Deep Learning in Scaphoid Nonunion Treatment.

ABSTRACT: Background/Objectives: Scaphoid fractures are notorious for a high rate of nonunion, resulting in chronic pain and impaired wrist function. The decision for surgical intervention often involves extensive imaging and prolonged conservative management, leading to delays in definitive treatment. The effectiveness of such treatment remains a subject of ongoing clinical debate, with no universally accepted predictive tool for surgical success. The objective of this study was to train a deep learning algorithm to reliably identify cases of nonunion with a high probability of subsequent union following operative revision. Methods: This study utilized a comprehensive database of 346 patients diagnosed with scaphoid nonunions, with preoperative and postoperative X-rays available for a

SUBMITTER: Tumen L 

PROVIDER: S-EPMC11942999 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature