Identification of core genes in systemic juvenile idiopathic arthritis based on 113 machine learning algorithms
This study elucidated biomarkers associated with sJIA, highlighting the crucial influence of 8 core genes on disease progression. It also successfully developed an effective diagnostic model, potentially guiding future clinical practice in managing sJIA.
Authors
- Jianwu Zeng (ORCID: https://orcid.org/0000-0002-3712-3288)
- Qifan Chen (ORCID: https://orcid.org/0000-0002-5297-7206)
- Bufan Li
- Xinyu Huang
- Maolin He (ORCID: https://orcid.org/0000-0002-3563-763X)
- Yu Sun (ORCID: https://orcid.org/0009-0003-6220-0163)
- Hongyan Wu (ORCID: https://orcid.org/0000-0002-0242-2069)
- Haijun Tang
- Yu-Nan Man
Institutions
- Guangxi Medical University (CN)
- The People's Hospital of Guangxi Zhuang Autonomous Region (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
- Riverside Hospital of Guangxi Zhuang Autonomous Region (CN)
Publication Details
- Journal
- Medicine
- Published
- 2025-09-19
- DOI
- https://doi.org/10.1097/md.0000000000044350
- Primary Topic
- Autoimmune and Inflammatory Disorders Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00