13 citations · 26 across the 6 of their papers we have counts for
3 papers · 1 filter
Rule induction for global explanation of trained models
Madhumita Sushil, Simon Šuster, Walter Daelemans
Understanding the behavior of a trained network and finding explanations for its outputs is important for improving the network's performance and generalization ability, and for en…
Patient representation learning and interpretable evaluation using clinical notes
Madhumita Sushil, Simon Šuster, Kim Luyckx +1
We have three contributions in this work: 1. We explore the utility of a stacked denoising autoencoder and a paragraph vector model to learn task-independent dense patient represen…
CliCR: A Dataset of Clinical Case Reports for Machine Reading Comprehension
Simon Šuster, Walter Daelemans
We present a new dataset for machine comprehension in the medical domain. Our dataset uses clinical case reports with around 100,000 gap-filling queries about these cases. We apply…