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Large-scale clinical data is invaluable to driving many computational scientific advances today.
Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, William W Cohen, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov. 2019 · 1901
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Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
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Computer-assisted de-identification of free text in the mimic ii database
Margaret Douglass, Gari D Clifford, Andrew Reisner, George B Moody, and Roger G Mark. 2004 · 2004
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Accuracy of veterans administration databases for a diagnosis of rheumatoid arthritis
Jasvinder A Singh, Aaron R Holmgren, and Siamak Noorbaloochi. 2004 · 2004
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Accuracy of icd-9-cm codes for identifying cardiovascular and stroke risk factors
Elena Birman-Deych, Amy D Waterman, Yan Yan, David S Nilasena, Martha J Radford, and Brian F Gage. 2005 · 2005
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Differential privacy: A survey of results
Cynthia Dwork. 2008 · 2008
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Automated de-identification of free-text medical records
Ishna Neamatullah, Margaret M Douglass, H Lehman Li-wei, Andrew Reisner, Mauricio Villarroel, William J Long, Peter Szolovits, George B Moody, Roger G Mark, and Gari D Clifford. 2008 · 2008
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Repurposing the clinical record: can an existing natural language processing system de-identify clinical notes?
Frances P Morrison, Li Li, Albert M Lai, and George Hripcsak. 2009 · 2009
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Broken promises of privacy: Responding to the surprising failure of anonymization
Paul Ohm. 2009 · 2009
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Semantic similarity and relatedness between clinical terms: an experimental study
Serguei Pakhomov, Bridget McInnes, Terrence Adam, Ying Liu, Ted Pedersen, and Genevieve B Melton. 2010 · 2010
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A systematic review of re-identification attacks on health data
Khaled El Emam, Elizabeth Jonker, Luk Arbuckle, and Bradley Malin. 2011 · 2011
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Data from clinical notes: a perspective on the tension between structure and flexible documentation
S Trent Rosenbloom, Joshua C Denny, Hua Xu, Nancy Lorenzi, William W Stead, and Kevin B Johnson. 2011 · 2011
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Generating text with recurrent neural networks
Ilya Sutskever, James Martens, and Geoffrey E Hinton. 2011 · 2011
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Recognizing textual entailment: Models and applications
Ido Dagan, Dan Roth, Mark Sammons, and Fabio Massimo Zanzotto. 2013 · 2013
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Bootstrapping a de-identification system for narrative patient records: cost-performance tradeoffs
David Hanauer, John Aberdeen, Samuel Bayer, Benjamin Wellner, Cheryl Clark, Kai Zheng, and Lynette Hirschman. 2013 · 2013
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Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence
Felix Köpcke, Benjamin Trinczek, Raphael W Majeed, Björn Schreiweis, Joachim Wenk, Thomas Leusch, Thomas Ganslandt, Christian Ohmann, Björn Bergh, Rainer Röhrig, et al. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. Corrado, and J. Dean. 2013 · 2013
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One billion word benchmark for measuring progress in statistical language modeling
C. Chelba, T. Mikolov, M.Schuster, Q. Ge, T. Brants, P. Koehn, and T. Robinson. 2014 · 2014
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Publishing data from electronic health records while preserving privacy: A survey of algorithms
Aris Gkoulalas-Divanis, Grigorios Loukides, and Jimeng Sun. 2014 · 2014
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Assisted annotation of medical free text using raptat
Glenn T Gobbel, Jennifer Garvin, Ruth Reeves, Robert M Cronin, Julia Heavirland, Jenifer Williams, Allison Weaver, Shrimalini Jayaramaraja, Dario Giuse, Theodore Speroff, et al. 2014 · 2014
Cited alongside, same era.
How essential are unstructured clinical narratives and information fusion to clinical trial recruitment?
Preethi Raghavan, James L Chen, Eric Fosler-Lussier, and Albert M Lai. 2014 · 2014
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Learning to capitalize with character-level recurrent neural networks: An empirical study
Raymond Hendy Susanto, Hai Leong Chieu, and Wei Lu. 2016 · 2016
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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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De-identification of patient notes with recurrent neural networks
Franck Dernoncourt, Ji Young Lee, Ozlem Uzuner, and Peter Szolovits. 2017 · 2017
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De-identification of clinical notes via recurrent neural network and conditional random field
Zengjian Liu, Buzhou Tang, Xiaolong Wang, and Qingcai Chen. 2017 · 2017
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Towards measuring membership privacy
Yunhui Long, Vincent Bindschaedler, and Carl A Gunter. 2017 · 2017
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Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/uthealth shared task track 1
Amber Stubbs, Christopher Kotfila, and Özlem Uzuner. 2015 · 2014
Cited alongside, same era.
Recurrent neural network regularization
Wojciech Zaremba, Ilya Sutskever, and Oriol Vinyals. 2014 · 2014
Cited alongside, same era.
Recurrent neural network language model adaptation for multi-genre broadcast speech recognition
Xie Chen, Tian Tan, Xunying Liu, Pierre Lanchantin, Moquan Wan, Mark JF Gales, and Philip C Woodland. 2015 · 2015
Cited alongside, same era.
To drop or not to drop: Robustness, consistency and differential privacy properties of dropout
Prateek Jain, Vivek Kulkarni, Abhradeep Thakurta, and Oliver Williams. 2015 · 2015
Cited alongside, same era.
Deep neural language models for machine translation
Thang Luong, Michael Kayser, and Christopher D Manning. 2015 · 2015
Cited alongside, same era.
Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang. 2016 · 2016
Cited alongside, same era.
Towards the creation of a large corpus of synthetically-identified clinical notes
Willie Boag, Tristan Naumann, and Peter Szolovits. 2016 · 2016
Cited alongside, same era.
Pointer sentinel mixture models
S. Merity, C. Xiong, J. Bradbury, and R. Socher. 2017 · 2017
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Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov. 2017 · 2017
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Privacy risk in machine learning: Analyzing the connection to overfitting
Samuel Yeom, Matt Fredrikson, and Somesh Jha. 2017 · 2017
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Natural language processing of clinical notes for identification of critical limb ischemia
Naveed Afzal, Vishnu Priya Mallipeddi, Sunghwan Sohn, Hongfang Liu, Rajeev Chaudhry, Christopher G Scott, Iftikhar J Kullo, and Adelaide M Arruda-Olson. 2018 · 2018
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Fine-tuned language models for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
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Deep ehr: Chronic disease prediction using medical notes
Jingshu Liu, Zachariah Zhang, and Narges Razavian. 2018 · 2018
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Learning differentially private language models without losing accuracy
H Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang. 2018 · 2018
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Scalable private learning with pate
Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Úlfar Erlingsson. 2018 · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2018 · 2018
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Lessons from natural language inference in the clinical domain
Alexey Romanov and Chaitanya Shivade. 2018 · 2018
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