	2	machine	machine	NOUN
cana-2865	178	3	learning	learn	VERB
cana-2865	178	4	for	for	ADP
cana-2865	178	5	classifying	classify	VERB
cana-2865	178	6	depression	depression	NOUN
cana-2865	178	7	.	.	PUNCT
cana-2865	179	1	"	"	PUNCT
cana-2865	179	2	,	,	PUNCT
cana-2865	179	3	ieee	ieee	NOUN
cana-2865	179	4	journal	journal	NOUN
cana-2865	179	5	of	of	ADP
cana-2865	179	6	biomedical	biomedical	ADJ
cana-2865	179	7	and	and	CCONJ
cana-2865	179	8	health	health	NOUN
cana-2865	179	9	informatics	informatic	NOUN
cana-2865	179	10	,	,	PUNCT
cana-2865	179	11	18(2	18(2	NUM
cana-2865	179	12	)	)	PUNCT
cana-2865	179	13	,	,	PUNCT
cana-2865	179	14	548	548	NUM
cana-2865	179	15	-	-	SYM
cana-2865	179	16	554	554	NUM
cana-2865	179	17	.	.	PUNCT
cana-2865	180	1	[	[	X
cana-2865	180	2	6	6	NUM
cana-2865	180	3	]	]	PUNCT
cana-2865	180	4	michalak	michalak	NOUN
cana-2865	180	5	,	,	PUNCT
cana-2865	180	6	j.	j.	PROPN
cana-2865	180	7	,	,	PUNCT
cana-2865	180	8	et	et	PROPN
cana-2865	180	9	al	al	PROPN
cana-2865	180	10	.	.	PUNCT
cana-2865	180	11	(	(	PUNCT
cana-2865	180	12	2012	2012	NUM
cana-2865	180	13	)	)	PUNCT
cana-2865	180	14	.	.	PUNCT
cana-2865	181	1	"	"	PUNCT
cana-2865	181	2	using	use	VERB
cana-2865	181	3	machine	machine	NOUN
cana-2865	181	4	learning	learn	VERB
cana-2865	181	5	algorithms	algorithm	NOUN
cana-2865	181	6	to	to	PART
cana-2865	181	7	predict	predict	VERB
cana-2865	181	8	major	major	ADJ
cana-2865	181	9	depressive	depressive	ADJ
cana-2865	181	10	disorder	disorder	NOUN
cana-2865	181	11	.	.	PUNCT
cana-2865	182	1	"	"	PUNCT
cana-2865	182	2	,	,	PUNCT
cana-2865	182	3	psychological	psychological	ADJ
cana-2865	182	4	medicine	medicine	NOUN
cana-2865	182	5	,	,	PUNCT
cana-2865	182	6	42(4	42(4	PROPN
cana-2865	182	7	)	)	PUNCT
cana-2865	182	8	,	,	PUNCT
cana-2865	182	9	735	735	NUM
cana-2865	182	10	-	-	SYM
cana-2865	182	11	747	747	NUM
cana-2865	182	12	.	.	PUNCT
cana-2865	182	13	http://doi.org/10.1177/07067437211037141	http://doi.org/10.1177/07067437211037141	PUNCT
cana-2865	183	1	[	[	X
cana-2865	183	2	7	7	NUM
cana-2865	183	3	]	]	X
cana-2865	183	4	guyon	guyon	NOUN
cana-2865	183	5	,	,	PUNCT
cana-2865	183	6	i.	i.	PROPN
cana-2865	183	7	,	,	PUNCT
cana-2865	183	8	&	&	CCONJ
cana-2865	183	9	elisseeff	elisseeff	PROPN
cana-2865	183	10	,	,	PUNCT
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cana-2865	183	12	(	(	PUNCT
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cana-2865	183	14	)	)	PUNCT
cana-2865	183	15	.	.	PUNCT
cana-2865	184	1	"	"	PUNCT
cana-2865	184	2	an	an	DET
cana-2865	184	3	introduction	introduction	NOUN
cana-2865	184	4	to	to	ADP
cana-2865	184	5	variable	variable	ADJ
cana-2865	184	6	and	and	CCONJ
cana-2865	184	7	feature	feature	NOUN
cana-2865	184	8	selection	selection	NOUN
cana-2865	184	9	.	.	PUNCT
cana-2865	185	1	"	"	PUNCT
cana-2865	185	2	,	,	PUNCT
cana-2865	185	3	journal	journal	NOUN
cana-2865	185	4	of	of	ADP
cana-2865	185	5	machine	machine	NOUN
cana-2865	185	6	learning	learn	VERB
cana-2865	185	7	research	research	NOUN
cana-2865	185	8	,	,	PUNCT
cana-2865	185	9	3	3	NUM
cana-2865	185	10	,	,	PUNCT
cana-2865	185	11	1157	1157	NUM
cana-2865	185	12	-	-	SYM
cana-2865	185	13	1182	1182	NUM
cana-2865	185	14	.	.	PUNCT
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cana-2865	187	1	[	[	X
cana-2865	187	2	8	8	NUM
cana-2865	187	3	]	]	X
cana-2865	187	4	zhang	zhang	PROPN
cana-2865	187	5	,	,	PUNCT
cana-2865	187	6	y.	y.	PROPN
cana-2865	187	7	,	,	PUNCT
cana-2865	187	8	&	&	CCONJ
cana-2865	187	9	wu	wu	PROPN
cana-2865	187	10	,	,	PUNCT
cana-2865	187	11	x.	x.	PROPN
cana-2865	187	12	(	(	PUNCT
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cana-2865	188	1	"	"	PUNCT
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cana-2865	188	6	-	-	PUNCT
cana-2865	188	7	dimensional	dimensional	ADJ
cana-2865	188	8	data	datum	NOUN
cana-2865	188	9	:	:	PUNCT
cana-2865	188	10	a	a	DET
cana-2865	188	11	fast	fast	ADJ
cana-2865	188	12	correlation	correlation	NOUN
cana-2865	188	13	-	-	PUNCT
cana-2865	188	14	based	base	VERB
cana-2865	188	15	filter	filter	NOUN
cana-2865	188	16	solution	solution	NOUN
cana-2865	188	17	.	.	PUNCT
cana-2865	189	1	"	"	PUNCT
cana-2865	189	2	,	,	PUNCT
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cana-2865	189	5	on	on	ADP
cana-2865	189	6	knowledge	knowledge	NOUN
cana-2865	189	7	and	and	CCONJ
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cana-2865	189	9	engineering	engineering	NOUN
cana-2865	189	10	,	,	PUNCT
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cana-2865	189	12	)	)	PUNCT
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cana-2865	189	15	-	-	SYM
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cana-2865	189	17	.	.	PUNCT
cana-2865	190	1	https://doi.org/10	https://doi.org/10	PROPN
cana-2865	190	2	.	.	PUNCT
cana-2865	191	1	221345776	221345776	NUM
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cana-2865	191	3	https://www.who.int/news-room/fact-sheets/detail/depression	https://www.who.int/news-room/fact-sheets/detail/depression	NOUN
