id	sid	tid	token	lemma	pos
ijassa-1009	1	1	microsoft	microsoft	PROPN
ijassa-1009	1	2	word	word	NOUN
ijassa-1009	1	3	1009	1009	NUM
ijassa-1009	1	4	article	article	NOUN
ijassa-1009	1	5	text	text	NOUN
ijassa-1009	1	6	,	,	PUNCT
ijassa-1009	1	7	copyedited.docx	copyedited.docx	VERB
ijassa-1009	1	8	adv	adv	PROPN
ijassa-1009	1	9	syst	syst	PROPN
ijassa-1009	1	10	sci	sci	PROPN
ijassa-1009	1	11	appl	appl	PROPN
ijassa-1009	1	12	2021	2021	NUM
ijassa-1009	1	13	;	;	PUNCT
ijassa-1009	1	14	02	02	NUM
ijassa-1009	1	15	;	;	PUNCT
ijassa-1009	1	16	42	42	NUM
ijassa-1009	1	17	-	-	SYM
ijassa-1009	1	18	57	57	NUM
ijassa-1009	1	19	published	publish	VERB
ijassa-1009	1	20	online	online	ADV
ijassa-1009	1	21	at	at	ADP
ijassa-1009	1	22	https://ijassa.ipu.ru	https://ijassa.ipu.ru	ADV
ijassa-1009	1	23	.	.	PUNCT
ijassa-1009	2	1	deep	deep	ADJ
ijassa-1009	2	2	learning	learning	NOUN
ijassa-1009	2	3	techniques	technique	NOUN
ijassa-1009	2	4	for	for	ADP
ijassa-1009	2	5	detection	detection	NOUN
ijassa-1009	2	6	of	of	ADP
ijassa-1009	2	7	covid-19	covid-19	PROPN
ijassa-1009	2	8	using	use	VERB
ijassa-1009	2	9	chest	chest	NOUN
ijassa-1009	2	10	x	x	NOUN
ijassa-1009	2	11	-	-	NOUN
ijassa-1009	2	12	rays	ray	NOUN
ijassa-1009	2	13	alampally	alampally	ADV
ijassa-1009	2	14	naveen1	naveen1	PROPN
ijassa-1009	2	15	*	*	PROPN
ijassa-1009	2	16	,	,	PUNCT
ijassa-1009	2	17	boddu	boddu	ADP
ijassa-1009	2	18	manoj1	manoj1	PROPN
ijassa-1009	2	19	,	,	PUNCT
ijassa-1009	2	20	golla	golla	PROPN
ijassa-1009	2	21	akhila1	akhila1	PROPN
ijassa-1009	2	22	,	,	PUNCT
ijassa-1009	2	23	maunil	maunil	PROPN
ijassa-1009	2	24	bipinkumar	bipinkumar	PROPN
ijassa-1009	2	25	nakarani1	nakarani1	PROPN
ijassa-1009	2	26	,	,	PUNCT
ijassa-1009	2	27	jaini	jaini	PROPN
ijassa-1009	2	28	rathna	rathna	PROPN
ijassa-1009	2	29	sreekar1	sreekar1	PROPN
ijassa-1009	2	30	,	,	PUNCT
ijassa-1009	2	31	pradyumn	pradyumn	NOUN
ijassa-1009	2	32	beriwal1	beriwal1	PROPN
ijassa-1009	2	33	,	,	PUNCT
ijassa-1009	2	34	nipun	nipun	ADJ
ijassa-1009	2	35	gupta1	gupta1	NOUN
ijassa-1009	2	36	,	,	PUNCT
ijassa-1009	2	37	swathi	swathi	NOUN
ijassa-1009	2	38	jamjala	jamjala	NOUN
ijassa-1009	2	39	narayanan1	narayanan1	NOUN
ijassa-1009	2	40	1	1	X
ijassa-1009	2	41	)	)	PUNCT
ijassa-1009	2	42	school	school	NOUN
ijassa-1009	2	43	of	of	ADP
ijassa-1009	2	44	computer	computer	NOUN
ijassa-1009	2	45	science	science	NOUN
ijassa-1009	2	46	and	and	CCONJ
ijassa-1009	2	47	engineering	engineering	NOUN
ijassa-1009	2	48	,	,	PUNCT
ijassa-1009	2	49	vellore	vellore	PROPN
ijassa-1009	2	50	institute	institute	PROPN
ijassa-1009	2	51	of	of	ADP
ijassa-1009	2	52	technology	technology	PROPN
ijassa-1009	2	53	,	,	PUNCT
ijassa-1009	2	54	vellore	vellore	PROPN
ijassa-1009	2	55	,	,	PUNCT
ijassa-1009	2	56	india	india	PROPN
ijassa-1009	2	57	e	e	PROPN
ijassa-1009	2	58	-	-	NOUN
ijassa-1009	2	59	mail	mail	NOUN
ijassa-1009	2	60	:	:	PUNCT
ijassa-1009	2	61	alampallynaveen123@gmail.com	alampallynaveen123@gmail.com	PROPN
ijassa-1009	2	62	,	,	PUNCT
ijassa-1009	2	63	manumanoj0010@gmail.com	manumanoj0010@gmail.com	X
ijassa-1009	2	64	,	,	PUNCT
ijassa-1009	2	65	akhilagolla2020@gmail.com	akhilagolla2020@gmail.com	PROPN
ijassa-1009	2	66	,	,	PUNCT
ijassa-1009	2	67	maunil2399@gmail.com	maunil2399@gmail.com	PROPN
ijassa-1009	2	68	,	,	PUNCT
ijassa-1009	2	69	j.rathnasreekar94@gmail.com	j.rathnasreekar94@gmail.com	PROPN
ijassa-1009	2	70	,	,	PUNCT
ijassa-1009	2	71	pradyumnberiwal@gmail.com	pradyumnberiwal@gmail.com	PROPN
ijassa-1009	2	72	,	,	PUNCT
ijassa-1009	2	73	nipungupta.2702@gmail.com	nipungupta.2702@gmail.com	PROPN
ijassa-1009	2	74	,	,	PUNCT
ijassa-1009	2	75	swathi.jns@gmail.com	swathi.jns@gmail.com	VERB
ijassa-1009	2	76	abstract	abstract	ADJ
ijassa-1009	2	77	:	:	PUNCT
ijassa-1009	2	78	the	the	DET
ijassa-1009	2	79	covid-19	covid-19	PROPN
ijassa-1009	2	80	pandemic	pandemic	ADJ
ijassa-1009	2	81	situation	situation	NOUN
ijassa-1009	2	82	keeps	keep	VERB
ijassa-1009	2	83	on	on	ADP
ijassa-1009	2	84	ruining	ruin	VERB
ijassa-1009	2	85	and	and	CCONJ
ijassa-1009	2	86	affecting	affect	VERB
ijassa-1009	2	87	the	the	DET
ijassa-1009	2	88	wellbeing	wellbeing	NOUN
ijassa-1009	2	89	and	and	CCONJ
ijassa-1009	2	90	prosperity	prosperity	NOUN
ijassa-1009	2	91	of	of	ADP
ijassa-1009	2	92	the	the	DET
ijassa-1009	2	93	worldwide	worldwide	ADJ
ijassa-1009	2	94	population	population	NOUN
ijassa-1009	2	95	and	and	CCONJ
ijassa-1009	2	96	due	due	ADP
ijassa-1009	2	97	to	to	ADP
ijassa-1009	2	98	this	this	DET
ijassa-1009	2	99	situation	situation	NOUN
ijassa-1009	2	100	,	,	PUNCT
ijassa-1009	2	101	the	the	DET
ijassa-1009	2	102	doctors	doctor	NOUN
ijassa-1009	2	103	around	around	ADP
ijassa-1009	2	104	the	the	DET
ijassa-1009	2	105	world	world	NOUN
ijassa-1009	2	106	are	be	AUX
ijassa-1009	2	107	working	work	VERB
ijassa-1009	2	108	restlessly	restlessly	ADV
ijassa-1009	2	109	,	,	PUNCT
ijassa-1009	2	110	as	as	SCONJ
ijassa-1009	2	111	the	the	DET
ijassa-1009	2	112	coronavirus	coronavirus	NOUN
ijassa-1009	2	113	is	be	AUX
ijassa-1009	2	114	increasing	increase	VERB
ijassa-1009	2	115	exponentially	exponentially	ADV
ijassa-1009	2	116	and	and	CCONJ
ijassa-1009	2	117	the	the	DET
ijassa-1009	2	118	situation	situation	NOUN
ijassa-1009	2	119	for	for	ADP
ijassa-1009	2	120	testing	testing	NOUN
ijassa-1009	2	121	has	have	AUX
ijassa-1009	2	122	become	become	VERB
ijassa-1009	2	123	quite	quite	DET
ijassa-1009	2	124	a	a	DET
ijassa-1009	2	125	problematic	problematic	ADJ
ijassa-1009	2	126	and	and	CCONJ
ijassa-1009	2	127	with	with	ADP
ijassa-1009	2	128	restricted	restricted	ADJ
ijassa-1009	2	129	testing	testing	NOUN
ijassa-1009	2	130	units	unit	NOUN
ijassa-1009	2	131	,	,	PUNCT
ijassa-1009	2	132	it	it	PRON
ijassa-1009	2	133	’s	’	VERB
ijassa-1009	2	134	impossible	impossible	ADJ
ijassa-1009	2	135	for	for	SCONJ
ijassa-1009	2	136	every	every	DET
ijassa-1009	2	137	patient	patient	NOUN
ijassa-1009	2	138	to	to	PART
ijassa-1009	2	139	be	be	AUX
ijassa-1009	2	140	tested	test	VERB
ijassa-1009	2	141	with	with	ADP
ijassa-1009	2	142	available	available	ADJ
ijassa-1009	2	143	facilities	facility	NOUN
ijassa-1009	2	144	.	.	PUNCT
ijassa-1009	3	1	effective	effective	ADJ
ijassa-1009	3	2	screening	screening	NOUN
ijassa-1009	3	3	of	of	ADP
ijassa-1009	3	4	infected	infected	ADJ
ijassa-1009	3	5	patients	patient	NOUN
ijassa-1009	3	6	through	through	ADP
ijassa-1009	3	7	chest	chest	NOUN
ijassa-1009	3	8	x	x	NOUN
ijassa-1009	3	9	-	-	NOUN
ijassa-1009	3	10	ray	ray	NOUN
ijassa-1009	3	11	images	image	NOUN
ijassa-1009	3	12	is	be	AUX
ijassa-1009	3	13	a	a	DET
ijassa-1009	3	14	critical	critical	ADJ
ijassa-1009	3	15	step	step	NOUN
ijassa-1009	3	16	in	in	ADP
ijassa-1009	3	17	combating	combat	VERB
ijassa-1009	3	18	covid-19	covid-19	PROPN
ijassa-1009	3	19	.	.	PUNCT
ijassa-1009	4	1	with	with	ADP
ijassa-1009	4	2	the	the	DET
ijassa-1009	4	3	help	help	NOUN
ijassa-1009	4	4	of	of	ADP
ijassa-1009	4	5	deep	deep	ADJ
ijassa-1009	4	6	learning	learning	NOUN
ijassa-1009	4	7	techniques	technique	NOUN
ijassa-1009	4	8	,	,	PUNCT
ijassa-1009	4	9	it	it	PRON
ijassa-1009	4	10	is	be	AUX
ijassa-1009	4	11	possible	possible	ADJ
ijassa-1009	4	12	to	to	PART
ijassa-1009	4	13	train	train	VERB
ijassa-1009	4	14	various	various	ADJ
ijassa-1009	4	15	radiology	radiology	NOUN
ijassa-1009	4	16	images	image	NOUN
ijassa-1009	4	17	and	and	CCONJ
ijassa-1009	4	18	detect	detect	VERB
ijassa-1009	4	19	covid-19	covid-19	PROPN
ijassa-1009	4	20	.	.	PUNCT
ijassa-1009	5	1	the	the	DET
ijassa-1009	5	2	dataset	dataset	NOUN
ijassa-1009	5	3	used	use	VERB
ijassa-1009	5	4	in	in	ADP
ijassa-1009	5	5	our	our	PRON
ijassa-1009	5	6	research	research	NOUN
ijassa-1009	5	7	work	work	NOUN
ijassa-1009	5	8	is	be	AUX
ijassa-1009	5	9	gathered	gather	VERB
ijassa-1009	5	10	from	from	ADP
ijassa-1009	5	11	different	different	ADJ
ijassa-1009	5	12	sources	source	NOUN
ijassa-1009	5	13	and	and	CCONJ
ijassa-1009	5	14	a	a	DET
ijassa-1009	5	15	specific	specific	ADJ
ijassa-1009	5	16	new	new	ADJ
ijassa-1009	5	17	dataset	dataset	NOUN
ijassa-1009	5	18	is	be	AUX
ijassa-1009	5	19	generated	generate	VERB
ijassa-1009	5	20	.	.	PUNCT
ijassa-1009	6	1	the	the	DET
ijassa-1009	6	2	proposed	propose	VERB
ijassa-1009	6	3	methodology	methodology	NOUN
ijassa-1009	6	4	implemented	implement	VERB
ijassa-1009	6	5	is	be	AUX
ijassa-1009	6	6	beneficial	beneficial	ADJ
ijassa-1009	6	7	to	to	ADP
ijassa-1009	6	8	the	the	DET
ijassa-1009	6	9	medical	medical	ADJ
ijassa-1009	6	10	practitioner	practitioner	NOUN
ijassa-1009	6	11	for	for	ADP
ijassa-1009	6	12	the	the	DET
ijassa-1009	6	13	diagnosis	diagnosis	NOUN
ijassa-1009	6	14	of	of	ADP
ijassa-1009	6	15	coronavirus	coronavirus	NOUN
ijassa-1009	6	16	infected	infect	VERB
ijassa-1009	6	17	patients	patient	NOUN
ijassa-1009	6	18	where	where	SCONJ
ijassa-1009	6	19	predictions	prediction	NOUN
ijassa-1009	6	20	can	can	AUX
ijassa-1009	6	21	be	be	AUX
ijassa-1009	6	22	done	do	VERB
ijassa-1009	6	23	automated	automate	VERB
ijassa-1009	6	24	using	use	VERB
ijassa-1009	6	25	deep	deep	ADJ
ijassa-1009	6	26	learning	learning	NOUN
ijassa-1009	6	27	.	.	PUNCT
ijassa-1009	7	1	the	the	DET
ijassa-1009	7	2	deep	deep	ADJ
ijassa-1009	7	3	learning	learning	NOUN
ijassa-1009	7	4	algorithms	algorithm	NOUN
ijassa-1009	7	5	that	that	PRON
ijassa-1009	7	6	are	be	AUX
ijassa-1009	7	7	used	use	VERB
ijassa-1009	7	8	to	to	PART
ijassa-1009	7	9	predict	predict	VERB
ijassa-1009	7	10	the	the	DET
ijassa-1009	7	11	covid	covid	NOUN
ijassa-1009	7	12	with	with	ADP
ijassa-1009	7	13	the	the	DET
ijassa-1009	7	14	help	help	NOUN
ijassa-1009	7	15	of	of	ADP
ijassa-1009	7	16	chest	chest	NOUN
ijassa-1009	7	17	x	x	NOUN
ijassa-1009	7	18	-	-	NOUN
ijassa-1009	7	19	ray	ray	NOUN
ijassa-1009	7	20	images	image	NOUN
ijassa-1009	7	21	are	be	AUX
ijassa-1009	7	22	evaluated	evaluate	VERB
ijassa-1009	7	23	for	for	ADP
ijassa-1009	7	24	their	their	PRON
ijassa-1009	7	25	prediction	prediction	NOUN
ijassa-1009	7	26	based	base	VERB
ijassa-1009	7	27	on	on	ADP
ijassa-1009	7	28	performance	performance	NOUN
ijassa-1009	7	29	metrics	metric	NOUN
ijassa-1009	7	30	such	such	ADJ
ijassa-1009	7	31	as	as	ADP
ijassa-1009	7	32	accuracy	accuracy	NOUN
ijassa-1009	7	33	,	,	PUNCT
ijassa-1009	7	34	precision	precision	NOUN
ijassa-1009	7	35	,	,	PUNCT
ijassa-1009	7	36	recall	recall	NOUN
ijassa-1009	7	37	,	,	PUNCT
ijassa-1009	7	38	and	and	CCONJ
ijassa-1009	7	39	f1	f1	NOUN
ijassa-1009	7	40	-	-	PUNCT
ijassa-1009	7	41	score	score	NOUN
ijassa-1009	7	42	.	.	PUNCT
ijassa-1009	8	1	in	in	ADP
ijassa-1009	8	2	this	this	DET
ijassa-1009	8	3	work	work	NOUN
ijassa-1009	8	4	,	,	PUNCT
ijassa-1009	8	5	the	the	DET
ijassa-1009	8	6	proposed	propose	VERB
ijassa-1009	8	7	model	model	NOUN
ijassa-1009	8	8	has	have	AUX
ijassa-1009	8	9	used	use	VERB
ijassa-1009	8	10	deep	deep	ADJ
ijassa-1009	8	11	learning	learning	NOUN
ijassa-1009	8	12	techniques	technique	NOUN
ijassa-1009	8	13	for	for	ADP
ijassa-1009	8	14	covid-19	covid-19	PROPN
ijassa-1009	8	15	prediction	prediction	NOUN
ijassa-1009	8	16	and	and	CCONJ
ijassa-1009	8	17	the	the	DET
ijassa-1009	8	18	results	result	NOUN
ijassa-1009	8	19	have	have	AUX
ijassa-1009	8	20	shown	show	VERB
ijassa-1009	8	21	superior	superior	ADJ
ijassa-1009	8	22	performance	performance	NOUN
ijassa-1009	8	23	in	in	ADP
ijassa-1009	8	24	prediction	prediction	NOUN
ijassa-1009	8	25	of	of	ADP
ijassa-1009	8	26	covid19	covid19	NOUN
ijassa-1009	8	27	.	.	PUNCT
ijassa-1009	9	1	keywords	keyword	NOUN
ijassa-1009	9	2	:	:	PUNCT
ijassa-1009	9	3	covid	covid	NOUN
ijassa-1009	9	4	,	,	PUNCT
ijassa-1009	9	5	x	x	ADJ
ijassa-1009	9	6	-	-	NOUN
ijassa-1009	9	7	ray	ray	NOUN
ijassa-1009	9	8	images	image	NOUN
ijassa-1009	9	9	,	,	PUNCT
ijassa-1009	9	10	transfer	transfer	NOUN
ijassa-1009	9	11	learning	learning	NOUN
ijassa-1009	9	12	,	,	PUNCT
ijassa-1009	9	13	radiology	radiology	NOUN
ijassa-1009	9	14	,	,	PUNCT
ijassa-1009	9	15	deep	deep	ADJ
ijassa-1009	9	16	learning	learning	NOUN
ijassa-1009	9	17	,	,	PUNCT
ijassa-1009	9	18	diagnosis	diagnosis	NOUN
ijassa-1009	9	19	1	1	NUM
ijassa-1009	9	20	.	.	PUNCT
ijassa-1009	10	1	introduction	introduction	NOUN
ijassa-1009	10	2	covid’19	covid’19	PROPN
ijassa-1009	10	3	has	have	AUX
ijassa-1009	10	4	influenced	influence	VERB
ijassa-1009	10	5	many	many	ADJ
ijassa-1009	10	6	nations	nation	NOUN
ijassa-1009	10	7	in	in	ADP
ijassa-1009	10	8	a	a	DET
ijassa-1009	10	9	very	very	ADV
ijassa-1009	10	10	little	little	ADJ
ijassa-1009	10	11	amount	amount	NOUN
ijassa-1009	10	12	of	of	ADP
ijassa-1009	10	13	time	time	NOUN
ijassa-1009	10	14	.	.	PUNCT
ijassa-1009	11	1	the	the	DET
ijassa-1009	11	2	coronavirus	coronavirus	NOUN
ijassa-1009	11	3	has	have	AUX
ijassa-1009	11	4	given	give	VERB
ijassa-1009	11	5	a	a	DET
ijassa-1009	11	6	devastating	devastating	ADJ
ijassa-1009	11	7	blow	blow	NOUN
ijassa-1009	11	8	to	to	ADP
ijassa-1009	11	9	the	the	DET
ijassa-1009	11	10	entire	entire	ADJ
ijassa-1009	11	11	world	world	NOUN
ijassa-1009	11	12	which	which	PRON
ijassa-1009	11	13	is	be	AUX
ijassa-1009	11	14	detrimental	detrimental	ADJ
ijassa-1009	11	15	to	to	ADP
ijassa-1009	11	16	the	the	DET
ijassa-1009	11	17	health	health	NOUN
ijassa-1009	11	18	condition	condition	NOUN
ijassa-1009	11	19	of	of	ADP
ijassa-1009	11	20	many	many	ADJ
ijassa-1009	11	21	people	people	NOUN
ijassa-1009	11	22	and	and	CCONJ
ijassa-1009	11	23	continues	continue	VERB
ijassa-1009	11	24	to	to	PART
ijassa-1009	11	25	intimidate	intimidate	VERB
ijassa-1009	11	26	the	the	DET
ijassa-1009	11	27	world	world	NOUN
ijassa-1009	11	28	.	.	PUNCT
ijassa-1009	12	1	this	this	DET
ijassa-1009	12	2	newly	newly	ADV
ijassa-1009	12	3	identified	identify	VERB
ijassa-1009	12	4	virus	virus	NOUN
ijassa-1009	12	5	is	be	AUX
ijassa-1009	12	6	extremely	extremely	ADV
ijassa-1009	12	7	dangerous	dangerous	ADJ
ijassa-1009	12	8	and	and	CCONJ
ijassa-1009	12	9	pathogenetically	pathogenetically	ADV
ijassa-1009	12	10	different	different	ADJ
ijassa-1009	12	11	from	from	ADP
ijassa-1009	12	12	sars	sar	NOUN
ijassa-1009	12	13	-	-	PUNCT
ijassa-1009	12	14	cov	cov	NOUN
ijassa-1009	12	15	,	,	PUNCT
ijassa-1009	12	16	mers	mer	NOUN
ijassa-1009	12	17	-	-	PUNCT
ijassa-1009	12	18	cov	cov	NOUN
ijassa-1009	12	19	,	,	PUNCT
ijassa-1009	12	20	avian	avian	ADJ
ijassa-1009	12	21	influenza	influenza	NOUN
ijassa-1009	12	22	,	,	PUNCT
ijassa-1009	12	23	influenza	influenza	NOUN
ijassa-1009	12	24	,	,	PUNCT
ijassa-1009	12	25	and	and	CCONJ
ijassa-1009	12	26	other	other	ADJ
ijassa-1009	12	27	various	various	ADJ
ijassa-1009	12	28	common	common	ADJ
ijassa-1009	12	29	respiratory	respiratory	ADJ
ijassa-1009	12	30	viruses	virus	NOUN
ijassa-1009	12	31	[	[	X
ijassa-1009	12	32	1	1	NUM
ijassa-1009	12	33	]	]	PUNCT
ijassa-1009	12	34	.	.	PUNCT
ijassa-1009	13	1	although	although	SCONJ
ijassa-1009	13	2	the	the	DET
ijassa-1009	13	3	diagnosis	diagnosis	NOUN
ijassa-1009	13	4	process	process	NOUN
ijassa-1009	13	5	has	have	AUX
ijassa-1009	13	6	become	become	VERB
ijassa-1009	13	7	relatively	relatively	ADV
ijassa-1009	13	8	rapid	rapid	ADJ
ijassa-1009	13	9	,	,	PUNCT
ijassa-1009	13	10	the	the	DET
ijassa-1009	13	11	financial	financial	ADJ
ijassa-1009	13	12	issues	issue	NOUN
ijassa-1009	13	13	arising	arise	VERB
ijassa-1009	13	14	from	from	ADP
ijassa-1009	13	15	the	the	DET
ijassa-1009	13	16	cost	cost	NOUN
ijassa-1009	13	17	of	of	ADP
ijassa-1009	13	18	diagnostic	diagnostic	ADJ
ijassa-1009	13	19	tests	test	NOUN
ijassa-1009	13	20	affect	affect	VERB
ijassa-1009	13	21	both	both	CCONJ
ijassa-1009	13	22	the	the	DET
ijassa-1009	13	23	patients	patient	NOUN
ijassa-1009	13	24	as	as	ADV
ijassa-1009	13	25	well	well	ADV
ijassa-1009	13	26	as	as	ADP
ijassa-1009	13	27	the	the	DET
ijassa-1009	13	28	gdp	gdp	NOUN
ijassa-1009	13	29	of	of	ADP
ijassa-1009	13	30	the	the	DET
ijassa-1009	13	31	country	country	NOUN
ijassa-1009	13	32	,	,	PUNCT
ijassa-1009	13	33	particularly	particularly	ADV
ijassa-1009	13	34	in	in	ADP
ijassa-1009	13	35	countries	country	NOUN
ijassa-1009	13	36	with	with	ADP
ijassa-1009	13	37	private	private	ADJ
ijassa-1009	13	38	health	health	NOUN
ijassa-1009	13	39	systems	system	NOUN
ijassa-1009	13	40	,	,	PUNCT
ijassa-1009	13	41	or	or	CCONJ
ijassa-1009	13	42	restricted	restrict	VERB
ijassa-1009	13	43	access	access	NOUN
ijassa-1009	13	44	to	to	ADP
ijassa-1009	13	45	health	health	NOUN
ijassa-1009	13	46	systems	system	NOUN
ijassa-1009	13	47	.	.	PUNCT
ijassa-1009	14	1	so	so	ADV
ijassa-1009	14	2	far	far	ADV
ijassa-1009	14	3	,	,	PUNCT
ijassa-1009	14	4	due	due	ADP
ijassa-1009	14	5	to	to	ADP
ijassa-1009	14	6	the	the	DET
ijassa-1009	14	7	lack	lack	NOUN
ijassa-1009	14	8	of	of	ADP
ijassa-1009	14	9	availability	availability	NOUN
ijassa-1009	14	10	of	of	ADP
ijassa-1009	14	11	public	public	ADJ
ijassa-1009	14	12	images	image	NOUN
ijassa-1009	14	13	of	of	ADP
ijassa-1009	14	14	covid-19	covid-19	PROPN
ijassa-1009	14	15	patients	patient	NOUN
ijassa-1009	14	16	,	,	PUNCT
ijassa-1009	14	17	detailed	detailed	ADJ
ijassa-1009	14	18	studies	study	NOUN
ijassa-1009	14	19	reporting	report	VERB
ijassa-1009	14	20	solutions	solution	NOUN
ijassa-1009	14	21	for	for	ADP
ijassa-1009	14	22	automatic	automatic	ADJ
ijassa-1009	14	23	detection	detection	NOUN
ijassa-1009	14	24	of	of	ADP
ijassa-1009	14	25	covid-19	covid-19	PROPN
ijassa-1009	14	26	from	from	ADP
ijassa-1009	14	27	x	x	NOUN
ijassa-1009	14	28	-	-	NOUN
ijassa-1009	14	29	ray	ray	NOUN
ijassa-1009	14	30	(	(	PUNCT
ijassa-1009	14	31	or	or	CCONJ
ijassa-1009	14	32	chest	chest	NOUN
ijassa-1009	14	33	ct	ct	NUM
ijassa-1009	14	34	)	)	PUNCT
ijassa-1009	14	35	images	image	NOUN
ijassa-1009	14	36	are	be	AUX
ijassa-1009	14	37	not	not	PART
ijassa-1009	14	38	available	available	ADJ
ijassa-1009	14	39	[	[	X
ijassa-1009	14	40	2	2	NUM
ijassa-1009	14	41	]	]	PUNCT
ijassa-1009	14	42	.	.	PUNCT
ijassa-1009	15	1	medical	medical	ADJ
ijassa-1009	15	2	predictions	prediction	NOUN
ijassa-1009	15	3	are	be	AUX
ijassa-1009	15	4	not	not	PART
ijassa-1009	15	5	accurate	accurate	ADJ
ijassa-1009	15	6	a	a	DET
ijassa-1009	15	7	lot	lot	NOUN
ijassa-1009	15	8	of	of	ADP
ijassa-1009	15	9	times	time	NOUN
ijassa-1009	15	10	and	and	CCONJ
ijassa-1009	15	11	their	their	PRON
ijassa-1009	15	12	uncertainty	uncertainty	NOUN
ijassa-1009	15	13	always	always	ADV
ijassa-1009	15	14	has	have	AUX
ijassa-1009	15	15	been	be	AUX
ijassa-1009	15	16	seriously	seriously	ADV
ijassa-1009	15	17	underestimated	underestimate	VERB
ijassa-1009	15	18	[	[	X
ijassa-1009	15	19	3	3	NUM
ijassa-1009	15	20	]	]	PUNCT
ijassa-1009	15	21	.	.	PUNCT
ijassa-1009	16	1	in	in	ADP
ijassa-1009	16	2	march	march	PROPN
ijassa-1009	16	3	2020	2020	NUM
ijassa-1009	16	4	,	,	PUNCT
ijassa-1009	16	5	there	there	PRON
ijassa-1009	16	6	has	have	AUX
ijassa-1009	16	7	been	be	AUX
ijassa-1009	16	8	an	an	DET
ijassa-1009	16	9	enormous	enormous	ADJ
ijassa-1009	16	10	increase	increase	NOUN
ijassa-1009	16	11	in	in	ADP
ijassa-1009	16	12	covid	covid	PROPN
ijassa-1009	16	13	cases	case	NOUN
ijassa-1009	16	14	which	which	PRON
ijassa-1009	16	15	consequently	consequently	ADV
ijassa-1009	16	16	,	,	PUNCT
ijassa-1009	16	17	lead	lead	VERB
ijassa-1009	16	18	to	to	ADP
ijassa-1009	16	19	a	a	DET
ijassa-1009	16	20	rapid	rapid	ADJ
ijassa-1009	16	21	increase	increase	NOUN
ijassa-1009	16	22	in	in	ADP
ijassa-1009	16	23	the	the	DET
ijassa-1009	16	24	x	x	NOUN
ijassa-1009	16	25	-	-	NOUN
ijassa-1009	16	26	ray	ray	NOUN
ijassa-1009	16	27	dataset	dataset	NOUN
ijassa-1009	16	28	.	.	PUNCT
ijassa-1009	17	1	this	this	PRON
ijassa-1009	17	2	helps	help	VERB
ijassa-1009	17	3	us	we	PRON
ijassa-1009	17	4	*	*	PUNCT
ijassa-1009	17	5	corresponding	correspond	VERB
ijassa-1009	17	6	author	author	NOUN
ijassa-1009	17	7	:	:	PUNCT
ijassa-1009	17	8	alampallynaveen123@gmail.com	alampallynaveen123@gmail.com	X
ijassa-1009	17	9	deep	deep	ADJ
ijassa-1009	17	10	learning	learning	NOUN
ijassa-1009	17	11	techniques	technique	NOUN
ijassa-1009	17	12	for	for	ADP
ijassa-1009	17	13	detection	detection	NOUN
ijassa-1009	17	14	of	of	ADP
ijassa-1009	17	15	covid-19	covid-19	PROPN
ijassa-1009	17	16	43	43	NUM
ijassa-1009	17	17	copyright	copyright	NOUN
ijassa-1009	17	18	©	©	PROPN
ijassa-1009	17	19	2021	2021	NUM
ijassa-1009	17	20	assa	assa	NOUN
ijassa-1009	17	21	.	.	PUNCT
ijassa-1009	18	1	adv	adv	PROPN
ijassa-1009	18	2	.	.	PUNCT
ijassa-1009	19	1	in	in	ADP
ijassa-1009	19	2	systems	system	NOUN
ijassa-1009	19	3	science	science	NOUN
ijassa-1009	19	4	and	and	CCONJ
ijassa-1009	19	5	appl	appl	NOUN
ijassa-1009	19	6	.	.	PUNCT
ijassa-1009	20	1	(	(	PUNCT
ijassa-1009	20	2	2021	2021	NUM
ijassa-1009	20	3	)	)	PUNCT
ijassa-1009	21	1	to	to	PART
ijassa-1009	21	2	analyze	analyze	VERB
ijassa-1009	21	3	the	the	DET
ijassa-1009	21	4	medical	medical	ADJ
ijassa-1009	21	5	images	image	NOUN
ijassa-1009	21	6	and	and	CCONJ
ijassa-1009	21	7	recognize	recognize	VERB
ijassa-1009	21	8	potential	potential	ADJ
ijassa-1009	21	9	trends	trend	NOUN
ijassa-1009	21	10	that	that	PRON
ijassa-1009	21	11	help	help	VERB
ijassa-1009	21	12	in	in	ADP
ijassa-1009	21	13	the	the	DET
ijassa-1009	21	14	automatic	automatic	ADJ
ijassa-1009	21	15	diagnosis	diagnosis	NOUN
ijassa-1009	21	16	.	.	PUNCT
ijassa-1009	22	1	the	the	DET
ijassa-1009	22	2	automated	automate	VERB
ijassa-1009	22	3	and	and	CCONJ
ijassa-1009	22	4	early	early	ADJ
ijassa-1009	22	5	covid-19	covid-19	PROPN
ijassa-1009	22	6	diagnosis	diagnosis	NOUN
ijassa-1009	22	7	can	can	AUX
ijassa-1009	22	8	be	be	AUX
ijassa-1009	22	9	helpful	helpful	ADJ
ijassa-1009	22	10	for	for	SCONJ
ijassa-1009	22	11	the	the	DET
ijassa-1009	22	12	countries	country	NOUN
ijassa-1009	22	13	to	to	PART
ijassa-1009	22	14	immediately	immediately	ADV
ijassa-1009	22	15	refer	refer	VERB
ijassa-1009	22	16	the	the	DET
ijassa-1009	22	17	patient	patient	NOUN
ijassa-1009	22	18	to	to	ADP
ijassa-1009	22	19	quarantine	quarantine	NOUN
ijassa-1009	22	20	,	,	PUNCT
ijassa-1009	22	21	rapid	rapid	ADJ
ijassa-1009	22	22	intubation	intubation	NOUN
ijassa-1009	22	23	,	,	PUNCT
ijassa-1009	22	24	or	or	CCONJ
ijassa-1009	22	25	severe	severe	ADJ
ijassa-1009	22	26	cases	case	NOUN
ijassa-1009	22	27	in	in	ADP
ijassa-1009	22	28	specialist	specialist	ADJ
ijassa-1009	22	29	hospitals	hospital	NOUN
ijassa-1009	22	30	,	,	PUNCT
ijassa-1009	22	31	and	and	CCONJ
ijassa-1009	22	32	control	control	VERB
ijassa-1009	22	33	the	the	DET
ijassa-1009	22	34	spread	spread	NOUN
ijassa-1009	22	35	of	of	ADP
ijassa-1009	22	36	the	the	DET
ijassa-1009	22	37	disease	disease	NOUN
ijassa-1009	22	38	.	.	PUNCT
ijassa-1009	23	1	the	the	DET
ijassa-1009	23	2	model	model	NOUN
ijassa-1009	23	3	can	can	AUX
ijassa-1009	23	4	detect	detect	VERB
ijassa-1009	23	5	the	the	DET
ijassa-1009	23	6	covid	covid	NOUN
ijassa-1009	23	7	from	from	ADP
ijassa-1009	23	8	x	x	NOUN
ijassa-1009	23	9	-	-	NOUN
ijassa-1009	23	10	ray	ray	NOUN
ijassa-1009	23	11	images	image	NOUN
ijassa-1009	23	12	or	or	CCONJ
ijassa-1009	23	13	ct	ct	NUM
ijassa-1009	23	14	images	image	NOUN
ijassa-1009	23	15	using	use	VERB
ijassa-1009	23	16	image	image	NOUN
ijassa-1009	23	17	classification	classification	NOUN
ijassa-1009	23	18	with	with	ADP
ijassa-1009	23	19	the	the	DET
ijassa-1009	23	20	help	help	NOUN
ijassa-1009	23	21	of	of	ADP
ijassa-1009	23	22	various	various	ADJ
ijassa-1009	23	23	deep	deep	ADJ
ijassa-1009	23	24	learning	learning	NOUN
ijassa-1009	23	25	techniques	technique	NOUN
ijassa-1009	23	26	[	[	X
ijassa-1009	23	27	4	4	NUM
ijassa-1009	23	28	]	]	PUNCT
ijassa-1009	23	29	.	.	PUNCT
ijassa-1009	24	1	due	due	ADP
ijassa-1009	24	2	to	to	ADP
ijassa-1009	24	3	a	a	DET
ijassa-1009	24	4	gradual	gradual	ADJ
ijassa-1009	24	5	increase	increase	NOUN
ijassa-1009	24	6	in	in	ADP
ijassa-1009	24	7	cases	case	NOUN
ijassa-1009	24	8	,	,	PUNCT
ijassa-1009	24	9	the	the	DET
ijassa-1009	24	10	testing	testing	NOUN
ijassa-1009	24	11	of	of	ADP
ijassa-1009	24	12	covid	covid	PROPN
ijassa-1009	24	13	has	have	AUX
ijassa-1009	24	14	become	become	VERB
ijassa-1009	24	15	the	the	DET
ijassa-1009	24	16	most	most	ADV
ijassa-1009	24	17	difficult	difficult	ADJ
ijassa-1009	24	18	situation	situation	NOUN
ijassa-1009	24	19	and	and	CCONJ
ijassa-1009	24	20	it	it	PRON
ijassa-1009	24	21	also	also	ADV
ijassa-1009	24	22	takes	take	VERB
ijassa-1009	24	23	more	more	ADJ
ijassa-1009	24	24	time	time	NOUN
ijassa-1009	24	25	.	.	PUNCT
ijassa-1009	25	1	to	to	PART
ijassa-1009	25	2	overcome	overcome	VERB
ijassa-1009	25	3	this	this	DET
ijassa-1009	25	4	situation	situation	NOUN
ijassa-1009	25	5	,	,	PUNCT
ijassa-1009	25	6	a	a	DET
ijassa-1009	25	7	model	model	NOUN
ijassa-1009	25	8	is	be	AUX
ijassa-1009	25	9	designed	design	VERB
ijassa-1009	25	10	,	,	PUNCT
ijassa-1009	25	11	by	by	ADP
ijassa-1009	25	12	which	which	PRON
ijassa-1009	25	13	the	the	DET
ijassa-1009	25	14	coronavirus	coronavirus	NOUN
ijassa-1009	25	15	can	can	AUX
ijassa-1009	25	16	easily	easily	ADV
ijassa-1009	25	17	be	be	AUX
ijassa-1009	25	18	predicted	predict	VERB
ijassa-1009	25	19	with	with	ADP
ijassa-1009	25	20	the	the	DET
ijassa-1009	25	21	most	most	ADV
ijassa-1009	25	22	appropriate	appropriate	ADJ
ijassa-1009	25	23	deep	deep	ADJ
ijassa-1009	25	24	learning	learning	NOUN
ijassa-1009	25	25	techniques	technique	NOUN
ijassa-1009	25	26	which	which	PRON
ijassa-1009	25	27	have	have	VERB
ijassa-1009	25	28	the	the	DET
ijassa-1009	25	29	highest	high	ADJ
ijassa-1009	25	30	accuracy	accuracy	NOUN
ijassa-1009	25	31	.	.	PUNCT
ijassa-1009	26	1	the	the	DET
ijassa-1009	26	2	effectiveness	effectiveness	NOUN
ijassa-1009	26	3	of	of	ADP
ijassa-1009	26	4	the	the	DET
ijassa-1009	26	5	deep	deep	ADJ
ijassa-1009	26	6	learning	learning	NOUN
ijassa-1009	26	7	technique	technique	NOUN
ijassa-1009	26	8	proposed	propose	VERB
ijassa-1009	26	9	is	be	AUX
ijassa-1009	26	10	pre	pre	ADJ
ijassa-1009	26	11	-	-	VERB
ijassa-1009	26	12	trained	train	VERB
ijassa-1009	26	13	fully	fully	ADV
ijassa-1009	26	14	convolutional	convolutional	ADJ
ijassa-1009	26	15	neural	neural	ADJ
ijassa-1009	26	16	networks	network	NOUN
ijassa-1009	26	17	with	with	ADP
ijassa-1009	26	18	regard	regard	NOUN
ijassa-1009	26	19	to	to	ADP
ijassa-1009	26	20	their	their	PRON
ijassa-1009	26	21	expertise	expertise	NOUN
ijassa-1009	26	22	in	in	ADP
ijassa-1009	26	23	the	the	DET
ijassa-1009	26	24	automatic	automatic	ADJ
ijassa-1009	26	25	diagnosis	diagnosis	NOUN
ijassa-1009	26	26	of	of	ADP
ijassa-1009	26	27	covid-19	covid-19	PROPN
ijassa-1009	26	28	from	from	ADP
ijassa-1009	26	29	thoracic	thoracic	NOUN
ijassa-1009	26	30	x	x	NOUN
ijassa-1009	26	31	-	-	NOUN
ijassa-1009	26	32	rays	ray	NOUN
ijassa-1009	26	33	.	.	PUNCT
ijassa-1009	27	1	the	the	DET
ijassa-1009	27	2	use	use	NOUN
ijassa-1009	27	3	of	of	ADP
ijassa-1009	27	4	machine	machine	NOUN
ijassa-1009	27	5	learning	learn	VERB
ijassa-1009	27	6	techniques	technique	NOUN
ijassa-1009	27	7	for	for	ADP
ijassa-1009	27	8	automated	automate	VERB
ijassa-1009	27	9	medical	medical	ADJ
ijassa-1009	27	10	diagnosis	diagnosis	NOUN
ijassa-1009	27	11	has	have	AUX
ijassa-1009	27	12	recently	recently	ADV
ijassa-1009	27	13	gained	gain	VERB
ijassa-1009	27	14	prominence	prominence	NOUN
ijassa-1009	27	15	by	by	ADP
ijassa-1009	27	16	being	be	AUX
ijassa-1009	27	17	an	an	DET
ijassa-1009	27	18	adjunct	adjunct	ADJ
ijassa-1009	27	19	method	method	NOUN
ijassa-1009	27	20	for	for	ADP
ijassa-1009	27	21	clinicians	clinician	NOUN
ijassa-1009	27	22	[	[	X
ijassa-1009	27	23	5	5	NUM
ijassa-1009	27	24	]	]	PUNCT
ijassa-1009	27	25	.	.	PUNCT
ijassa-1009	28	1	researchers	researcher	NOUN
ijassa-1009	28	2	are	be	AUX
ijassa-1009	28	3	increasingly	increasingly	ADV
ijassa-1009	28	4	applying	apply	VERB
ijassa-1009	28	5	the	the	DET
ijassa-1009	28	6	recent	recent	ADJ
ijassa-1009	28	7	advancements	advancement	NOUN
ijassa-1009	28	8	of	of	ADP
ijassa-1009	28	9	deep	deep	ADJ
ijassa-1009	28	10	learning	learning	NOUN
ijassa-1009	28	11	to	to	ADP
ijassa-1009	28	12	the	the	DET
ijassa-1009	28	13	analysis	analysis	NOUN
ijassa-1009	28	14	of	of	ADP
ijassa-1009	28	15	chest	chest	NOUN
ijassa-1009	28	16	x	x	NOUN
ijassa-1009	28	17	-	-	NOUN
ijassa-1009	28	18	ray	ray	NOUN
ijassa-1009	28	19	images	image	NOUN
ijassa-1009	28	20	to	to	PART
ijassa-1009	28	21	increase	increase	VERB
ijassa-1009	28	22	performance	performance	NOUN
ijassa-1009	28	23	and	and	CCONJ
ijassa-1009	28	24	relieve	relieve	VERB
ijassa-1009	28	25	the	the	DET
ijassa-1009	28	26	burden	burden	NOUN
ijassa-1009	28	27	of	of	ADP
ijassa-1009	28	28	radiologists	radiologist	NOUN
ijassa-1009	28	29	.	.	PUNCT
ijassa-1009	29	1	deep	deep	ADJ
ijassa-1009	29	2	learning	learning	NOUN
ijassa-1009	29	3	,	,	PUNCT
ijassa-1009	29	4	allows	allow	VERB
ijassa-1009	29	5	end	end	NOUN
ijassa-1009	29	6	-	-	PUNCT
ijassa-1009	29	7	toend	toend	NOUN
ijassa-1009	29	8	models	model	NOUN
ijassa-1009	29	9	to	to	PART
ijassa-1009	29	10	be	be	AUX
ijassa-1009	29	11	built	build	VERB
ijassa-1009	29	12	to	to	PART
ijassa-1009	29	13	achieve	achieve	VERB
ijassa-1009	29	14	promised	promise	VERB
ijassa-1009	29	15	results	result	NOUN
ijassa-1009	29	16	using	use	VERB
ijassa-1009	29	17	input	input	NOUN
ijassa-1009	29	18	data	datum	NOUN
ijassa-1009	29	19	without	without	ADP
ijassa-1009	29	20	the	the	DET
ijassa-1009	29	21	need	need	NOUN
ijassa-1009	29	22	for	for	ADP
ijassa-1009	29	23	manual	manual	ADJ
ijassa-1009	29	24	extraction	extraction	NOUN
ijassa-1009	29	25	of	of	ADP
ijassa-1009	29	26	features	feature	NOUN
ijassa-1009	29	27	.	.	PUNCT
ijassa-1009	30	1	the	the	DET
ijassa-1009	30	2	rapid	rapid	ADJ
ijassa-1009	30	3	rise	rise	NOUN
ijassa-1009	30	4	of	of	ADP
ijassa-1009	30	5	the	the	DET
ijassa-1009	30	6	covid-19	covid-19	PROPN
ijassa-1009	30	7	epidemic	epidemic	NOUN
ijassa-1009	30	8	has	have	AUX
ijassa-1009	30	9	required	require	VERB
ijassa-1009	30	10	the	the	DET
ijassa-1009	30	11	need	need	NOUN
ijassa-1009	30	12	for	for	ADP
ijassa-1009	30	13	expertise	expertise	NOUN
ijassa-1009	30	14	in	in	ADP
ijassa-1009	30	15	this	this	DET
ijassa-1009	30	16	field	field	NOUN
ijassa-1009	30	17	.	.	PUNCT
ijassa-1009	31	1	the	the	DET
ijassa-1009	31	2	interest	interest	NOUN
ijassa-1009	31	3	in	in	ADP
ijassa-1009	31	4	designing	design	VERB
ijassa-1009	31	5	automated	automate	VERB
ijassa-1009	31	6	detection	detection	NOUN
ijassa-1009	31	7	systems	system	NOUN
ijassa-1009	31	8	based	base	VERB
ijassa-1009	31	9	on	on	ADP
ijassa-1009	31	10	machine	machine	NOUN
ijassa-1009	31	11	learning	learning	NOUN
ijassa-1009	31	12	techniques	technique	NOUN
ijassa-1009	31	13	has	have	AUX
ijassa-1009	31	14	increased	increase	VERB
ijassa-1009	31	15	.	.	PUNCT
ijassa-1009	32	1	a	a	DET
ijassa-1009	32	2	weakly	weakly	ADV
ijassa-1009	32	3	-	-	PUNCT
ijassa-1009	32	4	supervised	supervise	VERB
ijassa-1009	32	5	classification	classification	NOUN
