Review
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jun 7, 2021; 27(21): 2681-2709
Published online Jun 7, 2021. doi: 10.3748/wjg.v27.i21.2681
Status quo and future prospects of artificial neural network from the perspective of gastroenterologists
Bo Cao, Ke-Cheng Zhang, Bo Wei, Lin Chen
Bo Cao, Ke-Cheng Zhang, Bo Wei, Lin Chen, Department of General Surgery & Institute of General Surgery, Chinese People’s Liberation Army General Hospital, Beijing 100853, China
Author contributions: Cao B wrote this review; Zhang KC and Wei B collected the information and reported studies; Chen L made the decision on this topic and revised the manuscript.
Supported by National Natural Science Foundation of China, No. 81773135 and No. 82073192.
Conflict-of-interest statement: The authors declare no conflict of interests for this article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Lin Chen, MD, PhD, Chief Doctor, Professor, Department of General Surgery & Institute of General Surgery, Chinese People’s Liberation Army General Hospital, No. 28 Fuxing Road, Beijing 100853, China. chenlin@301hospital.com.cn
Received: January 13, 2021
Peer-review started: January 13, 2021
First decision: March 29, 2021
Revised: March 29, 2021
Accepted: April 21, 2021
Article in press: April 21, 2021
Published online: June 7, 2021
Processing time: 134 Days and 1.6 Hours
Abstract

Artificial neural networks (ANNs) are one of the primary types of artificial intelligence and have been rapidly developed and used in many fields. In recent years, there has been a sharp increase in research concerning ANNs in gastrointestinal (GI) diseases. This state-of-the-art technique exhibits excellent performance in diagnosis, prognostic prediction, and treatment. Competitions between ANNs and GI experts suggest that efficiency and accuracy might be compatible in virtue of technique advancements. However, the shortcomings of ANNs are not negligible and may induce alterations in many aspects of medical practice. In this review, we introduce basic knowledge about ANNs and summarize the current achievements of ANNs in GI diseases from the perspective of gastroenterologists. Existing limitations and future directions are also proposed to optimize ANN’s clinical potential. In consideration of barriers to interdisciplinary knowledge, sophisticated concepts are discussed using plain words and metaphors to make this review more easily understood by medical practitioners and the general public.

Keywords: Artificial neural network; Gastrointestinal disease; Diagnosis; Treatment; Prognosis; Endoscopy

Core Tip: This review summarizes the current achievements and existing limitations of artificial neural networks (ANNs) used in gastrointestinal (GI) diseases. The future directions of ANNs are also discussed to provide references for promoting its clinical value. To make this review readable, we introduce the basic knowledge of ANN and illustrate the contents from the perspective of gastroenterologists. ANN is believed to play a critical role in clinical practice of GI diseases.