Machine learning models in predicting viability after testicular torsion: a proof of concept study

This proof-of-concept study explores machine learning algorithms to predict testicular viability following torsion, addressing a critical clinical challenge in determining salvageability. The research evaluates computational models that could assist urologists in surgical decision-making regarding orchidopexy versus orchiectomy based on preoperative and intraoperative parameters.