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Review
. 2020 Dec 14;26(46):7287-7298.
doi: 10.3748/wjg.v26.i46.7287.

Evolving role of artificial intelligence in gastrointestinal endoscopy

Affiliations
Review

Evolving role of artificial intelligence in gastrointestinal endoscopy

Gulshan Parasher et al. World J Gastroenterol. .

Abstract

Artificial intelligence (AI) is a combination of different technologies that enable machines to sense, comprehend, and learn with human-like levels of intelligence. AI technology will eventually enhance human capability, provide machines genuine autonomy, and reduce errors, and increase productivity and efficiency. AI seems promising, and the field is full of invention, novel applications; however, the limitation of machine learning suggests a cautious optimism as the right strategy. AI is also becoming incorporated into medicine to improve patient care by speeding up processes and achieving greater accuracy for optimal patient care. AI using deep learning technology has been used to identify, differentiate catalog images in several medical fields including gastrointestinal endoscopy. The gastrointestinal endoscopy field involves endoscopic diagnoses and prognostication of various digestive diseases using image analysis with the help of various gastrointestinal endoscopic device systems. AI-based endoscopic systems can reliably detect and provide crucial information on gastrointestinal pathology based on their training and validation. These systems can make gastroenterology practice easier, faster, more reliable, and reduce inter-observer variability in the coming years. However, the thought that these systems will replace human decision making replace gastrointestinal endoscopists does not seem plausible in the near future. In this review, we discuss AI and associated various technological terminologies, evolving role in gastrointestinal endoscopy, and future possibilities.

Keywords: Artificial intelligence; Endoscopic diagnosis; Gastric cancer; Gastrointestinal diseases; Gastrointestinal endoscopy; Machine learning.

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Conflict of interest statement

Conflict-of-interest statement: There is no conflict of interest associated with any of the senior author or other coauthors contributed their efforts in this manuscript.

Figures

Figure 1
Figure 1
Schematic representation of different aspects of machine learning approach. AI: Artificial intelligence; ML: Machine learning.

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