Post written by Mohamed Shiha, MRCP, from the Academic Unit of Gastroenterology, Sheffield Teaching Hospitals, Sheffield, UK. Adenoma detection rate (ADR) is the main quality indicator for the effectiveness of colonoscopy in preventing colorectal cancer. However, it is estimated that 1 in 4 adenomas are missed during colonoscopy. Recently, advances in artificial intelligence (AI) have enabled …
Tag: Artificial intelligence
Usefulness of artificial intelligence–assisted digital single-operator cholangioscopy as a second-opinion consultation tool during interhospital assessment of an indeterminate biliary stricture: a case report
Post written by Carlos Robles-Medranda, MD, FASGE, AGAF, from the Endoscopy Division, Instituto Ecuatoriano de Enfermedades Digestivas (IECED), Guayaquil, Ecuador. We describe a case of a patient cared for in a medical facility abroad (Colombia) who presented with jaundice and proximal common bile duct stenosis detected with MRCP. EUS identified a homogeneous hypoechoic lesion localized at …
Diagnostic accuracy of convolutional neural network–based machine learning algorithms in endoscopic severity prediction of ulcerative colitis: a systematic review and meta-analysis
Post written by Vinay Jahagirdar, MD, from the Department of Internal Medicine, University of Missouri Kansas City School of Medicine, Kansas City, Missouri, USA. The focus of our study was to assess the pooled diagnostic accuracy parameters of deep machine learning by means of convolutional neural network (CNN) algorithms in predicting the severity of ulcerative colitis …
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 …
Editor’s Choice: Computer-aided characterization of early cancer in Barrett’s esophagus on i-scan magnification imaging: a multicenter international study
GIE Associate Editor Seiichiro Abe, MD, PhD, FASGE, FJGES, highlights this article from the April issue: “Computer-aided characterization of early cancer in Barrett’s esophagus on i-scan magnification imaging: a multicenter international study” by Mohamed Hussein, MRCP, et al. Magnifying virtual chromoendoscopy is helpful in differentiating between dysplastic and nondysplastic lesions in patients with Barrett’s esophagus (BE), …
Artificial intelligence for detecting and delineating the extent of superficial esophageal squamous cell carcinoma and precancerous lesions under narrow-band imaging (with video)
Post written by Bing Hu, MD, from the Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, Sichuan, China. The focus of this study was to train an artificial intelligence (AI) system that could detect and delineate the extent of superficial esophageal squamous cell carcinoma (ESCC) and precancerous lesions under nonmagnified narrow-band imaging (NBI) and to …
Computer-aided characterization of early cancer in Barrett’s esophagus on i-scan magnification imaging: a multicenter international study
Post written by Mohamed Hussein, MRCP, from the Department of Gastroenterology, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom. We aimed to develop a computer-aided characterization system that could support the diagnosis of dysplasia in Barrett’s esophagus on magnification endoscopy. We also strived to assess the speeds of the networks in making this …
Editor’s Choice: Identification of patients with malignant biliary strictures using a cholangioscopy-based deep learning artificial intelligence (with video)
GIE Senior Associate Editor David L. Diehl, MD, highlights this article from the February issue: “Identification of patients with malignant biliary strictures using a cholangioscopy-based deep learning artificial intelligence (with video)” by Neil B. Marya, MD, et al. The assessment of indefinite biliary strictures is difficult because results of intraductal biopsy and cytologic brushing can be inconclusive. It …
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 …
Continue reading Artificial intelligence for disease diagnosis: the criterion standard challenge
Correlation of the detection rate of upper GI cancer with artificial intelligence score: results from a multicenter trial (with video)
Post written by Shi Wang, MD, from the Department of Endoscopy, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China. The quality of EGD is a prerequisite for a high detection rate of upper GI lesions, especially …
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