Healthcare AI is entering clinical practice faster than the evidence framework can evaluate it. FDA has cleared over 1,451 AI-enabled medical devices. Digital health companies are publishing clinical data at unprecedented scale. And new regulatory pathways like the Predetermined Change Control Plan (PCCP) are creating adaptive frameworks for AI that evolves after deployment.
But what does the evidence actually prove? What’s the difference between a vendor’s internal validation study and a prospective randomized controlled trial? How do you evaluate whether an AI health platform has enough clinical evidence to trust with patient care?
This guide maps the clinical AI evidence landscape — from the evidence pyramid that classifies proof quality, to the regulatory pathways governing AI devices, to the companies building the strongest (and weakest) evidence bases in digital health.
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