Patient privacy in AI-driven omics methods.

Journal: Trends in genetics : TIG
Published Date: Apr 17, 2024

Abstract

Artificial intelligence (AI) in omics analysis raises privacy threats to patients. Here, we briefly discuss risk factors to patient privacy in data sharing, model training, and release, as well as methods to safeguard and evaluate patient privacy in AI-driven omics methods.

Authors

  • Juexiao Zhou
  • Chao Huang
    University of North Carolina, Chapel Hill, NC, USA.
  • Xin Gao
    Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA.

Keywords

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