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AI speech processing framework detects inaudible COVID-19 cough


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.

MIT algorithm detects COVID-19 in the sound of your cough


A new MIT algorithm is capable of determining, with impressive accuracy, whether or not people have COVID-19 -- just by listening to them cough. The algorithm, which the researchers trained using the sound of tens of thousands of coughs recorded over the course of the pandemic, has a 98.5 percent success rate among patients who were already diagnosed with COVID-19, BBC News reports. If they didn't have any other symptoms aside from that cough, the success rate climbed to 100 percent. It shouldn't replace a proper lab test, the BBC suggests, but it could serve as a point-of-contact test before meeting a group or attending an event. Other teams of scientists have tried to diagnose the coronavirus for just about as long as the pandemic has been raging. In March, Carnegie Mellon University scientists built a "COVID Voice Detector" app that scanned for signs of COVID-19 in the sounds of people coughing and reciting the alphabet.

AI can detect COVID-19 by listening to your coughs


It's easy to be worried when you cough these days -- is it COVID-19, or are you just clearing your throat? You might get a clearer answer soon. MIT researchers have developed AI that can recognize forced coughing from people who have COVID-19, even if they're otherwise asymptomatic. The trick was to develop a slew of neural networks that can distinguish subtle changes indicative of the novel coronavirus' effects. One neural network detects sounds associated with vocal strength.

AI model can detect coronavirus from the sound of a cough - but humans can't


Scientists have created an artificial intelligence model that can detect if someone has coronavirus - purely from the sound of their cough. The AI algorithm, built in the US, correctly identified patients who were infected even if they had no other symptoms. Researchers say humans are unable to hear the vital difference in the sound of someone with a cough who is asymptomatic. They say this is because Covid-19 changes the way you produce sound, even if there are no symptoms. The model, developed by the Massachusetts Institute of Technology (MIT), was 98.5% successful in detecting people who had officially tested positive for Covid-19.

AI Model Detects Asymptomatic Covid-19 Infections Through Cellphone-Recorded Coughs


Massachusetts Institute of Technology researchers have found that people who are asymptomatic for Covid-19 may differ from healthy individuals in the way that they cough, which can be captured by artificial intelligence. Massachusetts Institute of Technology (MIT) researchers have developed an artificial intelligence model that differentiates between asymptomatic people infected with Covid-19 and healthy individuals via forced-cough recordings submitted through Web browsers, cellphones, and laptops. The MIT team trained the model on cough samples and spoken words; it accurately identified 98.5% of coughs from people confirmed to have the virus (100% from those who are asymptomatic) when fed new cough recordings. The researchers are incorporating the model into a user-friendly application which could potentially be a free, convenient, noninvasive prescreening tool to identify asymptomatic people infected with the virus. Users could log in daily, cough into their handset, and instantly receive information on whether they might be infected and confirm with a formal test.