Novel Model to Predict HCC Recurrence after Liver Transplantation Obtained Using Deep Learning: A Multicenter Study

Novel Model to Predict HCC Recurrence after Liver Transplantation Obtained Using Deep Learning: A Multicenter Study

Several models have been developed using conventional regression approaches to extend the criteria for liver transplantation (LT) in hepatocellular carcinoma (HCC) beyond the Milan criteria. We aimed to develop a novel model to predict tumor recurrence after LT by adopting artificial intelligence (M...

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Bibliographic Details
Main Authors: Joon Yeul Nam, Jeong-Hoon Lee, Junho Bae, Young Chang, Yuri Cho, Dong Hyun Sinn, Bo Hyun Kim, Seoung Hoon Kim, Nam-Joon Yi, Kwang-Woong Lee, Jong Man Kim, Joong-Won Park, Yoon Jun Kim, Jung-Hwan Yoon, Jae-Won Joh, Kyung-Suk Suh
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Cancers
Subjects:
deep learning
liver transplantation
hepatocellular carcinoma
Milan criteria
Online Access:https://www.mdpi.com/2072-6694/12/10/2791

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