id	sid	tid	token	lemma	pos
ajst-32536	1	1	28	28	NUM
ajst-32536	1	2	research	research	NOUN
ajst-32536	1	3	on	on	ADP
ajst-32536	1	4	parkinson	parkinson	NOUN
ajst-32536	1	5	's	's	PART
ajst-32536	1	6	disease	disease	NOUN
ajst-32536	1	7	detection	detection	NOUN
ajst-32536	1	8	based	base	VERB
ajst-32536	1	9	on	on	ADP
ajst-32536	1	10	deep	deep	ADJ
ajst-32536	1	11	residual	residual	ADJ
ajst-32536	1	12	shrinkage	shrinkage	NOUN
ajst-32536	1	13	network	network	NOUN
ajst-32536	1	14	mingze	mingze	NOUN
ajst-32536	1	15	yu	yu	PROPN
ajst-32536	1	16	*	*	PROPN
ajst-32536	1	17	northeastern	northeastern	PROPN
ajst-32536	1	18	university	university	PROPN
ajst-32536	1	19	at	at	ADP
ajst-32536	1	20	qinhuangdao	qinhuangdao	ADV
ajst-32536	1	21	,	,	PUNCT
ajst-32536	1	22	school	school	NOUN
ajst-32536	1	23	of	of	ADP
ajst-32536	1	24	computer	computer	NOUN
ajst-32536	1	25	and	and	CCONJ
ajst-32536	1	26	communication	communication	NOUN
ajst-32536	1	27	engineering	engineering	NOUN
ajst-32536	1	28	,	,	PUNCT
ajst-32536	1	29	qinhuangdao	qinhuangdao	ADV
ajst-32536	1	30	,	,	PUNCT
ajst-32536	1	31	hebei	hebei	PROPN
ajst-32536	1	32	,	,	PUNCT
ajst-32536	1	33	066004	066004	NUM
ajst-32536	1	34	,	,	PUNCT
ajst-32536	1	35	china	china	PROPN
ajst-32536	1	36	*	*	PUNCT
ajst-32536	1	37	corresponding	correspond	VERB
ajst-32536	1	38	author	author	NOUN
ajst-32536	1	39	email	email	NOUN
ajst-32536	1	40	:	:	PUNCT
ajst-32536	1	41	19846733685@163.com	19846733685@163.com	NUM
ajst-32536	1	42	abstract	abstract	ADJ
ajst-32536	1	43	.	.	PUNCT
ajst-32536	2	1	parkinson	parkinson	NOUN
ajst-32536	2	2	’s	’s	PART
ajst-32536	2	3	disease	disease	NOUN
ajst-32536	2	4	(	(	PUNCT
ajst-32536	2	5	parkinson	parkinson	NOUN
ajst-32536	2	6	’s	’s	PART
ajst-32536	2	7	disease	disease	NOUN
ajst-32536	2	8	,	,	PUNCT
ajst-32536	2	9	pd	pd	PROPN
ajst-32536	2	10	)	)	PUNCT
ajst-32536	2	11	is	be	AUX
ajst-32536	2	12	a	a	DET
ajst-32536	2	13	common	common	ADJ
ajst-32536	2	14	neurodegenerative	neurodegenerative	ADJ
ajst-32536	2	15	disorder	disorder	NOUN
ajst-32536	2	16	of	of	ADP
ajst-32536	2	17	the	the	DET
ajst-32536	2	18	nervous	nervous	ADJ
ajst-32536	2	19	system	system	NOUN
ajst-32536	2	20	.	.	PUNCT
ajst-32536	3	1	beyond	beyond	ADP
ajst-32536	3	2	severely	severely	ADV
ajst-32536	3	3	compromising	compromise	VERB
ajst-32536	3	4	patients	patient	NOUN
ajst-32536	3	5	’	'	PUNCT
ajst-32536	3	6	quality	quality	NOUN
ajst-32536	3	7	of	of	ADP
ajst-32536	3	8	daily	daily	ADJ
ajst-32536	3	9	life	life	NOUN
ajst-32536	3	10	,	,	PUNCT
ajst-32536	3	11	it	it	PRON
ajst-32536	3	12	also	also	ADV
ajst-32536	3	13	induces	induce	VERB
ajst-32536	3	14	non	non	ADJ
ajst-32536	3	15	-	-	ADJ
ajst-32536	3	16	motor	motor	ADJ
ajst-32536	3	17	symptoms	symptom	NOUN
ajst-32536	3	18	such	such	ADJ
ajst-32536	3	19	as	as	ADP
ajst-32536	3	20	cognitive	cognitive	ADJ
ajst-32536	3	21	impairment	impairment	NOUN
ajst-32536	3	22	and	and	CCONJ
ajst-32536	3	23	depression	depression	NOUN
ajst-32536	3	24	,	,	PUNCT
ajst-32536	3	25	thereby	thereby	ADV
ajst-32536	3	26	imposing	impose	VERB
ajst-32536	3	27	a	a	DET
ajst-32536	3	28	heavy	heavy	ADJ
ajst-32536	3	29	burden	burden	NOUN
ajst-32536	3	30	on	on	ADP
ajst-32536	3	31	patients	patient	NOUN
ajst-32536	3	32	’	'	PUNCT
ajst-32536	3	33	families	family	NOUN
ajst-32536	3	34	and	and	CCONJ
ajst-32536	3	35	society	society	NOUN
ajst-32536	3	36	as	as	ADP
ajst-32536	3	37	a	a	DET
ajst-32536	3	38	whole	whole	NOUN
ajst-32536	3	39	.	.	PUNCT
ajst-32536	4	1	conventional	conventional	ADJ
ajst-32536	4	2	pd	pd	PROPN
ajst-32536	4	3	detection	detection	NOUN
ajst-32536	4	4	methods	method	NOUN
ajst-32536	4	5	,	,	PUNCT
ajst-32536	4	6	however	however	ADV
ajst-32536	4	7	,	,	PUNCT
ajst-32536	4	8	are	be	AUX
ajst-32536	4	9	constrained	constrain	VERB
ajst-32536	4	10	by	by	ADP
ajst-32536	4	11	their	their	PRON
ajst-32536	4	12	dependence	dependence	NOUN
ajst-32536	4	13	on	on	ADP
ajst-32536	4	14	manual	manual	ADJ
ajst-32536	4	15	feature	feature	NOUN
ajst-32536	4	16	extraction	extraction	NOUN
ajst-32536	4	17	and	and	CCONJ
ajst-32536	4	18	susceptibility	susceptibility	NOUN
ajst-32536	4	19	to	to	ADP
ajst-32536	4	20	noisy	noisy	ADJ
ajst-32536	4	21	data	datum	NOUN
ajst-32536	4	22	.	.	PUNCT
ajst-32536	5	1	these	these	DET
ajst-32536	5	2	methods	method	NOUN
ajst-32536	5	3	suffer	suffer	VERB
ajst-32536	5	4	from	from	ADP
ajst-32536	5	5	limitations	limitation	NOUN
ajst-32536	5	6	including	include	VERB
ajst-32536	5	7	relatively	relatively	ADV
ajst-32536	5	8	low	low	ADJ
ajst-32536	5	9	detection	detection	NOUN
ajst-32536	5	10	accuracy	accuracy	NOUN
ajst-32536	5	11	and	and	CCONJ
ajst-32536	5	12	insufficient	insufficient	ADJ
ajst-32536	5	13	feature	feature	NOUN
ajst-32536	5	14	extraction	extraction	NOUN
ajst-32536	5	15	capability	capability	NOUN
ajst-32536	5	16	,	,	PUNCT
ajst-32536	5	17	making	make	VERB
ajst-32536	5	18	them	they	PRON
ajst-32536	5	19	barely	barely	ADV
ajst-32536	5	20	able	able	ADJ
ajst-32536	5	21	to	to	PART
ajst-32536	5	22	meet	meet	VERB
ajst-32536	5	23	the	the	DET
ajst-32536	5	24	requirements	requirement	NOUN
ajst-32536	5	25	for	for	ADP
ajst-32536	5	26	precision	precision	NOUN
ajst-32536	5	27	and	and	CCONJ
ajst-32536	5	28	stability	stability	NOUN
ajst-32536	5	29	in	in	ADP
ajst-32536	5	30	clinical	clinical	ADJ
ajst-32536	5	31	diagnosis.to	diagnosis.to	NUM
ajst-32536	5	32	address	address	NOUN
ajst-32536	5	33	the	the	DET
ajst-32536	5	34	limitations	limitation	NOUN
ajst-32536	5	35	of	of	ADP
ajst-32536	5	36	conventional	conventional	ADJ
ajst-32536	5	37	methods	method	NOUN
ajst-32536	5	38	,	,	PUNCT
ajst-32536	5	39	this	this	DET
ajst-32536	5	40	study	study	NOUN
ajst-32536	5	41	proposes	propose	VERB
ajst-32536	5	42	a	a	DET
ajst-32536	5	43	deep	deep	ADJ
ajst-32536	5	44	residual	residual	ADJ
ajst-32536	5	45	shrinking	shrink	VERB
ajst-32536	5	46	network	network	NOUN
ajst-32536	5	47	(	(	PUNCT
ajst-32536	5	48	deep	deep	ADJ
ajst-32536	5	49	residual	residual	ADJ
ajst-32536	5	50	shrinking	shrink	VERB
ajst-32536	5	51	network	network	NOUN
ajst-32536	5	52	,	,	PUNCT
ajst-32536	5	53	drsn	drsn	PROPN
ajst-32536	5	54	)	)	PUNCT
ajst-32536	5	55	based	base	VERB
ajst-32536	5	56	on	on	ADP
ajst-32536	5	57	pooling	pool	VERB
ajst-32536	5	58	fusion	fusion	NOUN
ajst-32536	5	59	for	for	ADP
ajst-32536	5	60	efficient	efficient	ADJ
ajst-32536	5	61	detection	detection	NOUN
ajst-32536	5	62	of	of	ADP
ajst-32536	5	63	parkinson	parkinson	NOUN
ajst-32536	5	64	’s	’s	PART
ajst-32536	5	65	disease	disease	NOUN
ajst-32536	5	66	.	.	PUNCT
ajst-32536	6	1	first	first	ADV
ajst-32536	6	2	,	,	PUNCT
ajst-32536	6	3	by	by	ADP
ajst-32536	6	4	introducing	introduce	VERB
ajst-32536	6	5	residual	residual	ADJ
ajst-32536	6	6	connections	connection	NOUN
ajst-32536	6	7	into	into	ADP
ajst-32536	6	8	the	the	DET
ajst-32536	6	9	network	network	NOUN
ajst-32536	6	10	structure	structure	NOUN
ajst-32536	6	11	,	,	PUNCT
ajst-32536	6	12	the	the	DET
ajst-32536	6	13	risks	risk	NOUN
ajst-32536	6	14	of	of	ADP
ajst-32536	6	15	gradient	gradient	ADJ
ajst-32536	6	16	vanishing	vanishing	NOUN
ajst-32536	6	17	or	or	CCONJ
ajst-32536	6	18	gradient	gradient	ADJ
ajst-32536	6	19	exploding	exploding	NOUN
ajst-32536	6	20	caused	cause	VERB
ajst-32536	6	21	by	by	ADP
ajst-32536	6	22	excessive	excessive	ADJ
ajst-32536	6	23	network	network	NOUN
ajst-32536	6	24	depth	depth	NOUN
ajst-32536	6	25	are	be	AUX
ajst-32536	6	26	effectively	effectively	ADV
ajst-32536	6	27	mitigated	mitigate	VERB
ajst-32536	6	28	,	,	PUNCT
ajst-32536	6	29	ensuring	ensure	VERB
ajst-32536	6	30	the	the	DET
ajst-32536	6	31	effective	effective	ADJ
ajst-32536	6	32	learning	learning	NOUN
ajst-32536	6	33	of	of	ADP
ajst-32536	6	34	deep	deep	ADJ
ajst-32536	6	35	-	-	PUNCT
ajst-32536	6	36	level	level	NOUN
ajst-32536	6	37	features	feature	NOUN
ajst-32536	6	38	.	.	PUNCT
ajst-32536	7	1	second	second	ADJ
ajst-32536	7	2	,	,	PUNCT
ajst-32536	7	3	a	a	DET
ajst-32536	7	4	multi	multi	ADJ
ajst-32536	7	5	-	-	ADJ
ajst-32536	7	6	scale	scale	ADJ
ajst-32536	7	7	pooling	pool	VERB
ajst-32536	7	8	feature	feature	NOUN
ajst-32536	7	9	fusion	fusion	NOUN
ajst-32536	7	10	strategy	strategy	NOUN
ajst-32536	7	11	is	be	AUX
ajst-32536	7	12	adopted	adopt	VERB
ajst-32536	7	13	to	to	PART
ajst-32536	7	14	extract	extract	VERB
ajst-32536	7	15	richer	rich	ADJ
ajst-32536	7	16	local	local	ADJ
ajst-32536	7	17	features	feature	NOUN
ajst-32536	7	18	from	from	ADP
ajst-32536	7	19	electroencephalogram	electroencephalogram	NOUN
ajst-32536	7	20	(	(	PUNCT
ajst-32536	7	21	electroencephalogram	electroencephalogram	NOUN
ajst-32536	7	22	,	,	PUNCT
ajst-32536	7	23	eeg	eeg	NOUN
ajst-32536	7	24	)	)	PUNCT
ajst-32536	7	25	signals	signal	NOUN
ajst-32536	7	26	.	.	PUNCT
ajst-32536	8	1	meanwhile	meanwhile	ADV
ajst-32536	8	2	,	,	PUNCT
ajst-32536	8	3	an	an	DET
ajst-32536	8	4	attention	attention	NOUN
ajst-32536	8	5	mechanism	mechanism	NOUN
ajst-32536	8	6	is	be	AUX
ajst-32536	8	7	integrated	integrate	VERB
ajst-32536	8	8	to	to	PART
ajst-32536	8	9	automatically	automatically	ADV
ajst-32536	8	10	derive	derive	VERB
ajst-32536	8	11	the	the	DET
ajst-32536	8	12	optimal	optimal	ADJ
ajst-32536	8	13	threshold	threshold	NOUN
ajst-32536	8	14	of	of	ADP
ajst-32536	8	15	the	the	DET
ajst-32536	8	16	soft	soft	ADJ
ajst-32536	8	17	-	-	PUNCT
ajst-32536	8	18	thresholding	thresholde	VERB
ajst-32536	8	19	function	function	NOUN
ajst-32536	8	20	,	,	PUNCT
ajst-32536	8	21	enabling	enable	VERB
ajst-32536	8	22	adaptive	adaptive	ADJ
ajst-32536	8	23	removal	removal	NOUN
ajst-32536	8	24	of	of	ADP
ajst-32536	8	25	noise	noise	NOUN
ajst-32536	8	26	in	in	ADP
ajst-32536	8	27	the	the	DET
ajst-32536	8	28	signals	signal	NOUN
ajst-32536	8	29	and	and	CCONJ
ajst-32536	8	30	enhancing	enhance	VERB
ajst-32536	8	31	the	the	DET
ajst-32536	8	32	representational	representational	ADJ
ajst-32536	8	33	capability	capability	NOUN
ajst-32536	8	34	of	of	ADP
ajst-32536	8	35	effective	effective	ADJ
ajst-32536	8	36	features.the	features.the	DET
ajst-32536	8	37	proposed	propose	VERB
ajst-32536	8	38	method	method	NOUN
ajst-32536	8	39	was	be	AUX
ajst-32536	8	40	validated	validate	VERB
ajst-32536	8	41	on	on	ADP
ajst-32536	8	42	the	the	DET
ajst-32536	8	43	parkinson	parkinson	NOUN
ajst-32536	8	44	’s	’s	PART
ajst-32536	8	45	disease	disease	NOUN
ajst-32536	8	46	neurophysiological	neurophysiological	ADJ
ajst-32536	8	47	activity	activity	NOUN
ajst-32536	8	48	dataset	dataset	NOUN
ajst-32536	8	49	and	and	CCONJ
ajst-32536	8	50	the	the	DET
ajst-32536	8	51	new	new	PROPN
ajst-32536	8	52	mexico	mexico	PROPN
ajst-32536	8	53	dataset	dataset	VERB
ajst-32536	8	54	.	.	PUNCT
ajst-32536	9	1	the	the	DET
ajst-32536	9	2	results	result	NOUN
ajst-32536	9	3	demonstrate	demonstrate	VERB
ajst-32536	9	4	that	that	SCONJ
ajst-32536	9	5	the	the	DET
ajst-32536	9	6	drsn	drsn	PROPN
ajst-32536	9	7	method	method	NOUN
ajst-32536	9	8	achieved	achieve	VERB
ajst-32536	9	9	an	an	DET
ajst-32536	9	10	accuracy	accuracy	NOUN
ajst-32536	9	11	of	of	ADP
ajst-32536	9	12	92.10	92.10	NUM
ajst-32536	9	13	%	%	NOUN
ajst-32536	9	14	,	,	PUNCT
ajst-32536	9	15	precision	precision	NOUN
ajst-32536	9	16	of	of	ADP
ajst-32536	9	17	91.27	91.27	NUM
ajst-32536	9	18	%	%	NOUN
ajst-32536	9	19	,	,	PUNCT
ajst-32536	9	20	recall	recall	NOUN
ajst-32536	9	21	of	of	ADP
ajst-32536	9	22	90.72	90.72	NUM
ajst-32536	9	23	%	%	NOUN
ajst-32536	9	24	,	,	PUNCT
ajst-32536	9	25	and	and	CCONJ
ajst-32536	9	26	f1	f1	NOUN
ajst-32536	9	27	-	-	PUNCT
ajst-32536	9	28	score	score	NOUN
ajst-32536	9	29	of	of	ADP
ajst-32536	9	30	90.99	90.99	NUM
ajst-32536	9	31	%	%	NOUN
ajst-32536	9	32	on	on	ADP
ajst-32536	9	33	the	the	DET
ajst-32536	9	34	pd	pd	PROPN
ajst-32536	9	35	neurophysiological	neurophysiological	ADJ
ajst-32536	9	36	activity	activity	NOUN
ajst-32536	9	37	dataset	dataset	NOUN
ajst-32536	9	38	.	.	PUNCT
ajst-32536	10	1	on	on	ADP
ajst-32536	10	2	the	the	DET
ajst-32536	10	3	new	new	PROPN
ajst-32536	10	4	mexico	mexico	PROPN
ajst-32536	10	5	dataset	dataset	VERB
ajst-32536	10	6	,	,	PUNCT
ajst-32536	10	7	it	it	PRON
ajst-32536	10	8	further	far	ADV
ajst-32536	10	9	yielded	yield	VERB
ajst-32536	10	10	an	an	DET
ajst-32536	10	11	accuracy	accuracy	NOUN
ajst-32536	10	12	of	of	ADP
ajst-32536	10	13	98.15	98.15	NUM
ajst-32536	10	14	%	%	NOUN
ajst-32536	10	15	,	,	PUNCT
ajst-32536	10	16	precision	precision	NOUN
ajst-32536	10	17	of	of	ADP
ajst-32536	10	18	97.63	97.63	NUM
ajst-32536	10	19	%	%	NOUN
ajst-32536	10	20	,	,	PUNCT
ajst-32536	10	21	recall	recall	NOUN
ajst-32536	10	22	of	of	ADP
ajst-32536	10	23	96.12	96.12	NUM
ajst-32536	10	24	%	%	NOUN
ajst-32536	10	25	,	,	PUNCT
ajst-32536	10	26	and	and	CCONJ
ajst-32536	10	27	f1	f1	NOUN
ajst-32536	10	28	-	-	PUNCT
ajst-32536	10	29	score	score	NOUN
ajst-32536	10	30	of	of	ADP
ajst-32536	10	31	96.87	96.87	NUM
ajst-32536	10	32	%	%	NOUN
ajst-32536	10	33	.	.	PUNCT
ajst-32536	11	1	in	in	ADP
ajst-32536	11	2	comparison	comparison	NOUN
ajst-32536	11	3	with	with	ADP
ajst-32536	11	4	traditional	traditional	ADJ
ajst-32536	11	5	methods	method	NOUN
ajst-32536	11	6	—	—	PUNCT
ajst-32536	11	7	including	include	VERB
ajst-32536	11	8	convolutional	convolutional	ADJ
ajst-32536	11	9	neural	neural	ADJ
ajst-32536	11	10	networks	network	NOUN
ajst-32536	11	11	(	(	PUNCT
ajst-32536	11	12	accuracy	accuracy	NOUN
ajst-32536	11	13	:	:	PUNCT
ajst-32536	11	14	88.00	88.00	NUM
ajst-32536	11	15	%	%	NOUN
ajst-32536	11	16	)	)	PUNCT
ajst-32536	11	17	and	and	CCONJ
ajst-32536	11	18	deep	deep	ADJ
ajst-32536	11	19	residual	residual	ADJ
ajst-32536	11	20	networks	network	NOUN
ajst-32536	11	21	(	(	PUNCT
ajst-32536	11	22	accuracy	accuracy	NOUN
ajst-32536	11	23	:	:	PUNCT
ajst-32536	11	24	92.03%)—the	92.03%)—the	DET
ajst-32536	11	25	proposed	propose	VERB
ajst-32536	11	26	method	method	NOUN
ajst-32536	11	27	exhibited	exhibit	VERB
ajst-32536	11	28	an	an	DET
ajst-32536	11	29	accuracy	accuracy	NOUN
ajst-32536	11	30	improvement	improvement	NOUN
ajst-32536	11	31	of	of	ADP
ajst-32536	11	32	10.15	10.15	NUM
ajst-32536	11	33	percentage	percentage	NOUN
ajst-32536	11	34	points	point	NOUN
ajst-32536	11	35	and	and	CCONJ
ajst-32536	11	36	6.12	6.12	NUM
ajst-32536	11	37	percentage	percentage	NOUN
ajst-32536	11	38	points	point	NOUN
ajst-32536	11	39	,	,	PUNCT
ajst-32536	11	40	respectively.leveraging	respectively.leverage	VERB
ajst-32536	11	41	the	the	DET
ajst-32536	11	42	residual	residual	ADJ
ajst-32536	11	43	connections	connection	NOUN
ajst-32536	11	44	that	that	PRON
ajst-32536	11	45	ensure	ensure	VERB
ajst-32536	11	46	the	the	DET
ajst-32536	11	47	stability	stability	NOUN
ajst-32536	11	48	of	of	ADP
ajst-32536	11	49	deep	deep	ADJ
ajst-32536	11	50	networks	network	NOUN
ajst-32536	11	51	,	,	PUNCT
ajst-32536	11	52	the	the	DET
ajst-32536	11	53	multi	multi	ADJ
ajst-32536	11	54	-	-	ADJ
ajst-32536	11	55	scale	scale	ADJ
ajst-32536	11	56	pooling	pooling	NOUN
ajst-32536	11	57	fusion	fusion	NOUN
ajst-32536	11	58	that	that	PRON
ajst-32536	11	59	enables	enable	VERB
ajst-32536	11	60	the	the	DET
ajst-32536	11	61	extraction	extraction	NOUN
ajst-32536	11	62	of	of	ADP
ajst-32536	11	63	rich	rich	ADJ
ajst-32536	11	64	features	feature	NOUN
ajst-32536	11	65	,	,	PUNCT
ajst-32536	11	66	and	and	CCONJ
ajst-32536	11	67	the	the	DET
ajst-32536	11	68	attention	attention	NOUN
ajst-32536	11	69	mechanism	mechanism	NOUN
ajst-32536	11	70	-	-	PUNCT
ajst-32536	11	71	driven	drive	VERB
ajst-32536	11	72	adaptive	adaptive	ADJ
ajst-32536	11	73	denoising	denoising	NOUN
ajst-32536	11	74	capability	capability	NOUN
ajst-32536	11	75	,	,	PUNCT
ajst-32536	11	76	this	this	DET
ajst-32536	11	77	method	method	NOUN
ajst-32536	11	78	demonstrates	demonstrate	VERB
ajst-32536	11	79	distinct	distinct	ADJ
ajst-32536	11	80	advantages	advantage	NOUN
ajst-32536	11	81	in	in	ADP
ajst-32536	11	82	parkinson	parkinson	NOUN
ajst-32536	11	83	’s	’s	PART
ajst-32536	11	84	disease	disease	NOUN
ajst-32536	11	85	detection	detection	NOUN
ajst-32536	11	86	.	.	PUNCT
ajst-32536	12	1	it	it	PRON
ajst-32536	12	2	effectively	effectively	ADV
ajst-32536	12	3	enhances	enhance	VERB
ajst-32536	12	4	detection	detection	NOUN
ajst-32536	12	5	accuracy	accuracy	NOUN
ajst-32536	12	6	and	and	CCONJ
ajst-32536	12	7	robustness	robustness	NOUN
ajst-32536	12	8	,	,	PUNCT
ajst-32536	12	9	thereby	thereby	ADV
ajst-32536	12	10	providing	provide	VERB
ajst-32536	12	11	more	more	ADV
ajst-32536	12	12	reliable	reliable	ADJ
ajst-32536	12	13	technical	technical	ADJ
ajst-32536	12	14	support	support	NOUN
ajst-32536	12	15	for	for	ADP
ajst-32536	12	16	the	the	DET
ajst-32536	12	17	auxiliary	auxiliary	ADJ
ajst-32536	12	18	diagnosis	diagnosis	NOUN
ajst-32536	12	19	of	of	ADP
ajst-32536	12	20	parkinson	parkinson	NOUN
ajst-32536	12	21	’s	’s	PART
ajst-32536	12	22	disease	disease	NOUN
ajst-32536	12	23	.	.	PUNCT
ajst-32536	13	1	keywords	keyword	NOUN
ajst-32536	13	2	:	:	PUNCT
ajst-32536	13	3	parkinson	parkinson	NOUN
ajst-32536	13	4	’s	’s	PART
ajst-32536	13	5	disease	disease	NOUN
ajst-32536	13	6	;	;	PUNCT
ajst-32536	13	7	pooling	pool	VERB
ajst-32536	13	8	fusion	fusion	NOUN
ajst-32536	13	9	;	;	PUNCT
ajst-32536	13	10	drsn	drsn	PROPN
ajst-32536	13	11	;	;	PUNCT
ajst-32536	13	12	noise	noise	NOUN
ajst-32536	13	13	resistance	resistance	NOUN
ajst-32536	13	14	;	;	PUNCT
ajst-32536	13	15	detection	detection	NOUN
ajst-32536	13	16	accuracy	accuracy	NOUN
ajst-32536	13	17	.	.	PUNCT
ajst-32536	14	1	1	1	X
ajst-32536	14	2	.	.	X
ajst-32536	14	3	introduction	introduction	NOUN
ajst-32536	14	4	parkinson	parkinson	NOUN
ajst-32536	14	5	’s	’s	PART
ajst-32536	14	6	disease	disease	NOUN
ajst-32536	14	7	(	(	PUNCT
ajst-32536	14	8	pd	pd	NOUN
ajst-32536	14	9	)	)	PUNCT
ajst-32536	14	10	is	be	AUX
ajst-32536	14	11	a	a	DET
ajst-32536	14	12	prevalent	prevalent	ADJ
ajst-32536	14	13	age	age	NOUN
ajst-32536	14	14	-	-	PUNCT
ajst-32536	14	15	related	relate	VERB
ajst-32536	14	16	neurodegenerative	neurodegenerative	ADJ
ajst-32536	14	17	disorder	disorder	NOUN
ajst-32536	14	18	in	in	ADP
ajst-32536	14	19	the	the	DET
ajst-32536	14	20	elderly	elderly	ADJ
ajst-32536	14	21	population	population	NOUN
ajst-32536	14	22	,	,	PUNCT
ajst-32536	14	23	frequently	frequently	ADV
ajst-32536	14	24	accompanied	accompany	VERB
ajst-32536	14	25	by	by	ADP
ajst-32536	14	26	a	a	DET
ajst-32536	14	27	spectrum	spectrum	NOUN
ajst-32536	14	28	of	of	ADP
ajst-32536	14	29	non	non	ADJ
ajst-32536	14	30	-	-	ADJ
ajst-32536	14	31	motor	motor	ADJ
ajst-32536	14	32	symptoms	symptom	NOUN
ajst-32536	14	33	such	such	ADJ
ajst-32536	14	34	as	as	ADP
ajst-32536	14	35	constipation	constipation	NOUN
ajst-32536	14	36	,	,	PUNCT
ajst-32536	14	37	hyposmia	hyposmia	NOUN
ajst-32536	14	38	,	,	PUNCT
ajst-32536	14	39	insomnia	insomnia	NOUN
ajst-32536	14	40	,	,	PUNCT
ajst-32536	14	41	emotional	emotional	ADJ
ajst-32536	14	42	disturbances	disturbance	NOUN
ajst-32536	14	43	,	,	PUNCT
ajst-32536	14	44	and	and	CCONJ
ajst-32536	14	45	cognitive	cognitive	ADJ
ajst-32536	14	46	decline	decline	NOUN
ajst-32536	14	47	.	.	PUNCT
ajst-32536	15	1	this	this	DET
ajst-32536	15	2	disease	disease	NOUN
ajst-32536	15	3	exerts	exert	VERB
ajst-32536	15	4	a	a	DET
ajst-32536	15	5	profound	profound	ADJ
ajst-32536	15	6	adverse	adverse	ADJ
ajst-32536	15	7	impact	impact	NOUN
ajst-32536	15	8	on	on	ADP
ajst-32536	15	9	the	the	DET
ajst-32536	15	10	quality	quality	NOUN
ajst-32536	15	11	of	of	ADP
ajst-32536	15	12	life	life	NOUN
ajst-32536	15	13	of	of	ADP
ajst-32536	15	14	both	both	DET
ajst-32536	15	15	patients	patient	NOUN
ajst-32536	15	16	and	and	CCONJ
ajst-32536	15	17	their	their	PRON
ajst-32536	15	18	families	family	NOUN
ajst-32536	15	19	[	[	X
ajst-32536	15	20	1	1	NUM
ajst-32536	15	21	]	]	PUNCT
ajst-32536	15	22	.	.	PUNCT
ajst-32536	16	1	currently	currently	ADV
ajst-32536	16	2	,	,	PUNCT
ajst-32536	16	3	there	there	PRON
ajst-32536	16	4	are	be	VERB
ajst-32536	16	5	over	over	ADP
ajst-32536	16	6	5	5	NUM
ajst-32536	16	7	million	million	NUM
ajst-32536	16	8	people	people	NOUN
ajst-32536	16	9	living	live	VERB
ajst-32536	16	10	with	with	ADP
ajst-32536	16	11	pd	pd	PROPN
ajst-32536	16	12	in	in	ADP
ajst-32536	16	13	china	china	PROPN
ajst-32536	16	14	,	,	PUNCT
ajst-32536	16	15	accounting	account	VERB
ajst-32536	16	16	for	for	ADP
ajst-32536	16	17	43.14	43.14	NUM
ajst-32536	16	18	%	%	NOUN
ajst-32536	16	19	of	of	ADP
ajst-32536	16	20	the	the	DET
ajst-32536	16	21	global	global	PROPN
ajst-32536	16	22	pd	pd	PROPN
ajst-32536	16	23	patient	patient	PROPN
ajst-32536	16	24	population	population	NOUN
ajst-32536	16	25	.	.	PUNCT
ajst-32536	17	1	owing	owe	VERB
ajst-32536	17	2	to	to	ADP
ajst-32536	17	3	the	the	DET
ajst-32536	17	4	high	high	ADJ
ajst-32536	17	5	heterogeneity	heterogeneity	NOUN
ajst-32536	17	6	of	of	ADP
ajst-32536	17	7	pd	pd	PROPN
ajst-32536	17	8	,	,	PUNCT
ajst-32536	17	9	patients	patient	NOUN
ajst-32536	17	10	exhibit	exhibit	VERB
ajst-32536	17	11	substantial	substantial	ADJ
ajst-32536	17	12	variability	variability	NOUN
ajst-32536	17	13	in	in	ADP
ajst-32536	17	14	multiple	multiple	ADJ
ajst-32536	17	15	dimensions	dimension	NOUN
ajst-32536	17	16	,	,	PUNCT
ajst-32536	17	17	including	include	VERB
ajst-32536	17	18	age	age	NOUN
ajst-32536	17	19	at	at	ADP
ajst-32536	17	20	onset	onset	NOUN
ajst-32536	17	21	,	,	PUNCT
ajst-32536	17	22	clinical	clinical	ADJ
ajst-32536	17	23	manifestations	manifestation	NOUN
ajst-32536	17	24	,	,	PUNCT
ajst-32536	17	25	therapeutic	therapeutic	ADJ
ajst-32536	17	26	responses	response	NOUN
ajst-32536	17	27	,	,	PUNCT
ajst-32536	17	28	and	and	CCONJ
ajst-32536	17	29	disease	disease	NOUN
ajst-32536	17	30	progression	progression	NOUN
ajst-32536	17	31	rate	rate	NOUN
ajst-32536	17	32	.	.	PUNCT
ajst-32536	18	1	therefore	therefore	ADV
ajst-32536	18	2	,	,	PUNCT
ajst-32536	18	3	the	the	DET
ajst-32536	18	4	early	early	ADJ
ajst-32536	18	5	achievement	achievement	NOUN
ajst-32536	18	6	of	of	ADP
ajst-32536	18	7	disease	disease	NOUN
ajst-32536	18	8	detection	detection	NOUN
ajst-32536	18	9	,	,	PUNCT
ajst-32536	18	10	prediction	prediction	NOUN
ajst-32536	18	11	of	of	ADP
ajst-32536	18	12	disease	disease	NOUN
ajst-32536	18	13	progression	progression	NOUN
ajst-32536	18	14	,	,	PUNCT
ajst-32536	18	15	and	and	CCONJ
ajst-32536	18	16	accurate	accurate	ADJ
ajst-32536	18	17	patient	patient	NOUN
ajst-32536	18	18	classification	classification	NOUN
ajst-32536	18	19	is	be	AUX
ajst-32536	18	20	of	of	ADP
ajst-32536	18	21	pivotal	pivotal	ADJ
ajst-32536	18	22	importance	importance	NOUN
ajst-32536	18	23	for	for	ADP
ajst-32536	18	24	the	the	DET
ajst-32536	18	25	implementation	implementation	NOUN
ajst-32536	18	26	of	of	ADP
ajst-32536	18	27	precision	precision	NOUN
ajst-32536	18	28	medicine	medicine	NOUN
ajst-32536	18	29	.	.	PUNCT
ajst-32536	19	1	against	against	ADP
ajst-32536	19	2	this	this	DET
ajst-32536	19	3	backdrop	backdrop	NOUN
ajst-32536	19	4	,	,	PUNCT
ajst-32536	19	5	the	the	DET
ajst-32536	19	6	adoption	adoption	NOUN
ajst-32536	19	7	of	of	ADP
ajst-32536	19	8	efficient	efficient	ADJ
ajst-32536	19	9	detection	detection	NOUN
ajst-32536	19	10	approaches	approach	NOUN
ajst-32536	19	11	holds	hold	VERB
ajst-32536	19	12	significant	significant	ADJ
ajst-32536	19	13	implications	implication	NOUN
ajst-32536	19	14	for	for	ADP
ajst-32536	19	15	advancing	advance	VERB
ajst-32536	19	16	pd	pd	PROPN
ajst-32536	19	17	clinical	clinical	ADJ
ajst-32536	19	18	management	management	NOUN
ajst-32536	19	19	.	.	PUNCT
ajst-32536	20	1	29	29	NUM
ajst-32536	20	2	traditional	traditional	ADJ
ajst-32536	20	3	detection	detection	NOUN
ajst-32536	20	4	modalities	modality	NOUN
ajst-32536	20	5	for	for	ADP
ajst-32536	20	6	parkinson	parkinson	NOUN
ajst-32536	20	7	’s	’s	PART
ajst-32536	20	8	disease	disease	NOUN
ajst-32536	20	9	(	(	PUNCT
ajst-32536	20	10	pd	pd	NOUN
ajst-32536	20	11	)	)	PUNCT
ajst-32536	20	12	include	include	VERB
ajst-32536	20	13	clinical	clinical	ADJ
ajst-32536	20	14	symptom	symptom	NOUN
ajst-32536	20	15	assessment	assessment	NOUN
ajst-32536	20	16	[	[	X
ajst-32536	20	17	2	2	NUM
ajst-32536	20	18	]	]	PUNCT
ajst-32536	20	19	,	,	PUNCT
ajst-32536	20	20	dopamine	dopamine	NOUN
ajst-32536	20	21	transporter	transporter	NOUN
ajst-32536	20	22	(	(	PUNCT
ajst-32536	20	23	dat	dat	ADJ
ajst-32536	20	24	)	)	PUNCT
ajst-32536	20	25	imaging	imaging	NOUN
ajst-32536	21	1	[	[	X
ajst-32536	21	2	3	3	NUM
ajst-32536	21	3	]	]	PUNCT
ajst-32536	21	4	,	,	PUNCT
ajst-32536	21	5	and	and	CCONJ
ajst-32536	21	6	neuroimaging	neuroimaging	NOUN
ajst-32536	21	7	examinations	examination	NOUN
ajst-32536	22	1	[	[	X
ajst-32536	22	2	4]—such	4]—such	NUM
ajst-32536	22	3	as	as	ADP
ajst-32536	22	4	computed	compute	VERB
ajst-32536	22	5	tomography	tomography	NOUN
ajst-32536	22	6	(	(	PUNCT
ajst-32536	22	7	ct	ct	NOUN
ajst-32536	22	8	)	)	PUNCT
ajst-32536	22	9	and	and	CCONJ
ajst-32536	22	10	magnetic	magnetic	ADJ
ajst-32536	22	11	resonance	resonance	NOUN
ajst-32536	22	12	imaging	imaging	NOUN
ajst-32536	22	13	(	(	PUNCT
ajst-32536	22	14	mri	mri	NOUN
ajst-32536	22	15	)	)	PUNCT
ajst-32536	22	16	.	.	PUNCT
ajst-32536	23	1	clinical	clinical	ADJ
ajst-32536	23	2	symptom	symptom	NOUN
ajst-32536	23	3	assessment	assessment	NOUN
ajst-32536	23	4	relies	rely	VERB
ajst-32536	23	5	on	on	ADP
ajst-32536	23	6	the	the	DET
ajst-32536	23	7	observation	observation	NOUN
ajst-32536	23	8	of	of	ADP
ajst-32536	23	9	patients	patient	NOUN
ajst-32536	23	10	’	'	PUNCT
ajst-32536	23	11	typical	typical	ADJ
ajst-32536	23	12	motor	motor	NOUN
ajst-32536	23	13	symptoms	symptom	NOUN
ajst-32536	23	14	,	,	PUNCT
ajst-32536	23	15	including	include	VERB
ajst-32536	23	16	resting	rest	VERB
ajst-32536	23	17	tremor	tremor	NOUN
ajst-32536	23	18	,	,	PUNCT
ajst-32536	23	19	muscle	muscle	NOUN
ajst-32536	23	20	rigidity	rigidity	NOUN
ajst-32536	23	21	,	,	PUNCT
ajst-32536	23	22	bradykinesia	bradykinesia	NOUN
ajst-32536	23	23	,	,	PUNCT
ajst-32536	23	24	and	and	CCONJ
ajst-32536	23	25	postural	postural	ADJ
ajst-32536	23	26	balance	balance	NOUN
ajst-32536	23	27	impairment	impairment	NOUN
ajst-32536	23	28	,	,	PUNCT
ajst-32536	23	29	with	with	ADP
ajst-32536	23	30	diagnostic	diagnostic	ADJ
ajst-32536	23	31	judgments	judgment	NOUN
ajst-32536	23	32	made	make	VERB
ajst-32536	23	33	by	by	ADP
ajst-32536	23	34	integrating	integrate	VERB
ajst-32536	23	35	the	the	DET
ajst-32536	23	36	presence	presence	NOUN
ajst-32536	23	37	and	and	CCONJ
ajst-32536	23	38	severity	severity	NOUN
ajst-32536	23	39	of	of	ADP
ajst-32536	23	40	these	these	DET
ajst-32536	23	41	symptoms	symptom	NOUN
ajst-32536	23	42	.	.	PUNCT
ajst-32536	24	1	nevertheless	nevertheless	ADV
ajst-32536	24	2	,	,	PUNCT
ajst-32536	24	3	this	this	DET
ajst-32536	24	4	method	method	NOUN
ajst-32536	24	5	is	be	AUX
ajst-32536	24	6	highly	highly	ADV
ajst-32536	24	7	subjective	subjective	ADJ
ajst-32536	24	8	:	:	PUNCT
ajst-32536	24	9	it	it	PRON
ajst-32536	24	10	is	be	AUX
ajst-32536	24	11	prone	prone	ADJ
ajst-32536	24	12	to	to	ADP
ajst-32536	24	13	misdiagnosis	misdiagnosis	NOUN
ajst-32536	24	14	when	when	SCONJ
ajst-32536	24	15	early	early	ADJ
ajst-32536	24	16	-	-	PUNCT
ajst-32536	24	17	stage	stage	NOUN
ajst-32536	24	18	symptoms	symptom	NOUN
ajst-32536	24	19	are	be	AUX
ajst-32536	24	20	atypical	atypical	ADJ
ajst-32536	24	21	,	,	PUNCT
ajst-32536	24	22	which	which	PRON
ajst-32536	24	23	imposes	impose	VERB
ajst-32536	24	24	inherent	inherent	ADJ
ajst-32536	24	25	limitations	limitation	NOUN
ajst-32536	24	26	on	on	ADP
ajst-32536	24	27	its	its	PRON
ajst-32536	24	28	diagnostic	diagnostic	ADJ
ajst-32536	24	29	accuracy	accuracy	NOUN
ajst-32536	24	30	.	.	PUNCT
ajst-32536	25	1	dat	dat	ADJ
ajst-32536	25	2	imaging	imaging	NOUN
ajst-32536	25	3	enables	enable	VERB
ajst-32536	25	4	the	the	DET
ajst-32536	25	5	visualization	visualization	NOUN
ajst-32536	25	6	of	of	ADP
ajst-32536	25	7	the	the	DET
ajst-32536	25	8	functional	functional	ADJ
ajst-32536	25	9	status	status	NOUN
ajst-32536	25	10	of	of	ADP
ajst-32536	25	11	dopaminergic	dopaminergic	ADJ
ajst-32536	25	12	neuron	neuron	NOUN
ajst-32536	25	13	terminals	terminal	NOUN
ajst-32536	25	14	via	via	ADP
ajst-32536	25	15	positron	positron	NOUN
ajst-32536	25	16	emission	emission	NOUN
ajst-32536	25	17	tomography	tomography	NOUN
ajst-32536	25	18	-	-	PUNCT
ajst-32536	25	19	computed	compute	VERB
ajst-32536	25	20	tomography	tomography	NOUN
ajst-32536	25	21	(	(	PUNCT
ajst-32536	25	22	pet	pet	NOUN
ajst-32536	25	23	-	-	PUNCT
ajst-32536	25	24	ct	ct	NOUN
ajst-32536	25	25	)	)	PUNCT
ajst-32536	25	26	following	follow	VERB
ajst-32536	25	27	the	the	DET
ajst-32536	25	28	injection	injection	NOUN
ajst-32536	25	29	of	of	ADP
ajst-32536	25	30	radioactive	radioactive	ADJ
ajst-32536	25	31	tracers	tracer	NOUN
ajst-32536	25	32	,	,	PUNCT
ajst-32536	25	33	and	and	CCONJ
ajst-32536	25	34	it	it	PRON
ajst-32536	25	35	aids	aid	VERB
ajst-32536	25	36	in	in	ADP
ajst-32536	25	37	diagnosis	diagnosis	NOUN
ajst-32536	25	38	based	base	VERB
ajst-32536	25	39	on	on	ADP
ajst-32536	25	40	the	the	DET
ajst-32536	25	41	reduced	reduce	VERB
ajst-32536	25	42	tracer	tracer	NOUN
ajst-32536	25	43	uptake	uptake	ADJ
ajst-32536	25	44	in	in	ADP
ajst-32536	25	45	the	the	DET
ajst-32536	25	46	striatal	striatal	ADJ
ajst-32536	25	47	region	region	NOUN
ajst-32536	25	48	.	.	PUNCT
ajst-32536	26	1	however	however	ADV
ajst-32536	26	2	,	,	PUNCT
ajst-32536	26	3	this	this	DET
ajst-32536	26	4	technique	technique	NOUN
ajst-32536	26	5	is	be	AUX
ajst-32536	26	6	encumbered	encumber	VERB
ajst-32536	26	7	by	by	ADP
ajst-32536	26	8	notable	notable	ADJ
ajst-32536	26	9	drawbacks	drawback	NOUN
ajst-32536	26	10	:	:	PUNCT
ajst-32536	26	11	it	it	PRON
ajst-32536	26	12	incurs	incur	VERB
ajst-32536	26	13	substantial	substantial	ADJ
ajst-32536	26	14	costs	cost	NOUN
ajst-32536	26	15	,	,	PUNCT
ajst-32536	26	16	requires	require	VERB
ajst-32536	26	17	radioactive	radioactive	ADJ
ajst-32536	26	18	pharmaceuticals	pharmaceutical	NOUN
ajst-32536	26	19	,	,	PUNCT
ajst-32536	26	20	imposes	impose	VERB
ajst-32536	26	21	strict	strict	ADJ
ajst-32536	26	22	demands	demand	NOUN
ajst-32536	26	23	on	on	ADP
ajst-32536	26	24	equipment	equipment	NOUN
ajst-32536	26	25	and	and	CCONJ
ajst-32536	26	26	resource	resource	NOUN
ajst-32536	26	27	allocation	allocation	NOUN
ajst-32536	26	28	,	,	PUNCT
ajst-32536	26	29	and	and	CCONJ
ajst-32536	26	30	exhibits	exhibit	VERB
ajst-32536	26	31	a	a	DET
ajst-32536	26	32	combined	combine	VERB
ajst-32536	26	33	false	false	ADJ
ajst-32536	26	34	-	-	PUNCT
ajst-32536	26	35	positive	positive	ADJ
ajst-32536	26	36	and	and	CCONJ
ajst-32536	26	37	false	false	ADJ
ajst-32536	26	38	-	-	PUNCT
ajst-32536	26	39	negative	negative	ADJ
ajst-32536	26	40	rate	rate	NOUN
ajst-32536	26	41	of	of	ADP
ajst-32536	26	42	approximately	approximately	ADV
ajst-32536	26	43	5	5	NUM
ajst-32536	26	44	%	%	NOUN
ajst-32536	26	45	.	.	PUNCT
ajst-32536	27	1	ct	ct	PROPN
ajst-32536	27	2	and	and	CCONJ
ajst-32536	27	3	mri	mri	NOUN
ajst-32536	27	4	are	be	AUX
ajst-32536	27	5	employed	employ	VERB
ajst-32536	27	6	to	to	PART
ajst-32536	27	7	rule	rule	VERB
ajst-32536	27	8	out	out	ADP
ajst-32536	27	9	pd	pd	ADJ
ajst-32536	27	10	-	-	PUNCT
ajst-32536	27	11	like	like	ADJ
ajst-32536	27	12	symptoms	symptom	NOUN
ajst-32536	27	13	caused	cause	VERB
ajst-32536	27	14	by	by	ADP
ajst-32536	27	15	other	other	ADJ
ajst-32536	27	16	organic	organic	ADJ
ajst-32536	27	17	diseases	disease	NOUN
ajst-32536	27	18	through	through	ADP
ajst-32536	27	19	anatomical	anatomical	ADJ
ajst-32536	27	20	imaging	imaging	NOUN
ajst-32536	27	21	.	.	PUNCT
ajst-32536	28	1	yet	yet	ADV
ajst-32536	28	2	,	,	PUNCT
ajst-32536	28	3	they	they	PRON
ajst-32536	28	4	lack	lack	VERB
ajst-32536	28	5	specific	specific	ADJ
ajst-32536	28	6	manifestations	manifestation	NOUN
ajst-32536	28	7	for	for	ADP
ajst-32536	28	8	pd	pd	PROPN
ajst-32536	28	9	itself	itself	PRON
ajst-32536	28	10	and	and	CCONJ
ajst-32536	28	11	are	be	AUX
ajst-32536	28	12	ineffective	ineffective	ADJ
ajst-32536	28	13	in	in	ADP
