Machine learning-based prediction of the necessity for the surgical treatment of distal radius fractures
The proposed ML models may assist in assessing the need for surgical treatment in patients with DRFs. By improving the accuracy of treatment decisions, this model may enhance the success rate of fracture treatments, guiding clinical decisions and improving efficiency in clinical settings.
Authors
- Sehun Chang
- Seok Woo Hong (ORCID: https://orcid.org/0000-0003-4059-1557)
- K H Kim
- Jongmin Lim (ORCID: https://orcid.org/0000-0002-8044-1724)
- Hyojin Park (ORCID: https://orcid.org/0000-0003-4814-8330)
- Eugene Kim
Institutions
- Kangbuk Samsung Hospital (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Journal of Orthopaedic Surgery and Research
- Published
- 2025-04-26
- DOI
- https://doi.org/10.1186/s13018-025-05830-z
- Citations
- 5
- Primary Topic
- Orthopedic Surgery and Rehabilitation
- Type
- article
- Field-Weighted Citation Impact
- 10.03
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea