id	sid	tid	token	lemma	pos
fcis-28019	1	1	frontiers	frontier	NOUN
fcis-28019	1	2	in	in	ADP
fcis-28019	1	3	computing	computing	NOUN
fcis-28019	1	4	and	and	CCONJ
fcis-28019	1	5	intelligent	intelligent	ADJ
fcis-28019	1	6	systems	system	NOUN
fcis-28019	1	7	issn	issn	VERB
fcis-28019	1	8	:	:	PUNCT
fcis-28019	1	9	2832	2832	NUM
fcis-28019	1	10	-	-	SYM
fcis-28019	1	11	6024	6024	NUM
fcis-28019	1	12	|	|	NOUN
fcis-28019	1	13	vol	vol	NOUN
fcis-28019	1	14	.	.	PROPN
fcis-28019	2	1	10	10	NUM
fcis-28019	2	2	,	,	PUNCT
fcis-28019	2	3	no	no	INTJ
fcis-28019	2	4	.	.	NOUN
fcis-28019	2	5	3	3	NUM
fcis-28019	2	6	,	,	PUNCT
fcis-28019	2	7	2024	2024	NUM
fcis-28019	2	8	15	15	NUM
fcis-28019	2	9	parkinson	parkinson	NOUN
fcis-28019	2	10	's	's	PART
fcis-28019	2	11	disease	disease	NOUN
fcis-28019	2	12	speech	speech	NOUN
fcis-28019	2	13	classification	classification	NOUN
fcis-28019	2	14	using	use	VERB
fcis-28019	2	15	1d	1d	NUM
fcis-28019	2	16	convolutional	convolutional	ADJ
fcis-28019	2	17	neural	neural	ADJ
fcis-28019	2	18	networks	network	NOUN
fcis-28019	2	19	zhen	zhen	PROPN
fcis-28019	2	20	yue	yue	PROPN
fcis-28019	2	21	1	1	NUM
fcis-28019	2	22	,	,	PUNCT
fcis-28019	2	23	haiyang	haiyang	PROPN
fcis-28019	2	24	wang	wang	PROPN
fcis-28019	2	25	2	2	NUM
fcis-28019	2	26	1	1	NUM
fcis-28019	2	27	school	school	NOUN
fcis-28019	2	28	of	of	ADP
fcis-28019	2	29	information	information	NOUN
fcis-28019	2	30	and	and	CCONJ
fcis-28019	2	31	control	control	PROPN
fcis-28019	2	32	engineering	engineering	PROPN
fcis-28019	2	33	,	,	PUNCT
fcis-28019	2	34	jilin	jilin	PROPN
fcis-28019	2	35	institute	institute	PROPN
fcis-28019	2	36	of	of	ADP
fcis-28019	2	37	chemical	chemical	PROPN
fcis-28019	2	38	technology	technology	PROPN
fcis-28019	2	39	,	,	PUNCT
fcis-28019	2	40	jilin	jilin	PROPN
fcis-28019	2	41	jilin	jilin	PROPN
fcis-28019	2	42	,	,	PUNCT
fcis-28019	2	43	132021	132021	NUM
fcis-28019	2	44	,	,	PUNCT
fcis-28019	2	45	china	china	PROPN
fcis-28019	2	46	2	2	NUM
fcis-28019	2	47	school	school	NOUN
fcis-28019	2	48	of	of	ADP
fcis-28019	2	49	mechanical	mechanical	ADJ
fcis-28019	2	50	and	and	CCONJ
fcis-28019	2	51	control	control	PROPN
fcis-28019	2	52	engineering	engineering	NOUN
fcis-28019	2	53	,	,	PUNCT
fcis-28019	2	54	baicheng	baicheng	PROPN
fcis-28019	2	55	normal	normal	ADJ
fcis-28019	2	56	university	university	NOUN
fcis-28019	2	57	,	,	PUNCT
fcis-28019	2	58	baicheng	baicheng	PROPN
fcis-28019	2	59	jilin	jilin	PROPN
fcis-28019	2	60	,	,	PUNCT
fcis-28019	2	61	137000	137000	NUM
fcis-28019	2	62	,	,	PUNCT
fcis-28019	2	63	china	china	PROPN
fcis-28019	2	64	abstract	abstract	NOUN
fcis-28019	2	65	:	:	PUNCT
fcis-28019	2	66	parkinson	parkinson	NOUN
fcis-28019	2	67	's	's	PART
fcis-28019	2	68	disease	disease	NOUN
fcis-28019	2	69	(	(	PUNCT
fcis-28019	2	70	pd	pd	NOUN
fcis-28019	2	71	)	)	PUNCT
fcis-28019	2	72	is	be	AUX
fcis-28019	2	73	a	a	DET
fcis-28019	2	74	neurodegenerative	neurodegenerative	ADJ
fcis-28019	2	75	disorder	disorder	NOUN
fcis-28019	2	76	caused	cause	VERB
fcis-28019	2	77	by	by	ADP
fcis-28019	2	78	a	a	DET
fcis-28019	2	79	lack	lack	NOUN
fcis-28019	2	80	of	of	ADP
fcis-28019	2	81	dopamine	dopamine	NOUN
fcis-28019	2	82	secretion	secretion	NOUN
fcis-28019	2	83	.	.	PUNCT
fcis-28019	3	1	both	both	PRON
fcis-28019	3	2	motor	motor	NOUN
fcis-28019	3	3	and	and	CCONJ
fcis-28019	3	4	non	non	ADJ
fcis-28019	3	5	-	-	ADJ
fcis-28019	3	6	motor	motor	ADJ
fcis-28019	3	7	activities	activity	NOUN
fcis-28019	3	8	of	of	ADP
fcis-28019	3	9	parkinson	parkinson	NOUN
fcis-28019	3	10	's	's	PART
fcis-28019	3	11	patients	patient	NOUN
fcis-28019	3	12	are	be	AUX
fcis-28019	3	13	affected	affect	VERB
fcis-28019	3	14	.	.	PUNCT
fcis-28019	4	1	this	this	DET
fcis-28019	4	2	study	study	NOUN
fcis-28019	4	3	proposes	propose	VERB
fcis-28019	4	4	a	a	DET
fcis-28019	4	5	method	method	NOUN
fcis-28019	4	6	for	for	ADP
fcis-28019	4	7	parkinson	parkinson	NOUN
fcis-28019	4	8	's	's	PART
fcis-28019	4	9	disease	disease	NOUN
fcis-28019	4	10	audio	audio	NOUN
fcis-28019	4	11	feature	feature	NOUN
fcis-28019	4	12	classification	classification	NOUN
fcis-28019	4	13	based	base	VERB
fcis-28019	4	14	on	on	ADP
fcis-28019	4	15	convolutional	convolutional	ADJ
fcis-28019	4	16	neural	neural	ADJ
fcis-28019	4	17	networks	network	NOUN
fcis-28019	4	18	(	(	PUNCT
fcis-28019	4	19	cnn	cnn	PROPN
fcis-28019	4	20	)	)	PUNCT
fcis-28019	4	21	.	.	PUNCT
fcis-28019	5	1	by	by	ADP
fcis-28019	5	2	extracting	extract	VERB
fcis-28019	5	3	features	feature	NOUN
fcis-28019	5	4	from	from	ADP
fcis-28019	5	5	the	the	DET
fcis-28019	5	6	speech	speech	NOUN
fcis-28019	5	7	signals	signal	NOUN
fcis-28019	5	8	of	of	ADP
fcis-28019	5	9	parkinson	parkinson	NOUN
fcis-28019	5	10	's	's	PART
fcis-28019	5	11	patients	patient	NOUN
fcis-28019	5	12	,	,	PUNCT
fcis-28019	5	13	and	and	CCONJ
fcis-28019	5	14	leveraging	leverage	VERB
fcis-28019	5	15	the	the	DET
fcis-28019	5	16	powerful	powerful	ADJ
fcis-28019	5	17	feature	feature	NOUN
fcis-28019	5	18	extraction	extraction	NOUN
fcis-28019	5	19	and	and	CCONJ
fcis-28019	5	20	classification	classification	NOUN
fcis-28019	5	21	capabilities	capability	NOUN
fcis-28019	5	22	of	of	ADP
fcis-28019	5	23	cnns	cnn	NOUN
fcis-28019	5	24	,	,	PUNCT
fcis-28019	5	25	an	an	DET
fcis-28019	5	26	efficient	efficient	ADJ
fcis-28019	5	27	diagnosis	diagnosis	NOUN
fcis-28019	5	28	of	of	ADP
fcis-28019	5	29	parkinson	parkinson	NOUN
fcis-28019	5	30	's	's	PART
fcis-28019	5	31	disease	disease	NOUN
fcis-28019	5	32	can	can	AUX
fcis-28019	5	33	be	be	AUX
fcis-28019	5	34	achieved	achieve	VERB
fcis-28019	5	35	.	.	PUNCT
fcis-28019	6	1	to	to	PART
fcis-28019	6	2	evaluate	evaluate	VERB
fcis-28019	6	3	the	the	DET
fcis-28019	6	4	performance	performance	NOUN
fcis-28019	6	5	of	of	ADP
fcis-28019	6	6	the	the	DET
fcis-28019	6	7	proposed	propose	VERB
fcis-28019	6	8	method	method	NOUN
fcis-28019	6	9	,	,	PUNCT
fcis-28019	6	10	experiments	experiment	NOUN
fcis-28019	6	11	were	be	AUX
fcis-28019	6	12	conducted	conduct	VERB
fcis-28019	6	13	on	on	ADP
fcis-28019	6	14	two	two	NUM
fcis-28019	6	15	datasets	dataset	NOUN
fcis-28019	6	16	,	,	PUNCT
fcis-28019	6	17	achieving	achieve	VERB
fcis-28019	6	18	accuracy	accuracy	NOUN
fcis-28019	6	19	rates	rate	NOUN
fcis-28019	6	20	of	of	ADP
fcis-28019	6	21	100	100	NUM
fcis-28019	6	22	%	%	NOUN
fcis-28019	6	23	and	and	CCONJ
fcis-28019	6	24	92.86	92.86	NUM
fcis-28019	6	25	%	%	NOUN
fcis-28019	6	26	,	,	PUNCT
fcis-28019	6	27	respectively	respectively	ADV
fcis-28019	6	28	.	.	PUNCT
fcis-28019	7	1	keywords	keyword	NOUN
fcis-28019	7	2	:	:	PUNCT
fcis-28019	7	3	parkinson	parkinson	NOUN
fcis-28019	7	4	disease	disease	NOUN
fcis-28019	7	5	;	;	PUNCT
fcis-28019	7	6	speech	speech	NOUN
fcis-28019	7	7	features	feature	NOUN
fcis-28019	7	8	;	;	PUNCT
fcis-28019	7	9	convolutional	convolutional	ADJ
fcis-28019	7	10	neural	neural	ADJ
fcis-28019	7	11	networks	network	NOUN
fcis-28019	7	12	.	.	PUNCT
fcis-28019	8	1	1	1	X
fcis-28019	8	2	.	.	X
fcis-28019	8	3	introduction	introduction	NOUN
fcis-28019	8	4	parkinson	parkinson	NOUN
fcis-28019	8	5	's	's	PART
fcis-28019	8	6	disease	disease	NOUN
fcis-28019	8	7	(	(	PUNCT
fcis-28019	8	8	pd	pd	NOUN
fcis-28019	8	9	)	)	PUNCT
fcis-28019	8	10	is	be	AUX
fcis-28019	8	11	a	a	DET
fcis-28019	8	12	common	common	ADJ
fcis-28019	8	13	neurodegenerative	neurodegenerative	ADJ
fcis-28019	8	14	disorder	disorder	NOUN
fcis-28019	8	15	characterized	characterize	VERB
fcis-28019	8	16	by	by	ADP
