Development and validation of machine learning models for predicting acute kidney injury in acute-on-chronic liver failure: a multimodel comparative study
The ML models can be reliable tools for predicting AKI in patients with ACLF. The RF model performed the best and can help medical clinicians to better identify patients with high risk of AKI in ACLF.
Authors
- Shuxuan Tang
- Ang Li (ORCID: https://orcid.org/0000-0002-9322-1325)
- Jing Zhang (ORCID: https://orcid.org/0000-0002-3082-8330)
- Jingyuan Liu (ORCID: https://orcid.org/0000-0001-5624-1258)
Institutions
- Capital Medical University (CN)
- Beijing Ditan Hospital (CN)
Publication Details
- Journal
- Renal Failure
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1080/0886022x.2025.2547262
- Primary Topic
- Acute Kidney Injury Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00