Highlight
– Liver transplantation (LT) generally offers better long-term survival than surgical resection (SR) for hepatocellular carcinoma (HCC), but donor scarcity and patient variability complicate treatment selection.
– A nationwide Korean cohort study developed separate machine learning (ML) models to predict 3-year overall survival (OS) following LT or SR and stratified patients into treatment-favorable groups.
– The ML models demonstrated robust predictive performance; counterfactual analyses suggest ML-guided treatment decisions could reduce mortality risk by over 50% compared to current clinical practice.
– External validation confirmed reproducibility, supporting potential clinical utility of ML-assisted personalized treatment selection for HCC.
