id	sid	tid	token	lemma	pos
cana-3964	1	1	communications	communication	NOUN
cana-3964	1	2	on	on	ADP
cana-3964	1	3	applied	apply	VERB
cana-3964	1	4	nonlinear	nonlinear	ADJ
cana-3964	1	5	analysis	analysis	NOUN
cana-3964	1	6	issn	issn	NOUN
cana-3964	1	7	:	:	PUNCT
cana-3964	1	8	1074	1074	NUM
cana-3964	1	9	-	-	PUNCT
cana-3964	1	10	133x	133x	NUM
cana-3964	1	11	vol	vol	NOUN
cana-3964	1	12	32	32	NUM
cana-3964	1	13	no	no	NOUN
cana-3964	1	14	.	.	PUNCT
cana-3964	2	1	9s	9s	NUM
cana-3964	2	2	(	(	PUNCT
cana-3964	2	3	2025	2025	NUM
cana-3964	2	4	)	)	PUNCT
cana-3964	3	1	554	554	NUM
cana-3964	3	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	3	3	machine	machine	NOUN
cana-3964	3	4	learning	learn	VERB
cana-3964	3	5	techniques	technique	NOUN
cana-3964	3	6	for	for	ADP
cana-3964	3	7	breast	breast	NOUN
cana-3964	3	8	cancer	cancer	NOUN
cana-3964	3	9	prediction	prediction	NOUN
cana-3964	3	10	:	:	PUNCT
cana-3964	3	11	a	a	DET
cana-3964	3	12	comprehensive	comprehensive	ADJ
cana-3964	3	13	review	review	NOUN
cana-3964	3	14	on	on	ADP
cana-3964	3	15	techniques	technique	NOUN
cana-3964	3	16	and	and	CCONJ
cana-3964	3	17	datasets	dataset	VERB
cana-3964	3	18	archana	archana	PROPN
cana-3964	3	19	singh1	singh1	PROPN
cana-3964	3	20	*	*	PROPN
cana-3964	3	21	,	,	PUNCT
cana-3964	3	22	kuldeep	kuldeep	PROPN
cana-3964	3	23	singh	singh	PROPN
cana-3964	3	24	kaswan2	kaswan2	PROPN
cana-3964	3	25	,	,	PUNCT
cana-3964	3	26	rajani3	rajani3	PUNCT
cana-3964	4	1	1,2department	1,2department	NUM
cana-3964	4	2	of	of	ADP
cana-3964	4	3	computer	computer	NOUN
cana-3964	4	4	science	science	PROPN
cana-3964	4	5	&	&	CCONJ
cana-3964	4	6	engineering	engineering	PROPN
cana-3964	4	7	,	,	PUNCT
cana-3964	4	8	galgotias	galgotias	PROPN
cana-3964	4	9	university	university	NOUN
cana-3964	4	10	,	,	PUNCT
cana-3964	4	11	greater	great	ADJ
cana-3964	4	12	noida	noida	PROPN
cana-3964	4	13	,	,	PUNCT
cana-3964	4	14	uttar	uttar	PROPN
cana-3964	4	15	pradesh	pradesh	PROPN
cana-3964	4	16	,	,	PUNCT
cana-3964	4	17	india	india	PROPN
cana-3964	4	18	.	.	PUNCT
cana-3964	5	1	3department	3department	NUM
cana-3964	5	2	of	of	ADP
cana-3964	5	3	computer	computer	NOUN
cana-3964	5	4	science	science	NOUN
cana-3964	5	5	,	,	PUNCT
cana-3964	5	6	kalindi	kalindi	PROPN
cana-3964	5	7	college	college	PROPN
cana-3964	5	8	,	,	PUNCT
cana-3964	5	9	university	university	PROPN
cana-3964	5	10	of	of	ADP
cana-3964	5	11	delhi	delhi	PROPN
cana-3964	5	12	,	,	PUNCT
cana-3964	5	13	new	new	ADJ
cana-3964	5	14	delhi	delhi	PROPN
cana-3964	5	15	,	,	PUNCT
cana-3964	5	16	india	india	PROPN
cana-3964	5	17	.	.	PUNCT
cana-3964	6	1	article	article	PROPN
cana-3964	6	2	history	history	NOUN
cana-3964	6	3	:	:	PUNCT
cana-3964	6	4	received	receive	VERB
cana-3964	6	5	:	:	PUNCT
cana-3964	6	6	12	12	NUM
cana-3964	6	7	-	-	SYM
cana-3964	6	8	11	11	NUM
cana-3964	6	9	-	-	PUNCT
cana-3964	6	10	2024	2024	NUM
cana-3964	6	11	revised	revise	VERB
cana-3964	6	12	:	:	PUNCT
cana-3964	6	13	17	17	NUM
cana-3964	6	14	-	-	SYM
cana-3964	6	15	12	12	NUM
cana-3964	6	16	-	-	PUNCT
cana-3964	6	17	2024	2024	NUM
cana-3964	6	18	accepted	accept	VERB
cana-3964	6	19	:	:	PUNCT
cana-3964	6	20	06	06	NUM
cana-3964	6	21	-	-	SYM
cana-3964	6	22	01	01	NUM
cana-3964	6	23	-	-	PUNCT
cana-3964	6	24	2025	2025	NUM
cana-3964	6	25	abstract	abstract	NOUN
cana-3964	6	26	:	:	PUNCT
cana-3964	6	27	breast	breast	NOUN
cana-3964	6	28	cancer	cancer	NOUN
cana-3964	6	29	(	(	PUNCT
cana-3964	6	30	bc	bc	PROPN
cana-3964	6	31	)	)	PUNCT
cana-3964	6	32	is	be	AUX
cana-3964	6	33	a	a	DET
cana-3964	6	34	key	key	ADJ
cana-3964	6	35	health	health	NOUN
cana-3964	6	36	concern	concern	NOUN
cana-3964	6	37	worldwide	worldwide	ADV
cana-3964	6	38	;	;	PUNCT
cana-3964	6	39	early	early	ADJ
cana-3964	6	40	detection	detection	NOUN
cana-3964	6	41	and	and	CCONJ
cana-3964	6	42	accurate	accurate	ADJ
cana-3964	6	43	diagnosis	diagnosis	NOUN
cana-3964	6	44	are	be	AUX
cana-3964	6	45	crucial	crucial	ADJ
cana-3964	6	46	for	for	ADP
cana-3964	6	47	improving	improve	VERB
cana-3964	6	48	patient	patient	ADJ
cana-3964	6	49	outcomes	outcome	NOUN
cana-3964	6	50	.	.	PUNCT
cana-3964	7	1	machine	machine	NOUN
cana-3964	7	2	learning	learning	NOUN
cana-3964	7	3	techniques	technique	NOUN
cana-3964	7	4	have	have	AUX
cana-3964	7	5	shown	show	VERB
cana-3964	7	6	promise	promise	NOUN
cana-3964	7	7	in	in	ADP
cana-3964	7	8	revolutionizing	revolutionize	VERB
cana-3964	7	9	breast	breast	NOUN
cana-3964	7	10	cancer	cancer	NOUN
cana-3964	7	11	diagnosis	diagnosis	NOUN
cana-3964	7	12	.	.	PUNCT
cana-3964	8	1	this	this	DET
cana-3964	8	2	review	review	NOUN
cana-3964	8	3	covers	cover	VERB
cana-3964	8	4	various	various	ADJ
cana-3964	8	5	machine	machine	NOUN
cana-3964	8	6	learning	learn	VERB
cana-3964	8	7	techniques	technique	NOUN
cana-3964	8	8	,	,	PUNCT
cana-3964	8	9	ranging	range	VERB
cana-3964	8	10	from	from	ADP
cana-3964	8	11	classic	classic	ADJ
cana-3964	8	12	algorithms	algorithm	NOUN
cana-3964	8	13	like	like	ADP
cana-3964	8	14	decision	decision	NOUN
cana-3964	8	15	trees	tree	NOUN
cana-3964	8	16	and	and	CCONJ
cana-3964	8	17	k	k	NOUN
cana-3964	8	18	-	-	PUNCT
cana-3964	8	19	nearest	near	ADJ
cana-3964	8	20	neighbor	neighbor	NOUN
cana-3964	8	21	(	(	PUNCT
cana-3964	8	22	knn	knn	PROPN
cana-3964	8	23	)	)	PUNCT
cana-3964	8	24	to	to	ADP
cana-3964	8	25	advanced	advanced	ADJ
cana-3964	8	26	methodologies	methodology	NOUN
cana-3964	8	27	such	such	ADJ
cana-3964	8	28	as	as	ADP
cana-3964	8	29	ensemble	ensemble	ADJ
cana-3964	8	30	learning	learning	NOUN
cana-3964	8	31	and	and	CCONJ
cana-3964	8	32	deep	deep	ADJ
cana-3964	8	33	learning	learning	NOUN
cana-3964	8	34	.	.	PUNCT
cana-3964	9	1	the	the	DET
cana-3964	9	2	variation	variation	NOUN
cana-3964	9	3	in	in	ADP
cana-3964	9	4	accuracy	accuracy	NOUN
cana-3964	9	5	metrics	metric	NOUN
cana-3964	9	6	and	and	CCONJ
cana-3964	9	7	the	the	DET
cana-3964	9	8	lack	lack	NOUN
cana-3964	9	9	of	of	ADP
cana-3964	9	10	standardized	standardized	ADJ
cana-3964	9	11	evaluation	evaluation	NOUN
cana-3964	9	12	methodologies	methodology	NOUN
cana-3964	9	13	make	make	VERB
cana-3964	9	14	it	it	PRON
cana-3964	9	15	challenging	challenge	VERB
cana-3964	9	16	to	to	PART
cana-3964	9	17	directly	directly	ADV
cana-3964	9	18	compare	compare	VERB
cana-3964	9	19	the	the	DET
cana-3964	9	20	performance	performance	NOUN
cana-3964	9	21	of	of	ADP
cana-3964	9	22	diverse	diverse	ADJ
cana-3964	9	23	algorithms	algorithm	NOUN
cana-3964	9	24	.	.	PUNCT
cana-3964	10	1	this	this	DET
cana-3964	10	2	study	study	NOUN
cana-3964	10	3	discusses	discuss	VERB
cana-3964	10	4	the	the	DET
cana-3964	10	5	data	datum	NOUN
cana-3964	10	6	sources	source	NOUN
cana-3964	10	7	and	and	CCONJ
cana-3964	10	8	methodology	methodology	NOUN
cana-3964	10	9	employed	employ	VERB
cana-3964	10	10	in	in	ADP
cana-3964	10	11	the	the	DET
cana-3964	10	12	examined	examine	VERB
cana-3964	10	13	studies	study	NOUN
cana-3964	10	14	,	,	PUNCT
cana-3964	10	15	as	as	ADV
cana-3964	10	16	well	well	ADV
cana-3964	10	17	as	as	ADP
cana-3964	10	18	comparing	compare	VERB
cana-3964	10	19	various	various	ADJ
cana-3964	10	20	machine	machine	NOUN
cana-3964	10	21	learning	learning	NOUN
cana-3964	10	22	approaches	approach	NOUN
cana-3964	10	23	.	.	PUNCT
cana-3964	11	1	the	the	DET
cana-3964	11	2	findings	finding	NOUN
cana-3964	11	3	of	of	ADP
cana-3964	11	4	this	this	DET
cana-3964	11	5	work	work	NOUN
cana-3964	11	6	indicate	indicate	VERB
cana-3964	11	7	that	that	DET
cana-3964	11	8	machine	machine	NOUN
cana-3964	11	9	learning	learning	NOUN
cana-3964	11	10	approaches	approach	NOUN
cana-3964	11	11	may	may	AUX
cana-3964	11	12	greatly	greatly	ADV
cana-3964	11	13	enhance	enhance	VERB
cana-3964	11	14	the	the	DET
cana-3964	11	15	diagnosis	diagnosis	NOUN
cana-3964	11	16	of	of	ADP
cana-3964	11	17	breast	breast	NOUN
cana-3964	11	18	cancer	cancer	NOUN
cana-3964	11	19	.	.	PUNCT
cana-3964	12	1	the	the	DET
cana-3964	12	2	comparison	comparison	NOUN
cana-3964	12	3	analysis	analysis	NOUN
cana-3964	12	4	clarified	clarify	VERB
cana-3964	12	5	that	that	SCONJ
cana-3964	12	6	ensemble	ensemble	ADJ
cana-3964	12	7	learning	learning	NOUN
cana-3964	12	8	provided	provide	VERB
cana-3964	12	9	better	well	ADJ
cana-3964	12	10	results	result	NOUN
cana-3964	12	11	on	on	ADP
cana-3964	12	12	the	the	DET
cana-3964	12	13	wisconsin	wisconsin	PROPN
cana-3964	12	14	breast	breast	PROPN
cana-3964	12	15	cancer	cancer	NOUN
cana-3964	12	16	dataset	dataset	NOUN
cana-3964	12	17	(	(	PUNCT
cana-3964	12	18	wdbc	wdbc	PROPN
cana-3964	12	19	)	)	PUNCT
cana-3964	12	20	,	,	PUNCT
cana-3964	12	21	attaining	attain	VERB
cana-3964	12	22	the	the	DET
cana-3964	12	23	highest	high	ADJ
cana-3964	12	24	metrics	metric	NOUN
cana-3964	12	25	with	with	ADP
cana-3964	12	26	an	an	DET
cana-3964	12	27	accuracy	accuracy	NOUN
cana-3964	12	28	,	,	PUNCT
cana-3964	12	29	precision	precision	NOUN
cana-3964	12	30	,	,	PUNCT
cana-3964	12	31	recall	recall	NOUN
cana-3964	12	32	,	,	PUNCT
cana-3964	12	33	and	and	CCONJ
cana-3964	12	34	an	an	DET
cana-3964	12	35	f1	f1	NOUN
cana-3964	12	36	-	-	PUNCT
cana-3964	12	37	score	score	NOUN
cana-3964	12	38	.	.	PUNCT
cana-3964	13	1	furthermore	furthermore	ADV
cana-3964	13	2	,	,	PUNCT
cana-3964	13	3	the	the	DET
cana-3964	13	4	optimized	optimize	VERB
cana-3964	13	5	framework	framework	NOUN
cana-3964	13	6	demonstrated	demonstrate	VERB
cana-3964	13	7	highest	high	ADJ
cana-3964	13	8	accuracy	accuracy	NOUN
cana-3964	13	9	on	on	ADP
cana-3964	13	10	ultrasound	ultrasound	ADJ
cana-3964	13	11	image	image	NOUN
cana-3964	13	12	data	datum	NOUN
cana-3964	13	13	,	,	PUNCT
cana-3964	13	14	underscoring	underscore	VERB
cana-3964	13	15	its	its	PRON
cana-3964	13	16	efficacy	efficacy	NOUN
cana-3964	13	17	and	and	CCONJ
cana-3964	13	18	robustness	robustness	NOUN
cana-3964	13	19	in	in	ADP
cana-3964	13	20	medical	medical	ADJ
cana-3964	13	21	diagnostics	diagnostic	NOUN
cana-3964	13	22	.	.	PUNCT
cana-3964	14	1	this	this	DET
cana-3964	14	2	review	review	NOUN
cana-3964	14	3	provides	provide	VERB
cana-3964	14	4	a	a	DET
cana-3964	14	5	unique	unique	ADJ
cana-3964	14	6	and	and	CCONJ
cana-3964	14	7	critical	critical	ADJ
cana-3964	14	8	analysis	analysis	NOUN
cana-3964	14	9	of	of	ADP
cana-3964	14	10	the	the	DET
cana-3964	14	11	machine	machine	NOUN
cana-3964	14	12	learning	learn	VERB
cana-3964	14	13	techniques	technique	NOUN
cana-3964	14	14	and	and	CCONJ
cana-3964	14	15	data	datum	NOUN
cana-3964	14	16	sources	source	NOUN
cana-3964	14	17	used	use	VERB
cana-3964	14	18	in	in	ADP
cana-3964	14	19	breast	breast	NOUN
cana-3964	14	20	cancer	cancer	NOUN
cana-3964	14	21	diagnosis	diagnosis	NOUN
cana-3964	14	22	and	and	CCONJ
cana-3964	14	23	highlights	highlight	NOUN
cana-3964	14	24	the	the	DET
cana-3964	14	25	need	need	NOUN
cana-3964	14	26	for	for	ADP
cana-3964	14	27	further	further	ADJ
cana-3964	14	28	research	research	NOUN
cana-3964	14	29	in	in	ADP
cana-3964	14	30	this	this	DET
cana-3964	14	31	area	area	NOUN
cana-3964	14	32	.	.	PUNCT
cana-3964	15	1	keywords	keyword	NOUN
cana-3964	15	2	:	:	PUNCT
cana-3964	15	3	breast	breast	NOUN
cana-3964	15	4	cancer	cancer	NOUN
cana-3964	15	5	,	,	PUNCT
cana-3964	15	6	diagnosis	diagnosis	NOUN
cana-3964	15	7	,	,	PUNCT
cana-3964	15	8	ml	ml	ADP
cana-3964	15	9	techniques	technique	NOUN
cana-3964	15	10	,	,	PUNCT
cana-3964	15	11	dataset	dataset	NOUN
cana-3964	15	12	,	,	PUNCT
cana-3964	15	13	wdbc	wdbc	PROPN
cana-3964	15	14	.	.	PUNCT
cana-3964	16	1	1	1	X
cana-3964	16	2	.	.	X
cana-3964	16	3	introduction	introduction	NOUN
cana-3964	16	4	breast	breast	NOUN
cana-3964	16	5	cancer	cancer	NOUN
cana-3964	16	6	is	be	AUX
cana-3964	16	7	a	a	DET
cana-3964	16	8	multifaceted	multifaceted	ADJ
cana-3964	16	9	and	and	CCONJ
cana-3964	16	10	widespread	widespread	ADJ
cana-3964	16	11	ailment	ailment	NOUN
cana-3964	16	12	that	that	PRON
cana-3964	16	13	predominantly	predominantly	ADV
cana-3964	16	14	impacts	impact	VERB
cana-3964	16	15	the	the	DET
cana-3964	16	16	cells	cell	NOUN
cana-3964	16	17	and	and	CCONJ
cana-3964	16	18	tissues	tissue	NOUN
cana-3964	16	19	of	of	ADP
cana-3964	16	20	the	the	DET
cana-3964	16	21	breast	breast	NOUN
cana-3964	16	22	.	.	PUNCT
cana-3964	17	1	this	this	DET
cana-3964	17	2	condition	condition	NOUN
cana-3964	17	3	is	be	AUX
cana-3964	17	4	identified	identify	VERB
cana-3964	17	5	by	by	ADP
cana-3964	17	6	the	the	DET
cana-3964	17	7	unregulated	unregulated	ADJ
cana-3964	17	8	proliferation	proliferation	NOUN
cana-3964	17	9	and	and	CCONJ
cana-3964	17	10	division	division	NOUN
cana-3964	17	11	of	of	ADP
cana-3964	17	12	irregular	irregular	ADJ
cana-3964	17	13	cells	cell	NOUN
cana-3964	17	14	in	in	ADP
cana-3964	17	15	the	the	DET
cana-3964	17	16	breast	breast	NOUN
cana-3964	17	17	tissue	tissue	NOUN
cana-3964	17	18	,	,	PUNCT
cana-3964	17	19	resulting	result	VERB
cana-3964	17	20	in	in	ADP
cana-3964	17	21	the	the	DET
cana-3964	17	22	development	development	NOUN
cana-3964	17	23	of	of	ADP
cana-3964	17	24	tumors	tumor	NOUN
cana-3964	17	25	,	,	PUNCT
cana-3964	17	26	which	which	PRON
cana-3964	17	27	may	may	AUX
cana-3964	17	28	be	be	AUX
cana-3964	17	29	categorized	categorize	VERB
cana-3964	17	30	as	as	ADP
cana-3964	17	31	either	either	CCONJ
cana-3964	17	32	benign	benign	ADJ
cana-3964	17	33	or	or	CCONJ
cana-3964	17	34	malignant	malignant	ADJ
cana-3964	17	35	.	.	PUNCT
cana-3964	18	1	breast	breast	NOUN
cana-3964	18	2	cancer	cancer	NOUN
cana-3964	18	3	affects	affect	VERB
cana-3964	18	4	individuals	individual	NOUN
cana-3964	18	5	of	of	ADP
cana-3964	18	6	all	all	DET
cana-3964	18	7	genders	gender	NOUN
cana-3964	18	8	,	,	PUNCT
cana-3964	18	9	though	though	SCONJ
cana-3964	18	10	it	it	PRON
cana-3964	18	11	is	be	AUX
cana-3964	18	12	more	more	ADV
cana-3964	18	13	commonly	commonly	ADV
cana-3964	18	14	diagnosed	diagnose	VERB
cana-3964	18	15	in	in	ADP
cana-3964	18	16	women	woman	NOUN
cana-3964	18	17	.	.	PUNCT
cana-3964	19	1	a	a	DET
cana-3964	19	2	new	new	ADJ
cana-3964	19	3	global	global	ADJ
cana-3964	19	4	breast	breast	PROPN
cana-3964	19	5	cancer	cancer	NOUN
cana-3964	19	6	initiative	initiative	NOUN
cana-3964	19	7	framework	framework	NOUN
cana-3964	19	8	was	be	AUX
cana-3964	19	9	announced	announce	VERB
cana-3964	19	10	by	by	ADP
cana-3964	19	11	the	the	DET
cana-3964	19	12	world	world	PROPN
cana-3964	19	13	health	health	PROPN
cana-3964	19	14	organization	organization	NOUN
cana-3964	19	15	(	(	PUNCT
cana-3964	19	16	who	who	PRON
cana-3964	19	17	)	)	PUNCT
cana-3964	19	18	in	in	ADP
cana-3964	19	19	2023	2023	NUM
cana-3964	19	20	with	with	ADP
cana-3964	19	21	the	the	DET
cana-3964	19	22	objective	objective	NOUN
cana-3964	19	23	of	of	ADP
cana-3964	19	24	offering	offer	VERB
cana-3964	19	25	a	a	DET
cana-3964	19	26	strategic	strategic	ADJ
cana-3964	19	27	route	route	NOUN
cana-3964	19	28	to	to	PART
cana-3964	19	29	reach	reach	VERB
cana-3964	19	30	the	the	DET
cana-3964	19	31	lofty	lofty	ADJ
cana-3964	19	32	target	target	NOUN
cana-3964	19	33	of	of	ADP
cana-3964	19	34	aims	aim	NOUN
cana-3964	19	35	to	to	PART
cana-3964	19	36	prevent	prevent	VERB
cana-3964	19	37	2.5	2.5	NUM
cana-3964	19	38	million	million	NUM
cana-3964	19	39	breast	breast	NOUN
cana-3964	19	40	cancer	cancer	NOUN
cana-3964	19	41	-	-	PUNCT
cana-3964	19	42	related	relate	VERB
cana-3964	19	43	deaths	death	NOUN
cana-3964	19	44	by	by	ADP
cana-3964	19	45	2040	2040	NUM
cana-3964	19	46	[	[	X
cana-3964	19	47	1	1	NUM
cana-3964	19	48	]	]	PUNCT
cana-3964	19	49	.	.	PUNCT
cana-3964	20	1	the	the	DET
cana-3964	20	2	framework	framework	NOUN
cana-3964	20	3	strongly	strongly	ADV
cana-3964	20	4	recommends	recommend	VERB
cana-3964	20	5	that	that	SCONJ
cana-3964	20	6	nations	nation	NOUN
cana-3964	20	7	adopt	adopt	VERB
cana-3964	20	8	three	three	NUM
cana-3964	20	9	fundamental	fundamental	ADJ
cana-3964	20	10	pillars	pillar	NOUN
cana-3964	20	11	of	of	ADP
cana-3964	20	12	action	action	NOUN
cana-3964	20	13	centred	centre	VERB
cana-3964	20	14	on	on	ADP
cana-3964	20	15	health	health	NOUN
cana-3964	20	16	promotion	promotion	NOUN
cana-3964	20	17	,	,	PUNCT
cana-3964	20	18	early	early	ADJ
cana-3964	20	19	discovery	discovery	NOUN
cana-3964	20	20	,	,	PUNCT
cana-3964	20	21	and	and	CCONJ
cana-3964	20	22	appropriate	appropriate	ADJ
cana-3964	20	23	diagnosis	diagnosis	NOUN
cana-3964	20	24	of	of	ADP
cana-3964	20	25	breast	breast	NOUN
cana-3964	20	26	cancer	cancer	NOUN
cana-3964	20	27	.	.	PUNCT
cana-3964	21	1	these	these	DET
cana-3964	21	2	strategic	strategic	ADJ
cana-3964	21	3	pillars	pillar	NOUN
cana-3964	21	4	are	be	AUX
cana-3964	21	5	envisioned	envision	VERB
cana-3964	21	6	as	as	ADP
cana-3964	21	7	the	the	DET
cana-3964	21	8	driving	drive	VERB
cana-3964	21	9	forces	force	NOUN
cana-3964	21	10	to	to	PART
cana-3964	21	11	meet	meet	VERB
cana-3964	21	12	the	the	DET
cana-3964	21	13	set	set	NOUN
cana-3964	21	14	targets	target	NOUN
cana-3964	21	15	.	.	PUNCT
cana-3964	22	1	this	this	DET
cana-3964	22	2	review	review	NOUN
cana-3964	22	3	paper	paper	NOUN
cana-3964	22	4	seeks	seek	VERB
cana-3964	22	5	to	to	PART
cana-3964	22	6	give	give	VERB
cana-3964	22	7	a	a	DET
cana-3964	22	8	summary	summary	NOUN
cana-3964	22	9	of	of	ADP
cana-3964	22	10	the	the	DET
cana-3964	22	11	various	various	ADJ
cana-3964	22	12	studies	study	NOUN
cana-3964	22	13	that	that	PRON
cana-3964	22	14	have	have	AUX
cana-3964	22	15	been	be	AUX
cana-3964	22	16	conducted	conduct	VERB
cana-3964	22	17	in	in	ADP
cana-3964	22	18	this	this	DET
cana-3964	22	19	area	area	NOUN
cana-3964	22	20	of	of	ADP
cana-3964	22	21	different	different	ADJ
cana-3964	22	22	ml	ml	NOUN
cana-3964	22	23	algorithms	algorithm	NOUN
cana-3964	22	24	.	.	PUNCT
cana-3964	23	1	in	in	ADP
cana-3964	23	2	this	this	DET
cana-3964	23	3	context	context	NOUN
cana-3964	23	4	,	,	PUNCT
cana-3964	23	5	38	38	NUM
cana-3964	23	6	studies	study	NOUN
cana-3964	23	7	published	publish	VERB
cana-3964	23	8	between	between	ADP
cana-3964	23	9	2016	2016	NUM
cana-3964	23	10	and	and	CCONJ
cana-3964	23	11	2024	2024	NUM
cana-3964	23	12	have	have	AUX
cana-3964	23	13	been	be	AUX
cana-3964	23	14	reviewed	review	VERB
cana-3964	23	15	,	,	PUNCT
cana-3964	23	16	covering	cover	VERB
cana-3964	23	17	a	a	DET
cana-3964	23	18	range	range	NOUN
cana-3964	23	19	of	of	ADP
cana-3964	23	20	approaches	approach	NOUN
cana-3964	23	21	,	,	PUNCT
cana-3964	23	22	including	include	VERB
cana-3964	23	23	“	"	PUNCT
cana-3964	23	24	logistic	logistic	ADJ
cana-3964	23	25	regression	regression	NOUN
cana-3964	23	26	,	,	PUNCT
cana-3964	23	27	decision	decision	NOUN
cana-3964	23	28	trees	tree	NOUN
cana-3964	23	29	,	,	PUNCT
cana-3964	23	30	k	k	NOUN
cana-3964	23	31	-	-	PUNCT
cana-3964	23	32	nearest	near	ADJ
cana-3964	23	33	neighbors	neighbor	NOUN
cana-3964	23	34	,	,	PUNCT
cana-3964	23	35	artificial	artificial	ADJ
cana-3964	23	36	neural	neural	ADJ
cana-3964	23	37	networks	network	NOUN
cana-3964	23	38	,	,	PUNCT
cana-3964	23	39	support	support	VERB
cana-3964	23	40	vector	vector	NOUN
cana-3964	23	41	machines	machine	NOUN
cana-3964	23	42	,	,	PUNCT
cana-3964	23	43	and	and	CCONJ
cana-3964	23	44	deep	deep	ADJ
cana-3964	23	45	learning	learning	NOUN
cana-3964	23	46	.	.	PUNCT
cana-3964	24	1	the	the	DET
cana-3964	24	2	wisconsin	wisconsin	PROPN
cana-3964	24	3	diagnostic	diagnostic	PROPN
cana-3964	24	4	breast	breast	NOUN
cana-3964	24	5	cancer	cancer	NOUN
cana-3964	24	6	(	(	PUNCT
cana-3964	24	7	wdbc	wdbc	PROPN
cana-3964	24	8	)	)	PUNCT
cana-3964	24	9	is	be	AUX
cana-3964	24	10	the	the	DET
cana-3964	24	11	reference	reference	NOUN
cana-3964	24	12	database	database	NOUN
cana-3964	24	13	used	use	VERB
cana-3964	24	14	communications	communication	NOUN
cana-3964	24	15	on	on	ADP
cana-3964	24	16	applied	apply	VERB
cana-3964	24	17	nonlinear	nonlinear	ADJ
cana-3964	24	18	analysis	analysis	NOUN
cana-3964	24	19	issn	issn	NOUN
cana-3964	24	20	:	:	PUNCT
cana-3964	24	21	1074	1074	NUM
cana-3964	24	22	-	-	PUNCT
cana-3964	24	23	133x	133x	NUM
cana-3964	24	24	vol	vol	NOUN
cana-3964	24	25	32	32	NUM
cana-3964	24	26	no	no	NOUN
cana-3964	24	27	.	.	PUNCT
cana-3964	25	1	9s	9s	NUM
cana-3964	25	2	(	(	PUNCT
cana-3964	25	3	2025	2025	NUM
cana-3964	25	4	)	)	PUNCT
cana-3964	25	5	555	555	NUM
cana-3964	25	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	25	7	in	in	ADP
cana-3964	25	8	the	the	DET
cana-3964	25	9	majority	majority	NOUN
cana-3964	25	10	of	of	ADP
cana-3964	25	11	references	reference	NOUN
cana-3964	25	12	,	,	PUNCT
cana-3964	25	13	and	and	CCONJ
cana-3964	25	14	it	it	PRON
cana-3964	25	15	serves	serve	VERB
cana-3964	25	16	as	as	ADP
cana-3964	25	17	a	a	DET
cana-3964	25	18	standard	standard	NOUN
cana-3964	25	19	for	for	ADP
cana-3964	25	20	comparing	compare	VERB
cana-3964	25	21	the	the	DET
cana-3964	25	22	outcomes	outcome	NOUN
cana-3964	25	23	of	of	ADP
cana-3964	25	24	various	various	ADJ
cana-3964	25	25	methods	method	NOUN
cana-3964	25	26	.	.	PUNCT
cana-3964	26	1	breast	breast	NOUN
cana-3964	26	2	cancer	cancer	NOUN
cana-3964	26	3	is	be	AUX
cana-3964	26	4	the	the	DET
cana-3964	26	5	most	most	ADV
cana-3964	26	6	frequent	frequent	ADJ
cana-3964	26	7	type	type	NOUN
cana-3964	26	8	of	of	ADP
cana-3964	26	9	cancer	cancer	NOUN
cana-3964	26	10	in	in	ADP
cana-3964	26	11	people	people	NOUN
cana-3964	26	12	,	,	PUNCT
cana-3964	26	13	with	with	SCONJ
cana-3964	26	14	over	over	ADP
cana-3964	26	15	2.3	2.3	NUM
cana-3964	26	16	million	million	NUM
cana-3964	26	17	new	new	ADJ
cana-3964	26	18	cases	case	NOUN
cana-3964	26	19	reported	report	VERB
cana-3964	26	20	each	each	DET
cana-3964	26	21	year	year	NOUN
cana-3964	26	22	.	.	PUNCT
cana-3964	27	1	surprisingly	surprisingly	ADV
cana-3964	27	2	,	,	PUNCT
cana-3964	27	3	it	it	PRON
cana-3964	27	4	is	be	AUX
cana-3964	27	5	either	either	CCONJ
cana-3964	27	6	the	the	DET
cana-3964	27	7	leading	leading	ADJ
cana-3964	27	8	or	or	CCONJ
cana-3964	27	9	secondary	secondary	ADJ
cana-3964	27	10	cause	cause	NOUN
cana-3964	27	11	of	of	ADP
cana-3964	27	12	female	female	ADJ
cana-3964	27	13	cancer	cancer	NOUN
cana-3964	27	14	-	-	PUNCT
cana-3964	27	15	related	relate	VERB
cana-3964	27	16	mortality	mortality	NOUN
cana-3964	27	17	in	in	ADP
cana-3964	27	18	95	95	NUM
cana-3964	27	19	%	%	NOUN
cana-3964	27	20	of	of	ADP
cana-3964	27	21	countries	country	NOUN
cana-3964	27	22	.	.	PUNCT
cana-3964	28	1	despite	despite	SCONJ
cana-3964	28	2	these	these	DET
cana-3964	28	3	alarming	alarming	ADJ
cana-3964	28	4	statistics	statistic	NOUN
cana-3964	28	5	,	,	PUNCT
cana-3964	28	6	survival	survival	NOUN
cana-3964	28	7	rates	rate	NOUN
cana-3964	28	8	for	for	ADP
cana-3964	28	9	breast	breast	NOUN
cana-3964	28	10	cancer	cancer	NOUN
cana-3964	28	11	exhibit	exhibit	VERB
cana-3964	28	12	substantial	substantial	ADJ
cana-3964	28	13	disparities	disparity	NOUN
cana-3964	28	14	both	both	PRON
cana-3964	28	15	between	between	ADP
cana-3964	28	16	countries	country	NOUN
cana-3964	28	17	and	and	CCONJ
cana-3964	28	18	within	within	ADP
cana-3964	28	19	them	they	PRON
cana-3964	28	20	.	.	PUNCT
cana-3964	29	1	unfortunately	unfortunately	ADV
cana-3964	29	2	,	,	PUNCT
cana-3964	29	3	around	around	ADP
cana-3964	29	4	eighty	eighty	NUM
cana-3964	29	5	percent	percent	NOUN
cana-3964	29	6	of	of	ADP
cana-3964	29	7	deaths	death	NOUN
cana-3964	29	8	from	from	ADP
cana-3964	29	9	cervical	cervical	ADJ
cana-3964	29	10	and	and	CCONJ
cana-3964	29	11	breast	breast	NOUN
cana-3964	29	12	cancer	cancer	NOUN
cana-3964	29	13	happen	happen	VERB
cana-3964	29	14	in	in	ADP
cana-3964	29	15	countries	country	NOUN
cana-3964	29	16	of	of	ADP
cana-3964	29	17	low	low	ADJ
cana-3964	29	18	and	and	CCONJ
cana-3964	29	19	middle	middle	ADJ
cana-3964	29	20	income	income	NOUN
cana-3964	29	21	.	.	PUNCT
cana-3964	30	1	age	age	NOUN
cana-3964	30	2	,	,	PUNCT
cana-3964	30	3	a	a	DET
cana-3964	30	4	family	family	NOUN
cana-3964	30	5	history	history	NOUN
cana-3964	30	6	of	of	ADP
cana-3964	30	7	the	the	DET
cana-3964	30	8	condition	condition	NOUN
cana-3964	30	9	,	,	PUNCT
cana-3964	30	10	certain	certain	ADJ
cana-3964	30	11	genetic	genetic	ADJ
cana-3964	30	12	mutations	mutation	NOUN
cana-3964	30	13	,	,	PUNCT
cana-3964	30	14	hormonal	hormonal	ADJ
cana-3964	30	15	changes	change	NOUN
cana-3964	30	16	,	,	PUNCT
cana-3964	30	17	and	and	CCONJ
cana-3964	30	18	environmental	environmental	ADJ
cana-3964	30	19	variables	variable	NOUN
cana-3964	30	20	are	be	AUX
cana-3964	30	21	among	among	ADP
cana-3964	30	22	the	the	DET
cana-3964	30	23	risk	risk	NOUN
cana-3964	30	24	factors	factor	NOUN
cana-3964	30	25	for	for	ADP
cana-3964	30	26	bc	bc	PROPN
cana-3964	30	27	.	.	PROPN
cana-3964	31	1	early	early	ADJ
cana-3964	31	2	detection	detection	NOUN
cana-3964	31	3	and	and	CCONJ
cana-3964	31	4	correct	correct	ADJ
cana-3964	31	5	treatment	treatment	NOUN
cana-3964	31	6	play	play	VERB
cana-3964	31	7	a	a	DET
cana-3964	31	8	crucial	crucial	ADJ
cana-3964	31	9	role	role	NOUN
cana-3964	31	10	in	in	ADP
cana-3964	31	11	improving	improve	VERB
cana-3964	31	12	the	the	DET
cana-3964	31	13	survival	survival	NOUN
cana-3964	31	14	rates	rate	NOUN
cana-3964	31	15	for	for	ADP
cana-3964	31	16	the	the	DET
cana-3964	31	17	diagnosis	diagnosis	NOUN
cana-3964	31	18	of	of	ADP
cana-3964	31	19	bc	bc	PROPN
cana-3964	32	1	[	[	X
cana-3964	32	2	2	2	NUM
cana-3964	32	3	]	]	PUNCT
cana-3964	32	4	.	.	PUNCT
cana-3964	33	1	machine	machine	NOUN
cana-3964	33	2	learning	learning	NOUN
cana-3964	33	3	allows	allow	VERB
cana-3964	33	4	computers	computer	NOUN
cana-3964	33	5	to	to	PART
cana-3964	33	6	learn	learn	VERB
cana-3964	33	7	from	from	ADP
cana-3964	33	8	data	datum	NOUN
cana-3964	33	9	and	and	CCONJ
cana-3964	33	10	expand	expand	VERB
cana-3964	33	11	performance	performance	NOUN
cana-3964	33	12	without	without	ADP
cana-3964	33	13	explicit	explicit	ADJ
cana-3964	33	14	programming	programming	NOUN
cana-3964	33	15	.	.	PUNCT
cana-3964	34	1	they	they	PRON
cana-3964	34	2	cover	cover	VERB
cana-3964	34	3	various	various	ADJ
