Validation of the Toronto recurrence inference using machine-learning for post-transplant hepatocellular carcinoma model

Validation of the Toronto recurrence inference using machine-learning for post-transplant hepatocellular carcinoma model

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,...

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Main Authors: Zhihao Li, Itsuko Chih-Yi Chen, Leonardo Centonze, Christian T. J. Magyar, Woo Jin Choi, Tommy Ivanics, Grainne M. O’Kane, Arndt Vogel, Lauren Erdman, Luciano De Carlis, Jan Lerut, Quirino Lai, Vatche G. Agopian, Neil Mehta, Chao-Long Chen, Gonzalo Sapisochin
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Communications Medicine
Online Access:https://doi.org/10.1038/s43856-025-00994-5
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https://doi.org/10.1038/s43856-025-00994-5

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