110 citations · 174 across the 11 of their papers we have counts for
4 papers · 1 filter
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…
Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes
Brett K. Beaulieu-Jones, Isaac S. Kohane, Andrew L. Beam
Biomedical association studies are increasingly done using clinical concepts, and in particular diagnostic codes from clinical data repositories as phenotypes. Clinical concepts ca…
Adversarial Attacks Against Medical Deep Learning Systems
Samuel G. Finlayson, Hyung Won Chung, Isaac S. Kohane +1
The discovery of adversarial examples has raised concerns about the practical deployment of deep learning systems. In this paper, we demonstrate that adversarial examples are capab…
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data
Andrew L. Beam, Benjamin Kompa, Allen Schmaltz +6
Word embeddings are a popular approach to unsupervised learning of word relationships that are widely used in natural language processing. In this article, we present a new set of…