Early risk stratification is key to guide the management of patients with non-ST-segment elevation acute coronary syndromes (NSTE-ACS). International treatment guidelines hinge on the GRACE scoring system which predicts the probability of future mortality in patients presenting with NSTE-ACS using clinical variables, the electrocardiogram, and cardiac biomarkers. Florian Wenzl et al. developed and externally validated the improved machine learning-based GRACE 3.0 score which provides increased predictive performance and accounts for sex differences in disease characteristics. Check out the full study led by the CMC and published in The Lancet.