Artificial intelligence and mortality prediction in acute coronary syndromes
Zachi Itzhak Attia, Paul A. Friedman · European Heart Journal · 2025
The process of artificial intelligence and mortality prediction using ECG data is illustrated. The 12 lead ECG data is processed to extract human-engineered features, forming the ECG risk model. Deep survival trees analyze the data through majority voting or averaging to produce a final result. This result categorizes individuals into bio-personalized risk groups using Bayesian GMM-based clustering, indicating low, moderate, and high risk of mortality.