id	sid	tid	token	lemma	pos
cana-2348	1	1	communications	communication	NOUN
cana-2348	1	2	on	on	ADP
cana-2348	1	3	applied	apply	VERB
cana-2348	1	4	nonlinear	nonlinear	ADJ
cana-2348	1	5	analysis	analysis	NOUN
cana-2348	1	6	issn	issn	NOUN
cana-2348	1	7	:	:	PUNCT
cana-2348	1	8	1074	1074	NUM
cana-2348	1	9	-	-	PUNCT
cana-2348	1	10	133x	133x	NUM
cana-2348	1	11	vol	vol	NOUN
cana-2348	1	12	32	32	NUM
cana-2348	1	13	no	no	NOUN
cana-2348	1	14	.	.	PUNCT
cana-2348	2	1	1s	1s	NUM
cana-2348	2	2	(	(	PUNCT
cana-2348	2	3	2025	2025	NUM
cana-2348	2	4	)	)	PUNCT
cana-2348	2	5	622	622	NUM
cana-2348	2	6	performance	performance	NOUN
cana-2348	2	7	comparison	comparison	NOUN
cana-2348	2	8	of	of	ADP
cana-2348	2	9	deep	deep	ADJ
cana-2348	2	10	learning	learning	NOUN
cana-2348	2	11	algorithm	algorithm	NOUN
cana-2348	2	12	for	for	ADP
cana-2348	2	13	autism	autism	NOUN
cana-2348	2	14	spectrum	spectrum	NOUN
cana-2348	2	15	disorder	disorder	NOUN
cana-2348	2	16	prediction	prediction	NOUN
cana-2348	2	17	1tintu	1tintu	NUM
cana-2348	2	18	varghese	varghese	NOUN
cana-2348	2	19	,	,	PUNCT
cana-2348	2	20	2	2	NUM
cana-2348	2	21	2dr	2dr	NOUN
cana-2348	2	22	k	k	NOUN
cana-2348	2	23	devasenapathy	devasenapathy	ADJ
cana-2348	2	24	*	*	PUNCT
cana-2348	2	25	1research	1research	NUM
cana-2348	2	26	scholar	scholar	NOUN
cana-2348	2	27	,	,	PUNCT
cana-2348	2	28	karpagam	karpagam	PROPN
cana-2348	2	29	academy	academy	PROPN
cana-2348	2	30	of	of	ADP
cana-2348	2	31	higher	high	ADJ
cana-2348	2	32	education	education	NOUN
cana-2348	2	33	,	,	PUNCT
cana-2348	2	34	coimbatore	coimbatore	PROPN
cana-2348	2	35	,	,	PUNCT
cana-2348	2	36	tinta.varughese@gmail.com1,9188086651	tinta.varughese@gmail.com1,9188086651	ADV
cana-2348	2	37	*	*	PUNCT
cana-2348	2	38	2assistant	2assistant	NUM
cana-2348	2	39	professor	professor	NOUN
cana-2348	2	40	,	,	PUNCT
cana-2348	2	41	karpagam	karpagam	PROPN
cana-2348	2	42	academy	academy	PROPN
cana-2348	2	43	of	of	ADP
cana-2348	2	44	higher	high	ADJ
cana-2348	2	45	education	education	NOUN
cana-2348	2	46	,	,	PUNCT
cana-2348	2	47	coimbatore	coimbatore	PROPN
cana-2348	2	48	,	,	PUNCT
cana-2348	2	49	drdevasenapathy.k@kahedu.edu.in2,9600965375	drdevasenapathy.k@kahedu.edu.in2,9600965375	NOUN
cana-2348	2	50	article	article	NOUN
cana-2348	2	51	history	history	NOUN
cana-2348	2	52	:	:	PUNCT
cana-2348	2	53	received	receive	VERB
cana-2348	2	54	:	:	PUNCT
cana-2348	2	55	04	04	NUM
cana-2348	2	56	-	-	PUNCT
cana-2348	2	57	09	09	NUM
cana-2348	2	58	-	-	PUNCT
cana-2348	2	59	2024	2024	NUM
cana-2348	2	60	revised	revise	VERB
cana-2348	2	61	:	:	PUNCT
cana-2348	2	62	19	19	NUM
cana-2348	2	63	-	-	SYM
cana-2348	2	64	10	10	NUM
cana-2348	2	65	-	-	PUNCT
cana-2348	2	66	2024	2024	NUM
cana-2348	2	67	accepted	accept	VERB
cana-2348	2	68	:	:	PUNCT
cana-2348	2	69	02	02	NUM
cana-2348	2	70	-	-	SYM
cana-2348	2	71	11	11	NUM
cana-2348	2	72	-	-	PUNCT
cana-2348	2	73	2024	2024	NUM
cana-2348	2	74	abstract	abstract	NOUN
cana-2348	2	75	:	:	PUNCT
cana-2348	2	76	autism	autism	NOUN
cana-2348	2	77	spectrum	spectrum	NOUN
cana-2348	2	78	disorder	disorder	NOUN
cana-2348	2	79	is	be	AUX
cana-2348	2	80	a	a	DET
cana-2348	2	81	complex	complex	ADJ
cana-2348	2	82	neurodevelopmental	neurodevelopmental	ADJ
cana-2348	2	83	condition	condition	NOUN
cana-2348	2	84	that	that	SCONJ
cana-2348	2	85	significantly	significantly	ADV
cana-2348	2	86	impacts	impact	VERB
cana-2348	2	87	social	social	ADJ
cana-2348	2	88	interaction	interaction	NOUN
cana-2348	2	89	and	and	CCONJ
cana-2348	2	90	conduct	conduct	NOUN
cana-2348	2	91	in	in	ADP
cana-2348	2	92	individuals	individual	NOUN
cana-2348	2	93	.	.	PUNCT
cana-2348	3	1	early	early	ADJ
cana-2348	3	2	diagnosis	diagnosis	NOUN
cana-2348	3	3	and	and	CCONJ
cana-2348	3	4	timely	timely	ADJ
cana-2348	3	5	intervention	intervention	NOUN
cana-2348	3	6	are	be	AUX
cana-2348	3	7	crucial	crucial	ADJ
cana-2348	3	8	for	for	ADP
cana-2348	3	9	effectively	effectively	ADV
cana-2348	3	10	managing	manage	VERB
cana-2348	3	11	the	the	DET
cana-2348	3	12	condition	condition	NOUN
cana-2348	3	13	and	and	CCONJ
cana-2348	3	14	enhancing	enhance	VERB
cana-2348	3	15	overall	overall	ADJ
cana-2348	3	16	outcomes	outcome	NOUN
cana-2348	3	17	.	.	PUNCT
cana-2348	4	1	this	this	DET
cana-2348	4	2	study	study	NOUN
cana-2348	4	3	concentrates	concentrate	VERB
cana-2348	4	4	on	on	ADP
cana-2348	4	5	creating	create	VERB
cana-2348	4	6	predictive	predictive	ADJ
cana-2348	4	7	models	model	NOUN
cana-2348	4	8	through	through	ADP
cana-2348	4	9	deep	deep	ADJ
cana-2348	4	10	learning	learning	NOUN
cana-2348	4	11	algorithms	algorithm	NOUN
cana-2348	4	12	to	to	PART
cana-2348	4	13	assist	assist	VERB
cana-2348	4	14	in	in	ADP
cana-2348	4	15	the	the	DET
cana-2348	4	16	early	early	ADJ
cana-2348	4	17	identification	identification	NOUN
cana-2348	4	18	of	of	ADP
cana-2348	4	19	asd	asd	PROPN
cana-2348	4	20	.	.	PUNCT
cana-2348	5	1	the	the	DET
cana-2348	5	2	study	study	NOUN
cana-2348	5	3	employs	employ	VERB
cana-2348	5	4	an	an	DET
cana-2348	5	5	extensive	extensive	ADJ
cana-2348	5	6	dataset	dataset	NOUN
cana-2348	5	7	that	that	PRON
cana-2348	5	8	covers	cover	VERB
cana-2348	5	9	various	various	ADJ
cana-2348	5	10	features	feature	NOUN
cana-2348	5	11	linked	link	VERB
cana-2348	5	12	to	to	ADP
cana-2348	5	13	asd	asd	PROPN
cana-2348	5	14	traits	trait	NOUN
cana-2348	5	15	,	,	PUNCT
cana-2348	5	16	such	such	ADJ
cana-2348	5	17	as	as	ADP
cana-2348	5	18	speech	speech	NOUN
cana-2348	5	19	and	and	CCONJ
cana-2348	5	20	language	language	NOUN
cana-2348	5	21	development	development	NOUN
cana-2348	5	22	,	,	PUNCT
cana-2348	5	23	learning	learn	VERB
cana-2348	5	24	disorders	disorder	NOUN
cana-2348	5	25	,	,	PUNCT
cana-2348	5	26	genetic	genetic	ADJ
cana-2348	5	27	factors	factor	NOUN
cana-2348	5	28	,	,	PUNCT
cana-2348	5	29	and	and	CCONJ
cana-2348	5	30	behavioral	behavioral	ADJ
cana-2348	5	31	characteristics	characteristic	NOUN
cana-2348	5	32	.	.	PUNCT
cana-2348	6	1	the	the	DET
cana-2348	6	2	investigation	investigation	NOUN
cana-2348	6	3	encompasses	encompass	VERB
cana-2348	6	4	the	the	DET
cana-2348	6	5	assessment	assessment	NOUN
cana-2348	6	6	of	of	ADP
cana-2348	6	7	three	three	NUM
cana-2348	6	8	recurrent	recurrent	ADJ
cana-2348	6	9	neural	neural	ADJ
cana-2348	6	10	network	network	NOUN
cana-2348	6	11	(	(	PUNCT
cana-2348	6	12	rnn	rnn	PROPN
cana-2348	6	13	)	)	PUNCT
cana-2348	6	14	architectures	architecture	NOUN
cana-2348	6	15	-	-	PUNCT
cana-2348	6	16	standard	standard	PROPN
cana-2348	6	17	rnn	rnn	NOUN
cana-2348	6	18	,	,	PUNCT
cana-2348	6	19	long	long	ADJ
cana-2348	6	20	short	short	ADJ
cana-2348	6	21	term	term	NOUN
cana-2348	6	22	memory(lstm	memory(lstm	PROPN
cana-2348	6	23	)	)	PUNCT
cana-2348	6	24	,	,	PUNCT
cana-2348	6	25	and	and	CCONJ
cana-2348	6	26	gated	gate	VERB
cana-2348	6	27	recurrent	recurrent	ADJ
cana-2348	6	28	unit(gru	unit(gru	NOUN
cana-2348	6	29	)	)	PUNCT
cana-2348	6	30	–	–	PUNCT
cana-2348	6	31	for	for	ADP
cana-2348	6	32	their	their	PRON
cana-2348	6	33	effectiveness	effectiveness	NOUN
cana-2348	6	34	in	in	ADP
cana-2348	6	35	predicting	predict	VERB
cana-2348	6	36	asd	asd	NOUN
cana-2348	6	37	.	.	PUNCT
cana-2348	7	1	the	the	DET
cana-2348	7	2	dataset	dataset	NOUN
cana-2348	7	3	is	be	AUX
cana-2348	7	4	split	split	VERB
cana-2348	7	5	into	into	ADP
cana-2348	7	6	80	80	NUM
cana-2348	7	7	%	%	NOUN
cana-2348	7	8	for	for	ADP
cana-2348	7	9	training	training	NOUN
cana-2348	7	10	and	and	CCONJ
cana-2348	7	11	20	20	NUM
cana-2348	7	12	%	%	NOUN
cana-2348	7	13	for	for	ADP
cana-2348	7	14	testing	testing	NOUN
cana-2348	7	15	.	.	PUNCT
cana-2348	8	1	this	this	DET
cana-2348	8	2	study	study	NOUN
cana-2348	8	3	compares	compare	VERB
cana-2348	8	4	rnn	rnn	PROPN
cana-2348	8	5	,	,	PUNCT
cana-2348	8	6	lstm	lstm	NOUN
cana-2348	8	7	,	,	PUNCT
cana-2348	8	8	and	and	CCONJ
cana-2348	8	9	gru	gru	NOUN
cana-2348	8	10	algorithms	algorithm	NOUN
cana-2348	8	11	.	.	PUNCT
cana-2348	9	1	the	the	DET
cana-2348	9	2	classification	classification	NOUN
cana-2348	9	3	results	result	NOUN
cana-2348	9	4	show	show	VERB
cana-2348	9	5	that	that	SCONJ
cana-2348	9	6	the	the	DET
cana-2348	9	7	lstm	lstm	PROPN
cana-2348	9	8	and	and	CCONJ
cana-2348	9	9	gru	gru	NOUN
cana-2348	9	10	models	model	NOUN
cana-2348	9	11	exhibited	exhibit	VERB
cana-2348	9	12	similar	similar	ADJ
cana-2348	9	13	accuracy	accuracy	NOUN
cana-2348	9	14	,	,	PUNCT
cana-2348	9	15	with	with	ADP
cana-2348	9	16	values	value	NOUN
cana-2348	9	17	of	of	ADP
cana-2348	9	18	71.03	71.03	NUM
cana-2348	9	19	%	%	NOUN
cana-2348	9	20	and	and	CCONJ
cana-2348	9	21	70.78	70.78	NUM
cana-2348	9	22	%	%	NOUN
cana-2348	9	23	respectively	respectively	ADV
cana-2348	9	24	.	.	PUNCT
cana-2348	10	1	keywords	keyword	NOUN
cana-2348	10	2	:	:	PUNCT
cana-2348	10	3	autism	autism	NOUN
cana-2348	10	4	spectrum	spectrum	NOUN
cana-2348	10	5	disorder	disorder	NOUN
cana-2348	10	6	,	,	PUNCT
cana-2348	10	7	deep	deep	ADJ
cana-2348	10	8	learning	learning	NOUN
cana-2348	10	9	,	,	PUNCT
cana-2348	10	10	lstm	lstm	PROPN
cana-2348	10	11	,	,	PUNCT
cana-2348	10	12	gru	gru	PROPN
cana-2348	10	13	,	,	PUNCT
cana-2348	10	14	rnn	rnn	VERB
cana-2348	10	15	1	1	NUM
cana-2348	10	16	.	.	PUNCT
cana-2348	11	1	introduction	introduction	NOUN
cana-2348	11	2	autism	autism	NOUN
cana-2348	11	3	spectrum	spectrum	NOUN
cana-2348	11	4	disorder(asd	disorder(asd	NOUN
cana-2348	11	5	)	)	PUNCT
cana-2348	11	6	presents	present	VERB
cana-2348	11	7	a	a	DET
cana-2348	11	8	notable	notable	ADJ
cana-2348	11	9	challenge	challenge	NOUN
cana-2348	11	10	within	within	ADP
cana-2348	11	11	the	the	DET
cana-2348	11	12	domain	domain	NOUN
cana-2348	11	13	of	of	ADP
cana-2348	11	14	neurodevelopmental	neurodevelopmental	ADJ
cana-2348	11	15	disorders	disorder	NOUN
cana-2348	11	16	,	,	PUNCT
cana-2348	11	17	influencing	influence	VERB
cana-2348	11	18	social	social	ADJ
cana-2348	11	19	interactions	interaction	NOUN
cana-2348	11	20	,	,	PUNCT
cana-2348	11	21	communication	communication	NOUN
cana-2348	11	22	skills	skill	NOUN
cana-2348	11	23	,	,	PUNCT
cana-2348	11	24	and	and	CCONJ
cana-2348	11	25	behavioral	behavioral	ADJ
cana-2348	11	26	patterns	pattern	NOUN
cana-2348	11	27	in	in	ADP
cana-2348	11	28	individuals	individual	NOUN
cana-2348	11	29	.	.	PUNCT
cana-2348	12	1	early	early	ADJ
cana-2348	12	2	identification	identification	NOUN
cana-2348	12	3	and	and	CCONJ
cana-2348	12	4	intervention	intervention	NOUN
cana-2348	12	5	are	be	AUX
cana-2348	12	6	vital	vital	ADJ
cana-2348	12	7	in	in	ADP
cana-2348	12	8	improving	improve	VERB
cana-2348	12	9	outcomes	outcome	NOUN
cana-2348	12	10	and	and	CCONJ
cana-2348	12	11	boosting	boost	VERB
cana-2348	12	12	the	the	DET
cana-2348	12	13	well	well	ADV
cana-2348	12	14	-	-	PUNCT
cana-2348	12	15	being	being	NOUN
cana-2348	12	16	of	of	ADP
cana-2348	12	17	individuals	individual	NOUN
cana-2348	12	18	with	with	ADP
cana-2348	12	19	asd	asd	PROPN
cana-2348	12	20	.	.	PUNCT
cana-2348	13	1	"recently	"recently	ADV
cana-2348	13	2	,	,	PUNCT
cana-2348	13	3	incorporating	incorporate	VERB
cana-2348	13	4	advanced	advanced	ADJ
cana-2348	13	5	machine	machine	NOUN
cana-2348	13	6	learning	learn	VERB
cana-2348	13	7	techniques	technique	NOUN
cana-2348	13	8	,	,	PUNCT
cana-2348	13	9	specifically	specifically	ADV
cana-2348	13	10	deep	deep	ADJ
cana-2348	13	11	learning	learning	NOUN
cana-2348	13	12	algorithms	algorithm	NOUN
cana-2348	13	13	has	have	AUX
cana-2348	13	14	emerged	emerge	VERB
cana-2348	13	15	as	as	ADP
cana-2348	13	16	a	a	DET
cana-2348	13	17	promising	promising	ADJ
cana-2348	13	18	avenue	avenue	NOUN
cana-2348	13	19	for	for	ADP
cana-2348	13	20	predicting	predict	VERB
cana-2348	13	21	modeling	modeling	NOUN
cana-2348	13	22	in	in	ADP
cana-2348	13	23	healthcare	healthcare	PROPN
cana-2348	13	24	.	.	PUNCT
cana-2348	14	1	early	early	ADJ
cana-2348	14	2	detection	detection	NOUN
cana-2348	14	3	of	of	ADP
cana-2348	14	4	autism	autism	NOUN
cana-2348	14	5	spectrum	spectrum	NOUN
cana-2348	14	6	disorder	disorder	NOUN
cana-2348	14	7	(	(	PUNCT
cana-2348	14	8	asd	asd	NOUN
cana-2348	14	9	)	)	PUNCT
cana-2348	14	10	in	in	ADP
cana-2348	14	11	children	child	NOUN
cana-2348	14	12	is	be	AUX
cana-2348	14	13	crucial	crucial	ADJ
cana-2348	14	14	for	for	ADP
cana-2348	14	15	providing	provide	VERB
cana-2348	14	16	timely	timely	ADJ
cana-2348	14	17	support	support	NOUN
cana-2348	14	18	and	and	CCONJ
cana-2348	14	19	interventions	intervention	NOUN
cana-2348	14	20	,	,	PUNCT
cana-2348	14	21	significantly	significantly	ADV
cana-2348	14	22	enhancing	enhance	VERB
cana-2348	14	23	their	their	PRON
cana-2348	14	24	developmental	developmental	ADJ
cana-2348	14	25	outcomes	outcome	NOUN
cana-2348	14	26	and	and	CCONJ
cana-2348	14	27	overall	overall	ADJ
cana-2348	14	28	quality	quality	NOUN
cana-2348	14	29	of	of	ADP
cana-2348	14	30	life[1	life[1	NOUN
cana-2348	14	31	]	]	PUNCT
cana-2348	14	32	.	.	PUNCT
cana-2348	15	1	early	early	ADJ
cana-2348	15	2	identification	identification	NOUN
cana-2348	15	3	also	also	ADV
cana-2348	15	4	enables	enable	VERB
cana-2348	15	5	timely	timely	ADJ
cana-2348	15	6	access	access	NOUN
cana-2348	15	7	to	to	ADP
cana-2348	15	8	health	health	NOUN
cana-2348	15	9	services	service	NOUN
cana-2348	15	10	,	,	PUNCT
cana-2348	15	11	which	which	PRON
cana-2348	15	12	can	can	AUX
cana-2348	15	13	help	help	VERB
cana-2348	15	14	mitigate	mitigate	VERB
cana-2348	15	15	the	the	DET
cana-2348	15	16	challenges	challenge	NOUN
cana-2348	15	17	faced	face	VERB
cana-2348	15	18	by	by	ADP
cana-2348	15	19	individuals	individual	NOUN
cana-2348	15	20	with	with	ADP
cana-2348	15	21	asd	asd	NOUN
cana-2348	15	22	and	and	CCONJ
cana-2348	15	23	their	their	PRON
cana-2348	15	24	families[2	families[2	NOUN
cana-2348	15	25	]	]	PUNCT
cana-2348	15	26	.	.	PUNCT
cana-2348	16	1	various	various	ADJ
cana-2348	16	2	methods	method	NOUN
cana-2348	16	3	for	for	ADP
cana-2348	16	4	detecting	detect	VERB
cana-2348	16	5	asd	asd	NOUN
cana-2348	16	6	in	in	ADP
cana-2348	16	7	children	child	NOUN
cana-2348	16	8	include	include	VERB
cana-2348	16	9	analyzing	analyze	VERB
cana-2348	16	10	family	family	NOUN
cana-2348	16	11	medical	medical	ADJ
cana-2348	16	12	history	history	NOUN
cana-2348	16	13	and	and	CCONJ
cana-2348	16	14	identifying	identify	VERB
cana-2348	16	15	specific	specific	ADJ
cana-2348	16	16	biomarkers[3	biomarkers[3	PROPN
cana-2348	16	17	]	]	X
cana-2348	16	18	.	.	PUNCT
cana-2348	17	1	this	this	DET
cana-2348	17	2	study	study	NOUN
cana-2348	17	3	explores	explore	VERB
cana-2348	17	4	the	the	DET
cana-2348	17	5	utilization	utilization	NOUN
cana-2348	17	6	of	of	ADP
cana-2348	17	7	deep	deep	ADJ
cana-2348	17	8	learning	learning	NOUN
cana-2348	17	9	,	,	PUNCT
cana-2348	17	10	particularly	particularly	ADV
cana-2348	17	11	focusing	focus	VERB
cana-2348	17	12	on	on	ADP
cana-2348	17	13	rnn	rnn	PROPN
cana-2348	17	14	,	,	PUNCT
cana-2348	17	15	lstm	lstm	ADJ
cana-2348	17	16	,	,	PUNCT
cana-2348	17	17	and	and	CCONJ
cana-2348	17	18	gru	gru	VERB
cana-2348	17	19	for	for	ADP
cana-2348	17	20	predicting	predict	VERB
cana-2348	17	21	autism	autism	NOUN
cana-2348	17	22	spectrum	spectrum	NOUN
cana-2348	17	23	disorder	disorder	NOUN
cana-2348	17	24	(	(	PUNCT
cana-2348	17	25	asd	asd	NOUN
cana-2348	17	26	)	)	PUNCT
cana-2348	17	27	.	.	PUNCT
cana-2348	18	1	by	by	ADP
cana-2348	18	2	using	use	VERB
cana-2348	18	3	a	a	DET
cana-2348	18	4	dataset	dataset	NOUN
cana-2348	18	5	that	that	PRON
cana-2348	18	6	encompasses	encompass	VERB
cana-2348	18	7	features	feature	NOUN
cana-2348	18	8	related	relate	VERB
cana-2348	18	9	to	to	ADP
cana-2348	18	10	traits	trait	NOUN
cana-2348	18	11	,	,	PUNCT
cana-2348	18	12	associated	associate	VERB
cana-2348	18	13	with	with	ADP
cana-2348	18	14	autism	autism	NOUN
cana-2348	18	15	spectrum	spectrum	VERB
cana-2348	18	16	disorder.we	disorder.we	PRON
cana-2348	18	17	conduct	conduct	VERB
cana-2348	18	18	data	datum	NOUN
cana-2348	18	19	preprocessing	preprocessing	NOUN
cana-2348	18	20	and	and	CCONJ
cana-2348	18	21	employ	employ	NOUN
cana-2348	18	22	rnn	rnn	PROPN
cana-2348	18	23	,	,	PUNCT
cana-2348	18	24	lstm	lstm	NOUN
cana-2348	18	25	,	,	PUNCT
cana-2348	18	26	and	and	CCONJ
cana-2348	18	27	gru	gru	NOUN
cana-2348	18	28	models	model	NOUN
cana-2348	18	29	.	.	PUNCT
cana-2348	19	1	performance	performance	NOUN
cana-2348	19	2	metrics	metric	NOUN
cana-2348	19	3	,	,	PUNCT
cana-2348	19	4	including	include	VERB
cana-2348	19	5	accuracy	accuracy	NOUN
cana-2348	19	6	,	,	PUNCT
cana-2348	19	7	f1	f1	NOUN
cana-2348	19	8	score	score	NOUN
cana-2348	19	9	,	,	PUNCT
cana-2348	19	10	and	and	CCONJ
cana-2348	19	11	precision	precision	NOUN
cana-2348	19	12	,	,	PUNCT
cana-2348	19	13	are	be	AUX
cana-2348	19	14	employed	employ	VERB
cana-2348	19	15	to	to	PART
cana-2348	19	16	assess	assess	VERB
cana-2348	19	17	the	the	DET
cana-2348	19	18	predictive	predictive	ADJ
cana-2348	19	19	mailto	mailto	NOUN
cana-2348	19	20	:	:	PUNCT
cana-2348	19	21	tinta.varughese@gmail.com1,9188086651	tinta.varughese@gmail.com1,9188086651	DET
cana-2348	19	22	communications	communication	NOUN
cana-2348	19	23	on	on	ADP
cana-2348	19	24	applied	apply	VERB
cana-2348	19	25	nonlinear	nonlinear	ADJ
cana-2348	19	26	analysis	analysis	NOUN
cana-2348	19	27	issn	issn	NOUN
cana-2348	19	28	:	:	PUNCT
cana-2348	19	29	1074	1074	NUM
cana-2348	19	30	-	-	PUNCT
cana-2348	19	31	133x	133x	NUM
cana-2348	19	32	vol	vol	NOUN
cana-2348	19	33	32	32	NUM
cana-2348	19	34	no	no	NOUN
cana-2348	19	35	.	.	NOUN
cana-2348	19	36	2	2	NUM
cana-2348	19	37	(	(	PUNCT
cana-2348	19	38	2025	2025	NUM
cana-2348	19	39	)	)	PUNCT
cana-2348	19	40	623	623	NUM
cana-2348	19	41	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	19	42	effectiveness	effectiveness	NOUN
cana-2348	19	43	of	of	ADP
cana-2348	19	44	each	each	DET
cana-2348	19	45	algorithm	algorithm	NOUN
cana-2348	19	46	.	.	PUNCT
cana-2348	20	1	the	the	DET
cana-2348	20	2	selected	select	VERB
cana-2348	20	3	elements	element	NOUN
cana-2348	20	4	for	for	ADP
cana-2348	20	5	predicting	predict	VERB
cana-2348	20	6	asd	asd	PROPN
cana-2348	20	7	encompass	encompass	NOUN
cana-2348	20	8	speech	speech	NOUN
cana-2348	20	9	and	and	CCONJ
cana-2348	20	10	language	language	NOUN
cana-2348	20	11	development	development	NOUN
cana-2348	20	12	,	,	PUNCT
cana-2348	20	13	learning	learn	VERB
cana-2348	20	14	disorders	disorder	NOUN
cana-2348	20	15	,	,	PUNCT
cana-2348	20	16	genetic	genetic	ADJ
cana-2348	20	17	factors	factor	NOUN
cana-2348	20	18	,	,	PUNCT
cana-2348	20	19	and	and	CCONJ
cana-2348	20	20	social	social	ADJ
cana-2348	20	21	and	and	CCONJ
cana-2348	20	22	behavioral	behavioral	ADJ
cana-2348	20	23	characteristics	characteristic	NOUN
cana-2348	20	24	.	.	PUNCT
cana-2348	21	1	the	the	DET
cana-2348	21	2	study	study	NOUN
cana-2348	21	3	seeks	seek	VERB
cana-2348	21	4	to	to	PART
cana-2348	21	5	improve	improve	VERB
cana-2348	21	6	the	the	DET
cana-2348	21	7	strength	strength	NOUN
cana-2348	21	8	and	and	CCONJ
cana-2348	21	9	applicability	applicability	NOUN
cana-2348	21	10	of	of	ADP
