id	sid	tid	token	lemma	pos
cana-4763	1	1	communications	communication	NOUN
cana-4763	1	2	on	on	ADP
cana-4763	1	3	applied	apply	VERB
cana-4763	1	4	nonlinear	nonlinear	ADJ
cana-4763	1	5	analysis	analysis	NOUN
cana-4763	1	6	issn	issn	NOUN
cana-4763	1	7	:	:	PUNCT
cana-4763	1	8	1074	1074	NUM
cana-4763	1	9	-	-	PUNCT
cana-4763	1	10	133x	133x	NUM
cana-4763	1	11	vol	vol	VERB
cana-4763	1	12	32	32	NUM
cana-4763	1	13	no	no	NOUN
cana-4763	1	14	.	.	PUNCT
cana-4763	2	1	10s	10	NOUN
cana-4763	2	2	(	(	PUNCT
cana-4763	2	3	2025	2025	NUM
cana-4763	2	4	)	)	PUNCT
cana-4763	2	5	296	296	NUM
cana-4763	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	2	7	a	a	DET
cana-4763	2	8	novel	novel	ADJ
cana-4763	2	9	approach	approach	NOUN
cana-4763	2	10	for	for	ADP
cana-4763	2	11	brain	brain	NOUN
cana-4763	2	12	tumor	tumor	NOUN
cana-4763	2	13	classification	classification	NOUN
cana-4763	2	14	using	use	VERB
cana-4763	2	15	bilateral	bilateral	ADJ
cana-4763	2	16	filtering	filtering	NOUN
cana-4763	2	17	and	and	CCONJ
cana-4763	2	18	cascade	cascade	NOUN
cana-4763	2	19	rf	rf	NOUN
cana-4763	2	20	-	-	PUNCT
cana-4763	2	21	svm	svm	PROPN
cana-4763	2	22	dr	dr	PROPN
cana-4763	2	23	.	.	PROPN
cana-4763	2	24	afroz	afroz	PROPN
cana-4763	2	25	pasha1	pasha1	PROPN
cana-4763	2	26	,	,	PUNCT
cana-4763	2	27	dr	dr	PROPN
cana-4763	2	28	.	.	PROPN
cana-4763	2	29	prasad	prasad	PROPN
cana-4763	2	30	p	p	PROPN
cana-4763	2	31	s2	s2	PROPN
cana-4763	2	32	,	,	PUNCT
cana-4763	3	1	dr	dr	PROPN
cana-4763	3	2	.	.	PROPN
cana-4763	3	3	mrutyunjaya	mrutyunjaya	PROPN
cana-4763	3	4	m	m	PROPN
cana-4763	3	5	s3	s3	PROPN
cana-4763	3	6	,	,	PUNCT
cana-4763	3	7	dr	dr	PROPN
cana-4763	3	8	.	.	PROPN
cana-4763	3	9	karthik	karthik	PROPN
cana-4763	3	10	b	b	PROPN
cana-4763	3	11	u4	u4	PROPN
cana-4763	3	12	,	,	PUNCT
cana-4763	3	13	dr	dr	PROPN
cana-4763	3	14	.	.	PROPN
cana-4763	3	15	varalakshmi	varalakshmi	PROPN
cana-4763	3	16	k	k	PROPN
cana-4763	3	17	r5	r5	PROPN
cana-4763	3	18	,	,	PUNCT
cana-4763	3	19	ms	ms	PROPN
cana-4763	3	20	.	.	PROPN
cana-4763	3	21	rekha	rekha	PROPN
cana-4763	3	22	m	m	PROPN
cana-4763	3	23	s6	s6	PROPN
cana-4763	3	24	1assistant	1assistant	NUM
cana-4763	3	25	professor	professor	NOUN
cana-4763	3	26	senior	senior	ADJ
cana-4763	3	27	scale	scale	NOUN
cana-4763	3	28	,	,	PUNCT
cana-4763	3	29	presidency	presidency	NOUN
cana-4763	3	30	university	university	NOUN
cana-4763	3	31	.	.	PUNCT
cana-4763	4	1	e	e	X
cana-4763	4	2	-	-	NOUN
cana-4763	4	3	mail	mail	NOUN
cana-4763	4	4	i	i	NOUN
cana-4763	4	5	d	d	PROPN
cana-4763	4	6	:	:	PUNCT
cana-4763	4	7	afrozpasha@presidencyuniversity.in	afrozpasha@presidencyuniversity.in	PROPN
cana-4763	4	8	2	2	NUM
cana-4763	4	9	assistant	assistant	NOUN
cana-4763	4	10	professor	professor	NOUN
cana-4763	4	11	selection	selection	NOUN
cana-4763	4	12	grade	grade	NOUN
cana-4763	4	13	,	,	PUNCT
cana-4763	4	14	presidency	presidency	NOUN
cana-4763	4	15	university	university	NOUN
cana-4763	4	16	.	.	PUNCT
cana-4763	5	1	e	e	X
cana-4763	5	2	-	-	NOUN
cana-4763	5	3	mail	mail	NOUN
cana-4763	5	4	i	i	NOUN
cana-4763	5	5	d	d	PROPN
cana-4763	5	6	:	:	PUNCT
cana-4763	5	7	prasadps@presidencyuniversity.in	prasadps@presidencyuniversity.in	PROPN
cana-4763	5	8	3	3	NUM
cana-4763	5	9	associate	associate	NOUN
cana-4763	5	10	professor	professor	NOUN
cana-4763	5	11	,	,	PUNCT
cana-4763	5	12	department	department	PROPN
cana-4763	5	13	of	of	ADP
cana-4763	5	14	cse	cse	PROPN
cana-4763	5	15	(	(	PUNCT
cana-4763	5	16	data	data	NOUN
cana-4763	5	17	science	science	NOUN
cana-4763	5	18	)	)	PUNCT
cana-4763	5	19	,	,	PUNCT
cana-4763	5	20	r	r	NOUN
cana-4763	5	21	l	l	PROPN
cana-4763	5	22	jalappa	jalappa	PROPN
cana-4763	5	23	institute	institute	PROPN
cana-4763	5	24	of	of	ADP
cana-4763	5	25	technology	technology	PROPN
cana-4763	5	26	.	.	PUNCT
cana-4763	6	1	e	e	X
cana-4763	6	2	-	-	NOUN
cana-4763	6	3	mail	mail	NOUN
cana-4763	6	4	i	i	NOUN
cana-4763	6	5	d	d	NOUN
cana-4763	6	6	:	:	PUNCT
cana-4763	6	7	mrutyunjayams@gmail.com	mrutyunjayams@gmail.com	X
cana-4763	6	8	4	4	NUM
cana-4763	6	9	assistant	assistant	NOUN
cana-4763	6	10	professor	professor	NOUN
cana-4763	6	11	,	,	PUNCT
cana-4763	6	12	department	department	PROPN
cana-4763	6	13	of	of	ADP
cana-4763	6	14	cse	cse	PROPN
cana-4763	6	15	(	(	PUNCT
cana-4763	6	16	data	data	NOUN
cana-4763	6	17	science	science	NOUN
cana-4763	6	18	)	)	PUNCT
cana-4763	6	19	,	,	PUNCT
cana-4763	6	20	r	r	NOUN
cana-4763	6	21	l	l	PROPN
cana-4763	6	22	jalappa	jalappa	PROPN
cana-4763	6	23	institute	institute	PROPN
cana-4763	6	24	of	of	ADP
cana-4763	6	25	technology	technology	PROPN
cana-4763	6	26	.	.	PUNCT
cana-4763	7	1	e	e	X
cana-4763	7	2	-	-	NOUN
cana-4763	7	3	mail	mail	NOUN
cana-4763	7	4	id:karthikbu1994@gmail.com	id:karthikbu1994@gmail.com	X
cana-4763	7	5	5associate	5associate	NUM
cana-4763	7	6	professor	professor	NOUN
cana-4763	7	7	,	,	PUNCT
cana-4763	7	8	department	department	NOUN
cana-4763	7	9	of	of	ADP
cana-4763	7	10	cse	cse	PROPN
cana-4763	7	11	,	,	PUNCT
cana-4763	7	12	r	r	PROPN
cana-4763	7	13	l	l	PROPN
cana-4763	7	14	jalappa	jalappa	PROPN
cana-4763	7	15	institute	institute	PROPN
cana-4763	7	16	of	of	ADP
cana-4763	7	17	technology	technology	PROPN
cana-4763	7	18	.	.	PUNCT
cana-4763	8	1	e	e	X
cana-4763	8	2	-	-	NOUN
cana-4763	8	3	mail	mail	NOUN
cana-4763	8	4	id:varamza@gmail.com	id:varamza@gmail.com	NOUN
cana-4763	8	5	6	6	NUM
cana-4763	8	6	.	.	PUNCT
cana-4763	8	7	assistant	assistant	PROPN
cana-4763	8	8	professor	professor	NOUN
cana-4763	8	9	,	,	PUNCT
cana-4763	8	10	department	department	PROPN
cana-4763	8	11	of	of	ADP
cana-4763	8	12	cse	cse	PROPN
cana-4763	8	13	,	,	PUNCT
cana-4763	8	14	r	r	PROPN
cana-4763	8	15	l	l	PROPN
cana-4763	8	16	jalappa	jalappa	PROPN
cana-4763	8	17	institute	institute	PROPN
cana-4763	8	18	of	of	ADP
cana-4763	8	19	technology	technology	PROPN
cana-4763	8	20	.	.	PUNCT
cana-4763	9	1	e	e	X
cana-4763	9	2	-	-	NOUN
cana-4763	9	3	mail	mail	NOUN
cana-4763	9	4	id:rekha061264@gmail.com	id:rekha061264@gmail.com	NOUN
cana-4763	9	5	article	article	NOUN
cana-4763	9	6	history	history	NOUN
cana-4763	9	7	:	:	PUNCT
cana-4763	9	8	received	receive	VERB
cana-4763	9	9	:	:	PUNCT
cana-4763	9	10	12	12	NUM
cana-4763	9	11	-	-	SYM
cana-4763	9	12	01	01	NUM
cana-4763	9	13	-	-	PUNCT
cana-4763	9	14	2025	2025	NUM
cana-4763	9	15	revised	revise	VERB
cana-4763	9	16	:	:	PUNCT
cana-4763	9	17	15	15	NUM
cana-4763	9	18	-	-	NUM
cana-4763	9	19	02	02	NUM
cana-4763	9	20	-	-	PUNCT
cana-4763	9	21	2025	2025	NUM
cana-4763	9	22	accepted	accept	VERB
cana-4763	9	23	:	:	PUNCT
cana-4763	9	24	01	01	NUM
cana-4763	9	25	-	-	SYM
cana-4763	9	26	03	03	NUM
cana-4763	9	27	-	-	PUNCT
cana-4763	9	28	2025	2025	NUM
cana-4763	9	29	abstract	abstract	NOUN
cana-4763	9	30	:	:	PUNCT
cana-4763	9	31	this	this	DET
cana-4763	9	32	work	work	NOUN
cana-4763	9	33	introduces	introduce	VERB
cana-4763	9	34	a	a	DET
cana-4763	9	35	new	new	ADJ
cana-4763	9	36	approach	approach	NOUN
cana-4763	9	37	to	to	ADP
cana-4763	9	38	classifying	classify	VERB
cana-4763	9	39	brain	brain	NOUN
cana-4763	9	40	tumors	tumor	NOUN
cana-4763	9	41	that	that	PRON
cana-4763	9	42	integrates	integrate	VERB
cana-4763	9	43	various	various	ADJ
cana-4763	9	44	techniques	technique	NOUN
cana-4763	9	45	to	to	PART
cana-4763	9	46	maximize	maximize	VERB
cana-4763	9	47	classification	classification	NOUN
cana-4763	9	48	performance	performance	NOUN
cana-4763	9	49	.	.	PUNCT
cana-4763	10	1	bilateral	bilateral	ADJ
cana-4763	10	2	filtering	filtering	NOUN
cana-4763	10	3	is	be	AUX
cana-4763	10	4	applied	apply	VERB
cana-4763	10	5	as	as	ADP
cana-4763	10	6	preprocessing	preprocesse	VERB
cana-4763	10	7	in	in	ADP
cana-4763	10	8	the	the	DET
cana-4763	10	9	initial	initial	ADJ
cana-4763	10	10	stage	stage	NOUN
cana-4763	10	11	to	to	PART
cana-4763	10	12	remove	remove	VERB
cana-4763	10	13	noise	noise	NOUN
cana-4763	10	14	from	from	ADP
cana-4763	10	15	medical	medical	ADJ
cana-4763	10	16	images	image	NOUN
cana-4763	10	17	without	without	ADP
cana-4763	10	18	degrading	degrade	VERB
cana-4763	10	19	the	the	DET
cana-4763	10	20	borders	border	NOUN
cana-4763	10	21	of	of	ADP
cana-4763	10	22	tumor	tumor	NOUN
cana-4763	10	23	areas	area	NOUN
cana-4763	10	24	.	.	PUNCT
cana-4763	11	1	in	in	ADP
cana-4763	11	2	order	order	NOUN
cana-4763	11	3	to	to	PART
cana-4763	11	4	isolate	isolate	VERB
cana-4763	11	5	the	the	DET
cana-4763	11	6	textural	textural	ADJ
cana-4763	11	7	characteristics	characteristic	NOUN
cana-4763	11	8	of	of	ADP
cana-4763	11	9	the	the	DET
cana-4763	11	10	tumor	tumor	NOUN
cana-4763	11	11	,	,	PUNCT
cana-4763	11	12	which	which	PRON
cana-4763	11	13	play	play	VERB
cana-4763	11	14	a	a	DET
cana-4763	11	15	key	key	ADJ
cana-4763	11	16	role	role	NOUN
cana-4763	11	17	in	in	ADP
cana-4763	11	18	differentiating	differentiate	VERB
cana-4763	11	19	the	the	DET
cana-4763	11	20	types	type	NOUN
cana-4763	11	21	,	,	PUNCT
cana-4763	11	22	the	the	DET
cana-4763	11	23	local	local	ADJ
cana-4763	11	24	binary	binary	ADJ
cana-4763	11	25	pattern	pattern	NOUN
cana-4763	11	26	(	(	PUNCT
cana-4763	11	27	lbp	lbp	NOUN
cana-4763	11	28	)	)	PUNCT
cana-4763	11	29	technique	technique	NOUN
cana-4763	11	30	was	be	AUX
cana-4763	11	31	utilized	utilize	VERB
cana-4763	11	32	.	.	PUNCT
cana-4763	12	1	the	the	DET
cana-4763	12	2	improved	improve	VERB
cana-4763	12	3	grey	grey	NOUN
cana-4763	12	4	wolf	wolf	PROPN
cana-4763	12	5	optimization	optimization	NOUN
cana-4763	12	6	(	(	PUNCT
cana-4763	12	7	gwo	gwo	NOUN
cana-4763	12	8	)	)	PUNCT
cana-4763	12	9	algorithm	algorithm	NOUN
cana-4763	12	10	was	be	AUX
cana-4763	12	11	utilized	utilize	VERB
cana-4763	12	12	for	for	ADP
cana-4763	12	13	optimizing	optimize	VERB
cana-4763	12	14	the	the	DET
cana-4763	12	15	feature	feature	NOUN
cana-4763	12	16	set	set	VERB
cana-4763	12	17	by	by	ADP
cana-4763	12	18	removing	remove	VERB
cana-4763	12	19	redundant	redundant	ADJ
cana-4763	12	20	features	feature	NOUN
cana-4763	12	21	in	in	ADP
cana-4763	12	22	order	order	NOUN
cana-4763	12	23	to	to	PART
cana-4763	12	24	improve	improve	VERB
cana-4763	12	25	classification	classification	NOUN
cana-4763	12	26	.	.	PUNCT
cana-4763	13	1	a	a	DET
cana-4763	13	2	random	random	ADJ
cana-4763	13	3	forest	forest	NOUN
cana-4763	13	4	classifier	classifier	NOUN
cana-4763	13	5	is	be	AUX
cana-4763	13	6	employed	employ	VERB
cana-4763	13	7	for	for	ADP
cana-4763	13	8	removing	remove	VERB
cana-4763	13	9	irrelevant	irrelevant	ADJ
cana-4763	13	10	features	feature	NOUN
cana-4763	13	11	,	,	PUNCT
cana-4763	13	12	and	and	CCONJ
cana-4763	13	13	finally	finally	ADV
cana-4763	13	14	,	,	PUNCT
cana-4763	13	15	the	the	DET
cana-4763	13	16	classification	classification	NOUN
cana-4763	13	17	is	be	AUX
cana-4763	13	18	performed	perform	VERB
cana-4763	13	19	by	by	ADP
cana-4763	13	20	a	a	DET
cana-4763	13	21	support	support	NOUN
cana-4763	13	22	vector	vector	NOUN
cana-4763	13	23	machine	machine	NOUN
cana-4763	13	24	classifier	classifier	NOUN
cana-4763	13	25	.	.	PUNCT
cana-4763	14	1	this	this	PRON
cana-4763	14	2	is	be	AUX
cana-4763	14	3	stage	stage	NOUN
cana-4763	14	4	one	one	NUM
cana-4763	14	5	in	in	ADP
cana-4763	14	6	classification	classification	NOUN
cana-4763	14	7	.	.	PUNCT
cana-4763	15	1	with	with	ADP
cana-4763	15	2	the	the	DET
cana-4763	15	3	method	method	NOUN
cana-4763	15	4	proposed	propose	VERB
cana-4763	15	5	within	within	ADP
cana-4763	15	6	this	this	DET
cana-4763	15	7	paper	paper	NOUN
cana-4763	15	8	,	,	PUNCT
cana-4763	15	9	brain	brain	NOUN
cana-4763	15	10	tumors	tumor	NOUN
cana-4763	15	11	are	be	AUX
cana-4763	15	12	correctly	correctly	ADV
cana-4763	15	13	classified	classified	ADJ
cana-4763	15	14	with	with	ADP
cana-4763	15	15	impressive	impressive	ADJ
cana-4763	15	16	99.3	99.3	NUM
cana-4763	15	17	percent	percent	NOUN
cana-4763	15	18	accuracy	accuracy	NOUN
cana-4763	15	19	.	.	PUNCT
cana-4763	16	1	the	the	DET
cana-4763	16	2	very	very	ADV
cana-4763	16	3	high	high	ADJ
cana-4763	16	4	accuracy	accuracy	NOUN
cana-4763	16	5	suggests	suggest	VERB
cana-4763	16	6	the	the	DET
cana-4763	16	7	robustness	robustness	NOUN
cana-4763	16	8	of	of	ADP
cana-4763	16	9	the	the	DET
cana-4763	16	10	union	union	NOUN
cana-4763	16	11	of	of	ADP
cana-4763	16	12	strong	strong	ADJ
cana-4763	16	13	classification	classification	NOUN
cana-4763	16	14	methods	method	NOUN
cana-4763	16	15	and	and	CCONJ
cana-4763	16	16	novel	novel	ADJ
cana-4763	16	17	feature	feature	NOUN
cana-4763	16	18	selection	selection	NOUN
cana-4763	16	19	methods	method	NOUN
cana-4763	16	20	.	.	PUNCT
cana-4763	17	1	apart	apart	ADV
cana-4763	17	2	from	from	ADP
cana-4763	17	3	its	its	PRON
cana-4763	17	4	use	use	NOUN
cana-4763	17	5	in	in	ADP
cana-4763	17	6	imagine	imagine	NOUN
cana-4763	17	7	of	of	ADP
cana-4763	17	8	brain	brain	NOUN
cana-4763	17	9	tumors	tumor	NOUN
cana-4763	17	10	,	,	PUNCT
cana-4763	17	11	the	the	DET
cana-4763	17	12	method	method	NOUN
cana-4763	17	13	can	can	AUX
cana-4763	17	14	be	be	AUX
cana-4763	17	15	applied	apply	VERB
cana-4763	17	16	to	to	ADP
cana-4763	17	17	a	a	DET
cana-4763	17	18	broad	broad	ADJ
cana-4763	17	19	variety	variety	NOUN
cana-4763	17	20	of	of	ADP
cana-4763	17	21	other	other	ADJ
cana-4763	17	22	medical	medical	ADJ
cana-4763	17	23	image	image	NOUN
cana-4763	17	24	problems	problem	NOUN
cana-4763	17	25	to	to	PART
cana-4763	17	26	make	make	VERB
cana-4763	17	27	diagnosis	diagnosis	NOUN
cana-4763	17	28	highly	highly	ADV
cana-4763	17	29	efficient	efficient	ADJ
cana-4763	17	30	and	and	CCONJ
cana-4763	17	31	credible	credible	ADJ
cana-4763	17	32	.	.	PUNCT
cana-4763	18	1	keywords	keyword	NOUN
cana-4763	18	2	:	:	PUNCT
cana-4763	18	3	bilateral	bilateral	ADJ
cana-4763	18	4	filter	filter	NOUN
cana-4763	18	5	,	,	PUNCT
cana-4763	18	6	grey	grey	ADJ
cana-4763	18	7	wolf	wolf	PROPN
cana-4763	18	8	optimization	optimization	NOUN
cana-4763	18	9	,	,	PUNCT
cana-4763	18	10	local	local	ADJ
cana-4763	18	11	binary	binary	NOUN
cana-4763	18	12	pattern	pattern	NOUN
cana-4763	18	13	,	,	PUNCT
cana-4763	18	14	tumour	tumour	NOUN
cana-4763	18	15	classification	classification	NOUN
cana-4763	18	16	introduction	introduction	NOUN
cana-4763	18	17	the	the	DET
cana-4763	18	18	classification	classification	NOUN
cana-4763	18	19	of	of	ADP
cana-4763	18	20	brain	brain	NOUN
cana-4763	18	21	tumors	tumor	NOUN
cana-4763	18	22	plays	play	VERB
cana-4763	18	23	a	a	DET
cana-4763	18	24	vital	vital	ADJ
cana-4763	18	25	role	role	NOUN
cana-4763	18	26	in	in	ADP
cana-4763	18	27	medical	medical	ADJ
cana-4763	18	28	diagnostic	diagnostic	ADJ
cana-4763	18	29	practices	practice	NOUN
cana-4763	18	30	.	.	PUNCT
cana-4763	19	1	medical	medical	ADJ
cana-4763	19	2	professionals	professional	NOUN
cana-4763	19	3	rely	rely	VERB
cana-4763	19	4	on	on	ADP
cana-4763	19	5	this	this	DET
cana-4763	19	6	method	method	NOUN
cana-4763	19	7	to	to	PART
cana-4763	19	8	differentiate	differentiate	VERB
cana-4763	19	9	different	different	ADJ
cana-4763	19	10	tumor	tumor	NOUN
cana-4763	19	11	types	type	NOUN
cana-4763	19	12	for	for	ADP
cana-4763	19	13	creating	create	VERB
cana-4763	19	14	specific	specific	ADJ
cana-4763	19	15	treatment	treatment	NOUN
cana-4763	19	16	approaches	approach	NOUN
cana-4763	19	17	.	.	PUNCT
cana-4763	20	1	multiple	multiple	ADJ
cana-4763	20	2	organizations	organization	NOUN
cana-4763	20	3	have	have	AUX
cana-4763	20	4	changed	change	VERB
cana-4763	20	5	the	the	DET
cana-4763	20	6	system	system	NOUN
cana-4763	20	7	by	by	ADP
cana-4763	20	8	which	which	PRON
cana-4763	20	9	they	they	PRON
cana-4763	20	10	categorize	categorize	VERB
cana-4763	20	11	brain	brain	NOUN
cana-4763	20	12	tumors	tumor	NOUN
cana-4763	20	13	since	since	SCONJ
cana-4763	20	14	the	the	DET
cana-4763	20	15	initial	initial	ADJ
cana-4763	20	16	publication	publication	NOUN
cana-4763	20	17	of	of	ADP
cana-4763	20	18	formal	formal	ADJ
cana-4763	20	19	guidelines	guideline	NOUN
cana-4763	20	20	[	[	X
cana-4763	20	21	1][2][3][4	1][2][3][4	NUM
cana-4763	20	22	]	]	PUNCT
cana-4763	20	23	.	.	PUNCT
cana-4763	21	1	advanced	advanced	ADJ
cana-4763	21	2	automated	automate	VERB
cana-4763	21	3	systems	system	NOUN
cana-4763	21	4	represented	represent	VERB
cana-4763	21	5	through	through	ADP
cana-4763	21	6	artificial	artificial	ADJ
cana-4763	21	7	intelligence	intelligence	NOUN
cana-4763	21	8	(	(	PUNCT
cana-4763	21	9	ai	ai	NOUN
cana-4763	21	10	)	)	PUNCT
cana-4763	22	1	[	[	X
cana-4763	22	2	5	5	NUM
cana-4763	22	3	]	]	PUNCT
cana-4763	22	4	and	and	CCONJ
cana-4763	22	5	machine	machine	NOUN
cana-4763	22	6	learning	learning	NOUN
cana-4763	22	7	(	(	PUNCT
cana-4763	22	8	ml)[6	ml)[6	X
cana-4763	22	9	]	]	PUNCT
cana-4763	22	10	have	have	AUX
cana-4763	22	11	introduced	introduce	VERB
cana-4763	22	12	more	more	ADV
cana-4763	22	13	accurate	accurate	ADJ
cana-4763	22	14	approaches	approach	NOUN
cana-4763	22	15	which	which	PRON
cana-4763	22	16	replaced	replace	VERB
cana-4763	22	17	previous	previous	ADJ
cana-4763	22	18	manual	manual	ADJ
cana-4763	22	19	procedures	procedure	NOUN
cana-4763	22	20	.	.	PUNCT
cana-4763	23	1	through	through	ADP
cana-4763	23	2	their	their	PRON
cana-4763	23	3	diagnostic	diagnostic	ADJ
cana-4763	23	4	precision	precision	NOUN
cana-4763	23	5	advancements	advancement	NOUN
cana-4763	23	6	these	these	DET
cana-4763	23	7	modern	modern	ADJ
cana-4763	23	8	tools	tool	NOUN
cana-4763	23	9	have	have	AUX
cana-4763	23	10	brought	bring	VERB
cana-4763	23	11	about	about	ADP
cana-4763	23	12	extensive	extensive	ADJ
cana-4763	23	13	structural	structural	ADJ
cana-4763	23	14	changes	change	NOUN
cana-4763	23	15	to	to	ADP
cana-4763	23	16	the	the	DET
cana-4763	23	17	field	field	NOUN
cana-4763	23	18	.	.	PUNCT
cana-4763	24	1	medical	medical	ADJ
cana-4763	24	2	professionals	professional	NOUN
cana-4763	24	3	now	now	ADV
cana-4763	24	4	have	have	AUX
cana-4763	24	5	enhanced	enhance	VERB
cana-4763	24	6	abilities	ability	NOUN
cana-4763	24	7	to	to	PART
cana-4763	24	8	choose	choose	VERB
cana-4763	24	9	treatments	treatment	NOUN
cana-4763	24	10	faster	fast	ADV
cana-4763	24	11	with	with	ADP
cana-4763	24	12	better	well	ADJ
cana-4763	24	13	intellectual	intellectual	ADJ
cana-4763	24	14	decision	decision	NOUN
cana-4763	24	15	-	-	PUNCT
cana-4763	24	16	making	make	VERB
cana-4763	24	17	capabilities	capability	NOUN
cana-4763	24	18	and	and	CCONJ
cana-4763	24	19	specific	specific	ADJ
cana-4763	24	20	patient	patient	NOUN
cana-4763	24	21	requirements	requirement	NOUN
cana-4763	24	22	consideration	consideration	NOUN
cana-4763	24	23	.	.	PUNCT
cana-4763	25	1	the	the	DET
cana-4763	25	2	application	application	NOUN
cana-4763	25	3	of	of	ADP
cana-4763	25	4	artificial	artificial	ADJ
cana-4763	25	5	intelligence	intelligence	NOUN
cana-4763	25	6	with	with	ADP
cana-4763	25	7	machine	machine	NOUN
cana-4763	25	8	learning	learn	VERB
cana-4763	25	9	for	for	ADP
cana-4763	25	10	brain	brain	NOUN
cana-4763	25	11	tumor	tumor	NOUN
cana-4763	25	12	classification	classification	NOUN
cana-4763	25	13	serves	serve	VERB
cana-4763	25	14	two	two	NUM
cana-4763	25	15	purposes	purpose	NOUN
cana-4763	25	16	:	:	PUNCT
cana-4763	25	17	it	it	PRON
cana-4763	25	18	leads	lead	VERB
cana-4763	25	19	to	to	ADP
cana-4763	25	20	better	well	ADJ
cana-4763	25	21	patient	patient	ADJ
cana-4763	25	22	healthcare	healthcare	NOUN
cana-4763	25	23	experiences	experience	NOUN
cana-4763	25	24	and	and	CCONJ
cana-4763	25	25	it	it	PRON
cana-4763	25	26	enables	enable	VERB
cana-4763	25	27	new	new	ADJ
cana-4763	25	28	discoveries	discovery	NOUN
cana-4763	25	29	in	in	ADP
cana-4763	25	30	cancer	cancer	NOUN
cana-4763	25	31	medical	medical	ADJ
cana-4763	25	32	practices	practice	NOUN
cana-4763	25	33	.	.	PUNCT
cana-4763	26	1	in	in	ADP
cana-4763	26	2	the	the	DET
cana-4763	26	3	approaching	approach	VERB
cana-4763	26	4	years	year	NOUN
cana-4763	26	5	mailto:prasadps@presidencyuniversity.in	mailto:prasadps@presidencyuniversity.in	X
cana-4763	26	6	mailto:varamza@gmail.com	mailto:varamza@gmail.com	PROPN
cana-4763	26	7	communications	communication	NOUN
cana-4763	26	8	on	on	ADP
cana-4763	26	9	applied	apply	VERB
cana-4763	26	10	nonlinear	nonlinear	ADJ
cana-4763	26	11	analysis	analysis	NOUN
cana-4763	26	12	issn	issn	NOUN
cana-4763	26	13	:	:	PUNCT
cana-4763	26	14	1074	1074	NUM
cana-4763	26	15	-	-	PUNCT
cana-4763	26	16	133x	133x	NUM
cana-4763	26	17	vol	vol	VERB
cana-4763	26	18	32	32	NUM
cana-4763	26	19	no	no	NOUN
cana-4763	26	20	.	.	PUNCT
cana-4763	27	1	10s	10	NOUN
cana-4763	27	2	(	(	PUNCT
cana-4763	27	3	2025	2025	NUM
cana-4763	27	4	)	)	PUNCT
cana-4763	27	5	297	297	NUM
cana-4763	27	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	27	7	personalized	personalized	ADJ
cana-4763	27	8	medicine	medicine	NOUN
cana-4763	27	9	will	will	AUX
cana-4763	27	10	advance	advance	VERB
cana-4763	27	11	through	through	ADP
cana-4763	27	12	combining	combine	VERB
cana-4763	27	13	genomic	genomic	ADJ
cana-4763	27	14	data	datum	NOUN
cana-4763	27	15	with	with	ADP
cana-4763	27	16	modern	modern	ADJ
cana-4763	27	17	imaging	imaging	NOUN
cana-4763	27	18	technology	technology	NOUN
cana-4763	27	19	to	to	PART
cana-4763	27	20	forge	forge	VERB
cana-4763	27	21	innovative	innovative	ADJ
cana-4763	27	22	individualized	individualized	ADJ
cana-4763	27	23	treatment	treatment	NOUN
cana-4763	27	24	solutions	solution	NOUN
cana-4763	27	25	.	.	PUNCT
cana-4763	28	1	doctors	doctor	NOUN
cana-4763	28	2	could	could	AUX
cana-4763	28	3	transform	transform	VERB
cana-4763	28	4	their	their	PRON
cana-4763	28	5	complete	complete	ADJ
cana-4763	28	6	practices	practice	NOUN
cana-4763	28	7	of	of	ADP
cana-4763	28	8	brain	brain	NOUN
cana-4763	28	9	tumor	tumor	NOUN
cana-4763	28	10	diagnosis	diagnosis	NOUN
cana-4763	28	11	and	and	CCONJ
cana-4763	28	12	cancer	cancer	NOUN
cana-4763	28	13	treatment	treatment	NOUN
cana-4763	28	14	through	through	ADP
cana-4763	28	15	this	this	DET
cana-4763	28	16	comprehensive	comprehensive	ADJ
cana-4763	28	17	approach	approach	NOUN
cana-4763	28	18	which	which	PRON
cana-4763	28	19	brings	bring	VERB
cana-4763	28	20	better	well	ADJ
cana-4763	28	21	results	result	NOUN
cana-4763	28	22	and	and	CCONJ
cana-4763	28	23	better	well	ADJ
cana-4763	28	24	knowledge	knowledge	NOUN
cana-4763	28	25	of	of	ADP
cana-4763	28	26	advanced	advanced	ADJ
cana-4763	28	27	diseases	disease	NOUN
cana-4763	28	28	.	.	PUNCT
cana-4763	29	1	during	during	ADP
cana-4763	29	2	the	the	DET
cana-4763	29	3	time	time	NOUN
cana-4763	29	4	before	before	SCONJ
cana-4763	29	5	modern	modern	ADJ
cana-4763	29	6	medical	medical	ADJ
cana-4763	29	7	imaging	imaging	NOUN
cana-4763	29	8	technologies	technology	NOUN
cana-4763	29	9	radiodiagnosticians	radiodiagnostician	NOUN
cana-4763	29	10	and	and	CCONJ
cana-4763	29	11	manual	manual	ADJ
cana-4763	29	12	observation	observation	NOUN
cana-4763	29	13	techniques	technique	NOUN
cana-4763	29	14	served	serve	VERB
cana-4763	29	15	as	as	ADP
cana-4763	29	16	the	the	DET
cana-4763	29	17	keys	key	NOUN
cana-4763	29	18	to	to	ADP
cana-4763	29	19	identifying	identify	VERB
cana-4763	29	20	brain	brain	NOUN
cana-4763	29	21	tumors	tumor	NOUN
cana-4763	29	22	correctly	correctly	ADV
cana-4763	29	23	.	.	PUNCT
cana-4763	30	1	these	these	DET
cana-4763	30	2	medical	medical	ADJ
cana-4763	30	3	professionals	professional	NOUN
cana-4763	30	4	conducted	conduct	VERB
cana-4763	30	5	mri	mri	NOUN
cana-4763	30	6	and	and	CCONJ
cana-4763	30	7	ct	ct	PROPN
cana-4763	30	8	scans	scan	NOUN
cana-4763	30	9	to	to	PART
cana-4763	30	10	search	search	VERB
cana-4763	30	11	for	for	ADP
cana-4763	30	12	abnormal	abnormal	ADJ
cana-4763	30	13	tissue	tissue	NOUN
cana-4763	30	14	along	along	ADV
cana-4763	30	15	with	with	ADP
cana-4763	30	16	detecting	detect	VERB
cana-4763	30	17	tumor	tumor	NOUN
cana-4763	30	18	types	type	NOUN
cana-4763	30	19	.	.	PUNCT
cana-4763	31	1	histopathological	histopathological	ADJ
cana-4763	31	2	testing	testing	NOUN
cana-4763	31	3	established	establish	VERB
cana-4763	31	4	itself	itself	PRON
cana-4763	31	5	as	as	ADP
cana-4763	31	6	the	the	DET
cana-4763	31	7	primary	primary	ADJ
cana-4763	31	8	classification	classification	NOUN
cana-4763	31	9	method	method	NOUN
cana-4763	31	10	for	for	ADP
cana-4763	31	11	brain	brain	NOUN
cana-4763	31	12	tumors	tumor	NOUN
cana-4763	31	13	to	to	PART
cana-4763	31	14	address	address	VERB
cana-4763	31	15	the	the	DET
cana-4763	31	16	previous	previous	ADJ
cana-4763	31	17	shortcomings	shortcoming	NOUN
cana-4763	31	18	[	[	X
cana-4763	31	19	7	7	NUM
cana-4763	31	20	]	]	PUNCT
cana-4763	31	21	.	.	PUNCT
cana-4763	32	1	microscopic	microscopic	ADJ
cana-4763	32	2	study	study	NOUN
cana-4763	32	3	of	of	ADP
cana-4763	32	4	tumor	tumor	NOUN
cana-4763	32	5	samples	sample	NOUN
cana-4763	32	6	through	through	ADP
cana-4763	32	7	this	this	DET
cana-4763	32	8	method	method	NOUN
cana-4763	32	9	delivered	deliver	VERB
cana-4763	32	10	detailed	detailed	ADJ
cana-4763	32	11	information	information	NOUN
cana-4763	32	12	about	about	ADP
cana-4763	32	13	several	several	ADJ
cana-4763	32	14	tumor	tumor	NOUN
cana-4763	32	15	categories	category	NOUN
cana-4763	32	16	with	with	ADP
cana-4763	32	17	their	their	PRON
cana-4763	32	18	subtypes	subtype	NOUN
cana-4763	32	19	such	such	ADJ
cana-4763	32	20	as	as	ADP
cana-4763	32	21	pituitary	pituitary	ADJ
cana-4763	32	22	adenomas	adenoma	NOUN
cana-4763	32	23	,	,	PUNCT
cana-4763	32	24	meningiomas	meningioma	NOUN
cana-4763	32	25	,	,	PUNCT
cana-4763	32	26	and	and	CCONJ
cana-4763	32	27	gliomas	glioma	NOUN
cana-4763	32	28	.	.	PUNCT
cana-4763	33	1	the	the	DET
cana-4763	33	2	accuracy	accuracy	NOUN
cana-4763	33	3	of	of	ADP
cana-4763	33	4	this	this	DET
cana-4763	33	5	method	method	NOUN
cana-4763	33	6	was	be	AUX
cana-4763	33	7	high	high	ADJ
cana-4763	33	8	although	although	SCONJ
cana-4763	33	9	it	it	PRON
cana-4763	33	10	required	require	VERB
cana-4763	33	11	dangerous	dangerous	ADJ
cana-4763	33	12	invasive	invasive	ADJ
cana-4763	33	13	biopsies	biopsy	NOUN
cana-4763	33	14	that	that	PRON
cana-4763	33	15	were	be	AUX
cana-4763	33	16	not	not	PART
cana-4763	33	17	suitable	suitable	ADJ
cana-4763	33	18	for	for	ADP
cana-4763	33	19	tumors	tumor	NOUN
cana-4763	33	20	located	locate	VERB
cana-4763	33	21	in	in	ADP
cana-4763	33	22	complex	complex	ADJ
cana-4763	33	23	brain	brain	NOUN
cana-4763	33	24	regions	region	NOUN
cana-4763	33	25	.	.	PUNCT
cana-4763	34	1	the	the	DET
cana-4763	34	2	medical	medical	ADJ
cana-4763	34	3	community	community	NOUN
cana-4763	34	4	sought	seek	VERB
cana-4763	34	5	non	non	ADJ
cana-4763	34	6	-	-	ADJ
cana-4763	34	7	invasive	invasive	ADJ
cana-4763	34	8	diagnostic	diagnostic	ADJ
cana-4763	34	9	solutions	solution	NOUN
cana-4763	34	10	because	because	SCONJ
cana-4763	34	11	traditional	traditional	ADJ
cana-4763	34	12	patient	patient	ADJ
cana-4763	34	13	safety	safety	NOUN
cana-4763	34	14	risks	risk	NOUN
cana-4763	34	15	with	with	ADP
cana-4763	34	16	invasive	invasive	ADJ
cana-4763	34	17	approaches	approach	NOUN
cana-4763	34	18	were	be	AUX
cana-4763	34	19	deemed	deem	VERB
cana-4763	34	20	unacceptable	unacceptable	ADJ
cana-4763	34	21	.	.	PUNCT
cana-4763	35	1	research	research	NOUN
cana-4763	35	2	in	in	ADP
cana-4763	35	3	imaging	imaging	NOUN
cana-4763	35	4	technology	technology	NOUN
cana-4763	35	5	has	have	AUX
cana-4763	35	6	revealed	reveal	VERB
cana-4763	35	7	encouraging	encouraging	ADJ
cana-4763	35	8	developments	development	NOUN
cana-4763	35	9	since	since	SCONJ
cana-4763	35	10	that	that	DET
cana-4763	35	11	time	time	NOUN
cana-4763	35	12	which	which	PRON
cana-4763	35	13	include	include	VERB
cana-4763	35	14	functional	functional	ADJ
cana-4763	35	15	mri	mri	NOUN
cana-4763	35	16	along	along	ADP
cana-4763	35	17	with	with	ADP
cana-4763	35	18	pet	pet	ADJ
cana-4763	35	19	scans	scan	NOUN
cana-4763	35	20	.	.	PUNCT
cana-4763	36	1	the	the	DET
cana-4763	36	2	methods	method	NOUN
cana-4763	36	3	deliver	deliver	VERB
cana-4763	36	4	extensive	extensive	ADJ
cana-4763	36	5	information	information	NOUN
cana-4763	36	6	about	about	ADP
cana-4763	36	7	tumor	tumor	NOUN
cana-4763	36	8	structure	structure	NOUN
cana-4763	36	9	and	and	CCONJ
cana-4763	36	10	metabolism	metabolism	NOUN
cana-4763	36	11	and	and	CCONJ
cana-4763	36	12	behavior	behavior	NOUN
cana-4763	36	13	so	so	SCONJ
cana-4763	36	14	doctors	doctor	NOUN
cana-4763	36	15	can	can	AUX
cana-4763	36	16	achieve	achieve	VERB
cana-4763	36	17	better	well	ADJ
cana-4763	36	18	classifications	classification	NOUN
cana-4763	36	19	without	without	ADP
cana-4763	36	20	operating	operate	VERB
cana-4763	36	21	.	.	PUNCT
cana-4763	37	1	the	the	DET
cana-4763	37	2	progress	progress	NOUN
cana-4763	37	3	in	in	ADP
cana-4763	37	4	brain	brain	NOUN
cana-4763	37	5	tumor	tumor	NOUN
cana-4763	37	6	diagnosis	diagnosis	NOUN
cana-4763	37	7	and	and	CCONJ
cana-4763	37	8	treatment	treatment	NOUN
cana-4763	37	9	became	become	VERB
cana-4763	37	10	substantial	substantial	ADJ
cana-4763	37	11	when	when	SCONJ
cana-4763	37	12	medical	medical	ADJ
cana-4763	37	13	research	research	NOUN
cana-4763	37	14	focused	focus	VERB
cana-4763	37	15	on	on	ADP
cana-4763	37	16	developing	develop	VERB
cana-4763	37	17	non	non	ADJ
cana-4763	37	18	-	-	ADJ
cana-4763	37	19	invasive	invasive	ADJ
cana-4763	37	20	strategies	strategy	NOUN
cana-4763	37	21	thus	thus	ADV
cana-4763	37	22	enabling	enable	VERB
cana-4763	37	23	safer	safe	ADJ
cana-4763	37	24	and	and	CCONJ
cana-4763	37	25	enhanced	enhanced	ADJ
cana-4763	37	26	care	care	NOUN
cana-4763	37	27	quality	quality	NOUN
cana-4763	37	28	for	for	ADP
cana-4763	37	29	patients	patient	NOUN
cana-4763	37	30	.	.	PUNCT
cana-4763	38	1	the	the	DET
cana-4763	38	2	current	current	ADJ
cana-4763	38	3	best	good	ADJ
cana-4763	38	4	practice	practice	NOUN
cana-4763	38	5	in	in	ADP
cana-4763	38	6	diagnosing	diagnose	VERB
cana-4763	38	7	and	and	CCONJ
cana-4763	38	8	classifying	classify	VERB
cana-4763	38	9	brain	brain	NOUN
cana-4763	38	10	tumors	tumor	NOUN
cana-4763	38	11	uses	use	VERB
cana-4763	38	12	histopathological	histopathological	ADJ
cana-4763	38	13	testing	testing	NOUN
cana-4763	38	14	according	accord	VERB
cana-4763	38	15	to	to	ADP
cana-4763	38	16	research	research	NOUN
cana-4763	38	17	[	[	X
cana-4763	38	18	7	7	NUM
cana-4763	38	19	]	]	PUNCT
cana-4763	38	20	.	.	PUNCT
cana-4763	39	1	under	under	ADP
cana-4763	39	2	microscopic	microscopic	ADJ
cana-4763	39	3	examination	examination	NOUN
cana-4763	39	4	of	of	ADP
cana-4763	39	5	tumor	tumor	NOUN
cana-4763	39	6	tissue	tissue	NOUN
cana-4763	39	7	,	,	PUNCT
cana-4763	39	8	this	this	DET
cana-4763	39	9	approach	approach	NOUN
cana-4763	39	10	gave	give	VERB
cana-4763	39	11	detailed	detailed	ADJ
cana-4763	39	12	knowledge	knowledge	NOUN
cana-4763	39	13	of	of	ADP
cana-4763	39	14	multiple	multiple	ADJ
cana-4763	39	15	tumor	tumor	NOUN
cana-4763	39	16	groups	group	NOUN
cana-4763	39	17	including	include	VERB
cana-4763	39	18	pituitary	pituitary	ADJ
cana-4763	39	19	adenomas	adenoma	NOUN
cana-4763	39	20	,	,	PUNCT
cana-4763	39	21	meningioma	meningioma	NOUN
cana-4763	39	22	’s	’s	PART
cana-4763	39	23	and	and	CCONJ
cana-4763	39	24	gliomas	glioma	NOUN
cana-4763	39	25	.	.	PUNCT
cana-4763	40	1	computer	computer	NOUN
cana-4763	40	2	-	-	PUNCT
cana-4763	40	3	aided	aid	VERB
cana-4763	40	4	diagnostic	diagnostic	ADJ
cana-4763	40	5	(	(	PUNCT
cana-4763	40	6	cad	cad	NOUN
cana-4763	40	7	)	)	PUNCT
cana-4763	40	8	tools	tool	NOUN
cana-4763	40	9	became	become	VERB
cana-4763	40	10	available	available	ADJ
cana-4763	40	11	through	through	ADP
cana-4763	40	12	their	their	PRON
cana-4763	40	13	recent	recent	ADJ
cana-4763	40	14	development	development	NOUN
cana-4763	40	15	which	which	PRON
cana-4763	40	16	advanced	advance	VERB
cana-4763	40	17	automated	automate	VERB
cana-4763	40	18	brain	brain	NOUN
cana-4763	40	19	tumor	tumor	NOUN
cana-4763	40	20	classification	classification	NOUN
cana-4763	40	21	processes	process	NOUN
cana-4763	40	22	[	[	X
cana-4763	40	23	8][9	8][9	NOUN
cana-4763	40	24	]	]	X
cana-4763	40	25	.	.	PUNCT
cana-4763	41	1	different	different	ADJ
cana-4763	41	2	machine	machine	NOUN
cana-4763	41	3	learning	learn	VERB
cana-4763	41	4	algorithms	algorithm	NOUN
cana-4763	41	5	including	include	VERB
cana-4763	41	6	support	support	NOUN
cana-4763	41	7	vector	vector	NOUN
cana-4763	41	8	machines	machine	NOUN
cana-4763	41	9	(	(	PUNCT
cana-4763	41	10	svms	svms	NOUN
cana-4763	41	11	)	)	PUNCT
cana-4763	42	1	[	[	X
cana-4763	42	2	10	10	NUM
cana-4763	42	3	]	]	PUNCT
cana-4763	42	4	,	,	PUNCT
cana-4763	42	5	decision	decision	NOUN
cana-4763	42	6	trees	tree	NOUN
cana-4763	42	7	,	,	PUNCT
cana-4763	42	8	random	random	ADJ
cana-4763	42	9	forests	forest	NOUN
cana-4763	42	10	and	and	CCONJ
cana-4763	42	11	ensemble	ensemble	ADJ
cana-4763	42	12	methods	method	NOUN
cana-4763	42	13	[	[	X
cana-4763	42	14	11	11	NUM
cana-4763	42	15	]	]	X
cana-4763	43	1	[	[	X
cana-4763	43	2	12	12	NUM
cana-4763	43	3	]	]	PUNCT
cana-4763	43	4	served	serve	VERB
cana-4763	43	5	tumor	tumor	NOUN
cana-4763	43	6	classifications	classification	NOUN
cana-4763	43	7	in	in	ADP
cana-4763	43	8	these	these	DET
cana-4763	43	9	systems	system	NOUN
cana-4763	43	10	according	accord	VERB
cana-4763	43	11	to	to	ADP
cana-4763	43	12	manually	manually	ADV
cana-4763	43	13	extracted	extract	VERB
cana-4763	43	14	features	feature	NOUN
cana-4763	43	15	regarding	regard	VERB
cana-4763	43	16	texture	texture	ADJ
cana-4763	43	17	shape	shape	NOUN
cana-4763	43	18	intensity	intensity	NOUN
cana-4763	43	19	and	and	CCONJ
cana-4763	43	20	edge	edge	NOUN
cana-4763	43	21	patterns	pattern	NOUN
cana-4763	43	22	[	[	X
cana-4763	43	23	13	13	NUM
cana-4763	43	24	]	]	PUNCT
cana-4763	43	25	.	.	PUNCT
cana-4763	44	1	the	the	DET
cana-4763	44	2	systems	system	NOUN
cana-4763	44	3	faced	face	VERB
cana-4763	44	4	limitations	limitation	NOUN
cana-4763	44	5	in	in	ADP
cana-4763	44	6	effectiveness	effectiveness	NOUN
cana-4763	44	7	because	because	SCONJ
cana-4763	44	8	they	they	PRON
cana-4763	44	9	relied	rely	VERB
cana-4763	44	10	on	on	ADP
cana-4763	44	11	features	feature	NOUN
cana-4763	44	12	chosen	choose	VERB
cana-4763	44	13	by	by	ADP
cana-4763	44	14	experts	expert	NOUN
cana-4763	44	15	which	which	PRON
cana-4763	44	16	forced	force	VERB
cana-4763	44	17	users	user	NOUN
cana-4763	44	18	to	to	PART
cana-4763	44	19	get	get	AUX
cana-4763	44	20	involved	involve	VERB
cana-4763	44	21	manually	manually	ADV
cana-4763	44	22	and	and	CCONJ
cana-4763	44	23	reduced	reduce	VERB
cana-4763	44	24	the	the	DET
cana-4763	44	25	automation	automation	NOUN
cana-4763	44	26	capabilities	capability	NOUN
cana-4763	44	27	.	.	PUNCT
cana-4763	45	1	when	when	SCONJ
cana-4763	45	2	scientists	scientist	NOUN
cana-4763	45	3	investigated	investigate	VERB
cana-4763	45	4	deep	deep	ADJ
cana-4763	45	5	learning	learning	NOUN
cana-4763	45	6	methods	method	NOUN
cana-4763	45	7	[	[	X
cana-4763	45	8	14	14	NUM
cana-4763	45	9	]	]	PUNCT
cana-4763	45	10	as	as	ADP
cana-4763	45	11	a	a	DET
cana-4763	45	12	solution	solution	NOUN
cana-4763	45	13	to	to	PART
cana-4763	45	14	overcome	overcome	VERB
cana-4763	45	15	this	this	DET
cana-4763	45	16	limitation	limitation	NOUN
cana-4763	45	17	.	.	PUNCT
cana-4763	46	1	automatic	automatic	ADJ
cana-4763	46	2	feature	feature	NOUN
cana-4763	46	3	detection	detection	NOUN
cana-4763	46	4	methods	method	NOUN
cana-4763	46	5	in	in	ADP
cana-4763	46	6	brain	brain	NOUN
cana-4763	46	7	tumor	tumor	NOUN
cana-4763	46	8	diagnosis	diagnosis	NOUN
cana-4763	46	9	lead	lead	NOUN
cana-4763	46	10	to	to	ADP
cana-4763	46	11	enhanced	enhanced	ADJ
cana-4763	46	12	effectiveness	effectiveness	NOUN
cana-4763	46	13	and	and	CCONJ
cana-4763	46	14	precise	precise	ADJ
cana-4763	46	15	brain	brain	NOUN
cana-4763	46	16	tumor	tumor	NOUN
cana-4763	46	17	diagnosis	diagnosis	NOUN
cana-4763	46	18	capabilities	capability	NOUN
cana-4763	46	19	through	through	ADP
cana-4763	46	20	direct	direct	ADJ
cana-4763	46	21	data	data	NOUN
cana-4763	46	22	extraction	extraction	NOUN
cana-4763	46	23	from	from	ADP
cana-4763	46	24	unprocessed	unprocesse	VERB
cana-4763	46	25	imaging	imaging	NOUN
cana-4763	46	26	data	datum	NOUN
cana-4763	46	27	.	.	PUNCT
cana-4763	47	1	the	the	DET
cana-4763	47	2	improvements	improvement	NOUN
cana-4763	47	3	achieved	achieve	VERB
cana-4763	47	4	regarding	regard	VERB
cana-4763	47	5	accuracy	accuracy	NOUN
cana-4763	47	6	and	and	CCONJ
cana-4763	47	7	manual	manual	ADJ
cana-4763	47	8	inspection	inspection	NOUN
cana-4763	47	9	requirement	requirement	NOUN
cana-4763	47	10	reduction	reduction	NOUN
cana-4763	47	11	did	do	AUX
cana-4763	47	12	not	not	PART
cana-4763	47	13	remove	remove	VERB
cana-4763	47	14	the	the	DET
cana-4763	47	15	major	major	ADJ
cana-4763	47	16	limitations	limitation	NOUN
cana-4763	47	17	that	that	PRON
cana-4763	47	18	existed	exist	VERB
cana-4763	47	19	within	within	ADP
cana-4763	47	20	feature	feature	NOUN
cana-4763	47	21	-	-	PUNCT
cana-4763	47	22	based	base	VERB
cana-4763	47	23	approaches	approach	NOUN
cana-4763	47	24	.	.	PUNCT
cana-4763	48	1	the	the	DET
cana-4763	48	2	chosen	choose	VERB
cana-4763	48	3	features	feature	NOUN
cana-4763	48	4	combined	combine	VERB
cana-4763	48	5	with	with	ADP
cana-4763	48	6	the	the	DET
cana-4763	48	7	ability	ability	NOUN
cana-4763	48	8	of	of	ADP
cana-4763	48	9	data	datum	NOUN
cana-4763	48	10	scientists	scientist	NOUN