ijassa-1009	32	6	and	and	CCONJ
ijassa-1009	32	7	localization	localization	NOUN
ijassa-1009	32	8	system	system	NOUN
ijassa-1009	32	9	proposed	propose	VERB
ijassa-1009	32	10	for	for	ADP
ijassa-1009	32	11	the	the	DET
ijassa-1009	32	12	computer	computer	NOUN
ijassa-1009	32	13	-	-	PUNCT
ijassa-1009	32	14	aided	aid	VERB
ijassa-1009	32	15	diagnosis	diagnosis	NOUN
ijassa-1009	32	16	of	of	ADP
ijassa-1009	32	17	common	common	ADJ
ijassa-1009	32	18	thoracic	thoracic	NOUN
ijassa-1009	32	19	diseases	disease	NOUN
ijassa-1009	32	20	developed	develop	VERB
ijassa-1009	32	21	121	121	NUM
ijassa-1009	32	22	-	-	PUNCT
ijassa-1009	32	23	layer	layer	NOUN
ijassa-1009	32	24	dense	dense	ADJ
ijassa-1009	32	25	convolutional	convolutional	ADJ
ijassa-1009	32	26	neural	neural	ADJ
ijassa-1009	32	27	networks	network	NOUN
ijassa-1009	32	28	[	[	X
ijassa-1009	32	29	6	6	NUM
ijassa-1009	32	30	]	]	PUNCT
ijassa-1009	32	31	.	.	PUNCT
ijassa-1009	33	1	for	for	ADP
ijassa-1009	33	2	many	many	ADJ
ijassa-1009	33	3	image	image	NOUN
ijassa-1009	33	4	processing	processing	NOUN
ijassa-1009	33	5	applications	application	NOUN
ijassa-1009	33	6	,	,	PUNCT
ijassa-1009	33	7	such	such	ADJ
ijassa-1009	33	8	as	as	ADP
ijassa-1009	33	9	image	image	NOUN
ijassa-1009	33	10	analysis	analysis	NOUN
ijassa-1009	33	11	,	,	PUNCT
ijassa-1009	33	12	image	image	NOUN
ijassa-1009	33	13	classification	classification	NOUN
ijassa-1009	33	14	,	,	PUNCT
ijassa-1009	33	15	and	and	CCONJ
ijassa-1009	33	16	image	image	NOUN
ijassa-1009	33	17	segmentation	segmentation	NOUN
ijassa-1009	33	18	,	,	PUNCT
ijassa-1009	33	19	deep	deep	ADJ
ijassa-1009	33	20	learning	learning	NOUN
ijassa-1009	33	21	techniques	technique	NOUN
ijassa-1009	33	22	have	have	AUX
ijassa-1009	33	23	demonstrated	demonstrate	VERB
ijassa-1009	33	24	high	high	ADJ
ijassa-1009	33	25	efficiency	efficiency	NOUN
ijassa-1009	33	26	.	.	PUNCT
ijassa-1009	34	1	image	image	NOUN
ijassa-1009	34	2	classification	classification	NOUN
ijassa-1009	34	3	is	be	AUX
ijassa-1009	34	4	achieved	achieve	VERB
ijassa-1009	34	5	through	through	ADP
ijassa-1009	34	6	a	a	DET
ijassa-1009	34	7	descriptor	descriptor	NOUN
ijassa-1009	34	8	extracting	extract	VERB
ijassa-1009	34	9	the	the	DET
ijassa-1009	34	10	import	import	NOUN
ijassa-1009	34	11	features	feature	NOUN
ijassa-1009	34	12	from	from	ADP
ijassa-1009	34	13	the	the	DET
ijassa-1009	34	14	images	image	NOUN
ijassa-1009	34	15	,	,	PUNCT
ijassa-1009	34	16	and	and	CCONJ
ijassa-1009	34	17	then	then	ADV
ijassa-1009	34	18	these	these	DET
ijassa-1009	34	19	features	feature	NOUN
ijassa-1009	34	20	can	can	AUX
ijassa-1009	34	21	be	be	AUX
ijassa-1009	34	22	used	use	VERB
ijassa-1009	34	23	using	use	VERB
ijassa-1009	34	24	classifiers	classifier	NOUN
ijassa-1009	34	25	in	in	ADP
ijassa-1009	34	26	the	the	DET
ijassa-1009	34	27	classification	classification	NOUN
ijassa-1009	34	28	task	task	NOUN
ijassa-1009	34	29	.	.	PUNCT
ijassa-1009	35	1	in	in	ADP
ijassa-1009	35	2	this	this	DET
ijassa-1009	35	3	research	research	NOUN
ijassa-1009	35	4	work	work	NOUN
ijassa-1009	35	5	,	,	PUNCT
ijassa-1009	35	6	four	four	NUM
ijassa-1009	35	7	major	major	ADJ
ijassa-1009	35	8	convolution	convolution	NOUN
ijassa-1009	35	9	neural	neural	ADJ
ijassa-1009	35	10	networks	network	NOUN
ijassa-1009	35	11	namely	namely	ADV
ijassa-1009	35	12	resnet50	resnet50	VERB
ijassa-1009	35	13	,	,	PUNCT
ijassa-1009	35	14	vgg16	vgg16	PROPN
ijassa-1009	35	15	,	,	PUNCT
ijassa-1009	35	16	inceptionv3	inceptionv3	PROPN
ijassa-1009	35	17	,	,	PUNCT
ijassa-1009	35	18	xception	xception	PROPN
ijassa-1009	35	19	are	be	AUX
ijassa-1009	35	20	used	use	VERB
ijassa-1009	35	21	for	for	ADP
ijassa-1009	35	22	evaluating	evaluate	VERB
ijassa-1009	35	23	the	the	DET
ijassa-1009	35	24	performance	performance	NOUN
ijassa-1009	35	25	against	against	ADP
ijassa-1009	35	26	coronaviruses	coronaviruse	NOUN
ijassa-1009	35	27	detection	detection	NOUN
ijassa-1009	35	28	.	.	PUNCT
ijassa-1009	36	1	2	2	X
ijassa-1009	36	2	.	.	X
ijassa-1009	36	3	literature	literature	NOUN
ijassa-1009	36	4	survey	survey	PROPN
ijassa-1009	36	5	covid	covid	PROPN
ijassa-1009	36	6	is	be	AUX
ijassa-1009	36	7	one	one	NUM
ijassa-1009	36	8	of	of	ADP
ijassa-1009	36	9	the	the	DET
ijassa-1009	36	10	major	major	ADJ
ijassa-1009	36	11	causes	cause	NOUN
ijassa-1009	36	12	of	of	ADP
ijassa-1009	36	13	death	death	NOUN
ijassa-1009	36	14	nowadays	nowadays	ADV
ijassa-1009	36	15	.	.	PUNCT
ijassa-1009	37	1	ali	ali	PROPN
ijassa-1009	37	2	et	et	PROPN
ijassa-1009	37	3	al	al	PROPN
ijassa-1009	37	4	.	.	PUNCT
ijassa-1009	38	1	[	[	X
ijassa-1009	38	2	7	7	X
ijassa-1009	38	3	]	]	PUNCT
ijassa-1009	38	4	had	have	AUX
ijassa-1009	38	5	proposed	propose	VERB
ijassa-1009	38	6	a	a	DET
ijassa-1009	38	7	deep	deep	ADJ
ijassa-1009	38	8	transfer	transfer	NOUN
ijassa-1009	38	9	learning	learn	VERB
ijassa-1009	38	10	technique	technique	NOUN
ijassa-1009	38	11	-	-	PUNCT
ijassa-1009	38	12	based	base	VERB
ijassa-1009	38	13	approach	approach	NOUN
ijassa-1009	38	14	for	for	ADP
ijassa-1009	38	15	covid-19	covid-19	PROPN
ijassa-1009	38	16	detection	detection	NOUN
ijassa-1009	38	17	using	use	VERB
ijassa-1009	38	18	chest	chest	NOUN
ijassa-1009	38	19	x	x	NOUN
ijassa-1009	38	20	-	-	NOUN
ijassa-1009	38	21	ray	ray	NOUN
ijassa-1009	38	22	images	image	NOUN
ijassa-1009	38	23	.	.	PUNCT
ijassa-1009	39	1	they	they	PRON
ijassa-1009	39	2	have	have	AUX
ijassa-1009	39	3	classified	classify	VERB
ijassa-1009	39	4	the	the	DET
ijassa-1009	39	5	images	image	NOUN
ijassa-1009	39	6	from	from	ADP
ijassa-1009	39	7	the	the	DET
ijassa-1009	39	8	three	three	NUM
ijassa-1009	39	9	datasets	dataset	NOUN
ijassa-1009	39	10	used	use	VERB
ijassa-1009	39	11	for	for	ADP
ijassa-1009	39	12	implementation	implementation	NOUN
ijassa-1009	39	13	into	into	ADP
ijassa-1009	39	14	four	four	NUM
ijassa-1009	39	15	classes	class	NOUN
ijassa-1009	39	16	namely	namely	ADV
ijassa-1009	39	17	covid-19	covid-19	PROPN
ijassa-1009	39	18	,	,	PUNCT
ijassa-1009	39	19	normal	normal	ADJ
ijassa-1009	39	20	(	(	PUNCT
ijassa-1009	39	21	healthy	healthy	ADJ
ijassa-1009	39	22	)	)	PUNCT
ijassa-1009	39	23	,	,	PUNCT
ijassa-1009	39	24	viral	viral	ADJ
ijassa-1009	39	25	pneumonia	pneumonia	NOUN
ijassa-1009	39	26	,	,	PUNCT
ijassa-1009	39	27	and	and	CCONJ
ijassa-1009	39	28	bacterial	bacterial	ADJ
ijassa-1009	39	29	pneumonia	pneumonia	NOUN
ijassa-1009	39	30	.	.	PUNCT
ijassa-1009	40	1	five	five	NUM
ijassa-1009	40	2	pre	pre	ADJ
ijassa-1009	40	3	-	-	ADJ
ijassa-1009	40	4	trained	train	VERB
ijassa-1009	40	5	convolutional	convolutional	ADJ
ijassa-1009	40	6	neural	neural	ADJ
ijassa-1009	40	7	network	network	NOUN
ijassa-1009	40	8	models	model	NOUN
ijassa-1009	40	9	were	be	AUX
ijassa-1009	40	10	used	use	VERB
ijassa-1009	40	11	in	in	ADP
ijassa-1009	40	12	this	this	DET
ijassa-1009	40	13	study	study	NOUN
ijassa-1009	40	14	–	–	PUNCT
ijassa-1009	40	15	resnet50	resnet50	NOUN
ijassa-1009	40	16	,	,	PUNCT
ijassa-1009	40	17	resnet101	resnet101	PROPN
ijassa-1009	40	18	,	,	PUNCT
ijassa-1009	40	19	resnet152	resnet152	PROPN
ijassa-1009	40	20	,	,	PUNCT
ijassa-1009	40	21	inceptionv3	inceptionv3	NOUN
ijassa-1009	40	22	and	and	CCONJ
ijassa-1009	40	23	inception	inception	NOUN
ijassa-1009	40	24	-	-	PUNCT
ijassa-1009	40	25	resnetv2	resnetv2	NOUN
ijassa-1009	40	26	.	.	PUNCT
ijassa-1009	41	1	the	the	DET
ijassa-1009	41	2	performance	performance	NOUN
ijassa-1009	41	3	analysis	analysis	NOUN
ijassa-1009	41	4	showed	show	VERB
ijassa-1009	41	5	that	that	SCONJ
ijassa-1009	41	6	the	the	DET
ijassa-1009	41	7	resnet50	resnet50	NOUN
ijassa-1009	41	8	convolutional	convolutional	ADJ
ijassa-1009	41	9	neural	neural	ADJ
ijassa-1009	41	10	network	network	NOUN
ijassa-1009	41	11	model	model	NOUN
ijassa-1009	41	12	showed	show	VERB
ijassa-1009	41	13	the	the	DET
ijassa-1009	41	14	highest	high	ADJ
ijassa-1009	41	15	accuracy	accuracy	NOUN
ijassa-1009	41	16	in	in	ADP
ijassa-1009	41	17	all	all	DET
ijassa-1009	41	18	the	the	DET
ijassa-1009	41	19	three	three	NUM
ijassa-1009	41	20	datasets	dataset	NOUN
ijassa-1009	41	21	.	.	PUNCT
ijassa-1009	42	1	a	a	DET
ijassa-1009	42	2	deep	deep	ADJ
ijassa-1009	42	3	convolutional	convolutional	ADJ
ijassa-1009	42	4	neural	neural	ADJ
ijassa-1009	42	5	network	network	NOUN
ijassa-1009	42	6	design	design	NOUN
ijassa-1009	42	7	for	for	ADP
ijassa-1009	42	8	the	the	DET
ijassa-1009	42	9	detection	detection	NOUN
ijassa-1009	42	10	of	of	ADP
ijassa-1009	42	11	coronavirus	coronavirus	NOUN
ijassa-1009	42	12	cases	case	NOUN
ijassa-1009	42	13	in	in	ADP
ijassa-1009	42	14	humans	human	NOUN
ijassa-1009	42	15	from	from	ADP
ijassa-1009	42	16	chest	chest	NOUN
ijassa-1009	42	17	x	x	NOUN
ijassa-1009	42	18	-	-	NOUN
ijassa-1009	42	19	ray	ray	NOUN
ijassa-1009	42	20	(	(	PUNCT
ijassa-1009	42	21	cxr	cxr	NOUN
ijassa-1009	42	22	)	)	PUNCT
ijassa-1009	42	23	images	image	NOUN
ijassa-1009	42	24	is	be	AUX
ijassa-1009	42	25	called	call	VERB
ijassa-1009	42	26	covid	covid	NOUN
ijassa-1009	42	27	-	-	PUNCT
ijassa-1009	42	28	net	net	NOUN
ijassa-1009	42	29	with	with	ADP
ijassa-1009	42	30	the	the	DET
ijassa-1009	42	31	help	help	NOUN
ijassa-1009	42	32	of	of	ADP
ijassa-1009	42	33	an	an	DET
ijassa-1009	42	34	opensource	opensource	NOUN
ijassa-1009	42	35	,	,	PUNCT
ijassa-1009	42	36	available	available	ADJ
ijassa-1009	42	37	to	to	ADP
ijassa-1009	42	38	the	the	DET
ijassa-1009	42	39	general	general	ADJ
ijassa-1009	42	40	public	public	NOUN
ijassa-1009	42	41	covid-19	covid-19	PROPN
ijassa-1009	42	42	dataset	dataset	NOUN
ijassa-1009	42	43	.	.	PUNCT
ijassa-1009	43	1	through	through	ADP
ijassa-1009	43	2	this	this	DET
ijassa-1009	43	3	method	method	NOUN
ijassa-1009	43	4	,	,	PUNCT
ijassa-1009	43	5	they	they	PRON
ijassa-1009	43	6	gained	gain	VERB
ijassa-1009	43	7	deeper	deep	ADJ
ijassa-1009	43	8	insights	insight	NOUN
ijassa-1009	43	9	into	into	ADP
ijassa-1009	43	10	critical	critical	ADJ
ijassa-1009	43	11	factors	factor	NOUN
ijassa-1009	43	12	that	that	PRON
ijassa-1009	43	13	are	be	AUX
ijassa-1009	43	14	related	relate	VERB
ijassa-1009	43	15	to	to	ADP
ijassa-1009	43	16	the	the	DET
ijassa-1009	43	17	covid-19	covid-19	PROPN
ijassa-1009	43	18	cases	case	NOUN
ijassa-1009	43	19	,	,	PUNCT
ijassa-1009	43	20	which	which	PRON
ijassa-1009	43	21	helped	help	VERB
ijassa-1009	43	22	doctors	doctor	NOUN
ijassa-1009	43	23	with	with	ADP
ijassa-1009	43	24	an	an	DET
ijassa-1009	43	25	improvement	improvement	NOUN
ijassa-1009	43	26	in	in	ADP
ijassa-1009	43	27	screening	screen	VERB
ijassa-1009	43	28	.	.	PUNCT
ijassa-1009	44	1	the	the	DET
ijassa-1009	44	2	obtained	obtain	VERB
ijassa-1009	44	3	model	model	NOUN
ijassa-1009	44	4	is	be	AUX
ijassa-1009	44	5	a	a	DET
ijassa-1009	44	6	successful	successful	ADJ
ijassa-1009	44	7	one	one	NOUN
ijassa-1009	44	8	as	as	SCONJ
ijassa-1009	44	9	it	it	PRON
ijassa-1009	44	10	has	have	VERB
ijassa-1009	44	11	a	a	DET
ijassa-1009	44	12	success	success	NOUN
ijassa-1009	44	13	ratio	ratio	NOUN
ijassa-1009	44	14	of	of	ADP
ijassa-1009	44	15	95.9	95.9	NUM
ijassa-1009	44	16	%	%	NOUN
ijassa-1009	44	17	in	in	ADP
ijassa-1009	44	18	detecting	detect	VERB
ijassa-1009	44	19	the	the	DET
ijassa-1009	44	20	covid-19	covid-19	PROPN
ijassa-1009	44	21	virus	virus	NOUN
ijassa-1009	44	22	and	and	CCONJ
ijassa-1009	44	23	it	it	PRON
ijassa-1009	44	24	can	can	AUX
ijassa-1009	44	25	also	also	ADV
ijassa-1009	44	26	identify	identify	VERB
ijassa-1009	44	27	non	non	ADJ
ijassa-1009	44	28	-	-	ADJ
ijassa-1009	44	29	covid	covid	ADJ
ijassa-1009	44	30	accurately	accurately	ADV
ijassa-1009	44	31	from	from	ADP
ijassa-1009	44	32	a	a	DET
ijassa-1009	44	33	person	person	NOUN
ijassa-1009	44	34	's	's	PART
ijassa-1009	44	35	chest	chest	NOUN
ijassa-1009	44	36	x	x	NOUN
ijassa-1009	44	37	-	-	NOUN
ijassa-1009	44	38	ray	ray	NOUN
ijassa-1009	44	39	.	.	PUNCT
ijassa-1009	45	1	but	but	CCONJ
ijassa-1009	45	2	also	also	ADV
ijassa-1009	45	3	,	,	PUNCT
ijassa-1009	45	4	a	a	DET
ijassa-1009	45	5	slight	slight	ADJ
ijassa-1009	45	6	problem	problem	NOUN
ijassa-1009	45	7	would	would	AUX
ijassa-1009	45	8	be	be	AUX
ijassa-1009	45	9	that	that	SCONJ
ijassa-1009	45	10	the	the	DET
ijassa-1009	45	11	detection	detection	NOUN
ijassa-1009	45	12	decisions	decision	NOUN
ijassa-1009	45	13	are	be	AUX
ijassa-1009	45	14	taken	take	VERB
ijassa-1009	45	15	only	only	ADV
ijassa-1009	45	16	by	by	ADP
ijassa-1009	45	17	covid	covid	NOUN
ijassa-1009	45	18	-	-	ADJ
ijassa-1009	45	19	net	net	NOUN
ijassa-1009	46	1	[	[	X
ijassa-1009	46	2	8	8	NUM
ijassa-1009	46	3	]	]	PUNCT
ijassa-1009	46	4	.	.	PUNCT
ijassa-1009	47	1	they	they	PRON
ijassa-1009	47	2	adapted	adapt	VERB
ijassa-1009	47	3	detrac	detrac	NOUN
ijassa-1009	47	4	(	(	PUNCT
ijassa-1009	47	5	decompose	decompose	NOUN
ijassa-1009	47	6	,	,	PUNCT
ijassa-1009	47	7	transfer	transfer	NOUN
ijassa-1009	47	8	and	and	CCONJ
ijassa-1009	47	9	compose	compose	VERB
ijassa-1009	47	10	)	)	PUNCT
ijassa-1009	47	11	–	–	PUNCT
ijassa-1009	47	12	a	a	DET
ijassa-1009	47	13	deep	deep	ADJ
ijassa-1009	47	14	cnn	cnn	NOUN
ijassa-1009	47	15	architecture	architecture	NOUN
ijassa-1009	47	16	that	that	PRON
ijassa-1009	47	17	depends	depend	VERB
ijassa-1009	47	18	on	on	ADP
ijassa-1009	47	19	a	a	DET
ijassa-1009	47	20	class	class	NOUN
ijassa-1009	47	21	decomposition	decomposition	NOUN
ijassa-1009	47	22	approach	approach	NOUN
ijassa-1009	47	23	for	for	ADP
ijassa-1009	47	24	the	the	DET
ijassa-1009	47	25	classification	classification	NOUN
ijassa-1009	47	26	of	of	ADP
ijassa-1009	47	27	covid-19	covid-19	PROPN
ijassa-1009	47	28	images	image	NOUN
ijassa-1009	47	29	.	.	PUNCT
ijassa-1009	48	1	the	the	DET
ijassa-1009	48	2	experimental	experimental	ADJ
ijassa-1009	48	3	results	result	NOUN
ijassa-1009	48	4	showed	show	VERB
ijassa-1009	48	5	that	that	SCONJ
ijassa-1009	48	6	detrac	detrac	NOUN
ijassa-1009	48	7	had	have	VERB
ijassa-1009	48	8	high	high	ADJ
ijassa-1009	48	9	accuracy	accuracy	NOUN
ijassa-1009	48	10	and	and	CCONJ
ijassa-1009	48	11	with	with	ADP
ijassa-1009	48	12	high	high	ADJ
ijassa-1009	48	13	sensitivity	sensitivity	NOUN
ijassa-1009	48	14	and	and	CCONJ
ijassa-1009	48	15	specificity	specificity	NOUN
ijassa-1009	48	16	respectively	respectively	ADV
ijassa-1009	48	17	[	[	X
ijassa-1009	48	18	9	9	NUM
ijassa-1009	48	19	]	]	PUNCT
ijassa-1009	48	20	.	.	PUNCT
ijassa-1009	49	1	the	the	DET
ijassa-1009	49	2	first	first	ADJ
ijassa-1009	49	3	-	-	PUNCT
ijassa-1009	49	4	ever	ever	ADV
ijassa-1009	49	5	data	data	NOUN
ijassa-1009	49	6	collection	collection	NOUN
ijassa-1009	49	7	of	of	ADP
ijassa-1009	49	8	covid-19	covid-19	PROPN
ijassa-1009	49	9	images	image	NOUN
ijassa-1009	49	10	are	be	AUX
ijassa-1009	49	11	made	make	VERB
ijassa-1009	49	12	accessible	accessible	ADJ
ijassa-1009	49	13	to	to	ADP
ijassa-1009	49	14	researchers	researcher	NOUN
ijassa-1009	49	15	.	.	PUNCT
ijassa-1009	50	1	they	they	PRON
ijassa-1009	50	2	have	have	AUX
ijassa-1009	50	3	collected	collect	VERB
ijassa-1009	50	4	cxr	cxr	NOUN
ijassa-1009	50	5	image	image	NOUN
ijassa-1009	50	6	data	datum	NOUN
ijassa-1009	50	7	,	,	PUNCT
ijassa-1009	50	8	which	which	PRON
ijassa-1009	50	9	is	be	AUX
ijassa-1009	50	10	about	about	ADV
ijassa-1009	50	11	542	542	NUM
ijassa-1009	50	12	chest	chest	NOUN
ijassa-1009	50	13	x	x	NOUN
ijassa-1009	50	14	-	-	NOUN
ijassa-1009	50	15	ray	ray	NOUN
ijassa-1009	50	16	images	image	NOUN
ijassa-1009	50	17	from	from	ADP
ijassa-1009	50	18	about	about	ADP
ijassa-1009	50	19	44	44	NUM
ijassa-1009	50	20	naveen	naveen	NOUN
ijassa-1009	50	21	et	et	PROPN
ijassa-1009	50	22	al	al	PROPN
ijassa-1009	50	23	.	.	PUNCT
ijassa-1009	51	1	copyright	copyright	PROPN
ijassa-1009	51	2	©	©	PROPN
ijassa-1009	51	3	2021	2021	NUM
ijassa-1009	51	4	assa	assa	NOUN
ijassa-1009	51	5	.	.	PUNCT
ijassa-1009	52	1	adv	adv	PROPN
ijassa-1009	52	2	.	.	PUNCT
ijassa-1009	53	1	in	in	ADP
ijassa-1009	53	2	systems	system	NOUN
ijassa-1009	53	3	science	science	NOUN
ijassa-1009	53	4	and	and	CCONJ
ijassa-1009	53	5	appl	appl	NOUN
ijassa-1009	53	6	.	.	PUNCT
ijassa-1009	54	1	(	(	PUNCT
ijassa-1009	54	2	2021	2021	NUM
ijassa-1009	54	3	)	)	PUNCT
ijassa-1009	54	4	262	262	NUM
ijassa-1009	54	5	covid-19	covid-19	PROPN
ijassa-1009	54	6	patients	patient	NOUN
ijassa-1009	54	7	from	from	ADP
ijassa-1009	54	8	26	26	NUM
ijassa-1009	54	9	different	different	ADJ
ijassa-1009	54	10	countries	country	NOUN
ijassa-1009	54	11	.	.	PUNCT
ijassa-1009	55	1	frontal	frontal	ADJ
ijassa-1009	55	2	and	and	CCONJ
ijassa-1009	55	3	lateral	lateral	ADJ
ijassa-1009	55	4	view	view	NOUN
ijassa-1009	55	5	imagery	imagery	NOUN
ijassa-1009	55	6	has	have	AUX
ijassa-1009	55	7	been	be	AUX
ijassa-1009	55	8	collected	collect	VERB
ijassa-1009	55	9	and	and	CCONJ
ijassa-1009	55	10	all	all	DET
ijassa-1009	55	11	the	the	DET
ijassa-1009	55	12	metadata	metadata	NOUN
ijassa-1009	55	13	such	such	ADJ
ijassa-1009	55	14	as	as	ADP
ijassa-1009	55	15	when	when	SCONJ
ijassa-1009	55	16	did	do	AUX
ijassa-1009	55	17	the	the	DET
ijassa-1009	55	18	patient	patient	ADJ
ijassa-1009	55	19	experience	experience	NOUN
ijassa-1009	55	20	first	first	ADJ
ijassa-1009	55	21	symptoms	symptom	NOUN
ijassa-1009	55	22	and	and	CCONJ
ijassa-1009	55	23	what	what	PRON
ijassa-1009	55	24	was	be	AUX
ijassa-1009	55	25	his	his	PRON
ijassa-1009	55	26	intensive	intensive	ADJ
ijassa-1009	55	27	care	care	NOUN
ijassa-1009	55	28	unit	unit	NOUN
ijassa-1009	55	29	(	(	PUNCT
ijassa-1009	55	30	icu	icu	PROPN
ijassa-1009	55	31	)	)	PUNCT
ijassa-1009	55	32	status	status	NOUN
ijassa-1009	55	33	,	,	PUNCT
ijassa-1009	55	34	intubation	intubation	NOUN
ijassa-1009	55	35	status	status	NOUN
ijassa-1009	55	36	,	,	PUNCT
ijassa-1009	55	37	or	or	CCONJ
ijassa-1009	55	38	his	his	PRON
ijassa-1009	55	39	survival	survival	NOUN
ijassa-1009	55	40	status	status	NOUN
ijassa-1009	55	41	[	[	X
ijassa-1009	55	42	10	10	NUM
ijassa-1009	55	43	]	]	PUNCT
ijassa-1009	55	44	.	.	PUNCT
ijassa-1009	56	1	suat	suat	PROPN
ijassa-1009	56	2	toraman	toraman	NOUN
ijassa-1009	56	3	,	,	PUNCT
ijassa-1009	56	4	talha	talha	PROPN
ijassa-1009	56	5	burak	burak	PROPN
ijassa-1009	56	6	alakus	alakus	PROPN
ijassa-1009	56	7	,	,	PUNCT
ijassa-1009	56	8	and	and	CCONJ
ijassa-1009	56	9	ibrahim	ibrahim	PROPN
ijassa-1009	56	10	turkoglu	turkoglu	PROPN
ijassa-1009	56	11	proposed	propose	VERB
ijassa-1009	56	12	a	a	DET
ijassa-1009	56	13	novel	novel	ADJ
ijassa-1009	56	14	artificial	artificial	ADJ
ijassa-1009	56	15	neural	neural	ADJ
ijassa-1009	56	16	network	network	NOUN
ijassa-1009	56	17	for	for	ADP
ijassa-1009	56	18	detecting	detect	VERB
ijassa-1009	56	19	covid-19	covid-19	PROPN
ijassa-1009	56	20	from	from	ADP
ijassa-1009	56	21	the	the	DET
ijassa-1009	56	22	chest	chest	NOUN
ijassa-1009	56	23	x	x	NOUN
ijassa-1009	56	24	-	-	NOUN
ijassa-1009	56	25	ray	ray	NOUN
ijassa-1009	56	26	images	image	NOUN
ijassa-1009	56	27	and	and	CCONJ
ijassa-1009	56	28	also	also	ADV
ijassa-1009	56	29	to	to	PART
ijassa-1009	56	30	classify	classify	VERB
ijassa-1009	56	31	the	the	DET
ijassa-1009	56	32	dataset	dataset	NOUN
ijassa-1009	56	33	images	image	NOUN
ijassa-1009	56	34	into	into	ADP
ijassa-1009	56	35	covid-19	covid-19	PROPN
ijassa-1009	56	36	,	,	PUNCT
ijassa-1009	56	37	and	and	CCONJ
ijassa-1009	56	38	pneumonia	pneumonia	NOUN
ijassa-1009	56	39	x	x	NOUN
ijassa-1009	56	40	-	-	NOUN
ijassa-1009	56	41	ray	ray	NOUN
ijassa-1009	56	42	images	image	NOUN
ijassa-1009	56	43	using	use	VERB
ijassa-1009	56	44	capsule	capsule	NOUN
ijassa-1009	56	45	networks	network	NOUN
ijassa-1009	56	46	.	.	PUNCT
ijassa-1009	57	1	the	the	DET
ijassa-1009	57	2	results	result	NOUN
ijassa-1009	57	3	displayed	display	VERB
ijassa-1009	57	4	using	use	VERB
ijassa-1009	57	5	capsule	capsule	ADJ
ijassa-1009	57	6	networks	network	NOUN
ijassa-1009	57	7	will	will	AUX
ijassa-1009	57	8	not	not	PART
ijassa-1009	57	9	only	only	ADV
ijassa-1009	57	10	lead	lead	VERB
ijassa-1009	57	11	to	to	ADP
ijassa-1009	57	12	higher	high	ADJ
ijassa-1009	57	13	accuracy	accuracy	NOUN
ijassa-1009	57	14	but	but	CCONJ
ijassa-1009	57	15	at	at	ADP
ijassa-1009	57	16	the	the	DET
ijassa-1009	57	17	same	same	ADJ
ijassa-1009	57	18	time	time	NOUN
ijassa-1009	57	19	can	can	AUX
ijassa-1009	57	20	be	be	AUX
ijassa-1009	57	21	effectively	effectively	ADV
ijassa-1009	57	22	used	use	VERB
ijassa-1009	57	23	for	for	ADP
ijassa-1009	57	24	classification	classification	NOUN
ijassa-1009	57	25	in	in	ADP
ijassa-1009	57	26	a	a	DET
ijassa-1009	57	27	limited	limited	ADJ
ijassa-1009	57	28	dataset	dataset	NOUN
ijassa-1009	57	29	too	too	ADV
ijassa-1009	58	1	[	[	X
ijassa-1009	58	2	11	11	NUM
ijassa-1009	58	3	]	]	PUNCT
ijassa-1009	58	4	.	.	PUNCT
ijassa-1009	59	1	the	the	DET
ijassa-1009	59	2	following	follow	VERB
ijassa-1009	59	3	study	study	NOUN
ijassa-1009	59	4	attempts	attempt	VERB
ijassa-1009	59	5	to	to	PART
ijassa-1009	59	6	give	give	VERB
ijassa-1009	59	7	insights	insight	NOUN
ijassa-1009	59	8	on	on	ADP
ijassa-1009	59	9	the	the	DET
ijassa-1009	59	10	feasibility	feasibility	NOUN
ijassa-1009	59	11	of	of	ADP
ijassa-1009	59	12	using	use	VERB
ijassa-1009	59	13	a	a	DET
ijassa-1009	59	14	deep	deep	ADJ
ijassa-1009	59	15	learningbased	learningbase	VERB
ijassa-1009	59	16	decision	decision	NOUN
ijassa-1009	59	17	tree	tree	NOUN
ijassa-1009	59	18	classifier	classifier	NOUN
ijassa-1009	59	19	for	for	ADP
ijassa-1009	59	20	detecting	detect	VERB
ijassa-1009	59	21	covid-19	covid-19	PROPN
ijassa-1009	59	22	from	from	ADP
ijassa-1009	59	23	chest	chest	NOUN
ijassa-1009	59	24	x	x	NOUN
ijassa-1009	59	25	-	-	NOUN
ijassa-1009	59	26	ray	ray	NOUN
ijassa-1009	59	27	images	image	NOUN
ijassa-1009	59	28	.	.	PUNCT
ijassa-1009	60	1	this	this	DET
ijassa-1009	60	2	proposed	propose	VERB
ijassa-1009	60	3	classifier	classifier	NOUN
ijassa-1009	60	4	consists	consist	VERB
ijassa-1009	60	5	of	of	ADP
ijassa-1009	60	6	three	three	NUM
ijassa-1009	60	7	binary	binary	ADJ
ijassa-1009	60	8	decision	decision	NOUN
ijassa-1009	60	9	trees	tree	NOUN
ijassa-1009	60	10	.	.	PUNCT
ijassa-1009	61	1	the	the	DET
ijassa-1009	61	2	first	first	ADJ
ijassa-1009	61	3	tree	tree	NOUN
ijassa-1009	61	4	classifies	classify	VERB
ijassa-1009	61	5	the	the	DET
ijassa-1009	61	6	chest	chest	NOUN
ijassa-1009	61	7	x	x	NOUN
ijassa-1009	61	8	-	-	NOUN
ijassa-1009	61	9	ray	ray	NOUN
ijassa-1009	61	10	images	image	NOUN
ijassa-1009	61	11	as	as	ADP
ijassa-1009	61	12	normal	normal	ADJ
ijassa-1009	61	13	and	and	CCONJ
ijassa-1009	61	14	abnormal	abnormal	ADJ
ijassa-1009	61	15	.	.	PUNCT
ijassa-1009	62	1	the	the	DET
ijassa-1009	62	2	second	second	ADJ
ijassa-1009	62	3	tree	tree	NOUN
ijassa-1009	62	4	identifies	identify	VERB
ijassa-1009	62	5	the	the	DET
ijassa-1009	62	6	abnormal	abnormal	ADJ
ijassa-1009	62	7	images	image	NOUN
ijassa-1009	62	8	with	with	ADP
ijassa-1009	62	9	signs	sign	NOUN
ijassa-1009	62	10	of	of	ADP
ijassa-1009	62	11	tuberculosis	tuberculosis	NOUN
ijassa-1009	62	12	and	and	CCONJ
ijassa-1009	62	13	the	the	DET
ijassa-1009	62	14	third	third	NOUN
ijassa-1009	62	15	does	do	VERB
ijassa-1009	62	16	the	the	DET
ijassa-1009	62	17	same	same	ADJ
ijassa-1009	62	18	thing	thing	NOUN
ijassa-1009	62	19	for	for	ADP
ijassa-1009	62	20	covid-19	covid-19	PROPN
ijassa-1009	62	21	.	.	PUNCT
ijassa-1009	63	1	the	the	DET
ijassa-1009	63	2	average	average	ADJ
ijassa-1009	63	3	accuracy	accuracy	NOUN
ijassa-1009	63	4	achieved	achieve	VERB
ijassa-1009	63	5	by	by	ADP
ijassa-1009	63	6	the	the	DET
ijassa-1009	63	7	proposed	propose	VERB
ijassa-1009	63	8	classifier	classifier	NOUN
ijassa-1009	63	9	was	be	AUX
ijassa-1009	63	10	found	find	VERB
ijassa-1009	63	11	to	to	PART
ijassa-1009	63	12	be	be	AUX
ijassa-1009	63	13	95	95	NUM
ijassa-1009	63	14	%	%	NOUN
ijassa-1009	63	15	.	.	PUNCT
ijassa-1009	64	1	[	[	X
ijassa-1009	64	2	12	12	NUM
ijassa-1009	64	3	]	]	PUNCT
ijassa-1009	64	4	.	.	PUNCT
ijassa-1009	65	1	a	a	DET
ijassa-1009	65	2	deep	deep	ADJ
ijassa-1009	65	3	learning	learning	NOUN
ijassa-1009	65	4	model	model	NOUN
ijassa-1009	65	5	was	be	AUX
ijassa-1009	65	6	used	use	VERB
ijassa-1009	65	7	for	for	ADP
ijassa-1009	65	8	detecting	detect	VERB
ijassa-1009	65	9	coronavirus	coronavirus	NOUN
ijassa-1009	65	10	,	,	PUNCT
ijassa-1009	65	11	which	which	PRON
ijassa-1009	65	12	is	be	AUX
ijassa-1009	65	13	a	a	DET
ijassa-1009	65	14	sub	sub	NOUN
ijassa-1009	65	15	-	-	ADJ
ijassa-1009	65	16	branch	branch	NOUN
ijassa-1009	65	17	of	of	ADP
ijassa-1009	65	18	artificial	artificial	ADJ
ijassa-1009	65	19	intelligence	intelligence	NOUN
ijassa-1009	65	20	.	.	PUNCT
ijassa-1009	66	1	the	the	DET
ijassa-1009	66	2	dataset	dataset	NOUN
ijassa-1009	66	3	used	use	VERB
ijassa-1009	66	4	for	for	ADP
ijassa-1009	66	5	this	this	DET
ijassa-1009	66	6	research	research	NOUN
ijassa-1009	66	7	consists	consist	VERB
ijassa-1009	66	8	mainly	mainly	ADV
ijassa-1009	66	9	of	of	ADP
ijassa-1009	66	10	three	three	NUM
ijassa-1009	66	11	classes	class	NOUN
ijassa-1009	66	12	that	that	PRON
ijassa-1009	66	13	are	be	AUX
ijassa-1009	66	14	coronavirus	coronavirus	NOUN
ijassa-1009	66	15	,	,	PUNCT
ijassa-1009	66	16	pneumonia	pneumonia	NOUN
ijassa-1009	66	17	,	,	PUNCT
ijassa-1009	66	18	and	and	CCONJ
ijassa-1009	66	19	normal	normal	ADJ
ijassa-1009	66	20	x	x	ADJ
ijassa-1009	66	21	-	-	NOUN
ijassa-1009	66	22	ray	ray	NOUN
ijassa-1009	66	23	imagery	imagery	NOUN
ijassa-1009	66	24	.	.	PUNCT
ijassa-1009	67	1	fuzzy	fuzzy	ADJ
ijassa-1009	67	2	color	color	NOUN
ijassa-1009	67	3	techniques	technique	NOUN
ijassa-1009	67	4	were	be	AUX
ijassa-1009	67	5	used	use	VERB
ijassa-1009	67	6	to	to	PART
ijassa-1009	67	7	restructure	restructure	VERB
ijassa-1009	67	8	the	the	DET
ijassa-1009	67	9	data	data	NOUN
ijassa-1009	67	10	classes	class	NOUN
ijassa-1009	67	11	that	that	PRON
ijassa-1009	67	12	would	would	AUX
ijassa-1009	67	13	be	be	AUX
ijassa-1009	67	14	used	use	VERB
ijassa-1009	67	15	as	as	ADP
ijassa-1009	67	16	a	a	DET
ijassa-1009	67	17	pre	pre	ADJ
ijassa-1009	67	18	-	-	ADJ
ijassa-1009	67	19	processing	processing	ADJ
ijassa-1009	67	20	step	step	NOUN
ijassa-1009	67	21	and	and	CCONJ
ijassa-1009	67	22	the	the	DET
ijassa-1009	67	23	images	image	NOUN
ijassa-1009	67	24	that	that	PRON
ijassa-1009	67	25	were	be	AUX
ijassa-1009	67	26	structured	structure	VERB
ijassa-1009	67	27	with	with	ADP
ijassa-1009	67	28	the	the	DET
ijassa-1009	67	29	original	original	ADJ
ijassa-1009	67	30	images	image	NOUN
ijassa-1009	67	31	were	be	AUX
ijassa-1009	67	32	stacked	stack	VERB
ijassa-1009	67	33	.	.	PUNCT
ijassa-1009	68	1	in	in	ADP
ijassa-1009	68	2	the	the	DET
ijassa-1009	68	3	following	following	ADJ
ijassa-1009	68	4	step	step	NOUN
ijassa-1009	68	5	,	,	PUNCT
ijassa-1009	68	6	deep	deep	ADJ
ijassa-1009	68	7	learning	learning	NOUN
ijassa-1009	68	8	models	model	NOUN
ijassa-1009	68	9	like	like	ADP
ijassa-1009	68	10	mobilenetv2	mobilenetv2	PROPN
ijassa-1009	68	11	,	,	PUNCT
ijassa-1009	68	12	squeeze	squeeze	VERB
ijassa-1009	68	13	net	net	NOUN
ijassa-1009	68	14	were	be	AUX
ijassa-1009	68	15	used	use	VERB
ijassa-1009	68	16	to	to	PART
ijassa-1009	68	17	train	train	VERB
ijassa-1009	68	18	the	the	DET
ijassa-1009	68	19	stacked	stack	VERB
ijassa-1009	68	20	dataset	dataset	NOUN
ijassa-1009	68	21	and	and	CCONJ
ijassa-1009	68	22	the	the	DET
ijassa-1009	68	23	social	social	ADJ
ijassa-1009	68	24	mimic	mimic	ADJ
ijassa-1009	68	25	optimization	optimization	NOUN
ijassa-1009	68	26	method	method	NOUN
ijassa-1009	68	27	was	be	AUX
ijassa-1009	68	28	used	use	VERB
ijassa-1009	68	29	to	to	PART
ijassa-1009	68	30	process	process	VERB
ijassa-1009	68	31	the	the	DET
ijassa-1009	68	32	feature	feature	NOUN
ijassa-1009	68	33	sets	set	NOUN
ijassa-1009	68	34	obtained	obtain	VERB
ijassa-1009	68	35	by	by	ADP
ijassa-1009	68	36	the	the	DET
ijassa-1009	68	37	models	model	NOUN
ijassa-1009	68	38	.	.	PUNCT
ijassa-1009	69	1	subsequently	subsequently	ADV
ijassa-1009	69	2	,	,	PUNCT
ijassa-1009	69	3	all	all	DET
ijassa-1009	69	4	the	the	DET
ijassa-1009	69	5	features	feature	NOUN
ijassa-1009	69	6	were	be	AUX
ijassa-1009	69	7	combined	combine	VERB
ijassa-1009	69	8	and	and	CCONJ
ijassa-1009	69	9	categorized	categorize	VERB
ijassa-1009	69	10	using	use	VERB
ijassa-1009	69	11	svm	svm	NOUN
ijassa-1009	69	12	that	that	PRON
ijassa-1009	69	13	is	be	AUX
ijassa-1009	69	14	support	support	NOUN
ijassa-1009	69	15	vector	vector	NOUN
ijassa-1009	69	16	machines	machine	NOUN
ijassa-1009	69	17	[	[	X
ijassa-1009	69	18	13	13	NUM
ijassa-1009	69	19	]	]	PUNCT
ijassa-1009	69	20	.	.	PUNCT
ijassa-1009	70	1	in	in	ADP
ijassa-1009	70	2	this	this	DET
ijassa-1009	70	3	research	research	NOUN
ijassa-1009	70	4	paper	paper	NOUN
ijassa-1009	70	5	,	,	PUNCT
ijassa-1009	70	6	the	the	DET
ijassa-1009	70	7	authors	author	NOUN
ijassa-1009	70	8	used	use	VERB
ijassa-1009	70	9	a	a	DET
ijassa-1009	70	10	dataset	dataset	NOUN
ijassa-1009	70	11	of	of	ADP
ijassa-1009	70	12	x	x	NOUN
ijassa-1009	70	13	-	-	NOUN
ijassa-1009	70	14	ray	ray	NOUN
ijassa-1009	70	15	images	image	NOUN
ijassa-1009	70	16	from	from	ADP
ijassa-1009	70	17	patients	patient	NOUN
ijassa-1009	70	18	that	that	PRON
ijassa-1009	70	19	have	have	VERB
ijassa-1009	70	20	diseases	disease	NOUN
ijassa-1009	70	21	similar	similar	ADJ
ijassa-1009	70	22	to	to	ADP
ijassa-1009	70	23	coronavirus	coronavirus	NOUN
ijassa-1009	70	24	(	(	PUNCT
ijassa-1009	70	25	covid-19	covid-19	PROPN
ijassa-1009	70	26	)	)	PUNCT
ijassa-1009	70	27	like	like	ADP
ijassa-1009	70	28	pneumonia	pneumonia	NOUN
ijassa-1009	70	29	.	.	PUNCT
ijassa-1009	71	1	incidents	incident	NOUN
ijassa-1009	71	2	from	from	ADP
ijassa-1009	71	3	daily	daily	ADJ
ijassa-1009	71	4	news	news	NOUN
ijassa-1009	71	5	and	and	CCONJ
ijassa-1009	71	6	cases	case	NOUN
ijassa-1009	71	7	were	be	AUX
ijassa-1009	71	8	utilized	utilize	VERB
ijassa-1009	71	9	for	for	ADP
ijassa-1009	71	10	the	the	DET
ijassa-1009	71	11	automatic	automatic	ADJ
ijassa-1009	71	12	detection	detection	NOUN
ijassa-1009	71	13	of	of	ADP
ijassa-1009	71	14	the	the	DET
ijassa-1009	71	15	covid-19	covid-19	PROPN
ijassa-1009	71	16	.	.	PUNCT
ijassa-1009	72	1	the	the	DET
ijassa-1009	72	2	purpose	purpose	NOUN
ijassa-1009	72	3	of	of	ADP
ijassa-1009	72	4	this	this	DET
ijassa-1009	72	5	study	study	NOUN
ijassa-1009	72	6	is	be	AUX
ijassa-1009	72	7	to	to	PART
ijassa-1009	72	8	evaluate	evaluate	VERB
ijassa-1009	72	9	the	the	DET
ijassa-1009	72	10	performance	performance	NOUN
ijassa-1009	72	11	of	of	ADP
ijassa-1009	72	12	state	state	NOUN
ijassa-1009	72	13	-	-	PUNCT
ijassa-1009	72	14	of	of	ADP
ijassa-1009	72	15	-	-	PUNCT
ijassa-1009	72	16	the	the	DET
ijassa-1009	72	17	-	-	PUNCT
ijassa-1009	72	18	art	art	NOUN
ijassa-1009	72	19	convolutional	convolutional	ADJ
ijassa-1009	72	20	neural	neural	ADJ
ijassa-1009	72	21	network	network	NOUN
