id	sid	tid	token	lemma	pos
ijassa-1100	1	1	adv	adv	PROPN
ijassa-1100	1	2	syst	syst	PROPN
ijassa-1100	1	3	sci	sci	PROPN
ijassa-1100	1	4	appl	appl	PROPN
ijassa-1100	1	5	2021	2021	NUM
ijassa-1100	1	6	;	;	PUNCT
ijassa-1100	1	7	03:31–39	03:31–39	NUM
ijassa-1100	1	8	published	publish	VERB
ijassa-1100	1	9	online	online	ADV
ijassa-1100	1	10	at	at	ADP
ijassa-1100	1	11	https://ijassa.ipu.ru	https://ijassa.ipu.ru	ADJ
ijassa-1100	1	12	.	.	PUNCT
ijassa-1100	2	1	convolution	convolution	NOUN
ijassa-1100	2	2	neural	neural	ADJ
ijassa-1100	2	3	network	network	NOUN
ijassa-1100	2	4	based	base	VERB
ijassa-1100	2	5	covid-19	covid-19	PROPN
ijassa-1100	2	6	screening	screen	VERB
ijassa-1100	2	7	model	model	NOUN
ijassa-1100	2	8	ashish	ashish	PROPN
ijassa-1100	2	9	nainwal	nainwal	PROPN
ijassa-1100	2	10	*	*	SYM
ijassa-1100	2	11	,	,	PUNCT
ijassa-1100	2	12	gorav	gorav	PROPN
ijassa-1100	2	13	kumar	kumar	PROPN
ijassa-1100	2	14	malik	malik	PROPN
ijassa-1100	2	15	,	,	PUNCT
ijassa-1100	2	16	amrish	amrish	PROPN
ijassa-1100	2	17	jangra	jangra	PROPN
ijassa-1100	2	18	dept	dept	PROPN
ijassa-1100	2	19	.	.	PROPN
ijassa-1100	3	1	of	of	ADP
ijassa-1100	3	2	electronics	electronic	NOUN
ijassa-1100	3	3	and	and	CCONJ
ijassa-1100	3	4	communication	communication	NOUN
ijassa-1100	3	5	engineering	engineering	NOUN
ijassa-1100	3	6	,	,	PUNCT
ijassa-1100	3	7	fet	fet	PROPN
ijassa-1100	3	8	gurukul	gurukul	PROPN
ijassa-1100	3	9	kangri	kangri	PROPN
ijassa-1100	3	10	(	(	PUNCT
ijassa-1100	3	11	deemed	deem	VERB
ijassa-1100	3	12	to	to	PART
ijassa-1100	3	13	be	be	AUX
ijassa-1100	3	14	)	)	PUNCT
ijassa-1100	3	15	university	university	NOUN
ijassa-1100	3	16	,	,	PUNCT
ijassa-1100	3	17	haridwar	haridwar	NOUN
ijassa-1100	3	18	,	,	PUNCT
ijassa-1100	3	19	uttarkhand	uttarkhand	ADJ
ijassa-1100	3	20	,	,	PUNCT
ijassa-1100	3	21	india	india	PROPN
ijassa-1100	3	22	abstract	abstract	NOUN
ijassa-1100	3	23	:	:	PUNCT
ijassa-1100	3	24	coronavirus	coronavirus	NOUN
ijassa-1100	3	25	disease	disease	NOUN
ijassa-1100	3	26	2019	2019	NUM
ijassa-1100	3	27	(	(	PUNCT
ijassa-1100	3	28	covid-19	covid-19	PROPN
ijassa-1100	3	29	)	)	PUNCT
ijassa-1100	3	30	is	be	AUX
ijassa-1100	3	31	a	a	DET
ijassa-1100	3	32	high	high	ADJ
ijassa-1100	3	33	death	death	NOUN
ijassa-1100	3	34	rate	rate	NOUN
ijassa-1100	3	35	respiratory	respiratory	ADJ
ijassa-1100	3	36	condition	condition	NOUN
ijassa-1100	3	37	that	that	PRON
ijassa-1100	3	38	requires	require	VERB
ijassa-1100	3	39	easy	easy	ADJ
ijassa-1100	3	40	-	-	PUNCT
ijassa-1100	3	41	to	to	PART
ijassa-1100	3	42	-	-	PUNCT
ijassa-1100	3	43	reach	reach	VERB
ijassa-1100	3	44	markers	marker	NOUN
ijassa-1100	3	45	for	for	ADP
ijassa-1100	3	46	prediction	prediction	NOUN
ijassa-1100	3	47	.	.	PUNCT
ijassa-1100	4	1	the	the	DET
ijassa-1100	4	2	electrocardiograph	electrocardiograph	NOUN
ijassa-1100	4	3	(	(	PUNCT
ijassa-1100	4	4	ecg	ecg	PROPN
ijassa-1100	4	5	)	)	PUNCT
ijassa-1100	4	6	alterations	alteration	NOUN
ijassa-1100	4	7	that	that	PRON
ijassa-1100	4	8	may	may	AUX
ijassa-1100	4	9	occur	occur	VERB
ijassa-1100	4	10	after	after	SCONJ
ijassa-1100	4	11	covid-19	covid-19	PROPN
ijassa-1100	4	12	hospitalization	hospitalization	NOUN
ijassa-1100	4	13	have	have	AUX
ijassa-1100	4	14	not	not	PART
ijassa-1100	4	15	been	be	AUX
ijassa-1100	4	16	fully	fully	ADV
ijassa-1100	4	17	studied	study	VERB
ijassa-1100	4	18	yet	yet	ADV
ijassa-1100	4	19	.	.	PUNCT
ijassa-1100	5	1	covid-19	covid-19	PROPN
ijassa-1100	5	2	also	also	ADV
ijassa-1100	5	3	affects	affect	VERB
ijassa-1100	5	4	heart	heart	NOUN
ijassa-1100	5	5	function	function	NOUN
ijassa-1100	5	6	,	,	PUNCT
ijassa-1100	5	7	which	which	PRON
ijassa-1100	5	8	can	can	AUX
ijassa-1100	5	9	be	be	AUX
ijassa-1100	5	10	seen	see	VERB
ijassa-1100	5	11	on	on	ADP
ijassa-1100	5	12	an	an	DET
ijassa-1100	5	13	ecg	ecg	PROPN
ijassa-1100	5	14	.	.	PROPN
ijassa-1100	6	1	as	as	ADP
ijassa-1100	6	2	a	a	DET
ijassa-1100	6	3	result	result	NOUN
ijassa-1100	6	4	,	,	PUNCT
ijassa-1100	6	5	ecg	ecg	PROPN
ijassa-1100	6	6	can	can	AUX
ijassa-1100	6	7	be	be	AUX
ijassa-1100	6	8	used	use	VERB
ijassa-1100	6	9	to	to	PART
ijassa-1100	6	10	detect	detect	VERB
ijassa-1100	6	11	virusinfected	virusinfected	ADJ
ijassa-1100	6	12	individuals	individual	NOUN
ijassa-1100	6	13	.	.	PUNCT
ijassa-1100	7	1	the	the	DET
ijassa-1100	7	2	database	database	NOUN
ijassa-1100	7	3	consists	consist	VERB
ijassa-1100	7	4	of	of	ADP
ijassa-1100	7	5	ecg	ecg	PROPN
ijassa-1100	7	6	images	image	NOUN
ijassa-1100	7	7	.	.	PUNCT
ijassa-1100	8	1	in	in	ADP
ijassa-1100	8	2	this	this	DET
ijassa-1100	8	3	scenario	scenario	NOUN
ijassa-1100	8	4	,	,	PUNCT
ijassa-1100	8	5	a	a	DET
ijassa-1100	8	6	convolution	convolution	NOUN
ijassa-1100	8	7	neural	neural	ADJ
ijassa-1100	8	8	network	network	NOUN
ijassa-1100	8	9	(	(	PUNCT
ijassa-1100	8	10	cnn	cnn	PROPN
ijassa-1100	8	11	)	)	PUNCT
ijassa-1100	8	12	is	be	AUX
ijassa-1100	8	13	utilized	utilize	VERB
ijassa-1100	8	14	to	to	PART
ijassa-1100	8	15	classify	classify	VERB
ijassa-1100	8	16	covid-19	covid-19	PROPN
ijassa-1100	8	17	ecg	ecg	PROPN
ijassa-1100	8	18	.	.	PUNCT
ijassa-1100	9	1	the	the	DET
ijassa-1100	9	2	model	model	NOUN
ijassa-1100	9	3	is	be	AUX
ijassa-1100	9	4	made	make	VERB
ijassa-1100	9	5	up	up	ADP
ijassa-1100	9	6	of	of	ADP
ijassa-1100	9	7	eight	eight	NUM
ijassa-1100	9	8	layers	layer	NOUN
ijassa-1100	9	9	,	,	PUNCT
ijassa-1100	9	10	including	include	VERB
ijassa-1100	9	11	a	a	DET
ijassa-1100	9	12	convolution	convolution	NOUN
ijassa-1100	9	13	layer	layer	NOUN
ijassa-1100	9	14	,	,	PUNCT
ijassa-1100	9	15	a	a	DET
ijassa-1100	9	16	max	max	NOUN
ijassa-1100	9	17	-	-	PUNCT
ijassa-1100	9	18	pooling	pool	VERB
ijassa-1100	9	19	layer	layer	NOUN
ijassa-1100	9	20	and	and	CCONJ
ijassa-1100	9	21	a	a	DET
ijassa-1100	9	22	dense	dense	ADJ
ijassa-1100	9	23	layer	layer	NOUN
ijassa-1100	9	24	.	.	PUNCT
ijassa-1100	10	1	the	the	DET
ijassa-1100	10	2	ecg	ecg	PROPN
ijassa-1100	10	3	image	image	NOUN
ijassa-1100	10	4	is	be	AUX
ijassa-1100	10	5	fed	feed	VERB
ijassa-1100	10	6	into	into	ADP
ijassa-1100	10	7	a	a	DET
ijassa-1100	10	8	cnn	cnn	PROPN
ijassa-1100	10	9	model	model	NOUN
ijassa-1100	10	10	,	,	PUNCT
ijassa-1100	10	11	which	which	PRON
ijassa-1100	10	12	classifies	classify	VERB
ijassa-1100	10	13	the	the	DET
ijassa-1100	10	14	covid-19	covid-19	PROPN
ijassa-1100	10	15	ecg	ecg	PROPN
ijassa-1100	10	16	.	.	PUNCT
ijassa-1100	11	1	the	the	DET
ijassa-1100	11	2	model	model	NOUN
ijassa-1100	11	3	provides	provide	VERB
ijassa-1100	11	4	us	we	PRON
ijassa-1100	11	5	with	with	ADP
ijassa-1100	11	6	98.11	98.11	NUM
ijassa-1100	11	7	%	%	NOUN
ijassa-1100	11	8	accuracy	accuracy	NOUN
ijassa-1100	11	9	,	,	PUNCT
ijassa-1100	11	10	98.6	98.6	NUM
ijassa-1100	11	11	%	%	NOUN
ijassa-1100	11	12	sensitivity	sensitivity	NOUN
ijassa-1100	11	13	and	and	CCONJ
ijassa-1100	11	14	96.40	96.40	NUM
ijassa-1100	11	15	%	%	NOUN
ijassa-1100	11	16	specificity	specificity	NOUN
ijassa-1100	11	17	.	.	PUNCT
ijassa-1100	12	1	although	although	SCONJ
ijassa-1100	12	2	100.00	100.00	NUM
ijassa-1100	12	3	%	%	NOUN
ijassa-1100	12	4	of	of	ADP
ijassa-1100	12	5	the	the	DET
ijassa-1100	12	6	categorization	categorization	NOUN
ijassa-1100	12	7	of	of	ADP
ijassa-1100	12	8	normal	normal	ADJ
ijassa-1100	12	9	images	image	NOUN
ijassa-1100	12	10	and	and	CCONJ
ijassa-1100	12	11	covid-19	covid-19	PROPN
ijassa-1100	12	12	ecgs	ecgs	NOUN
ijassa-1100	12	13	were	be	AUX
ijassa-1100	12	14	not	not	PART
ijassa-1100	12	15	accurately	accurately	ADV
ijassa-1100	12	16	determined	determine	VERB
ijassa-1100	12	17	by	by	ADP
ijassa-1100	12	18	the	the	DET
ijassa-1100	12	19	proposed	propose	VERB
ijassa-1100	12	20	cnn	cnn	PROPN
ijassa-1100	12	21	model	model	NOUN
ijassa-1100	12	22	,	,	PUNCT
ijassa-1100	12	23	this	this	PRON
ijassa-1100	12	24	is	be	AUX
ijassa-1100	12	25	the	the	DET
ijassa-1100	12	26	first	first	ADJ
ijassa-1100	12	27	cnn	cnn	PROPN
ijassa-1100	12	28	model	model	NOUN
ijassa-1100	12	29	to	to	PART
ijassa-1100	12	30	categorize	categorize	VERB
ijassa-1100	12	31	ecg	ecg	PROPN
ijassa-1100	12	32	images	image	NOUN
ijassa-1100	12	33	into	into	ADP
ijassa-1100	12	34	normal	normal	ADJ
ijassa-1100	12	35	and	and	CCONJ
ijassa-1100	12	36	covid-19	covid-19	PROPN
ijassa-1100	12	37	classes	class	NOUN
ijassa-1100	12	38	from	from	ADP
ijassa-1100	12	39	the	the	DET
ijassa-1100	12	40	ecg	ecg	PROPN
ijassa-1100	12	41	database	database	NOUN
ijassa-1100	12	42	and	and	CCONJ
ijassa-1100	12	43	provide	provide	VERB
ijassa-1100	12	44	additional	additional	ADJ
ijassa-1100	12	45	diagnostic	diagnostic	ADJ
ijassa-1100	12	46	to	to	ADP
ijassa-1100	12	47	medical	medical	ADJ
ijassa-1100	12	48	experts	expert	NOUN
ijassa-1100	12	49	.	.	PUNCT
ijassa-1100	13	1	keywords	keyword	NOUN
ijassa-1100	13	2	:	:	PUNCT
ijassa-1100	13	3	ecg	ecg	PROPN
ijassa-1100	13	4	,	,	PUNCT
ijassa-1100	13	5	convolution	convolution	NOUN
ijassa-1100	13	6	neural	neural	ADJ
ijassa-1100	13	7	network	network	NOUN
ijassa-1100	13	8	,	,	PUNCT
ijassa-1100	13	9	covid-19	covid-19	PROPN
ijassa-1100	13	10	1	1	NUM
ijassa-1100	13	11	.	.	PUNCT
ijassa-1100	14	1	introduction	introduction	NOUN
ijassa-1100	14	2	coronavirus	coronavirus	NOUN
ijassa-1100	14	3	disease	disease	NOUN
ijassa-1100	14	4	2019	2019	NUM
ijassa-1100	14	5	(	(	PUNCT
ijassa-1100	14	6	covid-19	covid-19	PROPN
ijassa-1100	14	7	)	)	PUNCT
ijassa-1100	14	8	is	be	AUX
ijassa-1100	14	9	the	the	DET
ijassa-1100	14	10	clinical	clinical	ADJ
ijassa-1100	14	11	sign	sign	NOUN
ijassa-1100	14	12	of	of	ADP
ijassa-1100	14	13	contamination	contamination	NOUN
ijassa-1100	14	14	with	with	ADP
ijassa-1100	14	15	the	the	DET
ijassa-1100	14	16	severe	severe	ADJ
ijassa-1100	14	17	acute	acute	ADJ
ijassa-1100	14	18	respiratory	respiratory	ADJ
ijassa-1100	14	19	syndrome	syndrome	NOUN
ijassa-1100	14	20	coronavirus-2	coronavirus-2	NUM
ijassa-1100	14	21	(	(	PUNCT
ijassa-1100	14	22	sars	sar	NOUN
ijassa-1100	14	23	-	-	PUNCT
ijassa-1100	14	24	cov-2	cov-2	NOUN
ijassa-1100	14	25	)	)	PUNCT
ijassa-1100	14	26	.	.	PUNCT
ijassa-1100	15	1	more	more	ADJ
ijassa-1100	15	2	than	than	ADP
ijassa-1100	15	3	170,000,000	170,000,000	NUM
ijassa-1100	15	4	persons	person	NOUN
ijassa-1100	15	5	in	in	ADP
ijassa-1100	15	6	more	more	ADJ
ijassa-1100	15	7	than	than	ADP
ijassa-1100	15	8	180	180	NUM
ijassa-1100	15	9	nations	nation	NOUN
ijassa-1100	15	10	or	or	CCONJ
ijassa-1100	15	11	regions	region	NOUN
ijassa-1100	15	12	worldwide	worldwide	ADV
ijassa-1100	15	13	suffered	suffer	VERB
ijassa-1100	15	14	as	as	ADP
ijassa-1100	15	15	a	a	DET
ijassa-1100	15	16	result	result	NOUN
ijassa-1100	15	17	of	of	ADP
ijassa-1100	15	18	the	the	DET
ijassa-1100	15	19	2019	2019	NUM
ijassa-1100	15	20	coronavirus	coronavirus	NOUN
ijassa-1100	15	21	disease	disease	NOUN
ijassa-1100	15	22	(	(	PUNCT
ijassa-1100	15	23	covid-19	covid-19	PROPN
ijassa-1100	15	24	)	)	PUNCT
ijassa-1100	15	25	global	global	ADJ
ijassa-1100	15	26	pandemic	pandemic	ADJ
ijassa-1100	15	27	[	[	X
ijassa-1100	15	28	1	1	NUM
ijassa-1100	15	29	]	]	PUNCT
ijassa-1100	15	30	.	.	PUNCT
ijassa-1100	16	1	the	the	DET
ijassa-1100	16	2	infection	infection	NOUN
ijassa-1100	16	3	’s	’s	PART
ijassa-1100	16	4	clinical	clinical	ADJ
ijassa-1100	16	5	course	course	NOUN
ijassa-1100	16	6	is	be	AUX
ijassa-1100	16	7	characterized	characterize	VERB
ijassa-1100	16	8	by	by	ADP
ijassa-1100	16	9	respiratory	respiratory	ADJ
ijassa-1100	16	10	symptoms	symptom	NOUN
ijassa-1100	16	11	(	(	PUNCT
ijassa-1100	16	12	fever	fever	NOUN
ijassa-1100	16	13	,	,	PUNCT
ijassa-1100	16	14	cough	cough	NOUN
ijassa-1100	16	15	,	,	PUNCT
ijassa-1100	16	16	and	and	CCONJ
ijassa-1100	16	17	tiredness	tiredness	NOUN
ijassa-1100	16	18	)	)	PUNCT
ijassa-1100	16	19	,	,	PUNCT
ijassa-1100	16	20	which	which	PRON
ijassa-1100	16	21	can	can	AUX
ijassa-1100	16	22	progress	progress	VERB
ijassa-1100	16	23	to	to	ADP
ijassa-1100	16	24	pneumonia	pneumonia	NOUN
ijassa-1100	16	25	,	,	PUNCT
ijassa-1100	16	26	acute	acute	ADJ
ijassa-1100	16	27	respiratory	respiratory	ADJ
ijassa-1100	16	28	distress	distress	NOUN
ijassa-1100	16	29	syndrome	syndrome	NOUN
ijassa-1100	16	30	(	(	PUNCT
ijassa-1100	16	31	ards	ard	NOUN
ijassa-1100	16	32	)	)	PUNCT
ijassa-1100	16	33	and	and	CCONJ
ijassa-1100	16	34	shock	shock	NOUN
ijassa-1100	17	1	[	[	X
ijassa-1100	17	2	2	2	NUM
ijassa-1100	17	3	]	]	PUNCT
ijassa-1100	17	4	.	.	PUNCT
ijassa-1100	18	1	the	the	DET
ijassa-1100	18	2	modern	modern	ADJ
ijassa-1100	18	3	world	world	NOUN
ijassa-1100	18	4	is	be	AUX
ijassa-1100	18	5	in	in	ADP
ijassa-1100	18	6	the	the	DET
ijassa-1100	18	7	midst	midst	NOUN
ijassa-1100	18	8	of	of	ADP
ijassa-1100	18	9	a	a	DET
ijassa-1100	18	10	never	never	ADV
ijassa-1100	18	11	-	-	PUNCT
ijassa-1100	18	12	before	before	ADV
ijassa-1100	18	13	-	-	PUNCT
ijassa-1100	18	14	seen	see	VERB
ijassa-1100	18	15	health	health	NOUN
ijassa-1100	18	16	disaster	disaster	NOUN
ijassa-1100	18	17	.	.	PUNCT
ijassa-1100	19	1	the	the	DET
ijassa-1100	19	2	covid-19	covid-19	PROPN
ijassa-1100	19	3	outbreak	outbreak	NOUN
ijassa-1100	19	4	is	be	AUX
ijassa-1100	19	5	wreaking	wreak	VERB
ijassa-1100	19	6	havoc	havoc	NOUN
ijassa-1100	19	7	on	on	ADP
ijassa-1100	19	8	hospitals	hospital	NOUN
ijassa-1100	19	9	and	and	CCONJ
ijassa-1100	19	10	medical	medical	ADJ
ijassa-1100	19	11	professionals	professional	NOUN
ijassa-1100	19	12	worldwide	worldwide	ADV
ijassa-1100	19	13	.	.	PUNCT
ijassa-1100	20	1	according	accord	VERB
ijassa-1100	20	2	to	to	ADP
ijassa-1100	20	3	epidemiological	epidemiological	ADJ
ijassa-1100	20	4	statistics	statistic	NOUN
ijassa-1100	20	5	,	,	PUNCT
ijassa-1100	20	6	coronavirus	coronavirus	NOUN
ijassa-1100	20	7	patients	patient	NOUN
ijassa-1100	20	8	with	with	ADP
ijassa-1100	20	9	prior	prior	ADJ
ijassa-1100	20	10	cardiovascular	cardiovascular	ADJ
ijassa-1100	20	11	irregularities	irregularity	NOUN
ijassa-1100	20	12	are	be	AUX
ijassa-1100	20	13	at	at	ADP
ijassa-1100	20	14	a	a	DET
ijassa-1100	20	15	higher	high	ADJ
ijassa-1100	20	16	danger	danger	NOUN
ijassa-1100	20	17	of	of	ADP
ijassa-1100	20	18	pre	pre	VERB
ijassa-1100	20	19	and	and	CCONJ
ijassa-1100	20	20	post	post	VERB
ijassa-1100	20	21	covid19	covid19	NOUN
ijassa-1100	20	22	related	relate	VERB
ijassa-1100	20	23	issues	issue	NOUN
ijassa-1100	20	24	and	and	CCONJ
ijassa-1100	20	25	mortality	mortality	NOUN
ijassa-1100	20	26	[	[	X
ijassa-1100	20	27	3	3	NUM
ijassa-1100	20	28	]	]	PUNCT
ijassa-1100	20	29	.	.	PUNCT
ijassa-1100	21	1	covid-19	covid-19	PROPN
ijassa-1100	21	2	has	have	VERB
ijassa-1100	21	3	the	the	DET
ijassa-1100	21	4	potential	potential	NOUN
ijassa-1100	21	5	to	to	PART
ijassa-1100	21	6	affect	affect	VERB
ijassa-1100	21	7	the	the	DET
ijassa-1100	21	8	heart	heart	NOUN
ijassa-1100	21	9	and	and	CCONJ
ijassa-1100	21	10	lungs	lung	NOUN
ijassa-1100	21	11	.	.	PUNCT
ijassa-1100	22	1	according	accord	VERB
ijassa-1100	22	2	to	to	ADP
ijassa-1100	22	3	several	several	ADJ
ijassa-1100	22	4	articles	article	NOUN
ijassa-1100	22	5	,	,	PUNCT
ijassa-1100	22	6	covid-19	covid-19	PROPN
ijassa-1100	22	7	has	have	AUX
ijassa-1100	22	8	been	be	AUX
ijassa-1100	22	9	related	relate	VERB
ijassa-1100	22	10	to	to	ADP
ijassa-1100	22	11	myocarditis	myocarditis	ADJ
ijassa-1100	22	12	,	,	PUNCT
ijassa-1100	22	13	acute	acute	ADJ
ijassa-1100	22	14	coronary	coronary	ADJ
ijassa-1100	22	15	syndromes	syndrome	NOUN
ijassa-1100	22	16	and	and	CCONJ
ijassa-1100	22	17	decompensated	decompensate	VERB
ijassa-1100	22	18	heart	heart	NOUN
ijassa-1100	22	19	failure	failure	NOUN
ijassa-1100	22	20	[	[	X
ijassa-1100	22	21	4	4	X
ijassa-1100	22	22	]	]	X
ijassa-1100	22	23	[	[	X
ijassa-1100	22	24	5	5	NUM
ijassa-1100	22	25	]	]	X
ijassa-1100	23	1	[	[	X
ijassa-1100	23	2	6	6	NUM
ijassa-1100	23	3	]	]	PUNCT
ijassa-1100	23	4	.	.	PUNCT
ijassa-1100	24	1	the	the	DET
ijassa-1100	24	2	pandemic	pandemic	NOUN
ijassa-1100	24	3	also	also	ADV
ijassa-1100	24	4	emphasizes	emphasize	VERB
ijassa-1100	24	5	the	the	DET
ijassa-1100	24	6	importance	importance	NOUN
ijassa-1100	24	7	of	of	ADP
ijassa-1100	24	8	preparing	prepare	VERB
ijassa-1100	24	9	cardiac	cardiac	ADJ
