Development and Validation of a Risk Stratification Model Using Disease Severity Hierarchy for Mortality or Major Cardiovascular Event

Key Points Question Does incorporating clinical domain knowledge regarding diseases, disease severity, and treatment pathways into machine learning improve risk stratification? Findings In this retrospective cohort study involving 51 969 patients, a new representation of patient data was developed and used to train machine learning models to predict mortality and major cardiovascular events. Results showed substantial improvement in prediction performance compared with traditional patient data representation methods. Meaning The findings of this study suggest that methods that can extract and represent the clinical knowledge contained in electronic medical records should be incorporated into machine learning models for use in clinical decision support systems.