Li-Nong Wang

Development and validation of an explainable XGBoost model for early mortality prediction in pediatric sepsis

Objective To develop and internally validate an explainable machine learning model for early mortality prediction in pediatric sepsis using routinely available clinical variables, to support clinical risk stratification and decision-making. Methods A total of 752 children with sepsis admitted to the Pediatric Intensive...