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馃挕Insights from #AACR26 poster "Lauren subtype classification in gastric cancer using deep learning on real-world H&E images"

The research team developed a deep learning classifier to automate Lauren subtype assignment in gastric cancer, addressing the inter-observer variability and scalability challenges of manual pathologist review. By analyzing de-identified H&E-stained images from 637 patient samples in the Tempus real-world database, the model achieved robust performance.

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CBACBA Frontier Insights (CFI)Chinese Biopharmaceutical Association (CBA)www.cba-usa.org