Upper gastrointestinal (GI) neoplasia account for 35% of GI cancers and 1.5 million cancer-
related deaths every year. Despite its efficacy in preventing cancer mortality, diagnostic …

The clinical application of a real-time artificial intelligence (AI) image processing system to
diagnose upper gastrointestinal (GI) malignancies remains an experimental research and …

With recent breakthroughs in artificial intelligence, computer‐aided diagnosis (CAD) for
upper gastrointestinal endoscopy is gaining increasing attention. Main research focuses in …

Objective Artificial intelligence (AI) may reduce underdiagnosed or overlooked upper GI
(UGI) neoplastic and preneoplastic conditions, due to subtle appearance and low disease …

With recent significant improvements in artificial intelligence (AI), especially in the field of
deep learning, an increasing number of studies have evaluated the use of AI in endoscopy …

Background Upper gastrointestinal cancers (including oesophageal cancer and gastric
cancer) are the most common cancers worldwide. Artificial intelligence platforms using deep …

Background and Aims Artificial intelligence (AI), specifically deep learning, offers the
potential to enhance the field of GI endoscopy in areas ranging from lesion detection and …

ABSTRACT Background and Aims Diagnosis of esophageal cancer or precursor lesions by
endoscopic imaging depends on endoscopist expertise and is inevitably subject to …

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

Background & Aims We aimed to develop and validate a deep-learning computer-aided
detection (CAD) system, suitable for use in real time in clinical practice, to improve …