id	sid	tid	token	lemma	pos
ajst-29292	1	1	academic	academic	ADJ
ajst-29292	1	2	journal	journal	NOUN
ajst-29292	1	3	of	of	ADP
ajst-29292	1	4	science	science	NOUN
ajst-29292	1	5	and	and	CCONJ
ajst-29292	1	6	technology	technology	NOUN
ajst-29292	1	7	issn	issn	NOUN
ajst-29292	1	8	:	:	PUNCT
ajst-29292	1	9	2771	2771	NUM
ajst-29292	1	10	-	-	SYM
ajst-29292	1	11	3032	3032	NUM
ajst-29292	1	12	|	|	NOUN
ajst-29292	1	13	vol	vol	NOUN
ajst-29292	1	14	.	.	PUNCT
ajst-29292	2	1	14	14	NUM
ajst-29292	2	2	,	,	PUNCT
ajst-29292	2	3	no	no	INTJ
ajst-29292	2	4	.	.	NOUN
ajst-29292	2	5	1	1	NUM
ajst-29292	2	6	,	,	PUNCT
ajst-29292	2	7	2025	2025	NUM
ajst-29292	2	8	85	85	NUM
ajst-29292	2	9	study	study	NOUN
ajst-29292	2	10	on	on	ADP
ajst-29292	2	11	the	the	DET
ajst-29292	2	12	efficacy	efficacy	NOUN
ajst-29292	2	13	of	of	ADP
ajst-29292	2	14	a	a	DET
ajst-29292	2	15	novel	novel	ADJ
ajst-29292	2	16	sedative	sedative	NOUN
ajst-29292	2	17	medication	medication	NOUN
ajst-29292	2	18	based	base	VERB
ajst-29292	2	19	on	on	ADP
ajst-29292	2	20	wilcoxon	wilcoxon	PROPN
ajst-29292	2	21	rank‐sum	rank‐sum	PROPN
ajst-29292	2	22	test	test	NOUN
ajst-29292	2	23	and	and	CCONJ
ajst-29292	2	24	multiple	multiple	ADJ
ajst-29292	2	25	machine	machine	NOUN
ajst-29292	2	26	learning	learning	NOUN
ajst-29292	2	27	models	model	NOUN
ajst-29292	3	1	yuxiao	yuxiao	PROPN
ajst-29292	3	2	chen	chen	PROPN
ajst-29292	3	3	*	*	PROPN
ajst-29292	3	4	school	school	NOUN
ajst-29292	3	5	of	of	ADP
ajst-29292	3	6	mechatronics	mechatronic	NOUN
ajst-29292	3	7	and	and	CCONJ
ajst-29292	3	8	mold	mold	NOUN
ajst-29292	3	9	engineering	engineering	NOUN
ajst-29292	3	10	,	,	PUNCT
ajst-29292	3	11	taizhou	taizhou	PROPN
ajst-29292	3	12	vocational	vocational	PROPN
ajst-29292	3	13	college	college	PROPN
ajst-29292	3	14	of	of	ADP
ajst-29292	3	15	science	science	PROPN
ajst-29292	3	16	&	&	CCONJ
ajst-29292	3	17	technology	technology	PROPN
ajst-29292	3	18	,	,	PUNCT
ajst-29292	3	19	taizhou	taizhou	PROPN
ajst-29292	3	20	,	,	PUNCT
ajst-29292	3	21	china	china	PROPN
ajst-29292	3	22	*	*	PUNCT
ajst-29292	3	23	corresponding	correspond	VERB
ajst-29292	3	24	author	author	NOUN
ajst-29292	3	25	abstract	abstract	NOUN
ajst-29292	3	26	:	:	PUNCT
ajst-29292	3	27	this	this	DET
ajst-29292	3	28	study	study	NOUN
ajst-29292	3	29	investigates	investigate	VERB
ajst-29292	3	30	the	the	DET
ajst-29292	3	31	efficacy	efficacy	NOUN
ajst-29292	3	32	of	of	ADP
ajst-29292	3	33	a	a	DET
ajst-29292	3	34	novel	novel	ADJ
ajst-29292	3	35	sedative	sedative	NOUN
ajst-29292	3	36	medication	medication	NOUN
ajst-29292	3	37	compared	compare	VERB
ajst-29292	3	38	to	to	ADP
ajst-29292	3	39	an	an	DET
ajst-29292	3	40	existing	exist	VERB
ajst-29292	3	41	drug	drug	NOUN
ajst-29292	3	42	using	use	VERB
ajst-29292	3	43	the	the	DET
ajst-29292	3	44	wilcoxon	wilcoxon	ADJ
ajst-29292	3	45	rank	rank	NOUN
ajst-29292	3	46	-	-	PUNCT
ajst-29292	3	47	sum	sum	NOUN
ajst-29292	3	48	test	test	NOUN
ajst-29292	3	49	and	and	CCONJ
ajst-29292	3	50	multiple	multiple	ADJ
ajst-29292	3	51	machine	machine	NOUN
ajst-29292	3	52	learning	learning	NOUN
ajst-29292	3	53	models	model	NOUN
ajst-29292	3	54	.	.	PUNCT
ajst-29292	4	1	the	the	DET
ajst-29292	4	2	wilcoxon	wilcoxon	ADJ
ajst-29292	4	3	rank	rank	NOUN
ajst-29292	4	4	-	-	PUNCT
ajst-29292	4	5	sum	sum	NOUN
ajst-29292	4	6	test	test	NOUN
ajst-29292	4	7	revealed	reveal	VERB
ajst-29292	4	8	statistically	statistically	ADV
ajst-29292	4	9	significant	significant	ADJ
ajst-29292	4	10	differences	difference	NOUN
ajst-29292	4	11	in	in	ADP
ajst-29292	4	12	petco200	petco200	PROPN
ajst-29292	4	13	,	,	PUNCT
ajst-29292	4	14	petco2005	petco2005	PROPN
ajst-29292	4	15	,	,	PUNCT
ajst-29292	4	16	ipi005	ipi005	PROPN
ajst-29292	4	17	,	,	PUNCT
ajst-29292	4	18	and	and	CCONJ
ajst-29292	4	19	moaas005	moaas005	PROPN
ajst-29292	4	20	indicators	indicator	NOUN
ajst-29292	4	21	,	,	PUNCT
ajst-29292	4	22	primarily	primarily	ADV
ajst-29292	4	23	within	within	ADP
ajst-29292	4	24	the	the	DET
ajst-29292	4	25	first	first	ADJ
ajst-29292	4	26	1	1	NUM
ajst-29292	4	27	to	to	PART
ajst-29292	4	28	3	3	NUM
ajst-29292	4	29	minutes	minute	NOUN
ajst-29292	4	30	post	post	ADJ
ajst-29292	4	31	-	-	NOUN
ajst-29292	4	32	induction	induction	NOUN
ajst-29292	4	33	.	.	PUNCT
ajst-29292	5	1	basic	basic	ADJ
ajst-29292	5	2	information	information	NOUN
ajst-29292	5	3	between	between	ADP
ajst-29292	5	4	the	the	DET
ajst-29292	5	5	novel	novel	NOUN
ajst-29292	5	6	and	and	CCONJ
ajst-29292	5	7	existing	exist	VERB
ajst-29292	5	8	drug	drug	NOUN
ajst-29292	5	9	groups	group	NOUN
ajst-29292	5	10	was	be	AUX
ajst-29292	5	11	comparable	comparable	ADJ
ajst-29292	5	12	,	,	PUNCT
ajst-29292	5	13	suggesting	suggest	VERB
ajst-29292	5	14	effective	effective	ADJ
ajst-29292	5	15	variable	variable	ADJ
ajst-29292	5	16	control	control	NOUN
ajst-29292	5	17	and	and	CCONJ
ajst-29292	5	18	attributing	attribute	VERB
ajst-29292	5	19	differences	difference	NOUN
ajst-29292	5	20	to	to	ADP
ajst-29292	5	21	the	the	DET
ajst-29292	5	22	novel	novel	ADJ
ajst-29292	5	23	sedative	sedative	NOUN
ajst-29292	5	24	.	.	PUNCT
ajst-29292	6	1	subsequently	subsequently	ADV
ajst-29292	6	2	,	,	PUNCT
ajst-29292	6	3	various	various	ADJ
ajst-29292	6	4	evaluation	evaluation	NOUN
ajst-29292	6	5	metrics	metric	NOUN
ajst-29292	6	6	including	include	VERB
ajst-29292	6	7	mse	mse	PROPN
ajst-29292	6	8	,	,	PUNCT
ajst-29292	6	9	rmse	rmse	PROPN
ajst-29292	6	10	,	,	PUNCT
ajst-29292	6	11	mae	mae	PROPN
ajst-29292	6	12	,	,	PUNCT
ajst-29292	6	13	mape	mape	NOUN
ajst-29292	6	14	,	,	PUNCT
ajst-29292	6	15	and	and	CCONJ
ajst-29292	6	16	r²	r²	NOUN
ajst-29292	6	17	were	be	AUX
ajst-29292	6	18	employed	employ	VERB
ajst-29292	6	19	.	.	PUNCT
ajst-29292	7	1	exploratory	exploratory	ADJ
ajst-29292	7	2	predictions	prediction	NOUN
ajst-29292	7	3	using	use	VERB
ajst-29292	7	4	the	the	DET
ajst-29292	7	5	random	random	ADJ
ajst-29292	7	6	forest	forest	NOUN
ajst-29292	7	7	(	(	PUNCT
ajst-29292	7	8	rf	rf	NOUN
ajst-29292	7	9	)	)	PUNCT
ajst-29292	7	10	model	model	NOUN
ajst-29292	7	11	yielded	yield	VERB
ajst-29292	7	12	suboptimal	suboptimal	ADJ
ajst-29292	7	13	results	result	NOUN
ajst-29292	7	14	.	.	PUNCT
ajst-29292	8	1	after	after	ADP
ajst-29292	8	2	comparing	compare	VERB
ajst-29292	8	3	the	the	DET
ajst-29292	8	4	performance	performance	NOUN
ajst-29292	8	5	of	of	ADP
ajst-29292	8	6	rf	rf	NOUN
ajst-29292	8	7	,	,	PUNCT
ajst-29292	8	8	xgboost	xgboost	PRON
ajst-29292	8	9	,	,	PUNCT
ajst-29292	8	10	catboost	catboost	ADJ
ajst-29292	8	11	,	,	PUNCT
ajst-29292	8	12	lightgbm	lightgbm	ADJ
ajst-29292	8	13	,	,	PUNCT
ajst-29292	8	14	and	and	CCONJ
ajst-29292	8	15	svr	svr	PROPN
ajst-29292	8	16	,	,	PUNCT
ajst-29292	8	17	a	a	DET
ajst-29292	8	18	combination	combination	NOUN
ajst-29292	8	19	of	of	ADP
ajst-29292	8	20	the	the	DET
ajst-29292	8	21	rf	rf	NOUN
ajst-29292	8	22	model	model	NOUN
ajst-29292	8	23	and	and	CCONJ
ajst-29292	8	24	logistic	logistic	ADJ
ajst-29292	8	25	regression	regression	NOUN
ajst-29292	8	26	was	be	AUX
ajst-29292	8	27	selected	select	VERB
ajst-29292	8	28	for	for	ADP
ajst-29292	8	29	regression	regression	NOUN
ajst-29292	8	30	predictions	prediction	NOUN
ajst-29292	8	31	based	base	VERB
ajst-29292	8	32	on	on	ADP
ajst-29292	8	33	data	datum	NOUN
ajst-29292	8	34	type	type	NOUN
ajst-29292	8	35	.	.	PUNCT
ajst-29292	9	1	visualization	visualization	NOUN
ajst-29292	9	2	of	of	ADP
ajst-29292	9	3	results	result	NOUN
ajst-29292	9	4	demonstrated	demonstrate	VERB
ajst-29292	9	5	good	good	ADJ
ajst-29292	9	6	predictive	predictive	ADJ
ajst-29292	9	7	performance	performance	NOUN
ajst-29292	9	8	and	and	CCONJ
ajst-29292	9	9	mitigated	mitigate	VERB
ajst-29292	9	10	overfitting	overfitting	NOUN
ajst-29292	9	11	.	.	PUNCT
ajst-29292	10	1	keywords	keyword	NOUN
ajst-29292	10	2	:	:	PUNCT
ajst-29292	10	3	wilcoxon	wilcoxon	ADJ
ajst-29292	10	4	rank	rank	NOUN
ajst-29292	10	5	-	-	PUNCT
ajst-29292	10	6	sum	sum	NOUN
ajst-29292	10	7	test	test	NOUN
ajst-29292	10	8	,	,	PUNCT
ajst-29292	10	9	rf	rf	VERB
ajst-29292	10	10	,	,	PUNCT
ajst-29292	10	11	xgboost	xgboost	ADV
ajst-29292	10	12	,	,	PUNCT
ajst-29292	10	13	lightgbm	lightgbm	ADJ
ajst-29292	10	14	.	.	PUNCT
ajst-29292	11	1	1	1	X
ajst-29292	11	2	.	.	X
ajst-29292	11	3	introduction	introduction	NOUN
ajst-29292	11	4	sedation	sedation	NOUN
ajst-29292	11	5	is	be	AUX
ajst-29292	11	6	a	a	DET
ajst-29292	11	7	crucial	crucial	ADJ
ajst-29292	11	8	aspect	aspect	NOUN
ajst-29292	11	9	of	of	ADP
ajst-29292	11	10	medical	medical	ADJ
ajst-29292	11	11	procedures	procedure	NOUN
ajst-29292	11	12	,	,	PUNCT
ajst-29292	11	13	ensuring	ensure	VERB
ajst-29292	11	14	patient	patient	ADJ
ajst-29292	11	15	comfort	comfort	NOUN
ajst-29292	11	16	and	and	CCONJ
ajst-29292	11	17	cooperation	cooperation	NOUN
ajst-29292	11	18	while	while	SCONJ
ajst-29292	11	19	allowing	allow	VERB
ajst-29292	11	20	medical	medical	ADJ
ajst-29292	11	21	staff	staff	NOUN
ajst-29292	11	22	to	to	PART
ajst-29292	11	23	perform	perform	VERB
ajst-29292	11	24	tasks	task	NOUN
ajst-29292	11	25	efficiently	efficiently	ADV
ajst-29292	11	26	.	.	PUNCT
ajst-29292	12	1	the	the	DET
ajst-29292	12	2	development	development	NOUN
ajst-29292	12	3	of	of	ADP
ajst-29292	12	4	novel	novel	ADJ
ajst-29292	12	5	sedative	sedative	NOUN
ajst-29292	12	6	medications	medication	NOUN
ajst-29292	12	7	aims	aim	VERB
ajst-29292	12	8	to	to	PART
ajst-29292	12	9	improve	improve	VERB
ajst-29292	12	10	efficacy	efficacy	NOUN
ajst-29292	12	11	,	,	PUNCT
ajst-29292	12	12	reduce	reduce	VERB
ajst-29292	12	13	side	side	NOUN
ajst-29292	12	14	effects	effect	NOUN
ajst-29292	12	15	,	,	PUNCT
ajst-29292	12	16	and	and	CCONJ
ajst-29292	12	17	enhance	enhance	VERB
ajst-29292	12	18	patient	patient	ADJ
ajst-29292	12	19	outcomes	outcome	NOUN
ajst-29292	12	20	.	.	PUNCT
ajst-29292	13	1	in	in	ADP
ajst-29292	13	2	this	this	DET
ajst-29292	13	3	study	study	NOUN
ajst-29292	13	4	,	,	PUNCT
ajst-29292	13	5	we	we	PRON
ajst-29292	13	6	focus	focus	VERB
ajst-29292	13	7	on	on	ADP
ajst-29292	13	8	evaluating	evaluate	VERB
ajst-29292	13	9	a	a	DET
ajst-29292	13	10	newly	newly	ADV
ajst-29292	13	11	developed	develop	VERB
ajst-29292	13	12	sedative	sedative	ADJ
ajst-29292	13	13	drug	drug	NOUN
ajst-29292	13	14	against	against	ADP
ajst-29292	13	15	an	an	DET
ajst-29292	13	16	established	establish	VERB
ajst-29292	13	17	medication	medication	NOUN
ajst-29292	13	18	.	.	PUNCT
ajst-29292	14	1	phong	phong	PROPN
ajst-29292	14	2	b.	b.	PROPN
ajst-29292	14	3	dao	dao	PROPN
ajst-29292	14	4	,	,	PUNCT
ajst-29292	14	5	in	in	ADP
ajst-29292	14	6	his	his	PRON
ajst-29292	14	7	work[1	work[1	PROPN
ajst-29292	14	8	]	]	PUNCT
ajst-29292	14	9	,	,	PUNCT
ajst-29292	14	10	applied	apply	VERB
ajst-29292	14	11	the	the	DET
ajst-29292	14	12	wilcoxon	wilcoxon	ADJ
ajst-29292	14	13	ranksum	ranksum	NOUN
ajst-29292	14	14	test	test	NOUN
ajst-29292	14	15	,	,	PUNCT
ajst-29292	14	16	a	a	DET
ajst-29292	14	17	non	non	ADJ
ajst-29292	14	18	-	-	ADJ
ajst-29292	14	19	parametric	parametric	ADJ
ajst-29292	14	20	statistical	statistical	ADJ
ajst-29292	14	21	test	test	NOUN
ajst-29292	14	22	from	from	ADP
ajst-29292	14	23	the	the	DET
ajst-29292	14	24	field	field	NOUN
ajst-29292	14	25	of	of	ADP
ajst-29292	14	26	statistics	statistic	NOUN
ajst-29292	14	27	,	,	PUNCT
ajst-29292	14	28	to	to	PART
ajst-29292	14	29	monitor	monitor	VERB
ajst-29292	14	30	the	the	DET
ajst-29292	14	31	operational	operational	ADJ
ajst-29292	14	32	status	status	NOUN
ajst-29292	14	33	and	and	CCONJ
ajst-29292	14	34	automate	automate	ADJ
ajst-29292	14	35	fault	fault	NOUN
ajst-29292	14	36	detection	detection	NOUN
ajst-29292	14	37	in	in	ADP
ajst-29292	14	38	wind	wind	NOUN
ajst-29292	14	39	turbines	turbine	NOUN
ajst-29292	14	40	.	.	PUNCT
ajst-29292	15	1	he	he	PRON
ajst-29292	15	2	introduced	introduce	VERB
ajst-29292	15	3	a	a	DET
ajst-29292	15	4	five	five	NUM
ajst-29292	15	5	-	-	PUNCT
ajst-29292	15	6	step	step	NOUN
ajst-29292	15	7	computational	computational	ADJ
ajst-29292	15	8	method	method	NOUN
ajst-29292	15	9	grounded	ground	VERB
ajst-29292	15	10	in	in	ADP
ajst-29292	15	11	statistical	statistical	ADJ
ajst-29292	15	12	hypothesis	hypothesis	NOUN
ajst-29292	15	13	testing	testing	NOUN
ajst-29292	15	14	,	,	PUNCT
ajst-29292	15	15	with	with	ADP
ajst-29292	15	16	the	the	DET
ajst-29292	15	17	null	null	ADJ
ajst-29292	15	18	hypothesis	hypothesis	NOUN
ajst-29292	15	19	stipulating	stipulate	VERB
ajst-29292	15	20	normal	normal	ADJ
ajst-29292	15	21	,	,	PUNCT
ajst-29292	15	22	fault	fault	NOUN
ajst-29292	15	23	-	-	PUNCT
ajst-29292	15	24	free	free	ADJ
ajst-29292	15	25	turbine	turbine	NOUN
ajst-29292	15	26	operation	operation	NOUN
ajst-29292	15	27	.	.	PUNCT
ajst-29292	16	1	rejection	rejection	NOUN
ajst-29292	16	2	of	of	ADP
ajst-29292	16	3	the	the	DET
ajst-29292	16	4	null	null	ADJ
ajst-29292	16	5	hypothesis	hypothesis	NOUN
ajst-29292	16	6	in	in	ADP
ajst-29292	16	7	favor	favor	NOUN
ajst-29292	16	8	of	of	ADP
ajst-29292	16	9	the	the	DET
ajst-29292	16	10	alternative	alternative	NOUN
ajst-29292	16	11	suggests	suggest	VERB
ajst-29292	16	12	turbine	turbine	NOUN
ajst-29292	16	13	malfunction	malfunction	NOUN
ajst-29292	16	14	,	,	PUNCT
ajst-29292	16	15	indicated	indicate	VERB
ajst-29292	16	16	by	by	ADP
ajst-29292	16	17	an	an	DET
ajst-29292	16	18	abrupt	abrupt	ADJ
ajst-29292	16	19	change	change	NOUN
ajst-29292	16	20	from	from	ADP
ajst-29292	16	21	0	0	NUM
ajst-29292	16	22	to	to	ADP
ajst-29292	16	23	1	1	NUM
ajst-29292	16	24	in	in	ADP
ajst-29292	16	25	the	the	DET
ajst-29292	16	26	test	test	NOUN
