id	sid	tid	token	lemma	pos
ajst-8015	1	1	academic	academic	ADJ
ajst-8015	1	2	journal	journal	NOUN
ajst-8015	1	3	of	of	ADP
ajst-8015	1	4	science	science	NOUN
ajst-8015	1	5	and	and	CCONJ
ajst-8015	1	6	technology	technology	NOUN
ajst-8015	1	7	issn	issn	NOUN
ajst-8015	1	8	:	:	PUNCT
ajst-8015	1	9	2771	2771	NUM
ajst-8015	1	10	-	-	SYM
ajst-8015	1	11	3032	3032	NUM
ajst-8015	1	12	|	|	NOUN
ajst-8015	1	13	vol	vol	NOUN
ajst-8015	1	14	.	.	PROPN
ajst-8015	2	1	5	5	NUM
ajst-8015	2	2	,	,	PUNCT
ajst-8015	2	3	no	no	INTJ
ajst-8015	2	4	.	.	NOUN
ajst-8015	2	5	3	3	NUM
ajst-8015	2	6	,	,	PUNCT
ajst-8015	2	7	2023	2023	NUM
ajst-8015	2	8	215	215	NUM
ajst-8015	2	9	artificial	artificial	ADJ
ajst-8015	2	10	intelligence	intelligence	NOUN
ajst-8015	2	11	approaches	approach	NOUN
ajst-8015	2	12	for	for	ADP
ajst-8015	2	13	early	early	ADJ
ajst-8015	2	14	detection	detection	NOUN
ajst-8015	2	15	and	and	CCONJ
ajst-8015	2	16	diagnosis	diagnosis	NOUN
ajst-8015	2	17	of	of	ADP
ajst-8015	2	18	alzheimer	alzheimer	PROPN
ajst-8015	2	19	's	's	PART
ajst-8015	2	20	disease	disease	NOUN
ajst-8015	2	21	:	:	PUNCT
ajst-8015	2	22	a	a	DET
ajst-8015	2	23	review	review	NOUN
ajst-8015	2	24	mingyang	mingyang	PROPN
ajst-8015	2	25	wei	wei	PROPN
ajst-8015	2	26	*	*	PROPN
ajst-8015	2	27	,	,	PUNCT
ajst-8015	2	28	yabei	yabei	PROPN
ajst-8015	2	29	li	li	PROPN
ajst-8015	2	30	,	,	PUNCT
ajst-8015	2	31	minjun	minjun	PROPN
ajst-8015	2	32	liang	liang	PROPN
ajst-8015	2	33	,	,	PUNCT
ajst-8015	2	34	mengbo	mengbo	PROPN
ajst-8015	2	35	xi	xi	PROPN
ajst-8015	2	36	,	,	PUNCT
ajst-8015	2	37	he	he	PRON
ajst-8015	2	38	tian	tian	ADJ
ajst-8015	2	39	school	school	NOUN
ajst-8015	2	40	of	of	ADP
ajst-8015	2	41	computer	computer	NOUN
ajst-8015	2	42	science	science	NOUN
ajst-8015	2	43	and	and	CCONJ
ajst-8015	2	44	technology	technology	NOUN
ajst-8015	2	45	,	,	PUNCT
ajst-8015	2	46	henan	henan	PROPN
ajst-8015	2	47	polytechnic	polytechnic	PROPN
ajst-8015	2	48	university	university	PROPN
ajst-8015	2	49	,	,	PUNCT
ajst-8015	2	50	jiaozuo	jiaozuo	PROPN
ajst-8015	2	51	,	,	PUNCT
ajst-8015	2	52	henan	henan	PROPN
ajst-8015	2	53	454000	454000	NUM
ajst-8015	2	54	,	,	PUNCT
ajst-8015	2	55	p	p	PROPN
ajst-8015	2	56	r	r	PROPN
ajst-8015	2	57	china	china	PROPN
ajst-8015	2	58	*	*	PUNCT
ajst-8015	2	59	corresponding	correspond	VERB
ajst-8015	2	60	author	author	NOUN
ajst-8015	2	61	:	:	PUNCT
ajst-8015	2	62	mingyang	mingyang	PROPN
ajst-8015	2	63	wei	wei	PROPN
ajst-8015	2	64	(	(	PUNCT
ajst-8015	2	65	wmy@home.hpu.edu.cn	wmy@home.hpu.edu.cn	PROPN
ajst-8015	2	66	)	)	PUNCT
ajst-8015	2	67	abstract	abstract	NOUN
ajst-8015	2	68	:	:	PUNCT
ajst-8015	3	1	alzheimer	alzheimer	PROPN
ajst-8015	3	2	's	's	PART
ajst-8015	3	3	disease	disease	NOUN
ajst-8015	3	4	(	(	PUNCT
ajst-8015	3	5	ad	ad	NOUN
ajst-8015	3	6	)	)	PUNCT
ajst-8015	3	7	is	be	AUX
ajst-8015	3	8	an	an	DET
ajst-8015	3	9	irreversible	irreversible	ADJ
ajst-8015	3	10	neurodegenerative	neurodegenerative	ADJ
ajst-8015	3	11	disease	disease	NOUN
ajst-8015	3	12	common	common	ADJ
ajst-8015	3	13	in	in	ADP
ajst-8015	3	14	the	the	DET
ajst-8015	3	15	elderly	elderly	ADJ
ajst-8015	3	16	.	.	PUNCT
ajst-8015	4	1	the	the	DET
ajst-8015	4	2	application	application	NOUN
ajst-8015	4	3	of	of	ADP
ajst-8015	4	4	artificial	artificial	ADJ
ajst-8015	4	5	intelligence	intelligence	NOUN
ajst-8015	4	6	technology	technology	NOUN
ajst-8015	4	7	to	to	ADP
ajst-8015	4	8	the	the	DET
ajst-8015	4	9	early	early	ADJ
ajst-8015	4	10	diagnosis	diagnosis	NOUN
ajst-8015	4	11	of	of	ADP
ajst-8015	4	12	ad	ad	NOUN
ajst-8015	4	13	can	can	AUX
ajst-8015	4	14	not	not	PART
ajst-8015	4	15	only	only	ADV
ajst-8015	4	16	improve	improve	VERB
ajst-8015	4	17	the	the	DET
ajst-8015	4	18	accuracy	accuracy	NOUN
ajst-8015	4	19	of	of	ADP
ajst-8015	4	20	prediction	prediction	NOUN
ajst-8015	4	21	compared	compare	VERB
ajst-8015	4	22	with	with	ADP
ajst-8015	4	23	traditional	traditional	ADJ
ajst-8015	4	24	methods	method	NOUN
ajst-8015	4	25	,	,	PUNCT
ajst-8015	4	26	but	but	CCONJ
ajst-8015	4	27	also	also	ADV
ajst-8015	4	28	save	save	VERB
ajst-8015	4	29	the	the	DET
ajst-8015	4	30	complicated	complicated	ADJ
ajst-8015	4	31	manual	manual	ADJ
ajst-8015	4	32	feature	feature	NOUN
ajst-8015	4	33	extraction	extraction	NOUN
ajst-8015	4	34	of	of	ADP
ajst-8015	4	35	traditional	traditional	ADJ
ajst-8015	4	36	methods	method	NOUN
ajst-8015	4	37	and	and	CCONJ
ajst-8015	4	38	speed	speed	VERB
ajst-8015	4	39	up	up	ADP
ajst-8015	4	40	the	the	DET
ajst-8015	4	41	diagnosis	diagnosis	NOUN
ajst-8015	4	42	.	.	PUNCT
ajst-8015	5	1	this	this	DET
ajst-8015	5	2	paper	paper	NOUN
ajst-8015	5	3	reviews	review	VERB
ajst-8015	5	4	various	various	ADJ
ajst-8015	5	5	applications	application	NOUN
ajst-8015	5	6	of	of	ADP
ajst-8015	5	7	artificial	artificial	ADJ
ajst-8015	5	8	intelligence	intelligence	NOUN
ajst-8015	5	9	algorithms	algorithm	NOUN
ajst-8015	5	10	in	in	ADP
ajst-8015	5	11	ad	ad	NOUN
ajst-8015	5	12	diagnosis	diagnosis	NOUN
ajst-8015	5	13	,	,	PUNCT
ajst-8015	5	14	including	include	VERB
ajst-8015	5	15	machine	machine	NOUN
ajst-8015	5	16	learning	learning	NOUN
ajst-8015	5	17	,	,	PUNCT
ajst-8015	5	18	convolutional	convolutional	ADJ
ajst-8015	5	19	neural	neural	ADJ
ajst-8015	5	20	network	network	NOUN
ajst-8015	5	21	,	,	PUNCT
ajst-8015	5	22	graph	graph	VERB
ajst-8015	5	23	convolutional	convolutional	ADJ
ajst-8015	5	24	neural	neural	ADJ
ajst-8015	5	25	network	network	NOUN
ajst-8015	5	26	,	,	PUNCT
ajst-8015	5	27	cyclic	cyclic	ADJ
ajst-8015	5	28	neural	neural	ADJ
ajst-8015	5	29	network	network	NOUN
ajst-8015	5	30	and	and	CCONJ
ajst-8015	5	31	other	other	ADJ
ajst-8015	5	32	mainstream	mainstream	NOUN
ajst-8015	5	33	deep	deep	ADJ
ajst-8015	5	34	learning	learning	NOUN
ajst-8015	5	35	technologies	technology	NOUN
ajst-8015	5	36	.	.	PUNCT
ajst-8015	6	1	the	the	DET
ajst-8015	6	2	advantages	advantage	NOUN
ajst-8015	6	3	and	and	CCONJ
ajst-8015	6	4	disadvantages	disadvantage	NOUN
ajst-8015	6	5	of	of	ADP
ajst-8015	6	6	each	each	DET
ajst-8015	6	7	approach	approach	NOUN
ajst-8015	6	8	are	be	AUX
ajst-8015	6	9	discussed	discuss	VERB
ajst-8015	6	10	,	,	PUNCT
ajst-8015	6	11	and	and	CCONJ
ajst-8015	6	12	finally	finally	ADV
ajst-8015	6	13	,	,	PUNCT
ajst-8015	6	14	we	we	PRON
ajst-8015	6	15	discuss	discuss	VERB
ajst-8015	6	16	limitations	limitation	NOUN
ajst-8015	6	17	and	and	CCONJ
ajst-8015	6	18	future	future	ADJ
ajst-8015	6	19	prospects	prospect	NOUN
ajst-8015	6	20	.	.	PUNCT
ajst-8015	7	1	keywords	keyword	NOUN
ajst-8015	7	2	:	:	PUNCT
ajst-8015	7	3	deep	deep	ADJ
ajst-8015	7	4	learning	learning	NOUN
ajst-8015	7	5	,	,	PUNCT
ajst-8015	7	6	machine	machine	NOUN
ajst-8015	7	7	learning	learning	NOUN
ajst-8015	7	8	,	,	PUNCT
ajst-8015	7	9	alzheimer	alzheimer	PROPN
ajst-8015	7	10	's	's	PART
ajst-8015	7	11	disease	disease	NOUN
ajst-8015	7	12	.	.	PUNCT
ajst-8015	8	1	1	1	X
ajst-8015	8	2	.	.	X
ajst-8015	8	3	introduction	introduction	NOUN
ajst-8015	8	4	alzheimer	alzheimer	PROPN
ajst-8015	8	5	's	's	PART
ajst-8015	8	6	disease	disease	NOUN
ajst-8015	8	7	(	(	PUNCT
ajst-8015	8	8	ad	ad	NOUN
ajst-8015	8	9	)	)	PUNCT
ajst-8015	8	10	is	be	AUX
ajst-8015	8	11	an	an	DET
ajst-8015	8	12	irreversible	irreversible	ADJ
ajst-8015	8	13	degenerative	degenerative	ADJ
ajst-8015	8	14	disease	disease	NOUN
ajst-8015	8	15	of	of	ADP
ajst-8015	8	16	nervous	nervous	ADJ
ajst-8015	8	17	system	system	NOUN
ajst-8015	8	18	.	.	PUNCT
ajst-8015	9	1	it	it	PRON
ajst-8015	9	2	is	be	AUX
ajst-8015	9	3	also	also	ADV
ajst-8015	9	4	known	know	VERB
ajst-8015	9	5	as	as	ADP
ajst-8015	9	6	"	"	PUNCT
ajst-8015	9	7	senile	senile	ADJ
ajst-8015	9	8	dementia	dementia	NOUN
ajst-8015	9	9	"	"	PUNCT
ajst-8015	9	10	because	because	SCONJ
ajst-8015	9	11	it	it	PRON
ajst-8015	9	12	is	be	AUX
ajst-8015	9	13	more	more	ADV
ajst-8015	9	14	common	common	ADJ
ajst-8015	9	15	in	in	ADP
ajst-8015	9	16	the	the	DET
ajst-8015	9	17	aged	aged	ADJ
ajst-8015	9	18	group	group	NOUN
ajst-8015	9	19	over	over	ADP
ajst-8015	9	20	60	60	NUM
ajst-8015	9	21	years	year	NOUN
ajst-8015	9	22	old	old	ADJ
ajst-8015	9	23	,	,	PUNCT
ajst-8015	9	24	and	and	CCONJ
ajst-8015	9	25	its	its	PRON
ajst-8015	9	26	specific	specific	ADJ
ajst-8015	9	27	clinical	clinical	ADJ
ajst-8015	9	28	manifestations	manifestation	NOUN
ajst-8015	9	29	are	be	AUX
ajst-8015	9	30	cognitive	cognitive	ADJ
ajst-8015	9	31	decline	decline	NOUN
ajst-8015	9	32	,	,	PUNCT
ajst-8015	9	33	memory	memory	NOUN
ajst-8015	9	34	decline	decline	NOUN
ajst-8015	9	35	,	,	PUNCT
ajst-8015	9	36	language	language	NOUN
ajst-8015	9	37	function	function	NOUN
ajst-8015	9	38	degradation[1	degradation[1	PROPN
ajst-8015	9	39	]	]	PUNCT
ajst-8015	9	40	.	.	PUNCT
ajst-8015	10	1	with	with	ADP
ajst-8015	10	2	the	the	DET
ajst-8015	10	3	deepening	deepening	NOUN
ajst-8015	10	4	of	of	ADP
ajst-8015	10	5	aging	age	VERB
ajst-8015	10	6	population	population	NOUN
ajst-8015	10	7	,	,	PUNCT
ajst-8015	10	8	the	the	DET
ajst-8015	10	9	incidence	incidence	NOUN
ajst-8015	10	10	of	of	ADP
ajst-8015	10	11	ad	ad	NOUN
ajst-8015	10	12	is	be	AUX
ajst-8015	10	13	constantly	constantly	ADV
ajst-8015	10	14	increasing	increase	VERB
ajst-8015	10	15	.	.	PUNCT
ajst-8015	11	1	according	accord	VERB
ajst-8015	11	2	to	to	ADP
ajst-8015	11	3	statistics	statistic	NOUN
ajst-8015	11	4	,	,	PUNCT
ajst-8015	11	5	there	there	PRON
ajst-8015	11	6	is	be	VERB
ajst-8015	11	7	one	one	NUM
ajst-8015	11	8	ad	ad	NOUN
ajst-8015	11	9	patient	patient	NOUN
ajst-8015	11	10	every	every	DET
ajst-8015	11	11	3	3	NUM
ajst-8015	11	12	seconds	second	NOUN
ajst-8015	11	13	in	in	ADP
ajst-8015	11	14	the	the	DET
ajst-8015	11	15	world	world	NOUN
ajst-8015	11	16	,	,	PUNCT
ajst-8015	11	17	and	and	CCONJ
ajst-8015	11	18	the	the	DET
ajst-8015	11	19	costs	cost	NOUN
ajst-8015	11	20	related	relate	VERB
ajst-8015	11	21	to	to	ADP
ajst-8015	11	22	dementia	dementia	NOUN
ajst-8015	11	23	continue	continue	VERB
ajst-8015	11	24	to	to	ADP
ajst-8015	11	25	increase[2	increase[2	PROPN
ajst-8015	11	26	]	]	PUNCT
ajst-8015	11	27	.	.	PUNCT
ajst-8015	12	1	it	it	PRON
ajst-8015	12	2	is	be	AUX
ajst-8015	12	3	estimated	estimate	VERB
ajst-8015	12	4	that	that	SCONJ
ajst-8015	12	5	by	by	ADP
ajst-8015	12	6	2050	2050	NUM
ajst-8015	12	7	,	,	PUNCT
ajst-8015	12	8	one	one	NUM
ajst-8015	12	9	out	out	ADP
ajst-8015	12	10	of	of	ADP
ajst-8015	12	11	every	every	DET
ajst-8015	12	12	85	85	NUM
ajst-8015	12	13	people	people	NOUN
ajst-8015	12	14	in	in	ADP
ajst-8015	12	15	the	the	DET
ajst-8015	12	16	world	world	NOUN
ajst-8015	12	17	will	will	AUX
ajst-8015	12	18	be	be	AUX
ajst-8015	12	19	affected	affect	VERB
ajst-8015	12	20	by	by	ADP
ajst-8015	12	21	this	this	DET
ajst-8015	12	22	disease	disease	NOUN
ajst-8015	12	23	,	,	PUNCT
ajst-8015	12	24	and	and	CCONJ
ajst-8015	12	25	the	the	DET
ajst-8015	12	26	number	number	NOUN
ajst-8015	12	27	of	of	ADP
ajst-8015	12	28	ad	ad	NOUN
ajst-8015	12	29	patients	patient	NOUN
ajst-8015	12	30	will	will	AUX
ajst-8015	12	31	exceed	exceed	VERB
ajst-8015	12	32	114	114	NUM
ajst-8015	12	33	million	million	NUM
ajst-8015	13	1	[	[	X
ajst-8015	13	2	3	3	NUM
ajst-8015	13	3	]	]	PUNCT
ajst-8015	13	4	.	.	PUNCT
ajst-8015	14	1	mild	mild	ADJ
ajst-8015	14	2	cognitive	cognitive	ADJ
ajst-8015	14	3	impairment	impairment	NOUN
ajst-8015	14	4	(	(	PUNCT
ajst-8015	14	5	mci	mci	NOUN
ajst-8015	14	6	)	)	PUNCT
ajst-8015	14	7	is	be	AUX
ajst-8015	14	8	a	a	DET
ajst-8015	14	9	transitional	transitional	ADJ
ajst-8015	14	10	state	state	NOUN
ajst-8015	14	11	between	between	ADP
ajst-8015	14	12	ad	ad	NOUN
ajst-8015	14	13	and	and	CCONJ
ajst-8015	14	14	control	control	NOUN
ajst-8015	14	15	normal	normal	ADJ
ajst-8015	14	16	(	(	PUNCT
ajst-8015	14	17	cn	cn	PROPN
ajst-8015	14	18	)	)	PUNCT
ajst-8015	14	19	.	.	PUNCT
ajst-8015	15	1	in	in	ADP
ajst-8015	15	2	this	this	DET
ajst-8015	15	3	stage	stage	NOUN
ajst-8015	15	4	,	,	PUNCT
ajst-8015	15	5	patients	patient	NOUN
ajst-8015	15	6	'	'	PART
ajst-8015	15	7	memory	memory	NOUN
ajst-8015	15	8	function	function	NOUN
ajst-8015	15	9	and	and	CCONJ
ajst-8015	15	10	thinking	thinking	NOUN
ajst-8015	15	11	ability	ability	NOUN
ajst-8015	15	12	are	be	AUX
ajst-8015	15	13	slightly	slightly	ADV
ajst-8015	15	14	decreased	decrease	VERB
ajst-8015	15	15	,	,	PUNCT
ajst-8015	15	16	but	but	CCONJ
ajst-8015	15	17	daily	daily	ADJ
ajst-8015	15	18	activities	activity	NOUN
ajst-8015	15	19	are	be	AUX
ajst-8015	15	20	not	not	PART
ajst-8015	15	21	affected	affect	VERB
ajst-8015	15	22	[	[	PUNCT
ajst-8015	15	23	4	4	NUM
ajst-8015	15	24	]	]	PUNCT
ajst-8015	15	25	.	.	PUNCT
ajst-8015	16	1	according	accord	VERB
ajst-8015	16	2	to	to	ADP
ajst-8015	16	3	different	different	ADJ
ajst-8015	16	4	classification	classification	NOUN
ajst-8015	16	5	criteria	criterion	NOUN
ajst-8015	16	6	,	,	PUNCT
ajst-8015	16	7	mci	mci	NOUN
ajst-8015	16	8	patients	patient	NOUN
ajst-8015	16	9	can	can	AUX
ajst-8015	16	10	be	be	AUX
ajst-8015	16	11	divided	divide	VERB
ajst-8015	16	12	into	into	ADP
ajst-8015	16	13	different	different	ADJ
ajst-8015	16	14	subtypes	subtype	NOUN
ajst-8015	16	15	.	.	PUNCT
ajst-8015	17	1	based	base	VERB
ajst-8015	17	2	on	on	ADP
ajst-8015	17	3	the	the	DET
ajst-8015	17	4	progression	progression	NOUN
ajst-8015	17	5	of	of	ADP
ajst-8015	17	6	the	the	DET
ajst-8015	17	7	disease	disease	NOUN
ajst-8015	17	8	,	,	PUNCT
ajst-8015	17	9	mci	mci	PROPN
ajst-8015	17	10	can	can	AUX
ajst-8015	17	11	be	be	AUX
ajst-8015	17	12	divided	divide	VERB
ajst-8015	17	13	into	into	ADP
ajst-8015	17	14	early	early	ADJ
ajst-8015	17	15	mci	mci	PROPN
ajst-8015	17	16	(	(	PUNCT
ajst-8015	17	17	early	early	ADJ
ajst-8015	17	18	mci	mci	NOUN
ajst-8015	17	19	,	,	PUNCT
ajst-8015	17	20	emci	emci	NOUN
ajst-8015	17	21	)	)	PUNCT
ajst-8015	17	22	and	and	CCONJ
ajst-8015	17	23	late	late	ADJ
ajst-8015	17	24	mci	mci	PROPN
ajst-8015	17	25	(	(	PUNCT
ajst-8015	17	26	late	late	ADJ
ajst-8015	17	27	mci	mci	PROPN
ajst-8015	17	28	,	,	PUNCT
ajst-8015	17	29	lmci	lmci	NOUN
ajst-8015	17	30	)	)	PUNCT
ajst-8015	17	31	.	.	PUNCT
ajst-8015	18	1	based	base	VERB
ajst-8015	18	2	on	on	ADP
ajst-8015	18	3	the	the	DET
ajst-8015	18	4	mechanism	mechanism	NOUN
ajst-8015	18	5	of	of	ADP
ajst-8015	18	6	disease	disease	NOUN
ajst-8015	18	7	transformation	transformation	NOUN
ajst-8015	18	8	,	,	PUNCT
ajst-8015	18	9	mci	mci	PROPN
ajst-8015	18	10	can	can	AUX
ajst-8015	18	11	be	be	AUX
ajst-8015	18	12	divided	divide	VERB
ajst-8015	18	13	into	into	ADP
ajst-8015	18	14	stable	stable	ADJ
ajst-8015	18	15	mci	mci	PROPN
ajst-8015	18	16	(	(	PUNCT
ajst-8015	18	17	smci	smci	NOUN
ajst-8015	18	18	)	)	PUNCT
ajst-8015	18	19	and	and	CCONJ
ajst-8015	18	20	progressive	progressive	ADJ
ajst-8015	18	21	mci	mci	PROPN
ajst-8015	18	22	(	(	PUNCT
ajst-8015	18	23	pmci	pmci	PROPN
ajst-8015	18	24	)	)	PUNCT
ajst-8015	18	25	.	.	PUNCT
ajst-8015	19	1	studies	study	NOUN
ajst-8015	19	2	have	have	AUX
ajst-8015	19	3	shown	show	VERB
ajst-8015	19	4	that	that	SCONJ
ajst-8015	19	5	32	32	NUM
ajst-8015	19	6	%	%	NOUN
ajst-8015	19	7	of	of	ADP
ajst-8015	19	8	mci	mci	PROPN
ajst-8015	19	9	patients	patient	NOUN
ajst-8015	19	10	will	will	AUX
ajst-8015	19	11	develop	develop	VERB
ajst-8015	19	12	ad	ad	NOUN
ajst-8015	19	13	within	within	ADP
ajst-8015	19	14	five	five	NUM
ajst-8015	19	15	years	year	NOUN
ajst-8015	19	16	,	,	PUNCT
ajst-8015	19	17	while	while	SCONJ
ajst-8015	19	18	the	the	DET
ajst-8015	19	19	annual	annual	ADJ
ajst-8015	19	20	conversion	conversion	NOUN
ajst-8015	19	21	rate	rate	NOUN
ajst-8015	19	22	of	of	ADP
ajst-8015	19	23	ad	ad	NOUN
ajst-8015	19	24	among	among	ADP
ajst-8015	19	25	cognitively	cognitively	ADV
ajst-8015	19	26	normal	normal	ADJ
ajst-8015	19	27	elderly	elderly	ADJ
ajst-8015	19	28	is	be	AUX
ajst-8015	19	29	only	only	ADV
ajst-8015	19	30	about	about	ADV
ajst-8015	19	31	1	1	NUM
ajst-8015	19	32	%	%	NOUN
ajst-8015	19	33	[	[	X
ajst-8015	19	34	5	5	NUM
ajst-8015	19	35	]	]	PUNCT
ajst-8015	19	36	.	.	PUNCT
ajst-8015	20	1	however	however	ADV
ajst-8015	20	2	,	,	PUNCT
ajst-8015	20	3	if	if	SCONJ
ajst-8015	20	4	patients	patient	NOUN
ajst-8015	20	5	with	with	ADP
ajst-8015	20	6	mci	mci	PROPN
ajst-8015	20	7	are	be	AUX
ajst-8015	20	8	identified	identify	VERB
ajst-8015	20	9	in	in	ADP
ajst-8015	20	10	time	time	NOUN
ajst-8015	20	11	and	and	CCONJ
ajst-8015	20	12	treated	treat	VERB
ajst-8015	20	13	effectively	effectively	ADV
ajst-8015	20	14	,	,	PUNCT
ajst-8015	20	15	patients	patient	NOUN
ajst-8015	20	16	with	with	ADP
ajst-8015	20	17	mci	mci	PROPN
ajst-8015	20	18	may	may	AUX
ajst-8015	20	19	not	not	PART
ajst-8015	20	20	eventually	eventually	ADV
ajst-8015	20	21	develop	develop	VERB
ajst-8015	20	22	ad	ad	NOUN
ajst-8015	20	23	.	.	PUNCT
ajst-8015	21	1	therefore	therefore	ADV
ajst-8015	21	2	,	,	PUNCT
ajst-8015	21	3	early	early	ADJ
ajst-8015	21	4	detection	detection	NOUN
ajst-8015	21	5	and	and	CCONJ
ajst-8015	21	6	treatment	treatment	NOUN
ajst-8015	21	7	of	of	ADP
ajst-8015	21	8	mci	mci	PROPN
ajst-8015	21	9	can	can	AUX
ajst-8015	21	10	effectively	effectively	ADV
ajst-8015	21	11	avoid	avoid	VERB
ajst-8015	21	12	the	the	DET
ajst-8015	21	13	occurrence	occurrence	NOUN
ajst-8015	21	14	of	of	ADP
ajst-8015	21	15	ad	ad	NOUN
ajst-8015	21	16	,	,	PUNCT
ajst-8015	21	17	which	which	PRON
ajst-8015	21	18	has	have	VERB
ajst-8015	21	19	important	important	ADJ
ajst-8015	21	20	clinical	clinical	ADJ
ajst-8015	21	21	and	and	CCONJ
ajst-8015	21	22	social	social	ADJ
ajst-8015	21	23	significance	significance	NOUN
ajst-8015	21	24	.	.	PUNCT
ajst-8015	22	1	with	with	ADP
ajst-8015	22	2	the	the	DET
ajst-8015	22	3	rapid	rapid	ADJ
ajst-8015	22	4	development	development	NOUN
ajst-8015	22	5	of	of	ADP
ajst-8015	22	6	neuroimaging	neuroimage	VERB
ajst-8015	22	7	technology	technology	NOUN
ajst-8015	22	8	,	,	PUNCT
ajst-8015	22	9	structural	structural	ADJ
ajst-8015	22	10	magnetic	magnetic	ADJ
ajst-8015	22	11	resonance	resonance	NOUN
ajst-8015	22	12	imaging	imaging	NOUN
ajst-8015	22	13	(	(	PUNCT
ajst-8015	22	14	smri	smri	PROPN
ajst-8015	22	15	)	)	PUNCT
ajst-8015	22	16	,	,	PUNCT
ajst-8015	22	17	diffusion	diffusion	NOUN
ajst-8015	22	18	tensor	tensor	NOUN
ajst-8015	22	19	imaging	imaging	NOUN
ajst-8015	22	20	(	(	PUNCT
ajst-8015	22	21	diffusion	diffusion	NOUN
ajst-8015	22	22	tensor	tensor	NOUN
ajst-8015	22	23	imaging	imaging	NOUN
ajst-8015	22	24	,	,	PUNCT
ajst-8015	22	25	dti	dti	PROPN
ajst-8015	22	26	)	)	PUNCT
ajst-8015	22	27	,	,	PUNCT
ajst-8015	22	28	functional	functional	ADJ
ajst-8015	22	29	magnetic	magnetic	ADJ
ajst-8015	22	30	resonance	resonance	NOUN
ajst-8015	22	31	imaging	imaging	NOUN
ajst-8015	22	32	(	(	PUNCT
ajst-8015	22	33	fmri	fmri	ADJ
ajst-8015	22	34	)	)	PUNCT
ajst-8015	22	35	and	and	CCONJ
ajst-8015	22	36	positron	positron	NOUN
ajst-8015	22	37	emission	emission	NOUN
ajst-8015	22	38	computed	compute	VERB
ajst-8015	22	39	tomography	tomography	NOUN
ajst-8015	22	40	,	,	PUNCT
ajst-8015	22	41	brain	brain	NOUN
ajst-8015	22	42	imaging	imaging	NOUN
ajst-8015	22	43	such	such	ADJ
ajst-8015	22	44	as	as	ADP
ajst-8015	22	45	pet	pet	NOUN
ajst-8015	22	46	has	have	AUX
ajst-8015	22	47	been	be	AUX
ajst-8015	22	48	widely	widely	ADV
ajst-8015	22	49	used	use	VERB
ajst-8015	22	50	in	in	ADP
ajst-8015	22	51	the	the	DET
ajst-8015	22	52	clinical	clinical	ADJ
ajst-8015	22	53	diagnosis	diagnosis	NOUN
ajst-8015	22	54	of	of	ADP
ajst-8015	22	55	ad	ad	NOUN
ajst-8015	22	56	.	.	PUNCT
ajst-8015	23	1	the	the	DET
ajst-8015	23	2	rich	rich	ADJ
ajst-8015	23	3	neuroimaging	neuroimaging	NOUN
ajst-8015	23	4	technology	technology	NOUN
ajst-8015	23	5	brings	bring	VERB
ajst-8015	23	6	convenience	convenience	NOUN
ajst-8015	23	7	to	to	ADP
ajst-8015	23	8	the	the	DET
ajst-8015	23	9	clinical	clinical	ADJ
ajst-8015	23	10	diagnosis	diagnosis	NOUN
ajst-8015	23	11	of	of	ADP
ajst-8015	23	12	ad	ad	NOUN
ajst-8015	23	13	,	,	PUNCT
ajst-8015	23	14	but	but	CCONJ
ajst-8015	23	15	also	also	ADV
ajst-8015	23	16	raises	raise	VERB
ajst-8015	23	17	new	new	ADJ
ajst-8015	23	18	problems	problem	NOUN
ajst-8015	23	19	.	.	PUNCT
ajst-8015	24	1	first	first	ADV
ajst-8015	24	2	of	of	ADP
ajst-8015	24	3	all	all	PRON
ajst-8015	24	4	,	,	PUNCT
ajst-8015	24	5	with	with	ADP
ajst-8015	24	6	the	the	DET
ajst-8015	24	7	continuous	continuous	ADJ
ajst-8015	24	8	update	update	NOUN
ajst-8015	24	9	and	and	CCONJ
ajst-8015	24	10	improvement	improvement	NOUN
ajst-8015	24	11	of	of	ADP
ajst-8015	24	12	neuroimaging	neuroimage	VERB
ajst-8015	24	13	technology	technology	NOUN
ajst-8015	24	14	,	,	PUNCT
ajst-8015	24	15	the	the	DET
ajst-8015	24	16	types	type	NOUN
ajst-8015	24	17	of	of	ADP
ajst-8015	24	18	brain	brain	NOUN
ajst-8015	24	19	imaging	imaging	NOUN
ajst-8015	24	20	images	image	NOUN
ajst-8015	24	21	of	of	ADP
ajst-8015	24	22	each	each	DET
ajst-8015	24	23	patient	patient	NOUN
ajst-8015	24	24	in	in	ADP
ajst-8015	24	25	clinical	clinical	ADJ
ajst-8015	24	26	practice	practice	NOUN
ajst-8015	24	27	have	have	AUX
ajst-8015	24	28	increased	increase	VERB
ajst-8015	24	29	significantly	significantly	ADV
ajst-8015	24	30	,	,	PUNCT
ajst-8015	24	31	which	which	PRON
ajst-8015	24	32	not	not	PART
ajst-8015	24	33	only	only	ADV
ajst-8015	24	34	aids	aid	VERB
ajst-8015	24	35	the	the	DET
ajst-8015	24	36	diagnosis	diagnosis	NOUN
ajst-8015	24	37	of	of	ADP
ajst-8015	24	38	doctors	doctor	NOUN
ajst-8015	24	39	but	but	CCONJ
ajst-8015	24	40	also	also	ADV
ajst-8015	24	41	increases	increase	VERB
ajst-8015	24	42	the	the	DET
ajst-8015	24	43	burden	burden	NOUN
ajst-8015	24	44	of	of	ADP
ajst-8015	24	45	doctors	doctor	NOUN
ajst-8015	24	46	.	.	PUNCT
ajst-8015	25	1	secondly	secondly	ADV
ajst-8015	25	2	,	,	PUNCT
ajst-8015	25	3	doctors	doctor	NOUN
ajst-8015	25	4	find	find	VERB
ajst-8015	25	5	diseased	diseased	ADJ
ajst-8015	25	6	areas	area	NOUN
ajst-8015	25	7	mainly	mainly	ADV
ajst-8015	25	8	by	by	ADP
ajst-8015	25	9	observing	observe	VERB
ajst-8015	25	10	neuroimages	neuroimage	NOUN
ajst-8015	25	11	with	with	ADP
ajst-8015	25	12	naked	naked	ADJ
ajst-8015	25	13	eyes	eye	NOUN
ajst-8015	25	14	based	base	VERB
ajst-8015	25	15	on	on	ADP
ajst-8015	25	16	clinical	clinical	ADJ
ajst-8015	25	17	experience	experience	NOUN
ajst-8015	25	18	,	,	PUNCT
ajst-8015	25	19	which	which	PRON
ajst-8015	25	20	makes	make	VERB
ajst-8015	25	21	the	the	DET
ajst-8015	25	22	diagnosis	diagnosis	NOUN
ajst-8015	25	23	results	result	NOUN
ajst-8015	25	24	of	of	ADP
ajst-8015	25	25	patients	patient	NOUN
ajst-8015	25	26	mainly	mainly	ADV
ajst-8015	25	27	depend	depend	VERB
ajst-8015	25	28	on	on	ADP
ajst-8015	25	29	the	the	DET
ajst-8015	25	30	clinical	clinical	ADJ
ajst-8015	25	31	experience	experience	NOUN
ajst-8015	25	32	of	of	ADP
ajst-8015	25	33	doctors	doctor	NOUN
ajst-8015	25	34	,	,	PUNCT
ajst-8015	25	35	and	and	CCONJ
ajst-8015	25	36	the	the	DET
ajst-8015	25	37	rich	rich	ADJ
ajst-8015	25	38	disease	disease	NOUN
ajst-8015	25	39	-	-	PUNCT
ajst-8015	25	40	related	relate	VERB
ajst-8015	25	41	information	information	NOUN
ajst-8015	25	42	contained	contain	VERB
ajst-8015	25	43	in	in	ADP
ajst-8015	25	44	neuroimages	neuroimage	NOUN
ajst-8015	25	45	is	be	AUX
ajst-8015	25	46	difficult	difficult	ADJ
ajst-8015	25	47	to	to	PART
ajst-8015	25	48	be	be	AUX
ajst-8015	25	49	observed	observe	VERB
ajst-8015	25	50	with	with	ADP
ajst-8015	25	51	naked	naked	ADJ
ajst-8015	25	52	eyes	eye	NOUN
ajst-8015	25	53	only	only	ADV
ajst-8015	25	54	.	.	PUNCT
ajst-8015	26	1	in	in	ADP
ajst-8015	26	2	recent	recent	ADJ
ajst-8015	26	3	years	year	NOUN
ajst-8015	26	4	,	,	PUNCT
ajst-8015	26	5	as	as	ADP
ajst-8015	26	6	an	an	DET
ajst-8015	26	7	important	important	ADJ
ajst-8015	26	8	technology	technology	NOUN
ajst-8015	26	9	of	of	ADP
ajst-8015	26	10	artificial	artificial	ADJ
ajst-8015	26	11	intelligence	intelligence	NOUN
ajst-8015	26	12	(	(	PUNCT
ajst-8015	26	13	ai	ai	NOUN
ajst-8015	26	14	)	)	PUNCT
ajst-8015	26	15	,	,	PUNCT
ajst-8015	26	16	deep	deep	ADJ
ajst-8015	26	17	learning	learning	NOUN
ajst-8015	26	18	algorithm	algorithm	NOUN
ajst-8015	26	19	has	have	AUX
ajst-8015	26	20	achieved	achieve	VERB
ajst-8015	26	21	great	great	ADJ
ajst-8015	26	22	success	success	NOUN
ajst-8015	26	23	in	in	ADP
ajst-8015	26	24	many	many	ADJ
ajst-8015	26	25	fields	field	NOUN
ajst-8015	26	26	.	.	PUNCT
ajst-8015	27	1	more	more	ADJ
ajst-8015	27	2	and	and	CCONJ
ajst-8015	27	3	more	more	ADV
ajst-8015	27	4	deep	deep	ADJ
ajst-8015	27	5	learning	learning	NOUN
ajst-8015	27	6	-	-	PUNCT
ajst-8015	27	7	based	base	VERB
ajst-8015	27	8	diagnosis	diagnosis	NOUN
ajst-8015	27	9	algorithms	algorithm	NOUN
ajst-8015	27	10	for	for	ADP
ajst-8015	27	11	alzheimer	alzheimer	PROPN
ajst-8015	27	12	's	's	PART
ajst-8015	27	13	disease	disease	NOUN
ajst-8015	27	14	have	have	AUX
ajst-8015	27	15	been	be	AUX
ajst-8015	27	16	proposed	propose	VERB
ajst-8015	27	17	.	.	PUNCT
ajst-8015	28	1	the	the	DET
ajst-8015	28	2	rest	rest	NOUN
ajst-8015	28	3	of	of	ADP
ajst-8015	28	4	this	this	DET
ajst-8015	28	5	paper	paper	NOUN
ajst-8015	28	6	is	be	AUX
ajst-8015	28	7	organized	organize	VERB
ajst-8015	28	8	as	as	SCONJ
ajst-8015	28	9	follows	follow	VERB
ajst-8015	28	10	.	.	PUNCT
ajst-8015	29	1	section	section	NOUN
ajst-8015	29	2	2	2	NUM
ajst-8015	29	3	discusses	discuss	VERB
ajst-8015	29	4	artificial	artificial	ADJ
ajst-8015	29	5	intelligence	intelligence	NOUN
ajst-8015	29	6	technologies	technology	NOUN
ajst-8015	29	7	for	for	ADP
ajst-8015	29	8	ad	ad	NOUN
ajst-8015	29	9	diagnosis	diagnosis	NOUN
ajst-8015	29	10	and	and	CCONJ
ajst-8015	29	11	discusses	discuss	VERB
ajst-8015	29	12	the	the	DET
ajst-8015	29	13	advantages	advantage	NOUN
ajst-8015	29	14	and	and	CCONJ
ajst-8015	29	15	disadvantages	disadvantage	NOUN
ajst-8015	29	16	of	of	ADP
ajst-8015	29	17	these	these	DET
ajst-8015	29	18	technologies	technology	NOUN
ajst-8015	29	19	.	.	PUNCT
ajst-8015	30	1	section	section	NOUN
ajst-8015	30	2	3	3	NUM
ajst-8015	30	3	provides	provide	VERB
ajst-8015	30	4	an	an	DET
ajst-8015	30	5	in	in	ADP
ajst-8015	30	6	-	-	PUNCT
ajst-8015	30	7	depth	depth	NOUN
ajst-8015	30	8	discussion	discussion	NOUN
ajst-8015	30	9	of	of	ADP
ajst-8015	30	10	existing	exist	VERB
ajst-8015	30	11	technologies	technology	NOUN
ajst-8015	30	12	and	and	CCONJ
ajst-8015	30	13	prospects	prospect	NOUN
ajst-8015	30	14	for	for	ADP
ajst-8015	30	15	future	future	ADJ
ajst-8015	30	16	work	work	NOUN
ajst-8015	30	17	.	.	PUNCT
ajst-8015	31	1	2	2	X
ajst-8015	31	2	.	.	X
ajst-8015	31	3	literature	literature	NOUN
ajst-8015	31	4	reviews	review	NOUN
ajst-8015	31	5	with	with	ADP
ajst-8015	31	6	the	the	DET
ajst-8015	31	7	improvement	improvement	NOUN
ajst-8015	31	8	of	of	ADP
ajst-8015	31	9	computer	computer	NOUN
ajst-8015	31	10	hardware	hardware	NOUN
ajst-8015	31	11	,	,	PUNCT
ajst-8015	31	12	intelligent	intelligent	ADJ
ajst-8015	31	13	recognition	recognition	NOUN
ajst-8015	31	14	algorithm	algorithm	NOUN
ajst-8015	31	15	based	base	VERB
ajst-8015	31	16	on	on	ADP
ajst-8015	31	17	machine	machine	NOUN
ajst-8015	31	18	learning	learning	NOUN
ajst-8015	31	19	has	have	AUX
ajst-8015	31	20	been	be	AUX
ajst-8015	31	21	more	more	ADV
ajst-8015	31	22	and	and	CCONJ
ajst-8015	31	23	more	more	ADV
ajst-8015	31	24	applied	apply	VERB
ajst-8015	31	25	in	in	ADP
ajst-8015	31	26	alzheimer	alzheimer	PROPN
ajst-8015	31	27	's	's	PART
ajst-8015	31	28	disease	disease	NOUN
ajst-8015	31	29	related	relate	VERB
ajst-8015	31	30	research	research	NOUN
ajst-8015	31	31	.	.	PUNCT
ajst-8015	32	1	at	at	ADP
ajst-8015	32	2	present	present	ADJ
ajst-8015	32	3	,	,	PUNCT
ajst-8015	32	4	there	there	PRON
ajst-8015	32	5	are	be	VERB
ajst-8015	32	6	three	three	NUM
ajst-8015	32	7	mainstream	mainstream	ADJ
ajst-8015	32	8	research	research	NOUN
ajst-8015	32	9	directions	direction	NOUN
ajst-8015	32	10	,	,	PUNCT
ajst-8015	32	11	which	which	PRON
ajst-8015	32	12	are	be	AUX
ajst-8015	32	13	the	the	DET
ajst-8015	32	14	classification	classification	NOUN
ajst-8015	32	15	of	of	ADP
ajst-8015	32	16	the	the	DET
ajst-8015	32	17	course	course	NOUN
ajst-8015	32	18	of	of	ADP
ajst-8015	32	19	cn	cn	PROPN
ajst-8015	32	20	,	,	PUNCT
ajst-8015	32	21	mci	mci	PROPN
ajst-8015	32	22	and	and	CCONJ
ajst-8015	32	23	ad	ad	NOUN
ajst-8015	32	24	based	base	VERB
ajst-8015	32	25	on	on	ADP
ajst-8015	32	26	mri	mri	NOUN
ajst-8015	32	27	images	image	NOUN
ajst-8015	32	28	.	.	PUNCT
ajst-8015	33	1	the	the	DET
ajst-8015	33	2	brain	brain	NOUN
ajst-8015	33	3	mri	mri	NOUN
ajst-8015	33	4	images	image	NOUN
ajst-8015	33	5	were	be	AUX
ajst-8015	33	6	preprocessed	preprocesse	VERB
ajst-8015	33	7	and	and	CCONJ
ajst-8015	33	8	segmented	segment	VERB
ajst-8015	33	9	.	.	PUNCT
ajst-8015	34	1	the	the	DET
ajst-8015	34	2	morphologic	morphologic	ADJ
ajst-8015	34	3	transformation	transformation	NOUN
ajst-8015	34	4	mechanism	mechanism	NOUN
ajst-8015	34	5	of	of	ADP
ajst-8015	34	6	brain	brain	NOUN
ajst-8015	34	7	from	from	ADP
ajst-8015	34	8	mci	mci	PROPN
ajst-8015	34	9	to	to	ADP
ajst-8015	34	10	ad	ad	NOUN
ajst-8015	34	11	was	be	AUX
ajst-8015	34	12	studied	study	VERB
ajst-8015	34	13	,	,	PUNCT
ajst-8015	34	14	and	and	CCONJ
ajst-8015	34	15	the	the	DET
ajst-8015	34	16	transformation	transformation	NOUN
ajst-8015	34	17	course	course	NOUN
ajst-8015	34	18	of	of	ADP
ajst-8015	34	19	patients	patient	NOUN
ajst-8015	34	20	was	be	AUX
ajst-8015	34	21	predicted	predict	VERB
ajst-8015	34	22	based	base	VERB
ajst-8015	34	23	on	on	ADP
ajst-8015	34	24	mri	mri	NOUN
ajst-8015	34	25	images	image	NOUN
ajst-8015	34	26	.	.	PUNCT
ajst-8015	35	1	among	among	ADP
ajst-8015	35	2	them	they	PRON
ajst-8015	35	3	,	,	PUNCT
ajst-8015	35	4	disease	disease	NOUN
ajst-8015	35	5	course	course	NOUN
ajst-8015	35	6	classification	classification	NOUN
ajst-8015	35	7	based	base	VERB
ajst-8015	35	8	on	on	ADP
ajst-8015	35	9	mri	mri	NOUN
ajst-8015	35	10	images	image	NOUN
ajst-8015	35	11	is	be	AUX
ajst-8015	35	12	the	the	DET
ajst-8015	35	13	direction	direction	NOUN
ajst-8015	35	14	with	with	ADP
ajst-8015	35	15	the	the	DET
ajst-8015	35	16	most	most	ADV
ajst-8015	35	17	relevant	relevant	ADJ
ajst-8015	35	18	studies	study	NOUN
ajst-8015	35	19	and	and	CCONJ
ajst-8015	35	20	the	the	DET
ajst-8015	35	21	greatest	great	ADJ
ajst-8015	35	22	application	application	NOUN
ajst-8015	35	23	significance	significance	NOUN
ajst-8015	35	24	.	.	PUNCT
ajst-8015	36	1	since	since	SCONJ
ajst-8015	36	2	it	it	PRON
ajst-8015	36	3	is	be	AUX
ajst-8015	36	4	difficult	difficult	ADJ
ajst-8015	36	5	for	for	SCONJ
ajst-8015	36	6	doctors	doctor	NOUN
ajst-8015	36	7	to	to	PART
ajst-8015	36	8	make	make	VERB
ajst-8015	36	9	clinical	clinical	ADJ
ajst-8015	36	10	diagnosis	diagnosis	NOUN
ajst-8015	36	11	directly	directly	ADV
ajst-8015	36	12	from	from	ADP
ajst-8015	36	13	patients	patient	NOUN
ajst-8015	36	14	'	'	PART
ajst-8015	36	15	brain	brain	NOUN
ajst-8015	36	16	mri	mri	NOUN
ajst-8015	36	17	images	image	NOUN
ajst-8015	36	18	,	,	PUNCT
ajst-8015	36	19	machine	machine	NOUN
ajst-8015	36	20	learning	learning	NOUN
ajst-8015	36	21	and	and	CCONJ
ajst-8015	36	22	data	datum	NOUN
ajst-8015	36	23	science	science	NOUN
ajst-8015	36	24	technology	technology	NOUN
ajst-8015	36	25	are	be	AUX
ajst-8015	36	26	expected	expect	VERB
ajst-8015	36	27	to	to	PART
ajst-8015	36	28	assist	assist	VERB
ajst-8015	36	29	doctors	doctor	NOUN
ajst-8015	36	30	to	to	PART
ajst-8015	36	31	identify	identify	VERB
ajst-8015	36	32	patients	patient	NOUN
ajst-8015	36	33	with	with	ADP
ajst-8015	36	34	alzheimer	alzheimer	PROPN
ajst-8015	36	35	's	's	PART
ajst-8015	36	36	disease	disease	NOUN
ajst-8015	36	37	through	through	ADP
ajst-8015	36	38	mri	mri	NOUN
ajst-8015	36	39	images	image	NOUN
ajst-8015	36	40	and	and	CCONJ
ajst-8015	36	41	improve	improve	VERB
ajst-8015	36	42	the	the	DET
ajst-8015	36	43	diagnostic	diagnostic	ADJ
ajst-8015	36	44	accuracy	accuracy	NOUN
ajst-8015	36	45	.	.	PUNCT
ajst-8015	37	1	216	216	NUM
ajst-8015	37	2	2.1	2.1	NUM
ajst-8015	37	3	.	.	PUNCT
ajst-8015	37	4	recognition	recognition	NOUN
ajst-8015	37	5	of	of	ADP
ajst-8015	37	6	alzheimer	alzheimer	PROPN
ajst-8015	37	7	's	's	PART
ajst-8015	37	8	disease	disease	NOUN
ajst-8015	37	9	based	base	VERB
ajst-8015	37	10	on	on	ADP
ajst-8015	37	11	machine	machine	NOUN
ajst-8015	37	12	learning	learning	NOUN
ajst-8015	37	13	methods	method	NOUN
ajst-8015	37	14	the	the	DET
ajst-8015	37	15	recognition	recognition	NOUN
ajst-8015	37	16	of	of	ADP
ajst-8015	37	17	alzheimer	alzheimer	PROPN
ajst-8015	37	18	's	's	PART
ajst-8015	37	19	disease	disease	NOUN
ajst-8015	37	20	based	base	VERB
ajst-8015	37	21	on	on	ADP
ajst-8015	37	22	machine	machine	NOUN
ajst-8015	37	23	learning	learning	NOUN
ajst-8015	37	24	method	method	NOUN
ajst-8015	37	25	is	be	AUX
ajst-8015	37	26	generally	generally	ADV
ajst-8015	37	27	divided	divide	VERB
ajst-8015	37	28	into	into	ADP
ajst-8015	37	29	the	the	DET
ajst-8015	37	30	following	follow	VERB
ajst-8015	37	31	steps	step	NOUN
ajst-8015	37	32	:	:	PUNCT
ajst-8015	37	33	firstly	firstly	ADV
ajst-8015	37	34	,	,	PUNCT
ajst-8015	37	35	preprocessing	preprocessing	NOUN
ajst-8015	37	36	of	of	ADP
ajst-8015	37	37	the	the	DET
ajst-8015	37	38	acquired	acquire	VERB
ajst-8015	37	39	neuroimage	neuroimage	NOUN
ajst-8015	37	40	data	datum	NOUN
ajst-8015	37	41	of	of	ADP
ajst-8015	37	42	the	the	DET
ajst-8015	37	43	subjects	subject	NOUN
ajst-8015	37	44	(	(	PUNCT
ajst-8015	37	45	including	include	VERB
ajst-8015	37	46	image	image	NOUN
ajst-8015	37	47	registration	registration	NOUN
ajst-8015	37	48	,	,	PUNCT
