Application of Artificial Intelligence in rheumatic disease classification: an example of ankylosing spondylitis severity inspection model
The automatic severity inspection model for AS developed in this paper is accurate and can support health professionals in rapidly assessing the severity of AS, enhancing assessment proficiency, and reducing the demands of human resources.
Authors
- Chengkun Yang (ORCID: https://orcid.org/0000-0001-6109-7334)
- Hsi‐Kai Tsou (ORCID: https://orcid.org/0000-0001-9374-9923)
- Pui‐Ying Leong (ORCID: https://orcid.org/0000-0003-2220-0903)
- Chih‐Wei Chen (ORCID: https://orcid.org/0000-0003-4004-7826)
- Chao‐Yuan Yeh (ORCID: https://orcid.org/0000-0002-1947-1596)
- Hao‐Hung Tsai
Institutions
- National Yang Ming Chiao Tung University (TW)
- National Chung Hsing University (TW)
- China Medical University (TW)
- Taichung Veterans General Hospital (TW)
- Chung Shan Medical University Hospital (TW)
- National Science and Technology Council (TW)
- Science Council (GB)
- The London College (GB)
- Kang-Ning Junior College of Medical Care and Management (TW)
- University College London (GB)
- Chung Shan Medical University (TW)
- China Medical University (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2025-06-08
- DOI
- https://doi.org/10.1080/07853890.2025.2512131
- Citations
- 1
- Primary Topic
- Spondyloarthritis Studies and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.67
Funders
- Chung Shan Medical University Hospital