Recent breakthroughs in artificial intelligence (AI), specifically via its emerging sub-field
“deep learning,” have direct implications for computer-aided detection and diagnosis (CADe …

Background Colonoscopy with computer-aided detection (CADe) has been shown in non-
blinded trials to improve detection of colon polyps and adenomas by providing visual alarms …

Introduction Eye tracking (ET) is a popular tool to study what factors affect the visual
behaviour of surgical team members. To our knowledge, there have been no reviews to date …

Background and Aims Up to 30% of adenomas might be missed during screening
colonoscopy—these could be polyps that appear on-screen but are not recognized by …

We developed and validated a deep-learning algorithm for polyp detection. We used a
YOLOv2 to develop the algorithm for automatic polyp detection on 8,075 images (503 …

Background Tandem colonoscopy studies have found that about one in five adenomas are
missed at colonoscopy. It remains debatable whether the combination of a computer-aided …

Background: Computer-aided detection (CADe) of colon polyps has been demonstrated to
improve colon polyp and adenoma detection during colonoscopy by indicating the location …

Background Multiple computer-aided systems for polyp detection (CADe) have been
introduced into clinical practice, with an unclear effect on examiner behavior. This study …

The latest state of the art technological innovations have led to a palpable progression in
endoscopic imaging and may facilitate standardisation of practice. One of the most rapidly …

Recent advances in neuroimaging technologies have rendered multimodal analysis of
operators' cognitive processes in complex task settings and environments increasingly more …