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    Group logo of 3.4 | Standards and Best Practices

    3.4 | Standards and Best Practices

    Public Ethics & Governance

    Public Ethics & Governance

    Active 3 months ago

    Purpose: To develop and adopt common standards for AI validation, quality assurance, and... View more

    Public Ethics & Governance

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    Group Description

    Purpose: To develop and adopt common standards for AI validation, quality assurance, and interoperability to ensure safety, reliability, and seamless integration of AI in healthcare.

    Description: This group is dedicated to establishing benchmarks, guidelines, and frameworks that promote consistency, trustworthiness, and widespread usability of AI technologies across healthcare systems. It’s about ensuring quality and compatibility.

    Intended Use: For members to discuss and contribute to the creation of industry standards, evaluate existing best practices for AI model testing and deployment, and promote interoperability to reduce fragmentation in the AI ecosystem.

    Limitations: While closely related to regulatory discussions, this group focuses on industry-driven standards and technical best practices, rather than legal compliance or policy enforcement (which are in 3.3). Not for general IT infrastructure.

    Key Activities:
    Discussions on methodologies for robust AI model testing and validation.
    Evaluating and advocating for common data exchange standards (e.g., FHIR, DICOM) for AI.
    Developing frameworks for responsible AI development and deployment.
    Collaborating on benchmarks for AI performance in specific use cases.

    Potential Users: AI Innovator/Developer, IT & Infrastructure Professional, Academic/Researcher, Policy/Regulatory/Legal Expert, Healthcare Leader/Administrator.

    Possible Discussions: “What are the essential criteria for validating AI diagnostic tools?”, “Challenges in standardizing AI model reporting for transparency,” “The role of FHIR in enabling AI interoperability.”

    Other Important Notes: This group is crucial for fostering a mature and reliable AI ecosystem, moving beyond individual projects to industry-wide coherence.

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