fcis-28019	8	17	motor	motor	NOUN
fcis-28019	8	18	impairments	impairment	NOUN
fcis-28019	8	19	,	,	PUNCT
fcis-28019	8	20	tremors	tremor	NOUN
fcis-28019	8	21	,	,	PUNCT
fcis-28019	8	22	muscle	muscle	NOUN
fcis-28019	8	23	rigidity	rigidity	NOUN
fcis-28019	8	24	,	,	PUNCT
fcis-28019	8	25	as	as	ADV
fcis-28019	8	26	well	well	ADV
fcis-28019	8	27	as	as	ADP
fcis-28019	8	28	speech	speech	NOUN
fcis-28019	8	29	and	and	CCONJ
fcis-28019	8	30	gait	gait	NOUN
fcis-28019	8	31	problems	problem	NOUN
fcis-28019	8	32	.	.	PUNCT
fcis-28019	9	1	speech	speech	NOUN
fcis-28019	9	2	features	feature	NOUN
fcis-28019	9	3	are	be	AUX
fcis-28019	9	4	one	one	NUM
fcis-28019	9	5	of	of	ADP
fcis-28019	9	6	the	the	DET
fcis-28019	9	7	common	common	ADJ
fcis-28019	9	8	symptoms	symptom	NOUN
fcis-28019	9	9	of	of	ADP
fcis-28019	9	10	pd	pd	NOUN
fcis-28019	9	11	patients	patient	NOUN
fcis-28019	9	12	,	,	PUNCT
fcis-28019	9	13	and	and	CCONJ
fcis-28019	9	14	analyzing	analyze	VERB
fcis-28019	9	15	the	the	DET
fcis-28019	9	16	speech	speech	NOUN
fcis-28019	9	17	signals	signal	NOUN
fcis-28019	9	18	of	of	ADP
fcis-28019	9	19	patients	patient	NOUN
fcis-28019	9	20	can	can	AUX
fcis-28019	9	21	provide	provide	VERB
fcis-28019	9	22	important	important	ADJ
fcis-28019	9	23	auxiliary	auxiliary	ADJ
fcis-28019	9	24	information	information	NOUN
fcis-28019	9	25	for	for	ADP
fcis-28019	9	26	early	early	ADJ
fcis-28019	9	27	diagnosis	diagnosis	NOUN
fcis-28019	9	28	of	of	ADP
fcis-28019	9	29	the	the	DET
fcis-28019	9	30	disease	disease	NOUN
fcis-28019	9	31	.	.	PUNCT
fcis-28019	10	1	traditional	traditional	ADJ
fcis-28019	10	2	parkinson	parkinson	NOUN
fcis-28019	10	3	’s	’s	PART
fcis-28019	10	4	speech	speech	NOUN
fcis-28019	10	5	diagnosis	diagnosis	NOUN
fcis-28019	10	6	methods	method	NOUN
fcis-28019	10	7	often	often	ADV
fcis-28019	10	8	rely	rely	VERB
fcis-28019	10	9	on	on	ADP
fcis-28019	10	10	the	the	DET
fcis-28019	10	11	experience	experience	NOUN
fcis-28019	10	12	of	of	ADP
fcis-28019	10	13	clinical	clinical	ADJ
fcis-28019	10	14	experts	expert	NOUN
fcis-28019	10	15	,	,	PUNCT
fcis-28019	10	16	and	and	CCONJ
fcis-28019	10	17	the	the	DET
fcis-28019	10	18	evaluation	evaluation	NOUN
fcis-28019	10	19	process	process	NOUN
fcis-28019	10	20	is	be	AUX
fcis-28019	10	21	cumbersome	cumbersome	ADJ
fcis-28019	10	22	and	and	CCONJ
fcis-28019	10	23	subjective	subjective	ADJ
fcis-28019	10	24	.	.	PUNCT
fcis-28019	11	1	in	in	ADP
fcis-28019	11	2	recent	recent	ADJ
fcis-28019	11	3	years	year	NOUN
fcis-28019	11	4	,	,	PUNCT
fcis-28019	11	5	with	with	ADP
fcis-28019	11	6	the	the	DET
fcis-28019	11	7	development	development	NOUN
fcis-28019	11	8	of	of	ADP
fcis-28019	11	9	machine	machine	NOUN
fcis-28019	11	10	learning	learning	NOUN
fcis-28019	11	11	and	and	CCONJ
fcis-28019	11	12	deep	deep	ADJ
fcis-28019	11	13	learning	learning	NOUN
fcis-28019	11	14	technologies	technology	NOUN
fcis-28019	11	15	,	,	PUNCT
fcis-28019	11	16	audio	audio	ADJ
fcis-28019	11	17	signal	signal	NOUN
fcis-28019	11	18	-	-	PUNCT
fcis-28019	11	19	based	base	VERB
fcis-28019	11	20	automated	automate	VERB
fcis-28019	11	21	diagnostic	diagnostic	ADJ
fcis-28019	11	22	methods	method	NOUN
fcis-28019	11	23	have	have	AUX
fcis-28019	11	24	gradually	gradually	ADV
fcis-28019	11	25	become	become	VERB
fcis-28019	11	26	a	a	DET
fcis-28019	11	27	research	research	NOUN
fcis-28019	11	28	hotspot	hotspot	NOUN
fcis-28019	11	29	.	.	PUNCT
fcis-28019	12	1	sakar	sakar	PROPN
fcis-28019	12	2	et	et	PROPN
fcis-28019	12	3	al	al	PROPN
fcis-28019	12	4	.	.	PUNCT
fcis-28019	13	1	[	[	X
fcis-28019	13	2	1	1	NUM
fcis-28019	13	3	]	]	X
fcis-28019	13	4	(	(	PUNCT
fcis-28019	13	5	2013	2013	NUM
fcis-28019	13	6	)	)	PUNCT
fcis-28019	13	7	used	use	VERB
fcis-28019	13	8	a	a	DET
fcis-28019	13	9	knn+svm	knn+svm	ADJ
fcis-28019	13	10	approach	approach	NOUN
fcis-28019	13	11	for	for	ADP
fcis-28019	13	12	classification	classification	NOUN
fcis-28019	13	13	.	.	PUNCT
fcis-28019	14	1	naranjo	naranjo	PROPN
fcis-28019	14	2	et	et	PROPN
fcis-28019	14	3	al	al	PROPN
fcis-28019	14	4	.	.	PUNCT
fcis-28019	15	1	[	[	X
fcis-28019	15	2	2	2	NUM
fcis-28019	15	3	]	]	PUNCT
fcis-28019	15	4	(	(	PUNCT
fcis-28019	15	5	2016	2016	NUM
fcis-28019	15	6	)	)	PUNCT
fcis-28019	15	7	proposed	propose	VERB
fcis-28019	15	8	a	a	DET
fcis-28019	15	9	clinical	clinical	ADJ
fcis-28019	15	10	expert	expert	NOUN
fcis-28019	15	11	system	system	NOUN
fcis-28019	15	12	based	base	VERB
fcis-28019	15	13	on	on	ADP
fcis-28019	15	14	bayesian	bayesian	NOUN
fcis-28019	15	15	methods	method	NOUN
fcis-28019	15	16	for	for	ADP
fcis-28019	15	17	detecting	detect	VERB
fcis-28019	15	18	parkinson	parkinson	NOUN
fcis-28019	15	19	's	's	PART
fcis-28019	15	20	disease	disease	NOUN
fcis-28019	15	21	,	,	PUNCT
fcis-28019	15	22	achieving	achieve	VERB
fcis-28019	15	23	an	an	DET
fcis-28019	15	24	accuracy	accuracy	NOUN
fcis-28019	15	25	of	of	ADP
fcis-28019	15	26	75.20	75.20	NUM
fcis-28019	15	27	%	%	NOUN
fcis-28019	15	28	.	.	PUNCT
fcis-28019	16	1	ali	ali	PROPN
fcis-28019	16	2	et	et	PROPN
fcis-28019	16	3	al	al	PROPN
fcis-28019	16	4	.	.	PUNCT
fcis-28019	17	1	[	[	X
fcis-28019	17	2	3	3	NUM
fcis-28019	17	3	]	]	PUNCT
fcis-28019	17	4	(	(	PUNCT
fcis-28019	17	5	2019	2019	NUM
fcis-28019	17	6	)	)	PUNCT
fcis-28019	17	7	applied	apply	VERB
fcis-28019	17	8	the	the	DET
fcis-28019	17	9	chi	chi	ADJ
fcis-28019	17	10	-	-	PUNCT
fcis-28019	17	11	square	square	ADJ
fcis-28019	17	12	statistical	statistical	ADJ
fcis-28019	17	13	feature	feature	NOUN
fcis-28019	17	14	selection	selection	NOUN
fcis-28019	17	15	method	method	NOUN
fcis-28019	17	16	to	to	PART
fcis-28019	17	17	select	select	VERB
fcis-28019	17	18	the	the	DET
fcis-28019	17	19	best	good	ADJ
fcis-28019	17	20	features	feature	NOUN
fcis-28019	17	21	from	from	ADP
fcis-28019	17	22	parkinson	parkinson	NOUN
fcis-28019	17	23	’s	’s	PART
fcis-28019	17	24	disease	disease	NOUN
fcis-28019	17	25	datasets	dataset	NOUN
fcis-28019	17	26	,	,	PUNCT
fcis-28019	17	27	achieving	achieve	VERB
fcis-28019	17	28	an	an	DET
fcis-28019	17	29	accuracy	accuracy	NOUN
fcis-28019	17	30	of	of	ADP
fcis-28019	17	31	100	100	NUM
fcis-28019	17	32	%	%	NOUN
fcis-28019	17	33	.	.	PUNCT
fcis-28019	18	1	traditional	traditional	ADJ
fcis-28019	18	2	diagnostic	diagnostic	ADJ
fcis-28019	18	3	methods	method	NOUN
fcis-28019	18	4	mainly	mainly	ADV
fcis-28019	18	5	rely	rely	VERB
fcis-28019	18	6	on	on	ADP
fcis-28019	18	7	the	the	DET
fcis-28019	18	8	clinical	clinical	ADJ
fcis-28019	18	9	experience	experience	NOUN
fcis-28019	18	10	of	of	ADP
fcis-28019	18	11	doctors	doctor	NOUN
fcis-28019	18	12	and	and	CCONJ
fcis-28019	18	13	physical	physical	ADJ
fcis-28019	18	14	examinations	examination	NOUN
fcis-28019	18	15	of	of	ADP
fcis-28019	18	16	patients	patient	NOUN
fcis-28019	18	17	,	,	PUNCT
fcis-28019	18	18	but	but	CCONJ
fcis-28019	18	19	these	these	DET
fcis-28019	18	20	methods	method	NOUN
fcis-28019	18	21	often	often	ADV
fcis-28019	18	22	suffer	suffer	VERB
fcis-28019	18	23	from	from	ADP
fcis-28019	18	24	subjectivity	subjectivity	NOUN
fcis-28019	18	25	and	and	CCONJ
fcis-28019	18	26	long	long	ADJ
fcis-28019	18	27	diagnostic	diagnostic	ADJ
fcis-28019	18	28	periods	period	NOUN
fcis-28019	18	29	.	.	PUNCT
fcis-28019	19	1	in	in	ADP
fcis-28019	19	2	contrast	contrast	NOUN
fcis-28019	19	3	,	,	PUNCT
fcis-28019	19	4	audio	audio	ADJ
fcis-28019	19	5	signal	signal	NOUN
fcis-28019	19	6	-	-	PUNCT
fcis-28019	19	7	based	base	VERB
