The Role of Artificial Intelligence, Machine Learning, and Deep Learning in Liver Transplantation

Abstract

Liver transplantation is a complex, resource-intensive procedure with critical challenges in donor- recipient matching, post-operative care, and long-term outcome prediction. The integration of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) into liver transplantation workflows promises to enhance clinical decision-making, optimize patient outcomes, and streamline resource allocation. This paper reviews recent advancements in AI, ML, and DL applications in liver transplantation, including donor organ evaluation, recipient selection, surgical risk prediction, and post-transplant monitoring. By summarizing key findings and ongoing research, we provide a roadmap for future innovations in this life-saving field.