De-identification
De-Identification is a data protection method that belongs to the class of privacy-preserving techniques, specifically characterized by the removal or transformation of personally identifiable information from datasets to prevent direct identification of individuals, while enabling data utility for secondary uses such as research or analysis.
273
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18.7K
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1K
Authors
409
Institutions
Publications per year
2017–2026
143
273
Emily Alsentzer, John R. Murphy, William Boag et al. · 2019 · 1.6K citations · Full text
Data Privacy through Optimal k-Anonymization
Roberto J. Bayardo, R. Agrawal · 2005 · 1.1K citations
Publicly Available Clinical BERT Embeddings
Emily Alsentzer, John R. Murphy, Willie Boag et al. · arXiv (Cornell University) · 2019 · 726 citations · Full text
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Vanderbilt University
Nashville, United States
9 h-index
30 publications
1.4K citations
Massachusetts Institute of Technology
Cambridge, United States
7 h-index
36 publications
9.6K citations
National University of Singapore
Singapore, Singapore
6 h-index
18 publications
3.1K citations
Regenstrief Institute
Indianapolis, United States
6 h-index
10 publications
865 citations
Harvard University
Cambridge, United States
5 h-index
18 publications
1.7K citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
20 publications
4.4K citations
Columbia University
New York, United States
5 h-index
17 publications
2.6K citations

University of Ottawa
Ottawa, Canada
5 h-index
7 publications
996 citations
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JAMIA · 16 publications · 3.1K citations
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Repository · 13 publications · 371 citations
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9 publications · 1.1K citations
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Book series · 9 publications · 166 citations
9
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9 publications · 618 citations
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