ajst-29292	16	27	decision	decision	NOUN
ajst-29292	16	28	.	.	PUNCT
ajst-29292	17	1	m.r	m.r	PROPN
ajst-29292	17	2	.	.	PROPN
ajst-29292	17	3	simi	simi	PROPN
ajst-29292	17	4	et	et	PROPN
ajst-29292	17	5	al	al	PROPN
ajst-29292	17	6	.	.	PUNCT
ajst-29292	18	1	[	[	X
ajst-29292	18	2	2	2	NUM
ajst-29292	18	3	]	]	PUNCT
ajst-29292	18	4	utilized	utilize	VERB
ajst-29292	18	5	the	the	DET
ajst-29292	18	6	wilcoxon	wilcoxon	ADJ
ajst-29292	18	7	rank	rank	NOUN
ajst-29292	18	8	-	-	PUNCT
ajst-29292	18	9	sum	sum	NOUN
ajst-29292	18	10	test	test	NOUN
ajst-29292	18	11	and	and	CCONJ
ajst-29292	18	12	nonparametric	nonparametric	NOUN
ajst-29292	18	13	statistical	statistical	ADJ
ajst-29292	18	14	methods	method	NOUN
ajst-29292	18	15	to	to	PART
ajst-29292	18	16	adjust	adjust	VERB
ajst-29292	18	17	the	the	DET
ajst-29292	18	18	parameter	parameter	NOUN
ajst-29292	18	19	rates	rate	NOUN
ajst-29292	18	20	of	of	ADP
ajst-29292	18	21	the	the	DET
ajst-29292	18	22	drastic	drastic	ADJ
ajst-29292	18	23	model	model	NOUN
ajst-29292	18	24	,	,	PUNCT
ajst-29292	18	25	an	an	DET
ajst-29292	18	26	enhanced	enhanced	ADJ
ajst-29292	18	27	version	version	NOUN
ajst-29292	18	28	incorporating	incorporate	VERB
ajst-29292	18	29	anthropogenic	anthropogenic	ADJ
ajst-29292	18	30	factors	factor	NOUN
ajst-29292	18	31	(	(	PUNCT
ajst-29292	18	32	land	land	NOUN
ajst-29292	18	33	use	use	NOUN
ajst-29292	18	34	and/or	and/or	CCONJ
ajst-29292	18	35	land	land	NOUN
ajst-29292	18	36	cover	cover	NOUN
ajst-29292	18	37	)	)	PUNCT
ajst-29292	18	38	.	.	PUNCT
ajst-29292	19	1	alexander	alexander	PROPN
ajst-29292	19	2	p.	p.	PROPN
ajst-29292	19	3	nocera	nocera	PROPN
ajst-29292	19	4	et	et	PROPN
ajst-29292	19	5	al	al	PROPN
ajst-29292	19	6	.	.	PUNCT
ajst-29292	20	1	[	[	X
ajst-29292	20	2	3	3	X
ajst-29292	20	3	]	]	PUNCT
ajst-29292	20	4	found	find	VERB
ajst-29292	20	5	a	a	DET
ajst-29292	20	6	positive	positive	ADJ
ajst-29292	20	7	correlation	correlation	NOUN
ajst-29292	20	8	between	between	ADP
ajst-29292	20	9	hindex	hindex	NOUN
ajst-29292	20	10	,	,	PUNCT
ajst-29292	20	11	m	m	NOUN
ajst-29292	20	12	-	-	NOUN
ajst-29292	20	13	index	index	NOUN
ajst-29292	20	14	,	,	PUNCT
ajst-29292	20	15	and	and	CCONJ
ajst-29292	20	16	academic	academic	ADJ
ajst-29292	20	17	ranking	ranking	NOUN
ajst-29292	20	18	among	among	ADP
ajst-29292	20	19	authors	author	NOUN
ajst-29292	20	20	.	.	PUNCT
ajst-29292	21	1	among	among	ADP
ajst-29292	21	2	the	the	DET
ajst-29292	21	3	2,253	2,253	NUM
ajst-29292	21	4	urological	urological	ADJ
ajst-29292	21	5	academics	academic	NOUN
ajst-29292	21	6	evaluated	evaluate	VERB
ajst-29292	21	7	,	,	PUNCT
ajst-29292	21	8	department	department	NOUN
ajst-29292	21	9	chairs	chair	NOUN
ajst-29292	21	10	/	/	SYM
ajst-29292	21	11	directors	director	NOUN
ajst-29292	21	12	and	and	CCONJ
ajst-29292	21	13	professors	professor	NOUN
ajst-29292	21	14	exhibited	exhibit	VERB
ajst-29292	21	15	the	the	DET
ajst-29292	21	16	highest	high	ADJ
ajst-29292	21	17	median	median	ADJ
ajst-29292	21	18	hand	hand	NOUN
ajst-29292	21	19	m	m	NOUN
ajst-29292	21	20	-	-	PUNCT
ajst-29292	21	21	indices	index	NOUN
ajst-29292	21	22	(	(	PUNCT
ajst-29292	21	23	26	26	NUM
ajst-29292	21	24	for	for	ADP
ajst-29292	21	25	chairs	chair	NOUN
ajst-29292	21	26	/	/	SYM
ajst-29292	21	27	directors	director	NOUN
ajst-29292	21	28	with	with	ADP
ajst-29292	21	29	an	an	DET
ajst-29292	21	30	m	m	NOUN
ajst-29292	21	31	-	-	PUNCT
ajst-29292	21	32	index	index	NOUN
ajst-29292	21	33	of	of	ADP
ajst-29292	21	34	1.046	1.046	NUM
ajst-29292	21	35	,	,	PUNCT
ajst-29292	21	36	and	and	CCONJ
ajst-29292	21	37	30	30	NUM
ajst-29292	21	38	for	for	ADP
ajst-29292	21	39	professors	professor	NOUN
ajst-29292	21	40	with	with	ADP
ajst-29292	21	41	an	an	DET
ajst-29292	21	42	m	m	NOUN
ajst-29292	21	43	-	-	NOUN
ajst-29292	21	44	index	index	NOUN
ajst-29292	21	45	of	of	ADP
ajst-29292	21	46	1.094	1.094	NUM
ajst-29292	21	47	)	)	PUNCT
ajst-29292	21	48	.	.	PUNCT
ajst-29292	22	1	yiwei	yiwei	PROPN
ajst-29292	22	2	jia	jia	PROPN
ajst-29292	22	3	et	et	PROPN
ajst-29292	22	4	al	al	PROPN
ajst-29292	22	5	.	.	PUNCT
ajst-29292	23	1	[	[	X
ajst-29292	23	2	4	4	X
ajst-29292	23	3	]	]	PUNCT
ajst-29292	23	4	extracted	extract	VERB
ajst-29292	23	5	clinical	clinical	ADJ
ajst-29292	23	6	data	datum	NOUN
ajst-29292	23	7	from	from	ADP
ajst-29292	23	8	1,230	1,230	NUM
ajst-29292	23	9	inflammatory	inflammatory	ADJ
ajst-29292	23	10	breast	breast	NOUN
ajst-29292	23	11	cancer	cancer	NOUN
ajst-29292	23	12	(	(	PUNCT
ajst-29292	23	13	ibc	ibc	PROPN
ajst-29292	23	14	)	)	PUNCT
ajst-29292	23	15	patients	patient	NOUN
ajst-29292	23	16	between	between	ADP
ajst-29292	23	17	2010	2010	NUM
ajst-29292	23	18	and	and	CCONJ
ajst-29292	23	19	2020	2020	NUM
ajst-29292	23	20	from	from	ADP
ajst-29292	23	21	the	the	DET
ajst-29292	23	22	surveillance	surveillance	NOUN
ajst-29292	23	23	,	,	PUNCT
ajst-29292	23	24	epidemiology	epidemiology	NOUN
ajst-29292	23	25	,	,	PUNCT
ajst-29292	23	26	and	and	CCONJ
ajst-29292	23	27	end	end	VERB
ajst-29292	23	28	results	result	NOUN
ajst-29292	23	29	(	(	PUNCT
ajst-29292	23	30	seer	seer	NOUN
ajst-29292	23	31	)	)	PUNCT
ajst-29292	23	32	database	database	NOUN
ajst-29292	23	33	.	.	PUNCT
ajst-29292	24	1	cox	cox	PROPN
ajst-29292	24	2	analysis	analysis	NOUN
ajst-29292	24	3	was	be	AUX
ajst-29292	24	4	employed	employ	VERB
ajst-29292	24	5	to	to	PART
ajst-29292	24	6	identify	identify	VERB
ajst-29292	24	7	clinicopathological	clinicopathological	ADJ
ajst-29292	24	8	features	feature	NOUN
ajst-29292	24	9	associated	associate	VERB
ajst-29292	24	10	with	with	ADP
ajst-29292	24	11	overall	overall	ADJ
ajst-29292	24	12	survival	survival	NOUN
ajst-29292	24	13	(	(	PUNCT
ajst-29292	24	14	os	os	NOUN
ajst-29292	24	15	)	)	PUNCT
ajst-29292	24	16	in	in	ADP
ajst-29292	24	17	ibc	ibc	PROPN
ajst-29292	24	18	patients	patient	NOUN
ajst-29292	24	19	.	.	PUNCT
ajst-29292	25	1	a	a	DET
ajst-29292	25	2	random	random	ADJ
ajst-29292	25	3	survival	survival	NOUN
ajst-29292	25	4	forest	forest	NOUN
ajst-29292	25	5	(	(	PUNCT
ajst-29292	25	6	rsf	rsf	PROPN
ajst-29292	25	7	)	)	PUNCT
ajst-29292	25	8	algorithm	algorithm	NOUN
ajst-29292	25	9	was	be	AUX
ajst-29292	25	10	used	use	VERB
ajst-29292	25	11	to	to	PART
ajst-29292	25	12	develop	develop	VERB
ajst-29292	25	13	an	an	DET
ajst-29292	25	14	accurate	accurate	ADJ
ajst-29292	25	15	prognostic	prognostic	ADJ
ajst-29292	25	16	prediction	prediction	NOUN
ajst-29292	25	17	model	model	NOUN
ajst-29292	25	18	for	for	ADP
ajst-29292	25	19	ibc	ibc	PROPN
ajst-29292	25	20	patients	patient	NOUN
ajst-29292	25	21	,	,	PUNCT
ajst-29292	25	22	with	with	ADP
ajst-29292	25	23	survival	survival	NOUN
ajst-29292	25	24	analysis	analysis	NOUN
ajst-29292	25	25	conducted	conduct	VERB
ajst-29292	25	26	using	use	VERB
ajst-29292	25	27	kaplan	kaplan	PROPN
ajst-29292	25	28	-	-	PUNCT
ajst-29292	25	29	meier	meier	PROPN
ajst-29292	25	30	methods	method	NOUN
ajst-29292	25	31	.	.	PUNCT
ajst-29292	26	1	benjamin	benjamin	PROPN
ajst-29292	26	2	d.	d.	PROPN
ajst-29292	26	3	simon	simon	PROPN
ajst-29292	26	4	et	et	PROPN
ajst-29292	26	5	al	al	PROPN
ajst-29292	26	6	.	.	PUNCT
ajst-29292	27	1	[	[	X
ajst-29292	27	2	5	5	NUM
ajst-29292	27	3	]	]	PUNCT
ajst-29292	27	4	employed	employ	VERB
ajst-29292	27	5	a	a	DET
ajst-29292	27	6	deep	deep	ADJ
ajst-29292	27	7	learning	learning	NOUN
ajst-29292	27	8	-	-	PUNCT
ajst-29292	27	9	based	base	VERB
ajst-29292	27	10	ai	ai	NOUN
ajst-29292	27	11	workflow	workflow	NOUN
ajst-29292	27	12	for	for	ADP
ajst-29292	27	13	automatic	automatic	ADJ
ajst-29292	27	14	extraprostatic	extraprostatic	ADJ
ajst-29292	27	15	extension	extension	NOUN
ajst-29292	27	16	(	(	PUNCT
ajst-29292	27	17	epe	epe	PROPN
ajst-29292	27	18	)	)	PUNCT
ajst-29292	27	19	grading	grading	NOUN
ajst-29292	27	20	of	of	ADP
ajst-29292	27	21	prostate	prostate	NOUN
ajst-29292	27	22	t2w	t2w	ADP
ajst-29292	27	23	mri	mri	PROPN
ajst-29292	27	24	,	,	PUNCT
ajst-29292	27	25	adc	adc	PROPN
ajst-29292	27	26	map	map	NOUN
ajst-29292	27	27	,	,	PUNCT
ajst-29292	27	28	and	and	CCONJ
ajst-29292	27	29	high	high	ADJ
ajst-29292	27	30	b	b	NOUN
ajst-29292	27	31	-	-	PUNCT
ajst-29292	27	32	value	value	NOUN
ajst-29292	27	33	dwi	dwi	PROPN
ajst-29292	27	34	.	.	PROPN
ajst-29292	28	1	results	result	NOUN
ajst-29292	28	2	indicated	indicate	VERB
ajst-29292	28	3	a	a	DET
ajst-29292	28	4	lesion	lesion	NOUN
ajst-29292	28	5	detection	detection	NOUN
ajst-29292	28	6	probability	probability	NOUN
ajst-29292	28	7	threshold	threshold	NOUN
ajst-29292	28	8	of	of	ADP
ajst-29292	28	9	0.45	0.45	NUM
ajst-29292	28	10	and	and	CCONJ
ajst-29292	28	11	a	a	DET
ajst-29292	28	12	balanced	balanced	ADJ
ajst-29292	28	13	accuracy	accuracy	NOUN
ajst-29292	28	14	score	score	NOUN
ajst-29292	28	15	for	for	ADP
ajst-29292	28	16	distance	distance	NOUN
ajst-29292	28	17	features	feature	NOUN
ajst-29292	28	18	of	of	ADP
ajst-29292	28	19	0.390±0.078	0.390±0.078	NOUN
ajst-29292	28	20	.	.	PUNCT
ajst-29292	29	1	when	when	SCONJ
ajst-29292	29	2	applied	apply	VERB
ajst-29292	29	3	to	to	ADP
ajst-29292	29	4	the	the	DET
ajst-29292	29	5	test	test	NOUN
ajst-29292	29	6	set	set	NOUN
ajst-29292	29	7	,	,	PUNCT
ajst-29292	29	8	the	the	DET
ajst-29292	29	9	roc	roc	PROPN
ajst-29292	29	10	auc	auc	NOUN
ajst-29292	29	11	values	value	NOUN
ajst-29292	29	12	for	for	ADP
ajst-29292	29	13	ai	ai	ADV
ajst-29292	29	14	-	-	PUNCT
ajst-29292	29	15	assigned	assign	VERB
ajst-29292	29	16	epe	epe	NOUN
ajst-29292	29	17	grades	grade	NOUN
ajst-29292	29	18	0	0	NUM
ajst-29292	29	19	-	-	SYM
ajst-29292	29	20	3	3	NUM
ajst-29292	29	21	were	be	AUX
ajst-29292	29	22	0.70	0.70	NUM
ajst-29292	29	23	,	,	PUNCT
ajst-29292	29	24	0.65	0.65	NUM
ajst-29292	29	25	,	,	PUNCT
ajst-29292	29	26	0.68	0.68	NUM
ajst-29292	29	27	,	,	PUNCT
ajst-29292	29	28	and	and	CCONJ
ajst-29292	29	29	0.55	0.55	NUM
ajst-29292	29	30	,	,	PUNCT
ajst-29292	29	31	respectively	respectively	ADV
ajst-29292	29	32	.	.	PUNCT
ajst-29292	30	1	the	the	DET
ajst-29292	30	2	primary	primary	ADJ
ajst-29292	30	3	objective	objective	NOUN
ajst-29292	30	4	is	be	AUX
ajst-29292	30	5	to	to	PART
ajst-29292	30	6	identify	identify	VERB
ajst-29292	30	7	any	any	DET
ajst-29292	30	8	statistically	statistically	ADV
ajst-29292	30	9	significant	significant	ADJ
ajst-29292	30	10	differences	difference	NOUN
ajst-29292	30	11	in	in	ADP
ajst-29292	30	12	vital	vital	ADJ
ajst-29292	30	13	signs	sign	NOUN
ajst-29292	30	14	and	and	CCONJ
ajst-29292	30	15	other	other	ADJ
ajst-29292	30	16	relevant	relevant	ADJ
ajst-29292	30	17	indicators	indicator	NOUN
ajst-29292	30	18	between	between	ADP
ajst-29292	30	19	patients	patient	NOUN
ajst-29292	30	20	receiving	receive	VERB
ajst-29292	30	21	the	the	DET
ajst-29292	30	22	novel	novel	ADJ
ajst-29292	30	23	sedative	sedative	NOUN
ajst-29292	30	24	and	and	CCONJ
ajst-29292	30	25	those	those	PRON
ajst-29292	30	26	receiving	receive	VERB
ajst-29292	30	27	the	the	DET
ajst-29292	30	28	existing	exist	VERB
ajst-29292	30	29	drug	drug	NOUN
ajst-29292	30	30	.	.	PUNCT
ajst-29292	31	1	to	to	PART
ajst-29292	31	2	achieve	achieve	VERB
ajst-29292	31	3	this	this	PRON
ajst-29292	31	4	,	,	PUNCT
ajst-29292	31	5	we	we	PRON
ajst-29292	31	6	utilize	utilize	VERB
ajst-29292	31	7	the	the	DET
ajst-29292	31	8	wilcoxon	wilcoxon	ADJ
ajst-29292	31	9	rank	rank	NOUN
ajst-29292	31	10	-	-	PUNCT
ajst-29292	31	11	sum	sum	NOUN
ajst-29292	31	12	test	test	NOUN
ajst-29292	31	13	,	,	PUNCT
ajst-29292	31	14	a	a	DET
ajst-29292	31	15	non	non	ADJ
ajst-29292	31	16	-	-	ADJ
ajst-29292	31	17	parametric	parametric	ADJ
ajst-29292	31	18	statistical	statistical	ADJ
ajst-29292	31	19	hypothesis	hypothesis	NOUN
ajst-29292	31	20	test	test	NOUN
ajst-29292	31	21	suitable	suitable	ADJ
ajst-29292	31	22	for	for	ADP
ajst-29292	31	23	comparing	compare	VERB
ajst-29292	31	24	two	two	NUM
ajst-29292	31	25	groups	group	NOUN
ajst-29292	31	26	of	of	ADP
ajst-29292	31	27	samples	sample	NOUN
ajst-29292	31	28	when	when	SCONJ
ajst-29292	31	29	the	the	DET
ajst-29292	31	30	underlying	underlie	VERB
ajst-29292	31	31	distributions	distribution	NOUN
ajst-29292	31	32	are	be	AUX
ajst-29292	31	33	unknown	unknown	ADJ
ajst-29292	31	34	or	or	CCONJ
ajst-29292	31	35	nonnormal	nonnormal	ADJ
ajst-29292	31	36	.	.	PUNCT
ajst-29292	32	1	furthermore	furthermore	ADV
ajst-29292	32	2	,	,	PUNCT
ajst-29292	32	3	we	we	PRON
ajst-29292	32	4	aim	aim	VERB
ajst-29292	32	5	to	to	PART
ajst-29292	32	6	employ	employ	VERB
ajst-29292	32	7	machine	machine	NOUN
ajst-29292	32	8	learning	learning	NOUN
ajst-29292	32	9	models	model	NOUN
ajst-29292	32	10	to	to	PART
ajst-29292	32	11	predict	predict	VERB
ajst-29292	32	12	the	the	DET
ajst-29292	32	13	effectiveness	effectiveness	NOUN
ajst-29292	32	14	of	of	ADP
ajst-29292	32	15	both	both	DET
ajst-29292	32	16	sedatives	sedative	NOUN
ajst-29292	32	17	based	base	VERB
ajst-29292	32	18	on	on	ADP
ajst-29292	32	19	various	various	ADJ
ajst-29292	32	20	physiological	physiological	ADJ
ajst-29292	32	21	and	and	CCONJ
ajst-29292	32	22	demographic	demographic	ADJ
ajst-29292	32	23	factors	factor	NOUN
ajst-29292	32	24	.	.	PUNCT
ajst-29292	33	1	by	by	ADP
ajst-29292	33	2	selecting	select	VERB
ajst-29292	33	3	appropriate	appropriate	ADJ
ajst-29292	33	4	evaluation	evaluation	NOUN
ajst-29292	33	5	metrics	metric	NOUN
ajst-29292	33	6	such	such	ADJ
ajst-29292	33	7	as	as	ADP
ajst-29292	33	8	mean	mean	NOUN
ajst-29292	33	9	squared	square	VERB
ajst-29292	33	10	error	error	NOUN
ajst-29292	33	11	(	(	PUNCT
ajst-29292	33	12	mse	mse	NOUN
ajst-29292	33	13	)	)	PUNCT
ajst-29292	33	14	,	,	PUNCT
ajst-29292	33	15	root	root	NOUN
