The Role of Artificial Intelligence in Chronic Liver Diseases and Liver Transplantation

In hepatology, pattern recognition in laboratory data and clinical characteristics is the hallmark of clinical care. Artificial intelligence (AI) tools, like machine or deep learning and large language models, provide interesting mechanisms for facilitating care advancement. The complexity and diversity of data, as well as genetic, environmental, and lifestyle factors, all contribute to individualized recommendations intuitively made by clinicians for patients with liver disease. AI tools provide the opportunity to train on high-volume data and simulate the clinician's subconscious thought processes in decision making. With tremendous growth in hepatology-focused AI, critical efforts are needed to consider multicenter efforts and enabling collection of clean data that are as free as possible of bias. Prospective evaluation of AI tools seamlessly integrated into workflows, especially through clinical trials, as well as patient partner and clinical stakeholder engagement, will be key to building trust in the individualized predictions provided. This review delves into the AI literature in hepatology for diagnostic, prognostic, and therapeutic applications.