ijassa-1100	24	10	healthcare	healthcare	NOUN
ijassa-1100	24	11	for	for	ADP
ijassa-1100	24	12	covid-19	covid-19	PROPN
ijassa-1100	24	13	as	as	ADV
ijassa-1100	24	14	well	well	ADV
ijassa-1100	24	15	as	as	ADP
ijassa-1100	24	16	acute	acute	ADJ
ijassa-1100	24	17	and	and	CCONJ
ijassa-1100	24	18	chronic	chronic	ADJ
ijassa-1100	24	19	cardiac	cardiac	NOUN
ijassa-1100	24	20	therapy	therapy	NOUN
ijassa-1100	24	21	in	in	ADP
ijassa-1100	24	22	individuals	individual	NOUN
ijassa-1100	24	23	where	where	SCONJ
ijassa-1100	24	24	patient	patient	ADJ
ijassa-1100	24	25	and	and	CCONJ
ijassa-1100	24	26	medical	medical	ADJ
ijassa-1100	24	27	delays	delay	NOUN
ijassa-1100	24	28	could	could	AUX
ijassa-1100	24	29	be	be	AUX
ijassa-1100	24	30	hazardous	hazardous	ADJ
ijassa-1100	24	31	.	.	PUNCT
ijassa-1100	25	1	lecun	lecun	PROPN
ijassa-1100	25	2	et	et	PROPN
ijassa-1100	25	3	al	al	PROPN
ijassa-1100	25	4	.	.	PROPN
ijassa-1100	25	5	introduced	introduce	VERB
ijassa-1100	25	6	cnn	cnn	PROPN
ijassa-1100	25	7	in	in	ADP
ijassa-1100	25	8	1990	1990	NUM
ijassa-1100	25	9	and	and	CCONJ
ijassa-1100	25	10	in	in	ADP
ijassa-1100	25	11	recent	recent	ADJ
ijassa-1100	25	12	years	year	NOUN
ijassa-1100	25	13	,	,	PUNCT
ijassa-1100	25	14	it	it	PRON
ijassa-1100	25	15	has	have	AUX
ijassa-1100	25	16	become	become	VERB
ijassa-1100	25	17	one	one	NUM
ijassa-1100	25	18	of	of	ADP
ijassa-1100	25	19	the	the	DET
ijassa-1100	25	20	most	most	ADV
ijassa-1100	25	21	potent	potent	ADJ
ijassa-1100	25	22	methods	method	NOUN
ijassa-1100	25	23	of	of	ADP
ijassa-1100	25	24	machine	machine	NOUN
ijassa-1100	25	25	learning	learn	VERB
ijassa-1100	26	1	[	[	X
ijassa-1100	26	2	7	7	NUM
ijassa-1100	26	3	]	]	PUNCT
ijassa-1100	26	4	.	.	PUNCT
ijassa-1100	27	1	cnn	cnn	PROPN
ijassa-1100	27	2	offers	offer	VERB
ijassa-1100	27	3	benefits	benefit	NOUN
ijassa-1100	27	4	both	both	PRON
ijassa-1100	27	5	in	in	ADP
ijassa-1100	27	6	accuracy	accuracy	NOUN
ijassa-1100	27	7	and	and	CCONJ
ijassa-1100	27	8	performance	performance	NOUN
ijassa-1100	27	9	in	in	ADP
ijassa-1100	27	10	imaging	imaging	NOUN
ijassa-1100	27	11	recognition	recognition	NOUN
ijassa-1100	27	12	,	,	PUNCT
ijassa-1100	27	13	sound	sound	ADJ
ijassa-1100	27	14	classification	classification	NOUN
ijassa-1100	27	15	and	and	CCONJ
ijassa-1100	27	16	semantic	semantic	ADJ
ijassa-1100	27	17	identification	identification	NOUN
ijassa-1100	27	18	with	with	ADP
ijassa-1100	27	19	the	the	DET
ijassa-1100	27	20	support	support	NOUN
ijassa-1100	27	21	of	of	ADP
ijassa-1100	27	22	fast	fast	ADV
ijassa-1100	27	23	-	-	PUNCT
ijassa-1100	27	24	growing	grow	VERB
ijassa-1100	27	25	graphics	graphic	NOUN
ijassa-1100	27	26	process	process	NOUN
ijassa-1100	27	27	unit	unit	NOUN
ijassa-1100	27	28	(	(	PUNCT
ijassa-1100	27	29	gpu	gpu	NOUN
ijassa-1100	27	30	)	)	PUNCT
ijassa-1100	27	31	technology	technology	NOUN
ijassa-1100	27	32	[	[	X
ijassa-1100	27	33	8	8	NUM
ijassa-1100	27	34	]	]	X
ijassa-1100	28	1	[	[	X
ijassa-1100	28	2	9	9	NUM
ijassa-1100	28	3	]	]	X
ijassa-1100	28	4	[	[	X
ijassa-1100	28	5	10	10	NUM
ijassa-1100	28	6	]	]	PUNCT
ijassa-1100	28	7	.	.	PUNCT
ijassa-1100	29	1	in	in	ADP
ijassa-1100	29	2	addition	addition	NOUN
ijassa-1100	29	3	,	,	PUNCT
ijassa-1100	29	4	recent	recent	ADJ
ijassa-1100	29	5	research	research	NOUN
ijassa-1100	29	6	has	have	AUX
ijassa-1100	29	7	demonstrated	demonstrate	VERB
ijassa-1100	29	8	the	the	DET
ijassa-1100	29	9	considerable	considerable	ADJ
ijassa-1100	29	10	promise	promise	NOUN
ijassa-1100	29	11	of	of	ADP
ijassa-1100	29	12	cnn	cnn	PROPN
ijassa-1100	29	13	with	with	ADP
ijassa-1100	29	14	biological	biological	ADJ
ijassa-1100	29	15	applications	application	NOUN
ijassa-1100	29	16	including	include	VERB
ijassa-1100	29	17	categorization	categorization	NOUN
ijassa-1100	29	18	of	of	ADP
ijassa-1100	29	19	animal	animal	NOUN
ijassa-1100	29	20	behavior	behavior	NOUN
ijassa-1100	29	21	,	,	PUNCT
ijassa-1100	29	22	the	the	DET
ijassa-1100	29	23	prediction	prediction	NOUN
ijassa-1100	29	24	of	of	ADP
ijassa-1100	29	25	protein	protein	NOUN
ijassa-1100	29	26	structures	structure	NOUN
ijassa-1100	29	27	∗corresponding	∗corresponde	VERB
ijassa-1100	29	28	author	author	NOUN
ijassa-1100	29	29	:	:	PUNCT
ijassa-1100	29	30	ashishnainwal86@gmail.com	ashishnainwal86@gmail.com	X
ijassa-1100	29	31	32	32	NUM
ijassa-1100	29	32	a.	a.	NOUN
ijassa-1100	29	33	nainwal	nainwal	NOUN
ijassa-1100	29	34	,	,	PUNCT
ijassa-1100	29	35	g	g	PROPN
ijassa-1100	29	36	k	k	PROPN
ijassa-1100	29	37	malik	malik	PROPN
ijassa-1100	29	38	,	,	PUNCT
ijassa-1100	29	39	amrish	amrish	VERB
ijassa-1100	29	40	and	and	CCONJ
ijassa-1100	29	41	pattern	pattern	NOUN
ijassa-1100	29	42	recognition	recognition	NOUN
ijassa-1100	29	43	(	(	PUNCT
ijassa-1100	29	44	emg	emg	NOUN
ijassa-1100	29	45	)	)	PUNCT
ijassa-1100	30	1	[	[	X
ijassa-1100	30	2	11	11	NUM
ijassa-1100	30	3	]	]	X
ijassa-1100	30	4	[	[	X
ijassa-1100	30	5	12	12	NUM
ijassa-1100	30	6	]	]	PUNCT
ijassa-1100	30	7	.	.	PUNCT
ijassa-1100	31	1	recent	recent	ADJ
ijassa-1100	31	2	research	research	NOUN
ijassa-1100	31	3	has	have	AUX
ijassa-1100	31	4	also	also	ADV
ijassa-1100	31	5	identified	identify	VERB
ijassa-1100	31	6	intriguing	intriguing	ADJ
ijassa-1100	31	7	uses	use	NOUN
ijassa-1100	31	8	of	of	ADP
ijassa-1100	31	9	cnn	cnn	PROPN
ijassa-1100	31	10	in	in	ADP
ijassa-1100	31	11	bio	bio	NOUN
ijassa-1100	31	12	-	-	PUNCT
ijassa-1100	31	13	signals	signal	NOUN
ijassa-1100	31	14	such	such	ADJ
ijassa-1100	31	15	as	as	ADP
ijassa-1100	31	16	ecg	ecg	PROPN
ijassa-1100	31	17	for	for	ADP
ijassa-1100	31	18	time	time	NOUN
ijassa-1100	31	19	series	series	NOUN
ijassa-1100	31	20	[	[	X
ijassa-1100	31	21	13	13	NUM
ijassa-1100	31	22	]	]	PUNCT
ijassa-1100	31	23	.	.	PUNCT
ijassa-1100	32	1	the	the	DET
ijassa-1100	32	2	cnn	cnn	PROPN
ijassa-1100	32	3	framework	framework	NOUN
ijassa-1100	32	4	benefits	benefit	NOUN
ijassa-1100	32	5	from	from	ADP
ijassa-1100	32	6	using	use	VERB
ijassa-1100	32	7	the	the	DET
ijassa-1100	32	8	huge	huge	ADJ
ijassa-1100	32	9	training	training	NOUN
ijassa-1100	32	10	data	datum	NOUN
ijassa-1100	32	11	set	set	VERB
ijassa-1100	32	12	to	to	ADP
ijassa-1100	32	13	overall	overall	ADJ
ijassa-1100	32	14	improvements	improvement	NOUN
ijassa-1100	32	15	of	of	ADP
ijassa-1100	32	16	classification	classification	NOUN
ijassa-1100	32	17	parameters	parameter	NOUN
ijassa-1100	32	18	.	.	PUNCT
ijassa-1100	33	1	degerli	degerli	ADV
ijassa-1100	33	2	et	et	PROPN
ijassa-1100	33	3	al	al	PROPN
ijassa-1100	33	4	.	.	PROPN
ijassa-1100	33	5	have	have	AUX
ijassa-1100	33	6	developed	develop	VERB
ijassa-1100	33	7	a	a	DET
ijassa-1100	33	8	unique	unique	ADJ
ijassa-1100	33	9	methodology	methodology	NOUN
ijassa-1100	33	10	to	to	ADP
ijassa-1100	33	11	the	the	DET
ijassa-1100	33	12	composite	composite	ADJ
ijassa-1100	33	13	location	location	NOUN
ijassa-1100	33	14	,	,	PUNCT
ijassa-1100	33	15	gradation	gradation	NOUN
ijassa-1100	33	16	and	and	CCONJ
ijassa-1100	33	17	detection	detection	NOUN
ijassa-1100	33	18	of	of	ADP
ijassa-1100	33	19	covid-19	covid-19	PROPN
ijassa-1100	33	20	from	from	ADP
ijassa-1100	33	21	15495	15495	NUM
ijassa-1100	33	22	cxr	cxr	NOUN
ijassa-1100	33	23	images	image	NOUN
ijassa-1100	33	24	with	with	ADP
ijassa-1100	33	25	the	the	DET
ijassa-1100	33	26	creation	creation	NOUN
ijassa-1100	33	27	of	of	ADP
ijassa-1100	33	28	the	the	DET
ijassa-1100	33	29	”	"	PUNCT
ijassa-1100	33	30	infection	infection	NOUN
ijassa-1100	33	31	mappings	mapping	NOUN
ijassa-1100	33	32	”	"	PUNCT
ijassa-1100	33	33	capable	capable	ADJ
ijassa-1100	33	34	of	of	ADP
ijassa-1100	33	35	precisely	precisely	ADV
ijassa-1100	33	36	detecting	detect	VERB
ijassa-1100	33	37	and	and	CCONJ
ijassa-1100	33	38	grading	grade	VERB
ijassa-1100	33	39	covid-19	covid-19	PROPN
ijassa-1100	33	40	seriousness	seriousness	NOUN
ijassa-1100	33	41	with	with	ADP
ijassa-1100	33	42	a	a	DET
ijassa-1100	33	43	precision	precision	NOUN
ijassa-1100	33	44	of	of	ADP
ijassa-1100	33	45	98.69	98.69	NUM
ijassa-1100	33	46	%	%	NOUN
ijassa-1100	33	47	[	[	X
ijassa-1100	33	48	14	14	NUM
ijassa-1100	33	49	]	]	PUNCT
ijassa-1100	33	50	.	.	PUNCT
ijassa-1100	34	1	kesim	kesim	PROPN
ijassa-1100	34	2	et	et	PROPN
ijassa-1100	34	3	al	al	PROPN
ijassa-1100	34	4	.	.	PROPN
ijassa-1100	34	5	suggested	suggest	VERB
ijassa-1100	34	6	a	a	DET
ijassa-1100	34	7	new	new	ADJ
ijassa-1100	34	8	cnn	cnn	NOUN
ijassa-1100	34	9	model	model	NOUN
ijassa-1100	34	10	for	for	ADP
ijassa-1100	34	11	chest	chest	NOUN
ijassa-1100	34	12	radiography	radiography	NOUN
ijassa-1100	34	13	data	datum	NOUN
ijassa-1100	34	14	(	(	PUNCT
ijassa-1100	34	15	xray	xray	NOUN
ijassa-1100	34	16	images	image	NOUN
ijassa-1100	34	17	)	)	PUNCT
ijassa-1100	34	18	categorization	categorization	NOUN
ijassa-1100	34	19	[	[	X
ijassa-1100	34	20	15	15	NUM
ijassa-1100	34	21	]	]	PUNCT
ijassa-1100	34	22	.	.	PUNCT
ijassa-1100	35	1	several	several	ADJ
ijassa-1100	35	2	in	in	ADP
ijassa-1100	35	3	-	-	PUNCT
ijassa-1100	35	4	depth	depth	NOUN
ijassa-1100	35	5	learning	learning	NOUN
ijassa-1100	35	6	models	model	NOUN
ijassa-1100	35	7	,	,	PUNCT
ijassa-1100	35	8	including	include	VERB
ijassa-1100	35	9	chest	chest	NOUN
ijassa-1100	35	10	x	x	NOUN
ijassa-1100	35	11	-	-	NOUN
ijassa-1100	35	12	ray	ray	NOUN
ijassa-1100	35	13	pictures	picture	NOUN
ijassa-1100	35	14	and	and	CCONJ
ijassa-1100	35	15	computer	computer	NOUN
ijassa-1100	35	16	ct	ct	PROPN
ijassa-1100	35	17	scans	scan	NOUN
ijassa-1100	35	18	have	have	AUX
ijassa-1100	35	19	been	be	AUX
ijassa-1100	35	20	proposed	propose	VERB
ijassa-1100	35	21	in	in	ADP
ijassa-1100	35	22	recent	recent	ADJ
ijassa-1100	35	23	research	research	NOUN
ijassa-1100	35	24	to	to	PART
ijassa-1100	35	25	detect	detect	VERB
ijassa-1100	35	26	anomalies	anomaly	NOUN
ijassa-1100	35	27	of	of	ADP
ijassa-1100	35	28	covid-19	covid-19	PROPN
ijassa-1100	35	29	in	in	ADP
ijassa-1100	35	30	patient	patient	ADJ
ijassa-1100	35	31	healthcare	healthcare	NOUN
ijassa-1100	35	32	[	[	X
ijassa-1100	35	33	16	16	NUM
ijassa-1100	35	34	]	]	PUNCT
ijassa-1100	35	35	.	.	PUNCT
ijassa-1100	36	1	in	in	ADP
ijassa-1100	36	2	this	this	DET
ijassa-1100	36	3	article	article	NOUN
ijassa-1100	36	4	,	,	PUNCT
ijassa-1100	36	5	the	the	DET
ijassa-1100	36	6	covid-19	covid-19	PROPN
ijassa-1100	36	7	patient	patient	NOUN
ijassa-1100	36	8	ecg	ecg	PROPN
ijassa-1100	36	9	and	and	CCONJ
ijassa-1100	36	10	normal	normal	ADJ
ijassa-1100	36	11	ecg	ecg	PROPN
ijassa-1100	36	12	images	image	NOUN
ijassa-1100	36	13	were	be	AUX
ijassa-1100	36	14	put	put	VERB
ijassa-1100	36	15	to	to	ADP
ijassa-1100	36	16	the	the	DET
ijassa-1100	36	17	proposed	propose	VERB
ijassa-1100	36	18	convolution	convolution	NOUN
ijassa-1100	36	19	neural	neural	ADJ
ijassa-1100	36	20	network	network	NOUN
ijassa-1100	36	21	.	.	PUNCT
ijassa-1100	37	1	the	the	DET
ijassa-1100	37	2	proposed	propose	VERB
ijassa-1100	37	3	cnn	cnn	PROPN
ijassa-1100	37	4	model	model	NOUN
ijassa-1100	37	5	has	have	VERB
ijassa-1100	37	6	eight	eight	NUM
ijassa-1100	37	7	layers	layer	NOUN
ijassa-1100	37	8	,	,	PUNCT
ijassa-1100	37	9	comprising	comprise	VERB
ijassa-1100	37	10	three	three	NUM
ijassa-1100	37	11	convolution	convolution	NOUN
ijassa-1100	37	12	layers	layer	NOUN
ijassa-1100	37	13	,	,	PUNCT
ijassa-1100	37	14	three	three	NUM
ijassa-1100	37	15	pooling	pool	VERB
ijassa-1100	37	16	layers	layer	NOUN
ijassa-1100	37	17	and	and	CCONJ
ijassa-1100	37	18	two	two	NUM
ijassa-1100	37	19	dense	dense	ADJ
ijassa-1100	37	20	layers	layer	NOUN
ijassa-1100	37	21	.	.	PUNCT
ijassa-1100	38	1	the	the	DET
ijassa-1100	38	2	approaches	approach	NOUN
ijassa-1100	38	3	yielded	yield	VERB
ijassa-1100	38	4	good	good	ADJ
ijassa-1100	38	5	results	result	NOUN
ijassa-1100	38	6	for	for	ADP
ijassa-1100	38	7	classifying	classify	VERB
ijassa-1100	38	8	covid-19	covid-19	PROPN
ijassa-1100	38	9	patients	patient	NOUN
ijassa-1100	38	10	based	base	VERB
ijassa-1100	38	11	on	on	ADP
ijassa-1100	38	12	their	their	PRON
ijassa-1100	38	13	ecg	ecg	PROPN
ijassa-1100	38	14	.	.	PROPN
ijassa-1100	38	15	2	2	NUM
ijassa-1100	38	16	.	.	NOUN
ijassa-1100	38	17	method	method	NOUN
ijassa-1100	38	18	and	and	CCONJ
ijassa-1100	38	19	material	material	NOUN
ijassa-1100	38	20	2.1	2.1	NUM
ijassa-1100	38	21	.	.	PUNCT
ijassa-1100	39	1	database	database	VERB
ijassa-1100	39	2	the	the	DET
ijassa-1100	39	3	collection	collection	NOUN
ijassa-1100	39	4	of	of	ADP
ijassa-1100	39	5	data	datum	NOUN
ijassa-1100	39	6	is	be	AUX
ijassa-1100	39	7	in	in	ADP
ijassa-1100	39	8	image	image	NOUN
ijassa-1100	39	9	data	datum	NOUN
ijassa-1100	39	10	form	form	NOUN
ijassa-1100	39	11	[	[	X
ijassa-1100	39	12	17	17	NUM
ijassa-1100	39	13	]	]	PUNCT
ijassa-1100	39	14	.	.	PUNCT
ijassa-1100	40	1	ch	ch	PROPN
ijassa-1100	40	2	.	.	PROPN
ijassa-1100	40	3	pervaiz	pervaiz	PROPN
ijassa-1100	40	4	elahi	elahi	PROPN
ijassa-1100	40	5	institute	institute	PROPN
ijassa-1100	40	6	of	of	ADP
ijassa-1100	40	7	cardiology	cardiology	NOUN
ijassa-1100	40	8	,	,	PUNCT
ijassa-1100	40	9	nishtar	nishtar	PROPN
ijassa-1100	40	10	medical	medical	PROPN
ijassa-1100	40	11	university	university	PROPN
ijassa-1100	40	12	and	and	CCONJ
ijassa-1100	40	13	punjab	punjab	PROPN
ijassa-1100	40	14	institute	institute	PROPN
ijassa-1100	40	15	of	of	ADP
ijassa-1100	40	16	cardiology	cardiology	NOUN
ijassa-1100	40	17	are	be	AUX
ijassa-1100	40	18	the	the	DET
ijassa-1100	40	19	data	datum	NOUN
ijassa-1100	40	20	sources	source	NOUN
ijassa-1100	40	21	,	,	PUNCT
ijassa-1100	40	22	all	all	PRON
ijassa-1100	40	23	of	of	ADP
ijassa-1100	40	24	which	which	PRON
ijassa-1100	40	25	are	be	AUX
ijassa-1100	40	26	situated	situate	VERB
ijassa-1100	40	27	in	in	ADP
ijassa-1100	40	28	pakistan	pakistan	PROPN
ijassa-1100	40	29	.	.	PUNCT
ijassa-1100	41	1	this	this	DET
ijassa-1100	41	2	image	image	NOUN
ijassa-1100	41	3	data	data	NOUN
ijassa-1100	41	4	collection	collection	NOUN
ijassa-1100	41	5	is	be	AUX
ijassa-1100	41	6	collected	collect	VERB
ijassa-1100	41	7	with	with	ADP
ijassa-1100	41	8	12	12	NUM
ijassa-1100	41	9	lead	lead	NOUN
ijassa-1100	41	10	-	-	PUNCT
ijassa-1100	41	11	based	base	VERB
ijassa-1100	41	12	edan	edan	PROPN
ijassa-1100	41	13	series	series	PROPN
ijassa-1100	41	14	equipment	equipment	PROPN
ijassa-1100	41	15	.	.	PUNCT
ijassa-1100	42	1	the	the	DET
ijassa-1100	42	2	rate	rate	NOUN
ijassa-1100	42	3	of	of	ADP
ijassa-1100	42	4	sampling	sample	VERB
ijassa-1100	42	5	is	be	AUX
ijassa-1100	42	6	500hz	500hz	NOUN
ijassa-1100	42	7	.	.	PUNCT
ijassa-1100	43	1	several	several	ADJ
ijassa-1100	43	2	medical	medical	ADJ
ijassa-1100	43	3	professionals	professional	NOUN
ijassa-1100	43	4	have	have	AUX
ijassa-1100	43	5	marked	mark	VERB
ijassa-1100	43	6	all	all	DET
ijassa-1100	43	7	ecg	ecg	PROPN
ijassa-1100	43	8	images	image	NOUN
ijassa-1100	43	9	.	.	PUNCT
ijassa-1100	44	1	figure	figure	VERB
ijassa-1100	44	2	2.1	2.1	NUM
ijassa-1100	44	3	and	and	CCONJ
ijassa-1100	44	4	2.2	2.2	NUM
ijassa-1100	44	5	shows	show	VERB
ijassa-1100	44	6	the	the	DET
ijassa-1100	44	7	image	image	NOUN
ijassa-1100	44	8	of	of	ADP
ijassa-1100	44	9	normal	normal	ADJ
ijassa-1100	44	10	ecg	ecg	PROPN
ijassa-1100	44	11	and	and	CCONJ
ijassa-1100	44	12	covid-19	covid-19	PROPN
ijassa-1100	44	13	patient	patient	NOUN
ijassa-1100	44	14	ecg	ecg	PROPN
ijassa-1100	44	15	respectively	respectively	ADV
ijassa-1100	44	16	.	.	PUNCT
ijassa-1100	45	1	s.	s.	PROPN
ijassa-1100	45	2	no	no	DET
ijassa-1100	45	3	type	type	NOUN
ijassa-1100	45	4	of	of	ADP
ijassa-1100	45	5	ecg	ecg	PROPN
ijassa-1100	45	6	no	no	PROPN
ijassa-1100	45	7	of	of	ADP
ijassa-1100	45	8	images	image	NOUN
ijassa-1100	45	9	sampling	sample	VERB
ijassa-1100	45	10	rate	rate	NOUN
ijassa-1100	45	11	1	1	NUM
ijassa-1100	45	12	covid-19	covid-19	PROPN
ijassa-1100	45	13	250	250	NUM
ijassa-1100	45	14	500	500	NUM
ijassa-1100	45	15	2	2	NUM
ijassa-1100	45	16	normal	normal	ADJ
ijassa-1100	45	17	859	859	NUM
ijassa-1100	45	18	500	500	NUM
ijassa-1100	45	19	table	table	NOUN
ijassa-1100	45	20	2.1	2.1	NUM
ijassa-1100	45	21	.	.	PUNCT
ijassa-1100	46	1	data	datum	NOUN
ijassa-1100	46	2	set	set	VERB
