Padding interpolation, median imputation, RobustScalar, and particle swarm optimization with heterogeneous classifiers: a robust combination for effective heart disease diagnosis
The results establish that the integrated framework of rigorous preprocessing and the hybrid IPSO optimization-classification model creates a highly effective and generalizable pipeline for automated heart disease diagnosis, addressing key limitations of existing approaches.
Authors
- Sanjay Dhanka (ORCID: https://orcid.org/0000-0003-1604-9645)
- Monish Khan (ORCID: https://orcid.org/0000-0003-4755-8338)
- Ankur Kumar (ORCID: https://orcid.org/0009-0007-2623-0065)
- Jeewan Singh
- Amel Ksibi
- Nitin Kumar (ORCID: https://orcid.org/0009-0001-2370-3492)
- Mohamed Abbas
- Surita Maini
Institutions
- Chandigarh University (IN)
- Princess Nourah bint Abdulrahman University (SA)
- Jadara University (JO)
- Graphic Era University (IN)
- Sant Longowal Institute of Engineering and Technology (IN)
- Chitkara University (IN)
- King Khalid University (SA)
- Indian Institute of Technology Mandi (IN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2026-01-12
- DOI
- https://doi.org/10.3389/fmed.2025.1721740
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Princess Nourah Bint Abdulrahman University
- King Khalid University