ArticleDigital health
Bioethical challenges in the integration of artificial intelligence in transplant surgery 4.0: A scoping review.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- Beyond generic principles: a framework for the ethical analysis of artificial intelligence in organ transplantation.Transplant international : official journal of the European Society for Organ Transplantation · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.