Background & Aims: Gastric cancer is the common malignancies from cancer worldwide.
Endoscopy is currently the most effective method to detect early gastric cancer (EGC) …

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

Purpose Management of peptic ulcer bleeding is clinically challenging. Accurate
characterization of the bleeding during endoscopy is key for endoscopic therapy. This study …

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

Objective The aim of this study was to assess the diagnostic ability of artificial intelligence
(AI) in the detection of early upper gastrointestinal cancer (EUGIC) using endoscopic …

Methods Investigators from Chulalongkorn University obtained 802 histological-proven GIM
images for AI model training. Four strategies were proposed to improve the model accuracy …

Gastric cancer (GC) is one of the most serious health problems worldwide. Chronic atrophic
gastritis (CAG) is most commonly caused by Helicobacter pylori (H. pylori) infection …

Background The ability of endoscopists to identify gastric lesions is uneven. Even
experienced endoscopists may miss or misdiagnose lesions due to heavy workload or …

Background The application of machine learning (ML) for identifying early gastric cancer
(EGC) has drawn increasing attention. However, there lacks evidence-based support for its …