ajst-29292	33	16	mean	mean	VERB
ajst-29292	33	17	squared	square	VERB
ajst-29292	33	18	error	error	NOUN
ajst-29292	33	19	(	(	PUNCT
ajst-29292	33	20	rmse	rmse	NOUN
ajst-29292	33	21	)	)	PUNCT
ajst-29292	33	22	,	,	PUNCT
ajst-29292	33	23	mean	mean	VERB
ajst-29292	33	24	absolute	absolute	ADJ
ajst-29292	33	25	error	error	NOUN
ajst-29292	33	26	(	(	PUNCT
ajst-29292	33	27	mae	mae	PROPN
ajst-29292	33	28	)	)	PUNCT
ajst-29292	33	29	,	,	PUNCT
ajst-29292	33	30	mean	mean	VERB
ajst-29292	33	31	absolute	absolute	ADJ
ajst-29292	33	32	percentage	percentage	NOUN
ajst-29292	33	33	error	error	NOUN
ajst-29292	33	34	(	(	PUNCT
ajst-29292	33	35	mape	mape	NOUN
ajst-29292	33	36	)	)	PUNCT
ajst-29292	33	37	,	,	PUNCT
ajst-29292	33	38	and	and	CCONJ
ajst-29292	33	39	the	the	DET
ajst-29292	33	40	coefficient	coefficient	NOUN
ajst-29292	33	41	of	of	ADP
ajst-29292	33	42	determination	determination	NOUN
ajst-29292	33	43	(	(	PUNCT
ajst-29292	33	44	r²	r²	PROPN
ajst-29292	33	45	)	)	PUNCT
ajst-29292	33	46	,	,	PUNCT
ajst-29292	33	47	we	we	PRON
ajst-29292	33	48	can	can	AUX
ajst-29292	33	49	quantify	quantify	VERB
ajst-29292	33	50	the	the	DET
ajst-29292	33	51	predictive	predictive	ADJ
ajst-29292	33	52	performance	performance	NOUN
ajst-29292	33	53	of	of	ADP
ajst-29292	33	54	the	the	DET
ajst-29292	33	55	models	model	NOUN
ajst-29292	33	56	.	.	PUNCT
ajst-29292	34	1	this	this	DET
ajst-29292	34	2	study	study	NOUN
ajst-29292	34	3	explores	explore	VERB
ajst-29292	34	4	multiple	multiple	ADJ
ajst-29292	34	5	machine	machine	NOUN
ajst-29292	34	6	learning	learn	VERB
ajst-29292	34	7	algorithms	algorithm	NOUN
ajst-29292	34	8	,	,	PUNCT
ajst-29292	34	9	including	include	VERB
ajst-29292	34	10	random	random	ADJ
ajst-29292	34	11	forest	forest	NOUN
ajst-29292	34	12	(	(	PUNCT
ajst-29292	34	13	rf	rf	NOUN
ajst-29292	34	14	)	)	PUNCT
ajst-29292	34	15	,	,	PUNCT
ajst-29292	34	16	xgboost	xgboost	PROPN
ajst-29292	34	17	,	,	PUNCT
ajst-29292	34	18	catboost	catboost	ADJ
ajst-29292	34	19	,	,	PUNCT
ajst-29292	34	20	lightgbm	lightgbm	ADJ
ajst-29292	34	21	,	,	PUNCT
ajst-29292	34	22	and	and	CCONJ
ajst-29292	34	23	support	support	VERB
ajst-29292	34	24	vector	vector	NOUN
ajst-29292	34	25	regression	regression	NOUN
ajst-29292	34	26	(	(	PUNCT
ajst-29292	34	27	svr	svr	PROPN
ajst-29292	34	28	)	)	PUNCT
ajst-29292	34	29	,	,	PUNCT
ajst-29292	34	30	to	to	PART
ajst-29292	34	31	identify	identify	VERB
ajst-29292	34	32	the	the	DET
ajst-29292	34	33	most	most	ADV
ajst-29292	34	34	suitable	suitable	ADJ
ajst-29292	34	35	model	model	NOUN
ajst-29292	34	36	for	for	ADP
ajst-29292	34	37	predicting	predict	VERB
ajst-29292	34	38	sedative	sedative	ADJ
ajst-29292	34	39	efficacy	efficacy	NOUN
ajst-29292	34	40	.	.	PUNCT
ajst-29292	35	1	2	2	X
ajst-29292	35	2	.	.	X
ajst-29292	35	3	test	test	NOUN
ajst-29292	35	4	modeling	modeling	NOUN
ajst-29292	35	5	and	and	CCONJ
ajst-29292	35	6	solving	solve	VERB
ajst-29292	35	7	2.1	2.1	NUM
ajst-29292	35	8	.	.	PUNCT
ajst-29292	35	9	normality	normality	NOUN
ajst-29292	35	10	test	test	NOUN
ajst-29292	35	11	in	in	ADP
ajst-29292	35	12	order	order	NOUN
ajst-29292	35	13	to	to	PART
ajst-29292	35	14	make	make	VERB
ajst-29292	35	15	a	a	DET
ajst-29292	35	16	choice	choice	NOUN
ajst-29292	35	17	of	of	ADP
ajst-29292	35	18	the	the	DET
ajst-29292	35	19	test	test	NOUN
ajst-29292	35	20	,	,	PUNCT
ajst-29292	35	21	the	the	DET
ajst-29292	35	22	above	above	ADJ
ajst-29292	35	23	data	datum	NOUN
ajst-29292	35	24	were	be	AUX
ajst-29292	35	25	subjected	subject	VERB
ajst-29292	35	26	to	to	ADP
ajst-29292	35	27	descriptive	descriptive	ADJ
ajst-29292	35	28	statistics	statistic	NOUN
ajst-29292	35	29	,	,	PUNCT
ajst-29292	35	30	and	and	CCONJ
ajst-29292	35	31	the	the	DET
ajst-29292	35	32	normality	normality	NOUN
ajst-29292	35	33	test	test	NOUN
ajst-29292	35	34	was	be	AUX
ajst-29292	35	35	determined	determine	VERB
ajst-29292	35	36	.	.	PUNCT
ajst-29292	36	1	the	the	DET
ajst-29292	36	2	data	datum	NOUN
ajst-29292	36	3	were	be	AUX
ajst-29292	36	4	plotted	plot	VERB
ajst-29292	36	5	on	on	ADP
ajst-29292	36	6	a	a	DET
ajst-29292	36	7	qq	qq	ADJ
ajst-29292	36	8	matrix	matrix	NOUN
ajst-29292	36	9	to	to	PART
ajst-29292	36	10	roughly	roughly	ADV
ajst-29292	36	11	visualize	visualize	VERB
ajst-29292	36	12	their	their	PRON
ajst-29292	36	13	distribution	distribution	NOUN
ajst-29292	36	14	,	,	PUNCT
ajst-29292	36	15	as	as	SCONJ
ajst-29292	36	16	shown	show	VERB
ajst-29292	36	17	in	in	ADP
ajst-29292	36	18	fig.1	fig.1	PROPN
ajst-29292	36	19	.	.	PUNCT
ajst-29292	37	1	86	86	NUM
ajst-29292	37	2	figure	figure	NOUN
ajst-29292	37	3	1	1	NUM
ajst-29292	37	4	.	.	PUNCT
ajst-29292	37	5	randomized	randomize	VERB
ajst-29292	37	6	9	9	NUM
ajst-29292	37	7	-	-	PUNCT
ajst-29292	37	8	individual	individual	ADJ
ajst-29292	37	9	test	test	NOUN
ajst-29292	37	10	for	for	ADP
ajst-29292	37	11	normality	normality	NOUN
ajst-29292	37	12	of	of	ADP
ajst-29292	37	13	signs	sign	NOUN
ajst-29292	37	14	as	as	SCONJ
ajst-29292	37	15	seen	see	VERB
ajst-29292	37	16	in	in	ADP
ajst-29292	37	17	figure	figure	NOUN
ajst-29292	37	18	1	1	NUM
ajst-29292	37	19	,	,	PUNCT
ajst-29292	37	20	some	some	DET
ajst-29292	37	21	data	datum	NOUN
ajst-29292	37	22	may	may	AUX
ajst-29292	37	23	have	have	VERB
ajst-29292	37	24	a	a	DET
ajst-29292	37	25	normal	normal	ADJ
ajst-29292	37	26	relationship	relationship	NOUN
ajst-29292	37	27	with	with	ADP
ajst-29292	37	28	each	each	DET
ajst-29292	37	29	other	other	ADJ
ajst-29292	37	30	and	and	CCONJ
ajst-29292	37	31	some	some	DET
ajst-29292	37	32	data	datum	NOUN
ajst-29292	37	33	may	may	AUX
ajst-29292	37	34	be	be	AUX
ajst-29292	37	35	normally	normally	ADV
ajst-29292	37	36	distributed	distribute	VERB
ajst-29292	37	37	,	,	PUNCT
ajst-29292	37	38	in	in	ADP
ajst-29292	37	39	order	order	NOUN
ajst-29292	37	40	to	to	PART
ajst-29292	37	41	further	far	ADV
ajst-29292	37	42	analyze	analyze	VERB
ajst-29292	37	43	the	the	DET
ajst-29292	37	44	data	datum	NOUN
ajst-29292	37	45	distribution	distribution	NOUN
ajst-29292	37	46	.	.	PUNCT
ajst-29292	38	1	2.2	2.2	NUM
ajst-29292	38	2	.	.	PUNCT
ajst-29292	38	3	normality	normality	NOUN
ajst-29292	38	4	test	test	NOUN
ajst-29292	38	5	:	:	PUNCT
ajst-29292	38	6	shapiro	shapiro	PROPN
ajst-29292	38	7	-	-	PUNCT
ajst-29292	38	8	wilk	wilk	NOUN
ajst-29292	38	9	test	test	NOUN
ajst-29292	38	10	the	the	DET
ajst-29292	38	11	shapiro	shapiro	PROPN
ajst-29292	38	12	-	-	PUNCT
ajst-29292	38	13	wilk	wilk	NOUN
ajst-29292	38	14	test	test	NOUN
ajst-29292	38	15	is	be	AUX
ajst-29292	38	16	a	a	DET
ajst-29292	38	17	statistical	statistical	ADJ
ajst-29292	38	18	method	method	NOUN
ajst-29292	38	19	used	use	VERB
ajst-29292	38	20	to	to	PART
ajst-29292	38	21	test	test	VERB
ajst-29292	38	22	whether	whether	SCONJ
ajst-29292	38	23	a	a	DET
ajst-29292	38	24	sample	sample	NOUN
ajst-29292	38	25	of	of	ADP
ajst-29292	38	26	data	datum	NOUN
ajst-29292	38	27	comes	come	VERB
ajst-29292	38	28	from	from	ADP
ajst-29292	38	29	a	a	DET
ajst-29292	38	30	normal	normal	ADJ
ajst-29292	38	31	distribution	distribution	NOUN
ajst-29292	38	32	.	.	PUNCT
ajst-29292	39	1	this	this	DET
ajst-29292	39	2	test	test	NOUN
ajst-29292	39	3	is	be	AUX
ajst-29292	39	4	particularly	particularly	ADV
ajst-29292	39	5	effective	effective	ADJ
ajst-29292	39	6	for	for	ADP
ajst-29292	39	7	small	small	ADJ
ajst-29292	39	8	samples	sample	NOUN
ajst-29292	39	9	and	and	CCONJ
ajst-29292	39	10	is	be	AUX
ajst-29292	39	11	one	one	NUM
ajst-29292	39	12	of	of	ADP
ajst-29292	39	13	the	the	DET
ajst-29292	39	14	most	most	ADV
ajst-29292	39	15	common	common	ADJ
ajst-29292	39	16	ways	way	NOUN
ajst-29292	39	17	of	of	ADP
ajst-29292	39	18	detecting	detect	VERB
ajst-29292	39	19	normality	normality	NOUN
ajst-29292	39	20	the	the	DET
ajst-29292	39	21	shapiro	shapiro	PROPN
ajst-29292	39	22	-	-	PUNCT
ajst-29292	39	23	wilk	wilk	NOUN
ajst-29292	39	24	test	test	NOUN
ajst-29292	39	25	assumes	assume	VERB
ajst-29292	39	26	that	that	SCONJ
ajst-29292	39	27	the	the	DET
ajst-29292	39	28	sample	sample	NOUN
ajst-29292	39	29	data	data	NOUN
ajst-29292	39	30	is	be	AUX
ajst-29292	39	31	from	from	ADP
ajst-29292	39	32	a	a	DET
ajst-29292	39	33	normal	normal	ADJ
ajst-29292	39	34	distribution	distribution	NOUN
ajst-29292	39	35	and	and	CCONJ
ajst-29292	39	36	the	the	DET
ajst-29292	39	37	alternative	alternative	ADJ
ajst-29292	39	38	assumption	assumption	NOUN
ajst-29292	39	39	is	be	AUX
ajst-29292	39	40	that	that	SCONJ
ajst-29292	39	41	the	the	DET
ajst-29292	39	42	sample	sample	NOUN
ajst-29292	39	43	data	data	NOUN
ajst-29292	39	44	is	be	AUX
ajst-29292	39	45	not	not	PART
ajst-29292	39	46	from	from	ADP
ajst-29292	39	47	a	a	DET
ajst-29292	39	48	normal	normal	ADJ
ajst-29292	39	49	distribution	distribution	NOUN
ajst-29292	39	50	.	.	PUNCT
ajst-29292	40	1	the	the	DET
ajst-29292	40	2	statistic	statistic	PROPN
ajst-29292	40	3	w	w	PROPN
ajst-29292	40	4	of	of	ADP
ajst-29292	40	5	the	the	DET
ajst-29292	40	6	shapiro	shapiro	PROPN
ajst-29292	40	7	-	-	PUNCT
ajst-29292	40	8	wilk	wilk	NOUN
ajst-29292	40	9	test	test	NOUN
ajst-29292	40	10	is	be	AUX
ajst-29292	40	11	calculated	calculate	VERB
ajst-29292	40	12	as	as	ADP
ajst-29292	40	13	:	:	PUNCT
ajst-29292	40	14	𝑊	𝑊	VERB
ajst-29292	40	15	∑	∑	DET
ajst-29292	40	16	  	  	SPACE
ajst-29292	40	17	∑	∑	PART
ajst-29292	40	18	  	  	SPACE
ajst-29292	40	19	̅	̅	NOUN
ajst-29292	40	20	(	(	PUNCT
ajst-29292	40	21	1	1	NUM
ajst-29292	40	22	)	)	PUNCT
ajst-29292	40	23	where	where	SCONJ
ajst-29292	40	24	:	:	PUNCT
ajst-29292	40	25	𝑥	𝑥	PRON
ajst-29292	40	26	is	be	AUX
ajst-29292	40	27	the	the	DET
ajst-29292	40	28	i	i	PROPN
ajst-29292	40	29	-	-	PUNCT
ajst-29292	40	30	th	th	X
ajst-29292	40	31	smallest	small	ADJ
ajst-29292	40	32	value	value	NOUN
ajst-29292	40	33	in	in	ADP
ajst-29292	40	34	the	the	DET
ajst-29292	40	35	sample	sample	NOUN
ajst-29292	40	36	data	datum	NOUN
ajst-29292	40	37	.	.	PUNCT
ajst-29292	41	1	�	�	NOUN
ajst-29292	41	2	̅	̅	NOUN
ajst-29292	41	3	�	�	NOUN
ajst-29292	41	4	is	be	AUX
ajst-29292	41	5	the	the	DET
ajst-29292	41	6	mean	mean	NOUN
ajst-29292	41	7	of	of	ADP
ajst-29292	41	8	the	the	DET
ajst-29292	41	9	sample	sample	NOUN
ajst-29292	41	10	data	datum	NOUN
ajst-29292	41	11	.	.	PUNCT
ajst-29292	42	1	𝑎	𝑎	PRON
ajst-29292	42	2	is	be	AUX
ajst-29292	42	3	the	the	DET
ajst-29292	42	4	coefficient	coefficient	NOUN
ajst-29292	42	5	associated	associate	VERB
ajst-29292	42	6	with	with	ADP
ajst-29292	42	7	the	the	DET
ajst-29292	42	8	theoretical	theoretical	ADJ
ajst-29292	42	9	rank	rank	NOUN
ajst-29292	42	10	under	under	ADP
ajst-29292	42	11	normal	normal	ADJ
ajst-29292	42	12	distribution	distribution	NOUN
ajst-29292	42	13	.	.	PUNCT
ajst-29292	43	1	all	all	DET
ajst-29292	43	2	p	p	NOUN
ajst-29292	43	3	-	-	PUNCT
ajst-29292	43	4	values	value	NOUN
ajst-29292	43	5	are	be	AUX
ajst-29292	43	6	very	very	ADV
ajst-29292	43	7	small	small	ADJ
ajst-29292	43	8	,	,	PUNCT
ajst-29292	43	9	less	less	ADJ
ajst-29292	43	10	than	than	ADP
ajst-29292	43	11	0.05	0.05	NUM
ajst-29292	43	12	,	,	PUNCT
ajst-29292	43	13	presenting	present	VERB
ajst-29292	43	14	significance	significance	NOUN
ajst-29292	43	15	and	and	CCONJ
ajst-29292	43	16	therefore	therefore	ADV
ajst-29292	43	17	all	all	DET
ajst-29292	43	18	data	datum	NOUN
ajst-29292	43	19	do	do	AUX
ajst-29292	43	20	not	not	PART
ajst-29292	43	21	satisfy	satisfy	VERB
ajst-29292	43	22	normal	normal	ADJ
ajst-29292	43	23	distribution	distribution	NOUN
ajst-29292	43	24	.	.	PUNCT
ajst-29292	44	1	2.3	2.3	NUM
ajst-29292	44	2	.	.	PUNCT
ajst-29292	44	3	test	test	NOUN
ajst-29292	44	4	of	of	ADP
ajst-29292	44	5	variance	variance	NOUN
ajst-29292	44	6	:	:	PUNCT
ajst-29292	44	7	wilcoxon	wilcoxon	PROPN
ajst-29292	44	8	rank	rank	PROPN
ajst-29292	44	9	sum	sum	PROPN
ajst-29292	44	10	test	test	NOUN
ajst-29292	44	11	the	the	DET
ajst-29292	44	12	wilcoxon	wilcoxon	ADJ
ajst-29292	44	13	rank	rank	PROPN
ajst-29292	44	14	sum	sum	PROPN
ajst-29292	44	15	test	test	NOUN
ajst-29292	44	16	,	,	PUNCT
ajst-29292	44	17	also	also	ADV
ajst-29292	44	18	known	know	VERB
ajst-29292	44	19	as	as	ADP
ajst-29292	44	20	the	the	DET
ajst-29292	44	21	mannwhitney	mannwhitney	NOUN
ajst-29292	44	22	u	u	PROPN
ajst-29292	44	23	test	test	NOUN
ajst-29292	44	24	,	,	PUNCT
ajst-29292	44	25	is	be	AUX
ajst-29292	44	26	a	a	DET
ajst-29292	44	27	nonparametric	nonparametric	ADJ
ajst-29292	44	28	statistical	statistical	ADJ
ajst-29292	44	29	test	test	NOUN
ajst-29292	44	30	used	use	VERB
ajst-29292	44	31	to	to	PART
ajst-29292	44	32	compare	compare	VERB
ajst-29292	44	33	the	the	DET
ajst-29292	44	34	distributions	distribution	NOUN
ajst-29292	44	35	of	of	ADP
ajst-29292	44	36	two	two	NUM
ajst-29292	44	37	independent	independent	ADJ
ajst-29292	44	38	samples	sample	NOUN
ajst-29292	44	39	for	for	ADP
ajst-29292	44	40	significant	significant	ADJ
ajst-29292	44	41	differences	difference	NOUN
ajst-29292	44	42	.	.	PUNCT
ajst-29292	45	1	this	this	DET
ajst-29292	45	2	test	test	NOUN
ajst-29292	45	3	is	be	AUX
ajst-29292	45	4	particularly	particularly	ADV
ajst-29292	45	5	useful	useful	ADJ
ajst-29292	45	6	in	in	ADP
ajst-29292	45	7	situations	situation	NOUN
ajst-29292	45	8	when	when	SCONJ
ajst-29292	45	9	the	the	DET
ajst-29292	45	10	data	datum	NOUN
ajst-29292	45	11	do	do	AUX
ajst-29292	45	12	not	not	PART
ajst-29292	45	13	meet	meet	VERB
ajst-29292	45	14	the	the	DET
ajst-29292	45	15	assumption	assumption	NOUN
ajst-29292	45	16	of	of	ADP
ajst-29292	45	17	normal	normal	ADJ
ajst-29292	45	18	distribution	distribution	NOUN
ajst-29292	45	19	.	.	PUNCT
ajst-29292	46	1	it	it	PRON
ajst-29292	46	2	can	can	AUX
