Machine-Learning: Harvard Team Uses Social Media to Combat Coronavirus

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Machine-Learning: Harvard Team Uses Social Media to Combat Coronavirus

According to report in the online-edition of Wired Magazine, artificial intelligence researchers are applying machine-learning techniques to social media, web, and other data for subtle signs of where the deadly coronavirus may be spreading.

The virus first cropped up in Wuhan, China, in December and has since triggering global hysteria, although it still remains unclear how dangerous and how contagious the virus is. As of mid-February, more than 31,000 people have been diagnosed with the disease in China, and at least 700 people have died, according to figures released by Chinese authorities.
According to the report, John Brownstein, chief innovation officer at Harvard Medical School and an expert on mining social media information for health trends, is part of an international team using machine-learning to comb through social media posts, news reports, data from official public health channels, and information supplied by doctors for warning signs the virus is taking hold in countries outside of China.

What we’re doing currently with Coronavirus is really trying to get an understanding of what’s happening on the ground through as many sources as we can get our hands on,

says John Brownstein, chief innovation officer at Boston Children’s Hospital and a professor at Harvard Medical School.
Other researchers and startups are reportedly also using artificial intelligence and other technologies to predict where the virus might appear next — and even potentially sound the alarm before other new, potentially threatening viruses become public health crises.
The Harvard team has created a tool it calls Healthmap, which collects information about new outbreaks from online news reports, chatrooms and more and uses the information to generate a map-like visualization that shows how and where the disease has been identified.

Author: Tim Cole
Image Credit: Pixabay

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