A multicenter explainable machine learning analysis of autoimmune disease comorbidity in ankylosing spondylitis
Using routinely available clinical data, an explainable machine learning framework enables accurate identification and characterization of autoimmune comorbidity in AS. This approach has practical potential for early risk stratification and clinical decision support in real-world settings.
Authors
- Chengqian Huang (ORCID: https://orcid.org/0000-0001-6681-7548)
- Changli Liu (ORCID: https://orcid.org/0000-0002-4531-5749)
- Jichong Zhu (ORCID: https://orcid.org/0000-0003-3701-5620)
- Lei Ren
- Jiang Xue
- Hong Cheng
- Hao Li
- Yang Lin
- Tianyou Chen
- Jiarui Chen
- Xinli Zhan
Institutions
- Guangxi University (CN)
- Guangxi Medical University (CN)
- Guilin Medical University (CN)
- The People's Hospital of Guangxi Zhuang Autonomous Region (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
- Affiliated Hospital of Youjiang Medical University for Nationalities (CN)
- Affiliated Hospital of Guilin Medical College (CN)
- Nanxi Mountain Hospital (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2026-02-26
- DOI
- https://doi.org/10.3389/fimmu.2026.1775877
- Primary Topic
- Spondyloarthritis Studies and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangxi Province