Intelligent Transplantation: AI, Machine Learning, and Digital Health Across the Transplant Continuum

Despite the extraordinary advances of transplantation in the last 50 years, the field faces persistent challenges: chronic donor organ shortages, unpredictable rejection episodes, wide variability in graft outcomes, and the lifelong burden of immunosuppression management. Artificial intelligence is rapidly emerging as tool capable of ameliorating these long-standing obstacles. It has shown potential in optimizing organ allocation nationally, organ selection locally, wait-list management, donor-recipient matching for living donors, and prognostication. Outside the clinical realm, AI will transform education of trainees. In the lab, it has already catalyzed research and will aid in producing the next generation of immunosuppressive medications. And, in a future OR, it will guide how we operate.This Research Topic for Frontiers in Transplantation brings together the growing community of AI researchers across the transplant continuum. We invite submissions from researchers worldwide to showcase how AI systems are reshaping clinical decision-making, policy choices, scientific research, and trainee education in transplantation.We seek articles about AI in transplant, writ large. Some topics of interest include, but are not limited to, how AI affects: &#8226 Organ allocation&#8226 Donor-recipient matching&#8226 Equity in transplant&#8226 Radiographic diagnoses&#8226 Pathological diagnoses&#8226 Determination of rejection&#8226 Educating the next generation of transplant providers&#8226 Facilitating novel immunosuppressive agents&#8226 Shaping health care policy and reimbursement&#8226 Facilitating database inquiry for outcomes research&#8226 Power basic science investigation Topic editors: Dimitrios Moris, Justin Barr, Emmanouil Giorgakis Source: https://www.frontiersin.org/research-topics/86946/intelligent-transplantation-ai-machine-learning-and-digital-health-across-the-transplant-continuum