Emerging role of artificial intelligence in GI endoscopy
Artificial intelligence (AI) is a broad descriptor term that includes machine learning (ML) in which the algorithm, based on the input raw data, analyzes features in a separate dataset without specifically being programmed and delivers a specified classification (Fig. 1). Deep learning techniques such as convolutional neural networks (CNNs) are transformative ML techniques that enable rapid and accurate image discrimination and classification and as such have many applications within medicine. In gastroenterology, CNNs have been used in several areas of GI endo scopy, including colorectal polyp detection, and classification, including assessment of the presence of advanced neoplasia in colonic polyps, evaluation of histologic inflammation in endocytoscopic images obtained during colonoscopy in patients with ulcerative colitis, analysis of endoscopic images for diagnosis of Helicobacter pylori infection, detection and depth assessment of early gastric cancer, dysplasia in Barrett’s esophagus, and detection of various abnormalities in wireless capsule endoscopy images (Table 1).
Source: Gastrointestinal Endoscopy - Category: Gastroenterology Authors: Rahul Pannala, Kumar Krishnan, Joshua Melson, Mansour A. Parsi, Allison R. Schulman, Shelby Sullivan, Guru Trikudanathan, Arvind J. Trindade, Rabindra R. Watson, John T. Maple, (previous Committee Chair, 2016-2019), David R. Lichtenstein, (American Societ Tags: Technology at the forefront Source Type: research
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