Deep Learning Classification of Rheumatoid Arthritis in Hand Radiographs Interpretability Insights and Web Application
This work advances clinical diagnosis, including early RA patients, by integrating deep learning with interpretable decision paths in hand radiographic analysis, while helping clinicians to use the model more proficiently. The framework provides both diagnostic assistance and educational insights into RA radiographic markers.
Authors
- Yuan Zhan (ORCID: https://orcid.org/0000-0002-4108-2917)
- Kanglin Cai
- Zhitao Feng (ORCID: https://orcid.org/0000-0003-1107-944X)
- Guangming Deng (ORCID: https://orcid.org/0000-0002-0501-2524)
- H. Z. Huang (ORCID: https://orcid.org/0000-0003-2593-0987)
- Dengfeng Dou (ORCID: https://orcid.org/0009-0003-9820-318X)
Institutions
- China Three Gorges University (CN)
- China Pharmaceutical University (CN)
- Capital Medical University (CN)
- State Administration of Traditional Chinese Medicine of the People's Republic of China (CN)
- Second Hospital of Yichang (CN)
Publication Details
- Journal
- ImmunoTargets and Therapy
- Published
- 2025-11-01
- DOI
- https://doi.org/10.2147/itt.s547159
- Primary Topic
- Rheumatoid Arthritis Research and Therapies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- China Pharmaceutical University
- Natural Science Foundation of Hubei Province