ijassa-1009	72	22	architectures	architecture	NOUN
ijassa-1009	72	23	that	that	PRON
ijassa-1009	72	24	are	be	AUX
ijassa-1009	72	25	suggested	suggest	VERB
ijassa-1009	72	26	over	over	ADP
ijassa-1009	72	27	the	the	DET
ijassa-1009	72	28	past	past	ADJ
ijassa-1009	72	29	years	year	NOUN
ijassa-1009	72	30	for	for	ADP
ijassa-1009	72	31	medical	medical	ADJ
ijassa-1009	72	32	image	image	NOUN
ijassa-1009	72	33	analysis	analysis	NOUN
ijassa-1009	72	34	and	and	CCONJ
ijassa-1009	72	35	classification	classification	NOUN
ijassa-1009	72	36	.	.	PUNCT
ijassa-1009	73	1	particularly	particularly	ADV
ijassa-1009	73	2	,	,	PUNCT
ijassa-1009	73	3	the	the	DET
ijassa-1009	73	4	method	method	NOUN
ijassa-1009	73	5	called	call	VERB
ijassa-1009	73	6	transfer	transfer	NOUN
ijassa-1009	73	7	learning	learning	NOUN
ijassa-1009	73	8	was	be	AUX
ijassa-1009	73	9	implemented	implement	VERB
ijassa-1009	73	10	.	.	PUNCT
ijassa-1009	74	1	it	it	PRON
ijassa-1009	74	2	is	be	AUX
ijassa-1009	74	3	shown	show	VERB
ijassa-1009	74	4	in	in	ADP
ijassa-1009	74	5	the	the	DET
ijassa-1009	74	6	paper	paper	NOUN
ijassa-1009	74	7	that	that	PRON
ijassa-1009	74	8	even	even	ADV
ijassa-1009	74	9	for	for	ADP
ijassa-1009	74	10	small	small	ADJ
ijassa-1009	74	11	medical	medical	ADJ
ijassa-1009	74	12	image	image	NOUN
ijassa-1009	74	13	datasets	dataset	NOUN
ijassa-1009	74	14	detection	detection	NOUN
ijassa-1009	74	15	of	of	ADP
ijassa-1009	74	16	various	various	ADJ
ijassa-1009	74	17	abnormalities	abnormality	NOUN
ijassa-1009	74	18	is	be	AUX
ijassa-1009	74	19	an	an	DET
ijassa-1009	74	20	achievable	achievable	ADJ
ijassa-1009	74	21	target	target	NOUN
ijassa-1009	74	22	with	with	ADP
ijassa-1009	74	23	the	the	DET
ijassa-1009	74	24	help	help	NOUN
ijassa-1009	74	25	of	of	ADP
ijassa-1009	74	26	transfer	transfer	NOUN
ijassa-1009	74	27	learning	learning	NOUN
ijassa-1009	74	28	,	,	PUNCT
ijassa-1009	74	29	and	and	CCONJ
ijassa-1009	74	30	it	it	PRON
ijassa-1009	74	31	often	often	ADV
ijassa-1009	74	32	yields	yield	VERB
ijassa-1009	74	33	remarkable	remarkable	ADJ
ijassa-1009	74	34	results	result	NOUN
ijassa-1009	74	35	.	.	PUNCT
ijassa-1009	75	1	the	the	DET
ijassa-1009	75	2	outcome	outcome	NOUN
ijassa-1009	75	3	of	of	ADP
ijassa-1009	75	4	the	the	DET
ijassa-1009	75	5	research	research	NOUN
ijassa-1009	75	6	proposed	propose	VERB
ijassa-1009	75	7	that	that	SCONJ
ijassa-1009	75	8	deep	deep	ADJ
ijassa-1009	75	9	learning	learning	NOUN
ijassa-1009	75	10	with	with	ADP
ijassa-1009	75	11	x	x	ADJ
ijassa-1009	75	12	-	-	NOUN
ijassa-1009	75	13	ray	ray	NOUN
ijassa-1009	75	14	imaging	imaging	NOUN
ijassa-1009	75	15	may	may	AUX
ijassa-1009	75	16	extract	extract	VERB
ijassa-1009	75	17	quite	quite	ADV
ijassa-1009	75	18	noteworthy	noteworthy	ADJ
ijassa-1009	75	19	biomarkers	biomarker	NOUN
ijassa-1009	75	20	related	relate	VERB
ijassa-1009	75	21	to	to	ADP
ijassa-1009	75	22	the	the	DET
ijassa-1009	75	23	coronavirus	coronavirus	NOUN
ijassa-1009	75	24	disease	disease	NOUN
ijassa-1009	75	25	,	,	PUNCT
ijassa-1009	75	26	with	with	ADP
ijassa-1009	75	27	the	the	DET
ijassa-1009	75	28	highest	high	ADJ
ijassa-1009	75	29	accuracy	accuracy	NOUN
ijassa-1009	75	30	,	,	PUNCT
ijassa-1009	75	31	highest	high	ADJ
ijassa-1009	75	32	sensitivity	sensitivity	NOUN
ijassa-1009	75	33	,	,	PUNCT
ijassa-1009	75	34	and	and	CCONJ
ijassa-1009	75	35	highest	high	ADJ
ijassa-1009	75	36	specificity	specificity	NOUN
ijassa-1009	75	37	which	which	PRON
ijassa-1009	75	38	is	be	AUX
ijassa-1009	75	39	quite	quite	ADV
ijassa-1009	75	40	remarkable	remarkable	ADJ
ijassa-1009	75	41	[	[	X
ijassa-1009	75	42	14	14	NUM
ijassa-1009	75	43	]	]	PUNCT
ijassa-1009	75	44	.	.	PUNCT
ijassa-1009	76	1	a	a	DET
ijassa-1009	76	2	deep	deep	ADJ
ijassa-1009	76	3	learning	learning	NOUN
ijassa-1009	76	4	-	-	PUNCT
ijassa-1009	76	5	based	base	VERB
ijassa-1009	76	6	lung	lung	NOUN
ijassa-1009	76	7	ct	ct	NUM
ijassa-1009	76	8	diagnosis	diagnosis	NOUN
ijassa-1009	76	9	system	system	NOUN
ijassa-1009	76	10	[	[	X
ijassa-1009	76	11	15	15	NUM
ijassa-1009	76	12	]	]	PUNCT
ijassa-1009	76	13	was	be	AUX
ijassa-1009	76	14	developed	develop	VERB
ijassa-1009	76	15	that	that	SCONJ
ijassa-1009	76	16	detects	detect	VERB
ijassa-1009	76	17	the	the	DET
ijassa-1009	76	18	patients	patient	NOUN
ijassa-1009	76	19	with	with	ADP
ijassa-1009	76	20	the	the	DET
ijassa-1009	76	21	presence	presence	NOUN
ijassa-1009	76	22	of	of	ADP
ijassa-1009	76	23	covid-19	covid-19	PROPN
ijassa-1009	76	24	.	.	PUNCT
ijassa-1009	77	1	the	the	DET
ijassa-1009	77	2	results	result	NOUN
ijassa-1009	77	3	of	of	ADP
ijassa-1009	77	4	the	the	DET
ijassa-1009	77	5	experiment	experiment	NOUN
ijassa-1009	77	6	show	show	VERB
ijassa-1009	77	7	that	that	SCONJ
ijassa-1009	77	8	the	the	DET
ijassa-1009	77	9	trained	train	VERB
ijassa-1009	77	10	model	model	NOUN
ijassa-1009	77	11	can	can	AUX
ijassa-1009	77	12	identify	identify	VERB
ijassa-1009	77	13	the	the	DET
ijassa-1009	77	14	covid-19	covid-19	PROPN
ijassa-1009	77	15	patients	patient	NOUN
ijassa-1009	77	16	from	from	ADP
ijassa-1009	77	17	others	other	NOUN
ijassa-1009	77	18	accurately	accurately	ADV
ijassa-1009	77	19	with	with	ADP
ijassa-1009	77	20	high	high	ADJ
ijassa-1009	77	21	sensitivity	sensitivity	NOUN
ijassa-1009	77	22	and	and	CCONJ
ijassa-1009	77	23	an	an	DET
ijassa-1009	77	24	excellent	excellent	ADJ
ijassa-1009	77	25	auc	auc	NOUN
ijassa-1009	77	26	.	.	PUNCT
ijassa-1009	78	1	besides	besides	ADV
ijassa-1009	78	2	,	,	PUNCT
ijassa-1009	78	3	the	the	DET
ijassa-1009	78	4	obtained	obtain	VERB
ijassa-1009	78	5	model	model	NOUN
ijassa-1009	78	6	is	be	AUX
ijassa-1009	78	7	capable	capable	ADJ
ijassa-1009	78	8	of	of	ADP
ijassa-1009	78	9	distinguishing	distinguish	VERB
ijassa-1009	78	10	the	the	DET
ijassa-1009	78	11	coronavirus	coronavirus	NOUN
ijassa-1009	78	12	patients	patient	NOUN
ijassa-1009	78	13	and	and	CCONJ
ijassa-1009	78	14	pneumonia	pneumonia	NOUN
ijassa-1009	78	15	-	-	PUNCT
ijassa-1009	78	16	infected	infect	VERB
ijassa-1009	78	17	patients	patient	NOUN
ijassa-1009	78	18	with	with	ADP
ijassa-1009	78	19	an	an	DET
ijassa-1009	78	20	astonishing	astonishing	ADJ
ijassa-1009	78	21	high	high	ADJ
ijassa-1009	78	22	auc	auc	NOUN
ijassa-1009	78	23	and	and	CCONJ
ijassa-1009	78	24	recall	recall	NOUN
ijassa-1009	78	25	.	.	PUNCT
ijassa-1009	79	1	furthermore	furthermore	ADV
ijassa-1009	79	2	,	,	PUNCT
ijassa-1009	79	3	the	the	DET
ijassa-1009	79	4	trained	train	VERB
ijassa-1009	79	5	model	model	NOUN
ijassa-1009	79	6	is	be	AUX
ijassa-1009	79	7	of	of	ADP
ijassa-1009	79	8	great	great	ADJ
ijassa-1009	79	9	help	help	NOUN
ijassa-1009	79	10	to	to	PART
ijassa-1009	79	11	assist	assist	VERB
ijassa-1009	79	12	doctors	doctor	NOUN
ijassa-1009	79	13	in	in	ADP
ijassa-1009	79	14	diagnosing	diagnose	VERB
ijassa-1009	79	15	coronavirus	coronavirus	NOUN
ijassa-1009	79	16	disease	disease	NOUN
ijassa-1009	79	17	since	since	SCONJ
ijassa-1009	79	18	it	it	PRON
ijassa-1009	79	19	can	can	AUX
ijassa-1009	79	20	also	also	ADV
ijassa-1009	79	21	localize	localize	VERB
ijassa-1009	79	22	the	the	DET
ijassa-1009	79	23	main	main	ADJ
ijassa-1009	79	24	lesion	lesion	NOUN
ijassa-1009	79	25	features	feature	NOUN
ijassa-1009	79	26	,	,	PUNCT
ijassa-1009	79	27	especially	especially	ADV
ijassa-1009	79	28	the	the	DET
ijassa-1009	79	29	ground	ground	NOUN
ijassa-1009	79	30	glass	glass	NOUN
ijassa-1009	79	31	opacity	opacity	NOUN
ijassa-1009	79	32	(	(	PUNCT
ijassa-1009	79	33	ggo	ggo	NOUN
ijassa-1009	79	34	)	)	PUNCT
ijassa-1009	79	35	.	.	PUNCT
ijassa-1009	80	1	also	also	ADV
ijassa-1009	80	2	,	,	PUNCT
ijassa-1009	80	3	the	the	DET
ijassa-1009	80	4	diagnosis	diagnosis	NOUN
ijassa-1009	80	5	is	be	AUX
ijassa-1009	80	6	super	super	ADJ
ijassa-1009	80	7	-	-	ADJ
ijassa-1009	80	8	fast	fast	ADJ
ijassa-1009	80	9	.	.	PUNCT
ijassa-1009	81	1	the	the	DET
ijassa-1009	81	2	diagnosis	diagnosis	NOUN
ijassa-1009	81	3	of	of	ADP
ijassa-1009	81	4	a	a	DET
ijassa-1009	81	5	patient	patient	NOUN
ijassa-1009	81	6	just	just	ADV
ijassa-1009	81	7	takes	take	VERB
ijassa-1009	81	8	about	about	ADV
ijassa-1009	81	9	30	30	NUM
ijassa-1009	81	10	seconds	second	NOUN
ijassa-1009	81	11	.	.	PUNCT
ijassa-1009	82	1	so	so	ADV
ijassa-1009	82	2	,	,	PUNCT
ijassa-1009	82	3	the	the	DET
ijassa-1009	82	4	conclusion	conclusion	NOUN
ijassa-1009	82	5	obtained	obtain	VERB
ijassa-1009	82	6	from	from	ADP
ijassa-1009	82	7	this	this	DET
ijassa-1009	82	8	research	research	NOUN
ijassa-1009	82	9	is	be	AUX
ijassa-1009	82	10	that	that	SCONJ
ijassa-1009	82	11	the	the	DET
ijassa-1009	82	12	established	establish	VERB
ijassa-1009	82	13	models	model	NOUN
ijassa-1009	82	14	can	can	AUX
ijassa-1009	82	15	achieve	achieve	VERB
ijassa-1009	82	16	a	a	DET
ijassa-1009	82	17	rapid	rapid	ADJ
ijassa-1009	82	18	and	and	CCONJ
ijassa-1009	82	19	accurate	accurate	ADJ
ijassa-1009	82	20	classification	classification	NOUN
ijassa-1009	82	21	of	of	ADP
ijassa-1009	82	22	coronavirus	coronavirus	NOUN
ijassa-1009	82	23	,	,	PUNCT
ijassa-1009	82	24	therefore	therefore	ADV
ijassa-1009	82	25	allowing	allow	VERB
ijassa-1009	82	26	the	the	DET
ijassa-1009	82	27	identification	identification	NOUN
ijassa-1009	82	28	of	of	ADP
ijassa-1009	82	29	patients	patient	NOUN
ijassa-1009	82	30	.	.	PUNCT
ijassa-1009	83	1	the	the	DET
ijassa-1009	83	2	authors	author	NOUN
ijassa-1009	83	3	of	of	ADP
ijassa-1009	83	4	this	this	DET
ijassa-1009	83	5	paper	paper	NOUN
ijassa-1009	83	6	compared	compare	VERB
ijassa-1009	83	7	the	the	DET
ijassa-1009	83	8	deep	deep	ADJ
ijassa-1009	83	9	learning	learning	NOUN
ijassa-1009	83	10	-	-	PUNCT
ijassa-1009	83	11	based	base	VERB
ijassa-1009	83	12	feature	feature	NOUN
ijassa-1009	83	13	extraction	extraction	NOUN
ijassa-1009	83	14	frameworks	framework	NOUN
ijassa-1009	83	15	for	for	ADP
ijassa-1009	83	16	the	the	DET
ijassa-1009	83	17	automatic	automatic	ADJ
ijassa-1009	83	18	classification	classification	NOUN
ijassa-1009	83	19	of	of	ADP
ijassa-1009	83	20	coronavirus	coronavirus	NOUN
ijassa-1009	83	21	.	.	PUNCT
ijassa-1009	84	1	to	to	PART
ijassa-1009	84	2	achieve	achieve	VERB
ijassa-1009	84	3	the	the	DET
ijassa-1009	84	4	most	most	ADV
ijassa-1009	84	5	accurate	accurate	ADJ
ijassa-1009	84	6	feature	feature	NOUN
ijassa-1009	84	7	,	,	PUNCT
ijassa-1009	84	8	algorithms	algorithm	NOUN
ijassa-1009	84	9	such	such	ADJ
ijassa-1009	84	10	as	as	ADP
ijassa-1009	84	11	xception	xception	NOUN
ijassa-1009	84	12	,	,	PUNCT
ijassa-1009	84	13	vggnet	vggnet	NOUN
ijassa-1009	84	14	,	,	PUNCT
ijassa-1009	84	15	resnet	resnet	NOUN
ijassa-1009	84	16	,	,	PUNCT
ijassa-1009	84	17	mobilenet	mobilenet	NOUN
ijassa-1009	84	18	,	,	PUNCT
ijassa-1009	84	19	inceptionv3	inceptionv3	NOUN
ijassa-1009	84	20	,	,	PUNCT
ijassa-1009	84	21	inceptionresnetv2	inceptionresnetv2	NOUN
ijassa-1009	84	22	,	,	PUNCT
ijassa-1009	84	23	densenet	densenet	NOUN
ijassa-1009	84	24	,	,	PUNCT
ijassa-1009	84	25	and	and	CCONJ
ijassa-1009	84	26	nasnet	nasnet	NOUN
ijassa-1009	84	27	were	be	AUX
ijassa-1009	84	28	used	use	VERB
ijassa-1009	84	29	in	in	ADP
ijassa-1009	84	30	the	the	DET
ijassa-1009	84	31	accurate	accurate	ADJ
ijassa-1009	84	32	classification	classification	NOUN
ijassa-1009	84	33	of	of	ADP
ijassa-1009	84	34	the	the	DET
ijassa-1009	84	35	virus	virus	NOUN
ijassa-1009	84	36	.	.	PUNCT
ijassa-1009	85	1	the	the	DET
ijassa-1009	85	2	features	feature	NOUN
ijassa-1009	85	3	were	be	AUX
ijassa-1009	85	4	extracted	extract	VERB
ijassa-1009	85	5	and	and	CCONJ
ijassa-1009	85	6	then	then	ADV
ijassa-1009	85	7	fed	feed	VERB
ijassa-1009	85	8	into	into	ADP
ijassa-1009	85	9	several	several	ADJ
ijassa-1009	85	10	machine	machine	NOUN
ijassa-1009	85	11	learning	learn	VERB
ijassa-1009	85	12	classifiers	classifier	NOUN
ijassa-1009	85	13	to	to	PART
ijassa-1009	85	14	distinguish	distinguish	VERB
ijassa-1009	85	15	the	the	DET
ijassa-1009	85	16	subjects	subject	NOUN
ijassa-1009	85	17	as	as	ADP
ijassa-1009	85	18	a	a	DET
ijassa-1009	85	19	case	case	NOUN
ijassa-1009	85	20	of	of	ADP
ijassa-1009	85	21	coronavirus	coronavirus	NOUN
ijassa-1009	85	22	or	or	CCONJ
ijassa-1009	85	23	not	not	PART
ijassa-1009	85	24	.	.	PUNCT
ijassa-1009	86	1	the	the	DET
ijassa-1009	86	2	approach	approach	NOUN
ijassa-1009	86	3	used	use	VERB
ijassa-1009	86	4	to	to	PART
ijassa-1009	86	5	avoid	avoid	VERB
ijassa-1009	86	6	taskspecific	taskspecific	ADJ
ijassa-1009	86	7	data	datum	NOUN
ijassa-1009	86	8	pre	pre	ADJ
ijassa-1009	86	9	-	-	ADJ
ijassa-1009	86	10	processing	processing	ADJ
ijassa-1009	86	11	methods	method	NOUN
ijassa-1009	86	12	supports	support	VERB
ijassa-1009	86	13	a	a	DET
ijassa-1009	86	14	better	well	ADJ
ijassa-1009	86	15	generalization	generalization	NOUN
ijassa-1009	86	16	ability	ability	NOUN
ijassa-1009	86	17	for	for	ADP
ijassa-1009	86	18	unseen	unseen	ADJ
ijassa-1009	86	19	data	datum	NOUN
ijassa-1009	86	20	.	.	PUNCT
ijassa-1009	87	1	the	the	DET
ijassa-1009	87	2	performance	performance	NOUN
ijassa-1009	87	3	of	of	ADP
ijassa-1009	87	4	the	the	DET
ijassa-1009	87	5	proposed	propose	VERB
ijassa-1009	87	6	method	method	NOUN
ijassa-1009	87	7	collaborates	collaborate	NOUN
ijassa-1009	87	8	on	on	ADP
ijassa-1009	87	9	a	a	DET
ijassa-1009	87	10	freely	freely	ADV
ijassa-1009	87	11	available	available	ADJ
ijassa-1009	87	12	dataset	dataset	NOUN
ijassa-1009	87	13	of	of	ADP
ijassa-1009	87	14	chest	chest	NOUN
ijassa-1009	87	15	deep	deep	ADJ
ijassa-1009	87	16	learning	learning	NOUN
ijassa-1009	87	17	techniques	technique	NOUN
ijassa-1009	87	18	for	for	ADP
ijassa-1009	87	19	detection	detection	NOUN
ijassa-1009	87	20	of	of	ADP
ijassa-1009	87	21	covid-19	covid-19	PROPN
ijassa-1009	87	22	45	45	NUM
ijassa-1009	87	23	copyright	copyright	NOUN
ijassa-1009	87	24	©	©	PROPN
ijassa-1009	87	25	2021	2021	NUM
ijassa-1009	87	26	assa	assa	NOUN
ijassa-1009	87	27	.	.	PUNCT
ijassa-1009	88	1	adv	adv	PROPN
ijassa-1009	88	2	.	.	PUNCT
ijassa-1009	89	1	in	in	ADP
ijassa-1009	89	2	systems	system	NOUN
ijassa-1009	89	3	science	science	NOUN
ijassa-1009	89	4	and	and	CCONJ
ijassa-1009	89	5	appl	appl	NOUN
ijassa-1009	89	6	.	.	PUNCT
ijassa-1009	90	1	(	(	PUNCT
ijassa-1009	90	2	2021	2021	NUM
ijassa-1009	90	3	)	)	PUNCT
ijassa-1009	91	1	x	x	X
ijassa-1009	91	2	-	-	NOUN
ijassa-1009	91	3	ray	ray	NOUN
ijassa-1009	91	4	and	and	CCONJ
ijassa-1009	91	5	ct	ct	NUM
ijassa-1009	91	6	images	image	NOUN
ijassa-1009	91	7	of	of	ADP
ijassa-1009	91	8	coronavirus	coronavirus	NOUN
ijassa-1009	91	9	patients	patient	NOUN
ijassa-1009	91	10	.	.	PUNCT
ijassa-1009	92	1	the	the	DET
ijassa-1009	92	2	best	good	ADJ
ijassa-1009	92	3	performance	performance	NOUN
ijassa-1009	92	4	was	be	AUX
ijassa-1009	92	5	achieved	achieve	VERB
ijassa-1009	92	6	by	by	ADP
ijassa-1009	92	7	the	the	DET
ijassa-1009	92	8	densenet121	densenet121	PROPN
ijassa-1009	92	9	feature	feature	NOUN
ijassa-1009	92	10	extractor	extractor	NOUN
ijassa-1009	92	11	with	with	ADP
ijassa-1009	92	12	a	a	DET
ijassa-1009	92	13	bagging	bag	VERB
ijassa-1009	92	14	tree	tree	NOUN
ijassa-1009	92	15	classifier	classifier	NOUN
ijassa-1009	92	16	which	which	PRON
ijassa-1009	92	17	was	be	AUX
ijassa-1009	92	18	a	a	DET
ijassa-1009	92	19	classification	classification	NOUN
ijassa-1009	92	20	accuracy	accuracy	NOUN
ijassa-1009	92	21	[	[	X
ijassa-1009	92	22	16	16	NUM
ijassa-1009	92	23	]	]	PUNCT
ijassa-1009	92	24	.	.	PUNCT
ijassa-1009	93	1	in	in	ADP
ijassa-1009	93	2	this	this	DET
ijassa-1009	93	3	report	report	NOUN
ijassa-1009	93	4	,	,	PUNCT
ijassa-1009	93	5	the	the	DET
ijassa-1009	93	6	authors	author	NOUN
ijassa-1009	93	7	implemented	implement	VERB
ijassa-1009	93	8	a	a	DET
ijassa-1009	93	9	deep	deep	ADJ
ijassa-1009	93	10	convolutional	convolutional	ADJ
ijassa-1009	93	11	neural	neural	ADJ
ijassa-1009	93	12	network	network	NOUN
ijassa-1009	93	13	architecture	architecture	NOUN
ijassa-1009	93	14	for	for	ADP
ijassa-1009	93	15	the	the	DET
ijassa-1009	93	16	detection	detection	NOUN
ijassa-1009	93	17	of	of	ADP
ijassa-1009	93	18	cases	case	NOUN
ijassa-1009	93	19	of	of	ADP
ijassa-1009	93	20	coronavirus	coronavirus	NOUN
ijassa-1009	93	21	in	in	ADP
ijassa-1009	93	22	humans	human	NOUN
ijassa-1009	93	23	from	from	ADP
ijassa-1009	93	24	chest	chest	NOUN
ijassa-1009	93	25	x	x	NOUN
ijassa-1009	93	26	-	-	NOUN
ijassa-1009	93	27	ray	ray	NOUN
ijassa-1009	93	28	(	(	PUNCT
ijassa-1009	93	29	cxr	cxr	NOUN
ijassa-1009	93	30	)	)	PUNCT
ijassa-1009	93	31	images	image	NOUN
ijassa-1009	93	32	,	,	PUNCT
ijassa-1009	93	33	called	call	VERB
ijassa-1009	93	34	covid	covid	NOUN
ijassa-1009	93	35	-	-	PUNCT
ijassa-1009	93	36	net	net	ADJ
ijassa-1009	93	37	,	,	PUNCT
ijassa-1009	93	38	accessible	accessible	ADJ
ijassa-1009	93	39	to	to	ADP
ijassa-1009	93	40	the	the	DET
ijassa-1009	93	41	general	general	ADJ
ijassa-1009	93	42	public	public	ADJ
ijassa-1009	93	43	dataset	dataset	NOUN
ijassa-1009	93	44	of	of	ADP
ijassa-1009	93	45	covid-19	covid-19	PROPN
ijassa-1009	93	46	with	with	ADP
ijassa-1009	93	47	the	the	DET
ijassa-1009	93	48	aid	aid	NOUN
ijassa-1009	93	49	of	of	ADP
ijassa-1009	93	50	an	an	DET
ijassa-1009	93	51	opensource	opensource	NOUN
ijassa-1009	93	52	.	.	PUNCT
ijassa-1009	94	1	in	in	ADP
ijassa-1009	94	2	addition	addition	NOUN
ijassa-1009	94	3	to	to	ADP
ijassa-1009	94	4	this	this	PRON
ijassa-1009	94	5	,	,	PUNCT
ijassa-1009	94	6	they	they	PRON
ijassa-1009	94	7	researched	research	VERB
ijassa-1009	94	8	how	how	SCONJ
ijassa-1009	94	9	covid	covid	PROPN
ijassa-1009	94	10	-	-	ADJ
ijassa-1009	94	11	net	net	NOUN
ijassa-1009	94	12	can	can	AUX
ijassa-1009	94	13	use	use	VERB
ijassa-1009	94	14	an	an	DET
ijassa-1009	94	15	explanatory	explanatory	ADJ
ijassa-1009	94	16	capacity	capacity	NOUN
ijassa-1009	94	17	approach	approach	NOUN
ijassa-1009	94	18	to	to	PART
ijassa-1009	94	19	make	make	VERB
ijassa-1009	94	20	predictions	prediction	NOUN
ijassa-1009	94	21	.	.	PUNCT
ijassa-1009	95	1	they	they	PRON
ijassa-1009	95	2	gained	gain	VERB
ijassa-1009	95	3	greater	great	ADJ
ijassa-1009	95	4	insights	insight	NOUN
ijassa-1009	95	5	into	into	ADP
ijassa-1009	95	6	crucial	crucial	ADJ
ijassa-1009	95	7	factors	factor	NOUN
ijassa-1009	95	8	linked	link	VERB
ijassa-1009	95	9	to	to	ADP
ijassa-1009	95	10	the	the	DET
ijassa-1009	95	11	covid-19	covid-19	PROPN
ijassa-1009	95	12	cases	case	NOUN
ijassa-1009	95	13	through	through	ADP
ijassa-1009	95	14	this	this	DET
ijassa-1009	95	15	approach	approach	NOUN
ijassa-1009	95	16	,	,	PUNCT
ijassa-1009	95	17	which	which	PRON
ijassa-1009	95	18	allowed	allow	VERB
ijassa-1009	95	19	doctors	doctor	NOUN
ijassa-1009	95	20	to	to	PART
ijassa-1009	95	21	enhance	enhance	VERB
ijassa-1009	95	22	screening	screen	VERB
ijassa-1009	95	23	.	.	PUNCT
ijassa-1009	96	1	the	the	DET
ijassa-1009	96	2	model	model	NOUN
ijassa-1009	96	3	obtained	obtain	VERB
ijassa-1009	96	4	is	be	AUX
ijassa-1009	96	5	a	a	DET
ijassa-1009	96	6	good	good	ADJ
ijassa-1009	96	7	one	one	NOUN
ijassa-1009	96	8	as	as	SCONJ
ijassa-1009	96	9	it	it	PRON
ijassa-1009	96	10	has	have	VERB
ijassa-1009	96	11	a	a	DET
ijassa-1009	96	12	high	high	ADJ
ijassa-1009	96	13	success	success	NOUN
ijassa-1009	96	14	ratio	ratio	NOUN
ijassa-1009	96	15	in	in	ADP
ijassa-1009	96	16	covid-19	covid-19	PROPN
ijassa-1009	96	17	virus	virus	NOUN
ijassa-1009	96	18	detection	detection	NOUN
ijassa-1009	96	19	and	and	CCONJ
ijassa-1009	96	20	can	can	AUX
ijassa-1009	96	21	also	also	ADV
ijassa-1009	96	22	reliably	reliably	ADV
ijassa-1009	96	23	distinguish	distinguish	VERB
ijassa-1009	96	24	non	non	ADJ
ijassa-1009	96	25	-	-	ADJ
ijassa-1009	96	26	covid	covid	ADJ
ijassa-1009	96	27	from	from	ADP
ijassa-1009	96	28	the	the	DET
ijassa-1009	96	29	chest	chest	NOUN
ijassa-1009	96	30	x	x	NOUN
ijassa-1009	96	31	-	-	NOUN
ijassa-1009	96	32	ray	ray	NOUN
ijassa-1009	96	33	of	of	ADP
ijassa-1009	96	34	a	a	DET
ijassa-1009	96	35	human	human	NOUN
ijassa-1009	96	36	[	[	X
ijassa-1009	96	37	17	17	NUM
ijassa-1009	96	38	]	]	PUNCT
ijassa-1009	96	39	.	.	PUNCT
ijassa-1009	97	1	but	but	CCONJ
ijassa-1009	97	2	also	also	ADV
ijassa-1009	97	3	,	,	PUNCT
ijassa-1009	97	4	a	a	DET
ijassa-1009	97	5	slight	slight	ADJ
ijassa-1009	97	6	problem	problem	NOUN
ijassa-1009	97	7	would	would	AUX
ijassa-1009	97	8	be	be	AUX
ijassa-1009	97	9	that	that	SCONJ
ijassa-1009	97	10	only	only	ADV
ijassa-1009	97	11	covid	covid	PROPN
ijassa-1009	97	12	-	-	PUNCT
ijassa-1009	97	13	net	net	NOUN
ijassa-1009	97	14	is	be	AUX
ijassa-1009	97	15	taking	take	VERB
ijassa-1009	97	16	the	the	DET
ijassa-1009	97	17	detection	detection	NOUN
ijassa-1009	97	18	decisions	decision	NOUN
ijassa-1009	97	19	.	.	PUNCT
ijassa-1009	98	1	mahesh	mahesh	PROPN
ijassa-1009	98	2	gour	gour	PROPN
ijassa-1009	98	3	and	and	CCONJ
ijassa-1009	98	4	sweta	sweta	PROPN
ijassa-1009	98	5	jain	jain	PROPN
ijassa-1009	98	6	introduced	introduce	VERB
ijassa-1009	98	7	a	a	DET
ijassa-1009	98	8	novel	novel	NOUN
ijassa-1009	98	9	stacked	stack	VERB
ijassa-1009	98	10	convolutional	convolutional	ADJ
ijassa-1009	98	11	neural	neural	ADJ
ijassa-1009	98	12	network	network	NOUN
ijassa-1009	98	13	for	for	ADP
ijassa-1009	98	14	the	the	DET
ijassa-1009	98	15	automatic	automatic	ADJ
ijassa-1009	98	16	analysis	analysis	NOUN
ijassa-1009	98	17	and	and	CCONJ
ijassa-1009	98	18	diagnosis	diagnosis	NOUN
ijassa-1009	98	19	of	of	ADP
ijassa-1009	98	20	the	the	DET
ijassa-1009	98	21	covid-19	covid-19	PROPN
ijassa-1009	98	22	from	from	ADP
ijassa-1009	98	23	the	the	DET
ijassa-1009	98	24	chest	chest	NOUN
ijassa-1009	98	25	x	x	NOUN
ijassa-1009	98	26	-	-	NOUN
ijassa-1009	98	27	ray	ray	NOUN
ijassa-1009	98	28	images	image	NOUN
ijassa-1009	98	29	of	of	ADP
ijassa-1009	98	30	the	the	DET
ijassa-1009	98	31	dataset	dataset	NOUN
ijassa-1009	98	32	.	.	PUNCT
ijassa-1009	99	1	the	the	DET
ijassa-1009	99	2	authors	author	NOUN
ijassa-1009	99	3	obtain	obtain	VERB
ijassa-1009	99	4	different	different	ADJ
ijassa-1009	99	5	sub	sub	NOUN
ijassa-1009	99	6	-	-	NOUN
ijassa-1009	99	7	models	model	NOUN
ijassa-1009	99	8	from	from	ADP
ijassa-1009	99	9	vgg19	vgg19	PROPN
ijassa-1009	99	10	and	and	CCONJ
ijassa-1009	99	11	create	create	VERB
ijassa-1009	99	12	a	a	DET
ijassa-1009	99	13	new	new	ADJ
ijassa-1009	99	14	30	30	NUM
ijassa-1009	99	15	layered	layered	ADJ
ijassa-1009	99	16	cnn	cnn	PROPN
ijassa-1009	99	17	model	model	NOUN
ijassa-1009	99	18	called	call	VERB
ijassa-1009	99	19	covnet30	covnet30	NOUN
ijassa-1009	100	1	[	[	X
ijassa-1009	100	2	18	18	NUM
ijassa-1009	100	3	]	]	PUNCT
ijassa-1009	100	4	.	.	PUNCT
ijassa-1009	101	1	for	for	ADP
ijassa-1009	101	2	the	the	DET
ijassa-1009	101	3	training	training	NOUN
ijassa-1009	101	4	and	and	CCONJ
ijassa-1009	101	5	creation	creation	NOUN
ijassa-1009	101	6	of	of	ADP
ijassa-1009	101	7	our	our	PRON
ijassa-1009	101	8	model	model	NOUN
ijassa-1009	101	9	,	,	PUNCT
ijassa-1009	101	10	have	have	AUX
ijassa-1009	101	11	used	use	VERB
ijassa-1009	101	12	heterogeneous	heterogeneous	ADJ
ijassa-1009	101	13	online	online	ADJ
ijassa-1009	101	14	sources	source	NOUN
ijassa-1009	101	15	for	for	ADP
ijassa-1009	101	16	data	data	NOUN
ijassa-1009	101	17	collection	collection	NOUN
ijassa-1009	101	18	.	.	PUNCT
ijassa-1009	102	1	our	our	PRON
ijassa-1009	102	2	dataset	dataset	NOUN
ijassa-1009	102	3	includes	include	VERB
ijassa-1009	102	4	images	image	NOUN
ijassa-1009	102	5	under	under	ADP
ijassa-1009	102	6	2	2	NUM
ijassa-1009	102	7	categories	category	NOUN
ijassa-1009	102	8	covid19	covid19	NOUN
ijassa-1009	102	9	chest	chest	NOUN
ijassa-1009	102	10	x	x	NOUN
ijassa-1009	102	11	-	-	NOUN
ijassa-1009	102	12	ray	ray	NOUN
ijassa-1009	102	13	images	image	NOUN
ijassa-1009	102	14	and	and	CCONJ
ijassa-1009	102	15	normal	normal	ADJ
ijassa-1009	102	16	chest	chest	NOUN
ijassa-1009	102	17	x	x	NOUN
ijassa-1009	102	18	-	-	NOUN
ijassa-1009	102	19	ray	ray	NOUN
ijassa-1009	102	20	images	image	NOUN
ijassa-1009	102	21	[	[	X
ijassa-1009	102	22	19,20	19,20	X
ijassa-1009	102	23	]	]	PUNCT
ijassa-1009	102	24	.	.	PUNCT
ijassa-1009	103	1	during	during	ADP
ijassa-1009	103	2	the	the	DET
ijassa-1009	103	3	development	development	NOUN
ijassa-1009	103	4	of	of	ADP
ijassa-1009	103	5	classification	classification	NOUN
ijassa-1009	103	6	models	model	NOUN
ijassa-1009	103	7	,	,	PUNCT
ijassa-1009	103	8	the	the	DET
ijassa-1009	103	9	initial	initial	ADJ
ijassa-1009	103	10	stage	stage	NOUN
ijassa-1009	103	11	included	include	VERB
ijassa-1009	103	12	the	the	DET
ijassa-1009	103	13	merging	merging	NOUN
ijassa-1009	103	14	of	of	ADP
ijassa-1009	103	15	the	the	DET
ijassa-1009	103	16	following	follow	VERB
ijassa-1009	103	17	github	github	PROPN
ijassa-1009	103	18	repositories	repository	NOUN
ijassa-1009	103	19	and	and	CCONJ
ijassa-1009	103	20	kaggle	kaggle	VERB
ijassa-1009	103	21	resources	resource	NOUN
ijassa-1009	103	22	which	which	PRON
ijassa-1009	103	23	maybe	maybe	ADV
ijassa-1009	103	24	have	have	AUX
ijassa-1009	103	25	been	be	AUX
ijassa-1009	103	26	updated	update	VERB
ijassa-1009	103	27	even	even	ADV
ijassa-1009	103	28	in	in	ADP
ijassa-1009	103	29	our	our	PRON
ijassa-1009	103	30	implementation	implementation	NOUN
ijassa-1009	103	31	.	.	PUNCT
ijassa-1009	104	1	we	we	PRON
ijassa-1009	104	2	would	would	AUX
ijassa-1009	104	3	like	like	VERB
ijassa-1009	104	4	to	to	PART
ijassa-1009	104	5	acknowledge	acknowledge	VERB
ijassa-1009	104	6	them	they	PRON
ijassa-1009	104	7	for	for	ADP
ijassa-1009	104	8	their	their	PRON
ijassa-1009	104	9	contributions	contribution	NOUN
ijassa-1009	104	10	to	to	ADP
ijassa-1009	104	11	this	this	DET
ijassa-1009	104	12	research	research	NOUN
ijassa-1009	104	13	work	work	NOUN
ijassa-1009	104	14	and	and	CCONJ
ijassa-1009	104	15	also	also	ADV
ijassa-1009	104	16	making	make	VERB
ijassa-1009	104	17	the	the	DET
ijassa-1009	104	18	data	data	NOUN
ijassa-1009	104	19	sources	source	NOUN
ijassa-1009	104	20	publicly	publicly	ADV
ijassa-1009	104	21	available	available	ADJ
ijassa-1009	104	22	.	.	PUNCT
ijassa-1009	105	1	2.1	2.1	NUM
ijassa-1009	105	2	.	.	PUNCT
ijassa-1009	106	1	github	github	PROPN
ijassa-1009	106	2	repositories	repositorie	VERB
ijassa-1009	106	3	the	the	DET
ijassa-1009	106	4	links	link	NOUN
ijassa-1009	106	5	are	be	AUX
ijassa-1009	106	6	provided	provide	VERB
ijassa-1009	106	7	below	below	ADP
ijassa-1009	106	8	:	:	PUNCT
ijassa-1009	106	9	•	•	NUM
ijassa-1009	106	10	https://github.com/ieee8023/covid-chestxray-dataset	https://github.com/ieee8023/covid-chestxray-dataset	X
ijassa-1009	106	11	•	•	NOUN
ijassa-1009	106	12	https://github.com/shervinmin/deepcovid	https://github.com/shervinmin/deepcovid	ADJ
ijassa-1009	106	13	•	•	NUM
ijassa-1009	106	14	https://www.dropbox.com/s/09b5nutjxotmftm/data_upload_v2.zip?dl=0	https://www.dropbox.com/s/09b5nutjxotmftm/data_upload_v2.zip?dl=0	PROPN
ijassa-1009	106	15	•	•	NOUN
ijassa-1009	106	16	https://github.com/cssegisanddata/covid-19	https://github.com/cssegisanddata/covid-19	PROPN
ijassa-1009	106	17	2.2	2.2	NUM
ijassa-1009	106	18	.	.	PUNCT
ijassa-1009	107	1	kaggle	kaggle	NOUN
ijassa-1009	107	2	repositories	repository	NOUN
ijassa-1009	107	3	the	the	DET
ijassa-1009	107	4	links	link	NOUN
ijassa-1009	107	5	are	be	AUX
ijassa-1009	107	6	provided	provide	VERB
ijassa-1009	107	7	below	below	ADP
ijassa-1009	107	8	:	:	PUNCT
ijassa-1009	107	9	•	•	NUM
ijassa-1009	107	10	https://www.kaggle.com/tawsifurrahman/covid19-radiography-database	https://www.kaggle.com/tawsifurrahman/covid19-radiography-database	PROPN
ijassa-1009	107	11	•	•	NOUN
ijassa-1009	107	12	https://www.kaggle.com/bachrr/covid-chest-xray?select=images	https://www.kaggle.com/bachrr/covid-chest-xray?select=image	NOUN
ijassa-1009	107	13	•	•	NOUN
ijassa-1009	107	14	https://www.qmenta.com/covid-19-kaggle-chest-x-ray-normal/	https://www.qmenta.com/covid-19-kaggle-chest-x-ray-normal/	PRON
ijassa-1009	107	15	the	the	DET
ijassa-1009	107	16	reason	reason	NOUN
ijassa-1009	107	17	behind	behind	ADP
ijassa-1009	107	18	creating	create	VERB
ijassa-1009	107	19	the	the	DET
ijassa-1009	107	20	new	new	ADJ
ijassa-1009	107	21	dataset	dataset	NOUN
ijassa-1009	107	22	is	be	AUX
ijassa-1009	107	23	that	that	SCONJ
ijassa-1009	107	24	researchers	researcher	NOUN
ijassa-1009	107	25	till	till	AUX
ijassa-1009	107	26	now	now	ADV
ijassa-1009	107	27	have	have	AUX
ijassa-1009	107	28	used	use	VERB
ijassa-1009	107	29	a	a	DET
ijassa-1009	107	30	smaller	small	ADJ
ijassa-1009	107	31	number	number	NOUN
ijassa-1009	107	32	of	of	ADP
ijassa-1009	107	33	covid	covid	PROPN
ijassa-1009	107	34	chest	chest	PROPN
ijassa-1009	107	35	x	x	NOUN
ijassa-1009	107	36	-	-	NOUN
ijassa-1009	107	37	ray	ray	NOUN
ijassa-1009	107	38	images	image	NOUN
ijassa-1009	107	39	which	which	PRON
ijassa-1009	107	40	is	be	AUX
ijassa-1009	107	41	not	not	PART
ijassa-1009	107	42	enough	enough	ADJ
ijassa-1009	107	43	to	to	PART
ijassa-1009	107	44	validate	validate	VERB
ijassa-1009	107	45	or	or	CCONJ
ijassa-1009	107	46	justify	justify	VERB
ijassa-1009	107	47	that	that	SCONJ
ijassa-1009	107	48	the	the	DET
ijassa-1009	107	49	model	model	NOUN
ijassa-1009	107	50	will	will	AUX
ijassa-1009	107	51	be	be	AUX
ijassa-1009	107	52	accurate	accurate	ADJ
ijassa-1009	107	53	in	in	ADP
ijassa-1009	107	54	any	any	DET
ijassa-1009	107	55	study	study	NOUN
ijassa-1009	107	56	.	.	PUNCT
ijassa-1009	108	1	so	so	ADV
ijassa-1009	108	2	,	,	PUNCT
ijassa-1009	108	3	a	a	DET
ijassa-1009	108	4	huge	huge	ADJ
ijassa-1009	108	5	dataset	dataset	NOUN
ijassa-1009	108	6	has	have	AUX
ijassa-1009	108	7	been	be	AUX
ijassa-1009	108	8	used	use	VERB
ijassa-1009	108	9	i.e.	i.e.	ADV
ijassa-1009	108	10	a	a	DET
ijassa-1009	108	11	greater	great	ADJ
ijassa-1009	108	12	number	number	NOUN
ijassa-1009	108	13	of	of	ADP
ijassa-1009	108	14	images	image	NOUN
ijassa-1009	108	15	compared	compare	VERB
ijassa-1009	108	16	to	to	ADP
ijassa-1009	108	17	other	other	ADJ
ijassa-1009	108	18	researchers	researcher	NOUN
ijassa-1009	108	19	’	'	PUNCT
ijassa-1009	108	20	datasets	dataset	NOUN
ijassa-1009	108	21	and	and	CCONJ
ijassa-1009	108	22	is	be	AUX
ijassa-1009	108	23	getting	get	VERB
ijassa-1009	108	24	better	well	ADJ
ijassa-1009	108	25	accuracy	accuracy	NOUN
ijassa-1009	108	26	for	for	ADP
ijassa-1009	108	27	some	some	DET
ijassa-1009	108	28	algorithms	algorithm	NOUN
ijassa-1009	108	29	in	in	ADP
ijassa-1009	108	30	our	our	PRON
ijassa-1009	108	31	model	model	NOUN
ijassa-1009	108	32	.	.	PUNCT
ijassa-1009	109	1	a	a	DET
ijassa-1009	109	2	heterogeneous	heterogeneous	ADJ
ijassa-1009	109	3	online	online	ADJ
ijassa-1009	109	4	data	datum	NOUN
ijassa-1009	109	5	collection	collection	NOUN
ijassa-1009	109	6	sources	source	NOUN
ijassa-1009	109	7	have	have	AUX
ijassa-1009	109	8	been	be	AUX
ijassa-1009	109	9	used	use	VERB
ijassa-1009	109	10	for	for	ADP
ijassa-1009	109	11	the	the	DET
