Background The aim of this study was to investigate the efficacy of diagnosing depth of wall
invasion of gastric cancer on endoscopic images using computer-aided pattern recognition …

Endoscopic resection is recommended for gastric neoplasms confined to mucosa or
superficial submucosa. The determination of invasion depth is based on gross morphology …

Abstract Background and Aim Recently, artificial intelligence (AI) has been used in
endoscopic examination and is expected to help in endoscopic diagnosis. We evaluated the …

Background and study aims The diagnostic ability of endoscopists to determine invasion
depth of early gastric cancer is not favorable. We designed an artificial intelligence (AI) …

Background and Aims According to guidelines, endoscopic resection should only be
performed for patients whose early gastric cancer invasion depth is within the mucosa or …

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 …

Artificial intelligence (AI) for GI endoscopy is an important and rapidly growing area of
research. Much initial work in AI for endoscopy has focused on detection and optical …

Background and Aims This study aimed to evaluate the accuracy and effectiveness of the
convolutional neural network (CNN) in diagnosing gastric cancer and predicting the …

Background Gastric cancer is a common kind of malignancies, with yearly occurrences
exceeding one million worldwide in 2017. Typically, ulcerous and cancerous tissues …

BACKGROUND: Although conventional endoscopy is a good diagnostic tool to evaluate
tumor depth (T staging) in early gastric cancer (EGC), its accuracy has not been determined …