Cardiovascular Disease Risk Prediction Using Data Mining Techniques

Abstract

At present, cardiovascular disease has become the leading cause of death worldwide. Particularly in the South Asian countries have a tremendous risk of cardiovascular disease at an early age than any other ethnic group. Most often it’s challenging for medical practitioners to predict cardiovascular disease 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, Nave Bayes , SVM. By using some properties like (age, gender, bp, stress etc) we can be predicted the chances of cardiovascular disease.