Data Analytics Approach for Heart Disease Prediction

Abstract

Recent advancement in technology has cast a strong impact on the utilization of the available data in the healthcare systems. This include employing the enormous data for prediction of heart disease in patient. Nevertheless, predicting heart disease has become one of the main challenges in the medical industry due to the accuracy and performances of prediction and diagnosis issues. One of the approaches to use enormous health care data is the use of data analytics to facilitate the prediction process. However, choosing the best analytics techniques is the most important process because it will influence the prediction and diagnosis result. Thus, this study aims to apply data analytics approach in collection of databases to evaluate the performance of the techniques for prediction of heart disease. In this study, a methodology to analysis the heart disease data will presented. Five algorithms based on the data analytics technique is implemented to observe the performance in heart disease data. Based on the result the decision tree technique shows better performance compared with other techniques with the highest accuracy, 98.53%. The results show the selected features and suitable analytics technique will influence the accuracy and performance of prediction process.