Artificial intelligence in gastroenterology: Where are we heading?

Autor: Glenn Koleth, James Emmanue, Marco Spadaccini, Pietro Mascagni, Kareem Khalaf, Yuichi Mori, Giulio Antonelli, Roberta Maselli, Silvia Carrara, Piera Alessia Galtieri, Gaia Pellegatta, Alessandro Fugazza, Andrea Anderloni, Carmelo Selvaggio, Michael Bretthauer, Alessio Aghemo, Antonino Spinelli, Victor Savevski, Prateek Sharma, Cesare Hassan, Alessandro Repici
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Endoscopy International Open, Vol 10, Iss 11, Pp E1474-E1480 (2022)
Druh dokumentu: article
ISSN: 2364-3722
2196-9736
DOI: 10.1055/a-1907-6569
Popis: 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.
Databáze: Directory of Open Access Journals
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