Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization.

Fine-Gray models had similar discrimination but superior calibration to the RSF-CR model, highlighting the importance of reporting calibration metrics for ML-based prediction models. The discrimination was modest in all readmission prediction models regardless of the methods used.