id	sid	tid	token	lemma	pos
cana-2347	1	1	communications	communication	NOUN
cana-2347	1	2	on	on	ADP
cana-2347	1	3	applied	apply	VERB
cana-2347	1	4	nonlinear	nonlinear	ADJ
cana-2347	1	5	analysis	analysis	NOUN
cana-2347	1	6	issn	issn	NOUN
cana-2347	1	7	:	:	PUNCT
cana-2347	1	8	1074	1074	NUM
cana-2347	1	9	-	-	PUNCT
cana-2347	1	10	133x	133x	NUM
cana-2347	1	11	vol	vol	NOUN
cana-2347	1	12	32	32	NUM
cana-2347	1	13	no	no	NOUN
cana-2347	1	14	.	.	PUNCT
cana-2347	2	1	1s	1s	NUM
cana-2347	2	2	(	(	PUNCT
cana-2347	2	3	2025	2025	NUM
cana-2347	2	4	)	)	PUNCT
cana-2347	2	5	611	611	NUM
cana-2347	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	2	7	cutting	cutting	NOUN
cana-2347	2	8	-	-	PUNCT
cana-2347	2	9	edge	edge	NOUN
cana-2347	2	10	deep	deep	ADJ
cana-2347	2	11	learning	learning	NOUN
cana-2347	2	12	strategies	strategy	NOUN
cana-2347	2	13	for	for	ADP
cana-2347	2	14	precise	precise	ADJ
cana-2347	2	15	ovarian	ovarian	ADJ
cana-2347	2	16	disease	disease	NOUN
cana-2347	2	17	detection	detection	NOUN
cana-2347	2	18	:	:	PUNCT
cana-2347	2	19	a	a	DET
cana-2347	2	20	comprehensive	comprehensive	ADJ
cana-2347	2	21	review	review	NOUN
cana-2347	2	22	soumya	soumya	ADV
cana-2347	2	23	koshy1	koshy1	PROPN
cana-2347	2	24	,	,	PUNCT
cana-2347	3	1	dr	dr	PROPN
cana-2347	3	2	.	.	PROPN
cana-2347	3	3	k.	k.	PROPN
cana-2347	3	4	ranjith	ranjith	PROPN
cana-2347	3	5	singh2	singh2	PROPN
cana-2347	4	1	*	*	PUNCT
cana-2347	4	2	1	1	NUM
cana-2347	4	3	research	research	NOUN
cana-2347	4	4	scholar	scholar	NOUN
cana-2347	4	5	,	,	PUNCT
cana-2347	4	6	karpagam	karpagam	PROPN
cana-2347	4	7	academy	academy	PROPN
cana-2347	4	8	of	of	ADP
cana-2347	4	9	higher	high	ADJ
cana-2347	4	10	education	education	NOUN
cana-2347	4	11	,	,	PUNCT
cana-2347	4	12	coimbatore	coimbatore	PROPN
cana-2347	4	13	,	,	PUNCT
cana-2347	4	14	soumyakoshy@kjcmt.ac.in	soumyakoshy@kjcmt.ac.in	NOUN
cana-2347	4	15	,	,	PUNCT
cana-2347	4	16	orchid	orchid	NOUN
cana-2347	4	17	i	i	NOUN
cana-2347	4	18	d	d	PROPN
cana-2347	4	19	:	:	PUNCT
cana-2347	4	20	00090008	00090008	NUM
cana-2347	4	21	-	-	SYM
cana-2347	4	22	5761	5761	NUM
cana-2347	4	23	-	-	SYM
cana-2347	4	24	6451	6451	NUM
cana-2347	4	25	2	2	NUM
cana-2347	4	26	hod	hod	NOUN
cana-2347	4	27	,	,	PUNCT
cana-2347	4	28	dept	dept	NOUN
cana-2347	4	29	.	.	PROPN
cana-2347	4	30	of	of	ADP
cana-2347	4	31	computer	computer	NOUN
cana-2347	4	32	technology	technology	NOUN
cana-2347	4	33	,	,	PUNCT
cana-2347	4	34	karpagam	karpagam	PROPN
cana-2347	4	35	academy	academy	PROPN
cana-2347	4	36	of	of	ADP
cana-2347	4	37	higher	high	ADJ
cana-2347	4	38	education	education	NOUN
cana-2347	4	39	,	,	PUNCT
cana-2347	4	40	coimbatore	coimbatore	PROPN
cana-2347	4	41	,	,	PUNCT
cana-2347	4	42	ranjithsingh.koppaiyan@kahedu.edu.in	ranjithsingh.koppaiyan@kahedu.edu.in	NOUN
cana-2347	4	43	,	,	PUNCT
cana-2347	4	44	orchid:(https://orcid.org/0000	orchid:(https://orcid.org/0000	VERB
cana-2347	4	45	-	-	PUNCT
cana-2347	4	46	0003	0003	NUM
cana-2347	4	47	-	-	PUNCT
cana-2347	4	48	2651	2651	NUM
cana-2347	4	49	-	-	PUNCT
cana-2347	4	50	2509	2509	NUM
cana-2347	4	51	)	)	PUNCT
cana-2347	4	52	article	article	NOUN
cana-2347	4	53	history	history	NOUN
cana-2347	4	54	:	:	PUNCT
cana-2347	4	55	received	receive	VERB
cana-2347	4	56	:	:	PUNCT
cana-2347	4	57	03	03	NUM
cana-2347	4	58	-	-	PUNCT
cana-2347	4	59	09	09	NUM
cana-2347	4	60	-	-	PUNCT
cana-2347	4	61	2024	2024	NUM
cana-2347	4	62	revised	revise	VERB
cana-2347	4	63	:	:	PUNCT
cana-2347	4	64	18	18	NUM
cana-2347	4	65	-	-	SYM
cana-2347	4	66	10	10	NUM
cana-2347	4	67	-	-	PUNCT
cana-2347	4	68	2024	2024	NUM
cana-2347	4	69	accepted	accept	VERB
cana-2347	4	70	:	:	PUNCT
cana-2347	4	71	02	02	NUM
cana-2347	4	72	-	-	SYM
cana-2347	4	73	11	11	NUM
cana-2347	4	74	-	-	PUNCT
cana-2347	4	75	2024	2024	NUM
cana-2347	4	76	abstract	abstract	NOUN
cana-2347	4	77	:	:	PUNCT
cana-2347	4	78	accurate	accurate	ADJ
cana-2347	4	79	and	and	CCONJ
cana-2347	4	80	timely	timely	ADJ
cana-2347	4	81	diagnosis	diagnosis	NOUN
cana-2347	4	82	of	of	ADP
cana-2347	4	83	ovary	ovary	ADJ
cana-2347	4	84	-	-	PUNCT
cana-2347	4	85	related	relate	VERB
cana-2347	4	86	diseases	disease	NOUN
cana-2347	4	87	is	be	AUX
cana-2347	4	88	of	of	ADP
cana-2347	4	89	paramount	paramount	ADJ
cana-2347	4	90	importance	importance	NOUN
cana-2347	4	91	in	in	ADP
cana-2347	4	92	the	the	DET
cana-2347	4	93	realm	realm	NOUN
cana-2347	4	94	of	of	ADP
cana-2347	4	95	medical	medical	ADJ
cana-2347	4	96	imaging	imaging	NOUN
cana-2347	4	97	.	.	PUNCT
cana-2347	5	1	utilizing	utilize	VERB
cana-2347	5	2	deep	deep	ADJ
cana-2347	5	3	learning	learning	NOUN
cana-2347	5	4	technology	technology	NOUN
cana-2347	5	5	has	have	AUX
cana-2347	5	6	emerged	emerge	VERB
cana-2347	5	7	as	as	ADP
cana-2347	5	8	a	a	DET
cana-2347	5	9	viable	viable	ADJ
cana-2347	5	10	method	method	NOUN
cana-2347	5	11	to	to	PART
cana-2347	5	12	improve	improve	VERB
cana-2347	5	13	the	the	DET
cana-2347	5	14	precision	precision	NOUN
cana-2347	5	15	and	and	CCONJ
cana-2347	5	16	effectiveness	effectiveness	NOUN
cana-2347	5	17	of	of	ADP
cana-2347	5	18	medical	medical	ADJ
cana-2347	5	19	image	image	NOUN
cana-2347	5	20	segmentation	segmentation	NOUN
cana-2347	5	21	,	,	PUNCT
cana-2347	5	22	which	which	PRON
cana-2347	5	23	directly	directly	ADV
cana-2347	5	24	impacts	impact	VERB
cana-2347	5	25	the	the	DET
cana-2347	5	26	detection	detection	NOUN
cana-2347	5	27	of	of	ADP
cana-2347	5	28	ovarian	ovarian	ADJ
cana-2347	5	29	diseases	disease	NOUN
cana-2347	5	30	.	.	PUNCT
cana-2347	6	1	ovarian	ovarian	ADJ
cana-2347	6	2	disease	disease	NOUN
cana-2347	6	3	detection	detection	NOUN
cana-2347	6	4	through	through	ADP
cana-2347	6	5	medical	medical	ADJ
cana-2347	6	6	image	image	NOUN
cana-2347	6	7	segmentation	segmentation	NOUN
cana-2347	6	8	is	be	AUX
cana-2347	6	9	critical	critical	ADJ
cana-2347	6	10	for	for	ADP
cana-2347	6	11	early	early	ADJ
cana-2347	6	12	diagnosis	diagnosis	NOUN
cana-2347	6	13	and	and	CCONJ
cana-2347	6	14	effective	effective	ADJ
cana-2347	6	15	treatment	treatment	NOUN
cana-2347	6	16	.	.	PUNCT
cana-2347	7	1	this	this	DET
cana-2347	7	2	study	study	NOUN
cana-2347	7	3	evaluates	evaluate	VERB
cana-2347	7	4	cutting	cut	VERB
cana-2347	7	5	-	-	PUNCT
cana-2347	7	6	edge	edge	NOUN
cana-2347	7	7	deep	deep	ADJ
cana-2347	7	8	learning	learning	NOUN
cana-2347	7	9	strategies	strategy	NOUN
cana-2347	7	10	using	use	VERB
cana-2347	7	11	the	the	DET
cana-2347	7	12	mmotu	mmotu	ADJ
cana-2347	7	13	ovarian	ovarian	ADJ
cana-2347	7	14	tumour	tumour	NOUN
cana-2347	7	15	ultrasound	ultrasound	NOUN
cana-2347	7	16	dataset	dataset	NOUN
cana-2347	7	17	,	,	PUNCT
cana-2347	7	18	which	which	PRON
cana-2347	7	19	includes	include	VERB
cana-2347	7	20	otu	otu	PROPN
cana-2347	7	21	2d	2d	PROPN
cana-2347	7	22	and	and	CCONJ
cana-2347	7	23	otu	otu	PROPN
cana-2347	7	24	ceus	ceus	PROPN
cana-2347	7	25	subsets	subset	VERB
cana-2347	7	26	.	.	PUNCT
cana-2347	8	1	we	we	PRON
cana-2347	8	2	implemented	implement	VERB
cana-2347	8	3	various	various	ADJ
cana-2347	8	4	models	model	NOUN
cana-2347	8	5	,	,	PUNCT
cana-2347	8	6	including	include	VERB
cana-2347	8	7	u	u	NOUN
cana-2347	8	8	-	-	NOUN
cana-2347	8	9	net	net	ADJ
cana-2347	8	10	,	,	PUNCT
cana-2347	8	11	its	its	PRON
cana-2347	8	12	variants	variant	NOUN
cana-2347	8	13	with	with	ADP
cana-2347	8	14	resnet	resnet	NOUN
cana-2347	8	15	and	and	CCONJ
cana-2347	8	16	densenet	densenet	NOUN
cana-2347	8	17	backbones	backbone	NOUN
cana-2347	8	18	,	,	PUNCT
cana-2347	8	19	cr	cr	NOUN
cana-2347	8	20	-	-	PUNCT
cana-2347	8	21	unet	unet	NOUN
cana-2347	8	22	,	,	PUNCT
cana-2347	8	23	and	and	CCONJ
cana-2347	8	24	ocys	ocy	NOUN
cana-2347	8	25	-	-	PUNCT
cana-2347	8	26	net	net	NOUN
cana-2347	8	27	,	,	PUNCT
cana-2347	8	28	along	along	ADP
cana-2347	8	29	with	with	ADP
cana-2347	8	30	ensemble	ensemble	ADJ
cana-2347	8	31	learning	learning	NOUN
cana-2347	8	32	and	and	CCONJ
cana-2347	8	33	transfer	transfer	VERB
cana-2347	8	34	learning	learning	NOUN
cana-2347	8	35	techniques	technique	NOUN
cana-2347	8	36	.	.	PUNCT
cana-2347	9	1	results	result	NOUN
cana-2347	9	2	show	show	VERB
cana-2347	9	3	that	that	SCONJ
cana-2347	9	4	while	while	SCONJ
cana-2347	9	5	the	the	DET
cana-2347	9	6	baseline	baseline	ADJ
cana-2347	9	7	u	u	NOUN
cana-2347	9	8	-	-	NOUN
cana-2347	9	9	net	net	ADJ
cana-2347	9	10	is	be	AUX
cana-2347	9	11	effective	effective	ADJ
cana-2347	9	12	,	,	PUNCT
cana-2347	9	13	advanced	advanced	ADJ
cana-2347	9	14	models	model	NOUN
cana-2347	9	15	,	,	PUNCT
cana-2347	9	16	particularly	particularly	ADV
cana-2347	9	17	cr	cr	NOUN
cana-2347	9	18	-	-	PUNCT
cana-2347	9	19	unet	unet	NOUN
cana-2347	9	20	and	and	CCONJ
cana-2347	9	21	densenet	densenet	NOUN
cana-2347	9	22	,	,	PUNCT
cana-2347	9	23	significantly	significantly	ADV
cana-2347	9	24	improve	improve	VERB
cana-2347	9	25	segmentation	segmentation	NOUN
cana-2347	9	26	accuracy	accuracy	NOUN
cana-2347	9	27	.	.	PUNCT
cana-2347	10	1	the	the	DET
cana-2347	10	2	best	good	ADJ
cana-2347	10	3	performance	performance	NOUN
cana-2347	10	4	was	be	AUX
cana-2347	10	5	achieved	achieve	VERB
cana-2347	10	6	using	use	VERB
cana-2347	10	7	an	an	DET
cana-2347	10	8	ensemble	ensemble	ADJ
cana-2347	10	9	model	model	NOUN
cana-2347	10	10	and	and	CCONJ
cana-2347	10	11	a	a	DET
cana-2347	10	12	fine	fine	ADV
cana-2347	10	13	-	-	PUNCT
cana-2347	10	14	tuned	tune	VERB
cana-2347	10	15	pre	pre	ADJ
cana-2347	10	16	-	-	ADJ
cana-2347	10	17	trained	train	VERB
cana-2347	10	18	network	network	NOUN
cana-2347	10	19	,	,	PUNCT
cana-2347	10	20	highlighting	highlight	VERB
cana-2347	10	21	the	the	DET
cana-2347	10	22	potential	potential	NOUN
cana-2347	10	23	of	of	ADP
cana-2347	10	24	these	these	DET
cana-2347	10	25	approaches	approach	NOUN
cana-2347	10	26	in	in	ADP
cana-2347	10	27	enhancing	enhance	VERB
cana-2347	10	28	the	the	DET
cana-2347	10	29	precision	precision	NOUN
cana-2347	10	30	and	and	CCONJ
cana-2347	10	31	reliability	reliability	NOUN
cana-2347	10	32	of	of	ADP
cana-2347	10	33	ovarian	ovarian	ADJ
cana-2347	10	34	disease	disease	NOUN
cana-2347	10	35	detection	detection	NOUN
cana-2347	10	36	.	.	PUNCT
cana-2347	11	1	keywords	keyword	NOUN
cana-2347	11	2	:	:	PUNCT
cana-2347	11	3	ovary	ovary	ADJ
cana-2347	11	4	,	,	PUNCT
cana-2347	11	5	deep	deep	ADJ
cana-2347	11	6	learning	learning	NOUN
cana-2347	11	7	,	,	PUNCT
cana-2347	11	8	resnet	resnet	NOUN
cana-2347	11	9	,	,	PUNCT
cana-2347	11	10	densenet	densenet	NOUN
cana-2347	11	11	,	,	PUNCT
cana-2347	11	12	u	u	NOUN
cana-2347	11	13	-	-	NOUN
cana-2347	11	14	net	net	ADJ
cana-2347	11	15	,	,	PUNCT
cana-2347	11	16	ocys	ocy	NOUN
cana-2347	11	17	-	-	PUNCT
cana-2347	11	18	net	net	NOUN
cana-2347	11	19	,	,	PUNCT
cana-2347	11	20	cr	cr	NOUN
cana-2347	11	21	-	-	PUNCT
cana-2347	11	22	unet	unet	NOUN
cana-2347	11	23	.	.	PUNCT
cana-2347	12	1	1	1	X
cana-2347	12	2	.	.	X
cana-2347	12	3	introduction	introduction	NOUN
cana-2347	12	4	the	the	DET
cana-2347	12	5	accurate	accurate	ADJ
cana-2347	12	6	and	and	CCONJ
cana-2347	12	7	timely	timely	ADJ
cana-2347	12	8	diagnosis	diagnosis	NOUN
cana-2347	12	9	of	of	ADP
cana-2347	12	10	ovary	ovary	ADJ
cana-2347	12	11	-	-	PUNCT
cana-2347	12	12	related	relate	VERB
cana-2347	12	13	diseases	disease	NOUN
cana-2347	12	14	is	be	AUX
cana-2347	12	15	a	a	DET
cana-2347	12	16	critical	critical	ADJ
cana-2347	12	17	imperative	imperative	NOUN
cana-2347	12	18	within	within	ADP
cana-2347	12	19	the	the	DET
cana-2347	12	20	realm	realm	NOUN
cana-2347	12	21	of	of	ADP
cana-2347	12	22	medical	medical	ADJ
cana-2347	12	23	imaging	imaging	NOUN
cana-2347	12	24	.	.	PUNCT
cana-2347	13	1	early	early	ADJ
cana-2347	13	2	detection	detection	NOUN
cana-2347	13	3	and	and	CCONJ
cana-2347	13	4	precise	precise	ADJ
cana-2347	13	5	delineation	delineation	NOUN
cana-2347	13	6	of	of	ADP
cana-2347	13	7	ovary	ovary	ADJ
cana-2347	13	8	abnormalities	abnormality	NOUN
cana-2347	13	9	are	be	AUX
cana-2347	13	10	pivotal	pivotal	ADJ
cana-2347	13	11	for	for	ADP
cana-2347	13	12	effective	effective	ADJ
cana-2347	13	13	clinical	clinical	ADJ
cana-2347	13	14	interventions	intervention	NOUN
cana-2347	13	15	,	,	PUNCT
cana-2347	13	16	patient	patient	ADJ
cana-2347	13	17	outcomes	outcome	NOUN
cana-2347	13	18	,	,	PUNCT
cana-2347	13	19	and	and	CCONJ
cana-2347	13	20	the	the	DET
cana-2347	13	21	progression	progression	NOUN
cana-2347	13	22	of	of	ADP
cana-2347	13	23	medical	medical	ADJ
cana-2347	13	24	research	research	NOUN
cana-2347	13	25	.	.	PUNCT
cana-2347	14	1	in	in	ADP
cana-2347	14	2	this	this	DET
cana-2347	14	3	context	context	NOUN
cana-2347	14	4	,	,	PUNCT
cana-2347	14	5	medical	medical	ADJ
cana-2347	14	6	image	image	NOUN
cana-2347	14	7	segmentation	segmentation	NOUN
cana-2347	14	8	stands	stand	VERB
cana-2347	14	9	as	as	ADP
cana-2347	14	10	a	a	DET
cana-2347	14	11	pivotal	pivotal	ADJ
cana-2347	14	12	process	process	NOUN
cana-2347	14	13	,	,	PUNCT
cana-2347	14	14	enabling	enable	VERB
cana-2347	14	15	the	the	DET
cana-2347	14	16	delineation	delineation	NOUN
cana-2347	14	17	of	of	ADP
cana-2347	14	18	regions	region	NOUN
cana-2347	14	19	of	of	ADP
cana-2347	14	20	interest	interest	NOUN
cana-2347	14	21	within	within	ADP
cana-2347	14	22	medical	medical	ADJ
cana-2347	14	23	images	image	NOUN
cana-2347	14	24	and	and	CCONJ
cana-2347	14	25	providing	provide	VERB
cana-2347	14	26	a	a	DET
cana-2347	14	27	foundation	foundation	NOUN
cana-2347	14	28	for	for	ADP
cana-2347	14	29	diagnostic	diagnostic	ADJ
cana-2347	14	30	analysis	analysis	NOUN
cana-2347	14	31	.	.	PUNCT
cana-2347	15	1	among	among	ADP
cana-2347	15	2	the	the	DET
cana-2347	15	3	manifold	manifold	ADJ
cana-2347	15	4	approaches	approach	NOUN
cana-2347	15	5	available	available	ADJ
cana-2347	15	6	for	for	ADP
cana-2347	15	7	medical	medical	ADJ
cana-2347	15	8	image	image	NOUN
cana-2347	15	9	segmentation	segmentation	NOUN
cana-2347	15	10	,	,	PUNCT
cana-2347	15	11	deep	deep	ADJ
cana-2347	15	12	learning	learning	NOUN
cana-2347	15	13	has	have	AUX
cana-2347	15	14	arisen	arise	VERB
cana-2347	15	15	as	as	ADP
cana-2347	15	16	a	a	DET
cana-2347	15	17	transformative	transformative	ADJ
cana-2347	15	18	technology	technology	NOUN
cana-2347	15	19	with	with	ADP
cana-2347	15	20	significant	significant	ADJ
cana-2347	15	21	promise	promise	NOUN
cana-2347	15	22	for	for	ADP
cana-2347	15	23	enhancing	enhance	VERB
cana-2347	15	24	both	both	DET
cana-2347	15	25	the	the	DET
cana-2347	15	26	accuracy	accuracy	NOUN
cana-2347	15	27	and	and	CCONJ
cana-2347	15	28	efficiency	efficiency	NOUN
cana-2347	15	29	of	of	ADP
cana-2347	15	30	this	this	DET
cana-2347	15	31	essential	essential	ADJ
cana-2347	15	32	task	task	NOUN
cana-2347	15	33	.	.	PUNCT
cana-2347	16	1	deep	deep	ADJ
cana-2347	16	2	learning	learning	NOUN
cana-2347	16	3	,	,	PUNCT
cana-2347	16	4	characterized	characterize	VERB
cana-2347	16	5	by	by	ADP
cana-2347	16	6	its	its	PRON
cana-2347	16	7	multi	multi	ADJ
cana-2347	16	8	-	-	ADJ
cana-2347	16	9	layered	layered	ADJ
cana-2347	16	10	neural	neural	ADJ
cana-2347	16	11	networks	network	NOUN
cana-2347	16	12	,	,	PUNCT
cana-2347	16	13	has	have	AUX
cana-2347	16	14	revolutionized	revolutionize	VERB
cana-2347	16	15	various	various	ADJ
cana-2347	16	16	fields	field	NOUN
cana-2347	16	17	of	of	ADP
cana-2347	16	18	computer	computer	NOUN
cana-2347	16	19	vision	vision	NOUN
cana-2347	16	20	,	,	PUNCT
cana-2347	16	21	including	include	VERB
cana-2347	16	22	medical	medical	ADJ
cana-2347	16	23	image	image	NOUN
cana-2347	16	24	analysis	analysis	NOUN
cana-2347	16	25	.	.	PUNCT
cana-2347	17	1	convolutional	convolutional	ADJ
cana-2347	17	2	neural	neural	ADJ
cana-2347	17	3	networks	network	NOUN
cana-2347	17	4	(	(	PUNCT
cana-2347	17	5	cnns	cnns	PROPN
cana-2347	17	6	)	)	PUNCT
cana-2347	17	7	and	and	CCONJ
cana-2347	17	8	recurrent	recurrent	ADJ
cana-2347	17	9	neural	neural	ADJ
cana-2347	17	10	networks	network	NOUN
cana-2347	17	11	(	(	PUNCT
cana-2347	17	12	rnns	rnns	PROPN
cana-2347	17	13	)	)	PUNCT
cana-2347	17	14	,	,	PUNCT
cana-2347	17	15	along	along	ADP
cana-2347	17	16	with	with	ADP
cana-2347	17	17	their	their	PRON
cana-2347	17	18	specialized	specialized	ADJ
cana-2347	17	19	variations	variation	NOUN
cana-2347	17	20	,	,	PUNCT
cana-2347	17	21	have	have	AUX
cana-2347	17	22	been	be	AUX
cana-2347	17	23	utilized	utilize	VERB
cana-2347	17	24	to	to	PART
cana-2347	17	25	tackle	tackle	VERB
cana-2347	17	26	the	the	DET
cana-2347	17	27	specific	specific	ADJ
cana-2347	17	28	difficulties	difficulty	NOUN
cana-2347	17	29	presented	present	VERB
cana-2347	17	30	by	by	ADP
cana-2347	17	31	ovarian	ovarian	ADJ
cana-2347	17	32	medical	medical	ADJ
cana-2347	17	33	image	image	NOUN
cana-2347	17	34	segmentation	segmentation	NOUN
cana-2347	17	35	.	.	PUNCT
cana-2347	18	1	these	these	DET
cana-2347	18	2	challenges	challenge	NOUN
cana-2347	18	3	include	include	VERB
cana-2347	18	4	the	the	DET
cana-2347	18	5	need	need	NOUN
cana-2347	18	6	to	to	PART
cana-2347	18	7	detect	detect	VERB
cana-2347	18	8	subtle	subtle	ADJ
cana-2347	18	9	structural	structural	ADJ
cana-2347	18	10	variations	variation	NOUN
cana-2347	18	11	,	,	PUNCT
cana-2347	18	12	accurately	accurately	ADV
cana-2347	18	13	localize	localize	VERB
cana-2347	18	14	anomalies	anomaly	NOUN
cana-2347	18	15	,	,	PUNCT
cana-2347	18	16	and	and	CCONJ
cana-2347	18	17	adapt	adapt	VERB
cana-2347	18	18	to	to	ADP
cana-2347	18	19	variations	variation	NOUN
cana-2347	18	20	in	in	ADP
cana-2347	18	21	image	image	NOUN
cana-2347	18	22	quality	quality	NOUN
cana-2347	18	23	and	and	CCONJ
cana-2347	18	24	acquisition	acquisition	NOUN
cana-2347	18	25	modalities	modality	NOUN
cana-2347	18	26	.	.	PUNCT
cana-2347	19	1	mailto:soumyakoshy@kjcmt.ac.in	mailto:soumyakoshy@kjcmt.ac.in	PROPN
cana-2347	19	2	mailto:ranjithsingh.koppaiyan@kahedu.edu.in	mailto:ranjithsingh.koppaiyan@kahedu.edu.in	PROPN
cana-2347	19	3	(	(	PUNCT
cana-2347	19	4	https:/orcid.org/0000	https:/orcid.org/0000	NOUN
cana-2347	19	5	-	-	PUNCT
cana-2347	19	6	0003	0003	NUM
cana-2347	19	7	-	-	PUNCT
cana-2347	19	8	2651	2651	NUM
cana-2347	19	9	-	-	PUNCT
cana-2347	19	10	2509	2509	NUM
cana-2347	19	11	)	)	PUNCT
cana-2347	19	12	communications	communication	NOUN
cana-2347	19	13	on	on	ADP
cana-2347	19	14	applied	apply	VERB
cana-2347	19	15	nonlinear	nonlinear	ADJ
cana-2347	19	16	analysis	analysis	NOUN
cana-2347	19	17	issn	issn	NOUN
cana-2347	19	18	:	:	PUNCT
cana-2347	19	19	1074	1074	NUM
cana-2347	19	20	-	-	PUNCT
cana-2347	19	21	133x	133x	NUM
cana-2347	19	22	vol	vol	NOUN
cana-2347	19	23	32	32	NUM
cana-2347	19	24	no	no	NOUN
cana-2347	19	25	.	.	PUNCT
cana-2347	20	1	1s	1s	NUM
cana-2347	20	2	(	(	PUNCT
cana-2347	20	3	2025	2025	NUM
cana-2347	20	4	)	)	PUNCT
cana-2347	20	5	612	612	NUM
cana-2347	20	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	21	1	this	this	DET
cana-2347	21	2	review	review	NOUN
cana-2347	21	3	paper	paper	NOUN
cana-2347	21	4	thoroughly	thoroughly	ADV
cana-2347	21	5	investigates	investigate	VERB
cana-2347	21	6	the	the	DET
cana-2347	21	7	latest	late	ADJ
cana-2347	21	8	advanced	advanced	ADJ
cana-2347	21	9	deep	deep	ADJ
cana-2347	21	10	learning	learning	NOUN
cana-2347	21	11	methods	method	NOUN
cana-2347	21	12	used	use	VERB
cana-2347	21	13	for	for	ADP
cana-2347	21	14	segmenting	segment	VERB
cana-2347	21	15	medical	medical	ADJ
cana-2347	21	16	images	image	NOUN
cana-2347	21	17	of	of	ADP
cana-2347	21	18	the	the	DET
cana-2347	21	19	ovary	ovary	NOUN
cana-2347	21	20	.	.	PUNCT
cana-2347	22	1	it	it	PRON
cana-2347	22	2	endeavours	endeavour	VERB
cana-2347	22	3	to	to	PART
cana-2347	22	4	provide	provide	VERB
cana-2347	22	5	a	a	DET
cana-2347	22	6	detailed	detailed	ADJ
