The team has developed a solution applying artificial intelligence to the accurate diagnosis of Covid-19 infections and provides intervention options. Infection patterns vary by country and territory. As a result, interventions may work in one country or territory but be less effective in another. A total 48 teams from 17 countries were selected for the final round out of a total 104 teams from 28 countries in the semi-finals. The results will be announced at the end of February 2021. The jury selected the VinBrain team for the final round based on the accuracy of its AI models and ability to easily interpret predictions of the solution. This approach can be used for any future pandemic response model. Members of VinBrain in the U.S. have come up with an extensive solution to this problem by developing region-specific AI models to predict the Covid-19 infection time series in those regions. The solution was based on the classical epidemic SEIR model, which was then expanded to integrate artificial intelligence. Amir Banifatemi, GM for Innovation and Growth at VinBrain in U.S. Photo courtesy of VinBrain . In order to train its AI models, the team used available data like demographics, medical infrastructure, and economic indicators. A special feature used by the VinBrain team is Google Maps mobile metrics collected from worldwide Android phones in an anonymous and secure way, measuring the movements of people in public areas like parks, hospitals, workplaces, grocery stores, stations, airports. Another unique feature used by the VinBrain team is Google's Covid-19 infection trend data aggregated anonymously and that contains popular Covid-19 symptom-related Google searches. The Pandemic Response Challenge co-organized by XPRIZE and Cognizant was launched in November 2020. With prize money of $500,000, the contest aims to harness the power of data and artificial intelligence to predict Covid-19 infection rates, and propose intervention …
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