cana-3964	34	4	methods	method	NOUN
cana-3964	34	5	,	,	PUNCT
cana-3964	34	6	including	include	VERB
cana-3964	34	7	unsupervised	unsupervised	ADJ
cana-3964	34	8	learning	learning	NOUN
cana-3964	34	9	(	(	PUNCT
cana-3964	34	10	which	which	PRON
cana-3964	34	11	finds	find	VERB
cana-3964	34	12	patterns	pattern	NOUN
cana-3964	34	13	in	in	ADP
cana-3964	34	14	unlabelled	unlabelled	ADJ
cana-3964	34	15	data	datum	NOUN
cana-3964	34	16	)	)	PUNCT
cana-3964	34	17	and	and	CCONJ
cana-3964	34	18	supervised	supervised	ADJ
cana-3964	34	19	learning	learning	NOUN
cana-3964	34	20	(	(	PUNCT
cana-3964	34	21	which	which	PRON
cana-3964	34	22	teaches	teach	VERB
cana-3964	34	23	models	model	NOUN
cana-3964	34	24	from	from	ADP
cana-3964	34	25	labelled	label	VERB
cana-3964	34	26	examples	example	NOUN
cana-3964	34	27	)	)	PUNCT
cana-3964	34	28	.	.	PUNCT
cana-3964	35	1	reinforcement	reinforcement	NOUN
cana-3964	35	2	learning	learning	NOUN
cana-3964	35	3	enables	enable	VERB
cana-3964	35	4	systems	system	NOUN
cana-3964	35	5	to	to	PART
cana-3964	35	6	make	make	VERB
cana-3964	35	7	decisions	decision	NOUN
cana-3964	35	8	through	through	ADP
cana-3964	35	9	trial	trial	NOUN
cana-3964	35	10	and	and	CCONJ
cana-3964	35	11	error	error	NOUN
cana-3964	35	12	.	.	PUNCT
cana-3964	36	1	deep	deep	ADJ
cana-3964	36	2	learning	learning	NOUN
cana-3964	36	3	employs	employ	VERB
cana-3964	36	4	neural	neural	ADJ
cana-3964	36	5	networks	network	NOUN
cana-3964	36	6	to	to	PART
cana-3964	36	7	handle	handle	VERB
cana-3964	36	8	complex	complex	ADJ
cana-3964	36	9	tasks	task	NOUN
cana-3964	36	10	like	like	ADP
cana-3964	36	11	image	image	NOUN
cana-3964	36	12	and	and	CCONJ
cana-3964	36	13	speech	speech	NOUN
cana-3964	36	14	recognition	recognition	NOUN
cana-3964	36	15	.	.	PUNCT
cana-3964	37	1	a	a	DET
cana-3964	37	2	hybrid	hybrid	ADJ
cana-3964	37	3	technique	technique	NOUN
cana-3964	37	4	for	for	ADP
cana-3964	37	5	bc	bc	PROPN
cana-3964	37	6	prediction	prediction	NOUN
cana-3964	37	7	based	base	VERB
cana-3964	37	8	on	on	ADP
cana-3964	37	9	machine	machine	NOUN
cana-3964	37	10	learning	learning	NOUN
cana-3964	37	11	was	be	AUX
cana-3964	37	12	given	give	VERB
cana-3964	37	13	[	[	X
cana-3964	37	14	3	3	NUM
cana-3964	37	15	]	]	PUNCT
cana-3964	37	16	.	.	PUNCT
cana-3964	38	1	the	the	DET
cana-3964	38	2	ability	ability	NOUN
cana-3964	38	3	of	of	ADP
cana-3964	38	4	dl	dl	PROPN
cana-3964	38	5	models	model	NOUN
cana-3964	38	6	to	to	PART
cana-3964	38	7	accurately	accurately	ADV
cana-3964	38	8	identify	identify	VERB
cana-3964	38	9	metastatic	metastatic	ADJ
cana-3964	38	10	lymph	lymph	NOUN
cana-3964	38	11	nodes	node	NOUN
cana-3964	38	12	,	,	PUNCT
cana-3964	38	13	a	a	DET
cana-3964	38	14	critical	critical	ADJ
cana-3964	38	15	component	component	NOUN
cana-3964	38	16	of	of	ADP
cana-3964	38	17	staging	staging	NOUN
cana-3964	38	18	and	and	CCONJ
cana-3964	38	19	therapy	therapy	NOUN
cana-3964	38	20	planning	planning	NOUN
cana-3964	38	21	was	be	AUX
cana-3964	38	22	highlighted	highlight	VERB
cana-3964	38	23	by	by	ADP
cana-3964	38	24	their	their	PRON
cana-3964	38	25	work	work	NOUN
cana-3964	38	26	[	[	X
cana-3964	38	27	4	4	NUM
cana-3964	38	28	]	]	PUNCT
cana-3964	38	29	.	.	PUNCT
cana-3964	39	1	the	the	DET
cana-3964	39	2	svm	svm	PROPN
cana-3964	39	3	method	method	NOUN
cana-3964	39	4	yielded	yield	VERB
cana-3964	39	5	the	the	DET
cana-3964	39	6	best	good	ADJ
cana-3964	39	7	result	result	NOUN
cana-3964	39	8	,	,	PUNCT
cana-3964	39	9	suggesting	suggest	VERB
cana-3964	39	10	its	its	PRON
cana-3964	39	11	potential	potential	NOUN
cana-3964	39	12	for	for	ADP
cana-3964	39	13	usage	usage	NOUN
cana-3964	39	14	in	in	ADP
cana-3964	39	15	clinical	clinical	ADJ
cana-3964	39	16	applications	application	NOUN
cana-3964	39	17	with	with	ADP
cana-3964	39	18	97.14	97.14	NUM
cana-3964	39	19	%	%	NOUN
cana-3964	39	20	accuracy	accuracy	NOUN
cana-3964	40	1	[	[	X
cana-3964	40	2	5	5	NUM
cana-3964	40	3	]	]	PUNCT
cana-3964	40	4	.	.	PUNCT
cana-3964	41	1	it	it	PRON
cana-3964	41	2	is	be	AUX
cana-3964	41	3	found	find	VERB
cana-3964	41	4	that	that	SCONJ
cana-3964	41	5	the	the	DET
cana-3964	41	6	svm	svm	PROPN
cana-3964	41	7	got	get	VERB
cana-3964	41	8	the	the	DET
cana-3964	41	9	highest	high	ADJ
cana-3964	41	10	94.44	94.44	NUM
cana-3964	41	11	%	%	NOUN
cana-3964	41	12	accuracy	accuracy	NOUN
cana-3964	42	1	[	[	X
cana-3964	42	2	6	6	NUM
cana-3964	42	3	]	]	PUNCT
cana-3964	42	4	.	.	PUNCT
cana-3964	43	1	[	[	X
cana-3964	43	2	7	7	X
cana-3964	43	3	]	]	PUNCT
cana-3964	43	4	evaluated	evaluate	VERB
cana-3964	43	5	the	the	DET
cana-3964	43	6	effectiveness	effectiveness	NOUN
cana-3964	43	7	of	of	ADP
cana-3964	43	8	ml	ml	ADP
cana-3964	43	9	algorithms	algorithm	NOUN
cana-3964	43	10	and	and	CCONJ
cana-3964	43	11	discovered	discover	VERB
cana-3964	43	12	that	that	SCONJ
cana-3964	43	13	svm	svm	PROPN
cana-3964	43	14	produces	produce	VERB
cana-3964	43	15	the	the	DET
cana-3964	43	16	best	good	ADJ
cana-3964	43	17	result	result	NOUN
cana-3964	43	18	with	with	ADP
cana-3964	43	19	97.5	97.5	NUM
cana-3964	43	20	%	%	NOUN
cana-3964	43	21	accuracy	accuracy	NOUN
cana-3964	43	22	.	.	PUNCT
cana-3964	44	1	[	[	X
cana-3964	44	2	8	8	NUM
cana-3964	44	3	]	]	PUNCT
cana-3964	44	4	focused	focus	VERB
cana-3964	44	5	on	on	ADP
cana-3964	44	6	diagnostic	diagnostic	ADJ
cana-3964	44	7	accuracy	accuracy	NOUN
cana-3964	44	8	as	as	ADV
cana-3964	44	9	well	well	ADV
cana-3964	44	10	as	as	ADP
cana-3964	44	11	predicting	predict	VERB
cana-3964	44	12	the	the	DET
cana-3964	44	13	prognosis	prognosis	NOUN
cana-3964	44	14	of	of	ADP
cana-3964	44	15	bc	bc	PROPN
cana-3964	44	16	.	.	PROPN
cana-3964	45	1	in	in	ADP
cana-3964	45	2	a	a	DET
cana-3964	45	3	study	study	NOUN
cana-3964	45	4	,	,	PUNCT
cana-3964	45	5	the	the	DET
cana-3964	45	6	knn	knn	PROPN
cana-3964	45	7	approach	approach	NOUN
cana-3964	45	8	found	find	VERB
cana-3964	45	9	an	an	DET
cana-3964	45	10	accuracy	accuracy	NOUN
cana-3964	45	11	of	of	ADP
cana-3964	45	12	95.61	95.61	NUM
cana-3964	45	13	%	%	NOUN
cana-3964	45	14	using	use	VERB
cana-3964	45	15	the	the	DET
cana-3964	45	16	wisconsin	wisconsin	PROPN
cana-3964	45	17	breast	breast	NOUN
cana-3964	45	18	cancer	cancer	NOUN
cana-3964	45	19	dataset	dataset	VERB
cana-3964	46	1	[	[	X
cana-3964	46	2	9	9	NUM
cana-3964	46	3	]	]	PUNCT
cana-3964	46	4	.	.	PUNCT
cana-3964	47	1	[	[	X
cana-3964	47	2	10	10	NUM
cana-3964	47	3	]	]	PUNCT
cana-3964	47	4	designed	design	VERB
cana-3964	47	5	an	an	DET
cana-3964	47	6	mlp	mlp	NOUN
cana-3964	47	7	model	model	NOUN
cana-3964	47	8	that	that	PRON
cana-3964	47	9	incorporated	incorporate	VERB
cana-3964	47	10	feature	feature	NOUN
cana-3964	47	11	selection	selection	NOUN
cana-3964	47	12	and	and	CCONJ
cana-3964	47	13	data	datum	NOUN
cana-3964	47	14	balancing	balance	VERB
cana-3964	47	15	techniques	technique	NOUN
cana-3964	47	16	,	,	PUNCT
cana-3964	47	17	achieving	achieve	VERB
cana-3964	47	18	an	an	DET
cana-3964	47	19	accuracy	accuracy	NOUN
cana-3964	47	20	of	of	ADP
cana-3964	47	21	97.70	97.70	NUM
cana-3964	47	22	%	%	NOUN
cana-3964	47	23	and	and	CCONJ
cana-3964	47	24	demonstrating	demonstrate	VERB
cana-3964	47	25	its	its	PRON
cana-3964	47	26	potential	potential	NOUN
cana-3964	47	27	for	for	ADP
cana-3964	47	28	clinical	clinical	ADJ
cana-3964	47	29	applications	application	NOUN
cana-3964	47	30	.	.	PUNCT
cana-3964	48	1	[	[	X
cana-3964	48	2	11	11	NUM
cana-3964	48	3	]	]	PUNCT
cana-3964	48	4	offered	offer	VERB
cana-3964	48	5	an	an	DET
cana-3964	48	6	analysis	analysis	NOUN
cana-3964	48	7	of	of	ADP
cana-3964	48	8	several	several	ADJ
cana-3964	48	9	ml	ml	NOUN
cana-3964	48	10	methods	method	NOUN
cana-3964	48	11	applied	apply	VERB
cana-3964	48	12	to	to	ADP
cana-3964	48	13	the	the	DET
cana-3964	48	14	diagnosis	diagnosis	NOUN
cana-3964	48	15	of	of	ADP
cana-3964	48	16	bc	bc	PROPN
cana-3964	48	17	,	,	PUNCT
cana-3964	48	18	emphasizing	emphasize	VERB
cana-3964	48	19	the	the	DET
cana-3964	48	20	high	high	ADJ
cana-3964	48	21	classification	classification	NOUN
cana-3964	48	22	accuracy	accuracy	NOUN
cana-3964	48	23	attained	attain	VERB
cana-3964	48	24	by	by	ADP
cana-3964	48	25	dts	dts	NOUN
cana-3964	48	26	,	,	PUNCT
cana-3964	48	27	svms	svms	NOUN
cana-3964	48	28	,	,	PUNCT
cana-3964	48	29	and	and	CCONJ
cana-3964	48	30	anns	ann	NOUN
cana-3964	48	31	.	.	PUNCT
cana-3964	49	1	in	in	ADP
cana-3964	49	2	a	a	DET
cana-3964	49	3	study	study	NOUN
cana-3964	49	4	comparing	compare	VERB
cana-3964	49	5	ml	ml	NOUN
cana-3964	49	6	algorithms	algorithm	NOUN
cana-3964	49	7	discovered	discover	VERB
cana-3964	49	8	that	that	SCONJ
cana-3964	49	9	the	the	DET
cana-3964	49	10	random	random	ADJ
cana-3964	49	11	forest	forest	NOUN
cana-3964	49	12	algorithm	algorithm	NOUN
cana-3964	49	13	outperformed	outperform	VERB
cana-3964	49	14	in	in	ADP
cana-3964	49	15	the	the	DET
cana-3964	49	16	context	context	NOUN
cana-3964	49	17	of	of	ADP
cana-3964	49	18	accuracy	accuracy	NOUN
cana-3964	49	19	and	and	CCONJ
cana-3964	49	20	f1	f1	NOUN
cana-3964	49	21	-	-	PUNCT
cana-3964	49	22	score	score	NOUN
cana-3964	49	23	[	[	X
cana-3964	49	24	12	12	NUM
cana-3964	49	25	]	]	PUNCT
cana-3964	49	26	.	.	PUNCT
cana-3964	50	1	in	in	ADP
cana-3964	50	2	[	[	X
cana-3964	50	3	13	13	NUM
cana-3964	50	4	]	]	PUNCT
cana-3964	50	5	different	different	ADJ
cana-3964	50	6	models	model	NOUN
cana-3964	50	7	and	and	CCONJ
cana-3964	50	8	found	find	VERB
cana-3964	50	9	that	that	SCONJ
cana-3964	50	10	svm	svm	PROPN
cana-3964	50	11	and	and	CCONJ
cana-3964	50	12	rf	rf	NOUN
cana-3964	50	13	were	be	AUX
cana-3964	50	14	the	the	DET
cana-3964	50	15	best	good	ADJ
cana-3964	50	16	models	model	NOUN
cana-3964	50	17	,	,	PUNCT
cana-3964	50	18	achieving	achieve	VERB
cana-3964	50	19	an	an	DET
cana-3964	50	20	accuracy	accuracy	NOUN
cana-3964	50	21	of	of	ADP
cana-3964	50	22	95.1739	95.1739	NUM
cana-3964	50	23	%	%	NOUN
cana-3964	50	24	.	.	PUNCT
cana-3964	51	1	[	[	X
cana-3964	51	2	14	14	NUM
cana-3964	51	3	]	]	X
cana-3964	51	4	utilized	utilize	VERB
cana-3964	51	5	ensemble	ensemble	ADJ
cana-3964	51	6	learning	learning	NOUN
cana-3964	51	7	for	for	ADP
cana-3964	51	8	breast	breast	NOUN
cana-3964	51	9	cancer	cancer	NOUN
cana-3964	51	10	detection	detection	NOUN
cana-3964	51	11	with	with	ADP
cana-3964	51	12	an	an	DET
cana-3964	51	13	accuracy	accuracy	NOUN
cana-3964	51	14	of	of	ADP
cana-3964	51	15	99.30	99.30	NUM
cana-3964	51	16	%	%	NOUN
cana-3964	51	17	.	.	PUNCT
cana-3964	52	1	[	[	X
cana-3964	52	2	15	15	NUM
cana-3964	52	3	]	]	PUNCT
cana-3964	52	4	compared	compare	VERB
cana-3964	52	5	the	the	DET
cana-3964	52	6	svm	svm	PROPN
cana-3964	52	7	and	and	CCONJ
cana-3964	52	8	ann	ann	PROPN
cana-3964	52	9	and	and	CCONJ
cana-3964	52	10	identified	identify	VERB
cana-3964	52	11	that	that	SCONJ
cana-3964	52	12	the	the	DET
cana-3964	52	13	svm	svm	NOUN
cana-3964	52	14	was	be	AUX
cana-3964	52	15	more	more	ADV
cana-3964	52	16	accurate	accurate	ADJ
cana-3964	52	17	in	in	ADP
cana-3964	52	18	detecting	detect	VERB
cana-3964	52	19	breast	breast	NOUN
cana-3964	52	20	cancer	cancer	NOUN
cana-3964	52	21	.	.	PUNCT
cana-3964	53	1	[	[	X
cana-3964	53	2	16	16	NUM
cana-3964	53	3	]	]	PUNCT
cana-3964	53	4	evaluated	evaluate	VERB
cana-3964	53	5	the	the	DET
cana-3964	53	6	performance	performance	NOUN
cana-3964	53	7	of	of	ADP
cana-3964	53	8	ann	ann	PROPN
cana-3964	53	9	and	and	CCONJ
cana-3964	53	10	decision	decision	NOUN
cana-3964	53	11	trees	tree	NOUN
cana-3964	53	12	and	and	CCONJ
cana-3964	53	13	observed	observe	VERB
cana-3964	53	14	that	that	SCONJ
cana-3964	53	15	ann	ann	PROPN
cana-3964	53	16	provides	provide	VERB
cana-3964	53	17	the	the	DET
cana-3964	53	18	best	good	ADJ
cana-3964	53	19	result.[17	result.[17	NOUN
cana-3964	53	20	]	]	PUNCT
cana-3964	53	21	employed	employ	VERB
cana-3964	53	22	feature	feature	NOUN
cana-3964	53	23	selection	selection	NOUN
cana-3964	53	24	techniques	technique	NOUN
cana-3964	53	25	and	and	CCONJ
cana-3964	53	26	achieved	achieve	VERB
cana-3964	53	27	97.45	97.45	NUM
cana-3964	53	28	%	%	NOUN
cana-3964	53	29	accuracy	accuracy	NOUN
cana-3964	53	30	by	by	ADP
cana-3964	53	31	using	use	VERB
cana-3964	53	32	a	a	DET
cana-3964	53	33	using	use	VERB
cana-3964	53	34	a	a	DET
cana-3964	53	35	random	random	ADJ
cana-3964	53	36	forest	forest	NOUN
cana-3964	53	37	algorithm	algorithm	NOUN
cana-3964	53	38	.	.	PUNCT
cana-3964	54	1	[	[	X
cana-3964	54	2	18	18	NUM
cana-3964	54	3	]	]	PUNCT
cana-3964	54	4	proposed	propose	VERB
cana-3964	54	5	an	an	DET
cana-3964	54	6	ensemble	ensemble	ADJ
cana-3964	54	7	ml	ml	X
cana-3964	54	8	approach	approach	NOUN
cana-3964	54	9	and	and	CCONJ
cana-3964	54	10	got	get	VERB
cana-3964	54	11	an	an	DET
cana-3964	54	12	accuracy	accuracy	NOUN
cana-3964	54	13	of	of	ADP
cana-3964	54	14	97	97	NUM
cana-3964	54	15	%	%	NOUN
cana-3964	54	16	by	by	ADP
cana-3964	54	17	combining	combine	VERB
cana-3964	54	18	multiple	multiple	ADJ
cana-3964	54	19	ml	ml	NOUN
cana-3964	54	20	models	model	NOUN
cana-3964	54	21	.	.	PUNCT
cana-3964	55	1	[	[	X
cana-3964	55	2	19	19	NUM
cana-3964	55	3	]	]	PUNCT
cana-3964	55	4	compared	compare	VERB
cana-3964	55	5	mlp	mlp	PROPN
cana-3964	55	6	and	and	CCONJ
cana-3964	55	7	cnn	cnn	PROPN
cana-3964	55	8	models	model	NOUN
cana-3964	55	9	and	and	CCONJ
cana-3964	55	10	found	find	VERB
cana-3964	55	11	that	that	SCONJ
cana-3964	55	12	cnn	cnn	PROPN
cana-3964	55	13	has	have	VERB
cana-3964	55	14	higher	high	ADJ
cana-3964	55	15	accuracy	accuracy	NOUN
cana-3964	55	16	than	than	ADP
cana-3964	55	17	mlp	mlp	PROPN
cana-3964	55	18	in	in	ADP
cana-3964	55	19	breast	breast	NOUN
cana-3964	55	20	cancer	cancer	NOUN
cana-3964	55	21	detection	detection	NOUN
cana-3964	55	22	.	.	PUNCT
cana-3964	56	1	[	[	X
cana-3964	56	2	20	20	NUM
cana-3964	56	3	]	]	PUNCT
cana-3964	56	4	developed	develop	VERB
cana-3964	56	5	an	an	DET
cana-3964	56	6	improved	improved	ADJ
cana-3964	56	7	predictive	predictive	ADJ
cana-3964	56	8	model	model	NOUN
cana-3964	56	9	using	use	VERB
cana-3964	56	10	ml	ml	VERB
cana-3964	56	11	.	.	PUNCT
cana-3964	57	1	in	in	ADP
cana-3964	57	2	this	this	DET
cana-3964	57	3	study	study	NOUN
cana-3964	57	4	,	,	PUNCT
cana-3964	57	5	the	the	DET
cana-3964	57	6	polynomial	polynomial	ADJ
cana-3964	57	7	svm	svm	NOUN
cana-3964	57	8	achieved	achieve	VERB
cana-3964	57	9	an	an	DET
cana-3964	57	10	accuracy	accuracy	NOUN
cana-3964	57	11	of	of	ADP
cana-3964	57	12	99.12%.[21	99.12%.[21	NOUN
cana-3964	57	13	]	]	PUNCT
cana-3964	57	14	proposed	propose	VERB
cana-3964	57	15	an	an	DET
cana-3964	57	16	optimized	optimize	VERB
cana-3964	57	17	framework	framework	NOUN
cana-3964	57	18	for	for	ADP
cana-3964	57	19	bc	bc	PROPN
cana-3964	57	20	classification	classification	NOUN
cana-3964	57	21	,	,	PUNCT
cana-3964	57	22	achieving	achieve	VERB
cana-3964	57	23	a	a	DET
cana-3964	57	24	high	high	ADJ
cana-3964	57	25	accuracy	accuracy	NOUN
cana-3964	57	26	of	of	ADP
cana-3964	57	27	99.86	99.86	NUM
cana-3964	57	28	%	%	NOUN
cana-3964	57	29	.	.	PUNCT
cana-3964	58	1	[	[	X
cana-3964	58	2	22	22	NUM
cana-3964	58	3	]	]	PUNCT
cana-3964	58	4	investigated	investigate	VERB
cana-3964	58	5	bc	bc	PROPN
cana-3964	58	6	detection	detection	NOUN
cana-3964	58	7	with	with	ADP
cana-3964	58	8	machine	machine	NOUN
cana-3964	58	9	learning	learning	NOUN
cana-3964	58	10	,	,	PUNCT
cana-3964	58	11	with	with	ADP
cana-3964	58	12	the	the	DET
cana-3964	58	13	xgboost	xgboost	PROPN
cana-3964	58	14	algorithm	algorithm	PROPN
cana-3964	58	15	achieving	achieve	VERB
cana-3964	58	16	an	an	DET
cana-3964	58	17	accuracy	accuracy	NOUN
cana-3964	58	18	of	of	ADP
cana-3964	58	19	98.24	98.24	NUM
cana-3964	58	20	%	%	NOUN
cana-3964	58	21	.	.	PUNCT
cana-3964	59	1	[	[	X
cana-3964	59	2	23	23	NUM
cana-3964	59	3	]	]	PUNCT
cana-3964	59	4	designed	design	VERB
cana-3964	59	5	a	a	DET
cana-3964	59	6	breast	breast	NOUN
cana-3964	59	7	cancer	cancer	NOUN
cana-3964	59	8	detection	detection	NOUN
cana-3964	59	9	model	model	NOUN
cana-3964	59	10	using	use	VERB
cana-3964	59	11	thermographic	thermographic	ADJ
cana-3964	59	12	images	image	NOUN
cana-3964	59	13	,	,	PUNCT
cana-3964	59	14	and	and	CCONJ
cana-3964	59	15	cnn	cnn	PROPN
cana-3964	59	16	outperformed	outperform	VERB
cana-3964	59	17	ml	ml	NOUN
cana-3964	59	18	models	model	NOUN
cana-3964	59	19	with	with	ADP
cana-3964	59	20	99.65	99.65	NUM
cana-3964	59	21	%	%	NOUN
cana-3964	59	22	accuracy	accuracy	NOUN
cana-3964	59	23	.	.	PUNCT
cana-3964	60	1	[	[	X
cana-3964	60	2	24	24	NUM
cana-3964	60	3	]	]	PUNCT
cana-3964	60	4	developed	develop	VERB
cana-3964	60	5	a	a	DET
cana-3964	60	6	bc	bc	PROPN
cana-3964	60	7	diagnosis	diagnosis	NOUN
cana-3964	60	8	method	method	NOUN
cana-3964	60	9	based	base	VERB
cana-3964	60	10	on	on	ADP
cana-3964	60	11	image	image	NOUN
cana-3964	60	12	processing	processing	NOUN
cana-3964	60	13	communications	communication	NOUN
cana-3964	60	14	on	on	ADP
cana-3964	60	15	applied	apply	VERB
cana-3964	60	16	nonlinear	nonlinear	ADJ
cana-3964	60	17	analysis	analysis	NOUN
cana-3964	60	18	issn	issn	NOUN
cana-3964	60	19	:	:	PUNCT
cana-3964	60	20	1074	1074	NUM
cana-3964	60	21	-	-	PUNCT
cana-3964	60	22	133x	133x	NUM
cana-3964	60	23	vol	vol	NOUN
cana-3964	60	24	32	32	NUM
cana-3964	60	25	no	no	NOUN
cana-3964	60	26	.	.	PUNCT
cana-3964	61	1	9s	9s	NUM
cana-3964	61	2	(	(	PUNCT
cana-3964	61	3	2025	2025	NUM
cana-3964	61	4	)	)	PUNCT
cana-3964	61	5	556	556	NUM
cana-3964	61	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	61	7	and	and	CCONJ
cana-3964	61	8	segmentation	segmentation	NOUN
cana-3964	61	9	techniques	technique	NOUN
cana-3964	61	10	,	,	PUNCT
cana-3964	61	11	achieving	achieve	VERB
cana-3964	61	12	a	a	DET
cana-3964	61	13	high	high	ADJ
cana-3964	61	14	accuracy	accuracy	NOUN
cana-3964	61	15	rate	rate	NOUN
cana-3964	61	16	of	of	ADP
cana-3964	61	17	96.8	96.8	NUM
cana-3964	61	18	%	%	NOUN
cana-3964	61	19	.	.	PUNCT
cana-3964	62	1	[	[	X
cana-3964	62	2	25	25	NUM
cana-3964	62	3	]	]	PUNCT
cana-3964	62	4	developed	develop	VERB
cana-3964	62	5	a	a	DET
cana-3964	62	6	deep	deep	ADJ
cana-3964	62	7	nnbased	nnbase	VERB
cana-3964	62	8	computer	computer	NOUN
cana-3964	62	9	-	-	PUNCT
cana-3964	62	10	aided	aid	VERB
cana-3964	62	11	diagnosis	diagnosis	NOUN
cana-3964	62	12	system	system	NOUN
cana-3964	62	13	in	in	ADP
cana-3964	62	14	which	which	PRON
cana-3964	62	15	transfer	transfer	NOUN
cana-3964	62	16	learning	learning	NOUN
cana-3964	62	17	was	be	AUX
cana-3964	62	18	used	use	VERB
cana-3964	62	19	and	and	CCONJ
cana-3964	62	20	achieved	achieve	VERB
cana-3964	62	21	an	an	DET
cana-3964	62	22	accuracy	accuracy	NOUN
cana-3964	62	23	of	of	ADP
cana-3964	62	24	99.70%.[26	99.70%.[26	NUM
cana-3964	62	25	]	]	PUNCT
cana-3964	62	26	designed	design	VERB
cana-3964	62	27	a	a	DET
cana-3964	62	28	deep	deep	ADJ
cana-3964	62	29	learning	learning	NOUN
cana-3964	62	30	approach	approach	NOUN
cana-3964	62	31	for	for	ADP
cana-3964	62	32	early	early	ADJ
cana-3964	62	33	-	-	PUNCT
cana-3964	62	34	stage	stage	NOUN
cana-3964	62	35	bc	bc	PROPN
cana-3964	62	36	diagnosis	diagnosis	NOUN
cana-3964	62	37	,	,	PUNCT
cana-3964	62	38	achieving	achieve	VERB
cana-3964	62	39	an	an	DET
cana-3964	62	40	accuracy	accuracy	NOUN
cana-3964	62	41	rate	rate	NOUN
cana-3964	62	42	of	of	ADP
cana-3964	62	43	97.2	97.2	NUM
cana-3964	62	44	%	%	NOUN
cana-3964	62	45	with	with	ADP
cana-3964	62	46	a	a	DET
cana-3964	62	47	hybrid	hybrid	ADJ
cana-3964	62	48	optimization	optimization	NOUN
cana-3964	62	49	technique	technique	NOUN
cana-3964	62	50	.	.	PUNCT
cana-3964	63	1	[	[	X
cana-3964	63	2	27	27	NUM
cana-3964	63	3	]	]	X
cana-3964	63	4	classified	classified	ADJ
cana-3964	63	5	breast	breast	NOUN
cana-3964	63	6	cancer	cancer	NOUN
cana-3964	63	7	metastases	metastasis	NOUN
cana-3964	63	8	,	,	PUNCT
cana-3964	63	9	and	and	CCONJ
cana-3964	63	10	their	their	PRON
cana-3964	63	11	decision	decision	NOUN
cana-3964	63	12	tree	tree	NOUN
cana-3964	63	13	method	method	NOUN
cana-3964	63	14	had	have	VERB
cana-3964	63	15	an	an	DET
cana-3964	63	16	83	83	NUM
cana-3964	63	17	%	%	NOUN
cana-3964	63	18	accuracy	accuracy	NOUN
cana-3964	63	19	rate	rate	NOUN
cana-3964	63	20	.	.	PUNCT
cana-3964	64	1	[	[	X
cana-3964	64	2	28	28	NUM
cana-3964	64	3	]	]	PUNCT
cana-3964	64	4	found	find	VERB
cana-3964	64	5	that	that	SCONJ
cana-3964	64	6	the	the	DET
cana-3964	64	7	svm	svm	ADJ
cana-3964	64	8	and	and	CCONJ
cana-3964	64	9	logistic	logistic	ADJ
cana-3964	64	10	regression	regression	NOUN
cana-3964	64	11	algorithms	algorithm	NOUN
cana-3964	64	12	had	have	VERB
cana-3964	64	13	the	the	DET
cana-3964	64	14	greatest	great	ADJ
cana-3964	64	15	accuracy	accuracy	NOUN
cana-3964	64	16	rate	rate	NOUN
cana-3964	64	17	of	of	ADP
cana-3964	64	18	99.12	99.12	NUM
cana-3964	64	19	%	%	NOUN
cana-3964	64	20	.	.	PUNCT
cana-3964	65	1	a	a	DET
cana-3964	65	2	decision	decision	NOUN
cana-3964	65	3	tree	tree	NOUN
cana-3964	65	4	was	be	AUX
cana-3964	65	5	used	use	VERB
cana-3964	65	6	to	to	PART
cana-3964	65	7	find	find	VERB
cana-3964	65	8	the	the	DET
cana-3964	65	9	category	category	NOUN
cana-3964	65	10	of	of	ADP
cana-3964	65	11	bc	bc	PROPN
cana-3964	65	12	c	c	PROPN
cana-3964	66	1	[	[	X
cana-3964	66	2	29]and	29]and	PROPN
cana-3964	66	3	got	get	VERB
cana-3964	66	4	an	an	DET
cana-3964	66	5	accuracy	accuracy	NOUN
cana-3964	66	6	97.4	97.4	NUM
cana-3964	66	7	%	%	NOUN
cana-3964	66	8	.	.	PUNCT
cana-3964	67	1	[	[	X
cana-3964	67	2	30	30	NUM
cana-3964	67	3	]	]	PUNCT
cana-3964	67	4	discovered	discover	VERB
cana-3964	67	5	that	that	SCONJ
cana-3964	67	6	the	the	DET
cana-3964	67	7	svm	svm	PROPN
cana-3964	67	8	had	have	VERB
cana-3964	67	9	a	a	DET
cana-3964	67	10	97.36	97.36	NUM
cana-3964	67	11	%	%	NOUN
cana-3964	67	12	accuracy	accuracy	NOUN
cana-3964	67	13	rate	rate	NOUN
cana-3964	67	14	.	.	PUNCT
cana-3964	68	1	the	the	DET
cana-3964	68	2	accuracy	accuracy	NOUN
cana-3964	68	3	of	of	ADP
cana-3964	68	4	predictions	prediction	NOUN
cana-3964	68	5	can	can	AUX
cana-3964	68	6	be	be	AUX
cana-3964	68	7	increased	increase	VERB
cana-3964	68	8	yet	yet	ADV
cana-3964	68	9	more	more	ADV
cana-3964	68	10	by	by	ADP
cana-3964	68	11	using	use	VERB
cana-3964	68	12	ensemble	ensemble	ADJ
cana-3964	68	13	models	model	NOUN
cana-3964	68	14	and	and	CCONJ
cana-3964	68	15	optimized	optimize	VERB
cana-3964	68	16	frameworks	framework	NOUN
cana-3964	68	17	.	.	PUNCT
cana-3964	69	1	the	the	DET
cana-3964	69	2	application	application	NOUN
cana-3964	69	3	of	of	ADP
cana-3964	69	4	ml	ml	ADP
cana-3964	69	5	algorithms	algorithm	NOUN
cana-3964	69	6	in	in	ADP
cana-3964	69	7	breast	breast	NOUN
cana-3964	69	8	cancer	cancer	NOUN
cana-3964	69	9	diagnosis	diagnosis	NOUN
cana-3964	69	10	has	have	AUX
cana-3964	69	11	increased	increase	VERB
cana-3964	69	12	day	day	NOUN
cana-3964	69	13	by	by	ADP
cana-3964	69	14	day	day	NOUN
cana-3964	69	15	because	because	SCONJ
cana-3964	69	16	they	they	PRON
cana-3964	69	17	have	have	AUX
cana-3964	69	18	become	become	VERB
cana-3964	69	19	extremely	extremely	ADV
cana-3964	69	20	useful	useful	ADJ
cana-3964	69	21	tools	tool	NOUN
cana-3964	69	22	in	in	ADP
cana-3964	69	23	the	the	DET
cana-3964	69	24	diagnosis	diagnosis	NOUN
cana-3964	69	25	of	of	ADP
cana-3964	69	26	bc	bc	PROPN
cana-3964	69	27	.	.	PROPN
cana-3964	69	28	mammography	mammography	NOUN
cana-3964	69	29	,	,	PUNCT
cana-3964	69	30	mri	mri	NOUN
cana-3964	69	31	scans	scan	NOUN
cana-3964	69	32	,	,	PUNCT
cana-3964	69	33	histopathological	histopathological	ADJ
cana-3964	69	34	images	image	NOUN
cana-3964	69	35	all	all	PRON
cana-3964	69	36	are	be	AUX
cana-3964	69	37	clarified	clarify	VERB
cana-3964	69	38	using	use	VERB
cana-3964	69	39	different	different	ADJ
cana-3964	69	40	algorithms	algorithm	NOUN
cana-3964	69	41	to	to	PART
cana-3964	69	42	help	help	VERB
cana-3964	69	43	clinicians	clinician	NOUN
cana-3964	69	44	spot	spot	VERB
cana-3964	69	45	the	the	DET
cana-3964	69	46	early	early	ADJ
cana-3964	69	47	-	-	PUNCT
cana-3964	69	48	stage	stage	NOUN
cana-3964	69	49	tumors	tumor	NOUN
cana-3964	69	50	at	at	ADP
cana-3964	69	51	the	the	DET
cana-3964	69	52	right	right	ADJ
cana-3964	69	53	instance	instance	NOUN
cana-3964	69	54	providing	provide	VERB
cana-3964	69	55	a	a	DET
cana-3964	69	56	better	well	ADJ
cana-3964	69	57	diagnostic	diagnostic	ADJ
cana-3964	69	58	result	result	NOUN
cana-3964	69	59	.	.	PUNCT
cana-3964	70	1	[	[	X
cana-3964	70	2	31	31	NUM
cana-3964	70	3	]	]	PUNCT
cana-3964	70	4	proposed	propose	VERB
cana-3964	70	5	an	an	DET
cana-3964	70	6	ensemble	ensemble	ADJ
cana-3964	70	7	framework	framework	NOUN
cana-3964	70	8	for	for	ADP
cana-3964	70	9	bc	bc	PROPN
cana-3964	70	10	prediction	prediction	NOUN
cana-3964	70	11	with	with	ADP
cana-3964	70	12	97.66	97.66	NUM
cana-3964	70	13	%	%	NOUN
cana-3964	70	14	accuracy	accuracy	NOUN
cana-3964	70	15	value	value	NOUN
cana-3964	70	16	.	.	PUNCT
cana-3964	71	1	2	2	X
cana-3964	71	2	.	.	X
cana-3964	71	3	ml	ml	NOUN
cana-3964	71	4	techniques	technique	NOUN
cana-3964	71	5	for	for	ADP
cana-3964	71	6	breast	breast	NOUN
cana-3964	71	7	cancer	cancer	NOUN
cana-3964	71	8	diagnosis	diagnosis	NOUN
cana-3964	71	9	the	the	DET
cana-3964	71	10	most	most	ADV
cana-3964	71	11	effective	effective	ADJ
cana-3964	71	12	way	way	NOUN
cana-3964	71	13	to	to	PART
cana-3964	71	14	categorize	categorize	VERB
cana-3964	71	15	breast	breast	NOUN
cana-3964	71	16	cancer	cancer	NOUN
cana-3964	71	17	trends	trend	NOUN
cana-3964	71	18	and	and	CCONJ
cana-3964	71	19	make	make	VERB
cana-3964	71	20	decisions	decision	NOUN
cana-3964	71	21	is	be	AUX
cana-3964	71	22	through	through	ADP
cana-3964	71	23	ml	ml	ADP
cana-3964	71	24	algorithms	algorithm	NOUN
cana-3964	71	25	,	,	PUNCT
cana-3964	71	26	which	which	PRON
cana-3964	71	27	take	take	VERB
cana-3964	71	28	significant	significant	ADJ
cana-3964	71	29	components	component	NOUN
cana-3964	71	30	out	out	ADP
cana-3964	71	31	of	of	ADP
cana-3964	71	32	massive	massive	ADJ
cana-3964	71	33	datasets	dataset	NOUN
cana-3964	71	34	.	.	PUNCT