cana-2347	22	7	and	and	CCONJ
cana-2347	22	8	critical	critical	ADJ
cana-2347	22	9	analysis	analysis	NOUN
cana-2347	22	10	of	of	ADP
cana-2347	22	11	the	the	DET
cana-2347	22	12	most	most	ADV
cana-2347	22	13	recent	recent	ADJ
cana-2347	22	14	advancements	advancement	NOUN
cana-2347	22	15	in	in	ADP
cana-2347	22	16	this	this	DET
cana-2347	22	17	domain	domain	NOUN
cana-2347	22	18	,	,	PUNCT
cana-2347	22	19	shedding	shed	VERB
cana-2347	22	20	light	light	NOUN
cana-2347	22	21	on	on	ADP
cana-2347	22	22	the	the	DET
cana-2347	22	23	methodologies	methodology	NOUN
cana-2347	22	24	,	,	PUNCT
cana-2347	22	25	models	model	NOUN
cana-2347	22	26	,	,	PUNCT
cana-2347	22	27	and	and	CCONJ
cana-2347	22	28	techniques	technique	NOUN
cana-2347	22	29	employed	employ	VERB
cana-2347	22	30	.	.	PUNCT
cana-2347	23	1	we	we	PRON
cana-2347	23	2	strive	strive	VERB
cana-2347	23	3	to	to	PART
cana-2347	23	4	provide	provide	VERB
cana-2347	23	5	a	a	DET
cana-2347	23	6	thorough	thorough	ADJ
cana-2347	23	7	comprehension	comprehension	NOUN
cana-2347	23	8	of	of	ADP
cana-2347	23	9	the	the	DET
cana-2347	23	10	advantages	advantage	NOUN
cana-2347	23	11	and	and	CCONJ
cana-2347	23	12	constraints	constraint	NOUN
cana-2347	23	13	of	of	ADP
cana-2347	23	14	these	these	DET
cana-2347	23	15	methods	method	NOUN
cana-2347	23	16	,	,	PUNCT
cana-2347	23	17	facilitating	facilitate	VERB
cana-2347	23	18	enhanced	enhanced	ADJ
cana-2347	23	19	accuracy	accuracy	NOUN
cana-2347	23	20	in	in	ADP
cana-2347	23	21	diagnosis	diagnosis	NOUN
cana-2347	23	22	and	and	CCONJ
cana-2347	23	23	the	the	DET
cana-2347	23	24	advancement	advancement	NOUN
cana-2347	23	25	of	of	ADP
cana-2347	23	26	medical	medical	ADJ
cana-2347	23	27	image	image	NOUN
cana-2347	23	28	segmentation	segmentation	NOUN
cana-2347	23	29	for	for	ADP
cana-2347	23	30	disorders	disorder	NOUN
cana-2347	23	31	related	relate	VERB
cana-2347	23	32	to	to	ADP
cana-2347	23	33	the	the	DET
cana-2347	23	34	ovary	ovary	NOUN
cana-2347	23	35	.	.	PUNCT
cana-2347	24	1	we	we	PRON
cana-2347	24	2	strive	strive	VERB
cana-2347	24	3	to	to	PART
cana-2347	24	4	provide	provide	VERB
cana-2347	24	5	a	a	DET
cana-2347	24	6	thorough	thorough	ADJ
cana-2347	24	7	comprehension	comprehension	NOUN
cana-2347	24	8	of	of	ADP
cana-2347	24	9	the	the	DET
cana-2347	24	10	advantages	advantage	NOUN
cana-2347	24	11	and	and	CCONJ
cana-2347	24	12	constraints	constraint	NOUN
cana-2347	24	13	of	of	ADP
cana-2347	24	14	these	these	DET
cana-2347	24	15	methods	method	NOUN
cana-2347	24	16	,	,	PUNCT
cana-2347	24	17	facilitating	facilitate	VERB
cana-2347	24	18	enhanced	enhanced	ADJ
cana-2347	24	19	accuracy	accuracy	NOUN
cana-2347	24	20	in	in	ADP
cana-2347	24	21	diagnosis	diagnosis	NOUN
cana-2347	24	22	and	and	CCONJ
cana-2347	24	23	the	the	DET
cana-2347	24	24	advancement	advancement	NOUN
cana-2347	24	25	of	of	ADP
cana-2347	24	26	medical	medical	ADJ
cana-2347	24	27	image	image	NOUN
cana-2347	24	28	segmentation	segmentation	NOUN
cana-2347	24	29	for	for	ADP
cana-2347	24	30	disorders	disorder	NOUN
cana-2347	24	31	related	relate	VERB
cana-2347	24	32	to	to	ADP
cana-2347	24	33	the	the	DET
cana-2347	24	34	ovary	ovary	NOUN
cana-2347	24	35	.	.	PUNCT
cana-2347	25	1	the	the	DET
cana-2347	25	2	following	follow	VERB
cana-2347	25	3	paper	paper	NOUN
cana-2347	25	4	is	be	AUX
cana-2347	25	5	organized	organize	VERB
cana-2347	25	6	as	as	SCONJ
cana-2347	25	7	follows	follow	VERB
cana-2347	25	8	:	:	PUNCT
cana-2347	25	9	related	related	ADJ
cana-2347	25	10	works	work	NOUN
cana-2347	25	11	are	be	AUX
cana-2347	25	12	presented	present	VERB
cana-2347	25	13	in	in	ADP
cana-2347	25	14	section	section	PROPN
cana-2347	25	15	ii	ii	PROPN
cana-2347	25	16	,	,	PUNCT
cana-2347	25	17	the	the	DET
cana-2347	25	18	suggested	suggest	VERB
cana-2347	25	19	technique	technique	NOUN
cana-2347	25	20	is	be	AUX
cana-2347	25	21	covered	cover	VERB
cana-2347	25	22	in	in	ADP
cana-2347	25	23	section	section	NOUN
cana-2347	25	24	iii	iii	PROPN
cana-2347	25	25	,	,	PUNCT
cana-2347	25	26	the	the	DET
cana-2347	25	27	results	result	NOUN
cana-2347	25	28	and	and	CCONJ
cana-2347	25	29	discussion	discussion	NOUN
cana-2347	25	30	are	be	AUX
cana-2347	25	31	covered	cover	VERB
cana-2347	25	32	in	in	ADP
cana-2347	25	33	section	section	NOUN
cana-2347	25	34	iv	iv	NUM
cana-2347	25	35	,	,	PUNCT
cana-2347	25	36	and	and	CCONJ
cana-2347	25	37	the	the	DET
cana-2347	25	38	conclusion	conclusion	NOUN
cana-2347	25	39	is	be	AUX
cana-2347	25	40	included	include	VERB
cana-2347	25	41	in	in	ADP
cana-2347	25	42	section	section	NOUN
cana-2347	25	43	v.	v.	ADP
cana-2347	25	44	2	2	NUM
cana-2347	25	45	.	.	X
cana-2347	25	46	related	relate	VERB
cana-2347	25	47	works	work	NOUN
cana-2347	25	48	in	in	ADP
cana-2347	25	49	their	their	PRON
cana-2347	25	50	research	research	NOUN
cana-2347	25	51	,	,	PUNCT
cana-2347	25	52	haoming	haome	VERB
cana-2347	25	53	li	li	PROPN
cana-2347	25	54	et	et	PROPN
cana-2347	25	55	al	al	PROPN
cana-2347	25	56	.	.	PUNCT
cana-2347	26	1	[	[	X
cana-2347	26	2	1	1	X
cana-2347	26	3	]	]	PUNCT
cana-2347	26	4	present	present	VERB
cana-2347	26	5	an	an	DET
cana-2347	26	6	innovative	innovative	ADJ
cana-2347	26	7	technique	technique	NOUN
cana-2347	26	8	for	for	ADP
cana-2347	26	9	segmenting	segment	VERB
cana-2347	26	10	ovaries	ovary	NOUN
cana-2347	26	11	and	and	CCONJ
cana-2347	26	12	follicles	follicle	NOUN
cana-2347	26	13	in	in	ADP
cana-2347	26	14	transvaginal	transvaginal	ADJ
cana-2347	26	15	ultrasound	ultrasound	NOUN
cana-2347	26	16	(	(	PUNCT
cana-2347	26	17	tvus	tvus	NOUN
cana-2347	26	18	)	)	PUNCT
cana-2347	26	19	images	image	NOUN
cana-2347	26	20	through	through	ADP
cana-2347	26	21	a	a	DET
cana-2347	26	22	deep	deep	ADJ
cana-2347	26	23	learning	learning	NOUN
cana-2347	26	24	model	model	NOUN
cana-2347	26	25	named	name	VERB
cana-2347	26	26	cr	cr	NOUN
cana-2347	26	27	-	-	PUNCT
cana-2347	26	28	unet	unet	NOUN
cana-2347	26	29	.	.	PUNCT
cana-2347	27	1	the	the	DET
cana-2347	27	2	approach	approach	NOUN
cana-2347	27	3	enhances	enhance	VERB
cana-2347	27	4	a	a	DET
cana-2347	27	5	standard	standard	ADJ
cana-2347	27	6	u	u	NOUN
cana-2347	27	7	-	-	NOUN
cana-2347	27	8	net	net	NOUN
cana-2347	27	9	by	by	ADP
cana-2347	27	10	embedding	embed	VERB
cana-2347	27	11	a	a	DET
cana-2347	27	12	spatial	spatial	ADJ
cana-2347	27	13	recurrent	recurrent	ADJ
cana-2347	27	14	neural	neural	ADJ
cana-2347	27	15	network	network	NOUN
cana-2347	27	16	(	(	PUNCT
cana-2347	27	17	rnn	rnn	PROPN
cana-2347	27	18	)	)	PUNCT
cana-2347	27	19	to	to	PART
cana-2347	27	20	better	well	ADV
cana-2347	27	21	capture	capture	VERB
cana-2347	27	22	both	both	CCONJ
cana-2347	27	23	multi	multi	ADJ
cana-2347	27	24	-	-	ADJ
cana-2347	27	25	scale	scale	ADJ
cana-2347	27	26	details	detail	NOUN
cana-2347	27	27	and	and	CCONJ
cana-2347	27	28	extensive	extensive	ADJ
cana-2347	27	29	spatial	spatial	ADJ
cana-2347	27	30	relationships	relationship	NOUN
cana-2347	27	31	.	.	PUNCT
cana-2347	28	1	to	to	PART
cana-2347	28	2	further	far	ADV
cana-2347	28	3	optimize	optimize	VERB
cana-2347	28	4	the	the	DET
cana-2347	28	5	training	training	NOUN
cana-2347	28	6	process	process	NOUN
cana-2347	28	7	,	,	PUNCT
cana-2347	28	8	the	the	DET
cana-2347	28	9	authors	author	NOUN
cana-2347	28	10	employ	employ	VERB
cana-2347	28	11	deep	deep	ADJ
cana-2347	28	12	supervision	supervision	NOUN
cana-2347	28	13	,	,	PUNCT
cana-2347	28	14	ensuring	ensure	VERB
cana-2347	28	15	a	a	DET
cana-2347	28	16	more	more	ADV
cana-2347	28	17	efficient	efficient	ADJ
cana-2347	28	18	learning	learning	NOUN
cana-2347	28	19	phase	phase	NOUN
cana-2347	28	20	,	,	PUNCT
cana-2347	28	21	and	and	CCONJ
cana-2347	28	22	use	use	VERB
cana-2347	28	23	self	self	NOUN
cana-2347	28	24	-	-	PUNCT
cana-2347	28	25	supervision	supervision	NOUN
cana-2347	28	26	to	to	PART
cana-2347	28	27	progressively	progressively	ADV
cana-2347	28	28	improve	improve	VERB
cana-2347	28	29	the	the	DET
cana-2347	28	30	accuracy	accuracy	NOUN
cana-2347	28	31	of	of	ADP
cana-2347	28	32	the	the	DET
cana-2347	28	33	segmentation	segmentation	NOUN
cana-2347	28	34	results	result	VERB
cana-2347	28	35	.	.	PUNCT
cana-2347	29	1	the	the	DET
cana-2347	29	2	authors	author	NOUN
cana-2347	29	3	tested	test	VERB
cana-2347	29	4	their	their	PRON
cana-2347	29	5	method	method	NOUN
cana-2347	29	6	on	on	ADP
cana-2347	29	7	a	a	DET
cana-2347	29	8	dataset	dataset	NOUN
cana-2347	29	9	consisting	consist	VERB
cana-2347	29	10	of	of	ADP
cana-2347	29	11	3204	3204	NUM
cana-2347	29	12	transvaginal	transvaginal	ADJ
cana-2347	29	13	ultrasound	ultrasound	NOUN
cana-2347	29	14	(	(	PUNCT
cana-2347	29	15	tvus	tvus	NOUN
cana-2347	29	16	)	)	PUNCT
cana-2347	29	17	images	image	NOUN
cana-2347	29	18	from	from	ADP
cana-2347	29	19	219	219	NUM
cana-2347	29	20	patients	patient	NOUN
cana-2347	29	21	,	,	PUNCT
cana-2347	29	22	comparing	compare	VERB
cana-2347	29	23	its	its	PRON
cana-2347	29	24	performance	performance	NOUN
cana-2347	29	25	against	against	ADP
cana-2347	29	26	other	other	ADJ
cana-2347	29	27	leading	lead	VERB
cana-2347	29	28	techniques	technique	NOUN
cana-2347	29	29	in	in	ADP
cana-2347	29	30	tvus	tvus	PROPN
cana-2347	29	31	image	image	NOUN
cana-2347	29	32	segmentation	segmentation	NOUN
cana-2347	29	33	.	.	PUNCT
cana-2347	30	1	the	the	DET
cana-2347	30	2	findings	finding	NOUN
cana-2347	30	3	demonstrated	demonstrate	VERB
cana-2347	30	4	that	that	SCONJ
cana-2347	30	5	their	their	PRON
cana-2347	30	6	approach	approach	NOUN
cana-2347	30	7	outperformed	outperform	VERB
cana-2347	30	8	the	the	DET
cana-2347	30	9	others	other	NOUN
cana-2347	30	10	,	,	PUNCT
cana-2347	30	11	achieving	achieve	VERB
cana-2347	30	12	the	the	DET
cana-2347	30	13	highest	high	ADJ
cana-2347	30	14	segmentation	segmentation	NOUN
cana-2347	30	15	accuracy	accuracy	NOUN
cana-2347	30	16	with	with	ADP
cana-2347	30	17	dice	dice	NOUN
cana-2347	30	18	similarity	similarity	NOUN
cana-2347	30	19	coefficients	coefficient	NOUN
cana-2347	30	20	(	(	PUNCT
cana-2347	30	21	dsc	dsc	NOUN
cana-2347	30	22	)	)	PUNCT
cana-2347	30	23	of	of	ADP
cana-2347	30	24	0.912	0.912	NUM
cana-2347	30	25	for	for	ADP
cana-2347	30	26	the	the	DET
cana-2347	30	27	ovary	ovary	NOUN
cana-2347	30	28	and	and	CCONJ
cana-2347	30	29	0.858	0.858	NUM
cana-2347	30	30	for	for	ADP
cana-2347	30	31	the	the	DET
cana-2347	30	32	follicles	follicle	NOUN
cana-2347	30	33	.	.	PUNCT
cana-2347	31	1	additionally	additionally	ADV
cana-2347	31	2	,	,	PUNCT
cana-2347	31	3	the	the	DET
cana-2347	31	4	paper	paper	NOUN
cana-2347	31	5	includes	include	VERB
cana-2347	31	6	qualitative	qualitative	ADJ
cana-2347	31	7	visual	visual	ADJ
cana-2347	31	8	comparisons	comparison	NOUN
cana-2347	31	9	in	in	ADP
cana-2347	31	10	figure	figure	NOUN
cana-2347	31	11	1	1	NUM
cana-2347	31	12	,	,	PUNCT
cana-2347	31	13	showcasing	showcase	VERB
cana-2347	31	14	the	the	DET
cana-2347	31	15	segmentation	segmentation	NOUN
cana-2347	31	16	results	result	NOUN
cana-2347	31	17	of	of	ADP
cana-2347	31	18	their	their	PRON
cana-2347	31	19	method	method	NOUN
cana-2347	31	20	alongside	alongside	ADP
cana-2347	31	21	those	those	PRON
cana-2347	31	22	of	of	ADP
cana-2347	31	23	other	other	ADJ
cana-2347	31	24	advanced	advanced	ADJ
cana-2347	31	25	techniques	technique	NOUN
cana-2347	31	26	.	.	PUNCT
cana-2347	32	1	the	the	DET
cana-2347	32	2	cr	cr	PROPN
cana-2347	32	3	-	-	PUNCT
cana-2347	32	4	unet	unet	NOUN
cana-2347	32	5	method	method	NOUN
cana-2347	32	6	introduced	introduce	VERB
cana-2347	32	7	shows	show	VERB
cana-2347	32	8	significant	significant	ADJ
cana-2347	32	9	potential	potential	NOUN
cana-2347	32	10	for	for	ADP
cana-2347	32	11	accurately	accurately	ADV
cana-2347	32	12	segmenting	segment	VERB
cana-2347	32	13	ovaries	ovary	NOUN
cana-2347	32	14	and	and	CCONJ
cana-2347	32	15	follicles	follicle	NOUN
cana-2347	32	16	in	in	ADP
cana-2347	32	17	tvus	tvus	NOUN
cana-2347	32	18	images	image	NOUN
cana-2347	32	19	,	,	PUNCT
cana-2347	32	20	surpassing	surpass	VERB
cana-2347	32	21	the	the	DET
cana-2347	32	22	performance	performance	NOUN
cana-2347	32	23	of	of	ADP
cana-2347	32	24	other	other	ADJ
cana-2347	32	25	cutting	cutting	NOUN
cana-2347	32	26	-	-	PUNCT
cana-2347	32	27	edge	edge	NOUN
cana-2347	32	28	techniques	technique	NOUN
cana-2347	32	29	.	.	PUNCT
cana-2347	33	1	despite	despite	SCONJ
cana-2347	33	2	these	these	DET
cana-2347	33	3	promising	promising	ADJ
cana-2347	33	4	results	result	NOUN
cana-2347	33	5	,	,	PUNCT
cana-2347	33	6	additional	additional	ADJ
cana-2347	33	7	studies	study	NOUN
cana-2347	33	8	are	be	AUX
cana-2347	33	9	necessary	necessary	ADJ
cana-2347	33	10	to	to	PART
cana-2347	33	11	assess	assess	VERB
cana-2347	33	12	the	the	DET
cana-2347	33	13	method	method	NOUN
cana-2347	33	14	’s	’s	PART
cana-2347	33	15	effectiveness	effectiveness	NOUN
cana-2347	33	16	on	on	ADP
cana-2347	33	17	larger	large	ADJ
cana-2347	33	18	and	and	CCONJ
cana-2347	33	19	more	more	ADV
cana-2347	33	20	varied	varied	ADJ
cana-2347	33	21	datasets	dataset	NOUN
cana-2347	33	22	and	and	CCONJ
cana-2347	33	23	to	to	PART
cana-2347	33	24	examine	examine	VERB
cana-2347	33	25	its	its	PRON
cana-2347	33	26	computational	computational	ADJ
cana-2347	33	27	efficiency	efficiency	NOUN
cana-2347	33	28	for	for	ADP
cana-2347	33	29	potential	potential	ADJ
cana-2347	33	30	real	real	ADJ
cana-2347	33	31	-	-	PUNCT
cana-2347	33	32	time	time	NOUN
cana-2347	33	33	application	application	NOUN
cana-2347	33	34	.	.	PUNCT
cana-2347	34	1	figure	figure	NOUN
cana-2347	34	2	1	1	NUM
cana-2347	34	3	:	:	PUNCT
cana-2347	34	4	learning	learn	VERB
cana-2347	34	5	curve	curve	NOUN
cana-2347	34	6	of	of	ADP
cana-2347	34	7	cr	cr	NOUN
cana-2347	34	8	-	-	PUNCT
cana-2347	34	9	unet	unet	NOUN
cana-2347	34	10	method	method	NOUN
cana-2347	34	11	to	to	PART
cana-2347	34	12	prove	prove	VERB
cana-2347	34	13	the	the	DET
cana-2347	34	14	model	model	NOUN
cana-2347	34	15	’s	’s	PART
cana-2347	34	16	resilience	resilience	NOUN
cana-2347	34	17	and	and	CCONJ
cana-2347	34	18	generalizability	generalizability	NOUN
cana-2347	34	19	,	,	PUNCT
cana-2347	34	20	more	more	ADJ
cana-2347	34	21	testing	testing	NOUN
cana-2347	34	22	on	on	ADP
cana-2347	34	23	bigger	big	ADJ
cana-2347	34	24	,	,	PUNCT
cana-2347	34	25	more	more	ADV
cana-2347	34	26	varied	varied	ADJ
cana-2347	34	27	datasets	dataset	NOUN
cana-2347	34	28	as	as	ADV
cana-2347	34	29	well	well	ADV
cana-2347	34	30	as	as	ADP
cana-2347	34	31	in	in	ADP
cana-2347	34	32	actual	actual	ADJ
cana-2347	34	33	clinical	clinical	ADJ
cana-2347	34	34	settings	setting	NOUN
cana-2347	34	35	is	be	AUX
cana-2347	34	36	needed	need	VERB
cana-2347	34	37	.	.	PUNCT
cana-2347	35	1	communications	communication	NOUN
cana-2347	35	2	on	on	ADP
cana-2347	35	3	applied	apply	VERB
cana-2347	35	4	nonlinear	nonlinear	ADJ
cana-2347	35	5	analysis	analysis	NOUN
cana-2347	35	6	issn	issn	NOUN
cana-2347	35	7	:	:	PUNCT
cana-2347	35	8	1074	1074	NUM
cana-2347	35	9	-	-	PUNCT
cana-2347	35	10	133x	133x	NUM
cana-2347	35	11	vol	vol	NOUN
cana-2347	35	12	32	32	NUM
cana-2347	35	13	no	no	NOUN
cana-2347	35	14	.	.	PUNCT
cana-2347	36	1	1s	1s	NUM
cana-2347	36	2	(	(	PUNCT
cana-2347	36	3	2025	2025	NUM
cana-2347	36	4	)	)	PUNCT
cana-2347	36	5	613	613	NUM
cana-2347	36	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	36	7	the	the	DET
cana-2347	36	8	creation	creation	NOUN
cana-2347	36	9	of	of	ADP
cana-2347	36	10	a	a	DET
cana-2347	36	11	deep	deep	ADJ
cana-2347	36	12	learning	learning	NOUN
cana-2347	36	13	model	model	NOUN
cana-2347	36	14	for	for	ADP
cana-2347	36	15	the	the	DET
cana-2347	36	16	identification	identification	NOUN
cana-2347	36	17	of	of	ADP
cana-2347	36	18	ovarian	ovarian	ADJ
cana-2347	36	19	cysts	cyst	NOUN
cana-2347	36	20	in	in	ADP
cana-2347	36	21	ultrasound	ultrasound	ADJ
cana-2347	36	22	images	image	NOUN
cana-2347	36	23	is	be	AUX
cana-2347	36	24	covered	cover	VERB
cana-2347	36	25	by	by	ADP
cana-2347	36	26	srivastava	srivastava	PROPN
cana-2347	36	27	,	,	PUNCT
cana-2347	36	28	sakshi	sakshi	PROPN
cana-2347	36	29	,	,	PUNCT
cana-2347	36	30	et	et	PROPN
cana-2347	36	31	al	al	PROPN
cana-2347	36	32	.	.	PUNCT
cana-2347	37	1	[	[	X
cana-2347	37	2	2	2	NUM
cana-2347	37	3	]	]	PUNCT
cana-2347	37	4	.	.	PUNCT
cana-2347	38	1	to	to	PART
cana-2347	38	2	improve	improve	VERB
cana-2347	38	3	the	the	DET
cana-2347	38	4	accuracy	accuracy	NOUN
cana-2347	38	5	of	of	ADP
cana-2347	38	6	the	the	DET
cana-2347	38	7	standard	standard	NOUN
cana-2347	38	8	vgg-16	vgg-16	NOUN
cana-2347	38	9	model	model	NOUN
cana-2347	38	10	in	in	ADP
cana-2347	38	11	identifying	identify	VERB
cana-2347	38	12	ovarian	ovarian	ADJ
cana-2347	38	13	cysts	cyst	NOUN
cana-2347	38	14	,	,	PUNCT
cana-2347	38	15	it	it	PRON
cana-2347	38	16	was	be	AUX
cana-2347	38	17	refined	refine	VERB
cana-2347	38	18	using	use	VERB
cana-2347	38	19	a	a	DET
cana-2347	38	20	dataset	dataset	NOUN
cana-2347	38	21	of	of	ADP
cana-2347	38	22	ultrasound	ultrasound	ADJ
cana-2347	38	23	images	image	NOUN
cana-2347	38	24	of	of	ADP
cana-2347	38	25	ovaries	ovary	NOUN
cana-2347	38	26	.	.	PUNCT
cana-2347	39	1	the	the	DET
cana-2347	39	2	accuracy	accuracy	NOUN
cana-2347	39	3	of	of	ADP
cana-2347	39	4	the	the	DET
cana-2347	39	5	suggested	suggest	VERB
cana-2347	39	6	model	model	NOUN
cana-2347	39	7	was	be	AUX
cana-2347	39	8	92.11	92.11	NUM
cana-2347	39	9	%	%	NOUN
cana-2347	39	10	.	.	PUNCT
cana-2347	40	1	this	this	DET
cana-2347	40	2	work	work	NOUN
cana-2347	40	3	has	have	AUX
cana-2347	40	4	indicated	indicate	VERB
cana-2347	40	5	a	a	DET
cana-2347	40	6	research	research	NOUN
cana-2347	40	7	gap	gap	NOUN
cana-2347	40	8	:	:	PUNCT
cana-2347	40	9	in	in	ADP
cana-2347	40	10	order	order	NOUN
cana-2347	40	11	to	to	PART
cana-2347	40	12	avoid	avoid	VERB
cana-2347	40	13	potential	potential	ADJ
cana-2347	40	14	problems	problem	NOUN
cana-2347	40	15	,	,	PUNCT
cana-2347	40	16	ovarian	ovarian	ADJ
cana-2347	40	17	cysts	cyst	NOUN
cana-2347	40	18	must	must	AUX
cana-2347	40	19	be	be	AUX
cana-2347	40	20	accurately	accurately	ADV
cana-2347	40	21	and	and	CCONJ
cana-2347	40	22	promptly	promptly	ADV
cana-2347	40	23	detected	detect	VERB
cana-2347	40	24	.	.	PUNCT
cana-2347	41	1	in	in	ADP
cana-2347	41	2	a	a	DET
cana-2347	41	3	study	study	NOUN
cana-2347	41	4	,	,	PUNCT
cana-2347	41	5	akazawa	akazawa	PROPN
cana-2347	41	6	et	et	PROPN
cana-2347	41	7	al	al	PROPN
cana-2347	41	8	.	.	PUNCT
cana-2347	42	1	[	[	X
cana-2347	42	2	3	3	X
cana-2347	42	3	]	]	PUNCT
cana-2347	42	4	used	use	VERB
cana-2347	42	5	artificial	artificial	ADJ
cana-2347	42	6	intelligence	intelligence	NOUN
cana-2347	42	7	(	(	PUNCT
cana-2347	42	8	ai	ai	NOUN
cana-2347	42	9	)	)	PUNCT
cana-2347	42	10	for	for	ADP
cana-2347	42	11	predicting	predict	VERB
cana-2347	42	12	the	the	DET
cana-2347	42	13	clinical	clinical	ADJ
cana-2347	42	14	diagnosis	diagnosis	NOUN
cana-2347	42	15	of	of	ADP
cana-2347	42	16	ovarian	ovarian	ADJ
cana-2347	42	17	cancers	cancer	NOUN
cana-2347	42	18	.	.	PUNCT
cana-2347	43	1	to	to	PART
cana-2347	43	2	produce	produce	VERB
cana-2347	43	3	diagnostic	diagnostic	ADJ
cana-2347	43	4	results	result	NOUN
cana-2347	43	5	based	base	VERB
cana-2347	43	6	on	on	ADP
cana-2347	43	7	16	16	NUM
cana-2347	43	8	features	feature	NOUN
cana-2347	43	9	,	,	PUNCT
cana-2347	43	10	the	the	DET
cana-2347	43	11	study	study	NOUN
cana-2347	43	12	used	use	VERB
cana-2347	43	13	five	five	NUM
cana-2347	43	14	machine	machine	NOUN
cana-2347	43	15	learning	learn	VERB
cana-2347	43	16	classifiers	classifier	NOUN
cana-2347	43	17	:	:	PUNCT
cana-2347	43	18	logistic	logistic	ADJ
cana-2347	43	19	regression	regression	NOUN
cana-2347	43	20	,	,	PUNCT
cana-2347	43	21	naive	naive	ADJ
cana-2347	43	22	bayes	bayes	NOUN