ajst-8015	37	49	brain	brain	NOUN
ajst-8015	37	50	tissue	tissue	NOUN
ajst-8015	37	51	segmentation	segmentation	NOUN
ajst-8015	37	52	,	,	PUNCT
ajst-8015	37	53	image	image	NOUN
ajst-8015	37	54	noise	noise	NOUN
ajst-8015	37	55	reduction	reduction	NOUN
ajst-8015	37	56	,	,	PUNCT
ajst-8015	37	57	etc	etc	X
ajst-8015	37	58	.	.	X
ajst-8015	37	59	)	)	PUNCT
ajst-8015	37	60	;	;	PUNCT
ajst-8015	37	61	then	then	ADV
ajst-8015	37	62	the	the	DET
ajst-8015	37	63	feature	feature	NOUN
ajst-8015	37	64	dimension	dimension	NOUN
ajst-8015	37	65	is	be	AUX
ajst-8015	37	66	improved	improve	VERB
ajst-8015	37	67	by	by	ADP
ajst-8015	37	68	dimensionality	dimensionality	NOUN
ajst-8015	37	69	reduction	reduction	NOUN
ajst-8015	37	70	method	method	NOUN
ajst-8015	37	71	.	.	PUNCT
ajst-8015	38	1	finally	finally	ADV
ajst-8015	38	2	,	,	PUNCT
ajst-8015	38	3	the	the	DET
ajst-8015	38	4	classification	classification	NOUN
ajst-8015	38	5	is	be	AUX
ajst-8015	38	6	carried	carry	VERB
ajst-8015	38	7	out	out	ADP
ajst-8015	38	8	in	in	ADP
ajst-8015	38	9	the	the	DET
ajst-8015	38	10	classifier	classifier	NOUN
ajst-8015	38	11	and	and	CCONJ
ajst-8015	38	12	the	the	DET
ajst-8015	38	13	result	result	NOUN
ajst-8015	38	14	is	be	AUX
ajst-8015	38	15	obtained	obtain	VERB
ajst-8015	38	16	.	.	PUNCT
ajst-8015	39	1	as	as	SCONJ
ajst-8015	39	2	shown	show	VERB
ajst-8015	39	3	in	in	ADP
ajst-8015	39	4	figure	figure	NOUN
ajst-8015	39	5	1	1	NUM
ajst-8015	39	6	.	.	PUNCT
ajst-8015	39	7	figure	figure	NOUN
ajst-8015	39	8	1	1	NUM
ajst-8015	39	9	.	.	PUNCT
ajst-8015	40	1	ad	ad	NOUN
ajst-8015	40	2	identification	identification	NOUN
ajst-8015	40	3	steps	step	NOUN
ajst-8015	40	4	based	base	VERB
ajst-8015	40	5	on	on	ADP
ajst-8015	40	6	a	a	DET
ajst-8015	40	7	machine	machine	NOUN
ajst-8015	40	8	learning	learning	NOUN
ajst-8015	40	9	method	method	NOUN
ajst-8015	40	10	2.1.1	2.1.1	NUM
ajst-8015	40	11	.	.	PUNCT
ajst-8015	41	1	feature	feature	NOUN
ajst-8015	41	2	extraction	extraction	NOUN
ajst-8015	41	3	the	the	DET
ajst-8015	41	4	process	process	NOUN
ajst-8015	41	5	of	of	ADP
ajst-8015	41	6	preprocessing	preprocesse	VERB
ajst-8015	41	7	the	the	DET
ajst-8015	41	8	original	original	ADJ
ajst-8015	41	9	image	image	NOUN
ajst-8015	41	10	data	datum	NOUN
ajst-8015	41	11	,	,	PUNCT
ajst-8015	41	12	eliminating	eliminate	VERB
ajst-8015	41	13	the	the	DET
ajst-8015	41	14	interference	interference	NOUN
ajst-8015	41	15	of	of	ADP
ajst-8015	41	16	redundant	redundant	ADJ
ajst-8015	41	17	factors	factor	NOUN
ajst-8015	41	18	and	and	CCONJ
ajst-8015	41	19	highlighting	highlight	VERB
ajst-8015	41	20	the	the	DET
ajst-8015	41	21	key	key	ADJ
ajst-8015	41	22	information	information	NOUN
ajst-8015	41	23	is	be	AUX
ajst-8015	41	24	called	call	VERB
ajst-8015	41	25	image	image	NOUN
ajst-8015	41	26	feature	feature	NOUN
ajst-8015	41	27	extraction	extraction	NOUN
ajst-8015	41	28	.	.	PUNCT
ajst-8015	42	1	commonly	commonly	ADV
ajst-8015	42	2	used	use	VERB
ajst-8015	42	3	feature	feature	NOUN
ajst-8015	42	4	extraction	extraction	NOUN
ajst-8015	42	5	methods	method	NOUN
ajst-8015	42	6	include	include	VERB
ajst-8015	42	7	:	:	PUNCT
ajst-8015	42	8	(	(	PUNCT
ajst-8015	42	9	1	1	X
ajst-8015	42	10	)	)	PUNCT
ajst-8015	42	11	voxel	voxel	PROPN
ajst-8015	42	12	based	base	VERB
ajst-8015	42	13	morphometry	morphometry	PROPN
ajst-8015	42	14	(	(	PUNCT
ajst-8015	42	15	vbm	vbm	PROPN
ajst-8015	42	16	)	)	PUNCT
ajst-8015	43	1	[	[	X
ajst-8015	43	2	6	6	NUM
ajst-8015	43	3	]	]	PUNCT
ajst-8015	43	4	.	.	PUNCT
ajst-8015	44	1	(	(	PUNCT
ajst-8015	44	2	2	2	X
ajst-8015	44	3	)	)	PUNCT
ajst-8015	44	4	region	region	NOUN
ajst-8015	44	5	of	of	ADP
ajst-8015	44	6	interest	interest	NOUN
ajst-8015	44	7	,	,	PUNCT
ajst-8015	44	8	(	(	PUNCT
ajst-8015	44	9	roi	roi	NOUN
ajst-8015	44	10	)	)	PUNCT
ajst-8015	44	11	methods	method	NOUN
ajst-8015	44	12	(	(	PUNCT
ajst-8015	44	13	3	3	NUM
ajst-8015	44	14	)	)	PUNCT
ajst-8015	44	15	patch	patch	NOUN
ajst-8015	44	16	based	base	VERB
ajst-8015	44	17	approach	approach	NOUN
ajst-8015	44	18	methods	method	NOUN
ajst-8015	44	19	[	[	X
ajst-8015	44	20	7	7	NUM
ajst-8015	44	21	]	]	PUNCT
ajst-8015	44	22	,	,	PUNCT
ajst-8015	44	23	(	(	PUNCT
ajst-8015	44	24	4	4	X
ajst-8015	44	25	)	)	PUNCT
ajst-8015	44	26	slice	slice	NOUN
ajst-8015	44	27	based	base	VERB
ajst-8015	44	28	methods	method	NOUN
ajst-8015	44	29	,	,	PUNCT
ajst-8015	44	30	(	(	PUNCT
ajst-8015	44	31	5	5	X
ajst-8015	44	32	)	)	PUNCT
ajst-8015	44	33	global	global	ADJ
ajst-8015	44	34	image	image	NOUN
ajst-8015	44	35	based	base	VERB
ajst-8015	44	36	methods	method	NOUN
ajst-8015	44	37	.	.	PUNCT
ajst-8015	45	1	vbm	vbm	PROPN
ajst-8015	45	2	methods	method	NOUN
ajst-8015	45	3	are	be	AUX
ajst-8015	45	4	often	often	ADV
ajst-8015	45	5	used	use	VERB
ajst-8015	45	6	in	in	ADP
ajst-8015	45	7	mri	mri	NOUN
ajst-8015	45	8	image	image	NOUN
ajst-8015	45	9	analysis	analysis	NOUN
ajst-8015	45	10	.	.	PUNCT
ajst-8015	46	1	the	the	DET
ajst-8015	46	2	principle	principle	NOUN
ajst-8015	46	3	is	be	AUX
ajst-8015	46	4	to	to	PART
ajst-8015	46	5	compare	compare	VERB
ajst-8015	46	6	the	the	DET
ajst-8015	46	7	changes	change	NOUN
ajst-8015	46	8	of	of	ADP
ajst-8015	46	9	voxel	voxel	PROPN
ajst-8015	46	10	intensity	intensity	NOUN
ajst-8015	46	11	in	in	ADP
ajst-8015	46	12	three	three	NUM
ajst-8015	46	13	-	-	PUNCT
ajst-8015	46	14	dimensional	dimensional	ADJ
ajst-8015	46	15	images	image	NOUN
ajst-8015	46	16	,	,	PUNCT
ajst-8015	46	17	and	and	CCONJ
ajst-8015	46	18	then	then	ADV
ajst-8015	46	19	reflect	reflect	VERB
ajst-8015	46	20	the	the	DET
ajst-8015	46	21	morphological	morphological	ADJ
ajst-8015	46	22	changes	change	NOUN
ajst-8015	46	23	of	of	ADP
ajst-8015	46	24	the	the	DET
ajst-8015	46	25	corresponding	corresponding	ADJ
ajst-8015	46	26	brain	brain	NOUN
ajst-8015	46	27	tissue	tissue	NOUN
ajst-8015	46	28	.	.	PUNCT
ajst-8015	47	1	zhang	zhang	PROPN
ajst-8015	47	2	et	et	PROPN
ajst-8015	47	3	al	al	PROPN
ajst-8015	47	4	.	.	PUNCT
ajst-8015	48	1	[	[	X
ajst-8015	48	2	8]combined	8]combine	VERB
ajst-8015	48	3	vbm	vbm	PROPN
ajst-8015	48	4	extraction	extraction	NOUN
ajst-8015	48	5	features	feature	VERB
ajst-8015	48	6	with	with	ADP
ajst-8015	48	7	support	support	NOUN
ajst-8015	48	8	vector	vector	NOUN
ajst-8015	48	9	machine	machine	NOUN
ajst-8015	48	10	(	(	PUNCT
ajst-8015	48	11	svm	svm	ADJ
ajst-8015	48	12	)	)	PUNCT
ajst-8015	48	13	classifier	classifier	NOUN
ajst-8015	48	14	for	for	ADP
ajst-8015	48	15	clinical	clinical	ADJ
ajst-8015	48	16	diagnosis	diagnosis	NOUN
ajst-8015	48	17	of	of	ADP
ajst-8015	48	18	ad	ad	NOUN
ajst-8015	48	19	.	.	PUNCT
ajst-8015	49	1	as	as	SCONJ
ajst-8015	49	2	it	it	PRON
ajst-8015	49	3	directly	directly	ADV
ajst-8015	49	4	uses	use	VERB
ajst-8015	49	5	the	the	DET
ajst-8015	49	6	voxel	voxel	PROPN
ajst-8015	49	7	strength	strength	NOUN
ajst-8015	49	8	as	as	ADP
ajst-8015	49	9	the	the	DET
ajst-8015	49	10	classification	classification	NOUN
ajst-8015	49	11	feature	feature	NOUN
ajst-8015	49	12	,	,	PUNCT
ajst-8015	49	13	it	it	PRON
ajst-8015	49	14	is	be	AUX
ajst-8015	49	15	the	the	DET
ajst-8015	49	16	most	most	ADV
ajst-8015	49	17	simple	simple	ADJ
ajst-8015	49	18	and	and	CCONJ
ajst-8015	49	19	intuitive	intuitive	ADJ
ajst-8015	49	20	.	.	PUNCT
ajst-8015	50	1	but	but	CCONJ
ajst-8015	50	2	the	the	DET
ajst-8015	50	3	defect	defect	NOUN
ajst-8015	50	4	of	of	ADP
ajst-8015	50	5	vbm	vbm	PROPN
ajst-8015	50	6	method	method	NOUN
ajst-8015	50	7	is	be	AUX
ajst-8015	50	8	that	that	SCONJ
ajst-8015	50	9	it	it	PRON
ajst-8015	50	10	ignores	ignore	VERB
ajst-8015	50	11	the	the	DET
ajst-8015	50	12	region	region	NOUN
ajst-8015	50	13	information	information	NOUN
ajst-8015	50	14	and	and	CCONJ
ajst-8015	50	15	the	the	DET
ajst-8015	50	16	high	high	ADJ
ajst-8015	50	17	dimension	dimension	NOUN
ajst-8015	50	18	of	of	ADP
ajst-8015	50	19	feature	feature	NOUN
ajst-8015	50	20	vector	vector	NOUN
ajst-8015	50	21	.	.	PUNCT
ajst-8015	51	1	good	good	ADJ
ajst-8015	51	2	et	et	PROPN
ajst-8015	51	3	al	al	PROPN
ajst-8015	51	4	.	.	PUNCT
ajst-8015	52	1	[	[	X
ajst-8015	52	2	9]proposed	9]propose	VERB
ajst-8015	52	3	an	an	DET
ajst-8015	52	4	improved	improved	ADJ
ajst-8015	52	5	vbm	vbm	PROPN
ajst-8015	52	6	method	method	NOUN
ajst-8015	52	7	to	to	PART
ajst-8015	52	8	avoid	avoid	VERB
ajst-8015	52	9	the	the	DET
ajst-8015	52	10	interaction	interaction	NOUN
ajst-8015	52	11	between	between	ADP
ajst-8015	52	12	brain	brain	NOUN
ajst-8015	52	13	tissues	tissue	NOUN
ajst-8015	52	14	during	during	ADP
ajst-8015	52	15	spatial	spatial	ADJ
ajst-8015	52	16	standardization	standardization	NOUN
ajst-8015	52	17	.	.	PUNCT
ajst-8015	53	1	studies	study	NOUN
ajst-8015	53	2	have	have	AUX
ajst-8015	53	3	found	find	VERB
ajst-8015	53	4	that	that	SCONJ
ajst-8015	53	5	some	some	DET
ajst-8015	53	6	brain	brain	NOUN
ajst-8015	53	7	tissues	tissue	NOUN
ajst-8015	53	8	(	(	PUNCT
ajst-8015	53	9	such	such	ADJ
ajst-8015	53	10	as	as	ADP
ajst-8015	53	11	hippocampus	hippocampus	NOUN
ajst-8015	53	12	,	,	PUNCT
ajst-8015	53	13	temporal	temporal	ADJ
ajst-8015	53	14	lobe	lobe	NOUN
ajst-8015	53	15	,	,	PUNCT
ajst-8015	53	16	amygdala	amygdala	NOUN
ajst-8015	53	17	,	,	PUNCT
ajst-8015	53	18	etc	etc	X
ajst-8015	53	19	.	.	X
ajst-8015	53	20	)	)	PUNCT
ajst-8015	53	21	in	in	ADP
ajst-8015	53	22	patients	patient	NOUN
ajst-8015	53	23	with	with	ADP
ajst-8015	53	24	alzheimer	alzheimer	PROPN
ajst-8015	53	25	's	's	PART
ajst-8015	53	26	disease	disease	NOUN
ajst-8015	53	27	show	show	VERB
ajst-8015	53	28	a	a	DET
ajst-8015	53	29	certain	certain	ADJ
ajst-8015	53	30	degree	degree	NOUN
ajst-8015	53	31	of	of	ADP
ajst-8015	53	32	atrophy	atrophy	NOUN
ajst-8015	53	33	compared	compare	VERB
ajst-8015	53	34	with	with	ADP
ajst-8015	53	35	normal	normal	ADJ
ajst-8015	53	36	people	people	NOUN
ajst-8015	53	37	.	.	PUNCT
ajst-8015	54	1	roi	roi	NOUN
ajst-8015	54	2	-	-	PUNCT
ajst-8015	54	3	based	base	VERB
ajst-8015	54	4	method	method	NOUN
ajst-8015	54	5	classifies	classify	VERB
ajst-8015	54	6	by	by	ADP
ajst-8015	54	7	extracting	extract	VERB
ajst-8015	54	8	the	the	DET
ajst-8015	54	9	image	image	NOUN
ajst-8015	54	10	features	feature	NOUN
ajst-8015	54	11	of	of	ADP
ajst-8015	54	12	specific	specific	ADJ
ajst-8015	54	13	brain	brain	NOUN
ajst-8015	54	14	regions	region	NOUN
ajst-8015	54	15	,	,	PUNCT
ajst-8015	54	16	which	which	PRON
ajst-8015	54	17	can	can	AUX
ajst-8015	54	18	eliminate	eliminate	VERB
ajst-8015	54	19	the	the	DET
ajst-8015	54	20	interference	interference	NOUN
ajst-8015	54	21	of	of	ADP
ajst-8015	54	22	irrelevant	irrelevant	ADJ
ajst-8015	54	23	brain	brain	NOUN
ajst-8015	54	24	regions	region	NOUN
ajst-8015	54	25	and	and	CCONJ
ajst-8015	54	26	improve	improve	VERB
ajst-8015	54	27	the	the	DET
ajst-8015	54	28	classification	classification	NOUN
ajst-8015	54	29	effect	effect	NOUN
ajst-8015	54	30	.	.	PUNCT
ajst-8015	55	1	ortiz[10	ortiz[10	X
ajst-8015	55	2	]	]	PUNCT
ajst-8015	56	1	used	use	VERB
ajst-8015	56	2	voxel	voxel	PROPN
ajst-8015	56	3	preselection	preselection	NOUN
ajst-8015	56	4	to	to	PART
ajst-8015	56	5	select	select	VERB
ajst-8015	56	6	98	98	NUM
ajst-8015	56	7	rois	rois	NOUN
ajst-8015	56	8	from	from	ADP
ajst-8015	56	9	mri	mri	NOUN
ajst-8015	56	10	and	and	CCONJ
ajst-8015	56	11	pet	pet	ADJ
ajst-8015	56	12	data	datum	NOUN
ajst-8015	56	13	and	and	CCONJ
ajst-8015	56	14	designed	design	VERB
ajst-8015	56	15	a	a	DET
ajst-8015	56	16	depth	depth	NOUN
ajst-8015	56	17	model	model	NOUN
ajst-8015	56	18	for	for	ADP
ajst-8015	56	19	each	each	DET
ajst-8015	56	20	roi	roi	NOUN
ajst-8015	56	21	.	.	PUNCT
ajst-8015	57	1	wee	wee	PROPN
ajst-8015	57	2	et	et	PROPN
ajst-8015	57	3	al	al	PROPN
ajst-8015	57	4	.	.	PUNCT
ajst-8015	58	1	[	[	X
ajst-8015	58	2	11	11	NUM
ajst-8015	58	3	]	]	PUNCT
ajst-8015	58	4	built	build	VERB
ajst-8015	58	5	the	the	DET
ajst-8015	58	6	alarm	alarm	NOUN
ajst-8015	58	7	network	network	NOUN
ajst-8015	58	8	through	through	ADP
ajst-8015	58	9	the	the	DET
ajst-8015	58	10	correlation	correlation	NOUN
ajst-8015	58	11	between	between	ADP
ajst-8015	58	12	the	the	DET
ajst-8015	58	13	average	average	ADJ
ajst-8015	58	14	cortical	cortical	ADJ
ajst-8015	58	15	thickness	thickness	NOUN
ajst-8015	58	16	of	of	ADP
ajst-8015	58	17	roi	roi	NOUN
ajst-8015	58	18	,	,	PUNCT
ajst-8015	58	19	and	and	CCONJ
ajst-8015	58	20	adopted	adopt	VERB
ajst-8015	58	21	the	the	DET
ajst-8015	58	22	twosample	twosample	NOUN
ajst-8015	58	23	t	t	PROPN
ajst-8015	58	24	test	test	NOUN
ajst-8015	58	25	to	to	PART
ajst-8015	58	26	select	select	VERB
ajst-8015	58	27	brain	brain	NOUN
ajst-8015	58	28	connections	connection	NOUN
ajst-8015	58	29	with	with	ADP
ajst-8015	58	30	significant	significant	ADJ
ajst-8015	58	31	differences	difference	NOUN
ajst-8015	58	32	in	in	ADP
ajst-8015	58	33	the	the	DET
ajst-8015	58	34	brain	brain	NOUN
ajst-8015	58	35	network	network	NOUN
ajst-8015	58	36	,	,	PUNCT
ajst-8015	58	37	so	so	SCONJ
ajst-8015	58	38	as	as	SCONJ
ajst-8015	58	39	to	to	PART
ajst-8015	58	40	improve	improve	VERB
ajst-8015	58	41	the	the	DET
ajst-8015	58	42	accuracy	accuracy	NOUN
ajst-8015	58	43	of	of	ADP
ajst-8015	58	44	ad	ad	NOUN
ajst-8015	58	45	.	.	PUNCT
ajst-8015	59	1	cui	cui	NOUN
ajst-8015	59	2	et	et	PROPN
ajst-8015	59	3	al	al	PROPN
ajst-8015	59	4	.	.	PUNCT
ajst-8015	60	1	[	[	X
ajst-8015	60	2	12	12	NUM
ajst-8015	60	3	]	]	PUNCT
ajst-8015	60	4	proposed	propose	VERB
ajst-8015	60	5	a	a	DET
ajst-8015	60	6	hippocampal	hippocampal	ADJ
ajst-8015	60	7	analysis	analysis	NOUN
ajst-8015	60	8	method	method	NOUN
ajst-8015	60	9	for	for	ADP
ajst-8015	60	10	ad	ad	NOUN
ajst-8015	60	11	diagnosis	diagnosis	NOUN
ajst-8015	60	12	based	base	VERB
ajst-8015	60	13	on	on	ADP
ajst-8015	60	14	the	the	DET
ajst-8015	60	15	combination	combination	NOUN
ajst-8015	60	16	of	of	ADP
ajst-8015	60	17	3d	3d	NUM
ajst-8015	60	18	dense	dense	ADJ
ajst-8015	60	19	connected	connected	ADJ
ajst-8015	60	20	convolutional	convolutional	ADJ
ajst-8015	60	21	network	network	NOUN
ajst-8015	60	22	and	and	CCONJ
ajst-8015	60	23	traditional	traditional	ADJ
ajst-8015	60	24	manual	manual	ADJ
ajst-8015	60	25	features	feature	NOUN
ajst-8015	60	26	,	,	PUNCT
ajst-8015	60	27	which	which	PRON
ajst-8015	60	28	combines	combine	VERB
ajst-8015	60	29	multi	multi	ADJ
ajst-8015	60	30	-	-	ADJ
ajst-8015	60	31	level	level	ADJ
ajst-8015	60	32	and	and	CCONJ
ajst-8015	60	33	multi	multi	ADJ
ajst-8015	60	34	-	-	ADJ
ajst-8015	60	35	type	type	ADJ
ajst-8015	60	36	features	feature	NOUN
ajst-8015	60	37	to	to	PART
ajst-8015	60	38	improve	improve	VERB
ajst-8015	60	39	the	the	DET
ajst-8015	60	40	accuracy	accuracy	NOUN
ajst-8015	60	41	of	of	ADP
ajst-8015	60	42	disease	disease	NOUN
ajst-8015	60	43	classification	classification	NOUN
ajst-8015	60	44	.	.	PUNCT
ajst-8015	61	1	li	li	PROPN
ajst-8015	61	2	et	et	PROPN
ajst-8015	61	3	al	al	PROPN
ajst-8015	61	4	.	.	PUNCT
ajst-8015	62	1	[	[	X
ajst-8015	62	2	13	13	NUM
ajst-8015	62	3	]	]	PUNCT
ajst-8015	62	4	combined	combine	VERB
ajst-8015	62	5	convolutional	convolutional	ADJ
ajst-8015	62	6	neural	neural	ADJ
ajst-8015	62	7	network	network	NOUN
ajst-8015	62	8	(	(	PUNCT
ajst-8015	62	9	cnn	cnn	PROPN
ajst-8015	62	10	)	)	PUNCT
ajst-8015	62	11	and	and	CCONJ
ajst-8015	62	12	recursive	recursive	ADJ
ajst-8015	62	13	neural	neural	ADJ
ajst-8015	62	14	network	network	NOUN
ajst-8015	62	15	(	(	PUNCT
ajst-8015	62	16	rnn	rnn	PROPN
ajst-8015	62	17	)	)	PUNCT
ajst-8015	62	18	to	to	PART
ajst-8015	62	19	cascade	cascade	VERB
ajst-8015	62	20	the	the	DET
ajst-8015	62	21	rnn	rnn	NOUN
ajst-8015	62	22	to	to	ADP
ajst-8015	62	23	the	the	DET
ajst-8015	62	24	density	density	NOUN
ajst-8015	62	25	and	and	CCONJ
ajst-8015	62	26	shape	shape	NOUN
ajst-8015	62	27	features	feature	NOUN
ajst-8015	62	28	of	of	ADP
ajst-8015	62	29	bilateral	bilateral	ADJ
ajst-8015	62	30	hippocampus	hippocampus	NOUN
ajst-8015	62	31	extracted	extract	VERB
ajst-8015	62	32	by	by	ADP
ajst-8015	62	33	cnn	cnn	PROPN
ajst-8015	62	34	,	,	PUNCT
ajst-8015	62	35	so	so	SCONJ
ajst-8015	62	36	as	as	SCONJ
ajst-8015	62	37	to	to	PART
ajst-8015	62	38	learn	learn	VERB
ajst-8015	62	39	high	high	ADJ
ajst-8015	62	40	-	-	PUNCT
ajst-8015	62	41	level	level	NOUN
ajst-8015	62	42	relevant	relevant	ADJ
ajst-8015	62	43	features	feature	NOUN
ajst-8015	62	44	for	for	ADP
ajst-8015	62	45	ad	ad	NOUN
ajst-8015	62	46	classification	classification	NOUN
ajst-8015	62	47	.	.	PUNCT
ajst-8015	63	1	roi	roi	NOUN
ajst-8015	63	2	methods	method	NOUN
ajst-8015	63	3	extract	extract	VERB
ajst-8015	63	4	very	very	ADV
ajst-8015	63	5	crude	crude	ADJ
ajst-8015	63	6	features	feature	NOUN
ajst-8015	63	7	and	and	CCONJ
ajst-8015	63	8	may	may	AUX
ajst-8015	63	9	miss	miss	VERB
ajst-8015	63	10	some	some	DET
ajst-8015	63	11	subtle	subtle	ADJ
ajst-8015	63	12	brain	brain	NOUN
ajst-8015	63	13	tissue	tissue	NOUN
ajst-8015	63	14	changes	change	NOUN
ajst-8015	63	15	.	.	PUNCT
ajst-8015	64	1	therefore	therefore	ADV
ajst-8015	64	2	,	,	PUNCT
ajst-8015	64	3	liu	liu	PROPN
ajst-8015	64	4	et	et	PROPN
ajst-8015	64	5	al	al	PROPN
ajst-8015	64	6	.	.	PUNCT
ajst-8015	65	1	[	[	X
ajst-8015	65	2	14	14	NUM
ajst-8015	65	3	]	]	PUNCT
ajst-8015	65	4	proposed	propose	VERB
ajst-8015	65	5	a	a	DET
ajst-8015	65	6	feature	feature	NOUN
ajst-8015	65	7	extraction	extraction	NOUN
ajst-8015	65	8	method	method	NOUN
ajst-8015	65	9	based	base	VERB
ajst-8015	65	10	on	on	ADP
ajst-8015	65	11	structural	structural	ADJ
ajst-8015	65	12	blocks	block	NOUN
ajst-8015	65	13	.	.	PUNCT
ajst-8015	66	1	the	the	DET
ajst-8015	66	2	method	method	NOUN
ajst-8015	66	3	based	base	VERB
ajst-8015	66	4	on	on	ADP
ajst-8015	66	5	structural	structural	ADJ
ajst-8015	66	6	blocks	block	NOUN
ajst-8015	66	7	can	can	AUX
ajst-8015	66	8	capture	capture	VERB
ajst-8015	66	9	the	the	DET
ajst-8015	66	10	patterns	pattern	NOUN
ajst-8015	66	11	related	relate	VERB
ajst-8015	66	12	to	to	ADP
ajst-8015	66	13	disease	disease	NOUN
ajst-8015	66	14	in	in	ADP
ajst-8015	66	15	the	the	DET
ajst-8015	66	16	brain	brain	NOUN
ajst-8015	66	17	by	by	ADP
ajst-8015	66	18	extracting	extract	VERB
ajst-8015	66	19	features	feature	NOUN
ajst-8015	66	20	from	from	ADP
ajst-8015	66	21	small	small	ADJ
ajst-8015	66	22	three	three	NUM
ajst-8015	66	23	-	-	PUNCT
ajst-8015	66	24	dimensional	dimensional	ADJ
ajst-8015	66	25	image	image	NOUN
ajst-8015	66	26	blocks	block	NOUN
ajst-8015	66	27	,	,	PUNCT
ajst-8015	66	28	which	which	PRON
ajst-8015	66	29	can	can	AUX
ajst-8015	66	30	not	not	PART
ajst-8015	66	31	only	only	ADV
ajst-8015	66	32	consider	consider	VERB
ajst-8015	66	33	the	the	DET
ajst-8015	66	34	slight	slight	ADJ
ajst-8015	66	35	changes	change	NOUN
ajst-8015	66	36	in	in	ADP
ajst-8015	66	37	brain	brain	NOUN
ajst-8015	66	38	tissue	tissue	NOUN
ajst-8015	66	39	but	but	CCONJ
ajst-8015	66	40	also	also	ADV
ajst-8015	66	41	reduce	reduce	VERB
ajst-8015	66	42	the	the	DET
ajst-8015	66	43	feature	feature	NOUN
ajst-8015	66	44	dimension	dimension	NOUN
ajst-8015	66	45	,	,	PUNCT
ajst-8015	66	46	so	so	SCONJ
ajst-8015	66	47	as	as	SCONJ
ajst-8015	66	48	to	to	PART
ajst-8015	66	49	avoid	avoid	VERB
ajst-8015	66	50	overfitting	overfitte	VERB
ajst-8015	66	51	.	.	PUNCT
ajst-8015	67	1	liu[15	liu[15	PROPN
ajst-8015	67	2	]	]	PUNCT
ajst-8015	67	3	proposed	propose	VERB
ajst-8015	67	4	a	a	DET
ajst-8015	67	5	hierarchical	hierarchical	ADJ
ajst-8015	67	6	integration	integration	NOUN
ajst-8015	67	7	classification	classification	NOUN
ajst-8015	67	8	method	method	NOUN
ajst-8015	67	9	.	.	PUNCT
ajst-8015	68	1	firstly	firstly	ADV
ajst-8015	68	2	,	,	PUNCT
ajst-8015	68	3	different	different	ADJ
ajst-8015	68	4	low	low	ADJ
ajst-8015	68	5	-	-	PUNCT
ajst-8015	68	6	level	level	NOUN
ajst-8015	68	7	classifiers	classifier	NOUN
ajst-8015	68	8	were	be	AUX
ajst-8015	68	9	constructed	construct	VERB
ajst-8015	68	10	by	by	ADP
ajst-8015	68	11	using	use	VERB
ajst-8015	68	12	the	the	DET
ajst-8015	68	13	imaging	imaging	NOUN
ajst-8015	68	14	of	of	ADP
ajst-8015	68	15	local	local	ADJ
ajst-8015	68	16	brain	brain	NOUN
ajst-8015	68	17	blocks	block	NOUN
ajst-8015	68	18	and	and	CCONJ
ajst-8015	68	19	the	the	DET
ajst-8015	68	20	spatial	spatial	ADJ
ajst-8015	68	21	correlation	correlation	NOUN
ajst-8015	68	22	features	feature	VERB
ajst-8015	68	23	between	between	ADP
ajst-8015	68	24	blocks	block	NOUN
ajst-8015	68	25	,	,	PUNCT
ajst-8015	68	26	and	and	CCONJ
ajst-8015	68	27	then	then	ADV
ajst-8015	68	28	the	the	DET
ajst-8015	68	29	output	output	NOUN
ajst-8015	68	30	of	of	ADP
ajst-8015	68	31	low	low	ADJ
ajst-8015	68	32	-	-	PUNCT
ajst-8015	68	33	level	level	NOUN
ajst-8015	68	34	classifiers	classifier	NOUN
ajst-8015	68	35	and	and	CCONJ
ajst-8015	68	36	the	the	DET
ajst-8015	68	37	statistical	statistical	ADJ
ajst-8015	68	38	features	feature	NOUN
ajst-8015	68	39	of	of	ADP
ajst-8015	68	40	voxels	voxel	NOUN
ajst-8015	68	41	in	in	ADP
ajst-8015	68	42	each	each	DET
ajst-8015	68	43	local	local	ADJ
ajst-8015	68	44	block	block	NOUN
ajst-8015	68	45	were	be	AUX
ajst-8015	68	46	integrated	integrate	VERB
ajst-8015	68	47	into	into	ADP
ajst-8015	68	48	a	a	DET
ajst-8015	68	49	feature	feature	NOUN
ajst-8015	68	50	vector	vector	NOUN
ajst-8015	68	51	to	to	PART
ajst-8015	68	52	construct	construct	VERB
ajst-8015	68	53	a	a	DET
ajst-8015	68	54	high	high	ADJ
ajst-8015	68	55	-	-	PUNCT
ajst-8015	68	56	level	level	NOUN
ajst-8015	68	57	classifier	classifier	NOUN
ajst-8015	68	58	for	for	ADP
ajst-8015	68	59	classification	classification	NOUN
ajst-8015	68	60	.	.	PUNCT
ajst-8015	69	1	li	li	PROPN
ajst-8015	69	2	et	et	PROPN
ajst-8015	69	3	al	al	PROPN
ajst-8015	69	4	.	.	PUNCT
ajst-8015	70	1	[	[	X
ajst-8015	70	2	16	16	NUM
ajst-8015	70	3	]	]	PUNCT
ajst-8015	70	4	evenly	evenly	ADV
ajst-8015	70	5	divided	divide	VERB
ajst-8015	70	6	mri	mri	NOUN
ajst-8015	70	7	images	image	NOUN
ajst-8015	70	8	into	into	ADP
ajst-8015	70	9	local	local	ADJ
ajst-8015	70	10	regions	region	NOUN
ajst-8015	70	11	of	of	ADP
ajst-8015	70	12	the	the	DET
ajst-8015	70	13	same	same	ADJ
ajst-8015	70	14	size	size	NOUN
ajst-8015	70	15	,	,	PUNCT
ajst-8015	70	16	extracted	extract	VERB
ajst-8015	70	17	several	several	ADJ
ajst-8015	70	18	3d	3d	NUM
ajst-8015	70	19	blocks	block	NOUN
ajst-8015	70	20	from	from	ADP
ajst-8015	70	21	each	each	DET
ajst-8015	70	22	region	region	NOUN
ajst-8015	70	23	,	,	PUNCT
ajst-8015	70	24	and	and	CCONJ
ajst-8015	70	25	then	then	ADV
ajst-8015	70	26	used	use	VERB
ajst-8015	70	27	k	k	PROPN
ajst-8015	70	28	-	-	PUNCT
ajst-8015	70	29	means	mean	VERB
ajst-8015	70	30	clustering	cluster	VERB
ajst-8015	70	31	algorithm	algorithm	NOUN
ajst-8015	70	32	to	to	PART
ajst-8015	70	33	divide	divide	VERB
ajst-8015	70	34	the	the	DET
ajst-8015	70	35	blocks	block	NOUN
ajst-8015	70	36	in	in	ADP
ajst-8015	70	37	each	each	DET
ajst-8015	70	38	region	region	NOUN
ajst-8015	70	39	into	into	ADP
ajst-8015	70	40	different	different	ADJ
ajst-8015	70	41	groups	group	NOUN
ajst-8015	70	42	for	for	ADP
ajst-8015	70	43	final	final	ADJ
ajst-8015	70	44	classification	classification	NOUN
ajst-8015	70	45	.	.	PUNCT
ajst-8015	71	1	liu[17	liu[17	PROPN
ajst-8015	71	2	]	]	PUNCT
ajst-8015	71	3	integrated	integrate	VERB
ajst-8015	71	4	image	image	NOUN
ajst-8015	71	5	blocks	block	NOUN
ajst-8015	71	6	and	and	CCONJ
ajst-8015	71	7	more	more	ADJ
ajst-8015	71	8	prior	prior	ADJ
ajst-8015	71	9	information	information	NOUN
ajst-8015	71	10	of	of	ADP
ajst-8015	71	11	subjects	subject	NOUN
ajst-8015	71	12	(	(	PUNCT
ajst-8015	71	13	age	age	NOUN
ajst-8015	71	14	,	,	PUNCT
ajst-8015	71	15	gender	gender	NOUN
ajst-8015	71	16	,	,	PUNCT
ajst-8015	71	17	education	education	NOUN
ajst-8015	71	18	level	level	NOUN
ajst-8015	71	19	)	)	PUNCT
ajst-8015	71	20	into	into	ADP
ajst-8015	71	21	the	the	DET
ajst-8015	71	22	learning	learning	NOUN
ajst-8015	71	23	model	model	NOUN
ajst-8015	71	24	,	,	PUNCT
ajst-8015	71	25	and	and	CCONJ
ajst-8015	71	26	proposed	propose	VERB
ajst-8015	71	27	an	an	DET
ajst-8015	71	28	ad	ad	NOUN
ajst-8015	71	29	classification	classification	NOUN
ajst-8015	71	30	regression	regression	NOUN
ajst-8015	71	31	framework	framework	NOUN
ajst-8015	71	32	based	base	VERB
ajst-8015	71	33	on	on	ADP
ajst-8015	71	34	deep	deep	ADJ
ajst-8015	71	35	multi	multi	NOUN
ajst-8015	71	36	-	-	NOUN
ajst-8015	71	37	task	task	ADJ
ajst-8015	71	38	and	and	CCONJ
ajst-8015	71	39	multi	multi	ADJ
ajst-8015	71	40	-	-	ADJ
ajst-8015	71	41	channel	channel	ADJ
ajst-8015	71	42	learning	learning	NOUN
ajst-8015	71	43	.	.	PUNCT
ajst-8015	72	1	ahmed	ahmed	PROPN
ajst-8015	72	2	et	et	PROPN
ajst-8015	72	3	al	al	PROPN
ajst-8015	72	4	.	.	PUNCT
ajst-8015	73	1	[	[	X
ajst-8015	73	2	18	18	NUM
ajst-8015	73	3	]	]	PUNCT
ajst-8015	73	4	proposed	propose	VERB
ajst-8015	73	5	an	an	DET
ajst-8015	73	6	ad	ad	NOUN
ajst-8015	73	7	diagnosis	diagnosis	NOUN
ajst-8015	73	8	algorithm	algorithm	NOUN
ajst-8015	73	9	based	base	VERB
ajst-8015	73	10	on	on	ADP
ajst-8015	73	11	block	block	NOUN
ajst-8015	73	12	classifier	classifier	NOUN
ajst-8015	73	13	integration	integration	NOUN
ajst-8015	73	14	.	.	PUNCT
ajst-8015	74	1	firstly	firstly	ADV
ajst-8015	74	2	,	,	PUNCT
ajst-8015	74	3	bilateral	bilateral	ADJ
ajst-8015	74	4	hippocampal	hippocampal	ADJ
ajst-8015	74	5	regions	region	NOUN
ajst-8015	74	6	were	be	AUX
ajst-8015	74	7	extracted	extract	VERB
ajst-8015	74	8	in	in	ADP
ajst-8015	74	9	the	the	DET
ajst-8015	74	10	form	form	NOUN
ajst-8015	74	11	of	of	ADP
ajst-8015	74	12	blocks	block	NOUN
ajst-8015	74	13	,	,	PUNCT
ajst-8015	74	14	then	then	ADV
ajst-8015	74	15	different	different	ADJ
ajst-8015	74	16	block	block	NOUN
ajst-8015	74	17	classifier	classifier	NOUN
ajst-8015	74	18	models	model	NOUN
ajst-8015	74	19	were	be	AUX
ajst-8015	74	20	established	establish	VERB
ajst-8015	74	21	based	base	VERB
ajst-8015	74	22	on	on	ADP
ajst-8015	74	23	the	the	DET
ajst-8015	74	24	left	left	ADJ
ajst-8015	74	25	,	,	PUNCT
ajst-8015	74	26	right	right	ADJ
ajst-8015	74	27	and	and	CCONJ
ajst-8015	74	28	bilateral	bilateral	ADJ
ajst-8015	74	29	hippocampi	hippocampi	ADJ
ajst-8015	74	30	respectively	respectively	ADV
ajst-8015	74	31	,	,	PUNCT
ajst-8015	74	32	and	and	CCONJ
ajst-8015	74	33	finally	finally	ADV
ajst-8015	74	34	,	,	PUNCT
ajst-8015	74	35	the	the	DET
ajst-8015	74	36	weighted	weighted	ADJ
ajst-8015	74	37	majority	majority	NOUN
ajst-8015	74	38	voting	voting	NOUN
ajst-8015	74	39	method	method	NOUN
ajst-8015	74	40	was	be	AUX
ajst-8015	74	41	used	use	VERB
ajst-8015	74	42	to	to	PART
ajst-8015	74	43	complete	complete	VERB
ajst-8015	74	44	ad	ad	NOUN
ajst-8015	74	45	diagnosis	diagnosis	NOUN
ajst-8015	74	46	.	.	PUNCT
ajst-8015	75	1	the	the	DET
ajst-8015	75	2	section	section	NOUN
ajst-8015	75	3	-	-	PUNCT
ajst-8015	75	4	based	base	VERB
ajst-8015	75	5	method	method	NOUN
ajst-8015	75	6	extracts	extract	VERB
ajst-8015	75	7	two	two	NUM
ajst-8015	75	8	-	-	PUNCT
ajst-8015	75	9	dimensional	dimensional	ADJ
ajst-8015	75	10	slices	slice	NOUN
ajst-8015	75	11	from	from	ADP
ajst-8015	75	12	a	a	DET
ajst-8015	75	13	plane	plane	NOUN
ajst-8015	75	14	of	of	ADP
ajst-8015	75	15	mri	mri	NOUN
ajst-8015	75	16	image	image	NOUN
ajst-8015	75	17	as	as	ADP
ajst-8015	75	18	input	input	NOUN
ajst-8015	75	19	to	to	PART
ajst-8015	75	20	reduce	reduce	VERB
ajst-8015	75	21	the	the	DET
ajst-8015	75	22	number	number	NOUN
ajst-8015	75	23	of	of	ADP
ajst-8015	75	24	hyperparameters	hyperparameter	NOUN
ajst-8015	75	25	.	.	PUNCT
ajst-8015	76	1	islam	islam	PROPN
ajst-8015	76	2	et	et	PROPN
ajst-8015	76	3	al	al	PROPN
ajst-8015	76	4	.	.	PUNCT
ajst-8015	77	1	[	[	X
ajst-8015	77	2	19	19	NUM
ajst-8015	77	3	]	]	PUNCT
ajst-8015	77	4	,	,	PUNCT
ajst-8015	77	5	under	under	ADP
ajst-8015	77	6	the	the	DET
ajst-8015	77	7	guidance	guidance	NOUN
ajst-8015	77	8	of	of	ADP
ajst-8015	77	9	neuroexperts	neuroexpert	NOUN
ajst-8015	77	10	,	,	PUNCT
ajst-8015	77	11	selected	select	VERB
ajst-8015	77	12	the	the	DET
ajst-8015	77	13	largest	large	ADJ
ajst-8015	77	14	50	50	NUM
ajst-8015	77	15	sections	section	NOUN
ajst-8015	77	16	of	of	ADP
ajst-8015	77	17	intracranial	intracranial	ADJ
ajst-8015	77	18	part	part	NOUN
ajst-8015	77	19	from	from	ADP
ajst-8015	77	20	mri	mri	NOUN
ajst-8015	77	21	of	of	ADP
ajst-8015	77	22	each	each	DET
ajst-8015	77	23	subject	subject	NOUN
ajst-8015	77	24	and	and	CCONJ
ajst-8015	77	25	classified	classify	VERB
ajst-8015	77	26	them	they	PRON
ajst-8015	77	27	using	use	VERB
ajst-8015	77	28	cnn	cnn	PROPN
ajst-8015	77	29	.	.	PUNCT
ajst-8015	78	1	luo	luo	PROPN
ajst-8015	78	2	et	et	PROPN
ajst-8015	78	3	al	al	PROPN
ajst-8015	78	4	.	.	PUNCT
ajst-8015	79	1	[	[	X
ajst-8015	79	2	20	20	NUM
ajst-8015	79	3	]	]	PUNCT
ajst-8015	79	4	extracted	extract	VERB
ajst-8015	79	5	seven	seven	NUM
ajst-8015	79	6	groups	group	NOUN
ajst-8015	79	7	of	of	ADP
ajst-8015	79	8	sections	section	NOUN
ajst-8015	79	9	(	(	PUNCT
ajst-8015	79	10	five	five	NUM
ajst-8015	79	11	in	in	ADP
ajst-8015	79	12	each	each	DET
ajst-8015	79	13	group	group	NOUN
ajst-8015	79	14	)	)	PUNCT
ajst-8015	79	15	from	from	ADP
ajst-8015	79	16	the	the	DET
ajst-8015	79	17	axial	axial	ADJ
ajst-8015	79	18	plane	plane	NOUN
ajst-8015	79	19	of	of	ADP
ajst-8015	79	20	mri	mri	NOUN
ajst-8015	79	21	images	image	NOUN
ajst-8015	79	22	,	,	PUNCT
ajst-8015	79	23	and	and	CCONJ
ajst-8015	79	24	each	each	DET
ajst-8015	79	25	group	group	NOUN
ajst-8015	79	26	was	be	AUX
ajst-8015	79	27	classified	classify	VERB
ajst-8015	79	28	by	by	ADP
ajst-8015	79	29	a	a	DET
ajst-8015	79	30	classifier	classifier	NOUN
ajst-8015	79	31	.	.	PUNCT
ajst-8015	80	1	wu	wu	PROPN
ajst-8015	80	2	et	et	PROPN
ajst-8015	80	3	al	al	PROPN
ajst-8015	80	4	.	.	PUNCT
ajst-8015	81	1	[	[	X
ajst-8015	81	2	21]combined	21]combined	NUM
ajst-8015	81	3	three	three	NUM
ajst-8015	81	4	axial	axial	ADJ
ajst-8015	81	5	plane	plane	NOUN
ajst-8015	81	6	slices	slice	NOUN
ajst-8015	81	7	into	into	ADP
ajst-8015	81	8	one	one	NUM
ajst-8015	81	9	rgb	rgb	PROPN
ajst-8015	81	10	color	color	NOUN
ajst-8015	81	11	image	image	NOUN
ajst-8015	81	12	,	,	PUNCT
ajst-8015	81	13	and	and	CCONJ
ajst-8015	81	14	finally	finally	ADV
ajst-8015	81	15	obtained	obtain	VERB
ajst-8015	81	16	16	16	NUM
ajst-8015	81	17	rgb	rgb	PROPN
ajst-8015	81	18	color	color	NOUN
ajst-8015	81	19	images	image	NOUN
ajst-8015	81	20	from	from	ADP
ajst-8015	81	21	each	each	DET
ajst-8015	81	22	mri	mri	NOUN
ajst-8015	81	23	image	image	NOUN
ajst-8015	81	24	.	.	PUNCT
ajst-8015	82	1	gao	gao	PROPN
ajst-8015	82	2	et	et	PROPN
ajst-8015	82	3	al	al	PROPN
ajst-8015	82	4	.	.	PUNCT
ajst-8015	83	1	[	[	X
ajst-8015	83	2	22	22	NUM
ajst-8015	83	3	]	]	PUNCT
ajst-8015	83	4	selected	select	VERB
ajst-8015	83	5	50	50	NUM
ajst-8015	83	6	largest	large	ADJ
ajst-8015	83	7	sagittal	sagittal	ADJ
ajst-8015	83	8	plane	plane	NOUN
ajst-8015	83	9	sections	section	NOUN
ajst-8015	83	10	from	from	ADP
ajst-8015	83	11	mri	mri	NOUN
ajst-8015	83	12	images	image	NOUN
ajst-8015	83	13	,	,	PUNCT
ajst-8015	83	14	and	and	CCONJ
ajst-8015	83	15	then	then	ADV
ajst-8015	83	16	used	use	VERB
ajst-8015	83	17	cnn	cnn	PROPN
ajst-8015	83	18	to	to	PART
ajst-8015	83	19	extract	extract	VERB
ajst-8015	83	20	longitudinal	longitudinal	ADJ
ajst-8015	83	21	features	feature	NOUN
ajst-8015	83	22	to	to	PART
ajst-8015	83	23	complete	complete	VERB
ajst-8015	83	24	the	the	DET
ajst-8015	83	25	classification	classification	NOUN
ajst-8015	83	26	.	.	PUNCT
ajst-8015	84	1	jian	jian	PROPN
ajst-8015	84	2	et	et	PROPN
ajst-8015	84	3	al	al	PROPN
ajst-8015	84	4	.	.	PUNCT
ajst-8015	85	1	[	[	X
ajst-8015	85	2	23	23	NUM
ajst-8015	85	3	]	]	PUNCT
ajst-8015	85	4	calculated	calculate	VERB
ajst-8015	85	5	the	the	DET
ajst-8015	85	6	image	image	NOUN
ajst-8015	85	7	entropy	entropy	NOUN
ajst-8015	85	8	of	of	ADP
ajst-8015	85	9	axial	axial	ADJ
ajst-8015	85	10	slices	slice	NOUN
ajst-8015	85	11	by	by	ADP
ajst-8015	85	12	using	use	VERB
ajst-8015	85	13	histograms	histogram	NOUN
ajst-8015	85	14	and	and	CCONJ
ajst-8015	85	15	selected	select	VERB
ajst-8015	85	16	32	32	NUM
ajst-8015	85	17	slices	slice	NOUN
ajst-8015	85	18	with	with	ADP
ajst-8015	85	19	the	the	DET
ajst-8015	85	20	most	most	ADJ
ajst-8015	85	21	information	information	NOUN
ajst-8015	85	22	,	,	PUNCT
ajst-8015	85	23	which	which	PRON
ajst-8015	85	24	were	be	AUX
ajst-8015	85	25	then	then	ADV
ajst-8015	85	26	classified	classify	VERB
ajst-8015	85	27	by	by	ADP
ajst-8015	85	28	cnn	cnn	PROPN
ajst-8015	85	29	.	.	PUNCT
ajst-8015	86	1	the	the	DET
ajst-8015	86	2	whole	whole	ADJ
ajst-8015	86	3	mri	mri	NOUN
ajst-8015	86	4	image	image	NOUN
ajst-8015	86	5	is	be	AUX
ajst-8015	86	6	used	use	VERB
ajst-8015	86	7	as	as	ADP
ajst-8015	86	8	the	the	DET
ajst-8015	86	9	model	model	NOUN
ajst-8015	86	10	input	input	NOUN
ajst-8015	86	11	in	in	ADP
ajst-8015	86	12	the	the	DET
ajst-8015	86	13	global	global	ADJ
ajst-8015	86	14	image	image	NOUN
ajst-8015	86	15	-	-	PUNCT
ajst-8015	86	16	based	base	VERB
ajst-8015	86	17	method	method	NOUN
ajst-8015	86	18	,	,	PUNCT
ajst-8015	86	19	which	which	PRON
ajst-8015	86	20	can	can	AUX
ajst-8015	86	21	fully	fully	ADV
ajst-8015	86	22	utilize	utilize	VERB
ajst-8015	86	23	the	the	DET
ajst-8015	86	24	spatial	spatial	ADJ
ajst-8015	86	25	information	information	NOUN
ajst-8015	86	26	of	of	ADP
ajst-8015	86	27	the	the	DET
ajst-8015	86	28	image	image	NOUN
ajst-8015	86	29	without	without	ADP
ajst-8015	86	30	manual	manual	ADJ
ajst-8015	86	31	feature	feature	NOUN
ajst-8015	86	32	extraction	extraction	NOUN
ajst-8015	86	33	.	.	PUNCT
ajst-8015	87	1	korolev	korolev	NOUN