fcis-28019	19	8	diagnostic	diagnostic	ADJ
fcis-28019	19	9	methods	method	NOUN
fcis-28019	19	10	can	can	AUX
fcis-28019	19	11	quickly	quickly	ADV
fcis-28019	19	12	and	and	CCONJ
fcis-28019	19	13	objectively	objectively	ADV
fcis-28019	19	14	assess	assess	VERB
fcis-28019	19	15	the	the	DET
fcis-28019	19	16	health	health	NOUN
fcis-28019	19	17	status	status	NOUN
fcis-28019	19	18	of	of	ADP
fcis-28019	19	19	patients	patient	NOUN
fcis-28019	19	20	by	by	ADP
fcis-28019	19	21	analyzing	analyze	VERB
fcis-28019	19	22	their	their	PRON
fcis-28019	19	23	speech	speech	NOUN
fcis-28019	19	24	features	feature	NOUN
fcis-28019	19	25	,	,	PUNCT
fcis-28019	19	26	offering	offer	VERB
fcis-28019	19	27	great	great	ADJ
fcis-28019	19	28	potential	potential	NOUN
fcis-28019	19	29	.	.	PUNCT
fcis-28019	20	1	researchers	researcher	NOUN
fcis-28019	20	2	can	can	AUX
fcis-28019	20	3	effectively	effectively	ADV
fcis-28019	20	4	use	use	VERB
fcis-28019	20	5	machine	machine	NOUN
fcis-28019	20	6	learning	learning	NOUN
fcis-28019	20	7	and	and	CCONJ
fcis-28019	20	8	related	related	ADJ
fcis-28019	20	9	algorithms	algorithm	NOUN
fcis-28019	20	10	to	to	PART
fcis-28019	20	11	perform	perform	VERB
fcis-28019	20	12	early	early	ADJ
fcis-28019	20	13	diagnosis	diagnosis	NOUN
fcis-28019	20	14	of	of	ADP
fcis-28019	20	15	parkinson	parkinson	NOUN
fcis-28019	20	16	's	's	PART
fcis-28019	20	17	disease	disease	NOUN
fcis-28019	20	18	,	,	PUNCT
fcis-28019	20	19	monitor	monitor	VERB
fcis-28019	20	20	disease	disease	NOUN
fcis-28019	20	21	progression	progression	NOUN
fcis-28019	20	22	,	,	PUNCT
fcis-28019	20	23	and	and	CCONJ
fcis-28019	20	24	provide	provide	VERB
fcis-28019	20	25	personalized	personalized	ADJ
fcis-28019	20	26	treatment	treatment	NOUN
fcis-28019	20	27	plans	plan	NOUN
fcis-28019	20	28	,	,	PUNCT
fcis-28019	20	29	thus	thus	ADV
fcis-28019	20	30	offering	offer	VERB
fcis-28019	20	31	new	new	ADJ
fcis-28019	20	32	possibilities	possibility	NOUN
fcis-28019	20	33	for	for	ADP
fcis-28019	20	34	early	early	ADJ
fcis-28019	20	35	intervention	intervention	NOUN
fcis-28019	20	36	of	of	ADP
fcis-28019	20	37	parkinson	parkinson	NOUN
fcis-28019	20	38	’s	’s	PART
fcis-28019	20	39	disease	disease	NOUN
fcis-28019	20	40	.	.	PUNCT
fcis-28019	21	1	2	2	X
fcis-28019	21	2	.	.	X
fcis-28019	21	3	dataset	dataset	NOUN
fcis-28019	21	4	and	and	CCONJ
fcis-28019	21	5	preprocessing	preprocesse	VERB
fcis-28019	21	6	2.1	2.1	NUM
fcis-28019	21	7	.	.	PUNCT
fcis-28019	22	1	dataset	dataset	VERB
fcis-28019	22	2	dataset1	dataset1	NOUN
fcis-28019	23	1	this	this	DET
fcis-28019	23	2	dataset	dataset	NOUN
fcis-28019	23	3	was	be	AUX
fcis-28019	23	4	collected	collect	VERB
fcis-28019	23	5	in	in	ADP
fcis-28019	23	6	collaboration	collaboration	NOUN
fcis-28019	23	7	between	between	ADP
fcis-28019	23	8	professor	professor	NOUN
fcis-28019	23	9	max	max	PROPN
fcis-28019	23	10	little	little	ADV
fcis-28019	23	11	from	from	ADP
fcis-28019	23	12	oxford	oxford	PROPN
fcis-28019	23	13	university	university	PROPN
fcis-28019	23	14	and	and	CCONJ
fcis-28019	23	15	the	the	DET
fcis-28019	23	16	national	national	ADJ
fcis-28019	23	17	centre	centre	NOUN
fcis-28019	23	18	for	for	ADP
fcis-28019	23	19	voice	voice	NOUN
fcis-28019	23	20	and	and	CCONJ
fcis-28019	23	21	speech	speech	NOUN
fcis-28019	23	22	(	(	PUNCT
fcis-28019	23	23	little	little	ADJ
fcis-28019	23	24	et	et	PROPN
fcis-28019	23	25	al	al	PROPN
fcis-28019	23	26	.	.	PROPN
fcis-28019	23	27	,	,	PUNCT
fcis-28019	23	28	2007	2007	NUM
fcis-28019	23	29	)	)	PUNCT
fcis-28019	23	30	.	.	PUNCT
fcis-28019	24	1	it	it	PRON
fcis-28019	24	2	contains	contain	VERB
fcis-28019	24	3	195	195	NUM
fcis-28019	24	4	speech	speech	NOUN
fcis-28019	24	5	recording	recording	NOUN
fcis-28019	24	6	samples	sample	NOUN
fcis-28019	24	7	from	from	ADP
fcis-28019	24	8	31	31	NUM
fcis-28019	24	9	individuals	individual	NOUN
fcis-28019	24	10	,	,	PUNCT
fcis-28019	24	11	23	23	NUM
fcis-28019	24	12	of	of	ADP
fcis-28019	24	13	whom	whom	PRON
fcis-28019	24	14	are	be	AUX
fcis-28019	24	15	parkinson	parkinson	NOUN
fcis-28019	24	16	’s	’s	PART
fcis-28019	24	17	disease	disease	NOUN
fcis-28019	24	18	(	(	PUNCT
fcis-28019	24	19	pd	pd	NOUN
fcis-28019	24	20	)	)	PUNCT
fcis-28019	24	21	patients	patient	NOUN
fcis-28019	24	22	.	.	PUNCT
fcis-28019	25	1	each	each	DET
fcis-28019	25	2	individual	individual	NOUN
fcis-28019	25	3	has	have	VERB
fcis-28019	25	4	approximately	approximately	ADV
fcis-28019	25	5	6	6	NUM
fcis-28019	25	6	recordings	recording	NOUN
fcis-28019	25	7	,	,	PUNCT
fcis-28019	25	8	with	with	ADP
fcis-28019	25	9	each	each	DET
fcis-28019	25	10	recording	recording	NOUN
fcis-28019	25	11	having	have	VERB
fcis-28019	25	12	22	22	NUM
fcis-28019	25	13	speech	speech	NOUN
fcis-28019	25	14	-	-	PUNCT
fcis-28019	25	15	related	relate	VERB
fcis-28019	25	16	features	feature	NOUN
fcis-28019	25	17	.	.	PUNCT
fcis-28019	26	1	dataset2	dataset2	NOUN
fcis-28019	26	2	this	this	DET
fcis-28019	26	3	dataset	dataset	NOUN
fcis-28019	26	4	includes	include	VERB
fcis-28019	26	5	speech	speech	NOUN
fcis-28019	26	6	recordings	recording	NOUN
fcis-28019	26	7	from	from	ADP
fcis-28019	26	8	40	40	NUM
fcis-28019	26	9	individuals	individual	NOUN
fcis-28019	26	10	(	(	PUNCT
fcis-28019	26	11	20	20	NUM
fcis-28019	26	12	pd	pd	NOUN
fcis-28019	26	13	patients	patient	NOUN
fcis-28019	26	14	and	and	CCONJ
fcis-28019	26	15	20	20	NUM
fcis-28019	26	16	healthy	healthy	ADJ
fcis-28019	26	17	individuals	individual	NOUN
fcis-28019	26	18	)	)	PUNCT
fcis-28019	26	19	recorded	record	VERB
fcis-28019	26	20	at	at	ADP
fcis-28019	26	21	the	the	DET
fcis-28019	26	22	neurology	neurology	NOUN
fcis-28019	26	23	department	department	NOUN
fcis-28019	26	24	of	of	ADP
fcis-28019	26	25	the	the	DET
fcis-28019	26	26	cerrahpaşa	cerrahpaşa	PROPN
fcis-28019	26	27	medical	medical	PROPN
fcis-28019	26	28	faculty	faculty	PROPN
fcis-28019	26	29	,	,	PUNCT
fcis-28019	26	30	istanbul	istanbul	PROPN
fcis-28019	26	31	university	university	PROPN
fcis-28019	26	32	(	(	PUNCT
fcis-28019	26	33	sakar	sakar	PROPN
fcis-28019	26	34	et	et	PROPN
fcis-28019	26	35	al	al	PROPN
fcis-28019	26	36	.	.	PROPN
fcis-28019	26	37	,	,	PUNCT
fcis-28019	26	38	2013	2013	NUM
fcis-28019	26	39	)	)	PUNCT
fcis-28019	26	40	.	.	PUNCT
fcis-28019	27	1	the	the	DET
fcis-28019	27	2	dataset	dataset	NOUN
fcis-28019	27	3	contains	contain	VERB
fcis-28019	27	4	1040	1040	NUM
fcis-28019	27	5	samples	sample	NOUN
fcis-28019	27	6	,	,	PUNCT
fcis-28019	27	7	including	include	VERB
fcis-28019	27	8	sentences	sentence	NOUN
fcis-28019	27	9	,	,	PUNCT
fcis-28019	27	10	vowels	vowel	NOUN
fcis-28019	27	11	,	,	PUNCT
fcis-28019	27	12	numbers	number	NOUN
fcis-28019	27	13	,	,	PUNCT
fcis-28019	27	14	and	and	CCONJ
fcis-28019	27	15	words	word	NOUN
fcis-28019	27	16	.	.	PUNCT
fcis-28019	28	1	it	it	PRON
fcis-28019	28	2	consists	consist	VERB
fcis-28019	28	3	of	of	ADP
fcis-28019	28	4	two	two	NUM
fcis-28019	28	5	independent	independent	ADJ
fcis-28019	28	6	training	training	NOUN
fcis-28019	28	7	and	and	CCONJ
fcis-28019	28	8	testing	testing	NOUN
fcis-28019	28	9	files	file	NOUN
fcis-28019	28	10	.	.	PUNCT
fcis-28019	29	1	the	the	DET
fcis-28019	29	2	training	training	NOUN
fcis-28019	29	3	set	set	NOUN
fcis-28019	29	4	contains	contain	VERB
fcis-28019	29	5	multiple	multiple	ADJ
fcis-28019	29	6	speech	speech	NOUN
fcis-28019	29	7	recordings	recording	NOUN
fcis-28019	29	8	,	,	PUNCT
fcis-28019	29	9	while	while	SCONJ
fcis-28019	29	10	the	the	DET
