Application of Artificial Intelligence in rheumatic disease classification: an example of ankylosing spondylitis severity inspection model.

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Title: Application of Artificial Intelligence in rheumatic disease classification: an example of ankylosing spondylitis severity inspection model.
Authors: Chen CW; Data Finance Innovation (DFI) Research Center, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.; National Council for Sustainable Development (NCSD), Executive Yuan, Taiwan Govt., Taiwan.; Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan.; Faculty of Engineering Sciences, University College London (UCL),London, UK., Tsai HH; Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan., Yeh CY; aetherAI Co., Ltd, Taipei, Taiwan., Yang CK; aetherAI Co., Ltd, Taipei, Taiwan., Tsou HK; Functional Neurosurgery Division, Neurological Institute, Taichung Veterans General Hospital, Taichung, Taiwan.; Department of Rehabilitation, Jen-Teh Junior College of Medicine, Nursing and Management, Miaoli County, Taiwan.; Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan., Leong PY; Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan.; Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung, Taiwan., Wei JC; Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan.; Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung, Taiwan.; Graduate Institute of Integrated Medicine, China Medical University, Taichung, Taiwan.
Source: Annals of medicine [Ann Med] 2025 Dec; Vol. 57 (1), pp. 2512131. Date of Electronic Publication: 2025 Jun 08.
Publication Type: Journal Article
Journal Info: Publisher: Informa Healthcare Country of Publication: England NLM ID: 8906388 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1365-2060 (Electronic) Linking ISSN: 07853890 NLM ISO Abbreviation: Ann Med Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1365-2060
DOI:10.1080/07853890.2025.2512131