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Korean J Gastroenterol  <  Volume 75(3); 2020 <  Articles

Korean J Gastroenterol 2020; 75(3): 120-131  https://doi.org/10.4166/kjg.2020.75.3.120
Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives
Chang Seok Bang
Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Korea
Correspondence to: Chang Seok Bang, Department of Internal Medicine, Hallym University College of Medicine, 1 Hallymdaehak-gil, Chuncheon 24252, Korea. Tel: +82-33-240-5821, Fax: +82-33-241-8064, E-mail: csbang@hallym.ac.kr, ORCID: https://orcid.org/0000-0003-4908-5431
Received: February 13, 2020; Revised: March 1, 2020; Accepted: March 2, 2020; Published online: March 25, 2020.
© The Korean Journal of Gastroenterology. All rights reserved.

This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Artificial intelligence using deep learning has been applied to gastrointestinal disorders for the detection, classification, and delineation of various lesion images. With the accumulation of enormous medical records, the evolution of computation power with graphic processing units, and the widespread use of open-source libraries in large-scale machine learning processes, medical artificial intelligence is overcoming its traditional limitations. This paper explains the basic concepts of deep learning model establishment and summarizes previous studies on upper gastrointestinal disorders. The limitations and perspectives on future development are also discussed.
Keywords: Artificial intelligence; Neural networks, computer; Deep learning; Gastroenterology; Endoscopy

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