ijassa-1100	46	3	details	detail	NOUN
ijassa-1100	46	4	all	all	DET
ijassa-1100	46	5	ecg	ecg	PROPN
ijassa-1100	46	6	devices	device	NOUN
ijassa-1100	46	7	used	use	VERB
ijassa-1100	46	8	to	to	PART
ijassa-1100	46	9	collect	collect	VERB
ijassa-1100	46	10	data	datum	NOUN
ijassa-1100	46	11	have	have	AUX
ijassa-1100	46	12	been	be	AUX
ijassa-1100	46	13	set	set	VERB
ijassa-1100	46	14	up	up	ADP
ijassa-1100	46	15	as	as	ADP
ijassa-1100	46	16	”	"	PUNCT
ijassa-1100	46	17	on	on	ADP
ijassa-1100	46	18	”	"	PUNCT
ijassa-1100	46	19	for	for	ADP
ijassa-1100	46	20	important	important	ADJ
ijassa-1100	46	21	warnings	warning	NOUN
ijassa-1100	46	22	.	.	PUNCT
ijassa-1100	47	1	ecg	ecg	PROPN
ijassa-1100	47	2	technicians	technician	NOUN
ijassa-1100	47	3	are	be	AUX
ijassa-1100	47	4	taught	teach	VERB
ijassa-1100	47	5	to	to	PART
ijassa-1100	47	6	respond	respond	VERB
ijassa-1100	47	7	to	to	ADP
ijassa-1100	47	8	all	all	DET
ijassa-1100	47	9	forms	form	NOUN
ijassa-1100	47	10	of	of	ADP
ijassa-1100	47	11	edan	edan	PROPN
ijassa-1100	47	12	ecg	ecg	PROPN
ijassa-1100	47	13	device	device	NOUN
ijassa-1100	47	14	alerts	alert	VERB
ijassa-1100	47	15	so	so	SCONJ
ijassa-1100	47	16	that	that	SCONJ
ijassa-1100	47	17	ecg	ecg	PROPN
ijassa-1100	47	18	technicians	technician	NOUN
ijassa-1100	47	19	are	be	AUX
ijassa-1100	47	20	able	able	ADJ
ijassa-1100	47	21	to	to	PART
ijassa-1100	47	22	carry	carry	VERB
ijassa-1100	47	23	out	out	ADP
ijassa-1100	47	24	all	all	DET
ijassa-1100	47	25	precautionary	precautionary	ADJ
ijassa-1100	47	26	actions	action	NOUN
ijassa-1100	47	27	during	during	ADP
ijassa-1100	47	28	ecg	ecg	PROPN
ijassa-1100	47	29	operations	operation	NOUN
ijassa-1100	47	30	.	.	PUNCT
ijassa-1100	48	1	this	this	DET
ijassa-1100	48	2	step	step	NOUN
ijassa-1100	48	3	is	be	AUX
ijassa-1100	48	4	crucial	crucial	ADJ
ijassa-1100	48	5	to	to	AUX
ijassa-1100	48	6	more	more	ADV
ijassa-1100	48	7	precisely	precisely	ADV
ijassa-1100	48	8	capture	capture	VERB
ijassa-1100	48	9	ecg	ecg	PROPN
ijassa-1100	48	10	images	image	NOUN
ijassa-1100	48	11	,	,	PUNCT
ijassa-1100	48	12	the	the	DET
ijassa-1100	48	13	data	datum	NOUN
ijassa-1100	48	14	created	create	VERB
ijassa-1100	48	15	by	by	ADP
ijassa-1100	48	16	highly	highly	ADV
ijassa-1100	48	17	qualified	qualified	ADJ
ijassa-1100	48	18	professionals	professional	NOUN
ijassa-1100	48	19	actively	actively	ADV
ijassa-1100	48	20	involved	involve	VERB
ijassa-1100	48	21	for	for	ADP
ijassa-1100	48	22	many	many	ADJ
ijassa-1100	48	23	years	year	NOUN
ijassa-1100	48	24	,	,	PUNCT
ijassa-1100	48	25	collected	collect	VERB
ijassa-1100	48	26	ecg	ecg	PROPN
ijassa-1100	48	27	images	image	NOUN
ijassa-1100	48	28	were	be	AUX
ijassa-1100	48	29	manually	manually	ADV
ijassa-1100	48	30	reviewed	review	VERB
ijassa-1100	48	31	by	by	ADP
ijassa-1100	48	32	medical	medical	ADJ
ijassa-1100	48	33	experts	expert	NOUN
ijassa-1100	48	34	and	and	CCONJ
ijassa-1100	48	35	supervised	supervise	VERB
ijassa-1100	48	36	by	by	ADP
ijassa-1100	48	37	senior	senior	ADJ
ijassa-1100	48	38	physicians	physician	NOUN
ijassa-1100	48	39	with	with	ADP
ijassa-1100	48	40	ecg	ecg	PROPN
ijassa-1100	48	41	interpretation	interpretation	NOUN
ijassa-1100	48	42	expertise	expertise	NOUN
ijassa-1100	48	43	.	.	PUNCT
ijassa-1100	49	1	2.2	2.2	NUM
ijassa-1100	49	2	.	.	PUNCT
ijassa-1100	50	1	preprocessing	preprocesse	VERB
ijassa-1100	50	2	the	the	DET
ijassa-1100	50	3	ecg	ecg	PROPN
ijassa-1100	50	4	interpretation	interpretation	NOUN
ijassa-1100	50	5	is	be	AUX
ijassa-1100	50	6	done	do	VERB
ijassa-1100	50	7	by	by	ADP
ijassa-1100	50	8	image	image	NOUN
ijassa-1100	50	9	,	,	PUNCT
ijassa-1100	50	10	so	so	SCONJ
ijassa-1100	50	11	we	we	PRON
ijassa-1100	50	12	need	need	VERB
ijassa-1100	50	13	to	to	PART
ijassa-1100	50	14	improve	improve	VERB
ijassa-1100	50	15	image	image	NOUN
ijassa-1100	50	16	quality	quality	NOUN
ijassa-1100	50	17	;	;	PUNCT
ijassa-1100	50	18	we	we	PRON
ijassa-1100	50	19	used	use	VERB
ijassa-1100	50	20	a	a	DET
ijassa-1100	50	21	non	non	ADJ
ijassa-1100	50	22	-	-	ADJ
ijassa-1100	50	23	linear	linear	ADJ
ijassa-1100	50	24	method	method	NOUN
ijassa-1100	50	25	gamma	gamma	NOUN
ijassa-1100	50	26	correction	correction	NOUN
ijassa-1100	50	27	for	for	ADP
ijassa-1100	50	28	enhancement	enhancement	NOUN
ijassa-1100	50	29	of	of	ADP
ijassa-1100	50	30	images	image	NOUN
ijassa-1100	50	31	its	its	PRON
ijassa-1100	50	32	improve	improve	VERB
ijassa-1100	50	33	the	the	DET
ijassa-1100	50	34	interpretability	interpretability	NOUN
ijassa-1100	50	35	or	or	CCONJ
ijassa-1100	50	36	view	view	NOUN
ijassa-1100	50	37	of	of	ADP
ijassa-1100	50	38	data	datum	NOUN
ijassa-1100	50	39	and	and	CCONJ
ijassa-1100	50	40	give	give	VERB
ijassa-1100	50	41	’	'	PUNCT
ijassa-1100	50	42	better	well	ADJ
ijassa-1100	50	43	’	'	PUNCT
ijassa-1100	50	44	contribution	contribution	NOUN
ijassa-1100	50	45	to	to	ADP
ijassa-1100	50	46	input	input	NOUN
ijassa-1100	50	47	preparation	preparation	NOUN
ijassa-1100	50	48	for	for	ADP
ijassa-1100	50	49	image	image	NOUN
ijassa-1100	50	50	processing	processing	NOUN
ijassa-1100	50	51	techniques	technique	NOUN
ijassa-1100	50	52	.	.	PUNCT
ijassa-1100	51	1	for	for	ADP
ijassa-1100	51	2	normalization	normalization	NOUN
ijassa-1100	51	3	of	of	ADP
ijassa-1100	51	4	images	image	NOUN
ijassa-1100	51	5	several	several	ADJ
ijassa-1100	51	6	operations	operation	NOUN
ijassa-1100	51	7	are	be	AUX
ijassa-1100	51	8	performed	perform	VERB
ijassa-1100	51	9	like	like	ADP
ijassa-1100	51	10	scalar	scalar	ADJ
ijassa-1100	51	11	multiplication	multiplication	NOUN
ijassa-1100	51	12	,	,	PUNCT
ijassa-1100	51	13	addition	addition	NOUN
ijassa-1100	51	14	and	and	CCONJ
ijassa-1100	51	15	subtraction	subtraction	NOUN
ijassa-1100	51	16	gamma	gamma	NOUN
ijassa-1100	51	17	correction	correction	NOUN
ijassa-1100	51	18	alludes	allude	VERB
ijassa-1100	51	19	to	to	ADP
ijassa-1100	51	20	the	the	DET
ijassa-1100	51	21	image	image	NOUN
ijassa-1100	51	22	enhancement	enhancement	NOUN
ijassa-1100	51	23	on	on	ADP
ijassa-1100	51	24	contrast	contrast	NOUN
ijassa-1100	51	25	by	by	ADP
ijassa-1100	51	26	changing	change	VERB
ijassa-1100	51	27	the	the	DET
ijassa-1100	51	28	unique	unique	ADJ
ijassa-1100	51	29	range	range	NOUN
ijassa-1100	51	30	of	of	ADP
ijassa-1100	51	31	pixel	pixel	PROPN
ijassa-1100	51	32	intensity	intensity	NOUN
ijassa-1100	51	33	distribution	distribution	NOUN
ijassa-1100	51	34	and	and	CCONJ
ijassa-1100	51	35	conveys	convey	VERB
ijassa-1100	51	36	a	a	DET
ijassa-1100	51	37	non	non	ADJ
ijassa-1100	51	38	-	-	ADJ
ijassa-1100	51	39	linear	linear	ADJ
ijassa-1100	51	40	technique	technique	NOUN
ijassa-1100	51	41	on	on	ADP
ijassa-1100	51	42	the	the	DET
ijassa-1100	51	43	source	source	NOUN
ijassa-1100	51	44	image	image	NOUN
ijassa-1100	51	45	pixels	pixel	NOUN
ijassa-1100	51	46	and	and	CCONJ
ijassa-1100	51	47	can	can	AUX
ijassa-1100	51	48	cause	cause	VERB
ijassa-1100	51	49	immersion	immersion	NOUN
ijassa-1100	51	50	of	of	ADP
ijassa-1100	51	51	the	the	DET
ijassa-1100	51	52	picture	picture	NOUN
ijassa-1100	51	53	is	be	AUX
ijassa-1100	51	54	changed	change	VERB
ijassa-1100	51	55	.	.	PUNCT
ijassa-1100	52	1	moreover	moreover	ADV
ijassa-1100	52	2	,	,	PUNCT
ijassa-1100	52	3	if	if	SCONJ
ijassa-1100	52	4	the	the	DET
ijassa-1100	52	5	gamma	gamma	NOUN
ijassa-1100	52	6	value	value	NOUN
ijassa-1100	52	7	is	be	AUX
ijassa-1100	52	8	too	too	ADV
ijassa-1100	52	9	large	large	ADJ
ijassa-1100	52	10	or	or	CCONJ
ijassa-1100	52	11	small	small	ADJ
ijassa-1100	52	12	shows	show	VERB
ijassa-1100	52	13	a	a	DET
ijassa-1100	52	14	low	low	ADJ
ijassa-1100	52	15	contrast	contrast	NOUN
ijassa-1100	52	16	image	image	NOUN
ijassa-1100	52	17	,	,	PUNCT
ijassa-1100	52	18	from	from	ADP
ijassa-1100	52	19	the	the	DET
ijassa-1100	52	20	outset	outset	NOUN
ijassa-1100	52	21	,	,	PUNCT
ijassa-1100	52	22	gamma	gamma	NOUN
ijassa-1100	52	23	revision	revision	NOUN
ijassa-1100	52	24	appears	appear	VERB
ijassa-1100	52	25	to	to	ADP
ijassa-1100	52	26	either	either	CCONJ
ijassa-1100	52	27	obscure	obscure	ADJ
ijassa-1100	52	28	or	or	CCONJ
ijassa-1100	52	29	light	light	VERB
ijassa-1100	52	30	up	up	ADP
ijassa-1100	52	31	a	a	DET
ijassa-1100	52	32	picture	picture	NOUN
ijassa-1100	52	33	,	,	PUNCT
ijassa-1100	52	34	however	however	ADV
ijassa-1100	52	35	,	,	PUNCT
ijassa-1100	52	36	this	this	PRON
ijassa-1100	52	37	is	be	AUX
ijassa-1100	52	38	a	a	DET
ijassa-1100	52	39	gross	gross	ADJ
ijassa-1100	52	40	misrepresentation	misrepresentation	NOUN
ijassa-1100	52	41	.	.	PUNCT
ijassa-1100	53	1	figure	figure	NOUN
ijassa-1100	53	2	2.3	2.3	NUM
ijassa-1100	53	3	shows	show	VERB
ijassa-1100	53	4	gamma	gamma	NOUN
ijassa-1100	53	5	-	-	PUNCT
ijassa-1100	53	6	corrected	correct	VERB
ijassa-1100	53	7	image	image	NOUN
ijassa-1100	53	8	on	on	ADP
ijassa-1100	53	9	two	two	NUM
ijassa-1100	53	10	different	different	ADJ
ijassa-1100	53	11	gamma	gamma	NOUN
ijassa-1100	53	12	values	value	NOUN
ijassa-1100	53	13	0.47	0.47	NUM
ijassa-1100	53	14	and	and	CCONJ
ijassa-1100	53	15	1.83	1.83	NUM
ijassa-1100	53	16	.	.	PUNCT
ijassa-1100	54	1	we	we	PRON
ijassa-1100	54	2	would	would	AUX
ijassa-1100	54	3	already	already	ADV
ijassa-1100	54	4	be	be	AUX
ijassa-1100	54	5	able	able	ADJ
ijassa-1100	54	6	to	to	PART
ijassa-1100	54	7	change	change	VERB
ijassa-1100	54	8	the	the	DET
ijassa-1100	54	9	normal	normal	ADJ
ijassa-1100	54	10	brightness	brightness	NOUN
ijassa-1100	54	11	of	of	ADP
ijassa-1100	54	12	a	a	DET
ijassa-1100	54	13	picture	picture	NOUN
ijassa-1100	54	14	by	by	ADP
ijassa-1100	54	15	some	some	DET
ijassa-1100	54	16	adjusted	adjust	VERB
ijassa-1100	54	17	standardization	standardization	NOUN
ijassa-1100	54	18	calculation	calculation	NOUN
ijassa-1100	54	19	,	,	PUNCT
ijassa-1100	54	20	the	the	DET
ijassa-1100	54	21	easiest	easy	ADJ
ijassa-1100	54	22	of	of	ADP
ijassa-1100	54	23	which	which	PRON
ijassa-1100	54	24	copyright	copyright	NOUN
ijassa-1100	54	25	©	©	PROPN
ijassa-1100	54	26	2021	2021	NUM
ijassa-1100	54	27	assa	assa	NOUN
ijassa-1100	54	28	.	.	PUNCT
ijassa-1100	55	1	adv	adv	PROPN
ijassa-1100	55	2	syst	syst	PROPN
ijassa-1100	55	3	sci	sci	PROPN
ijassa-1100	55	4	appl	appl	PROPN
ijassa-1100	55	5	(	(	PUNCT
ijassa-1100	55	6	2021	2021	NUM
ijassa-1100	55	7	)	)	PUNCT
ijassa-1100	55	8	convolution	convolution	NOUN
ijassa-1100	55	9	neural	neural	ADJ
ijassa-1100	55	10	network	network	NOUN
ijassa-1100	55	11	based	base	VERB
ijassa-1100	55	12	covid-19	covid-19	PROPN
ijassa-1100	55	13	screening	screen	VERB
ijassa-1100	55	14	model	model	NOUN
ijassa-1100	55	15	33	33	NUM
ijassa-1100	55	16	fig	fig	NOUN
ijassa-1100	55	17	.	.	PUNCT
ijassa-1100	56	1	2.1	2.1	NUM
ijassa-1100	56	2	.	.	X
ijassa-1100	56	3	normal	normal	ADJ
ijassa-1100	56	4	ecg	ecg	PROPN
ijassa-1100	56	5	fig	fig	NOUN
ijassa-1100	56	6	.	.	PUNCT
ijassa-1100	57	1	2.2	2.2	NUM
ijassa-1100	57	2	.	.	PUNCT
ijassa-1100	58	1	ecg	ecg	PROPN
ijassa-1100	58	2	of	of	ADP
ijassa-1100	58	3	covid-19	covid-19	PROPN
ijassa-1100	58	4	patient	patient	NOUN
ijassa-1100	58	5	would	would	AUX
ijassa-1100	58	6	be	be	AUX
ijassa-1100	58	7	basically	basically	ADV
ijassa-1100	58	8	enhancing	enhance	VERB
ijassa-1100	58	9	every	every	DET
ijassa-1100	58	10	pixel	pixel	PROPN
ijassa-1100	58	11	force	force	NOUN
ijassa-1100	58	12	esteem	esteem	NOUN
ijassa-1100	58	13	,	,	PUNCT
ijassa-1100	58	14	viably	viably	ADV
ijassa-1100	58	15	”	"	PUNCT
ijassa-1100	58	16	moving	move	VERB
ijassa-1100	58	17	”	"	PUNCT
ijassa-1100	58	18	the	the	DET
ijassa-1100	58	19	mean	mean	ADJ
ijassa-1100	58	20	pixel	pixel	PROPN
ijassa-1100	58	21	power	power	NOUN
ijassa-1100	58	22	esteems	esteem	VERB
ijassa-1100	58	23	across	across	ADP
ijassa-1100	58	24	the	the	DET
ijassa-1100	58	25	whole	whole	ADJ
ijassa-1100	58	26	picture	picture	NOUN
ijassa-1100	58	27	.	.	PUNCT
ijassa-1100	59	1	pixel	pixel	PROPN
ijassa-1100	59	2	(	(	PUNCT
ijassa-1100	59	3	p	p	NOUN
ijassa-1100	59	4	)	)	PUNCT
ijassa-1100	59	5	of	of	ADP
ijassa-1100	59	6	the	the	DET
ijassa-1100	59	7	image	image	NOUN
ijassa-1100	59	8	defined	define	VERB
ijassa-1100	59	9	in	in	ADP
ijassa-1100	59	10	a	a	DET
ijassa-1100	59	11	range	range	NOUN
ijassa-1100	59	12	between	between	ADP
ijassa-1100	59	13	0	0	NUM
ijassa-1100	59	14	-	-	SYM
ijassa-1100	59	15	255	255	NUM
ijassa-1100	59	16	,	,	PUNCT
ijassa-1100	59	17	δ	δ	PROPN
ijassa-1100	59	18	is	be	AUX
ijassa-1100	59	19	a	a	DET
ijassa-1100	59	20	representation	representation	NOUN
ijassa-1100	59	21	of	of	ADP
ijassa-1100	59	22	angle	angle	NOUN
ijassa-1100	59	23	value	value	NOUN
ijassa-1100	59	24	,	,	PUNCT
ijassa-1100	59	25	grayscale	grayscale	NOUN
ijassa-1100	59	26	image	image	NOUN
ijassa-1100	59	27	of	of	ADP
ijassa-1100	59	28	ecg	ecg	PROPN
ijassa-1100	59	29	signal	signal	NOUN
ijassa-1100	59	30	represented	represent	VERB
ijassa-1100	59	31	by	by	ADP
ijassa-1100	59	32	k	k	PROPN
ijassa-1100	59	33	of	of	ADP
ijassa-1100	59	34	the	the	DET
ijassa-1100	59	35	pixel	pixel	PROPN
ijassa-1100	59	36	(	(	PUNCT
ijassa-1100	59	37	kεp	kεp	PROPN
ijassa-1100	59	38	)	)	PUNCT
ijassa-1100	59	39	choose	choose	VERB
ijassa-1100	59	40	a	a	DET
ijassa-1100	59	41	midpoint	midpoint	NOUN
ijassa-1100	59	42	km	km	NOUN
ijassa-1100	59	43	of	of	ADP
ijassa-1100	59	44	the	the	DET
ijassa-1100	59	45	range	range	NOUN
ijassa-1100	59	46	[	[	X
ijassa-1100	59	47	0	0	NUM
ijassa-1100	59	48	,	,	PUNCT
ijassa-1100	59	49	255	255	NUM
ijassa-1100	59	50	]	]	PUNCT
ijassa-1100	59	51	.	.	PUNCT
ijassa-1100	60	1	the	the	DET
ijassa-1100	60	2	linear	linear	PROPN
ijassa-1100	60	3	map	map	NOUN
ijassa-1100	60	4	from	from	ADP
ijassa-1100	60	5	pixel	pixel	PROPN
ijassa-1100	60	6	group	group	NOUN
ijassa-1100	60	7	p	p	PROPN
ijassa-1100	60	8	to	to	ADP
ijassa-1100	60	9	group	group	PROPN
ijassa-1100	60	10	δ	δ	PROPN
ijassa-1100	60	11	represents	represent	VERB
ijassa-1100	60	12	as	as	ADP
ijassa-1100	60	13	:	:	PUNCT
ijassa-1100	60	14	φ	φ	NUM
ijassa-1100	60	15	:	:	PUNCT
ijassa-1100	61	1	p	p	X
ijassa-1100	61	2	→	→	SYM
ijassa-1100	61	3	δ	δ	X
ijassa-1100	61	4	=	=	PUNCT
ijassa-1100	61	5	{	{	PUNCT
ijassa-1100	61	6	ω|ω	ω|ω	NOUN
ijassa-1100	61	7	=	=	SYM
ijassa-1100	61	8	φ(k)},φ(k	φ(k)},φ(k	NUM
ijassa-1100	61	9	)	)	PUNCT
ijassa-1100	61	10	=	=	SYM
ijassa-1100	61	11	πk/2	πk/2	PROPN
ijassa-1100	61	12	km	km	NOUN
ijassa-1100	61	13	(	(	PUNCT
ijassa-1100	61	14	2.1	2.1	NUM
ijassa-1100	61	15	)	)	PUNCT
ijassa-1100	61	16	the	the	DET
ijassa-1100	61	17	δ	δ	PROPN
ijassa-1100	61	18	is	be	AUX
ijassa-1100	61	19	mapped	map	VERB
ijassa-1100	61	20	to	to	ADP
ijassa-1100	61	21	γ	γ	PROPN
ijassa-1100	61	22	(	(	PUNCT
ijassa-1100	61	23	gamma	gamma	NOUN
ijassa-1100	61	24	value	value	NOUN
ijassa-1100	61	25	symbol	symbol	NOUN
ijassa-1100	61	26	)	)	PUNCT
ijassa-1100	62	1	h	h	NOUN
ijassa-1100	62	2	:	:	PUNCT
ijassa-1100	62	3	δ	δ	PROPN
ijassa-1100	62	4	→	→	SYM
ijassa-1100	62	5	γ	γ	PROPN
ijassa-1100	62	6	,	,	PUNCT
ijassa-1100	62	7	γ	γ	X
ijassa-1100	62	8	=	=	X
ijassa-1100	62	9	{	{	PUNCT
ijassa-1100	62	10	γ|γ	γ|γ	NOUN
ijassa-1100	62	11	=	=	SYM
ijassa-1100	62	12	h(k	h(k	PROPN
ijassa-1100	62	13	)	)	PUNCT
ijassa-1100	62	14	}	}	PUNCT
ijassa-1100	62	15	(	(	PUNCT
ijassa-1100	62	16	2.2	2.2	NUM
ijassa-1100	62	17	)	)	PUNCT
ijassa-1100	62	18	h(k	h(k	PROPN
ijassa-1100	62	19	)	)	PUNCT
ijassa-1100	63	1	=	=	SYM
ijassa-1100	63	2	1	1	NUM
ijassa-1100	63	3	+	+	NUM
ijassa-1100	63	4	f1(k	f1(k	NOUN
ijassa-1100	63	5	)	)	PUNCT
ijassa-1100	63	6	(	(	PUNCT
ijassa-1100	63	7	2.3	2.3	NUM
ijassa-1100	63	8	)	)	PUNCT
ijassa-1100	63	9	f1(k	f1(k	PROPN
ijassa-1100	63	10	)	)	PUNCT
ijassa-1100	63	11	=	=	PUNCT
ijassa-1100	63	12	a	a	DET
ijassa-1100	63	13	cos(φ(k	cos(φ(k	NOUN
ijassa-1100	63	14	)	)	PUNCT
ijassa-1100	63	15	)	)	PUNCT
ijassa-1100	63	16	(	(	PUNCT
ijassa-1100	63	17	2.4	2.4	NUM
ijassa-1100	63	18	)	)	PUNCT
ijassa-1100	63	19	where	where	SCONJ
ijassa-1100	63	20	a	a	DET
ijassa-1100	63	21	lies	lie	NOUN
ijassa-1100	63	22	between	between	ADP
ijassa-1100	63	23	0	0	NUM
ijassa-1100	63	24	to	to	ADP
ijassa-1100	63	25	1	1	NUM
ijassa-1100	63	26	as	as	ADP
ijassa-1100	63	27	a	a	DET