cana-2347	43	23	,	,	PUNCT
cana-2347	43	24	random	random	ADJ
cana-2347	43	25	forest	forest	NOUN
cana-2347	43	26	,	,	PUNCT
cana-2347	43	27	support	support	NOUN
cana-2347	43	28	vector	vector	NOUN
cana-2347	43	29	machine	machine	NOUN
cana-2347	43	30	,	,	PUNCT
cana-2347	43	31	and	and	CCONJ
cana-2347	43	32	xgboost	xgboost	X
cana-2347	43	33	.	.	PUNCT
cana-2347	44	1	the	the	DET
cana-2347	44	2	study	study	NOUN
cana-2347	44	3	also	also	ADV
cana-2347	44	4	emphasizes	emphasize	VERB
cana-2347	44	5	the	the	DET
cana-2347	44	6	shortcomings	shortcoming	NOUN
cana-2347	44	7	of	of	ADP
cana-2347	44	8	ai	ai	PROPN
cana-2347	44	9	predictions	prediction	NOUN
cana-2347	44	10	,	,	PUNCT
cana-2347	44	11	such	such	ADJ
cana-2347	44	12	as	as	ADP
cana-2347	44	13	the	the	DET
cana-2347	44	14	absence	absence	NOUN
cana-2347	44	15	of	of	ADP
cana-2347	44	16	accountability	accountability	NOUN
cana-2347	44	17	,	,	PUNCT
cana-2347	44	18	and	and	CCONJ
cana-2347	44	19	underlines	underline	VERB
cana-2347	44	20	how	how	SCONJ
cana-2347	44	21	important	important	ADJ
cana-2347	44	22	it	it	PRON
cana-2347	44	23	is	be	AUX
cana-2347	44	24	for	for	SCONJ
cana-2347	44	25	medical	medical	ADJ
cana-2347	44	26	experts	expert	NOUN
cana-2347	44	27	to	to	PART
cana-2347	44	28	understand	understand	VERB
cana-2347	44	29	results	result	NOUN
cana-2347	44	30	in	in	ADP
cana-2347	44	31	order	order	NOUN
cana-2347	44	32	to	to	PART
cana-2347	44	33	make	make	VERB
cana-2347	44	34	decisions	decision	NOUN
cana-2347	44	35	.	.	PUNCT
cana-2347	45	1	the	the	DET
cana-2347	45	2	study	study	NOUN
cana-2347	45	3	emphasizes	emphasize	VERB
cana-2347	45	4	that	that	SCONJ
cana-2347	45	5	the	the	DET
cana-2347	45	6	limited	limited	ADJ
cana-2347	45	7	dataset	dataset	NOUN
cana-2347	45	8	of	of	ADP
cana-2347	45	9	202	202	NUM
cana-2347	45	10	cases	case	NOUN
cana-2347	45	11	may	may	AUX
cana-2347	45	12	restrict	restrict	VERB
cana-2347	45	13	the	the	DET
cana-2347	45	14	generalizability	generalizability	NOUN
cana-2347	45	15	of	of	ADP
cana-2347	45	16	the	the	DET
cana-2347	45	17	findings	finding	NOUN
cana-2347	45	18	,	,	PUNCT
cana-2347	45	19	despite	despite	SCONJ
cana-2347	45	20	the	the	DET
cana-2347	45	21	fact	fact	NOUN
cana-2347	45	22	that	that	SCONJ
cana-2347	45	23	it	it	PRON
cana-2347	45	24	provides	provide	VERB
cana-2347	45	25	insightful	insightful	ADJ
cana-2347	45	26	information	information	NOUN
cana-2347	45	27	for	for	ADP
cana-2347	45	28	the	the	DET
cana-2347	45	29	early	early	ADJ
cana-2347	45	30	detection	detection	NOUN
cana-2347	45	31	and	and	CCONJ
cana-2347	45	32	treatment	treatment	NOUN
cana-2347	45	33	of	of	ADP
cana-2347	45	34	ovarian	ovarian	ADJ
cana-2347	45	35	cancer	cancer	NOUN
cana-2347	45	36	.	.	PUNCT
cana-2347	46	1	figure	figure	NOUN
cana-2347	46	2	2	2	NUM
cana-2347	46	3	:	:	PUNCT
cana-2347	46	4	patient	patient	ADJ
cana-2347	46	5	and	and	CCONJ
cana-2347	46	6	tumour	tumour	ADJ
cana-2347	46	7	characteristics	characteristic	NOUN
cana-2347	46	8	figure	figure	NOUN
cana-2347	46	9	3	3	NUM
cana-2347	46	10	:	:	PUNCT
cana-2347	46	11	classifier	classifier	NOUN
cana-2347	46	12	accuracy	accuracy	NOUN
cana-2347	46	13	figure	figure	NOUN
cana-2347	46	14	4	4	NUM
cana-2347	46	15	:	:	PUNCT
cana-2347	46	16	random	random	ADJ
cana-2347	46	17	forest	forest	NOUN
cana-2347	46	18	correlation	correlation	NOUN
cana-2347	46	19	coefficient	coefficient	NOUN
cana-2347	46	20	figure	figure	NOUN
cana-2347	46	21	5	5	NUM
cana-2347	46	22	:	:	PUNCT
cana-2347	46	23	random	random	ADJ
cana-2347	46	24	forest	forest	NOUN
cana-2347	46	25	regression	regression	NOUN
cana-2347	46	26	coefficient	coefficient	NOUN
cana-2347	46	27	suha	suha	PROPN
cana-2347	46	28	et.al	et.al	PROPN
cana-2347	47	1	[	[	X
cana-2347	47	2	4	4	NUM
cana-2347	47	3	]	]	PUNCT
cana-2347	47	4	presents	present	VERB
cana-2347	47	5	a	a	DET
cana-2347	47	6	novel	novel	ADJ
cana-2347	47	7	approach	approach	NOUN
cana-2347	47	8	for	for	ADP
cana-2347	47	9	pcos	pcos	PROPN
cana-2347	47	10	detection	detection	NOUN
cana-2347	47	11	,	,	PUNCT
cana-2347	47	12	employing	employ	VERB
cana-2347	47	13	transfer	transfer	NOUN
cana-2347	47	14	learning	learning	NOUN
cana-2347	47	15	in	in	ADP
cana-2347	47	16	a	a	DET
cana-2347	47	17	cnn	cnn	NOUN
cana-2347	47	18	for	for	ADP
cana-2347	47	19	feature	feature	NOUN
cana-2347	47	20	extraction	extraction	NOUN
cana-2347	47	21	and	and	CCONJ
cana-2347	47	22	a	a	DET
cana-2347	47	23	stacking	stacking	NOUN
cana-2347	47	24	ensemble	ensemble	ADJ
cana-2347	47	25	for	for	ADP
cana-2347	47	26	image	image	NOUN
cana-2347	47	27	classification	classification	NOUN
cana-2347	47	28	.	.	PUNCT
cana-2347	48	1	while	while	SCONJ
cana-2347	48	2	not	not	PART
cana-2347	48	3	explicitly	explicitly	ADV
cana-2347	48	4	mentioned	mention	VERB
cana-2347	48	5	,	,	PUNCT
cana-2347	48	6	the	the	DET
cana-2347	48	7	paper	paper	NOUN
cana-2347	48	8	addresses	address	NOUN
cana-2347	48	9	research	research	NOUN
cana-2347	48	10	gaps	gap	NOUN
cana-2347	48	11	in	in	ADP
cana-2347	48	12	existing	exist	VERB
cana-2347	48	13	pcos	pcos	PROPN
cana-2347	48	14	detection	detection	NOUN
cana-2347	48	15	methods	method	NOUN
cana-2347	48	16	,	,	PUNCT
cana-2347	48	17	which	which	PRON
cana-2347	48	18	are	be	AUX
cana-2347	48	19	often	often	ADV
cana-2347	48	20	error	error	NOUN
cana-2347	48	21	-	-	PUNCT
cana-2347	48	22	prone	prone	ADJ
cana-2347	48	23	and	and	CCONJ
cana-2347	48	24	time	time	NOUN
cana-2347	48	25	-	-	PUNCT
cana-2347	48	26	consuming	consume	VERB
cana-2347	48	27	.	.	PUNCT
cana-2347	49	1	however	however	ADV
cana-2347	49	2	,	,	PUNCT
cana-2347	49	3	there	there	PRON
cana-2347	49	4	is	be	VERB
cana-2347	49	5	a	a	DET
cana-2347	49	6	need	need	NOUN
cana-2347	49	7	for	for	ADP
cana-2347	49	8	further	further	ADJ
cana-2347	49	9	research	research	NOUN
cana-2347	49	10	into	into	ADP
cana-2347	49	11	the	the	DET
cana-2347	49	12	model	model	NOUN
cana-2347	49	13	's	's	PART
cana-2347	49	14	interpretability	interpretability	NOUN
cana-2347	49	15	,	,	PUNCT
cana-2347	49	16	ensuring	ensure	VERB
cana-2347	49	17	its	its	PRON
cana-2347	49	18	clinical	clinical	ADJ
cana-2347	49	19	relevance	relevance	NOUN
cana-2347	49	20	.	.	PUNCT
cana-2347	50	1	additionally	additionally	ADV
cana-2347	50	2	,	,	PUNCT
cana-2347	50	3	the	the	DET
cana-2347	50	4	paper	paper	NOUN
cana-2347	50	5	does	do	AUX
cana-2347	50	6	not	not	PART
cana-2347	50	7	discuss	discuss	VERB
cana-2347	50	8	challenges	challenge	NOUN
cana-2347	50	9	related	relate	VERB
cana-2347	50	10	to	to	ADP
cana-2347	50	11	data	datum	NOUN
cana-2347	50	12	privacy	privacy	NOUN
cana-2347	50	13	or	or	CCONJ
cana-2347	50	14	the	the	DET
cana-2347	50	15	model	model	NOUN
cana-2347	50	16	's	's	PART
cana-2347	50	17	generalizability	generalizability	NOUN
cana-2347	50	18	across	across	ADP
cana-2347	50	19	diverse	diverse	ADJ
cana-2347	50	20	patient	patient	ADJ
cana-2347	50	21	populations	population	NOUN
cana-2347	50	22	.	.	PUNCT
cana-2347	51	1	in	in	ADP
cana-2347	51	2	order	order	NOUN
cana-2347	51	3	to	to	PART
cana-2347	51	4	guarantee	guarantee	VERB
cana-2347	51	5	the	the	DET
cana-2347	51	6	communications	communication	NOUN
cana-2347	51	7	on	on	ADP
cana-2347	51	8	applied	apply	VERB
cana-2347	51	9	nonlinear	nonlinear	ADJ
cana-2347	51	10	analysis	analysis	NOUN
cana-2347	51	11	issn	issn	NOUN
cana-2347	51	12	:	:	PUNCT
cana-2347	51	13	1074	1074	NUM
cana-2347	51	14	-	-	PUNCT
cana-2347	51	15	133x	133x	NUM
cana-2347	51	16	vol	vol	NOUN
cana-2347	51	17	32	32	NUM
cana-2347	51	18	no	no	NOUN
cana-2347	51	19	.	.	PUNCT
cana-2347	52	1	1s	1s	NUM
cana-2347	52	2	(	(	PUNCT
cana-2347	52	3	2025	2025	NUM
cana-2347	52	4	)	)	PUNCT
cana-2347	52	5	614	614	NUM
cana-2347	53	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	53	2	ethical	ethical	ADJ
cana-2347	53	3	and	and	CCONJ
cana-2347	53	4	efficient	efficient	ADJ
cana-2347	53	5	use	use	NOUN
cana-2347	53	6	of	of	ADP
cana-2347	53	7	this	this	DET
cana-2347	53	8	method	method	NOUN
cana-2347	53	9	in	in	ADP
cana-2347	53	10	healthcare	healthcare	PROPN
cana-2347	53	11	,	,	PUNCT
cana-2347	53	12	future	future	ADJ
cana-2347	53	13	studies	study	NOUN
cana-2347	53	14	should	should	AUX
cana-2347	53	15	concentrate	concentrate	VERB
cana-2347	53	16	on	on	ADP
cana-2347	53	17	filling	fill	VERB
cana-2347	53	18	in	in	ADP
cana-2347	53	19	these	these	DET
cana-2347	53	20	gaps	gap	NOUN
cana-2347	53	21	.	.	PUNCT
cana-2347	54	1	figure	figure	VERB
cana-2347	54	2	6	6	NUM
cana-2347	54	3	:	:	PUNCT
cana-2347	54	4	model	model	NOUN
cana-2347	54	5	performance	performance	NOUN
cana-2347	54	6	metrics	metric	NOUN
cana-2347	54	7	(	(	PUNCT
cana-2347	54	8	accuracy	accuracy	NOUN
cana-2347	54	9	)	)	PUNCT
cana-2347	54	10	and	and	CCONJ
cana-2347	54	11	execution	execution	NOUN
cana-2347	54	12	time	time	NOUN
cana-2347	54	13	for	for	ADP
cana-2347	54	14	various	various	ADJ
cana-2347	54	15	machine	machine	NOUN
cana-2347	54	16	learning	learning	NOUN
cana-2347	54	17	models	model	NOUN
cana-2347	54	18	this	this	PRON
cana-2347	54	19	is	be	AUX
cana-2347	54	20	a	a	DET
cana-2347	54	21	major	major	ADJ
cana-2347	54	22	breakthrough	breakthrough	NOUN
cana-2347	54	23	in	in	ADP
cana-2347	54	24	the	the	DET
cana-2347	54	25	field	field	NOUN
cana-2347	54	26	of	of	ADP
cana-2347	54	27	medical	medical	ADJ
cana-2347	54	28	image	image	NOUN
cana-2347	54	29	analysis	analysis	NOUN
cana-2347	54	30	and	and	CCONJ
cana-2347	54	31	the	the	DET
cana-2347	54	32	classification	classification	NOUN
cana-2347	54	33	of	of	ADP
cana-2347	54	34	ovarian	ovarian	ADJ
cana-2347	54	35	cysts	cyst	NOUN
cana-2347	54	36	in	in	ADP
cana-2347	54	37	ultrasound	ultrasound	NOUN
cana-2347	54	38	images	image	NOUN
cana-2347	54	39	.	.	PUNCT
cana-2347	55	1	in	in	ADP
cana-2347	55	2	earlier	early	ADJ
cana-2347	55	3	studies	study	NOUN
cana-2347	55	4	,	,	PUNCT
cana-2347	55	5	the	the	DET
cana-2347	55	6	use	use	NOUN
cana-2347	55	7	of	of	ADP
cana-2347	55	8	deep	deep	ADJ
cana-2347	55	9	learning	learning	NOUN
cana-2347	55	10	methods	method	NOUN
cana-2347	55	11	,	,	PUNCT
cana-2347	55	12	like	like	ADP
cana-2347	55	13	convolutional	convolutional	ADJ
cana-2347	55	14	neural	neural	ADJ
cana-2347	55	15	networks	network	NOUN
cana-2347	55	16	(	(	PUNCT
cana-2347	55	17	cnns	cnns	PROPN
cana-2347	55	18	)	)	PUNCT
cana-2347	55	19	,	,	PUNCT
cana-2347	55	20	to	to	PART
cana-2347	55	21	automate	automate	VERB
cana-2347	55	22	the	the	DET
cana-2347	55	23	diagnosis	diagnosis	NOUN
cana-2347	55	24	of	of	ADP
cana-2347	55	25	ovarian	ovarian	ADJ
cana-2347	55	26	cysts	cyst	NOUN
cana-2347	55	27	was	be	AUX
cana-2347	55	28	investigated	investigate	VERB
cana-2347	55	29	with	with	ADP
cana-2347	55	30	the	the	DET
cana-2347	55	31	goal	goal	NOUN
cana-2347	55	32	of	of	ADP
cana-2347	55	33	improving	improve	VERB
cana-2347	55	34	diagnostic	diagnostic	ADJ
cana-2347	55	35	precision	precision	NOUN
cana-2347	55	36	and	and	CCONJ
cana-2347	55	37	reducing	reduce	VERB
cana-2347	55	38	the	the	DET
cana-2347	55	39	amount	amount	NOUN
cana-2347	55	40	of	of	ADP
cana-2347	55	41	labour	labour	NOUN
cana-2347	55	42	for	for	ADP
cana-2347	55	43	clinicians	clinician	NOUN
cana-2347	55	44	.	.	PUNCT
cana-2347	56	1	a	a	DET
cana-2347	56	2	notable	notable	ADJ
cana-2347	56	3	contribution	contribution	NOUN
cana-2347	56	4	of	of	ADP
cana-2347	56	5	the	the	DET
cana-2347	56	6	paper	paper	NOUN
cana-2347	56	7	is	be	AUX
cana-2347	56	8	its	its	PRON
cana-2347	56	9	use	use	NOUN
cana-2347	56	10	of	of	ADP
cana-2347	56	11	a	a	DET
cana-2347	56	12	larger	large	ADJ
cana-2347	56	13	and	and	CCONJ
cana-2347	56	14	more	more	ADV
cana-2347	56	15	diverse	diverse	ADJ
cana-2347	56	16	dataset	dataset	NOUN
cana-2347	56	17	,	,	PUNCT
cana-2347	56	18	in	in	ADP
cana-2347	56	19	collaboration	collaboration	NOUN
cana-2347	56	20	with	with	ADP
cana-2347	56	21	medical	medical	ADJ
cana-2347	56	22	institutions	institution	NOUN
cana-2347	56	23	,	,	PUNCT
cana-2347	56	24	which	which	PRON
cana-2347	56	25	contributes	contribute	VERB
cana-2347	56	26	to	to	ADP
cana-2347	56	27	its	its	PRON
cana-2347	56	28	impressive	impressive	ADJ
cana-2347	56	29	accuracy	accuracy	NOUN
cana-2347	56	30	nevertheless	nevertheless	ADV
cana-2347	56	31	,	,	PUNCT
cana-2347	56	32	a	a	DET
cana-2347	56	33	research	research	NOUN
cana-2347	56	34	gap	gap	NOUN
cana-2347	56	35	persists	persist	VERB
cana-2347	56	36	,	,	PUNCT
cana-2347	56	37	as	as	SCONJ
cana-2347	56	38	further	further	ADJ
cana-2347	56	39	exploration	exploration	NOUN
cana-2347	56	40	into	into	ADP
cana-2347	56	41	the	the	DET
cana-2347	56	42	model	model	NOUN
cana-2347	56	43	's	's	PART
cana-2347	56	44	robustness	robustness	NOUN
cana-2347	56	45	in	in	ADP
cana-2347	56	46	various	various	ADJ
cana-2347	56	47	clinical	clinical	ADJ
cana-2347	56	48	scenarios	scenario	NOUN
cana-2347	56	49	,	,	PUNCT
cana-2347	56	50	patient	patient	ADJ
cana-2347	56	51	demographics	demographic	NOUN
cana-2347	56	52	,	,	PUNCT
cana-2347	56	53	and	and	CCONJ
cana-2347	56	54	imaging	imaging	NOUN
cana-2347	56	55	modalities	modality	NOUN
cana-2347	56	56	is	be	AUX
cana-2347	56	57	warranted	warrant	VERB
cana-2347	56	58	.	.	PUNCT
cana-2347	57	1	additionally	additionally	ADV
cana-2347	57	2	,	,	PUNCT
cana-2347	57	3	expanding	expand	VERB
cana-2347	57	4	the	the	DET
cana-2347	57	5	dataset	dataset	NOUN
cana-2347	57	6	size	size	NOUN
cana-2347	57	7	and	and	CCONJ
cana-2347	57	8	diversity	diversity	NOUN
cana-2347	57	9	remains	remain	VERB
cana-2347	57	10	essential	essential	ADJ
cana-2347	57	11	to	to	PART
cana-2347	57	12	bolster	bolster	VERB
cana-2347	57	13	the	the	DET
cana-2347	57	14	model	model	NOUN
cana-2347	57	15	's	's	PART
cana-2347	57	16	real	real	ADJ
cana-2347	57	17	-	-	PUNCT
cana-2347	57	18	world	world	NOUN
cana-2347	57	19	applicability	applicability	NOUN
cana-2347	57	20	and	and	CCONJ
cana-2347	57	21	reliability	reliability	NOUN
cana-2347	57	22	,	,	PUNCT
cana-2347	57	23	further	far	ADV
cana-2347	57	24	bridging	bridge	VERB
cana-2347	57	25	the	the	DET
cana-2347	57	26	gap	gap	NOUN
cana-2347	57	27	between	between	ADP
cana-2347	57	28	algorithmic	algorithmic	ADJ
cana-2347	57	29	advancements	advancement	NOUN
cana-2347	57	30	and	and	CCONJ
cana-2347	57	31	clinical	clinical	ADJ
cana-2347	57	32	practice	practice	NOUN
cana-2347	57	33	in	in	ADP
cana-2347	57	34	ovarian	ovarian	ADJ
cana-2347	57	35	cyst	cyst	NOUN
cana-2347	57	36	detection	detection	NOUN
cana-2347	57	37	.	.	PUNCT
cana-2347	58	1	in	in	ADP
cana-2347	58	2	another	another	DET
cana-2347	58	3	paper	paper	NOUN
cana-2347	58	4	martínez	martínez	NOUN
cana-2347	58	5	-	-	PUNCT
cana-2347	58	6	más	más	PROPN
cana-2347	58	7	et.al	et.al	PROPN
cana-2347	58	8	[	[	X
cana-2347	58	9	6	6	NUM
cana-2347	58	10	]	]	PUNCT
cana-2347	58	11	evaluates	evaluate	VERB
cana-2347	58	12	the	the	DET
cana-2347	58	13	effectiveness	effectiveness	NOUN
cana-2347	58	14	of	of	ADP
cana-2347	58	15	machine	machine	NOUN
cana-2347	58	16	learning	learn	VERB
cana-2347	58	17	algorithms	algorithm	NOUN
cana-2347	58	18	for	for	ADP
cana-2347	58	19	classifying	classify	VERB
cana-2347	58	20	ovarian	ovarian	ADJ
cana-2347	58	21	tumours	tumour	NOUN
cana-2347	58	22	based	base	VERB
cana-2347	58	23	on	on	ADP
cana-2347	58	24	ultrasound	ultrasound	NOUN
cana-2347	58	25	images	image	NOUN
cana-2347	58	26	.	.	PUNCT
cana-2347	59	1	the	the	DET
cana-2347	59	2	researchers	researcher	NOUN
cana-2347	59	3	found	find	VERB
cana-2347	59	4	that	that	SCONJ
cana-2347	59	5	using	use	VERB
cana-2347	59	6	fourier	fourier	NOUN
cana-2347	59	7	transform	transform	NOUN
cana-2347	59	8	features	feature	NOUN
cana-2347	59	9	in	in	ADP
cana-2347	59	10	machine	machine	NOUN
cana-2347	59	11	learning	learn	VERB
cana-2347	59	12	algorithms	algorithm	NOUN
cana-2347	59	13	resulted	result	VERB
cana-2347	59	14	in	in	ADP
cana-2347	59	15	high	high	ADJ
cana-2347	59	16	accuracy	accuracy	NOUN
cana-2347	59	17	rates	rate	NOUN
cana-2347	59	18	for	for	ADP
cana-2347	59	19	identifying	identify	VERB
cana-2347	59	20	ovarian	ovarian	ADJ
cana-2347	59	21	tumours	tumour	NOUN
cana-2347	59	22	.	.	PUNCT
cana-2347	60	1	the	the	DET
cana-2347	60	2	study	study	NOUN
cana-2347	60	3	did	do	AUX
cana-2347	60	4	,	,	PUNCT
cana-2347	60	5	however	however	ADV
cana-2347	60	6	,	,	PUNCT
cana-2347	60	7	have	have	VERB
cana-2347	60	8	certain	certain	ADJ
cana-2347	60	9	drawbacks	drawback	NOUN
cana-2347	60	10	,	,	PUNCT
cana-2347	60	11	such	such	ADJ
cana-2347	60	12	as	as	ADP
cana-2347	60	13	a	a	DET
cana-2347	60	14	limited	limited	ADJ
cana-2347	60	15	sample	sample	NOUN
cana-2347	60	16	size	size	NOUN
cana-2347	60	17	and	and	CCONJ
cana-2347	60	18	the	the	DET
cana-2347	60	19	use	use	NOUN
cana-2347	60	20	of	of	ADP
cana-2347	60	21	a	a	DET
cana-2347	60	22	single	single	ADJ
cana-2347	60	23	imaging	imaging	NOUN
cana-2347	60	24	modality	modality	NOUN
cana-2347	60	25	.	.	PUNCT
cana-2347	61	1	future	future	ADJ
cana-2347	61	2	research	research	NOUN
cana-2347	61	3	could	could	AUX
cana-2347	61	4	explore	explore	VERB
cana-2347	61	5	the	the	DET
cana-2347	61	6	use	use	NOUN
cana-2347	61	7	of	of	ADP
cana-2347	61	8	other	other	ADJ
cana-2347	61	9	imaging	imaging	NOUN
cana-2347	61	10	modalities	modality	NOUN
cana-2347	61	11	and	and	CCONJ
cana-2347	61	12	larger	large	ADJ
cana-2347	61	13	sample	sample	NOUN
cana-2347	61	14	sizes	size	NOUN
cana-2347	61	15	to	to	PART
cana-2347	61	16	further	far	ADV
cana-2347	61	17	validate	validate	VERB
cana-2347	61	18	these	these	DET
cana-2347	61	19	findings	finding	NOUN
cana-2347	61	20	.	.	PUNCT
cana-2347	62	1	furthermore	furthermore	ADV
cana-2347	62	2	,	,	PUNCT
cana-2347	62	3	the	the	DET
cana-2347	62	4	research	research	NOUN
cana-2347	62	5	did	do	AUX
cana-2347	62	6	not	not	PART
cana-2347	62	7	examine	examine	VERB
cana-2347	62	8	the	the	DET
cana-2347	62	9	possible	possible	ADJ
cana-2347	62	10	influence	influence	NOUN
cana-2347	62	11	of	of	ADP
cana-2347	62	12	socioeconomic	socioeconomic	ADJ
cana-2347	62	13	factors	factor	NOUN
cana-2347	62	14	on	on	ADP
cana-2347	62	15	the	the	DET
cana-2347	62	16	precision	precision	NOUN
cana-2347	62	17	of	of	ADP
cana-2347	62	18	tumour	tumour	NOUN
cana-2347	62	19	classification	classification	NOUN
cana-2347	62	20	,	,	PUNCT
cana-2347	62	21	an	an	DET
cana-2347	62	22	area	area	NOUN
cana-2347	62	23	that	that	PRON
cana-2347	62	24	requires	require	VERB
cana-2347	62	25	further	further	ADJ
cana-2347	62	26	investigation	investigation	NOUN
cana-2347	62	27	.	.	PUNCT
cana-2347	63	1	taking	take	VERB
cana-2347	63	2	everything	everything	PRON
cana-2347	63	3	looked	look	VERB
cana-2347	63	4	at	at	ADP
cana-2347	63	5	,	,	PUNCT
cana-2347	63	6	the	the	DET
cana-2347	63	7	study	study	NOUN
cana-2347	63	8	offers	offer	VERB
cana-2347	63	9	insightful	insightful	ADJ
cana-2347	63	10	information	information	NOUN
cana-2347	63	11	about	about	ADP
cana-2347	63	12	how	how	SCONJ
cana-2347	63	13	machine	machine	NOUN
cana-2347	63	14	learning	learn	VERB
cana-2347	63	15	algorithms	algorithm	NOUN
cana-2347	63	16	might	might	AUX
cana-2347	63	17	increase	increase	VERB
cana-2347	63	18	the	the	DET
cana-2347	63	19	precision	precision	NOUN
cana-2347	63	20	of	of	ADP
cana-2347	63	21	ovarian	ovarian	ADJ
cana-2347	63	22	tumour	tumour	NOUN
cana-2347	63	23	classification	classification	NOUN
cana-2347	63	24	;	;	PUNCT
cana-2347	63	25	however	however	ADV
cana-2347	63	26	,	,	PUNCT
cana-2347	63	27	more	more	ADJ
cana-2347	63	28	investigation	investigation	NOUN
cana-2347	63	29	is	be	AUX
cana-2347	63	30	required	require	VERB
cana-2347	63	31	to	to	PART
cana-2347	63	32	completely	completely	ADV
cana-2347	63	33	comprehend	comprehend	VERB
cana-2347	63	34	the	the	DET
