In less than a year, the pandemic has spurred the development of countless artificial intelligence models designed to aid in the diagnosis of Covid-19 and spot early warning signs of severe illness among those infected. But so far, only a few have received emergency use authorization from the Food and Drug Administration. That scarcity is a sign of the newness of these tools — as well as the murkiness of the regulatory landscape at a time when unapproved algorithms are being widely tested and rolled out in the clinic.
The latest such authorization, which amounts to a conditional approval of a product, was granted to a system meant to predict whether hospitalized Covid-19 patients are at risk of needing intubation — a heads-up that could allow clinicians to take mitigating steps and plan accordingly. The model was developed by Dascena, a San Francisco Bay Area company working on clinical machine learning systems for conditions including sepsis and acute kidney injury.