Post written by Pierce L. Claassen, MD, from Mayo Clinic, Internal Medicine, Scottsdale, Arizona, USA. The focus of our study was to evaluate the benefit of using computer-aided detection (CADe) in a rural medical center. It is known that CADe has the potential to increase adenoma detection rate (ADR), which is known to be associated with decreased …
Tag: Computer-aided
Deploying automated machine learning for computer vision projects: a brief introduction for endoscopists
Post written by Neal Mahajan, ScB, from the Division of Gastroenterology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, and Indiana University School of Medicine, Indianapolis, Indiana, USA. Our team has worked for several years on the use of machine learning (ML) in endoscopy and helped validate its additive effect in the endoscopy suite. We have noticed …
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 …
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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