A Massachusetts Institute of Technology research team has found that artificial intelligence can detect COVID positivity at a high accuracy rate simply by the sound of one’s cough recorded through a smartphone speaker — even for asymptomatic individuals.

Though the differences between the forced coughs of healthy and asymptomatic individuals are not discernable to the human ear, the research team discovered they can be picked up by technology.

After researchers Brian Subirana, Jordi Laguarta, and Ferran Hueto trained their model on tens of thousands of sample coughs and spoken words, they tested it on 1,064 subjects, finding that the model accurately identified 98.5% of coughs from people who were confirmed to have COVID-19, including 100% of coughs from asymptomatic individuals.

“We think this shows that the way you produce sound changes when you have COVID, even if you’re asymptomatic,” explained co-author Subirana, a research scientist in MIT’s Auto-ID Laboratory, after their paper was published in the IEEE Journal of Engineering in Medicine and Biology.

The MIT team is now working to incorporate their model into an app, which if approved by the FDA could provide a free, non-invasive pre-screening tool to help identify people who have COVID-19 — even those who are not experiencing symptoms.

Their hope is that users would be able to log into the app daily, record their cough, and instantly receive information on whether they might be infected, indicating that they should confirm the result with a formal test.

The full paper can be read here