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We read with interest the article by van der Sommen et al,1 and assert some important and relevant points of adopting artificial intelligence (AI)-assisted endoscopy in clinical practice. Computer-aided diagnosis systems have successfully applied to all segments of the GI tract, even the diagnosis of dysplasia in Barrett’s oesophagus which is the bane of expert endoscopists.2 Recently, colonoscopy with real-time computer-aided detection (CADe) systems achieved higher polyp detection as compared with the performance of expert endoscopists.3 However, in adopting CADe to conventional oesophagogastroduodenoscopy (OGD), related discussions for improving the detection of hard-to-find gastric cancers (GC) are inevitable.
The stomach has a wider, bent lumen, implicating more laborious gastric observations without a blind spot, compared with other GI tract anatomical features such as the oesophagus and colon. In routine OGD, the endoscopists have to distinguish gastric neoplasms from surrounding gastritis mucosa at more distant view, as opposed to detection of colorectal neoplasms and Barrett-related dysplasia by near-view images. In addition, early GCs usually show subtle elevation or depression and their irregular appearances easily hide in the coarse background gastritis caused by Helicobacter pylori infection. Therefore, it is sometimes difficult even for experts to discover early GCs, particularly smaller …