cana-3964	72	1	positive	positive	ADJ
cana-3964	72	2	outcomes	outcome	NOUN
cana-3964	72	3	have	have	AUX
cana-3964	72	4	been	be	AUX
cana-3964	72	5	obtained	obtain	VERB
cana-3964	72	6	from	from	ADP
cana-3964	72	7	the	the	DET
cana-3964	72	8	classification	classification	NOUN
cana-3964	72	9	of	of	ADP
cana-3964	72	10	data	datum	NOUN
cana-3964	72	11	utilizing	utilize	VERB
cana-3964	72	12	the	the	DET
cana-3964	72	13	knn	knn	PROPN
cana-3964	72	14	,	,	PUNCT
cana-3964	72	15	svm	svm	PROPN
cana-3964	72	16	,	,	PUNCT
cana-3964	72	17	and	and	CCONJ
cana-3964	72	18	dt	dt	ADP
cana-3964	72	19	algorithms	algorithm	NOUN
cana-3964	72	20	.	.	PUNCT
cana-3964	73	1	additionally	additionally	ADV
cana-3964	73	2	,	,	PUNCT
cana-3964	73	3	these	these	DET
cana-3964	73	4	methods	method	NOUN
cana-3964	73	5	significantly	significantly	ADV
cana-3964	73	6	support	support	VERB
cana-3964	73	7	clinical	clinical	ADJ
cana-3964	73	8	diagnosis	diagnosis	NOUN
cana-3964	73	9	and	and	CCONJ
cana-3964	73	10	decision	decision	NOUN
cana-3964	73	11	-	-	PUNCT
cana-3964	73	12	making	making	NOUN
cana-3964	73	13	.	.	PUNCT
cana-3964	74	1	in	in	ADP
cana-3964	74	2	this	this	DET
cana-3964	74	3	section	section	NOUN
cana-3964	74	4	,	,	PUNCT
cana-3964	74	5	ml	ml	ADP
cana-3964	74	6	techniques	technique	NOUN
cana-3964	74	7	for	for	ADP
cana-3964	74	8	breast	breast	NOUN
cana-3964	74	9	cancer	cancer	NOUN
cana-3964	74	10	diagnosis	diagnosis	NOUN
cana-3964	74	11	are	be	AUX
cana-3964	74	12	presented	present	VERB
cana-3964	74	13	.	.	PUNCT
cana-3964	75	1	it	it	PRON
cana-3964	75	2	covers	cover	VERB
cana-3964	75	3	a	a	DET
cana-3964	75	4	range	range	NOUN
cana-3964	75	5	of	of	ADP
cana-3964	75	6	techniques	technique	NOUN
cana-3964	75	7	,	,	PUNCT
cana-3964	75	8	such	such	ADJ
cana-3964	75	9	as	as	ADP
cana-3964	75	10	decision	decision	NOUN
cana-3964	75	11	trees	tree	NOUN
cana-3964	75	12	,	,	PUNCT
cana-3964	75	13	random	random	ADJ
cana-3964	75	14	forests	forest	NOUN
cana-3964	75	15	,	,	PUNCT
cana-3964	75	16	svm	svm	PROPN
cana-3964	75	17	,	,	PUNCT
cana-3964	75	18	ann	ann	PROPN
cana-3964	75	19	,	,	PUNCT
cana-3964	75	20	logistic	logistic	ADJ
cana-3964	75	21	regression	regression	NOUN
cana-3964	75	22	,	,	PUNCT
cana-3964	75	23	and	and	CCONJ
cana-3964	75	24	knn	knn	PROPN
cana-3964	75	25	.	.	PUNCT
cana-3964	76	1	each	each	DET
cana-3964	76	2	technique	technique	NOUN
cana-3964	76	3	is	be	AUX
cana-3964	76	4	described	describe	VERB
cana-3964	76	5	,	,	PUNCT
cana-3964	76	6	including	include	VERB
cana-3964	76	7	its	its	PRON
cana-3964	76	8	underlying	underlie	VERB
cana-3964	76	9	principles	principle	NOUN
cana-3964	76	10	,	,	PUNCT
cana-3964	76	11	training	training	NOUN
cana-3964	76	12	process	process	NOUN
cana-3964	76	13	,	,	PUNCT
cana-3964	76	14	and	and	CCONJ
cana-3964	76	15	specific	specific	ADJ
cana-3964	76	16	applications	application	NOUN
cana-3964	76	17	in	in	ADP
cana-3964	76	18	breast	breast	NOUN
cana-3964	76	19	cancer	cancer	NOUN
cana-3964	76	20	diagnosis	diagnosis	NOUN
cana-3964	76	21	.	.	PUNCT
cana-3964	77	1	the	the	DET
cana-3964	77	2	significance	significance	NOUN
cana-3964	77	3	of	of	ADP
cana-3964	77	4	these	these	DET
cana-3964	77	5	techniques	technique	NOUN
cana-3964	77	6	is	be	AUX
cana-3964	77	7	discussed	discuss	VERB
cana-3964	77	8	,	,	PUNCT
cana-3964	77	9	providing	provide	VERB
cana-3964	77	10	insights	insight	NOUN
cana-3964	77	11	into	into	ADP
cana-3964	77	12	their	their	PRON
cana-3964	77	13	suitability	suitability	NOUN
cana-3964	77	14	for	for	ADP
cana-3964	77	15	clinical	clinical	ADJ
cana-3964	77	16	implementation	implementation	NOUN
cana-3964	78	1	[	[	X
cana-3964	78	2	32	32	NUM
cana-3964	78	3	]	]	PUNCT
cana-3964	78	4	.	.	PUNCT
cana-3964	79	1	there	there	PRON
cana-3964	79	2	are	be	VERB
cana-3964	79	3	various	various	ADJ
cana-3964	79	4	ml	ml	NOUN
cana-3964	79	5	technologies	technology	NOUN
cana-3964	79	6	deployed	deploy	VERB
cana-3964	79	7	for	for	ADP
cana-3964	79	8	breast	breast	NOUN
cana-3964	79	9	cancer	cancer	NOUN
cana-3964	79	10	diagnosis	diagnosis	NOUN
cana-3964	79	11	.	.	PUNCT
cana-3964	80	1	the	the	DET
cana-3964	80	2	major	major	ADJ
cana-3964	80	3	ones	one	NOUN
cana-3964	80	4	among	among	ADP
cana-3964	80	5	these	these	PRON
cana-3964	80	6	are	be	AUX
cana-3964	80	7	presented	present	VERB
cana-3964	80	8	in	in	ADP
cana-3964	80	9	fig	fig	NOUN
cana-3964	80	10	.	.	PUNCT
cana-3964	81	1	1	1	X
cana-3964	81	2	.	.	X
cana-3964	81	3	fig	fig	NOUN
cana-3964	81	4	.	.	PUNCT
cana-3964	82	1	1	1	NUM
cana-3964	82	2	machine	machine	NOUN
cana-3964	82	3	learning	learn	VERB
cana-3964	82	4	techniques	technique	NOUN
cana-3964	82	5	2.1	2.1	NUM
cana-3964	82	6	logistic	logistic	ADJ
cana-3964	82	7	regression	regression	NOUN
cana-3964	82	8	(	(	PUNCT
cana-3964	82	9	lr	lr	NOUN
cana-3964	82	10	)	)	PUNCT
cana-3964	82	11	logistic	logistic	ADJ
cana-3964	82	12	regression	regression	NOUN
cana-3964	82	13	may	may	AUX
cana-3964	82	14	be	be	AUX
cana-3964	82	15	used	use	VERB
cana-3964	82	16	to	to	PART
cana-3964	82	17	detect	detect	VERB
cana-3964	82	18	if	if	SCONJ
cana-3964	82	19	a	a	DET
cana-3964	82	20	tumor	tumor	NOUN
cana-3964	82	21	is	be	AUX
cana-3964	82	22	benign	benign	ADJ
cana-3964	82	23	or	or	CCONJ
cana-3964	82	24	malignant	malignant	ADJ
cana-3964	82	25	.	.	PUNCT
cana-3964	83	1	the	the	DET
cana-3964	83	2	algorithm	algorithm	NOUN
cana-3964	83	3	learns	learn	VERB
cana-3964	83	4	from	from	ADP
cana-3964	83	5	a	a	DET
cana-3964	83	6	labeled	label	VERB
cana-3964	83	7	dataset	dataset	NOUN
cana-3964	83	8	,	,	PUNCT
cana-3964	83	9	where	where	SCONJ
cana-3964	83	10	each	each	DET
cana-3964	83	11	instance	instance	NOUN
cana-3964	83	12	represents	represent	VERB
cana-3964	83	13	a	a	DET
cana-3964	83	14	tumor	tumor	NOUN
cana-3964	83	15	and	and	CCONJ
cana-3964	83	16	is	be	AUX
cana-3964	83	17	associated	associate	VERB
cana-3964	83	18	with	with	ADP
cana-3964	83	19	a	a	DET
cana-3964	83	20	binary	binary	ADJ
cana-3964	83	21	class	class	NOUN
cana-3964	83	22	label	label	NOUN
cana-3964	83	23	indicating	indicate	VERB
cana-3964	83	24	its	its	PRON
cana-3964	83	25	malignancy.the	malignancy.the	DET
cana-3964	83	26	logistic	logistic	ADJ
cana-3964	83	27	regression	regression	NOUN
cana-3964	83	28	model	model	NOUN
cana-3964	83	29	uses	use	VERB
cana-3964	83	30	a	a	DET
cana-3964	83	31	special	special	ADJ
cana-3964	83	32	function	function	NOUN
cana-3964	83	33	known	know	VERB
cana-3964	83	34	as	as	ADP
cana-3964	83	35	“	"	PUNCT
cana-3964	83	36	the	the	DET
cana-3964	83	37	sigmoid	sigmoid	NOUN
cana-3964	83	38	function	function	NOUN
cana-3964	83	39	”	"	PUNCT
cana-3964	83	40	to	to	PART
cana-3964	83	41	map	map	VERB
cana-3964	83	42	the	the	DET
cana-3964	83	43	linear	linear	ADJ
cana-3964	83	44	relationship	relationship	NOUN
cana-3964	83	45	(	(	PUNCT
cana-3964	83	46	if	if	SCONJ
cana-3964	83	47	one	one	NUM
cana-3964	83	48	feature	feature	NOUN
cana-3964	83	49	grows	grow	VERB
cana-3964	83	50	,	,	PUNCT
cana-3964	83	51	the	the	DET
cana-3964	83	52	output	output	NOUN
cana-3964	83	53	also	also	ADV
cana-3964	83	54	grows	grow	VERB
cana-3964	83	55	and	and	CCONJ
cana-3964	83	56	when	when	SCONJ
cana-3964	83	57	one	one	NUM
cana-3964	83	58	feature	feature	NOUN
cana-3964	83	59	reduces	reduce	VERB
cana-3964	83	60	,	,	PUNCT
cana-3964	83	61	the	the	DET
cana-3964	83	62	output	output	NOUN
cana-3964	83	63	reduces	reduce	VERB
cana-3964	83	64	.	.	PUNCT
cana-3964	83	65	)	)	PUNCT
cana-3964	83	66	of	of	ADP
cana-3964	83	67	input	input	NOUN
cana-3964	83	68	features	feature	VERB
cana-3964	83	69	to	to	ADP
cana-3964	83	70	a	a	DET
cana-3964	83	71	probability	probability	NOUN
cana-3964	83	72	(	(	PUNCT
cana-3964	83	73	between	between	ADP
cana-3964	83	74	0	0	NUM
cana-3964	83	75	and	and	CCONJ
cana-3964	83	76	1	1	NUM
cana-3964	83	77	)	)	PUNCT
cana-3964	83	78	.	.	PUNCT
cana-3964	84	1	this	this	DET
cana-3964	84	2	communications	communication	NOUN
cana-3964	84	3	on	on	ADP
cana-3964	84	4	applied	apply	VERB
cana-3964	84	5	nonlinear	nonlinear	ADJ
cana-3964	84	6	analysis	analysis	NOUN
cana-3964	84	7	issn	issn	NOUN
cana-3964	84	8	:	:	PUNCT
cana-3964	84	9	1074	1074	NUM
cana-3964	84	10	-	-	PUNCT
cana-3964	84	11	133x	133x	NUM
cana-3964	84	12	vol	vol	NOUN
cana-3964	84	13	32	32	NUM
cana-3964	84	14	no	no	NOUN
cana-3964	84	15	.	.	PUNCT
cana-3964	85	1	9s	9s	NUM
cana-3964	85	2	(	(	PUNCT
cana-3964	85	3	2025	2025	NUM
cana-3964	85	4	)	)	PUNCT
cana-3964	85	5	557	557	NUM
cana-3964	85	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	85	7	probability	probability	NOUN
cana-3964	85	8	represents	represent	VERB
cana-3964	85	9	the	the	DET
cana-3964	85	10	chance	chance	NOUN
cana-3964	85	11	of	of	ADP
cana-3964	85	12	the	the	DET
cana-3964	85	13	tumor	tumor	NOUN
cana-3964	85	14	being	be	AUX
cana-3964	85	15	malignant	malignant	ADJ
cana-3964	85	16	.	.	PUNCT
cana-3964	86	1	a	a	DET
cana-3964	86	2	threshold	threshold	NOUN
cana-3964	86	3	is	be	AUX
cana-3964	86	4	then	then	ADV
cana-3964	86	5	applied	apply	VERB
cana-3964	86	6	to	to	ADP
cana-3964	86	7	the	the	DET
cana-3964	86	8	predicted	predict	VERB
cana-3964	86	9	probability	probability	NOUN
cana-3964	86	10	to	to	PART
cana-3964	86	11	make	make	VERB
cana-3964	86	12	the	the	DET
cana-3964	86	13	final	final	ADJ
cana-3964	86	14	classification	classification	NOUN
cana-3964	86	15	decision	decision	NOUN
cana-3964	86	16	.	.	PUNCT
cana-3964	87	1	it	it	PRON
cana-3964	87	2	has	have	VERB
cana-3964	87	3	low	low	ADJ
cana-3964	87	4	computational	computational	ADJ
cana-3964	87	5	cost	cost	NOUN
cana-3964	87	6	and	and	CCONJ
cana-3964	87	7	is	be	AUX
cana-3964	87	8	easy	easy	ADJ
cana-3964	87	9	to	to	PART
cana-3964	87	10	implement	implement	VERB
cana-3964	87	11	and	and	CCONJ
cana-3964	87	12	design	design	NOUN
cana-3964	87	13	but	but	CCONJ
cana-3964	87	14	the	the	DET
cana-3964	87	15	performance	performance	NOUN
cana-3964	87	16	of	of	ADP
cana-3964	87	17	this	this	DET
cana-3964	87	18	algorithm	algorithm	NOUN
cana-3964	87	19	decreases	decrease	VERB
cana-3964	87	20	with	with	ADP
cana-3964	87	21	large	large	ADJ
cana-3964	87	22	data	datum	NOUN
cana-3964	87	23	sets	set	NOUN
cana-3964	87	24	[	[	X
cana-3964	87	25	35	35	NUM
cana-3964	87	26	]	]	PUNCT
cana-3964	87	27	.	.	PUNCT
cana-3964	88	1	2.2	2.2	NUM
cana-3964	88	2	random	random	ADJ
cana-3964	88	3	forest	forest	NOUN
cana-3964	88	4	(	(	PUNCT
cana-3964	88	5	rf	rf	NOUN
cana-3964	88	6	)	)	PUNCT
cana-3964	88	7	multiple	multiple	ADJ
cana-3964	88	8	dts	dt	NOUN
cana-3964	88	9	are	be	AUX
cana-3964	88	10	used	use	VERB
cana-3964	88	11	in	in	ADP
cana-3964	88	12	the	the	DET
cana-3964	88	13	random	random	ADJ
cana-3964	88	14	forest	forest	NOUN
cana-3964	88	15	ensemble	ensemble	ADJ
cana-3964	88	16	learning	learning	NOUN
cana-3964	88	17	technique	technique	NOUN
cana-3964	88	18	to	to	PART
cana-3964	88	19	generate	generate	VERB
cana-3964	88	20	predictions	prediction	NOUN
cana-3964	88	21	.	.	PUNCT
cana-3964	89	1	it	it	PRON
cana-3964	89	2	is	be	AUX
cana-3964	89	3	used	use	VERB
cana-3964	89	4	to	to	PART
cana-3964	89	5	build	build	VERB
cana-3964	89	6	a	a	DET
cana-3964	89	7	set	set	NOUN
cana-3964	89	8	of	of	ADP
cana-3964	89	9	decision	decision	NOUN
cana-3964	89	10	trees	tree	NOUN
cana-3964	89	11	for	for	ADP
cana-3964	89	12	diagnosing	diagnose	VERB
cana-3964	89	13	breast	breast	NOUN
cana-3964	89	14	cancer	cancer	NOUN
cana-3964	89	15	,	,	PUNCT
cana-3964	89	16	with	with	SCONJ
cana-3964	89	17	each	each	DET
cana-3964	89	18	tree	tree	NOUN
cana-3964	89	19	being	be	AUX
cana-3964	89	20	trained	train	VERB
cana-3964	89	21	using	use	VERB
cana-3964	89	22	a	a	DET
cana-3964	89	23	different	different	ADJ
cana-3964	89	24	subset	subset	NOUN
cana-3964	89	25	of	of	ADP
cana-3964	89	26	the	the	DET
cana-3964	89	27	available	available	ADJ
cana-3964	89	28	information	information	NOUN
cana-3964	89	29	and	and	CCONJ
cana-3964	89	30	characteristics	characteristic	NOUN
cana-3964	89	31	[	[	X
cana-3964	89	32	11	11	NUM
cana-3964	89	33	]	]	PUNCT
cana-3964	89	34	.	.	PUNCT
cana-3964	90	1	either	either	CCONJ
cana-3964	90	2	a	a	DET
cana-3964	90	3	majority	majority	NOUN
cana-3964	90	4	vote	vote	NOUN
cana-3964	90	5	or	or	CCONJ
cana-3964	90	6	an	an	DET
cana-3964	90	7	average	average	NOUN
cana-3964	90	8	of	of	ADP
cana-3964	90	9	the	the	DET
cana-3964	90	10	estimates	estimate	NOUN
cana-3964	90	11	made	make	VERB
cana-3964	90	12	by	by	ADP
cana-3964	90	13	each	each	DET
cana-3964	90	14	individual	individual	ADJ
cana-3964	90	15	tree	tree	NOUN
cana-3964	90	16	is	be	AUX
cana-3964	90	17	used	use	VERB
cana-3964	90	18	to	to	PART
cana-3964	90	19	determine	determine	VERB
cana-3964	90	20	the	the	DET
cana-3964	90	21	final	final	ADJ
cana-3964	90	22	prediction	prediction	NOUN
cana-3964	90	23	.	.	PUNCT
cana-3964	91	1	rf	rf	PRON
cana-3964	91	2	can	can	AUX
cana-3964	91	3	handle	handle	VERB
cana-3964	91	4	high	high	ADJ
cana-3964	91	5	-	-	PUNCT
cana-3964	91	6	dimensional	dimensional	ADJ
cana-3964	91	7	data	datum	NOUN
cana-3964	91	8	,	,	PUNCT
cana-3964	91	9	capture	capture	NOUN
cana-3964	91	10	relationships	relationship	NOUN
cana-3964	91	11	,	,	PUNCT
cana-3964	91	12	and	and	CCONJ
cana-3964	91	13	minimize	minimize	VERB
cana-3964	91	14	overfitting	overfitte	VERB
cana-3964	91	15	.	.	PUNCT
cana-3964	92	1	2.3	2.3	NUM
cana-3964	92	2	decision	decision	NOUN
cana-3964	92	3	tree	tree	NOUN
cana-3964	92	4	(	(	PUNCT
cana-3964	92	5	dt	dt	NOUN
cana-3964	92	6	)	)	PUNCT
cana-3964	92	7	a	a	DET
cana-3964	92	8	dt	dt	NOUN
cana-3964	92	9	is	be	AUX
cana-3964	92	10	a	a	DET
cana-3964	92	11	common	common	ADJ
cana-3964	92	12	ml	ml	NOUN
cana-3964	92	13	technique	technique	NOUN
cana-3964	92	14	for	for	ADP
cana-3964	92	15	classification	classification	NOUN
cana-3964	92	16	tasks	task	NOUN
cana-3964	92	17	such	such	ADJ
cana-3964	92	18	as	as	ADP
cana-3964	92	19	diagnosing	diagnose	VERB
cana-3964	92	20	breast	breast	NOUN
cana-3964	92	21	cancer	cancer	NOUN
cana-3964	92	22	.	.	PUNCT
cana-3964	93	1	by	by	ADP
cana-3964	93	2	recursively	recursively	ADV
cana-3964	93	3	dividing	divide	VERB
cana-3964	93	4	the	the	DET
cana-3964	93	5	data	datum	NOUN
cana-3964	93	6	according	accord	VERB
cana-3964	93	7	to	to	ADP
cana-3964	93	8	the	the	DET
cana-3964	93	9	values	value	NOUN
cana-3964	93	10	of	of	ADP
cana-3964	93	11	input	input	NOUN
cana-3964	93	12	features	feature	NOUN
cana-3964	93	13	,	,	PUNCT
cana-3964	93	14	it	it	PRON
cana-3964	93	15	creates	create	VERB
cana-3964	93	16	a	a	DET
cana-3964	93	17	model	model	NOUN
cana-3964	93	18	that	that	PRON
cana-3964	93	19	resembles	resemble	VERB
cana-3964	93	20	a	a	DET
cana-3964	93	21	tree	tree	NOUN
cana-3964	93	22	[	[	X
cana-3964	93	23	36	36	NUM
cana-3964	93	24	]	]	PUNCT
cana-3964	93	25	.	.	PUNCT
cana-3964	94	1	in	in	ADP
cana-3964	94	2	this	this	DET
cana-3964	94	3	tree	tree	NOUN
cana-3964	94	4	structure	structure	NOUN
cana-3964	94	5	,	,	PUNCT
cana-3964	94	6	every	every	DET
cana-3964	94	7	leaf	leaf	NOUN
cana-3964	94	8	node	node	NOUN
cana-3964	94	9	represents	represent	VERB
cana-3964	94	10	a	a	DET
cana-3964	94	11	class	class	NOUN
cana-3964	94	12	(	(	PUNCT
cana-3964	94	13	benign	benign	ADJ
cana-3964	94	14	or	or	CCONJ
cana-3964	94	15	malignant	malignant	ADJ
cana-3964	94	16	)	)	PUNCT
cana-3964	94	17	,	,	PUNCT
cana-3964	94	18	and	and	CCONJ
cana-3964	94	19	every	every	DET
cana-3964	94	20	internal	internal	ADJ
cana-3964	94	21	node	node	NOUN
cana-3964	94	22	represents	represent	VERB
cana-3964	94	23	a	a	DET
cana-3964	94	24	feature	feature	NOUN
cana-3964	94	25	.	.	PUNCT
cana-3964	95	1	the	the	DET
cana-3964	95	2	dt	dt	PROPN
cana-3964	95	3	algorithm	algorithm	PROPN
cana-3964	95	4	learns	learn	VERB
cana-3964	95	5	from	from	ADP
cana-3964	95	6	the	the	DET
cana-3964	95	7	data	datum	NOUN
cana-3964	95	8	to	to	PART
cana-3964	95	9	determine	determine	VERB
cana-3964	95	10	the	the	DET
cana-3964	95	11	optimal	optimal	ADJ
cana-3964	95	12	splits	split	NOUN
cana-3964	95	13	that	that	PRON
cana-3964	95	14	best	well	ADV
cana-3964	95	15	separate	separate	VERB
cana-3964	95	16	the	the	DET
cana-3964	95	17	different	different	ADJ
cana-3964	95	18	classes	class	NOUN
cana-3964	95	19	.	.	PUNCT
cana-3964	96	1	dt	dt	PROPN
cana-3964	96	2	has	have	VERB
cana-3964	96	3	moderate	moderate	ADJ
cana-3964	96	4	computational	computational	ADJ
cana-3964	96	5	complexity	complexity	NOUN
cana-3964	96	6	together	together	ADV
cana-3964	96	7	with	with	ADP
cana-3964	96	8	high	high	ADJ
cana-3964	96	9	readability	readability	NOUN
cana-3964	96	10	;	;	PUNCT
cana-3964	96	11	however	however	ADV
cana-3964	96	12	,	,	PUNCT
cana-3964	96	13	this	this	DET
cana-3964	96	14	methodology	methodology	NOUN
cana-3964	96	15	might	might	AUX
cana-3964	96	16	overfit	overfit	VERB
cana-3964	96	17	.	.	PUNCT
cana-3964	97	1	fig	fig	NOUN
cana-3964	97	2	.	.	PUNCT
cana-3964	98	1	2	2	NUM
cana-3964	98	2	is	be	AUX
cana-3964	98	3	a	a	DET
cana-3964	98	4	representation	representation	NOUN
cana-3964	98	5	of	of	ADP
cana-3964	98	6	a	a	DET
cana-3964	98	7	decision	decision	NOUN
cana-3964	98	8	tree	tree	NOUN
cana-3964	98	9	for	for	ADP
cana-3964	98	10	bc	bc	PROPN
cana-3964	98	11	diagnosis	diagnosis	NOUN
cana-3964	98	12	[	[	X
cana-3964	98	13	11	11	NUM
cana-3964	98	14	]	]	PUNCT
cana-3964	98	15	.	.	PUNCT
cana-3964	99	1	fig	fig	NOUN
cana-3964	99	2	.	.	PUNCT
cana-3964	100	1	2	2	NUM
cana-3964	100	2	decision	decision	NOUN
cana-3964	100	3	tree	tree	NOUN
cana-3964	100	4	2.4	2.4	NUM
cana-3964	100	5	support	support	NOUN
cana-3964	100	6	vector	vector	NOUN
cana-3964	100	7	machine	machine	NOUN
cana-3964	100	8	(	(	PUNCT
cana-3964	100	9	svm	svm	ADJ
cana-3964	100	10	)	)	PUNCT
cana-3964	100	11	svm	svm	NOUN
cana-3964	100	12	is	be	AUX
cana-3964	100	13	a	a	DET
cana-3964	100	14	highly	highly	ADV
cana-3964	100	15	effective	effective	ADJ
cana-3964	100	16	supervised	supervised	ADJ
cana-3964	100	17	learning	learning	NOUN
cana-3964	100	18	system	system	NOUN
cana-3964	100	19	designed	design	VERB
cana-3964	100	20	for	for	ADP
cana-3964	100	21	categorization	categorization	NOUN
cana-3964	100	22	.	.	PUNCT
cana-3964	101	1	the	the	DET
cana-3964	101	2	goal	goal	NOUN
cana-3964	101	3	is	be	AUX
cana-3964	101	4	to	to	PART
cana-3964	101	5	identify	identify	VERB
cana-3964	101	6	the	the	DET
cana-3964	101	7	best	good	ADJ
cana-3964	101	8	hyperplane	hyperplane	NOUN
cana-3964	101	9	in	in	ADP
cana-3964	101	10	the	the	DET
cana-3964	101	11	breast	breast	NOUN
cana-3964	101	12	cancer	cancer	NOUN
cana-3964	101	13	dataset	dataset	NOUN
cana-3964	101	14	that	that	PRON
cana-3964	101	15	maximally	maximally	ADV
cana-3964	101	16	divides	divide	VERB
cana-3964	101	17	the	the	DET
cana-3964	101	18	two	two	NUM
cana-3964	101	19	groups	group	NOUN
cana-3964	101	20	(	(	PUNCT
cana-3964	101	21	malignant	malignant	ADJ
cana-3964	101	22	and	and	CCONJ
cana-3964	101	23	benign	benign	ADJ
cana-3964	101	24	)	)	PUNCT
cana-3964	101	25	.	.	PUNCT
cana-3964	102	1	high	high	ADJ
cana-3964	102	2	-	-	PUNCT
cana-3964	102	3	dimensional	dimensional	ADJ
cana-3964	102	4	data	datum	NOUN
cana-3964	102	5	can	can	AUX
cana-3964	102	6	be	be	AUX
cana-3964	102	7	handled	handle	VERB
cana-3964	102	8	by	by	ADP
cana-3964	102	9	“	"	PUNCT
cana-3964	102	10	svm	svm	PROPN
cana-3964	102	11	”	"	PUNCT
cana-3964	102	12	,	,	PUNCT
cana-3964	102	13	and	and	CCONJ
cana-3964	102	14	it	it	PRON
cana-3964	102	15	works	work	VERB
cana-3964	102	16	by	by	ADP
cana-3964	102	17	finding	find	VERB
cana-3964	102	18	the	the	DET
cana-3964	102	19	support	support	NOUN
cana-3964	102	20	vectors	vector	NOUN
cana-3964	102	21	,	,	PUNCT
cana-3964	102	22	which	which	PRON
cana-3964	102	23	are	be	AUX
cana-3964	102	24	the	the	DET
cana-3964	102	25	data	data	NOUN
cana-3964	102	26	points	point	NOUN
cana-3964	102	27	bordering	border	VERB
cana-3964	102	28	the	the	DET
cana-3964	102	29	decision	decision	NOUN
cana-3964	102	30	boundary	boundary	NOUN
cana-3964	102	31	,	,	PUNCT
cana-3964	102	32	to	to	PART
cana-3964	102	33	classify	classify	VERB
cana-3964	102	34	new	new	ADJ
cana-3964	102	35	instances	instance	NOUN
cana-3964	102	36	[	[	X
cana-3964	102	37	11	11	NUM
cana-3964	102	38	]	]	PUNCT
cana-3964	102	39	.	.	PUNCT
cana-3964	103	1	svm	svm	PROPN
cana-3964	103	2	is	be	AUX
cana-3964	103	3	more	more	ADV
cana-3964	103	4	computationally	computationally	ADV
cana-3964	103	5	expensive	expensive	ADJ
cana-3964	103	6	than	than	ADP
cana-3964	103	7	the	the	DET
cana-3964	103	8	other	other	ADJ
cana-3964	103	9	algorithms	algorithm	NOUN
cana-3964	103	10	especially	especially	ADV
cana-3964	103	11	when	when	SCONJ
cana-3964	103	12	dealing	deal	VERB
cana-3964	103	13	with	with	ADP
cana-3964	103	14	a	a	DET
cana-3964	103	15	large	large	ADJ
cana-3964	103	16	amount	amount	NOUN
cana-3964	103	17	of	of	ADP
cana-3964	103	18	data	datum	NOUN
cana-3964	103	19	;	;	PUNCT
cana-3964	103	20	requires	require	VERB
cana-3964	103	21	proper	proper	ADJ
cana-3964	103	22	calibration	calibration	NOUN
cana-3964	103	23	of	of	ADP
cana-3964	103	24	the	the	DET
cana-3964	103	25	parameters	parameter	NOUN
cana-3964	103	26	.	.	PUNCT
cana-3964	104	1	2.5	2.5	NUM
cana-3964	104	2	artificial	artificial	ADJ
cana-3964	104	3	neural	neural	ADJ
cana-3964	104	4	network	network	NOUN
cana-3964	104	5	(	(	PUNCT
cana-3964	104	6	ann	ann	PROPN
cana-3964	104	7	)	)	PUNCT
cana-3964	104	8	anns	anns	PROPN
cana-3964	104	9	are	be	AUX
cana-3964	104	10	the	the	DET
cana-3964	104	11	tool	tool	NOUN
cana-3964	104	12	for	for	ADP
cana-3964	104	13	breast	breast	NOUN
cana-3964	104	14	cancer	cancer	NOUN
cana-3964	104	15	diagnosis	diagnosis	NOUN
cana-3964	104	16	and	and	CCONJ
cana-3964	104	17	are	be	AUX
cana-3964	104	18	able	able	ADJ
cana-3964	104	19	to	to	PART
cana-3964	104	20	realize	realize	VERB
cana-3964	104	21	complex	complex	ADJ
cana-3964	104	22	patterns	pattern	NOUN
cana-3964	104	23	within	within	ADP
cana-3964	104	24	medical	medical	ADJ
cana-3964	104	25	data	datum	NOUN
cana-3964	104	26	.	.	PUNCT
cana-3964	105	1	these	these	DET
cana-3964	105	2	networks	network	NOUN
cana-3964	105	3	learn	learn	VERB
cana-3964	105	4	from	from	ADP
cana-3964	105	5	a	a	DET
cana-3964	105	6	vast	vast	ADJ
cana-3964	105	7	array	array	NOUN
cana-3964	105	8	of	of	ADP
cana-3964	105	9	patient	patient	ADJ
cana-3964	105	10	information	information	NOUN
cana-3964	105	11	,	,	PUNCT
cana-3964	105	12	such	such	ADJ
cana-3964	105	13	as	as	ADP
cana-3964	105	14	mammogram	mammogram	NOUN
cana-3964	105	15	images	image	NOUN
cana-3964	105	16	and	and	CCONJ
cana-3964	105	17	communications	communication	NOUN
cana-3964	105	18	on	on	ADP
cana-3964	105	19	applied	apply	VERB
cana-3964	105	20	nonlinear	nonlinear	ADJ
cana-3964	105	21	analysis	analysis	NOUN
cana-3964	105	22	issn	issn	NOUN
cana-3964	105	23	:	:	PUNCT
cana-3964	105	24	1074	1074	NUM
cana-3964	105	25	-	-	PUNCT
cana-3964	105	26	133x	133x	NUM
cana-3964	105	27	vol	vol	NOUN
cana-3964	105	28	32	32	NUM
cana-3964	105	29	no	no	NOUN
cana-3964	105	30	.	.	PUNCT
cana-3964	106	1	9s	9s	NUM
cana-3964	106	2	(	(	PUNCT
cana-3964	106	3	2025	2025	NUM
cana-3964	106	4	)	)	PUNCT
cana-3964	106	5	558	558	NUM
cana-3964	106	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	106	7	clinical	clinical	ADJ
cana-3964	106	8	records	record	NOUN
cana-3964	106	9	,	,	PUNCT
cana-3964	106	10	to	to	PART
cana-3964	106	11	separate	separate	VERB
cana-3964	106	12	refined	refined	ADJ
cana-3964	106	13	nuances	nuance	NOUN
cana-3964	106	14	indicative	indicative	ADJ
cana-3964	106	15	of	of	ADP
cana-3964	106	16	malignancy	malignancy	NOUN
cana-3964	106	17	.	.	PUNCT
cana-3964	107	1	these	these	DET
cana-3964	107	2	advancements	advancement	NOUN
cana-3964	107	3	hold	hold	VERB
cana-3964	107	4	promise	promise	NOUN
cana-3964	107	5	for	for	ADP
cana-3964	107	6	more	more	ADV
cana-3964	107	7	efficient	efficient	ADJ
cana-3964	107	8	and	and	CCONJ
cana-3964	107	9	reliable	reliable	ADJ
cana-3964	107	10	breast	breast	NOUN
cana-3964	107	11	cancer	cancer	NOUN
cana-3964	107	12	detection	detection	NOUN
cana-3964	107	13	.	.	PUNCT
cana-3964	108	1	it	it	PRON
cana-3964	108	2	has	have	VERB
cana-3964	108	3	very	very	ADV
cana-3964	108	4	high	high	ADJ
cana-3964	108	5	computational	computational	ADJ
cana-3964	108	6	cost	cost	NOUN
cana-3964	108	7	,	,	PUNCT
cana-3964	108	8	especially	especially	ADV
cana-3964	108	9	deep	deep	ADJ
cana-3964	108	10	learning	learning	NOUN
cana-3964	108	11	models	model	NOUN
cana-3964	108	12	requires	require	VERB
cana-3964	108	13	extensive	extensive	ADJ
cana-3964	108	14	training	training	NOUN
cana-3964	108	15	time	time	NOUN
cana-3964	108	16	and	and	CCONJ
cana-3964	108	17	higher	high	ADJ
cana-3964	108	18	performance	performance	NOUN
cana-3964	108	19	hardware	hardware	NOUN
cana-3964	108	20	.	.	PUNCT
cana-3964	109	1	2.6	2.6	NUM
cana-3964	109	2	k	k	ADV
cana-3964	109	3	-	-	PUNCT
cana-3964	109	4	nearest	near	ADJ
cana-3964	109	5	neighbor	neighbor	NOUN
cana-3964	109	6	(	(	PUNCT
cana-3964	109	7	knn	knn	PROPN
cana-3964	109	8	)	)	PUNCT
cana-3964	109	9	as	as	ADP
cana-3964	109	10	a	a	DET
cana-3964	109	11	non	non	ADJ
cana-3964	109	12	-	-	ADJ
cana-3964	109	13	parametric	parametric	ADJ
cana-3964	109	14	algorithm	algorithm	NOUN
cana-3964	109	15	knn	knn	PROPN
cana-3964	109	16	does	do	AUX
cana-3964	109	17	n't	not	PART
cana-3964	109	18	assume	assume	VERB
cana-3964	109	19	anything	anything	PRON
cana-3964	109	20	about	about	ADP
cana-3964	109	21	the	the	DET
cana-3964	109	22	distribution	distribution	NOUN
cana-3964	109	23	of	of	ADP
cana-3964	109	24	the	the	DET
cana-3964	109	25	underlying	underlie	VERB
cana-3964	109	26	data	datum	NOUN
cana-3964	109	27	.	.	PUNCT
cana-3964	110	1	research	research	NOUN
cana-3964	110	2	by	by	ADP
cana-3964	110	3	[	[	X
cana-3964	110	4	32	32	NUM
cana-3964	110	5	]	]	PUNCT
cana-3964	110	6	demonstrated	demonstrate	VERB
cana-3964	110	7	an	an	DET
cana-3964	110	8	impressive	impressive	ADJ
cana-3964	110	9	94	94	NUM
cana-3964	110	10	%	%	NOUN
cana-3964	110	11	accuracy	accuracy	NOUN
