A Framework for Predicting Heart Disease Using Machine Learning Methods

  • G. Vijay Suresh, Mohammad Sofia, Sk. Sadhik, K. Raviteja, M. Murali Krishna

Abstract

            Cardiovascular disease is one of the most common diseases. We used various attributes that can contribute well to these heart diseases to find better prediction methods, and also used prediction algorithms. “Non-invasive methods such as machine learning can accurately and effectively identify healthy people and people with heart disease. In the proposed study, we developed a diagnostic framework based on machine learning for predicting heart disease by using a heart disease data set. We used three popular machine learning algorithms, two feature selection algorithms, cross-validation techniques, and three performance evaluation classifier indicators, such as classification accuracy, specificity, sensitivity, and execution time. The proposed system can quickly identify and classify heart disease patients in healthy people[11]”.

Published
2020-05-13
How to Cite
G. Vijay Suresh, Mohammad Sofia, Sk. Sadhik, K. Raviteja, M. Murali Krishna. (2020). A Framework for Predicting Heart Disease Using Machine Learning Methods. International Journal of Advanced Science and Technology, 29(7), 1282 - 1289. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/15123
Section
Articles