Tumor Subtype Prediction with Convolutional Neural Networks

Problem: A growing amount of research has demonstrated the ability to predict tumor genomic subtypes from H&E histopathology. But this capability may be stronger for some cancer types and biomarkers than for others. This project evaluated the ability of a baseline convolutional neural net solution to predict genomic subtype for a cancer type that had not been previously evaluated in this manner.

Solution: Using open source research code and transfer learning, this project measured the classification accuracy of a multiple instance learning model to predict genomic subtype.