cana-3964	110	12	in	in	ADP
cana-3964	110	13	classifying	classify	VERB
cana-3964	110	14	breast	breast	NOUN
cana-3964	110	15	lesions	lesion	NOUN
cana-3964	110	16	using	use	VERB
cana-3964	110	17	a	a	DET
cana-3964	110	18	cnn	cnn	NOUN
cana-3964	110	19	architecture	architecture	NOUN
cana-3964	110	20	.	.	PUNCT
cana-3964	111	1	“	"	PUNCT
cana-3964	111	2	ensemble	ensemble	ADJ
cana-3964	111	3	learning	learning	NOUN
cana-3964	111	4	is	be	AUX
cana-3964	111	5	a	a	DET
cana-3964	111	6	technique	technique	NOUN
cana-3964	111	7	that	that	PRON
cana-3964	111	8	combines	combine	VERB
cana-3964	111	9	the	the	DET
cana-3964	111	10	predictions	prediction	NOUN
cana-3964	111	11	of	of	ADP
cana-3964	111	12	multiple	multiple	ADJ
cana-3964	111	13	base	base	NOUN
cana-3964	111	14	models	model	NOUN
cana-3964	111	15	known	know	VERB
cana-3964	111	16	as	as	ADP
cana-3964	111	17	weak	weak	ADJ
cana-3964	111	18	learners	learner	NOUN
cana-3964	111	19	to	to	PART
cana-3964	111	20	create	create	VERB
cana-3964	111	21	a	a	DET
cana-3964	111	22	more	more	ADV
cana-3964	111	23	robust	robust	ADJ
cana-3964	111	24	and	and	CCONJ
cana-3964	111	25	accurate	accurate	ADJ
cana-3964	111	26	final	final	ADJ
cana-3964	111	27	prediction	prediction	NOUN
cana-3964	111	28	”	"	PUNCT
cana-3964	111	29	.	.	PUNCT
cana-3964	112	1	it	it	PRON
cana-3964	112	2	leverages	leverage	VERB
cana-3964	112	3	the	the	DET
cana-3964	112	4	concept	concept	NOUN
cana-3964	112	5	that	that	SCONJ
cana-3964	112	6	aggregating	aggregate	VERB
cana-3964	112	7	the	the	DET
cana-3964	112	8	wisdom	wisdom	NOUN
cana-3964	112	9	of	of	ADP
cana-3964	112	10	multiple	multiple	ADJ
cana-3964	112	11	models	model	NOUN
cana-3964	112	12	often	often	ADV
cana-3964	112	13	yields	yield	VERB
cana-3964	112	14	better	well	ADJ
cana-3964	112	15	results	result	NOUN
cana-3964	112	16	than	than	ADP
cana-3964	112	17	relying	rely	VERB
cana-3964	112	18	on	on	ADP
cana-3964	112	19	a	a	DET
cana-3964	112	20	single	single	ADJ
cana-3964	112	21	model	model	NOUN
cana-3964	112	22	.	.	PUNCT
cana-3964	113	1	knn	knn	PROPN
cana-3964	113	2	is	be	AUX
cana-3964	113	3	simple	simple	ADJ
cana-3964	113	4	to	to	PART
cana-3964	113	5	implement	implement	VERB
cana-3964	113	6	but	but	CCONJ
cana-3964	113	7	not	not	PART
cana-3964	113	8	scalable	scalable	ADJ
cana-3964	113	9	for	for	ADP
cana-3964	113	10	large	large	ADJ
cana-3964	113	11	datasets	dataset	NOUN
cana-3964	113	12	and	and	CCONJ
cana-3964	113	13	has	have	VERB
cana-3964	113	14	high	high	ADJ
cana-3964	113	15	computational	computational	ADJ
cana-3964	113	16	cost	cost	NOUN
cana-3964	113	17	during	during	ADP
cana-3964	113	18	prediction	prediction	NOUN
cana-3964	113	19	,	,	PUNCT
cana-3964	113	20	as	as	SCONJ
cana-3964	113	21	it	it	PRON
cana-3964	113	22	involves	involve	VERB
cana-3964	113	23	calculating	calculate	VERB
cana-3964	113	24	distances	distance	NOUN
cana-3964	113	25	for	for	ADP
cana-3964	113	26	all	all	DET
cana-3964	113	27	instances	instance	NOUN
cana-3964	113	28	in	in	ADP
cana-3964	113	29	the	the	DET
cana-3964	113	30	training	training	NOUN
cana-3964	113	31	dataset	dataset	NOUN
cana-3964	113	32	.	.	PUNCT
cana-3964	114	1	2.7	2.7	NUM
cana-3964	114	2	ensemble	ensemble	ADJ
cana-3964	114	3	machine	machine	NOUN
cana-3964	114	4	learning	learn	VERB
cana-3964	114	5	ensemble	ensemble	ADJ
cana-3964	114	6	machine	machine	NOUN
cana-3964	114	7	learning	learning	NOUN
cana-3964	114	8	is	be	AUX
cana-3964	114	9	focused	focus	VERB
cana-3964	114	10	on	on	ADP
cana-3964	114	11	the	the	DET
cana-3964	114	12	provision	provision	NOUN
cana-3964	114	13	of	of	ADP
cana-3964	114	14	the	the	DET
cana-3964	114	15	final	final	ADJ
cana-3964	114	16	prediction	prediction	NOUN
cana-3964	114	17	by	by	ADP
cana-3964	114	18	aggregating	aggregate	VERB
cana-3964	114	19	several	several	ADJ
cana-3964	114	20	models	model	NOUN
cana-3964	114	21	to	to	PART
cana-3964	114	22	acquired	acquire	VERB
cana-3964	114	23	higher	high	ADJ
cana-3964	114	24	performance	performance	NOUN
cana-3964	114	25	.	.	PUNCT
cana-3964	115	1	the	the	DET
cana-3964	115	2	basic	basic	ADJ
cana-3964	115	3	concept	concept	NOUN
cana-3964	115	4	of	of	ADP
cana-3964	115	5	ensemble	ensemble	ADJ
cana-3964	115	6	methods	method	NOUN
cana-3964	115	7	is	be	AUX
cana-3964	115	8	that	that	SCONJ
cana-3964	115	9	combining	combine	VERB
cana-3964	115	10	different	different	ADJ
cana-3964	115	11	models	model	NOUN
cana-3964	115	12	will	will	AUX
cana-3964	115	13	help	help	VERB
cana-3964	115	14	to	to	PART
cana-3964	115	15	minimize	minimize	VERB
cana-3964	115	16	the	the	DET
cana-3964	115	17	biases	bias	NOUN
cana-3964	115	18	,	,	PUNCT
cana-3964	115	19	variances	variance	NOUN
cana-3964	115	20	and	and	CCONJ
cana-3964	115	21	errors	error	NOUN
cana-3964	115	22	inherent	inherent	ADJ
cana-3964	115	23	in	in	ADP
cana-3964	115	24	each	each	DET
cana-3964	115	25	individual	individual	ADJ
cana-3964	115	26	model	model	NOUN
cana-3964	115	27	.	.	PUNCT
cana-3964	116	1	these	these	PRON
cana-3964	116	2	include	include	VERB
cana-3964	116	3	bagging	bag	VERB
cana-3964	116	4	for	for	ADP
cana-3964	116	5	instance	instance	NOUN
cana-3964	116	6	the	the	DET
cana-3964	116	7	random	random	ADJ
cana-3964	116	8	forests	forest	NOUN
cana-3964	116	9	which	which	PRON
cana-3964	116	10	directly	directly	ADV
cana-3964	116	11	work	work	VERB
cana-3964	116	12	to	to	PART
cana-3964	116	13	reduce	reduce	VERB
cana-3964	116	14	variance	variance	NOUN
cana-3964	116	15	by	by	ADP
cana-3964	116	16	training	train	VERB
cana-3964	116	17	different	different	ADJ
cana-3964	116	18	models	model	NOUN
cana-3964	116	19	on	on	ADP
cana-3964	116	20	bootstrapped	bootstrappe	VERB
cana-3964	116	21	sample	sample	NOUN
cana-3964	116	22	data	datum	NOUN
cana-3964	116	23	,	,	PUNCT
cana-3964	116	24	and	and	CCONJ
cana-3964	116	25	boosting	boost	VERB
cana-3964	116	26	for	for	ADP
cana-3964	116	27	instance	instance	NOUN
cana-3964	116	28	the	the	DET
cana-3964	116	29	adaboost	adaboost	ADJ
cana-3964	116	30	which	which	PRON
cana-3964	116	31	in	in	ADP
cana-3964	116	32	its	its	PRON
cana-3964	116	33	theory	theory	NOUN
cana-3964	116	34	,	,	PUNCT
cana-3964	116	35	concentrates	concentrate	VERB
cana-3964	116	36	on	on	ADP
cana-3964	116	37	correcting	correct	VERB
cana-3964	116	38	for	for	ADP
cana-3964	116	39	mistakes	mistake	NOUN
cana-3964	116	40	done	do	VERB
cana-3964	116	41	in	in	ADP
cana-3964	116	42	the	the	DET
cana-3964	116	43	preceding	precede	VERB
cana-3964	116	44	models	model	NOUN
cana-3964	116	45	.	.	PUNCT
cana-3964	117	1	stacking	stack	VERB
cana-3964	117	2	is	be	AUX
cana-3964	117	3	the	the	DET
cana-3964	117	4	process	process	NOUN
cana-3964	117	5	in	in	ADP
cana-3964	117	6	which	which	PRON
cana-3964	117	7	multiple	multiple	ADJ
cana-3964	117	8	models	model	NOUN
cana-3964	117	9	’	'	PUNCT
cana-3964	117	10	prediction	prediction	NOUN
cana-3964	117	11	is	be	AUX
cana-3964	117	12	aggregated	aggregate	VERB
cana-3964	117	13	by	by	ADP
cana-3964	117	14	another	another	DET
cana-3964	117	15	model	model	NOUN
cana-3964	117	16	for	for	ADP
cana-3964	117	17	the	the	DET
cana-3964	117	18	final	final	ADJ
cana-3964	117	19	result	result	NOUN
cana-3964	117	20	.	.	PUNCT
cana-3964	118	1	ensemble	ensemble	ADJ
cana-3964	118	2	methods	method	NOUN
cana-3964	118	3	are	be	AUX
cana-3964	118	4	used	use	VERB
cana-3964	118	5	in	in	ADP
cana-3964	118	6	all	all	DET
cana-3964	118	7	complex	complex	ADJ
cana-3964	118	8	tasks	task	NOUN
cana-3964	118	9	such	such	ADJ
cana-3964	118	10	as	as	ADP
cana-3964	118	11	classification	classification	NOUN
cana-3964	118	12	and	and	CCONJ
cana-3964	118	13	regression	regression	NOUN
cana-3964	118	14	,	,	PUNCT
cana-3964	118	15	to	to	PART
cana-3964	118	16	obtain	obtain	VERB
cana-3964	118	17	accurate	accurate	ADJ
cana-3964	118	18	and	and	CCONJ
cana-3964	118	19	more	more	ADV
cana-3964	118	20	reliable	reliable	ADJ
cana-3964	118	21	outcomes	outcome	NOUN
cana-3964	118	22	.	.	PUNCT
cana-3964	119	1	each	each	PRON
cana-3964	119	2	of	of	ADP
cana-3964	119	3	the	the	DET
cana-3964	119	4	aforementioned	aforementioned	ADJ
cana-3964	119	5	algorithms	algorithm	NOUN
cana-3964	119	6	has	have	VERB
cana-3964	119	7	advantages	advantage	NOUN
cana-3964	119	8	and	and	CCONJ
cana-3964	119	9	disadvantages	disadvantage	NOUN
cana-3964	119	10	that	that	PRON
cana-3964	119	11	should	should	AUX
cana-3964	119	12	be	be	AUX
cana-3964	119	13	taken	take	VERB
cana-3964	119	14	into	into	ADP
cana-3964	119	15	account	account	NOUN
cana-3964	119	16	when	when	SCONJ
cana-3964	119	17	creating	create	VERB
cana-3964	119	18	models	model	NOUN
cana-3964	119	19	for	for	ADP
cana-3964	119	20	breast	breast	NOUN
cana-3964	119	21	cancer	cancer	NOUN
cana-3964	119	22	diagnosis	diagnosis	NOUN
cana-3964	119	23	.	.	PUNCT
cana-3964	120	1	the	the	DET
cana-3964	120	2	particular	particular	ADJ
cana-3964	120	3	needs	need	NOUN
cana-3964	120	4	,	,	PUNCT
cana-3964	120	5	dataset	dataset	NOUN
cana-3964	120	6	properties	property	NOUN
cana-3964	120	7	,	,	PUNCT
cana-3964	120	8	and	and	CCONJ
cana-3964	120	9	intended	intend	VERB
cana-3964	120	10	performance	performance	NOUN
cana-3964	120	11	indicators	indicator	NOUN
cana-3964	120	12	all	all	PRON
cana-3964	120	13	play	play	VERB
cana-3964	120	14	a	a	DET
cana-3964	120	15	role	role	NOUN
cana-3964	120	16	in	in	ADP
cana-3964	120	17	choosing	choose	VERB
cana-3964	120	18	the	the	DET
cana-3964	120	19	best	good	ADJ
cana-3964	120	20	method	method	NOUN
cana-3964	120	21	.	.	PUNCT
cana-3964	121	1	the	the	DET
cana-3964	121	2	performance	performance	NOUN
cana-3964	121	3	of	of	ADP
cana-3964	121	4	ml	ml	ADP
cana-3964	121	5	algorithms	algorithm	NOUN
cana-3964	121	6	can	can	AUX
cana-3964	121	7	be	be	AUX
cana-3964	121	8	generalized	generalize	VERB
cana-3964	121	9	by	by	ADP
cana-3964	121	10	considering	consider	VERB
cana-3964	121	11	key	key	ADJ
cana-3964	121	12	factors	factor	NOUN
cana-3964	121	13	such	such	ADJ
cana-3964	121	14	as	as	ADP
cana-3964	121	15	accuracy	accuracy	NOUN
cana-3964	121	16	,	,	PUNCT
cana-3964	121	17	sensitivity	sensitivity	NOUN
cana-3964	121	18	,	,	PUNCT
cana-3964	121	19	and	and	CCONJ
cana-3964	121	20	f1	f1	NOUN
cana-3964	121	21	-	-	PUNCT
cana-3964	121	22	score	score	NOUN
cana-3964	121	23	.	.	PUNCT
cana-3964	122	1	fig	fig	NOUN
cana-3964	122	2	.	.	PUNCT
cana-3964	123	1	3	3	NUM
cana-3964	123	2	shows	show	VERB
cana-3964	123	3	the	the	DET
cana-3964	123	4	performance	performance	NOUN
cana-3964	123	5	of	of	ADP
cana-3964	123	6	various	various	ADJ
cana-3964	123	7	ml	ml	NOUN
cana-3964	123	8	algorithms	algorithm	NOUN
cana-3964	123	9	and	and	CCONJ
cana-3964	123	10	branches	branch	NOUN
cana-3964	123	11	out	out	ADP
cana-3964	123	12	to	to	PART
cana-3964	123	13	include	include	VERB
cana-3964	123	14	decision	decision	NOUN
cana-3964	123	15	tree	tree	NOUN
cana-3964	123	16	and	and	CCONJ
cana-3964	123	17	svm	svm	PROPN
cana-3964	123	18	applied	apply	VERB
cana-3964	123	19	to	to	ADP
cana-3964	123	20	specific	specific	ADJ
cana-3964	123	21	datasets	dataset	NOUN
cana-3964	123	22	,	,	PUNCT
cana-3964	123	23	such	such	ADJ
cana-3964	123	24	as	as	ADP
cana-3964	123	25	wdbc	wdbc	NOUN
cana-3964	123	26	and	and	CCONJ
cana-3964	123	27	ultrasound	ultrasound	NOUN
cana-3964	123	28	images	image	NOUN
cana-3964	123	29	,	,	PUNCT
cana-3964	123	30	with	with	SCONJ
cana-3964	123	31	their	their	PRON
cana-3964	123	32	respective	respective	ADJ
cana-3964	123	33	performance	performance	NOUN
cana-3964	123	34	metrics	metric	NOUN
cana-3964	123	35	presented	present	VERB
cana-3964	123	36	.	.	PUNCT
cana-3964	124	1	another	another	DET
cana-3964	124	2	branch	branch	NOUN
cana-3964	124	3	explores	explore	VERB
cana-3964	124	4	deep	deep	ADJ
cana-3964	124	5	neural	neural	ADJ
cana-3964	124	6	networks	network	NOUN
cana-3964	124	7	applied	apply	VERB
cana-3964	124	8	to	to	ADP
cana-3964	124	9	the	the	DET
cana-3964	124	10	breakhis	breakhis	ADJ
cana-3964	124	11	dataset	dataset	NOUN
cana-3964	124	12	,	,	PUNCT
cana-3964	124	13	along	along	ADP
cana-3964	124	14	with	with	ADP
cana-3964	124	15	the	the	DET
cana-3964	124	16	expected	expect	VERB
cana-3964	124	17	accuracy	accuracy	NOUN
cana-3964	124	18	,	,	PUNCT
cana-3964	124	19	sensitivity	sensitivity	NOUN
cana-3964	124	20	,	,	PUNCT
cana-3964	124	21	and	and	CCONJ
cana-3964	124	22	specificity	specificity	NOUN
cana-3964	124	23	values	value	NOUN
cana-3964	124	24	.	.	PUNCT
cana-3964	125	1	in	in	ADP
cana-3964	125	2	the	the	DET
cana-3964	125	3	end	end	NOUN
cana-3964	125	4	,	,	PUNCT
cana-3964	125	5	the	the	DET
cana-3964	125	6	process	process	NOUN
cana-3964	125	7	leads	lead	VERB
cana-3964	125	8	to	to	ADP
cana-3964	125	9	a	a	DET
cana-3964	125	10	conclusion	conclusion	NOUN
cana-3964	125	11	and	and	CCONJ
cana-3964	125	12	insights	insight	NOUN
cana-3964	125	13	,	,	PUNCT
cana-3964	125	14	likely	likely	ADV
cana-3964	125	15	summarizing	summarize	VERB
cana-3964	125	16	which	which	DET
cana-3964	125	17	algorithms	algorithm	NOUN
cana-3964	125	18	performed	perform	VERB
cana-3964	125	19	best	well	ADV
cana-3964	125	20	on	on	ADP
cana-3964	125	21	different	different	ADJ
cana-3964	125	22	datasets	dataset	NOUN
cana-3964	125	23	and	and	CCONJ
cana-3964	125	24	providing	provide	VERB
cana-3964	125	25	valuable	valuable	ADJ
cana-3964	125	26	information	information	NOUN
cana-3964	125	27	for	for	ADP
cana-3964	125	28	breast	breast	NOUN
cana-3964	125	29	cancer	cancer	NOUN
cana-3964	125	30	detection	detection	NOUN
cana-3964	125	31	.	.	PUNCT
cana-3964	126	1	communications	communication	NOUN
cana-3964	126	2	on	on	ADP
cana-3964	126	3	applied	apply	VERB
cana-3964	126	4	nonlinear	nonlinear	ADJ
cana-3964	126	5	analysis	analysis	NOUN
cana-3964	126	6	issn	issn	NOUN
cana-3964	126	7	:	:	PUNCT
cana-3964	126	8	1074	1074	NUM
cana-3964	126	9	-	-	PUNCT
cana-3964	126	10	133x	133x	NUM
cana-3964	126	11	vol	vol	NOUN
cana-3964	126	12	32	32	NUM
cana-3964	126	13	no	no	NOUN
cana-3964	126	14	.	.	PUNCT
cana-3964	127	1	9s	9s	NUM
cana-3964	127	2	(	(	PUNCT
cana-3964	127	3	2025	2025	NUM
cana-3964	127	4	)	)	PUNCT
cana-3964	127	5	559	559	NUM
cana-3964	127	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	127	7	fig	fig	NOUN
cana-3964	127	8	.	.	PUNCT
cana-3964	128	1	3	3	NUM
cana-3964	128	2	generalized	generalized	ADJ
cana-3964	128	3	view	view	NOUN
cana-3964	128	4	of	of	ADP
cana-3964	128	5	performance	performance	NOUN
cana-3964	128	6	of	of	ADP
cana-3964	128	7	various	various	ADJ
cana-3964	128	8	ml	ml	NOUN
cana-3964	128	9	algorithms	algorithm	NOUN
cana-3964	128	10	in	in	ADP
cana-3964	128	11	breast	breast	NOUN
cana-3964	128	12	cancer	cancer	NOUN
cana-3964	128	13	diagnosis	diagnosis	NOUN
cana-3964	128	14	3	3	NUM
cana-3964	128	15	.	.	PUNCT
cana-3964	129	1	datasets	dataset	NOUN
cana-3964	129	2	used	use	VERB
cana-3964	129	3	in	in	ADP
cana-3964	129	4	breast	breast	NOUN
cana-3964	129	5	cancer	cancer	NOUN
cana-3964	129	6	diagnosis	diagnosis	NOUN
cana-3964	129	7	the	the	DET
cana-3964	129	8	studies	study	NOUN
cana-3964	129	9	reviewed	review	VERB
cana-3964	129	10	in	in	ADP
cana-3964	129	11	this	this	DET
cana-3964	129	12	paper	paper	NOUN
cana-3964	129	13	draw	draw	VERB
cana-3964	129	14	upon	upon	SCONJ
cana-3964	129	15	a	a	DET
cana-3964	129	16	variety	variety	NOUN
cana-3964	129	17	of	of	ADP
cana-3964	129	18	datasets	dataset	NOUN
cana-3964	129	19	,	,	PUNCT
cana-3964	129	20	each	each	PRON
cana-3964	129	21	tailored	tailor	VERB
cana-3964	129	22	to	to	ADP
cana-3964	129	23	specific	specific	ADJ
cana-3964	129	24	research	research	NOUN
cana-3964	129	25	objectives	objective	NOUN
cana-3964	129	26	and	and	CCONJ
cana-3964	129	27	methodologies	methodology	NOUN
cana-3964	129	28	.	.	PUNCT
cana-3964	130	1	table	table	NOUN
cana-3964	130	2	1	1	NUM
cana-3964	130	3	provides	provide	VERB
cana-3964	130	4	various	various	ADJ
cana-3964	130	5	datasets	dataset	NOUN
cana-3964	130	6	used	use	VERB
cana-3964	130	7	in	in	ADP
cana-3964	130	8	breast	breast	NOUN
cana-3964	130	9	cancer	cancer	NOUN
cana-3964	130	10	diagnosis	diagnosis	NOUN
cana-3964	130	11	,	,	PUNCT
cana-3964	130	12	as	as	SCONJ
cana-3964	130	13	analysed	analyse	VERB
cana-3964	130	14	in	in	ADP
cana-3964	130	15	this	this	DET
cana-3964	130	16	study	study	NOUN
cana-3964	130	17	.	.	PUNCT
cana-3964	131	1	most	most	ADJ
cana-3964	131	2	of	of	ADP
cana-3964	131	3	the	the	DET
cana-3964	131	4	papers	paper	NOUN
cana-3964	131	5	in	in	ADP
cana-3964	131	6	this	this	DET
cana-3964	131	7	review	review	NOUN
cana-3964	131	8	are	be	AUX
cana-3964	131	9	based	base	VERB
cana-3964	131	10	on	on	ADP
cana-3964	131	11	the	the	DET
cana-3964	131	12	“	"	PUNCT
cana-3964	131	13	wisconsin	wisconsin	PROPN
cana-3964	131	14	diagnostic	diagnostic	ADJ
cana-3964	131	15	breast	breast	NOUN
cana-3964	131	16	cancer	cancer	NOUN
cana-3964	131	17	(	(	PUNCT
cana-3964	131	18	wdbc	wdbc	PROPN
cana-3964	131	19	)	)	PUNCT
cana-3964	131	20	”	"	PUNCT
cana-3964	131	21	dataset	dataset	NOUN
cana-3964	132	1	.	.	PUNCT
cana-3964	132	2	table	table	NOUN
cana-3964	132	3	1	1	NUM
cana-3964	132	4	various	various	ADJ
cana-3964	132	5	datasets	dataset	NOUN
cana-3964	132	6	used	use	VERB
cana-3964	132	7	in	in	ADP
cana-3964	132	8	breast	breast	NOUN
cana-3964	132	9	cancer	cancer	NOUN
cana-3964	132	10	diagnosis	diagnosis	NOUN
cana-3964	132	11	dataset	dataset	NOUN
cana-3964	132	12	name	name	NOUN
cana-3964	132	13	description	description	NOUN
cana-3964	132	14	features	feature	VERB
cana-3964	132	15	labels	label	NOUN
cana-3964	132	16	source	source	NOUN
cana-3964	132	17	application	application	NOUN
cana-3964	132	18	wisconsin	wisconsin	PROPN
cana-3964	132	19	diagnostic	diagnostic	PROPN
cana-3964	132	20	breast	breast	NOUN
cana-3964	132	21	cancer	cancer	NOUN
cana-3964	132	22	(	(	PUNCT
cana-3964	132	23	wdbc	wdbc	PROPN
cana-3964	132	24	)	)	PUNCT
cana-3964	132	25	features	feature	NOUN
cana-3964	132	26	computed	compute	VERB
cana-3964	132	27	from	from	ADP
cana-3964	132	28	digitized	digitize	VERB
cana-3964	132	29	fna	fna	NOUN
cana-3964	132	30	images	image	NOUN
cana-3964	132	31	of	of	ADP
cana-3964	132	32	breast	breast	NOUN
cana-3964	132	33	mass	mass	NOUN
cana-3964	132	34	radius	radius	NOUN
cana-3964	132	35	,	,	PUNCT
cana-3964	132	36	texture	texture	ADJ
cana-3964	132	37	,	,	PUNCT
cana-3964	132	38	smoothness	smoothness	ADJ
cana-3964	132	39	,	,	PUNCT
cana-3964	132	40	compactness	compactness	NOUN
cana-3964	132	41	,	,	PUNCT
cana-3964	132	42	concavity	concavity	NOUN
cana-3964	132	43	,	,	PUNCT
cana-3964	132	44	symmetry	symmetry	NOUN
cana-3964	132	45	and	and	CCONJ
cana-3964	132	46	fractal	fractal	ADJ
cana-3964	132	47	dimension	dimension	NOUN
cana-3964	132	48	,	,	PUNCT
cana-3964	132	49	etc	etc	X
cana-3964	132	50	.	.	X
cana-3964	132	51	benign	benign	ADJ
cana-3964	132	52	(	(	PUNCT
cana-3964	132	53	b	b	NOUN
cana-3964	132	54	)	)	PUNCT
cana-3964	132	55	,	,	PUNCT
cana-3964	132	56	maligna	maligna	PROPN
cana-3964	132	57	nt	nt	PROPN
cana-3964	132	58	(	(	PUNCT
cana-3964	132	59	m	m	NOUN
cana-3964	132	60	)	)	PUNCT
cana-3964	132	61	uci	uci	NOUN
cana-3964	132	62	machine	machine	NOUN
cana-3964	132	63	learning	learning	PROPN
cana-3964	132	64	reposito	reposito	NOUN
cana-3964	132	65	ry	ry	AUX
cana-3964	132	66	developing	develop	VERB
cana-3964	132	67	predictive	predictive	ADJ
cana-3964	132	68	models	model	NOUN
cana-3964	132	69	for	for	ADP
cana-3964	132	70	classifying	classify	VERB
cana-3964	132	71	breast	breast	NOUN
cana-3964	132	72	masses	masse	NOUN
cana-3964	132	73	as	as	ADP
cana-3964	132	74	benign	benign	ADJ
cana-3964	132	75	or	or	CCONJ
cana-3964	132	76	malignant	malignant	ADJ
cana-3964	132	77	based	base	VERB
cana-3964	132	78	on	on	ADP
cana-3964	132	79	extracted	extract	VERB
cana-3964	132	80	features	feature	NOUN
cana-3964	132	81	.	.	PUNCT
cana-3964	133	1	breast	breast	NOUN
cana-3964	133	2	cancer	cancer	NOUN
cana-3964	133	3	histopathologi	histopathologi	PROPN
cana-3964	133	4	cal	cal	PROPN
cana-3964	133	5	database	database	NOUN
cana-3964	133	6	(	(	PUNCT
cana-3964	133	7	breakhis	breakhis	ADJ
cana-3964	133	8	)	)	PUNCT
cana-3964	133	9	histopatholog	histopatholog	VERB
cana-3964	133	10	ical	ical	ADJ
cana-3964	133	11	images	image	NOUN
cana-3964	133	12	of	of	ADP
cana-3964	133	13	breast	breast	NOUN
cana-3964	133	14	tissue	tissue	NOUN
cana-3964	133	15	samples	sample	VERB
cana-3964	133	16	highresolution	highresolution	NOUN
cana-3964	133	17	images	image	NOUN
cana-3964	133	18	of	of	ADP
cana-3964	133	19	cellular	cellular	ADJ
cana-3964	133	20	structures	structure	NOUN
cana-3964	133	21	types	type	NOUN
cana-3964	133	22	of	of	ADP
cana-3964	133	23	breast	breast	NOUN
cana-3964	133	24	cancer	cancer	NOUN
cana-3964	133	25	:	:	PUNCT
cana-3964	133	26	invasive	invasive	ADJ
cana-3964	133	27	ductal	ductal	ADJ
cana-3964	133	28	carcinom	carcinom	PROPN
cana-3964	133	29	a	a	DET
cana-3964	133	30	,	,	PUNCT
cana-3964	133	31	lobular	lobular	ADJ
cana-3964	133	32	carcinom	carcinom	NOUN
cana-3964	133	33	a	a	PRON
cana-3964	133	34	,	,	PUNCT
cana-3964	133	35	etc	etc	X
cana-3964	133	36	.	.	X
cana-3964	134	1	breakhis	breakhis	ADJ
cana-3964	134	2	database	database	NOUN
cana-3964	134	3	developing	develop	VERB
cana-3964	134	4	imagebased	imagebase	VERB
cana-3964	134	5	classification	classification	NOUN
cana-3964	134	6	and	and	CCONJ
cana-3964	134	7	segmentation	segmentation	NOUN
cana-3964	134	8	models	model	NOUN
cana-3964	134	9	for	for	ADP
cana-3964	134	10	identifying	identify	VERB
cana-3964	134	11	and	and	CCONJ
cana-3964	134	12	classifying	classify	VERB
cana-3964	134	13	different	different	ADJ
cana-3964	134	14	types	type	NOUN
cana-3964	134	15	of	of	ADP
cana-3964	134	16	breast	breast	NOUN
cana-3964	134	17	cancer	cancer	NOUN
cana-3964	134	18	from	from	ADP
cana-3964	134	19	histopathological	histopathological	ADJ
cana-3964	134	20	images	image	NOUN
cana-3964	134	21	.	.	PUNCT
cana-3964	134	22	communications	communication	NOUN
cana-3964	134	23	on	on	ADP
cana-3964	134	24	applied	apply	VERB
cana-3964	134	25	nonlinear	nonlinear	ADJ
cana-3964	134	26	analysis	analysis	NOUN
cana-3964	134	27	issn	issn	NOUN
cana-3964	134	28	:	:	PUNCT
cana-3964	134	29	1074	1074	NUM
cana-3964	134	30	-	-	PUNCT
cana-3964	134	31	133x	133x	NUM
cana-3964	134	32	vol	vol	NOUN
cana-3964	134	33	32	32	NUM
cana-3964	134	34	no	no	NOUN
cana-3964	134	35	.	.	PUNCT
cana-3964	135	1	9s	9s	NUM
cana-3964	135	2	(	(	PUNCT
cana-3964	135	3	2025	2025	NUM
cana-3964	135	4	)	)	PUNCT
cana-3964	135	5	560	560	NUM
cana-3964	135	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	135	7	mammograph	mammograph	NOUN
cana-3964	135	8	y	y	PROPN
cana-3964	135	9	databases	database	NOUN
cana-3964	135	10	mammograph	mammograph	NOUN
cana-3964	135	11	ic	ic	PROPN
cana-3964	135	12	images	image	NOUN
cana-3964	135	13	captured	capture	VERB
cana-3964	135	14	using	use	VERB
cana-3964	135	15	x	x	PROPN
cana-3964	135	16	-	-	NOUN
cana-3964	135	17	ray	ray	NOUN
cana-3964	135	18	imaging	imaging	NOUN
cana-3964	135	19	grayscale	grayscale	NOUN
cana-3964	135	20	images	image	NOUN
cana-3964	135	21	of	of	ADP
cana-3964	135	22	breast	breast	NOUN
cana-3964	135	23	tissue	tissue	NOUN
cana-3964	135	24	density	density	NOUN
cana-3964	135	25	and	and	CCONJ
cana-3964	135	26	anomalies	anomaly	NOUN
cana-3964	135	27	normal	normal	ADJ
cana-3964	135	28	,	,	PUNCT
cana-3964	135	29	benign	benign	ADJ
cana-3964	135	30	,	,	PUNCT
cana-3964	135	31	maligna	maligna	PROPN
cana-3964	135	32	nt	nt	PROPN
cana-3964	135	33	,	,	PUNCT
cana-3964	135	34	birads	birad	NOUN
cana-3964	135	35	categorie	categorie	PROPN
cana-3964	135	36	s	s	PART
cana-3964	135	37	various	various	ADJ
cana-3964	135	38	medical	medical	ADJ
cana-3964	135	39	imaging	imaging	NOUN
cana-3964	135	40	repositor	repositor	NOUN
cana-3964	135	41	ies	ies	PROPN
cana-3964	135	42	and	and	CCONJ
cana-3964	135	43	institutio	institutio	NOUN
cana-3964	135	44	ns	ns	CCONJ
cana-3964	135	45	developing	develop	VERB
cana-3964	135	46	machine	machine	NOUN
cana-3964	135	47	-	-	PUNCT
cana-3964	135	48	learning	learn	VERB
cana-3964	135	49	models	model	NOUN
cana-3964	135	50	for	for	ADP
cana-3964	135	51	mammogram	mammogram	NOUN
cana-3964	135	52	interpretation	interpretation	NOUN
cana-3964	135	53	,	,	PUNCT
cana-3964	135	54	anomaly	anomaly	NOUN
cana-3964	135	55	detection	detection	NOUN
cana-3964	135	56	,	,	PUNCT
cana-3964	135	57	and	and	CCONJ
cana-3964	135	58	breast	breast	NOUN
cana-3964	135	59	cancer	cancer	NOUN
cana-3964	135	60	risk	risk	NOUN
cana-3964	135	61	assessment	assessment	NOUN
cana-3964	135	62	.	.	PUNCT
cana-3964	136	1	ultrasound	ultrasound	NOUN
cana-3964	136	2	image	image	NOUN
cana-3964	136	3	databases	database	NOUN
cana-3964	136	4	ultrasound	ultrasound	NOUN
cana-3964	136	5	images	image	NOUN
cana-3964	136	6	created	create	VERB
cana-3964	136	7	using	use	VERB
cana-3964	136	8	sound	sound	NOUN
cana-3964	136	9	waves	wave	NOUN
cana-3964	136	10	images	image	NOUN
cana-3964	136	11	depicting	depict	VERB
cana-3964	136	12	tissue	tissue	NOUN
cana-3964	136	13	density	density	NOUN
cana-3964	136	14	,	,	PUNCT
cana-3964	136	15	texture	texture	NOUN
cana-3964	136	16	,	,	PUNCT
cana-3964	136	17	and	and	CCONJ
cana-3964	136	18	lesions	lesion	NOUN
cana-3964	136	19	lesion	lesion	NOUN
cana-3964	136	20	character	character	NOUN
cana-3964	136	21	istics	istic	NOUN
cana-3964	136	22	,	,	PUNCT
cana-3964	136	23	clinical	clinical	ADJ
cana-3964	136	24	outcome	outcome	NOUN
cana-3964	136	25	s	s	VERB
cana-3964	136	26	medical	medical	ADJ
cana-3964	136	27	institutio	institutio	PROPN
cana-3964	136	28	ns	ns	PROPN
cana-3964	136	29	,	,	PUNCT
cana-3964	136	30	research	research	NOUN
cana-3964	136	31	repositor	repositor	NOUN
cana-3964	136	32	ies	ie	NOUN
cana-3964	136	33	developing	develop	VERB
cana-3964	136	34	machine	machine	NOUN
cana-3964	136	35	-	-	PUNCT
cana-3964	136	36	learning	learn	VERB
cana-3964	136	37	algorithms	algorithm	NOUN
cana-3964	136	38	for	for	ADP
cana-3964	136	39	ultrasound	ultrasound	ADJ
