The challenges of assembling, maintaining and making available large data sets of clinical data for research

Emily R. Jefferson, Emanuele Trucco

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Citations (Scopus)

Abstract

Clinical images are needed to train algorithms however obtaining such images can present a range of challenges not necessarily obvious to those with a pure computational science background. This chapter provides a summary of the data governance constraints around access to patient records and what controls should be considered for secure access to anonymized health data.

Original languageEnglish
Title of host publicationComputational Retinal Image Analysis
Subtitle of host publicationTools, Applications and Perspectives
EditorsEmanuele Trucco, Tom MacGillivray, Yanwu Xu
PublisherAcademic Press
Chapter20
Pages429-444
Number of pages16
ISBN (Print)9780081028162
DOIs
Publication statusPublished - 2019

Publication series

NameThe Elsevier and MICCAI Society Book Series

Keywords

  • Clinical images
  • Data governance
  • Safe Havens
  • Trusted research environments
  • GDPR
  • Public trust

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