In surprising news this week, CMS (the Centres for Medicare & Medicaid Services) in the USA approved the first reimbursement for AI augmented medical care. have a deep learning model which identifies signs of stroke on brain CT and automatically contacts the neurointerventionalist, bypassing the first read normally performed by a general radiologist.

From their press material: demonstrated to CMS a significant reduction in time to treatment and improved clinical outcomes in patients suffering a stroke. Viz LVO has been granted a New Technology Add on Payment of up to $1,040 per use in patients with suspected strokes.

This is enormous news, and marks the start of a totally new era in medical AI.

Especially that pricetag!

Doing it tough

It is widely known in the medical AI community that it has been a troubled marketplace for AI developers. The majority of companies have developed putatively useful AI models, but have been unable to sell them to anyone. This has lead to many predictions that we are going to see a crash amongst medical AI startups, as capital runs out and revenue can’t take over. There have even been suggestions that a medical “AI winter” might be coming.

Hearing about layoffs at some prominent radiology AI companies. Suggests the AI bubble may be deflating…— Curt Langlotz (@curtlanglotz) November 1, 2019

To be clear, this was never a problem with the technology. Deep learning works, and there are lots of ways it can be applied usefully in medicine. It was an alignment problem: the people who procure medical technology (typically CIOs) are motivated by business needs, not how useful a model is.

The strongest business incentive is money, earning more or spending less, and proving that AI models can help here has been really difficult.

Most researchers and developers have focused on medical outcomes, like diagnostic performance or lives saved. But

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