A graph-optimized deep learning framework for recognition of Barrett’s esophagus and reflux esophagitis

Role of Artificial Intelligence in the Diagnosis of Gastroesophageal Reflux Disease

“…The main aim of the study was to provide a framework for the diagnosis of Barrett's esophagus and reflux esophagitis in endoscopic images using DL techniques. Experimental results showed that this model achieved a classification recognition accuracy of 93.0%, with macro-precision, macro-recall, and macro-F scores of 93.5%, 92.9%, and 93.2%, respectively [28].…”