cana-3964	136	40	image	image	NOUN
cana-3964	136	41	analysis	analysis	NOUN
cana-3964	136	42	and	and	CCONJ
cana-3964	136	43	breast	breast	NOUN
cana-3964	136	44	lesion	lesion	NOUN
cana-3964	136	45	detection	detection	NOUN
cana-3964	136	46	.	.	PUNCT
cana-3964	137	1	thermographi	thermographi	PROPN
cana-3964	137	2	c	c	NOUN
cana-3964	137	3	image	image	NOUN
cana-3964	137	4	databases	database	NOUN
cana-3964	137	5	infrared	infrare	VERB
cana-3964	137	6	images	image	NOUN
cana-3964	137	7	capturing	capture	VERB
cana-3964	137	8	heat	heat	NOUN
cana-3964	137	9	patterns	pattern	NOUN
cana-3964	137	10	emitted	emit	VERB
cana-3964	137	11	by	by	ADP
cana-3964	137	12	the	the	DET
cana-3964	137	13	body	body	NOUN
cana-3964	137	14	images	image	NOUN
cana-3964	137	15	showing	show	VERB
cana-3964	137	16	temperature	temperature	NOUN
cana-3964	137	17	variations	variation	NOUN
cana-3964	137	18	in	in	ADP
cana-3964	137	19	breast	breast	NOUN
cana-3964	137	20	tissue	tissue	NOUN
cana-3964	137	21	abnorma	abnorma	NOUN
cana-3964	137	22	l	l	PROPN
cana-3964	137	23	temperat	temperat	PROPN
cana-3964	137	24	ure	ure	PROPN
cana-3964	137	25	patterns	pattern	VERB
cana-3964	137	26	medical	medical	ADJ
cana-3964	137	27	research	research	NOUN
cana-3964	137	28	database	database	NOUN
cana-3964	137	29	s	s	PART
cana-3964	137	30	thermal	thermal	ADJ
cana-3964	137	31	analysis	analysis	NOUN
cana-3964	137	32	and	and	CCONJ
cana-3964	137	33	machine	machine	NOUN
cana-3964	137	34	learning	learning	NOUN
cana-3964	137	35	-	-	PUNCT
cana-3964	137	36	based	base	VERB
cana-3964	137	37	detection	detection	NOUN
cana-3964	137	38	of	of	ADP
cana-3964	137	39	temperature	temperature	NOUN
cana-3964	137	40	anomalies	anomaly	NOUN
cana-3964	137	41	in	in	ADP
cana-3964	137	42	breast	breast	NOUN
cana-3964	137	43	tissue	tissue	NOUN
cana-3964	137	44	.	.	PUNCT
cana-3964	138	1	these	these	PRON
cana-3964	138	2	are	be	AUX
cana-3964	138	3	some	some	PRON
cana-3964	138	4	of	of	ADP
cana-3964	138	5	the	the	DET
cana-3964	138	6	key	key	ADJ
cana-3964	138	7	types	type	NOUN
cana-3964	138	8	of	of	ADP
cana-3964	138	9	datasets	dataset	NOUN
cana-3964	138	10	used	use	VERB
cana-3964	138	11	for	for	ADP
cana-3964	138	12	bc	bc	PROPN
cana-3964	138	13	diagnosis	diagnosis	NOUN
cana-3964	138	14	using	use	VERB
cana-3964	138	15	ml	ml	NOUN
cana-3964	138	16	techniques	technique	NOUN
cana-3964	138	17	.	.	PUNCT
cana-3964	139	1	each	each	DET
cana-3964	139	2	dataset	dataset	NOUN
cana-3964	139	3	has	have	VERB
cana-3964	139	4	its	its	PRON
cana-3964	139	5	unique	unique	ADJ
cana-3964	139	6	characteristics	characteristic	NOUN
cana-3964	139	7	and	and	CCONJ
cana-3964	139	8	focuses	focus	VERB
cana-3964	139	9	on	on	ADP
cana-3964	139	10	different	different	ADJ
cana-3964	139	11	aspects	aspect	NOUN
cana-3964	139	12	of	of	ADP
cana-3964	139	13	breast	breast	NOUN
cana-3964	139	14	cancer	cancer	NOUN
cana-3964	139	15	detection	detection	NOUN
cana-3964	139	16	and	and	CCONJ
cana-3964	139	17	classification	classification	NOUN
cana-3964	139	18	,	,	PUNCT
cana-3964	139	19	contributing	contribute	VERB
cana-3964	139	20	to	to	ADP
cana-3964	139	21	the	the	DET
cana-3964	139	22	creation	creation	NOUN
cana-3964	139	23	of	of	ADP
cana-3964	139	24	precise	precise	ADJ
cana-3964	139	25	and	and	CCONJ
cana-3964	139	26	efficient	efficient	ADJ
cana-3964	139	27	diagnostic	diagnostic	ADJ
cana-3964	139	28	models	model	NOUN
cana-3964	139	29	.	.	PUNCT
cana-3964	140	1	table	table	NOUN
cana-3964	140	2	2	2	NUM
cana-3964	140	3	summarizes	summarize	NOUN
cana-3964	140	4	the	the	DET
cana-3964	140	5	strengths	strength	NOUN
cana-3964	140	6	and	and	CCONJ
cana-3964	140	7	limitations	limitation	NOUN
cana-3964	140	8	of	of	ADP
cana-3964	140	9	each	each	DET
cana-3964	140	10	breast	breast	NOUN
cana-3964	140	11	cancer	cancer	NOUN
cana-3964	140	12	dataset	dataset	VERB
cana-3964	140	13	in	in	ADP
cana-3964	140	14	a	a	DET
cana-3964	140	15	clear	clear	ADJ
cana-3964	140	16	and	and	CCONJ
cana-3964	140	17	organized	organized	ADJ
cana-3964	140	18	format	format	NOUN
cana-3964	140	19	.	.	PUNCT
cana-3964	141	1	these	these	DET
cana-3964	141	2	datasets	dataset	NOUN
cana-3964	141	3	serve	serve	VERB
cana-3964	141	4	as	as	ADP
cana-3964	141	5	essential	essential	ADJ
cana-3964	141	6	resources	resource	NOUN
cana-3964	141	7	for	for	ADP
cana-3964	141	8	advancing	advance	VERB
cana-3964	141	9	breast	breast	NOUN
cana-3964	141	10	cancer	cancer	NOUN
cana-3964	141	11	diagnosis	diagnosis	NOUN
cana-3964	141	12	through	through	ADP
cana-3964	141	13	ml	ml	NOUN
cana-3964	141	14	techniques	technique	NOUN
cana-3964	141	15	.	.	PUNCT
cana-3964	142	1	they	they	PRON
cana-3964	142	2	encompass	encompass	VERB
cana-3964	142	3	various	various	ADJ
cana-3964	142	4	data	datum	NOUN
cana-3964	142	5	modalities	modality	NOUN
cana-3964	142	6	,	,	PUNCT
cana-3964	142	7	including	include	VERB
cana-3964	142	8	clinical	clinical	ADJ
cana-3964	142	9	features	feature	NOUN
cana-3964	142	10	,	,	PUNCT
cana-3964	142	11	histopathological	histopathological	ADJ
cana-3964	142	12	images	image	NOUN
cana-3964	142	13	,	,	PUNCT
cana-3964	142	14	mammograms	mammogram	NOUN
cana-3964	142	15	,	,	PUNCT
cana-3964	142	16	ultrasound	ultrasound	NOUN
cana-3964	142	17	images	image	NOUN
cana-3964	142	18	,	,	PUNCT
cana-3964	142	19	and	and	CCONJ
cana-3964	142	20	thermographic	thermographic	ADJ
cana-3964	142	21	data	datum	NOUN
cana-3964	142	22	,	,	PUNCT
cana-3964	142	23	facilitating	facilitate	VERB
cana-3964	142	24	the	the	DET
cana-3964	142	25	development	development	NOUN
cana-3964	142	26	of	of	ADP
cana-3964	142	27	good	good	ADJ
cana-3964	142	28	diagnostic	diagnostic	ADJ
cana-3964	142	29	models	model	NOUN
cana-3964	142	30	for	for	ADP
cana-3964	142	31	improved	improved	ADJ
cana-3964	142	32	patient	patient	ADJ
cana-3964	142	33	care	care	NOUN
cana-3964	142	34	.	.	PUNCT
cana-3964	143	1	most	most	ADJ
cana-3964	143	2	of	of	ADP
cana-3964	143	3	the	the	DET
cana-3964	143	4	papers	paper	NOUN
cana-3964	143	5	in	in	ADP
cana-3964	143	6	this	this	DET
cana-3964	143	7	study	study	NOUN
cana-3964	143	8	used	use	VERB
cana-3964	143	9	the	the	DET
cana-3964	143	10	“	"	PUNCT
cana-3964	143	11	wdbc	wdbc	PROPN
cana-3964	143	12	”	"	PUNCT
cana-3964	143	13	dataset	dataset	VERB
cana-3964	143	14	for	for	ADP
cana-3964	143	15	breast	breast	NOUN
cana-3964	143	16	cancer	cancer	NOUN
cana-3964	143	17	diagnosis	diagnosis	NOUN
cana-3964	143	18	,	,	PUNCT
cana-3964	143	19	which	which	PRON
cana-3964	143	20	is	be	AUX
cana-3964	143	21	described	describe	VERB
cana-3964	143	22	in	in	ADP
cana-3964	143	23	this	this	DET
cana-3964	143	24	section	section	NOUN
cana-3964	143	25	.	.	PUNCT
cana-3964	144	1	the	the	DET
cana-3964	144	2	breast	breast	NOUN
cana-3964	144	3	cancer	cancer	NOUN
cana-3964	144	4	histopathological	histopathological	ADJ
cana-3964	144	5	database	database	NOUN
cana-3964	144	6	(	(	PUNCT
cana-3964	144	7	breakhis	breakhis	ADJ
cana-3964	144	8	)	)	PUNCT
cana-3964	144	9	has	have	VERB
cana-3964	144	10	rich	rich	ADJ
cana-3964	144	11	histopathological	histopathological	ADJ
cana-3964	144	12	images	image	NOUN
cana-3964	144	13	,	,	PUNCT
cana-3964	144	14	offers	offer	VERB
cana-3964	144	15	detailed	detailed	ADJ
cana-3964	144	16	cellular	cellular	ADJ
cana-3964	144	17	characterization	characterization	NOUN
cana-3964	144	18	with	with	ADP
cana-3964	144	19	different	different	ADJ
cana-3964	144	20	sample	sample	NOUN
cana-3964	144	21	types	type	NOUN
cana-3964	144	22	,	,	PUNCT
cana-3964	144	23	yet	yet	ADV
cana-3964	144	24	comes	come	VERB
cana-3964	144	25	with	with	ADP
cana-3964	144	26	the	the	DET
cana-3964	144	27	drawback	drawback	NOUN
cana-3964	144	28	,	,	PUNCT
cana-3964	144	29	it	it	PRON
cana-3964	144	30	is	be	AUX
cana-3964	144	31	more	more	ADV
cana-3964	144	32	complex	complex	ADJ
cana-3964	144	33	and	and	CCONJ
cana-3964	144	34	needs	need	VERB
cana-3964	144	35	a	a	DET
cana-3964	144	36	high	high	ADJ
cana-3964	144	37	and	and	CCONJ
cana-3964	144	38	time	time	NOUN
cana-3964	144	39	-	-	PUNCT
cana-3964	144	40	consuming	consume	VERB
cana-3964	144	41	computational	computational	ADJ
cana-3964	144	42	power	power	NOUN
cana-3964	144	43	.	.	PUNCT
cana-3964	145	1	mammography	mammography	NOUN
cana-3964	145	2	databases	database	NOUN
cana-3964	145	3	give	give	VERB
cana-3964	145	4	information	information	NOUN
cana-3964	145	5	about	about	ADP
cana-3964	145	6	the	the	DET
cana-3964	145	7	mammographic	mammographic	ADJ
cana-3964	145	8	image	image	NOUN
cana-3964	145	9	reflecting	reflect	VERB
cana-3964	145	10	the	the	DET
cana-3964	145	11	breast	breast	NOUN
cana-3964	145	12	tissue	tissue	NOUN
cana-3964	145	13	density	density	NOUN
cana-3964	145	14	and	and	CCONJ
cana-3964	145	15	abnormality	abnormality	NOUN
cana-3964	145	16	based	base	VERB
cana-3964	145	17	on	on	ADP
cana-3964	145	18	multicategory	multicategory	ADJ
cana-3964	145	19	labels	label	NOUN
cana-3964	145	20	but	but	CCONJ
cana-3964	145	21	is	be	AUX
cana-3964	145	22	invasive	invasive	ADJ
cana-3964	145	23	,	,	PUNCT
cana-3964	145	24	involves	involve	VERB
cana-3964	145	25	radiation	radiation	NOUN
cana-3964	145	26	exposure	exposure	NOUN
cana-3964	145	27	,	,	PUNCT
cana-3964	145	28	and	and	CCONJ
cana-3964	145	29	needs	need	VERB
cana-3964	145	30	the	the	DET
cana-3964	145	31	attention	attention	NOUN
cana-3964	145	32	of	of	ADP
cana-3964	145	33	a	a	DET
cana-3964	145	34	specialist	specialist	NOUN
cana-3964	145	35	.	.	PUNCT
cana-3964	146	1	ultrasound	ultrasound	NOUN
cana-3964	146	2	image	image	NOUN
cana-3964	146	3	databases	database	NOUN
cana-3964	146	4	present	present	VERB
cana-3964	146	5	a	a	DET
cana-3964	146	6	non	non	ADJ
cana-3964	146	7	-	-	ADJ
cana-3964	146	8	invasive	invasive	ADJ
cana-3964	146	9	real	real	ADJ
cana-3964	146	10	-	-	PUNCT
cana-3964	146	11	time	time	NOUN
cana-3964	146	12	information	information	NOUN
cana-3964	146	13	qualified	qualify	VERB
cana-3964	146	14	for	for	ADP
cana-3964	146	15	lesion	lesion	NOUN
cana-3964	146	16	detection	detection	NOUN
cana-3964	146	17	algorithms	algorithm	NOUN
cana-3964	146	18	but	but	CCONJ
cana-3964	146	19	have	have	VERB
cana-3964	146	20	the	the	DET
cana-3964	146	21	problem	problem	NOUN
cana-3964	146	22	of	of	ADP
cana-3964	146	23	limited	limited	ADJ
cana-3964	146	24	depth	depth	NOUN
cana-3964	146	25	penetration	penetration	NOUN
cana-3964	146	26	and	and	CCONJ
cana-3964	146	27	being	be	AUX
cana-3964	146	28	dependent	dependent	ADJ
cana-3964	146	29	on	on	ADP
cana-3964	146	30	the	the	DET
cana-3964	146	31	operator	operator	NOUN
cana-3964	146	32	.	.	PUNCT
cana-3964	147	1	finally	finally	ADV
cana-3964	147	2	,	,	PUNCT
cana-3964	147	3	for	for	ADP
cana-3964	147	4	diagnostics	diagnostic	NOUN
cana-3964	147	5	and	and	CCONJ
cana-3964	147	6	potential	potential	ADJ
cana-3964	147	7	biomarkers	biomarker	NOUN
cana-3964	147	8	based	base	VERB
cana-3964	147	9	on	on	ADP
cana-3964	147	10	thermography	thermography	NOUN
cana-3964	147	11	,	,	PUNCT
cana-3964	147	12	non	non	ADJ
cana-3964	147	13	-	-	ADJ
cana-3964	147	14	invasive	invasive	ADJ
cana-3964	147	15	thermographic	thermographic	ADJ
cana-3964	147	16	image	image	NOUN
cana-3964	147	17	databases	database	NOUN
cana-3964	147	18	contain	contain	VERB
cana-3964	147	19	temperature	temperature	NOUN
cana-3964	147	20	patterns	pattern	NOUN
cana-3964	147	21	and	and	CCONJ
cana-3964	147	22	are	be	AUX
cana-3964	147	23	poorly	poorly	ADV
cana-3964	147	24	influenced	influence	VERB
cana-3964	147	25	by	by	ADP
cana-3964	147	26	changes	change	NOUN
cana-3964	147	27	in	in	ADP
cana-3964	147	28	external	external	ADJ
cana-3964	147	29	temperature	temperature	NOUN
cana-3964	147	30	;	;	PUNCT
cana-3964	147	31	however	however	ADV
cana-3964	147	32	,	,	PUNCT
cana-3964	147	33	the	the	DET
cana-3964	147	34	resolution	resolution	NOUN
cana-3964	147	35	of	of	ADP
cana-3964	147	36	thermographic	thermographic	ADJ
cana-3964	147	37	images	image	NOUN
cana-3964	147	38	is	be	AUX
cana-3964	147	39	significantly	significantly	ADV
cana-3964	147	40	lower	low	ADJ
cana-3964	147	41	compared	compare	VERB
cana-3964	147	42	to	to	ADP
cana-3964	147	43	other	other	ADJ
cana-3964	147	44	types	type	NOUN
cana-3964	147	45	of	of	ADP
cana-3964	147	46	images	image	NOUN
cana-3964	147	47	.	.	PUNCT
cana-3964	148	1	communications	communication	NOUN
cana-3964	148	2	on	on	ADP
cana-3964	148	3	applied	apply	VERB
cana-3964	148	4	nonlinear	nonlinear	ADJ
cana-3964	148	5	analysis	analysis	NOUN
cana-3964	148	6	issn	issn	NOUN
cana-3964	148	7	:	:	PUNCT
cana-3964	148	8	1074	1074	NUM
cana-3964	148	9	-	-	PUNCT
cana-3964	148	10	133x	133x	NUM
cana-3964	148	11	vol	vol	NOUN
cana-3964	148	12	32	32	NUM
cana-3964	148	13	no	no	NOUN
cana-3964	148	14	.	.	PUNCT
cana-3964	149	1	9s	9s	NUM
cana-3964	149	2	(	(	PUNCT
cana-3964	149	3	2025	2025	NUM
cana-3964	149	4	)	)	PUNCT
cana-3964	149	5	561	561	NUM
cana-3964	149	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	149	7	table	table	NOUN
cana-3964	149	8	2	2	NUM
cana-3964	149	9	strengths	strength	NOUN
cana-3964	149	10	and	and	CCONJ
cana-3964	149	11	limitations	limitation	NOUN
cana-3964	149	12	of	of	ADP
cana-3964	149	13	each	each	DET
cana-3964	149	14	dataset	dataset	VERB
cana-3964	149	15	dataset	dataset	NOUN
cana-3964	149	16	name	name	NOUN
cana-3964	149	17	strengths	strength	NOUN
cana-3964	149	18	limitations	limitation	NOUN
cana-3964	149	19	wisconsin	wisconsin	VERB
cana-3964	149	20	diagnostic	diagnostic	ADJ
cana-3964	149	21	breast	breast	NOUN
cana-3964	149	22	cancer	cancer	NOUN
cana-3964	149	23	(	(	PUNCT
cana-3964	149	24	wdbc	wdbc	PROPN
cana-3964	149	25	)	)	PUNCT
cana-3964	149	26	well	well	ADV
cana-3964	149	27	-	-	PUNCT
cana-3964	149	28	established	establish	VERB
cana-3964	149	29	dataset	dataset	NOUN
cana-3964	149	30	widely	widely	ADV
cana-3964	149	31	used	use	VERB
cana-3964	149	32	in	in	ADP
cana-3964	149	33	breast	breast	NOUN
cana-3964	149	34	cancer	cancer	NOUN
cana-3964	149	35	research	research	NOUN
cana-3964	149	36	.	.	PUNCT
cana-3964	150	1	comprehensive	comprehensive	ADJ
cana-3964	150	2	features	feature	NOUN
cana-3964	150	3	from	from	ADP
cana-3964	150	4	digitized	digitize	VERB
cana-3964	150	5	images	image	NOUN
cana-3964	150	6	.	.	PUNCT
cana-3964	151	1	labels	label	NOUN
cana-3964	151	2	for	for	ADP
cana-3964	151	3	supervised	supervised	ADJ
cana-3964	151	4	learning	learning	NOUN
cana-3964	151	5	(	(	PUNCT
cana-3964	151	6	benign	benign	ADJ
cana-3964	151	7	and	and	CCONJ
cana-3964	151	8	malignant	malignant	ADJ
cana-3964	151	9	)	)	PUNCT
cana-3964	151	10	.	.	PUNCT
cana-3964	152	1	limited	limit	VERB
cana-3964	152	2	to	to	ADP
cana-3964	152	3	features	feature	NOUN
cana-3964	152	4	derived	derive	VERB
cana-3964	152	5	from	from	ADP
cana-3964	152	6	fna	fna	NOUN
cana-3964	152	7	images	image	NOUN
cana-3964	152	8	,	,	PUNCT
cana-3964	152	9	may	may	AUX
cana-3964	152	10	not	not	PART
cana-3964	152	11	capture	capture	AUX
cana-3964	152	12	all	all	DET
cana-3964	152	13	aspects	aspect	NOUN
cana-3964	152	14	of	of	ADP
cana-3964	152	15	breast	breast	NOUN
cana-3964	152	16	cancer	cancer	NOUN
cana-3964	152	17	.	.	PUNCT
cana-3964	153	1	breast	breast	NOUN
cana-3964	153	2	cancer	cancer	NOUN
cana-3964	153	3	histopathological	histopathological	ADJ
cana-3964	153	4	database	database	NOUN
cana-3964	153	5	(	(	PUNCT
cana-3964	153	6	breakhis	breakhis	ADJ
cana-3964	153	7	)	)	PUNCT
cana-3964	153	8	high	high	ADJ
cana-3964	153	9	-	-	PUNCT
cana-3964	153	10	resolution	resolution	NOUN
cana-3964	153	11	histopathological	histopathological	ADJ
cana-3964	153	12	images	image	NOUN
cana-3964	153	13	for	for	ADP
cana-3964	153	14	detailed	detailed	ADJ
cana-3964	153	15	cellular	cellular	ADJ
cana-3964	153	16	information	information	NOUN
cana-3964	153	17	.	.	PUNCT
cana-3964	154	1	enables	enable	VERB
cana-3964	154	2	image	image	NOUN
cana-3964	154	3	-	-	PUNCT
cana-3964	154	4	based	base	VERB
cana-3964	154	5	classification	classification	NOUN
cana-3964	154	6	and	and	CCONJ
cana-3964	154	7	segmentation	segmentation	NOUN
cana-3964	154	8	models	model	NOUN
cana-3964	154	9	.	.	PUNCT
cana-3964	155	1	diverse	diverse	ADJ
cana-3964	155	2	types	type	NOUN
cana-3964	155	3	of	of	ADP
cana-3964	155	4	breast	breast	NOUN
cana-3964	155	5	cancer	cancer	NOUN
cana-3964	155	6	samples	sample	NOUN
cana-3964	155	7	.	.	PUNCT
cana-3964	156	1	requires	require	VERB
cana-3964	156	2	advanced	advanced	ADJ
cana-3964	156	3	image	image	NOUN
cana-3964	156	4	processing	processing	NOUN
cana-3964	156	5	techniques	technique	NOUN
cana-3964	156	6	,	,	PUNCT
cana-3964	156	7	potentially	potentially	ADV
cana-3964	156	8	computationally	computationally	ADV
cana-3964	156	9	intensive	intensive	ADJ
cana-3964	156	10	.	.	PUNCT
cana-3964	157	1	limited	limit	VERB
cana-3964	157	2	to	to	ADP
cana-3964	157	3	histopathological	histopathological	ADJ
cana-3964	157	4	information	information	NOUN
cana-3964	157	5	.	.	PUNCT
cana-3964	158	1	mammography	mammography	NOUN
cana-3964	158	2	databases	database	VERB
cana-3964	158	3	mammographic	mammographic	ADJ
cana-3964	158	4	images	image	NOUN
cana-3964	158	5	provide	provide	VERB
cana-3964	158	6	insights	insight	NOUN
cana-3964	158	7	into	into	ADP
cana-3964	158	8	breast	breast	NOUN
cana-3964	158	9	tissue	tissue	NOUN
cana-3964	158	10	density	density	NOUN
cana-3964	158	11	and	and	CCONJ
cana-3964	158	12	anomalies	anomaly	NOUN
cana-3964	158	13	.	.	PUNCT
cana-3964	159	1	grayscale	grayscale	NOUN
cana-3964	159	2	images	image	NOUN
cana-3964	159	3	for	for	ADP
cana-3964	159	4	mammogram	mammogram	NOUN
cana-3964	159	5	interpretation	interpretation	NOUN
cana-3964	159	6	.	.	PUNCT
cana-3964	160	1	multi	multi	ADJ
cana-3964	160	2	-	-	ADJ
cana-3964	160	3	category	category	ADJ
cana-3964	160	4	labels	label	NOUN
cana-3964	160	5	(	(	PUNCT
cana-3964	160	6	normal	normal	ADJ
cana-3964	160	7	,	,	PUNCT
cana-3964	160	8	benign	benign	ADJ
cana-3964	160	9	,	,	PUNCT
cana-3964	160	10	malignant	malignant	ADJ
cana-3964	160	11	)	)	PUNCT
cana-3964	160	12	.	.	PUNCT
cana-3964	161	1	radiation	radiation	NOUN
cana-3964	161	2	exposure	exposure	NOUN
cana-3964	161	3	concerns	concern	NOUN
cana-3964	161	4	with	with	ADP
cana-3964	161	5	mammography	mammography	NOUN
cana-3964	161	6	.	.	PUNCT
cana-3964	162	1	interpretation	interpretation	NOUN
cana-3964	162	2	subjective	subjective	ADJ
cana-3964	162	3	and	and	CCONJ
cana-3964	162	4	dependent	dependent	ADJ
cana-3964	162	5	on	on	ADP
cana-3964	162	6	radiologists	radiologist	NOUN
cana-3964	162	7	'	'	PART
cana-3964	162	8	expertise	expertise	NOUN
cana-3964	162	9	.	.	PUNCT
cana-3964	163	1	ultrasound	ultrasound	NOUN
cana-3964	163	2	image	image	NOUN
cana-3964	163	3	databases	database	VERB
cana-3964	163	4	non	non	ADJ
cana-3964	163	5	-	-	ADJ
cana-3964	163	6	invasive	invasive	ADJ
cana-3964	163	7	ultrasound	ultrasound	NOUN
cana-3964	163	8	provides	provide	VERB
cana-3964	163	9	real	real	ADJ
cana-3964	163	10	-	-	PUNCT
cana-3964	163	11	time	time	NOUN
cana-3964	163	12	information	information	NOUN
cana-3964	163	13	.	.	PUNCT
cana-3964	164	1	suitable	suitable	ADJ
cana-3964	164	2	for	for	ADP
cana-3964	164	3	developing	develop	VERB
cana-3964	164	4	algorithms	algorithm	NOUN
cana-3964	164	5	for	for	ADP
cana-3964	164	6	breast	breast	NOUN
cana-3964	164	7	lesion	lesion	NOUN
cana-3964	164	8	detection	detection	NOUN
cana-3964	164	9	.	.	PUNCT
cana-3964	165	1	captures	capture	VERB
cana-3964	165	2	tissue	tissue	NOUN
cana-3964	165	3	density	density	NOUN
cana-3964	165	4	,	,	PUNCT
cana-3964	165	5	texture	texture	NOUN
cana-3964	165	6	,	,	PUNCT
cana-3964	165	7	and	and	CCONJ
cana-3964	165	8	lesion	lesion	NOUN
cana-3964	165	9	characteristics	characteristic	NOUN
cana-3964	165	10	.	.	PUNCT
cana-3964	166	1	operator	operator	NOUN
cana-3964	166	2	dependence	dependence	NOUN
cana-3964	166	3	in	in	ADP
cana-3964	166	4	capturing	capture	VERB
cana-3964	166	5	images	image	NOUN
cana-3964	166	6	.	.	PUNCT
cana-3964	166	7	limited	limited	ADJ
cana-3964	166	8	depth	depth	NOUN
cana-3964	166	9	penetration	penetration	NOUN
cana-3964	166	10	compared	compare	VERB
cana-3964	166	11	to	to	ADP
cana-3964	166	12	other	other	ADJ
cana-3964	166	13	imaging	imaging	NOUN
cana-3964	166	14	modalities	modality	NOUN
cana-3964	166	15	.	.	PUNCT
cana-3964	167	1	thermographic	thermographic	ADJ
cana-3964	167	2	image	image	NOUN
cana-3964	167	3	databases	database	VERB
cana-3964	167	4	non	non	ADJ
cana-3964	167	5	-	-	ADJ
cana-3964	167	6	invasive	invasive	ADJ
cana-3964	167	7	imaging	imaging	NOUN
cana-3964	167	8	captures	capture	VERB
cana-3964	167	9	temperature	temperature	NOUN
cana-3964	167	10	patterns	pattern	NOUN
cana-3964	167	11	in	in	ADP
cana-3964	167	12	breast	breast	NOUN
cana-3964	167	13	tissue	tissue	NOUN
cana-3964	167	14	.	.	PUNCT
cana-3964	168	1	potential	potential	NOUN
cana-3964	168	2	for	for	ADP
cana-3964	168	3	early	early	ADJ
cana-3964	168	4	detection	detection	NOUN
cana-3964	168	5	based	base	VERB
cana-3964	168	6	on	on	ADP
cana-3964	168	7	abnormal	abnormal	ADJ
cana-3964	168	8	temperature	temperature	NOUN
cana-3964	168	9	variations	variation	NOUN
cana-3964	168	10	.	.	PUNCT
cana-3964	169	1	complementary	complementary	ADJ
cana-3964	169	2	information	information	NOUN
cana-3964	169	3	to	to	ADP
cana-3964	169	4	other	other	ADJ
cana-3964	169	5	modalities	modality	NOUN
cana-3964	169	6	.	.	PUNCT
cana-3964	170	1	sensitivity	sensitivity	NOUN
cana-3964	170	2	to	to	ADP
cana-3964	170	3	external	external	ADJ
cana-3964	170	4	factors	factor	NOUN
cana-3964	170	5	affecting	affect	VERB
cana-3964	170	6	body	body	NOUN
cana-3964	170	7	temperature	temperature	NOUN
cana-3964	170	8	.	.	PUNCT
cana-3964	171	1	limited	limited	ADJ
cana-3964	171	2	resolution	resolution	NOUN
cana-3964	171	3	compared	compare	VERB
cana-3964	171	4	to	to	ADP
cana-3964	171	5	other	other	ADJ
cana-3964	171	6	imaging	imaging	NOUN
cana-3964	171	7	techniques	technique	NOUN
cana-3964	171	8	.	.	PUNCT
cana-3964	172	1	communications	communication	NOUN
cana-3964	172	2	on	on	ADP
cana-3964	172	3	applied	apply	VERB
cana-3964	172	4	nonlinear	nonlinear	ADJ
cana-3964	172	5	analysis	analysis	NOUN
cana-3964	172	6	issn	issn	NOUN
cana-3964	172	7	:	:	PUNCT
cana-3964	172	8	1074	1074	NUM
cana-3964	172	9	-	-	PUNCT
cana-3964	172	10	133x	133x	NUM
cana-3964	172	11	vol	vol	NOUN
cana-3964	172	12	32	32	NUM
cana-3964	172	13	no	no	NOUN
cana-3964	172	14	.	.	PUNCT
cana-3964	173	1	9s	9s	NUM
cana-3964	173	2	(	(	PUNCT
cana-3964	173	3	2025	2025	NUM
cana-3964	173	4	)	)	PUNCT
cana-3964	173	5	562	562	NUM
cana-3964	173	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	173	7	3.1	3.1	NUM
cana-3964	173	8	wisconsin	wisconsin	NOUN
cana-3964	173	9	diagnostic	diagnostic	PROPN
cana-3964	173	10	breast	breast	NOUN
cana-3964	173	11	cancer	cancer	NOUN
cana-3964	173	12	dataset	dataset	VERB
cana-3964	173	13	the	the	DET
cana-3964	173	14	wisconsin	wisconsin	PROPN
cana-3964	173	15	diagnostic	diagnostic	PROPN
cana-3964	173	16	breast	breast	NOUN
cana-3964	173	17	cancer	cancer	NOUN
cana-3964	173	18	(	(	PUNCT
cana-3964	173	19	wdbc	wdbc	PROPN
cana-3964	173	20	)	)	PUNCT
cana-3964	173	21	dataset	dataset	NOUN
cana-3964	173	22	was	be	AUX
cana-3964	173	23	obtained	obtain	VERB
cana-3964	173	24	from	from	ADP
cana-3964	173	25	the	the	DET
cana-3964	173	26	“	"	PUNCT
cana-3964	173	27	ml	ml	PROPN
cana-3964	173	28	uci	uci	PROPN
cana-3964	173	29	repository	repository	NOUN
cana-3964	173	30	,	,	PUNCT
cana-3964	173	31	"	"	PUNCT
cana-3964	173	32	an	an	DET
cana-3964	173	33	online	online	ADJ
cana-3964	173	34	source	source	NOUN
cana-3964	173	35	repository	repository	NOUN
cana-3964	173	36	.	.	PUNCT
cana-3964	174	1	dr	dr	PROPN
cana-3964	174	2	.	.	PROPN
cana-3964	174	3	wolberg	wolberg	PROPN
cana-3964	174	4	and	and	CCONJ
cana-3964	174	5	the	the	DET
cana-3964	174	6	hospitals	hospital	NOUN
cana-3964	174	7	of	of	ADP
cana-3964	174	8	wisconsin	wisconsin	PROPN
cana-3964	174	9	and	and	CCONJ
cana-3964	174	10	the	the	DET
cana-3964	174	11	university	university	NOUN
cana-3964	174	12	collected	collect	VERB
cana-3964	174	13	the	the	DET
cana-3964	174	14	dataset	dataset	NOUN
cana-3964	174	15	irregularly	irregularly	ADV
cana-3964	174	16	in	in	ADP
cana-3964	174	17	the	the	DET
cana-3964	174	18	past	past	NOUN
cana-3964	174	19	.	.	PUNCT
cana-3964	175	1	it	it	PRON
cana-3964	175	2	consists	consist	VERB
cana-3964	175	3	of	of	ADP
cana-3964	175	4	569	569	NUM
cana-3964	175	5	cases	case	NOUN
cana-3964	175	6	,	,	PUNCT
cana-3964	175	7	with	with	ADP
cana-3964	175	8	no	no	DET
cana-3964	175	9	specific	specific	ADJ
cana-3964	175	10	categorization	categorization	NOUN
cana-3964	175	11	as	as	ADP
cana-3964	175	12	either	either	CCONJ
cana-3964	175	13	dangerous	dangerous	ADJ
cana-3964	175	14	or	or	CCONJ
cana-3964	175	15	generous	generous	ADJ
cana-3964	175	16	.	.	PUNCT
cana-3964	176	1	the	the	DET
cana-3964	176	2	dataset	dataset	NOUN
cana-3964	176	3	under	under	ADP
cana-3964	176	4	consideration	consideration	NOUN
cana-3964	176	5	is	be	AUX
cana-3964	176	6	the	the	DET
cana-3964	176	7	wisconsin	wisconsin	PROPN
cana-3964	176	8	diagnostic	diagnostic	PROPN
cana-3964	176	9	breast	breast	NOUN
cana-3964	176	10	cancer	cancer	NOUN
cana-3964	176	11	(	(	PUNCT
cana-3964	176	12	wdbc	wdbc	PROPN
cana-3964	176	13	)	)	PUNCT
cana-3964	176	14	dataset	dataset	NOUN
cana-3964	176	15	,	,	PUNCT
cana-3964	176	16	which	which	PRON
cana-3964	176	17	is	be	AUX
cana-3964	176	18	widely	widely	ADV
cana-3964	176	19	used	use	VERB
cana-3964	176	20	in	in	ADP
cana-3964	176	21	the	the	DET
cana-3964	176	22	domain	domain	NOUN
cana-3964	176	23	of	of	ADP
cana-3964	176	24	medical	medical	ADJ
cana-3964	176	25	research	research	NOUN
cana-3964	176	26	for	for	ADP
cana-3964	176	27	developing	develop	VERB
cana-3964	176	28	predictive	predictive	ADJ
cana-3964	176	29	models	model	NOUN
cana-3964	176	30	.	.	PUNCT
cana-3964	177	1	this	this	DET
cana-3964	177	2	dataset	dataset	NOUN
