Echocardiography heart diagnosis using Artificial Neural Networks

Over the past decades a considerable amount of time and effort has been expended researching and developing to recognize heart valves diseases. The purpose of this paper is to set out an investigation into Echocardiography for the development of a heart valves diagnosis system. Artificial neural networks are finding many uses in the medical diagnosis application. The goal of this paper is to evaluate artificial neural network in heart disease diagnosis from Echocardiography video file. The cases are studied on valves dieses. Classification is an important tool in medical diagnosis decision support. Feed-forward back propagation neural net work is used as a classifier to detect type of valve diseases. The results of applying the artificial neural net works methodology and find which get high performance corresponding to symptoms of the person. In this study, the data were obtained from Echocardiography video file to diagnosed diseases. The data is separated into inputs and targets the diagnosis of heart diseases; the percent correctly classified in the simulation sample by the feed-forward back propagation network is 95percent.