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cana-2865	191	5	https://doi.org/10.1177/07067437211037141	https://doi.org/10.1177/07067437211037141	X
cana-2865	191	6	https://doi.org/10.5555/944919.944968	https://doi.org/10.5555/944919.944968	NOUN
cana-2865	192	1	https://doi.org/10.%20221345776	https://doi.org/10.%20221345776	PROPN
cana-2865	192	2	communications	communication	NOUN
cana-2865	192	3	on	on	ADP
cana-2865	192	4	applied	apply	VERB
cana-2865	192	5	nonlinear	nonlinear	ADJ
cana-2865	192	6	analysis	analysis	NOUN
cana-2865	192	7	issn	issn	NOUN
cana-2865	192	8	:	:	PUNCT
cana-2865	192	9	1074	1074	NUM
cana-2865	192	10	-	-	PUNCT
cana-2865	192	11	133x	133x	NUM
cana-2865	192	12	vol	vol	NOUN
cana-2865	192	13	32	32	NUM
cana-2865	192	14	no	no	NOUN
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cana-2865	193	2	(	(	PUNCT
cana-2865	193	3	2025	2025	NUM
cana-2865	193	4	)	)	PUNCT
cana-2865	193	5	478	478	NUM
cana-2865	193	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2865	194	1	[	[	X
cana-2865	194	2	9	9	NUM
cana-2865	194	3	]	]	X
cana-2865	194	4	nickolas	nickola	NOUN
cana-2865	194	5	.	.	PUNCT
cana-2865	195	1	p	p	X
cana-2865	195	2	,	,	PUNCT
cana-2865	195	3	et	et	PROPN
cana-2865	195	4	al	al	PROPN
cana-2865	195	5	.	.	PROPN
cana-2865	195	6	(	(	PUNCT
cana-2865	195	7	2022	2022	NUM
cana-2865	195	8	)	)	PUNCT
cana-2865	195	9	.	.	PUNCT
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cana-2865	196	2	a	a	DET
cana-2865	196	3	review	review	NOUN
cana-2865	196	4	of	of	ADP
cana-2865	196	5	feature	feature	NOUN
cana-2865	196	6	selection	selection	NOUN
cana-2865	196	7	methods	method	NOUN
cana-2865	196	8	in	in	ADP
cana-2865	196	9	machine	machine	NOUN
cana-2865	196	10	learning	learning	NOUN
cana-2865	196	11	.	.	PUNCT
cana-2865	197	1	"	"	PUNCT
cana-2865	197	2	,	,	PUNCT
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cana-2865	197	4	journal	journal	NOUN
cana-2865	197	5	of	of	ADP
cana-2865	197	6	advanced	advanced	ADJ
cana-2865	197	7	research	research	NOUN
cana-2865	197	8	in	in	ADP
cana-2865	197	9	computer	computer	NOUN
cana-2865	197	10	science	science	NOUN
cana-2865	197	11	and	and	CCONJ
cana-2865	197	12	software	software	NOUN
cana-2865	197	13	engineering	engineering	NOUN
cana-2865	197	14	,	,	PUNCT
cana-2865	197	15	6(3	6(3	NUM
cana-2865	197	16	)	)	PUNCT
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cana-2865	197	19	-	-	SYM
cana-2865	197	20	178	178	NUM
cana-2865	197	21	.	.	PUNCT
cana-2865	198	1	http://doi.org/10.3389/fbinf.2022.927312	http://doi.org/10.3389/fbinf.2022.927312	PROPN
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cana-2865	198	3	10	10	NUM
cana-2865	198	4	]	]	X
cana-2865	198	5	yang	yang	PROPN
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cana-2865	198	7	x.-s	x.-s	PROPN
cana-2865	198	8	.	.	PUNCT
cana-2865	199	1	(	(	PUNCT
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cana-2865	199	3	)	)	PUNCT
cana-2865	199	4	.	.	PUNCT
cana-2865	200	1	"	"	PUNCT
cana-2865	200	2	firefly	firefly	NOUN
cana-2865	200	3	algorithms	algorithm	NOUN
cana-2865	200	4	for	for	ADP
cana-2865	200	5	multimodal	multimodal	NOUN
cana-2865	200	6	optimization	optimization	NOUN
cana-2865	200	7	.	.	PUNCT
cana-2865	201	1	"	"	PUNCT
cana-2865	201	2	,	,	PUNCT
cana-2865	201	3	international	international	ADJ
cana-2865	201	4	symposium	symposium	NOUN
cana-2865	201	5	on	on	ADP
cana-2865	201	6	stochastic	stochastic	ADJ
cana-2865	201	7	algorithms	algorithm	NOUN
cana-2865	201	8	,	,	PUNCT
cana-2865	201	9	169	169	NUM
cana-2865	201	10	-	-	SYM
cana-2865	201	11	178	178	NUM
cana-2865	201	12	.	.	PUNCT
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cana-2865	202	2	[	[	X
cana-2865	202	3	11	11	NUM
cana-2865	202	4	]	]	PUNCT
cana-2865	202	5	alzahrani	alzahrani	NOUN
cana-2865	202	6	,	,	PUNCT
cana-2865	202	7	a.	a.	NOUN
cana-2865	202	8	i.	i.	PROPN
cana-2865	202	9	,	,	PUNCT
cana-2865	202	10	&	&	CCONJ
cana-2865	202	11	althubaiti	althubaiti	PROPN
cana-2865	202	12	,	,	PUNCT
cana-2865	202	13	s.	s.	PROPN
cana-2865	202	14	(	(	PUNCT
cana-2865	202	15	2020	2020	NUM
cana-2865	202	16	)	)	PUNCT
cana-2865	202	17	.	.	PUNCT
cana-2865	203	1	"	"	PUNCT
cana-2865	203	2	an	an	DET
cana-2865	203	3	improved	improved	ADJ
cana-2865	203	4	knn	knn	NOUN
cana-2865	203	5	algorithm	algorithm	NOUN
cana-2865	203	6	for	for	ADP
cana-2865	203	7	heart	heart	NOUN
cana-2865	203	8	disease	disease	NOUN
cana-2865	203	9	prediction	prediction	NOUN
cana-2865	203	10	.	.	PUNCT
cana-2865	204	1	"	"	PUNCT
cana-2865	204	2	,	,	PUNCT
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cana-2865	204	5	,	,	PUNCT
cana-2865	204	6	8	8	NUM
cana-2865	204	7	,	,	PUNCT
cana-2865	204	8	123596-123607.http://doi.org/	123596-123607.http://doi.org/	NUM
cana-2865	204	9	10.1109	10.1109	NUM
cana-2865	204	10	/	/	SYM
cana-2865	204	11	iceei52609.2021.9611110	iceei52609.2021.9611110	PROPN
cana-2865	205	1	[	[	X
cana-2865	205	2	12	12	NUM
cana-2865	205	3	]	]	X
