Breast cancer diagnosis using Artificial Neural Network models

Breast cancer is the second leading cause of cancer deaths worldwide and occurrs in one out of eight women. In this paper we develop a system for diagnosis, prognosis and prediction of breast cancer using Artificial Neural Network (ANN) models. This will assist the doctors in diagnosis of the disease. We implement four models of neural networks namely Back Propagation Algorithm, Radial Basis Function Networks, Learning vector Quantization and Competitive Learning Network Experimental results show that Learning Vector Quantization shows the best performance in the testing data set This is followed in order by CL, MLP and RBFN The high accuracy of the LVQ against the other models indicates its better ability for solving the classificatory problem of Breast Cancer diagnosis.