Bioethical challenges in the integration of artificial intelligence in transplant surgery 4.0: A scoping review - Nicolás Lozano-Suarez; Julia Andrea Gomez-Montero; Maritza Jiménez-Gómez; Santiago Cabas; Nicolás Giron-Londoño; Andrea García-López; Fernando Giron-Luque (Digital Health, 2025)
Introduction The integration of artificial intelligence (AI) into transplant surgery offers potential benefits, including enhanced precision and personalized patient care. However, these advancements raise critical ethical issues that must be addressed to ensure responsible implementation. This scoping review and bibliometric analysis explore the literature on the ethical considerations associated with the application of AI in transplant surgery. Methods Following Joanna Briggs Institute and PRISMA-ScR guidelines, we conducted a systematic search of databases, including PubMed, Scopus, Science Direct, JSTOR, LILACS, IEEE, and GreyNet from 2013 to 2025. We identified articles that discussed ethical implications in English or Spanish. Data were charted using Rayyan (Rayyan Systems Inc., Doha, Qatar) and analyzed with Biblioshiny . One reviewer reviewed each article twice to ensure accuracy. Results Our search identified 6824 records, of which 16 studies met the selection criteria. The bibliometric analysis revealed a significant increase in scholarly output on AI ethics in transplantation since 2020. Key ethical concerns comprehend dehumanization of medical care, limitations in AI interpretability, and erroneous decision-making. The potential benefits highlighted include improved donor-recipient matching and personalized patient care. However, the need for human oversight in AI applications is emphasized mitigating risks such as patient dehumanization and biased decision-making. Conclusion This review is the first to comprehensively map the ethical landscape of AI integration in transplant surgery. It identifies both the potential and the significant ethical challenges of these technologies. Future research should focus on developing frameworks for ethical AI implementation and ensuring that advancements in AI contribute to equitable and just healthcare practices.