cana-2865	205	4	chen	chen	PROPN
cana-2865	205	5	,	,	PUNCT
cana-2865	205	6	h.	h.	PROPN
cana-2865	205	7	,	,	PUNCT
cana-2865	205	8	et	et	PROPN
cana-2865	205	9	al	al	PROPN
cana-2865	205	10	.	.	PROPN
cana-2865	206	1	(	(	PUNCT
cana-2865	206	2	2020	2020	NUM
cana-2865	206	3	)	)	PUNCT
cana-2865	206	4	.	.	PUNCT
cana-2865	207	1	"	"	PUNCT
cana-2865	207	2	comparison	comparison	NOUN
cana-2865	207	3	of	of	ADP
cana-2865	207	4	deep	deep	ADJ
cana-2865	207	5	learning	learning	NOUN
cana-2865	207	6	and	and	CCONJ
cana-2865	207	7	traditional	traditional	ADJ
cana-2865	207	8	machine	machine	NOUN
cana-2865	207	9	learning	learning	NOUN
cana-2865	207	10	methods	method	NOUN
cana-2865	207	11	for	for	ADP
cana-2865	207	12	the	the	DET
cana-2865	207	13	diagnosis	diagnosis	NOUN
cana-2865	207	14	of	of	ADP
cana-2865	207	15	mdd	mdd	PROPN
cana-2865	207	16	.	.	PUNCT
cana-2865	207	17	"	"	PUNCT
cana-2865	207	18	,	,	PUNCT
cana-2865	207	19	ieee	ieee	NOUN
cana-2865	207	20	transactions	transaction	NOUN
cana-2865	207	21	on	on	ADP
cana-2865	207	22	neural	neural	ADJ
cana-2865	207	23	networks	network	NOUN
cana-2865	207	24	and	and	CCONJ
cana-2865	207	25	learning	learning	NOUN
cana-2865	207	26	systems	system	NOUN
cana-2865	207	27	,	,	PUNCT
cana-2865	207	28	31(3	31(3	NUM
cana-2865	207	29	)	)	PUNCT
cana-2865	207	30	,	,	PUNCT
cana-2865	207	31	850	850	NUM
cana-2865	207	32	-	-	SYM
cana-2865	207	33	861	861	NUM
cana-2865	207	34	.	.	PUNCT
cana-2865	208	1	[	[	X
cana-2865	208	2	13	13	NUM
cana-2865	208	3	]	]	SYM
cana-2865	208	4	haykin	haykin	PROPN
cana-2865	208	5	,	,	PUNCT
cana-2865	208	6	s.	s.	PROPN
cana-2865	208	7	(	(	PUNCT
cana-2865	208	8	2009	2009	NUM
cana-2865	208	9	)	)	PUNCT
cana-2865	208	10	.	.	PUNCT
cana-2865	209	1	"	"	PUNCT
cana-2865	209	2	neural	neural	ADJ
cana-2865	209	3	networks	network	NOUN
cana-2865	209	4	and	and	CCONJ
cana-2865	209	5	learning	learn	VERB
cana-2865	209	6	machines	machine	NOUN
cana-2865	209	7	.	.	PUNCT
cana-2865	210	1	"	"	PUNCT
cana-2865	210	2	,	,	PUNCT
cana-2865	210	3	pearson	pearson	PROPN
cana-2865	210	4	education	education	NOUN
cana-2865	210	5	.	.	PUNCT
cana-2865	211	1	[	[	X
cana-2865	211	2	14	14	NUM
cana-2865	211	3	]	]	X
cana-2865	211	4	tan	tan	PROPN
cana-2865	211	5	,	,	PUNCT
cana-2865	211	6	p.-n	p.-n	PROPN
cana-2865	211	7	.	.	PROPN
cana-2865	211	8	,	,	PUNCT
cana-2865	211	9	steinbach	steinbach	PROPN
cana-2865	211	10	,	,	PUNCT
cana-2865	211	11	m.	m.	NOUN
cana-2865	211	12	,	,	PUNCT
cana-2865	211	13	&	&	CCONJ
cana-2865	211	14	karpatne	karpatne	PROPN
cana-2865	211	15	,	,	PUNCT
cana-2865	211	16	a.	a.	NOUN
cana-2865	211	17	(	(	PUNCT
cana-2865	211	18	2018	2018	NUM
cana-2865	211	19	)	)	PUNCT
cana-2865	211	20	.	.	PUNCT
cana-2865	212	1	"	"	PUNCT
cana-2865	212	2	introduction	introduction	NOUN
cana-2865	212	3	to	to	ADP
cana-2865	212	4	data	datum	NOUN
cana-2865	212	5	mining	mining	NOUN
cana-2865	212	6	.	.	PUNCT
cana-2865	213	1	"	"	PUNCT
cana-2865	213	2	,	,	PUNCT
cana-2865	213	3	pearson	pearson	PROPN
cana-2865	213	4	.	.	PUNCT
cana-2865	214	1	[	[	X
cana-2865	214	2	15	15	NUM
cana-2865	214	3	]	]	X
cana-2865	214	4	langley	langley	PROPN
cana-2865	214	5	,	,	PUNCT
cana-2865	214	6	p.	p.	PROPN
cana-2865	214	7	,	,	PUNCT
cana-2865	214	8	&	&	CCONJ
cana-2865	214	9	sage	sage	NOUN
cana-2865	214	10	,	,	PUNCT
cana-2865	214	11	s.	s.	PROPN
cana-2865	214	12	(	(	PUNCT
cana-2865	214	13	2019	2019	NUM
cana-2865	214	14	)	)	PUNCT
cana-2865	214	15	.	.	PUNCT
cana-2865	215	1	"	"	PUNCT
cana-2865	215	2	naïve	naïve	ADJ
cana-2865	215	3	bayes	bayes	NOUN
cana-2865	215	4	classifiers	classifier	NOUN
cana-2865	215	5	.	.	PUNCT
cana-2865	216	1	"	"	PUNCT
cana-2865	216	2	,	,	PUNCT
cana-2865	216	3	encyclopedia	encyclopedia	NOUN
cana-2865	216	4	of	of	ADP
cana-2865	216	5	machine	machine	NOUN
cana-2865	216	6	learning	learning	NOUN
cana-2865	216	7	and	and	CCONJ
cana-2865	216	8	data	datum	NOUN
cana-2865	216	9	mining	mining	NOUN
cana-2865	216	10	,	,	PUNCT
cana-2865	216	11	707711	707711	NUM
cana-2865	216	12	.	.	PUNCT
cana-2865	217	1	[	[	X
cana-2865	217	2	16	16	NUM
cana-2865	217	3	]	]	SYM
cana-2865	217	4	mclachlan	mclachlan	PROPN
cana-2865	217	5	,	,	PUNCT
cana-2865	217	6	g.	g.	PROPN
cana-2865	217	7	j.	j.	PROPN
cana-2865	217	8	,	,	PUNCT
cana-2865	217	9	&	&	CCONJ
cana-2865	217	10	peel	peel	PROPN
cana-2865	217	11	,	,	PUNCT
cana-2865	217	12	d.	d.	PROPN
cana-2865	217	13	(	(	PUNCT
cana-2865	217	14	2000	2000	NUM
cana-2865	217	15	)	)	PUNCT
cana-2865	217	16	.	.	PUNCT
cana-2865	218	1	"	"	PUNCT
cana-2865	218	2	finite	finite	VERB
cana-2865	218	3	mixture	mixture	NOUN
cana-2865	218	4	models	model	NOUN
cana-2865	218	5	.	.	PUNCT
cana-2865	218	6	"	"	PUNCT
cana-2865	219	1	wiley	wiley	PROPN
cana-2865	219	2	series	series	PROPN
cana-2865	219	3	in	in	ADP
cana-2865	219	4	probability	probability	NOUN
cana-2865	219	5	and	and	CCONJ
cana-2865	219	6	statistics	statistic	NOUN
cana-2865	219	7	”	"	PUNCT
cana-2865	219	8	.	.	PUNCT
cana-2865	220	1	https://doi.org/10.1146/annurev-statistics-031017-100325	https://doi.org/10.1146/annurev-statistics-031017-100325	PROPN