ajst-8015	87	2	et	et	PROPN
ajst-8015	87	3	al	al	PROPN
ajst-8015	87	4	.	.	PUNCT
ajst-8015	88	1	[	[	X
ajst-8015	88	2	24	24	NUM
ajst-8015	88	3	]	]	PUNCT
ajst-8015	88	4	,	,	PUNCT
ajst-8015	88	5	backstrom	backstrom	PROPN
ajst-8015	88	6	et	et	PROPN
ajst-8015	88	7	al	al	PROPN
ajst-8015	88	8	.	.	PUNCT
ajst-8015	89	1	[	[	X
ajst-8015	89	2	25	25	NUM
ajst-8015	89	3	]	]	PUNCT
ajst-8015	89	4	,	,	PUNCT
ajst-8015	89	5	basaia	basaia	PROPN
ajst-8015	89	6	et	et	PROPN
ajst-8015	89	7	al	al	PROPN
ajst-8015	89	8	.	.	PUNCT
ajst-8015	90	1	[	[	X
ajst-8015	90	2	26	26	NUM
ajst-8015	90	3	]	]	PUNCT
ajst-8015	90	4	input	input	NOUN
ajst-8015	90	5	pre	pre	ADJ
ajst-8015	90	6	-	-	ADJ
ajst-8015	90	7	processed	processed	ADJ
ajst-8015	90	8	whole	whole	ADJ
ajst-8015	90	9	brain	brain	NOUN
ajst-8015	90	10	mri	mri	NOUN
ajst-8015	90	11	images	image	NOUN
ajst-8015	90	12	into	into	ADP
ajst-8015	90	13	3d	3d	ADJ
ajst-8015	90	14	convolutional	convolutional	ADJ
ajst-8015	90	15	neural	neural	ADJ
ajst-8015	90	16	network	network	NOUN
ajst-8015	90	17	structure	structure	NOUN
ajst-8015	90	18	for	for	ADP
ajst-8015	90	19	ad	ad	NOUN
ajst-8015	90	20	classification	classification	NOUN
ajst-8015	90	21	.	.	PUNCT
ajst-8015	91	1	wang	wang	PROPN
ajst-8015	91	2	et	et	PROPN
ajst-8015	91	3	al	al	PROPN
ajst-8015	91	4	.	.	PUNCT
ajst-8015	92	1	[	[	X
ajst-8015	92	2	27	27	NUM
ajst-8015	92	3	]	]	PUNCT
ajst-8015	92	4	proposed	propose	VERB
ajst-8015	92	5	a	a	DET
ajst-8015	92	6	probability	probability	NOUN
ajst-8015	92	7	-	-	PUNCT
ajst-8015	92	8	based	base	VERB
ajst-8015	92	9	fusion	fusion	NOUN
ajst-8015	92	10	method	method	NOUN
ajst-8015	92	11	for	for	ADP
ajst-8015	92	12	the	the	DET
ajst-8015	92	13	fusion	fusion	NOUN
ajst-8015	92	14	of	of	ADP
ajst-8015	92	15	three	three	NUM
ajst-8015	92	16	-	-	PUNCT
ajst-8015	92	17	dimensional	dimensional	ADJ
ajst-8015	92	18	dense	dense	ADJ
ajst-8015	92	19	connected	connected	ADJ
ajst-8015	92	20	networks	network	NOUN
ajst-8015	92	21	with	with	ADP
ajst-8015	92	22	different	different	ADJ
ajst-8015	92	23	structures	structure	NOUN
ajst-8015	92	24	to	to	PART
ajst-8015	92	25	diagnose	diagnose	VERB
ajst-8015	92	26	ad	ad	NOUN
ajst-8015	92	27	.	.	PUNCT
ajst-8015	93	1	2.1.2	2.1.2	X
ajst-8015	93	2	.	.	NOUN
ajst-8015	93	3	feature	feature	NOUN
ajst-8015	93	4	selection	selection	NOUN
ajst-8015	93	5	and	and	CCONJ
ajst-8015	93	6	dimension	dimension	NOUN
ajst-8015	93	7	reduction	reduction	NOUN
ajst-8015	93	8	data	datum	NOUN
ajst-8015	93	9	dimensionality	dimensionality	NOUN
ajst-8015	93	10	reduction	reduction	NOUN
ajst-8015	93	11	refers	refer	VERB
ajst-8015	93	12	to	to	ADP
ajst-8015	93	13	the	the	DET
ajst-8015	93	14	operation	operation	NOUN
ajst-8015	93	15	of	of	ADP
ajst-8015	93	16	converting	convert	VERB
ajst-8015	93	17	data	datum	NOUN
ajst-8015	93	18	points	point	NOUN
ajst-8015	93	19	in	in	ADP
ajst-8015	93	20	a	a	DET
ajst-8015	93	21	higher	higher	ADV
ajst-8015	93	22	-	-	PUNCT
ajst-8015	93	23	dimensional	dimensional	ADJ
ajst-8015	93	24	space	space	NOUN
ajst-8015	93	25	into	into	ADP
ajst-8015	93	26	a	a	DET
ajst-8015	93	27	217	217	NUM
ajst-8015	93	28	lower	lower	ADV
ajst-8015	93	29	-	-	PUNCT
ajst-8015	93	30	dimensional	dimensional	ADJ
ajst-8015	93	31	space	space	NOUN
ajst-8015	93	32	by	by	ADP
ajst-8015	93	33	using	use	VERB
ajst-8015	93	34	some	some	DET
ajst-8015	93	35	kind	kind	NOUN
ajst-8015	93	36	of	of	ADP
ajst-8015	93	37	mapping	mapping	NOUN
ajst-8015	93	38	.	.	PUNCT
ajst-8015	94	1	in	in	ADP
ajst-8015	94	2	order	order	NOUN
ajst-8015	94	3	to	to	PART
ajst-8015	94	4	ensure	ensure	VERB
ajst-8015	94	5	that	that	SCONJ
ajst-8015	94	6	the	the	DET
ajst-8015	94	7	amount	amount	NOUN
ajst-8015	94	8	of	of	ADP
ajst-8015	94	9	data	datum	NOUN
ajst-8015	94	10	is	be	AUX
ajst-8015	94	11	not	not	PART
ajst-8015	94	12	reduced	reduce	VERB
ajst-8015	94	13	,	,	PUNCT
ajst-8015	94	14	the	the	DET
ajst-8015	94	15	redundant	redundant	ADJ
ajst-8015	94	16	information	information	NOUN
ajst-8015	94	17	in	in	ADP
ajst-8015	94	18	the	the	DET
ajst-8015	94	19	original	original	ADJ
ajst-8015	94	20	data	datum	NOUN
ajst-8015	94	21	is	be	AUX
ajst-8015	94	22	removed	remove	VERB
ajst-8015	94	23	,	,	PUNCT
ajst-8015	94	24	so	so	SCONJ
ajst-8015	94	25	as	as	SCONJ
ajst-8015	94	26	to	to	PART
ajst-8015	94	27	improve	improve	VERB
ajst-8015	94	28	the	the	DET
ajst-8015	94	29	accuracy	accuracy	NOUN
ajst-8015	94	30	of	of	ADP
ajst-8015	94	31	recognition	recognition	NOUN
ajst-8015	94	32	.	.	PUNCT
ajst-8015	95	1	mainstream	mainstream	ADJ
ajst-8015	95	2	dimensionality	dimensionality	NOUN
ajst-8015	95	3	reduction	reduction	NOUN
ajst-8015	95	4	methods	method	NOUN
ajst-8015	95	5	include	include	VERB
ajst-8015	95	6	principal	principal	ADJ
ajst-8015	95	7	component	component	NOUN
ajst-8015	95	8	analysis	analysis	NOUN
ajst-8015	95	9	(	(	PUNCT
ajst-8015	95	10	pca	pca	NOUN
ajst-8015	95	11	)	)	PUNCT
ajst-8015	96	1	[	[	X
ajst-8015	96	2	28	28	NUM
ajst-8015	96	3	]	]	PUNCT
ajst-8015	96	4	,	,	PUNCT
ajst-8015	96	5	partial	partial	ADJ
ajst-8015	96	6	least	least	ADJ
ajst-8015	96	7	squares	square	NOUN
ajst-8015	96	8	,	,	PUNCT
ajst-8015	96	9	pls	pls	INTJ
ajst-8015	96	10	)	)	PUNCT
ajst-8015	96	11	,	,	PUNCT
ajst-8015	96	12	singular	singular	ADJ
ajst-8015	96	13	value	value	NOUN
ajst-8015	96	14	decomposition	decomposition	NOUN
ajst-8015	96	15	(	(	PUNCT
ajst-8015	96	16	svd	svd	PROPN
ajst-8015	96	17	)	)	PUNCT
ajst-8015	96	18	,	,	PUNCT
ajst-8015	96	19	low	low	ADJ
ajst-8015	96	20	variance	variance	NOUN
ajst-8015	96	21	filter	filter	NOUN
ajst-8015	96	22	(	(	PUNCT
ajst-8015	96	23	lvf	lvf	NOUN
ajst-8015	96	24	)	)	PUNCT
ajst-8015	96	25	,	,	PUNCT
ajst-8015	96	26	etc	etc	X
ajst-8015	96	27	.	.	X
ajst-8015	96	28	pca	pca	PROPN
ajst-8015	96	29	is	be	AUX
ajst-8015	96	30	the	the	DET
ajst-8015	96	31	most	most	ADV
ajst-8015	96	32	commonly	commonly	ADV
ajst-8015	96	33	used	use	VERB
ajst-8015	96	34	data	data	NOUN
ajst-8015	96	35	dimension	dimension	NOUN
ajst-8015	96	36	reduction	reduction	NOUN
ajst-8015	96	37	method	method	NOUN
ajst-8015	96	38	,	,	PUNCT
ajst-8015	96	39	whose	whose	DET
ajst-8015	96	40	essence	essence	NOUN
ajst-8015	96	41	is	be	AUX
ajst-8015	96	42	to	to	PART
ajst-8015	96	43	carry	carry	VERB
ajst-8015	96	44	out	out	ADP
ajst-8015	96	45	orthogonal	orthogonal	ADJ
ajst-8015	96	46	transformation	transformation	NOUN
ajst-8015	96	47	of	of	ADP
ajst-8015	96	48	existing	exist	VERB
ajst-8015	96	49	coordinates	coordinate	NOUN
ajst-8015	96	50	in	in	ADP
ajst-8015	96	51	space	space	NOUN
ajst-8015	96	52	according	accord	VERB
ajst-8015	96	53	to	to	ADP
ajst-8015	96	54	certain	certain	ADJ
ajst-8015	96	55	rules	rule	NOUN
ajst-8015	96	56	.	.	PUNCT
ajst-8015	97	1	khedher	khedher	PROPN
ajst-8015	97	2	et	et	PROPN
ajst-8015	97	3	al	al	PROPN
ajst-8015	97	4	.	.	PUNCT
ajst-8015	98	1	[	[	X
ajst-8015	98	2	29	29	NUM
ajst-8015	98	3	]	]	PUNCT
ajst-8015	98	4	carried	carry	VERB
ajst-8015	98	5	out	out	ADP
ajst-8015	98	6	feature	feature	NOUN
ajst-8015	98	7	extraction	extraction	NOUN
ajst-8015	98	8	and	and	CCONJ
ajst-8015	98	9	dimension	dimension	NOUN
ajst-8015	98	10	reduction	reduction	NOUN
ajst-8015	98	11	by	by	ADP
ajst-8015	98	12	pca	pca	PROPN
ajst-8015	98	13	and	and	CCONJ
ajst-8015	98	14	pls	pls	PROPN
ajst-8015	98	15	methods	method	NOUN
ajst-8015	98	16	,	,	PUNCT
ajst-8015	98	17	and	and	CCONJ
ajst-8015	98	18	completed	complete	VERB
ajst-8015	98	19	the	the	DET
ajst-8015	98	20	classification	classification	NOUN
ajst-8015	98	21	task	task	NOUN
ajst-8015	98	22	for	for	ADP
ajst-8015	98	23	alzheimer	alzheimer	PROPN
ajst-8015	98	24	's	's	PART
ajst-8015	98	25	disease	disease	NOUN
ajst-8015	98	26	patients	patient	NOUN
ajst-8015	98	27	and	and	CCONJ
ajst-8015	98	28	normal	normal	ADJ
ajst-8015	98	29	subjects	subject	NOUN
ajst-8015	98	30	.	.	PUNCT
ajst-8015	99	1	2.1.3	2.1.3	X
ajst-8015	99	2	.	.	PUNCT
ajst-8015	99	3	classification	classification	NOUN
ajst-8015	99	4	common	common	ADJ
ajst-8015	99	5	machine	machine	NOUN
ajst-8015	99	6	learning	learn	VERB
ajst-8015	99	7	classifiers	classifier	NOUN
ajst-8015	99	8	include	include	VERB
ajst-8015	99	9	support	support	NOUN
ajst-8015	99	10	vector	vector	NOUN
ajst-8015	99	11	machine	machine	NOUN
ajst-8015	99	12	(	(	PUNCT
ajst-8015	99	13	svm	svm	PROPN
ajst-8015	99	14	)	)	PUNCT
ajst-8015	99	15	,	,	PUNCT
ajst-8015	99	16	k	k	X
ajst-8015	99	17	-	-	PUNCT
ajst-8015	99	18	nearest	near	ADJ
ajst-8015	99	19	neighbors	neighbor	NOUN
ajst-8015	99	20	(	(	PUNCT
ajst-8015	99	21	k	k	X
ajst-8015	99	22	-	-	PUNCT
ajst-8015	99	23	nn	nn	NOUN
ajst-8015	99	24	)	)	PUNCT
ajst-8015	99	25	and	and	CCONJ
ajst-8015	99	26	logistic	logistic	ADJ
ajst-8015	99	27	regression	regression	NOUN
ajst-8015	99	28	classification	classification	NOUN
ajst-8015	99	29	.	.	PUNCT
ajst-8015	100	1	lrc	lrc	PROPN
ajst-8015	100	2	)	)	PUNCT
ajst-8015	100	3	,	,	PUNCT
ajst-8015	100	4	random	random	ADJ
ajst-8015	100	5	forest	forest	NOUN
ajst-8015	100	6	(	(	PUNCT
ajst-8015	100	7	rf	rf	NOUN
ajst-8015	100	8	)	)	PUNCT
ajst-8015	100	9	and	and	CCONJ
ajst-8015	100	10	so	so	ADV
ajst-8015	100	11	on	on	ADV
ajst-8015	100	12	.	.	PUNCT
ajst-8015	101	1	mesrob	mesrob	ADV
ajst-8015	101	2	et	et	PROPN
ajst-8015	101	3	al	al	PROPN
ajst-8015	101	4	.	.	PUNCT
ajst-8015	102	1	[	[	X
ajst-8015	102	2	30	30	NUM
ajst-8015	102	3	]	]	PUNCT
ajst-8015	102	4	proposed	propose	VERB
ajst-8015	102	5	a	a	DET
ajst-8015	102	6	method	method	NOUN
ajst-8015	102	7	based	base	VERB
ajst-8015	102	8	on	on	ADP
ajst-8015	102	9	svm	svm	PROPN
ajst-8015	102	10	classifier	classifier	NOUN
ajst-8015	102	11	to	to	PART
ajst-8015	102	12	classify	classify	VERB
ajst-8015	102	13	ad	ad	NOUN
ajst-8015	102	14	patients	patient	NOUN
ajst-8015	102	15	and	and	CCONJ
ajst-8015	102	16	normal	normal	ADJ
ajst-8015	102	17	subjects	subject	NOUN
ajst-8015	102	18	.	.	PUNCT
ajst-8015	103	1	the	the	DET
ajst-8015	103	2	subjects	subject	NOUN
ajst-8015	103	3	were	be	AUX
ajst-8015	103	4	divided	divide	VERB
ajst-8015	103	5	into	into	ADP
ajst-8015	103	6	two	two	NUM
ajst-8015	103	7	experimental	experimental	ADJ
ajst-8015	103	8	groups	group	NOUN
ajst-8015	103	9	,	,	PUNCT
ajst-8015	103	10	and	and	CCONJ
ajst-8015	103	11	the	the	DET
ajst-8015	103	12	features	feature	NOUN
ajst-8015	103	13	of	of	ADP
ajst-8015	103	14	roi	roi	NOUN
ajst-8015	103	15	brain	brain	NOUN
ajst-8015	103	16	region	region	NOUN
ajst-8015	103	17	(	(	PUNCT
ajst-8015	103	18	hippocampus	hippocampus	NOUN
ajst-8015	103	19	,	,	PUNCT
ajst-8015	103	20	amygdala	amygdala	NOUN
ajst-8015	103	21	,	,	PUNCT
ajst-8015	103	22	etc	etc	X
ajst-8015	103	23	.	.	X
ajst-8015	103	24	)	)	PUNCT
ajst-8015	103	25	and	and	CCONJ
ajst-8015	103	26	brain	brain	NOUN
ajst-8015	103	27	tissue	tissue	NOUN
ajst-8015	103	28	(	(	PUNCT
ajst-8015	103	29	gray	gray	ADJ
ajst-8015	103	30	matter	matter	NOUN
ajst-8015	103	31	,	,	PUNCT
ajst-8015	103	32	white	white	ADJ
ajst-8015	103	33	matter	matter	NOUN
ajst-8015	103	34	,	,	PUNCT
ajst-8015	103	35	etc	etc	X
ajst-8015	103	36	.	.	X
ajst-8015	103	37	)	)	PUNCT
ajst-8015	103	38	were	be	AUX
ajst-8015	103	39	extracted	extract	VERB
ajst-8015	103	40	respectively	respectively	ADV
ajst-8015	103	41	.	.	PUNCT
ajst-8015	104	1	the	the	DET
ajst-8015	104	2	classification	classification	NOUN
ajst-8015	104	3	results	result	NOUN
ajst-8015	104	4	of	of	ADP
ajst-8015	104	5	the	the	DET
ajst-8015	104	6	two	two	NUM
ajst-8015	104	7	experimental	experimental	ADJ
ajst-8015	104	8	groups	group	NOUN
ajst-8015	104	9	were	be	AUX
ajst-8015	104	10	compared	compare	VERB
ajst-8015	104	11	to	to	PART
ajst-8015	104	12	find	find	VERB
ajst-8015	104	13	out	out	ADP
ajst-8015	104	14	the	the	DET
ajst-8015	104	15	brain	brain	NOUN
ajst-8015	104	16	region	region	NOUN
ajst-8015	104	17	with	with	ADP
ajst-8015	104	18	the	the	DET
ajst-8015	104	19	highest	high	ADJ
ajst-8015	104	20	correlation	correlation	NOUN
ajst-8015	104	21	with	with	ADP
ajst-8015	104	22	ad	ad	NOUN
ajst-8015	104	23	.	.	PUNCT
ajst-8015	105	1	dimitriadis	dimitriadis	VERB
ajst-8015	105	2	et	et	PROPN
ajst-8015	105	3	al	al	PROPN
ajst-8015	105	4	.	.	PUNCT
ajst-8015	106	1	[	[	X
ajst-8015	106	2	31]proposed	31]proposed	NUM
ajst-8015	106	3	a	a	DET
ajst-8015	106	4	classification	classification	NOUN
ajst-8015	106	5	method	method	NOUN
ajst-8015	106	6	of	of	ADP
ajst-8015	106	7	alzheimer	alzheimer	PROPN
ajst-8015	106	8	's	's	PART
ajst-8015	106	9	disease	disease	NOUN
ajst-8015	106	10	based	base	VERB
ajst-8015	106	11	on	on	ADP
ajst-8015	106	12	rf	rf	NOUN
ajst-8015	106	13	classifier	classifier	NOUN
ajst-8015	106	14	.	.	PUNCT
ajst-8015	107	1	features	feature	NOUN
ajst-8015	107	2	such	such	ADJ
ajst-8015	107	3	as	as	ADP
ajst-8015	107	4	cortical	cortical	ADJ
ajst-8015	107	5	thickness	thickness	NOUN
ajst-8015	107	6	,	,	PUNCT
ajst-8015	107	7	cortical	cortical	ADJ
ajst-8015	107	8	surface	surface	NOUN
ajst-8015	107	9	area	area	NOUN
ajst-8015	107	10	,	,	PUNCT
ajst-8015	107	11	cortical	cortical	ADJ
ajst-8015	107	12	curvature	curvature	NOUN
ajst-8015	107	13	and	and	CCONJ
ajst-8015	107	14	hippocampal	hippocampal	ADJ
ajst-8015	107	15	volume	volume	NOUN
ajst-8015	107	16	were	be	AUX
ajst-8015	107	17	extracted	extract	VERB
ajst-8015	107	18	,	,	PUNCT
ajst-8015	107	19	and	and	CCONJ
ajst-8015	107	20	the	the	DET
ajst-8015	107	21	results	result	NOUN
ajst-8015	107	22	of	of	ADP
ajst-8015	107	23	each	each	DET
ajst-8015	107	24	classifier	classifier	NOUN
ajst-8015	107	25	were	be	AUX
ajst-8015	107	26	weighted	weight	VERB
ajst-8015	107	27	and	and	CCONJ
ajst-8015	107	28	fused	fuse	VERB
ajst-8015	107	29	into	into	ADP
ajst-8015	107	30	the	the	DET
ajst-8015	107	31	final	final	ADJ
ajst-8015	107	32	decision	decision	NOUN
ajst-8015	107	33	using	use	VERB
ajst-8015	107	34	the	the	DET
ajst-8015	107	35	proximity	proximity	NOUN
ajst-8015	107	36	strategy	strategy	NOUN
ajst-8015	107	37	.	.	PUNCT
ajst-8015	108	1	finally	finally	ADV
ajst-8015	108	2	,	,	PUNCT
ajst-8015	108	3	the	the	DET
ajst-8015	108	4	recognition	recognition	NOUN
ajst-8015	108	5	accuracy	accuracy	NOUN
ajst-8015	108	6	of	of	ADP
ajst-8015	108	7	the	the	DET
ajst-8015	108	8	multiclassification	multiclassification	NOUN
ajst-8015	108	9	model	model	NOUN
ajst-8015	108	10	was	be	AUX
ajst-8015	108	11	76	76	NUM
ajst-8015	108	12	%	%	NOUN
ajst-8015	108	13	.	.	PUNCT
ajst-8015	109	1	telagarapu	telagarapu	PROPN
ajst-8015	109	2	et	et	PROPN
ajst-8015	109	3	al	al	PROPN
ajst-8015	109	4	.	.	PUNCT
ajst-8015	110	1	[	[	X
ajst-8015	110	2	32	32	NUM
ajst-8015	110	3	]	]	PUNCT
ajst-8015	110	4	analyzed	analyze	VERB
ajst-8015	110	5	t1	t1	NOUN
ajst-8015	110	6	-	-	PUNCT
ajst-8015	110	7	weighted	weight	VERB
ajst-8015	110	8	mri	mri	NOUN
ajst-8015	110	9	images	image	NOUN
ajst-8015	110	10	of	of	ADP
ajst-8015	110	11	ad	ad	NOUN
ajst-8015	110	12	patients	patient	NOUN
ajst-8015	110	13	by	by	ADP
ajst-8015	110	14	using	use	VERB
ajst-8015	110	15	the	the	DET
ajst-8015	110	16	texture	texture	NOUN
ajst-8015	110	17	features	feature	NOUN
ajst-8015	110	18	of	of	ADP
ajst-8015	110	19	the	the	DET
ajst-8015	110	20	hippocampus	hippocampus	NOUN
ajst-8015	110	21	and	and	CCONJ
ajst-8015	110	22	k	k	PROPN
ajst-8015	110	23	-	-	PUNCT
ajst-8015	110	24	nn	nn	ADJ
ajst-8015	110	25	classifier	classifier	NOUN
ajst-8015	110	26	.	.	PUNCT
ajst-8015	111	1	by	by	ADP
ajst-8015	111	2	using	use	VERB
ajst-8015	111	3	glcm	glcm	NOUN
ajst-8015	111	4	method	method	NOUN
ajst-8015	111	5	,	,	PUNCT
ajst-8015	111	6	the	the	DET
ajst-8015	111	7	classification	classification	NOUN
ajst-8015	111	8	accuracy	accuracy	NOUN
ajst-8015	111	9	of	of	ADP
ajst-8015	111	10	74.73	74.73	NUM
ajst-8015	111	11	%	%	NOUN
ajst-8015	111	12	was	be	AUX
ajst-8015	111	13	achieved	achieve	VERB
ajst-8015	111	14	.	.	PUNCT
ajst-8015	112	1	to	to	PART
ajst-8015	112	2	sum	sum	VERB
ajst-8015	112	3	up	up	ADP
ajst-8015	112	4	,	,	PUNCT
ajst-8015	112	5	the	the	DET
ajst-8015	112	6	research	research	NOUN
ajst-8015	112	7	of	of	ADP
ajst-8015	112	8	machine	machine	NOUN
ajst-8015	112	9	learning	learning	NOUN
ajst-8015	112	10	in	in	ADP
ajst-8015	112	11	the	the	DET
ajst-8015	112	12	field	field	NOUN
ajst-8015	112	13	of	of	ADP
ajst-8015	112	14	alzheimer	alzheimer	PROPN
ajst-8015	112	15	's	's	PART
ajst-8015	112	16	disease	disease	NOUN
ajst-8015	112	17	diagnosis	diagnosis	NOUN
ajst-8015	112	18	has	have	AUX
ajst-8015	112	19	achieved	achieve	VERB
ajst-8015	112	20	fruitful	fruitful	ADJ
ajst-8015	112	21	results	result	NOUN
ajst-8015	112	22	,	,	PUNCT
ajst-8015	112	23	but	but	CCONJ
ajst-8015	112	24	there	there	PRON
ajst-8015	112	25	are	be	VERB
ajst-8015	112	26	also	also	ADV
ajst-8015	112	27	obvious	obvious	ADJ
ajst-8015	112	28	shortcomings	shortcoming	NOUN
ajst-8015	112	29	.	.	PUNCT
ajst-8015	113	1	1	1	X
ajst-8015	113	2	.	.	X
ajst-8015	113	3	voxel	voxel	PROPN
ajst-8015	113	4	-	-	PUNCT
ajst-8015	113	5	based	base	VERB
ajst-8015	113	6	methods	method	NOUN
ajst-8015	113	7	can	can	AUX
ajst-8015	113	8	obtain	obtain	VERB
ajst-8015	113	9	all	all	DET
ajst-8015	113	10	three	three	NUM
ajst-8015	113	11	-	-	PUNCT
ajst-8015	113	12	dimensional	dimensional	ADJ
ajst-8015	113	13	information	information	NOUN
ajst-8015	113	14	in	in	ADP
ajst-8015	113	15	a	a	DET
ajst-8015	113	16	single	single	ADJ
ajst-8015	113	17	scan	scan	NOUN
ajst-8015	113	18	,	,	PUNCT
ajst-8015	113	19	but	but	CCONJ
ajst-8015	113	20	they	they	PRON
ajst-8015	113	21	deal	deal	VERB
ajst-8015	113	22	with	with	ADP
ajst-8015	113	23	all	all	DET
ajst-8015	113	24	brain	brain	NOUN
ajst-8015	113	25	regions	region	NOUN
ajst-8015	113	26	uniformly	uniformly	ADV
ajst-8015	113	27	and	and	CCONJ
ajst-8015	113	28	are	be	AUX
ajst-8015	113	29	not	not	PART
ajst-8015	113	30	adapted	adapt	VERB
ajst-8015	113	31	to	to	ADP
ajst-8015	113	32	specific	specific	ADJ
ajst-8015	113	33	anatomical	anatomical	ADJ
ajst-8015	113	34	structures	structure	NOUN
ajst-8015	113	35	.	.	PUNCT
ajst-8015	114	1	in	in	ADP
ajst-8015	114	2	addition	addition	NOUN
ajst-8015	114	3	,	,	PUNCT
ajst-8015	114	4	voxel	voxel	PROPN
ajst-8015	114	5	-	-	PUNCT
ajst-8015	114	6	based	base	VERB
ajst-8015	114	7	methods	method	NOUN
ajst-8015	114	8	ignore	ignore	VERB
ajst-8015	114	9	local	local	ADJ
ajst-8015	114	10	information	information	NOUN
ajst-8015	114	11	because	because	SCONJ
ajst-8015	114	12	they	they	PRON
ajst-8015	114	13	deal	deal	VERB
ajst-8015	114	14	with	with	ADP
ajst-8015	114	15	each	each	DET
ajst-8015	114	16	voxel	voxel	PROPN
ajst-8015	114	17	independently	independently	ADV
ajst-8015	114	18	,	,	PUNCT
ajst-8015	114	19	often	often	ADV
ajst-8015	114	20	with	with	ADP
ajst-8015	114	21	high	high	ADJ
ajst-8015	114	22	characteristic	characteristic	ADJ
ajst-8015	114	23	dimensions	dimension	NOUN
ajst-8015	114	24	and	and	CCONJ
ajst-8015	114	25	high	high	ADJ
ajst-8015	114	26	computational	computational	ADJ
ajst-8015	114	27	load	load	NOUN
ajst-8015	114	28	.	.	PUNCT
ajst-8015	115	1	2	2	X
ajst-8015	115	2	.	.	X
ajst-8015	115	3	slice	slice	NOUN
ajst-8015	115	4	-	-	PUNCT
ajst-8015	115	5	based	base	VERB
ajst-8015	115	6	method	method	NOUN
ajst-8015	115	7	uses	use	VERB
ajst-8015	115	8	two	two	NUM
ajst-8015	115	9	-	-	PUNCT
ajst-8015	115	10	dimensional	dimensional	ADJ
ajst-8015	115	11	slicing	slicing	NOUN
ajst-8015	115	12	rather	rather	ADV
ajst-8015	115	13	than	than	ADP
ajst-8015	115	14	the	the	DET
ajst-8015	115	15	whole	whole	ADJ
ajst-8015	115	16	three	three	NUM
ajst-8015	115	17	-	-	PUNCT
ajst-8015	115	18	dimensional	dimensional	ADJ
ajst-8015	115	19	image	image	NOUN
ajst-8015	115	20	as	as	ADP
ajst-8015	115	21	input	input	NOUN
ajst-8015	115	22	,	,	PUNCT
ajst-8015	115	23	which	which	PRON
ajst-8015	115	24	can	can	AUX
ajst-8015	115	25	reduce	reduce	VERB
ajst-8015	115	26	a	a	DET
ajst-8015	115	27	large	large	ADJ
ajst-8015	115	28	number	number	NOUN
ajst-8015	115	29	of	of	ADP
ajst-8015	115	30	parameters	parameter	NOUN
ajst-8015	115	31	and	and	CCONJ
ajst-8015	115	32	simplify	simplify	VERB
ajst-8015	115	33	the	the	DET
ajst-8015	115	34	network	network	NOUN
ajst-8015	115	35	.	.	PUNCT
ajst-8015	116	1	however	however	ADV
ajst-8015	116	2	,	,	PUNCT
ajst-8015	116	3	slicing	slice	VERB
ajst-8015	116	4	method	method	NOUN
ajst-8015	116	5	requires	require	VERB
ajst-8015	116	6	certain	certain	ADJ
ajst-8015	116	7	prior	prior	ADJ
ajst-8015	116	8	knowledge	knowledge	NOUN
ajst-8015	116	9	,	,	PUNCT
ajst-8015	116	10	and	and	CCONJ
ajst-8015	116	11	only	only	ADV
ajst-8015	116	12	slices	slice	NOUN
ajst-8015	116	13	are	be	AUX
ajst-8015	116	14	selected	select	VERB
ajst-8015	116	15	from	from	ADP
ajst-8015	116	16	the	the	DET
ajst-8015	116	17	plane	plane	NOUN
ajst-8015	116	18	in	in	ADP
ajst-8015	116	19	one	one	NUM
ajst-8015	116	20	direction	direction	NOUN
ajst-8015	116	21	,	,	PUNCT
ajst-8015	116	22	so	so	CCONJ
ajst-8015	116	23	the	the	DET
ajst-8015	116	24	spatial	spatial	ADJ
ajst-8015	116	25	information	information	NOUN
ajst-8015	116	26	of	of	ADP
ajst-8015	116	27	the	the	DET
ajst-8015	116	28	image	image	NOUN
ajst-8015	116	29	can	can	AUX
ajst-8015	116	30	not	not	PART
ajst-8015	116	31	be	be	AUX
ajst-8015	116	32	fully	fully	ADV
ajst-8015	116	33	utilized	utilize	VERB
ajst-8015	116	34	.	.	PUNCT
ajst-8015	117	1	3	3	X
ajst-8015	117	2	.	.	X
ajst-8015	117	3	although	although	SCONJ
ajst-8015	117	4	block	block	NOUN
ajst-8015	117	5	-	-	PUNCT
ajst-8015	117	6	based	base	VERB
ajst-8015	117	7	methods	method	NOUN
ajst-8015	117	8	can	can	AUX
ajst-8015	117	9	compensate	compensate	VERB
ajst-8015	117	10	for	for	ADP
ajst-8015	117	11	the	the	DET
ajst-8015	117	12	three	three	NUM
ajst-8015	117	13	-	-	PUNCT
ajst-8015	117	14	dimensional	dimensional	ADJ
ajst-8015	117	15	information	information	NOUN
ajst-8015	117	16	loss	loss	NOUN
ajst-8015	117	17	in	in	ADP
ajst-8015	117	18	slice	slice	NOUN
ajst-8015	117	19	-	-	PUNCT
ajst-8015	117	20	based	base	VERB
ajst-8015	117	21	methods	method	NOUN
ajst-8015	117	22	,	,	PUNCT
ajst-8015	117	23	most	most	ADJ
ajst-8015	117	24	of	of	ADP
ajst-8015	117	25	them	they	PRON
ajst-8015	117	26	use	use	VERB
ajst-8015	117	27	integrated	integrate	VERB
ajst-8015	117	28	classifier	classifier	NOUN
ajst-8015	117	29	methods	method	NOUN
ajst-8015	117	30	,	,	PUNCT
ajst-8015	117	31	and	and	CCONJ
ajst-8015	117	32	feature	feature	NOUN
ajst-8015	117	33	extraction	extraction	NOUN
ajst-8015	117	34	and	and	CCONJ
ajst-8015	117	35	classification	classification	NOUN
ajst-8015	117	36	among	among	ADP
ajst-8015	117	37	each	each	DET
ajst-8015	117	38	block	block	NOUN
ajst-8015	117	39	are	be	AUX
ajst-8015	117	40	independent	independent	ADJ
ajst-8015	117	41	of	of	ADP
ajst-8015	117	42	each	each	DET
ajst-8015	117	43	other	other	ADJ
ajst-8015	117	44	.	.	PUNCT
ajst-8015	118	1	however	however	ADV
ajst-8015	118	2	,	,	PUNCT
ajst-8015	118	3	the	the	DET
ajst-8015	118	4	tissue	tissue	NOUN
ajst-8015	118	5	changes	change	NOUN
ajst-8015	118	6	between	between	ADP
ajst-8015	118	7	brains	brain	NOUN
ajst-8015	118	8	are	be	AUX
ajst-8015	118	9	correlated	correlate	VERB
ajst-8015	118	10	,	,	PUNCT
ajst-8015	118	11	and	and	CCONJ
ajst-8015	118	12	block	block	NOUN
ajst-8015	118	13	-	-	PUNCT
ajst-8015	118	14	based	base	VERB
ajst-8015	118	15	approaches	approach	NOUN
ajst-8015	118	16	do	do	AUX
ajst-8015	118	17	not	not	PART
ajst-8015	118	18	integrate	integrate	VERB
ajst-8015	118	19	the	the	DET
ajst-8015	118	20	features	feature	NOUN
ajst-8015	118	21	of	of	ADP
ajst-8015	118	22	each	each	DET
ajst-8015	118	23	block	block	NOUN
ajst-8015	118	24	well	well	ADV
ajst-8015	118	25	.	.	PUNCT
ajst-8015	119	1	4	4	X
ajst-8015	119	2	.	.	X
ajst-8015	119	3	roy	roy	NOUN
ajst-8015	119	4	-	-	PUNCT
ajst-8015	119	5	based	base	VERB
ajst-8015	119	6	methods	method	NOUN
ajst-8015	119	7	reduce	reduce	VERB
ajst-8015	119	8	the	the	DET
ajst-8015	119	9	number	number	NOUN
ajst-8015	119	10	of	of	ADP
ajst-8015	119	11	dimensions	dimension	NOUN
ajst-8015	119	12	by	by	ADP
ajst-8015	119	13	selecting	select	VERB
ajst-8015	119	14	specific	specific	ADJ
ajst-8015	119	15	areas	area	NOUN
ajst-8015	119	16	of	of	ADP
ajst-8015	119	17	the	the	DET
ajst-8015	119	18	brain	brain	NOUN
ajst-8015	119	19	to	to	PART
ajst-8015	119	20	extract	extract	VERB
ajst-8015	119	21	features	feature	NOUN
ajst-8015	119	22	.	.	PUNCT
ajst-8015	120	1	however	however	ADV
ajst-8015	120	2	,	,	PUNCT
ajst-8015	120	3	an	an	DET
ajst-8015	120	4	abnormal	abnormal	ADJ
ajst-8015	120	5	region	region	NOUN
ajst-8015	120	6	may	may	AUX
ajst-8015	120	7	represent	represent	VERB
ajst-8015	120	8	only	only	ADV
ajst-8015	120	9	a	a	DET
ajst-8015	120	10	small	small	ADJ
ajst-8015	120	11	fraction	fraction	NOUN
ajst-8015	120	12	of	of	ADP
ajst-8015	120	13	the	the	DET
ajst-8015	120	14	predefined	predefine	VERB
ajst-8015	120	15	roi	roi	NOUN
ajst-8015	120	16	region	region	NOUN
ajst-8015	120	17	and	and	CCONJ
ajst-8015	120	18	may	may	AUX
ajst-8015	120	19	be	be	AUX
ajst-8015	120	20	distributed	distribute	VERB
ajst-8015	120	21	to	to	ADP
ajst-8015	120	22	other	other	ADJ
ajst-8015	120	23	brain	brain	NOUN
ajst-8015	120	24	regions	region	NOUN
ajst-8015	120	25	,	,	PUNCT
ajst-8015	120	26	resulting	result	VERB
ajst-8015	120	27	in	in	ADP
ajst-8015	120	28	loss	loss	NOUN
ajst-8015	120	29	of	of	ADP
ajst-8015	120	30	identification	identification	NOUN
ajst-8015	120	31	information	information	NOUN
ajst-8015	120	32	.	.	PUNCT
ajst-8015	121	1	in	in	ADP
ajst-8015	121	2	addition	addition	NOUN
ajst-8015	121	3	,	,	PUNCT
ajst-8015	121	4	roi	roi	NOUN
ajst-8015	121	5	-	-	PUNCT
ajst-8015	121	6	based	base	VERB
ajst-8015	121	7	methods	method	NOUN
ajst-8015	121	8	also	also	ADV
ajst-8015	121	9	require	require	VERB
ajst-8015	121	10	prior	prior	ADJ
ajst-8015	121	11	knowledge	knowledge	NOUN
ajst-8015	121	12	of	of	ADP
ajst-8015	121	13	experts	expert	NOUN
ajst-8015	121	14	to	to	PART
ajst-8015	121	15	divide	divide	VERB
ajst-8015	121	16	roi	roi	NOUN
ajst-8015	121	17	.	.	PUNCT
ajst-8015	122	1	5	5	X
ajst-8015	122	2	.	.	PUNCT
ajst-8015	122	3	the	the	DET
ajst-8015	122	4	method	method	NOUN
ajst-8015	122	5	based	base	VERB
ajst-8015	122	6	on	on	ADP
ajst-8015	122	7	global	global	ADJ
ajst-8015	122	8	image	image	NOUN
ajst-8015	122	9	takes	take	VERB
ajst-8015	122	10	the	the	DET
ajst-8015	122	11	whole	whole	ADJ
ajst-8015	122	12	three	three	NUM
ajst-8015	122	13	-	-	PUNCT
ajst-8015	122	14	dimensional	dimensional	ADJ
ajst-8015	122	15	image	image	NOUN
ajst-8015	122	16	as	as	ADP
ajst-8015	122	17	the	the	DET
ajst-8015	122	18	input	input	NOUN
ajst-8015	122	19	,	,	PUNCT
ajst-8015	122	20	which	which	PRON
ajst-8015	122	21	can	can	AUX
ajst-8015	122	22	make	make	VERB
ajst-8015	122	23	full	full	ADJ
ajst-8015	122	24	use	use	NOUN
ajst-8015	122	25	of	of	ADP
ajst-8015	122	26	all	all	DET
ajst-8015	122	27	the	the	DET
ajst-8015	122	28	information	information	NOUN
ajst-8015	122	29	of	of	ADP
ajst-8015	122	30	the	the	DET
ajst-8015	122	31	image	image	NOUN
ajst-8015	122	32	.	.	PUNCT
ajst-8015	123	1	however	however	ADV
ajst-8015	123	2	,	,	PUNCT
ajst-8015	123	3	for	for	ADP
ajst-8015	123	4	samples	sample	NOUN
ajst-8015	123	5	with	with	ADP
ajst-8015	123	6	small	small	ADJ
ajst-8015	123	7	lesions	lesion	NOUN
ajst-8015	123	8	,	,	PUNCT
ajst-8015	123	9	there	there	PRON
ajst-8015	123	10	is	be	VERB
ajst-8015	123	11	a	a	DET
ajst-8015	123	12	large	large	ADJ
ajst-8015	123	13	amount	amount	NOUN
ajst-8015	123	14	of	of	ADP
ajst-8015	123	15	redundant	redundant	ADJ
ajst-8015	123	16	information	information	NOUN
ajst-8015	123	17	.	.	PUNCT
ajst-8015	124	1	in	in	ADP
ajst-8015	124	2	addition	addition	NOUN
ajst-8015	124	3	,	,	PUNCT
ajst-8015	124	4	similar	similar	ADJ
ajst-8015	124	5	to	to	ADP
ajst-8015	124	6	the	the	DET
ajst-8015	124	7	block	block	NOUN
ajst-8015	124	8	-	-	PUNCT
ajst-8015	124	9	based	base	VERB
ajst-8015	124	10	method	method	NOUN
ajst-8015	124	11	,	,	PUNCT
ajst-8015	124	12	the	the	DET
ajst-8015	124	13	global	global	ADJ
ajst-8015	124	14	image	image	NOUN
ajst-8015	124	15	-	-	PUNCT
ajst-8015	124	16	based	base	VERB
ajst-8015	124	17	method	method	NOUN
ajst-8015	124	18	has	have	VERB
ajst-8015	124	19	a	a	DET
ajst-8015	124	20	high	high	ADJ
ajst-8015	124	21	feature	feature	NOUN
ajst-8015	124	22	dimension	dimension	NOUN
ajst-8015	124	23	and	and	CCONJ
ajst-8015	124	24	a	a	DET
ajst-8015	124	25	high	high	ADJ
ajst-8015	124	26	computational	computational	ADJ
ajst-8015	124	27	load	load	NOUN
ajst-8015	124	28	.	.	PUNCT
ajst-8015	125	1	2.2	2.2	NUM
ajst-8015	125	2	.	.	PUNCT
ajst-8015	125	3	recognition	recognition	NOUN
ajst-8015	125	4	of	of	ADP
ajst-8015	125	5	alzheimer	alzheimer	PROPN
ajst-8015	125	6	's	's	PART
ajst-8015	125	7	disease	disease	NOUN
ajst-8015	125	8	based	base	VERB
ajst-8015	125	9	on	on	ADP
ajst-8015	125	10	deep	deep	ADJ
ajst-8015	125	11	learning	learning	NOUN
ajst-8015	125	12	methods	method	NOUN
ajst-8015	125	13	deep	deep	ADJ
ajst-8015	125	14	learning	learning	NOUN
ajst-8015	125	15	technology	technology	NOUN
ajst-8015	125	16	has	have	AUX
ajst-8015	125	17	been	be	AUX
ajst-8015	125	18	developing	develop	VERB
ajst-8015	125	19	in	in	ADP
ajst-8015	125	20	recent	recent	ADJ
ajst-8015	125	21	years	year	NOUN
ajst-8015	125	22	.	.	PUNCT
ajst-8015	126	1	under	under	ADP
ajst-8015	126	2	the	the	DET
ajst-8015	126	3	background	background	NOUN
ajst-8015	126	4	of	of	ADP
ajst-8015	126	5	improving	improve	VERB
ajst-8015	126	6	the	the	DET
ajst-8015	126	7	level	level	NOUN
ajst-8015	126	8	of	of	ADP
ajst-8015	126	9	computer	computer	NOUN
ajst-8015	126	10	hardware	hardware	NOUN
ajst-8015	126	11	and	and	CCONJ
ajst-8015	126	12	increasing	increase	VERB
ajst-8015	126	13	the	the	DET
ajst-8015	126	14	amount	amount	NOUN
ajst-8015	126	15	of	of	ADP
ajst-8015	126	16	training	training	NOUN
ajst-8015	126	17	data	datum	NOUN
ajst-8015	126	18	,	,	PUNCT
ajst-8015	126	19	the	the	DET
ajst-8015	126	20	recognition	recognition	NOUN
ajst-8015	126	21	effect	effect	NOUN
ajst-8015	126	22	of	of	ADP
ajst-8015	126	23	the	the	DET
ajst-8015	126	24	model	model	NOUN
ajst-8015	126	25	has	have	AUX
ajst-8015	126	26	been	be	AUX
ajst-8015	126	27	better	well	ADJ
ajst-8015	126	28	than	than	ADP
ajst-8015	126	29	the	the	DET
ajst-8015	126	30	traditional	traditional	ADJ
ajst-8015	126	31	machine	machine	NOUN
ajst-8015	126	32	learning	learning	NOUN
ajst-8015	126	33	algorithm	algorithm	NOUN
ajst-8015	126	34	.	.	PUNCT
ajst-8015	127	1	2.2.1	2.2.1	NUM
ajst-8015	127	2	.	.	PUNCT
ajst-8015	127	3	ad	ad	NOUN
ajst-8015	127	4	classification	classification	NOUN
ajst-8015	127	5	based	base	VERB
ajst-8015	127	6	on	on	ADP
ajst-8015	127	7	cnn	cnn	PROPN
ajst-8015	127	8	convolutional	convolutional	ADJ
ajst-8015	127	9	neural	neural	ADJ
ajst-8015	127	10	network	network	NOUN
ajst-8015	127	11	is	be	AUX
ajst-8015	127	12	a	a	DET
ajst-8015	127	13	feedforward	feedforward	ADJ
ajst-8015	127	14	neural	neural	ADJ
ajst-8015	127	15	network	network	NOUN
ajst-8015	127	16	that	that	PRON
ajst-8015	127	17	extracts	extract	VERB
ajst-8015	127	18	image	image	NOUN
ajst-8015	127	19	features	feature	NOUN
ajst-8015	127	20	by	by	ADP
ajst-8015	127	21	convolutional	convolutional	ADJ
ajst-8015	127	22	kernel	kernel	NOUN
ajst-8015	127	23	.	.	PUNCT
ajst-8015	128	1	it	it	PRON
ajst-8015	128	2	is	be	AUX
ajst-8015	128	3	composed	compose	VERB
ajst-8015	128	4	of	of	ADP
ajst-8015	128	5	input	input	NOUN
ajst-8015	128	6	layer	layer	NOUN
ajst-8015	128	7	,	,	PUNCT
ajst-8015	128	8	convolutional	convolutional	ADJ
ajst-8015	128	9	layer	layer	NOUN
ajst-8015	128	10	,	,	PUNCT
ajst-8015	128	11	pooling	pool	VERB
ajst-8015	128	12	layer	layer	NOUN
ajst-8015	128	13	,	,	PUNCT
ajst-8015	128	14	full	full	ADJ
ajst-8015	128	15	connection	connection	NOUN
ajst-8015	128	16	layer	layer	NOUN
ajst-8015	128	17	and	and	CCONJ
ajst-8015	128	18	output	output	NOUN
ajst-8015	128	19	layer	layer	NOUN
ajst-8015	128	20	.	.	PUNCT
ajst-8015	129	1	the	the	DET
ajst-8015	129	2	basic	basic	ADJ
ajst-8015	129	3	results	result	NOUN
ajst-8015	129	4	are	be	AUX
ajst-8015	129	5	shown	show	VERB
ajst-8015	129	6	in	in	ADP
ajst-8015	129	7	figure	figure	NOUN
ajst-8015	129	8	2	2	NUM
ajst-8015	129	9	.	.	PUNCT
ajst-8015	129	10	class	class	NOUN
ajst-8015	129	11	input	input	NOUN
ajst-8015	129	12	convolution	convolution	NOUN
ajst-8015	129	13	 	 	SPACE
ajst-8015	129	14	layer	layer	NOUN
ajst-8015	129	15	pooling	pool	VERB
ajst-8015	129	16	full	full	ADJ
ajst-8015	129	17	 	 	SPACE
ajst-8015	129	18	connect	connect	NOUN
ajst-8015	129	19	 	 	SPACE
ajst-8015	129	20	layerpooling	layerpooling	ADJ
ajst-8015	129	21	outputconvolution	outputconvolution	NOUN
ajst-8015	129	22	 	 	SPACE
ajst-8015	129	23	layer	layer	NOUN
ajst-8015	129	24	figure	figure	NOUN
ajst-8015	129	25	2	2	NUM
ajst-8015	129	26	.	.	PUNCT
ajst-8015	129	27	convolutional	convolutional	ADJ
ajst-8015	129	28	neural	neural	ADJ
ajst-8015	129	29	network	network	NOUN
ajst-8015	129	30	structure	structure	NOUN
ajst-8015	129	31	wang	wang	PROPN
ajst-8015	129	32	et	et	PROPN
ajst-8015	129	33	al	al	PROPN
ajst-8015	129	34	.	.	PUNCT
ajst-8015	130	1	[	[	X
ajst-8015	130	2	33	33	NUM
ajst-8015	130	3	]	]	PUNCT
ajst-8015	130	4	used	use	VERB
ajst-8015	130	5	2d	2d	NUM
ajst-8015	130	6	sections	section	NOUN
ajst-8015	130	7	of	of	ADP
ajst-8015	130	8	mri	mri	NOUN
ajst-8015	130	9	as	as	SCONJ
ajst-8015	130	10	training	training	NOUN
ajst-8015	130	11	samples	sample	NOUN
ajst-8015	130	12	to	to	PART
ajst-8015	130	13	construct	construct	VERB
