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AI Safety in Radiology
A Framework for Safe, Secure, and Trustworthy Artificial Intelligence
AI in radiology promises improved care but demands a meticulous approach to ensure AI Safety. The RAISE (Radiology AI Safety, an End-to-end lifecycle approach) framework ensures a comprehensive strategy, covering the AI lifecycle from pre- to post-deployment.Emphasizing regulatory compliance and ethics for accuracy, fairness, and trust, the framework advocates integrating quality, safety, and monitoring mechanisms at the platform level.
This spans pre-, peri-, and post-deployment stages, with rigorous validation and surveillance. Download our white paper to learn more about how RAISE accelerates responsible AI adoption, fostering trust among providers and patients.