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

• Main Authors: Hyo-Kyoung Nam (Author), Winnah Wu-In Lea (Author), Zepa Yang (Author), Eunjin Noh (Author), Young-Jun Rhie (Author), Kee-Hyoung Lee (Author), Suk-Joo Hong (Author)
• Format: Book
• Published: Korean Society of Pediatric Endocrinology, 2024-04-01T00:00:00Z.
• Subjects: article
• Online Access: 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,...