AI Medical Device Evidence Has a Lifecycle
AI-enabled medical-device analysis should follow evidence from intended use through submission, change control, monitoring, and post-market learning.
Devices, diagnostics, and the systems that support clinical workflows.
AI-enabled medical-device analysis should follow evidence from intended use through submission, change control, monitoring, and post-market learning.
Diagnostics analysis should follow the result from sample collection through interpretation, treatment, referral, and patient understanding.
SaMD products are easier to assess when product teams state intended purpose, users, decisions, evidence, and boundaries in plain language.
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