cana-2348	21	11	the	the	DET
cana-2348	21	12	developed	develop	VERB
cana-2348	21	13	models	model	NOUN
cana-2348	21	14	by	by	ADP
cana-2348	21	15	utilizing	utilize	VERB
cana-2348	21	16	a	a	DET
cana-2348	21	17	diverse	diverse	ADJ
cana-2348	21	18	and	and	CCONJ
cana-2348	21	19	comprehensive	comprehensive	ADJ
cana-2348	21	20	dataset	dataset	NOUN
cana-2348	21	21	.	.	PUNCT
cana-2348	22	1	this	this	DET
cana-2348	22	2	article	article	NOUN
cana-2348	22	3	presents	present	VERB
cana-2348	22	4	characteristics	characteristic	NOUN
cana-2348	22	5	of	of	ADP
cana-2348	22	6	rnn	rnn	PROPN
cana-2348	22	7	,	,	PUNCT
cana-2348	22	8	lstm	lstm	NOUN
cana-2348	22	9	,	,	PUNCT
cana-2348	22	10	and	and	CCONJ
cana-2348	22	11	gru	gru	VERB
cana-2348	22	12	algorithms	algorithm	NOUN
cana-2348	22	13	for	for	ADP
cana-2348	22	14	autism	autism	NOUN
cana-2348	22	15	spectrum	spectrum	NOUN
cana-2348	22	16	disorder	disorder	NOUN
cana-2348	22	17	prediction	prediction	NOUN
cana-2348	22	18	.	.	PUNCT
cana-2348	23	1	part	part	NOUN
cana-2348	23	2	2	2	NUM
cana-2348	23	3	focuses	focus	VERB
cana-2348	23	4	on	on	ADP
cana-2348	23	5	literature	literature	NOUN
cana-2348	23	6	review	review	NOUN
cana-2348	23	7	.	.	PUNCT
cana-2348	24	1	.ii	.ii	PUNCT
cana-2348	24	2	.	.	PUNCT
cana-2348	25	1	literature	literature	PROPN
cana-2348	25	2	review	review	PROPN
cana-2348	25	3	vaishali	vaishali	PROPN
cana-2348	25	4	r	r	PROPN
cana-2348	25	5	,	,	PUNCT
cana-2348	25	6	sasikala	sasikala	PROPN
cana-2348	25	7	r.	r.	PROPN
cana-2348	25	8	,	,	PUNCT
cana-2348	25	9	et	et	PROPN
cana-2348	25	10	al	al	PROPN
cana-2348	25	11	.	.	PUNCT
cana-2348	26	1	[	[	X
cana-2348	26	2	4	4	X
cana-2348	26	3	]	]	PUNCT
cana-2348	26	4	proposed	propose	VERB
cana-2348	26	5	an	an	DET
cana-2348	26	6	approach	approach	NOUN
cana-2348	26	7	for	for	ADP
cana-2348	26	8	identifying	identify	VERB
cana-2348	26	9	autism	autism	NOUN
cana-2348	26	10	spectrum	spectrum	NOUN
cana-2348	26	11	disorder	disorder	NOUN
cana-2348	26	12	(	(	PUNCT
cana-2348	26	13	asd	asd	NOUN
cana-2348	26	14	)	)	PUNCT
cana-2348	26	15	by	by	ADP
cana-2348	26	16	optimizing	optimize	VERB
cana-2348	26	17	behavior	behavior	NOUN
cana-2348	26	18	sets	set	NOUN
cana-2348	26	19	.	.	PUNCT
cana-2348	27	1	the	the	DET
cana-2348	27	2	study	study	NOUN
cana-2348	27	3	employed	employ	VERB
cana-2348	27	4	an	an	DET
cana-2348	27	5	asd	asd	NOUN
cana-2348	27	6	diagnosis	diagnosis	NOUN
cana-2348	27	7	dataset	dataset	VERB
cana-2348	27	8	with	with	ADP
cana-2348	27	9	21	21	NUM
cana-2348	27	10	attributes	attribute	NOUN
cana-2348	27	11	,	,	PUNCT
cana-2348	27	12	sourced	source	VERB
cana-2348	27	13	from	from	ADP
cana-2348	27	14	the	the	DET
cana-2348	27	15	uci	uci	PROPN
cana-2348	27	16	machine	machine	NOUN
cana-2348	27	17	learning	learn	VERB
cana-2348	27	18	repository	repository	NOUN
cana-2348	27	19	.	.	PUNCT
cana-2348	28	1	the	the	DET
cana-2348	28	2	authors	author	NOUN
cana-2348	28	3	utilized	utilize	VERB
cana-2348	28	4	a	a	DET
cana-2348	28	5	bio	bio	NOUN
cana-2348	28	6	-	-	PUNCT
cana-2348	28	7	inspired	inspire	VERB
cana-2348	28	8	binary	binary	ADJ
cana-2348	28	9	firefly	firefly	NOUN
cana-2348	28	10	feature	feature	NOUN
cana-2348	28	11	selection	selection	NOUN
cana-2348	28	12	framework	framework	NOUN
cana-2348	28	13	in	in	ADP
cana-2348	28	14	their	their	PRON
cana-2348	28	15	experiments	experiment	NOUN
cana-2348	28	16	.	.	PUNCT
cana-2348	29	1	the	the	DET
cana-2348	29	2	underlying	underlying	ADJ
cana-2348	29	3	hypothesis	hypothesis	NOUN
cana-2348	29	4	suggests	suggest	VERB
cana-2348	29	5	that	that	SCONJ
cana-2348	29	6	a	a	DET
cana-2348	29	7	machine	machine	NOUN
cana-2348	29	8	learning	learning	NOUN
cana-2348	29	9	model	model	NOUN
cana-2348	29	10	can	can	AUX
cana-2348	29	11	achieve	achieve	VERB
cana-2348	29	12	higher	high	ADJ
cana-2348	29	13	classification	classification	NOUN
cana-2348	29	14	accuracy	accuracy	NOUN
cana-2348	29	15	by	by	ADP
cana-2348	29	16	utilizing	utilize	VERB
cana-2348	29	17	a	a	DET
cana-2348	29	18	minimal	minimal	ADJ
cana-2348	29	19	subset	subset	NOUN
cana-2348	29	20	of	of	ADP
cana-2348	29	21	features.m	features.m	PROPN
cana-2348	29	22	.	.	PUNCT
cana-2348	30	1	s.	s.	PROPN
cana-2348	30	2	mythili	mythili	PROPN
cana-2348	30	3	,	,	PUNCT
cana-2348	30	4	a.	a.	PROPN
cana-2348	30	5	r.	r.	PROPN
cana-2348	30	6	mohamed	mohamed	PROPN
cana-2348	30	7	shanavas	shanavas	PROPN
cana-2348	30	8	,	,	PUNCT
cana-2348	30	9	et	et	PROPN
cana-2348	30	10	al	al	PROPN
cana-2348	30	11	.	.	PUNCT
cana-2348	31	1	[	[	X
cana-2348	31	2	5	5	NUM
cana-2348	31	3	]	]	PUNCT
cana-2348	31	4	conducted	conduct	VERB
cana-2348	31	5	an	an	DET
cana-2348	31	6	investigation	investigation	NOUN
cana-2348	31	7	focused	focus	VERB
cana-2348	31	8	on	on	ADP
cana-2348	31	9	the	the	DET
cana-2348	31	10	detection	detection	NOUN
cana-2348	31	11	and	and	CCONJ
cana-2348	31	12	classification	classification	NOUN
cana-2348	31	13	of	of	ADP
cana-2348	31	14	autism	autism	NOUN
cana-2348	31	15	spectrum	spectrum	NOUN
cana-2348	31	16	disorder	disorder	NOUN
cana-2348	31	17	(	(	PUNCT
cana-2348	31	18	asd	asd	NOUN
cana-2348	31	19	)	)	PUNCT
cana-2348	31	20	and	and	CCONJ
cana-2348	31	21	the	the	DET
cana-2348	31	22	assessment	assessment	NOUN
cana-2348	31	23	of	of	ADP
cana-2348	31	24	autism	autism	NOUN
cana-2348	31	25	severity	severity	NOUN
cana-2348	31	26	levels	level	NOUN
cana-2348	31	27	.	.	PUNCT
cana-2348	32	1	the	the	DET
cana-2348	32	2	primary	primary	ADJ
cana-2348	32	3	objective	objective	NOUN
cana-2348	32	4	was	be	AUX
cana-2348	32	5	to	to	PART
cana-2348	32	6	identify	identify	VERB
cana-2348	32	7	autismrelated	autismrelate	VERB
cana-2348	32	8	issues	issue	NOUN
cana-2348	32	9	and	and	CCONJ
cana-2348	32	10	evaluate	evaluate	VERB
cana-2348	32	11	the	the	DET
cana-2348	32	12	severity	severity	NOUN
cana-2348	32	13	of	of	ADP
cana-2348	32	14	the	the	DET
cana-2348	32	15	condition	condition	NOUN
cana-2348	32	16	.	.	PUNCT
cana-2348	33	1	to	to	PART
cana-2348	33	2	study	study	VERB
cana-2348	33	3	students	student	NOUN
cana-2348	33	4	'	'	PART
cana-2348	33	5	behavioral	behavioral	ADJ
cana-2348	33	6	and	and	CCONJ
cana-2348	33	7	social	social	ADJ
cana-2348	33	8	interaction	interaction	NOUN
cana-2348	33	9	dynamics	dynamic	NOUN
cana-2348	33	10	,	,	PUNCT
cana-2348	33	11	the	the	DET
cana-2348	33	12	researchers	researcher	NOUN
cana-2348	33	13	applied	apply	VERB
cana-2348	33	14	neural	neural	ADJ
cana-2348	33	15	networks	network	NOUN
cana-2348	33	16	,	,	PUNCT
cana-2348	33	17	support	support	VERB
cana-2348	33	18	vector	vector	NOUN
cana-2348	33	19	machines	machine	NOUN
cana-2348	33	20	(	(	PUNCT
cana-2348	33	21	svm	svm	PROPN
cana-2348	33	22	)	)	PUNCT
cana-2348	33	23	,	,	PUNCT
cana-2348	33	24	and	and	CCONJ
cana-2348	33	25	fuzzy	fuzzy	ADJ
cana-2348	33	26	techniques	technique	NOUN
cana-2348	33	27	,	,	PUNCT
cana-2348	33	28	utilizing	utilize	VERB
cana-2348	33	29	the	the	DET
cana-2348	33	30	weka	weka	PROPN
cana-2348	33	31	software	software	NOUN
cana-2348	33	32	for	for	ADP
cana-2348	33	33	data	datum	NOUN
cana-2348	33	34	analysis	analysis	NOUN
cana-2348	33	35	.	.	PUNCT
cana-2348	34	1	through	through	ADP
cana-2348	34	2	the	the	DET
cana-2348	34	3	application	application	NOUN
cana-2348	34	4	of	of	ADP
cana-2348	34	5	these	these	DET
cana-2348	34	6	classification	classification	NOUN
cana-2348	34	7	techniques	technique	NOUN
cana-2348	34	8	,	,	PUNCT
cana-2348	34	9	the	the	DET
cana-2348	34	10	research	research	NOUN
cana-2348	34	11	aimed	aim	VERB
cana-2348	34	12	to	to	PART
cana-2348	34	13	gain	gain	VERB
cana-2348	34	14	insights	insight	NOUN
cana-2348	34	15	into	into	ADP
cana-2348	34	16	the	the	DET
cana-2348	34	17	intricacies	intricacy	NOUN
cana-2348	34	18	of	of	ADP
cana-2348	34	19	autism	autism	NOUN
cana-2348	34	20	and	and	CCONJ
cana-2348	34	21	provide	provide	VERB
cana-2348	34	22	a	a	DET
cana-2348	34	23	nuanced	nuanced	ADJ
cana-2348	34	24	insight	insight	NOUN
cana-2348	34	25	into	into	ADP
cana-2348	34	26	the	the	DET
cana-2348	34	27	spectrum	spectrum	NOUN
cana-2348	34	28	of	of	ADP
cana-2348	34	29	severity	severity	NOUN
cana-2348	34	30	levels	level	NOUN
cana-2348	34	31	connected	connect	VERB
cana-2348	34	32	with	with	ADP
cana-2348	34	33	the	the	DET
cana-2348	34	34	disorder	disorder	NOUN
cana-2348	34	35	.	.	PUNCT
cana-2348	35	1	in	in	ADP
cana-2348	35	2	paper[6	paper[6	PROPN
cana-2348	35	3	]	]	PUNCT
cana-2348	35	4	,	,	PUNCT
cana-2348	35	5	the	the	DET
cana-2348	35	6	main	main	ADJ
cana-2348	35	7	aim	aim	NOUN
cana-2348	35	8	is	be	AUX
cana-2348	35	9	to	to	PART
cana-2348	35	10	identify	identify	VERB
cana-2348	35	11	the	the	DET
cana-2348	35	12	most	most	ADV
cana-2348	35	13	significant	significant	ADJ
cana-2348	35	14	traits	trait	NOUN
cana-2348	35	15	related	relate	VERB
cana-2348	35	16	to	to	ADP
cana-2348	35	17	asd	asd	NOUN
cana-2348	35	18	and	and	CCONJ
cana-2348	35	19	automate	automate	VERB
cana-2348	35	20	the	the	DET
cana-2348	35	21	diagnosis	diagnosis	NOUN
cana-2348	35	22	process	process	NOUN
cana-2348	35	23	using	use	VERB
cana-2348	35	24	classification	classification	NOUN
cana-2348	35	25	techniques	technique	NOUN
cana-2348	35	26	.	.	PUNCT
cana-2348	36	1	the	the	DET
cana-2348	36	2	study	study	NOUN
cana-2348	36	3	analyzes	analyze	VERB
cana-2348	36	4	datasets	dataset	NOUN
cana-2348	36	5	related	relate	VERB
cana-2348	36	6	to	to	ADP
cana-2348	36	7	autism	autism	NOUN
cana-2348	36	8	spectrum	spectrum	NOUN
cana-2348	36	9	disorder	disorder	NOUN
cana-2348	36	10	(	(	PUNCT
cana-2348	36	11	asd	asd	NOUN
cana-2348	36	12	)	)	PUNCT
cana-2348	36	13	spanning	span	VERB
cana-2348	36	14	different	different	ADJ
cana-2348	36	15	age	age	NOUN
cana-2348	36	16	ranges	range	NOUN
cana-2348	36	17	,	,	PUNCT
cana-2348	36	18	including	include	VERB
cana-2348	36	19	toddlers	toddler	NOUN
cana-2348	36	20	,	,	PUNCT
cana-2348	36	21	children	child	NOUN
cana-2348	36	22	,	,	PUNCT
cana-2348	36	23	adolescents	adolescent	NOUN
cana-2348	36	24	,	,	PUNCT
cana-2348	36	25	and	and	CCONJ
cana-2348	36	26	adults	adult	NOUN
cana-2348	36	27	.	.	PUNCT
cana-2348	37	1	the	the	DET
cana-2348	37	2	authors	author	NOUN
cana-2348	37	3	suggest	suggest	VERB
cana-2348	37	4	the	the	DET
cana-2348	37	5	potential	potential	NOUN
cana-2348	37	6	of	of	ADP
cana-2348	37	7	machine	machine	NOUN
cana-2348	37	8	learning	learning	NOUN
cana-2348	37	9	,	,	PUNCT
cana-2348	37	10	specifically	specifically	ADV
cana-2348	37	11	the	the	DET
cana-2348	37	12	mlp	mlp	NOUN
cana-2348	37	13	classifier	classifier	NOUN
cana-2348	37	14	,	,	PUNCT
cana-2348	37	15	in	in	ADP
cana-2348	37	16	enhancing	enhance	VERB
cana-2348	37	17	the	the	DET
cana-2348	37	18	accuracy	accuracy	NOUN
cana-2348	37	19	of	of	ADP
cana-2348	37	20	asd	asd	NOUN
cana-2348	37	21	diagnosis	diagnosis	NOUN
cana-2348	37	22	.	.	PUNCT
cana-2348	38	1	automation	automation	NOUN
cana-2348	38	2	of	of	ADP
cana-2348	38	3	the	the	DET
cana-2348	38	4	diagnosis	diagnosis	NOUN
cana-2348	38	5	process	process	NOUN
cana-2348	38	6	using	use	VERB
cana-2348	38	7	these	these	DET
cana-2348	38	8	techniques	technique	NOUN
cana-2348	38	9	may	may	AUX
cana-2348	38	10	contribute	contribute	VERB
cana-2348	38	11	to	to	ADP
cana-2348	38	12	more	more	ADV
cana-2348	38	13	efficient	efficient	ADJ
cana-2348	38	14	and	and	CCONJ
cana-2348	38	15	reliable	reliable	ADJ
cana-2348	38	16	early	early	ADJ
cana-2348	38	17	detection	detection	NOUN
cana-2348	38	18	.	.	PUNCT
cana-2348	39	1	in	in	ADP
cana-2348	39	2	the	the	DET
cana-2348	39	3	paper	paper	NOUN
cana-2348	39	4	,	,	PUNCT
cana-2348	39	5	the	the	DET
cana-2348	39	6	authors	author	NOUN
cana-2348	39	7	[	[	X
cana-2348	39	8	7	7	X
cana-2348	39	9	]	]	PUNCT
cana-2348	39	10	introduced	introduce	VERB
cana-2348	39	11	a	a	DET
cana-2348	39	12	powerful	powerful	ADJ
cana-2348	39	13	approach	approach	NOUN
cana-2348	39	14	for	for	ADP
cana-2348	39	15	diagnosing	diagnose	VERB
cana-2348	39	16	autism	autism	NOUN
cana-2348	39	17	spectrum	spectrum	NOUN
cana-2348	39	18	disorder	disorder	NOUN
cana-2348	39	19	(	(	PUNCT
cana-2348	39	20	asd	asd	NOUN
cana-2348	39	21	)	)	PUNCT
cana-2348	39	22	using	use	VERB
cana-2348	39	23	deep	deep	ADJ
cana-2348	39	24	learning	learning	NOUN
cana-2348	39	25	on	on	ADP
cana-2348	39	26	facial	facial	ADJ
cana-2348	39	27	images	image	NOUN
cana-2348	39	28	.	.	PUNCT
cana-2348	40	1	the	the	DET
cana-2348	40	2	method	method	NOUN
cana-2348	40	3	involves	involve	VERB
cana-2348	40	4	training	train	VERB
cana-2348	40	5	a	a	DET
cana-2348	40	6	convolutional	convolutional	ADJ
cana-2348	40	7	neural	neural	ADJ
cana-2348	40	8	network	network	NOUN
cana-2348	40	9	(	(	PUNCT
cana-2348	40	10	cnn	cnn	PROPN
cana-2348	40	11	)	)	PUNCT
cana-2348	40	12	with	with	ADP
cana-2348	40	13	a	a	DET
cana-2348	40	14	dataset	dataset	NOUN
cana-2348	40	15	,	,	PUNCT
cana-2348	40	16	incorporating	incorporate	VERB
cana-2348	40	17	pre	pre	ADJ
cana-2348	40	18	-	-	ADJ
cana-2348	40	19	processing	processing	ADJ
cana-2348	40	20	and	and	CCONJ
cana-2348	40	21	data	datum	NOUN
cana-2348	40	22	synthesis	synthesis	NOUN
cana-2348	40	23	.	.	PUNCT
cana-2348	41	1	the	the	DET
cana-2348	41	2	trained	train	VERB
cana-2348	41	3	model	model	NOUN
cana-2348	41	4	is	be	AUX
cana-2348	41	5	then	then	ADV
cana-2348	41	6	assessed	assess	VERB
cana-2348	41	7	on	on	ADP
cana-2348	41	8	an	an	DET
cana-2348	41	9	independent	independent	ADJ
cana-2348	41	10	test	test	NOUN
cana-2348	41	11	set	set	NOUN
cana-2348	41	12	.	.	PUNCT
cana-2348	42	1	the	the	DET
cana-2348	42	2	novel	novel	NOUN
cana-2348	42	3	approach	approach	NOUN
cana-2348	42	4	,	,	PUNCT
cana-2348	42	5	which	which	PRON
cana-2348	42	6	simultaneously	simultaneously	ADV
cana-2348	42	7	applies	apply	VERB
cana-2348	42	8	pre	pre	ADJ
cana-2348	42	9	-	-	ADJ
cana-2348	42	10	processing	processing	NOUN
cana-2348	42	11	and	and	CCONJ
cana-2348	42	12	augmentation	augmentation	NOUN
cana-2348	42	13	during	during	ADP
cana-2348	42	14	training	training	NOUN
cana-2348	42	15	,	,	PUNCT
cana-2348	42	16	outperforms	outperform	VERB
cana-2348	42	17	recent	recent	ADJ
cana-2348	42	18	methods	method	NOUN
cana-2348	42	19	,	,	PUNCT
cana-2348	42	20	achieving	achieve	VERB
cana-2348	42	21	a	a	DET
cana-2348	42	22	remarkable	remarkable	ADJ
cana-2348	42	23	98.9	98.9	NUM
cana-2348	42	24	%	%	NOUN
cana-2348	42	25	accuracy	accuracy	NOUN
cana-2348	42	26	,	,	PUNCT
cana-2348	42	27	sensitivity	sensitivity	NOUN
cana-2348	42	28	,	,	PUNCT
cana-2348	42	29	and	and	CCONJ
cana-2348	42	30	specificity	specificity	NOUN
cana-2348	42	31	,	,	PUNCT
cana-2348	42	32	with	with	ADP
cana-2348	42	33	a	a	DET
cana-2348	42	34	99.9	99.9	NUM
cana-2348	42	35	%	%	NOUN
cana-2348	42	36	area	area	NOUN
cana-2348	42	37	under	under	ADP
cana-2348	42	38	the	the	DET
cana-2348	42	39	curve	curve	NOUN
cana-2348	42	40	(	(	PUNCT
cana-2348	42	41	auc	auc	NOUN
cana-2348	42	42	)	)	PUNCT
cana-2348	42	43	.	.	PUNCT
cana-2348	43	1	notably	notably	ADV
cana-2348	43	2	,	,	PUNCT
cana-2348	43	3	the	the	DET
cana-2348	43	4	algorithm	algorithm	NOUN
cana-2348	43	5	integrates	integrate	VERB
cana-2348	43	6	explainable	explainable	ADJ
cana-2348	43	7	ai	ai	NOUN
cana-2348	43	8	techniques	technique	NOUN
cana-2348	43	9	,	,	PUNCT
cana-2348	43	10	enhancing	enhance	VERB
cana-2348	43	11	clarity	clarity	NOUN
cana-2348	43	12	for	for	ADP
cana-2348	43	13	clinicians	clinician	NOUN
cana-2348	43	14	and	and	CCONJ
cana-2348	43	15	providing	provide	VERB
cana-2348	43	16	a	a	DET
cana-2348	43	17	clear	clear	ADJ
cana-2348	43	18	understanding	understanding	NOUN
cana-2348	43	19	of	of	ADP
cana-2348	43	20	the	the	DET
cana-2348	43	21	asd	asd	PROPN
cana-2348	43	22	diagnosis	diagnosis	NOUN
cana-2348	43	23	model	model	NOUN
cana-2348	43	24	's	's	PART
cana-2348	43	25	decision	decision	NOUN
cana-2348	43	26	-	-	PUNCT
cana-2348	43	27	making	make	VERB
cana-2348	43	28	process	process	NOUN
cana-2348	43	29	.	.	PUNCT
cana-2348	44	1	this	this	DET
cana-2348	44	2	research	research	NOUN
cana-2348	44	3	contributes	contribute	VERB
cana-2348	44	4	to	to	ADP
cana-2348	44	5	the	the	DET
cana-2348	44	6	field	field	NOUN
cana-2348	44	7	by	by	ADP
cana-2348	44	8	delivering	deliver	VERB
cana-2348	44	9	a	a	DET
cana-2348	44	10	highly	highly	ADV
cana-2348	44	11	accurate	accurate	ADJ
cana-2348	44	12	and	and	CCONJ
cana-2348	44	13	transparent	transparent	ADJ
cana-2348	44	14	approach	approach	NOUN
cana-2348	44	15	to	to	ADP
cana-2348	44	16	asd	asd	NOUN
cana-2348	44	17	diagnosis	diagnosis	NOUN
cana-2348	44	18	from	from	ADP
cana-2348	44	19	facial	facial	ADJ
cana-2348	44	20	images	image	NOUN
cana-2348	44	21	.	.	PUNCT
cana-2348	45	1	communications	communication	NOUN
cana-2348	45	2	on	on	ADP
cana-2348	45	3	applied	apply	VERB
cana-2348	45	4	nonlinear	nonlinear	ADJ
cana-2348	45	5	analysis	analysis	NOUN
cana-2348	45	6	issn	issn	NOUN
cana-2348	45	7	:	:	PUNCT
cana-2348	45	8	1074	1074	NUM
cana-2348	45	9	-	-	PUNCT
cana-2348	45	10	133x	133x	NUM
cana-2348	45	11	vol	vol	NOUN
cana-2348	45	12	32	32	NUM
cana-2348	45	13	no	no	NOUN
cana-2348	45	14	.	.	NOUN
cana-2348	45	15	2	2	NUM
cana-2348	45	16	(	(	PUNCT
cana-2348	45	17	2025	2025	NUM
cana-2348	45	18	)	)	PUNCT
cana-2348	45	19	624	624	NUM
cana-2348	45	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	45	21	kang	kang	PROPN
cana-2348	45	22	's	's	PART
cana-2348	45	23	studies	study	NOUN
cana-2348	45	24	utilize	utilize	VERB
cana-2348	45	25	a	a	DET
cana-2348	45	26	support	support	NOUN
cana-2348	45	27	vector	vector	NOUN
cana-2348	45	28	machine	machine	NOUN
cana-2348	45	29	(	(	PUNCT
cana-2348	45	30	svm	svm	PROPN
cana-2348	45	31	)	)	PUNCT
cana-2348	45	32	to	to	PART
cana-2348	45	33	identify	identify	VERB
cana-2348	45	34	cases	case	NOUN
cana-2348	45	35	of	of	ADP
cana-2348	45	36	autism	autism	NOUN
cana-2348	45	37	spectrum	spectrum	NOUN
cana-2348	45	38	disorder	disorder	NOUN
cana-2348	45	39	(	(	PUNCT
cana-2348	45	40	asd	asd	NOUN
cana-2348	45	41	)	)	PUNCT
cana-2348	45	42	in	in	ADP
cana-2348	45	43	children	child	NOUN
cana-2348	45	44	,	,	PUNCT
cana-2348	45	45	relying	rely	VERB
cana-2348	45	46	on	on	ADP
cana-2348	45	47	both	both	DET
cana-2348	45	48	eeg	eeg	NOUN
cana-2348	45	49	and	and	CCONJ
cana-2348	45	50	eye	eye	NOUN
cana-2348	45	51	-	-	PUNCT
cana-2348	45	52	tracking	track	VERB
cana-2348	45	53	data	datum	NOUN
cana-2348	45	54	[	[	X
cana-2348	45	55	8	8	NUM
cana-2348	45	56	]	]	PUNCT
cana-2348	45	57	.	.	PUNCT
cana-2348	46	1	the	the	DET
cana-2348	46	2	classification	classification	NOUN
cana-2348	46	3	results	result	NOUN
cana-2348	46	4	from	from	ADP
cana-2348	46	5	these	these	DET
cana-2348	46	6	combined	combine	VERB
cana-2348	46	7	data	datum	NOUN
cana-2348	46	8	sources	source	NOUN
cana-2348	46	9	show	show	VERB
cana-2348	46	10	potential	potential	NOUN
cana-2348	46	11	for	for	ADP
cana-2348	46	12	improvement	improvement	NOUN
cana-2348	46	13	.	.	PUNCT
cana-2348	47	1	the	the	DET
cana-2348	47	2	studies	study	NOUN
cana-2348	47	3	suggest	suggest	VERB
cana-2348	47	4	employing	employ	VERB
cana-2348	47	5	both	both	PRON
