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World J Gastroenterol. Sep 28, 2020; 26(36): 5408-5419
Published online Sep 28, 2020. doi: 10.3748/wjg.v26.i36.5408
Artificial intelligence in gastric cancer: Application and future perspectives
Peng-Hui Niu, Lu-Lu Zhao, Hong-Liang Wu, Dong-Bing Zhao, Ying-Tai Chen
Peng-Hui Niu, Lu-Lu Zhao, Dong-Bing Zhao, Ying-Tai Chen, Department of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
Hong-Liang Wu, Department of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
Author contributions: Niu PH, Zhao LL, and Wu HL contributed equally to this work; All authors made substantial contributions to the intellectual content of this paper.
Supported by National Key R&D Program of China, No. 2017YFC0908300.
Conflict-of-interest statement: All the authors have no conflict of interest related to the manuscript.
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: Ying-Tai Chen, MD, Professor, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.17 Panjiayuan Nanli, Beijing 100021, China. yingtaichen@126.com
Received: May 24, 2020
Peer-review started: May 24, 2020
First decision: July 29, 2020
Revised: August 2, 2020
Accepted: August 29, 2020
Article in press: August 29, 2020
Published online: September 28, 2020
Processing time: 123 Days and 0.1 Hours
Abstract

Gastric cancer is the fourth leading cause of cancer-related mortality across the globe, with a 5-year survival rate of less than 40%. In recent years, several applications of artificial intelligence (AI) have emerged in the gastric cancer field based on its efficient computational power and learning capacities, such as image-based diagnosis and prognosis prediction. AI-assisted diagnosis includes pathology, endoscopy, and computerized tomography, while researchers in the prognosis circle focus on recurrence, metastasis, and survival prediction. In this review, a comprehensive literature search was performed on articles published up to April 2020 from the databases of PubMed, Embase, Web of Science, and the Cochrane Library. Thereby the current status of AI-applications was systematically summarized in gastric cancer. Moreover, future directions that target this field were also analyzed to overcome the risk of overfitting AI models and enhance their accuracy as well as the applicability in clinical practice.

Keywords: Gastric cancer; Image-based diagnosis; Prognosis prediction; Artificial intelligence; Machine learning; Deep learning

Core Tip: Recently, several applications of artificial intelligence have emerged in the gastric cancer field based on its efficient computational power and learning capacities, such as image-based diagnosis and prognosis prediction. In this review, we searched the relevant works published up to April 2020 from the databases of PubMed, Embase, Web of Science, and the Cochrane Library, thus comprehensively summarizing the current status of artificial intelligence applications in gastric cancer. In addition, challenges and future directions that target the field are also discussed to improve the accuracy and applicability of artificial intelligence models in clinical practice.