ajst-29292	46	3	be	be	AUX
ajst-29292	46	4	used	use	VERB
ajst-29292	46	5	to	to	PART
ajst-29292	46	6	compare	compare	VERB
ajst-29292	46	7	the	the	DET
ajst-29292	46	8	difference	difference	NOUN
ajst-29292	46	9	in	in	ADP
ajst-29292	46	10	medians	median	NOUN
ajst-29292	46	11	between	between	ADP
ajst-29292	46	12	two	two	NUM
ajst-29292	46	13	groups	group	NOUN
ajst-29292	46	14	of	of	ADP
ajst-29292	46	15	samples	sample	NOUN
ajst-29292	46	16	without	without	ADP
ajst-29292	46	17	assuming	assume	VERB
ajst-29292	46	18	a	a	DET
ajst-29292	46	19	specific	specific	ADJ
ajst-29292	46	20	distributional	distributional	ADJ
ajst-29292	46	21	pattern	pattern	NOUN
ajst-29292	46	22	for	for	ADP
ajst-29292	46	23	the	the	DET
ajst-29292	46	24	data	datum	NOUN
ajst-29292	46	25	.	.	PUNCT
ajst-29292	47	1	steps	step	NOUN
ajst-29292	47	2	in	in	ADP
ajst-29292	47	3	wilcoxon	wilcoxon	PROPN
ajst-29292	47	4	's	's	PART
ajst-29292	47	5	rank	rank	NOUN
ajst-29292	47	6	sum	sum	NOUN
ajst-29292	47	7	test	test	NOUN
ajst-29292	47	8	:	:	PUNCT
ajst-29292	48	1	step1	step1	NOUN
ajst-29292	48	2	:	:	PUNCT
ajst-29292	48	3	sorting	sorting	NOUN
ajst-29292	48	4	and	and	CCONJ
ajst-29292	48	5	rank	rank	NOUN
ajst-29292	48	6	assignment	assignment	NOUN
ajst-29292	48	7	:	:	PUNCT
ajst-29292	48	8	the	the	DET
ajst-29292	48	9	two	two	NUM
ajst-29292	48	10	sets	set	NOUN
ajst-29292	48	11	of	of	ADP
ajst-29292	48	12	samples	sample	NOUN
ajst-29292	48	13	are	be	AUX
ajst-29292	48	14	combined	combine	VERB
ajst-29292	48	15	and	and	CCONJ
ajst-29292	48	16	all	all	DET
ajst-29292	48	17	samples	sample	NOUN
ajst-29292	48	18	are	be	AUX
ajst-29292	48	19	sorted	sort	VERB
ajst-29292	48	20	in	in	ADP
ajst-29292	48	21	order	order	NOUN
ajst-29292	48	22	from	from	ADP
ajst-29292	48	23	smallest	small	ADJ
ajst-29292	48	24	to	to	AUX
ajst-29292	48	25	largest	large	ADJ
ajst-29292	48	26	.	.	PUNCT
ajst-29292	49	1	assign	assign	VERB
ajst-29292	49	2	a	a	DET
ajst-29292	49	3	rank	rank	NOUN
ajst-29292	49	4	value	value	NOUN
ajst-29292	49	5	to	to	ADP
ajst-29292	49	6	each	each	DET
ajst-29292	49	7	sample	sample	NOUN
ajst-29292	49	8	.	.	PUNCT
ajst-29292	50	1	step2	step2	PROPN
ajst-29292	50	2	:	:	PUNCT
ajst-29292	50	3	calculate	calculate	VERB
ajst-29292	50	4	the	the	DET
ajst-29292	50	5	rank	rank	NOUN
ajst-29292	50	6	sum	sum	NOUN
ajst-29292	50	7	for	for	ADP
ajst-29292	50	8	each	each	DET
ajst-29292	50	9	group	group	NOUN
ajst-29292	50	10	of	of	ADP
ajst-29292	50	11	samples	sample	NOUN
ajst-29292	50	12	.	.	PUNCT
ajst-29292	51	1	step3	step3	PROPN
ajst-29292	51	2	:	:	PUNCT
ajst-29292	51	3	calculate	calculate	VERB
ajst-29292	51	4	the	the	DET
ajst-29292	51	5	test	test	NOUN
ajst-29292	51	6	statistic	statistic	NOUN
ajst-29292	51	7	.	.	PUNCT
ajst-29292	52	1	calculate	calculate	VERB
ajst-29292	52	2	the	the	DET
ajst-29292	52	3	test	test	NOUN
ajst-29292	52	4	statistic	statistic	NOUN
ajst-29292	52	5	:	:	PUNCT
ajst-29292	52	6	87	87	NUM
ajst-29292	52	7	𝑈	𝑈	PROPN
ajst-29292	52	8	𝑅	𝑅	PROPN
ajst-29292	52	9	(	(	PUNCT
ajst-29292	52	10	2	2	NUM
ajst-29292	52	11	)	)	PUNCT
ajst-29292	52	12	𝑈	𝑈	PROPN
ajst-29292	52	13	𝑅	𝑅	PROPN
ajst-29292	52	14	(	(	PUNCT
ajst-29292	52	15	3	3	NUM
ajst-29292	52	16	)	)	PUNCT
ajst-29292	52	17	𝑈	𝑈	PROPN
ajst-29292	52	18	𝑚𝑖𝑛	𝑚𝑖𝑛	NOUN
ajst-29292	53	1	𝑈	𝑈	PROPN
ajst-29292	53	2	,	,	PUNCT
ajst-29292	53	3	𝑈	𝑈	PROPN
ajst-29292	53	4	(	(	PUNCT
ajst-29292	53	5	4	4	NUM
ajst-29292	53	6	)	)	PUNCT
ajst-29292	53	7	where	where	SCONJ
ajst-29292	53	8	ua	ua	PROPN
ajst-29292	53	9	,	,	PUNCT
ajst-29292	53	10	ub	ub	PROPN
ajst-29292	53	11	are	be	AUX
ajst-29292	53	12	the	the	DET
ajst-29292	53	13	u	u	NOUN
ajst-29292	53	14	-	-	NOUN
ajst-29292	53	15	statistics	statistic	NOUN
ajst-29292	53	16	of	of	ADP
ajst-29292	53	17	sample	sample	NOUN
ajst-29292	53	18	a	a	PRON
ajst-29292	53	19	and	and	CCONJ
ajst-29292	53	20	sample	sample	NOUN
ajst-29292	53	21	b	b	PROPN
ajst-29292	53	22	respectively	respectively	ADV
ajst-29292	53	23	.	.	PUNCT
ajst-29292	54	1	ra	ra	PROPN
ajst-29292	54	2	,	,	PUNCT
ajst-29292	54	3	rb	rb	NOUN
ajst-29292	54	4	are	be	AUX
ajst-29292	54	5	the	the	DET
ajst-29292	54	6	rank	rank	NOUN
ajst-29292	54	7	sums	sum	NOUN
ajst-29292	54	8	of	of	ADP
ajst-29292	54	9	sample	sample	NOUN
ajst-29292	54	10	a	a	PRON
ajst-29292	54	11	and	and	CCONJ
ajst-29292	54	12	sample	sample	NOUN
ajst-29292	54	13	b	b	NOUN
ajst-29292	54	14	respectively	respectively	ADV
ajst-29292	54	15	.	.	PUNCT
ajst-29292	55	1	na	na	ADP
ajst-29292	55	2	,	,	PUNCT
ajst-29292	55	3	nb	nb	X
ajst-29292	55	4	are	be	AUX
ajst-29292	55	5	the	the	DET
ajst-29292	55	6	sample	sample	NOUN
ajst-29292	55	7	sizes	size	NOUN
ajst-29292	55	8	of	of	ADP
ajst-29292	55	9	sample	sample	NOUN
ajst-29292	55	10	a	a	PRON
ajst-29292	55	11	and	and	CCONJ
ajst-29292	55	12	sample	sample	NOUN
ajst-29292	55	13	b	b	NOUN
ajst-29292	55	14	respectively	respectively	ADV
ajst-29292	55	15	.	.	PUNCT
ajst-29292	56	1	in	in	ADP
ajst-29292	56	2	order	order	NOUN
ajst-29292	56	3	to	to	PART
ajst-29292	56	4	use	use	VERB
ajst-29292	56	5	the	the	DET
ajst-29292	56	6	paired	pair	VERB
ajst-29292	56	7	-	-	PUNCT
ajst-29292	56	8	sample	sample	NOUN
ajst-29292	56	9	wilcoxon	wilcoxon	PROPN
ajst-29292	56	10	signed	sign	VERB
ajst-29292	56	11	rank	rank	NOUN
ajst-29292	56	12	test	test	NOUN
ajst-29292	56	13	for	for	ADP
ajst-29292	56	14	both	both	DET
ajst-29292	56	15	sets	set	NOUN
ajst-29292	56	16	of	of	ADP
ajst-29292	56	17	data	datum	NOUN
ajst-29292	56	18	,	,	PUNCT
ajst-29292	56	19	the	the	DET
ajst-29292	56	20	data	datum	NOUN
ajst-29292	56	21	were	be	AUX
ajst-29292	56	22	first	first	ADV
ajst-29292	56	23	screened	screen	VERB
ajst-29292	56	24	for	for	ADP
ajst-29292	56	25	the	the	DET
ajst-29292	56	26	same	same	ADJ
ajst-29292	56	27	number	number	NOUN
ajst-29292	56	28	of	of	ADP
ajst-29292	56	29	subjects	subject	NOUN
ajst-29292	56	30	to	to	PART
ajst-29292	56	31	ensure	ensure	VERB
ajst-29292	56	32	that	that	SCONJ
ajst-29292	56	33	the	the	DET
ajst-29292	56	34	sample	sample	NOUN
ajst-29292	56	35	sizes	size	NOUN
ajst-29292	56	36	were	be	AUX
ajst-29292	56	37	the	the	DET
ajst-29292	56	38	same	same	ADJ
ajst-29292	56	39	,	,	PUNCT
ajst-29292	56	40	even	even	ADV
ajst-29292	56	41	though	though	SCONJ
ajst-29292	56	42	the	the	DET
ajst-29292	56	43	sample	sample	NOUN
ajst-29292	56	44	sizes	size	NOUN
ajst-29292	56	45	for	for	ADP
ajst-29292	56	46	both	both	PRON
ajst-29292	56	47	drug	drug	NOUN
ajst-29292	56	48	b	b	PROPN
ajst-29292	56	49	and	and	CCONJ
ajst-29292	56	50	drug	drug	NOUN
ajst-29292	56	51	r	r	NOUN
ajst-29292	56	52	data	datum	NOUN
ajst-29292	56	53	were	be	AUX
ajst-29292	56	54	475	475	NUM
ajst-29292	56	55	.	.	PUNCT
ajst-29292	57	1	from	from	ADP
ajst-29292	57	2	the	the	DET
ajst-29292	57	3	extracted	extract	VERB
ajst-29292	57	4	data	datum	NOUN
ajst-29292	57	5	,	,	PUNCT
ajst-29292	57	6	it	it	PRON
ajst-29292	57	7	can	can	AUX
ajst-29292	57	8	be	be	AUX
ajst-29292	57	9	found	find	VERB
ajst-29292	57	10	that	that	SCONJ
ajst-29292	57	11	most	most	ADJ
ajst-29292	57	12	of	of	ADP
ajst-29292	57	13	the	the	DET
ajst-29292	57	14	vital	vital	ADJ
ajst-29292	57	15	signs	sign	NOUN
ajst-29292	57	16	that	that	PRON
ajst-29292	57	17	would	would	AUX
ajst-29292	57	18	show	show	VERB
ajst-29292	57	19	significant	significant	ADJ
ajst-29292	57	20	differences	difference	NOUN
ajst-29292	57	21	are	be	AUX
ajst-29292	57	22	mainly	mainly	ADV
ajst-29292	57	23	concentrated	concentrate	VERB
ajst-29292	57	24	in	in	ADP
ajst-29292	57	25	1min	1min	NUM
ajst-29292	57	26	to	to	ADP
ajst-29292	57	27	3min	3min	NUM
ajst-29292	57	28	after	after	ADP
ajst-29292	57	29	induction	induction	NOUN
ajst-29292	57	30	.	.	PUNCT
ajst-29292	58	1	the	the	DET
ajst-29292	58	2	basic	basic	ADJ
ajst-29292	58	3	information	information	NOUN
ajst-29292	58	4	of	of	ADP
ajst-29292	58	5	the	the	DET
ajst-29292	58	6	subjects	subject	NOUN
ajst-29292	58	7	was	be	AUX
ajst-29292	58	8	screened	screen	VERB
ajst-29292	58	9	from	from	ADP
ajst-29292	58	10	the	the	DET
ajst-29292	58	11	basic	basic	ADJ
ajst-29292	58	12	information	information	NOUN
ajst-29292	58	13	of	of	ADP
ajst-29292	58	14	the	the	DET
ajst-29292	58	15	subjects	subject	NOUN
ajst-29292	58	16	with	with	ADP
ajst-29292	58	17	each	each	PRON
ajst-29292	58	18	of	of	ADP
ajst-29292	58	19	the	the	DET
ajst-29292	58	20	475	475	NUM
ajst-29292	58	21	subjects	subject	NOUN
ajst-29292	58	22	sampled	sample	VERB
ajst-29292	58	23	above	above	ADV
ajst-29292	58	24	,	,	PUNCT
ajst-29292	58	25	and	and	CCONJ
ajst-29292	58	26	the	the	DET
ajst-29292	58	27	basic	basic	ADJ
ajst-29292	58	28	information	information	NOUN
ajst-29292	58	29	of	of	ADP
ajst-29292	58	30	the	the	DET
ajst-29292	58	31	subjects	subject	NOUN
ajst-29292	58	32	was	be	AUX
ajst-29292	58	33	subjected	subject	VERB
ajst-29292	58	34	to	to	ADP
ajst-29292	58	35	descriptive	descriptive	ADJ
ajst-29292	58	36	statistics	statistic	NOUN
ajst-29292	58	37	and	and	CCONJ
ajst-29292	58	38	plotted	plot	VERB
ajst-29292	58	39	as	as	ADP
ajst-29292	58	40	shown	show	VERB
ajst-29292	58	41	in	in	ADP
ajst-29292	58	42	fig.2	fig.2	PROPN
ajst-29292	58	43	.	.	PUNCT
ajst-29292	59	1	figure	figure	NOUN
ajst-29292	59	2	2	2	NUM
ajst-29292	59	3	.	.	PUNCT
ajst-29292	59	4	basic	basic	ADJ
ajst-29292	59	5	information	information	NOUN
ajst-29292	59	6	on	on	ADP
ajst-29292	59	7	all	all	DET
ajst-29292	59	8	subjects	subject	NOUN
ajst-29292	59	9	from	from	ADP
ajst-29292	59	10	the	the	DET
ajst-29292	59	11	above	above	ADJ
ajst-29292	59	12	basic	basic	ADJ
ajst-29292	59	13	information	information	NOUN
ajst-29292	59	14	of	of	ADP
ajst-29292	59	15	all	all	DET
ajst-29292	59	16	subjects	subject	NOUN
ajst-29292	59	17	,	,	PUNCT
ajst-29292	59	18	it	it	PRON
ajst-29292	59	19	can	can	AUX
ajst-29292	59	20	be	be	AUX
ajst-29292	59	21	seen	see	VERB
ajst-29292	59	22	that	that	SCONJ
ajst-29292	59	23	the	the	DET
ajst-29292	59	24	distribution	distribution	NOUN
ajst-29292	59	25	of	of	ADP
ajst-29292	59	26	information	information	NOUN
ajst-29292	59	27	of	of	ADP
ajst-29292	59	28	all	all	DET
ajst-29292	59	29	subjects	subject	NOUN
ajst-29292	59	30	is	be	AUX
ajst-29292	59	31	balanced	balance	VERB
ajst-29292	59	32	and	and	CCONJ
ajst-29292	59	33	basically	basically	ADV
ajst-29292	59	34	meets	meet	VERB
ajst-29292	59	35	the	the	DET
ajst-29292	59	36	normal	normal	ADJ
ajst-29292	59	37	distribution	distribution	NOUN
ajst-29292	59	38	,	,	PUNCT
ajst-29292	59	39	the	the	DET
ajst-29292	59	40	total	total	ADJ
ajst-29292	59	41	frequency	frequency	NOUN
ajst-29292	59	42	of	of	ADP
ajst-29292	59	43	age	age	NOUN
ajst-29292	59	44	and	and	CCONJ
ajst-29292	59	45	gender	gender	NOUN
ajst-29292	59	46	does	do	AUX
ajst-29292	59	47	not	not	PART
ajst-29292	59	48	differ	differ	VERB
ajst-29292	59	49	much	much	ADJ
ajst-29292	59	50	,	,	PUNCT
ajst-29292	59	51	and	and	CCONJ
ajst-29292	59	52	the	the	DET
ajst-29292	59	53	relationship	relationship	NOUN
ajst-29292	59	54	between	between	ADP
ajst-29292	59	55	gender	gender	NOUN
ajst-29292	59	56	age	age	NOUN
ajst-29292	59	57	and	and	CCONJ
ajst-29292	59	58	weight	weight	NOUN
ajst-29292	59	59	is	be	AUX
ajst-29292	59	60	more	more	ADV
ajst-29292	59	61	uniform	uniform	ADJ
ajst-29292	59	62	in	in	ADP
ajst-29292	59	63	line	line	NOUN
ajst-29292	59	64	with	with	ADP
ajst-29292	59	65	the	the	DET
ajst-29292	59	66	reality	reality	NOUN
ajst-29292	59	67	.	.	PUNCT
ajst-29292	60	1	further	further	ADJ
ajst-29292	60	2	comparison	comparison	NOUN
ajst-29292	60	3	of	of	ADP
ajst-29292	60	4	the	the	DET
ajst-29292	60	5	distribution	distribution	NOUN
ajst-29292	60	6	of	of	ADP
ajst-29292	60	7	data	datum	NOUN
ajst-29292	60	8	between	between	ADP
ajst-29292	60	9	the	the	DET
ajst-29292	60	10	two	two	NUM
ajst-29292	60	11	groups	group	NOUN
ajst-29292	60	12	,	,	PUNCT
ajst-29292	60	13	compare	compare	VERB
ajst-29292	60	14	the	the	DET
ajst-29292	60	15	data	datum	NOUN
ajst-29292	60	16	between	between	ADP
ajst-29292	60	17	the	the	DET
ajst-29292	60	18	two	two	NUM
ajst-29292	60	19	groups	group	NOUN
ajst-29292	60	20	whether	whether	SCONJ
ajst-29292	60	21	there	there	PRON
ajst-29292	60	22	are	be	VERB
ajst-29292	60	23	other	other	ADJ
ajst-29292	60	24	factors	factor	NOUN
ajst-29292	60	25	that	that	PRON
ajst-29292	60	26	may	may	AUX
ajst-29292	60	27	lead	lead	VERB
ajst-29292	60	28	to	to	ADP
ajst-29292	60	29	significant	significant	ADJ
ajst-29292	60	30	differences	difference	NOUN
ajst-29292	60	31	in	in	ADP
ajst-29292	60	32	vital	vital	ADJ
ajst-29292	60	33	signs	sign	NOUN
ajst-29292	60	34	found	find	VERB
ajst-29292	60	35	that	that	SCONJ
ajst-29292	60	36	the	the	DET
ajst-29292	60	37	age	age	NOUN
ajst-29292	60	38	distribution	distribution	NOUN
ajst-29292	60	39	of	of	ADP
ajst-29292	60	40	the	the	DET
ajst-29292	60	41	two	two	NUM
ajst-29292	60	42	groups	group	NOUN
ajst-29292	60	43	of	of	ADP
ajst-29292	60	44	subjects	subject	NOUN
ajst-29292	60	45	is	be	AUX
ajst-29292	60	46	more	more	ADV
ajst-29292	60	47	or	or	CCONJ
ajst-29292	60	48	less	less	ADV
ajst-29292	60	49	the	the	DET
ajst-29292	60	50	same	same	ADJ
ajst-29292	60	51	,	,	PUNCT
ajst-29292	60	52	and	and	CCONJ
ajst-29292	60	53	the	the	DET
ajst-29292	60	54	two	two	NUM
ajst-29292	60	55	groups	group	NOUN
ajst-29292	60	56	of	of	ADP
ajst-29292	60	57	data	datum	NOUN
ajst-29292	60	58	subjects	subject	NOUN
ajst-29292	60	59	appear	appear	VERB
ajst-29292	60	60	to	to	PART
ajst-29292	60	61	have	have	VERB
ajst-29292	60	62	a	a	DET
ajst-29292	60	63	history	history	NOUN
ajst-29292	60	64	of	of	ADP
ajst-29292	60	65	the	the	DET
ajst-29292	60	66	situation	situation	NOUN
ajst-29292	60	67	is	be	AUX
