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Stanford Study Questions How Medical AI Devices Are Evaluated


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A chest x-ray.

The researchers pointed to a deep learning model that analyzes chest X-rays for signs of collapsed lungs to prove their point. While the model worked accurately for one cohort of patient data, against two other patient data sites, the algorithms were 10% less accurate.

Credit: AI in Healthcare

Every day, more AI uses are coming to market, with medical devices a perfect target for innovating healthcare. And while more than 130 of such tools have been approved by the Federal Drug Administration, some experts are saying the review process needs to be reevaluated.

That's according to a group of Stanford researchers who wanted to know how much regulators and doctors actually know about the accuracy of the AI devices they are touting and approving. The evidence may actually reveal some of the faults with AI technology, according to the study, which was published in Nature. The researchers analyzed every AI medical device approved by the FDA between 2015 and 2020 for their study.

They found that approval for AI devices was starkly different than the approval process for pharmaceuticals.

From AI in Healthcare
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