Abstract: Medical diagnosis is one of the major problems in medical application. This includes the limitation of human expertise to diagnose disease manually. Extensive amount of knowledge and data stored in medical databases require specialized tools for analysis and effective usage of data. Breast cancer is one of the most common types of cancer in women in many countries. An intelligent tool, which will help in diagnosing the breast cancer, is the need of the hour. Researchers have found that Neural Network (NN) capabilities can help them to improve this domain and the use of Genetic Algorithms (GA) to optimize the input space. As many researchers have discovered, NNs and GAs may be combined which will result in highly successful adaptive systems. The performance of genetic algorithms and Adaptive Resonance Theory (ART) neural network for increasing the accuracy and objectivity of breast cancer diagnosis using the well-known and widely accepted Wisconsin Breast Cancer Data (WBCD) is examined in this study.
Punitha, C.P. Sumathi and T. Santhanam , 2007. A Combination of Genetic Algorithm and ART Neural Network for Breast Cancer Diagnosis. Asian Journal of Information Technology, 6: 112-117.