Artificial intelligence for disease diagnosis: the criterion standard challenge

Post written by Yuichi Mori, MD, PhD, from the Clinical Effectiveness Research Group, University of Oslo, and the Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway, and the Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan. The primary aim of this study was to focus attention on the major challenges that computer-aided …

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High pooled performance of convolutional neural networks in computer-aided diagnosis of GI ulcers and/or hemorrhage on wireless capsule endoscopy images

Post written by Babu P. Mohan, MD, from the Gastroenterology & Hepatology, University of Utah, Salt Lake City, Utah, USA. The study aimed to analyze the pooled rates of diagnostic accuracy parameters of computer-aided diagnosis (CAD) by convolutional neural networks (CNN)-based machine learning of wireless capsule endoscopy (WCE) images. Recent studies have reported on the …

Continue reading High pooled performance of convolutional neural networks in computer-aided diagnosis of GI ulcers and/or hemorrhage on wireless capsule endoscopy images

Introducing computer-aided detection to the endoscopy suite

Post written by Jeremy R. Glissen Brown, MD, from the Center for Advanced Endoscopy, Division of Gastroenterology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA. In this issue of VideoGIE, we are excited to present a video primer that outlines a computer-aided detection (CADe) system that we have applied prospectively during screening …

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