Ethics and Algorithms to Navigate AI’s Emerging Role in Organ Transplantation
Salybekov A.A. Yerkos A. Sedlmayr M. Wolfien M.
April 2025Multidisciplinary Digital Publishing Institute (MDPI)
Journal of Clinical Medicine
2025#14Issue 8
Background/Objectives: Solid organ transplantation remains a critical life-saving treatment for end-stage organ failure, yet it faces persistent challenges, such as organ scarcity, graft rejection, and postoperative complications. Artificial intelligence (AI) has the potential to address these challenges by revolutionizing transplantation practices. Methods: This review article explores the diverse applications of AI in solid organ transplantation, focusing on its impact on diagnostics, treatment, and the evolving market landscape. We discuss how machine learning, deep learning, and generative AI are harnessing vast datasets to predict transplant outcomes, personalized immunosuppressive regimens, and optimize patient selection. Additionally, we examine the ethical implications of AI in transplantation and highlight promising AI-driven innovations nearing FDA evaluation. Results: AI improves organ allocation processes, refines predictions for transplant outcomes, and enables tailored immunosuppressive regimens. These advancements contribute to better patient selection and enhance overall transplant success rates. Conclusions: By bridging the gap in organ availability and improving long-term transplant success, AI holds promise to significantly advance the field of solid organ transplantation.
artificial intelligence , deep learning , graft failure , machine learning , solid organ transplantation
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Regenerative Medicine Division, Cell and Gene Therapy Department, Qazaq Institute of Innovative Medicine, Astana, 020000, Kazakhstan
Department of Computer Science, Al-Farabi Kazakh National University, Almaty, 050040, Kazakhstan
Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TUD Dresden University of Technology, Dresden, 01069, Germany
Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Dresden, 01069, Germany
Regenerative Medicine Division
Department of Computer Science
Institute for Medical Informatics and Biometry
Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI)
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