Leveraging The Power of Hybrid Machine Learning Algorithms to Predict Cardiovascular Diseases - A Review

Volume 5 Issue 3 September - November 2017

Review Paper

Leveraging The Power of Hybrid Machine Learning Algorithms to Predict Cardiovascular Diseases - A Review

Anuradha. P*, VASANTHA KALYANI DAVID**

* Research Scholar, Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, India.

** Professor, Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, India.

Anuradha P., and David, V.K. (2017). Leveraging The Power of Hybrid Machine Learning Algorithms to Predict Cardiovascular Diseases - A Review. i-manager’s Journal on Computer Science, 5(3), 60-67. https://doi.org/10.26634/jcom.5.3.14018

Abstract

As people are becoming more health conscious, preventive health care is gaining importance over diagnostic health care. The goal of future medicine is to provide personalized medical care. According to World Health Organization (WHO), 31% of all global deaths are due to Cardiovascular Diseases (CVDs). In order to prevent heart diseases, the unexplored hidden information in the health care data can be efficiently obtained by applying hybrid Machine Learning Algorithms. These algorithms would help the medical practitioners to gain insight into higher dimensional data, thereby assisting them to predict cardiac arrests even before it occurs. This would enhance medical care and reduce costs for patients. This paper surveys and highlights on the suitable statistical and hybrid Machine Learning Algorithms used for feature selection, prediction, and performance evaluation.