Remo Monti

ContIG: Self-Supervised Multimodal Contrastive Learning for Medical Imaging With Genetics

High annotation costs are a substantial bottleneck in applying modern deep learning architectures to clinically relevant medical use cases, substantiating the need for novel algorithms to learn from unlabeled data. In this work, we propose ContIG, a self-supervised method that can learn from large d…