cana-2347	63	35	constraints	constraint	NOUN
cana-2347	63	36	and	and	CCONJ
cana-2347	63	37	possible	possible	ADJ
cana-2347	63	38	uses	use	NOUN
cana-2347	63	39	of	of	ADP
cana-2347	63	40	these	these	DET
cana-2347	63	41	techniques	technique	NOUN
cana-2347	63	42	.	.	PUNCT
cana-2347	64	1	communications	communication	NOUN
cana-2347	64	2	on	on	ADP
cana-2347	64	3	applied	apply	VERB
cana-2347	64	4	nonlinear	nonlinear	ADJ
cana-2347	64	5	analysis	analysis	NOUN
cana-2347	64	6	issn	issn	NOUN
cana-2347	64	7	:	:	PUNCT
cana-2347	64	8	1074	1074	NUM
cana-2347	64	9	-	-	PUNCT
cana-2347	64	10	133x	133x	NUM
cana-2347	64	11	vol	vol	NOUN
cana-2347	64	12	32	32	NUM
cana-2347	64	13	no	no	NOUN
cana-2347	64	14	.	.	PUNCT
cana-2347	65	1	1s	1s	NUM
cana-2347	65	2	(	(	PUNCT
cana-2347	65	3	2025	2025	NUM
cana-2347	65	4	)	)	PUNCT
cana-2347	65	5	615	615	NUM
cana-2347	65	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	65	7	figure	figure	NOUN
cana-2347	65	8	7	7	NUM
cana-2347	65	9	:	:	PUNCT
cana-2347	65	10	comparison	comparison	NOUN
cana-2347	65	11	of	of	ADP
cana-2347	65	12	classification	classification	NOUN
cana-2347	65	13	performance	performance	NOUN
cana-2347	65	14	measures	measure	NOUN
cana-2347	65	15	for	for	ADP
cana-2347	65	16	different	different	ADJ
cana-2347	65	17	machine	machine	NOUN
cana-2347	65	18	learning	learn	VERB
cana-2347	65	19	algorithms	algorithm	NOUN
cana-2347	65	20	in	in	ADP
cana-2347	65	21	this	this	DET
cana-2347	65	22	work	work	NOUN
cana-2347	65	23	,	,	PUNCT
cana-2347	65	24	deeparani	deeparani	PROPN
cana-2347	65	25	m.	m.	PROPN
cana-2347	65	26	et	et	PROPN
cana-2347	65	27	al	al	PROPN
cana-2347	65	28	.	.	PUNCT
cana-2347	66	1	[	[	X
cana-2347	66	2	7	7	X
cana-2347	66	3	]	]	PUNCT
cana-2347	66	4	provide	provide	VERB
cana-2347	66	5	a	a	DET
cana-2347	66	6	computer	computer	NOUN
cana-2347	66	7	-	-	PUNCT
cana-2347	66	8	aided	aid	VERB
cana-2347	66	9	diagnostic	diagnostic	ADJ
cana-2347	66	10	(	(	PUNCT
cana-2347	66	11	cad	cad	NOUN
cana-2347	66	12	)	)	PUNCT
cana-2347	66	13	system	system	NOUN
cana-2347	66	14	that	that	PRON
cana-2347	66	15	uses	use	VERB
cana-2347	66	16	ultrasound	ultrasound	NOUN
cana-2347	66	17	images	image	NOUN
cana-2347	66	18	to	to	PART
cana-2347	66	19	accurately	accurately	ADV
cana-2347	66	20	classify	classify	VERB
cana-2347	66	21	and	and	CCONJ
cana-2347	66	22	diagnose	diagnose	VERB
cana-2347	66	23	gynaecological	gynaecological	ADJ
cana-2347	66	24	abdominal	abdominal	ADJ
cana-2347	66	25	pelvic	pelvic	ADJ
cana-2347	66	26	masses	masse	NOUN
cana-2347	66	27	early	early	ADV
cana-2347	66	28	on	on	ADV
cana-2347	66	29	.	.	PUNCT
cana-2347	67	1	the	the	DET
cana-2347	67	2	system	system	NOUN
cana-2347	67	3	’s	’s	PART
cana-2347	67	4	foundation	foundation	NOUN
cana-2347	67	5	is	be	AUX
cana-2347	67	6	an	an	DET
cana-2347	67	7	evolutionary	evolutionary	ADJ
cana-2347	67	8	gravitational	gravitational	ADJ
cana-2347	67	9	neocognitron	neocognitron	PROPN
cana-2347	67	10	neural	neural	ADJ
cana-2347	67	11	network	network	NOUN
cana-2347	67	12	(	(	PUNCT
cana-2347	67	13	egnnn	egnnn	NOUN
cana-2347	67	14	)	)	PUNCT
cana-2347	67	15	with	with	ADP
cana-2347	67	16	efficient	efficient	ADJ
cana-2347	67	17	,	,	PUNCT
cana-2347	67	18	fast	fast	ADV
cana-2347	67	19	discrete	discrete	ADJ
cana-2347	67	20	curvelet	curvelet	NOUN
cana-2347	67	21	transform	transform	NOUN
cana-2347	67	22	with	with	ADP
cana-2347	67	23	the	the	DET
cana-2347	67	24	wrapping	wrapping	NOUN
cana-2347	67	25	method	method	NOUN
cana-2347	67	26	(	(	PUNCT
cana-2347	67	27	fdct	fdct	ADJ
cana-2347	67	28	-	-	PUNCT
cana-2347	67	29	wrp	wrp	NOUN
cana-2347	67	30	)	)	PUNCT
cana-2347	67	31	for	for	ADP
cana-2347	67	32	feature	feature	NOUN
cana-2347	67	33	extraction	extraction	NOUN
cana-2347	67	34	,	,	PUNCT
cana-2347	67	35	and	and	CCONJ
cana-2347	67	36	an	an	DET
cana-2347	67	37	adaptable	adaptable	ADJ
cana-2347	67	38	nomadic	nomadic	ADJ
cana-2347	67	39	people	people	NOUN
cana-2347	67	40	optimizer	optimizer	NOUN
cana-2347	67	41	(	(	PUNCT
cana-2347	67	42	npoa	npoa	NOUN
cana-2347	67	43	)	)	PUNCT
cana-2347	67	44	.	.	PUNCT
cana-2347	68	1	the	the	DET
cana-2347	68	2	proposed	propose	VERB
cana-2347	68	3	technique	technique	NOUN
cana-2347	68	4	aims	aim	VERB
cana-2347	68	5	to	to	PART
cana-2347	68	6	reduce	reduce	VERB
cana-2347	68	7	errors	error	NOUN
cana-2347	68	8	during	during	ADP
cana-2347	68	9	the	the	DET
cana-2347	68	10	classification	classification	NOUN
cana-2347	68	11	process	process	NOUN
cana-2347	68	12	and	and	CCONJ
cana-2347	68	13	increase	increase	VERB
cana-2347	68	14	the	the	DET
cana-2347	68	15	area	area	NOUN
cana-2347	68	16	under	under	ADP
cana-2347	68	17	the	the	DET
cana-2347	68	18	curve	curve	NOUN
cana-2347	68	19	value	value	NOUN
cana-2347	68	20	.	.	PUNCT
cana-2347	69	1	research	research	NOUN
cana-2347	69	2	gaps	gap	NOUN
cana-2347	69	3	in	in	ADP
cana-2347	69	4	this	this	DET
cana-2347	69	5	area	area	NOUN
cana-2347	69	6	may	may	AUX
cana-2347	69	7	include	include	VERB
cana-2347	69	8	the	the	DET
cana-2347	69	9	need	need	NOUN
cana-2347	69	10	for	for	ADP
cana-2347	69	11	further	further	ADJ
cana-2347	69	12	validation	validation	NOUN
cana-2347	69	13	of	of	ADP
cana-2347	69	14	the	the	DET
cana-2347	69	15	proposed	propose	VERB
cana-2347	69	16	technique	technique	NOUN
cana-2347	69	17	on	on	ADP
cana-2347	69	18	larger	large	ADJ
cana-2347	69	19	datasets	dataset	NOUN
cana-2347	69	20	and	and	CCONJ
cana-2347	69	21	comparison	comparison	NOUN
cana-2347	69	22	with	with	ADP
cana-2347	69	23	other	other	ADJ
cana-2347	69	24	existing	exist	VERB
cana-2347	69	25	techniques	technique	NOUN
cana-2347	69	26	.	.	PUNCT
cana-2347	70	1	additionally	additionally	ADV
cana-2347	70	2	,	,	PUNCT
cana-2347	70	3	the	the	DET
cana-2347	70	4	potential	potential	ADJ
cana-2347	70	5	impact	impact	NOUN
cana-2347	70	6	of	of	ADP
cana-2347	70	7	this	this	DET
cana-2347	70	8	technique	technique	NOUN
cana-2347	70	9	on	on	ADP
cana-2347	70	10	clinical	clinical	ADJ
cana-2347	70	11	decision	decision	NOUN
cana-2347	70	12	-	-	PUNCT
cana-2347	70	13	making	make	VERB
cana-2347	70	14	and	and	CCONJ
cana-2347	70	15	patient	patient	ADJ
cana-2347	70	16	outcomes	outcome	NOUN
cana-2347	70	17	needs	need	VERB
cana-2347	70	18	to	to	PART
cana-2347	70	19	be	be	AUX
cana-2347	70	20	explored	explore	VERB
cana-2347	70	21	.	.	PUNCT
cana-2347	71	1	denny	denny	PROPN
cana-2347	71	2	et	et	PROPN
cana-2347	71	3	al	al	PROPN
cana-2347	71	4	.	.	PUNCT
cana-2347	72	1	[	[	X
cana-2347	72	2	8	8	NUM
cana-2347	72	3	]	]	PUNCT
cana-2347	72	4	developed	develop	VERB
cana-2347	72	5	an	an	DET
cana-2347	72	6	advanced	advanced	ADJ
cana-2347	72	7	diagnostic	diagnostic	ADJ
cana-2347	72	8	system	system	NOUN
cana-2347	72	9	aimed	aim	VERB
cana-2347	72	10	at	at	ADP
cana-2347	72	11	the	the	DET
cana-2347	72	12	early	early	ADJ
cana-2347	72	13	identification	identification	NOUN
cana-2347	72	14	and	and	CCONJ
cana-2347	72	15	prediction	prediction	NOUN
cana-2347	72	16	of	of	ADP
cana-2347	72	17	polycystic	polycystic	ADJ
cana-2347	72	18	ovary	ovary	ADJ
cana-2347	72	19	syndrome	syndrome	NOUN
cana-2347	72	20	(	(	PUNCT
cana-2347	72	21	pcos	pcos	PROPN
cana-2347	72	22	)	)	PUNCT
cana-2347	72	23	in	in	ADP
cana-2347	72	24	women	woman	NOUN
cana-2347	72	25	using	use	VERB
cana-2347	72	26	machine	machine	NOUN
cana-2347	72	27	learning	learning	NOUN
cana-2347	72	28	methods	method	NOUN
cana-2347	72	29	.	.	PUNCT
cana-2347	73	1	the	the	DET
cana-2347	73	2	study	study	NOUN
cana-2347	73	3	involved	involve	VERB
cana-2347	73	4	collecting	collect	VERB
cana-2347	73	5	data	datum	NOUN
cana-2347	73	6	from	from	ADP
cana-2347	73	7	different	different	ADJ
cana-2347	73	8	hospitals	hospital	NOUN
cana-2347	73	9	and	and	CCONJ
cana-2347	73	10	clinics	clinic	NOUN
cana-2347	73	11	,	,	PUNCT
cana-2347	73	12	followed	follow	VERB
cana-2347	73	13	by	by	ADP
cana-2347	73	14	the	the	DET
cana-2347	73	15	application	application	NOUN
cana-2347	73	16	of	of	ADP
cana-2347	73	17	principal	principal	ADJ
cana-2347	73	18	component	component	NOUN
cana-2347	73	19	analysis	analysis	NOUN
cana-2347	73	20	(	(	PUNCT
cana-2347	73	21	pca	pca	NOUN
cana-2347	73	22	)	)	PUNCT
cana-2347	73	23	to	to	PART
cana-2347	73	24	refine	refine	VERB
cana-2347	73	25	the	the	DET
cana-2347	73	26	feature	feature	NOUN
cana-2347	73	27	set	set	VERB
cana-2347	73	28	for	for	ADP
cana-2347	73	29	classification	classification	NOUN
cana-2347	73	30	through	through	ADP
cana-2347	73	31	various	various	ADJ
cana-2347	73	32	machine	machine	NOUN
cana-2347	73	33	learning	learning	NOUN
cana-2347	73	34	models	model	NOUN
cana-2347	73	35	.	.	PUNCT
cana-2347	74	1	with	with	ADP
cana-2347	74	2	a	a	DET
cana-2347	74	3	prediction	prediction	NOUN
cana-2347	74	4	accuracy	accuracy	NOUN
cana-2347	74	5	of	of	ADP
cana-2347	74	6	89.02	89.02	NUM
cana-2347	74	7	%	%	NOUN
cana-2347	74	8	,	,	PUNCT
cana-2347	74	9	the	the	DET
cana-2347	74	10	random	random	ADJ
cana-2347	74	11	forest	forest	NOUN
cana-2347	74	12	classifier	classifier	NOUN
cana-2347	74	13	(	(	PUNCT
cana-2347	74	14	rfc	rfc	PROPN
cana-2347	74	15	)	)	PUNCT
cana-2347	74	16	proved	prove	VERB
cana-2347	74	17	to	to	PART
cana-2347	74	18	be	be	AUX
cana-2347	74	19	the	the	DET
cana-2347	74	20	most	most	ADV
cana-2347	74	21	successful	successful	ADJ
cana-2347	74	22	of	of	ADP
cana-2347	74	23	the	the	DET
cana-2347	74	24	techniques	technique	NOUN
cana-2347	74	25	examined	examine	VERB
cana-2347	74	26	.	.	PUNCT
cana-2347	75	1	the	the	DET
cana-2347	75	2	i	i	PROPN
cana-2347	75	3	-	-	PUNCT
cana-2347	75	4	hope	hope	NOUN
cana-2347	75	5	system	system	NOUN
cana-2347	75	6	represents	represent	VERB
cana-2347	75	7	a	a	DET
cana-2347	75	8	promising	promising	ADJ
cana-2347	75	9	solution	solution	NOUN
cana-2347	75	10	for	for	ADP
cana-2347	75	11	addressing	address	VERB
cana-2347	75	12	the	the	DET
cana-2347	75	13	widespread	widespread	ADJ
cana-2347	75	14	challenge	challenge	NOUN
cana-2347	75	15	of	of	ADP
cana-2347	75	16	infertility	infertility	NOUN
cana-2347	75	17	in	in	ADP
cana-2347	75	18	women	woman	NOUN
cana-2347	75	19	.	.	PUNCT
cana-2347	76	1	3	3	X
cana-2347	76	2	.	.	NUM
cana-2347	76	3	proposed	propose	VERB
cana-2347	76	4	methodology	methodology	NOUN
cana-2347	76	5	this	this	DET
cana-2347	76	6	section	section	NOUN
cana-2347	76	7	describes	describe	VERB
cana-2347	76	8	the	the	DET
cana-2347	76	9	suggested	suggest	VERB
cana-2347	76	10	approach	approach	NOUN
cana-2347	76	11	for	for	ADP
cana-2347	76	12	utilizing	utilize	VERB
cana-2347	76	13	state	state	NOUN
cana-2347	76	14	-	-	PUNCT
cana-2347	76	15	of	of	ADP
cana-2347	76	16	-	-	PUNCT
cana-2347	76	17	the	the	DET
cana-2347	76	18	-	-	PUNCT
cana-2347	76	19	art	art	NOUN
cana-2347	76	20	deep	deep	ADJ
cana-2347	76	21	learning	learning	NOUN
cana-2347	76	22	algorithms	algorithm	NOUN
cana-2347	76	23	to	to	PART
cana-2347	76	24	improve	improve	VERB
cana-2347	76	25	the	the	DET
cana-2347	76	26	precision	precision	NOUN
cana-2347	76	27	and	and	CCONJ
cana-2347	76	28	efficacy	efficacy	NOUN
cana-2347	76	29	of	of	ADP
cana-2347	76	30	medical	medical	ADJ
cana-2347	76	31	image	image	NOUN
cana-2347	76	32	segmentation	segmentation	NOUN
cana-2347	76	33	-	-	PUNCT
cana-2347	76	34	based	base	VERB
cana-2347	76	35	ovarian	ovarian	ADJ
cana-2347	76	36	disease	disease	NOUN
cana-2347	76	37	detection	detection	NOUN
cana-2347	76	38	.	.	PUNCT
cana-2347	77	1	the	the	DET
cana-2347	77	2	methodology	methodology	NOUN
cana-2347	77	3	is	be	AUX
cana-2347	77	4	structured	structure	VERB
cana-2347	77	5	into	into	ADP
cana-2347	77	6	several	several	ADJ
cana-2347	77	7	key	key	ADJ
cana-2347	77	8	components	component	NOUN
cana-2347	77	9	,	,	PUNCT
cana-2347	77	10	which	which	PRON
cana-2347	77	11	include	include	VERB
cana-2347	77	12	dataset	dataset	ADJ
cana-2347	77	13	preparation	preparation	NOUN
cana-2347	77	14	,	,	PUNCT
cana-2347	77	15	model	model	NOUN
cana-2347	77	16	architecture	architecture	NOUN
cana-2347	77	17	selection	selection	NOUN
cana-2347	77	18	,	,	PUNCT
cana-2347	77	19	training	training	NOUN
cana-2347	77	20	and	and	CCONJ
cana-2347	77	21	validation	validation	NOUN
cana-2347	77	22	processes	process	NOUN
cana-2347	77	23	,	,	PUNCT
cana-2347	77	24	performance	performance	NOUN
cana-2347	77	25	evaluation	evaluation	NOUN
cana-2347	77	26	,	,	PUNCT
cana-2347	77	27	and	and	CCONJ
cana-2347	77	28	comparative	comparative	ADJ
cana-2347	77	29	analysis	analysis	NOUN
cana-2347	77	30	.	.	PUNCT
cana-2347	78	1	communications	communication	NOUN
cana-2347	78	2	on	on	ADP
cana-2347	78	3	applied	apply	VERB
cana-2347	78	4	nonlinear	nonlinear	ADJ
cana-2347	78	5	analysis	analysis	NOUN
cana-2347	78	6	issn	issn	NOUN
cana-2347	78	7	:	:	PUNCT
cana-2347	78	8	1074	1074	NUM
cana-2347	78	9	-	-	PUNCT
cana-2347	78	10	133x	133x	NUM
cana-2347	78	11	vol	vol	NOUN
cana-2347	78	12	32	32	NUM
cana-2347	78	13	no	no	NOUN
cana-2347	78	14	.	.	PUNCT
cana-2347	79	1	1s	1s	NUM
cana-2347	79	2	(	(	PUNCT
cana-2347	79	3	2025	2025	NUM
cana-2347	79	4	)	)	PUNCT
cana-2347	79	5	616	616	NUM
cana-2347	79	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	79	7	figure	figure	NOUN
cana-2347	79	8	8	8	NUM
cana-2347	79	9	:	:	PUNCT
cana-2347	79	10	proposed	propose	VERB
cana-2347	79	11	methodology	methodology	NOUN
cana-2347	79	12	data	datum	NOUN
cana-2347	79	13	collection	collection	NOUN
cana-2347	79	14	the	the	DET
cana-2347	79	15	mmotu	mmotu	PROPN
cana-2347	79	16	ovarian	ovarian	ADJ
cana-2347	79	17	tumour	tumour	NOUN
cana-2347	79	18	ultrasound	ultrasound	NOUN
cana-2347	79	19	dataset	dataset	NOUN
cana-2347	79	20	served	serve	VERB
cana-2347	79	21	as	as	ADP
cana-2347	79	22	the	the	DET
cana-2347	79	23	study	study	NOUN
cana-2347	79	24	’s	’s	PART
cana-2347	79	25	data	datum	NOUN
cana-2347	79	26	set	set	NOUN
cana-2347	79	27	,	,	PUNCT
cana-2347	79	28	which	which	PRON
cana-2347	79	29	was	be	AUX
cana-2347	79	30	meticulously	meticulously	ADV
cana-2347	79	31	collected	collect	VERB
cana-2347	79	32	from	from	ADP
cana-2347	79	33	beijing	beijing	PROPN
cana-2347	79	34	shijitan	shijitan	PROPN
cana-2347	79	35	hospital	hospital	PROPN
cana-2347	79	36	,	,	PUNCT
cana-2347	79	37	capital	capital	PROPN
cana-2347	79	38	medical	medical	PROPN
cana-2347	79	39	university	university	PROPN
cana-2347	79	40	.	.	PUNCT
cana-2347	80	1	this	this	DET
cana-2347	80	2	dataset	dataset	NOUN
cana-2347	80	3	is	be	AUX
cana-2347	80	4	integral	integral	ADJ
cana-2347	80	5	to	to	ADP
cana-2347	80	6	the	the	DET
cana-2347	80	7	research	research	NOUN
cana-2347	80	8	due	due	ADP
cana-2347	80	9	to	to	ADP
cana-2347	80	10	its	its	PRON
cana-2347	80	11	diverse	diverse	ADJ
cana-2347	80	12	and	and	CCONJ
cana-2347	80	13	detailed	detailed	ADJ
cana-2347	80	14	imaging	imaging	NOUN
cana-2347	80	15	,	,	PUNCT
cana-2347	80	16	specifically	specifically	ADV
cana-2347	80	17	tailored	tailor	VERB
cana-2347	80	18	for	for	ADP
cana-2347	80	19	ovarian	ovarian	ADJ
cana-2347	80	20	tumour	tumour	NOUN
cana-2347	80	21	analysis	analysis	NOUN
cana-2347	80	22	.	.	PUNCT
cana-2347	81	1	the	the	DET
cana-2347	81	2	mmotu	mmotu	PROPN
cana-2347	81	3	dataset	dataset	NOUN
cana-2347	81	4	is	be	AUX
cana-2347	81	5	organized	organize	VERB
cana-2347	81	6	into	into	ADP
cana-2347	81	7	two	two	NUM
cana-2347	81	8	primary	primary	ADJ
cana-2347	81	9	subsets	subset	NOUN
cana-2347	81	10	:	:	PUNCT
cana-2347	81	11	otu	otu	PROPN
cana-2347	81	12	2d	2d	PROPN
cana-2347	81	13	subset	subset	VERB
cana-2347	81	14	:	:	PUNCT
cana-2347	81	15	this	this	DET
cana-2347	81	16	subset	subset	NOUN
cana-2347	81	17	consists	consist	VERB
cana-2347	81	18	of	of	ADP
cana-2347	81	19	standard	standard	ADJ
cana-2347	81	20	2d	2d	NUM
cana-2347	81	21	ultrasound	ultrasound	NOUN
cana-2347	81	22	images	image	NOUN
cana-2347	81	23	,	,	PUNCT
cana-2347	81	24	capturing	capture	VERB
cana-2347	81	25	a	a	DET
cana-2347	81	26	wide	wide	ADJ
cana-2347	81	27	range	range	NOUN
cana-2347	81	28	of	of	ADP
cana-2347	81	29	ovarian	ovarian	ADJ
cana-2347	81	30	tumour	tumour	NOUN
cana-2347	81	31	appearances	appearance	NOUN
cana-2347	81	32	.	.	PUNCT
cana-2347	82	1	these	these	DET
cana-2347	82	2	images	image	NOUN
cana-2347	82	3	provide	provide	VERB
cana-2347	82	4	essential	essential	ADJ
cana-2347	82	5	data	datum	NOUN
cana-2347	82	6	for	for	ADP
cana-2347	82	7	training	training	NOUN
cana-2347	82	8	models	model	NOUN
cana-2347	82	9	to	to	PART
cana-2347	82	10	recognize	recognize	VERB
cana-2347	82	11	and	and	CCONJ
cana-2347	82	12	segment	segment	VERB
cana-2347	82	13	ovarian	ovarian	ADJ
cana-2347	82	14	tumours	tumour	NOUN
cana-2347	82	15	based	base	VERB
cana-2347	82	16	on	on	ADP
cana-2347	82	17	typical	typical	ADJ
cana-2347	82	18	ultrasound	ultrasound	ADJ
cana-2347	82	19	imaging	imaging	NOUN
cana-2347	82	20	modalities	modality	NOUN
cana-2347	82	21	.	.	PUNCT
cana-2347	83	1	otu	otu	PROPN
cana-2347	83	2	ceus	ceus	PROPN
cana-2347	83	3	subset	subset	VERB
cana-2347	83	4	:	:	PUNCT
cana-2347	83	5	this	this	DET
cana-2347	83	6	subset	subset	NOUN
cana-2347	83	7	includes	include	VERB
cana-2347	83	8	170	170	NUM
cana-2347	83	9	images	image	NOUN
cana-2347	83	10	extracted	extract	VERB
cana-2347	83	11	from	from	ADP
cana-2347	83	12	contrast	contrast	NOUN
cana-2347	83	13	-	-	PUNCT
cana-2347	83	14	enhanced	enhance	VERB
cana-2347	83	15	ultrasound	ultrasound	NOUN
cana-2347	83	16	(	(	PUNCT
cana-2347	83	17	ceus	ceus	PROPN
cana-2347	83	18	)	)	PUNCT
cana-2347	83	19	sequences	sequence	NOUN
cana-2347	83	20	.	.	PUNCT
cana-2347	84	1	ceus	ceus	PROPN
cana-2347	84	2	provides	provide	VERB
cana-2347	84	3	enhanced	enhanced	ADJ
cana-2347	84	4	imaging	imaging	NOUN
cana-2347	84	5	contrast	contrast	NOUN
cana-2347	84	6	,	,	PUNCT
cana-2347	84	7	allowing	allow	VERB
cana-2347	84	8	for	for	ADP
cana-2347	84	9	a	a	DET
cana-2347	84	10	more	more	ADV
cana-2347	84	11	detailed	detailed	ADJ
cana-2347	84	12	examination	examination	NOUN
cana-2347	84	13	of	of	ADP
cana-2347	84	14	tumor	tumor	NOUN
cana-2347	84	15	structures	structure	NOUN
cana-2347	84	16	and	and	CCONJ
cana-2347	84	17	vascular	vascular	ADJ
cana-2347	84	18	patterns	pattern	NOUN
cana-2347	84	19	,	,	PUNCT
cana-2347	84	20	which	which	PRON
cana-2347	84	21	are	be	AUX
cana-2347	84	22	critical	critical	ADJ
cana-2347	84	23	for	for	ADP
cana-2347	84	24	accurate	accurate	ADJ
cana-2347	84	25	segmentation	segmentation	NOUN
cana-2347	84	26	and	and	CCONJ
cana-2347	84	27	diagnosis	diagnosis	NOUN
cana-2347	84	28	.	.	PUNCT
cana-2347	85	1	the	the	DET
cana-2347	85	2	combination	combination	NOUN
cana-2347	85	3	of	of	ADP
cana-2347	85	4	these	these	DET
cana-2347	85	5	subsets	subset	NOUN
cana-2347	85	6	offers	offer	VERB
cana-2347	85	7	a	a	DET
cana-2347	85	8	rich	rich	ADJ
cana-2347	85	9	and	and	CCONJ
cana-2347	85	10	comprehensive	comprehensive	ADJ
cana-2347	85	11	dataset	dataset	NOUN
cana-2347	85	12	,	,	PUNCT
cana-2347	85	13	ensuring	ensure	VERB
cana-2347	85	14	that	that	SCONJ
cana-2347	85	15	the	the	DET
cana-2347	85	16	deep	deep	ADJ
cana-2347	85	17	learning	learning	NOUN
cana-2347	85	18	models	model	NOUN
cana-2347	85	19	developed	develop	VERB
cana-2347	85	20	in	in	ADP
cana-2347	85	21	this	this	DET
cana-2347	85	22	study	study	NOUN
cana-2347	85	23	are	be	AUX
cana-2347	85	24	well	well	ADV
cana-2347	85	25	-	-	PUNCT
cana-2347	85	26	equipped	equip	VERB
cana-2347	85	27	to	to	PART
cana-2347	85	28	handle	handle	VERB
cana-2347	85	29	the	the	DET
cana-2347	85	30	complexities	complexity	NOUN
cana-2347	85	31	of	of	ADP
cana-2347	85	32	ovarian	ovarian	ADJ
cana-2347	85	33	tumour	tumour	NOUN
cana-2347	85	34	detection	detection	NOUN
cana-2347	85	35	across	across	ADP
