Alexander Hann1, Alexander Meining1. 1. Interventional and Experimental Endoscopy (InExEn), Department of Internal Medicine II, Gastroenterology, University Hospital Würzburg, Würzburg, Germany.
Abstract
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.
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.
Authors: Raf Bisschops; Miguel Areia; Emmanuel Coron; Daniela Dobru; Bernd Kaskas; Roman Kuvaev; Oliver Pech; Krish Ragunath; Bas Weusten; Pietro Familiari; Dirk Domagk; Roland Valori; Michal F Kaminski; Cristiano Spada; Michael Bretthauer; Cathy Bennett; Carlo Senore; Mário Dinis-Ribeiro; Matthew D Rutter Journal: Endoscopy Date: 2016-08-22 Impact factor: 10.093
Authors: Harry R Aslanian; Frederick K Shieh; Francis W Chan; Maria M Ciarleglio; Yanhong Deng; Jason N Rogart; Priya A Jamidar; Uzma D Siddiqui Journal: Am J Gastroenterol Date: 2013-02 Impact factor: 10.864