Development and validation of a deep learning model for automatic severity grading of hip osteoarthritis: a multi-center study
The developed model enables automatic and objective assessment of HOA severity using KL grading across diverse populations and imaging conditions. This tool shows potential to support disease monitoring, and large-scale epidemiologic research to enhance standardization and reproducibility in HOA assessment.
Authors
- Shenghao Xu (ORCID: https://orcid.org/0000-0003-3281-7747)
- Chaohui Guo (ORCID: https://orcid.org/0000-0001-8971-0081)
- Jianlin Zuo (ORCID: https://orcid.org/0000-0003-3602-0911)
- Jianlin Xiao (ORCID: https://orcid.org/0000-0001-7175-2726)
- Xiongfeng Tang (ORCID: https://orcid.org/0000-0002-0424-7946)
- Bo Chen (ORCID: https://orcid.org/0000-0002-2796-8201)
- Min Yang (ORCID: https://orcid.org/0000-0002-9034-3175)
- Yanguo Qin
Institutions
- Union Hospital (HK)
- Beijing University of Technology (CN)
- Second Affiliated Hospital of Jilin University (CN)
- East Asia Research (SG)
- Union Hospital (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2025-11-09
- DOI
- https://doi.org/10.1080/07853890.2025.2584361
- Citations
- 1
- Primary Topic
- Osteoarthritis Treatment and Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 1.67