Artificial Intelligence in Endoscopy

被引：10

作者：

Hann, Alexander ^{[1
]}

Meining, Alexander ^{[1
]}

机构：

[1] Univ Hosp Wurzburg, Dept Internal Med 2, Intervent & Expt Endoscopy InExEn, Gastroenterol, Wurzburg, Germany

来源：

VISCERAL MEDICINE | 2021年

关键词：

Artificial intelligence; Deep learning; Endoscopy; COMPUTER-AIDED DETECTION; COLORECTAL-CANCER; ADENOMA DETECTION; GASTROINTESTINAL ENDOSCOPY; PERFORMANCE-MEASURES; EUROPEAN-SOCIETY; COLONOSCOPY; TIME; POLYPS; SYSTEM;

D O I：

10.1159/000519407

中图分类号：

R57 [消化系及腹部疾病];

学科分类号：

摘要：

Background: Owing to their rapid development, artificial intelligence (AI) technologies offer a great promise for gastroenterology practice and research. At present, AI-guided image interpretation has already been used with success for endoscopic detection of early malignant lesions. Nonetheless, there are complex challenges and possible shortcomings that must be considered before full implementation can be realized. Summary: In this review, the current status of AI in endoscopy is summarized. Future perspectives and open questions for further studies are stressed. Key Messages: The usage of AI algorithms for polyp detection in screening colonoscopy results in a significant increase in the adenoma detection rate, mainly attributed to the identification of diminutive polyps. Computer-aided characterization of colorectal polyps accompanies the detection, but further studies are needed to evaluate the clinical benefit. In contrast to colonoscopy, usage of AI in gastroscopy is currently rather limited. Regarding other fields of endoscopic imaging, capsule endoscopy is the ideal imaging platform for AI, due to the potential of saving time in the video analysis. </p>

引用

页码：471 / 475

页数：5

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