Data De-identification

Data De-Identification is a privacy-preserving process in health information management whereby personally identifiable information is systematically removed or obscured from datasets to prevent the identification of individuals, distinguishing it from general data anonymization by allowing for potential re-identification under controlled conditions.

1.5K

Publications

116K

Citations

4.6K

Authors

1.5K

Institutions

Publications per year

2017–2026

655

Authors

4.6K

  1. BM
    Bradley Malin

    Vanderbilt University, United States

    35 publications · 2.9K citations

    25

    h-index

  2. KE
    Khaled El Emam

    University of Ottawa, Canada

    21 publications · 1.2K citations

    19

    h-index

  3. LS
    Latanya Sweeney

    Carnegie Mellon University, United States

    18 publications · 6.2K citations

    15

    h-index

  4. GL
    Grigorios Loukides

    Cardiff University, United Kingdom

    16 publications · 585 citations

    14

    h-index

  5. PC
    Peter Christen

    Australian National University, Australia

    13 publications · 1.2K citations

    12

    h-index

1–5 of 4.6K

Venues

  1. Journal of the American Medical Informatics Association

    JAMIA · 36 publications · 3.1K citations

    27

    h-index

  2. BMC Medical Informatics and Decision Making

    25 publications · 2.7K citations

    23

    h-index

  3. arXiv (Cornell University)

    Repository · 50 publications · 1.5K citations

    23

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 21 publications · 4.9K citations

    20

    h-index

  5. PubMed

    Repository · 29 publications · 1.1K citations

    19

    h-index

1–5