This narrative review evaluates AI's role in risk prediction and clinical applications in coronary artery disease, highlighting the implications for healthcare.
Key Points
AI models significantly improve risk prediction for coronary artery disease, enhancing early detection and tailored interventions.
These AI-based models outperform traditional scores like Framingham and ASCVD, particularly when utilizing multimodal data.
The implementation of AI tools in clinical settings supports decision-making but faces challenges like limited validation and potential bias.
Ethical deployment of AI tools in CAD prevention relies on transparency, fairness, and effective integration into clinical workflows.