fcis-28019	29	11	testing	testing	NOUN
fcis-28019	29	12	set	set	NOUN
fcis-28019	29	13	includes	include	VERB
fcis-28019	29	14	recordings	recording	NOUN
fcis-28019	29	15	from	from	ADP
fcis-28019	29	16	28	28	NUM
fcis-28019	29	17	pd	pd	NOUN
fcis-28019	29	18	patients	patient	NOUN
fcis-28019	29	19	,	,	PUNCT
fcis-28019	29	20	who	who	PRON
fcis-28019	29	21	pronounced	pronounce	VERB
fcis-28019	29	22	two	two	NUM
fcis-28019	29	23	vowels	vowel	NOUN
fcis-28019	29	24	(	(	PUNCT
fcis-28019	29	25	"	"	PUNCT
fcis-28019	29	26	a	a	DET
fcis-28019	29	27	"	"	PUNCT
fcis-28019	29	28	and	and	CCONJ
fcis-28019	29	29	"	"	PUNCT
fcis-28019	29	30	o	o	NOUN
fcis-28019	29	31	"	"	PUNCT
fcis-28019	29	32	)	)	PUNCT
fcis-28019	29	33	three	three	NUM
fcis-28019	29	34	times	time	NOUN
fcis-28019	29	35	,	,	PUNCT
fcis-28019	29	36	resulting	result	VERB
fcis-28019	29	37	in	in	ADP
fcis-28019	29	38	168	168	NUM
fcis-28019	29	39	samples	sample	NOUN
fcis-28019	29	40	.	.	PUNCT
fcis-28019	30	1	each	each	DET
fcis-28019	30	2	individual	individual	NOUN
fcis-28019	30	3	in	in	ADP
fcis-28019	30	4	the	the	DET
fcis-28019	30	5	training	training	NOUN
fcis-28019	30	6	set	set	NOUN
fcis-28019	30	7	has	have	VERB
fcis-28019	30	8	26	26	NUM
fcis-28019	30	9	recordings	recording	NOUN
fcis-28019	30	10	,	,	PUNCT
fcis-28019	30	11	while	while	SCONJ
fcis-28019	30	12	each	each	DET
fcis-28019	30	13	individual	individual	NOUN
fcis-28019	30	14	in	in	ADP
fcis-28019	30	15	the	the	DET
fcis-28019	30	16	testing	testing	NOUN
fcis-28019	30	17	set	set	NOUN
fcis-28019	30	18	has	have	VERB
fcis-28019	30	19	only	only	ADV
fcis-28019	30	20	6	6	NUM
fcis-28019	30	21	recordings	recording	NOUN
fcis-28019	30	22	.	.	PUNCT
fcis-28019	31	1	each	each	DET
fcis-28019	31	2	recording	recording	NOUN
fcis-28019	31	3	contains	contain	VERB
fcis-28019	31	4	26	26	NUM
fcis-28019	31	5	speech	speech	NOUN
fcis-28019	31	6	-	-	PUNCT
fcis-28019	31	7	related	relate	VERB
fcis-28019	31	8	features	feature	NOUN
fcis-28019	31	9	.	.	PUNCT
fcis-28019	32	1	2.2	2.2	NUM
fcis-28019	32	2	.	.	PUNCT
fcis-28019	32	3	preprocessing	preprocesse	VERB
fcis-28019	32	4	for	for	ADP
fcis-28019	32	5	dataset	dataset	NOUN
fcis-28019	32	6	1	1	NUM
fcis-28019	32	7	,	,	PUNCT
fcis-28019	32	8	the	the	DET
fcis-28019	32	9	first	first	ADJ
fcis-28019	32	10	6	6	NUM
fcis-28019	32	11	samples	sample	NOUN
fcis-28019	32	12	of	of	ADP
fcis-28019	32	13	each	each	DET
fcis-28019	32	14	subject	subject	NOUN
fcis-28019	32	15	are	be	AUX
fcis-28019	32	16	stacked	stack	VERB
fcis-28019	32	17	to	to	PART
fcis-28019	32	18	form	form	VERB
fcis-28019	32	19	a	a	DET
fcis-28019	32	20	shape	shape	NOUN
fcis-28019	32	21	of	of	ADP
fcis-28019	32	22	(	(	PUNCT
fcis-28019	32	23	6	6	NUM
fcis-28019	32	24	,	,	PUNCT
fcis-28019	32	25	22	22	NUM
fcis-28019	32	26	)	)	PUNCT
fcis-28019	32	27	.	.	PUNCT
fcis-28019	33	1	for	for	ADP
fcis-28019	33	2	dataset	dataset	NOUN
fcis-28019	33	3	2	2	NUM
fcis-28019	33	4	,	,	PUNCT
fcis-28019	33	5	since	since	SCONJ
fcis-28019	33	6	the	the	DET
fcis-28019	33	7	number	number	NOUN
fcis-28019	33	8	of	of	ADP
fcis-28019	33	9	samples	sample	NOUN
fcis-28019	33	10	per	per	ADP
fcis-28019	33	11	subject	subject	NOUN
fcis-28019	33	12	differs	differ	NOUN
fcis-28019	33	13	between	between	ADP
fcis-28019	33	14	the	the	DET
fcis-28019	33	15	training	training	NOUN
fcis-28019	33	16	set	set	NOUN
fcis-28019	33	17	(	(	PUNCT
fcis-28019	33	18	26	26	NUM
fcis-28019	33	19	samples	sample	NOUN
fcis-28019	33	20	per	per	ADP
fcis-28019	33	21	individual	individual	NOUN
fcis-28019	33	22	)	)	PUNCT
fcis-28019	33	23	and	and	CCONJ
fcis-28019	33	24	the	the	DET
fcis-28019	33	25	testing	testing	NOUN
fcis-28019	33	26	set	set	NOUN
fcis-28019	33	27	(	(	PUNCT
fcis-28019	33	28	6	6	NUM
fcis-28019	33	29	samples	sample	NOUN
fcis-28019	33	30	per	per	ADP
fcis-28019	33	31	individual	individual	NOUN
fcis-28019	33	32	)	)	PUNCT
fcis-28019	33	33	,	,	PUNCT
fcis-28019	33	34	the	the	DET
fcis-28019	33	35	first	first	ADJ
fcis-28019	33	36	6	6	NUM
fcis-28019	33	37	samples	sample	NOUN
fcis-28019	33	38	of	of	ADP
fcis-28019	33	39	each	each	DET
fcis-28019	33	40	subject	subject	NOUN
fcis-28019	33	41	in	in	ADP
fcis-28019	33	42	the	the	DET
fcis-28019	33	43	training	training	NOUN
fcis-28019	33	44	set	set	NOUN
fcis-28019	33	45	are	be	AUX
fcis-28019	33	46	selected	select	VERB
fcis-28019	33	47	and	and	CCONJ
fcis-28019	33	48	stacked	stack	VERB
fcis-28019	33	49	to	to	PART
fcis-28019	33	50	form	form	VERB
fcis-28019	33	51	a	a	DET
fcis-28019	33	52	shape	shape	NOUN
fcis-28019	33	53	of	of	ADP
fcis-28019	33	54	(	(	PUNCT
fcis-28019	33	55	6	6	NUM
fcis-28019	33	56	,	,	PUNCT
fcis-28019	33	57	26	26	NUM
fcis-28019	33	58	)	)	PUNCT
fcis-28019	33	59	,	,	PUNCT
fcis-28019	33	60	ensuring	ensure	VERB
fcis-28019	33	61	consistency	consistency	NOUN
fcis-28019	33	62	with	with	ADP
fcis-28019	33	63	the	the	DET
fcis-28019	33	64	number	number	NOUN
fcis-28019	33	65	of	of	ADP
fcis-28019	33	66	samples	sample	NOUN
fcis-28019	33	67	in	in	ADP
fcis-28019	33	68	the	the	DET
fcis-28019	33	69	testing	testing	NOUN
fcis-28019	33	70	set	set	NOUN
fcis-28019	33	71	.	.	PUNCT
fcis-28019	34	1	the	the	DET
fcis-28019	34	2	training	training	NOUN
fcis-28019	34	3	and	and	CCONJ
fcis-28019	34	4	testing	testing	NOUN
fcis-28019	34	5	sets	set	NOUN
fcis-28019	34	6	are	be	AUX
fcis-28019	34	7	split	split	VERB
fcis-28019	34	8	in	in	ADP
fcis-28019	34	9	an	an	DET
fcis-28019	34	10	8:2	8:2	NUM
fcis-28019	34	11	ratio	ratio	NOUN
fcis-28019	34	12	.	.	PUNCT
fcis-28019	35	1	in	in	ADP
fcis-28019	35	2	dataset	dataset	NOUN
fcis-28019	35	3	2	2	NUM
fcis-28019	35	4	,	,	PUNCT
fcis-28019	35	5	the	the	DET
fcis-28019	35	6	test	test	NOUN
fcis-28019	35	7	set	set	NOUN
fcis-28019	35	8	provided	provide	VERB
fcis-28019	35	9	by	by	ADP
fcis-28019	35	10	the	the	DET
fcis-28019	35	11	authors	author	NOUN
fcis-28019	35	12	contains	contain	VERB
fcis-28019	35	13	only	only	ADV
fcis-28019	35	14	one	one	NUM
fcis-28019	35	15	class	class	NOUN
fcis-28019	35	16	,	,	PUNCT
fcis-28019	35	17	pd	pd	NOUN
fcis-28019	35	18	patients	patient	NOUN
fcis-28019	35	19	.	.	PUNCT
fcis-28019	36	1	therefore	therefore	ADV
fcis-28019	36	2	,	,	PUNCT
fcis-28019	36	3	we	we	PRON
fcis-28019	36	4	mix	mix	VERB
fcis-28019	36	5	the	the	DET
fcis-28019	36	6	samples	sample	NOUN
fcis-28019	36	7	from	from	ADP
fcis-28019	36	8	the	the	DET
fcis-28019	36	9	training	training	NOUN
fcis-28019	36	10	and	and	CCONJ
fcis-28019	36	11	testing	testing	NOUN
fcis-28019	36	12	sets	set	NOUN
fcis-28019	36	13	and	and	CCONJ
fcis-28019	36	14	split	split	VERB
fcis-28019	36	15	them	they	PRON
fcis-28019	36	16	again	again	ADV
fcis-28019	36	17	in	in	ADP
fcis-28019	36	18	an	an	DET
fcis-28019	36	19	8:2	8:2	NUM
fcis-28019	36	20	ratio	ratio	NOUN
fcis-28019	36	21	to	to	PART
fcis-28019	36	22	ensure	ensure	VERB
fcis-28019	36	23	balanced	balanced	ADJ
fcis-28019	36	24	representation	representation	NOUN
fcis-28019	36	25	of	of	ADP
fcis-28019	36	26	both	both	DET
fcis-28019	36	27	classes	class	NOUN
fcis-28019	36	28	.	.	PUNCT
fcis-28019	37	1	this	this	DET
fcis-28019	37	2	translation	translation	NOUN
fcis-28019	37	3	accurately	accurately	ADV
fcis-28019	37	4	reflects	reflect	VERB
fcis-28019	37	5	the	the	DET
fcis-28019	37	6	structure	structure	NOUN
fcis-28019	37	7	and	and	CCONJ
fcis-28019	37	8	content	content	NOUN
fcis-28019	37	9	of	of	ADP
fcis-28019	37	10	your	your	PRON
fcis-28019	37	11	original	original	ADJ
fcis-28019	37	12	text	text	NOUN