ajst-32536	28	14	detecting	detect	VERB
ajst-32536	28	15	subtle	subtle	ADJ
ajst-32536	28	16	early	early	ADJ
ajst-32536	28	17	-	-	PUNCT
ajst-32536	28	18	stage	stage	NOUN
ajst-32536	28	19	pathological	pathological	ADJ
ajst-32536	28	20	changes	change	NOUN
ajst-32536	28	21	.	.	PUNCT
ajst-32536	29	1	specifically	specifically	ADV
ajst-32536	29	2	,	,	PUNCT
ajst-32536	29	3	ct	ct	PROPN
ajst-32536	29	4	exposes	expose	VERB
ajst-32536	29	5	patients	patient	NOUN
ajst-32536	29	6	to	to	ADP
ajst-32536	29	7	ionizing	ionize	VERB
ajst-32536	29	8	radiation	radiation	NOUN
ajst-32536	29	9	;	;	PUNCT
ajst-32536	29	10	mri	mri	NOUN
ajst-32536	29	11	,	,	PUNCT
ajst-32536	29	12	by	by	ADP
ajst-32536	29	13	contrast	contrast	NOUN
ajst-32536	29	14	,	,	PUNCT
ajst-32536	29	15	is	be	AUX
ajst-32536	29	16	time	time	NOUN
ajst-32536	29	17	-	-	PUNCT
ajst-32536	29	18	consuming	consume	VERB
ajst-32536	29	19	and	and	CCONJ
ajst-32536	29	20	costly	costly	ADJ
ajst-32536	29	21	,	,	PUNCT
ajst-32536	29	22	and	and	CCONJ
ajst-32536	29	23	it	it	PRON
ajst-32536	29	24	is	be	AUX
ajst-32536	29	25	contraindicated	contraindicate	VERB
ajst-32536	29	26	for	for	ADP
ajst-32536	29	27	patients	patient	NOUN
ajst-32536	29	28	with	with	ADP
ajst-32536	29	29	certain	certain	ADJ
ajst-32536	29	30	intracorporeal	intracorporeal	ADJ
ajst-32536	29	31	metal	metal	NOUN
ajst-32536	29	32	implants	implant	NOUN
ajst-32536	29	33	(	(	PUNCT
ajst-32536	29	34	e.g.	e.g.	ADV
ajst-32536	29	35	,	,	PUNCT
ajst-32536	29	36	pacemakers	pacemaker	NOUN
ajst-32536	29	37	,	,	PUNCT
ajst-32536	29	38	deep	deep	ADJ
ajst-32536	29	39	brain	brain	NOUN
ajst-32536	29	40	stimulation	stimulation	NOUN
ajst-32536	29	41	electrodes	electrode	NOUN
ajst-32536	29	42	)	)	PUNCT
ajst-32536	29	43	.	.	PUNCT
ajst-32536	30	1	in	in	ADP
ajst-32536	30	2	contrast	contrast	NOUN
ajst-32536	30	3	,	,	PUNCT
ajst-32536	30	4	electroencephalogram	electroencephalogram	X
ajst-32536	30	5	(	(	PUNCT
ajst-32536	30	6	eeg	eeg	NOUN
ajst-32536	30	7	)	)	PUNCT
ajst-32536	30	8	signal	signal	NOUN
ajst-32536	30	9	detection	detection	NOUN
ajst-32536	30	10	—	—	PUNCT
ajst-32536	30	11	an	an	DET
ajst-32536	30	12	approach	approach	NOUN
ajst-32536	30	13	that	that	PRON
ajst-32536	30	14	explores	explore	VERB
ajst-32536	30	15	pd	pd	PROPN
ajst-32536	30	16	pathogenesis	pathogenesis	NOUN
ajst-32536	30	17	by	by	ADP
ajst-32536	30	18	analyzing	analyze	VERB
ajst-32536	30	19	abnormal	abnormal	ADJ
ajst-32536	30	20	brain	brain	NOUN
ajst-32536	30	21	wave	wave	NOUN
ajst-32536	30	22	patterns	pattern	NOUN
ajst-32536	30	23	in	in	ADP
ajst-32536	30	24	affected	affected	ADJ
ajst-32536	30	25	patients	patient	NOUN
ajst-32536	30	26	—	—	PUNCT
ajst-32536	30	27	offers	offer	VERB
ajst-32536	30	28	distinct	distinct	ADJ
ajst-32536	30	29	and	and	CCONJ
ajst-32536	30	30	compelling	compelling	ADJ
ajst-32536	30	31	advantages	advantage	NOUN
ajst-32536	30	32	.	.	PUNCT
ajst-32536	31	1	compared	compare	VERB
ajst-32536	31	2	with	with	ADP
ajst-32536	31	3	clinical	clinical	ADJ
ajst-32536	31	4	symptom	symptom	NOUN
ajst-32536	31	5	assessment	assessment	NOUN
ajst-32536	31	6	,	,	PUNCT
ajst-32536	31	7	it	it	PRON
ajst-32536	31	8	demonstrates	demonstrate	VERB
ajst-32536	31	9	greater	great	ADJ
ajst-32536	31	10	objectivity	objectivity	NOUN
ajst-32536	31	11	by	by	ADP
ajst-32536	31	12	minimizing	minimize	VERB
ajst-32536	31	13	inter	inter	ADJ
ajst-32536	31	14	-	-	ADJ
ajst-32536	31	15	rater	rater	ADJ
ajst-32536	31	16	variability	variability	NOUN
ajst-32536	31	17	.	.	PUNCT
ajst-32536	32	1	unlike	unlike	ADP
ajst-32536	32	2	dat	dat	ADJ
ajst-32536	32	3	imaging	imaging	NOUN
ajst-32536	32	4	,	,	PUNCT
ajst-32536	32	5	it	it	PRON
ajst-32536	32	6	eliminates	eliminate	VERB
ajst-32536	32	7	the	the	DET
ajst-32536	32	8	need	need	NOUN
ajst-32536	32	9	for	for	ADP
ajst-32536	32	10	radioactive	radioactive	ADJ
ajst-32536	32	11	substances	substance	NOUN
ajst-32536	32	12	,	,	PUNCT
ajst-32536	32	13	thereby	thereby	ADV
ajst-32536	32	14	enhancing	enhance	VERB
ajst-32536	32	15	safety	safety	NOUN
ajst-32536	32	16	and	and	CCONJ
ajst-32536	32	17	reducing	reduce	VERB
ajst-32536	32	18	associated	associated	ADJ
ajst-32536	32	19	costs	cost	NOUN
ajst-32536	32	20	.	.	PUNCT
ajst-32536	33	1	furthermore	furthermore	ADV
ajst-32536	33	2	,	,	PUNCT
ajst-32536	33	3	eeg	eeg	PROPN
ajst-32536	33	4	is	be	AUX
ajst-32536	33	5	more	more	ADV
ajst-32536	33	6	sensitive	sensitive	ADJ
ajst-32536	33	7	to	to	ADP
ajst-32536	33	8	fluctuations	fluctuation	NOUN
ajst-32536	33	9	in	in	ADP
ajst-32536	33	10	cerebral	cerebral	ADJ
ajst-32536	33	11	functional	functional	ADJ
ajst-32536	33	12	activity	activity	NOUN
ajst-32536	33	13	,	,	PUNCT
ajst-32536	33	14	enabling	enable	VERB
ajst-32536	33	15	the	the	DET
ajst-32536	33	16	capture	capture	NOUN
ajst-32536	33	17	of	of	ADP
ajst-32536	33	18	subtle	subtle	ADJ
ajst-32536	33	19	early	early	ADJ
ajst-32536	33	20	-	-	PUNCT
ajst-32536	33	21	stage	stage	NOUN
ajst-32536	33	22	neurophysiological	neurophysiological	ADJ
ajst-32536	33	23	alterations	alteration	NOUN
ajst-32536	33	24	—	—	PUNCT
ajst-32536	33	25	an	an	DET
ajst-32536	33	26	attribute	attribute	NOUN
ajst-32536	33	27	that	that	PRON
ajst-32536	33	28	outperforms	outperform	VERB
ajst-32536	33	29	ct	ct	PRON
ajst-32536	33	30	and	and	CCONJ
ajst-32536	33	31	mri	mri	NOUN
ajst-32536	33	32	,	,	PUNCT
ajst-32536	33	33	as	as	SCONJ
ajst-32536	33	34	the	the	DET
ajst-32536	33	35	latter	latter	ADJ
ajst-32536	33	36	two	two	NUM
ajst-32536	33	37	show	show	NOUN
ajst-32536	33	38	no	no	DET
ajst-32536	33	39	specific	specific	ADJ
ajst-32536	33	40	imaging	imaging	NOUN
ajst-32536	33	41	changes	change	NOUN
ajst-32536	33	42	in	in	ADP
ajst-32536	33	43	early	early	ADJ
ajst-32536	33	44	pd	pd	PROPN
ajst-32536	33	45	and	and	CCONJ
ajst-32536	33	46	are	be	AUX
ajst-32536	33	47	burdened	burden	VERB
ajst-32536	33	48	by	by	ADP
ajst-32536	33	49	high	high	ADJ
ajst-32536	33	50	equipment	equipment	NOUN
ajst-32536	33	51	and	and	CCONJ
ajst-32536	33	52	examination	examination	NOUN
ajst-32536	33	53	expenses	expense	NOUN
ajst-32536	33	54	.	.	PUNCT
ajst-32536	34	1	göker	göker	NOUN
ajst-32536	34	2	et	et	PROPN
ajst-32536	34	3	al	al	PROPN
ajst-32536	34	4	.	.	PROPN
ajst-32536	34	5	calculated	calculate	VERB
ajst-32536	34	6	the	the	DET
ajst-32536	34	7	power	power	NOUN
ajst-32536	34	8	spectral	spectral	ADJ
ajst-32536	34	9	density	density	NOUN
ajst-32536	34	10	(	(	PUNCT
ajst-32536	34	11	psd	psd	NOUN
ajst-32536	34	12	)	)	PUNCT
ajst-32536	34	13	of	of	ADP
ajst-32536	34	14	eeg	eeg	NOUN
ajst-32536	34	15	signals	signal	NOUN
ajst-32536	34	16	across	across	ADP
ajst-32536	34	17	the	the	DET
ajst-32536	34	18	frequency	frequency	NOUN
ajst-32536	34	19	range	range	NOUN
ajst-32536	34	20	of	of	ADP
ajst-32536	34	21	1	1	NUM
ajst-32536	34	22	to	to	PART
ajst-32536	34	23	49	49	NUM
ajst-32536	34	24	hz	hz	VERB
ajst-32536	34	25	using	use	VERB
ajst-32536	34	26	periodogram	periodogram	NOUN
ajst-32536	34	27	,	,	PUNCT
ajst-32536	34	28	welch	welch	PROPN
ajst-32536	34	29	,	,	PUNCT
ajst-32536	34	30	and	and	CCONJ
ajst-32536	34	31	multitaper	multitaper	PROPN
ajst-32536	34	32	spectral	spectral	ADJ
ajst-32536	34	33	analysis	analysis	NOUN
ajst-32536	34	34	methods	method	NOUN
ajst-32536	34	35	,	,	PUNCT
ajst-32536	34	36	respectively	respectively	ADV
ajst-32536	34	37	.	.	PUNCT
ajst-32536	35	1	this	this	DET
ajst-32536	35	2	approach	approach	NOUN
ajst-32536	35	3	achieved	achieve	VERB
ajst-32536	35	4	a	a	DET
ajst-32536	35	5	specificity	specificity	NOUN
ajst-32536	35	6	of	of	ADP
ajst-32536	35	7	0.965	0.965	NUM
ajst-32536	35	8	,	,	PUNCT
ajst-32536	35	9	a	a	DET
ajst-32536	35	10	sensitivity	sensitivity	NOUN
ajst-32536	35	11	of	of	ADP
ajst-32536	35	12	0.994	0.994	NUM
ajst-32536	35	13	,	,	PUNCT
ajst-32536	35	14	a	a	DET
ajst-32536	35	15	precision	precision	NOUN
ajst-32536	35	16	of	of	ADP
ajst-32536	35	17	0.964	0.964	NUM
ajst-32536	35	18	,	,	PUNCT
ajst-32536	35	19	and	and	CCONJ
ajst-32536	35	20	an	an	DET
ajst-32536	35	21	accuracy	accuracy	NOUN
ajst-32536	35	22	of	of	ADP
ajst-32536	35	23	97.92	97.92	NUM
ajst-32536	35	24	%	%	NOUN
ajst-32536	35	25	[	[	X
ajst-32536	35	26	5	5	NUM
ajst-32536	35	27	]	]	PUNCT
ajst-32536	35	28	.	.	PUNCT
ajst-32536	36	1	nevertheless	nevertheless	ADV
ajst-32536	36	2	,	,	PUNCT
ajst-32536	36	3	psd	psd	NOUN
ajst-32536	36	4	primarily	primarily	ADV
ajst-32536	36	5	reflects	reflect	VERB
ajst-32536	36	6	the	the	DET
ajst-32536	36	7	power	power	NOUN
ajst-32536	36	8	distribution	distribution	NOUN
ajst-32536	36	9	of	of	ADP
ajst-32536	36	10	signals	signal	NOUN
ajst-32536	36	11	across	across	ADP
ajst-32536	36	12	different	different	ADJ
ajst-32536	36	13	frequencies	frequency	NOUN
ajst-32536	36	14	;	;	PUNCT
ajst-32536	36	15	its	its	PRON
ajst-32536	36	16	capacity	capacity	NOUN
ajst-32536	36	17	to	to	PART
ajst-32536	36	18	capture	capture	VERB
ajst-32536	36	19	the	the	DET
ajst-32536	36	20	subtle	subtle	ADJ
ajst-32536	36	21	,	,	PUNCT
ajst-32536	36	22	complex	complex	ADJ
ajst-32536	36	23	changes	change	NOUN
ajst-32536	36	24	in	in	ADP
ajst-32536	36	25	eeg	eeg	NOUN
ajst-32536	36	26	signals	signal	NOUN
ajst-32536	36	27	that	that	PRON
ajst-32536	36	28	occur	occur	VERB
ajst-32536	36	29	during	during	ADP
ajst-32536	36	30	the	the	DET
ajst-32536	36	31	early	early	ADJ
ajst-32536	36	32	stages	stage	NOUN
ajst-32536	36	33	of	of	ADP
ajst-32536	36	34	pd	pd	PROPN
ajst-32536	36	35	is	be	AUX
ajst-32536	36	36	limited	limit	VERB
ajst-32536	36	37	,	,	PUNCT
ajst-32536	36	38	making	make	VERB
ajst-32536	36	39	it	it	PRON
ajst-32536	36	40	difficult	difficult	ADJ
ajst-32536	36	41	to	to	PART
ajst-32536	36	42	accurately	accurately	ADV
ajst-32536	36	43	identify	identify	VERB
ajst-32536	36	44	ambiguous	ambiguous	ADJ
ajst-32536	36	45	and	and	CCONJ
ajst-32536	36	46	atypical	atypical	ADJ
ajst-32536	36	47	features	feature	NOUN
ajst-32536	36	48	.	.	PUNCT
ajst-32536	37	1	zhang	zhang	PROPN
ajst-32536	37	2	et	et	PROPN
ajst-32536	37	3	al	al	PROPN
ajst-32536	37	4	.	.	PROPN
ajst-32536	37	5	quantified	quantify	VERB
ajst-32536	37	6	the	the	DET
ajst-32536	37	7	synchrony	synchrony	NOUN
ajst-32536	37	8	of	of	ADP
ajst-32536	37	9	eeg	eeg	NOUN
ajst-32536	37	10	channels	channel	NOUN
ajst-32536	37	11	across	across	ADP
ajst-32536	37	12	different	different	ADJ
ajst-32536	37	13	frequency	frequency	NOUN
ajst-32536	37	14	bands	band	NOUN
ajst-32536	37	15	(	(	PUNCT
ajst-32536	37	16	delta	delta	NOUN
ajst-32536	37	17	,	,	PUNCT
ajst-32536	37	18	theta	theta	NOUN
ajst-32536	37	19	,	,	PUNCT
ajst-32536	37	20	alpha	alpha	NOUN
ajst-32536	37	21	,	,	PUNCT
ajst-32536	37	22	and	and	CCONJ
ajst-32536	37	23	beta	beta	NOUN
ajst-32536	37	24	)	)	PUNCT
ajst-32536	37	25	in	in	ADP
ajst-32536	37	26	early	early	ADJ
ajst-32536	37	27	pd	pd	NOUN
ajst-32536	37	28	by	by	ADP
ajst-32536	37	29	calculating	calculate	VERB
ajst-32536	37	30	the	the	DET
ajst-32536	37	31	phase	phase	NOUN
ajst-32536	37	32	synchronization	synchronization	NOUN
ajst-32536	37	33	index	index	NOUN
ajst-32536	37	34	.	.	PUNCT
ajst-32536	38	1	by	by	ADP
ajst-32536	38	2	comparing	compare	VERB
ajst-32536	38	3	the	the	DET
ajst-32536	38	4	graph	graph	NOUN
ajst-32536	38	5	-	-	PUNCT
ajst-32536	38	6	theoretic	theoretic	NOUN
ajst-32536	38	7	features	feature	NOUN
ajst-32536	38	8	in	in	ADP
ajst-32536	38	9	the	the	DET
ajst-32536	38	10	delta	delta	NOUN
ajst-32536	38	11	band	band	NOUN
ajst-32536	38	12	between	between	ADP
ajst-32536	38	13	the	the	DET
ajst-32536	38	14	pd	pd	PROPN
ajst-32536	38	15	group	group	NOUN
ajst-32536	38	16	and	and	CCONJ
ajst-32536	38	17	the	the	DET
ajst-32536	38	18	healthy	healthy	ADJ
ajst-32536	38	19	control	control	NOUN
ajst-32536	38	20	(	(	PUNCT
ajst-32536	38	21	hc	hc	NOUN
ajst-32536	38	22	)	)	PUNCT
ajst-32536	38	23	group	group	NOUN
ajst-32536	38	24	,	,	PUNCT
ajst-32536	38	25	the	the	DET
ajst-32536	38	26	study	study	NOUN
ajst-32536	38	27	concluded	conclude	VERB
ajst-32536	38	28	that	that	SCONJ
ajst-32536	38	29	there	there	PRON
ajst-32536	38	30	are	be	VERB
ajst-32536	38	31	significant	significant	ADJ
ajst-32536	38	32	differences	difference	NOUN
ajst-32536	38	33	in	in	ADP
ajst-32536	38	34	specific	specific	ADJ
ajst-32536	38	35	frequency	frequency	NOUN
ajst-32536	38	36	bands	band	NOUN
ajst-32536	38	37	of	of	ADP
ajst-32536	38	38	brain	brain	NOUN
ajst-32536	38	39	network	network	NOUN
ajst-32536	38	40	structure	structure	NOUN
ajst-32536	38	41	between	between	ADP
ajst-32536	38	42	patients	patient	NOUN
ajst-32536	38	43	with	with	ADP
ajst-32536	38	44	early	early	ADJ
ajst-32536	38	45	pd	pd	PROPN
ajst-32536	38	46	and	and	CCONJ
ajst-32536	38	47	healthy	healthy	ADJ
ajst-32536	38	48	subjects	subject	NOUN
ajst-32536	38	49	,	,	PUNCT
ajst-32536	38	50	with	with	ADP
ajst-32536	38	51	patients	patient	NOUN
ajst-32536	38	52	with	with	ADP
ajst-32536	38	53	early	early	ADJ
ajst-32536	38	54	pd	pd	NOUN
ajst-32536	38	55	exhibiting	exhibit	VERB
ajst-32536	38	56	abnormal	abnormal	ADJ
ajst-32536	38	57	characteristic	characteristic	ADJ
ajst-32536	38	58	brain	brain	NOUN
ajst-32536	38	59	activity	activity	NOUN
ajst-32536	38	60	in	in	ADP
ajst-32536	38	61	specific	specific	ADJ
ajst-32536	38	62	frequency	frequency	NOUN
ajst-32536	38	63	bands	band	NOUN
ajst-32536	38	64	[	[	X
ajst-32536	38	65	6	6	NUM
ajst-32536	38	66	]	]	PUNCT
ajst-32536	38	67	.	.	PUNCT
ajst-32536	39	1	however	however	ADV
ajst-32536	39	2	,	,	PUNCT
ajst-32536	39	3	the	the	DET
ajst-32536	39	4	frequency	frequency	NOUN
ajst-32536	39	5	band	band	NOUN
ajst-32536	39	6	analysis	analysis	NOUN
ajst-32536	39	7	scope	scope	NOUN
ajst-32536	39	8	of	of	ADP
ajst-32536	39	9	this	this	DET
ajst-32536	39	10	method	method	NOUN
ajst-32536	39	11	is	be	AUX
ajst-32536	39	12	relatively	relatively	ADV
ajst-32536	39	13	narrow	narrow	ADJ
ajst-32536	39	14	:	:	PUNCT
ajst-32536	39	15	it	it	PRON
ajst-32536	39	16	only	only	ADV
ajst-32536	39	17	focuses	focus	VERB
ajst-32536	39	18	on	on	ADP
ajst-32536	39	19	comparing	compare	VERB
ajst-32536	39	20	the	the	DET
ajst-32536	39	21	graph	graph	NOUN
ajst-32536	39	22	-	-	PUNCT
ajst-32536	39	23	theoretic	theoretic	ADJ
ajst-32536	39	24	features	feature	NOUN
ajst-32536	39	25	of	of	ADP
ajst-32536	39	26	the	the	DET
ajst-32536	39	27	delta	delta	NOUN
ajst-32536	39	28	band	band	NOUN
ajst-32536	39	29	and	and	CCONJ
ajst-32536	39	30	fails	fail	VERB
ajst-32536	39	31	to	to	PART
ajst-32536	39	32	fully	fully	ADV
ajst-32536	39	33	incorporate	incorporate	VERB
ajst-32536	39	34	the	the	DET
ajst-32536	39	35	analysis	analysis	NOUN
ajst-32536	39	36	of	of	ADP
ajst-32536	39	37	synchrony	synchrony	ADJ
ajst-32536	39	38	differences	difference	NOUN
ajst-32536	39	39	across	across	ADP
ajst-32536	39	40	other	other	ADJ
ajst-32536	39	41	frequency	frequency	NOUN
ajst-32536	39	42	bands	band	NOUN
ajst-32536	39	43	.	.	PUNCT
ajst-32536	40	1	minh	minh	PROPN
ajst-32536	40	2	tai	tai	PROPN
ajst-32536	41	1	pham	pham	PROPN
ajst-32536	41	2	nguyen	nguyen	PROPN
ajst-32536	41	3	et	et	PROPN
ajst-32536	41	4	al	al	PROPN
ajst-32536	41	5	.	.	PROPN
ajst-32536	41	6	proposed	propose	VERB
ajst-32536	41	7	dense	dense	ADJ
ajst-32536	41	8	multiscale	multiscale	ADJ
ajst-32536	41	9	sample	sample	NOUN
ajst-32536	41	10	entropy	entropy	NOUN
ajst-32536	41	11	(	(	PUNCT
ajst-32536	41	12	dm	dm	NOUN
ajst-32536	41	13	-	-	PUNCT
ajst-32536	41	14	samen	samen	NOUN
ajst-32536	41	15	)	)	PUNCT
ajst-32536	41	16	,	,	PUNCT
ajst-32536	41	17	which	which	PRON
ajst-32536	41	18	adopts	adopt	VERB
ajst-32536	41	19	a	a	DET
ajst-32536	41	20	weighting	weighting	NOUN
ajst-32536	41	21	mechanism	mechanism	NOUN
ajst-32536	41	22	to	to	PART
ajst-32536	41	23	reduce	reduce	VERB
ajst-32536	41	24	redundancy	redundancy	NOUN
ajst-32536	41	25	.	.	PUNCT
ajst-32536	42	1	in	in	ADP
ajst-32536	42	2	pd	pd	PROPN
ajst-32536	42	3	classification	classification	NOUN
ajst-32536	42	4	,	,	PUNCT
ajst-32536	42	5	this	this	DET
ajst-32536	42	6	method	method	NOUN
ajst-32536	42	7	achieved	achieve	VERB
ajst-32536	42	8	a	a	DET
ajst-32536	42	9	maximum	maximum	ADJ
ajst-32536	42	10	accuracy	accuracy	NOUN
ajst-32536	42	11	of	of	ADP
ajst-32536	42	12	98.38	98.38	NUM
ajst-32536	42	13	%	%	NOUN
ajst-32536	42	14	[	[	X
ajst-32536	42	15	7	7	NUM
ajst-32536	42	16	]	]	PUNCT
ajst-32536	42	17	.	.	PUNCT
ajst-32536	43	1	that	that	PRON
ajst-32536	43	2	said	say	VERB
ajst-32536	43	3	,	,	PUNCT
ajst-32536	43	4	this	this	DET
ajst-32536	43	5	method	method	NOUN
ajst-32536	43	6	relies	rely	VERB
ajst-32536	43	7	on	on	ADP
ajst-32536	43	8	reliable	reliable	ADJ
ajst-32536	43	9	and	and	CCONJ
ajst-32536	43	10	publicly	publicly	ADV
ajst-32536	43	11	accessible	accessible	ADJ
ajst-32536	43	12	datasets	dataset	NOUN
ajst-32536	43	13	for	for	ADP
ajst-32536	43	14	its	its	PRON
ajst-32536	43	15	data	data	NOUN
ajst-32536	43	16	source	source	NOUN
ajst-32536	43	17	,	,	PUNCT
ajst-32536	43	18	which	which	PRON
ajst-32536	43	19	may	may	AUX
ajst-32536	43	20	lead	lead	VERB
ajst-32536	43	21	to	to	ADP
ajst-32536	43	22	data	datum	NOUN
ajst-32536	43	23	imbalance	imbalance	NOUN
ajst-32536	43	24	;	;	PUNCT
ajst-32536	43	25	additionally	additionally	ADV
ajst-32536	43	26	,	,	PUNCT
ajst-32536	43	27	it	it	PRON
ajst-32536	43	28	exhibits	exhibit	VERB
ajst-32536	43	29	excessive	excessive	ADJ
ajst-32536	43	30	dependence	dependence	NOUN
ajst-32536	43	31	on	on	ADP
ajst-32536	43	32	a	a	DET
ajst-32536	43	33	single	single	ADJ
ajst-32536	43	34	dataset	dataset	NOUN
ajst-32536	43	35	.	.	PUNCT
ajst-32536	44	1	b.	b.	PROPN
ajst-32536	44	2	vidya	vidya	PROPN
ajst-32536	44	3	et	et	PROPN
ajst-32536	44	4	al	al	PROPN
ajst-32536	44	5	.	.	PROPN
ajst-32536	44	6	developed	develop	VERB
ajst-32536	44	7	a	a	DET
ajst-32536	44	8	gait	gait	ADJ
ajst-32536	44	9	classification	classification	NOUN
ajst-32536	44	10	-	-	PUNCT
ajst-32536	44	11	based	base	VERB
ajst-32536	44	12	decision	decision	NOUN
ajst-32536	44	13	support	support	NOUN
ajst-32536	44	14	system	system	NOUN
ajst-32536	44	15	using	use	VERB
ajst-32536	44	16	a	a	DET
ajst-32536	44	17	multiclass	multiclass	ADJ
ajst-32536	44	18	support	support	NOUN
ajst-32536	44	19	vector	vector	NOUN
ajst-32536	44	20	machine	machine	NOUN
ajst-32536	44	21	(	(	PUNCT
ajst-32536	44	22	mcsvm	mcsvm	NOUN
ajst-32536	44	23	)	)	PUNCT
ajst-32536	44	24	,	,	PUNCT
ajst-32536	44	25	employing	employ	VERB
ajst-32536	44	26	a	a	DET
ajst-32536	44	27	multiple	multiple	ADJ
ajst-32536	44	28	regression	regression	NOUN
ajst-32536	44	29	method	method	NOUN
ajst-32536	44	30	to	to	PART
ajst-32536	44	31	normalize	normalize	VERB
ajst-32536	44	32	gait	gait	ADJ
ajst-32536	44	33	time	time	NOUN
ajst-32536	44	34	-	-	PUNCT
ajst-32536	44	35	series	series	NOUN
ajst-32536	44	36	data	datum	NOUN
ajst-32536	44	37	.	.	PUNCT
ajst-32536	45	1	experimental	experimental	ADJ
ajst-32536	45	2	results	result	NOUN
ajst-32536	45	3	demonstrated	demonstrate	VERB
ajst-32536	45	4	that	that	SCONJ
ajst-32536	45	5	the	the	DET
ajst-32536	45	6	quadratic	quadratic	ADJ
ajst-32536	45	7	svm	svm	NOUN
ajst-32536	45	8	achieved	achieve	VERB
ajst-32536	45	9	an	an	DET
ajst-32536	45	10	average	average	ADJ
ajst-32536	45	11	accuracy	accuracy	NOUN
ajst-32536	45	12	of	of	ADP
ajst-32536	45	13	98.65	98.65	NUM
ajst-32536	45	14	%	%	NOUN
ajst-32536	45	15	,	,	PUNCT
ajst-32536	45	16	outperforming	outperform	VERB
ajst-32536	45	17	several	several	ADJ
ajst-32536	45	18	other	other	ADJ
ajst-32536	45	19	state	state	NOUN
ajst-32536	45	20	-	-	PUNCT
ajst-32536	45	21	of	of	ADP
ajst-32536	45	22	-	-	PUNCT
ajst-32536	45	23	the	the	DET
ajst-32536	45	24	-	-	PUNCT
ajst-32536	45	25	art	art	NOUN
ajst-32536	45	26	methods	method	NOUN
ajst-32536	45	27	that	that	PRON
ajst-32536	45	28	utilize	utilize	VERB
ajst-32536	45	29	gait	gait	NOUN
ajst-32536	45	30	datasets	dataset	NOUN
ajst-32536	45	31	for	for	ADP
ajst-32536	45	32	pd	pd	NOUN
ajst-32536	45	33	diagnosis	diagnosis	NOUN
ajst-32536	45	34	[	[	X
ajst-32536	45	35	8	8	NUM
ajst-32536	45	36	]	]	PUNCT
ajst-32536	45	37	.	.	PUNCT
ajst-32536	46	1	however	however	ADV
ajst-32536	46	2	,	,	PUNCT
ajst-32536	46	3	this	this	DET
ajst-32536	46	4	method	method	NOUN
ajst-32536	46	5	integrates	integrate	VERB
ajst-32536	46	6	multiple	multiple	ADJ
ajst-32536	46	7	binary	binary	ADJ
ajst-32536	46	8	classifiers	classifier	NOUN
ajst-32536	46	9	through	through	ADP
ajst-32536	46	10	"	"	PUNCT
ajst-32536	46	11	one	one	NUM
ajst-32536	46	12	-	-	PUNCT
ajst-32536	46	13	vs	vs	ADP
ajst-32536	46	14	-	-	PUNCT
ajst-32536	46	15	one	one	NOUN
ajst-32536	46	16	"	"	PUNCT
ajst-32536	46	17	or	or	CCONJ
ajst-32536	46	18	"	"	PUNCT
ajst-32536	46	19	one	one	NUM
ajst-32536	46	20	-	-	PUNCT
ajst-32536	46	21	vs	vs	ADP
ajst-32536	46	22	-	-	PUNCT
ajst-32536	46	23	rest	rest	NOUN
ajst-32536	46	24	"	"	PUNCT
ajst-32536	46	25	strategies	strategy	NOUN
ajst-32536	46	26	,	,	PUNCT
ajst-32536	46	27	which	which	PRON
ajst-32536	46	28	significantly	significantly	ADV
ajst-32536	46	29	increases	increase	VERB
ajst-32536	46	30	the	the	DET
ajst-32536	46	31	complexity	complexity	NOUN
ajst-32536	46	32	of	of	ADP
ajst-32536	46	33	the	the	DET
ajst-32536	46	34	model	model	NOUN
ajst-32536	46	35	.	.	PUNCT
ajst-32536	47	1	in	in	ADP
ajst-32536	47	2	recent	recent	ADJ
ajst-32536	47	3	years	year	NOUN
ajst-32536	47	4	,	,	PUNCT
ajst-32536	47	5	deep	deep	ADJ
ajst-32536	47	6	learning	learning	NOUN
ajst-32536	47	7	-	-	PUNCT
ajst-32536	47	8	based	base	VERB
ajst-32536	47	9	methods	method	NOUN
ajst-32536	47	10	30	30	NUM
ajst-32536	47	11	have	have	AUX
ajst-32536	47	12	been	be	AUX
ajst-32536	47	13	increasingly	increasingly	ADV
ajst-32536	47	14	applied	apply	VERB
ajst-32536	47	15	in	in	ADP
ajst-32536	47	16	pd	pd	PROPN
ajst-32536	47	17	detection	detection	NOUN
ajst-32536	47	18	,	,	PUNCT
ajst-32536	47	19	including	include	VERB
ajst-32536	47	20	convolutional	convolutional	ADJ
ajst-32536	47	21	neural	neural	ADJ
ajst-32536	47	22	networks	network	NOUN
ajst-32536	47	23	(	(	PUNCT
ajst-32536	47	24	cnns	cnns	PROPN
ajst-32536	47	25	)	)	PUNCT
ajst-32536	47	26	,	,	PUNCT
ajst-32536	47	27	long	long	ADJ
ajst-32536	47	28	short	short	ADJ
ajst-32536	47	29	-	-	PUNCT
ajst-32536	47	30	term	term	NOUN
ajst-32536	47	31	memory	memory	NOUN
ajst-32536	47	32	(	(	PUNCT
ajst-32536	47	33	lstm	lstm	NOUN
ajst-32536	47	34	)	)	PUNCT
ajst-32536	47	35	networks	network	NOUN
ajst-32536	47	36	,	,	PUNCT
ajst-32536	47	37	graph	graph	VERB
ajst-32536	47	38	convolutional	convolutional	ADJ
ajst-32536	47	39	networks	network	NOUN
ajst-32536	47	40	(	(	PUNCT
ajst-32536	47	41	gcns	gcns	PROPN
ajst-32536	47	42	)	)	PUNCT
ajst-32536	47	43	,	,	PUNCT
ajst-32536	47	44	and	and	CCONJ
ajst-32536	47	45	deep	deep	ADJ
ajst-32536	47	46	residual	residual	ADJ
ajst-32536	47	47	networks	network	NOUN
ajst-32536	47	48	(	(	PUNCT
ajst-32536	47	49	resnets	resnet	NOUN
ajst-32536	47	50	)	)	PUNCT
ajst-32536	47	51	.	.	PUNCT
ajst-32536	48	1	sivaranjini	sivaranjini	PROPN
ajst-32536	48	2	s	s	X
ajst-32536	48	3	et	et	PROPN
ajst-32536	48	4	al	al	PROPN
ajst-32536	48	5	.	.	PROPN
ajst-32536	48	6	refined	refine	VERB
ajst-32536	48	7	the	the	DET
ajst-32536	48	8	diagnosis	diagnosis	NOUN
ajst-32536	48	9	of	of	ADP
ajst-32536	48	10	parkinson	parkinson	NOUN
ajst-32536	48	11	’s	’s	PART
ajst-32536	48	12	disease	disease	NOUN
ajst-32536	48	13	(	(	PUNCT
ajst-32536	48	14	pd	pd	NOUN
ajst-32536	48	15	)	)	PUNCT
ajst-32536	48	16	using	use	VERB
ajst-32536	48	17	the	the	DET
ajst-32536	48	18	alexnet	alexnet	ADJ
ajst-32536	48	19	architecture	architecture	NOUN
ajst-32536	48	20	,	,	PUNCT
ajst-32536	48	21	a	a	DET
ajst-32536	48	22	type	type	NOUN
ajst-32536	48	23	of	of	ADP
ajst-32536	48	24	convolutional	convolutional	ADJ
ajst-32536	48	25	neural	neural	ADJ
ajst-32536	48	26	network	network	NOUN
ajst-32536	48	27	(	(	PUNCT
ajst-32536	48	28	cnn	cnn	PROPN
ajst-32536	48	29	)	)	PUNCT
ajst-32536	48	30	.	.	PUNCT
ajst-32536	49	1	they	they	PRON
ajst-32536	49	2	trained	train	VERB
ajst-32536	49	3	magnetic	magnetic	ADJ
ajst-32536	49	4	resonance	resonance	NOUN
ajst-32536	49	5	(	(	PUNCT
ajst-32536	49	6	mr	mr	PROPN
ajst-32536	49	7	)	)	PUNCT
ajst-32536	49	8	images	image	NOUN
ajst-32536	49	9	through	through	ADP
ajst-32536	49	10	a	a	DET
ajst-32536	49	11	transfer	transfer	NOUN
ajst-32536	49	12	learning	learn	VERB
ajst-32536	49	13	network	network	NOUN
ajst-32536	49	14	and	and	CCONJ
ajst-32536	49	15	conducted	conduct	VERB
ajst-32536	49	16	tests	test	NOUN
ajst-32536	49	17	to	to	PART
ajst-32536	49	18	measure	measure	VERB
ajst-32536	49	19	diagnostic	diagnostic	ADJ
ajst-32536	49	20	accuracy	accuracy	NOUN
ajst-32536	49	21	,	,	PUNCT
ajst-32536	49	22	achieving	achieve	VERB
ajst-32536	49	23	an	an	DET
ajst-32536	49	24	accuracy	accuracy	NOUN
ajst-32536	49	25	rate	rate	NOUN
ajst-32536	49	26	of	of	ADP
ajst-32536	49	27	88.9	88.9	NUM
ajst-32536	49	28	%	%	NOUN
ajst-32536	50	1	[	[	X
ajst-32536	50	2	9	9	NUM
ajst-32536	50	3	]	]	PUNCT
ajst-32536	50	4	.	.	PUNCT
ajst-32536	51	1	however	however	ADV
ajst-32536	51	2	,	,	PUNCT
ajst-32536	51	3	due	due	ADP
ajst-32536	51	4	to	to	ADP
ajst-32536	51	5	the	the	DET
ajst-32536	51	6	relatively	relatively	ADV
ajst-32536	51	7	shallow	shallow	ADJ
ajst-32536	51	8	depth	depth	NOUN
ajst-32536	51	9	of	of	ADP
ajst-32536	51	10	the	the	DET
ajst-32536	51	11	alexnet	alexnet	ADJ
ajst-32536	51	12	model	model	NOUN
ajst-32536	51	13	,	,	PUNCT
ajst-32536	51	14	its	its	PRON
ajst-32536	51	15	ability	ability	NOUN
ajst-32536	51	16	to	to	PART
ajst-32536	51	17	capture	capture	VERB
ajst-32536	51	18	subtle	subtle	ADJ
ajst-32536	51	19	structural	structural	ADJ
ajst-32536	51	20	changes	change	NOUN
ajst-32536	51	21	related	relate	VERB
ajst-32536	51	22	to	to	ADP
ajst-32536	51	23	pd	pd	PROPN
ajst-32536	51	24	in	in	ADP
ajst-32536	51	25	mr	mr	PROPN
ajst-32536	51	26	images	image	NOUN
ajst-32536	51	27	is	be	AUX
ajst-32536	51	28	limited	limit	VERB
ajst-32536	51	29	,	,	PUNCT
ajst-32536	51	30	which	which	PRON
ajst-32536	51	31	may	may	AUX
ajst-32536	51	32	result	result	VERB
ajst-32536	51	33	in	in	ADP
ajst-32536	51	34	the	the	DET
ajst-32536	51	35	omission	omission	NOUN
ajst-32536	51	36	of	of	ADP
ajst-32536	51	37	key	key	ADJ
ajst-32536	51	38	pathological	pathological	ADJ
ajst-32536	51	39	features	feature	NOUN
ajst-32536	51	40	.	.	PUNCT
ajst-32536	52	1	fatih	fatih	PROPN
ajst-32536	52	2	demir	demir	PROPN
ajst-32536	52	3	et	et	PROPN
ajst-32536	52	4	al	al	PROPN
ajst-32536	52	5	.	.	PROPN
ajst-32536	52	6	transformed	transform	VERB
ajst-32536	52	7	all	all	DET
ajst-32536	52	8	input	input	NOUN
ajst-32536	52	9	feature	feature	NOUN
ajst-32536	52	10	vectors	vector	NOUN
ajst-32536	52	11	into	into	ADP
ajst-32536	52	12	input	input	NOUN
ajst-32536	52	13	images	image	NOUN
ajst-32536	52	14	and	and	CCONJ
ajst-32536	52	15	employed	employ	VERB
ajst-32536	52	16	a	a	DET
ajst-32536	52	17	deep	deep	ADJ
ajst-32536	52	18	long	long	ADJ
ajst-32536	52	19	short	short	ADJ
ajst-32536	52	20	-	-	PUNCT
ajst-32536	52	21	term	term	NOUN
ajst-32536	52	22	memory	memory	NOUN
ajst-32536	52	23	(	(	PUNCT
ajst-32536	52	24	lstm	lstm	NOUN
ajst-32536	52	25	)	)	PUNCT
ajst-32536	52	26	network	network	NOUN
ajst-32536	52	27	for	for	ADP
ajst-32536	52	28	pd	pd	NOUN
ajst-32536	52	29	diagnosis	diagnosis	NOUN
ajst-32536	52	30	,	,	PUNCT
ajst-32536	52	31	attaining	attain	VERB
ajst-32536	52	32	an	an	DET
ajst-32536	52	33	accuracy	accuracy	NOUN
ajst-32536	52	34	of	of	ADP
ajst-32536	52	35	94.27	94.27	NUM
ajst-32536	52	36	%	%	NOUN
ajst-32536	52	37	[	[	X
ajst-32536	52	38	10	10	NUM
ajst-32536	52	39	]	]	PUNCT
ajst-32536	52	40	.	.	PUNCT
ajst-32536	53	1	nevertheless	nevertheless	ADV
ajst-32536	53	2	,	,	PUNCT
ajst-32536	53	3	the	the	DET
ajst-32536	53	4	process	process	NOUN
ajst-32536	53	5	of	of	ADP
ajst-32536	53	6	converting	convert	VERB
ajst-32536	53	7	feature	feature	NOUN
ajst-32536	53	8	vectors	vector	NOUN
ajst-32536	53	9	to	to	ADP
ajst-32536	53	10	images	image	NOUN
ajst-32536	53	11	in	in	ADP
ajst-32536	53	12	this	this	DET
ajst-32536	53	13	method	method	NOUN
ajst-32536	53	14	lacks	lack	VERB
ajst-32536	53	15	clear	clear	ADJ
ajst-32536	53	16	medical	medical	ADJ
ajst-32536	53	17	justification	justification	NOUN
ajst-32536	53	18	.	.	PUNCT
ajst-32536	54	1	if	if	SCONJ
ajst-32536	54	2	unreasonable	unreasonable	ADJ
ajst-32536	54	3	approaches	approach	NOUN
ajst-32536	54	4	are	be	AUX
ajst-32536	54	5	adopted	adopt	VERB
ajst-32536	54	6	for	for	ADP
ajst-32536	54	7	dimension	dimension	NOUN
ajst-32536	54	8	mapping	mapping	NOUN
ajst-32536	54	9	,	,	PUNCT
ajst-32536	54	10	pixel	pixel	PROPN
ajst-32536	54	11	assignment	assignment	NOUN
ajst-32536	54	12	,	,	PUNCT
ajst-32536	54	13	or	or	CCONJ
ajst-32536	54	14	other	other	ADJ
ajst-32536	54	15	conversion	conversion	NOUN
ajst-32536	54	16	steps	step	NOUN
ajst-32536	54	17	,	,	PUNCT
ajst-32536	54	18	the	the	DET
ajst-32536	54	19	inherent	inherent	ADJ
ajst-32536	54	20	correlations	correlation	NOUN
ajst-32536	54	21	between	between	ADP
ajst-32536	54	22	original	original	ADJ
ajst-32536	54	23	features	feature	NOUN
ajst-32536	54	24	may	may	AUX
ajst-32536	54	25	be	be	AUX
ajst-32536	54	26	disrupted	disrupt	VERB
ajst-32536	54	27	and	and	CCONJ
ajst-32536	54	28	lost	lose	VERB
ajst-32536	54	29	.	.	PUNCT
ajst-32536	55	1	utsha	utsha	PROPN
ajst-32536	55	2	saha	saha	PROPN
ajst-32536	55	3	et	et	PROPN
ajst-32536	55	4	al	al	PROPN
ajst-32536	55	5	.	.	PROPN
ajst-32536	55	6	proposed	propose	VERB
ajst-32536	55	7	a	a	DET
ajst-32536	55	8	diagnostic	diagnostic	ADJ
ajst-32536	55	9	approach	approach	NOUN
ajst-32536	55	10	combining	combine	VERB
ajst-32536	55	11	graph	graph	NOUN
ajst-32536	55	12	convolutional	convolutional	ADJ
ajst-32536	55	13	networks	network	NOUN
ajst-32536	55	14	(	(	PUNCT
ajst-32536	55	15	gcns	gcns	PROPN
ajst-32536	55	16	)	)	PUNCT
ajst-32536	55	17	with	with	ADP
ajst-32536	55	18	an	an	DET
ajst-32536	55	19	euclidean	euclidean	ADJ
ajst-32536	55	20	distance	distance	NOUN
ajst-32536	55	21	-	-	PUNCT
ajst-32536	55	22	based	base	VERB
ajst-32536	55	23	graph	graph	NOUN
ajst-32536	55	24	construction	construction	NOUN
ajst-32536	55	25	method	method	NOUN
ajst-32536	55	26	.	.	PUNCT
ajst-32536	56	1	this	this	DET
ajst-32536	56	2	method	method	NOUN
ajst-32536	56	3	learns	learn	VERB
ajst-32536	56	4	meaningful	meaningful	ADJ
ajst-32536	56	5	feature	feature	NOUN
ajst-32536	56	6	representations	representation	NOUN
ajst-32536	56	7	from	from	ADP
ajst-32536	56	8	graph	graph	NOUN
ajst-32536	56	9	-	-	PUNCT
ajst-32536	56	10	structured	structure	VERB
ajst-32536	56	11	data	datum	NOUN
ajst-32536	56	12	while	while	SCONJ
ajst-32536	56	13	capturing	capture	VERB
ajst-32536	56	14	similarities	similarity	NOUN
ajst-32536	56	15	between	between	ADP
ajst-32536	56	16	patient	patient	ADJ
ajst-32536	56	17	samples	sample	NOUN
ajst-32536	56	18	,	,	PUNCT
ajst-32536	56	19	ultimately	ultimately	ADV
ajst-32536	56	20	achieving	achieve	VERB
ajst-32536	56	21	a	a	DET
ajst-32536	56	22	high	high	ADJ
ajst-32536	56	23	classification	classification	NOUN
ajst-32536	56	24	accuracy	accuracy	NOUN
ajst-32536	56	25	of	of	ADP
ajst-32536	56	26	97.4	97.4	NUM
ajst-32536	56	27	%	%	NOUN
ajst-32536	56	28	on	on	ADP
ajst-32536	56	29	the	the	DET
ajst-32536	56	30	test	test	NOUN
ajst-32536	56	31	set	set	NOUN
ajst-32536	56	32	[	[	X
ajst-32536	56	33	11	11	NUM
ajst-32536	56	34	]	]	PUNCT
ajst-32536	56	35	.	.	PUNCT
ajst-32536	57	1	however	however	ADV
ajst-32536	57	2	,	,	PUNCT
ajst-32536	57	3	this	this	DET
ajst-32536	57	4	method	method	NOUN
ajst-32536	57	5	has	have	VERB
ajst-32536	57	6	a	a	DET
ajst-32536	57	7	limitation	limitation	NOUN
ajst-32536	57	8	in	in	ADP
ajst-32536	57	9	graph	graph	NOUN
ajst-32536	57	10	construction	construction	NOUN
ajst-32536	57	11	:	:	PUNCT
ajst-32536	57	12	it	it	PRON
ajst-32536	57	13	solely	solely	ADV
ajst-32536	57	14	relies	rely	VERB
ajst-32536	57	15	on	on	ADP
ajst-32536	57	16	euclidean	euclidean	ADJ
ajst-32536	57	17	distance	distance	NOUN
ajst-32536	57	18	to	to	PART
ajst-32536	57	19	measure	measure	VERB