cana-2865	221	1	[	[	X
cana-2865	221	2	17	17	NUM
cana-2865	221	3	]	]	PUNCT
cana-2865	221	4	cortes	corte	NOUN
cana-2865	221	5	,	,	PUNCT
cana-2865	221	6	c.	c.	NOUN
cana-2865	221	7	,	,	PUNCT
cana-2865	221	8	&	&	CCONJ
cana-2865	221	9	vapnik	vapnik	X
cana-2865	221	10	,	,	PUNCT
cana-2865	221	11	v.	v.	PROPN
cana-2865	221	12	(	(	PUNCT
cana-2865	221	13	1995	1995	NUM
cana-2865	221	14	)	)	PUNCT
cana-2865	221	15	.	.	PUNCT
cana-2865	222	1	"	"	PUNCT
cana-2865	222	2	support	support	NOUN
cana-2865	222	3	-	-	PUNCT
cana-2865	222	4	vector	vector	NOUN
cana-2865	222	5	networks	network	NOUN
cana-2865	222	6	.	.	PUNCT
cana-2865	222	7	"	"	PUNCT
cana-2865	222	8	machine	machine	NOUN
cana-2865	222	9	learning	learning	NOUN
cana-2865	222	10	,	,	PUNCT
cana-2865	222	11	20(3	20(3	NOUN
cana-2865	222	12	)	)	PUNCT
cana-2865	222	13	,	,	PUNCT
cana-2865	222	14	273	273	NUM
cana-2865	222	15	-	-	SYM
cana-2865	222	16	297	297	NUM
cana-2865	222	17	.	.	PUNCT
cana-2865	223	1	https://doi.org/10.1007/bf00994018	https://doi.org/10.1007/bf00994018	VERB
cana-2865	224	1	[	[	X
cana-2865	224	2	18	18	NUM
cana-2865	224	3	]	]	X
cana-2865	224	4	iglewicz	iglewicz	PROPN
cana-2865	224	5	,	,	PUNCT
cana-2865	224	6	b.	b.	PROPN
cana-2865	224	7	,	,	PUNCT
cana-2865	224	8	&	&	CCONJ
cana-2865	224	9	hoaglin	hoaglin	PROPN
cana-2865	224	10	,	,	PUNCT
cana-2865	224	11	d.	d.	PROPN
cana-2865	224	12	c.	c.	PROPN
cana-2865	224	13	(	(	PUNCT
cana-2865	224	14	1993	1993	NUM
cana-2865	224	15	)	)	PUNCT
cana-2865	224	16	.	.	PUNCT
cana-2865	225	1	"	"	PUNCT
cana-2865	225	2	how	how	SCONJ
cana-2865	225	3	to	to	PART
cana-2865	225	4	detect	detect	VERB
cana-2865	225	5	and	and	CCONJ
cana-2865	225	6	handle	handle	VERB
cana-2865	225	7	outliers	outlier	NOUN
cana-2865	225	8	.	.	PUNCT
cana-2865	226	1	"	"	PUNCT
cana-2865	226	2	,	,	PUNCT
cana-2865	226	3	sage	sage	NOUN
cana-2865	226	4	publications	publication	NOUN
cana-2865	226	5	.	.	PUNCT
cana-2865	227	1	[	[	X
cana-2865	227	2	19	19	NUM
cana-2865	227	3	]	]	SYM
cana-2865	227	4	li	li	PROPN
cana-2865	227	5	,	,	PUNCT
cana-2865	227	6	w.	w.	PROPN
cana-2865	227	7	,	,	PUNCT
cana-2865	227	8	et	et	PROPN
cana-2865	227	9	al	al	PROPN
cana-2865	227	10	.	.	PROPN
cana-2865	227	11	(	(	PUNCT
cana-2865	227	12	2021	2021	NUM
cana-2865	227	13	)	)	PUNCT
cana-2865	227	14	.	.	PUNCT
cana-2865	228	1	"	"	PUNCT
cana-2865	228	2	metaheuristic	metaheuristic	ADJ
cana-2865	228	3	algorithms	algorithm	NOUN
cana-2865	228	4	for	for	ADP
cana-2865	228	5	feature	feature	NOUN
cana-2865	228	6	selection	selection	NOUN
cana-2865	228	7	:	:	PUNCT
cana-2865	228	8	a	a	DET
cana-2865	228	9	review	review	NOUN
cana-2865	228	10	.	.	PUNCT
cana-2865	228	11	"	"	PUNCT
cana-2865	229	1	artificial	artificial	ADJ
cana-2865	229	2	intelligence	intelligence	NOUN
cana-2865	229	3	review	review	NOUN
cana-2865	229	4	,	,	PUNCT
cana-2865	229	5	54(6	54(6	NUM
cana-2865	229	6	)	)	PUNCT
cana-2865	229	7	,	,	PUNCT
cana-2865	229	8	4053	4053	NUM
cana-2865	229	9	-	-	SYM
cana-2865	229	10	4086	4086	NUM
cana-2865	229	11	.	.	PUNCT
cana-2865	230	1	http://doi.org/	http://doi.org/	PROPN
cana-2865	230	2	10.1109	10.1109	NUM
cana-2865	230	3	/	/	SYM
cana-2865	230	4	access.2021.3056407	access.2021.3056407	NOUN
cana-2865	230	5	.	.	PUNCT
cana-2865	231	1	[	[	X
cana-2865	231	2	20	20	NUM
cana-2865	231	3	]	]	X
cana-2865	231	4	chen	chen	PROPN
cana-2865	231	5	,	,	PUNCT
cana-2865	231	6	y.	y.	PROPN
cana-2865	231	7	,	,	PUNCT
cana-2865	231	8	&	&	CCONJ
cana-2865	231	9	wang	wang	PROPN
cana-2865	231	10	,	,	PUNCT
cana-2865	231	11	w.	w.	PROPN
cana-2865	231	12	(	(	PUNCT
cana-2865	231	13	2015	2015	NUM
cana-2865	231	14	)	)	PUNCT
cana-2865	231	15	.	.	PUNCT
cana-2865	232	1	"	"	PUNCT
cana-2865	232	2	an	an	DET
cana-2865	232	3	improved	improve	VERB
cana-2865	232	4	genetic	genetic	ADJ
cana-2865	232	5	algorithm	algorithm	NOUN
cana-2865	232	6	for	for	ADP
cana-2865	232	7	feature	feature	NOUN
cana-2865	232	8	selection	selection	NOUN
cana-2865	232	9	.	.	PUNCT
cana-2865	232	10	"	"	PUNCT
cana-2865	233	1	journal	journal	NOUN
cana-2865	233	2	of	of	ADP
cana-2865	233	3	computational	computational	ADJ
cana-2865	233	4	science	science	NOUN
cana-2865	233	5	,	,	PUNCT
cana-2865	233	6	9	9	NUM
cana-2865	233	7	,	,	PUNCT
cana-2865	233	8	202	202	NUM
cana-2865	233	9	-	-	SYM
cana-2865	233	10	210	210	NUM
cana-2865	233	11	.	.	PUNCT
cana-2865	234	1	https://doi.org/10.1145/3469678.3469682	https://doi.org/10.1145/3469678.3469682	NOUN
cana-2865	235	1	[	[	X
cana-2865	235	2	21	21	NUM
cana-2865	235	3	]	]	X
cana-2865	235	4	wang	wang	PROPN
cana-2865	235	5	,	,	PUNCT
cana-2865	235	6	w.	w.	PROPN
cana-2865	235	7	,	,	PUNCT
cana-2865	235	8	et	et	PROPN
cana-2865	235	9	al	al	PROPN
cana-2865	235	10	.	.	PUNCT
cana-2865	235	11	(	(	PUNCT
cana-2865	235	12	2018	2018	NUM
cana-2865	235	13	)	)	PUNCT
cana-2865	235	14	.	.	PUNCT
cana-2865	236	1	"	"	PUNCT
cana-2865	236	2	particle	particle	NOUN
cana-2865	236	3	swarm	swarm	NOUN
cana-2865	236	4	optimization	optimization	NOUN
