RESUMEN
With the rapid development of artificial intelligence （AI） technology in the field of medicine， AI models show great potential in the diagnosis， prognosis and efficacy prediction of hepatocellular carcinoma （HCC）. AI techniques include computational search algorithms， machine learning （ML） and deep learning （DL） models. Based on histopathology， radiomics and related molecular markers， the ML or DL algorithm is used to extract key information and then establish the diagnosis or prediction model， which may serve as a tool to aid in clinical decision-making. Further technical support， large-scale clinical validation and regulatory approvals are still needed due to the limitations on the application of AI models. This review summarizes the advances of AI in HC diagnosis， prediction of recurrence and prognosis， and highlights the radiomics， histopathology and molecular marker data.