Your Cancer &Data Science Club is back with a new event!
Computer Vision has great applications for cancer tissue classifications and diagnostics.
Recently, a preprint by @EMBL-BI went viral on Twitter, and we will try to understand what this fuss is about:
They trained a deep convolutional neural net in cancer histopathology *and* genomics using 14M images from 17k H&E slides across 28 cancer types. The outcome is stunning
— Pan-cancer computational histopathology analysis with deep learning extracts histopathological patterns and accurately discriminates 28 cancer and 14 normal tissue types
— Computational histopathology predicts whole genome duplications, focal amplifications and deletions, as well as driver gene mutations
— Wide-spread correlations with gene expression indicative of immune infiltration and proliferation
— Prognostic information augments conventional grading and histopathology subtyping in the majority of cancers
Speaker: Вячеслав Попіка, data scientist
Discussant: Mostafa Benhenda, data scientist