A machine learning-based method developed by a Mount Sinai research team allows medical facilities to forecast the mortality risk for certain cardiac surgery patients. The new method is the first institution-specific model for determining the risk of a cardiac patient before surgery and was developed using vast amounts of Electronic Health Data (EHR).

Comparing the data-driven approach to the current population-derived models reveals a considerable performance improvement.