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The accelerated adoption of digital pathology and advances in deep learning have enabled the development of powerful models for various pathology tasks across a diverse array of diseases and patient cohorts.
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An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images
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Rna-to-image multi-cancer synthesis using cascaded diffusion models
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Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer
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Pathnarratives: Data annotation for pathological human-ai collaborative diagnosis
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Leveraging medical twitter to build a visual–language foundation model for pathology ai
Huang, Z., Bianchi, F., Yuksekgonul, M., Montine, T. & Zou, J · 2023
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