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 …

Capsule endoscopy is ideally suited to artificial intelligence‐based interpretation given its
reliance on pattern recognition in still images. Time saving viewing modes and lesion …

Capsule endoscopy (CE) emerged out of the pressing clinical need to image the small
bowel (SB) in cases of midgut bleeding and provide an overall comfortable and reliable …

Capsule endoscopy (CE) has been increasingly utilised in recent years as a minimally
invasive tool to investigate the whole gastrointestinal (GI) tract and a range of capsules are …

Background and study aims Capsule endoscopy (CE) is the preferred method for small
bowel (SB) exploration. With a mean number of 50,000 SB frames per video, SBCE reading …

Background Further development of deep learning-based artificial intelligence (AI)
technology to automatically diagnose multiple abnormalities in small-bowel capsule …

BACKGROUND: Data about strategies for improving the diagnostic ability of capsule
endoscopy readers are lacking. AIM:(1) To evaluate the detection rate and the interobserver …

Simple Summary The exponential growth in artificial intelligence development, particularly
its application in capsule endoscopy, serves as a compelling model for gastroenterologists …

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 …

Background Although great advances in artificial intelligence for interpreting small bowel
capsule endoscopy (SBCE) images have been made in recent years, its practical use is still …