Heart Diseases Prediction using Machine Learning Algorithms

Abstract

Heart related diseases are the major reason for deaths worldwide. Increasing Deaths due to heart related issues in the last few years is an alarming situation. The leading factors which causes cardiac arrest and remaining heart problems are high blood pressure, diabetes, smoking and unhealthy diet. In order to reduce the death rate due to cardiovascular disease time to time diagnosis and effective treatment is obvious. Chest X-ray, Electrocardiogram (ECG) and coronary algorithms are Traditional cardiovascular disease diagnosis methods. These methods would require a highly qualified professionals and takes a lot of time and sometimes may lead to misdiagnosis. n this paper we are proposing machine learning algorithms which includes Logistic Regression, Decision Tree, Naïve Baye’s, SVM for automating the heart diseases prediction. We have used the medical profiles of patients like age, gender, previous chest pain data some other medical profiles in order to predict the odds of getting a heart disease. Depending upon our model prediction, patients can consult doctor.