Artificial Intelligence
Artificial intelligence using convolutional neural networks for real-time detection of early esophageal neoplasia in Barrett’s esophagus (with video)
The visual detection of early esophageal neoplasia (high-grade dysplasia and T1 cancer) in Barrett’s esophagus (BE) with white-light and virtual chromoendoscopy still remains challenging. The aim of this study was to assess whether a convolutional neural artificial intelligence network can aid in the recognition of early esophageal neoplasia in BE.641 ARTIFICIAL INTELLIGENCE DYSPLASIA DETECTION (AIDD) ALGORITHM FOR BARRETT’S ESOPHAGUS
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.
