An artificial neural network using a back propagation algorithm and feature selection provides highly accurate classification for the diagnosis of heart disease.
Does an Artificial Neural Network based pattern classification algorithm improve the diagnosis of heart disease?
An artificial neural network using back propagation and feature selection can provide highly accurate classification for the diagnosis of heart disease.
The ultimate aim of the proposed method is to establish a model for classification of medical data. In this paper we present ANN for Diagnosis of Heart disease. ANN works like the neural arrangement of brain. The mind studies from its past experiences. It can solve the problems that are not computable or solvable by current computing systems. Feature selection is most important process for selecting a relevant attribute among the huge data set. This reduced set of attributes is then passed to artificial neural network. ANN uses back propagation algorithm for better prediction of result, also the ANN is based on the knowledge this advantage can be taken for more accurate result. ANN provides better accuracy. The result given by ANN is highly accurate, so it may be charity in the therapeutic area for likelihood of diseases like swine flu and heart disease.
Tarle et al. (Tue,) conducted a other in Heart disease. Artificial Neural Network (ANN) with back propagation was evaluated on Classification accuracy. An artificial neural network using a back propagation algorithm and feature selection provides highly accurate classification for the diagnosis of heart disease.