ijassa-1009	109	12	training	training	NOUN
ijassa-1009	109	13	and	and	CCONJ
ijassa-1009	109	14	development	development	NOUN
ijassa-1009	109	15	of	of	ADP
ijassa-1009	109	16	our	our	PRON
ijassa-1009	109	17	model	model	NOUN
ijassa-1009	109	18	.	.	PUNCT
ijassa-1009	110	1	the	the	DET
ijassa-1009	110	2	initial	initial	ADJ
ijassa-1009	110	3	stage	stage	NOUN
ijassa-1009	110	4	involved	involve	VERB
ijassa-1009	110	5	combining	combine	VERB
ijassa-1009	110	6	the	the	DET
ijassa-1009	110	7	dataset	dataset	NOUN
ijassa-1009	110	8	from	from	ADP
ijassa-1009	110	9	various	various	ADJ
ijassa-1009	110	10	credible	credible	ADJ
ijassa-1009	110	11	sources	source	NOUN
ijassa-1009	110	12	during	during	ADP
ijassa-1009	110	13	the	the	DET
ijassa-1009	110	14	creation	creation	NOUN
ijassa-1009	110	15	of	of	ADP
ijassa-1009	110	16	classification	classification	NOUN
ijassa-1009	110	17	models	model	NOUN
ijassa-1009	110	18	and	and	CCONJ
ijassa-1009	110	19	also	also	ADV
ijassa-1009	110	20	making	make	VERB
ijassa-1009	110	21	the	the	DET
ijassa-1009	110	22	data	data	NOUN
ijassa-1009	110	23	sources	source	NOUN
ijassa-1009	110	24	publicly	publicly	ADV
ijassa-1009	110	25	accessible	accessible	ADJ
ijassa-1009	110	26	[	[	X
ijassa-1009	110	27	21	21	NUM
ijassa-1009	110	28	,	,	PUNCT
ijassa-1009	110	29	22	22	NUM
ijassa-1009	110	30	]	]	PUNCT
ijassa-1009	110	31	.	.	PUNCT
ijassa-1009	111	1	3	3	X
ijassa-1009	111	2	.	.	X
ijassa-1009	111	3	dataset	dataset	ADJ
ijassa-1009	111	4	collection	collection	NOUN
ijassa-1009	111	5	the	the	DET
ijassa-1009	111	6	dataset	dataset	NOUN
ijassa-1009	111	7	is	be	AUX
ijassa-1009	111	8	generated	generate	VERB
ijassa-1009	111	9	by	by	ADP
ijassa-1009	111	10	collecting	collect	VERB
ijassa-1009	111	11	a	a	DET
ijassa-1009	111	12	set	set	NOUN
ijassa-1009	111	13	of	of	ADP
ijassa-1009	111	14	chest	chest	NOUN
ijassa-1009	111	15	x	x	NOUN
ijassa-1009	111	16	-	-	NOUN
ijassa-1009	111	17	ray	ray	NOUN
ijassa-1009	111	18	images	image	NOUN
ijassa-1009	111	19	of	of	ADP
ijassa-1009	111	20	covid	covid	PROPN
ijassa-1009	111	21	-19	-19	PROPN
ijassa-1009	111	22	from	from	ADP
ijassa-1009	111	23	heterogeneous	heterogeneous	ADJ
ijassa-1009	111	24	online	online	ADJ
ijassa-1009	111	25	public	public	ADJ
ijassa-1009	111	26	sources	source	NOUN
ijassa-1009	111	27	like	like	ADP
ijassa-1009	111	28	github	github	PROPN
ijassa-1009	111	29	,	,	PUNCT
ijassa-1009	111	30	kaggle	kaggle	NOUN
ijassa-1009	111	31	,	,	PUNCT
ijassa-1009	111	32	and	and	CCONJ
ijassa-1009	111	33	certain	certain	ADJ
ijassa-1009	111	34	data	datum	NOUN
ijassa-1009	111	35	sources	source	NOUN
ijassa-1009	111	36	mentioned	mention	VERB
ijassa-1009	111	37	in	in	ADP
ijassa-1009	111	38	multiple	multiple	ADJ
ijassa-1009	111	39	research	research	NOUN
ijassa-1009	111	40	papers	paper	NOUN
ijassa-1009	111	41	.	.	PUNCT
ijassa-1009	112	1	in	in	ADP
ijassa-1009	112	2	the	the	DET
ijassa-1009	112	3	new	new	ADJ
ijassa-1009	112	4	dataset	dataset	NOUN
ijassa-1009	112	5	created	create	VERB
ijassa-1009	112	6	,	,	PUNCT
ijassa-1009	112	7	there	there	PRON
ijassa-1009	112	8	are	be	VERB
ijassa-1009	112	9	4539	4539	NUM
ijassa-1009	112	10	number	number	NOUN
ijassa-1009	112	11	of	of	ADP
ijassa-1009	112	12	covid-19	covid-19	PROPN
ijassa-1009	112	13	chest	chest	NOUN
ijassa-1009	112	14	x	x	NOUN
ijassa-1009	112	15	-	-	NOUN
ijassa-1009	112	16	ray	ray	NOUN
ijassa-1009	112	17	images	image	NOUN
ijassa-1009	112	18	and	and	CCONJ
ijassa-1009	112	19	5961	5961	NUM
ijassa-1009	112	20	number	number	NOUN
ijassa-1009	112	21	of	of	ADP
ijassa-1009	112	22	non	non	ADJ
ijassa-1009	112	23	-	-	ADJ
ijassa-1009	112	24	covid-19	covid-19	ADJ
ijassa-1009	112	25	chest	chest	NOUN
ijassa-1009	112	26	x	x	NOUN
ijassa-1009	112	27	-	-	NOUN
ijassa-1009	112	28	ray	ray	NOUN
ijassa-1009	112	29	images	image	NOUN
ijassa-1009	112	30	,	,	PUNCT
ijassa-1009	112	31	used	use	VERB
ijassa-1009	112	32	for	for	ADP
ijassa-1009	112	33	training	training	NOUN
ijassa-1009	112	34	and	and	CCONJ
ijassa-1009	112	35	testing	testing	NOUN
ijassa-1009	112	36	using	use	VERB
ijassa-1009	112	37	deep	deep	ADJ
ijassa-1009	112	38	learning	learning	NOUN
ijassa-1009	112	39	models	model	NOUN
ijassa-1009	112	40	.	.	PUNCT
ijassa-1009	113	1	a	a	DET
ijassa-1009	113	2	total	total	NOUN
ijassa-1009	113	3	of	of	ADP
ijassa-1009	113	4	10500	10500	NUM
ijassa-1009	113	5	images	image	NOUN
ijassa-1009	113	6	was	be	AUX
ijassa-1009	113	7	collected	collect	VERB
ijassa-1009	113	8	,	,	PUNCT
ijassa-1009	113	9	in	in	ADP
ijassa-1009	113	10	that	that	DET
ijassa-1009	113	11	8400	8400	NUM
ijassa-1009	113	12	was	be	AUX
ijassa-1009	113	13	used	use	VERB
ijassa-1009	113	14	for	for	ADP
ijassa-1009	113	15	the	the	DET
ijassa-1009	113	16	training	training	NOUN
ijassa-1009	113	17	phase	phase	NOUN
ijassa-1009	113	18	of	of	ADP
ijassa-1009	113	19	the	the	DET
ijassa-1009	113	20	model	model	NOUN
ijassa-1009	113	21	and	and	CCONJ
ijassa-1009	113	22	the	the	DET
ijassa-1009	113	23	rest	rest	NOUN
ijassa-1009	113	24	2100	2100	NUM
ijassa-1009	113	25	was	be	AUX
ijassa-1009	113	26	46	46	NUM
ijassa-1009	113	27	naveen	naveen	PROPN
ijassa-1009	113	28	et	et	PROPN
ijassa-1009	113	29	al	al	PROPN
ijassa-1009	113	30	.	.	PUNCT
ijassa-1009	114	1	copyright	copyright	PROPN
ijassa-1009	114	2	©	©	PROPN
ijassa-1009	114	3	2021	2021	NUM
ijassa-1009	114	4	assa	assa	NOUN
ijassa-1009	114	5	.	.	PUNCT
ijassa-1009	115	1	adv	adv	PROPN
ijassa-1009	115	2	.	.	PUNCT
ijassa-1009	116	1	in	in	ADP
ijassa-1009	116	2	systems	system	NOUN
ijassa-1009	116	3	science	science	NOUN
ijassa-1009	116	4	and	and	CCONJ
ijassa-1009	116	5	appl	appl	NOUN
ijassa-1009	116	6	.	.	PUNCT
ijassa-1009	117	1	(	(	PUNCT
ijassa-1009	117	2	2021	2021	NUM
ijassa-1009	117	3	)	)	PUNCT
ijassa-1009	117	4	used	use	VERB
ijassa-1009	117	5	for	for	ADP
ijassa-1009	117	6	the	the	DET
ijassa-1009	117	7	testing	testing	NOUN
ijassa-1009	117	8	phase	phase	NOUN
ijassa-1009	117	9	of	of	ADP
ijassa-1009	117	10	the	the	DET
ijassa-1009	117	11	model	model	NOUN
ijassa-1009	117	12	.	.	PUNCT
ijassa-1009	118	1	the	the	DET
ijassa-1009	118	2	training	training	NOUN
ijassa-1009	118	3	of	of	ADP
ijassa-1009	118	4	models	model	NOUN
ijassa-1009	118	5	also	also	ADV
ijassa-1009	118	6	includes	include	VERB
ijassa-1009	118	7	data	data	NOUN
ijassa-1009	118	8	argumentation	argumentation	NOUN
ijassa-1009	118	9	(	(	PUNCT
ijassa-1009	118	10	image	image	NOUN
ijassa-1009	118	11	data	datum	NOUN
ijassa-1009	118	12	generator	generator	PROPN
ijassa-1009	118	13	)	)	PUNCT
ijassa-1009	118	14	for	for	ADP
ijassa-1009	118	15	increasing	increase	VERB
ijassa-1009	118	16	the	the	DET
ijassa-1009	118	17	dataset	dataset	NOUN
ijassa-1009	118	18	size	size	NOUN
ijassa-1009	118	19	for	for	ADP
ijassa-1009	118	20	both	both	DET
ijassa-1009	118	21	training	training	NOUN
ijassa-1009	118	22	and	and	CCONJ
ijassa-1009	118	23	testing	testing	NOUN
ijassa-1009	118	24	[	[	X
ijassa-1009	118	25	23	23	NUM
ijassa-1009	118	26	,	,	PUNCT
ijassa-1009	118	27	24	24	NUM
ijassa-1009	118	28	]	]	PUNCT
ijassa-1009	118	29	.	.	PUNCT
ijassa-1009	119	1	fig	fig	NOUN
ijassa-1009	119	2	.	.	PUNCT
ijassa-1009	120	1	3.1	3.1	NUM
ijassa-1009	120	2	.	.	PUNCT
ijassa-1009	121	1	x	x	X
ijassa-1009	121	2	-	-	NOUN
ijassa-1009	121	3	ray	ray	NOUN
ijassa-1009	121	4	images	image	NOUN
ijassa-1009	121	5	of	of	ADP
ijassa-1009	121	6	covid	covid	ADJ
ijassa-1009	121	7	infected	infected	ADJ
ijassa-1009	121	8	patients	patient	NOUN
ijassa-1009	121	9	.	.	PUNCT
ijassa-1009	122	1	fig.3.2	fig.3.2	NOUN
ijassa-1009	122	2	.	.	PUNCT
ijassa-1009	123	1	x	x	X
ijassa-1009	123	2	-	-	PUNCT
ijassa-1009	123	3	ray	ray	NOUN
ijassa-1009	123	4	images	image	NOUN
ijassa-1009	123	5	of	of	ADP
ijassa-1009	123	6	normal	normal	ADJ
ijassa-1009	123	7	patients	patient	NOUN
ijassa-1009	123	8	.	.	PUNCT
ijassa-1009	124	1	after	after	ADP
ijassa-1009	124	2	data	data	NOUN
ijassa-1009	124	3	argumentation	argumentation	NOUN
ijassa-1009	124	4	8736	8736	NUM
ijassa-1009	124	5	training	training	NOUN
ijassa-1009	124	6	images	image	NOUN
ijassa-1009	124	7	were	be	AUX
ijassa-1009	124	8	generated	generate	VERB
ijassa-1009	124	9	and	and	CCONJ
ijassa-1009	124	10	2220	2220	NUM
ijassa-1009	124	11	testing	testing	NOUN
ijassa-1009	124	12	images	image	NOUN
ijassa-1009	124	13	.	.	PUNCT
ijassa-1009	125	1	4	4	X
ijassa-1009	125	2	.	.	NOUN
ijassa-1009	125	3	methodology	methodology	NOUN
ijassa-1009	125	4	diagnostic	diagnostic	ADJ
ijassa-1009	125	5	imaging	imaging	NOUN
ijassa-1009	125	6	modalities	modality	NOUN
ijassa-1009	125	7	,	,	PUNCT
ijassa-1009	125	8	such	such	ADJ
ijassa-1009	125	9	as	as	ADP
ijassa-1009	125	10	chest	chest	NOUN
ijassa-1009	125	11	x	x	NOUN
ijassa-1009	125	12	-	-	NOUN
ijassa-1009	125	13	ray	ray	NOUN
ijassa-1009	125	14	images	image	NOUN
ijassa-1009	125	15	are	be	AUX
ijassa-1009	125	16	playing	play	VERB
ijassa-1009	125	17	an	an	DET
ijassa-1009	125	18	important	important	ADJ
ijassa-1009	125	19	role	role	NOUN
ijassa-1009	125	20	in	in	ADP
ijassa-1009	125	21	confirming	confirm	VERB
ijassa-1009	125	22	the	the	DET
ijassa-1009	125	23	primary	primary	ADJ
ijassa-1009	125	24	diagnosis	diagnosis	NOUN
ijassa-1009	125	25	from	from	ADP
ijassa-1009	125	26	the	the	DET
ijassa-1009	125	27	polymerize	polymerize	NOUN
ijassa-1009	125	28	chain	chain	NOUN
ijassa-1009	125	29	reaction	reaction	NOUN
ijassa-1009	125	30	test	test	NOUN
ijassa-1009	125	31	for	for	ADP
ijassa-1009	125	32	covid-19	covid-19	PROPN
ijassa-1009	125	33	.	.	PUNCT
ijassa-1009	126	1	convolutional	convolutional	ADJ
ijassa-1009	126	2	neural	neural	ADJ
ijassa-1009	126	3	networks	network	NOUN
ijassa-1009	126	4	are	be	AUX
ijassa-1009	126	5	algorithms	algorithm	NOUN
ijassa-1009	126	6	that	that	PRON
ijassa-1009	126	7	are	be	AUX
ijassa-1009	126	8	used	use	VERB
ijassa-1009	126	9	to	to	PART
ijassa-1009	126	10	predict	predict	VERB
ijassa-1009	126	11	the	the	DET
ijassa-1009	126	12	class	class	NOUN
ijassa-1009	126	13	of	of	ADP
ijassa-1009	126	14	images	image	NOUN
ijassa-1009	126	15	[	[	X
ijassa-1009	126	16	25	25	NUM
ijassa-1009	126	17	]	]	PUNCT
ijassa-1009	126	18	.	.	PUNCT
ijassa-1009	127	1	in	in	ADP
ijassa-1009	127	2	our	our	PRON
ijassa-1009	127	3	proposed	propose	VERB
ijassa-1009	127	4	work	work	NOUN
ijassa-1009	127	5	,	,	PUNCT
ijassa-1009	127	6	deep	deep	ADJ
ijassa-1009	127	7	learning	learning	NOUN
ijassa-1009	127	8	techniques	technique	NOUN
ijassa-1009	127	9	have	have	AUX
ijassa-1009	127	10	been	be	AUX
ijassa-1009	127	11	applied	apply	VERB
ijassa-1009	127	12	like	like	ADP
ijassa-1009	127	13	vgg16	vgg16	NOUN
ijassa-1009	127	14	,	,	PUNCT
ijassa-1009	127	15	resnet50	resnet50	NOUN
ijassa-1009	127	16	,	,	PUNCT
ijassa-1009	127	17	inceptionv3	inceptionv3	NOUN
ijassa-1009	127	18	,	,	PUNCT
ijassa-1009	127	19	and	and	CCONJ
ijassa-1009	127	20	xceptionfor	xceptionfor	ADP
ijassa-1009	127	21	covid-19	covid-19	PROPN
ijassa-1009	127	22	prediction	prediction	NOUN
ijassa-1009	127	23	.	.	PUNCT
ijassa-1009	128	1	preprocessing	preprocessing	NOUN
ijassa-1009	128	2	of	of	ADP
ijassa-1009	128	3	data	datum	NOUN
ijassa-1009	128	4	has	have	AUX
ijassa-1009	128	5	been	be	AUX
ijassa-1009	128	6	implemented	implement	VERB
ijassa-1009	128	7	to	to	PART
ijassa-1009	128	8	establish	establish	VERB
ijassa-1009	128	9	the	the	DET
ijassa-1009	128	10	same	same	ADJ
ijassa-1009	128	11	size	size	NOUN
ijassa-1009	128	12	for	for	ADP
ijassa-1009	128	13	all	all	DET
ijassa-1009	128	14	data	datum	NOUN
ijassa-1009	128	15	and	and	CCONJ
ijassa-1009	128	16	to	to	PART
ijassa-1009	128	17	normalize	normalize	VERB
ijassa-1009	128	18	the	the	DET
ijassa-1009	128	19	images	image	NOUN
ijassa-1009	128	20	in	in	ADP
ijassa-1009	128	21	the	the	DET
ijassa-1009	128	22	dataset	dataset	NOUN
ijassa-1009	128	23	.	.	PUNCT
ijassa-1009	129	1	different	different	ADJ
ijassa-1009	129	2	techniques	technique	NOUN
ijassa-1009	129	3	such	such	ADJ
ijassa-1009	129	4	as	as	ADP
ijassa-1009	129	5	image	image	NOUN
ijassa-1009	129	6	resizing	resizing	NOUN
ijassa-1009	129	7	,	,	PUNCT
ijassa-1009	129	8	image	image	NOUN
ijassa-1009	129	9	data	datum	NOUN
ijassa-1009	129	10	generator	generator	PROPN
ijassa-1009	129	11	,	,	PUNCT
ijassa-1009	129	12	data	datum	NOUN
ijassa-1009	129	13	labelling	labelling	NOUN
ijassa-1009	129	14	,	,	PUNCT
ijassa-1009	129	15	and	and	CCONJ
ijassa-1009	129	16	data	datum	NOUN
ijassa-1009	129	17	normalization	normalization	NOUN
ijassa-1009	129	18	has	have	AUX
ijassa-1009	129	19	been	be	AUX
ijassa-1009	129	20	applied	apply	VERB
ijassa-1009	129	21	to	to	ADP
ijassa-1009	129	22	the	the	DET
ijassa-1009	129	23	dataset	dataset	NOUN
ijassa-1009	129	24	.	.	PUNCT
ijassa-1009	130	1	deep	deep	ADJ
ijassa-1009	130	2	learning	learning	NOUN
ijassa-1009	130	3	techniques	technique	NOUN
ijassa-1009	130	4	for	for	ADP
ijassa-1009	130	5	detection	detection	NOUN
ijassa-1009	130	6	of	of	ADP
ijassa-1009	130	7	covid-19	covid-19	PROPN
ijassa-1009	130	8	47	47	NUM
ijassa-1009	130	9	copyright	copyright	NOUN
ijassa-1009	130	10	©	©	PROPN
ijassa-1009	130	11	2021	2021	NUM
ijassa-1009	130	12	assa	assa	NOUN
ijassa-1009	130	13	.	.	PUNCT
ijassa-1009	131	1	adv	adv	PROPN
ijassa-1009	131	2	.	.	PUNCT
ijassa-1009	132	1	in	in	ADP
ijassa-1009	132	2	systems	system	NOUN
ijassa-1009	132	3	science	science	NOUN
ijassa-1009	132	4	and	and	CCONJ
ijassa-1009	132	5	appl	appl	NOUN
ijassa-1009	132	6	.	.	PUNCT
ijassa-1009	133	1	(	(	PUNCT
ijassa-1009	133	2	2021	2021	NUM
ijassa-1009	133	3	)	)	PUNCT
ijassa-1009	133	4	fig	fig	NOUN
ijassa-1009	133	5	.	.	PUNCT
ijassa-1009	134	1	4.1	4.1	NUM
ijassa-1009	134	2	.	.	PUNCT
ijassa-1009	134	3	block	block	NOUN
ijassa-1009	134	4	diagram	diagram	NOUN
ijassa-1009	134	5	of	of	ADP
ijassa-1009	134	6	the	the	DET
ijassa-1009	134	7	model	model	NOUN
ijassa-1009	134	8	.	.	PUNCT
ijassa-1009	134	9	.	.	PUNCT
ijassa-1009	135	1	the	the	DET
ijassa-1009	135	2	dataset	dataset	NOUN
ijassa-1009	135	3	is	be	AUX
ijassa-1009	135	4	prepared	prepare	VERB
ijassa-1009	135	5	for	for	ADP
ijassa-1009	135	6	the	the	DET
ijassa-1009	135	7	training	training	NOUN
ijassa-1009	135	8	and	and	CCONJ
ijassa-1009	135	9	testing	testing	NOUN
ijassa-1009	135	10	phase	phase	NOUN
ijassa-1009	135	11	by	by	ADP
ijassa-1009	135	12	applying	apply	VERB
ijassa-1009	135	13	the	the	DET
ijassa-1009	135	14	required	require	VERB
ijassa-1009	135	15	preprocessing	preprocessing	NOUN
ijassa-1009	135	16	.	.	PUNCT
ijassa-1009	136	1	then	then	ADV
ijassa-1009	136	2	,	,	PUNCT
ijassa-1009	136	3	the	the	DET
ijassa-1009	136	4	data	data	NOUN
ijassa-1009	136	5	is	be	AUX
ijassa-1009	136	6	split	split	VERB
ijassa-1009	136	7	into	into	ADP
ijassa-1009	136	8	an	an	DET
ijassa-1009	136	9	80:20	80:20	NUM
ijassa-1009	136	10	ratio	ratio	NOUN
ijassa-1009	136	11	for	for	ADP
ijassa-1009	136	12	training	training	NOUN
ijassa-1009	136	13	and	and	CCONJ
ijassa-1009	136	14	testing	test	VERB
ijassa-1009	136	15	the	the	DET
ijassa-1009	136	16	dataset	dataset	NOUN
ijassa-1009	136	17	to	to	PART
ijassa-1009	136	18	predict	predict	VERB
ijassa-1009	136	19	the	the	DET
ijassa-1009	136	20	outcome	outcome	NOUN
ijassa-1009	136	21	of	of	ADP
ijassa-1009	136	22	the	the	DET
ijassa-1009	136	23	chest	chest	NOUN
ijassa-1009	136	24	x	x	NOUN
ijassa-1009	136	25	-	-	NOUN
ijassa-1009	136	26	ray	ray	NOUN
ijassa-1009	136	27	image	image	NOUN
ijassa-1009	136	28	.	.	PUNCT
ijassa-1009	137	1	the	the	DET
ijassa-1009	137	2	deep	deep	ADJ
ijassa-1009	137	3	learning	learning	NOUN
ijassa-1009	137	4	models	model	NOUN
ijassa-1009	137	5	are	be	AUX
ijassa-1009	137	6	trained	train	VERB
ijassa-1009	137	7	for	for	ADP
ijassa-1009	137	8	500	500	NUM
ijassa-1009	137	9	epochs	epoch	NOUN
ijassa-1009	137	10	with	with	ADP
ijassa-1009	137	11	a	a	DET
ijassa-1009	137	12	batch	batch	NOUN
ijassa-1009	137	13	each	each	PRON
ijassa-1009	137	14	consisting	consist	VERB
ijassa-1009	137	15	of	of	ADP
ijassa-1009	137	16	32	32	NUM
ijassa-1009	137	17	images	image	NOUN
ijassa-1009	137	18	.	.	PUNCT
ijassa-1009	138	1	the	the	DET
ijassa-1009	138	2	requirement	requirement	NOUN
ijassa-1009	138	3	of	of	ADP
ijassa-1009	138	4	the	the	DET
ijassa-1009	138	5	model	model	NOUN
ijassa-1009	138	6	is	be	AUX
ijassa-1009	138	7	to	to	PART
ijassa-1009	138	8	recognize	recognize	VERB
ijassa-1009	138	9	the	the	DET
ijassa-1009	138	10	necessary	necessary	ADJ
ijassa-1009	138	11	features	feature	NOUN
ijassa-1009	138	12	from	from	ADP
ijassa-1009	138	13	the	the	DET
ijassa-1009	138	14	training	training	NOUN
ijassa-1009	138	15	phase	phase	NOUN
ijassa-1009	138	16	and	and	CCONJ
ijassa-1009	138	17	after	after	SCONJ
ijassa-1009	138	18	training	training	NOUN
ijassa-1009	138	19	make	make	VERB
ijassa-1009	138	20	the	the	DET
ijassa-1009	138	21	predictions	prediction	NOUN
ijassa-1009	138	22	and	and	CCONJ
ijassa-1009	138	23	classify	classify	VERB
ijassa-1009	138	24	the	the	DET
ijassa-1009	138	25	images	image	NOUN
ijassa-1009	138	26	.	.	PUNCT
ijassa-1009	139	1	in	in	ADP
ijassa-1009	139	2	this	this	DET
ijassa-1009	139	3	work	work	NOUN
ijassa-1009	139	4	,	,	PUNCT
ijassa-1009	139	5	the	the	DET
ijassa-1009	139	6	implementation	implementation	NOUN
ijassa-1009	139	7	of	of	ADP
ijassa-1009	139	8	all	all	DET
ijassa-1009	139	9	the	the	DET
ijassa-1009	139	10	architectures	architecture	NOUN
ijassa-1009	139	11	included	include	VERB
ijassa-1009	139	12	the	the	DET
ijassa-1009	139	13	addition	addition	NOUN
ijassa-1009	139	14	of	of	ADP
ijassa-1009	139	15	three	three	NUM
ijassa-1009	139	16	custom	custom	NOUN
ijassa-1009	139	17	layers	layer	NOUN
ijassa-1009	139	18	in	in	ADP
ijassa-1009	139	19	the	the	DET
ijassa-1009	139	20	pre	pre	ADJ
ijassa-1009	139	21	-	-	ADJ
ijassa-1009	139	22	trained	train	VERB
ijassa-1009	139	23	models	model	NOUN
ijassa-1009	139	24	for	for	ADP
ijassa-1009	139	25	training	train	VERB
ijassa-1009	139	26	the	the	DET
ijassa-1009	139	27	dataset	dataset	NOUN
ijassa-1009	139	28	.	.	PUNCT
ijassa-1009	140	1	the	the	DET
ijassa-1009	140	2	first	first	ADJ
ijassa-1009	140	3	layer	layer	NOUN
ijassa-1009	140	4	(	(	PUNCT
ijassa-1009	140	5	flatten	flatten	VERB
ijassa-1009	140	6	layer	layer	NOUN
ijassa-1009	140	7	)	)	PUNCT
ijassa-1009	140	8	was	be	AUX
ijassa-1009	140	9	used	use	VERB
ijassa-1009	140	10	to	to	PART
ijassa-1009	140	11	flatten	flatten	VERB
ijassa-1009	140	12	out	out	ADP
ijassa-1009	140	13	the	the	DET
ijassa-1009	140	14	input	input	NOUN
ijassa-1009	140	15	features	feature	NOUN
ijassa-1009	140	16	.	.	PUNCT
ijassa-1009	141	1	the	the	DET
ijassa-1009	141	2	next	next	ADJ
ijassa-1009	141	3	layer	layer	NOUN
ijassa-1009	141	4	is	be	AUX
ijassa-1009	141	5	the	the	DET
ijassa-1009	141	6	dropout	dropout	NOUN
ijassa-1009	141	7	layer	layer	NOUN
ijassa-1009	141	8	,	,	PUNCT
ijassa-1009	141	9	which	which	PRON
ijassa-1009	141	10	buried	bury	VERB
ijassa-1009	141	11	the	the	DET
ijassa-1009	141	12	problem	problem	NOUN
ijassa-1009	141	13	of	of	ADP
ijassa-1009	141	14	overfitting	overfitte	VERB
ijassa-1009	141	15	.	.	PUNCT
ijassa-1009	142	1	a	a	DET
ijassa-1009	142	2	dense	dense	ADJ
ijassa-1009	142	3	layer	layer	NOUN
ijassa-1009	142	4	with	with	ADP
ijassa-1009	142	5	a	a	DET
ijassa-1009	142	6	softmax	softmax	NOUN
ijassa-1009	142	7	activation	activation	NOUN
ijassa-1009	142	8	function	function	NOUN
ijassa-1009	142	9	is	be	AUX
ijassa-1009	142	10	used	use	VERB
ijassa-1009	142	11	as	as	ADP
ijassa-1009	142	12	an	an	DET
ijassa-1009	142	13	output	output	NOUN
ijassa-1009	142	14	layer	layer	NOUN
ijassa-1009	142	15	.	.	PUNCT
ijassa-1009	143	1	4.1	4.1	NUM
ijassa-1009	143	2	vgg16	vgg16	NOUN
ijassa-1009	143	3	vgg16	vgg16	NOUN
ijassa-1009	143	4	technique	technique	NOUN
ijassa-1009	143	5	is	be	AUX
ijassa-1009	143	6	a	a	DET
ijassa-1009	143	7	deep	deep	ADJ
ijassa-1009	143	8	learning	learning	NOUN
ijassa-1009	143	9	predictive	predictive	ADJ
ijassa-1009	143	10	model	model	NOUN
ijassa-1009	143	11	that	that	PRON
ijassa-1009	143	12	is	be	AUX
ijassa-1009	143	13	based	base	VERB
ijassa-1009	143	14	on	on	ADP
ijassa-1009	143	15	the	the	DET
ijassa-1009	143	16	ability	ability	NOUN
ijassa-1009	143	17	of	of	ADP
ijassa-1009	143	18	imitation	imitation	NOUN
ijassa-1009	143	19	effects	effect	NOUN
ijassa-1009	143	20	shown	show	VERB
ijassa-1009	143	21	by	by	ADP
ijassa-1009	143	22	multiple	multiple	ADJ
ijassa-1009	143	23	small	small	ADJ
ijassa-1009	143	24	filters	filter	NOUN
ijassa-1009	143	25	in	in	ADP
ijassa-1009	143	26	a	a	DET
ijassa-1009	143	27	sequence	sequence	NOUN
ijassa-1009	143	28	with	with	ADP
ijassa-1009	143	29	respect	respect	NOUN
ijassa-1009	143	30	to	to	ADP
ijassa-1009	143	31	large	large	ADJ
ijassa-1009	143	32	filters	filter	NOUN
ijassa-1009	143	33	[	[	X
ijassa-1009	143	34	26	26	NUM
ijassa-1009	143	35	]	]	PUNCT
ijassa-1009	143	36	.	.	PUNCT
ijassa-1009	144	1	for	for	ADP
ijassa-1009	144	2	interpreting	interpret	VERB
ijassa-1009	144	3	the	the	DET
ijassa-1009	144	4	effect	effect	NOUN
ijassa-1009	144	5	of	of	ADP
ijassa-1009	144	6	depth	depth	NOUN
ijassa-1009	144	7	on	on	ADP
ijassa-1009	144	8	accuracy	accuracy	NOUN
ijassa-1009	144	9	a	a	DET
ijassa-1009	144	10	simple	simple	ADJ
ijassa-1009	144	11	cnn	cnn	NOUN
ijassa-1009	144	12	with	with	ADP
ijassa-1009	144	13	a	a	DET
ijassa-1009	144	14	small	small	ADJ
ijassa-1009	144	15	convolution	convolution	NOUN
ijassa-1009	144	16	filter	filter	NOUN
ijassa-1009	144	17	of	of	ADP
ijassa-1009	144	18	size	size	NOUN
ijassa-1009	144	19	3x3	3x3	NUM
ijassa-1009	144	20	with	with	ADP
ijassa-1009	144	21	stride	stride	NOUN
ijassa-1009	144	22	and	and	CCONJ
ijassa-1009	144	23	padding	padding	NOUN
ijassa-1009	144	24	of	of	ADP
ijassa-1009	144	25	1	1	NUM
ijassa-1009	144	26	along	along	ADP
ijassa-1009	144	27	with	with	ADP
ijassa-1009	144	28	a	a	DET
ijassa-1009	144	29	2x2	2x2	NUM
ijassa-1009	144	30	max	max	NOUN
ijassa-1009	144	31	-	-	PUNCT
ijassa-1009	144	32	pool	pool	NOUN
ijassa-1009	144	33	with	with	ADP
ijassa-1009	144	34	a	a	DET
ijassa-1009	144	35	stride	stride	NOUN
ijassa-1009	144	36	of	of	ADP
ijassa-1009	144	37	2	2	NUM
ijassa-1009	144	38	for	for	ADP
ijassa-1009	144	39	16	16	NUM
ijassa-1009	144	40	layers	layer	NOUN
ijassa-1009	144	41	was	be	AUX
ijassa-1009	144	42	used	use	VERB
ijassa-1009	144	43	.	.	PUNCT
ijassa-1009	145	1	fig	fig	NOUN
ijassa-1009	145	2	.	.	PUNCT
ijassa-1009	146	1	4.1.1	4.1.1	X
ijassa-1009	146	2	.	.	PUNCT
ijassa-1009	147	1	architecture	architecture	NOUN
ijassa-1009	147	2	of	of	ADP
ijassa-1009	147	3	the	the	DET
ijassa-1009	147	4	vgg	vgg	PROPN
ijassa-1009	147	5	model	model	NOUN
ijassa-1009	147	6	.	.	PUNCT
ijassa-1009	148	1	it	it	PRON
ijassa-1009	148	2	shows	show	VERB
ijassa-1009	148	3	improvement	improvement	NOUN
ijassa-1009	148	4	over	over	ADP
ijassa-1009	148	5	alex	alex	PROPN
ijassa-1009	148	6	net	net	NOUN
ijassa-1009	148	7	by	by	ADP
ijassa-1009	148	8	substituting	substitute	VERB
ijassa-1009	148	9	large	large	ADJ
ijassa-1009	148	10	kernel	kernel	NOUN
ijassa-1009	148	11	sized	size	VERB
ijassa-1009	148	12	filters	filter	NOUN
ijassa-1009	148	13	with	with	ADP
ijassa-1009	148	14	multiple	multiple	ADJ
ijassa-1009	148	15	3x3	3x3	NUM
ijassa-1009	148	16	kernel	kernel	NOUN
ijassa-1009	148	17	sized	size	VERB
ijassa-1009	148	18	filters	filter	NOUN
ijassa-1009	148	19	one	one	NUM
ijassa-1009	148	20	after	after	ADP
ijassa-1009	148	21	another	another	PRON
ijassa-1009	148	22	.	.	PUNCT
ijassa-1009	149	1	the	the	DET
ijassa-1009	149	2	algorithms	algorithm	NOUN
ijassa-1009	149	3	were	be	AUX
ijassa-1009	149	4	specifically	specifically	ADV
ijassa-1009	149	5	trained	train	VERB
ijassa-1009	149	6	48	48	NUM
ijassa-1009	149	7	naveen	naveen	PROPN
ijassa-1009	149	8	et	et	PROPN
ijassa-1009	149	9	al	al	PROPN
ijassa-1009	149	10	.	.	PUNCT
ijassa-1009	150	1	copyright	copyright	PROPN
ijassa-1009	150	2	©	©	PROPN
ijassa-1009	150	3	2021	2021	NUM
ijassa-1009	150	4	assa	assa	NOUN
ijassa-1009	150	5	.	.	PUNCT
ijassa-1009	151	1	adv	adv	PROPN
ijassa-1009	151	2	.	.	PUNCT
ijassa-1009	152	1	in	in	ADP
ijassa-1009	152	2	systems	system	NOUN
ijassa-1009	152	3	science	science	NOUN
ijassa-1009	152	4	and	and	CCONJ
ijassa-1009	152	5	appl	appl	NOUN
ijassa-1009	152	6	.	.	PUNCT
ijassa-1009	153	1	(	(	PUNCT
ijassa-1009	153	2	2021	2021	NUM
ijassa-1009	153	3	)	)	PUNCT
ijassa-1009	153	4	for	for	ADP
ijassa-1009	153	5	image	image	NOUN
ijassa-1009	153	6	localization	localization	NOUN
ijassa-1009	153	7	.	.	PUNCT
ijassa-1009	154	1	the	the	DET
ijassa-1009	154	2	input	input	NOUN
ijassa-1009	154	3	to	to	ADP
ijassa-1009	154	4	the	the	DET
ijassa-1009	154	5	first	first	ADJ
ijassa-1009	154	6	convolutional	convolutional	ADJ
ijassa-1009	154	7	layer	layer	NOUN
ijassa-1009	154	8	is	be	AUX
ijassa-1009	154	9	an	an	DET
ijassa-1009	154	10	image	image	NOUN
ijassa-1009	154	11	after	after	ADP
ijassa-1009	154	12	preprocessing	preprocesse	VERB
ijassa-1009	154	13	the	the	DET
ijassa-1009	154	14	dataset	dataset	NOUN
ijassa-1009	154	15	.	.	PUNCT
ijassa-1009	155	1	the	the	DET
ijassa-1009	155	2	image	image	NOUN
ijassa-1009	155	3	is	be	AUX
ijassa-1009	155	4	passed	pass	VERB
ijassa-1009	155	5	over	over	ADP
ijassa-1009	155	6	a	a	DET
ijassa-1009	155	7	stack	stack	NOUN
ijassa-1009	155	8	of	of	ADP
ijassa-1009	155	9	layers	layer	NOUN
ijassa-1009	155	10	where	where	SCONJ
ijassa-1009	155	11	small	small	ADJ
ijassa-1009	155	12	size	size	NOUN
ijassa-1009	155	13	filters	filter	NOUN
ijassa-1009	155	14	of	of	ADP
ijassa-1009	155	15	3x3	3x3	NUM
ijassa-1009	155	16	have	have	AUX
ijassa-1009	155	17	been	be	AUX
ijassa-1009	155	18	used	use	VERB
ijassa-1009	155	19	and	and	CCONJ
ijassa-1009	155	20	pooling	pooling	NOUN
ijassa-1009	155	21	is	be	AUX
ijassa-1009	155	22	also	also	ADV
ijassa-1009	155	23	been	be	AUX
ijassa-1009	155	24	applied	apply	VERB
ijassa-1009	155	25	after	after	ADP
ijassa-1009	155	26	every	every	DET
ijassa-1009	155	27	convolutional	convolutional	ADJ
ijassa-1009	155	28	layer	layer	NOUN
ijassa-1009	155	29	.	.	PUNCT
ijassa-1009	156	1	a	a	DET
ijassa-1009	156	2	1x1conv	1x1conv	NUM
ijassa-1009	156	3	filter	filter	NOUN
ijassa-1009	156	4	had	have	AUX
ijassa-1009	156	5	also	also	ADV
ijassa-1009	156	6	been	be	AUX
ijassa-1009	156	7	used	use	VERB
ijassa-1009	156	8	for	for	ADP
ijassa-1009	156	9	the	the	DET
ijassa-1009	156	10	conversion	conversion	NOUN
ijassa-1009	156	11	of	of	ADP
ijassa-1009	156	12	input	input	NOUN
ijassa-1009	156	13	channels	channel	NOUN
ijassa-1009	156	14	to	to	PART
ijassa-1009	156	15	linear	linear	VERB
ijassa-1009	156	16	.	.	PUNCT
ijassa-1009	157	1	to	to	PART
ijassa-1009	157	2	help	help	VERB
ijassa-1009	157	3	us	we	PRON
ijassa-1009	157	4	extract	extract	VERB
ijassa-1009	157	5	the	the	DET
ijassa-1009	157	6	generic	generic	ADJ
ijassa-1009	157	7	low	low	ADJ
ijassa-1009	157	8	-	-	PUNCT
ijassa-1009	157	9	level	level	NOUN
ijassa-1009	157	10	descriptors	descriptor	NOUN
ijassa-1009	157	11	or	or	CCONJ
ijassa-1009	157	12	patterns	pattern	NOUN
ijassa-1009	157	13	from	from	ADP
ijassa-1009	157	14	the	the	DET
ijassa-1009	157	15	chest	chest	NOUN
ijassa-1009	157	16	x	x	NOUN
ijassa-1009	157	17	-	-	NOUN
ijassa-1009	157	18	ray	ray	NOUN
ijassa-1009	157	19	image	image	NOUN
ijassa-1009	157	20	data	datum	NOUN
ijassa-1009	157	21	,	,	PUNCT
ijassa-1009	157	22	then	then	ADV
ijassa-1009	157	23	froze	freeze	VERB
ijassa-1009	157	24	the	the	DET
ijassa-1009	157	25	weights	weight	NOUN
ijassa-1009	157	26	of	of	ADP
ijassa-1009	157	27	the	the	DET
ijassa-1009	157	28	earlier	early	ADJ
ijassa-1009	157	29	layers	layer	NOUN
ijassa-1009	157	30	of	of	ADP
ijassa-1009	157	31	the	the	DET
ijassa-1009	157	32	pre	pre	ADJ
ijassa-1009	157	33	-	-	ADJ
ijassa-1009	157	34	trained	train	VERB
ijassa-1009	157	35	backbone	backbone	NOUN
ijassa-1009	157	36	.	.	PUNCT
ijassa-1009	158	1	the	the	DET
ijassa-1009	158	2	first	first	ADJ
ijassa-1009	158	3	few	few	ADJ
ijassa-1009	158	4	layers	layer	NOUN
ijassa-1009	158	5	learn	learn	VERB
ijassa-1009	158	6	very	very	ADV
ijassa-1009	158	7	basic	basic	ADJ
ijassa-1009	158	8	and	and	CCONJ
ijassa-1009	158	9	generic	generic	ADJ
ijassa-1009	158	10	characteristics	characteristic	NOUN
ijassa-1009	158	11	that	that	PRON
ijassa-1009	158	12	generalize	generalize	VERB
ijassa-1009	158	13	to	to	ADP
ijassa-1009	158	14	almost	almost	ADV
ijassa-1009	158	15	all	all	DET
ijassa-1009	158	16	types	type	NOUN
ijassa-1009	158	17	of	of	ADP
ijassa-1009	158	18	images	image	NOUN
ijassa-1009	158	19	in	in	ADP
ijassa-1009	158	20	the	the	DET
ijassa-1009	158	21	convolutional	convolutional	ADJ
ijassa-1009	158	22	networks	network	NOUN
ijassa-1009	158	23	that	that	PRON
ijassa-1009	158	24	are	be	AUX
ijassa-1009	158	25	used	use	VERB
ijassa-1009	158	26	in	in	ADP
ijassa-1009	158	27	this	this	DET
ijassa-1009	158	28	research	research	NOUN
ijassa-1009	158	29	work	work	NOUN
ijassa-1009	158	30	.	.	PUNCT
ijassa-1009	159	1	the	the	DET
ijassa-1009	159	2	features	feature	NOUN
ijassa-1009	159	3	became	become	VERB
ijassa-1009	159	4	increasingly	increasingly	ADV
ijassa-1009	159	5	more	more	ADV
ijassa-1009	159	6	unique	unique	ADJ
ijassa-1009	159	7	to	to	ADP
ijassa-1009	159	8	the	the	DET
ijassa-1009	159	9	dataset	dataset	NOUN
ijassa-1009	159	10	on	on	ADP
ijassa-1009	159	11	which	which	PRON
ijassa-1009	159	12	the	the	DET
ijassa-1009	159	13	model	model	NOUN
ijassa-1009	159	14	was	be	AUX
ijassa-1009	159	15	trained	train	VERB
ijassa-1009	159	16	.	.	PUNCT
ijassa-1009	160	1	the	the	DET
ijassa-1009	160	2	objective	objective	NOUN
ijassa-1009	160	3	of	of	ADP
ijassa-1009	160	4	fine	fine	ADV
ijassa-1009	160	5	-	-	PUNCT
ijassa-1009	160	6	tuning	tuning	NOUN
ijassa-1009	160	7	is	be	AUX
ijassa-1009	160	8	to	to	PART
ijassa-1009	160	9	adapt	adapt	VERB
ijassa-1009	160	10	these	these	DET
ijassa-1009	160	11	specialized	specialized	ADJ
ijassa-1009	160	12	features	feature	NOUN
ijassa-1009	160	13	rather	rather	ADV
ijassa-1009	160	14	than	than	ADP
ijassa-1009	160	15	overwrite	overwrite	VERB
ijassa-1009	160	16	the	the	DET
ijassa-1009	160	17	generic	generic	ADJ
ijassa-1009	160	18	learning	learning	NOUN
ijassa-1009	160	19	,	,	PUNCT
ijassa-1009	160	20	to	to	PART
ijassa-1009	160	21	work	work	VERB
ijassa-1009	160	22	with	with	ADP
ijassa-1009	160	23	the	the	DET
ijassa-1009	160	24	newly	newly	ADV
ijassa-1009	160	25	fed	feed	VERB
ijassa-1009	160	26	covid-19	covid-19	PROPN
ijassa-1009	160	27	dataset	dataset	NOUN
ijassa-1009	160	28	.	.	PUNCT
ijassa-1009	161	1	vgg16	vgg16	NOUN
ijassa-1009	161	2	is	be	AUX
ijassa-1009	161	3	an	an	DET
ijassa-1009	161	4	improvement	improvement	NOUN
ijassa-1009	161	5	over	over	ADP
ijassa-1009	161	6	alexnet	alexnet	NOUN
ijassa-1009	161	7	,	,	PUNCT
ijassa-1009	161	8	which	which	PRON
ijassa-1009	161	9	used	use	VERB
ijassa-1009	161	10	to	to	PART
ijassa-1009	161	11	be	be	AUX
