Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy

被引:14
作者
Song, Ya-Qi [1 ]
Mao, Xin-Li [2 ,3 ]
Zhou, Xian-Bin [2 ,3 ]
He, Sai-Qin [2 ,3 ]
Chen, Ya-Hong [4 ]
Zhang, Li-Hui [5 ]
Xu, Shi-Wen [6 ]
Yan, Ling-Ling [2 ,3 ]
Tang, Shen-Ping [6 ]
Ye, Li-Ping [1 ,2 ,3 ,7 ]
Li, Shao-Wei [2 ,3 ,7 ]
机构
[1] Zhejiang Univ, Taizhou Hosp, Linhai, Peoples R China
[2] Wenzhou Med Univ, Key Lab Minimally Invas Tech & Rapid Rehabil Dige, Taizhou Hosp, Linhai, Peoples R China
[3] Wenzhou Med Univ, Dept Gastroenterol, Taizhou Hosp Zhejiang Prov, Linhai, Peoples R China
[4] Wenzhou Med Univ, Hlth Management Ctr, Taizhou Hosp Zhejiang Prov, Linhai, Peoples R China
[5] Wuhan Univ, Dept Gastroenterol, Renmin Hosp, Wuhan, Peoples R China
[6] Wenzhou Med Univ, Taizhou Hosp Zhejiang Prov, Linhai, Peoples R China
[7] Wenzhou Med Univ, Inst Digest Dis, Taizhou Hosp Zhejiang Prov, Linhai, Peoples R China
关键词
application; artificial intelligence; quality control; improving; gastrointestinal endoscopy; COMPUTER-AIDED DIAGNOSIS; SYSTEM; ESOPHAGUS; FEEDBACK; CANCERS; PRIMER;
D O I
10.3389/fmed.2021.709347
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
With the rapid development of science and technology, artificial intelligence (AI) systems are becoming ubiquitous, and their utility in gastroenteroscopy is beginning to be recognized. Digestive endoscopy is a conventional and reliable method of examining and diagnosing digestive tract diseases. However, with the increase in the number and types of endoscopy, problems such as a lack of skilled endoscopists and difference in the professional skill of doctors with different degrees of experience have become increasingly apparent. Most studies thus far have focused on using computers to detect and diagnose lesions, but improving the quality of endoscopic examination process itself is the basis for improving the detection rate and correctly diagnosing diseases. In the present study, we mainly reviewed the role of AI in monitoring systems, mainly through the endoscopic examination time, reducing the blind spot rate, improving the success rate for detecting high-risk lesions, evaluating intestinal preparation, increasing the detection rate of polyps, automatically collecting maps and writing reports. AI can even perform quality control evaluations for endoscopists, improve the detection rate of endoscopic lesions and reduce the burden on endoscopists.
引用
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页数:8
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