BREAST CANCER DIAGNOSIS USING STATISTICAL NEURAL NETWORKS

Abstract

Breast cancer is the second largest cause of cancer deaths among women. The performance of the statistical neural network structures, radial basis network (RBF), general regression neural network (GRNN) and probabilistic neural network (PNN) are examined on the Wisconsin breast cancer data (WBCD) in this paper. This is a well-used database in machine learning, neural network and signal processing. Statistical neural networks are used to increase the accuracy and objectivity of breast cancer diagnosis.