Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing.

Journal: Circulation. Cardiovascular quality and outcomes
Published Date:

Abstract

BACKGROUND: Data sharing accelerates scientific progress but sharing individual-level data while preserving patient privacy presents a barrier.

Authors

  • Brett K Beaulieu-Jones
    Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, United States; Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, United States. Electronic address: brettbe@med.upenn.edu.
  • Zhiwei Steven Wu
    Computer Science and Electrical Engineering Department, University of Minnesota, Minneapolis (Z.S.W.).
  • Chris Williams
    Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia. (C.W., C.S.G.).
  • Ran Lee
    Division of Cardiovascular Medicine, Department of Medicine, University of Michigan Medical School, Ann Arbor (R.L., J.B.B.).
  • Sanjeev P Bhavnani
    Scripps Clinic and Research Foundation, San Diego, CA (S.P.B.).
  • James Brian Byrd
    Division of Cardiovascular Medicine, Department of Medicine, University of Michigan Medical School, Ann Arbor (R.L., J.B.B.).
  • Casey S Greene
    Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, United States; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, United States; Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Perelman School of Medicine, University of Pennsylvania, United States. Electronic address: csgreene@upenn.edu.