To buy, or not to buy - Evaluating Commercial AI Solutions in Radiology (the ECLAIR guidelines)

Details

Ressource 1Download: Omoumi2021_ECLAIR_guidelines.pdf (322.73 [Ko])
State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_052270573951
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
To buy, or not to buy - Evaluating Commercial AI Solutions in Radiology (the ECLAIR guidelines)
Journal
European Radiology
Author(s)
Omoumi Patrick, Ducarouge Alexis, Tournier Antoine, Harvey Hugh, Kahn Charles E., Louvet-de Verchère Fanny, Pinto Dos Santos Daniel, Kober Tobias, Richiardi Jonas
ISSN
0938-7994 (print)
1432-1084 (electronic)
Publication state
In Press
Peer-reviewed
Oui
Language
english
Abstract
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.
Keywords
artificial intelligence, machine learning, medical imaging
Web of science
Create date
22/12/2020 16:49
Last modification date
16/04/2021 18:20
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