Interpretable machine learning for postoperative sepsis prediction in ICU patients following intracranial hematoma evacuation
Background Sepsis is a prevalent and life-threatening complication in ICU patients after intracranial hematoma evacuation. This study aimed to develop and externally validate an interpretable machine learning model for predicting sepsis risk in this high-risk neurocritical care population. Methods A multicenter retrosp...