ajst-29292	60	68	more	more	ADV
ajst-29292	60	69	or	or	CCONJ
ajst-29292	60	70	less	less	ADV
ajst-29292	60	71	the	the	DET
ajst-29292	60	72	same	same	ADJ
ajst-29292	60	73	.	.	PUNCT
ajst-29292	61	1	therefore	therefore	ADV
ajst-29292	61	2	,	,	PUNCT
ajst-29292	61	3	it	it	PRON
ajst-29292	61	4	was	be	AUX
ajst-29292	61	5	concluded	conclude	VERB
ajst-29292	61	6	that	that	SCONJ
ajst-29292	61	7	both	both	DET
ajst-29292	61	8	groups	group	NOUN
ajst-29292	61	9	of	of	ADP
ajst-29292	61	10	subjects	subject	NOUN
ajst-29292	61	11	had	have	VERB
ajst-29292	61	12	the	the	DET
ajst-29292	61	13	same	same	ADJ
ajst-29292	61	14	basic	basic	ADJ
ajst-29292	61	15	profile	profile	NOUN
ajst-29292	61	16	.	.	PUNCT
ajst-29292	62	1	all	all	DET
ajst-29292	62	2	the	the	DET
ajst-29292	62	3	variables	variable	NOUN
ajst-29292	62	4	were	be	AUX
ajst-29292	62	5	considered	consider	VERB
ajst-29292	62	6	to	to	PART
ajst-29292	62	7	be	be	AUX
ajst-29292	62	8	controlled	control	VERB
ajst-29292	62	9	in	in	ADP
ajst-29292	62	10	this	this	DET
ajst-29292	62	11	experiment	experiment	NOUN
ajst-29292	62	12	and	and	CCONJ
ajst-29292	62	13	the	the	DET
ajst-29292	62	14	reason	reason	NOUN
ajst-29292	62	15	for	for	ADP
ajst-29292	62	16	the	the	DET
ajst-29292	62	17	difference	difference	NOUN
ajst-29292	62	18	in	in	ADP
ajst-29292	62	19	vital	vital	ADJ
ajst-29292	62	20	signs	sign	NOUN
ajst-29292	62	21	indicators	indicator	NOUN
ajst-29292	62	22	was	be	AUX
ajst-29292	62	23	the	the	DET
ajst-29292	62	24	type	type	NOUN
ajst-29292	62	25	of	of	ADP
ajst-29292	62	26	sedative	sedative	ADJ
ajst-29292	62	27	drug	drug	NOUN
ajst-29292	62	28	.	.	PUNCT
ajst-29292	63	1	3	3	X
ajst-29292	63	2	.	.	X
ajst-29292	63	3	prediction	prediction	NOUN
ajst-29292	63	4	based	base	VERB
ajst-29292	63	5	on	on	ADP
ajst-29292	63	6	multiple	multiple	ADJ
ajst-29292	63	7	machine	machine	NOUN
ajst-29292	63	8	learning	learning	NOUN
ajst-29292	63	9	models	model	NOUN
ajst-29292	63	10	3.1	3.1	NUM
ajst-29292	63	11	.	.	PUNCT
ajst-29292	64	1	selection	selection	NOUN
ajst-29292	64	2	of	of	ADP
ajst-29292	64	3	evaluation	evaluation	NOUN
ajst-29292	64	4	indicators	indicator	NOUN
ajst-29292	64	5	mean	mean	VERB
ajst-29292	64	6	square	square	ADJ
ajst-29292	64	7	error	error	NOUN
ajst-29292	64	8	(	(	PUNCT
ajst-29292	64	9	mse	mse	NOUN
ajst-29292	64	10	)	)	PUNCT
ajst-29292	64	11	,	,	PUNCT
ajst-29292	64	12	root	root	NOUN
ajst-29292	64	13	mean	mean	VERB
ajst-29292	64	14	square	square	ADJ
ajst-29292	64	15	error	error	NOUN
ajst-29292	64	16	(	(	PUNCT
ajst-29292	64	17	rmse	rmse	NOUN
ajst-29292	64	18	)	)	PUNCT
ajst-29292	64	19	,	,	PUNCT
ajst-29292	64	20	mean	mean	VERB
ajst-29292	64	21	absolute	absolute	ADJ
ajst-29292	64	22	error	error	NOUN
ajst-29292	64	23	(	(	PUNCT
ajst-29292	64	24	mae	mae	PROPN
ajst-29292	64	25	)	)	PUNCT
ajst-29292	64	26	,	,	PUNCT
ajst-29292	64	27	mean	mean	VERB
ajst-29292	64	28	absolute	absolute	ADJ
ajst-29292	64	29	percentage	percentage	NOUN
ajst-29292	64	30	error	error	NOUN
ajst-29292	64	31	(	(	PUNCT
ajst-29292	64	32	mape	mape	NOUN
ajst-29292	64	33	)	)	PUNCT
ajst-29292	64	34	,	,	PUNCT
ajst-29292	64	35	and	and	CCONJ
ajst-29292	64	36	coefficient	coefficient	NOUN
ajst-29292	64	37	of	of	ADP
ajst-29292	64	38	determination	determination	NOUN
ajst-29292	64	39	(	(	PUNCT
ajst-29292	64	40	r2	r2	PROPN
ajst-29292	64	41	)	)	PUNCT
ajst-29292	64	42	are	be	AUX
ajst-29292	64	43	introduced	introduce	VERB
ajst-29292	64	44	as	as	ADP
ajst-29292	64	45	performance	performance	NOUN
ajst-29292	64	46	and	and	CCONJ
ajst-29292	64	47	evaluation	evaluation	NOUN
ajst-29292	64	48	indicators	indicator	NOUN
ajst-29292	64	49	.	.	PUNCT
ajst-29292	65	1	the	the	DET
ajst-29292	65	2	mean	mean	ADJ
ajst-29292	65	3	square	square	ADJ
ajst-29292	65	4	error	error	NOUN
ajst-29292	65	5	(	(	PUNCT
ajst-29292	65	6	mse	mse	NOUN
ajst-29292	65	7	)	)	PUNCT
ajst-29292	65	8	is	be	AUX
ajst-29292	65	9	calculated	calculate	VERB
ajst-29292	65	10	as	as	ADP
ajst-29292	65	11	:	:	PUNCT
ajst-29292	65	12	𝑀𝑆𝐸	𝑀𝑆𝐸	PROPN
ajst-29292	65	13	1	1	NUM
ajst-29292	65	14	𝑛	𝑛	PRON
ajst-29292	65	15	  	  	SPACE
ajst-29292	65	16	𝑦	𝑦	PRON
ajst-29292	65	17	𝑦	𝑦	X
ajst-29292	65	18	(	(	PUNCT
ajst-29292	65	19	5	5	NUM
ajst-29292	65	20	)	)	PUNCT
ajst-29292	65	21	𝑅𝑀𝑆𝐸	𝑅𝑀𝑆𝐸	NOUN
ajst-29292	65	22	√𝑀𝑆𝐸	√𝑀𝑆𝐸	NOUN
ajst-29292	65	23	1	1	NUM
ajst-29292	65	24	𝑛	𝑛	PRON
ajst-29292	65	25	  	  	SPACE
ajst-29292	65	26	𝑦	𝑦	PRON
ajst-29292	65	27	𝑦	𝑦	X
ajst-29292	65	28	(	(	PUNCT
ajst-29292	65	29	6	6	NUM
ajst-29292	65	30	)	)	PUNCT
ajst-29292	65	31	the	the	DET
ajst-29292	65	32	mean	mean	ADJ
ajst-29292	65	33	absolute	absolute	ADJ
ajst-29292	65	34	error	error	NOUN
ajst-29292	65	35	(	(	PUNCT
ajst-29292	65	36	mae	mae	PROPN
ajst-29292	65	37	)	)	PUNCT
ajst-29292	65	38	is	be	AUX
ajst-29292	65	39	calculated	calculate	VERB
ajst-29292	65	40	as	as	ADP
ajst-29292	65	41	:	:	PUNCT
ajst-29292	65	42	𝑀𝐴𝐸	𝑀𝐴𝐸	PROPN
ajst-29292	65	43	1	1	NUM
ajst-29292	65	44	𝑛	𝑛	PROPN
ajst-29292	65	45	  	  	SPACE
ajst-29292	65	46	|𝑦	|𝑦	PROPN
ajst-29292	65	47	𝑦	𝑦	PROPN
ajst-29292	65	48	|	|	NOUN
ajst-29292	65	49	(	(	PUNCT
ajst-29292	65	50	7	7	X
ajst-29292	65	51	)	)	PUNCT
ajst-29292	65	52	the	the	DET
ajst-29292	65	53	mean	mean	ADJ
ajst-29292	65	54	absolute	absolute	ADJ
ajst-29292	65	55	percentage	percentage	NOUN
ajst-29292	65	56	error	error	NOUN
ajst-29292	65	57	(	(	PUNCT
ajst-29292	65	58	mape	mape	NOUN
ajst-29292	65	59	)	)	PUNCT
ajst-29292	65	60	is	be	AUX
ajst-29292	65	61	calculated	calculate	VERB
ajst-29292	65	62	in	in	ADP
ajst-29292	65	63	the	the	DET
ajst-29292	65	64	format	format	NOUN
ajst-29292	65	65	:	:	PUNCT
ajst-29292	66	1	𝑀𝐴𝑃𝐸	𝑀𝐴𝑃𝐸	ADJ
ajst-29292	66	2	100	100	NUM
ajst-29292	66	3	%	%	NOUN
ajst-29292	66	4	𝑛	𝑛	PRON
ajst-29292	66	5	  	  	SPACE
ajst-29292	66	6	𝑦	𝑦	PRON
ajst-29292	66	7	𝑦	𝑦	NUM
ajst-29292	66	8	𝑦	𝑦	X
ajst-29292	66	9	(	(	PUNCT
ajst-29292	66	10	8)	8)	NUM
ajst-29292	66	11	in	in	ADP
ajst-29292	66	12	the	the	DET
ajst-29292	66	13	above	above	ADJ
ajst-29292	66	14	4	4	NUM
ajst-29292	66	15	equations	equation	NOUN
ajst-29292	66	16	,	,	PUNCT
ajst-29292	66	17	𝑦	𝑦	NOUN
ajst-29292	66	18	is	be	AUX
ajst-29292	66	19	the	the	DET
ajst-29292	66	20	ith	ith	PROPN
ajst-29292	66	21	actual	actual	ADJ
ajst-29292	66	22	value	value	NOUN
ajst-29292	66	23	and	and	CCONJ
ajst-29292	66	24	𝑦	𝑦	NOUN
ajst-29292	66	25	is	be	AUX
ajst-29292	66	26	the	the	DET
ajst-29292	66	27	ith	ith	PROPN
ajst-29292	66	28	predicted	predict	VERB
ajst-29292	66	29	value	value	NOUN
ajst-29292	66	30	.	.	PUNCT
ajst-29292	67	1	the	the	DET
ajst-29292	67	2	coefficient	coefficient	NOUN
ajst-29292	67	3	of	of	ADP
ajst-29292	67	4	determination	determination	NOUN
ajst-29292	67	5	(	(	PUNCT
ajst-29292	67	6	r2	r2	PROPN
ajst-29292	67	7	)	)	PUNCT
ajst-29292	67	8	is	be	AUX
ajst-29292	67	9	calculated	calculate	VERB
ajst-29292	67	10	as	as	ADP
ajst-29292	67	11	:	:	PUNCT
ajst-29292	67	12	𝑅	𝑅	PROPN
ajst-29292	67	13	1	1	NUM
ajst-29292	67	14	∑	∑	NOUN
ajst-29292	67	15	  	  	SPACE
ajst-29292	67	16	∑	∑	ADP
ajst-29292	67	17	  	  	SPACE
ajst-29292	67	18	(	(	PUNCT
ajst-29292	67	19	9	9	NUM
ajst-29292	67	20	)	)	PUNCT
ajst-29292	67	21	where	where	SCONJ
ajst-29292	67	22	,	,	PUNCT
ajst-29292	67	23	𝑦	𝑦	NOUN
ajst-29292	67	24	is	be	AUX
ajst-29292	67	25	the	the	DET
ajst-29292	67	26	mean	mean	NOUN
ajst-29292	67	27	of	of	ADP
ajst-29292	67	28	the	the	DET
ajst-29292	67	29	actual	actual	ADJ
ajst-29292	67	30	values	value	NOUN
ajst-29292	67	31	.	.	PUNCT
ajst-29292	68	1	mse	mse	PROPN
ajst-29292	68	2	is	be	AUX
ajst-29292	68	3	used	use	VERB
ajst-29292	68	4	to	to	PART
ajst-29292	68	5	measure	measure	VERB
ajst-29292	68	6	the	the	DET
ajst-29292	68	7	mean	mean	ADJ
ajst-29292	68	8	squared	square	VERB
ajst-29292	68	9	difference	difference	NOUN
ajst-29292	68	10	between	between	ADP
ajst-29292	68	11	the	the	DET
ajst-29292	68	12	predicted	predict	VERB
ajst-29292	68	13	and	and	CCONJ
ajst-29292	68	14	actual	actual	ADJ
ajst-29292	68	15	values	value	NOUN
ajst-29292	68	16	.	.	PUNCT
ajst-29292	69	1	rmse	rmse	PROPN
ajst-29292	69	2	is	be	AUX
ajst-29292	69	3	the	the	DET
ajst-29292	69	4	square	square	ADJ
ajst-29292	69	5	root	root	NOUN
ajst-29292	69	6	of	of	ADP
ajst-29292	69	7	mse	mse	NOUN
ajst-29292	69	8	,	,	PUNCT
ajst-29292	69	9	which	which	PRON
ajst-29292	69	10	indicates	indicate	VERB
ajst-29292	69	11	the	the	DET
ajst-29292	69	12	standard	standard	ADJ
ajst-29292	69	13	deviation	deviation	NOUN
ajst-29292	69	14	of	of	ADP
ajst-29292	69	15	the	the	DET
ajst-29292	69	16	prediction	prediction	NOUN
ajst-29292	69	17	error	error	NOUN
ajst-29292	69	18	.	.	PUNCT
ajst-29292	70	1	mae	mae	PROPN
ajst-29292	70	2	denotes	denote	VERB
ajst-29292	70	3	the	the	DET
ajst-29292	70	4	mean	mean	NOUN
ajst-29292	70	5	of	of	ADP
ajst-29292	70	6	the	the	DET
ajst-29292	70	7	absolute	absolute	ADJ
ajst-29292	70	8	difference	difference	NOUN
ajst-29292	70	9	between	between	ADP
ajst-29292	70	10	the	the	DET
ajst-29292	70	11	predicted	predict	VERB
ajst-29292	70	12	and	and	CCONJ
ajst-29292	70	13	actual	actual	ADJ
ajst-29292	70	14	values	value	NOUN
ajst-29292	70	15	.	.	PUNCT
ajst-29292	71	1	mape	mape	NOUN
ajst-29292	71	2	is	be	AUX
ajst-29292	71	3	the	the	DET
ajst-29292	71	4	mean	mean	NOUN
ajst-29292	71	5	of	of	ADP
ajst-29292	71	6	the	the	DET
ajst-29292	71	7	absolute	absolute	ADJ
ajst-29292	71	8	percentage	percentage	NOUN
ajst-29292	71	9	of	of	ADP
ajst-29292	71	10	the	the	DET
ajst-29292	71	11	prediction	prediction	NOUN
ajst-29292	71	12	error	error	NOUN
ajst-29292	71	13	,	,	PUNCT
ajst-29292	71	14	which	which	PRON
ajst-29292	71	15	is	be	AUX
ajst-29292	71	16	used	use	VERB
ajst-29292	71	17	as	as	ADP
ajst-29292	71	18	a	a	DET
ajst-29292	71	19	measure	measure	NOUN
ajst-29292	71	20	of	of	ADP
ajst-29292	71	21	the	the	DET
ajst-29292	71	22	relative	relative	ADJ
ajst-29292	71	23	magnitude	magnitude	NOUN
ajst-29292	71	24	of	of	ADP
ajst-29292	71	25	the	the	DET
ajst-29292	71	26	error	error	NOUN
ajst-29292	71	27	.	.	PUNCT
ajst-29292	72	1	r2	r2	PROPN
ajst-29292	72	2	denotes	denote	VERB
ajst-29292	72	3	the	the	DET
ajst-29292	72	4	ability	ability	NOUN
ajst-29292	72	5	of	of	ADP
ajst-29292	72	6	the	the	DET
ajst-29292	72	7	model	model	NOUN
ajst-29292	72	8	to	to	PART
ajst-29292	72	9	explain	explain	VERB
ajst-29292	72	10	the	the	DET
ajst-29292	72	11	data	datum	NOUN
ajst-29292	72	12	,	,	PUNCT
ajst-29292	72	13	which	which	PRON
ajst-29292	72	14	reflects	reflect	VERB
ajst-29292	72	15	the	the	DET
ajst-29292	72	16	effectiveness	effectiveness	NOUN
ajst-29292	72	17	of	of	ADP
ajst-29292	72	18	the	the	DET
ajst-29292	72	19	model	model	NOUN
ajst-29292	72	20	's	's	PART
ajst-29292	72	21	fit	fit	NOUN
ajst-29292	72	22	.	.	PUNCT
ajst-29292	73	1	3.2	3.2	NUM
ajst-29292	73	2	.	.	PUNCT
ajst-29292	74	1	rf	rf	VERB
ajst-29292	74	2	exploratory	exploratory	ADJ
ajst-29292	74	3	prediction	prediction	NOUN
ajst-29292	74	4	the	the	DET
ajst-29292	74	5	random	random	ADJ
ajst-29292	74	6	forest	forest	NOUN
ajst-29292	74	7	model	model	NOUN
ajst-29292	74	8	was	be	AUX
ajst-29292	74	9	used	use	VERB
ajst-29292	74	10	to	to	PART
ajst-29292	74	11	predict	predict	VERB
ajst-29292	74	12	the	the	DET
ajst-29292	74	13	ipi005	ipi005	PROPN
ajst-29292	74	14	indicator	indicator	NOUN
ajst-29292	74	15	data	data	PROPN
ajst-29292	74	16	,	,	PUNCT
ajst-29292	74	17	and	and	CCONJ
ajst-29292	74	18	the	the	DET
ajst-29292	74	19	prediction	prediction	NOUN
ajst-29292	74	20	results	result	NOUN
ajst-29292	74	21	were	be	AUX
ajst-29292	74	22	obtained	obtain	VERB
ajst-29292	74	23	as	as	SCONJ
ajst-29292	74	24	shown	show	VERB
ajst-29292	74	25	in	in	ADP
ajst-29292	74	26	table	table	NOUN
ajst-29292	75	1	1	1	NUM
ajst-29292	75	2	.	.	X
ajst-29292	75	3	88	88	NUM
ajst-29292	75	4	table	table	NOUN
ajst-29292	75	5	1	1	NUM
ajst-29292	75	6	.	.	PUNCT
ajst-29292	76	1	rf	rf	NOUN
ajst-29292	76	2	model	model	NOUN
ajst-29292	76	3	performance	performance	NOUN
ajst-29292	76	4	evaluation	evaluation	NOUN
ajst-29292	76	5	metrics	metric	NOUN
ajst-29292	76	6	mse	mse	PROPN
ajst-29292	76	7	rmse	rmse	PROPN
ajst-29292	76	8	mae	mae	PROPN
ajst-29292	76	9	mape(%	mape(%	PROPN
ajst-29292	76	10	)	)	PUNCT
ajst-29292	76	11	r2	r2	PROPN
ajst-29292	76	12	training	training	NOUN
ajst-29292	76	13	set	set	VERB
ajst-29292	76	14	1.682	1.682	NUM
ajst-29292	76	15	1.297	1.297	NUM
ajst-29292	76	16	0.98	0.98	NUM
ajst-29292	76	17	12.215	12.215	NUM
ajst-29292	76	18	0.59	0.59	NUM
ajst-29292	76	19	test	test	NOUN
ajst-29292	76	20	set	set	VERB
ajst-29292	76	21	4.619	4.619	NUM
ajst-29292	76	22	2.149	2.149	NUM
ajst-29292	76	23	1.468	1.468	NUM
ajst-29292	76	24	17.039	17.039	NUM
ajst-29292	76	25	-0.053	-0.053	VERB
ajst-29292	76	26	from	from	ADP
ajst-29292	76	27	the	the	DET
ajst-29292	76	28	content	content	NOUN
ajst-29292	76	29	of	of	ADP
ajst-29292	76	30	table	table	NOUN
ajst-29292	76	31	1	1	NUM
ajst-29292	76	32	,	,	PUNCT
ajst-29292	76	33	it	it	PRON
ajst-29292	76	34	can	can	AUX
ajst-29292	76	35	be	be	AUX
ajst-29292	76	36	seen	see	VERB
ajst-29292	76	37	that	that	SCONJ
ajst-29292	76	38	the	the	DET
ajst-29292	76	39	test	test	NOUN
ajst-29292	76	40	set	set	VERB
ajst-29292	76	41	data	datum	NOUN
ajst-29292	76	42	of	of	ADP
ajst-29292	76	43	mse	mse	PROPN
ajst-29292	76	44	,	,	PUNCT
ajst-29292	76	45	rmse	rmse	PROPN
ajst-29292	76	46	,	,	PUNCT
ajst-29292	76	47	mae	mae	PROPN
ajst-29292	76	48	,	,	PUNCT
ajst-29292	76	49	and	and	CCONJ
ajst-29292	76	50	mape	mape	NOUN
ajst-29292	76	51	were	be	AUX
ajst-29292	76	52	higher	high	ADJ
ajst-29292	76	53	than	than	ADP
ajst-29292	76	54	the	the	DET
ajst-29292	76	55	training	training	NOUN
