Application of Machine Learning Algorithm: Forecasting Heart disease

The healthcare industry produces a huge amount of complex data about patient records. This data can be processed and mined to uncover hidden patterns, which will provide professionals in the healthcare field with additional information and help them in making better informed decisions. Using data in such a way is known as data mining. One such area in the healthcare industry where data mining can be used is early prediction of heart diseases so that patients can get the appropriate treatment. This paper compares the efficiencies of the following supervised machine learning models: Logistic Regression, Naïve Bayes, Support Vector Machine, K-Nearest Neighbors, Decision Tree, Neural Networks, Random Forest. It was found that the Neural Networks algorithm provides the highest accuracy of 81.32%.