Survival Prediction of a Patient afterward a Heart Attack by Machine Learning

Abstract

Heart attack is a major threat to human life. It occurs in one or more coronary arteries refilled by the oxygen-rich blood, which also supplies into the heart muscle, suddenly becomes blocked, and unfortunately, a few heart muscle sections can’t get sufficient oxygen. In past, most patients suffered heart attacks at some stage in life. Unfortunately, some of them lost their lives due to this. When the non-survival and survival variables both are examined that determines whether a patient will survive for one more year after suffering from a heart attack. A supervised learning technique has been applied to the Echocardiogram Dataset. The experimental outcomes show that the proposed methodology applied with several data preprocessing approaches achieved a decent 94.74% classification accuracy.