ijassa-1009	161	12	a	a	DET
ijassa-1009	161	13	state	state	NOUN
ijassa-1009	161	14	of	of	ADP
ijassa-1009	161	15	art	art	NOUN
ijassa-1009	161	16	model	model	NOUN
ijassa-1009	161	17	until	until	ADP
ijassa-1009	161	18	the	the	DET
ijassa-1009	161	19	introduction	introduction	NOUN
ijassa-1009	161	20	of	of	ADP
ijassa-1009	161	21	vgg16	vgg16	NOUN
ijassa-1009	161	22	that	that	PRON
ijassa-1009	161	23	reduced	reduce	VERB
ijassa-1009	161	24	the	the	DET
ijassa-1009	161	25	image	image	NOUN
ijassa-1009	161	26	size	size	NOUN
ijassa-1009	161	27	very	very	ADV
ijassa-1009	161	28	drastically	drastically	ADV
ijassa-1009	161	29	using	use	VERB
ijassa-1009	161	30	convolution	convolution	NOUN
ijassa-1009	161	31	to	to	PART
ijassa-1009	161	32	avoid	avoid	VERB
ijassa-1009	161	33	without	without	ADP
ijassa-1009	161	34	needing	need	VERB
ijassa-1009	161	35	sgd	sgd	PROPN
ijassa-1009	161	36	(	(	PUNCT
ijassa-1009	161	37	stochastic	stochastic	ADJ
ijassa-1009	161	38	gradient	gradient	ADJ
ijassa-1009	161	39	descent	descent	NOUN
ijassa-1009	161	40	)	)	PUNCT
ijassa-1009	161	41	necessarily	necessarily	ADV
ijassa-1009	161	42	and	and	CCONJ
ijassa-1009	161	43	to	to	PART
ijassa-1009	161	44	increase	increase	VERB
ijassa-1009	161	45	the	the	DET
ijassa-1009	161	46	number	number	NOUN
ijassa-1009	161	47	of	of	ADP
ijassa-1009	161	48	channels	channel	NOUN
ijassa-1009	161	49	to	to	PART
ijassa-1009	161	50	make	make	VERB
ijassa-1009	161	51	the	the	DET
ijassa-1009	161	52	image	image	NOUN
ijassa-1009	161	53	while	while	SCONJ
ijassa-1009	161	54	reducing	reduce	VERB
ijassa-1009	161	55	height	height	NOUN
ijassa-1009	161	56	and	and	CCONJ
ijassa-1009	161	57	width	width	NOUN
ijassa-1009	161	58	of	of	ADP
ijassa-1009	161	59	the	the	DET
ijassa-1009	161	60	image	image	NOUN
ijassa-1009	161	61	simultaneously	simultaneously	ADV
ijassa-1009	161	62	.	.	PUNCT
ijassa-1009	162	1	this	this	PRON
ijassa-1009	162	2	improves	improve	VERB
ijassa-1009	162	3	the	the	DET
ijassa-1009	162	4	computational	computational	ADJ
ijassa-1009	162	5	speed	speed	NOUN
ijassa-1009	162	6	and	and	CCONJ
ijassa-1009	162	7	accuracy	accuracy	NOUN
ijassa-1009	162	8	of	of	ADP
ijassa-1009	162	9	our	our	PRON
ijassa-1009	162	10	model	model	NOUN
ijassa-1009	162	11	without	without	ADP
ijassa-1009	162	12	going	go	VERB
ijassa-1009	162	13	through	through	ADP
ijassa-1009	162	14	a	a	DET
ijassa-1009	162	15	deep	deep	ADJ
ijassa-1009	162	16	neural	neural	ADJ
ijassa-1009	162	17	network	network	NOUN
ijassa-1009	162	18	.	.	PUNCT
ijassa-1009	163	1	4.2	4.2	NUM
ijassa-1009	163	2	resnet50	resnet50	NOUN
ijassa-1009	163	3	resnet50	resnet50	NOUN
ijassa-1009	163	4	is	be	AUX
ijassa-1009	163	5	a	a	DET
ijassa-1009	163	6	deep	deep	ADJ
ijassa-1009	163	7	learning	learning	NOUN
ijassa-1009	163	8	pre	pre	ADJ
ijassa-1009	163	9	-	-	ADJ
ijassa-1009	163	10	trained	train	VERB
ijassa-1009	163	11	model	model	NOUN
ijassa-1009	163	12	,	,	PUNCT
ijassa-1009	163	13	which	which	PRON
ijassa-1009	163	14	is	be	AUX
ijassa-1009	163	15	trained	train	VERB
ijassa-1009	163	16	on	on	ADP
ijassa-1009	163	17	the	the	DET
ijassa-1009	163	18	imagenet	imagenet	NOUN
ijassa-1009	163	19	dataset	dataset	NOUN
ijassa-1009	163	20	.	.	PUNCT
ijassa-1009	164	1	the	the	DET
ijassa-1009	164	2	backbone	backbone	NOUN
ijassa-1009	164	3	of	of	ADP
ijassa-1009	164	4	this	this	DET
ijassa-1009	164	5	architecture	architecture	NOUN
ijassa-1009	164	6	involves	involve	VERB
ijassa-1009	164	7	introducing	introduce	VERB
ijassa-1009	164	8	an	an	DET
ijassa-1009	164	9	identity	identity	NOUN
ijassa-1009	164	10	shortcut	shortcut	NOUN
ijassa-1009	164	11	connection	connection	NOUN
ijassa-1009	164	12	that	that	PRON
ijassa-1009	164	13	will	will	AUX
ijassa-1009	164	14	enable	enable	VERB
ijassa-1009	164	15	us	we	PRON
ijassa-1009	164	16	to	to	PART
ijassa-1009	164	17	skip	skip	VERB
ijassa-1009	164	18	multiple	multiple	ADJ
ijassa-1009	164	19	layers	layer	NOUN
ijassa-1009	164	20	.	.	PUNCT
ijassa-1009	165	1	it	it	PRON
ijassa-1009	165	2	is	be	AUX
ijassa-1009	165	3	the	the	DET
ijassa-1009	165	4	short	short	ADJ
ijassa-1009	165	5	name	name	NOUN
ijassa-1009	165	6	for	for	ADP
ijassa-1009	165	7	the	the	DET
ijassa-1009	165	8	residual	residual	ADJ
ijassa-1009	165	9	network	network	NOUN
ijassa-1009	165	10	and	and	CCONJ
ijassa-1009	165	11	it	it	PRON
ijassa-1009	165	12	introduces	introduce	VERB
ijassa-1009	165	13	the	the	DET
ijassa-1009	165	14	concept	concept	NOUN
ijassa-1009	165	15	of	of	ADP
ijassa-1009	165	16	residual	residual	ADJ
ijassa-1009	165	17	layers	layer	NOUN
ijassa-1009	165	18	.	.	PUNCT
ijassa-1009	166	1	fig	fig	NOUN
ijassa-1009	166	2	.	.	PUNCT
ijassa-1009	167	1	4.2.1	4.2.1	NOUN
ijassa-1009	167	2	.	.	PUNCT
ijassa-1009	168	1	architecture	architecture	NOUN
ijassa-1009	168	2	of	of	ADP
ijassa-1009	168	3	the	the	DET
ijassa-1009	168	4	resnet50	resnet50	NOUN
ijassa-1009	168	5	model	model	PROPN
ijassa-1009	168	6	.	.	PUNCT
ijassa-1009	169	1	resnet50	resnet50	NOUN
ijassa-1009	169	2	architecture	architecture	NOUN
ijassa-1009	169	3	is	be	AUX
ijassa-1009	169	4	pretty	pretty	ADV
ijassa-1009	169	5	similar	similar	ADJ
ijassa-1009	169	6	to	to	ADP
ijassa-1009	169	7	resnet18	resnet18	VERB
ijassa-1009	169	8	,	,	PUNCT
ijassa-1009	169	9	the	the	DET
ijassa-1009	169	10	main	main	ADJ
ijassa-1009	169	11	difference	difference	NOUN
ijassa-1009	169	12	being	be	AUX
ijassa-1009	169	13	having	have	VERB
ijassa-1009	169	14	more	more	ADJ
ijassa-1009	169	15	layers	layer	NOUN
ijassa-1009	169	16	.	.	PUNCT
ijassa-1009	170	1	resnet50	resnet50	PROPN
ijassa-1009	170	2	network	network	NOUN
ijassa-1009	170	3	each	each	DET
ijassa-1009	170	4	2	2	NUM
ijassa-1009	170	5	-	-	PUNCT
ijassa-1009	170	6	layer	layer	NOUN
ijassa-1009	170	7	block	block	NOUN
ijassa-1009	170	8	in	in	ADP
ijassa-1009	170	9	the	the	DET
ijassa-1009	170	10	34	34	NUM
ijassa-1009	170	11	-	-	PUNCT
ijassa-1009	170	12	layer	layer	NOUN
ijassa-1009	170	13	net	net	NOUN
ijassa-1009	170	14	is	be	AUX
ijassa-1009	170	15	replaced	replace	VERB
ijassa-1009	170	16	by	by	ADP
ijassa-1009	170	17	a	a	DET
ijassa-1009	170	18	3layer	3layer	NUM
ijassa-1009	170	19	bottleneck	bottleneck	NOUN
ijassa-1009	170	20	block	block	NOUN
ijassa-1009	170	21	leading	lead	VERB
ijassa-1009	170	22	to	to	ADP
ijassa-1009	170	23	a	a	DET
ijassa-1009	170	24	50	50	NUM
ijassa-1009	170	25	-	-	PUNCT
ijassa-1009	170	26	layer	layer	NOUN
ijassa-1009	170	27	model	model	NOUN
ijassa-1009	170	28	.	.	PUNCT
ijassa-1009	171	1	the	the	DET
ijassa-1009	171	2	idea	idea	NOUN
ijassa-1009	171	3	behind	behind	ADP
ijassa-1009	171	4	this	this	PRON
ijassa-1009	171	5	is	be	AUX
ijassa-1009	171	6	to	to	PART
ijassa-1009	171	7	skip	skip	VERB
ijassa-1009	171	8	layers	layer	NOUN
ijassa-1009	171	9	and	and	CCONJ
ijassa-1009	171	10	establish	establish	VERB
ijassa-1009	171	11	direct	direct	ADJ
ijassa-1009	171	12	short	short	ADJ
ijassa-1009	171	13	connections	connection	NOUN
ijassa-1009	171	14	to	to	PART
ijassa-1009	171	15	prevent	prevent	VERB
ijassa-1009	171	16	saturation	saturation	NOUN
ijassa-1009	171	17	of	of	ADP
ijassa-1009	171	18	accuracy	accuracy	NOUN
ijassa-1009	171	19	[	[	X
ijassa-1009	171	20	27	27	NUM
ijassa-1009	171	21	]	]	PUNCT
ijassa-1009	171	22	.	.	PUNCT
ijassa-1009	172	1	the	the	DET
ijassa-1009	172	2	insertion	insertion	NOUN
ijassa-1009	172	3	of	of	ADP
ijassa-1009	172	4	short	short	ADJ
ijassa-1009	172	5	connections	connection	NOUN
ijassa-1009	172	6	will	will	AUX
ijassa-1009	172	7	lead	lead	VERB
ijassa-1009	172	8	the	the	DET
ijassa-1009	172	9	network	network	NOUN
ijassa-1009	172	10	to	to	PART
ijassa-1009	172	11	turn	turn	VERB
ijassa-1009	172	12	into	into	ADP
ijassa-1009	172	13	its	its	PRON
ijassa-1009	172	14	residual	residual	ADJ
ijassa-1009	172	15	counterpart	counterpart	NOUN
ijassa-1009	172	16	.	.	PUNCT
ijassa-1009	173	1	as	as	SCONJ
ijassa-1009	173	2	the	the	DET
ijassa-1009	173	3	network	network	NOUN
ijassa-1009	173	4	gets	get	VERB
ijassa-1009	173	5	deeper	deep	ADJ
ijassa-1009	173	6	and	and	CCONJ
ijassa-1009	173	7	more	more	ADV
ijassa-1009	173	8	complex	complex	ADJ
ijassa-1009	173	9	,	,	PUNCT
ijassa-1009	173	10	it	it	PRON
ijassa-1009	173	11	avoids	avoid	VERB
ijassa-1009	173	12	the	the	DET
ijassa-1009	173	13	distortion	distortion	NOUN
ijassa-1009	173	14	that	that	PRON
ijassa-1009	173	15	happens	happen	VERB
ijassa-1009	173	16	in	in	ADP
ijassa-1009	173	17	the	the	DET
ijassa-1009	173	18	model	model	NOUN
ijassa-1009	173	19	during	during	ADP
ijassa-1009	173	20	training	training	NOUN
ijassa-1009	173	21	.	.	PUNCT
ijassa-1009	174	1	the	the	DET
ijassa-1009	174	2	shortcut	shortcut	NOUN
ijassa-1009	174	3	connections	connection	NOUN
ijassa-1009	174	4	perform	perform	VERB
ijassa-1009	174	5	identity	identity	NOUN
ijassa-1009	174	6	mappings	mapping	NOUN
ijassa-1009	174	7	and	and	CCONJ
ijassa-1009	174	8	the	the	DET
ijassa-1009	174	9	outputs	output	NOUN
ijassa-1009	174	10	obtained	obtain	VERB
ijassa-1009	174	11	are	be	AUX
ijassa-1009	174	12	added	add	VERB
ijassa-1009	174	13	to	to	ADP
ijassa-1009	174	14	the	the	DET
ijassa-1009	174	15	outputs	output	NOUN
ijassa-1009	174	16	of	of	ADP
ijassa-1009	174	17	other	other	ADJ
ijassa-1009	174	18	stacked	stack	VERB
ijassa-1009	174	19	layers	layer	NOUN
ijassa-1009	174	20	.	.	PUNCT
ijassa-1009	175	1	one	one	NUM
ijassa-1009	175	2	of	of	ADP
ijassa-1009	175	3	the	the	DET
ijassa-1009	175	4	advantages	advantage	NOUN
ijassa-1009	175	5	of	of	ADP
ijassa-1009	175	6	the	the	DET
ijassa-1009	175	7	architecture	architecture	NOUN
ijassa-1009	175	8	deep	deep	ADJ
ijassa-1009	175	9	learning	learning	NOUN
ijassa-1009	175	10	techniques	technique	NOUN
ijassa-1009	175	11	for	for	ADP
ijassa-1009	175	12	detection	detection	NOUN
ijassa-1009	175	13	of	of	ADP
ijassa-1009	175	14	covid-19	covid-19	PROPN
ijassa-1009	175	15	49	49	NUM
ijassa-1009	175	16	copyright	copyright	NOUN
ijassa-1009	175	17	©	©	PROPN
ijassa-1009	175	18	2021	2021	NUM
ijassa-1009	175	19	assa	assa	NOUN
ijassa-1009	175	20	.	.	PUNCT
ijassa-1009	176	1	adv	adv	PROPN
ijassa-1009	176	2	.	.	PUNCT
ijassa-1009	177	1	in	in	ADP
ijassa-1009	177	2	systems	system	NOUN
ijassa-1009	177	3	science	science	NOUN
ijassa-1009	177	4	and	and	CCONJ
ijassa-1009	177	5	appl	appl	NOUN
ijassa-1009	177	6	.	.	PUNCT
ijassa-1009	178	1	(	(	PUNCT
ijassa-1009	178	2	2021	2021	NUM
ijassa-1009	178	3	)	)	PUNCT
ijassa-1009	178	4	includes	include	VERB
ijassa-1009	178	5	helping	help	VERB
ijassa-1009	178	6	the	the	DET
ijassa-1009	178	7	network	network	NOUN
ijassa-1009	178	8	to	to	PART
ijassa-1009	178	9	create	create	VERB
ijassa-1009	178	10	a	a	DET
ijassa-1009	178	11	path	path	NOUN
ijassa-1009	178	12	,	,	PUNCT
ijassa-1009	178	13	which	which	PRON
ijassa-1009	178	14	will	will	AUX
ijassa-1009	178	15	help	help	VERB
ijassa-1009	178	16	us	we	PRON
ijassa-1009	178	17	simplify	simplify	VERB
ijassa-1009	178	18	the	the	DET
ijassa-1009	178	19	gradient	gradient	NOUN
ijassa-1009	178	20	updates	update	NOUN
ijassa-1009	178	21	for	for	ADP
ijassa-1009	178	22	the	the	DET
ijassa-1009	178	23	preceding	precede	VERB
ijassa-1009	178	24	layers	layer	NOUN
ijassa-1009	178	25	.	.	PUNCT
ijassa-1009	179	1	4.3	4.3	NUM
ijassa-1009	179	2	inceptionv3	inceptionv3	NOUN
ijassa-1009	179	3	inceptionv3	inceptionv3	NOUN
ijassa-1009	179	4	architecture	architecture	NOUN
ijassa-1009	179	5	aims	aim	VERB
ijassa-1009	179	6	to	to	PART
ijassa-1009	179	7	assist	assist	VERB
ijassa-1009	179	8	in	in	ADP
ijassa-1009	179	9	image	image	NOUN
ijassa-1009	179	10	analysis	analysis	NOUN
ijassa-1009	179	11	and	and	CCONJ
ijassa-1009	179	12	object	object	VERB
ijassa-1009	179	13	detection	detection	NOUN
ijassa-1009	179	14	.	.	PUNCT
ijassa-1009	180	1	it	it	PRON
ijassa-1009	180	2	is	be	AUX
ijassa-1009	180	3	a	a	DET
ijassa-1009	180	4	type	type	NOUN
ijassa-1009	180	5	of	of	ADP
ijassa-1009	180	6	neural	neural	ADJ
ijassa-1009	180	7	network	network	NOUN
ijassa-1009	180	8	model	model	NOUN
ijassa-1009	180	9	of	of	ADP
ijassa-1009	180	10	convolution	convolution	NOUN
ijassa-1009	180	11	.	.	PUNCT
ijassa-1009	181	1	it	it	PRON
ijassa-1009	181	2	consists	consist	VERB
ijassa-1009	181	3	of	of	ADP
ijassa-1009	181	4	several	several	ADJ
ijassa-1009	181	5	stages	stage	NOUN
ijassa-1009	181	6	of	of	ADP
ijassa-1009	181	7	convolution	convolution	NOUN
ijassa-1009	181	8	and	and	CCONJ
ijassa-1009	181	9	full	full	ADJ
ijassa-1009	181	10	pooling	pooling	NOUN
ijassa-1009	181	11	.	.	PUNCT
ijassa-1009	182	1	it	it	PRON
ijassa-1009	182	2	increases	increase	VERB
ijassa-1009	182	3	the	the	DET
ijassa-1009	182	4	depth	depth	NOUN
ijassa-1009	182	5	and	and	CCONJ
ijassa-1009	182	6	width	width	NOUN
ijassa-1009	182	7	of	of	ADP
ijassa-1009	182	8	the	the	DET
ijassa-1009	182	9	network	network	NOUN
ijassa-1009	182	10	and	and	CCONJ
ijassa-1009	182	11	improves	improve	VERB
ijassa-1009	182	12	the	the	DET
ijassa-1009	182	13	involvement	involvement	NOUN
ijassa-1009	182	14	of	of	ADP
ijassa-1009	182	15	computing	compute	VERB
ijassa-1009	182	16	resources	resource	NOUN
ijassa-1009	182	17	inside	inside	ADP
ijassa-1009	182	18	the	the	DET
ijassa-1009	182	19	network	network	NOUN
ijassa-1009	182	20	while	while	SCONJ
ijassa-1009	182	21	keeping	keep	VERB
ijassa-1009	182	22	computation	computation	NOUN
ijassa-1009	182	23	operations	operation	NOUN
ijassa-1009	182	24	unchanged	unchanged	ADJ
ijassa-1009	182	25	[	[	X
ijassa-1009	182	26	28	28	NUM
ijassa-1009	182	27	]	]	PUNCT
ijassa-1009	182	28	.	.	PUNCT
ijassa-1009	183	1	fig	fig	NOUN
ijassa-1009	183	2	.	.	PUNCT
ijassa-1009	184	1	4.3.1	4.3.1	X
ijassa-1009	184	2	.	.	PUNCT
ijassa-1009	185	1	architecture	architecture	NOUN
ijassa-1009	185	2	of	of	ADP
ijassa-1009	185	3	the	the	DET
ijassa-1009	185	4	inceptionv3	inceptionv3	NOUN
ijassa-1009	185	5	model	model	NOUN
ijassa-1009	185	6	.	.	PUNCT
ijassa-1009	186	1	in	in	ADP
ijassa-1009	186	2	general	general	ADJ
ijassa-1009	186	3	,	,	PUNCT
ijassa-1009	186	4	it	it	PRON
ijassa-1009	186	5	has	have	VERB
ijassa-1009	186	6	48	48	NUM
ijassa-1009	186	7	layers	layer	NOUN
ijassa-1009	186	8	and	and	CCONJ
ijassa-1009	186	9	uses	use	VERB
ijassa-1009	186	10	inception	inception	NOUN
ijassa-1009	186	11	modules	module	NOUN
ijassa-1009	186	12	consisting	consist	VERB
ijassa-1009	186	13	of	of	ADP
ijassa-1009	186	14	a	a	DET
ijassa-1009	186	15	concatenated	concatenate	VERB
ijassa-1009	186	16	layer	layer	NOUN
ijassa-1009	186	17	with	with	ADP
ijassa-1009	186	18	convolutions	convolution	NOUN
ijassa-1009	186	19	of	of	ADP
ijassa-1009	186	20	1	1	NUM
ijassa-1009	186	21	x	x	SYM
ijassa-1009	186	22	13	13	NUM
ijassa-1009	186	23	x	x	SYM
ijassa-1009	186	24	3	3	NUM
ijassa-1009	186	25	and	and	CCONJ
ijassa-1009	186	26	5	5	NUM
ijassa-1009	186	27	x	x	SYM
ijassa-1009	186	28	5	5	NUM
ijassa-1009	186	29	.	.	PUNCT
ijassa-1009	186	30	reducing	reduce	VERB
ijassa-1009	186	31	the	the	DET
ijassa-1009	186	32	number	number	NOUN
ijassa-1009	186	33	of	of	ADP
ijassa-1009	186	34	channels	channel	NOUN
ijassa-1009	186	35	in	in	ADP
ijassa-1009	186	36	the	the	DET
ijassa-1009	186	37	image	image	NOUN
ijassa-1009	186	38	is	be	AUX
ijassa-1009	186	39	the	the	DET
ijassa-1009	186	40	basic	basic	ADJ
ijassa-1009	186	41	concept	concept	NOUN
ijassa-1009	186	42	of	of	ADP
ijassa-1009	186	43	the	the	DET
ijassa-1009	186	44	1x1	1x1	NUM
ijassa-1009	186	45	convolution	convolution	NOUN
ijassa-1009	186	46	.	.	PUNCT
ijassa-1009	187	1	thus	thus	ADV
ijassa-1009	187	2	,	,	PUNCT
ijassa-1009	187	3	it	it	PRON
ijassa-1009	187	4	also	also	ADV
ijassa-1009	187	5	decreases	decrease	VERB
ijassa-1009	187	6	the	the	DET
ijassa-1009	187	7	number	number	NOUN
ijassa-1009	187	8	of	of	ADP
ijassa-1009	187	9	parameters	parameter	NOUN
ijassa-1009	187	10	.	.	PUNCT
ijassa-1009	188	1	the	the	DET
ijassa-1009	188	2	size	size	NOUN
ijassa-1009	188	3	of	of	ADP
ijassa-1009	188	4	the	the	DET
ijassa-1009	188	5	matrix	matrix	NOUN
ijassa-1009	188	6	is	be	AUX
ijassa-1009	188	7	usually	usually	ADV
ijassa-1009	188	8	not	not	PART
ijassa-1009	188	9	affected	affect	VERB
ijassa-1009	188	10	by	by	ADP
ijassa-1009	188	11	1x1	1x1	NUM
ijassa-1009	188	12	convolution	convolution	NOUN
ijassa-1009	188	13	;	;	PUNCT
ijassa-1009	188	14	however	however	ADV
ijassa-1009	188	15	,	,	PUNCT
ijassa-1009	188	16	if	if	SCONJ
ijassa-1009	188	17	the	the	DET
ijassa-1009	188	18	input	input	NOUN
ijassa-1009	188	19	matrix	matrix	NOUN
ijassa-1009	188	20	is	be	AUX
ijassa-1009	188	21	multi	multi	ADJ
ijassa-1009	188	22	-	-	ADJ
ijassa-1009	188	23	channel	channel	NOUN
ijassa-1009	188	24	,	,	PUNCT
ijassa-1009	188	25	the	the	DET
ijassa-1009	188	26	channel	channel	NOUN
ijassa-1009	188	27	number	number	NOUN
ijassa-1009	188	28	of	of	ADP
ijassa-1009	188	29	the	the	DET
ijassa-1009	188	30	1x1	1x1	NUM
ijassa-1009	188	31	convolution	convolution	NOUN
ijassa-1009	188	32	method	method	NOUN
ijassa-1009	188	33	output	output	NOUN
ijassa-1009	188	34	matrix	matrix	NOUN
ijassa-1009	188	35	is	be	AUX
ijassa-1009	188	36	equivalent	equivalent	ADJ
ijassa-1009	188	37	to	to	ADP
ijassa-1009	188	38	the	the	DET
ijassa-1009	188	39	number	number	NOUN
ijassa-1009	188	40	of	of	ADP
ijassa-1009	188	41	1x1	1x1	NUM
ijassa-1009	188	42	convolution	convolution	NOUN
ijassa-1009	188	43	filter	filter	NOUN
ijassa-1009	188	44	channels	channel	NOUN
ijassa-1009	188	45	added	add	VERB
ijassa-1009	188	46	.	.	PUNCT
ijassa-1009	189	1	this	this	DET
ijassa-1009	189	2	architecture	architecture	NOUN
ijassa-1009	189	3	's	's	PART
ijassa-1009	189	4	key	key	ADJ
ijassa-1009	189	5	benefit	benefit	NOUN
ijassa-1009	189	6	is	be	AUX
ijassa-1009	189	7	that	that	SCONJ
ijassa-1009	189	8	it	it	PRON
ijassa-1009	189	9	enables	enable	VERB
ijassa-1009	189	10	one	one	NUM
ijassa-1009	189	11	to	to	PART
ijassa-1009	189	12	reduce	reduce	VERB
ijassa-1009	189	13	the	the	DET
ijassa-1009	189	14	number	number	NOUN
ijassa-1009	189	15	of	of	ADP
ijassa-1009	189	16	parameters	parameter	NOUN
ijassa-1009	189	17	and	and	CCONJ
ijassa-1009	189	18	increase	increase	VERB
ijassa-1009	189	19	the	the	DET
ijassa-1009	189	20	speed	speed	NOUN
ijassa-1009	189	21	of	of	ADP
ijassa-1009	189	22	training	training	NOUN
ijassa-1009	189	23	.	.	PUNCT
ijassa-1009	190	1	another	another	DET
ijassa-1009	190	2	benefit	benefit	NOUN
ijassa-1009	190	3	of	of	ADP
ijassa-1009	190	4	this	this	DET
ijassa-1009	190	5	architecture	architecture	NOUN
ijassa-1009	190	6	is	be	AUX
ijassa-1009	190	7	that	that	SCONJ
ijassa-1009	190	8	it	it	PRON
ijassa-1009	190	9	enables	enable	VERB
ijassa-1009	190	10	the	the	DET
ijassa-1009	190	11	user	user	NOUN
ijassa-1009	190	12	to	to	PART
ijassa-1009	190	13	perform	perform	VERB
ijassa-1009	190	14	the	the	DET
ijassa-1009	190	15	localization	localization	NOUN
ijassa-1009	190	16	according	accord	VERB
ijassa-1009	190	17	to	to	ADP
ijassa-1009	190	18	their	their	PRON
ijassa-1009	190	19	parameters	parameter	NOUN
ijassa-1009	190	20	and	and	CCONJ
ijassa-1009	190	21	helps	help	VERB
ijassa-1009	190	22	us	we	PRON
ijassa-1009	190	23	to	to	PART
ijassa-1009	190	24	recognize	recognize	VERB
ijassa-1009	190	25	with	with	ADP
ijassa-1009	190	26	better	well	ADJ
ijassa-1009	190	27	accuracy	accuracy	NOUN
ijassa-1009	190	28	.	.	PUNCT
ijassa-1009	191	1	4.4	4.4	NUM
ijassa-1009	191	2	xception	xception	PROPN
ijassa-1009	191	3	xception	xception	PROPN
ijassa-1009	191	4	is	be	AUX
ijassa-1009	191	5	a	a	DET
ijassa-1009	191	6	71	71	NUM
ijassa-1009	191	7	-	-	PUNCT
ijassa-1009	191	8	layer	layer	NOUN
ijassa-1009	191	9	deep	deep	ADJ
ijassa-1009	191	10	convolutional	convolutional	ADJ
ijassa-1009	191	11	neural	neural	ADJ
ijassa-1009	191	12	network	network	NOUN
ijassa-1009	191	13	.	.	PUNCT
ijassa-1009	192	1	it	it	PRON
ijassa-1009	192	2	involves	involve	VERB
ijassa-1009	192	3	depth	depth	NOUN
ijassa-1009	192	4	wise	wise	ADJ
ijassa-1009	192	5	separable	separable	ADJ
ijassa-1009	192	6	convolutions	convolution	NOUN
ijassa-1009	192	7	instead	instead	ADV
ijassa-1009	192	8	of	of	ADP
ijassa-1009	192	9	standard	standard	ADJ
ijassa-1009	192	10	inception	inception	ADJ
ijassa-1009	192	11	modules	module	NOUN
ijassa-1009	192	12	.	.	PUNCT
ijassa-1009	193	1	it	it	PRON
ijassa-1009	193	2	is	be	AUX
ijassa-1009	193	3	an	an	DET
ijassa-1009	193	4	extension	extension	NOUN
ijassa-1009	193	5	of	of	ADP
ijassa-1009	193	6	the	the	DET
ijassa-1009	193	7	inception	inception	ADJ
ijassa-1009	193	8	architecture	architecture	NOUN
ijassa-1009	193	9	.	.	PUNCT
ijassa-1009	194	1	a	a	DET
ijassa-1009	194	2	pre	pre	ADJ
ijassa-1009	194	3	-	-	ADJ
ijassa-1009	194	4	trained	train	VERB
ijassa-1009	194	5	version	version	NOUN
ijassa-1009	194	6	of	of	ADP
ijassa-1009	194	7	the	the	DET
ijassa-1009	194	8	network	network	NOUN
ijassa-1009	194	9	trained	train	VERB
ijassa-1009	194	10	on	on	ADP
ijassa-1009	194	11	more	more	ADJ
ijassa-1009	194	12	than	than	ADP
ijassa-1009	194	13	10	10	NUM
ijassa-1009	194	14	lakh	lakh	NOUN
ijassa-1009	194	15	images	image	NOUN
ijassa-1009	194	16	from	from	ADP
ijassa-1009	194	17	the	the	DET
ijassa-1009	194	18	imagenet	imagenet	NOUN
ijassa-1009	194	19	database	database	NOUN
ijassa-1009	194	20	can	can	AUX
ijassa-1009	194	21	be	be	AUX
ijassa-1009	194	22	loaded	load	VERB
ijassa-1009	194	23	.	.	PUNCT
ijassa-1009	195	1	in	in	ADP
ijassa-1009	195	2	this	this	DET
ijassa-1009	195	3	model	model	NOUN
ijassa-1009	195	4	,	,	PUNCT
ijassa-1009	195	5	the	the	DET
ijassa-1009	195	6	initiation	initiation	NOUN
ijassa-1009	195	7	of	of	ADP
ijassa-1009	195	8	convolution	convolution	NOUN
ijassa-1009	195	9	modules	module	NOUN
ijassa-1009	195	10	is	be	AUX
ijassa-1009	195	11	replaced	replace	VERB
ijassa-1009	195	12	by	by	ADP
ijassa-1009	195	13	depth	depth	NOUN
ijassa-1009	195	14	-	-	PUNCT
ijassa-1009	195	15	wise	wise	ADJ
ijassa-1009	195	16	separable	separable	ADJ
ijassa-1009	195	17	convolutions	convolution	NOUN
ijassa-1009	195	18	.	.	PUNCT
ijassa-1009	196	1	point	point	NOUN
ijassa-1009	196	2	-	-	PUNCT
ijassa-1009	196	3	wise	wise	ADJ
ijassa-1009	196	4	convolution	convolution	NOUN
ijassa-1009	196	5	layers	layer	NOUN
ijassa-1009	196	6	obey	obey	VERB
ijassa-1009	196	7	the	the	DET
ijassa-1009	196	8	depth	depth	NOUN
ijassa-1009	196	9	of	of	ADP
ijassa-1009	196	10	wise	wise	ADJ
ijassa-1009	196	11	convolution	convolution	NOUN
ijassa-1009	196	12	layers	layer	NOUN
ijassa-1009	196	13	.	.	PUNCT
ijassa-1009	197	1	for	for	ADP
ijassa-1009	197	2	a	a	DET
ijassa-1009	197	3	large	large	ADJ
ijassa-1009	197	4	range	range	NOUN
ijassa-1009	197	5	of	of	ADP
ijassa-1009	197	6	images	image	NOUN
ijassa-1009	197	7	,	,	PUNCT
ijassa-1009	197	8	the	the	DET
ijassa-1009	197	9	network	network	NOUN
ijassa-1009	197	10	is	be	AUX
ijassa-1009	197	11	capable	capable	ADJ
ijassa-1009	197	12	of	of	ADP
ijassa-1009	197	13	learningrich	learningrich	ADJ
ijassa-1009	197	14	feature	feature	NOUN
ijassa-1009	197	15	representations	representation	NOUN
ijassa-1009	197	16	and	and	CCONJ
ijassa-1009	197	17	is	be	AUX
ijassa-1009	197	18	able	able	ADJ
ijassa-1009	197	19	to	to	PART
ijassa-1009	197	20	perform	perform	VERB
ijassa-1009	197	21	a	a	DET
ijassa-1009	197	22	little	little	ADJ
ijassa-1009	197	23	better	well	ADJ
ijassa-1009	197	24	than	than	ADP
ijassa-1009	197	25	the	the	DET
ijassa-1009	197	26	inception	inception	ADJ
ijassa-1009	197	27	network	network	NOUN
ijassa-1009	197	28	.	.	PUNCT
ijassa-1009	198	1	the	the	DET
ijassa-1009	198	2	input	input	NOUN
ijassa-1009	198	3	image	image	NOUN
ijassa-1009	198	4	was	be	AUX
ijassa-1009	198	5	first	first	ADV
ijassa-1009	198	6	sent	send	VERB
ijassa-1009	198	7	through	through	ADP
ijassa-1009	198	8	the	the	DET
ijassa-1009	198	9	entry	entry	NOUN
ijassa-1009	198	10	flow	flow	NOUN
ijassa-1009	198	11	in	in	ADP
ijassa-1009	198	12	this	this	DET
ijassa-1009	198	13	analysis	analysis	NOUN
ijassa-1009	198	14	,	,	PUNCT
ijassa-1009	198	15	then	then	ADV
ijassa-1009	198	16	eight	eight	NUM
ijassa-1009	198	17	times	time	NOUN
ijassa-1009	198	18	through	through	ADP
ijassa-1009	198	19	the	the	DET
ijassa-1009	198	20	middle	middle	ADJ
ijassa-1009	198	21	flow	flow	NOUN
ijassa-1009	198	22	,	,	PUNCT
ijassa-1009	198	23	and	and	CCONJ
ijassa-1009	198	24	finally	finally	ADV
ijassa-1009	198	25	through	through	ADP
ijassa-1009	198	26	the	the	DET
ijassa-1009	198	27	exit	exit	NOUN
ijassa-1009	198	28	flow	flow	NOUN
ijassa-1009	198	29	that	that	PRON
ijassa-1009	198	30	includes	include	VERB
ijassa-1009	198	31	a	a	DET
ijassa-1009	198	32	softmax	softmax	NOUN
ijassa-1009	198	33	layer	layer	NOUN
ijassa-1009	198	34	.	.	PUNCT
ijassa-1009	199	1	50	50	NUM
ijassa-1009	199	2	naveen	naveen	NOUN
ijassa-1009	199	3	et	et	PROPN
ijassa-1009	199	4	al	al	PROPN
ijassa-1009	199	5	.	.	PUNCT
ijassa-1009	200	1	copyright	copyright	PROPN
ijassa-1009	200	2	©	©	PROPN
ijassa-1009	200	3	2021	2021	NUM
ijassa-1009	200	4	assa	assa	NOUN
ijassa-1009	200	5	.	.	PUNCT
ijassa-1009	201	1	adv	adv	PROPN
ijassa-1009	201	2	.	.	PUNCT
ijassa-1009	202	1	in	in	ADP
ijassa-1009	202	2	systems	system	NOUN
ijassa-1009	202	3	science	science	NOUN
ijassa-1009	202	4	and	and	CCONJ
ijassa-1009	202	5	appl	appl	NOUN
ijassa-1009	202	6	.	.	PUNCT
ijassa-1009	203	1	(	(	PUNCT
ijassa-1009	203	2	2021	2021	NUM
ijassa-1009	203	3	)	)	PUNCT
ijassa-1009	203	4	fig	fig	NOUN
ijassa-1009	203	5	.	.	PUNCT
ijassa-1009	204	1	4.4.1	4.4.1	X
ijassa-1009	204	2	.	.	PUNCT
ijassa-1009	205	1	architecture	architecture	NOUN
ijassa-1009	205	2	of	of	ADP
ijassa-1009	205	3	the	the	DET
ijassa-1009	205	4	xception	xception	PROPN
ijassa-1009	205	5	model	model	NOUN
ijassa-1009	205	6	.	.	PUNCT
ijassa-1009	206	1	5	5	X
ijassa-1009	206	2	.	.	PUNCT
ijassa-1009	206	3	computational	computational	ADJ
ijassa-1009	206	4	experimental	experimental	ADJ
ijassa-1009	206	5	setup	setup	NOUN
ijassa-1009	206	6	in	in	ADP
ijassa-1009	206	7	this	this	DET
ijassa-1009	206	8	research	research	NOUN
ijassa-1009	206	9	paper	paper	NOUN
ijassa-1009	206	10	,	,	PUNCT
ijassa-1009	206	11	the	the	DET
ijassa-1009	206	12	proposed	propose	VERB
ijassa-1009	206	13	architecture	architecture	NOUN
ijassa-1009	206	14	is	be	AUX
ijassa-1009	206	15	to	to	PART
ijassa-1009	206	16	demonstrate	demonstrate	VERB
ijassa-1009	206	17	the	the	DET
ijassa-1009	206	18	pipeline	pipeline	NOUN
ijassa-1009	206	19	model	model	NOUN
ijassa-1009	206	20	that	that	PRON
ijassa-1009	206	21	assembled	assemble	VERB
ijassa-1009	206	22	would	would	AUX
ijassa-1009	206	23	optimize	optimize	VERB
ijassa-1009	206	24	the	the	DET
ijassa-1009	206	25	outcome	outcome	NOUN
ijassa-1009	206	26	and	and	CCONJ
ijassa-1009	206	27	evaluate	evaluate	VERB
ijassa-1009	206	28	all	all	DET
ijassa-1009	206	29	model	model	NOUN
ijassa-1009	206	30	results	result	NOUN
ijassa-1009	206	31	,	,	PUNCT
ijassa-1009	206	32	then	then	ADV
ijassa-1009	206	33	compare	compare	VERB
ijassa-1009	206	34	model	model	NOUN
ijassa-1009	206	35	accuracy	accuracy	NOUN
ijassa-1009	206	36	,	,	PUNCT
ijassa-1009	206	37	training	training	NOUN
ijassa-1009	206	38	time	time	NOUN
ijassa-1009	206	39	,	,	PUNCT
ijassa-1009	206	40	and	and	CCONJ
ijassa-1009	206	41	model	model	NOUN
ijassa-1009	206	42	loss	loss	NOUN
ijassa-1009	206	43	of	of	ADP
ijassa-1009	206	44	the	the	DET
ijassa-1009	206	45	vgg16	vgg16	PROPN
ijassa-1009	206	46	,	,	PUNCT
ijassa-1009	206	47	resnet50	resnet50	NOUN
ijassa-1009	206	48	,	,	PUNCT
ijassa-1009	206	49	inceptionv3	inceptionv3	NOUN
ijassa-1009	206	50	,	,	PUNCT
ijassa-1009	206	51	and	and	CCONJ
ijassa-1009	206	52	xception	xception	NOUN
ijassa-1009	206	53	algorithms	algorithm	VERB
ijassa-1009	206	54	on	on	ADP
ijassa-1009	206	55	the	the	DET
ijassa-1009	206	56	dataset	dataset	NOUN
ijassa-1009	206	57	while	while	SCONJ
ijassa-1009	206	58	training	training	NOUN
ijassa-1009	206	59	.	.	PUNCT
ijassa-1009	207	1	the	the	DET
ijassa-1009	207	2	classification	classification	NOUN
ijassa-1009	207	3	model	model	NOUN
ijassa-1009	207	4	is	be	AUX
ijassa-1009	207	5	evaluated	evaluate	VERB
ijassa-1009	207	6	in	in	ADP
ijassa-1009	207	7	terms	term	NOUN
ijassa-1009	207	8	of	of	ADP
ijassa-1009	207	9	precision	precision	NOUN
ijassa-1009	207	10	,	,	PUNCT
ijassa-1009	207	11	recall	recall	NOUN
ijassa-1009	207	12	,	,	PUNCT
ijassa-1009	207	13	and	and	CCONJ
ijassa-1009	207	14	f1	f1	NOUN
ijassa-1009	207	15	-	-	PUNCT
ijassa-1009	207	16	score	score	NOUN
ijassa-1009	207	17	and	and	CCONJ
ijassa-1009	207	18	is	be	AUX
ijassa-1009	207	19	applied	apply	VERB
ijassa-1009	207	20	to	to	ADP
ijassa-1009	207	21	the	the	DET
ijassa-1009	207	22	dataset	dataset	NOUN
ijassa-1009	207	23	after	after	SCONJ
ijassa-1009	207	24	data	datum	NOUN
ijassa-1009	207	25	set	set	VERB
ijassa-1009	207	26	collection	collection	NOUN
ijassa-1009	207	27	and	and	CCONJ
ijassa-1009	207	28	using	use	VERB
ijassa-1009	207	29	different	different	ADJ
ijassa-1009	207	30	data	datum	NOUN
ijassa-1009	207	31	preprocessing	preprocesse	VERB
ijassa-1009	207	32	techniques	technique	NOUN
ijassa-1009	207	33	[	[	X
ijassa-1009	207	34	29	29	NUM
ijassa-1009	207	35	]	]	PUNCT
ijassa-1009	207	36	.	.	PUNCT
ijassa-1009	208	1	transfer	transfer	NOUN
ijassa-1009	208	2	learning	learn	VERB
ijassa-1009	208	3	modules	module	NOUN
ijassa-1009	208	4	from	from	ADP
ijassa-1009	208	5	deep	deep	ADJ
ijassa-1009	208	6	learning	learning	NOUN
ijassa-1009	208	7	were	be	AUX
ijassa-1009	208	8	implemented	implement	VERB
ijassa-1009	208	9	.	.	PUNCT
ijassa-1009	209	1	several	several	ADJ
ijassa-1009	209	2	machine	machine	NOUN
ijassa-1009	209	3	learning	learning	NOUN
ijassa-1009	209	4	libraries	library	NOUN
ijassa-1009	209	5	such	such	ADJ
ijassa-1009	209	6	as	as	ADP
ijassa-1009	209	7	tensorflow	tensorflow	NOUN
ijassa-1009	209	8	2.3.2	2.3.2	NUM
ijassa-1009	209	9	,	,	PUNCT
ijassa-1009	209	10	sklearn	sklearn	PROPN
ijassa-1009	209	11	,	,	PUNCT
ijassa-1009	209	12	seaborn	seaborn	PROPN
ijassa-1009	209	13	,	,	PUNCT
ijassa-1009	209	14	numpy	numpy	NOUN
ijassa-1009	209	15	,	,	PUNCT
ijassa-1009	209	16	matplotlib	matplotlib	PROPN
ijassa-1009	209	17	,	,	PUNCT
ijassa-1009	209	18	and	and	CCONJ
ijassa-1009	209	19	opencv	opencv	PROPN
ijassa-1009	209	20	are	be	AUX
ijassa-1009	209	21	used	use	VERB
ijassa-1009	209	22	to	to	PART
ijassa-1009	209	23	incorporate	incorporate	VERB
ijassa-1009	209	24	all	all	DET
ijassa-1009	209	25	transfer	transfer	NOUN
ijassa-1009	209	26	learning	learning	NOUN
ijassa-1009	209	27	,	,	PUNCT
ijassa-1009	209	28	and	and	CCONJ
ijassa-1009	209	29	the	the	DET
ijassa-1009	209	30	training	training	NOUN
ijassa-1009	209	31	and	and	CCONJ
ijassa-1009	209	32	testing	testing	NOUN
ijassa-1009	209	33	procedures	procedure	NOUN
ijassa-1009	209	34	are	be	AUX
ijassa-1009	209	35	carried	carry	VERB
ijassa-1009	209	36	out	out	ADP
ijassa-1009	209	37	on	on	ADP
ijassa-1009	209	38	the	the	DET
