Imaging AI in Practice: A Demonstration of Future Workflow Using Integration Standards Article Swipe
Walter F. Wiggins
,
Kirti Magudia
,
Teri M. Sippel Schmidt
,
Stacy D. O’Connor
,
Christopher D. Carr
,
Marc Kohli
,
Katherine P. Andriole
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1148/ryai.2021210152
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1148/ryai.2021210152
Artificial intelligence (AI) tools are rapidly being developed for radiology and other clinical areas. These tools have the potential to dramatically change clinical practice; however, for these tools to be usable and function as intended, they must be integrated into existing radiology systems. In a collaborative effort between the Radiological Society of North America, radiologists, and imaging-focused vendors, the Imaging AI in Practice (IAIP) demonstrations were developed to show how AI tools can generate, consume, and present results throughout the radiology workflow in a simulated clinical environment. The IAIP demonstrations highlight the critical importance of semantic and interoperability standards, as well as orchestration profiles for successful clinical integration of radiology AI tools. Keywords: Computer Applications-General (Informatics), Technology Assessment © RSNA, 2021.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1148/ryai.2021210152
- OA Status
- green
- Cited By
- 32
- References
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W3208934937Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1148/ryai.2021210152Digital Object Identifier
- Title
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Imaging AI in Practice: A Demonstration of Future Workflow Using Integration StandardsWork title
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articleOpenAlex work type
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enPrimary language
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2021Year of publication
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2021-10-27Full publication date if available
- Authors
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Walter F. Wiggins, Kirti Magudia, Teri M. Sippel Schmidt, Stacy D. O’Connor, Christopher D. Carr, Marc Kohli, Katherine P. AndrioleList of authors in order
- Landing page
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https://doi.org/10.1148/ryai.2021210152Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.ncbi.nlm.nih.gov/pmc/articles/8637229Direct OA link when available
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32Total citation count in OpenAlex
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2025: 7, 2024: 14, 2023: 7, 2022: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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