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©The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Transplant. Mar 18, 2026; 16(1): 111103
Published online Mar 18, 2026. doi: 10.5500/wjt.v16.i1.111103
Published online Mar 18, 2026. doi: 10.5500/wjt.v16.i1.111103
Protocol for a global electronic Delphi on integrating artificial intelligence into solid organ transplantation
Rowan Abuyadek, Department of Health Administration and Behavioural Sciences, High Institute of Public Health, Alexandria University, Alexandria 21561, Egypt
Sara A Ghitani, Department of Forensic Medicine and Clinical Toxicology, Faculty of Medicine, Alexandria University, Alexandria 21524, Egypt
Ramy Shaaban, Department of Instructional Technology and Learning Sciences, Utah State University, Logan, UT 84322, United States
Muhammad AbdelAziz Quoritem, Department of Nephrology, Alsabah Hospital, Farwaneya 00965, Kuwait
Mohammed S Foula, Department of Surgery, King Fahad University Hospital, Imam Abdul
Rodaina Osama Abdel Majid, Department of Public Health, High Institute of Public Health Ale
Manar Mokhtar, Department of General Surgery, Royal Glamorgan Hospital, Cwm Taf Mor
Yasir Ahmed Mohammed Elhadi, Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, Abu Dhabi 15551, United Arab Emirates
Amr Alnagar, Department of General Surgery, University Hospitals of Birmingham, Birming
Author contributions: Abuyadek R, Shabaan R, Abdel Majid RO, and Mokhtar M contributed to literature review, retrieving contact details of experts was done by all authors, tool building on Qualtrics; Abuyadek R and Alnagar A conceptualized and consensus on methodology; A Ghitany S, Quoritem MA, Foula MS, and Elhadi YAM critically revised the manuscript; All authors provided input and review.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Amr Alnagar, PhD, Department of General Surgery, University Hospi
Received: June 24, 2025
Revised: August 17, 2025
Accepted: October 22, 2025
Published online: March 18, 2026
Processing time: 204 Days and 24 Hours
Revised: August 17, 2025
Accepted: October 22, 2025
Published online: March 18, 2026
Processing time: 204 Days and 24 Hours
Core Tip
Core Tip: This study uniquely captures the collective insights of global transplantation experts on the integration of artificial intelligence, using an electronic Delphi approach to identify consensus, concerns, and implementation barriers - providing a critical foundation for ethically grounded and clinically relevant artificial intelligence adoption in organ transplantation. Initial findings show a globally positive outlook on artificial intelligence’s role in supporting transplantation processes, especially in donor matching and post-operative care areas. This should be considered with caution among professionals implementing the new technologies into high-stakes clinical practice.