Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm
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...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2010
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| Online Access: | http://hdl.handle.net/20.500.11937/3481 |
| _version_ | 1848744244007665664 |
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| author | Chan, Kit Yan Zhu, H. Lau, C. Dillon, Tharam S. Ling, S. |
| author2 | Gary Fogel |
| author_facet | Gary Fogel Chan, Kit Yan Zhu, H. Lau, C. Dillon, Tharam S. Ling, S. |
| author_sort | Chan, Kit Yan |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T05:58:23Z |
| format | Conference Paper |
| id | curtin-20.500.11937-3481 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T05:58:23Z |
| publishDate | 2010 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-34812017-09-13T16:04:15Z Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm Chan, Kit Yan Zhu, H. Lau, C. Dillon, Tharam S. Ling, S. Gary Fogel 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 Conference Paper http://hdl.handle.net/20.500.11937/3481 10.1109/CEC.2010.5586308 IEEE fulltext |
| spellingShingle | Chan, Kit Yan Zhu, H. Lau, C. Dillon, Tharam S. Ling, S. Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm |
| title | Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm |
| title_full | Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm |
| title_fullStr | Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm |
| title_full_unstemmed | Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm |
| title_short | Determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm |
| title_sort | determination of chemo-responses for osteosarcoma using a hybrid evolutionary algorithm |
| url | http://hdl.handle.net/20.500.11937/3481 |