Early Heart Attack Prediction Using Machine Learning Technique

Abstract

Heart attack is a disease which has become the leading cause of death worldwide. Particularly in the South Asian countries have a tremendous risk of heart attack at an early age than any other ethnic group. Most often it’s challenging for medical practitioners to predict heart attack as it requires experience and knowledge which is a complex task to accomplish. This health industry has enormous amounts of data which is useful for making effective conclusions using their hidden information. Using appropriate results and making effective decisions on data, some superior data mining techniques are used such as Logistic Regression, Decision Tree, K-NN. By using some properties like (age, gender, bp, stress etc). we can be predicted the chances of heart attack. In this project, based on the global data set. We applied data mining techniques to determine indicators responsible for the heart attack. In the future, further incorporation & AI will help the systematic detectors.