ajst-32536	57	20	similarities	similarity	NOUN
ajst-32536	57	21	between	between	ADP
ajst-32536	57	22	patient	patient	ADJ
ajst-32536	57	23	samples	sample	NOUN
ajst-32536	57	24	.	.	PUNCT
ajst-32536	58	1	in	in	ADP
ajst-32536	58	2	clinical	clinical	ADJ
ajst-32536	58	3	practice	practice	NOUN
ajst-32536	58	4	,	,	PUNCT
ajst-32536	58	5	however	however	ADV
ajst-32536	58	6	,	,	PUNCT
ajst-32536	58	7	the	the	DET
ajst-32536	58	8	pathological	pathological	ADJ
ajst-32536	58	9	features	feature	NOUN
ajst-32536	58	10	of	of	ADP
ajst-32536	58	11	patients	patient	NOUN
ajst-32536	58	12	often	often	ADV
ajst-32536	58	13	exhibit	exhibit	VERB
ajst-32536	58	14	non	non	ADJ
ajst-32536	58	15	-	-	ADJ
ajst-32536	58	16	linear	linear	ADJ
ajst-32536	58	17	correlations	correlation	NOUN
ajst-32536	58	18	,	,	PUNCT
ajst-32536	58	19	and	and	CCONJ
ajst-32536	58	20	clinical	clinical	ADJ
ajst-32536	58	21	similarities	similarity	NOUN
ajst-32536	58	22	do	do	AUX
ajst-32536	58	23	not	not	PART
ajst-32536	58	24	necessarily	necessarily	ADV
ajst-32536	58	25	conform	conform	VERB
ajst-32536	58	26	to	to	ADP
ajst-32536	58	27	the	the	DET
ajst-32536	58	28	linear	linear	ADJ
ajst-32536	58	29	assumptions	assumption	NOUN
ajst-32536	58	30	of	of	ADP
ajst-32536	58	31	euclidean	euclidean	ADJ
ajst-32536	58	32	space	space	NOUN
ajst-32536	58	33	—	—	PUNCT
ajst-32536	58	34	this	this	PRON
ajst-32536	58	35	restricts	restrict	VERB
ajst-32536	58	36	the	the	DET
ajst-32536	58	37	model	model	NOUN
ajst-32536	58	38	’s	’s	PART
ajst-32536	58	39	ability	ability	NOUN
ajst-32536	58	40	to	to	PART
ajst-32536	58	41	characterize	characterize	VERB
ajst-32536	58	42	complex	complex	ADJ
ajst-32536	58	43	pathological	pathological	ADJ
ajst-32536	58	44	features	feature	NOUN
ajst-32536	58	45	to	to	ADP
ajst-32536	58	46	a	a	DET
ajst-32536	58	47	certain	certain	ADJ
ajst-32536	58	48	extent	extent	NOUN
ajst-32536	58	49	.	.	PUNCT
ajst-32536	59	1	lucas	lucas	PROPN
ajst-32536	59	2	de	de	PROPN
ajst-32536	59	3	o.	o.	PROPN
ajst-32536	59	4	santos	santos	PROPN
ajst-32536	59	5	et	et	AUX
ajst-32536	59	6	al	al	PROPN
ajst-32536	59	7	.	.	PROPN
ajst-32536	59	8	utilized	utilize	VERB
ajst-32536	59	9	a	a	DET
ajst-32536	59	10	residual	residual	ADJ
ajst-32536	59	11	neural	neural	ADJ
ajst-32536	59	12	network	network	NOUN
ajst-32536	59	13	for	for	ADP
ajst-32536	59	14	pd	pd	NOUN
ajst-32536	59	15	diagnosis	diagnosis	NOUN
ajst-32536	59	16	,	,	PUNCT
ajst-32536	59	17	following	follow	VERB
ajst-32536	59	18	a	a	DET
ajst-32536	59	19	specific	specific	ADJ
ajst-32536	59	20	workflow	workflow	NOUN
ajst-32536	59	21	:	:	PUNCT
ajst-32536	59	22	first	first	ADV
ajst-32536	59	23	converting	convert	VERB
ajst-32536	59	24	electroencephalogram	electroencephalogram	NOUN
ajst-32536	59	25	(	(	PUNCT
ajst-32536	59	26	eeg	eeg	NOUN
ajst-32536	59	27	)	)	PUNCT
ajst-32536	59	28	signals	signal	NOUN
ajst-32536	59	29	to	to	ADP
ajst-32536	59	30	the	the	DET
ajst-32536	59	31	frequency	frequency	NOUN
ajst-32536	59	32	domain	domain	NOUN
ajst-32536	59	33	,	,	PUNCT
ajst-32536	59	34	identifying	identify	VERB
ajst-32536	59	35	spectral	spectral	ADJ
ajst-32536	59	36	markers	marker	NOUN
ajst-32536	59	37	via	via	ADP
ajst-32536	59	38	directed	direct	VERB
ajst-32536	59	39	graphs	graph	NOUN
ajst-32536	59	40	,	,	PUNCT
ajst-32536	59	41	integrating	integrate	VERB
ajst-32536	59	42	multi	multi	ADJ
ajst-32536	59	43	-	-	ADJ
ajst-32536	59	44	channel	channel	ADJ
ajst-32536	59	45	data	datum	NOUN
ajst-32536	59	46	,	,	PUNCT
ajst-32536	59	47	and	and	CCONJ
ajst-32536	59	48	finally	finally	ADV
ajst-32536	59	49	classifying	classify	VERB
ajst-32536	59	50	the	the	DET
ajst-32536	59	51	generated	generate	VERB
ajst-32536	59	52	spectral	spectral	ADJ
ajst-32536	59	53	tensors	tensor	NOUN
ajst-32536	59	54	using	use	VERB
ajst-32536	59	55	different	different	ADJ
ajst-32536	59	56	neural	neural	ADJ
ajst-32536	59	57	network	network	NOUN
ajst-32536	59	58	architectures	architecture	NOUN
ajst-32536	59	59	.	.	PUNCT
ajst-32536	60	1	this	this	DET
ajst-32536	60	2	method	method	NOUN
ajst-32536	60	3	yielded	yield	VERB
ajst-32536	60	4	an	an	DET
ajst-32536	60	5	accuracy	accuracy	NOUN
ajst-32536	60	6	of	of	ADP
ajst-32536	60	7	96.7	96.7	NUM
ajst-32536	60	8	%	%	NOUN
ajst-32536	60	9	,	,	PUNCT
ajst-32536	60	10	a	a	DET
ajst-32536	60	11	precision	precision	NOUN
ajst-32536	60	12	of	of	ADP
ajst-32536	60	13	97.22	97.22	NUM
ajst-32536	60	14	%	%	NOUN
ajst-32536	60	15	,	,	PUNCT
ajst-32536	60	16	and	and	CCONJ
ajst-32536	60	17	an	an	DET
ajst-32536	60	18	f1	f1	NOUN
ajst-32536	60	19	-	-	PUNCT
ajst-32536	60	20	score	score	NOUN
ajst-32536	60	21	of	of	ADP
ajst-32536	60	22	96.63	96.63	NUM
ajst-32536	60	23	%	%	NOUN
ajst-32536	61	1	[	[	X
ajst-32536	61	2	12	12	NUM
ajst-32536	61	3	]	]	PUNCT
ajst-32536	61	4	.	.	PUNCT
ajst-32536	62	1	yet	yet	ADV
ajst-32536	62	2	,	,	PUNCT
ajst-32536	62	3	it	it	PRON
ajst-32536	62	4	has	have	VERB
ajst-32536	62	5	a	a	DET
ajst-32536	62	6	notable	notable	ADJ
ajst-32536	62	7	drawback	drawback	NOUN
ajst-32536	62	8	:	:	PUNCT
ajst-32536	62	9	the	the	DET
ajst-32536	62	10	frequency	frequency	NOUN
ajst-32536	62	11	-	-	PUNCT
ajst-32536	62	12	domain	domain	NOUN
ajst-32536	62	13	transformation	transformation	NOUN
ajst-32536	62	14	leads	lead	VERB
ajst-32536	62	15	to	to	ADP
ajst-32536	62	16	the	the	DET
ajst-32536	62	17	loss	loss	NOUN
ajst-32536	62	18	of	of	ADP
ajst-32536	62	19	time	time	NOUN
ajst-32536	62	20	-	-	PUNCT
ajst-32536	62	21	domain	domain	NOUN
ajst-32536	62	22	information	information	NOUN
ajst-32536	62	23	.	.	PUNCT
ajst-32536	63	1	eeg	eeg	NOUN
ajst-32536	63	2	signals	signal	NOUN
ajst-32536	63	3	contain	contain	VERB
ajst-32536	63	4	rich	rich	ADJ
ajst-32536	63	5	temporal	temporal	ADJ
ajst-32536	63	6	dynamic	dynamic	ADJ
ajst-32536	63	7	features	feature	NOUN
ajst-32536	63	8	,	,	PUNCT
ajst-32536	63	9	and	and	CCONJ
ajst-32536	63	10	simply	simply	ADV
ajst-32536	63	11	converting	convert	VERB
ajst-32536	63	12	them	they	PRON
ajst-32536	63	13	to	to	ADP
ajst-32536	63	14	the	the	DET
ajst-32536	63	15	frequency	frequency	NOUN
ajst-32536	63	16	domain	domain	NOUN
ajst-32536	63	17	for	for	ADP
ajst-32536	63	18	analysis	analysis	NOUN
ajst-32536	63	19	tends	tend	VERB
ajst-32536	63	20	to	to	PART
ajst-32536	63	21	overlook	overlook	VERB
ajst-32536	63	22	transient	transient	ADJ
ajst-32536	63	23	waveform	waveform	NOUN
ajst-32536	63	24	changes	change	NOUN
ajst-32536	63	25	.	.	PUNCT
ajst-32536	64	1	this	this	PRON
ajst-32536	64	2	impairs	impair	VERB
ajst-32536	64	3	the	the	DET
ajst-32536	64	4	accuracy	accuracy	NOUN
ajst-32536	64	5	of	of	ADP
ajst-32536	64	6	capturing	capture	VERB
ajst-32536	64	7	sudden	sudden	ADJ
ajst-32536	64	8	neural	neural	ADJ
ajst-32536	64	9	activities	activity	NOUN
ajst-32536	64	10	and	and	CCONJ
ajst-32536	64	11	is	be	AUX
ajst-32536	64	12	unfavorable	unfavorable	ADJ
ajst-32536	64	13	for	for	ADP
ajst-32536	64	14	excavating	excavate	VERB
ajst-32536	64	15	subtle	subtle	ADJ
ajst-32536	64	16	neurophysiological	neurophysiological	ADJ
ajst-32536	64	17	features	feature	NOUN
ajst-32536	64	18	associated	associate	VERB
ajst-32536	64	19	with	with	ADP
ajst-32536	64	20	early	early	ADJ
ajst-32536	64	21	-	-	PUNCT
ajst-32536	64	22	stage	stage	NOUN
ajst-32536	64	23	pd	pd	NOUN
ajst-32536	64	24	.	.	PROPN
ajst-32536	65	1	in	in	ADP
ajst-32536	65	2	view	view	NOUN
ajst-32536	65	3	of	of	ADP
ajst-32536	65	4	the	the	DET
ajst-32536	65	5	limitations	limitation	NOUN
ajst-32536	65	6	of	of	ADP
ajst-32536	65	7	the	the	DET
ajst-32536	65	8	aforementioned	aforementioned	ADJ
ajst-32536	65	9	methods	method	NOUN
ajst-32536	65	10	,	,	PUNCT
ajst-32536	65	11	this	this	DET
ajst-32536	65	12	study	study	NOUN
ajst-32536	65	13	proposes	propose	VERB
ajst-32536	65	14	the	the	DET
ajst-32536	65	15	use	use	NOUN
ajst-32536	65	16	of	of	ADP
ajst-32536	65	17	a	a	DET
ajst-32536	65	18	deep	deep	ADJ
ajst-32536	65	19	residual	residual	ADJ
ajst-32536	65	20	shrinking	shrink	VERB
ajst-32536	65	21	network	network	NOUN
ajst-32536	65	22	(	(	PUNCT
ajst-32536	65	23	drsn	drsn	PROPN
ajst-32536	65	24	)	)	PUNCT
ajst-32536	65	25	based	base	VERB
ajst-32536	65	26	on	on	ADP
ajst-32536	65	27	pooling	pool	VERB
ajst-32536	65	28	fusion	fusion	NOUN
ajst-32536	65	29	for	for	ADP
ajst-32536	65	30	pd	pd	PROPN
ajst-32536	65	31	detection	detection	NOUN
ajst-32536	65	32	.	.	PUNCT
ajst-32536	66	1	during	during	ADP
ajst-32536	66	2	the	the	DET
ajst-32536	66	3	threshold	threshold	NOUN
ajst-32536	66	4	derivation	derivation	NOUN
ajst-32536	66	5	stage	stage	NOUN
ajst-32536	66	6	of	of	ADP
ajst-32536	66	7	the	the	DET
ajst-32536	66	8	deep	deep	ADJ
ajst-32536	66	9	residual	residual	ADJ
ajst-32536	66	10	shrinking	shrink	VERB
ajst-32536	66	11	network	network	NOUN
ajst-32536	66	12	,	,	PUNCT
ajst-32536	66	13	this	this	DET
ajst-32536	66	14	method	method	NOUN
ajst-32536	66	15	employs	employ	VERB
ajst-32536	66	16	both	both	DET
ajst-32536	66	17	average	average	ADJ
ajst-32536	66	18	pooling	pooling	NOUN
ajst-32536	66	19	and	and	CCONJ
ajst-32536	66	20	max	max	PROPN
ajst-32536	66	21	pooling	pooling	NOUN
ajst-32536	66	22	to	to	PART
ajst-32536	66	23	simultaneously	simultaneously	ADV
ajst-32536	66	24	extract	extract	VERB
ajst-32536	66	25	multi	multi	ADJ
ajst-32536	66	26	-	-	ADJ
ajst-32536	66	27	scale	scale	ADJ
ajst-32536	66	28	features	feature	NOUN
ajst-32536	66	29	of	of	ADP
ajst-32536	66	30	eeg	eeg	NOUN
ajst-32536	66	31	signals	signal	NOUN
ajst-32536	66	32	and	and	CCONJ
ajst-32536	66	33	perform	perform	VERB
ajst-32536	66	34	feature	feature	NOUN
ajst-32536	66	35	fusion	fusion	NOUN
ajst-32536	66	36	,	,	PUNCT
ajst-32536	66	37	thereby	thereby	ADV
ajst-32536	66	38	further	far	ADV
ajst-32536	66	39	enhancing	enhance	VERB
ajst-32536	66	40	its	its	PRON
ajst-32536	66	41	diagnostic	diagnostic	ADJ
ajst-32536	66	42	accuracy	accuracy	NOUN
ajst-32536	66	43	in	in	ADP
ajst-32536	66	44	real	real	ADJ
ajst-32536	66	45	-	-	PUNCT
ajst-32536	66	46	world	world	NOUN
ajst-32536	66	47	scenarios	scenario	NOUN
ajst-32536	66	48	.	.	PUNCT
ajst-32536	67	1	experiments	experiment	NOUN
ajst-32536	67	2	have	have	AUX
ajst-32536	67	3	demonstrated	demonstrate	VERB
ajst-32536	67	4	that	that	SCONJ
ajst-32536	67	5	the	the	DET
ajst-32536	67	6	drsn	drsn	PROPN
ajst-32536	67	7	-	-	PUNCT
ajst-32536	67	8	pf	pf	PROPN
ajst-32536	67	9	method	method	NOUN
ajst-32536	67	10	proposed	propose	VERB
ajst-32536	67	11	in	in	ADP
ajst-32536	67	12	this	this	DET
ajst-32536	67	13	study	study	NOUN
ajst-32536	67	14	can	can	AUX
ajst-32536	67	15	effectively	effectively	ADV
ajst-32536	67	16	achieve	achieve	VERB
ajst-32536	67	17	disease	disease	NOUN
ajst-32536	67	18	diagnosis	diagnosis	NOUN
ajst-32536	67	19	under	under	ADP
ajst-32536	67	20	noise	noise	NOUN
ajst-32536	67	21	conditions	condition	NOUN
ajst-32536	67	22	with	with	ADP
ajst-32536	67	23	different	different	ADJ
ajst-32536	67	24	signal	signal	NOUN
ajst-32536	67	25	-	-	PUNCT
ajst-32536	67	26	to	to	ADP
ajst-32536	67	27	-	-	PUNCT
ajst-32536	67	28	noise	noise	NOUN
ajst-32536	67	29	ratios	ratio	NOUN
ajst-32536	67	30	(	(	PUNCT
ajst-32536	67	31	snr	snr	PROPN
ajst-32536	67	32	)	)	PUNCT
ajst-32536	67	33	.	.	PUNCT
ajst-32536	68	1	2	2	X
ajst-32536	68	2	.	.	X
ajst-32536	68	3	datasets	dataset	VERB
ajst-32536	68	4	2.1	2.1	NUM
ajst-32536	68	5	neurophysiological	neurophysiological	ADJ
ajst-32536	68	6	activity	activity	NOUN
ajst-32536	68	7	datasets	dataset	NOUN
ajst-32536	68	8	for	for	ADP
ajst-32536	68	9	parkinson	parkinson	NOUN
ajst-32536	68	10	’s	’s	PART
ajst-32536	68	11	disease	disease	NOUN
ajst-32536	68	12	this	this	DET
ajst-32536	68	13	dataset	dataset	NOUN
ajst-32536	68	14	encompasses	encompass	VERB
ajst-32536	68	15	electroencephalogram	electroencephalogram	NOUN
ajst-32536	68	16	(	(	PUNCT
ajst-32536	68	17	eeg	eeg	NOUN
ajst-32536	68	18	)	)	PUNCT
ajst-32536	68	19	signals	signal	NOUN
ajst-32536	68	20	that	that	PRON
ajst-32536	68	21	are	be	AUX
ajst-32536	68	22	modeled	model	VERB
ajst-32536	68	23	to	to	PART
ajst-32536	68	24	simulate	simulate	VERB
ajst-32536	68	25	neural	neural	ADJ
ajst-32536	68	26	activity	activity	NOUN
ajst-32536	68	27	in	in	ADP
ajst-32536	68	28	patients	patient	NOUN
ajst-32536	68	29	with	with	ADP
ajst-32536	68	30	parkinson	parkinson	NOUN
ajst-32536	68	31	’s	’s	PART
ajst-32536	68	32	disease	disease	NOUN
ajst-32536	68	33	.	.	PUNCT
ajst-32536	69	1	it	it	PRON
ajst-32536	69	2	is	be	AUX
ajst-32536	69	3	designed	design	VERB
ajst-32536	69	4	to	to	PART
ajst-32536	69	5	underpin	underpin	VERB
ajst-32536	69	6	research	research	NOUN
ajst-32536	69	7	in	in	ADP
ajst-32536	69	8	biomedical	biomedical	ADJ
ajst-32536	69	9	signal	signal	NOUN
ajst-32536	69	10	processing	processing	NOUN
ajst-32536	69	11	,	,	PUNCT
ajst-32536	69	12	as	as	ADV
ajst-32536	69	13	well	well	ADV
ajst-32536	69	14	as	as	ADP
ajst-32536	69	15	investigations	investigation	NOUN
ajst-32536	69	16	into	into	ADP
ajst-32536	69	17	machine	machine	NOUN
ajst-32536	69	18	learning	learning	NOUN
ajst-32536	69	19	models	model	NOUN
ajst-32536	69	20	tailored	tailor	VERB
ajst-32536	69	21	for	for	ADP
ajst-32536	69	22	the	the	DET
ajst-32536	69	23	analysis	analysis	NOUN
ajst-32536	69	24	and	and	CCONJ
ajst-32536	69	25	modulation	modulation	NOUN
ajst-32536	69	26	of	of	ADP
ajst-32536	69	27	neural	neural	ADJ
ajst-32536	69	28	activity	activity	NOUN
ajst-32536	69	29	.	.	PUNCT
ajst-32536	70	1	the	the	DET
ajst-32536	70	2	salient	salient	NOUN
ajst-32536	70	3	features	feature	NOUN
ajst-32536	70	4	of	of	ADP
ajst-32536	70	5	this	this	DET
ajst-32536	70	6	dataset	dataset	NOUN
ajst-32536	70	7	are	be	AUX
ajst-32536	70	8	outlined	outline	VERB
ajst-32536	70	9	as	as	SCONJ
ajst-32536	70	10	follows	follow	VERB
ajst-32536	70	11	:	:	PUNCT
ajst-32536	70	12	first	first	ADV
ajst-32536	70	13	,	,	PUNCT
ajst-32536	70	14	it	it	PRON
ajst-32536	70	15	contains	contain	VERB
ajst-32536	70	16	raw	raw	ADJ
ajst-32536	70	17	time	time	NOUN
ajst-32536	70	18	-	-	PUNCT
ajst-32536	70	19	series	series	NOUN
ajst-32536	70	20	eeg	eeg	NOUN
ajst-32536	70	21	signals	signal	NOUN
ajst-32536	70	22	with	with	ADP
ajst-32536	70	23	artificially	artificially	ADV
ajst-32536	70	24	introduced	introduce	VERB
ajst-32536	70	25	noise	noise	NOUN
ajst-32536	70	26	,	,	PUNCT
ajst-32536	70	27	which	which	PRON
ajst-32536	70	28	serves	serve	VERB
ajst-32536	70	29	to	to	PART
ajst-32536	70	30	replicate	replicate	VERB
ajst-32536	70	31	neural	neural	ADJ
ajst-32536	70	32	activity	activity	NOUN
ajst-32536	70	33	in	in	ADP
ajst-32536	70	34	real	real	ADJ
ajst-32536	70	35	-	-	PUNCT
ajst-32536	70	36	world	world	NOUN
ajst-32536	70	37	scenarios	scenario	NOUN
ajst-32536	70	38	.	.	PUNCT
ajst-32536	71	1	second	second	ADJ
ajst-32536	71	2	,	,	PUNCT
ajst-32536	71	3	time	time	NOUN
ajst-32536	71	4	-	-	PUNCT
ajst-32536	71	5	frequency	frequency	NOUN
ajst-32536	71	6	features	feature	NOUN
ajst-32536	71	7	are	be	AUX
ajst-32536	71	8	derived	derive	VERB
ajst-32536	71	9	through	through	ADP
ajst-32536	71	10	the	the	DET
ajst-32536	71	11	application	application	NOUN
ajst-32536	71	12	of	of	ADP
ajst-32536	71	13	the	the	DET
ajst-32536	71	14	short	short	ADJ
ajst-32536	71	15	-	-	PUNCT
ajst-32536	71	16	time	time	NOUN
ajst-32536	71	17	fourier	fourier	NOUN
ajst-32536	71	18	transform	transform	NOUN
ajst-32536	71	19	(	(	PUNCT
ajst-32536	71	20	stft)—a	stft)—a	NOUN
ajst-32536	71	21	technique	technique	NOUN
ajst-32536	71	22	employed	employ	VERB
ajst-32536	71	23	to	to	PART
ajst-32536	71	24	extract	extract	VERB
ajst-32536	71	25	magnitude	magnitude	NOUN
ajst-32536	71	26	and	and	CCONJ
ajst-32536	71	27	phase	phase	NOUN
ajst-32536	71	28	components	component	NOUN
ajst-32536	71	29	,	,	PUNCT
ajst-32536	71	30	thereby	thereby	ADV
ajst-32536	71	31	enabling	enable	VERB
ajst-32536	71	32	meticulous	meticulous	ADJ
ajst-32536	71	33	time	time	NOUN
ajst-32536	71	34	-	-	PUNCT
ajst-32536	71	35	frequency	frequency	NOUN
ajst-32536	71	36	domain	domain	NOUN
ajst-32536	71	37	analysis	analysis	NOUN
ajst-32536	71	38	.	.	PUNCT
ajst-32536	72	1	31	31	NUM
ajst-32536	72	2	third	third	ADJ
ajst-32536	72	3	,	,	PUNCT
ajst-32536	72	4	it	it	PRON
ajst-32536	72	5	incorporates	incorporate	VERB
ajst-32536	72	6	metadata	metadata	NOUN
ajst-32536	72	7	that	that	PRON
ajst-32536	72	8	includes	include	VERB
ajst-32536	72	9	patient	patient	NOUN
ajst-32536	72	10	-	-	PUNCT
ajst-32536	72	11	specific	specific	ADJ
ajst-32536	72	12	information	information	NOUN
ajst-32536	72	13	such	such	ADJ
ajst-32536	72	14	as	as	ADP
ajst-32536	72	15	age	age	NOUN
ajst-32536	72	16	,	,	PUNCT
ajst-32536	72	17	gender	gender	NOUN
ajst-32536	72	18	,	,	PUNCT
ajst-32536	72	19	clinical	clinical	ADJ
ajst-32536	72	20	stage	stage	NOUN
ajst-32536	72	21	,	,	PUNCT
ajst-32536	72	22	and	and	CCONJ
ajst-32536	72	23	condition	condition	NOUN
ajst-32536	72	24	labels	label	NOUN
ajst-32536	72	25	,	,	PUNCT
ajst-32536	72	26	facilitating	facilitate	VERB
ajst-32536	72	27	contextual	contextual	ADJ
ajst-32536	72	28	comprehension	comprehension	NOUN
ajst-32536	72	29	of	of	ADP
ajst-32536	72	30	the	the	DET
ajst-32536	72	31	data	datum	NOUN
ajst-32536	72	32	.	.	PUNCT
ajst-32536	73	1	fourth	fourth	ADJ
ajst-32536	73	2	,	,	PUNCT
ajst-32536	73	3	a	a	DET
ajst-32536	73	4	target	target	NOUN
ajst-32536	73	5	column	column	NOUN
ajst-32536	73	6	is	be	AUX
ajst-32536	73	7	included	include	VERB
ajst-32536	73	8	,	,	PUNCT
ajst-32536	73	9	where	where	SCONJ
ajst-32536	73	10	numerical	numerical	ADJ
ajst-32536	73	11	labels	label	NOUN
ajst-32536	73	12	correspond	correspond	VERB
ajst-32536	73	13	to	to	ADP
ajst-32536	73	14	distinct	distinct	ADJ
ajst-32536	73	15	states	state	NOUN
ajst-32536	73	16	of	of	ADP
ajst-32536	73	17	parkinson	parkinson	NOUN
ajst-32536	73	18	’s	’s	PART
ajst-32536	73	19	disease	disease	NOUN
ajst-32536	73	20	:	:	PUNCT
ajst-32536	73	21	specifically	specifically	ADV
ajst-32536	73	22	,	,	PUNCT
ajst-32536	73	23	0	0	NUM
ajst-32536	73	24	denotes	denote	NOUN
ajst-32536	73	25	rest	rest	NOUN
ajst-32536	73	26	tremor	tremor	NOUN
ajst-32536	73	27	,	,	PUNCT
ajst-32536	73	28	1	1	NUM
ajst-32536	73	29	represents	represent	VERB
ajst-32536	73	30	rigidity	rigidity	NOUN
ajst-32536	73	31	,	,	PUNCT
ajst-32536	73	32	2	2	NUM
ajst-32536	73	33	indicates	indicate	VERB
ajst-32536	73	34	the	the	DET
ajst-32536	73	35	normal	normal	ADJ
ajst-32536	73	36	state	state	NOUN
ajst-32536	73	37	,	,	PUNCT
ajst-32536	73	38	and	and	CCONJ
ajst-32536	73	39	3	3	NUM
ajst-32536	73	40	stands	stand	VERB
ajst-32536	73	41	for	for	ADP
ajst-32536	73	42	the	the	DET
ajst-32536	73	43	onmedication	onmedication	NOUN
ajst-32536	73	44	state	state	NOUN
ajst-32536	73	45	.	.	PUNCT
ajst-32536	74	1	in	in	ADP
ajst-32536	74	2	essence	essence	NOUN
ajst-32536	74	3	,	,	PUNCT
ajst-32536	74	4	this	this	DET
ajst-32536	74	5	dataset	dataset	NOUN
ajst-32536	74	6	comprises	comprise	VERB
ajst-32536	74	7	synthetic	synthetic	ADJ
ajst-32536	74	8	eeg	eeg	NOUN
ajst-32536	74	9	signal	signal	NOUN
ajst-32536	74	10	data	datum	NOUN
ajst-32536	74	11	simulated	simulate	VERB
ajst-32536	74	12	for	for	ADP
ajst-32536	74	13	parkinson	parkinson	NOUN
ajst-32536	74	14	’s	’s	PART
ajst-32536	74	15	disease	disease	NOUN
ajst-32536	74	16	research	research	NOUN
ajst-32536	74	17	,	,	PUNCT
ajst-32536	74	18	encompassing	encompass	VERB
ajst-32536	74	19	four	four	NUM
ajst-32536	74	20	core	core	NOUN
ajst-32536	74	21	components	component	NOUN
ajst-32536	74	22	:	:	PUNCT
ajst-32536	74	23	patient	patient	ADJ
ajst-32536	74	24	metadata	metadata	NOUN
ajst-32536	74	25	(	(	PUNCT
ajst-32536	74	26	including	include	VERB
ajst-32536	74	27	attributes	attribute	NOUN
ajst-32536	74	28	such	such	ADJ
ajst-32536	74	29	as	as	ADP
ajst-32536	74	30	age	age	NOUN
ajst-32536	74	31	,	,	PUNCT
ajst-32536	74	32	gender	gender	NOUN
ajst-32536	74	33	,	,	PUNCT
ajst-32536	74	34	clinical	clinical	ADJ
ajst-32536	74	35	stage	stage	NOUN
ajst-32536	74	36	,	,	PUNCT
ajst-32536	74	37	and	and	CCONJ
ajst-32536	74	38	condition	condition	NOUN
ajst-32536	74	39	labels	label	NOUN
ajst-32536	74	40	)	)	PUNCT
ajst-32536	74	41	;	;	PUNCT
ajst-32536	75	1	raw	raw	ADJ
ajst-32536	75	2	neural	neural	ADJ
ajst-32536	75	3	signals	signal	NOUN
ajst-32536	75	4	augmented	augment	VERB
ajst-32536	75	5	with	with	ADP
ajst-32536	75	6	noise	noise	NOUN
ajst-32536	75	7	to	to	PART
ajst-32536	75	8	mimic	mimic	VERB
ajst-32536	75	9	real	real	ADJ
ajst-32536	75	10	-	-	PUNCT
ajst-32536	75	11	world	world	NOUN
ajst-32536	75	12	environments	environment	NOUN
ajst-32536	75	13	;	;	PUNCT
ajst-32536	75	14	stft	stft	X
ajst-32536	75	15	-	-	PUNCT
ajst-32536	75	16	derived	derive	VERB
ajst-32536	75	17	features	feature	NOUN
ajst-32536	75	18	(	(	PUNCT
ajst-32536	75	19	encompassing	encompass	VERB
ajst-32536	75	20	magnitude	magnitude	NOUN
ajst-32536	75	21	and	and	CCONJ
ajst-32536	75	22	phase	phase	NOUN
ajst-32536	75	23	components	component	NOUN
ajst-32536	75	24	extracted	extract	VERB
ajst-32536	75	25	via	via	ADP
ajst-32536	75	26	stft	stft	PROPN
ajst-32536	75	27	)	)	PUNCT
ajst-32536	75	28	;	;	PUNCT
ajst-32536	75	29	and	and	CCONJ
ajst-32536	75	30	numerical	numerical	ADJ
ajst-32536	75	31	classifications	classification	NOUN
ajst-32536	75	32	corresponding	correspond	VERB
ajst-32536	75	33	to	to	ADP
ajst-32536	75	34	parkinson	parkinson	NOUN
ajst-32536	75	35	’s	’s	PART
ajst-32536	75	36	disease	disease	NOUN
ajst-32536	75	37	states	state	NOUN
ajst-32536	75	38	(	(	PUNCT
ajst-32536	75	39	e.g.	e.g.	ADV
ajst-32536	75	40	,	,	PUNCT
ajst-32536	75	41	rest	rest	NOUN
ajst-32536	75	42	tremor	tremor	NOUN
ajst-32536	75	43	,	,	PUNCT
ajst-32536	75	44	rigidity	rigidity	NOUN
ajst-32536	75	45	,	,	PUNCT
ajst-32536	75	46	normal	normal	ADJ
ajst-32536	75	47	state	state	NOUN
ajst-32536	75	48	,	,	PUNCT
ajst-32536	75	49	and	and	CCONJ
ajst-32536	75	50	on	on	ADP
ajst-32536	75	51	-	-	PUNCT
ajst-32536	75	52	medication	medication	NOUN
ajst-32536	75	53	state	state	NOUN
ajst-32536	75	54	)	)	PUNCT
ajst-32536	75	55	.	.	PUNCT
ajst-32536	76	1	the	the	DET
ajst-32536	76	2	dataset	dataset	NOUN
ajst-32536	76	3	is	be	AUX
ajst-32536	76	4	accessible	accessible	ADJ
ajst-32536	76	5	at	at	ADP
ajst-32536	76	6	the	the	DET
ajst-32536	76	7	following	follow	VERB
ajst-32536	76	8	link	link	NOUN
ajst-32536	76	9	:	:	PUNCT
ajst-32536	76	10	https://www.kaggle.com/datasets/ziya07/neural-activity-dataset-forparkinsons-disease	https://www.kaggle.com/datasets/ziya07/neural-activity-dataset-forparkinsons-disease	VERB
ajst-32536	76	11	2.2	2.2	NUM
ajst-32536	77	1	the	the	DET
ajst-32536	77	2	new	new	PROPN
ajst-32536	77	3	mexico	mexico	PROPN
ajst-32536	77	4	dataset	dataset	VERB
ajst-32536	77	5	this	this	DET
ajst-32536	77	6	dataset	dataset	NOUN
ajst-32536	77	7	was	be	AUX
ajst-32536	77	8	collected	collect	VERB
ajst-32536	77	9	by	by	ADP
ajst-32536	77	10	the	the	DET
ajst-32536	77	11	university	university	NOUN
ajst-32536	77	12	of	of	ADP
ajst-32536	77	13	new	new	PROPN
ajst-32536	77	14	mexico	mexico	PROPN
ajst-32536	77	15	(	(	PUNCT
ajst-32536	77	16	unm	unm	PROPN
ajst-32536	77	17	)	)	PUNCT
ajst-32536	77	18	and	and	CCONJ
ajst-32536	77	19	comprises	comprise	VERB
ajst-32536	77	20	electroencephalogram	electroencephalogram	NOUN
ajst-32536	77	21	(	(	PUNCT
ajst-32536	77	22	eeg	eeg	NOUN
ajst-32536	77	23	)	)	PUNCT
ajst-32536	77	24	signal	signal	NOUN
ajst-32536	77	25	data	datum	NOUN
ajst-32536	77	26	from	from	ADP
ajst-32536	77	27	27	27	NUM
ajst-32536	77	28	patients	patient	NOUN
ajst-32536	77	29	with	with	ADP
ajst-32536	77	30	parkinson	parkinson	NOUN
ajst-32536	77	31	’s	’s	PART
ajst-32536	77	32	disease	disease	NOUN
ajst-32536	77	33	(	(	PUNCT
ajst-32536	77	34	pd	pd	NOUN
ajst-32536	77	35	)	)	PUNCT
ajst-32536	77	36	and	and	CCONJ
ajst-32536	77	37	27	27	NUM
ajst-32536	77	38	gender	gender	NOUN
ajst-32536	77	39	-	-	PUNCT
ajst-32536	77	40	matched	match	VERB
ajst-32536	77	41	healthy	healthy	ADJ
ajst-32536	77	42	controls	control	NOUN
ajst-32536	77	43	.	.	PUNCT
ajst-32536	78	1	the	the	DET
ajst-32536	78	2	pd	pd	PROPN
ajst-32536	78	3	patients	patient	NOUN
ajst-32536	78	4	visited	visit	VERB
ajst-32536	78	5	the	the	DET
ajst-32536	78	6	laboratory	laboratory	NOUN
ajst-32536	78	7	twice	twice	ADV
ajst-32536	78	8	for	for	ADP
ajst-32536	78	9	data	data	NOUN
ajst-32536	78	10	collection	collection	NOUN
ajst-32536	78	11	,	,	PUNCT
ajst-32536	78	12	with	with	ADP
ajst-32536	78	13	an	an	DET
ajst-32536	78	14	interval	interval	NOUN
ajst-32536	78	15	of	of	ADP
ajst-32536	78	16	7	7	NUM
ajst-32536	78	17	days	day	NOUN
ajst-32536	78	18	[	[	X
ajst-32536	78	19	13	13	NUM
ajst-32536	78	20	]	]	SYM
ajst-32536	78	21	:	:	PUNCT
ajst-32536	78	22	one	one	NUM
ajst-32536	78	23	visit	visit	NOUN
ajst-32536	78	24	occurred	occur	VERB
ajst-32536	78	25	during	during	ADP
ajst-32536	78	26	the	the	DET
ajst-32536	78	27	period	period	NOUN
ajst-32536	78	28	when	when	SCONJ
ajst-32536	78	29	they	they	PRON
ajst-32536	78	30	were	be	AUX
ajst-32536	78	31	on	on	ADP
ajst-32536	78	32	medication	medication	NOUN
ajst-32536	78	33	,	,	PUNCT
ajst-32536	78	34	and	and	CCONJ
ajst-32536	78	35	the	the	DET
ajst-32536	78	36	other	other	ADJ
ajst-32536	78	37	took	take	VERB
ajst-32536	78	38	place	place	NOUN
ajst-32536	78	39	after	after	ADP
ajst-32536	78	40	an	an	DET
ajst-32536	78	41	overnight	overnight	ADJ
ajst-32536	78	42	withdrawal	withdrawal	NOUN
ajst-32536	78	43	from	from	ADP
ajst-32536	78	44	medication	medication	NOUN
ajst-32536	78	45	for	for	ADP
ajst-32536	78	46	15	15	NUM
ajst-32536	78	47	hours	hour	NOUN
ajst-32536	78	48	.	.	PUNCT
ajst-32536	79	1	consequently	consequently	ADV
ajst-32536	79	2	,	,	PUNCT
ajst-32536	79	3	this	this	DET
ajst-32536	79	4	dataset	dataset	NOUN
ajst-32536	79	5	contains	contain	VERB
ajst-32536	79	6	information	information	NOUN
ajst-32536	79	7	on	on	ADP
ajst-32536	79	8	the	the	DET
ajst-32536	79	9	27	27	NUM
ajst-32536	79	10	pd	pd	NOUN
ajst-32536	79	11	patients	patient	NOUN
ajst-32536	79	12	in	in	ADP
ajst-32536	79	13	both	both	PRON
ajst-32536	79	14	treated	treat	VERB
ajst-32536	79	15	(	(	PUNCT
ajst-32536	79	16	on	on	ADP
ajst-32536	79	17	-	-	PUNCT
ajst-32536	79	18	medication	medication	NOUN
ajst-32536	79	19	)	)	PUNCT
ajst-32536	79	20	and	and	CCONJ
ajst-32536	79	21	untreated	untreated	ADJ
ajst-32536	79	22	(	(	PUNCT
ajst-32536	79	23	off	off	ADP
ajst-32536	79	24	-	-	PUNCT
ajst-32536	79	25	medication	medication	NOUN
ajst-32536	79	26	)	)	PUNCT
ajst-32536	79	27	states.for	states.for	ADP
ajst-32536	79	28	each	each	DET
ajst-32536	79	29	patient	patient	NOUN
ajst-32536	79	30	and	and	CCONJ
ajst-32536	79	31	control	control	NOUN
ajst-32536	79	32	subject	subject	NOUN
ajst-32536	79	33	,	,	PUNCT
ajst-32536	79	34	data	datum	NOUN
ajst-32536	79	35	were	be	AUX
ajst-32536	79	36	collected	collect	VERB
ajst-32536	79	37	over	over	ADP
ajst-32536	79	38	a	a	DET
ajst-32536	79	39	duration	duration	NOUN
ajst-32536	79	40	of	of	ADP
ajst-32536	79	41	two	two	NUM
ajst-32536	79	42	minutes	minute	NOUN
ajst-32536	79	43	.	.	PUNCT
ajst-32536	80	1	the	the	DET
ajst-32536	80	2	eeg	eeg	PROPN
ajst-32536	80	3	data	datum	NOUN
ajst-32536	80	4	were	be	AUX
ajst-32536	80	5	acquired	acquire	VERB
ajst-32536	80	6	at	at	ADP
ajst-32536	80	7	a	a	DET
ajst-32536	80	8	sampling	sample	VERB
ajst-32536	80	9	rate	rate	NOUN
ajst-32536	80	10	of	of	ADP
ajst-32536	80	11	500	500	NUM
ajst-32536	80	12	hz	hz	VERB
ajst-32536	80	13	using	use	VERB
ajst-32536	80	14	64	64	NUM
ajst-32536	80	15	silver	silver	ADJ
ajst-32536	80	16	/	/	SYM
ajst-32536	80	17	silver	silver	NOUN
ajst-32536	80	18	chloride	chloride	NOUN
ajst-32536	80	19	(	(	PUNCT
ajst-32536	80	20	ag	ag	NOUN
ajst-32536	80	21	/	/	SYM
ajst-32536	80	22	agcl	agcl	NOUN
ajst-32536	80	23	)	)	PUNCT
ajst-32536	80	24	channels	channel	NOUN
ajst-32536	80	25	,	,	PUNCT
ajst-32536	80	26	with	with	ADP
ajst-32536	80	27	an	an	DET
ajst-32536	80	28	online	online	ADJ
ajst-32536	80	29	reference	reference	NOUN
ajst-32536	80	30	to	to	ADP
ajst-32536	80	31	the	the	DET
ajst-32536	80	32	cpz	cpz	NOUN
ajst-32536	80	33	electrode	electrode	NOUN
ajst-32536	80	34	and	and	CCONJ
ajst-32536	80	35	via	via	ADP
ajst-32536	80	36	the	the	DET
ajst-32536	80	37	brain	brain	NOUN
ajst-32536	80	38	vision	vision	PROPN
ajst-32536	80	39	data	data	PROPN
ajst-32536	80	40	acquisition	acquisition	NOUN
ajst-32536	80	41	system	system	NOUN
ajst-32536	80	42	.	.	PUNCT
ajst-32536	81	1	as	as	ADP
ajst-32536	81	2	a	a	DET
ajst-32536	81	3	result	result	NOUN
ajst-32536	81	4	,	,	PUNCT
ajst-32536	81	5	cpz	cpz	PROPN
ajst-32536	81	6	channel	channel	NOUN
ajst-32536	81	7	data	datum	NOUN
ajst-32536	81	8	are	be	AUX
ajst-32536	81	9	absent	absent	ADJ
ajst-32536	81	10	from	from	ADP
ajst-32536	81	11	this	this	DET
ajst-32536	81	12	dataset	dataset	NOUN
ajst-32536	81	13	.	.	PUNCT
ajst-32536	82	1	3	3	X
ajst-32536	82	2	.	.	X
ajst-32536	82	3	methodology	methodology	NOUN
ajst-32536	82	4	3.1	3.1	NUM
ajst-32536	82	5	theoretical	theoretical	ADJ
ajst-32536	82	6	foundations	foundation	NOUN
ajst-32536	82	7	the	the	DET
ajst-32536	82	8	deep	deep	ADJ
ajst-32536	82	9	residual	residual	ADJ
ajst-32536	82	10	shrinkage	shrinkage	NOUN
ajst-32536	82	11	network	network	NOUN
ajst-32536	82	12	(	(	PUNCT
ajst-32536	82	13	drsn	drsn	PROPN
ajst-32536	82	14	)	)	PUNCT
ajst-32536	82	15	can	can	AUX
ajst-32536	82	16	be	be	AUX
ajst-32536	82	17	regarded	regard	VERB
ajst-32536	82	18	as	as	ADP
ajst-32536	82	19	a	a	DET
ajst-32536	82	20	variant	variant	NOUN
ajst-32536	82	21	of	of	ADP
ajst-32536	82	22	the	the	DET
ajst-32536	82	23	convolutional	convolutional	ADJ
ajst-32536	82	24	neural	neural	ADJ
ajst-32536	82	25	network	network	NOUN
ajst-32536	82	26	(	(	PUNCT
ajst-32536	82	27	cnn	cnn	PROPN
ajst-32536	82	28	)	)	PUNCT
ajst-32536	82	29	.	.	PUNCT
ajst-32536	83	1	it	it	PRON
ajst-32536	83	2	retains	retain	VERB
ajst-32536	83	3	the	the	DET
ajst-32536	83	4	core	core	ADJ
ajst-32536	83	5	architecture	architecture	NOUN
ajst-32536	83	6	of	of	ADP
ajst-32536	83	7	cnn	cnn	PROPN
ajst-32536	83	8	while	while	SCONJ
ajst-32536	83	9	integrating	integrate	VERB
ajst-32536	83	10	residual	residual	ADJ
ajst-32536	83	11	learning	learning	NOUN
ajst-32536	83	12	,	,	PUNCT
ajst-32536	83	13	soft	soft	ADJ
ajst-32536	83	14	-	-	PUNCT
ajst-32536	83	15	threshold	threshold	NOUN
ajst-32536	83	16	denoising	denoising	NOUN
ajst-32536	83	17	,	,	PUNCT
ajst-32536	83	18	and	and	CCONJ
ajst-32536	83	19	the	the	DET
ajst-32536	83	20	attention	attention	NOUN
ajst-32536	83	21	mechanism	mechanism	NOUN
ajst-32536	83	22	(	(	PUNCT
ajst-32536	83	23	am	be	AUX
ajst-32536	83	24	)	)	PUNCT
ajst-32536	83	25	.	.	PUNCT
ajst-32536	84	1	this	this	DET
ajst-32536	84	2	integration	integration	NOUN
ajst-32536	84	3	approach	approach	NOUN
ajst-32536	84	4	not	not	PART
ajst-32536	84	5	only	only	ADV
ajst-32536	84	6	effectively	effectively	ADV
ajst-32536	84	7	addresses	address	VERB
ajst-32536	84	8	the	the	DET
ajst-32536	84	9	challenge	challenge	NOUN
ajst-32536	84	10	of	of	ADP
ajst-32536	84	11	training	train	VERB
ajst-32536	84	12	traditional	traditional	ADJ
ajst-32536	84	13	deep	deep	ADJ
ajst-32536	84	14	networks	network	NOUN
ajst-32536	84	15	—	—	PUNCT
ajst-32536	84	16	a	a	DET
ajst-32536	84	17	long	long	ADV
ajst-32536	84	18	-	-	PUNCT
ajst-32536	84	19	standing	stand	VERB
ajst-32536	84	20	issue	issue	NOUN
ajst-32536	84	21	in	in	ADP
ajst-32536	84	22	deep	deep	ADJ
ajst-32536	84	23	learning	learning	NOUN
ajst-32536	84	24	—	—	PUNCT
ajst-32536	84	25	but	but	CCONJ
ajst-32536	84	26	also	also	ADV
ajst-32536	84	27	enhances	enhance	VERB
ajst-32536	84	28	the	the	DET
ajst-32536	84	29	feature	feature	NOUN
ajst-32536	84	30	extraction	extraction	NOUN
ajst-32536	84	31	performance	performance	NOUN
ajst-32536	84	32	for	for	ADP
ajst-32536	84	33	noisy	noisy	ADJ
ajst-32536	84	34	vibration	vibration	NOUN
ajst-32536	84	35	signals	signal	NOUN
ajst-32536	84	36	,	,	PUNCT
ajst-32536	84	37	thereby	thereby	ADV
ajst-32536	84	38	endowing	endow	VERB
ajst-32536	84	39	the	the	DET
ajst-32536	84	40	network	network	NOUN