cana-2865	236	5	for	for	ADP
cana-2865	236	6	feature	feature	NOUN
cana-2865	236	7	selection	selection	NOUN
cana-2865	236	8	in	in	ADP
cana-2865	236	9	a	a	DET
cana-2865	236	10	medical	medical	ADJ
cana-2865	236	11	dataset	dataset	NOUN
cana-2865	236	12	.	.	PUNCT
cana-2865	237	1	"	"	PUNCT
cana-2865	237	2	,	,	PUNCT
cana-2865	237	3	journal	journal	NOUN
cana-2865	237	4	of	of	ADP
cana-2865	237	5	healthcare	healthcare	PROPN
cana-2865	237	6	engineering	engineering	NOUN
cana-2865	237	7	,	,	PUNCT
cana-2865	237	8	2018	2018	NUM
cana-2865	237	9	,	,	PUNCT
cana-2865	237	10	1	1	NUM
cana-2865	237	11	-	-	SYM
cana-2865	237	12	10	10	NUM
cana-2865	237	13	.	.	PUNCT
cana-2865	238	1	http://doi.org/	http://doi.org/	PROPN
cana-2865	238	2	10.1109	10.1109	NUM
cana-2865	238	3	/	/	SYM
cana-2865	238	4	access.2018.2843443	access.2018.2843443	NOUN
cana-2865	238	5	[	[	X
cana-2865	238	6	22	22	NUM
cana-2865	238	7	]	]	X
cana-2865	238	8	yang	yang	PROPN
cana-2865	238	9	,	,	PUNCT
cana-2865	238	10	x.-s	x.-s	PROPN
cana-2865	238	11	.	.	PROPN
cana-2865	238	12	,	,	PUNCT
cana-2865	238	13	&	&	CCONJ
cana-2865	238	14	deb	deb	PROPN
cana-2865	238	15	,	,	PUNCT
cana-2865	238	16	s.	s.	PROPN
cana-2865	238	17	(	(	PUNCT
cana-2865	238	18	2009	2009	NUM
cana-2865	238	19	)	)	PUNCT
cana-2865	238	20	.	.	PUNCT
cana-2865	239	1	"	"	PUNCT
cana-2865	239	2	cuckoo	cuckoo	NOUN
cana-2865	239	3	search	search	NOUN
cana-2865	239	4	via	via	ADP
cana-2865	239	5	lévy	lévy	ADJ
cana-2865	239	6	flights	flight	NOUN
cana-2865	239	7	.	.	PUNCT
cana-2865	240	1	"	"	PUNCT
cana-2865	240	2	,	,	PUNCT
cana-2865	240	3	proceedings	proceeding	NOUN
cana-2865	240	4	of	of	ADP
cana-2865	240	5	world	world	PROPN
cana-2865	240	6	congress	congress	PROPN
cana-2865	240	7	on	on	ADP
cana-2865	240	8	nature	nature	PROPN
cana-2865	240	9	&	&	CCONJ
cana-2865	240	10	biologically	biologically	ADV
cana-2865	240	11	inspired	inspire	VERB
cana-2865	240	12	computing	computing	NOUN
cana-2865	240	13	(	(	PUNCT
cana-2865	240	14	nabic	nabic	ADJ
cana-2865	240	15	)	)	PUNCT
cana-2865	240	16	,	,	PUNCT
cana-2865	240	17	210	210	NUM
cana-2865	240	18	-	-	SYM
cana-2865	240	19	214	214	NUM
cana-2865	240	20	.	.	PUNCT
cana-2865	241	1	https://doi.org/10.1109/nabic.2009.5393690	https://doi.org/10.1109/nabic.2009.5393690	PROPN
cana-2865	242	1	[	[	X
cana-2865	242	2	23	23	NUM
cana-2865	242	3	]	]	PUNCT
cana-2865	242	4	mirjalili	mirjalili	NOUN
cana-2865	242	5	,	,	PUNCT
cana-2865	242	6	s.	s.	PROPN
cana-2865	242	7	(	(	PUNCT
cana-2865	242	8	2016	2016	NUM
cana-2865	242	9	)	)	PUNCT
cana-2865	242	10	.	.	PUNCT
cana-2865	243	1	"	"	PUNCT
cana-2865	243	2	sca	sca	NOUN
cana-2865	243	3	:	:	PUNCT
cana-2865	243	4	a	a	DET
cana-2865	243	5	sine	sine	ADJ
cana-2865	243	6	cosine	cosine	NOUN
cana-2865	243	7	algorithm	algorithm	NOUN
cana-2865	243	8	for	for	ADP
cana-2865	243	9	solving	solve	VERB
cana-2865	243	10	optimization	optimization	NOUN
cana-2865	243	11	problems	problem	NOUN
cana-2865	243	12	.	.	PUNCT
cana-2865	244	1	"	"	PUNCT
cana-2865	244	2	,	,	PUNCT
cana-2865	244	3	knowledge	knowledge	NOUN
cana-2865	244	4	-	-	PUNCT
cana-2865	244	5	based	base	VERB
cana-2865	244	6	systems	system	NOUN
cana-2865	244	7	,	,	PUNCT
cana-2865	244	8	96	96	NUM
cana-2865	244	9	,	,	PUNCT
cana-2865	244	10	120	120	NUM
cana-2865	244	11	-	-	SYM
cana-2865	244	12	133	133	NUM
cana-2865	244	13	.	.	PUNCT
cana-2865	245	1	https://doi.org/10.1016/j.knosys.2015.12.022	https://doi.org/10.1016/j.knosys.2015.12.022	NOUN
cana-2865	245	2	[	[	X
cana-2865	245	3	24	24	NUM
cana-2865	245	4	]	]	SYM
cana-2865	245	5	shabani	shabani	PROPN
cana-2865	245	6	,	,	PUNCT
cana-2865	245	7	a.	a.	PROPN
cana-2865	245	8	,	,	PUNCT
cana-2865	245	9	et	et	PROPN
cana-2865	245	10	al	al	PROPN
cana-2865	245	11	.	.	PROPN
cana-2865	246	1	(	(	PUNCT
cana-2865	246	2	2019	2019	NUM
cana-2865	246	3	)	)	PUNCT
cana-2865	246	4	.	.	PUNCT
cana-2865	247	1	"	"	PUNCT
cana-2865	247	2	feature	feature	NOUN
cana-2865	247	3	selection	selection	NOUN
cana-2865	247	4	using	use	VERB
cana-2865	247	5	firefly	firefly	NOUN
cana-2865	247	6	algorithm	algorithm	NOUN
cana-2865	247	7	for	for	ADP
cana-2865	247	8	high	high	ADJ
cana-2865	247	9	-	-	PUNCT
cana-2865	247	10	dimensional	dimensional	ADJ
cana-2865	247	11	data	datum	NOUN
cana-2865	247	12	.	.	PUNCT
cana-2865	248	1	"	"	PUNCT
cana-2865	248	2	,	,	PUNCT
cana-2865	248	3	artificial	artificial	ADJ
cana-2865	248	4	intelligence	intelligence	NOUN
cana-2865	248	5	review	review	NOUN
cana-2865	248	6	,	,	PUNCT
cana-2865	248	7	52(2	52(2	NUM
cana-2865	248	8	)	)	PUNCT
cana-2865	248	9	,	,	PUNCT
cana-2865	248	10	611	611	NUM
cana-2865	248	11	-	-	SYM
cana-2865	248	12	628	628	NUM
cana-2865	248	13	.	.	PUNCT
cana-2865	249	1	[	[	X
cana-2865	249	2	25	25	NUM
cana-2865	249	3	]	]	PUNCT
cana-2865	249	4	mumtaz	mumtaz	PROPN
cana-2865	249	5	w	w	PROPN
cana-2865	249	6	,	,	PUNCT
cana-2865	249	7	xia	xia	PROPN
cana-2865	249	8	l	l	PROPN
cana-2865	249	9	,	,	PUNCT
cana-2865	249	10	mohd	mohd	PROPN
cana-2865	249	11	yasin	yasin	PROPN
