Asymptomatic people who are infected with Covid-19 exhibit, by definition, no discernible physical symptoms of the disease. They are thus less likely to seek out testing for the virus, and could unknowingly spread the infection to others. But it seems those who are asymptomatic may not be entirely free of changes wrought by the virus. MIT researchers have now found that people who are asymptomatic may differ from healthy individuals in the way that they cough. These differences are not decipherable to the human ear.
An algorithm can detect the coronavirus in people who are asymptomatic, just from listening to the way they cough. Coronavirus patients who don't have symptoms still exhibit subtle changes not always detectable by the naked eye - or ear. Researchers at MIT developed an AI-powered model that distinguishes asymptomatic people from uninfected individuals by analyzing recordings of coughs submitted by tens of thousands of volunteers online. The algorithm accurately identified 98.5 percent of coughs from people who tested positive for the virus, including 100 percent of coughs from asymptomatic patients. The team is gathering more samples, with the goal of producing an app that could be a convenient and free pre-screening tool. Researchers at MIT used AI to analyze thousands of coughs and detect differences in those of people with coronavirus.
At least one out of every five people who get the coronavirus doesn't show symptoms and can unknowingly spread the virus to others. Those who don't feel sick and aren't notified of exposure can't know that they should get tested. But researchers at the Massachusetts Institute of Technology may have found a way to identify these silent coronavirus carriers without a test. A study published in September describes an artificial-intelligence model that can distinguish between the coughs of people with the coronavirus and those who are healthy. It can even tell from voluntary, forced coughs whether people were healthy or were asymptomatic carriers, based on sound variations too subtle for the human ear to discern.
The aim of the AI algorithm is to separate healthy patients from ill but asymptomatic ones based on coughing tone, feeling, and other biomarkers. In a continuation of the involvement of artificial intelligence (AI) in healthcare, a new app may help diagnose asymptomatic COVID-19 carriers through a simple listening test -- a cough from someone infected versus a regular cough. It may seem straight from science fiction, but a research team at MIT believes that asymptomatic carriers may be showing subtle signs through the sound of their cough. They've built an app, programming it with thousands of data points from healthy and sick volunteers. AI was able to identify coughs coming from those infected with the virus with a 98.5% accuracy rate.
Asymptomatic spread of COVID-19 is a huge contributor to the pandemic, but of course if there are no symptoms, how can anyone tell they should isolate or get a test? MIT research has found that hidden in the sound of coughs is a pattern that subtly, but reliably, marks a person as likely to be in the early stages of infection. It could make for a much-needed early warning system for the virus. The sound of one's cough can be very revealing, as doctors have known for many years. AI models have been built to detect conditions like pneumonia, asthma and even neuromuscular diseases, all of which alter how a person coughs in different ways.