ajst-32536	84	41	with	with	ADP
ajst-32536	84	42	excellent	excellent	ADJ
ajst-32536	84	43	denoising	denoising	NOUN
ajst-32536	84	44	capability	capability	NOUN
ajst-32536	84	45	.	.	PUNCT
ajst-32536	85	1	3.1.1	3.1.1	NUM
ajst-32536	85	2	residual	residual	ADJ
ajst-32536	85	3	learning	learn	VERB
ajst-32536	85	4	the	the	DET
ajst-32536	85	5	ideology	ideology	NOUN
ajst-32536	85	6	of	of	ADP
ajst-32536	85	7	residual	residual	ADJ
ajst-32536	85	8	learning	learning	NOUN
ajst-32536	85	9	,	,	PUNCT
ajst-32536	85	10	leveraging	leverage	VERB
ajst-32536	85	11	its	its	PRON
ajst-32536	85	12	unique	unique	ADJ
ajst-32536	85	13	identity	identity	NOUN
ajst-32536	85	14	mapping	mapping	NOUN
ajst-32536	85	15	structure	structure	NOUN
ajst-32536	85	16	,	,	PUNCT
ajst-32536	85	17	has	have	AUX
ajst-32536	85	18	been	be	AUX
ajst-32536	85	19	widely	widely	ADV
ajst-32536	85	20	adopted	adopt	VERB
ajst-32536	85	21	in	in	ADP
ajst-32536	85	22	deep	deep	ADJ
ajst-32536	85	23	learning	learning	NOUN
ajst-32536	85	24	architectures	architecture	NOUN
ajst-32536	85	25	.	.	PUNCT
ajst-32536	86	1	this	this	DET
ajst-32536	86	2	structure	structure	NOUN
ajst-32536	86	3	can	can	AUX
ajst-32536	86	4	effectively	effectively	ADV
ajst-32536	86	5	mitigate	mitigate	VERB
ajst-32536	86	6	the	the	DET
ajst-32536	86	7	phenomena	phenomenon	NOUN
ajst-32536	86	8	of	of	ADP
ajst-32536	86	9	gradient	gradient	ADJ
ajst-32536	86	10	vanishing	vanishing	NOUN
ajst-32536	86	11	or	or	CCONJ
ajst-32536	86	12	gradient	gradient	NOUN
ajst-32536	86	13	exploding	explode	VERB
ajst-32536	86	14	that	that	PRON
ajst-32536	86	15	often	often	ADV
ajst-32536	86	16	occur	occur	VERB
ajst-32536	86	17	in	in	ADP
ajst-32536	86	18	deep	deep	ADJ
ajst-32536	86	19	network	network	NOUN
ajst-32536	86	20	architectures	architecture	NOUN
ajst-32536	86	21	.	.	PUNCT
ajst-32536	87	1	the	the	DET
ajst-32536	87	2	specific	specific	ADJ
ajst-32536	87	3	structure	structure	NOUN
ajst-32536	87	4	is	be	AUX
ajst-32536	87	5	illustrated	illustrate	VERB
ajst-32536	87	6	in	in	ADP
ajst-32536	87	7	figure	figure	NOUN
ajst-32536	87	8	1	1	NUM
ajst-32536	87	9	.	.	PUNCT
ajst-32536	87	10	residual	residual	ADJ
ajst-32536	87	11	learning	learning	NOUN
ajst-32536	87	12	can	can	AUX
ajst-32536	87	13	be	be	AUX
ajst-32536	87	14	mathematically	mathematically	ADV
ajst-32536	87	15	expressed	express	VERB
ajst-32536	87	16	as	as	ADV
ajst-32536	87	17	formulated	formulate	VERB
ajst-32536	87	18	as	as	ADP
ajst-32536	87	19	equation	equation	NOUN
ajst-32536	87	20	(	(	PUNCT
ajst-32536	87	21	1	1	NUM
ajst-32536	87	22	):	):	PUNCT
ajst-32536	87	23			PROPN
ajst-32536	87	24			PROPN
ajst-32536	87	25	,	,	PUNCT
ajst-32536	87	26	iy	iy	PROPN
ajst-32536	87	27	x	x	X
ajst-32536	87	28	s	s	PROPN
ajst-32536	87	29	x	x	PROPN
ajst-32536	87	30			VERB
ajst-32536	87	31			X
ajst-32536	87	32	(	(	PUNCT
ajst-32536	87	33	1	1	NUM
ajst-32536	87	34	)	)	PUNCT
ajst-32536	87	35	in	in	ADP
ajst-32536	87	36	the	the	DET
ajst-32536	87	37	formula(1	formula(1	ADJ
ajst-32536	87	38	):	):	PUNCT
ajst-32536	87	39	x	x	PUNCT
ajst-32536	87	40	and	and	CCONJ
ajst-32536	87	41	y	y	PROPN
ajst-32536	87	42	denote	denote	VERB
ajst-32536	87	43	the	the	DET
ajst-32536	87	44	input	input	NOUN
ajst-32536	87	45	vector	vector	NOUN
ajst-32536	87	46	and	and	CCONJ
ajst-32536	87	47	output	output	NOUN
ajst-32536	87	48	vector	vector	NOUN
ajst-32536	87	49	,	,	PUNCT
ajst-32536	87	50	respectively;si	respectively;si	PROPN
ajst-32536	87	51	represents	represent	VERB
ajst-32536	87	52	the	the	DET
ajst-32536	87	53	coefficient	coefficient	NOUN
ajst-32536	87	54	of	of	ADP
ajst-32536	87	55	the	the	DET
ajst-32536	87	56	i	i	PROPN
ajst-32536	87	57	-	-	PUNCT
ajst-32536	87	58	th	th	X
ajst-32536	87	59	weight	weight	NOUN
ajst-32536	87	60	layer	layer	NOUN
ajst-32536	87	61	;	;	PUNCT
ajst-32536	87	62	and	and	CCONJ
ajst-32536	87	63			VERB
ajst-32536	87	64	stands	stand	VERB
ajst-32536	87	65	for	for	ADP
ajst-32536	87	66	the	the	DET
ajst-32536	87	67	residual	residual	ADJ
ajst-32536	87	68	function	function	NOUN
ajst-32536	87	69	,	,	PUNCT
ajst-32536	87	70	whose	whose	DET
ajst-32536	87	71	expression	expression	NOUN
ajst-32536	87	72	is	be	AUX
ajst-32536	87	73	given	give	VERB
ajst-32536	87	74	by	by	ADP
ajst-32536	87	75	:	:	PUNCT
ajst-32536	87	76			NOUN
ajst-32536	87	77	2	2	NOUN
ajst-32536	87	78	1	1	NUM
ajst-32536	87	79	t	t	NOUN
ajst-32536	87	80	x	x	NOUN
ajst-32536	88	1			PROPN
ajst-32536	88	2	s	s	PART
ajst-32536	88	3	s	s	X
ajst-32536	88	4	(	(	PUNCT
ajst-32536	88	5	2	2	NUM
ajst-32536	88	6	)	)	PUNCT
ajst-32536	88	7	in	in	ADP
ajst-32536	88	8	equation(2),	equation(2),	PROPN
ajst-32536	88	9	denotes	denote	VERB
ajst-32536	88	10	the	the	DET
ajst-32536	88	11	activation	activation	NOUN
ajst-32536	88	12	function	function	NOUN
ajst-32536	88	13	.	.	PUNCT
ajst-32536	89	1	32	32	NUM
ajst-32536	89	2	figure	figure	NOUN
ajst-32536	89	3	1	1	NUM
ajst-32536	89	4	.	.	PUNCT
ajst-32536	89	5	structure	structure	NOUN
ajst-32536	89	6	of	of	ADP
ajst-32536	89	7	residual	residual	ADJ
ajst-32536	89	8	learning	learning	NOUN
ajst-32536	89	9	3.1.2	3.1.2	NUM
ajst-32536	89	10	soft	soft	ADJ
ajst-32536	89	11	-	-	PUNCT
ajst-32536	89	12	thresholding	thresholde	VERB
ajst-32536	89	13	function	function	NOUN
ajst-32536	89	14	the	the	DET
ajst-32536	89	15	soft	soft	ADJ
ajst-32536	89	16	-	-	PUNCT
ajst-32536	89	17	thresholding	thresholde	VERB
ajst-32536	89	18	function	function	NOUN
ajst-32536	89	19	is	be	AUX
ajst-32536	89	20	a	a	DET
ajst-32536	89	21	widely	widely	ADV
ajst-32536	89	22	employed	employ	VERB
ajst-32536	89	23	denoising	denoising	NOUN
ajst-32536	89	24	function	function	NOUN
ajst-32536	89	25	,	,	PUNCT
ajst-32536	89	26	whose	whose	DET
ajst-32536	89	27	core	core	NOUN
ajst-32536	89	28	idea	idea	NOUN
ajst-32536	89	29	lies	lie	VERB
ajst-32536	89	30	in	in	ADP
ajst-32536	89	31	eliminating	eliminate	VERB
ajst-32536	89	32	near	near	ADV
ajst-32536	89	33	-	-	PUNCT
ajst-32536	89	34	zero	zero	NUM
ajst-32536	89	35	features	feature	NOUN
ajst-32536	89	36	within	within	ADP
ajst-32536	89	37	the	the	DET
ajst-32536	89	38	threshold	threshold	NOUN
ajst-32536	89	39	region	region	NOUN
ajst-32536	89	40	.	.	PUNCT
ajst-32536	90	1	the	the	DET
ajst-32536	90	2	definition	definition	NOUN
ajst-32536	90	3	of	of	ADP
ajst-32536	90	4	the	the	DET
ajst-32536	90	5	soft	soft	ADJ
ajst-32536	90	6	-	-	PUNCT
ajst-32536	90	7	thresholding	thresholde	VERB
ajst-32536	90	8	function	function	NOUN
ajst-32536	90	9	is	be	AUX
ajst-32536	90	10	given	give	VERB
ajst-32536	90	11	by	by	ADP
ajst-32536	90	12	:	:	PUNCT
ajst-32536	90	13	(	(	PUNCT
ajst-32536	90	14	)	)	PUNCT
ajst-32536	90	15	(	(	PUNCT
ajst-32536	90	16	|	|	ADV
ajst-32536	90	17	|	|	ADV
ajst-32536	90	18	)	)	PUNCT
ajst-32536	90	19	,	,	PUNCT
ajst-32536	90	20	|	|	ADV
ajst-32536	90	21	|	|	ADV
ajst-32536	90	22	;	;	PUNCT
ajst-32536	90	23	(	(	PUNCT
ajst-32536	90	24	)	)	PUNCT
ajst-32536	90	25	0	0	NUM
ajst-32536	90	26	,	,	PUNCT
ajst-32536	90	27	|	|	ADV
ajst-32536	90	28	|	|	ADV
ajst-32536	90	29	.	.	PUNCT
ajst-32536	91	1	sgn	sgn	NOUN
ajst-32536	91	2	x	x	X
ajst-32536	91	3	x	x	PUNCT
ajst-32536	91	4	x	x	VERB
ajst-32536	91	5	y	y	NOUN
ajst-32536	91	6	f	f	NOUN
ajst-32536	91	7	x	x	X
ajst-32536	91	8	x	x	X
ajst-32536	91	9			NOUN
ajst-32536	91	10			NOUN
ajst-32536	91	11			NOUN
ajst-32536	91	12			NOUN
ajst-32536	91	13			PROPN
ajst-32536	91	14			NUM
ajst-32536	91	15			PROPN
ajst-32536	91	16			NUM
ajst-32536	91	17			PROPN
ajst-32536	91	18	(	(	PUNCT
ajst-32536	91	19	3	3	NUM
ajst-32536	91	20	)	)	PUNCT
ajst-32536	91	21	in	in	ADP
ajst-32536	91	22	formula	formula	NOUN
ajst-32536	91	23	(	(	PUNCT
ajst-32536	91	24	3	3	NUM
ajst-32536	91	25	):	):	PUNCT
ajst-32536	91	26	x	x	X
ajst-32536	91	27	and	and	CCONJ
ajst-32536	91	28	y	y	PROPN
ajst-32536	91	29	represent	represent	VERB
ajst-32536	91	30	the	the	DET
ajst-32536	91	31	input	input	NOUN
ajst-32536	91	32	feature	feature	NOUN
ajst-32536	91	33	and	and	CCONJ
ajst-32536	91	34	output	output	NOUN
ajst-32536	91	35	feature	feature	NOUN
ajst-32536	91	36	,	,	PUNCT
ajst-32536	91	37	respectively	respectively	ADV
ajst-32536	91	38	;	;	PUNCT
ajst-32536	91	39			NOUN
ajst-32536	91	40	denotes	denote	VERB
ajst-32536	91	41	the	the	DET
ajst-32536	91	42	threshold	threshold	NOUN
ajst-32536	91	43	;	;	PUNCT
ajst-32536	91	44	(	(	PUNCT
ajst-32536	91	45	)	)	PUNCT
ajst-32536	91	46	sgn	sgn	NOUN
ajst-32536	91	47			PROPN
ajst-32536	91	48	is	be	AUX
ajst-32536	91	49	a	a	DET
ajst-32536	91	50	sign	sign	NOUN
ajst-32536	91	51	function	function	NOUN
ajst-32536	91	52	.	.	PUNCT
ajst-32536	92	1	when	when	SCONJ
ajst-32536	92	2	0x	0x	X
ajst-32536	92	3			X
ajst-32536	92	4	,	,	PUNCT
ajst-32536	92	5			NOUN
ajst-32536	92	6			PUNCT
ajst-32536	92	7	1sgn	1sgn	NUM
ajst-32536	92	8	x	x	SYM
ajst-32536	92	9			NOUN
ajst-32536	92	10	;	;	PUNCT
ajst-32536	92	11	when	when	SCONJ
ajst-32536	92	12	0x	0x	NOUN
ajst-32536	92	13			NUM
ajst-32536	92	14	,	,	PUNCT
ajst-32536	92	15			NOUN
ajst-32536	92	16			PUNCT
ajst-32536	93	1	0sgn	0sgn	NOUN
ajst-32536	93	2	x	x	PUNCT
ajst-32536	93	3			NOUN
ajst-32536	93	4	;	;	PUNCT
ajst-32536	93	5	when	when	SCONJ
ajst-32536	93	6	0x	0x	X
ajst-32536	93	7			PROPN
ajst-32536	93	8	,	,	PUNCT
ajst-32536	93	9	1sgn	1sgn	NUM
ajst-32536	93	10	x	x	SYM
ajst-32536	93	11			NUM
ajst-32536	93	12			PROPN
ajst-32536	93	13	（	（	SYM
ajst-32536	93	14	）	）	PUNCT
ajst-32536	93	15	.	.	PUNCT
ajst-32536	94	1	threshold	threshold	NOUN
ajst-32536	94	2	setting	set	VERB
ajst-32536	94	3	is	be	AUX
ajst-32536	94	4	a	a	DET
ajst-32536	94	5	crucial	crucial	ADJ
ajst-32536	94	6	issue	issue	NOUN
ajst-32536	94	7	in	in	ADP
ajst-32536	94	8	soft	soft	ADJ
ajst-32536	94	9	threshold	threshold	NOUN
ajst-32536	94	10	denoising	denoise	VERB
ajst-32536	94	11	.	.	PUNCT
ajst-32536	95	1	in	in	ADP
ajst-32536	95	2	reference	reference	NOUN
ajst-32536	95	3	[	[	X
ajst-32536	95	4	14	14	NUM
ajst-32536	95	5	]	]	PUNCT
ajst-32536	95	6	,	,	PUNCT
ajst-32536	95	7	the	the	DET
ajst-32536	95	8	sum	sum	NOUN
ajst-32536	95	9	of	of	ADP
ajst-32536	95	10	squares	square	NOUN
ajst-32536	95	11	is	be	AUX
ajst-32536	95	12	first	first	ADV
ajst-32536	95	13	calculated	calculate	VERB
ajst-32536	95	14	for	for	ADP
ajst-32536	95	15	the	the	DET
ajst-32536	95	16	coefficient	coefficient	NOUN
ajst-32536	95	17	t	t	PROPN
ajst-32536	95	18	.	.	PUNCT
ajst-32536	96	1	then	then	ADV
ajst-32536	96	2	,	,	PUNCT
ajst-32536	96	3	within	within	ADP
ajst-32536	96	4	the	the	DET
ajst-32536	96	5	window	window	NOUN
ajst-32536	96	6	centered	center	VERB
ajst-32536	96	7	on	on	ADP
ajst-32536	96	8	wavelet	wavelet	NOUN
ajst-32536	96	9	coefficients	coefficient	NOUN
ajst-32536	96	10	,	,	PUNCT
ajst-32536	96	11	the	the	DET
ajst-32536	96	12	corresponding	corresponding	ADJ
ajst-32536	96	13	shrinkage	shrinkage	NOUN
ajst-32536	96	14	factor	factor	NOUN
ajst-32536	96	15			PROPN
ajst-32536	96	16	is	be	AUX
ajst-32536	96	17	computed	compute	VERB
ajst-32536	96	18	,	,	PUNCT
ajst-32536	96	19	and	and	CCONJ
ajst-32536	96	20	thus	thus	ADV
ajst-32536	96	21	the	the	DET
ajst-32536	96	22	global	global	ADJ
ajst-32536	96	23	threshold	threshold	NOUN
ajst-32536	96	24	is	be	AUX
ajst-32536	96	25	obtained	obtain	VERB
ajst-32536	96	26	.	.	PUNCT
ajst-32536	97	1	based	base	VERB
ajst-32536	97	2	on	on	ADP
ajst-32536	97	3	this	this	PRON
ajst-32536	97	4	,	,	PUNCT
ajst-32536	97	5	it	it	PRON
ajst-32536	97	6	is	be	AUX
ajst-32536	97	7	determined	determine	VERB
ajst-32536	97	8	whether	whether	SCONJ
ajst-32536	97	9	the	the	DET
ajst-32536	97	10	wavelet	wavelet	NOUN
ajst-32536	97	11	coefficients	coefficient	NOUN
ajst-32536	97	12	should	should	AUX
ajst-32536	97	13	undergo	undergo	VERB
ajst-32536	97	14	shrinkage	shrinkage	NOUN
ajst-32536	97	15	towards	towards	ADP
ajst-32536	97	16			X
ajst-32536	97	17	or	or	CCONJ
ajst-32536	97	18	be	be	AUX
ajst-32536	97	19	directly	directly	ADV
ajst-32536	97	20	set	set	VERB
ajst-32536	97	21	to	to	ADP
ajst-32536	97	22			X
ajst-32536	97	23	.	.	PUNCT
ajst-32536	98	1	3.1.3	3.1.3	NUM
ajst-32536	98	2	attention	attention	NOUN
ajst-32536	98	3	mechanism	mechanism	NOUN
ajst-32536	98	4	squeeze	squeeze	NOUN
ajst-32536	98	5	-	-	PUNCT
ajst-32536	98	6	and	and	CCONJ
ajst-32536	98	7	-	-	PUNCT
ajst-32536	98	8	excitation	excitation	NOUN
ajst-32536	98	9	(	(	PUNCT
ajst-32536	98	10	se	se	X
ajst-32536	98	11	)	)	PUNCT
ajst-32536	98	12	,	,	PUNCT
ajst-32536	98	13	a	a	DET
ajst-32536	98	14	commonly	commonly	ADV
ajst-32536	98	15	used	use	VERB
ajst-32536	98	16	attention	attention	NOUN
ajst-32536	98	17	mechanism	mechanism	NOUN
ajst-32536	98	18	,	,	PUNCT
ajst-32536	98	19	enables	enable	VERB
ajst-32536	98	20	adaptive	adaptive	ADJ
ajst-32536	98	21	adjustment	adjustment	NOUN
ajst-32536	98	22	of	of	ADP
ajst-32536	98	23	the	the	DET
ajst-32536	98	24	network	network	NOUN
ajst-32536	98	25	’s	’s	PART
ajst-32536	98	26	degree	degree	NOUN
ajst-32536	98	27	of	of	ADP
ajst-32536	98	28	focus	focus	NOUN
ajst-32536	98	29	on	on	ADP
ajst-32536	98	30	feature	feature	NOUN
ajst-32536	98	31	information	information	NOUN
ajst-32536	98	32	across	across	ADP
ajst-32536	98	33	different	different	ADJ
ajst-32536	98	34	channels	channel	NOUN
ajst-32536	98	35	.	.	PUNCT
ajst-32536	99	1	it	it	PRON
ajst-32536	99	2	can	can	AUX
ajst-32536	99	3	be	be	AUX
ajst-32536	99	4	employed	employ	VERB
ajst-32536	99	5	to	to	PART
ajst-32536	99	6	emphasize	emphasize	VERB
ajst-32536	99	7	critical	critical	ADJ
ajst-32536	99	8	features	feature	NOUN
ajst-32536	99	9	while	while	SCONJ
ajst-32536	99	10	de	de	NOUN
ajst-32536	99	11	-	-	ADJ
ajst-32536	99	12	emphasizing	emphasize	VERB
ajst-32536	99	13	irrelevant	irrelevant	ADJ
ajst-32536	99	14	ones	one	NOUN
ajst-32536	99	15	[	[	X
ajst-32536	99	16	15	15	NUM
ajst-32536	99	17	]	]	PUNCT
ajst-32536	99	18	.	.	PUNCT
ajst-32536	100	1	the	the	DET
ajst-32536	100	2	workflow	workflow	NOUN
ajst-32536	100	3	of	of	ADP
ajst-32536	100	4	the	the	DET
ajst-32536	100	5	se	se	PROPN
ajst-32536	100	6	mechanism	mechanism	NOUN
ajst-32536	100	7	proceeds	proceed	NOUN
ajst-32536	100	8	as	as	SCONJ
ajst-32536	100	9	follows	follow	VERB
ajst-32536	100	10	:	:	PUNCT
ajst-32536	100	11	first	first	ADV
ajst-32536	100	12	,	,	PUNCT
ajst-32536	100	13	these	these	DET
ajst-32536	100	14	features	feature	NOUN
ajst-32536	100	15	are	be	AUX
ajst-32536	100	16	compressed	compress	VERB
ajst-32536	100	17	into	into	ADP
ajst-32536	100	18	a	a	DET
ajst-32536	100	19	channel	channel	NOUN
ajst-32536	100	20	descriptor	descriptor	NOUN
ajst-32536	100	21	to	to	PART
ajst-32536	100	22	obtain	obtain	VERB
ajst-32536	100	23	aggregated	aggregated	ADJ
ajst-32536	100	24	features	feature	NOUN
ajst-32536	100	25	that	that	PRON
ajst-32536	100	26	encapsulate	encapsulate	VERB
ajst-32536	100	27	global	global	ADJ
ajst-32536	100	28	information	information	NOUN
ajst-32536	100	29	.	.	PUNCT
ajst-32536	101	1	for	for	ADP
ajst-32536	101	2	this	this	DET
ajst-32536	101	3	compression	compression	NOUN
ajst-32536	101	4	process	process	NOUN
ajst-32536	101	5	,	,	PUNCT
ajst-32536	101	6	the	the	DET
ajst-32536	101	7	calculation	calculation	NOUN
ajst-32536	101	8	formula	formula	NOUN
ajst-32536	101	9	for	for	ADP
ajst-32536	101	10	the	the	DET
ajst-32536	101	11	i	i	PROPN
ajst-32536	101	12	-	-	PUNCT
ajst-32536	101	13	th	th	X
ajst-32536	101	14	element	element	NOUN
ajst-32536	101	15	of	of	ADP
ajst-32536	101	16	the	the	DET
ajst-32536	101	17	aggregated	aggregate	VERB
ajst-32536	101	18	features	feature	NOUN
ajst-32536	101	19	is	be	AUX
ajst-32536	101	20	given	give	VERB
ajst-32536	101	21	by	by	ADP
ajst-32536	101	22	:	:	PUNCT
ajst-32536	101	23	1	1	NUM
ajst-32536	101	24	1	1	NUM
ajst-32536	101	25	1	1	NUM
ajst-32536	101	26	(	(	PUNCT
ajst-32536	101	27	,	,	PUNCT
ajst-32536	101	28	)	)	PUNCT
ajst-32536	102	1	a	a	DET
ajst-32536	102	2	b	b	NOUN
ajst-32536	103	1	i	i	PRON
ajst-32536	104	1	i	i	VERB
ajst-32536	104	2	m	m	VERB
ajst-32536	104	3	n	n	VERB
ajst-32536	104	4	y	y	PROPN
ajst-32536	104	5	x	x	VERB
ajst-32536	104	6	m	m	VERB
ajst-32536	104	7	n	n	ADV
ajst-32536	104	8	a	a	DET
ajst-32536	104	9	b	b	NOUN
ajst-32536	104	10			NOUN
ajst-32536	105	1			NOUN
ajst-32536	106	1			PROPN
ajst-32536	106	2			NOUN
ajst-32536	106	3			PRON
ajst-32536	106	4	(	(	PUNCT
ajst-32536	106	5	4	4	NUM
ajst-32536	106	6	)	)	PUNCT
ajst-32536	106	7	in	in	ADP
ajst-32536	106	8	formula(4	formula(4	PROPN
ajst-32536	106	9	)	)	PUNCT
ajst-32536	106	10	,	,	PUNCT
ajst-32536	106	11	a	a	DET
ajst-32536	106	12	b	b	NOUN
ajst-32536	106	13	represents	represent	VERB
ajst-32536	106	14	the	the	DET
ajst-32536	106	15	spatial	spatial	ADJ
ajst-32536	106	16	dimension	dimension	NOUN
ajst-32536	106	17	.	.	PUNCT
ajst-32536	107	1	the	the	DET
ajst-32536	107	2	weight	weight	NOUN
ajst-32536	107	3	coefficients	coefficient	NOUN
ajst-32536	107	4	s	s	PART
ajst-32536	107	5	of	of	ADP
ajst-32536	107	6	different	different	ADJ
ajst-32536	107	7	channels	channel	NOUN
ajst-32536	107	8	are	be	AUX
ajst-32536	107	9	obtained	obtain	VERB
ajst-32536	107	10	through	through	ADP
ajst-32536	107	11	the	the	DET
ajst-32536	107	12	excitation	excitation	NOUN
ajst-32536	107	13	step	step	NOUN
ajst-32536	107	14	,	,	PUNCT
ajst-32536	107	15	and	and	CCONJ
ajst-32536	107	16	the	the	DET
ajst-32536	107	17	calculation	calculation	NOUN
ajst-32536	107	18	method	method	NOUN
ajst-32536	107	19	is	be	AUX
ajst-32536	107	20	as	as	SCONJ
ajst-32536	107	21	follows	follow	VERB
ajst-32536	107	22	:	:	PUNCT
ajst-32536	108	1			PROPN
ajst-32536	108	2			PROPN
ajst-32536	108	3	2	2	X
ajst-32536	108	4	1s	1s	PROPN
ajst-32536	108	5	w	w	VERB
ajst-32536	108	6	w	w	NOUN
ajst-32536	108	7	y	y	ADJ
ajst-32536	108	8			PROPN
ajst-32536	108	9	(	(	PUNCT
ajst-32536	108	10	5	5	NUM
ajst-32536	108	11	)	)	PUNCT
ajst-32536	108	12	in	in	ADP
ajst-32536	108	13	formula(5	formula(5	NOUN
ajst-32536	108	14	):	):	PUNCT
ajst-32536	108	15			NUM
ajst-32536	108	16	and	and	CCONJ
ajst-32536	108	17			NUM
ajst-32536	108	18	denote	denote	VERB
ajst-32536	108	19	the	the	DET
ajst-32536	108	20	sigmoid	sigmoid	NOUN
ajst-32536	108	21	and	and	CCONJ
ajst-32536	108	22	relu	relu	NOUN
ajst-32536	108	23	activation	activation	NOUN
ajst-32536	108	24	functions	function	NOUN
ajst-32536	108	25	,	,	PUNCT
ajst-32536	108	26	respectively	respectively	ADV
ajst-32536	108	27	,	,	PUNCT
ajst-32536	108	28	and	and	CCONJ
ajst-32536	108	29	iw	iw	PROPN
ajst-32536	108	30	represents	represent	VERB
ajst-32536	108	31	the	the	DET
ajst-32536	108	32	i	i	PROPN
ajst-32536	108	33	-	-	PUNCT
ajst-32536	108	34	th	th	X
ajst-32536	108	35	set	set	NOUN
ajst-32536	108	36	of	of	ADP
ajst-32536	108	37	trainable	trainable	ADJ
ajst-32536	108	38	parameters	parameter	NOUN
ajst-32536	108	39	.	.	PUNCT
ajst-32536	109	1	33	33	NUM
ajst-32536	109	2	3.2	3.2	NUM
ajst-32536	109	3	drsn	drsn	NOUN
ajst-32536	109	4	based	base	VERB
ajst-32536	109	5	on	on	ADP
ajst-32536	109	6	pooling	pool	VERB
ajst-32536	109	7	fusion	fusion	NOUN
ajst-32536	109	8	3.2.1	3.2.1	NUM
ajst-32536	109	9	the	the	DET
ajst-32536	109	10	drsn	drsn	PROPN
ajst-32536	109	11	network	network	NOUN
ajst-32536	109	12	as	as	SCONJ
ajst-32536	109	13	illustrated	illustrate	VERB
ajst-32536	109	14	in	in	ADP
ajst-32536	109	15	figure	figure	NOUN
ajst-32536	109	16	2	2	NUM
ajst-32536	109	17	,	,	PUNCT
ajst-32536	109	18	the	the	DET
ajst-32536	109	19	deep	deep	ADJ
ajst-32536	109	20	residual	residual	ADJ
ajst-32536	109	21	shrinkage	shrinkage	NOUN
ajst-32536	109	22	network	network	NOUN
ajst-32536	109	23	(	(	PUNCT
ajst-32536	109	24	drsn	drsn	PROPN
ajst-32536	109	25	)	)	PUNCT
ajst-32536	109	26	comprises	comprise	VERB
ajst-32536	109	27	an	an	DET
ajst-32536	109	28	input	input	NOUN
ajst-32536	109	29	layer	layer	NOUN
ajst-32536	109	30	,	,	PUNCT
ajst-32536	109	31	convolutional	convolutional	ADJ
ajst-32536	109	32	layers	layer	NOUN
ajst-32536	109	33	(	(	PUNCT
ajst-32536	109	34	conv	conv	ADJ
ajst-32536	109	35	)	)	PUNCT
ajst-32536	109	36	,	,	PUNCT
ajst-32536	109	37	residual	residual	ADJ
ajst-32536	109	38	shrinkage	shrinkage	NOUN
ajst-32536	109	39	building	building	NOUN
ajst-32536	109	40	units	unit	NOUN
ajst-32536	109	41	(	(	PUNCT
ajst-32536	109	42	rsbu	rsbu	NOUN
ajst-32536	109	43	)	)	PUNCT
ajst-32536	109	44	,	,	PUNCT
ajst-32536	109	45	batch	batch	VERB
ajst-32536	109	46	normalization	normalization	NOUN
ajst-32536	109	47	layers	layer	NOUN
ajst-32536	109	48	(	(	PUNCT
ajst-32536	109	49	bn	bn	NOUN
ajst-32536	109	50	)	)	PUNCT
ajst-32536	109	51	,	,	PUNCT
ajst-32536	109	52	rectified	rectify	VERB
ajst-32536	109	53	linear	linear	ADJ
ajst-32536	109	54	unit	unit	NOUN
ajst-32536	109	55	layers	layer	NOUN
ajst-32536	109	56	(	(	PUNCT
ajst-32536	109	57	relu	relu	NOUN
ajst-32536	109	58	)	)	PUNCT
ajst-32536	109	59	,	,	PUNCT
ajst-32536	109	60	a	a	DET
ajst-32536	109	61	global	global	ADJ
ajst-32536	109	62	average	average	ADJ
ajst-32536	109	63	pooling	pool	VERB
ajst-32536	109	64	layer	layer	NOUN
ajst-32536	109	65	(	(	PUNCT
ajst-32536	109	66	gap	gap	NOUN
ajst-32536	109	67	)	)	PUNCT
ajst-32536	109	68	,	,	PUNCT
ajst-32536	109	69	fully	fully	ADV
ajst-32536	109	70	connected	connected	ADJ
ajst-32536	109	71	layers	layer	NOUN
ajst-32536	109	72	(	(	PUNCT
ajst-32536	109	73	fc	fc	INTJ
ajst-32536	109	74	)	)	PUNCT
ajst-32536	109	75	,	,	PUNCT
ajst-32536	109	76	and	and	CCONJ
ajst-32536	109	77	an	an	DET
ajst-32536	109	78	output	output	NOUN
ajst-32536	109	79	layer	layer	NOUN
ajst-32536	110	1	[	[	X
ajst-32536	110	2	16	16	NUM
ajst-32536	110	3	]	]	PUNCT
ajst-32536	110	4	.	.	PUNCT
ajst-32536	111	1	figure	figure	NOUN
ajst-32536	111	2	2	2	NUM
ajst-32536	111	3	.	.	PUNCT
ajst-32536	111	4	overall	overall	ADJ
ajst-32536	111	5	architecture	architecture	NOUN
ajst-32536	111	6	of	of	ADP
ajst-32536	111	7	the	the	DET
ajst-32536	111	8	drsn	drsn	PROPN
ajst-32536	111	9	convolutional	convolutional	ADJ
ajst-32536	111	10	layers	layer	NOUN
ajst-32536	111	11	(	(	PUNCT
ajst-32536	111	12	conv	conv	ADJ
ajst-32536	111	13	)	)	PUNCT
ajst-32536	111	14	are	be	AUX
ajst-32536	111	15	a	a	DET
ajst-32536	111	16	key	key	ADJ
ajst-32536	111	17	component	component	NOUN
ajst-32536	111	18	that	that	PRON
ajst-32536	111	19	distinguishes	distinguish	VERB
ajst-32536	111	20	them	they	PRON
ajst-32536	111	21	from	from	ADP
ajst-32536	111	22	traditional	traditional	ADJ
ajst-32536	111	23	fully	fully	ADV
ajst-32536	111	24	connected	connect	VERB
ajst-32536	111	25	neural	neural	ADJ
ajst-32536	111	26	networks	network	NOUN
ajst-32536	111	27	.	.	PUNCT
ajst-32536	112	1	they	they	PRON
ajst-32536	112	2	are	be	AUX
ajst-32536	112	3	implemented	implement	VERB
ajst-32536	112	4	using	use	VERB
ajst-32536	112	5	convolution	convolution	NOUN
ajst-32536	112	6	instead	instead	ADV
ajst-32536	112	7	of	of	ADP
ajst-32536	112	8	matrix	matrix	NOUN
ajst-32536	112	9	multiplication	multiplication	NOUN
ajst-32536	112	10	,	,	PUNCT
ajst-32536	112	11	which	which	PRON
ajst-32536	112	12	enables	enable	VERB
ajst-32536	112	13	the	the	DET
ajst-32536	112	14	convolution	convolution	NOUN
ajst-32536	112	15	kernels	kernel	NOUN
ajst-32536	112	16	in	in	ADP
ajst-32536	112	17	the	the	DET
ajst-32536	112	18	convolutional	convolutional	ADJ
ajst-32536	112	19	layer	layer	NOUN
ajst-32536	112	20	to	to	PART
ajst-32536	112	21	have	have	VERB
ajst-32536	112	22	fewer	few	ADJ
ajst-32536	112	23	parameters	parameter	NOUN
ajst-32536	112	24	than	than	ADP
ajst-32536	112	25	the	the	DET
ajst-32536	112	26	transformation	transformation	NOUN
ajst-32536	112	27	matrices	matrix	NOUN
ajst-32536	112	28	in	in	ADP
ajst-32536	112	29	fully	fully	ADV
ajst-32536	112	30	connected	connected	ADJ
ajst-32536	112	31	layers	layer	NOUN
ajst-32536	112	32	(	(	PUNCT
ajst-32536	112	33	fc	fc	INTJ
ajst-32536	112	34	)	)	PUNCT
ajst-32536	112	35	.	.	PUNCT
ajst-32536	113	1	batch	batch	NOUN
ajst-32536	113	2	normalization	normalization	NOUN
ajst-32536	113	3	(	(	PUNCT
ajst-32536	113	4	bn	bn	NOUN
ajst-32536	113	5	)	)	PUNCT
ajst-32536	113	6	is	be	AUX
ajst-32536	113	7	a	a	DET
ajst-32536	113	8	feature	feature	NOUN
ajst-32536	113	9	normalization	normalization	NOUN
ajst-32536	113	10	technique	technique	NOUN
ajst-32536	113	11	.	.	PUNCT
ajst-32536	114	1	it	it	PRON
ajst-32536	114	2	is	be	AUX
ajst-32536	114	3	inserted	insert	VERB
ajst-32536	114	4	into	into	ADP
ajst-32536	114	5	deep	deep	ADJ
ajst-32536	114	6	learning	learning	NOUN
ajst-32536	114	7	architectures	architecture	NOUN
ajst-32536	114	8	as	as	ADP
ajst-32536	114	9	a	a	DET
ajst-32536	114	10	trainable	trainable	ADJ
ajst-32536	114	11	process	process	NOUN
ajst-32536	114	12	,	,	PUNCT
ajst-32536	114	13	aiming	aim	VERB
ajst-32536	114	14	to	to	PART
ajst-32536	114	15	transform	transform	VERB
ajst-32536	114	16	features	feature	NOUN
ajst-32536	114	17	into	into	ADP
ajst-32536	114	18	an	an	DET
ajst-32536	114	19	ideal	ideal	ADJ
ajst-32536	114	20	distribution	distribution	NOUN
ajst-32536	114	21	,	,	PUNCT
ajst-32536	114	22	thereby	thereby	ADV
ajst-32536	114	23	accelerating	accelerate	VERB
ajst-32536	114	24	the	the	DET
ajst-32536	114	25	training	training	NOUN
ajst-32536	114	26	speed	speed	NOUN
ajst-32536	114	27	.	.	PUNCT
ajst-32536	115	1	the	the	DET
ajst-32536	115	2	rectified	rectified	ADJ
ajst-32536	115	3	linear	linear	PROPN
ajst-32536	115	4	unit	unit	NOUN
ajst-32536	115	5	(	(	PUNCT
ajst-32536	115	6	relu	relu	NOUN
ajst-32536	115	7	)	)	PUNCT
ajst-32536	115	8	is	be	AUX
ajst-32536	115	9	one	one	NUM
ajst-32536	115	10	of	of	ADP
ajst-32536	115	11	the	the	DET
ajst-32536	115	12	most	most	ADV
ajst-32536	115	13	popular	popular	ADJ
ajst-32536	115	14	activation	activation	NOUN
ajst-32536	115	15	functions	function	NOUN
ajst-32536	115	16	in	in	ADP
ajst-32536	115	17	deep	deep	ADJ
ajst-32536	115	18	neural	neural	ADJ
ajst-32536	115	19	networks	network	NOUN
ajst-32536	115	20	.	.	PUNCT
ajst-32536	116	1	the	the	DET
ajst-32536	116	2	partial	partial	ADJ
ajst-32536	116	3	derivative	derivative	NOUN
ajst-32536	116	4	of	of	ADP
ajst-32536	116	5	its	its	PRON
ajst-32536	116	6	non	non	ADJ
ajst-32536	116	7	-	-	ADJ
ajst-32536	116	8	zero	zero	NUM
ajst-32536	116	9	output	output	NOUN
ajst-32536	116	10	feature	feature	NOUN
ajst-32536	116	11	with	with	ADP
ajst-32536	116	12	respect	respect	NOUN
ajst-32536	116	13	to	to	ADP
ajst-32536	116	14	the	the	DET
ajst-32536	116	15	input	input	NOUN
ajst-32536	116	16	feature	feature	NOUN
ajst-32536	116	17	is	be	AUX
ajst-32536	116	18	always	always	ADV
ajst-32536	116	19	1	1	NUM
ajst-32536	116	20	,	,	PUNCT
ajst-32536	116	21	which	which	PRON
ajst-32536	116	22	can	can	AUX
ajst-32536	116	23	effectively	effectively	ADV
ajst-32536	116	24	reduce	reduce	VERB
ajst-32536	116	25	the	the	DET
ajst-32536	116	26	risk	risk	NOUN
ajst-32536	116	27	of	of	ADP
ajst-32536	116	28	gradient	gradient	ADJ
ajst-32536	116	29	explosion	explosion	NOUN
ajst-32536	116	30	and	and	CCONJ
ajst-32536	116	31	vanishing	vanish	VERB
ajst-32536	116	32	.	.	PUNCT
ajst-32536	117	1	global	global	ADJ
ajst-32536	117	2	average	average	ADJ
ajst-32536	117	3	pooling	pooling	NOUN
ajst-32536	117	4	(	(	PUNCT
ajst-32536	117	5	gap	gap	NOUN
ajst-32536	117	6	)	)	PUNCT
ajst-32536	117	7	calculates	calculate	VERB
ajst-32536	117	8	the	the	DET
ajst-32536	117	9	average	average	ADJ
ajst-32536	117	10	value	value	NOUN
ajst-32536	117	11	of	of	ADP
ajst-32536	117	12	each	each	DET
ajst-32536	117	13	channel	channel	NOUN
ajst-32536	117	14	of	of	ADP
ajst-32536	117	15	the	the	DET
ajst-32536	117	16	output	output	NOUN
ajst-32536	117	17	feature	feature	NOUN
ajst-32536	117	18	map	map	NOUN
ajst-32536	117	19	,	,	PUNCT
ajst-32536	117	20	thereby	thereby	ADV
ajst-32536	117	21	reducing	reduce	VERB
ajst-32536	117	22	the	the	DET
ajst-32536	117	23	number	number	NOUN
ajst-32536	117	24	of	of	ADP
ajst-32536	117	25	parameters	parameter	NOUN
ajst-32536	117	26	that	that	PRON
ajst-32536	117	27	need	need	VERB
ajst-32536	117	28	to	to	PART
ajst-32536	117	29	be	be	AUX
ajst-32536	117	30	trained	train	VERB
ajst-32536	117	31	in	in	ADP
ajst-32536	117	32	the	the	DET
ajst-32536	117	33	fully	fully	ADV
ajst-32536	117	34	connected	connect	VERB
ajst-32536	117	35	layer	layer	NOUN
ajst-32536	117	36	(	(	PUNCT
ajst-32536	117	37	fc	fc	INTJ
ajst-32536	117	38	)	)	PUNCT
ajst-32536	117	39	.	.	PUNCT
ajst-32536	118	1	figure	figure	VERB
ajst-32536	118	2	3	3	NUM
ajst-32536	118	3	.	.	PUNCT
ajst-32536	118	4	overall	overall	ADJ
ajst-32536	118	5	architecture	architecture	NOUN
ajst-32536	118	6	of	of	ADP
ajst-32536	118	7	the	the	DET
ajst-32536	118	8	rsbu	rsbu	NOUN
ajst-32536	118	9	as	as	ADP
ajst-32536	118	10	the	the	DET
ajst-32536	118	11	core	core	NOUN
ajst-32536	118	12	module	module	NOUN
ajst-32536	118	13	of	of	ADP
ajst-32536	118	14	the	the	DET
ajst-32536	118	15	drsn	drsn	PROPN
ajst-32536	118	16	,	,	PUNCT
ajst-32536	118	17	the	the	DET
ajst-32536	118	18	residual	residual	ADJ
ajst-32536	118	19	shrinkage	shrinkage	NOUN
ajst-32536	118	20	building	building	NOUN
ajst-32536	118	21	unit	unit	NOUN
ajst-32536	118	22	(	(	PUNCT
ajst-32536	118	23	rsbu	rsbu	NOUN
ajst-32536	118	24	)	)	PUNCT
ajst-32536	118	25	integrates	integrate	VERB
ajst-32536	118	26	basic	basic	ADJ
ajst-32536	118	27	functional	functional	ADJ
ajst-32536	118	28	components	component	NOUN
ajst-32536	118	29	in	in	ADP
ajst-32536	118	30	its	its	PRON
ajst-32536	118	31	structural	structural	ADJ
ajst-32536	118	32	design	design	NOUN
ajst-32536	118	33	and	and	CCONJ
ajst-32536	118	34	innovatively	innovatively	ADV
ajst-32536	118	35	incorporates	incorporate	VERB
ajst-32536	118	36	the	the	DET
ajst-32536	118	37	idea	idea	NOUN
ajst-32536	118	38	of	of	ADP
ajst-32536	118	39	residual	residual	ADJ
ajst-32536	118	40	learning	learning	NOUN
ajst-32536	118	41	and	and	CCONJ
ajst-32536	118	42	the	the	DET
ajst-32536	118	43	soft	soft	ADJ
ajst-32536	118	44	-	-	PUNCT
ajst-32536	118	45	thresholding	thresholde	VERB
ajst-32536	118	46	denoising	denoising	NOUN
ajst-32536	118	47	mechanism	mechanism	NOUN
ajst-32536	118	48	,	,	PUNCT
ajst-32536	118	49	as	as	SCONJ
ajst-32536	118	50	shown	show	VERB
ajst-32536	118	51	in	in	ADP
ajst-32536	118	52	figure	figure	NOUN
ajst-32536	118	53	3	3	NUM
ajst-32536	118	54	.	.	PUNCT
ajst-32536	119	1	specifically	specifically	ADV
ajst-32536	119	2	,	,	PUNCT
ajst-32536	119	3	on	on	ADP
ajst-32536	119	4	the	the	DET
ajst-32536	119	5	one	one	NUM
ajst-32536	119	6	hand	hand	NOUN
ajst-32536	119	7	,	,	PUNCT
ajst-32536	119	8	an	an	DET
ajst-32536	119	9	efficient	efficient	ADJ
ajst-32536	119	10	gradient	gradient	NOUN
ajst-32536	119	11	conduction	conduction	NOUN
ajst-32536	119	12	channel	channel	NOUN
ajst-32536	119	13	is	be	AUX
ajst-32536	119	14	built	build	VERB
ajst-32536	119	15	through	through	ADP
ajst-32536	119	16	the	the	DET
ajst-32536	119	17	identity	identity	NOUN
ajst-32536	119	18	mapping	mapping	NOUN
ajst-32536	119	19	path	path	NOUN
ajst-32536	119	20	to	to	PART
ajst-32536	119	21	ensure	ensure	VERB
ajst-32536	119	22	that	that	SCONJ
ajst-32536	119	23	gradients	gradient	NOUN
ajst-32536	119	24	can	can	AUX
ajst-32536	119	25	effectively	effectively	ADV
ajst-32536	119	26	flow	flow	VERB
ajst-32536	119	27	to	to	ADP
ajst-32536	119	28	the	the	DET
ajst-32536	119	29	shallow	shallow	ADJ
ajst-32536	119	30	network	network	NOUN
ajst-32536	119	31	close	close	ADJ
ajst-32536	119	32	to	to	ADP
ajst-32536	119	33	the	the	DET
ajst-32536	119	34	input	input	NOUN
ajst-32536	119	35	layer	layer	NOUN
ajst-32536	119	36	,	,	PUNCT
ajst-32536	119	37	thereby	thereby	ADV
ajst-32536	119	38	significantly	significantly	ADV
ajst-32536	119	39	improving	improve	VERB
ajst-32536	119	40	the	the	DET
ajst-32536	119	41	parameter	parameter	NOUN
ajst-32536	119	42	update	update	NOUN
ajst-32536	119	43	efficiency	efficiency	NOUN
ajst-32536	119	44	and	and	CCONJ
ajst-32536	119	45	reducing	reduce	VERB
ajst-32536	119	46	the	the	DET
ajst-32536	119	47	training	training	NOUN
ajst-32536	119	48	difficulty	difficulty	NOUN
ajst-32536	119	49	.	.	PUNCT
ajst-32536	120	1	on	on	ADP
ajst-32536	120	2	the	the	DET
ajst-32536	120	3	other	other	ADJ
ajst-32536	120	4	hand	hand	NOUN