ajst-29292	76	56	set	set	NOUN
ajst-29292	76	57	,	,	PUNCT
ajst-29292	76	58	indicating	indicate	VERB
ajst-29292	76	59	that	that	SCONJ
ajst-29292	76	60	the	the	DET
ajst-29292	76	61	model	model	NOUN
ajst-29292	76	62	overfitted	overfitte	VERB
ajst-29292	76	63	the	the	DET
ajst-29292	76	64	training	training	NOUN
ajst-29292	76	65	set	set	VERB
ajst-29292	76	66	data	datum	NOUN
ajst-29292	76	67	;	;	PUNCT
ajst-29292	76	68	the	the	DET
ajst-29292	76	69	r²	r²	NOUN
ajst-29292	76	70	value	value	NOUN
ajst-29292	76	71	was	be	AUX
ajst-29292	76	72	negative	negative	ADJ
ajst-29292	76	73	,	,	PUNCT
ajst-29292	76	74	indicating	indicate	VERB
ajst-29292	76	75	that	that	SCONJ
ajst-29292	76	76	the	the	DET
ajst-29292	76	77	model	model	NOUN
ajst-29292	76	78	was	be	AUX
ajst-29292	76	79	unable	unable	ADJ
ajst-29292	76	80	to	to	PART
ajst-29292	76	81	explain	explain	VERB
ajst-29292	76	82	the	the	DET
ajst-29292	76	83	variation	variation	NOUN
ajst-29292	76	84	of	of	ADP
ajst-29292	76	85	the	the	DET
ajst-29292	76	86	data	datum	NOUN
ajst-29292	76	87	on	on	ADP
ajst-29292	76	88	the	the	DET
ajst-29292	76	89	test	test	NOUN
ajst-29292	76	90	set	set	NOUN
ajst-29292	76	91	.	.	PUNCT
ajst-29292	77	1	observation	observation	NOUN
ajst-29292	77	2	of	of	ADP
ajst-29292	77	3	the	the	DET
ajst-29292	77	4	data	datum	NOUN
ajst-29292	77	5	characteristics	characteristic	NOUN
ajst-29292	77	6	revealed	reveal	VERB
ajst-29292	77	7	that	that	SCONJ
ajst-29292	77	8	gender	gender	NOUN
ajst-29292	77	9	,	,	PUNCT
ajst-29292	77	10	history	history	NOUN
ajst-29292	77	11	of	of	ADP
ajst-29292	77	12	surgery	surgery	NOUN
ajst-29292	77	13	,	,	PUNCT
ajst-29292	77	14	smoking	smoking	NOUN
ajst-29292	77	15	,	,	PUNCT
ajst-29292	77	16	alcoholism	alcoholism	NOUN
ajst-29292	77	17	,	,	PUNCT
ajst-29292	77	18	and	and	CCONJ
ajst-29292	77	19	history	history	NOUN
ajst-29292	77	20	of	of	ADP
ajst-29292	77	21	motion	motion	NOUN
ajst-29292	77	22	sickness	sickness	NOUN
ajst-29292	77	23	were	be	AUX
ajst-29292	77	24	discrete	discrete	ADJ
ajst-29292	77	25	categorical	categorical	ADJ
ajst-29292	77	26	data	datum	NOUN
ajst-29292	77	27	the	the	DET
ajst-29292	77	28	rest	rest	NOUN
ajst-29292	77	29	of	of	ADP
ajst-29292	77	30	the	the	DET
ajst-29292	77	31	data	datum	NOUN
ajst-29292	77	32	such	such	ADJ
ajst-29292	77	33	as	as	ADP
ajst-29292	77	34	age	age	NOUN
ajst-29292	77	35	,	,	PUNCT
ajst-29292	77	36	height	height	NOUN
ajst-29292	77	37	,	,	PUNCT
ajst-29292	77	38	and	and	CCONJ
ajst-29292	77	39	weight	weight	NOUN
ajst-29292	77	40	were	be	AUX
ajst-29292	77	41	continuous	continuous	ADJ
ajst-29292	77	42	data	datum	NOUN
ajst-29292	77	43	,	,	PUNCT
ajst-29292	77	44	so	so	SCONJ
ajst-29292	77	45	the	the	DET
ajst-29292	77	46	indicator	indicator	NOUN
ajst-29292	77	47	columns	column	NOUN
ajst-29292	77	48	of	of	ADP
ajst-29292	77	49	the	the	DET
ajst-29292	77	50	two	two	NUM
ajst-29292	77	51	data	datum	NOUN
ajst-29292	77	52	categories	category	NOUN
ajst-29292	77	53	were	be	AUX
ajst-29292	77	54	split	split	VERB
ajst-29292	77	55	and	and	CCONJ
ajst-29292	77	56	predicted	predict	VERB
ajst-29292	77	57	the	the	DET
ajst-29292	77	58	ipi	ipi	PROPN
ajst-29292	77	59	data	datum	NOUN
ajst-29292	77	60	within	within	ADP
ajst-29292	77	61	3	3	NUM
ajst-29292	77	62	minutes	minute	NOUN
ajst-29292	77	63	of	of	ADP
ajst-29292	77	64	administration	administration	NOUN
ajst-29292	77	65	of	of	ADP
ajst-29292	77	66	the	the	DET
ajst-29292	77	67	medication	medication	NOUN
ajst-29292	77	68	,	,	PUNCT
ajst-29292	77	69	respectively	respectively	ADV
ajst-29292	77	70	.	.	PUNCT
ajst-29292	78	1	the	the	DET
ajst-29292	78	2	extensive	extensive	ADJ
ajst-29292	78	3	use	use	NOUN
ajst-29292	78	4	of	of	ADP
ajst-29292	78	5	the	the	DET
ajst-29292	78	6	category	category	NOUN
ajst-29292	78	7	mapping	mapping	NOUN
ajst-29292	78	8	method	method	NOUN
ajst-29292	78	9	with	with	ADP
ajst-29292	78	10	solo	solo	ADJ
ajst-29292	78	11	thermal	thermal	ADJ
ajst-29292	78	12	coding	coding	NOUN
ajst-29292	78	13	for	for	ADP
ajst-29292	78	14	the	the	DET
ajst-29292	78	15	indicators	indicator	NOUN
ajst-29292	78	16	of	of	ADP
ajst-29292	78	17	gender	gender	NOUN
ajst-29292	78	18	,	,	PUNCT
ajst-29292	78	19	history	history	NOUN
ajst-29292	78	20	of	of	ADP
ajst-29292	78	21	surgery	surgery	NOUN
ajst-29292	78	22	,	,	PUNCT
ajst-29292	78	23	smoking	smoking	NOUN
ajst-29292	78	24	,	,	PUNCT
ajst-29292	78	25	alcohol	alcohol	NOUN
ajst-29292	78	26	use	use	NOUN
ajst-29292	78	27	,	,	PUNCT
ajst-29292	78	28	and	and	CCONJ
ajst-29292	78	29	history	history	NOUN
ajst-29292	78	30	of	of	ADP
ajst-29292	78	31	motion	motion	NOUN
ajst-29292	78	32	sickness	sickness	NOUN
ajst-29292	78	33	led	lead	VERB
ajst-29292	78	34	to	to	ADP
ajst-29292	78	35	the	the	DET
ajst-29292	78	36	problem	problem	NOUN
ajst-29292	78	37	of	of	ADP
ajst-29292	78	38	dimensional	dimensional	ADJ
ajst-29292	78	39	catastrophe	catastrophe	NOUN
ajst-29292	78	40	,	,	PUNCT
ajst-29292	78	41	i.e.	i.e.	X
ajst-29292	78	42	,	,	PUNCT
ajst-29292	78	43	increased	increase	VERB
ajst-29292	78	44	computational	computational	ADJ
ajst-29292	78	45	complexity	complexity	NOUN
ajst-29292	78	46	,	,	PUNCT
ajst-29292	78	47	overfitting	overfitte	VERB
ajst-29292	78	48	of	of	ADP
ajst-29292	78	49	the	the	DET
ajst-29292	78	50	model	model	NOUN
ajst-29292	78	51	,	,	PUNCT
ajst-29292	78	52	increased	increase	VERB
ajst-29292	78	53	sparsity	sparsity	NOUN
ajst-29292	78	54	of	of	ADP
ajst-29292	78	55	the	the	DET
ajst-29292	78	56	data	datum	NOUN
ajst-29292	78	57	,	,	PUNCT
ajst-29292	78	58	and	and	CCONJ
ajst-29292	78	59	decreased	decrease	VERB
ajst-29292	78	60	feature	feature	NOUN
ajst-29292	78	61	relevance	relevance	NOUN
ajst-29292	78	62	.	.	PUNCT
ajst-29292	79	1	this	this	PRON
ajst-29292	79	2	ultimately	ultimately	ADV
ajst-29292	79	3	resulted	result	VERB
ajst-29292	79	4	in	in	ADP
ajst-29292	79	5	the	the	DET
ajst-29292	79	6	inability	inability	NOUN
ajst-29292	79	7	to	to	PART
ajst-29292	79	8	accurately	accurately	ADV
ajst-29292	79	9	predict	predict	VERB
ajst-29292	79	10	ipi	ipi	PROPN
ajst-29292	79	11	data	datum	NOUN
ajst-29292	79	12	within	within	ADP
ajst-29292	79	13	3	3	NUM
ajst-29292	79	14	minutes	minute	NOUN
ajst-29292	79	15	of	of	ADP
ajst-29292	79	16	medication	medication	NOUN
ajst-29292	79	17	administration	administration	NOUN
ajst-29292	79	18	.	.	PUNCT
ajst-29292	80	1	the	the	DET
ajst-29292	80	2	use	use	NOUN
ajst-29292	80	3	of	of	ADP
ajst-29292	80	4	alternative	alternative	ADJ
ajst-29292	80	5	coding	code	VERB
ajst-29292	80	6	methods	method	NOUN
ajst-29292	80	7	for	for	ADP
ajst-29292	80	8	the	the	DET
ajst-29292	80	9	prediction	prediction	NOUN
ajst-29292	80	10	of	of	ADP
ajst-29292	80	11	multiple	multiple	ADJ
ajst-29292	80	12	ipi	ipi	PROPN
ajst-29292	80	13	data	datum	NOUN
ajst-29292	80	14	would	would	AUX
ajst-29292	80	15	increase	increase	VERB
ajst-29292	80	16	the	the	DET
ajst-29292	80	17	computational	computational	ADJ
ajst-29292	80	18	and	and	CCONJ
ajst-29292	80	19	processing	processing	NOUN
ajst-29292	80	20	costs	cost	NOUN
ajst-29292	80	21	significantly	significantly	ADV
ajst-29292	80	22	.	.	PUNCT
ajst-29292	81	1	taking	take	VERB
ajst-29292	81	2	the	the	DET
ajst-29292	81	3	above	above	ADJ
ajst-29292	81	4	factors	factor	NOUN
ajst-29292	81	5	into	into	ADP
ajst-29292	81	6	account	account	NOUN
ajst-29292	81	7	,	,	PUNCT
ajst-29292	81	8	the	the	DET
ajst-29292	81	9	data	data	NOUN
ajst-29292	81	10	indicators	indicator	NOUN
ajst-29292	81	11	were	be	AUX
ajst-29292	81	12	split	split	VERB
ajst-29292	81	13	,	,	PUNCT
ajst-29292	81	14	continuous	continuous	ADJ
ajst-29292	81	15	data	datum	NOUN
ajst-29292	81	16	and	and	CCONJ
ajst-29292	81	17	discrete	discrete	ADJ
ajst-29292	81	18	data	datum	NOUN
ajst-29292	81	19	were	be	AUX
ajst-29292	81	20	predicted	predict	VERB
ajst-29292	81	21	separately	separately	ADV
ajst-29292	81	22	,	,	PUNCT
ajst-29292	81	23	and	and	CCONJ
ajst-29292	81	24	the	the	DET
ajst-29292	81	25	two	two	NUM
ajst-29292	81	26	predictions	prediction	NOUN
ajst-29292	81	27	were	be	AUX
ajst-29292	81	28	finally	finally	ADV
ajst-29292	81	29	summed	sum	VERB
ajst-29292	81	30	.	.	PUNCT
ajst-29292	82	1	3.3	3.3	NUM
ajst-29292	82	2	.	.	PUNCT
ajst-29292	83	1	multi	multi	ADJ
ajst-29292	83	2	-	-	ADJ
ajst-29292	83	3	model	model	ADJ
ajst-29292	83	4	comparison	comparison	NOUN
ajst-29292	83	5	random	random	ADJ
ajst-29292	83	6	forest	forest	NOUN
ajst-29292	83	7	regression	regression	NOUN
ajst-29292	83	8	is	be	AUX
ajst-29292	83	9	in	in	ADP
ajst-29292	83	10	the	the	DET
ajst-29292	83	11	process	process	NOUN
ajst-29292	83	12	of	of	ADP
ajst-29292	83	13	generating	generate	VERB
ajst-29292	83	14	many	many	ADJ
ajst-29292	83	15	decision	decision	NOUN
ajst-29292	83	16	trees	tree	NOUN
ajst-29292	83	17	,	,	PUNCT
ajst-29292	83	18	is	be	AUX
ajst-29292	83	19	through	through	ADP
ajst-29292	83	20	the	the	DET
ajst-29292	83	21	modeling	modeling	NOUN
ajst-29292	83	22	dataset	dataset	NOUN
ajst-29292	83	23	of	of	ADP
ajst-29292	83	24	sample	sample	NOUN
ajst-29292	83	25	observations	observation	NOUN
ajst-29292	83	26	and	and	CCONJ
ajst-29292	83	27	feature	feature	NOUN
ajst-29292	83	28	variables	variable	NOUN
ajst-29292	83	29	are	be	AUX
ajst-29292	83	30	randomly	randomly	ADV
ajst-29292	83	31	sampled	sample	VERB
ajst-29292	83	32	,	,	PUNCT
ajst-29292	83	33	each	each	DET
ajst-29292	83	34	sampling	sampling	NOUN
ajst-29292	83	35	result	result	NOUN
ajst-29292	83	36	is	be	AUX
ajst-29292	83	37	a	a	DET
ajst-29292	83	38	tree	tree	NOUN
ajst-29292	83	39	,	,	PUNCT
ajst-29292	83	40	and	and	CCONJ
ajst-29292	83	41	each	each	DET
ajst-29292	83	42	tree	tree	NOUN
ajst-29292	83	43	will	will	AUX
ajst-29292	83	44	generate	generate	VERB
ajst-29292	83	45	rules	rule	NOUN
ajst-29292	83	46	and	and	CCONJ
ajst-29292	83	47	judgment	judgment	NOUN
ajst-29292	83	48	values	value	NOUN
ajst-29292	83	49	that	that	PRON
ajst-29292	83	50	match	match	VERB
ajst-29292	83	51	its	its	PRON
ajst-29292	83	52	own	own	ADJ
ajst-29292	83	53	attributes	attribute	NOUN
ajst-29292	83	54	,	,	PUNCT
ajst-29292	83	55	and	and	CCONJ
ajst-29292	83	56	the	the	DET
ajst-29292	83	57	forest	forest	NOUN
ajst-29292	83	58	finally	finally	ADV
ajst-29292	83	59	integrates	integrate	VERB
ajst-29292	83	60	the	the	DET
ajst-29292	83	61	rules	rule	NOUN
ajst-29292	83	62	and	and	CCONJ
ajst-29292	83	63	judgment	judgment	NOUN
ajst-29292	83	64	values	value	NOUN
ajst-29292	83	65	of	of	ADP
ajst-29292	83	66	all	all	DET
ajst-29292	83	67	the	the	DET
ajst-29292	83	68	decision	decision	NOUN
ajst-29292	83	69	trees	tree	NOUN
ajst-29292	83	70	,	,	PUNCT
ajst-29292	83	71	to	to	PART
ajst-29292	83	72	achieve	achieve	VERB
ajst-29292	83	73	the	the	DET
ajst-29292	83	74	regression	regression	NOUN
ajst-29292	83	75	of	of	ADP
ajst-29292	83	76	the	the	DET
ajst-29292	83	77	random	random	ADJ
ajst-29292	83	78	forest	forest	NOUN
ajst-29292	83	79	algorithm	algorithm	NOUN
ajst-29292	83	80	.	.	PUNCT
ajst-29292	84	1	xgboost	xgboost	PROPN
ajst-29292	84	2	is	be	AUX
ajst-29292	84	3	an	an	DET
ajst-29292	84	4	efficient	efficient	ADJ
ajst-29292	84	5	implementation	implementation	NOUN
ajst-29292	84	6	of	of	ADP
ajst-29292	84	7	gbdt	gbdt	NOUN
ajst-29292	84	8	.	.	PUNCT
ajst-29292	85	1	unlike	unlike	ADP
ajst-29292	85	2	gbdt	gbdt	NOUN
ajst-29292	85	3	,	,	PUNCT
ajst-29292	85	4	xgboost	xgboost	ADV
ajst-29292	85	5	adds	add	VERB
ajst-29292	85	6	a	a	DET
ajst-29292	85	7	regularization	regularization	NOUN
ajst-29292	85	8	term	term	NOUN
ajst-29292	85	9	to	to	ADP
ajst-29292	85	10	the	the	DET
ajst-29292	85	11	loss	loss	NOUN
ajst-29292	85	12	function	function	NOUN
ajst-29292	85	13	;	;	PUNCT
ajst-29292	85	14	and	and	CCONJ
ajst-29292	85	15	since	since	SCONJ
ajst-29292	85	16	some	some	DET
ajst-29292	85	17	loss	loss	NOUN
ajst-29292	85	18	functions	function	NOUN
ajst-29292	85	19	are	be	AUX
ajst-29292	85	20	difficult	difficult	ADJ
ajst-29292	85	21	to	to	PART
ajst-29292	85	22	compute	compute	VERB
ajst-29292	85	23	derivatives	derivative	NOUN
ajst-29292	85	24	,	,	PUNCT
ajst-29292	85	25	xgboost	xgboost	PROPN
ajst-29292	85	26	uses	use	VERB
ajst-29292	85	27	a	a	DET
ajst-29292	85	28	second	second	ADJ
ajst-29292	85	29	-	-	PUNCT
ajst-29292	85	30	order	order	NOUN
ajst-29292	85	31	taylor	taylor	NOUN
ajst-29292	85	32	expansion	expansion	NOUN
ajst-29292	85	33	of	of	ADP
ajst-29292	85	34	the	the	DET
ajst-29292	85	35	loss	loss	NOUN
ajst-29292	85	36	function	function	NOUN
ajst-29292	85	37	as	as	SCONJ
ajst-29292	85	38	the	the	DET
ajst-29292	85	39	loss	loss	NOUN
ajst-29292	85	40	function	function	NOUN
ajst-29292	85	41	fit	fit	ADJ
ajst-29292	85	42	.	.	PUNCT
ajst-29292	86	1	in	in	ADP
ajst-29292	86	2	regression	regression	NOUN
ajst-29292	86	3	problems	problem	NOUN
ajst-29292	86	4	,	,	PUNCT
ajst-29292	86	5	the	the	DET
ajst-29292	86	6	goal	goal	NOUN
ajst-29292	86	7	of	of	ADP
ajst-29292	86	8	xgboost	xgboost	ADV
ajst-29292	86	9	is	be	AUX
ajst-29292	86	10	to	to	PART
ajst-29292	86	11	minimize	minimize	VERB
ajst-29292	86	12	a	a	DET
ajst-29292	86	13	loss	loss	NOUN
ajst-29292	86	14	function	function	NOUN
ajst-29292	86	15	in	in	ADP
ajst-29292	86	16	order	order	NOUN
ajst-29292	86	17	to	to	PART
ajst-29292	86	18	predict	predict	VERB
ajst-29292	86	19	continuous	continuous	ADJ
ajst-29292	86	20	variables	variable	NOUN
ajst-29292	86	21	as	as	ADV
ajst-29292	86	22	accurately	accurately	ADV
ajst-29292	86	23	as	as	ADP
ajst-29292	86	24	possible	possible	ADJ
ajst-29292	86	25	.	.	PUNCT
ajst-29292	87	1	catboost	catboost	PROPN
ajst-29292	87	2	is	be	AUX
