Beyond traditional models: Jaya-optimized ensembles for accurate heart disease prediction.
Journal:
Computers in biology and medicine
Published Date:
Jul 16, 2025
Abstract
INTRODUCTION: Heart Disease (HD) stands as the foremost reason for mortality all over the world for both men and women. Millions of people are affected worldwide every year, resulting in numerous fatalities. Timely and precise detection is essential for enhancing patient survival rates and potentially preventing further complications. To avoid these situations, we herein present novel and practical ensemble methods that include different machine learning (ML) and Jaya optimization techniques for HD classification. The key benefits of the Jaya optimization method include its simplicity in implementation, faster convergence, and the absence of algorithm-specific parameter requirements.
