Automatic mass classification of breast cancer using ann

Breast cancer is one of the leading causes of mortality among women, and the early diagnosis is of significant clinical importance. To perform classification of medical data, the neural network was trained and tested with breast cancer database by using feed forward neural network multilayer perceptron model and back propogation learning algorithm with Levenberg Marquardt learning and variable learning rate. The performance of the network was evaluated and the experimental results showed that by applying this neural network model, stable and accurate results could be achieved. The results obtained by using the neural network model predicted a higher degree of accuracy when compared with the existing results.