The use of artificial intelligence-based tools is regarded as a promising approach to
increase clinical efficiency in diagnostic imaging, improve the interpretability of results, and …

Gastrointestinal (GI) disease is one of the most common diseases and primarily examined
by GI endoscopy. Recently, deep learning (DL), in particular convolutional neural networks …

Automatic detection of diseases and anatomical landmarks in medical images by the use of
computers is important and considered a challenging process that could help medical …

Gastrointestinal (GI) diseases constitute a leading problem in the human digestive system.
Consequently, several studies have explored automatic classification of GI diseases as a …

Background In recent years, deep learning has gained remarkable attention in medical
image analysis due to its capacity to provide results comparable to specialists and, in some …

Abstract Machine learning (ML)-and deep learning (DL)-based imaging modalities have
exhibited the capacity to handle extremely high dimensional data for a number of computer …

The development of convolutional neural networks has achieved impressive advances of
machine learning in recent years, leading to an increasing use of artificial intelligence (AI) in …

Extensive implementation of artificial intelligence (AI) in the field of medical diagnosis has
been expected for half a century. For a long time, the leading methods to AI were based on …

The clinical application of a real-time artificial intelligence (AI) image processing system to
diagnose upper gastrointestinal (GI) malignancies remains an experimental research and …

Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for
several purposes, including,(1) making a clinical diagnosis, in real time, based on the visual …