ajst-32536	120	5	,	,	PUNCT
ajst-32536	120	6	an	an	DET
ajst-32536	120	7	attention	attention	NOUN
ajst-32536	120	8	mechanism	mechanism	NOUN
ajst-32536	120	9	is	be	AUX
ajst-32536	120	10	used	use	VERB
ajst-32536	120	11	to	to	PART
ajst-32536	120	12	adaptively	adaptively	ADV
ajst-32536	120	13	derive	derive	VERB
ajst-32536	120	14	the	the	DET
ajst-32536	120	15	corresponding	corresponding	ADJ
ajst-32536	120	16	threshold	threshold	NOUN
ajst-32536	120	17	for	for	ADP
ajst-32536	120	18	each	each	DET
ajst-32536	120	19	sample	sample	NOUN
ajst-32536	120	20	,	,	PUNCT
ajst-32536	120	21	and	and	CCONJ
ajst-32536	120	22	then	then	ADV
ajst-32536	120	23	the	the	DET
ajst-32536	120	24	soft	soft	ADJ
ajst-32536	120	25	-	-	PUNCT
ajst-32536	120	26	thresholding	thresholde	VERB
ajst-32536	120	27	function	function	NOUN
ajst-32536	120	28	is	be	AUX
ajst-32536	120	29	used	use	VERB
ajst-32536	120	30	to	to	PART
ajst-32536	120	31	achieve	achieve	VERB
ajst-32536	120	32	accurate	accurate	ADJ
ajst-32536	120	33	denoising	denoising	NOUN
ajst-32536	120	34	of	of	ADP
ajst-32536	120	35	vibration	vibration	NOUN
ajst-32536	120	36	signals	signal	NOUN
ajst-32536	120	37	,	,	PUNCT
ajst-32536	120	38	and	and	CCONJ
ajst-32536	120	39	the	the	DET
ajst-32536	120	40	specific	specific	ADJ
ajst-32536	120	41	process	process	NOUN
ajst-32536	120	42	is	be	AUX
ajst-32536	120	43	shown	show	VERB
ajst-32536	120	44	in	in	ADP
ajst-32536	120	45	figure	figure	NOUN
ajst-32536	120	46	4	4	NUM
ajst-32536	120	47	.	.	PUNCT
ajst-32536	121	1	based	base	VERB
ajst-32536	121	2	on	on	ADP
ajst-32536	121	3	the	the	DET
ajst-32536	121	4	above	above	ADJ
ajst-32536	121	5	modular	modular	ADJ
ajst-32536	121	6	design	design	NOUN
ajst-32536	121	7	innovations	innovation	NOUN
ajst-32536	121	8	,	,	PUNCT
ajst-32536	121	9	34	34	NUM
ajst-32536	121	10	compared	compare	VERB
ajst-32536	121	11	with	with	ADP
ajst-32536	121	12	traditional	traditional	ADJ
ajst-32536	121	13	cnns	cnn	NOUN
ajst-32536	121	14	,	,	PUNCT
ajst-32536	121	15	drsn	drsn	VERB
ajst-32536	121	16	not	not	PART
ajst-32536	121	17	only	only	ADV
ajst-32536	121	18	has	have	VERB
ajst-32536	121	19	significant	significant	ADJ
ajst-32536	121	20	advantages	advantage	NOUN
ajst-32536	121	21	such	such	ADJ
ajst-32536	121	22	as	as	ADP
ajst-32536	121	23	lower	low	ADJ
ajst-32536	121	24	training	training	NOUN
ajst-32536	121	25	difficulty	difficulty	NOUN
ajst-32536	121	26	and	and	CCONJ
ajst-32536	121	27	stronger	strong	ADJ
ajst-32536	121	28	denoising	denoising	NOUN
ajst-32536	121	29	ability	ability	NOUN
ajst-32536	121	30	but	but	CCONJ
ajst-32536	121	31	has	have	AUX
ajst-32536	121	32	also	also	ADV
ajst-32536	121	33	been	be	AUX
ajst-32536	121	34	widely	widely	ADV
ajst-32536	121	35	used	use	VERB
ajst-32536	121	36	in	in	ADP
ajst-32536	121	37	the	the	DET
ajst-32536	121	38	field	field	NOUN
ajst-32536	121	39	of	of	ADP
ajst-32536	121	40	fault	fault	NOUN
ajst-32536	121	41	diagnosis	diagnosis	NOUN
ajst-32536	121	42	.	.	PUNCT
ajst-32536	122	1	figure	figure	NOUN
ajst-32536	122	2	4	4	NUM
ajst-32536	122	3	.	.	PUNCT
ajst-32536	123	1	structure	structure	NOUN
ajst-32536	123	2	of	of	ADP
ajst-32536	123	3	the	the	DET
ajst-32536	123	4	attention	attention	NOUN
ajst-32536	123	5	module	module	NOUN
ajst-32536	123	6	3.2.2	3.2.2	NUM
ajst-32536	123	7	drsn	drsn	NOUN
ajst-32536	123	8	based	base	VERB
ajst-32536	123	9	on	on	ADP
ajst-32536	123	10	pooling	pool	VERB
ajst-32536	123	11	fusion	fusion	NOUN
ajst-32536	123	12	as	as	SCONJ
ajst-32536	123	13	illustrated	illustrate	VERB
ajst-32536	123	14	in	in	ADP
ajst-32536	123	15	figure	figure	NOUN
ajst-32536	123	16	5	5	NUM
ajst-32536	123	17	,	,	PUNCT
ajst-32536	123	18	the	the	DET
ajst-32536	123	19	deep	deep	ADJ
ajst-32536	123	20	residual	residual	ADJ
ajst-32536	123	21	shrinkage	shrinkage	NOUN
ajst-32536	123	22	network	network	NOUN
ajst-32536	123	23	based	base	VERB
ajst-32536	123	24	on	on	ADP
ajst-32536	123	25	pooling	pool	VERB
ajst-32536	123	26	fusion	fusion	NOUN
ajst-32536	123	27	(	(	PUNCT
ajst-32536	123	28	drsnpf	drsnpf	NOUN
ajst-32536	123	29	)	)	PUNCT
ajst-32536	123	30	,	,	PUNCT
ajst-32536	123	31	innovatively	innovatively	ADV
ajst-32536	123	32	proposed	propose	VERB
ajst-32536	123	33	in	in	ADP
ajst-32536	123	34	this	this	DET
ajst-32536	123	35	study	study	NOUN
ajst-32536	123	36	,	,	PUNCT
ajst-32536	123	37	adopts	adopt	VERB
ajst-32536	123	38	a	a	DET
ajst-32536	123	39	multi	multi	ADJ
ajst-32536	123	40	-	-	ADJ
ajst-32536	123	41	pooling	pool	VERB
ajst-32536	123	42	fusion	fusion	NOUN
ajst-32536	123	43	structure	structure	NOUN
ajst-32536	123	44	where	where	SCONJ
ajst-32536	123	45	the	the	DET
ajst-32536	123	46	maxpooling	maxpoole	VERB
ajst-32536	123	47	layer	layer	NOUN
ajst-32536	123	48	and	and	CCONJ
ajst-32536	123	49	average	average	ADJ
ajst-32536	123	50	-	-	PUNCT
ajst-32536	123	51	pooling	pool	VERB
ajst-32536	123	52	layer	layer	NOUN
ajst-32536	123	53	work	work	NOUN
ajst-32536	123	54	in	in	ADP
ajst-32536	123	55	synergy	synergy	NOUN
ajst-32536	123	56	,	,	PUNCT
ajst-32536	123	57	replacing	replace	VERB
ajst-32536	123	58	the	the	DET
ajst-32536	123	59	global	global	ADJ
ajst-32536	123	60	average	average	ADJ
ajst-32536	123	61	pooling	pooling	NOUN
ajst-32536	123	62	(	(	PUNCT
ajst-32536	123	63	gap	gap	NOUN
ajst-32536	123	64	)	)	PUNCT
ajst-32536	123	65	in	in	ADP
ajst-32536	123	66	the	the	DET
ajst-32536	123	67	original	original	ADJ
ajst-32536	123	68	model	model	NOUN
ajst-32536	123	69	.	.	PUNCT
ajst-32536	124	1	this	this	DET
ajst-32536	124	2	design	design	NOUN
ajst-32536	124	3	is	be	AUX
ajst-32536	124	4	not	not	PART
ajst-32536	124	5	a	a	DET
ajst-32536	124	6	simple	simple	ADJ
ajst-32536	124	7	component	component	NOUN
ajst-32536	124	8	replacement	replacement	NOUN
ajst-32536	124	9	,	,	PUNCT
ajst-32536	124	10	but	but	CCONJ
ajst-32536	124	11	rather	rather	ADV
ajst-32536	124	12	achieves	achieve	VERB
ajst-32536	124	13	information	information	NOUN
ajst-32536	124	14	gain	gain	NOUN
ajst-32536	124	15	in	in	ADP
ajst-32536	124	16	the	the	DET
ajst-32536	124	17	threshold	threshold	NOUN
ajst-32536	124	18	derivation	derivation	NOUN
ajst-32536	124	19	stage	stage	NOUN
ajst-32536	124	20	through	through	ADP
ajst-32536	124	21	the	the	DET
ajst-32536	124	22	complementary	complementary	ADJ
ajst-32536	124	23	characteristics	characteristic	NOUN
ajst-32536	124	24	of	of	ADP
ajst-32536	124	25	the	the	DET
ajst-32536	124	26	two	two	NUM
ajst-32536	124	27	pooling	pool	VERB
ajst-32536	124	28	methods	method	NOUN
ajst-32536	124	29	:	:	PUNCT
ajst-32536	124	30	max	max	PROPN
ajst-32536	124	31	-	-	PUNCT
ajst-32536	124	32	pooling	pool	VERB
ajst-32536	124	33	excels	excel	NOUN
ajst-32536	124	34	at	at	ADP
ajst-32536	124	35	capturing	capture	VERB
ajst-32536	124	36	the	the	DET
ajst-32536	124	37	extreme	extreme	ADJ
ajst-32536	124	38	value	value	NOUN
ajst-32536	124	39	information	information	NOUN
ajst-32536	124	40	of	of	ADP
ajst-32536	124	41	salient	salient	NOUN
ajst-32536	124	42	features	feature	NOUN
ajst-32536	124	43	,	,	PUNCT
ajst-32536	124	44	while	while	SCONJ
ajst-32536	124	45	average	average	ADJ
ajst-32536	124	46	-	-	PUNCT
ajst-32536	124	47	pooling	pooling	NOUN
ajst-32536	124	48	can	can	AUX
ajst-32536	124	49	preserve	preserve	VERB
ajst-32536	124	50	the	the	DET
ajst-32536	124	51	overall	overall	ADJ
ajst-32536	124	52	trend	trend	NOUN
ajst-32536	124	53	of	of	ADP
ajst-32536	124	54	feature	feature	NOUN
ajst-32536	124	55	distribution	distribution	NOUN
ajst-32536	124	56	.	.	PUNCT
ajst-32536	125	1	the	the	DET
ajst-32536	125	2	fusion	fusion	NOUN
ajst-32536	125	3	of	of	ADP
ajst-32536	125	4	the	the	DET
ajst-32536	125	5	two	two	NUM
ajst-32536	125	6	enables	enable	VERB
ajst-32536	125	7	the	the	DET
ajst-32536	125	8	thresholds	threshold	NOUN
ajst-32536	125	9	generated	generate	VERB
ajst-32536	125	10	by	by	ADP
ajst-32536	125	11	the	the	DET
ajst-32536	125	12	attention	attention	NOUN
ajst-32536	125	13	module	module	NOUN
ajst-32536	125	14	to	to	PART
ajst-32536	125	15	more	more	ADV
ajst-32536	125	16	comprehensively	comprehensively	ADV
ajst-32536	125	17	cover	cover	VERB
ajst-32536	125	18	the	the	DET
ajst-32536	125	19	diverse	diverse	ADJ
ajst-32536	125	20	attributes	attribute	NOUN
ajst-32536	125	21	of	of	ADP
ajst-32536	125	22	local	local	ADJ
ajst-32536	125	23	features	feature	NOUN
ajst-32536	125	24	.	.	PUNCT
ajst-32536	126	1	this	this	DET
ajst-32536	126	2	information	information	NOUN
ajst-32536	126	3	compensation	compensation	NOUN
ajst-32536	126	4	mechanism	mechanism	NOUN
ajst-32536	126	5	directly	directly	ADV
ajst-32536	126	6	enhances	enhance	VERB
ajst-32536	126	7	the	the	DET
ajst-32536	126	8	model	model	NOUN
ajst-32536	126	9	’s	’s	PART
ajst-32536	126	10	ability	ability	NOUN
ajst-32536	126	11	to	to	PART
ajst-32536	126	12	extract	extract	VERB
ajst-32536	126	13	weak	weak	ADJ
ajst-32536	126	14	features	feature	NOUN
ajst-32536	126	15	from	from	ADP
ajst-32536	126	16	noisy	noisy	ADJ
ajst-32536	126	17	vibration	vibration	NOUN
ajst-32536	126	18	signals	signal	NOUN
ajst-32536	126	19	.	.	PUNCT
ajst-32536	127	1	the	the	DET
ajst-32536	127	2	remaining	remain	VERB
ajst-32536	127	3	architectural	architectural	ADJ
ajst-32536	127	4	components	component	NOUN
ajst-32536	127	5	of	of	ADP
ajst-32536	127	6	drsn	drsn	PROPN
ajst-32536	127	7	-	-	PUNCT
ajst-32536	127	8	pf	pf	PROPN
ajst-32536	127	9	remain	remain	VERB
ajst-32536	127	10	consistent	consistent	ADJ
ajst-32536	127	11	with	with	ADP
ajst-32536	127	12	the	the	DET
ajst-32536	127	13	original	original	ADJ
ajst-32536	127	14	drsn	drsn	NOUN
ajst-32536	127	15	,	,	PUNCT
ajst-32536	127	16	ensuring	ensure	VERB
ajst-32536	127	17	the	the	DET
ajst-32536	127	18	pertinence	pertinence	NOUN
ajst-32536	127	19	of	of	ADP
ajst-32536	127	20	the	the	DET
ajst-32536	127	21	innovative	innovative	ADJ
ajst-32536	127	22	design	design	NOUN
ajst-32536	127	23	and	and	CCONJ
ajst-32536	127	24	the	the	DET
ajst-32536	127	25	stability	stability	NOUN
ajst-32536	127	26	of	of	ADP
ajst-32536	127	27	the	the	DET
ajst-32536	127	28	system	system	NOUN
ajst-32536	127	29	.	.	PUNCT
ajst-32536	128	1	figure	figure	NOUN
ajst-32536	128	2	5	5	NUM
ajst-32536	128	3	.	.	PUNCT
ajst-32536	129	1	structure	structure	NOUN
ajst-32536	129	2	of	of	ADP
ajst-32536	129	3	the	the	DET
ajst-32536	129	4	attention	attention	NOUN
ajst-32536	129	5	module	module	NOUN
ajst-32536	129	6	based	base	VERB
ajst-32536	129	7	on	on	ADP
ajst-32536	129	8	pooling	pool	VERB
ajst-32536	129	9	fusion	fusion	NOUN
ajst-32536	129	10	4	4	NUM
ajst-32536	129	11	.	.	PUNCT
ajst-32536	130	1	dataset	dataset	VERB
ajst-32536	130	2	4.1	4.1	NUM
ajst-32536	130	3	detection	detection	NOUN
ajst-32536	130	4	results	result	NOUN
ajst-32536	130	5	of	of	ADP
ajst-32536	130	6	neural	neural	ADJ
ajst-32536	130	7	activity	activity	NOUN
ajst-32536	130	8	datasets	dataset	NOUN
ajst-32536	130	9	for	for	ADP
ajst-32536	130	10	pd	pd	PROPN
ajst-32536	130	11	for	for	ADP
ajst-32536	130	12	the	the	DET
ajst-32536	130	13	eeg	eeg	NOUN
ajst-32536	130	14	dataset	dataset	NOUN
ajst-32536	130	15	of	of	ADP
ajst-32536	130	16	parkinson	parkinson	NOUN
ajst-32536	130	17	’s	’s	PART
ajst-32536	130	18	disease	disease	NOUN
ajst-32536	130	19	(	(	PUNCT
ajst-32536	130	20	pd	pd	NOUN
ajst-32536	130	21	)	)	PUNCT
ajst-32536	130	22	in	in	ADP
ajst-32536	130	23	question	question	NOUN
ajst-32536	130	24	,	,	PUNCT
ajst-32536	130	25	the	the	DET
ajst-32536	130	26	preprocessing	preprocessing	NOUN
ajst-32536	130	27	and	and	CCONJ
ajst-32536	130	28	feature	feature	NOUN
ajst-32536	130	29	engineering	engineering	NOUN
ajst-32536	130	30	procedures	procedure	NOUN
ajst-32536	130	31	were	be	AUX
ajst-32536	130	32	implemented	implement	VERB
ajst-32536	130	33	as	as	SCONJ
ajst-32536	130	34	follows	follow	VERB
ajst-32536	130	35	:	:	PUNCT
ajst-32536	130	36	first	first	ADV
ajst-32536	130	37	,	,	PUNCT
ajst-32536	130	38	age	age	NOUN
ajst-32536	130	39	,	,	PUNCT
ajst-32536	130	40	a	a	DET
ajst-32536	130	41	continuous	continuous	ADJ
ajst-32536	130	42	variable	variable	NOUN
ajst-32536	130	43	in	in	ADP
ajst-32536	130	44	the	the	DET
ajst-32536	130	45	metadata	metadata	NOUN
ajst-32536	130	46	,	,	PUNCT
ajst-32536	130	47	was	be	AUX
ajst-32536	130	48	subjected	subject	VERB
ajst-32536	130	49	to	to	ADP
ajst-32536	130	50	normalization	normalization	NOUN
ajst-32536	130	51	to	to	PART
ajst-32536	130	52	eliminate	eliminate	VERB
ajst-32536	130	53	the	the	DET
ajst-32536	130	54	influence	influence	NOUN
ajst-32536	130	55	of	of	ADP
ajst-32536	130	56	different	different	ADJ
ajst-32536	130	57	magnitude	magnitude	NOUN
ajst-32536	130	58	scales	scale	NOUN
ajst-32536	130	59	.	.	PUNCT
ajst-32536	131	1	in	in	ADP
ajst-32536	131	2	contrast	contrast	NOUN
ajst-32536	131	3	,	,	PUNCT
ajst-32536	131	4	categorical	categorical	ADJ
ajst-32536	131	5	variables	variable	NOUN
ajst-32536	131	6	—	—	PUNCT
ajst-32536	131	7	including	include	VERB
ajst-32536	131	8	gender	gender	NOUN
ajst-32536	131	9	and	and	CCONJ
ajst-32536	131	10	clinical	clinical	ADJ
ajst-32536	131	11	stage	stage	NOUN
ajst-32536	131	12	—	—	PUNCT
ajst-32536	131	13	were	be	AUX
ajst-32536	131	14	encoded	encode	VERB
ajst-32536	131	15	using	use	VERB
ajst-32536	131	16	one	one	NUM
ajst-32536	131	17	-	-	PUNCT
ajst-32536	131	18	hot	hot	ADJ
ajst-32536	131	19	encoding	encoding	NOUN
ajst-32536	131	20	,	,	PUNCT
ajst-32536	131	21	a	a	DET
ajst-32536	131	22	standard	standard	ADJ
ajst-32536	131	23	technique	technique	NOUN
ajst-32536	131	24	to	to	PART
ajst-32536	131	25	convert	convert	VERB
ajst-32536	131	26	discrete	discrete	ADJ
ajst-32536	131	27	categorical	categorical	ADJ
ajst-32536	131	28	information	information	NOUN
ajst-32536	131	29	into	into	ADP
ajst-32536	131	30	a	a	DET
ajst-32536	131	31	numerical	numerical	ADJ
ajst-32536	131	32	format	format	NOUN
ajst-32536	131	33	compatible	compatible	ADJ
ajst-32536	131	34	with	with	ADP
ajst-32536	131	35	machine	machine	NOUN
ajst-32536	131	36	learning	learning	NOUN
ajst-32536	131	37	models	model	NOUN
ajst-32536	131	38	.	.	PUNCT
ajst-32536	132	1	second	second	ADJ
ajst-32536	132	2	,	,	PUNCT
ajst-32536	132	3	regarding	regard	VERB
ajst-32536	132	4	the	the	DET
ajst-32536	132	5	raw	raw	ADJ
ajst-32536	132	6	eeg	eeg	NOUN
ajst-32536	132	7	signals	signal	NOUN
ajst-32536	132	8	contaminated	contaminate	VERB
ajst-32536	132	9	with	with	ADP
ajst-32536	132	10	simulated	simulated	ADJ
ajst-32536	132	11	noise	noise	NOUN
ajst-32536	132	12	,	,	PUNCT
ajst-32536	132	13	a	a	DET
ajst-32536	132	14	band	band	NOUN
ajst-32536	132	15	-	-	PUNCT
ajst-32536	132	16	pass	pass	NOUN
ajst-32536	132	17	filter	filter	NOUN
ajst-32536	132	18	(	(	PUNCT
ajst-32536	132	19	0.5–40	0.5–40	NOUN
ajst-32536	132	20	hz	hz	VERB
ajst-32536	132	21	)	)	PUNCT
ajst-32536	132	22	was	be	AUX
ajst-32536	132	23	applied	apply	VERB
ajst-32536	132	24	.	.	PUNCT
ajst-32536	133	1	this	this	DET
ajst-32536	133	2	filtering	filter	VERB
ajst-32536	133	3	step	step	NOUN
ajst-32536	133	4	aimed	aim	VERB
ajst-32536	133	5	to	to	PART
ajst-32536	133	6	retain	retain	VERB
ajst-32536	133	7	the	the	DET
ajst-32536	133	8	primary	primary	ADJ
ajst-32536	133	9	frequency	frequency	NOUN
ajst-32536	133	10	bands	band	NOUN
ajst-32536	133	11	associated	associate	VERB
ajst-32536	133	12	with	with	ADP
ajst-32536	133	13	neural	neural	ADJ
ajst-32536	133	14	activity	activity	NOUN
ajst-32536	133	15	(	(	PUNCT
ajst-32536	133	16	e.g.	e.g.	ADV
ajst-32536	133	17	,	,	PUNCT
ajst-32536	133	18	delta	delta	NOUN
ajst-32536	133	19	,	,	PUNCT
ajst-32536	133	20	theta	theta	NOUN
ajst-32536	133	21	,	,	PUNCT
ajst-32536	133	22	alpha	alpha	NOUN
ajst-32536	133	23	,	,	PUNCT
ajst-32536	133	24	beta	beta	NOUN
ajst-32536	133	25	,	,	PUNCT
ajst-32536	133	26	and	and	CCONJ
ajst-32536	133	27	low	low	ADJ
ajst-32536	133	28	gamma	gamma	NOUN
ajst-32536	133	29	35	35	NUM
ajst-32536	133	30	bands	band	NOUN
ajst-32536	133	31	)	)	PUNCT
ajst-32536	133	32	while	while	SCONJ
ajst-32536	133	33	suppressing	suppress	VERB
ajst-32536	133	34	extraneous	extraneous	ADJ
ajst-32536	133	35	noise	noise	NOUN
ajst-32536	133	36	components	component	NOUN
ajst-32536	133	37	outside	outside	ADP
ajst-32536	133	38	this	this	DET
ajst-32536	133	39	range	range	NOUN
ajst-32536	133	40	.	.	PUNCT
ajst-32536	134	1	subsequent	subsequent	ADJ
ajst-32536	134	2	to	to	ADP
ajst-32536	134	3	filtering	filter	VERB
ajst-32536	134	4	,	,	PUNCT
ajst-32536	134	5	the	the	DET
ajst-32536	134	6	eeg	eeg	NOUN
ajst-32536	134	7	signals	signal	NOUN
ajst-32536	134	8	were	be	AUX
ajst-32536	134	9	segmented	segment	VERB
ajst-32536	134	10	into	into	ADP
ajst-32536	134	11	fixed	fix	VERB
ajst-32536	134	12	-	-	PUNCT
ajst-32536	134	13	length	length	NOUN
ajst-32536	134	14	epochs	epoch	NOUN
ajst-32536	134	15	and	and	CCONJ
ajst-32536	134	16	standardized	standardized	ADJ
ajst-32536	134	17	(	(	PUNCT
ajst-32536	134	18	i.e.	i.e.	X
ajst-32536	134	19	,	,	PUNCT
ajst-32536	134	20	z	z	NOUN
ajst-32536	134	21	-	-	PUNCT
ajst-32536	134	22	score	score	NOUN
ajst-32536	134	23	normalization	normalization	NOUN
ajst-32536	134	24	)	)	PUNCT
ajst-32536	134	25	to	to	PART
ajst-32536	134	26	ensure	ensure	VERB
ajst-32536	134	27	that	that	SCONJ
ajst-32536	134	28	each	each	DET
ajst-32536	134	29	signal	signal	ADJ
ajst-32536	134	30	channel	channel	NOUN
ajst-32536	134	31	had	have	VERB
ajst-32536	134	32	a	a	DET
ajst-32536	134	33	mean	mean	NOUN
ajst-32536	134	34	of	of	ADP
ajst-32536	134	35	0	0	NUM
ajst-32536	134	36	and	and	CCONJ
ajst-32536	134	37	a	a	DET
ajst-32536	134	38	standard	standard	ADJ
ajst-32536	134	39	deviation	deviation	NOUN
ajst-32536	134	40	of	of	ADP
ajst-32536	134	41	1	1	NUM
ajst-32536	134	42	,	,	PUNCT
ajst-32536	134	43	mitigating	mitigate	VERB
ajst-32536	134	44	the	the	DET
ajst-32536	134	45	impact	impact	NOUN
ajst-32536	134	46	of	of	ADP
ajst-32536	134	47	inter	inter	ADJ
ajst-32536	134	48	-	-	ADJ
ajst-32536	134	49	channel	channel	ADJ
ajst-32536	134	50	amplitude	amplitude	NOUN
ajst-32536	134	51	variations	variation	NOUN
ajst-32536	134	52	.	.	PUNCT
ajst-32536	135	1	third	third	ADJ
ajst-32536	135	2	,	,	PUNCT
ajst-32536	135	3	for	for	ADP
ajst-32536	135	4	the	the	DET
ajst-32536	135	5	existing	exist	VERB
ajst-32536	135	6	time	time	NOUN
ajst-32536	135	7	-	-	PUNCT
ajst-32536	135	8	frequency	frequency	NOUN
ajst-32536	135	9	features	feature	NOUN
ajst-32536	135	10	derived	derive	VERB
ajst-32536	135	11	from	from	ADP
ajst-32536	135	12	short	short	ADJ
ajst-32536	135	13	-	-	PUNCT
ajst-32536	135	14	time	time	NOUN
ajst-32536	135	15	fourier	fourier	NOUN
ajst-32536	135	16	transform	transform	NOUN
ajst-32536	135	17	(	(	PUNCT
ajst-32536	135	18	stft)—encompassing	stft)—encompasse	VERB
ajst-32536	135	19	both	both	DET
ajst-32536	135	20	amplitude	amplitude	NOUN
ajst-32536	135	21	and	and	CCONJ
ajst-32536	135	22	phase	phase	NOUN
ajst-32536	135	23	components	component	NOUN
ajst-32536	135	24	—	—	PUNCT
ajst-32536	135	25	dimensionality	dimensionality	NOUN
ajst-32536	135	26	reduction	reduction	NOUN
ajst-32536	135	27	was	be	AUX
ajst-32536	135	28	performed	perform	VERB
ajst-32536	135	29	.	.	PUNCT
ajst-32536	136	1	this	this	PRON
ajst-32536	136	2	was	be	AUX
ajst-32536	136	3	achieved	achieve	VERB
ajst-32536	136	4	through	through	ADP
ajst-32536	136	5	either	either	DET
ajst-32536	136	6	feature	feature	NOUN
ajst-32536	136	7	selection	selection	NOUN
ajst-32536	136	8	(	(	PUNCT
ajst-32536	136	9	to	to	PART
ajst-32536	136	10	retain	retain	VERB
ajst-32536	136	11	only	only	ADV
ajst-32536	136	12	the	the	DET
ajst-32536	136	13	most	most	ADV
ajst-32536	136	14	discriminative	discriminative	NOUN
ajst-32536	136	15	features	feature	NOUN
ajst-32536	136	16	)	)	PUNCT
ajst-32536	136	17	or	or	CCONJ
ajst-32536	136	18	principal	principal	ADJ
ajst-32536	136	19	component	component	NOUN
ajst-32536	136	20	analysis	analysis	NOUN
ajst-32536	136	21	(	(	PUNCT
ajst-32536	136	22	pca	pca	NOUN
ajst-32536	136	23	,	,	PUNCT
ajst-32536	136	24	to	to	PART
ajst-32536	136	25	transform	transform	VERB
ajst-32536	136	26	the	the	DET
ajst-32536	136	27	feature	feature	NOUN
ajst-32536	136	28	space	space	NOUN
ajst-32536	136	29	into	into	ADP
ajst-32536	136	30	a	a	DET
ajst-32536	136	31	lower	lower	ADV
ajst-32536	136	32	-	-	PUNCT
ajst-32536	136	33	dimensional	dimensional	ADJ
ajst-32536	136	34	subspace	subspace	NOUN
ajst-32536	136	35	while	while	SCONJ
ajst-32536	136	36	preserving	preserve	VERB
ajst-32536	136	37	the	the	DET
ajst-32536	136	38	majority	majority	NOUN
ajst-32536	136	39	of	of	ADP
ajst-32536	136	40	variance	variance	NOUN
ajst-32536	136	41	)	)	PUNCT
ajst-32536	136	42	,	,	PUNCT
ajst-32536	136	43	thereby	thereby	ADV
ajst-32536	136	44	alleviating	alleviate	VERB
ajst-32536	136	45	the	the	DET
ajst-32536	136	46	curse	curse	NOUN
ajst-32536	136	47	of	of	ADP
ajst-32536	136	48	dimensionality	dimensionality	NOUN
ajst-32536	136	49	and	and	CCONJ
ajst-32536	136	50	improving	improve	VERB
ajst-32536	136	51	computational	computational	ADJ
ajst-32536	136	52	efficiency	efficiency	NOUN
ajst-32536	136	53	.	.	PUNCT
ajst-32536	137	1	fourth	fourth	ADJ
ajst-32536	137	2	,	,	PUNCT
ajst-32536	137	3	the	the	DET
ajst-32536	137	4	processed	process	VERB
ajst-32536	137	5	metadata	metadata	NOUN
ajst-32536	137	6	features	feature	NOUN
ajst-32536	137	7	(	(	PUNCT
ajst-32536	137	8	normalized	normalize	VERB
ajst-32536	137	9	age	age	NOUN
ajst-32536	137	10	and	and	CCONJ
ajst-32536	137	11	one	one	NUM
ajst-32536	137	12	-	-	PUNCT
ajst-32536	137	13	hot	hot	ADJ
ajst-32536	137	14	encoded	encode	VERB
ajst-32536	137	15	categorical	categorical	ADJ
ajst-32536	137	16	variables	variable	NOUN
ajst-32536	137	17	)	)	PUNCT
ajst-32536	137	18	,	,	PUNCT
ajst-32536	137	19	filtered	filter	VERB
ajst-32536	137	20	eeg	eeg	PROPN
ajst-32536	137	21	time	time	NOUN
ajst-32536	137	22	-	-	PUNCT
ajst-32536	137	23	domain	domain	NOUN
ajst-32536	137	24	features	feature	NOUN
ajst-32536	137	25	,	,	PUNCT
ajst-32536	137	26	and	and	CCONJ
ajst-32536	137	27	dimensionally	dimensionally	ADV
ajst-32536	137	28	reduced	reduce	VERB
ajst-32536	137	29	stft	stft	PROPN
ajst-32536	137	30	time	time	NOUN
ajst-32536	137	31	-	-	PUNCT
ajst-32536	137	32	frequency	frequency	NOUN
ajst-32536	137	33	features	feature	NOUN
ajst-32536	137	34	were	be	AUX
ajst-32536	137	35	effectively	effectively	ADV
ajst-32536	137	36	fused	fuse	VERB
ajst-32536	137	37	and	and	CCONJ
ajst-32536	137	38	aligned	align	VERB
ajst-32536	137	39	.	.	PUNCT
ajst-32536	138	1	this	this	DET
ajst-32536	138	2	fusion	fusion	NOUN
ajst-32536	138	3	step	step	NOUN
ajst-32536	138	4	ensured	ensure	VERB
ajst-32536	138	5	temporal	temporal	ADJ
ajst-32536	138	6	and	and	CCONJ
ajst-32536	138	7	semantic	semantic	ADJ
ajst-32536	138	8	consistency	consistency	NOUN
ajst-32536	138	9	across	across	ADP
ajst-32536	138	10	different	different	ADJ
ajst-32536	138	11	feature	feature	NOUN
ajst-32536	138	12	modalities	modality	NOUN
ajst-32536	138	13	,	,	PUNCT
ajst-32536	138	14	integrating	integrate	VERB
ajst-32536	138	15	complementary	complementary	ADJ
ajst-32536	138	16	information	information	NOUN
ajst-32536	138	17	from	from	ADP
ajst-32536	138	18	demographic	demographic	ADJ
ajst-32536	138	19	,	,	PUNCT
ajst-32536	138	20	raw	raw	ADJ
ajst-32536	138	21	signal	signal	NOUN
ajst-32536	138	22	,	,	PUNCT
ajst-32536	138	23	and	and	CCONJ
ajst-32536	138	24	time	time	NOUN
ajst-32536	138	25	-	-	PUNCT
ajst-32536	138	26	frequency	frequency	NOUN
ajst-32536	138	27	domains	domain	NOUN
ajst-32536	138	28	.	.	PUNCT
ajst-32536	139	1	finally	finally	ADV
ajst-32536	139	2	,	,	PUNCT
ajst-32536	139	3	to	to	PART
ajst-32536	139	4	address	address	VERB
ajst-32536	139	5	the	the	DET
ajst-32536	139	6	class	class	NOUN
ajst-32536	139	7	imbalance	imbalance	NOUN
ajst-32536	139	8	issue	issue	NOUN
ajst-32536	139	9	inherent	inherent	ADJ
ajst-32536	139	10	in	in	ADP
ajst-32536	139	11	the	the	DET
ajst-32536	139	12	classification	classification	NOUN
ajst-32536	139	13	labels	label	NOUN
ajst-32536	139	14	(	(	PUNCT
ajst-32536	139	15	a	a	DET
ajst-32536	139	16	common	common	ADJ
ajst-32536	139	17	challenge	challenge	NOUN
ajst-32536	139	18	in	in	ADP
ajst-32536	139	19	medical	medical	ADJ
ajst-32536	139	20	datasets	dataset	NOUN
ajst-32536	139	21	)	)	PUNCT
ajst-32536	139	22	,	,	PUNCT
ajst-32536	139	23	techniques	technique	NOUN
ajst-32536	139	24	such	such	ADJ
ajst-32536	139	25	as	as	ADP
ajst-32536	139	26	oversampling	oversample	VERB
ajst-32536	139	27	(	(	PUNCT
ajst-32536	139	28	e.g.	e.g.	ADV
ajst-32536	139	29	,	,	PUNCT
ajst-32536	139	30	synthetic	synthetic	ADJ
ajst-32536	139	31	minority	minority	NOUN
ajst-32536	139	32	oversampling	oversample	VERB
ajst-32536	139	33	technique	technique	NOUN
ajst-32536	139	34	,	,	PUNCT
ajst-32536	139	35	smote	smote	NOUN
ajst-32536	139	36	)	)	PUNCT
ajst-32536	139	37	were	be	AUX
ajst-32536	139	38	employed	employ	VERB
ajst-32536	139	39	to	to	PART
ajst-32536	139	40	balance	balance	VERB
ajst-32536	139	41	the	the	DET
ajst-32536	139	42	sample	sample	NOUN
ajst-32536	139	43	distribution	distribution	NOUN
ajst-32536	139	44	across	across	ADP
ajst-32536	139	45	different	different	ADJ
ajst-32536	139	46	classes	class	NOUN
ajst-32536	139	47	.	.	PUNCT
ajst-32536	140	1	through	through	ADP
ajst-32536	140	2	the	the	DET
ajst-32536	140	3	aforementioned	aforementioned	ADJ
ajst-32536	140	4	steps	step	NOUN
ajst-32536	140	5	,	,	PUNCT
ajst-32536	140	6	a	a	DET
ajst-32536	140	7	unified	unified	ADJ
ajst-32536	140	8	and	and	CCONJ
ajst-32536	140	9	well	well	ADV
ajst-32536	140	10	-	-	PUNCT
ajst-32536	140	11	structured	structure	VERB
ajst-32536	140	12	feature	feature	NOUN
ajst-32536	140	13	matrix	matrix	NOUN
ajst-32536	140	14	was	be	AUX
ajst-32536	140	15	constructed	construct	VERB
ajst-32536	140	16	for	for	ADP
ajst-32536	140	17	subsequent	subsequent	ADJ
ajst-32536	140	18	model	model	NOUN
ajst-32536	140	19	training	training	NOUN
ajst-32536	140	20	and	and	CCONJ
ajst-32536	140	21	validation	validation	NOUN
ajst-32536	140	22	.	.	PUNCT
ajst-32536	141	1	the	the	DET
ajst-32536	141	2	dataset	dataset	NOUN
ajst-32536	141	3	was	be	AUX
ajst-32536	141	4	split	split	VERB
ajst-32536	141	5	into	into	ADP
ajst-32536	141	6	a	a	DET
ajst-32536	141	7	training	training	NOUN
ajst-32536	141	8	set	set	NOUN
ajst-32536	141	9	and	and	CCONJ
ajst-32536	141	10	a	a	DET
ajst-32536	141	11	test	test	NOUN
ajst-32536	141	12	set	set	VERB
ajst-32536	141	13	at	at	ADP
ajst-32536	141	14	a	a	DET
ajst-32536	141	15	ratio	ratio	NOUN
ajst-32536	141	16	of	of	ADP
ajst-32536	141	17	7:3	7:3	NUM
ajst-32536	141	18	.	.	PUNCT
ajst-32536	142	1	the	the	DET
ajst-32536	142	2	detailed	detailed	ADJ
ajst-32536	142	3	performance	performance	NOUN
ajst-32536	142	4	metrics	metric	NOUN
ajst-32536	142	5	of	of	ADP
ajst-32536	142	6	dataset	dataset	NOUN
ajst-32536	142	7	validation	validation	NOUN
ajst-32536	142	8	are	be	AUX
ajst-32536	142	9	presented	present	VERB
ajst-32536	142	10	in	in	ADP
ajst-32536	142	11	table	table	NOUN
ajst-32536	142	12	1	1	NUM
ajst-32536	142	13	.	.	PUNCT
ajst-32536	142	14	table	table	NOUN
ajst-32536	142	15	1	1	NUM
ajst-32536	142	16	.	.	PUNCT
ajst-32536	142	17	dataset	dataset	NOUN
ajst-32536	142	18	validation	validation	NOUN
ajst-32536	142	19	results	result	NOUN
ajst-32536	142	20	evaluation	evaluation	NOUN
ajst-32536	142	21	metric	metric	ADJ
ajst-32536	142	22	accuracy	accuracy	NOUN
ajst-32536	142	23	precision	precision	NOUN
ajst-32536	142	24	recall	recall	NOUN
ajst-32536	142	25	f1	f1	NOUN
ajst-32536	142	26	score	score	NOUN
ajst-32536	142	27	value	value	NOUN
ajst-32536	142	28	(	(	PUNCT
ajst-32536	142	29	%	%	INTJ
ajst-32536	142	30	)	)	PUNCT
ajst-32536	142	31	92.10	92.10	NUM
ajst-32536	142	32	91.27	91.27	NUM
ajst-32536	142	33	90.72	90.72	NUM
ajst-32536	142	34	90.99	90.99	NUM
ajst-32536	142	35	as	as	SCONJ
ajst-32536	142	36	can	can	AUX
ajst-32536	142	37	be	be	AUX
ajst-32536	142	38	seen	see	VERB
ajst-32536	142	39	from	from	ADP
ajst-32536	142	40	table	table	NOUN
ajst-32536	142	41	1	1	NUM
ajst-32536	142	42	,	,	PUNCT
ajst-32536	142	43	the	the	DET
ajst-32536	142	44	detection	detection	NOUN
ajst-32536	142	45	results	result	NOUN
ajst-32536	142	46	of	of	ADP
ajst-32536	142	47	drsn	drsn	NOUN
ajst-32536	142	48	on	on	ADP
ajst-32536	142	49	the	the	DET
ajst-32536	142	50	parkinson	parkinson	NOUN
ajst-32536	142	51	's	's	PART
ajst-32536	142	52	disease	disease	NOUN
ajst-32536	142	53	neural	neural	ADJ
ajst-32536	142	54	activity	activity	NOUN
ajst-32536	142	55	dataset	dataset	NOUN
ajst-32536	142	56	show	show	NOUN
ajst-32536	142	57	that	that	SCONJ
ajst-32536	142	58	the	the	DET
ajst-32536	142	59	accuracy	accuracy	NOUN
ajst-32536	142	60	is	be	AUX
ajst-32536	142	61	92.10	92.10	NUM
ajst-32536	142	62	%	%	NOUN
ajst-32536	142	63	,	,	PUNCT
ajst-32536	142	64	the	the	DET
ajst-32536	142	65	precision	precision	NOUN
ajst-32536	142	66	is	be	AUX
ajst-32536	142	67	91.27	91.27	NUM
ajst-32536	142	68	%	%	NOUN
ajst-32536	142	69	,	,	PUNCT
ajst-32536	142	70	the	the	DET
ajst-32536	142	71	recall	recall	NOUN
ajst-32536	142	72	is	be	AUX
ajst-32536	142	73	90.72	90.72	NUM
ajst-32536	142	74	%	%	NOUN
ajst-32536	142	75	,	,	PUNCT
ajst-32536	142	76	and	and	CCONJ
ajst-32536	142	77	the	the	DET
ajst-32536	142	78	f1	f1	PROPN
ajst-32536	142	79	score	score	NOUN
ajst-32536	142	80	is	be	AUX
ajst-32536	142	81	90.99	90.99	NUM
ajst-32536	142	82	%	%	NOUN
ajst-32536	142	83	.	.	PUNCT
ajst-32536	143	1	an	an	DET
ajst-32536	143	2	accuracy	accuracy	NOUN
ajst-32536	143	3	of	of	ADP
ajst-32536	143	4	92.10	92.10	NUM
ajst-32536	143	5	%	%	NOUN
ajst-32536	143	6	verifies	verifie	NOUN
ajst-32536	143	7	the	the	DET
ajst-32536	143	8	efficient	efficient	ADJ
ajst-32536	143	9	discrimination	discrimination	NOUN
ajst-32536	143	10	ability	ability	NOUN
ajst-32536	143	11	of	of	ADP
ajst-32536	143	12	the	the	DET
ajst-32536	143	13	multi	multi	ADJ
ajst-32536	143	14	-	-	ADJ
ajst-32536	143	15	feature	feature	ADJ
ajst-32536	143	16	fusion	fusion	NOUN
ajst-32536	143	17	architecture	architecture	NOUN
ajst-32536	143	18	for	for	ADP
ajst-32536	143	19	the	the	DET
ajst-32536	143	20	four	four	NUM
ajst-32536	143	21	types	type	NOUN
ajst-32536	143	22	of	of	ADP
ajst-32536	143	23	labels	label	NOUN
ajst-32536	143	24	,	,	PUNCT
ajst-32536	143	25	namely	namely	ADV
ajst-32536	143	26	"	"	PUNCT
ajst-32536	143	27	resting	rest	VERB
ajst-32536	143	28	tremor	tremor	NOUN
ajst-32536	143	29	"	"	PUNCT
ajst-32536	143	30	,	,	PUNCT
ajst-32536	143	31	"	"	PUNCT
ajst-32536	143	32	rigidity	rigidity	NOUN
ajst-32536	143	33	"	"	PUNCT
ajst-32536	143	34	,	,	PUNCT
ajst-32536	143	35	"	"	PUNCT
ajst-32536	143	36	normal	normal	ADJ
ajst-32536	143	37	"	"	PUNCT
ajst-32536	143	38	,	,	PUNCT
ajst-32536	143	39	and	and	CCONJ
ajst-32536	143	40	"	"	PUNCT
ajst-32536	143	41	medication	medication	NOUN
ajst-32536	143	42	state	state	NOUN
ajst-32536	143	43	"	"	PUNCT
ajst-32536	143	44	,	,	PUNCT
ajst-32536	143	45	and	and	CCONJ
ajst-32536	143	46	solves	solve	VERB
ajst-32536	143	47	the	the	DET
ajst-32536	143	48	problems	problem	NOUN
ajst-32536	143	49	of	of	ADP
ajst-32536	143	50	insufficient	insufficient	ADJ
ajst-32536	143	51	feature	feature	NOUN
ajst-32536	143	52	extraction	extraction	NOUN
ajst-32536	143	53	and	and	CCONJ
ajst-32536	143	54	weak	weak	ADJ
ajst-32536	143	55	noise	noise	NOUN
ajst-32536	143	56	resistance	resistance	NOUN
ajst-32536	143	57	of	of	ADP
ajst-32536	143	58	traditional	traditional	ADJ
ajst-32536	143	59	methods	method	NOUN
ajst-32536	143	60	.	.	PUNCT
ajst-32536	144	1	a	a	DET
ajst-32536	144	2	precision	precision	NOUN
ajst-32536	144	3	of	of	ADP
ajst-32536	144	4	91.27	91.27	NUM
ajst-32536	144	5	%	%	NOUN
ajst-32536	144	6	reduces	reduce	VERB
ajst-32536	144	7	false	false	ADJ
ajst-32536	144	8	-	-	PUNCT
ajst-32536	144	9	positive	positive	ADJ
ajst-32536	144	10	misjudgments	misjudgment	NOUN
ajst-32536	144	11	.	.	PUNCT
ajst-32536	145	1	a	a	DET
ajst-32536	145	2	recall	recall	NOUN
ajst-32536	145	3	of	of	ADP
ajst-32536	145	4	90.72	90.72	NUM
