Implementation of clinical artificial intelligence in radiology: who decides and how?

D Daye, WF Wiggins, MP Lungren, T Alkasab, N Kottler… - Radiology, 2022 - pubs.rsna.org
D Daye, WF Wiggins, MP Lungren, T Alkasab, N Kottler, B Allen, CJ Roth, BC Bizzo
Radiology, 2022pubs.rsna.org
As the role of artificial intelligence (AI) in clinical practice evolves, governance structures
oversee the implementation, maintenance, and monitoring of clinical AI algorithms to
enhance quality, manage resources, and ensure patient safety. In this article, a framework is
established for the infrastructure required for clinical AI implementation and presents a road
map for governance. The road map answers four key questions: Who decides which tools to
implement? What factors should be considered when assessing an application for …
As the role of artificial intelligence (AI) in clinical practice evolves, governance structures oversee the implementation, maintenance, and monitoring of clinical AI algorithms to enhance quality, manage resources, and ensure patient safety. In this article, a framework is established for the infrastructure required for clinical AI implementation and presents a road map for governance. The road map answers four key questions: Who decides which tools to implement? What factors should be considered when assessing an application for implementation? How should applications be implemented in clinical practice? Finally, how should tools be monitored and maintained after clinical implementation? Among the many challenges for the implementation of AI in clinical practice, devising flexible governance structures that can quickly adapt to a changing environment will be essential to ensure quality patient care and practice improvement objectives.
© RSNA, 2022
An earlier incorrect version appeared online. This article was corrected on August 2, 2022.
Radiological Society of North America
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