Anonymize or synthesize? Privacy-preserving methods for heart failure score analytics
We could demonstrate that anonymization and synthetization methods protect privacy while retaining data utility for heart failure risk assessment. Both approaches and a combination thereof introduce only minimal deviations from the original data set over all features. While data synthesis techniques produce any number of new records, data anonymization techniques offer more formal privacy guarantees. Consequently, data synthesis on anonymized data further enhances privacy protection with little impacting data utility. We share all generated data sets with the scientific community through a use and access agreement.
Authors
- Tim Johann (ORCID: https://orcid.org/0000-0001-5792-1562)
- Fabian Praßer (ORCID: https://orcid.org/0000-0003-3172-3095)
- Christoph Dieterich (ORCID: https://orcid.org/0000-0001-9468-6311)
- Karen Otte
Institutions
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
- German Centre for Cardiovascular Research (DE)
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
Publication Details
- Journal
- European Heart Journal - Digital Health
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1093/ehjdh/ztae083
- Citations
- 2
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 0.69
Funders
- Bundesministerium für Bildung und Forschung