Predicting the Risk of Heart Attacks using Neural Network and Decision Tree
|S.Florence1, N.G.Bhuvaneswari Amma2, G.Annapoorani2 and K.Malathi2
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The healthcare environment is more and more data enriched, but the amount of knowledge getting from those data is very less, because lack of data analysis tools. We need to get the hidden relationships from the data. In the healthcare system to predict the heart attack perfectly, there are some techniques which are already in use. There is some lack of accuracy in the available techniques like Naïve Bayes. Here, this paper proposes the system which uses neural network and Decision tree (ID3) to predict the heart attacks. Here the dataset with 6 attributes is used to diagnose the heart attacks. The dataset used is acath heart attack dataset provided by UCI machine learning repository. The results of the prediction give more accurate output than the other techniques.