Review
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jul 14, 2021; 27(26): 4088-4103
Published online Jul 14, 2021. doi: 10.3748/wjg.v27.i26.4088
Non-occlusive mesenteric ischemia: Diagnostic challenges and perspectives in the era of artificial intelligence
Simon Bourcier, Julian Klug, Lee S Nguyen
Simon Bourcier, Department of Intensive Care Medicine, University Hospital of Geneva, Geneva 1201, Switzerland
Julian Klug, Department of Internal Medicine, Groupement Hospitalier de l’Ouest Lémanique, Nyon 1260, Switzerland
Lee S Nguyen, Department of Intensive Care Medicine, CMC Ambroise Paré, Neuilly-sur-Seine 92200, France
Author contributions: Bourcier S wrote the manuscript; Klug J significantly contributed to the manuscript; Nguyen LS co-wrote and supervised this work.
Conflict-of-interest statement: The authors have no conflict of interest regarding this work.
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: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Lee S Nguyen, MD, PhD, Doctor, Senior Researcher, Department of Intensive Care Medicine, CMC Ambroise Paré, 25 Boulevard Victor Hugo, Neuilly-sur-Seine 92200, France. nguyen.lee@icloud.com
Received: January 28, 2021
Peer-review started: January 28, 2021
First decision: March 7, 2021
Revised: March 25, 2021
Accepted: June 18, 2021
Article in press: June 18, 2021
Published online: July 14, 2021
Core Tip

Core Tip: In this review we focus on non-occlusive mesenteric ischemia and discuss the challenges of a reliable diagnosis, which requires several simultaneous elements, including physical examination, biomarkers, and imaging elements. While taken individually these elements do not provide sufficient diagnostic accuracy, a multimodal approach relying on artificial intelligent algorithms may increase speed and accuracy in recognizing this rare but severe condition.