5 papers
ML4H Abstract Track 2019
Matthew B. A. McDermott, Emily Alsentzer, Sam Finlayson +5
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) workshop at NeurIPS 2019. This index is not complete, as some accepted abstracts chose to opt-out…
Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles
Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering +2
Modeling the relationship between chemical structure and molecular activity is a key goal in drug development. Many benchmark tasks have been proposed for molecular property predic…
Towards generative adversarial networks as a new paradigm for radiology education
Samuel G. Finlayson, Hyunkwang Lee, Isaac S. Kohane +1
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. Nevertheless,…
Privacy-Preserving Distributed Deep Learning for Clinical Data
Brett K. Beaulieu-Jones, William Yuan, Samuel G. Finlayson +1
Deep learning with medical data often requires larger samples sizes than are available at single providers. While data sharing among institutions is desirable to train more accurat…
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018
Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones +15
This volume represents the accepted submissions from the Machine Learning for Health (ML4H) workshop at the conference on Neural Information Processing Systems (NeurIPS) 2018, held…