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Prognostic prediction of gastric cancer based on H&E findings and machine learning pathomics

30 Sept 2024

Abstract excerpt

AIM: In this research, we aimed to develop a model for the accurate prediction of gastric cancer based on H&E findings combined with machine learning pathomics. METHODS: Transcriptome data, pathological images, and clinical data from 443 cases were retrieved from TCGA (The Cancer Genome Atlas Program) for survival analysis. The images were segmented using the Otsu algorithm, and features were extracted using the...

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PMID: 39299554
DOI: 10.1016/j.mcp.2024.101983

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