Heart Disease Diagnosis Using Machine Learning Algorithm

Recent advances in computing and developments in technology have facilitated the routine collection and storage of medical data that can be used to support medical decisions. However, in most countries, there is a first need for collecting and organizing patient’s data in digitized form. Then, the collected data are to be analyzed in order for a medical decision to be drawn, whether this involves diagnosis, prediction, course of treatment, or signal and image analysis. In this paper, India centric dataset is used for Heart disease diagnosis. The correct diagnosis performance of the automatic diagnosis system is estimated by using classification accuracy, sensitivity and specificity analysis. The study shows that, the SVM with Sequential Minimization Optimization learning algorithm have better choice for medical disease diagnosis application.

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