Machine Learning Prediction of Poor Flexion-Extension Outcome After Open Elbow Arthrolysis: Identifying Individual Predisposition Using Clinical and Laboratory Indicators
We have successfully developed a machine learning model using 14 key indicators to predict poor flexion-extension outcomes, which preliminarily explains the "elbow stiffness predisposition."
Authors
- Cunyi Fan (ORCID: https://orcid.org/0000-0002-7854-5233)
- Yaowei Lv (ORCID: https://orcid.org/0000-0002-5269-4548)
- Yuanming Ouyang
- Wencai Liu (ORCID: https://orcid.org/0000-0002-5350-3125)
- Limin Han
- Yuanhao Tong (ORCID: https://orcid.org/0000-0001-8842-1974)
- Xinyu Wang (ORCID: https://orcid.org/0009-0007-0789-9660)
Institutions
- Shanghai Sixth People's Hospital (CN)
Publication Details
- Journal
- Orthopaedic Journal of Sports Medicine
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1177/23259671251389129
- Primary Topic
- Elbow and Forearm Trauma Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00