Publication: Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning
Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning
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Sirinukunwattana, K., Domingo, E., Richman, S., et al, & Koelzer, V. H. (2019). Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning (No. 645143; BioRxiv). https://doi.org/10.1101/645143
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Image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data. Here we predict consensus molecular subtypes (CMS) of colorectal cancer (CRC) from standard H&E sections using deep learning. Domain adversarial training of a neural classification network was performed using 1,553 tissue sections with comprehensive multi- omic data from three independent datasets. Image-based consensus molecular subtyping (imCMS) accurately classified CRC whole-slide images and preoperativ
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Sirinukunwattana, K., Domingo, E., Richman, S., et al, & Koelzer, V. H. (2019). Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning (No. 645143; BioRxiv). https://doi.org/10.1101/645143
