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BMI 5334 Biomedical Data Privacy

3 semester credit hours
Lecture contact hours: 2; Lab contact hours: 3
Web-based and classroom instruction
Instructor Consent Required
Class limited to 20 students

The massive increase in the number of biomedical and health related datasets offer great opportunities for optimizing healthcare and understanding the molecular basis of diseases. These also bring novel challenges centered around protecting the privacy of consumers, patients, and their family members. Students will explore privacy preserving data analysis methods aimed at maximizing data utility while respecting the privacy of individuals. Foundational statistical methods that protect the privacy of individuals will be applied during hands-on exercises.

Upon successfully completing this course, students will:

  • Summarize privacy risks around sharing biomedical data
  • Define metrics for measuring privacy
  • Compare and contrast the advantages and shortcomings of popular methods for privacy preserving data mining
  • Apply data sanitization methods for protecting personal information derived from disparate data sources such as EHRs and genetic data
  • Quantify privacy risks in data analysis using appropriate computational methods