Concordance Between Large Language Models and Multidisciplinary Tumor Board Recommendations in Treatment Allocation for Hepatocellular Carcinoma

Background/Objectives: Treatment allocation for hepatocellular carcinoma (HCC) is a highly complex task that requires multidisciplinary tumor board (MDT) input; however, its accessibility and reliability can vary across the healthcare system. Large language models (LLMs) have emerged as potential clinical decision-making tools to aid MDTs. Our aim was to compare different LLM-generated treatment recommendations for HCC cases with MDT decisions.