AI Innovations in Liver Transplantation: From Big Data to Better Outcomes

Abstract

Artificial intelligence (AI) has emerged as a transformative field in computational research with diverse applications in medicine, particularly in the field of liver transplantation (LT) given its ability to analyze and build upon complex and multidimensional data. This literature review investigates the application of AI in LT, focusing on its role in pre-implantation biopsy evaluation, development of recipient prognosis algorithms, imaging analysis, and decision-making support systems, with the findings revealing that AI can be applied across a variety of fields within LT, including diagnosis, organ allocation, and surgery planning. As a result, algorithms are being developed to assess steatosis in pre-implantation biopsies and predict liver graft function, with AI applications displaying great accuracy across various studies included in this review. Despite its relatively recent introduction to transplantation, AI demonstrates potential in delivering cost and time-efficient outcomes. However, these tools cannot replace the role of healthcare professionals, with their widespread adoption demanding thorough clinical testing and oversight.