cana-3964	177	3	consists	consist	VERB
cana-3964	177	4	of	of	ADP
cana-3964	177	5	32	32	NUM
cana-3964	177	6	attributes	attribute	NOUN
cana-3964	177	7	that	that	PRON
cana-3964	177	8	represent	represent	VERB
cana-3964	177	9	various	various	ADJ
cana-3964	177	10	clinical	clinical	ADJ
cana-3964	177	11	and	and	CCONJ
cana-3964	177	12	morphological	morphological	ADJ
cana-3964	177	13	features	feature	NOUN
cana-3964	177	14	extracted	extract	VERB
cana-3964	177	15	from	from	ADP
cana-3964	177	16	breast	breast	NOUN
cana-3964	177	17	cancer	cancer	NOUN
cana-3964	177	18	biopsies	biopsy	NOUN
cana-3964	177	19	.	.	PUNCT
cana-3964	178	1	these	these	DET
cana-3964	178	2	attributes	attribute	NOUN
cana-3964	178	3	are	be	AUX
cana-3964	178	4	essential	essential	ADJ
cana-3964	178	5	for	for	ADP
cana-3964	178	6	distinguishing	distinguish	VERB
cana-3964	178	7	between	between	ADP
cana-3964	178	8	two	two	NUM
cana-3964	178	9	classes	class	NOUN
cana-3964	178	10	of	of	ADP
cana-3964	178	11	cancer	cancer	NOUN
cana-3964	178	12	diagnoses	diagnosis	NOUN
cana-3964	178	13	:	:	PUNCT
cana-3964	178	14	benign	benign	ADJ
cana-3964	178	15	and	and	CCONJ
cana-3964	178	16	malignant	malignant	ADJ
cana-3964	178	17	.	.	PUNCT
cana-3964	179	1	the	the	DET
cana-3964	179	2	dataset	dataset	NOUN
cana-3964	179	3	includes	include	VERB
cana-3964	179	4	569	569	NUM
cana-3964	179	5	cases	case	NOUN
cana-3964	179	6	,	,	PUNCT
cana-3964	179	7	of	of	ADP
cana-3964	179	8	which	which	PRON
cana-3964	179	9	357	357	NUM
cana-3964	179	10	cases	case	NOUN
cana-3964	179	11	are	be	AUX
cana-3964	179	12	classified	classify	VERB
cana-3964	179	13	as	as	ADP
cana-3964	179	14	benign	benign	ADJ
cana-3964	179	15	and	and	CCONJ
cana-3964	179	16	212	212	NUM
cana-3964	179	17	as	as	ADP
cana-3964	179	18	malignant	malignant	ADJ
cana-3964	179	19	.	.	PUNCT
cana-3964	180	1	this	this	DET
cana-3964	180	2	balanced	balanced	ADJ
cana-3964	180	3	distribution	distribution	NOUN
cana-3964	180	4	of	of	ADP
cana-3964	180	5	cases	case	NOUN
cana-3964	180	6	allows	allow	VERB
cana-3964	180	7	for	for	ADP
cana-3964	180	8	an	an	DET
cana-3964	180	9	effective	effective	ADJ
cana-3964	180	10	evaluation	evaluation	NOUN
cana-3964	180	11	of	of	ADP
cana-3964	180	12	machine	machine	NOUN
cana-3964	180	13	learning	learn	VERB
cana-3964	180	14	algorithms	algorithm	NOUN
cana-3964	180	15	aimed	aim	VERB
cana-3964	180	16	at	at	ADP
cana-3964	180	17	breast	breast	NOUN
cana-3964	180	18	cancer	cancer	NOUN
cana-3964	180	19	classification	classification	NOUN
cana-3964	180	20	.	.	PUNCT
cana-3964	181	1	the	the	DET
cana-3964	181	2	detailed	detailed	ADJ
cana-3964	181	3	attribute	attribute	NOUN
cana-3964	181	4	measurements	measurement	NOUN
cana-3964	181	5	provide	provide	VERB
cana-3964	181	6	a	a	DET
cana-3964	181	7	comprehensive	comprehensive	ADJ
cana-3964	181	8	basis	basis	NOUN
cana-3964	181	9	for	for	ADP
cana-3964	181	10	accurately	accurately	ADV
cana-3964	181	11	training	train	VERB
cana-3964	181	12	predictive	predictive	ADJ
cana-3964	181	13	models	model	NOUN
cana-3964	181	14	,	,	PUNCT
cana-3964	181	15	thereby	thereby	ADV
cana-3964	181	16	enabling	enable	VERB
cana-3964	181	17	early	early	ADJ
cana-3964	181	18	and	and	CCONJ
cana-3964	181	19	precise	precise	ADJ
cana-3964	181	20	diagnosis	diagnosis	NOUN
cana-3964	181	21	of	of	ADP
cana-3964	181	22	breast	breast	NOUN
cana-3964	181	23	cancer	cancer	NOUN
cana-3964	181	24	.	.	PUNCT
cana-3964	182	1	table	table	NOUN
cana-3964	182	2	3	3	NUM
cana-3964	182	3	provides	provide	VERB
cana-3964	182	4	a	a	DET
cana-3964	182	5	visual	visual	ADJ
cana-3964	182	6	representation	representation	NOUN
cana-3964	182	7	of	of	ADP
cana-3964	182	8	the	the	DET
cana-3964	182	9	wdbc	wdbc	NOUN
cana-3964	182	10	dataset	dataset	NOUN
cana-3964	182	11	.	.	PUNCT
cana-3964	183	1	table	table	NOUN
cana-3964	183	2	3	3	NUM
cana-3964	183	3	visualization	visualization	NOUN
cana-3964	183	4	of	of	ADP
cana-3964	183	5	wdbc	wdbc	NOUN
cana-3964	183	6	dataset	dataset	VERB
cana-3964	183	7	dataset	dataset	NOUN
cana-3964	183	8	attributes	attribute	NOUN
cana-3964	183	9	cases	case	NOUN
cana-3964	183	10	classes	class	NOUN
cana-3964	183	11	wdbc	wdbc	VERB
cana-3964	183	12	32	32	NUM
cana-3964	183	13	569	569	NUM
cana-3964	183	14	2	2	NUM
cana-3964	183	15	benign	benign	ADJ
cana-3964	183	16	(	(	PUNCT
cana-3964	183	17	357	357	NUM
cana-3964	183	18	)	)	PUNCT
cana-3964	183	19	malignant	malignant	NOUN
cana-3964	183	20	(	(	PUNCT
cana-3964	183	21	212	212	NUM
cana-3964	183	22	)	)	PUNCT
cana-3964	183	23	-description	-description	PROPN
cana-3964	183	24	:	:	PUNCT
cana-3964	183	25	a	a	DET
cana-3964	183	26	breast	breast	NOUN
cana-3964	183	27	mass	mass	NOUN
cana-3964	183	28	fine	fine	ADJ
cana-3964	183	29	needle	needle	NOUN
cana-3964	183	30	aspiration	aspiration	NOUN
cana-3964	183	31	(	(	PUNCT
cana-3964	183	32	fna	fna	NOUN
cana-3964	183	33	)	)	PUNCT
cana-3964	183	34	sample	sample	NOUN
cana-3964	183	35	is	be	AUX
cana-3964	183	36	utilized	utilize	VERB
cana-3964	183	37	to	to	PART
cana-3964	183	38	calculate	calculate	VERB
cana-3964	183	39	features	feature	NOUN
cana-3964	183	40	that	that	PRON
cana-3964	183	41	describe	describe	VERB
cana-3964	183	42	the	the	DET
cana-3964	183	43	features	feature	NOUN
cana-3964	183	44	of	of	ADP
cana-3964	183	45	the	the	DET
cana-3964	183	46	cell	cell	NOUN
cana-3964	183	47	nuclei	nucleus	NOUN
cana-3964	183	48	seen	see	VERB
cana-3964	183	49	in	in	ADP
cana-3964	183	50	the	the	DET
cana-3964	183	51	images	image	NOUN
cana-3964	183	52	.	.	PUNCT
cana-3964	184	1	-labels	-label	NOUN
cana-3964	184	2	:	:	PUNCT
cana-3964	184	3	each	each	DET
cana-3964	184	4	sample	sample	NOUN
cana-3964	184	5	is	be	AUX
cana-3964	184	6	labelled	label	VERB
cana-3964	184	7	as	as	ADP
cana-3964	184	8	either	either	CCONJ
cana-3964	184	9	benign	benign	ADJ
cana-3964	184	10	(	(	PUNCT
cana-3964	184	11	b	b	NOUN
cana-3964	184	12	)	)	PUNCT
cana-3964	184	13	or	or	CCONJ
cana-3964	184	14	malignant	malignant	ADJ
cana-3964	184	15	(	(	PUNCT
cana-3964	184	16	m	m	NOUN
cana-3964	184	17	)	)	PUNCT
cana-3964	184	18	.	.	PUNCT
cana-3964	185	1	-source	-source	NOUN
cana-3964	185	2	:	:	PUNCT
cana-3964	185	3	“	"	PUNCT
cana-3964	185	4	uci	uci	NOUN
cana-3964	185	5	machine	machine	NOUN
cana-3964	185	6	learning	learn	VERB
cana-3964	185	7	repository	repository	NOUN
cana-3964	185	8	”	"	PUNCT
cana-3964	185	9	.	.	PUNCT
cana-3964	186	1	-application	-application	NOUN
cana-3964	186	2	:	:	PUNCT
cana-3964	186	3	used	use	VERB
cana-3964	186	4	to	to	PART
cana-3964	186	5	develop	develop	VERB
cana-3964	186	6	predictive	predictive	ADJ
cana-3964	186	7	models	model	NOUN
cana-3964	186	8	for	for	ADP
cana-3964	186	9	classifying	classify	VERB
cana-3964	186	10	breast	breast	NOUN
cana-3964	186	11	masses	masse	NOUN
cana-3964	186	12	as	as	ADP
cana-3964	186	13	benign	benign	ADJ
cana-3964	186	14	or	or	CCONJ
cana-3964	186	15	malignant	malignant	ADJ
cana-3964	186	16	based	base	VERB
cana-3964	186	17	on	on	ADP
cana-3964	186	18	the	the	DET
cana-3964	186	19	extracted	extract	VERB
cana-3964	186	20	features	feature	NOUN
cana-3964	186	21	.	.	PUNCT
cana-3964	187	1	the	the	DET
cana-3964	187	2	dataset	dataset	NOUN
cana-3964	187	3	is	be	AUX
cana-3964	187	4	widely	widely	ADV
cana-3964	187	5	used	use	VERB
cana-3964	187	6	for	for	ADP
cana-3964	187	7	classification	classification	NOUN
cana-3964	187	8	tasks	task	NOUN
cana-3964	187	9	,	,	PUNCT
cana-3964	187	10	particularly	particularly	ADV
cana-3964	187	11	for	for	ADP
cana-3964	187	12	binary	binary	ADJ
cana-3964	187	13	classification	classification	NOUN
cana-3964	187	14	algorithms	algorithm	NOUN
cana-3964	187	15	like	like	ADP
cana-3964	187	16	knn	knn	PROPN
cana-3964	187	17	,	,	PUNCT
cana-3964	187	18	svm	svm	ADJ
cana-3964	187	19	,	,	PUNCT
cana-3964	187	20	decision	decision	NOUN
cana-3964	187	21	trees	tree	NOUN
cana-3964	187	22	,	,	PUNCT
cana-3964	187	23	and	and	CCONJ
cana-3964	187	24	more	more	ADJ
cana-3964	187	25	.	.	PUNCT
cana-3964	188	1	the	the	DET
cana-3964	188	2	dataset	dataset	NOUN
cana-3964	188	3	can	can	AUX
cana-3964	188	4	be	be	AUX
cana-3964	188	5	accessed	access	VERB
cana-3964	188	6	from	from	ADP
cana-3964	188	7	various	various	ADJ
cana-3964	188	8	machine	machine	NOUN
cana-3964	188	9	learning	learning	NOUN
cana-3964	188	10	libraries	library	NOUN
cana-3964	188	11	or	or	CCONJ
cana-3964	188	12	repositories	repository	NOUN
cana-3964	188	13	online	online	ADV
cana-3964	189	1	[	[	X
cana-3964	189	2	33	33	NUM
cana-3964	189	3	]	]	PUNCT
cana-3964	189	4	.	.	PUNCT
cana-3964	190	1	it	it	PRON
cana-3964	190	2	is	be	AUX
cana-3964	190	3	a	a	DET
cana-3964	190	4	popular	popular	ADJ
cana-3964	190	5	choice	choice	NOUN
cana-3964	190	6	for	for	ADP
cana-3964	190	7	learning	learn	VERB
cana-3964	190	8	and	and	CCONJ
cana-3964	190	9	practicing	practice	VERB
cana-3964	190	10	ml	ml	NOUN
cana-3964	190	11	techniques	technique	NOUN
cana-3964	190	12	,	,	PUNCT
cana-3964	190	13	especially	especially	ADV
cana-3964	190	14	in	in	ADP
cana-3964	190	15	the	the	DET
cana-3964	190	16	medical	medical	ADJ
cana-3964	190	17	domain	domain	NOUN
cana-3964	190	18	.	.	PUNCT
cana-3964	191	1	the	the	DET
cana-3964	191	2	description	description	NOUN
cana-3964	191	3	of	of	ADP
cana-3964	191	4	various	various	ADJ
cana-3964	191	5	datasets	dataset	NOUN
cana-3964	191	6	used	use	VERB
cana-3964	191	7	in	in	ADP
cana-3964	191	8	breast	breast	NOUN
cana-3964	191	9	cancer	cancer	NOUN
cana-3964	191	10	diagnosis	diagnosis	NOUN
cana-3964	191	11	is	be	AUX
cana-3964	191	12	shown	show	VERB
cana-3964	191	13	in	in	ADP
cana-3964	191	14	fig	fig	NOUN
cana-3964	191	15	4	4	NUM
cana-3964	191	16	.	.	PUNCT
cana-3964	192	1	these	these	DET
cana-3964	192	2	datasets	dataset	NOUN
cana-3964	192	3	include	include	VERB
cana-3964	192	4	medical	medical	ADJ
cana-3964	192	5	imaging	imaging	NOUN
cana-3964	192	6	,	,	PUNCT
cana-3964	192	7	wdbc	wdbc	NOUN
cana-3964	192	8	,	,	PUNCT
cana-3964	192	9	clinical	clinical	ADJ
cana-3964	192	10	records	record	NOUN
cana-3964	192	11	,	,	PUNCT
cana-3964	192	12	and	and	CCONJ
cana-3964	192	13	histopathological	histopathological	ADJ
cana-3964	192	14	data	datum	NOUN
cana-3964	192	15	.	.	PUNCT
cana-3964	193	1	each	each	DET
cana-3964	193	2	dataset	dataset	NOUN
cana-3964	193	3	serves	serve	VERB
cana-3964	193	4	a	a	DET
cana-3964	193	5	unique	unique	ADJ
cana-3964	193	6	purpose	purpose	NOUN
cana-3964	193	7	in	in	ADP
cana-3964	193	8	breast	breast	NOUN
cana-3964	193	9	cancer	cancer	NOUN
cana-3964	193	10	detection	detection	NOUN
cana-3964	193	11	and	and	CCONJ
cana-3964	193	12	enabling	enable	VERB
cana-3964	193	13	researchers	researcher	NOUN
cana-3964	193	14	to	to	PART
cana-3964	193	15	develop	develop	VERB
cana-3964	193	16	more	more	ADV
cana-3964	193	17	accurate	accurate	ADJ
cana-3964	193	18	and	and	CCONJ
cana-3964	193	19	personalized	personalized	ADJ
cana-3964	193	20	diagnostic	diagnostic	ADJ
cana-3964	193	21	approaches	approach	NOUN
cana-3964	193	22	.	.	PUNCT
cana-3964	194	1	these	these	DET
cana-3964	194	2	data	datum	NOUN
cana-3964	194	3	sources	source	NOUN
cana-3964	194	4	are	be	AUX
cana-3964	194	5	contributing	contribute	VERB
cana-3964	194	6	to	to	ADP
cana-3964	194	7	the	the	DET
cana-3964	194	8	ongoing	ongoing	ADJ
cana-3964	194	9	research	research	NOUN
cana-3964	194	10	progress	progress	NOUN
cana-3964	194	11	toward	toward	ADP
cana-3964	194	12	improving	improve	VERB
cana-3964	194	13	breast	breast	NOUN
cana-3964	194	14	cancer	cancer	NOUN
cana-3964	194	15	diagnosis	diagnosis	NOUN
cana-3964	194	16	and	and	CCONJ
cana-3964	194	17	reducing	reduce	VERB
cana-3964	194	18	patient	patient	ADJ
cana-3964	194	19	mortality	mortality	NOUN
cana-3964	194	20	.	.	PUNCT
cana-3964	195	1	communications	communication	NOUN
cana-3964	195	2	on	on	ADP
cana-3964	195	3	applied	apply	VERB
cana-3964	195	4	nonlinear	nonlinear	ADJ
cana-3964	195	5	analysis	analysis	NOUN
cana-3964	195	6	issn	issn	NOUN
cana-3964	195	7	:	:	PUNCT
cana-3964	195	8	1074	1074	NUM
cana-3964	195	9	-	-	PUNCT
cana-3964	195	10	133x	133x	NUM
cana-3964	195	11	vol	vol	NOUN
cana-3964	195	12	32	32	NUM
cana-3964	195	13	no	no	NOUN
cana-3964	195	14	.	.	PUNCT
cana-3964	196	1	9s	9s	NUM
cana-3964	196	2	(	(	PUNCT
cana-3964	196	3	2025	2025	NUM
cana-3964	196	4	)	)	PUNCT
cana-3964	197	1	563	563	NUM
cana-3964	197	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	197	3	fig	fig	NOUN
cana-3964	197	4	.	.	PUNCT
cana-3964	197	5	4	4	NUM
cana-3964	197	6	diverse	diverse	ADJ
cana-3964	197	7	datasets	dataset	NOUN
cana-3964	197	8	with	with	ADP
cana-3964	197	9	description	description	NOUN
cana-3964	197	10	for	for	ADP
cana-3964	197	11	breast	breast	NOUN
cana-3964	197	12	cancer	cancer	NOUN
cana-3964	197	13	diagnosis	diagnosis	NOUN
cana-3964	197	14	the	the	DET
cana-3964	197	15	datasets	dataset	NOUN
cana-3964	197	16	for	for	ADP
cana-3964	197	17	breast	breast	NOUN
cana-3964	197	18	cancer	cancer	NOUN
cana-3964	197	19	research	research	NOUN
cana-3964	197	20	can	can	AUX
cana-3964	197	21	be	be	AUX
cana-3964	197	22	collected	collect	VERB
cana-3964	197	23	from	from	ADP
cana-3964	197	24	various	various	ADJ
cana-3964	197	25	sources	source	NOUN
cana-3964	197	26	.	.	PUNCT
cana-3964	198	1	the	the	DET
cana-3964	198	2	wdbc	wdbc	NOUN
cana-3964	198	3	has	have	VERB
cana-3964	198	4	a	a	DET
cana-3964	198	5	moderate	moderate	ADJ
cana-3964	198	6	-	-	PUNCT
cana-3964	198	7	size	size	NOUN
cana-3964	198	8	with	with	ADP
cana-3964	198	9	30	30	NUM
cana-3964	198	10	numerical	numerical	ADJ
cana-3964	198	11	attributes	attribute	NOUN
cana-3964	198	12	,	,	PUNCT
cana-3964	198	13	which	which	PRON
cana-3964	198	14	is	be	AUX
cana-3964	198	15	ideal	ideal	ADJ
cana-3964	198	16	for	for	ADP
cana-3964	198	17	diagnostic	diagnostic	ADJ
cana-3964	198	18	purposes	purpose	NOUN
cana-3964	198	19	.	.	PUNCT
cana-3964	199	1	the	the	DET
cana-3964	199	2	mammograms	mammogram	NOUN
cana-3964	199	3	dataset	dataset	NOUN
cana-3964	199	4	presents	present	VERB
cana-3964	199	5	a	a	DET
cana-3964	199	6	large	large	ADJ
cana-3964	199	7	-	-	PUNCT
cana-3964	199	8	scale	scale	NOUN
cana-3964	199	9	image	image	NOUN
cana-3964	199	10	-	-	PUNCT
cana-3964	199	11	based	base	VERB
cana-3964	199	12	dataset	dataset	NOUN
cana-3964	199	13	and	and	CCONJ
cana-3964	199	14	the	the	DET
cana-3964	199	15	breast	breast	NOUN
cana-3964	199	16	cancer	cancer	NOUN
cana-3964	199	17	histopathological	histopathological	ADJ
cana-3964	199	18	database	database	NOUN
cana-3964	199	19	(	(	PUNCT
cana-3964	199	20	breakhis	breakhis	ADJ
cana-3964	199	21	)	)	PUNCT
cana-3964	199	22	is	be	AUX
cana-3964	199	23	a	a	DET
cana-3964	199	24	breast	breast	NOUN
cana-3964	199	25	cancer	cancer	NOUN
cana-3964	199	26	histopathological	histopathological	ADJ
cana-3964	199	27	database	database	NOUN
cana-3964	199	28	,	,	PUNCT
cana-3964	199	29	which	which	PRON
cana-3964	199	30	is	be	AUX
cana-3964	199	31	made	make	VERB
cana-3964	199	32	of	of	ADP
cana-3964	199	33	7,909	7,909	NUM
cana-3964	199	34	microscopic	microscopic	ADJ
cana-3964	199	35	images	image	NOUN
cana-3964	199	36	of	of	ADP
cana-3964	199	37	tissue	tissue	NOUN
cana-3964	199	38	samples	sample	NOUN
cana-3964	199	39	of	of	ADP
cana-3964	199	40	breast	breast	NOUN
cana-3964	199	41	cancer	cancer	NOUN
cana-3964	199	42	,	,	PUNCT
cana-3964	199	43	which	which	PRON
cana-3964	199	44	are	be	AUX
cana-3964	199	45	split	split	VERB
cana-3964	199	46	into	into	ADP
cana-3964	199	47	benign	benign	ADJ
cana-3964	199	48	and	and	CCONJ
cana-3964	199	49	malignant	malignant	ADJ
cana-3964	199	50	classes	class	NOUN
cana-3964	199	51	[	[	X
cana-3964	199	52	34	34	NUM
cana-3964	199	53	]	]	PUNCT
cana-3964	199	54	.	.	PUNCT
cana-3964	200	1	the	the	DET
cana-3964	200	2	thermographic	thermographic	ADJ
cana-3964	200	3	images	image	NOUN
cana-3964	200	4	dataset	dataset	VERB
cana-3964	200	5	,	,	PUNCT
cana-3964	200	6	though	though	SCONJ
cana-3964	200	7	small	small	ADJ
cana-3964	200	8	in	in	ADP
cana-3964	200	9	size	size	NOUN
cana-3964	200	10	,	,	PUNCT
cana-3964	200	11	contributes	contribute	VERB
cana-3964	200	12	additional	additional	ADJ
cana-3964	200	13	imaging	imaging	NOUN
cana-3964	200	14	data	datum	NOUN
cana-3964	200	15	.	.	PUNCT
cana-3964	201	1	finally	finally	ADV
cana-3964	201	2	,	,	PUNCT
cana-3964	201	3	the	the	DET
cana-3964	201	4	clinical	clinical	ADJ
cana-3964	201	5	text	text	NOUN
cana-3964	201	6	data	datum	NOUN
cana-3964	201	7	dataset	dataset	NOUN
cana-3964	201	8	contains	contain	VERB
cana-3964	201	9	textual	textual	ADJ
cana-3964	201	10	features	feature	NOUN
cana-3964	201	11	and	and	CCONJ
cana-3964	201	12	offers	offer	VERB
cana-3964	201	13	a	a	DET
cana-3964	201	14	different	different	ADJ
cana-3964	201	15	dimension	dimension	NOUN
cana-3964	201	16	to	to	ADP
cana-3964	201	17	breast	breast	NOUN
cana-3964	201	18	cancer	cancer	NOUN
cana-3964	201	19	analysis	analysis	NOUN
cana-3964	201	20	.	.	PUNCT
cana-3964	202	1	researchers	researcher	NOUN
cana-3964	202	2	can	can	AUX
cana-3964	202	3	select	select	VERB
cana-3964	202	4	from	from	ADP
cana-3964	202	5	these	these	DET
cana-3964	202	6	datasets	dataset	NOUN
cana-3964	202	7	based	base	VERB
cana-3964	202	8	on	on	ADP
cana-3964	202	9	their	their	PRON
cana-3964	202	10	specific	specific	ADJ
cana-3964	202	11	research	research	NOUN
cana-3964	202	12	objectives	objective	NOUN
cana-3964	202	13	,	,	PUNCT
cana-3964	202	14	size	size	NOUN
cana-3964	202	15	requirements	requirement	NOUN
cana-3964	202	16	,	,	PUNCT
cana-3964	202	17	and	and	CCONJ
cana-3964	202	18	the	the	DET
cana-3964	202	19	type	type	NOUN
cana-3964	202	20	of	of	ADP
cana-3964	202	21	data	datum	NOUN
cana-3964	202	22	,	,	PUNCT
cana-3964	202	23	like	like	ADP
cana-3964	202	24	numerical	numerical	ADJ
cana-3964	202	25	,	,	PUNCT
cana-3964	202	26	image	image	NOUN
cana-3964	202	27	-	-	PUNCT
cana-3964	202	28	based	base	VERB
cana-3964	202	29	,	,	PUNCT
cana-3964	202	30	or	or	CCONJ
cana-3964	202	31	textual	textual	ADJ
cana-3964	202	32	,	,	PUNCT
cana-3964	202	33	that	that	PRON
cana-3964	202	34	best	good	ADJ
cana-3964	202	35	suits	suit	VERB
cana-3964	202	36	their	their	PRON
cana-3964	202	37	research	research	NOUN
cana-3964	202	38	[	[	X
cana-3964	202	39	37	37	NUM
cana-3964	202	40	]	]	PUNCT
cana-3964	202	41	.	.	PUNCT
cana-3964	203	1	4	4	X
cana-3964	203	2	.	.	X
cana-3964	203	3	performance	performance	NOUN
cana-3964	203	4	evaluation	evaluation	NOUN
cana-3964	203	5	and	and	CCONJ
cana-3964	203	6	comparison	comparison	NOUN
cana-3964	203	7	this	this	DET
cana-3964	203	8	section	section	NOUN
cana-3964	203	9	reviews	review	VERB
cana-3964	203	10	the	the	DET
cana-3964	203	11	research	research	NOUN
cana-3964	203	12	to	to	PART
cana-3964	203	13	compare	compare	VERB
cana-3964	203	14	the	the	DET
cana-3964	203	15	performance	performance	NOUN
cana-3964	203	16	of	of	ADP
cana-3964	203	17	ml	ml	NOUN
cana-3964	203	18	techniques	technique	NOUN
cana-3964	203	19	in	in	ADP
cana-3964	203	20	breast	breast	NOUN
cana-3964	203	21	cancer	cancer	NOUN
cana-3964	203	22	diagnosis	diagnosis	NOUN
cana-3964	203	23	on	on	ADP
cana-3964	203	24	a	a	DET
cana-3964	203	25	variety	variety	NOUN
cana-3964	203	26	of	of	ADP
cana-3964	203	27	datasets	dataset	NOUN
cana-3964	203	28	.	.	PUNCT
cana-3964	204	1	it	it	PRON
cana-3964	204	2	can	can	AUX
cana-3964	204	3	be	be	AUX
cana-3964	204	4	calculated	calculate	VERB
cana-3964	204	5	by	by	ADP
cana-3964	204	6	using	use	VERB
cana-3964	204	7	the	the	DET
cana-3964	204	8	parameters	parameter	NOUN
cana-3964	204	9	accuracy	accuracy	NOUN
cana-3964	204	10	,	,	PUNCT
cana-3964	204	11	precision	precision	NOUN
cana-3964	204	12	,	,	PUNCT
cana-3964	204	13	recall	recall	NOUN
cana-3964	204	14	,	,	PUNCT
cana-3964	204	15	and	and	CCONJ
cana-3964	204	16	f1	f1	NOUN
cana-3964	204	17	-	-	PUNCT
cana-3964	204	18	score	score	NOUN
cana-3964	204	19	.	.	PUNCT
cana-3964	205	1	true	true	ADJ
cana-3964	205	2	positives	positive	NOUN
cana-3964	205	3	(	(	PUNCT
cana-3964	205	4	tp	tp	NOUN
cana-3964	205	5	)	)	PUNCT
cana-3964	205	6	and	and	CCONJ
cana-3964	205	7	true	true	ADJ
cana-3964	205	8	negatives	negative	NOUN
cana-3964	205	9	(	(	PUNCT
cana-3964	205	10	tn	tn	NOUN
cana-3964	205	11	)	)	PUNCT
cana-3964	205	12	are	be	AUX
cana-3964	205	13	taken	take	VERB
cana-3964	205	14	into	into	ADP
cana-3964	205	15	account	account	NOUN
cana-3964	205	16	while	while	SCONJ
cana-3964	205	17	calculating	calculate	VERB
cana-3964	205	18	accuracy	accuracy	NOUN
cana-3964	205	19	,	,	PUNCT
cana-3964	205	20	which	which	PRON
cana-3964	205	21	is	be	AUX
cana-3964	205	22	a	a	DET
cana-3964	205	23	measure	measure	NOUN
cana-3964	205	24	of	of	ADP
cana-3964	205	25	the	the	DET
cana-3964	205	26	total	total	ADJ
cana-3964	205	27	correctness	correctness	NOUN
cana-3964	205	28	of	of	ADP
cana-3964	205	29	forecasts	forecast	NOUN
cana-3964	205	30	[	[	X
cana-3964	205	31	38	38	NUM
cana-3964	205	32	]	]	PUNCT
cana-3964	205	33	.	.	PUNCT
cana-3964	206	1	accuracy	accuracy	NOUN
cana-3964	207	1	=	=	PRON
cana-3964	207	2	tp	tp	X
cana-3964	207	3	+	+	NOUN
cana-3964	207	4	tn	tn	PROPN
cana-3964	207	5	/	/	SYM
cana-3964	207	6	(	(	PUNCT
cana-3964	207	7	tp	tp	ADP
cana-3964	207	8	+	+	CCONJ
cana-3964	207	9	tn	tn	NOUN
cana-3964	208	1	+	+	CCONJ
cana-3964	208	2	fp	fp	PROPN
cana-3964	208	3	+	+	NUM
cana-3964	208	4	fn	fn	NOUN
cana-3964	208	5	)	)	PUNCT
cana-3964	208	6	,	,	PUNCT
cana-3964	208	7	precision	precision	NOUN
cana-3964	208	8	=	=	SYM
cana-3964	208	9	𝑇p/	𝑇p/	PROPN
cana-3964	208	10	(	(	PUNCT
cana-3964	208	11	tp+fp	tp+fp	NOUN
cana-3964	208	12	)	)	PUNCT
cana-3964	208	13	,	,	PUNCT
cana-3964	208	14	recall	recall	NOUN
cana-3964	208	15	=	=	SYM
cana-3964	208	16	tp/	tp/	PROPN
cana-3964	208	17	(	(	PUNCT
cana-3964	208	18	tp+fn	tp+fn	NOUN
cana-3964	208	19	)	)	PUNCT
cana-3964	208	20	,	,	PUNCT
cana-3964	208	21	f1	f1	NOUN
cana-3964	208	22	-	-	PUNCT
cana-3964	208	23	score	score	NOUN
cana-3964	208	24	=	=	PUNCT
cana-3964	208	25	2*(precision	2*(precision	NUM
cana-3964	208	26	*	*	NOUN
cana-3964	208	27	recall	recall	NOUN
cana-3964	208	28	)	)	PUNCT
cana-3964	208	29	/	/	PUNCT
cana-3964	208	30	(	(	PUNCT
cana-3964	208	31	precision	precision	NOUN
cana-3964	208	32	+	+	CCONJ
cana-3964	208	33	recall	recall	NOUN
cana-3964	208	34	)	)	PUNCT
cana-3964	208	35	.	.	PUNCT
cana-3964	209	1	the	the	DET
cana-3964	209	2	terms	term	NOUN
cana-3964	209	3	related	relate	VERB
cana-3964	209	4	to	to	ADP
cana-3964	209	5	these	these	DET
cana-3964	209	6	metrics	metric	NOUN
cana-3964	209	7	are	be	AUX
cana-3964	209	8	described	describe	VERB
cana-3964	209	9	and	and	CCONJ
cana-3964	209	10	clarified	clarify	VERB
cana-3964	209	11	in	in	ADP
cana-3964	209	12	table	table	NOUN
cana-3964	209	13	4	4	NUM
cana-3964	209	14	.	.	PUNCT
cana-3964	209	15	table	table	NOUN
cana-3964	209	16	4	4	NUM
cana-3964	209	17	description	description	NOUN
cana-3964	209	18	of	of	ADP
cana-3964	209	19	short	short	ADJ
cana-3964	209	20	terms	term	NOUN
cana-3964	209	21	used	use	VERB
cana-3964	209	22	in	in	ADP
cana-3964	209	23	performance	performance	NOUN
cana-3964	209	24	metrices	metrice	NOUN
cana-3964	209	25	short	short	ADJ
cana-3964	209	26	terms	term	NOUN
cana-3964	209	27	description	description	NOUN
cana-3964	209	28	clarification	clarification	NOUN
cana-3964	209	29	tp	tp	ADP
cana-3964	209	30	true	true	ADJ
cana-3964	209	31	positives	positive	NOUN
cana-3964	209	32	properly	properly	ADV
cana-3964	209	33	identified	identify	VERB
cana-3964	209	34	positive	positive	ADJ
cana-3964	209	35	cases	case	NOUN
cana-3964	209	36	tn	tn	ADP
cana-3964	209	37	true	true	ADJ
cana-3964	209	38	negatives	negative	NOUN
cana-3964	209	39	accurately	accurately	ADV
cana-3964	209	40	identified	identify	VERB
cana-3964	209	41	negative	negative	ADJ
cana-3964	209	42	cases	case	NOUN
cana-3964	209	43	fp	fp	DET
cana-3964	209	44	false	false	ADJ
cana-3964	209	45	positives	positive	NOUN
cana-3964	209	46	(	(	PUNCT
cana-3964	209	47	type	type	NOUN
cana-3964	209	48	1	1	NUM
cana-3964	209	49	error	error	NOUN
cana-3964	209	50	)	)	PUNCT
cana-3964	209	51	negative	negative	ADJ
cana-3964	209	52	cases	case	NOUN
cana-3964	209	53	incorrectly	incorrectly	ADV
cana-3964	209	54	predicted	predict	VERB
cana-3964	209	55	as	as	ADP
cana-3964	209	56	positive	positive	ADJ
cana-3964	209	57	communications	communication	NOUN
cana-3964	209	58	on	on	ADP
cana-3964	209	59	applied	apply	VERB
cana-3964	209	60	nonlinear	nonlinear	ADJ
cana-3964	209	61	analysis	analysis	NOUN
cana-3964	209	62	issn	issn	NOUN
cana-3964	209	63	:	:	PUNCT
cana-3964	209	64	1074	1074	NUM
cana-3964	209	65	-	-	PUNCT
cana-3964	209	66	133x	133x	NUM
cana-3964	209	67	vol	vol	NOUN
cana-3964	209	68	32	32	NUM
cana-3964	209	69	no	no	NOUN
cana-3964	209	70	.	.	PUNCT
cana-3964	210	1	9s	9s	NUM
cana-3964	210	2	(	(	PUNCT
cana-3964	210	3	2025	2025	NUM
cana-3964	210	4	)	)	PUNCT
cana-3964	210	5	564	564	NUM
cana-3964	210	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	210	7	fn	fn	PRON
cana-3964	210	8	false	false	ADJ
cana-3964	210	9	negatives	negative	NOUN
cana-3964	210	10	(	(	PUNCT
cana-3964	210	11	type	type	NOUN
cana-3964	210	12	2	2	NUM
cana-3964	210	13	error	error	NOUN
cana-3964	210	14	)	)	PUNCT
cana-3964	210	15	positive	positive	ADJ
cana-3964	210	16	cases	case	NOUN
cana-3964	210	17	incorrectly	incorrectly	ADV
cana-3964	210	18	predicted	predict	VERB
cana-3964	210	19	as	as	ADP
cana-3964	210	20	negative	negative	ADJ
cana-3964	210	21	table	table	NOUN
cana-3964	210	22	5	5	NUM
cana-3964	210	23	provides	provide	VERB
cana-3964	210	24	an	an	DET
cana-3964	210	25	overview	overview	NOUN
cana-3964	210	26	of	of	ADP
cana-3964	210	27	diverse	diverse	ADJ
cana-3964	210	28	studies	study	NOUN
cana-3964	210	29	in	in	ADP
cana-3964	210	30	breast	breast	NOUN
cana-3964	210	31	cancer	cancer	NOUN
cana-3964	210	32	diagnosis	diagnosis	NOUN
cana-3964	210	33	.	.	PUNCT
cana-3964	211	1	it	it	PRON
cana-3964	211	2	covers	cover	VERB
cana-3964	211	3	the	the	DET
