Journal of the American College of Surgeons
Development, Validation, and Comparison of Machine Learning Models for Predicting Pediatric Surgical Site Infections Using the NSQIP-P Database.
Carrie T Chan, Mark J Pletcher, Karthik Balakrishnan, Yulin Hswen, Aaron Scheffler
Published: 202510.1097/XCS.0000000000001683
Abstract
BACKGROUND: Surgical site infections (SSIs) cause substantial postoperative morbidity in children. Despite being largely preventable, SSI rates have continued to rise. Existing SSI predictive models are predominantly designed for adults. This study a…
Preview only. Read the full abstract at the source