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Imaging AI in Practice: A Demonstration of Future Workflow Using Integration Standards

Walter F. Wiggins, Kirti Magudia, Teri M. Sippel Schmidt, Stacy D. O’Connor, Christopher D. Carr, Marc Kohli, Katherine P. Andriole

2021Radiology Artificial Intelligence40 citationsDOIOpen Access PDF

Abstract

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

Topics & Concepts

WorkflowMedicineInteroperabilityOrchestrationMedical physicsInformaticsUSableClinical PracticeRadiologyComputer scienceWorld Wide WebDatabaseMusicalArtVisual artsEngineeringFamily medicineElectrical engineeringRadiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and EducationRadiology practices and education