Published June 2021 | Version v1
Journal article

To buy or not to buy. Evaluating commercial AI solutions in radiology (the ECLAIR guidelines)

  • 1. Department of Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne (Switzerland)
  • 2. Gleamer, Paris (France)
  • 3. Hardian Health, Haywards Heath (United Kingdom)
  • 4. Department of Radiology, University of Pennsylvania, Philadelphia, PA (United States)
  • 5. IBM Watson Health, Paris (France)
  • 6. Department of Radiology, University Hospital of Cologne, Cologne (Germany)
  • 7. Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne (Switzerland)

Description

Artificial intelligence (AI) has made impressive progress over the past few years, including many applications in medical imaging. Numerous commercial solutions based on AI techniques are now available for sale, forcing radiology practices to learn how to properly assess these tools. While several guidelines describing good practices for conducting and reporting AI-based research in medicine and radiology have been published, fewer efforts have focused on recommendations addressing the key questions to consider when critically assessing AI solutions before purchase. Commercial AI solutions are typically complicated software products, for the evaluation of which many factors are to be considered. In this work, authors from academia and industry have joined efforts to propose a practical framework that will help stakeholders evaluate commercial AI solutions in radiology (the ECLAIR guidelines) and reach an informed decision. Topics to consider in the evaluation include the relevance of the solution from the point of view of each stakeholder, issues regarding performance and validation, usability and integration, regulatory and legal aspects, and financial and support services.

Additional details

Identifiers

Publishing Information

Journal Title
European Radiology
Journal Volume
31
Journal Issue
6
Journal Page Range
p. 3786-3796
ISSN
0938-7994
CODEN
EURAE3