Abstract
Liver cancer remains one of the most formidable challenges in modern medicine, characterized by its high incidence and mortality rate. Emerging evidence underscores the critical roles of the immune microenvironment in tumor initiation, development, prognosis, and therapeutic responsiveness. However, the composition of the immune microenvironment of liver cancer (LC-IME) and its association with clinicopathological significance remain unelucidated. In this review, we present the recent developments related to the use of artificial intelligence (AI) for studying the immune microenvironment of liver cancer, focusing on the deciphering of complex high-throughput data. Additionally, we discussed the current challenges of data harmonization and algorithm interpretability for studying LC-IME.