A novel analysis methodology for assessment of re-identification risks for the National Cancer Institute cancer registry privacy preserving record linkage technique
Re-identification risk is deemed low for the new NCI PPRL software. Token frequency analysis provides a reliable estimate of the re-identification risk in token-based PPRL tools.
Authors
- Benmei Liu (ORCID: https://orcid.org/0000-0003-0096-139X)
- Valentina I. Petkov (ORCID: https://orcid.org/0009-0009-8297-5381)
- Lynne Penberthy (ORCID: https://orcid.org/0000-0001-9372-9869)
- Esmeralda Casas-Silva (ORCID: https://orcid.org/0000-0002-9704-0812)
- Murat Kantarcıoğlu (ORCID: https://orcid.org/0000-0001-9795-9063)
- Bradley Malin (ORCID: https://orcid.org/0000-0003-3040-5175)
- Will Howe (ORCID: https://orcid.org/0009-0009-4227-5217)
- Diana Velasquez-Kolnik (ORCID: https://orcid.org/0009-0003-1866-6281)
Institutions
- Vanderbilt University (US)
- Information Management Services (US)
- Frederick National Laboratory for Cancer Research (US)
- National Cancer Institute (US)
- Virginia Tech (US)
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1093/jamia/ocaf172
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00