ijassa-1009	209	39	google	google	PROPN
ijassa-1009	209	40	colab	colab	PROPN
ijassa-1009	209	41	platform	platform	NOUN
ijassa-1009	209	42	.	.	PUNCT
ijassa-1009	210	1	all	all	DET
ijassa-1009	210	2	the	the	DET
ijassa-1009	210	3	experiments	experiment	NOUN
ijassa-1009	210	4	presented	present	VERB
ijassa-1009	210	5	in	in	ADP
ijassa-1009	210	6	this	this	DET
ijassa-1009	210	7	paper	paper	NOUN
ijassa-1009	210	8	have	have	AUX
ijassa-1009	210	9	been	be	AUX
ijassa-1009	210	10	performed	perform	VERB
ijassa-1009	210	11	on	on	ADP
ijassa-1009	210	12	google	google	PROPN
ijassa-1009	210	13	colaboratory	colaboratory	PROPN
ijassa-1009	210	14	with	with	ADP
ijassa-1009	210	15	the	the	DET
ijassa-1009	210	16	use	use	NOUN
ijassa-1009	210	17	of	of	ADP
ijassa-1009	210	18	gpu	gpu	PROPN
ijassa-1009	210	19	,	,	PUNCT
ijassa-1009	210	20	tesla	tesla	PROPN
ijassa-1009	210	21	k80	k80	ADJ
ijassa-1009	210	22	graphical	graphical	ADJ
ijassa-1009	210	23	processing	processing	NOUN
ijassa-1009	210	24	unit	unit	NOUN
ijassa-1009	210	25	with	with	ADP
ijassa-1009	210	26	12	12	NUM
ijassa-1009	210	27	gb	gb	PROPN
ijassa-1009	210	28	gddr5	gddr5	NOUN
ijassa-1009	210	29	vram	vram	NOUN
ijassa-1009	210	30	hardware	hardware	NOUN
ijassa-1009	210	31	from	from	ADP
ijassa-1009	210	32	the	the	DET
ijassa-1009	210	33	online	online	ADJ
ijassa-1009	210	34	cloud	cloud	NOUN
ijassa-1009	210	35	service	service	NOUN
ijassa-1009	210	36	that	that	PRON
ijassa-1009	210	37	is	be	AUX
ijassa-1009	210	38	available	available	ADJ
ijassa-1009	210	39	for	for	ADP
ijassa-1009	210	40	free	free	ADJ
ijassa-1009	210	41	.	.	PUNCT
ijassa-1009	211	1	the	the	DET
ijassa-1009	211	2	cnn	cnn	PROPN
ijassa-1009	211	3	models	model	NOUN
ijassa-1009	211	4	(	(	PUNCT
ijassa-1009	211	5	resnet50	resnet50	NOUN
ijassa-1009	211	6	,	,	PUNCT
ijassa-1009	211	7	vgg16	vgg16	PROPN
ijassa-1009	211	8	,	,	PUNCT
ijassa-1009	211	9	inceptionv3	inceptionv3	NOUN
ijassa-1009	211	10	,	,	PUNCT
ijassa-1009	211	11	and	and	CCONJ
ijassa-1009	211	12	xception	xception	NOUN
ijassa-1009	211	13	)	)	PUNCT
ijassa-1009	211	14	pre	pre	VERB
ijassa-1009	211	15	-	-	VERB
ijassa-1009	211	16	trained	train	VERB
ijassa-1009	211	17	on	on	ADP
ijassa-1009	211	18	the	the	DET
ijassa-1009	211	19	imagenet	imagenet	NOUN
ijassa-1009	211	20	dataset	dataset	NOUN
ijassa-1009	211	21	are	be	AUX
ijassa-1009	211	22	used	use	VERB
ijassa-1009	211	23	with	with	ADP
ijassa-1009	211	24	random	random	ADJ
ijassa-1009	211	25	initialization	initialization	NOUN
ijassa-1009	211	26	weights	weight	NOUN
ijassa-1009	211	27	,	,	PUNCT
ijassa-1009	211	28	and	and	CCONJ
ijassa-1009	211	29	adaptive	adaptive	ADJ
ijassa-1009	211	30	moment	moment	NOUN
ijassa-1009	211	31	estimation	estimation	NOUN
ijassa-1009	211	32	(	(	PUNCT
ijassa-1009	211	33	adam	adam	PROPN
ijassa-1009	211	34	)	)	PUNCT
ijassa-1009	211	35	optimization	optimization	NOUN
ijassa-1009	211	36	of	of	ADP
ijassa-1009	211	37	the	the	DET
ijassa-1009	211	38	cross	cross	ADJ
ijassa-1009	211	39	-	-	ADJ
ijassa-1009	211	40	entropy	entropy	ADJ
ijassa-1009	211	41	function	function	NOUN
ijassa-1009	211	42	has	have	AUX
ijassa-1009	211	43	been	be	AUX
ijassa-1009	211	44	performed	perform	VERB
ijassa-1009	211	45	.	.	PUNCT
ijassa-1009	212	1	there	there	PRON
ijassa-1009	212	2	has	have	AUX
ijassa-1009	212	3	been	be	AUX
ijassa-1009	212	4	a	a	DET
ijassa-1009	212	5	random	random	ADJ
ijassa-1009	212	6	division	division	NOUN
ijassa-1009	212	7	of	of	ADP
ijassa-1009	212	8	data	datum	NOUN
ijassa-1009	212	9	into	into	ADP
ijassa-1009	212	10	two	two	NUM
ijassa-1009	212	11	separate	separate	ADJ
ijassa-1009	212	12	datasets	dataset	NOUN
ijassa-1009	212	13	(	(	PUNCT
ijassa-1009	212	14	train	train	NOUN
ijassa-1009	212	15	&	&	CCONJ
ijassa-1009	212	16	test	test	NOUN
ijassa-1009	212	17	)	)	PUNCT
ijassa-1009	212	18	of	of	ADP
ijassa-1009	212	19	80	80	NUM
ijassa-1009	212	20	%	%	NOUN
ijassa-1009	212	21	and	and	CCONJ
ijassa-1009	212	22	20	20	NUM
ijassa-1009	212	23	%	%	NOUN
ijassa-1009	212	24	for	for	ADP
ijassa-1009	212	25	training	training	NOUN
ijassa-1009	212	26	and	and	CCONJ
ijassa-1009	212	27	testing	testing	NOUN
ijassa-1009	212	28	,	,	PUNCT
ijassa-1009	212	29	respectively	respectively	ADV
ijassa-1009	212	30	.	.	PUNCT
ijassa-1009	213	1	for	for	ADP
ijassa-1009	213	2	all	all	DET
ijassa-1009	213	3	experiments	experiment	NOUN
ijassa-1009	213	4	,	,	PUNCT
ijassa-1009	213	5	the	the	DET
ijassa-1009	213	6	batch	batch	NOUN
ijassa-1009	213	7	size	size	NOUN
ijassa-1009	213	8	of	of	ADP
ijassa-1009	213	9	32	32	NUM
ijassa-1009	213	10	,	,	PUNCT
ijassa-1009	213	11	a	a	DET
ijassa-1009	213	12	learning	learn	VERB
ijassa-1009	213	13	rate	rate	NOUN
ijassa-1009	213	14	of	of	ADP
ijassa-1009	213	15	0.00001	0.00001	NUM
ijassa-1009	213	16	,	,	PUNCT
ijassa-1009	213	17	and	and	CCONJ
ijassa-1009	213	18	a	a	DET
ijassa-1009	213	19	number	number	NOUN
ijassa-1009	213	20	of	of	ADP
ijassa-1009	213	21	epochs	epoch	NOUN
ijassa-1009	213	22	of	of	ADP
ijassa-1009	213	23	500	500	NUM
ijassa-1009	213	24	were	be	AUX
ijassa-1009	213	25	respectively	respectively	ADV
ijassa-1009	213	26	used	use	VERB
ijassa-1009	213	27	.	.	PUNCT
ijassa-1009	214	1	these	these	PRON
ijassa-1009	214	2	are	be	AUX
ijassa-1009	214	3	some	some	PRON
ijassa-1009	214	4	of	of	ADP
ijassa-1009	214	5	the	the	DET
ijassa-1009	214	6	results	result	NOUN
ijassa-1009	214	7	after	after	ADP
ijassa-1009	214	8	applying	apply	VERB
ijassa-1009	214	9	all	all	DET
ijassa-1009	214	10	the	the	DET
ijassa-1009	214	11	algorithms	algorithm	NOUN
ijassa-1009	214	12	.	.	PUNCT
ijassa-1009	215	1	,	,	PUNCT
ijassa-1009	215	2	deep	deep	ADJ
ijassa-1009	215	3	learning	learning	NOUN
ijassa-1009	215	4	techniques	technique	NOUN
ijassa-1009	215	5	for	for	ADP
ijassa-1009	215	6	detection	detection	NOUN
ijassa-1009	215	7	of	of	ADP
ijassa-1009	215	8	covid-19	covid-19	PROPN
ijassa-1009	215	9	51	51	NUM
ijassa-1009	215	10	copyright	copyright	NOUN
ijassa-1009	215	11	©	©	PROPN
ijassa-1009	215	12	2021	2021	NUM
ijassa-1009	215	13	assa	assa	NOUN
ijassa-1009	215	14	.	.	PUNCT
ijassa-1009	216	1	adv	adv	PROPN
ijassa-1009	216	2	.	.	PUNCT
ijassa-1009	217	1	in	in	ADP
ijassa-1009	217	2	systems	system	NOUN
ijassa-1009	217	3	science	science	NOUN
ijassa-1009	217	4	and	and	CCONJ
ijassa-1009	217	5	appl	appl	NOUN
ijassa-1009	217	6	.	.	PUNCT
ijassa-1009	218	1	(	(	PUNCT
ijassa-1009	218	2	2021	2021	NUM
ijassa-1009	218	3	)	)	PUNCT
ijassa-1009	218	4	5.1	5.1	NUM
ijassa-1009	218	5	vgg16	vgg16	NOUN
ijassa-1009	218	6	fig	fig	NOUN
ijassa-1009	218	7	.	.	PUNCT
ijassa-1009	219	1	5.1.1	5.1.1	NOUN
ijassa-1009	219	2	.	.	PUNCT
ijassa-1009	220	1	epoch	epoch	NOUN
ijassa-1009	220	2	vs	vs	ADP
ijassa-1009	220	3	accuracy	accuracy	NOUN
ijassa-1009	220	4	in	in	ADP
ijassa-1009	220	5	fig	fig	NOUN
ijassa-1009	220	6	.	.	PUNCT
ijassa-1009	221	1	5.1.1	5.1.1	X
ijassa-1009	221	2	.	.	PUNCT
ijassa-1009	222	1	in	in	ADP
ijassa-1009	222	2	this	this	DET
ijassa-1009	222	3	model	model	NOUN
ijassa-1009	222	4	accuracy	accuracy	NOUN
ijassa-1009	222	5	,	,	PUNCT
ijassa-1009	222	6	the	the	DET
ijassa-1009	222	7	x	x	NOUN
ijassa-1009	222	8	-	-	ADJ
ijassa-1009	222	9	axis	axis	NOUN
ijassa-1009	222	10	indicates	indicate	VERB
ijassa-1009	222	11	the	the	DET
ijassa-1009	222	12	epoch	epoch	NOUN
ijassa-1009	222	13	and	and	CCONJ
ijassa-1009	222	14	the	the	DET
ijassa-1009	222	15	y	y	NOUN
ijassa-1009	222	16	-	-	PUNCT
ijassa-1009	222	17	axis	axis	NOUN
ijassa-1009	222	18	indicates	indicate	VERB
ijassa-1009	222	19	the	the	DET
ijassa-1009	222	20	accuracy	accuracy	NOUN
ijassa-1009	222	21	of	of	ADP
ijassa-1009	222	22	training	training	NOUN
ijassa-1009	222	23	and	and	CCONJ
ijassa-1009	222	24	testing	testing	NOUN
ijassa-1009	222	25	of	of	ADP
ijassa-1009	222	26	data	datum	NOUN
ijassa-1009	222	27	which	which	PRON
ijassa-1009	222	28	displays	display	VERB
ijassa-1009	222	29	the	the	DET
ijassa-1009	222	30	graph	graph	NOUN
ijassa-1009	222	31	of	of	ADP
ijassa-1009	222	32	our	our	PRON
ijassa-1009	222	33	dataset	dataset	NOUN
ijassa-1009	222	34	.	.	PUNCT
ijassa-1009	223	1	fig	fig	NOUN
ijassa-1009	223	2	.	.	PUNCT
ijassa-1009	224	1	5.1.2	5.1.2	X
ijassa-1009	224	2	.	.	X
ijassa-1009	224	3	epoch	epoch	NOUN
ijassa-1009	224	4	vs	vs	ADP
ijassa-1009	224	5	loss	loss	NOUN
ijassa-1009	224	6	in	in	ADP
ijassa-1009	224	7	fig	fig	NOUN
ijassa-1009	224	8	.	.	PUNCT
ijassa-1009	225	1	5.1.2	5.1.2	NUM
ijassa-1009	225	2	.	.	X
ijassa-1009	225	3	in	in	ADP
ijassa-1009	225	4	this	this	DET
ijassa-1009	225	5	model	model	NOUN
ijassa-1009	225	6	loss	loss	NOUN
ijassa-1009	225	7	,	,	PUNCT
ijassa-1009	225	8	the	the	DET
ijassa-1009	225	9	x	x	NOUN
ijassa-1009	225	10	-	-	ADJ
ijassa-1009	225	11	axis	axis	NOUN
ijassa-1009	225	12	indicates	indicate	VERB
ijassa-1009	225	13	the	the	DET
ijassa-1009	225	14	epoch	epoch	NOUN
ijassa-1009	225	15	and	and	CCONJ
ijassa-1009	225	16	the	the	DET
ijassa-1009	225	17	y	y	NOUN
ijassa-1009	225	18	-	-	PUNCT
ijassa-1009	225	19	axis	axis	NOUN
ijassa-1009	225	20	indicates	indicate	VERB
ijassa-1009	225	21	the	the	DET
ijassa-1009	225	22	accuracy	accuracy	NOUN
ijassa-1009	225	23	of	of	ADP
ijassa-1009	225	24	training	training	NOUN
ijassa-1009	225	25	and	and	CCONJ
ijassa-1009	225	26	testing	testing	NOUN
ijassa-1009	225	27	of	of	ADP
ijassa-1009	225	28	data	datum	NOUN
ijassa-1009	225	29	which	which	PRON
ijassa-1009	225	30	displays	display	VERB
ijassa-1009	225	31	the	the	DET
ijassa-1009	225	32	graph	graph	NOUN
ijassa-1009	225	33	of	of	ADP
ijassa-1009	225	34	our	our	PRON
ijassa-1009	225	35	dataset	dataset	NOUN
ijassa-1009	225	36	.	.	PUNCT
ijassa-1009	226	1	5.2	5.2	NUM
ijassa-1009	226	2	resnet50	resnet50	NOUN
ijassa-1009	226	3	fig	fig	NOUN
ijassa-1009	226	4	.	.	PUNCT
ijassa-1009	227	1	5.2.1	5.2.1	X
ijassa-1009	227	2	.	.	PUNCT
ijassa-1009	228	1	epoch	epoch	NOUN
ijassa-1009	228	2	vs	vs	ADP
ijassa-1009	228	3	accuracy	accuracy	NOUN
ijassa-1009	228	4	in	in	ADP
ijassa-1009	228	5	fig	fig	NOUN
ijassa-1009	228	6	.	.	PUNCT
ijassa-1009	229	1	5.2.1	5.2.1	NUM
ijassa-1009	229	2	,	,	PUNCT
ijassa-1009	229	3	the	the	DET
ijassa-1009	229	4	graph	graph	NOUN
ijassa-1009	229	5	displays	display	VERB
ijassa-1009	229	6	the	the	DET
ijassa-1009	229	7	model	model	NOUN
ijassa-1009	229	8	accuracy	accuracy	NOUN
ijassa-1009	229	9	of	of	ADP
ijassa-1009	229	10	epoch	epoch	NOUN
ijassa-1009	229	11	with	with	ADP
ijassa-1009	229	12	respect	respect	NOUN
ijassa-1009	229	13	to	to	ADP
ijassa-1009	229	14	accuracy	accuracy	NOUN
ijassa-1009	229	15	for	for	ADP
ijassa-1009	229	16	the	the	DET
ijassa-1009	229	17	resnet50	resnet50	NOUN
ijassa-1009	229	18	model	model	NOUN
ijassa-1009	229	19	.	.	PUNCT
ijassa-1009	230	1	52	52	NUM
ijassa-1009	230	2	naveen	naveen	NOUN
ijassa-1009	230	3	et	et	PROPN
ijassa-1009	230	4	al	al	PROPN
ijassa-1009	230	5	.	.	PUNCT
ijassa-1009	231	1	copyright	copyright	PROPN
ijassa-1009	231	2	©	©	PROPN
ijassa-1009	231	3	2021	2021	NUM
ijassa-1009	231	4	assa	assa	NOUN
ijassa-1009	231	5	.	.	PUNCT
ijassa-1009	232	1	adv	adv	PROPN
ijassa-1009	232	2	.	.	PUNCT
ijassa-1009	233	1	in	in	ADP
ijassa-1009	233	2	systems	system	NOUN
ijassa-1009	233	3	science	science	NOUN
ijassa-1009	233	4	and	and	CCONJ
ijassa-1009	233	5	appl	appl	NOUN
ijassa-1009	233	6	.	.	PUNCT
ijassa-1009	234	1	(	(	PUNCT
ijassa-1009	234	2	2021	2021	NUM
ijassa-1009	234	3	)	)	PUNCT
ijassa-1009	234	4	fig	fig	NOUN
ijassa-1009	234	5	.	.	PUNCT
ijassa-1009	235	1	5.2.2	5.2.2	NUM
ijassa-1009	235	2	.	.	PUNCT
ijassa-1009	236	1	epoch	epoch	NOUN
ijassa-1009	236	2	vs	vs	ADP
ijassa-1009	236	3	loss	loss	NOUN
ijassa-1009	236	4	in	in	ADP
ijassa-1009	236	5	fig	fig	NOUN
ijassa-1009	236	6	.	.	PUNCT
ijassa-1009	237	1	5.2.1	5.2.1	NUM
ijassa-1009	237	2	,	,	PUNCT
ijassa-1009	237	3	the	the	DET
ijassa-1009	237	4	graph	graph	NOUN
ijassa-1009	237	5	displays	display	VERB
ijassa-1009	237	6	the	the	DET
ijassa-1009	237	7	model	model	NOUN
ijassa-1009	237	8	loss	loss	NOUN
ijassa-1009	237	9	of	of	ADP
ijassa-1009	237	10	epoch	epoch	NOUN
ijassa-1009	237	11	with	with	ADP
ijassa-1009	237	12	respect	respect	NOUN
ijassa-1009	237	13	to	to	ADP
ijassa-1009	237	14	for	for	ADP
ijassa-1009	237	15	resnet50	resnet50	NOUN
ijassa-1009	237	16	model	model	NOUN
ijassa-1009	237	17	.	.	PUNCT
ijassa-1009	238	1	5.3	5.3	NUM
ijassa-1009	238	2	inceptionv3	inceptionv3	NOUN
ijassa-1009	238	3	fig	fig	NOUN
ijassa-1009	238	4	.	.	PUNCT
ijassa-1009	239	1	5.3.1	5.3.1	X
ijassa-1009	239	2	.	.	PUNCT
ijassa-1009	240	1	epoch	epoch	PROPN
ijassa-1009	240	2	vs	vs	ADP
ijassa-1009	240	3	accuracy	accuracy	NOUN
ijassa-1009	240	4	in	in	ADP
ijassa-1009	240	5	fig	fig	NOUN
ijassa-1009	240	6	.	.	PUNCT
ijassa-1009	241	1	5.3.1	5.3.1	X
ijassa-1009	241	2	.	.	PUNCT
ijassa-1009	242	1	in	in	ADP
ijassa-1009	242	2	this	this	DET
ijassa-1009	242	3	model	model	NOUN
ijassa-1009	242	4	accuracy	accuracy	NOUN
ijassa-1009	242	5	,	,	PUNCT
ijassa-1009	242	6	the	the	DET
ijassa-1009	242	7	x	x	NOUN
ijassa-1009	242	8	-	-	ADJ
ijassa-1009	242	9	axis	axis	NOUN
ijassa-1009	242	10	indicates	indicate	VERB
ijassa-1009	242	11	the	the	DET
ijassa-1009	242	12	epoch	epoch	NOUN
ijassa-1009	242	13	and	and	CCONJ
ijassa-1009	242	14	the	the	DET
ijassa-1009	242	15	y	y	NOUN
ijassa-1009	242	16	-	-	PUNCT
ijassa-1009	242	17	axis	axis	NOUN
ijassa-1009	242	18	indicates	indicate	VERB
ijassa-1009	242	19	the	the	DET
ijassa-1009	242	20	accuracy	accuracy	NOUN
ijassa-1009	242	21	of	of	ADP
ijassa-1009	242	22	training	training	NOUN
ijassa-1009	242	23	and	and	CCONJ
ijassa-1009	242	24	testing	testing	NOUN
ijassa-1009	242	25	of	of	ADP
ijassa-1009	242	26	data	datum	NOUN
ijassa-1009	242	27	which	which	PRON
ijassa-1009	242	28	displays	display	VERB
ijassa-1009	242	29	the	the	DET
ijassa-1009	242	30	graph	graph	NOUN
ijassa-1009	242	31	of	of	ADP
ijassa-1009	242	32	our	our	PRON
ijassa-1009	242	33	dataset	dataset	NOUN
ijassa-1009	242	34	for	for	ADP
ijassa-1009	242	35	the	the	DET
ijassa-1009	242	36	inceptionv3	inceptionv3	NOUN
ijassa-1009	242	37	model	model	NOUN
ijassa-1009	242	38	.	.	PUNCT
ijassa-1009	243	1	fig	fig	NOUN
ijassa-1009	243	2	.	.	PUNCT
ijassa-1009	244	1	5.3.2	5.3.2	X
ijassa-1009	244	2	.	.	PUNCT
ijassa-1009	245	1	epoch	epoch	NOUN
ijassa-1009	245	2	vs	vs	ADP
ijassa-1009	245	3	loss	loss	NOUN
ijassa-1009	245	4	in	in	ADP
ijassa-1009	245	5	fig	fig	NOUN
ijassa-1009	245	6	.	.	PUNCT
ijassa-1009	246	1	5.3.2	5.3.2	X
ijassa-1009	246	2	.	.	PUNCT
ijassa-1009	247	1	in	in	ADP
ijassa-1009	247	2	this	this	DET
ijassa-1009	247	3	model	model	NOUN
ijassa-1009	247	4	loss	loss	NOUN
ijassa-1009	247	5	,	,	PUNCT
ijassa-1009	247	6	the	the	DET
ijassa-1009	247	7	x	x	NOUN
ijassa-1009	247	8	-	-	ADJ
ijassa-1009	247	9	axis	axis	NOUN
ijassa-1009	247	10	indicates	indicate	VERB
ijassa-1009	247	11	the	the	DET
ijassa-1009	247	12	epoch	epoch	NOUN
ijassa-1009	247	13	and	and	CCONJ
ijassa-1009	247	14	the	the	DET
ijassa-1009	247	15	y	y	NOUN
ijassa-1009	247	16	-	-	PUNCT
ijassa-1009	247	17	axis	axis	NOUN
ijassa-1009	247	18	indicates	indicate	VERB
ijassa-1009	247	19	the	the	DET
ijassa-1009	247	20	accuracy	accuracy	NOUN
ijassa-1009	247	21	of	of	ADP
ijassa-1009	247	22	training	training	NOUN
ijassa-1009	247	23	and	and	CCONJ
ijassa-1009	247	24	testing	testing	NOUN
ijassa-1009	247	25	of	of	ADP
ijassa-1009	247	26	data	datum	NOUN
ijassa-1009	247	27	which	which	PRON
ijassa-1009	247	28	displays	display	VERB
ijassa-1009	247	29	the	the	DET
ijassa-1009	247	30	graph	graph	NOUN
ijassa-1009	247	31	of	of	ADP
ijassa-1009	247	32	our	our	PRON
ijassa-1009	247	33	dataset	dataset	NOUN
ijassa-1009	247	34	for	for	ADP
ijassa-1009	247	35	the	the	DET
ijassa-1009	247	36	inceptionv3	inceptionv3	NOUN
ijassa-1009	247	37	model	model	NOUN
ijassa-1009	247	38	.	.	PUNCT
ijassa-1009	248	1	deep	deep	ADJ
ijassa-1009	248	2	learning	learning	NOUN
ijassa-1009	248	3	techniques	technique	NOUN
ijassa-1009	248	4	for	for	ADP
ijassa-1009	248	5	detection	detection	NOUN
ijassa-1009	248	6	of	of	ADP
ijassa-1009	248	7	covid-19	covid-19	PROPN
ijassa-1009	248	8	53	53	NUM
ijassa-1009	248	9	copyright	copyright	NOUN
ijassa-1009	248	10	©	©	PROPN
ijassa-1009	248	11	2021	2021	NUM
ijassa-1009	248	12	assa	assa	NOUN
ijassa-1009	248	13	.	.	PUNCT
ijassa-1009	249	1	adv	adv	PROPN
ijassa-1009	249	2	.	.	PUNCT
ijassa-1009	250	1	in	in	ADP
ijassa-1009	250	2	systems	system	NOUN
ijassa-1009	250	3	science	science	NOUN
ijassa-1009	250	4	and	and	CCONJ
ijassa-1009	250	5	appl	appl	NOUN
ijassa-1009	250	6	.	.	PUNCT
ijassa-1009	251	1	(	(	PUNCT
ijassa-1009	251	2	2021	2021	NUM
ijassa-1009	251	3	)	)	PUNCT
ijassa-1009	251	4	5.4	5.4	NUM
ijassa-1009	251	5	xception	xception	PROPN
ijassa-1009	251	6	fig	fig	NOUN
ijassa-1009	251	7	.	.	PUNCT
ijassa-1009	252	1	5.4.1	5.4.1	X
ijassa-1009	252	2	.	.	PUNCT
ijassa-1009	253	1	epoch	epoch	PROPN
ijassa-1009	253	2	vs	vs	ADP
ijassa-1009	253	3	accuracy	accuracy	NOUN
ijassa-1009	253	4	in	in	ADP
ijassa-1009	253	5	fig	fig	NOUN
ijassa-1009	253	6	.	.	PUNCT
ijassa-1009	254	1	5.4.1	5.4.1	NUM
ijassa-1009	254	2	,	,	PUNCT
ijassa-1009	254	3	the	the	DET
ijassa-1009	254	4	graph	graph	NOUN
ijassa-1009	254	5	displays	display	VERB
ijassa-1009	254	6	the	the	DET
ijassa-1009	254	7	model	model	NOUN
ijassa-1009	254	8	accuracy	accuracy	NOUN
ijassa-1009	254	9	of	of	ADP
ijassa-1009	254	10	epoch	epoch	NOUN
ijassa-1009	254	11	with	with	ADP
ijassa-1009	254	12	respect	respect	NOUN
ijassa-1009	254	13	to	to	ADP
ijassa-1009	254	14	accuracy	accuracy	NOUN
ijassa-1009	254	15	for	for	ADP
ijassa-1009	254	16	the	the	DET
ijassa-1009	254	17	xception	xception	PROPN
ijassa-1009	254	18	model	model	PROPN
ijassa-1009	254	19	.	.	PUNCT
ijassa-1009	255	1	fig	fig	NOUN
ijassa-1009	255	2	.	.	PUNCT
ijassa-1009	256	1	5.4.2	5.4.2	X
ijassa-1009	256	2	.	.	PUNCT
ijassa-1009	257	1	epoch	epoch	NOUN
ijassa-1009	257	2	vs	vs	ADP
ijassa-1009	257	3	loss	loss	NOUN
ijassa-1009	257	4	in	in	ADP
ijassa-1009	257	5	fig	fig	NOUN
ijassa-1009	257	6	.	.	PUNCT
ijassa-1009	258	1	5.4.2	5.4.2	NUM
ijassa-1009	258	2	,	,	PUNCT
ijassa-1009	258	3	the	the	DET
ijassa-1009	258	4	graph	graph	NOUN
ijassa-1009	258	5	displays	display	VERB
ijassa-1009	258	6	the	the	DET
ijassa-1009	258	7	model	model	NOUN
ijassa-1009	258	8	loss	loss	NOUN
ijassa-1009	258	9	of	of	ADP
ijassa-1009	258	10	epoch	epoch	NOUN
ijassa-1009	258	11	with	with	ADP
ijassa-1009	258	12	respect	respect	NOUN
ijassa-1009	258	13	to	to	ADP
ijassa-1009	258	14	loss	loss	NOUN
ijassa-1009	258	15	for	for	ADP
ijassa-1009	258	16	the	the	DET
ijassa-1009	258	17	xception	xception	PROPN
ijassa-1009	258	18	model	model	NOUN
ijassa-1009	258	19	.	.	PUNCT
ijassa-1009	259	1	if	if	SCONJ
ijassa-1009	259	2	true	true	ADJ
ijassa-1009	259	3	positive	positive	ADJ
ijassa-1009	259	4	is	be	AUX
ijassa-1009	259	5	categorized	categorize	VERB
ijassa-1009	259	6	as	as	ADP
ijassa-1009	259	7	the	the	DET
ijassa-1009	259	8	number	number	NOUN
ijassa-1009	259	9	of	of	ADP
ijassa-1009	259	10	covid-19	covid-19	PROPN
ijassa-1009	259	11	chest	chest	NOUN
ijassa-1009	259	12	x	x	NOUN
ijassa-1009	259	13	-	-	NOUN
ijassa-1009	259	14	ray	ray	NOUN
ijassa-1009	259	15	images	image	NOUN
ijassa-1009	259	16	;	;	PUNCT
ijassa-1009	259	17	false	false	ADJ
ijassa-1009	259	18	negative	negative	NOUN
ijassa-1009	259	19	is	be	AUX
ijassa-1009	259	20	the	the	DET
ijassa-1009	259	21	number	number	NOUN
ijassa-1009	259	22	of	of	ADP
ijassa-1009	259	23	covid-19	covid-19	PROPN
ijassa-1009	259	24	chest	chest	NOUN
ijassa-1009	259	25	x	x	NOUN
ijassa-1009	259	26	-	-	NOUN
ijassa-1009	259	27	ray	ray	NOUN
ijassa-1009	259	28	images	image	NOUN
ijassa-1009	259	29	misclassifies	misclassifie	NOUN
ijassa-1009	259	30	as	as	ADP
ijassa-1009	259	31	normal	normal	ADJ
ijassa-1009	259	32	;	;	PUNCT
ijassa-1009	259	33	false	false	ADJ
ijassa-1009	259	34	positive	positive	ADJ
ijassa-1009	259	35	is	be	AUX
ijassa-1009	259	36	the	the	DET
ijassa-1009	259	37	number	number	NOUN
ijassa-1009	259	38	of	of	ADP
ijassa-1009	259	39	normal	normal	ADJ
ijassa-1009	259	40	chest	chest	NOUN
ijassa-1009	259	41	x	x	NOUN
ijassa-1009	259	42	-	-	NOUN
ijassa-1009	259	43	ray	ray	NOUN
ijassa-1009	259	44	images	image	NOUN
ijassa-1009	259	45	misclassified	misclassifie	VERB
ijassa-1009	259	46	as	as	ADP
ijassa-1009	259	47	covid-19	covid-19	PROPN
ijassa-1009	259	48	;	;	PUNCT
ijassa-1009	259	49	the	the	DET
ijassa-1009	259	50	true	true	ADJ
ijassa-1009	259	51	negative	negative	NOUN
ijassa-1009	259	52	is	be	AUX
ijassa-1009	259	53	the	the	DET
ijassa-1009	259	54	normal	normal	ADJ
ijassa-1009	259	55	number	number	NOUN
ijassa-1009	259	56	of	of	ADP
ijassa-1009	259	57	chest	chest	NOUN
ijassa-1009	259	58	x	x	NOUN
ijassa-1009	259	59	-	-	NOUN
ijassa-1009	259	60	ray	ray	NOUN
ijassa-1009	259	61	images	image	NOUN
ijassa-1009	259	62	.	.	PUNCT
ijassa-1009	260	1	in	in	ADP
ijassa-1009	260	2	the	the	DET
ijassa-1009	260	3	convergence	convergence	NOUN
ijassa-1009	260	4	graph	graph	NOUN
ijassa-1009	260	5	field	field	NOUN
ijassa-1009	260	6	,	,	PUNCT
ijassa-1009	260	7	it	it	PRON
ijassa-1009	260	8	is	be	AUX
ijassa-1009	260	9	a	a	DET
ijassa-1009	260	10	standard	standard	ADJ
ijassa-1009	260	11	measure	measure	NOUN
ijassa-1009	260	12	to	to	PART
ijassa-1009	260	13	check	check	VERB
ijassa-1009	260	14	how	how	SCONJ
ijassa-1009	260	15	quickly	quickly	ADV
ijassa-1009	260	16	the	the	DET
ijassa-1009	260	17	model	model	NOUN
ijassa-1009	260	18	is	be	AUX
ijassa-1009	260	19	able	able	ADJ
ijassa-1009	260	20	to	to	PART
ijassa-1009	260	21	classify	classify	VERB
ijassa-1009	260	22	the	the	DET
ijassa-1009	260	23	data	datum	NOUN
ijassa-1009	260	24	.	.	PUNCT
ijassa-1009	261	1	accuracy	accuracy	NOUN
ijassa-1009	261	2	,	,	PUNCT
ijassa-1009	261	3	recall	recall	NOUN
ijassa-1009	261	4	,	,	PUNCT
ijassa-1009	261	5	f1score	f1score	NOUN
ijassa-1009	261	6	,	,	PUNCT
ijassa-1009	261	7	accuracy	accuracy	NOUN
ijassa-1009	261	8	is	be	AUX
ijassa-1009	261	9	defined	define	VERB
ijassa-1009	261	10	and	and	CCONJ
ijassa-1009	261	11	the	the	DET
ijassa-1009	261	12	following	follow	VERB
ijassa-1009	261	13	equations	equation	NOUN
ijassa-1009	261	14	will	will	AUX
ijassa-1009	261	15	describe	describe	VERB
ijassa-1009	261	16	them	they	PRON
ijassa-1009	261	17	.	.	PUNCT
ijassa-1009	262	1	precision	precision	NOUN
ijassa-1009	262	2	=	=	PUNCT
ijassa-1009	262	3	!	!	PUNCT
ijassa-1009	262	4	"	"	PUNCT
ijassa-1009	262	5	!	!	PUNCT
ijassa-1009	263	1	"	"	PUNCT
ijassa-1009	263	2	#	#	SYM
ijassa-1009	263	3	$	$	SYM
ijassa-1009	263	4	"	"	PUNCT
ijassa-1009	263	5	.	.	PUNCT
ijassa-1009	264	1	(	(	PUNCT
ijassa-1009	264	2	5.1	5.1	NUM
ijassa-1009	264	3	)	)	PUNCT
ijassa-1009	264	4	recall	recall	NOUN
ijassa-1009	264	5	=	=	PUNCT
ijassa-1009	264	6	!	!	PUNCT
ijassa-1009	264	7	"	"	PUNCT
ijassa-1009	264	8	!	!	PUNCT
ijassa-1009	265	1	"	"	PUNCT
ijassa-1009	265	2	#	#	SYM
ijassa-1009	265	3	$	$	SYM
ijassa-1009	265	4	&	&	CCONJ
ijassa-1009	265	5	.	.	PUNCT
ijassa-1009	266	1	(	(	PUNCT
ijassa-1009	266	2	5.2	5.2	NUM
ijassa-1009	266	3	)	)	PUNCT
ijassa-1009	266	4	f1	f1	NOUN
ijassa-1009	266	5	-	-	PUNCT
ijassa-1009	266	6	score	score	NOUN
ijassa-1009	266	7	=	=	PUNCT
ijassa-1009	266	8	'	'	PUNCT
ijassa-1009	266	9	∗("*+,-.-/0∗1+,233	∗("*+,-.-/0∗1+,233	PROPN
ijassa-1009	266	10	)	)	PUNCT
ijassa-1009	266	11	"	"	PUNCT
ijassa-1009	266	12	*	*	PUNCT
ijassa-1009	266	13	+	+	ADJ
ijassa-1009	266	14	,	,	PUNCT
ijassa-1009	266	15	-.-/0#1+,233	-.-/0#1+,233	NOUN
ijassa-1009	266	16	.	.	PUNCT
ijassa-1009	267	1	(	(	PUNCT
ijassa-1009	267	2	5.3	5.3	NUM
ijassa-1009	267	3	)	)	PUNCT
ijassa-1009	267	4	accuracy	accuracy	NOUN
ijassa-1009	267	5	:	:	PUNCT
ijassa-1009	267	6	it	it	PRON
ijassa-1009	267	7	is	be	AUX
ijassa-1009	267	8	defining	define	VERB
ijassa-1009	267	9	as	as	ADP
ijassa-1009	267	10	the	the	DET
ijassa-1009	267	11	number	number	NOUN
ijassa-1009	267	12	of	of	ADP
ijassa-1009	267	13	true	true	ADJ
ijassa-1009	267	14	positives	positive	NOUN
ijassa-1009	267	15	and	and	CCONJ
ijassa-1009	267	16	true	true	ADJ
ijassa-1009	267	17	negatives	negative	NOUN
ijassa-1009	267	18	by	by	ADP
ijassa-1009	267	19	the	the	DET
ijassa-1009	267	20	number	number	NOUN
ijassa-1009	267	21	of	of	ADP
ijassa-1009	267	22	true	true	ADJ
ijassa-1009	267	23	positives	positive	NOUN
ijassa-1009	267	24	,	,	PUNCT
ijassa-1009	267	25	true	true	ADJ
ijassa-1009	267	26	negatives	negative	NOUN
ijassa-1009	267	27	,	,	PUNCT
ijassa-1009	267	28	false	false	ADJ
ijassa-1009	267	29	positives	positive	NOUN
ijassa-1009	267	30	,	,	PUNCT
ijassa-1009	267	31	and	and	CCONJ
ijassa-1009	267	32	false	false	ADJ
ijassa-1009	267	33	negatives	negative	NOUN
ijassa-1009	267	34	.	.	PUNCT
ijassa-1009	268	1	accuracy	accuracy	NOUN
ijassa-1009	268	2	=	=	SYM
ijassa-1009	268	3	𝑇𝑃+𝑇𝑁	𝑇𝑃+𝑇𝑁	NOUN
ijassa-1009	268	4	!	!	PUNCT
ijassa-1009	269	1	"	"	PUNCT
ijassa-1009	269	2	#	#	X
ijassa-1009	269	3	!	!	PUNCT
ijassa-1009	269	4	&	&	CCONJ
ijassa-1009	269	5	#	#	SYM
ijassa-1009	269	6	$	$	SYM
ijassa-1009	269	7	"	"	PUNCT
ijassa-1009	269	8	#	#	SYM
ijassa-1009	269	9	$	$	SYM
ijassa-1009	269	10	&	&	CCONJ
ijassa-1009	269	11	.	.	PUNCT
ijassa-1009	270	1	(	(	PUNCT
ijassa-1009	270	2	5.4	5.4	NUM
ijassa-1009	270	3	)	)	PUNCT
ijassa-1009	270	4	54	54	NUM
ijassa-1009	270	5	naveen	naveen	NOUN
ijassa-1009	270	6	et	et	PROPN
ijassa-1009	270	7	al	al	PROPN
ijassa-1009	270	8	.	.	PUNCT
ijassa-1009	271	1	copyright	copyright	PROPN
ijassa-1009	271	2	©	©	PROPN
ijassa-1009	271	3	2021	2021	NUM
ijassa-1009	271	4	assa	assa	NOUN
ijassa-1009	271	5	.	.	PUNCT
ijassa-1009	272	1	adv	adv	PROPN
ijassa-1009	272	2	.	.	PUNCT
ijassa-1009	273	1	in	in	ADP
ijassa-1009	273	2	systems	system	NOUN
ijassa-1009	273	3	science	science	NOUN
ijassa-1009	273	4	and	and	CCONJ
ijassa-1009	273	5	appl	appl	NOUN
ijassa-1009	273	6	.	.	PUNCT
ijassa-1009	274	1	(	(	PUNCT
ijassa-1009	274	2	2021	2021	NUM
ijassa-1009	274	3	)	)	PUNCT
ijassa-1009	274	4	table	table	NOUN
ijassa-1009	274	5	5.1	5.1	NUM
ijassa-1009	274	6	.	.	PUNCT
ijassa-1009	275	1	classification	classification	NOUN
ijassa-1009	275	2	report	report	NOUN
ijassa-1009	275	3	of	of	ADP
ijassa-1009	275	4	all	all	DET
ijassa-1009	275	5	algorithms	algorithm	NOUN
ijassa-1009	275	6	.	.	PUNCT
ijassa-1009	276	1	algorithms	algorithms	PROPN
ijassa-1009	276	2	precision	precision	NOUN
ijassa-1009	276	3	recall	recall	VERB
ijassa-1009	276	4	f1	f1	NOUN
ijassa-1009	276	5	-	-	PUNCT
ijassa-1009	276	6	score	score	NOUN
ijassa-1009	276	7	accuracy	accuracy	NOUN
ijassa-1009	276	8	vgg16	vgg16	NOUN
ijassa-1009	276	9	0.90	0.90	NUM
ijassa-1009	276	10	0.89	0.89	NUM
ijassa-1009	276	11	0.89	0.89	NUM
ijassa-1009	276	12	0.91	0.91	NUM
ijassa-1009	276	13	resnet50	resnet50	NOUN
ijassa-1009	276	14	0.83	0.83	NUM
ijassa-1009	276	15	0.82	0.82	NUM
ijassa-1009	276	16	0.82	0.82	NUM
ijassa-1009	276	17	0.83	0.83	NUM
ijassa-1009	276	18	inceptionv3	inceptionv3	NOUN
ijassa-1009	276	19	0.96	0.96	NUM
ijassa-1009	276	20	0.96	0.96	NUM
ijassa-1009	276	21	0.96	0.96	NUM
ijassa-1009	276	22	0.96	0.96	NUM
ijassa-1009	276	23	xception	xception	NOUN
ijassa-1009	276	24	0.91	0.91	NUM
ijassa-1009	276	25	0.91	0.91	NUM
ijassa-1009	276	26	0.91	0.91	NUM
ijassa-1009	276	27	0.92	0.92	NUM
ijassa-1009	276	28	fig	fig	NOUN
ijassa-1009	276	29	.	.	PUNCT
ijassa-1009	277	1	5.5.2	5.5.2	NUM
ijassa-1009	277	2	.	.	PUNCT
ijassa-1009	277	3	classification	classification	NOUN
ijassa-1009	277	4	report	report	NOUN
ijassa-1009	277	5	in	in	ADP
ijassa-1009	277	6	the	the	DET
ijassa-1009	277	7	above	above	ADJ
ijassa-1009	277	8	table	table	NOUN
ijassa-1009	277	9	.	.	PUNCT
ijassa-1009	278	1	5.1	5.1	NUM
ijassa-1009	278	2	,	,	PUNCT
ijassa-1009	278	3	the	the	DET
ijassa-1009	278	4	precision	precision	NOUN
ijassa-1009	278	5	,	,	PUNCT
ijassa-1009	278	6	recall	recall	NOUN
ijassa-1009	278	7	,	,	PUNCT
ijassa-1009	278	8	f1	f1	NOUN
ijassa-1009	278	9	-	-	PUNCT
ijassa-1009	278	10	score	score	NOUN
ijassa-1009	278	11	and	and	CCONJ
ijassa-1009	278	12	accuracy	accuracy	NOUN
ijassa-1009	278	13	performances	performance	NOUN
ijassa-1009	278	14	are	be	AUX
ijassa-1009	278	15	listed	list	VERB
ijassa-1009	278	16	after	after	ADP
ijassa-1009	278	17	processing	process	VERB
ijassa-1009	278	18	via	via	ADP
ijassa-1009	278	19	various	various	ADJ
ijassa-1009	278	20	algorithms	algorithm	NOUN
ijassa-1009	278	21	.	.	PUNCT
ijassa-1009	279	1	the	the	DET
ijassa-1009	279	2	algorithms	algorithm	NOUN
ijassa-1009	279	3	are	be	AUX
ijassa-1009	279	4	trained	train	VERB
ijassa-1009	279	5	and	and	CCONJ
ijassa-1009	279	6	probed	probe	VERB
ijassa-1009	279	7	on	on	ADP
ijassa-1009	279	8	the	the	DET
ijassa-1009	279	9	chest	chest	NOUN
ijassa-1009	279	10	x	x	NOUN
ijassa-1009	279	11	-	-	NOUN
ijassa-1009	279	12	ray	ray	NOUN
ijassa-1009	279	13	image	image	NOUN
ijassa-1009	279	14	dataset	dataset	NOUN
ijassa-1009	279	15	of	of	ADP
ijassa-1009	279	16	the	the	DET
ijassa-1009	279	17	pre	pre	ADJ
ijassa-1009	279	18	-	-	ADJ
ijassa-1009	279	19	trained	train	VERB
ijassa-1009	279	20	models	model	NOUN
ijassa-1009	279	21	.	.	PUNCT
ijassa-1009	280	1	in	in	ADP
ijassa-1009	280	2	the	the	DET
ijassa-1009	280	3	above	above	ADJ
ijassa-1009	280	4	figures	figure	NOUN
ijassa-1009	280	5	,	,	PUNCT
ijassa-1009	280	6	the	the	DET
ijassa-1009	280	7	model	model	NOUN
ijassa-1009	280	8	accuracy	accuracy	NOUN
ijassa-1009	280	9	and	and	CCONJ
ijassa-1009	280	10	model	model	NOUN
ijassa-1009	280	11	loss	loss	NOUN
ijassa-1009	280	12	of	of	ADP
ijassa-1009	280	13	the	the	DET
ijassa-1009	280	14	trained	train	VERB
ijassa-1009	280	15	models	model	NOUN
ijassa-1009	280	16	are	be	AUX
ijassa-1009	280	17	given	give	VERB
ijassa-1009	280	18	.	.	PUNCT
ijassa-1009	281	1	it	it	PRON
ijassa-1009	281	2	can	can	AUX
ijassa-1009	281	3	be	be	AUX
ijassa-1009	281	4	said	say	VERB
ijassa-1009	281	5	that	that	SCONJ
ijassa-1009	281	6	for	for	ADP
ijassa-1009	281	7	the	the	DET
ijassa-1009	281	8	initiation	initiation	NOUN
ijassa-1009	281	9	,	,	PUNCT
ijassa-1009	281	10	the	the	DET
ijassa-1009	281	11	highest	high	ADJ
ijassa-1009	281	12	model	model	NOUN
ijassa-1009	281	13	training	training	NOUN
ijassa-1009	281	14	accuracy	accuracy	NOUN
ijassa-1009	281	15	is	be	AUX
ijassa-1009	281	16	obtained	obtain	VERB
ijassa-1009	281	17	for	for	ADP
ijassa-1009	281	18	inceptionv3	inceptionv3	NOUN
ijassa-1009	281	19	and	and	CCONJ
ijassa-1009	281	20	the	the	DET
ijassa-1009	281	21	training	training	NOUN
ijassa-1009	281	22	is	be	AUX
ijassa-1009	281	23	carried	carry	VERB
ijassa-1009	281	24	out	out	ADP
ijassa-1009	281	25	for	for	ADP
ijassa-1009	281	26	500	500	NUM
ijassa-1009	281	27	epochs	epoch	NOUN
ijassa-1009	281	28	.	.	PUNCT
ijassa-1009	282	1	it	it	PRON
ijassa-1009	282	2	can	can	AUX
ijassa-1009	282	3	be	be	AUX
ijassa-1009	282	4	analyzed	analyze	VERB
ijassa-1009	282	5	that	that	SCONJ
ijassa-1009	282	6	from	from	ADP
