Open Access
CC BY-NC-ND 4.0 · Endoscopy 2022; 10(11): E1474-E1480
DOI: 10.1055/a-1907-6569
Original article

Artificial intelligence in gastroenterology: Where are we heading?

Glenn Koleth
 1   Hospital Selayang, Department of Gastroenterology and Hepatology, Selangor, Malaysia
,
James Emmanue
 1   Hospital Selayang, Department of Gastroenterology and Hepatology, Selangor, Malaysia
 2   Queen Elizabeth Hospital, Department of Gastroenterology and Hepatology, Sabah, Malaysia
,
Marco Spadaccini
 3   Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Pietro Mascagni
 5   Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
 6   Institute of Image-Guided Surgery, IHU-Strasbourg, France
,
Kareem Khalaf
 3   Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Yuichi Mori
 7   Clinical Effectiveness Research Group, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
 8   Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
,
Giulio Antonelli
 9   "Sapienza" University of Rome, Department of Anatomical, Histological, Forensic Medicine and Orthopedics Sciences, Rome, Italy
10   Ospedale dei Castelli Hospital, Gastroenterology and Digestive Endoscopy Unit, Ariccia, Rome, Italy
,
Roberta Maselli
 3   Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Silvia Carrara
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Piera Alessia Galtieri
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Gaia Pellegatta
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Alessandro Fugazza
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Andrea Anderloni
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Carmelo Selvaggio
 3   Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy
,
Michael Bretthauer
 7   Clinical Effectiveness Research Group, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
,
Alessio Aghemo
 3   Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy
11   Humanitas Research Hospital – IRCCS, Internal Medicine and Hepatology Unit, Rozzano, Italy
,
Antonino Spinelli
 3   Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy
12   Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; Division of Colon and Rectal Surgery, Humanitas Clinical and Research Hospital IRCCS, Rozzano, Milan, Italy
,
Victor Savevski
13   Humanitas Clinical and Research Center – IRCCS, Artificial Intelligence Research, Rozzano, Italy
,
Prateek Sharma
14   Kansas City VA Medical Center, Gastroenterology and Hepatology, Kansas City, United States
,
Cesare Hassan**
 3   Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
,
Alessandro Repici**
 3   Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy
 4   Humanitas Clinical and Research Center – IRCCS, Endoscopy Unit, Rozzano, Italy
› Author Affiliations
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Abstract

Background and study aims Artificial intelligence (AI) is set to impact several fields within gastroenterology. In gastrointestinal endoscopy, AI-based tools have translated into clinical practice faster than expected. We aimed to evaluate the status of research for AI in gastroenterology while predicting its future applications.

Methods All studies registered on Clinicaltrials.gov up to November 2021 were analyzed. The studies included used AI in gastrointestinal endoscopy, inflammatory bowel disease (IBD), hepatology, and pancreatobiliary diseases. Data regarding the study field, methodology, endpoints, and publication status were retrieved, pooled, and analyzed to observe underlying temporal and geographical trends.

Results Of the 103 study entries retrieved according to our inclusion/exclusion criteria, 76 (74 %) were based on AI application to gastrointestinal endoscopy, mainly for detection and characterization of colorectal neoplasia (52/103, 50 %). Image analysis was also more frequently reported than data analysis for pancreaticobiliary (six of 10 [60 %]), liver diseases (eight of nine [89 %]), and IBD (six of eight [75 %]). Overall, 48 of 103 study entries (47 %) were interventional and 55 (53 %) observational. In 2018, one of eight studies (12.5 %) were interventional, while in 2021, 21 of 34 (61.8 %) were interventional, with an inverse ratio between observational and interventional studies during the study period. The majority of the studies were planned as single-center (74 of 103 [72 %]) and more were in Asia (45 of 103 [44 %]) and Europe (44 of 103 [43 %]).

Conclusions AI implementation in gastroenterology is dominated by computer-aided detection and characterization of colorectal neoplasia. The timeframe for translational research is characterized by a swift conversion of observational into interventional studies.

** These authors share senior authorship.


Supplementary material



Publication History

Received: 02 December 2021

Accepted after revision: 20 July 2022

Accepted Manuscript online:
22 July 2022

Article published online:
15 November 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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