• Revolutionizing Organ Transplantation Using the Power of Artificial Intelligence
  • Faezeh Arghidash,1,*
    1. Department of Medical Biotechnology and Nanotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran


  • Introduction: One of the mainstays of contemporary medicine is organ transplantation, which provides patients with end-stage organ failure with life-saving therapies (1). Organ supplies are still scarce, with about 100,000 people waiting for transplants every day (2). The demand for donor organs is far greater than the supply, which results in longer waiting times and higher transplant candidate mortality rates even with major improvements in surgical methods and immunosuppressive treatments (3). Both donors and recipients go through a pre-transplant evaluation of histocompatibility, pathology, and clinical case histories as part of the standard of care for organ transplantation. Following the identification of a compatible pair, the organ transplant will take place and be closely followed up. Post-transplant monitoring consists of reviewing the electronic medical record (EMR), evaluating body fluids and blood for organ function and donor-specific antibody formation, and performing protocol biopsies if rejection is suspected (4-7). A promising strategy to get around these challenges and boost the effectiveness and efficiency of transplant operations is the use of artificial intelligence (AI) in organ retrieval and transplantation processes (8). AI holds promise for enhancing organ transplantation by optimizing critical procedures such as donor-recipient matching, surgical planning, post-operative care, and transplant center operational logistics (9). This technology allows healthcare providers to optimize organ allocation, improve surgical outcomes, and reduce judgment errors in the transplant process (10). (Fig.1.). Fig.1. ML (machine learning) and AI applications in organ transplantation (11).
  • Methods: Relevant studies were searched in PubMed, Google Scholar, and ScienceDirect databases from 2010 to 2024, and the resulting studies were reviewed.
  • Results: AI and ML present previously unheard-of chances to enhance healthcare delivery efficiency, alleviate organ shortages, and improve patient outcomes. Transplantation medicine could undergo a revolution thanks to AI and ML, which could enhance donor-recipient matching, improve image analysis and surgical planning, forecast post-transplant outcomes, and simplify operational logistics. Integrating AI and ML into transplantation processes is essential. It delivers personalized treatment plans, reduces patient waiting times, and significantly enhances transplant success rates. AI-driven predictive analytics facilitate early detection and intervention, improving long-term patient management and quality of life. Furthermore, improvements in robotic surgery and remote monitoring systems improve surgical accuracy and offer ongoing post-operative care, which supports favorable results even more.
  • Conclusion: Notwithstanding all the challenges, such as interoperability issues, data privacy concerns, regulatory compliance, and the need for comprehensive clinical validation of AI models, AI and ML-enhanced organ transplantation has the potential to improve transplant recipient care globally and save more lives.
  • Keywords: Artificial intelligence, Organ transplantation, Remote monitoring, Surgical planning.