Development of an interpretable machine learning model for predicting in-hospital mortality in ICU patients with sepsis: a retrospective cohort study
Background Sepsis ranks among the primary causes of mortality in intensive care units (ICUs), often resulting in multiple organ dysfunction due to dysregulated systemic inflammation. Timely recognition of patients at high risk is essential, yet existing clinical scoring systems show limited predictive performance. We a...