cana-2348	47	6	eeg	eeg	NOUN
cana-2348	47	7	and	and	CCONJ
cana-2348	47	8	eye	eye	NOUN
cana-2348	47	9	-	-	PUNCT
cana-2348	47	10	tracking	track	VERB
cana-2348	47	11	data	datum	NOUN
cana-2348	47	12	together	together	ADV
cana-2348	47	13	improves	improve	VERB
cana-2348	47	14	the	the	DET
cana-2348	47	15	precision	precision	NOUN
cana-2348	47	16	of	of	ADP
cana-2348	47	17	detecting	detect	VERB
cana-2348	47	18	asd	asd	NOUN
cana-2348	47	19	compared	compare	VERB
cana-2348	47	20	to	to	ADP
cana-2348	47	21	relying	rely	VERB
cana-2348	47	22	solely	solely	ADV
cana-2348	47	23	on	on	ADP
cana-2348	47	24	electroencephalography	electroencephalography	NOUN
cana-2348	47	25	or	or	CCONJ
cana-2348	47	26	eye	eye	NOUN
cana-2348	47	27	-	-	PUNCT
cana-2348	47	28	tracking	track	VERB
cana-2348	47	29	data	datum	NOUN
cana-2348	47	30	separately	separately	ADV
cana-2348	47	31	.	.	PUNCT
cana-2348	48	1	this	this	DET
cana-2348	48	2	observation	observation	NOUN
cana-2348	48	3	underscores	underscore	VERB
cana-2348	48	4	the	the	DET
cana-2348	48	5	importance	importance	NOUN
cana-2348	48	6	of	of	ADP
cana-2348	48	7	leveraging	leverage	VERB
cana-2348	48	8	multiple	multiple	ADJ
cana-2348	48	9	modalities	modality	NOUN
cana-2348	48	10	in	in	ADP
cana-2348	48	11	the	the	DET
cana-2348	48	12	diagnostic	diagnostic	ADJ
cana-2348	48	13	process	process	NOUN
cana-2348	48	14	.	.	PUNCT
cana-2348	49	1	the	the	DET
cana-2348	49	2	studies	study	NOUN
cana-2348	49	3	contribute	contribute	VERB
cana-2348	49	4	to	to	ADP
cana-2348	49	5	the	the	DET
cana-2348	49	6	field	field	NOUN
cana-2348	49	7	's	's	PART
cana-2348	49	8	understanding	understanding	NOUN
cana-2348	49	9	of	of	ADP
cana-2348	49	10	the	the	DET
cana-2348	49	11	complementary	complementary	ADJ
cana-2348	49	12	nature	nature	NOUN
cana-2348	49	13	of	of	ADP
cana-2348	49	14	eeg	eeg	PROPN
cana-2348	49	15	and	and	CCONJ
cana-2348	49	16	eye	eye	NOUN
cana-2348	49	17	-	-	PUNCT
cana-2348	49	18	tracking	track	VERB
cana-2348	49	19	data	datum	NOUN
cana-2348	49	20	in	in	ADP
cana-2348	49	21	improving	improve	VERB
cana-2348	49	22	the	the	DET
cana-2348	49	23	classification	classification	NOUN
cana-2348	49	24	of	of	ADP
cana-2348	49	25	asd	asd	PROPN
cana-2348	49	26	cases	case	NOUN
cana-2348	49	27	in	in	ADP
cana-2348	49	28	children	child	NOUN
cana-2348	49	29	.	.	PUNCT
cana-2348	50	1	the	the	DET
cana-2348	50	2	study	study	NOUN
cana-2348	50	3	[	[	X
cana-2348	50	4	9	9	NUM
cana-2348	50	5	]	]	PUNCT
cana-2348	50	6	explores	explore	VERB
cana-2348	50	7	the	the	DET
cana-2348	50	8	use	use	NOUN
cana-2348	50	9	of	of	ADP
cana-2348	50	10	document	document	NOUN
cana-2348	50	11	classification	classification	NOUN
cana-2348	50	12	algorithms	algorithm	NOUN
cana-2348	50	13	to	to	PART
cana-2348	50	14	improve	improve	VERB
cana-2348	50	15	the	the	DET
cana-2348	50	16	efficiency	efficiency	NOUN
cana-2348	50	17	of	of	ADP
cana-2348	50	18	measuring	measure	VERB
cana-2348	50	19	the	the	DET
cana-2348	50	20	occurrence	occurrence	NOUN
cana-2348	50	21	of	of	ADP
cana-2348	50	22	autism	autism	NOUN
cana-2348	50	23	spectrum	spectrum	NOUN
cana-2348	50	24	disorder	disorder	NOUN
cana-2348	50	25	(	(	PUNCT
cana-2348	50	26	asd	asd	NOUN
cana-2348	50	27	)	)	PUNCT
cana-2348	50	28	in	in	ADP
cana-2348	50	29	children	child	NOUN
cana-2348	50	30	in	in	ADP
cana-2348	50	31	the	the	DET
cana-2348	50	32	united	united	PROPN
cana-2348	50	33	states	states	PROPN
cana-2348	50	34	,	,	PUNCT
cana-2348	50	35	a	a	DET
cana-2348	50	36	process	process	NOUN
cana-2348	50	37	traditionally	traditionally	ADV
cana-2348	50	38	managed	manage	VERB
cana-2348	50	39	through	through	ADP
cana-2348	50	40	labor	labor	NOUN
cana-2348	50	41	-	-	PUNCT
cana-2348	50	42	intensive	intensive	ADJ
cana-2348	50	43	procedures	procedure	NOUN
cana-2348	50	44	by	by	ADP
cana-2348	50	45	the	the	DET
cana-2348	50	46	centers	center	NOUN
cana-2348	50	47	for	for	ADP
cana-2348	50	48	disease	disease	NOUN
cana-2348	50	49	control	control	NOUN
cana-2348	50	50	and	and	CCONJ
cana-2348	50	51	prevention	prevention	NOUN
cana-2348	50	52	(	(	PUNCT
cana-2348	50	53	cdc	cdc	PROPN
cana-2348	50	54	)	)	PUNCT
cana-2348	50	55	.	.	PUNCT
cana-2348	51	1	while	while	SCONJ
cana-2348	51	2	random	random	ADJ
cana-2348	51	3	forest	forest	NOUN
cana-2348	51	4	methods	method	NOUN
cana-2348	51	5	have	have	AUX
cana-2348	51	6	shown	show	VERB
cana-2348	51	7	promise	promise	NOUN
cana-2348	51	8	,	,	PUNCT
cana-2348	51	9	they	they	PRON
cana-2348	51	10	still	still	ADV
cana-2348	51	11	lag	lag	VERB
cana-2348	51	12	behind	behind	ADP
cana-2348	51	13	human	human	ADJ
cana-2348	51	14	classification	classification	NOUN
cana-2348	51	15	accuracy	accuracy	NOUN
cana-2348	51	16	.	.	PUNCT
cana-2348	52	1	the	the	DET
cana-2348	52	2	research	research	NOUN
cana-2348	52	3	aims	aim	VERB
cana-2348	52	4	to	to	PART
cana-2348	52	5	investigate	investigate	VERB
cana-2348	52	6	whether	whether	SCONJ
cana-2348	52	7	newly	newly	ADV
cana-2348	52	8	available	available	ADJ
cana-2348	52	9	document	document	NOUN
cana-2348	52	10	classification	classification	NOUN
cana-2348	52	11	algorithms	algorithm	NOUN
cana-2348	52	12	can	can	AUX
cana-2348	52	13	help	help	VERB
cana-2348	52	14	reduce	reduce	VERB
cana-2348	52	15	this	this	DET
cana-2348	52	16	disparity	disparity	NOUN
cana-2348	52	17	.	.	PUNCT
cana-2348	53	1	iii.dataset	iii.dataset	PROPN
cana-2348	53	2	description	description	NOUN
cana-2348	53	3	data	datum	NOUN
cana-2348	53	4	preprocessing	preprocessing	NOUN
cana-2348	53	5	plays	play	VERB
cana-2348	53	6	a	a	DET
cana-2348	53	7	pivotal	pivotal	ADJ
cana-2348	53	8	role	role	NOUN
cana-2348	53	9	in	in	ADP
cana-2348	53	10	machine	machine	NOUN
cana-2348	53	11	learning	learning	NOUN
cana-2348	53	12	and	and	CCONJ
cana-2348	53	13	data	datum	NOUN
cana-2348	53	14	analysis	analysis	NOUN
cana-2348	53	15	by	by	ADP
cana-2348	53	16	readying	ready	VERB
cana-2348	53	17	the	the	DET
cana-2348	53	18	dataset	dataset	NOUN
cana-2348	53	19	for	for	ADP
cana-2348	53	20	analysis	analysis	NOUN
cana-2348	53	21	or	or	CCONJ
cana-2348	53	22	model	model	NOUN
cana-2348	53	23	training	training	NOUN
cana-2348	53	24	.	.	PUNCT
cana-2348	54	1	it	it	PRON
cana-2348	54	2	encompasses	encompass	VERB
cana-2348	54	3	various	various	ADJ
cana-2348	54	4	steps	step	NOUN
cana-2348	54	5	to	to	PART
cana-2348	54	6	cleanse	cleanse	VERB
cana-2348	54	7	,	,	PUNCT
cana-2348	54	8	transform	transform	VERB
cana-2348	54	9	,	,	PUNCT
cana-2348	54	10	and	and	CCONJ
cana-2348	54	11	manipulate	manipulate	VERB
cana-2348	54	12	the	the	DET
cana-2348	54	13	data	datum	NOUN
cana-2348	54	14	,	,	PUNCT
cana-2348	54	15	ensuring	ensure	VERB
cana-2348	54	16	its	its	PRON
cana-2348	54	17	quality	quality	NOUN
cana-2348	54	18	and	and	CCONJ
cana-2348	54	19	alignment	alignment	NOUN
cana-2348	54	20	with	with	ADP
cana-2348	54	21	the	the	DET
cana-2348	54	22	selected	select	VERB
cana-2348	54	23	machine	machine	NOUN
cana-2348	54	24	learning	learning	NOUN
cana-2348	54	25	algorithms	algorithm	NOUN
cana-2348	54	26	.	.	PUNCT
cana-2348	55	1	the	the	DET
cana-2348	55	2	dataset	dataset	NOUN
cana-2348	55	3	used	use	VERB
cana-2348	55	4	in	in	ADP
cana-2348	55	5	this	this	DET
cana-2348	55	6	study	study	NOUN
cana-2348	55	7	was	be	AUX
cana-2348	55	8	acquired	acquire	VERB
cana-2348	55	9	from	from	ADP
cana-2348	55	10	kaggle	kaggle	PROPN
cana-2348	55	11	.	.	PUNCT
cana-2348	56	1	the	the	DET
cana-2348	56	2	dataset	dataset	NOUN
cana-2348	56	3	comprises	comprise	VERB
cana-2348	56	4	2,000	2,000	NUM
cana-2348	56	5	instances	instance	NOUN
cana-2348	56	6	,	,	PUNCT
cana-2348	56	7	encompassing	encompass	VERB
cana-2348	56	8	diverse	diverse	ADJ
cana-2348	56	9	demographic	demographic	ADJ
cana-2348	56	10	and	and	CCONJ
cana-2348	56	11	clinical	clinical	ADJ
cana-2348	56	12	profiles	profile	NOUN
cana-2348	56	13	.	.	PUNCT
cana-2348	57	1	the	the	DET
cana-2348	57	2	dataset	dataset	NOUN
cana-2348	57	3	incorporates	incorporate	VERB
cana-2348	57	4	the	the	DET
cana-2348	57	5	following	follow	VERB
cana-2348	57	6	features	feature	NOUN
cana-2348	57	7	.	.	PUNCT
cana-2348	58	1	1	1	X
cana-2348	58	2	.	.	X
cana-2348	58	3	age	age	NOUN
cana-2348	58	4	–	–	PUNCT
cana-2348	58	5	the	the	DET
cana-2348	58	6	age	age	NOUN
cana-2348	58	7	of	of	ADP
cana-2348	58	8	individuals	individual	NOUN
cana-2348	58	9	2.speech	2.speech	NUM
cana-2348	58	10	delay	delay	NOUN
cana-2348	58	11	/	/	SYM
cana-2348	58	12	language	language	NOUN
cana-2348	58	13	disorder(binary)-existence(1	disorder(binary)-existence(1	NOUN
cana-2348	58	14	)	)	PUNCT
cana-2348	58	15	or	or	CCONJ
cana-2348	58	16	lack(0	lack(0	PROPN
cana-2348	58	17	)	)	PUNCT
cana-2348	58	18	of	of	ADP
cana-2348	58	19	speech	speech	NOUN
cana-2348	58	20	delay	delay	NOUN
cana-2348	58	21	or	or	CCONJ
cana-2348	58	22	language	language	NOUN
cana-2348	58	23	disorder	disorder	NOUN
cana-2348	58	24	3	3	NUM
cana-2348	58	25	.	.	PUNCT
cana-2348	58	26	genetic	genetic	ADJ
cana-2348	58	27	disorder(binary	disorder(binary	PROPN
cana-2348	58	28	):	):	PUNCT
cana-2348	58	29	existence	existence	NOUN
cana-2348	58	30	(	(	PUNCT
cana-2348	58	31	1	1	NUM
cana-2348	58	32	)	)	PUNCT
cana-2348	58	33	or	or	CCONJ
cana-2348	58	34	lack	lack	NOUN
cana-2348	58	35	(	(	PUNCT
cana-2348	58	36	0	0	NUM
cana-2348	58	37	)	)	PUNCT
cana-2348	58	38	of	of	ADP
cana-2348	58	39	known	know	VERB
cana-2348	58	40	genetic	genetic	ADJ
cana-2348	58	41	disorders	disorder	NOUN
cana-2348	58	42	associated	associate	VERB
cana-2348	58	43	with	with	ADP
cana-2348	58	44	asd	asd	PROPN
cana-2348	58	45	.	.	PROPN
cana-2348	59	1	4	4	NUM
cana-2348	59	2	.	.	X
cana-2348	60	1	depression(binary	depression(binary	ADJ
cana-2348	60	2	):	):	PUNCT
cana-2348	60	3	existence	existence	NOUN
cana-2348	60	4	(	(	PUNCT
cana-2348	60	5	1	1	NUM
cana-2348	60	6	)	)	PUNCT
cana-2348	60	7	or	or	CCONJ
cana-2348	60	8	lack	lack	NOUN
cana-2348	60	9	(	(	PUNCT
cana-2348	60	10	0	0	NUM
cana-2348	60	11	)	)	PUNCT
cana-2348	60	12	of	of	ADP
cana-2348	60	13	depression	depression	NOUN
cana-2348	60	14	.	.	PUNCT
cana-2348	61	1	5	5	X
cana-2348	61	2	.	.	X
cana-2348	61	3	global	global	ADJ
cana-2348	61	4	developmental	developmental	ADJ
cana-2348	61	5	delay	delay	NOUN
cana-2348	61	6	/	/	SYM
cana-2348	61	7	intellectual	intellectual	ADJ
cana-2348	61	8	disability(binary	disability(binary	PROPN
cana-2348	61	9	):	):	PUNCT
cana-2348	61	10	existence	existence	NOUN
cana-2348	61	11	(	(	PUNCT
cana-2348	61	12	1	1	NUM
cana-2348	61	13	)	)	PUNCT
cana-2348	61	14	or	or	CCONJ
cana-2348	61	15	lack	lack	NOUN
cana-2348	61	16	(	(	PUNCT
cana-2348	61	17	0	0	NUM
cana-2348	61	18	)	)	PUNCT
cana-2348	61	19	of	of	ADP
cana-2348	61	20	global	global	ADJ
cana-2348	61	21	developmental	developmental	ADJ
cana-2348	61	22	delay	delay	NOUN
cana-2348	61	23	or	or	CCONJ
cana-2348	61	24	intellectual	intellectual	ADJ
cana-2348	61	25	disability	disability	NOUN
cana-2348	61	26	.	.	PUNCT
cana-2348	62	1	6	6	X
cana-2348	62	2	.	.	X
cana-2348	62	3	social	social	ADJ
cana-2348	62	4	/	/	SYM
cana-2348	62	5	behavioural	behavioural	ADJ
cana-2348	62	6	issues(binary	issues(binary	PROPN
cana-2348	62	7	):	):	PUNCT
cana-2348	62	8	existence	existence	NOUN
cana-2348	62	9	(	(	PUNCT
cana-2348	62	10	1	1	NUM
cana-2348	62	11	)	)	PUNCT
cana-2348	62	12	or	or	CCONJ
cana-2348	62	13	lack	lack	NOUN
cana-2348	62	14	(	(	PUNCT
cana-2348	62	15	0	0	NUM
cana-2348	62	16	)	)	PUNCT
cana-2348	62	17	of	of	ADP
cana-2348	62	18	social	social	ADJ
cana-2348	62	19	or	or	CCONJ
cana-2348	62	20	behavioral	behavioral	ADJ
cana-2348	62	21	issues	issue	NOUN
cana-2348	62	22	.	.	PUNCT
cana-2348	63	1	7	7	X
cana-2348	63	2	.	.	X
cana-2348	63	3	anxiety	anxiety	PROPN
cana-2348	63	4	disorder(binary	disorder(binary	PROPN
cana-2348	63	5	):	):	PUNCT
cana-2348	63	6	existence	existence	NOUN
cana-2348	63	7	(	(	PUNCT
cana-2348	63	8	1	1	NUM
cana-2348	63	9	)	)	PUNCT
cana-2348	63	10	or	or	CCONJ
cana-2348	63	11	lack	lack	NOUN
cana-2348	63	12	(	(	PUNCT
cana-2348	63	13	0	0	NUM
cana-2348	63	14	)	)	PUNCT
cana-2348	63	15	of	of	ADP
cana-2348	63	16	an	an	DET
cana-2348	63	17	anxiety	anxiety	NOUN
cana-2348	63	18	disorder	disorder	NOUN
cana-2348	63	19	.	.	PUNCT
cana-2348	64	1	8	8	X
cana-2348	64	2	.	.	X
cana-2348	65	1	sex(categorical	sex(categorical	X
cana-2348	65	2	):	):	PUNCT
cana-2348	65	3	gender	gender	NOUN
cana-2348	65	4	of	of	ADP
cana-2348	65	5	the	the	DET
cana-2348	65	6	individual	individual	ADJ
cana-2348	65	7	(	(	PUNCT
cana-2348	65	8	male	male	ADJ
cana-2348	65	9	,	,	PUNCT
cana-2348	65	10	female	female	NOUN
cana-2348	65	11	)	)	PUNCT
cana-2348	65	12	9	9	NUM
cana-2348	65	13	.	.	PUNCT
cana-2348	66	1	jaundice(binary	jaundice(binary	ADJ
cana-2348	66	2	):	):	PUNCT
cana-2348	66	3	existence	existence	NOUN
cana-2348	66	4	(	(	PUNCT
cana-2348	66	5	1	1	NUM
cana-2348	66	6	)	)	PUNCT
cana-2348	66	7	or	or	CCONJ
cana-2348	66	8	lack	lack	NOUN
cana-2348	66	9	(	(	PUNCT
cana-2348	66	10	0	0	NUM
cana-2348	66	11	)	)	PUNCT
cana-2348	66	12	of	of	ADP
cana-2348	66	13	jaundice	jaundice	NOUN
cana-2348	66	14	during	during	ADP
cana-2348	66	15	infancy	infancy	NOUN
cana-2348	66	16	.	.	PUNCT
cana-2348	67	1	10	10	NUM
cana-2348	67	2	.	.	PUNCT
cana-2348	67	3	family	family	NOUN
cana-2348	67	4	member	member	NOUN
cana-2348	67	5	with	with	ADP
cana-2348	67	6	asd(binary	asd(binary	ADJ
cana-2348	67	7	):	):	PUNCT
cana-2348	67	8	existence	existence	NOUN
cana-2348	67	9	(	(	PUNCT
cana-2348	67	10	1	1	NUM
cana-2348	67	11	)	)	PUNCT
cana-2348	67	12	or	or	CCONJ
cana-2348	67	13	lack	lack	NOUN
cana-2348	67	14	(	(	PUNCT
cana-2348	67	15	0	0	NUM
cana-2348	67	16	)	)	PUNCT
cana-2348	67	17	of	of	ADP
cana-2348	67	18	a	a	DET
cana-2348	67	19	family	family	NOUN
cana-2348	67	20	member	member	NOUN
cana-2348	67	21	diagnosed	diagnose	VERB
cana-2348	67	22	with	with	ADP
cana-2348	67	23	autism	autism	NOUN
cana-2348	67	24	.	.	PUNCT
cana-2348	68	1	most	most	ADJ
cana-2348	68	2	of	of	ADP
cana-2348	68	3	the	the	DET
cana-2348	68	4	features	feature	NOUN
cana-2348	68	5	are	be	AUX
cana-2348	68	6	binary	binary	ADJ
cana-2348	68	7	,	,	PUNCT
cana-2348	68	8	representing	represent	VERB
cana-2348	68	9	the	the	DET
cana-2348	68	10	existence	existence	NOUN
cana-2348	68	11	or	or	CCONJ
cana-2348	68	12	lack	lack	NOUN
cana-2348	68	13	of	of	ADP
cana-2348	68	14	specific	specific	ADJ
cana-2348	68	15	characteristics	characteristic	NOUN
cana-2348	68	16	.	.	PUNCT
cana-2348	69	1	communications	communication	NOUN
cana-2348	69	2	on	on	ADP
cana-2348	69	3	applied	apply	VERB
cana-2348	69	4	nonlinear	nonlinear	ADJ
cana-2348	69	5	analysis	analysis	NOUN
cana-2348	69	6	issn	issn	NOUN
cana-2348	69	7	:	:	PUNCT
cana-2348	69	8	1074	1074	NUM
cana-2348	69	9	-	-	PUNCT
cana-2348	69	10	133x	133x	NUM
cana-2348	69	11	vol	vol	NOUN
cana-2348	69	12	32	32	NUM
cana-2348	69	13	no	no	NOUN
cana-2348	69	14	.	.	NOUN
cana-2348	69	15	2	2	NUM
cana-2348	69	16	(	(	PUNCT
cana-2348	69	17	2025	2025	NUM
cana-2348	69	18	)	)	PUNCT
cana-2348	69	19	625	625	NUM
cana-2348	69	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	69	21	the	the	DET
cana-2348	69	22	dataset	dataset	NOUN
cana-2348	69	23	underwent	undergo	VERB
cana-2348	69	24	a	a	DET
cana-2348	69	25	number	number	NOUN
cana-2348	69	26	of	of	ADP
cana-2348	69	27	preparation	preparation	NOUN
cana-2348	69	28	processes	process	NOUN
cana-2348	69	29	before	before	SCONJ
cana-2348	69	30	the	the	DET
cana-2348	69	31	analysis	analysis	NOUN
cana-2348	69	32	started	start	VERB
cana-2348	69	33	to	to	PART
cana-2348	69	34	make	make	VERB
cana-2348	69	35	sure	sure	ADJ
cana-2348	69	36	it	it	PRON
cana-2348	69	37	was	be	AUX
cana-2348	69	38	suitable	suitable	ADJ
cana-2348	69	39	for	for	ADP
cana-2348	69	40	machine	machine	NOUN
cana-2348	69	41	learning	learn	VERB
cana-2348	69	42	applications	application	NOUN
cana-2348	69	43	.	.	PUNCT
cana-2348	70	1	table	table	NOUN
cana-2348	70	2	1	1	NUM
cana-2348	70	3	presents	present	VERB
cana-2348	70	4	a	a	DET
cana-2348	70	5	summary	summary	NOUN
cana-2348	70	6	of	of	ADP
cana-2348	70	7	the	the	DET
cana-2348	70	8	preprocessing	preprocessing	NOUN
cana-2348	70	9	steps	step	NOUN
cana-2348	70	10	applied	apply	VERB
cana-2348	70	11	to	to	ADP
cana-2348	70	12	the	the	DET
cana-2348	70	13	dataset	dataset	NOUN
cana-2348	70	14	and	and	CCONJ
cana-2348	70	15	the	the	DET
cana-2348	70	16	corresponding	corresponding	ADJ
cana-2348	70	17	results	result	NOUN
cana-2348	70	18	.	.	PUNCT
cana-2348	71	1	preprocessing	preprocesse	VERB
cana-2348	71	2	stage	stage	NOUN
cana-2348	71	3	dataset	dataset	NOUN
cana-2348	71	4	size	size	NOUN
cana-2348	71	5	features	feature	VERB
cana-2348	71	6	target	target	NOUN
cana-2348	71	7	encoding	encode	VERB
cana-2348	71	8	categorical	categorical	ADJ
cana-2348	71	9	encoding	encoding	NOUN
cana-2348	71	10	original	original	ADJ
cana-2348	71	11	dataset	dataset	NOUN
cana-2348	71	12	2000	2000	NUM
cana-2348	71	13	10	10	NUM
cana-2348	71	14	no	no	INTJ
cana-2348	71	15	no	no	INTJ
cana-2348	71	16	after	after	ADP
cana-2348	71	17	removing	remove	VERB
cana-2348	71	18	irrelevant	irrelevant	ADJ
cana-2348	71	19	features	feature	NOUN
cana-2348	71	20	2000	2000	NUM
cana-2348	71	21	8	8	NUM
cana-2348	71	22	no	no	INTJ
cana-2348	71	23	no	no	ADV
cana-2348	71	24	after	after	ADP
cana-2348	71	25	imputing	impute	VERB
cana-2348	71	26	missing	miss	VERB
cana-2348	71	27	values	value	NOUN
cana-2348	71	28	2000	2000	NUM
cana-2348	71	29	8	8	NUM
cana-2348	72	1	no	no	INTJ
cana-2348	72	2	no	no	INTJ
cana-2348	72	3	after	after	ADP
cana-2348	72	4	target	target	NOUN
cana-2348	72	5	variable	variable	NOUN
cana-2348	72	6	encoding	encode	VERB
cana-2348	72	7	2000	2000	NUM
cana-2348	72	8	8	8	NUM
cana-2348	73	1	yes	yes	INTJ
cana-2348	73	2	no	no	INTJ
cana-2348	73	3	after	after	ADP
cana-2348	73	4	one	one	NUM
cana-2348	73	5	-	-	PUNCT
cana-2348	73	6	hot	hot	ADJ
cana-2348	73	7	encoding	encoding	NOUN
cana-2348	73	8	of	of	ADP
cana-2348	73	9	categorical	categorical	ADJ
cana-2348	73	10	columns	column	NOUN
cana-2348	73	11	2000	2000	NUM
cana-2348	73	12	14	14	NUM
cana-2348	74	1	yes	yes	INTJ
cana-2348	74	2	yes	yes	INTJ
cana-2348	74	3	training	training	NOUN
cana-2348	74	4	set	set	VERB
cana-2348	74	5	1600	1600	NUM
cana-2348	74	6	14	14	NUM
cana-2348	75	1	yes	yes	INTJ
cana-2348	75	2	yes	yes	INTJ
cana-2348	76	1	testing	testing	NOUN
cana-2348	76	2	set	set	VERB
cana-2348	76	3	400	400	NUM
cana-2348	76	4	14	14	NUM
cana-2348	77	1	yes	yes	INTJ
cana-2348	78	1	yes	yes	INTJ
cana-2348	78	2	table	table	NOUN
cana-2348	78	3	1	1	NUM
cana-2348	78	4	:	:	PUNCT
cana-2348	78	5	dataset	dataset	ADJ
cana-2348	78	6	overview	overview	NOUN
cana-2348	78	7	at	at	ADP
cana-2348	78	8	various	various	ADJ
cana-2348	78	9	preprocessing	preprocessing	NOUN
cana-2348	78	10	steps	step	NOUN
cana-2348	78	11	in	in	ADP
cana-2348	78	12	this	this	DET
cana-2348	78	13	table	table	NOUN
cana-2348	78	14	,	,	PUNCT
cana-2348	78	15	•	•	DET
cana-2348	78	16	“	"	PUNCT
cana-2348	78	17	preprocessing	preprocesse	VERB
cana-2348	78	18	stage	stage	NOUN
cana-2348	78	19	”	"	PUNCT
