AI Interoperability in Imaging White Paper

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Public Comment and Navigating the AI Interoperability in Imaging Document

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The AI Interoperability in Imaging White Paper is a long document. Reviewers are encouraged to provide feedback, even if only on portions of the document. To optimize their efforts, reviewers may consider:

• Paying particular attention to the Questions in sectionSection 1.4.
• Focusing on specific areas that align with their interests and expertise:
  • 2.1 Applications of AI in Imaging focuses on activities that AI can be applied to. The use cases in chapter 3 will be driven by these applications. This section may appeal to clinical reviewers.
    • Note: this white paper specifically strives to broaden the map of applications beyond radiology image analysis. Reviewers are encouraged to consider:
  • Imaging specialties beyond radiology, such as cardiology, pathology, dentistry, ophthalmology, dermatology, etc.
    • Tasks beyond image analysis, such as ordering, acquisition, reporting, and departmental operations analysis.
  • 2.2 Personas and Systems provides brief definitions that may clarify the subsequent use case sections. This section may appeal to both clinical and technical reviewers.
  • 3 Use Cases focuses on the steps that create, update, and use AI Applications. At the beginning of each Use Case Group and Use Case includes a statement of the task covered in the block. This section may appeal to data scientists and technical reviewers.
  • 4 Entities focuses on common data structures and metadata in AI workflows. This section may appeal to technical reviewers.