Computerized Breast Cancer Diagnosis with Genetic Algorithms and Neural Network

Breast cancer has become a common mortality factor in Malaysia. Despite the fact, not all general hospitals have the mammogram facilities. The long waiting for diagnosing a breast cancer may increase the possibility of fatality and the cancer spreading. Therefore a computerized breast cancer diagnosis prototype has been developed to reduce the time taken and indirectly reducing the probability of death. As Back Propagation Neural Network(BPNN) are commonly used in medical field[9], the prototype model will use this method as a classifier as well. However, BPNN has several issue and weakness to be address. Therefore, the architecture will be enhanced with Genetic Algorithm(GA) technology. By combining the GA and BPNN, a faster classifier model can be developed, without downgrading the classification performance. The development of this model, namely GAwNN; is aimed to reduce the diagnosis time as well as increasing the accuracy percentage in classifying mass in breast to either benign, or malignant.