Patient privacy in AI-driven omics methods

Juexiao Zhou, Chao Huang, Xin Gao*

*Corresponding author for this work

Research output: Contribution to journalShort surveypeer-review

1 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)383-386
Number of pages4
JournalTrends in Genetics
Volume40
Issue number5
DOIs
StatePublished - May 2024

Keywords

  • artificial intelligence
  • omics
  • privacy

ASJC Scopus subject areas

  • Genetics

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