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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM3944
Volume:
4 |
5 |
May 2020
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
One of the leading causes of death worldwide is still heart disease. Reducing its impact and prevalence requires prompt intervention and early detection. In this study, a K-Nearest Neighbors (KNN) algorithm-based machine learning system for heart disease prediction is presented. To deliver real-time risk evaluations, the model is implemented via a Flask web application after being trained on structured medical datasets. The system helps users make preventive healthcare decisions by providing an instantaneous estimate of the chance of heart disease based on certain medical factors they enter.
KEYWORDS
Publication Date
4/21/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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