Biomarker Prediction for Precision Medicine

Problem: An overwhelming amount of research over the last few years has demonstrated that a number of molecular tumor biomarkers can be predicted from H&E whole slide images. This is a weakly supervised classification problem as the model must learn which regions of tissue are associated with each class. A number of multiple instance learning approaches have been proposed to tackle this.

Solution: This project involved identifying the most promising approaches for building a robust and generalizable model for predicting a particular molecular biomarker. Open source code bases were used where suitable.