ijassa-1100	63	28	weighted	weighted	ADJ
ijassa-1100	63	29	factor	factor	NOUN
ijassa-1100	63	30	and	and	CCONJ
ijassa-1100	63	31	h	h	NOUN
ijassa-1100	63	32	is	be	AUX
ijassa-1100	63	33	the	the	DET
ijassa-1100	63	34	histogram	histogram	NOUN
ijassa-1100	63	35	intensity	intensity	NOUN
ijassa-1100	63	36	level	level	NOUN
ijassa-1100	63	37	.	.	PUNCT
ijassa-1100	64	1	according	accord	VERB
ijassa-1100	64	2	to	to	ADP
ijassa-1100	64	3	map	map	NOUN
ijassa-1100	64	4	,	,	PUNCT
ijassa-1100	64	5	group	group	NOUN
ijassa-1100	64	6	p	p	NOUN
ijassa-1100	64	7	and	and	CCONJ
ijassa-1100	64	8	gamma	gamma	PROPN
ijassa-1100	64	9	group	group	NOUN
ijassa-1100	64	10	pixel	pixel	PROPN
ijassa-1100	64	11	values	value	NOUN
ijassa-1100	64	12	are	be	AUX
ijassa-1100	64	13	interrelated	interrelated	ADJ
ijassa-1100	64	14	.	.	PUNCT
ijassa-1100	65	1	gamma	gamma	NOUN
ijassa-1100	65	2	number	number	NOUN
ijassa-1100	65	3	helps	help	VERB
ijassa-1100	65	4	to	to	PART
ijassa-1100	65	5	find	find	VERB
ijassa-1100	65	6	the	the	DET
ijassa-1100	65	7	arbitrary	arbitrary	ADJ
ijassa-1100	65	8	pixel	pixel	NOUN
ijassa-1100	65	9	value	value	NOUN
ijassa-1100	65	10	.	.	PUNCT
ijassa-1100	66	1	let	let	VERB
ijassa-1100	66	2	γ(k	γ(k	PROPN
ijassa-1100	66	3	)	)	PUNCT
ijassa-1100	67	1	=	=	SYM
ijassa-1100	67	2	h(k	h(k	PROPN
ijassa-1100	67	3	)	)	PUNCT
ijassa-1100	67	4	,	,	PUNCT
ijassa-1100	67	5	and	and	CCONJ
ijassa-1100	67	6	gamma	gamma	NOUN
ijassa-1100	67	7	correction	correction	NOUN
ijassa-1100	67	8	function	function	NOUN
ijassa-1100	67	9	is	be	AUX
ijassa-1100	67	10	defined	define	VERB
ijassa-1100	67	11	as	as	ADP
ijassa-1100	67	12	:	:	PUNCT
ijassa-1100	67	13	t	t	PROPN
ijassa-1100	67	14	(	(	PUNCT
ijassa-1100	67	15	k	k	X
ijassa-1100	67	16	)	)	PUNCT
ijassa-1100	67	17	=	=	SYM
ijassa-1100	68	1	255	255	NUM
ijassa-1100	69	1	(	(	PUNCT
ijassa-1100	69	2	k	k	NOUN
ijassa-1100	69	3	255	255	NUM
ijassa-1100	69	4	)	)	SYM
ijassa-1100	69	5	1	1	NUM
ijassa-1100	69	6	/	/	SYM
ijassa-1100	69	7	γ(x	γ(x	NOUN
ijassa-1100	69	8	)	)	PUNCT
ijassa-1100	69	9	(	(	PUNCT
ijassa-1100	69	10	2.5	2.5	NUM
ijassa-1100	69	11	)	)	PUNCT
ijassa-1100	69	12	copyright	copyright	NOUN
ijassa-1100	69	13	©	©	PROPN
ijassa-1100	69	14	2021	2021	NUM
ijassa-1100	69	15	assa	assa	NOUN
ijassa-1100	69	16	.	.	PUNCT
ijassa-1100	70	1	adv	adv	PROPN
ijassa-1100	70	2	syst	syst	PROPN
ijassa-1100	70	3	sci	sci	PROPN
ijassa-1100	70	4	appl	appl	PROPN
ijassa-1100	70	5	(	(	PUNCT
ijassa-1100	70	6	2021	2021	NUM
ijassa-1100	70	7	)	)	PUNCT
ijassa-1100	70	8	34	34	NUM
ijassa-1100	70	9	a.	a.	NOUN
ijassa-1100	70	10	nainwal	nainwal	NOUN
ijassa-1100	70	11	,	,	PUNCT
ijassa-1100	70	12	g	g	PROPN
ijassa-1100	70	13	k	k	PROPN
ijassa-1100	70	14	malik	malik	PROPN
ijassa-1100	70	15	,	,	PUNCT
ijassa-1100	70	16	amrish	amrish	VERB
ijassa-1100	70	17	fig	fig	NOUN
ijassa-1100	70	18	.	.	PUNCT
ijassa-1100	71	1	2.3	2.3	NUM
ijassa-1100	71	2	.	.	PUNCT
ijassa-1100	72	1	:	:	PUNCT
ijassa-1100	72	2	input	input	NOUN
ijassa-1100	72	3	image	image	NOUN
ijassa-1100	72	4	:	:	PUNCT
ijassa-1100	72	5	(	(	PUNCT
ijassa-1100	72	6	i)ecg	i)ecg	VERB
ijassa-1100	72	7	trace	trace	NOUN
ijassa-1100	72	8	image	image	NOUN
ijassa-1100	72	9	original	original	ADJ
ijassa-1100	72	10	(	(	PUNCT
ijassa-1100	72	11	ii)gamma	ii)gamma	PROPN
ijassa-1100	72	12	corrected	correct	VERB
ijassa-1100	72	13	image	image	NOUN
ijassa-1100	72	14	when	when	SCONJ
ijassa-1100	72	15	γ=.47	γ=.47	PROPN
ijassa-1100	72	16	(	(	PUNCT
ijassa-1100	72	17	iii	iii	NOUN
ijassa-1100	72	18	)	)	PUNCT
ijassa-1100	72	19	gamma	gamma	NOUN
ijassa-1100	72	20	corrected	correct	VERB
ijassa-1100	72	21	image	image	NOUN
ijassa-1100	72	22	when	when	SCONJ
ijassa-1100	72	23	γ=1.83	γ=1.83	ADV
ijassa-1100	72	24	where	where	SCONJ
ijassa-1100	72	25	the	the	DET
ijassa-1100	72	26	output	output	NOUN
ijassa-1100	72	27	pixel	pixel	PROPN
ijassa-1100	72	28	correction	correction	NOUN
ijassa-1100	72	29	value	value	NOUN
ijassa-1100	72	30	is	be	AUX
ijassa-1100	72	31	represented	represent	VERB
ijassa-1100	72	32	by	by	ADP
ijassa-1100	72	33	t(k	t(k	PROPN
ijassa-1100	72	34	)	)	PUNCT
ijassa-1100	72	35	in	in	ADP
ijassa-1100	72	36	grayscale	grayscale	NOUN
ijassa-1100	72	37	.	.	PUNCT
ijassa-1100	73	1	after	after	ADP
ijassa-1100	73	2	gamma	gamma	NOUN
ijassa-1100	73	3	correction	correction	NOUN
ijassa-1100	73	4	,	,	PUNCT
ijassa-1100	73	5	the	the	DET
ijassa-1100	73	6	dataset	dataset	NOUN
ijassa-1100	73	7	is	be	AUX
ijassa-1100	73	8	treated	treat	VERB
ijassa-1100	73	9	so	so	SCONJ
ijassa-1100	73	10	that	that	SCONJ
ijassa-1100	73	11	the	the	DET
ijassa-1100	73	12	ecg	ecg	PROPN
ijassa-1100	73	13	images	image	NOUN
ijassa-1100	73	14	scale	scale	NOUN
ijassa-1100	73	15	to	to	PART
ijassa-1100	73	16	meet	meet	VERB
ijassa-1100	73	17	the	the	DET
ijassa-1100	73	18	cnn	cnn	PROPN
ijassa-1100	73	19	network	network	NOUN
ijassa-1100	73	20	input	input	NOUN
ijassa-1100	73	21	picture	picture	NOUN
ijassa-1100	73	22	size	size	NOUN
ijassa-1100	73	23	needs	need	VERB
ijassa-1100	73	24	.	.	PUNCT
ijassa-1100	74	1	the	the	DET
ijassa-1100	74	2	z	z	NOUN
ijassa-1100	74	3	-	-	PUNCT
ijassa-1100	74	4	score	score	NOUN
ijassa-1100	74	5	normalization	normalization	NOUN
ijassa-1100	74	6	was	be	AUX
ijassa-1100	74	7	performed	perform	VERB
ijassa-1100	74	8	with	with	ADP
ijassa-1100	74	9	the	the	DET
ijassa-1100	74	10	average	average	ADJ
ijassa-1100	74	11	and	and	CCONJ
ijassa-1100	74	12	standard	standard	ADJ
ijassa-1100	74	13	deviation	deviation	NOUN
ijassa-1100	74	14	of	of	ADP
ijassa-1100	74	15	images	image	NOUN
ijassa-1100	74	16	.	.	PUNCT
ijassa-1100	75	1	2.3	2.3	NUM
ijassa-1100	75	2	.	.	PUNCT
ijassa-1100	76	1	convolution	convolution	NOUN
ijassa-1100	76	2	neural	neural	ADJ
ijassa-1100	76	3	network	network	PROPN
ijassa-1100	76	4	cnn	cnn	PROPN
ijassa-1100	76	5	is	be	AUX
ijassa-1100	76	6	the	the	DET
ijassa-1100	76	7	popular	popular	ADJ
ijassa-1100	76	8	sort	sort	NOUN
ijassa-1100	76	9	of	of	ADP
ijassa-1100	76	10	neural	neural	ADJ
ijassa-1100	76	11	artificial	artificial	ADJ
ijassa-1100	76	12	network	network	NOUN
ijassa-1100	76	13	that	that	PRON
ijassa-1100	76	14	includes	include	VERB
ijassa-1100	76	15	algorithms	algorithm	NOUN
ijassa-1100	76	16	for	for	ADP
ijassa-1100	76	17	supervised	supervised	ADJ
ijassa-1100	76	18	learning	learning	NOUN
ijassa-1100	76	19	tasks	task	NOUN
ijassa-1100	76	20	.	.	PUNCT
ijassa-1100	77	1	it	it	PRON
ijassa-1100	77	2	is	be	AUX
ijassa-1100	77	3	also	also	ADV
ijassa-1100	77	4	an	an	DET
ijassa-1100	77	5	essential	essential	ADJ
ijassa-1100	77	6	tool	tool	NOUN
ijassa-1100	77	7	for	for	ADP
ijassa-1100	77	8	deep	deep	ADJ
ijassa-1100	77	9	learning	learning	NOUN
ijassa-1100	77	10	with	with	ADP
ijassa-1100	77	11	many	many	ADJ
ijassa-1100	77	12	hidden	hidden	ADJ
ijassa-1100	77	13	layers	layer	NOUN
ijassa-1100	77	14	and	and	CCONJ
ijassa-1100	77	15	parameters	parameter	NOUN
ijassa-1100	77	16	.	.	PUNCT
ijassa-1100	78	1	in	in	ADP
ijassa-1100	78	2	several	several	ADJ
ijassa-1100	78	3	areas	area	NOUN
ijassa-1100	78	4	like	like	ADP
ijassa-1100	78	5	image	image	NOUN
ijassa-1100	78	6	processing	processing	NOUN
ijassa-1100	78	7	,	,	PUNCT
ijassa-1100	78	8	design	design	NOUN
ijassa-1100	78	9	recognition	recognition	NOUN
ijassa-1100	78	10	and	and	CCONJ
ijassa-1100	78	11	other	other	ADJ
ijassa-1100	78	12	cognitive	cognitive	ADJ
ijassa-1100	78	13	tasks	task	NOUN
ijassa-1100	78	14	,	,	PUNCT
ijassa-1100	78	15	the	the	DET
ijassa-1100	78	16	cnn	cnn	PROPN
ijassa-1100	78	17	was	be	AUX
ijassa-1100	78	18	widely	widely	ADV
ijassa-1100	78	19	used	use	VERB
ijassa-1100	78	20	.	.	PUNCT
ijassa-1100	79	1	a	a	DET
ijassa-1100	79	2	standard	standard	ADJ
ijassa-1100	79	3	cnn	cnn	PROPN
ijassa-1100	79	4	is	be	AUX
ijassa-1100	79	5	made	make	VERB
ijassa-1100	79	6	up	up	ADP
ijassa-1100	79	7	of	of	ADP
ijassa-1100	79	8	three	three	NUM
ijassa-1100	79	9	-	-	PUNCT
ijassa-1100	79	10	layer	layer	NOUN
ijassa-1100	79	11	types	type	NOUN
ijassa-1100	79	12	:	:	PUNCT
ijassa-1100	79	13	the	the	DET
ijassa-1100	79	14	convolutions	convolution	NOUN
ijassa-1100	79	15	layer	layer	NOUN
ijassa-1100	79	16	,	,	PUNCT
ijassa-1100	79	17	the	the	DET
ijassa-1100	79	18	fully	fully	ADV
ijassa-1100	79	19	connected	connect	VERB
ijassa-1100	79	20	layer	layer	NOUN
ijassa-1100	79	21	and	and	CCONJ
ijassa-1100	79	22	the	the	DET
ijassa-1100	79	23	pooling	pool	VERB
ijassa-1100	79	24	layer	layer	NOUN
ijassa-1100	79	25	.	.	PUNCT
ijassa-1100	80	1	the	the	DET
ijassa-1100	80	2	convolution	convolution	NOUN
ijassa-1100	80	3	layer	layer	NOUN
ijassa-1100	80	4	conducts	conduct	NOUN
ijassa-1100	80	5	overlapping	overlap	VERB
ijassa-1100	80	6	operations	operation	NOUN
ijassa-1100	80	7	throughout	throughout	ADP
ijassa-1100	80	8	the	the	DET
ijassa-1100	80	9	entire	entire	ADJ
ijassa-1100	80	10	image	image	NOUN
ijassa-1100	80	11	spatially	spatially	ADV
ijassa-1100	80	12	to	to	PART
ijassa-1100	80	13	create	create	VERB
ijassa-1100	80	14	characteristics	characteristic	NOUN
ijassa-1100	80	15	.	.	PUNCT
ijassa-1100	81	1	for	for	ADP
ijassa-1100	81	2	downsampling	downsample	VERB
ijassa-1100	81	3	maps	map	NOUN
ijassa-1100	81	4	,	,	PUNCT
ijassa-1100	81	5	the	the	DET
ijassa-1100	81	6	pooling	pooling	NOUN
ijassa-1100	81	7	layer	layer	NOUN
ijassa-1100	81	8	is	be	AUX
ijassa-1100	81	9	responsible	responsible	ADJ
ijassa-1100	81	10	.	.	PUNCT
ijassa-1100	82	1	the	the	DET
ijassa-1100	82	2	fully	fully	ADV
ijassa-1100	82	3	connected	connect	VERB
ijassa-1100	82	4	layer	layer	NOUN
ijassa-1100	82	5	classifies	classify	VERB
ijassa-1100	82	6	depending	depend	VERB
ijassa-1100	82	7	on	on	ADP
ijassa-1100	82	8	the	the	DET
ijassa-1100	82	9	characteristics	characteristic	NOUN
ijassa-1100	82	10	learned	learn	VERB
ijassa-1100	82	11	.	.	PUNCT
ijassa-1100	83	1	one	one	NUM
ijassa-1100	83	2	-	-	PUNCT
ijassa-1100	83	3	dimensional	dimensional	ADJ
ijassa-1100	83	4	signal	signal	NOUN
ijassa-1100	83	5	evolution	evolution	NOUN
ijassa-1100	83	6	is	be	AUX
ijassa-1100	83	7	referred	refer	VERB
ijassa-1100	83	8	to	to	ADP
ijassa-1100	83	9	as	as	ADP
ijassa-1100	83	10	1d	1d	NUM
ijassa-1100	83	11	convolution	convolution	NOUN
ijassa-1100	83	12	or	or	CCONJ
ijassa-1100	83	13	simply	simply	ADV
ijassa-1100	83	14	convolution	convolution	NOUN
ijassa-1100	83	15	.	.	PUNCT
ijassa-1100	84	1	if	if	SCONJ
ijassa-1100	84	2	the	the	DET
ijassa-1100	84	3	convolution	convolution	NOUN
ijassa-1100	84	4	occurs	occur	VERB
ijassa-1100	84	5	between	between	ADP
ijassa-1100	84	6	two	two	NUM
ijassa-1100	84	7	signals	signal	NOUN
ijassa-1100	84	8	covering	cover	VERB
ijassa-1100	84	9	two	two	NUM
ijassa-1100	84	10	perpendicular	perpendicular	ADJ
ijassa-1100	84	11	dimensions	dimension	NOUN
ijassa-1100	84	12	,	,	PUNCT
ijassa-1100	84	13	the	the	DET
ijassa-1100	84	14	convolution	convolution	NOUN
ijassa-1100	84	15	shall	shall	AUX
ijassa-1100	84	16	be	be	AUX
ijassa-1100	84	17	called	call	VERB
ijassa-1100	84	18	a	a	DET
ijassa-1100	84	19	2d	2d	NUM
ijassa-1100	84	20	convolution	convolution	NOUN
ijassa-1100	84	21	.	.	PUNCT
ijassa-1100	85	1	figure	figure	VERB
ijassa-1100	85	2	2.4	2.4	NUM
ijassa-1100	85	3	shows	show	VERB
ijassa-1100	85	4	the	the	DET
ijassa-1100	85	5	2d	2d	NUM
ijassa-1100	85	6	convolution	convolution	NOUN
ijassa-1100	85	7	operation	operation	NOUN
ijassa-1100	85	8	.	.	PUNCT
ijassa-1100	86	1	this	this	DET
ijassa-1100	86	2	notion	notion	NOUN
ijassa-1100	86	3	may	may	AUX
ijassa-1100	86	4	be	be	AUX
ijassa-1100	86	5	expanded	expand	VERB
ijassa-1100	86	6	to	to	PART
ijassa-1100	86	7	include	include	VERB
ijassa-1100	86	8	multi	multi	ADJ
ijassa-1100	86	9	-	-	ADJ
ijassa-1100	86	10	dimensional	dimensional	ADJ
ijassa-1100	86	11	signals	signal	NOUN
ijassa-1100	86	12	via	via	ADP
ijassa-1100	86	13	which	which	PRON
ijassa-1100	86	14	multi	multi	ADJ
ijassa-1100	86	15	-	-	ADJ
ijassa-1100	86	16	dimensional	dimensional	ADJ
ijassa-1100	86	17	convergence	convergence	NOUN
ijassa-1100	86	18	is	be	AUX
ijassa-1100	86	19	possible	possible	ADJ
ijassa-1100	86	20	.	.	PUNCT
ijassa-1100	87	1	polling	polling	NOUN
ijassa-1100	87	2	is	be	AUX
ijassa-1100	87	3	used	use	VERB
ijassa-1100	87	4	to	to	ADP
ijassa-1100	87	5	simplifying	simplify	VERB
ijassa-1100	87	6	or	or	CCONJ
ijassa-1100	87	7	reducing	reduce	VERB
ijassa-1100	87	8	the	the	DET
ijassa-1100	87	9	information	information	NOUN
ijassa-1100	87	10	acquired	acquire	VERB
ijassa-1100	87	11	from	from	ADP
ijassa-1100	87	12	feature	feature	NOUN
ijassa-1100	87	13	maps	map	NOUN
ijassa-1100	87	14	spatial	spatial	ADJ
ijassa-1100	87	15	dimensions	dimension	NOUN
ijassa-1100	87	16	.	.	PUNCT
ijassa-1100	88	1	the	the	DET
ijassa-1100	88	2	most	most	ADV
ijassa-1100	88	3	frequent	frequent	ADJ
ijassa-1100	88	4	usage	usage	NOUN
ijassa-1100	88	5	of	of	ADP
ijassa-1100	88	6	pooling	pooling	NOUN
ijassa-1100	88	7	is	be	AUX
ijassa-1100	88	8	the	the	DET
ijassa-1100	88	9	maximum	maximum	NOUN
ijassa-1100	88	10	of	of	ADP
ijassa-1100	88	11	pooling	pooling	NOUN
ijassa-1100	88	12	because	because	SCONJ
ijassa-1100	88	13	of	of	ADP
ijassa-1100	88	14	its	its	PRON
ijassa-1100	88	15	speed	speed	NOUN
ijassa-1100	88	16	and	and	CCONJ
ijassa-1100	88	17	increased	increase	VERB
ijassa-1100	88	18	convergence	convergence	NOUN
ijassa-1100	88	19	.	.	PUNCT
ijassa-1100	89	1	this	this	PRON
ijassa-1100	89	2	is	be	AUX
ijassa-1100	89	3	what	what	PRON
ijassa-1100	89	4	makes	make	VERB
ijassa-1100	89	5	a	a	DET
ijassa-1100	89	6	filter	filter	NOUN
ijassa-1100	89	7	(	(	PUNCT
ijassa-1100	89	8	usually	usually	ADV
ijassa-1100	89	9	the	the	DET
ijassa-1100	89	10	size	size	NOUN
ijassa-1100	89	11	2x2	2x2	NUM
ijassa-1100	89	12	)	)	PUNCT
ijassa-1100	89	13	and	and	CCONJ
ijassa-1100	89	14	a	a	DET
ijassa-1100	89	15	step	step	NOUN
ijassa-1100	89	16	the	the	DET
ijassa-1100	89	17	length	length	NOUN
ijassa-1100	89	18	is	be	AUX
ijassa-1100	89	19	the	the	DET
ijassa-1100	89	20	same	same	ADJ
ijassa-1100	89	21	.	.	PUNCT
ijassa-1100	90	1	figure	figure	VERB
ijassa-1100	90	2	2.5	2.5	NUM
ijassa-1100	90	3	shows	show	VERB
ijassa-1100	90	4	the	the	DET
ijassa-1100	90	5	polling	polling	NOUN
ijassa-1100	90	6	operation	operation	NOUN
ijassa-1100	90	7	.	.	PUNCT
ijassa-1100	91	1	each	each	DET
ijassa-1100	91	2	input	input	NOUN
ijassa-1100	91	3	is	be	AUX
ijassa-1100	91	4	connected	connect	VERB
ijassa-1100	91	5	to	to	ADP
ijassa-1100	91	6	each	each	DET
ijassa-1100	91	7	output	output	NOUN
ijassa-1100	91	8	and	and	CCONJ
ijassa-1100	91	9	hence	hence	ADV
ijassa-1100	91	10	has	have	VERB
ijassa-1100	91	11	the	the	DET
ijassa-1100	91	12	phrase	phrase	NOUN
ijassa-1100	91	13	”	"	PUNCT
ijassa-1100	91	14	fully	fully	ADV
ijassa-1100	91	15	connected	connect	VERB
ijassa-1100	91	16	.	.	PUNCT
ijassa-1100	92	1	”	"	PUNCT
ijassa-1100	92	2	it	it	PRON
ijassa-1100	92	3	is	be	AUX
ijassa-1100	92	4	the	the	DET
ijassa-1100	92	5	last	last	ADJ
ijassa-1100	92	6	layer	layer	NOUN
ijassa-1100	92	7	,	,	PUNCT
ijassa-1100	92	8	usually	usually	ADV
ijassa-1100	92	9	following	follow	VERB
ijassa-1100	92	10	cnn	cnn	PROPN
ijassa-1100	92	11	’s	’s	PART
ijassa-1100	92	12	last	last	ADJ
ijassa-1100	92	13	pooling	pool	VERB
ijassa-1100	92	14	layer	layer	NOUN
ijassa-1100	92	15	.	.	PUNCT
ijassa-1100	93	1	fully	fully	ADV
ijassa-1100	93	2	linked	link	VERB
ijassa-1100	93	3	layers	layer	NOUN
ijassa-1100	93	4	act	act	VERB
ijassa-1100	93	5	like	like	ADP
ijassa-1100	93	6	a	a	DET
ijassa-1100	93	7	typical	typical	ADJ
ijassa-1100	93	8	neural	neural	ADJ
ijassa-1100	93	9	network	network	NOUN
ijassa-1100	93	10	and	and	CCONJ
ijassa-1100	93	11	contain	contain	VERB
ijassa-1100	93	12	around	around	ADV
ijassa-1100	93	13	90	90	NUM
ijassa-1100	93	14	%	%	NOUN
ijassa-1100	93	15	of	of	ADP
ijassa-1100	93	16	cnn	cnn	PROPN
ijassa-1100	93	17	parameters	parameter	NOUN
ijassa-1100	93	18	.	.	PUNCT
ijassa-1100	94	1	this	this	DET
ijassa-1100	94	2	copyright	copyright	NOUN
ijassa-1100	94	3	©	©	PROPN
ijassa-1100	94	4	2021	2021	NUM
ijassa-1100	94	5	assa	assa	NOUN
ijassa-1100	94	6	.	.	PUNCT
ijassa-1100	95	1	adv	adv	PROPN
ijassa-1100	95	2	syst	syst	PROPN
ijassa-1100	95	3	sci	sci	PROPN
