Development and prospective validation of a machine learning model to predict mortality in cirrhosis with esophageal variceal bleeding
This ML model shows promise in improving mortality prediction for AEVB, potentially aiding timely clinical interventions and decision-making. Prospective validation underscores its generalizability and clinical utility. Future research should explore external validation in diverse settings.
Authors
- Jonathan Soldera (ORCID: https://orcid.org/0000-0001-6055-4783)
- Alana Zulian Terres (ORCID: https://orcid.org/0000-0003-4075-757X)
- Leandro Luís Corso (ORCID: https://orcid.org/0000-0001-9962-9578)
- Rafael Sartori Balbinot (ORCID: https://orcid.org/0000-0002-1464-3213)
- Elisa Fioreze dal Bó
- Raul Angelo Balbinot
- Andressa Daiane Ferraza
- Silvana Sartori Balbinot
- Fernanda Tomé
Institutions
- Universidade de Caxias do Sul (BR)
- Lear (United States) (US)
Publication Details
- Journal
- World Journal of Hepatology
- Published
- 2026-02-12
- DOI
- https://doi.org/10.4254/wjh.v18.i2.111099
- Primary Topic
- Liver Disease and Transplantation
- Type
- article
- Field-Weighted Citation Impact
- 0.00