A new coalition aims to close AI’s credibility gap in medicine with testing and oversight

To read the medical literature, you might think AI is taking over medicine. It can detect cancers on images earlier, find heart issues invisible to cardiologists, and predict organ dysfunction hours before it becomes dangerous to hospitalized patients.

But most of the AI models described in journals — and lionized in press releases — never make it into clinical use. And the rare exceptions have fallen well short of their revolutionary expectations.

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