Application of machine learning in assessing disease activity in SLE
This pioneering machine learning model, using objective laboratory indicators, enhances clinical feasibility and provides a novel method for assessing SLE disease activity, that may enable timely evaluation of SLE activity, facilitating preparation for treatment and prognosis.
Authors
- Peihong Yuan (ORCID: https://orcid.org/0000-0002-2578-7407)
- Renren Ouyang
- Ting Wang (ORCID: https://orcid.org/0000-0003-4712-6658)
- Rujia Chen (ORCID: https://orcid.org/0000-0001-6744-3509)
- Wei Wei (ORCID: https://orcid.org/0000-0002-2234-4459)
- Yun Wang (ORCID: https://orcid.org/0000-0001-8619-0455)
- Feng Wang (ORCID: https://orcid.org/0009-0003-1503-545X)
- Hongyan Hou (ORCID: https://orcid.org/0000-0003-2337-0509)
Institutions
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Lupus Science & Medicine
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1136/lupus-2024-001456
- Primary Topic
- Systemic Lupus Erythematosus Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Health Commission of Hubei Province