Identification of diagnostic biomarkers for fibromyalgia using gene expression analysis and machine learning
The study successfully identifies three diagnostic biomarkers for FM, supported by both bioinformatics analysis and machine learning models. These findings could significantly improve diagnostic accuracy for FM, leading to better patient management and treatment outcomes.
Authors
- Chenyang Song
- Juan Jiao (ORCID: https://orcid.org/0000-0002-4370-5137)
- Li Yang (ORCID: https://orcid.org/0000-0001-8771-7044)
- Jianan Zhao (ORCID: https://orcid.org/0000-0002-8439-1082)
- Cen Chang (ORCID: https://orcid.org/0000-0002-7449-2613)
- Yaxin Cheng
- Fuyu Zhao
- Yunshen Li
- Shiya Wu (ORCID: https://orcid.org/0009-0005-3780-8227)
- Bingheng He
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Shanghai University of Traditional Chinese Medicine (CN)
- Tongren Hospital (CN)
- Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine (CN)
- Guang’anmen Hospital (CN)
Publication Details
- Journal
- Frontiers in Genetics
- Published
- 2025-04-17
- DOI
- https://doi.org/10.3389/fgene.2025.1535541
- Citations
- 2
- Primary Topic
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Type
- article
- Field-Weighted Citation Impact
- 2.94
Funders
- Shanghai Municipal Health Commission