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MIMIC-III, a freely accessible critical care database
TLDR
MIMIC-III (‘Medical Information Mart for Intensive Care’) is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. Expand
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What Is a Knowledge Representation?
TLDR
We go back to basics to address the question of knowledge representation and show that the answer can best be understood in terms of five different roles that a representation plays, each of which places different and, at times, conflicting demands on the properties a representation should have. Expand
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De-identification of patient notes with recurrent neural networks
TLDR
We introduce the first de-identification system based on artificial neural networks (ANNs), which requires no handcrafted features or rules, unlike existing systems. Expand
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Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment
TLDR
We present the TextFooler, a general attack framework, to generate natural adversarial texts for text classification and textual entailment tasks. Expand
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Viewpoint Paper: Evaluating the State-of-the-Art in Automatic De-identification
TLDR
We conducted a de-identification challenge on automatically removing private health information (PHI) from medical discharge records. Expand
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Automated de-identification of free-text medical records
TLDR
We describe an automated Perl-based de-identification software package that is generally usable on most free-text medical records, e.g., nursing notes, discharge summaries, X-ray reports, etc. Expand
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NeuroNER: an easy-to-use program for named-entity recognition based on neural networks
TLDR
In this paper, we present NeuroNER, an easy-to-use named-entity recognition tool based on ANNs. Expand
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A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data
TLDR
We evaluate the use of multivariate timeseries modeling with the multi-task Gaussian process (GP) models using noisy, incomplete, sparse, heterogeneous and unevenly-sampled clinical data, including both physiological signals and clinical notes. Expand
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Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment
TLDR
We present TextFooler, a simple but strong baseline to generate natural adversarial text that outperforms state-of-the-art attacks in terms of success rate and perturbation rate. Expand
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Implementing electronic medical record systems in developing countries.
The developing world faces a series of health crises including HIV/AIDS and tuberculosis that threaten the lives of millions of people. Lack of infrastructure and trained, experienced staff areExpand
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