Artificial Intelligence in Endoscopy

Please always quote using this URN: urn:nbn:de:bvb:20-opus-352461
  • 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 forBackground: 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.show moreshow less

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Metadaten
Author: Alexander Hann, Alexander Meining
URN:urn:nbn:de:bvb:20-opus-352461
Document Type:Journal article
Faculties:Medizinische Fakultät / Medizinische Klinik und Poliklinik II
Language:English
Parent Title (English):Visceral Medicine
Year of Completion:2021
Volume:37
Pagenumber:471-475
Source:Visceral Medicine (2021) 37:471-475. https://doi.org/10.1159/000519407
DOI:https://doi.org/10.1159/000519407
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:artificial intelligence; deep learning; endoscopy
Release Date:2024/11/27
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International