fcis-28019	37	13	while	while	SCONJ
fcis-28019	37	14	maintaining	maintain	VERB
fcis-28019	37	15	clarity	clarity	NOUN
fcis-28019	37	16	and	and	CCONJ
fcis-28019	37	17	technical	technical	ADJ
fcis-28019	37	18	accuracy	accuracy	NOUN
fcis-28019	37	19	.	.	PUNCT
fcis-28019	38	1	let	let	VERB
fcis-28019	38	2	me	i	PRON
fcis-28019	38	3	know	know	VERB
fcis-28019	38	4	if	if	SCONJ
fcis-28019	38	5	you	you	PRON
fcis-28019	38	6	need	need	VERB
fcis-28019	38	7	further	further	ADJ
fcis-28019	38	8	adjustments	adjustment	NOUN
fcis-28019	38	9	!	!	PUNCT
fcis-28019	39	1	3	3	X
fcis-28019	39	2	.	.	NUM
fcis-28019	39	3	models	model	NOUN
fcis-28019	39	4	and	and	CCONJ
fcis-28019	39	5	results	result	VERB
fcis-28019	39	6	3.1	3.1	NUM
fcis-28019	39	7	.	.	PUNCT
fcis-28019	39	8	model	model	NOUN
fcis-28019	39	9	architecture	architecture	NOUN
fcis-28019	39	10	16	16	NUM
fcis-28019	39	11	table	table	NOUN
fcis-28019	39	12	1	1	NUM
fcis-28019	39	13	.	.	PUNCT
fcis-28019	39	14	model	model	NOUN
fcis-28019	39	15	architecture	architecture	NOUN
fcis-28019	39	16	layer	layer	NOUN
fcis-28019	39	17	(	(	PUNCT
fcis-28019	39	18	type	type	NOUN
fcis-28019	39	19	)	)	PUNCT
fcis-28019	39	20	filters	filter	NOUN
fcis-28019	39	21	kernel	kernel	PROPN
fcis-28019	39	22	size	size	NOUN
fcis-28019	39	23	activation	activation	NOUN
fcis-28019	39	24	function	function	NOUN
fcis-28019	39	25	conv1d	conv1d	NOUN
fcis-28019	39	26	32	32	NUM
fcis-28019	39	27	3	3	NUM
fcis-28019	39	28	relu	relu	NOUN
fcis-28019	39	29	maxpooling1d	maxpooling1d	NOUN
fcis-28019	39	30	2	2	NUM
fcis-28019	39	31	flatten	flatten	VERB
fcis-28019	39	32	dense	dense	ADJ
fcis-28019	39	33	64	64	NUM
fcis-28019	39	34	relu	relu	NOUN
fcis-28019	39	35	dense	dense	ADJ
fcis-28019	39	36	1	1	NUM
fcis-28019	39	37	sigmoid	sigmoid	NOUN
fcis-28019	39	38	3.2	3.2	NUM
fcis-28019	39	39	.	.	PUNCT
fcis-28019	40	1	results	result	VERB
fcis-28019	40	2	the	the	DET
fcis-28019	40	3	four	four	NUM
fcis-28019	40	4	-	-	PUNCT
fcis-28019	40	5	evaluation	evaluation	NOUN
fcis-28019	40	6	metrics	metric	NOUN
fcis-28019	40	7	used	use	VERB
fcis-28019	40	8	as	as	ADP
fcis-28019	40	9	results	result	NOUN
fcis-28019	40	10	are	be	AUX
fcis-28019	40	11	precision	precision	NOUN
fcis-28019	40	12	,	,	PUNCT
fcis-28019	40	13	recall	recall	NOUN
fcis-28019	40	14	,	,	PUNCT
fcis-28019	40	15	f1	f1	NOUN
fcis-28019	40	16	score	score	NOUN
fcis-28019	40	17	,	,	PUNCT
fcis-28019	40	18	and	and	CCONJ
fcis-28019	40	19	accuracy	accuracy	NOUN
fcis-28019	40	20	.	.	PUNCT
fcis-28019	41	1	table	table	NOUN
fcis-28019	41	2	2	2	NUM
fcis-28019	41	3	.	.	PUNCT
fcis-28019	41	4	classification	classification	NOUN
fcis-28019	41	5	performance	performance	NOUN
fcis-28019	41	6	dataset	dataset	NOUN
fcis-28019	41	7	precision	precision	NOUN
fcis-28019	41	8	recall	recall	NOUN
fcis-28019	41	9	f1	f1	PROPN
fcis-28019	41	10	score	score	NOUN
fcis-28019	41	11	accuracy	accuracy	NOUN
fcis-28019	41	12	dataset1	dataset1	NOUN
fcis-28019	41	13	100	100	NUM
fcis-28019	41	14	%	%	NOUN
fcis-28019	41	15	100	100	NUM
fcis-28019	41	16	%	%	NOUN
fcis-28019	41	17	100	100	NUM
fcis-28019	41	18	%	%	NOUN
fcis-28019	41	19	100	100	NUM
fcis-28019	41	20	%	%	NOUN
fcis-28019	41	21	dataset2	dataset2	NOUN
fcis-28019	41	22	88.89	88.89	NUM
fcis-28019	41	23	%	%	NOUN
fcis-28019	41	24	100.00	100.00	NUM
fcis-28019	41	25	%	%	NOUN
fcis-28019	41	26	94.12	94.12	NUM
fcis-28019	41	27	%	%	NOUN
fcis-28019	41	28	92.86	92.86	NUM
fcis-28019	41	29	%	%	NOUN
fcis-28019	41	30	table	table	NOUN
fcis-28019	41	31	3	3	NUM
fcis-28019	41	32	.	.	PUNCT
fcis-28019	41	33	comparison	comparison	NOUN
fcis-28019	41	34	of	of	ADP
fcis-28019	41	35	dataset	dataset	NOUN
fcis-28019	41	36	1	1	NUM
fcis-28019	41	37	with	with	ADP
fcis-28019	41	38	other	other	ADJ
fcis-28019	41	39	methods	method	NOUN
fcis-28019	41	40	authors	author	NOUN
fcis-28019	41	41	classifier	classifier	AUX
fcis-28019	41	42	accuracy	accuracy	PROPN
fcis-28019	41	43	fayyazifar	fayyazifar	ADV
fcis-28019	41	44	et	et	PROPN
fcis-28019	41	45	al	al	PROPN
fcis-28019	41	46	.	.	PROPN
fcis-28019	42	1	(	(	PUNCT
fcis-28019	42	2	2017	2017	NUM
fcis-28019	42	3	)	)	PUNCT
fcis-28019	43	1	[	[	X
fcis-28019	43	2	5	5	X
fcis-28019	43	3	]	]	PUNCT
fcis-28019	43	4	bagging	bag	VERB
fcis-28019	43	5	algorithm	algorithm	NOUN
fcis-28019	43	6	98.28	98.28	NUM
fcis-28019	43	7	%	%	NOUN
fcis-28019	43	8	haq	haq	PROPN
fcis-28019	43	9	et	et	PROPN
fcis-28019	43	10	al	al	PROPN
fcis-28019	43	11	.	.	PROPN
fcis-28019	44	1	(	(	PUNCT
fcis-28019	44	2	2018	2018	NUM
fcis-28019	44	3	)	)	PUNCT
fcis-28019	45	1	[	[	X
fcis-28019	45	2	6	6	NUM
fcis-28019	45	3	]	]	X
fcis-28019	45	4	deep	deep	ADJ
fcis-28019	45	5	nn	nn	PROPN
fcis-28019	45	6	98.00	98.00	NUM
fcis-28019	45	7	%	%	NOUN
fcis-28019	45	8	haq	haq	PROPN
fcis-28019	45	9	et	et	PROPN
fcis-28019	45	10	al	al	PROPN
fcis-28019	45	11	.	.	PROPN
fcis-28019	45	12	(	(	PUNCT
fcis-28019	45	13	2019	2019	NUM
fcis-28019	45	14	)	)	PUNCT
fcis-28019	46	1	[	[	X
fcis-28019	46	2	7	7	X
fcis-28019	46	3	]	]	X
fcis-28019	46	4	l1	l1	PROPN
fcis-28019	46	5	-	-	PUNCT
fcis-28019	46	6	norm	norm	NOUN
fcis-28019	46	7	svm	svm	NOUN
fcis-28019	46	8	99.00	99.00	NUM
fcis-28019	46	9	%	%	NOUN
fcis-28019	46	10	sharma	sharma	PROPN
fcis-28019	46	11	et	et	PROPN
fcis-28019	46	12	al	al	PROPN
fcis-28019	46	13	(	(	PUNCT
fcis-28019	46	14	2020)[8	2020)[8	PROPN
fcis-28019	46	15	]	]	PUNCT
fcis-28019	46	16	knn	knn	VERB
fcis-28019	46	17	99.25	99.25	NUM
fcis-28019	46	18	%	%	NOUN
fcis-28019	46	19	prposed	prpose	VERB
fcis-28019	46	20	1d	1d	NOUN
fcis-28019	46	21	-	-	PUNCT
fcis-28019	46	22	cnn	cnn	PROPN
fcis-28019	46	23	100	100	NUM
fcis-28019	46	24	%	%	NOUN
fcis-28019	46	25	table	table	NOUN
fcis-28019	46	26	4	4	NUM
fcis-28019	46	27	.	.	PUNCT
fcis-28019	46	28	comparison	comparison	NOUN
fcis-28019	46	29	of	of	ADP
fcis-28019	46	30	dataset	dataset	NOUN
fcis-28019	46	31	2	2	NUM
fcis-28019	46	32	with	with	ADP
fcis-28019	46	33	other	other	ADJ
fcis-28019	46	34	methods	method	NOUN
fcis-28019	46	35	authors	author	NOUN
fcis-28019	46	36	classifier	classifier	PROPN
fcis-28019	46	37	accuracy	accuracy	PROPN
fcis-28019	46	38	sakar	sakar	PROPN
fcis-28019	46	39	et	et	PROPN
fcis-28019	46	40	al	al	PROPN
fcis-28019	46	41	.	.	PUNCT
fcis-28019	47	1	(	(	PUNCT
fcis-28019	47	2	2013)[1	2013)[1	NUM
fcis-28019	47	3	]	]	PUNCT
fcis-28019	47	4	knn	knn	PROPN
fcis-28019	48	1	+	+	NOUN
fcis-28019	48	2	svm	svm	PROPN
fcis-28019	48	3	68.45	68.45	NUM
fcis-28019	48	4	%	%	NOUN
fcis-28019	48	5	li	li	PROPN
fcis-28019	48	6	et	et	PROPN
fcis-28019	48	7	al	al	PROPN
fcis-28019	48	8	.	.	PUNCT
fcis-28019	49	1	(	(	PUNCT
fcis-28019	49	2	2017)[9	2017)[9	PROPN
fcis-28019	49	3	]	]	X
fcis-28019	49	4	ensemble	ensemble	ADJ
fcis-28019	49	5	learning	learning	NOUN
fcis-28019	49	6	algorithm	algorithm	NOUN
fcis-28019	49	7	86.5	86.5	NUM
fcis-28019	49	8	%	%	NOUN
fcis-28019	49	9	ali	ali	PROPN
fcis-28019	49	10	et	et	PROPN
fcis-28019	49	11	al	al	PROPN
fcis-28019	49	12	.	.	PROPN
fcis-28019	50	1	(	(	PUNCT
fcis-28019	50	2	2019)[3	2019)[3	NUM
fcis-28019	50	3	]	]	X
fcis-28019	50	4	nn	nn	PROPN
fcis-28019	50	5	100	100	NUM
fcis-28019	50	6	%	%	NOUN
fcis-28019	50	7	sharma	sharma	PROPN
fcis-28019	50	8	et	et	PROPN
fcis-28019	50	9	al(2020)[8	al(2020)[8	PROPN
fcis-28019	50	10	]	]	X
fcis-28019	50	11	knn	knn	PROPN
fcis-28019	51	1	94.54	94.54	NUM
fcis-28019	51	2	%	%	NOUN
fcis-28019	51	3	pramanik	pramanik	VERB
fcis-28019	51	4	et	et	PROPN
fcis-28019	51	5	al	al	PROPN
