MIT Lab Thinks It Can Diagnose COVID-19 from the Way You Cough
upstart writes in with an IRC submission for RandomFactor:
Academics claim their AI software can detect, with 98.5 per cent accuracy, whether or not someone has caught the COVID-19 coronavirus, just from the sound of their coughing.
To build this software, the MIT team used three ResNet50 models, a popular convolutional neural network designed by Microsoft. They're normally used to process images for computer vision, though in this case they're analyzing audio.
The boffins produced a dataset of 5,320 people, who in April and May submitted audio clips of themselves coughing. Participants also had to fill out a questionnaire that asked if they had caught the coronavirus or not, if they had confirmed this with an official test or not, and what symptoms they had. Thus this experiment relies on the honesty of these human data sources, so bear that in mind.
[...] The results appear promising enough that the team said they are working with a Fortune 100 company to flesh out their model into a fully fledged diagnostic tool.
[...] "The effective implementation of this group diagnostic tool could diminish the spread of the pandemic if everyone uses it before going to a classroom, a factory, or a restaurant."
[...] "The sounds of talking and coughing are both influenced by the vocal cords and surrounding organs," Subirana said.
"This means that when you talk, part of your talking is like coughing, and vice versa. It also means that things we easily derive from fluent speech, AI can pick up simply from coughs, including things like the person's gender, mother tongue, or even emotional state. There's in fact sentiment embedded in how you cough.
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