Artificial intelligence and liver transplantation: looking inside the Pandora’s box

Abstract

Artificial intelligence (AI) is the discipline of computer science dedicated to processing a large amount of throughput data and is based on algorithms that can rationalize increasingly complex tasks and ultimately reproduce human intelligence. It has been speculated for clinical uses in liver transplantation (LT) for several years, but its application remains incipient worldwide. Therefore, the recent advancements of digital and robotic tools in daily medical practice make the modern environment propitious to its proper implementation. Nevertheless, it is noteworthy that this technology has significant limitations: (i) its unconditional dependence on a pre-established reliable and extensive database; (ii) the potential impact on independent medical decision-making; and (iii) a major economic and environmental burden. So, despite its seducing and flawless simplicity features, AI emerges as a new “Pandora’s box” that should be carefully understood and used under the light of ethical principles to improve clinical outcomes, promote medical and para-medical working conditions, and increase patient safety and access to medical care. The present work aims to review literature data supporting AI implementation on this basis.

Keywords

Liver transplantation / artificial intelligence / machine learning / organ allocation / donor-recipient matching / sustainability / big data / explainability

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