Breast cancer diagnosis using WNN based on GA

Authors:
Xiaomei Yi;Peng Wu;Jian Li;Lijuan Liu
Affiliations:
Department of Information Engineering, ZheJiang Agricultural & Forestry University, Hangzhou, China;Department of Information Engineering, ZheJiang Agricultural & Forestry University, Hangzhou, China;Department of Information Engineering, ZheJiang Agricultural & Forestry University, Hangzhou, China;Department of Information Engineering, ZheJiang Agricultural & Forestry University, Hangzhou, China
Venue:
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Year:
2010

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Abstract

Breast cancer diagnosis is an important field of medical research. In order to improve the accuracy of diagnosis, this article proposed a model of breast cancer diagnosis with wavelet neural network (WNN) based on genetic algorithm (GA). In this model, wavelet is used as the excitation function of the neural network, and genetic algorithm is used to optimize the weight of neural network. On the basis of it the WNN-GA implements learning step and built the WNN-GA model of breast cancer diagnosis. The result of the experiment shows that this algorithm can be used in breast cancer diagnosis effective and reliable.