Predicting the Reparability of Rotator Cuff Tears: Machine Learning and Comparison With Previous Scoring Systems
The performance of the machine learning model, which provides a probability estimation for rotator cuff reparability, is comparable with that of the adjusted scoring system. Nevertheless, when deploying prediction models beyond the original cohort, regardless of whether they rely on machine learning or scoring systems, clinicians should exercise caution and not rely solely on the output of the model.
Authors
- Woo Jung Sung (ORCID: https://orcid.org/0000-0001-7958-5459)
- Yong‐Min Chun (ORCID: https://orcid.org/0000-0002-8147-6136)
- Joon‐Ryul Lim (ORCID: https://orcid.org/0000-0002-0123-7136)
- Tae‐Hwan Yoon (ORCID: https://orcid.org/0000-0002-2859-5240)
- Seung-Hwan Shin (ORCID: https://orcid.org/0000-0002-5664-8848)
Institutions
- Yonsei University (KR)
- Severance Hospital (KR)
Publication Details
- Journal
- The American Journal of Sports Medicine
- Published
- 2024-11-03
- DOI
- https://doi.org/10.1177/03635465241287527
- Citations
- 5
- Primary Topic
- Shoulder Injury and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.86