Deep learning for hepatocellular carcinoma recurrence before and after liver transplantation: a multicenter cohort study.

ABSTRACT: Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to mortality. We developed a recurrence prediction system for HCC patients before and after LT. Data from patients with HCC who underwent LT were retrospectively collected from three specialist centres in China. Pre- and post-operative variables were selected using support vector machine, random forest, and logistic regression (LR). Then, pre- and post-operative models were developed using three machine learning methods: LR, stacking, and two survival-based approaches. Models were evaluated using seven assessment indices, and patients were classified as either high- or low-risk based on recurrence risk. 466 patients were included and followed for a median of 51.0 months (95% CI 47.8-54.2). The

SUBMITTER: Cao S 

PROVIDER: S-EPMC11882823 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature