Open AccessArtificial Intelligence in Endoscopy
Author(s) -
Alexander Hann,
Alexander Meining
Publication year - 2021
Publication title -
visceral medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.598
H-Index - 17
eISSN - 2297-475X
pISSN - 2297-4725
DOI - 10.1159/000519407
Subject(s) - colonoscopy , capsule endoscopy , endoscopy , medicine , adenoma , medical physics , radiology , artificial intelligence , computer science , pathology , colorectal cancer , cancer
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.