Personal Key Indicators of Heart Disease

Abstract

Heart Disease is recognized as a serious health problem nowadays all over the world.  A healthy lifestyle should be manageable based on useful or inspiring factors which prevent the risk of heart disease. Personal key indicators responsible for heart disease help us to live a stable and healthy life which decreases its risk. Some of the Risk factors which are responsible for coronary artery disease are Age, Smoking, High blood, Diabetes, Obesity, Lack of exercise, Poor sleep, Unhealthy diet, Family history. If we are able to identify personal key indicators which causes CAD then one can live healthy and stable lifestyle. Our aim is to find the personal key indicators which causes coronary artery disease. We have computed the risk ratio for the groups Alcohol drinkers, Physical activity, Diabetes, Smokers, difficulty in walking among the male and female who are exposed to heart disease and not exposed to heart disease. Oversampling technique is used to make the data balance. For the original data and balanced data, we fit the machine learning tools such as logistic regression, Decision Tree, K-nearest Neighbour and Random Forest. For this model precision, recall and f1-score is calculated. Form these matrices best suitable model is proposed.