Gastric cancer has a high mortality rate worldwide, but it can be prevented with early
detection through regular gastroscopy. Herein, we propose a deep learning-based computer …

Background and Aims: To investigate the impact of the computer-assisted system on
esophagogastroduodenoscopy (EGD) training for novice trainees in a prospective …

Both traditional and wireless capsule endoscopes can generate tens of thousands of images
for each patient. It is desirable to have the majority of irrelevant images filtered out by …

Abstract Background and Objective Videocapsule endoscopy (VCE) is a relatively new
technique for evaluating the presence of villous atrophy in celiac disease patients. The …

Background and Aims Gastric precancerous conditions, including gastric atrophy (GA) and
intestinal metaplasia (IM), play an important role in the development of gastric cancer. Image …

Wireless capsule endoscopy (WCE) is a swallowable device used for screening different
parts of the human digestive system. Automatic WCE image analysis methods reduce the …

Capsule endoscopy identifies damaged areas in a patient's small intestine but often outputs
poor-quality images or misses lesions, leading to either misdiagnosis or repetition of the …

Deep learning (DL) based image processing methods have been successfully applied to
low-dose x-ray images based on the assumption that the feature distribution of the training …

Background and Aims Annually, 4 million people are affected by ulcers in the GI tract, and
poorly managed ulcers can lead to adverse events that may increase the risk of developing …

We read with interest the editorial by Hassan et al [1] entitled “AI everywhere in endoscopy,
not only for detection and characterization,” prompted by the recent paper of Hansen et al …