Abstract:Gastric Intestinal Metaplasia (GIM) is a precancerous histopathological change. During the process of atrophic gastritis, intestinal epithelial cells replace the normal gastric mucosa. The clinical significance of intestinal metaplasia is to suggest the risk of gastric cancer. Gastric mucosa with extensive intestinal metaplasia background has a higher risk of gastric cancer. In addition, incomplete intestinal metaplasia is associated with intestinal-type gastric cancer, so endoscopic monitoring of intestinal metaplasia is of great significance for timely detection and management of early gastric cancer. Meanwhile, OLGIM Grading provides a better risk assessment of gastric mucosal cancer which targets intestinal metaplasia, but every assessment requires standard biopsy, which increases the risk of injury. In this context, the Endoscopic Grading of Gastric Intestinal Metaplasia was proposed, but its application is limited by the accuracy of endoscopic diagnosis of intestinal metaplasia and the convenience of clinical use. We analyzed the diagnostic effects of various endoscopic diagnostic techniques on intestinal metaplasia, combined with artificial intelligence assisted identification of intestinal metaplasia area, and reviewed the feasibility of EGGIM score.