Development and Validation of an Interpretable Machine Learning–Based Prediction Model of Sepsis: A Retrospective Multicenter Cohort Study

Aims/Background: Sepsis is a leading cause of morbidity and mortality in intensive care units (ICUs). Early identification of patients at high risk of death is essential to guide timely interventions and optimize resource allocation. This study aimed to develop and validate an interpretable machine learning model for predicting 28-day mortality in adult ICU patients.