Early risk stratification of sepsis-related liver injury via machine learning: a multicohort study

Our study explored ML-based models for predicting SRLI among sepsis at an earlier stage and the performance of random forest model ranked best. The significant predictive contribution of prothrombin time highlights its potential as a key monitoring marker for early risk stratification in septic patients.