A scoping review of artificial intelligence in living donor liver transplantation - current status and untapped potential

Abstract

While the surgical technicalities of living donor liver transplantation (LDLT) have matured since its development several decades ago, clinical challenges remain in pre-transplantation and post-transplantation management. The ability of artificial intelligence (AI) to perform sophisticated analyses of complex non-linear relationships holds potential to aid clinical decision-making. This is particularly relevant in LDLT, where grafts are a precious resource within a dynamic setting of donor, recipient, and procedural factors that must be considered. Clinical issues of graft and patient survival, patient selection and stratification, survival predictors for expanded transplantation criteria, and post-transplantation outcomes remain relevant challenges that benefit from analysis with sophisticated AI models. This scoping review summarised 16 AI studies in pre- and post-transplantation assessment and transplant oncology, providing an overview of the current landscape and future directions for development.

Keywords

Living donor liver transplantation / artificial intelligence / machine learning / deep learning

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