cana-2348	78	20	describes	describe	VERB
cana-2348	78	21	the	the	DET
cana-2348	78	22	different	different	ADJ
cana-2348	78	23	stages	stage	NOUN
cana-2348	78	24	of	of	ADP
cana-2348	78	25	preprocessing	preprocesse	VERB
cana-2348	78	26	.	.	PUNCT
cana-2348	79	1	•	•	NUM
cana-2348	79	2	“	"	PUNCT
cana-2348	79	3	dataset	dataset	ADJ
cana-2348	79	4	size	size	NOUN
cana-2348	79	5	”	"	PUNCT
cana-2348	79	6	indicates	indicate	VERB
cana-2348	79	7	the	the	DET
cana-2348	79	8	number	number	NOUN
cana-2348	79	9	of	of	ADP
cana-2348	79	10	instances	instance	NOUN
cana-2348	79	11	in	in	ADP
cana-2348	79	12	the	the	DET
cana-2348	79	13	dataset	dataset	NOUN
cana-2348	79	14	at	at	ADP
cana-2348	79	15	each	each	DET
cana-2348	79	16	stage	stage	NOUN
cana-2348	79	17	.	.	PUNCT
cana-2348	80	1	•	•	NUM
cana-2348	80	2	“	"	PUNCT
cana-2348	80	3	features	feature	NOUN
cana-2348	80	4	”	"	PUNCT
cana-2348	80	5	represents	represent	VERB
cana-2348	80	6	the	the	DET
cana-2348	80	7	number	number	NOUN
cana-2348	80	8	of	of	ADP
cana-2348	80	9	features	feature	NOUN
cana-2348	80	10	remaining	remain	VERB
cana-2348	80	11	after	after	ADP
cana-2348	80	12	each	each	DET
cana-2348	80	13	pre	pre	ADJ
cana-2348	80	14	-	-	ADJ
cana-2348	80	15	processing	processing	ADJ
cana-2348	80	16	stage	stage	NOUN
cana-2348	80	17	.	.	PUNCT
cana-2348	81	1	•	•	NUM
cana-2348	81	2	“	"	PUNCT
cana-2348	81	3	target	target	NOUN
cana-2348	81	4	encoding	encoding	NOUN
cana-2348	81	5	”	"	PUNCT
cana-2348	81	6	specifies	specifie	NOUN
cana-2348	81	7	whether	whether	SCONJ
cana-2348	81	8	the	the	DET
cana-2348	81	9	target	target	NOUN
cana-2348	81	10	variable	variable	NOUN
cana-2348	81	11	has	have	AUX
cana-2348	81	12	been	be	AUX
cana-2348	81	13	encoded	encode	VERB
cana-2348	81	14	into	into	ADP
cana-2348	81	15	numerical	numerical	ADJ
cana-2348	81	16	format(yes	format(yes	PROPN
cana-2348	81	17	/	/	SYM
cana-2348	81	18	no	no	NOUN
cana-2348	81	19	)	)	PUNCT
cana-2348	81	20	•	•	NUM
cana-2348	81	21	“	"	PUNCT
cana-2348	81	22	categorical	categorical	ADJ
cana-2348	81	23	encoding	encoding	NOUN
cana-2348	81	24	”	"	PUNCT
cana-2348	81	25	indicates	indicate	VERB
cana-2348	81	26	whether	whether	SCONJ
cana-2348	81	27	categorical	categorical	ADJ
cana-2348	81	28	variables	variable	NOUN
cana-2348	81	29	have	have	AUX
cana-2348	81	30	been	be	AUX
cana-2348	81	31	encoded	encode	VERB
cana-2348	81	32	using	use	VERB
cana-2348	81	33	one	one	NUM
cana-2348	81	34	-	-	PUNCT
cana-2348	81	35	hot	hot	ADJ
cana-2348	81	36	encoding(yes	encoding(ye	NOUN
cana-2348	81	37	/	/	SYM
cana-2348	81	38	no	no	NOUN
cana-2348	81	39	)	)	PUNCT
cana-2348	81	40	a	a	DET
cana-2348	81	41	preliminary	preliminary	ADJ
cana-2348	81	42	examination	examination	NOUN
cana-2348	81	43	revealed	reveal	VERB
cana-2348	81	44	minimal	minimal	ADJ
cana-2348	81	45	missing	missing	ADJ
cana-2348	81	46	values	value	NOUN
cana-2348	81	47	and	and	CCONJ
cana-2348	81	48	imputation	imputation	NOUN
cana-2348	81	49	techniques	technique	NOUN
cana-2348	81	50	were	be	AUX
cana-2348	81	51	applied	apply	VERB
cana-2348	81	52	for	for	ADP
cana-2348	81	53	handling	handle	VERB
cana-2348	81	54	them	they	PRON
cana-2348	81	55	.	.	PUNCT
cana-2348	82	1	to	to	PART
cana-2348	82	2	facilitate	facilitate	VERB
cana-2348	82	3	the	the	DET
cana-2348	82	4	training	training	NOUN
cana-2348	82	5	of	of	ADP
cana-2348	82	6	machine	machine	NOUN
cana-2348	82	7	learning	learning	NOUN
cana-2348	82	8	models	model	NOUN
cana-2348	82	9	,	,	PUNCT
cana-2348	82	10	the	the	DET
cana-2348	82	11	target	target	NOUN
cana-2348	82	12	variable	variable	ADJ
cana-2348	82	13	'	'	PUNCT
cana-2348	82	14	autism	autism	NOUN
cana-2348	82	15	'	'	PUNCT
cana-2348	82	16	was	be	AUX
cana-2348	82	17	encoded	encode	VERB
cana-2348	82	18	into	into	ADP
cana-2348	82	19	a	a	DET
cana-2348	82	20	numerical	numerical	ADJ
cana-2348	82	21	format	format	NOUN
cana-2348	82	22	using	use	VERB
cana-2348	82	23	label	label	NOUN
cana-2348	82	24	encoding	encoding	NOUN
cana-2348	82	25	.	.	PUNCT
cana-2348	83	1	this	this	DET
cana-2348	83	2	transformation	transformation	NOUN
cana-2348	83	3	replaced	replace	VERB
cana-2348	83	4	'	'	PUNCT
cana-2348	83	5	yes	yes	INTJ
cana-2348	83	6	'	'	PUNCT
cana-2348	83	7	with	with	ADP
cana-2348	83	8	1	1	NUM
cana-2348	83	9	and	and	CCONJ
cana-2348	83	10	'	'	PUNCT
cana-2348	83	11	no	no	INTJ
cana-2348	83	12	'	'	PUNCT
cana-2348	83	13	with	with	ADP
cana-2348	83	14	0	0	NUM
cana-2348	83	15	.	.	PUNCT
cana-2348	84	1	categorical	categorical	ADJ
cana-2348	84	2	variables	variable	NOUN
cana-2348	84	3	in	in	ADP
cana-2348	84	4	the	the	DET
cana-2348	84	5	feature	feature	NOUN
cana-2348	84	6	set	set	NOUN
cana-2348	84	7	were	be	AUX
cana-2348	84	8	subjected	subject	VERB
cana-2348	84	9	to	to	ADP
cana-2348	84	10	one	one	NUM
cana-2348	84	11	-	-	PUNCT
cana-2348	84	12	hot	hot	ADJ
cana-2348	84	13	encoding	encoding	NOUN
cana-2348	84	14	.	.	PUNCT
cana-2348	85	1	this	this	DET
cana-2348	85	2	technique	technique	NOUN
cana-2348	85	3	creates	create	VERB
cana-2348	85	4	binary	binary	ADJ
cana-2348	85	5	vectors	vector	NOUN
cana-2348	85	6	for	for	ADP
cana-2348	85	7	each	each	DET
cana-2348	85	8	category	category	NOUN
cana-2348	85	9	,	,	PUNCT
cana-2348	85	10	ensuring	ensure	VERB
cana-2348	85	11	compatibility	compatibility	NOUN
cana-2348	85	12	with	with	ADP
cana-2348	85	13	the	the	DET
cana-2348	85	14	deep	deep	ADJ
cana-2348	85	15	learning	learning	NOUN
cana-2348	85	16	model	model	NOUN
cana-2348	85	17	.	.	PUNCT
cana-2348	86	1	the	the	DET
cana-2348	86	2	dataset	dataset	NOUN
cana-2348	86	3	was	be	AUX
cana-2348	86	4	partitioned	partition	VERB
cana-2348	86	5	randomly	randomly	ADV
cana-2348	86	6	into	into	ADP
cana-2348	86	7	training	training	NOUN
cana-2348	86	8	(	(	PUNCT
cana-2348	86	9	80	80	NUM
cana-2348	86	10	%	%	NOUN
cana-2348	86	11	)	)	PUNCT
cana-2348	86	12	and	and	CCONJ
cana-2348	86	13	testing	testing	NOUN
cana-2348	86	14	(	(	PUNCT
cana-2348	86	15	20	20	NUM
cana-2348	86	16	%	%	NOUN
cana-2348	86	17	)	)	PUNCT
cana-2348	86	18	sets	set	NOUN
cana-2348	86	19	.	.	PUNCT
cana-2348	87	1	iv.model	iv.model	NOUN
cana-2348	87	2	architecture	architecture	NOUN
cana-2348	87	3	deep	deep	ADJ
cana-2348	87	4	learning	learning	NOUN
cana-2348	87	5	,	,	PUNCT
cana-2348	87	6	a	a	DET
cana-2348	87	7	method	method	NOUN
cana-2348	87	8	within	within	ADP
cana-2348	87	9	machine	machine	NOUN
cana-2348	87	10	learning	learning	NOUN
cana-2348	87	11	,	,	PUNCT
cana-2348	87	12	has	have	AUX
cana-2348	87	13	garnered	garner	VERB
cana-2348	87	14	considerable	considerable	ADJ
cana-2348	87	15	attention	attention	NOUN
cana-2348	87	16	[	[	X
cana-2348	87	17	10	10	NUM
cana-2348	87	18	]	]	PUNCT
cana-2348	87	19	.	.	PUNCT
cana-2348	88	1	it	it	PRON
cana-2348	88	2	excels	excel	VERB
cana-2348	88	3	in	in	ADP
cana-2348	88	4	predicting	predict	VERB
cana-2348	88	5	models	model	NOUN
cana-2348	88	6	with	with	ADP
cana-2348	88	7	high	high	ADJ
cana-2348	88	8	complexity	complexity	NOUN
cana-2348	88	9	and	and	CCONJ
cana-2348	88	10	finds	find	VERB
cana-2348	88	11	application	application	NOUN
cana-2348	88	12	across	across	ADP
cana-2348	88	13	various	various	ADJ
cana-2348	88	14	domains	domain	NOUN
cana-2348	88	15	.	.	PUNCT
cana-2348	89	1	[	[	X
cana-2348	89	2	11	11	NUM
cana-2348	89	3	]	]	PUNCT
cana-2348	89	4	.	.	PUNCT
cana-2348	90	1	three	three	NUM
cana-2348	90	2	deep	deep	ADJ
cana-2348	90	3	learning	learning	NOUN
cana-2348	90	4	architectures	architecture	NOUN
cana-2348	90	5	were	be	AUX
cana-2348	90	6	implemented	implement	VERB
cana-2348	90	7	and	and	CCONJ
cana-2348	90	8	compared	compare	VERB
cana-2348	90	9	:	:	PUNCT
cana-2348	90	10	recurrent	recurrent	ADJ
cana-2348	90	11	neural	neural	ADJ
cana-2348	90	12	network(rnn	network(rnn	NOUN
cana-2348	90	13	)	)	PUNCT
cana-2348	90	14	,	,	PUNCT
cana-2348	90	15	long	long	ADJ
cana-2348	90	16	short	short	ADJ
cana-2348	90	17	term	term	NOUN
cana-2348	90	18	memory(lstm	memory(lstm	PROPN
cana-2348	90	19	)	)	PUNCT
cana-2348	90	20	,	,	PUNCT
cana-2348	90	21	and	and	CCONJ
cana-2348	90	22	gated	gate	VERB
cana-2348	90	23	recurrent	recurrent	ADJ
cana-2348	90	24	unit(gru	unit(gru	NOUN
cana-2348	90	25	)	)	PUNCT
cana-2348	90	26	.	.	PUNCT
cana-2348	91	1	each	each	DET
cana-2348	91	2	model	model	NOUN
cana-2348	91	3	comprised	comprise	VERB
cana-2348	91	4	initial	initial	ADJ
cana-2348	91	5	layers	layer	NOUN
cana-2348	91	6	for	for	ADP
cana-2348	91	7	capturing	capture	VERB
cana-2348	91	8	sequential	sequential	ADJ
cana-2348	91	9	dependencies	dependency	NOUN
cana-2348	91	10	,	,	PUNCT
cana-2348	91	11	followed	follow	VERB
cana-2348	91	12	by	by	ADP
cana-2348	91	13	dense	dense	ADJ
cana-2348	91	14	layers	layer	NOUN
cana-2348	91	15	to	to	PART
cana-2348	91	16	learn	learn	VERB
cana-2348	91	17	complex	complex	ADJ
cana-2348	91	18	patterns	pattern	NOUN
cana-2348	91	19	.	.	PUNCT
cana-2348	92	1	batch	batch	NOUN
cana-2348	92	2	normalization	normalization	NOUN
cana-2348	92	3	and	and	CCONJ
cana-2348	92	4	dropout	dropout	NOUN
cana-2348	92	5	layers	layer	NOUN
cana-2348	92	6	were	be	AUX
cana-2348	92	7	introduced	introduce	VERB
cana-2348	92	8	to	to	PART
cana-2348	92	9	mitigate	mitigate	VERB
cana-2348	92	10	overfitting	overfitting	NOUN
cana-2348	92	11	and	and	CCONJ
cana-2348	92	12	enhance	enhance	VERB
cana-2348	92	13	model	model	NOUN
cana-2348	92	14	performance	performance	NOUN
cana-2348	92	15	.	.	PUNCT
cana-2348	93	1	the	the	DET
cana-2348	93	2	models	model	NOUN
cana-2348	93	3	underwent	undergo	VERB
cana-2348	93	4	training	training	NOUN
cana-2348	93	5	using	use	VERB
cana-2348	93	6	the	the	DET
cana-2348	93	7	training	training	NOUN
cana-2348	93	8	data	datum	NOUN
cana-2348	93	9	,	,	PUNCT
cana-2348	93	10	and	and	CCONJ
cana-2348	93	11	their	their	PRON
cana-2348	93	12	performance	performance	NOUN
cana-2348	93	13	was	be	AUX
cana-2348	93	14	assessed	assess	VERB
cana-2348	93	15	on	on	ADP
cana-2348	93	16	the	the	DET
cana-2348	93	17	validation	validation	NOUN
cana-2348	93	18	data	datum	NOUN
cana-2348	93	19	.	.	PUNCT
cana-2348	94	1	training	training	NOUN
cana-2348	94	2	parameters	parameter	NOUN
cana-2348	94	3	,	,	PUNCT
cana-2348	94	4	including	include	VERB
cana-2348	94	5	the	the	DET
cana-2348	94	6	number	number	NOUN
cana-2348	94	7	of	of	ADP
cana-2348	94	8	communications	communication	NOUN
cana-2348	94	9	on	on	ADP
cana-2348	94	10	applied	apply	VERB
cana-2348	94	11	nonlinear	nonlinear	ADJ
cana-2348	94	12	analysis	analysis	NOUN
cana-2348	94	13	issn	issn	NOUN
cana-2348	94	14	:	:	PUNCT
cana-2348	94	15	1074	1074	NUM
cana-2348	94	16	-	-	PUNCT
cana-2348	94	17	133x	133x	NUM
cana-2348	94	18	vol	vol	NOUN
cana-2348	94	19	32	32	NUM
cana-2348	94	20	no	no	NOUN
cana-2348	94	21	.	.	NOUN
cana-2348	94	22	2	2	NUM
cana-2348	94	23	(	(	PUNCT
cana-2348	94	24	2025	2025	NUM
cana-2348	94	25	)	)	PUNCT
cana-2348	94	26	626	626	NUM
cana-2348	94	27	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	94	28	epochs	epoch	NOUN
cana-2348	94	29	,	,	PUNCT
cana-2348	94	30	batch	batch	NOUN
cana-2348	94	31	size	size	NOUN
cana-2348	94	32	,	,	PUNCT
cana-2348	94	33	and	and	CCONJ
cana-2348	94	34	optimizer	optimizer	NOUN
cana-2348	94	35	configurations	configuration	NOUN
cana-2348	94	36	,	,	PUNCT
cana-2348	94	37	were	be	AUX
cana-2348	94	38	fine	fine	ADV
cana-2348	94	39	-	-	PUNCT
cana-2348	94	40	tuned	tune	VERB
cana-2348	94	41	for	for	ADP
cana-2348	94	42	each	each	DET
cana-2348	94	43	architecture	architecture	NOUN
cana-2348	94	44	.	.	PUNCT
cana-2348	95	1	accuracy	accuracy	NOUN
cana-2348	95	2	,	,	PUNCT
cana-2348	95	3	f1	f1	NOUN
cana-2348	95	4	score	score	NOUN
cana-2348	95	5	,	,	PUNCT
cana-2348	95	6	and	and	CCONJ
cana-2348	95	7	precision	precision	NOUN
cana-2348	95	8	were	be	AUX
cana-2348	95	9	tracked	track	VERB
cana-2348	95	10	during	during	ADP
cana-2348	95	11	training	training	NOUN
cana-2348	95	12	to	to	PART
cana-2348	95	13	monitor	monitor	VERB
cana-2348	95	14	model	model	NOUN
cana-2348	95	15	convergence	convergence	NOUN
cana-2348	95	16	and	and	CCONJ
cana-2348	95	17	performance	performance	NOUN
cana-2348	95	18	.	.	PUNCT
cana-2348	96	1	figure	figure	NOUN
cana-2348	96	2	1	1	NUM
cana-2348	96	3	:	:	PUNCT
cana-2348	96	4	model	model	NOUN
cana-2348	96	5	architecture	architecture	NOUN
cana-2348	96	6	1	1	NUM
cana-2348	96	7	.	.	PUNCT
cana-2348	96	8	recurrent	recurrent	ADJ
cana-2348	96	9	neural	neural	ADJ
cana-2348	96	10	network	network	NOUN
cana-2348	96	11	(	(	PUNCT
cana-2348	96	12	rnn	rnn	PROPN
cana-2348	96	13	):	):	PUNCT
cana-2348	96	14	in	in	ADP
cana-2348	96	15	simpler	simple	ADJ
cana-2348	96	16	terms	term	NOUN
cana-2348	96	17	,	,	PUNCT
cana-2348	96	18	recurrent	recurrent	ADJ
cana-2348	96	19	neural	neural	ADJ
cana-2348	96	20	networks	network	NOUN
cana-2348	96	21	(	(	PUNCT
cana-2348	96	22	rnns	rnns	PROPN
cana-2348	96	23	)	)	PUNCT
cana-2348	96	24	are	be	AUX
cana-2348	96	25	structured	structure	VERB
cana-2348	96	26	to	to	PART
cana-2348	96	27	interpret	interpret	VERB
cana-2348	96	28	sequential	sequential	ADJ
cana-2348	96	29	data	datum	NOUN
cana-2348	96	30	by	by	ADP
cana-2348	96	31	allowing	allow	VERB
cana-2348	96	32	information	information	NOUN
cana-2348	96	33	to	to	PART
cana-2348	96	34	flow	flow	VERB
cana-2348	96	35	not	not	PART
cana-2348	96	36	just	just	ADV
cana-2348	96	37	forward	forward	ADV
cana-2348	96	38	but	but	CCONJ
cana-2348	96	39	also	also	ADV
cana-2348	96	40	backward	backward	ADJ
cana-2348	96	41	through	through	ADP
cana-2348	96	42	the	the	DET
cana-2348	96	43	network	network	NOUN
cana-2348	96	44	.	.	PUNCT
cana-2348	97	1	this	this	PRON
cana-2348	97	2	is	be	AUX
cana-2348	97	3	achieved	achieve	VERB
cana-2348	97	4	through	through	ADP
cana-2348	97	5	loops	loop	NOUN
cana-2348	97	6	within	within	ADP
cana-2348	97	7	the	the	DET
cana-2348	97	8	network	network	NOUN
cana-2348	97	9	that	that	PRON
cana-2348	97	10	connect	connect	VERB
cana-2348	97	11	hidden	hidden	ADJ
cana-2348	97	12	units	unit	NOUN
cana-2348	97	13	.	.	PUNCT
cana-2348	98	1	the	the	DET
cana-2348	98	2	internal	internal	ADJ
cana-2348	98	3	connections	connection	NOUN
cana-2348	98	4	facilitate	facilitate	NOUN
cana-2348	98	5	rnns	rnn	NOUN
cana-2348	98	6	in	in	ADP
cana-2348	98	7	efficiently	efficiently	ADV
cana-2348	98	8	leveraging	leverage	VERB
cana-2348	98	9	previous	previous	ADJ
cana-2348	98	10	information	information	NOUN
cana-2348	98	11	to	to	PART
cana-2348	98	12	anticipate	anticipate	VERB
cana-2348	98	13	future	future	ADJ
cana-2348	98	14	outcomes	outcome	NOUN
cana-2348	98	15	,	,	PUNCT
cana-2348	98	16	making	make	VERB
cana-2348	98	17	them	they	PRON
cana-2348	98	18	adept	adept	ADJ
cana-2348	98	19	at	at	ADP
cana-2348	98	20	recognizing	recognize	VERB
cana-2348	98	21	patterns	pattern	NOUN
cana-2348	98	22	in	in	ADP
cana-2348	98	23	sequential	sequential	ADJ
cana-2348	98	24	data	datum	NOUN
cana-2348	98	25	.	.	PUNCT
cana-2348	99	1	specifically	specifically	ADV
cana-2348	99	2	,	,	PUNCT
cana-2348	99	3	rnns	rnn	NOUN
cana-2348	99	4	excel	excel	VERB
cana-2348	99	5	at	at	ADP
cana-2348	99	6	capturing	capture	VERB
cana-2348	99	7	temporal	temporal	ADJ
cana-2348	99	8	dependencies	dependency	NOUN
cana-2348	99	9	between	between	ADP
cana-2348	99	10	data	datum	NOUN
cana-2348	99	11	points	point	NOUN
cana-2348	99	12	that	that	PRON
cana-2348	99	13	might	might	AUX
cana-2348	99	14	be	be	AUX
cana-2348	99	15	widely	widely	ADV
cana-2348	99	16	spaced	space	VERB
cana-2348	99	17	apart	apart	ADV
cana-2348	99	18	in	in	ADP
cana-2348	99	19	a	a	DET
cana-2348	99	20	sequence	sequence	NOUN
cana-2348	99	21	.	.	PUNCT
cana-2348	100	1	this	this	DET
cana-2348	100	2	ability	ability	NOUN
cana-2348	100	3	to	to	PART
cana-2348	100	4	grasp	grasp	VERB
cana-2348	100	5	long	long	ADJ
cana-2348	100	6	-	-	PUNCT
cana-2348	100	7	range	range	NOUN
cana-2348	100	8	relationships	relationship	NOUN
cana-2348	100	9	is	be	AUX
cana-2348	100	10	crucial	crucial	ADJ
cana-2348	100	11	for	for	ADP
cana-2348	100	12	tasks	task	NOUN
cana-2348	100	13	like	like	ADP
cana-2348	100	14	time	time	NOUN
cana-2348	100	15	series	series	PROPN
cana-2348	100	16	forecasting	forecasting	PROPN
cana-2348	100	17	,	,	PUNCT
cana-2348	100	18	language	language	NOUN
cana-2348	100	19	translation	translation	NOUN
cana-2348	100	20	,	,	PUNCT
cana-2348	100	21	and	and	CCONJ
cana-2348	100	22	speech	speech	NOUN
cana-2348	100	23	recognition	recognition	NOUN
cana-2348	100	24	.	.	PUNCT
cana-2348	101	1	figure	figure	NOUN
cana-2348	101	2	2	2	NUM
cana-2348	101	3	:	:	PUNCT
cana-2348	101	4	rnn	rnn	VERB
cana-2348	101	5	architecture	architecture	NOUN
cana-2348	101	6	asd	asd	NOUN
cana-2348	101	7	dataset	dataset	VERB
cana-2348	101	8	data	datum	NOUN
cana-2348	101	9	preprocessing	preprocesse	VERB
cana-2348	101	10	splitting	splitting	NOUN
cana-2348	101	11	data	datum	NOUN
cana-2348	101	12	build	build	VERB
cana-2348	101	13	an	an	DET
cana-2348	101	14	rnnbased	rnnbase	VERB
cana-2348	101	15	prediction	prediction	NOUN
cana-2348	101	16	model	model	NOUN
cana-2348	101	17	evaluate	evaluate	VERB
cana-2348	101	18	performance	performance	NOUN
cana-2348	101	19	and	and	CCONJ
cana-2348	101	20	analysis	analysis	NOUN
cana-2348	101	21	build	build	VERB
cana-2348	101	22	an	an	DET
cana-2348	101	23	lstmbased	lstmbase	VERB
cana-2348	101	24	prediction	prediction	NOUN
cana-2348	101	25	model	model	NOUN
cana-2348	101	26	build	build	PROPN
cana-2348	101	27	gru	gru	PROPN
cana-2348	101	28	based	base	VERB
cana-2348	101	29	prediction	prediction	NOUN
cana-2348	101	30	model	model	NOUN
cana-2348	101	31	communications	communication	NOUN
cana-2348	101	32	on	on	ADP
cana-2348	101	33	applied	apply	VERB
cana-2348	101	34	nonlinear	nonlinear	ADJ
cana-2348	101	35	analysis	analysis	NOUN
cana-2348	101	36	issn	issn	NOUN
cana-2348	101	37	:	:	PUNCT
cana-2348	101	38	1074	1074	NUM
cana-2348	101	39	-	-	PUNCT
cana-2348	101	40	133x	133x	NUM
cana-2348	101	41	vol	vol	NOUN
cana-2348	101	42	32	32	NUM
cana-2348	101	43	no	no	NOUN
cana-2348	101	44	.	.	NOUN
cana-2348	101	45	2	2	NUM
cana-2348	101	46	(	(	PUNCT
cana-2348	101	47	2025	2025	NUM
cana-2348	101	48	)	)	PUNCT
cana-2348	101	49	627	627	NUM
cana-2348	101	50	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	101	51	figure	figure	NOUN
cana-2348	101	52	1	1	NUM
cana-2348	101	53	illustrates	illustrate	VERB
cana-2348	101	54	the	the	DET
cana-2348	101	55	rnn	rnn	NOUN
cana-2348	101	56	architecture	architecture	NOUN
cana-2348	101	57	where	where	SCONJ
cana-2348	101	58	given	give	VERB
cana-2348	101	59	an	an	DET
cana-2348	101	60	input	input	NOUN
cana-2348	101	61	series	series	NOUN
cana-2348	101	62	𝑥	𝑥	PROPN
cana-2348	101	63	=	=	SYM
cana-2348	101	64	{	{	PUNCT
cana-2348	101	65	𝑥1	𝑥1	NOUN
cana-2348	101	66	,	,	PUNCT
cana-2348	101	67	𝑥2	𝑥2	NOUN
cana-2348	101	68	,	,	PUNCT
cana-2348	101	69	…	…	PUNCT
cana-2348	101	70	.	.	PUNCT
cana-2348	102	1	𝑥𝑇	𝑥𝑇	NOUN
cana-2348	102	2	}	}	PUNCT
cana-2348	102	3	,	,	PUNCT
cana-2348	102	4	the	the	DET
cana-2348	102	5	rnn	rnn	NOUN
cana-2348	102	6	iteratively	iteratively	ADV
cana-2348	102	7	computes	compute	VERB
