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Researchers developed Prov-GigaPath, a whole-slide pathology foundation model using a novel vision transformer architecture. The model demonstrates superior performance in mutation prediction, cancer subtyping, and vision-language tasks. It leverages large-scale real-world data from over 30,000 patients to enhance clinical diagnostics.

Convolutional neural networkLong sequence network longnetProvidence gigapixel pathology modelVision transformerLong sequence networkHierarchical image pyramid transformerContrastive learning based pathology modelData efficient generalizationSelf supervised machine learningDiagnostic imagingCancer genome atlasSimple frameworkContrastive learningVisual representationsAttention based multiple instance learningProvidence pathology