Korean J Gastroenterol.  2020 Mar;75(3):120-131. 10.4166/kjg.2020.75.3.120.

Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives

• Bang CS

• KMID: 2471895
• DOI: http://doi.org/10.4166/kjg.2020.75.3.120

Abstract

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.

Keyword

Endoscopy; Gastroenterology; Deep learning; Neural networks, computer; Artificial intelligence

MeSH Terms

Artificial Intelligence
Classification
Endoscopy
Gastroenterology
Learning*
Machine Learning
Medical Records

Figure

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  Fig. 1. Schematic view of perceptron.

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  Fig. 2. Schematic view of a deep neural network.

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  Fig. 3. Schematic view of a convolutional neural network.

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  Fig. 4. Mechanistic scheme of an artificial neural network.

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  Fig. 5. Limitation of a single perceptron.

Reference

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