Development and multi-center validation of machine learning models based on targeted metabolomics for rheumatoid arthritis

Abstract Background Rheumatoid arthritis (RA) remains in urgent need of more effective biomarkers to improve diagnostic accuracy. Methods In this study, we conducted a comprehensive analysis of 2,863 blood samples obtained from seven cohorts comprising RA, osteoarthritis (OA), and healthy control (H...

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Autori principali:	Jifeng Tang, Renquan Jiang, Huali Gao, Jinfang Xia, Yanhui Ma, Zhenge Han, Haitao Yu, Yizhong Zhang, Fang Xie, Huiming Sheng, Jinpiao Lin
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2025-11-01
Serie:	Journal of Translational Medicine
Soggetti:	Rheumatoid arthritis Metabolomics Biomarkers Diagnostic model Seronegative RA Multi-center study
Accesso online:	https://doi.org/10.1186/s12967-025-07265-w
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