cana-2347	85	36	different	different	ADJ
cana-2347	85	37	imaging	imaging	NOUN
cana-2347	85	38	techniques	technique	NOUN
cana-2347	85	39	.	.	PUNCT
cana-2347	86	1	data	datum	NOUN
cana-2347	86	2	preprocessing	preprocesse	VERB
cana-2347	86	3	data	datum	NOUN
cana-2347	86	4	preprocessing	preprocessing	NOUN
cana-2347	86	5	is	be	AUX
cana-2347	86	6	a	a	DET
cana-2347	86	7	crucial	crucial	ADJ
cana-2347	86	8	step	step	NOUN
cana-2347	86	9	in	in	ADP
cana-2347	86	10	preparing	prepare	VERB
cana-2347	86	11	the	the	DET
cana-2347	86	12	mmotu	mmotu	NOUN
cana-2347	86	13	dataset	dataset	VERB
cana-2347	86	14	for	for	ADP
cana-2347	86	15	training	train	VERB
cana-2347	86	16	the	the	DET
cana-2347	86	17	deep	deep	ADJ
cana-2347	86	18	learning	learning	NOUN
cana-2347	86	19	models	model	NOUN
cana-2347	86	20	.	.	PUNCT
cana-2347	87	1	the	the	DET
cana-2347	87	2	preprocessing	preprocessing	NOUN
cana-2347	87	3	pipeline	pipeline	NOUN
cana-2347	87	4	includes	include	VERB
cana-2347	87	5	several	several	ADJ
cana-2347	87	6	key	key	ADJ
cana-2347	87	7	steps	step	NOUN
cana-2347	87	8	:	:	PUNCT
cana-2347	87	9	communications	communication	NOUN
cana-2347	87	10	on	on	ADP
cana-2347	87	11	applied	apply	VERB
cana-2347	87	12	nonlinear	nonlinear	ADJ
cana-2347	87	13	analysis	analysis	NOUN
cana-2347	87	14	issn	issn	NOUN
cana-2347	87	15	:	:	PUNCT
cana-2347	87	16	1074	1074	NUM
cana-2347	87	17	-	-	PUNCT
cana-2347	87	18	133x	133x	NUM
cana-2347	87	19	vol	vol	NOUN
cana-2347	87	20	32	32	NUM
cana-2347	88	1	no	no	NOUN
cana-2347	88	2	.	.	PUNCT
cana-2347	89	1	1s	1s	NUM
cana-2347	89	2	(	(	PUNCT
cana-2347	89	3	2025	2025	NUM
cana-2347	89	4	)	)	PUNCT
cana-2347	89	5	617	617	NUM
cana-2347	89	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	89	7	image	image	NOUN
cana-2347	89	8	resizing	resizing	NOUN
cana-2347	89	9	:	:	PUNCT
cana-2347	89	10	all	all	DET
cana-2347	89	11	images	image	NOUN
cana-2347	89	12	in	in	ADP
cana-2347	89	13	the	the	DET
cana-2347	89	14	otu	otu	PROPN
cana-2347	89	15	2d	2d	PROPN
cana-2347	89	16	and	and	CCONJ
cana-2347	90	1	otu	otu	PROPN
cana-2347	90	2	ceus	ceus	PROPN
cana-2347	90	3	subsets	subset	NOUN
cana-2347	90	4	are	be	AUX
cana-2347	90	5	resized	resize	VERB
cana-2347	90	6	to	to	ADP
cana-2347	90	7	a	a	DET
cana-2347	90	8	consistent	consistent	ADJ
cana-2347	90	9	resolution	resolution	NOUN
cana-2347	90	10	.	.	PUNCT
cana-2347	91	1	this	this	DET
cana-2347	91	2	standardization	standardization	NOUN
cana-2347	91	3	is	be	AUX
cana-2347	91	4	necessary	necessary	ADJ
cana-2347	91	5	to	to	PART
cana-2347	91	6	ensure	ensure	VERB
cana-2347	91	7	uniformity	uniformity	NOUN
cana-2347	91	8	in	in	ADP
cana-2347	91	9	input	input	NOUN
cana-2347	91	10	dimensions	dimension	NOUN
cana-2347	91	11	across	across	ADP
cana-2347	91	12	the	the	DET
cana-2347	91	13	dataset	dataset	NOUN
cana-2347	91	14	,	,	PUNCT
cana-2347	91	15	facilitating	facilitate	VERB
cana-2347	91	16	more	more	ADV
cana-2347	91	17	efficient	efficient	ADJ
cana-2347	91	18	model	model	NOUN
cana-2347	91	19	training	training	NOUN
cana-2347	91	20	and	and	CCONJ
cana-2347	91	21	inference	inference	NOUN
cana-2347	91	22	.	.	PUNCT
cana-2347	92	1	normalization	normalization	NOUN
cana-2347	92	2	:	:	PUNCT
cana-2347	92	3	the	the	DET
cana-2347	92	4	image	image	NOUN
cana-2347	92	5	’s	’s	PART
cana-2347	92	6	pixel	pixel	PROPN
cana-2347	92	7	intensity	intensity	NOUN
cana-2347	92	8	values	value	NOUN
cana-2347	92	9	are	be	AUX
cana-2347	92	10	standardized	standardize	VERB
cana-2347	92	11	to	to	PART
cana-2347	92	12	fall	fall	VERB
cana-2347	92	13	into	into	ADP
cana-2347	92	14	a	a	DET
cana-2347	92	15	predetermined	predetermined	ADJ
cana-2347	92	16	range	range	NOUN
cana-2347	92	17	(	(	PUNCT
cana-2347	92	18	[	[	X
cana-2347	92	19	0,1	0,1	NUM
cana-2347	92	20	]	]	PUNCT
cana-2347	92	21	)	)	PUNCT
cana-2347	92	22	.	.	PUNCT
cana-2347	93	1	this	this	DET
cana-2347	93	2	normalization	normalization	NOUN
cana-2347	93	3	step	step	NOUN
cana-2347	93	4	reduces	reduce	VERB
cana-2347	93	5	the	the	DET
cana-2347	93	6	impact	impact	NOUN
cana-2347	93	7	of	of	ADP
cana-2347	93	8	variations	variation	NOUN
cana-2347	93	9	in	in	ADP
cana-2347	93	10	image	image	NOUN
cana-2347	93	11	brightness	brightness	NOUN
cana-2347	93	12	and	and	CCONJ
cana-2347	93	13	contrast	contrast	NOUN
cana-2347	93	14	,	,	PUNCT
cana-2347	93	15	allowing	allow	VERB
cana-2347	93	16	the	the	DET
cana-2347	93	17	model	model	NOUN
cana-2347	93	18	to	to	PART
cana-2347	93	19	focus	focus	VERB
cana-2347	93	20	on	on	ADP
cana-2347	93	21	the	the	DET
cana-2347	93	22	underlying	underlie	VERB
cana-2347	93	23	structures	structure	NOUN
cana-2347	93	24	in	in	ADP
cana-2347	93	25	the	the	DET
cana-2347	93	26	images	image	NOUN
cana-2347	93	27	.	.	PUNCT
cana-2347	94	1	data	datum	NOUN
cana-2347	94	2	augmentation	augmentation	PROPN
cana-2347	94	3	:	:	PUNCT
cana-2347	94	4	a	a	DET
cana-2347	94	5	variety	variety	NOUN
cana-2347	94	6	of	of	ADP
cana-2347	94	7	data	datum	NOUN
cana-2347	94	8	augmentation	augmentation	NOUN
cana-2347	94	9	approaches	approach	NOUN
cana-2347	94	10	are	be	AUX
cana-2347	94	11	used	use	VERB
cana-2347	94	12	to	to	PART
cana-2347	94	13	improve	improve	VERB
cana-2347	94	14	the	the	DET
cana-2347	94	15	model	model	NOUN
cana-2347	94	16	’s	’s	PART
cana-2347	94	17	capacity	capacity	NOUN
cana-2347	94	18	to	to	PART
cana-2347	94	19	generalize	generalize	VERB
cana-2347	94	20	to	to	ADP
cana-2347	94	21	new	new	ADJ
cana-2347	94	22	,	,	PUNCT
cana-2347	94	23	unknown	unknown	ADJ
cana-2347	94	24	data	datum	NOUN
cana-2347	94	25	.	.	PUNCT
cana-2347	95	1	these	these	DET
cana-2347	95	2	techniques	technique	NOUN
cana-2347	95	3	include	include	VERB
cana-2347	95	4	:	:	PUNCT
cana-2347	95	5	rotation	rotation	NOUN
cana-2347	95	6	and	and	CCONJ
cana-2347	95	7	flipping	flipping	NOUN
cana-2347	95	8	:	:	PUNCT
cana-2347	95	9	random	random	ADJ
cana-2347	95	10	rotations	rotation	NOUN
cana-2347	95	11	and	and	CCONJ
cana-2347	95	12	horizontal	horizontal	ADJ
cana-2347	95	13	/	/	SYM
cana-2347	95	14	vertical	vertical	ADJ
cana-2347	95	15	flipping	flipping	NOUN
cana-2347	95	16	are	be	AUX
cana-2347	95	17	performed	perform	VERB
cana-2347	95	18	to	to	PART
cana-2347	95	19	simulate	simulate	VERB
cana-2347	95	20	different	different	ADJ
cana-2347	95	21	orientations	orientation	NOUN
cana-2347	95	22	of	of	ADP
cana-2347	95	23	the	the	DET
cana-2347	95	24	ovarian	ovarian	ADJ
cana-2347	95	25	tumours	tumour	NOUN
cana-2347	95	26	.	.	PUNCT
cana-2347	96	1	scaling	scale	VERB
cana-2347	96	2	:	:	PUNCT
cana-2347	96	3	the	the	DET
cana-2347	96	4	images	image	NOUN
cana-2347	96	5	are	be	AUX
cana-2347	96	6	randomly	randomly	ADV
cana-2347	96	7	scaled	scale	VERB
cana-2347	96	8	to	to	ADP
cana-2347	96	9	mimic	mimic	ADJ
cana-2347	96	10	variations	variation	NOUN
cana-2347	96	11	in	in	ADP
cana-2347	96	12	tumour	tumour	ADJ
cana-2347	96	13	size	size	NOUN
cana-2347	96	14	,	,	PUNCT
cana-2347	96	15	helping	help	VERB
cana-2347	96	16	the	the	DET
cana-2347	96	17	model	model	NOUN
cana-2347	96	18	to	to	PART
cana-2347	96	19	learn	learn	VERB
cana-2347	96	20	scale	scale	NOUN
cana-2347	96	21	-	-	PUNCT
cana-2347	96	22	invariant	invariant	ADJ
cana-2347	96	23	features	feature	NOUN
cana-2347	96	24	.	.	PUNCT
cana-2347	97	1	contrast	contrast	NOUN
cana-2347	97	2	adjustment	adjustment	NOUN
cana-2347	97	3	:	:	PUNCT
cana-2347	97	4	the	the	DET
cana-2347	97	5	contrast	contrast	NOUN
cana-2347	97	6	of	of	ADP
cana-2347	97	7	the	the	DET
cana-2347	97	8	images	image	NOUN
cana-2347	97	9	is	be	AUX
cana-2347	97	10	varied	varied	ADJ
cana-2347	97	11	to	to	PART
cana-2347	97	12	simulate	simulate	VERB
cana-2347	97	13	different	different	ADJ
cana-2347	97	14	imaging	imaging	NOUN
cana-2347	97	15	conditions	condition	NOUN
cana-2347	97	16	,	,	PUNCT
cana-2347	97	17	ensuring	ensure	VERB
cana-2347	97	18	that	that	SCONJ
cana-2347	97	19	the	the	DET
cana-2347	97	20	model	model	NOUN
cana-2347	97	21	can	can	AUX
cana-2347	97	22	robustly	robustly	ADV
cana-2347	97	23	handle	handle	VERB
cana-2347	97	24	variations	variation	NOUN
cana-2347	97	25	in	in	ADP
cana-2347	97	26	image	image	NOUN
cana-2347	97	27	quality	quality	NOUN
cana-2347	97	28	.	.	PUNCT
cana-2347	98	1	by	by	ADP
cana-2347	98	2	producing	produce	VERB
cana-2347	98	3	a	a	DET
cana-2347	98	4	varied	varied	ADJ
cana-2347	98	5	and	and	CCONJ
cana-2347	98	6	representative	representative	ADJ
cana-2347	98	7	training	training	NOUN
cana-2347	98	8	data	datum	NOUN
cana-2347	98	9	set	set	VERB
cana-2347	98	10	,	,	PUNCT
cana-2347	98	11	these	these	DET
cana-2347	98	12	preprocessing	preprocesse	VERB
cana-2347	98	13	stages	stage	NOUN
cana-2347	98	14	significantly	significantly	ADV
cana-2347	98	15	increase	increase	VERB
cana-2347	98	16	the	the	DET
cana-2347	98	17	deep	deep	ADJ
cana-2347	98	18	learning	learning	NOUN
cana-2347	98	19	model	model	NOUN
cana-2347	98	20	’s	’s	PART
cana-2347	98	21	resilience	resilience	NOUN
cana-2347	98	22	and	and	CCONJ
cana-2347	98	23	capacity	capacity	NOUN
cana-2347	98	24	for	for	ADP
cana-2347	98	25	generalization	generalization	NOUN
cana-2347	98	26	.	.	PUNCT
cana-2347	99	1	this	this	DET
cana-2347	99	2	work	work	NOUN
cana-2347	99	3	guarantees	guarantee	VERB
cana-2347	99	4	that	that	SCONJ
cana-2347	99	5	the	the	DET
cana-2347	99	6	models	model	NOUN
cana-2347	99	7	can	can	AUX
cana-2347	99	8	segment	segment	VERB
cana-2347	99	9	ovarian	ovarian	ADJ
cana-2347	99	10	tumours	tumour	NOUN
cana-2347	99	11	across	across	ADP
cana-2347	99	12	a	a	DET
cana-2347	99	13	range	range	NOUN
cana-2347	99	14	of	of	ADP
cana-2347	99	15	real	real	ADJ
cana-2347	99	16	-	-	PUNCT
cana-2347	99	17	world	world	NOUN
cana-2347	99	18	imaging	imaging	NOUN
cana-2347	99	19	scenarios	scenario	NOUN
cana-2347	99	20	by	by	ADP
cana-2347	99	21	meticulously	meticulously	ADV
cana-2347	99	22	preparing	prepare	VERB
cana-2347	99	23	the	the	DET
cana-2347	99	24	mmotu	mmotu	PROPN
cana-2347	99	25	data	data	PROPN
cana-2347	99	26	set	set	VERB
cana-2347	99	27	.	.	PUNCT
cana-2347	100	1	model	model	NOUN
cana-2347	100	2	architecture	architecture	NOUN
cana-2347	100	3	selection	selection	NOUN
cana-2347	100	4	the	the	DET
cana-2347	100	5	core	core	NOUN
cana-2347	100	6	of	of	ADP
cana-2347	100	7	the	the	DET
cana-2347	100	8	proposed	propose	VERB
cana-2347	100	9	methodology	methodology	NOUN
cana-2347	100	10	lies	lie	VERB
cana-2347	100	11	in	in	ADP
cana-2347	100	12	selecting	selecting	NOUN
cana-2347	100	13	and	and	CCONJ
cana-2347	100	14	evaluating	evaluate	VERB
cana-2347	100	15	different	different	ADJ
cana-2347	100	16	deep	deep	ADJ
cana-2347	100	17	learning	learning	NOUN
cana-2347	100	18	architectures	architecture	NOUN
cana-2347	100	19	to	to	PART
cana-2347	100	20	achieve	achieve	VERB
cana-2347	100	21	optimal	optimal	ADJ
cana-2347	100	22	performance	performance	NOUN
cana-2347	100	23	in	in	ADP
cana-2347	100	24	ovarian	ovarian	ADJ
cana-2347	100	25	disease	disease	NOUN
cana-2347	100	26	detection	detection	NOUN
cana-2347	100	27	:	:	PUNCT
cana-2347	100	28	•	•	NUM
cana-2347	100	29	baseline	baseline	PROPN
cana-2347	100	30	model	model	NOUN
cana-2347	100	31	(	(	PUNCT
cana-2347	100	32	u	u	NOUN
cana-2347	100	33	-	-	NOUN
cana-2347	100	34	net	net	ADJ
cana-2347	100	35	):	):	PUNCT
cana-2347	100	36	the	the	DET
cana-2347	100	37	u	u	ADJ
cana-2347	100	38	-	-	ADJ
cana-2347	100	39	net	net	ADJ
cana-2347	100	40	architecture	architecture	NOUN
cana-2347	100	41	is	be	AUX
cana-2347	100	42	employed	employ	VERB
cana-2347	100	43	as	as	ADP
cana-2347	100	44	the	the	DET
cana-2347	100	45	baseline	baseline	NOUN
cana-2347	100	46	model	model	NOUN
cana-2347	100	47	due	due	ADP
cana-2347	100	48	to	to	ADP
cana-2347	100	49	its	its	PRON
cana-2347	100	50	effectiveness	effectiveness	NOUN
cana-2347	100	51	in	in	ADP
cana-2347	100	52	medical	medical	ADJ
cana-2347	100	53	image	image	NOUN
cana-2347	100	54	segmentation	segmentation	NOUN
cana-2347	100	55	tasks	task	NOUN
cana-2347	100	56	.	.	PUNCT
cana-2347	101	1	it	it	PRON
cana-2347	101	2	serves	serve	VERB
cana-2347	101	3	as	as	ADP
cana-2347	101	4	a	a	DET
cana-2347	101	5	reference	reference	NOUN
cana-2347	101	6	point	point	NOUN
cana-2347	101	7	to	to	PART
cana-2347	101	8	measure	measure	VERB
cana-2347	101	9	the	the	DET
cana-2347	101	10	impact	impact	NOUN
cana-2347	101	11	of	of	ADP
cana-2347	101	12	more	more	ADV
cana-2347	101	13	advanced	advanced	ADJ
cana-2347	101	14	techniques	technique	NOUN
cana-2347	101	15	.	.	PUNCT
cana-2347	102	1	•	•	NUM
cana-2347	102	2	u	u	ADJ
cana-2347	102	3	-	-	ADJ
cana-2347	102	4	net	net	ADJ
cana-2347	102	5	variants	variant	NOUN
cana-2347	102	6	:	:	PUNCT
cana-2347	102	7	the	the	DET
cana-2347	102	8	methodology	methodology	NOUN
cana-2347	102	9	explores	explore	VERB
cana-2347	102	10	variants	variant	NOUN
cana-2347	102	11	of	of	ADP
cana-2347	102	12	u	u	NOUN
cana-2347	102	13	-	-	NOUN
cana-2347	102	14	net	net	ADJ
cana-2347	102	15	,	,	PUNCT
cana-2347	102	16	incorporating	incorporate	VERB
cana-2347	102	17	resnet	resnet	NOUN
cana-2347	102	18	and	and	CCONJ
cana-2347	102	19	densenet	densenet	NOUN
cana-2347	102	20	backbones	backbone	NOUN
cana-2347	102	21	.	.	PUNCT
cana-2347	103	1	these	these	DET
cana-2347	103	2	variants	variant	NOUN
cana-2347	103	3	are	be	AUX
cana-2347	103	4	selected	select	VERB
cana-2347	103	5	to	to	PART
cana-2347	103	6	assess	assess	VERB
cana-2347	103	7	whether	whether	SCONJ
cana-2347	103	8	deeper	deep	ADJ
cana-2347	103	9	,	,	PUNCT
cana-2347	103	10	more	more	ADV
cana-2347	103	11	complex	complex	ADJ
cana-2347	103	12	architectures	architecture	NOUN
cana-2347	103	13	can	can	AUX
cana-2347	103	14	capture	capture	VERB
cana-2347	103	15	more	more	ADV
cana-2347	103	16	intricate	intricate	ADJ
cana-2347	103	17	features	feature	NOUN
cana-2347	103	18	in	in	ADP
cana-2347	103	19	ovarian	ovarian	ADJ
cana-2347	103	20	scans	scan	NOUN
cana-2347	103	21	,	,	PUNCT
cana-2347	103	22	leading	lead	VERB
cana-2347	103	23	to	to	ADP
cana-2347	103	24	improved	improve	VERB
cana-2347	103	25	segmentation	segmentation	NOUN
cana-2347	103	26	accuracy	accuracy	NOUN
cana-2347	103	27	.	.	PUNCT
cana-2347	104	1	•	•	NUM
cana-2347	104	2	advanced	advanced	ADJ
cana-2347	104	3	models	model	NOUN
cana-2347	104	4	(	(	PUNCT
cana-2347	104	5	cr	cr	NOUN
cana-2347	104	6	-	-	PUNCT
cana-2347	104	7	unet	unet	NOUN
cana-2347	104	8	,	,	PUNCT
cana-2347	104	9	ocys	ocy	NOUN
cana-2347	104	10	-	-	PUNCT
cana-2347	104	11	net	net	NOUN
cana-2347	104	12	):	):	PUNCT
cana-2347	104	13	in	in	ADP
cana-2347	104	14	addition	addition	NOUN
cana-2347	104	15	to	to	ADP
cana-2347	104	16	u	u	ADJ
cana-2347	104	17	-	-	ADJ
cana-2347	104	18	net	net	ADJ
cana-2347	104	19	variants	variant	NOUN
cana-2347	104	20	,	,	PUNCT
cana-2347	104	21	the	the	DET
cana-2347	104	22	methodology	methodology	NOUN
cana-2347	104	23	includes	include	VERB
cana-2347	104	24	advanced	advanced	ADJ
cana-2347	104	25	models	model	NOUN
cana-2347	104	26	like	like	ADP
cana-2347	104	27	cr	cr	NOUN
cana-2347	104	28	-	-	PUNCT
cana-2347	104	29	unet	unet	NOUN
cana-2347	104	30	and	and	CCONJ
cana-2347	104	31	ocys	ocy	NOUN
cana-2347	104	32	-	-	PUNCT
cana-2347	104	33	net	net	NOUN
cana-2347	104	34	,	,	PUNCT
cana-2347	104	35	which	which	PRON
cana-2347	104	36	are	be	AUX
cana-2347	104	37	specifically	specifically	ADV
cana-2347	104	38	designed	design	VERB
cana-2347	104	39	for	for	ADP
cana-2347	104	40	medical	medical	ADJ
cana-2347	104	41	imaging	imaging	NOUN
cana-2347	104	42	.	.	PUNCT
cana-2347	105	1	these	these	DET
cana-2347	105	2	models	model	NOUN
cana-2347	105	3	are	be	AUX
cana-2347	105	4	evaluated	evaluate	VERB
cana-2347	105	5	based	base	VERB
cana-2347	105	6	on	on	ADP
cana-2347	105	7	their	their	PRON
cana-2347	105	8	ability	ability	NOUN
cana-2347	105	9	to	to	PART
cana-2347	105	10	handle	handle	VERB
cana-2347	105	11	the	the	DET
cana-2347	105	12	complexities	complexity	NOUN
cana-2347	105	13	of	of	ADP
cana-2347	105	14	ovarian	ovarian	ADJ
cana-2347	105	15	disease	disease	NOUN
cana-2347	105	16	detection	detection	NOUN
cana-2347	105	17	.	.	PUNCT
cana-2347	106	1	•	•	NOUN
cana-2347	106	2	transfer	transfer	NOUN
cana-2347	106	3	learning	learning	NOUN
cana-2347	106	4	:	:	PUNCT
cana-2347	106	5	to	to	PART
cana-2347	106	6	further	far	ADV
cana-2347	106	7	enhance	enhance	VERB
cana-2347	106	8	model	model	NOUN
cana-2347	106	9	performance	performance	NOUN
cana-2347	106	10	,	,	PUNCT
cana-2347	106	11	transfer	transfer	NOUN
cana-2347	106	12	learning	learning	NOUN
cana-2347	106	13	is	be	AUX
cana-2347	106	14	applied	apply	VERB
cana-2347	106	15	by	by	ADP
cana-2347	106	16	fine	fine	ADV
cana-2347	106	17	-	-	PUNCT
cana-2347	106	18	tuning	tune	VERB
cana-2347	106	19	pre	pre	ADJ
cana-2347	106	20	-	-	ADJ
cana-2347	106	21	trained	train	VERB
cana-2347	106	22	models	model	NOUN
cana-2347	106	23	on	on	ADP
cana-2347	106	24	the	the	DET
cana-2347	106	25	ovarian	ovarian	ADJ
cana-2347	106	26	dataset	dataset	NOUN
cana-2347	106	27	.	.	PUNCT
cana-2347	107	1	this	this	DET
cana-2347	107	2	approach	approach	NOUN
cana-2347	107	3	leverages	leverage	VERB
cana-2347	107	4	the	the	DET
cana-2347	107	5	knowledge	knowledge	NOUN
cana-2347	107	6	gained	gain	VERB
cana-2347	107	7	from	from	ADP
cana-2347	107	8	large	large	ADJ
cana-2347	107	9	-	-	PUNCT
cana-2347	107	10	scale	scale	NOUN
cana-2347	107	11	image	image	NOUN
cana-2347	107	12	datasets	dataset	NOUN
cana-2347	107	13	to	to	PART
cana-2347	107	14	improve	improve	VERB
cana-2347	107	15	detection	detection	NOUN
cana-2347	107	16	accuracy	accuracy	NOUN
cana-2347	107	17	.	.	PUNCT
cana-2347	108	1	training	training	NOUN
cana-2347	108	2	and	and	CCONJ
cana-2347	108	3	validation	validation	NOUN
cana-2347	108	4	processes	process	NOUN
cana-2347	108	5	each	each	DET
cana-2347	108	6	model	model	NOUN
cana-2347	108	7	is	be	AUX
cana-2347	108	8	subjected	subject	VERB
cana-2347	108	9	to	to	ADP
cana-2347	108	10	a	a	DET
cana-2347	108	11	thorough	thorough	ADJ
cana-2347	108	12	training	training	NOUN
cana-2347	108	13	process	process	NOUN
cana-2347	108	14	,	,	PUNCT
cana-2347	108	15	where	where	SCONJ
cana-2347	108	16	the	the	DET
cana-2347	108	17	dataset	dataset	NOUN
cana-2347	108	18	is	be	AUX
cana-2347	108	19	divided	divide	VERB
cana-2347	108	20	into	into	ADP
cana-2347	108	21	training	training	NOUN
cana-2347	108	22	and	and	CCONJ
cana-2347	108	23	validation	validation	NOUN
cana-2347	108	24	sets	set	NOUN
cana-2347	108	25	.	.	PUNCT
cana-2347	109	1	the	the	DET
cana-2347	109	2	training	training	NOUN
cana-2347	109	3	involves	involve	VERB
cana-2347	109	4	repeatedly	repeatedly	ADV
cana-2347	109	5	adjusting	adjust	VERB
cana-2347	109	6	the	the	DET
cana-2347	109	7	model	model	NOUN
cana-2347	109	8	’s	’s	PART
cana-2347	109	9	parameters	parameter	NOUN
cana-2347	109	10	to	to	PART
cana-2347	109	11	reduce	reduce	VERB
cana-2347	109	12	communications	communication	NOUN
cana-2347	109	13	on	on	ADP
cana-2347	109	14	applied	apply	VERB
cana-2347	109	15	nonlinear	nonlinear	ADJ
cana-2347	109	16	analysis	analysis	NOUN
cana-2347	109	17	issn	issn	NOUN
cana-2347	109	18	:	:	PUNCT
cana-2347	109	19	1074	1074	NUM
cana-2347	109	20	-	-	PUNCT
cana-2347	109	21	133x	133x	NUM
cana-2347	109	22	vol	vol	NOUN
cana-2347	109	23	32	32	NUM
cana-2347	109	24	no	no	NOUN
cana-2347	109	25	.	.	PUNCT
cana-2347	110	1	1s	1s	NUM
cana-2347	110	2	(	(	PUNCT
cana-2347	110	3	2025	2025	NUM
cana-2347	110	4	)	)	PUNCT
cana-2347	110	5	618	618	NUM
cana-2347	110	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	110	7	segmentation	segmentation	NOUN
cana-2347	110	8	errors	error	NOUN
cana-2347	110	9	.	.	PUNCT
cana-2347	111	1	methods	method	NOUN
cana-2347	111	2	like	like	ADP
