Clinical validation of a deep-learning-based bone age software in healthy Korean children

• Auteurs principaux: Hyo-Kyoung Nam (Auteur), Winnah Wu-In Lea (Auteur), Zepa Yang (Auteur), Eunjin Noh (Auteur), Young-Jun Rhie (Auteur), Kee-Hyoung Lee (Auteur), Suk-Joo Hong (Auteur)
• Format: Livre
• Publié: Korean Society of Pediatric Endocrinology, 2024-04-01T00:00:00Z.
• Sujets: article
• Accès en ligne: Connect to this object online.

Purpose Bone age (BA) is needed to assess developmental status and growth disorders. We evaluated the clinical performance of a deep-learning-based BA software to estimate the chronological age (CA) of healthy Korean children. Methods This retrospective study included 371 healthy children (217 boys,...