With the rapid development of artificial intelligence(AI) technology in healthcare, disease diagnosis, and treatment and prevention, the application of AI in liver diseases is gaining increasely attention as well. Acute-on-chronic liver failure (ACLF) is a multifactorial syndrome characterized by acute decompensated liver deterioration of chronic liver disease, accompanied by organ failure (not only liver failure or extra-hepatic organ failure), with a high short-term mortality rate. Early detection, accurate assessment of prognosis and early intervention are essential to improve the clinical outcome of ACLF patients. Although studies on prognostic factors of ACLF and common prognostic scoring models at home and abroad have been the focus of attention in the field of liver disease, the clinical value of AI in the diagnosis and prognosis prediction of ACLF has rarely been reported. This paper focuses on the application of AI in the prognosis prediction and evaluation of ACLF, aiming to help clinicians understand the framework of the latest model and provide new ideas for the prognosis prediction model of ACLF.

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