cana-2348	102	8	the	the	DET
cana-2348	102	9	hidden	hidden	ADJ
cana-2348	102	10	state	state	NOUN
cana-2348	102	11	sequence	sequence	NOUN
cana-2348	102	12	ℎ	ℎ	X
cana-2348	102	13	=	=	SYM
cana-2348	102	14	{	{	PUNCT
cana-2348	102	15	ℎ1	ℎ1	PROPN
cana-2348	102	16	,	,	PUNCT
cana-2348	102	17	ℎ2	ℎ2	NOUN
cana-2348	102	18	,	,	PUNCT
cana-2348	102	19	…	…	PUNCT
cana-2348	102	20	,	,	PUNCT
cana-2348	102	21	ℎ𝑇	ℎ𝑇	NOUN
cana-2348	102	22	}	}	PUNCT
cana-2348	102	23	and	and	CCONJ
cana-2348	102	24	the	the	DET
cana-2348	102	25	output	output	NOUN
cana-2348	102	26	sequence	sequence	NOUN
cana-2348	102	27	𝑦	𝑦	NOUN
cana-2348	102	28	=	=	SYM
cana-2348	102	29	{	{	PUNCT
cana-2348	102	30	𝑦1	𝑦1	PROPN
cana-2348	102	31	,	,	PUNCT
cana-2348	102	32	𝑦2	𝑦2	NOUN
cana-2348	102	33	,	,	PUNCT
cana-2348	102	34	…	…	PUNCT
cana-2348	102	35	,	,	PUNCT
cana-2348	102	36	𝑦𝑇	𝑦𝑇	NOUN
cana-2348	102	37	}	}	PUNCT
cana-2348	102	38	using	use	VERB
cana-2348	102	39	the	the	DET
cana-2348	102	40	below	below	ADJ
cana-2348	102	41	equations	equation	NOUN
cana-2348	102	42	.	.	PUNCT
cana-2348	103	1	ℎ𝑡	ℎ𝑡	NOUN
cana-2348	103	2	=	=	SYM
cana-2348	103	3	𝑓(ℎ𝑡	𝑓(ℎ𝑡	NOUN
cana-2348	103	4	=	=	SYM
cana-2348	103	5	𝑓(𝑌ℎ𝑥𝑥𝑡	𝑓(𝑌ℎ𝑥𝑥𝑡	NOUN
cana-2348	103	6	+	+	CCONJ
cana-2348	103	7	𝑌ℎℎℎ𝑡	𝑌ℎℎℎ𝑡	PROPN
cana-2348	103	8	−	−	PROPN
cana-2348	103	9	1	1	NUM
cana-2348	103	10	+	+	NUM
cana-2348	103	11	𝑐ℎ)---(1	𝑐ℎ)---(1	NOUN
cana-2348	103	12	)	)	PUNCT
cana-2348	103	13	yt	yt	PROPN
cana-2348	103	14	=	=	NOUN
cana-2348	103	15	g(yyhht+cy)-----------(2	g(yyhht+cy)-----------(2	NOUN
cana-2348	103	16	)	)	PUNCT
cana-2348	103	17	here	here	ADV
cana-2348	103	18	yhx	yhx	NOUN
cana-2348	103	19	,	,	PUNCT
cana-2348	103	20	yhh	yhh	NOUN
cana-2348	103	21	,	,	PUNCT
cana-2348	103	22	and	and	CCONJ
cana-2348	103	23	yyh	yyh	PROPN
cana-2348	103	24	represent	represent	VERB
cana-2348	103	25	the	the	DET
cana-2348	103	26	input	input	NOUN
cana-2348	103	27	-	-	PUNCT
cana-2348	103	28	hidden	hide	VERB
cana-2348	103	29	weight	weight	NOUN
cana-2348	103	30	matrix	matrix	NOUN
cana-2348	103	31	,	,	PUNCT
cana-2348	103	32	hidden	hide	VERB
cana-2348	103	33	-	-	PUNCT
cana-2348	103	34	hidden	hide	VERB
cana-2348	103	35	weight	weight	NOUN
cana-2348	103	36	matrix	matrix	NOUN
cana-2348	103	37	,	,	PUNCT
cana-2348	103	38	and	and	CCONJ
cana-2348	103	39	hidden	hide	VERB
cana-2348	103	40	-	-	PUNCT
cana-2348	103	41	output	output	NOUN
cana-2348	103	42	weight	weight	NOUN
cana-2348	103	43	matrix	matrix	NOUN
cana-2348	103	44	.	.	PUNCT
cana-2348	104	1	the	the	DET
cana-2348	104	2	ch	ch	NOUN
cana-2348	104	3	,	,	PUNCT
cana-2348	104	4	cy	cy	AUX
cana-2348	104	5	denote	denote	VERB
cana-2348	104	6	the	the	DET
cana-2348	104	7	biases	bias	NOUN
cana-2348	104	8	of	of	ADP
cana-2348	104	9	the	the	DET
cana-2348	104	10	hidden	hide	VERB
cana-2348	104	11	layer	layer	NOUN
cana-2348	104	12	and	and	CCONJ
cana-2348	104	13	the	the	DET
cana-2348	104	14	output	output	NOUN
cana-2348	104	15	layer	layer	NOUN
cana-2348	104	16	,	,	PUNCT
cana-2348	104	17	respectively	respectively	ADV
cana-2348	104	18	.	.	PUNCT
cana-2348	105	1	further	far	ADV
cana-2348	105	2	,	,	PUNCT
cana-2348	105	3	the	the	DET
cana-2348	105	4	activation	activation	NOUN
cana-2348	105	5	functions	function	NOUN
cana-2348	105	6	for	for	ADP
cana-2348	105	7	the	the	DET
cana-2348	105	8	output	output	NOUN
cana-2348	105	9	layer	layer	NOUN
cana-2348	105	10	and	and	CCONJ
cana-2348	105	11	the	the	DET
cana-2348	105	12	hidden	hide	VERB
cana-2348	105	13	layer	layer	NOUN
cana-2348	105	14	are	be	AUX
cana-2348	105	15	g	g	PROPN
cana-2348	105	16	(	(	PUNCT
cana-2348	105	17	.	.	PUNCT
cana-2348	105	18	)	)	PUNCT
cana-2348	106	1	and	and	CCONJ
cana-2348	106	2	f	f	X
cana-2348	106	3	(	(	PUNCT
cana-2348	106	4	.	.	PUNCT
cana-2348	106	5	)	)	PUNCT
cana-2348	106	6	respectively	respectively	ADV
cana-2348	106	7	.	.	PUNCT
cana-2348	107	1	.the	.the	PRON
cana-2348	107	2	recurrent	recurrent	ADJ
cana-2348	107	3	neural	neural	ADJ
cana-2348	107	4	network	network	NOUN
cana-2348	107	5	utilizes	utilize	VERB
cana-2348	107	6	hidden	hide	VERB
cana-2348	107	7	state	state	NOUN
cana-2348	107	8	ℎ𝑇	ℎ𝑇	NOUN
cana-2348	107	9	at	at	ADP
cana-2348	107	10	timestep	timestep	NOUN
cana-2348	107	11	t	t	NOUN
cana-2348	107	12	to	to	PART
cana-2348	107	13	retain	retain	VERB
cana-2348	107	14	information	information	NOUN
cana-2348	107	15	from	from	ADP
cana-2348	107	16	previous	previous	ADJ
cana-2348	107	17	time	time	NOUN
cana-2348	107	18	steps	step	NOUN
cana-2348	107	19	,	,	PUNCT
cana-2348	107	20	capturing	capture	VERB
cana-2348	107	21	all	all	DET
cana-2348	107	22	relevant	relevant	ADJ
cana-2348	107	23	information	information	NOUN
cana-2348	107	24	contained	contain	VERB
cana-2348	107	25	within	within	ADP
cana-2348	107	26	each	each	DET
cana-2348	107	27	preceding	precede	VERB
cana-2348	107	28	time	time	NOUN
cana-2348	107	29	step	step	NOUN
cana-2348	107	30	.	.	PUNCT
cana-2348	108	1	2	2	X
cana-2348	108	2	.	.	X
cana-2348	108	3	long	long	ADJ
cana-2348	108	4	short	short	ADJ
cana-2348	108	5	-	-	PUNCT
cana-2348	108	6	term	term	NOUN
cana-2348	108	7	memory(lstm	memory(lstm	PROPN
cana-2348	108	8	):	):	PUNCT
cana-2348	108	9	the	the	DET
cana-2348	108	10	long	long	ADJ
cana-2348	108	11	short	short	ADJ
cana-2348	108	12	-	-	PUNCT
cana-2348	108	13	term	term	NOUN
cana-2348	108	14	memory	memory	NOUN
cana-2348	108	15	architecture	architecture	NOUN
cana-2348	108	16	was	be	AUX
cana-2348	108	17	selected	select	VERB
cana-2348	108	18	to	to	PART
cana-2348	108	19	tackle	tackle	VERB
cana-2348	108	20	the	the	DET
cana-2348	108	21	issue	issue	NOUN
cana-2348	108	22	of	of	ADP
cana-2348	108	23	vanishing	vanish	VERB
cana-2348	108	24	gradients	gradient	NOUN
cana-2348	108	25	and	and	CCONJ
cana-2348	108	26	accurately	accurately	ADV
cana-2348	108	27	model	model	VERB
cana-2348	108	28	long	long	ADJ
cana-2348	108	29	-	-	PUNCT
cana-2348	108	30	term	term	NOUN
cana-2348	108	31	relationships	relationship	NOUN
cana-2348	108	32	within	within	ADP
cana-2348	108	33	the	the	DET
cana-2348	108	34	dataset	dataset	NOUN
cana-2348	108	35	.	.	PUNCT
cana-2348	109	1	the	the	DET
cana-2348	109	2	model	model	NOUN
cana-2348	109	3	architecture	architecture	NOUN
cana-2348	109	4	featured	feature	VERB
cana-2348	109	5	a	a	DET
cana-2348	109	6	single	single	ADJ
cana-2348	109	7	lstm	lstm	NOUN
cana-2348	109	8	layer	layer	NOUN
cana-2348	109	9	with	with	ADP
cana-2348	109	10	64	64	NUM
cana-2348	109	11	units	unit	NOUN
cana-2348	109	12	and	and	CCONJ
cana-2348	109	13	utilized	utilize	VERB
cana-2348	109	14	a	a	DET
cana-2348	109	15	relu	relu	NOUN
cana-2348	109	16	activation	activation	NOUN
cana-2348	109	17	function	function	NOUN
cana-2348	109	18	.	.	PUNCT
cana-2348	110	1	to	to	PART
cana-2348	110	2	ensure	ensure	VERB
cana-2348	110	3	regularization	regularization	NOUN
cana-2348	110	4	,	,	PUNCT
cana-2348	110	5	batch	batch	NOUN
cana-2348	110	6	normalization	normalization	NOUN
cana-2348	110	7	,	,	PUNCT
cana-2348	110	8	and	and	CCONJ
cana-2348	110	9	dropout	dropout	NOUN
cana-2348	110	10	layers	layer	NOUN
cana-2348	110	11	were	be	AUX
cana-2348	110	12	incorporated	incorporate	VERB
cana-2348	110	13	.	.	PUNCT
cana-2348	111	1	for	for	ADP
cana-2348	111	2	the	the	DET
cana-2348	111	3	binary	binary	ADJ
cana-2348	111	4	classification	classification	NOUN
cana-2348	111	5	output	output	NOUN
cana-2348	111	6	,	,	PUNCT
cana-2348	111	7	a	a	DET
cana-2348	111	8	dense	dense	ADJ
cana-2348	111	9	layer	layer	NOUN
cana-2348	111	10	with	with	ADP
cana-2348	111	11	a	a	DET
cana-2348	111	12	sigmoid	sigmoid	NOUN
cana-2348	111	13	activation	activation	NOUN
cana-2348	111	14	function	function	NOUN
cana-2348	111	15	was	be	AUX
cana-2348	111	16	employed	employ	VERB
cana-2348	111	17	.	.	PUNCT
cana-2348	112	1	an	an	DET
cana-2348	112	2	lstm	lstm	ADJ
cana-2348	112	3	cell	cell	NOUN
cana-2348	112	4	usually	usually	ADV
cana-2348	112	5	comprises	comprise	VERB
cana-2348	112	6	several	several	ADJ
cana-2348	112	7	crucial	crucial	ADJ
cana-2348	112	8	components	component	NOUN
cana-2348	112	9	:	:	PUNCT
cana-2348	112	10	1	1	X
cana-2348	112	11	.	.	X
cana-2348	112	12	cell	cell	NOUN
cana-2348	112	13	state	state	NOUN
cana-2348	112	14	(	(	PUNCT
cana-2348	112	15	ct	ct	PROPN
cana-2348	112	16	):	):	PUNCT
cana-2348	112	17	within	within	ADP
cana-2348	112	18	the	the	DET
cana-2348	112	19	lstm	lstm	NOUN
cana-2348	112	20	cell	cell	NOUN
cana-2348	112	21	,	,	PUNCT
cana-2348	112	22	the	the	DET
cana-2348	112	23	cell	cell	NOUN
cana-2348	112	24	state	state	NOUN
cana-2348	112	25	functions	function	NOUN
cana-2348	112	26	as	as	ADP
cana-2348	112	27	the	the	DET
cana-2348	112	28	internal	internal	ADJ
cana-2348	112	29	memory	memory	NOUN
cana-2348	112	30	.	.	PUNCT
cana-2348	113	1	it	it	PRON
cana-2348	113	2	can	can	AUX
cana-2348	113	3	carry	carry	VERB
cana-2348	113	4	information	information	NOUN
cana-2348	113	5	across	across	ADP
cana-2348	113	6	extensive	extensive	ADJ
cana-2348	113	7	sequences	sequence	NOUN
cana-2348	113	8	,	,	PUNCT
cana-2348	113	9	which	which	PRON
cana-2348	113	10	makes	make	VERB
cana-2348	113	11	it	it	PRON
cana-2348	113	12	adept	adept	ADJ
cana-2348	113	13	at	at	ADP
cana-2348	113	14	capturing	capture	VERB
cana-2348	113	15	long	long	ADJ
cana-2348	113	16	-	-	PUNCT
cana-2348	113	17	term	term	NOUN
cana-2348	113	18	dependencies	dependency	NOUN
cana-2348	113	19	.	.	PUNCT
cana-2348	114	1	2	2	X
cana-2348	114	2	.	.	X
cana-2348	114	3	hidden	hide	VERB
cana-2348	114	4	state	state	NOUN
cana-2348	114	5	(	(	PUNCT
cana-2348	114	6	ht	ht	PROPN
cana-2348	114	7	):	):	PUNCT
cana-2348	114	8	at	at	ADP
cana-2348	114	9	a	a	DET
cana-2348	114	10	given	give	VERB
cana-2348	114	11	time	time	NOUN
cana-2348	114	12	step	step	NOUN
cana-2348	114	13	,	,	PUNCT
cana-2348	114	14	it	it	PRON
cana-2348	114	15	represents	represent	VERB
cana-2348	114	16	the	the	DET
cana-2348	114	17	output	output	NOUN
cana-2348	114	18	of	of	ADP
cana-2348	114	19	the	the	DET
cana-2348	114	20	lstm	lstm	NOUN
cana-2348	114	21	cell	cell	NOUN
cana-2348	114	22	.	.	PUNCT
cana-2348	115	1	it	it	PRON
cana-2348	115	2	holds	hold	VERB
cana-2348	115	3	the	the	DET
cana-2348	115	4	information	information	NOUN
cana-2348	115	5	that	that	PRON
cana-2348	115	6	the	the	DET
cana-2348	115	7	cell	cell	NOUN
cana-2348	115	8	considers	consider	VERB
cana-2348	115	9	relevant	relevant	ADJ
cana-2348	115	10	for	for	ADP
cana-2348	115	11	the	the	DET
cana-2348	115	12	current	current	ADJ
cana-2348	115	13	prediction	prediction	NOUN
cana-2348	115	14	or	or	CCONJ
cana-2348	115	15	processing	processing	NOUN
cana-2348	115	16	step	step	NOUN
cana-2348	115	17	.	.	PUNCT
cana-2348	116	1	4	4	X
cana-2348	116	2	.	.	X
cana-2348	116	3	input	input	NOUN
cana-2348	116	4	gate	gate	NOUN
cana-2348	116	5	(	(	PUNCT
cana-2348	116	6	i	i	NOUN
cana-2348	116	7	):	):	PUNCT
cana-2348	116	8	it	it	PRON
cana-2348	116	9	controls	control	VERB
cana-2348	116	10	the	the	DET
cana-2348	116	11	influx	influx	NOUN
cana-2348	116	12	of	of	ADP
cana-2348	116	13	information	information	NOUN
cana-2348	116	14	into	into	ADP
cana-2348	116	15	the	the	DET
cana-2348	116	16	cell	cell	NOUN
cana-2348	116	17	state	state	NOUN
cana-2348	116	18	,	,	PUNCT
cana-2348	116	19	determining	determine	VERB
cana-2348	116	20	which	which	DET
cana-2348	116	21	values	value	NOUN
cana-2348	116	22	from	from	ADP
cana-2348	116	23	the	the	DET
cana-2348	116	24	input	input	NOUN
cana-2348	116	25	and	and	CCONJ
cana-2348	116	26	the	the	DET
cana-2348	116	27	previous	previous	ADJ
cana-2348	116	28	hidden	hidden	ADJ
cana-2348	116	29	state	state	NOUN
cana-2348	116	30	must	must	AUX
cana-2348	116	31	be	be	AUX
cana-2348	116	32	modified	modify	VERB
cana-2348	116	33	and	and	CCONJ
cana-2348	116	34	integrated	integrate	VERB
cana-2348	116	35	into	into	ADP
cana-2348	116	36	the	the	DET
cana-2348	116	37	cell	cell	NOUN
cana-2348	116	38	state	state	NOUN
cana-2348	116	39	.	.	PUNCT
cana-2348	117	1	5	5	X
cana-2348	117	2	.	.	X
cana-2348	117	3	forget	forget	VERB
cana-2348	117	4	gate	gate	NOUN
cana-2348	117	5	(	(	PUNCT
cana-2348	117	6	f	f	X
cana-2348	117	7	):	):	PUNCT
cana-2348	117	8	it	it	PRON
cana-2348	117	9	determines	determine	VERB
cana-2348	117	10	the	the	DET
cana-2348	117	11	values	value	NOUN
cana-2348	117	12	based	base	VERB
cana-2348	117	13	on	on	ADP
cana-2348	117	14	the	the	DET
cana-2348	117	15	previous	previous	ADJ
cana-2348	117	16	cell	cell	NOUN
cana-2348	117	17	state	state	NOUN
cana-2348	117	18	,	,	PUNCT
cana-2348	117	19	excluding	exclude	VERB
cana-2348	117	20	the	the	DET
cana-2348	117	21	input	input	NOUN
cana-2348	117	22	.	.	PUNCT
cana-2348	118	1	it	it	PRON
cana-2348	118	2	controls	control	VERB
cana-2348	118	3	the	the	DET
cana-2348	118	4	information	information	NOUN
cana-2348	118	5	that	that	PRON
cana-2348	118	6	should	should	AUX
cana-2348	118	7	be	be	AUX
cana-2348	118	8	removed	remove	VERB
cana-2348	118	9	from	from	ADP
cana-2348	118	10	the	the	DET
cana-2348	118	11	cell	cell	NOUN
cana-2348	118	12	state	state	NOUN
cana-2348	118	13	.	.	PUNCT
cana-2348	119	1	6	6	X
cana-2348	119	2	.	.	X
cana-2348	119	3	output	output	NOUN
cana-2348	119	4	gate	gate	NOUN
cana-2348	119	5	(	(	PUNCT
cana-2348	119	6	o	o	NOUN
cana-2348	119	7	):	):	PUNCT
cana-2348	119	8	it	it	PRON
cana-2348	119	9	dictates	dictate	VERB
cana-2348	119	10	which	which	DET
cana-2348	119	11	part	part	NOUN
cana-2348	119	12	of	of	ADP
cana-2348	119	13	the	the	DET
cana-2348	119	14	memory	memory	NOUN
cana-2348	119	15	state	state	NOUN
cana-2348	119	16	is	be	AUX
cana-2348	119	17	to	to	PART
cana-2348	119	18	be	be	AUX
cana-2348	119	19	revealed	reveal	VERB
cana-2348	119	20	as	as	ADP
cana-2348	119	21	the	the	DET
cana-2348	119	22	hidden	hidden	ADJ
cana-2348	119	23	state	state	NOUN
cana-2348	119	24	for	for	ADP
cana-2348	119	25	a	a	DET
cana-2348	119	26	present	present	ADJ
cana-2348	119	27	time	time	NOUN
cana-2348	119	28	interval	interval	NOUN
cana-2348	119	29	.	.	PUNCT
cana-2348	120	1	communications	communication	NOUN
cana-2348	120	2	on	on	ADP
cana-2348	120	3	applied	apply	VERB
cana-2348	120	4	nonlinear	nonlinear	ADJ
cana-2348	120	5	analysis	analysis	NOUN
cana-2348	120	6	issn	issn	NOUN
cana-2348	120	7	:	:	PUNCT
cana-2348	120	8	1074	1074	NUM
cana-2348	120	9	-	-	PUNCT
cana-2348	120	10	133x	133x	NUM
cana-2348	120	11	vol	vol	NOUN
cana-2348	120	12	32	32	NUM
cana-2348	120	13	no	no	NOUN
cana-2348	120	14	.	.	NOUN
cana-2348	120	15	2	2	NUM
cana-2348	120	16	(	(	PUNCT
cana-2348	120	17	2025	2025	NUM
cana-2348	120	18	)	)	PUNCT
cana-2348	120	19	628	628	NUM
cana-2348	120	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	120	21	figure	figure	NOUN
cana-2348	120	22	3	3	NUM
cana-2348	120	23	:	:	PUNCT
cana-2348	120	24	lstm	lstm	ADJ
cana-2348	120	25	architecture	architecture	NOUN
cana-2348	120	26	in	in	ADP
cana-2348	120	27	this	this	DET
cana-2348	120	28	diagram	diagram	NOUN
cana-2348	120	29	:	:	PUNCT
cana-2348	120	30	•	•	ADP
cana-2348	120	31	the	the	DET
cana-2348	120	32	arrows	arrow	NOUN
cana-2348	120	33	represent	represent	VERB
cana-2348	120	34	the	the	DET
cana-2348	120	35	flow	flow	NOUN
cana-2348	120	36	of	of	ADP
cana-2348	120	37	information	information	NOUN
cana-2348	120	38	.	.	PUNCT
cana-2348	121	1	•	•	NUM
cana-2348	121	2	each	each	DET
cana-2348	121	3	gate	gate	NOUN
cana-2348	121	4	(	(	PUNCT
cana-2348	121	5	input	input	NOUN
cana-2348	121	6	gate	gate	NOUN
cana-2348	121	7	,	,	PUNCT
cana-2348	121	8	forget	forget	VERB
cana-2348	121	9	gate	gate	NOUN
cana-2348	121	10	,	,	PUNCT
cana-2348	121	11	output	output	NOUN
cana-2348	121	12	gate	gate	NOUN
cana-2348	121	13	)	)	PUNCT
cana-2348	121	14	is	be	AUX
cana-2348	121	15	like	like	ADP
cana-2348	121	16	a	a	DET
cana-2348	121	17	small	small	ADJ
cana-2348	121	18	neural	neural	ADJ
cana-2348	121	19	network	network	NOUN
cana-2348	121	20	layer	layer	NOUN
cana-2348	121	21	that	that	PRON
cana-2348	121	22	takes	take	VERB
cana-2348	121	23	inputs	input	NOUN
cana-2348	121	24	,	,	PUNCT
cana-2348	121	25	applies	apply	VERB
cana-2348	121	26	weights	weight	NOUN
cana-2348	121	27	,	,	PUNCT
cana-2348	121	28	and	and	CCONJ
cana-2348	121	29	produces	produce	VERB
cana-2348	121	30	outputs	output	NOUN
cana-2348	121	31	.	.	PUNCT
cana-2348	122	1	•	•	NOUN
cana-2348	122	2	the	the	DET
cana-2348	122	3	forget	forget	NOUN
cana-2348	122	4	gate	gate	PROPN
cana-2348	122	5	determines	determine	NOUN
cana-2348	122	6	which	which	PRON
cana-2348	122	7	aspects	aspect	NOUN
cana-2348	122	8	of	of	ADP
cana-2348	122	9	the	the	DET
cana-2348	122	10	prior	prior	ADJ
cana-2348	122	11	cell	cell	NOUN
cana-2348	122	12	state	state	NOUN
cana-2348	122	13	to	to	PART
cana-2348	122	14	retain	retain	VERB
cana-2348	122	15	or	or	CCONJ
cana-2348	122	16	discard	discard	ADJ
cana-2348	122	17	.	.	PUNCT
cana-2348	123	1	this	this	DET
cana-2348	123	2	gate	gate	NOUN
cana-2348	123	3	evaluates	evaluate	VERB
cana-2348	123	4	the	the	DET
cana-2348	123	5	importance	importance	NOUN
cana-2348	123	6	of	of	ADP
cana-2348	123	7	the	the	DET
cana-2348	123	8	previous	previous	ADJ
cana-2348	123	9	information	information	NOUN
cana-2348	123	10	and	and	CCONJ
cana-2348	123	11	decides	decide	VERB
cana-2348	123	12	whether	whether	SCONJ
cana-2348	123	13	to	to	PART
cana-2348	123	14	keep	keep	VERB
cana-2348	123	15	it	it	PRON
cana-2348	123	16	in	in	ADP
cana-2348	123	17	the	the	DET
cana-2348	123	18	cell	cell	NOUN
cana-2348	123	19	state	state	NOUN
cana-2348	123	20	or	or	CCONJ
cana-2348	123	21	remove	remove	VERB
cana-2348	123	22	it	it	PRON
cana-2348	123	23	.	.	PUNCT
cana-2348	124	1	•	•	NUM
cana-2348	124	2	the	the	DET
cana-2348	124	3	input	input	NOUN
cana-2348	124	4	gate	gate	NOUN
cana-2348	124	5	assesses	assess	VERB
cana-2348	124	6	the	the	DET
cana-2348	124	7	relevance	relevance	NOUN
cana-2348	124	8	of	of	ADP
cana-2348	124	9	incoming	incoming	ADJ
cana-2348	124	10	data	datum	NOUN
cana-2348	124	11	from	from	ADP
cana-2348	124	12	the	the	DET
cana-2348	124	13	current	current	ADJ
cana-2348	124	14	input	input	NOUN
cana-2348	124	15	and	and	CCONJ
cana-2348	124	16	the	the	DET
cana-2348	124	17	previous	previous	ADJ
cana-2348	124	18	hidden	hidden	ADJ
cana-2348	124	19	state	state	NOUN
cana-2348	124	20	,	,	PUNCT
cana-2348	124	21	deciding	decide	VERB
cana-2348	124	22	which	which	PRON
cana-2348	124	23	parts	part	NOUN
cana-2348	124	24	should	should	AUX
cana-2348	124	25	be	be	AUX
cana-2348	124	26	incorporated	incorporate	VERB
cana-2348	124	27	into	into	ADP
cana-2348	124	28	the	the	DET
cana-2348	124	29	cell	cell	NOUN
cana-2348	124	30	state	state	NOUN
cana-2348	124	31	.	.	PUNCT
cana-2348	125	1	it	it	PRON
cana-2348	125	2	updates	update	VERB
cana-2348	125	3	the	the	DET
cana-2348	125	4	cell	cell	NOUN
cana-2348	125	5	state	state	NOUN
cana-2348	125	6	by	by	ADP
cana-2348	125	7	incorporating	incorporate	VERB
cana-2348	125	8	this	this	DET
cana-2348	125	9	new	new	ADJ
cana-2348	125	10	information	information	NOUN
cana-2348	125	11	based	base	VERB
cana-2348	125	12	on	on	ADP
cana-2348	125	13	its	its	PRON
