Prediction of disease level using multilayer perceptron of Artificial Neural Network for patient monitoring

Abstract

ANN has been proved as a powerful discriminating classifier for tasks in medical diagnosis for early detection of diseases. In our research, ANN has been used for predicting three different diseases (heart disease, liver disorder, lung cancer). Feed-forward back propagation neural network algorithm with Multi-Layer Perceptron is used as a classifier to distinguish between infected or non-infected person. The results of applying the ANNs methodology to diagnosis of these disease based upon selected symptoms show abilities of the network to learn the patterns corresponding to symptoms of the person. In our proposed work, Multi-Layer Perceptron with having 2 hidden layer is used to predict medical diseases. Here in case of liver disorder prediction patients are classified into four categories: normal condition, abnormal condition (initial), abnormal condition and severe condition. This neural network model shows good performance in predicting disease with less error.