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Found 5 papers, 3 papers with code
Subgraph Neural Networks
Deep learning methods for graphs achieve remarkable performance on many node-level and graph-level prediction tasks.
Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles
Modeling the relationship between chemical structure and molecular activity is a key goal in drug development.
Privacy-Preserving Distributed Deep Learning for Clinical Data
Deep learning with medical data often requires larger samples sizes than are available at single providers.
Towards generative adversarial networks as a new paradigm for radiology education
Medical students and radiology trainees typically view thousands of images in order to "train their eye" to detect the subtle visual patterns necessary for diagnosis.
Adversarial Attacks Against Medical Deep Learning Systems
The discovery of adversarial examples has raised concerns about the practical deployment of deep learning systems.
