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Free AI-Based Phone App To Be Available Soon For Faster Detection of COVID-19

Free AI-Based Phone App To Be Available Soon For Faster Detection of COVID-19

Researchers at the Medical College of Georgia have been working to develop an AI-based framework using a Phone-based survey to reduce the time to identification of a person under investigation (PUI) for the COVID-19 infection as well as the rapid isolation of this individual.

The World Health Organization’s situational data indicates that there were more than 70 thousand confirmed cases with more than 2000 death rates. The researchers are trying to mitigate such issues by quick detection through the phone-based app without spending much of the available medical resources.

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They are using machine learning algorithms in a mobile phone-based web survey to improve possible case identifications of COVID-19 in a faster manner to bring timely interventions. The researchers hope that this app will help reduce the spread of the pandemic in the susceptible population.

According to sources, Arni S.R. Srinivasa Rao, PhD, director of the Laboratory for Theory and Mathematical Modeling in the MCG Division of Infectious Diseases at Augusta University (AU), and Jose Vazquez, MD, chief of the MCG Division of Infectious Diseases reported that the app, which could be available within the next few weeks, will also provide local and public health officials with additional real-time information on the emerging demographics of those most at risk of coronavirus infection. This will help to better target prevention and treatment initiatives.  

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To create the AI-based app, researchers have collected the basic travel history along with the more common manifestations using a  phone-based online survey, where the collected data can be used to assist in the preliminary screening and early identification of possible COVID-19 infected individuals. 

The collected data is then processed through artificial intelligence (AI) framework which can ultimately evaluate individuals that may be infected and stratify them into no-risk, minimal-risk, moderate-risk, and high-risk of being infected with the virus. The identification of the high-risk cases can then be quarantined earlier, thus decreasing the chance of spread.

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