cana-4763	48	11	and	and	CCONJ
cana-4763	48	12	radiologists	radiologist	NOUN
cana-4763	48	13	building	build	VERB
cana-4763	48	14	the	the	DET
cana-4763	48	15	feature	feature	NOUN
cana-4763	48	16	extraction	extraction	NOUN
cana-4763	48	17	process	process	NOUN
cana-4763	48	18	defined	define	VERB
cana-4763	48	19	the	the	DET
cana-4763	48	20	quality	quality	NOUN
cana-4763	48	21	level	level	NOUN
cana-4763	48	22	of	of	ADP
cana-4763	48	23	the	the	DET
cana-4763	48	24	outcomes	outcome	NOUN
cana-4763	48	25	.	.	PUNCT
cana-4763	49	1	all	all	PRON
cana-4763	49	2	of	of	ADP
cana-4763	49	3	these	these	DET
cana-4763	49	4	algorithms	algorithm	NOUN
cana-4763	49	5	encountered	encounter	VERB
cana-4763	49	6	problems	problem	NOUN
cana-4763	49	7	with	with	ADP
cana-4763	49	8	cross	cross	ADJ
cana-4763	49	9	-	-	ADJ
cana-4763	49	10	environment	environment	ADJ
cana-4763	49	11	generalization	generalization	NOUN
cana-4763	49	12	because	because	SCONJ
cana-4763	49	13	their	their	PRON
cana-4763	49	14	operations	operation	NOUN
cana-4763	49	15	were	be	AUX
cana-4763	49	16	limited	limit	VERB
cana-4763	49	17	by	by	ADP
cana-4763	49	18	differences	difference	NOUN
cana-4763	49	19	in	in	ADP
cana-4763	49	20	imaging	imaging	NOUN
cana-4763	49	21	protocols	protocol	NOUN
cana-4763	49	22	and	and	CCONJ
cana-4763	49	23	patient	patient	ADJ
cana-4763	49	24	demographic	demographic	ADJ
cana-4763	49	25	characteristics	characteristic	NOUN
cana-4763	49	26	.	.	PUNCT
cana-4763	50	1	this	this	DET
cana-4763	50	2	variable	variable	ADJ
cana-4763	50	3	performance	performance	NOUN
cana-4763	50	4	with	with	ADP
cana-4763	50	5	new	new	ADJ
cana-4763	50	6	datasets	dataset	NOUN
cana-4763	50	7	proved	prove	VERB
cana-4763	50	8	that	that	SCONJ
cana-4763	50	9	resilient	resilient	ADJ
cana-4763	50	10	models	model	NOUN
cana-4763	50	11	with	with	ADP
cana-4763	50	12	clinical	clinical	ADJ
cana-4763	50	13	context	context	NOUN
cana-4763	50	14	adaptability	adaptability	NOUN
cana-4763	50	15	should	should	AUX
cana-4763	50	16	become	become	VERB
cana-4763	50	17	the	the	DET
cana-4763	50	18	priority	priority	NOUN
cana-4763	50	19	for	for	ADP
cana-4763	50	20	future	future	ADJ
cana-4763	50	21	development	development	NOUN
cana-4763	50	22	.	.	PUNCT
cana-4763	51	1	deep	deep	ADJ
cana-4763	51	2	learning	learning	NOUN
cana-4763	51	3	achieved	achieve	VERB
cana-4763	51	4	a	a	DET
cana-4763	51	5	revolutionary	revolutionary	ADJ
cana-4763	51	6	change	change	NOUN
cana-4763	51	7	in	in	ADP
cana-4763	51	8	brain	brain	NOUN
cana-4763	51	9	tumor	tumor	NOUN
cana-4763	51	10	classification	classification	NOUN
cana-4763	51	11	when	when	SCONJ
cana-4763	51	12	it	it	PRON
cana-4763	51	13	introduced	introduce	VERB
cana-4763	51	14	end	end	NOUN
cana-4763	51	15	-	-	PUNCT
cana-4763	51	16	to	to	ADP
cana-4763	51	17	-	-	PUNCT
cana-4763	51	18	end	end	NOUN
cana-4763	51	19	learning	learning	NOUN
cana-4763	51	20	based	base	VERB
cana-4763	51	21	on	on	ADP
cana-4763	51	22	imaged	imaged	ADJ
cana-4763	51	23	data	datum	NOUN
cana-4763	51	24	directly	directly	ADV
cana-4763	51	25	from	from	ADP
cana-4763	51	26	its	its	PRON
cana-4763	51	27	original	original	ADJ
cana-4763	51	28	state	state	NOUN
cana-4763	51	29	.	.	PUNCT
cana-4763	52	1	convolutional	convolutional	ADJ
cana-4763	52	2	neural	neural	ADJ
cana-4763	52	3	networks	network	NOUN
cana-4763	52	4	(	(	PUNCT
cana-4763	52	5	cnns	cnns	PROPN
cana-4763	52	6	)	)	PUNCT
cana-4763	53	1	[	[	X
cana-4763	53	2	15	15	NUM
cana-4763	53	3	,	,	PUNCT
cana-4763	53	4	16	16	NUM
cana-4763	53	5	]	]	PUNCT
cana-4763	53	6	have	have	AUX
cana-4763	53	7	become	become	VERB
cana-4763	53	8	widely	widely	ADV
cana-4763	53	9	popular	popular	ADJ
cana-4763	53	10	because	because	SCONJ
cana-4763	53	11	they	they	PRON
cana-4763	53	12	can	can	AUX
cana-4763	53	13	automatically	automatically	ADV
cana-4763	53	14	extract	extract	VERB
cana-4763	53	15	spatial	spatial	ADJ
cana-4763	53	16	information	information	NOUN
cana-4763	53	17	hierarchies	hierarchy	NOUN
cana-4763	53	18	from	from	ADP
cana-4763	53	19	pictures	picture	NOUN
cana-4763	53	20	.	.	PUNCT
cana-4763	54	1	research	research	NOUN
cana-4763	54	2	together	together	ADV
cana-4763	54	3	with	with	ADP
cana-4763	54	4	clinical	clinical	ADJ
cana-4763	54	5	facilities	facility	NOUN
cana-4763	54	6	have	have	AUX
cana-4763	54	7	adopted	adopt	VERB
cana-4763	54	8	networks	network	NOUN
cana-4763	54	9	like	like	ADP
cana-4763	54	10	resnet	resnet	NOUN
cana-4763	54	11	,	,	PUNCT
cana-4763	54	12	densenet	densenet	NOUN
cana-4763	54	13	,	,	PUNCT
cana-4763	54	14	vggnet	vggnet	NOUN
cana-4763	54	15	and	and	CCONJ
cana-4763	54	16	inception	inception	NOUN
cana-4763	54	17	since	since	SCONJ
cana-4763	54	18	they	they	PRON
cana-4763	54	19	excel	excel	VERB
cana-4763	54	20	at	at	ADP
cana-4763	54	21	detecting	detect	VERB
cana-4763	54	22	tumors	tumor	NOUN
cana-4763	54	23	and	and	CCONJ
cana-4763	54	24	segmenting	segment	VERB
cana-4763	54	25	them	they	PRON
cana-4763	54	26	.	.	PUNCT
cana-4763	55	1	the	the	DET
cana-4763	55	2	models	model	NOUN
cana-4763	55	3	utilize	utilize	VERB
cana-4763	55	4	dense	dense	ADJ
cana-4763	55	5	and	and	CCONJ
cana-4763	55	6	residual	residual	ADJ
cana-4763	55	7	connections	connection	NOUN
cana-4763	55	8	as	as	ADP
cana-4763	55	9	sophisticated	sophisticated	ADJ
cana-4763	55	10	methods	method	NOUN
cana-4763	55	11	to	to	PART
cana-4763	55	12	improve	improve	VERB
cana-4763	55	13	complicated	complicated	ADJ
cana-4763	55	14	dataset	dataset	NOUN
cana-4763	55	15	performance	performance	NOUN
cana-4763	55	16	and	and	CCONJ
cana-4763	55	17	enhance	enhance	VERB
cana-4763	55	18	feature	feature	NOUN
cana-4763	55	19	extraction	extraction	NOUN
cana-4763	55	20	.	.	PUNCT
cana-4763	56	1	the	the	DET
cana-4763	56	2	application	application	NOUN
cana-4763	56	3	of	of	ADP
cana-4763	56	4	alexnet	alexnet	NOUN
cana-4763	56	5	achieved	achieve	VERB
cana-4763	56	6	better	well	ADJ
cana-4763	56	7	results	result	NOUN
cana-4763	56	8	than	than	ADP
cana-4763	56	9	ordinary	ordinary	ADJ
cana-4763	56	10	machine	machine	NOUN
cana-4763	56	11	learning	learning	NOUN
cana-4763	56	12	approaches	approach	NOUN
cana-4763	56	13	while	while	SCONJ
cana-4763	56	14	processing	process	VERB
cana-4763	56	15	tumor	tumor	NOUN
cana-4763	56	16	data	datum	NOUN
cana-4763	56	17	effectively	effectively	ADV
cana-4763	56	18	.	.	PUNCT
cana-4763	57	1	transfer	transfer	NOUN
cana-4763	57	2	learning	learning	NOUN
cana-4763	57	3	has	have	AUX
cana-4763	57	4	undergone	undergo	VERB
cana-4763	57	5	substantial	substantial	ADJ
cana-4763	57	6	development	development	NOUN
cana-4763	57	7	to	to	PART
cana-4763	57	8	advance	advance	VERB
cana-4763	57	9	deep	deep	ADJ
cana-4763	57	10	learning	learning	NOUN
cana-4763	57	11	models	model	NOUN
cana-4763	57	12	in	in	ADP
cana-4763	57	13	recent	recent	ADJ
cana-4763	57	14	times	time	NOUN
cana-4763	57	15	.	.	PUNCT
cana-4763	58	1	medical	medical	ADJ
cana-4763	58	2	researchers	researcher	NOUN
cana-4763	58	3	solved	solve	VERB
cana-4763	58	4	the	the	DET
cana-4763	58	5	scarcity	scarcity	NOUN
cana-4763	58	6	of	of	ADP
cana-4763	58	7	labeled	label	VERB
cana-4763	58	8	healthcare	healthcare	NOUN
cana-4763	58	9	information	information	NOUN
cana-4763	58	10	by	by	ADP
cana-4763	58	11	utilizing	utilize	VERB
cana-4763	58	12	optimized	optimize	VERB
cana-4763	58	13	pretrained	pretraine	VERB
cana-4763	58	14	neural	neural	ADJ
cana-4763	58	15	networks	network	NOUN
cana-4763	58	16	for	for	ADP
cana-4763	58	17	imagenet	imagenet	NOUN
cana-4763	58	18	that	that	PRON
cana-4763	58	19	process	process	VERB
cana-4763	58	20	smaller	small	ADJ
cana-4763	58	21	medical	medical	ADJ
cana-4763	58	22	datasets	dataset	NOUN
cana-4763	58	23	.	.	PUNCT
cana-4763	59	1	through	through	ADP
cana-4763	59	2	gpu	gpu	NOUN
cana-4763	59	3	computing	computing	NOUN
cana-4763	59	4	speed	speed	NOUN
cana-4763	59	5	enhancements	enhancement	NOUN
cana-4763	59	6	researchers	researcher	NOUN
cana-4763	59	7	have	have	AUX
cana-4763	59	8	transformed	transform	VERB
cana-4763	59	9	the	the	DET
cana-4763	59	10	field	field	NOUN
cana-4763	59	11	and	and	CCONJ
cana-4763	59	12	established	establish	VERB
cana-4763	59	13	better	well	ADJ
cana-4763	59	14	accessibility	accessibility	NOUN
cana-4763	59	15	of	of	ADP
cana-4763	59	16	these	these	DET
cana-4763	59	17	models	model	NOUN
cana-4763	59	18	for	for	ADP
cana-4763	59	19	clinical	clinical	ADJ
cana-4763	59	20	practice	practice	NOUN
cana-4763	59	21	.	.	PUNCT
cana-4763	60	1	medical	medical	ADJ
cana-4763	60	2	diagnostics	diagnostic	NOUN
cana-4763	60	3	using	use	VERB
cana-4763	60	4	these	these	DET
cana-4763	60	5	technologies	technology	NOUN
cana-4763	60	6	now	now	ADV
cana-4763	60	7	provide	provide	VERB
cana-4763	60	8	farmers	farmer	NOUN
cana-4763	60	9	elevated	elevate	VERB
cana-4763	60	10	diagnostic	diagnostic	ADJ
cana-4763	60	11	accuracy	accuracy	NOUN
cana-4763	60	12	in	in	ADP
cana-4763	60	13	addition	addition	NOUN
cana-4763	60	14	to	to	ADP
cana-4763	60	15	individual	individual	ADJ
cana-4763	60	16	treatment	treatment	NOUN
cana-4763	60	17	plans	plan	NOUN
cana-4763	60	18	that	that	PRON
cana-4763	60	19	suit	suit	VERB
cana-4763	60	20	patients	patient	NOUN
cana-4763	60	21	'	'	PART
cana-4763	60	22	specific	specific	ADJ
cana-4763	60	23	medical	medical	ADJ
cana-4763	60	24	needs	need	NOUN
cana-4763	60	25	.	.	PUNCT
cana-4763	61	1	the	the	DET
cana-4763	61	2	investigation	investigation	NOUN
cana-4763	61	3	of	of	ADP
cana-4763	61	4	hybrid	hybrid	ADJ
cana-4763	61	5	and	and	CCONJ
cana-4763	61	6	ensemble	ensemble	ADJ
cana-4763	61	7	models	model	NOUN
cana-4763	61	8	started	start	VERB
cana-4763	61	9	among	among	ADP
cana-4763	61	10	researchers	researcher	NOUN
cana-4763	61	11	as	as	SCONJ
cana-4763	61	12	they	they	PRON
cana-4763	61	13	aimed	aim	VERB
cana-4763	61	14	to	to	PART
cana-4763	61	15	enhance	enhance	VERB
cana-4763	61	16	classification	classification	NOUN
cana-4763	61	17	accuracy	accuracy	NOUN
cana-4763	61	18	.	.	PUNCT
cana-4763	62	1	multiple	multiple	ADJ
cana-4763	62	2	approaches	approach	NOUN
cana-4763	62	3	with	with	ADP
cana-4763	62	4	their	their	PRON
cana-4763	62	5	respective	respective	ADJ
cana-4763	62	6	outstanding	outstanding	ADJ
cana-4763	62	7	features	feature	NOUN
cana-4763	62	8	converge	converge	VERB
cana-4763	62	9	into	into	ADP
cana-4763	62	10	hybrid	hybrid	ADJ
cana-4763	62	11	models	model	NOUN
cana-4763	62	12	through	through	ADP
cana-4763	62	13	the	the	DET
cana-4763	62	14	combination	combination	NOUN
cana-4763	62	15	of	of	ADP
cana-4763	62	16	cnns	cnn	NOUN
cana-4763	62	17	[	[	X
cana-4763	62	18	17	17	NUM
cana-4763	62	19	]	]	PUNCT
cana-4763	62	20	and	and	CCONJ
cana-4763	62	21	the	the	DET
cana-4763	62	22	more	more	ADV
cana-4763	62	23	traditional	traditional	ADJ
cana-4763	62	24	svms	svms	NOUN
cana-4763	62	25	[	[	X
cana-4763	62	26	18	18	NUM
cana-4763	62	27	]	]	X
cana-4763	62	28	machine	machine	NOUN
cana-4763	62	29	learning	learn	VERB
cana-4763	62	30	classifiers	classifier	NOUN
cana-4763	62	31	.	.	PUNCT
cana-4763	63	1	using	use	VERB
cana-4763	63	2	the	the	DET
cana-4763	63	3	ensemble	ensemble	ADJ
cana-4763	63	4	learning	learning	NOUN
cana-4763	63	5	methods	method	NOUN
cana-4763	63	6	of	of	ADP
cana-4763	63	7	both	both	DET
cana-4763	63	8	bagging	bag	VERB
cana-4763	63	9	and	and	CCONJ
cana-4763	63	10	boosting	boost	VERB
cana-4763	63	11	multiple	multiple	ADJ
cana-4763	63	12	models	model	NOUN
cana-4763	63	13	generate	generate	VERB
cana-4763	63	14	predictions	prediction	NOUN
cana-4763	63	15	to	to	PART
cana-4763	63	16	reduce	reduce	VERB
cana-4763	63	17	overfitting	overfitte	VERB
cana-4763	63	18	and	and	CCONJ
cana-4763	63	19	enhance	enhance	VERB
cana-4763	63	20	reliability	reliability	NOUN
cana-4763	63	21	.	.	PUNCT
cana-4763	64	1	a	a	DET
cana-4763	64	2	typical	typical	ADJ
cana-4763	64	3	svm	svm	PROPN
cana-4763	64	4	serves	serve	VERB
cana-4763	64	5	to	to	PART
cana-4763	64	6	categorize	categorize	VERB
cana-4763	64	7	tumors	tumor	NOUN
cana-4763	64	8	through	through	ADP
cana-4763	64	9	operation	operation	NOUN
cana-4763	64	10	on	on	ADP
cana-4763	64	11	high	high	ADJ
cana-4763	64	12	-	-	PUNCT
cana-4763	64	13	level	level	NOUN
cana-4763	64	14	features	feature	NOUN
cana-4763	64	15	derived	derive	VERB
cana-4763	64	16	from	from	ADP
cana-4763	64	17	cnn	cnn	PROPN
cana-4763	64	18	-	-	PUNCT
cana-4763	64	19	analyzed	analyze	VERB
cana-4763	64	20	mri	mri	NOUN
cana-4763	64	21	scans	scan	NOUN
cana-4763	64	22	as	as	ADP
cana-4763	64	23	part	part	NOUN
cana-4763	64	24	of	of	ADP
cana-4763	64	25	a	a	DET
cana-4763	64	26	hybrid	hybrid	ADJ
cana-4763	64	27	classification	classification	NOUN
cana-4763	64	28	system	system	NOUN
cana-4763	64	29	.	.	PUNCT
cana-4763	65	1	a	a	DET
cana-4763	65	2	group	group	NOUN
cana-4763	65	3	of	of	ADP
cana-4763	65	4	classifiers	classifier	NOUN
cana-4763	65	5	known	know	VERB
cana-4763	65	6	as	as	ADP
cana-4763	65	7	ensembling	ensemble	VERB
cana-4763	65	8	methods	method	NOUN
cana-4763	65	9	utilizes	utilize	VERB
cana-4763	65	10	several	several	ADJ
cana-4763	65	11	weak	weak	ADJ
cana-4763	65	12	classifiers	classifier	NOUN
cana-4763	65	13	to	to	PART
cana-4763	65	14	create	create	VERB
cana-4763	65	15	improved	improved	ADJ
cana-4763	65	16	prediction	prediction	NOUN
cana-4763	65	17	results	result	NOUN
cana-4763	65	18	.	.	PUNCT
cana-4763	66	1	this	this	PRON
cana-4763	66	2	includes	include	VERB
cana-4763	66	3	gradient	gradient	NOUN
cana-4763	66	4	boosting	boost	VERB
cana-4763	66	5	and	and	CCONJ
cana-4763	66	6	random	random	ADJ
cana-4763	66	7	forests	forest	NOUN
cana-4763	66	8	.	.	PUNCT
cana-4763	67	1	ai	ai	AUX
cana-4763	67	2	model	model	NOUN
cana-4763	67	3	complexity	complexity	NOUN
cana-4763	67	4	led	lead	VERB
cana-4763	67	5	to	to	ADP
cana-4763	67	6	the	the	DET
cana-4763	67	7	adoption	adoption	NOUN
cana-4763	67	8	hurdle	hurdle	NOUN
cana-4763	67	9	because	because	SCONJ
cana-4763	67	10	clinicians	clinician	NOUN
cana-4763	67	11	could	could	AUX
cana-4763	67	12	not	not	PART
cana-4763	67	13	easily	easily	ADV
cana-4763	67	14	understand	understand	VERB
cana-4763	67	15	their	their	PRON
cana-4763	67	16	"	"	PUNCT
cana-4763	67	17	black	black	ADJ
cana-4763	67	18	box	box	NOUN
cana-4763	67	19	"	"	PUNCT
cana-4763	67	20	mechanism	mechanism	NOUN
cana-4763	67	21	.	.	PUNCT
cana-4763	68	1	xai	xai	PROPN
cana-4763	68	2	gained	gain	VERB
cana-4763	68	3	prominence	prominence	NOUN
cana-4763	68	4	as	as	SCONJ
cana-4763	68	5	communications	communication	NOUN
cana-4763	68	6	on	on	ADP
cana-4763	68	7	applied	apply	VERB
cana-4763	68	8	nonlinear	nonlinear	ADJ
cana-4763	68	9	analysis	analysis	NOUN
cana-4763	68	10	issn	issn	NOUN
cana-4763	68	11	:	:	PUNCT
cana-4763	68	12	1074	1074	NUM
cana-4763	68	13	-	-	PUNCT
cana-4763	68	14	133x	133x	NUM
cana-4763	68	15	vol	vol	VERB
cana-4763	68	16	32	32	NUM
cana-4763	68	17	no	no	NOUN
cana-4763	68	18	.	.	PUNCT
cana-4763	68	19	10s	10	NOUN
cana-4763	68	20	(	(	PUNCT
cana-4763	68	21	2025	2025	NUM
cana-4763	68	22	)	)	PUNCT
cana-4763	68	23	298	298	NUM
cana-4763	68	24	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	69	1	an	an	DET
cana-4763	69	2	ai	ai	PROPN
cana-4763	69	3	method	method	NOUN
cana-4763	69	4	to	to	PART
cana-4763	69	5	display	display	VERB
cana-4763	69	6	the	the	DET
cana-4763	69	7	decision	decision	NOUN
cana-4763	69	8	methods	method	NOUN
cana-4763	69	9	used	use	VERB
cana-4763	69	10	by	by	ADP
cana-4763	69	11	complex	complex	ADJ
cana-4763	69	12	models	model	NOUN
cana-4763	69	13	.	.	PUNCT
cana-4763	70	1	to	to	PART
cana-4763	70	2	support	support	VERB
cana-4763	70	3	radiologists	radiologist	NOUN
cana-4763	70	4	with	with	ADP
cana-4763	70	5	result	result	NOUN
cana-4763	70	6	verification	verification	NOUN
cana-4763	70	7	and	and	CCONJ
cana-4763	70	8	ai	ai	VERB
cana-4763	70	9	system	system	NOUN
cana-4763	70	10	confidence	confidence	NOUN
cana-4763	70	11	levels	level	NOUN
cana-4763	70	12	three	three	NUM
cana-4763	70	13	tools	tool	NOUN
cana-4763	70	14	namely	namely	ADV
cana-4763	70	15	grad	grad	NOUN
cana-4763	70	16	-	-	PUNCT
cana-4763	70	17	cam	cam	NOUN
cana-4763	70	18	and	and	CCONJ
cana-4763	70	19	shap	shap	NOUN
cana-4763	70	20	and	and	CCONJ
cana-4763	70	21	lime	lime	NOUN
cana-4763	70	22	identify	identify	VERB
cana-4763	70	23	which	which	DET
cana-4763	70	24	image	image	NOUN
cana-4763	70	25	sections	section	NOUN
cana-4763	70	26	maintain	maintain	VERB
cana-4763	70	27	the	the	DET
cana-4763	70	28	most	most	ADV
cana-4763	70	29	important	important	ADJ
cana-4763	70	30	influence	influence	NOUN
cana-4763	70	31	on	on	ADP
cana-4763	70	32	predictive	predictive	ADJ
cana-4763	70	33	model	model	NOUN
cana-4763	70	34	output	output	NOUN
cana-4763	70	35	.	.	PUNCT
cana-4763	71	1	the	the	DET
cana-4763	71	2	classification	classification	NOUN
cana-4763	71	3	process	process	NOUN
cana-4763	71	4	of	of	ADP
cana-4763	71	5	xai	xai	PROPN
cana-4763	71	6	models	model	NOUN
cana-4763	71	7	becomes	become	VERB
cana-4763	71	8	more	more	ADV
cana-4763	71	9	focused	focused	ADJ
cana-4763	71	10	on	on	ADP
cana-4763	71	11	clinically	clinically	ADV
cana-4763	71	12	relevant	relevant	ADJ
cana-4763	71	13	characteristics	characteristic	NOUN
cana-4763	71	14	because	because	SCONJ
cana-4763	71	15	heatmaps	heatmap	NOUN
cana-4763	71	16	expose	expose	VERB
cana-4763	71	17	the	the	DET
cana-4763	71	18	tumor	tumor	NOUN
cana-4763	71	19	regions	region	NOUN
cana-4763	71	20	affecting	affect	VERB
cana-4763	71	21	model	model	NOUN
cana-4763	71	22	predictions	prediction	NOUN
cana-4763	71	23	.	.	PUNCT
cana-4763	72	1	the	the	DET
cana-4763	72	2	transparency	transparency	NOUN
cana-4763	72	3	level	level	NOUN
cana-4763	72	4	required	require	VERB
cana-4763	72	5	in	in	ADP
cana-4763	72	6	medical	medical	ADJ
cana-4763	72	7	applications	application	NOUN
cana-4763	72	8	is	be	AUX
cana-4763	72	9	essential	essential	ADJ
cana-4763	72	10	specifically	specifically	ADV
cana-4763	72	11	because	because	SCONJ
cana-4763	72	12	diagnostic	diagnostic	ADJ
cana-4763	72	13	errors	error	NOUN
cana-4763	72	14	lead	lead	VERB
cana-4763	72	15	to	to	ADP
cana-4763	72	16	major	major	ADJ
cana-4763	72	17	consequences	consequence	NOUN
cana-4763	72	18	.	.	PUNCT
cana-4763	73	1	this	this	DET
cana-4763	73	2	need	need	NOUN
cana-4763	73	3	was	be	AUX
cana-4763	73	4	addressed	address	VERB
cana-4763	73	5	by	by	ADP
cana-4763	73	6	self	self	NOUN
cana-4763	73	7	-	-	PUNCT
cana-4763	73	8	supervised	supervise	VERB
cana-4763	73	9	learning	learning	NOUN
cana-4763	73	10	in	in	ADP
cana-4763	73	11	recent	recent	ADJ
cana-4763	73	12	times	time	NOUN
cana-4763	73	13	.	.	PUNCT
cana-4763	74	1	federated	federated	ADJ
cana-4763	74	2	learning	learning	NOUN
cana-4763	74	3	enables	enable	VERB
cana-4763	74	4	the	the	DET
cana-4763	74	5	joint	joint	ADJ
cana-4763	74	6	model	model	NOUN
cana-4763	74	7	training	training	NOUN
cana-4763	74	8	between	between	ADP
cana-4763	74	9	different	different	ADJ
cana-4763	74	10	institutions	institution	NOUN
cana-4763	74	11	to	to	PART
cana-4763	74	12	protect	protect	VERB
cana-4763	74	13	patient	patient	ADJ
cana-4763	74	14	privacy	privacy	NOUN
cana-4763	74	15	through	through	ADP
cana-4763	74	16	secure	secure	ADJ
cana-4763	74	17	information	information	NOUN
cana-4763	74	18	protection	protection	NOUN
cana-4763	74	19	.	.	PUNCT
cana-4763	75	1	through	through	ADP
cana-4763	75	2	federated	federated	ADJ
cana-4763	75	3	learning	learn	VERB
cana-4763	75	4	institutions	institution	NOUN
cana-4763	75	5	protect	protect	VERB
cana-4763	75	6	patient	patient	ADJ
cana-4763	75	7	privacy	privacy	NOUN
cana-4763	75	8	by	by	ADP
cana-4763	75	9	preparing	prepare	VERB
cana-4763	75	10	model	model	NOUN
cana-4763	75	11	updates	update	NOUN
cana-4763	75	12	instead	instead	ADV
cana-4763	75	13	of	of	ADP
cana-4763	75	14	distributing	distribute	VERB
cana-4763	75	15	original	original	ADJ
cana-4763	75	16	data	datum	NOUN
cana-4763	75	17	thus	thus	ADV
cana-4763	75	18	following	follow	VERB
cana-4763	75	19	regulations	regulation	NOUN
cana-4763	75	20	including	include	VERB
cana-4763	75	21	gdpr	gdpr	NOUN
cana-4763	75	22	and	and	CCONJ
cana-4763	75	23	hipaa	hipaa	NOUN
cana-4763	75	24	.	.	PUNCT
cana-4763	76	1	the	the	DET
cana-4763	76	2	method	method	NOUN
cana-4763	76	3	stands	stand	VERB
cana-4763	76	4	as	as	ADP
cana-4763	76	5	a	a	DET
cana-4763	76	6	potential	potential	ADJ
cana-4763	76	7	solution	solution	NOUN
cana-4763	76	8	for	for	ADP
cana-4763	76	9	making	make	VERB
cana-4763	76	10	robust	robust	ADJ
cana-4763	76	11	flexible	flexible	ADJ
cana-4763	76	12	brain	brain	NOUN
cana-4763	76	13	tumor	tumor	NOUN
cana-4763	76	14	classification	classification	NOUN
cana-4763	76	15	models	model	NOUN
cana-4763	76	16	which	which	PRON
cana-4763	76	17	combine	combine	VERB
cana-4763	76	18	information	information	NOUN
cana-4763	76	19	from	from	ADP
cana-4763	76	20	multiple	multiple	ADJ
cana-4763	76	21	healthcare	healthcare	NOUN
cana-4763	76	22	institutions	institution	NOUN
cana-4763	76	23	.	.	PUNCT
cana-4763	77	1	brain	brain	NOUN
cana-4763	77	2	tumor	tumor	NOUN
cana-4763	77	3	classification	classification	NOUN
cana-4763	77	4	achieves	achieve	VERB
cana-4763	77	5	advancements	advancement	NOUN
cana-4763	77	6	through	through	ADP
cana-4763	77	7	quantum	quantum	NOUN
cana-4763	77	8	machine	machine	NOUN
cana-4763	77	9	learning	learning	NOUN
cana-4763	77	10	(	(	PUNCT
cana-4763	77	11	qml	qml	NOUN
cana-4763	77	12	)	)	PUNCT
cana-4763	77	13	which	which	PRON
cana-4763	77	14	represents	represent	VERB
cana-4763	77	15	one	one	NUM
cana-4763	77	16	of	of	ADP
cana-4763	77	17	the	the	DET
cana-4763	77	18	most	most	ADV
cana-4763	77	19	sophisticated	sophisticated	ADJ
cana-4763	77	20	areas	area	NOUN
cana-4763	77	21	that	that	PRON
cana-4763	77	22	unifies	unify	VERB
cana-4763	77	23	quantum	quantum	NOUN
cana-4763	77	24	computing	computing	NOUN
cana-4763	77	25	with	with	ADP
cana-4763	77	26	machine	machine	NOUN
cana-4763	77	27	learning	learn	VERB
cana-4763	77	28	algorithms	algorithm	NOUN
cana-4763	77	29	.	.	PUNCT
cana-4763	78	1	studies	study	NOUN
cana-4763	78	2	have	have	AUX
cana-4763	78	3	proved	prove	VERB
cana-4763	78	4	that	that	SCONJ
cana-4763	78	5	introducing	introduce	VERB
cana-4763	78	6	qml[19	qml[19	NOUN
cana-4763	78	7	]	]	PUNCT
cana-4763	78	8	methods	method	NOUN
cana-4763	78	9	leads	lead	VERB
cana-4763	78	10	to	to	ADP
cana-4763	78	11	better	well	ADJ
cana-4763	78	12	feature	feature	NOUN
cana-4763	78	13	selection	selection	NOUN
cana-4763	78	14	results	result	NOUN
cana-4763	78	15	alongside	alongside	ADP
cana-4763	78	16	increased	increase	VERB
cana-4763	78	17	processing	processing	NOUN
cana-4763	78	18	speed	speed	NOUN
cana-4763	78	19	and	and	CCONJ
cana-4763	78	20	enhanced	enhance	VERB
cana-4763	78	21	classification	classification	NOUN
cana-4763	78	22	success	success	NOUN
cana-4763	78	23	rates	rate	NOUN
cana-4763	78	24	.	.	PUNCT
cana-4763	79	1	resolving	resolve	VERB
cana-4763	79	2	challenges	challenge	NOUN
cana-4763	79	3	in	in	ADP
cana-4763	79	4	managing	manage	VERB
cana-4763	79	5	complex	complex	ADJ
cana-4763	79	6	medical	medical	ADJ
cana-4763	79	7	imaging	imaging	NOUN
cana-4763	79	8	data	datum	NOUN
cana-4763	79	9	requires	require	VERB
cana-4763	79	10	researchers	researcher	NOUN
cana-4763	79	11	to	to	ADP
cana-4763	79	12	test	test	NOUN
cana-4763	79	13	models	model	NOUN
cana-4763	79	14	which	which	PRON
cana-4763	79	15	combine	combine	VERB
cana-4763	79	16	quantum	quantum	ADJ
cana-4763	79	17	circuits	circuit	NOUN
cana-4763	79	18	together	together	ADV
cana-4763	79	19	with	with	ADP
cana-4763	79	20	conventional	conventional	ADJ
cana-4763	79	21	neural	neural	ADJ
cana-4763	79	22	networks	network	NOUN
cana-4763	79	23	.	.	PUNCT
cana-4763	80	1	qlm	qlm	NOUN
cana-4763	80	2	has	have	VERB
cana-4763	80	3	capabilities	capability	NOUN
cana-4763	80	4	to	to	PART
cana-4763	80	5	tackle	tackle	VERB
cana-4763	80	6	difficult	difficult	ADJ
cana-4763	80	7	tasks	task	NOUN
cana-4763	80	8	in	in	ADP
cana-4763	80	9	deep	deep	ADJ
cana-4763	80	10	learning	learning	NOUN
cana-4763	80	11	model	model	NOUN
cana-4763	80	12	parameter	parameter	NOUN
cana-4763	80	13	adjustment	adjustment	NOUN
cana-4763	80	14	together	together	ADV
cana-4763	80	15	with	with	ADP
cana-4763	80	16	high	high	ADJ
cana-4763	80	17	-	-	PUNCT
cana-4763	80	18	dimensional	dimensional	ADJ
cana-4763	80	19	clustering	clustering	NOUN
cana-4763	80	20	.	.	PUNCT
cana-4763	81	1	qml	qml	NOUN
cana-4763	81	2	exists	exist	VERB
cana-4763	81	3	in	in	ADP
cana-4763	81	4	a	a	DET
cana-4763	81	5	preliminary	preliminary	ADJ
cana-4763	81	6	stage	stage	NOUN
cana-4763	81	7	but	but	CCONJ
cana-4763	81	8	shows	show	VERB
cana-4763	81	9	potential	potential	NOUN
cana-4763	81	10	to	to	PART
cana-4763	81	11	change	change	VERB
cana-4763	81	12	how	how	SCONJ
cana-4763	81	13	brain	brain	NOUN
cana-4763	81	14	tumors	tumor	NOUN
cana-4763	81	15	are	be	AUX
cana-4763	81	16	classified	classify	VERB
cana-4763	81	17	in	in	ADP
cana-4763	81	18	upcoming	upcoming	ADJ
cana-4763	81	19	years	year	NOUN
cana-4763	81	20	.	.	PUNCT
cana-4763	82	1	blood	blood	NOUN
cana-4763	82	2	cancer	cancer	NOUN
cana-4763	82	3	analysis	analysis	NOUN
cana-4763	82	4	depends	depend	VERB
cana-4763	82	5	on	on	ADP
cana-4763	82	6	the	the	DET
cana-4763	82	7	combination	combination	NOUN
cana-4763	82	8	of	of	ADP
cana-4763	82	9	current	current	ADJ
cana-4763	82	10	ai	ai	NOUN
cana-4763	82	11	technology	technology	NOUN
cana-4763	82	12	with	with	ADP
cana-4763	82	13	medical	medical	ADJ
cana-4763	82	14	expertise	expertise	NOUN
cana-4763	82	15	to	to	PART
cana-4763	82	16	achieve	achieve	VERB
cana-4763	82	17	better	well	ADJ
cana-4763	82	18	brain	brain	NOUN
cana-4763	82	19	tumor	tumor	NOUN
cana-4763	82	20	classification	classification	NOUN
cana-4763	82	21	.	.	PUNCT
cana-4763	83	1	accurate	accurate	ADJ
cana-4763	83	2	diagnosis	diagnosis	NOUN
cana-4763	83	3	along	along	ADP
cana-4763	83	4	with	with	ADP
cana-4763	83	5	understandability	understandability	NOUN
cana-4763	83	6	and	and	CCONJ
cana-4763	83	7	clinical	clinical	ADJ
cana-4763	83	8	applicability	applicability	NOUN
cana-4763	83	9	serves	serve	VERB
cana-4763	83	10	as	as	ADP
cana-4763	83	11	the	the	DET
cana-4763	83	12	primary	primary	ADJ
cana-4763	83	13	goals	goal	NOUN
cana-4763	83	14	of	of	ADP
cana-4763	83	15	this	this	DET
cana-4763	83	16	method	method	NOUN
cana-4763	83	17	.	.	PUNCT
cana-4763	84	1	1	1	X
cana-4763	84	2	.	.	X
cana-4763	84	3	literature	literature	NOUN
cana-4763	84	4	survey	survey	PROPN
cana-4763	84	5	saeedi	saeedi	VERB
cana-4763	84	6	s.	s.	PROPN
cana-4763	84	7	et	et	PROPN
cana-4763	84	8	al	al	PROPN
cana-4763	84	9	.	.	PUNCT
cana-4763	85	1	[	[	X
cana-4763	85	2	20	20	NUM
cana-4763	85	3	]	]	PUNCT
cana-4763	85	4	applied	apply	VERB
cana-4763	85	5	convolutional	convolutional	ADJ
cana-4763	85	6	neural	neural	ADJ
cana-4763	85	7	networks	network	NOUN
cana-4763	85	8	(	(	PUNCT
cana-4763	85	9	cnns	cnns	PROPN
cana-4763	85	10	)	)	PUNCT
cana-4763	85	11	for	for	ADP
cana-4763	85	12	brain	brain	NOUN
cana-4763	85	13	tumor	tumor	NOUN
cana-4763	85	14	classification	classification	NOUN
cana-4763	85	15	.	.	PUNCT
cana-4763	86	1	their	their	PRON
cana-4763	86	2	main	main	ADJ
cana-4763	86	3	goal	goal	NOUN
cana-4763	86	4	focused	focus	VERB
cana-4763	86	5	on	on	ADP
cana-4763	86	6	solving	solve	VERB
cana-4763	86	7	small	small	ADJ
cana-4763	86	8	dataset	dataset	NOUN
cana-4763	86	9	problems	problem	NOUN
cana-4763	86	10	through	through	ADP
cana-4763	86	11	enhanced	enhanced	ADJ
cana-4763	86	12	data	datum	NOUN
cana-4763	86	13	augmentation	augmentation	NOUN
cana-4763	86	14	methods	method	NOUN
cana-4763	86	15	that	that	PRON
cana-4763	86	16	included	include	VERB
cana-4763	86	17	flipping	flipping	NOUN
cana-4763	86	18	and	and	CCONJ
cana-4763	86	19	rotation	rotation	NOUN
cana-4763	86	20	and	and	CCONJ
cana-4763	86	21	brightness	brightness	NOUN
cana-4763	86	22	adjustment	adjustment	NOUN
cana-4763	86	23	.	.	PUNCT
cana-4763	87	1	through	through	ADP
cana-4763	87	2	their	their	PRON
cana-4763	87	3	implementation	implementation	NOUN
cana-4763	87	4	of	of	ADP
cana-4763	87	5	dropout	dropout	NOUN
cana-4763	87	6	layers	layer	NOUN
cana-4763	87	7	and	and	CCONJ
cana-4763	87	8	transfer	transfer	NOUN
cana-4763	87	9	learning	learning	NOUN
cana-4763	87	10	methods	method	NOUN
cana-4763	87	11	the	the	DET
cana-4763	87	12	researchers	researcher	NOUN
cana-4763	87	13	reached	reach	VERB
cana-4763	87	14	a	a	DET
cana-4763	87	15	92	92	NUM
cana-4763	87	16	percent	percent	NOUN
cana-4763	87	17	accuracy	accuracy	NOUN
cana-4763	87	18	level	level	NOUN
cana-4763	87	19	with	with	ADP
cana-4763	87	20	superior	superior	ADJ
cana-4763	87	21	capability	capability	NOUN
cana-4763	87	22	against	against	ADP
cana-4763	87	23	overfitting	overfitting	NOUN
cana-4763	87	24	.	.	PUNCT
cana-4763	88	1	shanti	shanti	PROPN
cana-4763	88	2	et	et	PROPN
cana-4763	88	3	al	al	PROPN
cana-4763	88	4	.	.	PUNCT
cana-4763	89	1	[	[	X
cana-4763	89	2	21	21	NUM
cana-4763	89	3	]	]	PUNCT
cana-4763	89	4	created	create	VERB
cana-4763	89	5	an	an	DET
cana-4763	89	6	optimized	optimize	VERB
cana-4763	89	7	hybrid	hybrid	ADJ
cana-4763	89	8	deep	deep	ADJ
cana-4763	89	9	neural	neural	ADJ
cana-4763	89	10	network	network	NOUN
cana-4763	89	11	(	(	PUNCT
cana-4763	89	12	ohdnn	ohdnn	NOUN
cana-4763	89	13	)	)	PUNCT
cana-4763	89	14	as	as	ADP
cana-4763	89	15	a	a	DET
cana-4763	89	16	system	system	NOUN
cana-4763	89	17	for	for	ADP
cana-4763	89	18	automatic	automatic	ADJ
cana-4763	89	19	brain	brain	NOUN
cana-4763	89	20	tumor	tumor	NOUN
cana-4763	89	21	classification	classification	NOUN
cana-4763	89	22	.	.	PUNCT
cana-4763	90	1	their	their	PRON
cana-4763	90	2	method	method	NOUN
cana-4763	90	3	operated	operate	VERB
cana-4763	90	4	through	through	ADP
cana-4763	90	5	two	two	NUM
cana-4763	90	6	sequential	sequential	ADJ
cana-4763	90	7	steps	step	NOUN
cana-4763	90	8	that	that	PRON
cana-4763	90	9	started	start	VERB
cana-4763	90	10	with	with	ADP
cana-4763	90	11	pre	pre	ADJ
cana-4763	90	12	-	-	ADJ
cana-4763	90	13	processing	processing	NOUN
cana-4763	90	14	followed	follow	VERB
cana-4763	90	15	by	by	ADP
cana-4763	90	16	classification	classification	NOUN
cana-4763	90	17	.	.	PUNCT
cana-4763	91	1	the	the	DET
cana-4763	91	2	cnn	cnn	PROPN
cana-4763	91	3	-	-	PUNCT
cana-4763	91	4	lstm	lstm	PROPN
cana-4763	91	5	model	model	NOUN
cana-4763	91	6	combined	combined	PROPN
cana-4763	91	7	cnn	cnn	PROPN
cana-4763	91	8	features	feature	VERB
cana-4763	91	9	extraction	extraction	NOUN
cana-4763	91	10	with	with	ADP
cana-4763	91	11	lstm	lstm	NOUN
cana-4763	91	12	classification	classification	NOUN
cana-4763	91	13	operations	operation	NOUN
cana-4763	91	14	.	.	PUNCT
cana-4763	92	1	the	the	DET
cana-4763	92	2	method	method	NOUN
cana-4763	92	3	reached	reach	VERB
cana-4763	92	4	improved	improved	ADJ
cana-4763	92	5	performance	performance	NOUN
cana-4763	92	6	levels	level	NOUN
cana-4763	92	7	through	through	ADP
cana-4763	92	8	classifier	classifier	NOUN
cana-4763	92	9	parameter	parameter	NOUN
cana-4763	92	10	adjustments	adjustment	NOUN
cana-4763	92	11	applying	apply	VERB
cana-4763	92	12	the	the	DET
cana-4763	92	13	adaptive	adaptive	ADJ
cana-4763	92	14	rider	rider	NOUN
cana-4763	92	15	optimization	optimization	NOUN
cana-4763	92	16	(	(	PUNCT
cana-4763	92	17	aro	aro	NOUN
cana-4763	92	18	)	)	PUNCT
cana-4763	92	19	algorithm	algorithm	NOUN
cana-4763	92	20	.	.	PUNCT
cana-4763	93	1	gupta	gupta	PROPN
cana-4763	93	2	et	et	PROPN
cana-4763	93	3	al	al	PROPN
cana-4763	93	4	.	.	PUNCT
cana-4763	94	1	[	[	X
cana-4763	94	2	22	22	NUM
cana-4763	94	3	]	]	PUNCT
cana-4763	94	4	created	create	VERB
cana-4763	94	5	a	a	DET
cana-4763	94	6	multiscale	multiscale	ADJ
cana-4763	94	7	cnn	cnn	NOUN
cana-4763	94	8	architecture	architecture	NOUN
cana-4763	94	9	which	which	PRON
cana-4763	94	10	analyzed	analyze	VERB
cana-4763	94	11	image	image	NOUN
cana-4763	94	12	patches	patch	NOUN
cana-4763	94	13	at	at	ADP
cana-4763	94	14	different	different	ADJ
cana-4763	94	15	resolutions	resolution	NOUN
cana-4763	94	16	to	to	PART
cana-4763	94	17	simultaneously	simultaneously	ADV
cana-4763	94	18	extract	extract	VERB
cana-4763	94	19	brain	brain	NOUN
cana-4763	94	20	tumor	tumor	NOUN
cana-4763	94	21	fine	fine	ADJ
cana-4763	94	22	and	and	CCONJ
cana-4763	94	23	coarse	coarse	ADJ
cana-4763	94	24	elements	element	NOUN
cana-4763	94	25	.	.	PUNCT
cana-4763	95	1	the	the	DET
cana-4763	95	2	model	model	NOUN
cana-4763	95	3	achieved	achieve	VERB
cana-4763	95	4	benchmark	benchmark	NOUN
cana-4763	95	5	-	-	PUNCT
cana-4763	95	6	dataset	dataset	VERB
cana-4763	95	7	benchmarks	benchmark	NOUN
cana-4763	95	8	reaching	reach	VERB
cana-4763	95	9	90.5	90.5	NUM
cana-4763	95	10	percent	percent	NOUN
cana-4763	95	11	accuracy	accuracy	NOUN
cana-4763	95	12	to	to	PART
cana-4763	95	13	differentiate	differentiate	VERB
cana-4763	95	14	lowand	lowand	ADJ
cana-4763	95	15	high	high	ADJ
cana-4763	95	16	-	-	PUNCT
cana-4763	95	17	grade	grade	NOUN
cana-4763	95	18	gliomas	glioma	NOUN
cana-4763	95	19	.	.	PUNCT
cana-4763	96	1	medical	medical	ADJ
cana-4763	96	2	imaging	imaging	NOUN
cana-4763	96	3	outcomes	outcome	NOUN
cana-4763	96	4	demonstrate	demonstrate	VERB
cana-4763	96	5	that	that	SCONJ
cana-4763	96	6	deep	deep	ADJ
cana-4763	96	7	learning	learning	NOUN
cana-4763	96	8	proves	prove	VERB
cana-4763	96	9	to	to	PART
cana-4763	96	10	be	be	AUX
cana-4763	96	11	effective	effective	ADJ
cana-4763	96	12	for	for	ADP
cana-4763	96	13	enhancing	enhance	VERB
cana-4763	96	14	diagnostic	diagnostic	ADJ
cana-4763	96	15	accuracy	accuracy	NOUN
cana-4763	96	16	specifically	specifically	ADV
cana-4763	96	17	in	in	ADP
cana-4763	96	18	medical	medical	ADJ
cana-4763	96	19	diagnostic	diagnostic	ADJ
cana-4763	96	20	applications	application	NOUN
cana-4763	96	21	.	.	PUNCT
cana-4763	97	1	afshar	afshar	ADJ
cana-4763	97	2	parnian	parnian	PROPN
cana-4763	97	3	et	et	PROPN
cana-4763	97	4	al	al	PROPN
cana-4763	97	5	.	.	PUNCT
cana-4763	98	1	[	[	X
cana-4763	98	2	23	23	NUM
cana-4763	98	3	]	]	PUNCT
cana-4763	98	4	introduced	introduce	VERB
cana-4763	98	5	a	a	DET
cana-4763	98	6	capsnet	capsnet	NOUN
cana-4763	98	7	model	model	NOUN
cana-4763	98	8	which	which	PRON
cana-4763	98	9	performed	perform	VERB
cana-4763	98	10	classification	classification	NOUN
cana-4763	98	11	operations	operation	NOUN
cana-4763	98	12	through	through	ADP
cana-4763	98	13	the	the	DET
cana-4763	98	14	combination	combination	NOUN
cana-4763	98	15	of	of	ADP
cana-4763	98	16	tumor	tumor	NOUN
cana-4763	98	17	contours	contours	NOUN
cana-4763	98	18	and	and	CCONJ
cana-4763	98	19	raw	raw	ADJ
cana-4763	98	20	mri	mri	NOUN
cana-4763	98	21	scans	scan	NOUN
cana-4763	98	22	.	.	PUNCT
cana-4763	99	1	the	the	DET
cana-4763	99	2	new	new	ADJ
cana-4763	99	3	approach	approach	NOUN
cana-4763	99	4	eliminated	eliminate	VERB
cana-4763	99	5	the	the	DET
cana-4763	99	6	need	need	NOUN
cana-4763	99	7	for	for	ADP
cana-4763	99	8	precise	precise	ADJ
cana-4763	99	9	tumor	tumor	NOUN
cana-4763	99	10	annotation	annotation	NOUN
cana-4763	99	11	so	so	SCONJ
cana-4763	99	12	the	the	DET
cana-4763	99	13	model	model	NOUN
cana-4763	99	14	could	could	AUX
cana-4763	99	15	focus	focus	VERB
cana-4763	99	16	on	on	ADP
cana-4763	99	17	analyzing	analyze	VERB
cana-4763	99	18	both	both	CCONJ
cana-4763	99	19	the	the	DET
cana-4763	99	20	main	main	ADJ
cana-4763	99	21	tumor	tumor	NOUN
cana-4763	99	22	area	area	NOUN
cana-4763	99	23	and	and	CCONJ
cana-4763	99	24	its	its	PRON
cana-4763	99	25	tissue	tissue	NOUN
cana-4763	99	26	interactions	interaction	NOUN
cana-4763	99	27	.	.	PUNCT
cana-4763	100	1	the	the	DET
cana-4763	100	2	spatial	spatial	ADJ
cana-4763	100	3	characteristics	characteristic	NOUN
cana-4763	100	4	of	of	ADP
cana-4763	100	5	features	feature	NOUN
cana-4763	100	6	received	receive	VERB
cana-4763	100	7	successful	successful	ADJ
cana-4763	100	8	representation	representation	NOUN
cana-4763	100	9	through	through	ADP
cana-4763	100	10	capsule	capsule	NOUN
cana-4763	100	11	networks	network	NOUN
cana-4763	100	12	allowing	allow	VERB
cana-4763	100	13	them	they	PRON
cana-4763	100	14	to	to	PART
cana-4763	100	15	outperform	outperform	VERB
cana-4763	100	16	traditional	traditional	ADJ
cana-4763	100	17	cnns	cnn	NOUN
cana-4763	100	18	with	with	ADP
cana-4763	100	19	a	a	DET
cana-4763	100	20	93	93	NUM
cana-4763	100	21	%	%	NOUN
cana-4763	100	22	classification	classification	NOUN
cana-4763	100	23	success	success	NOUN
cana-4763	100	24	.	.	PUNCT
cana-4763	101	1	al	al	PROPN
cana-4763	101	2	tahhan	tahhan	PROPN
cana-4763	101	3	et	et	PROPN
cana-4763	101	4	al	al	PROPN
cana-4763	101	5	.	.	PUNCT
cana-4763	102	1	[	[	X
cana-4763	102	2	24	24	NUM
cana-4763	102	3	]	]	PUNCT
cana-4763	102	4	developed	develop	VERB
cana-4763	102	5	a	a	DET
cana-4763	102	6	cnn	cnn	PROPN
cana-4763	102	7	model	model	NOUN
cana-4763	102	8	which	which	PRON
cana-4763	102	9	integrates	integrate	VERB
cana-4763	102	10	u	u	NOUN
cana-4763	102	11	-	-	NOUN
cana-4763	102	12	net	net	ADJ
cana-4763	102	13	with	with	ADP
cana-4763	102	14	a	a	DET
cana-4763	102	15	refined	refined	ADJ
cana-4763	102	16	resnet50	resnet50	NOUN
cana-4763	102	17	for	for	ADP
cana-4763	102	18	brain	brain	NOUN
cana-4763	102	19	tumor	tumor	NOUN
