Validation of the Toronto recurrence inference using machine-learning for post-transplant hepatocellular carcinoma model.
Journal:
Communications medicine
Published Date:
Jul 9, 2025
Abstract
BACKGROUND: Organ shortages require prioritizing hepatocellular carcinoma (HCC) patients with the highest survival benefit for allografts. While traditional models like AFP, MORAL, and HALT-HCC are commonly used for recurrence risk prediction, the TRIUMPH model, which uses machine learning, has shown superior performance. This study aims to externally validate the model.
Authors
Keywords
No keywords available for this article.