ijassa-1100	95	4	appl	appl	PROPN
ijassa-1100	95	5	(	(	PUNCT
ijassa-1100	95	6	2021	2021	NUM
ijassa-1100	95	7	)	)	PUNCT
ijassa-1100	95	8	convolution	convolution	NOUN
ijassa-1100	95	9	neural	neural	ADJ
ijassa-1100	95	10	network	network	NOUN
ijassa-1100	95	11	based	base	VERB
ijassa-1100	95	12	covid-19	covid-19	PROPN
ijassa-1100	95	13	screening	screen	VERB
ijassa-1100	95	14	model	model	NOUN
ijassa-1100	95	15	35	35	NUM
ijassa-1100	95	16	fig	fig	NOUN
ijassa-1100	95	17	.	.	PUNCT
ijassa-1100	96	1	2.4	2.4	NUM
ijassa-1100	96	2	.	.	PUNCT
ijassa-1100	97	1	2d	2d	NUM
ijassa-1100	97	2	convolution	convolution	NOUN
ijassa-1100	97	3	operation	operation	NOUN
ijassa-1100	97	4	fig	fig	NOUN
ijassa-1100	97	5	.	.	PUNCT
ijassa-1100	98	1	2.5	2.5	NUM
ijassa-1100	98	2	.	.	PUNCT
ijassa-1100	99	1	operation	operation	NOUN
ijassa-1100	99	2	of	of	ADP
ijassa-1100	99	3	max	max	PROPN
ijassa-1100	99	4	polling	polling	NOUN
ijassa-1100	99	5	layer	layer	NOUN
ijassa-1100	99	6	essentially	essentially	ADV
ijassa-1100	99	7	enters	enter	VERB
ijassa-1100	99	8	the	the	DET
ijassa-1100	99	9	last	last	ADJ
ijassa-1100	99	10	pooling	pool	VERB
ijassa-1100	99	11	layer	layer	NOUN
ijassa-1100	99	12	output	output	NOUN
ijassa-1100	99	13	and	and	CCONJ
ijassa-1100	99	14	produces	produce	VERB
ijassa-1100	99	15	a	a	DET
ijassa-1100	99	16	n	n	ADV
ijassa-1100	99	17	-	-	PUNCT
ijassa-1100	99	18	dimensional	dimensional	ADJ
ijassa-1100	99	19	vector	vector	NOUN
ijassa-1100	99	20	where	where	SCONJ
ijassa-1100	99	21	n	n	PRON
ijassa-1100	99	22	is	be	AUX
ijassa-1100	99	23	the	the	DET
ijassa-1100	99	24	number	number	NOUN
ijassa-1100	99	25	of	of	ADP
ijassa-1100	99	26	classes	class	NOUN
ijassa-1100	99	27	to	to	PART
ijassa-1100	99	28	pick	pick	VERB
ijassa-1100	99	29	from	from	ADP
ijassa-1100	99	30	.	.	PUNCT
ijassa-1100	100	1	as	as	SCONJ
ijassa-1100	100	2	the	the	DET
ijassa-1100	100	3	function	function	NOUN
ijassa-1100	100	4	for	for	ADP
ijassa-1100	100	5	neuron	neuron	NOUN
ijassa-1100	100	6	activation	activation	NOUN
ijassa-1100	100	7	,	,	PUNCT
ijassa-1100	100	8	non	non	ADJ
ijassa-1100	100	9	-	-	ADJ
ijassa-1100	100	10	linear	linear	ADJ
ijassa-1100	100	11	transfer	transfer	NOUN
ijassa-1100	100	12	functions	function	NOUN
ijassa-1100	100	13	are	be	AUX
ijassa-1100	100	14	employed	employ	VERB
ijassa-1100	100	15	in	in	ADP
ijassa-1100	100	16	ann	ann	PROPN
ijassa-1100	100	17	.	.	PUNCT
ijassa-1100	101	1	for	for	ADP
ijassa-1100	101	2	example	example	NOUN
ijassa-1100	101	3	,	,	PUNCT
ijassa-1100	101	4	the	the	DET
ijassa-1100	101	5	most	most	ADV
ijassa-1100	101	6	frequent	frequent	ADJ
ijassa-1100	101	7	activation	activation	NOUN
ijassa-1100	101	8	functions	function	NOUN
ijassa-1100	101	9	are	be	AUX
ijassa-1100	101	10	sigmoid	sigmoid	NOUN
ijassa-1100	101	11	f(x	f(x	NOUN
ijassa-1100	101	12	)	)	PUNCT
ijassa-1100	102	1	=	=	PUNCT
ijassa-1100	103	1	1/(1	1/(1	NUM
ijassa-1100	104	1	+	+	CCONJ
ijassa-1100	104	2	exp(−x	exp(−x	PROPN
ijassa-1100	104	3	)	)	PUNCT
ijassa-1100	104	4	)	)	PUNCT
ijassa-1100	105	1	and	and	CCONJ
ijassa-1100	105	2	hyperbolic	hyperbolic	ADJ
ijassa-1100	105	3	tangent	tangent	NOUN
ijassa-1100	105	4	f(x	f(x	PROPN
ijassa-1100	105	5	)	)	PUNCT
ijassa-1100	105	6	=	=	SYM
ijassa-1100	105	7	tanh(x	tanh(x	PROPN
ijassa-1100	105	8	)	)	PUNCT
ijassa-1100	105	9	.	.	PUNCT
ijassa-1100	106	1	sigmoid	sigmoid	NOUN
ijassa-1100	106	2	and	and	CCONJ
ijassa-1100	106	3	hyperbolic	hyperbolic	ADJ
ijassa-1100	106	4	tangents	tangent	NOUN
ijassa-1100	106	5	are	be	AUX
ijassa-1100	106	6	both	both	PRON
ijassa-1100	106	7	non	non	ADJ
ijassa-1100	106	8	-	-	ADJ
ijassa-1100	106	9	linear	linear	ADJ
ijassa-1100	106	10	saturating	saturating	NOUN
ijassa-1100	106	11	functions	function	NOUN
ijassa-1100	106	12	,	,	PUNCT
ijassa-1100	106	13	which	which	PRON
ijassa-1100	106	14	with	with	ADP
ijassa-1100	106	15	an	an	DET
ijassa-1100	106	16	increasing	increase	VERB
ijassa-1100	106	17	input	input	NOUN
ijassa-1100	106	18	decrease	decrease	NOUN
ijassa-1100	106	19	to	to	ADP
ijassa-1100	106	20	almost	almost	ADV
ijassa-1100	106	21	zero	zero	NUM
ijassa-1100	106	22	.	.	PUNCT
ijassa-1100	107	1	a	a	DET
ijassa-1100	107	2	recent	recent	ADJ
ijassa-1100	107	3	study	study	NOUN
ijassa-1100	107	4	has	have	AUX
ijassa-1100	107	5	shown	show	VERB
ijassa-1100	107	6	the	the	DET
ijassa-1100	107	7	growth	growth	NOUN
ijassa-1100	107	8	in	in	ADP
ijassa-1100	107	9	cnn	cnn	PROPN
ijassa-1100	107	10	applications	application	NOUN
ijassa-1100	107	11	’	'	PUNCT
ijassa-1100	107	12	rate	rate	NOUN
ijassa-1100	107	13	of	of	ADP
ijassa-1100	107	14	speed	speed	NOUN
ijassa-1100	107	15	and	and	CCONJ
ijassa-1100	107	16	rating	rating	NOUN
ijassa-1100	107	17	performance	performance	NOUN
ijassa-1100	107	18	,	,	PUNCT
ijassa-1100	107	19	as	as	ADV
ijassa-1100	107	20	well	well	ADV
ijassa-1100	107	21	as	as	ADP
ijassa-1100	107	22	the	the	DET
ijassa-1100	107	23	classification	classification	NOUN
ijassa-1100	107	24	performance	performance	NOUN
ijassa-1100	107	25	of	of	ADP
ijassa-1100	107	26	such	such	DET
ijassa-1100	107	27	a	a	DET
ijassa-1100	107	28	linear	linear	ADJ
ijassa-1100	107	29	rectified	rectified	ADJ
ijassa-1100	107	30	function	function	NOUN
ijassa-1100	107	31	f(x	f(x	PROPN
ijassa-1100	107	32	)	)	PUNCT
ijassa-1100	107	33	=	=	SYM
ijassa-1100	107	34	maximal(0,x)(relu	maximal(0,x)(relu	NOUN
ijassa-1100	107	35	)	)	PUNCT
ijassa-1100	107	36	.	.	PUNCT
ijassa-1100	108	1	the	the	DET
ijassa-1100	108	2	activation	activation	NOUN
ijassa-1100	108	3	function	function	NOUN
ijassa-1100	108	4	relu	relu	NOUN
ijassa-1100	108	5	is	be	AUX
ijassa-1100	108	6	in	in	ADP
ijassa-1100	108	7	the	the	DET
ijassa-1100	108	8	dense	dense	ADJ
ijassa-1100	108	9	layer	layer	NOUN
ijassa-1100	108	10	of	of	ADP
ijassa-1100	108	11	our	our	PRON
ijassa-1100	108	12	cnn	cnn	PROPN
ijassa-1100	108	13	model	model	NOUN
ijassa-1100	108	14	.	.	PUNCT
ijassa-1100	109	1	the	the	DET
ijassa-1100	109	2	suggested	suggest	VERB
ijassa-1100	109	3	2	2	NUM
ijassa-1100	109	4	-	-	ADJ
ijassa-1100	109	5	dimensional	dimensional	ADJ
ijassa-1100	109	6	(	(	PUNCT
ijassa-1100	109	7	2d	2d	NOUN
ijassa-1100	109	8	)	)	PUNCT
ijassa-1100	109	9	cnn	cnn	PROPN
ijassa-1100	109	10	model	model	NOUN
ijassa-1100	109	11	is	be	AUX
ijassa-1100	109	12	shown	show	VERB
ijassa-1100	109	13	in	in	ADP
ijassa-1100	109	14	figure	figure	NOUN
ijassa-1100	109	15	2.6	2.6	NUM
ijassa-1100	109	16	.	.	PUNCT
ijassa-1100	110	1	the	the	DET
ijassa-1100	110	2	eight	eight	NUM
ijassa-1100	110	3	layers	layer	NOUN
ijassa-1100	110	4	of	of	ADP
ijassa-1100	110	5	the	the	DET
ijassa-1100	110	6	proposed	propose	VERB
ijassa-1100	110	7	model	model	NOUN
ijassa-1100	110	8	consist	consist	NOUN
ijassa-1100	110	9	of	of	ADP
ijassa-1100	110	10	three	three	NUM
ijassa-1100	110	11	convolution	convolution	NOUN
ijassa-1100	110	12	layers	layer	NOUN
ijassa-1100	110	13	,	,	PUNCT
ijassa-1100	110	14	three	three	NUM
ijassa-1100	110	15	max	max	NOUN
ijassa-1100	110	16	-	-	PUNCT
ijassa-1100	110	17	pooling	pool	VERB
ijassa-1100	110	18	layers	layer	NOUN
ijassa-1100	110	19	,	,	PUNCT
ijassa-1100	110	20	and	and	CCONJ
ijassa-1100	110	21	two	two	NUM
ijassa-1100	110	22	dense	dense	ADJ
ijassa-1100	110	23	layers(fully	layers(fully	ADV
ijassa-1100	110	24	connected	connect	VERB
ijassa-1100	110	25	)	)	PUNCT
ijassa-1100	110	26	.	.	PUNCT
ijassa-1100	111	1	the	the	DET
ijassa-1100	111	2	layers	layer	NOUN
ijassa-1100	111	3	are	be	AUX
ijassa-1100	111	4	converged	converge	VERB
ijassa-1100	111	5	to	to	ADP
ijassa-1100	111	6	the	the	DET
ijassa-1100	111	7	corresponding	corresponding	ADJ
ijassa-1100	111	8	kernel	kernel	NOUN
ijassa-1100	111	9	size	size	NOUN
ijassa-1100	111	10	for	for	ADP
ijassa-1100	111	11	each	each	DET
ijassa-1100	111	12	convolution	convolution	NOUN
ijassa-1100	111	13	layer	layer	NOUN
ijassa-1100	111	14	(	(	PUNCT
ijassa-1100	111	15	64	64	NUM
ijassa-1100	111	16	,	,	PUNCT
ijassa-1100	111	17	32	32	NUM
ijassa-1100	111	18	and	and	CCONJ
ijassa-1100	111	19	64	64	NUM
ijassa-1100	111	20	)	)	PUNCT
ijassa-1100	111	21	.	.	PUNCT
ijassa-1100	112	1	the	the	DET
ijassa-1100	112	2	max	max	PROPN
ijassa-1100	112	3	-	-	PUNCT
ijassa-1100	112	4	pooling	pool	VERB
ijassa-1100	112	5	layer	layer	NOUN
ijassa-1100	112	6	also	also	ADV
ijassa-1100	112	7	called	call	VERB
ijassa-1100	112	8	a	a	DET
ijassa-1100	112	9	downsample	downsample	NOUN
ijassa-1100	112	10	layer	layer	NOUN
ijassa-1100	112	11	,	,	PUNCT
ijassa-1100	112	12	should	should	AUX
ijassa-1100	112	13	be	be	AUX
ijassa-1100	112	14	utilized	utilize	VERB
ijassa-1100	112	15	to	to	ADP
ijassa-1100	112	16	the	the	DET
ijassa-1100	112	17	features	feature	NOUN
ijassa-1100	112	18	maps	map	NOUN
ijassa-1100	112	19	after	after	ADP
ijassa-1100	112	20	every	every	DET
ijassa-1100	112	21	two	two	NUM
ijassa-1100	112	22	convolution	convolution	NOUN
ijassa-1100	112	23	layers	layer	NOUN
ijassa-1100	112	24	.	.	PUNCT
ijassa-1100	113	1	it	it	PRON
ijassa-1100	113	2	was	be	AUX
ijassa-1100	113	3	used	use	VERB
ijassa-1100	113	4	to	to	ADP
ijassa-1100	113	5	copyright	copyright	NOUN
ijassa-1100	113	6	©	©	PROPN
ijassa-1100	113	7	2021	2021	NUM
ijassa-1100	113	8	assa	assa	NOUN
ijassa-1100	113	9	.	.	PUNCT
ijassa-1100	114	1	adv	adv	PROPN
ijassa-1100	114	2	syst	syst	PROPN
ijassa-1100	114	3	sci	sci	PROPN
ijassa-1100	114	4	appl	appl	PROPN
ijassa-1100	114	5	(	(	PUNCT
ijassa-1100	114	6	2021	2021	NUM
ijassa-1100	114	7	)	)	PUNCT
ijassa-1100	114	8	36	36	NUM
ijassa-1100	114	9	a.	a.	NOUN
ijassa-1100	114	10	nainwal	nainwal	NOUN
ijassa-1100	114	11	,	,	PUNCT
ijassa-1100	114	12	g	g	PROPN
ijassa-1100	114	13	k	k	PROPN
ijassa-1100	114	14	malik	malik	PROPN
ijassa-1100	114	15	,	,	PUNCT
ijassa-1100	114	16	amrish	amrish	VERB
ijassa-1100	114	17	fig	fig	NOUN
ijassa-1100	114	18	.	.	PUNCT
ijassa-1100	115	1	2.6	2.6	NUM
ijassa-1100	115	2	.	.	PUNCT
ijassa-1100	116	1	cnn	cnn	PROPN
ijassa-1100	116	2	model	model	PROPN
ijassa-1100	116	3	decrease	decrease	VERB
ijassa-1100	116	4	computer	computer	NOUN
ijassa-1100	116	5	complexity	complexity	NOUN
ijassa-1100	116	6	and	and	CCONJ
ijassa-1100	116	7	override	override	NOUN
ijassa-1100	116	8	controls	control	NOUN
ijassa-1100	116	9	.	.	PUNCT
ijassa-1100	117	1	the	the	DET
ijassa-1100	117	2	stride	stride	NOUN
ijassa-1100	117	3	is	be	AUX
ijassa-1100	117	4	set	set	VERB
ijassa-1100	117	5	to	to	ADP
ijassa-1100	117	6	1	1	NUM
ijassa-1100	117	7	and	and	CCONJ
ijassa-1100	117	8	2	2	NUM
ijassa-1100	117	9	,	,	PUNCT
ijassa-1100	117	10	respectively	respectively	ADV
ijassa-1100	117	11	,	,	PUNCT
ijassa-1100	117	12	for	for	ADP
ijassa-1100	117	13	the	the	DET
ijassa-1100	117	14	convolution	convolution	NOUN
ijassa-1100	117	15	and	and	CCONJ
ijassa-1100	117	16	the	the	DET
ijassa-1100	117	17	max	max	PROPN
ijassa-1100	117	18	-	-	PUNCT
ijassa-1100	117	19	pooling	pool	VERB
ijassa-1100	117	20	layer	layer	NOUN
ijassa-1100	117	21	.	.	PUNCT
ijassa-1100	118	1	two	two	NUM
ijassa-1100	118	2	activation	activation	NOUN
ijassa-1100	118	3	functions	function	NOUN
ijassa-1100	118	4	relu	relu	NOUN
ijassa-1100	118	5	and	and	CCONJ
ijassa-1100	118	6	softmax	softmax	NOUN
ijassa-1100	118	7	are	be	AUX
ijassa-1100	118	8	used	use	VERB
ijassa-1100	118	9	in	in	ADP
ijassa-1100	118	10	dense	dense	ADJ
ijassa-1100	118	11	layer	layer	NOUN
ijassa-1100	118	12	to	to	PART
ijassa-1100	118	13	improve	improve	VERB
ijassa-1100	118	14	the	the	DET
ijassa-1100	118	15	performance	performance	NOUN
ijassa-1100	118	16	of	of	ADP
ijassa-1100	118	17	the	the	DET
ijassa-1100	118	18	model	model	NOUN
ijassa-1100	118	19	.	.	PUNCT
ijassa-1100	119	1	3	3	X
ijassa-1100	119	2	.	.	NOUN
ijassa-1100	119	3	result	result	NOUN
ijassa-1100	119	4	and	and	CCONJ
ijassa-1100	119	5	discussion	discussion	NOUN
ijassa-1100	119	6	this	this	DET
ijassa-1100	119	7	section	section	NOUN
ijassa-1100	119	8	discusses	discuss	VERB
ijassa-1100	119	9	the	the	DET
ijassa-1100	119	10	performance	performance	NOUN
ijassa-1100	119	11	of	of	ADP
ijassa-1100	119	12	the	the	DET
ijassa-1100	119	13	ecg	ecg	PROPN
ijassa-1100	119	14	image	image	NOUN
ijassa-1100	119	15	classification	classification	NOUN
ijassa-1100	119	16	network	network	NOUN
ijassa-1100	119	17	.	.	PUNCT
ijassa-1100	120	1	we	we	PRON
ijassa-1100	120	2	suggested	suggest	VERB
ijassa-1100	120	3	an	an	DET
ijassa-1100	120	4	efficient	efficient	ADJ
ijassa-1100	120	5	approach	approach	NOUN
ijassa-1100	120	6	to	to	PART
ijassa-1100	120	7	extract	extract	VERB
ijassa-1100	120	8	and	and	CCONJ
ijassa-1100	120	9	detect	detect	VERB
ijassa-1100	120	10	characteristics	characteristic	NOUN
ijassa-1100	120	11	from	from	ADP
ijassa-1100	120	12	each	each	DET
ijassa-1100	120	13	ecg	ecg	PROPN
ijassa-1100	120	14	image	image	NOUN
ijassa-1100	120	15	to	to	PART
ijassa-1100	120	16	examine	examine	VERB
ijassa-1100	120	17	the	the	DET
ijassa-1100	120	18	performance	performance	NOUN
ijassa-1100	120	19	of	of	ADP
ijassa-1100	120	20	the	the	DET
ijassa-1100	120	21	proposed	propose	VERB
ijassa-1100	120	22	system	system	NOUN
ijassa-1100	120	23	.	.	PUNCT
ijassa-1100	121	1	the	the	DET
ijassa-1100	121	2	cnn	cnn	PROPN
ijassa-1100	121	3	model	model	NOUN
ijassa-1100	121	4	is	be	AUX
ijassa-1100	121	5	built	build	VERB
ijassa-1100	121	6	in	in	ADP
ijassa-1100	121	7	python	python	NOUN
ijassa-1100	121	8	by	by	ADP
ijassa-1100	121	9	using	use	VERB
ijassa-1100	121	10	the	the	DET
ijassa-1100	121	11	keras	keras	PROPN
ijassa-1100	121	12	library	library	NOUN
ijassa-1100	121	13	in	in	ADP
ijassa-1100	121	14	colab.research	colab.research	NOUN
ijassa-1100	121	15	(	(	PUNCT
ijassa-1100	121	16	open	open	ADJ
ijassa-1100	121	17	source	source	NOUN
ijassa-1100	121	18	)	)	PUNCT
ijassa-1100	121	19	google	google	PROPN
ijassa-1100	121	20	platform	platform	NOUN
ijassa-1100	121	21	.	.	PUNCT
ijassa-1100	122	1	the	the	DET
ijassa-1100	122	2	filtered	filter	VERB
ijassa-1100	122	3	image	image	NOUN
ijassa-1100	122	4	is	be	AUX
ijassa-1100	122	5	sent	send	VERB
ijassa-1100	122	6	into	into	ADP
ijassa-1100	122	7	the	the	DET
ijassa-1100	122	8	cnn	cnn	PROPN
ijassa-1100	122	9	model	model	NOUN
ijassa-1100	122	10	,	,	PUNCT
ijassa-1100	122	11	which	which	PRON
ijassa-1100	122	12	classifies	classify	VERB
ijassa-1100	122	13	it	it	PRON
ijassa-1100	122	14	.	.	PUNCT
ijassa-1100	123	1	the	the	DET
ijassa-1100	123	2	image	image	NOUN
ijassa-1100	123	3	is	be	AUX
ijassa-1100	123	4	filtered	filter	VERB
ijassa-1100	123	5	during	during	ADP
ijassa-1100	123	6	preprocessing	preprocesse	VERB
ijassa-1100	123	7	to	to	PART
ijassa-1100	123	8	increase	increase	VERB
ijassa-1100	123	9	system	system	NOUN
ijassa-1100	123	10	accuracy	accuracy	NOUN
ijassa-1100	123	11	.	.	PUNCT
ijassa-1100	124	1	different	different	ADJ
ijassa-1100	124	2	measures	measure	NOUN
ijassa-1100	124	3	have	have	AUX
ijassa-1100	124	4	been	be	AUX
ijassa-1100	124	5	used	use	VERB
ijassa-1100	124	6	to	to	PART
ijassa-1100	124	7	evaluate	evaluate	VERB
ijassa-1100	124	8	the	the	DET
ijassa-1100	124	9	system	system	NOUN
ijassa-1100	124	10	’s	’s	PART
ijassa-1100	124	11	performance	performance	NOUN
ijassa-1100	124	12	.	.	PUNCT
ijassa-1100	125	1	three	three	NUM
ijassa-1100	125	2	key	key	ADJ
ijassa-1100	125	3	indexes	index	NOUN
ijassa-1100	125	4	are	be	AUX
ijassa-1100	125	5	used	use	VERB
ijassa-1100	125	6	to	to	PART
ijassa-1100	125	7	assess	assess	VERB
ijassa-1100	125	8	the	the	DET
ijassa-1100	125	9	classifier	classifier	NOUN
ijassa-1100	125	10	’s	’s	PART
ijassa-1100	125	11	performance	performance	NOUN
ijassa-1100	125	12	,	,	PUNCT
ijassa-1100	125	13	namely	namely	ADV
ijassa-1100	125	14	accuracy(acc	accuracy(acc	NOUN
ijassa-1100	125	15	)	)	PUNCT
ijassa-1100	125	16	,	,	PUNCT
ijassa-1100	125	17	sensitivity(se	sensitivity(se	NOUN
ijassa-1100	125	18	)	)	PUNCT
ijassa-1100	125	19	and	and	CCONJ
ijassa-1100	125	20	specificity(sp	specificity(sp	VERB
ijassa-1100	125	21	)	)	PUNCT
ijassa-1100	125	22	.	.	PUNCT
ijassa-1100	126	1	se	se	X
ijassa-1100	127	1	=	=	PUNCT
ijassa-1100	127	2	(	(	PUNCT
ijassa-1100	127	3	tp	tp	PART
ijassa-1100	127	4	/	/	SYM
ijassa-1100	127	5	tp	tp	X