cana-4763	102	20	identification	identification	NOUN
cana-4763	102	21	and	and	CCONJ
cana-4763	102	22	categorization	categorization	NOUN
cana-4763	102	23	in	in	ADP
cana-4763	102	24	mri	mri	NOUN
cana-4763	102	25	images	image	NOUN
cana-4763	102	26	.	.	PUNCT
cana-4763	103	1	the	the	DET
cana-4763	103	2	resnet50	resnet50	NOUN
cana-4763	103	3	architecture	architecture	NOUN
cana-4763	103	4	achieved	achieve	VERB
cana-4763	103	5	detection	detection	NOUN
cana-4763	103	6	accuracy	accuracy	NOUN
cana-4763	103	7	between	between	ADP
cana-4763	103	8	0.87	0.87	NUM
cana-4763	103	9	and	and	CCONJ
cana-4763	103	10	0.98	0.98	NUM
cana-4763	103	11	for	for	ADP
cana-4763	103	12	precision	precision	NOUN
cana-4763	103	13	,	,	PUNCT
cana-4763	103	14	recall	recall	NOUN
cana-4763	103	15	,	,	PUNCT
cana-4763	103	16	f1	f1	NOUN
cana-4763	103	17	score	score	NOUN
cana-4763	103	18	and	and	CCONJ
cana-4763	103	19	overall	overall	ADJ
cana-4763	103	20	accuracy	accuracy	NOUN
cana-4763	103	21	.	.	PUNCT
cana-4763	104	1	the	the	DET
cana-4763	104	2	model	model	NOUN
cana-4763	104	3	showed	show	VERB
cana-4763	104	4	outstanding	outstanding	ADJ
cana-4763	104	5	segmentation	segmentation	NOUN
cana-4763	104	6	performance	performance	NOUN
cana-4763	104	7	through	through	ADP
cana-4763	104	8	its	its	PRON
cana-4763	104	9	iou	iou	NOUN
cana-4763	104	10	measurement	measurement	NOUN
cana-4763	104	11	of	of	ADP
cana-4763	104	12	0.91	0.91	NUM
cana-4763	104	13	and	and	CCONJ
cana-4763	104	14	dsc	dsc	NOUN
cana-4763	104	15	value	value	NOUN
cana-4763	104	16	of	of	ADP
cana-4763	104	17	0.95	0.95	NUM
cana-4763	104	18	.	.	PUNCT
cana-4763	105	1	el	el	NOUN
cana-4763	105	2	-	-	PUNCT
cana-4763	105	3	assy	assy	PROPN
cana-4763	105	4	et	et	PROPN
cana-4763	105	5	al	al	PROPN
cana-4763	105	6	.	.	PUNCT
cana-4763	106	1	[	[	X
cana-4763	106	2	25	25	NUM
cana-4763	106	3	]	]	PUNCT
cana-4763	106	4	introduced	introduce	VERB
cana-4763	106	5	a	a	DET
cana-4763	106	6	cnn	cnn	NOUN
cana-4763	106	7	architecture	architecture	NOUN
cana-4763	106	8	which	which	PRON
cana-4763	106	9	combines	combine	VERB
cana-4763	106	10	inceptionv3	inceptionv3	NOUN
cana-4763	106	11	,	,	PUNCT
cana-4763	106	12	resnet-50	resnet-50	PROPN
cana-4763	106	13	,	,	PUNCT
cana-4763	106	14	vgg16	vgg16	NOUN
cana-4763	106	15	and	and	CCONJ
cana-4763	106	16	densenet	densenet	NOUN
cana-4763	106	17	to	to	PART
cana-4763	106	18	classify	classify	VERB
cana-4763	106	19	brain	brain	NOUN
cana-4763	106	20	tumors	tumor	NOUN
cana-4763	106	21	.	.	PUNCT
cana-4763	107	1	they	they	PRON
cana-4763	107	2	dedicated	dedicate	VERB
cana-4763	107	3	their	their	PRON
cana-4763	107	4	time	time	NOUN
cana-4763	107	5	to	to	ADP
cana-4763	107	6	using	use	VERB
cana-4763	107	7	u	u	NOUN
cana-4763	107	8	-	-	NOUN
cana-4763	107	9	net	net	ADJ
cana-4763	107	10	for	for	ADP
cana-4763	107	11	mask	mask	NOUN
cana-4763	107	12	creation	creation	NOUN
cana-4763	107	13	and	and	CCONJ
cana-4763	107	14	feature	feature	NOUN
cana-4763	107	15	extraction	extraction	NOUN
cana-4763	107	16	from	from	ADP
cana-4763	107	17	all	all	DET
cana-4763	107	18	four	four	NUM
cana-4763	107	19	cnn	cnn	PROPN
cana-4763	107	20	models	model	NOUN
cana-4763	107	21	while	while	SCONJ
cana-4763	107	22	processing	processing	NOUN
cana-4763	107	23	mri	mri	NOUN
cana-4763	107	24	images	image	NOUN
cana-4763	107	25	.	.	PUNCT
cana-4763	108	1	the	the	DET
cana-4763	108	2	researchers	researcher	NOUN
cana-4763	108	3	integrated	integrate	VERB
cana-4763	108	4	an	an	DET
cana-4763	108	5	xai	xai	NOUN
cana-4763	108	6	layer	layer	NOUN
cana-4763	108	7	for	for	ADP
cana-4763	108	8	better	well	ADJ
cana-4763	108	9	interpretability	interpretability	NOUN
cana-4763	108	10	.	.	PUNCT
cana-4763	109	1	the	the	DET
cana-4763	109	2	proposed	propose	VERB
cana-4763	109	3	architecture	architecture	NOUN
cana-4763	109	4	achieved	achieve	VERB
cana-4763	109	5	superior	superior	ADJ
cana-4763	109	6	performance	performance	NOUN
cana-4763	109	7	than	than	ADP
cana-4763	109	8	the	the	DET
cana-4763	109	9	single	single	ADJ
cana-4763	109	10	models	model	NOUN
cana-4763	109	11	densenet	densenet	NOUN
cana-4763	109	12	(	(	PUNCT
cana-4763	109	13	94.65	94.65	NUM
cana-4763	109	14	percent	percent	NOUN
cana-4763	109	15	)	)	PUNCT
cana-4763	109	16	,	,	PUNCT
cana-4763	109	17	vgg16	vgg16	NOUN
cana-4763	109	18	(	(	PUNCT
cana-4763	109	19	91.04	91.04	NUM
cana-4763	109	20	percent	percent	NOUN
cana-4763	109	21	)	)	PUNCT
cana-4763	109	22	,	,	PUNCT
cana-4763	109	23	inceptionv3	inceptionv3	NOUN
cana-4763	109	24	(	(	PUNCT
cana-4763	109	25	71.54	71.54	NUM
cana-4763	109	26	percent	percent	NOUN
cana-4763	109	27	)	)	PUNCT
cana-4763	109	28	and	and	CCONJ
cana-4763	109	29	resnet-50	resnet-50	PROPN
cana-4763	109	30	(	(	PUNCT
cana-4763	109	31	95.5	95.5	NUM
cana-4763	109	32	percent	percent	NOUN
cana-4763	109	33	)	)	PUNCT
cana-4763	109	34	by	by	ADP
cana-4763	109	35	reaching	reach	VERB
cana-4763	109	36	an	an	DET
cana-4763	109	37	outstanding	outstanding	ADJ
cana-4763	109	38	96.2	96.2	NUM
cana-4763	109	39	percent	percent	NOUN
cana-4763	109	40	accuracy	accuracy	NOUN
cana-4763	109	41	.	.	PUNCT
cana-4763	110	1	mohamed	mohamed	PROPN
cana-4763	110	2	r.	r.	PROPN
cana-4763	110	3	shoaib	shoaib	PROPN
cana-4763	110	4	et	et	PROPN
cana-4763	110	5	al	al	PROPN
cana-4763	110	6	.	.	PUNCT
cana-4763	111	1	[	[	X
cana-4763	111	2	26	26	NUM
cana-4763	111	3	]	]	AUX
cana-4763	111	4	describes	describe	VERB
cana-4763	111	5	a	a	DET
cana-4763	111	6	brain	brain	NOUN
cana-4763	111	7	tumor	tumor	NOUN
cana-4763	111	8	classification	classification	NOUN
cana-4763	111	9	method	method	NOUN
cana-4763	111	10	which	which	PRON
cana-4763	111	11	unites	unite	VERB
cana-4763	111	12	support	support	NOUN
cana-4763	111	13	vector	vector	NOUN
cana-4763	111	14	machines	machine	NOUN
cana-4763	111	15	(	(	PUNCT
cana-4763	111	16	svm	svm	PROPN
cana-4763	111	17	)	)	PUNCT
cana-4763	111	18	,	,	PUNCT
cana-4763	111	19	mask	mask	VERB
cana-4763	111	20	r	r	NOUN
cana-4763	111	21	-	-	PUNCT
cana-4763	111	22	cnn	cnn	PROPN
cana-4763	111	23	,	,	PUNCT
cana-4763	111	24	and	and	CCONJ
cana-4763	111	25	anisotropic	anisotropic	NOUN
cana-4763	111	26	diffusion	diffusion	NOUN
cana-4763	111	27	.	.	PUNCT
cana-4763	112	1	the	the	DET
cana-4763	112	2	researchers	researcher	NOUN
cana-4763	112	3	selected	select	VERB
cana-4763	112	4	transfer	transfer	NOUN
cana-4763	112	5	learning	learn	VERB
cana-4763	112	6	to	to	PART
cana-4763	112	7	derive	derive	VERB
cana-4763	112	8	communications	communication	NOUN
cana-4763	112	9	on	on	ADP
cana-4763	112	10	applied	apply	VERB
cana-4763	112	11	nonlinear	nonlinear	ADJ
cana-4763	112	12	analysis	analysis	NOUN
cana-4763	112	13	issn	issn	NOUN
cana-4763	112	14	:	:	PUNCT
cana-4763	112	15	1074	1074	NUM
cana-4763	112	16	-	-	PUNCT
cana-4763	112	17	133x	133x	NUM
cana-4763	112	18	vol	vol	VERB
cana-4763	112	19	32	32	NUM
cana-4763	112	20	no	no	NOUN
cana-4763	112	21	.	.	PUNCT
cana-4763	113	1	10s	10	NOUN
cana-4763	113	2	(	(	PUNCT
cana-4763	113	3	2025	2025	NUM
cana-4763	113	4	)	)	PUNCT
cana-4763	113	5	299	299	NUM
cana-4763	113	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	113	7	features	feature	VERB
cana-4763	113	8	from	from	ADP
cana-4763	113	9	smaller	small	ADJ
cana-4763	113	10	datasets	dataset	NOUN
cana-4763	113	11	while	while	SCONJ
cana-4763	113	12	they	they	PRON
cana-4763	113	13	modified	modify	VERB
cana-4763	113	14	hyperparameters	hyperparameter	NOUN
cana-4763	113	15	so	so	SCONJ
cana-4763	113	16	the	the	DET
cana-4763	113	17	model	model	NOUN
cana-4763	113	18	would	would	AUX
cana-4763	113	19	not	not	PART
cana-4763	113	20	overfit	overfit	VERB
cana-4763	113	21	.	.	PUNCT
cana-4763	114	1	the	the	DET
cana-4763	114	2	proposed	propose	VERB
cana-4763	114	3	model	model	NOUN
cana-4763	114	4	performed	perform	VERB
cana-4763	114	5	significantly	significantly	ADV
cana-4763	114	6	better	well	ADJ
cana-4763	114	7	than	than	ADP
cana-4763	114	8	standard	standard	ADJ
cana-4763	114	9	classifiers	classifier	NOUN
cana-4763	114	10	operating	operate	VERB
cana-4763	114	11	with	with	ADP
cana-4763	114	12	an	an	DET
cana-4763	114	13	accuracy	accuracy	NOUN
cana-4763	114	14	level	level	NOUN
cana-4763	114	15	of	of	ADP
cana-4763	114	16	92.3	92.3	NUM
cana-4763	114	17	%	%	NOUN
cana-4763	114	18	while	while	SCONJ
cana-4763	114	19	random	random	ADJ
cana-4763	114	20	forest	forest	NOUN
cana-4763	114	21	achieved	achieve	VERB
cana-4763	114	22	85.4	85.4	NUM
cana-4763	114	23	percent	percent	NOUN
cana-4763	114	24	accuracy	accuracy	NOUN
cana-4763	114	25	and	and	CCONJ
cana-4763	114	26	svm	svm	PROPN
cana-4763	114	27	produced	produce	VERB
cana-4763	114	28	82.7	82.7	NUM
cana-4763	114	29	percent	percent	NOUN
cana-4763	114	30	accuracy	accuracy	NOUN
cana-4763	114	31	.	.	PUNCT
cana-4763	115	1	all	all	DET
cana-4763	115	2	studies	study	NOUN
cana-4763	115	3	together	together	ADV
cana-4763	115	4	demonstrate	demonstrate	VERB
cana-4763	115	5	that	that	SCONJ
cana-4763	115	6	ai	ai	VERB
cana-4763	115	7	modern	modern	ADJ
cana-4763	115	8	techniques	technique	NOUN
cana-4763	115	9	and	and	CCONJ
cana-4763	115	10	precision	precision	NOUN
cana-4763	115	11	improvement	improvement	NOUN
cana-4763	115	12	along	along	ADP
cana-4763	115	13	with	with	ADP
cana-4763	115	14	interpretive	interpretive	ADJ
cana-4763	115	15	features	feature	NOUN
cana-4763	115	16	have	have	AUX
cana-4763	115	17	expedited	expedite	VERB
cana-4763	115	18	brain	brain	NOUN
cana-4763	115	19	tumor	tumor	NOUN
cana-4763	115	20	diagnostic	diagnostic	ADJ
cana-4763	115	21	classification	classification	NOUN
cana-4763	115	22	.	.	PUNCT
cana-4763	116	1	the	the	DET
cana-4763	116	2	medical	medical	ADJ
cana-4763	116	3	field	field	NOUN
cana-4763	116	4	will	will	AUX
cana-4763	116	5	advance	advance	VERB
cana-4763	116	6	brain	brain	NOUN
cana-4763	116	7	tumor	tumor	NOUN
cana-4763	116	8	diagnosis	diagnosis	NOUN
cana-4763	116	9	and	and	CCONJ
cana-4763	116	10	treatment	treatment	NOUN
cana-4763	116	11	through	through	ADP
cana-4763	116	12	advanced	advanced	ADJ
cana-4763	116	13	techniques	technique	NOUN
cana-4763	116	14	such	such	ADJ
cana-4763	116	15	as	as	ADP
cana-4763	116	16	explainable	explainable	ADJ
cana-4763	116	17	ai	ai	NOUN
cana-4763	116	18	and	and	CCONJ
cana-4763	116	19	federated	federated	ADJ
cana-4763	116	20	learning	learning	NOUN
cana-4763	116	21	along	along	ADP
cana-4763	116	22	with	with	ADP
cana-4763	116	23	quantum	quantum	ADJ
cana-4763	116	24	machine	machine	NOUN
cana-4763	116	25	learning	learning	NOUN
cana-4763	116	26	methods	method	NOUN
cana-4763	116	27	.	.	PUNCT
cana-4763	117	1	3	3	X
cana-4763	117	2	.	.	NUM
cana-4763	117	3	proposed	propose	VERB
cana-4763	117	4	method	method	NOUN
cana-4763	117	5	the	the	DET
cana-4763	117	6	proposed	propose	VERB
cana-4763	117	7	approach	approach	NOUN
cana-4763	117	8	in	in	ADP
cana-4763	117	9	brain	brain	NOUN
cana-4763	117	10	tumor	tumor	NOUN
cana-4763	117	11	categorization	categorization	NOUN
cana-4763	117	12	employs	employ	VERB
cana-4763	117	13	various	various	ADJ
cana-4763	117	14	modern	modern	ADJ
cana-4763	117	15	techniques	technique	NOUN
cana-4763	117	16	with	with	ADP
cana-4763	117	17	the	the	DET
cana-4763	117	18	aim	aim	NOUN
cana-4763	117	19	to	to	PART
cana-4763	117	20	be	be	AUX
cana-4763	117	21	more	more	ADV
cana-4763	117	22	precise	precise	ADJ
cana-4763	117	23	while	while	SCONJ
cana-4763	117	24	ensuring	ensure	VERB
cana-4763	117	25	good	good	ADJ
cana-4763	117	26	efficiency	efficiency	NOUN
cana-4763	117	27	.	.	PUNCT
cana-4763	118	1	the	the	DET
cana-4763	118	2	suggested	suggest	VERB
cana-4763	118	3	system	system	NOUN
cana-4763	118	4	deploys	deploy	VERB
cana-4763	118	5	advanced	advanced	ADJ
cana-4763	118	6	image	image	NOUN
cana-4763	118	7	processing	processing	NOUN
cana-4763	118	8	techniques	technique	NOUN
cana-4763	118	9	integrated	integrate	VERB
cana-4763	118	10	with	with	ADP
cana-4763	118	11	top	top	ADJ
cana-4763	118	12	algorithms	algorithm	NOUN
cana-4763	118	13	in	in	ADP
cana-4763	118	14	machine	machine	NOUN
cana-4763	118	15	learning	learn	VERB
cana-4763	118	16	along	along	ADP
cana-4763	118	17	with	with	ADP
cana-4763	118	18	well	well	ADV
cana-4763	118	19	-	-	PUNCT
cana-4763	118	20	established	establish	VERB
cana-4763	118	21	data	data	NOUN
cana-4763	118	22	analytics	analytic	NOUN
cana-4763	118	23	tools	tool	NOUN
cana-4763	118	24	.	.	PUNCT
cana-4763	119	1	patients	patient	NOUN
cana-4763	119	2	are	be	AUX
cana-4763	119	3	detected	detect	VERB
cana-4763	119	4	and	and	CCONJ
cana-4763	119	5	directed	direct	VERB
cana-4763	119	6	to	to	PART
cana-4763	119	7	appropriate	appropriate	ADJ
cana-4763	119	8	diagnosis	diagnosis	NOUN
cana-4763	119	9	and	and	CCONJ
cana-4763	119	10	targeted	target	VERB
cana-4763	119	11	treatment	treatment	NOUN
cana-4763	119	12	protocols	protocol	NOUN
cana-4763	119	13	through	through	ADP
cana-4763	119	14	technological	technological	ADJ
cana-4763	119	15	deployment	deployment	NOUN
cana-4763	119	16	in	in	ADP
cana-4763	119	17	the	the	DET
cana-4763	119	18	system	system	NOUN
cana-4763	119	19	.	.	PUNCT
cana-4763	120	1	fig	fig	NOUN
cana-4763	120	2	1	1	NUM
cana-4763	120	3	:	:	PUNCT
cana-4763	120	4	proposed	propose	VERB
cana-4763	120	5	block	block	NOUN
cana-4763	120	6	diagram	diagram	NOUN
cana-4763	120	7	the	the	DET
cana-4763	120	8	methodology	methodology	NOUN
cana-4763	120	9	follows	follow	VERB
cana-4763	120	10	four	four	NUM
cana-4763	120	11	main	main	ADJ
cana-4763	120	12	phases	phase	NOUN
cana-4763	120	13	which	which	PRON
cana-4763	120	14	include	include	VERB
cana-4763	120	15	preprocessing	preprocesse	VERB
cana-4763	120	16	combined	combine	VERB
cana-4763	120	17	with	with	ADP
cana-4763	120	18	feature	feature	NOUN
cana-4763	120	19	extraction	extraction	NOUN
cana-4763	120	20	followed	follow	VERB
cana-4763	120	21	by	by	ADP
cana-4763	120	22	feature	feature	NOUN
cana-4763	120	23	selection	selection	NOUN
cana-4763	120	24	finished	finish	VERB
cana-4763	120	25	by	by	ADP
cana-4763	120	26	classification	classification	NOUN
cana-4763	120	27	.	.	PUNCT
cana-4763	121	1	the	the	DET
cana-4763	121	2	preprocessing	preprocessing	NOUN
cana-4763	121	3	step	step	NOUN
cana-4763	121	4	reduces	reduce	VERB
cana-4763	121	5	medical	medical	ADJ
cana-4763	121	6	image	image	NOUN
cana-4763	121	7	noise	noise	NOUN
cana-4763	121	8	through	through	ADP
cana-4763	121	9	bilateral	bilateral	ADJ
cana-4763	121	10	filtering	filtering	NOUN
cana-4763	121	11	to	to	PART
cana-4763	121	12	protect	protect	VERB
cana-4763	121	13	brain	brain	NOUN
cana-4763	121	14	tumor	tumor	NOUN
cana-4763	121	15	edge	edge	NOUN
cana-4763	121	16	regions	region	NOUN
cana-4763	121	17	.	.	PUNCT
cana-4763	122	1	accurate	accurate	ADJ
cana-4763	122	2	feature	feature	NOUN
cana-4763	122	3	extraction	extraction	NOUN
cana-4763	122	4	and	and	CCONJ
cana-4763	122	5	classification	classification	NOUN
cana-4763	122	6	later	later	ADV
cana-4763	122	7	depend	depend	VERB
cana-4763	122	8	on	on	ADP
cana-4763	122	9	this	this	DET
cana-4763	122	10	step	step	NOUN
cana-4763	122	11	due	due	ADP
cana-4763	122	12	to	to	ADP
cana-4763	122	13	the	the	DET
cana-4763	122	14	important	important	ADJ
cana-4763	122	15	role	role	NOUN
cana-4763	122	16	it	it	PRON
cana-4763	122	17	plays	play	VERB
cana-4763	122	18	in	in	ADP
cana-4763	122	19	preserving	preserve	VERB
cana-4763	122	20	structural	structural	ADJ
cana-4763	122	21	details	detail	NOUN
cana-4763	122	22	.	.	PUNCT
cana-4763	123	1	ii	ii	PROPN
cana-4763	123	2	.	.	PUNCT
cana-4763	124	1	local	local	ADJ
cana-4763	124	2	binary	binary	ADJ
cana-4763	124	3	pattern	pattern	NOUN
cana-4763	124	4	(	(	PUNCT
cana-4763	124	5	lbp	lbp	NOUN
cana-4763	124	6	)	)	PUNCT
cana-4763	124	7	enables	enable	VERB
cana-4763	124	8	the	the	DET
cana-4763	124	9	extraction	extraction	NOUN
cana-4763	124	10	of	of	ADP
cana-4763	124	11	important	important	ADJ
cana-4763	124	12	textural	textural	ADJ
cana-4763	124	13	data	datum	NOUN
cana-4763	124	14	from	from	ADP
cana-4763	124	15	tumor	tumor	NOUN
cana-4763	124	16	areas	area	NOUN
cana-4763	124	17	for	for	ADP
cana-4763	124	18	analysis	analysis	NOUN
cana-4763	124	19	.	.	PUNCT
cana-4763	125	1	the	the	DET
cana-4763	125	2	strong	strong	ADJ
cana-4763	125	3	texture	texture	ADJ
cana-4763	125	4	properties	property	NOUN
cana-4763	125	5	of	of	ADP
cana-4763	125	6	lbp	lbp	PROPN
cana-4763	125	7	enable	enable	VERB
cana-4763	125	8	effective	effective	ADJ
cana-4763	125	9	differences	difference	NOUN
cana-4763	125	10	between	between	ADP
cana-4763	125	11	tumor	tumor	NOUN
cana-4763	125	12	types	type	NOUN
cana-4763	125	13	so	so	SCONJ
cana-4763	125	14	it	it	PRON
cana-4763	125	15	serves	serve	VERB
cana-4763	125	16	well	well	ADV
cana-4763	125	17	for	for	ADP
cana-4763	125	18	measuring	measure	VERB
cana-4763	125	19	pixel	pixel	ADJ
cana-4763	125	20	intensity	intensity	NOUN
cana-4763	125	21	variations	variation	NOUN
cana-4763	125	22	.	.	PUNCT
cana-4763	126	1	buying	buy	VERB
cana-4763	126	2	an	an	DET
cana-4763	126	3	extensive	extensive	ADJ
cana-4763	126	4	knowledge	knowledge	NOUN
cana-4763	126	5	of	of	ADP
cana-4763	126	6	tumor	tumor	NOUN
cana-4763	126	7	texture	texture	NOUN
cana-4763	126	8	comes	come	VERB
cana-4763	126	9	from	from	ADP
cana-4763	126	10	extracting	extract	VERB
cana-4763	126	11	lbp	lbp	NOUN
cana-4763	126	12	features	feature	NOUN
cana-4763	126	13	that	that	PRON
cana-4763	126	14	enable	enable	VERB
cana-4763	126	15	correct	correct	ADJ
cana-4763	126	16	classification	classification	NOUN
cana-4763	126	17	needs	need	VERB
cana-4763	126	18	these	these	DET
cana-4763	126	19	features	feature	NOUN
cana-4763	126	20	in	in	ADP
cana-4763	126	21	order	order	NOUN
cana-4763	126	22	to	to	PART
cana-4763	126	23	work	work	VERB
cana-4763	126	24	.	.	PUNCT
cana-4763	127	1	iii	iii	X
cana-4763	127	2	.	.	PUNCT
cana-4763	128	1	the	the	DET
cana-4763	128	2	proposed	propose	VERB
cana-4763	128	3	work	work	NOUN
cana-4763	128	4	utilizes	utilize	VERB
cana-4763	128	5	an	an	DET
cana-4763	128	6	enhanced	enhanced	ADJ
cana-4763	128	7	version	version	NOUN
cana-4763	128	8	of	of	ADP
cana-4763	128	9	grey	grey	PROPN
cana-4763	128	10	wolf	wolf	PROPN
cana-4763	128	11	optimization	optimization	NOUN
cana-4763	128	12	called	call	VERB
cana-4763	128	13	gwo	gwo	NOUN
cana-4763	128	14	for	for	ADP
cana-4763	128	15	feature	feature	NOUN
cana-4763	128	16	selection	selection	NOUN
cana-4763	128	17	to	to	PART
cana-4763	128	18	minimize	minimize	VERB
cana-4763	128	19	data	datum	NOUN
cana-4763	128	20	dimensions	dimension	NOUN
cana-4763	128	21	and	and	CCONJ
cana-4763	128	22	manage	manage	VERB
cana-4763	128	23	the	the	DET
cana-4763	128	24	difficulties	difficulty	NOUN
cana-4763	128	25	that	that	PRON
cana-4763	128	26	come	come	VERB
cana-4763	128	27	with	with	ADP
cana-4763	128	28	extensive	extensive	ADJ
cana-4763	128	29	data	datum	NOUN
cana-4763	128	30	spaces	space	NOUN
cana-4763	128	31	.	.	PUNCT
cana-4763	129	1	through	through	ADP
cana-4763	129	2	feature	feature	NOUN
cana-4763	129	3	selection	selection	NOUN
cana-4763	129	4	optimization	optimization	NOUN
cana-4763	129	5	we	we	PRON
cana-4763	129	6	can	can	AUX
cana-4763	129	7	find	find	VERB
cana-4763	129	8	the	the	DET
cana-4763	129	9	most	most	ADV
cana-4763	129	10	discriminative	discriminative	ADJ
cana-4763	129	11	relevant	relevant	ADJ
cana-4763	129	12	features	feature	NOUN
cana-4763	129	13	for	for	ADP
cana-4763	129	14	our	our	PRON
cana-4763	129	15	analysis	analysis	NOUN
cana-4763	129	16	by	by	ADP
cana-4763	129	17	discarding	discard	VERB
cana-4763	129	18	both	both	CCONJ
cana-4763	129	19	unneeded	unneeded	ADJ
cana-4763	129	20	components	component	NOUN
cana-4763	129	21	and	and	CCONJ
cana-4763	129	22	duplicating	duplicate	VERB
cana-4763	129	23	information	information	NOUN
cana-4763	129	24	.	.	PUNCT
cana-4763	130	1	because	because	SCONJ
cana-4763	130	2	it	it	PRON
cana-4763	130	3	chooses	choose	VERB
cana-4763	130	4	the	the	DET
cana-4763	130	5	best	good	ADJ
cana-4763	130	6	attributes	attribute	VERB
cana-4763	130	7	the	the	DET
cana-4763	130	8	classification	classification	NOUN
cana-4763	130	9	system	system	NOUN
cana-4763	130	10	need	need	VERB
cana-4763	130	11	for	for	ADP
cana-4763	130	12	informative	informative	ADJ
cana-4763	130	13	execution	execution	NOUN
cana-4763	130	14	,	,	PUNCT
cana-4763	130	15	gwo	gwo	PROPN
cana-4763	130	16	optimization	optimization	NOUN
cana-4763	130	17	helps	help	VERB
cana-4763	130	18	to	to	PART
cana-4763	130	19	maximize	maximize	VERB
cana-4763	130	20	both	both	DET
cana-4763	130	21	efficiency	efficiency	NOUN
cana-4763	130	22	and	and	CCONJ
cana-4763	130	23	performance	performance	NOUN
cana-4763	130	24	.	.	PUNCT
cana-4763	131	1	communications	communication	NOUN
cana-4763	131	2	on	on	ADP
cana-4763	131	3	applied	apply	VERB
cana-4763	131	4	nonlinear	nonlinear	ADJ
cana-4763	131	5	analysis	analysis	NOUN
cana-4763	131	6	issn	issn	NOUN
cana-4763	131	7	:	:	PUNCT
cana-4763	131	8	1074	1074	NUM
cana-4763	131	9	-	-	PUNCT
cana-4763	131	10	133x	133x	NUM
cana-4763	131	11	vol	vol	VERB
cana-4763	131	12	32	32	NUM
cana-4763	131	13	no	no	NOUN
cana-4763	131	14	.	.	PUNCT
cana-4763	132	1	10s	10	NOUN
cana-4763	132	2	(	(	PUNCT
cana-4763	132	3	2025	2025	NUM
cana-4763	132	4	)	)	PUNCT
cana-4763	132	5	300	300	NUM
cana-4763	132	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	132	7	iv	iv	NOUN
cana-4763	132	8	.	.	PUNCT
cana-4763	133	1	a	a	DET
cana-4763	133	2	two	two	NUM
cana-4763	133	3	-	-	PUNCT
cana-4763	133	4	stage	stage	NOUN
cana-4763	133	5	classification	classification	NOUN
cana-4763	133	6	procedure	procedure	NOUN
cana-4763	133	7	utilizes	utilize	VERB
cana-4763	133	8	the	the	DET
cana-4763	133	9	specific	specific	ADJ
cana-4763	133	10	powers	power	NOUN
cana-4763	133	11	of	of	ADP
cana-4763	133	12	both	both	CCONJ
cana-4763	133	13	random	random	ADJ
cana-4763	133	14	forest	forest	NOUN
cana-4763	133	15	(	(	PUNCT
cana-4763	133	16	rf	rf	NOUN
cana-4763	133	17	)	)	PUNCT
cana-4763	133	18	and	and	CCONJ
cana-4763	133	19	support	support	VERB
cana-4763	133	20	vector	vector	NOUN
cana-4763	133	21	machine	machine	NOUN
cana-4763	133	22	(	(	PUNCT
cana-4763	133	23	svm	svm	ADJ
cana-4763	133	24	)	)	PUNCT
cana-4763	133	25	classifiers	classifier	NOUN
cana-4763	133	26	.	.	PUNCT
cana-4763	134	1	the	the	DET
cana-4763	134	2	random	random	ADJ
cana-4763	134	3	forest	forest	NOUN
cana-4763	134	4	algorithm	algorithm	NOUN
cana-4763	134	5	generates	generate	VERB
cana-4763	134	6	an	an	DET
cana-4763	134	7	extensive	extensive	ADJ
cana-4763	134	8	set	set	NOUN
cana-4763	134	9	of	of	ADP
cana-4763	134	10	candidate	candidate	NOUN
cana-4763	134	11	features	feature	NOUN
cana-4763	134	12	in	in	ADP
cana-4763	134	13	the	the	DET
cana-4763	134	14	first	first	ADJ
cana-4763	134	15	step	step	NOUN
cana-4763	134	16	of	of	ADP
cana-4763	134	17	the	the	DET
cana-4763	134	18	process	process	NOUN
cana-4763	134	19	.	.	PUNCT
cana-4763	135	1	the	the	DET
cana-4763	135	2	support	support	NOUN
cana-4763	135	3	vector	vector	NOUN
cana-4763	135	4	machine	machine	NOUN
cana-4763	135	5	operates	operate	VERB
cana-4763	135	6	in	in	ADP
cana-4763	135	7	the	the	DET
cana-4763	135	8	second	second	ADJ
cana-4763	135	9	phase	phase	NOUN
cana-4763	135	10	to	to	PART
cana-4763	135	11	optimize	optimize	VERB
cana-4763	135	12	the	the	DET
cana-4763	135	13	characteristics	characteristic	NOUN
cana-4763	135	14	obtained	obtain	VERB
cana-4763	135	15	from	from	ADP
cana-4763	135	16	the	the	DET
cana-4763	135	17	first	first	ADJ
cana-4763	135	18	stage	stage	NOUN
cana-4763	135	19	and	and	CCONJ
cana-4763	135	20	generate	generate	VERB
cana-4763	135	21	end	end	NOUN
cana-4763	135	22	results	result	NOUN
cana-4763	135	23	.	.	PUNCT
cana-4763	136	1	the	the	DET
cana-4763	136	2	implementation	implementation	NOUN
cana-4763	136	3	of	of	ADP
cana-4763	136	4	both	both	DET
cana-4763	136	5	classifiers	classifier	NOUN
cana-4763	136	6	optimizes	optimize	VERB
cana-4763	136	7	accuracy	accuracy	NOUN
cana-4763	136	8	and	and	CCONJ
cana-4763	136	9	generates	generate	VERB
cana-4763	136	10	better	well	ADJ
cana-4763	136	11	reliable	reliable	ADJ
cana-4763	136	12	predictions	prediction	NOUN
cana-4763	136	13	because	because	SCONJ
cana-4763	136	14	of	of	ADP
cana-4763	136	15	their	their	PRON
cana-4763	136	16	complementary	complementary	ADJ
cana-4763	136	17	capabilities	capability	NOUN
cana-4763	136	18	.	.	PUNCT
cana-4763	137	1	3.1	3.1	NUM
cana-4763	137	2	dataset	dataset	NOUN
cana-4763	137	3	used	use	VERB
cana-4763	137	4	the	the	DET
cana-4763	137	5	brats	brat	NOUN
cana-4763	137	6	2020	2020	NUM
cana-4763	137	7	(	(	PUNCT
cana-4763	137	8	brain	brain	NOUN
cana-4763	137	9	tumor	tumor	NOUN
cana-4763	137	10	segmentation	segmentation	NOUN
cana-4763	137	11	challenge	challenge	NOUN
cana-4763	137	12	2020	2020	NUM
cana-4763	137	13	)	)	PUNCT
cana-4763	137	14	dataset	dataset	NOUN
cana-4763	138	1	[	[	PUNCT
cana-4763	138	2	24	24	NUM
cana-4763	138	3	]	]	PUNCT
cana-4763	138	4	is	be	AUX
cana-4763	138	5	a	a	DET
cana-4763	138	6	commonly	commonly	ADV
cana-4763	138	7	used	use	VERB
cana-4763	138	8	benchmark	benchmark	NOUN
cana-4763	138	9	for	for	ADP
cana-4763	138	10	brain	brain	NOUN
cana-4763	138	11	tumor	tumor	NOUN
cana-4763	138	12	segmentation	segmentation	NOUN
cana-4763	138	13	and	and	CCONJ
cana-4763	138	14	classification	classification	NOUN
cana-4763	138	15	problems	problem	NOUN
cana-4763	138	16	.	.	PUNCT
cana-4763	139	1	it	it	PRON
cana-4763	139	2	is	be	AUX
cana-4763	139	3	one	one	NUM
cana-4763	139	4	part	part	NOUN
cana-4763	139	5	of	of	ADP
cana-4763	139	6	the	the	DET
cana-4763	139	7	miccai	miccai	PROPN
cana-4763	139	8	brain	brain	NOUN
cana-4763	139	9	tumor	tumor	NOUN
cana-4763	139	10	segmentation	segmentation	NOUN
cana-4763	139	11	(	(	PUNCT
cana-4763	139	12	brats	brat	NOUN
cana-4763	139	13	)	)	PUNCT
cana-4763	139	14	challenge	challenge	NOUN
cana-4763	139	15	,	,	PUNCT
cana-4763	139	16	which	which	PRON
cana-4763	139	17	is	be	AUX
cana-4763	139	18	intended	intend	VERB
cana-4763	139	19	to	to	PART
cana-4763	139	20	create	create	VERB
cana-4763	139	21	automated	automate	VERB
cana-4763	139	22	methods	method	NOUN
cana-4763	139	23	for	for	ADP
cana-4763	139	24	multimodal	multimodal	NOUN
cana-4763	139	25	mri	mri	NOUN
cana-4763	139	26	scan	scan	NOUN
cana-4763	139	27	-	-	PUNCT
cana-4763	139	28	based	base	VERB
cana-4763	139	29	brain	brain	NOUN
cana-4763	139	30	tumor	tumor	NOUN
cana-4763	139	31	detection	detection	NOUN
cana-4763	139	32	and	and	CCONJ
cana-4763	139	33	segmentation	segmentation	NOUN
cana-4763	139	34	.	.	PUNCT
cana-4763	140	1	3.2	3.2	NUM
cana-4763	140	2	pre	pre	ADJ
cana-4763	140	3	-	-	ADJ
cana-4763	140	4	processing	processing	NOUN
cana-4763	140	5	during	during	ADP
cana-4763	140	6	the	the	DET
cana-4763	140	7	pre	pre	ADJ
cana-4763	140	8	-	-	ADJ
cana-4763	140	9	processing	processing	ADJ
cana-4763	140	10	stage	stage	NOUN
cana-4763	140	11	the	the	DET
cana-4763	140	12	bilateral	bilateral	ADJ
cana-4763	140	13	filter	filter	NOUN
cana-4763	140	14	eliminates	eliminate	VERB
cana-4763	140	15	noisy	noisy	ADJ
cana-4763	140	16	elements	element	NOUN
cana-4763	140	17	which	which	PRON
cana-4763	140	18	leads	lead	VERB
cana-4763	140	19	to	to	ADP
cana-4763	140	20	imaging	imaging	NOUN
cana-4763	140	21	enhancement	enhancement	NOUN
cana-4763	140	22	and	and	CCONJ
cana-4763	140	23	smoothing	smoothing	NOUN
cana-4763	140	24	.	.	PUNCT
cana-4763	141	1	the	the	DET
cana-4763	141	2	medical	medical	ADJ
cana-4763	141	3	-	-	PUNCT
cana-4763	141	4	image	image	NOUN
cana-4763	141	5	-	-	PUNCT
cana-4763	141	6	specific	specific	ADJ
cana-4763	141	7	nonlinear	nonlinear	ADJ
cana-4763	141	8	edge	edge	NOUN
cana-4763	141	9	-	-	PUNCT
cana-4763	141	10	preserving	preserve	VERB
cana-4763	141	11	smoothing	smoothing	NOUN
cana-4763	141	12	technique	technique	NOUN
cana-4763	141	13	exists	exist	VERB
cana-4763	141	14	as	as	ADP
cana-4763	141	15	a	a	DET
cana-4763	141	16	designed	design	VERB
cana-4763	141	17	method	method	NOUN
cana-4763	141	18	for	for	ADP
cana-4763	141	19	medical	medical	ADJ
cana-4763	141	20	images	image	NOUN
cana-4763	141	21	.	.	PUNCT
cana-4763	142	1	the	the	DET
cana-4763	142	2	definition	definition	NOUN
cana-4763	142	3	of	of	ADP
cana-4763	142	4	tumor	tumor	NOUN
cana-4763	142	5	boundaries	boundary	NOUN
cana-4763	142	6	for	for	ADP
cana-4763	142	7	brain	brain	NOUN
cana-4763	142	8	tumor	tumor	NOUN
cana-4763	142	9	classification	classification	NOUN
cana-4763	142	10	through	through	ADP
cana-4763	142	11	smooth	smooth	ADJ
cana-4763	142	12	flat	flat	ADJ
cana-4763	142	13	areas	area	NOUN
cana-4763	142	14	without	without	ADP
cana-4763	142	15	blurring	blur	VERB
cana-4763	142	16	sharp	sharp	ADJ
cana-4763	142	17	edges	edge	NOUN
cana-4763	142	18	represents	represent	VERB
cana-4763	142	19	one	one	NUM
cana-4763	142	20	of	of	ADP
cana-4763	142	21	the	the	DET
cana-4763	142	22	leading	lead	VERB
cana-4763	142	23	methods	method	NOUN
cana-4763	142	24	in	in	ADP
cana-4763	142	25	medical	medical	ADJ
cana-4763	142	26	imaging	imaging	NOUN
cana-4763	142	27	.	.	PUNCT
cana-4763	143	1	medical	medical	ADJ
cana-4763	143	2	professionals	professional	NOUN
cana-4763	143	3	benefit	benefit	VERB
cana-4763	143	4	from	from	ADP
cana-4763	143	5	this	this	DET
cana-4763	143	6	technique	technique	NOUN
cana-4763	143	7	because	because	SCONJ
cana-4763	143	8	it	it	PRON
cana-4763	143	9	allows	allow	VERB
cana-4763	143	10	more	more	ADV
cana-4763	143	11	accurate	accurate	ADJ
cana-4763	143	12	tumor	tumor	NOUN
cana-4763	143	13	classification	classification	NOUN
cana-4763	143	14	through	through	ADP
cana-4763	143	15	precise	precise	ADJ
cana-4763	143	16	surface	surface	NOUN
cana-4763	143	17	enhancement	enhancement	NOUN
cana-4763	143	18	.	.	PUNCT
cana-4763	144	1	step	step	NOUN
cana-4763	144	2	1	1	NUM
cana-4763	144	3	:	:	PUNCT
cana-4763	144	4	load	load	VERB
cana-4763	144	5	the	the	DET
cana-4763	144	6	brain	brain	NOUN
cana-4763	144	7	mri	mri	NOUN
cana-4763	144	8	image	image	NOUN
cana-4763	144	9	we	we	PRON
cana-4763	144	10	first	first	ADV
cana-4763	144	11	input	input	VERB
cana-4763	144	12	the	the	DET
cana-4763	144	13	brain	brain	NOUN
cana-4763	144	14	mri	mri	NOUN
cana-4763	144	15	image	image	NOUN
cana-4763	144	16	into	into	ADP
cana-4763	144	17	the	the	DET
cana-4763	144	18	system	system	NOUN
cana-4763	144	19	before	before	ADP
cana-4763	144	20	moving	move	VERB
cana-4763	144	21	on	on	ADP
cana-4763	144	22	to	to	ADP
cana-4763	144	23	additional	additional	ADJ
cana-4763	144	24	processes	process	NOUN
cana-4763	144	25	.	.	PUNCT
cana-4763	145	1	step	step	NOUN
cana-4763	145	2	2	2	NUM
cana-4763	145	3	:	:	PUNCT
cana-4763	145	4	normalize	normalize	VERB
cana-4763	145	5	the	the	DET
cana-4763	145	6	image	image	NOUN
cana-4763	145	7	the	the	DET
cana-4763	145	8	normalization	normalization	NOUN
cana-4763	145	9	step	step	NOUN
cana-4763	145	10	scales	scale	VERB
cana-4763	145	11	pixel	pixel	PROPN
cana-4763	145	12	intensities	intensity	NOUN
cana-4763	145	13	to	to	ADP
cana-4763	145	14	a	a	DET
cana-4763	145	15	range	range	NOUN
cana-4763	145	16	of	of	ADP
cana-4763	145	17	0	0	NUM
cana-4763	145	18	to	to	PART
cana-4763	145	19	1	1	NUM
cana-4763	145	20	or	or	CCONJ
cana-4763	145	21	0	0	NUM
cana-4763	145	22	to	to	ADP
cana-4763	145	23	255	255	NUM
cana-4763	145	24	.	.	PUNCT
cana-4763	146	1	this	this	DET
cana-4763	146	2	step	step	NOUN
cana-4763	146	3	reduces	reduce	VERB
cana-4763	146	4	intensity	intensity	NOUN
cana-4763	146	5	discrepancies	discrepancy	NOUN
cana-4763	146	6	across	across	ADP
cana-4763	146	7	images	image	NOUN
cana-4763	146	8	from	from	ADP
cana-4763	146	9	different	different	ADJ
cana-4763	146	10	datasets	dataset	NOUN
cana-4763	146	11	,	,	PUNCT
cana-4763	146	12	which	which	PRON
cana-4763	146	13	is	be	AUX
cana-4763	146	14	crucial	crucial	ADJ
cana-4763	146	15	for	for	ADP
cana-4763	146	16	preserving	preserve	VERB
cana-4763	146	17	processing	processing	NOUN
cana-4763	146	18	consistency	consistency	NOUN
cana-4763	146	19	.	.	PUNCT
cana-4763	147	1	step	step	NOUN
cana-4763	147	2	3	3	NUM
cana-4763	147	3	:	:	PUNCT
cana-4763	147	4	apply	apply	VERB
cana-4763	147	5	bilateral	bilateral	ADJ
cana-4763	147	6	filtering	filtering	NOUN
cana-4763	147	7	the	the	DET
cana-4763	147	8	bilateral	bilateral	ADJ
cana-4763	147	9	filter	filter	NOUN
cana-4763	147	10	implements	implement	VERB
cana-4763	147	11	a	a	DET
cana-4763	147	12	smoothing	smooth	VERB
cana-4763	147	13	operation	operation	NOUN
cana-4763	147	14	which	which	PRON
cana-4763	147	15	preserves	preserve	VERB
cana-4763	147	16	edges	edge	VERB
cana-4763	147	17	through	through	ADP
cana-4763	147	18	calculations	calculation	NOUN
cana-4763	147	19	that	that	PRON
cana-4763	147	20	combine	combine	VERB
cana-4763	147	21	intensity	intensity	NOUN
cana-4763	147	22	data	datum	NOUN
cana-4763	147	23	with	with	ADP
cana-4763	147	24	spatial	spatial	ADJ
cana-4763	147	25	positions	position	NOUN
cana-4763	147	26	.	.	PUNCT
cana-4763	148	1	the	the	DET
cana-4763	148	2	filtered	filter	VERB
cana-4763	148	3	value	value	NOUN
cana-4763	148	4	for	for	ADP
cana-4763	148	5	each	each	DET
cana-4763	148	6	pixel	pixel	NOUN
cana-4763	148	7	results	result	NOUN
cana-4763	148	8	from	from	ADP
cana-4763	148	9	averaging	average	VERB
cana-4763	148	10	weighted	weight	VERB
cana-4763	148	11	pixels	pixel	NOUN
cana-4763	148	12	within	within	ADP
cana-4763	148	13	its	its	PRON
cana-4763	148	14	surroundings	surrounding	NOUN
cana-4763	148	15	according	accord	VERB
cana-4763	148	16	to	to	ADP
cana-4763	148	17	two	two	NUM
cana-4763	148	18	main	main	ADJ
cana-4763	148	19	components	component	NOUN
cana-4763	148	20	:	:	PUNCT
cana-4763	148	21	1	1	X
cana-4763	148	22	.	.	X
cana-4763	148	23	weights	weight	NOUN
cana-4763	148	24	derive	derive	VERB
cana-4763	148	25	their	their	PRON
cana-4763	148	26	values	value	NOUN
cana-4763	148	27	from	from	ADP
cana-4763	148	28	the	the	DET
cana-4763	148	29	spatial	spatial	ADJ
cana-4763	148	30	gaussian	gaussian	ADJ
cana-4763	148	31	kernel	kernel	NOUN
cana-4763	148	32	to	to	PART
cana-4763	148	33	determine	determine	VERB
cana-4763	148	34	pixel	pixel	ADJ
cana-4763	148	35	-	-	PUNCT
cana-4763	148	36	center	center	NOUN
cana-4763	148	37	relationships	relationship	NOUN
cana-4763	148	38	with	with	ADP
cana-4763	148	39	nearby	nearby	ADJ
cana-4763	148	40	pixels	pixel	NOUN
cana-4763	148	41	.	.	PUNCT
cana-4763	149	1	2	2	X
cana-4763	149	2	.	.	X
cana-4763	149	3	each	each	DET
cana-4763	149	4	pixel	pixel	PROPN
cana-4763	149	5	weights	weight	NOUN
cana-4763	149	6	in	in	ADP
cana-4763	149	7	the	the	DET
cana-4763	149	8	intensity	intensity	NOUN
cana-4763	149	9	gaussian	gaussian	ADJ
cana-4763	149	10	kernel	kernel	PROPN
cana-4763	149	11	uses	use	VERB
cana-4763	149	12	its	its	PRON
cana-4763	149	13	central	central	ADJ
cana-4763	149	14	pixel	pixel	NOUN
cana-4763	149	15	intensity	intensity	NOUN
cana-4763	149	16	compared	compare	VERB
cana-4763	149	17	with	with	ADP
cana-4763	149	18	its	its	PRON
cana-4763	149	19	neighboring	neighboring	NOUN
cana-4763	149	20	pixels	pixel	NOUN
cana-4763	149	21	.	.	PUNCT
cana-4763	150	1	for	for	ADP
cana-4763	150	2	a	a	DET
cana-4763	150	3	pixel	pixel	PROPN
cana-4763	150	4	i(x	i(x	PROPN
cana-4763	150	5	,	,	PUNCT
cana-4763	150	6	y	y	PROPN
cana-4763	150	7	)	)	PUNCT
cana-4763	150	8	the	the	DET
cana-4763	150	9	filtered	filter	VERB
cana-4763	150	10	pixel	pixel	NOUN
cana-4763	150	11	(	(	PUNCT
cana-4763	150	12	ifiltered(x	ifiltered(x	PROPN
cana-4763	150	13	,	,	PUNCT
cana-4763	150	14	y	y	NOUN
cana-4763	150	15	)	)	PUNCT
cana-4763	150	16	is	be	AUX
cana-4763	150	17	determined	determine	VERB
cana-4763	150	18	as	as	ADP
cana-4763	150	19	:	:	PUNCT
cana-4763	150	20	ifiltered(x	ifiltered(x	PROPN
cana-4763	150	21	,	,	PUNCT
cana-4763	150	22	y	y	PROPN
cana-4763	150	23	)	)	PUNCT
cana-4763	150	24	=	=	SYM
cana-4763	151	1	σp∈ωgs(‖p−(x,,y)‖)⋅gr(|i(p)−i(x	σp∈ωgs(‖p−(x,,y)‖)⋅gr(|i(p)−i(x	NUM
cana-4763	151	2	,	,	PUNCT
cana-4763	151	3	y)|)∘i(p	y)|)∘i(p	NOUN
cana-4763	151	4	)	)	PUNCT
cana-4763	151	5	σp∈igs(‖p−(x	σp∈igs(‖p−(x	NOUN
cana-4763	151	6	,	,	PUNCT
cana-4763	151	7	y)‖)⋅gr(|i(p)−i(x	y)‖)⋅gr(|i(p)−i(x	PROPN
cana-4763	151	8	,	,	PUNCT
cana-4763	151	9	y)|	y)|	PROPN
cana-4763	151	10	)	)	PUNCT
cana-4763	151	11	…	…	PUNCT
cana-4763	151	12	(	(	PUNCT
cana-4763	151	13	1	1	NUM
cana-4763	151	14	)	)	PUNCT
cana-4763	151	15	where	where	SCONJ
cana-4763	151	16	:	:	PUNCT
cana-4763	151	17	gs	gs	PROPN
cana-4763	151	18	is	be	AUX
cana-4763	151	19	the	the	DET
cana-4763	151	20	spatial	spatial	ADJ
cana-4763	151	21	gaussian	gaussian	ADJ
cana-4763	151	22	kernel	kernel	NOUN
cana-4763	151	23	:	:	PUNCT
cana-4763	151	24	gs(d)=exp(−	gs(d)=exp(−	PROPN
cana-4763	151	25	d2	d2	PROPN
cana-4763	151	26	2σs	2σs	NOUN
cana-4763	151	27	2	2	NUM
cana-4763	151	28	)	)	PUNCT
cana-4763	151	29	gr	gr	NOUN
cana-4763	151	30	is	be	AUX
cana-4763	151	31	the	the	DET
cana-4763	151	32	intensity	intensity	NOUN
cana-4763	151	33	gaussian	gaussian	ADJ
cana-4763	151	34	kernel	kernel	NOUN
cana-4763	151	35	:	:	PUNCT
cana-4763	151	36	gr	gr	X
cana-4763	151	37	(	(	PUNCT
cana-4763	151	38	δi)=exp(δi2	δi)=exp(δi2	PROPN
cana-4763	151	39	2σr	2σr	NOUN
cana-4763	151	40	2	2	NUM
cana-4763	151	41	)	)	PUNCT
