Facebook, NYU Langone Health Use AI to Predict Health of Covid-19 Patients

Facebook’s use of machine learning to predict the types of content users are most interested in seeing in their News Feeds has been chronicled often through the years, but the social network is also working on potential ways to predict the treatment and resource needs of Covid-19 patients as part of its ongoing collaboration with NYU Langone Health’s Predictive Analytics Unit and Department of Radiology.

The two parties developed three machine learning models that may be able to help doctors predict how their patients’ conditions will develop and ensure that they have sufficient resources on hand to care for those patients:

A model for predicting patient deterioration based on a single X-ray.
A model for predicting patient deterioration based on a sequence of X-rays.
A model for predicting how much supplemental oxygen (if any) a patient might need based on a single X-ray.

Research engineer Matthew Muckley, research assistant Koustuv Sinha, research engineer Anuroop Sriram and program manager Nafissa Yakubova wrote in a blog post, “Our model using sequential chest X-rays can predict up to four days (96 hours) in advance if a patient may need more intensive care solutions, generally outperforming predictions by human experts. These predictions could help doctors avoid sending at-risk patients home too soon and help hospitals better predict demand for supplemental oxygen and other limited resources.”

NYU Langone Health professor of radiology William Moore added, “We have been able to show that with the use of this artificial intelligence algorithm, serial chest radiographs can predict the need for escalation of care in patients with Covid-19. As Covid-19 continues to be a major public health issue, the ability to predict a patient’s need for elevation of care—for example, intensive care unit admission—will be essential for hospitals.”

Facebook and NYU Langone Health are open-sourcing their pretrained models and publishing their research so that the broader community can benefit from it and build upon it.