Prediction of Heart disease using DNN

Machine learning classification techniques are extremely useful in the medical field by providing accurate results and quick diagnosis of diseases. Hence, these techniques save lot of time for both doctors and patients. The neural networks can be used as classifiers predict the diagnosis of Cardiovascular Heart disease. This research has explored neural networks, where it has analyzed many optimizing algorithms and weight initializing techniques in this research. The most common algorithms are used and observed their effect on the accuracy of the model. The coronary heart disease dataset is used in the thesis as data to work on. In order to compare results, further analysis has been done and results are compared with performance of other classifiers.