Explainable AI in Cardiology Diagnostics: A Systematic Review of Machine Learning, Meta-heuristic Optimization, and Clinical Text Mining for Coronary Artery Disease

Key Points

• Explainable AI techniques improve diagnostic accuracy for coronary artery disease when evaluated against existing methods.
• Key findings indicate that using clinical text mining methods has shown a notable increase in diagnostic reliability.
• Observational analysis of machine learning frameworks details diverse approaches to enhance coronary artery disease prediction.
• Implications highlight a strong need for integrating explainable AI into clinical practice to optimize diagnostic processes.