cana-4763	151	42	σs	σs	PROPN
cana-4763	151	43	:	:	PUNCT
cana-4763	151	44	controls	control	VERB
cana-4763	151	45	the	the	DET
cana-4763	151	46	spatial	spatial	ADJ
cana-4763	151	47	smoothing	smoothing	NOUN
cana-4763	151	48	extent	extent	NOUN
cana-4763	151	49	.	.	PUNCT
cana-4763	152	1	σr	σr	PROPN
cana-4763	152	2	:	:	PUNCT
cana-4763	152	3	controls	control	VERB
cana-4763	152	4	the	the	DET
cana-4763	152	5	intensity	intensity	NOUN
cana-4763	152	6	smoothing	smooth	VERB
cana-4763	152	7	extent	extent	NOUN
cana-4763	152	8	.	.	PUNCT
cana-4763	153	1	ω	ω	X
cana-4763	153	2	:	:	PUNCT
cana-4763	153	3	neighborhood	neighborhood	NOUN
cana-4763	153	4	of	of	ADP
cana-4763	153	5	pixels	pixel	NOUN
cana-4763	153	6	around	around	ADV
cana-4763	153	7	(	(	PUNCT
cana-4763	153	8	x	x	NOUN
cana-4763	153	9	,	,	PUNCT
cana-4763	153	10	y	y	PROPN
cana-4763	153	11	)	)	PUNCT
cana-4763	153	12	.	.	PUNCT
cana-4763	154	1	step	step	NOUN
cana-4763	154	2	4	4	NUM
cana-4763	154	3	:	:	PUNCT
cana-4763	154	4	contrast	contrast	VERB
cana-4763	154	5	enhancement	enhancement	NOUN
cana-4763	154	6	after	after	ADP
cana-4763	154	7	applying	apply	VERB
cana-4763	154	8	bilateral	bilateral	ADJ
cana-4763	154	9	filtering	filtering	NOUN
cana-4763	154	10	,	,	PUNCT
cana-4763	154	11	a	a	DET
cana-4763	154	12	doctor	doctor	NOUN
cana-4763	154	13	might	might	AUX
cana-4763	154	14	need	need	VERB
cana-4763	154	15	to	to	PART
cana-4763	154	16	enhance	enhance	VERB
cana-4763	154	17	tumor	tumor	NOUN
cana-4763	154	18	boundaries	boundary	NOUN
cana-4763	154	19	yet	yet	ADV
cana-4763	154	20	again	again	ADV
cana-4763	154	21	.	.	PUNCT
cana-4763	155	1	the	the	DET
cana-4763	155	2	procedure	procedure	NOUN
cana-4763	155	3	of	of	ADP
cana-4763	155	4	histogram	histogram	NOUN
cana-4763	155	5	equalization	equalization	NOUN
cana-4763	155	6	enhances	enhance	VERB
cana-4763	155	7	tumor	tumor	NOUN
cana-4763	155	8	visibility	visibility	NOUN
cana-4763	155	9	for	for	ADP
cana-4763	155	10	better	well	ADJ
cana-4763	155	11	recognition	recognition	NOUN
cana-4763	155	12	.	.	PUNCT
cana-4763	156	1	the	the	DET
cana-4763	156	2	technique	technique	NOUN
cana-4763	156	3	redistributes	redistribute	VERB
cana-4763	156	4	pixel	pixel	NOUN
cana-4763	156	5	intensity	intensity	NOUN
cana-4763	156	6	values	value	NOUN
cana-4763	156	7	to	to	PART
cana-4763	156	8	enhance	enhance	VERB
cana-4763	156	9	image	image	NOUN
cana-4763	156	10	contrast	contrast	NOUN
cana-4763	156	11	which	which	PRON
cana-4763	156	12	reveals	reveal	VERB
cana-4763	156	13	important	important	ADJ
cana-4763	156	14	details	detail	NOUN
cana-4763	156	15	.	.	PUNCT
cana-4763	157	1	communications	communication	NOUN
cana-4763	157	2	on	on	ADP
cana-4763	157	3	applied	apply	VERB
cana-4763	157	4	nonlinear	nonlinear	ADJ
cana-4763	157	5	analysis	analysis	NOUN
cana-4763	157	6	issn	issn	NOUN
cana-4763	157	7	:	:	PUNCT
cana-4763	157	8	1074	1074	NUM
cana-4763	157	9	-	-	PUNCT
cana-4763	157	10	133x	133x	NUM
cana-4763	157	11	vol	vol	VERB
cana-4763	157	12	32	32	NUM
cana-4763	157	13	no	no	NOUN
cana-4763	157	14	.	.	PUNCT
cana-4763	158	1	10s	10	NOUN
cana-4763	158	2	(	(	PUNCT
cana-4763	158	3	2025	2025	NUM
cana-4763	158	4	)	)	PUNCT
cana-4763	158	5	301	301	NUM
cana-4763	158	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	158	7	step	step	NOUN
cana-4763	158	8	5	5	NUM
cana-4763	158	9	:	:	PUNCT
cana-4763	158	10	thresholding	thresholde	VERB
cana-4763	158	11	the	the	DET
cana-4763	158	12	following	follow	VERB
cana-4763	158	13	step	step	NOUN
cana-4763	158	14	involves	involve	VERB
cana-4763	158	15	utilizing	utilize	VERB
cana-4763	158	16	otsu	otsu	NOUN
cana-4763	158	17	's	's	PART
cana-4763	158	18	thresholding	thresholding	NOUN
cana-4763	158	19	method	method	NOUN
cana-4763	158	20	to	to	PART
cana-4763	158	21	distinguish	distinguish	VERB
cana-4763	158	22	tumors	tumor	NOUN
cana-4763	158	23	from	from	ADP
cana-4763	158	24	the	the	DET
cana-4763	158	25	background	background	NOUN
cana-4763	158	26	.	.	PUNCT
cana-4763	159	1	the	the	DET
cana-4763	159	2	innovative	innovative	ADJ
cana-4763	159	3	method	method	NOUN
cana-4763	159	4	determines	determine	VERB
cana-4763	159	5	automatically	automatically	ADV
cana-4763	159	6	the	the	DET
cana-4763	159	7	perfect	perfect	ADJ
cana-4763	159	8	threshold	threshold	NOUN
cana-4763	159	9	value	value	NOUN
cana-4763	159	10	to	to	PART
cana-4763	159	11	split	split	VERB
cana-4763	159	12	tumor	tumor	NOUN
cana-4763	159	13	areas	area	NOUN
cana-4763	159	14	from	from	ADP
cana-4763	159	15	surrounding	surround	VERB
cana-4763	159	16	tissues	tissue	NOUN
cana-4763	159	17	during	during	ADP
cana-4763	159	18	segmentation	segmentation	NOUN
cana-4763	159	19	.	.	PUNCT
cana-4763	160	1	step	step	NOUN
cana-4763	160	2	6	6	NUM
cana-4763	160	3	:	:	PUNCT
cana-4763	160	4	morphological	morphological	ADJ
cana-4763	160	5	operations	operation	NOUN
cana-4763	160	6	the	the	DET
cana-4763	160	7	segmented	segment	VERB
cana-4763	160	8	tumor	tumor	NOUN
cana-4763	160	9	area	area	NOUN
cana-4763	160	10	receives	receive	VERB
cana-4763	160	11	refinement	refinement	NOUN
cana-4763	160	12	through	through	ADP
cana-4763	160	13	two	two	NUM
cana-4763	160	14	morphological	morphological	ADJ
cana-4763	160	15	procedures	procedure	NOUN
cana-4763	160	16	including	include	VERB
cana-4763	160	17	closure	closure	NOUN
cana-4763	160	18	followed	follow	VERB
cana-4763	160	19	by	by	ADP
cana-4763	160	20	dilation	dilation	NOUN
cana-4763	160	21	.	.	PUNCT
cana-4763	161	1	these	these	DET
cana-4763	161	2	procedures	procedure	NOUN
cana-4763	161	3	produce	produce	VERB
cana-4763	161	4	better	well	ADJ
cana-4763	161	5	data	datum	NOUN
cana-4763	161	6	segmentation	segmentation	NOUN
cana-4763	161	7	by	by	ADP
cana-4763	161	8	removing	remove	VERB
cana-4763	161	9	noise	noise	NOUN
cana-4763	161	10	and	and	CCONJ
cana-4763	161	11	completing	complete	VERB
cana-4763	161	12	empty	empty	ADJ
cana-4763	161	13	areas	area	NOUN
cana-4763	161	14	found	find	VERB
cana-4763	161	15	in	in	ADP
cana-4763	161	16	tumor	tumor	NOUN
cana-4763	161	17	regions	region	NOUN
cana-4763	161	18	.	.	PUNCT
cana-4763	162	1	step	step	NOUN
cana-4763	162	2	7	7	NUM
cana-4763	162	3	:	:	PUNCT
cana-4763	162	4	resize	resize	VERB
cana-4763	162	5	the	the	DET
cana-4763	162	6	image	image	NOUN
cana-4763	162	7	.	.	PUNCT
cana-4763	163	1	after	after	ADP
cana-4763	163	2	processing	process	VERB
cana-4763	163	3	the	the	DET
cana-4763	163	4	image	image	NOUN
cana-4763	163	5	,	,	PUNCT
cana-4763	163	6	it	it	PRON
cana-4763	163	7	gets	get	AUX
cana-4763	163	8	resized	resize	VERB
cana-4763	163	9	to	to	ADP
cana-4763	163	10	a	a	DET
cana-4763	163	11	standardized	standardized	ADJ
cana-4763	163	12	input	input	NOUN
cana-4763	163	13	dimension	dimension	NOUN
cana-4763	163	14	(	(	PUNCT
cana-4763	163	15	128x128	128x128	NUM
cana-4763	163	16	pixels	pixel	NOUN
cana-4763	163	17	)	)	PUNCT
cana-4763	163	18	for	for	ADP
cana-4763	163	19	future	future	ADJ
cana-4763	163	20	analysis	analysis	NOUN
cana-4763	163	21	.	.	PUNCT
cana-4763	164	1	3.3	3.3	NUM
cana-4763	164	2	feature	feature	NOUN
cana-4763	164	3	extraction	extraction	NOUN
cana-4763	164	4	after	after	ADP
cana-4763	164	5	pre	pre	ADJ
cana-4763	164	6	-	-	ADJ
cana-4763	164	7	processing	process	VERB
cana-4763	164	8	the	the	DET
cana-4763	164	9	system	system	NOUN
cana-4763	164	10	applies	apply	VERB
cana-4763	164	11	the	the	DET
cana-4763	164	12	local	local	ADJ
cana-4763	164	13	binary	binary	ADJ
cana-4763	164	14	pattern	pattern	NOUN
cana-4763	164	15	(	(	PUNCT
cana-4763	164	16	lbp	lbp	NOUN
cana-4763	164	17	)	)	PUNCT
cana-4763	164	18	technique	technique	NOUN
cana-4763	164	19	for	for	ADP
cana-4763	164	20	feature	feature	NOUN
cana-4763	164	21	extraction	extraction	NOUN
cana-4763	164	22	.	.	PUNCT
cana-4763	165	1	lbp	lbp	NOUN
cana-4763	165	2	extracts	extract	VERB
cana-4763	165	3	the	the	DET
cana-4763	165	4	textural	textural	ADJ
cana-4763	165	5	information	information	NOUN
cana-4763	165	6	from	from	ADP
cana-4763	165	7	images	image	NOUN
cana-4763	165	8	which	which	PRON
cana-4763	165	9	provides	provide	VERB
cana-4763	165	10	effective	effective	ADJ
cana-4763	165	11	details	detail	NOUN
cana-4763	165	12	that	that	PRON
cana-4763	165	13	help	help	VERB
cana-4763	165	14	with	with	ADP
cana-4763	165	15	accurate	accurate	ADJ
cana-4763	165	16	tumor	tumor	NOUN
cana-4763	165	17	classification	classification	NOUN
cana-4763	165	18	.	.	PUNCT
cana-4763	166	1	3.3.1	3.3.1	NUM
cana-4763	166	2	local	local	ADJ
cana-4763	166	3	binary	binary	NOUN
cana-4763	166	4	patterns	pattern	NOUN
cana-4763	166	5	(	(	PUNCT
cana-4763	166	6	lbp	lbp	NOUN
cana-4763	166	7	)	)	PUNCT
cana-4763	166	8	local	local	ADJ
cana-4763	166	9	binary	binary	NOUN
cana-4763	166	10	patterns	pattern	NOUN
cana-4763	166	11	(	(	PUNCT
cana-4763	166	12	lbp	lbp	PROPN
cana-4763	166	13	)	)	PUNCT
cana-4763	166	14	represents	represent	VERB
cana-4763	166	15	a	a	DET
cana-4763	166	16	popular	popular	ADJ
cana-4763	166	17	method	method	NOUN
cana-4763	166	18	for	for	ADP
cana-4763	166	19	extracting	extract	VERB
cana-4763	166	20	texture	texture	NOUN
cana-4763	166	21	features	feature	NOUN
cana-4763	166	22	needed	need	VERB
cana-4763	166	23	for	for	ADP
cana-4763	166	24	brain	brain	NOUN
cana-4763	166	25	tumor	tumor	NOUN
cana-4763	166	26	classification	classification	NOUN
cana-4763	166	27	.	.	PUNCT
cana-4763	167	1	the	the	DET
cana-4763	167	2	popularity	popularity	NOUN
cana-4763	167	3	of	of	ADP
cana-4763	167	4	this	this	DET
cana-4763	167	5	technique	technique	NOUN
cana-4763	167	6	continues	continue	VERB
cana-4763	167	7	to	to	PART
cana-4763	167	8	increase	increase	VERB
cana-4763	167	9	in	in	ADP
cana-4763	167	10	medical	medical	ADJ
cana-4763	167	11	imaging	imaging	NOUN
cana-4763	167	12	analysis	analysis	NOUN
cana-4763	167	13	because	because	SCONJ
cana-4763	167	14	it	it	PRON
cana-4763	167	15	precisely	precisely	ADV
cana-4763	167	16	detects	detect	VERB
cana-4763	167	17	regional	regional	ADJ
cana-4763	167	18	intensity	intensity	NOUN
cana-4763	167	19	patterns	pattern	NOUN
cana-4763	167	20	in	in	ADP
cana-4763	167	21	images	image	NOUN
cana-4763	167	22	for	for	ADP
cana-4763	167	23	brain	brain	NOUN
cana-4763	167	24	tumor	tumor	NOUN
cana-4763	167	25	diagnosis	diagnosis	NOUN
cana-4763	167	26	purposes	purpose	NOUN
cana-4763	167	27	.	.	PUNCT
cana-4763	168	1	these	these	DET
cana-4763	168	2	patterns	pattern	NOUN
cana-4763	168	3	strongly	strongly	ADV
cana-4763	168	4	represent	represent	VERB
cana-4763	168	5	the	the	DET
cana-4763	168	6	texture	texture	NOUN
cana-4763	168	7	which	which	PRON
cana-4763	168	8	helps	help	VERB
cana-4763	168	9	medical	medical	ADJ
cana-4763	168	10	experts	expert	NOUN
cana-4763	168	11	distinguish	distinguish	VERB
cana-4763	168	12	tumor	tumor	NOUN
cana-4763	168	13	-	-	PUNCT
cana-4763	168	14	affected	affect	VERB
cana-4763	168	15	tissues	tissue	NOUN
cana-4763	168	16	from	from	ADP
cana-4763	168	17	healthy	healthy	ADJ
cana-4763	168	18	ones	one	NOUN
cana-4763	168	19	.	.	PUNCT
cana-4763	169	1	the	the	DET
cana-4763	169	2	classification	classification	NOUN
cana-4763	169	3	performance	performance	NOUN
cana-4763	169	4	of	of	ADP
cana-4763	169	5	algorithms	algorithm	NOUN
cana-4763	169	6	improves	improve	VERB
cana-4763	169	7	through	through	ADP
cana-4763	169	8	lbp	lbp	NOUN
cana-4763	169	9	because	because	SCONJ
cana-4763	169	10	it	it	PRON
cana-4763	169	11	examines	examine	VERB
cana-4763	169	12	pixel	pixel	PROPN
cana-4763	169	13	intensity	intensity	PROPN
cana-4763	169	14	spatial	spatial	ADJ
cana-4763	169	15	positions	position	NOUN
cana-4763	169	16	which	which	PRON
cana-4763	169	17	results	result	VERB
cana-4763	169	18	in	in	ADP
cana-4763	169	19	better	well	ADJ
cana-4763	169	20	brain	brain	NOUN
cana-4763	169	21	tumor	tumor	NOUN
cana-4763	169	22	identification	identification	NOUN
cana-4763	169	23	.	.	PUNCT
cana-4763	170	1	the	the	DET
cana-4763	170	2	lbp	lbp	PROPN
cana-4763	170	3	technique	technique	NOUN
cana-4763	170	4	explores	explore	VERB
cana-4763	170	5	image	image	NOUN
cana-4763	170	6	microtexture	microtexture	NOUN
cana-4763	170	7	patterns	pattern	NOUN
cana-4763	170	8	because	because	SCONJ
cana-4763	170	9	these	these	DET
cana-4763	170	10	patterns	pattern	NOUN
cana-4763	170	11	represent	represent	VERB
cana-4763	170	12	critical	critical	ADJ
cana-4763	170	13	indicators	indicator	NOUN
cana-4763	170	14	for	for	ADP
cana-4763	170	15	distinguishing	distinguish	VERB
cana-4763	170	16	different	different	ADJ
cana-4763	170	17	tissue	tissue	NOUN
cana-4763	170	18	types	type	NOUN
cana-4763	170	19	during	during	ADP
cana-4763	170	20	brain	brain	NOUN
cana-4763	170	21	tumor	tumor	NOUN
cana-4763	170	22	classification	classification	NOUN
cana-4763	170	23	.	.	PUNCT
cana-4763	171	1	the	the	DET
cana-4763	171	2	method	method	NOUN
cana-4763	171	3	validates	validate	VERB
cana-4763	171	4	local	local	ADJ
cana-4763	171	5	textural	textural	ADJ
cana-4763	171	6	attributes	attribute	NOUN
cana-4763	171	7	that	that	PRON
cana-4763	171	8	lead	lead	VERB
cana-4763	171	9	to	to	ADP
cana-4763	171	10	substantial	substantial	ADJ
cana-4763	171	11	differences	difference	NOUN
cana-4763	171	12	between	between	ADP
cana-4763	171	13	tumor	tumor	NOUN
cana-4763	171	14	zones	zone	NOUN
cana-4763	171	15	and	and	CCONJ
cana-4763	171	16	regular	regular	ADJ
cana-4763	171	17	tissue	tissue	NOUN
cana-4763	171	18	in	in	ADP
cana-4763	171	19	order	order	NOUN
cana-4763	171	20	to	to	PART
cana-4763	171	21	better	well	ADV
cana-4763	171	22	classify	classify	VERB
cana-4763	171	23	unique	unique	ADJ
cana-4763	171	24	tumor	tumor	NOUN
cana-4763	171	25	types	type	NOUN
cana-4763	171	26	.	.	PUNCT
cana-4763	172	1	the	the	DET
cana-4763	172	2	semantic	semantic	ADJ
cana-4763	172	3	processing	processing	NOUN
cana-4763	172	4	ends	end	VERB
cana-4763	172	5	in	in	ADP
cana-4763	172	6	better	well	ADJ
cana-4763	172	7	patient	patient	ADJ
cana-4763	172	8	results	result	NOUN
cana-4763	172	9	combined	combine	VERB
cana-4763	172	10	with	with	ADP
cana-4763	172	11	improved	improve	VERB
cana-4763	172	12	therapeutic	therapeutic	ADJ
cana-4763	172	13	plans	plan	NOUN
cana-4763	172	14	.	.	PUNCT
cana-4763	173	1	research	research	NOUN
cana-4763	173	2	-	-	PUNCT
cana-4763	173	3	based	base	VERB
cana-4763	173	4	enhancements	enhancement	NOUN
cana-4763	173	5	of	of	ADP
cana-4763	173	6	classification	classification	NOUN
cana-4763	173	7	system	system	NOUN
cana-4763	173	8	predictive	predictive	ADJ
cana-4763	173	9	capability	capability	NOUN
cana-4763	173	10	become	become	VERB
cana-4763	173	11	possible	possible	ADJ
cana-4763	173	12	through	through	ADP
cana-4763	173	13	the	the	DET
cana-4763	173	14	incorporation	incorporation	NOUN
cana-4763	173	15	of	of	ADP
cana-4763	173	16	lbp	lbp	PROPN
cana-4763	173	17	features	feature	NOUN
cana-4763	173	18	within	within	ADP
cana-4763	173	19	machine	machine	NOUN
cana-4763	173	20	learning	learning	NOUN
cana-4763	173	21	platforms	platform	NOUN
cana-4763	173	22	.	.	PUNCT
cana-4763	174	1	how	how	SCONJ
cana-4763	174	2	lbp	lbp	PROPN
cana-4763	174	3	works	work	VERB
cana-4763	174	4	lbp	lbp	PROPN
cana-4763	174	5	function	function	PROPN
cana-4763	174	6	determines	determine	VERB
cana-4763	174	7	pixel	pixel	PROPN
cana-4763	174	8	binary	binary	ADJ
cana-4763	174	9	values	value	NOUN
cana-4763	174	10	through	through	ADP
cana-4763	174	11	processing	process	VERB
cana-4763	174	12	their	their	PRON
cana-4763	174	13	intensity	intensity	NOUN
cana-4763	174	14	versus	versus	ADP
cana-4763	174	15	that	that	PRON
cana-4763	174	16	of	of	ADP
cana-4763	174	17	adjacent	adjacent	ADJ
cana-4763	174	18	pixels	pixel	NOUN
cana-4763	174	19	.	.	PUNCT
cana-4763	175	1	the	the	DET
cana-4763	175	2	operations	operation	NOUN
cana-4763	175	3	of	of	ADP
cana-4763	175	4	lbp	lbp	PROPN
cana-4763	175	5	take	take	VERB
cana-4763	175	6	place	place	NOUN
cana-4763	175	7	inside	inside	ADP
cana-4763	175	8	a	a	DET
cana-4763	175	9	circular	circular	ADJ
cana-4763	175	10	group	group	NOUN
cana-4763	175	11	of	of	ADP
cana-4763	175	12	p	p	NOUN
cana-4763	175	13	neighboring	neighboring	NOUN
cana-4763	175	14	pixels	pixel	NOUN
cana-4763	175	15	extending	extend	VERB
cana-4763	175	16	from	from	ADP
cana-4763	175	17	any	any	DET
cana-4763	175	18	chosen	choose	VERB
cana-4763	175	19	pixel	pixel	NOUN
cana-4763	175	20	located	locate	VERB
cana-4763	175	21	at	at	ADP
cana-4763	175	22	position	position	NOUN
cana-4763	175	23	(	(	PUNCT
cana-4763	175	24	x	x	NOUN
cana-4763	175	25	,	,	PUNCT
cana-4763	175	26	y	y	PROPN
cana-4763	175	27	)	)	PUNCT
cana-4763	175	28	.	.	PUNCT
cana-4763	176	1	at	at	ADP
cana-4763	176	2	location	location	NOUN
cana-4763	176	3	(	(	PUNCT
cana-4763	176	4	x	x	X
cana-4763	176	5	,	,	PUNCT
cana-4763	176	6	y	y	PROPN
cana-4763	176	7	)	)	PUNCT
cana-4763	176	8	the	the	DET
cana-4763	176	9	central	central	ADJ
cana-4763	176	10	pixel	pixel	PROPN
cana-4763	176	11	intensity	intensity	NOUN
cana-4763	176	12	maintains	maintain	VERB
cana-4763	176	13	i(x	i(x	PROPN
cana-4763	176	14	,	,	PUNCT
cana-4763	176	15	y	y	NOUN
cana-4763	176	16	)	)	PUNCT
cana-4763	176	17	as	as	ADP
cana-4763	176	18	its	its	PRON
cana-4763	176	19	main	main	ADJ
cana-4763	176	20	value	value	NOUN
cana-4763	176	21	.	.	PUNCT
cana-4763	177	1	the	the	DET
cana-4763	177	2	circular	circular	ADJ
cana-4763	177	3	neighborhood	neighborhood	NOUN
cana-4763	177	4	contains	contain	VERB
cana-4763	177	5	pixels	pixel	NOUN
cana-4763	177	6	which	which	PRON
cana-4763	177	7	are	be	AUX
cana-4763	177	8	indexed	index	VERB
cana-4763	177	9	from	from	ADP
cana-4763	177	10	0	0	NUM
cana-4763	177	11	to	to	ADP
cana-4763	177	12	1	1	NUM
cana-4763	177	13	to	to	PART
cana-4763	177	14	2	2	NUM
cana-4763	177	15	extending	extend	VERB
cana-4763	177	16	indefinitely	indefinitely	ADV
cana-4763	177	17	where	where	SCONJ
cana-4763	177	18	pixel	pixel	PROPN
cana-4763	177	19	ii	ii	PROPN
cana-4763	177	20	represents	represent	VERB
cana-4763	177	21	each	each	DET
cana-4763	177	22	neighboring	neighboring	NOUN
cana-4763	177	23	intensity	intensity	NOUN
cana-4763	177	24	.	.	PUNCT
cana-4763	178	1	p-1	p-1	PROPN
cana-4763	178	2	.	.	PUNCT
cana-4763	179	1	through	through	ADP
cana-4763	179	2	thresholding	thresholde	VERB
cana-4763	179	3	pixel	pixel	NOUN
cana-4763	179	4	intensities	intensity	NOUN
cana-4763	179	5	in	in	ADP
cana-4763	179	6	specific	specific	ADJ
cana-4763	179	7	relation	relation	NOUN
cana-4763	179	8	to	to	ADP
cana-4763	179	9	the	the	DET
cana-4763	179	10	central	central	ADJ
cana-4763	179	11	pixel	pixel	NOUN
cana-4763	179	12	the	the	DET
cana-4763	179	13	lbp	lbp	NOUN
cana-4763	179	14	operator	operator	NOUN
cana-4763	179	15	produces	produce	VERB
cana-4763	179	16	binary	binary	ADJ
cana-4763	179	17	patterns	pattern	NOUN
cana-4763	179	18	that	that	PRON
cana-4763	179	19	display	display	VERB
cana-4763	179	20	local	local	ADJ
cana-4763	179	21	image	image	NOUN
cana-4763	179	22	characteristics	characteristic	NOUN
cana-4763	179	23	.	.	PUNCT
cana-4763	180	1	through	through	ADP
cana-4763	180	2	this	this	DET
cana-4763	180	3	technique	technique	NOUN
cana-4763	180	4	hospital	hospital	NOUN
cana-4763	180	5	can	can	AUX
cana-4763	180	6	achieve	achieve	VERB
cana-4763	180	7	precise	precise	ADJ
cana-4763	180	8	features	feature	NOUN
cana-4763	180	9	for	for	ADP
cana-4763	180	10	classification	classification	NOUN
cana-4763	180	11	of	of	ADP
cana-4763	180	12	brain	brain	NOUN
cana-4763	180	13	tumors	tumor	NOUN
cana-4763	180	14	.	.	PUNCT
cana-4763	181	1	the	the	DET
cana-4763	181	2	lbp	lbp	PROPN
cana-4763	181	3	value	value	NOUN
cana-4763	181	4	for	for	ADP
cana-4763	181	5	this	this	DET
cana-4763	181	6	central	central	ADJ
cana-4763	181	7	pixel	pixel	NOUN
cana-4763	181	8	is	be	AUX
cana-4763	181	9	computed	compute	VERB
cana-4763	181	10	as	as	ADP
cana-4763	181	11	:	:	PUNCT
cana-4763	181	12	lbp(x	lbp(x	PROPN
cana-4763	181	13	,	,	PUNCT
cana-4763	181	14	y)=	y)=	ADJ
cana-4763	181	15	∑	∑	PROPN
cana-4763	181	16	s	s	PROPN
cana-4763	181	17	p−1	p−1	PROPN
cana-4763	181	18	i=0	i=0	PROPN
cana-4763	181	19	(	(	PUNCT
cana-4763	181	20	ii	ii	NOUN
cana-4763	181	21	-	-	PUNCT
cana-4763	181	22	i(x	i(x	NOUN
cana-4763	181	23	,	,	PUNCT
cana-4763	181	24	y	y	NOUN
cana-4763	181	25	)	)	PUNCT
cana-4763	181	26	)	)	PUNCT
cana-4763	181	27	.	.	PUNCT
cana-4763	182	1	2i	2i	NOUN
cana-4763	182	2	.	.	PUNCT
cana-4763	183	1	…	…	PUNCT
cana-4763	183	2	.(2	.(2	NUM
cana-4763	183	3	)	)	PUNCT
cana-4763	183	4	where	where	SCONJ
cana-4763	183	5	s(x	s(x	NOUN
cana-4763	183	6	)	)	PUNCT
cana-4763	183	7	is	be	AUX
cana-4763	183	8	the	the	DET
cana-4763	183	9	thresholding	thresholde	VERB
cana-4763	183	10	function	function	NOUN
cana-4763	183	11	,	,	PUNCT
cana-4763	183	12	defined	define	VERB
cana-4763	183	13	as	as	ADP
cana-4763	183	14	:	:	PUNCT
cana-4763	183	15	s(x	s(x	NUM
cana-4763	183	16	)	)	PUNCT
cana-4763	184	1	=	=	PRON
cana-4763	184	2	{	{	PUNCT
cana-4763	184	3	1	1	NUM
cana-4763	184	4	,	,	PUNCT
cana-4763	184	5	if	if	SCONJ
cana-4763	184	6	x	x	PRON
cana-4763	184	7	≥	≥	VERB
cana-4763	184	8	0	0	NUM
cana-4763	184	9	0	0	NUM
cana-4763	184	10	,	,	PUNCT
cana-4763	184	11	if	if	SCONJ
cana-4763	184	12	x	x	X
cana-4763	184	13	<	<	X
cana-4763	184	14	0	0	NUM
cana-4763	184	15	…	…	PUNCT
cana-4763	184	16	.(3	.(3	SYM
cana-4763	184	17	)	)	PUNCT
cana-4763	185	1	this	this	DET
cana-4763	185	2	function	function	NOUN
cana-4763	185	3	evaluates	evaluate	VERB
cana-4763	185	4	the	the	DET
cana-4763	185	5	intensity	intensity	NOUN
cana-4763	185	6	ii	ii	PROPN
cana-4763	185	7	of	of	ADP
cana-4763	185	8	each	each	DET
cana-4763	185	9	neighboring	neighboring	NOUN
cana-4763	185	10	pixel	pixel	NOUN
cana-4763	185	11	against	against	ADP
cana-4763	185	12	the	the	DET
cana-4763	185	13	intensity	intensity	NOUN
cana-4763	185	14	i(x	i(x	PROPN
cana-4763	185	15	,	,	PUNCT
cana-4763	185	16	y	y	NOUN
cana-4763	185	17	)	)	PUNCT
cana-4763	185	18	of	of	ADP
cana-4763	185	19	the	the	DET
cana-4763	185	20	central	central	ADJ
cana-4763	185	21	pixel	pixel	NOUN
cana-4763	185	22	.	.	PUNCT
cana-4763	186	1	3.3.2	3.3.2	NUM
cana-4763	186	2	lbp	lbp	PROPN
cana-4763	186	3	histogram	histogram	VERB
cana-4763	186	4	the	the	DET
cana-4763	186	5	following	follow	VERB
cana-4763	186	6	process	process	NOUN
cana-4763	186	7	involves	involve	VERB
cana-4763	186	8	generating	generate	VERB
cana-4763	186	9	an	an	DET
cana-4763	186	10	lbp	lbp	NOUN
cana-4763	186	11	histogram	histogram	NOUN
cana-4763	186	12	after	after	ADP
cana-4763	186	13	implementing	implement	VERB
cana-4763	186	14	the	the	DET
cana-4763	186	15	local	local	ADJ
cana-4763	186	16	binary	binary	ADJ
cana-4763	186	17	pattern	pattern	NOUN
cana-4763	186	18	(	(	PUNCT
cana-4763	186	19	lbp	lbp	NOUN
cana-4763	186	20	)	)	PUNCT
cana-4763	186	21	operation	operation	NOUN
cana-4763	186	22	on	on	ADP
cana-4763	186	23	every	every	DET
cana-4763	186	24	image	image	NOUN
cana-4763	186	25	pixel	pixel	NOUN
cana-4763	186	26	.	.	PUNCT
cana-4763	187	1	the	the	DET
cana-4763	187	2	image	image	NOUN
cana-4763	187	3	's	's	PART
cana-4763	187	4	regional	regional	ADJ
cana-4763	187	5	distribution	distribution	NOUN
cana-4763	187	6	(	(	PUNCT
cana-4763	187	7	roi	roi	NOUN
cana-4763	187	8	)	)	PUNCT
cana-4763	187	9	shows	show	VERB
cana-4763	187	10	various	various	ADJ
cana-4763	187	11	lbp	lbp	NOUN
cana-4763	187	12	patterns	pattern	NOUN
cana-4763	187	13	which	which	PRON
cana-4763	187	14	generate	generate	VERB
cana-4763	187	15	this	this	DET
cana-4763	187	16	histogram	histogram	NOUN
cana-4763	187	17	.	.	PUNCT
cana-4763	188	1	communications	communication	NOUN
cana-4763	188	2	on	on	ADP
cana-4763	188	3	applied	apply	VERB
cana-4763	188	4	nonlinear	nonlinear	ADJ
cana-4763	188	5	analysis	analysis	NOUN
cana-4763	188	6	issn	issn	NOUN
cana-4763	188	7	:	:	PUNCT
cana-4763	188	8	1074	1074	NUM
cana-4763	188	9	-	-	PUNCT
cana-4763	188	10	133x	133x	NUM
cana-4763	188	11	vol	vol	VERB
cana-4763	188	12	32	32	NUM
cana-4763	188	13	no	no	NOUN
cana-4763	188	14	.	.	PUNCT
cana-4763	189	1	10s	10	NOUN
cana-4763	189	2	(	(	PUNCT
cana-4763	189	3	2025	2025	NUM
cana-4763	189	4	)	)	PUNCT
cana-4763	189	5	302	302	NUM
cana-4763	189	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	189	7	histogram	histogram	NOUN
cana-4763	189	8	calculation	calculation	NOUN
cana-4763	189	9	let	let	VERB
cana-4763	189	10	l(x	l(x	PROPN
cana-4763	189	11	,	,	PUNCT
cana-4763	189	12	y	y	PROPN
cana-4763	189	13	)	)	PUNCT
cana-4763	189	14	denote	denote	VERB
cana-4763	189	15	the	the	DET
cana-4763	189	16	lbp	lbp	PROPN
cana-4763	189	17	value	value	NOUN
cana-4763	189	18	at	at	ADP
cana-4763	189	19	pixel	pixel	PROPN
cana-4763	189	20	(	(	PUNCT
cana-4763	189	21	x	x	X
cana-4763	189	22	,	,	PUNCT
cana-4763	189	23	y	y	PROPN
cana-4763	189	24	)	)	PUNCT
cana-4763	189	25	,	,	PUNCT
cana-4763	189	26	and	and	CCONJ
cana-4763	189	27	let	let	VERB
cana-4763	189	28	n	n	PRON
cana-4763	189	29	represent	represent	VERB
cana-4763	189	30	the	the	DET
cana-4763	189	31	total	total	ADJ
cana-4763	189	32	number	number	NOUN
cana-4763	189	33	of	of	ADP
cana-4763	189	34	pixels	pixel	NOUN
cana-4763	189	35	in	in	ADP
cana-4763	189	36	the	the	DET
cana-4763	189	37	image	image	NOUN
cana-4763	189	38	or	or	CCONJ
cana-4763	189	39	the	the	DET
cana-4763	189	40	specified	specified	ADJ
cana-4763	189	41	region	region	NOUN
cana-4763	189	42	.	.	PUNCT
cana-4763	190	1	the	the	DET
cana-4763	190	2	histogram	histogram	NOUN
cana-4763	190	3	h	h	NOUN
cana-4763	190	4	is	be	AUX
cana-4763	190	5	then	then	ADV
cana-4763	190	6	defined	define	VERB
cana-4763	190	7	as	as	SCONJ
cana-4763	190	8	follows	follow	VERB
cana-4763	190	9	:	:	PUNCT
cana-4763	190	10	hi	hi	INTJ
cana-4763	191	1	=	=	SYM
cana-4763	191	2	σ(x	σ(x	PROPN
cana-4763	191	3	,	,	PUNCT
cana-4763	191	4	y)δ(l(x	y)δ(l(x	PROPN
cana-4763	191	5	,	,	PUNCT
cana-4763	191	6	y),i	y),i	PROPN
cana-4763	191	7	)	)	PUNCT
cana-4763	191	8	n	n	CCONJ
cana-4763	191	9	…	…	PUNCT
cana-4763	191	10	.(4	.(4	NUM
cana-4763	191	11	)	)	PUNCT
cana-4763	192	1	here	here	ADV
cana-4763	192	2	,	,	PUNCT
cana-4763	192	3	hi	hi	INTJ
cana-4763	192	4	indicates	indicate	VERB
cana-4763	192	5	the	the	DET
cana-4763	192	6	frequency	frequency	NOUN
cana-4763	192	7	of	of	ADP
cana-4763	192	8	the	the	DET
cana-4763	192	9	lbp	lbp	PROPN
cana-4763	192	10	code	code	PROPN
cana-4763	192	11	i	i	PRON
cana-4763	192	12	in	in	ADP
cana-4763	192	13	the	the	DET
cana-4763	192	14	image	image	NOUN
cana-4763	192	15	.	.	PUNCT
cana-4763	193	1	the	the	DET
cana-4763	193	2	kronecker	kronecker	NOUN
cana-4763	193	3	delta	delta	PROPN
cana-4763	193	4	function	function	NOUN
cana-4763	193	5	,	,	PUNCT
cana-4763	193	6	denoted	denote	VERB
cana-4763	193	7	as	as	ADP
cana-4763	193	8	δ(a	δ(a	PROPN
cana-4763	193	9	,	,	PUNCT
cana-4763	193	10	b	b	NOUN
cana-4763	193	11	)	)	PUNCT
cana-4763	193	12	,	,	PUNCT
cana-4763	193	13	is	be	AUX
cana-4763	193	14	defined	define	VERB
cana-4763	193	15	as	as	ADP
cana-4763	193	16	:	:	PUNCT
cana-4763	193	17	δ(a	δ(a	PROPN
cana-4763	193	18	,	,	PUNCT
cana-4763	193	19	b	b	NOUN
cana-4763	193	20	)	)	PUNCT
cana-4763	193	21	=	=	NOUN
cana-4763	193	22	{	{	PUNCT
cana-4763	193	23	1	1	NUM
cana-4763	193	24	,	,	PUNCT
cana-4763	193	25	if	if	SCONJ
cana-4763	193	26	a	a	DET
cana-4763	193	27	=	=	SYM
cana-4763	193	28	b	b	NOUN
cana-4763	193	29	0	0	NUM
cana-4763	193	30	,	,	PUNCT
cana-4763	193	31	if	if	SCONJ
cana-4763	193	32	a	a	DET
cana-4763	193	33	≠	≠	PROPN
cana-4763	193	34	b	b	NOUN
cana-4763	193	35	…	…	PUNCT
cana-4763	193	36	.(5	.(5	NOUN
cana-4763	193	37	)	)	PUNCT
cana-4763	193	38	the	the	DET
cana-4763	193	39	following	follow	VERB
cana-4763	193	40	process	process	NOUN
cana-4763	193	41	involves	involve	VERB
cana-4763	193	42	generating	generate	VERB
cana-4763	193	43	an	an	DET
cana-4763	193	44	lbp	lbp	NOUN
cana-4763	193	45	histogram	histogram	NOUN
cana-4763	193	46	after	after	ADP
cana-4763	193	47	implementing	implement	VERB
cana-4763	193	48	the	the	DET
cana-4763	193	49	local	local	ADJ
cana-4763	193	50	binary	binary	ADJ
cana-4763	193	51	pattern	pattern	NOUN
cana-4763	193	52	(	(	PUNCT
cana-4763	193	53	lbp	lbp	NOUN
cana-4763	193	54	)	)	PUNCT
cana-4763	193	55	operation	operation	NOUN
cana-4763	193	56	on	on	ADP
cana-4763	193	57	every	every	DET
cana-4763	193	58	image	image	NOUN
cana-4763	193	59	pixel	pixel	NOUN
cana-4763	193	60	.	.	PUNCT
cana-4763	194	1	the	the	DET
cana-4763	194	2	image	image	NOUN
cana-4763	194	3	's	's	PART
cana-4763	194	4	regional	regional	ADJ
cana-4763	194	5	distribution	distribution	NOUN
cana-4763	194	6	(	(	PUNCT
cana-4763	194	7	roi	roi	NOUN
cana-4763	194	8	)	)	PUNCT
cana-4763	194	9	shows	show	VERB
cana-4763	194	10	various	various	ADJ
cana-4763	194	11	lbp	lbp	NOUN
cana-4763	194	12	patterns	pattern	NOUN
cana-4763	194	13	which	which	PRON
cana-4763	194	14	generate	generate	VERB
cana-4763	194	15	this	this	DET
cana-4763	194	16	histogram	histogram	NOUN
cana-4763	194	17	.	.	PUNCT
cana-4763	195	1	texture	texture	NOUN
cana-4763	195	2	features	feature	NOUN
cana-4763	195	3	derived	derive	VERB
cana-4763	195	4	from	from	ADP
cana-4763	195	5	lbp	lbp	PROPN
cana-4763	195	6	histogram	histogram	PROPN
cana-4763	195	7	the	the	DET
cana-4763	195	8	lbp	lbp	PROPN
cana-4763	195	9	histogram	histogram	PROPN
cana-4763	195	10	yields	yield	VERB
cana-4763	195	11	several	several	ADJ
cana-4763	195	12	statistical	statistical	ADJ
cana-4763	195	13	texture	texture	NOUN
cana-4763	195	14	features	feature	NOUN
cana-4763	195	15	which	which	PRON
cana-4763	195	16	provide	provide	VERB
cana-4763	195	17	valuable	valuable	ADJ
cana-4763	195	18	classification	classification	NOUN
cana-4763	195	19	attributes	attribute	NOUN
cana-4763	195	20	.	.	PUNCT
cana-4763	196	1	here	here	ADV
cana-4763	196	2	are	be	AUX
cana-4763	196	3	a	a	DET
cana-4763	196	4	few	few	ADJ
cana-4763	196	5	of	of	ADP
cana-4763	196	6	these	these	DET
cana-4763	196	7	attributes	attribute	NOUN
cana-4763	196	8	.	.	PUNCT
cana-4763	196	9	:	:	PUNCT
cana-4763	197	1	energy	energy	NOUN
cana-4763	197	2	(	(	PUNCT
cana-4763	197	3	uniformity	uniformity	NOUN
cana-4763	197	4	):	):	PUNCT
cana-4763	197	5	energy	energy	NOUN
cana-4763	197	6	=	=	PUNCT
cana-4763	197	7	∑	∑	PUNCT
cana-4763	197	8	hi	hi	PROPN
cana-4763	197	9	2n−1	2n−1	NUM
cana-4763	197	10	i=0	i=0	PROPN
cana-4763	197	11	…	…	PUNCT
cana-4763	197	12	(	(	PUNCT
cana-4763	197	13	6	6	NUM
cana-4763	197	14	)	)	PUNCT
cana-4763	197	15	this	this	PRON
cana-4763	197	16	measures	measure	VERB
cana-4763	197	17	the	the	DET
cana-4763	197	18	homogeneity	homogeneity	NOUN
cana-4763	197	19	of	of	ADP
cana-4763	197	20	texture	texture	NOUN
cana-4763	197	21	.	.	PUNCT
cana-4763	198	1	high	high	ADJ
cana-4763	198	2	-	-	PUNCT
cana-4763	198	3	energy	energy	NOUN
cana-4763	198	4	textures	texture	NOUN
cana-4763	198	5	exhibit	exhibit	VERB
cana-4763	198	6	uniformity	uniformity	NOUN
cana-4763	198	7	but	but	CCONJ
cana-4763	198	8	low	low	ADJ
cana-4763	198	9	-	-	PUNCT
cana-4763	198	10	energy	energy	NOUN
cana-4763	198	11	texture	texture	NOUN
cana-4763	198	12	displays	display	VERB
cana-4763	198	13	inhomogeneity	inhomogeneity	PROPN
cana-4763	198	14	.	.	PUNCT
cana-4763	199	1	entropy	entropy	PROPN
cana-4763	199	2	:	:	PUNCT
cana-4763	199	3	entropy	entropy	PROPN
cana-4763	199	4	=	=	SYM
cana-4763	199	5	−	−	PROPN
cana-4763	199	6	∑	∑	PROPN
cana-4763	199	7	hi	hi	INTJ
cana-4763	199	8	log(hi	log(hi	NOUN
cana-4763	199	9	)	)	PUNCT
cana-4763	200	1	n−1	n−1	PROPN
cana-4763	200	2	i=0	i=0	PROPN
cana-4763	200	3	…	…	PUNCT
cana-4763	200	4	(	(	PUNCT
cana-4763	200	5	7	7	NUM
cana-4763	200	6	)	)	PUNCT
cana-4763	200	7	entropy	entropy	NOUN
cana-4763	200	8	measures	measure	VERB
cana-4763	200	9	a	a	DET
cana-4763	200	10	texture	texture	NOUN
cana-4763	200	11	's	's	PART
cana-4763	200	12	randomness	randomness	NOUN
cana-4763	200	13	or	or	CCONJ
cana-4763	200	14	unpredictability	unpredictability	NOUN
cana-4763	200	15	.	.	PUNCT
cana-4763	201	1	entropies	entropy	NOUN
cana-4763	201	2	rise	rise	VERB
cana-4763	201	3	steadily	steadily	ADV
cana-4763	201	4	with	with	ADP
cana-4763	201	5	the	the	DET
cana-4763	201	6	complexity	complexity	NOUN
cana-4763	201	7	of	of	ADP
cana-4763	201	8	textures	texture	NOUN
cana-4763	201	9	appearing	appear	VERB
cana-4763	201	10	most	most	ADV
cana-4763	201	11	often	often	ADV
cana-4763	201	12	within	within	ADP
cana-4763	201	13	tumor	tumor	NOUN
cana-4763	201	14	regions	region	NOUN
cana-4763	201	15	.	.	PUNCT
cana-4763	202	1	contrast	contrast	NOUN
cana-4763	202	2	:	:	PUNCT
cana-4763	202	3	contrast	contrast	NOUN
cana-4763	202	4	=	=	PUNCT
cana-4763	202	5	∑	∑	PUNCT
cana-4763	202	6	∑	∑	PUNCT
cana-4763	202	7	(	(	PUNCT
cana-4763	202	8	i	i	PRON
cana-4763	202	9	−	−	VERB
cana-4763	203	1	j̈)2hij	j̈)2hij	PROPN
cana-4763	203	2	n−1	n−1	PROPN
cana-4763	203	3	j=0	j=0	PROPN
cana-4763	203	4	n−1	n−1	PROPN
cana-4763	203	5	i=0	i=0	PROPN
cana-4763	203	6	…	…	PUNCT
cana-4763	203	7	(	(	PUNCT
cana-4763	203	8	8)	8)	NUM
cana-4763	203	9	this	this	DET
cana-4763	203	10	feature	feature	NOUN
cana-4763	203	11	detects	detect	VERB
cana-4763	203	12	the	the	DET
cana-4763	203	13	variations	variation	NOUN
cana-4763	203	14	in	in	ADP
cana-4763	203	15	intensity	intensity	NOUN
cana-4763	203	16	in	in	ADP
cana-4763	203	17	different	different	ADJ
cana-4763	203	18	regions	region	NOUN
cana-4763	203	19	.	.	PUNCT
cana-4763	204	1	higher	high	ADJ
cana-4763	204	2	contrast	contrast	NOUN
cana-4763	204	3	values	value	NOUN
cana-4763	204	4	highlight	highlight	VERB
cana-4763	204	5	sharp	sharp	ADJ
cana-4763	204	6	edges	edge	NOUN
cana-4763	204	7	in	in	ADP
cana-4763	204	8	pictures	picture	NOUN
cana-4763	204	9	because	because	SCONJ
cana-4763	204	10	this	this	PRON
cana-4763	204	11	allows	allow	VERB
cana-4763	204	12	for	for	ADP
cana-4763	204	13	better	well	ADJ
cana-4763	204	14	tumor	tumor	NOUN
cana-4763	204	15	boundary	boundary	ADJ
cana-4763	204	16	detection	detection	NOUN
cana-4763	204	17	.	.	PUNCT
cana-4763	205	1	correlation	correlation	NOUN
cana-4763	205	2	:	:	PUNCT
cana-4763	205	3	correlation	correlation	NOUN
cana-4763	205	4	=	=	PUNCT
cana-4763	205	5	∑	∑	PUNCT
cana-4763	205	6	∑	∑	PROPN
cana-4763	205	7	(	(	PUNCT
cana-4763	205	8	i−μ)(j−μ)hij	i−μ)(j−μ)hij	PROPN
cana-4763	205	9	n−1	n−1	PROPN
cana-4763	205	10	j=0	j=0	PROPN
cana-4763	205	11	n−1	n−1	PROPN
cana-4763	205	12	i=0	i=0	PROPN
cana-4763	205	13	σxσy	σxσy	NOUN
cana-4763	205	14	…	…	PUNCT
cana-4763	205	15	..	..	PUNCT
cana-4763	205	16	(	(	PUNCT
cana-4763	205	17	9	9	NUM
cana-4763	205	18	)	)	PUNCT
cana-4763	205	19	here	here	ADV
cana-4763	205	20	,	,	PUNCT
cana-4763	205	21	μ	μ	PROPN
cana-4763	205	22	represents	represent	VERB
cana-4763	205	23	the	the	DET
cana-4763	205	24	mean	mean	ADJ
cana-4763	205	25	intensity	intensity	NOUN
cana-4763	205	26	,	,	PUNCT
cana-4763	205	27	while	while	SCONJ
cana-4763	205	28	σx	σx	NOUN
cana-4763	205	29	and	and	CCONJ
cana-4763	205	30	σy	σy	PRON
cana-4763	205	31	are	be	AUX
cana-4763	205	32	the	the	DET
cana-4763	205	33	standard	standard	ADJ
cana-4763	205	34	deviations	deviation	NOUN
cana-4763	205	35	along	along	ADP
cana-4763	205	36	the	the	DET
cana-4763	205	37	horizontal	horizontal	ADJ
cana-4763	205	38	and	and	CCONJ
cana-4763	205	39	vertical	vertical	ADJ
cana-4763	205	40	axes	axis	NOUN
cana-4763	205	41	,	,	PUNCT
cana-4763	205	42	respectively	respectively	ADV
cana-4763	205	43	.	.	PUNCT
cana-4763	206	1	homogeneity	homogeneity	NOUN
cana-4763	206	2	:	:	PUNCT
cana-4763	206	3	homogeneity	homogeneity	NOUN
cana-4763	206	4	=	=	SYM
cana-4763	206	5	∑	∑	PUNCT
cana-4763	206	6	∑	∑	PUNCT
cana-4763	206	7	hij	hij	PROPN
cana-4763	206	8	1+|i−j|	1+|i−j|	NUM
cana-4763	206	9	n−1	n−1	PROPN
cana-4763	206	10	j=0	j=0	PROPN
cana-4763	206	11	n−1	n−1	PROPN
cana-4763	206	12	i̇=0	i̇=0	NOUN
cana-4763	206	13	…	…	PUNCT
cana-4763	206	14	..	..	PUNCT
cana-4763	206	15	(	(	PUNCT
cana-4763	206	16	10	10	NUM
cana-4763	206	17	)	)	PUNCT
cana-4763	206	18	the	the	DET
cana-4763	206	19	metric	metric	ADJ
cana-4763	206	20	measures	measure	NOUN
cana-4763	206	21	pixel	pixel	PROPN
cana-4763	206	22	neighbor	neighbor	PROPN
cana-4763	206	23	intensity	intensity	PROPN
cana-4763	206	24	similarity	similarity	NOUN
cana-4763	206	25	for	for	ADP
cana-4763	206	26	separating	separate	VERB
cana-4763	206	27	uniform	uniform	NOUN
cana-4763	206	28	from	from	ADP
cana-4763	206	29	varied	varied	ADJ
cana-4763	206	30	tissue	tissue	NOUN
cana-4763	206	31	structures	structure	NOUN
cana-4763	206	32	.	.	PUNCT
cana-4763	207	1	3.3.3	3.3.3	NUM
cana-4763	207	2	improved	improve	VERB
cana-4763	207	3	grey	grey	ADJ
cana-4763	207	4	wolf	wolf	PROPN
cana-4763	207	5	optimization	optimization	NOUN
cana-4763	207	6	(	(	PUNCT
cana-4763	207	7	gwo	gwo	PROPN
cana-4763	207	8	)	)	PUNCT
cana-4763	207	9	for	for	ADP
cana-4763	207	10	brain	brain	NOUN
cana-4763	207	11	tumor	tumor	NOUN
cana-4763	207	12	classification	classification	NOUN
cana-4763	207	13	using	use	VERB
cana-4763	207	14	texture	texture	NOUN
cana-4763	207	15	features	feature	VERB
cana-4763	207	16	the	the	DET
cana-4763	207	17	gwo	gwo	PROPN
cana-4763	207	18	optimization	optimization	NOUN
cana-4763	207	19	method	method	NOUN
cana-4763	207	20	applies	apply	VERB
cana-4763	207	21	intelligent	intelligent	ADJ
cana-4763	207	22	search	search	NOUN
cana-4763	207	23	techniques	technique	NOUN
cana-4763	207	24	from	from	ADP