ajst-32536	145	5	%	%	NOUN
ajst-32536	145	6	reduces	reduce	VERB
ajst-32536	145	7	the	the	DET
ajst-32536	145	8	risk	risk	NOUN
ajst-32536	145	9	of	of	ADP
ajst-32536	145	10	early	early	ADJ
ajst-32536	145	11	missed	miss	VERB
ajst-32536	145	12	diagnosis	diagnosis	NOUN
ajst-32536	145	13	,	,	PUNCT
ajst-32536	145	14	and	and	CCONJ
ajst-32536	145	15	an	an	DET
ajst-32536	145	16	f1	f1	ADJ
ajst-32536	145	17	score	score	NOUN
ajst-32536	145	18	of	of	ADP
ajst-32536	145	19	90.99	90.99	NUM
ajst-32536	145	20	%	%	NOUN
ajst-32536	145	21	achieves	achieve	VERB
ajst-32536	145	22	a	a	DET
ajst-32536	145	23	balance	balance	NOUN
ajst-32536	145	24	between	between	ADP
ajst-32536	145	25	"	"	PUNCT
ajst-32536	145	26	precision	precision	NOUN
ajst-32536	145	27	"	"	PUNCT
ajst-32536	145	28	and	and	CCONJ
ajst-32536	145	29	"	"	PUNCT
ajst-32536	145	30	comprehensiveness	comprehensiveness	NOUN
ajst-32536	145	31	"	"	PUNCT
ajst-32536	145	32	.	.	PUNCT
ajst-32536	146	1	4.2	4.2	NUM
ajst-32536	146	2	detection	detection	NOUN
ajst-32536	146	3	results	result	NOUN
ajst-32536	146	4	of	of	ADP
ajst-32536	146	5	the	the	DET
ajst-32536	146	6	new	new	PROPN
ajst-32536	146	7	mexico	mexico	PROPN
ajst-32536	146	8	dataset	dataset	VERB
ajst-32536	146	9	for	for	ADP
ajst-32536	146	10	the	the	DET
ajst-32536	146	11	university	university	NOUN
ajst-32536	146	12	of	of	ADP
ajst-32536	146	13	new	new	PROPN
ajst-32536	146	14	mexico	mexico	PROPN
ajst-32536	146	15	(	(	PUNCT
ajst-32536	146	16	unm	unm	PROPN
ajst-32536	146	17	)	)	PUNCT
ajst-32536	146	18	parkinson	parkinson	NOUN
ajst-32536	146	19	’s	’s	PART
ajst-32536	146	20	disease	disease	NOUN
ajst-32536	146	21	(	(	PUNCT
ajst-32536	146	22	pd	pd	NOUN
ajst-32536	146	23	)	)	PUNCT
ajst-32536	146	24	eeg	eeg	PROPN
ajst-32536	146	25	dataset	dataset	NOUN
ajst-32536	146	26	,	,	PUNCT
ajst-32536	146	27	the	the	DET
ajst-32536	146	28	preprocessing	preprocessing	NOUN
ajst-32536	146	29	workflow	workflow	NOUN
ajst-32536	146	30	was	be	AUX
ajst-32536	146	31	implemented	implement	VERB
ajst-32536	146	32	in	in	ADP
ajst-32536	146	33	the	the	DET
ajst-32536	146	34	following	follow	VERB
ajst-32536	146	35	sequential	sequential	ADJ
ajst-32536	146	36	steps	step	NOUN
ajst-32536	146	37	:	:	PUNCT
ajst-32536	146	38	first	first	ADJ
ajst-32536	146	39	,	,	PUNCT
ajst-32536	146	40	channel	channel	NOUN
ajst-32536	146	41	-	-	PUNCT
ajst-32536	146	42	level	level	NOUN
ajst-32536	146	43	operations	operation	NOUN
ajst-32536	146	44	were	be	AUX
ajst-32536	146	45	performed	perform	VERB
ajst-32536	146	46	.	.	PUNCT
ajst-32536	147	1	owing	owe	VERB
ajst-32536	147	2	to	to	ADP
ajst-32536	147	3	the	the	DET
ajst-32536	147	4	absence	absence	NOUN
ajst-32536	147	5	of	of	ADP
ajst-32536	147	6	cpz	cpz	PROPN
ajst-32536	147	7	channel	channel	NOUN
ajst-32536	147	8	data	datum	NOUN
ajst-32536	147	9	—	—	PUNCT
ajst-32536	147	10	a	a	DET
ajst-32536	147	11	consequence	consequence	NOUN
ajst-32536	147	12	of	of	ADP
ajst-32536	147	13	using	use	VERB
ajst-32536	147	14	an	an	DET
ajst-32536	147	15	online	online	ADJ
ajst-32536	147	16	cpz	cpz	NOUN
ajst-32536	147	17	reference	reference	NOUN
ajst-32536	147	18	during	during	ADP
ajst-32536	147	19	data	data	NOUN
ajst-32536	147	20	acquisition	acquisition	NOUN
ajst-32536	147	21	—	—	PUNCT
ajst-32536	147	22	an	an	DET
ajst-32536	147	23	alternative	alternative	ADJ
ajst-32536	147	24	valid	valid	ADJ
ajst-32536	147	25	electrode	electrode	NOUN
ajst-32536	147	26	configuration	configuration	NOUN
ajst-32536	147	27	was	be	AUX
ajst-32536	147	28	adopted	adopt	VERB
ajst-32536	147	29	for	for	ADP
ajst-32536	147	30	re	re	NOUN
ajst-32536	147	31	-	-	NOUN
ajst-32536	147	32	referencing	referencing	ADJ
ajst-32536	147	33	,	,	PUNCT
ajst-32536	147	34	specifically	specifically	ADV
ajst-32536	147	35	converting	convert	VERB
ajst-32536	147	36	to	to	ADP
ajst-32536	147	37	a	a	DET
ajst-32536	147	38	whole	whole	ADJ
ajst-32536	147	39	-	-	PUNCT
ajst-32536	147	40	brain	brain	NOUN
ajst-32536	147	41	average	average	ADJ
ajst-32536	147	42	reference	reference	NOUN
ajst-32536	147	43	to	to	PART
ajst-32536	147	44	ensure	ensure	VERB
ajst-32536	147	45	spatial	spatial	ADJ
ajst-32536	147	46	consistency	consistency	NOUN
ajst-32536	147	47	of	of	ADP
ajst-32536	147	48	the	the	DET
ajst-32536	147	49	eeg	eeg	NOUN
ajst-32536	147	50	signals	signal	NOUN
ajst-32536	147	51	across	across	ADP
ajst-32536	147	52	all	all	DET
ajst-32536	147	53	channels	channel	NOUN
ajst-32536	147	54	.	.	PUNCT
ajst-32536	148	1	second	second	ADJ
ajst-32536	148	2	,	,	PUNCT
ajst-32536	148	3	the	the	DET
ajst-32536	148	4	raw	raw	ADJ
ajst-32536	148	5	eeg	eeg	NOUN
ajst-32536	148	6	signals	signal	NOUN
ajst-32536	148	7	,	,	PUNCT
ajst-32536	148	8	originally	originally	ADV
ajst-32536	148	9	sampled	sample	VERB
ajst-32536	148	10	at	at	ADP
ajst-32536	148	11	500	500	NUM
ajst-32536	148	12	hz	hz	NOUN
ajst-32536	148	13	,	,	PUNCT
ajst-32536	148	14	were	be	AUX
ajst-32536	148	15	downsampled	downsample	VERB
ajst-32536	148	16	to	to	ADP
ajst-32536	148	17	250	250	NUM
ajst-32536	148	18	hz	hz	NOUN
ajst-32536	148	19	.	.	PUNCT
ajst-32536	149	1	this	this	DET
ajst-32536	149	2	step	step	NOUN
ajst-32536	149	3	aimed	aim	VERB
ajst-32536	149	4	to	to	PART
ajst-32536	149	5	reduce	reduce	VERB
ajst-32536	149	6	redundant	redundant	ADJ
ajst-32536	149	7	data	datum	NOUN
ajst-32536	149	8	volume	volume	NOUN
ajst-32536	149	9	while	while	SCONJ
ajst-32536	149	10	preserving	preserve	VERB
ajst-32536	149	11	critical	critical	ADJ
ajst-32536	149	12	neural	neural	ADJ
ajst-32536	149	13	activity	activity	NOUN
ajst-32536	149	14	information	information	NOUN
ajst-32536	149	15	.	.	PUNCT
ajst-32536	150	1	concurrently	concurrently	ADV
ajst-32536	150	2	,	,	PUNCT
ajst-32536	150	3	a	a	DET
ajst-32536	150	4	band	band	NOUN
ajst-32536	150	5	-	-	PUNCT
ajst-32536	150	6	pass	pass	NOUN
ajst-32536	150	7	filter	filter	NOUN
ajst-32536	150	8	(	(	PUNCT
ajst-32536	150	9	e.g.	e.g.	ADV
ajst-32536	150	10	,	,	PUNCT
ajst-32536	150	11	0.5–45	0.5–45	NOUN
ajst-32536	150	12	hz	hz	VERB
ajst-32536	150	13	)	)	PUNCT
ajst-32536	150	14	was	be	AUX
ajst-32536	150	15	applied	apply	VERB
ajst-32536	150	16	to	to	PART
ajst-32536	150	17	eliminate	eliminate	VERB
ajst-32536	150	18	low	low	ADJ
ajst-32536	150	19	-	-	PUNCT
ajst-32536	150	20	frequency	frequency	NOUN
ajst-32536	150	21	drifts	drift	NOUN
ajst-32536	150	22	(	(	PUNCT
ajst-32536	150	23	attributed	attribute	VERB
ajst-32536	150	24	to	to	ADP
ajst-32536	150	25	physiological	physiological	ADJ
ajst-32536	150	26	artifacts	artifact	NOUN
ajst-32536	150	27	such	such	ADJ
ajst-32536	150	28	as	as	ADP
ajst-32536	150	29	respiration	respiration	NOUN
ajst-32536	150	30	or	or	CCONJ
ajst-32536	150	31	skin	skin	NOUN
ajst-32536	150	32	potential	potential	NOUN
ajst-32536	150	33	)	)	PUNCT
ajst-32536	150	34	and	and	CCONJ
ajst-32536	150	35	high	high	ADJ
ajst-32536	150	36	-	-	PUNCT
ajst-32536	150	37	frequency	frequency	NOUN
ajst-32536	150	38	noise	noise	NOUN
ajst-32536	150	39	(	(	PUNCT
ajst-32536	150	40	e.g.	e.g.	ADV
ajst-32536	150	41	,	,	PUNCT
ajst-32536	150	42	electromagnetic	electromagnetic	ADJ
ajst-32536	150	43	interference	interference	NOUN
ajst-32536	150	44	)	)	PUNCT
ajst-32536	150	45	,	,	PUNCT
ajst-32536	150	46	thereby	thereby	ADV
ajst-32536	150	47	refining	refine	VERB
ajst-32536	150	48	the	the	DET
ajst-32536	150	49	signal	signal	NOUN
ajst-32536	150	50	-	-	PUNCT
ajst-32536	150	51	to	to	ADP
ajst-32536	150	52	-	-	PUNCT
ajst-32536	150	53	noise	noise	NOUN
ajst-32536	150	54	ratio	ratio	NOUN
ajst-32536	150	55	.	.	PUNCT
ajst-32536	151	1	third	third	ADJ
ajst-32536	151	2	,	,	PUNCT
ajst-32536	151	3	artifact	artifact	ADJ
ajst-32536	151	4	removal	removal	NOUN
ajst-32536	151	5	was	be	AUX
ajst-32536	151	6	conducted	conduct	VERB
ajst-32536	151	7	via	via	ADP
ajst-32536	151	8	independent	independent	ADJ
ajst-32536	151	9	component	component	NOUN
ajst-32536	151	10	analysis	analysis	NOUN
ajst-32536	151	11	(	(	PUNCT
ajst-32536	151	12	ica	ica	PROPN
ajst-32536	151	13	)	)	PUNCT
ajst-32536	151	14	.	.	PUNCT
ajst-32536	152	1	this	this	DET
ajst-32536	152	2	technique	technique	NOUN
ajst-32536	152	3	enabled	enable	VERB
ajst-32536	152	4	the	the	DET
ajst-32536	152	5	identification	identification	NOUN
ajst-32536	152	6	and	and	CCONJ
ajst-32536	152	7	subsequent	subsequent	ADJ
ajst-32536	152	8	removal	removal	NOUN
ajst-32536	152	9	of	of	ADP
ajst-32536	152	10	non	non	ADJ
ajst-32536	152	11	-	-	ADJ
ajst-32536	152	12	neural	neural	ADJ
ajst-32536	152	13	biological	biological	ADJ
ajst-32536	152	14	artifacts	artifact	NOUN
ajst-32536	152	15	,	,	PUNCT
ajst-32536	152	16	including	include	VERB
ajst-32536	152	17	electrooculographic	electrooculographic	ADJ
ajst-32536	152	18	(	(	PUNCT
ajst-32536	152	19	eog	eog	PROPN
ajst-32536	152	20	)	)	PUNCT
ajst-32536	152	21	signals	signal	NOUN
ajst-32536	152	22	(	(	PUNCT
ajst-32536	152	23	resulting	result	VERB
ajst-32536	152	24	from	from	ADP
ajst-32536	152	25	eye	eye	NOUN
ajst-32536	152	26	movements	movement	NOUN
ajst-32536	152	27	or	or	CCONJ
ajst-32536	152	28	blinks	blink	VERB
ajst-32536	152	29	)	)	PUNCT
ajst-32536	152	30	and	and	CCONJ
ajst-32536	152	31	electromyographic	electromyographic	ADJ
ajst-32536	152	32	(	(	PUNCT
ajst-32536	152	33	emg	emg	NOUN
ajst-32536	152	34	)	)	PUNCT
ajst-32536	152	35	signals	signal	NOUN
ajst-32536	152	36	(	(	PUNCT
ajst-32536	152	37	originating	originate	VERB
ajst-32536	152	38	from	from	ADP
ajst-32536	152	39	muscle	muscle	NOUN
ajst-32536	152	40	tension	tension	NOUN
ajst-32536	152	41	)	)	PUNCT
ajst-32536	152	42	,	,	PUNCT
ajst-32536	152	43	which	which	PRON
ajst-32536	152	44	could	could	AUX
ajst-32536	152	45	otherwise	otherwise	ADV
ajst-32536	152	46	confound	confound	VERB
ajst-32536	152	47	the	the	DET
ajst-32536	152	48	interpretation	interpretation	NOUN
ajst-32536	152	49	of	of	ADP
ajst-32536	152	50	neural	neural	ADJ
ajst-32536	152	51	activity	activity	NOUN
ajst-32536	152	52	.	.	PUNCT
ajst-32536	153	1	fourth	fourth	ADJ
ajst-32536	153	2	,	,	PUNCT
ajst-32536	153	3	the	the	DET
ajst-32536	153	4	continuous	continuous	ADJ
ajst-32536	153	5	two	two	NUM
ajst-32536	153	6	-	-	PUNCT
ajst-32536	153	7	minute	minute	NOUN
ajst-32536	153	8	eeg	eeg	NOUN
ajst-32536	153	9	recordings	recording	NOUN
ajst-32536	153	10	were	be	AUX
ajst-32536	153	11	segmented	segment	VERB
ajst-32536	153	12	into	into	ADP
ajst-32536	153	13	equal	equal	ADJ
ajst-32536	153	14	-	-	PUNCT
ajst-32536	153	15	length	length	NOUN
ajst-32536	153	16	epochs	epoch	NOUN
ajst-32536	153	17	based	base	VERB
ajst-32536	153	18	on	on	ADP
ajst-32536	153	19	experimental	experimental	ADJ
ajst-32536	153	20	conditions	condition	NOUN
ajst-32536	153	21	(	(	PUNCT
ajst-32536	153	22	e.g.	e.g.	ADV
ajst-32536	153	23	,	,	PUNCT
ajst-32536	153	24	resting	rest	VERB
ajst-32536	153	25	state	state	NOUN
ajst-32536	153	26	or	or	CCONJ
ajst-32536	153	27	task36	task36	NOUN
ajst-32536	153	28	specific	specific	ADJ
ajst-32536	153	29	periods	period	NOUN
ajst-32536	153	30	)	)	PUNCT
ajst-32536	153	31	.	.	PUNCT
ajst-32536	154	1	baseline	baseline	PROPN
ajst-32536	154	2	correction	correction	NOUN
ajst-32536	154	3	was	be	AUX
ajst-32536	154	4	further	far	ADV
ajst-32536	154	5	applied	apply	VERB
ajst-32536	154	6	to	to	ADP
ajst-32536	154	7	each	each	DET
ajst-32536	154	8	epoch	epoch	NOUN
ajst-32536	154	9	to	to	PART
ajst-32536	154	10	adjust	adjust	VERB
ajst-32536	154	11	for	for	ADP
ajst-32536	154	12	signal	signal	NOUN
ajst-32536	154	13	offsets	offset	NOUN
ajst-32536	154	14	relative	relative	ADJ
ajst-32536	154	15	to	to	ADP
ajst-32536	154	16	a	a	DET
ajst-32536	154	17	pre	pre	ADJ
ajst-32536	154	18	-	-	ADJ
ajst-32536	154	19	defined	define	VERB
ajst-32536	154	20	baseline	baseline	NOUN
ajst-32536	154	21	period	period	NOUN
ajst-32536	154	22	,	,	PUNCT
ajst-32536	154	23	ensuring	ensure	VERB
ajst-32536	154	24	that	that	SCONJ
ajst-32536	154	25	variations	variation	NOUN
ajst-32536	154	26	in	in	ADP
ajst-32536	154	27	signal	signal	ADJ
ajst-32536	154	28	amplitude	amplitude	NOUN
ajst-32536	154	29	reflected	reflect	VERB
ajst-32536	154	30	true	true	ADJ
ajst-32536	154	31	neural	neural	ADJ
ajst-32536	154	32	fluctuations	fluctuation	NOUN
ajst-32536	154	33	rather	rather	ADV
ajst-32536	154	34	than	than	ADP
ajst-32536	154	35	baseline	baseline	VERB
ajst-32536	154	36	drifts	drift	NOUN
ajst-32536	154	37	.	.	PUNCT
ajst-32536	155	1	fifth	fifth	ADJ
ajst-32536	155	2	,	,	PUNCT
ajst-32536	155	3	data	datum	NOUN
ajst-32536	155	4	normalization	normalization	NOUN
ajst-32536	155	5	was	be	AUX
ajst-32536	155	6	performed	perform	VERB
ajst-32536	155	7	on	on	ADP
ajst-32536	155	8	recordings	recording	NOUN
ajst-32536	155	9	corresponding	correspond	VERB
ajst-32536	155	10	to	to	ADP
ajst-32536	155	11	different	different	ADJ
ajst-32536	155	12	states	state	NOUN
ajst-32536	155	13	(	(	PUNCT
ajst-32536	155	14	medicated	medicate	VERB
ajst-32536	155	15	vs.	vs.	X
ajst-32536	155	16	unmedicated	unmedicated	ADJ
ajst-32536	155	17	)	)	PUNCT
ajst-32536	155	18	for	for	ADP
ajst-32536	155	19	each	each	DET
ajst-32536	155	20	participant	participant	NOUN
ajst-32536	155	21	.	.	PUNCT
ajst-32536	156	1	this	this	DET
ajst-32536	156	2	step	step	NOUN
ajst-32536	156	3	standardized	standardize	VERB
ajst-32536	156	4	the	the	DET
ajst-32536	156	5	signal	signal	ADJ
ajst-32536	156	6	amplitude	amplitude	NOUN
ajst-32536	156	7	scale	scale	NOUN
ajst-32536	156	8	across	across	ADP
ajst-32536	156	9	all	all	DET
ajst-32536	156	10	conditions	condition	NOUN
ajst-32536	156	11	,	,	PUNCT
ajst-32536	156	12	eliminating	eliminate	VERB
ajst-32536	156	13	potential	potential	ADJ
ajst-32536	156	14	biases	bias	NOUN
ajst-32536	156	15	arising	arise	VERB
ajst-32536	156	16	from	from	ADP
ajst-32536	156	17	inter	inter	ADJ
ajst-32536	156	18	-	-	ADJ
ajst-32536	156	19	state	state	ADJ
ajst-32536	156	20	differences	difference	NOUN
ajst-32536	156	21	in	in	ADP
ajst-32536	156	22	signal	signal	ADJ
ajst-32536	156	23	magnitude	magnitude	NOUN
ajst-32536	156	24	and	and	CCONJ
ajst-32536	156	25	facilitating	facilitate	VERB
ajst-32536	156	26	cross	cross	ADJ
ajst-32536	156	27	-	-	ADJ
ajst-32536	156	28	condition	condition	ADJ
ajst-32536	156	29	comparisons	comparison	NOUN
ajst-32536	156	30	.	.	PUNCT
ajst-32536	157	1	finally	finally	ADV
ajst-32536	157	2	,	,	PUNCT
ajst-32536	157	3	a	a	DET
ajst-32536	157	4	labeled	label	VERB
ajst-32536	157	5	dataset	dataset	NOUN
ajst-32536	157	6	was	be	AUX
ajst-32536	157	7	constructed	construct	VERB
ajst-32536	157	8	,	,	PUNCT
ajst-32536	157	9	encompassing	encompass	VERB
ajst-32536	157	10	data	datum	NOUN
ajst-32536	157	11	from	from	ADP
ajst-32536	157	12	both	both	DET
ajst-32536	157	13	pd	pd	PROPN
ajst-32536	157	14	patients	patient	NOUN
ajst-32536	157	15	and	and	CCONJ
ajst-32536	157	16	healthy	healthy	ADJ
ajst-32536	157	17	control	control	NOUN
ajst-32536	157	18	subjects	subject	NOUN
ajst-32536	157	19	,	,	PUNCT
ajst-32536	157	20	as	as	ADV
ajst-32536	157	21	well	well	ADV
ajst-32536	157	22	as	as	ADP
ajst-32536	157	23	from	from	ADP
ajst-32536	157	24	pd	pd	PROPN
ajst-32536	157	25	patients	patient	NOUN
ajst-32536	157	26	in	in	ADP
ajst-32536	157	27	distinct	distinct	ADJ
ajst-32536	157	28	medication	medication	NOUN
ajst-32536	157	29	states	state	NOUN
ajst-32536	157	30	(	(	PUNCT
ajst-32536	157	31	medicated	medicate	VERB
ajst-32536	157	32	vs.	vs.	X
ajst-32536	157	33	unmedicated	unmedicated	ADJ
ajst-32536	157	34	)	)	PUNCT
ajst-32536	157	35	.	.	PUNCT
ajst-32536	158	1	this	this	DET
ajst-32536	158	2	preprocessed	preprocesse	VERB
ajst-32536	158	3	and	and	CCONJ
ajst-32536	158	4	labeled	label	VERB
ajst-32536	158	5	dataset	dataset	NOUN
ajst-32536	158	6	laid	lay	VERB
ajst-32536	158	7	the	the	DET
ajst-32536	158	8	foundation	foundation	NOUN
ajst-32536	158	9	for	for	ADP
ajst-32536	158	10	subsequent	subsequent	ADJ
ajst-32536	158	11	feature	feature	NOUN
ajst-32536	158	12	extraction	extraction	NOUN
ajst-32536	158	13	and	and	CCONJ
ajst-32536	158	14	analysis	analysis	NOUN
ajst-32536	158	15	across	across	ADP
ajst-32536	158	16	the	the	DET
ajst-32536	158	17	time	time	NOUN
ajst-32536	158	18	domain	domain	NOUN
ajst-32536	158	19	,	,	PUNCT
ajst-32536	158	20	frequency	frequency	NOUN
ajst-32536	158	21	domain	domain	NOUN
ajst-32536	158	22	,	,	PUNCT
ajst-32536	158	23	and	and	CCONJ
ajst-32536	158	24	time	time	NOUN
ajst-32536	158	25	-	-	PUNCT
ajst-32536	158	26	frequency	frequency	NOUN
ajst-32536	158	27	domain	domain	NOUN
ajst-32536	158	28	.	.	PUNCT
ajst-32536	159	1	the	the	DET
ajst-32536	159	2	validation	validation	NOUN
ajst-32536	159	3	results	result	NOUN
ajst-32536	159	4	of	of	ADP
ajst-32536	159	5	this	this	DET
ajst-32536	159	6	dataset	dataset	NOUN
ajst-32536	159	7	are	be	AUX
ajst-32536	159	8	presented	present	VERB
ajst-32536	159	9	in	in	ADP
ajst-32536	159	10	table	table	NOUN
ajst-32536	159	11	2	2	NUM
ajst-32536	159	12	.	.	PUNCT
ajst-32536	159	13	table	table	NOUN
ajst-32536	159	14	2	2	NUM
ajst-32536	159	15	.	.	PUNCT
ajst-32536	159	16	dataset	dataset	NOUN
ajst-32536	159	17	validation	validation	NOUN
ajst-32536	159	18	results	result	NOUN
ajst-32536	159	19	evaluation	evaluation	NOUN
ajst-32536	159	20	metric	metric	ADJ
ajst-32536	159	21	accuracy	accuracy	NOUN
ajst-32536	159	22	precision	precision	NOUN
ajst-32536	159	23	recall	recall	NOUN
ajst-32536	159	24	f1	f1	NOUN
ajst-32536	159	25	score	score	NOUN
ajst-32536	159	26	value	value	NOUN
ajst-32536	159	27	(	(	PUNCT
ajst-32536	159	28	%	%	INTJ
ajst-32536	159	29	)	)	PUNCT
ajst-32536	159	30	98.15	98.15	NUM
ajst-32536	159	31	97.63	97.63	NUM
ajst-32536	159	32	96.12	96.12	NUM
ajst-32536	159	33	96.87	96.87	NUM
ajst-32536	159	34	as	as	SCONJ
ajst-32536	159	35	indicated	indicate	VERB
ajst-32536	159	36	in	in	ADP
ajst-32536	159	37	table	table	NOUN
ajst-32536	159	38	2	2	NUM
ajst-32536	159	39	,	,	PUNCT
ajst-32536	159	40	the	the	DET
ajst-32536	159	41	model	model	NOUN
ajst-32536	159	42	constructed	construct	VERB
ajst-32536	159	43	by	by	ADP
ajst-32536	159	44	drsn	drsn	PROPN
ajst-32536	159	45	demonstrates	demonstrate	VERB
ajst-32536	159	46	exceptional	exceptional	ADJ
ajst-32536	159	47	performance	performance	NOUN
ajst-32536	159	48	in	in	ADP
ajst-32536	159	49	detection	detection	NOUN
ajst-32536	159	50	tasks	task	NOUN
ajst-32536	159	51	using	use	VERB
ajst-32536	159	52	the	the	DET
ajst-32536	159	53	unm	unm	PROPN
ajst-32536	159	54	parkinson	parkinson	NOUN
ajst-32536	159	55	’s	’s	PART
ajst-32536	159	56	disease	disease	NOUN
ajst-32536	159	57	(	(	PUNCT
ajst-32536	159	58	pd	pd	NOUN
ajst-32536	159	59	)	)	PUNCT
ajst-32536	159	60	eeg	eeg	PROPN
ajst-32536	159	61	dataset	dataset	NOUN
ajst-32536	159	62	.	.	PUNCT
ajst-32536	160	1	specifically	specifically	ADV
ajst-32536	160	2	,	,	PUNCT
ajst-32536	160	3	it	it	PRON
ajst-32536	160	4	achieves	achieve	VERB
ajst-32536	160	5	an	an	DET
ajst-32536	160	6	accuracy	accuracy	NOUN
ajst-32536	160	7	of	of	ADP
ajst-32536	160	8	98.15	98.15	NUM
ajst-32536	160	9	%	%	NOUN
ajst-32536	160	10	,	,	PUNCT
ajst-32536	160	11	a	a	DET
ajst-32536	160	12	precision	precision	NOUN
ajst-32536	160	13	of	of	ADP
ajst-32536	160	14	97.63	97.63	NUM
ajst-32536	160	15	%	%	NOUN
ajst-32536	160	16	,	,	PUNCT
ajst-32536	160	17	a	a	DET
ajst-32536	160	18	recall	recall	NOUN
ajst-32536	160	19	of	of	ADP
ajst-32536	160	20	96.12	96.12	NUM
ajst-32536	160	21	%	%	NOUN
ajst-32536	160	22	,	,	PUNCT
ajst-32536	160	23	and	and	CCONJ
ajst-32536	160	24	an	an	DET
ajst-32536	160	25	f1	f1	ADJ
ajst-32536	160	26	score	score	NOUN
ajst-32536	160	27	of	of	ADP
ajst-32536	160	28	96.87%—all	96.87%—all	NUM
ajst-32536	160	29	metrics	metric	NOUN
ajst-32536	160	30	attaining	attain	VERB
ajst-32536	160	31	notably	notably	ADV
ajst-32536	160	32	high	high	ADJ
ajst-32536	160	33	levels	level	NOUN
ajst-32536	160	34	.	.	PUNCT
ajst-32536	161	1	these	these	DET
ajst-32536	161	2	results	result	NOUN
ajst-32536	161	3	underscore	underscore	VERB
ajst-32536	161	4	that	that	SCONJ
ajst-32536	161	5	the	the	DET
ajst-32536	161	6	model	model	NOUN
ajst-32536	161	7	exhibits	exhibit	VERB
ajst-32536	161	8	three	three	NUM
ajst-32536	161	9	key	key	ADJ
ajst-32536	161	10	strengths	strength	NOUN
ajst-32536	161	11	in	in	ADP
ajst-32536	161	12	classification	classification	NOUN
ajst-32536	161	13	tasks	task	NOUN
ajst-32536	161	14	:	:	PUNCT
ajst-32536	161	15	strong	strong	ADJ
ajst-32536	161	16	overall	overall	ADJ
ajst-32536	161	17	accuracy	accuracy	NOUN
ajst-32536	161	18	in	in	ADP
ajst-32536	161	19	distinguishing	distinguish	VERB
ajst-32536	161	20	between	between	ADP
ajst-32536	161	21	classes	class	NOUN
ajst-32536	161	22	,	,	PUNCT
ajst-32536	161	23	robust	robust	ADJ
ajst-32536	161	24	capability	capability	NOUN
ajst-32536	161	25	to	to	PART
ajst-32536	161	26	correctly	correctly	ADV
ajst-32536	161	27	identify	identify	VERB
ajst-32536	161	28	positive	positive	ADJ
ajst-32536	161	29	cases	case	NOUN
ajst-32536	161	30	(	(	PUNCT
ajst-32536	161	31	e.g.	e.g.	ADV
ajst-32536	161	32	,	,	PUNCT
ajst-32536	161	33	pd	pd	ADJ
ajst-32536	161	34	-	-	PUNCT
ajst-32536	161	35	related	relate	VERB
ajst-32536	161	36	states	state	NOUN
ajst-32536	161	37	)	)	PUNCT
ajst-32536	161	38	,	,	PUNCT
ajst-32536	161	39	and	and	CCONJ
ajst-32536	161	40	a	a	DET
ajst-32536	161	41	well	well	ADV
ajst-32536	161	42	-	-	PUNCT
ajst-32536	161	43	balanced	balance	VERB
ajst-32536	161	44	trade	trade	NOUN
ajst-32536	161	45	-	-	PUNCT
ajst-32536	161	46	off	off	NOUN
ajst-32536	161	47	between	between	ADP
ajst-32536	161	48	recall	recall	NOUN
ajst-32536	161	49	(	(	PUNCT
ajst-32536	161	50	capturing	capture	VERB
ajst-32536	161	51	true	true	ADJ
ajst-32536	161	52	positive	positive	ADJ
ajst-32536	161	53	cases	case	NOUN
ajst-32536	161	54	)	)	PUNCT
ajst-32536	161	55	and	and	CCONJ
ajst-32536	161	56	precision	precision	NOUN
ajst-32536	161	57	(	(	PUNCT
ajst-32536	161	58	minimizing	minimize	VERB
ajst-32536	161	59	false	false	ADJ
ajst-32536	161	60	positive	positive	ADJ
ajst-32536	161	61	cases	case	NOUN
ajst-32536	161	62	)	)	PUNCT
ajst-32536	161	63	.	.	PUNCT
ajst-32536	162	1	5	5	X
ajst-32536	162	2	.	.	X
ajst-32536	162	3	discussion	discussion	NOUN
ajst-32536	162	4	5.1	5.1	NUM
ajst-32536	162	5	comparison	comparison	NOUN
ajst-32536	162	6	with	with	ADP
ajst-32536	162	7	alternative	alternative	ADJ
ajst-32536	162	8	methods	method	NOUN
ajst-32536	162	9	to	to	PART
ajst-32536	162	10	demonstrate	demonstrate	VERB
ajst-32536	162	11	the	the	DET
ajst-32536	162	12	advantages	advantage	NOUN
ajst-32536	162	13	of	of	ADP
ajst-32536	162	14	the	the	DET
ajst-32536	162	15	pooling	pool	VERB
ajst-32536	162	16	fusion	fusion	NOUN
ajst-32536	162	17	-	-	PUNCT
ajst-32536	162	18	based	base	VERB
ajst-32536	162	19	drsn	drsn	NOUN
ajst-32536	162	20	proposed	propose	VERB
ajst-32536	162	21	in	in	ADP
ajst-32536	162	22	this	this	DET
ajst-32536	162	23	study	study	NOUN
ajst-32536	162	24	for	for	ADP
ajst-32536	162	25	parkinson	parkinson	NOUN
ajst-32536	162	26	’s	’s	PART
ajst-32536	162	27	disease	disease	NOUN
ajst-32536	162	28	(	(	PUNCT
ajst-32536	162	29	pd	pd	NOUN
ajst-32536	162	30	)	)	PUNCT
ajst-32536	162	31	detection	detection	NOUN
ajst-32536	162	32	,	,	PUNCT
ajst-32536	162	33	a	a	DET
ajst-32536	162	34	comparative	comparative	ADJ
ajst-32536	162	35	analysis	analysis	NOUN
ajst-32536	162	36	was	be	AUX
ajst-32536	162	37	conducted	conduct	VERB
ajst-32536	162	38	against	against	ADP
ajst-32536	162	39	traditional	traditional	ADJ
ajst-32536	162	40	pd	pd	PROPN
ajst-32536	162	41	detection	detection	NOUN
ajst-32536	162	42	methods	method	NOUN
ajst-32536	162	43	.	.	PUNCT
ajst-32536	163	1	specifically	specifically	ADV
ajst-32536	163	2	,	,	PUNCT
ajst-32536	163	3	the	the	DET
ajst-32536	163	4	accuracy	accuracy	NOUN
ajst-32536	163	5	of	of	ADP
ajst-32536	163	6	conventional	conventional	ADJ
ajst-32536	163	7	approaches	approach	NOUN
ajst-32536	163	8	—	—	PUNCT
ajst-32536	163	9	including	include	VERB
ajst-32536	163	10	convolutional	convolutional	ADJ
ajst-32536	163	11	neural	neural	ADJ
ajst-32536	163	12	network	network	NOUN
ajst-32536	163	13	(	(	PUNCT
ajst-32536	163	14	cnn	cnn	PROPN
ajst-32536	163	15	)	)	PUNCT
ajst-32536	163	16	,	,	PUNCT
ajst-32536	163	17	multi	multi	ADJ
ajst-32536	163	18	-	-	ADJ
ajst-32536	163	19	scale	scale	ADJ
ajst-32536	163	20	convolutional	convolutional	ADJ
ajst-32536	163	21	neural	neural	ADJ
ajst-32536	163	22	network	network	NOUN
ajst-32536	163	23	(	(	PUNCT
ajst-32536	163	24	mscnn	mscnn	PROPN
ajst-32536	163	25	)	)	PUNCT
ajst-32536	163	26	,	,	PUNCT
ajst-32536	163	27	long	long	ADJ
ajst-32536	163	28	short	short	ADJ
ajst-32536	163	29	-	-	PUNCT
ajst-32536	163	30	term	term	NOUN
ajst-32536	163	31	memory	memory	NOUN
ajst-32536	163	32	(	(	PUNCT
ajst-32536	163	33	lstm	lstm	NOUN
ajst-32536	163	34	)	)	PUNCT
ajst-32536	163	35	,	,	PUNCT
ajst-32536	163	36	deep	deep	ADJ
ajst-32536	163	37	residual	residual	ADJ
ajst-32536	163	38	networks	network	NOUN
ajst-32536	163	39	(	(	PUNCT
ajst-32536	163	40	resnet	resnet	NOUN
ajst-32536	163	41	)	)	PUNCT
ajst-32536	163	42	,	,	PUNCT
ajst-32536	163	43	and	and	CCONJ
ajst-32536	163	44	transformer	transformer	NOUN
ajst-32536	163	45	—	—	PUNCT
ajst-32536	163	46	was	be	AUX
ajst-32536	163	47	evaluated	evaluate	VERB
ajst-32536	163	48	on	on	ADP
ajst-32536	163	49	the	the	DET
ajst-32536	163	50	same	same	ADJ
ajst-32536	163	51	neural	neural	ADJ
ajst-32536	163	52	activity	activity	NOUN
ajst-32536	163	53	dataset	dataset	NOUN
ajst-32536	163	54	of	of	ADP
ajst-32536	163	55	pd	pd	PROPN
ajst-32536	163	56	.	.	PUNCT
ajst-32536	164	1	the	the	DET
ajst-32536	164	2	comparative	comparative	ADJ
ajst-32536	164	3	results	result	NOUN
ajst-32536	164	4	are	be	AUX
ajst-32536	164	5	presented	present	VERB
ajst-32536	164	6	in	in	ADP
ajst-32536	164	7	table	table	NOUN
ajst-32536	164	8	3	3	NUM
ajst-32536	164	9	.	.	PUNCT
ajst-32536	164	10	table	table	NOUN
ajst-32536	164	11	3	3	NUM
ajst-32536	164	12	.	.	PUNCT
ajst-32536	164	13	comparison	comparison	NOUN
ajst-32536	164	14	of	of	ADP
ajst-32536	164	15	accuracy	accuracy	NOUN
ajst-32536	164	16	among	among	ADP
ajst-32536	164	17	various	various	ADJ
ajst-32536	164	18	methods	method	NOUN
ajst-32536	164	19	on	on	ADP
ajst-32536	164	20	the	the	DET
ajst-32536	164	21	parkinson	parkinson	NOUN
ajst-32536	164	22	’s	’s	PART
ajst-32536	164	23	disease	disease	NOUN
ajst-32536	164	24	neural	neural	ADJ
ajst-32536	164	25	activity	activity	NOUN
ajst-32536	164	26	dataset	dataset	NOUN
ajst-32536	164	27	reference	reference	NOUN
ajst-32536	164	28	method	method	NOUN
ajst-32536	164	29	accuracy	accuracy	NOUN
ajst-32536	164	30	(	(	PUNCT
ajst-32536	164	31	%	%	INTJ
ajst-32536	164	32	)	)	PUNCT
ajst-32536	165	1	[	[	X
ajst-32536	165	2	17	17	NUM
ajst-32536	165	3	]	]	PUNCT
ajst-32536	165	4	cnn	cnn	PROPN
ajst-32536	165	5	88	88	NUM
ajst-32536	165	6	%	%	NOUN
ajst-32536	166	1	[	[	X
ajst-32536	166	2	18	18	NUM
ajst-32536	166	3	]	]	PUNCT
ajst-32536	166	4	lstm	lstm	NOUN
ajst-32536	166	5	83	83	NUM
ajst-32536	166	6	%	%	NOUN
ajst-32536	167	1	[	[	X
ajst-32536	167	2	19	19	NUM
ajst-32536	167	3	]	]	PUNCT
ajst-32536	167	4	mcnn	mcnn	NOUN
ajst-32536	167	5	85.87	85.87	NUM
ajst-32536	167	6	[	[	X
ajst-32536	167	7	20	20	NUM
ajst-32536	167	8	]	]	PUNCT
ajst-32536	167	9	resnet	resnet	NOUN
ajst-32536	167	10	92.03	92.03	NUM
ajst-32536	167	11	%	%	NOUN
ajst-32536	167	12	[	[	X
ajst-32536	167	13	21	21	NUM
ajst-32536	167	14	]	]	PUNCT
ajst-32536	167	15	transformer	transformer	NOUN
ajst-32536	167	16	83.3	83.3	NUM
ajst-32536	167	17	%	%	NOUN
ajst-32536	167	18	this	this	DET
ajst-32536	167	19	work	work	NOUN
ajst-32536	167	20	drsn	drsn	NOUN
ajst-32536	167	21	92.10	92.10	NUM
ajst-32536	167	22	as	as	SCONJ
ajst-32536	167	23	shown	show	VERB
ajst-32536	167	24	in	in	ADP
ajst-32536	167	25	table	table	NOUN
ajst-32536	167	26	3	3	NUM
ajst-32536	167	27	,	,	PUNCT
ajst-32536	167	28	on	on	ADP
ajst-32536	167	29	the	the	DET
ajst-32536	167	30	parkinson	parkinson	NOUN
ajst-32536	167	31	’s	’s	PART
ajst-32536	167	32	disease	disease	NOUN
ajst-32536	167	33	(	(	PUNCT
ajst-32536	167	34	pd	pd	NOUN
ajst-32536	167	35	)	)	PUNCT
ajst-32536	167	36	neural	neural	ADJ
ajst-32536	167	37	activity	activity	NOUN
ajst-32536	167	38	dataset	dataset	NOUN
ajst-32536	167	39	,	,	PUNCT
ajst-32536	167	40	the	the	DET
ajst-32536	167	41	drsn	drsn	PROPN
ajst-32536	167	42	method	method	NOUN
ajst-32536	167	43	proposed	propose	VERB
ajst-32536	167	44	in	in	ADP
ajst-32536	167	45	this	this	DET
ajst-32536	167	46	study	study	NOUN
ajst-32536	167	47	achieves	achieve	VERB
ajst-32536	167	48	an	an	DET
ajst-32536	167	49	accuracy	accuracy	NOUN
ajst-32536	167	50	of	of	ADP
ajst-32536	167	51	92.10	92.10	NUM
ajst-32536	167	52	%	%	NOUN
ajst-32536	167	53	,	,	PUNCT
ajst-32536	167	54	demonstrating	demonstrate	VERB
ajst-32536	167	55	significant	significant	ADJ
ajst-32536	167	56	advantages	advantage	NOUN
ajst-32536	167	57	over	over	ADP
ajst-32536	167	58	traditional	traditional	ADJ
ajst-32536	167	59	deep	deep	ADJ
ajst-32536	167	60	learning	learning	NOUN
ajst-32536	167	61	approaches	approach	NOUN
ajst-32536	167	62	.	.	PUNCT
ajst-32536	168	1	specifically	specifically	ADV
ajst-32536	168	2	,	,	PUNCT
ajst-32536	168	3	the	the	DET
ajst-32536	168	4	accuracy	accuracy	NOUN
ajst-32536	168	5	of	of	ADP
ajst-32536	168	6	drsn	drsn	NOUN
ajst-32536	168	7	outperforms	outperform	NOUN
ajst-32536	168	8	that	that	PRON
ajst-32536	168	9	of	of	ADP
ajst-32536	168	10	cnn	cnn	PROPN
ajst-32536	168	11	(	(	PUNCT
ajst-32536	168	12	88	88	NUM
ajst-32536	168	13	%	%	NOUN
ajst-32536	168	14	)	)	PUNCT
ajst-32536	168	15	,	,	PUNCT
ajst-32536	168	16	lstm	lstm	NOUN
ajst-32536	168	17	(	(	PUNCT
ajst-32536	168	18	83	83	NUM
ajst-32536	168	19	%	%	NOUN
ajst-32536	168	20	)	)	PUNCT
ajst-32536	168	21	,	,	PUNCT
ajst-32536	168	22	mscnn	mscnn	PROPN
ajst-32536	168	23	(	(	PUNCT
ajst-32536	168	24	85.87	85.87	NUM
ajst-32536	168	25	%	%	NOUN
ajst-32536	168	26	)	)	PUNCT
ajst-32536	168	27	,	,	PUNCT
ajst-32536	168	28	and	and	CCONJ
ajst-32536	168	29	transformer	transformer	NOUN
ajst-32536	168	30	(	(	PUNCT
ajst-32536	168	31	83.3	83.3	NUM
ajst-32536	168	32	%	%	NOUN
ajst-32536	168	33	)	)	PUNCT
ajst-32536	168	34	.	.	PUNCT
ajst-32536	169	1	even	even	ADV
ajst-32536	169	2	when	when	SCONJ
ajst-32536	169	3	compared	compare	VERB
ajst-32536	169	4	with	with	ADP
ajst-32536	169	5	resnet	resnet	NOUN
ajst-32536	169	6	(	(	PUNCT
ajst-32536	169	7	92.03%)—another	92.03%)—another	NUM
ajst-32536	169	8	method	method	NOUN
ajst-32536	169	9	that	that	PRON
ajst-32536	169	10	also	also	ADV
ajst-32536	169	11	leverages	leverage	VERB
ajst-32536	169	12	the	the	DET
ajst-32536	169	13	advantages	advantage	NOUN
ajst-32536	169	14	of	of	ADP
ajst-32536	169	15	deep	deep	ADJ
ajst-32536	169	16	network	network	NOUN
ajst-32536	169	17	architectures	architecture	NOUN
ajst-32536	169	18	—	—	PUNCT
ajst-32536	169	19	the	the	DET
ajst-32536	169	20	marginal	marginal	ADJ
ajst-32536	169	21	improvement	improvement	NOUN
ajst-32536	169	22	in	in	ADP
ajst-32536	169	23	accuracy	accuracy	NOUN
ajst-32536	169	24	still	still	ADV
ajst-32536	169	25	reflects	reflect	VERB
ajst-32536	169	26	drsn	drsn	PROPN
ajst-32536	169	27	’s	’s	PART
ajst-32536	169	28	optimized	optimize	VERB
ajst-32536	169	29	performance	performance	NOUN
ajst-32536	169	30	in	in	ADP
ajst-32536	169	31	feature	feature	NOUN
ajst-32536	169	32	extraction	extraction	NOUN
ajst-32536	169	33	and	and	CCONJ
ajst-32536	169	34	noise	noise	NOUN
ajst-32536	169	35	suppression.this	suppression.this	PRON
ajst-32536	169	36	superiority	superiority	NOUN
ajst-32536	169	37	can	can	AUX
ajst-32536	169	38	be	be	AUX
ajst-32536	169	39	attributed	attribute	VERB
ajst-32536	169	40	to	to	ADP
ajst-32536	169	41	three	three	NUM
ajst-32536	169	42	core	core	NOUN
ajst-32536	169	43	design	design	NOUN
ajst-32536	169	44	features	feature	NOUN
ajst-32536	169	45	of	of	ADP
ajst-32536	169	46	drsn	drsn	PROPN
ajst-32536	169	47	:	:	PUNCT
ajst-32536	169	48	first	first	ADJ
ajst-32536	169	49	,	,	PUNCT
