Artificial intelligence (AI) was first described in 1950; however, several limitations in early
models prevented widespread acceptance and application to medicine. In the early 2000s …

Background and Aims Deep learning is an innovative algorithm based on neural networks.
Wireless capsule endoscopy (WCE) is considered the criterion standard for detecting small …

Background Artificial intelligence (AI)-based polyp detection systems are used during
colonoscopy with the aim of increasing lesion detection and improving colonoscopy quality …

1 ESGE suggests that high definition endoscopy, and dye or virtual chromoendoscopy, as
well as add-on devices, can be used in average risk patients to increase the endoscopist's …

Background We have developed the computer-aided detection (CADe) system using an
original deep learning algorithm based on a convolutional neural network for assisting …

Background and Aims Artificial intelligence (AI) is being implemented in colonoscopy
practice, but no study has investigated whether AI is cost saving. We aimed to quantify the …

Machine learning is increasingly integrated into clinical practice, with applications ranging
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …

Abstract Machine vision is being employed in defect detection, size measurement, pattern
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …

There has been a vast increase in GI literature focused on the use of machine learning in
endoscopy. The relative novelty of this field poses a challenge for reviewers and readers of …

Artificial intelligence (AI) has already been implemented widely in the medical field in the
recent years. This paper first reviews the background of AI and radiotherapy. Then it …