Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy - Song, Ya-qi; Mao, Xin-li; Zhou, Xian-bin; He, Sai-qin; Chen, Ya-hong; Zhang, Li-hui; Xu, Shi-wen; Yan, Ling-ling; Tang, Shen-ping; Ye, Li-ping; Li, Shao-wei (Frontiers in Medicine, 2021)
With the rapid development of science and technology, artificial intelligence 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 artificial intelligence 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. Artificial intelligence can even perform quality control evaluations for endoscopists, improve the detection rate of endoscopic lesions and reduce the burden on endoscopists.