Benutzer: Gast  Login
Titel:

A scalable software solution for anonymizing high-dimensional biomedical data.

Dokumenttyp:
Article; Journal Article
Autor(en):
Meurers, Thierry; Bild, Raffael; Do, Kieu-Mi; Prasser, Fabian
Abstract:
BACKGROUND: Data anonymization is an important building block for ensuring privacy and fosters the reuse of data. However, transforming the data in a way that preserves the privacy of subjects while maintaining a high degree of data quality is challenging and particularly difficult when processing complex datasets that contain a high number of attributes. In this article we present how we extended the open source software ARX to improve its support for high-dimensional, biomedical datasets. FIND...     »
Zeitschriftentitel:
Gigascience
Jahr:
2021
Band / Volume:
10
Heft / Issue:
10
Volltext / DOI:
doi:10.1093/gigascience/giab068
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/34605868
TUM Einrichtung:
Institut für Medizinische Statistik und Epidemiologie
 BibTeX