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Deep Learning/Neural Network

Artificial Intelligence in Gastrointestinal Endoscopy

https://www.e-ce.org/journal/view.php?number=7344

 

Focused Review Series: Application of Artificial Intelligence in GI Endoscopy

 

Clin Endosc 2020; 53(2): 132-141.

Published online: March 30, 2020

DOI: https://doi.org/10.5946/ce.2020.038

Artificial Intelligence in Gastrointestinal Endoscopy

Alexander P. Abadir1, Mohammed Fahad Ali1, William Karnes2, Jason B. Samarasena2

1Department of Medicine, University of California Irvine, Orange, CA, USA

2Division of Gastroenterology & Hepatology, Department of Medicine, H. H. Chao Comprehensive Digestive Disease Center, University of California Irvine, Orange, CA, USA

Correspondence: Jason B. Samarasena Division of Gastroenterology & Hepatology, Department of Medicine, H. H. Chao Comprehensive Digestive Disease Center, University of California Irvine, 333 City Blvd West, Suite 400, Orange, CA 92868, USA
Tel: +1-714-456-6745, Fax: +1-714-456-7753, E-mail: jsamaras@uci.edu

Received February 3, 2020       Revised March 17, 2020       Accepted March 17, 2020

Copyright © 2020 Korean Society of Gastrointestinal Endoscopy

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

 

 

Abstract

Artificial intelligence (AI) is rapidly integrating into modern technology and clinical practice. Although in its nascency, AI has become a hot topic of investigation for applications in clinical practice. Multiple fields of medicine have embraced the possibility of a future with AI assisting in diagnosis and pathology applications.

In the field of gastroenterology, AI has been studied as a tool to assist in risk stratification, diagnosis, and pathologic identification. Specifically, AI has become of great interest in endoscopy as a technology with substantial potential to revolutionize the practice of a modern gastroenterologist. From cancer screening to automated report generation, AI has touched upon all aspects of modern endoscopy.

Here, we review landmark AI developments in endoscopy. Starting with broad definitions to develop understanding, we will summarize the current state of AI research and its potential applications. With innovation developing rapidly, this article touches upon the remarkable advances in AI-assisted endoscopy since its initial evaluation at the turn of the millennium, and the potential impact these AI models may have on the modern clinical practice. As with any discussion of new technology, its limitations must also be understood to apply clinical AI tools successfully.

Key words: Artificial intelligence; Colonoscopy; Computer assisted diagnosis; Early detection of cancer; Endoscopy

 

 

 

 

 

 

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