Metabolomic Subtyping and Machine Learning-Based Diagnosis Reveal Clinical Heterogeneity in Silicosis
These findings highlight metabolic heterogeneity in silicosis and suggest clinically relevant subtypes, providing a foundation for improved stratification, early detection, and targeted interventions.
Authors
- Xinyu Ji (ORCID: https://orcid.org/0000-0003-3002-2609)
- Yuanfang Chen
- A A Li
- Xiaocheng Peng
- Yizhou Yang
- Baoli Zhu (ORCID: https://orcid.org/0000-0002-4112-4574)
- Hangju Zhu
- Lei Han
- Shidan Wang
- Xinyu Li
- Jianye Guo
- Ming Xu
- Ye Li
- Jia Si
Institutions
- Nanjing Health and Health Commission (CN)
- Jiangsu Provincial Center for Disease Control and Prevention (CN)
- Jiangsu Cancer Hospital (CN)
- Ocean University of China (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Metabolites
- Published
- 2026-01-12
- DOI
- https://doi.org/10.3390/metabo16010067
- Primary Topic
- Occupational and environmental lung diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00