ajst-8015	130	14	an	an	DET
ajst-8015	130	15	8	8	NUM
ajst-8015	130	16	-	-	PUNCT
ajst-8015	130	17	layer	layer	NOUN
ajst-8015	130	18	cnn	cnn	PROPN
ajst-8015	130	19	model	model	NOUN
ajst-8015	130	20	to	to	PART
ajst-8015	130	21	achieve	achieve	VERB
ajst-8015	130	22	ad	ad	NOUN
ajst-8015	130	23	prediction	prediction	NOUN
ajst-8015	130	24	.	.	PUNCT
ajst-8015	131	1	due	due	ADP
ajst-8015	131	2	to	to	ADP
ajst-8015	131	3	the	the	DET
ajst-8015	131	4	small	small	ADJ
ajst-8015	131	5	number	number	NOUN
ajst-8015	131	6	of	of	ADP
ajst-8015	131	7	medical	medical	ADJ
ajst-8015	131	8	image	image	NOUN
ajst-8015	131	9	samples	sample	NOUN
ajst-8015	131	10	,	,	PUNCT
ajst-8015	131	11	the	the	DET
ajst-8015	131	12	training	training	NOUN
ajst-8015	131	13	effect	effect	NOUN
ajst-8015	131	14	of	of	ADP
ajst-8015	131	15	random	random	ADJ
ajst-8015	131	16	initialization	initialization	NOUN
ajst-8015	131	17	parameters	parameter	NOUN
ajst-8015	131	18	is	be	AUX
ajst-8015	131	19	generally	generally	ADV
ajst-8015	131	20	poor	poor	ADJ
ajst-8015	131	21	.	.	PUNCT
ajst-8015	132	1	therefore	therefore	ADV
ajst-8015	132	2	,	,	PUNCT
ajst-8015	132	3	liu	liu	PROPN
ajst-8015	132	4	et	et	PROPN
ajst-8015	132	5	al	al	PROPN
ajst-8015	132	6	.	.	PUNCT
ajst-8015	133	1	[	[	X
ajst-8015	133	2	34	34	NUM
ajst-8015	133	3	]	]	PUNCT
ajst-8015	133	4	firstly	firstly	ADV
ajst-8015	133	5	used	use	VERB
ajst-8015	133	6	the	the	DET
ajst-8015	133	7	large	large	ADJ
ajst-8015	133	8	-	-	PUNCT
ajst-8015	133	9	scale	scale	NOUN
ajst-8015	133	10	data	datum	NOUN
ajst-8015	133	11	set	set	VERB
ajst-8015	133	12	imagenet	imagenet	NOUN
ajst-8015	133	13	to	to	AUX
ajst-8015	133	14	pre	pre	VERB
ajst-8015	133	15	-	-	VERB
ajst-8015	133	16	train	train	VERB
ajst-8015	133	17	the	the	DET
ajst-8015	133	18	twodimensional	twodimensional	ADJ
ajst-8015	133	19	convolutional	convolutional	ADJ
ajst-8015	133	20	neural	neural	ADJ
ajst-8015	133	21	network	network	NOUN
ajst-8015	133	22	(	(	PUNCT
ajst-8015	133	23	2d	2d	NOUN
ajst-8015	133	24	-	-	PUNCT
ajst-8015	133	25	cnn	cnn	PROPN
ajst-8015	133	26	)	)	PUNCT
ajst-8015	133	27	model	model	NOUN
ajst-8015	133	28	,	,	PUNCT
ajst-8015	133	29	and	and	CCONJ
ajst-8015	133	30	used	use	VERB
ajst-8015	133	31	the	the	DET
ajst-8015	133	32	pre	pre	ADJ
ajst-8015	133	33	-	-	ADJ
ajst-8015	133	34	trained	train	VERB
ajst-8015	133	35	model	model	NOUN
ajst-8015	133	36	to	to	PART
ajst-8015	133	37	train	train	VERB
ajst-8015	133	38	mri	mri	NOUN
ajst-8015	133	39	images	image	NOUN
ajst-8015	133	40	.	.	PUNCT
ajst-8015	134	1	sarraf	sarraf	NOUN
ajst-8015	134	2	et	et	PROPN
ajst-8015	134	3	al	al	PROPN
ajst-8015	134	4	.	.	PUNCT
ajst-8015	135	1	[	[	X
ajst-8015	135	2	35	35	NUM
ajst-8015	135	3	]	]	PUNCT
ajst-8015	135	4	applied	apply	VERB
ajst-8015	135	5	lenet-5	lenet-5	NUM
ajst-8015	135	6	architecture	architecture	NOUN
ajst-8015	135	7	to	to	PART
ajst-8015	135	8	classify	classify	VERB
ajst-8015	135	9	fmri	fmri	ADJ
ajst-8015	135	10	data	datum	NOUN
ajst-8015	135	11	of	of	ADP
ajst-8015	135	12	ad	ad	NOUN
ajst-8015	135	13	and	and	CCONJ
ajst-8015	135	14	hc	hc	NOUN
ajst-8015	135	15	control	control	NOUN
ajst-8015	135	16	subjects	subject	NOUN
ajst-8015	135	17	,	,	PUNCT
ajst-8015	135	18	and	and	CCONJ
ajst-8015	135	19	the	the	DET
ajst-8015	135	20	classification	classification	NOUN
ajst-8015	135	21	accuracy	accuracy	NOUN
ajst-8015	135	22	reached	reach	VERB
ajst-8015	135	23	96.86	96.86	NUM
ajst-8015	135	24	%	%	NOUN
ajst-8015	135	25	.	.	PUNCT
ajst-8015	136	1	in	in	ADP
ajst-8015	136	2	addition	addition	NOUN
ajst-8015	136	3	,	,	PUNCT
ajst-8015	136	4	dai	dai	PROPN
ajst-8015	136	5	et	et	PROPN
ajst-8015	136	6	al	al	PROPN
ajst-8015	136	7	.	.	PUNCT
ajst-8015	137	1	[	[	X
ajst-8015	137	2	36]improved	36]improved	NUM
ajst-8015	137	3	the	the	DET
ajst-8015	137	4	existing	exist	VERB
ajst-8015	137	5	lenet-5	lenet-5	PROPN
ajst-8015	137	6	model	model	NOUN
ajst-8015	137	7	,	,	PUNCT
ajst-8015	137	8	designed	design	VERB
ajst-8015	137	9	a	a	DET
ajst-8015	137	10	10	10	NUM
ajst-8015	137	11	-	-	PUNCT
ajst-8015	137	12	layer	layer	NOUN
ajst-8015	137	13	cnn	cnn	NOUN
ajst-8015	137	14	,	,	PUNCT
ajst-8015	137	15	and	and	CCONJ
ajst-8015	137	16	conducted	conduct	VERB
ajst-8015	137	17	training	training	NOUN
ajst-8015	137	18	and	and	CCONJ
ajst-8015	137	19	testing	testing	NOUN
ajst-8015	137	20	on	on	ADP
ajst-8015	137	21	mri	mri	NOUN
ajst-8015	137	22	,	,	PUNCT
ajst-8015	137	23	pet	pet	ADJ
ajst-8015	137	24	and	and	CCONJ
ajst-8015	137	25	multi	multi	ADJ
ajst-8015	137	26	-	-	ADJ
ajst-8015	137	27	mode	mode	ADJ
ajst-8015	137	28	fusion	fusion	NOUN
ajst-8015	137	29	images	image	NOUN
ajst-8015	137	30	respectively	respectively	ADV
ajst-8015	137	31	.	.	PUNCT
ajst-8015	138	1	the	the	DET
ajst-8015	138	2	average	average	ADJ
ajst-8015	138	3	accuracy	accuracy	NOUN
ajst-8015	138	4	of	of	ADP
ajst-8015	138	5	clinical	clinical	ADJ
ajst-8015	138	6	mmse	mmse	ADJ
ajst-8015	138	7	classification	classification	NOUN
ajst-8015	138	8	results	result	NOUN
ajst-8015	138	9	combined	combine	VERB
ajst-8015	138	10	with	with	ADP
ajst-8015	138	11	bayesian	bayesian	NOUN
ajst-8015	138	12	method	method	NOUN
ajst-8015	138	13	at	at	ADP
ajst-8015	138	14	the	the	DET
ajst-8015	138	15	network	network	NOUN
ajst-8015	138	16	output	output	NOUN
ajst-8015	138	17	layer	layer	NOUN
ajst-8015	138	18	reached	reach	VERB
ajst-8015	138	19	88.244	88.244	NUM
ajst-8015	138	20	%	%	NOUN
ajst-8015	138	21	.	.	PUNCT
ajst-8015	139	1	shakarami	shakarami	PROPN
ajst-8015	139	2	et	et	PROPN
ajst-8015	139	3	al	al	PROPN
ajst-8015	139	4	.	.	PUNCT
ajst-8015	140	1	[	[	X
ajst-8015	140	2	37	37	NUM
ajst-8015	140	3	]	]	PUNCT
ajst-8015	140	4	added	add	VERB
ajst-8015	140	5	a	a	DET
ajst-8015	140	6	full	full	ADJ
ajst-8015	140	7	-	-	PUNCT
ajst-8015	140	8	connection	connection	NOUN
ajst-8015	140	9	layer	layer	NOUN
ajst-8015	140	10	to	to	ADP
ajst-8015	140	11	the	the	DET
ajst-8015	140	12	end	end	NOUN
ajst-8015	140	13	of	of	ADP
ajst-8015	140	14	alexnet	alexnet	NOUN
ajst-8015	140	15	to	to	PART
ajst-8015	140	16	reduce	reduce	VERB
ajst-8015	140	17	the	the	DET
ajst-8015	140	18	length	length	NOUN
ajst-8015	140	19	of	of	ADP
ajst-8015	140	20	feature	feature	NOUN
ajst-8015	140	21	vectors	vector	NOUN
ajst-8015	140	22	,	,	PUNCT
ajst-8015	140	23	and	and	CCONJ
ajst-8015	140	24	used	use	VERB
ajst-8015	140	25	support	support	NOUN
ajst-8015	140	26	vector	vector	NOUN
ajst-8015	140	27	218	218	NUM
ajst-8015	140	28	machine	machine	NOUN
ajst-8015	140	29	(	(	PUNCT
ajst-8015	140	30	svm	svm	PROPN
ajst-8015	140	31	)	)	PUNCT
ajst-8015	140	32	to	to	PART
ajst-8015	140	33	replace	replace	VERB
ajst-8015	140	34	the	the	DET
ajst-8015	140	35	original	original	ADJ
ajst-8015	140	36	classification	classification	NOUN
ajst-8015	140	37	output	output	NOUN
ajst-8015	140	38	layer	layer	NOUN
ajst-8015	140	39	as	as	ADP
ajst-8015	140	40	the	the	DET
ajst-8015	140	41	classifier	classifier	NOUN
ajst-8015	140	42	.	.	PUNCT
ajst-8015	141	1	the	the	DET
ajst-8015	141	2	average	average	ADJ
ajst-8015	141	3	classification	classification	NOUN
ajst-8015	141	4	accuracy	accuracy	NOUN
ajst-8015	141	5	reached	reach	VERB
ajst-8015	141	6	96.39	96.39	NUM
ajst-8015	141	7	%	%	NOUN
ajst-8015	141	8	.	.	PUNCT
ajst-8015	142	1	kazemi	kazemi	PROPN
ajst-8015	142	2	et	et	PROPN
ajst-8015	142	3	al	al	PROPN
ajst-8015	142	4	.	.	PUNCT
ajst-8015	143	1	[	[	X
ajst-8015	143	2	38	38	NUM
ajst-8015	143	3	]	]	PUNCT
ajst-8015	143	4	adopted	adopt	VERB
ajst-8015	143	5	alexnet	alexnet	ADJ
ajst-8015	143	6	model	model	NOUN
ajst-8015	143	7	,	,	PUNCT
ajst-8015	143	8	updated	update	VERB
ajst-8015	143	9	weights	weight	NOUN
ajst-8015	143	10	with	with	ADP
ajst-8015	143	11	stochastic	stochastic	ADJ
ajst-8015	143	12	gradient	gradient	ADJ
ajst-8015	143	13	descent	descent	NOUN
ajst-8015	143	14	solution	solution	NOUN
ajst-8015	143	15	,	,	PUNCT
ajst-8015	143	16	and	and	CCONJ
ajst-8015	143	17	used	use	VERB
ajst-8015	143	18	deep	deep	ADJ
ajst-8015	143	19	learning	learning	NOUN
ajst-8015	143	20	method	method	NOUN
ajst-8015	143	21	for	for	ADP
ajst-8015	143	22	the	the	DET
ajst-8015	143	23	first	first	ADJ
ajst-8015	143	24	time	time	NOUN
ajst-8015	143	25	to	to	PART
ajst-8015	143	26	classify	classify	VERB
ajst-8015	143	27	different	different	ADJ
ajst-8015	143	28	stages	stage	NOUN
ajst-8015	143	29	of	of	ADP
ajst-8015	143	30	ad	ad	NOUN
ajst-8015	143	31	,	,	PUNCT
ajst-8015	143	32	namely	namely	ADV
ajst-8015	143	33	normal	normal	ADJ
ajst-8015	143	34	healthy	healthy	ADJ
ajst-8015	143	35	control	control	NOUN
ajst-8015	143	36	(	(	PUNCT
ajst-8015	143	37	nc	nc	PROPN
ajst-8015	143	38	)	)	PUNCT
ajst-8015	143	39	,	,	PUNCT
ajst-8015	143	40	significant	significant	ADJ
ajst-8015	143	41	memory	memory	NOUN
ajst-8015	143	42	concern	concern	NOUN
ajst-8015	143	43	(	(	PUNCT
ajst-8015	143	44	smci	smci	NOUN
ajst-8015	143	45	)	)	PUNCT
ajst-8015	143	46	,	,	PUNCT
ajst-8015	143	47	early	early	ADJ
ajst-8015	143	48	mild	mild	ADJ
ajst-8015	143	49	cognitive	cognitive	ADJ
ajst-8015	143	50	impairment	impairment	NOUN
ajst-8015	143	51	(	(	PUNCT
ajst-8015	143	52	emci	emci	NOUN
ajst-8015	143	53	)	)	PUNCT
ajst-8015	143	54	,	,	PUNCT
ajst-8015	143	55	late	late	ADJ
ajst-8015	143	56	mild	mild	ADJ
ajst-8015	143	57	cognitive	cognitive	ADJ
ajst-8015	143	58	impairment	impairment	NOUN
ajst-8015	143	59	(	(	PUNCT
ajst-8015	143	60	lmci	lmci	NOUN
ajst-8015	143	61	)	)	PUNCT
ajst-8015	143	62	and	and	CCONJ
ajst-8015	143	63	ad	ad	NOUN
ajst-8015	143	64	.	.	PUNCT
ajst-8015	144	1	the	the	DET
ajst-8015	144	2	average	average	ADJ
ajst-8015	144	3	accuracy	accuracy	NOUN
ajst-8015	144	4	was	be	AUX
ajst-8015	144	5	97.63	97.63	NUM
ajst-8015	144	6	%	%	NOUN
ajst-8015	144	7	.	.	PUNCT
ajst-8015	145	1	hon	hon	PROPN
ajst-8015	145	2	et	et	PROPN
ajst-8015	145	3	al	al	PROPN
ajst-8015	145	4	.	.	PUNCT
ajst-8015	146	1	[	[	X
ajst-8015	146	2	39	39	NUM
ajst-8015	146	3	]	]	PUNCT
ajst-8015	146	4	selected	select	VERB
ajst-8015	146	5	information	information	NOUN
ajst-8015	146	6	-	-	PUNCT
ajst-8015	146	7	rich	rich	ADJ
ajst-8015	146	8	slices	slice	NOUN
ajst-8015	146	9	in	in	ADP
ajst-8015	146	10	mri	mri	NOUN
ajst-8015	146	11	by	by	ADP
ajst-8015	146	12	image	image	NOUN
ajst-8015	146	13	entropy	entropy	PROPN
ajst-8015	146	14	,	,	PUNCT
ajst-8015	146	15	adopted	adopt	VERB
ajst-8015	146	16	the	the	DET
ajst-8015	146	17	pre	pre	ADJ
ajst-8015	146	18	-	-	ADJ
ajst-8015	146	19	trained	train	VERB
ajst-8015	146	20	vgg	vgg	ADJ
ajst-8015	146	21	network	network	NOUN
ajst-8015	146	22	on	on	ADP
ajst-8015	146	23	a	a	DET
ajst-8015	146	24	large	large	ADJ
ajst-8015	146	25	-	-	PUNCT
ajst-8015	146	26	scale	scale	NOUN
ajst-8015	146	27	data	datum	NOUN
ajst-8015	146	28	set	set	VERB
ajst-8015	146	29	as	as	ADP
ajst-8015	146	30	a	a	DET
ajst-8015	146	31	classification	classification	NOUN
ajst-8015	146	32	model	model	NOUN
ajst-8015	146	33	,	,	PUNCT
ajst-8015	146	34	and	and	CCONJ
ajst-8015	146	35	realized	realize	VERB
ajst-8015	146	36	the	the	DET
ajst-8015	146	37	binary	binary	ADJ
ajst-8015	146	38	classification	classification	NOUN
ajst-8015	146	39	of	of	ADP
ajst-8015	146	40	ad	ad	NOUN
ajst-8015	146	41	and	and	CCONJ
ajst-8015	146	42	nc	nc	NOUN
ajst-8015	146	43	by	by	ADP
ajst-8015	146	44	modifying	modify	VERB
ajst-8015	146	45	the	the	DET
ajst-8015	146	46	number	number	NOUN
ajst-8015	146	47	of	of	ADP
ajst-8015	146	48	fully	fully	ADV
ajst-8015	146	49	connected	connected	ADJ
ajst-8015	146	50	output	output	NOUN
ajst-8015	146	51	nodes	node	NOUN
ajst-8015	146	52	of	of	ADP
ajst-8015	146	53	vgg	vgg	NOUN
ajst-8015	146	54	.	.	PUNCT
ajst-8015	147	1	ding	de	VERB
ajst-8015	147	2	et	et	PROPN
ajst-8015	147	3	al	al	PROPN
ajst-8015	147	4	.	.	PUNCT
ajst-8015	148	1	[	[	X
ajst-8015	148	2	40]selected	40]selected	NUM
ajst-8015	148	3	16	16	NUM
ajst-8015	148	4	slices	slice	NOUN
ajst-8015	148	5	of	of	ADP
ajst-8015	148	6	pet	pet	ADJ
ajst-8015	148	7	image	image	NOUN
ajst-8015	148	8	at	at	ADP
ajst-8015	148	9	equal	equal	ADJ
ajst-8015	148	10	intervals	interval	NOUN
ajst-8015	148	11	to	to	PART
ajst-8015	148	12	form	form	VERB
ajst-8015	148	13	a	a	DET
ajst-8015	148	14	4×4	4×4	NUM
ajst-8015	148	15	grid	grid	NOUN
ajst-8015	148	16	image	image	NOUN
ajst-8015	148	17	,	,	PUNCT
ajst-8015	148	18	used	use	VERB
ajst-8015	148	19	inception	inception	NOUN
ajst-8015	148	20	v3	v3	PROPN
ajst-8015	148	21	model	model	NOUN
ajst-8015	148	22	to	to	PART
ajst-8015	148	23	train	train	VERB
ajst-8015	148	24	the	the	DET
ajst-8015	148	25	grid	grid	NOUN
ajst-8015	148	26	image	image	NOUN
ajst-8015	148	27	,	,	PUNCT
ajst-8015	148	28	conducted	conduct	VERB
ajst-8015	148	29	training	training	NOUN
ajst-8015	148	30	on	on	ADP
ajst-8015	148	31	adni	adni	DET
ajst-8015	148	32	open	open	ADJ
ajst-8015	148	33	data	datum	NOUN
ajst-8015	148	34	set	set	VERB
ajst-8015	148	35	and	and	CCONJ
ajst-8015	148	36	tested	test	VERB
ajst-8015	148	37	on	on	ADP
ajst-8015	148	38	40	40	NUM
ajst-8015	148	39	outlier	outlier	NOUN
ajst-8015	148	40	independent	independent	ADJ
ajst-8015	148	41	test	test	NOUN
ajst-8015	148	42	sets	set	NOUN
ajst-8015	148	43	.	.	PUNCT
ajst-8015	149	1	the	the	DET
ajst-8015	149	2	results	result	NOUN
ajst-8015	149	3	showed	show	VERB
ajst-8015	149	4	that	that	SCONJ
ajst-8015	149	5	,	,	PUNCT
ajst-8015	149	6	ad	ad	NOUN
ajst-8015	149	7	was	be	AUX
ajst-8015	149	8	predicted	predict	VERB
ajst-8015	149	9	an	an	DET
ajst-8015	149	10	average	average	NOUN
ajst-8015	149	11	of	of	ADP
ajst-8015	149	12	75.8	75.8	NUM
ajst-8015	149	13	months	month	NOUN
ajst-8015	149	14	earlier	early	ADV
ajst-8015	149	15	than	than	ADP
ajst-8015	149	16	the	the	DET
ajst-8015	149	17	final	final	ADJ
ajst-8015	149	18	diagnosis	diagnosis	NOUN
ajst-8015	149	19	.	.	PUNCT
ajst-8015	150	1	yee	yee	PROPN
ajst-8015	150	2	et	et	PROPN
ajst-8015	150	3	al	al	PROPN
ajst-8015	150	4	.	.	PUNCT
ajst-8015	151	1	[	[	X
ajst-8015	151	2	41]used	41]use	VERB
ajst-8015	151	3	the	the	DET
ajst-8015	151	4	algorithm	algorithm	NOUN
ajst-8015	151	5	designed	design	VERB
ajst-8015	151	6	by	by	ADP
ajst-8015	151	7	residual	residual	ADJ
ajst-8015	151	8	structure	structure	NOUN
ajst-8015	151	9	in	in	ADP
ajst-8015	151	10	resnet	resnet	NOUN
ajst-8015	151	11	to	to	PART
ajst-8015	151	12	classify	classify	VERB
ajst-8015	151	13	nc	nc	PROPN
ajst-8015	151	14	and	and	CCONJ
ajst-8015	151	15	ad	ad	NOUN
ajst-8015	151	16	with	with	ADP
ajst-8015	151	17	an	an	DET
ajst-8015	151	18	accuracy	accuracy	NOUN
ajst-8015	151	19	of	of	ADP
ajst-8015	151	20	93.5	93.5	NUM
ajst-8015	151	21	%	%	NOUN
ajst-8015	151	22	.	.	PUNCT
ajst-8015	152	1	in	in	ADP
ajst-8015	152	2	addition	addition	NOUN
ajst-8015	152	3	,	,	PUNCT
ajst-8015	152	4	the	the	DET
ajst-8015	152	5	accuracy	accuracy	NOUN
ajst-8015	152	6	of	of	ADP
ajst-8015	152	7	predicting	predict	VERB
ajst-8015	152	8	the	the	DET
ajst-8015	152	9	conversion	conversion	NOUN
ajst-8015	152	10	of	of	ADP
ajst-8015	152	11	smci	smci	NOUN
ajst-8015	152	12	into	into	ADP
ajst-8015	152	13	ad	ad	NOUN
ajst-8015	152	14	within	within	ADP
ajst-8015	152	15	3	3	NUM
ajst-8015	152	16	years	year	NOUN
ajst-8015	152	17	was	be	AUX
ajst-8015	152	18	74.0	74.0	NUM
ajst-8015	152	19	%	%	NOUN
ajst-8015	152	20	,	,	PUNCT
ajst-8015	152	21	and	and	CCONJ
ajst-8015	152	22	the	the	DET
ajst-8015	152	23	decrease	decrease	NOUN
ajst-8015	152	24	of	of	ADP
ajst-8015	152	25	accuracy	accuracy	NOUN
ajst-8015	152	26	was	be	AUX
ajst-8015	152	27	mainly	mainly	ADV
ajst-8015	152	28	due	due	ADJ
ajst-8015	152	29	to	to	ADP
ajst-8015	152	30	the	the	DET
ajst-8015	152	31	misclassification	misclassification	NOUN
ajst-8015	152	32	of	of	ADP
ajst-8015	152	33	nc	nc	PROPN
ajst-8015	152	34	and	and	CCONJ
ajst-8015	152	35	smci	smci	NOUN
ajst-8015	152	36	.	.	PUNCT
ajst-8015	153	1	fulton	fulton	PROPN
ajst-8015	153	2	et	et	PROPN
ajst-8015	153	3	al	al	PROPN
ajst-8015	153	4	.	.	PUNCT
ajst-8015	154	1	[	[	X
ajst-8015	154	2	42	42	NUM
ajst-8015	154	3	]	]	PUNCT
ajst-8015	154	4	classified	classified	ADJ
ajst-8015	154	5	ad	ad	NOUN
ajst-8015	154	6	and	and	CCONJ
ajst-8015	154	7	mci	mci	NOUN
ajst-8015	154	8	in	in	ADP
ajst-8015	154	9	the	the	DET
ajst-8015	154	10	improved	improved	ADJ
ajst-8015	154	11	50	50	NUM
ajst-8015	154	12	-	-	PUNCT
ajst-8015	154	13	layer	layer	NOUN
ajst-8015	154	14	residual	residual	ADJ
ajst-8015	154	15	network	network	NOUN
ajst-8015	154	16	,	,	PUNCT
ajst-8015	154	17	namely	namely	ADV
ajst-8015	154	18	resnet50	resnet50	NOUN
ajst-8015	154	19	,	,	PUNCT
ajst-8015	154	20	and	and	CCONJ
ajst-8015	154	21	achieved	achieve	VERB
ajst-8015	154	22	a	a	DET
ajst-8015	154	23	classification	classification	NOUN
ajst-8015	154	24	accuracy	accuracy	NOUN
ajst-8015	154	25	of	of	ADP
ajst-8015	154	26	98.99	98.99	NUM
ajst-8015	154	27	%	%	NOUN
ajst-8015	154	28	.	.	PUNCT
ajst-8015	155	1	wang	wang	PROPN
ajst-8015	155	2	et	et	PROPN
ajst-8015	155	3	al	al	PROPN
ajst-8015	155	4	.	.	PUNCT
ajst-8015	156	1	[	[	X
ajst-8015	156	2	43	43	NUM
ajst-8015	156	3	]	]	PUNCT
ajst-8015	156	4	adopted	adopt	VERB
ajst-8015	156	5	the	the	DET
ajst-8015	156	6	densenet	densenet	NOUN
ajst-8015	156	7	model	model	NOUN
ajst-8015	156	8	on	on	ADP
ajst-8015	156	9	the	the	DET
ajst-8015	156	10	basis	basis	NOUN
ajst-8015	156	11	of	of	ADP
ajst-8015	156	12	3d	3d	NOUN
ajst-8015	156	13	-	-	PUNCT
ajst-8015	156	14	mri	mri	NOUN
ajst-8015	156	15	to	to	PART
ajst-8015	156	16	conduct	conduct	VERB
ajst-8015	156	17	a	a	DET
ajst-8015	156	18	series	series	NOUN
ajst-8015	156	19	of	of	ADP
ajst-8015	156	20	hyperparameter	hyperparameter	NOUN
ajst-8015	156	21	optimization	optimization	NOUN
ajst-8015	156	22	experiments	experiment	NOUN
ajst-8015	156	23	,	,	PUNCT
ajst-8015	156	24	select	select	ADJ
ajst-8015	156	25	several	several	ADJ
ajst-8015	156	26	optimized	optimize	VERB
ajst-8015	156	27	3ddensenet	3ddensenet	NUM
ajst-8015	156	28	classifiers	classifier	NOUN
ajst-8015	156	29	,	,	PUNCT
ajst-8015	156	30	and	and	CCONJ
ajst-8015	156	31	then	then	ADV
ajst-8015	156	32	integrate	integrate	VERB
ajst-8015	156	33	the	the	DET
ajst-8015	156	34	results	result	NOUN
ajst-8015	156	35	of	of	ADP
ajst-8015	156	36	each	each	DET
ajst-8015	156	37	classifier	classifier	NOUN
ajst-8015	156	38	,	,	PUNCT
ajst-8015	156	39	finally	finally	ADV
ajst-8015	156	40	proving	prove	VERB
ajst-8015	156	41	the	the	DET
ajst-8015	156	42	superiority	superiority	NOUN
ajst-8015	156	43	of	of	ADP
ajst-8015	156	44	the	the	DET
ajst-8015	156	45	integration	integration	NOUN
ajst-8015	156	46	method	method	NOUN
ajst-8015	156	47	.	.	PUNCT
ajst-8015	157	1	in	in	ADP
ajst-8015	157	2	the	the	DET
ajst-8015	157	3	study	study	NOUN
ajst-8015	157	4	of	of	ADP
ajst-8015	157	5	literature	literature	NOUN
ajst-8015	157	6	[	[	X
ajst-8015	157	7	44	44	NUM
ajst-8015	157	8	]	]	PUNCT
ajst-8015	157	9	,	,	PUNCT
ajst-8015	157	10	a	a	DET
ajst-8015	157	11	convolutional	convolutional	ADJ
ajst-8015	157	12	recursive	recursive	ADJ
ajst-8015	157	13	hybrid	hybrid	ADJ
ajst-8015	157	14	neural	neural	ADJ
ajst-8015	157	15	network	network	NOUN
ajst-8015	157	16	combining	combine	VERB
ajst-8015	157	17	3d	3d	NUM
ajst-8015	157	18	densenets	densenet	NOUN
ajst-8015	157	19	and	and	CCONJ
ajst-8015	157	20	bi	bi	ADJ
ajst-8015	157	21	-	-	ADJ
ajst-8015	157	22	directional	directional	ADJ
ajst-8015	157	23	gated	gate	VERB
ajst-8015	157	24	recurrent	recurrent	ADJ
ajst-8015	157	25	unit	unit	NOUN
ajst-8015	157	26	(	(	PUNCT
ajst-8015	157	27	bgru	bgru	NOUN
ajst-8015	157	28	)	)	PUNCT
ajst-8015	157	29	is	be	AUX
ajst-8015	157	30	proposed	propose	VERB
ajst-8015	157	31	.	.	PUNCT
ajst-8015	158	1	hippocampal	hippocampal	ADJ
ajst-8015	158	2	features	feature	NOUN
ajst-8015	158	3	were	be	AUX
ajst-8015	158	4	extracted	extract	VERB
ajst-8015	158	5	and	and	CCONJ
ajst-8015	158	6	analyzed	analyze	VERB
ajst-8015	158	7	by	by	ADP
ajst-8015	158	8	smri	smri	NOUN
ajst-8015	158	9	images	image	NOUN
ajst-8015	158	10	to	to	PART
ajst-8015	158	11	classify	classify	VERB
ajst-8015	158	12	and	and	CCONJ
ajst-8015	158	13	diagnose	diagnose	VERB
ajst-8015	158	14	the	the	DET
ajst-8015	158	15	course	course	NOUN
ajst-8015	158	16	of	of	ADP
ajst-8015	158	17	ad	ad	NOUN
ajst-8015	158	18	.	.	PUNCT
ajst-8015	159	1	in	in	ADP
ajst-8015	159	2	the	the	DET
ajst-8015	159	3	classification	classification	NOUN
ajst-8015	159	4	of	of	ADP
ajst-8015	159	5	ad	ad	NOUN
ajst-8015	159	6	and	and	CCONJ
ajst-8015	159	7	nc	nc	PROPN
ajst-8015	159	8	,	,	PUNCT
ajst-8015	159	9	mci	mci	PROPN
ajst-8015	159	10	and	and	CCONJ
ajst-8015	159	11	nc	nc	PROPN
ajst-8015	159	12	,	,	PUNCT
ajst-8015	159	13	pmci	pmci	VERB
ajst-8015	159	14	and	and	CCONJ
ajst-8015	159	15	smci	smci	VERB
ajst-8015	159	16	in	in	ADP
ajst-8015	159	17	adni	adni	ADJ
ajst-8015	159	18	data	datum	NOUN
ajst-8015	159	19	set	set	VERB
ajst-8015	159	20	,	,	PUNCT
ajst-8015	159	21	the	the	DET
ajst-8015	159	22	area	area	NOUN
ajst-8015	159	23	under	under	ADP
ajst-8015	159	24	roc	roc	PROPN
ajst-8015	159	25	curve	curve	NOUN
ajst-8015	159	26	reached	reach	VERB
ajst-8015	159	27	91.0	91.0	NUM
ajst-8015	159	28	%	%	NOUN
ajst-8015	159	29	,	,	PUNCT
ajst-8015	159	30	75.8	75.8	NUM
ajst-8015	159	31	%	%	NOUN
ajst-8015	159	32	and	and	CCONJ
ajst-8015	159	33	74.6	74.6	NUM
ajst-8015	159	34	%	%	NOUN
ajst-8015	159	35	,	,	PUNCT
ajst-8015	159	36	respectively	respectively	ADV
ajst-8015	159	37	.	.	PUNCT
ajst-8015	160	1	since	since	SCONJ
ajst-8015	160	2	the	the	DET
ajst-8015	160	3	brain	brain	NOUN
ajst-8015	160	4	image	image	NOUN
ajst-8015	160	5	is	be	AUX
ajst-8015	160	6	a	a	DET
ajst-8015	160	7	three	three	NUM
ajst-8015	160	8	-	-	PUNCT
ajst-8015	160	9	dimensional	dimensional	ADJ
ajst-8015	160	10	image	image	NOUN
ajst-8015	160	11	,	,	PUNCT
ajst-8015	160	12	2dcnn	2dcnn	NUM
ajst-8015	160	13	model	model	NOUN
ajst-8015	160	14	can	can	AUX
ajst-8015	160	15	not	not	PART
ajst-8015	160	16	fully	fully	ADV
ajst-8015	160	17	extract	extract	VERB
ajst-8015	160	18	the	the	DET
ajst-8015	160	19	features	feature	NOUN
ajst-8015	160	20	of	of	ADP
ajst-8015	160	21	each	each	DET
ajst-8015	160	22	dimension	dimension	NOUN
ajst-8015	160	23	.	.	PUNCT
ajst-8015	161	1	in	in	ADP
ajst-8015	161	2	order	order	NOUN
ajst-8015	161	3	to	to	PART
ajst-8015	161	4	solve	solve	VERB
ajst-8015	161	5	this	this	DET
ajst-8015	161	6	problem	problem	NOUN
ajst-8015	161	7	,	,	PUNCT
ajst-8015	161	8	liu	liu	PROPN
ajst-8015	161	9	et	et	PROPN
ajst-8015	161	10	al	al	PROPN
ajst-8015	161	11	.	.	PUNCT
ajst-8015	162	1	[	[	X
ajst-8015	162	2	45	45	NUM
ajst-8015	162	3	]	]	PUNCT
ajst-8015	162	4	proposed	propose	VERB
ajst-8015	162	5	a	a	DET
ajst-8015	162	6	classification	classification	NOUN
ajst-8015	162	7	model	model	NOUN
ajst-8015	162	8	based	base	VERB
ajst-8015	162	9	on	on	ADP
ajst-8015	162	10	cnn	cnn	PROPN
ajst-8015	162	11	and	and	CCONJ
ajst-8015	162	12	recurrent	recurrent	ADJ
ajst-8015	162	13	neural	neural	ADJ
ajst-8015	162	14	network	network	NOUN
ajst-8015	162	15	(	(	PUNCT
ajst-8015	162	16	rnn	rnn	PROPN
ajst-8015	162	17	)	)	PUNCT
ajst-8015	162	18	and	and	CCONJ
ajst-8015	162	19	extracted	extract	VERB
ajst-8015	162	20	the	the	DET
ajst-8015	162	21	internal	internal	ADJ
ajst-8015	162	22	features	feature	NOUN
ajst-8015	162	23	of	of	ADP
ajst-8015	162	24	slices	slice	NOUN
ajst-8015	162	25	through	through	ADP
ajst-8015	162	26	2d	2d	PROPN
ajst-8015	162	27	-	-	PUNCT
ajst-8015	162	28	cnn	cnn	PROPN
ajst-8015	162	29	.	.	PUNCT
ajst-8015	163	1	bidirectional	bidirectional	ADJ
ajst-8015	163	2	recursive	recursive	ADJ
ajst-8015	163	3	neural	neural	ADJ
ajst-8015	163	4	network	network	NOUN
ajst-8015	163	5	(	(	PUNCT
ajst-8015	163	6	bgru	bgru	NOUN
ajst-8015	163	7	)	)	PUNCT
ajst-8015	163	8	was	be	AUX
ajst-8015	163	9	used	use	VERB
ajst-8015	163	10	to	to	PART
ajst-8015	163	11	extract	extract	VERB
ajst-8015	163	12	the	the	DET
ajst-8015	163	13	features	feature	NOUN
ajst-8015	163	14	between	between	ADP
ajst-8015	163	15	slices	slice	NOUN
ajst-8015	163	16	.	.	PUNCT
ajst-8015	164	1	finally	finally	ADV
ajst-8015	164	2	,	,	PUNCT
ajst-8015	164	3	the	the	DET
ajst-8015	164	4	classification	classification	NOUN
ajst-8015	164	5	was	be	AUX
ajst-8015	164	6	realized	realize	VERB
ajst-8015	164	7	by	by	ADP
ajst-8015	164	8	multi	multi	ADJ
ajst-8015	164	9	-	-	ADJ
ajst-8015	164	10	layer	layer	ADJ
ajst-8015	164	11	perceptron	perceptron	PROPN
ajst-8015	164	12	.	.	PUNCT
ajst-8015	165	1	li	li	PROPN
ajst-8015	165	2	et	et	PROPN
ajst-8015	165	3	al	al	PROPN
ajst-8015	165	4	.	.	PUNCT
ajst-8015	166	1	[	[	X
ajst-8015	166	2	46]proposed	46]proposed	NUM
ajst-8015	166	3	to	to	PART
ajst-8015	166	4	directly	directly	ADV
ajst-8015	166	5	construct	construct	VERB
ajst-8015	166	6	a	a	DET
ajst-8015	166	7	threedimensional	threedimensional	ADJ
ajst-8015	166	8	convolutional	convolutional	ADJ
ajst-8015	166	9	neural	neural	ADJ
ajst-8015	166	10	network	network	NOUN
ajst-8015	166	11	(	(	PUNCT
ajst-8015	166	12	3d	3d	PROPN
ajst-8015	166	13	-	-	PUNCT
ajst-8015	166	14	cnn	cnn	NOUN
ajst-8015	166	15	)	)	PUNCT
ajst-8015	166	16	model	model	NOUN
ajst-8015	166	17	to	to	PART
ajst-8015	166	18	fully	fully	ADV
ajst-8015	166	19	extract	extract	VERB
ajst-8015	166	20	information	information	NOUN
ajst-8015	166	21	of	of	ADP
ajst-8015	166	22	various	various	ADJ
ajst-8015	166	23	dimensions	dimension	NOUN
ajst-8015	166	24	,	,	PUNCT
ajst-8015	166	25	extract	extract	VERB
ajst-8015	166	26	features	feature	NOUN
ajst-8015	166	27	from	from	ADP
ajst-8015	166	28	mri	mri	NOUN
ajst-8015	166	29	gray	gray	ADJ
ajst-8015	166	30	matter	matter	NOUN
ajst-8015	166	31	(	(	PUNCT
ajst-8015	166	32	gm	gm	PROPN
ajst-8015	166	33	)	)	PUNCT
ajst-8015	166	34	density	density	NOUN
ajst-8015	166	35	map	map	NOUN
ajst-8015	166	36	and	and	CCONJ
ajst-8015	166	37	pet	pet	ADJ
ajst-8015	166	38	image	image	NOUN
ajst-8015	166	39	,	,	PUNCT
ajst-8015	166	40	and	and	CCONJ
ajst-8015	166	41	train	train	VERB
ajst-8015	166	42	the	the	DET
ajst-8015	166	43	extracted	extract	VERB
ajst-8015	166	44	features	feature	NOUN
ajst-8015	166	45	through	through	ADP
ajst-8015	166	46	sparse	sparse	ADJ
ajst-8015	166	47	regression	regression	NOUN
ajst-8015	166	48	classifiers	classifier	NOUN
ajst-8015	166	49	to	to	PART
ajst-8015	166	50	achieve	achieve	VERB
ajst-8015	166	51	ad	ad	NOUN
ajst-8015	166	52	prediction	prediction	NOUN
ajst-8015	166	53	.	.	PUNCT
ajst-8015	167	1	hosseini	hosseini	PROPN
ajst-8015	167	2	-	-	PUNCT
ajst-8015	167	3	asl	asl	PROPN
ajst-8015	167	4	et	et	NOUN
ajst-8015	167	5	al	al	PROPN
ajst-8015	167	6	.	.	PUNCT
ajst-8015	168	1	[	[	X
ajst-8015	168	2	47	47	NUM
ajst-8015	168	3	]	]	PUNCT
ajst-8015	168	4	constructed	construct	VERB
ajst-8015	168	5	a	a	DET
ajst-8015	168	6	3d	3d	NUM
ajst-8015	168	7	autoencoder	autoencoder	NOUN
ajst-8015	168	8	to	to	PART
ajst-8015	168	9	capture	capture	VERB
ajst-8015	168	10	mri	mri	VERB
ajst-8015	168	11	anatomical	anatomical	ADJ
ajst-8015	168	12	shape	shape	NOUN
ajst-8015	168	13	changes	change	NOUN
ajst-8015	168	14	,	,	PUNCT
ajst-8015	168	15	and	and	CCONJ
ajst-8015	168	16	then	then	ADV
ajst-8015	168	17	modified	modify	VERB
ajst-8015	168	18	the	the	DET
ajst-8015	168	19	pre	pre	ADJ
ajst-8015	168	20	-	-	ADJ
ajst-8015	168	21	trained	train	VERB
ajst-8015	168	22	autoencoder	autoencoder	NOUN
ajst-8015	168	23	into	into	ADP
ajst-8015	168	24	a	a	DET
ajst-8015	168	25	3d	3d	NUM
ajst-8015	168	26	-	-	PUNCT
ajst-8015	168	27	cnn	cnn	PROPN
ajst-8015	168	28	model	model	NOUN
ajst-8015	168	29	to	to	PART
ajst-8015	168	30	achieve	achieve	VERB
ajst-8015	168	31	the	the	DET
ajst-8015	168	32	final	final	ADJ
ajst-8015	168	33	classification	classification	NOUN
ajst-8015	168	34	.	.	PUNCT
ajst-8015	169	1	huang	huang	PROPN
ajst-8015	169	2	et	et	PROPN
ajst-8015	169	3	al	al	PROPN
ajst-8015	169	4	.	.	PUNCT
ajst-8015	170	1	[	[	X
ajst-8015	170	2	48	48	NUM
ajst-8015	170	3	]	]	PUNCT
ajst-8015	170	4	,	,	PUNCT
ajst-8015	170	5	referring	refer	VERB
ajst-8015	170	6	to	to	ADP
ajst-8015	170	7	the	the	DET
ajst-8015	170	8	idea	idea	NOUN
ajst-8015	170	9	of	of	ADP
ajst-8015	170	10	vgg	vgg	NOUN
ajst-8015	170	11	,	,	PUNCT
ajst-8015	170	12	designed	design	VERB
ajst-8015	170	13	a	a	DET
ajst-8015	170	14	variant	variant	ADJ
ajst-8015	170	15	model	model	NOUN
ajst-8015	170	16	of	of	ADP
ajst-8015	170	17	3dvgg	3dvgg	NUM
ajst-8015	170	18	for	for	ADP
ajst-8015	170	19	single	single	ADJ
ajst-8015	170	20	mode	mode	NOUN
ajst-8015	170	21	.	.	PUNCT
ajst-8015	171	1	they	they	PRON
ajst-8015	171	2	conducted	conduct	VERB
ajst-8015	171	3	experiments	experiment	NOUN
ajst-8015	171	4	based	base	VERB
ajst-8015	171	5	on	on	ADP
ajst-8015	171	6	mri	mri	NOUN
ajst-8015	171	7	and	and	CCONJ
ajst-8015	171	8	pet	pet	ADJ
ajst-8015	171	9	images	image	NOUN
ajst-8015	171	10	respectively	respectively	ADV
ajst-8015	171	11	,	,	PUNCT
ajst-8015	171	12	and	and	CCONJ
ajst-8015	171	13	realized	realize	VERB
ajst-8015	171	14	multi	multi	ADJ
ajst-8015	171	15	-	-	ADJ
ajst-8015	171	16	mode	mode	ADJ
ajst-8015	171	17	prediction	prediction	NOUN
ajst-8015	171	18	through	through	ADP
ajst-8015	171	19	feature	feature	NOUN
ajst-8015	171	20	fusion	fusion	NOUN
ajst-8015	171	21	.	.	PUNCT
ajst-8015	172	1	the	the	DET
ajst-8015	172	2	results	result	NOUN
ajst-8015	172	3	show	show	VERB
ajst-8015	172	4	that	that	SCONJ
ajst-8015	172	5	the	the	DET
ajst-8015	172	6	best	good	ADJ
ajst-8015	172	7	results	result	NOUN
ajst-8015	172	8	can	can	AUX
ajst-8015	172	9	be	be	AUX
ajst-8015	172	10	obtained	obtain	VERB
ajst-8015	172	11	with	with	ADP
ajst-8015	172	12	full	full	ADJ
ajst-8015	172	13	image	image	NOUN
ajst-8015	172	14	input	input	NOUN
ajst-8015	172	15	,	,	PUNCT
ajst-8015	172	16	which	which	PRON
ajst-8015	172	17	proves	prove	VERB
ajst-8015	172	18	that	that	SCONJ
ajst-8015	172	19	the	the	DET
ajst-8015	172	20	segmentation	segmentation	NOUN
ajst-8015	172	21	of	of	ADP
ajst-8015	172	22	key	key	ADJ
ajst-8015	172	23	parts	part	NOUN
ajst-8015	172	24	is	be	AUX
ajst-8015	172	25	not	not	PART
ajst-8015	172	26	a	a	DET
ajst-8015	172	27	prerequisite	prerequisite	NOUN
ajst-8015	172	28	for	for	ADP
ajst-8015	172	29	classification	classification	NOUN
ajst-8015	172	30	based	base	VERB
ajst-8015	172	31	on	on	ADP
ajst-8015	172	32	cnn	cnn	PROPN
ajst-8015	172	33	.	.	PUNCT
ajst-8015	173	1	liu	liu	PROPN
ajst-8015	173	2	et	et	PROPN
ajst-8015	173	3	al	al	PROPN
ajst-8015	173	4	.	.	PUNCT
ajst-8015	174	1	[	[	X
ajst-8015	174	2	49]proposed	49]propose	VERB
ajst-8015	174	3	a	a	DET
ajst-8015	174	4	3dcnn	3dcnn	NUM
ajst-8015	174	5	model	model	NOUN
ajst-8015	174	6	based	base	VERB
ajst-8015	174	7	on	on	ADP
ajst-8015	174	8	mri	mri	NOUN
ajst-8015	174	9	to	to	PART
ajst-8015	174	10	achieve	achieve	VERB
ajst-8015	174	11	three	three	NUM
ajst-8015	174	12	classifications	classification	NOUN
ajst-8015	174	13	,	,	PUNCT
ajst-8015	174	14	and	and	CCONJ
ajst-8015	174	15	integrated	integrate	VERB
ajst-8015	174	16	the	the	DET
ajst-8015	174	17	age	age	NOUN
ajst-8015	174	18	information	information	NOUN
ajst-8015	174	19	of	of	ADP
ajst-8015	174	20	patients	patient	NOUN
ajst-8015	174	21	into	into	ADP
ajst-8015	174	22	the	the	DET
ajst-8015	174	23	model	model	NOUN
ajst-8015	174	24	,	,	PUNCT
ajst-8015	174	25	further	far	ADV
ajst-8015	174	26	improving	improve	VERB
ajst-8015	174	27	the	the	DET
ajst-8015	174	28	prediction	prediction	NOUN
ajst-8015	174	29	accuracy	accuracy	NOUN
ajst-8015	174	30	.	.	PUNCT
ajst-8015	175	1	2.2.2	2.2.2	X
ajst-8015	175	2	.	.	PUNCT
ajst-8015	175	3	ad	ad	NOUN
ajst-8015	175	4	classification	classification	NOUN
ajst-8015	175	5	based	base	VERB
ajst-8015	175	6	on	on	ADP
ajst-8015	175	7	gcn	gcn	NOUN
ajst-8015	175	8	similar	similar	ADJ
ajst-8015	175	9	to	to	ADP
ajst-8015	175	10	two	two	NUM
ajst-8015	175	11	-	-	PUNCT
ajst-8015	175	12	dimensional	dimensional	ADJ
ajst-8015	175	13	convolution	convolution	NOUN
ajst-8015	175	14	,	,	PUNCT
ajst-8015	175	15	gcns	gcns	PROPN
ajst-8015	175	16	also	also	ADV
ajst-8015	175	17	carries	carry	VERB
ajst-8015	175	18	out	out	ADP
ajst-8015	175	19	sliding	slide	VERB
ajst-8015	175	20	calculation	calculation	NOUN
ajst-8015	175	21	through	through	ADP
ajst-8015	175	22	convolution	convolution	NOUN
ajst-8015	175	23	check	check	NOUN
ajst-8015	175	24	of	of	ADP
ajst-8015	175	25	input	input	NOUN
ajst-8015	175	26	data	datum	NOUN
ajst-8015	175	27	.	.	PUNCT
ajst-8015	176	1	this	this	DET
ajst-8015	176	2	kind	kind	NOUN
ajst-8015	176	3	of	of	ADP
ajst-8015	176	4	model	model	NOUN
ajst-8015	176	5	regards	regard	VERB
ajst-8015	176	6	each	each	DET
ajst-8015	176	7	node	node	NOUN
ajst-8015	176	8	in	in	ADP
ajst-8015	176	9	the	the	DET
ajst-8015	176	10	graph	graph	NOUN
ajst-8015	176	11	structure	structure	NOUN
ajst-8015	176	12	as	as	ADP
ajst-8015	176	13	a	a	DET
ajst-8015	176	14	point	point	NOUN
ajst-8015	176	15	in	in	ADP
ajst-8015	176	16	euclidean	euclidean	ADJ
ajst-8015	176	17	space	space	NOUN
ajst-8015	176	18	,	,	PUNCT
ajst-8015	176	19	and	and	CCONJ
ajst-8015	176	20	updates	update	VERB
ajst-8015	176	21	the	the	DET
ajst-8015	176	22	node	node	ADJ
ajst-8015	176	23	representation	representation	NOUN
ajst-8015	176	24	by	by	ADP
ajst-8015	176	25	carrying	carry	VERB
ajst-8015	176	26	out	out	ADP
ajst-8015	176	27	convolution	convolution	NOUN
ajst-8015	176	28	operations	operation	NOUN
ajst-8015	176	29	around	around	ADP
ajst-8015	176	30	this	this	DET
ajst-8015	176	31	point	point	NOUN
ajst-8015	176	32	.	.	PUNCT
ajst-8015	177	1	as	as	SCONJ
ajst-8015	177	2	shown	show	VERB
