Machine Learning–Based Selection of Resection vs Transplant and Survival in Hepatocellular Carcinoma

Can machine learning (ML)–based risk stratification be used to optimize individualized treatment selection between liver transplantation (LT) and surgical resection for patients with hepatocellular carcinoma (HCC)?In this cohort study of 3915 patients with HCC, ML models stratified treatment-specific risk and identified an LT-favorable group. Counterfactual analysis suggested that ML-guided decisions may potentially improve survival compared with clinical practice decisions, with consistent findings in an external validation cohort.Findings from this study suggested that ML-based decision-support models can stratify patients with HCC by treatment-related risk, enabling personalized, risk-aligned treatment selection between LT and surgical resection and potentially improving survival outcomes through optimized clinical decision-making.

Corresponding Author: Ji Won Han, MD, PhD, Division of Gastroenterology and Hepatology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea (tmznjf@catholic.ac.kr).

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