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Soltani et al present a practical roadmap for evaluating, implementing, and governing clinical artificial intelligence (AI) systems.1 As health systems move from aspiration to adoption, their framework appropriately emphasizes the full AI governance lifecycle, from problem identification through post-deployment monitoring.
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Baughman et al. (2026) studied this question.
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