Machine Learning Enhances Decision-Making in Hepatocellular Carcinoma Treatment

A machine learning model accurately predicts optimal treatment choices for hepatocellular carcinoma, comparing liver transplantation to surgical resection. The model stratifies patients into high- and low-risk groups, estimating potential survival improvements from tailored decisions. In a nationwide study of over 4,500 patients, machine learning outperformed traditional clinical decision-making approaches, suggesting enhanced outcomes. These findings underscore the model’s potential role in supplementing current treatment guidelines.