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Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA.

Authors :
Brady, Adrian P.
Allen, Bibb
Chong, Jaron
Kotter, Elmar
Kottler, Nina
Mongan, John
Oakden-Rayner, Lauren
dos Santos, Daniel Pinto
Tang, An
Wald, Christoph
Slavotinek, John
Source :
Canadian Association of Radiologists Journal. May2024, Vol. 75 Issue 2, p226-244. 19p.
Publication Year :
2024

Abstract

Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever‑growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones. This multi‑society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08465371
Volume :
75
Issue :
2
Database :
Academic Search Index
Journal :
Canadian Association of Radiologists Journal
Publication Type :
Academic Journal
Accession number :
176861755
Full Text :
https://doi.org/10.1177/08465371231222229