ajst-8015	177	3	in	in	ADP
ajst-8015	177	4	figure	figure	NOUN
ajst-8015	177	5	3	3	NUM
ajst-8015	177	6	,	,	PUNCT
ajst-8015	177	7	the	the	DET
ajst-8015	177	8	convolution	convolution	NOUN
ajst-8015	177	9	kernel	kernel	NOUN
ajst-8015	177	10	of	of	ADP
ajst-8015	177	11	traditional	traditional	ADJ
ajst-8015	177	12	two	two	NUM
ajst-8015	177	13	-	-	PUNCT
ajst-8015	177	14	dimensional	dimensional	ADJ
ajst-8015	177	15	convolution	convolution	NOUN
ajst-8015	177	16	is	be	AUX
ajst-8015	177	17	a	a	DET
ajst-8015	177	18	matrix	matrix	NOUN
ajst-8015	177	19	,	,	PUNCT
ajst-8015	177	20	which	which	PRON
ajst-8015	177	21	slides	slide	VERB
ajst-8015	177	22	on	on	ADP
ajst-8015	177	23	the	the	DET
ajst-8015	177	24	input	input	NOUN
ajst-8015	177	25	data	datum	NOUN
ajst-8015	177	26	at	at	ADP
ajst-8015	177	27	a	a	DET
ajst-8015	177	28	fixed	fix	VERB
ajst-8015	177	29	stride	stride	NOUN
ajst-8015	177	30	and	and	CCONJ
ajst-8015	177	31	calculates	calculate	VERB
ajst-8015	177	32	the	the	DET
ajst-8015	177	33	output	output	NOUN
ajst-8015	177	34	value	value	NOUN
ajst-8015	177	35	through	through	ADP
ajst-8015	177	36	convolution	convolution	NOUN
ajst-8015	177	37	operation	operation	NOUN
ajst-8015	177	38	.	.	PUNCT
ajst-8015	178	1	the	the	DET
ajst-8015	178	2	shape	shape	NOUN
ajst-8015	178	3	and	and	CCONJ
ajst-8015	178	4	size	size	NOUN
ajst-8015	178	5	of	of	ADP
ajst-8015	178	6	convolution	convolution	NOUN
ajst-8015	178	7	kernel	kernel	PROPN
ajst-8015	178	8	window	window	NOUN
ajst-8015	178	9	of	of	ADP
ajst-8015	178	10	gcns	gcns	PROPN
ajst-8015	178	11	based	base	VERB
ajst-8015	178	12	on	on	ADP
ajst-8015	178	13	spatial	spatial	ADJ
ajst-8015	178	14	domain	domain	NOUN
ajst-8015	178	15	are	be	AUX
ajst-8015	178	16	dynamic	dynamic	ADJ
ajst-8015	178	17	.	.	PUNCT
ajst-8015	179	1	it	it	PRON
ajst-8015	179	2	is	be	AUX
ajst-8015	179	3	based	base	VERB
ajst-8015	179	4	on	on	ADP
ajst-8015	179	5	adjacency	adjacency	NOUN
ajst-8015	179	6	matrix	matrix	NOUN
ajst-8015	179	7	of	of	ADP
ajst-8015	179	8	graph	graph	NOUN
ajst-8015	179	9	structure	structure	NOUN
ajst-8015	179	10	,	,	PUNCT
ajst-8015	179	11	and	and	CCONJ
ajst-8015	179	12	adaptively	adaptively	ADV
ajst-8015	179	13	adjusts	adjust	VERB
ajst-8015	179	14	convolution	convolution	NOUN
ajst-8015	179	15	kernel	kernel	NOUN
ajst-8015	179	16	according	accord	VERB
ajst-8015	179	17	to	to	ADP
ajst-8015	179	18	geometric	geometric	ADJ
ajst-8015	179	19	relation	relation	NOUN
ajst-8015	179	20	between	between	ADP
ajst-8015	179	21	nodes	node	NOUN
ajst-8015	179	22	.	.	PUNCT
ajst-8015	180	1	zhao	zhao	PROPN
ajst-8015	180	2	et	et	PROPN
ajst-8015	180	3	al	al	PROPN
ajst-8015	180	4	.	.	PUNCT
ajst-8015	181	1	[	[	X
ajst-8015	181	2	50	50	NUM
ajst-8015	181	3	]	]	PUNCT
ajst-8015	181	4	firstly	firstly	ADV
ajst-8015	181	5	extracted	extract	VERB
ajst-8015	181	6	the	the	DET
ajst-8015	181	7	functional	functional	ADJ
ajst-8015	181	8	connection	connection	NOUN
ajst-8015	181	9	coefficient	coefficient	NOUN
ajst-8015	181	10	matrix	matrix	NOUN
ajst-8015	181	11	from	from	ADP
ajst-8015	181	12	the	the	DET
ajst-8015	181	13	brain	brain	NOUN
ajst-8015	181	14	functional	functional	ADJ
ajst-8015	181	15	connection	connection	NOUN
ajst-8015	181	16	of	of	ADP
ajst-8015	181	17	rsmri	rsmri	ADJ
ajst-8015	181	18	images	image	NOUN
ajst-8015	181	19	,	,	PUNCT
ajst-8015	181	20	and	and	CCONJ
ajst-8015	181	21	each	each	DET
ajst-8015	181	22	matrix	matrix	NOUN
ajst-8015	181	23	was	be	AUX
ajst-8015	181	24	combined	combine	VERB
ajst-8015	181	25	with	with	ADP
ajst-8015	181	26	the	the	DET
ajst-8015	181	27	subject	subject	NOUN
ajst-8015	181	28	's	's	PART
ajst-8015	181	29	gender	gender	NOUN
ajst-8015	181	30	,	,	PUNCT
ajst-8015	181	31	scanning	scan	VERB
ajst-8015	181	32	device	device	NOUN
ajst-8015	181	33	information	information	NOUN
ajst-8015	181	34	and	and	CCONJ
ajst-8015	181	35	label	label	NOUN
ajst-8015	181	36	to	to	PART
ajst-8015	181	37	generate	generate	VERB
ajst-8015	181	38	the	the	DET
ajst-8015	181	39	subject	subject	NOUN
ajst-8015	181	40	vector	vector	NOUN
ajst-8015	181	41	.	.	PUNCT
ajst-8015	182	1	then	then	ADV
ajst-8015	182	2	,	,	PUNCT
ajst-8015	182	3	each	each	DET
ajst-8015	182	4	subject	subject	NOUN
ajst-8015	182	5	vector	vector	NOUN
ajst-8015	182	6	was	be	AUX
ajst-8015	182	7	taken	take	VERB
ajst-8015	182	8	as	as	ADP
ajst-8015	182	9	the	the	DET
ajst-8015	182	10	vertex	vertex	NOUN
ajst-8015	182	11	,	,	PUNCT
ajst-8015	182	12	and	and	CCONJ
ajst-8015	182	13	the	the	DET
ajst-8015	182	14	similarity	similarity	NOUN
ajst-8015	182	15	between	between	ADP
ajst-8015	182	16	nodes	node	NOUN
ajst-8015	182	17	was	be	AUX
ajst-8015	182	18	taken	take	VERB
ajst-8015	182	19	as	as	ADP
ajst-8015	182	20	the	the	DET
ajst-8015	182	21	edge	edge	NOUN
ajst-8015	182	22	.	.	PUNCT
ajst-8015	183	1	finally	finally	ADV
ajst-8015	183	2	,	,	PUNCT
ajst-8015	183	3	ad	ad	NOUN
ajst-8015	183	4	prediction	prediction	NOUN
ajst-8015	183	5	was	be	AUX
ajst-8015	183	6	completed	complete	VERB
ajst-8015	183	7	through	through	ADP
ajst-8015	183	8	node	node	ADJ
ajst-8015	183	9	classification	classification	NOUN
ajst-8015	183	10	.	.	PUNCT
ajst-8015	184	1	guo[51	guo[51	PUNCT
ajst-8015	184	2	]	]	PUNCT
ajst-8015	184	3	takes	take	VERB
ajst-8015	184	4	the	the	DET
ajst-8015	184	5	region	region	NOUN
ajst-8015	184	6	of	of	ADP
ajst-8015	184	7	interest	interest	NOUN
ajst-8015	184	8	(	(	PUNCT
ajst-8015	184	9	roi	roi	NOUN
ajst-8015	184	10	)	)	PUNCT
ajst-8015	184	11	as	as	ADP
ajst-8015	184	12	the	the	DET
ajst-8015	184	13	vertex	vertex	NOUN
ajst-8015	184	14	,	,	PUNCT
ajst-8015	184	15	calculates	calculate	VERB
ajst-8015	184	16	the	the	DET
ajst-8015	184	17	similarity	similarity	NOUN
ajst-8015	184	18	of	of	ADP
ajst-8015	184	19	the	the	DET
ajst-8015	184	20	data	datum	NOUN
ajst-8015	184	21	in	in	ADP
ajst-8015	184	22	the	the	DET
ajst-8015	184	23	roi	roi	NOUN
ajst-8015	184	24	region	region	NOUN
ajst-8015	184	25	,	,	PUNCT
ajst-8015	184	26	then	then	ADV
ajst-8015	184	27	converts	convert	VERB
ajst-8015	184	28	each	each	DET
ajst-8015	184	29	mri	mri	NOUN
ajst-8015	184	30	image	image	NOUN
ajst-8015	184	31	into	into	ADP
ajst-8015	184	32	a	a	DET
ajst-8015	184	33	graph	graph	NOUN
ajst-8015	184	34	,	,	PUNCT
ajst-8015	184	35	and	and	CCONJ
ajst-8015	184	36	finally	finally	ADV
ajst-8015	184	37	realizes	realize	VERB
ajst-8015	184	38	the	the	DET
ajst-8015	184	39	purpose	purpose	NOUN
ajst-8015	184	40	of	of	ADP
ajst-8015	184	41	predicting	predict	VERB
ajst-8015	184	42	ad	ad	NOUN
ajst-8015	184	43	through	through	ADP
ajst-8015	184	44	graph	graph	NOUN
ajst-8015	184	45	classification	classification	NOUN
ajst-8015	184	46	.	.	PUNCT
ajst-8015	185	1	(	(	PUNCT
ajst-8015	185	2	a)convolution	a)convolution	NOUN
ajst-8015	185	3	neural	neural	ADJ
ajst-8015	185	4	network	network	NOUN
ajst-8015	185	5	(	(	PUNCT
ajst-8015	185	6	b)graph	b)graph	PROPN
ajst-8015	185	7	convolution	convolution	NOUN
ajst-8015	185	8	network	network	NOUN
ajst-8015	185	9	figure	figure	NOUN
ajst-8015	185	10	3	3	NUM
ajst-8015	185	11	.	.	NOUN
ajst-8015	185	12	comparison	comparison	NOUN
ajst-8015	185	13	between	between	ADP
ajst-8015	185	14	cnn	cnn	PROPN
ajst-8015	185	15	and	and	CCONJ
ajst-8015	185	16	gcn	gcn	PROPN
ajst-8015	185	17	parisot	parisot	PROPN
ajst-8015	185	18	et	et	PROPN
ajst-8015	185	19	al	al	PROPN
ajst-8015	185	20	.	.	PUNCT
ajst-8015	186	1	[	[	X
ajst-8015	186	2	52	52	NUM
ajst-8015	186	3	]	]	PUNCT
ajst-8015	186	4	used	use	VERB
ajst-8015	186	5	mtfs	mtfs	PROPN
ajst-8015	186	6	-	-	NOUN
ajst-8015	186	7	glasso	glasso	NOUN
ajst-8015	186	8	to	to	PART
ajst-8015	186	9	fuse	fuse	VERB
ajst-8015	186	10	the	the	DET
ajst-8015	186	11	brain	brain	NOUN
ajst-8015	186	12	structure	structure	NOUN
ajst-8015	186	13	and	and	CCONJ
ajst-8015	186	14	functional	functional	ADJ
ajst-8015	186	15	network	network	NOUN
ajst-8015	186	16	features	feature	VERB
ajst-8015	186	17	into	into	ADP
ajst-8015	186	18	a	a	DET
ajst-8015	186	19	vector	vector	NOUN
ajst-8015	186	20	with	with	ADP
ajst-8015	186	21	dimension	dimension	NOUN
ajst-8015	186	22	90	90	NUM
ajst-8015	186	23	.	.	PUNCT
ajst-8015	187	1	taking	take	VERB
ajst-8015	187	2	this	this	DET
ajst-8015	187	3	vector	vector	NOUN
ajst-8015	187	4	as	as	ADP
ajst-8015	187	5	the	the	DET
ajst-8015	187	6	vertex	vertex	NOUN
ajst-8015	187	7	,	,	PUNCT
ajst-8015	187	8	phenotypic	phenotypic	ADJ
ajst-8015	187	9	information	information	NOUN
ajst-8015	187	10	of	of	ADP
ajst-8015	187	11	subjects	subject	NOUN
ajst-8015	187	12	(	(	PUNCT
ajst-8015	187	13	gender	gender	NOUN
ajst-8015	187	14	,	,	PUNCT
ajst-8015	187	15	age	age	NOUN
ajst-8015	187	16	,	,	PUNCT
ajst-8015	187	17	imaging	imaging	NOUN
ajst-8015	187	18	equipment	equipment	NOUN
ajst-8015	187	19	)	)	PUNCT
ajst-8015	187	20	was	be	AUX
ajst-8015	187	21	219	219	NUM
ajst-8015	187	22	integrated	integrate	VERB
ajst-8015	187	23	into	into	ADP
ajst-8015	187	24	the	the	DET
ajst-8015	187	25	edge	edge	NOUN
ajst-8015	187	26	for	for	ADP
ajst-8015	187	27	composition	composition	NOUN
ajst-8015	187	28	.	.	PUNCT
ajst-8015	188	1	finally	finally	ADV
ajst-8015	188	2	,	,	PUNCT
ajst-8015	188	3	the	the	DET
ajst-8015	188	4	classification	classification	NOUN
ajst-8015	188	5	accuracy	accuracy	NOUN
ajst-8015	188	6	of	of	ADP
ajst-8015	188	7	84%ad	84%ad	NOUN
ajst-8015	188	8	was	be	AUX
ajst-8015	188	9	achieved	achieve	VERB
ajst-8015	188	10	by	by	ADP
ajst-8015	188	11	using	use	VERB
ajst-8015	188	12	graph	graph	NOUN
ajst-8015	188	13	classification	classification	NOUN
ajst-8015	188	14	.	.	PUNCT
ajst-8015	189	1	the	the	DET
ajst-8015	189	2	approach	approach	NOUN
ajst-8015	189	3	of	of	ADP
ajst-8015	189	4	ad	ad	NOUN
ajst-8015	189	5	prediction	prediction	NOUN
ajst-8015	189	6	based	base	VERB
ajst-8015	189	7	on	on	ADP
ajst-8015	189	8	gcn	gcn	NOUN
ajst-8015	189	9	is	be	AUX
ajst-8015	189	10	consistent	consistent	ADJ
ajst-8015	189	11	with	with	ADP
ajst-8015	189	12	the	the	DET
ajst-8015	189	13	approach	approach	NOUN
ajst-8015	189	14	based	base	VERB
ajst-8015	189	15	on	on	ADP
ajst-8015	189	16	roi	roi	NOUN
ajst-8015	189	17	.	.	PUNCT
ajst-8015	190	1	however	however	ADV
ajst-8015	190	2	,	,	PUNCT
ajst-8015	190	3	compared	compare	VERB
ajst-8015	190	4	with	with	ADP
ajst-8015	190	5	previous	previous	ADJ
ajst-8015	190	6	work	work	NOUN
ajst-8015	190	7	using	use	VERB
ajst-8015	190	8	cnn	cnn	PROPN
ajst-8015	190	9	to	to	PART
ajst-8015	190	10	model	model	NOUN
ajst-8015	190	11	roi	roi	NOUN
ajst-8015	190	12	features	feature	NOUN
ajst-8015	190	13	,	,	PUNCT
ajst-8015	190	14	gcn	gcn	NOUN
ajst-8015	190	15	can	can	AUX
ajst-8015	190	16	effectively	effectively	ADV
ajst-8015	190	17	model	model	VERB
ajst-8015	190	18	global	global	ADJ
ajst-8015	190	19	features	feature	NOUN
ajst-8015	190	20	,	,	PUNCT
ajst-8015	190	21	avoid	avoid	VERB
ajst-8015	190	22	the	the	DET
ajst-8015	190	23	defect	defect	NOUN
ajst-8015	190	24	that	that	PRON
ajst-8015	190	25	cnn	cnn	PROPN
ajst-8015	190	26	can	can	AUX
ajst-8015	190	27	not	not	PART
ajst-8015	190	28	do	do	VERB
ajst-8015	190	29	global	global	ADJ
ajst-8015	190	30	modeling	modeling	NOUN
ajst-8015	190	31	,	,	PUNCT
ajst-8015	190	32	effectively	effectively	ADV
ajst-8015	190	33	reduce	reduce	VERB
ajst-8015	190	34	the	the	DET
ajst-8015	190	35	learning	learning	NOUN
ajst-8015	190	36	time	time	NOUN
ajst-8015	190	37	and	and	CCONJ
ajst-8015	190	38	improve	improve	VERB
ajst-8015	190	39	the	the	DET
ajst-8015	190	40	classification	classification	NOUN
ajst-8015	190	41	accuracy	accuracy	NOUN
ajst-8015	190	42	.	.	PUNCT
ajst-8015	191	1	however	however	ADV
ajst-8015	191	2	,	,	PUNCT
ajst-8015	191	3	using	use	VERB
ajst-8015	191	4	gcn	gcn	NOUN
ajst-8015	191	5	to	to	PART
ajst-8015	191	6	predict	predict	VERB
ajst-8015	191	7	ad	ad	NOUN
ajst-8015	191	8	requires	require	VERB
ajst-8015	191	9	first	first	ADV
ajst-8015	191	10	converting	convert	VERB
ajst-8015	191	11	euclidean	euclidean	ADJ
ajst-8015	191	12	spatial	spatial	ADJ
ajst-8015	191	13	data	datum	NOUN
ajst-8015	191	14	into	into	ADP
ajst-8015	191	15	graph	graph	NOUN
ajst-8015	191	16	data	datum	NOUN
ajst-8015	191	17	,	,	PUNCT
ajst-8015	191	18	which	which	PRON
ajst-8015	191	19	requires	require	VERB
ajst-8015	191	20	third	third	ADJ
ajst-8015	191	21	-	-	PUNCT
ajst-8015	191	22	party	party	NOUN
ajst-8015	191	23	medical	medical	ADJ
ajst-8015	191	24	image	image	NOUN
ajst-8015	191	25	processing	processing	NOUN
ajst-8015	191	26	software	software	NOUN
ajst-8015	191	27	to	to	PART
ajst-8015	191	28	generate	generate	VERB
ajst-8015	191	29	data	datum	NOUN
ajst-8015	191	30	and	and	CCONJ
ajst-8015	191	31	integrate	integrate	VERB
ajst-8015	191	32	it	it	PRON
ajst-8015	191	33	with	with	ADP
ajst-8015	191	34	the	the	DET
ajst-8015	191	35	data	data	NOUN
ajst-8015	191	36	processing	processing	NOUN
ajst-8015	191	37	framework	framework	NOUN
ajst-8015	191	38	.	.	PUNCT
ajst-8015	192	1	2.2.3	2.2.3	X
ajst-8015	192	2	.	.	PUNCT
ajst-8015	192	3	ad	ad	NOUN
ajst-8015	192	4	classification	classification	NOUN
ajst-8015	192	5	based	base	VERB
ajst-8015	192	6	on	on	ADP
ajst-8015	192	7	rnn	rnn	PROPN
ajst-8015	192	8	rnn	rnn	PROPN
ajst-8015	192	9	include	include	VERB
ajst-8015	192	10	loop	loop	NOUN
ajst-8015	192	11	connections	connection	NOUN
ajst-8015	192	12	in	in	ADP
ajst-8015	192	13	the	the	DET
ajst-8015	192	14	network	network	NOUN
ajst-8015	192	15	structure	structure	NOUN
ajst-8015	192	16	,	,	PUNCT
ajst-8015	192	17	allowing	allow	VERB
ajst-8015	192	18	them	they	PRON
ajst-8015	192	19	to	to	PART
ajst-8015	192	20	retain	retain	VERB
ajst-8015	192	21	information	information	NOUN
ajst-8015	192	22	about	about	ADP
ajst-8015	192	23	previous	previous	ADJ
ajst-8015	192	24	time	time	NOUN
ajst-8015	192	25	steps	step	NOUN
ajst-8015	192	26	when	when	SCONJ
ajst-8015	192	27	processing	processing	NOUN
ajst-8015	192	28	sequence	sequence	NOUN
ajst-8015	192	29	data	datum	NOUN
ajst-8015	192	30	.	.	PUNCT
ajst-8015	193	1	at	at	ADP
ajst-8015	193	2	each	each	DET
ajst-8015	193	3	time	time	NOUN
ajst-8015	193	4	step	step	NOUN
ajst-8015	193	5	,	,	PUNCT
ajst-8015	193	6	the	the	DET
ajst-8015	193	7	rnn	rnn	NOUN
ajst-8015	193	8	receives	receive	VERB
ajst-8015	193	9	an	an	DET
ajst-8015	193	10	input	input	NOUN
ajst-8015	193	11	and	and	CCONJ
ajst-8015	193	12	calculates	calculate	VERB
ajst-8015	193	13	a	a	DET
ajst-8015	193	14	new	new	ADJ
ajst-8015	193	15	hidden	hidden	ADJ
ajst-8015	193	16	state	state	NOUN
ajst-8015	193	17	based	base	VERB
ajst-8015	193	18	on	on	ADP
ajst-8015	193	19	the	the	DET
ajst-8015	193	20	current	current	ADJ
ajst-8015	193	21	input	input	NOUN
ajst-8015	193	22	and	and	CCONJ
ajst-8015	193	23	the	the	DET
ajst-8015	193	24	hidden	hidden	ADJ
ajst-8015	193	25	state	state	NOUN
ajst-8015	193	26	of	of	ADP
ajst-8015	193	27	the	the	DET
ajst-8015	193	28	previous	previous	ADJ
ajst-8015	193	29	time	time	NOUN
ajst-8015	193	30	step	step	NOUN
ajst-8015	193	31	.	.	PUNCT
ajst-8015	194	1	the	the	DET
ajst-8015	194	2	new	new	ADJ
ajst-8015	194	3	hidden	hidden	ADJ
ajst-8015	194	4	state	state	NOUN
ajst-8015	194	5	is	be	AUX
ajst-8015	194	6	then	then	ADV
ajst-8015	194	7	used	use	VERB
ajst-8015	194	8	to	to	PART
ajst-8015	194	9	produce	produce	VERB
ajst-8015	194	10	the	the	DET
ajst-8015	194	11	output	output	NOUN
ajst-8015	194	12	of	of	ADP
ajst-8015	194	13	the	the	DET
ajst-8015	194	14	current	current	ADJ
ajst-8015	194	15	time	time	NOUN
ajst-8015	194	16	step	step	NOUN
ajst-8015	194	17	and	and	CCONJ
ajst-8015	194	18	passed	pass	VERB
ajst-8015	194	19	to	to	ADP
ajst-8015	194	20	the	the	DET
ajst-8015	194	21	next	next	ADJ
ajst-8015	194	22	time	time	NOUN
ajst-8015	194	23	step	step	NOUN
ajst-8015	194	24	to	to	PART
ajst-8015	194	25	update	update	VERB
ajst-8015	194	26	the	the	DET
ajst-8015	194	27	state	state	NOUN
ajst-8015	194	28	.	.	PUNCT
ajst-8015	195	1	in	in	ADP
ajst-8015	195	2	this	this	DET
ajst-8015	195	3	way	way	NOUN
ajst-8015	195	4	,	,	PUNCT
ajst-8015	195	5	rnn	rnn	PROPN
ajst-8015	195	6	can	can	AUX
ajst-8015	195	7	capture	capture	VERB
ajst-8015	195	8	dependencies	dependency	NOUN
ajst-8015	195	9	and	and	CCONJ
ajst-8015	195	10	dynamic	dynamic	ADJ
ajst-8015	195	11	characteristics	characteristic	NOUN
ajst-8015	195	12	in	in	ADP
ajst-8015	195	13	sequences	sequence	NOUN
ajst-8015	195	14	.	.	PUNCT
ajst-8015	196	1	its	its	PRON
ajst-8015	196	2	structure	structure	NOUN
ajst-8015	196	3	is	be	AUX
ajst-8015	196	4	shown	show	VERB
ajst-8015	196	5	in	in	ADP
ajst-8015	196	6	figure	figure	NOUN
ajst-8015	196	7	4	4	NUM
ajst-8015	196	8	.	.	PUNCT
ajst-8015	197	1	=	=	NOUN
ajst-8015	197	2	a	a	PRON
ajst-8015	197	3	ht	ht	X
ajst-8015	197	4	xt	xt	ADP
ajst-8015	197	5	a	a	DET
ajst-8015	197	6	h0	h0	NOUN
ajst-8015	197	7	x0	x0	PROPN
ajst-8015	197	8	a	a	DET
ajst-8015	197	9	h1	h1	PROPN
ajst-8015	197	10	x1	x1	PROPN
ajst-8015	197	11	a	a	DET
ajst-8015	197	12	ht	ht	X
ajst-8015	197	13	xt	xt	PROPN
ajst-8015	197	14	...	...	PUNCT
ajst-8015	198	1	figure	figure	NOUN
ajst-8015	198	2	4	4	NUM
ajst-8015	198	3	.	.	PUNCT
ajst-8015	199	1	recurrent	recurrent	ADJ
ajst-8015	199	2	neural	neural	ADJ
ajst-8015	199	3	network	network	NOUN
ajst-8015	199	4	structure	structure	NOUN
ajst-8015	199	5	li	li	PROPN
ajst-8015	199	6	et	et	PROPN
ajst-8015	199	7	al	al	PROPN
ajst-8015	199	8	.	.	PUNCT
ajst-8015	200	1	[	[	X
ajst-8015	200	2	53	53	NUM
ajst-8015	200	3	]	]	PUNCT
ajst-8015	200	4	used	use	VERB
ajst-8015	200	5	lstm	lstm	NOUN
ajst-8015	200	6	and	and	CCONJ
ajst-8015	200	7	an	an	DET
ajst-8015	200	8	automatic	automatic	ADJ
ajst-8015	200	9	encoder	encoder	NOUN
ajst-8015	200	10	to	to	PART
ajst-8015	200	11	generate	generate	VERB
ajst-8015	200	12	image	image	NOUN
ajst-8015	200	13	representations	representation	NOUN
ajst-8015	200	14	of	of	ADP
ajst-8015	200	15	mri	mri	NOUN
ajst-8015	200	16	and	and	CCONJ
ajst-8015	200	17	combined	combine	VERB
ajst-8015	200	18	this	this	DET
ajst-8015	200	19	feature	feature	NOUN
ajst-8015	200	20	with	with	ADP
ajst-8015	200	21	hand	hand	NOUN
ajst-8015	200	22	-	-	PUNCT
ajst-8015	200	23	made	make	VERB
ajst-8015	200	24	features	feature	NOUN
ajst-8015	200	25	such	such	ADJ
ajst-8015	200	26	as	as	ADP
ajst-8015	200	27	hippocampus	hippocampus	NOUN
ajst-8015	200	28	volume	volume	NOUN
ajst-8015	200	29	measurements	measurement	NOUN
ajst-8015	200	30	and	and	CCONJ
ajst-8015	200	31	demographic	demographic	ADJ
ajst-8015	200	32	information	information	NOUN
ajst-8015	200	33	to	to	PART
ajst-8015	200	34	construct	construct	VERB
ajst-8015	200	35	a	a	DET
ajst-8015	200	36	prognostic	prognostic	ADJ
ajst-8015	200	37	model	model	NOUN
ajst-8015	200	38	predicting	predict	VERB
ajst-8015	200	39	the	the	DET
ajst-8015	200	40	early	early	ADJ
ajst-8015	200	41	stages	stage	NOUN
ajst-8015	200	42	between	between	ADP
ajst-8015	200	43	mci	mci	PROPN
ajst-8015	200	44	and	and	CCONJ
ajst-8015	200	45	ad	ad	NOUN
ajst-8015	200	46	using	use	VERB
ajst-8015	200	47	longitudinal	longitudinal	ADJ
ajst-8015	200	48	analysis	analysis	NOUN
ajst-8015	200	49	.	.	PUNCT
ajst-8015	201	1	srivastava	srivastava	PROPN
ajst-8015	201	2	et	et	PROPN
ajst-8015	201	3	al	al	PROPN
ajst-8015	201	4	.	.	PUNCT
ajst-8015	202	1	[	[	X
ajst-8015	202	2	54	54	NUM
ajst-8015	202	3	]	]	PUNCT
ajst-8015	202	4	used	use	VERB
ajst-8015	202	5	lstm	lstm	NOUN
ajst-8015	202	6	autoencoders	autoencoder	NOUN
ajst-8015	202	7	to	to	PART
ajst-8015	202	8	generate	generate	VERB
ajst-8015	202	9	mri	mri	NOUN
ajst-8015	202	10	representations	representation	NOUN
ajst-8015	202	11	of	of	ADP
ajst-8015	202	12	patient	patient	ADJ
ajst-8015	202	13	information	information	NOUN
ajst-8015	202	14	and	and	CCONJ
ajst-8015	202	15	used	use	VERB
ajst-8015	202	16	a	a	DET
ajst-8015	202	17	k	k	NOUN
ajst-8015	202	18	-	-	PUNCT
ajst-8015	202	19	means	means	NOUN
ajst-8015	202	20	clustering	cluster	VERB
ajst-8015	202	21	t	t	NOUN
ajst-8015	202	22	-	-	PUNCT
ajst-8015	202	23	distributed	distribute	VERB
ajst-8015	202	24	random	random	ADJ
ajst-8015	202	25	adjacency	adjacency	NOUN
ajst-8015	202	26	embedding	embed	VERB
ajst-8015	202	27	algorithm	algorithm	NOUN
ajst-8015	202	28	(	(	PUNCT
ajst-8015	202	29	t	t	NOUN
ajst-8015	202	30	-	-	PUNCT
ajst-8015	202	31	sne	sne	NOUN
ajst-8015	202	32	)	)	PUNCT
ajst-8015	202	33	to	to	PART
ajst-8015	202	34	classify	classify	VERB
ajst-8015	202	35	ad	ad	NOUN
ajst-8015	202	36	.	.	PUNCT
ajst-8015	203	1	lee	lee	PROPN
ajst-8015	203	2	et	et	PROPN
ajst-8015	203	3	al	al	PROPN
ajst-8015	203	4	.	.	PUNCT
ajst-8015	204	1	[	[	X
ajst-8015	204	2	55	55	NUM
ajst-8015	204	3	]	]	PUNCT
ajst-8015	204	4	proposed	propose	VERB
ajst-8015	204	5	a	a	DET
ajst-8015	204	6	multimodal	multimodal	ADJ
ajst-8015	204	7	recursive	recursive	ADJ
ajst-8015	204	8	neural	neural	ADJ
ajst-8015	204	9	network	network	NOUN
ajst-8015	204	10	(	(	PUNCT
ajst-8015	204	11	mrnn	mrnn	PROPN
ajst-8015	204	12	)	)	PUNCT
ajst-8015	204	13	to	to	PART
ajst-8015	204	14	analyze	analyze	VERB
ajst-8015	204	15	the	the	DET
ajst-8015	204	16	conversion	conversion	NOUN
ajst-8015	204	17	from	from	ADP
ajst-8015	204	18	mci	mci	PROPN
ajst-8015	204	19	to	to	ADP
ajst-8015	204	20	ad	ad	NOUN
ajst-8015	204	21	.	.	PUNCT
ajst-8015	205	1	the	the	DET
ajst-8015	205	2	mrnn	mrnn	PROPN
ajst-8015	205	3	is	be	AUX
ajst-8015	205	4	trained	train	VERB
ajst-8015	205	5	by	by	ADP
ajst-8015	205	6	using	use	VERB
ajst-8015	205	7	population	population	NOUN
ajst-8015	205	8	information	information	NOUN
ajst-8015	205	9	,	,	PUNCT
ajst-8015	205	10	neuroimaging	neuroimaging	NOUN
ajst-8015	205	11	information	information	NOUN
ajst-8015	205	12	,	,	PUNCT
ajst-8015	205	13	cognitive	cognitive	ADJ
ajst-8015	205	14	performance	performance	NOUN
ajst-8015	205	15	,	,	PUNCT
ajst-8015	205	16	and	and	CCONJ
ajst-8015	205	17	time	time	NOUN
ajst-8015	205	18	series	series	NOUN
ajst-8015	205	19	measured	measure	VERB
ajst-8015	205	20	by	by	ADP
ajst-8015	205	21	cerebrospinal	cerebrospinal	ADJ
ajst-8015	205	22	fluid	fluid	NOUN
ajst-8015	205	23	(	(	PUNCT
ajst-8015	205	24	cfs	cfs	PROPN
ajst-8015	205	25	)	)	PUNCT
ajst-8015	205	26	,	,	PUNCT
ajst-8015	205	27	respectively	respectively	ADV
ajst-8015	205	28	,	,	PUNCT
ajst-8015	205	29	to	to	PART
ajst-8015	205	30	input	input	VERB
ajst-8015	205	31	a	a	DET
ajst-8015	205	32	gated	gate	VERB
ajst-8015	205	33	recursive	recursive	ADJ
ajst-8015	205	34	unit	unit	NOUN
ajst-8015	205	35	(	(	PUNCT
ajst-8015	205	36	grus	grus	NOUN
ajst-8015	205	37	)	)	PUNCT
ajst-8015	205	38	,	,	PUNCT
ajst-8015	205	39	which	which	PRON
ajst-8015	205	40	ultimately	ultimately	ADV
ajst-8015	205	41	concatenates	concatenate	VERB
ajst-8015	205	42	the	the	DET
ajst-8015	205	43	characteristics	characteristic	NOUN
ajst-8015	205	44	of	of	ADP
ajst-8015	205	45	all	all	DET
ajst-8015	205	46	the	the	DET
ajst-8015	205	47	data	datum	NOUN
ajst-8015	205	48	to	to	PART
ajst-8015	205	49	make	make	VERB
ajst-8015	205	50	the	the	DET
ajst-8015	205	51	final	final	ADJ
ajst-8015	205	52	prediction	prediction	NOUN
ajst-8015	205	53	.	.	PUNCT
ajst-8015	206	1	the	the	DET
ajst-8015	206	2	above	above	ADJ
ajst-8015	206	3	work	work	NOUN
ajst-8015	206	4	can	can	AUX
ajst-8015	206	5	effectively	effectively	ADV
ajst-8015	206	6	predict	predict	VERB
ajst-8015	206	7	the	the	DET
ajst-8015	206	8	transformation	transformation	NOUN
ajst-8015	206	9	process	process	NOUN
ajst-8015	206	10	of	of	ADP
ajst-8015	206	11	mci	mci	PROPN
ajst-8015	206	12	to	to	ADP
ajst-8015	206	13	ad	ad	NOUN
ajst-8015	206	14	through	through	ADP
ajst-8015	206	15	longitudinal	longitudinal	ADJ
ajst-8015	206	16	analysis	analysis	NOUN
ajst-8015	206	17	using	use	VERB
ajst-8015	206	18	rnn	rnn	NOUN
ajst-8015	206	19	.	.	PUNCT
ajst-8015	207	1	however	however	ADV
ajst-8015	207	2	,	,	PUNCT
ajst-8015	207	3	these	these	DET
ajst-8015	207	4	work	work	NOUN
ajst-8015	207	5	are	be	AUX
ajst-8015	207	6	heavily	heavily	ADV
ajst-8015	207	7	dependent	dependent	ADJ
ajst-8015	207	8	on	on	ADP
ajst-8015	207	9	the	the	DET
ajst-8015	207	10	time	time	NOUN
ajst-8015	207	11	series	series	NOUN
ajst-8015	207	12	related	relate	VERB
ajst-8015	207	13	to	to	ADP
ajst-8015	207	14	mri	mri	NOUN
ajst-8015	207	15	measurements	measurement	NOUN
ajst-8015	207	16	,	,	PUNCT
ajst-8015	207	17	and	and	CCONJ
ajst-8015	207	18	it	it	PRON
ajst-8015	207	19	is	be	AUX
ajst-8015	207	20	extremely	extremely	ADV
ajst-8015	207	21	challenging	challenging	ADJ
ajst-8015	207	22	to	to	PART
ajst-8015	207	23	collect	collect	VERB
ajst-8015	207	24	complete	complete	ADJ
ajst-8015	207	25	and	and	CCONJ
ajst-8015	207	26	high	high	ADJ
ajst-8015	207	27	-	-	PUNCT
ajst-8015	207	28	quality	quality	NOUN
ajst-8015	207	29	longitudinal	longitudinal	ADJ
ajst-8015	207	30	mri	mri	NOUN
ajst-8015	207	31	data	datum	NOUN
ajst-8015	207	32	for	for	ADP
ajst-8015	207	33	each	each	DET
ajst-8015	207	34	subject	subject	NOUN
ajst-8015	207	35	.	.	PUNCT
ajst-8015	208	1	therefore	therefore	ADV
ajst-8015	208	2	,	,	PUNCT
ajst-8015	208	3	the	the	DET
ajst-8015	208	4	lack	lack	NOUN
ajst-8015	208	5	and	and	CCONJ
ajst-8015	208	6	incomplete	incomplete	ADJ
ajst-8015	208	7	data	datum	NOUN
ajst-8015	208	8	is	be	AUX
ajst-8015	208	9	an	an	DET
ajst-8015	208	10	important	important	ADJ
ajst-8015	208	11	limitation	limitation	NOUN
ajst-8015	208	12	of	of	ADP
ajst-8015	208	13	using	use	VERB
ajst-8015	208	14	rnn	rnn	NOUN
ajst-8015	208	15	to	to	PART
ajst-8015	208	16	predict	predict	VERB
ajst-8015	208	17	ad	ad	NOUN
ajst-8015	208	18	.	.	PUNCT
ajst-8015	209	1	to	to	PART
ajst-8015	209	2	sum	sum	VERB
ajst-8015	209	3	up	up	ADP
ajst-8015	209	4	,	,	PUNCT
ajst-8015	209	5	compared	compare	VERB
ajst-8015	209	6	with	with	ADP
ajst-8015	209	7	traditional	traditional	ADJ
ajst-8015	209	8	machine	machine	NOUN
ajst-8015	209	9	learning	learning	NOUN
ajst-8015	209	10	algorithms	algorithm	NOUN
ajst-8015	209	11	,	,	PUNCT
ajst-8015	209	12	deep	deep	ADJ
ajst-8015	209	13	learning	learning	NOUN
ajst-8015	209	14	is	be	AUX
ajst-8015	209	15	more	more	ADV
ajst-8015	209	16	widely	widely	ADV
ajst-8015	209	17	used	use	VERB
ajst-8015	209	18	in	in	ADP
ajst-8015	209	19	ad	ad	NOUN
ajst-8015	209	20	assisted	assist	VERB
ajst-8015	209	21	diagnosis	diagnosis	NOUN
ajst-8015	209	22	research	research	NOUN
ajst-8015	209	23	.	.	PUNCT
ajst-8015	210	1	deep	deep	ADJ
ajst-8015	210	2	learning	learning	NOUN
ajst-8015	210	3	technologies	technology	NOUN
ajst-8015	210	4	,	,	PUNCT
ajst-8015	210	5	such	such	ADJ
ajst-8015	210	6	as	as	ADP
ajst-8015	210	7	cnn	cnn	PROPN
ajst-8015	210	8	,	,	PUNCT
ajst-8015	210	9	gcn	gcn	NOUN
ajst-8015	210	10	and	and	CCONJ
ajst-8015	210	11	rnn	rnn	PROPN
ajst-8015	210	12	,	,	PUNCT
ajst-8015	210	13	can	can	AUX
ajst-8015	210	14	achieve	achieve	VERB
ajst-8015	210	15	better	well	ADJ
ajst-8015	210	16	performance	performance	NOUN
ajst-8015	210	17	for	for	ADP
ajst-8015	210	18	high	high	ADJ
ajst-8015	210	19	-	-	PUNCT
ajst-8015	210	20	level	level	NOUN
ajst-8015	210	21	automatic	automatic	ADJ
ajst-8015	210	22	feature	feature	NOUN
ajst-8015	210	23	extraction	extraction	NOUN
ajst-8015	210	24	of	of	ADP
ajst-8015	210	25	data	datum	NOUN
ajst-8015	210	26	sets	set	NOUN
ajst-8015	210	27	.	.	PUNCT
ajst-8015	211	1	it	it	PRON
ajst-8015	211	2	can	can	AUX
ajst-8015	211	3	not	not	PART
ajst-8015	211	4	only	only	ADV
ajst-8015	211	5	combine	combine	AUX
ajst-8015	211	6	manually	manually	ADV
ajst-8015	211	7	made	make	VERB
ajst-8015	211	8	features	feature	NOUN
ajst-8015	211	9	with	with	ADP
ajst-8015	211	10	feature	feature	NOUN
ajst-8015	211	11	maps	map	NOUN
ajst-8015	211	12	of	of	ADP
ajst-8015	211	13	input	input	NOUN
ajst-8015	211	14	data	datum	NOUN
ajst-8015	211	15	,	,	PUNCT
ajst-8015	211	16	but	but	CCONJ
ajst-8015	211	17	also	also	ADV
ajst-8015	211	18	directly	directly	ADV
ajst-8015	211	19	extract	extract	VERB
ajst-8015	211	20	specific	specific	ADJ
ajst-8015	211	21	input	input	NOUN
ajst-8015	211	22	data	data	NOUN
ajst-8015	211	23	patterns	pattern	NOUN
ajst-8015	211	24	for	for	ADP
ajst-8015	211	25	classification	classification	NOUN
ajst-8015	211	26	or	or	CCONJ
ajst-8015	211	27	regression	regression	NOUN
ajst-8015	211	28	tasks	task	NOUN
ajst-8015	211	29	.	.	PUNCT
ajst-8015	212	1	however	however	ADV
ajst-8015	212	2	,	,	PUNCT
ajst-8015	212	3	there	there	PRON
ajst-8015	212	4	are	be	VERB
ajst-8015	212	5	still	still	ADV
ajst-8015	212	6	some	some	DET
ajst-8015	212	7	limitations	limitation	NOUN
ajst-8015	212	8	in	in	ADP
ajst-8015	212	9	applying	apply	VERB
ajst-8015	212	10	deep	deep	ADJ
ajst-8015	212	11	learning	learning	NOUN
ajst-8015	212	12	to	to	ADP
ajst-8015	212	13	the	the	DET
ajst-8015	212	14	classification	classification	NOUN
ajst-8015	212	15	or	or	CCONJ
ajst-8015	212	16	regression	regression	NOUN
ajst-8015	212	17	of	of	ADP
ajst-8015	212	18	ad	ad	NOUN
ajst-8015	212	19	patients	patient	NOUN
ajst-8015	212	20	,	,	PUNCT
ajst-8015	212	21	as	as	SCONJ
ajst-8015	212	22	follows	follow	VERB
ajst-8015	212	23	:	:	PUNCT
ajst-8015	212	24	(	(	PUNCT
ajst-8015	212	25	1	1	X
ajst-8015	212	26	)	)	PUNCT
ajst-8015	212	27	interpretability	interpretability	NOUN
ajst-8015	212	28	.	.	PUNCT
ajst-8015	213	1	traditional	traditional	ADJ
ajst-8015	213	2	machine	machine	NOUN
ajst-8015	213	3	learning	learn	VERB
ajst-8015	213	4	methods	method	NOUN
ajst-8015	213	5	require	require	VERB
ajst-8015	213	6	experts	expert	NOUN
ajst-8015	213	7	to	to	PART
ajst-8015	213	8	participate	participate	VERB
ajst-8015	213	9	in	in	ADP
ajst-8015	213	10	the	the	DET
ajst-8015	213	11	preprocessing	preprocessing	NOUN
ajst-8015	213	12	steps	step	NOUN
ajst-8015	213	13	in	in	ADP
ajst-8015	213	14	order	order	NOUN
ajst-8015	213	15	to	to	PART
ajst-8015	213	16	extract	extract	VERB
ajst-8015	213	17	and	and	CCONJ
ajst-8015	213	18	select	select	ADJ
ajst-8015	213	19	features	feature	NOUN
ajst-8015	213	20	from	from	ADP
ajst-8015	213	21	images	image	NOUN
ajst-8015	213	22	.	.	PUNCT
ajst-8015	214	1	however	however	ADV
ajst-8015	214	2	,	,	PUNCT
ajst-8015	214	3	deep	deep	ADJ
ajst-8015	214	4	learning	learning	NOUN
ajst-8015	214	5	does	do	AUX
ajst-8015	214	6	not	not	PART
ajst-8015	214	7	require	require	VERB
ajst-8015	214	8	manual	manual	ADJ
ajst-8015	214	9	intervention	intervention	NOUN
ajst-8015	214	10	and	and	CCONJ
ajst-8015	214	11	can	can	AUX
ajst-8015	214	12	achieve	achieve	VERB
ajst-8015	214	13	better	well	ADJ
ajst-8015	214	14	performance	performance	NOUN
ajst-8015	214	15	compared	compare	VERB
ajst-8015	214	16	with	with	ADP
ajst-8015	214	17	traditional	traditional	ADJ
ajst-8015	214	18	machine	machine	NOUN
ajst-8015	214	19	learning	learning	NOUN
ajst-8015	214	20	that	that	PRON
ajst-8015	214	21	relies	rely	VERB
ajst-8015	214	22	on	on	ADP
ajst-8015	214	23	pre	pre	ADJ
ajst-8015	214	24	-	-	ADJ
ajst-8015	214	25	processing	processing	NOUN
ajst-8015	214	26	,	,	PUNCT
ajst-8015	214	27	which	which	PRON
ajst-8015	214	28	also	also	ADV
ajst-8015	214	29	leads	lead	VERB
ajst-8015	214	30	to	to	ADP
ajst-8015	214	31	the	the	DET
ajst-8015	214	32	uncertainty	uncertainty	NOUN
ajst-8015	214	33	of	of	ADP
ajst-8015	214	34	deep	deep	ADJ
ajst-8015	214	35	learning	learning	NOUN
ajst-8015	214	36	and	and	CCONJ
ajst-8015	214	37	the	the	DET
ajst-8015	214	38	demand	demand	NOUN
ajst-8015	214	39	for	for	ADP
ajst-8015	214	40	large	large	ADJ
ajst-8015	214	41	amounts	amount	NOUN
ajst-8015	214	42	of	of	ADP
ajst-8015	214	43	training	training	NOUN
ajst-8015	214	44	data	datum	NOUN
ajst-8015	214	45	.	.	PUNCT
ajst-8015	215	1	(	(	PUNCT
ajst-8015	215	2	2	2	NUM
ajst-8015	215	3	)	)	PUNCT
ajst-8015	215	4	generalization	generalization	NOUN
ajst-8015	215	5	.	.	PUNCT
ajst-8015	216	1	due	due	ADP
ajst-8015	216	2	to	to	ADP
ajst-8015	216	3	the	the	DET
ajst-8015	216	4	different	different	ADJ
ajst-8015	216	5	imaging	imaging	NOUN
ajst-8015	216	6	equipment	equipment	NOUN
ajst-8015	216	7	in	in	ADP
ajst-8015	216	8	different	different	ADJ
ajst-8015	216	9	hospitals	hospital	NOUN
ajst-8015	216	10	,	,	PUNCT
ajst-8015	216	11	the	the	DET
ajst-8015	216	12	scanning	scanning	NOUN
ajst-8015	216	13	parameters	parameter	NOUN
ajst-8015	216	14	are	be	AUX
ajst-8015	216	15	not	not	PART
ajst-8015	216	16	all	all	DET
ajst-8015	216	17	the	the	DET
ajst-8015	216	18	same	same	ADJ
ajst-8015	216	19	,	,	PUNCT
ajst-8015	216	20	so	so	CCONJ
ajst-8015	216	21	the	the	DET
ajst-8015	216	22	classification	classification	NOUN
ajst-8015	216	23	effect	effect	NOUN
ajst-8015	216	24	of	of	ADP
ajst-8015	216	25	cnn	cnn	PROPN
ajst-8015	216	26	on	on	ADP
ajst-8015	216	27	diseases	disease	NOUN
ajst-8015	216	28	will	will	AUX
ajst-8015	216	29	be	be	AUX
ajst-8015	216	30	affected	affect	VERB
ajst-8015	216	31	.	.	PUNCT
ajst-8015	217	1	there	there	PRON
ajst-8015	217	2	will	will	AUX
ajst-8015	217	3	be	be	AUX
ajst-8015	217	4	a	a	DET
ajst-8015	217	5	situation	situation	NOUN
ajst-8015	217	6	that	that	SCONJ
ajst-8015	217	7	the	the	DET
ajst-8015	217	8	model	model	NOUN
ajst-8015	217	9	has	have	VERB
ajst-8015	217	10	a	a	DET
ajst-8015	217	11	good	good	ADJ
ajst-8015	217	12	training	training	NOUN
ajst-8015	217	13	effect	effect	NOUN
ajst-8015	217	14	on	on	ADP
ajst-8015	217	15	one	one	NUM
ajst-8015	217	16	data	datum	NOUN
ajst-8015	217	17	set	set	VERB
ajst-8015	217	18	,	,	PUNCT
ajst-8015	217	19	but	but	CCONJ
ajst-8015	217	20	its	its	PRON
ajst-8015	217	21	effect	effect	NOUN
ajst-8015	217	22	will	will	AUX
ajst-8015	217	23	suddenly	suddenly	ADV
ajst-8015	217	24	decline	decline	VERB
