A New Hybrid Approach For Mining Breast Cancer Pattern Using Discrete Particle Swarm Optimization And Statistical Method

Yeh, W; Chang, W; Chung, YY

A New Hybrid Approach For Mining Breast Cancer Pattern Using Discrete Particle Swarm Optimization And Statistical Method

Yeh, W Chang, W Chung, YY

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Publisher:: Pergamon-Elsevier Science Ltd
Publication Type:: Journal Article
Citation:: Expert Systems With Applications, 2009, 36 (4), pp. 8204 - 8211
Issue Date:: 2009-01

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Full metadata record

Field	Value	Language
dc.contributor.author	Yeh, W	en_US
dc.contributor.author	Chang, W	en_US
dc.contributor.author	Chung, YY	en_US
dc.date.issued	2009-01	en_US
dc.identifier.citation	Expert Systems With Applications, 2009, 36 (4), pp. 8204 - 8211	en_US
dc.identifier.issn	0957-4174	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14540
dc.description.abstract	Breast cancer is one of the leading causes of death among the women in many parts of the world. In 2007, approximately 178,480 women in the United States have been found to have invasive breast cancer. In this paper, we have developed an efficient hybrid	en_US
dc.publisher	Pergamon-Elsevier Science Ltd	en_US
dc.relation.ispartof	Expert Systems With Applications	en_US
dc.relation.isbasedon	10.1016/j.eswa.2008.10.004	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A New Hybrid Approach For Mining Breast Cancer Pattern Using Discrete Particle Swarm Optimization And Statistical Method	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	36	en_US
utslib.location.activity	ISI:000264528600103	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
dc.location.activity	ISI:000264528600103	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.issue	4	en_US
pubs.volume	36	en_US

Abstract:

Breast cancer is one of the leading causes of death among the women in many parts of the world. In 2007, approximately 178,480 women in the United States have been found to have invasive breast cancer. In this paper, we have developed an efficient hybrid

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http://hdl.handle.net/10453/14540