cana-2865	249	12	ma	ma	PROPN
cana-2865	249	13	,	,	PUNCT
cana-2865	249	14	azhar	azhar	PROPN
cana-2865	249	15	ali	ali	PROPN
cana-2865	249	16	ss	ss	PROPN
cana-2865	249	17	,	,	PUNCT
cana-2865	249	18	malik	malik	PROPN
cana-2865	249	19	as	as	ADP
cana-2865	249	20	(	(	PUNCT
cana-2865	249	21	2017	2017	NUM
cana-2865	249	22	)	)	PUNCT
cana-2865	249	23	,	,	PUNCT
cana-2865	249	24	“	"	PUNCT
cana-2865	249	25	a	a	DET
cana-2865	249	26	wavelet	wavelet	NOUN
cana-2865	249	27	-	-	PUNCT
cana-2865	249	28	based	base	VERB
cana-2865	249	29	technique	technique	NOUN
cana-2865	249	30	to	to	PART
cana-2865	249	31	predict	predict	VERB
cana-2865	249	32	treatment	treatment	NOUN
cana-2865	249	33	outcome	outcome	NOUN
cana-2865	249	34	for	for	ADP
cana-2865	249	35	major	major	ADJ
cana-2865	249	36	depressive	depressive	ADJ
cana-2865	249	37	disorder	disorder	NOUN
cana-2865	249	38	.	.	PUNCT
cana-2865	249	39	”	"	PUNCT
cana-2865	250	1	,	,	PUNCT
cana-2865	250	2	plos	plo	VERB
cana-2865	250	3	one	one	NUM
cana-2865	250	4	vol	vol	NOUN
cana-2865	250	5	12(2	12(2	NUM
cana-2865	250	6	)	)	PUNCT
cana-2865	250	7	.	.	PUNCT
cana-2865	251	1	https://doi.org/10.1371/journal.pone.0171409	https://doi.org/10.1371/journal.pone.0171409	AUX
cana-2865	251	2	.	.	PUNCT
cana-2865	252	1	[	[	X
cana-2865	252	2	26	26	NUM
cana-2865	252	3	]	]	X
cana-2865	252	4	cai	cai	X
cana-2865	252	5	,	,	PUNCT
cana-2865	252	6	hanshu	hanshu	PROPN
cana-2865	252	7	,	,	PUNCT
cana-2865	252	8	et	et	PROPN
cana-2865	252	9	al	al	PROPN
cana-2865	252	10	.	.	PUNCT
cana-2865	253	1	"	"	PUNCT
cana-2865	253	2	a	a	DET
cana-2865	253	3	pervasive	pervasive	ADJ
cana-2865	253	4	approach	approach	NOUN
cana-2865	253	5	to	to	ADP
cana-2865	253	6	eeg	eeg	NOUN
cana-2865	253	7	-	-	PUNCT
cana-2865	253	8	based	base	VERB
cana-2865	253	9	depression	depression	NOUN
cana-2865	253	10	detection	detection	NOUN
cana-2865	253	11	.	.	PUNCT
cana-2865	253	12	"	"	PUNCT
cana-2865	254	1	hindawi	hindawi	ADJ
cana-2865	254	2	publishing	publishing	NOUN
cana-2865	254	3	corporation	corporation	NOUN
cana-2865	254	4	,	,	PUNCT
cana-2865	254	5	vol	vol	NOUN
cana-2865	254	6	1	1	NUM
cana-2865	254	7	.	.	NOUN
cana-2865	254	8	2018	2018	NUM
cana-2865	254	9	,	,	PUNCT
cana-2865	254	10	p.	p.	NOUN
cana-2865	254	11	1	1	NUM
cana-2865	254	12	-	-	SYM
cana-2865	254	13	13	13	NUM
cana-2865	254	14	.	.	PUNCT
cana-2865	254	15	https://doi.org/10.1155/2018/5238028	https://doi.org/10.1155/2018/5238028	NOUN
cana-2865	254	16	.	.	PUNCT
cana-2865	255	1	[	[	X
cana-2865	255	2	27	27	NUM
cana-2865	255	3	]	]	SYM
cana-2865	255	4	claudio	claudio	PROPN
cana-2865	255	5	greco	greco	PROPN
cana-2865	255	6	,	,	PUNCT
cana-2865	255	7	olimpia	olimpia	PROPN
cana-2865	255	8	matarazzo	matarazzo	PROPN
cana-2865	255	9	et	et	PROPN
cana-2865	255	10	al	al	PROPN
cana-2865	255	11	,	,	PUNCT
cana-2865	255	12	”	"	PUNCT
cana-2865	255	13	discriminative	discriminative	NOUN
cana-2865	255	14	power	power	NOUN
cana-2865	255	15	of	of	ADP
cana-2865	255	16	eeg	eeg	NOUN
cana-2865	255	17	-	-	PUNCT
cana-2865	255	18	based	base	VERB
cana-2865	255	19	biomarkers	biomarker	NOUN
cana-2865	255	20	in	in	ADP
cana-2865	255	21	major	major	ADJ
cana-2865	255	22	depressive	depressive	ADJ
cana-2865	255	23	disorder	disorder	NOUN
cana-2865	255	24	:	:	PUNCT
cana-2865	255	25	a	a	DET
cana-2865	255	26	systematic	systematic	ADJ
cana-2865	255	27	review	review	NOUN
cana-2865	255	28	”	"	PUNCT
cana-2865	255	29	,	,	PUNCT
cana-2865	255	30	ieee	ieee	NOUN
cana-2865	255	31	explore	explore	NOUN
cana-2865	255	32	,	,	PUNCT
cana-2865	255	33	vol	vol	NOUN
cana-2865	255	34	9	9	NUM
cana-2865	255	35	,	,	PUNCT
cana-2865	255	36	aug	aug	PROPN
cana-2865	255	37	2021	2021	NUM
cana-2865	255	38	,	,	PUNCT
cana-2865	255	39	112850	112850	NUM
cana-2865	255	40	–	–	PUNCT
cana-2865	255	41	112870	112870	NUM
cana-2865	255	42	,	,	PUNCT
cana-2865	255	43	http://doi.org/	http://doi.org/	NOUN
cana-2865	255	44	https://doi.org/10.1109/access.2021.3103047	https://doi.org/10.1109/access.2021.3103047	PROPN
cana-2865	255	45	[	[	X
cana-2865	255	46	28	28	NUM
cana-2865	255	47	]	]	X
cana-2865	255	48	f.s.d	f.s.d	ADJ
cana-2865	255	49	augiro	augiro	PROPN
cana-2865	255	50	neto	neto	VERB
cana-2865	255	51	et	et	PROPN
cana-2865	255	52	al	al	PROPN
cana-2865	255	53	,	,	PUNCT
cana-2865	255	54	“	"	PUNCT
cana-2865	255	55	depression	depression	NOUN
cana-2865	255	56	biomarkers	biomarker	NOUN
cana-2865	255	57	using	use	VERB
cana-2865	255	58	non	non	ADJ
cana-2865	255	59	-	-	ADJ
cana-2865	255	60	invasive	invasive	ADJ
cana-2865	255	61	eeg	eeg	NOUN
cana-2865	255	62	:	:	PUNCT
cana-2865	255	63	a	a	DET
cana-2865	255	64	review	review	NOUN
cana-2865	255	65	”	"	PUNCT
cana-2865	255	66	,	,	PUNCT
cana-2865	255	67	neuroscience	neuroscience	NOUN
cana-2865	255	68	&	&	CCONJ
cana-2865	255	69	biobehavioral	biobehavioral	ADJ
cana-2865	255	70	reviews	review	NOUN
cana-2865	255	71	,	,	PUNCT
cana-2865	255	72	vol	vol	NOUN
cana-2865	255	73	105	105	NUM
cana-2865	255	74	,	,	PUNCT
cana-2865	255	75	oct	oct	PROPN