ajst-32536	169	50	residual	residual	ADJ
ajst-32536	169	51	connections	connection	NOUN
ajst-32536	169	52	ensure	ensure	VERB
ajst-32536	169	53	the	the	DET
ajst-32536	169	54	stability	stability	NOUN
ajst-32536	169	55	of	of	ADP
ajst-32536	169	56	deep	deep	ADJ
ajst-32536	169	57	network	network	NOUN
ajst-32536	169	58	training	training	NOUN
ajst-32536	169	59	,	,	PUNCT
ajst-32536	169	60	mitigating	mitigate	VERB
ajst-32536	169	61	37	37	NUM
ajst-32536	169	62	the	the	DET
ajst-32536	169	63	vanishing	vanish	VERB
ajst-32536	169	64	gradient	gradient	NOUN
ajst-32536	169	65	problem	problem	NOUN
ajst-32536	169	66	common	common	ADJ
ajst-32536	169	67	in	in	ADP
ajst-32536	169	68	deep	deep	ADJ
ajst-32536	169	69	models	model	NOUN
ajst-32536	169	70	;	;	PUNCT
ajst-32536	169	71	second	second	X
ajst-32536	169	72	,	,	PUNCT
ajst-32536	169	73	attention	attention	NOUN
ajst-32536	169	74	mechanism	mechanism	NOUN
ajst-32536	169	75	-	-	PUNCT
ajst-32536	169	76	driven	drive	VERB
ajst-32536	169	77	adaptive	adaptive	ADJ
ajst-32536	169	78	denoising	denoising	NOUN
ajst-32536	169	79	effectively	effectively	ADV
ajst-32536	169	80	filters	filter	VERB
ajst-32536	169	81	out	out	ADP
ajst-32536	169	82	irrelevant	irrelevant	ADJ
ajst-32536	169	83	noise	noise	NOUN
ajst-32536	169	84	from	from	ADP
ajst-32536	169	85	eeg	eeg	NOUN
ajst-32536	169	86	signals	signal	NOUN
ajst-32536	169	87	;	;	PUNCT
ajst-32536	169	88	and	and	CCONJ
ajst-32536	169	89	third	third	ADJ
ajst-32536	169	90	,	,	PUNCT
ajst-32536	169	91	multi	multi	ADJ
ajst-32536	169	92	-	-	ADJ
ajst-32536	169	93	scale	scale	ADJ
ajst-32536	169	94	pooling	pooling	NOUN
ajst-32536	169	95	fusion	fusion	NOUN
ajst-32536	169	96	enhances	enhance	VERB
ajst-32536	169	97	the	the	DET
ajst-32536	169	98	representation	representation	NOUN
ajst-32536	169	99	of	of	ADP
ajst-32536	169	100	critical	critical	ADJ
ajst-32536	169	101	discriminative	discriminative	NOUN
ajst-32536	169	102	features	feature	NOUN
ajst-32536	169	103	.	.	PUNCT
ajst-32536	170	1	together	together	ADV
ajst-32536	170	2	,	,	PUNCT
ajst-32536	170	3	these	these	DET
ajst-32536	170	4	components	component	NOUN
ajst-32536	170	5	address	address	VERB
ajst-32536	170	6	the	the	DET
ajst-32536	170	7	inherent	inherent	ADJ
ajst-32536	170	8	limitations	limitation	NOUN
ajst-32536	170	9	of	of	ADP
ajst-32536	170	10	traditional	traditional	ADJ
ajst-32536	170	11	methods	method	NOUN
ajst-32536	170	12	—	—	PUNCT
ajst-32536	170	13	such	such	ADJ
ajst-32536	170	14	as	as	ADP
ajst-32536	170	15	insufficient	insufficient	ADJ
ajst-32536	170	16	feature	feature	NOUN
ajst-32536	170	17	capture	capture	NOUN
ajst-32536	170	18	in	in	ADP
ajst-32536	170	19	noisy	noisy	ADJ
ajst-32536	170	20	eeg	eeg	NOUN
ajst-32536	170	21	signals	signal	NOUN
ajst-32536	170	22	and	and	CCONJ
ajst-32536	170	23	weak	weak	ADJ
ajst-32536	170	24	anti	anti	ADJ
ajst-32536	170	25	-	-	ADJ
ajst-32536	170	26	interference	interference	ADJ
ajst-32536	170	27	capability	capability	NOUN
ajst-32536	170	28	—	—	PUNCT
ajst-32536	170	29	thereby	thereby	ADV
ajst-32536	170	30	further	far	ADV
ajst-32536	170	31	validating	validate	VERB
ajst-32536	170	32	that	that	SCONJ
ajst-32536	170	33	drsn	drsn	NOUN
ajst-32536	170	34	outperforms	outperform	VERB
ajst-32536	170	35	existing	exist	VERB
ajst-32536	170	36	mainstream	mainstream	NOUN
ajst-32536	170	37	deep	deep	ADJ
ajst-32536	170	38	learning	learning	NOUN
ajst-32536	170	39	models	model	NOUN
ajst-32536	170	40	in	in	ADP
ajst-32536	170	41	pd	pd	PROPN
ajst-32536	170	42	detection	detection	NOUN
ajst-32536	170	43	tasks	task	NOUN
ajst-32536	170	44	.	.	PUNCT
ajst-32536	171	1	table	table	NOUN
ajst-32536	171	2	4	4	NUM
ajst-32536	171	3	.	.	PUNCT
ajst-32536	171	4	comparison	comparison	NOUN
ajst-32536	171	5	of	of	ADP
ajst-32536	171	6	accuracy	accuracy	NOUN
ajst-32536	171	7	among	among	ADP
ajst-32536	171	8	various	various	ADJ
ajst-32536	171	9	methods	method	NOUN
ajst-32536	171	10	on	on	ADP
ajst-32536	171	11	the	the	DET
ajst-32536	171	12	unm	unm	PROPN
ajst-32536	171	13	dataset	dataset	PROPN
ajst-32536	171	14	reference	reference	NOUN
ajst-32536	171	15	method	method	NOUN
ajst-32536	171	16	accuracy(%	accuracy(%	VERB
ajst-32536	171	17	)	)	PUNCT
ajst-32536	172	1	[	[	X
ajst-32536	172	2	22	22	NUM
ajst-32536	172	3	]	]	PUNCT
ajst-32536	172	4	mcpnet	mcpnet	NOUN
ajst-32536	172	5	92.5	92.5	NUM
ajst-32536	172	6	%	%	NOUN
ajst-32536	173	1	[	[	X
ajst-32536	173	2	23	23	NUM
ajst-32536	173	3	]	]	X
ajst-32536	173	4	cnn	cnn	PROPN
ajst-32536	173	5	-	-	PUNCT
ajst-32536	173	6	bilstm	bilstm	NOUN
ajst-32536	173	7	97.24	97.24	NUM
ajst-32536	173	8	%	%	NOUN
ajst-32536	173	9	[	[	X
ajst-32536	173	10	24	24	NUM
ajst-32536	173	11	]	]	X
ajst-32536	173	12	gnn	gnn	X
ajst-32536	173	13	69.40	69.40	NUM
ajst-32536	173	14	%	%	NOUN
ajst-32536	174	1	[	[	X
ajst-32536	174	2	25	25	NUM
ajst-32536	174	3	]	]	PUNCT
ajst-32536	174	4	cnn	cnn	PROPN
ajst-32536	174	5	93.10	93.10	NUM
ajst-32536	174	6	%	%	NOUN
ajst-32536	174	7	[	[	X
ajst-32536	174	8	26	26	NUM
ajst-32536	174	9	]	]	PUNCT
ajst-32536	174	10	transformer	transformer	NOUN
ajst-32536	174	11	94	94	NUM
ajst-32536	174	12	%	%	NOUN
ajst-32536	174	13	this	this	DET
ajst-32536	174	14	work	work	NOUN
ajst-32536	174	15	drsn	drsn	VERB
ajst-32536	174	16	98.15	98.15	NUM
ajst-32536	174	17	as	as	SCONJ
ajst-32536	174	18	indicated	indicate	VERB
ajst-32536	174	19	in	in	ADP
ajst-32536	174	20	table	table	NOUN
ajst-32536	174	21	4	4	NUM
ajst-32536	174	22	,	,	PUNCT
ajst-32536	174	23	on	on	ADP
ajst-32536	174	24	the	the	DET
ajst-32536	174	25	unm	unm	PROPN
ajst-32536	174	26	parkinson	parkinson	NOUN
ajst-32536	174	27	’s	’s	PART
ajst-32536	174	28	disease	disease	NOUN
ajst-32536	174	29	(	(	PUNCT
ajst-32536	174	30	pd	pd	NOUN
ajst-32536	174	31	)	)	PUNCT
ajst-32536	174	32	eeg	eeg	PROPN
ajst-32536	174	33	dataset	dataset	NOUN
ajst-32536	174	34	,	,	PUNCT
ajst-32536	174	35	the	the	DET
ajst-32536	174	36	drsn	drsn	PROPN
ajst-32536	174	37	method	method	NOUN
ajst-32536	174	38	proposed	propose	VERB
ajst-32536	174	39	in	in	ADP
ajst-32536	174	40	this	this	DET
ajst-32536	174	41	study	study	NOUN
ajst-32536	174	42	achieves	achieve	VERB
ajst-32536	174	43	an	an	DET
ajst-32536	174	44	accuracy	accuracy	NOUN
ajst-32536	174	45	of	of	ADP
ajst-32536	174	46	98.15	98.15	NUM
ajst-32536	174	47	%	%	NOUN
ajst-32536	174	48	,	,	PUNCT
ajst-32536	174	49	which	which	PRON
ajst-32536	174	50	significantly	significantly	ADV
ajst-32536	174	51	outperforms	outperform	VERB
ajst-32536	174	52	other	other	ADJ
ajst-32536	174	53	comparative	comparative	ADJ
ajst-32536	174	54	methods	method	NOUN
ajst-32536	174	55	,	,	PUNCT
ajst-32536	174	56	demonstrating	demonstrate	VERB
ajst-32536	174	57	robust	robust	ADJ
ajst-32536	174	58	classification	classification	NOUN
ajst-32536	174	59	performance	performance	NOUN
ajst-32536	174	60	and	and	CCONJ
ajst-32536	174	61	strong	strong	ADJ
ajst-32536	174	62	environmental	environmental	ADJ
ajst-32536	174	63	adaptability	adaptability	NOUN
ajst-32536	174	64	.	.	PUNCT
ajst-32536	175	1	specifically	specifically	ADV
ajst-32536	175	2	,	,	PUNCT
ajst-32536	175	3	the	the	DET
ajst-32536	175	4	accuracy	accuracy	NOUN
ajst-32536	175	5	of	of	ADP
ajst-32536	175	6	drsn	drsn	NOUN
ajst-32536	175	7	not	not	PART
ajst-32536	175	8	only	only	ADV
ajst-32536	175	9	far	far	ADV
ajst-32536	175	10	surpasses	surpasse	NOUN
ajst-32536	175	11	that	that	PRON
ajst-32536	175	12	of	of	ADP
ajst-32536	175	13	models	model	NOUN
ajst-32536	175	14	with	with	ADP
ajst-32536	175	15	inherent	inherent	ADJ
ajst-32536	175	16	limitations	limitation	NOUN
ajst-32536	175	17	in	in	ADP
ajst-32536	175	18	graph	graph	NOUN
ajst-32536	175	19	-	-	PUNCT
ajst-32536	175	20	structured	structure	VERB
ajst-32536	175	21	data	datum	NOUN
ajst-32536	175	22	processing	processing	NOUN
ajst-32536	175	23	—	—	PUNCT
ajst-32536	175	24	such	such	ADJ
ajst-32536	175	25	as	as	ADP
ajst-32536	175	26	graph	graph	NOUN
ajst-32536	175	27	neural	neural	ADJ
ajst-32536	175	28	network	network	NOUN
ajst-32536	175	29	(	(	PUNCT
ajst-32536	175	30	gnn	gnn	PROPN
ajst-32536	175	31	)	)	PUNCT
ajst-32536	175	32	,	,	PUNCT
ajst-32536	175	33	which	which	PRON
ajst-32536	175	34	yields	yield	VERB
ajst-32536	175	35	an	an	DET
ajst-32536	175	36	accuracy	accuracy	NOUN
ajst-32536	175	37	of	of	ADP
ajst-32536	175	38	69.40	69.40	NUM
ajst-32536	175	39	—	—	PUNCT
ajst-32536	175	40	but	but	CCONJ
ajst-32536	175	41	also	also	ADV
ajst-32536	175	42	exceeds	exceed	VERB
ajst-32536	175	43	that	that	PRON
ajst-32536	175	44	of	of	ADP
ajst-32536	175	45	methods	method	NOUN
ajst-32536	175	46	optimized	optimize	VERB
ajst-32536	175	47	for	for	ADP
ajst-32536	175	48	eeg	eeg	NOUN
ajst-32536	175	49	signal	signal	NOUN
ajst-32536	175	50	analysis	analysis	NOUN
ajst-32536	175	51	,	,	PUNCT
ajst-32536	175	52	including	include	VERB
ajst-32536	175	53	traditional	traditional	ADJ
ajst-32536	175	54	convolutional	convolutional	ADJ
ajst-32536	175	55	neural	neural	ADJ
ajst-32536	175	56	network	network	NOUN
ajst-32536	175	57	(	(	PUNCT
ajst-32536	175	58	cnn	cnn	PROPN
ajst-32536	175	59	,	,	PUNCT
ajst-32536	175	60	93.10	93.10	NUM
ajst-32536	175	61	%	%	NOUN
ajst-32536	175	62	)	)	PUNCT
ajst-32536	175	63	,	,	PUNCT
ajst-32536	175	64	transformer	transformer	NOUN
ajst-32536	175	65	(	(	PUNCT
ajst-32536	175	66	94	94	NUM
ajst-32536	175	67	%	%	NOUN
ajst-32536	175	68	)	)	PUNCT
ajst-32536	175	69	,	,	PUNCT
ajst-32536	175	70	and	and	CCONJ
ajst-32536	175	71	mcpnet	mcpnet	NOUN
ajst-32536	175	72	(	(	PUNCT
ajst-32536	175	73	92.5	92.5	NUM
ajst-32536	175	74	%	%	NOUN
ajst-32536	175	75	)	)	PUNCT
ajst-32536	175	76	.	.	PUNCT
ajst-32536	176	1	even	even	ADV
ajst-32536	176	2	when	when	SCONJ
ajst-32536	176	3	compared	compare	VERB
ajst-32536	176	4	with	with	ADP
ajst-32536	176	5	the	the	DET
ajst-32536	176	6	relatively	relatively	ADV
ajst-32536	176	7	high	high	ADJ
ajst-32536	176	8	-	-	PUNCT
ajst-32536	176	9	performance	performance	NOUN
ajst-32536	176	10	cnn	cnn	NOUN
ajst-32536	176	11	-	-	NOUN
ajst-32536	176	12	bilstm	bilstm	NOUN
ajst-32536	176	13	(	(	PUNCT
ajst-32536	176	14	97.24	97.24	NUM
ajst-32536	176	15	%	%	NOUN
ajst-32536	176	16	)	)	PUNCT
ajst-32536	176	17	,	,	PUNCT
ajst-32536	176	18	drsn	drsn	PROPN
ajst-32536	176	19	still	still	ADV
ajst-32536	176	20	achieves	achieve	VERB
ajst-32536	176	21	an	an	DET
ajst-32536	176	22	improvement	improvement	NOUN
ajst-32536	176	23	of	of	ADP
ajst-32536	176	24	nearly	nearly	ADV
ajst-32536	176	25	1	1	NUM
ajst-32536	176	26	percentage	percentage	NOUN
ajst-32536	176	27	point.the	point.the	DET
ajst-32536	176	28	core	core	NOUN
ajst-32536	176	29	driver	driver	NOUN
ajst-32536	176	30	of	of	ADP
ajst-32536	176	31	this	this	DET
ajst-32536	176	32	superiority	superiority	NOUN
ajst-32536	176	33	lies	lie	VERB
ajst-32536	176	34	in	in	ADP
ajst-32536	176	35	the	the	DET
ajst-32536	176	36	unique	unique	ADJ
ajst-32536	176	37	characteristics	characteristic	NOUN
ajst-32536	176	38	of	of	ADP
ajst-32536	176	39	the	the	DET
ajst-32536	176	40	unm	unm	PROPN
ajst-32536	176	41	dataset	dataset	NOUN
ajst-32536	176	42	:	:	PUNCT
ajst-32536	176	43	it	it	PRON
ajst-32536	176	44	includes	include	VERB
ajst-32536	176	45	data	datum	NOUN
ajst-32536	176	46	from	from	ADP
ajst-32536	176	47	pd	pd	PROPN
ajst-32536	176	48	patients	patient	NOUN
ajst-32536	176	49	in	in	ADP
ajst-32536	176	50	both	both	CCONJ
ajst-32536	176	51	medicated	medicated	ADJ
ajst-32536	176	52	and	and	CCONJ
ajst-32536	176	53	unmedicated	unmedicated	ADJ
ajst-32536	176	54	states	state	NOUN
ajst-32536	176	55	as	as	ADV
ajst-32536	176	56	well	well	ADV
ajst-32536	176	57	as	as	ADP
ajst-32536	176	58	from	from	ADP
ajst-32536	176	59	healthy	healthy	ADJ
ajst-32536	176	60	controls	control	NOUN
ajst-32536	176	61	,	,	PUNCT
ajst-32536	176	62	while	while	SCONJ
ajst-32536	176	63	also	also	ADV
ajst-32536	176	64	suffering	suffer	VERB
ajst-32536	176	65	from	from	ADP
ajst-32536	176	66	missing	miss	VERB
ajst-32536	176	67	data	datum	NOUN
ajst-32536	176	68	in	in	ADP
ajst-32536	176	69	the	the	DET
ajst-32536	176	70	cpz	cpz	PROPN
ajst-32536	176	71	channel	channel	NOUN
ajst-32536	176	72	.	.	PUNCT
ajst-32536	177	1	in	in	ADP
ajst-32536	177	2	response	response	NOUN
ajst-32536	177	3	to	to	ADP
ajst-32536	177	4	these	these	DET
ajst-32536	177	5	challenges	challenge	NOUN
ajst-32536	177	6	,	,	PUNCT
ajst-32536	177	7	drsn	drsn	NOUN
ajst-32536	177	8	leverages	leverage	VERB
ajst-32536	177	9	a	a	DET
ajst-32536	177	10	pooling	pool	VERB
ajst-32536	177	11	fusion	fusion	NOUN
ajst-32536	177	12	strategy	strategy	NOUN
ajst-32536	177	13	to	to	PART
ajst-32536	177	14	fully	fully	ADV
ajst-32536	177	15	integrate	integrate	VERB
ajst-32536	177	16	global	global	ADJ
ajst-32536	177	17	distribution	distribution	NOUN
ajst-32536	177	18	information	information	NOUN
ajst-32536	177	19	and	and	CCONJ
ajst-32536	177	20	local	local	ADJ
ajst-32536	177	21	extreme	extreme	ADJ
ajst-32536	177	22	value	value	NOUN
ajst-32536	177	23	information	information	NOUN
ajst-32536	177	24	of	of	ADP
ajst-32536	177	25	features	feature	NOUN
ajst-32536	177	26	.	.	PUNCT
ajst-32536	178	1	complemented	complement	VERB
ajst-32536	178	2	by	by	ADP
ajst-32536	178	3	an	an	DET
ajst-32536	178	4	attention	attention	NOUN
ajst-32536	178	5	mechanism	mechanism	NOUN
ajst-32536	178	6	that	that	PRON
ajst-32536	178	7	adaptively	adaptively	ADV
ajst-32536	178	8	enhances	enhance	VERB
ajst-32536	178	9	features	feature	NOUN
ajst-32536	178	10	from	from	ADP
ajst-32536	178	11	key	key	ADJ
ajst-32536	178	12	channels	channel	NOUN
ajst-32536	178	13	,	,	PUNCT
ajst-32536	178	14	drsn	drsn	VERB
ajst-32536	178	15	effectively	effectively	ADV
ajst-32536	178	16	mitigates	mitigate	NOUN
ajst-32536	178	17	interference	interference	NOUN
ajst-32536	178	18	caused	cause	VERB
ajst-32536	178	19	by	by	ADP
ajst-32536	178	20	data	datum	NOUN
ajst-32536	178	21	incompleteness	incompleteness	NOUN
ajst-32536	178	22	and	and	CCONJ
ajst-32536	178	23	state	state	NOUN
ajst-32536	178	24	variability	variability	NOUN
ajst-32536	178	25	.	.	PUNCT
ajst-32536	179	1	meanwhile	meanwhile	ADV
ajst-32536	179	2	,	,	PUNCT
ajst-32536	179	3	its	its	PRON
ajst-32536	179	4	residual	residual	ADJ
ajst-32536	179	5	shrinkage	shrinkage	NOUN
ajst-32536	179	6	structure	structure	NOUN
ajst-32536	179	7	suppresses	suppress	VERB
ajst-32536	179	8	the	the	DET
ajst-32536	179	9	impact	impact	NOUN
ajst-32536	179	10	of	of	ADP
ajst-32536	179	11	noise	noise	NOUN
ajst-32536	179	12	on	on	ADP
ajst-32536	179	13	feature	feature	NOUN
ajst-32536	179	14	extraction	extraction	NOUN
ajst-32536	179	15	.	.	PUNCT
ajst-32536	180	1	collectively	collectively	ADV
ajst-32536	180	2	,	,	PUNCT
ajst-32536	180	3	these	these	DET
ajst-32536	180	4	design	design	NOUN
ajst-32536	180	5	elements	element	NOUN
ajst-32536	180	6	enable	enable	VERB
ajst-32536	180	7	drsn	drsn	NOUN
ajst-32536	180	8	to	to	PART
ajst-32536	180	9	achieve	achieve	VERB
ajst-32536	180	10	more	more	ADV
ajst-32536	180	11	stable	stable	ADJ
ajst-32536	180	12	and	and	CCONJ
ajst-32536	180	13	accurate	accurate	ADJ
ajst-32536	180	14	pd	pd	NOUN
ajst-32536	180	15	detection	detection	NOUN
ajst-32536	180	16	results	result	NOUN
ajst-32536	180	17	than	than	ADP
ajst-32536	180	18	existing	exist	VERB
ajst-32536	180	19	mainstream	mainstream	NOUN
ajst-32536	180	20	models	model	NOUN
ajst-32536	180	21	in	in	ADP
ajst-32536	180	22	complex	complex	ADJ
ajst-32536	180	23	data	datum	NOUN
ajst-32536	180	24	scenarios	scenario	NOUN
ajst-32536	180	25	.	.	PUNCT
ajst-32536	181	1	5.2	5.2	NUM
ajst-32536	181	2	research	research	NOUN
ajst-32536	181	3	limitations	limitation	NOUN
ajst-32536	181	4	and	and	CCONJ
ajst-32536	181	5	future	future	ADJ
ajst-32536	181	6	improvement	improvement	NOUN
ajst-32536	181	7	directions	direction	NOUN
ajst-32536	181	8	despite	despite	SCONJ
ajst-32536	181	9	the	the	DET
ajst-32536	181	10	superior	superior	ADJ
ajst-32536	181	11	performance	performance	NOUN
ajst-32536	181	12	of	of	ADP
ajst-32536	181	13	drsn	drsn	NOUN
ajst-32536	181	14	on	on	ADP
ajst-32536	181	15	the	the	DET
ajst-32536	181	16	new	new	PROPN
ajst-32536	181	17	mexico	mexico	PROPN
ajst-32536	181	18	dataset	dataset	VERB
ajst-32536	181	19	and	and	CCONJ
ajst-32536	181	20	the	the	DET
ajst-32536	181	21	parkinson	parkinson	NOUN
ajst-32536	181	22	’s	’s	PART
ajst-32536	181	23	disease	disease	NOUN
ajst-32536	181	24	(	(	PUNCT
ajst-32536	181	25	pd	pd	NOUN
ajst-32536	181	26	)	)	PUNCT
ajst-32536	181	27	neural	neural	ADJ
ajst-32536	181	28	activity	activity	NOUN
ajst-32536	181	29	dataset	dataset	NOUN
ajst-32536	181	30	,	,	PUNCT
ajst-32536	181	31	the	the	DET
ajst-32536	181	32	current	current	ADJ
ajst-32536	181	33	study	study	NOUN
ajst-32536	181	34	has	have	VERB
ajst-32536	181	35	a	a	DET
ajst-32536	181	36	notable	notable	ADJ
ajst-32536	181	37	limitation	limitation	NOUN
ajst-32536	181	38	:	:	PUNCT
ajst-32536	181	39	it	it	PRON
ajst-32536	181	40	focuses	focus	VERB
ajst-32536	181	41	solely	solely	ADV
ajst-32536	181	42	on	on	ADP
ajst-32536	181	43	the	the	DET
ajst-32536	181	44	association	association	NOUN
ajst-32536	181	45	between	between	ADP
ajst-32536	181	46	neuroelectric	neuroelectric	ADJ
ajst-32536	181	47	activity	activity	NOUN
ajst-32536	181	48	features	feature	NOUN
ajst-32536	181	49	and	and	CCONJ
ajst-32536	181	50	disease	disease	NOUN
ajst-32536	181	51	states	state	NOUN
ajst-32536	181	52	,	,	PUNCT
ajst-32536	181	53	without	without	ADP
ajst-32536	181	54	delving	delve	VERB
ajst-32536	181	55	into	into	ADP
ajst-32536	181	56	the	the	DET
ajst-32536	181	57	dynamic	dynamic	ADJ
ajst-32536	181	58	relationship	relationship	NOUN
ajst-32536	181	59	between	between	ADP
ajst-32536	181	60	these	these	DET
ajst-32536	181	61	features	feature	NOUN
ajst-32536	181	62	and	and	CCONJ
ajst-32536	181	63	disease	disease	NOUN
ajst-32536	181	64	progression	progression	NOUN
ajst-32536	181	65	.	.	PUNCT
ajst-32536	182	1	in	in	ADP
ajst-32536	182	2	future	future	ADJ
ajst-32536	182	3	research	research	NOUN
ajst-32536	182	4	,	,	PUNCT
ajst-32536	182	5	longitudinal	longitudinal	ADJ
ajst-32536	182	6	follow	follow	NOUN
ajst-32536	182	7	-	-	PUNCT
ajst-32536	182	8	up	up	ADP
ajst-32536	182	9	data	datum	NOUN
ajst-32536	182	10	could	could	AUX
ajst-32536	182	11	be	be	AUX
ajst-32536	182	12	integrated	integrate	VERB
ajst-32536	182	13	to	to	PART
ajst-32536	182	14	construct	construct	VERB
ajst-32536	182	15	a	a	DET
ajst-32536	182	16	"	"	PUNCT
ajst-32536	182	17	feature	feature	NOUN
ajst-32536	182	18	-	-	PUNCT
ajst-32536	182	19	disease	disease	NOUN
ajst-32536	182	20	progression	progression	NOUN
ajst-32536	182	21	"	"	PUNCT
ajst-32536	182	22	prediction	prediction	NOUN
ajst-32536	182	23	model	model	NOUN
ajst-32536	182	24	.	.	PUNCT
ajst-32536	183	1	this	this	DET
ajst-32536	183	2	enhancement	enhancement	NOUN
ajst-32536	183	3	would	would	AUX
ajst-32536	183	4	enable	enable	VERB
ajst-32536	183	5	drsn	drsn	NOUN
ajst-32536	183	6	to	to	PART
ajst-32536	183	7	not	not	PART
ajst-32536	183	8	only	only	ADV
ajst-32536	183	9	achieve	achieve	VERB
ajst-32536	183	10	accurate	accurate	ADJ
ajst-32536	183	11	pd	pd	NOUN
ajst-32536	183	12	detection	detection	NOUN
ajst-32536	183	13	but	but	CCONJ
ajst-32536	183	14	also	also	ADV
ajst-32536	183	15	provide	provide	VERB
ajst-32536	183	16	support	support	NOUN
ajst-32536	183	17	for	for	ADP
ajst-32536	183	18	evaluating	evaluate	VERB
ajst-32536	183	19	disease	disease	NOUN
ajst-32536	183	20	progression	progression	NOUN
ajst-32536	183	21	—	—	PUNCT
ajst-32536	183	22	thereby	thereby	ADV
ajst-32536	183	23	further	far	ADV
ajst-32536	183	24	expanding	expand	VERB
ajst-32536	183	25	its	its	PRON
ajst-32536	183	26	clinical	clinical	ADJ
ajst-32536	183	27	application	application	NOUN
ajst-32536	183	28	value	value	NOUN
ajst-32536	183	29	.	.	PUNCT
ajst-32536	184	1	6	6	X
ajst-32536	184	2	.	.	X
ajst-32536	184	3	conclusion	conclusion	NOUN
ajst-32536	184	4	to	to	PART
ajst-32536	184	5	address	address	VERB
ajst-32536	184	6	the	the	DET
ajst-32536	184	7	early	early	ADJ
ajst-32536	184	8	detection	detection	NOUN
ajst-32536	184	9	and	and	CCONJ
ajst-32536	184	10	classification	classification	NOUN
ajst-32536	184	11	of	of	ADP
ajst-32536	184	12	parkinson	parkinson	NOUN
ajst-32536	184	13	’s	’s	PART
ajst-32536	184	14	disease	disease	NOUN
ajst-32536	184	15	(	(	PUNCT
ajst-32536	184	16	pd	pd	PROPN
ajst-32536	184	17	)	)	PUNCT
ajst-32536	184	18	,	,	PUNCT
ajst-32536	184	19	this	this	DET
ajst-32536	184	20	study	study	NOUN
ajst-32536	184	21	proposes	propose	VERB
ajst-32536	184	22	a	a	DET
ajst-32536	184	23	drsn	drsn	NOUN
ajst-32536	184	24	method	method	NOUN
ajst-32536	184	25	based	base	VERB
ajst-32536	184	26	on	on	ADP
ajst-32536	184	27	pooling	pool	VERB
ajst-32536	184	28	fusion	fusion	NOUN
ajst-32536	184	29	.	.	PUNCT
ajst-32536	185	1	by	by	ADP
ajst-32536	185	2	integrating	integrate	VERB
ajst-32536	185	3	average	average	ADJ
ajst-32536	185	4	pooling	pooling	NOUN
ajst-32536	185	5	and	and	CCONJ
ajst-32536	185	6	max	max	PROPN
ajst-32536	185	7	pooling	pooling	NOUN
ajst-32536	185	8	strategies	strategy	NOUN
ajst-32536	185	9	,	,	PUNCT
ajst-32536	185	10	this	this	DET
ajst-32536	185	11	method	method	NOUN
ajst-32536	185	12	exhibits	exhibit	VERB
ajst-32536	185	13	significant	significant	ADJ
ajst-32536	185	14	advantages	advantage	NOUN
ajst-32536	185	15	in	in	ADP
ajst-32536	185	16	multi	multi	ADJ
ajst-32536	185	17	-	-	ADJ
ajst-32536	185	18	scale	scale	ADJ
ajst-32536	185	19	feature	feature	NOUN
ajst-32536	185	20	extraction	extraction	NOUN
ajst-32536	185	21	and	and	CCONJ
ajst-32536	185	22	noise	noise	NOUN
ajst-32536	185	23	suppression	suppression	NOUN
ajst-32536	185	24	,	,	PUNCT
ajst-32536	185	25	effectively	effectively	ADV
ajst-32536	185	26	enhancing	enhance	VERB
ajst-32536	185	27	the	the	DET
ajst-32536	185	28	model	model	NOUN
ajst-32536	185	29	’s	’s	PART
ajst-32536	185	30	classification	classification	NOUN
ajst-32536	185	31	performance	performance	NOUN
ajst-32536	185	32	in	in	ADP
ajst-32536	185	33	real	real	ADJ
ajst-32536	185	34	-	-	PUNCT
ajst-32536	185	35	world	world	NOUN
ajst-32536	185	36	noisy	noisy	ADJ
ajst-32536	185	37	environments	environment	NOUN
ajst-32536	185	38	.	.	PUNCT
ajst-32536	186	1	experimental	experimental	ADJ
ajst-32536	186	2	results	result	NOUN
ajst-32536	186	3	on	on	ADP
ajst-32536	186	4	the	the	DET
ajst-32536	186	5	pd	pd	PROPN
ajst-32536	186	6	neural	neural	ADJ
ajst-32536	186	7	activity	activity	NOUN
ajst-32536	186	8	dataset	dataset	NOUN
ajst-32536	186	9	and	and	CCONJ
ajst-32536	186	10	the	the	DET
ajst-32536	186	11	unm	unm	PROPN
ajst-32536	186	12	pd	pd	PROPN
ajst-32536	186	13	eeg	eeg	PROPN
ajst-32536	186	14	dataset	dataset	NOUN
ajst-32536	186	15	demonstrate	demonstrate	VERB
ajst-32536	186	16	38	38	NUM
ajst-32536	186	17	that	that	PRON
ajst-32536	186	18	drsn	drsn	PROPN
ajst-32536	186	19	achieves	achieve	VERB
ajst-32536	186	20	an	an	DET
ajst-32536	186	21	accuracy	accuracy	NOUN
ajst-32536	186	22	of	of	ADP
ajst-32536	186	23	92.10	92.10	NUM
ajst-32536	186	24	%	%	NOUN
ajst-32536	186	25	and	and	CCONJ
ajst-32536	186	26	98.15	98.15	NUM
ajst-32536	186	27	%	%	NOUN
ajst-32536	186	28	,	,	PUNCT
ajst-32536	186	29	respectively	respectively	ADV
ajst-32536	186	30	.	.	PUNCT
ajst-32536	187	1	meanwhile	meanwhile	ADV
ajst-32536	187	2	,	,	PUNCT
ajst-32536	187	3	its	its	PRON
ajst-32536	187	4	precision	precision	NOUN
ajst-32536	187	5	,	,	PUNCT
ajst-32536	187	6	recall	recall	NOUN
ajst-32536	187	7	,	,	PUNCT
ajst-32536	187	8	and	and	CCONJ
ajst-32536	187	9	f1	f1	NOUN
ajst-32536	187	10	score	score	NOUN
ajst-32536	187	11	all	all	PRON
ajst-32536	187	12	remain	remain	VERB
ajst-32536	187	13	at	at	ADP
ajst-32536	187	14	relatively	relatively	ADV
ajst-32536	187	15	high	high	ADJ
ajst-32536	187	16	levels	level	NOUN
ajst-32536	187	17	—	—	PUNCT
ajst-32536	187	18	these	these	DET
ajst-32536	187	19	outcomes	outcome	NOUN
ajst-32536	187	20	validate	validate	VERB
ajst-32536	187	21	that	that	SCONJ
ajst-32536	187	22	the	the	DET
ajst-32536	187	23	model	model	NOUN
ajst-32536	187	24	possesses	possess	VERB
ajst-32536	187	25	excellent	excellent	ADJ
ajst-32536	187	26	classification	classification	NOUN
ajst-32536	187	27	consistency	consistency	NOUN
ajst-32536	187	28	,	,	PUNCT
ajst-32536	187	29	robustness	robustness	NOUN
ajst-32536	187	30	,	,	PUNCT
ajst-32536	187	31	and	and	CCONJ
ajst-32536	187	32	generalization	generalization	NOUN
ajst-32536	187	33	capability	capability	NOUN
ajst-32536	187	34	across	across	ADP
ajst-32536	187	35	datasets	dataset	NOUN
ajst-32536	187	36	of	of	ADP
ajst-32536	187	37	different	different	ADJ
ajst-32536	187	38	origins	origin	NOUN
ajst-32536	187	39	and	and	CCONJ
ajst-32536	187	40	under	under	ADP
ajst-32536	187	41	varying	vary	VERB
ajst-32536	187	42	signal	signal	NOUN
ajst-32536	187	43	-	-	PUNCT
ajst-32536	187	44	to	to	ADP
ajst-32536	187	45	-	-	PUNCT
ajst-32536	187	46	noise	noise	NOUN
ajst-32536	187	47	ratio	ratio	NOUN
ajst-32536	187	48	(	(	PUNCT
ajst-32536	187	49	snr	snr	NOUN
ajst-32536	187	50	)	)	PUNCT
ajst-32536	187	51	conditions	condition	NOUN
ajst-32536	187	52	.	.	PUNCT
ajst-32536	188	1	this	this	DET
ajst-32536	188	2	study	study	NOUN
ajst-32536	188	3	not	not	PART
ajst-32536	188	4	only	only	ADV
ajst-32536	188	5	provides	provide	VERB
ajst-32536	188	6	a	a	DET
ajst-32536	188	7	new	new	ADJ
ajst-32536	188	8	and	and	CCONJ
ajst-32536	188	9	effective	effective	ADJ
ajst-32536	188	10	tool	tool	NOUN
ajst-32536	188	11	for	for	ADP
ajst-32536	188	12	the	the	DET
ajst-32536	188	13	auxiliary	auxiliary	ADJ
ajst-32536	188	14	diagnosis	diagnosis	NOUN
ajst-32536	188	15	of	of	ADP
ajst-32536	188	16	pd	pd	PROPN
ajst-32536	188	17	but	but	CCONJ
ajst-32536	188	18	also	also	ADV
ajst-32536	188	19	offers	offer	VERB
ajst-32536	188	20	a	a	DET
ajst-32536	188	21	referable	referable	ADJ
ajst-32536	188	22	deep	deep	ADJ
ajst-32536	188	23	learning	learning	NOUN
ajst-32536	188	24	model	model	NOUN
ajst-32536	188	25	design	design	NOUN
ajst-32536	188	26	framework	framework	NOUN
ajst-32536	188	27	for	for	ADP
ajst-32536	188	28	the	the	DET
ajst-32536	188	29	detection	detection	NOUN
ajst-32536	188	30	of	of	ADP
ajst-32536	188	31	neurological	neurological	ADJ
ajst-32536	188	32	diseases	disease	NOUN
ajst-32536	188	33	based	base	VERB
ajst-32536	188	34	on	on	ADP
ajst-32536	188	35	eeg	eeg	NOUN
ajst-32536	188	36	signals	signal	NOUN
ajst-32536	188	37	.	.	PUNCT
ajst-32536	189	1	consequently	consequently	ADV
ajst-32536	189	2	,	,	PUNCT
ajst-32536	189	3	it	it	PRON
ajst-32536	189	4	holds	hold	VERB
ajst-32536	189	5	considerable	considerable	ADJ
ajst-32536	189	6	potential	potential	NOUN
ajst-32536	189	7	for	for	ADP
ajst-32536	189	8	clinical	clinical	ADJ
ajst-32536	189	9	translation	translation	NOUN
ajst-32536	189	10	and	and	CCONJ
ajst-32536	189	11	high	high	ADJ
ajst-32536	189	12	application	application	NOUN
ajst-32536	189	13	value	value	NOUN
ajst-32536	189	14	.	.	PUNCT
ajst-32536	190	1	references	reference	NOUN
ajst-32536	190	2	[	[	X
ajst-32536	190	3	1	1	X
ajst-32536	190	4	]	]	PUNCT
ajst-32536	190	5	clarke	clarke	PROPN
ajst-32536	190	6	c	c	PROPN
ajst-32536	190	7	e.	e.	PROPN
ajst-32536	190	8	parkinson	parkinson	PROPN
ajst-32536	190	9	's	's	PART
ajst-32536	190	10	disease[j	disease[j	NOUN
ajst-32536	190	11	]	]	PUNCT
ajst-32536	190	12	.	.	PUNCT
ajst-32536	191	1	bmj	bmj	PROPN
ajst-32536	191	2	,	,	PUNCT
ajst-32536	191	3	2007	2007	NUM
ajst-32536	191	4	,	,	PUNCT
ajst-32536	191	5	335(7617	335(7617	NUM
ajst-32536	191	6	):	):	PUNCT
ajst-32536	191	7	441	441	NUM
ajst-32536	191	8	-	-	SYM
ajst-32536	191	9	445	445	NUM
ajst-32536	191	10	.	.	PUNCT
ajst-32536	192	1	[	[	X
ajst-32536	192	2	2	2	NUM
ajst-32536	192	3	]	]	X
ajst-32536	192	4	jankovic	jankovic	PROPN
ajst-32536	192	5	j.	j.	PROPN
ajst-32536	192	6	parkinson	parkinson	PROPN
ajst-32536	192	7	’s	’s	PART
ajst-32536	192	8	disease	disease	NOUN
ajst-32536	192	9	:	:	PUNCT
ajst-32536	192	10	clinical	clinical	ADJ
ajst-32536	192	11	features	feature	NOUN
ajst-32536	192	12	and	and	CCONJ
ajst-32536	192	13	diagnosis[j	diagnosis[j	NOUN
ajst-32536	192	14	]	]	PUNCT
ajst-32536	192	15	.	.	PUNCT
ajst-32536	193	1	journal	journal	PROPN
ajst-32536	193	2	of	of	ADP
ajst-32536	193	3	neurology	neurology	NOUN
ajst-32536	193	4	,	,	PUNCT
ajst-32536	193	5	neurosurgery	neurosurgery	NOUN
ajst-32536	193	6	&	&	CCONJ
ajst-32536	193	7	psychiatry	psychiatry	NOUN
ajst-32536	193	8	,	,	PUNCT
ajst-32536	193	9	2008	2008	NUM
ajst-32536	193	10	,	,	PUNCT
ajst-32536	193	11	79(4	79(4	NOUN
ajst-32536	193	12	):	):	PUNCT
ajst-32536	193	13	368	368	NUM
ajst-32536	193	14	-	-	SYM
ajst-32536	193	15	376	376	NUM
ajst-32536	193	16	.	.	PUNCT
ajst-32536	194	1	[	[	X
ajst-32536	194	2	3	3	X
ajst-32536	194	3	]	]	PUNCT
ajst-32536	194	4	akdemir	akdemir	NOUN
ajst-32536	194	5	ü	ü	PROPN
ajst-32536	194	6	ö	ö	PROPN
ajst-32536	194	7	,	,	PUNCT
ajst-32536	194	8	bora	bora	PROPN
ajst-32536	194	9	h	h	PROPN
ajst-32536	194	10	a	a	DET
ajst-32536	194	11	t	t	PROPN
ajst-32536	194	12	,	,	PUNCT
ajst-32536	194	13	atay	atay	NOUN
ajst-32536	194	14	l	l	PROPN
ajst-32536	194	15	ö.	ö.	PROPN
ajst-32536	194	16	dopamine	dopamine	NOUN
ajst-32536	194	17	transporter	transporter	NOUN
ajst-32536	194	18	spect	spect	NOUN
ajst-32536	194	19	imaging	imaging	NOUN
ajst-32536	194	20	in	in	ADP
ajst-32536	194	21	parkinson	parkinson	NOUN
ajst-32536	194	22	's	's	PART
ajst-32536	194	23	disease	disease	NOUN
ajst-32536	194	24	and	and	CCONJ
ajst-32536	194	25	parkinsoniandisorders[j	parkinsoniandisorders[j	NOUN
ajst-32536	194	26	]	]	PUNCT
ajst-32536	194	27	.	.	PUNCT
ajst-32536	195	1	turkish	turkish	ADJ
ajst-32536	195	2	journal	journal	PROPN
ajst-32536	195	3	of	of	ADP
ajst-32536	195	4	medical	medical	ADJ
ajst-32536	195	5	sciences	science	NOUN
ajst-32536	195	6	,	,	PUNCT
ajst-32536	195	7	2021	2021	NUM
ajst-32536	195	8	,	,	PUNCT
ajst-32536	195	9	51(2	51(2	NUM
ajst-32536	195	10	):	):	PUNCT
ajst-32536	195	11	400	400	NUM
ajst-32536	195	12	-	-	SYM
ajst-32536	195	13	410	410	NUM
ajst-32536	195	14	.	.	PUNCT
ajst-32536	196	1	[	[	X
ajst-32536	196	2	4	4	X
ajst-32536	196	3	]	]	X
ajst-32536	196	4	brooks	brooks	PROPN
ajst-32536	196	5	d	d	PROPN
ajst-32536	196	6	j	j	PROPN
ajst-32536	196	7	,	,	PUNCT
ajst-32536	196	8	frey	frey	PROPN
ajst-32536	196	9	k	k	PROPN
ajst-32536	196	10	a	a	PROPN
ajst-32536	196	11	,	,	PUNCT
ajst-32536	196	12	marek	marek	PROPN
ajst-32536	196	13	k	k	PROPN
ajst-32536	196	14	l	l	PROPN
ajst-32536	196	15	,	,	PUNCT
ajst-32536	196	16	et	et	PROPN
ajst-32536	196	17	al	al	PROPN
ajst-32536	196	18	.	.	PROPN
ajst-32536	196	19	assessment	assessment	NOUN
ajst-32536	196	20	of	of	ADP
ajst-32536	196	21	neuroimaging	neuroimage	VERB
ajst-32536	196	22	techniques	technique	NOUN
ajst-32536	196	23	as	as	ADP
ajst-32536	196	24	biomarkers	biomarker	NOUN
ajst-32536	196	25	of	of	ADP
ajst-32536	196	26	the	the	DET
ajst-32536	196	27	progression	progression	NOUN
ajst-32536	196	28	of	of	ADP
ajst-32536	196	29	parkinson	parkinson	NOUN
ajst-32536	196	30	's	's	PART
ajst-32536	196	31	disease[j	disease[j	NOUN
ajst-32536	196	32	]	]	PUNCT
ajst-32536	196	33	.	.	PUNCT
ajst-32536	196	34	experimental	experimental	ADJ
ajst-32536	196	35	neurology	neurology	NOUN
ajst-32536	196	36	,	,	PUNCT
ajst-32536	196	37	2003	2003	NUM
ajst-32536	196	38	,	,	PUNCT
ajst-32536	196	39	184	184	NUM
ajst-32536	196	40	:	:	SYM
ajst-32536	196	41	68	68	NUM
ajst-32536	196	42	-	-	SYM
ajst-32536	196	43	79	79	NUM
ajst-32536	196	44	.	.	PUNCT
ajst-32536	197	1	[	[	X
ajst-32536	197	2	5	5	X
ajst-32536	197	3	]	]	PUNCT
ajst-32536	197	4	göker	göker	PROPN
ajst-32536	197	5	h.	h.	PROPN
ajst-32536	197	6	automatic	automatic	ADJ
ajst-32536	197	7	detection	detection	NOUN
ajst-32536	197	8	of	of	ADP
ajst-32536	197	9	parkinson	parkinson	NOUN
ajst-32536	197	10	’s	’s	PART
ajst-32536	197	11	disease	disease	NOUN
ajst-32536	197	12	from	from	ADP
ajst-32536	197	13	power	power	NOUN
ajst-32536	197	14	spectral	spectral	ADJ
