Artificial intelligence in gastric cancer: Application and future perspectives

被引：82
作者：
Niu, Peng-Hui [1 ]
Zhao, Lu-Lu [1 ]
Wu, Hong-Liang [2 ]
Zhao, Dong-Bing [1 ]
Chen, Ying-Tai [1 ]
机构：
[1] Chinese Acad Med Sci & Peking Union Med Coll, Dept Pancreat & Gastr Surg, Natl Clin Res Ctr Canc, Natl Canc Ctr,Canc Hosp, Beijing 100021, Peoples R China
[2] Chinese Acad Med Sci & Peking Union Med Coll, Canc Hosp, Natl Clin Res Ctr Canc, Dept Anesthesiol,Natl Canc Ctr, Beijing 100021, Peoples R China
来源：
WORLD JOURNAL OF GASTROENTEROLOGY | 2020年 / 26卷 / 36期
基金：
国家重点研发计划;
关键词：
Gastric cancer; Image-based diagnosis; Prognosis prediction; Artificial intelligence; Machine learning; Deep learning; WHOLE-SLIDE IMAGES; NEURAL-NETWORKS; PREDICTION; DIAGNOSIS; CLASSIFICATION; ENDOSCOPY; SYSTEM; IDENTIFICATION; SEGMENTATION; VALIDATION;
D O I：
10.3748/wjg.v26.i36.5408
中图分类号：
R57 [消化系及腹部疾病];
学科分类号：
摘要：
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.
引用
收藏
页码：5408 / 5419
页数：13
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