cana-2347	111	3	early	early	ADJ
cana-2347	111	4	stopping	stop	VERB
cana-2347	111	5	and	and	CCONJ
cana-2347	111	6	learning	learn	VERB
cana-2347	111	7	rate	rate	NOUN
cana-2347	111	8	scheduling	scheduling	NOUN
cana-2347	111	9	are	be	AUX
cana-2347	111	10	applied	apply	VERB
cana-2347	111	11	during	during	ADP
cana-2347	111	12	training	training	NOUN
cana-2347	111	13	to	to	PART
cana-2347	111	14	avoid	avoid	VERB
cana-2347	111	15	overfitting	overfitte	VERB
cana-2347	111	16	and	and	CCONJ
cana-2347	111	17	ensure	ensure	VERB
cana-2347	111	18	steady	steady	ADJ
cana-2347	111	19	convergence	convergence	NOUN
cana-2347	111	20	.	.	PUNCT
cana-2347	112	1	concurrent	concurrent	ADJ
cana-2347	112	2	validation	validation	NOUN
cana-2347	112	3	is	be	AUX
cana-2347	112	4	carried	carry	VERB
cana-2347	112	5	out	out	ADP
cana-2347	112	6	to	to	PART
cana-2347	112	7	track	track	VERB
cana-2347	112	8	how	how	SCONJ
cana-2347	112	9	well	well	ADV
cana-2347	112	10	the	the	DET
cana-2347	112	11	model	model	NOUN
cana-2347	112	12	generalizes	generalize	VERB
cana-2347	112	13	to	to	ADP
cana-2347	112	14	new	new	ADJ
cana-2347	112	15	data	datum	NOUN
cana-2347	112	16	.	.	PUNCT
cana-2347	113	1	the	the	DET
cana-2347	113	2	validation	validation	NOUN
cana-2347	113	3	results	result	NOUN
cana-2347	113	4	guide	guide	VERB
cana-2347	113	5	hyperparameter	hyperparameter	NOUN
cana-2347	113	6	tuning	tuning	NOUN
cana-2347	113	7	and	and	CCONJ
cana-2347	113	8	model	model	NOUN
cana-2347	113	9	adjustments	adjustment	NOUN
cana-2347	113	10	,	,	PUNCT
cana-2347	113	11	ensuring	ensure	VERB
cana-2347	113	12	that	that	SCONJ
cana-2347	113	13	the	the	DET
cana-2347	113	14	final	final	ADJ
cana-2347	113	15	model	model	NOUN
cana-2347	113	16	is	be	AUX
cana-2347	113	17	well	well	ADV
cana-2347	113	18	-	-	PUNCT
cana-2347	113	19	optimized	optimize	VERB
cana-2347	113	20	for	for	ADP
cana-2347	113	21	the	the	DET
cana-2347	113	22	specific	specific	ADJ
cana-2347	113	23	task	task	NOUN
cana-2347	113	24	of	of	ADP
cana-2347	113	25	ovarian	ovarian	ADJ
cana-2347	113	26	disease	disease	NOUN
cana-2347	113	27	detection	detection	NOUN
cana-2347	113	28	.	.	PUNCT
cana-2347	114	1	performance	performance	NOUN
cana-2347	114	2	evaluation	evaluation	NOUN
cana-2347	114	3	performance	performance	NOUN
cana-2347	114	4	evaluation	evaluation	NOUN
cana-2347	114	5	is	be	AUX
cana-2347	114	6	a	a	DET
cana-2347	114	7	critical	critical	ADJ
cana-2347	114	8	component	component	NOUN
cana-2347	114	9	of	of	ADP
cana-2347	114	10	the	the	DET
cana-2347	114	11	proposed	propose	VERB
cana-2347	114	12	methodology	methodology	NOUN
cana-2347	114	13	.	.	PUNCT
cana-2347	115	1	each	each	DET
cana-2347	115	2	model	model	NOUN
cana-2347	115	3	is	be	AUX
cana-2347	115	4	assessed	assess	VERB
cana-2347	115	5	using	use	VERB
cana-2347	115	6	a	a	DET
cana-2347	115	7	combination	combination	NOUN
cana-2347	115	8	of	of	ADP
cana-2347	115	9	quantitative	quantitative	ADJ
cana-2347	115	10	and	and	CCONJ
cana-2347	115	11	qualitative	qualitative	ADJ
cana-2347	115	12	metrics	metric	NOUN
cana-2347	115	13	:	:	PUNCT
cana-2347	115	14	quantitative	quantitative	ADJ
cana-2347	115	15	evaluation	evaluation	NOUN
cana-2347	115	16	:	:	PUNCT
cana-2347	115	17	a	a	DET
cana-2347	115	18	numerical	numerical	ADJ
cana-2347	115	19	evaluation	evaluation	NOUN
cana-2347	115	20	of	of	ADP
cana-2347	115	21	the	the	DET
cana-2347	115	22	segmentation	segmentation	NOUN
cana-2347	115	23	accuracy	accuracy	NOUN
cana-2347	115	24	of	of	ADP
cana-2347	115	25	the	the	DET
cana-2347	115	26	model	model	NOUN
cana-2347	115	27	is	be	AUX
cana-2347	115	28	produced	produce	VERB
cana-2347	115	29	by	by	ADP
cana-2347	115	30	computing	compute	VERB
cana-2347	115	31	metrics	metric	NOUN
cana-2347	115	32	like	like	ADP
cana-2347	115	33	the	the	DET
cana-2347	115	34	f1	f1	PROPN
cana-2347	115	35	score	score	NOUN
cana-2347	115	36	,	,	PUNCT
cana-2347	115	37	precision	precision	NOUN
cana-2347	115	38	,	,	PUNCT
cana-2347	115	39	recall	recall	NOUN
cana-2347	115	40	,	,	PUNCT
cana-2347	115	41	intersection	intersection	NOUN
cana-2347	115	42	over	over	ADP
cana-2347	115	43	union	union	NOUN
cana-2347	115	44	(	(	PUNCT
cana-2347	115	45	iou	iou	NOUN
cana-2347	115	46	)	)	PUNCT
cana-2347	115	47	,	,	PUNCT
cana-2347	115	48	dice	dice	NOUN
cana-2347	115	49	coefficient	coefficient	NOUN
cana-2347	115	50	and	and	CCONJ
cana-2347	115	51	precision	precision	NOUN
cana-2347	115	52	.	.	PUNCT
cana-2347	116	1	these	these	DET
cana-2347	116	2	metrics	metric	NOUN
cana-2347	116	3	offer	offer	VERB
cana-2347	116	4	insight	insight	NOUN
cana-2347	116	5	into	into	ADP
cana-2347	116	6	how	how	SCONJ
cana-2347	116	7	well	well	ADV
cana-2347	116	8	the	the	DET
cana-2347	116	9	model	model	NOUN
cana-2347	116	10	distinguishes	distinguish	VERB
cana-2347	116	11	between	between	ADP
cana-2347	116	12	healthy	healthy	ADJ
cana-2347	116	13	and	and	CCONJ
cana-2347	116	14	diseased	diseased	ADJ
cana-2347	116	15	ovarian	ovarian	ADJ
cana-2347	116	16	tissue	tissue	NOUN
cana-2347	116	17	.	.	PUNCT
cana-2347	117	1	qualitative	qualitative	ADJ
cana-2347	117	2	evaluation	evaluation	NOUN
cana-2347	117	3	:	:	PUNCT
cana-2347	117	4	alongside	alongside	ADP
cana-2347	117	5	quantitative	quantitative	ADJ
cana-2347	117	6	metrics	metric	NOUN
cana-2347	117	7	,	,	PUNCT
cana-2347	117	8	visual	visual	ADJ
cana-2347	117	9	assessments	assessment	NOUN
cana-2347	117	10	of	of	ADP
cana-2347	117	11	the	the	DET
cana-2347	117	12	segmentation	segmentation	NOUN
cana-2347	117	13	outputs	output	NOUN
cana-2347	117	14	are	be	AUX
cana-2347	117	15	conducted	conduct	VERB
cana-2347	117	16	.	.	PUNCT
cana-2347	118	1	this	this	DET
cana-2347	118	2	qualitative	qualitative	ADJ
cana-2347	118	3	evaluation	evaluation	NOUN
cana-2347	118	4	helps	help	VERB
cana-2347	118	5	detect	detect	VERB
cana-2347	118	6	patterns	pattern	NOUN
cana-2347	118	7	or	or	CCONJ
cana-2347	118	8	anomalies	anomaly	NOUN
cana-2347	118	9	that	that	PRON
cana-2347	118	10	might	might	AUX
cana-2347	118	11	be	be	AUX
cana-2347	118	12	overlooked	overlook	VERB
cana-2347	118	13	by	by	ADP
cana-2347	118	14	numerical	numerical	ADJ
cana-2347	118	15	metrics	metric	NOUN
cana-2347	118	16	alone	alone	ADV
cana-2347	118	17	.	.	PUNCT
cana-2347	119	1	it	it	PRON
cana-2347	119	2	offers	offer	VERB
cana-2347	119	3	a	a	DET
cana-2347	119	4	more	more	ADV
cana-2347	119	5	complete	complete	ADJ
cana-2347	119	6	understanding	understanding	NOUN
cana-2347	119	7	of	of	ADP
cana-2347	119	8	the	the	DET
cana-2347	119	9	model	model	NOUN
cana-2347	119	10	’s	’s	PART
cana-2347	119	11	real	real	ADJ
cana-2347	119	12	-	-	PUNCT
cana-2347	119	13	world	world	NOUN
cana-2347	119	14	performance	performance	NOUN
cana-2347	119	15	and	and	CCONJ
cana-2347	119	16	effectiveness	effectiveness	NOUN
cana-2347	119	17	.	.	PUNCT
cana-2347	120	1	4	4	X
cana-2347	120	2	.	.	NOUN
cana-2347	120	3	results	result	NOUN
cana-2347	120	4	and	and	CCONJ
cana-2347	120	5	discussion	discussion	NOUN
cana-2347	120	6	in	in	ADP
cana-2347	120	7	this	this	DET
cana-2347	120	8	study	study	NOUN
cana-2347	120	9	,	,	PUNCT
cana-2347	120	10	we	we	PRON
cana-2347	120	11	evaluated	evaluate	VERB
cana-2347	120	12	several	several	ADJ
cana-2347	120	13	deep	deep	ADJ
cana-2347	120	14	learning	learning	NOUN
cana-2347	120	15	models	model	NOUN
cana-2347	120	16	,	,	PUNCT
cana-2347	120	17	starting	start	VERB
cana-2347	120	18	with	with	ADP
cana-2347	120	19	the	the	DET
cana-2347	120	20	baseline	baseline	ADJ
cana-2347	120	21	u	u	NOUN
cana-2347	120	22	-	-	NOUN
cana-2347	120	23	net	net	ADJ
cana-2347	120	24	and	and	CCONJ
cana-2347	120	25	moving	move	VERB
cana-2347	120	26	to	to	ADP
cana-2347	120	27	more	more	ADV
cana-2347	120	28	advanced	advanced	ADJ
cana-2347	120	29	architectures	architecture	NOUN
cana-2347	120	30	,	,	PUNCT
cana-2347	120	31	including	include	VERB
cana-2347	120	32	u	u	NOUN
cana-2347	120	33	-	-	ADJ
cana-2347	120	34	net	net	ADJ
cana-2347	120	35	variants	variant	NOUN
cana-2347	120	36	with	with	ADP
cana-2347	120	37	resnet	resnet	NOUN
cana-2347	120	38	and	and	CCONJ
cana-2347	120	39	densenet	densenet	NOUN
cana-2347	120	40	backbones	backbone	NOUN
cana-2347	120	41	,	,	PUNCT
cana-2347	120	42	crunet	crunet	NOUN
cana-2347	120	43	,	,	PUNCT
cana-2347	120	44	ocys	ocy	NOUN
cana-2347	120	45	-	-	PUNCT
cana-2347	120	46	net	net	NOUN
cana-2347	120	47	,	,	PUNCT
cana-2347	120	48	and	and	CCONJ
cana-2347	120	49	an	an	DET
cana-2347	120	50	ensemble	ensemble	ADJ
cana-2347	120	51	model	model	NOUN
cana-2347	120	52	.	.	PUNCT
cana-2347	121	1	additionally	additionally	ADV
cana-2347	121	2	,	,	PUNCT
cana-2347	121	3	transfer	transfer	NOUN
cana-2347	121	4	learning	learning	NOUN
cana-2347	121	5	was	be	AUX
cana-2347	121	6	incorporated	incorporate	VERB
cana-2347	121	7	by	by	ADP
cana-2347	121	8	finetuning	finetune	VERB
cana-2347	121	9	a	a	DET
cana-2347	121	10	pre	pre	ADJ
cana-2347	121	11	-	-	ADJ
cana-2347	121	12	trained	train	VERB
cana-2347	121	13	model	model	NOUN
cana-2347	121	14	to	to	PART
cana-2347	121	15	assess	assess	VERB
cana-2347	121	16	whether	whether	SCONJ
cana-2347	121	17	it	it	PRON
cana-2347	121	18	could	could	AUX
cana-2347	121	19	further	far	ADV
cana-2347	121	20	improve	improve	VERB
cana-2347	121	21	performance	performance	NOUN
cana-2347	121	22	.	.	PUNCT
cana-2347	122	1	the	the	DET
cana-2347	122	2	results	result	NOUN
cana-2347	122	3	were	be	AUX
cana-2347	122	4	measured	measure	VERB
cana-2347	122	5	using	use	VERB
cana-2347	122	6	the	the	DET
cana-2347	122	7	following	follow	VERB
cana-2347	122	8	metrics	metric	NOUN
cana-2347	122	9	:	:	PUNCT
cana-2347	122	10	dice	dice	NOUN
cana-2347	122	11	coefficient	coefficient	NOUN
cana-2347	122	12	,	,	PUNCT
cana-2347	122	13	intersection	intersection	NOUN
cana-2347	122	14	over	over	ADP
cana-2347	122	15	union	union	NOUN
cana-2347	122	16	(	(	PUNCT
cana-2347	122	17	iou	iou	NOUN
cana-2347	122	18	)	)	PUNCT
cana-2347	122	19	,	,	PUNCT
cana-2347	122	20	precision	precision	NOUN
cana-2347	122	21	,	,	PUNCT
cana-2347	122	22	recall	recall	NOUN
cana-2347	122	23	,	,	PUNCT
cana-2347	122	24	and	and	CCONJ
cana-2347	122	25	f1	f1	PROPN
cana-2347	122	26	score	score	NOUN
cana-2347	122	27	.	.	PUNCT
cana-2347	123	1	these	these	DET
cana-2347	123	2	metrics	metric	NOUN
cana-2347	123	3	provide	provide	VERB
cana-2347	123	4	a	a	DET
cana-2347	123	5	comprehensive	comprehensive	ADJ
cana-2347	123	6	assessment	assessment	NOUN
cana-2347	123	7	of	of	ADP
cana-2347	123	8	the	the	DET
cana-2347	123	9	models	model	NOUN
cana-2347	123	10	'	'	PART
cana-2347	123	11	segmentation	segmentation	NOUN
cana-2347	123	12	accuracy	accuracy	NOUN
cana-2347	123	13	on	on	ADP
cana-2347	123	14	the	the	DET
cana-2347	123	15	mmotu	mmotu	PROPN
cana-2347	123	16	dataset	dataset	NOUN
cana-2347	123	17	,	,	PUNCT
cana-2347	123	18	specifically	specifically	ADV
cana-2347	123	19	on	on	ADP
cana-2347	123	20	the	the	DET
cana-2347	123	21	otu	otu	PROPN
cana-2347	123	22	2d	2d	PROPN
cana-2347	123	23	and	and	CCONJ
cana-2347	123	24	otu	otu	PROPN
cana-2347	123	25	ceus	ceus	PROPN
cana-2347	123	26	subsets	subset	NOUN
cana-2347	123	27	.	.	PUNCT
cana-2347	124	1	communications	communication	NOUN
cana-2347	124	2	on	on	ADP
cana-2347	124	3	applied	apply	VERB
cana-2347	124	4	nonlinear	nonlinear	ADJ
cana-2347	124	5	analysis	analysis	NOUN
cana-2347	124	6	issn	issn	NOUN
cana-2347	124	7	:	:	PUNCT
cana-2347	124	8	1074	1074	NUM
cana-2347	124	9	-	-	PUNCT
cana-2347	124	10	133x	133x	NUM
cana-2347	124	11	vol	vol	NOUN
cana-2347	124	12	32	32	NUM
cana-2347	124	13	no	no	NOUN
cana-2347	124	14	.	.	PUNCT
cana-2347	125	1	1s	1s	NUM
cana-2347	125	2	(	(	PUNCT
cana-2347	125	3	2025	2025	NUM
cana-2347	125	4	)	)	PUNCT
cana-2347	125	5	619	619	NUM
cana-2347	125	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	125	7	discussions	discussion	NOUN
cana-2347	125	8	baseline	baseline	PROPN
cana-2347	125	9	model	model	NOUN
cana-2347	125	10	(	(	PUNCT
cana-2347	125	11	u	u	NOUN
cana-2347	125	12	-	-	NOUN
cana-2347	125	13	net	net	NOUN
cana-2347	125	14	)	)	PUNCT
cana-2347	125	15	the	the	DET
cana-2347	125	16	baseline	baseline	ADJ
cana-2347	125	17	u	u	ADJ
cana-2347	125	18	-	-	ADJ
cana-2347	125	19	net	net	ADJ
cana-2347	125	20	model	model	NOUN
cana-2347	125	21	provided	provide	VERB
cana-2347	125	22	a	a	DET
cana-2347	125	23	strong	strong	ADJ
cana-2347	125	24	starting	starting	NOUN
cana-2347	125	25	point	point	NOUN
cana-2347	125	26	for	for	ADP
cana-2347	125	27	ovarian	ovarian	ADJ
cana-2347	125	28	tumor	tumor	NOUN
cana-2347	125	29	segmentation	segmentation	NOUN
cana-2347	125	30	,	,	PUNCT
cana-2347	125	31	achieving	achieve	VERB
cana-2347	125	32	a	a	DET
cana-2347	125	33	dice	dice	NOUN
cana-2347	125	34	coefficient	coefficient	NOUN
cana-2347	125	35	of	of	ADP
cana-2347	125	36	0.85	0.85	NUM
cana-2347	125	37	on	on	ADP
cana-2347	125	38	the	the	DET
cana-2347	125	39	otu	otu	PROPN
cana-2347	125	40	2d	2d	PROPN
cana-2347	125	41	subset	subset	VERB
cana-2347	125	42	and	and	CCONJ
cana-2347	125	43	0.82	0.82	NUM
cana-2347	125	44	on	on	ADP
cana-2347	125	45	the	the	DET
cana-2347	125	46	otu	otu	PROPN
cana-2347	125	47	ceus	ceus	PROPN
cana-2347	125	48	subset	subset	VERB
cana-2347	125	49	.	.	PUNCT
cana-2347	126	1	these	these	DET
cana-2347	126	2	results	result	NOUN
cana-2347	126	3	confirm	confirm	VERB
cana-2347	126	4	the	the	DET
cana-2347	126	5	effectiveness	effectiveness	NOUN
cana-2347	126	6	of	of	ADP
cana-2347	126	7	u	u	NOUN
cana-2347	126	8	-	-	NOUN
cana-2347	126	9	net	net	ADJ
cana-2347	126	10	in	in	ADP
cana-2347	126	11	medical	medical	ADJ
cana-2347	126	12	image	image	NOUN
cana-2347	126	13	segmentation	segmentation	NOUN
cana-2347	126	14	,	,	PUNCT
cana-2347	126	15	particularly	particularly	ADV
cana-2347	126	16	in	in	ADP
cana-2347	126	17	handling	handle	VERB
cana-2347	126	18	standard	standard	ADJ
cana-2347	126	19	ultrasound	ultrasound	NOUN
cana-2347	126	20	images	image	NOUN
cana-2347	126	21	.	.	PUNCT
cana-2347	127	1	impact	impact	NOUN
cana-2347	127	2	of	of	ADP
cana-2347	127	3	u	u	ADJ
cana-2347	127	4	-	-	ADJ
cana-2347	127	5	net	net	ADJ
cana-2347	127	6	variants	variant	NOUN
cana-2347	127	7	replacing	replace	VERB
cana-2347	127	8	the	the	DET
cana-2347	127	9	standard	standard	ADJ
cana-2347	127	10	u	u	ADJ
cana-2347	127	11	-	-	ADJ
cana-2347	127	12	net	net	ADJ
cana-2347	127	13	backbone	backbone	NOUN
cana-2347	127	14	with	with	ADP
cana-2347	127	15	resnet	resnet	NOUN
cana-2347	127	16	and	and	CCONJ
cana-2347	127	17	densenet	densenet	NOUN
cana-2347	127	18	resulted	result	VERB
cana-2347	127	19	in	in	ADP
cana-2347	127	20	noticeable	noticeable	ADJ
cana-2347	127	21	performance	performance	NOUN
cana-2347	127	22	improvements	improvement	NOUN
cana-2347	127	23	.	.	PUNCT
cana-2347	128	1	the	the	DET
cana-2347	128	2	densenet	densenet	NOUN
cana-2347	128	3	variant	variant	NOUN
cana-2347	128	4	outperformed	outperform	VERB
cana-2347	128	5	the	the	DET
cana-2347	128	6	resnet	resnet	ADJ
cana-2347	128	7	variant	variant	NOUN
cana-2347	128	8	on	on	ADP
cana-2347	128	9	both	both	DET
cana-2347	128	10	subsets	subset	NOUN
cana-2347	128	11	,	,	PUNCT
cana-2347	128	12	suggesting	suggest	VERB
cana-2347	128	13	that	that	SCONJ
cana-2347	128	14	its	its	PRON
cana-2347	128	15	densely	densely	ADV
cana-2347	128	16	connected	connected	ADJ
cana-2347	128	17	layers	layer	NOUN
cana-2347	128	18	are	be	AUX
cana-2347	128	19	more	more	ADV
cana-2347	128	20	effective	effective	ADJ
cana-2347	128	21	in	in	ADP
cana-2347	128	22	capturing	capture	VERB
cana-2347	128	23	complex	complex	ADJ
cana-2347	128	24	features	feature	NOUN
cana-2347	128	25	from	from	ADP
cana-2347	128	26	ultrasound	ultrasound	NOUN
cana-2347	128	27	images	image	NOUN
cana-2347	128	28	.	.	PUNCT
cana-2347	129	1	advanced	advanced	ADJ
cana-2347	129	2	models	model	NOUN
cana-2347	129	3	(	(	PUNCT
cana-2347	129	4	cr	cr	NOUN
cana-2347	129	5	-	-	PUNCT
cana-2347	129	6	unet	unet	NOUN
cana-2347	129	7	,	,	PUNCT
cana-2347	129	8	ocys	ocy	NOUN
cana-2347	129	9	-	-	PUNCT
cana-2347	129	10	net	net	NOUN
cana-2347	129	11	)	)	PUNCT
cana-2347	129	12	both	both	PRON
cana-2347	129	13	cr	cr	PROPN
cana-2347	129	14	-	-	PUNCT
cana-2347	129	15	unet	unet	NOUN
cana-2347	129	16	and	and	CCONJ
cana-2347	129	17	ocys	ocy	NOUN
cana-2347	129	18	-	-	PUNCT
cana-2347	129	19	net	net	NOUN
cana-2347	129	20	further	further	ADJ
cana-2347	129	21	improved	improve	VERB
cana-2347	129	22	performance	performance	NOUN
cana-2347	129	23	over	over	ADP
cana-2347	129	24	the	the	DET
cana-2347	129	25	u	u	ADJ
cana-2347	129	26	-	-	ADJ
cana-2347	129	27	net	net	ADJ
cana-2347	129	28	variants	variant	NOUN
cana-2347	129	29	,	,	PUNCT
cana-2347	129	30	with	with	ADP
cana-2347	129	31	cr	cr	NOUN
cana-2347	129	32	-	-	PUNCT
cana-2347	129	33	unet	unet	NOUN
cana-2347	129	34	slightly	slightly	ADV
cana-2347	129	35	outperforming	outperform	VERB
cana-2347	129	36	ocys	ocys	ADJ
cana-2347	129	37	-	-	PUNCT
cana-2347	129	38	net	net	NOUN
cana-2347	129	39	.	.	PUNCT
cana-2347	130	1	the	the	DET
cana-2347	130	2	higher	high	ADJ
cana-2347	130	3	dice	dice	NOUN
cana-2347	130	4	coefficient	coefficient	NOUN
cana-2347	130	5	and	and	CCONJ
cana-2347	130	6	iou	iou	PROPN
cana-2347	130	7	scores	score	NOUN
cana-2347	130	8	indicate	indicate	VERB
cana-2347	130	9	that	that	SCONJ
cana-2347	130	10	cr	cr	PROPN
cana-2347	130	11	-	-	PUNCT
cana-2347	130	12	unet	unet	NOUN
cana-2347	130	13	's	's	PART
cana-2347	130	14	architecture	architecture	NOUN
cana-2347	130	15	is	be	AUX
cana-2347	130	16	better	well	ADV
cana-2347	130	17	suited	suited	ADJ
cana-2347	130	18	for	for	ADP
cana-2347	130	19	the	the	DET
cana-2347	130	20	segmentation	segmentation	NOUN
cana-2347	130	21	tasks	task	NOUN
cana-2347	130	22	on	on	ADP
cana-2347	130	23	the	the	DET
cana-2347	130	24	mmotu	mmotu	PROPN
cana-2347	130	25	dataset	dataset	PROPN
cana-2347	130	26	.	.	PUNCT
cana-2347	131	1	ensemble	ensemble	ADJ
cana-2347	131	2	learning	learn	VERB
cana-2347	131	3	the	the	DET
cana-2347	131	4	ensemble	ensemble	ADJ
cana-2347	131	5	model	model	NOUN
cana-2347	131	6	,	,	PUNCT
cana-2347	131	7	combining	combine	VERB
cana-2347	131	8	cr	cr	NOUN
cana-2347	131	9	-	-	PUNCT
cana-2347	131	10	unet	unet	NOUN
cana-2347	131	11	and	and	CCONJ
cana-2347	131	12	the	the	DET
cana-2347	131	13	best	well	ADV
cana-2347	131	14	-	-	PUNCT
cana-2347	131	15	performing	perform	VERB
cana-2347	131	16	u	u	ADJ
cana-2347	131	17	-	-	ADJ
cana-2347	131	18	net	net	ADJ
cana-2347	131	19	variant	variant	NOUN
cana-2347	131	20	(	(	PUNCT
cana-2347	131	21	densenet	densenet	NOUN
cana-2347	131	22	)	)	PUNCT
cana-2347	131	23	,	,	PUNCT
cana-2347	131	24	achieved	achieve	VERB
cana-2347	131	25	the	the	DET
cana-2347	131	26	highest	high	ADJ
cana-2347	131	27	performance	performance	NOUN
cana-2347	131	28	metrics	metric	NOUN
cana-2347	131	29	on	on	ADP
cana-2347	131	30	both	both	DET
cana-2347	131	31	subsets	subset	NOUN
cana-2347	131	32	.	.	PUNCT
cana-2347	132	1	this	this	PRON
cana-2347	132	2	suggests	suggest	VERB
cana-2347	132	3	that	that	SCONJ
cana-2347	132	4	ensemble	ensemble	ADJ
cana-2347	132	5	learning	learning	NOUN
cana-2347	132	6	can	can	AUX
cana-2347	132	7	effectively	effectively	ADV
cana-2347	132	8	leverage	leverage	VERB
cana-2347	132	9	the	the	DET
cana-2347	132	10	strengths	strength	NOUN
cana-2347	132	11	of	of	ADP
cana-2347	132	12	multiple	multiple	ADJ
cana-2347	132	13	models	model	NOUN
cana-2347	132	14	to	to	PART
cana-2347	132	15	enhance	enhance	VERB
cana-2347	132	16	segmentation	segmentation	NOUN
cana-2347	132	17	accuracy	accuracy	NOUN
cana-2347	132	18	.	.	PUNCT
cana-2347	133	1	transfer	transfer	NOUN
cana-2347	133	2	learning	learn	VERB
