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Artif Intell Gastrointest Endosc. Mar 8, 2024; 5(1): 89138
Published online Mar 8, 2024. doi: 10.37126/aige.v5.i1.89138
Artificial intelligence: Applications in critical care gastroenterology
Deven Juneja
Deven Juneja, Department of Critical Care Medicine, Max Super Speciality Hospital, New Delhi 110017, India
Author contributions: Juneja D researched the subject, performed data accusation, performed the writing and reviewed the final manuscript.
Conflict-of-interest statement: All the author declare that they have no conflict of interest.
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: Deven Juneja, DNB, MBBS, Director, Department of Critical Care Medicine, Max Super Speciality Hospital, 1 Press Enclave Road, Saket, New Delhi 110017, India. devenjuneja@gmail.com
Received: October 21, 2023
Peer-review started: October 21, 2023
First decision: December 7, 2023
Revised: December 7, 2023
Accepted: December 26, 2023
Article in press: December 26, 2023
Published online: March 8, 2024
Core Tip

Core Tip: The scope and applications of artificial intelligence (AI) are rapidly increasing. It is being increasingly applied in various fields, even in healthcare settings. The data generated by critically ill patients admitted in intensive care units (ICUs) is huge, which may be helpful in developing AI algorithms aimed to aid in their management. Patients with primary gastrointestinal diseases may frequently require ICU admission for management of advanced disease or related complications. Use of AI may aid the critical care physicians in managing such patients by helping in early diagnosis, prediction of complications, assessing response to therapy and overall prognostication.