Risk Factors for Pediatric Sepsis in the Emergency Department: A Machine Learning Pilot Study.

Machine learning models trained to identify pediatric sepsis using ED clinical and sociodemographic variables confirmed well-established predictors, including heart rate and mean arterial pressure, and identified underappreciated relationships between sepsis and patient age, immunization status, and demographics.