ajst-29292	87	3	a	a	DET
ajst-29292	87	4	gbdt	gbdt	NOUN
ajst-29292	87	5	framework	framework	NOUN
ajst-29292	87	6	based	base	VERB
ajst-29292	87	7	on	on	ADP
ajst-29292	87	8	the	the	DET
ajst-29292	87	9	symmetric	symmetric	ADJ
ajst-29292	87	10	decision	decision	NOUN
ajst-29292	87	11	tree	tree	NOUN
ajst-29292	87	12	algorithm	algorithm	NOUN
ajst-29292	87	13	,	,	PUNCT
ajst-29292	87	14	which	which	PRON
ajst-29292	87	15	mainly	mainly	ADV
ajst-29292	87	16	addresses	address	VERB
ajst-29292	87	17	the	the	DET
ajst-29292	87	18	pain	pain	NOUN
ajst-29292	87	19	point	point	NOUN
ajst-29292	87	20	of	of	ADP
ajst-29292	87	21	efficiently	efficiently	ADV
ajst-29292	87	22	and	and	CCONJ
ajst-29292	87	23	rationally	rationally	ADV
ajst-29292	87	24	handling	handle	VERB
ajst-29292	87	25	category	category	NOUN
ajst-29292	87	26	-	-	PUNCT
ajst-29292	87	27	based	base	VERB
ajst-29292	87	28	features	feature	NOUN
ajst-29292	87	29	and	and	CCONJ
ajst-29292	87	30	dealing	deal	VERB
ajst-29292	87	31	with	with	ADP
ajst-29292	87	32	gradient	gradient	ADJ
ajst-29292	87	33	bias	bias	NOUN
ajst-29292	87	34	and	and	CCONJ
ajst-29292	87	35	prediction	prediction	NOUN
ajst-29292	87	36	bias	bias	NOUN
ajst-29292	87	37	to	to	PART
ajst-29292	87	38	improve	improve	VERB
ajst-29292	87	39	the	the	DET
ajst-29292	87	40	accuracy	accuracy	NOUN
ajst-29292	87	41	and	and	CCONJ
ajst-29292	87	42	generalization	generalization	NOUN
ajst-29292	87	43	ability	ability	NOUN
ajst-29292	87	44	of	of	ADP
ajst-29292	87	45	the	the	DET
ajst-29292	87	46	algorithm	algorithm	NOUN
ajst-29292	87	47	.	.	PUNCT
ajst-29292	88	1	support	support	NOUN
ajst-29292	88	2	vector	vector	NOUN
ajst-29292	88	3	machine	machine	NOUN
ajst-29292	88	4	regression	regression	NOUN
ajst-29292	88	5	(	(	PUNCT
ajst-29292	88	6	svr	svr	PROPN
ajst-29292	88	7	)	)	PUNCT
ajst-29292	88	8	maps	map	VERB
ajst-29292	88	9	the	the	DET
ajst-29292	88	10	data	datum	NOUN
ajst-29292	88	11	into	into	ADP
ajst-29292	88	12	the	the	DET
ajst-29292	88	13	high	high	ADJ
ajst-29292	88	14	-	-	PUNCT
ajst-29292	88	15	dimensional	dimensional	ADJ
ajst-29292	88	16	data	datum	NOUN
ajst-29292	88	17	feature	feature	NOUN
ajst-29292	88	18	space	space	NOUN
ajst-29292	88	19	with	with	ADP
ajst-29292	88	20	a	a	DET
ajst-29292	88	21	nonlinear	nonlinear	ADJ
ajst-29292	88	22	mapping	mapping	NOUN
ajst-29292	88	23	,	,	PUNCT
ajst-29292	88	24	which	which	PRON
ajst-29292	88	25	makes	make	VERB
ajst-29292	88	26	the	the	DET
ajst-29292	88	27	independent	independent	ADJ
ajst-29292	88	28	variable	variable	NOUN
ajst-29292	88	29	and	and	CCONJ
ajst-29292	88	30	the	the	DET
ajst-29292	88	31	dependent	dependent	ADJ
ajst-29292	88	32	variable	variable	NOUN
ajst-29292	88	33	in	in	ADP
ajst-29292	88	34	the	the	DET
ajst-29292	88	35	high	high	ADV
ajst-29292	88	36	-	-	PUNCT
ajst-29292	88	37	dimensional	dimensional	ADJ
ajst-29292	88	38	data	datum	NOUN
ajst-29292	88	39	feature	feature	NOUN
ajst-29292	88	40	space	space	NOUN
ajst-29292	88	41	have	have	VERB
ajst-29292	88	42	good	good	ADJ
ajst-29292	88	43	linear	linear	ADJ
ajst-29292	88	44	regression	regression	NOUN
ajst-29292	88	45	characteristics	characteristic	NOUN
ajst-29292	88	46	,	,	PUNCT
ajst-29292	88	47	and	and	CCONJ
ajst-29292	88	48	the	the	DET
ajst-29292	88	49	fitting	fitting	NOUN
ajst-29292	88	50	is	be	AUX
ajst-29292	88	51	performed	perform	VERB
ajst-29292	88	52	in	in	ADP
ajst-29292	88	53	this	this	DET
ajst-29292	88	54	feature	feature	NOUN
ajst-29292	88	55	space	space	NOUN
ajst-29292	88	56	and	and	CCONJ
ajst-29292	88	57	then	then	ADV
ajst-29292	88	58	return	return	VERB
ajst-29292	88	59	to	to	ADP
ajst-29292	88	60	the	the	DET
ajst-29292	88	61	original	original	ADJ
ajst-29292	88	62	space	space	NOUN
ajst-29292	88	63	.	.	PUNCT
ajst-29292	89	1	lightgbm	lightgbm	PROPN
ajst-29292	89	2	is	be	AUX
ajst-29292	89	3	an	an	DET
ajst-29292	89	4	efficient	efficient	ADJ
ajst-29292	89	5	implementation	implementation	NOUN
ajst-29292	89	6	of	of	ADP
ajst-29292	89	7	xgboost	xgboost	PROPN
ajst-29292	89	8	,	,	PUNCT
ajst-29292	89	9	the	the	DET
ajst-29292	89	10	idea	idea	NOUN
ajst-29292	89	11	is	be	AUX
ajst-29292	89	12	to	to	PART
ajst-29292	89	13	discretize	discretize	VERB
ajst-29292	89	14	continuous	continuous	ADJ
ajst-29292	89	15	floating	float	VERB
ajst-29292	89	16	-	-	PUNCT
ajst-29292	89	17	point	point	NOUN
ajst-29292	89	18	features	feature	NOUN
ajst-29292	89	19	into	into	ADP
ajst-29292	89	20	k	k	PROPN
ajst-29292	89	21	discrete	discrete	ADJ
ajst-29292	89	22	values	value	NOUN
ajst-29292	89	23	and	and	CCONJ
ajst-29292	89	24	construct	construct	VERB
ajst-29292	89	25	a	a	DET
ajst-29292	89	26	histogram	histogram	NOUN
ajst-29292	89	27	of	of	ADP
ajst-29292	89	28	width	width	PROPN
ajst-29292	89	29	k.	k.	PROPN
ajst-29292	89	30	then	then	ADV
ajst-29292	89	31	traverse	traverse	VERB
ajst-29292	89	32	the	the	DET
ajst-29292	89	33	training	training	NOUN
ajst-29292	89	34	data	datum	NOUN
ajst-29292	89	35	and	and	CCONJ
ajst-29292	89	36	calculate	calculate	VERB
ajst-29292	89	37	the	the	DET
ajst-29292	89	38	cumulative	cumulative	ADJ
ajst-29292	89	39	statistic	statistic	NOUN
ajst-29292	89	40	of	of	ADP
ajst-29292	89	41	each	each	DET
ajst-29292	89	42	discrete	discrete	ADJ
ajst-29292	89	43	value	value	NOUN
ajst-29292	89	44	in	in	ADP
ajst-29292	89	45	the	the	DET
ajst-29292	89	46	histogram	histogram	NOUN
ajst-29292	89	47	.	.	PUNCT
ajst-29292	90	1	in	in	ADP
ajst-29292	90	2	feature	feature	NOUN
ajst-29292	90	3	selection	selection	NOUN
ajst-29292	90	4	,	,	PUNCT
ajst-29292	90	5	we	we	PRON
ajst-29292	90	6	only	only	ADV
ajst-29292	90	7	need	need	VERB
ajst-29292	90	8	to	to	PART
ajst-29292	90	9	traverse	traverse	VERB
ajst-29292	90	10	to	to	PART
ajst-29292	90	11	find	find	VERB
ajst-29292	90	12	the	the	DET
ajst-29292	90	13	optimal	optimal	ADJ
ajst-29292	90	14	segmentation	segmentation	NOUN
ajst-29292	90	15	points	point	NOUN
ajst-29292	90	16	based	base	VERB
ajst-29292	90	17	on	on	ADP
ajst-29292	90	18	the	the	DET
ajst-29292	90	19	discrete	discrete	ADJ
ajst-29292	90	20	values	value	NOUN
ajst-29292	90	21	of	of	ADP
ajst-29292	90	22	the	the	DET
ajst-29292	90	23	histogram	histogram	NOUN
ajst-29292	90	24	;	;	PUNCT
ajst-29292	90	25	and	and	CCONJ
ajst-29292	90	26	we	we	PRON
ajst-29292	90	27	use	use	VERB
ajst-29292	90	28	the	the	DET
ajst-29292	90	29	grow	grow	VERB
ajst-29292	90	30	-	-	PUNCT
ajst-29292	90	31	by	by	ADP
ajst-29292	90	32	-	-	PUNCT
ajst-29292	90	33	leaf	leaf	NOUN
ajst-29292	90	34	strategy	strategy	NOUN
ajst-29292	90	35	with	with	ADP
ajst-29292	90	36	depth	depth	NOUN
ajst-29292	90	37	restriction	restriction	NOUN
ajst-29292	90	38	,	,	PUNCT
ajst-29292	90	39	which	which	PRON
ajst-29292	90	40	saves	save	VERB
ajst-29292	90	41	a	a	DET
ajst-29292	90	42	lot	lot	NOUN
ajst-29292	90	43	of	of	ADP
ajst-29292	90	44	time	time	NOUN
ajst-29292	90	45	and	and	CCONJ
ajst-29292	90	46	space	space	NOUN
ajst-29292	90	47	overhead	overhead	ADV
ajst-29292	90	48	.	.	PUNCT
ajst-29292	91	1	for	for	ADP
ajst-29292	91	2	the	the	DET
ajst-29292	91	3	continuous	continuous	ADJ
ajst-29292	91	4	data	datum	NOUN
ajst-29292	91	5	metrics	metric	NOUN
ajst-29292	91	6	,	,	PUNCT
ajst-29292	91	7	ipi005	ipi005	PROPN
ajst-29292	91	8	is	be	AUX
ajst-29292	91	9	chosen	choose	VERB
ajst-29292	91	10	as	as	ADP
ajst-29292	91	11	the	the	DET
ajst-29292	91	12	test	test	NOUN
ajst-29292	91	13	metric	metric	NOUN
ajst-29292	91	14	,	,	PUNCT
ajst-29292	91	15	and	and	CCONJ
ajst-29292	91	16	the	the	DET
ajst-29292	91	17	metrics	metric	NOUN
ajst-29292	91	18	are	be	AUX
ajst-29292	91	19	predicted	predict	VERB
ajst-29292	91	20	using	use	VERB
ajst-29292	91	21	randomforest	randomforest	PROPN
ajst-29292	91	22	,	,	PUNCT
ajst-29292	91	23	xgboost	xgboost	ADV
ajst-29292	91	24	,	,	PUNCT
ajst-29292	91	25	catboost	catboost	PROPN
ajst-29292	91	26	,	,	PUNCT
ajst-29292	91	27	svr	svr	PROPN
ajst-29292	91	28	,	,	PUNCT
ajst-29292	91	29	and	and	CCONJ
ajst-29292	91	30	lightgbm	lightgbm	ADJ
ajst-29292	91	31	,	,	PUNCT
ajst-29292	91	32	respectively	respectively	ADV
ajst-29292	91	33	.	.	PUNCT
ajst-29292	92	1	the	the	DET
ajst-29292	92	2	results	result	NOUN
ajst-29292	92	3	show	show	VERB
ajst-29292	92	4	that	that	SCONJ
ajst-29292	92	5	the	the	DET
ajst-29292	92	6	randomforest	randomfor	ADJ
ajst-29292	92	7	model	model	NOUN
ajst-29292	92	8	has	have	VERB
ajst-29292	92	9	the	the	DET
ajst-29292	92	10	optimal	optimal	ADJ
ajst-29292	92	11	prediction	prediction	NOUN
ajst-29292	92	12	results	result	NOUN
ajst-29292	92	13	for	for	ADP
ajst-29292	92	14	this	this	DET
ajst-29292	92	15	data	datum	NOUN
ajst-29292	92	16	,	,	PUNCT
ajst-29292	92	17	so	so	CCONJ
ajst-29292	92	18	the	the	DET
ajst-29292	92	19	randomforest	randomfor	ADJ
ajst-29292	92	20	model	model	NOUN
ajst-29292	92	21	is	be	AUX
ajst-29292	92	22	used	use	VERB
ajst-29292	92	23	for	for	ADP
ajst-29292	92	24	the	the	DET
ajst-29292	92	25	continuous	continuous	ADJ
ajst-29292	92	26	data	datum	NOUN
ajst-29292	92	27	to	to	PART
ajst-29292	92	28	evaluate	evaluate	VERB
ajst-29292	92	29	the	the	DET
ajst-29292	92	30	continuity	continuity	NOUN
ajst-29292	92	31	indicators	indicator	NOUN
ajst-29292	92	32	,	,	PUNCT
ajst-29292	92	33	and	and	CCONJ
ajst-29292	92	34	the	the	DET
ajst-29292	92	35	logistic	logistic	ADJ
ajst-29292	92	36	regression	regression	NOUN
ajst-29292	92	37	model	model	NOUN
ajst-29292	92	38	is	be	AUX
ajst-29292	92	39	used	use	VERB
ajst-29292	92	40	to	to	PART
ajst-29292	92	41	predict	predict	VERB
ajst-29292	92	42	the	the	DET
ajst-29292	92	43	values	value	NOUN
ajst-29292	92	44	of	of	ADP
ajst-29292	92	45	the	the	DET
ajst-29292	92	46	discontinuous	discontinuous	ADJ
ajst-29292	92	47	dichotomous	dichotomous	ADJ
ajst-29292	92	48	data	datum	NOUN
ajst-29292	92	49	for	for	ADP
ajst-29292	92	50	the	the	DET
ajst-29292	92	51	two	two	NUM
ajst-29292	92	52	different	different	ADJ
ajst-29292	92	53	types	type	NOUN
ajst-29292	92	54	of	of	ADP
ajst-29292	92	55	data	datum	NOUN
ajst-29292	92	56	,	,	PUNCT
ajst-29292	92	57	respectively	respectively	ADV
ajst-29292	92	58	.	.	PUNCT
ajst-29292	93	1	the	the	DET
ajst-29292	93	2	regression	regression	NOUN
ajst-29292	93	3	results	result	NOUN
ajst-29292	93	4	of	of	ADP
ajst-29292	93	5	the	the	DET
ajst-29292	93	6	above	above	ADJ
ajst-29292	93	7	two	two	NUM
ajst-29292	93	8	types	type	NOUN
ajst-29292	93	9	of	of	ADP
ajst-29292	93	10	data	datum	NOUN
ajst-29292	93	11	were	be	AUX
ajst-29292	93	12	combined	combine	VERB
ajst-29292	93	13	,	,	PUNCT
ajst-29292	93	14	and	and	CCONJ
ajst-29292	93	15	the	the	DET
ajst-29292	93	16	weights	weight	NOUN
ajst-29292	93	17	of	of	ADP
ajst-29292	93	18	the	the	DET
ajst-29292	93	19	two	two	NUM
ajst-29292	93	20	predictions	prediction	NOUN
ajst-29292	93	21	in	in	ADP
ajst-29292	93	22	the	the	DET
ajst-29292	93	23	actual	actual	ADJ
ajst-29292	93	24	prediction	prediction	NOUN
ajst-29292	93	25	results	result	NOUN
ajst-29292	93	26	were	be	AUX
ajst-29292	93	27	determined	determine	VERB
ajst-29292	93	28	by	by	ADP
ajst-29292	93	29	comparing	compare	VERB
ajst-29292	93	30	the	the	DET
ajst-29292	93	31	two	two	NUM
ajst-29292	93	32	types	type	NOUN
ajst-29292	93	33	of	of	ADP
ajst-29292	93	34	data	datum	NOUN
ajst-29292	93	35	with	with	ADP
ajst-29292	93	36	the	the	DET
ajst-29292	93	37	actual	actual	ADJ
ajst-29292	93	38	errors	error	NOUN
ajst-29292	93	39	.	.	PUNCT
ajst-29292	94	1	4	4	X
ajst-29292	94	2	.	.	X
ajst-29292	94	3	conclusion	conclusion	VERB
ajst-29292	94	4	our	our	PRON
ajst-29292	94	5	findings	finding	NOUN
ajst-29292	94	6	indicate	indicate	VERB
ajst-29292	94	7	that	that	SCONJ
ajst-29292	94	8	the	the	DET
ajst-29292	94	9	novel	novel	ADJ
ajst-29292	94	10	sedative	sedative	NOUN
ajst-29292	94	11	medication	medication	NOUN
ajst-29292	94	12	exhibits	exhibit	VERB
ajst-29292	94	13	statistically	statistically	ADV
ajst-29292	94	14	significant	significant	ADJ
ajst-29292	94	15	differences	difference	NOUN
ajst-29292	94	16	in	in	ADP
ajst-29292	94	17	specific	specific	ADJ
ajst-29292	94	18	vital	vital	ADJ
ajst-29292	94	19	signs	sign	NOUN
ajst-29292	94	20	compared	compare	VERB
ajst-29292	94	21	to	to	ADP
ajst-29292	94	22	the	the	DET
ajst-29292	94	23	existing	exist	VERB
ajst-29292	94	24	drug	drug	NOUN
ajst-29292	94	25	,	,	PUNCT
ajst-29292	94	26	primarily	primarily	ADV
ajst-29292	94	27	within	within	ADP
ajst-29292	94	28	the	the	DET
ajst-29292	94	29	first	first	ADJ
ajst-29292	94	30	1	1	NUM
ajst-29292	94	31	to	to	PART
ajst-29292	94	32	3	3	NUM
ajst-29292	94	33	minutes	minute	NOUN
ajst-29292	94	34	post	post	ADJ
ajst-29292	94	35	-	-	NOUN
ajst-29292	94	36	induction	induction	NOUN
ajst-29292	94	37	.	.	PUNCT
ajst-29292	95	1	these	these	DET
ajst-29292	95	2	differences	difference	NOUN
ajst-29292	95	3	were	be	AUX
ajst-29292	95	4	observed	observe	VERB
ajst-29292	95	5	in	in	ADP
ajst-29292	95	6	indicators	indicator	NOUN
ajst-29292	95	7	such	such	ADJ
ajst-29292	95	8	as	as	ADP
ajst-29292	95	9	petco200	petco200	PROPN
ajst-29292	95	10	,	,	PUNCT
ajst-29292	95	11	petco2005	petco2005	PROPN
ajst-29292	95	12	,	,	PUNCT
ajst-29292	95	13	ipi005	ipi005	PROPN
ajst-29292	95	14	,	,	PUNCT
ajst-29292	95	15	and	and	CCONJ
ajst-29292	95	16	moaas005	moaas005	PROPN
ajst-29292	95	17	,	,	PUNCT
ajst-29292	95	18	suggesting	suggest	VERB
ajst-29292	95	19	early	early	ADJ
ajst-29292	95	20	and	and	CCONJ
ajst-29292	95	21	notable	notable	ADJ
ajst-29292	95	22	effects	effect	NOUN
ajst-29292	95	23	of	of	ADP
ajst-29292	95	24	the	the	DET
ajst-29292	95	25	novel	novel	ADJ
ajst-29292	95	26	sedative	sedative	NOUN
ajst-29292	95	27	.	.	PUNCT
