AN INNOVATIVE MACHINE LEARNING-BASED ALGORITHM FOR DIAGNOSING PEDIATRIC OVARIAN TORSION

This study presents a novel machine learning algorithm that integrates clinical examination findings, ultrasound imaging features, and laboratory values to improve diagnostic accuracy for ovarian torsion in pediatric patients. The approach addresses a critical diagnostic challenge in pediatric emergency medicine where timely recognition is essential to preserve ovarian function.