cana-2347	133	3	the	the	DET
cana-2347	133	4	transfer	transfer	NOUN
cana-2347	133	5	learning	learning	NOUN
cana-2347	133	6	approach	approach	NOUN
cana-2347	133	7	,	,	PUNCT
cana-2347	133	8	involving	involve	VERB
cana-2347	133	9	fine	fine	ADV
cana-2347	133	10	-	-	PUNCT
cana-2347	133	11	tuning	tune	VERB
cana-2347	133	12	a	a	DET
cana-2347	133	13	pre	pre	ADJ
cana-2347	133	14	-	-	ADJ
cana-2347	133	15	trained	train	VERB
cana-2347	133	16	model	model	NOUN
cana-2347	133	17	,	,	PUNCT
cana-2347	133	18	provided	provide	VERB
cana-2347	133	19	the	the	DET
cana-2347	133	20	best	good	ADJ
cana-2347	133	21	overall	overall	ADJ
cana-2347	133	22	results	result	NOUN
cana-2347	133	23	,	,	PUNCT
cana-2347	133	24	particularly	particularly	ADV
cana-2347	133	25	on	on	ADP
cana-2347	133	26	the	the	DET
cana-2347	133	27	otu	otu	PROPN
cana-2347	133	28	ceus	ceus	PROPN
cana-2347	133	29	subset	subset	VERB
cana-2347	133	30	.	.	PUNCT
cana-2347	134	1	the	the	DET
cana-2347	134	2	fine	fine	ADV
cana-2347	134	3	-	-	PUNCT
cana-2347	134	4	tuned	tune	VERB
cana-2347	134	5	model	model	NOUN
cana-2347	134	6	's	's	PART
cana-2347	134	7	superior	superior	ADJ
cana-2347	134	8	performance	performance	NOUN
cana-2347	134	9	(	(	PUNCT
cana-2347	134	10	dice	dice	NOUN
cana-2347	134	11	coefficient	coefficient	NOUN
cana-2347	134	12	of	of	ADP
cana-2347	134	13	0.92	0.92	NUM
cana-2347	134	14	on	on	ADP
cana-2347	134	15	otu	otu	PROPN
cana-2347	134	16	2d	2d	PROPN
cana-2347	134	17	and	and	CCONJ
cana-2347	134	18	0.90	0.90	NUM
cana-2347	134	19	on	on	ADP
cana-2347	134	20	otu	otu	PROPN
cana-2347	134	21	ceus	ceus	PROPN
cana-2347	134	22	)	)	PUNCT
cana-2347	134	23	demonstrates	demonstrate	VERB
cana-2347	134	24	the	the	DET
cana-2347	134	25	value	value	NOUN
cana-2347	134	26	of	of	ADP
cana-2347	134	27	using	use	VERB
cana-2347	134	28	pre	pre	ADJ
cana-2347	134	29	-	-	ADJ
cana-2347	134	30	trained	train	VERB
cana-2347	134	31	networks	network	NOUN
cana-2347	134	32	for	for	ADP
cana-2347	134	33	medical	medical	ADJ
cana-2347	134	34	image	image	NOUN
cana-2347	134	35	segmentation	segmentation	NOUN
cana-2347	134	36	,	,	PUNCT
cana-2347	134	37	especially	especially	ADV
cana-2347	134	38	when	when	SCONJ
cana-2347	134	39	dealing	deal	VERB
cana-2347	134	40	with	with	ADP
cana-2347	134	41	limited	limited	ADJ
cana-2347	134	42	and	and	CCONJ
cana-2347	134	43	specialized	specialized	ADJ
cana-2347	134	44	datasets	dataset	NOUN
cana-2347	134	45	like	like	ADP
cana-2347	134	46	mmotu	mmotu	NOUN
cana-2347	134	47	.	.	PUNCT
cana-2347	135	1	5	5	NUM
cana-2347	135	2	.	.	X
cana-2347	135	3	conclusion	conclusion	NOUN
cana-2347	135	4	the	the	DET
cana-2347	135	5	results	result	NOUN
cana-2347	135	6	from	from	ADP
cana-2347	135	7	this	this	DET
cana-2347	135	8	study	study	NOUN
cana-2347	135	9	suggest	suggest	VERB
cana-2347	135	10	that	that	SCONJ
cana-2347	135	11	while	while	SCONJ
cana-2347	135	12	the	the	DET
cana-2347	135	13	baseline	baseline	ADJ
cana-2347	135	14	u	u	NOUN
cana-2347	135	15	-	-	NOUN
cana-2347	135	16	net	net	NOUN
cana-2347	135	17	provides	provide	VERB
cana-2347	135	18	a	a	DET
cana-2347	135	19	solid	solid	ADJ
cana-2347	135	20	foundation	foundation	NOUN
cana-2347	135	21	,	,	PUNCT
cana-2347	135	22	more	more	ADV
cana-2347	135	23	advanced	advanced	ADJ
cana-2347	135	24	models	model	NOUN
cana-2347	135	25	such	such	ADJ
cana-2347	135	26	as	as	ADP
cana-2347	135	27	cr	cr	NOUN
cana-2347	135	28	-	-	PUNCT
cana-2347	135	29	unet	unet	NOUN
cana-2347	135	30	and	and	CCONJ
cana-2347	135	31	transfer	transfer	VERB
cana-2347	135	32	learning	learning	NOUN
cana-2347	135	33	approaches	approach	NOUN
cana-2347	135	34	significantly	significantly	ADV
cana-2347	135	35	enhance	enhance	VERB
cana-2347	135	36	segmentation	segmentation	NOUN
cana-2347	135	37	accuracy	accuracy	NOUN
cana-2347	135	38	.	.	PUNCT
cana-2347	136	1	the	the	DET
cana-2347	136	2	ensemble	ensemble	ADJ
cana-2347	136	3	model	model	NOUN
cana-2347	136	4	and	and	CCONJ
cana-2347	136	5	fine	fine	ADV
cana-2347	136	6	-	-	PUNCT
cana-2347	136	7	tuned	tune	VERB
cana-2347	136	8	pre	pre	ADJ
cana-2347	136	9	-	-	ADJ
cana-2347	136	10	trained	train	VERB
cana-2347	136	11	models	model	NOUN
cana-2347	136	12	are	be	AUX
cana-2347	136	13	particularly	particularly	ADV
cana-2347	136	14	effective	effective	ADJ
cana-2347	136	15	,	,	PUNCT
cana-2347	136	16	offering	offer	VERB
cana-2347	136	17	the	the	DET
cana-2347	136	18	highest	high	ADJ
cana-2347	136	19	performance	performance	NOUN
cana-2347	136	20	across	across	ADP
cana-2347	136	21	both	both	DET
cana-2347	136	22	subsets	subset	NOUN
cana-2347	136	23	of	of	ADP
cana-2347	136	24	the	the	DET
cana-2347	136	25	mmotu	mmotu	PROPN
cana-2347	136	26	dataset	dataset	NOUN
cana-2347	136	27	.	.	PUNCT
cana-2347	137	1	these	these	DET
cana-2347	137	2	findings	finding	NOUN
cana-2347	137	3	indicate	indicate	VERB
cana-2347	137	4	that	that	SCONJ
cana-2347	137	5	leveraging	leverage	VERB
cana-2347	137	6	multiple	multiple	ADJ
cana-2347	137	7	deep	deep	ADJ
cana-2347	137	8	learning	learning	NOUN
cana-2347	137	9	strategies	strategy	NOUN
cana-2347	137	10	can	can	AUX
cana-2347	137	11	lead	lead	VERB
cana-2347	137	12	to	to	ADP
cana-2347	137	13	more	more	ADV
cana-2347	137	14	precise	precise	ADJ
cana-2347	137	15	and	and	CCONJ
cana-2347	137	16	reliable	reliable	ADJ
cana-2347	137	17	ovarian	ovarian	ADJ
cana-2347	137	18	disease	disease	NOUN
cana-2347	137	19	detection	detection	NOUN
cana-2347	137	20	,	,	PUNCT
cana-2347	137	21	ultimately	ultimately	ADV
cana-2347	137	22	contributing	contribute	VERB
cana-2347	137	23	to	to	ADP
cana-2347	137	24	better	well	ADJ
cana-2347	137	25	clinical	clinical	ADJ
cana-2347	137	26	outcomes	outcome	NOUN
cana-2347	137	27	.	.	PUNCT
cana-2347	138	1	references	reference	NOUN
cana-2347	138	2	[	[	X
cana-2347	138	3	1	1	NUM
cana-2347	138	4	]	]	SYM
cana-2347	138	5	li	li	X
cana-2347	138	6	,	,	PUNCT
cana-2347	138	7	haoming	haoming	NOUN
cana-2347	138	8	,	,	PUNCT
cana-2347	138	9	et	et	PROPN
cana-2347	138	10	al	al	PROPN
cana-2347	138	11	.	.	PUNCT
cana-2347	139	1	"	"	PUNCT
cana-2347	139	2	cr	cr	X
cana-2347	139	3	-	-	PUNCT
cana-2347	139	4	unet	unet	NOUN
cana-2347	139	5	:	:	PUNCT
cana-2347	139	6	a	a	DET
cana-2347	139	7	composite	composite	ADJ
cana-2347	139	8	network	network	NOUN
cana-2347	139	9	for	for	ADP
cana-2347	139	10	ovary	ovary	ADJ
cana-2347	139	11	and	and	CCONJ
cana-2347	139	12	follicle	follicle	VERB
cana-2347	139	13	segmentation	segmentation	NOUN
cana-2347	139	14	in	in	ADP
cana-2347	139	15	ultrasound	ultrasound	NOUN
cana-2347	139	16	images	image	NOUN
cana-2347	139	17	.	.	PUNCT
cana-2347	139	18	"	"	PUNCT
cana-2347	139	19	ieee	ieee	PROPN
cana-2347	139	20	journal	journal	PROPN
cana-2347	139	21	of	of	ADP
cana-2347	139	22	biomedical	biomedical	ADJ
cana-2347	139	23	and	and	CCONJ
cana-2347	139	24	health	health	NOUN
cana-2347	139	25	informatics	informatic	NOUN
cana-2347	139	26	24.4	24.4	NUM
cana-2347	139	27	(	(	PUNCT
cana-2347	139	28	2019	2019	NUM
cana-2347	139	29	):	):	PUNCT
cana-2347	139	30	974	974	NUM
cana-2347	139	31	-	-	SYM
cana-2347	139	32	983	983	NUM
cana-2347	139	33	.	.	PUNCT
cana-2347	140	1	[	[	X
cana-2347	140	2	2	2	NUM
cana-2347	140	3	]	]	X
cana-2347	140	4	srivastava	srivastava	PROPN
cana-2347	140	5	,	,	PUNCT
cana-2347	140	6	sakshi	sakshi	PROPN
cana-2347	140	7	,	,	PUNCT
cana-2347	140	8	et	et	PROPN
cana-2347	140	9	al	al	PROPN
cana-2347	140	10	.	.	PUNCT
cana-2347	140	11	"	"	PUNCT
cana-2347	140	12	detection	detection	NOUN
cana-2347	140	13	of	of	ADP
cana-2347	140	14	ovarian	ovarian	ADJ
cana-2347	140	15	cyst	cyst	NOUN
cana-2347	140	16	in	in	ADP
cana-2347	140	17	ultrasound	ultrasound	NOUN
cana-2347	140	18	images	image	NOUN
cana-2347	140	19	using	use	VERB
cana-2347	140	20	fine	fine	ADV
cana-2347	140	21	-	-	PUNCT
cana-2347	140	22	tuned	tune	VERB
cana-2347	140	23	vgg-16	vgg-16	NOUN
cana-2347	140	24	deep	deep	ADJ
cana-2347	140	25	learning	learning	NOUN
cana-2347	140	26	network	network	NOUN
cana-2347	140	27	.	.	PUNCT
cana-2347	140	28	"	"	PUNCT
cana-2347	141	1	sn	sn	PROPN
cana-2347	141	2	computer	computer	NOUN
cana-2347	141	3	science	science	NOUN
cana-2347	141	4	1	1	NUM
cana-2347	141	5	(	(	PUNCT
cana-2347	141	6	2020	2020	NUM
cana-2347	141	7	):	):	PUNCT
cana-2347	141	8	1	1	NUM
cana-2347	141	9	-	-	SYM
cana-2347	141	10	8	8	NUM
cana-2347	141	11	.	.	PUNCT
cana-2347	141	12	communications	communication	NOUN
cana-2347	141	13	on	on	ADP
cana-2347	141	14	applied	apply	VERB
cana-2347	141	15	nonlinear	nonlinear	ADJ
cana-2347	141	16	analysis	analysis	NOUN
cana-2347	141	17	issn	issn	NOUN
cana-2347	141	18	:	:	PUNCT
cana-2347	141	19	1074	1074	NUM
cana-2347	141	20	-	-	PUNCT
cana-2347	141	21	133x	133x	NUM
cana-2347	141	22	vol	vol	NOUN
cana-2347	141	23	32	32	NUM
cana-2347	141	24	no	no	NOUN
cana-2347	141	25	.	.	PUNCT
cana-2347	142	1	1s	1s	NUM
cana-2347	142	2	(	(	PUNCT
cana-2347	142	3	2025	2025	NUM
cana-2347	142	4	)	)	PUNCT
cana-2347	142	5	620	620	NUM
cana-2347	142	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	143	1	[	[	X
cana-2347	143	2	3	3	NUM
cana-2347	143	3	]	]	PUNCT
cana-2347	143	4	akazawa	akazawa	NOUN
cana-2347	143	5	,	,	PUNCT
cana-2347	143	6	munetoshi	munetoshi	NOUN
cana-2347	143	7	,	,	PUNCT
cana-2347	143	8	and	and	CCONJ
cana-2347	143	9	kazunori	kazunori	PROPN
cana-2347	143	10	hashimoto	hashimoto	NOUN
cana-2347	143	11	.	.	PUNCT
cana-2347	144	1	"	"	PUNCT
cana-2347	144	2	artificial	artificial	ADJ
cana-2347	144	3	intelligence	intelligence	NOUN
cana-2347	144	4	in	in	ADP
cana-2347	144	5	ovarian	ovarian	ADJ
cana-2347	144	6	cancer	cancer	NOUN
cana-2347	144	7	diagnosis	diagnosis	NOUN
cana-2347	144	8	.	.	PUNCT
cana-2347	144	9	"	"	PUNCT
cana-2347	145	1	anticancer	anticancer	NOUN
cana-2347	145	2	research	research	NOUN
cana-2347	145	3	40.8	40.8	NUM
cana-2347	145	4	(	(	PUNCT
cana-2347	145	5	2020	2020	NUM
cana-2347	145	6	):	):	PUNCT
cana-2347	145	7	4795	4795	NUM
cana-2347	145	8	-	-	SYM
cana-2347	145	9	4800	4800	NUM
cana-2347	145	10	.	.	PUNCT
cana-2347	146	1	[	[	X
cana-2347	146	2	4	4	NUM
cana-2347	146	3	]	]	X
cana-2347	146	4	suha	suha	NOUN
cana-2347	146	5	,	,	PUNCT
cana-2347	146	6	sayma	sayma	PROPN
cana-2347	146	7	alam	alam	PROPN
cana-2347	146	8	,	,	PUNCT
cana-2347	146	9	and	and	CCONJ
cana-2347	146	10	muhammad	muhammad	PROPN
cana-2347	146	11	nazrul	nazrul	PROPN
cana-2347	146	12	islam	islam	PROPN
cana-2347	146	13	.	.	PUNCT
cana-2347	147	1	"	"	PUNCT
cana-2347	147	2	an	an	DET
cana-2347	147	3	extended	extended	ADJ
cana-2347	147	4	machine	machine	NOUN
cana-2347	147	5	learning	learning	NOUN
cana-2347	147	6	technique	technique	NOUN
cana-2347	147	7	for	for	ADP
cana-2347	147	8	polycystic	polycystic	ADJ
cana-2347	147	9	ovary	ovary	ADJ
cana-2347	147	10	syndrome	syndrome	NOUN
cana-2347	147	11	detection	detection	NOUN
cana-2347	147	12	using	use	VERB
cana-2347	147	13	ovary	ovary	ADJ
cana-2347	147	14	ultrasound	ultrasound	ADJ
cana-2347	147	15	image	image	NOUN
cana-2347	147	16	.	.	PUNCT
cana-2347	147	17	"	"	PUNCT
cana-2347	148	1	scientific	scientific	ADJ
cana-2347	148	2	reports	report	NOUN
cana-2347	148	3	12.1	12.1	NUM
cana-2347	148	4	(	(	PUNCT
cana-2347	148	5	2022	2022	NUM
cana-2347	148	6	):	):	PUNCT
cana-2347	148	7	17123	17123	NUM
cana-2347	148	8	.	.	PUNCT
cana-2347	149	1	[	[	X
cana-2347	149	2	5	5	NUM
cana-2347	149	3	]	]	SYM
cana-2347	149	4	fan	fan	PROPN
cana-2347	149	5	,	,	PUNCT
cana-2347	149	6	junfang	junfang	PROPN
cana-2347	149	7	,	,	PUNCT
cana-2347	149	8	et	et	PROPN
cana-2347	149	9	al	al	PROPN
cana-2347	149	10	.	.	PUNCT
cana-2347	150	1	"	"	PUNCT
cana-2347	150	2	accurate	accurate	ADJ
cana-2347	150	3	ovarian	ovarian	ADJ
cana-2347	150	4	cyst	cyst	NOUN
cana-2347	150	5	classification	classification	NOUN
cana-2347	150	6	with	with	ADP
cana-2347	150	7	a	a	DET
cana-2347	150	8	lightweight	lightweight	ADJ
cana-2347	150	9	deep	deep	ADJ
cana-2347	150	10	learning	learning	NOUN
cana-2347	150	11	model	model	NOUN
cana-2347	150	12	for	for	ADP
cana-2347	150	13	ultrasound	ultrasound	NOUN
cana-2347	150	14	images	image	NOUN
cana-2347	150	15	.	.	PUNCT
cana-2347	150	16	"	"	PUNCT
cana-2347	150	17	ieee	ieee	NOUN
cana-2347	150	18	access	access	NOUN
cana-2347	150	19	(	(	PUNCT
cana-2347	150	20	2023	2023	NUM
cana-2347	150	21	)	)	PUNCT
cana-2347	150	22	.	.	PUNCT
cana-2347	151	1	[	[	X
cana-2347	151	2	6	6	NUM
cana-2347	151	3	]	]	X
cana-2347	151	4	martínez	martínez	NOUN
cana-2347	151	5	-	-	PUNCT
cana-2347	151	6	más	más	PROPN
cana-2347	151	7	,	,	PUNCT
cana-2347	151	8	josé	josé	PROPN
cana-2347	151	9	,	,	PUNCT
cana-2347	151	10	et	et	PROPN
cana-2347	151	11	al	al	PROPN
cana-2347	151	12	.	.	PUNCT
cana-2347	152	1	"	"	PUNCT
cana-2347	152	2	evaluation	evaluation	NOUN
cana-2347	152	3	of	of	ADP
cana-2347	152	4	machine	machine	NOUN
cana-2347	152	5	learning	learning	NOUN
cana-2347	152	6	methods	method	NOUN
cana-2347	152	7	with	with	ADP
cana-2347	152	8	fourier	fouri	ADJ
cana-2347	152	9	transform	transform	NOUN
cana-2347	152	10	features	feature	NOUN
cana-2347	152	11	for	for	ADP
cana-2347	152	12	classifying	classify	VERB
cana-2347	152	13	ovarian	ovarian	ADJ
cana-2347	152	14	tumors	tumor	NOUN
cana-2347	152	15	based	base	VERB
cana-2347	152	16	on	on	ADP
cana-2347	152	17	ultrasound	ultrasound	NOUN
cana-2347	152	18	images	image	NOUN
cana-2347	152	19	.	.	PUNCT
cana-2347	152	20	"	"	PUNCT
cana-2347	153	1	plos	plo	VERB
cana-2347	153	2	one	one	NUM
cana-2347	153	3	14.7	14.7	NUM
cana-2347	153	4	(	(	PUNCT
cana-2347	153	5	2019	2019	NUM
cana-2347	153	6	):	):	PUNCT
cana-2347	153	7	e0219388	e0219388	NOUN
cana-2347	153	8	.	.	PUNCT
cana-2347	154	1	[	[	X
cana-2347	154	2	7	7	NUM
cana-2347	154	3	]	]	X
cana-2347	154	4	deeparani	deeparani	ADJ
cana-2347	154	5	,	,	PUNCT
cana-2347	154	6	m.	m.	NOUN
cana-2347	154	7	,	,	PUNCT
cana-2347	154	8	and	and	CCONJ
cana-2347	154	9	m.	m.	PROPN
cana-2347	154	10	kalamani	kalamani	PROPN
cana-2347	154	11	.	.	PUNCT
cana-2347	155	1	"	"	PUNCT
cana-2347	155	2	gynecological	gynecological	ADJ
cana-2347	155	3	healthcare	healthcare	NOUN
cana-2347	155	4	:	:	PUNCT
cana-2347	155	5	unveiling	unveil	VERB
cana-2347	155	6	pelvic	pelvic	ADJ
cana-2347	155	7	masses	masse	NOUN
cana-2347	155	8	classification	classification	VERB
cana-2347	155	9	through	through	ADP
cana-2347	155	10	evolutionary	evolutionary	ADJ
cana-2347	155	11	gravitational	gravitational	ADJ
cana-2347	155	12	neocognitron	neocognitron	PROPN
cana-2347	155	13	neural	neural	ADJ
cana-2347	155	14	network	network	NOUN
cana-2347	155	15	optimized	optimize	VERB
cana-2347	155	16	with	with	ADP
cana-2347	155	17	nomadic	nomadic	ADJ
cana-2347	155	18	people	people	NOUN
cana-2347	155	19	optimizer	optimizer	VERB
cana-2347	155	20	.	.	PUNCT
cana-2347	155	21	"	"	PUNCT
cana-2347	156	1	diagnostics	diagnostic	NOUN
cana-2347	156	2	13.19	13.19	NUM
cana-2347	156	3	(	(	PUNCT
cana-2347	156	4	2023	2023	NUM
cana-2347	156	5	):	):	PUNCT
cana-2347	156	6	3131	3131	NUM
cana-2347	156	7	.	.	PUNCT
cana-2347	157	1	[	[	X
cana-2347	157	2	8	8	NUM
cana-2347	157	3	]	]	PUNCT
cana-2347	157	4	a.	a.	NOUN
cana-2347	157	5	denny	denny	PROPN
cana-2347	157	6	,	,	PUNCT
cana-2347	157	7	a.	a.	PROPN
cana-2347	157	8	raj	raj	PROPN
cana-2347	157	9	,	,	PUNCT
cana-2347	157	10	a.	a.	NOUN
cana-2347	157	11	ashok	ashok	PROPN
cana-2347	157	12	,	,	PUNCT
cana-2347	157	13	c.	c.	PROPN
cana-2347	157	14	m.	m.	PROPN
cana-2347	157	15	ram	ram	PROPN
cana-2347	157	16	and	and	CCONJ
cana-2347	157	17	r.	r.	PROPN
cana-2347	157	18	george	george	PROPN
cana-2347	157	19	,	,	PUNCT
cana-2347	157	20	"	"	PUNCT
cana-2347	157	21	i	i	PROPN
cana-2347	157	22	-	-	PUNCT
cana-2347	157	23	hope	hope	NOUN
cana-2347	157	24	:	:	PUNCT
cana-2347	157	25	detection	detection	NOUN
cana-2347	157	26	and	and	CCONJ
cana-2347	157	27	prediction	prediction	NOUN
cana-2347	157	28	system	system	NOUN
cana-2347	157	29	for	for	ADP
cana-2347	157	30	polycystic	polycystic	ADJ
cana-2347	157	31	ovary	ovary	ADJ
cana-2347	157	32	syndrome	syndrome	NOUN
cana-2347	157	33	(	(	PUNCT
cana-2347	157	34	pcos	pco	NOUN
cana-2347	157	35	)	)	PUNCT
cana-2347	157	36	using	use	VERB
cana-2347	157	37	machine	machine	NOUN
cana-2347	157	38	learning	learning	NOUN
cana-2347	157	39	techniques	technique	NOUN
cana-2347	157	40	,	,	PUNCT
cana-2347	157	41	"	"	PUNCT
cana-2347	157	42	tencon	tencon	NOUN
cana-2347	157	43	2019	2019	NUM
cana-2347	157	44	2019	2019	NUM
cana-2347	157	45	ieee	ieee	NOUN
cana-2347	157	46	region	region	NOUN
cana-2347	157	47	10	10	NUM
cana-2347	157	48	conference	conference	NOUN
cana-2347	157	49	(	(	PUNCT
cana-2347	157	50	tencon	tencon	NOUN
cana-2347	157	51	)	)	PUNCT
cana-2347	157	52	,	,	PUNCT
cana-2347	157	53	2019	2019	NUM
cana-2347	157	54	,	,	PUNCT
cana-2347	157	55	pp	pp	ADJ
cana-2347	157	56	.	.	PUNCT
cana-2347	158	1	673	673	NUM
cana-2347	158	2	-	-	SYM
cana-2347	158	3	678	678	NUM
cana-2347	158	4	,	,	PUNCT
cana-2347	158	5	doi	doi	NOUN
cana-2347	158	6	:	:	PUNCT
cana-2347	158	7	10.1109	10.1109	NUM
cana-2347	158	8	/	/	SYM
cana-2347	158	9	tencon.2019.8929674	tencon.2019.8929674	NOUN
cana-2347	158	10	.	.	PUNCT
cana-2347	159	1	[	[	X
cana-2347	159	2	9	9	NUM
cana-2347	159	3	]	]	PUNCT
cana-2347	159	4	durairaj	durairaj	VERB
cana-2347	159	5	,	,	PUNCT
cana-2347	159	6	m.	m.	NOUN
cana-2347	159	7	,	,	PUNCT
cana-2347	159	8	and	and	CCONJ
cana-2347	159	9	r.	r.	PROPN
cana-2347	159	10	nandhakumar	nandhakumar	PROPN
cana-2347	159	11	.	.	PUNCT
cana-2347	160	1	"	"	PUNCT
cana-2347	160	2	data	datum	NOUN
cana-2347	160	3	mining	mining	NOUN
cana-2347	160	4	application	application	NOUN
cana-2347	160	5	on	on	ADP
cana-2347	160	6	ivf	ivf	ADJ
cana-2347	160	7	data	datum	NOUN
cana-2347	160	8	for	for	ADP
cana-2347	160	9	the	the	DET
cana-2347	160	10	selection	selection	NOUN
cana-2347	160	11	of	of	ADP
cana-2347	160	12	influential	influential	ADJ
cana-2347	160	13	parameters	parameter	NOUN
cana-2347	160	14	on	on	ADP
cana-2347	160	15	fertility	fertility	NOUN
cana-2347	160	16	.	.	PUNCT
cana-2347	160	17	"	"	PUNCT
cana-2347	161	1	int	int	NOUN
cana-2347	161	2	j	j	PROPN
cana-2347	161	3	eng	eng	PROPN
cana-2347	161	4	adv	adv	PROPN
cana-2347	161	5	technol	technol	NOUN
cana-2347	161	6	(	(	PUNCT
cana-2347	161	7	ijeat	ijeat	PROPN
cana-2347	161	8	)	)	PUNCT
cana-2347	161	9	2.6	2.6	NUM
cana-2347	161	10	(	(	PUNCT
cana-2347	161	11	2013	2013	NUM
cana-2347	161	12	):	):	PUNCT
cana-2347	161	13	262	262	NUM
cana-2347	161	14	-	-	SYM
cana-2347	161	15	266	266	NUM
cana-2347	161	16	.	.	PUNCT
cana-2347	162	1	[	[	X
cana-2347	162	2	10	10	NUM
cana-2347	162	3	]	]	PUNCT
cana-2347	162	4	bachelot	bachelot	NOUN
cana-2347	162	5	,	,	PUNCT
cana-2347	162	6	g.	g.	PROPN
cana-2347	162	7	,	,	PUNCT
cana-2347	162	8	lévy	lévy	PROPN
cana-2347	162	9	,	,	PUNCT
cana-2347	162	10	r.	r.	PROPN
cana-2347	162	11	,	,	PUNCT
cana-2347	162	12	bachelot	bachelot	ADV
cana-2347	162	13	,	,	PUNCT
cana-2347	162	14	a.	a.	PROPN
cana-2347	162	15	et	et	PROPN
cana-2347	162	16	al	al	PROPN
cana-2347	162	17	.	.	PUNCT
cana-2347	163	1	“	"	PUNCT
cana-2347	163	2	proof	proof	NOUN
cana-2347	163	3	of	of	ADP
cana-2347	163	4	concept	concept	NOUN
cana-2347	163	5	and	and	CCONJ
cana-2347	163	6	development	development	NOUN
cana-2347	163	7	of	of	ADP
cana-2347	163	8	a	a	DET
cana-2347	163	9	couple	couple	NOUN
cana-2347	163	10	-	-	PUNCT
cana-2347	163	11	based	base	VERB
cana-2347	163	12	machine	machine	NOUN
cana-2347	163	13	learning	learning	NOUN
cana-2347	163	14	model	model	NOUN
cana-2347	163	15	to	to	PART
cana-2347	163	16	stratify	stratify	VERB
cana-2347	163	17	infertile	infertile	ADJ
cana-2347	163	18	patients	patient	NOUN
cana-2347	163	19	with	with	ADP
cana-2347	163	20	idiopathic	idiopathic	ADJ
