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World J Clin Cases. Sep 26, 2020; 8(18): 3971-3977
Published online Sep 26, 2020. doi: 10.12998/wjcc.v8.i18.3971
Application of artificial neural networks in detection and diagnosis of gastrointestinal and liver tumors
Wei-Bo Mao, Jia-Yu Lyu, Deep K Vaishnani, Yu-Man Lyu, Wei Gong, Xi-Ling Xue, Yang-Ping Shentu, Jun Ma
Wei-Bo Mao, Wei Gong, Department of Pathology, Lishui Hospital of Zhejiang University, Lishui Central Hospital, Lishui 323000, Zhejiang Province, China
Jia-Yu Lyu, Xi-Ling Xue, Department of Psychiatry, The Affiliated Kangning Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China
Deep K Vaishnani, School of International Studies, Wenzhou Medical University, Wenzhou 325035, Zhejiang Province, China
Yu-Man Lyu, College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, Zhejiang Province, China
Yang-Ping Shentu, Jun Ma, Department of Pathology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
Author contributions: Mao WB and Lyu JY contributed equally to this work; Vaishnani DK collected the history and special feature of machine learning and the recent trend of computer-aided detection and diagnosis for endoscopic and ultrasonic images; Lyu YM and Shentu YP worked on deep learning and the background and significance of diagnostic artificial intelligence; Ma J worked on artificial neural network and deep learning.
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: Jun Ma, MD, Doctor, Department of Pathology, First Affiliated Hospital of Wenzhou Medical University, No. 1 Nanbaixiang Street, Wenzhou 325000, Zhejiang Province, China. majun@wzhospital.cn
Received: February 28, 2020
Peer-review started: February 28, 2020
First decision: April 22, 2020
Revised: May 10, 2020
Accepted: June 29, 2020
Article in press: June 29, 2020
Published online: September 26, 2020
Processing time: 206 Days and 16.6 Hours
Core Tip

Core Tip: This paper describes the application of artificial neural networks (ANNs) in the detection and diagnosis of gastrointestinal and liver tumors. We review the artificial intelligence, ANNs and their ability, parallel processing capability, and nonlinear processing. We also discuss the working principle and characteristics of ANNs.