fcis-28019	51	6	(	(	PUNCT
fcis-28019	51	7	2023	2023	NUM
fcis-28019	51	8	)	)	PUNCT
fcis-28019	52	1	[	[	X
fcis-28019	52	2	9	9	NUM
fcis-28019	52	3	]	]	PUNCT
fcis-28019	52	4	sysfor	sysfor	ADP
fcis-28019	52	5	92.86	92.86	NUM
fcis-28019	52	6	%	%	NOUN
fcis-28019	52	7	ali	ali	PROPN
fcis-28019	52	8	l	l	PROPN
fcis-28019	52	9	et	et	PROPN
fcis-28019	52	10	al	al	PROPN
fcis-28019	52	11	(	(	PUNCT
fcis-28019	52	12	2024	2024	NUM
fcis-28019	52	13	)	)	PUNCT
fcis-28019	53	1	[	[	X
fcis-28019	53	2	10	10	NUM
fcis-28019	53	3	]	]	X
fcis-28019	53	4	dnn	dnn	PROPN
fcis-28019	53	5	97.5	97.5	NUM
fcis-28019	53	6	%	%	NOUN
fcis-28019	53	7	prposed	prpose	VERB
fcis-28019	53	8	1d	1d	NUM
fcis-28019	53	9	-	-	PUNCT
fcis-28019	53	10	cnn	cnn	NOUN
fcis-28019	53	11	92.86	92.86	NUM
fcis-28019	53	12	%	%	NOUN
fcis-28019	53	13	4	4	NUM
fcis-28019	53	14	.	.	X
fcis-28019	54	1	summary	summary	VERB
fcis-28019	54	2	the	the	DET
fcis-28019	54	3	results	result	NOUN
fcis-28019	54	4	of	of	ADP
fcis-28019	54	5	using	use	VERB
fcis-28019	54	6	a	a	DET
fcis-28019	54	7	one	one	NUM
fcis-28019	54	8	-	-	PUNCT
fcis-28019	54	9	dimensional	dimensional	ADJ
fcis-28019	54	10	convolutional	convolutional	ADJ
fcis-28019	54	11	neural	neural	ADJ
fcis-28019	54	12	network	network	NOUN
fcis-28019	54	13	for	for	ADP
fcis-28019	54	14	parkinson	parkinson	NOUN
fcis-28019	54	15	's	's	PART
fcis-28019	54	16	speech	speech	NOUN
fcis-28019	54	17	classification	classification	NOUN
fcis-28019	54	18	show	show	NOUN
fcis-28019	54	19	varying	vary	VERB
fcis-28019	54	20	performance	performance	NOUN
fcis-28019	54	21	across	across	ADP
fcis-28019	54	22	different	different	ADJ
fcis-28019	54	23	datasets	dataset	NOUN
fcis-28019	54	24	.	.	PUNCT
fcis-28019	55	1	in	in	ADP
fcis-28019	55	2	dataset1	dataset1	PROPN
fcis-28019	55	3	,	,	PUNCT
fcis-28019	55	4	the	the	DET
fcis-28019	55	5	model	model	NOUN
fcis-28019	55	6	achieves	achieve	VERB
fcis-28019	55	7	100	100	NUM
fcis-28019	55	8	%	%	NOUN
fcis-28019	55	9	in	in	ADP
fcis-28019	55	10	all	all	DET
fcis-28019	55	11	metrics	metric	NOUN
fcis-28019	55	12	(	(	PUNCT
fcis-28019	55	13	precision	precision	NOUN
fcis-28019	55	14	,	,	PUNCT
fcis-28019	55	15	recall	recall	NOUN
fcis-28019	55	16	,	,	PUNCT
fcis-28019	55	17	f1	f1	NOUN
fcis-28019	55	18	score	score	NOUN
fcis-28019	55	19	,	,	PUNCT
fcis-28019	55	20	and	and	CCONJ
fcis-28019	55	21	accuracy	accuracy	NOUN
fcis-28019	55	22	)	)	PUNCT
fcis-28019	55	23	,	,	PUNCT
fcis-28019	55	24	demonstrating	demonstrate	VERB
fcis-28019	55	25	excellent	excellent	ADJ
fcis-28019	55	26	performance	performance	NOUN
fcis-28019	55	27	.	.	PUNCT
fcis-28019	56	1	in	in	ADP
fcis-28019	56	2	dataset2	dataset2	PROPN
fcis-28019	56	3	,	,	PUNCT
fcis-28019	56	4	the	the	DET
fcis-28019	56	5	model	model	NOUN
fcis-28019	56	6	still	still	ADV
fcis-28019	56	7	performs	perform	VERB
fcis-28019	56	8	well	well	ADV
fcis-28019	56	9	,	,	PUNCT
fcis-28019	56	10	despite	despite	SCONJ
fcis-28019	56	11	a	a	DET
fcis-28019	56	12	slightly	slightly	ADV
fcis-28019	56	13	lower	low	ADJ
fcis-28019	56	14	precision	precision	NOUN
fcis-28019	56	15	(	(	PUNCT
fcis-28019	56	16	88.89	88.89	NUM
fcis-28019	56	17	%	%	NOUN
fcis-28019	56	18	)	)	PUNCT
fcis-28019	56	19	,	,	PUNCT
fcis-28019	56	20	with	with	ADP
fcis-28019	56	21	a	a	DET
fcis-28019	56	22	perfect	perfect	ADJ
fcis-28019	56	23	recall	recall	NOUN
fcis-28019	56	24	of	of	ADP
fcis-28019	56	25	100	100	NUM
fcis-28019	56	26	%	%	NOUN
fcis-28019	56	27	,	,	PUNCT
fcis-28019	56	28	indicating	indicate	VERB
fcis-28019	56	29	that	that	SCONJ
fcis-28019	56	30	it	it	PRON
fcis-28019	56	31	effectively	effectively	ADV
fcis-28019	56	32	identifies	identify	VERB
fcis-28019	56	33	all	all	DET
fcis-28019	56	34	parkinson	parkinson	NOUN
fcis-28019	56	35	's	's	PART
fcis-28019	56	36	patients	patient	NOUN
fcis-28019	56	37	.	.	PUNCT
fcis-28019	57	1	overall	overall	ADV
fcis-28019	57	2	,	,	PUNCT
fcis-28019	57	3	the	the	DET
fcis-28019	57	4	model	model	NOUN
fcis-28019	57	5	exhibits	exhibit	VERB
fcis-28019	57	6	high	high	ADJ
fcis-28019	57	7	accuracy	accuracy	NOUN
fcis-28019	57	8	and	and	CCONJ
fcis-28019	57	9	stability	stability	NOUN
fcis-28019	57	10	in	in	ADP
fcis-28019	57	11	the	the	DET
fcis-28019	57	12	classification	classification	NOUN
fcis-28019	57	13	task	task	NOUN
fcis-28019	57	14	.	.	PUNCT
fcis-28019	58	1	acknowledgments	acknowledgment	NOUN
fcis-28019	58	2	natural	natural	PROPN
fcis-28019	58	3	science	science	PROPN
fcis-28019	58	4	foundation	foundation	NOUN
fcis-28019	58	5	of	of	ADP
fcis-28019	58	6	science	science	NOUN
fcis-28019	58	7	and	and	CCONJ
fcis-28019	58	8	technology	technology	PROPN
fcis-28019	58	9	department	department	PROPN
fcis-28019	58	10	of	of	ADP
fcis-28019	58	11	jilin	jilin	PROPN
fcis-28019	58	12	province	province	PROPN
fcis-28019	58	13	,	,	PUNCT
fcis-28019	58	14	no	no	INTJ
fcis-28019	58	15	.	.	PUNCT
fcis-28019	59	1	20130101170jc	20130101170jc	NOUN
fcis-28019	59	2	;	;	PUNCT
fcis-28019	59	3	jilin	jilin	PROPN
fcis-28019	59	4	provincial	provincial	PROPN
fcis-28019	59	5	department	department	PROPN
fcis-28019	59	6	of	of	ADP
fcis-28019	59	7	education	education	PROPN
fcis-28019	59	8	"	"	PUNCT
fcis-28019	59	9	12th	12th	ADJ
fcis-28019	59	10	five	five	NUM
fcis-28019	59	11	-	-	PUNCT
fcis-28019	59	12	year	year	NOUN
fcis-28019	59	13	"	"	PUNCT
fcis-28019	59	14	science	science	NOUN
fcis-28019	59	15	and	and	CCONJ
fcis-28019	59	16	technology	technology	NOUN
fcis-28019	59	17	research	research	NOUN
fcis-28019	59	18	fund	fund	NOUN
fcis-28019	59	19	project	project	NOUN
fcis-28019	59	20	(	(	PUNCT
fcis-28019	59	21	2014404	2014404	NUM
fcis-28019	59	22	)	)	PUNCT
fcis-28019	59	23	.	.	PUNCT
fcis-28019	60	1	references	reference	NOUN
fcis-28019	60	2	[	[	X
fcis-28019	60	3	1	1	X
fcis-28019	60	4	]	]	X
fcis-28019	60	5	sakar	sakar	PROPN
fcis-28019	60	6	b	b	PROPN
fcis-28019	60	7	e	e	PROPN
fcis-28019	60	8	,	,	PUNCT
fcis-28019	60	9	isenkul	isenkul	NOUN
fcis-28019	60	10	m	m	PROPN
fcis-28019	60	11	e	e	PROPN
fcis-28019	60	12	,	,	PUNCT
fcis-28019	60	13	sakar	sakar	PROPN
fcis-28019	60	14	c	c	PROPN
fcis-28019	60	15	o	o	PROPN
fcis-28019	60	16	,	,	PUNCT
fcis-28019	60	17	et	et	PROPN
fcis-28019	60	18	al	al	PROPN
fcis-28019	60	19	.	.	PUNCT
fcis-28019	60	20	collection	collection	NOUN
fcis-28019	60	21	and	and	CCONJ
fcis-28019	60	22	analysis	analysis	NOUN
fcis-28019	60	23	of	of	ADP
fcis-28019	60	24	a	a	DET
fcis-28019	60	25	parkinson	parkinson	NOUN
fcis-28019	60	26	speech	speech	NOUN
fcis-28019	60	27	dataset	dataset	VERB
fcis-28019	60	28	with	with	ADP
fcis-28019	60	29	multiple	multiple	ADJ
fcis-28019	60	30	types	type	NOUN
fcis-28019	60	31	of	of	ADP
fcis-28019	60	32	sound	sound	ADJ
fcis-28019	60	33	recordings[j	recordings[j	PROPN
fcis-28019	60	34	]	]	PUNCT
fcis-28019	60	35	.	.	PUNCT
fcis-28019	61	1	ieee	ieee	PROPN
fcis-28019	61	2	journal	journal	PROPN
fcis-28019	61	3	of	of	ADP
fcis-28019	61	4	biomedical	biomedical	ADJ
fcis-28019	61	5	and	and	CCONJ
fcis-28019	61	6	health	health	NOUN
fcis-28019	61	7	informatics	informatic	NOUN
fcis-28019	61	8	,	,	PUNCT
fcis-28019	61	9	2013	2013	NUM
fcis-28019	61	10	,	,	PUNCT
fcis-28019	61	11	17(4	17(4	NUM
fcis-28019	61	12	):	):	PUNCT
fcis-28019	61	13	828	828	NUM
fcis-28019	61	14	-	-	SYM
fcis-28019	61	15	834	834	NUM
fcis-28019	61	16	.	.	PUNCT
fcis-28019	62	1	[	[	X
fcis-28019	62	2	2	2	NUM
fcis-28019	62	3	]	]	PUNCT
fcis-28019	62	4	naranjo	naranjo	PROPN
fcis-28019	62	5	l	l	PROPN
