Automatic bone age assessment: a Turkish population study
The developed automated BAA model for the Turkish population offers a reliable and efficient alternative to traditional methods. By utilizing deep learning with diverse datasets from Bağcılar Hospital and publicly available sources, the model minimizes assessment time and reduces variability. This advancement enhances clinical decision-making, supports standardized BAA practices, and improves patient care in various healthcare settings.
Authors
- Musa Atay (ORCID: https://orcid.org/0000-0001-7750-3093)
- Gül Gizem Pamuk (ORCID: https://orcid.org/0000-0002-8326-7506)
- Tan Cimilli (ORCID: https://orcid.org/0000-0001-7500-7707)
- Candan Varlık (ORCID: https://orcid.org/0000-0003-3331-6493)
- Murat Yüce (ORCID: https://orcid.org/0000-0003-0619-5868)
- Samet Öztürk (ORCID: https://orcid.org/0000-0002-7142-1545)
Institutions
- University of Health Science (KH)
- Sağlık Bilimleri Üniversitesi (TR)
- University of Health Sciences Antigua (AG)
Publication Details
- Journal
- Diagnostic and Interventional Radiology
- Published
- 2025-03-17
- DOI
- https://doi.org/10.4274/dir.2025.242999
- Citations
- 1
- Primary Topic
- Forensic Anthropology and Bioarchaeology Studies
- Type
- article
- Field-Weighted Citation Impact
- 8.27