cana-3964	211	4	datasets	dataset	NOUN
cana-3964	211	5	utilized	utilize	VERB
cana-3964	211	6	,	,	PUNCT
cana-3964	211	7	the	the	DET
cana-3964	211	8	algorithms	algorithm	NOUN
cana-3964	211	9	applied	apply	VERB
cana-3964	211	10	,	,	PUNCT
cana-3964	211	11	and	and	CCONJ
cana-3964	211	12	the	the	DET
cana-3964	211	13	corresponding	corresponding	ADJ
cana-3964	211	14	levels	level	NOUN
cana-3964	211	15	of	of	ADP
cana-3964	211	16	accuracy	accuracy	NOUN
cana-3964	211	17	,	,	PUNCT
cana-3964	211	18	precision	precision	NOUN
cana-3964	211	19	,	,	PUNCT
cana-3964	211	20	recall	recall	NOUN
cana-3964	211	21	,	,	PUNCT
cana-3964	211	22	and	and	CCONJ
cana-3964	211	23	f1score	f1score	NOUN
cana-3964	211	24	achieved	achieve	VERB
cana-3964	211	25	in	in	ADP
cana-3964	211	26	each	each	DET
cana-3964	211	27	research	research	NOUN
cana-3964	211	28	and	and	CCONJ
cana-3964	211	29	presents	present	VERB
cana-3964	211	30	a	a	DET
cana-3964	211	31	comparison	comparison	NOUN
cana-3964	211	32	of	of	ADP
cana-3964	211	33	research	research	NOUN
cana-3964	211	34	and	and	CCONJ
cana-3964	211	35	highlighting	highlight	VERB
cana-3964	211	36	the	the	DET
cana-3964	211	37	dataset	dataset	NOUN
cana-3964	211	38	used	use	VERB
cana-3964	211	39	,	,	PUNCT
cana-3964	211	40	the	the	DET
cana-3964	211	41	algorithms	algorithm	NOUN
cana-3964	211	42	employed	employ	VERB
cana-3964	211	43	,	,	PUNCT
cana-3964	211	44	and	and	CCONJ
cana-3964	211	45	the	the	DET
cana-3964	211	46	performance	performance	NOUN
cana-3964	211	47	metrics	metric	NOUN
cana-3964	211	48	.	.	PUNCT
cana-3964	212	1	table	table	NOUN
cana-3964	212	2	5	5	NUM
cana-3964	212	3	comparison	comparison	NOUN
cana-3964	212	4	of	of	ADP
cana-3964	212	5	various	various	ADJ
cana-3964	212	6	author	author	NOUN
cana-3964	212	7	’s	’s	PART
cana-3964	212	8	works	work	NOUN
cana-3964	212	9	in	in	ADP
cana-3964	212	10	breast	breast	NOUN
cana-3964	212	11	cancer	cancer	NOUN
cana-3964	212	12	diagnosis	diagnosis	NOUN
cana-3964	212	13	author	author	NOUN
cana-3964	212	14	&	&	CCONJ
cana-3964	212	15	year	year	PROPN
cana-3964	212	16	dataset	dataset	VERB
cana-3964	212	17	algorith	algorith	PROPN
cana-3964	212	18	ms	ms	PROPN
cana-3964	212	19	accura	accura	PROPN
cana-3964	212	20	cy	cy	AUX
cana-3964	212	21	precisio	precisio	VERB
cana-3964	212	22	n	n	PRON
cana-3964	212	23	recall	recall	VERB
cana-3964	212	24	f1sco	f1sco	PROPN
cana-3964	212	25	re	re	PROPN
cana-3964	212	26	limitations	limitations	PROPN
cana-3964	212	27	agarap	agarap	PROPN
cana-3964	212	28	(	(	PUNCT
cana-3964	212	29	2018	2018	NUM
cana-3964	212	30	)	)	PUNCT
cana-3964	213	1	[	[	X
cana-3964	213	2	5	5	NUM
cana-3964	213	3	]	]	PUNCT
cana-3964	213	4	wdbc	wdbc	VERB
cana-3964	213	5	support	support	NOUN
cana-3964	213	6	vector	vector	NOUN
cana-3964	213	7	machine	machine	NOUN
cana-3964	213	8	.9714	.9714	NOUN
cana-3964	213	9	0	0	NUM
cana-3964	213	10	.98	.98	NUM
cana-3964	213	11	0.97	0.97	NUM
cana-3964	213	12	0.97	0.97	NUM
cana-3964	213	13	more	more	ADJ
cana-3964	213	14	dataset	dataset	NOUN
cana-3964	213	15	may	may	AUX
cana-3964	213	16	be	be	AUX
cana-3964	213	17	used	use	VERB
cana-3964	213	18	and	and	CCONJ
cana-3964	213	19	deep	deep	ADJ
cana-3964	213	20	learning	learning	NOUN
cana-3964	213	21	can	can	AUX
cana-3964	213	22	be	be	AUX
cana-3964	213	23	applied	apply	VERB
cana-3964	213	24	to	to	PART
cana-3964	213	25	improve	improve	VERB
cana-3964	213	26	rajaguru	rajaguru	ADV
cana-3964	213	27	and	and	CCONJ
cana-3964	213	28	s	s	PROPN
cana-3964	213	29	(	(	PUNCT
cana-3964	213	30	2019	2019	NUM
cana-3964	213	31	)	)	PUNCT
cana-3964	214	1	[	[	X
cana-3964	214	2	9	9	NUM
cana-3964	214	3	]	]	PUNCT
cana-3964	214	4	wdbc	wdbc	NOUN
cana-3964	214	5	knn	knn	PROPN
cana-3964	214	6	.9561	.9561	PROPN
cana-3964	215	1	.9452	.9452	PUNCT
cana-3964	215	2	expensive	expensive	ADJ
cana-3964	215	3	for	for	ADP
cana-3964	215	4	large	large	ADJ
cana-3964	215	5	datasets	dataset	NOUN
cana-3964	215	6	.	.	PUNCT
cana-3964	216	1	al	al	PROPN
cana-3964	216	2	-	-	PUNCT
cana-3964	216	3	shargabi	shargabi	PROPN
cana-3964	216	4	et	et	PROPN
cana-3964	216	5	al	al	PROPN
cana-3964	216	6	.	.	PROPN
cana-3964	217	1	(	(	PUNCT
cana-3964	217	2	2019	2019	NUM
cana-3964	217	3	)	)	PUNCT
cana-3964	218	1	[	[	X
cana-3964	218	2	10	10	NUM
cana-3964	218	3	]	]	PUNCT
cana-3964	218	4	wdbc	wdbc	NOUN
cana-3964	218	5	multilayer	multilayer	NOUN
cana-3964	218	6	perceptro	perceptro	NOUN
cana-3964	218	7	n	n	INTJ
cana-3964	218	8	.9770	.9770	NOUN
cana-3964	218	9	prone	prone	ADJ
cana-3964	218	10	to	to	ADP
cana-3964	218	11	overfitting	overfitte	VERB
cana-3964	218	12	,	,	PUNCT
cana-3964	218	13	particular	particular	ADJ
cana-3964	218	14	on	on	ADP
cana-3964	218	15	small	small	ADJ
cana-3964	218	16	datasets	dataset	NOUN
cana-3964	218	17	.	.	PUNCT
cana-3964	219	1	chaurasia	chaurasia	PROPN
cana-3964	219	2	and	and	CCONJ
cana-3964	219	3	pal	pal	ADJ
cana-3964	219	4	(	(	PUNCT
cana-3964	219	5	2020	2020	NUM
cana-3964	219	6	)	)	PUNCT
cana-3964	220	1	[	[	X
cana-3964	220	2	13	13	NUM
cana-3964	220	3	]	]	PUNCT
cana-3964	220	4	wdbc	wdbc	VERB
cana-3964	220	5	ensemble	ensemble	ADJ
cana-3964	220	6	learning	learning	NOUN
cana-3964	220	7	.95173	.95173	NOUN
cana-3964	220	8	9	9	NUM
cana-3964	220	9	investigate	investigate	VERB
cana-3964	220	10	deep	deep	ADJ
cana-3964	220	11	learning	learning	NOUN
cana-3964	220	12	for	for	ADP
cana-3964	220	13	better	well	ADJ
cana-3964	220	14	classification	classification	NOUN
cana-3964	220	15	and	and	CCONJ
cana-3964	220	16	validate	validate	VERB
cana-3964	220	17	&	&	CCONJ
cana-3964	220	18	construct	construct	VERB
cana-3964	220	19	an	an	DET
cana-3964	220	20	ideal	ideal	ADJ
cana-3964	220	21	classifier	classifier	NOUN
cana-3964	220	22	murtirawat	murtirawat	VERB
cana-3964	220	23	et	et	PROPN
cana-3964	220	24	al	al	PROPN
cana-3964	220	25	.	.	PROPN
cana-3964	221	1	(	(	PUNCT
cana-3964	221	2	2020	2020	NUM
cana-3964	221	3	)	)	PUNCT
cana-3964	222	1	[	[	X
cana-3964	222	2	14	14	NUM
cana-3964	222	3	]	]	PUNCT
cana-3964	222	4	wdbc	wdbc	VERB
cana-3964	222	5	ensemble	ensemble	ADJ
cana-3964	222	6	learning	learning	NOUN
cana-3964	222	7	.9930	.9930	PROPN
cana-3964	222	8	1.0	1.0	NUM
cana-3964	222	9	.977	.977	NUM
cana-3964	222	10	7	7	NUM
cana-3964	222	11	.9887	.9887	NUM
cana-3964	222	12	more	more	ADJ
cana-3964	222	13	data	datum	NOUN
cana-3964	222	14	can	can	AUX
cana-3964	222	15	be	be	AUX
cana-3964	222	16	added	add	VERB
cana-3964	222	17	into	into	ADP
cana-3964	222	18	database	database	NOUN
cana-3964	222	19	which	which	PRON
cana-3964	222	20	will	will	AUX
cana-3964	222	21	help	help	VERB
cana-3964	222	22	in	in	ADP
cana-3964	222	23	training	training	NOUN
cana-3964	222	24	of	of	ADP
cana-3964	222	25	ml	ml	NOUN
cana-3964	222	26	model	model	NOUN
cana-3964	222	27	and	and	CCONJ
cana-3964	222	28	would	would	AUX
cana-3964	222	29	work	work	VERB
cana-3964	222	30	more	more	ADV
cana-3964	222	31	accurately	accurately	ADV
cana-3964	222	32	hazra	hazra	VERB
cana-3964	222	33	et	et	PROPN
cana-3964	222	34	al	al	PROPN
cana-3964	222	35	.	.	PROPN
cana-3964	223	1	(	(	PUNCT
cana-3964	223	2	2020	2020	NUM
cana-3964	223	3	)	)	PUNCT
cana-3964	224	1	[	[	X
cana-3964	224	2	16	16	NUM
cana-3964	224	3	]	]	PUNCT
cana-3964	224	4	wdbc	wdbc	VERB
cana-3964	224	5	artificial	artificial	ADJ
cana-3964	224	6	neural	neural	ADJ
cana-3964	224	7	networks	network	NOUN
cana-3964	224	8	.9855	.9855	VERB
cana-3964	224	9	1.00	1.00	NUM
cana-3964	224	10	0.97	0.97	NUM
cana-3964	224	11	0.99	0.99	NUM
cana-3964	224	12	incorporate	incorporate	VERB
cana-3964	224	13	the	the	DET
cana-3964	224	14	selected	select	VERB
cana-3964	224	15	method	method	NOUN
cana-3964	224	16	into	into	ADP
cana-3964	224	17	a	a	DET
cana-3964	224	18	practical	practical	ADJ
cana-3964	224	19	strategy	strategy	NOUN
cana-3964	224	20	.	.	PUNCT
cana-3964	225	1	haq	haq	PROPN
cana-3964	225	2	et	et	PROPN
cana-3964	225	3	al	al	PROPN
cana-3964	225	4	.	.	PROPN
cana-3964	226	1	(	(	PUNCT
cana-3964	226	2	2021	2021	NUM
cana-3964	226	3	)	)	PUNCT
cana-3964	227	1	[	[	X
cana-3964	227	2	17	17	NUM
cana-3964	227	3	]	]	PUNCT
cana-3964	227	4	wdbc	wdbc	NOUN
cana-3964	227	5	pcasvm	pcasvm	NOUN
cana-3964	227	6	.9745	.9745	PROPN
cana-3964	228	1	0.88	0.88	NUM
cana-3964	228	2	other	other	ADJ
cana-3964	228	3	feature	feature	NOUN
cana-3964	228	4	selection	selection	NOUN
cana-3964	228	5	algorithm	algorithm	NOUN
cana-3964	228	6	and	and	CCONJ
cana-3964	228	7	deep	deep	ADJ
cana-3964	228	8	learning	learning	NOUN
cana-3964	228	9	can	can	AUX
cana-3964	228	10	be	be	AUX
cana-3964	228	11	applied	apply	VERB
cana-3964	228	12	.	.	PUNCT
cana-3964	229	1	communications	communication	NOUN
cana-3964	229	2	on	on	ADP
cana-3964	229	3	applied	apply	VERB
cana-3964	229	4	nonlinear	nonlinear	ADJ
cana-3964	229	5	analysis	analysis	NOUN
cana-3964	229	6	issn	issn	NOUN
cana-3964	229	7	:	:	PUNCT
cana-3964	229	8	1074	1074	NUM
cana-3964	229	9	-	-	PUNCT
cana-3964	229	10	133x	133x	NUM
cana-3964	229	11	vol	vol	NOUN
cana-3964	229	12	32	32	NUM
cana-3964	229	13	no	no	NOUN
cana-3964	229	14	.	.	PUNCT
cana-3964	230	1	9s	9s	NUM
cana-3964	230	2	(	(	PUNCT
cana-3964	230	3	2025	2025	NUM
cana-3964	230	4	)	)	PUNCT
cana-3964	230	5	565	565	NUM
cana-3964	230	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	230	7	jabbar	jabbar	NOUN
cana-3964	230	8	(	(	PUNCT
cana-3964	230	9	2021	2021	NUM
cana-3964	230	10	)	)	PUNCT
cana-3964	231	1	[	[	X
cana-3964	231	2	18	18	NUM
cana-3964	231	3	]	]	PUNCT
cana-3964	231	4	wdbc	wdbc	NOUN
cana-3964	231	5	bayesian	bayesian	NOUN
cana-3964	231	6	network	network	NOUN
cana-3964	231	7	and	and	CCONJ
cana-3964	231	8	(	(	PUNCT
cana-3964	231	9	rbf	rbf	PROPN
cana-3964	231	10	)	)	PUNCT
cana-3964	231	11	0.97	0.97	NUM
cana-3964	231	12	.9672	.9672	NOUN
cana-3964	231	13	accuracy	accuracy	NOUN
cana-3964	231	14	may	may	AUX
cana-3964	231	15	be	be	AUX
cana-3964	231	16	increase	increase	VERB
cana-3964	231	17	by	by	ADP
cana-3964	231	18	using	use	VERB
cana-3964	231	19	other	other	ADJ
cana-3964	231	20	methods	method	NOUN
cana-3964	231	21	rasool	rasool	PROPN
cana-3964	231	22	et	et	PROPN
cana-3964	231	23	al	al	PROPN
cana-3964	231	24	.	.	PROPN
cana-3964	232	1	(	(	PUNCT
cana-3964	232	2	2022	2022	NUM
cana-3964	232	3	)	)	PUNCT
cana-3964	233	1	[	[	X
cana-3964	233	2	20	20	NUM
cana-3964	233	3	]	]	PUNCT
cana-3964	233	4	wdbc	wdbc	VERB
cana-3964	233	5	polynomi	polynomi	NOUN
cana-3964	233	6	al	al	PROPN
cana-3964	233	7	svm	svm	PROPN
cana-3964	233	8	.9912	.9912	PROPN
cana-3964	233	9	.9862	.9862	PROPN
cana-3964	233	10	1.00	1.00	NUM
cana-3964	233	11	.993	.993	NUM
cana-3964	233	12	try	try	VERB
cana-3964	233	13	different	different	ADJ
cana-3964	233	14	global	global	ADJ
cana-3964	233	15	datasets	dataset	NOUN
cana-3964	233	16	to	to	PART
cana-3964	233	17	check	check	VERB
cana-3964	233	18	how	how	SCONJ
cana-3964	233	19	the	the	DET
cana-3964	233	20	performance	performance	NOUN
cana-3964	233	21	is	be	AUX
cana-3964	233	22	affected	affect	VERB
cana-3964	233	23	by	by	ADP
cana-3964	233	24	region	region	NOUN
cana-3964	233	25	.	.	PUNCT
cana-3964	234	1	mangukiya	mangukiya	PROPN
cana-3964	234	2	et	et	PROPN
cana-3964	234	3	al	al	PROPN
cana-3964	234	4	.	.	PROPN
cana-3964	235	1	(	(	PUNCT
cana-3964	235	2	2022	2022	NUM
cana-3964	235	3	)	)	PUNCT
cana-3964	236	1	[	[	X
cana-3964	236	2	22	22	NUM
cana-3964	236	3	]	]	PUNCT
cana-3964	236	4	wdbc	wdbc	VERB
cana-3964	236	5	xgboost	xgboost	X
cana-3964	237	1	.9824	.9824	PRON
cana-3964	237	2	examine	examine	VERB
cana-3964	237	3	scalability	scalability	NOUN
cana-3964	237	4	and	and	CCONJ
cana-3964	237	5	efficiency	efficiency	NOUN
cana-3964	237	6	on	on	ADP
cana-3964	237	7	large	large	ADJ
cana-3964	237	8	datasets	dataset	NOUN
cana-3964	237	9	.	.	PUNCT
cana-3964	238	1	hossin	hossin	VERB
cana-3964	238	2	et	et	PROPN
cana-3964	238	3	al	al	PROPN
cana-3964	238	4	.	.	PROPN
cana-3964	239	1	(	(	PUNCT
cana-3964	239	2	2023	2023	NUM
cana-3964	239	3	)	)	PUNCT
cana-3964	240	1	[	[	X
cana-3964	240	2	28	28	NUM
cana-3964	240	3	]	]	X
cana-3964	240	4	wdbc	wdbc	VERB
cana-3964	240	5	logistic	logistic	ADJ
cana-3964	240	6	regressio	regressio	NOUN
cana-3964	240	7	n	n	NOUN
cana-3964	240	8	and	and	CCONJ
cana-3964	240	9	svm	svm	PROPN
cana-3964	240	10	.9912	.9912	PROPN
cana-3964	240	11	.977	.977	NUM
cana-3964	240	12	3	3	NUM
cana-3964	240	13	massive	massive	ADJ
cana-3964	240	14	datasets	dataset	NOUN
cana-3964	240	15	and	and	CCONJ
cana-3964	240	16	new	new	ADJ
cana-3964	240	17	algorithms	algorithm	NOUN
cana-3964	240	18	can	can	AUX
cana-3964	240	19	be	be	AUX
cana-3964	240	20	used	use	VERB
cana-3964	240	21	to	to	PART
cana-3964	240	22	improve	improve	VERB
cana-3964	240	23	accuracy	accuracy	NOUN
cana-3964	240	24	chen	chen	PROPN
cana-3964	240	25	et	et	PROPN
cana-3964	240	26	al	al	PROPN
cana-3964	240	27	.	.	PROPN
cana-3964	241	1	(	(	PUNCT
cana-3964	241	2	2023	2023	NUM
cana-3964	241	3	)	)	PUNCT
cana-3964	242	1	[	[	X
cana-3964	242	2	29	29	NUM
cana-3964	242	3	]	]	PUNCT
cana-3964	242	4	wdbc	wdbc	VERB
cana-3964	242	5	xgboost	xgboost	ADV
cana-3964	242	6	.974	.974	NUM
cana-3964	242	7	0.960	0.960	NUM
cana-3964	242	8	1.00	1.00	NUM
cana-3964	242	9	0.980	0.980	NUM
cana-3964	242	10	limited	limit	VERB
cana-3964	242	11	to	to	ADP
cana-3964	242	12	numerical	numerical	PROPN
cana-3964	242	13	data	data	PROPN
cana-3964	242	14	kadhim	kadhim	PROPN
cana-3964	242	15	and	and	CCONJ
cana-3964	242	16	kamil	kamil	PROPN
cana-3964	242	17	(	(	PUNCT
cana-3964	242	18	2023	2023	NUM
cana-3964	242	19	)	)	PUNCT
cana-3964	243	1	[	[	X
cana-3964	243	2	30	30	NUM
cana-3964	243	3	]	]	PUNCT
cana-3964	243	4	wdbc	wdbc	VERB
cana-3964	243	5	gb	gb	ADP
cana-3964	243	6	.9736	.9736	NOUN
cana-3964	243	7	1.00	1.00	NUM
cana-3964	243	8	.978	.978	NUM
cana-3964	243	9	7	7	NUM
cana-3964	243	10	more	more	ADJ
cana-3964	243	11	datasets	dataset	NOUN
cana-3964	243	12	may	may	AUX
cana-3964	243	13	be	be	AUX
cana-3964	243	14	used	use	VERB
cana-3964	243	15	.	.	PUNCT
cana-3964	244	1	sharma	sharma	PROPN
cana-3964	244	2	et	et	PROPN
cana-3964	244	3	al	al	PROPN
cana-3964	244	4	.	.	PROPN
cana-3964	244	5	(	(	PUNCT
cana-3964	244	6	2024	2024	NUM
cana-3964	244	7	)	)	PUNCT
cana-3964	245	1	[	[	X
cana-3964	245	2	31	31	NUM
cana-3964	245	3	]	]	PUNCT
cana-3964	245	4	wdbc	wdbc	VERB
cana-3964	245	5	stacked	stack	VERB
cana-3964	245	6	based	base	VERB
cana-3964	245	7	ensemble	ensemble	ADJ
cana-3964	245	8	classifier	classifier	NOUN
cana-3964	245	9	.9766	.9766	PROPN
cana-3964	246	1	deep	deep	ADJ
cana-3964	246	2	learning	learning	NOUN
cana-3964	246	3	technique	technique	NOUN
cana-3964	246	4	may	may	AUX
cana-3964	246	5	be	be	AUX
cana-3964	246	6	used	use	VERB
cana-3964	246	7	in	in	ADP
cana-3964	246	8	to	to	PART
cana-3964	246	9	handle	handle	VERB
cana-3964	246	10	large	large	ADJ
cana-3964	246	11	amount	amount	NOUN
cana-3964	246	12	of	of	ADP
cana-3964	246	13	data	datum	NOUN
cana-3964	246	14	and	and	CCONJ
cana-3964	246	15	ensure	ensure	VERB
cana-3964	246	16	patient	patient	NOUN
cana-3964	246	17	’s	’s	PART
cana-3964	246	18	data	datum	NOUN
cana-3964	246	19	privacy	privacy	NOUN
cana-3964	246	20	.	.	PUNCT
cana-3964	247	1	allugunti	allugunti	NOUN
cana-3964	247	2	(	(	PUNCT
cana-3964	247	3	2022	2022	NUM
cana-3964	247	4	)	)	PUNCT
cana-3964	248	1	[	[	X
cana-3964	248	2	23	23	NUM
cana-3964	248	3	]	]	X
cana-3964	248	4	thermo	thermo	NOUN
cana-3964	248	5	graphic	graphic	ADJ
cana-3964	248	6	images	image	NOUN
cana-3964	248	7	cnn	cnn	PROPN
cana-3964	248	8	.9965	.9965	PRON
cana-3964	248	9	lack	lack	NOUN
cana-3964	248	10	of	of	ADP
cana-3964	248	11	practical	practical	ADJ
cana-3964	248	12	relevance	relevance	NOUN
cana-3964	248	13	aljuaid	aljuaid	VERB
cana-3964	248	14	et	et	PROPN
cana-3964	248	15	al	al	PROPN
cana-3964	248	16	.	.	PROPN
cana-3964	249	1	(	(	PUNCT
cana-3964	249	2	2022	2022	NUM
cana-3964	249	3	)	)	PUNCT
cana-3964	250	1	[	[	X
cana-3964	250	2	25	25	NUM
cana-3964	250	3	]	]	X
cana-3964	250	4	breakhi	breakhi	PROPN
cana-3964	250	5	s	s	PART
cana-3964	250	6	deep	deep	ADJ
cana-3964	250	7	neural	neural	ADJ
cana-3964	250	8	networks	network	NOUN
cana-3964	250	9	.9970	.9970	PROPN
cana-3964	250	10	.9959	.9959	DET
cana-3964	250	11	model	model	NOUN
cana-3964	250	12	may	may	AUX
cana-3964	250	13	be	be	AUX
cana-3964	250	14	improved	improve	VERB
cana-3964	250	15	by	by	ADP
cana-3964	250	16	using	use	VERB
cana-3964	250	17	different	different	ADJ
cana-3964	250	18	of	of	ADP
cana-3964	250	19	datasets	dataset	NOUN
cana-3964	250	20	.	.	PUNCT
cana-3964	251	1	dewangan	dewangan	PROPN
cana-3964	251	2	et	et	PROPN
cana-3964	251	3	al	al	PROPN
cana-3964	251	4	.	.	PROPN
cana-3964	252	1	(	(	PUNCT
cana-3964	252	2	2022	2022	NUM
cana-3964	252	3	)	)	PUNCT
cana-3964	253	1	[	[	X
cana-3964	253	2	26	26	NUM
cana-3964	253	3	]	]	PUNCT
cana-3964	253	4	mri	mri	NOUN
cana-3964	253	5	images	image	NOUN
cana-3964	253	6	hybrid	hybrid	ADJ
cana-3964	253	7	optimizat	optimizat	ADJ
cana-3964	253	8	ion	ion	NOUN
cana-3964	253	9	(	(	PUNCT
cana-3964	253	10	bpbrw	bpbrw	NOUN
cana-3964	253	11	with	with	ADP
cana-3964	253	12	hkhabo	hkhabo	NOUN
cana-3964	253	13	)	)	PUNCT
cana-3964	253	14	.996	.996	NUM
cana-3964	253	15	1.0	1.0	NUM
cana-3964	253	16	.999	.999	NUM
cana-3964	253	17	security	security	NOUN
cana-3964	253	18	approach	approach	NOUN
cana-3964	253	19	may	may	AUX
cana-3964	253	20	be	be	AUX
cana-3964	253	21	added	add	VERB
cana-3964	253	22	to	to	PART
cana-3964	253	23	enhance	enhance	VERB
cana-3964	253	24	performance	performance	NOUN
cana-3964	253	25	.	.	PUNCT
cana-3964	254	1	botlagunta	botlagunta	PROPN
cana-3964	254	2	et	et	PROPN
cana-3964	254	3	al	al	PROPN
cana-3964	254	4	.	.	PROPN
cana-3964	255	1	(	(	PUNCT
cana-3964	255	2	2023	2023	NUM
cana-3964	255	3	)	)	PUNCT
cana-3964	256	1	[	[	X
cana-3964	256	2	27	27	NUM
cana-3964	256	3	]	]	X
cana-3964	256	4	clinical	clinical	ADJ
cana-3964	256	5	text	text	NOUN
cana-3964	256	6	data	datum	NOUN
cana-3964	256	7	decision	decision	NOUN
cana-3964	256	8	tree	tree	NOUN
cana-3964	256	9	0.83	0.83	NUM
cana-3964	256	10	0.83	0.83	NUM
cana-3964	256	11	0.86	0.86	NUM
cana-3964	256	12	0.85	0.85	NUM
cana-3964	256	13	various	various	ADJ
cana-3964	256	14	statistical	statistical	ADJ
cana-3964	256	15	methods	method	NOUN
cana-3964	256	16	and	and	CCONJ
cana-3964	256	17	machine	machine	NOUN
cana-3964	256	18	learning	learning	NOUN
cana-3964	256	19	models	model	NOUN
cana-3964	256	20	may	may	AUX
cana-3964	256	21	be	be	AUX
cana-3964	256	22	deployed	deploy	VERB
cana-3964	256	23	.	.	PUNCT
cana-3964	257	1	communications	communication	NOUN
cana-3964	257	2	on	on	ADP
cana-3964	257	3	applied	apply	VERB
cana-3964	257	4	nonlinear	nonlinear	ADJ
cana-3964	257	5	analysis	analysis	NOUN
cana-3964	257	6	issn	issn	NOUN
cana-3964	257	7	:	:	PUNCT
cana-3964	257	8	1074	1074	NUM
cana-3964	257	9	-	-	PUNCT
cana-3964	257	10	133x	133x	NUM
cana-3964	257	11	vol	vol	NOUN
cana-3964	257	12	32	32	NUM
cana-3964	257	13	no	no	NOUN
cana-3964	257	14	.	.	PUNCT
cana-3964	258	1	9s	9s	NUM
cana-3964	258	2	(	(	PUNCT
cana-3964	258	3	2025	2025	NUM
cana-3964	258	4	)	)	PUNCT
cana-3964	258	5	566	566	NUM
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cana-3964	258	7	michael	michael	PROPN
cana-3964	258	8	et	et	PROPN
cana-3964	258	9	al	al	PROPN
cana-3964	258	10	.	.	PROPN
cana-3964	259	1	(	(	PUNCT
cana-3964	259	2	2022	2022	NUM
cana-3964	259	3	)	)	PUNCT
cana-3964	260	1	[	[	X
cana-3964	260	2	21	21	NUM
cana-3964	260	3	]	]	PUNCT
cana-3964	260	4	ultraso	ultraso	NOUN
cana-3964	260	5	und	und	VERB
cana-3964	260	6	images	image	NOUN
cana-3964	260	7	optimize	optimize	NOUN
cana-3964	260	8	d	d	X
cana-3964	260	9	framewor	framewor	X
cana-3964	260	10	k	k	PROPN
cana-3964	260	11	.9986	.9986	PROPN
cana-3964	260	12	1.00	1.00	NUM
cana-3964	260	13	.996	.996	NUM
cana-3964	260	14	.998	.998	NUM
cana-3964	260	15	different	different	ADJ
cana-3964	260	16	dataset	dataset	NOUN
cana-3964	260	17	may	may	AUX
cana-3964	260	18	be	be	AUX
cana-3964	260	19	used	use	VERB
cana-3964	260	20	the	the	DET
cana-3964	260	21	studies	study	NOUN
cana-3964	260	22	encompass	encompass	VERB
cana-3964	260	23	a	a	DET
cana-3964	260	24	range	range	NOUN
cana-3964	260	25	of	of	ADP
cana-3964	260	26	datasets	dataset	NOUN
cana-3964	260	27	,	,	PUNCT
cana-3964	260	28	including	include	VERB
cana-3964	260	29	the	the	DET
cana-3964	260	30	“	"	PUNCT
cana-3964	260	31	wisconsin	wisconsin	PROPN
cana-3964	260	32	breast	breast	NOUN
cana-3964	260	33	cancer	cancer	NOUN
cana-3964	260	34	dataset	dataset	NOUN
cana-3964	260	35	,	,	PUNCT
cana-3964	260	36	"	"	PUNCT
cana-3964	260	37	clinical	clinical	ADJ
cana-3964	260	38	and	and	CCONJ
cana-3964	260	39	pathological	pathological	ADJ
cana-3964	260	40	features	feature	NOUN
cana-3964	260	41	,	,	PUNCT
cana-3964	260	42	mammograms	mammogram	NOUN
cana-3964	260	43	,	,	PUNCT
cana-3964	260	44	thermographic	thermographic	ADJ
cana-3964	260	45	image	image	NOUN
cana-3964	260	46	data	datum	NOUN
cana-3964	260	47	,	,	PUNCT
cana-3964	260	48	and	and	CCONJ
cana-3964	260	49	the	the	DET
cana-3964	260	50	breakhis	breakhis	ADJ
cana-3964	260	51	dataset	dataset	NOUN
cana-3964	260	52	.	.	PUNCT
cana-3964	261	1	the	the	DET
cana-3964	261	2	limitations	limitation	NOUN
cana-3964	261	3	of	of	ADP
cana-3964	261	4	each	each	DET
cana-3964	261	5	study	study	NOUN
cana-3964	261	6	are	be	AUX
cana-3964	261	7	also	also	ADV
cana-3964	261	8	addressed	address	VERB
cana-3964	261	9	in	in	ADP
cana-3964	261	10	this	this	DET
cana-3964	261	11	review	review	NOUN
cana-3964	261	12	paper	paper	NOUN
cana-3964	261	13	.	.	PUNCT
cana-3964	262	1	overall	overall	ADV
cana-3964	262	2	,	,	PUNCT
cana-3964	262	3	the	the	DET
cana-3964	262	4	comparison	comparison	NOUN
cana-3964	262	5	highlights	highlight	VERB
cana-3964	262	6	the	the	DET
cana-3964	262	7	effectiveness	effectiveness	NOUN
cana-3964	262	8	of	of	ADP
cana-3964	262	9	various	various	ADJ
cana-3964	262	10	ml	ml	NOUN
cana-3964	262	11	techniques	technique	NOUN
cana-3964	262	12	in	in	ADP
cana-3964	262	13	bc	bc	PROPN
cana-3964	262	14	across	across	ADP
cana-3964	262	15	different	different	ADJ
cana-3964	262	16	datasets	dataset	NOUN
cana-3964	262	17	.	.	PUNCT
cana-3964	263	1	the	the	DET
cana-3964	263	2	choice	choice	NOUN
cana-3964	263	3	of	of	ADP
cana-3964	263	4	algorithm	algorithm	NOUN
cana-3964	263	5	and	and	CCONJ
cana-3964	263	6	dataset	dataset	VERB
cana-3964	263	7	greatly	greatly	ADV
cana-3964	263	8	affects	affect	VERB
cana-3964	263	9	the	the	DET
cana-3964	263	10	accuracy	accuracy	NOUN
cana-3964	263	11	achieved	achieve	VERB
cana-3964	263	12	and	and	CCONJ
cana-3964	263	13	other	other	ADJ
cana-3964	263	14	metrics	metric	NOUN
cana-3964	263	15	.	.	PUNCT
cana-3964	264	1	fig	fig	NOUN
cana-3964	264	2	.	.	PUNCT
cana-3964	265	1	5	5	NUM
cana-3964	265	2	performance	performance	NOUN
cana-3964	265	3	metrices	metrice	NOUN
cana-3964	265	4	chart	chart	NOUN
cana-3964	265	5	of	of	ADP
cana-3964	265	6	different	different	ADJ
cana-3964	265	7	ml	ml	NOUN
cana-3964	265	8	algorithms	algorithm	NOUN
cana-3964	265	9	on	on	ADP
cana-3964	265	10	wdbc	wdbc	NOUN
cana-3964	265	11	dataset	dataset	VERB
cana-3964	265	12	the	the	DET
cana-3964	265	13	values	value	NOUN
cana-3964	265	14	of	of	ADP
cana-3964	265	15	accuracy	accuracy	NOUN
cana-3964	265	16	,	,	PUNCT
cana-3964	265	17	precision	precision	NOUN
cana-3964	265	18	,	,	PUNCT
cana-3964	265	19	recall	recall	NOUN
cana-3964	265	20	,	,	PUNCT
cana-3964	265	21	and	and	CCONJ
cana-3964	265	22	f1	f1	NOUN
cana-3964	265	23	-	-	PUNCT
cana-3964	265	24	score	score	NOUN
cana-3964	265	25	gained	gain	VERB
cana-3964	265	26	by	by	ADP
cana-3964	265	27	using	use	VERB
cana-3964	265	28	several	several	ADJ
cana-3964	265	29	ml	ml	NOUN
cana-3964	265	30	algorithms	algorithm	NOUN
cana-3964	265	31	on	on	ADP
cana-3964	265	32	the	the	DET
cana-3964	265	33	wdbc	wdbc	NOUN
cana-3964	265	34	dataset	dataset	NOUN
cana-3964	265	35	are	be	AUX
cana-3964	265	36	shown	show	VERB
cana-3964	265	37	in	in	ADP
cana-3964	265	38	fig	fig	NOUN
cana-3964	265	39	.	.	PUNCT
cana-3964	266	1	5	5	X
cana-3964	266	2	.	.	X
cana-3964	266	3	it	it	PRON
cana-3964	266	4	shows	show	VERB
cana-3964	266	5	that	that	SCONJ
cana-3964	266	6	,	,	PUNCT
cana-3964	266	7	when	when	SCONJ
cana-3964	266	8	compared	compare	VERB
cana-3964	266	9	to	to	ADP
cana-3964	266	10	the	the	DET
cana-3964	266	11	other	other	ADJ
cana-3964	266	12	methods	method	NOUN
cana-3964	266	13	,	,	PUNCT
cana-3964	266	14	ensemble	ensemble	ADJ
cana-3964	266	15	have	have	AUX
cana-3964	266	16	done	do	VERB
cana-3964	266	17	the	the	DET
cana-3964	266	18	best	good	ADJ
cana-3964	266	19	and	and	CCONJ
cana-3964	266	20	attained	attain	VERB
cana-3964	266	21	the	the	DET
cana-3964	266	22	maximum	maximum	ADJ
cana-3964	266	23	value	value	NOUN
cana-3964	266	24	[	[	X
cana-3964	266	25	31	31	NUM
cana-3964	266	26	]	]	PUNCT
cana-3964	266	27	.	.	PUNCT
cana-3964	267	1	these	these	DET
cana-3964	267	2	findings	finding	NOUN
cana-3964	267	3	provide	provide	VERB
cana-3964	267	4	valuable	valuable	ADJ
cana-3964	267	5	insights	insight	NOUN
cana-3964	267	6	for	for	ADP
cana-3964	267	7	researchers	researcher	NOUN
cana-3964	267	8	in	in	ADP
cana-3964	267	9	developing	develop	VERB
cana-3964	267	10	improved	improved	ADJ
cana-3964	267	11	and	and	CCONJ
cana-3964	267	12	accurate	accurate	ADJ
cana-3964	267	13	models	model	NOUN
cana-3964	267	14	for	for	ADP
cana-3964	267	15	breast	breast	NOUN
cana-3964	267	16	cancer	cancer	NOUN
cana-3964	267	17	.	.	PUNCT
cana-3964	268	1	5	5	X
cana-3964	268	2	.	.	X
cana-3964	268	3	challenges	challenge	NOUN
cana-3964	268	4	while	while	SCONJ
cana-3964	268	5	the	the	DET
cana-3964	268	6	presented	present	VERB
cana-3964	268	7	studies	study	NOUN
cana-3964	268	8	highlight	highlight	VERB
cana-3964	268	9	significant	significant	ADJ
cana-3964	268	10	achievements	achievement	NOUN
cana-3964	268	11	in	in	ADP
cana-3964	268	12	bc	bc	PROPN
cana-3964	268	13	diagnosis	diagnosis	NOUN
cana-3964	268	14	using	use	VERB