fcis-28019	62	6	,	,	PUNCT
fcis-28019	62	7	perez	perez	PROPN
fcis-28019	62	8	c	c	PROPN
fcis-28019	62	9	j	j	PROPN
fcis-28019	62	10	,	,	PUNCT
fcis-28019	62	11	campos	campos	PROPN
fcis-28019	62	12	-	-	PUNCT
fcis-28019	62	13	roca	roca	PROPN
fcis-28019	62	14	y	y	PROPN
fcis-28019	62	15	,	,	PUNCT
fcis-28019	62	16	et	et	PROPN
fcis-28019	62	17	al	al	PROPN
fcis-28019	62	18	.	.	PUNCT
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fcis-28019	63	2	voice	voice	NOUN
fcis-28019	63	3	recording	recording	NOUN
fcis-28019	63	4	replications	replication	NOUN
fcis-28019	63	5	for	for	ADP
fcis-28019	63	6	parkinson	parkinson	NOUN
fcis-28019	63	7	’s	’s	PART
fcis-28019	63	8	disease	disease	NOUN
fcis-28019	63	9	detection[j	detection[j	PROPN
fcis-28019	63	10	]	]	PUNCT
fcis-28019	63	11	.	.	PUNCT
fcis-28019	64	1	expert	expert	NOUN
fcis-28019	64	2	systems	system	NOUN
fcis-28019	64	3	with	with	ADP
fcis-28019	64	4	applications	application	NOUN
fcis-28019	64	5	,	,	PUNCT
fcis-28019	64	6	2016	2016	NUM
fcis-28019	64	7	,	,	PUNCT
fcis-28019	64	8	46	46	NUM
fcis-28019	64	9	:	:	SYM
fcis-28019	64	10	286	286	NUM
fcis-28019	64	11	-	-	SYM
fcis-28019	64	12	292	292	NUM
fcis-28019	64	13	.	.	PUNCT
fcis-28019	65	1	[	[	X
fcis-28019	65	2	3	3	X
fcis-28019	65	3	]	]	X
fcis-28019	65	4	ali	ali	PROPN
fcis-28019	65	5	l	l	PROPN
fcis-28019	65	6	,	,	PUNCT
fcis-28019	65	7	zhu	zhu	PROPN
fcis-28019	65	8	c	c	X
fcis-28019	65	9	,	,	PUNCT
fcis-28019	65	10	zhou	zhou	PROPN
fcis-28019	65	11	m	m	PROPN
fcis-28019	65	12	,	,	PUNCT
fcis-28019	65	13	et	et	PROPN
fcis-28019	65	14	al	al	PROPN
fcis-28019	65	15	.	.	PROPN
fcis-28019	66	1	early	early	ADJ
fcis-28019	66	2	diagnosis	diagnosis	NOUN
fcis-28019	66	3	of	of	ADP
fcis-28019	66	4	parkinson	parkinson	NOUN
fcis-28019	66	5	’s	’s	PART
fcis-28019	66	6	disease	disease	NOUN
fcis-28019	66	7	from	from	ADP
fcis-28019	66	8	multiple	multiple	ADJ
fcis-28019	66	9	voice	voice	NOUN
fcis-28019	66	10	recordings	recording	NOUN
fcis-28019	66	11	by	by	ADP
fcis-28019	66	12	simultaneous	simultaneous	ADJ
fcis-28019	66	13	sample	sample	NOUN
fcis-28019	66	14	and	and	CCONJ
fcis-28019	66	15	feature	feature	NOUN
fcis-28019	66	16	selection[j	selection[j	NOUN
fcis-28019	66	17	]	]	PUNCT
fcis-28019	66	18	.	.	PUNCT
fcis-28019	67	1	expert	expert	NOUN
fcis-28019	67	2	systems	system	NOUN
fcis-28019	67	3	with	with	ADP
fcis-28019	67	4	applications	application	NOUN
fcis-28019	67	5	,	,	PUNCT
fcis-28019	67	6	2019	2019	NUM
fcis-28019	67	7	,	,	PUNCT
fcis-28019	67	8	137	137	NUM
fcis-28019	67	9	:	:	PUNCT
fcis-28019	67	10	22	22	NUM
fcis-28019	67	11	-	-	SYM
fcis-28019	67	12	28	28	NUM
fcis-28019	67	13	.	.	PUNCT
fcis-28019	68	1	[	[	X
fcis-28019	68	2	4	4	X
fcis-28019	68	3	]	]	X
fcis-28019	68	4	little	little	ADJ
fcis-28019	68	5	m	m	NOUN
fcis-28019	68	6	,	,	PUNCT
fcis-28019	68	7	mcsharry	mcsharry	VERB
fcis-28019	68	8	p	p	NOUN
fcis-28019	68	9	,	,	PUNCT
fcis-28019	68	10	roberts	roberts	PROPN
fcis-28019	68	11	s	s	PROPN
fcis-28019	68	12	,	,	PUNCT
fcis-28019	68	13	et	et	PROPN
fcis-28019	68	14	al	al	PROPN
fcis-28019	68	15	.	.	PUNCT
fcis-28019	68	16	exploiting	exploit	VERB
fcis-28019	68	17	nonlinear	nonlinear	ADJ
fcis-28019	68	18	recurrence	recurrence	NOUN
fcis-28019	68	19	and	and	CCONJ
fcis-28019	68	20	fractal	fractal	ADJ
fcis-28019	68	21	scaling	scale	VERB
fcis-28019	68	22	properties	property	NOUN
fcis-28019	68	23	for	for	ADP
fcis-28019	68	24	voice	voice	NOUN
fcis-28019	68	25	disorder	disorder	NOUN
fcis-28019	68	26	detection[j	detection[j	PROPN
fcis-28019	68	27	]	]	PUNCT
fcis-28019	68	28	.	.	PUNCT
fcis-28019	69	1	nature	nature	NOUN
fcis-28019	69	2	precedings	preceding	NOUN
fcis-28019	69	3	,	,	PUNCT
fcis-28019	69	4	2007	2007	NUM
fcis-28019	69	5	:	:	PUNCT
fcis-28019	69	6	1	1	NUM
fcis-28019	69	7	-	-	SYM
fcis-28019	69	8	1	1	NUM
fcis-28019	69	9	.	.	PUNCT
fcis-28019	70	1	[	[	X
fcis-28019	70	2	5	5	NUM
fcis-28019	70	3	]	]	SYM
fcis-28019	70	4	fayyazifar	fayyazifar	ADV
fcis-28019	70	5	,	,	PUNCT
fcis-28019	70	6	n.	n.	NOUN
fcis-28019	70	7	,	,	PUNCT
fcis-28019	70	8	&	&	CCONJ
fcis-28019	70	9	samadiani	samadiani	PROPN
fcis-28019	70	10	,	,	PUNCT
fcis-28019	70	11	n.	n.	NOUN
fcis-28019	70	12	(	(	PUNCT
fcis-28019	70	13	2017	2017	NUM
fcis-28019	70	14	)	)	PUNCT
fcis-28019	70	15	.	.	PUNCT
fcis-28019	71	1	parkinson	parkinson	NOUN
fcis-28019	71	2	's	's	PART
fcis-28019	71	3	disease	disease	NOUN
fcis-28019	71	4	detection	detection	NOUN
fcis-28019	71	5	using	use	VERB
fcis-28019	71	6	ensemble	ensemble	ADJ
fcis-28019	71	7	techniques	technique	NOUN
fcis-28019	71	8	and	and	CCONJ
fcis-28019	71	9	genetic	genetic	ADJ
fcis-28019	71	10	algorithm	algorithm	NOUN
fcis-28019	71	11	.	.	PUNCT
fcis-28019	72	1	in	in	ADP
fcis-28019	72	2	2017	2017	NUM
fcis-28019	72	3	artificial	artificial	ADJ
fcis-28019	72	4	intelligence	intelligence	NOUN
fcis-28019	72	5	and	and	CCONJ
fcis-28019	72	6	signal	signal	PROPN
fcis-28019	72	7	processing	processing	NOUN
fcis-28019	72	8	(	(	PUNCT
fcis-28019	72	9	aisp	aisp	NOUN
fcis-28019	72	10	)	)	PUNCT
fcis-28019	72	11	(	(	PUNCT
fcis-28019	72	12	pp	pp	ADP
fcis-28019	72	13	.	.	PUNCT
fcis-28019	73	1	162–165	162–165	NUM
fcis-28019	73	2	)	)	PUNCT
fcis-28019	73	3	.	.	PUNCT
fcis-28019	74	1	shiraz	shiraz	PROPN
fcis-28019	74	2	.	.	PUNCT
fcis-28019	75	1	[	[	X
fcis-28019	75	2	6	6	NUM
fcis-28019	75	3	]	]	X
fcis-28019	75	4	haq	haq	PROPN
fcis-28019	75	5	a	a	DET
fcis-28019	75	6	u	u	PROPN
fcis-28019	75	7	,	,	PUNCT
fcis-28019	75	8	li	li	PROPN
fcis-28019	75	9	j	j	PROPN
fcis-28019	75	10	,	,	PUNCT
fcis-28019	75	11	memon	memon	PROPN
fcis-28019	75	12	m	m	PROPN
fcis-28019	75	13	h	h	PROPN
fcis-28019	75	14	,	,	PUNCT
fcis-28019	75	15	et	et	PROPN
fcis-28019	75	16	al	al	PROPN
fcis-28019	75	17	.	.	PROPN
fcis-28019	75	18	comparative	comparative	ADJ
fcis-28019	75	19	analysis	analysis	NOUN
fcis-28019	75	20	of	of	ADP
fcis-28019	75	21	the	the	DET
fcis-28019	75	22	classification	classification	NOUN
fcis-28019	75	23	performance	performance	NOUN
fcis-28019	75	24	of	of	ADP
fcis-28019	75	25	machine	machine	NOUN
fcis-28019	75	26	learning	learn	VERB
fcis-28019	75	27	classifiers	classifier	NOUN
fcis-28019	75	28	and	and	CCONJ
fcis-28019	75	29	deep	deep	ADJ
fcis-28019	75	30	neural	neural	ADJ
fcis-28019	75	31	network	network	NOUN
fcis-28019	75	32	classifier	classifier	NOUN
fcis-28019	75	33	for	for	ADP
fcis-28019	75	34	prediction	prediction	NOUN
fcis-28019	75	35	of	of	ADP
fcis-28019	75	36	parkinson	parkinson	NOUN
fcis-28019	75	37	disease[c]//2018	disease[c]//2018	PROPN
fcis-28019	75	38	15th	15th	ADJ
fcis-28019	75	39	international	international	ADJ
fcis-28019	75	40	computer	computer	NOUN
fcis-28019	75	41	conference	conference	NOUN
fcis-28019	75	42	on	on	ADP
fcis-28019	75	43	wavelet	wavelet	NOUN
fcis-28019	75	44	active	active	ADJ
fcis-28019	75	45	media	medium	NOUN
fcis-28019	75	46	technology	technology	NOUN
fcis-28019	75	47	and	and	CCONJ
fcis-28019	75	48	information	information	NOUN
fcis-28019	75	49	processing	processing	NOUN
fcis-28019	75	50	(	(	PUNCT
fcis-28019	75	51	iccwamtip	iccwamtip	PROPN
fcis-28019	75	52	)	)	PUNCT
fcis-28019	75	53	.	.	PUNCT
fcis-28019	76	1	ieee	ieee	NOUN
fcis-28019	76	2	,	,	PUNCT
fcis-28019	76	3	2018	2018	NUM
fcis-28019	76	4	:	:	PUNCT
fcis-28019	76	5	101	101	NUM
fcis-28019	76	6	-	-	SYM
fcis-28019	76	7	106	106	NUM
fcis-28019	76	8	.	.	PUNCT
fcis-28019	77	1	[	[	X
fcis-28019	77	2	7	7	NUM
fcis-28019	77	3	]	]	X
fcis-28019	77	4	haq	haq	PROPN