cana-2865	255	76	2019	2019	NUM
cana-2865	255	77	,	,	PUNCT
cana-2865	255	78	83	83	NUM
cana-2865	255	79	-	-	SYM
cana-2865	255	80	93	93	NUM
cana-2865	255	81	,	,	PUNCT
cana-2865	255	82	https://doi.org/10.1016/j.neubiorev.2019.07.021	https://doi.org/10.1016/j.neubiorev.2019.07.021	PROPN
cana-2865	255	83	[	[	X
cana-2865	255	84	29	29	NUM
cana-2865	255	85	]	]	PUNCT
cana-2865	255	86	nishant	nishant	PROPN
cana-2865	255	87	sharma	sharma	PROPN
cana-2865	255	88	et	et	PROPN
cana-2865	255	89	al	al	PROPN
cana-2865	255	90	,	,	PUNCT
cana-2865	255	91	“	"	PUNCT
cana-2865	255	92	automated	automate	VERB
cana-2865	255	93	detection	detection	NOUN
cana-2865	255	94	of	of	ADP
cana-2865	255	95	depression	depression	NOUN
cana-2865	255	96	using	use	VERB
cana-2865	255	97	wavelet	wavelet	NOUN
cana-2865	255	98	scattering	scatter	VERB
cana-2865	255	99	networks	network	NOUN
cana-2865	255	100	”	"	PUNCT
cana-2865	255	101	,	,	PUNCT
cana-2865	255	102	medical	medical	ADJ
cana-2865	255	103	engineering	engineering	PROPN
cana-2865	255	104	&	&	CCONJ
cana-2865	255	105	physics	physics	PROPN
cana-2865	255	106	,	,	PUNCT
cana-2865	255	107	vol	vol	NOUN
cana-2865	255	108	124(181	124(181	NUM
cana-2865	255	109	)	)	PUNCT
cana-2865	255	110	,	,	PUNCT
cana-2865	255	111	feb	feb	PROPN
cana-2865	255	112	2024	2024	NUM
cana-2865	255	113	,	,	PUNCT
cana-2865	255	114	http://dx.doi.org/10.1016/j.medengphy.2024.104107	http://dx.doi.org/10.1016/j.medengphy.2024.104107	NUM
cana-2865	255	115	[	[	SYM
cana-2865	255	116	30	30	NUM
cana-2865	255	117	]	]	X
cana-2865	255	118	arora	arora	PROPN
cana-2865	255	119	,	,	PUNCT
cana-2865	255	120	sankalap	sankalap	NOUN
cana-2865	255	121	,	,	PUNCT
cana-2865	255	122	and	and	CCONJ
cana-2865	255	123	satvir	satvir	ADJ
cana-2865	255	124	singh	singh	PROPN
cana-2865	255	125	.	.	PUNCT
cana-2865	256	1	"	"	PUNCT
cana-2865	256	2	the	the	DET
cana-2865	256	3	firefly	firefly	NOUN
cana-2865	256	4	optimization	optimization	NOUN
cana-2865	256	5	algorithm	algorithm	NOUN
cana-2865	256	6	:	:	PUNCT
cana-2865	256	7	convergence	convergence	NOUN
cana-2865	256	8	analysis	analysis	NOUN
cana-2865	256	9	and	and	CCONJ
cana-2865	256	10	parameter	parameter	NOUN
cana-2865	256	11	selection	selection	NOUN
cana-2865	256	12	.	.	PUNCT
cana-2865	256	13	"	"	PUNCT
cana-2865	257	1	international	international	ADJ
cana-2865	257	2	journal	journal	NOUN
cana-2865	257	3	of	of	ADP
cana-2865	257	4	computer	computer	NOUN
cana-2865	257	5	applications	application	NOUN
cana-2865	257	6	vol	vol	NOUN
cana-2865	257	7	(	(	PUNCT
cana-2865	257	8	69	69	NUM
cana-2865	257	9	)	)	PUNCT
cana-2865	257	10	no.3	no.3	PROPN
cana-2865	257	11	,	,	PUNCT
cana-2865	257	12	may	may	AUX
cana-2865	257	13	2013	2013	NUM
cana-2865	257	14	.	.	PUNCT
cana-2865	258	1	https://doi.org/10.5120/118267528	https://doi.org/10.5120/118267528	X
cana-2865	258	2	.	.	PUNCT
cana-2865	259	1	[	[	X
cana-2865	259	2	31	31	NUM
cana-2865	259	3	]	]	PUNCT
cana-2865	259	4	r.a.movahed	r.a.movahe	VERB
cana-2865	259	5	et	et	PROPN
cana-2865	259	6	al	al	PROPN
cana-2865	259	7	,	,	PUNCT
cana-2865	259	8	“	"	PUNCT
cana-2865	259	9	a	a	DET
cana-2865	259	10	major	major	ADJ
cana-2865	259	11	depressive	depressive	ADJ
cana-2865	259	12	disorder	disorder	NOUN
cana-2865	259	13	classification	classification	NOUN
cana-2865	259	14	framework	framework	NOUN
cana-2865	259	15	based	base	VERB
cana-2865	259	16	on	on	ADP
cana-2865	259	17	eeg	eeg	NOUN
cana-2865	259	18	signals	signal	NOUN
cana-2865	259	19	using	use	VERB
cana-2865	259	20	statistical	statistical	ADJ
cana-2865	259	21	,	,	PUNCT
cana-2865	259	22	spectral	spectral	ADJ
cana-2865	259	23	,	,	PUNCT
cana-2865	259	24	wavelet	wavelet	NOUN
cana-2865	259	25	,	,	PUNCT
cana-2865	259	26	functional	functional	ADJ
cana-2865	259	27	connectivity	connectivity	NOUN
cana-2865	259	28	,	,	PUNCT
cana-2865	259	29	and	and	CCONJ
cana-2865	259	30	nonlinear	nonlinear	ADJ
cana-2865	259	31	analysis	analysis	NOUN
cana-2865	259	32	”	"	PUNCT
cana-2865	259	33	,	,	PUNCT
cana-2865	259	34	journal	journal	NOUN
cana-2865	259	35	of	of	ADP
cana-2865	259	36	neuroscience	neuroscience	NOUN
cana-2865	259	37	methods	method	NOUN
cana-2865	259	38	,	,	PUNCT
cana-2865	259	39	vol	vol	NOUN
cana-2865	259	40	358	358	NUM
cana-2865	259	41	,	,	PUNCT
cana-2865	259	42	july	july	PROPN
cana-2865	259	43	2021	2021	NUM
cana-2865	259	44	,	,	PUNCT
cana-2865	259	45	https://doi.org/10.1016/j.jneumeth.2021.109209	https://doi.org/10.1016/j.jneumeth.2021.109209	VERB
cana-2865	259	46	[	[	X
cana-2865	259	47	32	32	NUM
cana-2865	259	48	]	]	PUNCT
cana-2865	259	49	nayab	nayab	PROPN
cana-2865	259	50	bashir	bashir	PROPN
cana-2865	259	51	et	et	PROPN
cana-2865	259	52	al	al	PROPN
cana-2865	259	53	,	,	PUNCT
cana-2865	259	54	“	"	PUNCT
cana-2865	259	55	eeg	eeg	X
cana-2865	259	56	based	base	VERB
cana-2865	259	57	major	major	ADJ
cana-2865	259	58	depressive	depressive	ADJ
cana-2865	259	59	disorder	disorder	NOUN
cana-2865	259	60	(	(	PUNCT
cana-2865	259	61	mdd	mdd	PROPN
