Predicting in-hospital mortality in patients with alcoholic cirrhosis complicated by severe acute kidney injury: development and validation of an explainable machine learning model
The Lasso-LR model exhibits robust predictive capability for in-hospital mortality among patients with alcoholic cirrhosis complicated by AKI, offering valuable prognostic insights and individualized treatment decision support for healthcare professionals.
Authors
- Shihui Liu (ORCID: https://orcid.org/0000-0002-6827-9357)
- Mingliang Sun (ORCID: https://orcid.org/0000-0002-6245-3844)
- Jinyu Zhang (ORCID: https://orcid.org/0000-0002-9200-5348)
- Jie Min (ORCID: https://orcid.org/0000-0002-7629-5541)
- Lei Zhong (ORCID: https://orcid.org/0000-0002-0208-1823)
- Z. Z. Du (ORCID: https://orcid.org/0009-0003-4567-982X)
Institutions
- Zhejiang Chinese Medical University (CN)
- Huzhou Normal University (CN)
- Huzhou Central Hospital (CN)
- Affiliated Hospital of Jining Medical University (CN)
- Jinzhou Medical University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-05-08
- DOI
- https://doi.org/10.3389/fmed.2025.1570928
- Citations
- 2
- Primary Topic
- Alcohol Consumption and Health Effects
- Type
- article
- Field-Weighted Citation Impact
- 2.94