The Improvement Effect of Real-time Artificial Intelligence Assisted Identification of Bleeding Points on Hemostasis Efficiency in Endoscopic Submucosal Dissection

Brief Summary

The goal of this clinical trial is to learn if an artificial intelligence (AI) system that identifies bleeding points in real time can help stop bleeding faster during endoscopic submucosal dissection (ESD) - a minimally invasive surgery for early digestive tract cancer or precancerous lesions. It will also learn about the AI system's effect on surgery-related problems (like perforation or delayed bleeding) and total surgery time. The main questions it aims to answer are: 1. Does the AI system shorten the time it takes to stop each bleed during ESD? 2. How does the AI system affect the rate of surgery-related problems and total surgery time? Researchers will compare two groups to see if the AI system improves hemostasis efficiency: 1. AI group: During ESD, the AI system will real-time spot and mark bleeding points. Doctors will use these marks to stop bleeding. 2. Control group: Doctors will use the same equipment but without the AI system - they will find and stop bleeding using their own experience. Participants will: 1. Have ESD surgery for esophageal, stomach, or colorectal lesions that need this treatment; 2. Be randomly assigned to either the AI group or the control group; 3. Attend follow-up checks in 14 days after surgery to check for complications; 4. Have their surgery videos reviewed by experts to record hemostasis time and total surgery time.