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DeepPathFinder™

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DeepPathFinder™ can lead you to deep-dive 
into tumor microenviromnent

By using not only pathologist annotation but also masked data with multiple IHC as training data.
It is feasible to identify cells on H&E stained slides that are not distinguishable by human perception.

Extract information from morphological features, such as genetic mutations that is difficult to obtain without genomic testing. [Publication]

  • BRAF, KRAS and MSI-H and so on

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A spatial combination of the obtained features is used to predict patient prognosis and drug efficacy. [Publication]

  • Predicting prognosis and drug efficacy from pathological features

Multidimensional features can be obtained from cell/tissue features

  • TILs count and density in stroma

  • Fibroblast count and density in stroma

  • Distance from tumor area and each lymphocyte

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Quantifying IHC imaging and combination analysis with H&E image

  • HER2, ER, PgR, Ki-67

Workflow

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