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Beyond generic principles: a framework for the ethical analysis of artificial intelligence in organ transplantation

Nadia Primc

Transplant International · 2026

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Artificial intelligence (AI) is increasingly entering clinical medicine, and organ transplantation is no exception. While a growing body of literature addresses the ethical challenges of AI in healthcare, systematic analysis of the specific ethical dimensions of AI use in organ transplantation is missing. This gap reflects a genuine analytical challenge: the transplantation process is ethically complex in ways that general AI ethics frameworks do not adequately capture. Transplantation medicine simultaneously bears ethical obligations to deceased donors, living donors, donor families, organ recipients, and the public at large. These obligations shift substantially across the stages of the transplantation process, from the patient-centred ethics of donor identification and listing decisions, through the distributive justice logic governing organ allocation, to the professional responsibility questions of the peri- and post-transplant phases. A rigorous ethical analysis of AI in organ transplantation therefore requires, first, a systematic mapping of AI use cases and models onto the transplantation process; second, an identification of the stakeholder-specific ethical obligations pertinent at each stage; and third, an in-depth analysis of how those obligations are specifically affected by the properties of the AI system in question. This paper proposes this framework and illustrates it using the example of AI-assisted organ allocation.

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Publikationsdaten

Autor:innen
Nadia Primc
Quelle
Transplant International
Publikation
2026-01-01
Band / Ausgabe
Nicht angegeben
Seiten
Nicht angegeben
ISSN / ISBN
1432-2277
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Zitierfähiger Nachweis

Nadia Primc (2026). Beyond generic principles: a framework for the ethical analysis of artificial intelligence in organ transplantation. Transplant International. https://doi.org/10.3389/ti.2026.16525
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