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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Nouna, Zaid
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Computer Science & IT Engineering

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Heart disease prediction optimization using metaheuristic algorithms Nouna, Zaid; Bouyghf, Hamid; Nahid, Mohammed; Sabiri, Issa
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp4332-4341

Abstract

This study explores metaheuristics hyperparameter tuning effectiveness in machine learning models for heart disease prediction. The optimized models are k-nearest neighbors (KNN) and support vector machines (SVM) using metaheuristics to identify configurations that minimize prediction error. Even though the main focus is utilizing metaheuristics to efficiently navigate the hyperparameter search space and determine optimal setting, a pre-processing and feature selection phase precedes the training phase to ensure data quality. Convergence curves and boxplots visualize the optimization process and the impact of tuning on model performance using three different metaheuristics, where an error of 0.1188 is reached. This research contributes to the field by demonstrating the potential of metaheuristics for improving heart disease prediction performance through optimized machine learning models.
Co-Authors Bouyghf, Hamid Nahid, Mohammed Sabiri, Issa