Gastric cancer accounts for a significant proportion of worldwide cancer-related morbidity
and mortality. The well documented precancerous cascade provides an opportunity for …

Abstract Originally proposed by John McCarthy in 1955, artificial intelligence (AI) has
achieved a breakthrough and revolutionized the processing methods of clinical medicine …

Objectives Artificial intelligence (AI) uses deep learning functionalities that may enhance the
detection of early gastric cancer during endoscopy. An AI‐based endoscopic system for …

Simple Summary We previously constructed a VGG-16-based artificial intelligence (AI)
model (image classifier [IC]) to predict the invasion depth in early gastric cancer (EGC) using …

The gastrointestinal (GI) tract can be affected by different diseases or lesions such as
esophagitis, ulcers, hemorrhoids, and polyps, among others. Some of them can be …

We stand at the threshold of a new era: the incorporation of artificial intelligence (AI) into
routine gastrointestinal (GI) endoscopy practice to improve clinical performance. Preliminary …

Esophageal cancer is a major cause of cancer-related mortality worldwide, with significant
regional disparities. Early detection of precursor lesions is essential to improve patient …

Simple Summary We summarize the main components of the tumor microenvironment in
gastro-esophageal adenocarcinomas (GEA). In addition, we highlight past and present …

Diagnosing gastrointestinal cancer by classical means is a hazardous procedure. Years
have witnessed several computerized solutions for stomach disease detection and …

Background: The awareness on deep learning is rapidly increasing day by day and various
researchers have explored its application in cancer diagnostics. However, there is a need of …