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Author/Affiliation: Landis HumphreyOpen AccessArticle
18 Pages, 2,322 KB 
Multi Attribute Stratified Sampling: An Automated Framework for Privacy-Preserving Healthcare Data Publishing with Multiple Sensitive Attributes
Abstract:
The accumulation and analysis of large-scale patient data have led to breakthrough discoveries in potential flags for diseases based on pattern recognition, highlight medication efficacy, and local population health trends that would be impossible with traditional paper-based records. However, these benefits come with unique challenges posed by the application of data sharing for research and…
Read More(This article belongs to the SP20 (Special Issue on Multidisciplinary Frontiers in Engineering, Computing and Applied Sciences 2026) & Section Theory & Methods in Computer Science (CTM))