Abstract Purpose of Review Recently numerous researchers have shown remarkable
progress using convolutional neural network-based artificial intelligence (AI) for endoscopy …

Background Recent developments in artificial intelligence (AI) systems have enabled
advancements in endoscopy. Deep learning systems, using convolutional neural networks …

Abstract Background and Aim The utility of artificial intelligence (AI) in colonoscopy has
gained popularity in current times. Recent trials have evaluated the efficacy of deep …

Abstract Purpose of Review Artificial intelligence (AI) is a rapidly growing field in
gastrointestinal endoscopy, and its potential applications are virtually endless, with studies …

Background and study aims With the advent of deep neural networks (DNN) learning, the
field of artificial intelligence (AI) is rapidly evolving. Recent randomized controlled trials …

Today gastroenterologists face the challenge of how to perceive and interpret the high
volume—about 30 highdefinition frames per s—of rich visual data presented in real time …

Background This meta-analysis aimed to determine whether artificial intelligence (AI)
improves colonoscopy outcome metrics ie adenoma detection rate (ADR) and polyp …

Abstract Background and Aims Randomized controlled trials (RCTs) have reported that
artificial intelligence (AI) improves endoscopic polyp detection. Different methodologies …

Artificial intelligence (AI) systems, especially after the successful application of
Convolutional Neural Networks, are revolutionizing modern medicine. Gastrointestinal …

Background Colonoscopy is a mainstay to detect premalignant neoplastic lesions in the
colon. Real-time Artificial Intelligence (AI)-aided colonoscopy purportedly improves the …