A Spectrum of Cardiac Health Risk Assessment Intelligent System
Medical diagnosis, particularly for cardiac conditions, is complex due to clinical variability, subjectivity, and incomplete information, which can lead to delays or errors. This article presents the development of an intelligent system using ECG data to enhance clinical efficiency, reduce diagnostic errors, and support medical decisionmaking. The system smoothly integrates into clinical workflows, analyzes complex data, and enhances patient outcomes. The Python programming language has been used to develop the code for this model.
Authors
- K. Vinoth Kumar (ORCID: https://orcid.org/0000-0002-3009-1658)
- Pankaj Srivastava (ORCID: https://orcid.org/0000-0001-8063-6209)
Institutions
- Motilal Nehru National Institute of Technology (IN)
Publication Details
- Journal
- Nepal Journal of Mathematical Sciences
- Published
- 2025-04-21
- DOI
- https://doi.org/10.3126/njmathsci.v6i1.77372
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00