AUR-RRA Review: Logistics of Academic-Industry Partnerships in Artificial Intelligence

Acad Radiol. 2022 Jan;29(1):119-128. doi: 10.1016/j.acra.2021.08.002. Epub 2021 Sep 22.


The Radiology Research Alliance (RRA) of the Association of University Radiologists (AUR) convenes Task Forces to address current topics in radiology. In this article, the AUR-RRA Task Force on Academic-Industry Partnerships for Artificial Intelligence, considered issues of importance to academic radiology departments contemplating industry partnerships in artificial intelligence (AI) development, testing and evaluation. Our goal was to create a framework encompassing the domains of clinical, technical, regulatory, legal and financial considerations that impact the arrangement and success of such partnerships.

Keywords: academic radiology; academic-industry collaborations; academic-industry partnerships; and computer assisted diagnosis; artificial intelligence; challenges; clinical data ownership; deep learning; machine learning; opportunities; pitfalls.

MeSH terms

  • Artificial Intelligence*
  • Humans
  • Radiography
  • Radiologists
  • Radiology*
  • Universities