We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
LEVERAGING THE POWER OF HYBRID MACHINE LEARNING ALGORITHMS TO PREDICT CARDIOVASCULAR DISEASES - A REVIEW.
- Authors
ANURADHA P.; DAVID, VASANTHA KALYANI
- 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.
- Subjects
COMPUTERS in the health care industry; CARDIOVASCULAR disease diagnosis; MEDICAL care; MACHINE learning; WORLD Health Organization
- Publication
I-Manager's Journal on Computer Science, 2017, Vol 5, Issue 3, p60
- ISSN
2347-2227
- Publication type
Article
- DOI
10.26634/jcom.5.3.14018