ajst-29292	96	1	the	the	DET
ajst-29292	96	2	comparability	comparability	NOUN
ajst-29292	96	3	of	of	ADP
ajst-29292	96	4	basic	basic	ADJ
ajst-29292	96	5	information	information	NOUN
ajst-29292	96	6	between	between	ADP
ajst-29292	96	7	the	the	DET
ajst-29292	96	8	two	two	NUM
ajst-29292	96	9	groups	group	NOUN
ajst-29292	96	10	suggests	suggest	VERB
ajst-29292	96	11	that	that	SCONJ
ajst-29292	96	12	these	these	DET
ajst-29292	96	13	differences	difference	NOUN
ajst-29292	96	14	are	be	AUX
ajst-29292	96	15	attributable	attributable	ADJ
ajst-29292	96	16	to	to	ADP
ajst-29292	96	17	the	the	DET
ajst-29292	96	18	novel	novel	ADJ
ajst-29292	96	19	sedative	sedative	NOUN
ajst-29292	96	20	itself	itself	PRON
ajst-29292	96	21	,	,	PUNCT
ajst-29292	96	22	rather	rather	ADV
ajst-29292	96	23	than	than	ADP
ajst-29292	96	24	confounding	confound	VERB
ajst-29292	96	25	variables	variable	NOUN
ajst-29292	96	26	.	.	PUNCT
ajst-29292	97	1	regarding	regard	VERB
ajst-29292	97	2	machine	machine	NOUN
ajst-29292	97	3	learning	learning	NOUN
ajst-29292	97	4	predictions	prediction	NOUN
ajst-29292	97	5	,	,	PUNCT
ajst-29292	97	6	while	while	SCONJ
ajst-29292	97	7	the	the	DET
ajst-29292	97	8	initial	initial	ADJ
ajst-29292	97	9	exploratory	exploratory	ADJ
ajst-29292	97	10	random	random	ADJ
ajst-29292	97	11	forest	forest	NOUN
ajst-29292	97	12	(	(	PUNCT
ajst-29292	97	13	rf	rf	NOUN
ajst-29292	97	14	)	)	PUNCT
ajst-29292	97	15	model	model	NOUN
ajst-29292	97	16	yielded	yield	VERB
ajst-29292	97	17	suboptimal	suboptimal	ADJ
ajst-29292	97	18	results	result	NOUN
ajst-29292	97	19	,	,	PUNCT
ajst-29292	97	20	a	a	DET
ajst-29292	97	21	more	more	ADV
ajst-29292	97	22	comprehensive	comprehensive	ADJ
ajst-29292	97	23	analysis	analysis	NOUN
ajst-29292	97	24	involving	involve	VERB
ajst-29292	97	25	multiple	multiple	ADJ
ajst-29292	97	26	algorithms	algorithm	NOUN
ajst-29292	97	27	led	lead	VERB
ajst-29292	97	28	to	to	ADP
ajst-29292	97	29	the	the	DET
ajst-29292	97	30	selection	selection	NOUN
ajst-29292	97	31	of	of	ADP
ajst-29292	97	32	a	a	DET
ajst-29292	97	33	combination	combination	NOUN
ajst-29292	97	34	of	of	ADP
ajst-29292	97	35	rf	rf	NOUN
ajst-29292	97	36	and	and	CCONJ
ajst-29292	97	37	logistic	logistic	ADJ
ajst-29292	97	38	regression	regression	NOUN
ajst-29292	97	39	models	model	NOUN
ajst-29292	97	40	.	.	PUNCT
ajst-29292	98	1	these	these	DET
ajst-29292	98	2	models	model	NOUN
ajst-29292	98	3	provided	provide	VERB
ajst-29292	98	4	good	good	ADJ
ajst-29292	98	5	predictive	predictive	ADJ
ajst-29292	98	6	performance	performance	NOUN
ajst-29292	98	7	,	,	PUNCT
ajst-29292	98	8	as	as	SCONJ
ajst-29292	98	9	evidenced	evidence	VERB
ajst-29292	98	10	by	by	ADP
ajst-29292	98	11	the	the	DET
ajst-29292	98	12	evaluation	evaluation	NOUN
ajst-29292	98	13	metrics	metric	NOUN
ajst-29292	98	14	,	,	PUNCT
ajst-29292	98	15	and	and	CCONJ
ajst-29292	98	16	effectively	effectively	ADV
ajst-29292	98	17	avoided	avoid	VERB
ajst-29292	98	18	overfitting	overfitting	NOUN
ajst-29292	98	19	.	.	PUNCT
ajst-29292	99	1	the	the	DET
ajst-29292	99	2	visualization	visualization	NOUN
ajst-29292	99	3	of	of	ADP
ajst-29292	99	4	results	result	NOUN
ajst-29292	99	5	further	far	ADV
ajst-29292	99	6	supported	support	VERB
ajst-29292	99	7	the	the	DET
ajst-29292	99	8	reliability	reliability	NOUN
ajst-29292	99	9	and	and	CCONJ
ajst-29292	99	10	accuracy	accuracy	NOUN
ajst-29292	99	11	of	of	ADP
ajst-29292	99	12	the	the	DET
ajst-29292	99	13	selected	select	VERB
ajst-29292	99	14	models	model	NOUN
ajst-29292	99	15	.	.	PUNCT
ajst-29292	100	1	in	in	ADP
ajst-29292	100	2	conclusion	conclusion	NOUN
ajst-29292	100	3	,	,	PUNCT
ajst-29292	100	4	this	this	DET
ajst-29292	100	5	study	study	NOUN
ajst-29292	100	6	contributes	contribute	VERB
ajst-29292	100	7	to	to	ADP
ajst-29292	100	8	the	the	DET
ajst-29292	100	9	understanding	understanding	NOUN
ajst-29292	100	10	of	of	ADP
ajst-29292	100	11	the	the	DET
ajst-29292	100	12	efficacy	efficacy	NOUN
ajst-29292	100	13	of	of	ADP
ajst-29292	100	14	novel	novel	ADJ
ajst-29292	100	15	sedative	sedative	ADJ
ajst-29292	100	16	medications	medication	NOUN
ajst-29292	100	17	and	and	CCONJ
ajst-29292	100	18	demonstrates	demonstrate	VERB
ajst-29292	100	19	the	the	DET
ajst-29292	100	20	potential	potential	NOUN
ajst-29292	100	21	of	of	ADP
ajst-29292	100	22	machine	machine	NOUN
ajst-29292	100	23	learning	learn	VERB
ajst-29292	100	24	in	in	ADP
ajst-29292	100	25	predicting	predict	VERB
ajst-29292	100	26	sedative	sedative	ADJ
ajst-29292	100	27	effects	effect	NOUN
ajst-29292	100	28	based	base	VERB
ajst-29292	100	29	on	on	ADP
ajst-29292	100	30	patient	patient	ADJ
ajst-29292	100	31	data	datum	NOUN
ajst-29292	100	32	.	.	PUNCT
ajst-29292	101	1	future	future	ADJ
ajst-29292	101	2	research	research	NOUN
ajst-29292	101	3	could	could	AUX
ajst-29292	101	4	explore	explore	VERB
ajst-29292	101	5	additional	additional	ADJ
ajst-29292	101	6	physiological	physiological	ADJ
ajst-29292	101	7	indicators	indicator	NOUN
ajst-29292	101	8	,	,	PUNCT
ajst-29292	101	9	larger	large	ADJ
ajst-29292	101	10	sample	sample	NOUN
ajst-29292	101	11	sizes	size	NOUN
ajst-29292	101	12	,	,	PUNCT
ajst-29292	101	13	and	and	CCONJ
ajst-29292	101	14	longer	long	ADJ
ajst-29292	101	15	observation	observation	NOUN
ajst-29292	101	16	periods	period	NOUN
ajst-29292	101	17	to	to	PART
ajst-29292	101	18	further	far	ADV
ajst-29292	101	19	validate	validate	VERB
ajst-29292	101	20	and	and	CCONJ
ajst-29292	101	21	refine	refine	VERB
ajst-29292	101	22	these	these	DET
ajst-29292	101	23	findings	finding	NOUN
ajst-29292	101	24	.	.	PUNCT
ajst-29292	102	1	references	reference	NOUN
ajst-29292	102	2	[	[	X
ajst-29292	102	3	1	1	NUM
ajst-29292	102	4	]	]	PUNCT
ajst-29292	102	5	p.	p.	PROPN
ajst-29292	102	6	b.	b.	PROPN
ajst-29292	103	1	dao	dao	PROPN
ajst-29292	103	2	,	,	PUNCT
ajst-29292	103	3	“	"	PUNCT
ajst-29292	103	4	on	on	ADP
ajst-29292	103	5	wilcoxon	wilcoxon	PROPN
ajst-29292	103	6	rank	rank	PROPN
ajst-29292	103	7	sum	sum	PROPN
ajst-29292	103	8	test	test	NOUN
ajst-29292	103	9	for	for	ADP
ajst-29292	103	10	condition	condition	NOUN
ajst-29292	103	11	monitoring	monitoring	NOUN
ajst-29292	103	12	and	and	CCONJ
ajst-29292	103	13	fault	fault	VERB
ajst-29292	103	14	detection	detection	NOUN
ajst-29292	103	15	of	of	ADP
ajst-29292	103	16	wind	wind	NOUN
ajst-29292	103	17	turbines	turbine	NOUN
ajst-29292	103	18	,	,	PUNCT
ajst-29292	103	19	”	"	PUNCT
ajst-29292	103	20	applied	apply	VERB
ajst-29292	103	21	energy	energy	NOUN
ajst-29292	103	22	,	,	PUNCT
ajst-29292	103	23	vol	vol	NOUN
ajst-29292	103	24	.	.	PROPN
ajst-29292	103	25	318	318	NUM
ajst-29292	103	26	,	,	PUNCT
ajst-29292	103	27	p.	p.	NOUN
ajst-29292	103	28	119209	119209	NUM
ajst-29292	103	29	,	,	PUNCT
ajst-29292	103	30	jul	jul	PROPN
ajst-29292	103	31	.	.	PROPN
ajst-29292	103	32	2022	2022	NUM
ajst-29292	103	33	.	.	PUNCT
ajst-29292	103	34	89	89	NUM
ajst-29292	104	1	[	[	SYM
ajst-29292	104	2	2	2	NUM
ajst-29292	104	3	]	]	PUNCT
ajst-29292	104	4	m.	m.	PROPN
ajst-29292	104	5	r.	r.	PROPN
ajst-29292	104	6	simi	simi	PROPN
ajst-29292	104	7	,	,	PUNCT
ajst-29292	104	8	b.	b.	PROPN
ajst-29292	104	9	k.	k.	PROPN
ajst-29292	104	10	bindhu	bindhu	PROPN
ajst-29292	104	11	,	,	PUNCT
ajst-29292	104	12	a.	a.	NOUN
ajst-29292	104	13	varghese	varghese	PROPN
ajst-29292	104	14	,	,	PUNCT
ajst-29292	104	15	and	and	CCONJ
ajst-29292	104	16	m.	m.	PROPN
ajst-29292	104	17	r.	r.	PROPN
ajst-29292	104	18	rani	rani	PROPN
ajst-29292	104	19	,	,	PUNCT
ajst-29292	104	20	“	"	PUNCT
ajst-29292	104	21	optimization	optimization	NOUN
ajst-29292	104	22	of	of	ADP
ajst-29292	104	23	drastica	drastica	NOUN
ajst-29292	104	24	vulnerability	vulnerability	NOUN
ajst-29292	104	25	assessment	assessment	NOUN
ajst-29292	104	26	model	model	NOUN
ajst-29292	104	27	by	by	ADP
ajst-29292	104	28	wilcoxon	wilcoxon	PROPN
ajst-29292	104	29	rank	rank	PROPN
ajst-29292	104	30	sum	sum	PROPN
ajst-29292	104	31	non	non	PRON
ajst-29292	104	32	parametrical	parametrical	ADJ
ajst-29292	104	33	statistical	statistical	ADJ
ajst-29292	104	34	test	test	NOUN
ajst-29292	104	35	,	,	PUNCT
ajst-29292	104	36	”	"	PUNCT
ajst-29292	104	37	materials	material	NOUN
ajst-29292	104	38	today	today	NOUN
ajst-29292	104	39	:	:	PUNCT
ajst-29292	104	40	proceedings	proceeding	NOUN
ajst-29292	104	41	,	,	PUNCT
ajst-29292	104	42	vol	vol	NOUN
ajst-29292	104	43	.	.	PROPN
ajst-29292	104	44	58	58	NUM
ajst-29292	104	45	,	,	PUNCT
ajst-29292	104	46	pp	pp	ADJ
ajst-29292	104	47	.	.	PUNCT
ajst-29292	105	1	121–127	121–127	NUM
ajst-29292	105	2	,	,	PUNCT
ajst-29292	105	3	jan	jan	PROPN
ajst-29292	105	4	.	.	PROPN
ajst-29292	105	5	2022	2022	NUM
ajst-29292	105	6	.	.	PUNCT
ajst-29292	106	1	[	[	X
ajst-29292	106	2	3	3	NUM
ajst-29292	106	3	]	]	PUNCT
ajst-29292	106	4	a.	a.	NOUN
ajst-29292	106	5	p.	p.	PROPN
ajst-29292	106	6	nocera	nocera	PROPN
ajst-29292	106	7	,	,	PUNCT
ajst-29292	106	8	h.	h.	PROPN
ajst-29292	106	9	boudreau	boudreau	PROPN
ajst-29292	106	10	,	,	PUNCT
ajst-29292	106	11	c.	c.	PROPN
ajst-29292	106	12	j.	j.	PROPN
ajst-29292	106	13	boyd	boyd	PROPN
ajst-29292	106	14	,	,	PUNCT
ajst-29292	106	15	a.	a.	PROPN
ajst-29292	106	16	tamhane	tamhane	PROPN
ajst-29292	106	17	,	,	PUNCT
ajst-29292	106	18	k.	k.	PROPN
ajst-29292	106	19	d.	d.	PROPN
ajst-29292	106	20	martin	martin	PROPN
ajst-29292	106	21	,	,	PUNCT
ajst-29292	106	22	and	and	CCONJ
ajst-29292	106	23	s.	s.	PROPN
ajst-29292	106	24	rais	rais	PROPN
ajst-29292	106	25	-	-	PUNCT
ajst-29292	106	26	bahrami	bahrami	NOUN
ajst-29292	106	27	,	,	PUNCT
ajst-29292	106	28	“	"	PUNCT
ajst-29292	106	29	correlation	correlation	NOUN
ajst-29292	106	30	between	between	ADP
ajst-29292	106	31	h	h	NOUN
ajst-29292	106	32	-	-	PUNCT
ajst-29292	106	33	index	index	NOUN
ajst-29292	106	34	,	,	PUNCT
ajst-29292	106	35	m	m	NOUN
ajst-29292	106	36	-	-	NOUN
ajst-29292	106	37	index	index	NOUN
ajst-29292	106	38	,	,	PUNCT
ajst-29292	106	39	and	and	CCONJ
ajst-29292	106	40	academic	academic	ADJ
ajst-29292	106	41	rank	rank	NOUN
ajst-29292	106	42	in	in	ADP
ajst-29292	106	43	urology	urology	NOUN
ajst-29292	106	44	,	,	PUNCT
ajst-29292	106	45	”	"	PUNCT
ajst-29292	106	46	urology	urology	NOUN
ajst-29292	106	47	,	,	PUNCT
ajst-29292	106	48	vol	vol	NOUN
ajst-29292	106	49	.	.	PROPN
ajst-29292	106	50	189	189	NUM
ajst-29292	106	51	,	,	PUNCT
ajst-29292	106	52	pp	pp	ADJ
ajst-29292	106	53	.	.	PUNCT
ajst-29292	107	1	150–155	150–155	NUM
ajst-29292	107	2	,	,	PUNCT
ajst-29292	107	3	jul	jul	PROPN
ajst-29292	107	4	.	.	PROPN
ajst-29292	107	5	2024	2024	NUM
ajst-29292	107	6	.	.	PUNCT
ajst-29292	108	1	[	[	X
ajst-29292	108	2	4	4	X
ajst-29292	108	3	]	]	X
ajst-29292	108	4	y.	y.	PROPN
ajst-29292	108	5	jia	jia	PROPN
ajst-29292	108	6	et	et	PROPN
ajst-29292	108	7	al	al	PROPN
ajst-29292	108	8	.	.	PROPN
ajst-29292	108	9	,	,	PUNCT
ajst-29292	108	10	“	"	PUNCT
ajst-29292	108	11	prognostic	prognostic	ADJ
ajst-29292	108	12	prediction	prediction	NOUN
ajst-29292	108	13	for	for	ADP
ajst-29292	108	14	inflammatory	inflammatory	ADJ
ajst-29292	108	15	breast	breast	NOUN
ajst-29292	108	16	cancer	cancer	NOUN
ajst-29292	108	17	patients	patient	NOUN
ajst-29292	108	18	using	use	VERB
ajst-29292	108	19	random	random	ADJ
ajst-29292	108	20	survival	survival	NOUN
ajst-29292	108	21	forest	forest	NOUN
ajst-29292	108	22	modeling	modeling	NOUN
ajst-29292	108	23	,	,	PUNCT
ajst-29292	108	24	”	"	PUNCT
ajst-29292	108	25	translational	translational	ADJ
ajst-29292	108	26	oncology	oncology	NOUN
ajst-29292	108	27	,	,	PUNCT
ajst-29292	108	28	vol	vol	NOUN
ajst-29292	108	29	.	.	PROPN
ajst-29292	108	30	52	52	NUM
ajst-29292	108	31	,	,	PUNCT
ajst-29292	108	32	p.	p.	NOUN
ajst-29292	108	33	102246	102246	NUM
ajst-29292	108	34	,	,	PUNCT
ajst-29292	108	35	feb	feb	PROPN
ajst-29292	108	36	.	.	PROPN
ajst-29292	108	37	2025	2025	NUM
ajst-29292	108	38	.	.	PUNCT
ajst-29292	109	1	[	[	X
ajst-29292	109	2	5	5	NUM
ajst-29292	109	3	]	]	PUNCT
ajst-29292	109	4	b.	b.	PROPN
ajst-29292	109	5	d.	d.	PROPN
ajst-29292	109	6	simon	simon	PROPN
ajst-29292	109	7	et	et	PROPN
ajst-29292	109	8	al	al	PROPN
ajst-29292	109	9	.	.	PROPN
ajst-29292	109	10	,	,	PUNCT
ajst-29292	109	11	“	"	PUNCT
ajst-29292	109	12	automated	automate	VERB
ajst-29292	109	13	detection	detection	NOUN
ajst-29292	109	14	and	and	CCONJ
ajst-29292	109	15	grading	grading	NOUN
ajst-29292	109	16	of	of	ADP
ajst-29292	109	17	extraprostatic	extraprostatic	ADJ
ajst-29292	109	18	extension	extension	NOUN
ajst-29292	109	19	of	of	ADP
ajst-29292	109	20	prostate	prostate	NOUN
ajst-29292	109	21	cancer	cancer	NOUN
ajst-29292	109	22	at	at	ADP
ajst-29292	109	23	mri	mri	NOUN
ajst-29292	109	24	via	via	ADP
ajst-29292	109	25	cascaded	cascade	VERB
ajst-29292	109	26	deep	deep	ADJ
ajst-29292	109	27	learning	learning	NOUN
ajst-29292	109	28	and	and	CCONJ
ajst-29292	109	29	random	random	ADJ
ajst-29292	109	30	forest	forest	NOUN
ajst-29292	109	31	classification	classification	NOUN
ajst-29292	109	32	,	,	PUNCT
ajst-29292	109	33	”	"	PUNCT
ajst-29292	109	34	academic	academic	ADJ
ajst-29292	109	35	radiology	radiology	NOUN
ajst-29292	109	36	,	,	PUNCT
ajst-29292	109	37	vol	vol	NOUN
ajst-29292	109	38	.	.	PROPN
ajst-29292	109	39	31	31	NUM
ajst-29292	109	40	,	,	PUNCT
ajst-29292	109	41	no	no	INTJ
ajst-29292	109	42	.	.	NOUN
ajst-29292	109	43	10	10	NUM
ajst-29292	109	44	,	,	PUNCT
ajst-29292	109	45	pp	pp	ADJ
ajst-29292	109	46	.	.	PUNCT
ajst-29292	110	1	4096–4106	4096–4106	NOUN
ajst-29292	110	2	,	,	PUNCT
ajst-29292	110	3	oct	oct	PROPN
ajst-29292	110	4	.	.	PROPN
ajst-29292	110	5	2024	2024	NUM
ajst-29292	110	6	.	.	PUNCT