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
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.