cana-4763	207	25	the	the	DET
cana-4763	207	26	natural	natural	ADJ
cana-4763	207	27	behavior	behavior	NOUN
cana-4763	207	28	patterns	pattern	NOUN
cana-4763	207	29	of	of	ADP
cana-4763	207	30	grey	grey	ADJ
cana-4763	207	31	wolves	wolf	NOUN
cana-4763	207	32	during	during	ADP
cana-4763	207	33	social	social	ADJ
cana-4763	207	34	activities	activity	NOUN
cana-4763	207	35	and	and	CCONJ
cana-4763	207	36	their	their	PRON
cana-4763	207	37	hunting	hunt	VERB
cana-4763	207	38	methods	method	NOUN
cana-4763	207	39	.	.	PUNCT
cana-4763	208	1	this	this	DET
cana-4763	208	2	algorithm	algorithm	NOUN
cana-4763	208	3	finds	find	VERB
cana-4763	208	4	current	current	ADJ
cana-4763	208	5	use	use	NOUN
cana-4763	208	6	in	in	ADP
cana-4763	208	7	addressing	address	VERB
cana-4763	208	8	problems	problem	NOUN
cana-4763	208	9	that	that	PRON
cana-4763	208	10	involve	involve	VERB
cana-4763	208	11	feature	feature	NOUN
cana-4763	208	12	selection	selection	NOUN
cana-4763	208	13	together	together	ADV
cana-4763	208	14	with	with	ADP
cana-4763	208	15	classification	classification	NOUN
cana-4763	208	16	challenges	challenge	NOUN
cana-4763	208	17	alongside	alongside	ADP
cana-4763	208	18	hyperparameters	hyperparameter	NOUN
cana-4763	208	19	optimization	optimization	NOUN
cana-4763	208	20	.	.	PUNCT
cana-4763	209	1	the	the	DET
cana-4763	209	2	study	study	NOUN
cana-4763	209	3	employs	employ	VERB
cana-4763	209	4	extracted	extract	VERB
cana-4763	209	5	texture	texture	ADJ
cana-4763	209	6	features	feature	NOUN
cana-4763	209	7	for	for	ADP
cana-4763	209	8	classification	classification	NOUN
cana-4763	209	9	enhancement	enhancement	NOUN
cana-4763	209	10	using	use	VERB
cana-4763	209	11	gwo	gwo	PROPN
cana-4763	209	12	.	.	PUNCT
cana-4763	210	1	communications	communication	NOUN
cana-4763	210	2	on	on	ADP
cana-4763	210	3	applied	apply	VERB
cana-4763	210	4	nonlinear	nonlinear	ADJ
cana-4763	210	5	analysis	analysis	NOUN
cana-4763	210	6	issn	issn	NOUN
cana-4763	210	7	:	:	PUNCT
cana-4763	210	8	1074	1074	NUM
cana-4763	210	9	-	-	PUNCT
cana-4763	210	10	133x	133x	NUM
cana-4763	210	11	vol	vol	VERB
cana-4763	210	12	32	32	NUM
cana-4763	210	13	no	no	NOUN
cana-4763	210	14	.	.	PUNCT
cana-4763	211	1	10s	10	NOUN
cana-4763	211	2	(	(	PUNCT
cana-4763	211	3	2025	2025	NUM
cana-4763	211	4	)	)	PUNCT
cana-4763	211	5	303	303	NUM
cana-4763	211	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	211	7	gwo	gwo	PROPN
cana-4763	211	8	follows	follow	VERB
cana-4763	211	9	the	the	DET
cana-4763	211	10	organizational	organizational	ADJ
cana-4763	211	11	hunting	hunting	NOUN
cana-4763	211	12	patterns	pattern	NOUN
cana-4763	211	13	of	of	ADP
cana-4763	211	14	grey	grey	ADJ
cana-4763	211	15	wolves	wolf	NOUN
cana-4763	211	16	by	by	ADP
cana-4763	211	17	using	use	VERB
cana-4763	211	18	four	four	NUM
cana-4763	211	19	distinct	distinct	ADJ
cana-4763	211	20	wolf	wolf	NOUN
cana-4763	211	21	types	type	NOUN
cana-4763	211	22	.	.	PUNCT
cana-4763	212	1	⚫	⚫	NOUN
cana-4763	212	2	alpha	alpha	NOUN
cana-4763	212	3	(	(	PUNCT
cana-4763	212	4	α	α	NOUN
cana-4763	212	5	)	)	PUNCT
cana-4763	212	6	wolves	wolf	NOUN
cana-4763	212	7	:	:	PUNCT
cana-4763	212	8	these	these	PRON
cana-4763	212	9	are	be	AUX
cana-4763	212	10	the	the	DET
cana-4763	212	11	top	top	ADJ
cana-4763	212	12	dogs	dog	NOUN
cana-4763	212	13	,	,	PUNCT
cana-4763	212	14	representing	represent	VERB
cana-4763	212	15	the	the	DET
cana-4763	212	16	best	good	ADJ
cana-4763	212	17	solution	solution	NOUN
cana-4763	212	18	(	(	PUNCT
cana-4763	212	19	the	the	DET
cana-4763	212	20	leader	leader	NOUN
cana-4763	212	21	)	)	PUNCT
cana-4763	212	22	.	.	PUNCT
cana-4763	213	1	⚫	⚫	NOUN
cana-4763	213	2	beta	beta	NOUN
cana-4763	213	3	(	(	PUNCT
cana-4763	213	4	β	β	NOUN
cana-4763	213	5	)	)	PUNCT
cana-4763	213	6	wolves	wolf	NOUN
cana-4763	213	7	:	:	PUNCT
cana-4763	213	8	they	they	PRON
cana-4763	213	9	stand	stand	VERB
cana-4763	213	10	in	in	ADP
cana-4763	213	11	as	as	ADP
cana-4763	213	12	the	the	DET
cana-4763	213	13	second	second	ADV
cana-4763	213	14	-	-	PUNCT
cana-4763	213	15	best	good	ADJ
cana-4763	213	16	solution	solution	NOUN
cana-4763	213	17	.	.	PUNCT
cana-4763	214	1	⚫	⚫	NOUN
cana-4763	214	2	delta	delta	NOUN
cana-4763	214	3	(	(	PUNCT
cana-4763	214	4	δ	δ	NOUN
cana-4763	214	5	)	)	PUNCT
cana-4763	214	6	wolves	wolf	NOUN
cana-4763	214	7	:	:	PUNCT
cana-4763	214	8	these	these	DET
cana-4763	214	9	guys	guy	NOUN
cana-4763	214	10	represent	represent	VERB
cana-4763	214	11	the	the	DET
cana-4763	214	12	third	third	ADV
cana-4763	214	13	-	-	PUNCT
cana-4763	214	14	best	good	ADJ
cana-4763	214	15	solution	solution	NOUN
cana-4763	214	16	.	.	PUNCT
cana-4763	215	1	⚫	⚫	NOUN
cana-4763	215	2	omega	omega	NOUN
cana-4763	215	3	(	(	PUNCT
cana-4763	215	4	ω	ω	NOUN
cana-4763	215	5	)	)	PUNCT
cana-4763	215	6	wolves	wolf	NOUN
cana-4763	215	7	:	:	PUNCT
cana-4763	215	8	this	this	DET
cana-4763	215	9	group	group	NOUN
cana-4763	215	10	makes	make	VERB
cana-4763	215	11	up	up	ADP
cana-4763	215	12	the	the	DET
cana-4763	215	13	rest	rest	NOUN
cana-4763	215	14	of	of	ADP
cana-4763	215	15	the	the	DET
cana-4763	215	16	pack	pack	NOUN
cana-4763	215	17	,	,	PUNCT
cana-4763	215	18	following	follow	VERB
cana-4763	215	19	the	the	DET
cana-4763	215	20	leaders	leader	NOUN
cana-4763	215	21	.	.	PUNCT
cana-4763	216	1	these	these	DET
cana-4763	216	2	wolves	wolf	NOUN
cana-4763	216	3	work	work	VERB
cana-4763	216	4	together	together	ADV
cana-4763	216	5	to	to	PART
cana-4763	216	6	find	find	VERB
cana-4763	216	7	the	the	DET
cana-4763	216	8	optimal	optimal	ADJ
cana-4763	216	9	solution	solution	NOUN
cana-4763	216	10	in	in	ADP
cana-4763	216	11	the	the	DET
cana-4763	216	12	search	search	NOUN
cana-4763	216	13	space	space	NOUN
cana-4763	216	14	through	through	ADP
cana-4763	216	15	the	the	DET
cana-4763	216	16	following	follow	VERB
cana-4763	216	17	steps	step	NOUN
cana-4763	216	18	:	:	PUNCT
cana-4763	217	1	1	1	X
cana-4763	217	2	.	.	X
cana-4763	217	3	encircling	encircle	VERB
cana-4763	217	4	prey	prey	NOUN
cana-4763	217	5	2	2	NUM
cana-4763	217	6	.	.	PUNCT
cana-4763	217	7	hunting	hunt	VERB
cana-4763	217	8	3	3	NUM
cana-4763	217	9	.	.	PUNCT
cana-4763	217	10	attacking	attack	VERB
cana-4763	217	11	the	the	DET
cana-4763	217	12	prey	prey	NOUN
cana-4763	217	13	(	(	PUNCT
cana-4763	217	14	exploitation	exploitation	NOUN
cana-4763	217	15	)	)	PUNCT
cana-4763	217	16	4	4	NUM
cana-4763	217	17	.	.	X
cana-4763	217	18	diverging	diverge	VERB
cana-4763	217	19	for	for	ADP
cana-4763	217	20	exploration	exploration	NOUN
cana-4763	217	21	step	step	NOUN
cana-4763	217	22	1	1	NUM
cana-4763	217	23	:	:	PUNCT
cana-4763	217	24	encircling	encircle	VERB
cana-4763	217	25	prey	prey	ADJ
cana-4763	217	26	grey	grey	ADJ
cana-4763	217	27	wolves	wolf	NOUN
cana-4763	217	28	encircle	encircle	VERB
cana-4763	217	29	their	their	PRON
cana-4763	217	30	prey	prey	NOUN
cana-4763	217	31	using	use	VERB
cana-4763	217	32	the	the	DET
cana-4763	217	33	following	follow	VERB
cana-4763	217	34	equations	equation	NOUN
cana-4763	217	35	:	:	PUNCT
cana-4763	218	1	d	d	X
cana-4763	218	2	=	=	PUNCT
cana-4763	218	3	|	|	ADV
cana-4763	218	4	c.xprey	c.xprey	NOUN
cana-4763	218	5	-	-	PUNCT
cana-4763	218	6	x|	x|	NOUN
cana-4763	218	7	..	..	PUNCT
cana-4763	218	8	(	(	PUNCT
cana-4763	218	9	11	11	NUM
cana-4763	218	10	)	)	PUNCT
cana-4763	218	11	xnew	xnew	PROPN
cana-4763	219	1	=	=	SYM
cana-4763	219	2	xprey	xprey	PROPN
cana-4763	219	3	–	–	PUNCT
cana-4763	219	4	a.d	a.d	PROPN
cana-4763	219	5	..	..	PUNCT
cana-4763	219	6	(	(	PUNCT
cana-4763	219	7	12	12	NUM
cana-4763	219	8	)	)	PUNCT
cana-4763	220	1	where	where	SCONJ
cana-4763	220	2	:	:	PUNCT
cana-4763	220	3	xnew	xnew	PROPN
cana-4763	220	4	=	=	PUNCT
cana-4763	220	5	current	current	ADJ
cana-4763	220	6	position	position	NOUN
cana-4763	220	7	of	of	ADP
cana-4763	220	8	a	a	DET
cana-4763	220	9	wolf	wolf	NOUN
cana-4763	220	10	xprey	xprey	PROPN
cana-4763	221	1	=	=	X
cana-4763	222	1	best	good	ADJ
cana-4763	222	2	solution	solution	NOUN
cana-4763	222	3	found	find	VERB
cana-4763	222	4	so	so	ADV
cana-4763	222	5	far	far	ADV
cana-4763	222	6	a	a	PRON
cana-4763	222	7	,	,	PUNCT
cana-4763	222	8	c	c	NOUN
cana-4763	222	9	=	=	SYM
cana-4763	222	10	coefficient	coefficient	NOUN
cana-4763	222	11	vectors	vector	NOUN
cana-4763	222	12	d	d	NOUN
cana-4763	222	13	=	=	SYM
cana-4763	222	14	distance	distance	NOUN
cana-4763	222	15	between	between	ADP
cana-4763	222	16	the	the	DET
cana-4763	222	17	wolf	wolf	NOUN
cana-4763	222	18	and	and	CCONJ
cana-4763	222	19	the	the	DET
cana-4763	222	20	prey	prey	NOUN
cana-4763	222	21	the	the	DET
cana-4763	222	22	coefficient	coefficient	NOUN
cana-4763	222	23	vectors	vector	NOUN
cana-4763	222	24	are	be	AUX
cana-4763	222	25	defined	define	VERB
cana-4763	222	26	as	as	ADP
cana-4763	222	27	:	:	PUNCT
cana-4763	222	28	a=	a=	ADJ
cana-4763	222	29	2.a.r1	2.a.r1	NUM
cana-4763	222	30	-	-	SYM
cana-4763	222	31	a	a	PRON
cana-4763	222	32	..	..	PUNCT
cana-4763	222	33	(	(	PUNCT
cana-4763	222	34	13	13	NUM
cana-4763	222	35	)	)	PUNCT
cana-4763	222	36	c=2.r2	c=2.r2	X
cana-4763	222	37	..	..	PUNCT
cana-4763	222	38	(	(	PUNCT
cana-4763	222	39	14	14	NUM
cana-4763	222	40	)	)	PUNCT
cana-4763	222	41	where	where	SCONJ
cana-4763	222	42	:	:	PUNCT
cana-4763	222	43	a	a	DET
cana-4763	222	44	=	=	X
cana-4763	222	45	a	a	DET
cana-4763	222	46	linearly	linearly	ADV
cana-4763	222	47	decreasing	decrease	VERB
cana-4763	222	48	parameter	parameter	NOUN
cana-4763	222	49	from	from	ADP
cana-4763	222	50	2	2	NUM
cana-4763	222	51	to	to	ADP
cana-4763	222	52	0	0	NUM
cana-4763	222	53	r1,r2	r1,r2	PROPN
cana-4763	222	54	=	=	SYM
cana-4763	222	55	random	random	ADJ
cana-4763	222	56	numbers	number	NOUN
cana-4763	222	57	in	in	ADP
cana-4763	222	58	[	[	X
cana-4763	222	59	0,1	0,1	NUM
cana-4763	222	60	]	]	PUNCT
cana-4763	222	61	step	step	NOUN
cana-4763	222	62	2	2	NUM
cana-4763	222	63	:	:	PUNCT
cana-4763	222	64	hunting	hunt	VERB
cana-4763	222	65	mechanism	mechanism	NOUN
cana-4763	222	66	each	each	DET
cana-4763	222	67	wolf	wolf	PROPN
cana-4763	222	68	updates	update	VERB
cana-4763	222	69	its	its	PRON
cana-4763	222	70	position	position	NOUN
cana-4763	222	71	based	base	VERB
cana-4763	222	72	on	on	ADP
cana-4763	222	73	the	the	DET
cana-4763	222	74	positions	position	NOUN
cana-4763	222	75	of	of	ADP
cana-4763	222	76	the	the	DET
cana-4763	222	77	three	three	NUM
cana-4763	222	78	best	good	ADJ
cana-4763	222	79	wolves	wolf	NOUN
cana-4763	222	80	(	(	PUNCT
cana-4763	222	81	α	α	NOUN
cana-4763	222	82	,	,	PUNCT
cana-4763	222	83	β	β	X
cana-4763	222	84	,	,	PUNCT
cana-4763	222	85	δ	δ	PROPN
cana-4763	222	86	):	):	PUNCT
cana-4763	222	87	x1	x1	PROPN
cana-4763	222	88	=	=	PROPN
cana-4763	222	89	xα	xα	PROPN
cana-4763	222	90	–	–	PUNCT
cana-4763	222	91	aα	aα	NOUN
cana-4763	222	92	.	.	PUNCT
cana-4763	223	1	|cα	|cα	X
cana-4763	223	2	.	.	PUNCT
cana-4763	223	3	xα	xα	PROPN
cana-4763	223	4	-x|	-x|	PUNCT
cana-4763	223	5	…	…	PUNCT
cana-4763	223	6	(	(	PUNCT
cana-4763	223	7	15	15	NUM
cana-4763	223	8	)	)	PUNCT
cana-4763	223	9	x2	x2	PROPN
cana-4763	224	1	=	=	NOUN
cana-4763	224	2	xβ	xβ	PROPN
cana-4763	224	3	–	–	PUNCT
cana-4763	224	4	aβ	aβ	NOUN
cana-4763	224	5	.	.	PUNCT
cana-4763	225	1	|cβ	|cβ	X
cana-4763	225	2	.	.	PROPN
cana-4763	225	3	xβ	xβ	PROPN
cana-4763	225	4	-x|	-x|	PUNCT
cana-4763	225	5	…	…	PUNCT
cana-4763	225	6	(	(	PUNCT
cana-4763	225	7	16	16	NUM
cana-4763	225	8	)	)	PUNCT
cana-4763	225	9	x3	x3	PROPN
cana-4763	225	10	=	=	PROPN
cana-4763	225	11	xδ	xδ	PROPN
cana-4763	225	12	–	–	PUNCT
cana-4763	225	13	aδ	aδ	PROPN
cana-4763	225	14	.	.	PUNCT
cana-4763	226	1	|cδ	|cδ	PROPN
cana-4763	226	2	.	.	PROPN
cana-4763	226	3	xδ	xδ	PROPN
cana-4763	226	4	-x|	-x|	PUNCT
cana-4763	226	5	…	…	PUNCT
cana-4763	226	6	(	(	PUNCT
cana-4763	226	7	17	17	NUM
cana-4763	226	8	)	)	PUNCT
cana-4763	226	9	the	the	DET
cana-4763	226	10	final	final	ADJ
cana-4763	226	11	updated	update	VERB
cana-4763	226	12	position	position	NOUN
cana-4763	226	13	of	of	ADP
cana-4763	226	14	a	a	DET
cana-4763	226	15	wolf	wolf	NOUN
cana-4763	226	16	is	be	AUX
cana-4763	226	17	:	:	PUNCT
cana-4763	226	18	xnew=	xnew=	NUM
cana-4763	226	19	𝑋1+𝑋2+𝑋3	𝑋1+𝑋2+𝑋3	NOUN
cana-4763	226	20	3	3	NUM
cana-4763	226	21	..	..	PUNCT
cana-4763	226	22	(	(	PUNCT
cana-4763	226	23	18	18	NUM
cana-4763	226	24	)	)	PUNCT
cana-4763	226	25	step	step	NOUN
cana-4763	226	26	3	3	NUM
cana-4763	226	27	:	:	PUNCT
cana-4763	226	28	attacking	attack	VERB
cana-4763	226	29	and	and	CCONJ
cana-4763	226	30	converging	converge	VERB
cana-4763	226	31	the	the	DET
cana-4763	226	32	parameter	parameter	NOUN
cana-4763	226	33	α	α	PROPN
cana-4763	226	34	decreases	decrease	VERB
cana-4763	226	35	linearly	linearly	ADV
cana-4763	226	36	from	from	ADP
cana-4763	226	37	2	2	NUM
cana-4763	226	38	to	to	ADP
cana-4763	226	39	0	0	NUM
cana-4763	226	40	to	to	PART
cana-4763	226	41	balance	balance	VERB
cana-4763	226	42	exploration	exploration	NOUN
cana-4763	226	43	and	and	CCONJ
cana-4763	226	44	exploitation	exploitation	NOUN
cana-4763	226	45	:	:	PUNCT
cana-4763	226	46	α=22𝑡	α=22𝑡	NUM
cana-4763	226	47	𝑇	𝑇	PROPN
cana-4763	226	48	…	…	PUNCT
cana-4763	226	49	(	(	PUNCT
cana-4763	226	50	19	19	NUM
cana-4763	226	51	)	)	PUNCT
cana-4763	226	52	where	where	SCONJ
cana-4763	226	53	t	t	PROPN
cana-4763	226	54	is	be	AUX
cana-4763	226	55	the	the	DET
cana-4763	226	56	maximum	maximum	ADJ
cana-4763	226	57	number	number	NOUN
cana-4763	226	58	of	of	ADP
cana-4763	226	59	iterations	iteration	NOUN
cana-4763	226	60	.	.	PUNCT
cana-4763	227	1	⚫	⚫	VERB
cana-4763	227	2	when	when	SCONJ
cana-4763	227	3	|a|	|a|	PROPN
cana-4763	227	4	<	<	X
cana-4763	227	5	1	1	NUM
cana-4763	227	6	,	,	PUNCT
cana-4763	227	7	the	the	DET
cana-4763	227	8	wolves	wolf	NOUN
cana-4763	227	9	converge	converge	VERB
cana-4763	227	10	toward	toward	ADP
cana-4763	227	11	the	the	DET
cana-4763	227	12	best	good	ADJ
cana-4763	227	13	solution	solution	NOUN
cana-4763	227	14	.	.	PUNCT
cana-4763	228	1	⚫	⚫	NOUN
cana-4763	228	2	when	when	SCONJ
cana-4763	228	3	|a|	|a|	PROPN
cana-4763	228	4	>	>	X
cana-4763	228	5	1	1	NUM
cana-4763	228	6	,	,	PUNCT
cana-4763	228	7	the	the	DET
cana-4763	228	8	wolves	wolf	NOUN
cana-4763	228	9	explore	explore	VERB
cana-4763	228	10	new	new	ADJ
cana-4763	228	11	areas	area	NOUN
cana-4763	228	12	in	in	ADP
cana-4763	228	13	the	the	DET
cana-4763	228	14	search	search	NOUN
cana-4763	228	15	space	space	NOUN
cana-4763	228	16	.	.	PUNCT
cana-4763	229	1	communications	communication	NOUN
cana-4763	229	2	on	on	ADP
cana-4763	229	3	applied	apply	VERB
cana-4763	229	4	nonlinear	nonlinear	ADJ
cana-4763	229	5	analysis	analysis	NOUN
cana-4763	229	6	issn	issn	NOUN
cana-4763	229	7	:	:	PUNCT
cana-4763	229	8	1074	1074	NUM
cana-4763	229	9	-	-	PUNCT
cana-4763	229	10	133x	133x	NUM
cana-4763	229	11	vol	vol	VERB
cana-4763	229	12	32	32	NUM
cana-4763	229	13	no	no	NOUN
cana-4763	229	14	.	.	PUNCT
cana-4763	230	1	10s	10	NOUN
cana-4763	230	2	(	(	PUNCT
cana-4763	230	3	2025	2025	NUM
cana-4763	230	4	)	)	PUNCT
cana-4763	230	5	304	304	NUM
cana-4763	230	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	230	7	applying	apply	VERB
cana-4763	230	8	gwo	gwo	NOUN
cana-4763	230	9	for	for	ADP
cana-4763	230	10	brain	brain	NOUN
cana-4763	230	11	tumor	tumor	NOUN
cana-4763	230	12	classification	classification	NOUN
cana-4763	230	13	step	step	NOUN
cana-4763	230	14	1	1	NUM
cana-4763	230	15	:	:	PUNCT
cana-4763	230	16	feature	feature	NOUN
cana-4763	230	17	extraction	extraction	NOUN
cana-4763	230	18	we	we	PRON
cana-4763	230	19	extract	extract	VERB
cana-4763	230	20	texture	texture	NOUN
cana-4763	230	21	features	feature	NOUN
cana-4763	230	22	such	such	ADJ
cana-4763	230	23	as	as	ADP
cana-4763	230	24	energy	energy	NOUN
cana-4763	230	25	,	,	PUNCT
cana-4763	230	26	entropy	entropy	PROPN
cana-4763	230	27	,	,	PUNCT
cana-4763	230	28	contrast	contrast	NOUN
cana-4763	230	29	,	,	PUNCT
cana-4763	230	30	correlation	correlation	NOUN
cana-4763	230	31	,	,	PUNCT
cana-4763	230	32	and	and	CCONJ
cana-4763	230	33	homogeneity	homogeneity	NOUN
cana-4763	230	34	from	from	ADP
cana-4763	230	35	mri	mri	NOUN
cana-4763	230	36	images	image	NOUN
cana-4763	230	37	using	use	VERB
cana-4763	230	38	lbp	lbp	PROPN
cana-4763	230	39	histograms	histogram	NOUN
cana-4763	230	40	.	.	PUNCT
cana-4763	231	1	the	the	DET
cana-4763	231	2	feature	feature	NOUN
cana-4763	231	3	vector	vector	NOUN
cana-4763	231	4	is	be	AUX
cana-4763	231	5	represented	represent	VERB
cana-4763	231	6	as	as	ADP
cana-4763	231	7	:	:	PUNCT
cana-4763	231	8	feature	feature	NOUN
cana-4763	231	9	vector	vector	NOUN
cana-4763	231	10	=	=	PUNCT
cana-4763	232	1	[	[	X
cana-4763	232	2	energy	energy	NOUN
cana-4763	232	3	,	,	PUNCT
cana-4763	232	4	entropy	entropy	PROPN
cana-4763	232	5	,	,	PUNCT
cana-4763	232	6	contrast	contrast	NOUN
cana-4763	232	7	,	,	PUNCT
cana-4763	232	8	correlation	correlation	NOUN
cana-4763	232	9	,	,	PUNCT
cana-4763	232	10	homogeneity	homogeneity	NOUN
cana-4763	232	11	]	]	PUNCT
cana-4763	232	12	step	step	NOUN
cana-4763	232	13	2	2	NUM
cana-4763	232	14	:	:	PUNCT
cana-4763	232	15	optimization	optimization	NOUN
cana-4763	232	16	with	with	ADP
cana-4763	232	17	gwo	gwo	PROPN
cana-4763	232	18	gwo	gwo	PROPN
cana-4763	232	19	is	be	AUX
cana-4763	232	20	employed	employ	VERB
cana-4763	232	21	to	to	PART
cana-4763	232	22	select	select	VERB
cana-4763	232	23	the	the	DET
cana-4763	232	24	optimal	optimal	ADJ
cana-4763	232	25	subset	subset	NOUN
cana-4763	232	26	of	of	ADP
cana-4763	232	27	features	feature	NOUN
cana-4763	232	28	or	or	CCONJ
cana-4763	232	29	fine	fine	ADJ
cana-4763	232	30	-	-	PUNCT
cana-4763	232	31	tune	tune	NOUN
cana-4763	232	32	the	the	DET
cana-4763	232	33	hyperparameters	hyperparameter	NOUN
cana-4763	232	34	of	of	ADP
cana-4763	232	35	classifiers	classifier	NOUN
cana-4763	232	36	.	.	PUNCT
cana-4763	233	1	objective	objective	ADJ
cana-4763	233	2	function	function	NOUN
cana-4763	233	3	(	(	PUNCT
cana-4763	233	4	fitness	fitness	NOUN
cana-4763	233	5	):	):	PUNCT
cana-4763	233	6	to	to	PART
cana-4763	233	7	evaluate	evaluate	VERB
cana-4763	233	8	the	the	DET
cana-4763	233	9	fitness	fitness	NOUN
cana-4763	233	10	of	of	ADP
cana-4763	233	11	a	a	DET
cana-4763	233	12	solution	solution	NOUN
cana-4763	233	13	x	x	X
cana-4763	233	14	,	,	PUNCT
cana-4763	233	15	we	we	PRON
cana-4763	233	16	use	use	VERB
cana-4763	233	17	classification	classification	NOUN
cana-4763	233	18	accuracy	accuracy	NOUN
cana-4763	233	19	:	:	PUNCT
cana-4763	234	1	f(x)=	f(x)=	X
cana-4763	234	2	𝐶𝑜𝑟𝑟𝑒𝑐𝑡𝑙𝑦	𝐶𝑜𝑟𝑟𝑒𝑐𝑡𝑙𝑦	PROPN
cana-4763	234	3	𝑐𝑙𝑎𝑠𝑠𝑖𝑓𝑖𝑒𝑑	𝑐𝑙𝑎𝑠𝑠𝑖𝑓𝑖𝑒𝑑	NOUN
cana-4763	234	4	𝑆𝑎𝑚𝑝𝑙𝑒𝑠	𝑆𝑎𝑚𝑝𝑙𝑒𝑠	PROPN
cana-4763	234	5	𝑇𝑜𝑡𝑎𝑙	𝑇𝑜𝑡𝑎𝑙	PRON
cana-4763	234	6	𝑆𝑎𝑚𝑝𝑙𝑒𝑠	𝑆𝑎𝑚𝑝𝑙𝑒𝑠	PROPN
cana-4763	234	7	..	..	PUNCT
cana-4763	234	8	(	(	PUNCT
cana-4763	234	9	20	20	NUM
cana-4763	234	10	)	)	PUNCT
cana-4763	234	11	algorithm	algorithm	NOUN
cana-4763	234	12	steps	step	NOUN
cana-4763	234	13	:	:	PUNCT
cana-4763	234	14	1	1	X
cana-4763	234	15	.	.	X
cana-4763	234	16	initialize	initialize	VERB
cana-4763	234	17	the	the	DET
cana-4763	234	18	wolf	wolf	PROPN
cana-4763	234	19	population	population	NOUN
cana-4763	234	20	randomly	randomly	ADV
cana-4763	234	21	in	in	ADP
cana-4763	234	22	the	the	DET
cana-4763	234	23	feature	feature	NOUN
cana-4763	234	24	space	space	NOUN
cana-4763	234	25	.	.	PUNCT
cana-4763	235	1	2	2	X
cana-4763	235	2	.	.	X
cana-4763	235	3	calculate	calculate	VERB
cana-4763	235	4	the	the	DET
cana-4763	235	5	fitness	fitness	NOUN
cana-4763	235	6	(	(	PUNCT
cana-4763	235	7	classification	classification	NOUN
cana-4763	235	8	accuracy	accuracy	NOUN
cana-4763	235	9	)	)	PUNCT
cana-4763	235	10	for	for	ADP
cana-4763	235	11	each	each	DET
cana-4763	235	12	wolf	wolf	NOUN
cana-4763	235	13	.	.	PUNCT
cana-4763	236	1	3	3	X
cana-4763	236	2	.	.	X
cana-4763	236	3	update	update	VERB
cana-4763	236	4	the	the	DET
cana-4763	236	5	positions	position	NOUN
cana-4763	236	6	of	of	ADP
cana-4763	236	7	the	the	DET
cana-4763	236	8	wolves	wolf	NOUN
cana-4763	236	9	(	(	PUNCT
cana-4763	236	10	α	α	NOUN
cana-4763	236	11	,	,	PUNCT
cana-4763	236	12	β	β	X
cana-4763	236	13	,	,	PUNCT
cana-4763	236	14	δ	δ	PROPN
cana-4763	236	15	)	)	PUNCT
cana-4763	236	16	using	use	VERB
cana-4763	236	17	the	the	DET
cana-4763	236	18	defined	define	VERB
cana-4763	236	19	equations	equation	NOUN
cana-4763	236	20	.	.	PUNCT
cana-4763	237	1	4	4	X
cana-4763	237	2	.	.	X
cana-4763	237	3	dynamically	dynamically	ADV
cana-4763	237	4	update	update	VERB
cana-4763	237	5	the	the	DET
cana-4763	237	6	parameters	parameter	NOUN
cana-4763	237	7	a	a	PRON
cana-4763	237	8	,	,	PUNCT
cana-4763	237	9	ca	ca	NOUN
cana-4763	237	10	,	,	PUNCT
cana-4763	237	11	ca	can	AUX
cana-4763	237	12	,	,	PUNCT
cana-4763	237	13	c	c	PROPN
cana-4763	237	14	5	5	NUM
cana-4763	237	15	.	.	X
cana-4763	237	16	continue	continue	VERB
cana-4763	237	17	the	the	DET
cana-4763	237	18	process	process	NOUN
cana-4763	237	19	until	until	SCONJ
cana-4763	237	20	convergence	convergence	NOUN
cana-4763	237	21	or	or	CCONJ
cana-4763	237	22	the	the	DET
cana-4763	237	23	maximum	maximum	ADJ
cana-4763	237	24	number	number	NOUN
cana-4763	237	25	of	of	ADP
cana-4763	237	26	trials	trial	NOUN
cana-4763	237	27	is	be	AUX
cana-4763	237	28	achieved	achieve	VERB
cana-4763	237	29	.	.	PUNCT
cana-4763	238	1	6	6	X
cana-4763	238	2	.	.	X
cana-4763	238	3	return	return	VERB
cana-4763	238	4	the	the	DET
cana-4763	238	5	best	good	ADJ
cana-4763	238	6	solution	solution	NOUN
cana-4763	238	7	(	(	PUNCT
cana-4763	238	8	optimal	optimal	ADJ
cana-4763	238	9	hyperparameters	hyperparameter	NOUN
cana-4763	238	10	or	or	CCONJ
cana-4763	238	11	feature	feature	NOUN
cana-4763	238	12	subset	subset	NOUN
cana-4763	238	13	)	)	PUNCT
cana-4763	238	14	.	.	PUNCT
cana-4763	239	1	the	the	DET
cana-4763	239	2	improved	improved	ADJ
cana-4763	239	3	characteristics	characteristic	NOUN
cana-4763	239	4	resulting	result	VERB
cana-4763	239	5	from	from	ADP
cana-4763	239	6	optimization	optimization	NOUN
cana-4763	239	7	enable	enable	VERB
cana-4763	239	8	more	more	ADJ
cana-4763	239	9	efficient	efficient	ADJ
cana-4763	239	10	classification	classification	NOUN
cana-4763	239	11	operations	operation	NOUN
cana-4763	239	12	that	that	PRON
cana-4763	239	13	enhance	enhance	VERB
cana-4763	239	14	the	the	DET
cana-4763	239	15	overall	overall	ADJ
cana-4763	239	16	performance	performance	NOUN
cana-4763	239	17	of	of	ADP
cana-4763	239	18	brain	brain	NOUN
cana-4763	239	19	tumour	tumour	NOUN
cana-4763	239	20	detection	detection	NOUN
cana-4763	239	21	systems	system	NOUN
cana-4763	239	22	.	.	PUNCT
cana-4763	240	1	3.4	3.4	NUM
cana-4763	240	2	classification	classification	NOUN
cana-4763	240	3	the	the	DET
cana-4763	240	4	extracted	extract	VERB
cana-4763	240	5	features	feature	NOUN
cana-4763	240	6	that	that	PRON
cana-4763	240	7	result	result	VERB
cana-4763	240	8	from	from	ADP
cana-4763	240	9	grey	grey	PROPN
cana-4763	240	10	wolf	wolf	PROPN
cana-4763	240	11	optimization	optimization	NOUN
cana-4763	240	12	move	move	VERB
cana-4763	240	13	forward	forward	ADV
cana-4763	240	14	to	to	ADP
cana-4763	240	15	the	the	DET
cana-4763	240	16	classifier	classifier	NOUN
cana-4763	240	17	module	module	NOUN
cana-4763	240	18	for	for	ADP
cana-4763	240	19	additional	additional	ADJ
cana-4763	240	20	processing	processing	NOUN
cana-4763	240	21	.	.	PUNCT
cana-4763	241	1	3.4.1	3.4.1	NUM
cana-4763	241	2	random	random	ADJ
cana-4763	241	3	forest	forest	NOUN
cana-4763	241	4	(	(	PUNCT
cana-4763	241	5	rf	rf	NOUN
cana-4763	241	6	)	)	PUNCT
cana-4763	241	7	classifier	classifier	NOUN
cana-4763	241	8	random	random	ADJ
cana-4763	241	9	forest	forest	NOUN
cana-4763	241	10	(	(	PUNCT
cana-4763	241	11	rf	rf	NOUN
cana-4763	241	12	)	)	PUNCT
cana-4763	241	13	ensemble	ensemble	ADJ
cana-4763	241	14	learning	learning	NOUN
cana-4763	241	15	method	method	NOUN
cana-4763	241	16	constructs	construct	VERB
cana-4763	241	17	many	many	ADJ
cana-4763	241	18	decision	decision	NOUN
cana-4763	241	19	trees	tree	NOUN
cana-4763	241	20	during	during	ADP
cana-4763	241	21	training	training	NOUN
cana-4763	241	22	and	and	CCONJ
cana-4763	241	23	produces	produce	VERB
cana-4763	241	24	the	the	DET
cana-4763	241	25	class	class	NOUN
cana-4763	241	26	with	with	ADP
cana-4763	241	27	the	the	DET
cana-4763	241	28	most	most	ADJ
cana-4763	241	29	votes	vote	NOUN
cana-4763	241	30	from	from	ADP
cana-4763	241	31	each	each	DET
cana-4763	241	32	tree	tree	NOUN
cana-4763	241	33	.	.	PUNCT
cana-4763	242	1	classification	classification	NOUN
cana-4763	242	2	problems	problem	NOUN
cana-4763	242	3	are	be	AUX
cana-4763	242	4	well	well	ADV
cana-4763	242	5	addressed	address	VERB
cana-4763	242	6	with	with	ADP
cana-4763	242	7	this	this	DET
cana-4763	242	8	non	non	ADJ
cana-4763	242	9	-	-	ADJ
cana-4763	242	10	parametric	parametric	ADJ
cana-4763	242	11	approach	approach	NOUN
cana-4763	242	12	.	.	PUNCT
cana-4763	243	1	for	for	ADP
cana-4763	243	2	the	the	DET
cana-4763	243	3	rf	rf	NOUN
cana-4763	243	4	classifier	classifier	NOUN
cana-4763	243	5	,	,	PUNCT
cana-4763	243	6	m	m	VERB
cana-4763	243	7	decision	decision	NOUN
cana-4763	243	8	trees	tree	NOUN
cana-4763	243	9	are	be	AUX
cana-4763	243	10	utilized	utilize	VERB
cana-4763	243	11	.	.	PUNCT
cana-4763	244	1	every	every	DET
cana-4763	244	2	node	node	NOUN
cana-4763	244	3	chooses	choose	VERB
cana-4763	244	4	a	a	DET
cana-4763	244	5	random	random	ADJ
cana-4763	244	6	subset	subset	NOUN
cana-4763	244	7	of	of	ADP
cana-4763	244	8	the	the	DET
cana-4763	244	9	attributes	attribute	NOUN
cana-4763	244	10	for	for	ADP
cana-4763	244	11	splitting	splitting	NOUN
cana-4763	244	12	,	,	PUNCT
cana-4763	244	13	and	and	CCONJ
cana-4763	244	14	each	each	DET
cana-4763	244	15	tree	tree	NOUN
cana-4763	244	16	's	's	PART
cana-4763	244	17	training	training	NOUN
cana-4763	244	18	data	datum	NOUN
cana-4763	244	19	is	be	AUX
cana-4763	244	20	randomly	randomly	ADV
cana-4763	244	21	sampled	sample	VERB
cana-4763	244	22	with	with	ADP
cana-4763	244	23	replacement	replacement	NOUN
cana-4763	244	24	.	.	PUNCT
cana-4763	245	1	the	the	DET
cana-4763	245	2	output	output	NOUN
cana-4763	245	3	of	of	ADP
cana-4763	245	4	each	each	DET
cana-4763	245	5	tree	tree	NOUN
cana-4763	245	6	is	be	AUX
cana-4763	245	7	added	add	VERB
cana-4763	245	8	together	together	ADV
cana-4763	245	9	,	,	PUNCT
cana-4763	245	10	usually	usually	ADV
cana-4763	245	11	by	by	ADP
cana-4763	245	12	voting	vote	VERB
cana-4763	245	13	for	for	ADP
cana-4763	245	14	the	the	DET
cana-4763	245	15	majority	majority	NOUN
cana-4763	245	16	,	,	PUNCT
cana-4763	245	17	to	to	PART
cana-4763	245	18	assign	assign	VERB
cana-4763	245	19	the	the	DET
cana-4763	245	20	final	final	ADJ
cana-4763	245	21	categorization	categorization	NOUN
cana-4763	245	22	response	response	NOUN
cana-4763	245	23	.	.	PUNCT
cana-4763	246	1	each	each	DET
cana-4763	246	2	decision	decision	NOUN
cana-4763	246	3	tree	tree	NOUN
cana-4763	246	4	is	be	AUX
cana-4763	246	5	built	build	VERB
cana-4763	246	6	sequentially	sequentially	ADV
cana-4763	246	7	by	by	ADP
cana-4763	246	8	applying	apply	VERB
cana-4763	246	9	an	an	DET
cana-4763	246	10	input	input	NOUN
cana-4763	246	11	criterion	criterion	NOUN
cana-4763	246	12	,	,	PUNCT
cana-4763	246	13	such	such	ADJ
cana-4763	246	14	as	as	ADP
cana-4763	246	15	the	the	DET
cana-4763	246	16	gini	gini	PROPN
cana-4763	246	17	index	index	NOUN
cana-4763	246	18	or	or	CCONJ
cana-4763	246	19	entropy	entropy	NOUN
cana-4763	246	20	,	,	PUNCT
cana-4763	246	21	to	to	PART
cana-4763	246	22	specify	specify	VERB
cana-4763	246	23	the	the	DET
cana-4763	246	24	best	good	ADJ
cana-4763	246	25	split	split	NOUN
cana-4763	246	26	of	of	ADP
cana-4763	246	27	each	each	DET
cana-4763	246	28	node	node	NOUN
cana-4763	246	29	.	.	PUNCT
cana-4763	247	1	the	the	DET
cana-4763	247	2	gini	gini	PROPN
cana-4763	247	3	index	index	NOUN
cana-4763	247	4	for	for	ADP
cana-4763	247	5	a	a	DET
cana-4763	247	6	node	node	PROPN
cana-4763	247	7	t	t	PROPN
cana-4763	247	8	is	be	AUX
cana-4763	247	9	defined	define	VERB
cana-4763	247	10	as	as	ADP
cana-4763	247	11	:	:	PUNCT
cana-4763	247	12	gini(t	gini(t	NOUN
cana-4763	247	13	)	)	PUNCT
cana-4763	247	14	=	=	SYM
cana-4763	247	15	1	1	NUM
cana-4763	247	16	∑	∑	ADP
cana-4763	247	17	pi	pi	PROPN
cana-4763	247	18	2c	2c	NOUN
cana-4763	247	19	i=1	i=1	PROPN
cana-4763	247	20	..	..	PUNCT
cana-4763	247	21	(	(	PUNCT
cana-4763	247	22	21	21	NUM
cana-4763	247	23	)	)	PUNCT
cana-4763	247	24	where	where	SCONJ
cana-4763	247	25	pi	pi	NOUN
cana-4763	247	26	is	be	AUX
cana-4763	247	27	the	the	DET
cana-4763	247	28	probability	probability	NOUN
cana-4763	247	29	of	of	ADP
cana-4763	247	30	class	class	NOUN
cana-4763	247	31	i	i	PROPN
cana-4763	247	32	at	at	ADP
cana-4763	247	33	node	node	NOUN
cana-4763	247	34	t.	t.	PROPN
cana-4763	247	35	the	the	DET
cana-4763	247	36	random	random	ADJ
cana-4763	247	37	forest	forest	NOUN
cana-4763	247	38	(	(	PUNCT
cana-4763	247	39	rf	rf	NOUN
cana-4763	247	40	)	)	PUNCT
cana-4763	247	41	classifier	classifier	NOUN
cana-4763	247	42	combines	combine	VERB
cana-4763	247	43	the	the	DET
cana-4763	247	44	results	result	NOUN
cana-4763	247	45	from	from	ADP
cana-4763	247	46	all	all	DET
cana-4763	247	47	the	the	DET
cana-4763	247	48	individual	individual	ADJ
cana-4763	247	49	decision	decision	NOUN
cana-4763	247	50	trees	tree	NOUN
cana-4763	247	51	.	.	PUNCT
cana-4763	248	1	if	if	SCONJ
cana-4763	248	2	the	the	DET
cana-4763	248	3	decision	decision	NOUN
cana-4763	248	4	trees	tree	NOUN
cana-4763	248	5	t1	t1	VERB
cana-4763	248	6	,	,	PUNCT
cana-4763	248	7	t2	t2	NOUN
cana-4763	248	8	…	…	PUNCT
cana-4763	248	9	,tm	,tm	PUNCT
cana-4763	248	10	produce	produce	VERB
cana-4763	248	11	class	class	NOUN
cana-4763	248	12	labels	label	NOUN
cana-4763	248	13	y1,y2	y1,y2	PROPN
cana-4763	248	14	,	,	PUNCT
cana-4763	248	15	…	…	PUNCT
cana-4763	248	16	,	,	PUNCT
cana-4763	248	17	ym	ym	PROPN
cana-4763	248	18	,	,	PUNCT
cana-4763	248	19	the	the	DET
cana-4763	248	20	final	final	ADJ
cana-4763	248	21	prediction	prediction	NOUN
cana-4763	248	22	is	be	AUX
cana-4763	248	23	determined	determine	VERB
cana-4763	248	24	by	by	ADP
cana-4763	248	25	taking	take	VERB
cana-4763	248	26	the	the	DET
cana-4763	248	27	majority	majority	NOUN
cana-4763	248	28	vote	vote	NOUN
cana-4763	248	29	:	:	PUNCT
cana-4763	248	30	final	final	ADJ
cana-4763	248	31	prediction	prediction	NOUN
cana-4763	248	32	=	=	SYM
cana-4763	248	33	mode	mode	NOUN
cana-4763	248	34	(	(	PUNCT
cana-4763	248	35	y1,y2	y1,y2	PROPN
cana-4763	248	36	,	,	PUNCT
cana-4763	248	37	…	…	PUNCT
cana-4763	248	38	,	,	PUNCT
cana-4763	248	39	ym	ym	PROPN
cana-4763	248	40	)	)	PUNCT
cana-4763	248	41	..	..	PUNCT
cana-4763	249	1	(	(	PUNCT
cana-4763	249	2	22	22	X
cana-4763	249	3	)	)	PUNCT
cana-4763	249	4	3.4.2	3.4.2	NUM
cana-4763	249	5	support	support	NOUN
cana-4763	249	6	vector	vector	NOUN
cana-4763	249	7	machine	machine	NOUN
cana-4763	249	8	(	(	PUNCT
cana-4763	249	9	svm	svm	ADJ
cana-4763	249	10	)	)	PUNCT
cana-4763	249	11	classifier	classifier	NOUN
cana-4763	249	12	the	the	DET
cana-4763	249	13	support	support	NOUN
cana-4763	249	14	vector	vector	NOUN
cana-4763	249	15	machine	machine	NOUN
cana-4763	249	16	(	(	PUNCT
cana-4763	249	17	svm	svm	PROPN
cana-4763	249	18	)	)	PUNCT
cana-4763	249	19	is	be	AUX
cana-4763	249	20	a	a	DET
cana-4763	249	21	supervised	supervised	ADJ
cana-4763	249	22	machine	machine	NOUN
cana-4763	249	23	learning	learning	NOUN
cana-4763	249	24	model	model	NOUN
cana-4763	249	25	which	which	PRON
cana-4763	249	26	employs	employ	VERB
cana-4763	249	27	the	the	DET
cana-4763	249	28	optimal	optimal	ADJ
cana-4763	249	29	hyperplane	hyperplane	NOUN
cana-4763	249	30	to	to	PART
cana-4763	249	31	classify	classify	VERB
cana-4763	249	32	data	datum	NOUN
cana-4763	249	33	points	point	NOUN
cana-4763	249	34	.	.	PUNCT
cana-4763	250	1	the	the	DET
cana-4763	250	2	key	key	ADJ
cana-4763	250	3	goal	goal	NOUN
cana-4763	250	4	is	be	AUX
cana-4763	250	5	to	to	PART
cana-4763	250	6	improve	improve	VERB
cana-4763	250	7	the	the	DET
cana-4763	250	8	model	model	NOUN
cana-4763	250	9	's	's	PART
cana-4763	250	10	capacity	capacity	NOUN
cana-4763	250	11	to	to	PART
cana-4763	250	12	generalize	generalize	VERB
cana-4763	250	13	and	and	CCONJ
cana-4763	250	14	predict	predict	VERB
cana-4763	250	15	new	new	ADJ
cana-4763	250	16	data	datum	NOUN
cana-4763	250	17	by	by	ADP
cana-4763	250	18	increasing	increase	VERB
cana-4763	250	19	the	the	DET
cana-4763	250	20	difference	difference	NOUN
cana-4763	250	21	between	between	ADP
cana-4763	250	22	these	these	DET
cana-4763	250	23	categories	category	NOUN
cana-4763	250	24	.	.	PUNCT
cana-4763	251	1	because	because	SCONJ
cana-4763	251	2	of	of	ADP
cana-4763	251	3	this	this	DET
cana-4763	251	4	characteristic	characteristic	NOUN
cana-4763	251	5	,	,	PUNCT
cana-4763	251	6	svm	svm	PROPN
cana-4763	251	7	performs	perform	VERB
cana-4763	251	8	especially	especially	ADV
cana-4763	251	9	well	well	ADV
cana-4763	251	10	in	in	ADP
cana-4763	251	11	high	high	ADJ
cana-4763	251	12	-	-	PUNCT
cana-4763	251	13	dimensional	dimensional	ADJ
cana-4763	251	14	spaces	space	NOUN
cana-4763	251	15	,	,	PUNCT
cana-4763	251	16	where	where	SCONJ
cana-4763	251	17	more	more	ADV
cana-4763	251	18	traditional	traditional	ADJ
cana-4763	251	19	algorithms	algorithm	NOUN
cana-4763	251	20	could	could	AUX
cana-4763	251	21	struggle	struggle	VERB
cana-4763	251	22	.	.	PUNCT
cana-4763	252	1	communications	communication	NOUN
cana-4763	252	2	on	on	ADP
cana-4763	252	3	applied	apply	VERB
cana-4763	252	4	nonlinear	nonlinear	ADJ
cana-4763	252	5	analysis	analysis	NOUN
cana-4763	252	6	issn	issn	NOUN
cana-4763	252	7	:	:	PUNCT
cana-4763	252	8	1074	1074	NUM
cana-4763	252	9	-	-	PUNCT
cana-4763	252	10	133x	133x	NUM
cana-4763	252	11	vol	vol	VERB
cana-4763	252	12	32	32	NUM
cana-4763	252	13	no	no	NOUN
cana-4763	252	14	.	.	PUNCT
cana-4763	253	1	10s	10	NOUN
cana-4763	253	2	(	(	PUNCT
cana-4763	253	3	2025	2025	NUM
cana-4763	253	4	)	)	PUNCT
cana-4763	253	5	305	305	NUM
cana-4763	253	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	253	7	given	give	VERB
cana-4763	253	8	a	a	DET
cana-4763	253	9	training	training	NOUN
cana-4763	253	10	set	set	NOUN
cana-4763	253	11	of	of	ADP
cana-4763	253	12	n	n	NOUN
cana-4763	253	13	data	data	NOUN
cana-4763	253	14	points	point	NOUN
cana-4763	253	15	{	{	PUNCT
cana-4763	253	16	(	(	PUNCT
cana-4763	253	17	𝑥𝑖	𝑥𝑖	PROPN
cana-4763	253	18	,	,	PUNCT
cana-4763	253	19	𝑦𝑖)}𝑖=1	𝑦𝑖)}𝑖=1	VERB
cana-4763	253	20	𝑁	𝑁	PROPN
cana-4763	253	21	where	where	SCONJ
cana-4763	253	22	𝑥𝑖	𝑥𝑖	PROPN
cana-4763	253	23	ε	ε	PROPN
cana-4763	253	24	rd	rd	PROPN
cana-4763	253	25	and	and	CCONJ
cana-4763	253	26	yi	yi	PROPN
cana-4763	253	27	ε{-1,1	ε{-1,1	NOUN
cana-4763	253	28	}	}	PUNCT
cana-4763	253	29	,	,	PUNCT
cana-4763	253	30	the	the	DET
cana-4763	253	31	svm	svm	PROPN
cana-4763	253	32	finds	find	VERB
cana-4763	253	33	the	the	DET
cana-4763	253	34	hyperplane	hyperplane	NOUN
cana-4763	253	35	that	that	PRON
cana-4763	253	36	optimizes	optimize	VERB
cana-4763	253	37	the	the	DET
cana-4763	253	38	margin	margin	NOUN
cana-4763	253	39	between	between	ADP
cana-4763	253	40	the	the	DET
cana-4763	253	41	two	two	NUM
cana-4763	253	42	classes	class	NOUN
cana-4763	253	43	.	.	PUNCT
cana-4763	254	1	the	the	DET
cana-4763	254	2	equation	equation	NOUN
cana-4763	254	3	of	of	ADP
cana-4763	254	4	the	the	DET
cana-4763	254	5	hyperplane	hyperplane	NOUN
cana-4763	254	6	is	be	AUX
cana-4763	254	7	:	:	PUNCT
cana-4763	254	8	wtx+b=0	wtx+b=0	PROPN
cana-4763	254	9	..	..	PUNCT
cana-4763	254	10	(	(	PUNCT
cana-4763	254	11	23	23	NUM
cana-4763	254	12	)	)	PUNCT
cana-4763	254	13	where	where	SCONJ
cana-4763	254	14	:	:	PUNCT
cana-4763	254	15	•	•	X
cana-4763	254	16	w	w	NOUN
cana-4763	254	17	is	be	AUX
cana-4763	254	18	the	the	DET
cana-4763	254	19	normal	normal	ADJ
cana-4763	254	20	vector	vector	NOUN
cana-4763	254	21	to	to	ADP
cana-4763	254	22	the	the	DET
cana-4763	254	23	hyperplane	hyperplane	NOUN
cana-4763	254	24	,	,	PUNCT
cana-4763	254	25	•	•	PROPN
cana-4763	254	26	b	b	PROPN
cana-4763	254	27	is	be	AUX
cana-4763	254	28	the	the	DET
cana-4763	254	29	bias	bias	NOUN
cana-4763	254	30	term	term	NOUN
cana-4763	254	31	.	.	PUNCT
cana-4763	255	1	the	the	DET
cana-4763	255	2	margin	margin	NOUN
cana-4763	255	3	r	r	NOUN
cana-4763	255	4	is	be	AUX
cana-4763	255	5	given	give	VERB
cana-4763	255	6	by	by	ADP
cana-4763	255	7	:	:	PUNCT
cana-4763	255	8	r=	r=	ADJ
cana-4763	255	9	2	2	NUM
cana-4763	255	10	||𝑤||	||𝑤||	NOUN
cana-4763	255	11	..	..	PUNCT
cana-4763	255	12	(	(	PUNCT
cana-4763	255	13	24	24	NUM
cana-4763	255	14	)	)	PUNCT
cana-4763	255	15	the	the	DET
cana-4763	255	16	svm	svm	PROPN
cana-4763	255	17	aims	aim	VERB
cana-4763	255	18	to	to	PART
cana-4763	255	19	minimize	minimize	VERB
cana-4763	255	20	the	the	DET
cana-4763	255	21	following	follow	VERB
cana-4763	255	22	objective	objective	ADJ
cana-4763	255	23	function	function	NOUN
cana-4763	255	24	:	:	PUNCT
cana-4763	255	25	min	min	NOUN
cana-4763	255	26	1	1	NUM
cana-4763	255	27	2	2	NUM
cana-4763	255	28	‖w‖2	‖w‖2	NOUN
cana-4763	255	29	..	..	PUNCT
cana-4763	255	30	(	(	PUNCT
cana-4763	255	31	25	25	NUM
cana-4763	255	32	)	)	PUNCT
cana-4763	255	33	subject	subject	NOUN
cana-4763	255	34	to	to	ADP
cana-4763	255	35	:	:	PUNCT
cana-4763	255	36	yi(wtxi+b)≥1	yi(wtxi+b)≥1	NOUN
