Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm

Chan, KY; Zhu, H; Lau, C; Dillon, TS; Ling, SH

Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm

Chan, KY Zhu, H Lau, C Dillon, TS Ling, SH

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Publication Type:: Conference Proceeding
Citation:: 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, 2010
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Chan, KY	en_US
dc.contributor.author	Zhu, H	en_US
dc.contributor.author	Lau, C	en_US
dc.contributor.author	Dillon, TS	en_US
dc.contributor.author	Ling, SH https://orcid.org/0000-0003-0849-5098	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, 2010	en_US
dc.identifier.isbn	9781424469109	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16202
dc.description.abstract	In this paper, a hybrid evolutionary algorithm (HEA) based on the approaches of the evolutionary algorithm and a local search (LS) is proposed to determine the gene signatures for predicting histologic response of chemotherapy on osteosarcoma patients, which is one of the most common malignant bone tumor in children. The HEA consists of a population of individuals but the evolution of individuals is conducted by a LS, rather than the crossover and mutation used in the traditional evolutionary algorithms. The proposed HEA can simultaneously optimize the feature subset and the classifier through a common solution coding mechanism. Experimental results indicate that HEA can obtain more accurate signatures than the other existing approaches in determining chemoresponse for osteosarcoma. © 2010 IEEE.	en_US
dc.relation.ispartof	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010	en_US
dc.relation.isbasedon	10.1109/CEC.2010.5586308	en_US
dc.title	Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Barcelona, Spain	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 Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

In this paper, a hybrid evolutionary algorithm (HEA) based on the approaches of the evolutionary algorithm and a local search (LS) is proposed to determine the gene signatures for predicting histologic response of chemotherapy on osteosarcoma patients, which is one of the most common malignant bone tumor in children. The HEA consists of a population of individuals but the evolution of individuals is conducted by a LS, rather than the crossover and mutation used in the traditional evolutionary algorithms. The proposed HEA can simultaneously optimize the feature subset and the classifier through a common solution coding mechanism. Experimental results indicate that HEA can obtain more accurate signatures than the other existing approaches in determining chemoresponse for osteosarcoma. © 2010 IEEE.

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