BREAST CANCER DIAGNOSIS BY ARTIFICIAL NEURAL NETWORKS (ANN’S)

Abstract

Breast cancer is the second largest cause of cancer deaths among women. This project aim for early diagnosis of breast cancer and reduce the human diagnosis errorsthrough (ANN’s). Here we canstudy the performance of different Neural Network structures: Radial Basis Function(RBF), General Regression Neural Network (GRNN)and Back propagation NeuralNetwork(BPNN), are examined on the Wisconsin Breast Cancer Data (WBCD).The result demonstrated that; the BPNN is the best classification accuracy.