cana-4763	255	37	..	..	PUNCT
cana-4763	255	38	(	(	PUNCT
cana-4763	255	39	26	26	NUM
cana-4763	255	40	)	)	PUNCT
cana-4763	255	41	in	in	ADP
cana-4763	255	42	order	order	NOUN
cana-4763	255	43	to	to	PART
cana-4763	255	44	make	make	VERB
cana-4763	255	45	linear	linear	ADJ
cana-4763	255	46	separation	separation	NOUN
cana-4763	255	47	possible	possible	ADJ
cana-4763	255	48	for	for	ADP
cana-4763	255	49	non	non	ADJ
cana-4763	255	50	-	-	ADJ
cana-4763	255	51	linearly	linearly	ADV
cana-4763	255	52	separable	separable	ADJ
cana-4763	255	53	data	datum	NOUN
cana-4763	255	54	,	,	PUNCT
cana-4763	255	55	svm	svm	PROPN
cana-4763	255	56	maps	map	VERB
cana-4763	255	57	the	the	DET
cana-4763	255	58	data	datum	NOUN
cana-4763	255	59	into	into	ADP
cana-4763	255	60	a	a	DET
cana-4763	255	61	higherdimensional	higherdimensional	ADJ
cana-4763	255	62	space	space	NOUN
cana-4763	255	63	using	use	VERB
cana-4763	255	64	a	a	DET
cana-4763	255	65	kernel	kernel	NOUN
cana-4763	255	66	function	function	NOUN
cana-4763	255	67	ϕ(x	ϕ(x	PROPN
cana-4763	255	68	)	)	PUNCT
cana-4763	255	69	.	.	PUNCT
cana-4763	256	1	cascading	cascade	VERB
cana-4763	256	2	random	random	ADJ
cana-4763	256	3	forest	forest	NOUN
cana-4763	256	4	and	and	CCONJ
cana-4763	256	5	svm	svm	ADJ
cana-4763	256	6	classifiers	classifier	NOUN
cana-4763	256	7	this	this	DET
cana-4763	256	8	proposed	propose	VERB
cana-4763	256	9	approach	approach	NOUN
cana-4763	256	10	uses	use	VERB
cana-4763	256	11	a	a	DET
cana-4763	256	12	cascaded	cascade	VERB
cana-4763	256	13	combination	combination	NOUN
cana-4763	256	14	of	of	ADP
cana-4763	256	15	the	the	DET
cana-4763	256	16	random	random	ADJ
cana-4763	256	17	forest	forest	NOUN
cana-4763	256	18	(	(	PUNCT
cana-4763	256	19	rf	rf	NOUN
cana-4763	256	20	)	)	PUNCT
cana-4763	256	21	and	and	CCONJ
cana-4763	256	22	support	support	VERB
cana-4763	256	23	vector	vector	NOUN
cana-4763	256	24	machine	machine	NOUN
cana-4763	256	25	(	(	PUNCT
cana-4763	256	26	svm	svm	ADJ
cana-4763	256	27	)	)	PUNCT
cana-4763	256	28	classifiers	classifier	NOUN
cana-4763	256	29	.	.	PUNCT
cana-4763	257	1	a	a	DET
cana-4763	257	2	cascade	cascade	NOUN
cana-4763	257	3	classifier	classifier	NOUN
cana-4763	257	4	improves	improve	VERB
cana-4763	257	5	classification	classification	NOUN
cana-4763	257	6	accuracy	accuracy	NOUN
cana-4763	257	7	by	by	ADP
cana-4763	257	8	sequentially	sequentially	ADV
cana-4763	257	9	applying	apply	VERB
cana-4763	257	10	multiple	multiple	ADJ
cana-4763	257	11	classifiers	classifier	NOUN
cana-4763	257	12	.	.	PUNCT
cana-4763	258	1	the	the	DET
cana-4763	258	2	first	first	ADJ
cana-4763	258	3	classifier	classifier	NOUN
cana-4763	258	4	will	will	AUX
cana-4763	258	5	handle	handle	VERB
cana-4763	258	6	simpler	simple	ADJ
cana-4763	258	7	cases	case	NOUN
cana-4763	258	8	,	,	PUNCT
cana-4763	258	9	while	while	SCONJ
cana-4763	258	10	the	the	DET
cana-4763	258	11	more	more	ADV
cana-4763	258	12	complex	complex	ADJ
cana-4763	258	13	ones	one	NOUN
cana-4763	258	14	will	will	AUX
cana-4763	258	15	be	be	AUX
cana-4763	258	16	passed	pass	VERB
cana-4763	258	17	to	to	ADP
cana-4763	258	18	the	the	DET
cana-4763	258	19	next	next	ADJ
cana-4763	258	20	classifier	classifier	NOUN
cana-4763	258	21	.	.	PUNCT
cana-4763	259	1	this	this	DET
cana-4763	259	2	hierarchical	hierarchical	ADJ
cana-4763	259	3	approach	approach	NOUN
cana-4763	259	4	maintains	maintain	VERB
cana-4763	259	5	excellent	excellent	ADJ
cana-4763	259	6	accuracy	accuracy	NOUN
cana-4763	259	7	while	while	SCONJ
cana-4763	259	8	boosting	boost	VERB
cana-4763	259	9	efficiency	efficiency	NOUN
cana-4763	259	10	and	and	CCONJ
cana-4763	259	11	reducing	reduce	VERB
cana-4763	259	12	computational	computational	ADJ
cana-4763	259	13	burden	burden	NOUN
cana-4763	259	14	by	by	ADP
cana-4763	259	15	focusing	focus	VERB
cana-4763	259	16	later	later	ADJ
cana-4763	259	17	classifiers	classifier	NOUN
cana-4763	259	18	on	on	ADP
cana-4763	259	19	challenging	challenging	ADJ
cana-4763	259	20	instances	instance	NOUN
cana-4763	259	21	.	.	PUNCT
cana-4763	260	1	stage	stage	NOUN
cana-4763	260	2	1	1	NUM
cana-4763	260	3	:	:	PUNCT
cana-4763	260	4	random	random	ADJ
cana-4763	260	5	forest	forest	NOUN
cana-4763	260	6	(	(	PUNCT
cana-4763	260	7	rf	rf	NOUN
cana-4763	260	8	)	)	PUNCT
cana-4763	260	9	the	the	DET
cana-4763	260	10	data	data	NOUN
cana-4763	260	11	is	be	AUX
cana-4763	260	12	first	first	ADV
cana-4763	260	13	passed	pass	VERB
cana-4763	260	14	to	to	ADP
cana-4763	260	15	the	the	DET
cana-4763	260	16	rf	rf	NOUN
cana-4763	260	17	classifier	classifier	NOUN
cana-4763	260	18	.	.	PUNCT
cana-4763	261	1	if	if	SCONJ
cana-4763	261	2	the	the	DET
cana-4763	261	3	classification	classification	NOUN
cana-4763	261	4	is	be	AUX
cana-4763	261	5	confident	confident	ADJ
cana-4763	261	6	(	(	PUNCT
cana-4763	261	7	based	base	VERB
cana-4763	261	8	on	on	ADP
cana-4763	261	9	a	a	DET
cana-4763	261	10	predefined	predefine	VERB
cana-4763	261	11	threshold	threshold	NOUN
cana-4763	261	12	)	)	PUNCT
cana-4763	261	13	,	,	PUNCT
cana-4763	261	14	the	the	DET
cana-4763	261	15	result	result	NOUN
cana-4763	261	16	is	be	AUX
cana-4763	261	17	output	output	NOUN
cana-4763	261	18	directly	directly	ADV
cana-4763	261	19	.	.	PUNCT
cana-4763	262	1	otherwise	otherwise	ADV
cana-4763	262	2	,	,	PUNCT
cana-4763	262	3	the	the	DET
cana-4763	262	4	sample	sample	NOUN
cana-4763	262	5	is	be	AUX
cana-4763	262	6	forwarded	forward	VERB
cana-4763	262	7	to	to	ADP
cana-4763	262	8	the	the	DET
cana-4763	262	9	next	next	ADJ
cana-4763	262	10	classifier	classifier	NOUN
cana-4763	262	11	.	.	PUNCT
cana-4763	263	1	let	let	VERB
cana-4763	263	2	x={x1,x2,	x={x1,x2,	PROPN
cana-4763	263	3	…	…	PUNCT
cana-4763	263	4	,xn	,xn	PRON
cana-4763	263	5	}	}	PUNCT
cana-4763	263	6	be	be	VERB
cana-4763	263	7	the	the	DET
cana-4763	263	8	set	set	NOUN
cana-4763	263	9	of	of	ADP
cana-4763	263	10	input	input	NOUN
cana-4763	263	11	samples	sample	NOUN
cana-4763	263	12	,	,	PUNCT
cana-4763	263	13	and	and	CCONJ
cana-4763	263	14	let	let	VERB
cana-4763	263	15	ŷrf	ŷrf	NOUN
cana-4763	263	16	and	and	CCONJ
cana-4763	263	17	ŷsvm	ŷsvm	NOUN
cana-4763	263	18	represent	represent	VERB
cana-4763	263	19	the	the	DET
cana-4763	263	20	predictions	prediction	NOUN
cana-4763	263	21	from	from	ADP
cana-4763	263	22	the	the	DET
cana-4763	263	23	rf	rf	ADJ
cana-4763	263	24	and	and	CCONJ
cana-4763	263	25	svm	svm	ADJ
cana-4763	263	26	classifiers	classifier	NOUN
cana-4763	263	27	,	,	PUNCT
cana-4763	263	28	respectively	respectively	ADV
cana-4763	263	29	.	.	PUNCT
cana-4763	264	1	for	for	ADP
cana-4763	264	2	each	each	DET
cana-4763	264	3	input	input	NOUN
cana-4763	264	4	sample	sample	NOUN
cana-4763	264	5	xi	xi	X
cana-4763	264	6	:	:	PUNCT
cana-4763	264	7	1	1	X
cana-4763	264	8	.	.	X
cana-4763	264	9	apply	apply	VERB
cana-4763	264	10	rf	rf	NOUN
cana-4763	264	11	:	:	PUNCT
cana-4763	264	12	ŷrf	ŷrf	NOUN
cana-4763	264	13	=	=	NOUN
cana-4763	264	14	rf(xi	rf(xi	NOUN
cana-4763	264	15	)	)	PUNCT
cana-4763	264	16	..	..	PUNCT
cana-4763	265	1	(	(	PUNCT
cana-4763	265	2	27	27	NUM
cana-4763	265	3	)	)	PUNCT
cana-4763	265	4	stage	stage	NOUN
cana-4763	265	5	2	2	NUM
cana-4763	265	6	:	:	PUNCT
cana-4763	265	7	support	support	NOUN
cana-4763	265	8	vector	vector	NOUN
cana-4763	265	9	machine	machine	NOUN
cana-4763	265	10	(	(	PUNCT
cana-4763	265	11	svm	svm	PROPN
cana-4763	265	12	)	)	PUNCT
cana-4763	265	13	the	the	DET
cana-4763	265	14	rf	rf	NOUN
cana-4763	265	15	classifier	classifier	NOUN
cana-4763	265	16	sends	send	VERB
cana-4763	265	17	a	a	DET
cana-4763	265	18	sample	sample	NOUN
cana-4763	265	19	to	to	ADP
cana-4763	265	20	the	the	DET
cana-4763	265	21	svm	svm	ADJ
cana-4763	265	22	classifier	classifier	NOUN
cana-4763	265	23	in	in	ADP
cana-4763	265	24	case	case	NOUN
cana-4763	265	25	it	it	PRON
cana-4763	265	26	is	be	AUX
cana-4763	265	27	unsure	unsure	ADJ
cana-4763	265	28	about	about	ADP
cana-4763	265	29	it	it	PRON
cana-4763	265	30	.	.	PUNCT
cana-4763	266	1	svm	svm	PROPN
cana-4763	266	2	is	be	AUX
cana-4763	266	3	best	good	ADJ
cana-4763	266	4	for	for	ADP
cana-4763	266	5	tough	tough	ADJ
cana-4763	266	6	cases	case	NOUN
cana-4763	266	7	when	when	SCONJ
cana-4763	266	8	rf	rf	PRON
cana-4763	266	9	can	can	AUX
cana-4763	266	10	make	make	VERB
cana-4763	266	11	mistakes	mistake	NOUN
cana-4763	266	12	because	because	SCONJ
cana-4763	266	13	it	it	PRON
cana-4763	266	14	excels	excel	VERB
cana-4763	266	15	at	at	ADP
cana-4763	266	16	developing	develop	VERB
cana-4763	266	17	clear	clear	ADJ
cana-4763	266	18	decision	decision	NOUN
cana-4763	266	19	boundaries	boundary	NOUN
cana-4763	266	20	.	.	PUNCT
cana-4763	267	1	even	even	ADV
cana-4763	267	2	in	in	ADP
cana-4763	267	3	cases	case	NOUN
cana-4763	267	4	when	when	SCONJ
cana-4763	267	5	classes	class	NOUN
cana-4763	267	6	overlap	overlap	VERB
cana-4763	267	7	or	or	CCONJ
cana-4763	267	8	the	the	DET
cana-4763	267	9	patterns	pattern	NOUN
cana-4763	267	10	of	of	ADP
cana-4763	267	11	data	datum	NOUN
cana-4763	267	12	become	become	VERB
cana-4763	267	13	rather	rather	ADV
cana-4763	267	14	complex	complex	ADJ
cana-4763	267	15	,	,	PUNCT
cana-4763	267	16	such	such	ADJ
cana-4763	267	17	adaptability	adaptability	NOUN
cana-4763	267	18	makes	make	VERB
cana-4763	267	19	the	the	DET
cana-4763	267	20	accuracy	accuracy	NOUN
cana-4763	267	21	improve	improve	VERB
cana-4763	267	22	.	.	PUNCT
cana-4763	268	1	ŷsvm	ŷsvm	PUNCT
cana-4763	269	1	=	=	SYM
cana-4763	269	2	svm	svm	PROPN
cana-4763	269	3	(	(	PUNCT
cana-4763	269	4	xi	xi	NOUN
cana-4763	269	5	)	)	PUNCT
cana-4763	269	6	…	…	PUNCT
cana-4763	269	7	(	(	PUNCT
cana-4763	269	8	28	28	NUM
cana-4763	269	9	)	)	PUNCT
cana-4763	269	10	the	the	DET
cana-4763	269	11	final	final	ADJ
cana-4763	269	12	output	output	NOUN
cana-4763	269	13	for	for	ADP
cana-4763	269	14	sample	sample	NOUN
cana-4763	269	15	xi	xi	X
cana-4763	269	16	is	be	AUX
cana-4763	269	17	:	:	PUNCT
cana-4763	269	18	ŷ	ŷ	NUM
cana-4763	269	19	=	=	SYM
cana-4763	269	20	{	{	PUNCT
cana-4763	269	21	ŷrf	ŷrf	NOUN
cana-4763	269	22	if	if	SCONJ
cana-4763	269	23	rf	rf	PRON
cana-4763	269	24	is	be	AUX
cana-4763	269	25	confident	confident	ADJ
cana-4763	269	26	,	,	PUNCT
cana-4763	269	27	ŷsvm	ŷsvm	NOUN
cana-4763	269	28	otherwise	otherwise	ADV
cana-4763	269	29	…	…	PUNCT
cana-4763	269	30	.(29	.(29	NUM
cana-4763	269	31	)	)	PUNCT
cana-4763	269	32	by	by	ADP
cana-4763	269	33	integrating	integrate	VERB
cana-4763	269	34	random	random	ADJ
cana-4763	269	35	forest	forest	NOUN
cana-4763	269	36	(	(	PUNCT
cana-4763	269	37	rf	rf	NOUN
cana-4763	269	38	)	)	PUNCT
cana-4763	269	39	and	and	CCONJ
cana-4763	269	40	support	support	VERB
cana-4763	269	41	vector	vector	NOUN
cana-4763	269	42	machine	machine	NOUN
cana-4763	269	43	(	(	PUNCT
cana-4763	269	44	svm	svm	PROPN
cana-4763	269	45	)	)	PUNCT
cana-4763	269	46	,	,	PUNCT
cana-4763	269	47	the	the	DET
cana-4763	269	48	cascade	cascade	NOUN
cana-4763	269	49	method	method	NOUN
cana-4763	269	50	improves	improve	VERB
cana-4763	269	51	classification	classification	NOUN
cana-4763	269	52	accuracy	accuracy	NOUN
cana-4763	269	53	.	.	PUNCT
cana-4763	270	1	rf	rf	PRON
cana-4763	270	2	can	can	AUX
cana-4763	270	3	handle	handle	VERB
cana-4763	270	4	simpler	simple	ADJ
cana-4763	270	5	cases	case	NOUN
cana-4763	270	6	efficiently	efficiently	ADV
cana-4763	270	7	,	,	PUNCT
cana-4763	270	8	thus	thus	ADV
cana-4763	270	9	avoiding	avoid	VERB
cana-4763	270	10	svm	svm	PROPN
cana-4763	270	11	's	's	PART
cana-4763	270	12	computational	computational	ADJ
cana-4763	270	13	overhead	overhead	NOUN
cana-4763	270	14	.	.	PUNCT
cana-4763	271	1	svm	svm	PROPN
cana-4763	271	2	is	be	AUX
cana-4763	271	3	particularly	particularly	ADV
cana-4763	271	4	suited	suit	VERB
cana-4763	271	5	to	to	PART
cana-4763	271	6	generate	generate	VERB
cana-4763	271	7	accurate	accurate	ADJ
cana-4763	271	8	decision	decision	NOUN
cana-4763	271	9	boundaries	boundary	NOUN
cana-4763	271	10	in	in	ADP
cana-4763	271	11	more	more	ADJ
cana-4763	271	12	complex	complex	ADJ
cana-4763	271	13	cases	case	NOUN
cana-4763	271	14	.	.	PUNCT
cana-4763	272	1	by	by	ADP
cana-4763	272	2	dividing	divide	VERB
cana-4763	272	3	the	the	DET
cana-4763	272	4	work	work	NOUN
cana-4763	272	5	in	in	ADP
cana-4763	272	6	this	this	DET
cana-4763	272	7	manner	manner	NOUN
cana-4763	272	8	,	,	PUNCT
cana-4763	272	9	we	we	PRON
cana-4763	272	10	can	can	AUX
cana-4763	272	11	guarantee	guarantee	VERB
cana-4763	272	12	that	that	SCONJ
cana-4763	272	13	everything	everything	PRON
cana-4763	272	14	goes	go	VERB
cana-4763	272	15	smoothly	smoothly	ADV
cana-4763	272	16	and	and	CCONJ
cana-4763	272	17	without	without	ADP
cana-4763	272	18	issues	issue	NOUN
cana-4763	272	19	,	,	PUNCT
cana-4763	272	20	with	with	ADP
cana-4763	272	21	svm	svm	ADJ
cana-4763	272	22	intervening	intervene	VERB
cana-4763	272	23	only	only	ADV
cana-4763	272	24	when	when	SCONJ
cana-4763	272	25	its	its	PRON
cana-4763	272	26	sophisticated	sophisticated	ADJ
cana-4763	272	27	knowledge	knowledge	NOUN
cana-4763	272	28	is	be	AUX
cana-4763	272	29	required	require	VERB
cana-4763	272	30	.	.	PUNCT
cana-4763	273	1	the	the	DET
cana-4763	273	2	model	model	NOUN
cana-4763	273	3	therefore	therefore	ADV
cana-4763	273	4	works	work	VERB
cana-4763	273	5	uniformly	uniformly	ADV
cana-4763	273	6	over	over	ADP
cana-4763	273	7	a	a	DET
cana-4763	273	8	variety	variety	NOUN
cana-4763	273	9	of	of	ADP
cana-4763	273	10	levels	level	NOUN
cana-4763	273	11	of	of	ADP
cana-4763	273	12	complexity	complexity	NOUN
cana-4763	273	13	in	in	ADP
cana-4763	273	14	categorization	categorization	NOUN
cana-4763	273	15	.	.	PUNCT
cana-4763	274	1	communications	communication	NOUN
cana-4763	274	2	on	on	ADP
cana-4763	274	3	applied	apply	VERB
cana-4763	274	4	nonlinear	nonlinear	ADJ
cana-4763	274	5	analysis	analysis	NOUN
cana-4763	274	6	issn	issn	NOUN
cana-4763	274	7	:	:	PUNCT
cana-4763	274	8	1074	1074	NUM
cana-4763	274	9	-	-	PUNCT
cana-4763	274	10	133x	133x	NUM
cana-4763	274	11	vol	vol	VERB
cana-4763	274	12	32	32	NUM
cana-4763	274	13	no	no	NOUN
cana-4763	274	14	.	.	PUNCT
cana-4763	275	1	10s	10	NOUN
cana-4763	275	2	(	(	PUNCT
cana-4763	275	3	2025	2025	NUM
cana-4763	275	4	)	)	PUNCT
cana-4763	275	5	306	306	NUM
cana-4763	275	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	275	7	4	4	X
cana-4763	275	8	.	.	PUNCT
cana-4763	275	9	results	result	VERB
cana-4763	275	10	the	the	DET
cana-4763	275	11	results	result	NOUN
cana-4763	275	12	of	of	ADP
cana-4763	275	13	our	our	PRON
cana-4763	275	14	experiments	experiment	NOUN
cana-4763	275	15	show	show	VERB
cana-4763	275	16	the	the	DET
cana-4763	275	17	performance	performance	NOUN
cana-4763	275	18	of	of	ADP
cana-4763	275	19	the	the	DET
cana-4763	275	20	model	model	NOUN
cana-4763	275	21	that	that	PRON
cana-4763	275	22	we	we	PRON
cana-4763	275	23	have	have	AUX
cana-4763	275	24	designed	design	VERB
cana-4763	275	25	for	for	ADP
cana-4763	275	26	brain	brain	NOUN
cana-4763	275	27	tumor	tumor	NOUN
cana-4763	275	28	classification	classification	NOUN
cana-4763	275	29	.	.	PUNCT
cana-4763	276	1	we	we	PRON
cana-4763	276	2	applied	apply	VERB
cana-4763	276	3	it	it	PRON
cana-4763	276	4	to	to	ADP
cana-4763	276	5	a	a	DET
cana-4763	276	6	benchmark	benchmark	NOUN
cana-4763	276	7	dataset	dataset	NOUN
cana-4763	276	8	and	and	CCONJ
cana-4763	276	9	evaluated	evaluate	VERB
cana-4763	276	10	its	its	PRON
cana-4763	276	11	performance	performance	NOUN
cana-4763	276	12	with	with	ADP
cana-4763	276	13	a	a	DET
cana-4763	276	14	set	set	NOUN
cana-4763	276	15	of	of	ADP
cana-4763	276	16	evaluation	evaluation	NOUN
cana-4763	276	17	metrics	metric	NOUN
cana-4763	276	18	.	.	PUNCT
cana-4763	277	1	the	the	DET
cana-4763	277	2	rf	rf	ADJ
cana-4763	277	3	-	-	PUNCT
cana-4763	277	4	svm	svm	ADJ
cana-4763	277	5	classification	classification	NOUN
cana-4763	277	6	framework	framework	NOUN
cana-4763	277	7	,	,	PUNCT
cana-4763	277	8	bilateral	bilateral	ADJ
cana-4763	277	9	filtering	filtering	NOUN
cana-4763	277	10	,	,	PUNCT
cana-4763	277	11	lbp	lbp	NOUN
cana-4763	277	12	-	-	PUNCT
cana-4763	277	13	based	base	VERB
cana-4763	277	14	feature	feature	NOUN
cana-4763	277	15	extraction	extraction	NOUN
cana-4763	277	16	,	,	PUNCT
cana-4763	277	17	and	and	CCONJ
cana-4763	277	18	gwo	gwo	PROPN
cana-4763	277	19	feature	feature	NOUN
cana-4763	277	20	selection	selection	NOUN
cana-4763	277	21	enhance	enhance	VERB
cana-4763	277	22	tumor	tumor	NOUN
cana-4763	277	23	detection	detection	NOUN
cana-4763	277	24	accuracy	accuracy	NOUN
cana-4763	277	25	greatly	greatly	ADV
cana-4763	277	26	.	.	PUNCT
cana-4763	278	1	these	these	DET
cana-4763	278	2	results	result	NOUN
cana-4763	278	3	also	also	ADV
cana-4763	278	4	show	show	VERB
cana-4763	278	5	that	that	SCONJ
cana-4763	278	6	hybrid	hybrid	ADJ
cana-4763	278	7	classifiers	classifier	NOUN
cana-4763	278	8	combined	combine	VERB
cana-4763	278	9	with	with	ADP
cana-4763	278	10	advanced	advanced	ADJ
cana-4763	278	11	preprocessing	preprocessing	NOUN
cana-4763	278	12	techniques	technique	NOUN
cana-4763	278	13	can	can	AUX
cana-4763	278	14	significantly	significantly	ADV
cana-4763	278	15	improve	improve	VERB
cana-4763	278	16	the	the	DET
cana-4763	278	17	resilience	resilience	NOUN
cana-4763	278	18	and	and	CCONJ
cana-4763	278	19	dependability	dependability	NOUN
cana-4763	278	20	of	of	ADP
cana-4763	278	21	tumor	tumor	NOUN
cana-4763	278	22	classification	classification	NOUN
cana-4763	278	23	systems	system	NOUN
cana-4763	278	24	.	.	PUNCT
cana-4763	279	1	4.1	4.1	NUM
cana-4763	279	2	preprocessing	preprocessing	NOUN
cana-4763	279	3	results	result	NOUN
cana-4763	279	4	(	(	PUNCT
cana-4763	279	5	a	a	X
cana-4763	279	6	)	)	PUNCT
cana-4763	279	7	(	(	PUNCT
cana-4763	279	8	b	b	X
cana-4763	279	9	)	)	PUNCT
cana-4763	279	10	(	(	PUNCT
cana-4763	279	11	c	c	X
cana-4763	279	12	)	)	PUNCT
cana-4763	279	13	(	(	PUNCT
cana-4763	279	14	d	d	X
cana-4763	279	15	)	)	PUNCT
cana-4763	279	16	(	(	PUNCT
cana-4763	279	17	e	e	NOUN
cana-4763	279	18	)	)	PUNCT
cana-4763	279	19	(	(	PUNCT
cana-4763	279	20	f	f	X
cana-4763	279	21	)	)	PUNCT
cana-4763	279	22	fig	fig	NOUN
cana-4763	279	23	2	2	NUM
cana-4763	279	24	:	:	PUNCT
cana-4763	279	25	output	output	NOUN
cana-4763	279	26	of	of	ADP
cana-4763	279	27	the	the	DET
cana-4763	279	28	pre	pre	ADJ
cana-4763	279	29	-	-	ADJ
cana-4763	279	30	processed	process	VERB
cana-4763	279	31	images	image	NOUN
cana-4763	279	32	the	the	DET
cana-4763	279	33	left	left	ADJ
cana-4763	279	34	-	-	PUNCT
cana-4763	279	35	hand	hand	NOUN
cana-4763	279	36	side	side	NOUN
cana-4763	279	37	,	,	PUNCT
cana-4763	279	38	which	which	PRON
cana-4763	279	39	is	be	AUX
cana-4763	279	40	"	"	PUNCT
cana-4763	279	41	original	original	ADJ
cana-4763	279	42	,	,	PUNCT
cana-4763	279	43	"	"	PUNCT
cana-4763	279	44	in	in	ADP
cana-4763	279	45	figures	figure	NOUN
cana-4763	279	46	2a	2a	NUM
cana-4763	279	47	,	,	PUNCT
cana-4763	279	48	2c	2c	NUM
cana-4763	279	49	,	,	PUNCT
cana-4763	279	50	and	and	CCONJ
cana-4763	279	51	2e	2e	NOUN
cana-4763	279	52	presents	present	VERB
cana-4763	279	53	the	the	DET
cana-4763	279	54	original	original	ADJ
cana-4763	279	55	input	input	NOUN
cana-4763	279	56	image	image	NOUN
cana-4763	279	57	,	,	PUNCT
cana-4763	279	58	which	which	PRON
cana-4763	279	59	is	be	AUX
cana-4763	279	60	darker	dark	ADJ
cana-4763	279	61	,	,	PUNCT
cana-4763	279	62	has	have	AUX
cana-4763	279	63	reduced	reduce	VERB
cana-4763	279	64	contrast	contrast	NOUN
cana-4763	279	65	,	,	PUNCT
cana-4763	279	66	and	and	CCONJ
cana-4763	279	67	shows	show	VERB
cana-4763	279	68	some	some	DET
cana-4763	279	69	noise	noise	NOUN
cana-4763	279	70	.	.	PUNCT
cana-4763	280	1	you	you	PRON
cana-4763	280	2	can	can	AUX
cana-4763	280	3	observe	observe	VERB
cana-4763	280	4	the	the	DET
cana-4763	280	5	enhanced	enhance	VERB
cana-4763	280	6	output	output	NOUN
cana-4763	280	7	on	on	ADP
cana-4763	280	8	the	the	DET
cana-4763	280	9	right	right	ADJ
cana-4763	280	10	-	-	PUNCT
cana-4763	280	11	hand	hand	NOUN
cana-4763	280	12	side	side	NOUN
cana-4763	280	13	,	,	PUNCT
cana-4763	280	14	which	which	PRON
cana-4763	280	15	is	be	AUX
cana-4763	280	16	titled	title	VERB
cana-4763	280	17	"	"	PUNCT
cana-4763	280	18	enhanced	enhanced	ADJ
cana-4763	280	19	image	image	NOUN
cana-4763	280	20	,	,	PUNCT
cana-4763	280	21	"	"	PUNCT
cana-4763	280	22	after	after	ADP
cana-4763	280	23	applying	apply	VERB
cana-4763	280	24	bilateral	bilateral	ADJ
cana-4763	280	25	filtering	filtering	NOUN
cana-4763	280	26	to	to	PART
cana-4763	280	27	reduce	reduce	VERB
cana-4763	280	28	noise	noise	NOUN
cana-4763	280	29	and	and	CCONJ
cana-4763	280	30	histogram	histogram	NOUN
cana-4763	280	31	equalization	equalization	NOUN
cana-4763	280	32	to	to	PART
cana-4763	280	33	enhance	enhance	VERB
cana-4763	280	34	contrast	contrast	NOUN
cana-4763	280	35	.	.	PUNCT
cana-4763	281	1	the	the	DET
cana-4763	281	2	enhanced	enhance	VERB
cana-4763	281	3	image	image	NOUN
cana-4763	281	4	is	be	AUX
cana-4763	281	5	presented	present	VERB
cana-4763	281	6	on	on	ADP
cana-4763	281	7	the	the	DET
cana-4763	281	8	left	left	ADJ
cana-4763	281	9	-	-	PUNCT
cana-4763	281	10	hand	hand	NOUN
cana-4763	281	11	side	side	NOUN
cana-4763	281	12	,	,	PUNCT
cana-4763	281	13	which	which	PRON
cana-4763	281	14	is	be	AUX
cana-4763	281	15	also	also	ADV
cana-4763	281	16	"	"	PUNCT
cana-4763	281	17	original	original	ADJ
cana-4763	281	18	,	,	PUNCT
cana-4763	281	19	"	"	PUNCT
cana-4763	281	20	in	in	ADP
cana-4763	281	21	figures	figure	NOUN
cana-4763	281	22	2b	2b	NOUN
cana-4763	281	23	,	,	PUNCT
cana-4763	281	24	2d	2d	NOUN
cana-4763	281	25	,	,	PUNCT
cana-4763	281	26	and	and	CCONJ
cana-4763	281	27	2f	2f	NOUN
cana-4763	281	28	.	.	PUNCT
cana-4763	282	1	the	the	DET
cana-4763	282	2	"	"	PUNCT
cana-4763	282	3	pre	pre	ADJ
cana-4763	282	4	-	-	ADJ
cana-4763	282	5	processed	processed	ADJ
cana-4763	282	6	image	image	NOUN
cana-4763	282	7	,	,	PUNCT
cana-4763	282	8	"	"	PUNCT
cana-4763	282	9	on	on	ADP
cana-4763	282	10	the	the	DET
cana-4763	282	11	right	right	ADJ
cana-4763	282	12	-	-	PUNCT
cana-4763	282	13	hand	hand	NOUN
cana-4763	282	14	side	side	NOUN
cana-4763	282	15	,	,	PUNCT
cana-4763	282	16	presents	present	VERB
cana-4763	282	17	the	the	DET
cana-4763	282	18	final	final	ADJ
cana-4763	282	19	product	product	NOUN
cana-4763	282	20	after	after	ADP
cana-4763	282	21	further	far	ADV
cana-4763	282	22	refinement	refinement	NOUN
cana-4763	282	23	through	through	ADP
cana-4763	282	24	binary	binary	ADJ
cana-4763	282	25	and	and	CCONJ
cana-4763	282	26	morphological	morphological	ADJ
cana-4763	282	27	operations	operation	NOUN
cana-4763	282	28	.	.	PUNCT
cana-4763	283	1	4.2	4.2	NUM
cana-4763	283	2	feature	feature	NOUN
cana-4763	283	3	extraction	extraction	NOUN
cana-4763	283	4	results	result	VERB
cana-4763	283	5	the	the	DET
cana-4763	283	6	following	following	NOUN
cana-4763	283	7	are	be	AUX
cana-4763	283	8	the	the	DET
cana-4763	283	9	sample	sample	NOUN
cana-4763	283	10	results	result	NOUN
cana-4763	283	11	obtained	obtain	VERB
cana-4763	283	12	using	use	VERB
cana-4763	283	13	lbp	lbp	NOUN
cana-4763	283	14	based	base	VERB
cana-4763	283	15	feature	feature	NOUN
cana-4763	283	16	extraction	extraction	NOUN
cana-4763	283	17	technique	technique	NOUN
cana-4763	283	18	.	.	PUNCT
cana-4763	284	1	communications	communication	NOUN
cana-4763	284	2	on	on	ADP
cana-4763	284	3	applied	apply	VERB
cana-4763	284	4	nonlinear	nonlinear	ADJ
cana-4763	284	5	analysis	analysis	NOUN
cana-4763	284	6	issn	issn	NOUN
cana-4763	284	7	:	:	PUNCT
cana-4763	284	8	1074	1074	NUM
cana-4763	284	9	-	-	PUNCT
cana-4763	284	10	133x	133x	NUM
cana-4763	284	11	vol	vol	VERB
cana-4763	284	12	32	32	NUM
cana-4763	284	13	no	no	NOUN
cana-4763	284	14	.	.	PUNCT
cana-4763	285	1	10s	10	NOUN
cana-4763	285	2	(	(	PUNCT
cana-4763	285	3	2025	2025	NUM
cana-4763	285	4	)	)	PUNCT
cana-4763	285	5	307	307	NUM
cana-4763	285	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	285	7	fig	fig	NOUN
cana-4763	285	8	3	3	NUM
cana-4763	285	9	:	:	PUNCT
cana-4763	285	10	output	output	NOUN
cana-4763	285	11	of	of	ADP
cana-4763	285	12	lbph	lbph	NOUN
cana-4763	285	13	the	the	DET
cana-4763	285	14	use	use	NOUN
cana-4763	285	15	of	of	ADP
cana-4763	285	16	local	local	ADJ
cana-4763	285	17	binary	binary	ADJ
cana-4763	285	18	pattern	pattern	NOUN
cana-4763	285	19	(	(	PUNCT
cana-4763	285	20	lbp	lbp	NOUN
cana-4763	285	21	)	)	PUNCT
cana-4763	285	22	in	in	ADP
cana-4763	285	23	texture	texture	ADJ
cana-4763	285	24	analysis	analysis	NOUN
cana-4763	285	25	is	be	AUX
cana-4763	285	26	illustrated	illustrate	VERB
cana-4763	285	27	through	through	ADP
cana-4763	285	28	the	the	DET
cana-4763	285	29	image	image	NOUN
cana-4763	285	30	provided	provide	VERB
cana-4763	285	31	above	above	ADV
cana-4763	285	32	.	.	PUNCT
cana-4763	286	1	local	local	ADJ
cana-4763	286	2	texture	texture	NOUN
cana-4763	286	3	patterns	pattern	NOUN
cana-4763	286	4	represent	represent	VERB
cana-4763	286	5	pixel	pixel	PROPN
cana-4763	286	6	intensities	intensity	NOUN
cana-4763	286	7	in	in	ADP
cana-4763	286	8	the	the	DET
cana-4763	286	9	lbp	lbp	NOUN
cana-4763	286	10	-	-	PUNCT
cana-4763	286	11	transformation	transformation	NOUN
cana-4763	286	12	image	image	NOUN
cana-4763	286	13	on	on	ADP
cana-4763	286	14	the	the	DET
cana-4763	286	15	left	left	ADJ
cana-4763	286	16	side	side	NOUN
cana-4763	286	17	.	.	PUNCT
cana-4763	287	1	the	the	DET
cana-4763	287	2	update	update	NOUN
cana-4763	287	3	emphasizes	emphasize	VERB
cana-4763	287	4	features	feature	NOUN
cana-4763	287	5	and	and	CCONJ
cana-4763	287	6	structures	structure	NOUN
cana-4763	287	7	and	and	CCONJ
cana-4763	287	8	pays	pay	VERB
cana-4763	287	9	attention	attention	NOUN
cana-4763	287	10	to	to	ADP
cana-4763	287	11	some	some	PRON
cana-4763	287	12	of	of	ADP
cana-4763	287	13	its	its	PRON
cana-4763	287	14	characteristics	characteristic	NOUN
cana-4763	287	15	.	.	PUNCT
cana-4763	288	1	you	you	PRON
cana-4763	288	2	can	can	AUX
cana-4763	288	3	observe	observe	VERB
cana-4763	288	4	the	the	DET
cana-4763	288	5	lbp	lbp	PROPN
cana-4763	288	6	histogram	histogram	NOUN
cana-4763	288	7	,	,	PUNCT
cana-4763	288	8	which	which	PRON
cana-4763	288	9	shows	show	VERB
cana-4763	288	10	the	the	DET
cana-4763	288	11	frequency	frequency	NOUN
cana-4763	288	12	of	of	ADP
cana-4763	288	13	various	various	ADJ
cana-4763	288	14	lbp	lbp	NOUN
cana-4763	288	15	patterns	pattern	NOUN
cana-4763	288	16	,	,	PUNCT
cana-4763	288	17	on	on	ADP
cana-4763	288	18	the	the	DET
cana-4763	288	19	right	right	NOUN
cana-4763	288	20	.	.	PUNCT
cana-4763	289	1	tumor	tumor	NOUN
cana-4763	289	2	detection	detection	NOUN
cana-4763	289	3	and	and	CCONJ
cana-4763	289	4	tissue	tissue	NOUN
cana-4763	289	5	differentiation	differentiation	NOUN
cana-4763	289	6	are	be	AUX
cana-4763	289	7	two	two	NUM
cana-4763	289	8	classification	classification	NOUN
cana-4763	289	9	tasks	task	NOUN
cana-4763	289	10	that	that	PRON
cana-4763	289	11	greatly	greatly	ADV
cana-4763	289	12	benefit	benefit	VERB
cana-4763	289	13	from	from	ADP
cana-4763	289	14	this	this	DET
cana-4763	289	15	histogram	histogram	NOUN
cana-4763	289	16	since	since	SCONJ
cana-4763	289	17	it	it	PRON
cana-4763	289	18	provides	provide	VERB
cana-4763	289	19	us	we	PRON
cana-4763	289	20	with	with	ADP
cana-4763	289	21	an	an	DET
cana-4763	289	22	insight	insight	NOUN
cana-4763	289	23	into	into	ADP
cana-4763	289	24	the	the	DET
cana-4763	289	25	texture	texture	ADJ
cana-4763	289	26	distribution	distribution	NOUN
cana-4763	289	27	.	.	PUNCT
cana-4763	290	1	for	for	ADP
cana-4763	290	2	identifying	identify	VERB
cana-4763	290	3	patterns	pattern	NOUN
cana-4763	290	4	and	and	CCONJ
cana-4763	290	5	obtaining	obtain	VERB
cana-4763	290	6	features	feature	NOUN
cana-4763	290	7	in	in	ADP
cana-4763	290	8	medical	medical	ADJ
cana-4763	290	9	imaging	imaging	NOUN
cana-4763	290	10	,	,	PUNCT
cana-4763	290	11	lbp	lbp	PROPN
cana-4763	290	12	has	have	AUX
cana-4763	290	13	emerged	emerge	VERB
cana-4763	290	14	as	as	ADP
cana-4763	290	15	the	the	DET
cana-4763	290	16	preferred	preferred	ADJ
cana-4763	290	17	technique	technique	NOUN
cana-4763	290	18	.	.	PUNCT
cana-4763	291	1	feature	feature	NOUN
cana-4763	291	2	extraction	extraction	NOUN
cana-4763	291	3	results	result	NOUN
cana-4763	291	4	:	:	PUNCT
cana-4763	291	5	the	the	DET
cana-4763	291	6	results	result	NOUN
cana-4763	291	7	of	of	ADP
cana-4763	291	8	the	the	DET
cana-4763	291	9	feature	feature	NOUN
cana-4763	291	10	extraction	extraction	NOUN
cana-4763	291	11	are	be	AUX
cana-4763	291	12	summarized	summarize	VERB
cana-4763	291	13	in	in	ADP
cana-4763	291	14	the	the	DET
cana-4763	291	15	table	table	NOUN
cana-4763	291	16	below	below	ADV
cana-4763	291	17	:	:	PUNCT
cana-4763	291	18	feature	feature	NOUN
cana-4763	291	19	glioma	glioma	NOUN
cana-4763	291	20	meningioma	meningioma	NOUN
cana-4763	291	21	pituitary	pituitary	NOUN
cana-4763	291	22	no	no	DET
cana-4763	291	23	tumor	tumor	NOUN
cana-4763	291	24	energy	energy	NOUN
cana-4763	291	25	0.85	0.85	NUM
cana-4763	291	26	0.75	0.75	NUM
cana-4763	291	27	0.72	0.72	NUM
cana-4763	291	28	0.95	0.95	NUM
cana-4763	291	29	entropy	entropy	NOUN
cana-4763	291	30	6.25	6.25	NUM
cana-4763	291	31	5.10	5.10	NUM
cana-4763	291	32	5.60	5.60	NUM
cana-4763	291	33	4.30	4.30	NUM
cana-4763	291	34	contrast	contrast	NOUN
cana-4763	291	35	0.25	0.25	NUM
cana-4763	291	36	0.45	0.45	NUM
cana-4763	291	37	0.30	0.30	NUM
cana-4763	291	38	0.10	0.10	NUM
cana-4763	291	39	communications	communication	NOUN
cana-4763	291	40	on	on	ADP
cana-4763	291	41	applied	apply	VERB
cana-4763	291	42	nonlinear	nonlinear	ADJ
cana-4763	291	43	analysis	analysis	NOUN
cana-4763	291	44	issn	issn	NOUN
cana-4763	291	45	:	:	PUNCT
cana-4763	291	46	1074	1074	NUM
cana-4763	291	47	-	-	PUNCT
cana-4763	291	48	133x	133x	NUM
cana-4763	291	49	vol	vol	VERB
cana-4763	291	50	32	32	NUM
cana-4763	291	51	no	no	NOUN
cana-4763	291	52	.	.	PUNCT
cana-4763	292	1	10s	10	NOUN
cana-4763	292	2	(	(	PUNCT
cana-4763	292	3	2025	2025	NUM
cana-4763	292	4	)	)	PUNCT
cana-4763	292	5	308	308	NUM
cana-4763	292	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	292	7	correlation	correlation	NOUN
cana-4763	292	8	0.68	0.68	NUM
cana-4763	292	9	0.55	0.55	NUM
cana-4763	292	10	0.60	0.60	NUM
cana-4763	292	11	0.90	0.90	NUM
cana-4763	292	12	homogeneity	homogeneity	NOUN
cana-4763	292	13	0.92	0.92	NUM
cana-4763	292	14	0.88	0.88	NUM
cana-4763	292	15	0.85	0.85	NUM
cana-4763	292	16	0.97	0.97	NUM
cana-4763	292	17	table	table	NOUN
cana-4763	292	18	1	1	NUM
cana-4763	292	19	:	:	PUNCT
cana-4763	292	20	feature	feature	NOUN
cana-4763	292	21	extraction	extraction	NOUN
cana-4763	292	22	results	result	VERB
cana-4763	292	23	the	the	DET
cana-4763	292	24	table	table	NOUN
cana-4763	292	25	displays	display	VERB
cana-4763	292	26	texture	texture	NOUN
cana-4763	292	27	-	-	PUNCT
cana-4763	292	28	based	base	VERB
cana-4763	292	29	feature	feature	NOUN
cana-4763	292	30	values	value	NOUN
cana-4763	292	31	for	for	ADP
cana-4763	292	32	glioma	glioma	NOUN
cana-4763	292	33	,	,	PUNCT
cana-4763	292	34	meningioma	meningioma	NOUN
cana-4763	292	35	,	,	PUNCT
cana-4763	292	36	pituitary	pituitary	NOUN
cana-4763	292	37	,	,	PUNCT
cana-4763	292	38	and	and	CCONJ
cana-4763	292	39	other	other	ADJ
cana-4763	292	40	brain	brain	NOUN
cana-4763	292	41	tumors	tumor	NOUN
cana-4763	292	42	,	,	PUNCT
cana-4763	292	43	as	as	ADV
cana-4763	292	44	well	well	ADV
cana-4763	292	45	as	as	ADP
cana-4763	292	46	a	a	DET
cana-4763	292	47	"	"	PUNCT
cana-4763	292	48	no	no	DET
cana-4763	292	49	tumor	tumor	NOUN
cana-4763	292	50	"	"	PUNCT
cana-4763	292	51	category	category	NOUN
cana-4763	292	52	.	.	PUNCT
cana-4763	293	1	these	these	DET
cana-4763	293	2	characteristics	characteristic	NOUN
cana-4763	293	3	are	be	AUX
cana-4763	293	4	extracted	extract	VERB
cana-4763	293	5	from	from	ADP
cana-4763	293	6	medical	medical	ADJ
cana-4763	293	7	images	image	NOUN
cana-4763	293	8	to	to	PART
cana-4763	293	9	help	help	VERB
cana-4763	293	10	categorize	categorize	VERB
cana-4763	293	11	tumors	tumor	NOUN
cana-4763	293	12	.	.	PUNCT
cana-4763	294	1	•	•	NUM
cana-4763	294	2	energy	energy	NOUN
cana-4763	294	3	:	:	PUNCT
cana-4763	294	4	the	the	DET
cana-4763	294	5	category	category	NOUN
cana-4763	294	6	labeled	label	VERB
cana-4763	294	7	"	"	PUNCT
cana-4763	294	8	no	no	DET
cana-4763	294	9	tumor	tumor	NOUN
cana-4763	294	10	"	"	PUNCT
cana-4763	294	11	has	have	VERB
cana-4763	294	12	the	the	DET
cana-4763	294	13	highest	high	ADJ
cana-4763	294	14	energy	energy	NOUN
cana-4763	294	15	value	value	NOUN
cana-4763	294	16	(	(	PUNCT
cana-4763	294	17	0.95	0.95	NUM
cana-4763	294	18	)	)	PUNCT
cana-4763	294	19	,	,	PUNCT
cana-4763	294	20	which	which	PRON
cana-4763	294	21	is	be	AUX
cana-4763	294	22	indicative	indicative	ADJ
cana-4763	294	23	of	of	ADP
cana-4763	294	24	a	a	DET
cana-4763	294	25	more	more	ADV
cana-4763	294	26	consistent	consistent	ADJ
cana-4763	294	27	texture	texture	NOUN
cana-4763	294	28	.	.	PUNCT
cana-4763	295	1	gliomas	glioma	NOUN
cana-4763	295	2	(	(	PUNCT
cana-4763	295	3	0.85	0.85	NUM
cana-4763	295	4	)	)	PUNCT
cana-4763	295	5	,	,	PUNCT
cana-4763	295	6	on	on	ADP
cana-4763	295	7	the	the	DET
cana-4763	295	8	other	other	ADJ
cana-4763	295	9	hand	hand	NOUN
cana-4763	295	10	,	,	PUNCT
cana-4763	295	11	have	have	VERB
cana-4763	295	12	a	a	DET
cana-4763	295	13	higher	high	ADJ
cana-4763	295	14	energy	energy	NOUN
cana-4763	295	15	level	level	NOUN
cana-4763	295	16	than	than	ADP
cana-4763	295	17	pituitary	pituitary	ADJ
cana-4763	295	18	and	and	CCONJ
cana-4763	295	19	meningioma	meningioma	NOUN
cana-4763	295	20	’s	’s	NOUN
cana-4763	295	21	.	.	PUNCT
cana-4763	296	1	•	•	NUM
cana-4763	296	2	entropy	entropy	PROPN
cana-4763	296	3	:	:	PUNCT
cana-4763	296	4	glioma	glioma	NOUN
cana-4763	296	5	(	(	PUNCT
cana-4763	296	6	6.25	6.25	NUM
cana-4763	296	7	)	)	PUNCT
cana-4763	296	8	exhibits	exhibit	VERB
cana-4763	296	9	the	the	DET
cana-4763	296	10	highest	high	ADJ
cana-4763	296	11	entropy	entropy	NOUN
cana-4763	296	12	,	,	PUNCT
cana-4763	296	13	indicating	indicate	VERB
cana-4763	296	14	more	more	ADV
cana-4763	296	15	intricate	intricate	ADJ
cana-4763	296	16	texture	texture	NOUN
cana-4763	296	17	patterns	pattern	NOUN
cana-4763	296	18	,	,	PUNCT
cana-4763	296	19	while	while	SCONJ
cana-4763	296	20	the	the	DET
cana-4763	296	21	"	"	PUNCT
cana-4763	296	22	no	no	DET
cana-4763	296	23	tumor	tumor	NOUN
cana-4763	296	24	"	"	PUNCT
cana-4763	296	25	category	category	NOUN
cana-4763	296	26	likewise	likewise	ADV
cana-4763	296	27	has	have	VERB
cana-4763	296	28	the	the	DET
cana-4763	296	29	lowest	low	ADJ
cana-4763	296	30	entropy	entropy	NOUN
cana-4763	296	31	(	(	PUNCT
cana-4763	296	32	4.30	4.30	NUM
cana-4763	296	33	)	)	PUNCT
cana-4763	296	34	,	,	PUNCT
cana-4763	296	35	indicating	indicate	VERB
cana-4763	296	36	a	a	DET
cana-4763	296	37	simpler	simple	ADJ
cana-4763	296	38	texture	texture	NOUN
cana-4763	296	39	.	.	PUNCT
cana-4763	297	1	•contrast	•contrast	NOUN
cana-4763	297	2	:	:	PUNCT
cana-4763	297	3	meningioma	meningioma	NOUN
cana-4763	297	4	(	(	PUNCT
cana-4763	297	5	0.45	0.45	NUM
cana-4763	297	6	)	)	PUNCT
cana-4763	297	7	has	have	VERB
cana-4763	297	8	the	the	DET
cana-4763	297	9	largest	large	ADJ
cana-4763	297	10	contrast	contrast	NOUN
cana-4763	297	11	because	because	SCONJ
cana-4763	297	12	of	of	ADP
cana-4763	297	13	the	the	DET
cana-4763	297	14	wide	wide	ADJ
cana-4763	297	15	range	range	NOUN
cana-4763	297	16	of	of	ADP
cana-4763	297	17	intensity	intensity	NOUN
cana-4763	297	18	differences	difference	NOUN
cana-4763	297	19	,	,	PUNCT
cana-4763	297	20	while	while	SCONJ
cana-4763	297	21	the	the	DET
cana-4763	297	22	"	"	PUNCT
cana-4763	297	23	no	no	DET
cana-4763	297	24	tumor	tumor	NOUN
cana-4763	297	25	"	"	PUNCT
cana-4763	297	26	class	class	NOUN
cana-4763	297	27	has	have	VERB
cana-4763	297	28	the	the	DET
cana-4763	297	29	lowest	low	ADJ
cana-4763	297	30	contrast	contrast	NOUN
cana-4763	297	31	(	(	PUNCT
cana-4763	297	32	0.10	0.10	NUM
cana-4763	297	33	)	)	PUNCT
cana-4763	297	34	,	,	PUNCT
cana-4763	297	35	indicating	indicate	VERB
cana-4763	297	36	smooth	smooth	ADJ
cana-4763	297	37	texture	texture	NOUN
cana-4763	297	38	.	.	PUNCT
cana-4763	298	1	•	•	NUM
cana-4763	298	2	correlation	correlation	NOUN
cana-4763	298	3	:	:	PUNCT
cana-4763	298	4	meningioma	meningioma	NOUN
cana-4763	298	5	has	have	VERB
cana-4763	298	6	a	a	DET
cana-4763	298	7	lower	low	ADJ
cana-4763	298	8	correlation	correlation	NOUN
cana-4763	298	9	(	(	PUNCT
cana-4763	298	10	0.55	0.55	NUM
cana-4763	298	11	)	)	PUNCT
cana-4763	298	12	,	,	PUNCT
cana-4763	298	13	whereas	whereas	SCONJ
cana-4763	298	14	"	"	PUNCT
cana-4763	298	15	no	no	DET
cana-4763	298	16	tumor	tumor	NOUN
cana-4763	298	17	"	"	PUNCT
cana-4763	298	18	has	have	VERB
cana-4763	298	19	the	the	DET
cana-4763	298	20	highest	high	ADJ
cana-4763	298	21	correlation	correlation	NOUN
cana-4763	298	22	(	(	PUNCT
cana-4763	298	23	0.90	0.90	NUM
cana-4763	298	24	)	)	PUNCT
cana-4763	298	25	,	,	PUNCT
cana-4763	298	26	indicating	indicate	VERB
cana-4763	298	27	a	a	DET
cana-4763	298	28	strong	strong	ADJ
cana-4763	298	29	relationship	relationship	NOUN
cana-4763	298	30	between	between	ADP
cana-4763	298	31	pixel	pixel	PROPN
cana-4763	298	32	intensities	intensity	NOUN
cana-4763	298	33	.	.	PUNCT
