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©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastroenterol. Jul 28, 2020; 1(1): 12-18
Published online Jul 28, 2020. doi: 10.35712/aig.v1.i1.12
Published online Jul 28, 2020. doi: 10.35712/aig.v1.i1.12
Application of artificial intelligence in the diagnosis and prediction of gastric cancer
Yin-Yin Qie, Department of General Surgery, The Affiliated Hospital, Jiangsu University, Zhenjiang 212001, Jiangsu Province, China
Xiao-Fei Xue, Xiao-Gang Wang, Sheng-Chun Dang, Department of General Surgery, Pucheng Hospital, Weinan 715500, Shaanxi Province, China
Sheng-Chun Dang, Department of General Surgery, the Affiliated Hospital, Jiangsu University, Zhenjiang 212001, Jiangsu Province, China
Author contributions: All authors made substantial contributions to conception, design, and attainment of data, were engaged in preparing the article or revising it analytically for essential intellectual content, gave final approval of the version to be published, and agreed to be accountable for all aspects of the work.
Supported by grants from the Zhenjiang Science and Technology Committee , No. SH 2019061 .
Conflict-of-interest statement: The authors declare having no conflicts of interest.
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: Sheng-Chun Dang, MD, Chief Doctor, Professor, Surgeon, Department of General Surgery, The Affiliated Hospital, Jiangsu University, No. 438, Jiefang Road, Zhenjiang 212001, Jiangsu Province, China. dscgu@163.com
Received: June 12, 2020
Peer-review started: June 12, 2020
First decision: June 18, 2020
Revised: July 13, 2020
Accepted: July 16, 2020
Article in press: July 16, 2020
Published online: July 28, 2020
Processing time: 45 Days and 1 Hours
Peer-review started: June 12, 2020
First decision: June 18, 2020
Revised: July 13, 2020
Accepted: July 16, 2020
Article in press: July 16, 2020
Published online: July 28, 2020
Processing time: 45 Days and 1 Hours
Core Tip
Core tip: Much research has been focused on improving the sensitivity and specificity of diagnostic tools for gastric cancer, in order to more accurately predict the survival times of gastric cancer patients. Artificial intelligence technology has been applied to various fields of medicine as a branch of computer science. This article discusses the application and research status of artificial intelligence in gastric cancer diagnosis and survival prediction.