A machine learning model for non-invasive prediction of advanced liver fibrosis in patients with chronic hepatitis B
The ML-based RF model offers a highly accurate, non-invasive interpretable tool for predicting significant liver fibrosis in patients with CHB, offering potential for clinical application in routine fibrosis risk assessment.
Authors
- Jingwei Song
Institutions
- Xinjiang Medical University (CN)
Publication Details
- Journal
- American Journal of Translational Research
- Published
- 2025-01-01
- DOI
- https://doi.org/10.62347/kevq8263
- Citations
- 3
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 4.06
Funders
- Natural Science Foundation of Xinjiang