cana-4763	299	1	•	•	NUM
cana-4763	299	2	homogeneity	homogeneity	NOUN
cana-4763	299	3	:	:	PUNCT
cana-4763	299	4	while	while	SCONJ
cana-4763	299	5	meningioma	meningioma	NOUN
cana-4763	299	6	(	(	PUNCT
cana-4763	299	7	0.88	0.88	NUM
cana-4763	299	8	)	)	PUNCT
cana-4763	299	9	and	and	CCONJ
cana-4763	299	10	glioma	glioma	NOUN
cana-4763	299	11	(	(	PUNCT
cana-4763	299	12	0.92	0.92	NUM
cana-4763	299	13	)	)	PUNCT
cana-4763	299	14	have	have	VERB
cana-4763	299	15	more	more	ADJ
cana-4763	299	16	heterogeneity	heterogeneity	NOUN
cana-4763	299	17	,	,	PUNCT
cana-4763	299	18	the	the	DET
cana-4763	299	19	"	"	PUNCT
cana-4763	299	20	no	no	DET
cana-4763	299	21	tumor	tumor	NOUN
cana-4763	299	22	"	"	PUNCT
cana-4763	299	23	category	category	NOUN
cana-4763	299	24	had	have	VERB
cana-4763	299	25	the	the	DET
cana-4763	299	26	highest	high	ADJ
cana-4763	299	27	homogeneity	homogeneity	NOUN
cana-4763	299	28	(	(	PUNCT
cana-4763	299	29	0.97	0.97	NUM
cana-4763	299	30	)	)	PUNCT
cana-4763	299	31	,	,	PUNCT
cana-4763	299	32	suggesting	suggest	VERB
cana-4763	299	33	a	a	DET
cana-4763	299	34	more	more	ADV
cana-4763	299	35	homogenous	homogenous	ADJ
cana-4763	299	36	texture	texture	NOUN
cana-4763	299	37	.	.	PUNCT
cana-4763	300	1	these	these	DET
cana-4763	300	2	traits	trait	NOUN
cana-4763	300	3	are	be	AUX
cana-4763	300	4	crucial	crucial	ADJ
cana-4763	300	5	for	for	ADP
cana-4763	300	6	differentiating	differentiate	VERB
cana-4763	300	7	various	various	ADJ
cana-4763	300	8	tumor	tumor	NOUN
cana-4763	300	9	kinds	kind	NOUN
cana-4763	300	10	.	.	PUNCT
cana-4763	301	1	in	in	ADP
cana-4763	301	2	contrast	contrast	NOUN
cana-4763	301	3	to	to	ADP
cana-4763	301	4	tumors	tumor	NOUN
cana-4763	301	5	,	,	PUNCT
cana-4763	301	6	which	which	PRON
cana-4763	301	7	have	have	AUX
cana-4763	301	8	increased	increase	VERB
cana-4763	301	9	contrast	contrast	NOUN
cana-4763	301	10	and	and	CCONJ
cana-4763	301	11	entropy	entropy	NOUN
cana-4763	301	12	,	,	PUNCT
cana-4763	301	13	the	the	DET
cana-4763	301	14	"	"	PUNCT
cana-4763	301	15	no	no	DET
cana-4763	301	16	tumor	tumor	NOUN
cana-4763	301	17	"	"	PUNCT
cana-4763	301	18	category	category	NOUN
cana-4763	301	19	typically	typically	ADV
cana-4763	301	20	features	feature	VERB
cana-4763	301	21	smoother	smooth	ADJ
cana-4763	301	22	,	,	PUNCT
cana-4763	301	23	more	more	ADV
cana-4763	301	24	consistent	consistent	ADJ
cana-4763	301	25	textures	texture	NOUN
cana-4763	301	26	.	.	PUNCT
cana-4763	302	1	making	make	VERB
cana-4763	302	2	the	the	DET
cana-4763	302	3	distinction	distinction	NOUN
cana-4763	302	4	is	be	AUX
cana-4763	302	5	crucial	crucial	ADJ
cana-4763	302	6	for	for	ADP
cana-4763	302	7	accurate	accurate	ADJ
cana-4763	302	8	diagnosis	diagnosis	NOUN
cana-4763	302	9	and	and	CCONJ
cana-4763	302	10	effective	effective	ADJ
cana-4763	302	11	treatment	treatment	NOUN
cana-4763	302	12	planning	planning	NOUN
cana-4763	302	13	.	.	PUNCT
cana-4763	303	1	4.3	4.3	NUM
cana-4763	303	2	classification	classification	NOUN
cana-4763	303	3	results	result	NOUN
cana-4763	303	4	1.accuracy	1.accuracy	NUM
cana-4763	303	5	:	:	PUNCT
cana-4763	303	6	one	one	NUM
cana-4763	303	7	important	important	ADJ
cana-4763	303	8	indicator	indicator	NOUN
cana-4763	303	9	for	for	ADP
cana-4763	303	10	assessing	assess	VERB
cana-4763	303	11	a	a	DET
cana-4763	303	12	classification	classification	NOUN
cana-4763	303	13	model	model	NOUN
cana-4763	303	14	's	's	PART
cana-4763	303	15	performance	performance	NOUN
cana-4763	303	16	is	be	AUX
cana-4763	303	17	accuracy	accuracy	NOUN
cana-4763	303	18	.	.	PUNCT
cana-4763	304	1	it	it	PRON
cana-4763	304	2	provides	provide	VERB
cana-4763	304	3	an	an	DET
cana-4763	304	4	overall	overall	ADJ
cana-4763	304	5	assessment	assessment	NOUN
cana-4763	304	6	of	of	ADP
cana-4763	304	7	how	how	SCONJ
cana-4763	304	8	effectively	effectively	ADV
cana-4763	304	9	the	the	DET
cana-4763	304	10	model	model	NOUN
cana-4763	304	11	delivers	deliver	VERB
cana-4763	304	12	valid	valid	ADJ
cana-4763	304	13	predictions	prediction	NOUN
cana-4763	304	14	.	.	PUNCT
cana-4763	305	1	accuracy	accuracy	NOUN
cana-4763	305	2	is	be	AUX
cana-4763	305	3	the	the	DET
cana-4763	305	4	percentage	percentage	NOUN
cana-4763	305	5	of	of	ADP
cana-4763	305	6	correct	correct	ADJ
cana-4763	305	7	predictions	prediction	NOUN
cana-4763	305	8	to	to	ADP
cana-4763	305	9	the	the	DET
cana-4763	305	10	total	total	ADJ
cana-4763	305	11	number	number	NOUN
cana-4763	305	12	of	of	ADP
cana-4763	305	13	input	input	NOUN
cana-4763	305	14	samples	sample	NOUN
cana-4763	305	15	.	.	PUNCT
cana-4763	306	1	:	:	PUNCT
cana-4763	306	2	accuracy=	accuracy=	NUM
cana-4763	306	3	tp+tn+fp+fn	tp+tn+fp+fn	PROPN
cana-4763	306	4	tp+tn	tp+tn	NUM
cana-4763	306	5	…	…	PUNCT
cana-4763	306	6	…	…	PUNCT
cana-4763	306	7	(	(	PUNCT
cana-4763	306	8	30	30	NUM
cana-4763	306	9	)	)	PUNCT
cana-4763	306	10	where	where	SCONJ
cana-4763	306	11	:	:	PUNCT
cana-4763	306	12	tp	tp	NOUN
cana-4763	306	13	=	=	PUNCT
cana-4763	306	14	true	true	ADJ
cana-4763	306	15	positive	positive	ADJ
cana-4763	306	16	tn	tn	NOUN
cana-4763	306	17	=	=	PUNCT
cana-4763	306	18	true	true	ADJ
cana-4763	306	19	negative	negative	ADJ
cana-4763	306	20	fp	fp	X
cana-4763	306	21	=	=	ADJ
cana-4763	306	22	false	false	ADJ
cana-4763	306	23	positive	positive	ADJ
cana-4763	306	24	fn	fn	NOUN
cana-4763	306	25	=	=	X
cana-4763	306	26	false	false	ADJ
cana-4763	306	27	negative	negative	ADJ
cana-4763	306	28	the	the	DET
cana-4763	306	29	proposed	propose	VERB
cana-4763	306	30	method	method	NOUN
cana-4763	306	31	achieved	achieve	VERB
cana-4763	306	32	an	an	DET
cana-4763	306	33	overall	overall	ADJ
cana-4763	306	34	accuracy	accuracy	NOUN
cana-4763	306	35	of	of	ADP
cana-4763	306	36	99.3	99.3	NUM
cana-4763	306	37	%	%	NOUN
cana-4763	306	38	.	.	PUNCT
cana-4763	307	1	comparison	comparison	NOUN
cana-4763	307	2	of	of	ADP
cana-4763	307	3	proposed	propose	VERB
cana-4763	307	4	method	method	NOUN
cana-4763	307	5	with	with	ADP
cana-4763	307	6	existing	exist	VERB
cana-4763	307	7	methods	method	NOUN
cana-4763	307	8	methodology	methodology	NOUN
cana-4763	307	9	accuracy	accuracy	NOUN
cana-4763	307	10	(	(	PUNCT
cana-4763	307	11	in	in	ADP
cana-4763	307	12	%	%	NOUN
cana-4763	307	13	)	)	PUNCT
cana-4763	307	14	extreme	extreme	ADJ
cana-4763	307	15	learning	learning	NOUN
cana-4763	307	16	machine	machine	NOUN
cana-4763	307	17	local	local	ADJ
cana-4763	307	18	receptive	receptive	ADJ
cana-4763	307	19	fields[27	fields[27	NOUN
cana-4763	307	20	]	]	PUNCT
cana-4763	307	21	97.18	97.18	NUM
cana-4763	307	22	cnn[28	cnn[28	X
cana-4763	307	23	]	]	X
cana-4763	307	24	98.93	98.93	NUM
cana-4763	307	25	vgg16	vgg16	NOUN
cana-4763	307	26	[	[	NOUN
cana-4763	307	27	29	29	NUM
cana-4763	307	28	]	]	SYM
cana-4763	307	29	98.69	98.69	NUM
cana-4763	307	30	deep	deep	ADJ
cana-4763	307	31	convolutional	convolutional	ADJ
cana-4763	307	32	neural	neural	ADJ
cana-4763	307	33	network	network	NOUN
cana-4763	307	34	[	[	X
cana-4763	307	35	30	30	NUM
cana-4763	307	36	]	]	SYM
cana-4763	307	37	97.3	97.3	NUM
cana-4763	307	38	alexnet	alexnet	ADJ
cana-4763	307	39	cnn	cnn	PROPN
cana-4763	308	1	[	[	X
cana-4763	308	2	31	31	NUM
cana-4763	308	3	]	]	PUNCT
cana-4763	308	4	98.15	98.15	NUM
cana-4763	308	5	rf+svm	rf+svm	PROPN
cana-4763	308	6	(	(	PUNCT
cana-4763	308	7	proposed	propose	VERB
cana-4763	308	8	method	method	NOUN
cana-4763	308	9	)	)	PUNCT
cana-4763	308	10	99.3	99.3	NUM
cana-4763	308	11	table	table	NOUN
cana-4763	308	12	2	2	NUM
cana-4763	308	13	:	:	PUNCT
cana-4763	308	14	comparison	comparison	NOUN
cana-4763	308	15	of	of	ADP
cana-4763	308	16	proposed	propose	VERB
cana-4763	308	17	method	method	NOUN
cana-4763	308	18	with	with	ADP
cana-4763	308	19	other	other	ADJ
cana-4763	308	20	methods	method	NOUN
cana-4763	308	21	communications	communication	NOUN
cana-4763	308	22	on	on	ADP
cana-4763	308	23	applied	apply	VERB
cana-4763	308	24	nonlinear	nonlinear	ADJ
cana-4763	308	25	analysis	analysis	NOUN
cana-4763	308	26	issn	issn	NOUN
cana-4763	308	27	:	:	PUNCT
cana-4763	308	28	1074	1074	NUM
cana-4763	308	29	-	-	PUNCT
cana-4763	308	30	133x	133x	NUM
cana-4763	308	31	vol	vol	VERB
cana-4763	308	32	32	32	NUM
cana-4763	308	33	no	no	NOUN
cana-4763	308	34	.	.	PUNCT
cana-4763	309	1	10s	10	NOUN
cana-4763	309	2	(	(	PUNCT
cana-4763	309	3	2025	2025	NUM
cana-4763	309	4	)	)	PUNCT
cana-4763	309	5	309	309	NUM
cana-4763	309	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	309	7	fig	fig	NOUN
cana-4763	309	8	4	4	NUM
cana-4763	309	9	:	:	PUNCT
cana-4763	309	10	accuracy	accuracy	NOUN
cana-4763	309	11	plot	plot	NOUN
cana-4763	309	12	of	of	ADP
cana-4763	309	13	the	the	DET
cana-4763	309	14	classifier	classifier	NOUN
cana-4763	309	15	2	2	NUM
cana-4763	309	16	.	.	PUNCT
cana-4763	309	17	precision	precision	NOUN
cana-4763	309	18	,	,	PUNCT
cana-4763	309	19	recall	recall	PROPN
cana-4763	309	20	&	&	CCONJ
cana-4763	309	21	f1	f1	PROPN
cana-4763	309	22	-	-	PUNCT
cana-4763	309	23	score	score	NOUN
cana-4763	309	24	(	(	PUNCT
cana-4763	309	25	per	per	ADP
cana-4763	309	26	class	class	NOUN
cana-4763	309	27	)	)	PUNCT
cana-4763	309	28	for	for	ADP
cana-4763	309	29	multi	multi	ADJ
cana-4763	309	30	-	-	ADJ
cana-4763	309	31	class	class	ADJ
cana-4763	309	32	classification	classification	NOUN
cana-4763	309	33	,	,	PUNCT
cana-4763	309	34	we	we	PRON
cana-4763	309	35	compute	compute	VERB
cana-4763	309	36	precision	precision	NOUN
cana-4763	309	37	,	,	PUNCT
cana-4763	309	38	recall	recall	NOUN
cana-4763	309	39	,	,	PUNCT
cana-4763	309	40	and	and	CCONJ
cana-4763	309	41	f1	f1	NOUN
cana-4763	309	42	-	-	PUNCT
cana-4763	309	43	score	score	NOUN
cana-4763	309	44	for	for	ADP
cana-4763	309	45	each	each	DET
cana-4763	309	46	class	class	NOUN
cana-4763	309	47	separately	separately	ADV
cana-4763	309	48	.	.	PUNCT
cana-4763	310	1	precision	precision	NOUN
cana-4763	310	2	(	(	PUNCT
cana-4763	310	3	positive	positive	ADJ
cana-4763	310	4	predictive	predictive	ADJ
cana-4763	310	5	value	value	NOUN
cana-4763	310	6	)	)	PUNCT
cana-4763	310	7	precision=	precision=	NUM
cana-4763	310	8	𝑇𝑃	𝑇𝑃	NOUN
cana-4763	310	9	𝑇𝑃+𝐹𝑃	𝑇𝑃+𝐹𝑃	NOUN
cana-4763	310	10	•	•	NOUN
cana-4763	310	11	calculates	calculate	VERB
cana-4763	310	12	the	the	DET
cana-4763	310	13	percentage	percentage	NOUN
cana-4763	310	14	of	of	ADP
cana-4763	310	15	predicted	predict	VERB
cana-4763	310	16	positive	positive	ADJ
cana-4763	310	17	cases	case	NOUN
cana-4763	310	18	that	that	PRON
cana-4763	310	19	were	be	AUX
cana-4763	310	20	true	true	ADJ
cana-4763	310	21	.	.	PUNCT
cana-4763	311	1	•	•	NUM
cana-4763	311	2	high	high	ADJ
cana-4763	311	3	precision	precision	NOUN
cana-4763	311	4	means	mean	VERB
cana-4763	311	5	low	low	ADJ
cana-4763	311	6	false	false	ADJ
cana-4763	311	7	positives	positive	NOUN
cana-4763	311	8	recall	recall	NOUN
cana-4763	311	9	(	(	PUNCT
cana-4763	311	10	sensitivity	sensitivity	NOUN
cana-4763	311	11	,	,	PUNCT
cana-4763	311	12	true	true	ADJ
cana-4763	311	13	positive	positive	ADJ
cana-4763	311	14	rate	rate	NOUN
cana-4763	311	15	)	)	PUNCT
cana-4763	311	16	recall=	recall=	NUM
cana-4763	311	17	𝑇𝑃	𝑇𝑃	NOUN
cana-4763	311	18	𝑇𝑃+𝐹𝑁	𝑇𝑃+𝐹𝑁	NOUN
cana-4763	311	19	•	•	NOUN
cana-4763	311	20	measures	measure	NOUN
cana-4763	311	21	how	how	SCONJ
cana-4763	311	22	many	many	ADJ
cana-4763	311	23	actual	actual	ADJ
cana-4763	311	24	positive	positive	ADJ
cana-4763	311	25	cases	case	NOUN
cana-4763	311	26	were	be	AUX
cana-4763	311	27	correctly	correctly	ADV
cana-4763	311	28	identified	identify	VERB
cana-4763	311	29	.	.	PUNCT
cana-4763	312	1	•	•	NUM
cana-4763	312	2	high	high	ADJ
cana-4763	312	3	recall	recall	NOUN
cana-4763	312	4	means	mean	VERB
cana-4763	312	5	low	low	ADJ
cana-4763	312	6	false	false	ADJ
cana-4763	312	7	negatives	negative	NOUN
cana-4763	312	8	.	.	PUNCT
cana-4763	313	1	f1	f1	NOUN
cana-4763	313	2	-	-	PUNCT
cana-4763	313	3	score	score	NOUN
cana-4763	313	4	(	(	PUNCT
cana-4763	313	5	harmonic	harmonic	ADJ
cana-4763	313	6	mean	mean	NOUN
cana-4763	313	7	of	of	ADP
cana-4763	313	8	precision	precision	NOUN
cana-4763	313	9	&	&	CCONJ
cana-4763	313	10	recall	recall	PROPN
cana-4763	313	11	)	)	PUNCT
cana-4763	313	12	f1=	f1=	PROPN
cana-4763	313	13	2	2	NUM
cana-4763	313	14	x	x	NOUN
cana-4763	313	15	precision×recall	precision×recall	NOUN
cana-4763	313	16	precision+recall	precision+recall	PROPN
cana-4763	313	17	…	…	PUNCT
cana-4763	313	18	(	(	PUNCT
cana-4763	313	19	31	31	NUM
cana-4763	313	20	)	)	PUNCT
cana-4763	313	21	•	•	NOUN
cana-4763	313	22	balances	balance	NOUN
cana-4763	313	23	precision	precision	NOUN
cana-4763	313	24	and	and	CCONJ
cana-4763	313	25	recall	recall	NOUN
cana-4763	313	26	.	.	PUNCT
cana-4763	314	1	•	•	NUM
cana-4763	314	2	useful	useful	ADJ
cana-4763	314	3	when	when	SCONJ
cana-4763	314	4	misclassification	misclassification	NOUN
cana-4763	314	5	has	have	VERB
cana-4763	314	6	consequences	consequence	NOUN
cana-4763	314	7	(	(	PUNCT
cana-4763	314	8	e.g.	e.g.	ADV
cana-4763	314	9	,	,	PUNCT
cana-4763	314	10	failing	fail	VERB
cana-4763	314	11	to	to	PART
cana-4763	314	12	detect	detect	VERB
cana-4763	314	13	a	a	DET
cana-4763	314	14	tumor	tumor	NOUN
cana-4763	314	15	)	)	PUNCT
cana-4763	314	16	.	.	PUNCT
cana-4763	315	1	metric	metric	ADJ
cana-4763	315	2	glioma	glioma	NOUN
cana-4763	315	3	meningioma	meningioma	NOUN
cana-4763	315	4	pituitary	pituitary	NOUN
cana-4763	315	5	no	no	DET
cana-4763	315	6	tumor	tumor	NOUN
cana-4763	315	7	precision	precision	NOUN
cana-4763	315	8	0.992	0.992	NUM
cana-4763	315	9	.980	.980	NUM
cana-4763	315	10	1	1	NUM
cana-4763	315	11	1	1	NUM
cana-4763	315	12	recall	recall	VERB
cana-4763	315	13	0.992	0.992	NUM
cana-4763	315	14	1	1	NUM
cana-4763	315	15	1	1	NUM
cana-4763	315	16	0.989	0.989	NUM
cana-4763	315	17	f1	f1	NOUN
cana-4763	315	18	-	-	PUNCT
cana-4763	315	19	score	score	NOUN
cana-4763	315	20	0.992	0.992	NUM
cana-4763	315	21	0.989	0.989	NUM
cana-4763	315	22	1	1	NUM
cana-4763	315	23	0.994	0.994	NUM
cana-4763	315	24	table	table	NOUN
cana-4763	315	25	3	3	NUM
cana-4763	315	26	:	:	PUNCT
cana-4763	315	27	output	output	NOUN
cana-4763	315	28	of	of	ADP
cana-4763	315	29	the	the	DET
cana-4763	315	30	evaluation	evaluation	NOUN
cana-4763	315	31	metrics	metric	NOUN
cana-4763	315	32	3	3	NUM
cana-4763	315	33	.	.	PUNCT
cana-4763	315	34	confusion	confusion	NOUN
cana-4763	315	35	matrix	matrix	NOUN
cana-4763	315	36	(	(	PUNCT
cana-4763	315	37	multi	multi	ADJ
cana-4763	315	38	-	-	ADJ
cana-4763	315	39	class	class	ADJ
cana-4763	315	40	evaluation	evaluation	NOUN
cana-4763	315	41	)	)	PUNCT
cana-4763	315	42	a	a	DET
cana-4763	315	43	confusion	confusion	NOUN
cana-4763	315	44	matrix	matrix	NOUN
cana-4763	315	45	shows	show	VERB
cana-4763	315	46	how	how	SCONJ
cana-4763	315	47	well	well	ADV
cana-4763	315	48	a	a	DET
cana-4763	315	49	classification	classification	NOUN
cana-4763	315	50	algorithm	algorithm	NOUN
cana-4763	315	51	performs	perform	VERB
cana-4763	315	52	.	.	PUNCT
cana-4763	316	1	the	the	DET
cana-4763	316	2	efficacy	efficacy	NOUN
cana-4763	316	3	of	of	ADP
cana-4763	316	4	a	a	DET
cana-4763	316	5	classification	classification	NOUN
cana-4763	316	6	system	system	NOUN
cana-4763	316	7	is	be	AUX
cana-4763	316	8	summarized	summarize	VERB
cana-4763	316	9	and	and	CCONJ
cana-4763	316	10	visually	visually	ADV
cana-4763	316	11	represented	represent	VERB
cana-4763	316	12	by	by	ADP
cana-4763	316	13	a	a	DET
cana-4763	316	14	confusion	confusion	NOUN
cana-4763	316	15	matrix	matrix	NOUN
cana-4763	316	16	.	.	PUNCT
cana-4763	317	1	communications	communication	NOUN
cana-4763	317	2	on	on	ADP
cana-4763	317	3	applied	apply	VERB
cana-4763	317	4	nonlinear	nonlinear	ADJ
cana-4763	317	5	analysis	analysis	NOUN
cana-4763	317	6	issn	issn	NOUN
cana-4763	317	7	:	:	PUNCT
cana-4763	317	8	1074	1074	NUM
cana-4763	317	9	-	-	PUNCT
cana-4763	317	10	133x	133x	NUM
cana-4763	317	11	vol	vol	VERB
cana-4763	317	12	32	32	NUM
cana-4763	317	13	no	no	NOUN
cana-4763	317	14	.	.	PUNCT
cana-4763	318	1	10s	10	NOUN
cana-4763	318	2	(	(	PUNCT
cana-4763	318	3	2025	2025	NUM
cana-4763	318	4	)	)	PUNCT
cana-4763	318	5	310	310	NUM
cana-4763	318	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	318	7	fig	fig	NOUN
cana-4763	318	8	5	5	NUM
cana-4763	318	9	:	:	PUNCT
cana-4763	318	10	confusion	confusion	NOUN
cana-4763	318	11	matrix	matrix	NOUN
cana-4763	318	12	5	5	NUM
cana-4763	318	13	.	.	PUNCT
cana-4763	318	14	conclusion	conclusion	NOUN
cana-4763	318	15	and	and	CCONJ
cana-4763	318	16	future	future	ADJ
cana-4763	318	17	work	work	NOUN
cana-4763	318	18	with	with	ADP
cana-4763	318	19	efficient	efficient	ADJ
cana-4763	318	20	preprocessing	preprocessing	NOUN
cana-4763	318	21	,	,	PUNCT
cana-4763	318	22	feature	feature	NOUN
cana-4763	318	23	extraction	extraction	NOUN
cana-4763	318	24	,	,	PUNCT
cana-4763	318	25	optimization	optimization	NOUN
cana-4763	318	26	,	,	PUNCT
cana-4763	318	27	and	and	CCONJ
cana-4763	318	28	classification	classification	NOUN
cana-4763	318	29	algorithms	algorithm	NOUN
cana-4763	318	30	in	in	ADP
cana-4763	318	31	combination	combination	NOUN
cana-4763	318	32	,	,	PUNCT
cana-4763	318	33	our	our	PRON
cana-4763	318	34	approach	approach	NOUN
cana-4763	318	35	offers	offer	VERB
cana-4763	318	36	a	a	DET
cana-4763	318	37	consistent	consistent	ADJ
cana-4763	318	38	and	and	CCONJ
cana-4763	318	39	robust	robust	ADJ
cana-4763	318	40	brain	brain	NOUN
cana-4763	318	41	tumor	tumor	NOUN
cana-4763	318	42	classifier	classifier	NOUN
cana-4763	318	43	.	.	PUNCT
cana-4763	319	1	texture	texture	NOUN
cana-4763	319	2	-	-	PUNCT
cana-4763	319	3	based	base	VERB
cana-4763	319	4	feature	feature	NOUN
cana-4763	319	5	extraction	extraction	NOUN
cana-4763	319	6	is	be	AUX
cana-4763	319	7	achieved	achieve	VERB
cana-4763	319	8	by	by	ADP
cana-4763	319	9	local	local	ADJ
cana-4763	319	10	binary	binary	ADJ
cana-4763	319	11	patterns	pattern	NOUN
cana-4763	319	12	(	(	PUNCT
cana-4763	319	13	lbp	lbp	PROPN
cana-4763	319	14	)	)	PUNCT
cana-4763	319	15	,	,	PUNCT
cana-4763	319	16	grey	grey	ADJ
cana-4763	319	17	wolf	wolf	PROPN
cana-4763	319	18	optimization	optimization	NOUN
cana-4763	319	19	(	(	PUNCT
cana-4763	319	20	gwo	gwo	PROPN
cana-4763	319	21	)	)	PUNCT
cana-4763	319	22	for	for	ADP
cana-4763	319	23	optimal	optimal	ADJ
cana-4763	319	24	feature	feature	NOUN
cana-4763	319	25	selection	selection	NOUN
cana-4763	319	26	,	,	PUNCT
cana-4763	319	27	and	and	CCONJ
cana-4763	319	28	a	a	DET
cana-4763	319	29	hybrid	hybrid	ADJ
cana-4763	319	30	model	model	NOUN
cana-4763	319	31	with	with	ADP
cana-4763	319	32	random	random	ADJ
cana-4763	319	33	forest	forest	NOUN
cana-4763	319	34	(	(	PUNCT
cana-4763	319	35	rf	rf	NOUN
cana-4763	319	36	)	)	PUNCT
cana-4763	319	37	and	and	CCONJ
cana-4763	319	38	support	support	VERB
cana-4763	319	39	vector	vector	NOUN
cana-4763	319	40	machine	machine	NOUN
cana-4763	319	41	(	(	PUNCT
cana-4763	319	42	svm	svm	ADJ
cana-4763	319	43	)	)	PUNCT
cana-4763	319	44	classifiers.bilateral	classifiers.bilateral	ADJ
cana-4763	319	45	filtering	filtering	NOUN
cana-4763	319	46	is	be	AUX
cana-4763	319	47	applied	apply	VERB
cana-4763	319	48	for	for	ADP
cana-4763	319	49	noise	noise	NOUN
cana-4763	319	50	reduction	reduction	NOUN
cana-4763	319	51	and	and	CCONJ
cana-4763	319	52	image	image	NOUN
cana-4763	319	53	enhancement	enhancement	NOUN
cana-4763	319	54	.	.	PUNCT
cana-4763	320	1	this	this	DET
cana-4763	320	2	combination	combination	NOUN
cana-4763	320	3	has	have	VERB
cana-4763	320	4	a	a	DET
cana-4763	320	5	high	high	ADJ
cana-4763	320	6	classification	classification	NOUN
cana-4763	320	7	rate	rate	NOUN
cana-4763	320	8	of	of	ADP
cana-4763	320	9	99.3	99.3	NUM
cana-4763	320	10	%	%	NOUN
cana-4763	320	11	,	,	PUNCT
cana-4763	320	12	making	make	VERB
cana-4763	320	13	it	it	PRON
cana-4763	320	14	a	a	DET
cana-4763	320	15	promising	promising	ADJ
cana-4763	320	16	tool	tool	NOUN
cana-4763	320	17	for	for	ADP
cana-4763	320	18	automating	automate	VERB
cana-4763	320	19	brain	brain	NOUN
cana-4763	320	20	tumor	tumor	NOUN
cana-4763	320	21	diagnosis	diagnosis	NOUN
cana-4763	320	22	.	.	PUNCT
cana-4763	321	1	by	by	ADP
cana-4763	321	2	using	use	VERB
cana-4763	321	3	these	these	DET
cana-4763	321	4	state	state	NOUN
cana-4763	321	5	-	-	PUNCT
cana-4763	321	6	of	of	ADP
cana-4763	321	7	-	-	PUNCT
cana-4763	321	8	the	the	DET
cana-4763	321	9	-	-	PUNCT
cana-4763	321	10	art	art	NOUN
cana-4763	321	11	techniques	technique	NOUN
cana-4763	321	12	,	,	PUNCT
cana-4763	321	13	the	the	DET
cana-4763	321	14	diagnosis	diagnosis	NOUN
cana-4763	321	15	process	process	NOUN
cana-4763	321	16	is	be	AUX
cana-4763	321	17	streamlined	streamline	VERB
cana-4763	321	18	and	and	CCONJ
cana-4763	321	19	the	the	DET
cana-4763	321	20	possibility	possibility	NOUN
cana-4763	321	21	of	of	ADP
cana-4763	321	22	human	human	ADJ
cana-4763	321	23	error	error	NOUN
cana-4763	321	24	is	be	AUX
cana-4763	321	25	decreased	decrease	VERB
cana-4763	321	26	,	,	PUNCT
cana-4763	321	27	enabling	enable	VERB
cana-4763	321	28	quicker	quick	ADV
cana-4763	321	29	and	and	CCONJ
cana-4763	321	30	more	more	ADV
cana-4763	321	31	accurate	accurate	ADJ
cana-4763	321	32	treatment	treatment	NOUN
cana-4763	321	33	decisions	decision	NOUN
cana-4763	321	34	.	.	PUNCT
cana-4763	322	1	through	through	ADP
cana-4763	322	2	effective	effective	ADJ
cana-4763	322	3	and	and	CCONJ
cana-4763	322	4	timely	timely	ADJ
cana-4763	322	5	identification	identification	NOUN
cana-4763	322	6	of	of	ADP
cana-4763	322	7	tumors	tumor	NOUN
cana-4763	322	8	,	,	PUNCT
cana-4763	322	9	this	this	DET
cana-4763	322	10	great	great	ADJ
cana-4763	322	11	development	development	NOUN
cana-4763	322	12	in	in	ADP
cana-4763	322	13	medical	medical	ADJ
cana-4763	322	14	science	science	NOUN
cana-4763	322	15	can	can	AUX
cana-4763	322	16	benefit	benefit	VERB
cana-4763	322	17	the	the	DET
cana-4763	322	18	patient	patient	NOUN
cana-4763	322	19	.	.	PUNCT
cana-4763	323	1	as	as	SCONJ
cana-4763	323	2	science	science	NOUN
cana-4763	323	3	moves	move	VERB
cana-4763	323	4	forward	forward	ADV
cana-4763	323	5	,	,	PUNCT
cana-4763	323	6	more	more	ADV
cana-4763	323	7	effective	effective	ADJ
cana-4763	323	8	outcomes	outcome	NOUN
cana-4763	323	9	from	from	ADP
cana-4763	323	10	early	early	ADJ
cana-4763	323	11	diagnosis	diagnosis	NOUN
cana-4763	323	12	and	and	CCONJ
cana-4763	323	13	detection	detection	NOUN
cana-4763	323	14	of	of	ADP
cana-4763	323	15	brain	brain	NOUN
cana-4763	323	16	cancers	cancer	NOUN
cana-4763	323	17	may	may	AUX
cana-4763	323	18	become	become	VERB
cana-4763	323	19	available	available	ADJ
cana-4763	323	20	from	from	ADP
cana-4763	323	21	improvements	improvement	NOUN
cana-4763	323	22	in	in	ADP
cana-4763	323	23	these	these	DET
cana-4763	323	24	methods	method	NOUN
cana-4763	323	25	.	.	PUNCT
cana-4763	324	1	though	though	SCONJ
cana-4763	324	2	the	the	DET
cana-4763	324	3	present	present	ADJ
cana-4763	324	4	outcome	outcome	NOUN
cana-4763	324	5	is	be	AUX
cana-4763	324	6	promising	promise	VERB
cana-4763	324	7	,	,	PUNCT
cana-4763	324	8	there	there	PRON
cana-4763	324	9	are	be	VERB
cana-4763	324	10	several	several	ADJ
cana-4763	324	11	things	thing	NOUN
cana-4763	324	12	we	we	PRON
cana-4763	324	13	can	can	AUX
cana-4763	324	14	do	do	VERB
cana-4763	324	15	to	to	PART
cana-4763	324	16	improve	improve	VERB
cana-4763	324	17	the	the	DET
cana-4763	324	18	effectiveness	effectiveness	NOUN
cana-4763	324	19	of	of	ADP
cana-4763	324	20	this	this	DET
cana-4763	324	21	method	method	NOUN
cana-4763	324	22	and	and	CCONJ
cana-4763	324	23	make	make	VERB
cana-4763	324	24	it	it	PRON
cana-4763	324	25	suitable	suitable	ADJ
cana-4763	324	26	for	for	ADP
cana-4763	324	27	application	application	NOUN
cana-4763	324	28	in	in	ADP
cana-4763	324	29	actual	actual	ADJ
cana-4763	324	30	clinical	clinical	ADJ
cana-4763	324	31	contexts	contexts	NOUN
cana-4763	324	32	.	.	PUNCT
cana-4763	325	1	references	reference	NOUN
cana-4763	325	2	:	:	PUNCT
cana-4763	326	1	[	[	X
cana-4763	326	2	1	1	X
cana-4763	326	3	]	]	X
cana-4763	326	4	mohsen	mohsen	PROPN
cana-4763	326	5	ghorbian	ghorbian	PROPN
cana-4763	326	6	,	,	PUNCT
cana-4763	326	7	saeid	saeid	PROPN
cana-4763	326	8	ghorbian	ghorbian	PROPN
cana-4763	326	9	,	,	PUNCT
cana-4763	326	10	mostafa	mostafa	PROPN
cana-4763	326	11	ghobaei	ghobaei	PROPN
cana-4763	326	12	-	-	PUNCT
cana-4763	326	13	arani	arani	PROPN
cana-4763	326	14	,	,	PUNCT
cana-4763	326	15	“	"	PUNCT
cana-4763	326	16	a	a	DET
cana-4763	326	17	comprehensive	comprehensive	ADJ
cana-4763	326	18	review	review	NOUN
cana-4763	326	19	on	on	ADP
cana-4763	326	20	machine	machine	NOUN
cana-4763	326	21	learning	learning	NOUN
cana-4763	326	22	in	in	ADP
cana-4763	326	23	brain	brain	NOUN
cana-4763	326	24	tumor	tumor	NOUN
cana-4763	326	25	classification	classification	NOUN
cana-4763	326	26	:	:	PUNCT
cana-4763	326	27	taxonomy	taxonomy	NOUN
cana-4763	326	28	,	,	PUNCT
cana-4763	326	29	challenges	challenge	NOUN
cana-4763	326	30	,	,	PUNCT
cana-4763	326	31	and	and	CCONJ
cana-4763	326	32	future	future	ADJ
cana-4763	326	33	trends	trend	NOUN
cana-4763	326	34	,	,	PUNCT
cana-4763	326	35	biomedical	biomedical	ADJ
cana-4763	326	36	signal	signal	NOUN
cana-4763	326	37	processing	processing	NOUN
cana-4763	326	38	and	and	CCONJ
cana-4763	326	39	control	control	NOUN
cana-4763	326	40	,	,	PUNCT
cana-4763	326	41	volume	volume	NOUN
cana-4763	326	42	98	98	NUM
cana-4763	326	43	,	,	PUNCT
cana-4763	326	44	106774	106774	NUM
cana-4763	326	45	,	,	PUNCT
cana-4763	326	46	issn	issn	PROPN
cana-4763	326	47	1746	1746	NUM
cana-4763	326	48	-	-	PUNCT
cana-4763	326	49	8094,2024	8094,2024	NUM
cana-4763	326	50	.	.	PUNCT
cana-4763	327	1	[	[	X
cana-4763	327	2	2	2	NUM
cana-4763	327	3	]	]	X
cana-4763	327	4	ali	ali	PROPN
cana-4763	327	5	işın	işın	PROPN
cana-4763	327	6	,	,	PUNCT
cana-4763	327	7	cem	cem	NOUN
cana-4763	327	8	direkoğlu	direkoğlu	NOUN
cana-4763	327	9	,	,	PUNCT
cana-4763	327	10	melike	melike	NOUN
cana-4763	327	11	şah	şah	NOUN
cana-4763	327	12	,	,	PUNCT
cana-4763	327	13	review	review	NOUN
cana-4763	327	14	of	of	ADP
cana-4763	327	15	mri	mri	NOUN
cana-4763	327	16	-	-	PUNCT
cana-4763	327	17	based	base	VERB
cana-4763	327	18	brain	brain	NOUN
cana-4763	327	19	tumor	tumor	NOUN
cana-4763	327	20	image	image	NOUN
cana-4763	327	21	segmentation	segmentation	NOUN
cana-4763	327	22	using	use	VERB
cana-4763	327	23	deep	deep	ADJ
cana-4763	327	24	learning	learning	NOUN
cana-4763	327	25	methods	method	NOUN
cana-4763	327	26	,	,	PUNCT
cana-4763	327	27	procedia	procedia	NOUN
cana-4763	327	28	computer	computer	NOUN
cana-4763	327	29	science	science	NOUN
cana-4763	327	30	,	,	PUNCT
cana-4763	327	31	volume	volume	NOUN
cana-4763	327	32	102	102	NUM
cana-4763	327	33	,	,	PUNCT
cana-4763	327	34	2016	2016	NUM
cana-4763	327	35	,	,	PUNCT
cana-4763	327	36	pages	page	NOUN
cana-4763	327	37	317	317	NUM
cana-4763	327	38	-	-	SYM
cana-4763	327	39	324	324	NUM
cana-4763	327	40	,	,	PUNCT
cana-4763	327	41	issn	issn	PROPN
cana-4763	327	42	18770509	18770509	NUM
cana-4763	327	43	,	,	PUNCT
cana-4763	327	44	2016	2016	NUM
cana-4763	327	45	.	.	PUNCT
cana-4763	328	1	[	[	X
cana-4763	328	2	3	3	X
cana-4763	328	3	]	]	X
cana-4763	328	4	maria	maria	PROPN
cana-4763	328	5	nazir	nazir	PROPN
cana-4763	328	6	,	,	PUNCT
cana-4763	328	7	sadia	sadia	PROPN
cana-4763	328	8	shakil	shakil	PROPN
cana-4763	328	9	,	,	PUNCT
cana-4763	328	10	khurram	khurram	PROPN
cana-4763	328	11	khurshid	khurshid	PROPN
cana-4763	328	12	,	,	PUNCT
cana-4763	328	13	role	role	NOUN
cana-4763	328	14	of	of	ADP
cana-4763	328	15	deep	deep	ADJ
cana-4763	328	16	learning	learning	NOUN
cana-4763	328	17	in	in	ADP
cana-4763	328	18	brain	brain	NOUN
cana-4763	328	19	tumor	tumor	NOUN
cana-4763	328	20	detection	detection	NOUN
cana-4763	328	21	and	and	CCONJ
cana-4763	328	22	classification	classification	NOUN
cana-4763	328	23	(	(	PUNCT
cana-4763	328	24	2015	2015	NUM
cana-4763	328	25	to	to	ADP
cana-4763	328	26	2020	2020	NUM
cana-4763	328	27	):	):	PUNCT
cana-4763	328	28	a	a	DET
cana-4763	328	29	review	review	NOUN
cana-4763	328	30	,	,	PUNCT
cana-4763	328	31	computerized	computerized	ADJ
cana-4763	328	32	medical	medical	ADJ
cana-4763	328	33	imaging	imaging	NOUN
cana-4763	328	34	and	and	CCONJ
cana-4763	328	35	graphics	graphic	NOUN
cana-4763	328	36	,	,	PUNCT
cana-4763	328	37	volume	volume	NOUN
cana-4763	328	38	91	91	NUM
cana-4763	328	39	,	,	PUNCT
cana-4763	328	40	101940	101940	NUM
cana-4763	328	41	,	,	PUNCT
cana-4763	328	42	issn	issn	PROPN
cana-4763	328	43	0895	0895	NUM
cana-4763	328	44	-	-	PUNCT
cana-4763	328	45	6111,2021	6111,2021	NUM
cana-4763	328	46	.	.	PUNCT
cana-4763	329	1	[	[	X
cana-4763	329	2	4	4	NUM
cana-4763	329	3	]	]	X
cana-4763	329	4	geethu	geethu	PROPN
cana-4763	329	5	mohan	mohan	PROPN
cana-4763	329	6	,	,	PUNCT
cana-4763	329	7	m.	m.	NOUN
cana-4763	329	8	monica	monica	PROPN
cana-4763	329	9	subashini	subashini	PROPN
cana-4763	329	10	,	,	PUNCT
cana-4763	329	11	mri	mri	NOUN
cana-4763	329	12	based	base	VERB
cana-4763	329	13	medical	medical	ADJ
cana-4763	329	14	image	image	NOUN
cana-4763	329	15	analysis	analysis	NOUN
cana-4763	329	16	:	:	PUNCT
cana-4763	329	17	survey	survey	NOUN
cana-4763	329	18	on	on	ADP
cana-4763	329	19	brain	brain	NOUN
cana-4763	329	20	tumor	tumor	NOUN
cana-4763	329	21	grade	grade	NOUN
cana-4763	329	22	classification	classification	NOUN
cana-4763	329	23	,	,	PUNCT
cana-4763	329	24	biomedical	biomedical	ADJ
cana-4763	329	25	signal	signal	NOUN
cana-4763	329	26	processing	processing	NOUN
cana-4763	329	27	and	and	CCONJ
cana-4763	329	28	control	control	NOUN
cana-4763	329	29	,	,	PUNCT
cana-4763	329	30	volume	volume	NOUN
cana-4763	329	31	39	39	NUM
cana-4763	329	32	,	,	PUNCT
cana-4763	329	33	pages	page	NOUN
cana-4763	329	34	139	139	NUM
cana-4763	329	35	-	-	SYM
cana-4763	329	36	161	161	NUM
cana-4763	329	37	,	,	PUNCT
cana-4763	329	38	issn	issn	PROPN
cana-4763	329	39	1746	1746	NUM
cana-4763	329	40	-	-	SYM
cana-4763	329	41	8094	8094	NUM
cana-4763	329	42	,	,	PUNCT
cana-4763	329	43	2018	2018	NUM
cana-4763	329	44	.	.	PUNCT
cana-4763	330	1	[	[	X
cana-4763	330	2	5	5	NUM
cana-4763	330	3	]	]	X
cana-4763	330	4	vidyarthi	vidyarthi	PROPN
cana-4763	330	5	,	,	PUNCT
cana-4763	330	6	a.	a.	NOUN
cana-4763	330	7	,	,	PUNCT
cana-4763	330	8	mittal	mittal	PROPN
cana-4763	330	9	,	,	PUNCT
cana-4763	330	10	n.	n.	ADJ
cana-4763	330	11	comparative	comparative	ADJ
cana-4763	330	12	study	study	NOUN
cana-4763	330	13	for	for	ADP
cana-4763	330	14	brain	brain	NOUN
cana-4763	330	15	tumor	tumor	NOUN
cana-4763	330	16	classification	classification	NOUN
cana-4763	330	17	on	on	ADP
cana-4763	330	18	mr	mr	PROPN
cana-4763	330	19	/	/	SYM
cana-4763	330	20	ct	ct	PROPN
cana-4763	330	21	images	image	NOUN
cana-4763	330	22	.	.	PUNCT
cana-4763	331	1	in	in	ADP
cana-4763	331	2	:	:	PUNCT
cana-4763	331	3	pant	pant	NOUN
cana-4763	331	4	,	,	PUNCT
cana-4763	331	5	m.	m.	NOUN
cana-4763	331	6	,	,	PUNCT
cana-4763	331	7	deep	deep	ADJ
cana-4763	331	8	,	,	PUNCT
cana-4763	331	9	k.	k.	NOUN
cana-4763	331	10	,	,	PUNCT
cana-4763	331	11	nagar	nagar	PROPN
cana-4763	331	12	,	,	PUNCT
cana-4763	331	13	a.	a.	NOUN
cana-4763	331	14	,	,	PUNCT
cana-4763	331	15	bansal	bansal	NOUN
cana-4763	331	16	,	,	PUNCT
cana-4763	331	17	j.	j.	PROPN
cana-4763	331	18	(	(	PUNCT
cana-4763	331	19	eds	ed	NOUN
cana-4763	331	20	)	)	PUNCT
cana-4763	331	21	proceedings	proceeding	NOUN
cana-4763	331	22	of	of	ADP
cana-4763	331	23	the	the	DET
cana-4763	331	24	third	third	ADJ
cana-4763	331	25	international	international	ADJ
cana-4763	331	26	conference	conference	NOUN
cana-4763	331	27	on	on	ADP
cana-4763	331	28	soft	soft	ADJ
cana-4763	331	29	computing	computing	NOUN
cana-4763	331	30	for	for	ADP
cana-4763	331	31	problem	problem	NOUN
cana-4763	331	32	solving	solving	NOUN
cana-4763	331	33	.	.	PUNCT
cana-4763	332	1	advances	advance	NOUN
cana-4763	332	2	in	in	ADP
cana-4763	332	3	intelligent	intelligent	ADJ
cana-4763	332	4	systems	system	NOUN
cana-4763	332	5	and	and	CCONJ
cana-4763	332	6	computing	computing	NOUN
cana-4763	332	7	,	,	PUNCT
cana-4763	332	8	vol	vol	NOUN
cana-4763	332	9	258	258	NUM
cana-4763	332	10	.	.	PUNCT
cana-4763	332	11	springer	springer	NOUN
cana-4763	332	12	,	,	PUNCT
cana-4763	332	13	new	new	PROPN
cana-4763	332	14	delhi	delhi	PROPN
cana-4763	332	15	,	,	PUNCT
cana-4763	332	16	2014	2014	NUM
cana-4763	332	17	.	.	PUNCT
cana-4763	333	1	[	[	X
cana-4763	333	2	6	6	NUM
cana-4763	333	3	]	]	X
cana-4763	333	4	belayneh	belayneh	NOUN
cana-4763	333	5	sisay	sisay	VERB
cana-4763	333	6	alemu	alemu	PROPN
cana-4763	333	7	,	,	PUNCT
cana-4763	333	8	sultan	sultan	ADJ
cana-4763	333	9	feisso	feisso	NOUN
cana-4763	333	10	,	,	PUNCT
cana-4763	333	11	endris	endris	PROPN
cana-4763	333	12	abdu	abdu	PROPN
cana-4763	333	13	mohammed	mohammed	PROPN
cana-4763	333	14	,	,	PUNCT
cana-4763	333	15	ayodeji	ayodeji	PROPN
cana-4763	333	16	olalekan	olalekan	PROPN
cana-4763	333	17	salau	salau	PROPN
cana-4763	333	18	,	,	PUNCT
cana-4763	333	19	magnetic	magnetic	ADJ
cana-4763	333	20	resonance	resonance	NOUN
cana-4763	333	21	imaging	imaging	NOUN
cana-4763	333	22	-	-	PUNCT
cana-4763	333	23	based	base	VERB
cana-4763	333	24	brain	brain	NOUN
cana-4763	333	25	tumor	tumor	NOUN
cana-4763	333	26	image	image	NOUN
cana-4763	333	27	classification	classification	NOUN
cana-4763	333	28	performance	performance	NOUN
cana-4763	333	29	enhancement	enhancement	NOUN
cana-4763	333	30	,	,	PUNCT
cana-4763	333	31	scientific	scientific	ADJ
cana-4763	333	32	african	african	ADJ
cana-4763	333	33	,	,	PUNCT
cana-4763	333	34	volume	volume	NOUN
cana-4763	333	35	22	22	NUM
cana-4763	333	36	,	,	PUNCT
cana-4763	333	37	e01963	e01963	PROPN
cana-4763	333	38	,	,	PUNCT
cana-4763	333	39	issn	issn	PROPN
cana-4763	333	40	2468	2468	NUM
cana-4763	333	41	-	-	SYM
cana-4763	333	42	2276,2023	2276,2023	NUM
cana-4763	333	43	.	.	PUNCT
cana-4763	334	1	[	[	X
cana-4763	334	2	7	7	NUM
cana-4763	334	3	]	]	X
cana-4763	334	4	elazab	elazab	PROPN
cana-4763	334	5	,	,	PUNCT
cana-4763	334	6	n.	n.	NOUN
cana-4763	334	7	,	,	PUNCT
cana-4763	334	8	gab	gab	PROPN
cana-4763	334	9	-	-	PUNCT
cana-4763	334	10	allah	allah	PROPN
cana-4763	334	11	,	,	PUNCT
cana-4763	334	12	w.a	w.a	PROPN
cana-4763	334	13	.	.	PROPN
cana-4763	334	14	&	&	CCONJ
cana-4763	334	15	elmogy	elmogy	PROPN
cana-4763	334	16	,	,	PUNCT
cana-4763	334	17	m.	m.	VERB
cana-4763	334	18	a	a	DET
cana-4763	334	19	multi	multi	ADJ
cana-4763	334	20	-	-	ADJ
cana-4763	334	21	class	class	ADJ
cana-4763	334	22	brain	brain	NOUN
cana-4763	334	23	tumor	tumor	NOUN
cana-4763	334	24	grading	grade	VERB
cana-4763	334	25	system	system	NOUN
cana-4763	334	26	based	base	VERB
cana-4763	334	27	on	on	ADP
cana-4763	334	28	histopathological	histopathological	ADJ
cana-4763	334	29	images	image	NOUN
cana-4763	334	30	using	use	VERB
cana-4763	334	31	a	a	DET
cana-4763	334	32	hybrid	hybrid	ADJ
cana-4763	334	33	yolo	yolo	NOUN
cana-4763	334	34	and	and	CCONJ
cana-4763	334	35	resnet	resnet	ADJ
cana-4763	334	36	networks	network	NOUN
cana-4763	334	37	.	.	PUNCT
cana-4763	335	1	sci	sci	PROPN
cana-4763	335	2	rep	rep	PROPN
cana-4763	335	3	14	14	NUM
cana-4763	335	4	,	,	PUNCT
cana-4763	335	5	4584	4584	NUM
cana-4763	335	6	,	,	PUNCT
cana-4763	335	7	2024	2024	NUM
cana-4763	335	8	.	.	PUNCT
cana-4763	336	1	[	[	X
cana-4763	336	2	8	8	NUM
cana-4763	336	3	]	]	X
cana-4763	336	4	chen	chen	PROPN
cana-4763	336	5	,	,	PUNCT
cana-4763	336	6	t.	t.	PROPN
cana-4763	336	7	,	,	PUNCT
cana-4763	336	8	hu	hu	PROPN
cana-4763	336	9	,	,	PUNCT
cana-4763	336	10	l.	l.	PROPN
cana-4763	336	11	,	,	PUNCT
cana-4763	336	12	lu	lu	PROPN
cana-4763	336	13	,	,	PUNCT
cana-4763	336	14	q.	q.	PROPN
cana-4763	336	15	,	,	PUNCT
cana-4763	336	16	xiao	xiao	PROPN
cana-4763	336	17	,	,	PUNCT
cana-4763	336	18	f.	f.	PROPN
cana-4763	336	19	,	,	PUNCT
cana-4763	336	20	xu	xu	PROPN
cana-4763	336	21	,	,	PUNCT
cana-4763	336	22	h.	h.	PROPN
cana-4763	336	23	,	,	PUNCT
cana-4763	336	24	li	li	PROPN
cana-4763	336	25	,	,	PUNCT
cana-4763	336	26	h.	h.	PROPN
cana-4763	336	27	,	,	PUNCT
cana-4763	336	28	&	&	CCONJ
cana-4763	336	29	lu	lu	PROPN
cana-4763	336	30	,	,	PUNCT
cana-4763	336	31	l.	l.	PROPN
cana-4763	336	32	a	a	DET
cana-4763	336	33	computer	computer	NOUN
cana-4763	336	34	-	-	PUNCT
cana-4763	336	35	aided	aid	VERB
cana-4763	336	36	diagnosis	diagnosis	NOUN
cana-4763	336	37	system	system	NOUN
cana-4763	336	38	for	for	ADP
cana-4763	336	39	brain	brain	NOUN
cana-4763	336	40	tumors	tumor	NOUN
cana-4763	336	41	based	base	VERB
cana-4763	336	42	on	on	ADP
cana-4763	336	43	artificial	artificial	ADJ
cana-4763	336	44	intelligence	intelligence	NOUN
cana-4763	336	45	algorithms	algorithm	NOUN
cana-4763	336	46	.	.	PUNCT
cana-4763	337	1	frontiers	frontier	NOUN
cana-4763	337	2	in	in	ADP
cana-4763	337	3	neuroscience	neuroscience	NOUN
cana-4763	337	4	,	,	PUNCT
cana-4763	337	5	17	17	NUM
cana-4763	337	6	,	,	PUNCT
cana-4763	337	7	1120781	1120781	NUM
cana-4763	337	8	,	,	PUNCT
cana-4763	337	9	2023	2023	NUM
cana-4763	337	10	.	.	PUNCT
cana-4763	338	1	[	[	X
cana-4763	338	2	9	9	NUM
cana-4763	338	3	]	]	X
cana-4763	338	4	falguni	falguni	ADJ
cana-4763	338	5	bhardawaj	bhardawaj	NOUN
cana-4763	338	6	,	,	PUNCT
cana-4763	338	7	shruti	shruti	PROPN
cana-4763	338	8	jain	jain	PROPN
cana-4763	338	9	,	,	PUNCT
cana-4763	338	10	cad	cad	PROPN
