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Artificial intelligence in gastric cancer: applications and challenges

文献类型：期刊论文

作者Cao, Runnan7,8; Tang, Lei6; Fang, Mengjie3,7,8; Zhong, Lianzhen7,8; Wang, Siwen7,8; Gong, Lixin4,5; Li, Jiazheng6; Dong, Di1,7,8; Tian, Jie2,3
刊名GASTROENTEROLOGY REPORT
出版日期2022-01-25
卷号10页码:16
关键词gastric cancer artificial intelligence radiomics endoscopy computed tomography pathology
ISSN号2052-0034
DOI10.1093/gastro/goac064
通讯作者Dong, Di(di.dong@ia.ac.cn) ; Tian, Jie(jie.tian@ia.ac.cn)
英文摘要Gastric cancer (GC) is one of the most common malignant tumors with high mortality. Accurate diagnosis and treatment decisions for GC rely heavily on human experts' careful judgments on medical images. However, the improvement of the accuracy is hindered by imaging conditions, limited experience, objective criteria, and inter-observer discrepancies. Recently, the developments of machine learning, especially deep-learning algorithms, have been facilitating computers to extract more information from data automatically. Researchers are exploring the far-reaching applications of artificial intelligence (AI) in various clinical practices, including GC. Herein, we aim to provide a broad framework to summarize current research on AI in GC. In the screening of GC, AI can identify precancerous diseases and assist in early cancer detection with endoscopic examination and pathological confirmation. In the diagnosis of GC, AI can support tumor-node-metastasis (TNM) staging and subtype classification. For treatment decisions, AI can help with surgical margin determination and prognosis prediction. Meanwhile, current approaches are challenged by data scarcity and poor interpretability. To tackle these problems, more regulated data, unified processing procedures, and advanced algorithms are urgently needed to build more accurate and robust AI models for GC.
WOS关键词HELICOBACTER-PYLORI INFECTION ; CONVOLUTIONAL NEURAL-NETWORKS ; ENDOSCOPIC ULTRASONOGRAPHY ; CT GASTROGRAPHY ; DIAGNOSIS ; IMAGES ; CLASSIFICATION ; RADIOMICS ; TUMORS ; RISK
资助项目National Natural ScienceFoundation of China ; National Key R&D Program of China[82022036] ; National Key R&D Program of China[91959130] ; National Key R&D Program of China[81971776] ; National Key R&D Program of China[62027901] ; National Key R&D Program of China[81930053] ; Beijing Natural Science Foundation[2017YFA0205200] ; Strategic Priority Research Program of Chinese Academy of Sciences[Z20J00105] ; Youth Innovation Promotion Association CAS[XDB38040200] ; [Y2021049]
WOS研究方向Gastroenterology & Hepatology
语种英语
WOS记录号WOS:000892487000003
出版者OXFORD UNIV PRESS
资助机构National Natural ScienceFoundation of China ; National Key R&D Program of China ; Beijing Natural Science Foundation ; Strategic Priority Research Program of Chinese Academy of Sciences ; Youth Innovation Promotion Association CAS
源URL[http://ir.ia.ac.cn/handle/173211/50836]  
专题自动化研究所_中国科学院分子影像重点实验室
通讯作者Dong, Di; Tian, Jie
作者单位1.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China
2.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian, Shaanxi, Peoples R China
3.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Engn Med, Beijing, Peoples R China
4.Northeastern Univ, Biol Informat Engn Sch, Shenyang, Liaoning, Peoples R China
5.Northeastern Univ, Coll Med, Shenyang, Liaoning, Peoples R China
6.Peking Univ Canc Hosp & Inst, Radiol Dept, Key Lab Carcinogenesis & Translat Res, Minist Educ Beijing, Beijing, Peoples R China
7.Chinese Acad Sci, CAS Key Lab Mol Imaging, Beijing Key Lab Mol Imaging, Inst Automat,State Key Lab Management & Control Co, Beijing, Peoples R China
8.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Cao, Runnan,Tang, Lei,Fang, Mengjie,et al. Artificial intelligence in gastric cancer: applications and challenges[J]. GASTROENTEROLOGY REPORT,2022,10:16.
APA Cao, Runnan.,Tang, Lei.,Fang, Mengjie.,Zhong, Lianzhen.,Wang, Siwen.,...&Tian, Jie.(2022).Artificial intelligence in gastric cancer: applications and challenges.GASTROENTEROLOGY REPORT,10,16.
MLA Cao, Runnan,et al."Artificial intelligence in gastric cancer: applications and challenges".GASTROENTEROLOGY REPORT 10(2022):16.

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来源：自动化研究所

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