ijassa-1100	127	6	+	+	CCONJ
ijassa-1100	127	7	fn))×	fn))×	PROPN
ijassa-1100	127	8	100	100	NUM
ijassa-1100	127	9	sp	sp	ADP
ijassa-1100	127	10	=	=	SYM
ijassa-1100	127	11	(	(	PUNCT
ijassa-1100	127	12	tn/(tn	tn/(tn	NOUN
ijassa-1100	127	13	+	+	SYM
ijassa-1100	127	14	fp	fp	X
ijassa-1100	127	15	)	)	PUNCT
ijassa-1100	127	16	×	×	PROPN
ijassa-1100	127	17	100	100	NUM
ijassa-1100	127	18	acc	acc	NOUN
ijassa-1100	127	19	=	=	PUNCT
ijassa-1100	127	20	(	(	PUNCT
ijassa-1100	127	21	(	(	PUNCT
ijassa-1100	127	22	tp	tp	PART
ijassa-1100	127	23	+	+	CCONJ
ijassa-1100	127	24	tn)/(tp	tn)/(tp	ADJ
ijassa-1100	127	25	+	+	CCONJ
ijassa-1100	127	26	tn	tn	NOUN
ijassa-1100	127	27	+	+	SYM
ijassa-1100	127	28	fp	fp	PROPN
ijassa-1100	127	29	+	+	CCONJ
ijassa-1100	127	30	fn))×	fn))×	PROPN
ijassa-1100	127	31	100	100	NUM
ijassa-1100	127	32	predicted	predict	VERB
ijassa-1100	127	33	normal	normal	ADJ
ijassa-1100	127	34	covid-19	covid-19	PROPN
ijassa-1100	127	35	accuracy	accuracy	NOUN
ijassa-1100	127	36	sensitivity	sensitivity	NOUN
ijassa-1100	127	37	specificity	specificity	NOUN
ijassa-1100	127	38	original	original	ADJ
ijassa-1100	127	39	normal	normal	ADJ
ijassa-1100	127	40	847	847	NUM
ijassa-1100	127	41	12	12	NUM
ijassa-1100	127	42	98.11	98.11	NUM
ijassa-1100	127	43	98.60	98.60	NUM
ijassa-1100	127	44	96.40	96.40	NUM
ijassa-1100	127	45	covid-19	covid-19	PROPN
ijassa-1100	127	46	9	9	NUM
ijassa-1100	127	47	241	241	NUM
ijassa-1100	127	48	98.11	98.11	NUM
ijassa-1100	127	49	96.40	96.40	NUM
ijassa-1100	127	50	98.60	98.60	NUM
ijassa-1100	127	51	table	table	NOUN
ijassa-1100	127	52	3.2	3.2	NUM
ijassa-1100	127	53	.	.	PUNCT
ijassa-1100	128	1	confusion	confusion	NOUN
ijassa-1100	128	2	matrix	matrix	NOUN
ijassa-1100	128	3	for	for	ADP
ijassa-1100	128	4	complete	complete	ADJ
ijassa-1100	128	5	data	datum	NOUN
ijassa-1100	128	6	set	set	VERB
ijassa-1100	128	7	predicted	predict	VERB
ijassa-1100	128	8	normal	normal	ADJ
ijassa-1100	128	9	covid-19	covid-19	PROPN
ijassa-1100	128	10	accuracy	accuracy	NOUN
ijassa-1100	128	11	sensitivity	sensitivity	NOUN
ijassa-1100	128	12	specificity	specificity	NOUN
ijassa-1100	128	13	original	original	ADJ
ijassa-1100	128	14	normal	normal	ADJ
ijassa-1100	128	15	243	243	NUM
ijassa-1100	128	16	7	7	NUM
ijassa-1100	128	17	97	97	NUM
ijassa-1100	128	18	97.2	97.2	NUM
ijassa-1100	128	19	96.8	96.8	NUM
ijassa-1100	128	20	covid-19	covid-19	PROPN
ijassa-1100	128	21	8	8	NUM
ijassa-1100	128	22	242	242	NUM
ijassa-1100	128	23	97	97	NUM
ijassa-1100	128	24	96.8	96.8	NUM
ijassa-1100	128	25	97.2	97.2	NUM
ijassa-1100	128	26	table	table	NOUN
ijassa-1100	128	27	3.3	3.3	NUM
ijassa-1100	128	28	.	.	PUNCT
ijassa-1100	129	1	confusion	confusion	NOUN
ijassa-1100	129	2	matrix	matrix	NOUN
ijassa-1100	129	3	for	for	ADP
ijassa-1100	129	4	balanced	balanced	ADJ
ijassa-1100	129	5	data	datum	NOUN
ijassa-1100	129	6	set	set	VERB
ijassa-1100	129	7	copyright	copyright	NOUN
ijassa-1100	129	8	©	©	PROPN
ijassa-1100	129	9	2021	2021	NUM
ijassa-1100	129	10	assa	assa	NOUN
ijassa-1100	129	11	.	.	PUNCT
ijassa-1100	130	1	adv	adv	PROPN
ijassa-1100	130	2	syst	syst	PROPN
ijassa-1100	130	3	sci	sci	PROPN
ijassa-1100	130	4	appl	appl	PROPN
ijassa-1100	130	5	(	(	PUNCT
ijassa-1100	130	6	2021	2021	NUM
ijassa-1100	130	7	)	)	PUNCT
ijassa-1100	130	8	convolution	convolution	NOUN
ijassa-1100	130	9	neural	neural	ADJ
ijassa-1100	130	10	network	network	NOUN
ijassa-1100	130	11	based	base	VERB
ijassa-1100	130	12	covid-19	covid-19	PROPN
ijassa-1100	130	13	screening	screen	VERB
ijassa-1100	130	14	model	model	NOUN
ijassa-1100	130	15	37	37	NUM
ijassa-1100	130	16	fig	fig	NOUN
ijassa-1100	130	17	.	.	PUNCT
ijassa-1100	131	1	3.7	3.7	NUM
ijassa-1100	131	2	.	.	PUNCT
ijassa-1100	132	1	training	training	NOUN
ijassa-1100	132	2	and	and	CCONJ
ijassa-1100	132	3	validation	validation	NOUN
ijassa-1100	132	4	accuracy	accuracy	NOUN
ijassa-1100	132	5	and	and	CCONJ
ijassa-1100	132	6	loss	loss	NOUN
ijassa-1100	132	7	plot	plot	NOUN
ijassa-1100	132	8	for	for	ADP
ijassa-1100	132	9	complete	complete	ADJ
ijassa-1100	132	10	data	datum	NOUN
ijassa-1100	132	11	set	set	VERB
ijassa-1100	132	12	and	and	CCONJ
ijassa-1100	132	13	balanced	balanced	ADJ
ijassa-1100	132	14	data	datum	NOUN
ijassa-1100	132	15	set	set	VERB
ijassa-1100	132	16	where	where	SCONJ
ijassa-1100	132	17	the	the	DET
ijassa-1100	132	18	number	number	NOUN
ijassa-1100	132	19	of	of	ADP
ijassa-1100	132	20	impostor	impostor	NOUN
ijassa-1100	132	21	acceptations	acceptation	NOUN
ijassa-1100	132	22	is	be	AUX
ijassa-1100	132	23	false	false	ADV
ijassa-1100	132	24	positive	positive	ADJ
ijassa-1100	132	25	(	(	PUNCT
ijassa-1100	132	26	fp	fp	NOUN
ijassa-1100	132	27	)	)	PUNCT
ijassa-1100	132	28	,	,	PUNCT
ijassa-1100	132	29	true	true	ADJ
ijassa-1100	132	30	negative	negative	ADJ
ijassa-1100	132	31	(	(	PUNCT
ijassa-1100	132	32	tn	tn	NOUN
ijassa-1100	132	33	)	)	PUNCT
ijassa-1100	132	34	is	be	AUX
ijassa-1100	132	35	an	an	DET
ijassa-1100	132	36	impostor	impostor	NOUN
ijassa-1100	132	37	refusal	refusal	NOUN
ijassa-1100	132	38	number	number	NOUN
ijassa-1100	132	39	;	;	PUNCT
ijassa-1100	132	40	false	false	ADJ
ijassa-1100	132	41	negative	negative	ADJ
ijassa-1100	132	42	(	(	PUNCT
ijassa-1100	132	43	fn	fn	NOUN
ijassa-1100	132	44	)	)	PUNCT
ijassa-1100	132	45	is	be	AUX
ijassa-1100	132	46	a	a	DET
ijassa-1100	132	47	valid	valid	ADJ
ijassa-1100	132	48	denial	denial	NOUN
ijassa-1100	132	49	number	number	NOUN
ijassa-1100	132	50	and	and	CCONJ
ijassa-1100	132	51	true	true	ADJ
ijassa-1100	132	52	positive	positive	ADJ
ijassa-1100	132	53	(	(	PUNCT
ijassa-1100	132	54	tp	tp	NOUN
ijassa-1100	132	55	)	)	PUNCT
ijassa-1100	132	56	is	be	AUX
ijassa-1100	132	57	a	a	DET
ijassa-1100	132	58	valid	valid	ADJ
ijassa-1100	132	59	acceptance	acceptance	NOUN
ijassa-1100	132	60	.	.	PUNCT
ijassa-1100	133	1	table	table	NOUN
ijassa-1100	133	2	3.2	3.2	NUM
ijassa-1100	133	3	shows	show	VERB
ijassa-1100	133	4	the	the	DET
ijassa-1100	133	5	confusion	confusion	NOUN
ijassa-1100	133	6	matrix	matrix	NOUN
ijassa-1100	133	7	for	for	ADP
ijassa-1100	133	8	complete	complete	ADJ
ijassa-1100	133	9	data	datum	NOUN
ijassa-1100	133	10	set	set	VERB
ijassa-1100	133	11	with	with	ADP
ijassa-1100	133	12	859	859	NUM
ijassa-1100	133	13	samples	sample	NOUN
ijassa-1100	133	14	of	of	ADP
ijassa-1100	133	15	normal	normal	ADJ
ijassa-1100	133	16	ecg	ecg	PROPN
ijassa-1100	133	17	and	and	CCONJ
ijassa-1100	133	18	250	250	NUM
ijassa-1100	133	19	samples	sample	NOUN
ijassa-1100	133	20	of	of	ADP
ijassa-1100	133	21	covid-19	covid-19	PROPN
ijassa-1100	133	22	patient	patient	NOUN
ijassa-1100	133	23	ecg.proposed	ecg.propose	VERB
ijassa-1100	133	24	convolution	convolution	NOUN
ijassa-1100	133	25	neural	neural	ADJ
ijassa-1100	133	26	network	network	NOUN
ijassa-1100	133	27	used	use	VERB
ijassa-1100	133	28	60	60	NUM
ijassa-1100	133	29	%	%	NOUN
ijassa-1100	133	30	of	of	ADP
ijassa-1100	133	31	data	datum	NOUN
ijassa-1100	133	32	for	for	ADP
ijassa-1100	133	33	training	training	NOUN
ijassa-1100	133	34	and	and	CCONJ
ijassa-1100	133	35	40	40	NUM
ijassa-1100	133	36	%	%	NOUN
ijassa-1100	133	37	data	datum	NOUN
ijassa-1100	133	38	for	for	ADP
ijassa-1100	133	39	testing	testing	NOUN
ijassa-1100	133	40	purposes	purpose	NOUN
ijassa-1100	133	41	.	.	PUNCT
ijassa-1100	134	1	it	it	PRON
ijassa-1100	134	2	demonstrates	demonstrate	VERB
ijassa-1100	134	3	that	that	SCONJ
ijassa-1100	134	4	98.60	98.60	NUM
ijassa-1100	134	5	%	%	NOUN
ijassa-1100	134	6	of	of	ADP
ijassa-1100	134	7	normal	normal	ADJ
ijassa-1100	134	8	ecg	ecg	PROPN
ijassa-1100	134	9	segments	segment	NOUN
ijassa-1100	134	10	are	be	AUX
ijassa-1100	134	11	accurately	accurately	ADV
ijassa-1100	134	12	classified	classify	VERB
ijassa-1100	134	13	in	in	ADP
ijassa-1100	134	14	the	the	DET
ijassa-1100	134	15	normal	normal	ADJ
ijassa-1100	134	16	class	class	NOUN
ijassa-1100	134	17	,	,	PUNCT
ijassa-1100	134	18	while	while	SCONJ
ijassa-1100	134	19	96.40	96.40	NUM
ijassa-1100	134	20	%	%	NOUN
ijassa-1100	134	21	of	of	ADP
ijassa-1100	134	22	covid19	covid19	NOUN
ijassa-1100	134	23	images	image	NOUN
ijassa-1100	134	24	are	be	AUX
ijassa-1100	134	25	accurately	accurately	ADV
ijassa-1100	134	26	classified	classify	VERB
ijassa-1100	134	27	in	in	ADP
ijassa-1100	134	28	the	the	DET
ijassa-1100	134	29	covid-19	covid-19	PROPN
ijassa-1100	134	30	class	class	NOUN
ijassa-1100	134	31	.	.	PUNCT
ijassa-1100	135	1	only	only	ADV
ijassa-1100	135	2	1.40	1.40	NUM
ijassa-1100	135	3	%	%	NOUN
ijassa-1100	135	4	and	and	CCONJ
ijassa-1100	135	5	3.6%of	3.6%of	NUM
ijassa-1100	135	6	ecg	ecg	PROPN
ijassa-1100	135	7	images	image	NOUN
ijassa-1100	135	8	are	be	AUX
ijassa-1100	135	9	misclassified	misclassifie	VERB
ijassa-1100	135	10	as	as	ADP
ijassa-1100	135	11	covid-19	covid-19	PROPN
ijassa-1100	135	12	and	and	CCONJ
ijassa-1100	135	13	normal	normal	ADJ
ijassa-1100	135	14	class	class	NOUN
ijassa-1100	135	15	,	,	PUNCT
ijassa-1100	135	16	respectively	respectively	ADV
ijassa-1100	135	17	.	.	PUNCT
ijassa-1100	136	1	the	the	DET
ijassa-1100	136	2	model	model	NOUN
ijassa-1100	136	3	incorrectly	incorrectly	ADV
ijassa-1100	136	4	detects	detect	VERB
ijassa-1100	136	5	12	12	NUM
ijassa-1100	136	6	normal	normal	ADJ
ijassa-1100	136	7	ecg	ecg	PROPN
ijassa-1100	136	8	images	image	NOUN
ijassa-1100	136	9	as	as	ADP
ijassa-1100	136	10	covid-19	covid-19	PROPN
ijassa-1100	136	11	ecg	ecg	PROPN
ijassa-1100	136	12	and	and	CCONJ
ijassa-1100	136	13	correctly	correctly	ADV
ijassa-1100	136	14	detects	detect	VERB
ijassa-1100	136	15	847	847	NUM
ijassa-1100	136	16	images	image	NOUN
ijassa-1100	136	17	.	.	PUNCT
ijassa-1100	137	1	out	out	ADP
ijassa-1100	137	2	of	of	ADP
ijassa-1100	137	3	250	250	NUM
ijassa-1100	137	4	covid	covid	PROPN
ijassa-1100	137	5	-19	-19	PUNCT
ijassa-1100	137	6	ecg	ecg	PROPN
ijassa-1100	137	7	images	image	NOUN
ijassa-1100	137	8	,	,	PUNCT
ijassa-1100	137	9	the	the	DET
ijassa-1100	137	10	network	network	NOUN
ijassa-1100	137	11	incorrectly	incorrectly	ADV
ijassa-1100	137	12	classifies	classify	VERB
ijassa-1100	137	13	9	9	NUM
ijassa-1100	137	14	of	of	ADP
ijassa-1100	137	15	them	they	PRON
ijassa-1100	137	16	,	,	PUNCT
ijassa-1100	137	17	while	while	SCONJ
ijassa-1100	137	18	the	the	DET
ijassa-1100	137	19	rest	rest	NOUN
ijassa-1100	137	20	are	be	AUX
ijassa-1100	137	21	correctly	correctly	ADV
ijassa-1100	137	22	identified	identify	VERB
ijassa-1100	137	23	.	.	PUNCT
ijassa-1100	138	1	with	with	ADP
ijassa-1100	138	2	the	the	DET
ijassa-1100	138	3	entire	entire	ADJ
ijassa-1100	138	4	data	datum	NOUN
ijassa-1100	138	5	set	set	VERB
ijassa-1100	138	6	,	,	PUNCT
ijassa-1100	138	7	the	the	DET
ijassa-1100	138	8	accuracy	accuracy	NOUN
ijassa-1100	138	9	is	be	AUX
ijassa-1100	138	10	98.11	98.11	NUM
ijassa-1100	138	11	%	%	NOUN
ijassa-1100	138	12	.	.	PUNCT
ijassa-1100	139	1	table	table	NOUN
ijassa-1100	139	2	3.3	3.3	NUM
ijassa-1100	139	3	illustrates	illustrate	VERB
ijassa-1100	139	4	the	the	DET
ijassa-1100	139	5	confusion	confusion	NOUN
ijassa-1100	139	6	matrix	matrix	NOUN
ijassa-1100	139	7	for	for	ADP
ijassa-1100	139	8	a	a	DET
ijassa-1100	139	9	balanced	balanced	ADJ
ijassa-1100	139	10	data	datum	NOUN
ijassa-1100	139	11	set	set	VERB
ijassa-1100	139	12	with	with	ADP
ijassa-1100	139	13	250	250	NUM
ijassa-1100	139	14	samples	sample	NOUN
ijassa-1100	139	15	of	of	ADP
ijassa-1100	139	16	each	each	DET
ijassa-1100	139	17	class	class	NOUN
ijassa-1100	139	18	.	.	PUNCT
ijassa-1100	140	1	out	out	ADP
ijassa-1100	140	2	of	of	ADP
ijassa-1100	140	3	250	250	NUM
ijassa-1100	140	4	images	image	NOUN
ijassa-1100	140	5	,	,	PUNCT
ijassa-1100	140	6	7	7	NUM
ijassa-1100	140	7	normal	normal	ADJ
ijassa-1100	140	8	ecg	ecg	PROPN
ijassa-1100	140	9	images	image	NOUN
ijassa-1100	140	10	and	and	CCONJ
ijassa-1100	140	11	8	8	NUM
ijassa-1100	140	12	covid-19	covid-19	PROPN
ijassa-1100	140	13	ecg	ecg	PROPN
ijassa-1100	140	14	images	image	NOUN
ijassa-1100	140	15	are	be	AUX
ijassa-1100	140	16	classified	classify	VERB
ijassa-1100	140	17	copyright	copyright	NOUN
ijassa-1100	140	18	©	©	PROPN
ijassa-1100	140	19	2021	2021	NUM
ijassa-1100	140	20	assa	assa	NOUN
ijassa-1100	140	21	.	.	PUNCT
ijassa-1100	141	1	adv	adv	PROPN
ijassa-1100	141	2	syst	syst	PROPN
ijassa-1100	141	3	sci	sci	PROPN
ijassa-1100	141	4	appl	appl	PROPN
ijassa-1100	141	5	(	(	PUNCT
ijassa-1100	141	6	2021	2021	NUM
ijassa-1100	141	7	)	)	PUNCT
ijassa-1100	141	8	38	38	NUM
ijassa-1100	141	9	a.	a.	NOUN
ijassa-1100	141	10	nainwal	nainwal	NOUN
ijassa-1100	141	11	,	,	PUNCT
ijassa-1100	141	12	g	g	PROPN
ijassa-1100	141	13	k	k	PROPN
ijassa-1100	141	14	malik	malik	PROPN
ijassa-1100	141	15	,	,	PUNCT
ijassa-1100	141	16	amrish	amrish	VERB
ijassa-1100	141	17	wrong	wrong	ADV
ijassa-1100	141	18	.	.	PUNCT
ijassa-1100	142	1	in	in	ADP
ijassa-1100	142	2	this	this	DET
ijassa-1100	142	3	data	datum	NOUN
ijassa-1100	142	4	set	set	VERB
ijassa-1100	142	5	2.8	2.8	NUM
ijassa-1100	142	6	%	%	NOUN
ijassa-1100	142	7	of	of	ADP
ijassa-1100	142	8	normal	normal	ADJ
ijassa-1100	142	9	ecg	ecg	PROPN
ijassa-1100	142	10	images	image	NOUN
ijassa-1100	142	11	are	be	AUX
ijassa-1100	142	12	incorrectly	incorrectly	ADV
ijassa-1100	142	13	labeled	label	VERB
ijassa-1100	142	14	as	as	ADP
ijassa-1100	142	15	covid-19	covid-19	PROPN
ijassa-1100	142	16	.	.	PUNCT
ijassa-1100	143	1	furthermore	furthermore	ADV
ijassa-1100	143	2	,	,	PUNCT
ijassa-1100	143	3	the	the	DET
ijassa-1100	143	4	misclassification	misclassification	NOUN
ijassa-1100	143	5	rate	rate	NOUN
ijassa-1100	143	6	of	of	ADP
ijassa-1100	143	7	the	the	DET
ijassa-1100	143	8	covid-19	covid-19	PROPN
ijassa-1100	143	9	ecg	ecg	PROPN
ijassa-1100	143	10	image	image	NOUN
ijassa-1100	143	11	is	be	AUX
ijassa-1100	143	12	approximately	approximately	ADV
ijassa-1100	143	13	3.2	3.2	NUM
ijassa-1100	143	14	%	%	NOUN
ijassa-1100	143	15	.	.	PUNCT
ijassa-1100	144	1	the	the	DET
ijassa-1100	144	2	accuracy	accuracy	NOUN
ijassa-1100	144	3	of	of	ADP
ijassa-1100	144	4	this	this	DET
ijassa-1100	144	5	scenario	scenario	NOUN
ijassa-1100	144	6	is	be	AUX
ijassa-1100	144	7	97	97	NUM
ijassa-1100	144	8	%	%	NOUN
ijassa-1100	144	9	.	.	PUNCT
ijassa-1100	145	1	figure	figure	NOUN
ijassa-1100	145	2	3.7	3.7	NUM
ijassa-1100	145	3	shows	show	VERB
ijassa-1100	145	4	the	the	DET
ijassa-1100	145	5	graph	graph	NOUN
ijassa-1100	145	6	between	between	ADP
ijassa-1100	145	7	accuracy	accuracy	NOUN
ijassa-1100	145	8	and	and	CCONJ
ijassa-1100	145	9	loss	loss	NOUN
ijassa-1100	145	10	versus	versus	ADP
ijassa-1100	145	11	no	no	PRON
ijassa-1100	145	12	of	of	ADP
ijassa-1100	145	13	epochs	epoch	NOUN
ijassa-1100	145	14	.	.	PUNCT
ijassa-1100	146	1	the	the	DET
ijassa-1100	146	2	first	first	ADJ
ijassa-1100	146	3	two	two	NUM
ijassa-1100	146	4	graphs	graph	NOUN
ijassa-1100	146	5	show	show	VERB
ijassa-1100	146	6	the	the	DET
ijassa-1100	146	7	training	training	NOUN
ijassa-1100	146	8	and	and	CCONJ
ijassa-1100	146	9	validation	validation	NOUN
ijassa-1100	146	10	accuracy	accuracy	NOUN
ijassa-1100	146	11	vs.	vs.	ADP
ijassa-1100	146	12	epochs	epoch	NOUN
ijassa-1100	146	13	and	and	CCONJ
ijassa-1100	146	14	loss	loss	NOUN
ijassa-1100	146	15	vs.	vs.	ADP
ijassa-1100	146	16	epochs	epoch	NOUN
ijassa-1100	146	17	,	,	PUNCT
ijassa-1100	146	18	respectively	respectively	ADV
ijassa-1100	146	19	for	for	ADP
ijassa-1100	146	20	the	the	DET
ijassa-1100	146	21	complete	complete	ADJ
ijassa-1100	146	22	data	datum	NOUN
ijassa-1100	146	23	set	set	VERB
ijassa-1100	146	24	.	.	PUNCT
ijassa-1100	147	1	the	the	DET
ijassa-1100	147	2	following	follow	VERB
ijassa-1100	147	3	two	two	NUM
ijassa-1100	147	4	plots	plot	NOUN
ijassa-1100	147	5	are	be	AUX
ijassa-1100	147	6	for	for	ADP
ijassa-1100	147	7	a	a	DET
ijassa-1100	147	8	balanced	balanced	ADJ
ijassa-1100	147	9	data	datum	NOUN
ijassa-1100	147	10	set	set	VERB
ijassa-1100	147	11	.	.	PUNCT
ijassa-1100	148	1	it	it	PRON
ijassa-1100	148	2	can	can	AUX
ijassa-1100	148	3	also	also	ADV
ijassa-1100	148	4	be	be	AUX
ijassa-1100	148	5	shown	show	VERB
ijassa-1100	148	6	that	that	SCONJ
ijassa-1100	148	7	after	after	ADP
