An Explainable Machine Learning Model for Predicting Short‐Term Haemodynamic Changes Post‐ <scp>TIPS</scp> With Prognostic Implications
The six-feature SVR_RBF model enhances the accuracy and prognostic utility of PPG measurements before TIPS completion, supporting clinical decision-making without additional invasive assessments.
Authors
- Yaozu Liu
- Wei Zhang (ORCID: https://orcid.org/0000-0001-7800-3189)
- Jiaze Yu
- Yongjie Zhou
- Mengxuan Yang (ORCID: https://orcid.org/0000-0003-4652-2472)
- J Z Luo
- Jingqin Ma
- Li Ma
- Zhiping Yan
Institutions
- Shanghai Medical College of Fudan University (CN)
- Fudan University (CN)
- Jinshan Hospital of Fudan University (CN)
- Zhongshan Hospital (CN)
Publication Details
- Journal
- Liver International
- Published
- 2026-01-02
- DOI
- https://doi.org/10.1111/liv.70505
- Primary Topic
- Liver Disease and Transplantation
- Type
- article
- Field-Weighted Citation Impact
- 0.00