cana-2347	163	21	infertility	infertility	NOUN
cana-2347	163	22	”	"	PUNCT
cana-2347	163	23	.	.	PUNCT
cana-2347	164	1	sci	sci	PROPN
cana-2347	164	2	rep	rep	PROPN
cana-2347	164	3	11	11	NUM
cana-2347	164	4	,	,	PUNCT
cana-2347	164	5	24003	24003	NUM
cana-2347	164	6	(	(	PUNCT
cana-2347	164	7	2021	2021	NUM
cana-2347	164	8	)	)	PUNCT
cana-2347	164	9	.	.	PUNCT
cana-2347	165	1	https://doi.org/10.1038/s41598-021-03165-311	https://doi.org/10.1038/s41598-021-03165-311	NOUN
cana-2347	165	2	.	.	PUNCT
cana-2347	166	1	[	[	X
cana-2347	166	2	11	11	NUM
cana-2347	166	3	]	]	X
cana-2347	166	4	mehrjerd	mehrjerd	NOUN
cana-2347	166	5	,	,	PUNCT
cana-2347	166	6	a.	a.	PROPN
cana-2347	166	7	,	,	PUNCT
cana-2347	166	8	rezaei	rezaei	PROPN
cana-2347	166	9	,	,	PUNCT
cana-2347	166	10	h.	h.	PROPN
cana-2347	166	11	,	,	PUNCT
cana-2347	166	12	eslami	eslami	PROPN
cana-2347	166	13	,	,	PUNCT
cana-2347	166	14	s.	s.	PROPN
cana-2347	166	15	et	et	PROPN
cana-2347	166	16	al	al	PROPN
cana-2347	166	17	.	.	PUNCT
cana-2347	166	18	“	"	PUNCT
cana-2347	166	19	internal	internal	ADJ
cana-2347	166	20	validation	validation	NOUN
cana-2347	166	21	and	and	CCONJ
cana-2347	166	22	comparison	comparison	NOUN
cana-2347	166	23	of	of	ADP
cana-2347	166	24	predictive	predictive	ADJ
cana-2347	166	25	models	model	NOUN
cana-2347	166	26	to	to	PART
cana-2347	166	27	determine	determine	VERB
cana-2347	166	28	success	success	NOUN
cana-2347	166	29	rate	rate	NOUN
cana-2347	166	30	of	of	ADP
cana-2347	166	31	infertility	infertility	NOUN
cana-2347	166	32	treatments	treatment	NOUN
cana-2347	166	33	:	:	PUNCT
cana-2347	166	34	a	a	DET
cana-2347	166	35	retrospective	retrospective	ADJ
cana-2347	166	36	study	study	NOUN
cana-2347	166	37	of	of	ADP
cana-2347	166	38	2485	2485	NUM
cana-2347	166	39	cycles	cycle	NOUN
cana-2347	166	40	.	.	PUNCT
cana-2347	166	41	”	"	PUNCT
cana-2347	167	1	sci	sci	PROPN
cana-2347	167	2	rep	rep	PROPN
cana-2347	167	3	12	12	NUM
cana-2347	167	4	,	,	PUNCT
cana-2347	167	5	7216	7216	NUM
cana-2347	167	6	(	(	PUNCT
cana-2347	167	7	2022	2022	NUM
cana-2347	167	8	)	)	PUNCT
cana-2347	167	9	.	.	PUNCT
cana-2347	168	1	https://doi.org/10.1038/s41598-022-10902-9	https://doi.org/10.1038/s41598-022-10902-9	NOUN
cana-2347	169	1	[	[	X
cana-2347	169	2	12	12	NUM
cana-2347	169	3	]	]	PUNCT
cana-2347	169	4	vats	vat	NOUN
cana-2347	169	5	,	,	PUNCT
cana-2347	169	6	sakshi	sakshi	PROPN
cana-2347	169	7	,	,	PUNCT
cana-2347	169	8	et	et	PROPN
cana-2347	169	9	al	al	PROPN
cana-2347	169	10	.	.	PUNCT
cana-2347	170	1	"	"	PUNCT
cana-2347	170	2	combination	combination	NOUN
cana-2347	170	3	of	of	ADP
cana-2347	170	4	expression	expression	NOUN
cana-2347	170	5	data	datum	NOUN
cana-2347	170	6	and	and	CCONJ
cana-2347	170	7	predictive	predictive	ADJ
cana-2347	170	8	modelling	modelling	NOUN
cana-2347	170	9	for	for	ADP
cana-2347	170	10	polycystic	polycystic	ADJ
cana-2347	170	11	ovary	ovary	ADJ
cana-2347	170	12	disease	disease	NOUN
cana-2347	170	13	and	and	CCONJ
cana-2347	170	14	assessing	assess	VERB
cana-2347	170	15	risk	risk	NOUN
cana-2347	170	16	of	of	ADP
cana-2347	170	17	infertility	infertility	NOUN
cana-2347	170	18	using	use	VERB
cana-2347	170	19	machine	machine	NOUN
cana-2347	170	20	learning	learn	VERB
cana-2347	170	21	techniques	technique	NOUN
cana-2347	170	22	.	.	PUNCT
cana-2347	170	23	"	"	PUNCT
cana-2347	171	1	innovations	innovation	NOUN
cana-2347	171	2	in	in	ADP
cana-2347	171	3	computational	computational	ADJ
cana-2347	171	4	intelligence	intelligence	NOUN
cana-2347	171	5	and	and	CCONJ
cana-2347	171	6	computer	computer	NOUN
cana-2347	171	7	vision	vision	NOUN
cana-2347	171	8	.	.	PUNCT
cana-2347	172	1	springer	springer	PROPN
cana-2347	172	2	,	,	PUNCT
cana-2347	172	3	singapore	singapore	PROPN
cana-2347	172	4	,	,	PUNCT
cana-2347	172	5	2022	2022	NUM
cana-2347	172	6	.	.	PUNCT
cana-2347	173	1	547	547	NUM
cana-2347	173	2	-	-	SYM
cana-2347	173	3	555	555	NUM
cana-2347	173	4	.	.	PUNCT
cana-2347	174	1	[	[	X
cana-2347	174	2	13	13	NUM
cana-2347	174	3	]	]	SYM
cana-2347	174	4	nandipati	nandipati	PROPN
cana-2347	174	5	,	,	PUNCT
cana-2347	174	6	satish	satish	PROPN
cana-2347	174	7	cr	cr	PROPN
cana-2347	174	8	,	,	PUNCT
cana-2347	174	9	c.	c.	PROPN
cana-2347	174	10	x.	x.	PROPN
cana-2347	174	11	ying	ying	PROPN
cana-2347	174	12	,	,	PUNCT
cana-2347	174	13	and	and	CCONJ
cana-2347	174	14	khaw	khaw	PROPN
cana-2347	174	15	khai	khai	PROPN
cana-2347	174	16	wah	wah	PROPN
cana-2347	174	17	.	.	PUNCT
cana-2347	175	1	"	"	PUNCT
cana-2347	175	2	polycystic	polycystic	ADJ
cana-2347	175	3	ovarian	ovarian	ADJ
cana-2347	175	4	syndrome	syndrome	NOUN
cana-2347	175	5	(	(	PUNCT
cana-2347	175	6	pcos	pcos	NOUN
cana-2347	175	7	)	)	PUNCT
cana-2347	175	8	classification	classification	NOUN
cana-2347	175	9	and	and	CCONJ
cana-2347	175	10	feature	feature	NOUN
cana-2347	175	11	selection	selection	NOUN
cana-2347	175	12	by	by	ADP
cana-2347	175	13	machine	machine	NOUN
cana-2347	175	14	learning	learn	VERB
cana-2347	175	15	techniques	technique	NOUN
cana-2347	175	16	.	.	PUNCT
cana-2347	175	17	"	"	PUNCT
cana-2347	176	1	appl	appl	PROPN
cana-2347	176	2	math	math	PROPN
cana-2347	176	3	comput	comput	PROPN
cana-2347	176	4	intell	intell	PROPN
cana-2347	176	5	9	9	NUM
cana-2347	176	6	(	(	PUNCT
cana-2347	176	7	2020	2020	NUM
cana-2347	176	8	):	):	PUNCT
cana-2347	176	9	65	65	NUM
cana-2347	176	10	-	-	SYM
cana-2347	176	11	74	74	NUM
cana-2347	176	12	.	.	PUNCT
cana-2347	177	1	[	[	X
cana-2347	177	2	14	14	NUM
cana-2347	177	3	]	]	X
cana-2347	177	4	wang	wang	PROPN
cana-2347	177	5	,	,	PUNCT
cana-2347	177	6	cheng	cheng	PROPN
cana-2347	177	7	-	-	PUNCT
cana-2347	177	8	wei	wei	PROPN
cana-2347	177	9	,	,	PUNCT
cana-2347	177	10	et	et	PROPN
cana-2347	177	11	al	al	PROPN
cana-2347	177	12	.	.	PUNCT
cana-2347	178	1	"	"	PUNCT
cana-2347	178	2	predicting	predict	VERB
cana-2347	178	3	clinical	clinical	ADJ
cana-2347	178	4	pregnancy	pregnancy	NOUN
cana-2347	178	5	using	use	VERB
cana-2347	178	6	clinical	clinical	ADJ
cana-2347	178	7	features	feature	NOUN
cana-2347	178	8	and	and	CCONJ
cana-2347	178	9	machine	machine	NOUN
cana-2347	178	10	learning	learn	VERB
cana-2347	178	11	algorithms	algorithm	NOUN
cana-2347	178	12	in	in	ADV
cana-2347	178	13	in	in	ADP
cana-2347	178	14	vitro	vitro	X
cana-2347	178	15	fertilization	fertilization	NOUN
cana-2347	178	16	.	.	PUNCT
cana-2347	178	17	"	"	PUNCT
cana-2347	179	1	plos	plo	VERB
cana-2347	179	2	one	one	NUM
cana-2347	179	3	17.6	17.6	NUM
cana-2347	179	4	(	(	PUNCT
cana-2347	179	5	2022	2022	NUM
cana-2347	179	6	):	):	PUNCT
cana-2347	179	7	e0267554	e0267554	PROPN
cana-2347	179	8	.	.	PUNCT
cana-2347	180	1	[	[	X
cana-2347	180	2	15	15	NUM
cana-2347	180	3	]	]	PUNCT
cana-2347	180	4	tadepalli	tadepalli	NOUN
cana-2347	180	5	,	,	PUNCT
cana-2347	180	6	satya	satya	PROPN
cana-2347	180	7	kiranmai	kiranmai	NOUN
cana-2347	180	8	,	,	PUNCT
cana-2347	180	9	and	and	CCONJ
cana-2347	180	10	p.	p.	NOUN
cana-2347	180	11	v.	v.	ADP
cana-2347	180	12	lakshmi	lakshmi	PROPN
cana-2347	180	13	.	.	PUNCT
cana-2347	181	1	"	"	PUNCT
cana-2347	181	2	application	application	NOUN
cana-2347	181	3	of	of	ADP
cana-2347	181	4	machine	machine	NOUN
cana-2347	181	5	learning	learning	NOUN
cana-2347	181	6	and	and	CCONJ
cana-2347	181	7	artificial	artificial	ADJ
cana-2347	181	8	intelligence	intelligence	NOUN
cana-2347	181	9	techniques	technique	NOUN
cana-2347	181	10	for	for	ADP
cana-2347	181	11	ivf	ivf	ADJ
cana-2347	181	12	analysis	analysis	NOUN
cana-2347	181	13	and	and	CCONJ
cana-2347	181	14	prediction	prediction	NOUN
cana-2347	181	15	.	.	PUNCT
cana-2347	181	16	"	"	PUNCT
cana-2347	182	1	international	international	ADJ
cana-2347	182	2	journal	journal	NOUN
cana-2347	182	3	of	of	ADP
cana-2347	182	4	big	big	ADJ
cana-2347	182	5	data	datum	NOUN
cana-2347	182	6	and	and	CCONJ
cana-2347	182	7	analytics	analytic	NOUN
cana-2347	182	8	in	in	ADP
cana-2347	182	9	healthcare	healthcare	PROPN
cana-2347	182	10	(	(	PUNCT
cana-2347	182	11	ijbdah	ijbdah	PROPN
cana-2347	182	12	)	)	PUNCT
cana-2347	182	13	4.2	4.2	NUM
cana-2347	182	14	(	(	PUNCT
cana-2347	182	15	2019	2019	NUM
cana-2347	182	16	):	):	PUNCT
cana-2347	182	17	21	21	NUM
cana-2347	182	18	-	-	SYM
cana-2347	182	19	33	33	NUM
cana-2347	182	20	.	.	PUNCT
cana-2347	183	1	[	[	X
cana-2347	183	2	16	16	NUM
cana-2347	183	3	]	]	PUNCT
cana-2347	183	4	visalaxi	visalaxi	NOUN
cana-2347	183	5	,	,	PUNCT
cana-2347	183	6	s.	s.	PROPN
cana-2347	183	7	,	,	PUNCT
cana-2347	183	8	dinah	dinah	PROPN
cana-2347	183	9	punnoose	punnoose	VERB
cana-2347	183	10	,	,	PUNCT
cana-2347	183	11	and	and	CCONJ
cana-2347	183	12	t.	t.	PROPN
cana-2347	183	13	sudalai	sudalai	PROPN
cana-2347	183	14	muthu	muthu	PROPN
cana-2347	183	15	.	.	PUNCT
cana-2347	184	1	"	"	PUNCT
cana-2347	184	2	an	an	DET
cana-2347	184	3	analogy	analogy	NOUN
cana-2347	184	4	of	of	ADP
cana-2347	184	5	endometriosis	endometriosis	NOUN
cana-2347	184	6	recognition	recognition	NOUN
cana-2347	184	7	using	use	VERB
cana-2347	184	8	machine	machine	NOUN
cana-2347	184	9	learning	learn	VERB
cana-2347	184	10	techniques	technique	NOUN
cana-2347	184	11	.	.	PUNCT
cana-2347	184	12	"	"	PUNCT
cana-2347	185	1	2021	2021	NUM
cana-2347	185	2	third	third	ADJ
cana-2347	185	3	international	international	ADJ
cana-2347	185	4	conference	conference	NOUN
cana-2347	185	5	on	on	ADP
cana-2347	185	6	intelligent	intelligent	ADJ
cana-2347	185	7	communication	communication	NOUN
cana-2347	185	8	technologies	technology	NOUN
cana-2347	185	9	and	and	CCONJ
cana-2347	185	10	virtual	virtual	ADJ
cana-2347	185	11	mobile	mobile	ADJ
cana-2347	185	12	networks	network	NOUN
cana-2347	185	13	(	(	PUNCT
cana-2347	185	14	icicv	icicv	PROPN
cana-2347	185	15	)	)	PUNCT
cana-2347	185	16	.	.	PUNCT
cana-2347	186	1	ieee	ieee	NOUN
cana-2347	186	2	,	,	PUNCT
cana-2347	186	3	2021	2021	NUM
cana-2347	186	4	.	.	PUNCT
cana-2347	187	1	[	[	X
cana-2347	187	2	17	17	NUM
cana-2347	187	3	]	]	X
cana-2347	187	4	quesada	quesada	PROPN
cana-2347	187	5	,	,	PUNCT
cana-2347	187	6	juan	juan	PROPN
cana-2347	187	7	,	,	PUNCT
cana-2347	187	8	et	et	PROPN
cana-2347	187	9	al	al	PROPN
cana-2347	187	10	.	.	PUNCT
cana-2347	188	1	"	"	PUNCT
cana-2347	188	2	endometriosis	endometriosis	NOUN
cana-2347	188	3	:	:	PUNCT
cana-2347	188	4	a	a	DET
cana-2347	188	5	multimodal	multimodal	ADJ
cana-2347	188	6	imaging	imaging	NOUN
cana-2347	188	7	review	review	NOUN
cana-2347	188	8	.	.	PUNCT
cana-2347	188	9	"	"	PUNCT
cana-2347	189	1	european	european	ADJ
cana-2347	189	2	journal	journal	PROPN
cana-2347	189	3	of	of	ADP
cana-2347	189	4	radiology	radiology	NOUN
cana-2347	189	5	(	(	PUNCT
cana-2347	189	6	2022	2022	NUM
cana-2347	189	7	):	):	PUNCT
cana-2347	189	8	110610	110610	NUM
cana-2347	189	9	.	.	PUNCT
cana-2347	190	1	authors	author	NOUN
cana-2347	190	2	biography	biography	PROPN
cana-2347	190	3	soumya	soumya	PROPN
cana-2347	190	4	koshy	koshy	PROPN
cana-2347	190	5	is	be	AUX
cana-2347	190	6	an	an	DET
cana-2347	190	7	experienced	experienced	ADJ
cana-2347	190	8	educator	educator	NOUN
cana-2347	190	9	and	and	CCONJ
cana-2347	190	10	researcher	researcher	NOUN
cana-2347	190	11	with	with	ADP
cana-2347	190	12	over	over	ADP
cana-2347	190	13	13	13	NUM
cana-2347	190	14	years	year	NOUN
cana-2347	190	15	of	of	ADP
cana-2347	190	16	teaching	teaching	NOUN
cana-2347	190	17	experience	experience	NOUN
cana-2347	190	18	in	in	ADP
cana-2347	190	19	computer	computer	NOUN
cana-2347	190	20	science	science	NOUN
cana-2347	190	21	.	.	PUNCT
cana-2347	191	1	holding	hold	VERB
cana-2347	191	2	a	a	DET
cana-2347	191	3	master	master	NOUN
cana-2347	191	4	’s	’s	PART
cana-2347	191	5	degree	degree	NOUN
cana-2347	191	6	in	in	ADP
cana-2347	191	7	computer	computer	NOUN
cana-2347	191	8	applications	application	NOUN
cana-2347	191	9	,	,	PUNCT
cana-2347	191	10	she	she	PRON
cana-2347	191	11	is	be	AUX
cana-2347	191	12	currently	currently	ADV
cana-2347	191	13	pursuing	pursue	VERB
cana-2347	191	14	a	a	DET
cana-2347	191	15	phd	phd	NOUN
cana-2347	191	16	specializing	specialize	VERB
cana-2347	191	17	in	in	ADP
cana-2347	191	18	the	the	DET
cana-2347	191	19	application	application	NOUN
cana-2347	191	20	of	of	ADP
cana-2347	191	21	deep	deep	ADJ
cana-2347	191	22	learning	learning	NOUN
cana-2347	191	23	for	for	ADP
cana-2347	191	24	medical	medical	ADJ
cana-2347	191	25	imaging	imaging	NOUN
cana-2347	191	26	,	,	PUNCT
cana-2347	191	27	particularly	particularly	ADV
cana-2347	191	28	in	in	ADP
cana-2347	191	29	ovarian	ovarian	ADJ
cana-2347	191	30	disease	disease	NOUN
cana-2347	191	31	detection	detection	NOUN
cana-2347	191	32	and	and	CCONJ
cana-2347	191	33	stage	stage	NOUN
cana-2347	191	34	-	-	PUNCT
cana-2347	191	35	specific	specific	ADJ
cana-2347	191	36	prognosis	prognosis	NOUN
cana-2347	191	37	of	of	ADP
cana-2347	191	38	endometriosis	endometriosis	NOUN
cana-2347	191	39	.	.	PUNCT
cana-2347	192	1	passionate	passionate	ADJ
cana-2347	192	2	about	about	ADP
cana-2347	192	3	exploring	explore	VERB
cana-2347	192	4	innovative	innovative	ADJ
cana-2347	192	5	teaching	teaching	NOUN
cana-2347	192	6	methods	method	NOUN
cana-2347	192	7	and	and	CCONJ
cana-2347	192	8	advancements	advancement	NOUN
cana-2347	192	9	in	in	ADP
cana-2347	192	10	artificial	artificial	ADJ
cana-2347	192	11	intelligence	intelligence	NOUN
cana-2347	192	12	and	and	CCONJ
cana-2347	192	13	machine	machine	NOUN
cana-2347	192	14	learning	learning	NOUN
cana-2347	192	15	,	,	PUNCT
cana-2347	192	16	she	she	PRON
cana-2347	192	17	combines	combine	VERB
cana-2347	192	18	her	her	PRON
cana-2347	192	19	strong	strong	ADJ
cana-2347	192	20	academic	academic	ADJ
cana-2347	192	21	foundation	foundation	NOUN
cana-2347	192	22	with	with	ADP
cana-2347	192	23	practical	practical	ADJ
cana-2347	192	24	research	research	NOUN
cana-2347	192	25	insights	insight	NOUN
cana-2347	192	26	to	to	PART
cana-2347	192	27	contribute	contribute	VERB
cana-2347	192	28	to	to	ADP
cana-2347	192	29	the	the	DET
cana-2347	192	30	field	field	NOUN
cana-2347	192	31	.	.	PUNCT
cana-2347	193	1	she	she	PRON
cana-2347	193	2	is	be	AUX
cana-2347	193	3	dedicated	dedicate	VERB
cana-2347	193	4	to	to	ADP
cana-2347	193	5	driving	drive	VERB
cana-2347	193	6	progress	progress	NOUN
cana-2347	193	7	in	in	ADP
cana-2347	193	8	ai	ai	ADJ
cana-2347	193	9	-	-	PUNCT
cana-2347	193	10	driven	drive	VERB
cana-2347	193	11	healthcare	healthcare	NOUN
cana-2347	193	12	solutions	solution	NOUN
cana-2347	193	13	and	and	CCONJ
cana-2347	193	14	fostering	foster	VERB
cana-2347	193	15	a	a	DET
cana-2347	193	16	new	new	ADJ
cana-2347	193	17	generation	generation	NOUN
cana-2347	193	18	of	of	ADP
cana-2347	193	19	tech	tech	NOUN
cana-2347	193	20	enthusiasts	enthusiast	NOUN
cana-2347	193	21	in	in	ADP
cana-2347	193	22	computer	computer	NOUN
cana-2347	193	23	science	science	NOUN
cana-2347	193	24	and	and	CCONJ
cana-2347	193	25	machine	machine	NOUN
cana-2347	193	26	learning	learning	NOUN
cana-2347	193	27	.	.	PUNCT
cana-2347	194	1	communications	communication	NOUN
cana-2347	194	2	on	on	ADP
cana-2347	194	3	applied	apply	VERB
cana-2347	194	4	nonlinear	nonlinear	ADJ
cana-2347	194	5	analysis	analysis	NOUN
cana-2347	194	6	issn	issn	NOUN
cana-2347	194	7	:	:	PUNCT
cana-2347	194	8	1074	1074	NUM
cana-2347	194	9	-	-	PUNCT
cana-2347	194	10	133x	133x	NUM
cana-2347	194	11	vol	vol	NOUN
cana-2347	194	12	32	32	NUM
cana-2347	194	13	no	no	NOUN
cana-2347	194	14	.	.	PUNCT
cana-2347	195	1	1s	1s	NUM
cana-2347	195	2	(	(	PUNCT
cana-2347	195	3	2025	2025	NUM
cana-2347	195	4	)	)	PUNCT
cana-2347	195	5	621	621	NUM
cana-2347	195	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2347	195	7	dr	dr	PROPN
cana-2347	195	8	.	.	PROPN
cana-2347	196	1	k	k	PROPN
cana-2347	196	2	ranjith	ranjith	PROPN
cana-2347	196	3	singh	singh	PROPN
cana-2347	196	4	,	,	PUNCT
cana-2347	196	5	associate	associate	ADJ
cana-2347	196	6	professor	professor	NOUN
cana-2347	196	7	in	in	ADP
cana-2347	196	8	the	the	DET
cana-2347	196	9	department	department	NOUN
cana-2347	196	10	of	of	ADP
cana-2347	196	11	computer	computer	NOUN
cana-2347	196	12	science	science	NOUN
cana-2347	196	13	at	at	ADP
cana-2347	196	14	karpagam	karpagam	PROPN
cana-2347	196	15	academy	academy	PROPN
cana-2347	196	16	of	of	ADP
cana-2347	196	17	higher	high	ADJ
cana-2347	196	18	education	education	NOUN
cana-2347	196	19	,	,	PUNCT
cana-2347	196	20	coimbatore	coimbatore	PROPN
cana-2347	196	21	,	,	PUNCT
cana-2347	196	22	tamil	tamil	PROPN
cana-2347	196	23	nadu	nadu	PROPN
cana-2347	196	24	,	,	PUNCT
cana-2347	196	25	india	india	PROPN
cana-2347	196	26	.	.	PUNCT
cana-2347	197	1	he	he	PRON
cana-2347	197	2	has	have	VERB
cana-2347	197	3	21	21	NUM
cana-2347	197	4	years	year	NOUN
cana-2347	197	5	of	of	ADP
cana-2347	197	6	experience	experience	NOUN
cana-2347	197	7	in	in	ADP
cana-2347	197	8	academic	academic	ADJ
cana-2347	197	9	field	field	NOUN
cana-2347	197	10	.	.	PUNCT
cana-2347	198	1	his	his	PRON
cana-2347	198	2	area	area	NOUN
cana-2347	198	3	of	of	ADP
cana-2347	198	4	interest	interest	NOUN
cana-2347	198	5	is	be	AUX
cana-2347	198	6	network	network	NOUN
cana-2347	198	7	security	security	NOUN
cana-2347	198	8	and	and	CCONJ
cana-2347	198	9	cryptography	cryptography	NOUN
cana-2347	198	10	.	.	PUNCT
cana-2347	199	1	his	his	PRON
cana-2347	199	2	phd	phd	NOUN
cana-2347	199	3	work	work	NOUN
cana-2347	199	4	focused	focus	VERB
cana-2347	199	5	on	on	ADP
cana-2347	199	6	trust	trust	NOUN
cana-2347	199	7	based	base	VERB
cana-2347	199	8	routing	routing	NOUN
cana-2347	199	9	mechanism	mechanism	NOUN
cana-2347	199	10	in	in	ADP
cana-2347	199	11	manet	manet	NOUN
cana-2347	199	12	,	,	PUNCT
cana-2347	199	13	combining	combine	VERB
cana-2347	199	14	trust	trust	NOUN
cana-2347	199	15	based	base	VERB
cana-2347	199	16	routing	routing	NOUN
cana-2347	199	17	algorithms	algorithm	NOUN
cana-2347	199	18	,	,	PUNCT
cana-2347	199	19	and	and	CCONJ
cana-2347	199	20	security	security	NOUN
cana-2347	199	21	protocols	protocol	NOUN
cana-2347	199	22	.	.	PUNCT
cana-2347	200	1	the	the	DET
cana-2347	200	2	study	study	NOUN
cana-2347	200	3	involved	involve	VERB
cana-2347	200	4	trust	trust	NOUN
cana-2347	200	5	based	base	VERB
cana-2347	200	6	routing	routing	NOUN
cana-2347	200	7	algorithms	algorithm	NOUN
cana-2347	200	8	,	,	PUNCT
cana-2347	200	9	and	and	CCONJ
cana-2347	200	10	control	control	NOUN
cana-2347	200	11	of	of	ADP
cana-2347	200	12	trust	trust	NOUN
cana-2347	200	13	management	management	NOUN
cana-2347	200	14	system	system	NOUN
cana-2347	200	15	.	.	PUNCT
cana-2347	201	1	he	he	PRON
cana-2347	201	2	has	have	AUX
cana-2347	201	3	published	publish	VERB
cana-2347	201	4	more	more	ADJ
cana-2347	201	5	than	than	ADP
cana-2347	201	6	22	22	NUM
cana-2347	201	7	research	research	NOUN
cana-2347	201	8	papers	paper	NOUN
cana-2347	201	9	in	in	ADP
cana-2347	201	10	scopus	scopus	PROPN
cana-2347	201	11	and	and	CCONJ
cana-2347	201	12	sci	sci	PROPN
cana-2347	201	13	.	.	PROPN
cana-2347	201	14	orcid	orcid	PROPN
cana-2347	201	15	(	(	PUNCT
cana-2347	201	16	https://orcid.org/0000-0003-2651-2509	https://orcid.org/0000-0003-2651-2509	PROPN
cana-2347	201	17	)	)	PUNCT
cana-2347	201	18	,	,	PUNCT
cana-2347	201	19	scopus	scopus	PROPN
cana-2347	201	20	i	i	PROPN
cana-2347	201	21	d	d	PROPN
cana-2347	201	22	:	:	PUNCT
cana-2347	201	23	57216271806	57216271806	NUM
cana-2347	201	24	,	,	PUNCT
cana-2347	201	25	53318740700	53318740700	NUM
cana-2347	201	26	(	(	PUNCT
cana-2347	201	27	https:/orcid.org/0000	https:/orcid.org/0000	NOUN
cana-2347	201	28	-	-	PUNCT
cana-2347	201	29	0003	0003	NUM
cana-2347	201	30	-	-	PUNCT
cana-2347	201	31	2651	2651	NUM
cana-2347	201	32	-	-	PUNCT
cana-2347	201	33	2509	2509	NUM
cana-2347	201	34	)	)	PUNCT