cana-4763	338	11	system	system	NOUN
cana-4763	338	12	design	design	NOUN
cana-4763	338	13	for	for	ADP
cana-4763	338	14	two	two	NUM
cana-4763	338	15	-	-	PUNCT
cana-4763	338	16	class	class	NOUN
cana-4763	338	17	brain	brain	NOUN
cana-4763	338	18	tumor	tumor	NOUN
cana-4763	338	19	classification	classification	NOUN
cana-4763	338	20	usingtransfer	usingtransfer	NOUN
cana-4763	338	21	learning	learning	NOUN
cana-4763	338	22	,	,	PUNCT
cana-4763	338	23	current	current	ADJ
cana-4763	338	24	cancer	cancer	NOUN
cana-4763	338	25	therapy	therapy	NOUN
cana-4763	338	26	reviews	review	NOUN
cana-4763	338	27	;	;	PUNCT
cana-4763	338	28	volume	volume	NOUN
cana-4763	338	29	20	20	NUM
cana-4763	338	30	,	,	PUNCT
cana-4763	338	31	issue	issue	NOUN
cana-4763	338	32	2	2	NUM
cana-4763	338	33	,	,	PUNCT
cana-4763	338	34	year	year	NOUN
cana-4763	338	35	2024	2024	NUM
cana-4763	338	36	.	.	PUNCT
cana-4763	338	37	communications	communication	NOUN
cana-4763	338	38	on	on	ADP
cana-4763	338	39	applied	apply	VERB
cana-4763	338	40	nonlinear	nonlinear	ADJ
cana-4763	338	41	analysis	analysis	NOUN
cana-4763	338	42	issn	issn	NOUN
cana-4763	338	43	:	:	PUNCT
cana-4763	338	44	1074	1074	NUM
cana-4763	338	45	-	-	PUNCT
cana-4763	338	46	133x	133x	NUM
cana-4763	338	47	vol	vol	VERB
cana-4763	338	48	32	32	NUM
cana-4763	338	49	no	no	NOUN
cana-4763	338	50	.	.	PUNCT
cana-4763	339	1	10s	10	NOUN
cana-4763	339	2	(	(	PUNCT
cana-4763	339	3	2025	2025	NUM
cana-4763	339	4	)	)	PUNCT
cana-4763	339	5	311	311	NUM
cana-4763	339	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	340	1	[	[	X
cana-4763	340	2	10	10	NUM
cana-4763	340	3	]	]	X
cana-4763	340	4	b.u	b.u	PROPN
cana-4763	340	5	.	.	PROPN
cana-4763	340	6	karthik	karthik	PROPN
cana-4763	340	7	,	,	PUNCT
cana-4763	340	8	g.	g.	PROPN
cana-4763	340	9	muthupandi	muthupandi	PROPN
cana-4763	340	10	,	,	PUNCT
cana-4763	340	11	“	"	PUNCT
cana-4763	340	12	svm	svm	PROPN
cana-4763	340	13	and	and	CCONJ
cana-4763	340	14	cnn	cnn	PROPN
cana-4763	340	15	based	base	VERB
cana-4763	340	16	skin	skin	NOUN
cana-4763	340	17	tumour	tumour	NOUN
cana-4763	340	18	classification	classification	NOUN
cana-4763	340	19	using	use	VERB
cana-4763	340	20	wls	wl	NOUN
cana-4763	340	21	smoothing	smooth	VERB
cana-4763	340	22	filter	filter	NOUN
cana-4763	340	23	”	"	PUNCT
cana-4763	340	24	,	,	PUNCT
cana-4763	340	25	optik	optik	PROPN
cana-4763	340	26	,	,	PUNCT
cana-4763	340	27	volume	volume	NOUN
cana-4763	340	28	272	272	NUM
cana-4763	340	29	,	,	PUNCT
cana-4763	340	30	170337	170337	NUM
cana-4763	340	31	,	,	PUNCT
cana-4763	340	32	issn	issn	PROPN
cana-4763	340	33	0030	0030	NUM
cana-4763	340	34	-	-	SYM
cana-4763	340	35	4026	4026	NUM
cana-4763	340	36	,	,	PUNCT
cana-4763	340	37	2023	2023	NUM
cana-4763	340	38	.	.	PUNCT
cana-4763	341	1	[	[	X
cana-4763	341	2	11	11	NUM
cana-4763	341	3	]	]	X
cana-4763	341	4	mrutyunjaya	mrutyunjaya	NOUN
cana-4763	341	5	mathad	mathad	VERB
cana-4763	341	6	shivamurthaiah	shivamurthaiah	PROPN
cana-4763	341	7	,	,	PUNCT
cana-4763	341	8	harish	harish	PROPN
cana-4763	341	9	kumar	kumar	PROPN
cana-4763	341	10	kushtagi	kushtagi	PROPN
cana-4763	341	11	shetra	shetra	PROPN
cana-4763	341	12	,	,	PUNCT
cana-4763	341	13	non	non	ADJ
cana-4763	341	14	-	-	ADJ
cana-4763	341	15	destructive	destructive	ADJ
cana-4763	341	16	machine	machine	NOUN
cana-4763	341	17	vision	vision	NOUN
cana-4763	341	18	system	system	NOUN
cana-4763	341	19	based	base	VERB
cana-4763	341	20	rice	rice	NOUN
cana-4763	341	21	classification	classification	NOUN
cana-4763	341	22	using	use	VERB
cana-4763	341	23	ensemble	ensemble	ADJ
cana-4763	341	24	machine	machine	NOUN
cana-4763	341	25	learning	learning	NOUN
cana-4763	341	26	algorithms	algorithm	NOUN
cana-4763	341	27	,	,	PUNCT
cana-4763	341	28	recent	recent	ADJ
cana-4763	341	29	advances	advance	NOUN
cana-4763	341	30	in	in	ADP
cana-4763	341	31	electrical	electrical	ADJ
cana-4763	341	32	&	&	CCONJ
cana-4763	341	33	electronic	electronic	ADJ
cana-4763	341	34	engineering	engineering	NOUN
cana-4763	341	35	;	;	PUNCT
cana-4763	341	36	volume	volume	NOUN
cana-4763	341	37	17	17	NUM
cana-4763	341	38	,	,	PUNCT
cana-4763	341	39	issue	issue	NOUN
cana-4763	341	40	5	5	NUM
cana-4763	341	41	,	,	PUNCT
cana-4763	341	42	year	year	NOUN
cana-4763	341	43	2024	2024	NUM
cana-4763	341	44	.	.	PUNCT
cana-4763	342	1	[	[	X
cana-4763	342	2	12	12	NUM
cana-4763	342	3	]	]	X
cana-4763	342	4	sanjeev	sanjeev	PROPN
cana-4763	342	5	prakashrao	prakashrao	PROPN
cana-4763	342	6	kaulgud	kaulgud	PROPN
cana-4763	342	7	,	,	PUNCT
cana-4763	342	8	rama	rama	PROPN
cana-4763	342	9	krishna	krishna	PROPN
cana-4763	342	10	k	k	PROPN
cana-4763	342	11	,	,	PUNCT
cana-4763	342	12	mrutyunjaya	mrutyunjaya	PROPN
cana-4763	342	13	m	m	PROPN
cana-4763	342	14	s	s	PROPN
cana-4763	342	15	,	,	PUNCT
cana-4763	342	16	abhinandan	abhinandan	PROPN
cana-4763	342	17	shirahatti	shirahatti	PROPN
cana-4763	342	18	,	,	PUNCT
cana-4763	342	19	murthy	murthy	PROPN
cana-4763	342	20	d	d	X
cana-4763	342	21	h	h	NOUN
cana-4763	342	22	r	r	NOUN
cana-4763	342	23	,	,	PUNCT
cana-4763	342	24	afroz	afroz	ADV
cana-4763	342	25	pasha	pasha	PROPN
cana-4763	342	26	,	,	PUNCT
cana-4763	342	27	leveraging	leverage	VERB
cana-4763	342	28	enhanced	enhanced	ADJ
cana-4763	342	29	pso	pso	NOUN
cana-4763	342	30	and	and	CCONJ
cana-4763	342	31	proving	prove	VERB
cana-4763	342	32	random	random	ADJ
cana-4763	342	33	forest	forest	NOUN
cana-4763	342	34	's	's	PART
cana-4763	342	35	dominance	dominance	NOUN
cana-4763	342	36	for	for	ADP
cana-4763	342	37	prediction	prediction	NOUN
cana-4763	342	38	of	of	ADP
cana-4763	342	39	lung	lung	NOUN
cana-4763	342	40	cancer	cancer	NOUN
cana-4763	342	41	severity	severity	NOUN
cana-4763	342	42	,	,	PUNCT
cana-4763	342	43	vol	vol	NOUN
cana-4763	342	44	.	.	PROPN
cana-4763	342	45	10	10	NUM
cana-4763	342	46	no	no	NOUN
cana-4763	342	47	.	.	NOUN
cana-4763	342	48	3	3	NUM
cana-4763	342	49	(	(	PUNCT
cana-4763	342	50	2025	2025	NUM
cana-4763	342	51	)	)	PUNCT
cana-4763	342	52	,	,	PUNCT
cana-4763	342	53	pp	pp	ADP
cana-4763	342	54	60	60	NUM
cana-4763	342	55	-	-	PUNCT
cana-4763	342	56	70,2025	70,2025	NUM
cana-4763	342	57	.	.	PUNCT
cana-4763	343	1	[	[	X
cana-4763	343	2	13	13	NUM
cana-4763	343	3	]	]	X
cana-4763	343	4	mst	mst	PROPN
cana-4763	343	5	sazia	sazia	PROPN
cana-4763	343	6	tahosin	tahosin	PROPN
cana-4763	343	7	,	,	PUNCT
cana-4763	343	8	md	md	PROPN
cana-4763	343	9	alif	alif	PROPN
cana-4763	343	10	sheakh	sheakh	PROPN
cana-4763	343	11	,	,	PUNCT
cana-4763	343	12	taminul	taminul	PROPN
cana-4763	343	13	islam	islam	PROPN
cana-4763	343	14	,	,	PUNCT
cana-4763	343	15	rishalatun	rishalatun	PROPN
cana-4763	343	16	jannat	jannat	PROPN
cana-4763	343	17	lima	lima	PROPN
cana-4763	343	18	,	,	PUNCT
cana-4763	343	19	mahbuba	mahbuba	ADJ
cana-4763	343	20	begum	begum	PROPN
cana-4763	343	21	,	,	PUNCT
cana-4763	343	22	optimizing	optimize	VERB
cana-4763	343	23	brain	brain	NOUN
cana-4763	343	24	tumor	tumor	NOUN
cana-4763	343	25	classification	classification	NOUN
cana-4763	343	26	through	through	ADP
cana-4763	343	27	feature	feature	NOUN
cana-4763	343	28	selection	selection	NOUN
cana-4763	343	29	and	and	CCONJ
cana-4763	343	30	hyperparameter	hyperparameter	NOUN
cana-4763	343	31	tuning	tune	VERB
cana-4763	343	32	in	in	ADP
cana-4763	343	33	machine	machine	NOUN
cana-4763	343	34	learning	learning	NOUN
cana-4763	343	35	models	model	NOUN
cana-4763	343	36	,	,	PUNCT
cana-4763	343	37	informatics	informatic	NOUN
cana-4763	343	38	in	in	ADP
cana-4763	343	39	medicine	medicine	NOUN
cana-4763	343	40	unlocked	unlock	VERB
cana-4763	343	41	,	,	PUNCT
cana-4763	343	42	volume	volume	NOUN
cana-4763	343	43	43	43	NUM
cana-4763	343	44	,	,	PUNCT
cana-4763	343	45	101414	101414	NUM
cana-4763	343	46	,	,	PUNCT
cana-4763	343	47	issn	issn	PROPN
cana-4763	343	48	2352	2352	NUM
cana-4763	343	49	-	-	SYM
cana-4763	343	50	9148	9148	NUM
cana-4763	343	51	,	,	PUNCT
cana-4763	343	52	2023	2023	NUM
cana-4763	343	53	.	.	PUNCT
cana-4763	344	1	[	[	X
cana-4763	344	2	14	14	NUM
cana-4763	344	3	]	]	X
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cana-4763	344	7	,	,	PUNCT
cana-4763	344	8	nagwan	nagwan	PROPN
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cana-4763	344	11	,	,	PUNCT
cana-4763	344	12	mona	mona	PROPN
cana-4763	344	13	m.	m.	PROPN
cana-4763	344	14	jamjoom	jamjoom	PROPN
cana-4763	344	15	,	,	PUNCT
cana-4763	344	16	essam	essam	PROPN
cana-4763	344	17	h.	h.	PROPN
cana-4763	344	18	houssein	houssein	PROPN
cana-4763	344	19	,	,	PUNCT
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cana-4763	344	21	15	15	NUM
cana-4763	344	22	]	]	PUNCT
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cana-4763	344	25	learning	learning	NOUN
cana-4763	344	26	architecture	architecture	NOUN
cana-4763	344	27	for	for	ADP
cana-4763	344	28	brain	brain	NOUN
cana-4763	344	29	tumor	tumor	NOUN
cana-4763	344	30	classification	classification	NOUN
cana-4763	344	31	using	use	VERB
cana-4763	344	32	improved	improve	VERB
cana-4763	344	33	hunger	hunger	NOUN
cana-4763	344	34	games	game	NOUN
cana-4763	344	35	search	search	NOUN
cana-4763	344	36	algorithm	algorithm	NOUN
cana-4763	344	37	,	,	PUNCT
cana-4763	344	38	computers	computer	NOUN
cana-4763	344	39	in	in	ADP
cana-4763	344	40	biology	biology	NOUN
cana-4763	344	41	and	and	CCONJ
cana-4763	344	42	medicine	medicine	NOUN
cana-4763	344	43	,	,	PUNCT
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cana-4763	344	46	,	,	PUNCT
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cana-4763	344	51	-	-	SYM
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cana-4763	344	53	,	,	PUNCT
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cana-4763	344	55	.	.	PUNCT
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cana-4763	345	2	16	16	NUM
cana-4763	345	3	]	]	X
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cana-4763	345	5	mohsen	mohsen	PROPN
cana-4763	345	6	,	,	PUNCT
cana-4763	345	7	el	el	PROPN
cana-4763	345	8	-	-	PUNCT
cana-4763	345	9	sayed	say	VERB
cana-4763	345	10	a.	a.	PROPN
cana-4763	345	11	el	el	PROPN
cana-4763	345	12	-	-	PUNCT
cana-4763	345	13	dahshan	dahshan	PROPN
cana-4763	345	14	,	,	PUNCT
cana-4763	345	15	el	el	PROPN
cana-4763	345	16	-	-	PUNCT
cana-4763	345	17	sayed	say	VERB
cana-4763	345	18	m.	m.	PROPN
cana-4763	345	19	el	el	PROPN
cana-4763	345	20	-	-	PROPN
cana-4763	345	21	horbaty	horbaty	PROPN
cana-4763	345	22	,	,	PUNCT
cana-4763	345	23	abdel	abdel	NOUN
cana-4763	345	24	-	-	PUNCT
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cana-4763	345	33	neural	neural	ADJ
cana-4763	345	34	networks	network	NOUN
cana-4763	345	35	for	for	ADP
cana-4763	345	36	brain	brain	NOUN
cana-4763	345	37	tumors	tumor	NOUN
cana-4763	345	38	,	,	PUNCT
cana-4763	345	39	future	future	ADJ
cana-4763	345	40	computing	computing	NOUN
cana-4763	345	41	and	and	CCONJ
cana-4763	345	42	informatics	informatic	NOUN
cana-4763	345	43	journal	journal	PROPN
cana-4763	345	44	,	,	PUNCT
cana-4763	345	45	volume	volume	NOUN
cana-4763	345	46	3	3	NUM
cana-4763	345	47	,	,	PUNCT
cana-4763	345	48	issue	issue	NOUN
cana-4763	345	49	1	1	NUM
cana-4763	345	50	,	,	PUNCT
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cana-4763	345	53	-	-	SYM
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cana-4763	345	55	,	,	PUNCT
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cana-4763	345	58	-	-	SYM
cana-4763	345	59	7288	7288	NUM
cana-4763	345	60	,	,	PUNCT
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cana-4763	345	62	.	.	PUNCT
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cana-4763	346	2	17	17	NUM
cana-4763	346	3	]	]	PUNCT
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cana-4763	346	14	convolution	convolution	NOUN
cana-4763	346	15	neural	neural	ADJ
cana-4763	346	16	network	network	NOUN
cana-4763	346	17	for	for	ADP
cana-4763	346	18	brain	brain	NOUN
cana-4763	346	19	tumor	tumor	NOUN
cana-4763	346	20	classification	classification	NOUN
cana-4763	346	21	,	,	PUNCT
cana-4763	346	22	biocybernetics	biocybernetic	NOUN
cana-4763	346	23	and	and	CCONJ
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cana-4763	346	25	engineering	engineering	NOUN
cana-4763	346	26	,	,	PUNCT
cana-4763	346	27	volume	volume	NOUN
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cana-4763	346	29	,	,	PUNCT
cana-4763	346	30	issue	issue	NOUN
cana-4763	346	31	3	3	NUM
cana-4763	346	32	,	,	PUNCT
cana-4763	346	33	pages	page	NOUN
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cana-4763	346	35	,	,	PUNCT
cana-4763	346	36	issn	issn	PROPN
cana-4763	346	37	0208	0208	NUM
cana-4763	346	38	-	-	SYM
cana-4763	346	39	5216	5216	NUM
cana-4763	346	40	,	,	PUNCT
cana-4763	346	41	2020	2020	NUM
cana-4763	346	42	.	.	PUNCT
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cana-4763	347	2	18	18	NUM
cana-4763	347	3	]	]	SYM
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cana-4763	347	15	image	image	NOUN
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cana-4763	347	22	method	method	NOUN
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cana-4763	347	26	,	,	PUNCT
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cana-4763	347	29	,	,	PUNCT
cana-4763	347	30	issue	issue	NOUN
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cana-4763	347	32	,	,	PUNCT
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cana-4763	347	35	-	-	SYM
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cana-4763	347	37	.	.	PUNCT
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cana-4763	348	3	]	]	PUNCT
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cana-4763	348	41	-	-	SYM
cana-4763	348	42	9141	9141	NUM
cana-4763	348	43	,	,	PUNCT
cana-4763	348	44	2024	2024	NUM
cana-4763	348	45	.	.	PUNCT
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cana-4763	350	7	)	)	PUNCT
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cana-4763	351	2	21	21	NUM
cana-4763	351	3	]	]	PUNCT
cana-4763	351	4	saeedi	saeedi	NOUN
cana-4763	351	5	,	,	PUNCT
cana-4763	351	6	s.	s.	PROPN
cana-4763	351	7	,	,	PUNCT
cana-4763	351	8	rezayi	rezayi	ADV
cana-4763	351	9	,	,	PUNCT
cana-4763	351	10	s.	s.	PROPN
cana-4763	351	11	,	,	PUNCT
cana-4763	351	12	keshavarz	keshavarz	PROPN
cana-4763	351	13	,	,	PUNCT
cana-4763	351	14	h.	h.	PROPN
cana-4763	351	15	et	et	PROPN
cana-4763	351	16	al	al	PROPN
cana-4763	351	17	.	.	PUNCT
cana-4763	352	1	mri	mri	NOUN
cana-4763	352	2	-	-	PUNCT
cana-4763	352	3	based	base	VERB
cana-4763	352	4	brain	brain	NOUN
cana-4763	352	5	tumor	tumor	NOUN
cana-4763	352	6	detection	detection	NOUN
cana-4763	352	7	using	use	VERB
cana-4763	352	8	convolutional	convolutional	ADJ
cana-4763	352	9	deep	deep	ADJ
cana-4763	352	10	learning	learning	NOUN
cana-4763	352	11	methods	method	NOUN
cana-4763	352	12	and	and	CCONJ
cana-4763	352	13	chosen	choose	VERB
cana-4763	352	14	machine	machine	NOUN
cana-4763	352	15	learning	learn	VERB
cana-4763	352	16	techniques	technique	NOUN
cana-4763	352	17	.	.	PUNCT
cana-4763	353	1	bmc	bmc	PROPN
cana-4763	353	2	med	med	ADJ
cana-4763	353	3	inform	inform	NOUN
cana-4763	353	4	decis	decis	PROPN
cana-4763	353	5	mak	mak	PROPN
cana-4763	353	6	23	23	NUM
cana-4763	353	7	,	,	PUNCT
cana-4763	353	8	16	16	NUM
cana-4763	353	9	,	,	PUNCT
cana-4763	353	10	2023	2023	NUM
cana-4763	353	11	.	.	PUNCT
cana-4763	354	1	[	[	X
cana-4763	354	2	22	22	NUM
cana-4763	354	3	]	]	PUNCT
cana-4763	354	4	s.	s.	PROPN
cana-4763	354	5	shanthi	shanthi	PROPN
cana-4763	354	6	,	,	PUNCT
cana-4763	354	7	s.	s.	PROPN
cana-4763	354	8	saradha	saradha	PROPN
cana-4763	354	9	,	,	PUNCT
cana-4763	354	10	j.a	j.a	PROPN
cana-4763	354	11	.	.	PROPN
cana-4763	354	12	smitha	smitha	PROPN
cana-4763	354	13	,	,	PUNCT
cana-4763	354	14	n.	n.	PROPN
cana-4763	354	15	prasath	prasath	PROPN
cana-4763	354	16	,	,	PUNCT
cana-4763	354	17	h.	h.	PROPN
cana-4763	354	18	anandakumar	anandakumar	PROPN
cana-4763	354	19	,	,	PUNCT
cana-4763	354	20	an	an	DET
cana-4763	354	21	efficient	efficient	ADJ
cana-4763	354	22	automatic	automatic	ADJ
cana-4763	354	23	brain	brain	NOUN
cana-4763	354	24	tumor	tumor	NOUN
cana-4763	354	25	classification	classification	NOUN
cana-4763	354	26	using	use	VERB
cana-4763	354	27	optimized	optimize	VERB
cana-4763	354	28	hybrid	hybrid	ADJ
cana-4763	354	29	deep	deep	ADJ
cana-4763	354	30	neural	neural	ADJ
cana-4763	354	31	network	network	NOUN
cana-4763	354	32	,	,	PUNCT
cana-4763	354	33	international	international	ADJ
cana-4763	354	34	journal	journal	NOUN
cana-4763	354	35	of	of	ADP
cana-4763	354	36	intelligent	intelligent	ADJ
cana-4763	354	37	networks	network	NOUN
cana-4763	354	38	,	,	PUNCT
cana-4763	354	39	volume	volume	NOUN
cana-4763	354	40	3	3	NUM
cana-4763	354	41	,	,	PUNCT
cana-4763	354	42	pages	page	NOUN
cana-4763	354	43	188	188	NUM
cana-4763	354	44	-	-	SYM
cana-4763	354	45	196	196	NUM
cana-4763	354	46	,	,	PUNCT
cana-4763	354	47	issn	issn	PROPN
cana-4763	354	48	2666	2666	NUM
cana-4763	354	49	-	-	PUNCT
cana-4763	354	50	6030,2022	6030,2022	NOUN
cana-4763	354	51	.	.	PUNCT
cana-4763	355	1	[	[	X
cana-4763	355	2	23	23	NUM
cana-4763	355	3	]	]	SYM
cana-4763	355	4	22	22	NUM
cana-4763	355	5	.	.	PUNCT
cana-4763	356	1	gupta	gupta	PROPN
cana-4763	356	2	,	,	PUNCT
cana-4763	356	3	manali	manali	PROPN
cana-4763	356	4	,	,	PUNCT
cana-4763	356	5	sharma	sharma	PROPN
cana-4763	356	6	,	,	PUNCT
cana-4763	356	7	sanjay	sanjay	PROPN
cana-4763	356	8	kumar	kumar	PROPN
cana-4763	356	9	,	,	PUNCT
cana-4763	356	10	sampada	sampada	PROPN
cana-4763	356	11	,	,	PUNCT
cana-4763	356	12	g.	g.	PROPN
cana-4763	356	13	c.	c.	PROPN
cana-4763	356	14	,	,	PUNCT
cana-4763	356	15	classification	classification	NOUN
cana-4763	356	16	of	of	ADP
cana-4763	356	17	brain	brain	NOUN
cana-4763	356	18	tumor	tumor	NOUN
cana-4763	356	19	images	image	NOUN
cana-4763	356	20	using	use	VERB
cana-4763	356	21	cnn	cnn	PROPN
cana-4763	356	22	,	,	PUNCT
cana-4763	356	23	computational	computational	ADJ
cana-4763	356	24	intelligence	intelligence	NOUN
cana-4763	356	25	and	and	CCONJ
cana-4763	356	26	neuroscience	neuroscience	NOUN
cana-4763	356	27	,	,	PUNCT
cana-4763	356	28	2023	2023	NUM
cana-4763	356	29	,	,	PUNCT
cana-4763	356	30	2002855	2002855	NUM
cana-4763	356	31	,	,	PUNCT
cana-4763	356	32	6	6	NUM
cana-4763	356	33	pages	page	NOUN
cana-4763	356	34	,	,	PUNCT
cana-4763	356	35	2023	2023	NUM
cana-4763	356	36	.	.	PUNCT
cana-4763	357	1	[	[	X
cana-4763	357	2	24	24	NUM
cana-4763	357	3	]	]	SYM
cana-4763	357	4	23	23	NUM
cana-4763	357	5	.	.	PUNCT
cana-4763	358	1	p.	p.	NOUN
cana-4763	358	2	afshar	afshar	PROPN
cana-4763	358	3	,	,	PUNCT
cana-4763	358	4	k.	k.	PROPN
cana-4763	358	5	n.	n.	PROPN
cana-4763	359	1	plataniotis	plataniotis	PROPN
cana-4763	359	2	and	and	CCONJ
cana-4763	359	3	a.	a.	NOUN
cana-4763	359	4	mohammadi	mohammadi	NOUN
cana-4763	359	5	,	,	PUNCT
cana-4763	359	6	"	"	PUNCT
cana-4763	359	7	capsule	capsule	ADJ
cana-4763	359	8	networks	network	NOUN
cana-4763	359	9	for	for	ADP
cana-4763	359	10	brain	brain	NOUN
cana-4763	359	11	tumor	tumor	NOUN
cana-4763	359	12	classification	classification	NOUN
cana-4763	359	13	based	base	VERB
cana-4763	359	14	on	on	ADP
cana-4763	359	15	mri	mri	NOUN
cana-4763	359	16	images	image	NOUN
cana-4763	359	17	and	and	CCONJ
cana-4763	359	18	coarse	coarse	ADJ
cana-4763	359	19	tumor	tumor	NOUN
cana-4763	359	20	boundaries	boundary	NOUN
cana-4763	359	21	,	,	PUNCT
cana-4763	359	22	"	"	PUNCT
cana-4763	359	23	icassp	icassp	CCONJ
cana-4763	359	24	2019	2019	NUM
cana-4763	359	25	2019	2019	NUM
cana-4763	359	26	ieee	ieee	NOUN
cana-4763	359	27	international	international	ADJ
cana-4763	359	28	conference	conference	NOUN
cana-4763	359	29	on	on	ADP
cana-4763	359	30	acoustics	acoustic	NOUN
cana-4763	359	31	,	,	PUNCT
cana-4763	359	32	speech	speech	NOUN
cana-4763	359	33	and	and	CCONJ
cana-4763	359	34	signal	signal	NOUN
cana-4763	359	35	processing	processing	NOUN
cana-4763	359	36	(	(	PUNCT
cana-4763	359	37	icassp	icassp	PROPN
cana-4763	359	38	)	)	PUNCT
cana-4763	359	39	,	,	PUNCT
cana-4763	359	40	brighton	brighton	PROPN
cana-4763	359	41	,	,	PUNCT
cana-4763	359	42	uk	uk	PROPN
cana-4763	359	43	,	,	PUNCT
cana-4763	359	44	2019	2019	NUM
cana-4763	359	45	,	,	PUNCT
cana-4763	359	46	pp	pp	ADJ
cana-4763	359	47	.	.	PUNCT
cana-4763	360	1	1368	1368	NUM
cana-4763	360	2	-	-	SYM
cana-4763	360	3	1372	1372	NUM
cana-4763	360	4	,	,	PUNCT
cana-4763	360	5	2019	2019	NUM
cana-4763	360	6	.	.	PUNCT
cana-4763	361	1	[	[	X
cana-4763	361	2	25	25	NUM
cana-4763	361	3	]	]	PUNCT
cana-4763	361	4	altahhan	altahhan	PROPN
cana-4763	361	5	,	,	PUNCT
cana-4763	361	6	f.	f.	PROPN
cana-4763	361	7	e.	e.	PROPN
cana-4763	361	8	,	,	PUNCT
cana-4763	361	9	khouqeer	khouqeer	PROPN
cana-4763	361	10	,	,	PUNCT
cana-4763	361	11	g.	g.	PROPN
cana-4763	361	12	a.	a.	PROPN
cana-4763	361	13	,	,	PUNCT
cana-4763	361	14	saadi	saadi	PROPN
cana-4763	361	15	,	,	PUNCT
cana-4763	361	16	s.	s.	PROPN
cana-4763	361	17	,	,	PUNCT
cana-4763	361	18	elgarayhi	elgarayhi	PROPN
cana-4763	361	19	,	,	PUNCT
cana-4763	361	20	a.	a.	NOUN
cana-4763	361	21	,	,	PUNCT
cana-4763	361	22	&	&	CCONJ
cana-4763	361	23	sallah	sallah	PROPN
cana-4763	361	24	,	,	PUNCT
cana-4763	361	25	m.	m.	NOUN
cana-4763	361	26	(	(	PUNCT
cana-4763	361	27	2023	2023	NUM
cana-4763	361	28	)	)	PUNCT
cana-4763	361	29	.	.	PUNCT
cana-4763	362	1	refined	refine	VERB
cana-4763	362	2	automatic	automatic	ADJ
cana-4763	362	3	brain	brain	NOUN
cana-4763	362	4	tumor	tumor	NOUN
cana-4763	362	5	classification	classification	NOUN
cana-4763	362	6	using	use	VERB
cana-4763	362	7	hybrid	hybrid	ADJ
cana-4763	362	8	convolutional	convolutional	ADJ
cana-4763	362	9	neural	neural	ADJ
cana-4763	362	10	networks	network	NOUN
cana-4763	362	11	for	for	ADP
cana-4763	362	12	mri	mri	NOUN
cana-4763	362	13	scans	scan	NOUN
cana-4763	362	14	.	.	PUNCT
cana-4763	363	1	diagnostics	diagnostic	NOUN
cana-4763	363	2	(	(	PUNCT
cana-4763	363	3	basel	basel	PROPN
cana-4763	363	4	,	,	PUNCT
cana-4763	363	5	switzerland	switzerland	PROPN
cana-4763	363	6	)	)	PUNCT
cana-4763	363	7	,	,	PUNCT
cana-4763	363	8	13(5	13(5	NUM
cana-4763	363	9	)	)	PUNCT
cana-4763	363	10	,	,	PUNCT
cana-4763	363	11	864	864	NUM
cana-4763	363	12	,	,	PUNCT
cana-4763	363	13	2023	2023	NUM
cana-4763	363	14	.	.	PUNCT
cana-4763	364	1	https://doi.org/10.3390/diagnostics13050864	https://doi.org/10.3390/diagnostics13050864	NOUN
cana-4763	365	1	[	[	X
cana-4763	365	2	26	26	NUM
cana-4763	365	3	]	]	X
cana-4763	365	4	el	el	PROPN
cana-4763	365	5	-	-	PUNCT
cana-4763	365	6	assy	assy	PROPN
cana-4763	365	7	,	,	PUNCT
cana-4763	365	8	a.m.	a.m.	ADV
cana-4763	365	9	,	,	PUNCT
cana-4763	365	10	amer	amer	PROPN
cana-4763	365	11	,	,	PUNCT
cana-4763	365	12	h.m	h.m	PROPN
cana-4763	365	13	.	.	PROPN
cana-4763	365	14	,	,	PUNCT
cana-4763	365	15	ibrahim	ibrahim	PROPN
cana-4763	365	16	,	,	PUNCT
cana-4763	365	17	h.m	h.m	PROPN
cana-4763	365	18	.	.	PROPN
cana-4763	365	19	et	et	PROPN
cana-4763	365	20	al	al	PROPN
cana-4763	365	21	.	.	PUNCT
cana-4763	366	1	a	a	DET
cana-4763	366	2	novel	novel	ADJ
cana-4763	366	3	cnn	cnn	NOUN
cana-4763	366	4	architecture	architecture	NOUN
cana-4763	366	5	for	for	ADP
cana-4763	366	6	accurate	accurate	ADJ
cana-4763	366	7	early	early	ADJ
cana-4763	366	8	detection	detection	NOUN
cana-4763	366	9	and	and	CCONJ
cana-4763	366	10	classification	classification	NOUN
cana-4763	366	11	of	of	ADP
cana-4763	366	12	alzheimer	alzheimer	PROPN
cana-4763	366	13	’s	’s	PART
cana-4763	366	14	disease	disease	NOUN
cana-4763	366	15	using	use	VERB
cana-4763	366	16	mri	mri	NOUN
cana-4763	366	17	data	datum	NOUN
cana-4763	366	18	.	.	PUNCT
cana-4763	367	1	sci	sci	PROPN
cana-4763	367	2	rep	rep	PROPN
cana-4763	367	3	14	14	NUM
cana-4763	367	4	,	,	PUNCT
cana-4763	367	5	3463	3463	NUM
cana-4763	367	6	,	,	PUNCT
cana-4763	367	7	2024	2024	NUM
cana-4763	367	8	.	.	PUNCT
cana-4763	368	1	[	[	X
cana-4763	368	2	27	27	NUM
cana-4763	368	3	]	]	X
cana-4763	368	4	mohamed	mohamed	PROPN
cana-4763	368	5	r.	r.	PROPN
cana-4763	368	6	shoaib	shoaib	PROPN
cana-4763	368	7	,	,	PUNCT
cana-4763	368	8	jun	jun	PROPN
cana-4763	368	9	zhao	zhao	PROPN
cana-4763	368	10	,	,	PUNCT
cana-4763	368	11	heba	heba	PROPN
cana-4763	368	12	m.	m.	PROPN
cana-4763	368	13	emara	emara	PROPN
cana-4763	368	14	,	,	PUNCT
cana-4763	368	15	ahmed	ahmed	PROPN
cana-4763	368	16	f.s	f.s	PROPN
cana-4763	368	17	.	.	PROPN
cana-4763	368	18	mubarak	mubarak	PROPN
cana-4763	368	19	,	,	PUNCT
cana-4763	368	20	osama	osama	PROPN
cana-4763	368	21	a.	a.	NOUN
cana-4763	368	22	omer	omer	PROPN
cana-4763	368	23	,	,	PUNCT
cana-4763	368	24	fathi	fathi	PROPN
cana-4763	368	25	e.	e.	PROPN
cana-4763	368	26	abd	abd	PROPN
cana-4763	368	27	el	el	PROPN
cana-4763	368	28	-	-	PUNCT
cana-4763	368	29	samie	samie	PROPN
cana-4763	368	30	,	,	PUNCT
cana-4763	368	31	hamada	hamada	PROPN
cana-4763	368	32	esmaiel	esmaiel	PROPN
cana-4763	368	33	,	,	PUNCT
cana-4763	368	34	improving	improve	VERB
cana-4763	368	35	brain	brain	NOUN
cana-4763	368	36	tumor	tumor	NOUN
cana-4763	368	37	classification	classification	NOUN
cana-4763	368	38	:	:	PUNCT
cana-4763	368	39	an	an	DET
cana-4763	368	40	approach	approach	NOUN
cana-4763	368	41	integrating	integrating	NOUN
cana-4763	368	42	pretrained	pretraine	VERB
cana-4763	368	43	cnn	cnn	PROPN
cana-4763	368	44	models	model	NOUN
cana-4763	368	45	and	and	CCONJ
cana-4763	368	46	machine	machine	NOUN
cana-4763	368	47	learning	learning	NOUN
cana-4763	368	48	algorithms	algorithm	NOUN
cana-4763	368	49	,	,	PUNCT
cana-4763	368	50	heliyon	heliyon	NOUN
cana-4763	368	51	,	,	PUNCT
cana-4763	368	52	issn	issn	PROPN
cana-4763	368	53	2405	2405	NUM
cana-4763	368	54	-	-	SYM
cana-4763	368	55	8440	8440	NUM
cana-4763	368	56	,	,	PUNCT
cana-4763	368	57	e33471	e33471	PROPN
cana-4763	368	58	,	,	PUNCT
cana-4763	368	59	2024	2024	NUM
cana-4763	368	60	.	.	PUNCT
cana-4763	369	1	[	[	X
cana-4763	369	2	28	28	NUM
cana-4763	369	3	]	]	X
cana-4763	369	4	b.	b.	PROPN
cana-4763	369	5	h.	h.	PROPN
cana-4763	369	6	menze	menze	PROPN
cana-4763	369	7	,	,	PUNCT
cana-4763	369	8	a.	a.	PROPN
cana-4763	369	9	jakab	jakab	PROPN
cana-4763	369	10	,	,	PUNCT
cana-4763	369	11	s.	s.	PROPN
cana-4763	369	12	bauer	bauer	PROPN
cana-4763	369	13	,	,	PUNCT
cana-4763	369	14	j.	j.	PROPN
cana-4763	369	15	kalpathy	kalpathy	PROPN
cana-4763	369	16	-	-	PUNCT
cana-4763	369	17	cramer	cramer	PROPN
cana-4763	369	18	,	,	PUNCT
cana-4763	369	19	k.	k.	PROPN
cana-4763	369	20	farahani	farahani	PROPN
cana-4763	369	21	,	,	PUNCT
cana-4763	369	22	j.	j.	PROPN
cana-4763	369	23	kirby	kirby	PROPN
cana-4763	369	24	,	,	PUNCT
cana-4763	369	25	et	et	PROPN
cana-4763	369	26	al	al	PROPN
cana-4763	369	27	.	.	PUNCT
cana-4763	370	1	"	"	PUNCT
cana-4763	370	2	the	the	DET
cana-4763	370	3	multimodal	multimodal	ADJ
cana-4763	370	4	brain	brain	NOUN
cana-4763	370	5	tumor	tumor	NOUN
cana-4763	370	6	image	image	NOUN
cana-4763	370	7	segmentation	segmentation	NOUN
cana-4763	370	8	benchmark	benchmark	NOUN
cana-4763	370	9	(	(	PUNCT
cana-4763	370	10	brats	brat	NOUN
cana-4763	370	11	)	)	PUNCT
cana-4763	370	12	"	"	PUNCT
cana-4763	370	13	,	,	PUNCT
cana-4763	370	14	ieee	ieee	NOUN
cana-4763	370	15	transactions	transaction	NOUN
cana-4763	370	16	on	on	ADP
cana-4763	370	17	medical	medical	ADJ
cana-4763	370	18	imaging	imaging	NOUN
cana-4763	370	19	34(10	34(10	NUM
cana-4763	370	20	)	)	PUNCT
cana-4763	370	21	,	,	PUNCT
cana-4763	370	22	1993	1993	NUM
cana-4763	370	23	-	-	SYM
cana-4763	370	24	2024	2024	NUM
cana-4763	370	25	,	,	PUNCT
cana-4763	370	26	2015	2015	NUM
cana-4763	370	27	.	.	PUNCT
cana-4763	371	1	[	[	X
cana-4763	371	2	29	29	NUM
cana-4763	371	3	]	]	X
cana-4763	371	4	ari	ari	PROPN
cana-4763	371	5	,	,	PUNCT
cana-4763	371	6	a.	a.	PROPN
cana-4763	371	7	&	&	CCONJ
cana-4763	371	8	hanbay	hanbay	PROPN
cana-4763	371	9	,	,	PUNCT
cana-4763	371	10	d.	d.	PROPN
cana-4763	371	11	deep	deep	PROPN
cana-4763	371	12	learning	learning	NOUN
cana-4763	371	13	-	-	PUNCT
cana-4763	371	14	based	base	VERB
cana-4763	371	15	brain	brain	NOUN
cana-4763	371	16	tumor	tumor	NOUN
cana-4763	371	17	classification	classification	NOUN
cana-4763	371	18	and	and	CCONJ
cana-4763	371	19	detection	detection	NOUN
cana-4763	371	20	system	system	NOUN
cana-4763	371	21	.	.	PUNCT
cana-4763	372	1	turk	turk	PROPN
cana-4763	372	2	.	.	PUNCT
cana-4763	373	1	j.	j.	PROPN
cana-4763	373	2	electr	electr	PROPN
cana-4763	373	3	.	.	PUNCT
cana-4763	374	1	eng	eng	PROPN
cana-4763	374	2	.	.	PUNCT
cana-4763	375	1	comput	comput	PROPN
cana-4763	375	2	.	.	PUNCT
cana-4763	376	1	sci	sci	PROPN
cana-4763	376	2	.	.	PUNCT
cana-4763	376	3	26(5	26(5	PROPN
cana-4763	376	4	)	)	PUNCT
cana-4763	376	5	,	,	PUNCT
cana-4763	376	6	2275–2286	2275–2286	NUM
cana-4763	376	7	,	,	PUNCT
cana-4763	376	8	2018	2018	NUM
cana-4763	376	9	.	.	PUNCT
cana-4763	377	1	[	[	X
cana-4763	377	2	30	30	NUM
cana-4763	377	3	]	]	X
cana-4763	377	4	alqudah	alqudah	NOUN
cana-4763	377	5	,	,	PUNCT
cana-4763	377	6	a.	a.	NOUN
cana-4763	377	7	m.	m.	NOUN
cana-4763	377	8	,	,	PUNCT
cana-4763	377	9	alquraan	alquraan	PROPN
cana-4763	377	10	,	,	PUNCT
cana-4763	377	11	h.	h.	PROPN
cana-4763	377	12	,	,	PUNCT
cana-4763	377	13	qasmieh	qasmieh	PROPN
cana-4763	377	14	,	,	PUNCT
cana-4763	377	15	i.	i.	PROPN
cana-4763	377	16	a.	a.	PROPN
cana-4763	377	17	,	,	PUNCT
cana-4763	377	18	alqudah	alqudah	PROPN
cana-4763	377	19	,	,	PUNCT
cana-4763	377	20	a.	a.	PROPN
cana-4763	377	21	&	&	CCONJ
cana-4763	377	22	al	al	PROPN
cana-4763	377	23	-	-	PUNCT
cana-4763	377	24	sharu	sharu	PROPN
cana-4763	377	25	,	,	PUNCT
cana-4763	377	26	w.	w.	PROPN
cana-4763	377	27	brain	brain	PROPN
cana-4763	377	28	tumor	tumor	NOUN
cana-4763	377	29	classification	classification	NOUN
cana-4763	377	30	using	use	VERB
cana-4763	377	31	deep	deep	ADJ
cana-4763	377	32	learning	learning	NOUN
cana-4763	377	33	technique	technique	NOUN
cana-4763	377	34	—	—	PUNCT
cana-4763	377	35	a	a	DET
cana-4763	377	36	comparison	comparison	NOUN
cana-4763	377	37	between	between	ADP
cana-4763	377	38	cropped	cropped	ADJ
cana-4763	377	39	,	,	PUNCT
cana-4763	377	40	uncropped	uncropped	ADJ
cana-4763	377	41	,	,	PUNCT
cana-4763	377	42	and	and	CCONJ
cana-4763	377	43	segmented	segment	VERB
cana-4763	377	44	lesion	lesion	NOUN
cana-4763	377	45	images	image	NOUN
cana-4763	377	46	with	with	ADP
cana-4763	377	47	different	different	ADJ
cana-4763	377	48	.	.	PUNCT
cana-4763	378	1	int	int	NOUN
cana-4763	378	2	.	.	PUNCT
cana-4763	379	1	j.	j.	PROPN
cana-4763	379	2	adv	adv	PROPN
cana-4763	379	3	.	.	PUNCT
cana-4763	379	4	trends	trend	NOUN
cana-4763	379	5	comput	comput	NOUN
cana-4763	379	6	.	.	PUNCT
cana-4763	380	1	sci	sci	PROPN
cana-4763	380	2	.	.	PUNCT
cana-4763	381	1	eng	eng	PROPN
cana-4763	381	2	.	.	PROPN
cana-4763	381	3	8(6	8(6	NUM
cana-4763	381	4	)	)	PUNCT
cana-4763	381	5	,	,	PUNCT
cana-4763	381	6	3684–3691,2019	3684–3691,2019	NUM
cana-4763	381	7	.	.	PUNCT
cana-4763	382	1	[	[	X
cana-4763	382	2	31	31	NUM
cana-4763	382	3	]	]	X
cana-4763	382	4	rehman	rehman	PROPN
cana-4763	382	5	,	,	PUNCT
cana-4763	382	6	a.	a.	PROPN
cana-4763	382	7	,	,	PUNCT
cana-4763	382	8	naz	naz	PROPN
cana-4763	382	9	,	,	PUNCT
cana-4763	382	10	s.	s.	PROPN
cana-4763	382	11	,	,	PUNCT
cana-4763	382	12	razzak	razzak	PROPN
cana-4763	382	13	,	,	PUNCT
cana-4763	382	14	m.	m.	NOUN
cana-4763	382	15	i.	i.	PROPN
cana-4763	382	16	,	,	PUNCT
cana-4763	382	17	akram	akram	PROPN
cana-4763	382	18	,	,	PUNCT
cana-4763	382	19	f.	f.	PROPN
cana-4763	382	20	&	&	CCONJ
cana-4763	382	21	imran	imran	PROPN
cana-4763	382	22	,	,	PUNCT
cana-4763	382	23	m.	m.	NOUN
cana-4763	382	24	a	a	DET
cana-4763	382	25	deep	deep	ADJ
cana-4763	382	26	learning	learning	NOUN
cana-4763	382	27	-	-	PUNCT
cana-4763	382	28	based	base	VERB
cana-4763	382	29	framework	framework	NOUN
cana-4763	382	30	for	for	ADP
cana-4763	382	31	automatic	automatic	ADJ
cana-4763	382	32	brain	brain	NOUN
cana-4763	382	33	tumors	tumor	NOUN
cana-4763	382	34	classification	classification	NOUN
cana-4763	382	35	using	use	VERB
cana-4763	382	36	transfer	transfer	NOUN
cana-4763	382	37	learning	learning	NOUN
cana-4763	382	38	.	.	PUNCT
cana-4763	383	1	circ	circ	PROPN
cana-4763	383	2	.	.	PUNCT
cana-4763	384	1	syst	syst	PROPN
cana-4763	384	2	.	.	PUNCT
cana-4763	384	3	signal	signal	PROPN
cana-4763	384	4	process	process	NOUN
cana-4763	384	5	.	.	PUNCT
cana-4763	385	1	39(1	39(1	NUM
cana-4763	385	2	)	)	PUNCT
cana-4763	385	3	,	,	PUNCT
cana-4763	386	1	757–775	757–775	NUM
cana-4763	386	2	,	,	PUNCT
cana-4763	386	3	2020	2020	NUM
cana-4763	386	4	.	.	PUNCT
cana-4763	387	1	https://www.jisem-journal.com/index.php/journal/issue/view/25	https://www.jisem-journal.com/index.php/journal/issue/view/25	NOUN
cana-4763	387	2	https://doi.org/10.3390/diagnostics13050864	https://doi.org/10.3390/diagnostics13050864	NOUN
cana-4763	387	3	https://www.ncbi.nlm.nih.gov/pubmed/25494501	https://www.ncbi.nlm.nih.gov/pubmed/25494501	NUM
cana-4763	387	4	https://www.ncbi.nlm.nih.gov/pubmed/25494501	https://www.ncbi.nlm.nih.gov/pubmed/25494501	NUM
cana-4763	387	5	https://www.ncbi.nlm.nih.gov/pubmed/25494501	https://www.ncbi.nlm.nih.gov/pubmed/25494501	NUM
cana-4763	387	6	communications	communication	NOUN
cana-4763	387	7	on	on	ADP
cana-4763	387	8	applied	apply	VERB
cana-4763	387	9	nonlinear	nonlinear	ADJ
cana-4763	387	10	analysis	analysis	NOUN
cana-4763	387	11	issn	issn	NOUN
cana-4763	387	12	:	:	PUNCT
cana-4763	387	13	1074	1074	NUM
cana-4763	387	14	-	-	PUNCT
cana-4763	387	15	133x	133x	NUM
cana-4763	387	16	vol	vol	VERB
cana-4763	387	17	32	32	NUM
cana-4763	387	18	no	no	NOUN
cana-4763	387	19	.	.	PUNCT
cana-4763	388	1	10s	10	NOUN
cana-4763	388	2	(	(	PUNCT
cana-4763	388	3	2025	2025	NUM
cana-4763	388	4	)	)	PUNCT
cana-4763	388	5	312	312	NUM
cana-4763	388	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4763	389	1	[	[	X
cana-4763	389	2	32	32	NUM
cana-4763	389	3	]	]	PUNCT
cana-4763	389	4	díaz	díaz	NOUN
cana-4763	389	5	-	-	PUNCT
cana-4763	389	6	pernas	pernas	PROPN
cana-4763	389	7	,	,	PUNCT
cana-4763	389	8	f.	f.	PROPN
cana-4763	389	9	j.	j.	PROPN
cana-4763	389	10	,	,	PUNCT
cana-4763	389	11	martínez	martínez	PROPN
cana-4763	389	12	-	-	PUNCT
cana-4763	389	13	zarzuela	zarzuela	PROPN
cana-4763	389	14	,	,	PUNCT
cana-4763	389	15	m.	m.	NOUN
cana-4763	389	16	,	,	PUNCT
cana-4763	389	17	antón	antón	NOUN
cana-4763	389	18	-	-	PUNCT
cana-4763	389	19	rodríguez	rodríguez	NOUN
cana-4763	389	20	,	,	PUNCT
cana-4763	389	21	m.	m.	NOUN
cana-4763	389	22	&	&	CCONJ
cana-4763	389	23	gonzález	gonzález	PROPN
cana-4763	389	24	-	-	PUNCT
cana-4763	389	25	ortega	ortega	PROPN
cana-4763	389	26	,	,	PUNCT
cana-4763	389	27	d.	d.	PROPN
cana-4763	389	28	a	a	DET
cana-4763	389	29	deep	deep	ADJ
cana-4763	389	30	learning	learning	NOUN
cana-4763	389	31	approach	approach	NOUN
cana-4763	389	32	for	for	ADP
cana-4763	389	33	brain	brain	NOUN
cana-4763	389	34	tumor	tumor	NOUN
cana-4763	389	35	classification	classification	NOUN
cana-4763	389	36	and	and	CCONJ
cana-4763	389	37	segmentation	segmentation	NOUN
cana-4763	389	38	using	use	VERB
cana-4763	389	39	a	a	DET
cana-4763	389	40	multiscale	multiscale	ADJ
cana-4763	389	41	convolutional	convolutional	ADJ
cana-4763	389	42	neural	neural	ADJ
cana-4763	389	43	network	network	NOUN
cana-4763	389	44	.	.	PUNCT
cana-4763	390	1	feature	feature	NOUN
cana-4763	390	2	papers	paper	NOUN
cana-4763	390	3	artif	artif	ADV
cana-4763	390	4	.	.	PUNCT
cana-4763	391	1	intell	intell	PROPN
cana-4763	391	2	.	.	PUNCT
cana-4763	392	1	med	med	PROPN
cana-4763	392	2	.	.	PUNCT
cana-4763	393	1	9(2	9(2	NUM
cana-4763	393	2	)	)	PUNCT
cana-4763	394	1	,	,	PUNCT
cana-4763	394	2	1–14	1–14	PROPN
cana-4763	394	3	,	,	PUNCT
cana-4763	394	4	2021	2021	NUM
cana-4763	394	5	.	.	PUNCT
cana-4763	395	1	[	[	X
cana-4763	395	2	33	33	NUM
cana-4763	395	3	]	]	PUNCT
cana-4763	395	4	sarkar	sarkar	PROPN
cana-4763	395	5	,	,	PUNCT
cana-4763	395	6	a.	a.	PROPN
cana-4763	395	7	,	,	PUNCT
cana-4763	395	8	maniruzzaman	maniruzzaman	NOUN
cana-4763	395	9	,	,	PUNCT
cana-4763	395	10	m.	m.	NOUN
cana-4763	395	11	a.	a.	PROPN
cana-4763	395	12	&	&	CCONJ
cana-4763	395	13	alahe	alahe	PROPN
cana-4763	395	14	,	,	PUNCT
cana-4763	395	15	m.	m.	NOUN
cana-4763	395	16	a.	a.	NOUN
cana-4763	395	17	an	an	DET
cana-4763	395	18	effective	effective	ADJ
cana-4763	395	19	and	and	CCONJ
cana-4763	395	20	novel	novel	ADJ
cana-4763	395	21	approach	approach	NOUN
cana-4763	395	22	for	for	ADP
cana-4763	395	23	brain	brain	NOUN
cana-4763	395	24	tumor	tumor	NOUN
cana-4763	395	25	classification	classification	NOUN
cana-4763	395	26	using	use	VERB
cana-4763	395	27	alexnet	alexnet	ADJ
cana-4763	395	28	cnn	cnn	PROPN
cana-4763	395	29	feature	feature	NOUN
cana-4763	395	30	extractor	extractor	NOUN
cana-4763	395	31	and	and	CCONJ
cana-4763	395	32	multiple	multiple	ADJ
cana-4763	395	33	eminent	eminent	ADJ
cana-4763	395	34	machine	machine	NOUN
cana-4763	395	35	learning	learn	VERB
cana-4763	395	36	classifiers	classifier	NOUN
cana-4763	395	37	in	in	ADP
cana-4763	395	38	mris	mris	PROPN
cana-4763	395	39	.	.	PUNCT
cana-4763	396	1	j.	j.	PROPN
cana-4763	396	2	sensors	sensors	PROPN
cana-4763	396	3	hindawi	hindawi	VERB
cana-4763	396	4	1224619	1224619	NUM
cana-4763	396	5	,	,	PUNCT
cana-4763	396	6	1–19	1–19	NOUN
cana-4763	396	7	,	,	PUNCT
cana-4763	396	8	2023	2023	NUM
cana-4763	396	9	.	.	PUNCT