cana-2865	259	62	)	)	PUNCT
cana-2865	259	63	detection	detection	NOUN
cana-2865	259	64	using	use	VERB
cana-2865	259	65	machine	machine	NOUN
cana-2865	259	66	learning	learning	NOUN
cana-2865	259	67	”	"	PUNCT
cana-2865	259	68	,	,	PUNCT
cana-2865	259	69	pattern	pattern	NOUN
cana-2865	259	70	recognition	recognition	NOUN
cana-2865	259	71	and	and	CCONJ
cana-2865	259	72	artificial	artificial	ADJ
cana-2865	259	73	intelligence	intelligence	NOUN
cana-2865	259	74	,	,	PUNCT
cana-2865	259	75	april	april	PROPN
cana-2865	259	76	2022	2022	NUM
cana-2865	259	77	,	,	PUNCT
cana-2865	259	78	172	172	NUM
cana-2865	259	79	-	-	SYM
cana-2865	259	80	183	183	NUM
cana-2865	259	81	,	,	PUNCT
cana-2865	259	82	http://dx.doi.org/10.1007/978-3-031-04112-9_13	http://dx.doi.org/10.1007/978-3-031-04112-9_13	NOUN
cana-2865	259	83	http://dx.doi.org/10.3389/fbinf.2022.927312	http://dx.doi.org/10.3389/fbinf.2022.927312	NOUN
cana-2865	259	84	https://doi.org/10.1007/978-3-642-04944-6_14	https://doi.org/10.1007/978-3-642-04944-6_14	VERB
cana-2865	259	85	https://doi.org/10.1109/iceei52609.2021.9611110	https://doi.org/10.1109/iceei52609.2021.9611110	PROPN
cana-2865	259	86	http://dx.doi.org/10.1109/access.2021.3056407	http://dx.doi.org/10.1109/access.2021.3056407	NOUN
cana-2865	259	87	https://doi.org/10.1145/3469678.3469682	https://doi.org/10.1145/3469678.3469682	ADV
cana-2865	259	88	http://dx.doi.org/10.1109/access.2018.2843443	http://dx.doi.org/10.1109/access.2018.2843443	VERB
cana-2865	259	89	https://doi.org/10.1109/nabic.2009.5393690	https://doi.org/10.1109/nabic.2009.5393690	PROPN
cana-2865	259	90	https://doi.org/10.1016/j.knosys.2015.12.022	https://doi.org/10.1016/j.knosys.2015.12.022	NOUN
cana-2865	259	91	https://doi.org/10.1371/journal.pone.0171409	https://doi.org/10.1371/journal.pone.0171409	NOUN
cana-2865	259	92	https://doi.org/10.1155/2018/5238028	https://doi.org/10.1155/2018/5238028	NOUN
cana-2865	259	93	https://doi.org/10.1109/access.2021.3103047	https://doi.org/10.1109/access.2021.3103047	PROPN
cana-2865	259	94	https://www.sciencedirect.com/journal/neuroscience-and-biobehavioral-reviews	https://www.sciencedirect.com/journal/neuroscience-and-biobehavioral-review	NOUN
cana-2865	259	95	https://www.sciencedirect.com/journal/neuroscience-and-biobehavioral-reviews	https://www.sciencedirect.com/journal/neuroscience-and-biobehavioral-reviews	NOUN
cana-2865	259	96	https://doi.org/10.1016/j.neubiorev.2019.07.021	https://doi.org/10.1016/j.neubiorev.2019.07.021	VERB
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cana-2865	259	105	nonlinear	nonlinear	ADJ
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cana-2865	259	107	issn	issn	NOUN
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cana-2865	260	2	(	(	PUNCT
cana-2865	260	3	2025	2025	NUM
cana-2865	260	4	)	)	PUNCT
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cana-2865	261	60	”	"	PUNCT
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cana-2865	262	3	]	]	PUNCT
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cana-2865	262	9	“	"	PUNCT
cana-2865	262	10	eeg	eeg	NOUN
cana-2865	262	11	-	-	PUNCT
cana-2865	262	12	based	base	VERB
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cana-2865	262	14	depressive	depressive	ADJ
cana-2865	262	15	disorder	disorder	NOUN
cana-2865	262	16	recognition	recognition	NOUN
cana-2865	262	17	by	by	ADP
cana-2865	262	18	neural	neural	ADJ
cana-2865	262	19	oscillation	oscillation	NOUN
cana-2865	262	20	and	and	CCONJ
cana-2865	262	21	asymmetry	asymmetry	NOUN
cana-2865	262	22	”	"	PUNCT
cana-2865	262	23	,	,	PUNCT
cana-2865	262	24	frontiers	frontier	NOUN
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cana-2865	262	27	,	,	PUNCT
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cana-2865	262	29	18	18	NUM
cana-2865	262	30	,	,	PUNCT
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cana-2865	262	33	,	,	PUNCT
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cana-2865	265	12	"	"	PUNCT
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cana-2865	266	7	-	-	SYM
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cana-2865	266	9	.	.	PUNCT
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cana-2865	269	1	"	"	PUNCT
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cana-2865	269	7	-	-	SYM
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cana-2865	269	9	.	.	PUNCT
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cana-2865	273	8	,	,	PUNCT
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cana-2865	273	10	-	-	SYM
cana-2865	273	11	204	204	NUM
cana-2865	273	12	.	.	PUNCT
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cana-2865	277	7	,	,	PUNCT
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cana-2865	277	11	.	.	PUNCT
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cana-2865	280	10	)	)	PUNCT
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cana-2865	280	15	.	.	PUNCT
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