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De-identification is the process of removing 18 protected health information (PHI) from clinical notes in order for the text to be considered not individually identifiable.
O. Uzuner, Y. Luo, and P. Szolovits, “Evaluating the state-of-the-art in automatic de-identification,” Journal of the American Medical Informatics Association
2007
Earlier work this paper cites.
I. Neamatullah, M. M. Douglass, L. wei H Lehman, A. Reisner, M. Villarroel, W. J. Long, P. Szolovits, G. B. Moody, R. G. Mark, and G. D. Clifford, “Automated de-identification of free-text medical records,” BMC Medical Informatics and Decision Making
2008
Earlier work this paper cites.
F. P. Morrison, L. Li, A. M. Lai, and G. Hripcsak, “Repurposing the clinical record: Can an existing natural language processing system de-identify clinical notes?,” Journal of the American Medical Informatics Association
2009
Earlier work this paper cites.
S. M. Meystre, F. J. Friedlin, B. R. South, S. Shen, and M. H. Samore, “Automatic de-identification of textual documents in the electronic health record: a review of recent research.,” BMC medical research methodology
2010
Earlier work this paper cites.
O. Ferrández, B. R. South, S. Shen, F. J. Friedlin, M. H. Samore, and S. M. Meystre, “Evaluating current automatic de-identification methods with veteran’s health administration clinical documents,” BMC Medical Research Methodology
2012
Earlier work this paper cites.
S. Pyysalo, F. Ginter, H. Moen, T. Salakoski, and S. Ananiadou, “Distributional semantics resources for biomedical text embeddingsfirst,” 01 2013
2013
Earlier work this paper cites.
J. Pennington, R. Socher, and C. D. Manning, “Glove: Global vectors for word representation,” in In EMNLP
2014
Earlier work this paper cites.
A. Stubbs, C. Kotfila, and Ö. Uzuner, “Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/uthealth shared task track 1,” Journal of Biomedical Informatics
2015
Earlier work this paper cites.
O. f. C. R. HHS Office of the Secretary and OCR, “Methods for de-identification of phi,” Nov 2015
2015
Cited alongside, same era.
H. Yang and J. M. Garibaldi, “Automatic detection of protected health information from clinic narratives.,” Journal of biomedical informatics
2015
Cited alongside, same era.
Z. Liu, Y. Chen, B. Tang, X. Wang, Q. Chen, H. Li, J. Wang, Q. Deng, and S. Zhu, “Automatic de-identification of electronic medical records using token-level and character-level conditional random fields,” Journal of Biomedical Informatics
2015
Cited alongside, same era.
Y. Gal and Z. Ghahramani, “A theoretically grounded application of dropout in recurrent neural networks,” CoRR
2015
Cited alongside, same era.
Z. Huang, W. Xu, and K. Yu, “Bidirectional lstm-crf models for sequence tagging,” CoRR
2015
Cited alongside, same era.
J. Adler-Milstein and A. K. Jha, “Hitech act drove large gains in hospital electronic health record adoption,” Health Affairs
2017
Later among the works it cites.
B. McCann, J. Bradbury, C. Xiong, and R. Socher, “Learned in translation: Contextualized word vectors,” CoRR
2017
Later among the works it cites.
F. Dernoncourt, J. Y. Lee, and P. Szolovits, “Neuroner: an easy-to-use program for named-entity recognition based on neural networks,” CoRR
2017
Later among the works it cites.
Z. Liu, B. Tang, X. Wang, and Q. Chen, “De-identification of clinical notes via recurrent neural network and conditional random field.,” Journal of biomedical informatics
2017
Later among the works it cites.
N. Reimers and I. Gurevych, “Optimal hyperparameters for deep lstm-networks for sequence labeling tasks,” CoRR
2017
Later among the works it cites.
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F. Dernoncourt, J. Y. Lee, O. Uzuner, and P. Szolovits, “De-identification of patient notes with recurrent neural networks,” CoRR
2016
Cited alongside, same era.
X. Ma and E. Hovy, “End-to-end sequence labeling via bi-directional lstm-cnns-crf,” CoRR
2016
Cited alongside, same era.
G. Lample, M. Ballesteros, S. Subramanian, K. Kawakami, and C. Dyer, “Neural architectures for named entity recognition,” CoRR
2016
Cited alongside, same era.
P. Burckhardt and R. Padman, “deidentify,” AMIA Annu Symp Proc
2017
Later among the works it cites.
M. E. Peters, M. Neumann, M. Iyyer, M. Gardner, C. Clark, K. Lee, and L. Zettlemoyer, “Deep contextualized word representations,” in Proc. of NAACL
2018
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