ijassa-1009	282	7	the	the	DET
ijassa-1009	282	8	model	model	NOUN
ijassa-1009	282	9	loss	loss	NOUN
ijassa-1009	282	10	figures	figure	NOUN
ijassa-1009	282	11	that	that	SCONJ
ijassa-1009	282	12	the	the	DET
ijassa-1009	282	13	loss	loss	NOUN
ijassa-1009	282	14	values	value	NOUN
ijassa-1009	282	15	are	be	AUX
ijassa-1009	282	16	reduced	reduce	VERB
ijassa-1009	282	17	in	in	ADP
ijassa-1009	282	18	all	all	DET
ijassa-1009	282	19	pre	pre	ADJ
ijassa-1009	282	20	-	-	ADJ
ijassa-1009	282	21	trained	train	VERB
ijassa-1009	282	22	models	model	NOUN
ijassa-1009	282	23	,	,	PUNCT
ijassa-1009	282	24	and	and	CCONJ
ijassa-1009	282	25	with	with	ADP
ijassa-1009	282	26	the	the	DET
ijassa-1009	282	27	help	help	NOUN
ijassa-1009	282	28	of	of	ADP
ijassa-1009	282	29	the	the	DET
ijassa-1009	282	30	confusion	confusion	NOUN
ijassa-1009	282	31	matrix	matrix	NOUN
ijassa-1009	282	32	,	,	PUNCT
ijassa-1009	282	33	a	a	DET
ijassa-1009	282	34	comparison	comparison	NOUN
ijassa-1009	282	35	of	of	ADP
ijassa-1009	282	36	all	all	DET
ijassa-1009	282	37	algorithms	algorithm	NOUN
ijassa-1009	282	38	is	be	AUX
ijassa-1009	282	39	listed	list	VERB
ijassa-1009	282	40	out	out	ADP
ijassa-1009	282	41	based	base	VERB
ijassa-1009	282	42	on	on	ADP
ijassa-1009	282	43	performance	performance	NOUN
ijassa-1009	282	44	from	from	ADP
ijassa-1009	282	45	the	the	DET
ijassa-1009	282	46	classification	classification	NOUN
ijassa-1009	282	47	table	table	NOUN
ijassa-1009	282	48	.	.	PUNCT
ijassa-1009	283	1	after	after	ADP
ijassa-1009	283	2	comparing	compare	VERB
ijassa-1009	283	3	the	the	DET
ijassa-1009	283	4	precision	precision	NOUN
ijassa-1009	283	5	,	,	PUNCT
ijassa-1009	283	6	recall	recall	NOUN
ijassa-1009	283	7	,	,	PUNCT
ijassa-1009	283	8	f1	f1	NOUN
ijassa-1009	283	9	-	-	PUNCT
ijassa-1009	283	10	score	score	NOUN
ijassa-1009	283	11	,	,	PUNCT
ijassa-1009	283	12	and	and	CCONJ
ijassa-1009	283	13	accuracy	accuracy	NOUN
ijassa-1009	283	14	from	from	ADP
ijassa-1009	283	15	the	the	DET
ijassa-1009	283	16	above	above	ADJ
ijassa-1009	283	17	table	table	NOUN
ijassa-1009	283	18	,	,	PUNCT
ijassa-1009	283	19	the	the	DET
ijassa-1009	283	20	inceptionv3	inceptionv3	NOUN
ijassa-1009	283	21	gives	give	VERB
ijassa-1009	283	22	the	the	DET
ijassa-1009	283	23	best	good	ADJ
ijassa-1009	283	24	results	result	NOUN
ijassa-1009	283	25	in	in	ADP
ijassa-1009	283	26	both	both	CCONJ
ijassa-1009	283	27	the	the	DET
ijassa-1009	283	28	training	training	NOUN
ijassa-1009	283	29	and	and	CCONJ
ijassa-1009	283	30	testing	testing	NOUN
ijassa-1009	283	31	phase	phase	NOUN
ijassa-1009	283	32	and	and	CCONJ
ijassa-1009	283	33	shows	show	VERB
ijassa-1009	283	34	better	well	ADJ
ijassa-1009	283	35	output	output	NOUN
ijassa-1009	283	36	than	than	ADP
ijassa-1009	283	37	the	the	DET
ijassa-1009	283	38	other	other	ADJ
ijassa-1009	283	39	three	three	NUM
ijassa-1009	283	40	models	model	NOUN
ijassa-1009	283	41	.	.	PUNCT
ijassa-1009	284	1	0,75	0,75	NOUN
ijassa-1009	284	2	0,8	0,8	NUM
ijassa-1009	284	3	0,85	0,85	PUNCT
ijassa-1009	285	1	0,9	0,9	NUM
ijassa-1009	285	2	0,95	0,95	SYM
ijassa-1009	285	3	1	1	NUM
ijassa-1009	285	4	vgg16	vgg16	NOUN
ijassa-1009	285	5	resnet50	resnet50	NOUN
ijassa-1009	285	6	inceptionv3	inceptionv3	PROPN
ijassa-1009	285	7	xception	xception	PROPN
ijassa-1009	285	8	classification	classification	NOUN
ijassa-1009	285	9	report	report	NOUN
ijassa-1009	285	10	precision	precision	NOUN
ijassa-1009	285	11	recall	recall	VERB
ijassa-1009	285	12	f1	f1	NOUN
ijassa-1009	285	13	-	-	PUNCT
ijassa-1009	285	14	score	score	NOUN
ijassa-1009	285	15	accuracy	accuracy	NOUN
ijassa-1009	285	16	deep	deep	ADJ
ijassa-1009	285	17	learning	learning	NOUN
ijassa-1009	285	18	techniques	technique	NOUN
ijassa-1009	285	19	for	for	ADP
ijassa-1009	285	20	detection	detection	NOUN
ijassa-1009	285	21	of	of	ADP
ijassa-1009	285	22	covid-19	covid-19	PROPN
ijassa-1009	285	23	55	55	NUM
ijassa-1009	285	24	copyright	copyright	NOUN
ijassa-1009	285	25	©	©	PROPN
ijassa-1009	285	26	2021	2021	NUM
ijassa-1009	285	27	assa	assa	NOUN
ijassa-1009	285	28	.	.	PUNCT
ijassa-1009	286	1	adv	adv	PROPN
ijassa-1009	286	2	.	.	PUNCT
ijassa-1009	287	1	in	in	ADP
ijassa-1009	287	2	systems	system	NOUN
ijassa-1009	287	3	science	science	NOUN
ijassa-1009	287	4	and	and	CCONJ
ijassa-1009	287	5	appl	appl	NOUN
ijassa-1009	287	6	.	.	PUNCT
ijassa-1009	288	1	(	(	PUNCT
ijassa-1009	288	2	2021	2021	NUM
ijassa-1009	288	3	)	)	PUNCT
ijassa-1009	288	4	6	6	NUM
ijassa-1009	288	5	.	.	X
ijassa-1009	288	6	conclusion	conclusion	NOUN
ijassa-1009	288	7	early	early	ADJ
ijassa-1009	288	8	prediction	prediction	NOUN
ijassa-1009	288	9	of	of	ADP
ijassa-1009	288	10	coronavirus	coronavirus	NOUN
ijassa-1009	288	11	is	be	AUX
ijassa-1009	288	12	vital	vital	ADJ
ijassa-1009	288	13	to	to	PART
ijassa-1009	288	14	prevent	prevent	VERB
ijassa-1009	288	15	the	the	DET
ijassa-1009	288	16	spread	spread	NOUN
ijassa-1009	288	17	of	of	ADP
ijassa-1009	288	18	the	the	DET
ijassa-1009	288	19	disease	disease	NOUN
ijassa-1009	288	20	among	among	ADP
ijassa-1009	288	21	other	other	ADJ
ijassa-1009	288	22	people	people	NOUN
ijassa-1009	288	23	.	.	PUNCT
ijassa-1009	289	1	so	so	ADV
ijassa-1009	289	2	,	,	PUNCT
ijassa-1009	289	3	the	the	DET
ijassa-1009	289	4	use	use	NOUN
ijassa-1009	289	5	of	of	ADP
ijassa-1009	289	6	deep	deep	ADJ
ijassa-1009	289	7	learning	learning	NOUN
ijassa-1009	289	8	algorithms	algorithm	NOUN
ijassa-1009	289	9	for	for	ADP
ijassa-1009	289	10	the	the	DET
ijassa-1009	289	11	diagnosis	diagnosis	NOUN
ijassa-1009	289	12	of	of	ADP
ijassa-1009	289	13	covid-19	covid-19	PROPN
ijassa-1009	289	14	has	have	AUX
ijassa-1009	289	15	become	become	VERB
ijassa-1009	289	16	a	a	DET
ijassa-1009	289	17	major	major	ADJ
ijassa-1009	289	18	concern	concern	NOUN
ijassa-1009	289	19	during	during	ADP
ijassa-1009	289	20	this	this	DET
ijassa-1009	289	21	pandemic	pandemic	NOUN
ijassa-1009	289	22	considering	consider	VERB
ijassa-1009	289	23	the	the	DET
ijassa-1009	289	24	accuracies	accuracy	NOUN
ijassa-1009	289	25	and	and	CCONJ
ijassa-1009	289	26	f1	f1	ADJ
ijassa-1009	289	27	score	score	NOUN
ijassa-1009	289	28	of	of	ADP
ijassa-1009	289	29	the	the	DET
ijassa-1009	289	30	present	present	ADJ
ijassa-1009	289	31	algorithms	algorithm	NOUN
ijassa-1009	289	32	.	.	PUNCT
ijassa-1009	290	1	keeping	keep	VERB
ijassa-1009	290	2	that	that	PRON
ijassa-1009	290	3	in	in	ADP
ijassa-1009	290	4	mind	mind	NOUN
ijassa-1009	290	5	,	,	PUNCT
ijassa-1009	290	6	we	we	PRON
ijassa-1009	290	7	came	come	VERB
ijassa-1009	290	8	up	up	ADP
ijassa-1009	290	9	with	with	ADP
ijassa-1009	290	10	better	well	ADJ
ijassa-1009	290	11	accuracies	accuracy	NOUN
ijassa-1009	290	12	for	for	ADP
ijassa-1009	290	13	the	the	DET
ijassa-1009	290	14	algorithm	algorithm	NOUN
ijassa-1009	290	15	compared	compare	VERB
ijassa-1009	290	16	to	to	ADP
ijassa-1009	290	17	the	the	DET
ijassa-1009	290	18	one	one	NOUN
ijassa-1009	290	19	which	which	PRON
ijassa-1009	290	20	is	be	AUX
ijassa-1009	290	21	present	present	ADJ
ijassa-1009	290	22	.	.	PUNCT
ijassa-1009	291	1	we	we	PRON
ijassa-1009	291	2	collected	collect	VERB
ijassa-1009	291	3	a	a	DET
ijassa-1009	291	4	huge	huge	ADJ
ijassa-1009	291	5	dataset	dataset	NOUN
ijassa-1009	291	6	of	of	ADP
ijassa-1009	291	7	x	x	NOUN
ijassa-1009	291	8	-	-	NOUN
ijassa-1009	291	9	ray	ray	NOUN
ijassa-1009	291	10	images	image	NOUN
ijassa-1009	291	11	from	from	ADP
ijassa-1009	291	12	different	different	ADJ
ijassa-1009	291	13	reliable	reliable	ADJ
ijassa-1009	291	14	sources	source	NOUN
ijassa-1009	291	15	and	and	CCONJ
ijassa-1009	291	16	combined	combine	VERB
ijassa-1009	291	17	them	they	PRON
ijassa-1009	291	18	to	to	PART
ijassa-1009	291	19	form	form	VERB
ijassa-1009	291	20	one	one	NUM
ijassa-1009	291	21	.	.	PUNCT
ijassa-1009	292	1	large	large	ADJ
ijassa-1009	292	2	datasets	dataset	NOUN
ijassa-1009	292	3	could	could	AUX
ijassa-1009	292	4	lead	lead	VERB
ijassa-1009	292	5	us	we	PRON
ijassa-1009	292	6	to	to	PART
ijassa-1009	292	7	identify	identify	VERB
ijassa-1009	292	8	coronavirus	coronavirus	NOUN
ijassa-1009	292	9	infection	infection	NOUN
ijassa-1009	292	10	more	more	ADV
ijassa-1009	292	11	accurately	accurately	ADV
ijassa-1009	292	12	and	and	CCONJ
ijassa-1009	292	13	reliably	reliably	ADV
ijassa-1009	292	14	when	when	SCONJ
ijassa-1009	292	15	training	training	NOUN
ijassa-1009	292	16	and	and	CCONJ
ijassa-1009	292	17	testing	test	VERB
ijassa-1009	292	18	the	the	DET
ijassa-1009	292	19	model	model	NOUN
ijassa-1009	292	20	.	.	PUNCT
ijassa-1009	293	1	in	in	ADP
ijassa-1009	293	2	an	an	DET
ijassa-1009	293	3	effort	effort	NOUN
ijassa-1009	293	4	to	to	PART
ijassa-1009	293	5	identify	identify	VERB
ijassa-1009	293	6	the	the	DET
ijassa-1009	293	7	covid19	covid19	NOUN
ijassa-1009	293	8	affected	affect	VERB
ijassa-1009	293	9	patients	patient	NOUN
ijassa-1009	293	10	more	more	ADV
ijassa-1009	293	11	accurately	accurately	ADV
ijassa-1009	293	12	and	and	CCONJ
ijassa-1009	293	13	precisely	precisely	ADV
ijassa-1009	293	14	we	we	PRON
ijassa-1009	293	15	have	have	AUX
ijassa-1009	293	16	implemented	implement	VERB
ijassa-1009	293	17	four	four	NUM
ijassa-1009	293	18	different	different	ADJ
ijassa-1009	293	19	algorithms	algorithm	NOUN
ijassa-1009	293	20	and	and	CCONJ
ijassa-1009	293	21	compared	compare	VERB
ijassa-1009	293	22	each	each	PRON
ijassa-1009	293	23	among	among	ADP
ijassa-1009	293	24	themselves	themselves	PRON
ijassa-1009	293	25	for	for	ADP
ijassa-1009	293	26	better	well	ADJ
ijassa-1009	293	27	results	result	NOUN
ijassa-1009	293	28	.	.	PUNCT
ijassa-1009	294	1	out	out	ADP
ijassa-1009	294	2	of	of	ADP
ijassa-1009	294	3	the	the	DET
ijassa-1009	294	4	four	four	NUM
ijassa-1009	294	5	models	model	NOUN
ijassa-1009	294	6	vgg16	vgg16	PROPN
ijassa-1009	294	7	,	,	PUNCT
ijassa-1009	294	8	resnet50	resnet50	NOUN
ijassa-1009	294	9	,	,	PUNCT
ijassa-1009	294	10	inceptionv3	inceptionv3	NOUN
ijassa-1009	294	11	,	,	PUNCT
ijassa-1009	294	12	and	and	CCONJ
ijassa-1009	294	13	xception	xception	NOUN
ijassa-1009	294	14	.	.	PUNCT
ijassa-1009	295	1	inceptionv3	inceptionv3	NOUN
ijassa-1009	295	2	showed	show	VERB
ijassa-1009	295	3	better	well	ADJ
ijassa-1009	295	4	results	result	NOUN
ijassa-1009	295	5	among	among	ADP
ijassa-1009	295	6	other	other	ADJ
ijassa-1009	295	7	algorithms	algorithm	NOUN
ijassa-1009	295	8	and	and	CCONJ
ijassa-1009	295	9	also	also	ADV
ijassa-1009	295	10	with	with	ADP
ijassa-1009	295	11	the	the	DET
ijassa-1009	295	12	previously	previously	ADV
ijassa-1009	295	13	proposed	propose	VERB
ijassa-1009	295	14	algorithms	algorithm	NOUN
ijassa-1009	295	15	with	with	ADP
ijassa-1009	295	16	an	an	DET
ijassa-1009	295	17	f1	f1	ADJ
ijassa-1009	295	18	score	score	NOUN
ijassa-1009	295	19	of	of	ADP
ijassa-1009	295	20	96	96	NUM
ijassa-1009	295	21	%	%	NOUN
ijassa-1009	295	22	whereas	whereas	SCONJ
ijassa-1009	295	23	the	the	DET
ijassa-1009	295	24	previously	previously	ADV
ijassa-1009	295	25	proposed	propose	VERB
ijassa-1009	295	26	inceptionv3	inceptionv3	NOUN
ijassa-1009	295	27	algorithm	algorithm	NOUN
ijassa-1009	295	28	has	have	VERB
ijassa-1009	295	29	a	a	DET
ijassa-1009	295	30	score	score	NOUN
ijassa-1009	295	31	of	of	ADP
ijassa-1009	295	32	94.8	94.8	NUM
ijassa-1009	295	33	%	%	NOUN
ijassa-1009	295	34	.	.	PUNCT
ijassa-1009	296	1	further	far	ADV
ijassa-1009	296	2	,	,	PUNCT
ijassa-1009	296	3	current	current	ADJ
ijassa-1009	296	4	research	research	NOUN
ijassa-1009	296	5	work	work	NOUN
ijassa-1009	296	6	can	can	AUX
ijassa-1009	296	7	be	be	AUX
ijassa-1009	296	8	enhanced	enhance	VERB
ijassa-1009	296	9	by	by	ADP
ijassa-1009	296	10	improving	improve	VERB
ijassa-1009	296	11	the	the	DET
ijassa-1009	296	12	efficiency	efficiency	NOUN
ijassa-1009	296	13	of	of	ADP
ijassa-1009	296	14	the	the	DET
ijassa-1009	296	15	model	model	NOUN
ijassa-1009	296	16	and	and	CCONJ
ijassa-1009	296	17	also	also	ADV
ijassa-1009	296	18	by	by	ADP
ijassa-1009	296	19	reducing	reduce	VERB
ijassa-1009	296	20	the	the	DET
ijassa-1009	296	21	training	training	NOUN
ijassa-1009	296	22	time	time	NOUN
ijassa-1009	296	23	with	with	ADP
ijassa-1009	296	24	an	an	DET
ijassa-1009	296	25	improved	improved	ADJ
ijassa-1009	296	26	version	version	NOUN
ijassa-1009	296	27	of	of	ADP
ijassa-1009	296	28	the	the	DET
ijassa-1009	296	29	present	present	ADJ
ijassa-1009	296	30	code	code	NOUN
ijassa-1009	296	31	.	.	PUNCT
ijassa-1009	297	1	finally	finally	ADV
ijassa-1009	297	2	,	,	PUNCT
ijassa-1009	297	3	the	the	DET
ijassa-1009	297	4	current	current	ADJ
ijassa-1009	297	5	model	model	NOUN
ijassa-1009	297	6	can	can	AUX
ijassa-1009	297	7	be	be	AUX
ijassa-1009	297	8	deployed	deploy	VERB
ijassa-1009	297	9	across	across	ADP
ijassa-1009	297	10	various	various	ADJ
ijassa-1009	297	11	devices	device	NOUN
ijassa-1009	297	12	such	such	ADJ
ijassa-1009	297	13	as	as	ADP
ijassa-1009	297	14	mobile	mobile	ADJ
ijassa-1009	297	15	phones	phone	NOUN
ijassa-1009	297	16	such	such	ADJ
ijassa-1009	297	17	that	that	SCONJ
ijassa-1009	297	18	patients	patient	NOUN
ijassa-1009	297	19	can	can	AUX
ijassa-1009	297	20	scan	scan	VERB
ijassa-1009	297	21	their	their	PRON
ijassa-1009	297	22	x	x	NOUN
ijassa-1009	297	23	-	-	NOUN
ijassa-1009	297	24	rays	ray	NOUN
ijassa-1009	297	25	and	and	CCONJ
ijassa-1009	297	26	can	can	AUX
ijassa-1009	297	27	get	get	VERB
ijassa-1009	297	28	the	the	DET
ijassa-1009	297	29	prediction	prediction	NOUN
ijassa-1009	297	30	.	.	PUNCT
ijassa-1009	298	1	references	reference	NOUN
ijassa-1009	298	2	1	1	NUM
ijassa-1009	298	3	.	.	PUNCT
ijassa-1009	298	4	abbas	abbas	PROPN
ijassa-1009	298	5	,	,	PUNCT
ijassa-1009	298	6	a.	a.	PROPN
ijassa-1009	298	7	,	,	PUNCT
ijassa-1009	298	8	abdelsamea	abdelsamea	NOUN
ijassa-1009	298	9	,	,	PUNCT
ijassa-1009	298	10	m.	m.	NOUN
ijassa-1009	298	11	m.	m.	NOUN
ijassa-1009	298	12	,	,	PUNCT
ijassa-1009	298	13	&	&	CCONJ
ijassa-1009	298	14	gaber	gaber	PROPN
ijassa-1009	298	15	,	,	PUNCT
ijassa-1009	298	16	m.	m.	NOUN
ijassa-1009	298	17	m.	m.	NOUN
ijassa-1009	298	18	(	(	PUNCT
ijassa-1009	298	19	2020	2020	NUM
ijassa-1009	298	20	)	)	PUNCT
ijassa-1009	298	21	.	.	PUNCT
ijassa-1009	299	1	classification	classification	NOUN
ijassa-1009	299	2	of	of	ADP
ijassa-1009	299	3	covid-19	covid-19	PROPN
ijassa-1009	299	4	in	in	ADP
ijassa-1009	299	5	chest	chest	NOUN
ijassa-1009	299	6	x	x	NOUN
ijassa-1009	299	7	-	-	NOUN
ijassa-1009	299	8	ray	ray	NOUN
ijassa-1009	299	9	images	image	NOUN
ijassa-1009	299	10	using	use	VERB
ijassa-1009	299	11	detrac	detrac	NOUN
ijassa-1009	299	12	deep	deep	ADJ
ijassa-1009	299	13	convolutional	convolutional	ADJ
ijassa-1009	299	14	neural	neural	ADJ
ijassa-1009	299	15	network	network	NOUN
ijassa-1009	299	16	.	.	PUNCT
ijassa-1009	300	1	arxiv	arxiv	PROPN
ijassa-1009	300	2	preprint	preprint	NOUN
ijassa-1009	300	3	arxiv:2003.13815	arxiv:2003.13815	NOUN
ijassa-1009	300	4	.	.	PUNCT
ijassa-1009	301	1	2	2	X
ijassa-1009	301	2	.	.	X
ijassa-1009	301	3	apostolopoulos	apostolopoulos	PROPN
ijassa-1009	301	4	,	,	PUNCT
ijassa-1009	301	5	i.	i.	PROPN
ijassa-1009	301	6	d.	d.	PROPN
ijassa-1009	301	7	,	,	PUNCT
ijassa-1009	301	8	&	&	CCONJ
ijassa-1009	301	9	mpesiana	mpesiana	PROPN
ijassa-1009	301	10	,	,	PUNCT
ijassa-1009	301	11	t.	t.	NOUN
ijassa-1009	301	12	a.	a.	NOUN
ijassa-1009	301	13	(	(	PUNCT
ijassa-1009	301	14	2020	2020	NUM
ijassa-1009	301	15	)	)	PUNCT
ijassa-1009	301	16	.	.	PUNCT
ijassa-1009	302	1	covid-19	covid-19	PROPN
ijassa-1009	302	2	:	:	PUNCT
ijassa-1009	302	3	automatic	automatic	ADJ
ijassa-1009	302	4	detection	detection	NOUN
ijassa-1009	302	5	from	from	ADP
ijassa-1009	302	6	xray	xray	ADJ
ijassa-1009	302	7	images	image	NOUN
ijassa-1009	302	8	utilizing	utilize	VERB
ijassa-1009	302	9	transfer	transfer	NOUN
ijassa-1009	302	10	learning	learning	NOUN
ijassa-1009	302	11	with	with	ADP
ijassa-1009	302	12	convolutional	convolutional	ADJ
ijassa-1009	302	13	neural	neural	ADJ
ijassa-1009	302	14	networks	network	NOUN
ijassa-1009	302	15	.	.	PUNCT
ijassa-1009	303	1	physical	physical	ADJ
ijassa-1009	303	2	and	and	CCONJ
ijassa-1009	303	3	engineering	engineering	NOUN
ijassa-1009	303	4	sciences	science	NOUN
ijassa-1009	303	5	in	in	ADP
ijassa-1009	303	6	medicine	medicine	NOUN
ijassa-1009	303	7	,	,	PUNCT
ijassa-1009	303	8	1	1	NUM
ijassa-1009	303	9	.	.	NOUN
ijassa-1009	303	10	3	3	NUM
ijassa-1009	303	11	.	.	X
ijassa-1009	304	1	asif	asif	NOUN
ijassa-1009	304	2	,	,	PUNCT
ijassa-1009	304	3	s.	s.	PROPN
ijassa-1009	304	4	,	,	PUNCT
ijassa-1009	304	5	wenhui	wenhui	PROPN
ijassa-1009	304	6	,	,	PUNCT
ijassa-1009	304	7	y.	y.	PROPN
ijassa-1009	304	8	,	,	PUNCT
ijassa-1009	304	9	jin	jin	PROPN
ijassa-1009	304	10	,	,	PUNCT
ijassa-1009	304	11	h.	h.	PROPN
ijassa-1009	304	12	,	,	PUNCT
ijassa-1009	304	13	tao	tao	PROPN
ijassa-1009	304	14	,	,	PUNCT
ijassa-1009	304	15	y.	y.	PROPN
ijassa-1009	304	16	,	,	PUNCT
ijassa-1009	304	17	&	&	CCONJ
ijassa-1009	304	18	jinhai	jinhai	PROPN
ijassa-1009	304	19	,	,	PUNCT
ijassa-1009	304	20	s.	s.	PROPN
ijassa-1009	304	21	(	(	PUNCT
ijassa-1009	304	22	2020	2020	NUM
ijassa-1009	304	23	)	)	PUNCT
ijassa-1009	304	24	.	.	PUNCT
ijassa-1009	305	1	classification	classification	NOUN
ijassa-1009	305	2	of	of	ADP
ijassa-1009	305	3	covid-19	covid-19	PROPN
ijassa-1009	305	4	from	from	ADP
ijassa-1009	305	5	chest	chest	NOUN
ijassa-1009	305	6	x	x	NOUN
ijassa-1009	305	7	-	-	NOUN
ijassa-1009	305	8	ray	ray	NOUN
ijassa-1009	305	9	images	image	NOUN
ijassa-1009	305	10	using	use	VERB
ijassa-1009	305	11	deep	deep	ADJ
ijassa-1009	305	12	convolutional	convolutional	ADJ
ijassa-1009	305	13	neural	neural	ADJ
ijassa-1009	305	14	networks	network	NOUN
ijassa-1009	305	15	.	.	PUNCT
ijassa-1009	306	1	medrxiv	medrxiv	INTJ
ijassa-1009	306	2	.	.	PROPN
ijassa-1009	307	1	4	4	NUM
ijassa-1009	307	2	.	.	X
ijassa-1009	307	3	cohen	cohen	PROPN
ijassa-1009	307	4	,	,	PUNCT
ijassa-1009	307	5	j.	j.	PROPN
ijassa-1009	307	6	p.	p.	PROPN
ijassa-1009	307	7	,	,	PUNCT
ijassa-1009	307	8	morrison	morrison	PROPN
ijassa-1009	307	9	,	,	PUNCT
ijassa-1009	307	10	p.	p.	PROPN
ijassa-1009	307	11	,	,	PUNCT
ijassa-1009	307	12	dao	dao	PROPN
ijassa-1009	307	13	,	,	PUNCT
ijassa-1009	307	14	l.	l.	PROPN
ijassa-1009	307	15	,	,	PUNCT
ijassa-1009	307	16	roth	roth	PROPN
ijassa-1009	307	17	,	,	PUNCT
ijassa-1009	307	18	k.	k.	PROPN
ijassa-1009	307	19	,	,	PUNCT
ijassa-1009	307	20	duong	duong	PROPN
ijassa-1009	307	21	,	,	PUNCT
ijassa-1009	307	22	t.	t.	PROPN
ijassa-1009	307	23	q.	q.	PROPN
ijassa-1009	307	24	,	,	PUNCT
ijassa-1009	307	25	&	&	CCONJ
ijassa-1009	307	26	ghassemi	ghassemi	PROPN
ijassa-1009	307	27	,	,	PUNCT
ijassa-1009	307	28	m.	m.	NOUN
ijassa-1009	307	29	(	(	PUNCT
ijassa-1009	307	30	2020	2020	NUM
ijassa-1009	307	31	)	)	PUNCT
ijassa-1009	307	32	.	.	PUNCT
ijassa-1009	308	1	covid-19	covid-19	PROPN
ijassa-1009	308	2	image	image	NOUN
ijassa-1009	308	3	data	datum	NOUN
ijassa-1009	308	4	collection	collection	NOUN
ijassa-1009	308	5	:	:	PUNCT
ijassa-1009	308	6	prospective	prospective	ADJ
ijassa-1009	308	7	predictions	prediction	NOUN
ijassa-1009	308	8	are	be	AUX
ijassa-1009	308	9	the	the	DET
ijassa-1009	308	10	future	future	NOUN
ijassa-1009	308	11	.	.	PUNCT
ijassa-1009	309	1	arxiv	arxiv	PROPN
ijassa-1009	309	2	preprint	preprint	NOUN
ijassa-1009	309	3	arxiv:2006.11988	arxiv:2006.11988	NOUN
ijassa-1009	309	4	.	.	PUNCT
ijassa-1009	310	1	5	5	NUM
ijassa-1009	310	2	.	.	X
ijassa-1009	310	3	contini	contini	PROPN
ijassa-1009	310	4	,	,	PUNCT
ijassa-1009	310	5	c.	c.	PROPN
ijassa-1009	310	6	,	,	PUNCT
ijassa-1009	310	7	di	di	NOUN
ijassa-1009	310	8	nuzzo	nuzzo	PROPN
ijassa-1009	310	9	,	,	PUNCT
ijassa-1009	310	10	m.	m.	NOUN
ijassa-1009	310	11	,	,	PUNCT
ijassa-1009	310	12	barp	barp	NOUN
ijassa-1009	310	13	,	,	PUNCT
ijassa-1009	310	14	n.	n.	NOUN
ijassa-1009	310	15	,	,	PUNCT
ijassa-1009	310	16	bonazza	bonazza	NOUN
ijassa-1009	310	17	,	,	PUNCT
ijassa-1009	310	18	a.	a.	NOUN
ijassa-1009	310	19	,	,	PUNCT
ijassa-1009	310	20	de	de	PROPN
ijassa-1009	310	21	giorgio	giorgio	PROPN
ijassa-1009	310	22	,	,	PUNCT
ijassa-1009	310	23	r.	r.	PROPN
ijassa-1009	310	24	,	,	PUNCT
ijassa-1009	310	25	tognon	tognon	NOUN
ijassa-1009	310	26	,	,	PUNCT
ijassa-1009	310	27	m.	m.	NOUN
ijassa-1009	310	28	,	,	PUNCT
ijassa-1009	310	29	&	&	CCONJ
ijassa-1009	310	30	rubino	rubino	PROPN
ijassa-1009	310	31	,	,	PUNCT
ijassa-1009	310	32	s.	s.	PROPN
ijassa-1009	310	33	(	(	PUNCT
ijassa-1009	310	34	2020	2020	NUM
ijassa-1009	310	35	)	)	PUNCT
ijassa-1009	310	36	.	.	PUNCT
ijassa-1009	311	1	the	the	DET
ijassa-1009	311	2	novel	novel	ADJ
ijassa-1009	311	3	zoonotic	zoonotic	ADJ
ijassa-1009	311	4	covid-19	covid-19	PROPN
ijassa-1009	311	5	pandemic	pandemic	NOUN
ijassa-1009	311	6	:	:	PUNCT
ijassa-1009	311	7	an	an	DET
ijassa-1009	311	8	expected	expect	VERB
ijassa-1009	311	9	global	global	ADJ
ijassa-1009	311	10	health	health	NOUN
ijassa-1009	311	11	concern	concern	NOUN
ijassa-1009	311	12	.	.	PUNCT
ijassa-1009	312	1	the	the	DET
ijassa-1009	312	2	journal	journal	NOUN
ijassa-1009	312	3	of	of	ADP
ijassa-1009	312	4	infection	infection	NOUN
ijassa-1009	312	5	in	in	ADP
ijassa-1009	312	6	developing	develop	VERB
ijassa-1009	312	7	countries	country	NOUN
ijassa-1009	312	8	,	,	PUNCT
ijassa-1009	312	9	14(03	14(03	PROPN
ijassa-1009	312	10	)	)	PUNCT
ijassa-1009	312	11	,	,	PUNCT
ijassa-1009	312	12	254	254	NUM
ijassa-1009	312	13	-	-	SYM
ijassa-1009	312	14	264	264	NUM
ijassa-1009	312	15	.	.	NOUN
ijassa-1009	313	1	6	6	NUM
ijassa-1009	313	2	.	.	X
ijassa-1009	313	3	gour	gour	PROPN
ijassa-1009	313	4	,	,	PUNCT
ijassa-1009	313	5	m.	m.	NOUN
ijassa-1009	313	6	,	,	PUNCT
ijassa-1009	313	7	&	&	CCONJ
ijassa-1009	313	8	jain	jain	PROPN
ijassa-1009	313	9	,	,	PUNCT
ijassa-1009	313	10	s.	s.	PROPN
ijassa-1009	313	11	(	(	PUNCT
ijassa-1009	313	12	2020	2020	NUM
ijassa-1009	313	13	)	)	PUNCT
ijassa-1009	313	14	.	.	PUNCT
ijassa-1009	314	1	stacked	stack	VERB
ijassa-1009	314	2	convolutional	convolutional	ADJ
ijassa-1009	314	3	neural	neural	ADJ
ijassa-1009	314	4	network	network	NOUN
ijassa-1009	314	5	for	for	ADP
ijassa-1009	314	6	diagnosis	diagnosis	NOUN
ijassa-1009	314	7	of	of	ADP
ijassa-1009	314	8	covid-19	covid-19	PROPN
ijassa-1009	314	9	disease	disease	NOUN
ijassa-1009	314	10	from	from	ADP
ijassa-1009	314	11	x	x	NOUN
ijassa-1009	314	12	-	-	NOUN
ijassa-1009	314	13	ray	ray	NOUN
ijassa-1009	314	14	images	image	NOUN
ijassa-1009	314	15	.	.	PUNCT
ijassa-1009	315	1	arxiv	arxiv	PROPN
ijassa-1009	315	2	preprint	preprint	NOUN
ijassa-1009	315	3	arxiv:2006.13817	arxiv:2006.13817	NOUN
ijassa-1009	315	4	.	.	PUNCT
ijassa-1009	316	1	7	7	X
ijassa-1009	316	2	.	.	X
ijassa-1009	316	3	haghanifar	haghanifar	PROPN
ijassa-1009	316	4	,	,	PUNCT
ijassa-1009	316	5	a.	a.	PROPN
ijassa-1009	316	6	,	,	PUNCT
ijassa-1009	316	7	majdabadi	majdabadi	NOUN
ijassa-1009	316	8	,	,	PUNCT
ijassa-1009	316	9	m.	m.	NOUN
ijassa-1009	316	10	m.	m.	NOUN
ijassa-1009	316	11	,	,	PUNCT
ijassa-1009	316	12	&	&	CCONJ
ijassa-1009	316	13	ko	ko	PROPN
ijassa-1009	316	14	,	,	PUNCT
ijassa-1009	316	15	s.	s.	PROPN
ijassa-1009	316	16	(	(	PUNCT
ijassa-1009	316	17	2020	2020	NUM
ijassa-1009	316	18	)	)	PUNCT
ijassa-1009	316	19	.	.	PUNCT
ijassa-1009	317	1	covid	covid	NOUN
ijassa-1009	317	2	-	-	PUNCT
ijassa-1009	317	3	cxnet	cxnet	NOUN
ijassa-1009	317	4	:	:	PUNCT
ijassa-1009	317	5	detecting	detect	VERB
ijassa-1009	317	6	covid-19	covid-19	PROPN
ijassa-1009	317	7	in	in	ADP
ijassa-1009	317	8	frontal	frontal	ADJ
ijassa-1009	317	9	chest	chest	NOUN
ijassa-1009	317	10	x	x	NOUN
ijassa-1009	317	11	-	-	NOUN
ijassa-1009	317	12	ray	ray	NOUN
ijassa-1009	317	13	images	image	NOUN
ijassa-1009	317	14	using	use	VERB
ijassa-1009	317	15	deep	deep	ADJ
ijassa-1009	317	16	learning	learning	NOUN
ijassa-1009	317	17	.	.	PUNCT
ijassa-1009	318	1	arxiv	arxiv	PROPN
ijassa-1009	318	2	preprint	preprint	PROPN
ijassa-1009	318	3	arxiv:2006.13807	arxiv:2006.13807	VERB
ijassa-1009	318	4	.	.	PUNCT
ijassa-1009	319	1	8	8	X
ijassa-1009	319	2	.	.	PUNCT
ijassa-1009	320	1	hamzah	hamzah	PROPN
ijassa-1009	320	2	,	,	PUNCT
ijassa-1009	320	3	f.	f.	PROPN
ijassa-1009	320	4	b.	b.	PROPN
ijassa-1009	320	5	,	,	PUNCT
ijassa-1009	320	6	lau	lau	PROPN
ijassa-1009	320	7	,	,	PUNCT
ijassa-1009	320	8	c.	c.	PROPN
ijassa-1009	320	9	,	,	PUNCT
ijassa-1009	320	10	nazri	nazri	PROPN
ijassa-1009	320	11	,	,	PUNCT
ijassa-1009	320	12	h.	h.	PROPN
ijassa-1009	320	13	,	,	PUNCT
ijassa-1009	320	14	ligot	ligot	VERB
ijassa-1009	320	15	,	,	PUNCT
ijassa-1009	320	16	d.	d.	PROPN
ijassa-1009	320	17	v.	v.	PROPN
ijassa-1009	320	18	,	,	PUNCT
ijassa-1009	320	19	et	et	PROPN
ijassa-1009	320	20	.	.	PUNCT
ijassa-1009	321	1	al	al	PROPN
ijassa-1009	321	2	.	.	PROPN
ijassa-1009	321	3	(	(	PUNCT
ijassa-1009	321	4	2020	2020	NUM
ijassa-1009	321	5	)	)	PUNCT
ijassa-1009	321	6	.	.	PUNCT
ijassa-1009	322	1	coronatracker	coronatracker	NOUN
ijassa-1009	322	2	:	:	PUNCT
ijassa-1009	322	3	worldwide	worldwide	PROPN
ijassa-1009	322	4	covid-19	covid-19	PROPN
ijassa-1009	322	5	outbreak	outbreak	NOUN
ijassa-1009	322	6	data	data	VERB
ijassa-1009	322	7	analysis	analysis	NOUN
ijassa-1009	322	8	and	and	CCONJ
ijassa-1009	322	9	prediction	prediction	NOUN
ijassa-1009	322	10	.	.	PUNCT
ijassa-1009	323	1	bull	bull	PROPN
ijassa-1009	323	2	world	world	PROPN
ijassa-1009	323	3	health	health	NOUN
ijassa-1009	323	4	organ	organ	NOUN
ijassa-1009	323	5	,	,	PUNCT
ijassa-1009	323	6	1	1	NUM
ijassa-1009	323	7	,	,	PUNCT
ijassa-1009	323	8	32	32	NUM
ijassa-1009	323	9	.	.	NOUN
ijassa-1009	324	1	9	9	NUM
ijassa-1009	324	2	.	.	X
ijassa-1009	324	3	kassani	kassani	PROPN
ijassa-1009	324	4	,	,	PUNCT
ijassa-1009	324	5	s.	s.	PROPN
ijassa-1009	324	6	h.	h.	PROPN
ijassa-1009	324	7	,	,	PUNCT
ijassa-1009	324	8	kassasni	kassasni	VERB
ijassa-1009	324	9	,	,	PUNCT
ijassa-1009	324	10	p.	p.	PROPN
ijassa-1009	324	11	h.	h.	PROPN
ijassa-1009	324	12	,	,	PUNCT
ijassa-1009	324	13	wesolowski	wesolowski	PROPN
ijassa-1009	324	14	,	,	PUNCT
ijassa-1009	324	15	m.	m.	NOUN
ijassa-1009	324	16	j.	j.	PROPN
ijassa-1009	324	17	,	,	PUNCT
ijassa-1009	324	18	schneider	schneider	PROPN
ijassa-1009	324	19	,	,	PUNCT
ijassa-1009	324	20	k.	k.	PROPN
ijassa-1009	324	21	a.	a.	PROPN
ijassa-1009	324	22	,	,	PUNCT
ijassa-1009	324	23	&	&	CCONJ
ijassa-1009	324	24	deters	deter	NOUN
ijassa-1009	324	25	,	,	PUNCT
ijassa-1009	324	26	r.	r.	PROPN
ijassa-1009	324	27	(	(	PUNCT
ijassa-1009	324	28	2020	2020	NUM
ijassa-1009	324	29	)	)	PUNCT
ijassa-1009	324	30	.	.	PUNCT
ijassa-1009	325	1	automatic	automatic	ADJ
ijassa-1009	325	2	detection	detection	NOUN
ijassa-1009	325	3	of	of	ADP
ijassa-1009	325	4	coronavirus	coronavirus	NOUN
ijassa-1009	325	5	disease	disease	NOUN
ijassa-1009	325	6	(	(	PUNCT
ijassa-1009	325	7	covid-19	covid-19	PROPN
ijassa-1009	325	8	)	)	PUNCT
ijassa-1009	325	9	in	in	ADP
ijassa-1009	325	10	x	x	NOUN
ijassa-1009	325	11	-	-	NOUN
ijassa-1009	325	12	ray	ray	NOUN
ijassa-1009	325	13	and	and	CCONJ
ijassa-1009	325	14	ct	ct	NUM
ijassa-1009	325	15	images	image	NOUN
ijassa-1009	325	16	:	:	PUNCT
ijassa-1009	325	17	a	a	DET
ijassa-1009	325	18	machine	machine	NOUN
ijassa-1009	325	19	learning	learning	NOUN
ijassa-1009	325	20	-	-	PUNCT
ijassa-1009	325	21	based	base	VERB
ijassa-1009	325	22	approach	approach	NOUN
ijassa-1009	325	23	.	.	PUNCT
ijassa-1009	326	1	arxiv	arxiv	PROPN
ijassa-1009	326	2	preprint	preprint	PROPN
ijassa-1009	326	3	arxiv:2004.10641	arxiv:2004.10641	PROPN
ijassa-1009	326	4	.	.	PUNCT
ijassa-1009	327	1	56	56	NUM
ijassa-1009	327	2	naveen	naveen	NOUN
ijassa-1009	327	3	et	et	PROPN
ijassa-1009	327	4	al	al	PROPN
ijassa-1009	327	5	.	.	PUNCT
ijassa-1009	327	6	copyright	copyright	PROPN
ijassa-1009	327	7	©	©	PROPN
ijassa-1009	327	8	2021	2021	NUM
ijassa-1009	327	9	assa	assa	NOUN
ijassa-1009	327	10	.	.	PUNCT
ijassa-1009	328	1	adv	adv	PROPN
ijassa-1009	328	2	.	.	PUNCT
ijassa-1009	329	1	in	in	ADP
ijassa-1009	329	2	systems	system	NOUN
ijassa-1009	329	3	science	science	NOUN
ijassa-1009	329	4	and	and	CCONJ
ijassa-1009	329	5	appl	appl	NOUN
ijassa-1009	329	6	.	.	PUNCT
ijassa-1009	330	1	(	(	PUNCT
ijassa-1009	330	2	2021	2021	NUM
ijassa-1009	330	3	)	)	PUNCT
ijassa-1009	330	4	10	10	NUM
ijassa-1009	330	5	.	.	PUNCT
ijassa-1009	331	1	islam	islam	PROPN
ijassa-1009	331	2	,	,	PUNCT
ijassa-1009	331	3	m.	m.	PROPN
ijassa-1009	331	4	z.	z.	PROPN
ijassa-1009	331	5	,	,	PUNCT
ijassa-1009	331	6	islam	islam	PROPN
ijassa-1009	331	7	,	,	PUNCT
ijassa-1009	331	8	m.	m.	NOUN
ijassa-1009	331	9	m.	m.	NOUN
ijassa-1009	331	10	,	,	PUNCT
ijassa-1009	331	11	&	&	CCONJ
ijassa-1009	331	12	asraf	asraf	NOUN
ijassa-1009	331	13	,	,	PUNCT
ijassa-1009	331	14	a.	a.	NOUN
ijassa-1009	331	15	(	(	PUNCT
ijassa-1009	331	16	2020	2020	NUM
ijassa-1009	331	17	)	)	PUNCT
ijassa-1009	331	18	.	.	PUNCT
ijassa-1009	332	1	a	a	DET
ijassa-1009	332	2	combined	combine	VERB
ijassa-1009	332	3	deep	deep	ADJ
ijassa-1009	332	4	cnn	cnn	PROPN
ijassa-1009	332	5	-	-	PUNCT
ijassa-1009	332	6	lstm	lstm	ADJ
ijassa-1009	332	7	network	network	NOUN
ijassa-1009	332	8	for	for	ADP
ijassa-1009	332	9	the	the	DET
ijassa-1009	332	10	detection	detection	NOUN
ijassa-1009	332	11	of	of	ADP
ijassa-1009	332	12	novel	novel	ADJ
ijassa-1009	332	13	coronavirus	coronavirus	NOUN
ijassa-1009	332	14	(	(	PUNCT
ijassa-1009	332	15	covid-19	covid-19	PROPN
ijassa-1009	332	16	)	)	PUNCT
ijassa-1009	332	17	using	use	VERB
ijassa-1009	332	18	x	x	NOUN
ijassa-1009	332	19	-	-	NOUN
ijassa-1009	332	20	ray	ray	NOUN
ijassa-1009	332	21	images	image	NOUN
ijassa-1009	332	22	.	.	PUNCT
ijassa-1009	333	1	informatics	informatic	NOUN
ijassa-1009	333	2	in	in	ADP
ijassa-1009	333	3	medicine	medicine	NOUN
ijassa-1009	333	4	unlocked	unlock	VERB
ijassa-1009	333	5	,	,	PUNCT
ijassa-1009	333	6	20	20	NUM
ijassa-1009	333	7	,	,	PUNCT
ijassa-1009	333	8	100412	100412	NUM
ijassa-1009	333	9	.	.	PUNCT
ijassa-1009	334	1	11	11	NUM
ijassa-1009	334	2	.	.	X
ijassa-1009	335	1	ismael	ismael	PROPN
ijassa-1009	335	2	,	,	PUNCT
ijassa-1009	335	3	a.	a.	NOUN
ijassa-1009	335	4	m.	m.	NOUN
ijassa-1009	335	5	,	,	PUNCT
ijassa-1009	335	6	&	&	CCONJ
ijassa-1009	335	7	şengür	şengür	NOUN
ijassa-1009	335	8	,	,	PUNCT
ijassa-1009	335	9	a.	a.	NOUN
ijassa-1009	335	10	(	(	PUNCT
ijassa-1009	335	11	2020	2020	NUM
ijassa-1009	335	12	)	)	PUNCT
ijassa-1009	335	13	.	.	PUNCT
ijassa-1009	336	1	deep	deep	ADJ
ijassa-1009	336	2	learning	learning	NOUN
ijassa-1009	336	3	approaches	approach	NOUN
ijassa-1009	336	4	for	for	ADP
ijassa-1009	336	5	covid-19	covid-19	PROPN
ijassa-1009	336	6	detection	detection	NOUN
ijassa-1009	336	7	based	base	VERB
ijassa-1009	336	8	on	on	ADP
ijassa-1009	336	9	chest	chest	NOUN
ijassa-1009	336	10	x	x	NOUN
ijassa-1009	336	11	-	-	NOUN
ijassa-1009	336	12	ray	ray	NOUN
ijassa-1009	336	13	images	image	NOUN
ijassa-1009	336	14	.	.	PUNCT