cana-2348	125	14	significance	significance	NOUN
cana-2348	125	15	.	.	PUNCT
cana-2348	126	1	•	•	NOUN
cana-2348	126	2	the	the	DET
cana-2348	126	3	output	output	NOUN
cana-2348	126	4	gate	gate	NOUN
cana-2348	126	5	identifies	identify	VERB
cana-2348	126	6	the	the	DET
cana-2348	126	7	portion	portion	NOUN
cana-2348	126	8	of	of	ADP
cana-2348	126	9	the	the	DET
cana-2348	126	10	cell	cell	NOUN
cana-2348	126	11	state	state	NOUN
cana-2348	126	12	that	that	PRON
cana-2348	126	13	is	be	AUX
cana-2348	126	14	to	to	PART
cana-2348	126	15	be	be	AUX
cana-2348	126	16	revealed	reveal	VERB
cana-2348	126	17	as	as	ADP
cana-2348	126	18	the	the	DET
cana-2348	126	19	hidden	hidden	ADJ
cana-2348	126	20	state	state	NOUN
cana-2348	126	21	.	.	PUNCT
cana-2348	127	1	it	it	PRON
cana-2348	127	2	controls	control	VERB
cana-2348	127	3	what	what	PRON
cana-2348	127	4	data	datum	NOUN
cana-2348	127	5	is	be	AUX
cana-2348	127	6	output	output	NOUN
cana-2348	127	7	from	from	ADP
cana-2348	127	8	the	the	DET
cana-2348	127	9	cell	cell	NOUN
cana-2348	127	10	state	state	NOUN
cana-2348	127	11	to	to	PART
cana-2348	127	12	be	be	AUX
cana-2348	127	13	used	use	VERB
cana-2348	127	14	for	for	ADP
cana-2348	127	15	the	the	DET
cana-2348	127	16	current	current	ADJ
cana-2348	127	17	time	time	NOUN
cana-2348	127	18	step	step	NOUN
cana-2348	127	19	's	's	PART
cana-2348	127	20	processing	processing	NOUN
cana-2348	127	21	or	or	CCONJ
cana-2348	127	22	prediction	prediction	NOUN
cana-2348	127	23	.	.	PUNCT
cana-2348	128	1	3	3	X
cana-2348	128	2	.	.	X
cana-2348	128	3	gated	gate	VERB
cana-2348	128	4	recurrent	recurrent	ADJ
cana-2348	128	5	unit	unit	NOUN
cana-2348	128	6	(	(	PUNCT
cana-2348	128	7	gru	gru	PROPN
cana-2348	128	8	):	):	PUNCT
cana-2348	128	9	the	the	DET
cana-2348	128	10	gated	gate	VERB
cana-2348	128	11	recurrent	recurrent	ADJ
cana-2348	128	12	unit	unit	NOUN
cana-2348	128	13	architecture	architecture	NOUN
cana-2348	128	14	was	be	AUX
cana-2348	128	15	designed	design	VERB
cana-2348	128	16	as	as	ADP
cana-2348	128	17	a	a	DET
cana-2348	128	18	variant	variant	NOUN
cana-2348	128	19	of	of	ADP
cana-2348	128	20	long	long	ADJ
cana-2348	128	21	short	short	ADJ
cana-2348	128	22	-	-	PUNCT
cana-2348	128	23	term	term	NOUN
cana-2348	128	24	memory	memory	NOUN
cana-2348	128	25	,	,	PUNCT
cana-2348	128	26	offering	offer	VERB
cana-2348	128	27	similar	similar	ADJ
cana-2348	128	28	capabilities	capability	NOUN
cana-2348	128	29	with	with	ADP
cana-2348	128	30	a	a	DET
cana-2348	128	31	reduced	reduced	ADJ
cana-2348	128	32	computational	computational	ADJ
cana-2348	128	33	cost	cost	NOUN
cana-2348	128	34	.	.	PUNCT
cana-2348	129	1	the	the	DET
cana-2348	129	2	model	model	NOUN
cana-2348	129	3	included	include	VERB
cana-2348	129	4	a	a	DET
cana-2348	129	5	single	single	ADJ
cana-2348	129	6	gru	gru	NOUN
cana-2348	129	7	layer	layer	NOUN
cana-2348	129	8	with	with	ADP
cana-2348	129	9	64	64	NUM
cana-2348	129	10	units	unit	NOUN
cana-2348	129	11	and	and	CCONJ
cana-2348	129	12	employed	employ	VERB
cana-2348	129	13	a	a	DET
cana-2348	129	14	relu	relu	NOUN
cana-2348	129	15	activation	activation	NOUN
cana-2348	129	16	function	function	NOUN
cana-2348	129	17	.	.	PUNCT
cana-2348	130	1	batch	batch	NOUN
cana-2348	130	2	normalization	normalization	NOUN
cana-2348	130	3	and	and	CCONJ
cana-2348	130	4	dropout	dropout	NOUN
cana-2348	130	5	layers	layer	NOUN
cana-2348	130	6	were	be	AUX
cana-2348	130	7	used	use	VERB
cana-2348	130	8	to	to	PART
cana-2348	130	9	ensure	ensure	VERB
cana-2348	130	10	regularization	regularization	NOUN
cana-2348	130	11	.	.	PUNCT
cana-2348	131	1	for	for	ADP
cana-2348	131	2	the	the	DET
cana-2348	131	3	binary	binary	ADJ
cana-2348	131	4	classification	classification	NOUN
cana-2348	131	5	output	output	NOUN
cana-2348	131	6	,	,	PUNCT
cana-2348	131	7	a	a	DET
cana-2348	131	8	dense	dense	ADJ
cana-2348	131	9	layer	layer	NOUN
cana-2348	131	10	with	with	ADP
cana-2348	131	11	a	a	DET
cana-2348	131	12	sigmoid	sigmoid	NOUN
cana-2348	131	13	activation	activation	NOUN
cana-2348	131	14	function	function	NOUN
cana-2348	131	15	was	be	AUX
cana-2348	131	16	utilized	utilize	VERB
cana-2348	131	17	as	as	ADP
cana-2348	131	18	the	the	DET
cana-2348	131	19	final	final	ADJ
cana-2348	131	20	layer	layer	NOUN
cana-2348	131	21	.	.	PUNCT
cana-2348	132	1	gru	gru	NOUN
cana-2348	132	2	components	component	NOUN
cana-2348	132	3	:	:	PUNCT
cana-2348	132	4	1	1	X
cana-2348	132	5	.	.	X
cana-2348	132	6	update	update	NOUN
cana-2348	132	7	gate	gate	NOUN
cana-2348	132	8	(	(	PUNCT
cana-2348	132	9	𝒛𝒕	𝒛𝒕	ADV
cana-2348	132	10	):	):	PUNCT
cana-2348	132	11	the	the	DET
cana-2348	132	12	degree	degree	NOUN
cana-2348	132	13	to	to	PART
cana-2348	132	14	which	which	PRON
cana-2348	132	15	the	the	DET
cana-2348	132	16	merging	merging	NOUN
cana-2348	132	17	of	of	ADP
cana-2348	132	18	the	the	DET
cana-2348	132	19	previous	previous	ADJ
cana-2348	132	20	hidden	hidden	ADJ
cana-2348	132	21	state	state	NOUN
cana-2348	132	22	with	with	ADP
cana-2348	132	23	the	the	DET
cana-2348	132	24	candidate	candidate	NOUN
cana-2348	132	25	's	's	PART
cana-2348	132	26	new	new	ADJ
cana-2348	132	27	hidden	hidden	ADJ
cana-2348	132	28	state	state	NOUN
cana-2348	132	29	is	be	AUX
cana-2348	132	30	determined	determine	VERB
cana-2348	132	31	.	.	PUNCT
cana-2348	133	1	forgetgate	forgetgate	NOUN
cana-2348	133	2	(	(	PUNCT
cana-2348	133	3	ft	ft	NOUN
cana-2348	133	4	)	)	PUNCT
cana-2348	133	5	inputgate	inputgate	NOUN
cana-2348	133	6	(	(	PUNCT
cana-2348	133	7	it	it	PRON
cana-2348	133	8	)	)	PUNCT
cana-2348	133	9	cellstate	cellstate	VERB
cana-2348	133	10	(	(	PUNCT
cana-2348	133	11	ct	ct	NOUN
cana-2348	133	12	)	)	PUNCT
cana-2348	133	13	outputgate	outputgate	ADV
cana-2348	133	14	(	(	PUNCT
cana-2348	133	15	ot	ot	ADJ
cana-2348	133	16	)	)	PUNCT
cana-2348	133	17	hiddenstate	hiddenstate	NOUN
cana-2348	133	18	(	(	PUNCT
cana-2348	133	19	ht	ht	PROPN
cana-2348	133	20	)	)	PUNCT
cana-2348	133	21	communications	communication	NOUN
cana-2348	133	22	on	on	ADP
cana-2348	133	23	applied	apply	VERB
cana-2348	133	24	nonlinear	nonlinear	ADJ
cana-2348	133	25	analysis	analysis	NOUN
cana-2348	133	26	issn	issn	NOUN
cana-2348	133	27	:	:	PUNCT
cana-2348	133	28	1074	1074	NUM
cana-2348	133	29	-	-	PUNCT
cana-2348	133	30	133x	133x	NUM
cana-2348	133	31	vol	vol	NOUN
cana-2348	133	32	32	32	NUM
cana-2348	133	33	no	no	NOUN
cana-2348	133	34	.	.	NOUN
cana-2348	133	35	2	2	NUM
cana-2348	133	36	(	(	PUNCT
cana-2348	133	37	2025	2025	NUM
cana-2348	133	38	)	)	PUNCT
cana-2348	133	39	629	629	NUM
cana-2348	133	40	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	133	41	2	2	X
cana-2348	133	42	.	.	X
cana-2348	133	43	reset	reset	NOUN
cana-2348	133	44	gate	gate	NOUN
cana-2348	133	45	(	(	PUNCT
cana-2348	133	46	𝒓𝒕	𝒓𝒕	NOUN
cana-2348	133	47	):	):	PUNCT
cana-2348	133	48	the	the	DET
cana-2348	133	49	reset	reset	NOUN
cana-2348	133	50	gate	gate	NOUN
cana-2348	133	51	influences	influence	VERB
cana-2348	133	52	the	the	DET
cana-2348	133	53	candidate	candidate	NOUN
cana-2348	133	54	's	's	PART
cana-2348	133	55	new	new	ADJ
cana-2348	133	56	hidden	hidden	ADJ
cana-2348	133	57	state	state	NOUN
cana-2348	133	58	by	by	ADP
cana-2348	133	59	controlling	control	VERB
cana-2348	133	60	how	how	SCONJ
cana-2348	133	61	much	much	ADJ
cana-2348	133	62	of	of	ADP
cana-2348	133	63	the	the	DET
cana-2348	133	64	past	past	ADJ
cana-2348	133	65	information	information	NOUN
cana-2348	133	66	to	to	PART
cana-2348	133	67	forget	forget	VERB
cana-2348	133	68	.	.	PUNCT
cana-2348	134	1	this	this	DET
cana-2348	134	2	process	process	NOUN
cana-2348	134	3	helps	help	VERB
cana-2348	134	4	in	in	ADP
cana-2348	134	5	determining	determine	VERB
cana-2348	134	6	which	which	DET
cana-2348	134	7	previous	previous	ADJ
cana-2348	134	8	information	information	NOUN
cana-2348	134	9	is	be	AUX
cana-2348	134	10	retained	retain	VERB
cana-2348	134	11	and	and	CCONJ
cana-2348	134	12	which	which	PRON
cana-2348	134	13	is	be	AUX
cana-2348	134	14	discarded	discard	VERB
cana-2348	134	15	,	,	PUNCT
cana-2348	134	16	shaping	shape	VERB
cana-2348	134	17	the	the	DET
cana-2348	134	18	new	new	ADJ
cana-2348	134	19	hidden	hidden	ADJ
cana-2348	134	20	state	state	NOUN
cana-2348	134	21	accordingly	accordingly	ADV
cana-2348	134	22	.	.	PUNCT
cana-2348	135	1	3	3	X
cana-2348	135	2	.	.	X
cana-2348	135	3	candidate	candidate	NOUN
cana-2348	135	4	hidden	hide	VERB
cana-2348	135	5	state	state	NOUN
cana-2348	135	6	(	(	PUNCT
cana-2348	135	7	𝒉′𝒕	𝒉′𝒕	NOUN
cana-2348	135	8	):	):	PUNCT
cana-2348	135	9	the	the	DET
cana-2348	135	10	new	new	ADJ
cana-2348	135	11	hidden	hidden	ADJ
cana-2348	135	12	state	state	NOUN
cana-2348	135	13	candidate	candidate	NOUN
cana-2348	135	14	creates	create	VERB
cana-2348	135	15	an	an	DET
cana-2348	135	16	updated	update	VERB
cana-2348	135	17	representation	representation	NOUN
cana-2348	135	18	by	by	ADP
cana-2348	135	19	integrating	integrate	VERB
cana-2348	135	20	information	information	NOUN
cana-2348	135	21	from	from	ADP
cana-2348	135	22	the	the	DET
cana-2348	135	23	previous	previous	ADJ
cana-2348	135	24	hidden	hide	VERB
cana-2348	135	25	state	state	NOUN
cana-2348	135	26	and	and	CCONJ
cana-2348	135	27	present	present	ADJ
cana-2348	135	28	input	input	NOUN
cana-2348	135	29	.	.	PUNCT
cana-2348	136	1	4	4	X
cana-2348	136	2	.	.	X
cana-2348	136	3	hidden	hide	VERB
cana-2348	136	4	state	state	NOUN
cana-2348	136	5	(	(	PUNCT
cana-2348	136	6	𝒉𝒕	𝒉𝒕	NOUN
cana-2348	136	7	):	):	PUNCT
cana-2348	136	8	the	the	DET
cana-2348	136	9	update	update	NOUN
cana-2348	136	10	gate	gate	NOUN
cana-2348	136	11	regulates	regulate	VERB
cana-2348	136	12	the	the	DET
cana-2348	136	13	extent	extent	NOUN
cana-2348	136	14	to	to	PART
cana-2348	136	15	which	which	PRON
cana-2348	136	16	the	the	DET
cana-2348	136	17	candidate	candidate	NOUN
cana-2348	136	18	state	state	NOUN
cana-2348	136	19	influences	influence	VERB
cana-2348	136	20	the	the	DET
cana-2348	136	21	current	current	ADJ
cana-2348	136	22	state	state	NOUN
cana-2348	136	23	,	,	PUNCT
cana-2348	136	24	effectively	effectively	ADV
cana-2348	136	25	blending	blend	VERB
cana-2348	136	26	past	past	ADJ
cana-2348	136	27	information	information	NOUN
cana-2348	136	28	with	with	ADP
cana-2348	136	29	new	new	ADJ
cana-2348	136	30	inputs	input	NOUN
cana-2348	136	31	to	to	PART
cana-2348	136	32	form	form	VERB
cana-2348	136	33	the	the	DET
cana-2348	136	34	updated	update	VERB
cana-2348	136	35	hidden	hidden	ADJ
cana-2348	136	36	state	state	NOUN
cana-2348	136	37	.	.	PUNCT
cana-2348	137	1	the	the	DET
cana-2348	137	2	final	final	ADJ
cana-2348	137	3	hidden	hidden	ADJ
cana-2348	137	4	state	state	NOUN
cana-2348	137	5	is	be	AUX
cana-2348	137	6	formed	form	VERB
cana-2348	137	7	by	by	ADP
cana-2348	137	8	blending	blend	VERB
cana-2348	137	9	the	the	DET
cana-2348	137	10	current	current	ADJ
cana-2348	137	11	hidden	hide	VERB
cana-2348	137	12	state	state	NOUN
cana-2348	137	13	with	with	ADP
cana-2348	137	14	the	the	DET
cana-2348	137	15	candidate	candidate	NOUN
cana-2348	137	16	's	's	PART
cana-2348	137	17	new	new	ADJ
cana-2348	137	18	hidden	hidden	ADJ
cana-2348	137	19	state	state	NOUN
cana-2348	137	20	,	,	PUNCT
cana-2348	137	21	regulated	regulate	VERB
cana-2348	137	22	by	by	ADP
cana-2348	137	23	this	this	DET
cana-2348	137	24	gate	gate	NOUN
cana-2348	137	25	.	.	PUNCT
cana-2348	138	1	key	key	ADJ
cana-2348	138	2	performance	performance	NOUN
cana-2348	138	3	indicators	indicator	NOUN
cana-2348	138	4	,	,	PUNCT
cana-2348	138	5	including	include	VERB
cana-2348	138	6	accuracy	accuracy	NOUN
cana-2348	138	7	,	,	PUNCT
cana-2348	138	8	f1	f1	NOUN
cana-2348	138	9	score	score	NOUN
cana-2348	138	10	,	,	PUNCT
cana-2348	138	11	and	and	CCONJ
cana-2348	138	12	precision	precision	NOUN
cana-2348	138	13	were	be	AUX
cana-2348	138	14	used	use	VERB
cana-2348	138	15	to	to	PART
cana-2348	138	16	evaluate	evaluate	VERB
cana-2348	138	17	the	the	DET
cana-2348	138	18	model	model	NOUN
cana-2348	138	19	,	,	PUNCT
cana-2348	138	20	to	to	PART
cana-2348	138	21	comprehensively	comprehensively	ADV
cana-2348	138	22	assess	assess	VERB
cana-2348	138	23	classification	classification	NOUN
cana-2348	138	24	effectiveness	effectiveness	NOUN
cana-2348	138	25	.	.	PUNCT
cana-2348	139	1	classification	classification	NOUN
cana-2348	139	2	reports	report	NOUN
cana-2348	139	3	were	be	AUX
cana-2348	139	4	generated	generate	VERB
cana-2348	139	5	to	to	PART
cana-2348	139	6	provide	provide	VERB
cana-2348	139	7	detailed	detailed	ADJ
cana-2348	139	8	insights	insight	NOUN
cana-2348	139	9	into	into	ADP
cana-2348	139	10	the	the	DET
cana-2348	139	11	model	model	NOUN
cana-2348	139	12	's	's	PART
cana-2348	139	13	ability	ability	NOUN
cana-2348	139	14	to	to	PART
cana-2348	139	15	correctly	correctly	ADV
cana-2348	139	16	classify	classify	VERB
cana-2348	139	17	individuals	individual	NOUN
cana-2348	139	18	with	with	ADP
cana-2348	139	19	or	or	CCONJ
cana-2348	139	20	without	without	ADP
cana-2348	139	21	autism	autism	NOUN
cana-2348	139	22	spectrum	spectrum	NOUN
cana-2348	139	23	disorder	disorder	NOUN
cana-2348	139	24	.	.	PUNCT
cana-2348	140	1	v.	v.	ADP
cana-2348	140	2	result	result	NOUN
cana-2348	140	3	and	and	CCONJ
cana-2348	140	4	discussion	discussion	NOUN
cana-2348	140	5	while	while	SCONJ
cana-2348	140	6	the	the	DET
cana-2348	140	7	current	current	ADJ
cana-2348	140	8	study	study	NOUN
cana-2348	140	9	compares	compare	VERB
cana-2348	140	10	the	the	DET
cana-2348	140	11	performance	performance	NOUN
cana-2348	140	12	of	of	ADP
cana-2348	140	13	various	various	ADJ
cana-2348	140	14	deep	deep	ADJ
cana-2348	140	15	learning	learning	NOUN
cana-2348	140	16	algorithms	algorithm	NOUN
cana-2348	140	17	for	for	ADP
cana-2348	140	18	predicting	predict	VERB
cana-2348	140	19	autism	autism	NOUN
cana-2348	140	20	spectrum	spectrum	NOUN
cana-2348	140	21	disorder	disorder	NOUN
cana-2348	140	22	,	,	PUNCT
cana-2348	140	23	it	it	PRON
cana-2348	140	24	is	be	AUX
cana-2348	140	25	essential	essential	ADJ
cana-2348	140	26	to	to	PART
cana-2348	140	27	acknowledge	acknowledge	VERB
cana-2348	140	28	the	the	DET
cana-2348	140	29	existing	exist	VERB
cana-2348	140	30	research	research	NOUN
cana-2348	140	31	gaps	gap	NOUN
cana-2348	140	32	that	that	PRON
cana-2348	140	33	provide	provide	VERB
cana-2348	140	34	avenues	avenue	NOUN
cana-2348	140	35	for	for	ADP
cana-2348	140	36	future	future	ADJ
cana-2348	140	37	exploration	exploration	NOUN
cana-2348	140	38	.	.	PUNCT
cana-2348	141	1	firstly	firstly	ADV
cana-2348	141	2	,	,	PUNCT
cana-2348	141	3	the	the	DET
cana-2348	141	4	majority	majority	NOUN
cana-2348	141	5	of	of	ADP
cana-2348	141	6	existing	exist	VERB
cana-2348	141	7	literature	literature	NOUN
cana-2348	141	8	primarily	primarily	ADV
cana-2348	141	9	focuses	focus	VERB
cana-2348	141	10	on	on	ADP
cana-2348	141	11	the	the	DET
cana-2348	141	12	accuracy	accuracy	NOUN
cana-2348	141	13	of	of	ADP
cana-2348	141	14	predictive	predictive	ADJ
cana-2348	141	15	models	model	NOUN
cana-2348	141	16	,	,	PUNCT
cana-2348	141	17	neglecting	neglect	VERB
cana-2348	141	18	the	the	DET
cana-2348	141	19	interpretability	interpretability	NOUN
cana-2348	141	20	and	and	CCONJ
cana-2348	141	21	explainability	explainability	NOUN
cana-2348	141	22	of	of	ADP
cana-2348	141	23	these	these	DET
cana-2348	141	24	models	model	NOUN
cana-2348	141	25	,	,	PUNCT
cana-2348	141	26	which	which	PRON
cana-2348	141	27	are	be	AUX
cana-2348	141	28	crucial	crucial	ADJ
cana-2348	141	29	aspects	aspect	NOUN
cana-2348	141	30	in	in	ADP
cana-2348	141	31	the	the	DET
cana-2348	141	32	context	context	NOUN
cana-2348	141	33	of	of	ADP
cana-2348	141	34	medical	medical	ADJ
cana-2348	141	35	diagnostics	diagnostic	NOUN
cana-2348	141	36	.	.	PUNCT
cana-2348	142	1	addressing	address	VERB
cana-2348	142	2	this	this	DET
cana-2348	142	3	gap	gap	NOUN
cana-2348	142	4	would	would	AUX
cana-2348	142	5	contribute	contribute	VERB
cana-2348	142	6	to	to	ADP
cana-2348	142	7	building	build	VERB
cana-2348	142	8	trust	trust	NOUN
cana-2348	142	9	in	in	ADP
cana-2348	142	10	the	the	DET
cana-2348	142	11	practical	practical	ADJ
cana-2348	142	12	application	application	NOUN
cana-2348	142	13	of	of	ADP
cana-2348	142	14	deep	deep	ADJ
cana-2348	142	15	learning	learning	NOUN
cana-2348	142	16	algorithms	algorithm	NOUN
cana-2348	142	17	for	for	ADP
cana-2348	142	18	asd	asd	PROPN
cana-2348	142	19	prediction	prediction	NOUN
cana-2348	142	20	,	,	PUNCT
cana-2348	142	21	ensuring	ensure	VERB
cana-2348	142	22	that	that	SCONJ
cana-2348	142	23	the	the	DET
cana-2348	142	24	generated	generate	VERB
cana-2348	142	25	insights	insight	NOUN
cana-2348	142	26	are	be	AUX
cana-2348	142	27	not	not	PART
cana-2348	142	28	only	only	ADV
cana-2348	142	29	accurate	accurate	ADJ
cana-2348	142	30	but	but	CCONJ
cana-2348	142	31	also	also	ADV
cana-2348	142	32	transparent	transparent	ADJ
cana-2348	142	33	and	and	CCONJ
cana-2348	142	34	understandable	understandable	ADJ
cana-2348	142	35	for	for	ADP
cana-2348	142	36	clinicians	clinician	NOUN
cana-2348	142	37	and	and	CCONJ
cana-2348	142	38	stakeholders	stakeholder	NOUN
cana-2348	142	39	.	.	PUNCT
cana-2348	143	1	furthermore	furthermore	ADV
cana-2348	143	2	,	,	PUNCT
cana-2348	143	3	while	while	SCONJ
cana-2348	143	4	the	the	DET
cana-2348	143	5	study	study	NOUN
cana-2348	143	6	identifies	identify	VERB
cana-2348	143	7	the	the	DET
cana-2348	143	8	most	most	ADV
cana-2348	143	9	effective	effective	ADJ
cana-2348	143	10	deep	deep	ADJ
cana-2348	143	11	learning	learning	NOUN
cana-2348	143	12	algorithm	algorithm	NOUN
cana-2348	143	13	for	for	ADP
cana-2348	143	14	asd	asd	PROPN
cana-2348	143	15	prediction	prediction	NOUN
cana-2348	143	16	based	base	VERB
cana-2348	143	17	on	on	ADP
cana-2348	143	18	the	the	DET
cana-2348	143	19	utilized	utilize	VERB
cana-2348	143	20	dataset	dataset	NOUN
cana-2348	143	21	,	,	PUNCT
cana-2348	143	22	there	there	PRON
cana-2348	143	23	is	be	VERB
cana-2348	143	24	an	an	DET
cana-2348	143	25	opportunity	opportunity	NOUN
cana-2348	143	26	to	to	PART
cana-2348	143	27	explore	explore	VERB
cana-2348	143	28	the	the	DET
cana-2348	143	29	impact	impact	NOUN
cana-2348	143	30	of	of	ADP
cana-2348	143	31	different	different	ADJ
cana-2348	143	32	feature	feature	NOUN
cana-2348	143	33	sets	set	NOUN
cana-2348	143	34	and	and	CCONJ
cana-2348	143	35	data	datum	NOUN
cana-2348	143	36	representations	representation	NOUN
cana-2348	143	37	on	on	ADP
cana-2348	143	38	model	model	NOUN
cana-2348	143	39	performance	performance	NOUN
cana-2348	143	40	.	.	PUNCT
cana-2348	144	1	investigating	investigate	VERB
cana-2348	144	2	the	the	DET
cana-2348	144	3	influence	influence	NOUN
cana-2348	144	4	of	of	ADP
cana-2348	144	5	varied	varied	ADJ
cana-2348	144	6	input	input	NOUN
cana-2348	144	7	features	feature	NOUN
cana-2348	144	8	,	,	PUNCT
cana-2348	144	9	such	such	ADJ
cana-2348	144	10	as	as	ADP
cana-2348	144	11	different	different	ADJ
cana-2348	144	12	types	type	NOUN
cana-2348	144	13	of	of	ADP
cana-2348	144	14	behavioral	behavioral	ADJ