cana-3964	268	15	diverse	diverse	ADJ
cana-3964	268	16	ml	ml	NOUN
cana-3964	268	17	algorithms	algorithm	NOUN
cana-3964	268	18	and	and	CCONJ
cana-3964	268	19	datasets	dataset	NOUN
cana-3964	268	20	,	,	PUNCT
cana-3964	268	21	challenges	challenge	NOUN
cana-3964	268	22	remain	remain	VERB
cana-3964	268	23	.	.	PUNCT
cana-3964	269	1	ensuring	ensure	VERB
cana-3964	269	2	robustness	robustness	NOUN
cana-3964	269	3	across	across	ADP
cana-3964	269	4	various	various	ADJ
cana-3964	269	5	datasets	dataset	NOUN
cana-3964	269	6	,	,	PUNCT
cana-3964	269	7	especially	especially	ADV
cana-3964	269	8	when	when	SCONJ
cana-3964	269	9	dealing	deal	VERB
cana-3964	269	10	with	with	ADP
cana-3964	269	11	distinct	distinct	ADJ
cana-3964	269	12	modalities	modality	NOUN
cana-3964	269	13	like	like	ADP
cana-3964	269	14	mammograms	mammogram	NOUN
cana-3964	269	15	,	,	PUNCT
cana-3964	269	16	ultrasound	ultrasound	NOUN
cana-3964	269	17	images	image	NOUN
cana-3964	269	18	,	,	PUNCT
cana-3964	269	19	and	and	CCONJ
cana-3964	269	20	clinical	clinical	ADJ
cana-3964	269	21	data	datum	NOUN
cana-3964	269	22	,	,	PUNCT
cana-3964	269	23	is	be	AUX
cana-3964	269	24	essential	essential	ADJ
cana-3964	269	25	.	.	PUNCT
cana-3964	270	1	addressing	address	VERB
cana-3964	270	2	imbalanced	imbalanced	ADJ
cana-3964	270	3	datasets	dataset	NOUN
cana-3964	270	4	to	to	PART
cana-3964	270	5	prevent	prevent	VERB
cana-3964	270	6	biased	biased	ADJ
cana-3964	270	7	predictions	prediction	NOUN
cana-3964	270	8	is	be	AUX
cana-3964	270	9	crucial	crucial	ADJ
cana-3964	270	10	for	for	ADP
cana-3964	270	11	clinical	clinical	ADJ
cana-3964	270	12	reliability	reliability	NOUN
cana-3964	270	13	.	.	PUNCT
cana-3964	271	1	future	future	ADJ
cana-3964	271	2	directions	direction	NOUN
cana-3964	271	3	involve	involve	VERB
cana-3964	271	4	integrating	integrate	VERB
cana-3964	271	5	multi	multi	ADJ
cana-3964	271	6	-	-	ADJ
cana-3964	271	7	modal	modal	ADJ
cana-3964	271	8	data	datum	NOUN
cana-3964	271	9	to	to	PART
cana-3964	271	10	enhance	enhance	VERB
cana-3964	271	11	accuracy	accuracy	NOUN
cana-3964	271	12	further	far	ADV
cana-3964	271	13	.	.	PUNCT
cana-3964	272	1	embracing	embrace	VERB
cana-3964	272	2	explainable	explainable	ADJ
cana-3964	272	3	ai	ai	NOUN
cana-3964	272	4	methods	method	NOUN
cana-3964	272	5	will	will	AUX
cana-3964	272	6	bridge	bridge	VERB
cana-3964	272	7	the	the	DET
cana-3964	272	8	gap	gap	NOUN
cana-3964	272	9	between	between	ADP
cana-3964	272	10	complex	complex	ADJ
cana-3964	272	11	models	model	NOUN
cana-3964	272	12	and	and	CCONJ
cana-3964	272	13	clinical	clinical	ADJ
cana-3964	272	14	understanding	understanding	NOUN
cana-3964	272	15	.	.	PUNCT
cana-3964	273	1	additionally	additionally	ADV
cana-3964	273	2	,	,	PUNCT
cana-3964	273	3	advancing	advance	VERB
cana-3964	273	4	privacy	privacy	NOUN
cana-3964	273	5	-	-	PUNCT
cana-3964	273	6	preserving	preserve	VERB
cana-3964	273	7	techniques	technique	NOUN
cana-3964	273	8	and	and	CCONJ
cana-3964	273	9	ensuring	ensure	VERB
cana-3964	273	10	model	model	NOUN
cana-3964	273	11	fairness	fairness	NOUN
cana-3964	273	12	across	across	ADP
cana-3964	273	13	diverse	diverse	ADJ
cana-3964	273	14	patient	patient	NOUN
cana-3964	273	15	groups	group	NOUN
cana-3964	273	16	will	will	AUX
cana-3964	273	17	be	be	AUX
cana-3964	273	18	pivotal	pivotal	ADJ
cana-3964	273	19	.	.	PUNCT
cana-3964	274	1	as	as	SCONJ
cana-3964	274	2	we	we	PRON
cana-3964	274	3	move	move	VERB
cana-3964	274	4	forward	forward	ADV
cana-3964	274	5	,	,	PUNCT
cana-3964	274	6	these	these	DET
cana-3964	274	7	challenges	challenge	NOUN
cana-3964	274	8	and	and	CCONJ
cana-3964	274	9	directions	direction	NOUN
cana-3964	274	10	will	will	AUX
cana-3964	274	11	shape	shape	VERB
cana-3964	274	12	the	the	DET
cana-3964	274	13	evolution	evolution	NOUN
cana-3964	274	14	of	of	ADP
cana-3964	274	15	ml	ml	ADV
cana-3964	274	16	-	-	PUNCT
cana-3964	274	17	driven	drive	VERB
cana-3964	274	18	breast	breast	NOUN
cana-3964	274	19	cancer	cancer	NOUN
cana-3964	274	20	diagnosis	diagnosis	NOUN
cana-3964	274	21	.	.	PUNCT
cana-3964	275	1	a	a	DET
cana-3964	275	2	major	major	ADJ
cana-3964	275	3	issue	issue	NOUN
cana-3964	275	4	in	in	ADP
cana-3964	275	5	using	use	VERB
cana-3964	275	6	machine	machine	NOUN
cana-3964	275	7	learning	learn	VERB
cana-3964	275	8	algorithms	algorithm	NOUN
cana-3964	275	9	for	for	ADP
cana-3964	275	10	diagnosis	diagnosis	NOUN
cana-3964	275	11	of	of	ADP
cana-3964	275	12	diseases	disease	NOUN
cana-3964	275	13	is	be	AUX
cana-3964	275	14	the	the	DET
cana-3964	275	15	availability	availability	NOUN
cana-3964	275	16	of	of	ADP
cana-3964	275	17	appropriate	appropriate	ADJ
cana-3964	275	18	materials	material	NOUN
cana-3964	275	19	,	,	PUNCT
cana-3964	275	20	appropriately	appropriately	ADV
cana-3964	275	21	large	large	ADJ
cana-3964	275	22	and	and	CCONJ
cana-3964	275	23	diverse	diverse	ADJ
cana-3964	275	24	.	.	PUNCT
cana-3964	276	1	[	[	X
cana-3964	276	2	9	9	NUM
cana-3964	276	3	]	]	PUNCT
cana-3964	276	4	and	and	CCONJ
cana-3964	276	5	[	[	X
cana-3964	276	6	5	5	NUM
cana-3964	276	7	]	]	PUNCT
cana-3964	276	8	reported	report	VERB
cana-3964	276	9	maximum	maximum	ADJ
cana-3964	276	10	accuracies	accuracy	NOUN
cana-3964	276	11	of	of	ADP
cana-3964	276	12	95	95	NUM
cana-3964	276	13	.	.	PUNCT
cana-3964	277	1	75	75	NUM
cana-3964	277	2	%	%	NOUN
cana-3964	277	3	and	and	CCONJ
cana-3964	277	4	99	99	NUM
cana-3964	277	5	.	.	NOUN
cana-3964	277	6	5	5	NUM
cana-3964	277	7	%	%	NOUN
cana-3964	277	8	respectively	respectively	ADV
cana-3964	277	9	,	,	PUNCT
cana-3964	277	10	on	on	ADP
cana-3964	277	11	the	the	DET
cana-3964	277	12	wdbc	wdbc	NOUN
cana-3964	277	13	dataset	dataset	NOUN
cana-3964	278	1	but	but	CCONJ
cana-3964	278	2	they	they	PRON
cana-3964	278	3	called	call	VERB
cana-3964	278	4	for	for	ADP
cana-3964	278	5	more	more	ADV
cana-3964	278	6	diverse	diverse	ADJ
cana-3964	278	7	data	datum	NOUN
cana-3964	278	8	and	and	CCONJ
cana-3964	278	9	high	high	ADJ
cana-3964	278	10	computational	computational	ADJ
cana-3964	278	11	costs	cost	NOUN
cana-3964	278	12	.	.	PUNCT
cana-3964	279	1	in	in	ADP
cana-3964	279	2	the	the	DET
cana-3964	279	3	case	case	NOUN
cana-3964	279	4	of	of	ADP
cana-3964	279	5	breakhis	breakhis	NOUN
cana-3964	279	6	,	,	PUNCT
cana-3964	279	7	[	[	X
cana-3964	279	8	25	25	NUM
cana-3964	279	9	]	]	PUNCT
cana-3964	279	10	employed	employ	VERB
cana-3964	279	11	deep	deep	ADJ
cana-3964	279	12	neural	neural	ADJ
cana-3964	279	13	networks	network	NOUN
cana-3964	279	14	with	with	ADP
cana-3964	279	15	high	high	ADJ
cana-3964	279	16	accuracy	accuracy	NOUN
cana-3964	279	17	and	and	CCONJ
cana-3964	279	18	suggested	suggest	VERB
cana-3964	279	19	other	other	ADJ
cana-3964	279	20	diverse	diverse	ADJ
cana-3964	279	21	datasets	dataset	NOUN
cana-3964	279	22	.	.	PUNCT
cana-3964	280	1	communications	communication	NOUN
cana-3964	280	2	on	on	ADP
cana-3964	280	3	applied	apply	VERB
cana-3964	280	4	nonlinear	nonlinear	ADJ
cana-3964	280	5	analysis	analysis	NOUN
cana-3964	280	6	issn	issn	NOUN
cana-3964	280	7	:	:	PUNCT
cana-3964	280	8	1074	1074	NUM
cana-3964	280	9	-	-	PUNCT
cana-3964	280	10	133x	133x	NUM
cana-3964	280	11	vol	vol	NOUN
cana-3964	280	12	32	32	NUM
cana-3964	280	13	no	no	NOUN
cana-3964	280	14	.	.	PUNCT
cana-3964	281	1	9s	9s	NUM
cana-3964	281	2	(	(	PUNCT
cana-3964	281	3	2025	2025	NUM
cana-3964	281	4	)	)	PUNCT
cana-3964	281	5	567	567	NUM
cana-3964	281	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3964	281	7	6	6	NUM
cana-3964	281	8	.	.	PUNCT
cana-3964	281	9	conclusion	conclusion	NOUN
cana-3964	281	10	&	&	CCONJ
cana-3964	281	11	future	future	ADJ
cana-3964	281	12	scope	scope	NOUN
cana-3964	281	13	this	this	DET
cana-3964	281	14	paper	paper	NOUN
cana-3964	281	15	assesses	assesse	NOUN
cana-3964	281	16	and	and	CCONJ
cana-3964	281	17	contrasts	contrast	VERB
cana-3964	281	18	the	the	DET
cana-3964	281	19	worth	worth	NOUN
cana-3964	281	20	of	of	ADP
cana-3964	281	21	ml	ml	ADP
cana-3964	281	22	algorithms	algorithm	NOUN
cana-3964	281	23	,	,	PUNCT
cana-3964	281	24	including	include	VERB
cana-3964	281	25	svm	svm	PROPN
cana-3964	281	26	,	,	PUNCT
cana-3964	281	27	knn	knn	PROPN
cana-3964	281	28	,	,	PUNCT
cana-3964	281	29	rf	rf	PROPN
cana-3964	281	30	,	,	PUNCT
cana-3964	281	31	dt	dt	PROPN
cana-3964	281	32	,	,	PUNCT
cana-3964	281	33	pca	pca	PROPN
cana-3964	281	34	,	,	PUNCT
cana-3964	281	35	lr	lr	NOUN
cana-3964	281	36	,	,	PUNCT
cana-3964	281	37	elm	elm	PROPN
cana-3964	281	38	,	,	PUNCT
cana-3964	281	39	ann	ann	PROPN
cana-3964	281	40	,	,	PUNCT
cana-3964	281	41	mlp	mlp	PROPN
cana-3964	281	42	,	,	PUNCT
cana-3964	281	43	xgboost	xgboost	ADV
cana-3964	281	44	,	,	PUNCT
cana-3964	281	45	and	and	CCONJ
cana-3964	281	46	dl	dl	X
cana-3964	281	47	,	,	PUNCT
cana-3964	281	48	as	as	SCONJ
cana-3964	281	49	employed	employ	VERB
cana-3964	281	50	by	by	ADP
cana-3964	281	51	different	different	ADJ
cana-3964	281	52	researchers	researcher	NOUN
cana-3964	281	53	in	in	ADP
cana-3964	281	54	their	their	PRON
cana-3964	281	55	studies	study	NOUN
cana-3964	281	56	.	.	PUNCT
cana-3964	282	1	according	accord	VERB
cana-3964	282	2	to	to	ADP
cana-3964	282	3	the	the	DET
cana-3964	282	4	analysis	analysis	NOUN
cana-3964	282	5	of	of	ADP
cana-3964	282	6	various	various	ADJ
cana-3964	282	7	author	author	NOUN
cana-3964	282	8	’s	’s	PART
cana-3964	282	9	works	work	NOUN
cana-3964	282	10	among	among	ADP
cana-3964	282	11	those	those	PRON
cana-3964	282	12	who	who	PRON
cana-3964	282	13	diagnose	diagnose	VERB
cana-3964	282	14	breast	breast	NOUN
cana-3964	282	15	cancer	cancer	NOUN
cana-3964	282	16	,	,	PUNCT
cana-3964	282	17	ml	ml	ADP
cana-3964	282	18	algorithms	algorithm	NOUN
cana-3964	282	19	have	have	AUX
cana-3964	282	20	shown	show	VERB
cana-3964	282	21	tremendous	tremendous	ADJ
cana-3964	282	22	promise	promise	NOUN
cana-3964	282	23	in	in	ADP
cana-3964	282	24	terms	term	NOUN
cana-3964	282	25	of	of	ADP
cana-3964	282	26	producing	produce	VERB
cana-3964	282	27	accurate	accurate	ADJ
cana-3964	282	28	and	and	CCONJ
cana-3964	282	29	dependable	dependable	ADJ
cana-3964	282	30	outcomes	outcome	NOUN
cana-3964	282	31	.	.	PUNCT
cana-3964	283	1	to	to	PART
cana-3964	283	2	build	build	VERB
cana-3964	283	3	predictive	predictive	ADJ
cana-3964	283	4	models	model	NOUN
cana-3964	283	5	for	for	ADP
cana-3964	283	6	breast	breast	NOUN
cana-3964	283	7	cancer	cancer	NOUN
cana-3964	283	8	diagnosis	diagnosis	NOUN
cana-3964	283	9	,	,	PUNCT
cana-3964	283	10	many	many	ADJ
cana-3964	283	11	methods	method	NOUN
cana-3964	283	12	such	such	ADJ
cana-3964	283	13	as	as	ADP
cana-3964	283	14	svm	svm	ADJ
cana-3964	283	15	,	,	PUNCT
cana-3964	283	16	dt	dt	X
cana-3964	283	17	,	,	PUNCT
cana-3964	283	18	rf	rf	PROPN
cana-3964	283	19	,	,	PUNCT
cana-3964	283	20	mlp	mlp	PROPN
cana-3964	283	21	,	,	PUNCT
cana-3964	283	22	ann	ann	PROPN
cana-3964	283	23	,	,	PUNCT
cana-3964	283	24	deep	deep	ADJ
cana-3964	283	25	learning	learning	NOUN
cana-3964	283	26	,	,	PUNCT
cana-3964	283	27	and	and	CCONJ
cana-3964	283	28	an	an	DET
cana-3964	283	29	optimized	optimize	VERB
cana-3964	283	30	framework	framework	NOUN
cana-3964	283	31	have	have	AUX
cana-3964	283	32	been	be	AUX
cana-3964	283	33	used	use	VERB
cana-3964	283	34	.	.	PUNCT
cana-3964	284	1	the	the	DET
cana-3964	284	2	reported	report	VERB
cana-3964	284	3	accuracies	accuracy	NOUN
cana-3964	284	4	range	range	VERB
cana-3964	284	5	from	from	ADP
cana-3964	284	6	.9561	.9561	PROPN
cana-3964	284	7	to	to	ADP
cana-3964	284	8	.993	.993	NUM
cana-3964	284	9	on	on	ADP
cana-3964	284	10	the	the	DET
cana-3964	284	11	wdbc	wdbc	NOUN
cana-3964	284	12	dataset	dataset	NOUN
cana-3964	284	13	,	,	PUNCT
cana-3964	284	14	indicating	indicate	VERB
cana-3964	284	15	the	the	DET
cana-3964	284	16	effectiveness	effectiveness	NOUN
cana-3964	284	17	of	of	ADP
cana-3964	284	18	these	these	DET
cana-3964	284	19	models	model	NOUN
cana-3964	284	20	in	in	ADP
cana-3964	284	21	distinguishing	distinguish	VERB
cana-3964	284	22	between	between	ADP
cana-3964	284	23	malignant	malignant	ADJ
cana-3964	284	24	and	and	CCONJ
cana-3964	284	25	benign	benign	ADJ
cana-3964	284	26	cases	case	NOUN
cana-3964	284	27	.	.	PUNCT
cana-3964	285	1	in	in	ADP
cana-3964	285	2	conclusion	conclusion	NOUN
cana-3964	285	3	,	,	PUNCT
cana-3964	285	4	the	the	DET
cana-3964	285	5	analysis	analysis	NOUN
cana-3964	285	6	of	of	ADP
cana-3964	285	7	existing	exist	VERB
cana-3964	285	8	works	work	NOUN
cana-3964	285	9	highlights	highlight	VERB
cana-3964	285	10	the	the	DET
cana-3964	285	11	potential	potential	NOUN
cana-3964	285	12	of	of	ADP
cana-3964	285	13	ml	ml	ADP
cana-3964	285	14	techniques	technique	NOUN
cana-3964	285	15	in	in	ADP
cana-3964	285	16	breast	breast	NOUN
cana-3964	285	17	cancer	cancer	NOUN
cana-3964	285	18	diagnosis	diagnosis	NOUN
cana-3964	285	19	.	.	PUNCT
cana-3964	286	1	it	it	PRON
cana-3964	286	2	is	be	AUX
cana-3964	286	3	observed	observe	VERB
cana-3964	286	4	that	that	SCONJ
cana-3964	286	5	ensemble	ensemble	ADJ
cana-3964	286	6	method	method	NOUN
cana-3964	286	7	obtains	obtain	VERB
cana-3964	286	8	the	the	DET
cana-3964	286	9	best	good	ADJ
cana-3964	286	10	performance	performance	NOUN
cana-3964	286	11	with	with	ADP
cana-3964	286	12	the	the	DET
cana-3964	286	13	highest	high	ADJ
cana-3964	286	14	accuracy	accuracy	NOUN
cana-3964	286	15	on	on	ADP
cana-3964	286	16	the	the	DET
cana-3964	286	17	wdbc	wdbc	NOUN
cana-3964	286	18	dataset	dataset	NOUN
cana-3964	286	19	and	and	CCONJ
cana-3964	286	20	an	an	DET
cana-3964	286	21	optimized	optimize	VERB
cana-3964	286	22	framework	framework	NOUN
cana-3964	286	23	on	on	ADP
cana-3964	286	24	thermographic	thermographic	ADJ
cana-3964	286	25	images	image	NOUN
cana-3964	286	26	.	.	PUNCT
cana-3964	287	1	comparative	comparative	ADJ
cana-3964	287	2	analysis	analysis	NOUN
cana-3964	287	3	shows	show	VERB
cana-3964	287	4	that	that	SCONJ
cana-3964	287	5	the	the	DET
cana-3964	287	6	ensemble	ensemble	ADJ
cana-3964	287	7	learning	learning	NOUN
cana-3964	287	8	outperformed	outperform	VERB
cana-3964	287	9	,	,	PUNCT
cana-3964	287	10	and	and	CCONJ
cana-3964	287	11	their	their	PRON
cana-3964	287	12	accuracy	accuracy	NOUN
cana-3964	287	13	,	,	PUNCT
cana-3964	287	14	precision	precision	NOUN
cana-3964	287	15	,	,	PUNCT
cana-3964	287	16	recall	recall	NOUN
cana-3964	287	17	,	,	PUNCT
cana-3964	287	18	and	and	CCONJ
cana-3964	287	19	f1	f1	NOUN
cana-3964	287	20	-	-	PUNCT
cana-3964	287	21	score	score	NOUN
cana-3964	287	22	are	be	AUX
cana-3964	287	23	.993	.993	NUM
cana-3964	287	24	,	,	PUNCT
cana-3964	287	25	1.00	1.00	NUM
cana-3964	287	26	,	,	PUNCT
cana-3964	287	27	.9777	.9777	PROPN
cana-3964	287	28	,	,	PUNCT
cana-3964	287	29	and	and	CCONJ
cana-3964	287	30	.9887	.9887	PROPN
cana-3964	287	31	,	,	PUNCT
cana-3964	287	32	respectively	respectively	ADV
cana-3964	287	33	.	.	PUNCT
cana-3964	288	1	the	the	DET
cana-3964	288	2	future	future	ADJ
cana-3964	288	3	scope	scope	NOUN
cana-3964	288	4	lies	lie	VERB
cana-3964	288	5	in	in	ADP
cana-3964	288	6	addressing	address	VERB
cana-3964	288	7	the	the	DET
cana-3964	288	8	aforementioned	aforementioned	ADJ
cana-3964	288	9	areas	area	NOUN
cana-3964	288	10	of	of	ADP
cana-3964	288	11	improvement	improvement	NOUN
cana-3964	288	12	to	to	PART
cana-3964	288	13	boost	boost	VERB
cana-3964	288	14	the	the	DET
cana-3964	288	15	accuracy	accuracy	NOUN
cana-3964	288	16	,	,	PUNCT
cana-3964	288	17	sensitivity	sensitivity	NOUN
cana-3964	288	18	,	,	PUNCT
cana-3964	288	19	and	and	CCONJ
cana-3964	288	20	specificity	specificity	NOUN
cana-3964	288	21	of	of	ADP
cana-3964	288	22	these	these	DET
cana-3964	288	23	models	model	NOUN
cana-3964	288	24	on	on	ADP
cana-3964	288	25	different	different	ADJ
cana-3964	288	26	datasets	dataset	NOUN
cana-3964	288	27	,	,	PUNCT
cana-3964	288	28	ultimately	ultimately	ADV
cana-3964	288	29	contributing	contribute	VERB
cana-3964	288	30	to	to	ADP
cana-3964	288	31	more	more	ADV
cana-3964	288	32	effective	effective	ADJ
cana-3964	288	33	breast	breast	NOUN
cana-3964	288	34	cancer	cancer	NOUN
cana-3964	288	35	management	management	NOUN
cana-3964	288	36	and	and	CCONJ
cana-3964	288	37	improved	improve	VERB
cana-3964	288	38	patient	patient	ADJ
cana-3964	288	39	outcomes	outcome	NOUN
cana-3964	288	40	.	.	PUNCT
cana-3964	289	1	data	datum	NOUN
cana-3964	289	2	availability	availability	NOUN
cana-3964	289	3	statement	statement	NOUN
cana-3964	289	4	data	datum	NOUN
cana-3964	289	5	sharing	share	VERB
cana-3964	289	6	not	not	PART
cana-3964	289	7	applicable	applicable	ADJ
cana-3964	289	8	to	to	ADP
cana-3964	289	9	this	this	DET
cana-3964	289	10	article	article	NOUN
cana-3964	289	11	as	as	SCONJ
cana-3964	289	12	no	no	DET
cana-3964	289	13	datasets	dataset	NOUN
cana-3964	289	14	were	be	AUX
cana-3964	289	15	generated	generate	VERB
cana-3964	289	16	or	or	CCONJ
cana-3964	289	17	analysed	analyse	VERB
cana-3964	289	18	during	during	ADP
cana-3964	289	19	the	the	DET
cana-3964	289	20	current	current	ADJ
cana-3964	289	21	study	study	NOUN
cana-3964	289	22	.	.	PUNCT
cana-3964	290	1	conflicts	conflict	NOUN
cana-3964	290	2	of	of	ADP
cana-3964	290	3	interest	interest	NOUN
cana-3964	290	4	:	:	PUNCT
cana-3964	290	5	the	the	DET
cana-3964	290	6	authors	author	NOUN
cana-3964	290	7	declare	declare	VERB
cana-3964	290	8	that	that	SCONJ
cana-3964	290	9	there	there	PRON
cana-3964	290	10	is	be	VERB
cana-3964	290	11	no	no	DET
cana-3964	290	12	conflict	conflict	NOUN
cana-3964	290	13	of	of	ADP
cana-3964	290	14	interest	interest	NOUN
cana-3964	290	15	.	.	PUNCT
cana-3964	291	1	references	reference	NOUN
cana-3964	291	2	[	[	X
cana-3964	291	3	1	1	X
cana-3964	291	4	]	]	PUNCT
cana-3964	291	5	who	who	PRON
cana-3964	291	6	launches	launch	VERB
cana-3964	291	7	new	new	ADJ
cana-3964	291	8	roadmap	roadmap	NOUN
cana-3964	291	9	on	on	ADP
cana-3964	291	10	breast	breast	NOUN
cana-3964	291	11	cancer	cancer	NOUN
cana-3964	291	12	.	.	PUNCT
cana-3964	292	1	(	(	PUNCT
cana-3964	292	2	2023	2023	NUM
cana-3964	292	3	,	,	PUNCT
cana-3964	292	4	february	february	PROPN
cana-3964	292	5	3	3	NUM
cana-3964	292	6	)	)	PUNCT
cana-3964	292	7	.	.	PUNCT
cana-3964	293	1	retrieved	retrieve	VERB
cana-3964	293	2	from	from	ADP
cana-3964	293	3	https://www.who.int/news/item/03-02-2023-who-launches-new-roadmap-on-breast-cancer	https://www.who.int/news/item/03-02-2023-who-launches-new-roadmap-on-breast-cancer	X
cana-3964	293	4	.	.	PUNCT
cana-3964	294	1	[	[	X
cana-3964	294	2	2	2	NUM
cana-3964	294	3	]	]	X
cana-3964	294	4	asri	asri	PROPN
cana-3964	294	5	,	,	PUNCT
cana-3964	294	6	h.	h.	PROPN
cana-3964	294	7	,	,	PUNCT
cana-3964	294	8	mousannif	mousannif	PROPN
cana-3964	294	9	,	,	PUNCT
cana-3964	294	10	h.	h.	PROPN
cana-3964	294	11	,	,	PUNCT
cana-3964	294	12	al	al	PROPN
cana-3964	294	13	moatassime	moatassime	PROPN
cana-3964	294	14	,	,	PUNCT
cana-3964	294	15	h.	h.	PROPN
cana-3964	294	16	,	,	PUNCT
cana-3964	294	17	&	&	CCONJ
cana-3964	294	18	noel	noel	PROPN
cana-3964	294	19	,	,	PUNCT
cana-3964	294	20	t.	t.	PROPN
cana-3964	294	21	(	(	PUNCT
cana-3964	294	22	2016	2016	NUM
cana-3964	294	23	)	)	PUNCT
cana-3964	294	24	.	.	PUNCT
cana-3964	295	1	using	use	VERB
cana-3964	295	2	machine	machine	NOUN
cana-3964	295	3	learning	learn	VERB
cana-3964	295	4	algorithms	algorithm	NOUN
cana-3964	295	5	for	for	ADP
cana-3964	295	6	breast	breast	NOUN
cana-3964	295	7	cancer	cancer	NOUN
cana-3964	295	8	risk	risk	NOUN
cana-3964	295	9	prediction	prediction	NOUN
cana-3964	295	10	and	and	CCONJ
cana-3964	295	11	diagnosis	diagnosis	NOUN
cana-3964	295	12	.	.	PUNCT
cana-3964	296	1	procedia	procedia	NOUN
cana-3964	296	2	computer	computer	NOUN
cana-3964	296	3	science	science	NOUN
cana-3964	296	4	,	,	PUNCT
cana-3964	296	5	83	83	NUM
cana-3964	296	6	,	,	PUNCT
cana-3964	296	7	1064	1064	NUM
cana-3964	296	8	-	-	SYM
cana-3964	296	9	1069	1069	NUM
cana-3964	296	10	.	.	PUNCT
cana-3964	297	1	[	[	X
cana-3964	297	2	3	3	NUM
cana-3964	297	3	]	]	X
cana-3964	297	4	rathi	rathi	NOUN
cana-3964	297	5	,	,	PUNCT
cana-3964	297	6	m.	m.	NOUN
cana-3964	297	7	,	,	PUNCT
cana-3964	297	8	&	&	CCONJ
cana-3964	297	9	pareek	pareek	PROPN
cana-3964	297	10	,	,	PUNCT
cana-3964	297	11	v.	v.	PROPN
cana-3964	297	12	(	(	PUNCT
cana-3964	297	13	2016	2016	NUM
cana-3964	297	14	)	)	PUNCT
cana-3964	297	15	.	.	PUNCT
cana-3964	298	1	hybrid	hybrid	ADJ
cana-3964	298	2	approach	approach	NOUN
cana-3964	298	3	to	to	PART
cana-3964	298	4	predict	predict	VERB
cana-3964	298	5	breast	breast	NOUN
cana-3964	298	6	cancer	cancer	NOUN
cana-3964	298	7	using	use	VERB
cana-3964	298	8	machine	machine	NOUN
cana-3964	298	9	learning	learn	VERB
cana-3964	298	10	techniques	technique	NOUN
cana-3964	298	11	.	.	PUNCT
cana-3964	299	1	international	international	ADJ
cana-3964	299	2	journal	journal	NOUN
cana-3964	299	3	of	of	ADP
cana-3964	299	4	computer	computer	NOUN
cana-3964	299	5	science	science	NOUN
cana-3964	299	6	and	and	CCONJ
cana-3964	299	7	engineering	engineering	NOUN
cana-3964	299	8	,	,	PUNCT
cana-3964	299	9	5(3	5(3	NUM
cana-3964	299	10	)	)	PUNCT
cana-3964	299	11	,	,	PUNCT
cana-3964	299	12	125	125	NUM
cana-3964	299	13	-	-	SYM
cana-3964	299	14	136	136	NUM
cana-3964	299	15	.	.	PUNCT
cana-3964	300	1	[	[	X
cana-3964	300	2	4	4	NUM
cana-3964	300	3	]	]	X
cana-3964	300	4	bejnordi	bejnordi	PROPN
cana-3964	300	5	,	,	PUNCT
cana-3964	300	6	b.	b.	PROPN
cana-3964	300	7	e.	e.	PROPN
cana-3964	300	8	,	,	PUNCT
cana-3964	300	9	veta	veta	PROPN
cana-3964	300	10	,	,	PUNCT
cana-3964	300	11	m.	m.	NOUN
cana-3964	300	12	,	,	PUNCT
cana-3964	300	13	van	van	PROPN
cana-3964	300	14	diest	diest	NOUN
cana-3964	300	15	,	,	PUNCT
cana-3964	300	16	p.	p.	PROPN
cana-3964	300	17	j.	j.	PROPN
cana-3964	300	18	,	,	PUNCT
cana-3964	300	19	van	van	PROPN
cana-3964	300	20	ginneken	ginneken	PROPN
cana-3964	300	21	,	,	PUNCT
cana-3964	300	22	b.	b.	PROPN
cana-3964	300	23	,	,	PUNCT
cana-3964	300	24	karssemeijer	karssemeijer	PROPN
cana-3964	300	25	,	,	PUNCT
cana-3964	300	26	n.	n.	NOUN
cana-3964	300	27	,	,	PUNCT
cana-3964	300	28	litjens	litjen	NOUN
cana-3964	300	29	,	,	PUNCT
cana-3964	300	30	g.	g.	PROPN
cana-3964	300	31	,	,	PUNCT
cana-3964	300	32	...	...	PUNCT
cana-3964	300	33	geessink	geessink	NOUN
cana-3964	300	34	,	,	PUNCT
cana-3964	300	35	g.	g.	PROPN
cana-3964	300	36	(	(	PUNCT
cana-3964	300	37	2017	2017	NUM
cana-3964	300	38	)	)	PUNCT
cana-3964	300	39	.	.	PUNCT
cana-3964	301	1	diagnostic	diagnostic	ADJ
cana-3964	301	2	assessment	assessment	NOUN
cana-3964	301	3	of	of	ADP
cana-3964	301	4	deep	deep	ADJ
cana-3964	301	5	learning	learning	NOUN
cana-3964	301	6	algorithms	algorithm	NOUN
cana-3964	301	7	for	for	ADP
cana-3964	301	8	detection	detection	NOUN
cana-3964	301	9	of	of	ADP
cana-3964	301	10	lymph	lymph	NOUN
cana-3964	301	11	node	node	NOUN
cana-3964	301	12	metastases	metastasis	NOUN
cana-3964	301	13	in	in	ADP
cana-3964	301	14	women	woman	NOUN
cana-3964	301	15	with	with	ADP
cana-3964	301	16	breast	breast	NOUN
cana-3964	301	17	cancer	cancer	NOUN
cana-3964	301	18	.	.	PUNCT
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cana-3964	302	4	)	)	PUNCT
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cana-3964	303	2	5	5	NUM
cana-3964	303	3	]	]	PUNCT
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cana-3964	305	2	proceedings	proceeding	NOUN
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cana-3964	305	5	2nd	2nd	ADJ
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cana-3964	305	16	.	.	PUNCT
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cana-3964	306	2	-	-	SYM
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cana-3964	307	22	)	)	PUNCT
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cana-3964	308	7	.	.	PUNCT
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cana-3964	309	2	2018	2018	NUM
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cana-3964	309	5	,	,	PUNCT
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cana-3964	309	8	,	,	PUNCT
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cana-3964	309	11	'	'	PART
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cana-3964	309	13	(	(	PUNCT
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cana-3964	309	15	)	)	PUNCT
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cana-3964	310	2	-	-	SYM
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cana-3964	310	4	)	)	PUNCT
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cana-3964	311	2	7	7	NUM
cana-3964	311	3	]	]	SYM
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cana-3964	311	5	,	,	PUNCT
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cana-3964	311	9	,	,	PUNCT
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cana-3964	312	5	cancer	cancer	NOUN
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cana-3964	312	10	.	.	PUNCT
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cana-3964	313	17	,	,	PUNCT
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cana-3964	313	19	-	-	SYM
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cana-3964	313	21	.	.	PUNCT
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cana-3964	314	22	,	,	PUNCT
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cana-3964	314	26	)	)	PUNCT
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cana-3964	318	8	)	)	PUNCT
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cana-3964	318	11	-	-	SYM
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cana-3964	321	20	)	)	PUNCT
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cana-3964	325	11	in	in	ADP
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cana-3964	327	2	-	-	SYM
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cana-3964	328	2	12	12	NUM
cana-3964	328	3	]	]	X
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cana-3964	328	14	)	)	PUNCT
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cana-3964	350	8	)	)	PUNCT
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