BACKGROUND: Difficulties in establishing diagnosis of small bowel (SB) disorders, prevented their effective treatment. This problem was largely resolved by wireless capsule endoscopy (WCE), which has since become the first line investigation for susp...
The manual reading of capsule endoscopy (CE) videos in small bowel disease diagnosis is time-intensive. Algorithms introduced to automate this process are premature for real clinical applications, and multi-diagnosis using these methods has not been ...
Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work demonstrates the promising ben...
Nutrition (Burbank, Los Angeles County, Calif.)
Oct 11, 2018
OBJECTIVE: The aim of this study was to evaluate kidney function outcome in adults on home parenteral nutrition (HPN) for chronic intestinal failure using the newly recommended equations for estimated glomerular filtration rate (eGFR) assessment in c...
African journal of primary health care & family medicine
Dec 9, 2015
BACKGROUND: In South Africa, studies on the prevalence of intestinal helminth co-infection amongst HIV-infected patients as well as possible interactions between these two infection sare limited.
Journal of gastroenterology and hepatology
Apr 1, 2021
The maturing development in artificial intelligence (AI) and genomics has propelled the advances in intestinal diseases including intestinal cancer, inflammatory bowel disease (IBD), and irritable bowel syndrome (IBS). On the other hand, colorectal c...
Journal of gastroenterology and hepatology
Jan 1, 2021
Neural network-based solutions are under development to alleviate physicians from the tedious task of small-bowel capsule endoscopy reviewing. Computer-assisted detection is a critical step, aiming to reduce reading times while maintaining accuracy. ...
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
May 1, 2020
BACKGROUND AND AIM: To examine whether our convolutional neural network (CNN) system based on deep learning can reduce the reading time of endoscopists without oversight of abnormalities in the capsule-endoscopy reading process.
BACKGROUND & AIMS: Capsule endoscopy has revolutionized investigation of the small bowel. However, this technique produces a video that is 8-10 hours long, so analysis is time consuming for gastroenterologists. Deep convolutional neural networks (CNN...
BACKGROUND AND AIMS: GI angiectasia (GIA) is the most common small-bowel (SB) vascular lesion, with an inherent risk of bleeding. SB capsule endoscopy (SB-CE) is the currently accepted diagnostic procedure. The aim of this study was to develop a comp...