PRAGUE MEDICAL REPORT, Vol 127 No 2 (2026), 69–80
ReviewLiver Transplantation in the Era of Artificial Intelligence: Surgical Innovation, Risk Stratification, and Patient-centred Care
Aditi Naidu Patti
, Vinod Kumar Mugada
, Devika Boddu, Benarjee Veera Mani Kishore Boddeda, Srinivasa Rao Yarguntla
DOI: https://doi.org/10.14712/23362936.2026.11
published online: 19. 06. 2026
abstract
Liver transplantation continues to be the most effective and, in many cases, the only therapeutic recourse for individuals suffering from end-stage liver disease, select hepatocellular malignancies, and uncommon hepatic disorders. Alongside clinical advancements, artificial intelligence (AI) is increasingly being explored for its capacity to support clinical decision-making at all stages of the transplant continuum. In this narrative review, we synthesize recent advancements in liver transplantation and examine the expanding role of AI throughout the process. AI-driven technologies have demonstrated the ability to improve donor-recipient compatibility, evaluate graft function, interpret diagnostic images, and support post-surgical monitoring. Still, obstacles such as limited data availability, bias within algorithms, and unresolved ethical questions continue to pose challenges. At the same time, innovations like machine perfusion, synthetic grafts, and predictive models are helping refine surgical procedures and post-transplant care. Introducing AI into the transplant workflow may boost accuracy, fairness, and healthcare quality. A patient-centred approach that incorporates modern technology, mental health resources, and ethical responsibility will be essential for the future of liver transplantation.
keywords: Artificial intelligence; Liver transplantation; Risk stratification; Graft viability; Transplant outcomes

Liver Transplantation in the Era of Artificial Intelligence: Surgical Innovation, Risk Stratification, and Patient-centred Care is licensed under a Creative Commons Attribution 4.0 International License.
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ISSN: 1214-6994
E-ISSN: 2336-2936