Covid-19 has created a havoc in most places in the world and has shown no signs of going away. The number of people affected by the virus has been on the rise and so are the testing numbers. A team of researchers at Massachusetts Institute of Technology (MIT) have developed an app that will be able to diagnose Covid-19 by analysing people’s cough.
As per multiple online reports, the researchers used machine learning (ML) and artificial intelligence (AI) to find out if anyone has Covid-19 but are asymptomatic and those who are fine and aren’t infected.
The app uses an AI framework which is based on a similar one used for Alzheimer’s research. The model users four biomarkers related to vocal cord strength, lung and respiratory response, sentiment and muscular degradation specific to Covid-19.
The team of researchers collected about 70,000 recordings from a site where people left samples of coughs through their smartphones. These recordings led to about 200,000 forced cough samples and out of which 2,500 were confirmed to have Covid-19 or were asymptomatic. “When validated with subjects diagnosed using an official test, the model achieves COVID-19 sensitivity of 98.5% with a specificity of 94.2% (AUC: 0.97). For asymptomatic subjects it achieves sensitivity of 100% with a specificity of 83.2%,” the researchers noted.
As per reports, the researchers noted in their conclusion, “AI techniques can produce a free, non-invasive, real-time, any-time, instantly distributable, large-scale COVID-19 asymptomatic screening tool to augment current approaches in containing the spread of COVID-19.”
They further said that, “practical use cases could be for daily screening of students, workers, and public as schools, jobs, and transport reopen, or for pool testing to quickly alert of outbreaks in groups.”
A pre-screening app is being created by the team of researchers and it intends to distribute it to free. It is also reported that the team will work with a number of hospitals to increase the cough recording pool for further research and training.
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