By Casey Ross, Rebecca Robbins and Erin Brodwin
The coronavirus outbreak has rapidly accelerated the nation’s slow-moving effort to incorporate artificial intelligence into medical care, as hospitals grasp onto experimental technologies to relieve an unprecedented strain on their resources.
AI has become one of the first lines of defense in the pandemic. Hospitals are using it to help screen and triage patients and identify those most likely to develop severe symptoms. They’re scanning faces to check temperatures and harnessing fitness tracker data, to zero in on individual cases and potential clusters. They are also using AI to keep tabs on the virus in their own communities. They need to know who has the disease, who is likely to get it, and what supplies are going to run out tomorrow, two weeks from now, and further down the road.
There’s a crucial caveat: It’s not clear if these AI tools are going to work. Many are based on drips of data, often from patients in China with severe disease. Those data might not be applicable to people in other places or with milder disease. Hospitals are testing models for Covid-19 care that were never intended to be used in such a scenario. Some AI systems could also be susceptible to overfitting, meaning that they’ve modeled their training data so well that they have trouble analyzing new data — which is coming in constantly as cases rise.
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AI could also be used to catch early symptoms of the illness in health care workers, who are at particularly high risk of contracting the virus. In San Francisco, researchers at the University of California are using wearable rings made by health tech company Oura to track health care workers’ vital signs for early indications of Covid-19. If those signs — including elevated heart rate and increased temperature — show up reliably on the rings, they could be fed into an algorithm that would give hospitals a heads-up about workers who need to be isolated or receive medical care.
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