ajst-8015	217	25	when	when	SCONJ
ajst-8015	217	26	it	it	PRON
ajst-8015	217	27	is	be	AUX
ajst-8015	217	28	used	use	VERB
ajst-8015	217	29	on	on	ADP
ajst-8015	217	30	another	another	DET
ajst-8015	217	31	data	datum	NOUN
ajst-8015	217	32	set	set	VERB
ajst-8015	217	33	.	.	PUNCT
ajst-8015	218	1	to	to	PART
ajst-8015	218	2	solve	solve	VERB
ajst-8015	218	3	this	this	DET
ajst-8015	218	4	problem	problem	NOUN
ajst-8015	218	5	,	,	PUNCT
ajst-8015	218	6	in	in	ADP
ajst-8015	218	7	the	the	DET
ajst-8015	218	8	current	current	ADJ
ajst-8015	218	9	research	research	NOUN
ajst-8015	218	10	,	,	PUNCT
ajst-8015	218	11	on	on	ADP
ajst-8015	218	12	the	the	DET
ajst-8015	218	13	one	one	NUM
ajst-8015	218	14	hand	hand	NOUN
ajst-8015	218	15	,	,	PUNCT
ajst-8015	218	16	the	the	DET
ajst-8015	218	17	difficulty	difficulty	NOUN
ajst-8015	218	18	of	of	ADP
ajst-8015	218	19	generalization	generalization	NOUN
ajst-8015	218	20	in	in	ADP
ajst-8015	218	21	practical	practical	ADJ
ajst-8015	218	22	application	application	NOUN
ajst-8015	218	23	is	be	AUX
ajst-8015	218	24	alleviated	alleviate	VERB
ajst-8015	218	25	by	by	ADP
ajst-8015	218	26	expanding	expand	VERB
ajst-8015	218	27	the	the	DET
ajst-8015	218	28	sources	source	NOUN
ajst-8015	218	29	of	of	ADP
ajst-8015	218	30	data	datum	NOUN
ajst-8015	218	31	sets	set	NOUN
ajst-8015	218	32	;	;	PUNCT
ajst-8015	218	33	on	on	ADP
ajst-8015	218	34	the	the	DET
ajst-8015	218	35	other	other	ADJ
ajst-8015	218	36	hand	hand	NOUN
ajst-8015	218	37	,	,	PUNCT
ajst-8015	218	38	it	it	PRON
ajst-8015	218	39	is	be	AUX
ajst-8015	218	40	overcome	overcome	VERB
ajst-8015	218	41	by	by	ADP
ajst-8015	218	42	technical	technical	ADJ
ajst-8015	218	43	means	mean	NOUN
ajst-8015	218	44	,	,	PUNCT
ajst-8015	218	45	such	such	ADJ
ajst-8015	218	46	as	as	ADP
ajst-8015	218	47	transfer	transfer	NOUN
ajst-8015	218	48	learning	learning	NOUN
ajst-8015	218	49	,	,	PUNCT
ajst-8015	218	50	that	that	ADV
ajst-8015	218	51	is	is	ADV
ajst-8015	218	52	,	,	PUNCT
ajst-8015	218	53	pre	pre	ADJ
ajst-8015	218	54	-	-	VERB
ajst-8015	218	55	training	train	VERB
ajst-8015	218	56	a	a	DET
ajst-8015	218	57	large	large	ADJ
ajst-8015	218	58	number	number	NOUN
ajst-8015	218	59	of	of	ADP
ajst-8015	218	60	data	datum	NOUN
ajst-8015	218	61	sets	set	NOUN
ajst-8015	218	62	and	and	CCONJ
ajst-8015	218	63	then	then	ADV
ajst-8015	218	64	fine	fine	ADV
ajst-8015	218	65	-	-	PUNCT
ajst-8015	218	66	tuning	tune	VERB
ajst-8015	218	67	a	a	DET
ajst-8015	218	68	small	small	ADJ
ajst-8015	218	69	number	number	NOUN
ajst-8015	218	70	of	of	ADP
ajst-8015	218	71	data	datum	NOUN
ajst-8015	218	72	sets	set	NOUN
ajst-8015	218	73	.	.	PUNCT
ajst-8015	219	1	or	or	CCONJ
ajst-8015	219	2	multi	multi	ADJ
ajst-8015	219	3	-	-	ADJ
ajst-8015	219	4	task	task	ADJ
ajst-8015	219	5	learning	learning	NOUN
ajst-8015	219	6	(	(	PUNCT
ajst-8015	219	7	mtl	mtl	PROPN
ajst-8015	219	8	)	)	PUNCT
ajst-8015	219	9	method	method	NOUN
ajst-8015	219	10	.	.	PUNCT
ajst-8015	220	1	however	however	ADV
ajst-8015	220	2	,	,	PUNCT
ajst-8015	220	3	this	this	DET
ajst-8015	220	4	problem	problem	NOUN
ajst-8015	220	5	has	have	AUX
ajst-8015	220	6	not	not	PART
ajst-8015	220	7	been	be	AUX
ajst-8015	220	8	effectively	effectively	ADV
ajst-8015	220	9	solved	solve	VERB
ajst-8015	220	10	and	and	CCONJ
ajst-8015	220	11	is	be	AUX
ajst-8015	220	12	still	still	ADV
ajst-8015	220	13	being	be	AUX
ajst-8015	220	14	explored	explore	VERB
ajst-8015	220	15	and	and	CCONJ
ajst-8015	220	16	studied	study	VERB
ajst-8015	220	17	.	.	PUNCT
ajst-8015	221	1	3	3	X
ajst-8015	221	2	.	.	X
ajst-8015	221	3	summary	summary	NOUN
ajst-8015	221	4	and	and	CCONJ
ajst-8015	221	5	prospect	prospect	VERB
ajst-8015	221	6	traditional	traditional	ADJ
ajst-8015	221	7	machine	machine	NOUN
ajst-8015	221	8	learning	learning	NOUN
ajst-8015	221	9	methods	method	NOUN
ajst-8015	221	10	have	have	AUX
ajst-8015	221	11	previously	previously	ADV
ajst-8015	221	12	been	be	AUX
ajst-8015	221	13	widely	widely	ADV
ajst-8015	221	14	used	use	VERB
ajst-8015	221	15	to	to	PART
ajst-8015	221	16	manually	manually	ADV
ajst-8015	221	17	extract	extract	VERB
ajst-8015	221	18	features	feature	NOUN
ajst-8015	221	19	to	to	PART
ajst-8015	221	20	predict	predict	VERB
ajst-8015	221	21	ad	ad	NOUN
ajst-8015	221	22	.	.	PUNCT
ajst-8015	222	1	in	in	ADP
ajst-8015	222	2	contrast	contrast	NOUN
ajst-8015	222	3	,	,	PUNCT
ajst-8015	222	4	cnn	cnn	PROPN
ajst-8015	222	5	,	,	PUNCT
ajst-8015	222	6	gcn	gcn	PROPN
ajst-8015	222	7	,	,	PUNCT
ajst-8015	222	8	rnn	rnn	NOUN
ajst-8015	222	9	and	and	CCONJ
ajst-8015	222	10	other	other	ADJ
ajst-8015	222	11	deep	deep	ADJ
ajst-8015	222	12	learning	learning	NOUN
ajst-8015	222	13	technologies	technology	NOUN
ajst-8015	222	14	can	can	AUX
ajst-8015	222	15	automatically	automatically	ADV
ajst-8015	222	16	extract	extract	VERB
ajst-8015	222	17	useful	useful	ADJ
ajst-8015	222	18	features	feature	NOUN
ajst-8015	222	19	from	from	ADP
ajst-8015	222	20	complex	complex	ADJ
ajst-8015	222	21	image	image	NOUN
ajst-8015	222	22	data	datum	NOUN
ajst-8015	222	23	in	in	ADP
ajst-8015	222	24	an	an	DET
ajst-8015	222	25	end	end	NOUN
ajst-8015	222	26	-	-	PUNCT
ajst-8015	222	27	to	to	ADP
ajst-8015	222	28	-	-	PUNCT
ajst-8015	222	29	end	end	NOUN
ajst-8015	222	30	way	way	NOUN
ajst-8015	222	31	,	,	PUNCT
ajst-8015	222	32	which	which	PRON
ajst-8015	222	33	can	can	AUX
ajst-8015	222	34	avoid	avoid	VERB
ajst-8015	222	35	complex	complex	ADJ
ajst-8015	222	36	manual	manual	ADJ
ajst-8015	222	37	feature	feature	NOUN
ajst-8015	222	38	extraction	extraction	NOUN
ajst-8015	222	39	steps	step	NOUN
ajst-8015	222	40	and	and	CCONJ
ajst-8015	222	41	save	save	VERB
ajst-8015	222	42	a	a	DET
ajst-8015	222	43	lot	lot	NOUN
ajst-8015	222	44	of	of	ADP
ajst-8015	222	45	manpower	manpower	NOUN
ajst-8015	222	46	and	and	CCONJ
ajst-8015	222	47	material	material	NOUN
ajst-8015	222	48	resources	resource	NOUN
ajst-8015	222	49	.	.	PUNCT
ajst-8015	223	1	however	however	ADV
ajst-8015	223	2	,	,	PUNCT
ajst-8015	223	3	deep	deep	ADJ
ajst-8015	223	4	learning	learning	NOUN
ajst-8015	223	5	technology	technology	NOUN
ajst-8015	223	6	still	still	ADV
ajst-8015	223	7	has	have	VERB
ajst-8015	223	8	the	the	DET
ajst-8015	223	9	following	follow	VERB
ajst-8015	223	10	limitations	limitation	NOUN
ajst-8015	223	11	:	:	PUNCT
ajst-8015	223	12	1	1	X
ajst-8015	223	13	.	.	PUNCT
ajst-8015	223	14	data	datum	NOUN
ajst-8015	223	15	dependence	dependence	NOUN
ajst-8015	223	16	:	:	PUNCT
ajst-8015	223	17	deep	deep	ADJ
ajst-8015	223	18	learning	learning	NOUN
ajst-8015	223	19	models	model	NOUN
ajst-8015	223	20	require	require	VERB
ajst-8015	223	21	a	a	DET
ajst-8015	223	22	large	large	ADJ
ajst-8015	223	23	amount	amount	NOUN
ajst-8015	223	24	of	of	ADP
ajst-8015	223	25	annotated	annotate	VERB
ajst-8015	223	26	data	datum	NOUN
ajst-8015	223	27	for	for	ADP
ajst-8015	223	28	training	training	NOUN
ajst-8015	223	29	,	,	PUNCT
ajst-8015	223	30	which	which	PRON
ajst-8015	223	31	may	may	AUX
ajst-8015	223	32	lead	lead	VERB
ajst-8015	223	33	to	to	ADP
ajst-8015	223	34	high	high	ADJ
ajst-8015	223	35	cost	cost	NOUN
ajst-8015	223	36	of	of	ADP
ajst-8015	223	37	data	datum	NOUN
ajst-8015	223	38	collection	collection	NOUN
ajst-8015	223	39	and	and	CCONJ
ajst-8015	223	40	annotation	annotation	NOUN
ajst-8015	223	41	,	,	PUNCT
ajst-8015	223	42	and	and	CCONJ
ajst-8015	223	43	may	may	AUX
ajst-8015	223	44	also	also	ADV
ajst-8015	223	45	be	be	AUX
ajst-8015	223	46	limited	limit	VERB
ajst-8015	223	47	in	in	ADP
ajst-8015	223	48	areas	area	NOUN
ajst-8015	223	49	where	where	SCONJ
ajst-8015	223	50	data	datum	NOUN
ajst-8015	223	51	is	be	AUX
ajst-8015	223	52	scarce	scarce	ADJ
ajst-8015	223	53	.	.	PUNCT
ajst-8015	224	1	2	2	X
ajst-8015	224	2	.	.	X
ajst-8015	224	3	computing	compute	VERB
ajst-8015	224	4	resource	resource	NOUN
ajst-8015	224	5	requirements	requirement	NOUN
ajst-8015	224	6	:	:	PUNCT
ajst-8015	224	7	training	training	NOUN
ajst-8015	224	8	and	and	CCONJ
ajst-8015	224	9	reasoning	reasoning	NOUN
ajst-8015	224	10	of	of	ADP
ajst-8015	224	11	deep	deep	ADJ
ajst-8015	224	12	learning	learning	NOUN
ajst-8015	224	13	models	model	NOUN
ajst-8015	224	14	usually	usually	ADV
ajst-8015	224	15	require	require	VERB
ajst-8015	224	16	a	a	DET
ajst-8015	224	17	large	large	ADJ
ajst-8015	224	18	amount	amount	NOUN
ajst-8015	224	19	of	of	ADP
ajst-8015	224	20	computing	compute	VERB
ajst-8015	224	21	resources	resource	NOUN
ajst-8015	224	22	,	,	PUNCT
ajst-8015	224	23	which	which	PRON
ajst-8015	224	24	can	can	AUX
ajst-8015	224	25	lead	lead	VERB
ajst-8015	224	26	to	to	ADP
ajst-8015	224	27	high	high	ADJ
ajst-8015	224	28	computing	computing	NOUN
ajst-8015	224	29	costs	cost	NOUN
ajst-8015	224	30	and	and	CCONJ
ajst-8015	224	31	energy	energy	NOUN
ajst-8015	224	32	consumption	consumption	NOUN
ajst-8015	224	33	.	.	PUNCT
ajst-8015	225	1	3	3	X
ajst-8015	225	2	.	.	X
ajst-8015	225	3	model	model	NOUN
ajst-8015	225	4	interpretability	interpretability	NOUN
ajst-8015	225	5	:	:	PUNCT
ajst-8015	225	6	deep	deep	ADJ
ajst-8015	225	7	learning	learning	NOUN
ajst-8015	225	8	models	model	NOUN
ajst-8015	225	9	are	be	AUX
ajst-8015	225	10	often	often	ADV
ajst-8015	225	11	220	220	NUM
ajst-8015	225	12	considered	consider	VERB
ajst-8015	225	13	"	"	PUNCT
ajst-8015	225	14	black	black	ADJ
ajst-8015	225	15	boxes	box	NOUN
ajst-8015	225	16	"	"	PUNCT
ajst-8015	225	17	whose	whose	DET
ajst-8015	225	18	inner	inner	ADJ
ajst-8015	225	19	workings	working	NOUN
ajst-8015	225	20	are	be	AUX
ajst-8015	225	21	difficult	difficult	ADJ
ajst-8015	225	22	to	to	PART
ajst-8015	225	23	explain	explain	VERB
ajst-8015	225	24	.	.	PUNCT
ajst-8015	226	1	this	this	PRON
ajst-8015	226	2	can	can	AUX
ajst-8015	226	3	lead	lead	VERB
ajst-8015	226	4	to	to	ADP
ajst-8015	226	5	limited	limit	VERB
ajst-8015	226	6	applications	application	NOUN
ajst-8015	226	7	in	in	ADP
ajst-8015	226	8	areas	area	NOUN
ajst-8015	226	9	that	that	PRON
ajst-8015	226	10	require	require	VERB
ajst-8015	226	11	interpretability	interpretability	NOUN
ajst-8015	226	12	,	,	PUNCT
ajst-8015	226	13	such	such	ADJ
ajst-8015	226	14	as	as	ADP
ajst-8015	226	15	healthcare	healthcare	NOUN
ajst-8015	226	16	and	and	CCONJ
ajst-8015	226	17	finance	finance	NOUN
ajst-8015	226	18	.	.	PUNCT
ajst-8015	227	1	4	4	X
ajst-8015	227	2	.	.	X
ajst-8015	227	3	generalization	generalization	NOUN
ajst-8015	227	4	ability	ability	NOUN
ajst-8015	227	5	:	:	PUNCT
ajst-8015	227	6	although	although	SCONJ
ajst-8015	227	7	deep	deep	ADJ
ajst-8015	227	8	learning	learning	NOUN
ajst-8015	227	9	models	model	NOUN
ajst-8015	227	10	perform	perform	VERB
ajst-8015	227	11	well	well	ADV
ajst-8015	227	12	on	on	ADP
ajst-8015	227	13	training	training	NOUN
ajst-8015	227	14	data	datum	NOUN
ajst-8015	227	15	,	,	PUNCT
ajst-8015	227	16	they	they	PRON
ajst-8015	227	17	may	may	AUX
ajst-8015	227	18	have	have	AUX
ajst-8015	227	19	limited	limit	VERB
ajst-8015	227	20	generalization	generalization	NOUN
ajst-8015	227	21	ability	ability	NOUN
ajst-8015	227	22	on	on	ADP
ajst-8015	227	23	new	new	ADJ
ajst-8015	227	24	,	,	PUNCT
ajst-8015	227	25	unseen	unseen	ADJ
ajst-8015	227	26	data	datum	NOUN
ajst-8015	227	27	.	.	PUNCT
ajst-8015	228	1	this	this	PRON
ajst-8015	228	2	can	can	AUX
ajst-8015	228	3	lead	lead	VERB
ajst-8015	228	4	to	to	ADP
ajst-8015	228	5	overfitting	overfitte	VERB
ajst-8015	228	6	problems	problem	NOUN
ajst-8015	228	7	and	and	CCONJ
ajst-8015	228	8	difficulties	difficulty	NOUN
ajst-8015	228	9	in	in	ADP
ajst-8015	228	10	moving	move	VERB
ajst-8015	228	11	tasks	task	NOUN
ajst-8015	228	12	across	across	ADP
ajst-8015	228	13	domains	domain	NOUN
ajst-8015	228	14	.	.	PUNCT
ajst-8015	229	1	references	reference	NOUN
ajst-8015	229	2	[	[	X
ajst-8015	229	3	1	1	NUM
ajst-8015	229	4	]	]	PUNCT
ajst-8015	229	5	y.-g	y.-g	PROPN
ajst-8015	229	6	.	.	PUNCT
ajst-8015	230	1	chen	chen	PROPN
ajst-8015	230	2	,	,	PUNCT
ajst-8015	230	3	“	"	PUNCT
ajst-8015	230	4	research	research	NOUN
ajst-8015	230	5	progress	progress	NOUN
ajst-8015	230	6	in	in	ADP
ajst-8015	230	7	the	the	DET
ajst-8015	230	8	pathogenesis	pathogenesis	NOUN
ajst-8015	230	9	of	of	ADP
ajst-8015	230	10	alzheimer	alzheimer	PROPN
ajst-8015	230	11	’s	’s	PART
ajst-8015	230	12	disease	disease	NOUN
ajst-8015	230	13	,	,	PUNCT
ajst-8015	230	14	”	"	PUNCT
ajst-8015	230	15	chinese	chinese	ADJ
ajst-8015	230	16	medical	medical	ADJ
ajst-8015	230	17	journal	journal	PROPN
ajst-8015	230	18	,	,	PUNCT
ajst-8015	230	19	vol	vol	NOUN
ajst-8015	230	20	.	.	PROPN
ajst-8015	230	21	131	131	NUM
ajst-8015	230	22	,	,	PUNCT
ajst-8015	230	23	no	no	INTJ
ajst-8015	230	24	.	.	NOUN
ajst-8015	230	25	13	13	NUM
ajst-8015	230	26	,	,	PUNCT
ajst-8015	230	27	p.	p.	NOUN
ajst-8015	230	28	1618	1618	NUM
ajst-8015	230	29	,	,	PUNCT
ajst-8015	230	30	2018	2018	NUM
ajst-8015	230	31	.	.	PUNCT
ajst-8015	231	1	[	[	X
ajst-8015	231	2	2	2	NUM
ajst-8015	231	3	]	]	PUNCT
ajst-8015	231	4	c.	c.	PROPN
ajst-8015	231	5	patterson	patterson	PROPN
ajst-8015	231	6	,	,	PUNCT
ajst-8015	231	7	“	"	PUNCT
ajst-8015	231	8	the	the	DET
ajst-8015	231	9	state	state	NOUN
ajst-8015	231	10	of	of	ADP
ajst-8015	231	11	the	the	DET
ajst-8015	231	12	art	art	NOUN
ajst-8015	231	13	of	of	ADP
ajst-8015	231	14	dementia	dementia	NOUN
ajst-8015	231	15	research	research	NOUN
ajst-8015	231	16	:	:	PUNCT
ajst-8015	231	17	new	new	ADJ
ajst-8015	231	18	frontiers	frontier	NOUN
ajst-8015	231	19	,	,	PUNCT
ajst-8015	231	20	”	"	PUNCT
ajst-8015	231	21	world	world	PROPN
ajst-8015	231	22	alzheimer	alzheimer	PROPN
ajst-8015	231	23	report	report	PROPN
ajst-8015	231	24	,	,	PUNCT
ajst-8015	231	25	vol	vol	NOUN
ajst-8015	231	26	.	.	PROPN
ajst-8015	231	27	2018	2018	NUM
ajst-8015	231	28	,	,	PUNCT
ajst-8015	231	29	2018	2018	NUM
ajst-8015	231	30	.	.	PUNCT
ajst-8015	232	1	[	[	X
ajst-8015	232	2	3	3	NUM
ajst-8015	232	3	]	]	PUNCT
ajst-8015	232	4	x.	x.	NOUN
ajst-8015	232	5	wang	wang	PROPN
ajst-8015	232	6	,	,	PUNCT
ajst-8015	232	7	j.	j.	PROPN
ajst-8015	232	8	qi	qi	PROPN
ajst-8015	232	9	,	,	PUNCT
ajst-8015	232	10	y.	y.	PROPN
ajst-8015	232	11	yang	yang	PROPN
ajst-8015	232	12	,	,	PUNCT
ajst-8015	232	13	and	and	CCONJ
ajst-8015	232	14	p.	p.	PROPN
ajst-8015	232	15	yang	yang	PROPN
ajst-8015	232	16	,	,	PUNCT
ajst-8015	232	17	“	"	PUNCT
ajst-8015	232	18	a	a	DET
ajst-8015	232	19	survey	survey	NOUN
ajst-8015	232	20	of	of	ADP
ajst-8015	232	21	disease	disease	NOUN
ajst-8015	232	22	progression	progression	NOUN
ajst-8015	232	23	modeling	modeling	NOUN
ajst-8015	232	24	techniques	technique	NOUN
ajst-8015	232	25	for	for	ADP
ajst-8015	232	26	alzheimer	alzheimer	PROPN
ajst-8015	232	27	’s	’s	PART
ajst-8015	232	28	diseases	disease	NOUN
ajst-8015	232	29	,	,	PUNCT
ajst-8015	232	30	”	"	PUNCT
ajst-8015	232	31	in	in	ADP
ajst-8015	232	32	2019	2019	NUM
ajst-8015	232	33	ieee	ieee	NOUN
ajst-8015	232	34	17th	17th	ADJ
ajst-8015	232	35	international	international	ADJ
ajst-8015	232	36	conference	conference	NOUN
ajst-8015	232	37	on	on	ADP
ajst-8015	232	38	industrial	industrial	ADJ
ajst-8015	232	39	informatics	informatic	NOUN
ajst-8015	232	40	(	(	PUNCT
ajst-8015	232	41	indin	indin	NOUN
ajst-8015	232	42	)	)	PUNCT
ajst-8015	232	43	,	,	PUNCT
ajst-8015	232	44	ieee	ieee	NOUN
ajst-8015	232	45	,	,	PUNCT
ajst-8015	232	46	2019	2019	NUM
ajst-8015	232	47	,	,	PUNCT
ajst-8015	232	48	pp	pp	ADJ
ajst-8015	232	49	.	.	PUNCT
ajst-8015	233	1	1237–1242	1237–1242	NUM
ajst-8015	233	2	.	.	PUNCT
ajst-8015	234	1	[	[	X
ajst-8015	234	2	4	4	X
ajst-8015	234	3	]	]	X
ajst-8015	234	4	j.	j.	PROPN
ajst-8015	234	5	c.	c.	PROPN
ajst-8015	234	6	morris	morris	PROPN
ajst-8015	234	7	et	et	PROPN
ajst-8015	234	8	al	al	PROPN
ajst-8015	234	9	.	.	PROPN
ajst-8015	234	10	,	,	PUNCT
ajst-8015	234	11	“	"	PUNCT
ajst-8015	234	12	mild	mild	ADJ
ajst-8015	234	13	cognitive	cognitive	ADJ
ajst-8015	234	14	impairment	impairment	NOUN
ajst-8015	234	15	represents	represent	VERB
ajst-8015	234	16	early	early	ADJ
ajst-8015	234	17	-	-	PUNCT
ajst-8015	234	18	stage	stage	NOUN
ajst-8015	234	19	alzheimer	alzheimer	NOUN
ajst-8015	234	20	disease	disease	NOUN
ajst-8015	234	21	,	,	PUNCT
ajst-8015	234	22	”	"	PUNCT
ajst-8015	234	23	archives	archive	NOUN
ajst-8015	234	24	of	of	ADP
ajst-8015	234	25	neurology	neurology	NOUN
ajst-8015	234	26	,	,	PUNCT
ajst-8015	234	27	vol	vol	NOUN
ajst-8015	234	28	.	.	PROPN
ajst-8015	235	1	58	58	NUM
ajst-8015	235	2	,	,	PUNCT
ajst-8015	235	3	no	no	INTJ
ajst-8015	235	4	.	.	NOUN
ajst-8015	235	5	3	3	NUM
ajst-8015	235	6	,	,	PUNCT
ajst-8015	235	7	pp	pp	ADJ
ajst-8015	235	8	.	.	PUNCT
ajst-8015	236	1	397–405	397–405	NUM
ajst-8015	236	2	,	,	PUNCT
ajst-8015	236	3	2001	2001	NUM
ajst-8015	236	4	.	.	PUNCT
ajst-8015	237	1	[	[	X
ajst-8015	237	2	5	5	NUM
ajst-8015	237	3	]	]	PUNCT
ajst-8015	237	4	a.	a.	NOUN
ajst-8015	237	5	ward	ward	PROPN
ajst-8015	237	6	,	,	PUNCT
ajst-8015	237	7	s.	s.	PROPN
ajst-8015	237	8	tardiff	tardiff	PROPN
ajst-8015	237	9	,	,	PUNCT
ajst-8015	237	10	c.	c.	PROPN
ajst-8015	237	11	dye	dye	PROPN
ajst-8015	237	12	,	,	PUNCT
ajst-8015	237	13	and	and	CCONJ
ajst-8015	237	14	h.	h.	PROPN
ajst-8015	237	15	m.	m.	PROPN
ajst-8015	237	16	arrighi	arrighi	PROPN
ajst-8015	237	17	,	,	PUNCT
ajst-8015	237	18	“	"	PUNCT
ajst-8015	237	19	rate	rate	NOUN
ajst-8015	237	20	of	of	ADP
ajst-8015	237	21	conversion	conversion	NOUN
ajst-8015	237	22	from	from	ADP
ajst-8015	237	23	prodromal	prodromal	ADJ
ajst-8015	237	24	alzheimer	alzheimer	PROPN
ajst-8015	237	25	’s	’s	PART
ajst-8015	237	26	disease	disease	NOUN
ajst-8015	237	27	to	to	ADP
ajst-8015	237	28	alzheimer	alzheimer	PROPN
ajst-8015	237	29	’s	’s	PART
ajst-8015	237	30	dementia	dementia	PROPN
ajst-8015	237	31	:	:	PUNCT
ajst-8015	237	32	a	a	DET
ajst-8015	237	33	systematic	systematic	ADJ
ajst-8015	237	34	review	review	NOUN
ajst-8015	237	35	of	of	ADP
ajst-8015	237	36	the	the	DET
ajst-8015	237	37	literature	literature	NOUN
ajst-8015	237	38	,	,	PUNCT
ajst-8015	237	39	”	"	PUNCT
ajst-8015	237	40	dement	dement	PROPN
ajst-8015	237	41	geriatr	geriatr	PROPN
ajst-8015	237	42	cogn	cogn	VERB
ajst-8015	237	43	dis	dis	PROPN
ajst-8015	237	44	extra	extra	ADJ
ajst-8015	237	45	,	,	PUNCT
ajst-8015	237	46	vol	vol	NOUN
ajst-8015	237	47	.	.	PROPN
ajst-8015	238	1	3	3	NUM
ajst-8015	238	2	,	,	PUNCT
ajst-8015	238	3	no	no	INTJ
ajst-8015	238	4	.	.	NOUN
ajst-8015	238	5	1	1	NUM
ajst-8015	238	6	,	,	PUNCT
ajst-8015	238	7	pp	pp	ADJ
ajst-8015	238	8	.	.	PUNCT
ajst-8015	239	1	320–332	320–332	NUM
ajst-8015	239	2	,	,	PUNCT
ajst-8015	239	3	2013	2013	NUM
ajst-8015	239	4	,	,	PUNCT
ajst-8015	239	5	doi	doi	NOUN
ajst-8015	239	6	:	:	PUNCT
ajst-8015	239	7	10.1159/000354370	10.1159/000354370	NUM
ajst-8015	239	8	.	.	PUNCT
ajst-8015	240	1	[	[	X
ajst-8015	240	2	6	6	NUM
ajst-8015	240	3	]	]	PUNCT
ajst-8015	240	4	j.	j.	PROPN
ajst-8015	240	5	ashburner	ashburner	PROPN
ajst-8015	240	6	and	and	CCONJ
ajst-8015	240	7	k.	k.	PROPN
ajst-8015	240	8	j.	j.	PROPN
ajst-8015	240	9	friston	friston	PROPN
ajst-8015	240	10	,	,	PUNCT
ajst-8015	240	11	“	"	PUNCT
ajst-8015	240	12	voxel	voxel	PROPN
ajst-8015	240	13	-	-	PUNCT
ajst-8015	240	14	based	base	VERB
ajst-8015	240	15	morphometry	morphometry	NOUN
ajst-8015	240	16	—	—	PUNCT
ajst-8015	240	17	the	the	DET
ajst-8015	240	18	methods	method	NOUN
ajst-8015	240	19	,	,	PUNCT
ajst-8015	240	20	”	"	PUNCT
ajst-8015	240	21	neuroimage	neuroimage	NOUN
ajst-8015	240	22	,	,	PUNCT
ajst-8015	240	23	vol	vol	NOUN
ajst-8015	240	24	.	.	PROPN
ajst-8015	240	25	11	11	NUM
ajst-8015	240	26	,	,	PUNCT
ajst-8015	240	27	no	no	INTJ
ajst-8015	240	28	.	.	NOUN
ajst-8015	240	29	6	6	NUM
ajst-8015	240	30	,	,	PUNCT
ajst-8015	240	31	pp	pp	ADJ
ajst-8015	240	32	.	.	PUNCT
ajst-8015	241	1	805–821	805–821	NUM
ajst-8015	241	2	,	,	PUNCT
ajst-8015	241	3	2000	2000	NUM
ajst-8015	241	4	.	.	PUNCT
ajst-8015	242	1	[	[	X
ajst-8015	242	2	7	7	NUM
ajst-8015	242	3	]	]	X
ajst-8015	242	4	h.-i	h.-i	PROPN
ajst-8015	242	5	.	.	PUNCT
ajst-8015	242	6	suk	suk	PROPN
ajst-8015	242	7	,	,	PUNCT
ajst-8015	242	8	s.-w	s.-w	PROPN
ajst-8015	242	9	.	.	PUNCT
ajst-8015	243	1	lee	lee	PROPN
ajst-8015	243	2	,	,	PUNCT
ajst-8015	243	3	d.	d.	PROPN
ajst-8015	243	4	shen	shen	PROPN
ajst-8015	243	5	,	,	PUNCT
ajst-8015	243	6	and	and	CCONJ
ajst-8015	243	7	a.	a.	PROPN
ajst-8015	243	8	d.	d.	PROPN
ajst-8015	243	9	n.	n.	PROPN
ajst-8015	243	10	initiative	initiative	PROPN
ajst-8015	243	11	,	,	PUNCT
ajst-8015	243	12	“	"	PUNCT
ajst-8015	243	13	hierarchical	hierarchical	ADJ
ajst-8015	243	14	feature	feature	NOUN
ajst-8015	243	15	representation	representation	NOUN
ajst-8015	243	16	and	and	CCONJ
ajst-8015	243	17	multimodal	multimodal	NOUN
ajst-8015	243	18	fusion	fusion	NOUN
ajst-8015	243	19	with	with	ADP
ajst-8015	243	20	deep	deep	ADJ
ajst-8015	243	21	learning	learning	NOUN
ajst-8015	243	22	for	for	ADP
ajst-8015	243	23	ad	ad	NOUN
ajst-8015	243	24	/	/	SYM
ajst-8015	243	25	mci	mci	NOUN
ajst-8015	243	26	diagnosis	diagnosis	NOUN
ajst-8015	243	27	,	,	PUNCT
ajst-8015	243	28	”	"	PUNCT
ajst-8015	243	29	neuroimage	neuroimage	NOUN
ajst-8015	243	30	,	,	PUNCT
ajst-8015	243	31	vol	vol	NOUN
ajst-8015	243	32	.	.	PROPN
ajst-8015	244	1	101	101	NUM
ajst-8015	244	2	,	,	PUNCT
ajst-8015	244	3	pp	pp	ADJ
ajst-8015	244	4	.	.	PUNCT
ajst-8015	245	1	569–582	569–582	NUM
ajst-8015	245	2	,	,	PUNCT
ajst-8015	245	3	2014	2014	NUM
ajst-8015	245	4	.	.	PUNCT
ajst-8015	246	1	[	[	X
ajst-8015	246	2	8	8	X
ajst-8015	246	3	]	]	PUNCT
ajst-8015	246	4	j.	j.	PROPN
ajst-8015	246	5	zhang	zhang	PROPN
ajst-8015	246	6	,	,	PUNCT
ajst-8015	246	7	b.	b.	PROPN
ajst-8015	246	8	yan	yan	PROPN
ajst-8015	246	9	,	,	PUNCT
ajst-8015	246	10	x.	x.	PROPN
ajst-8015	246	11	huang	huang	PROPN
ajst-8015	246	12	,	,	PUNCT
ajst-8015	246	13	p.	p.	PROPN
ajst-8015	246	14	yang	yang	PROPN
ajst-8015	246	15	,	,	PUNCT
ajst-8015	246	16	and	and	CCONJ
ajst-8015	246	17	c.	c.	PROPN
ajst-8015	246	18	huang	huang	PROPN
ajst-8015	246	19	,	,	PUNCT
ajst-8015	246	20	“	"	PUNCT
ajst-8015	246	21	the	the	DET
ajst-8015	246	22	diagnosis	diagnosis	NOUN
ajst-8015	246	23	of	of	ADP
ajst-8015	246	24	alzheimer	alzheimer	PROPN
ajst-8015	246	25	’s	’s	PART
ajst-8015	246	26	disease	disease	NOUN
ajst-8015	246	27	based	base	VERB
ajst-8015	246	28	on	on	ADP
ajst-8015	246	29	voxel	voxel	PROPN
ajst-8015	246	30	-	-	PUNCT
ajst-8015	246	31	based	base	VERB
ajst-8015	246	32	morphometry	morphometry	NOUN
ajst-8015	246	33	and	and	CCONJ
ajst-8015	246	34	support	support	VERB
ajst-8015	246	35	vector	vector	NOUN
ajst-8015	246	36	machine	machine	NOUN
ajst-8015	246	37	,	,	PUNCT
ajst-8015	246	38	”	"	PUNCT
ajst-8015	246	39	in	in	ADP
ajst-8015	246	40	2008	2008	NUM
ajst-8015	246	41	fourth	fourth	ADJ
ajst-8015	246	42	international	international	ADJ
ajst-8015	246	43	conference	conference	NOUN
ajst-8015	246	44	on	on	ADP
ajst-8015	246	45	natural	natural	ADJ
ajst-8015	246	46	computation	computation	NOUN
ajst-8015	246	47	,	,	PUNCT
ajst-8015	246	48	ieee	ieee	NOUN
ajst-8015	246	49	,	,	PUNCT
ajst-8015	246	50	2008	2008	NUM
ajst-8015	246	51	,	,	PUNCT
ajst-8015	246	52	pp	pp	ADJ
ajst-8015	246	53	.	.	PUNCT
ajst-8015	247	1	197–201	197–201	NUM
ajst-8015	247	2	.	.	PUNCT
ajst-8015	248	1	[	[	X
ajst-8015	248	2	9	9	NUM
ajst-8015	248	3	]	]	X
ajst-8015	248	4	c.	c.	NOUN
ajst-8015	248	5	good	good	PROPN
ajst-8015	248	6	,	,	PUNCT
ajst-8015	248	7	i.	i.	PROPN
ajst-8015	248	8	johnsrude	johnsrude	PROPN
ajst-8015	248	9	,	,	PUNCT
ajst-8015	248	10	j.	j.	PROPN
ajst-8015	248	11	ashburner	ashburner	PROPN
ajst-8015	248	12	,	,	PUNCT
ajst-8015	248	13	k.	k.	PROPN
ajst-8015	248	14	friston	friston	PROPN
ajst-8015	248	15	,	,	PUNCT
ajst-8015	248	16	and	and	CCONJ
ajst-8015	248	17	r.	r.	PROPN
ajst-8015	248	18	frackowiak	frackowiak	PROPN
ajst-8015	248	19	,	,	PUNCT
ajst-8015	248	20	“	"	PUNCT
ajst-8015	248	21	voxel	voxel	PROPN
ajst-8015	248	22	based	base	VERB
ajst-8015	248	23	morphometry	morphometry	NOUN
ajst-8015	248	24	of	of	ADP
ajst-8015	248	25	465	465	NUM
ajst-8015	248	26	normal	normal	ADJ
ajst-8015	248	27	adult	adult	NOUN
ajst-8015	248	28	human	human	ADJ
ajst-8015	248	29	brains	brain	NOUN
ajst-8015	248	30	,	,	PUNCT
ajst-8015	248	31	”	"	PUNCT
ajst-8015	248	32	neuroimage	neuroimage	NOUN
ajst-8015	248	33	,	,	PUNCT
ajst-8015	248	34	vol	vol	NOUN
ajst-8015	248	35	.	.	PROPN
ajst-8015	249	1	11	11	NUM
ajst-8015	249	2	,	,	PUNCT
ajst-8015	249	3	no	no	INTJ
ajst-8015	249	4	.	.	NOUN
ajst-8015	249	5	5	5	NUM
ajst-8015	249	6	,	,	PUNCT
ajst-8015	250	1	p.	p.	NOUN
ajst-8015	250	2	s607	s607	PROPN
ajst-8015	250	3	,	,	PUNCT
ajst-8015	250	4	2000	2000	NUM
ajst-8015	250	5	.	.	PUNCT
ajst-8015	251	1	[	[	X
ajst-8015	251	2	10	10	NUM
ajst-8015	251	3	]	]	X
ajst-8015	251	4	a.	a.	NOUN
ajst-8015	251	5	ortiz	ortiz	PROPN
ajst-8015	251	6	,	,	PUNCT
ajst-8015	251	7	j.	j.	PROPN
ajst-8015	251	8	munilla	munilla	PROPN
ajst-8015	251	9	,	,	PUNCT
ajst-8015	251	10	j.	j.	PROPN
ajst-8015	251	11	m.	m.	PROPN
ajst-8015	251	12	gorriz	gorriz	PROPN
ajst-8015	251	13	,	,	PUNCT
ajst-8015	251	14	and	and	CCONJ
ajst-8015	251	15	j.	j.	PROPN
ajst-8015	251	16	ramirez	ramirez	PROPN
ajst-8015	251	17	,	,	PUNCT
ajst-8015	251	18	“	"	PUNCT
ajst-8015	251	19	ensembles	ensemble	NOUN
ajst-8015	251	20	of	of	ADP
ajst-8015	251	21	deep	deep	ADJ
ajst-8015	251	22	learning	learning	NOUN
ajst-8015	251	23	architectures	architecture	NOUN
ajst-8015	251	24	for	for	ADP
ajst-8015	251	25	the	the	DET
ajst-8015	251	26	early	early	ADJ
ajst-8015	251	27	diagnosis	diagnosis	NOUN
ajst-8015	251	28	of	of	ADP
ajst-8015	251	29	the	the	DET
ajst-8015	251	30	alzheimer	alzheimer	PROPN
ajst-8015	251	31	’s	’s	PART
ajst-8015	251	32	disease	disease	NOUN
ajst-8015	251	33	,	,	PUNCT
ajst-8015	251	34	”	"	PUNCT
ajst-8015	251	35	international	international	ADJ
ajst-8015	251	36	journal	journal	NOUN
ajst-8015	251	37	of	of	ADP
ajst-8015	251	38	neural	neural	ADJ
ajst-8015	251	39	systems	system	NOUN
ajst-8015	251	40	,	,	PUNCT
ajst-8015	251	41	vol	vol	NOUN
ajst-8015	251	42	.	.	PROPN
ajst-8015	251	43	26	26	NUM
ajst-8015	251	44	,	,	PUNCT
ajst-8015	251	45	no	no	INTJ
ajst-8015	251	46	.	.	NOUN
ajst-8015	251	47	07	07	NUM
ajst-8015	251	48	,	,	PUNCT
ajst-8015	251	49	p.	p.	NOUN
ajst-8015	251	50	1650025	1650025	NUM
ajst-8015	251	51	,	,	PUNCT
ajst-8015	251	52	2016	2016	NUM
ajst-8015	251	53	.	.	PUNCT
ajst-8015	252	1	[	[	X
ajst-8015	252	2	11	11	NUM
ajst-8015	252	3	]	]	PUNCT
ajst-8015	252	4	c.-y	c.-y	NOUN
ajst-8015	252	5	.	.	PUNCT
ajst-8015	253	1	wee	wee	ADJ
ajst-8015	253	2	,	,	PUNCT
ajst-8015	253	3	p.-t	p.-t	NOUN
ajst-8015	253	4	.	.	PUNCT
ajst-8015	254	1	yap	yap	PROPN
ajst-8015	254	2	,	,	PUNCT
ajst-8015	254	3	d.	d.	PROPN
ajst-8015	254	4	shen	shen	PROPN
ajst-8015	254	5	,	,	PUNCT
ajst-8015	254	6	and	and	CCONJ
ajst-8015	254	7	a.	a.	PROPN
ajst-8015	254	8	d.	d.	PROPN
ajst-8015	254	9	n.	n.	PROPN
ajst-8015	254	10	initiative	initiative	PROPN
ajst-8015	254	11	,	,	PUNCT
ajst-8015	254	12	“	"	PUNCT
ajst-8015	254	13	prediction	prediction	NOUN
ajst-8015	254	14	of	of	ADP
ajst-8015	254	15	alzheimer	alzheimer	PROPN
ajst-8015	254	16	’s	’s	PART
ajst-8015	254	17	disease	disease	NOUN
ajst-8015	254	18	and	and	CCONJ
ajst-8015	254	19	mild	mild	ADJ
ajst-8015	254	20	cognitive	cognitive	ADJ
ajst-8015	254	21	impairment	impairment	NOUN
ajst-8015	254	22	using	use	VERB
ajst-8015	254	23	cortical	cortical	ADJ
ajst-8015	254	24	morphological	morphological	ADJ
ajst-8015	254	25	patterns	pattern	NOUN
ajst-8015	254	26	,	,	PUNCT
ajst-8015	254	27	”	"	PUNCT
ajst-8015	254	28	human	human	ADJ
ajst-8015	254	29	brain	brain	NOUN
ajst-8015	254	30	mapping	mapping	NOUN
ajst-8015	254	31	,	,	PUNCT
ajst-8015	254	32	vol	vol	NOUN
ajst-8015	254	33	.	.	PROPN
ajst-8015	255	1	34	34	NUM
ajst-8015	255	2	,	,	PUNCT
ajst-8015	255	3	no	no	INTJ
ajst-8015	255	4	.	.	NOUN
ajst-8015	255	5	12	12	NUM
ajst-8015	255	6	,	,	PUNCT
ajst-8015	255	7	pp	pp	ADJ
ajst-8015	255	8	.	.	PUNCT
ajst-8015	256	1	3411–3425	3411–3425	NUM
ajst-8015	256	2	,	,	PUNCT
ajst-8015	256	3	2013	2013	NUM
ajst-8015	256	4	.	.	PUNCT
ajst-8015	257	1	[	[	X
ajst-8015	257	2	12	12	NUM
ajst-8015	257	3	]	]	X
ajst-8015	257	4	r.	r.	PROPN
ajst-8015	257	5	cui	cui	PROPN
ajst-8015	257	6	and	and	CCONJ
ajst-8015	257	7	m.	m.	PROPN
ajst-8015	257	8	liu	liu	PROPN
ajst-8015	257	9	,	,	PUNCT
ajst-8015	257	10	“	"	PUNCT
ajst-8015	257	11	hippocampus	hippocampus	VERB
ajst-8015	257	12	analysis	analysis	NOUN
ajst-8015	257	13	by	by	ADP
ajst-8015	257	14	combination	combination	NOUN
ajst-8015	257	15	of	of	ADP
ajst-8015	257	16	3	3	NUM
ajst-8015	257	17	-	-	PUNCT
ajst-8015	257	18	d	d	NOUN
ajst-8015	257	19	densenet	densenet	NOUN
ajst-8015	257	20	and	and	CCONJ
ajst-8015	257	21	shapes	shape	NOUN
ajst-8015	257	22	for	for	ADP
ajst-8015	257	23	alzheimer	alzheimer	PROPN
ajst-8015	257	24	’s	’s	PART
ajst-8015	257	25	disease	disease	NOUN
ajst-8015	257	26	diagnosis	diagnosis	NOUN
ajst-8015	257	27	,	,	PUNCT
ajst-8015	257	28	”	"	PUNCT
ajst-8015	257	29	ieee	ieee	NOUN
ajst-8015	257	30	journal	journal	NOUN
ajst-8015	257	31	of	of	ADP
ajst-8015	257	32	biomedical	biomedical	ADJ
ajst-8015	257	33	and	and	CCONJ
ajst-8015	257	34	health	health	NOUN
ajst-8015	257	35	informatics	informatic	NOUN
ajst-8015	257	36	,	,	PUNCT
ajst-8015	257	37	vol	vol	NOUN
ajst-8015	257	38	.	.	PROPN
ajst-8015	257	39	23	23	NUM
ajst-8015	257	40	,	,	PUNCT
ajst-8015	257	41	no	no	INTJ
ajst-8015	257	42	.	.	NOUN
ajst-8015	257	43	5	5	NUM
ajst-8015	257	44	,	,	PUNCT
ajst-8015	257	45	pp	pp	ADJ
ajst-8015	257	46	.	.	PUNCT
ajst-8015	258	1	2099–2107	2099–2107	NUM
ajst-8015	258	2	,	,	PUNCT
ajst-8015	258	3	2018	2018	NUM
ajst-8015	258	4	.	.	PUNCT
ajst-8015	259	1	[	[	X
ajst-8015	259	2	13	13	NUM
ajst-8015	259	3	]	]	X
ajst-8015	259	4	f.	f.	PROPN
ajst-8015	259	5	li	li	PROPN
ajst-8015	259	6	,	,	PUNCT
ajst-8015	259	7	m.	m.	PROPN
ajst-8015	259	8	liu	liu	PROPN
ajst-8015	259	9	,	,	PUNCT
ajst-8015	259	10	and	and	CCONJ
ajst-8015	259	11	a.	a.	PROPN
ajst-8015	259	12	d.	d.	PROPN
ajst-8015	259	13	n.	n.	PROPN
ajst-8015	259	14	initiative	initiative	PROPN
ajst-8015	259	15	,	,	PUNCT
ajst-8015	259	16	“	"	PUNCT
ajst-8015	259	17	a	a	DET
ajst-8015	259	18	hybrid	hybrid	ADJ
ajst-8015	259	19	convolutional	convolutional	ADJ
ajst-8015	259	20	and	and	CCONJ
ajst-8015	259	21	recurrent	recurrent	ADJ
ajst-8015	259	22	neural	neural	ADJ
ajst-8015	259	23	network	network	NOUN
ajst-8015	259	24	for	for	ADP
ajst-8015	259	25	hippocampus	hippocampus	NOUN
ajst-8015	259	26	analysis	analysis	NOUN
ajst-8015	259	27	in	in	ADP
ajst-8015	259	28	alzheimer	alzheimer	PROPN
ajst-8015	259	29	’s	’s	PART
ajst-8015	259	30	disease	disease	NOUN
ajst-8015	259	31	,	,	PUNCT
ajst-8015	259	32	”	"	PUNCT
ajst-8015	259	33	journal	journal	NOUN
ajst-8015	259	34	of	of	ADP
ajst-8015	259	35	neuroscience	neuroscience	NOUN
ajst-8015	259	36	methods	method	NOUN
ajst-8015	259	37	,	,	PUNCT
ajst-8015	259	38	vol	vol	NOUN
ajst-8015	259	39	.	.	PROPN
ajst-8015	259	40	323	323	NUM
ajst-8015	259	41	,	,	PUNCT
ajst-8015	259	42	pp	pp	ADJ
ajst-8015	259	43	.	.	PUNCT
ajst-8015	260	1	108–118	108–118	NUM
ajst-8015	260	2	,	,	PUNCT
ajst-8015	260	3	2019	2019	NUM
ajst-8015	260	4	.	.	PUNCT
ajst-8015	261	1	[	[	X
ajst-8015	261	2	14	14	NUM
ajst-8015	261	3	]	]	PUNCT
ajst-8015	261	4	m.	m.	NOUN
ajst-8015	261	5	liu	liu	PROPN
ajst-8015	261	6	,	,	PUNCT
ajst-8015	261	7	d.	d.	PROPN
ajst-8015	261	8	zhang	zhang	PROPN
ajst-8015	261	9	,	,	PUNCT
ajst-8015	261	10	d.	d.	PROPN
ajst-8015	261	11	shen	shen	PROPN
ajst-8015	261	12	,	,	PUNCT
ajst-8015	261	13	and	and	CCONJ
ajst-8015	261	14	a.	a.	PROPN
ajst-8015	261	15	d.	d.	PROPN
ajst-8015	261	16	n.	n.	PROPN
ajst-8015	261	17	initiative	initiative	PROPN
ajst-8015	261	18	,	,	PUNCT
ajst-8015	261	19	“	"	PUNCT
ajst-8015	261	20	ensemble	ensemble	ADJ
ajst-8015	261	21	sparse	sparse	ADJ
ajst-8015	261	22	classification	classification	NOUN
ajst-8015	261	23	of	of	ADP
ajst-8015	261	24	alzheimer	alzheimer	PROPN
ajst-8015	261	25	’s	’s	PART
ajst-8015	261	26	disease	disease	NOUN
ajst-8015	261	27	,	,	PUNCT
ajst-8015	261	28	”	"	PUNCT
ajst-8015	261	29	neuroimage	neuroimage	NOUN
ajst-8015	261	30	,	,	PUNCT
ajst-8015	261	31	vol	vol	NOUN
ajst-8015	261	32	.	.	PROPN
ajst-8015	261	33	60	60	NUM
ajst-8015	261	34	,	,	PUNCT
ajst-8015	261	35	no	no	INTJ
ajst-8015	261	36	.	.	NOUN
ajst-8015	261	37	2	2	NUM
ajst-8015	261	38	,	,	PUNCT
ajst-8015	261	39	pp	pp	ADJ
ajst-8015	261	40	.	.	PUNCT
ajst-8015	261	41	1106–1116	1106–1116	NUM
ajst-8015	261	42	,	,	PUNCT
ajst-8015	261	43	2012	2012	NUM
ajst-8015	261	44	.	.	PUNCT
ajst-8015	262	1	[	[	X
ajst-8015	262	2	15	15	NUM
ajst-8015	262	3	]	]	X
ajst-8015	262	4	m.	m.	NOUN
ajst-8015	262	5	liu	liu	PROPN
ajst-8015	262	6	,	,	PUNCT
ajst-8015	262	7	d.	d.	PROPN
ajst-8015	262	8	zhang	zhang	PROPN
ajst-8015	262	9	,	,	PUNCT
ajst-8015	262	10	d.	d.	PROPN
ajst-8015	262	11	shen	shen	PROPN
ajst-8015	262	12	,	,	PUNCT
ajst-8015	262	13	and	and	CCONJ
ajst-8015	262	14	a.	a.	PROPN
ajst-8015	262	15	d.	d.	PROPN
ajst-8015	262	16	n.	n.	PROPN
ajst-8015	262	17	initiative	initiative	PROPN
ajst-8015	262	18	,	,	PUNCT
ajst-8015	262	19	“	"	PUNCT
ajst-8015	262	20	hierarchical	hierarchical	ADJ
ajst-8015	262	21	fusion	fusion	NOUN
ajst-8015	262	22	of	of	ADP
ajst-8015	262	23	features	feature	NOUN
ajst-8015	262	24	and	and	CCONJ
ajst-8015	262	25	classifier	classifier	NOUN
ajst-8015	262	26	decisions	decision	NOUN
ajst-8015	262	27	for	for	ADP
ajst-8015	262	28	alzheimer	alzheimer	PROPN
ajst-8015	262	29	’s	’s	PART
ajst-8015	262	30	disease	disease	NOUN