ijassa-1100	148	8	a	a	DET
ijassa-1100	148	9	few	few	ADJ
ijassa-1100	148	10	epochs	epoch	NOUN
ijassa-1100	148	11	,	,	PUNCT
ijassa-1100	148	12	the	the	DET
ijassa-1100	148	13	networks	network	NOUN
ijassa-1100	148	14	achieve	achieve	VERB
ijassa-1100	148	15	and	and	CCONJ
ijassa-1100	148	16	stable	stable	ADJ
ijassa-1100	148	17	with	with	ADP
ijassa-1100	148	18	the	the	DET
ijassa-1100	148	19	highest	high	ADJ
ijassa-1100	148	20	accuracy	accuracy	NOUN
ijassa-1100	148	21	and	and	CCONJ
ijassa-1100	148	22	lowest	low	ADJ
ijassa-1100	148	23	loss	loss	NOUN
ijassa-1100	148	24	.	.	PUNCT
ijassa-1100	149	1	4	4	X
ijassa-1100	149	2	.	.	X
ijassa-1100	149	3	conclusion	conclusion	NOUN
ijassa-1100	149	4	this	this	DET
ijassa-1100	149	5	article	article	NOUN
ijassa-1100	149	6	presents	present	VERB
ijassa-1100	149	7	an	an	DET
ijassa-1100	149	8	approach	approach	NOUN
ijassa-1100	149	9	for	for	ADP
ijassa-1100	149	10	the	the	DET
ijassa-1100	149	11	screening	screening	NOUN
ijassa-1100	149	12	of	of	ADP
ijassa-1100	149	13	covid-19	covid-19	PROPN
ijassa-1100	149	14	based	base	VERB
ijassa-1100	149	15	on	on	ADP
ijassa-1100	149	16	the	the	DET
ijassa-1100	149	17	convolution	convolution	NOUN
ijassa-1100	149	18	neural	neural	ADJ
ijassa-1100	149	19	networks	network	NOUN
ijassa-1100	149	20	using	use	VERB
ijassa-1100	149	21	data	data	NOUN
ijassa-1100	149	22	-	-	PUNCT
ijassa-1100	149	23	set	set	VERB
ijassa-1100	149	24	features	feature	NOUN
ijassa-1100	149	25	.	.	PUNCT
ijassa-1100	150	1	the	the	DET
ijassa-1100	150	2	suggested	suggest	VERB
ijassa-1100	150	3	approach	approach	NOUN
ijassa-1100	150	4	provides	provide	VERB
ijassa-1100	150	5	links	link	NOUN
ijassa-1100	150	6	between	between	ADP
ijassa-1100	150	7	multiple	multiple	ADJ
ijassa-1100	150	8	layers	layer	NOUN
ijassa-1100	150	9	of	of	ADP
ijassa-1100	150	10	the	the	DET
ijassa-1100	150	11	original	original	ADJ
ijassa-1100	150	12	cnn	cnn	NOUN
ijassa-1100	150	13	architecture	architecture	NOUN
ijassa-1100	150	14	using	use	VERB
ijassa-1100	150	15	convolution	convolution	NOUN
ijassa-1100	150	16	blocks	block	NOUN
ijassa-1100	150	17	,	,	PUNCT
ijassa-1100	150	18	which	which	PRON
ijassa-1100	150	19	produce	produce	VERB
ijassa-1100	150	20	dynamic	dynamic	ADJ
ijassa-1100	150	21	layer	layer	NOUN
ijassa-1100	150	22	combinations	combination	NOUN
ijassa-1100	150	23	of	of	ADP
ijassa-1100	150	24	different	different	ADJ
ijassa-1100	150	25	layers	layer	NOUN
ijassa-1100	150	26	.	.	PUNCT
ijassa-1100	151	1	the	the	DET
ijassa-1100	151	2	suggested	suggest	VERB
ijassa-1100	151	3	approach	approach	NOUN
ijassa-1100	151	4	is	be	AUX
ijassa-1100	151	5	used	use	VERB
ijassa-1100	151	6	to	to	PART
ijassa-1100	151	7	examine	examine	VERB
ijassa-1100	151	8	two	two	NUM
ijassa-1100	151	9	scenarios	scenario	NOUN
ijassa-1100	151	10	of	of	ADP
ijassa-1100	151	11	the	the	DET
ijassa-1100	151	12	classification	classification	NOUN
ijassa-1100	151	13	task	task	NOUN
ijassa-1100	151	14	.	.	PUNCT
ijassa-1100	152	1	the	the	DET
ijassa-1100	152	2	accuracy	accuracy	NOUN
ijassa-1100	152	3	,	,	PUNCT
ijassa-1100	152	4	sensitivity	sensitivity	NOUN
ijassa-1100	152	5	and	and	CCONJ
ijassa-1100	152	6	specificity	specificity	NOUN
ijassa-1100	152	7	are	be	AUX
ijassa-1100	152	8	used	use	VERB
ijassa-1100	152	9	to	to	PART
ijassa-1100	152	10	analyze	analyze	VERB
ijassa-1100	152	11	outcomes	outcome	NOUN
ijassa-1100	152	12	.	.	PUNCT
ijassa-1100	153	1	the	the	DET
ijassa-1100	153	2	model	model	NOUN
ijassa-1100	153	3	gives	give	VERB
ijassa-1100	153	4	98.11	98.11	NUM
ijassa-1100	153	5	%	%	NOUN
ijassa-1100	153	6	accuracy	accuracy	NOUN
ijassa-1100	153	7	for	for	ADP
ijassa-1100	153	8	complete	complete	ADJ
ijassa-1100	153	9	data	datum	NOUN
ijassa-1100	153	10	set	set	VERB
ijassa-1100	153	11	and	and	CCONJ
ijassa-1100	153	12	97	97	NUM
ijassa-1100	153	13	%	%	NOUN
ijassa-1100	153	14	accuracy	accuracy	NOUN
ijassa-1100	153	15	for	for	ADP
ijassa-1100	153	16	balanced	balanced	ADJ
ijassa-1100	153	17	data	datum	NOUN
ijassa-1100	153	18	set	set	VERB
ijassa-1100	153	19	.	.	PUNCT
ijassa-1100	154	1	since	since	SCONJ
ijassa-1100	154	2	the	the	DET
ijassa-1100	154	3	suggested	suggest	VERB
ijassa-1100	154	4	approach	approach	NOUN
ijassa-1100	154	5	leverages	leverage	VERB
ijassa-1100	154	6	the	the	DET
ijassa-1100	154	7	ecg	ecg	PROPN
ijassa-1100	154	8	trace	trace	NOUN
ijassa-1100	154	9	image	image	NOUN
ijassa-1100	154	10	that	that	PRON
ijassa-1100	154	11	smartphone	smartphone	NOUN
ijassa-1100	154	12	acquired	acquire	VERB
ijassa-1100	154	13	and	and	CCONJ
ijassa-1100	154	14	widely	widely	ADV
ijassa-1100	154	15	accessible	accessible	ADJ
ijassa-1100	154	16	facilities	facility	NOUN
ijassa-1100	154	17	in	in	ADP
ijassa-1100	154	18	low	low	ADJ
ijassa-1100	154	19	resource	resource	NOUN
ijassa-1100	154	20	nations	nation	NOUN
ijassa-1100	154	21	,	,	PUNCT
ijassa-1100	154	22	this	this	DET
ijassa-1100	154	23	study	study	NOUN
ijassa-1100	154	24	helps	help	VERB
ijassa-1100	154	25	to	to	PART
ijassa-1100	154	26	diagnose	diagnose	VERB
ijassa-1100	154	27	covid-19	covid-19	PROPN
ijassa-1100	154	28	and	and	CCONJ
ijassa-1100	154	29	other	other	ADJ
ijassa-1100	154	30	heart	heart	NOUN
ijassa-1100	154	31	defects	defect	NOUN
ijassa-1100	154	32	as	as	ADP
ijassa-1100	154	33	a	a	DET
ijassa-1100	154	34	second	second	ADJ
ijassa-1100	154	35	opinion	opinion	NOUN
ijassa-1100	154	36	by	by	ADP
ijassa-1100	154	37	computer	computer	NOUN
ijassa-1100	154	38	-	-	PUNCT
ijassa-1100	154	39	aided	aid	VERB
ijassa-1100	154	40	methods	method	NOUN
ijassa-1100	154	41	.	.	PUNCT
ijassa-1100	155	1	references	reference	NOUN
ijassa-1100	155	2	1	1	NUM
ijassa-1100	155	3	.	.	X
ijassa-1100	155	4	dong	dong	PROPN
ijassa-1100	155	5	,	,	PUNCT
ijassa-1100	155	6	e.	e.	PROPN
ijassa-1100	155	7	,	,	PUNCT
ijassa-1100	155	8	du	du	PROPN
ijassa-1100	155	9	,	,	PUNCT
ijassa-1100	155	10	h.	h.	PROPN
ijassa-1100	155	11	,	,	PUNCT
ijassa-1100	155	12	&	&	CCONJ
ijassa-1100	155	13	gardner	gardner	PROPN
ijassa-1100	155	14	,	,	PUNCT
ijassa-1100	155	15	l.	l.	PROPN
ijassa-1100	155	16	(	(	PUNCT
ijassa-1100	155	17	2020	2020	NUM
ijassa-1100	155	18	)	)	PUNCT
ijassa-1100	155	19	an	an	DET
ijassa-1100	155	20	interactive	interactive	ADJ
ijassa-1100	155	21	web	web	NOUN
ijassa-1100	155	22	-	-	PUNCT
ijassa-1100	155	23	based	base	VERB
ijassa-1100	155	24	dashboard	dashboard	NOUN
ijassa-1100	155	25	to	to	PART
ijassa-1100	155	26	track	track	VERB
ijassa-1100	155	27	covid-19	covid-19	PROPN
ijassa-1100	155	28	in	in	ADP
ijassa-1100	155	29	real	real	ADJ
ijassa-1100	155	30	time	time	NOUN
ijassa-1100	155	31	.	.	PUNCT
ijassa-1100	156	1	the	the	DET
ijassa-1100	156	2	lancet	lancet	ADJ
ijassa-1100	156	3	infectious	infectious	ADJ
ijassa-1100	156	4	diseases	disease	NOUN
ijassa-1100	156	5	,	,	PUNCT
ijassa-1100	156	6	20	20	NUM
ijassa-1100	156	7	,	,	PUNCT
ijassa-1100	156	8	533–534	533–534	NUM
ijassa-1100	156	9	.	.	NOUN
ijassa-1100	156	10	2	2	NUM
ijassa-1100	156	11	.	.	X
ijassa-1100	156	12	grasselli	grasselli	PROPN
ijassa-1100	156	13	,	,	PUNCT
ijassa-1100	156	14	g.	g.	PROPN
ijassa-1100	156	15	,	,	PUNCT
ijassa-1100	156	16	et	et	PROPN
ijassa-1100	156	17	al	al	PROPN
ijassa-1100	156	18	.	.	PROPN
ijassa-1100	156	19	(	(	PUNCT
ijassa-1100	156	20	2020	2020	NUM
ijassa-1100	156	21	)	)	PUNCT
ijassa-1100	156	22	baseline	baseline	NOUN
ijassa-1100	156	23	characteristics	characteristic	NOUN
ijassa-1100	156	24	and	and	CCONJ
ijassa-1100	156	25	outcomes	outcome	NOUN
ijassa-1100	156	26	of	of	ADP
ijassa-1100	156	27	1591	1591	NUM
ijassa-1100	156	28	patients	patient	NOUN
ijassa-1100	156	29	infected	infect	VERB
ijassa-1100	156	30	with	with	ADP
ijassa-1100	156	31	sars	sar	NOUN
ijassa-1100	156	32	-	-	PUNCT
ijassa-1100	156	33	cov-2	cov-2	PART
ijassa-1100	156	34	admitted	admit	VERB
ijassa-1100	156	35	to	to	PART
ijassa-1100	156	36	icus	icus	VERB
ijassa-1100	156	37	of	of	ADP
ijassa-1100	156	38	the	the	DET
ijassa-1100	156	39	lombardy	lombardy	PROPN
ijassa-1100	156	40	region	region	PROPN
ijassa-1100	156	41	,	,	PUNCT
ijassa-1100	156	42	italy	italy	PROPN
ijassa-1100	156	43	.	.	PUNCT
ijassa-1100	157	1	jama	jama	PROPN
ijassa-1100	157	2	,	,	PUNCT
ijassa-1100	157	3	323	323	NUM
ijassa-1100	157	4	,	,	PUNCT
ijassa-1100	157	5	1574	1574	NUM
ijassa-1100	157	6	–	–	PUNCT
ijassa-1100	157	7	1581	1581	NUM
ijassa-1100	157	8	.	.	PUNCT
ijassa-1100	158	1	3	3	X
ijassa-1100	158	2	.	.	X
ijassa-1100	158	3	bergamaschi	bergamaschi	PROPN
ijassa-1100	158	4	,	,	PUNCT
ijassa-1100	158	5	l.	l.	PROPN
ijassa-1100	158	6	,	,	PUNCT
ijassa-1100	158	7	et	et	PROPN
ijassa-1100	158	8	al	al	PROPN
ijassa-1100	158	9	.	.	PROPN
ijassa-1100	158	10	(	(	PUNCT
ijassa-1100	158	11	2021	2021	NUM
ijassa-1100	158	12	)	)	PUNCT
ijassa-1100	158	13	the	the	DET
ijassa-1100	158	14	value	value	NOUN
ijassa-1100	158	15	of	of	ADP
ijassa-1100	158	16	ecg	ecg	PROPN
ijassa-1100	158	17	changes	change	NOUN
ijassa-1100	158	18	in	in	ADP
ijassa-1100	158	19	risk	risk	NOUN
ijassa-1100	158	20	stratification	stratification	NOUN
ijassa-1100	158	21	of	of	ADP
ijassa-1100	158	22	covid-19	covid-19	PROPN
ijassa-1100	158	23	patients	patient	NOUN
ijassa-1100	158	24	.	.	PUNCT
ijassa-1100	159	1	annals	annal	NOUN
ijassa-1100	159	2	of	of	ADP
ijassa-1100	159	3	noninvasive	noninvasive	ADJ
ijassa-1100	159	4	electrocardiology	electrocardiology	NOUN
ijassa-1100	159	5	,	,	PUNCT
ijassa-1100	159	6	p.	p.	PROPN
ijassa-1100	159	7	e12815	e12815	PROPN
ijassa-1100	159	8	.	.	PROPN
ijassa-1100	160	1	4	4	X
ijassa-1100	160	2	.	.	X
ijassa-1100	160	3	doyen	doyen	NOUN
ijassa-1100	160	4	,	,	PUNCT
ijassa-1100	160	5	d.	d.	PROPN
ijassa-1100	160	6	,	,	PUNCT
ijassa-1100	160	7	moceri	moceri	PROPN
ijassa-1100	160	8	,	,	PUNCT
ijassa-1100	160	9	p.	p.	PROPN
ijassa-1100	160	10	,	,	PUNCT
ijassa-1100	160	11	ducreux	ducreux	PROPN
ijassa-1100	160	12	,	,	PUNCT
ijassa-1100	160	13	d.	d.	PROPN
ijassa-1100	160	14	,	,	PUNCT
ijassa-1100	160	15	&	&	CCONJ
ijassa-1100	160	16	dellamonica	dellamonica	PROPN
ijassa-1100	160	17	,	,	PUNCT
ijassa-1100	160	18	j.	j.	PROPN
ijassa-1100	160	19	(	(	PUNCT
ijassa-1100	160	20	2020	2020	NUM
ijassa-1100	160	21	)	)	PUNCT
ijassa-1100	160	22	myocarditis	myocarditis	NOUN
ijassa-1100	160	23	in	in	ADP
ijassa-1100	160	24	a	a	DET
ijassa-1100	160	25	patient	patient	NOUN
ijassa-1100	160	26	with	with	ADP
ijassa-1100	160	27	covid-19	covid-19	PROPN
ijassa-1100	160	28	:	:	PUNCT
ijassa-1100	160	29	a	a	DET
ijassa-1100	160	30	cause	cause	NOUN
ijassa-1100	160	31	of	of	ADP
ijassa-1100	160	32	raised	raise	VERB
ijassa-1100	160	33	troponin	troponin	PROPN
ijassa-1100	160	34	and	and	CCONJ
ijassa-1100	160	35	ecg	ecg	PROPN
ijassa-1100	160	36	changes	change	NOUN
ijassa-1100	160	37	.	.	PUNCT
ijassa-1100	161	1	the	the	DET
ijassa-1100	161	2	lancet	lancet	NOUN
ijassa-1100	161	3	,	,	PUNCT
ijassa-1100	161	4	395	395	NUM
ijassa-1100	161	5	,	,	PUNCT
ijassa-1100	161	6	1516	1516	NUM
ijassa-1100	161	7	.	.	PUNCT
ijassa-1100	162	1	5	5	NUM
ijassa-1100	162	2	.	.	X
ijassa-1100	162	3	zheng	zheng	PROPN
ijassa-1100	162	4	,	,	PUNCT
ijassa-1100	162	5	y.-y	y.-y	PROPN
ijassa-1100	162	6	.	.	PROPN
ijassa-1100	162	7	,	,	PUNCT
ijassa-1100	162	8	ma	ma	PROPN
ijassa-1100	162	9	,	,	PUNCT
ijassa-1100	162	10	y.-t	y.-t	NOUN
ijassa-1100	162	11	.	.	PUNCT
ijassa-1100	162	12	,	,	PUNCT
ijassa-1100	162	13	zhang	zhang	PROPN
ijassa-1100	162	14	,	,	PUNCT
ijassa-1100	162	15	j.-y	j.-y	PROPN
ijassa-1100	162	16	.	.	PROPN
ijassa-1100	162	17	,	,	PUNCT
ijassa-1100	162	18	&	&	CCONJ
ijassa-1100	162	19	xie	xie	PROPN
ijassa-1100	162	20	,	,	PUNCT
ijassa-1100	162	21	x.	x.	PROPN
ijassa-1100	162	22	(	(	PUNCT
ijassa-1100	162	23	2020	2020	NUM
ijassa-1100	162	24	)	)	PUNCT
ijassa-1100	162	25	covid-19	covid-19	PROPN
ijassa-1100	162	26	and	and	CCONJ
ijassa-1100	162	27	the	the	DET
ijassa-1100	162	28	cardiovascular	cardiovascular	ADJ
ijassa-1100	162	29	system	system	NOUN
ijassa-1100	162	30	.	.	PUNCT
ijassa-1100	163	1	nature	nature	NOUN
ijassa-1100	163	2	reviews	review	VERB
ijassa-1100	163	3	cardiology	cardiology	NOUN
ijassa-1100	163	4	,	,	PUNCT
ijassa-1100	163	5	17	17	NUM
ijassa-1100	163	6	,	,	PUNCT
ijassa-1100	163	7	259–260	259–260	NUM
ijassa-1100	163	8	.	.	PUNCT
ijassa-1100	164	1	6	6	NUM
ijassa-1100	164	2	.	.	X
ijassa-1100	164	3	angeli	angeli	PROPN
ijassa-1100	164	4	,	,	PUNCT
ijassa-1100	164	5	f.	f.	PROPN
ijassa-1100	164	6	,	,	PUNCT
ijassa-1100	164	7	spanevello	spanevello	PROPN
ijassa-1100	164	8	,	,	PUNCT
ijassa-1100	164	9	a.	a.	NOUN
ijassa-1100	164	10	,	,	PUNCT
ijassa-1100	164	11	de	de	PROPN
ijassa-1100	164	12	ponti	ponti	PROPN
ijassa-1100	164	13	,	,	PUNCT
ijassa-1100	164	14	r.	r.	PROPN
ijassa-1100	164	15	,	,	PUNCT
ijassa-1100	164	16	visca	visca	PROPN
ijassa-1100	164	17	,	,	PUNCT
ijassa-1100	164	18	d.	d.	PROPN
ijassa-1100	164	19	,	,	PUNCT
ijassa-1100	164	20	marazzato	marazzato	PROPN
ijassa-1100	164	21	,	,	PUNCT
ijassa-1100	164	22	j.	j.	PROPN
ijassa-1100	164	23	,	,	PUNCT
ijassa-1100	164	24	palmiotto	palmiotto	PROPN
ijassa-1100	164	25	,	,	PUNCT
ijassa-1100	164	26	g.	g.	PROPN
ijassa-1100	164	27	,	,	PUNCT
ijassa-1100	164	28	feci	feci	PROPN
ijassa-1100	164	29	,	,	PUNCT
ijassa-1100	164	30	d.	d.	PROPN
ijassa-1100	164	31	,	,	PUNCT
ijassa-1100	164	32	reboldi	reboldi	NOUN
ijassa-1100	164	33	,	,	PUNCT
ijassa-1100	164	34	g.	g.	PROPN
ijassa-1100	164	35	,	,	PUNCT
ijassa-1100	164	36	fabbri	fabbri	NOUN
ijassa-1100	164	37	,	,	PUNCT
ijassa-1100	164	38	l.	l.	PROPN
ijassa-1100	164	39	m.	m.	PROPN
ijassa-1100	164	40	,	,	PUNCT
ijassa-1100	164	41	&	&	CCONJ
ijassa-1100	164	42	verdecchia	verdecchia	PROPN
ijassa-1100	164	43	,	,	PUNCT
ijassa-1100	164	44	p.	p.	NOUN
ijassa-1100	164	45	(	(	PUNCT
ijassa-1100	164	46	2020	2020	NUM
ijassa-1100	164	47	)	)	PUNCT
ijassa-1100	164	48	electrocardiographic	electrocardiographic	ADJ
ijassa-1100	164	49	features	feature	NOUN
ijassa-1100	164	50	of	of	ADP
ijassa-1100	164	51	patients	patient	NOUN
ijassa-1100	164	52	with	with	ADP
ijassa-1100	164	53	covid-19	covid-19	PROPN
ijassa-1100	164	54	pneumonia	pneumonia	NOUN
ijassa-1100	164	55	.	.	PUNCT
ijassa-1100	165	1	european	european	PROPN
ijassa-1100	165	2	journal	journal	PROPN
ijassa-1100	165	3	of	of	ADP
ijassa-1100	165	4	internal	internal	ADJ
ijassa-1100	165	5	medicine	medicine	NOUN
ijassa-1100	165	6	,	,	PUNCT
ijassa-1100	165	7	78	78	NUM
ijassa-1100	165	8	,	,	PUNCT
ijassa-1100	165	9	101–106	101–106	NUM
ijassa-1100	165	10	.	.	PUNCT
ijassa-1100	166	1	7	7	X
ijassa-1100	166	2	.	.	X
ijassa-1100	166	3	lecun	lecun	ADJ
ijassa-1100	166	4	,	,	PUNCT
ijassa-1100	166	5	y.	y.	PROPN
ijassa-1100	166	6	,	,	PUNCT
ijassa-1100	166	7	bottou	bottou	PROPN
ijassa-1100	166	8	,	,	PUNCT
ijassa-1100	166	9	l.	l.	PROPN
ijassa-1100	166	10	,	,	PUNCT
ijassa-1100	166	11	bengio	bengio	PROPN
ijassa-1100	166	12	,	,	PUNCT
ijassa-1100	166	13	y.	y.	PROPN
ijassa-1100	166	14	,	,	PUNCT
ijassa-1100	166	15	&	&	CCONJ
ijassa-1100	166	16	haffner	haffner	PROPN
ijassa-1100	166	17	,	,	PUNCT
ijassa-1100	166	18	p.	p.	NOUN
ijassa-1100	166	19	(	(	PUNCT
ijassa-1100	166	20	1998	1998	NUM
ijassa-1100	166	21	)	)	PUNCT
ijassa-1100	166	22	gradient	gradient	NOUN
ijassa-1100	166	23	-	-	PUNCT
ijassa-1100	166	24	based	base	VERB
ijassa-1100	166	25	learning	learning	NOUN
ijassa-1100	166	26	applied	apply	VERB
ijassa-1100	166	27	to	to	ADP
ijassa-1100	166	28	document	document	NOUN
ijassa-1100	166	29	recognition	recognition	NOUN
ijassa-1100	166	30	.	.	PUNCT
ijassa-1100	167	1	proceedings	proceeding	NOUN
ijassa-1100	167	2	of	of	ADP
ijassa-1100	167	3	the	the	DET
ijassa-1100	167	4	ieee	ieee	NOUN
ijassa-1100	167	5	,	,	PUNCT
ijassa-1100	167	6	86	86	NUM
ijassa-1100	167	7	,	,	PUNCT
ijassa-1100	167	8	2278–2324	2278–2324	NUM
ijassa-1100	167	9	.	.	NOUN
ijassa-1100	167	10	8	8	NUM
ijassa-1100	167	11	.	.	X
ijassa-1100	167	12	lee	lee	PROPN
ijassa-1100	167	13	,	,	PUNCT
ijassa-1100	167	14	h.	h.	PROPN
ijassa-1100	167	15	&	&	CCONJ
ijassa-1100	167	16	kwon	kwon	PROPN
ijassa-1100	167	17	,	,	PUNCT
ijassa-1100	167	18	h.	h.	PROPN
ijassa-1100	167	19	(	(	PUNCT
ijassa-1100	167	20	2017	2017	NUM