ijassa-1009	337	1	expert	expert	NOUN
ijassa-1009	337	2	systems	system	NOUN
ijassa-1009	337	3	with	with	ADP
ijassa-1009	337	4	applications	application	NOUN
ijassa-1009	337	5	,	,	PUNCT
ijassa-1009	337	6	164	164	NUM
ijassa-1009	337	7	,	,	PUNCT
ijassa-1009	337	8	114054	114054	NUM
ijassa-1009	337	9	.	.	PUNCT
ijassa-1009	338	1	12	12	NUM
ijassa-1009	338	2	.	.	PUNCT
ijassa-1009	339	1	jain	jain	PROPN
ijassa-1009	339	2	,	,	PUNCT
ijassa-1009	339	3	g.	g.	PROPN
ijassa-1009	339	4	,	,	PUNCT
ijassa-1009	339	5	mittal	mittal	PROPN
ijassa-1009	339	6	,	,	PUNCT
ijassa-1009	339	7	d.	d.	PROPN
ijassa-1009	339	8	,	,	PUNCT
ijassa-1009	339	9	thakur	thakur	PROPN
ijassa-1009	339	10	,	,	PUNCT
ijassa-1009	339	11	d.	d.	PROPN
ijassa-1009	339	12	,	,	PUNCT
ijassa-1009	339	13	&	&	CCONJ
ijassa-1009	339	14	mittal	mittal	PROPN
ijassa-1009	339	15	,	,	PUNCT
ijassa-1009	339	16	m.	m.	NOUN
ijassa-1009	339	17	k.	k.	PROPN
ijassa-1009	339	18	(	(	PUNCT
ijassa-1009	339	19	2020	2020	NUM
ijassa-1009	339	20	)	)	PUNCT
ijassa-1009	339	21	.	.	PUNCT
ijassa-1009	340	1	a	a	DET
ijassa-1009	340	2	deep	deep	ADJ
ijassa-1009	340	3	learning	learning	NOUN
ijassa-1009	340	4	approach	approach	NOUN
ijassa-1009	340	5	to	to	PART
ijassa-1009	340	6	detect	detect	VERB
ijassa-1009	340	7	covid-19	covid-19	PROPN
ijassa-1009	340	8	coronavirus	coronavirus	NOUN
ijassa-1009	340	9	with	with	ADP
ijassa-1009	340	10	x	x	ADJ
ijassa-1009	340	11	-	-	NOUN
ijassa-1009	340	12	ray	ray	NOUN
ijassa-1009	340	13	images	image	NOUN
ijassa-1009	340	14	.	.	PUNCT
ijassa-1009	341	1	biocybernetics	biocybernetic	NOUN
ijassa-1009	341	2	and	and	CCONJ
ijassa-1009	341	3	biomedical	biomedical	ADJ
ijassa-1009	341	4	engineering	engineering	NOUN
ijassa-1009	341	5	,	,	PUNCT
ijassa-1009	341	6	40(4	40(4	NUM
ijassa-1009	341	7	)	)	PUNCT
ijassa-1009	341	8	,	,	PUNCT
ijassa-1009	341	9	1391	1391	NUM
ijassa-1009	341	10	-	-	SYM
ijassa-1009	341	11	1405	1405	NUM
ijassa-1009	341	12	.	.	PUNCT
ijassa-1009	342	1	13	13	NUM
ijassa-1009	342	2	.	.	PUNCT
ijassa-1009	342	3	kassani	kassani	PROPN
ijassa-1009	342	4	,	,	PUNCT
ijassa-1009	342	5	s.	s.	PROPN
ijassa-1009	342	6	h.	h.	PROPN
ijassa-1009	342	7	,	,	PUNCT
ijassa-1009	342	8	kassasni	kassasni	VERB
ijassa-1009	342	9	,	,	PUNCT
ijassa-1009	342	10	p.	p.	PROPN
ijassa-1009	342	11	h.	h.	PROPN
ijassa-1009	342	12	,	,	PUNCT
ijassa-1009	342	13	wesolowski	wesolowski	PROPN
ijassa-1009	342	14	,	,	PUNCT
ijassa-1009	342	15	m.	m.	NOUN
ijassa-1009	342	16	j.	j.	PROPN
ijassa-1009	342	17	,	,	PUNCT
ijassa-1009	342	18	schneider	schneider	PROPN
ijassa-1009	342	19	,	,	PUNCT
ijassa-1009	342	20	k.	k.	PROPN
ijassa-1009	342	21	a.	a.	PROPN
ijassa-1009	342	22	,	,	PUNCT
ijassa-1009	342	23	&	&	CCONJ
ijassa-1009	342	24	deters	deter	NOUN
ijassa-1009	342	25	,	,	PUNCT
ijassa-1009	342	26	r.	r.	PROPN
ijassa-1009	342	27	(	(	PUNCT
ijassa-1009	342	28	2020	2020	NUM
ijassa-1009	342	29	)	)	PUNCT
ijassa-1009	342	30	.	.	PUNCT
ijassa-1009	343	1	automatic	automatic	ADJ
ijassa-1009	343	2	detection	detection	NOUN
ijassa-1009	343	3	of	of	ADP
ijassa-1009	343	4	coronavirus	coronavirus	NOUN
ijassa-1009	343	5	disease	disease	NOUN
ijassa-1009	343	6	(	(	PUNCT
ijassa-1009	343	7	covid-19	covid-19	PROPN
ijassa-1009	343	8	)	)	PUNCT
ijassa-1009	343	9	in	in	ADP
ijassa-1009	343	10	x	x	NOUN
ijassa-1009	343	11	-	-	NOUN
ijassa-1009	343	12	ray	ray	NOUN
ijassa-1009	343	13	and	and	CCONJ
ijassa-1009	343	14	ct	ct	NUM
ijassa-1009	343	15	images	image	NOUN
ijassa-1009	343	16	:	:	PUNCT
ijassa-1009	343	17	a	a	DET
ijassa-1009	343	18	machine	machine	NOUN
ijassa-1009	343	19	learning	learning	NOUN
ijassa-1009	343	20	-	-	PUNCT
ijassa-1009	343	21	based	base	VERB
ijassa-1009	343	22	approach	approach	NOUN
ijassa-1009	343	23	.	.	PUNCT
ijassa-1009	344	1	arxiv	arxiv	PROPN
ijassa-1009	344	2	preprint	preprint	PROPN
ijassa-1009	344	3	arxiv:2004.10641	arxiv:2004.10641	PROPN
ijassa-1009	344	4	.	.	PUNCT
ijassa-1009	345	1	14	14	NUM
ijassa-1009	345	2	.	.	PUNCT
ijassa-1009	345	3	maguolo	maguolo	PROPN
ijassa-1009	345	4	,	,	PUNCT
ijassa-1009	345	5	g.	g.	PROPN
ijassa-1009	345	6	,	,	PUNCT
ijassa-1009	345	7	&	&	CCONJ
ijassa-1009	345	8	nanni	nanni	PROPN
ijassa-1009	345	9	,	,	PUNCT
ijassa-1009	345	10	l.	l.	PROPN
ijassa-1009	345	11	(	(	PUNCT
ijassa-1009	345	12	2020	2020	NUM
ijassa-1009	345	13	)	)	PUNCT
ijassa-1009	345	14	.	.	PUNCT
ijassa-1009	346	1	a	a	DET
ijassa-1009	346	2	critic	critic	ADJ
ijassa-1009	346	3	evaluation	evaluation	NOUN
ijassa-1009	346	4	of	of	ADP
ijassa-1009	346	5	methods	method	NOUN
ijassa-1009	346	6	for	for	ADP
ijassa-1009	346	7	covid-19	covid-19	PROPN
ijassa-1009	346	8	automatic	automatic	ADJ
ijassa-1009	346	9	detection	detection	NOUN
ijassa-1009	346	10	from	from	ADP
ijassa-1009	346	11	x	x	NOUN
ijassa-1009	346	12	-	-	NOUN
ijassa-1009	346	13	ray	ray	NOUN
ijassa-1009	346	14	images	image	NOUN
ijassa-1009	346	15	.	.	PUNCT
ijassa-1009	347	1	arxiv	arxiv	PROPN
ijassa-1009	347	2	preprint	preprint	PROPN
ijassa-1009	347	3	arxiv:2004.12823	arxiv:2004.12823	NUM
ijassa-1009	347	4	.	.	PUNCT
ijassa-1009	348	1	15	15	NUM
ijassa-1009	348	2	.	.	X
ijassa-1009	349	1	minaee	minaee	PROPN
ijassa-1009	349	2	,	,	PUNCT
ijassa-1009	349	3	s.	s.	PROPN
ijassa-1009	349	4	,	,	PUNCT
ijassa-1009	349	5	kafieh	kafieh	PROPN
ijassa-1009	349	6	,	,	PUNCT
ijassa-1009	349	7	r.	r.	PROPN
ijassa-1009	349	8	,	,	PUNCT
ijassa-1009	349	9	sonka	sonka	PROPN
ijassa-1009	349	10	,	,	PUNCT
ijassa-1009	349	11	m.	m.	NOUN
ijassa-1009	349	12	,	,	PUNCT
ijassa-1009	349	13	yazdani	yazdani	PROPN
ijassa-1009	349	14	,	,	PUNCT
ijassa-1009	349	15	s.	s.	PROPN
ijassa-1009	349	16	,	,	PUNCT
ijassa-1009	349	17	&	&	CCONJ
ijassa-1009	349	18	soufi	soufi	PROPN
ijassa-1009	349	19	,	,	PUNCT
ijassa-1009	349	20	g.	g.	PROPN
ijassa-1009	349	21	j.	j.	PROPN
ijassa-1009	349	22	(	(	PUNCT
ijassa-1009	349	23	2020	2020	NUM
ijassa-1009	349	24	)	)	PUNCT
ijassa-1009	349	25	.	.	PUNCT
ijassa-1009	350	1	deep	deep	ADJ
ijassa-1009	350	2	-	-	PUNCT
ijassa-1009	350	3	covid	covid	NOUN
ijassa-1009	350	4	:	:	PUNCT
ijassa-1009	350	5	predicting	predict	VERB
ijassa-1009	350	6	covid-19	covid-19	PROPN
ijassa-1009	350	7	from	from	ADP
ijassa-1009	350	8	chest	chest	NOUN
ijassa-1009	350	9	x	x	NOUN
ijassa-1009	350	10	-	-	NOUN
ijassa-1009	350	11	ray	ray	NOUN
ijassa-1009	350	12	images	image	NOUN
ijassa-1009	350	13	using	use	VERB
ijassa-1009	350	14	deep	deep	ADJ
ijassa-1009	350	15	transfer	transfer	NOUN
ijassa-1009	350	16	learning	learning	NOUN
ijassa-1009	350	17	.	.	PUNCT
ijassa-1009	351	1	arxiv	arxiv	PROPN
ijassa-1009	351	2	preprint	preprint	NOUN
ijassa-1009	351	3	arxiv:2004.09363	arxiv:2004.09363	ADJ
ijassa-1009	351	4	.	.	PUNCT
ijassa-1009	352	1	16	16	NUM
ijassa-1009	352	2	.	.	PUNCT
ijassa-1009	353	1	narin	narin	PROPN
ijassa-1009	353	2	,	,	PUNCT
ijassa-1009	353	3	a.	a.	PROPN
ijassa-1009	353	4	,	,	PUNCT
ijassa-1009	353	5	kaya	kaya	PROPN
ijassa-1009	353	6	,	,	PUNCT
ijassa-1009	353	7	c.	c.	PROPN
ijassa-1009	353	8	,	,	PUNCT
ijassa-1009	353	9	&	&	CCONJ
ijassa-1009	353	10	pamuk	pamuk	PROPN
ijassa-1009	353	11	,	,	PUNCT
ijassa-1009	353	12	z.	z.	PROPN
ijassa-1009	353	13	(	(	PUNCT
ijassa-1009	353	14	2020	2020	NUM
ijassa-1009	353	15	)	)	PUNCT
ijassa-1009	353	16	.	.	PUNCT
ijassa-1009	354	1	automatic	automatic	ADJ
ijassa-1009	354	2	detection	detection	NOUN
ijassa-1009	354	3	of	of	ADP
ijassa-1009	354	4	coronavirus	coronavirus	NOUN
ijassa-1009	354	5	disease	disease	NOUN
ijassa-1009	354	6	(	(	PUNCT
ijassa-1009	354	7	covid-19	covid-19	PROPN
ijassa-1009	354	8	)	)	PUNCT
ijassa-1009	354	9	using	use	VERB
ijassa-1009	354	10	x	x	NOUN
ijassa-1009	354	11	-	-	NOUN
ijassa-1009	354	12	ray	ray	NOUN
ijassa-1009	354	13	images	image	NOUN
ijassa-1009	354	14	and	and	CCONJ
ijassa-1009	354	15	deep	deep	ADJ
ijassa-1009	354	16	convolutional	convolutional	ADJ
ijassa-1009	354	17	neural	neural	ADJ
ijassa-1009	354	18	networks	network	NOUN
ijassa-1009	354	19	.	.	PUNCT
ijassa-1009	355	1	arxiv	arxiv	PROPN
ijassa-1009	355	2	preprint	preprint	PROPN
ijassa-1009	355	3	arxiv:2003.10849	arxiv:2003.10849	PROPN
ijassa-1009	355	4	.	.	PUNCT
ijassa-1009	356	1	17	17	NUM
ijassa-1009	356	2	.	.	X
ijassa-1009	356	3	ozturk	ozturk	PROPN
ijassa-1009	356	4	,	,	PUNCT
ijassa-1009	356	5	t.	t.	PROPN
ijassa-1009	356	6	,	,	PUNCT
ijassa-1009	356	7	talo	talo	PROPN
ijassa-1009	356	8	,	,	PUNCT
ijassa-1009	356	9	m.	m.	NOUN
ijassa-1009	356	10	,	,	PUNCT
ijassa-1009	356	11	yildirim	yildirim	PROPN
ijassa-1009	356	12	,	,	PUNCT
ijassa-1009	356	13	e.	e.	PROPN
ijassa-1009	356	14	a.	a.	PROPN
ijassa-1009	356	15	,	,	PUNCT
ijassa-1009	356	16	baloglu	baloglu	PROPN
ijassa-1009	356	17	,	,	PUNCT
ijassa-1009	356	18	u.	u.	PROPN
ijassa-1009	356	19	b.	b.	PROPN
ijassa-1009	356	20	,	,	PUNCT
ijassa-1009	356	21	yildirim	yildirim	PROPN
ijassa-1009	356	22	,	,	PUNCT
ijassa-1009	356	23	o.	o.	PROPN
ijassa-1009	356	24	,	,	PUNCT
ijassa-1009	356	25	&	&	CCONJ
ijassa-1009	356	26	acharya	acharya	PROPN
ijassa-1009	356	27	,	,	PUNCT
ijassa-1009	356	28	u.	u.	PROPN
ijassa-1009	356	29	r.	r.	PROPN
ijassa-1009	356	30	(	(	PUNCT
ijassa-1009	356	31	2020	2020	NUM
ijassa-1009	356	32	)	)	PUNCT
ijassa-1009	356	33	.	.	PUNCT
ijassa-1009	357	1	automated	automate	VERB
ijassa-1009	357	2	detection	detection	NOUN
ijassa-1009	357	3	of	of	ADP
ijassa-1009	357	4	covid-19	covid-19	PROPN
ijassa-1009	357	5	cases	case	NOUN
ijassa-1009	357	6	using	use	VERB
ijassa-1009	357	7	deep	deep	ADJ
ijassa-1009	357	8	neural	neural	ADJ
ijassa-1009	357	9	networks	network	NOUN
ijassa-1009	357	10	with	with	ADP
ijassa-1009	357	11	x	x	ADJ
ijassa-1009	357	12	-	-	NOUN
ijassa-1009	357	13	ray	ray	NOUN
ijassa-1009	357	14	images	image	NOUN
ijassa-1009	357	15	.	.	PUNCT
ijassa-1009	358	1	computers	computer	NOUN
ijassa-1009	358	2	in	in	ADP
ijassa-1009	358	3	biology	biology	NOUN
ijassa-1009	358	4	and	and	CCONJ
ijassa-1009	358	5	medicine	medicine	NOUN
ijassa-1009	358	6	,	,	PUNCT
ijassa-1009	358	7	103792	103792	NUM
ijassa-1009	358	8	.	.	PUNCT
ijassa-1009	359	1	18	18	NUM
ijassa-1009	359	2	.	.	PUNCT
ijassa-1009	359	3	petropoulos	petropoulos	PROPN
ijassa-1009	359	4	,	,	PUNCT
ijassa-1009	359	5	f.	f.	PROPN
ijassa-1009	359	6	,	,	PUNCT
ijassa-1009	359	7	&	&	CCONJ
ijassa-1009	359	8	makridakis	makridakis	PROPN
ijassa-1009	359	9	,	,	PUNCT
ijassa-1009	359	10	s.	s.	PROPN
ijassa-1009	359	11	(	(	PUNCT
ijassa-1009	359	12	2020	2020	NUM
ijassa-1009	359	13	)	)	PUNCT
ijassa-1009	359	14	.	.	PUNCT
ijassa-1009	360	1	forecasting	forecast	VERB
ijassa-1009	360	2	the	the	DET
ijassa-1009	360	3	novel	novel	ADJ
ijassa-1009	360	4	coronavirus	coronavirus	NOUN
ijassa-1009	360	5	covid19	covid19	NOUN
ijassa-1009	360	6	.	.	PUNCT
ijassa-1009	361	1	plos	plos	PROPN
ijassa-1009	361	2	one	one	NUM
ijassa-1009	361	3	,	,	PUNCT
ijassa-1009	361	4	15(3	15(3	NUM
ijassa-1009	361	5	)	)	PUNCT
ijassa-1009	361	6	,	,	PUNCT
ijassa-1009	361	7	e0231236	e0231236	PROPN
ijassa-1009	361	8	.	.	PROPN
ijassa-1009	361	9	19	19	NUM
ijassa-1009	361	10	.	.	PUNCT
ijassa-1009	362	1	rahimzadeh	rahimzadeh	PROPN
ijassa-1009	362	2	,	,	PUNCT
ijassa-1009	362	3	m.	m.	NOUN
ijassa-1009	362	4	,	,	PUNCT
ijassa-1009	362	5	&	&	CCONJ
ijassa-1009	362	6	attar	attar	PROPN
ijassa-1009	362	7	,	,	PUNCT
ijassa-1009	362	8	a.	a.	NOUN
ijassa-1009	362	9	(	(	PUNCT
ijassa-1009	362	10	2020	2020	NUM
ijassa-1009	362	11	)	)	PUNCT
ijassa-1009	362	12	.	.	PUNCT
ijassa-1009	363	1	a	a	DET
ijassa-1009	363	2	modified	modify	VERB
ijassa-1009	363	3	deep	deep	ADJ
ijassa-1009	363	4	convolutional	convolutional	ADJ
ijassa-1009	363	5	neural	neural	ADJ
ijassa-1009	363	6	network	network	NOUN
ijassa-1009	363	7	for	for	ADP
ijassa-1009	363	8	detecting	detect	VERB
ijassa-1009	363	9	covid-19	covid-19	PROPN
ijassa-1009	363	10	and	and	CCONJ
ijassa-1009	363	11	pneumonia	pneumonia	NOUN
ijassa-1009	363	12	from	from	ADP
ijassa-1009	363	13	chest	chest	NOUN
ijassa-1009	363	14	x	x	NOUN
ijassa-1009	363	15	-	-	NOUN
ijassa-1009	363	16	ray	ray	NOUN
ijassa-1009	363	17	images	image	NOUN
ijassa-1009	363	18	based	base	VERB
ijassa-1009	363	19	on	on	ADP
ijassa-1009	363	20	the	the	DET
ijassa-1009	363	21	concatenation	concatenation	NOUN
ijassa-1009	363	22	of	of	ADP
ijassa-1009	363	23	xception	xception	NOUN
ijassa-1009	363	24	and	and	CCONJ
ijassa-1009	363	25	resnet50v2	resnet50v2	PROPN
ijassa-1009	363	26	.	.	NOUN
ijassa-1009	363	27	informatics	informatic	NOUN
ijassa-1009	363	28	in	in	ADP
ijassa-1009	363	29	medicine	medicine	NOUN
ijassa-1009	363	30	unlocked	unlock	VERB
ijassa-1009	363	31	,	,	PUNCT
ijassa-1009	363	32	100360	100360	NUM
ijassa-1009	363	33	.	.	PUNCT
ijassa-1009	364	1	20	20	NUM
ijassa-1009	364	2	.	.	PUNCT
ijassa-1009	364	3	sahlol	sahlol	PROPN
ijassa-1009	364	4	,	,	PUNCT
ijassa-1009	364	5	a.	a.	NOUN
ijassa-1009	364	6	t.	t.	PROPN
ijassa-1009	364	7	,	,	PUNCT
ijassa-1009	364	8	yousri	yousri	PROPN
ijassa-1009	364	9	,	,	PUNCT
ijassa-1009	364	10	d.	d.	PROPN
ijassa-1009	364	11	,	,	PUNCT
ijassa-1009	364	12	ewees	ewees	PROPN
ijassa-1009	364	13	,	,	PUNCT
ijassa-1009	364	14	a.	a.	NOUN
ijassa-1009	364	15	a.	a.	PROPN
ijassa-1009	364	16	,	,	PUNCT
ijassa-1009	364	17	al	al	PROPN
ijassa-1009	364	18	-	-	PUNCT
ijassa-1009	364	19	qaness	qaness	PROPN
ijassa-1009	364	20	,	,	PUNCT
ijassa-1009	364	21	m.	m.	NOUN
ijassa-1009	364	22	a.	a.	PROPN
ijassa-1009	364	23	,	,	PUNCT
ijassa-1009	364	24	damasevicius	damasevicius	PROPN
ijassa-1009	364	25	,	,	PUNCT
ijassa-1009	364	26	r.	r.	PROPN
ijassa-1009	364	27	,	,	PUNCT
ijassa-1009	364	28	&	&	CCONJ
ijassa-1009	364	29	abd	abd	PROPN
ijassa-1009	364	30	elaziz	elaziz	PROPN
ijassa-1009	364	31	,	,	PUNCT
ijassa-1009	364	32	m.	m.	NOUN
ijassa-1009	364	33	(	(	PUNCT
ijassa-1009	364	34	2020	2020	NUM
ijassa-1009	364	35	)	)	PUNCT
ijassa-1009	364	36	.	.	PUNCT
ijassa-1009	365	1	covid-19	covid-19	PROPN
ijassa-1009	365	2	image	image	NOUN
ijassa-1009	365	3	classification	classification	NOUN
ijassa-1009	365	4	using	use	VERB
ijassa-1009	365	5	deep	deep	ADJ
ijassa-1009	365	6	features	feature	NOUN
ijassa-1009	365	7	and	and	CCONJ
ijassa-1009	365	8	fractionalorder	fractionalorder	ADJ
ijassa-1009	365	9	marine	marine	ADJ
ijassa-1009	365	10	predators	predator	NOUN
ijassa-1009	365	11	algorithm	algorithm	NOUN
ijassa-1009	365	12	.	.	PUNCT
ijassa-1009	366	1	scientific	scientific	ADJ
ijassa-1009	366	2	reports	report	NOUN
ijassa-1009	366	3	,	,	PUNCT
ijassa-1009	366	4	10(1	10(1	NUM
ijassa-1009	366	5	)	)	PUNCT
ijassa-1009	366	6	,	,	PUNCT
ijassa-1009	366	7	1	1	NUM
ijassa-1009	366	8	-	-	SYM
ijassa-1009	366	9	15	15	NUM
ijassa-1009	366	10	.	.	NOUN
ijassa-1009	367	1	21	21	NUM
ijassa-1009	367	2	.	.	X
ijassa-1009	367	3	tartaglione	tartaglione	NOUN
ijassa-1009	367	4	,	,	PUNCT
ijassa-1009	367	5	e.	e.	PROPN
ijassa-1009	367	6	,	,	PUNCT
ijassa-1009	367	7	barbano	barbano	INTJ
ijassa-1009	367	8	,	,	PUNCT
ijassa-1009	367	9	c.	c.	PROPN
ijassa-1009	367	10	a.	a.	PROPN
ijassa-1009	367	11	,	,	PUNCT
ijassa-1009	367	12	berzovini	berzovini	PROPN
ijassa-1009	367	13	,	,	PUNCT
ijassa-1009	367	14	c.	c.	PROPN
ijassa-1009	367	15	,	,	PUNCT
ijassa-1009	367	16	calandri	calandri	PROPN
ijassa-1009	367	17	,	,	PUNCT
ijassa-1009	367	18	m.	m.	NOUN
ijassa-1009	367	19	,	,	PUNCT
ijassa-1009	367	20	&	&	CCONJ
ijassa-1009	367	21	grangetto	grangetto	PROPN
ijassa-1009	367	22	,	,	PUNCT
ijassa-1009	367	23	m.	m.	NOUN
ijassa-1009	367	24	(	(	PUNCT
ijassa-1009	367	25	2020	2020	NUM
ijassa-1009	367	26	)	)	PUNCT
ijassa-1009	367	27	.	.	PUNCT
ijassa-1009	368	1	unveiling	unveil	VERB
ijassa-1009	368	2	covid-19	covid-19	PROPN
ijassa-1009	368	3	from	from	ADP
ijassa-1009	368	4	chest	chest	NOUN
ijassa-1009	368	5	x	x	NOUN
ijassa-1009	368	6	-	-	NOUN
ijassa-1009	368	7	ray	ray	NOUN
ijassa-1009	368	8	with	with	ADP
ijassa-1009	368	9	deep	deep	ADJ
ijassa-1009	368	10	learning	learning	NOUN
ijassa-1009	368	11	:	:	PUNCT
ijassa-1009	368	12	a	a	DET
ijassa-1009	368	13	hurdles	hurdle	NOUN
ijassa-1009	368	14	race	race	VERB
ijassa-1009	368	15	with	with	ADP
ijassa-1009	368	16	small	small	ADJ
ijassa-1009	368	17	data	datum	NOUN
ijassa-1009	368	18	.	.	PUNCT
ijassa-1009	369	1	arxiv	arxiv	PROPN
ijassa-1009	369	2	preprint	preprint	VERB
ijassa-1009	369	3	arxiv:2004.05405	arxiv:2004.05405	PROPN
ijassa-1009	369	4	.	.	PUNCT
ijassa-1009	370	1	22	22	NUM
ijassa-1009	370	2	.	.	PUNCT
ijassa-1009	371	1	toğaçar	toğaçar	PROPN
ijassa-1009	371	2	,	,	PUNCT
ijassa-1009	371	3	m.	m.	NOUN
ijassa-1009	371	4	,	,	PUNCT
ijassa-1009	371	5	ergen	ergen	PROPN
ijassa-1009	371	6	,	,	PUNCT
ijassa-1009	371	7	b.	b.	PROPN
ijassa-1009	371	8	,	,	PUNCT
ijassa-1009	371	9	&	&	CCONJ
ijassa-1009	371	10	cömert	cömert	PROPN
ijassa-1009	371	11	,	,	PUNCT
ijassa-1009	371	12	z.	z.	PROPN
ijassa-1009	371	13	(	(	PUNCT
ijassa-1009	371	14	2020	2020	NUM
ijassa-1009	371	15	)	)	PUNCT
ijassa-1009	371	16	.	.	PUNCT
ijassa-1009	372	1	covid-19	covid-19	PROPN
ijassa-1009	372	2	detection	detection	NOUN
ijassa-1009	372	3	using	use	VERB
ijassa-1009	372	4	deep	deep	ADJ
ijassa-1009	372	5	learning	learning	NOUN
ijassa-1009	372	6	models	model	NOUN
ijassa-1009	372	7	to	to	PART
ijassa-1009	372	8	exploit	exploit	VERB
ijassa-1009	372	9	social	social	ADJ
ijassa-1009	372	10	mimic	mimic	ADJ
ijassa-1009	372	11	optimization	optimization	NOUN
ijassa-1009	372	12	and	and	CCONJ
ijassa-1009	372	13	structured	structured	ADJ
ijassa-1009	372	14	chest	chest	NOUN
ijassa-1009	372	15	x	x	NOUN
ijassa-1009	372	16	-	-	NOUN
ijassa-1009	372	17	ray	ray	NOUN
ijassa-1009	372	18	images	image	NOUN
ijassa-1009	372	19	using	use	VERB
ijassa-1009	372	20	fuzzy	fuzzy	ADJ
ijassa-1009	372	21	color	color	NOUN
ijassa-1009	372	22	and	and	CCONJ
ijassa-1009	372	23	stacking	stacking	NOUN
ijassa-1009	372	24	approaches	approach	NOUN
ijassa-1009	372	25	.	.	PUNCT
ijassa-1009	373	1	computers	computer	NOUN
ijassa-1009	373	2	in	in	ADP
ijassa-1009	373	3	biology	biology	NOUN
ijassa-1009	373	4	and	and	CCONJ
ijassa-1009	373	5	medicine	medicine	NOUN
ijassa-1009	373	6	,	,	PUNCT
ijassa-1009	373	7	103805	103805	NUM
ijassa-1009	373	8	.	.	PUNCT
ijassa-1009	374	1	23	23	NUM
ijassa-1009	374	2	.	.	X
ijassa-1009	375	1	toraman	toraman	NOUN
ijassa-1009	375	2	,	,	PUNCT
ijassa-1009	375	3	s.	s.	PROPN
ijassa-1009	375	4	,	,	PUNCT
ijassa-1009	375	5	alakus	alaku	NOUN
ijassa-1009	375	6	,	,	PUNCT
ijassa-1009	375	7	t.	t.	PROPN
ijassa-1009	375	8	b.	b.	PROPN
ijassa-1009	375	9	,	,	PUNCT
ijassa-1009	375	10	&	&	CCONJ
ijassa-1009	375	11	turkoglu	turkoglu	PROPN
ijassa-1009	375	12	,	,	PUNCT
ijassa-1009	375	13	i.	i.	PROPN
ijassa-1009	375	14	(	(	PUNCT
ijassa-1009	375	15	2020	2020	NUM
ijassa-1009	375	16	)	)	PUNCT
ijassa-1009	375	17	.	.	PUNCT
ijassa-1009	376	1	convolutional	convolutional	ADJ
ijassa-1009	376	2	capsnet	capsnet	NOUN
ijassa-1009	376	3	:	:	PUNCT
ijassa-1009	376	4	a	a	DET
ijassa-1009	376	5	novel	novel	ADJ
ijassa-1009	376	6	artificial	artificial	ADJ
ijassa-1009	376	7	neural	neural	ADJ
ijassa-1009	376	8	network	network	NOUN
ijassa-1009	376	9	approach	approach	NOUN
ijassa-1009	376	10	to	to	PART
ijassa-1009	376	11	detect	detect	VERB
ijassa-1009	376	12	covid-19	covid-19	PROPN
ijassa-1009	376	13	disease	disease	NOUN
ijassa-1009	376	14	from	from	ADP
ijassa-1009	376	15	x	x	NOUN
ijassa-1009	376	16	-	-	NOUN
ijassa-1009	376	17	ray	ray	NOUN
ijassa-1009	376	18	images	image	NOUN
ijassa-1009	376	19	using	use	VERB
ijassa-1009	376	20	capsule	capsule	NOUN
ijassa-1009	376	21	networks	network	NOUN
ijassa-1009	376	22	.	.	PUNCT
ijassa-1009	377	1	chaos	chaos	NOUN
ijassa-1009	377	2	,	,	PUNCT
ijassa-1009	377	3	solitons	soliton	NOUN
ijassa-1009	377	4	&	&	CCONJ
ijassa-1009	377	5	fractals	fractal	NOUN
ijassa-1009	377	6	,	,	PUNCT
ijassa-1009	377	7	140	140	NUM
ijassa-1009	377	8	,	,	PUNCT
ijassa-1009	377	9	110122	110122	NUM
ijassa-1009	377	10	.	.	PUNCT
ijassa-1009	378	1	24	24	NUM
ijassa-1009	378	2	.	.	PUNCT
ijassa-1009	379	1	wang	wang	PROPN
ijassa-1009	379	2	,	,	PUNCT
ijassa-1009	379	3	l.	l.	PROPN
ijassa-1009	379	4	,	,	PUNCT
ijassa-1009	379	5	&	&	CCONJ
ijassa-1009	379	6	wong	wong	PROPN
ijassa-1009	379	7	,	,	PUNCT
ijassa-1009	379	8	a.	a.	NOUN
ijassa-1009	379	9	(	(	PUNCT
ijassa-1009	379	10	2020	2020	NUM
ijassa-1009	379	11	)	)	PUNCT
ijassa-1009	379	12	.	.	PUNCT
ijassa-1009	380	1	covid	covid	PROPN
ijassa-1009	380	2	-	-	PUNCT
ijassa-1009	380	3	net	net	NOUN
ijassa-1009	380	4	:	:	PUNCT
ijassa-1009	380	5	a	a	DET
ijassa-1009	380	6	tailored	tailor	VERB
ijassa-1009	380	7	deep	deep	ADJ
ijassa-1009	380	8	convolutional	convolutional	ADJ
ijassa-1009	380	9	neural	neural	ADJ
ijassa-1009	380	10	network	network	NOUN
ijassa-1009	380	11	design	design	NOUN
ijassa-1009	380	12	for	for	ADP
ijassa-1009	380	13	detection	detection	NOUN
ijassa-1009	380	14	of	of	ADP
ijassa-1009	380	15	covid-19	covid-19	PROPN
ijassa-1009	380	16	cases	case	NOUN
ijassa-1009	380	17	from	from	ADP
ijassa-1009	380	18	chest	chest	NOUN
ijassa-1009	380	19	x	x	NOUN
ijassa-1009	380	20	-	-	NOUN
ijassa-1009	380	21	ray	ray	NOUN
ijassa-1009	380	22	images	image	NOUN
ijassa-1009	380	23	.	.	PUNCT
ijassa-1009	381	1	arxiv	arxiv	PROPN
ijassa-1009	381	2	preprint	preprint	VERB
ijassa-1009	381	3	arxiv:2003.09871	arxiv:2003.09871	PROPN
ijassa-1009	381	4	.	.	PUNCT
ijassa-1009	382	1	25	25	NUM
ijassa-1009	382	2	.	.	X
ijassa-1009	383	1	wang	wang	PROPN
ijassa-1009	383	2	,	,	PUNCT
ijassa-1009	383	3	x.	x.	PROPN
ijassa-1009	383	4	,	,	PUNCT
ijassa-1009	383	5	peng	peng	PROPN
ijassa-1009	383	6	,	,	PUNCT
ijassa-1009	383	7	y.	y.	PROPN
ijassa-1009	383	8	,	,	PUNCT
ijassa-1009	383	9	lu	lu	PROPN
ijassa-1009	383	10	,	,	PUNCT
ijassa-1009	383	11	l.	l.	PROPN
ijassa-1009	383	12	,	,	PUNCT
ijassa-1009	383	13	lu	lu	PROPN
ijassa-1009	383	14	,	,	PUNCT
ijassa-1009	383	15	z.	z.	PROPN
ijassa-1009	383	16	,	,	PUNCT
ijassa-1009	383	17	bagheri	bagheri	PROPN
ijassa-1009	383	18	,	,	PUNCT
ijassa-1009	383	19	m.	m.	NOUN
ijassa-1009	383	20	,	,	PUNCT
ijassa-1009	383	21	&	&	CCONJ
ijassa-1009	383	22	summers	summers	PROPN
ijassa-1009	383	23	,	,	PUNCT
ijassa-1009	383	24	r.	r.	PROPN
ijassa-1009	383	25	m.	m.	PROPN
ijassa-1009	383	26	(	(	PUNCT
ijassa-1009	383	27	2017	2017	NUM
ijassa-1009	383	28	)	)	PUNCT
ijassa-1009	383	29	.	.	PUNCT
ijassa-1009	384	1	chestx	chestx	NOUN
ijassa-1009	384	2	-	-	PUNCT
ijassa-1009	384	3	ray8	ray8	PROPN
ijassa-1009	384	4	:	:	PUNCT
ijassa-1009	384	5	hospital	hospital	NOUN
ijassa-1009	384	6	-	-	PUNCT
ijassa-1009	384	7	scale	scale	NOUN
ijassa-1009	384	8	chest	chest	NOUN
ijassa-1009	384	9	x	x	NOUN
ijassa-1009	384	10	-	-	NOUN
ijassa-1009	384	11	ray	ray	NOUN
ijassa-1009	384	12	database	database	NOUN
ijassa-1009	384	13	and	and	CCONJ
ijassa-1009	384	14	benchmarks	benchmark	NOUN
ijassa-1009	384	15	on	on	ADP
ijassa-1009	384	16	weakly	weakly	ADV
ijassa-1009	384	17	-	-	PUNCT
ijassa-1009	384	18	supervised	supervise	VERB
ijassa-1009	384	19	classification	classification	NOUN
ijassa-1009	384	20	and	and	CCONJ
ijassa-1009	384	21	localization	localization	NOUN
ijassa-1009	384	22	of	of	ADP
ijassa-1009	384	23	common	common	ADJ
ijassa-1009	384	24	thorax	thorax	NOUN
ijassa-1009	384	25	diseases	disease	NOUN
ijassa-1009	384	26	.	.	PUNCT
ijassa-1009	385	1	in	in	ADP
ijassa-1009	385	2	proceedings	proceeding	NOUN
ijassa-1009	385	3	of	of	ADP
ijassa-1009	385	4	the	the	DET
ijassa-1009	385	5	ieee	ieee	NOUN
ijassa-1009	385	6	conference	conference	NOUN
ijassa-1009	385	7	on	on	ADP
ijassa-1009	385	8	computer	computer	NOUN
ijassa-1009	385	9	vision	vision	NOUN
ijassa-1009	385	10	and	and	CCONJ
ijassa-1009	385	11	pattern	pattern	NOUN
ijassa-1009	385	12	recognition	recognition	NOUN
ijassa-1009	385	13	(	(	PUNCT
ijassa-1009	385	14	pp	pp	ADJ
ijassa-1009	385	15	.	.	PUNCT
ijassa-1009	386	1	2097	2097	NUM
ijassa-1009	386	2	-	-	SYM
ijassa-1009	386	3	2106	2106	NUM
ijassa-1009	386	4	)	)	PUNCT
ijassa-1009	386	5	.	.	PUNCT
ijassa-1009	387	1	deep	deep	ADJ
ijassa-1009	387	2	learning	learning	NOUN
ijassa-1009	387	3	techniques	technique	NOUN
ijassa-1009	387	4	for	for	ADP
ijassa-1009	387	5	detection	detection	NOUN
ijassa-1009	387	6	of	of	ADP
ijassa-1009	387	7	covid-19	covid-19	PROPN
ijassa-1009	387	8	57	57	NUM
ijassa-1009	387	9	copyright	copyright	NOUN
ijassa-1009	387	10	©	©	PROPN
ijassa-1009	387	11	2021	2021	NUM
ijassa-1009	387	12	assa	assa	NOUN
ijassa-1009	387	13	.	.	PUNCT
ijassa-1009	388	1	adv	adv	PROPN
ijassa-1009	388	2	.	.	PUNCT
ijassa-1009	389	1	in	in	ADP
ijassa-1009	389	2	systems	system	NOUN
ijassa-1009	389	3	science	science	NOUN
ijassa-1009	389	4	and	and	CCONJ
ijassa-1009	389	5	appl	appl	NOUN
ijassa-1009	389	6	.	.	PUNCT
ijassa-1009	390	1	(	(	PUNCT
ijassa-1009	390	2	2021	2021	NUM
ijassa-1009	390	3	)	)	PUNCT
ijassa-1009	390	4	26	26	NUM
ijassa-1009	390	5	.	.	PUNCT
ijassa-1009	391	1	xu	xu	INTJ
ijassa-1009	391	2	,	,	PUNCT
ijassa-1009	391	3	a.	a.	PROPN
ijassa-1009	391	4	y.	y.	PROPN
ijassa-1009	391	5	(	(	PUNCT
ijassa-1009	391	6	2020	2020	NUM
ijassa-1009	391	7	)	)	PUNCT
ijassa-1009	391	8	.	.	PUNCT
ijassa-1009	392	1	detecting	detect	VERB
ijassa-1009	392	2	covid-19	covid-19	PROPN
ijassa-1009	392	3	induced	induce	VERB
ijassa-1009	392	4	pneumonia	pneumonia	NOUN
ijassa-1009	392	5	from	from	ADP
ijassa-1009	392	6	chest	chest	NOUN
ijassa-1009	392	7	x	x	NOUN
ijassa-1009	392	8	-	-	NOUN
ijassa-1009	392	9	rays	ray	NOUN
ijassa-1009	392	10	with	with	ADP
ijassa-1009	392	11	transfer	transfer	NOUN
ijassa-1009	392	12	learning	learning	NOUN
ijassa-1009	392	13	:	:	PUNCT
ijassa-1009	392	14	an	an	DET
ijassa-1009	392	15	implementation	implementation	NOUN
ijassa-1009	392	16	in	in	ADP
ijassa-1009	392	17	tensorflow	tensorflow	NOUN
ijassa-1009	392	18	and	and	CCONJ
ijassa-1009	392	19	keras	keras	PROPN
ijassa-1009	392	20	.	.	PROPN
ijassa-1009	393	1	towards	towards	ADP
ijassa-1009	393	2	data	data	NOUN
ijassa-1009	393	3	science	science	NOUN
ijassa-1009	393	4	.	.	PUNCT
ijassa-1009	394	1	27	27	NUM
ijassa-1009	394	2	.	.	PUNCT
ijassa-1009	394	3	song	song	NOUN
ijassa-1009	394	4	,	,	PUNCT
ijassa-1009	394	5	y.	y.	PROPN
ijassa-1009	394	6	,	,	PUNCT
ijassa-1009	394	7	zheng	zheng	PROPN
ijassa-1009	394	8	,	,	PUNCT
ijassa-1009	394	9	s.	s.	PROPN
ijassa-1009	394	10	,	,	PUNCT
ijassa-1009	394	11	li	li	PROPN
ijassa-1009	394	12	,	,	PUNCT
ijassa-1009	394	13	l.	l.	PROPN
ijassa-1009	394	14	,	,	PUNCT
ijassa-1009	394	15	zhang	zhang	PROPN
ijassa-1009	394	16	,	,	PUNCT
ijassa-1009	394	17	x.	x.	PROPN
ijassa-1009	394	18	,	,	PUNCT
ijassa-1009	394	19	zhang	zhang	PROPN
ijassa-1009	394	20	,	,	PUNCT
ijassa-1009	394	21	x.	x.	PROPN
ijassa-1009	394	22	,	,	PUNCT
ijassa-1009	394	23	huang	huang	PROPN
ijassa-1009	394	24	,	,	PUNCT
ijassa-1009	394	25	z.	z.	PROPN
ijassa-1009	394	26	,	,	PUNCT
ijassa-1009	394	27	...	...	PUNCT
ijassa-1009	394	28	&	&	CCONJ
ijassa-1009	394	29	chong	chong	PROPN
ijassa-1009	394	30	,	,	PUNCT
ijassa-1009	394	31	y.	y.	PROPN
ijassa-1009	394	32	(	(	PUNCT
ijassa-1009	394	33	2020	2020	NUM
ijassa-1009	394	34	)	)	PUNCT
ijassa-1009	394	35	.	.	PUNCT
ijassa-1009	395	1	deep	deep	ADJ
ijassa-1009	395	2	learning	learning	NOUN
ijassa-1009	395	3	enables	enable	VERB
ijassa-1009	395	4	accurate	accurate	ADJ
ijassa-1009	395	5	diagnosis	diagnosis	NOUN
ijassa-1009	395	6	of	of	ADP
ijassa-1009	395	7	novel	novel	ADJ
ijassa-1009	395	8	coronavirus	coronavirus	NOUN
ijassa-1009	395	9	(	(	PUNCT
ijassa-1009	395	10	covid-19	covid-19	PROPN
ijassa-1009	395	11	)	)	PUNCT
ijassa-1009	395	12	with	with	ADP
ijassa-1009	395	13	ct	ct	NUM
ijassa-1009	395	14	images	image	NOUN
ijassa-1009	395	15	.	.	PUNCT
ijassa-1009	396	1	medrxiv	medrxiv	INTJ
ijassa-1009	396	2	.	.	PUNCT
ijassa-1009	397	1	28	28	NUM
ijassa-1009	397	2	.	.	X
ijassa-1009	397	3	yoo	yoo	PROPN
ijassa-1009	397	4	,	,	PUNCT
ijassa-1009	397	5	s.	s.	PROPN
ijassa-1009	397	6	h.	h.	PROPN
ijassa-1009	397	7	,	,	PUNCT
ijassa-1009	397	8	geng	geng	PROPN
ijassa-1009	397	9	,	,	PUNCT
ijassa-1009	397	10	h.	h.	PROPN
ijassa-1009	397	11	,	,	PUNCT
ijassa-1009	397	12	chiu	chiu	PROPN
ijassa-1009	397	13	,	,	PUNCT
ijassa-1009	397	14	t.	t.	PROPN
ijassa-1009	397	15	l.	l.	PROPN
ijassa-1009	397	16	,	,	PUNCT
ijassa-1009	397	17	yu	yu	PROPN
ijassa-1009	397	18	,	,	PUNCT
ijassa-1009	397	19	s.	s.	PROPN
ijassa-1009	397	20	k.	k.	PROPN
ijassa-1009	397	21	,	,	PUNCT
ijassa-1009	397	22	et	et	PROPN
ijassa-1009	397	23	.	.	PUNCT
ijassa-1009	398	1	al	al	PROPN
ijassa-1009	398	2	.	.	PROPN
ijassa-1009	398	3	(	(	PUNCT
ijassa-1009	398	4	2020	2020	NUM
ijassa-1009	398	5	)	)	PUNCT
ijassa-1009	398	6	.	.	PUNCT
ijassa-1009	399	1	deep	deep	ADJ
ijassa-1009	399	2	learning	learning	NOUN
ijassa-1009	399	3	-	-	PUNCT
ijassa-1009	399	4	based	base	VERB
ijassa-1009	399	5	decisiontree	decisiontree	ADJ
ijassa-1009	399	6	classifier	classifier	NOUN
ijassa-1009	399	7	for	for	ADP
ijassa-1009	399	8	covid-19	covid-19	PROPN
ijassa-1009	399	9	diagnosis	diagnosis	NOUN
ijassa-1009	399	10	from	from	ADP
ijassa-1009	399	11	chest	chest	NOUN
ijassa-1009	399	12	x	x	NOUN
ijassa-1009	399	13	-	-	NOUN
ijassa-1009	399	14	ray	ray	NOUN
ijassa-1009	399	15	imaging	imaging	NOUN
ijassa-1009	399	16	.	.	PUNCT
ijassa-1009	400	1	frontiers	frontier	NOUN
ijassa-1009	400	2	in	in	ADP
ijassa-1009	400	3	medicine	medicine	NOUN
ijassa-1009	400	4	,	,	PUNCT
ijassa-1009	400	5	7	7	NUM
ijassa-1009	400	6	,	,	PUNCT
ijassa-1009	400	7	427	427	NUM
ijassa-1009	400	8	.	.	NOUN
ijassa-1009	400	9	29	29	NUM
ijassa-1009	400	10	.	.	X
ijassa-1009	401	1	zhang	zhang	PROPN
ijassa-1009	401	2	,	,	PUNCT
ijassa-1009	401	3	j.	j.	PROPN
ijassa-1009	401	4	,	,	PUNCT
ijassa-1009	401	5	xie	xie	PROPN
ijassa-1009	401	6	,	,	PUNCT
ijassa-1009	401	7	y.	y.	PROPN
ijassa-1009	401	8	,	,	PUNCT
ijassa-1009	401	9	li	li	PROPN
ijassa-1009	401	10	,	,	PUNCT
ijassa-1009	401	11	y.	y.	PROPN
ijassa-1009	401	12	,	,	PUNCT
ijassa-1009	401	13	shen	shen	PROPN
ijassa-1009	401	14	,	,	PUNCT
ijassa-1009	401	15	c.	c.	PROPN
ijassa-1009	401	16	,	,	PUNCT
ijassa-1009	401	17	&	&	CCONJ
ijassa-1009	401	18	xia	xia	PROPN
ijassa-1009	401	19	,	,	PUNCT
ijassa-1009	401	20	y.	y.	PROPN
ijassa-1009	401	21	(	(	PUNCT
ijassa-1009	401	22	2020	2020	NUM
ijassa-1009	401	23	)	)	PUNCT
ijassa-1009	401	24	.	.	PUNCT
ijassa-1009	402	1	covid-19	covid-19	PROPN
ijassa-1009	402	2	screening	screen	VERB
ijassa-1009	402	3	on	on	ADP
ijassa-1009	402	4	chest	chest	NOUN
ijassa-1009	402	5	x	x	NOUN
ijassa-1009	402	6	-	-	NOUN
ijassa-1009	402	7	ray	ray	NOUN
ijassa-1009	402	8	images	image	NOUN
ijassa-1009	402	9	using	use	VERB
ijassa-1009	402	10	deep	deep	ADJ
ijassa-1009	402	11	learning	learning	NOUN
ijassa-1009	402	12	based	base	VERB
ijassa-1009	402	13	anomaly	anomaly	PROPN
ijassa-1009	402	14	detection	detection	NOUN
ijassa-1009	402	15	.	.	PUNCT
ijassa-1009	403	1	arxiv	arxiv	PROPN
ijassa-1009	403	2	preprint	preprint	NOUN
ijassa-1009	403	3	arxiv:2003.12338	arxiv:2003.12338	NUM
ijassa-1009	403	4	.	.	PUNCT