IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-030-77287-1_12.html
   My bibliography  Save this book chapter

HEalth: Privately Computing on Shared Healthcare Data

In: Protecting Privacy through Homomorphic Encryption

Author

Listed:
  • Leo de Castro

    (Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory)

  • Erin Hales

    (University of London, Information Security Group, Royal Holloway)

  • Mimee Xu

    (New York University, Courant Institute of Mathematics)

Abstract

We give an overview of how to use threshold Fully Homomorphic Encryption (FHE) to enable data sharing in a medical context. Hospitals in the US are not currently equipped or motivated to share data privately. Threshold encryption would allow hospitals to share sensitive data securely. The combined encrypted data from all the hospitals can be used to compute statistics and even carry out machine learning at a large scale. We propose the use case of assessing ‘fairness’ in the context of hospital admissions. We analyse how fairness can be computed from the data, and describe how this could be beneficial to patients as well as regulators.

Suggested Citation

  • Leo de Castro & Erin Hales & Mimee Xu, 2021. "HEalth: Privately Computing on Shared Healthcare Data," Springer Books, in: Kristin Lauter & Wei Dai & Kim Laine (ed.), Protecting Privacy through Homomorphic Encryption, pages 157-162, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-77287-1_12
    DOI: 10.1007/978-3-030-77287-1_12
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-030-77287-1_12. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.