Table 2.

Overview of AI applications in CDSS for cardiology, detailing their implementation in clinical settings, performance metrics, and future considerations.

Study	AI Application	CDSS in Clinical Settings	Performance Metrics	Future Considerations
[55]	AI-driven CDSS in clinical practice	Real-time recommendations based on patient data	68% improvement in clinical practice	Disparity in assessing various AI-driven CDSS models
[56]	AI-driven CDSS for sepsis prediction	Predicting sepsis outcomes	Potential in early sepsis detection	Challenges in EHR data quality and standardization Prospective validation studies for clinical impact assessment.
[57]	AI-driven CDSS for myocardial infarction prediction	Predicting myocardial infarction outcomes	Moderate improvement over traditional methods; F1 Score: 0.092 and AUC: 0.835	Calibration challenges due to overfitting from low-event frequency Adequate discrimination despite poor calibration