ajst-32536	197	15	density	density	NOUN
ajst-32536	197	16	of	of	ADP
ajst-32536	197	17	electroencephalography	electroencephalography	NOUN
ajst-32536	197	18	(	(	PUNCT
ajst-32536	197	19	eeg	eeg	NOUN
ajst-32536	197	20	)	)	PUNCT
ajst-32536	197	21	signals	signal	NOUN
ajst-32536	197	22	using	use	VERB
ajst-32536	197	23	deep	deep	ADJ
ajst-32536	197	24	learning	learning	NOUN
ajst-32536	197	25	model[j	model[j	PROPN
ajst-32536	197	26	]	]	PUNCT
ajst-32536	197	27	.	.	PUNCT
ajst-32536	198	1	physical	physical	ADJ
ajst-32536	198	2	and	and	CCONJ
ajst-32536	198	3	engineering	engineering	NOUN
ajst-32536	198	4	sciences	science	NOUN
ajst-32536	198	5	in	in	ADP
ajst-32536	198	6	medicine	medicine	NOUN
ajst-32536	198	7	,	,	PUNCT
ajst-32536	198	8	2023	2023	NUM
ajst-32536	198	9	,	,	PUNCT
ajst-32536	198	10	46(3	46(3	NUM
ajst-32536	198	11	):	):	PUNCT
ajst-32536	198	12	1163	1163	NUM
ajst-32536	198	13	-	-	SYM
ajst-32536	198	14	1174	1174	NUM
ajst-32536	198	15	.	.	PUNCT
ajst-32536	199	1	[	[	X
ajst-32536	199	2	6	6	NUM
ajst-32536	199	3	]	]	X
ajst-32536	199	4	zhang	zhang	PROPN
ajst-32536	199	5	w	w	PROPN
ajst-32536	199	6	,	,	PUNCT
ajst-32536	199	7	han	han	PROPN
ajst-32536	199	8	x	x	PROPN
ajst-32536	199	9	,	,	PUNCT
ajst-32536	199	10	qiu	qiu	PROPN
ajst-32536	199	11	s	s	PROPN
ajst-32536	199	12	,	,	PUNCT
ajst-32536	199	13	et	et	PROPN
ajst-32536	199	14	al	al	PROPN
ajst-32536	199	15	.	.	PUNCT
ajst-32536	199	16	analysis	analysis	NOUN
ajst-32536	199	17	of	of	ADP
ajst-32536	199	18	brain	brain	NOUN
ajst-32536	199	19	functional	functional	ADJ
ajst-32536	199	20	network	network	NOUN
ajst-32536	199	21	based	base	VERB
ajst-32536	199	22	on	on	ADP
ajst-32536	199	23	eeg	eeg	NOUN
ajst-32536	199	24	signals	signal	NOUN
ajst-32536	199	25	for	for	ADP
ajst-32536	199	26	early	early	ADJ
ajst-32536	199	27	-	-	PUNCT
ajst-32536	199	28	stage	stage	NOUN
ajst-32536	199	29	parkinson	parkinson	NOUN
ajst-32536	199	30	’s	’s	PART
ajst-32536	199	31	disease	disease	NOUN
ajst-32536	199	32	detection[j	detection[j	PROPN
ajst-32536	199	33	]	]	PUNCT
ajst-32536	199	34	.	.	PUNCT
ajst-32536	200	1	ieee	ieee	NOUN
ajst-32536	200	2	access	access	NOUN
ajst-32536	200	3	,	,	PUNCT
ajst-32536	200	4	2022	2022	NUM
ajst-32536	200	5	,	,	PUNCT
ajst-32536	200	6	10	10	NUM
ajst-32536	200	7	:	:	SYM
ajst-32536	200	8	21347	21347	NUM
ajst-32536	200	9	-	-	SYM
ajst-32536	200	10	21358	21358	NUM
ajst-32536	200	11	.	.	PUNCT
ajst-32536	201	1	[	[	X
ajst-32536	201	2	7	7	X
ajst-32536	201	3	]	]	X
ajst-32536	201	4	nguyen	nguyen	NOUN
ajst-32536	201	5	m	m	PROPN
ajst-32536	201	6	t	t	PROPN
ajst-32536	201	7	p	p	NOUN
ajst-32536	201	8	,	,	PUNCT
ajst-32536	201	9	tran	tran	PROPN
ajst-32536	201	10	m	m	PROPN
ajst-32536	202	1	k	k	PROPN
ajst-32536	202	2	p	p	PROPN
ajst-32536	202	3	,	,	PUNCT
ajst-32536	202	4	nakano	nakano	PROPN
ajst-32536	202	5	t	t	PROPN
ajst-32536	202	6	,	,	PUNCT
ajst-32536	202	7	et	et	PROPN
ajst-32536	202	8	al	al	PROPN
ajst-32536	202	9	.	.	PUNCT
ajst-32536	203	1	an	an	DET
ajst-32536	203	2	approach	approach	NOUN
ajst-32536	203	3	for	for	ADP
ajst-32536	203	4	detecting	detect	VERB
ajst-32536	203	5	parkinson	parkinson	NOUN
ajst-32536	203	6	’s	’s	PART
ajst-32536	203	7	disease	disease	NOUN
ajst-32536	203	8	by	by	ADP
ajst-32536	203	9	integrating	integrate	VERB
ajst-32536	203	10	optimal	optimal	ADJ
ajst-32536	203	11	feature	feature	NOUN
ajst-32536	203	12	selection	selection	NOUN
ajst-32536	203	13	strategies	strategy	NOUN
ajst-32536	203	14	with	with	ADP
ajst-32536	203	15	dense	dense	ADJ
ajst-32536	203	16	multiscale	multiscale	ADJ
ajst-32536	203	17	sample	sample	NOUN
ajst-32536	203	18	entropy[j	entropy[j	PROPN
ajst-32536	203	19	]	]	PUNCT
ajst-32536	203	20	.	.	PUNCT
ajst-32536	204	1	information	information	NOUN
ajst-32536	204	2	,	,	PUNCT
ajst-32536	204	3	2024	2024	NUM
ajst-32536	204	4	,	,	PUNCT
ajst-32536	204	5	16(1	16(1	NUM
ajst-32536	204	6	):	):	PUNCT
ajst-32536	204	7	1	1	NUM
ajst-32536	204	8	.	.	PUNCT
ajst-32536	205	1	[	[	X
ajst-32536	205	2	8	8	NUM
ajst-32536	205	3	]	]	X
ajst-32536	205	4	vidya	vidya	PROPN
ajst-32536	205	5	b	b	PROPN
ajst-32536	205	6	,	,	PUNCT
ajst-32536	205	7	sasikumar	sasikumar	PROPN
ajst-32536	205	8	p.	p.	PROPN
ajst-32536	205	9	gait	gait	PROPN
ajst-32536	205	10	based	base	VERB
ajst-32536	205	11	parkinson	parkinson	NOUN
ajst-32536	205	12	’s	’s	PART
ajst-32536	205	13	disease	disease	NOUN
ajst-32536	205	14	diagnosis	diagnosis	NOUN
ajst-32536	205	15	and	and	CCONJ
ajst-32536	205	16	severity	severity	NOUN
ajst-32536	205	17	rating	rating	NOUN
ajst-32536	205	18	using	use	VERB
ajst-32536	205	19	multi	multi	ADJ
ajst-32536	205	20	-	-	ADJ
ajst-32536	205	21	class	class	ADJ
ajst-32536	205	22	support	support	NOUN
ajst-32536	205	23	vector	vector	NOUN
ajst-32536	205	24	machine[j	machine[j	PROPN
ajst-32536	205	25	]	]	PUNCT
ajst-32536	205	26	.	.	PUNCT
ajst-32536	206	1	applied	apply	VERB
ajst-32536	206	2	soft	soft	ADJ
ajst-32536	206	3	computing	computing	NOUN
ajst-32536	206	4	,	,	PUNCT
ajst-32536	206	5	2021	2021	NUM
ajst-32536	206	6	,	,	PUNCT
ajst-32536	206	7	113	113	NUM
ajst-32536	206	8	:	:	SYM
ajst-32536	206	9	107939	107939	NUM
ajst-32536	206	10	.	.	PUNCT
ajst-32536	207	1	[	[	X
ajst-32536	207	2	9	9	NUM
ajst-32536	207	3	]	]	PUNCT
ajst-32536	207	4	sivaranjini	sivaranjini	X
ajst-32536	207	5	s	s	PROPN
ajst-32536	207	6	,	,	PUNCT
ajst-32536	207	7	sujatha	sujatha	PROPN
ajst-32536	207	8	c	c	PROPN
ajst-32536	207	9	m.	m.	PROPN
ajst-32536	207	10	deep	deep	ADJ
ajst-32536	207	11	learning	learning	NOUN
ajst-32536	207	12	based	base	VERB
ajst-32536	207	13	diagnosis	diagnosis	NOUN
ajst-32536	207	14	of	of	ADP
ajst-32536	207	15	parkinson	parkinson	NOUN
ajst-32536	207	16	’s	’s	PART
ajst-32536	207	17	disease	disease	NOUN
ajst-32536	207	18	using	use	VERB
ajst-32536	207	19	convolutional	convolutional	ADJ
ajst-32536	207	20	neural	neural	ADJ
ajst-32536	207	21	network[j	network[j	NOUN
ajst-32536	207	22	]	]	PUNCT
ajst-32536	207	23	.	.	PUNCT
ajst-32536	208	1	multimedia	multimedia	NOUN
ajst-32536	208	2	tools	tool	NOUN
ajst-32536	208	3	and	and	CCONJ
ajst-32536	208	4	applications	application	NOUN
ajst-32536	208	5	,	,	PUNCT
ajst-32536	208	6	2020	2020	NUM
ajst-32536	208	7	,	,	PUNCT
ajst-32536	208	8	79(21	79(21	NOUN
ajst-32536	208	9	):	):	PUNCT
ajst-32536	208	10	15467	15467	NUM
ajst-32536	208	11	-	-	SYM
ajst-32536	208	12	15479	15479	NUM
ajst-32536	208	13	.	.	PUNCT
ajst-32536	209	1	[	[	X
ajst-32536	209	2	10	10	NUM
ajst-32536	209	3	]	]	X
ajst-32536	209	4	demir	demir	PROPN
ajst-32536	209	5	f	f	PROPN
ajst-32536	209	6	,	,	PUNCT
ajst-32536	209	7	sengur	sengur	PROPN
ajst-32536	209	8	a	a	PROPN
ajst-32536	209	9	,	,	PUNCT
ajst-32536	209	10	ari	ari	PROPN
ajst-32536	209	11	a	a	PROPN
ajst-32536	209	12	,	,	PUNCT
ajst-32536	209	13	et	et	PROPN
ajst-32536	209	14	al	al	PROPN
ajst-32536	209	15	.	.	PROPN
ajst-32536	209	16	feature	feature	PROPN
ajst-32536	209	17	mapping	mapping	NOUN
ajst-32536	209	18	and	and	CCONJ
ajst-32536	209	19	deep	deep	ADJ
ajst-32536	209	20	long	long	ADJ
ajst-32536	209	21	short	short	ADJ
ajst-32536	209	22	term	term	NOUN
ajst-32536	209	23	memory	memory	NOUN
ajst-32536	209	24	network	network	NOUN
ajst-32536	209	25	-	-	PUNCT
ajst-32536	209	26	based	base	VERB
ajst-32536	209	27	efficient	efficient	ADJ
ajst-32536	209	28	approach	approach	NOUN
ajst-32536	209	29	for	for	ADP
ajst-32536	209	30	parkinson	parkinson	NOUN
ajst-32536	209	31	’s	’s	PART
ajst-32536	209	32	disease	disease	NOUN
ajst-32536	209	33	diagnosis[j	diagnosis[j	PROPN
ajst-32536	209	34	]	]	PUNCT
ajst-32536	209	35	.	.	PUNCT
ajst-32536	210	1	ieee	ieee	NOUN
ajst-32536	210	2	access	access	NOUN
ajst-32536	210	3	,	,	PUNCT
ajst-32536	210	4	2021	2021	NUM
ajst-32536	210	5	,	,	PUNCT
ajst-32536	210	6	9	9	NUM
ajst-32536	210	7	:	:	SYM
ajst-32536	210	8	149456	149456	NUM
ajst-32536	210	9	-	-	SYM
ajst-32536	210	10	149464	149464	NUM
ajst-32536	210	11	.	.	PUNCT
ajst-32536	211	1	[	[	X
ajst-32536	211	2	11	11	NUM
ajst-32536	211	3	]	]	X
ajst-32536	211	4	saha	saha	PROPN
ajst-32536	211	5	u	u	PROPN
ajst-32536	211	6	,	,	PUNCT
ajst-32536	211	7	ahamed	ahamed	PROPN
ajst-32536	211	8	i	i	PRON
ajst-32536	211	9	u	u	PROPN
ajst-32536	211	10	,	,	PUNCT
ajst-32536	211	11	ahamed	ahamed	PROPN
ajst-32536	211	12	i	i	PRON
ajst-32536	211	13	u	u	PROPN
ajst-32536	211	14	,	,	PUNCT
ajst-32536	211	15	et	et	PROPN
ajst-32536	211	16	al	al	PROPN
ajst-32536	211	17	.	.	PROPN
ajst-32536	211	18	graph	graph	VERB
ajst-32536	211	19	convolutional	convolutional	ADJ
ajst-32536	211	20	network	network	NOUN
ajst-32536	211	21	-	-	PUNCT
ajst-32536	211	22	based	base	VERB
ajst-32536	211	23	approach	approach	NOUN
ajst-32536	211	24	for	for	ADP
ajst-32536	211	25	parkinson	parkinson	NOUN
ajst-32536	211	26	’s	’s	PART
ajst-32536	211	27	disease	disease	NOUN
ajst-32536	211	28	classification	classification	NOUN
ajst-32536	211	29	using	use	VERB
ajst-32536	211	30	euclidean	euclidean	ADJ
ajst-32536	211	31	distance	distance	NOUN
ajst-32536	211	32	graphs[c]//2024	graphs[c]//2024	PROPN
ajst-32536	211	33	7th	7th	ADJ
ajst-32536	211	34	international	international	ADJ
ajst-32536	211	35	conference	conference	NOUN
ajst-32536	211	36	on	on	ADP
ajst-32536	211	37	informatics	informatic	NOUN
ajst-32536	211	38	and	and	CCONJ
ajst-32536	211	39	computational	computational	ADJ
ajst-32536	211	40	sciences	science	NOUN
ajst-32536	211	41	(	(	PUNCT
ajst-32536	211	42	icicos	icico	NOUN
ajst-32536	211	43	)	)	PUNCT
ajst-32536	211	44	.	.	PUNCT
ajst-32536	212	1	ieee	ieee	NOUN
ajst-32536	212	2	,	,	PUNCT
ajst-32536	212	3	2024	2024	NUM
ajst-32536	212	4	:	:	PUNCT
ajst-32536	212	5	532	532	NUM
ajst-32536	212	6	-	-	SYM
ajst-32536	212	7	537	537	NUM
ajst-32536	212	8	.	.	PUNCT
ajst-32536	213	1	[	[	X
ajst-32536	213	2	12	12	NUM
ajst-32536	213	3	]	]	PUNCT
ajst-32536	213	4	santos	santos	PROPN
ajst-32536	213	5	l	l	NOUN
ajst-32536	213	6	o	o	PROPN
ajst-32536	213	7	,	,	PUNCT
ajst-32536	213	8	medeiros	medeiros	PROPN
ajst-32536	213	9	a	a	DET
ajst-32536	213	10	g	g	NOUN
ajst-32536	213	11	,	,	PUNCT
ajst-32536	213	12	rego	rego	NOUN
ajst-32536	213	13	p	p	NOUN
ajst-32536	213	14	a	a	DET
ajst-32536	213	15	l	l	NOUN
ajst-32536	213	16	,	,	PUNCT
ajst-32536	213	17	et	et	PROPN
ajst-32536	213	18	al	al	PROPN
ajst-32536	213	19	.	.	PROPN
ajst-32536	213	20	graph	graph	NOUN
ajst-32536	213	21	-	-	PUNCT
ajst-32536	213	22	based	base	VERB
ajst-32536	213	23	eeg	eeg	NOUN
ajst-32536	213	24	analysis	analysis	NOUN
ajst-32536	213	25	for	for	ADP
ajst-32536	213	26	parkinson	parkinson	NOUN
ajst-32536	213	27	’s	’s	PART
ajst-32536	213	28	disease	disease	NOUN
ajst-32536	213	29	classification	classification	NOUN
ajst-32536	213	30	:	:	PUNCT
ajst-32536	213	31	a	a	DET
ajst-32536	213	32	residual	residual	ADJ
ajst-32536	213	33	neural	neural	ADJ
ajst-32536	213	34	network	network	NOUN
ajst-32536	213	35	approach[c]//2024	approach[c]//2024	NUM
ajst-32536	213	36	international	international	ADJ
ajst-32536	213	37	joint	joint	ADJ
ajst-32536	213	38	conference	conference	NOUN
ajst-32536	213	39	on	on	ADP
ajst-32536	213	40	neural	neural	ADJ
ajst-32536	213	41	networks	network	NOUN
ajst-32536	213	42	(	(	PUNCT
ajst-32536	213	43	ijcnn	ijcnn	PROPN
ajst-32536	213	44	)	)	PUNCT
ajst-32536	213	45	.	.	PUNCT
ajst-32536	214	1	ieee	ieee	PROPN
ajst-32536	214	2	,	,	PUNCT
ajst-32536	214	3	2024	2024	NUM
ajst-32536	214	4	:	:	PUNCT
ajst-32536	214	5	1	1	NUM
ajst-32536	214	6	-	-	SYM
ajst-32536	214	7	8	8	NUM
ajst-32536	214	8	.	.	PUNCT
ajst-32536	215	1	[	[	X
ajst-32536	215	2	13	13	NUM
ajst-32536	215	3	]	]	X
ajst-32536	215	4	chauhan	chauhan	PROPN
ajst-32536	215	5	m	m	PROPN
ajst-32536	215	6	k	k	PROPN
ajst-32536	215	7	,	,	PUNCT
ajst-32536	215	8	ghosal	ghosal	PROPN
ajst-32536	215	9	p.	p.	PROPN
ajst-32536	215	10	a	a	DET
ajst-32536	215	11	hybrid	hybrid	ADJ
ajst-32536	215	12	cnn	cnn	PROPN
ajst-32536	215	13	-	-	PUNCT
ajst-32536	215	14	bilstm	bilstm	NOUN
ajst-32536	215	15	neural	neural	ADJ
ajst-32536	215	16	network	network	NOUN
ajst-32536	215	17	architecture	architecture	NOUN
ajst-32536	215	18	for	for	ADP
ajst-32536	215	19	early	early	ADJ
ajst-32536	215	20	prediction	prediction	NOUN
ajst-32536	215	21	of	of	ADP
ajst-32536	215	22	parkinson	parkinson	NOUN
ajst-32536	215	23	's	's	PART
ajst-32536	215	24	disease[c]//2024	disease[c]//2024	PROPN
ajst-32536	215	25	ieee	ieee	NOUN
ajst-32536	215	26	international	international	ADJ
ajst-32536	215	27	symposium	symposium	NOUN
ajst-32536	215	28	on	on	ADP
ajst-32536	215	29	smart	smart	ADJ
ajst-32536	215	30	electronic	electronic	ADJ
ajst-32536	215	31	systems	system	NOUN
ajst-32536	215	32	(	(	PUNCT
ajst-32536	215	33	ises	ise	NOUN
ajst-32536	215	34	)	)	PUNCT
ajst-32536	215	35	.	.	PUNCT
ajst-32536	216	1	ieee	ieee	NOUN
ajst-32536	216	2	,	,	PUNCT
ajst-32536	216	3	2024	2024	NUM
ajst-32536	216	4	:	:	PUNCT
ajst-32536	216	5	303	303	NUM
ajst-32536	216	6	-	-	SYM
ajst-32536	216	7	308	308	NUM
ajst-32536	216	8	.	.	PUNCT
ajst-32536	217	1	[	[	X
ajst-32536	217	2	14	14	NUM
ajst-32536	217	3	]	]	X
ajst-32536	217	4	dai	dai	PROPN
ajst-32536	217	5	y	y	PROPN
ajst-32536	217	6	,	,	PUNCT
ajst-32536	217	7	tang	tang	PROPN
ajst-32536	217	8	z	z	PROPN
ajst-32536	217	9	,	,	PUNCT
ajst-32536	217	10	wang	wang	PROPN
ajst-32536	217	11	y	y	PROPN
ajst-32536	217	12	,	,	PUNCT
ajst-32536	217	13	et	et	PROPN
ajst-32536	217	14	al	al	PROPN
ajst-32536	217	15	.	.	PROPN
ajst-32536	217	16	data	datum	NOUN
ajst-32536	217	17	driven	drive	VERB
ajst-32536	217	18	intelligent	intelligent	ADJ
ajst-32536	217	19	diagnostics	diagnostic	NOUN
ajst-32536	217	20	for	for	ADP
ajst-32536	217	21	parkinson	parkinson	NOUN
ajst-32536	217	22	’s	’s	PART
ajst-32536	217	23	disease[j	disease[j	NOUN
ajst-32536	217	24	]	]	PUNCT
ajst-32536	217	25	.	.	PUNCT
ajst-32536	218	1	ieee	ieee	NOUN
ajst-32536	218	2	access	access	NOUN
ajst-32536	218	3	,	,	PUNCT
ajst-32536	218	4	2019	2019	NUM
ajst-32536	218	5	,	,	PUNCT
ajst-32536	218	6	7	7	NUM
ajst-32536	218	7	:	:	SYM
ajst-32536	218	8	106941	106941	NUM
ajst-32536	218	9	-	-	SYM
ajst-32536	218	10	106950	106950	NUM
ajst-32536	218	11	.	.	PUNCT
ajst-32536	219	1	[	[	X
ajst-32536	219	2	15	15	X
ajst-32536	219	3	]	]	X
ajst-32536	219	4	mekruksavanich	mekruksavanich	PROPN
ajst-32536	219	5	s	s	PROPN
ajst-32536	219	6	,	,	PUNCT
ajst-32536	219	7	jitpattanakul	jitpattanakul	PROPN
ajst-32536	219	8	a.	a.	NOUN
ajst-32536	219	9	detection	detection	NOUN
ajst-32536	219	10	of	of	ADP
ajst-32536	219	11	freezing	freezing	NOUN
ajst-32536	219	12	of	of	ADP
ajst-32536	219	13	gait	gait	NOUN
ajst-32536	219	14	in	in	ADP
ajst-32536	219	15	parkinson	parkinson	NOUN
ajst-32536	219	16	's	's	PART
ajst-32536	219	17	disease	disease	NOUN
ajst-32536	219	18	by	by	ADP
ajst-32536	219	19	squeeze	squeeze	NOUN
ajst-32536	219	20	-	-	PUNCT
ajst-32536	219	21	andexcitation	andexcitation	NOUN
ajst-32536	219	22	convolutional	convolutional	ADJ
ajst-32536	219	23	neural	neural	ADJ
ajst-32536	219	24	network	network	NOUN
ajst-32536	219	25	with	with	ADP
ajst-32536	219	26	wearable	wearable	ADJ
ajst-32536	219	27	sensors[c]//2021	sensors[c]//2021	PROPN
ajst-32536	219	28	15th	15th	ADJ
ajst-32536	219	29	international	international	ADJ
ajst-32536	219	30	conference	conference	NOUN
ajst-32536	219	31	on	on	ADP
ajst-32536	219	32	open	open	ADJ
ajst-32536	219	33	source	source	NOUN
ajst-32536	219	34	systems	system	NOUN
ajst-32536	219	35	and	and	CCONJ
ajst-32536	219	36	technologies	technology	NOUN
ajst-32536	219	37	(	(	PUNCT
ajst-32536	219	38	icosst	icosst	NOUN
ajst-32536	219	39	)	)	PUNCT
ajst-32536	219	40	.	.	PUNCT
ajst-32536	220	1	ieee	ieee	NOUN
ajst-32536	220	2	,	,	PUNCT
ajst-32536	220	3	2021	2021	NUM
ajst-32536	220	4	:	:	PUNCT
ajst-32536	220	5	1	1	NUM
ajst-32536	220	6	-	-	SYM
ajst-32536	220	7	5	5	NUM
ajst-32536	220	8	.	.	PUNCT
ajst-32536	221	1	[	[	X
ajst-32536	221	2	16	16	NUM
ajst-32536	221	3	]	]	X
ajst-32536	221	4	zhao	zhao	PROPN
ajst-32536	221	5	m	m	PROPN
ajst-32536	221	6	,	,	PUNCT
ajst-32536	221	7	zhong	zhong	PROPN
ajst-32536	221	8	s	s	PROPN
ajst-32536	221	9	,	,	PUNCT
ajst-32536	221	10	fu	fu	ADJ
ajst-32536	221	11	x	x	NOUN
ajst-32536	221	12	,	,	PUNCT
ajst-32536	221	13	et	et	PROPN
ajst-32536	221	14	al	al	PROPN
ajst-32536	221	15	.	.	PUNCT
ajst-32536	222	1	deep	deep	ADJ
ajst-32536	222	2	residual	residual	ADJ
ajst-32536	222	3	shrinkage	shrinkage	NOUN
ajst-32536	222	4	networks	network	NOUN
ajst-32536	222	5	for	for	ADP
ajst-32536	222	6	fault	fault	NOUN
ajst-32536	222	7	diagnosis[j	diagnosis[j	NOUN
ajst-32536	222	8	]	]	PUNCT
ajst-32536	222	9	.	.	PUNCT
ajst-32536	223	1	ieee	ieee	NOUN
ajst-32536	223	2	transactions	transaction	NOUN
ajst-32536	223	3	on	on	ADP
ajst-32536	223	4	industrial	industrial	ADJ
ajst-32536	223	5	informatics	informatic	NOUN
ajst-32536	223	6	,	,	PUNCT
ajst-32536	223	7	2019	2019	NUM
ajst-32536	223	8	,	,	PUNCT
ajst-32536	223	9	16(7	16(7	NUM
ajst-32536	223	10	):	):	PUNCT
ajst-32536	223	11	4681	4681	NUM
ajst-32536	223	12	-	-	SYM
ajst-32536	223	13	4690	4690	NUM
ajst-32536	223	14	.	.	PUNCT
ajst-32536	224	1	[	[	X
ajst-32536	224	2	17	17	NUM
ajst-32536	224	3	]	]	SYM
ajst-32536	224	4	khatamino	khatamino	NOUN
ajst-32536	224	5	p	p	X
ajst-32536	224	6	,	,	PUNCT
ajst-32536	224	7	cantürk	cantürk	PROPN
ajst-32536	224	8	i	i	PRON
ajst-32536	224	9	,	,	PUNCT
ajst-32536	224	10	özyılmaz	özyılmaz	PROPN
ajst-32536	224	11	l.	l.	PROPN
ajst-32536	224	12	a	a	DET
ajst-32536	224	13	deep	deep	ADJ
ajst-32536	224	14	learning	learning	NOUN
ajst-32536	224	15	-	-	PUNCT
ajst-32536	224	16	cnn	cnn	PROPN
ajst-32536	224	17	based	base	VERB
ajst-32536	224	18	system	system	NOUN
ajst-32536	224	19	for	for	ADP
ajst-32536	224	20	medical	medical	ADJ
ajst-32536	224	21	diagnosis	diagnosis	NOUN
ajst-32536	224	22	:	:	PUNCT
ajst-32536	224	23	an	an	DET
ajst-32536	224	24	application	application	NOUN
ajst-32536	224	25	on	on	ADP
ajst-32536	224	26	parkinson	parkinson	NOUN
ajst-32536	224	27	’s	’s	PART
ajst-32536	224	28	disease	disease	NOUN
ajst-32536	224	29	handwriting	handwrite	VERB
ajst-32536	224	30	drawings[c]//2018	drawings[c]//2018	NUM
ajst-32536	224	31	6th	6th	ADJ
ajst-32536	224	32	international	international	ADJ
ajst-32536	224	33	conference	conference	NOUN
ajst-32536	224	34	on	on	ADP
ajst-32536	224	35	control	control	PROPN
ajst-32536	224	36	engineering	engineering	PROPN
ajst-32536	224	37	&	&	CCONJ
ajst-32536	224	38	information	information	NOUN
ajst-32536	224	39	technology	technology	NOUN
ajst-32536	224	40	(	(	PUNCT
ajst-32536	224	41	ceit	ceit	PROPN
ajst-32536	224	42	)	)	PUNCT
ajst-32536	224	43	.	.	PUNCT
ajst-32536	225	1	ieee	ieee	PROPN
ajst-32536	225	2	,	,	PUNCT
ajst-32536	225	3	2018	2018	NUM
ajst-32536	225	4	:	:	PUNCT
ajst-32536	225	5	1	1	NUM
ajst-32536	225	6	-	-	SYM
ajst-32536	225	7	6	6	NUM
ajst-32536	225	8	.	.	NOUN
ajst-32536	225	9	39	39	NUM
ajst-32536	226	1	[	[	SYM
ajst-32536	226	2	18	18	NUM
ajst-32536	226	3	]	]	X
ajst-32536	226	4	reyes	reyes	PROPN
ajst-32536	226	5	j	j	PROPN
ajst-32536	226	6	f	f	PROPN
ajst-32536	226	7	,	,	PUNCT
ajst-32536	226	8	montealegre	montealegre	VERB
ajst-32536	226	9	j	j	PROPN
ajst-32536	226	10	s	s	PROPN
ajst-32536	226	11	,	,	PUNCT
ajst-32536	226	12	castano	castano	PROPN
ajst-32536	226	13	y	y	PROPN
ajst-32536	226	14	j	j	PROPN
ajst-32536	226	15	,	,	PUNCT
ajst-32536	226	16	et	et	PROPN
ajst-32536	226	17	al	al	PROPN
ajst-32536	226	18	.	.	PUNCT
ajst-32536	227	1	lstm	lstm	PROPN
ajst-32536	227	2	and	and	CCONJ
ajst-32536	227	3	convolution	convolution	NOUN
ajst-32536	227	4	networks	network	NOUN
ajst-32536	227	5	exploration	exploration	NOUN
ajst-32536	227	6	for	for	ADP
ajst-32536	227	7	parkinson	parkinson	NOUN
ajst-32536	227	8	’s	’s	PART
ajst-32536	227	9	diagnosis[c]//2019	diagnosis[c]//2019	PUNCT
ajst-32536	227	10	ieee	ieee	NOUN
ajst-32536	227	11	colombian	colombian	ADJ
ajst-32536	227	12	conference	conference	NOUN
ajst-32536	227	13	on	on	ADP
ajst-32536	227	14	communications	communication	NOUN
ajst-32536	227	15	and	and	CCONJ
ajst-32536	227	16	computing	computing	NOUN
ajst-32536	227	17	(	(	PUNCT
ajst-32536	227	18	colcom	colcom	NOUN
ajst-32536	227	19	)	)	PUNCT
ajst-32536	227	20	.	.	PUNCT
ajst-32536	228	1	ieee	ieee	PROPN
ajst-32536	228	2	,	,	PUNCT
ajst-32536	228	3	2019	2019	NUM
ajst-32536	228	4	:	:	PUNCT
ajst-32536	228	5	1	1	NUM
ajst-32536	228	6	-	-	SYM
ajst-32536	228	7	4	4	NUM
ajst-32536	228	8	.	.	PUNCT
ajst-32536	229	1	[	[	X
ajst-32536	229	2	19	19	NUM
ajst-32536	229	3	]	]	PUNCT
ajst-32536	229	4	qiu	qiu	PROPN
ajst-32536	229	5	l	l	PROPN
ajst-32536	229	6	,	,	PUNCT
ajst-32536	229	7	li	li	PROPN
ajst-32536	229	8	j	j	PROPN
ajst-32536	229	9	,	,	PUNCT
ajst-32536	229	10	pan	pan	PROPN
ajst-32536	229	11	j.	j.	PROPN
ajst-32536	229	12	parkinson	parkinson	PROPN
ajst-32536	229	13	’s	’s	PART
ajst-32536	229	14	disease	disease	NOUN
ajst-32536	229	15	detection	detection	NOUN
ajst-32536	229	16	based	base	VERB
ajst-32536	229	17	on	on	ADP
ajst-32536	229	18	multi	multi	ADJ
ajst-32536	229	19	-	-	ADJ
ajst-32536	229	20	pattern	pattern	ADJ
ajst-32536	229	21	analysis	analysis	NOUN
ajst-32536	229	22	and	and	CCONJ
ajst-32536	229	23	multi	multi	ADJ
ajst-32536	229	24	-	-	ADJ
ajst-32536	229	25	scale	scale	ADJ
ajst-32536	229	26	convolutional	convolutional	ADJ
ajst-32536	229	27	neural	neural	ADJ
ajst-32536	229	28	networks[j	networks[j	NOUN
ajst-32536	229	29	]	]	X
ajst-32536	229	30	.	.	PUNCT
ajst-32536	230	1	frontiers	frontier	NOUN
ajst-32536	230	2	in	in	ADP
ajst-32536	230	3	neuroscience	neuroscience	NOUN
ajst-32536	230	4	,	,	PUNCT
ajst-32536	230	5	2022	2022	NUM
ajst-32536	230	6	,	,	PUNCT
ajst-32536	230	7	16	16	NUM
ajst-32536	230	8	:	:	SYM
ajst-32536	230	9	957181	957181	NUM
ajst-32536	230	10	.	.	PUNCT
ajst-32536	231	1	[	[	X
ajst-32536	231	2	20	20	NUM
ajst-32536	231	3	]	]	X
ajst-32536	231	4	yang	yang	PROPN
ajst-32536	231	5	x	x	PROPN
ajst-32536	231	6	,	,	PUNCT
ajst-32536	231	7	ye	ye	PRON
ajst-32536	231	8	q	q	NOUN
ajst-32536	231	9	,	,	PUNCT
ajst-32536	231	10	cai	cai	PROPN
ajst-32536	231	11	g	g	PROPN
ajst-32536	231	12	,	,	PUNCT
ajst-32536	231	13	et	et	PROPN
ajst-32536	231	14	al	al	PROPN
ajst-32536	231	15	.	.	PROPN
ajst-32536	231	16	pd	pd	PROPN
ajst-32536	231	17	-	-	PUNCT
ajst-32536	231	18	resnet	resnet	NOUN
ajst-32536	231	19	for	for	ADP
ajst-32536	231	20	classification	classification	NOUN
ajst-32536	231	21	of	of	ADP
ajst-32536	231	22	parkinson	parkinson	NOUN
ajst-32536	231	23	’s	’s	PART
ajst-32536	231	24	disease	disease	NOUN
ajst-32536	231	25	from	from	ADP
ajst-32536	231	26	gait[j	gait[j	NOUN
ajst-32536	231	27	]	]	X
ajst-32536	231	28	.	.	PUNCT
ajst-32536	232	1	ieee	ieee	PROPN
ajst-32536	232	2	journal	journal	PROPN
ajst-32536	232	3	of	of	ADP
ajst-32536	232	4	translational	translational	ADJ
ajst-32536	232	5	engineering	engineering	NOUN
ajst-32536	232	6	in	in	ADP
ajst-32536	232	7	health	health	NOUN
ajst-32536	232	8	and	and	CCONJ
ajst-32536	232	9	medicine	medicine	NOUN
ajst-32536	232	10	,	,	PUNCT
ajst-32536	232	11	2022	2022	NUM
ajst-32536	232	12	,	,	PUNCT
ajst-32536	232	13	10	10	NUM
ajst-32536	232	14	:	:	SYM
ajst-32536	232	15	1	1	NUM
ajst-32536	232	16	-	-	SYM
ajst-32536	232	17	11	11	NUM
ajst-32536	232	18	.	.	PUNCT
ajst-32536	233	1	[	[	X
ajst-32536	233	2	21	21	NUM
ajst-32536	233	3	]	]	X
ajst-32536	233	4	güven	güven	PROPN
ajst-32536	233	5	m.	m.	NOUN
ajst-32536	233	6	detection	detection	PROPN
ajst-32536	233	7	of	of	ADP
ajst-32536	233	8	alzheimer	alzheimer	PROPN
ajst-32536	233	9	’s	’s	PART
ajst-32536	233	10	and	and	CCONJ
ajst-32536	233	11	parkinson	parkinson	NOUN
ajst-32536	233	12	’s	’s	PART
ajst-32536	233	13	diseases	disease	NOUN
ajst-32536	233	14	using	use	VERB
ajst-32536	233	15	deep	deep	ADJ
ajst-32536	233	16	learning	learning	NOUN
ajst-32536	233	17	-	-	PUNCT
ajst-32536	233	18	based	base	VERB
ajst-32536	233	19	various	various	ADJ
ajst-32536	233	20	transformers	transformer	NOUN
ajst-32536	233	21	models[j	models[j	PROPN
ajst-32536	233	22	]	]	PUNCT
ajst-32536	233	23	.	.	PUNCT
ajst-32536	234	1	engineering	engineering	NOUN
ajst-32536	234	2	proceedings	proceeding	NOUN
ajst-32536	234	3	,	,	PUNCT
ajst-32536	234	4	2024	2024	NUM
ajst-32536	234	5	,	,	PUNCT
ajst-32536	234	6	73(1	73(1	NUM
ajst-32536	234	7	):	):	PUNCT
ajst-32536	234	8	4	4	NUM
ajst-32536	234	9	.	.	PUNCT
ajst-32536	235	1	[	[	X
ajst-32536	235	2	22	22	NUM
ajst-32536	235	3	]	]	PUNCT
ajst-32536	235	4	qiu	qiu	PROPN
ajst-32536	235	5	l	l	PROPN
ajst-32536	235	6	,	,	PUNCT
ajst-32536	235	7	li	li	PROPN
ajst-32536	235	8	j	j	PROPN
ajst-32536	235	9	,	,	PUNCT
ajst-32536	235	10	zhong	zhong	PROPN
ajst-32536	235	11	l	l	PROPN
ajst-32536	235	12	,	,	PUNCT
ajst-32536	235	13	et	et	PROPN
ajst-32536	235	14	al	al	PROPN
ajst-32536	235	15	.	.	PUNCT
ajst-32536	236	1	a	a	DET
ajst-32536	236	2	novel	novel	ADJ
ajst-32536	236	3	eeg	eeg	NOUN
ajst-32536	236	4	-	-	PUNCT
ajst-32536	236	5	based	base	VERB
ajst-32536	236	6	parkinson	parkinson	NOUN
ajst-32536	236	7	’s	’s	PART
ajst-32536	236	8	disease	disease	NOUN
ajst-32536	236	9	detection	detection	NOUN
ajst-32536	236	10	model	model	NOUN
ajst-32536	236	11	using	use	VERB
ajst-32536	236	12	multiscale	multiscale	ADJ
ajst-32536	236	13	convolutional	convolutional	ADJ
ajst-32536	236	14	prototype	prototype	NOUN
ajst-32536	236	15	networks[j	networks[j	PROPN
ajst-32536	236	16	]	]	X
ajst-32536	236	17	.	.	PUNCT
ajst-32536	237	1	ieee	ieee	NOUN
ajst-32536	237	2	transactions	transaction	NOUN
ajst-32536	237	3	on	on	ADP
ajst-32536	237	4	instrumentation	instrumentation	NOUN
ajst-32536	237	5	and	and	CCONJ
ajst-32536	237	6	measurement	measurement	NOUN
ajst-32536	237	7	,	,	PUNCT
ajst-32536	237	8	2024	2024	NUM
ajst-32536	237	9	,	,	PUNCT
ajst-32536	237	10	73	73	NUM
ajst-32536	237	11	:	:	SYM
ajst-32536	237	12	1	1	NUM
ajst-32536	237	13	-	-	SYM
ajst-32536	237	14	14	14	NUM
ajst-32536	237	15	.	.	PUNCT
ajst-32536	238	1	[	[	X
ajst-32536	238	2	23	23	NUM
ajst-32536	238	3	]	]	X
ajst-32536	238	4	chauhan	chauhan	PROPN
ajst-32536	238	5	m	m	PROPN
ajst-32536	238	6	k	k	PROPN
ajst-32536	238	7	,	,	PUNCT
ajst-32536	238	8	ghosal	ghosal	PROPN
ajst-32536	238	9	p.	p.	PROPN
ajst-32536	238	10	a	a	DET
ajst-32536	238	11	hybrid	hybrid	ADJ
ajst-32536	238	12	cnn	cnn	PROPN
ajst-32536	238	13	-	-	PUNCT
ajst-32536	238	14	bilstm	bilstm	NOUN
ajst-32536	238	15	neural	neural	ADJ
ajst-32536	238	16	network	network	NOUN
ajst-32536	238	17	architecture	architecture	NOUN
ajst-32536	238	18	for	for	ADP
ajst-32536	238	19	early	early	ADJ
ajst-32536	238	20	prediction	prediction	NOUN
ajst-32536	238	21	of	of	ADP
ajst-32536	238	22	parkinson	parkinson	NOUN
ajst-32536	238	23	's	's	PART
ajst-32536	238	24	disease[c]//2024	disease[c]//2024	PROPN
ajst-32536	238	25	ieee	ieee	NOUN
ajst-32536	238	26	international	international	ADJ
ajst-32536	238	27	symposium	symposium	NOUN
ajst-32536	238	28	on	on	ADP
ajst-32536	238	29	smart	smart	ADJ
ajst-32536	238	30	electronic	electronic	ADJ
ajst-32536	238	31	systems	system	NOUN
ajst-32536	238	32	(	(	PUNCT
ajst-32536	238	33	ises	ise	NOUN
ajst-32536	238	34	)	)	PUNCT
ajst-32536	238	35	.	.	PUNCT
ajst-32536	239	1	ieee	ieee	NOUN
ajst-32536	239	2	,	,	PUNCT
ajst-32536	239	3	2024	2024	NUM
ajst-32536	239	4	:	:	PUNCT
ajst-32536	239	5	303	303	NUM
ajst-32536	239	6	-	-	SYM
ajst-32536	239	7	308	308	NUM
ajst-32536	239	8	.	.	PUNCT
ajst-32536	240	1	[	[	X
ajst-32536	240	2	24	24	NUM
ajst-32536	240	3	]	]	PUNCT
ajst-32536	240	4	neves	neve	NOUN
ajst-32536	240	5	c	c	PROPN
ajst-32536	240	6	,	,	PUNCT
ajst-32536	240	7	zeng	zeng	PROPN
ajst-32536	240	8	y	y	PROPN
ajst-32536	240	9	,	,	PUNCT
ajst-32536	240	10	xiao	xiao	PROPN
ajst-32536	240	11	y.	y.	PROPN
ajst-32536	240	12	parkinson	parkinson	PROPN
ajst-32536	240	13	’s	’s	PART
ajst-32536	240	14	disease	disease	NOUN
ajst-32536	240	15	detection	detection	NOUN
ajst-32536	240	16	from	from	ADP
ajst-32536	240	17	resting	rest	VERB
ajst-32536	240	18	state	state	NOUN
ajst-32536	240	19	eeg	eeg	NOUN
ajst-32536	240	20	using	use	VERB
ajst-32536	240	21	multi	multi	ADJ
ajst-32536	240	22	-	-	ADJ
ajst-32536	240	23	head	head	ADJ
ajst-32536	240	24	graph	graph	NOUN
ajst-32536	240	25	structure	structure	NOUN
ajst-32536	240	26	learning	learn	VERB
ajst-32536	240	27	with	with	ADP
ajst-32536	240	28	gradient	gradient	NOUN
ajst-32536	240	29	weighted	weight	VERB
ajst-32536	240	30	graph	graph	NOUN
ajst-32536	240	31	attention	attention	NOUN
ajst-32536	240	32	explanations[c]//international	explanations[c]//international	ADJ
ajst-32536	240	33	workshop	workshop	NOUN
ajst-32536	240	34	on	on	ADP
ajst-32536	240	35	machine	machine	NOUN
ajst-32536	240	36	learning	learning	NOUN
ajst-32536	240	37	in	in	ADP
ajst-32536	240	38	clinical	clinical	ADJ
ajst-32536	240	39	neuroimaging	neuroimaging	NOUN
ajst-32536	240	40	.	.	PUNCT
ajst-32536	241	1	cham	cham	PROPN
ajst-32536	241	2	:	:	PUNCT
ajst-32536	241	3	springer	springer	NOUN
ajst-32536	241	4	nature	nature	PROPN
ajst-32536	241	5	switzerland	switzerland	PROPN
ajst-32536	241	6	,	,	PUNCT
ajst-32536	241	7	2024	2024	NUM
ajst-32536	241	8	:	:	PUNCT
ajst-32536	241	9	3	3	NUM
ajst-32536	241	10	-	-	SYM
ajst-32536	241	11	12	12	NUM
ajst-32536	241	12	.	.	PUNCT
ajst-32536	242	1	[	[	X
ajst-32536	242	2	25	25	NUM
ajst-32536	242	3	]	]	X
ajst-32536	242	4	rizvi	rizvi	PROPN
ajst-32536	242	5	s	s	PART
ajst-32536	242	6	q	q	NOUN
ajst-32536	242	7	a	a	PROPN
ajst-32536	242	8	,	,	PUNCT
ajst-32536	242	9	wang	wang	PROPN
ajst-32536	242	10	g	g	PROPN
ajst-32536	242	11	,	,	PUNCT
ajst-32536	242	12	khan	khan	PROPN
ajst-32536	242	13	a	a	PROPN
ajst-32536	242	14	,	,	PUNCT
ajst-32536	242	15	et	et	PROPN
ajst-32536	242	16	al	al	PROPN
ajst-32536	242	17	.	.	PUNCT
ajst-32536	243	1	classifying	classify	VERB
ajst-32536	243	2	parkinson	parkinson	NOUN
ajst-32536	243	3	’s	’s	PART
ajst-32536	243	4	disease	disease	NOUN
ajst-32536	243	5	using	use	VERB
ajst-32536	243	6	resting	rest	VERB
ajst-32536	243	7	state	state	NOUN
ajst-32536	243	8	electroencephalogram	electroencephalogram	NOUN
ajst-32536	243	9	signals	signal	NOUN
ajst-32536	243	10	and	and	CCONJ
ajst-32536	243	11	u	u	NOUN
ajst-32536	243	12	en	en	NOUN
ajst-32536	243	13	-	-	NOUN
ajst-32536	243	14	pdnet[j	pdnet[j	NOUN
ajst-32536	243	15	]	]	X
ajst-32536	243	16	.	.	PUNCT
ajst-32536	244	1	ieee	ieee	NOUN
ajst-32536	244	2	access	access	NOUN
ajst-32536	244	3	,	,	PUNCT
ajst-32536	244	4	2023	2023	NUM
ajst-32536	244	5	,	,	PUNCT
ajst-32536	244	6	11	11	NUM
ajst-32536	244	7	:	:	SYM
ajst-32536	244	8	107703	107703	NUM
ajst-32536	244	9	-	-	SYM
ajst-32536	244	10	107724	107724	NUM
ajst-32536	244	11	.	.	PUNCT
ajst-32536	245	1	[	[	X
ajst-32536	245	2	26	26	NUM
ajst-32536	245	3	]	]	X
ajst-32536	245	4	afonso	afonso	PROPN
ajst-32536	245	5	m	m	VERB
ajst-32536	245	6	m	m	PROPN
ajst-32536	245	7	,	,	PUNCT
ajst-32536	245	8	edla	edla	PROPN
ajst-32536	245	9	d	d	PROPN
ajst-32536	245	10	r	r	PROPN
ajst-32536	245	11	,	,	PUNCT
ajst-32536	245	12	ramesh	ramesh	PROPN
ajst-32536	245	13	d.	d.	PROPN
ajst-32536	245	14	transformers	transformers	PROPN
ajst-32536	245	15	-	-	PUNCT
ajst-32536	245	16	based	base	VERB
ajst-32536	245	17	deep	deep	ADJ
ajst-32536	245	18	learning	learning	NOUN
ajst-32536	245	19	for	for	ADP
ajst-32536	245	20	parkinson	parkinson	NOUN
ajst-32536	245	21	’s	’s	PART
ajst-32536	245	22	disease	disease	NOUN
ajst-32536	245	23	detection	detection	NOUN
ajst-32536	245	24	using	use	VERB
ajst-32536	245	25	electroencephalography	electroencephalography	NOUN
ajst-32536	245	26	and	and	CCONJ
ajst-32536	245	27	stockwell	stockwell	PROPN
ajst-32536	245	28	transform[j	transform[j	PROPN
ajst-32536	245	29	]	]	PUNCT
ajst-32536	245	30	.	.	PUNCT
ajst-32536	246	1	procedia	procedia	PROPN
ajst-32536	246	2	computer	computer	NOUN
ajst-32536	246	3	science	science	NOUN
ajst-32536	246	4	,	,	PUNCT
ajst-32536	246	5	2025	2025	NUM
ajst-32536	246	6	,	,	PUNCT
ajst-32536	246	7	258	258	NUM
ajst-32536	246	8	:	:	SYM
ajst-32536	246	9	4094	4094	NUM
ajst-32536	246	10	-	-	SYM
ajst-32536	246	11	4104	4104	NUM
ajst-32536	246	12	.	.	PUNCT