Goja S, Yadav SK. Artificial intelligence in liver transplantation: Opportunities and challenges. World J Gastrointest Surg 2025; 17(11): 112058 [DOI: 10.4240/wjgs.v17.i11.112058]
Corresponding Author of This Article
Sanjay Goja, MD, FACS, FRCS, Chief Physician, Director, Liver Transplantation and HPB Surgery, Narayana Health Institute of HPB Surgery and Transplantation, DLF Phase III, Sector 24, Gurugram, Delhi NCR 122002, Harayana, India. drsanjaygoja@gmail.com
Research Domain of This Article
Transplantation
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastrointest Surg. Nov 27, 2025; 17(11): 112058 Published online Nov 27, 2025. doi: 10.4240/wjgs.v17.i11.112058
Artificial intelligence in liver transplantation: Opportunities and challenges
Sanjay Goja, Sanjay Kumar Yadav
Sanjay Goja, Sanjay Kumar Yadav, Liver Transplantation and HPB Surgery, Narayana Health Institute of HPB Surgery and Transplantation, Delhi NCR 122002, Harayana, India
Author contributions: Goja S Designed research, performed research, contributed to analytics, wrote and edited; Yadav SK Performed research, contributed to analytics, wrote and edited paper.
Conflict-of-interest statement: There is no conflict of interest associated with any of the senior author or other coauthors contributed their efforts in this manuscript.
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: Sanjay Goja, MD, FACS, FRCS, Chief Physician, Director, Liver Transplantation and HPB Surgery, Narayana Health Institute of HPB Surgery and Transplantation, DLF Phase III, Sector 24, Gurugram, Delhi NCR 122002, Harayana, India. drsanjaygoja@gmail.com
Received: July 17, 2025 Revised: August 16, 2025 Accepted: September 25, 2025 Published online: November 27, 2025 Processing time: 131 Days and 22.2 Hours
Abstract
The management of liver transplant recipients and their outcome prediction is complex due to nonlinear interaction of multiple pre, peri and postoperative factors. Artificial intelligence (AI) has a potentially significant role in understanding and decision making at all stages of liver transplantation procedure. The role starts right from diagnosis of liver cirrhosis, followed by best course of action and prognostication. By analyzing numerous data points, AI can assist in the complex decision-making process of determining transplant candidacy. AI algorithms can analyze vast datasets of donor and recipient characteristics to improve the accuracy of matching, leading to better graft survival rates. This will help in optimizing the allocation of scarce organs, ensuring that they go to the most suitable recipients. AI can be used to predict the pre-operative risk factors and risk of post-operative complications such as graft rejection or post-transplant infections, allowing timely and tailored treatment. AI-powered imaging analysis can assist surgeons in preoperative planning and provide real-time guidance during surgery, increasing precision and improved safety. Therefore, AI has the potential to enhance long term patient and graft survival. The major challenges on use of AI are data availability, data quality, ethical considerations and clinical integration. In essence, AI holds great promise for revolutionizing liver transplantation albeit with some challenges.
Core Tip: Artificial intelligence (AI) has the potential to revolutionize liver transplantation by improving outcomes and optimizing resource allocation. It aids in diagnosis, transplant candidacy, matching donors and recipients, donor liver quality, predicting complexities or complications, and providing real-time surgical guidance. Post-transplant, AI can detect early signs of complications, tailoring immunosuppression, enhancing patient and graft survival. By leveraging advanced algorithms and machine learning techniques, AI provides clinicians with powerful tools to improve patient outcomes and streamline the transplantation process. As we move forward, it is imperative to address ethical challenges and ensure the responsible use of AI in healthcare.
