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

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Open access
Authors
Chan, Kit Yan
Zhu, H.
Lau, C.
Dillon, Tharam S.
Ling, S.
Date
2010
Collection
Type
Conference Paper
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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.

Citation
Chan, Kit Yan and Zhu, Hailong and Lau, Ching and Dillon, Tharam S. and Ling, Sai Ho. 2010. Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm, in Fogel, G. (ed), IEEE Congress on Evolutionary Computation (CEC 2010), Jul 18 2010, pp. 1-5. Barcelona, Spain: IEEE.
Source Title
Proceedings of the IEEE congress on evolutionary computation (CEC 2010)
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DOI
Department
Digital Ecosystems and Business Intelligence Institute (DEBII)
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