The gold standard and most widely used approach for screening and surveillance of
Barrett’s esophagus (BE) is esophagogastroduodenoscopy. However, the visual detection
of early esophageal neoplasia (high grade dysplasia and T1 stage adenocarcinoma) in
BE with white light and electronic virtual chromoendoscopy is still often difficult.
The aim of this study is to assess if a convolutional neural artificial intelligence
network can aid in the recognition of early esophageal neoplasia in BE.
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© 2019 Published by Elsevier Inc.
