An Insight on Machine Learning Algorithms for Predicting Heart Diseases
Main Article Content
Abstract
Heart Disease (HD) is one among the critical diseases that severely affects the human kind. The presence of heart disease arise insufficient blood supply to other body parts. Henceforth, diagnosing the HD on time prevents the heart failure. Traditional diagnosing procedure regarding HD detection and prediction becomes unreliable in many circumstances. Recent studies put forth the witness that implication of Machine Learning (ML) in traditional HD detection and prediction has resulted in superior performance. Further, Computer Aided Diagnosis using one-dimensional and multi-dimensional signals assists in diagnosing the HDs at an early stage, thereby saving the human life. The objective of this manuscript is to present an overview of HDs, symptoms and role of ML in HD predictions followed by various state-of-the-art ML algorithms that aids in identification and prediction of HD at an early stage to save the human life;
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.