Determination of Skeletal Age From Hand Radiographs Using Deep Learning
Development of an accurate DL model for determination of bone age from the hand reduces the time required for age estimation. Additionally, streamlined skeletal age estimation can aid practitioners in determining optimal treatment strategies and may be useful in research settings to decrease workload and improve reporting.
Authors
- Daniel W. Green (ORCID: https://orcid.org/0000-0001-7286-6864)
- Peter D. Fabricant (ORCID: https://orcid.org/0000-0002-8070-685X)
- Moein Shariatnia (ORCID: https://orcid.org/0000-0002-3940-8359)
- Samuel A. Beber (ORCID: https://orcid.org/0009-0009-8477-9413)
- Olivia C. Tracey (ORCID: https://orcid.org/0000-0002-3563-6696)
- Amir Dalili-Yazdi
- Ayoosh Pareek (ORCID: https://orcid.org/0000-0001-8683-1697)
- Joshua T. Bram (ORCID: https://orcid.org/0000-0003-3913-2804)
- Ruth H. Jones (ORCID: https://orcid.org/0009-0006-3097-0747)
Institutions
- Hospital for Special Surgery (US)
- Sharif University of Technology (IR)
- Tehran University of Medical Sciences (IR)
Publication Details
- Journal
- The American Journal of Sports Medicine
- Published
- 2025-08-15
- DOI
- https://doi.org/10.1177/03635465251359618
- Citations
- 3
- Primary Topic
- Forensic Anthropology and Bioarchaeology Studies
- Type
- article
- Field-Weighted Citation Impact
- 24.82