A simple machine learning approach for preoperative diagnosis of esophageal burns after caustic substance ingestion in children

This multicenter study demonstrates that machine learning models using complete blood count parameters, particularly platelet distribution width, can predict esophageal burns in children after caustic ingestion with 84-92% accuracy. The approach offers a non-invasive screening tool to guide endoscopy decisions in pediatric caustic exposure cases.