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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. | LitMetric

AI Article Synopsis

  • AI has the potential to transform radiology by improving diagnosis and management of medical conditions, but it also poses risks that need careful evaluation.
  • A collaborative statement from radiology societies across multiple regions emphasizes the need to distinguish between effective AI tools and those that could be harmful or ineffective.
  • The paper outlines practical and ethical considerations for developers and regulators of AI in radiology, along with suggestions for ensuring the safety and efficacy of these technologies in clinical settings.

Article 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.

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Source
http://dx.doi.org/10.1111/1754-9485.13612DOI Listing

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