Background: Gastric cancer (GC), a significant health burden worldwide, is typically
diagnosed in the advanced stages due to its non-specific symptoms and complex …

Purpose: Gastric cancer remains the leading cause of cancer-related deaths in Northeast
Asia. Population-based endoscopic screenings in the region have yielded successful results …

Background Deep learning models have previously been established to predict the
histopathology and invasion depth of gastric lesions using endoscopic images. This study …

Gastric cancer (GC) is one of the most common malignant tumors with high mortality.
Accurate diagnosis and treatment decisions for GC rely heavily on human experts' careful …

Stomach cancer has a high annual mortality rate worldwide necessitating early detection
and accurate treatment. Even experienced specialists can make erroneous judgments …

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 …

Previous studies on deep learning (DL) applications in pathology have focused on
pathologist-versus-algorithm comparisons. However, DL will not replace the breadth and …

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 …

Artificial intelligence and disease detection go hand in hand. Convolutional neural networks,
a significant area of artificial intelligence applications, are crucial in the detection of stomach …

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 …