Background: With the development of new technologies such as magnifying endoscopy with
narrow band imaging, endoscopists achieved better accuracy for diagnosis of gastric cancer …

Screening endoscopy improves detection and prognosis of patients with gastric cancer.
However, even expert endoscopists can miss early gastric cancer under standard white light …

Objectives Endoscopists' abilities to diagnose early gastric cancers (EGCs) vary, especially
between specialists and nonspecialists. We developed an artificial intelligence (AI)‐based …

Background Gastric cancer (GC) represents a malignancy with a multi-factorial combination
of genetic, environmental, and microbial factors. Targeting lysosomes presents significant …

Given the breakthroughs in key technologies, such as image recognition, deep learning and
neural networks, artificial intelligence (AI) continues to be increasingly developed, leading to …

Background This study aims to develop and validate a predictive model combining deep
transfer learning, radiomics, and clinical features for lymph node metastasis (LNM) in early …

Background Upper gastrointestinal cancers are aggressive malignancies with poor
prognosis, even following multimodality therapy. As such, they require timely and accurate …

Screening endoscopy has advanced to facilitate improvements in the detection and
prognosis of gastric cancer. However, most early gastric cancers (EGCs) have subtle …

Background and Aims Insufficient validation limits the generalizability of deep learning in
diagnosing Helicobacter pylori infection with endoscopic images. The aim of this study was …

Background An ever-increasing number of artificial intelligence (AI) models targeting
healthcare applications are developed and published every day, but their use in real-world …