Open access
Sep 2026
Bridging Accuracy and Explainability in AI-ECG: A Multi-Stage Hyperparameter Tuning Framework for Reinforcement Learning–Based Random Forests
Background: Deep learning applied to ECG has demonstrated strong diagnostic performance for acute coronary syndrome (ACS), but widespread clinical adoption remains limited by lack of interpretability and model robustness. Classical machine learning approaches, such as random forests (RF), offer greater explainability b...
Karam Daoud, Rui Ji, N. Riek et al.
· Journal of Electrocardiology · 0 citations