Using Machine Learning Analysis to Assist in Differentiating between Necrotizing Enterocolitis and Spontaneous Intestinal Perforation: A Novel Predictive Analytic Tool

Necrotizing enterocolitis (NEC) and spontaneous intestinal perforation (SIP) are devastating diseases in preterm neonates, often requiring surgical treatment. Previous studies evaluated outcomes in peritoneal drain placement versus laparotomy, but the accuracy of the presumptive diagnosis remains unknown without bowel visualization. Predictive analytics provide the opportunity to determine the etiology of perforation and guide surgical decision making. The purpose of this investigation was to build and evaluate machine learning models to differentiate NEC and SIP.

Source: Journal of Pediatric Surgery - November 12, 2020 Category: Surgery Authors: Allison C. Lure, Xinsong Du, Erik W. Black, Raechel Irons, Dominick J. Lemas, Janice A. Taylor, Orlyn Lavilla, Diomel de la Cruz, Josef Neu Source Type: research