Artificial intelligence applications in pathological diagnosis of gastric cancer

被引:4
|
作者
Deng, Yang [1 ]
Qin, Hang-Yu [1 ]
Zhou, Yan-Yan [1 ]
Liu, Hong-Hong [1 ]
Jiang, Yong [2 ]
Liu, Jian-Ping [2 ]
Bao, Ji [1 ]
机构
[1] Sichuan Univ, Inst Clin Pathol, West China Hosp, Chengdu 610041, Sichuan, Peoples R China
[2] Sichuan Univ, West China Hosp, Dept Pathol, Chengdu 610041, Sichuan, Peoples R China
关键词
Gastric cancer; Pathological diagnosis; Artificial intelligence; Gastroenterology; HELICOBACTER-PYLORI INFECTION; CONVOLUTIONAL NEURAL-NETWORKS; WHOLE-SLIDE IMAGES; CLASSIFICATION; ENDOSCOPY; DISCRIMINATION; BENIGN; SYSTEM;
D O I
10.1016/j.heliyon.2022.e12431
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Globally, gastric cancer is the third leading cause of death from tumors. Prevention and individualized treatment are considered to be the best options for reducing the mortality rate of gastric cancer. Artificial intelligence (AI) technology has been widely used in the field of gastric cancer, including diagnosis, prognosis, and image analysis. Eligible papers were identified from PubMed and IEEE up to April 13, 2022. Through the comparison of these articles, the application status of AI technology in the diagnosis of gastric cancer was summarized, including application types, application scenarios, advantages and limitations. This review presents the current state and role of AI in the diagnosis of gastric cancer based on four aspects: 1) accurate sampling from early diagnosis (endoscopy), 2) digital pathological diagnosis, 3) molecules and genes, and 4) clinical big data analysis and prognosis prediction. AI plays a very important role in facilitating the diagnosis of gastric cancer; however, it also has shortcomings such as interpretability. The purpose of this review is to provide assistance to researchers working in this domain.
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页数:6
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