ijassa-1100	167	21	)	)	PUNCT
ijassa-1100	167	22	going	go	VERB
ijassa-1100	167	23	deeper	deeply	ADV
ijassa-1100	167	24	with	with	ADP
ijassa-1100	167	25	contextual	contextual	ADJ
ijassa-1100	167	26	cnn	cnn	NOUN
ijassa-1100	167	27	for	for	ADP
ijassa-1100	167	28	hyperspectral	hyperspectral	ADJ
ijassa-1100	167	29	image	image	NOUN
ijassa-1100	167	30	classification	classification	NOUN
ijassa-1100	167	31	.	.	PUNCT
ijassa-1100	168	1	ieee	ieee	NOUN
ijassa-1100	168	2	transactions	transaction	NOUN
ijassa-1100	168	3	on	on	ADP
ijassa-1100	168	4	image	image	NOUN
ijassa-1100	168	5	processing	processing	NOUN
ijassa-1100	168	6	,	,	PUNCT
ijassa-1100	168	7	26	26	NUM
ijassa-1100	168	8	,	,	PUNCT
ijassa-1100	168	9	4843–4855	4843–4855	NUM
ijassa-1100	168	10	.	.	NOUN
ijassa-1100	169	1	9	9	X
ijassa-1100	169	2	.	.	X
ijassa-1100	169	3	hershey	hershey	PROPN
ijassa-1100	169	4	,	,	PUNCT
ijassa-1100	169	5	s.	s.	PROPN
ijassa-1100	169	6	,	,	PUNCT
ijassa-1100	169	7	et	et	PROPN
ijassa-1100	169	8	al	al	PROPN
ijassa-1100	169	9	.	.	PROPN
ijassa-1100	170	1	(	(	PUNCT
ijassa-1100	170	2	2017	2017	NUM
ijassa-1100	170	3	)	)	PUNCT
ijassa-1100	170	4	cnn	cnn	PROPN
ijassa-1100	170	5	architectures	architecture	VERB
ijassa-1100	170	6	for	for	ADP
ijassa-1100	170	7	large	large	ADJ
ijassa-1100	170	8	-	-	PUNCT
ijassa-1100	170	9	scale	scale	NOUN
ijassa-1100	170	10	audio	audio	NOUN
ijassa-1100	170	11	classification	classification	NOUN
ijassa-1100	170	12	.	.	PUNCT
ijassa-1100	171	1	in	in	ADP
ijassa-1100	171	2	2017	2017	NUM
ijassa-1100	171	3	ieee	ieee	NOUN
ijassa-1100	171	4	international	international	ADJ
ijassa-1100	171	5	conference	conference	NOUN
ijassa-1100	171	6	on	on	ADP
ijassa-1100	171	7	acoustics	acoustic	NOUN
ijassa-1100	171	8	,	,	PUNCT
ijassa-1100	171	9	speech	speech	NOUN
ijassa-1100	171	10	and	and	CCONJ
ijassa-1100	171	11	signal	signal	NOUN
ijassa-1100	171	12	processing	processing	NOUN
ijassa-1100	171	13	(	(	PUNCT
ijassa-1100	171	14	icassp	icassp	PROPN
ijassa-1100	171	15	)	)	PUNCT
ijassa-1100	171	16	,	,	PUNCT
ijassa-1100	171	17	131	131	NUM
ijassa-1100	171	18	–	–	SYM
ijassa-1100	171	19	135	135	NUM
ijassa-1100	171	20	,	,	PUNCT
ijassa-1100	171	21	ieee	ieee	NOUN
ijassa-1100	171	22	.	.	PUNCT
ijassa-1100	172	1	10	10	NUM
ijassa-1100	172	2	.	.	PUNCT
ijassa-1100	173	1	pei	pei	PROPN
ijassa-1100	173	2	,	,	PUNCT
ijassa-1100	173	3	z.	z.	PROPN
ijassa-1100	173	4	,	,	PUNCT
ijassa-1100	173	5	li	li	PROPN
ijassa-1100	173	6	,	,	PUNCT
ijassa-1100	173	7	c.	c.	PROPN
ijassa-1100	173	8	,	,	PUNCT
ijassa-1100	173	9	qin	qin	PROPN
ijassa-1100	173	10	,	,	PUNCT
ijassa-1100	173	11	x.	x.	PROPN
ijassa-1100	173	12	,	,	PUNCT
ijassa-1100	173	13	chen	chen	PROPN
ijassa-1100	173	14	,	,	PUNCT
ijassa-1100	173	15	x.	x.	PROPN
ijassa-1100	173	16	,	,	PUNCT
ijassa-1100	173	17	&	&	CCONJ
ijassa-1100	173	18	wei	wei	PROPN
ijassa-1100	173	19	,	,	PUNCT
ijassa-1100	173	20	g.	g.	PROPN
ijassa-1100	173	21	(	(	PUNCT
ijassa-1100	173	22	2019	2019	NUM
ijassa-1100	173	23	)	)	PUNCT
ijassa-1100	173	24	iteration	iteration	NOUN
ijassa-1100	173	25	time	time	NOUN
ijassa-1100	173	26	prediction	prediction	NOUN
ijassa-1100	173	27	for	for	ADP
ijassa-1100	173	28	cnn	cnn	PROPN
ijassa-1100	173	29	in	in	ADP
ijassa-1100	173	30	multi	multi	ADJ
ijassa-1100	173	31	-	-	ADJ
ijassa-1100	173	32	gpu	gpu	ADJ
ijassa-1100	173	33	platform	platform	NOUN
ijassa-1100	173	34	:	:	PUNCT
ijassa-1100	173	35	modeling	modeling	NOUN
ijassa-1100	173	36	and	and	CCONJ
ijassa-1100	173	37	analysis	analysis	NOUN
ijassa-1100	173	38	.	.	PUNCT
ijassa-1100	174	1	ieee	ieee	NOUN
ijassa-1100	174	2	access	access	NOUN
ijassa-1100	174	3	,	,	PUNCT
ijassa-1100	174	4	7	7	NUM
ijassa-1100	174	5	,	,	PUNCT
ijassa-1100	174	6	64788–64797	64788–64797	NUM
ijassa-1100	174	7	.	.	PUNCT
ijassa-1100	175	1	11	11	NUM
ijassa-1100	175	2	.	.	PUNCT
ijassa-1100	176	1	zhai	zhai	PROPN
ijassa-1100	176	2	,	,	PUNCT
ijassa-1100	176	3	x.	x.	PROPN
ijassa-1100	176	4	,	,	PUNCT
ijassa-1100	176	5	jelfs	jelfs	PROPN
ijassa-1100	176	6	,	,	PUNCT
ijassa-1100	176	7	b.	b.	PROPN
ijassa-1100	176	8	,	,	PUNCT
ijassa-1100	176	9	chan	chan	PROPN
ijassa-1100	176	10	,	,	PUNCT
ijassa-1100	176	11	r.	r.	PROPN
ijassa-1100	176	12	h.	h.	PROPN
ijassa-1100	176	13	,	,	PUNCT
ijassa-1100	176	14	&	&	CCONJ
ijassa-1100	176	15	tin	tin	PROPN
ijassa-1100	176	16	,	,	PUNCT
ijassa-1100	176	17	c.	c.	NOUN
ijassa-1100	176	18	(	(	PUNCT
ijassa-1100	176	19	2017	2017	NUM
ijassa-1100	176	20	)	)	PUNCT
ijassa-1100	176	21	self	self	NOUN
ijassa-1100	176	22	-	-	PUNCT
ijassa-1100	176	23	recalibrating	recalibrate	VERB
ijassa-1100	176	24	surface	surface	NOUN
ijassa-1100	176	25	emg	emg	NOUN
ijassa-1100	176	26	pattern	pattern	NOUN
ijassa-1100	176	27	recognition	recognition	NOUN
ijassa-1100	176	28	for	for	ADP
ijassa-1100	176	29	neuroprosthesis	neuroprosthesis	PROPN
ijassa-1100	176	30	control	control	NOUN
ijassa-1100	176	31	based	base	VERB
ijassa-1100	176	32	on	on	ADP
ijassa-1100	176	33	convolutional	convolutional	ADJ
ijassa-1100	176	34	neural	neural	ADJ
ijassa-1100	176	35	network	network	NOUN
ijassa-1100	176	36	.	.	PUNCT
ijassa-1100	177	1	frontiers	frontier	NOUN
ijassa-1100	177	2	in	in	ADP
ijassa-1100	177	3	neuroscience	neuroscience	NOUN
ijassa-1100	177	4	,	,	PUNCT
ijassa-1100	177	5	11	11	NUM
ijassa-1100	177	6	,	,	PUNCT
ijassa-1100	177	7	379	379	NUM
ijassa-1100	177	8	.	.	PUNCT
ijassa-1100	177	9	12	12	NUM
ijassa-1100	177	10	.	.	PUNCT
ijassa-1100	178	1	cheng	cheng	PROPN
ijassa-1100	178	2	,	,	PUNCT
ijassa-1100	178	3	j.	j.	PROPN
ijassa-1100	178	4	,	,	PUNCT
ijassa-1100	178	5	liu	liu	PROPN
ijassa-1100	178	6	,	,	PUNCT
ijassa-1100	178	7	y.	y.	PROPN
ijassa-1100	178	8	,	,	PUNCT
ijassa-1100	178	9	&	&	CCONJ
ijassa-1100	178	10	ma	ma	PROPN
ijassa-1100	178	11	,	,	PUNCT
ijassa-1100	178	12	y.	y.	PROPN
ijassa-1100	178	13	(	(	PUNCT
ijassa-1100	178	14	2020	2020	NUM
ijassa-1100	178	15	)	)	PUNCT
ijassa-1100	178	16	protein	protein	NOUN
ijassa-1100	178	17	secondary	secondary	ADJ
ijassa-1100	178	18	structure	structure	NOUN
ijassa-1100	178	19	prediction	prediction	NOUN
ijassa-1100	178	20	based	base	VERB
ijassa-1100	178	21	on	on	ADP
ijassa-1100	178	22	integration	integration	NOUN
ijassa-1100	178	23	of	of	ADP
ijassa-1100	178	24	cnn	cnn	PROPN
ijassa-1100	178	25	and	and	CCONJ
ijassa-1100	178	26	lstm	lstm	PROPN
ijassa-1100	178	27	model	model	PROPN
ijassa-1100	178	28	.	.	PUNCT
ijassa-1100	179	1	journal	journal	PROPN
ijassa-1100	179	2	of	of	ADP
ijassa-1100	179	3	visual	visual	ADJ
ijassa-1100	179	4	communication	communication	NOUN
ijassa-1100	179	5	and	and	CCONJ
ijassa-1100	179	6	image	image	NOUN
ijassa-1100	179	7	copyright	copyright	NOUN
ijassa-1100	179	8	©	©	PROPN
ijassa-1100	179	9	2021	2021	NUM
ijassa-1100	179	10	assa	assa	NOUN
ijassa-1100	179	11	.	.	PUNCT
ijassa-1100	180	1	adv	adv	PROPN
ijassa-1100	180	2	syst	syst	PROPN
ijassa-1100	180	3	sci	sci	PROPN
ijassa-1100	180	4	appl	appl	PROPN
ijassa-1100	180	5	(	(	PUNCT
ijassa-1100	180	6	2021	2021	NUM
ijassa-1100	180	7	)	)	PUNCT
ijassa-1100	180	8	convolution	convolution	NOUN
ijassa-1100	180	9	neural	neural	ADJ
ijassa-1100	180	10	network	network	NOUN
ijassa-1100	180	11	based	base	VERB
ijassa-1100	180	12	covid-19	covid-19	PROPN
ijassa-1100	180	13	screening	screen	VERB
ijassa-1100	180	14	model	model	NOUN
ijassa-1100	180	15	39	39	NUM
ijassa-1100	180	16	representation	representation	NOUN
ijassa-1100	180	17	,	,	PUNCT
ijassa-1100	180	18	71	71	NUM
ijassa-1100	180	19	,	,	PUNCT
ijassa-1100	180	20	102844	102844	NUM
ijassa-1100	180	21	.	.	PUNCT
ijassa-1100	181	1	13	13	NUM
ijassa-1100	181	2	.	.	PUNCT
ijassa-1100	182	1	li	li	PROPN
ijassa-1100	182	2	,	,	PUNCT
ijassa-1100	182	3	y.	y.	PROPN
ijassa-1100	182	4	,	,	PUNCT
ijassa-1100	182	5	pang	pang	NOUN
ijassa-1100	182	6	,	,	PUNCT
ijassa-1100	182	7	y.	y.	PROPN
ijassa-1100	182	8	,	,	PUNCT
ijassa-1100	182	9	wang	wang	PROPN
ijassa-1100	182	10	,	,	PUNCT
ijassa-1100	182	11	j.	j.	PROPN
ijassa-1100	182	12	,	,	PUNCT
ijassa-1100	182	13	&	&	CCONJ
ijassa-1100	182	14	li	li	PROPN
ijassa-1100	182	15	,	,	PUNCT
ijassa-1100	182	16	x.	x.	PROPN
ijassa-1100	182	17	(	(	PUNCT
ijassa-1100	182	18	2018	2018	NUM
ijassa-1100	182	19	)	)	PUNCT
ijassa-1100	182	20	patient	patient	NOUN
ijassa-1100	182	21	-	-	PUNCT
ijassa-1100	182	22	specific	specific	ADJ
ijassa-1100	182	23	ecg	ecg	PROPN
ijassa-1100	182	24	classification	classification	NOUN
ijassa-1100	182	25	by	by	ADP
ijassa-1100	182	26	deeper	deep	ADJ
ijassa-1100	182	27	cnn	cnn	PROPN
ijassa-1100	182	28	from	from	ADP
ijassa-1100	182	29	generic	generic	ADJ
ijassa-1100	182	30	to	to	ADP
ijassa-1100	182	31	dedicated	dedicated	ADJ
ijassa-1100	182	32	.	.	PUNCT
ijassa-1100	183	1	neurocomputing	neurocomputing	NOUN
ijassa-1100	183	2	,	,	PUNCT
ijassa-1100	183	3	314	314	NUM
ijassa-1100	183	4	,	,	PUNCT
ijassa-1100	183	5	336–346	336–346	NUM
ijassa-1100	183	6	.	.	NOUN
ijassa-1100	183	7	14	14	NUM
ijassa-1100	183	8	.	.	PUNCT
ijassa-1100	184	1	degerli	degerli	ADJ
ijassa-1100	184	2	,	,	PUNCT
ijassa-1100	184	3	a.	a.	PROPN
ijassa-1100	184	4	,	,	PUNCT
ijassa-1100	184	5	ahishali	ahishali	NOUN
ijassa-1100	184	6	,	,	PUNCT
ijassa-1100	184	7	m.	m.	NOUN
ijassa-1100	184	8	,	,	PUNCT
ijassa-1100	184	9	yamac	yamac	NOUN
ijassa-1100	184	10	,	,	PUNCT
ijassa-1100	184	11	m.	m.	NOUN
ijassa-1100	184	12	,	,	PUNCT
ijassa-1100	184	13	kiranyaz	kiranyaz	NOUN
ijassa-1100	184	14	,	,	PUNCT
ijassa-1100	184	15	s.	s.	PROPN
ijassa-1100	184	16	,	,	PUNCT
ijassa-1100	184	17	chowdhury	chowdhury	PROPN
ijassa-1100	184	18	,	,	PUNCT
ijassa-1100	184	19	m.	m.	PROPN
ijassa-1100	184	20	e.	e.	PROPN
ijassa-1100	184	21	,	,	PUNCT
ijassa-1100	184	22	hameed	hameed	PROPN
ijassa-1100	184	23	,	,	PUNCT
ijassa-1100	184	24	k.	k.	PROPN
ijassa-1100	184	25	,	,	PUNCT
ijassa-1100	184	26	hamid	hamid	PROPN
ijassa-1100	184	27	,	,	PUNCT
ijassa-1100	184	28	t.	t.	PROPN
ijassa-1100	184	29	,	,	PUNCT
ijassa-1100	184	30	mazhar	mazhar	PROPN
ijassa-1100	184	31	,	,	PUNCT
ijassa-1100	184	32	r.	r.	PROPN
ijassa-1100	184	33	,	,	PUNCT
ijassa-1100	184	34	&	&	CCONJ
ijassa-1100	184	35	gabbouj	gabbouj	NOUN
ijassa-1100	184	36	,	,	PUNCT
ijassa-1100	184	37	m.	m.	NOUN
ijassa-1100	184	38	(	(	PUNCT
ijassa-1100	184	39	2021	2021	NUM
ijassa-1100	184	40	)	)	PUNCT
ijassa-1100	184	41	covid-19	covid-19	PROPN
ijassa-1100	184	42	infection	infection	NOUN
ijassa-1100	184	43	map	map	NOUN
ijassa-1100	184	44	generation	generation	NOUN
ijassa-1100	184	45	and	and	CCONJ
ijassa-1100	184	46	detection	detection	NOUN
ijassa-1100	184	47	from	from	ADP
ijassa-1100	184	48	chest	chest	NOUN
ijassa-1100	184	49	x	x	NOUN
ijassa-1100	184	50	-	-	NOUN
ijassa-1100	184	51	ray	ray	NOUN
ijassa-1100	184	52	images	image	NOUN
ijassa-1100	184	53	.	.	PUNCT
ijassa-1100	185	1	health	health	NOUN
ijassa-1100	185	2	information	information	NOUN
ijassa-1100	185	3	science	science	NOUN
ijassa-1100	185	4	and	and	CCONJ
ijassa-1100	185	5	systems	system	NOUN
ijassa-1100	185	6	,	,	PUNCT
ijassa-1100	185	7	9	9	NUM
ijassa-1100	185	8	,	,	PUNCT
ijassa-1100	185	9	1–16	1–16	NOUN
ijassa-1100	185	10	.	.	PUNCT
ijassa-1100	186	1	15	15	NUM
ijassa-1100	186	2	.	.	PUNCT
ijassa-1100	187	1	kesim	kesim	PROPN
ijassa-1100	187	2	,	,	PUNCT
ijassa-1100	187	3	e.	e.	PROPN
ijassa-1100	187	4	,	,	PUNCT
ijassa-1100	187	5	dokur	dokur	PROPN
ijassa-1100	187	6	,	,	PUNCT
ijassa-1100	187	7	z.	z.	PROPN
ijassa-1100	187	8	,	,	PUNCT
ijassa-1100	187	9	&	&	CCONJ
ijassa-1100	187	10	olmez	olmez	NOUN
ijassa-1100	187	11	,	,	PUNCT
ijassa-1100	187	12	t.	t.	PROPN
ijassa-1100	187	13	(	(	PUNCT
ijassa-1100	187	14	2019	2019	NUM
ijassa-1100	187	15	)	)	PUNCT
ijassa-1100	187	16	x	x	X
ijassa-1100	187	17	-	-	PUNCT
ijassa-1100	187	18	ray	ray	NOUN
ijassa-1100	187	19	chest	chest	NOUN
ijassa-1100	187	20	image	image	NOUN
ijassa-1100	187	21	classification	classification	NOUN
ijassa-1100	187	22	by	by	ADP
ijassa-1100	187	23	a	a	DET
ijassa-1100	187	24	smallsized	smallsize	VERB
ijassa-1100	187	25	convolutional	convolutional	ADJ
ijassa-1100	187	26	neural	neural	ADJ
ijassa-1100	187	27	network	network	NOUN
ijassa-1100	187	28	.	.	PUNCT
ijassa-1100	188	1	in	in	ADP
ijassa-1100	188	2	2019	2019	NUM
ijassa-1100	188	3	scientific	scientific	ADJ
ijassa-1100	188	4	meeting	meeting	NOUN
ijassa-1100	188	5	on	on	ADP
ijassa-1100	188	6	electrical	electrical	ADJ
ijassa-1100	188	7	-	-	PUNCT
ijassa-1100	188	8	electronics	electronic	NOUN
ijassa-1100	188	9	&	&	CCONJ
ijassa-1100	188	10	biomedical	biomedical	ADJ
ijassa-1100	188	11	engineering	engineering	NOUN
ijassa-1100	188	12	and	and	CCONJ
ijassa-1100	188	13	computer	computer	NOUN
ijassa-1100	188	14	science	science	NOUN
ijassa-1100	188	15	(	(	PUNCT
ijassa-1100	188	16	ebbt	ebbt	PROPN
ijassa-1100	188	17	)	)	PUNCT
ijassa-1100	188	18	,	,	PUNCT
ijassa-1100	188	19	1–5	1–5	PROPN
ijassa-1100	188	20	,	,	PUNCT
ijassa-1100	188	21	ieee	ieee	NOUN
ijassa-1100	188	22	.	.	PUNCT
ijassa-1100	188	23	16	16	NUM
ijassa-1100	188	24	.	.	PUNCT
ijassa-1100	189	1	qiblawey	qiblawey	PROPN
ijassa-1100	189	2	,	,	PUNCT
ijassa-1100	189	3	y.	y.	PROPN
ijassa-1100	189	4	,	,	PUNCT
ijassa-1100	189	5	et	et	PROPN
ijassa-1100	189	6	al	al	PROPN
ijassa-1100	189	7	.	.	PROPN
ijassa-1100	190	1	(	(	PUNCT
ijassa-1100	190	2	2021	2021	NUM
ijassa-1100	190	3	)	)	PUNCT
ijassa-1100	190	4	detection	detection	NOUN
ijassa-1100	190	5	and	and	CCONJ
ijassa-1100	190	6	severity	severity	NOUN
ijassa-1100	190	7	classification	classification	NOUN
ijassa-1100	190	8	of	of	ADP
ijassa-1100	190	9	covid-19	covid-19	PROPN
ijassa-1100	190	10	in	in	ADP
ijassa-1100	190	11	ct	ct	NUM
ijassa-1100	190	12	images	image	NOUN
ijassa-1100	190	13	using	use	VERB
ijassa-1100	190	14	deep	deep	ADJ
ijassa-1100	190	15	learning	learning	NOUN
ijassa-1100	190	16	.	.	PUNCT
ijassa-1100	191	1	diagnostics	diagnostic	NOUN
ijassa-1100	191	2	,	,	PUNCT
ijassa-1100	191	3	11	11	NUM
ijassa-1100	191	4	,	,	PUNCT
ijassa-1100	191	5	893	893	NUM
ijassa-1100	191	6	.	.	PUNCT
ijassa-1100	192	1	17	17	NUM
ijassa-1100	192	2	.	.	PUNCT
ijassa-1100	193	1	khan	khan	PROPN
ijassa-1100	193	2	,	,	PUNCT
ijassa-1100	193	3	a.	a.	PROPN
ijassa-1100	193	4	h.	h.	PROPN
ijassa-1100	193	5	,	,	PUNCT
ijassa-1100	193	6	hussain	hussain	PROPN
ijassa-1100	193	7	,	,	PUNCT
ijassa-1100	193	8	m.	m.	NOUN
ijassa-1100	193	9	,	,	PUNCT
ijassa-1100	193	10	&	&	CCONJ
ijassa-1100	193	11	malik	malik	PROPN
ijassa-1100	193	12	,	,	PUNCT
ijassa-1100	193	13	m.	m.	PROPN
ijassa-1100	193	14	k.	k.	PROPN
ijassa-1100	193	15	(	(	PUNCT
ijassa-1100	193	16	2021	2021	NUM
ijassa-1100	193	17	)	)	PUNCT
ijassa-1100	193	18	ecg	ecg	PROPN
ijassa-1100	193	19	images	image	VERB
ijassa-1100	193	20	dataset	dataset	NOUN
ijassa-1100	193	21	of	of	ADP
ijassa-1100	193	22	cardiac	cardiac	ADJ
ijassa-1100	193	23	and	and	CCONJ
ijassa-1100	193	24	covid-19	covid-19	PROPN
ijassa-1100	193	25	patients	patient	NOUN
ijassa-1100	193	26	.	.	PUNCT
ijassa-1100	194	1	data	datum	NOUN
ijassa-1100	194	2	in	in	ADP
ijassa-1100	194	3	brief	brief	ADJ
ijassa-1100	194	4	,	,	PUNCT
ijassa-1100	194	5	34	34	NUM
ijassa-1100	194	6	,	,	PUNCT
ijassa-1100	194	7	106762	106762	NUM
ijassa-1100	194	8	.	.	PUNCT
ijassa-1100	195	1	copyright	copyright	NOUN
ijassa-1100	195	2	©	©	PROPN
ijassa-1100	195	3	2021	2021	NUM
ijassa-1100	195	4	assa	assa	NOUN
ijassa-1100	195	5	.	.	PUNCT
ijassa-1100	196	1	adv	adv	PROPN
ijassa-1100	196	2	syst	syst	PROPN
ijassa-1100	196	3	sci	sci	PROPN
ijassa-1100	196	4	appl	appl	PROPN
ijassa-1100	196	5	(	(	PUNCT
ijassa-1100	196	6	2021	2021	NUM
ijassa-1100	196	7	)	)	PUNCT
ijassa-1100	196	8	introduction	introduction	NOUN
ijassa-1100	196	9	method	method	NOUN
ijassa-1100	196	10	and	and	CCONJ
ijassa-1100	196	11	material	material	NOUN
ijassa-1100	196	12	database	database	NOUN
ijassa-1100	196	13	preprocessing	preprocessing	NOUN
ijassa-1100	196	14	convolution	convolution	NOUN
ijassa-1100	196	15	neural	neural	ADJ
ijassa-1100	196	16	network	network	NOUN
ijassa-1100	196	17	result	result	NOUN
ijassa-1100	196	18	and	and	CCONJ
ijassa-1100	196	19	discussion	discussion	NOUN
ijassa-1100	196	20	conclusion	conclusion	NOUN