ajst-8015	262	31	diagnosis	diagnosis	NOUN
ajst-8015	262	32	,	,	PUNCT
ajst-8015	262	33	”	"	PUNCT
ajst-8015	262	34	human	human	ADJ
ajst-8015	262	35	brain	brain	NOUN
ajst-8015	262	36	mapping	mapping	NOUN
ajst-8015	262	37	,	,	PUNCT
ajst-8015	262	38	vol	vol	NOUN
ajst-8015	262	39	.	.	PROPN
ajst-8015	262	40	35	35	NUM
ajst-8015	262	41	,	,	PUNCT
ajst-8015	262	42	no	no	INTJ
ajst-8015	262	43	.	.	NOUN
ajst-8015	262	44	4	4	NUM
ajst-8015	262	45	,	,	PUNCT
ajst-8015	262	46	pp	pp	ADJ
ajst-8015	262	47	.	.	PUNCT
ajst-8015	263	1	1305–1319	1305–1319	NUM
ajst-8015	263	2	,	,	PUNCT
ajst-8015	263	3	2014	2014	NUM
ajst-8015	263	4	.	.	PUNCT
ajst-8015	264	1	[	[	X
ajst-8015	264	2	16	16	NUM
ajst-8015	264	3	]	]	X
ajst-8015	264	4	f.	f.	PROPN
ajst-8015	264	5	li	li	PROPN
ajst-8015	264	6	,	,	PUNCT
ajst-8015	264	7	m.	m.	PROPN
ajst-8015	264	8	liu	liu	PROPN
ajst-8015	264	9	,	,	PUNCT
ajst-8015	264	10	and	and	CCONJ
ajst-8015	264	11	a.	a.	PROPN
ajst-8015	264	12	d.	d.	PROPN
ajst-8015	264	13	n.	n.	PROPN
ajst-8015	264	14	initiative	initiative	PROPN
ajst-8015	264	15	,	,	PUNCT
ajst-8015	264	16	“	"	PUNCT
ajst-8015	264	17	alzheimer	alzheimer	X
ajst-8015	264	18	’s	’s	PART
ajst-8015	264	19	disease	disease	NOUN
ajst-8015	264	20	diagnosis	diagnosis	NOUN
ajst-8015	264	21	based	base	VERB
ajst-8015	264	22	on	on	ADP
ajst-8015	264	23	multiple	multiple	ADJ
ajst-8015	264	24	cluster	cluster	NOUN
ajst-8015	264	25	dense	dense	ADJ
ajst-8015	264	26	convolutional	convolutional	ADJ
ajst-8015	264	27	networks	network	NOUN
ajst-8015	264	28	,	,	PUNCT
ajst-8015	264	29	”	"	PUNCT
ajst-8015	264	30	computerized	computerized	ADJ
ajst-8015	264	31	medical	medical	ADJ
ajst-8015	264	32	imaging	imaging	NOUN
ajst-8015	264	33	and	and	CCONJ
ajst-8015	264	34	graphics	graphic	NOUN
ajst-8015	264	35	,	,	PUNCT
ajst-8015	264	36	vol	vol	NOUN
ajst-8015	264	37	.	.	PROPN
ajst-8015	264	38	70	70	NUM
ajst-8015	264	39	,	,	PUNCT
ajst-8015	264	40	pp	pp	ADJ
ajst-8015	264	41	.	.	PUNCT
ajst-8015	265	1	101–110	101–110	NUM
ajst-8015	265	2	,	,	PUNCT
ajst-8015	265	3	2018	2018	NUM
ajst-8015	265	4	.	.	PUNCT
ajst-8015	266	1	[	[	X
ajst-8015	266	2	17	17	NUM
ajst-8015	266	3	]	]	PUNCT
ajst-8015	266	4	m.	m.	NOUN
ajst-8015	266	5	liu	liu	PROPN
ajst-8015	266	6	,	,	PUNCT
ajst-8015	266	7	j.	j.	PROPN
ajst-8015	266	8	zhang	zhang	PROPN
ajst-8015	266	9	,	,	PUNCT
ajst-8015	266	10	e.	e.	PROPN
ajst-8015	266	11	adeli	adeli	PROPN
ajst-8015	266	12	,	,	PUNCT
ajst-8015	266	13	and	and	CCONJ
ajst-8015	266	14	d.	d.	PROPN
ajst-8015	266	15	shen	shen	PROPN
ajst-8015	266	16	,	,	PUNCT
ajst-8015	266	17	“	"	PUNCT
ajst-8015	266	18	joint	joint	ADJ
ajst-8015	266	19	classification	classification	NOUN
ajst-8015	266	20	and	and	CCONJ
ajst-8015	266	21	regression	regression	NOUN
ajst-8015	266	22	via	via	ADP
ajst-8015	266	23	deep	deep	ADJ
ajst-8015	266	24	multi	multi	ADJ
ajst-8015	266	25	-	-	ADJ
ajst-8015	266	26	task	task	ADJ
ajst-8015	266	27	multi	multi	ADJ
ajst-8015	266	28	-	-	ADJ
ajst-8015	266	29	channel	channel	ADJ
ajst-8015	266	30	learning	learning	NOUN
ajst-8015	266	31	for	for	ADP
ajst-8015	266	32	alzheimer	alzheimer	PROPN
ajst-8015	266	33	’s	’s	PART
ajst-8015	266	34	disease	disease	NOUN
ajst-8015	266	35	diagnosis	diagnosis	NOUN
ajst-8015	266	36	,	,	PUNCT
ajst-8015	266	37	”	"	PUNCT
ajst-8015	266	38	ieee	ieee	NOUN
ajst-8015	266	39	transactions	transaction	NOUN
ajst-8015	266	40	on	on	ADP
ajst-8015	266	41	biomedical	biomedical	ADJ
ajst-8015	266	42	engineering	engineering	NOUN
ajst-8015	266	43	,	,	PUNCT
ajst-8015	266	44	vol	vol	NOUN
ajst-8015	266	45	.	.	PROPN
ajst-8015	266	46	66	66	NUM
ajst-8015	266	47	,	,	PUNCT
ajst-8015	266	48	no	no	INTJ
ajst-8015	266	49	.	.	NOUN
ajst-8015	266	50	5	5	NUM
ajst-8015	266	51	,	,	PUNCT
ajst-8015	266	52	pp	pp	ADJ
ajst-8015	266	53	.	.	PUNCT
ajst-8015	266	54	1195–1206	1195–1206	NUM
ajst-8015	266	55	,	,	PUNCT
ajst-8015	266	56	2018	2018	NUM
ajst-8015	266	57	.	.	PUNCT
ajst-8015	267	1	[	[	X
ajst-8015	267	2	18	18	NUM
ajst-8015	267	3	]	]	X
ajst-8015	267	4	s.	s.	PROPN
ajst-8015	267	5	ahmed	ahme	VERB
ajst-8015	267	6	et	et	PROPN
ajst-8015	267	7	al	al	PROPN
ajst-8015	267	8	.	.	PROPN
ajst-8015	267	9	,	,	PUNCT
ajst-8015	267	10	“	"	PUNCT
ajst-8015	267	11	ensembles	ensemble	NOUN
ajst-8015	267	12	of	of	ADP
ajst-8015	267	13	patch	patch	NOUN
ajst-8015	267	14	-	-	PUNCT
ajst-8015	267	15	based	base	VERB
ajst-8015	267	16	classifiers	classifier	NOUN
ajst-8015	267	17	for	for	ADP
ajst-8015	267	18	diagnosis	diagnosis	NOUN
ajst-8015	267	19	of	of	ADP
ajst-8015	267	20	alzheimer	alzheimer	NOUN
ajst-8015	267	21	diseases	disease	NOUN
ajst-8015	267	22	,	,	PUNCT
ajst-8015	267	23	”	"	PUNCT
ajst-8015	267	24	ieee	ieee	NOUN
ajst-8015	267	25	access	access	NOUN
ajst-8015	267	26	,	,	PUNCT
ajst-8015	267	27	vol	vol	NOUN
ajst-8015	267	28	.	.	PROPN
ajst-8015	267	29	7	7	NUM
ajst-8015	267	30	,	,	PUNCT
ajst-8015	267	31	pp	pp	ADJ
ajst-8015	267	32	.	.	PUNCT
ajst-8015	268	1	73373–73383	73373–73383	NUM
ajst-8015	268	2	,	,	PUNCT
ajst-8015	268	3	2019	2019	NUM
ajst-8015	268	4	.	.	PUNCT
ajst-8015	269	1	[	[	X
ajst-8015	269	2	19	19	NUM
ajst-8015	269	3	]	]	X
ajst-8015	269	4	j.	j.	PROPN
ajst-8015	269	5	islam	islam	PROPN
ajst-8015	269	6	and	and	CCONJ
ajst-8015	269	7	y.	y.	PROPN
ajst-8015	269	8	zhang	zhang	PROPN
ajst-8015	269	9	,	,	PUNCT
ajst-8015	269	10	“	"	PUNCT
ajst-8015	269	11	a	a	DET
ajst-8015	269	12	novel	novel	ADJ
ajst-8015	269	13	deep	deep	ADJ
ajst-8015	269	14	learning	learning	NOUN
ajst-8015	269	15	based	base	VERB
ajst-8015	269	16	multi	multi	ADJ
ajst-8015	269	17	-	-	ADJ
ajst-8015	269	18	class	class	ADJ
ajst-8015	269	19	classification	classification	NOUN
ajst-8015	269	20	method	method	NOUN
ajst-8015	269	21	for	for	ADP
ajst-8015	269	22	alzheimer	alzheimer	PROPN
ajst-8015	269	23	’s	’s	PART
ajst-8015	269	24	disease	disease	NOUN
ajst-8015	269	25	detection	detection	NOUN
ajst-8015	269	26	using	use	VERB
ajst-8015	269	27	brain	brain	NOUN
ajst-8015	269	28	mri	mri	NOUN
ajst-8015	269	29	data	datum	NOUN
ajst-8015	269	30	,	,	PUNCT
ajst-8015	269	31	”	"	PUNCT
ajst-8015	269	32	in	in	ADP
ajst-8015	269	33	international	international	ADJ
ajst-8015	269	34	conference	conference	NOUN
ajst-8015	269	35	on	on	ADP
ajst-8015	269	36	brain	brain	NOUN
ajst-8015	269	37	informatics	informatic	NOUN
ajst-8015	269	38	,	,	PUNCT
ajst-8015	269	39	springer	springer	NOUN
ajst-8015	269	40	,	,	PUNCT
ajst-8015	269	41	2017	2017	NUM
ajst-8015	269	42	,	,	PUNCT
ajst-8015	269	43	pp	pp	ADJ
ajst-8015	269	44	.	.	PUNCT
ajst-8015	270	1	213–222	213–222	NUM
ajst-8015	270	2	.	.	PUNCT
ajst-8015	271	1	[	[	X
ajst-8015	271	2	20	20	NUM
ajst-8015	271	3	]	]	PUNCT
ajst-8015	271	4	s.	s.	PROPN
ajst-8015	271	5	luo	luo	PROPN
ajst-8015	271	6	,	,	PUNCT
ajst-8015	271	7	x.	x.	PROPN
ajst-8015	271	8	li	li	PROPN
ajst-8015	271	9	,	,	PUNCT
ajst-8015	271	10	and	and	CCONJ
ajst-8015	271	11	j.	j.	PROPN
ajst-8015	271	12	li	li	PROPN
ajst-8015	271	13	,	,	PUNCT
ajst-8015	271	14	“	"	PUNCT
ajst-8015	271	15	automatic	automatic	ADJ
ajst-8015	271	16	alzheimer	alzheimer	PROPN
ajst-8015	271	17	’s	’s	PART
ajst-8015	271	18	disease	disease	NOUN
ajst-8015	271	19	recognition	recognition	NOUN
ajst-8015	271	20	from	from	ADP
ajst-8015	271	21	mri	mri	NOUN
ajst-8015	271	22	data	datum	NOUN
ajst-8015	271	23	using	use	VERB
ajst-8015	271	24	deep	deep	ADJ
ajst-8015	271	25	learning	learning	NOUN
ajst-8015	271	26	method	method	NOUN
ajst-8015	271	27	,	,	PUNCT
ajst-8015	271	28	”	"	PUNCT
ajst-8015	271	29	journal	journal	NOUN
ajst-8015	271	30	of	of	ADP
ajst-8015	271	31	applied	apply	VERB
ajst-8015	271	32	mathematics	mathematic	NOUN
ajst-8015	271	33	and	and	CCONJ
ajst-8015	271	34	physics	physics	NOUN
ajst-8015	271	35	,	,	PUNCT
ajst-8015	271	36	vol	vol	NOUN
ajst-8015	271	37	.	.	PROPN
ajst-8015	271	38	5	5	NUM
ajst-8015	271	39	,	,	PUNCT
ajst-8015	271	40	no	no	INTJ
ajst-8015	271	41	.	.	NOUN
ajst-8015	271	42	9	9	NUM
ajst-8015	271	43	,	,	PUNCT
ajst-8015	271	44	pp	pp	ADJ
ajst-8015	271	45	.	.	PUNCT
ajst-8015	271	46	1892–1898	1892–1898	NUM
ajst-8015	271	47	,	,	PUNCT
ajst-8015	271	48	2017	2017	NUM
ajst-8015	271	49	.	.	PUNCT
ajst-8015	272	1	[	[	X
ajst-8015	272	2	21	21	NUM
ajst-8015	272	3	]	]	PUNCT
ajst-8015	272	4	the	the	DET
ajst-8015	272	5	alzheimer	alzheimer	PROPN
ajst-8015	272	6	’s	’s	PART
ajst-8015	272	7	disease	disease	NOUN
ajst-8015	272	8	neuroimaging	neuroimaging	NOUN
ajst-8015	272	9	initiative	initiative	NOUN
ajst-8015	272	10	et	et	PROPN
ajst-8015	272	11	al	al	PROPN
ajst-8015	272	12	.	.	PROPN
ajst-8015	272	13	,	,	PUNCT
ajst-8015	272	14	“	"	PUNCT
ajst-8015	272	15	discrimination	discrimination	NOUN
ajst-8015	272	16	and	and	CCONJ
ajst-8015	272	17	conversion	conversion	NOUN
ajst-8015	272	18	prediction	prediction	NOUN
ajst-8015	272	19	of	of	ADP
ajst-8015	272	20	mild	mild	ADJ
ajst-8015	272	21	cognitive	cognitive	ADJ
ajst-8015	272	22	impairment	impairment	NOUN
ajst-8015	272	23	using	use	VERB
ajst-8015	272	24	convolutional	convolutional	ADJ
ajst-8015	272	25	neural	neural	ADJ
ajst-8015	272	26	networks	network	NOUN
ajst-8015	272	27	,	,	PUNCT
ajst-8015	272	28	”	"	PUNCT
ajst-8015	272	29	quant	quant	NOUN
ajst-8015	272	30	.	.	PUNCT
ajst-8015	273	1	imaging	imaging	PROPN
ajst-8015	273	2	med	med	PROPN
ajst-8015	273	3	.	.	PUNCT
ajst-8015	273	4	surg	surg	PROPN
ajst-8015	273	5	,	,	PUNCT
ajst-8015	273	6	vol	vol	NOUN
ajst-8015	273	7	.	.	PROPN
ajst-8015	273	8	8	8	NUM
ajst-8015	273	9	,	,	PUNCT
ajst-8015	273	10	no	no	INTJ
ajst-8015	273	11	.	.	NOUN
ajst-8015	273	12	10	10	NUM
ajst-8015	273	13	,	,	PUNCT
ajst-8015	273	14	pp	pp	ADJ
ajst-8015	273	15	.	.	PUNCT
ajst-8015	274	1	992–1003	992–1003	NUM
ajst-8015	274	2	,	,	PUNCT
ajst-8015	274	3	nov	nov	PROPN
ajst-8015	274	4	.	.	PROPN
ajst-8015	274	5	2018	2018	NUM
ajst-8015	274	6	,	,	PUNCT
ajst-8015	274	7	doi	doi	NOUN
ajst-8015	274	8	:	:	PUNCT
ajst-8015	274	9	10.21037	10.21037	NUM
ajst-8015	274	10	/	/	SYM
ajst-8015	274	11	qims.2018.10.17	qims.2018.10.17	NOUN
ajst-8015	274	12	.	.	PUNCT
ajst-8015	275	1	[	[	X
ajst-8015	275	2	22	22	NUM
ajst-8015	275	3	]	]	PUNCT
ajst-8015	275	4	l.	l.	PROPN
ajst-8015	275	5	gao	gao	PROPN
ajst-8015	275	6	et	et	PROPN
ajst-8015	275	7	al	al	PROPN
ajst-8015	275	8	.	.	PROPN
ajst-8015	275	9	,	,	PUNCT
ajst-8015	275	10	“	"	PUNCT
ajst-8015	275	11	brain	brain	NOUN
ajst-8015	275	12	disease	disease	NOUN
ajst-8015	275	13	diagnosis	diagnosis	NOUN
ajst-8015	275	14	using	use	VERB
ajst-8015	275	15	deep	deep	ADJ
ajst-8015	275	16	learning	learning	NOUN
ajst-8015	275	17	features	feature	NOUN
ajst-8015	275	18	from	from	ADP
ajst-8015	275	19	longitudinal	longitudinal	ADJ
ajst-8015	275	20	mr	mr	PROPN
ajst-8015	275	21	images	image	NOUN
ajst-8015	275	22	,	,	PUNCT
ajst-8015	275	23	”	"	PUNCT
ajst-8015	275	24	in	in	ADP
ajst-8015	275	25	asia	asia	PROPN
ajst-8015	275	26	-	-	PUNCT
ajst-8015	275	27	pacific	pacific	PROPN
ajst-8015	275	28	web	web	NOUN
ajst-8015	275	29	(	(	PUNCT
ajst-8015	275	30	apweb	apweb	NOUN
ajst-8015	275	31	)	)	PUNCT
ajst-8015	275	32	and	and	CCONJ
ajst-8015	275	33	web	web	NOUN
ajst-8015	275	34	-	-	ADJ
ajst-8015	275	35	age	age	ADJ
ajst-8015	275	36	information	information	NOUN
ajst-8015	275	37	management	management	NOUN
ajst-8015	275	38	(	(	PUNCT
ajst-8015	275	39	waim	waim	NOUN
ajst-8015	275	40	)	)	PUNCT
ajst-8015	275	41	joint	joint	ADJ
ajst-8015	275	42	international	international	ADJ
ajst-8015	275	43	conference	conference	NOUN
ajst-8015	275	44	on	on	ADP
ajst-8015	275	45	web	web	NOUN
ajst-8015	275	46	and	and	CCONJ
ajst-8015	275	47	big	big	ADJ
ajst-8015	275	48	data	datum	NOUN
ajst-8015	275	49	,	,	PUNCT
ajst-8015	275	50	springer	springer	NOUN
ajst-8015	275	51	,	,	PUNCT
ajst-8015	275	52	2018	2018	NUM
ajst-8015	275	53	,	,	PUNCT
ajst-8015	275	54	pp	pp	ADJ
ajst-8015	275	55	.	.	PUNCT
ajst-8015	276	1	327–339	327–339	NUM
ajst-8015	276	2	.	.	PUNCT
ajst-8015	277	1	[	[	X
ajst-8015	277	2	23	23	NUM
ajst-8015	277	3	]	]	X
ajst-8015	277	4	r.	r.	PROPN
ajst-8015	277	5	jain	jain	PROPN
ajst-8015	277	6	,	,	PUNCT
ajst-8015	277	7	n.	n.	PROPN
ajst-8015	277	8	jain	jain	PROPN
ajst-8015	277	9	,	,	PUNCT
ajst-8015	277	10	a.	a.	NOUN
ajst-8015	277	11	aggarwal	aggarwal	NOUN
ajst-8015	277	12	,	,	PUNCT
ajst-8015	277	13	and	and	CCONJ
ajst-8015	277	14	d.	d.	PROPN
ajst-8015	277	15	j.	j.	PROPN
ajst-8015	277	16	hemanth	hemanth	PROPN
ajst-8015	277	17	,	,	PUNCT
ajst-8015	277	18	“	"	PUNCT
ajst-8015	277	19	convolutional	convolutional	ADJ
ajst-8015	277	20	neural	neural	ADJ
ajst-8015	277	21	network	network	NOUN
ajst-8015	277	22	based	base	VERB
ajst-8015	277	23	alzheimer	alzheimer	PROPN
ajst-8015	277	24	’s	’s	PART
ajst-8015	277	25	disease	disease	NOUN
ajst-8015	277	26	classification	classification	NOUN
ajst-8015	277	27	from	from	ADP
ajst-8015	277	28	magnetic	magnetic	ADJ
ajst-8015	277	29	resonance	resonance	NOUN
ajst-8015	277	30	brain	brain	NOUN
ajst-8015	277	31	images	image	NOUN
ajst-8015	277	32	,	,	PUNCT
ajst-8015	277	33	”	"	PUNCT
ajst-8015	277	34	cognitive	cognitive	ADJ
ajst-8015	277	35	systems	system	NOUN
ajst-8015	277	36	research	research	NOUN
ajst-8015	277	37	,	,	PUNCT
ajst-8015	277	38	vol	vol	NOUN
ajst-8015	277	39	.	.	PROPN
ajst-8015	277	40	57	57	NUM
ajst-8015	277	41	,	,	PUNCT
ajst-8015	277	42	pp	pp	ADJ
ajst-8015	277	43	.	.	PUNCT
ajst-8015	278	1	147–159	147–159	NUM
ajst-8015	278	2	,	,	PUNCT
ajst-8015	278	3	2019	2019	NUM
ajst-8015	278	4	.	.	PUNCT
ajst-8015	279	1	[	[	X
ajst-8015	279	2	24	24	NUM
ajst-8015	279	3	]	]	PUNCT
ajst-8015	279	4	s.	s.	PROPN
ajst-8015	279	5	korolev	korolev	PROPN
ajst-8015	279	6	,	,	PUNCT
ajst-8015	279	7	a.	a.	NOUN
ajst-8015	279	8	safiullin	safiullin	PROPN
ajst-8015	279	9	,	,	PUNCT
ajst-8015	279	10	m.	m.	NOUN
ajst-8015	279	11	belyaev	belyaev	PROPN
ajst-8015	279	12	,	,	PUNCT
ajst-8015	279	13	and	and	CCONJ
ajst-8015	279	14	y.	y.	PROPN
ajst-8015	279	15	dodonova	dodonova	PROPN
ajst-8015	279	16	,	,	PUNCT
ajst-8015	279	17	“	"	PUNCT
ajst-8015	279	18	residual	residual	ADJ
ajst-8015	279	19	and	and	CCONJ
ajst-8015	279	20	plain	plain	ADJ
ajst-8015	279	21	convolutional	convolutional	ADJ
ajst-8015	279	22	neural	neural	ADJ
ajst-8015	279	23	networks	network	NOUN
ajst-8015	279	24	for	for	ADP
ajst-8015	279	25	3d	3d	NUM
ajst-8015	279	26	brain	brain	NOUN
ajst-8015	279	27	mri	mri	NOUN
ajst-8015	279	28	classification	classification	NOUN
ajst-8015	279	29	,	,	PUNCT
ajst-8015	279	30	”	"	PUNCT
ajst-8015	279	31	in	in	ADP
ajst-8015	279	32	2017	2017	NUM
ajst-8015	279	33	ieee	ieee	NOUN
ajst-8015	279	34	14th	14th	ADJ
ajst-8015	279	35	international	international	ADJ
ajst-8015	279	36	symposium	symposium	NOUN
ajst-8015	279	37	on	on	ADP
ajst-8015	279	38	biomedical	biomedical	ADJ
ajst-8015	279	39	imaging	imaging	NOUN
ajst-8015	279	40	(	(	PUNCT
ajst-8015	279	41	isbi	isbi	NOUN
ajst-8015	279	42	2017	2017	NUM
ajst-8015	279	43	)	)	PUNCT
ajst-8015	279	44	,	,	PUNCT
ajst-8015	279	45	ieee	ieee	NOUN
ajst-8015	279	46	,	,	PUNCT
ajst-8015	279	47	2017	2017	NUM
ajst-8015	279	48	,	,	PUNCT
ajst-8015	279	49	pp	pp	ADJ
ajst-8015	279	50	.	.	PUNCT
ajst-8015	280	1	835–838	835–838	NUM
ajst-8015	280	2	.	.	PUNCT
ajst-8015	281	1	[	[	X
ajst-8015	281	2	25	25	NUM
ajst-8015	281	3	]	]	PUNCT
ajst-8015	281	4	k.	k.	PROPN
ajst-8015	281	5	bäckström	bäckström	PROPN
ajst-8015	281	6	,	,	PUNCT
ajst-8015	281	7	m.	m.	NOUN
ajst-8015	281	8	nazari	nazari	PROPN
ajst-8015	281	9	,	,	PUNCT
ajst-8015	281	10	i.	i.	PROPN
ajst-8015	281	11	y.-h	y.-h	PROPN
ajst-8015	281	12	.	.	PUNCT
ajst-8015	282	1	gu	gu	PROPN
ajst-8015	282	2	,	,	PUNCT
ajst-8015	282	3	and	and	CCONJ
ajst-8015	282	4	a.	a.	PROPN
ajst-8015	282	5	s.	s.	PROPN
ajst-8015	282	6	jakola	jakola	PROPN
ajst-8015	282	7	,	,	PUNCT
ajst-8015	282	8	“	"	PUNCT
ajst-8015	282	9	an	an	DET
ajst-8015	282	10	efficient	efficient	ADJ
ajst-8015	282	11	3d	3d	NOUN
ajst-8015	282	12	deep	deep	ADJ
ajst-8015	282	13	convolutional	convolutional	ADJ
ajst-8015	282	14	network	network	NOUN
ajst-8015	282	15	for	for	ADP
ajst-8015	282	16	alzheimer	alzheimer	PROPN
ajst-8015	282	17	’s	’s	PART
ajst-8015	282	18	disease	disease	NOUN
ajst-8015	282	19	diagnosis	diagnosis	NOUN
ajst-8015	282	20	using	use	VERB
ajst-8015	282	21	mr	mr	PROPN
ajst-8015	282	22	images	image	NOUN
ajst-8015	282	23	,	,	PUNCT
ajst-8015	282	24	”	"	PUNCT
ajst-8015	282	25	in	in	ADP
ajst-8015	282	26	2018	2018	NUM
ajst-8015	282	27	ieee	ieee	NOUN
ajst-8015	282	28	15th	15th	ADJ
ajst-8015	282	29	international	international	ADJ
ajst-8015	282	30	symposium	symposium	NOUN
ajst-8015	282	31	on	on	ADP
ajst-8015	282	32	biomedical	biomedical	ADJ
ajst-8015	282	33	imaging	imaging	NOUN
ajst-8015	282	34	(	(	PUNCT
ajst-8015	282	35	isbi	isbi	NOUN
ajst-8015	282	36	2018	2018	NUM
ajst-8015	282	37	)	)	PUNCT
ajst-8015	282	38	,	,	PUNCT
ajst-8015	282	39	ieee	ieee	NOUN
ajst-8015	282	40	,	,	PUNCT
ajst-8015	282	41	2018	2018	NUM
ajst-8015	282	42	,	,	PUNCT
ajst-8015	282	43	pp	pp	ADJ
ajst-8015	282	44	.	.	PUNCT
ajst-8015	283	1	149–153	149–153	NUM
ajst-8015	283	2	.	.	PUNCT
ajst-8015	284	1	[	[	X
ajst-8015	284	2	26	26	NUM
ajst-8015	284	3	]	]	X
ajst-8015	284	4	s.	s.	PROPN
ajst-8015	284	5	basaia	basaia	PROPN
ajst-8015	284	6	et	et	PROPN
ajst-8015	284	7	al	al	PROPN
ajst-8015	284	8	.	.	PROPN
ajst-8015	284	9	,	,	PUNCT
ajst-8015	284	10	“	"	PUNCT
ajst-8015	284	11	automated	automate	VERB
ajst-8015	284	12	classification	classification	NOUN
ajst-8015	284	13	of	of	ADP
ajst-8015	284	14	alzheimer	alzheimer	PROPN
ajst-8015	284	15	’s	’s	PART
ajst-8015	284	16	disease	disease	NOUN
ajst-8015	284	17	and	and	CCONJ
ajst-8015	284	18	mild	mild	ADJ
ajst-8015	284	19	cognitive	cognitive	ADJ
ajst-8015	284	20	impairment	impairment	NOUN
ajst-8015	284	21	using	use	VERB
ajst-8015	284	22	a	a	DET
ajst-8015	284	23	single	single	ADJ
ajst-8015	284	24	mri	mri	NOUN
ajst-8015	284	25	and	and	CCONJ
ajst-8015	284	26	deep	deep	ADJ
ajst-8015	284	27	neural	neural	ADJ
ajst-8015	284	28	networks	network	NOUN
ajst-8015	284	29	,	,	PUNCT
ajst-8015	284	30	”	"	PUNCT
ajst-8015	284	31	neuroimage	neuroimage	NOUN
ajst-8015	284	32	:	:	PUNCT
ajst-8015	284	33	clinical	clinical	ADJ
ajst-8015	284	34	,	,	PUNCT
ajst-8015	284	35	vol	vol	NOUN
ajst-8015	284	36	.	.	PROPN
ajst-8015	284	37	21	21	NUM
ajst-8015	284	38	,	,	PUNCT
ajst-8015	284	39	p.	p.	NOUN
ajst-8015	284	40	101645	101645	NUM
ajst-8015	284	41	,	,	PUNCT
ajst-8015	284	42	2019	2019	NUM
ajst-8015	284	43	.	.	PUNCT
ajst-8015	285	1	[	[	X
ajst-8015	285	2	27	27	NUM
ajst-8015	285	3	]	]	X
ajst-8015	285	4	h.	h.	PROPN
ajst-8015	285	5	wang	wang	PROPN
ajst-8015	285	6	et	et	PROPN
ajst-8015	285	7	al	al	PROPN
ajst-8015	285	8	.	.	PROPN
ajst-8015	285	9	,	,	PUNCT
ajst-8015	285	10	“	"	PUNCT
ajst-8015	285	11	ensemble	ensemble	ADJ
ajst-8015	285	12	of	of	ADP
ajst-8015	285	13	3d	3d	NUM
ajst-8015	285	14	densely	densely	ADV
ajst-8015	285	15	connected	connect	VERB
ajst-8015	285	16	convolutional	convolutional	ADJ
ajst-8015	285	17	network	network	NOUN
ajst-8015	285	18	for	for	ADP
ajst-8015	285	19	diagnosis	diagnosis	NOUN
ajst-8015	285	20	of	of	ADP
ajst-8015	285	21	mild	mild	ADJ
ajst-8015	285	22	cognitive	cognitive	ADJ
ajst-8015	285	23	impairment	impairment	NOUN
ajst-8015	285	24	and	and	CCONJ
ajst-8015	285	25	alzheimer	alzheimer	PROPN
ajst-8015	285	26	’s	’s	PART
ajst-8015	285	27	disease	disease	NOUN
ajst-8015	285	28	,	,	PUNCT
ajst-8015	285	29	”	"	PUNCT
ajst-8015	285	30	neurocomputing	neurocomputing	NOUN
ajst-8015	285	31	,	,	PUNCT
ajst-8015	285	32	vol	vol	NOUN
ajst-8015	285	33	.	.	NOUN
ajst-8015	285	34	333	333	NUM
ajst-8015	285	35	,	,	PUNCT
ajst-8015	285	36	pp	pp	ADJ
ajst-8015	285	37	.	.	PUNCT
ajst-8015	286	1	145–156	145–156	NUM
ajst-8015	286	2	,	,	PUNCT
ajst-8015	286	3	2019	2019	NUM
ajst-8015	286	4	.	.	PUNCT
ajst-8015	287	1	[	[	X
ajst-8015	287	2	28	28	NUM
ajst-8015	287	3	]	]	X
ajst-8015	287	4	m.	m.	NOUN
ajst-8015	287	5	turk	turk	PROPN
ajst-8015	287	6	and	and	CCONJ
ajst-8015	287	7	a.	a.	PROPN
ajst-8015	287	8	pentland	pentland	PROPN
ajst-8015	287	9	,	,	PUNCT
ajst-8015	287	10	“	"	PUNCT
ajst-8015	287	11	eigenfaces	eigenface	NOUN
ajst-8015	287	12	for	for	ADP
ajst-8015	287	13	recognition	recognition	NOUN
ajst-8015	287	14	,	,	PUNCT
ajst-8015	287	15	”	"	PUNCT
ajst-8015	287	16	journal	journal	NOUN
ajst-8015	287	17	of	of	ADP
ajst-8015	287	18	cognitive	cognitive	ADJ
ajst-8015	287	19	neuroscience	neuroscience	NOUN
ajst-8015	287	20	,	,	PUNCT
ajst-8015	287	21	vol	vol	NOUN
ajst-8015	287	22	.	.	PROPN
ajst-8015	288	1	3	3	NUM
ajst-8015	288	2	,	,	PUNCT
ajst-8015	288	3	no	no	INTJ
ajst-8015	288	4	.	.	NOUN
ajst-8015	288	5	1	1	NUM
ajst-8015	288	6	,	,	PUNCT
ajst-8015	288	7	pp	pp	ADJ
ajst-8015	288	8	.	.	PUNCT
ajst-8015	289	1	71–86	71–86	NUM
ajst-8015	289	2	,	,	PUNCT
ajst-8015	289	3	1991	1991	NUM
ajst-8015	289	4	.	.	PUNCT
ajst-8015	290	1	[	[	X
ajst-8015	290	2	29	29	NUM
ajst-8015	290	3	]	]	X
ajst-8015	290	4	l.	l.	PROPN
ajst-8015	290	5	khedher	khedher	PROPN
ajst-8015	290	6	,	,	PUNCT
ajst-8015	290	7	j.	j.	PROPN
ajst-8015	290	8	ramírez	ramírez	PROPN
ajst-8015	290	9	,	,	PUNCT
ajst-8015	290	10	j.	j.	PROPN
ajst-8015	290	11	m.	m.	PROPN
ajst-8015	290	12	górriz	górriz	PROPN
ajst-8015	290	13	,	,	PUNCT
ajst-8015	290	14	a.	a.	PROPN
ajst-8015	290	15	brahim	brahim	PROPN
ajst-8015	290	16	,	,	PUNCT
ajst-8015	290	17	f.	f.	PROPN
ajst-8015	290	18	segovia	segovia	PROPN
ajst-8015	290	19	,	,	PUNCT
ajst-8015	290	20	and	and	CCONJ
ajst-8015	290	21	a.	a.	PROPN
ajst-8015	290	22	s	s	PROPN
ajst-8015	290	23	d.	d.	PROPN
ajst-8015	290	24	n.	n.	PROPN
ajst-8015	290	25	initiative	initiative	PROPN
ajst-8015	290	26	,	,	PUNCT
ajst-8015	290	27	“	"	PUNCT
ajst-8015	290	28	early	early	ADJ
ajst-8015	290	29	diagnosis	diagnosis	NOUN
ajst-8015	290	30	of	of	ADP
ajst-8015	290	31	alzheimer׳	alzheimer׳	PROPN
ajst-8015	290	32	s	s	PART
ajst-8015	290	33	disease	disease	NOUN
ajst-8015	290	34	based	base	VERB
ajst-8015	290	35	on	on	ADP
ajst-8015	290	36	partial	partial	ADJ
ajst-8015	290	37	least	least	ADJ
ajst-8015	290	38	squares	square	NOUN
ajst-8015	290	39	,	,	PUNCT
ajst-8015	290	40	principal	principal	ADJ
ajst-8015	290	41	component	component	NOUN
ajst-8015	290	42	analysis	analysis	NOUN
ajst-8015	290	43	and	and	CCONJ
ajst-8015	290	44	support	support	NOUN
ajst-8015	290	45	vector	vector	NOUN
ajst-8015	290	46	machine	machine	NOUN
ajst-8015	290	47	using	use	VERB
ajst-8015	290	48	segmented	segment	VERB
ajst-8015	290	49	mri	mri	NOUN
ajst-8015	290	50	images	image	NOUN
ajst-8015	290	51	,	,	PUNCT
ajst-8015	290	52	”	"	PUNCT
ajst-8015	290	53	neurocomputing	neurocomputing	NOUN
ajst-8015	290	54	,	,	PUNCT
ajst-8015	290	55	vol	vol	NOUN
ajst-8015	290	56	.	.	PROPN
ajst-8015	290	57	151	151	NUM
ajst-8015	290	58	,	,	PUNCT
ajst-8015	290	59	pp	pp	ADJ
ajst-8015	290	60	.	.	PUNCT
ajst-8015	291	1	139–150	139–150	NUM
ajst-8015	291	2	,	,	PUNCT
ajst-8015	291	3	2015	2015	NUM
ajst-8015	291	4	.	.	PUNCT
ajst-8015	292	1	[	[	X
ajst-8015	292	2	30	30	NUM
ajst-8015	292	3	]	]	X
ajst-8015	292	4	l.	l.	PROPN
ajst-8015	292	5	mesrob	mesrob	ADV
ajst-8015	292	6	et	et	PROPN
ajst-8015	292	7	al	al	PROPN
ajst-8015	292	8	.	.	PROPN
ajst-8015	292	9	,	,	PUNCT
ajst-8015	292	10	“	"	PUNCT
ajst-8015	292	11	identification	identification	NOUN
ajst-8015	292	12	of	of	ADP
ajst-8015	292	13	atrophy	atrophy	NOUN
ajst-8015	292	14	patterns	pattern	NOUN
ajst-8015	292	15	in	in	ADP
ajst-8015	292	16	alzheimer	alzheimer	PROPN
ajst-8015	292	17	’s	’s	PART
ajst-8015	292	18	disease	disease	NOUN
ajst-8015	292	19	based	base	VERB
ajst-8015	292	20	on	on	ADP
ajst-8015	292	21	svm	svm	ADJ
ajst-8015	292	22	feature	feature	NOUN
ajst-8015	292	23	selection	selection	NOUN
ajst-8015	292	24	and	and	CCONJ
ajst-8015	292	25	anatomical	anatomical	ADJ
ajst-8015	292	26	parcellation	parcellation	NOUN
ajst-8015	292	27	,	,	PUNCT
ajst-8015	292	28	”	"	PUNCT
ajst-8015	292	29	in	in	ADP
ajst-8015	292	30	international	international	ADJ
ajst-8015	292	31	workshop	workshop	NOUN
ajst-8015	292	32	on	on	ADP
ajst-8015	292	33	medical	medical	ADJ
ajst-8015	292	34	imaging	imaging	NOUN
ajst-8015	292	35	and	and	CCONJ
ajst-8015	292	36	virtual	virtual	ADJ
ajst-8015	292	37	reality	reality	NOUN
ajst-8015	292	38	,	,	PUNCT
ajst-8015	292	39	springer	springer	NOUN
ajst-8015	292	40	,	,	PUNCT
ajst-8015	292	41	2008	2008	NUM
ajst-8015	292	42	,	,	PUNCT
ajst-8015	292	43	pp	pp	ADJ
ajst-8015	292	44	.	.	PUNCT
ajst-8015	293	1	124	124	NUM
ajst-8015	293	2	–	–	PUNCT
ajst-8015	293	3	132	132	NUM
ajst-8015	293	4	.	.	NOUN
ajst-8015	293	5	221	221	NUM
ajst-8015	294	1	[	[	X
ajst-8015	294	2	31	31	NUM
ajst-8015	294	3	]	]	PUNCT
ajst-8015	294	4	s.	s.	PROPN
ajst-8015	294	5	i.	i.	PROPN
ajst-8015	294	6	dimitriadis	dimitriadis	PROPN
ajst-8015	294	7	,	,	PUNCT
ajst-8015	294	8	d.	d.	PROPN
ajst-8015	294	9	liparas	liparas	PROPN
ajst-8015	294	10	,	,	PUNCT
ajst-8015	294	11	m.	m.	NOUN
ajst-8015	294	12	n.	n.	PROPN
ajst-8015	294	13	tsolaki	tsolaki	PROPN
ajst-8015	294	14	,	,	PUNCT
ajst-8015	294	15	and	and	CCONJ
ajst-8015	294	16	a.	a.	PROPN
ajst-8015	294	17	d.	d.	PROPN
ajst-8015	294	18	n.	n.	PROPN
ajst-8015	294	19	initiative	initiative	PROPN
ajst-8015	294	20	,	,	PUNCT
ajst-8015	294	21	“	"	PUNCT
ajst-8015	294	22	random	random	ADJ
ajst-8015	294	23	forest	forest	NOUN
ajst-8015	294	24	feature	feature	NOUN
ajst-8015	294	25	selection	selection	NOUN
ajst-8015	294	26	,	,	PUNCT
ajst-8015	294	27	fusion	fusion	NOUN
ajst-8015	294	28	and	and	CCONJ
ajst-8015	294	29	ensemble	ensemble	ADJ
ajst-8015	294	30	strategy	strategy	NOUN
ajst-8015	294	31	:	:	PUNCT
ajst-8015	294	32	combining	combine	VERB
ajst-8015	294	33	multiple	multiple	ADJ
ajst-8015	294	34	morphological	morphological	ADJ
ajst-8015	294	35	mri	mri	NOUN
ajst-8015	294	36	measures	measure	NOUN
ajst-8015	294	37	to	to	PART
ajst-8015	294	38	discriminate	discriminate	VERB
ajst-8015	294	39	among	among	ADP
ajst-8015	294	40	healhy	healhy	ADJ
ajst-8015	294	41	elderly	elderly	ADJ
ajst-8015	294	42	,	,	PUNCT
ajst-8015	294	43	mci	mci	PROPN
ajst-8015	294	44	,	,	PUNCT
ajst-8015	294	45	cmci	cmci	NOUN
ajst-8015	294	46	and	and	CCONJ
ajst-8015	294	47	alzheimer	alzheimer	PROPN
ajst-8015	294	48	’s	’s	PART
ajst-8015	294	49	disease	disease	NOUN
ajst-8015	294	50	patients	patient	NOUN
ajst-8015	294	51	:	:	PUNCT
ajst-8015	294	52	from	from	ADP
ajst-8015	294	53	the	the	DET
ajst-8015	294	54	alzheimer	alzheimer	PROPN
ajst-8015	294	55	’s	’s	PART
ajst-8015	294	56	disease	disease	NOUN
ajst-8015	294	57	neuroimaging	neuroimaging	NOUN
ajst-8015	294	58	initiative	initiative	NOUN
ajst-8015	294	59	(	(	PUNCT
ajst-8015	294	60	adni	adni	ADJ
ajst-8015	294	61	)	)	PUNCT
ajst-8015	294	62	database	database	NOUN
ajst-8015	294	63	,	,	PUNCT
ajst-8015	294	64	”	"	PUNCT
ajst-8015	294	65	journal	journal	NOUN
ajst-8015	294	66	of	of	ADP
ajst-8015	294	67	neuroscience	neuroscience	NOUN
ajst-8015	294	68	methods	method	NOUN
ajst-8015	294	69	,	,	PUNCT
ajst-8015	294	70	vol	vol	NOUN
ajst-8015	294	71	.	.	PROPN
ajst-8015	294	72	302	302	NUM
ajst-8015	294	73	,	,	PUNCT
ajst-8015	294	74	pp	pp	ADJ
ajst-8015	294	75	.	.	PUNCT
ajst-8015	295	1	14–23	14–23	NUM
ajst-8015	295	2	,	,	PUNCT
ajst-8015	295	3	2018	2018	NUM
ajst-8015	295	4	.	.	PUNCT
ajst-8015	296	1	[	[	X
ajst-8015	296	2	32	32	NUM
ajst-8015	296	3	]	]	PUNCT
ajst-8015	296	4	p.	p.	PROPN
ajst-8015	296	5	telagarapu	telagarapu	PROPN
ajst-8015	296	6	,	,	PUNCT
ajst-8015	296	7	b.	b.	PROPN
ajst-8015	296	8	mohanty	mohanty	PROPN
ajst-8015	296	9	,	,	PUNCT
ajst-8015	296	10	and	and	CCONJ
ajst-8015	296	11	k.	k.	PROPN
ajst-8015	296	12	r.	r.	PROPN
ajst-8015	296	13	anandh	anandh	PROPN
ajst-8015	296	14	,	,	PUNCT
ajst-8015	296	15	“	"	PUNCT
ajst-8015	296	16	analysis	analysis	NOUN
ajst-8015	296	17	of	of	ADP
ajst-8015	296	18	alzheimer	alzheimer	NOUN
ajst-8015	296	19	condition	condition	NOUN
ajst-8015	296	20	in	in	ADP
ajst-8015	296	21	t1	t1	PROPN
ajst-8015	296	22	-	-	PUNCT
ajst-8015	296	23	weighted	weight	VERB
ajst-8015	296	24	mr	mr	PROPN
ajst-8015	296	25	images	image	NOUN
ajst-8015	296	26	using	use	VERB
ajst-8015	296	27	texture	texture	NOUN
ajst-8015	296	28	features	feature	NOUN
ajst-8015	296	29	and	and	CCONJ
ajst-8015	296	30	k	k	PROPN
ajst-8015	296	31	-	-	PUNCT
ajst-8015	296	32	nn	nn	PROPN
ajst-8015	296	33	classifier	classifier	NOUN
ajst-8015	296	34	,	,	PUNCT
ajst-8015	296	35	”	"	PUNCT
ajst-8015	296	36	in	in	ADP
ajst-8015	296	37	2018	2018	NUM
ajst-8015	296	38	international	international	PROPN
ajst-8015	296	39	cet	cet	PROPN
ajst-8015	296	40	conference	conference	NOUN
ajst-8015	296	41	on	on	ADP
ajst-8015	296	42	control	control	NOUN
ajst-8015	296	43	,	,	PUNCT
ajst-8015	296	44	communication	communication	NOUN
ajst-8015	296	45	,	,	PUNCT
ajst-8015	296	46	and	and	CCONJ
ajst-8015	296	47	computing	computing	NOUN
ajst-8015	296	48	(	(	PUNCT
ajst-8015	296	49	ic4	ic4	NOUN
ajst-8015	296	50	)	)	PUNCT
ajst-8015	296	51	,	,	PUNCT
ajst-8015	296	52	ieee	ieee	NOUN
ajst-8015	296	53	,	,	PUNCT
ajst-8015	296	54	2018	2018	NUM
ajst-8015	296	55	,	,	PUNCT
ajst-8015	296	56	pp	pp	ADJ
ajst-8015	296	57	.	.	PUNCT
ajst-8015	297	1	331–334	331–334	NUM
ajst-8015	297	2	.	.	PUNCT
ajst-8015	298	1	[	[	X
ajst-8015	298	2	33	33	NUM
ajst-8015	298	3	]	]	PUNCT
ajst-8015	298	4	s.-h	s.-h	NOUN
ajst-8015	298	5	.	.	PUNCT
ajst-8015	299	1	wang	wang	PROPN
ajst-8015	299	2	,	,	PUNCT
ajst-8015	299	3	p.	p.	PROPN
ajst-8015	299	4	phillips	phillips	PROPN
ajst-8015	299	5	,	,	PUNCT
ajst-8015	299	6	y.	y.	PROPN
ajst-8015	299	7	sui	sui	PROPN
ajst-8015	299	8	,	,	PUNCT
ajst-8015	299	9	b.	b.	PROPN
ajst-8015	299	10	liu	liu	PROPN
ajst-8015	299	11	,	,	PUNCT
ajst-8015	299	12	m.	m.	PROPN
ajst-8015	299	13	yang	yang	PROPN
ajst-8015	299	14	,	,	PUNCT
ajst-8015	299	15	and	and	CCONJ
ajst-8015	299	16	h.	h.	PROPN
ajst-8015	299	17	cheng	cheng	PROPN
ajst-8015	299	18	,	,	PUNCT
ajst-8015	299	19	“	"	PUNCT
ajst-8015	299	20	classification	classification	NOUN
ajst-8015	299	21	of	of	ADP
ajst-8015	299	22	alzheimer	alzheimer	PROPN
ajst-8015	299	23	’s	’s	PART
ajst-8015	299	24	disease	disease	NOUN
ajst-8015	299	25	based	base	VERB
ajst-8015	299	26	on	on	ADP
ajst-8015	299	27	eight	eight	NUM
ajst-8015	299	28	-	-	PUNCT
ajst-8015	299	29	layer	layer	NOUN
ajst-8015	299	30	convolutional	convolutional	ADJ
ajst-8015	299	31	neural	neural	ADJ
ajst-8015	299	32	network	network	NOUN
ajst-8015	299	33	with	with	ADP
ajst-8015	299	34	leaky	leaky	ADJ
ajst-8015	299	35	rectified	rectified	ADJ
ajst-8015	299	36	linear	linear	NOUN
ajst-8015	299	37	unit	unit	NOUN
ajst-8015	299	38	and	and	CCONJ
ajst-8015	299	39	max	max	PROPN
ajst-8015	299	40	pooling	pooling	PROPN
ajst-8015	299	41	,	,	PUNCT
ajst-8015	299	42	”	"	PUNCT
ajst-8015	299	43	journal	journal	NOUN
ajst-8015	299	44	of	of	ADP
ajst-8015	299	45	medical	medical	ADJ
ajst-8015	299	46	systems	system	NOUN
ajst-8015	299	47	,	,	PUNCT
ajst-8015	299	48	vol	vol	NOUN
ajst-8015	299	49	.	.	PROPN
ajst-8015	299	50	42	42	NUM
ajst-8015	299	51	,	,	PUNCT
ajst-8015	299	52	no	no	INTJ
ajst-8015	299	53	.	.	NOUN
ajst-8015	299	54	5	5	NUM
ajst-8015	299	55	,	,	PUNCT
ajst-8015	299	56	pp	pp	PROPN
ajst-8015	299	57	.	.	PUNCT
ajst-8015	300	1	1–11	1–11	NOUN
ajst-8015	300	2	,	,	PUNCT
ajst-8015	300	3	2018	2018	NUM
ajst-8015	300	4	.	.	PUNCT
ajst-8015	301	1	[	[	X
ajst-8015	301	2	34	34	NUM
ajst-8015	301	3	]	]	PUNCT
ajst-8015	301	4	j.	j.	PROPN
ajst-8015	301	5	liu	liu	PROPN
ajst-8015	301	6	et	et	PROPN
ajst-8015	301	7	al	al	PROPN
ajst-8015	301	8	.	.	PROPN
ajst-8015	301	9	,	,	PUNCT
ajst-8015	301	10	“	"	PUNCT
ajst-8015	301	11	applications	application	NOUN
ajst-8015	301	12	of	of	ADP
ajst-8015	301	13	deep	deep	ADJ
ajst-8015	301	14	learning	learning	NOUN
ajst-8015	301	15	to	to	PART
ajst-8015	301	16	mri	mri	VERB
ajst-8015	301	17	images	image	NOUN
ajst-8015	301	18	:	:	PUNCT
ajst-8015	301	19	a	a	DET
ajst-8015	301	20	survey	survey	NOUN
ajst-8015	301	21	,	,	PUNCT
ajst-8015	301	22	”	"	PUNCT
ajst-8015	301	23	big	big	ADJ
ajst-8015	301	24	data	datum	NOUN
ajst-8015	301	25	mining	mining	NOUN
ajst-8015	301	26	and	and	CCONJ
ajst-8015	301	27	analytics	analytic	NOUN
ajst-8015	301	28	,	,	PUNCT
ajst-8015	301	29	vol	vol	NOUN
ajst-8015	301	30	.	.	PROPN
ajst-8015	301	31	1	1	NUM
ajst-8015	301	32	,	,	PUNCT
ajst-8015	301	33	no	no	INTJ
ajst-8015	301	34	.	.	NOUN
ajst-8015	301	35	1	1	NUM
ajst-8015	301	36	,	,	PUNCT
ajst-8015	301	37	pp	pp	ADJ
ajst-8015	301	38	.	.	PUNCT
ajst-8015	301	39	1	1	NUM
ajst-8015	301	40	–	–	PUNCT
ajst-8015	301	41	18	18	NUM
ajst-8015	301	42	,	,	PUNCT
ajst-8015	301	43	2018	2018	NUM
ajst-8015	301	44	.	.	PUNCT
ajst-8015	302	1	[	[	X
ajst-8015	302	2	35	35	NUM
ajst-8015	302	3	]	]	X
ajst-8015	302	4	s.	s.	PROPN
ajst-8015	302	5	sarraf	sarraf	PROPN
ajst-8015	302	6	and	and	CCONJ
ajst-8015	302	7	g.	g.	PROPN
ajst-8015	302	8	tofighi	tofighi	PROPN
ajst-8015	302	9	,	,	PUNCT
ajst-8015	302	10	“	"	PUNCT
ajst-8015	302	11	deep	deep	ADJ
ajst-8015	302	12	learning	learning	NOUN
ajst-8015	302	13	-	-	PUNCT
ajst-8015	302	14	based	base	VERB
ajst-8015	302	15	pipeline	pipeline	NOUN
ajst-8015	302	16	to	to	PART
ajst-8015	302	17	recognize	recognize	VERB
ajst-8015	302	18	alzheimer	alzheimer	PROPN
ajst-8015	302	19	’s	’s	PART
ajst-8015	302	20	disease	disease	NOUN
ajst-8015	302	21	using	use	VERB
ajst-8015	302	22	fmri	fmri	PROPN
ajst-8015	302	23	data	datum	NOUN
ajst-8015	302	24	,	,	PUNCT
ajst-8015	302	25	”	"	PUNCT
ajst-8015	302	26	in	in	ADP
ajst-8015	302	27	2016	2016	NUM
ajst-8015	302	28	future	future	ADJ
ajst-8015	302	29	technologies	technology	NOUN
ajst-8015	302	30	conference	conference	NOUN
