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Poster Presentation: USCAP 2022
Study Objective: To clinically validate the performance of an AI-based algorithm in the detection of gastric adenocarcinoma (AdC), high-grade (HG) dysplasia, and Helicobacter pylori (H. pylori), and to implement it in routine clinical workflow.
Conclusions:
- Galen Gastric (AI) demonstrated accurate detection of a broad range of pathological features in clinical use, including adenocarcinoma, HG dysplasia, H.pylori, being an effective and user-friendly diagnostic support tool for pathologists,
- The AI-powered Galen Gastric proposes a more cost-effective diagnosis workflow, enabling efficient detection of Helicobacter pylori together with reduction in turnaround time and minimizing ordering of additional stains.
- AI enables accurate detection of multiple pathological features beyond cancer detection, such as adenoma, LG dysplasia, neuroendocrine neoplasms and more.
