Zhang YH, Fang AQ, Zhu HY, Du YQ. Facing the challenges of autoimmune pancreatitis diagnosis: The answer from artificial intelligence. World J Gastroenterol 2025; 31(12): 102950 [PMID: 40182594 DOI: 10.3748/wjg.v31.i12.102950]
Corresponding Author of This Article
Hui-Yun Zhu, MD, Department of Gastroenterology, Changhai Hospital, Second Military Medical University (Naval Medical University), No. 168 Changhai Road, Shanghai 200433, China. zhuhuiyun0205@qq.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Letter to the Editor
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 Gastroenterol. Mar 28, 2025; 31(12): 102950 Published online Mar 28, 2025. doi: 10.3748/wjg.v31.i12.102950
Facing the challenges of autoimmune pancreatitis diagnosis: The answer from artificial intelligence
You-Han Zhang, Ai-Qiao Fang, Hui-Yun Zhu, Yi-Qi Du
You-Han Zhang, Ai-Qiao Fang, Hui-Yun Zhu, Yi-Qi Du, Department of Gastroenterology, Changhai Hospital, Second Military Medical University (Naval Medical University), Shanghai 200433, China
Co-first authors: You-Han Zhang and Ai-Qiao Fang.
Co-corresponding authors: Hui-Yun Zhu and Yi-Qi Du.
Author contributions: Zhang YH and Fang AQ contributed to the writing and editing of the manuscript, and the literature review, and they contributed equally to this article as co-first authors; Zhu HY and Du YQ are the co-corresponding authors of this manuscript. All authors have read and approved the final manuscript.
Supported by Youth Start-up Fund of the Naval Medical University, No. 2023QN052; Basic Medical Research Project of the First Affiliated Hospital of Naval Medical University, No. 2023QD16; Simulated RCT Research Project of Shanghai Hospital Deveopment Center, No. SHDC2024CRI048; Changhai Hospital Changfeng Talent Plan; and Shanghai Public Health Key Discipline Project, No. GWVI-11.1-21.
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: Hui-Yun Zhu, MD, Department of Gastroenterology, Changhai Hospital, Second Military Medical University (Naval Medical University), No. 168 Changhai Road, Shanghai 200433, China. zhuhuiyun0205@qq.com
Received: November 4, 2024 Revised: February 19, 2025 Accepted: February 26, 2025 Published online: March 28, 2025 Processing time: 143 Days and 21.4 Hours
Abstract
Current diagnosis of autoimmune pancreatitis (AIP) is challenging and often requires combining multiple dimensions. There is a need to explore new methods for diagnosing AIP. The development of artificial intelligence (AI) is evident, and it is believed to have potential in the clinical diagnosis of AIP. This article aims to list the current diagnostic difficulties of AIP, describe existing AI applications, and suggest directions for future AI usages in AIP diagnosis.
Core Tip: The current diagnosis of autoimmune pancreatitis (AIP) is challenging and often requires multidisciplinary and comprehensive judgment. Misdiagnosis of AIP in clinical practice is common, so it is necessary to find new diagnostic methods for AIP. The development of artificial intelligence (AI) is evident, and we believe that it holds significant potential as a positive auxiliary tool for AIP diagnosis, with substantial practical value in clinical practice. This article aims to highlight the role of AI in AIP diagnosis, suggesting a promising avenue for future development.