fcis-28019	77	5	,	,	PUNCT
fcis-28019	77	6	a.	a.	PROPN
fcis-28019	77	7	u.	u.	PROPN
fcis-28019	77	8	,	,	PUNCT
fcis-28019	77	9	li	li	PROPN
fcis-28019	77	10	,	,	PUNCT
fcis-28019	77	11	j.	j.	PROPN
fcis-28019	77	12	p.	p.	PROPN
fcis-28019	77	13	,	,	PUNCT
fcis-28019	77	14	memon	memon	PROPN
fcis-28019	77	15	,	,	PUNCT
fcis-28019	77	16	m.	m.	PROPN
fcis-28019	77	17	h.	h.	PROPN
fcis-28019	77	18	,	,	PUNCT
fcis-28019	77	19	khan	khan	PROPN
fcis-28019	77	20	,	,	PUNCT
fcis-28019	77	21	j.	j.	PROPN
fcis-28019	77	22	,	,	PUNCT
fcis-28019	77	23	malik	malik	PROPN
fcis-28019	77	24	,	,	PUNCT
fcis-28019	77	25	a.	a.	PROPN
fcis-28019	77	26	,	,	PUNCT
fcis-28019	77	27	ahmad	ahmad	PROPN
fcis-28019	77	28	,	,	PUNCT
fcis-28019	77	29	t.	t.	PROPN
fcis-28019	77	30	,	,	PUNCT
fcis-28019	77	31	…	…	PUNCT
fcis-28019	77	32	shahid	shahid	NOUN
fcis-28019	77	33	,	,	PUNCT
fcis-28019	77	34	m.	m.	NOUN
fcis-28019	77	35	(	(	PUNCT
fcis-28019	77	36	2019	2019	NUM
fcis-28019	77	37	)	)	PUNCT
fcis-28019	77	38	.	.	PUNCT
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fcis-28019	78	2	selection	selection	NOUN
fcis-28019	78	3	based	base	VERB
fcis-28019	78	4	on	on	ADP
fcis-28019	78	5	l1	l1	PROPN
fcis-28019	78	6	-	-	PUNCT
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fcis-28019	78	8	support	support	NOUN
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fcis-28019	78	14	system	system	NOUN
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fcis-28019	78	17	's	's	PART
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fcis-28019	78	19	using	use	VERB
fcis-28019	78	20	voice	voice	NOUN
fcis-28019	78	21	recordings	recording	NOUN
fcis-28019	78	22	.	.	PUNCT
fcis-28019	79	1	ieee	ieee	NOUN
fcis-28019	79	2	access	access	NOUN
fcis-28019	79	3	,	,	PUNCT
fcis-28019	79	4	7	7	NUM
fcis-28019	79	5	,	,	PUNCT
fcis-28019	79	6	37718–37734	37718–37734	NUM
fcis-28019	79	7	.	.	PUNCT
fcis-28019	80	1	https://doi.org/10	https://doi.org/10	PROPN
fcis-28019	80	2	.	.	PUNCT
fcis-28019	81	1	1109/	1109/	NUM
fcis-28019	81	2	access	access	NOUN
fcis-28019	81	3	.	.	PUNCT
fcis-28019	82	1	2019	2019	NUM
fcis-28019	82	2	.	.	PUNCT
fcis-28019	83	1	2906350	2906350	NUM
fcis-28019	83	2	17	17	NUM
fcis-28019	84	1	[	[	SYM
fcis-28019	84	2	8	8	NUM
fcis-28019	84	3	]	]	X
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fcis-28019	84	5	s	s	PART
fcis-28019	84	6	r	r	PROPN
fcis-28019	84	7	,	,	PUNCT
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fcis-28019	84	10	,	,	PUNCT
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fcis-28019	84	18	binary	binary	PROPN
fcis-28019	84	19	rao	rao	PROPN
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fcis-28019	84	21	algorithms[j	algorithms[j	PROPN
fcis-28019	84	22	]	]	X
fcis-28019	84	23	.	.	PUNCT
fcis-28019	85	1	expert	expert	NOUN
fcis-28019	85	2	systems	system	NOUN
fcis-28019	85	3	,	,	PUNCT
fcis-28019	85	4	2021	2021	NUM
fcis-28019	85	5	,	,	PUNCT
fcis-28019	85	6	38(4	38(4	NUM
fcis-28019	85	7	):	):	PUNCT
fcis-28019	85	8	e12674	e12674	NOUN
fcis-28019	85	9	.	.	PUNCT
fcis-28019	86	1	[	[	X
fcis-28019	86	2	9	9	NUM
fcis-28019	86	3	]	]	SYM
fcis-28019	86	4	li	li	PROPN
fcis-28019	86	5	y	y	PROPN
fcis-28019	86	6	,	,	PUNCT
fcis-28019	86	7	yang	yang	PROPN
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fcis-28019	86	9	,	,	PUNCT
fcis-28019	86	10	wang	wang	PROPN
fcis-28019	86	11	p	p	PROPN
fcis-28019	86	12	,	,	PUNCT
fcis-28019	86	13	et	et	PROPN
fcis-28019	86	14	al	al	PROPN
fcis-28019	86	15	.	.	PUNCT
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fcis-28019	86	17	of	of	ADP
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fcis-28019	86	19	's	's	PART
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fcis-28019	86	23	tree	tree	NOUN
fcis-28019	86	24	based	base	VERB
fcis-28019	86	25	instance	instance	NOUN
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fcis-28019	86	27	and	and	CCONJ
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fcis-28019	86	30	algorithms[j	algorithms[j	PROPN
fcis-28019	86	31	]	]	X
fcis-28019	86	32	.	.	PUNCT
fcis-28019	87	1	journal	journal	PROPN
fcis-28019	87	2	of	of	ADP
fcis-28019	87	3	medical	medical	ADJ
fcis-28019	87	4	imaging	imaging	NOUN
fcis-28019	87	5	and	and	CCONJ
fcis-28019	87	6	health	health	NOUN
fcis-28019	87	7	informatics	informatic	NOUN
fcis-28019	87	8	,	,	PUNCT
fcis-28019	87	9	2017	2017	NUM
fcis-28019	87	10	,	,	PUNCT
fcis-28019	87	11	7(2	7(2	NUM
fcis-28019	87	12	):	):	PUNCT
fcis-28019	87	13	444	444	NUM
fcis-28019	87	14	-	-	SYM
fcis-28019	87	15	452	452	NUM
fcis-28019	87	16	.	.	PUNCT
fcis-28019	88	1	[	[	X
fcis-28019	88	2	10	10	NUM
fcis-28019	88	3	]	]	PUNCT
fcis-28019	88	4	pramanik	pramanik	X
fcis-28019	88	5	m	m	PROPN
fcis-28019	88	6	,	,	PUNCT
fcis-28019	88	7	pradhan	pradhan	PROPN
fcis-28019	88	8	r	r	PROPN
fcis-28019	88	9	,	,	PUNCT
fcis-28019	88	10	nandy	nandy	PROPN
fcis-28019	88	11	p	p	PROPN
fcis-28019	88	12	,	,	PUNCT
fcis-28019	88	13	et	et	PROPN
fcis-28019	88	14	al	al	PROPN
fcis-28019	88	15	.	.	PUNCT
fcis-28019	89	1	the	the	DET
fcis-28019	89	2	forex++	forex++	ADJ
fcis-28019	89	3	based	base	VERB
fcis-28019	89	4	decision	decision	NOUN
fcis-28019	89	5	tree	tree	NOUN
fcis-28019	89	6	ensemble	ensemble	ADJ
fcis-28019	89	7	approach	approach	NOUN
fcis-28019	89	8	for	for	ADP
fcis-28019	89	9	robust	robust	ADJ
fcis-28019	89	10	detection	detection	NOUN
fcis-28019	89	11	of	of	ADP
fcis-28019	89	12	parkinson	parkinson	NOUN
fcis-28019	89	13	’s	’s	PART
fcis-28019	89	14	disease[j	disease[j	NOUN
fcis-28019	89	15	]	]	PUNCT
fcis-28019	89	16	.	.	PUNCT
fcis-28019	90	1	journal	journal	PROPN
fcis-28019	90	2	of	of	ADP
fcis-28019	90	3	ambient	ambient	ADJ
fcis-28019	90	4	intelligence	intelligence	NOUN
fcis-28019	90	5	and	and	CCONJ
fcis-28019	90	6	humanized	humanize	VERB
fcis-28019	90	7	computing	computing	NOUN
fcis-28019	90	8	,	,	PUNCT
fcis-28019	90	9	2023	2023	NUM
fcis-28019	90	10	,	,	PUNCT
fcis-28019	90	11	14(9	14(9	NUM
fcis-28019	90	12	):	):	PUNCT
fcis-28019	90	13	11429	11429	NUM
fcis-28019	90	14	-	-	SYM
fcis-28019	90	15	11453	11453	NUM
fcis-28019	90	16	.	.	PUNCT
fcis-28019	91	1	[	[	X
fcis-28019	91	2	11	11	NUM
fcis-28019	91	3	]	]	PUNCT
fcis-28019	91	4	ali	ali	PROPN
fcis-28019	91	5	l	l	PROPN
fcis-28019	91	6	,	,	PUNCT
fcis-28019	91	7	javeed	javeed	NOUN
fcis-28019	91	8	a	a	NOUN
fcis-28019	91	9	,	,	PUNCT
fcis-28019	91	10	noor	noor	PROPN
fcis-28019	91	11	a	a	PROPN
fcis-28019	91	12	,	,	PUNCT
fcis-28019	91	13	et	et	PROPN
fcis-28019	91	14	al	al	PROPN
fcis-28019	91	15	.	.	PROPN
fcis-28019	91	16	parkinson	parkinson	PROPN
fcis-28019	91	17	’s	’s	PART
fcis-28019	91	18	disease	disease	NOUN
fcis-28019	91	19	detection	detection	NOUN
fcis-28019	91	20	based	base	VERB
fcis-28019	91	21	on	on	ADP
fcis-28019	91	22	features	feature	NOUN
fcis-28019	91	23	refinement	refinement	VERB
fcis-28019	91	24	through	through	ADP
fcis-28019	91	25	l1	l1	PROPN
fcis-28019	91	26	regularized	regularize	VERB
fcis-28019	91	27	svm	svm	NOUN
fcis-28019	91	28	and	and	CCONJ
fcis-28019	91	29	deep	deep	ADJ
fcis-28019	91	30	neural	neural	ADJ
fcis-28019	91	31	network[j	network[j	PROPN
fcis-28019	91	32	]	]	PUNCT
fcis-28019	91	33	.	.	PUNCT
fcis-28019	92	1	scientific	scientific	ADJ
fcis-28019	92	2	reports	report	NOUN
fcis-28019	92	3	,	,	PUNCT
fcis-28019	92	4	2024	2024	NUM
fcis-28019	92	5	,	,	PUNCT
fcis-28019	92	6	14(1	14(1	NUM
fcis-28019	92	7	):	):	PUNCT
fcis-28019	92	8	1333	1333	NUM
fcis-28019	92	9	.	.	PUNCT