Application of Artificial Intelligence on the Diagnosis of Helicobacter Pylori Infection and Premalignant Gastric Lesion: A Randomized Clinical Trial

This is a randomized clinical trial designed to evaluate the effectiveness of AI-assisted endoscopy compared with routine endoscopy in reducing gastric cancer-specific mortality. Participants will be allocated in a 1:1 ratio using a computer-generated randomization sequence after eligibility assessment and informed consent. One group will receive artificial intelligence-assisted interpretation for physician reference, while the control group will undergo routine endoscopy without AI assistance. In routine clinical practice, patients diagnosed with H. pylori infection receive antibiotic eradication therapy to reduce the risk of gastric cancer incidence and mortality, while those with premalignant gastric conditions are generally advised to undergo surveillance upper endoscopy every two years. We hypothesize that AI-assisted interpretation may further reduce gastric cancer-specific mortality through two mechanisms: (1) improved detection of H. pylori infection, enabling timely eradication therapy; and (2) earlier identification of gastric cancer via AI-supported detection of premalignant gastric conditions and appropriate recommendations for surveillance endoscopy. The primary endpoint is gastric cancer-specific mortality.