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. © 2010 Springer-Verlag.
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CITATION STYLE
Yi, X., Wu, P., Li, J., & Liu, L. (2010). Breast cancer diagnosis using WNN based on GA. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6330 LNBI, pp. 367–374). https://doi.org/10.1007/978-3-642-15615-1_44
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