cana-2348	144	15	data	datum	NOUN
cana-2348	144	16	or	or	CCONJ
cana-2348	144	17	additional	additional	ADJ
cana-2348	144	18	biomarkers	biomarker	NOUN
cana-2348	144	19	,	,	PUNCT
cana-2348	144	20	could	could	AUX
cana-2348	144	21	provide	provide	VERB
cana-2348	144	22	valuable	valuable	ADJ
cana-2348	144	23	insights	insight	NOUN
cana-2348	144	24	into	into	ADP
cana-2348	144	25	optimizing	optimize	VERB
cana-2348	144	26	model	model	NOUN
cana-2348	144	27	inputs	input	NOUN
cana-2348	144	28	for	for	ADP
cana-2348	144	29	enhanced	enhanced	ADJ
cana-2348	144	30	accuracy	accuracy	NOUN
cana-2348	144	31	and	and	CCONJ
cana-2348	144	32	clinical	clinical	ADJ
cana-2348	144	33	relevance	relevance	NOUN
cana-2348	144	34	.	.	PUNCT
cana-2348	145	1	addressing	address	VERB
cana-2348	145	2	these	these	DET
cana-2348	145	3	research	research	NOUN
cana-2348	145	4	gaps	gap	NOUN
cana-2348	145	5	would	would	AUX
cana-2348	145	6	both	both	PRON
cana-2348	145	7	strengthen	strengthen	VERB
cana-2348	145	8	the	the	DET
cana-2348	145	9	current	current	ADJ
cana-2348	145	10	findings	finding	NOUN
cana-2348	145	11	and	and	CCONJ
cana-2348	145	12	foster	foster	VERB
cana-2348	145	13	the	the	DET
cana-2348	145	14	creation	creation	NOUN
cana-2348	145	15	of	of	ADP
cana-2348	145	16	more	more	ADV
cana-2348	145	17	robust	robust	ADJ
cana-2348	145	18	and	and	CCONJ
cana-2348	145	19	adaptable	adaptable	ADJ
cana-2348	145	20	deep	deep	ADJ
cana-2348	145	21	-	-	PUNCT
cana-2348	145	22	learning	learn	VERB
cana-2348	145	23	models	model	NOUN
cana-2348	145	24	for	for	ADP
cana-2348	145	25	asd	asd	PROPN
cana-2348	145	26	prediction	prediction	NOUN
cana-2348	145	27	,	,	PUNCT
cana-2348	145	28	fostering	foster	VERB
cana-2348	145	29	their	their	PRON
cana-2348	145	30	integration	integration	NOUN
cana-2348	145	31	into	into	ADP
cana-2348	145	32	clinical	clinical	ADJ
cana-2348	145	33	practice	practice	NOUN
cana-2348	145	34	and	and	CCONJ
cana-2348	145	35	improving	improve	VERB
cana-2348	145	36	the	the	DET
cana-2348	145	37	overall	overall	ADJ
cana-2348	145	38	understanding	understanding	NOUN
cana-2348	145	39	of	of	ADP
cana-2348	145	40	the	the	DET
cana-2348	145	41	disorder	disorder	NOUN
cana-2348	145	42	.	.	PUNCT
cana-2348	146	1	in	in	ADP
cana-2348	146	2	this	this	DET
cana-2348	146	3	study	study	NOUN
cana-2348	146	4	,	,	PUNCT
cana-2348	146	5	the	the	DET
cana-2348	146	6	models	model	NOUN
cana-2348	146	7	were	be	AUX
cana-2348	146	8	evaluated	evaluate	VERB
cana-2348	146	9	using	use	VERB
cana-2348	146	10	key	key	ADJ
cana-2348	146	11	performance	performance	NOUN
cana-2348	146	12	metrics	metric	NOUN
cana-2348	146	13	including	include	VERB
cana-2348	146	14	accuracy	accuracy	NOUN
cana-2348	146	15	,	,	PUNCT
cana-2348	146	16	precision	precision	NOUN
cana-2348	146	17	,	,	PUNCT
cana-2348	146	18	and	and	CCONJ
cana-2348	146	19	f1	f1	PROPN
cana-2348	146	20	score	score	NOUN
cana-2348	146	21	.	.	PUNCT
cana-2348	147	1	the	the	DET
cana-2348	147	2	results	result	NOUN
cana-2348	147	3	obtained	obtain	VERB
cana-2348	147	4	for	for	ADP
cana-2348	147	5	each	each	DET
cana-2348	147	6	architecture	architecture	NOUN
cana-2348	147	7	are	be	AUX
cana-2348	147	8	summarized	summarize	VERB
cana-2348	147	9	below	below	ADV
cana-2348	147	10	:	:	PUNCT
cana-2348	147	11	rnn	rnn	VERB
cana-2348	147	12	lstm	lstm	PROPN
cana-2348	147	13	gru	gru	PROPN
cana-2348	147	14	accuracy	accuracy	NOUN
cana-2348	147	15	70.78	70.78	NUM
cana-2348	147	16	%	%	NOUN
cana-2348	147	17	71.03	71.03	NUM
cana-2348	147	18	%	%	NOUN
cana-2348	147	19	70.78	70.78	NUM
cana-2348	147	20	%	%	NOUN
cana-2348	147	21	precision	precision	NOUN
cana-2348	147	22	63.41	63.41	NUM
cana-2348	147	23	%	%	NOUN
cana-2348	147	24	63.87	63.87	NUM
cana-2348	147	25	%	%	NOUN
cana-2348	147	26	63.41	63.41	NUM
cana-2348	147	27	%	%	NOUN
cana-2348	147	28	f1	f1	NOUN
cana-2348	147	29	score	score	NOUN
cana-2348	147	30	77.00	77.00	NUM
cana-2348	147	31	%	%	NOUN
cana-2348	147	32	77.50	77.50	NUM
cana-2348	147	33	%	%	NOUN
cana-2348	147	34	77.61	77.61	NUM
cana-2348	147	35	%	%	NOUN
cana-2348	147	36	table	table	NOUN
cana-2348	147	37	2	2	NUM
cana-2348	147	38	:	:	PUNCT
cana-2348	147	39	summary	summary	NOUN
cana-2348	147	40	results	result	VERB
cana-2348	147	41	communications	communication	NOUN
cana-2348	147	42	on	on	ADP
cana-2348	147	43	applied	apply	VERB
cana-2348	147	44	nonlinear	nonlinear	ADJ
cana-2348	147	45	analysis	analysis	NOUN
cana-2348	147	46	issn	issn	NOUN
cana-2348	147	47	:	:	PUNCT
cana-2348	147	48	1074	1074	NUM
cana-2348	147	49	-	-	PUNCT
cana-2348	147	50	133x	133x	NUM
cana-2348	147	51	vol	vol	NOUN
cana-2348	147	52	32	32	NUM
cana-2348	147	53	no	no	NOUN
cana-2348	147	54	.	.	NOUN
cana-2348	147	55	2	2	NUM
cana-2348	147	56	(	(	PUNCT
cana-2348	147	57	2025	2025	NUM
cana-2348	147	58	)	)	PUNCT
cana-2348	147	59	630	630	NUM
cana-2348	147	60	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	147	61	the	the	DET
cana-2348	147	62	lstm	lstm	PROPN
cana-2348	147	63	model	model	NOUN
cana-2348	147	64	achieved	achieve	VERB
cana-2348	147	65	the	the	DET
cana-2348	147	66	highest	high	ADJ
cana-2348	147	67	accuracy	accuracy	NOUN
cana-2348	147	68	among	among	ADP
cana-2348	147	69	the	the	DET
cana-2348	147	70	three	three	NUM
cana-2348	147	71	architectures	architecture	NOUN
cana-2348	147	72	,	,	PUNCT
cana-2348	147	73	closely	closely	ADV
cana-2348	147	74	followed	follow	VERB
cana-2348	147	75	by	by	ADP
cana-2348	147	76	gru	gru	PROPN
cana-2348	147	77	and	and	CCONJ
cana-2348	147	78	rnn	rnn	PROPN
cana-2348	147	79	.	.	PUNCT
cana-2348	148	1	the	the	DET
cana-2348	148	2	marginal	marginal	ADJ
cana-2348	148	3	differences	difference	NOUN
cana-2348	148	4	suggest	suggest	VERB
cana-2348	148	5	that	that	SCONJ
cana-2348	148	6	all	all	DET
cana-2348	148	7	models	model	NOUN
cana-2348	148	8	demonstrated	demonstrate	VERB
cana-2348	148	9	comparable	comparable	ADJ
cana-2348	148	10	overall	overall	ADJ
cana-2348	148	11	predictive	predictive	ADJ
cana-2348	148	12	performance	performance	NOUN
cana-2348	148	13	.	.	PUNCT
cana-2348	149	1	precision	precision	NOUN
cana-2348	149	2	assesses	assess	VERB
cana-2348	149	3	a	a	DET
cana-2348	149	4	model	model	NOUN
cana-2348	149	5	's	's	PART
cana-2348	149	6	effectiveness	effectiveness	NOUN
cana-2348	149	7	in	in	ADP
cana-2348	149	8	accurately	accurately	ADV
cana-2348	149	9	identifying	identify	VERB
cana-2348	149	10	positive	positive	ADJ
cana-2348	149	11	cases	case	NOUN
cana-2348	149	12	.	.	PUNCT
cana-2348	150	1	the	the	DET
cana-2348	150	2	proportion	proportion	NOUN
cana-2348	150	3	of	of	ADP
cana-2348	150	4	true	true	ADJ
cana-2348	150	5	positive	positive	ADJ
cana-2348	150	6	predictions	prediction	NOUN
cana-2348	150	7	to	to	ADP
cana-2348	150	8	the	the	DET
cana-2348	150	9	total	total	ADJ
cana-2348	150	10	number	number	NOUN
cana-2348	150	11	of	of	ADP
cana-2348	150	12	predicted	predict	VERB
cana-2348	150	13	positive	positive	ADJ
cana-2348	150	14	outcomes	outcome	NOUN
cana-2348	150	15	is	be	AUX
cana-2348	150	16	represented	represent	VERB
cana-2348	150	17	by	by	ADP
cana-2348	150	18	it	it	PRON
cana-2348	150	19	.	.	PUNCT
cana-2348	151	1	the	the	DET
cana-2348	151	2	model	model	NOUN
cana-2348	151	3	's	's	PART
cana-2348	151	4	precision	precision	NOUN
cana-2348	151	5	in	in	ADP
cana-2348	151	6	predicting	predict	VERB
cana-2348	151	7	a	a	DET
cana-2348	151	8	favorable	favorable	ADJ
cana-2348	151	9	outcome	outcome	NOUN
cana-2348	151	10	is	be	AUX
cana-2348	151	11	evaluated	evaluate	VERB
cana-2348	151	12	by	by	ADP
cana-2348	151	13	measuring	measure	VERB
cana-2348	151	14	the	the	DET
cana-2348	151	15	accuracy	accuracy	NOUN
cana-2348	151	16	of	of	ADP
cana-2348	151	17	positive	positive	ADJ
cana-2348	151	18	predictions	prediction	NOUN
cana-2348	151	19	.	.	PUNCT
cana-2348	152	1	the	the	DET
cana-2348	152	2	lstm	lstm	PROPN
cana-2348	152	3	and	and	CCONJ
cana-2348	152	4	gru	gru	NOUN
cana-2348	152	5	models	model	NOUN
cana-2348	152	6	exhibited	exhibit	VERB
cana-2348	152	7	slightly	slightly	ADV
cana-2348	152	8	higher	high	ADJ
cana-2348	152	9	precision	precision	NOUN
cana-2348	152	10	compared	compare	VERB
cana-2348	152	11	to	to	ADP
cana-2348	152	12	the	the	DET
cana-2348	152	13	rnn	rnn	NOUN
cana-2348	152	14	model	model	NOUN
cana-2348	152	15	.	.	PUNCT
cana-2348	153	1	a	a	DET
cana-2348	153	2	thorough	thorough	ADJ
cana-2348	153	3	assessment	assessment	NOUN
cana-2348	153	4	of	of	ADP
cana-2348	153	5	a	a	DET
cana-2348	153	6	model	model	NOUN
cana-2348	153	7	’s	’s	PART
cana-2348	153	8	performance	performance	NOUN
cana-2348	153	9	is	be	AUX
cana-2348	153	10	provided	provide	VERB
cana-2348	153	11	by	by	ADP
cana-2348	153	12	the	the	DET
cana-2348	153	13	f1	f1	PROPN
cana-2348	153	14	score	score	NOUN
cana-2348	153	15	,	,	PUNCT
cana-2348	153	16	which	which	PRON
cana-2348	153	17	takes	take	VERB
cana-2348	153	18	into	into	ADP
cana-2348	153	19	account	account	NOUN
cana-2348	153	20	both	both	DET
cana-2348	153	21	precision	precision	NOUN
cana-2348	153	22	and	and	CCONJ
cana-2348	153	23	recall	recall	NOUN
cana-2348	153	24	.	.	PUNCT
cana-2348	154	1	all	all	DET
cana-2348	154	2	three	three	NUM
cana-2348	154	3	models	model	NOUN
cana-2348	154	4	demonstrated	demonstrate	VERB
cana-2348	154	5	high	high	ADJ
cana-2348	154	6	f1	f1	NOUN
cana-2348	154	7	scores	score	NOUN
cana-2348	154	8	,	,	PUNCT
cana-2348	154	9	indicating	indicate	VERB
cana-2348	154	10	an	an	DET
cana-2348	154	11	effective	effective	ADJ
cana-2348	154	12	balance	balance	NOUN
cana-2348	154	13	between	between	ADP
cana-2348	154	14	precision	precision	NOUN
cana-2348	154	15	and	and	CCONJ
cana-2348	154	16	recall	recall	NOUN
cana-2348	154	17	.	.	PUNCT
cana-2348	155	1	to	to	PART
cana-2348	155	2	offer	offer	VERB
cana-2348	155	3	a	a	DET
cana-2348	155	4	visual	visual	ADJ
cana-2348	155	5	representation	representation	NOUN
cana-2348	155	6	of	of	ADP
cana-2348	155	7	the	the	DET
cana-2348	155	8	comparative	comparative	ADJ
cana-2348	155	9	results	result	NOUN
cana-2348	155	10	,	,	PUNCT
cana-2348	155	11	the	the	DET
cana-2348	155	12	following	follow	VERB
cana-2348	155	13	chart	chart	NOUN
cana-2348	155	14	illustrates	illustrate	VERB
cana-2348	155	15	the	the	DET
cana-2348	155	16	performance	performance	NOUN
cana-2348	155	17	metrics	metric	NOUN
cana-2348	155	18	achieved	achieve	VERB
cana-2348	155	19	by	by	ADP
cana-2348	155	20	the	the	DET
cana-2348	155	21	rnn	rnn	PROPN
cana-2348	155	22	,	,	PUNCT
cana-2348	155	23	lstm	lstm	ADJ
cana-2348	155	24	,	,	PUNCT
cana-2348	155	25	and	and	CCONJ
cana-2348	155	26	gru	gru	NOUN
cana-2348	155	27	models	model	NOUN
cana-2348	155	28	.	.	PUNCT
cana-2348	156	1	this	this	DET
cana-2348	156	2	chart	chart	NOUN
cana-2348	156	3	aims	aim	VERB
cana-2348	156	4	to	to	PART
cana-2348	156	5	provide	provide	VERB
cana-2348	156	6	an	an	DET
cana-2348	156	7	overview	overview	NOUN
cana-2348	156	8	and	and	CCONJ
cana-2348	156	9	facilitate	facilitate	VERB
cana-2348	156	10	a	a	DET
cana-2348	156	11	more	more	ADV
cana-2348	156	12	intuitive	intuitive	ADJ
cana-2348	156	13	understanding	understanding	NOUN
cana-2348	156	14	of	of	ADP
cana-2348	156	15	the	the	DET
cana-2348	156	16	comparative	comparative	ADJ
cana-2348	156	17	analysis	analysis	NOUN
cana-2348	156	18	.	.	PUNCT
cana-2348	157	1	figure	figure	NOUN
cana-2348	157	2	4	4	NUM
cana-2348	157	3	:	:	PUNCT
cana-2348	157	4	performane	performane	VERB
cana-2348	157	5	comparison	comparison	NOUN
cana-2348	157	6	of	of	ADP
cana-2348	157	7	rnn	rnn	PROPN
cana-2348	157	8	,	,	PUNCT
cana-2348	157	9	lstm	lstm	NOUN
cana-2348	157	10	,	,	PUNCT
cana-2348	157	11	and	and	CCONJ
cana-2348	157	12	gru	gru	VERB
cana-2348	157	13	v.	v.	ADP
cana-2348	157	14	conclusion	conclusion	NOUN
cana-2348	157	15	in	in	ADP
cana-2348	157	16	this	this	DET
cana-2348	157	17	study	study	NOUN
cana-2348	157	18	,	,	PUNCT
cana-2348	157	19	we	we	PRON
cana-2348	157	20	conducted	conduct	VERB
cana-2348	157	21	a	a	DET
cana-2348	157	22	comprehensive	comprehensive	ADJ
cana-2348	157	23	comparison	comparison	NOUN
cana-2348	157	24	of	of	ADP
cana-2348	157	25	three	three	NUM
cana-2348	157	26	recurrent	recurrent	ADJ
cana-2348	157	27	neural	neural	ADJ
cana-2348	157	28	network	network	NOUN
cana-2348	157	29	architectures	architecture	NOUN
cana-2348	157	30	,	,	PUNCT
cana-2348	157	31	lstm	lstm	NOUN
cana-2348	157	32	and	and	CCONJ
cana-2348	157	33	gru	gru	NOUN
cana-2348	157	34	-	-	PUNCT
cana-2348	157	35	for	for	ADP
cana-2348	157	36	the	the	DET
cana-2348	157	37	task	task	NOUN
cana-2348	157	38	of	of	ADP
cana-2348	157	39	autism	autism	NOUN
cana-2348	157	40	prediction	prediction	NOUN
cana-2348	157	41	.	.	PUNCT
cana-2348	158	1	across	across	ADP
cana-2348	158	2	the	the	DET
cana-2348	158	3	performance	performance	NOUN
cana-2348	158	4	metrics	metric	NOUN
cana-2348	158	5	,	,	PUNCT
cana-2348	158	6	the	the	DET
cana-2348	158	7	lstm	lstm	PROPN
cana-2348	158	8	and	and	CCONJ
cana-2348	158	9	gru	gru	NOUN
cana-2348	158	10	models	model	NOUN
cana-2348	158	11	exhibited	exhibit	VERB
cana-2348	158	12	similar	similar	ADJ
cana-2348	158	13	accuracy	accuracy	NOUN
cana-2348	158	14	,	,	PUNCT
cana-2348	158	15	with	with	ADP
cana-2348	158	16	values	value	NOUN
cana-2348	158	17	of	of	ADP
cana-2348	158	18	71.03	71.03	NUM
cana-2348	158	19	%	%	NOUN
cana-2348	158	20	and	and	CCONJ
cana-2348	158	21	70.78	70.78	NUM
cana-2348	158	22	%	%	NOUN
cana-2348	158	23	,	,	PUNCT
cana-2348	158	24	respectively	respectively	ADV
cana-2348	158	25	.	.	PUNCT
cana-2348	159	1	the	the	DET
cana-2348	159	2	f1	f1	PROPN
cana-2348	159	3	scores	score	NOUN
cana-2348	159	4	were	be	AUX
cana-2348	159	5	close	close	ADJ
cana-2348	159	6	,	,	PUNCT
cana-2348	159	7	with	with	ADP
cana-2348	159	8	lstm	lstm	NOUN
cana-2348	159	9	leading	lead	VERB
cana-2348	159	10	at	at	ADP
cana-2348	159	11	77.50	77.50	NUM
cana-2348	159	12	%	%	NOUN
cana-2348	159	13	and	and	CCONJ
cana-2348	159	14	gru	gru	NOUN
cana-2348	159	15	following	follow	VERB
cana-2348	159	16	closely	closely	ADV
cana-2348	159	17	at	at	ADP
cana-2348	159	18	77.61	77.61	NUM
cana-2348	159	19	%	%	NOUN
cana-2348	159	20	.	.	PUNCT
cana-2348	160	1	precision	precision	NOUN
cana-2348	160	2	scores	score	NOUN
cana-2348	160	3	were	be	AUX
cana-2348	160	4	also	also	ADV
cana-2348	160	5	comparable	comparable	ADJ
cana-2348	160	6	,	,	PUNCT
cana-2348	160	7	with	with	ADP
cana-2348	160	8	lstm	lstm	NOUN
cana-2348	160	9	slightly	slightly	ADV
cana-2348	160	10	outperforming	outperform	VERB
cana-2348	160	11	the	the	DET
cana-2348	160	12	other	other	ADJ
cana-2348	160	13	models	model	NOUN
cana-2348	160	14	at	at	ADP
cana-2348	160	15	63.87	63.87	NUM
cana-2348	160	16	%	%	NOUN
cana-2348	160	17	.	.	PUNCT
cana-2348	161	1	our	our	PRON
cana-2348	161	2	research	research	NOUN
cana-2348	161	3	extends	extend	VERB
cana-2348	161	4	to	to	ADP
cana-2348	161	5	the	the	DET
cana-2348	161	6	body	body	NOUN
cana-2348	161	7	of	of	ADP
cana-2348	161	8	knowledge	knowledge	NOUN
cana-2348	161	9	by	by	ADP
cana-2348	161	10	providing	provide	VERB
cana-2348	161	11	insight	insight	NOUN
cana-2348	161	12	into	into	ADP
cana-2348	161	13	whether	whether	SCONJ
cana-2348	161	14	deep	deep	ADJ
cana-2348	161	15	learning	learning	NOUN
cana-2348	161	16	techniques	technique	NOUN
cana-2348	161	17	are	be	AUX
cana-2348	161	18	appropriate	appropriate	ADJ
cana-2348	161	19	for	for	ADP
cana-2348	161	20	predicting	predict	VERB
cana-2348	161	21	autism	autism	NOUN
cana-2348	161	22	.	.	PUNCT
cana-2348	162	1	future	future	ADJ
cana-2348	162	2	research	research	NOUN
cana-2348	162	3	could	could	AUX
cana-2348	162	4	explore	explore	VERB
cana-2348	162	5	hybrid	hybrid	ADJ
cana-2348	162	6	models	model	NOUN
cana-2348	162	7	,	,	PUNCT
cana-2348	162	8	hyperparameter	hyperparameter	NOUN
cana-2348	162	9	tuning	tuning	NOUN
cana-2348	162	10	,	,	PUNCT
cana-2348	162	11	and	and	CCONJ
cana-2348	162	12	the	the	DET
cana-2348	162	13	inclusion	inclusion	NOUN
cana-2348	162	14	of	of	ADP
cana-2348	162	15	additional	additional	ADJ
cana-2348	162	16	features	feature	NOUN
cana-2348	162	17	to	to	PART
cana-2348	162	18	further	far	ADV
cana-2348	162	19	enhance	enhance	VERB
cana-2348	162	20	predictive	predictive	ADJ
cana-2348	162	21	performance	performance	NOUN
cana-2348	162	22	.	.	PUNCT
cana-2348	163	1	despite	despite	SCONJ
cana-2348	163	2	the	the	DET
cana-2348	163	3	results	result	NOUN
cana-2348	163	4	,	,	PUNCT
cana-2348	163	5	this	this	DET
cana-2348	163	6	study	study	NOUN
cana-2348	163	7	has	have	VERB
cana-2348	163	8	limitations	limitation	NOUN
cana-2348	163	9	,	,	PUNCT
cana-2348	163	10	communications	communication	NOUN
cana-2348	163	11	on	on	ADP
cana-2348	163	12	applied	apply	VERB
cana-2348	163	13	nonlinear	nonlinear	ADJ
cana-2348	163	14	analysis	analysis	NOUN
cana-2348	163	15	issn	issn	NOUN
cana-2348	163	16	:	:	PUNCT
cana-2348	163	17	1074	1074	NUM
cana-2348	163	18	-	-	PUNCT
cana-2348	163	19	133x	133x	NUM
cana-2348	163	20	vol	vol	NOUN
cana-2348	163	21	32	32	NUM
cana-2348	163	22	no	no	NOUN
cana-2348	163	23	.	.	NOUN
cana-2348	163	24	2	2	NUM
cana-2348	163	25	(	(	PUNCT
cana-2348	163	26	2025	2025	NUM
cana-2348	163	27	)	)	PUNCT
cana-2348	163	28	631	631	NUM
cana-2348	163	29	https://internationalpubls.com	https://internationalpubls.com	X
cana-2348	163	30	including	include	VERB
cana-2348	163	31	the	the	DET
cana-2348	163	32	reliance	reliance	NOUN
cana-2348	163	33	on	on	ADP
cana-2348	163	34	a	a	DET
cana-2348	163	35	specific	specific	ADJ
cana-2348	163	36	dataset	dataset	NOUN
cana-2348	163	37	and	and	CCONJ
cana-2348	163	38	potential	potential	ADJ
cana-2348	163	39	biases	bias	NOUN
cana-2348	163	40	inherent	inherent	ADJ
cana-2348	163	41	in	in	ADP
cana-2348	163	42	the	the	DET
cana-2348	163	43	data	datum	NOUN
cana-2348	163	44	.	.	PUNCT
cana-2348	164	1	our	our	PRON
cana-2348	164	2	comparative	comparative	ADJ
cana-2348	164	3	analysis	analysis	NOUN
cana-2348	164	4	offers	offer	VERB
cana-2348	164	5	valuable	valuable	ADJ
cana-2348	164	6	insights	insight	NOUN
cana-2348	164	7	into	into	ADP
cana-2348	164	8	the	the	DET
cana-2348	164	9	performance	performance	NOUN
cana-2348	164	10	of	of	ADP
cana-2348	164	11	rnn	rnn	PROPN
cana-2348	164	12	,	,	PUNCT
cana-2348	164	13	lstm	lstm	NOUN
cana-2348	164	14	,	,	PUNCT
cana-2348	164	15	and	and	CCONJ
cana-2348	164	16	gru	gru	NOUN
cana-2348	164	17	models	model	NOUN
cana-2348	164	18	for	for	ADP
cana-2348	164	19	autism	autism	NOUN
cana-2348	164	20	prediction	prediction	NOUN
cana-2348	164	21	.	.	PUNCT
cana-2348	165	1	the	the	DET
cana-2348	165	2	findings	finding	NOUN
cana-2348	165	3	contribute	contribute	VERB
cana-2348	165	4	to	to	ADP
cana-2348	165	5	the	the	DET
cana-2348	165	6	knowledge	knowledge	NOUN
cana-2348	165	7	enhancement	enhancement	NOUN
cana-2348	165	8	in	in	ADP
cana-2348	165	9	the	the	DET
cana-2348	165	10	application	application	NOUN
cana-2348	165	11	of	of	ADP
cana-2348	165	12	deep	deep	ADJ
cana-2348	165	13	learning	learning	NOUN
cana-2348	165	14	in	in	ADP
cana-2348	165	15	healthcare	healthcare	NOUN
