Machine learning-based plasma metabolomics for improved cirrhosis risk stratification
1 H-NMR serum metabolomics significantly improves the prediction of cirrhosis risk in patients with CLD. The APRI + Metabolomics model demonstrated strong discriminatory power, with key metabolites involved in fatty acid and amino acid metabolism, providing a promising tool for the early screening of cirrhosis risk.
Authors
- Jingru Song (ORCID: https://orcid.org/0000-0002-1917-4890)
- Ling‐Ping Lai (ORCID: https://orcid.org/0000-0002-9651-7420)
- Yi Sang (ORCID: https://orcid.org/0000-0001-6534-0741)
- Binbin Liu (ORCID: https://orcid.org/0000-0002-3458-4046)
- Jie Zhang (ORCID: https://orcid.org/0000-0001-6900-5393)
- Wei Ye (ORCID: https://orcid.org/0000-0002-8211-1956)
- Siqi Chen (ORCID: https://orcid.org/0000-0002-9498-3823)
- Yujun Zhang (ORCID: https://orcid.org/0000-0001-5252-2108)
- Kai Huang (ORCID: https://orcid.org/0000-0003-3348-2723)
- J. Qi (ORCID: https://orcid.org/0009-0007-6837-7137)
- Ziwei Gao (ORCID: https://orcid.org/0009-0007-2040-4669)
Institutions
- Zhejiang Chinese Medical University (CN)
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
Publication Details
- Journal
- BMC Gastroenterology
- Published
- 2025-02-06
- DOI
- https://doi.org/10.1186/s12876-025-03655-y
- Citations
- 2
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.71