Artificial Intelligence in Kidney Transplantation: A Comprehensive Scientometric Analysis

The integration of artificial intelligence (AI) has profoundly influenced kidney transplantation, enhancing the ability to predict graft survival, diagnose rejection, and improve post-transplant care. This study aims to provide an overview of AI research in kidney transplantation, identifying major contributors, research patterns, and key areas of focus. The data collection and retrieval process involved a systematic search conducted on September 28, 2023, using the Web of Science database. The search resulted in the identification of 269 scholarly articles exclusively focused on AI in kidney transplantation. These articles formed the basis of our comprehensive bibliometric analysis.

Analysis reveals a notable increase in publications since 2017, peaking at 87 in 2022. Machine learning (ML) emerged as the predominant AI subtype, with leading institutions including the Medical University of Vienna, Hannover Medical School, and the University of Alberta. The United States led in publications and citations. Primary research areas include graft outcome, survival, immunosuppressive treatments, and rejection.

The growing integration of AI, particularly ML, underscores the importance of interdisciplinary collaboration and international cooperation in shaping the field. Further research is needed to address current challenges and fully exploit AI's potential in kidney transplantation.