Evaluating an AI System to Automatically Score Gastric Intestinal Metaplasia Using the EGGIM Method in Patients Aged 40 to 75 Years

What this Trial Is About

This research aims to evaluate an artificial intelligence AI system designed to automatically assess the extent of gastric intestinal metaplasia GIM during endoscopy by calculating the EGGIM scores. Gastric intestinal metaplasia is an important precancerous condition, and the study seeks to validate the accuracy, performance, and reliability of this AI-assisted scoring method in a prospective, multi-center setting. Participants will undergo an image-enhanced endoscopy IEE examination, where both experienced endoscopists and the AI system independently assess the extent of GIM using the EGGIM score. This study builds on prior preliminary research and aims to confirm the AI systems diagnostic performance compared to human experts. During the study, patients aged 40 to 75 years who consent to participate will have their endoscopic images evaluated by both the AI and the endoscopists. The main outcome measured is how well the AI system diagnoses the grade of intestinal metaplasia by calculating the EGGIM score within one year. This observational study involves no experimental treatments, focusing on diagnostic evaluation and data collection over the study period.

Artificial Intelligence in Assessing Gastric Intestinal Metaplasia Via the EGGIM Score