Several machine learning algorithms have been developed in the past years with the aim to
improve SBCE (Small Bowel Capsule Endoscopy) feasibility ensuring at the same time a …

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 …

Background: Artificial intelligence (AI) is rapidly infiltrating multiple areas in medicine, with
gastrointestinal endoscopy paving the way in both research and clinical applications …

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 …

Abstract Background and Aim Convolutional neural network (CNN) systems that
automatically detect abnormalities from small‐bowel capsule endoscopy (SBCE) images are …

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 & 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 …

The role of capsule endoscopy and enteroscopy in managing various small-bowel
pathologies is well-established. However, their broader application has been hampered …

Objectives Poorly visualized images that appear during small bowel capsule endoscopy
(SBCE) can confuse the interpretation of small bowel lesions and increase the physician's …