Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm
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Copyright © 2010 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
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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.
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