A Machine Learning–Based Prognostication Model Enhances Prediction of Early Hepatic Encephalopathy in Patients With Noncancer-Related Cirrhosis: Multicenter Longitudinal Cohort Study in Taiwan
We developed a novel ML model for predicting HE in patients with noncancer-related cirrhosis. This model provides a practical guide to help physicians and these patients in shared decision-making regarding treatment strategy, with the ultimate goal of improving clinical care and reducing the burden of HE-related morbid complications.
Authors
- Yi-Wen Tsai (ORCID: https://orcid.org/0000-0002-8191-4036)
- Yiu-Hua Cheng
- Yi-Chuan Chen (ORCID: https://orcid.org/0000-0001-6324-561X)
- Wei-Chung Yeh (ORCID: https://orcid.org/0000-0001-9345-4121)
- Hsin-Yu Chen (ORCID: https://orcid.org/0009-0007-9310-4122)
Institutions
- Chang Gung University (TW)
- Chang Gung Memorial Hospital (TW)
- Taipei Municipal YangMing Hospital (TW)
- Keelung Chang Gung Memorial Hospital (TW)
- Linkou Chang Gung Memorial Hospital (TW)
- National Defense Medical Center (TW)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-06-16
- DOI
- https://doi.org/10.2196/71229
- Citations
- 2
- Primary Topic
- Liver Disease and Transplantation
- Type
- article
- Field-Weighted Citation Impact
- 2.64