We propose DisCeRn: Disease-Contrastive Representations from Multi-Modal Medical Data, a method for modifying contrastive loss by weighting negative pair of samples differently based on marginally related observed pathologies. The detailed project report and presentation can be found here and here respectively. This project is done in part of course CSC2541: ML in Healthcare
