Multimodal AI in Hepatocellular Carcinoma: Bridging Diagnosis, Therapy and Prognosis Toward Precision Oncology

Background

This narrative review summarizes recent advances in multimodal AI for hepatocellular carcinoma (HCC), a highly heterogeneous malignancy. Traditional singlemodal data (eg imaging, serology, pathology) are insufficient for accurate diagnosis and personalized treatment. Multimodal technology, which integrates four categories of data (imaging, pathology, molecular, and clinical) through artificial intelligence (AI), has emerged as a promising solution. This review aims to summarize the sources, characteristics, and standardization of multimodal data in HCC, and to comprehensively update its clinical applications in diagnosis, treatment decision-making, and prognosis prediction.