As millions of people worldwide battle the symptoms of COVID-19, a group of "silent patients" may not even know they're sick and spreading the virus. Asymptomatic people, by definition, have no physical symptoms of the illnesses they carry. Researchers at the Massachusetts Institute of Technology (MIT) however, say they may be showing symptoms after all -- in the sound of their cough. Their study has created an artificial intelligence program that can identify if someone has coronavirus by the way their coughing sounds. Researchers programmed their AI model with thousands of different recorded coughs from both healthy and sick volunteers.
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.
Researchers at MIT say they've developed an algorithm that can diagnose COVID-19 by the sound of someone's cough, even if that person is asymptomatic. In a paper published in the IEEE Journal of Engineering in Medicine and Biology, the team reports that their approach distinguishes between infected and healthy individuals through "forced-cough" recordings contributed via smartphones, laptops, and other mobile devices. Applying AI to discern the cause of a cough isn't a new idea. Last year, a group of Australian researchers developed a smartphone app that could ostensibly identify respiratory disorders like pneumonia and bronchitis by "listening" to a person's exhalations. The potential for bias exists in these systems -- algorithms trained on imbalanced or unrepresentative datasets can lead to worse health outcomes for certain user groups -- but studies suggest they could be a useful tool on the front lines of the coronavirus pandemic.
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the coronavirus disease (COVID-19), continues to spread across the globe. With over 46.9 million people infected so far, it is crucial to determine how the virus spreads to mitigate its effect. Many people infected with the SARS-CoV-2 virus are asymptomatic (have no symptoms) or are pre-symptomatic (yet to present symptoms), which means that they can transmit the virus even if they do not feel any symptom at all. With a large fraction of people having no symptoms, it is hard to pinpoint those infected. Now, a team of researchers at the Massachusetts Institute of Technology (MIT) has found that asymptomatic people may differ from those who are healthy in the way they cough.