Interpretable machine learning for early in-hospital mortality prediction in intensive care unit patients with acute upper gastrointestinal bleeding: Development and multicenter external validation.
BACKGROUND Early mortality risk stratification remains challenging in intensive care unit (ICU) patients with acute upper gastrointestinal bleeding (AUGIB). We developed a parsimonious, interpretable ensemble model and evaluated its performance across independent ICU cohorts. METHODS MIMIC-IV was used for model devel...