ajst-8015	302	31	(	(	PUNCT
ajst-8015	302	32	ftc	ftc	PROPN
ajst-8015	302	33	)	)	PUNCT
ajst-8015	302	34	,	,	PUNCT
ajst-8015	302	35	ieee	ieee	NOUN
ajst-8015	302	36	,	,	PUNCT
ajst-8015	302	37	2016	2016	NUM
ajst-8015	302	38	,	,	PUNCT
ajst-8015	302	39	pp	pp	ADV
ajst-8015	302	40	.	.	PUNCT
ajst-8015	302	41	816	816	NUM
ajst-8015	302	42	–	–	PUNCT
ajst-8015	302	43	820	820	NUM
ajst-8015	302	44	.	.	PUNCT
ajst-8015	303	1	[	[	X
ajst-8015	303	2	36	36	NUM
ajst-8015	303	3	]	]	X
ajst-8015	303	4	y.	y.	PROPN
ajst-8015	303	5	dai	dai	PROPN
ajst-8015	303	6	,	,	PUNCT
ajst-8015	303	7	d.	d.	PROPN
ajst-8015	303	8	qiu	qiu	PROPN
ajst-8015	303	9	,	,	PUNCT
ajst-8015	303	10	y.	y.	PROPN
ajst-8015	303	11	wang	wang	PROPN
ajst-8015	303	12	,	,	PUNCT
ajst-8015	303	13	s.	s.	PROPN
ajst-8015	303	14	dong	dong	PROPN
ajst-8015	303	15	,	,	PUNCT
ajst-8015	303	16	and	and	CCONJ
ajst-8015	303	17	h.-l	h.-l	PROPN
ajst-8015	303	18	.	.	PUNCT
ajst-8015	304	1	wang	wang	PROPN
ajst-8015	304	2	,	,	PUNCT
ajst-8015	304	3	“	"	PUNCT
ajst-8015	304	4	research	research	NOUN
ajst-8015	304	5	on	on	ADP
ajst-8015	304	6	computer	computer	NOUN
ajst-8015	304	7	-	-	PUNCT
ajst-8015	304	8	aided	aid	VERB
ajst-8015	304	9	diagnosis	diagnosis	NOUN
ajst-8015	304	10	of	of	ADP
ajst-8015	304	11	alzheimer	alzheimer	PROPN
ajst-8015	304	12	’s	’s	PART
ajst-8015	304	13	disease	disease	NOUN
ajst-8015	304	14	based	base	VERB
ajst-8015	304	15	on	on	ADP
ajst-8015	304	16	heterogeneous	heterogeneous	ADJ
ajst-8015	304	17	medical	medical	ADJ
ajst-8015	304	18	data	datum	NOUN
ajst-8015	304	19	fusion	fusion	NOUN
ajst-8015	304	20	,	,	PUNCT
ajst-8015	304	21	”	"	PUNCT
ajst-8015	304	22	international	international	ADJ
ajst-8015	304	23	journal	journal	NOUN
ajst-8015	304	24	of	of	ADP
ajst-8015	304	25	pattern	pattern	NOUN
ajst-8015	304	26	recognition	recognition	NOUN
ajst-8015	304	27	and	and	CCONJ
ajst-8015	304	28	artificial	artificial	ADJ
ajst-8015	304	29	intelligence	intelligence	NOUN
ajst-8015	304	30	,	,	PUNCT
ajst-8015	304	31	vol	vol	NOUN
ajst-8015	304	32	.	.	PROPN
ajst-8015	304	33	33	33	NUM
ajst-8015	304	34	,	,	PUNCT
ajst-8015	304	35	no	no	INTJ
ajst-8015	304	36	.	.	NOUN
ajst-8015	304	37	05	05	NUM
ajst-8015	304	38	,	,	PUNCT
ajst-8015	304	39	p.	p.	NOUN
ajst-8015	304	40	1957001	1957001	NUM
ajst-8015	304	41	,	,	PUNCT
ajst-8015	304	42	2019	2019	NUM
ajst-8015	304	43	.	.	PUNCT
ajst-8015	305	1	[	[	X
ajst-8015	305	2	37	37	NUM
ajst-8015	305	3	]	]	PUNCT
ajst-8015	305	4	a.	a.	NOUN
ajst-8015	305	5	shakarami	shakarami	PROPN
ajst-8015	305	6	,	,	PUNCT
ajst-8015	305	7	h.	h.	PROPN
ajst-8015	305	8	tarrah	tarrah	PROPN
ajst-8015	305	9	,	,	PUNCT
ajst-8015	305	10	and	and	CCONJ
ajst-8015	305	11	a.	a.	NOUN
ajst-8015	305	12	mahdavi	mahdavi	PROPN
ajst-8015	305	13	-	-	PUNCT
ajst-8015	305	14	hormat	hormat	NOUN
ajst-8015	305	15	,	,	PUNCT
ajst-8015	305	16	“	"	PUNCT
ajst-8015	305	17	a	a	DET
ajst-8015	305	18	cad	cad	NOUN
ajst-8015	305	19	system	system	NOUN
ajst-8015	305	20	for	for	ADP
ajst-8015	305	21	diagnosing	diagnose	VERB
ajst-8015	305	22	alzheimer	alzheimer	PROPN
ajst-8015	305	23	’s	’s	PART
ajst-8015	305	24	disease	disease	NOUN
ajst-8015	305	25	using	use	VERB
ajst-8015	305	26	2d	2d	NUM
ajst-8015	305	27	slices	slice	NOUN
ajst-8015	305	28	and	and	CCONJ
ajst-8015	305	29	an	an	DET
ajst-8015	305	30	improved	improved	ADJ
ajst-8015	305	31	alexnet	alexnet	ADJ
ajst-8015	305	32	-	-	PUNCT
ajst-8015	305	33	svm	svm	NOUN
ajst-8015	305	34	method	method	NOUN
ajst-8015	305	35	,	,	PUNCT
ajst-8015	305	36	”	"	PUNCT
ajst-8015	305	37	optik	optik	PROPN
ajst-8015	305	38	,	,	PUNCT
ajst-8015	305	39	vol	vol	NOUN
ajst-8015	305	40	.	.	PROPN
ajst-8015	305	41	212	212	NUM
ajst-8015	305	42	,	,	PUNCT
ajst-8015	305	43	p.	p.	NOUN
ajst-8015	305	44	164237	164237	NUM
ajst-8015	305	45	,	,	PUNCT
ajst-8015	305	46	2020	2020	NUM
ajst-8015	305	47	.	.	PUNCT
ajst-8015	306	1	[	[	X
ajst-8015	306	2	38	38	NUM
ajst-8015	306	3	]	]	X
ajst-8015	306	4	y.	y.	PROPN
ajst-8015	306	5	kazemi	kazemi	PROPN
ajst-8015	306	6	and	and	CCONJ
ajst-8015	306	7	s.	s.	PROPN
ajst-8015	306	8	houghten	houghten	PROPN
ajst-8015	306	9	,	,	PUNCT
ajst-8015	306	10	“	"	PUNCT
ajst-8015	306	11	a	a	DET
ajst-8015	306	12	deep	deep	ADJ
ajst-8015	306	13	learning	learning	NOUN
ajst-8015	306	14	pipeline	pipeline	NOUN
ajst-8015	306	15	to	to	PART
ajst-8015	306	16	classify	classify	VERB
ajst-8015	306	17	different	different	ADJ
ajst-8015	306	18	stages	stage	NOUN
ajst-8015	306	19	of	of	ADP
ajst-8015	306	20	alzheimer	alzheimer	PROPN
ajst-8015	306	21	’s	’s	PART
ajst-8015	306	22	disease	disease	NOUN
ajst-8015	306	23	from	from	ADP
ajst-8015	306	24	fmri	fmri	PROPN
ajst-8015	306	25	data	datum	NOUN
ajst-8015	306	26	,	,	PUNCT
ajst-8015	306	27	”	"	PUNCT
ajst-8015	306	28	in	in	ADP
ajst-8015	306	29	2018	2018	NUM
ajst-8015	306	30	ieee	ieee	NOUN
ajst-8015	306	31	conference	conference	NOUN
ajst-8015	306	32	on	on	ADP
ajst-8015	306	33	computational	computational	ADJ
ajst-8015	306	34	intelligence	intelligence	NOUN
ajst-8015	306	35	in	in	ADP
ajst-8015	306	36	bioinformatics	bioinformatics	NOUN
ajst-8015	306	37	and	and	CCONJ
ajst-8015	306	38	computational	computational	ADJ
ajst-8015	306	39	biology	biology	NOUN
ajst-8015	306	40	(	(	PUNCT
ajst-8015	306	41	cibcb	cibcb	NOUN
ajst-8015	306	42	)	)	PUNCT
ajst-8015	306	43	,	,	PUNCT
ajst-8015	306	44	ieee	ieee	NOUN
ajst-8015	306	45	,	,	PUNCT
ajst-8015	306	46	2018	2018	NUM
ajst-8015	306	47	,	,	PUNCT
ajst-8015	306	48	pp	pp	ADV
ajst-8015	306	49	.	.	PUNCT
ajst-8015	307	1	1–8	1–8	X
ajst-8015	307	2	.	.	PUNCT
ajst-8015	308	1	[	[	X
ajst-8015	308	2	39	39	NUM
ajst-8015	308	3	]	]	PUNCT
ajst-8015	308	4	m.	m.	NOUN
ajst-8015	308	5	hon	hon	PROPN
ajst-8015	308	6	and	and	CCONJ
ajst-8015	308	7	n.	n.	PROPN
ajst-8015	308	8	m.	m.	PROPN
ajst-8015	308	9	khan	khan	PROPN
ajst-8015	308	10	,	,	PUNCT
ajst-8015	308	11	“	"	PUNCT
ajst-8015	308	12	towards	towards	ADP
ajst-8015	308	13	alzheimer	alzheimer	PROPN
ajst-8015	308	14	’s	’s	PART
ajst-8015	308	15	disease	disease	NOUN
ajst-8015	308	16	classification	classification	NOUN
ajst-8015	308	17	through	through	ADP
ajst-8015	308	18	transfer	transfer	NOUN
ajst-8015	308	19	learning	learning	NOUN
ajst-8015	308	20	,	,	PUNCT
ajst-8015	308	21	”	"	PUNCT
ajst-8015	308	22	in	in	ADP
ajst-8015	308	23	2017	2017	NUM
ajst-8015	308	24	ieee	ieee	NOUN
ajst-8015	308	25	international	international	ADJ
ajst-8015	308	26	conference	conference	NOUN
ajst-8015	308	27	on	on	ADP
ajst-8015	308	28	bioinformatics	bioinformatics	NOUN
ajst-8015	308	29	and	and	CCONJ
ajst-8015	308	30	biomedicine	biomedicine	NOUN
ajst-8015	308	31	(	(	PUNCT
ajst-8015	308	32	bibm	bibm	PROPN
ajst-8015	308	33	)	)	PUNCT
ajst-8015	308	34	,	,	PUNCT
ajst-8015	308	35	ieee	ieee	NOUN
ajst-8015	308	36	,	,	PUNCT
ajst-8015	308	37	2017	2017	NUM
ajst-8015	308	38	,	,	PUNCT
ajst-8015	308	39	pp	pp	ADJ
ajst-8015	308	40	.	.	PUNCT
ajst-8015	308	41	1166–1169	1166–1169	NUM
ajst-8015	308	42	.	.	PUNCT
ajst-8015	309	1	[	[	X
ajst-8015	309	2	40	40	NUM
ajst-8015	309	3	]	]	X
ajst-8015	309	4	y.	y.	PROPN
ajst-8015	309	5	ding	ding	PROPN
ajst-8015	309	6	et	et	PROPN
ajst-8015	309	7	al	al	PROPN
ajst-8015	309	8	.	.	PROPN
ajst-8015	309	9	,	,	PUNCT
ajst-8015	309	10	“	"	PUNCT
ajst-8015	309	11	a	a	DET
ajst-8015	309	12	deep	deep	ADJ
ajst-8015	309	13	learning	learning	NOUN
ajst-8015	309	14	model	model	NOUN
ajst-8015	309	15	to	to	PART
ajst-8015	309	16	predict	predict	VERB
ajst-8015	309	17	a	a	DET
ajst-8015	309	18	diagnosis	diagnosis	NOUN
ajst-8015	309	19	of	of	ADP
ajst-8015	309	20	alzheimer	alzheimer	NOUN
ajst-8015	309	21	disease	disease	NOUN
ajst-8015	309	22	by	by	ADP
ajst-8015	309	23	using	use	VERB
ajst-8015	309	24	18f	18f	PROPN
ajst-8015	309	25	-	-	PUNCT
ajst-8015	309	26	fdg	fdg	PROPN
ajst-8015	309	27	pet	pet	NOUN
ajst-8015	309	28	of	of	ADP
ajst-8015	309	29	the	the	DET
ajst-8015	309	30	brain	brain	NOUN
ajst-8015	309	31	,	,	PUNCT
ajst-8015	309	32	”	"	PUNCT
ajst-8015	309	33	radiology	radiology	NOUN
ajst-8015	309	34	,	,	PUNCT
ajst-8015	309	35	vol	vol	NOUN
ajst-8015	309	36	.	.	PROPN
ajst-8015	309	37	290	290	NUM
ajst-8015	309	38	,	,	PUNCT
ajst-8015	309	39	no	no	INTJ
ajst-8015	309	40	.	.	NOUN
ajst-8015	309	41	2	2	NUM
ajst-8015	309	42	,	,	PUNCT
ajst-8015	309	43	pp	pp	ADJ
ajst-8015	309	44	.	.	PUNCT
ajst-8015	310	1	456–464	456–464	NUM
ajst-8015	310	2	,	,	PUNCT
ajst-8015	310	3	2019	2019	NUM
ajst-8015	310	4	.	.	PUNCT
ajst-8015	311	1	[	[	X
ajst-8015	311	2	41	41	NUM
ajst-8015	311	3	]	]	X
ajst-8015	311	4	e.	e.	PROPN
ajst-8015	311	5	yee	yee	PROPN
ajst-8015	311	6	,	,	PUNCT
ajst-8015	311	7	k.	k.	PROPN
ajst-8015	311	8	popuri	popuri	PROPN
ajst-8015	311	9	,	,	PUNCT
ajst-8015	311	10	m.	m.	PROPN
ajst-8015	311	11	f.	f.	PROPN
ajst-8015	311	12	beg	beg	PROPN
ajst-8015	311	13	,	,	PUNCT
ajst-8015	311	14	and	and	CCONJ
ajst-8015	311	15	a.	a.	PROPN
ajst-8015	311	16	d.	d.	PROPN
ajst-8015	311	17	n.	n.	PROPN
ajst-8015	311	18	initiative	initiative	PROPN
ajst-8015	311	19	,	,	PUNCT
ajst-8015	311	20	“	"	PUNCT
ajst-8015	311	21	quantifying	quantify	VERB
ajst-8015	311	22	brain	brain	NOUN
ajst-8015	311	23	metabolism	metabolism	NOUN
ajst-8015	311	24	from	from	ADP
ajst-8015	311	25	fdg	fdg	ADJ
ajst-8015	311	26	-	-	ADJ
ajst-8015	311	27	pet	pet	ADJ
ajst-8015	311	28	images	image	NOUN
ajst-8015	311	29	into	into	ADP
ajst-8015	311	30	a	a	DET
ajst-8015	311	31	probability	probability	NOUN
ajst-8015	311	32	of	of	ADP
ajst-8015	311	33	alzheimer	alzheimer	PROPN
ajst-8015	311	34	’s	’s	PART
ajst-8015	311	35	dementia	dementia	NOUN
ajst-8015	311	36	score	score	NOUN
ajst-8015	311	37	,	,	PUNCT
ajst-8015	311	38	”	"	PUNCT
ajst-8015	311	39	human	human	ADJ
ajst-8015	311	40	brain	brain	NOUN
ajst-8015	311	41	mapping	mapping	NOUN
ajst-8015	311	42	,	,	PUNCT
ajst-8015	311	43	vol	vol	NOUN
ajst-8015	311	44	.	.	PROPN
ajst-8015	311	45	41	41	NUM
ajst-8015	311	46	,	,	PUNCT
ajst-8015	311	47	no	no	INTJ
ajst-8015	311	48	.	.	NOUN
ajst-8015	311	49	1	1	NUM
ajst-8015	311	50	,	,	PUNCT
ajst-8015	311	51	pp	pp	ADJ
ajst-8015	311	52	.	.	PUNCT
ajst-8015	312	1	5–16	5–16	NOUN
ajst-8015	312	2	,	,	PUNCT
ajst-8015	312	3	2020	2020	NUM
ajst-8015	312	4	.	.	PUNCT
ajst-8015	313	1	[	[	X
ajst-8015	313	2	42	42	NUM
ajst-8015	313	3	]	]	X
ajst-8015	313	4	l.	l.	PROPN
ajst-8015	313	5	v.	v.	PROPN
ajst-8015	313	6	fulton	fulton	PROPN
ajst-8015	313	7	,	,	PUNCT
ajst-8015	313	8	d.	d.	PROPN
ajst-8015	313	9	dolezel	dolezel	PROPN
ajst-8015	313	10	,	,	PUNCT
ajst-8015	313	11	j.	j.	PROPN
ajst-8015	313	12	harrop	harrop	PROPN
ajst-8015	313	13	,	,	PUNCT
ajst-8015	313	14	y.	y.	PROPN
ajst-8015	313	15	yan	yan	PROPN
ajst-8015	313	16	,	,	PUNCT
ajst-8015	313	17	and	and	CCONJ
ajst-8015	313	18	c.	c.	PROPN
ajst-8015	313	19	p.	p.	PROPN
ajst-8015	313	20	fulton	fulton	PROPN
ajst-8015	313	21	,	,	PUNCT
ajst-8015	313	22	“	"	PUNCT
ajst-8015	313	23	classification	classification	NOUN
ajst-8015	313	24	of	of	ADP
ajst-8015	313	25	alzheimer	alzheimer	PROPN
ajst-8015	313	26	’s	’s	PART
ajst-8015	313	27	disease	disease	NOUN
ajst-8015	313	28	with	with	ADP
ajst-8015	313	29	and	and	CCONJ
ajst-8015	313	30	without	without	ADP
ajst-8015	313	31	imagery	imagery	NOUN
ajst-8015	313	32	using	use	VERB
ajst-8015	313	33	gradient	gradient	NOUN
ajst-8015	313	34	boosted	boost	VERB
ajst-8015	313	35	machines	machine	NOUN
ajst-8015	313	36	and	and	CCONJ
ajst-8015	313	37	resnet-50	resnet-50	NOUN
ajst-8015	313	38	,	,	PUNCT
ajst-8015	313	39	”	"	PUNCT
ajst-8015	313	40	brain	brain	NOUN
ajst-8015	313	41	sciences	science	NOUN
ajst-8015	313	42	,	,	PUNCT
ajst-8015	313	43	vol	vol	NOUN
ajst-8015	313	44	.	.	PROPN
ajst-8015	313	45	9	9	NUM
ajst-8015	313	46	,	,	PUNCT
ajst-8015	313	47	no	no	INTJ
ajst-8015	313	48	.	.	NOUN
ajst-8015	313	49	9	9	NUM
ajst-8015	313	50	,	,	PUNCT
ajst-8015	313	51	p.	p.	NOUN
ajst-8015	313	52	212	212	NUM
ajst-8015	313	53	,	,	PUNCT
ajst-8015	313	54	2019	2019	NUM
ajst-8015	313	55	.	.	PUNCT
ajst-8015	314	1	[	[	X
ajst-8015	314	2	43	43	NUM
ajst-8015	314	3	]	]	X
ajst-8015	314	4	h.	h.	PROPN
ajst-8015	314	5	wang	wang	PROPN
ajst-8015	314	6	et	et	PROPN
ajst-8015	314	7	al	al	PROPN
ajst-8015	314	8	.	.	PROPN
ajst-8015	314	9	,	,	PUNCT
ajst-8015	314	10	“	"	PUNCT
ajst-8015	314	11	ensemble	ensemble	ADJ
ajst-8015	314	12	of	of	ADP
ajst-8015	314	13	3d	3d	NUM
ajst-8015	314	14	densely	densely	ADV
ajst-8015	314	15	connected	connect	VERB
ajst-8015	314	16	convolutional	convolutional	ADJ
ajst-8015	314	17	network	network	NOUN
ajst-8015	314	18	for	for	ADP
ajst-8015	314	19	diagnosis	diagnosis	NOUN
ajst-8015	314	20	of	of	ADP
ajst-8015	314	21	mild	mild	ADJ
ajst-8015	314	22	cognitive	cognitive	ADJ
ajst-8015	314	23	impairment	impairment	NOUN
ajst-8015	314	24	and	and	CCONJ
ajst-8015	314	25	alzheimer	alzheimer	PROPN
ajst-8015	314	26	’s	’s	PART
ajst-8015	314	27	disease	disease	NOUN
ajst-8015	314	28	,	,	PUNCT
ajst-8015	314	29	”	"	PUNCT
ajst-8015	314	30	neurocomputing	neurocomputing	NOUN
ajst-8015	314	31	,	,	PUNCT
ajst-8015	314	32	vol	vol	NOUN
ajst-8015	314	33	.	.	NOUN
ajst-8015	314	34	333	333	NUM
ajst-8015	314	35	,	,	PUNCT
ajst-8015	314	36	pp	pp	ADJ
ajst-8015	314	37	.	.	PUNCT
ajst-8015	315	1	145–156	145–156	NUM
ajst-8015	315	2	,	,	PUNCT
ajst-8015	315	3	2019	2019	NUM
ajst-8015	315	4	.	.	PUNCT
ajst-8015	316	1	[	[	X
ajst-8015	316	2	44	44	NUM
ajst-8015	316	3	]	]	X
ajst-8015	316	4	f.	f.	PROPN
ajst-8015	316	5	li	li	PROPN
ajst-8015	316	6	,	,	PUNCT
ajst-8015	316	7	m.	m.	PROPN
ajst-8015	316	8	liu	liu	PROPN
ajst-8015	316	9	,	,	PUNCT
ajst-8015	316	10	and	and	CCONJ
ajst-8015	316	11	a.	a.	PROPN
ajst-8015	316	12	d.	d.	PROPN
ajst-8015	316	13	n.	n.	PROPN
ajst-8015	316	14	initiative	initiative	PROPN
ajst-8015	316	15	,	,	PUNCT
ajst-8015	316	16	“	"	PUNCT
ajst-8015	316	17	a	a	DET
ajst-8015	316	18	hybrid	hybrid	ADJ
ajst-8015	316	19	convolutional	convolutional	ADJ
ajst-8015	316	20	and	and	CCONJ
ajst-8015	316	21	recurrent	recurrent	ADJ
ajst-8015	316	22	neural	neural	ADJ
ajst-8015	316	23	network	network	NOUN
ajst-8015	316	24	for	for	ADP
ajst-8015	316	25	hippocampus	hippocampus	NOUN
ajst-8015	316	26	analysis	analysis	NOUN
ajst-8015	316	27	in	in	ADP
ajst-8015	316	28	alzheimer	alzheimer	PROPN
ajst-8015	316	29	’s	’s	PART
ajst-8015	316	30	disease	disease	NOUN
ajst-8015	316	31	,	,	PUNCT
ajst-8015	316	32	”	"	PUNCT
ajst-8015	316	33	journal	journal	NOUN
ajst-8015	316	34	of	of	ADP
ajst-8015	316	35	neuroscience	neuroscience	NOUN
ajst-8015	316	36	methods	method	NOUN
ajst-8015	316	37	,	,	PUNCT
ajst-8015	316	38	vol	vol	NOUN
ajst-8015	316	39	.	.	PROPN
ajst-8015	316	40	323	323	NUM
ajst-8015	316	41	,	,	PUNCT
ajst-8015	316	42	pp	pp	ADJ
ajst-8015	316	43	.	.	PUNCT
ajst-8015	317	1	108–118	108–118	NUM
ajst-8015	317	2	,	,	PUNCT
ajst-8015	317	3	2019	2019	NUM
ajst-8015	317	4	.	.	PUNCT
ajst-8015	318	1	[	[	X
ajst-8015	318	2	45	45	NUM
ajst-8015	318	3	]	]	PUNCT
ajst-8015	318	4	m.	m.	NOUN
ajst-8015	318	5	liu	liu	PROPN
ajst-8015	318	6	,	,	PUNCT
ajst-8015	318	7	d.	d.	PROPN
ajst-8015	318	8	cheng	cheng	PROPN
ajst-8015	318	9	,	,	PUNCT
ajst-8015	318	10	w.	w.	PROPN
ajst-8015	318	11	yan	yan	PROPN
ajst-8015	318	12	,	,	PUNCT
ajst-8015	318	13	and	and	CCONJ
ajst-8015	318	14	a.	a.	PROPN
ajst-8015	318	15	d.	d.	PROPN
ajst-8015	318	16	n.	n.	PROPN
ajst-8015	318	17	initiative	initiative	PROPN
ajst-8015	318	18	,	,	PUNCT
ajst-8015	318	19	“	"	PUNCT
ajst-8015	318	20	classification	classification	NOUN
ajst-8015	318	21	of	of	ADP
ajst-8015	318	22	alzheimer	alzheimer	PROPN
ajst-8015	318	23	’s	’s	PART
ajst-8015	318	24	disease	disease	NOUN
ajst-8015	318	25	by	by	ADP
ajst-8015	318	26	combination	combination	NOUN
ajst-8015	318	27	of	of	ADP
ajst-8015	318	28	convolutional	convolutional	ADJ
ajst-8015	318	29	and	and	CCONJ
ajst-8015	318	30	recurrent	recurrent	ADJ
ajst-8015	318	31	neural	neural	ADJ
ajst-8015	318	32	networks	network	NOUN
ajst-8015	318	33	using	use	VERB
ajst-8015	318	34	fdg	fdg	PROPN
ajst-8015	318	35	-	-	ADJ
ajst-8015	318	36	pet	pet	ADJ
ajst-8015	318	37	images	image	NOUN
ajst-8015	318	38	,	,	PUNCT
ajst-8015	318	39	”	"	PUNCT
ajst-8015	318	40	frontiers	frontier	NOUN
ajst-8015	318	41	in	in	ADP
ajst-8015	318	42	neuroinformatics	neuroinformatic	NOUN
ajst-8015	318	43	,	,	PUNCT
ajst-8015	318	44	vol	vol	NOUN
ajst-8015	318	45	.	.	PROPN
ajst-8015	318	46	12	12	NUM
ajst-8015	318	47	,	,	PUNCT
ajst-8015	318	48	p.	p.	NOUN
ajst-8015	318	49	35	35	NUM
ajst-8015	318	50	,	,	PUNCT
ajst-8015	318	51	2018	2018	NUM
ajst-8015	318	52	.	.	PUNCT
ajst-8015	319	1	[	[	X
ajst-8015	319	2	46	46	NUM
ajst-8015	319	3	]	]	PUNCT
ajst-8015	319	4	r.	r.	PROPN
ajst-8015	319	5	li	li	PROPN
ajst-8015	319	6	et	et	PROPN
ajst-8015	319	7	al	al	PROPN
ajst-8015	319	8	.	.	PROPN
ajst-8015	319	9	,	,	PUNCT
ajst-8015	319	10	“	"	PUNCT
ajst-8015	319	11	deep	deep	ADJ
ajst-8015	319	12	learning	learning	NOUN
ajst-8015	319	13	based	base	VERB
ajst-8015	319	14	imaging	imaging	NOUN
ajst-8015	319	15	data	datum	NOUN
ajst-8015	319	16	completion	completion	NOUN
ajst-8015	319	17	for	for	ADP
ajst-8015	319	18	improved	improved	ADJ
ajst-8015	319	19	brain	brain	NOUN
ajst-8015	319	20	disease	disease	NOUN
ajst-8015	319	21	diagnosis	diagnosis	NOUN
ajst-8015	319	22	,	,	PUNCT
ajst-8015	319	23	”	"	PUNCT
ajst-8015	319	24	in	in	ADP
ajst-8015	319	25	international	international	ADJ
ajst-8015	319	26	conference	conference	NOUN
ajst-8015	319	27	on	on	ADP
ajst-8015	319	28	medical	medical	ADJ
ajst-8015	319	29	image	image	NOUN
ajst-8015	319	30	computing	computing	NOUN
ajst-8015	319	31	and	and	CCONJ
ajst-8015	319	32	computer	computer	NOUN
ajst-8015	319	33	-	-	PUNCT
ajst-8015	319	34	assisted	assist	VERB
ajst-8015	319	35	intervention	intervention	NOUN
ajst-8015	319	36	,	,	PUNCT
ajst-8015	319	37	springer	springer	NOUN
ajst-8015	319	38	,	,	PUNCT
ajst-8015	319	39	2014	2014	NUM
ajst-8015	319	40	,	,	PUNCT
ajst-8015	319	41	pp	pp	ADP
ajst-8015	319	42	.	.	PUNCT
ajst-8015	320	1	305–312	305–312	NUM
ajst-8015	320	2	.	.	PUNCT
ajst-8015	321	1	[	[	X
ajst-8015	321	2	47	47	NUM
ajst-8015	321	3	]	]	PUNCT
ajst-8015	321	4	e.	e.	PROPN
ajst-8015	321	5	hosseini	hosseini	PROPN
ajst-8015	321	6	-	-	PUNCT
ajst-8015	321	7	asl	asl	PROPN
ajst-8015	321	8	,	,	PUNCT
ajst-8015	321	9	r.	r.	PROPN
ajst-8015	321	10	keynton	keynton	PROPN
ajst-8015	321	11	,	,	PUNCT
ajst-8015	321	12	and	and	CCONJ
ajst-8015	321	13	a.	a.	PROPN
ajst-8015	321	14	el	el	PROPN
ajst-8015	321	15	-	-	PUNCT
ajst-8015	321	16	baz	baz	PROPN
ajst-8015	321	17	,	,	PUNCT
ajst-8015	321	18	“	"	PUNCT
ajst-8015	321	19	alzheimer	alzheimer	X
ajst-8015	321	20	’s	’s	PART
ajst-8015	321	21	disease	disease	NOUN
ajst-8015	321	22	diagnostics	diagnostic	NOUN
ajst-8015	321	23	by	by	ADP
ajst-8015	321	24	adaptation	adaptation	NOUN
ajst-8015	321	25	of	of	ADP
ajst-8015	321	26	3d	3d	NUM
ajst-8015	321	27	convolutional	convolutional	ADJ
ajst-8015	321	28	network	network	NOUN
ajst-8015	321	29	,	,	PUNCT
ajst-8015	321	30	”	"	PUNCT
ajst-8015	321	31	in	in	ADP
ajst-8015	321	32	2016	2016	NUM
ajst-8015	321	33	ieee	ieee	NOUN
ajst-8015	321	34	international	international	ADJ
ajst-8015	321	35	conference	conference	NOUN
ajst-8015	321	36	on	on	ADP
ajst-8015	321	37	image	image	NOUN
ajst-8015	321	38	processing	processing	NOUN
ajst-8015	321	39	(	(	PUNCT
ajst-8015	321	40	icip	icip	PROPN
ajst-8015	321	41	)	)	PUNCT
ajst-8015	321	42	,	,	PUNCT
ajst-8015	321	43	ieee	ieee	NOUN
ajst-8015	321	44	,	,	PUNCT
ajst-8015	321	45	2016	2016	NUM
ajst-8015	321	46	,	,	PUNCT
ajst-8015	321	47	pp	pp	ADJ
ajst-8015	321	48	.	.	PUNCT
ajst-8015	322	1	126–130	126–130	NUM
ajst-8015	322	2	.	.	PUNCT
ajst-8015	323	1	[	[	X
ajst-8015	323	2	48	48	NUM
ajst-8015	323	3	]	]	X
ajst-8015	323	4	y.	y.	PROPN
ajst-8015	323	5	huang	huang	PROPN
ajst-8015	323	6	,	,	PUNCT
ajst-8015	323	7	j.	j.	PROPN
ajst-8015	323	8	xu	xu	PROPN
ajst-8015	323	9	,	,	PUNCT
ajst-8015	323	10	y.	y.	PROPN
ajst-8015	323	11	zhou	zhou	PROPN
ajst-8015	323	12	,	,	PUNCT
ajst-8015	323	13	t.	t.	PROPN
ajst-8015	323	14	tong	tong	PROPN
ajst-8015	323	15	,	,	PUNCT
ajst-8015	323	16	x.	x.	PROPN
ajst-8015	323	17	zhuang	zhuang	PROPN
ajst-8015	323	18	,	,	PUNCT
ajst-8015	323	19	and	and	CCONJ
ajst-8015	323	20	a.	a.	PROPN
ajst-8015	323	21	d.	d.	PROPN
ajst-8015	323	22	n.	n.	PROPN
ajst-8015	323	23	initiative	initiative	PROPN
ajst-8015	323	24	(	(	PUNCT
ajst-8015	323	25	adni	adni	ADJ
ajst-8015	323	26	,	,	PUNCT
ajst-8015	323	27	“	"	PUNCT
ajst-8015	323	28	diagnosis	diagnosis	NOUN
ajst-8015	323	29	of	of	ADP
ajst-8015	323	30	alzheimer	alzheimer	PROPN
ajst-8015	323	31	’s	’s	PART
ajst-8015	323	32	disease	disease	NOUN
ajst-8015	323	33	via	via	ADP
ajst-8015	323	34	multimodality	multimodality	NOUN
ajst-8015	323	35	3d	3d	NOUN
ajst-8015	323	36	convolutional	convolutional	ADJ
ajst-8015	323	37	neural	neural	ADJ
ajst-8015	323	38	network	network	NOUN
ajst-8015	323	39	,	,	PUNCT
ajst-8015	323	40	”	"	PUNCT
ajst-8015	323	41	frontiers	frontier	NOUN
ajst-8015	323	42	in	in	ADP
ajst-8015	323	43	neuroscience	neuroscience	NOUN
ajst-8015	323	44	,	,	PUNCT
ajst-8015	323	45	vol	vol	NOUN
ajst-8015	323	46	.	.	PROPN
ajst-8015	323	47	13	13	NUM
ajst-8015	323	48	,	,	PUNCT
ajst-8015	323	49	p.	p.	NOUN
ajst-8015	323	50	509	509	NUM
ajst-8015	323	51	,	,	PUNCT
ajst-8015	323	52	2019	2019	NUM
ajst-8015	323	53	.	.	PUNCT
ajst-8015	324	1	[	[	X
ajst-8015	324	2	49	49	NUM
ajst-8015	324	3	]	]	PUNCT
ajst-8015	324	4	s.	s.	PROPN
ajst-8015	324	5	liu	liu	PROPN
ajst-8015	324	6	,	,	PUNCT
ajst-8015	324	7	c.	c.	PROPN
ajst-8015	324	8	yadav	yadav	PROPN
ajst-8015	324	9	,	,	PUNCT
ajst-8015	324	10	c.	c.	PROPN
ajst-8015	324	11	fernandez	fernandez	PROPN
ajst-8015	324	12	-	-	PUNCT
ajst-8015	324	13	granda	granda	PROPN
ajst-8015	324	14	,	,	PUNCT
ajst-8015	324	15	and	and	CCONJ
ajst-8015	324	16	n.	n.	PROPN
ajst-8015	324	17	razavian	razavian	NOUN
ajst-8015	324	18	,	,	PUNCT
ajst-8015	324	19	“	"	PUNCT
ajst-8015	324	20	on	on	ADP
ajst-8015	324	21	the	the	DET
ajst-8015	324	22	design	design	NOUN
ajst-8015	324	23	of	of	ADP
ajst-8015	324	24	convolutional	convolutional	ADJ
ajst-8015	324	25	neural	neural	ADJ
ajst-8015	324	26	networks	network	NOUN
ajst-8015	324	27	for	for	ADP
ajst-8015	324	28	automatic	automatic	ADJ
ajst-8015	324	29	detection	detection	NOUN
ajst-8015	324	30	of	of	ADP
ajst-8015	324	31	alzheimer	alzheimer	PROPN
ajst-8015	324	32	’s	’s	PART
ajst-8015	324	33	disease	disease	NOUN
ajst-8015	324	34	,	,	PUNCT
ajst-8015	324	35	”	"	PUNCT
ajst-8015	324	36	in	in	ADP
ajst-8015	324	37	machine	machine	NOUN
ajst-8015	324	38	learning	learn	VERB
ajst-8015	324	39	for	for	ADP
ajst-8015	324	40	health	health	NOUN
ajst-8015	324	41	workshop	workshop	NOUN
ajst-8015	324	42	,	,	PUNCT
ajst-8015	324	43	pmlr	pmlr	NOUN
ajst-8015	324	44	,	,	PUNCT
ajst-8015	324	45	2020	2020	NUM
ajst-8015	324	46	,	,	PUNCT
ajst-8015	324	47	pp	pp	ADV
ajst-8015	324	48	.	.	PUNCT
ajst-8015	325	1	184–201	184–201	NUM
ajst-8015	325	2	.	.	PUNCT
ajst-8015	326	1	[	[	X
ajst-8015	326	2	50	50	NUM
ajst-8015	326	3	]	]	PUNCT
ajst-8015	326	4	x.	x.	NOUN
ajst-8015	326	5	zhao	zhao	PROPN
ajst-8015	326	6	,	,	PUNCT
ajst-8015	326	7	f.	f.	PROPN
ajst-8015	326	8	zhou	zhou	PROPN
ajst-8015	326	9	,	,	PUNCT
ajst-8015	326	10	l.	l.	PROPN
ajst-8015	326	11	ou	ou	PROPN
ajst-8015	326	12	-	-	PUNCT
ajst-8015	326	13	yang	yang	PROPN
ajst-8015	326	14	,	,	PUNCT
ajst-8015	326	15	t.	t.	PROPN
ajst-8015	326	16	wang	wang	PROPN
ajst-8015	326	17	,	,	PUNCT
ajst-8015	326	18	and	and	CCONJ
ajst-8015	326	19	b.	b.	PROPN
ajst-8015	326	20	lei	lei	PROPN
ajst-8015	326	21	,	,	PUNCT
ajst-8015	326	22	“	"	PUNCT
ajst-8015	326	23	graph	graph	VERB
ajst-8015	326	24	convolutional	convolutional	ADJ
ajst-8015	326	25	network	network	NOUN
ajst-8015	326	26	analysis	analysis	NOUN
ajst-8015	326	27	for	for	ADP
ajst-8015	326	28	mild	mild	ADJ
ajst-8015	326	29	cognitive	cognitive	ADJ
ajst-8015	326	30	impairment	impairment	NOUN
ajst-8015	326	31	prediction	prediction	NOUN
ajst-8015	326	32	,	,	PUNCT
ajst-8015	326	33	”	"	PUNCT
ajst-8015	326	34	in	in	ADP
ajst-8015	326	35	2019	2019	NUM
ajst-8015	326	36	ieee	ieee	NOUN
ajst-8015	326	37	16th	16th	ADJ
ajst-8015	326	38	international	international	ADJ
ajst-8015	326	39	symposium	symposium	NOUN
ajst-8015	326	40	on	on	ADP
ajst-8015	326	41	biomedical	biomedical	ADJ
ajst-8015	326	42	imaging	imaging	NOUN
ajst-8015	326	43	(	(	PUNCT
ajst-8015	326	44	isbi	isbi	NOUN
ajst-8015	326	45	2019	2019	NUM
ajst-8015	326	46	)	)	PUNCT
ajst-8015	326	47	,	,	PUNCT
ajst-8015	326	48	ieee	ieee	NOUN
ajst-8015	326	49	,	,	PUNCT
ajst-8015	326	50	2019	2019	NUM
ajst-8015	326	51	,	,	PUNCT
ajst-8015	326	52	pp	pp	ADJ
ajst-8015	326	53	.	.	PUNCT
ajst-8015	326	54	1598–1601	1598–1601	NUM
ajst-8015	326	55	.	.	PUNCT
ajst-8015	327	1	[	[	X
ajst-8015	327	2	51	51	NUM
ajst-8015	327	3	]	]	PUNCT
ajst-8015	327	4	j.	j.	PROPN
ajst-8015	327	5	guo	guo	PROPN
ajst-8015	327	6	,	,	PUNCT
ajst-8015	327	7	w.	w.	PROPN
ajst-8015	327	8	qiu	qiu	PROPN
ajst-8015	327	9	,	,	PUNCT
ajst-8015	327	10	x.	x.	PROPN
ajst-8015	327	11	li	li	PROPN
ajst-8015	327	12	,	,	PUNCT
ajst-8015	327	13	x.	x.	PROPN
ajst-8015	327	14	zhao	zhao	PROPN
ajst-8015	327	15	,	,	PUNCT
ajst-8015	327	16	n.	n.	PROPN
ajst-8015	327	17	guo	guo	PROPN
ajst-8015	327	18	,	,	PUNCT
ajst-8015	327	19	and	and	CCONJ
ajst-8015	327	20	q.	q.	PROPN
ajst-8015	327	21	li	li	PROPN
ajst-8015	327	22	,	,	PUNCT
ajst-8015	327	23	“	"	PUNCT
ajst-8015	327	24	predicting	predict	VERB
ajst-8015	327	25	alzheimer	alzheimer	PROPN
ajst-8015	327	26	’s	’s	PART
ajst-8015	327	27	disease	disease	NOUN
ajst-8015	327	28	by	by	ADP
ajst-8015	327	29	hierarchical	hierarchical	ADJ
ajst-8015	327	30	graph	graph	NOUN
ajst-8015	327	31	convolution	convolution	NOUN
ajst-8015	327	32	from	from	ADP
ajst-8015	327	33	positron	positron	NOUN
ajst-8015	327	34	emission	emission	NOUN
ajst-8015	327	35	tomography	tomography	NOUN
ajst-8015	327	36	imaging	imaging	NOUN
ajst-8015	327	37	,	,	PUNCT
ajst-8015	327	38	”	"	PUNCT
ajst-8015	327	39	in	in	ADP
ajst-8015	327	40	2019	2019	NUM
ajst-8015	327	41	ieee	ieee	NOUN
ajst-8015	327	42	international	international	ADJ
ajst-8015	327	43	conference	conference	NOUN
ajst-8015	327	44	on	on	ADP
ajst-8015	327	45	big	big	ADJ
ajst-8015	327	46	data	datum	NOUN
ajst-8015	327	47	(	(	PUNCT
ajst-8015	327	48	big	big	ADJ
ajst-8015	327	49	data	datum	NOUN
ajst-8015	327	50	)	)	PUNCT
ajst-8015	327	51	,	,	PUNCT
ajst-8015	327	52	ieee	ieee	NOUN
ajst-8015	327	53	,	,	PUNCT
ajst-8015	327	54	2019	2019	NUM
ajst-8015	327	55	,	,	PUNCT
ajst-8015	327	56	pp	pp	ADJ
ajst-8015	327	57	.	.	PUNCT
ajst-8015	328	1	5359–5363	5359–5363	NUM
ajst-8015	328	2	.	.	PUNCT
ajst-8015	329	1	[	[	X
ajst-8015	329	2	52	52	NUM
ajst-8015	329	3	]	]	PUNCT
ajst-8015	329	4	j.	j.	PROPN
ajst-8015	329	5	liu	liu	PROPN
ajst-8015	329	6	,	,	PUNCT
ajst-8015	329	7	g.	g.	PROPN
ajst-8015	329	8	tan	tan	PROPN
ajst-8015	329	9	,	,	PUNCT
ajst-8015	329	10	w.	w.	PROPN
ajst-8015	329	11	lan	lan	PROPN
ajst-8015	329	12	,	,	PUNCT
ajst-8015	329	13	and	and	CCONJ
ajst-8015	329	14	j.	j.	PROPN
ajst-8015	329	15	wang	wang	PROPN
ajst-8015	329	16	,	,	PUNCT
ajst-8015	329	17	“	"	PUNCT
ajst-8015	329	18	identification	identification	NOUN
ajst-8015	329	19	of	of	ADP
ajst-8015	329	20	early	early	ADJ
ajst-8015	329	21	mild	mild	ADJ
ajst-8015	329	22	cognitive	cognitive	ADJ
ajst-8015	329	23	impairment	impairment	NOUN
ajst-8015	329	24	using	use	VERB
ajst-8015	329	25	multi	multi	ADJ
ajst-8015	329	26	-	-	ADJ
ajst-8015	329	27	modal	modal	ADJ
ajst-8015	329	28	data	datum	NOUN
ajst-8015	329	29	and	and	CCONJ
ajst-8015	329	30	graph	graph	VERB
ajst-8015	329	31	convolutional	convolutional	ADJ
ajst-8015	329	32	networks	network	NOUN
ajst-8015	329	33	,	,	PUNCT
ajst-8015	329	34	”	"	PUNCT
ajst-8015	329	35	bmc	bmc	ADJ
ajst-8015	329	36	bioinformatics	bioinformatics	NOUN
ajst-8015	329	37	,	,	PUNCT
ajst-8015	329	38	vol	vol	NOUN
ajst-8015	329	39	.	.	PROPN
ajst-8015	329	40	21	21	NUM
ajst-8015	329	41	,	,	PUNCT
ajst-8015	329	42	no	no	INTJ
ajst-8015	329	43	.	.	PUNCT
ajst-8015	329	44	s6	s6	PROPN
ajst-8015	329	45	,	,	PUNCT
ajst-8015	329	46	p.	p.	NOUN
ajst-8015	329	47	123	123	NUM
ajst-8015	329	48	,	,	PUNCT
ajst-8015	329	49	nov	nov	PROPN
ajst-8015	329	50	.	.	PROPN
ajst-8015	329	51	2020	2020	NUM
ajst-8015	329	52	,	,	PUNCT
ajst-8015	329	53	doi	doi	NOUN
ajst-8015	329	54	:	:	PUNCT
ajst-8015	329	55	10.1186	10.1186	NUM
ajst-8015	329	56	/	/	SYM
ajst-8015	329	57	s12859	s12859	NOUN
ajst-8015	329	58	-	-	PUNCT
ajst-8015	329	59	020	020	NUM
ajst-8015	329	60	-	-	PUNCT
ajst-8015	329	61	3437	3437	NUM
ajst-8015	329	62	-	-	SYM
ajst-8015	329	63	6	6	NUM
ajst-8015	329	64	.	.	PUNCT
ajst-8015	330	1	[	[	X
ajst-8015	330	2	53	53	NUM
ajst-8015	330	3	]	]	PUNCT
ajst-8015	330	4	h.	h.	PROPN
ajst-8015	330	5	li	li	PROPN
ajst-8015	330	6	and	and	CCONJ
ajst-8015	330	7	y.	y.	PROPN
ajst-8015	330	8	fan	fan	PROPN
ajst-8015	330	9	,	,	PUNCT
ajst-8015	330	10	“	"	PUNCT
ajst-8015	330	11	early	early	ADJ
ajst-8015	330	12	prediction	prediction	NOUN
ajst-8015	330	13	of	of	ADP
ajst-8015	330	14	alzheimer	alzheimer	PROPN
ajst-8015	330	15	’s	’s	PART
ajst-8015	330	16	disease	disease	NOUN
ajst-8015	330	17	dementia	dementia	NOUN
ajst-8015	330	18	based	base	VERB
ajst-8015	330	19	on	on	ADP
ajst-8015	330	20	baseline	baseline	NOUN
ajst-8015	330	21	hippocampal	hippocampal	ADJ
ajst-8015	330	22	mri	mri	NOUN
ajst-8015	330	23	and	and	CCONJ
ajst-8015	330	24	1	1	NUM
ajst-8015	330	25	-	-	PUNCT
ajst-8015	330	26	year	year	NOUN
ajst-8015	330	27	follow	follow	NOUN
ajst-8015	330	28	-	-	PUNCT
ajst-8015	330	29	up	up	ADP
ajst-8015	330	30	cognitive	cognitive	ADJ
ajst-8015	330	31	measures	measure	NOUN
ajst-8015	330	32	using	use	VERB
ajst-8015	330	33	deep	deep	ADJ
ajst-8015	330	34	recurrent	recurrent	ADJ
ajst-8015	330	35	neural	neural	ADJ
ajst-8015	330	36	networks	network	NOUN
ajst-8015	330	37	,	,	PUNCT
ajst-8015	330	38	”	"	PUNCT
ajst-8015	330	39	in	in	ADP
ajst-8015	330	40	2019	2019	NUM
ajst-8015	330	41	ieee	ieee	NOUN
ajst-8015	330	42	16th	16th	ADJ
ajst-8015	330	43	international	international	ADJ
ajst-8015	330	44	symposium	symposium	NOUN
ajst-8015	330	45	on	on	ADP
ajst-8015	330	46	biomedical	biomedical	ADJ
ajst-8015	330	47	imaging	imaging	NOUN
ajst-8015	330	48	(	(	PUNCT
ajst-8015	330	49	isbi	isbi	NOUN
ajst-8015	330	50	2019	2019	NUM
ajst-8015	330	51	)	)	PUNCT
ajst-8015	330	52	,	,	PUNCT
ajst-8015	330	53	ieee	ieee	NOUN
ajst-8015	330	54	,	,	PUNCT
ajst-8015	330	55	2019	2019	NUM
ajst-8015	330	56	,	,	PUNCT
ajst-8015	330	57	pp	pp	ADV
ajst-8015	330	58	.	.	PUNCT
ajst-8015	331	1	368–371	368–371	NUM
ajst-8015	331	2	.	.	PUNCT
ajst-8015	332	1	[	[	X
ajst-8015	332	2	54	54	NUM
ajst-8015	332	3	]	]	X
ajst-8015	332	4	n.	n.	PROPN
ajst-8015	332	5	srivastava	srivastava	PROPN
ajst-8015	332	6	,	,	PUNCT
ajst-8015	332	7	e.	e.	PROPN
ajst-8015	332	8	mansimov	mansimov	PROPN
ajst-8015	332	9	,	,	PUNCT
ajst-8015	332	10	and	and	CCONJ
ajst-8015	332	11	r.	r.	PROPN
ajst-8015	332	12	salakhudinov	salakhudinov	PROPN
ajst-8015	332	13	,	,	PUNCT
ajst-8015	332	14	“	"	PUNCT
ajst-8015	332	15	unsupervised	unsupervised	ADJ
ajst-8015	332	16	learning	learning	NOUN
ajst-8015	332	17	of	of	ADP
ajst-8015	332	18	video	video	NOUN
ajst-8015	332	19	representations	representation	NOUN
ajst-8015	332	20	using	use	VERB
ajst-8015	332	21	lstms	lstms	NOUN
ajst-8015	332	22	,	,	PUNCT
ajst-8015	332	23	”	"	PUNCT
ajst-8015	332	24	in	in	ADP
ajst-8015	332	25	international	international	ADJ
ajst-8015	332	26	conference	conference	NOUN
ajst-8015	332	27	on	on	ADP
ajst-8015	332	28	machine	machine	NOUN
ajst-8015	332	29	learning	learning	NOUN
ajst-8015	332	30	,	,	PUNCT
ajst-8015	332	31	pmlr	pmlr	NOUN
ajst-8015	332	32	,	,	PUNCT
ajst-8015	332	33	2015	2015	NUM
ajst-8015	332	34	,	,	PUNCT
ajst-8015	332	35	pp	pp	ADJ
ajst-8015	332	36	.	.	PUNCT
ajst-8015	333	1	843–852	843–852	NUM
ajst-8015	333	2	.	.	PUNCT
ajst-8015	334	1	[	[	X
ajst-8015	334	2	55	55	NUM
ajst-8015	334	3	]	]	X
ajst-8015	334	4	g.	g.	PROPN
ajst-8015	334	5	lee	lee	PROPN
ajst-8015	334	6	,	,	PUNCT
ajst-8015	334	7	k.	k.	PROPN
ajst-8015	334	8	nho	nho	PROPN
ajst-8015	334	9	,	,	PUNCT
ajst-8015	334	10	b.	b.	PROPN
ajst-8015	334	11	kang	kang	PROPN
ajst-8015	334	12	,	,	PUNCT
ajst-8015	334	13	k.-a	k.-a	PROPN
ajst-8015	334	14	.	.	PUNCT
ajst-8015	335	1	sohn	sohn	PROPN
ajst-8015	335	2	,	,	PUNCT
ajst-8015	335	3	and	and	CCONJ
ajst-8015	335	4	d.	d.	PROPN
ajst-8015	335	5	kim	kim	PROPN
ajst-8015	335	6	,	,	PUNCT
ajst-8015	335	7	“	"	PUNCT
ajst-8015	335	8	predicting	predict	VERB
ajst-8015	335	9	alzheimer	alzheimer	PROPN
ajst-8015	335	10	’s	’s	PART
ajst-8015	335	11	disease	disease	NOUN
ajst-8015	335	12	progression	progression	NOUN
ajst-8015	335	13	using	use	VERB
ajst-8015	335	14	multi	multi	ADJ
ajst-8015	335	15	-	-	ADJ
ajst-8015	335	16	modal	modal	ADJ
ajst-8015	335	17	deep	deep	ADJ
ajst-8015	335	18	learning	learning	NOUN
ajst-8015	335	19	approach	approach	NOUN
ajst-8015	335	20	,	,	PUNCT
ajst-8015	335	21	”	"	PUNCT
ajst-8015	335	22	scientific	scientific	ADJ
ajst-8015	335	23	reports	report	NOUN
ajst-8015	335	24	,	,	PUNCT
ajst-8015	335	25	vol	vol	NOUN
ajst-8015	335	26	.	.	PROPN
ajst-8015	335	27	9	9	NUM
ajst-8015	335	28	,	,	PUNCT
ajst-8015	335	29	no	no	INTJ
ajst-8015	335	30	.	.	NOUN
ajst-8015	335	31	1	1	NUM
ajst-8015	335	32	,	,	PUNCT
ajst-8015	335	33	pp	pp	ADJ
ajst-8015	335	34	.	.	PUNCT
ajst-8015	336	1	1–12	1–12	NOUN
ajst-8015	336	2	,	,	PUNCT
ajst-8015	336	3	2019	2019	NUM
ajst-8015	336	4	.	.	PUNCT