Qie YY, Xue XF, Wang XG, Dang SC. Application of artificial intelligence in the diagnosis and prediction of gastric cancer. Artif Intell Gastroenterol 2020; 1(1): 12-18 [DOI: 10.35712/aig.v1.i1.12]
Corresponding Author of This Article
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
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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/
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 bygrants 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
Abstract
Gastric cancer is the second leading cause of cancer deaths worldwide. Despite the great progress in the diagnosis and treatment of gastric cancer, the incidence and mortality rate of the disease in China are still relatively high. The high mortality rate of gastric cancer may be related to its low early diagnosis rate and poor prognosis. 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. Taking appropriate treatment measures is the key to reducing the mortality rate of gastric cancer. In the past decade, 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.
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.
