Скачать или смотреть Eduarda Almeida on “Artificial intelligence for endoscopic grading of gastric intestinal..."

Eduarda Almeida on “Artificial intelligence for endoscopic grading of gastric intestinal metaplasia: advancing risk stratification for gastric cancer”

In this study, an artificial intelligence (AI) approach for assessment of gastric intestinal metaplasia using the Endoscopic Grading of Gastric Intestinal Metaplasia (EGGIM) classification was developed and evaluated. Two datasets with 1280 narrow-band images were used. In 88%, an accurate indication for gastric surveillance (EGGIM ≥5) was achieved, with 85% specificity and no false-negative results. Positive and negative predictive values were 62% and 100%. AI tools for EGGIM assessment may contribute to improving the identification of patients at risk of gastric cancer.

Find the article at: https://doi.org/10.1055/a-2657-9906

Eduarda Almeida, Miguel Lopes Martins, David Marques et al.
Artificial intelligence for endoscopic grading of gastric intestinal metaplasia: advancing risk stratification for gastric cancer

Endoscopy 2025; 57: 1254–1260. © 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License