Development and evaluation of a machine learning-based risk prediction model for enteral feeding intolerance in sepsis patients (opens in new tab)

BackgroundEarly detection and prediction of enteral feeding intolerance (EFI) are essential for effective management of septic patients. This study seeks to develop an interpretable machine learning (ML) model for predicting EFI in septic patients.MethodsData were collected from septic patients admitted to the intensive care unit and receiving enteral nutrition (EN) at a tertiary hospital in Shandong Province between January 2023 and July 2025. A retrospective cohort was randomly divided into...