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 …

Background Accurate prediction of pathologic results for early gastric cancer (EGC) based
on endoscopic findings is essential in deciding between endoscopic and surgical resection …

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 …

In early gastric cancer (EGC), tumor invasion depth is an important factor for determining the
treatment method. However, as endoscopic ultrasonography has limitations when …

Background We developed an artificial intelligence (AI)-based endoscopic ultrasonography
(EUS) system for diagnosing the invasion depth of early gastric cancer (EGC), and we …

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) …

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 We aimed to develop and validate a deep learning–based system
that covers various aspects of early gastric cancer (EGC) diagnosis, including detecting …

Background and Aims Diagnosing the invasion depth of gastric cancer (GC) is necessary to
determine the optimal method of treatment. Although the efficacy of evaluating macroscopic …

Background Early gastric cancer (EGC) is defined as a lesion restricted to the mucosa or
submucosa, independent of size or evidence of regional lymph node metastases. Although …