ArticleEuropean radiology2025
A critical comparative study of the performance of three AI-assisted programs for bone age determination.
Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- External Validation of Deeplasia for Automated Bone Age Assessment Compared with Four Commercial AI Systems.Diagnostics (Basel, Switzerland) · 2026Article
- Current applications and challenges of artificial intelligence applied to diagnostics in pediatric musculoskeletal imaging.Pediatric radiology · 2026Review
- Article
- Comparative study of the performance of two versions of the same AI tool for pediatric skeletal maturation assessment.European radiology · 2026Article
- AI in Musculoskeletal Imaging: An End-to-End Perspective.Journal of clinical medicine · 2026Review
- Proof-of-concept comparison of an artificial intelligence-based bone age assessment tool with Greulich-Pyle and Tanner-Whitehouse version 2 methods in a pediatric cohort.Pediatric radiology · 2026Article
- Observational
- Automated Bone Age Assessment and Adult Height Prediction from Pediatric Hand Radiographs via a Cascaded Deep Learning Framework.Journal of medical systems · 2025Article
- The combined diagnostic and therapeutic value of ultrasound and X-ray bone age index in girls with idiopathic central precocious puberty.Endocrine connections · 2025Article
- [Current Landscape and Commercialization of AI Models in Musculoskeletal Imaging].Journal of the Korean Society of Radiology · 2025Review
- Comparison of BoneXpert and IB-Lab-PANDA automated Bone Age Evaluation in Children With Growth and Puberty Disorders.Journal of the Endocrine Society · 2025Article
- Potential of Artificial Intelligence for Bone Age Assessment in Iranian Children and Adolescents: An Exploratory Study.Archives of Iranian medicine · 2025Article
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5 authors.
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Abstract
objectivesTo date, AI-supported programs for bone age (BA) determination for medical use in Europe have almost only been validated separately, according to Greulich and Pyle (G&P). Therefore, the current study aimed to compare the performance of three programs, namely BoneXpert, PANDA, and BoneView, on a single Central European population. MATERIALS AND
methodsFor this retrospective study, hand radiographs of 306 children aged 1-18 years, stratified by gender and age, were included. A subgroup consisting of the age group accounting for 90% of examinations in clinical practice was formed. The G&P BA was estimated by three human experts-as ground truth-and three AI-supported programs. The mean absolute deviation, the root mean squared error (RMSE), and dropouts by the AI were calculated.
resultsThe correlation between all programs and the ground truth was prominent (R
conclusionAll three AI programs predict BA after G&P in the main age range with similar high reliability. Differences arise at the boundaries of childhood. KEY POINTS: Question There is a lack of comparative, independent validation for artificial intelligence-based bone age estimation in children. Findings Three commercially available programs estimate bone age after Greulich and Pyle with similarly high reliability in a central European cohort. Clinical relevance The comparative study will help the reader choose a software for bone age estimation approved for the European market depending on the targeted age group and economic considerations.
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