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Outcome prediction from clinical text can prevent doctors from overlooking possible risks and help hospitals to plan capacities.
Longformer: The Long-Document Transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020 · 2004
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Viewpoint Paper: Evaluating the State-of-the-Art in Automatic De-identification
Özlem Uzuner, Yuan Luo, and Peter Szolovits. 2007 · 2007
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Viewpoint Paper: Identifying Patient Smoking Status from Medical Discharge Records
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2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text
Özlem Uzuner, Brett R. South, Shuying Shen, and Scott L. DuVall. 2011 · 2010
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Evaluating temporal relations in clinical text: 2012 i2b2 Challenge
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Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/UTHealth shared task Track 1
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MIMIC-III, a freely accessible critical care database
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Factors affecting length of stay in teaching hospitals of a middle-income country
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Generating Multi-label Discrete Patient Records using Generative Adversarial Networks
Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter F. Stewart, and Jimeng Sun. 2017 · 2017
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What’s in a Note? Unpacking Predictive Value in Clinical Note Representations
Willie Boag, Dustin Doss, Tristan Naumann, and Peter Szolovits. 2018 · 2018
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MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
Edward Choi, Cao Xiao, Walter F. Stewart, and Jimeng Sun. 2018 · 2018
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Deep EHR: Chronic Disease Prediction Using Medical Notes
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Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU
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A Neural Architecture for Automated ICD Coding
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Deep Patient Representation of Clinical Notes via Multi-Task Learning for Mortality Prediction
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Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse
Dmitriy Dligach, Majid Afshar, and Timothy A. Miller. 2019 · 2019
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Ontological attention ensembles for capturing semantic concepts in ICD code prediction from clinical text
Matús Falis, Maciej Pajak, Aneta Lisowska, Patrick Schrempf, Lucas Deckers, Shadia Mikhael, Sotirios A. Tsaftaris, and Alison O’Neil. 2019 · 2019
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An Analysis of Attention over Clinical Notes for Predictive Tasks
Sarthak Jain, Ramin Mohammadi, and Byron C. Wallace. 2019 · 2019
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Using Clinical Notes with Time Series Data for ICU Management
Swaraj Khadanga, Karan Aggarwal, Shafiq R. Joty, and Jaideep Srivastava. 2019 · 2019
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ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission
Kexin Huang, Jaan Altosaar, and Rajesh Ranganath. 2019 · 2020
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Predicting Multiple ICD-10 Codes from Brazilian-Portuguese Clinical Notes
Arthur D. Reys, Danilo Silva, Daniel Severo, Saulo Pedro, Marcia M. de Souza e Sá, and Guilherme A. C. Salgado. 2020 · 2020
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Rudolf Schneider, Tom Oberhauser, Paul Grundmann, Felix Alexander Gers, Alexander Loeser, and Steffen Staab. 2020 · 2020
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Thomas Searle, Zina M. Ibrahim, and Richard J. B. Dobson. 2020 · 2020
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Big bird: Transformers for longer sequences
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BERT-XML: large scale automated ICD coding using BERT pretraining
Zachariah Zhang, Jingshu Liu, and Narges Razavian. 2020 · 2020
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