cana-2348	165	16	and	and	CCONJ
cana-2348	165	17	lay	lie	VERB
cana-2348	165	18	for	for	ADP
cana-2348	165	19	future	future	ADJ
cana-2348	165	20	advancements	advancement	NOUN
cana-2348	165	21	in	in	ADP
cana-2348	165	22	this	this	DET
cana-2348	165	23	field	field	NOUN
cana-2348	165	24	.	.	PUNCT
cana-2348	166	1	references	reference	NOUN
cana-2348	166	2	[	[	X
cana-2348	166	3	1	1	NUM
cana-2348	166	4	]	]	X
cana-2348	166	5	metcalfe	metcalfe	PROPN
cana-2348	166	6	,	,	PUNCT
cana-2348	166	7	d.	d.	PROPN
cana-2348	166	8	,	,	PUNCT
cana-2348	166	9	mckenzie	mckenzie	PROPN
cana-2348	166	10	,	,	PUNCT
cana-2348	166	11	k.	k.	PROPN
cana-2348	166	12	,	,	PUNCT
cana-2348	166	13	mccarty	mccarty	PROPN
cana-2348	166	14	,	,	PUNCT
cana-2348	166	15	k.	k.	PROPN
cana-2348	166	16	,	,	PUNCT
cana-2348	166	17	&	&	CCONJ
cana-2348	166	18	murray	murray	PROPN
cana-2348	166	19	,	,	PUNCT
cana-2348	166	20	g.	g.	PROPN
cana-2348	166	21	(	(	PUNCT
cana-2348	166	22	2020	2020	NUM
cana-2348	166	23	)	)	PUNCT
cana-2348	166	24	.	.	PUNCT
cana-2348	167	1	screening	screen	VERB
cana-2348	167	2	tools	tool	NOUN
cana-2348	167	3	for	for	ADP
cana-2348	167	4	autism	autism	NOUN
cana-2348	167	5	spectrum	spectrum	NOUN
cana-2348	167	6	disorder	disorder	NOUN
cana-2348	167	7	,	,	PUNCT
cana-2348	167	8	used	use	VERB
cana-2348	167	9	with	with	ADP
cana-2348	167	10	people	people	NOUN
cana-2348	167	11	with	with	ADP
cana-2348	167	12	an	an	DET
cana-2348	167	13	intellectual	intellectual	ADJ
cana-2348	167	14	disability	disability	NOUN
cana-2348	167	15	:	:	PUNCT
cana-2348	167	16	a	a	DET
cana-2348	167	17	systematic	systematic	ADJ
cana-2348	167	18	review	review	NOUN
cana-2348	167	19	.	.	PUNCT
cana-2348	168	1	research	research	NOUN
cana-2348	168	2	in	in	ADP
cana-2348	168	3	autism	autism	NOUN
cana-2348	168	4	spectrum	spectrum	NOUN
cana-2348	168	5	disorders	disorder	NOUN
cana-2348	168	6	,	,	PUNCT
cana-2348	168	7	74	74	NUM
cana-2348	168	8	.	.	PUNCT
cana-2348	169	1	[	[	X
cana-2348	169	2	2	2	NUM
cana-2348	169	3	]	]	PUNCT
cana-2348	169	4	robins	robin	NOUN
cana-2348	169	5	,	,	PUNCT
cana-2348	169	6	d.	d.	PROPN
cana-2348	169	7	l.	l.	PROPN
cana-2348	169	8	(	(	PUNCT
cana-2348	169	9	2008	2008	NUM
cana-2348	169	10	)	)	PUNCT
cana-2348	169	11	.	.	PUNCT
cana-2348	170	1	screening	screen	VERB
cana-2348	170	2	for	for	ADP
cana-2348	170	3	autism	autism	NOUN
cana-2348	170	4	spectrum	spectrum	NOUN
cana-2348	170	5	disorders	disorder	NOUN
cana-2348	170	6	in	in	ADP
cana-2348	170	7	primary	primary	ADJ
cana-2348	170	8	care	care	NOUN
cana-2348	170	9	settings	setting	NOUN
cana-2348	170	10	.	.	PUNCT
cana-2348	171	1	international	international	ADJ
cana-2348	171	2	journal	journal	PROPN
cana-2348	171	3	of	of	ADP
cana-2348	171	4	research	research	NOUN
cana-2348	171	5	and	and	CCONJ
cana-2348	171	6	practice	practice	NOUN
cana-2348	171	7	,	,	PUNCT
cana-2348	171	8	12(5	12(5	NUM
cana-2348	171	9	)	)	PUNCT
cana-2348	171	10	,	,	PUNCT
cana-2348	171	11	537	537	NUM
cana-2348	171	12	-	-	SYM
cana-2348	171	13	556	556	NUM
cana-2348	171	14	.	.	PUNCT
cana-2348	172	1	[	[	X
cana-2348	172	2	3	3	NUM
cana-2348	172	3	]	]	X
cana-2348	172	4	bridgemohan	bridgemohan	NOUN
cana-2348	172	5	,	,	PUNCT
cana-2348	172	6	c.	c.	NOUN
cana-2348	172	7	,	,	PUNCT
cana-2348	172	8	cochran	cochran	PROPN
cana-2348	172	9	,	,	PUNCT
cana-2348	172	10	d.	d.	PROPN
cana-2348	172	11	m.	m.	PROPN
cana-2348	172	12	,	,	PUNCT
cana-2348	172	13	&	&	CCONJ
cana-2348	172	14	howe	howe	PROPN
cana-2348	172	15	,	,	PUNCT
cana-2348	172	16	y.	y.	PROPN
cana-2348	172	17	j.	j.	PROPN
cana-2348	172	18	(	(	PUNCT
cana-2348	172	19	2019	2019	NUM
cana-2348	172	20	)	)	PUNCT
cana-2348	172	21	.	.	PUNCT
cana-2348	173	1	investigating	investigate	VERB
cana-2348	173	2	potential	potential	ADJ
cana-2348	173	3	biomarkers	biomarker	NOUN
cana-2348	173	4	in	in	ADP
cana-2348	173	5	autism	autism	NOUN
cana-2348	173	6	spectrum	spectrum	NOUN
cana-2348	173	7	disorder	disorder	NOUN
cana-2348	173	8	.	.	PUNCT
cana-2348	174	1	frontiers	frontier	NOUN
cana-2348	174	2	in	in	ADP
cana-2348	174	3	integrative	integrative	ADJ
cana-2348	174	4	neuroscience	neuroscience	NOUN
cana-2348	174	5	,	,	PUNCT
cana-2348	174	6	13(31	13(31	NUM
cana-2348	174	7	)	)	PUNCT
cana-2348	174	8	.	.	PUNCT
cana-2348	175	1	[	[	X
cana-2348	175	2	4	4	NUM
cana-2348	175	3	]	]	X
cana-2348	175	4	vaishali	vaishali	PROPN
cana-2348	175	5	,	,	PUNCT
cana-2348	175	6	r.	r.	PROPN
cana-2348	175	7	,	,	PUNCT
cana-2348	175	8	&	&	CCONJ
cana-2348	175	9	sasikala	sasikala	PROPN
cana-2348	175	10	,	,	PUNCT
cana-2348	175	11	r.	r.	PROPN
cana-2348	175	12	(	(	PUNCT
cana-2348	175	13	2018	2018	NUM
cana-2348	175	14	)	)	PUNCT
cana-2348	175	15	.	.	PUNCT
cana-2348	176	1	a	a	DET
cana-2348	176	2	machine	machine	NOUN
cana-2348	176	3	learning	learning	NOUN
cana-2348	176	4	-	-	PUNCT
cana-2348	176	5	based	base	VERB
cana-2348	176	6	approach	approach	NOUN
cana-2348	176	7	to	to	PART
cana-2348	176	8	classify	classify	VERB
cana-2348	176	9	autism	autism	NOUN
cana-2348	176	10	with	with	ADP
cana-2348	176	11	optimum	optimum	ADJ
cana-2348	176	12	behavior	behavior	NOUN
cana-2348	176	13	sets	set	NOUN
cana-2348	176	14	.	.	PUNCT
cana-2348	177	1	international	international	ADJ
cana-2348	177	2	journal	journal	NOUN
cana-2348	177	3	of	of	ADP
cana-2348	177	4	engineering	engineering	PROPN
cana-2348	177	5	&	&	CCONJ
cana-2348	177	6	technology	technology	PROPN
cana-2348	177	7	,	,	PUNCT
cana-2348	177	8	7(4	7(4	NUM
cana-2348	177	9	)	)	PUNCT
cana-2348	177	10	,	,	PUNCT
cana-2348	177	11	18	18	NUM
cana-2348	177	12	.	.	PUNCT
cana-2348	178	1	[	[	X
cana-2348	178	2	5	5	NUM
cana-2348	178	3	]	]	X
cana-2348	178	4	mythili	mythili	NOUN
cana-2348	178	5	,	,	PUNCT
cana-2348	178	6	m.	m.	NOUN
cana-2348	178	7	s.	s.	PROPN
cana-2348	178	8	,	,	PUNCT
cana-2348	178	9	&	&	CCONJ
cana-2348	178	10	mohamed	mohamed	PROPN
cana-2348	178	11	shanavas	shanavas	PROPN
cana-2348	178	12	,	,	PUNCT
cana-2348	178	13	a.	a.	PROPN
cana-2348	178	14	r.	r.	PROPN
cana-2348	178	15	(	(	PUNCT
cana-2348	178	16	2014	2014	NUM
cana-2348	178	17	)	)	PUNCT
cana-2348	178	18	.	.	PUNCT
cana-2348	179	1	a	a	DET
cana-2348	179	2	study	study	NOUN
cana-2348	179	3	on	on	ADP
cana-2348	179	4	autism	autism	NOUN
cana-2348	179	5	spectrum	spectrum	NOUN
cana-2348	179	6	disorders	disorder	NOUN
cana-2348	179	7	using	use	VERB
cana-2348	179	8	classification	classification	NOUN
cana-2348	179	9	techniques	technique	NOUN
cana-2348	179	10	.	.	PUNCT
cana-2348	180	1	international	international	ADJ
cana-2348	180	2	journal	journal	NOUN
cana-2348	180	3	of	of	ADP
cana-2348	180	4	soft	soft	ADJ
cana-2348	180	5	computing	computing	NOUN
cana-2348	180	6	and	and	CCONJ
cana-2348	180	7	engineering	engineering	NOUN
cana-2348	180	8	(	(	PUNCT
cana-2348	180	9	ijsce	ijsce	INTJ
cana-2348	180	10	)	)	PUNCT
cana-2348	180	11	,	,	PUNCT
cana-2348	180	12	4	4	NUM
cana-2348	180	13	,	,	PUNCT
cana-2348	180	14	88	88	NUM
cana-2348	180	15	-	-	SYM
cana-2348	180	16	91	91	NUM
cana-2348	180	17	.	.	PUNCT
cana-2348	181	1	[	[	X
cana-2348	181	2	6	6	NUM
cana-2348	181	3	]	]	X
cana-2348	181	4	hossain	hossain	PROPN
cana-2348	181	5	,	,	PUNCT
cana-2348	181	6	m.	m.	PROPN
cana-2348	181	7	d.	d.	PROPN
cana-2348	181	8	,	,	PUNCT
cana-2348	181	9	kabir	kabir	PROPN
cana-2348	181	10	,	,	PUNCT
cana-2348	181	11	m.	m.	NOUN
cana-2348	181	12	a.	a.	PROPN
cana-2348	181	13	,	,	PUNCT
cana-2348	181	14	anwar	anwar	PROPN
cana-2348	181	15	,	,	PUNCT
cana-2348	181	16	a.	a.	PROPN
cana-2348	181	17	,	,	PUNCT
cana-2348	181	18	&	&	CCONJ
cana-2348	181	19	islam	islam	PROPN
cana-2348	181	20	,	,	PUNCT
cana-2348	181	21	m.	m.	NOUN
cana-2348	181	22	z.	z.	PROPN
cana-2348	181	23	(	(	PUNCT
cana-2348	181	24	2021	2021	NUM
cana-2348	181	25	)	)	PUNCT
cana-2348	181	26	.	.	PUNCT
cana-2348	182	1	detecting	detect	VERB
cana-2348	182	2	autism	autism	NOUN
cana-2348	182	3	spectrum	spectrum	NOUN
cana-2348	182	4	disorder	disorder	NOUN
cana-2348	182	5	using	use	VERB
cana-2348	182	6	machine	machine	NOUN
cana-2348	182	7	learning	learn	VERB
cana-2348	182	8	techniques	technique	NOUN
cana-2348	182	9	.	.	PUNCT
cana-2348	183	1	health	health	NOUN
cana-2348	183	2	information	information	NOUN
cana-2348	183	3	science	science	NOUN
cana-2348	183	4	and	and	CCONJ
cana-2348	183	5	systems	system	NOUN
cana-2348	183	6	,	,	PUNCT
cana-2348	183	7	9(1	9(1	NUM
cana-2348	183	8	)	)	PUNCT
cana-2348	183	9	.	.	PUNCT
cana-2348	184	1	https://doi.org/10.1007/s13755-02100145-9	https://doi.org/10.1007/s13755-02100145-9	PROPN
cana-2348	185	1	[	[	X
cana-2348	185	2	7	7	NUM
cana-2348	185	3	]	]	X
cana-2348	185	4	alam	alam	PROPN
cana-2348	185	5	,	,	PUNCT
cana-2348	185	6	m.	m.	NOUN
cana-2348	185	7	s.	s.	PROPN
cana-2348	185	8	,	,	PUNCT
cana-2348	185	9	rashid	rashid	PROPN
cana-2348	185	10	,	,	PUNCT
cana-2348	185	11	m.	m.	NOUN
cana-2348	185	12	m.	m.	NOUN
cana-2348	185	13	,	,	PUNCT
cana-2348	185	14	faizabadi	faizabadi	NOUN
cana-2348	185	15	,	,	PUNCT
cana-2348	185	16	a.	a.	PROPN
cana-2348	185	17	r.	r.	PROPN
cana-2348	185	18	,	,	PUNCT
cana-2348	185	19	mohd	mohd	PROPN
cana-2348	185	20	zaki	zaki	PROPN
cana-2348	185	21	,	,	PUNCT
cana-2348	185	22	h.	h.	PROPN
cana-2348	185	23	f.	f.	PROPN
cana-2348	185	24	,	,	PUNCT
cana-2348	185	25	alam	alam	PROPN
cana-2348	185	26	,	,	PUNCT
cana-2348	185	27	t.	t.	PROPN
cana-2348	185	28	e.	e.	PROPN
cana-2348	185	29	,	,	PUNCT
cana-2348	185	30	ali	ali	PROPN
cana-2348	185	31	,	,	PUNCT
cana-2348	185	32	m.	m.	PROPN
cana-2348	185	33	s.	s.	PROPN
cana-2348	185	34	,	,	PUNCT
cana-2348	185	35	gupta	gupta	PROPN
cana-2348	185	36	,	,	PUNCT
cana-2348	185	37	k.	k.	PROPN
cana-2348	185	38	d.	d.	PROPN
cana-2348	185	39	,	,	PUNCT
cana-2348	185	40	&	&	CCONJ
cana-2348	185	41	ahsan	ahsan	PROPN
cana-2348	185	42	,	,	PUNCT
cana-2348	185	43	m.	m.	NOUN
cana-2348	185	44	m.	m.	NOUN
cana-2348	185	45	(	(	PUNCT
cana-2348	185	46	2023	2023	NUM
cana-2348	185	47	)	)	PUNCT
cana-2348	185	48	.	.	PUNCT
cana-2348	186	1	efficient	efficient	ADJ
cana-2348	186	2	deep	deep	ADJ
cana-2348	186	3	learning	learning	NOUN
cana-2348	186	4	-	-	PUNCT
cana-2348	186	5	based	base	VERB
cana-2348	186	6	data	data	NOUN
cana-2348	186	7	-	-	PUNCT
cana-2348	186	8	centric	centric	ADJ
cana-2348	186	9	approach	approach	NOUN
cana-2348	186	10	for	for	ADP
cana-2348	186	11	autism	autism	NOUN
cana-2348	186	12	spectrum	spectrum	NOUN
cana-2348	186	13	disorder	disorder	NOUN
cana-2348	186	14	diagnosis	diagnosis	NOUN
cana-2348	186	15	from	from	ADP
cana-2348	186	16	facial	facial	ADJ
cana-2348	186	17	images	image	NOUN
cana-2348	186	18	using	use	VERB
cana-2348	186	19	explainable	explainable	ADJ
cana-2348	186	20	ai	ai	NOUN
cana-2348	186	21	.	.	PUNCT
cana-2348	187	1	technologies	technology	NOUN
cana-2348	187	2	,	,	PUNCT
cana-2348	187	3	11	11	NUM
cana-2348	187	4	,	,	PUNCT
cana-2348	187	5	115	115	NUM
cana-2348	187	6	.	.	PUNCT
cana-2348	188	1	https://doi.org/10.3390/technologies11050115	https://doi.org/10.3390/technologies11050115	PROPN
cana-2348	189	1	[	[	X
cana-2348	189	2	8	8	NUM
cana-2348	189	3	]	]	X
cana-2348	189	4	kang	kang	PROPN
cana-2348	189	5	,	,	PUNCT
cana-2348	189	6	j.	j.	PROPN
cana-2348	189	7	,	,	PUNCT
cana-2348	189	8	han	han	PROPN
cana-2348	189	9	,	,	PUNCT
cana-2348	189	10	x.	x.	NOUN
cana-2348	189	11	,	,	PUNCT
cana-2348	189	12	song	song	NOUN
cana-2348	189	13	,	,	PUNCT
cana-2348	189	14	j.	j.	PROPN
cana-2348	189	15	,	,	PUNCT
cana-2348	189	16	niu	niu	PROPN
cana-2348	189	17	,	,	PUNCT
cana-2348	189	18	z.	z.	PROPN
cana-2348	189	19	,	,	PUNCT
cana-2348	189	20	&	&	CCONJ
cana-2348	189	21	li	li	PROPN
cana-2348	189	22	,	,	PUNCT
cana-2348	189	23	x.	x.	PROPN
cana-2348	189	24	(	(	PUNCT
cana-2348	189	25	2020	2020	NUM
cana-2348	189	26	)	)	PUNCT
cana-2348	189	27	.	.	PUNCT
cana-2348	190	1	the	the	DET
cana-2348	190	2	identification	identification	NOUN
cana-2348	190	3	of	of	ADP
cana-2348	190	4	children	child	NOUN
cana-2348	190	5	with	with	ADP
cana-2348	190	6	autism	autism	NOUN
cana-2348	190	7	spectrum	spectrum	NOUN
cana-2348	190	8	disorder	disorder	NOUN
cana-2348	190	9	by	by	ADP
cana-2348	190	10	svm	svm	ADJ
cana-2348	190	11	approach	approach	NOUN
cana-2348	190	12	on	on	ADP
cana-2348	190	13	eeg	eeg	PROPN
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cana-2348	190	15	eye	eye	NOUN
cana-2348	190	16	-	-	PUNCT
cana-2348	190	17	tracking	track	VERB
cana-2348	190	18	data	datum	NOUN
cana-2348	190	19	.	.	PUNCT
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cana-2348	191	2	in	in	ADP
cana-2348	191	3	biology	biology	NOUN
cana-2348	191	4	and	and	CCONJ
cana-2348	191	5	medicine	medicine	NOUN
cana-2348	191	6	,	,	PUNCT
cana-2348	191	7	120	120	NUM
cana-2348	191	8	,	,	PUNCT
cana-2348	191	9	1	1	NUM
cana-2348	191	10	-	-	SYM
cana-2348	191	11	5	5	NUM
cana-2348	191	12	.	.	PUNCT
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cana-2348	192	2	9	9	NUM
cana-2348	192	3	]	]	SYM
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cana-2348	192	6	s.	s.	PROPN
cana-2348	192	7	h.	h.	PROPN
cana-2348	192	8	,	,	PUNCT
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cana-2348	192	12	j.	j.	PROPN
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cana-2348	192	17	c.	c.	PROPN
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cana-2348	192	21	)	)	PUNCT
cana-2348	192	22	.	.	PUNCT
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cana-2348	193	3	of	of	ADP
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cana-2348	193	5	learning	learn	VERB
cana-2348	193	6	algorithms	algorithm	NOUN
cana-2348	193	7	for	for	ADP
cana-2348	193	8	the	the	DET
cana-2348	193	9	surveillance	surveillance	NOUN
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cana-2348	193	12	spectrum	spectrum	NOUN
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cana-2348	193	14	.	.	PUNCT
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cana-2348	194	5	.	.	PUNCT
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cana-2348	196	2	10	10	NUM
cana-2348	196	3	]	]	X
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cana-2348	196	5	,	,	PUNCT
cana-2348	196	6	l.	l.	PROPN
cana-2348	196	7	,	,	PUNCT
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cana-2348	196	10	,	,	PUNCT
cana-2348	196	11	l.	l.	PROPN
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cana-2348	196	13	2001	2001	NUM
cana-2348	196	14	)	)	PUNCT
cana-2348	196	15	.	.	PUNCT
cana-2348	197	1	recurrent	recurrent	ADJ
cana-2348	197	2	neural	neural	ADJ
cana-2348	197	3	networks	network	NOUN
cana-2348	197	4	.	.	PUNCT
cana-2348	198	1	design	design	NOUN
cana-2348	198	2	and	and	CCONJ
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cana-2348	198	4	.	.	PUNCT
cana-2348	199	1	[	[	X
cana-2348	199	2	11	11	NUM
cana-2348	199	3	]	]	SYM
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cana-2348	199	5	,	,	PUNCT
cana-2348	199	6	r.	r.	PROPN
cana-2348	199	7	,	,	PUNCT
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cana-2348	199	9	,	,	PUNCT
cana-2348	199	10	t.	t.	PROPN
cana-2348	199	11	,	,	PUNCT
cana-2348	199	12	&	&	CCONJ
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cana-2348	199	14	,	,	PUNCT
cana-2348	199	15	y.	y.	PROPN
cana-2348	199	16	(	(	PUNCT
cana-2348	199	17	2013	2013	NUM
cana-2348	199	18	)	)	PUNCT
cana-2348	199	19	.	.	PUNCT
cana-2348	200	1	on	on	ADP
cana-2348	200	2	the	the	DET
cana-2348	200	3	difficulty	difficulty	NOUN
cana-2348	200	4	of	of	ADP
cana-2348	200	5	training	training	NOUN
cana-2348	200	6	recurrent	recurrent	ADJ
cana-2348	200	7	neural	neural	ADJ
cana-2348	200	8	networks	network	NOUN
cana-2348	200	9	.	.	PUNCT
cana-2348	201	1	in	in	ADP
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cana-2348	201	3	(	(	PUNCT
cana-2348	201	4	3	3	NUM
cana-2348	201	5	)	)	PUNCT
cana-2348	201	6	,	,	PUNCT
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cana-2348	201	8	.	.	PROPN
cana-2348	201	9	28	28	NUM
cana-2348	202	1	(	(	PUNCT
cana-2348	202	2	pp	pp	ADJ
cana-2348	202	3	.	.	PUNCT
cana-2348	202	4	1310–1318	1310–1318	NUM
cana-2348	202	5	)	)	PUNCT
cana-2348	202	6	.	.	PUNCT
cana-2348	203	1	[	[	X
cana-2348	203	2	12	12	NUM
cana-2348	203	3	]	]	X
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cana-2348	203	5	,	,	PUNCT
cana-2348	203	6	g.	g.	PROPN
cana-2348	203	7	e.	e.	PROPN
cana-2348	203	8	,	,	PUNCT
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cana-2348	203	10	,	,	PUNCT
cana-2348	203	11	s.	s.	PROPN
cana-2348	203	12	,	,	PUNCT
cana-2348	203	13	&	&	CCONJ
cana-2348	203	14	teh	teh	PROPN
cana-2348	203	15	,	,	PUNCT
cana-2348	203	16	y.	y.	PROPN
cana-2348	203	17	w.	w.	PROPN
cana-2348	203	18	(	(	PUNCT
cana-2348	203	19	2006	2006	NUM
cana-2348	203	20	)	)	PUNCT
cana-2348	203	21	.	.	PUNCT
cana-2348	204	1	a	a	DET
cana-2348	204	2	fast	fast	ADJ
cana-2348	204	3	learning	learn	VERB
cana-2348	204	4	algorithm	algorithm	NOUN
cana-2348	204	5	for	for	ADP
cana-2348	204	6	deep	deep	ADJ
cana-2348	204	7	belief	belief	NOUN
cana-2348	204	8	nets	net	NOUN
cana-2348	204	9	.	.	PUNCT
cana-2348	205	1	neural	neural	ADJ
cana-2348	205	2	computation	computation	NOUN
cana-2348	205	3	,	,	PUNCT
cana-2348	205	4	18(7	18(7	NUM
cana-2348	205	5	)	)	PUNCT
cana-2348	205	6	,	,	PUNCT
cana-2348	205	7	1527	1527	NUM
cana-2348	205	8	-	-	SYM
cana-2348	205	9	1554	1554	NUM
cana-2348	205	10	.	.	PUNCT
cana-2348	206	1	[	[	X
cana-2348	206	2	13	13	NUM
cana-2348	206	3	]	]	SYM
cana-2348	206	4	emmert	emmert	NOUN
cana-2348	206	5	-	-	PUNCT
cana-2348	206	6	streib	streib	PROPN
cana-2348	206	7	,	,	PUNCT
cana-2348	206	8	f.	f.	PROPN
cana-2348	206	9	,	,	PUNCT
cana-2348	206	10	yang	yang	PROPN
cana-2348	206	11	,	,	PUNCT
cana-2348	206	12	z.	z.	PROPN
cana-2348	206	13	,	,	PUNCT
cana-2348	206	14	feng	feng	PROPN
cana-2348	206	15	,	,	PUNCT
cana-2348	206	16	h.	h.	PROPN
cana-2348	206	17	,	,	PUNCT
cana-2348	206	18	tripathi	tripathi	PROPN
cana-2348	206	19	,	,	PUNCT
cana-2348	206	20	s.	s.	PROPN
cana-2348	206	21	,	,	PUNCT
cana-2348	206	22	&	&	CCONJ
cana-2348	206	23	dehmer	dehmer	PROPN
cana-2348	206	24	,	,	PUNCT
cana-2348	206	25	m.	m.	NOUN
cana-2348	206	26	(	(	PUNCT
cana-2348	206	27	2020	2020	NUM
cana-2348	206	28	)	)	PUNCT
cana-2348	206	29	.	.	PUNCT
cana-2348	207	1	an	an	DET
cana-2348	207	2	introductory	introductory	ADJ
cana-2348	207	3	review	review	NOUN
cana-2348	207	4	of	of	ADP
cana-2348	207	5	deep	deep	ADJ
cana-2348	207	6	learning	learning	NOUN
cana-2348	207	7	for	for	ADP
cana-2348	207	8	prediction	prediction	NOUN
cana-2348	207	9	models	model	NOUN
cana-2348	207	10	with	with	ADP
cana-2348	207	11	big	big	ADJ
cana-2348	207	12	data	datum	NOUN
cana-2348	207	13	.	.	PUNCT
cana-2348	208	1	frontiers	frontier	NOUN
cana-2348	208	2	in	in	ADP
cana-2348	208	3	artificial	artificial	ADJ
cana-2348	208	4	intelligence	intelligence	NOUN
cana-2348	208	5	,	,	PUNCT
cana-2348	208	6	3	3	NUM
cana-2348	208	7	,	,	PUNCT
cana-2348	208	8	4	4	NUM
cana-2348	208	9	.	.	NOUN
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cana-2348	208	11	https://doi.org/10.1371/journal.pone.0222907	https://doi.org/10.1371/journal.pone.0222907	PROPN