Privacy-Preserving Health Data Release

Designed a de-identification workflow for a 150k-record health analytics dataset using direct identifier removal, quasi-identifier generalization, suppression, and diversity checks. Balanced k-anonymity-style privacy protections with utility for disease, fairness, and regional risk analysis.