CardioPredict - Smart Prediction of Cardiac Diseases

Prediction of patterns to prevent and control diseases is a challenging and a prominent requirement in medical domain. In this , we propose a machine learning framework to predict the possibility of having heart disease using machine learning algorithms. The framework is executed using the algorithm Logistic Regression. Heart Disease UCI dataset is used for training and testing the model. The dataset is preprocessed followed by feature selection to select most prominent features. The resultant dataset is then used for training the framework. The results are combined and show that Logistic Regression gives maximum accuracy.