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An AI algorithm detected the Coronavirus outbreak a week before scientists and doctors did

Using machine learning and AI, an algorithm utilized by Canadian firm BlueDot was able to detect the Coronavirus outbreak a week before the CDC and WHO did.

GIven that organizations like the CDC and WHO have to rely on official sources to confirm outbreaks, they are prone to fallible human politicians with their own agendas "BlueDot uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations" which allows it to overcome tight-lipped officials As of this writing, there have been 7,815 cases worldwide of the virus, with 170 dead already, though deaths have been confined to China

On the 6th and 9th of January, the Centre for Disease Control (CDC) and World Health Organization (WHO) respectively warned the world of a Coronavirus outbreak originating in Wahun, China. Since then, and as of this writing, there have been 7,815 cases worldwide, with 170 dead already, though fatalities are confined to mainland China. 

What if I told you that an AI algorithm had warned us of the outbreak a week prior?

Machine beats manGraphs by CNNLast month, a Canadian health monitoring platform sent word to its customers of a potential Coronavirus outbreak an entire week before the CDC and WHO made their official announcements. 

This fascinating reveal comes courtesy of an exclusive report by Wired, who first broke the story. 

BlueDot uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan,” Wired explained.

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How it works

GIven that organizations like the CDC and WHO have to rely on official sources to confirm outbreaks, they are prone to fallible human politicians with their own agendas. As Wired explains, “tight-lipped Chinese officials do not have a good track record of sharing information about diseases, air pollution, or natural disasters. But public health officials at WHO and the CDC have to rely on these very same health officials for their own disease monitoring.”

An AI has no concern for officials and human permission – it instead deals with available data and reports to formulate its own conclusion, which happened to be right on the money this time. 

“We know that governments may not be relied upon to provide information in a timely fashion,” says Kamran Khan, BlueDot’s founder and CEO. “We can pick up news of possible outbreaks, little murmurs or forums or blogs of indications of some kind of unusual events going on.” 

According to Khan, Bluedot doesn’t use social media postings because that data is too messy, which makes sense given the volume of fake news on sites like Facebook. However, the algorithm leverages another piece of crucial data: global airline ticketing data. As per Wired’s report, this data can help predict where and when infected residents are headed next. It correctly predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei, and Tokyo in the days following its initial appearance. 

Khan explained that once the program completes its data collection, human analysis takes over. Epidemiologists check that the conclusions make sense from a scientific standpoint, and then a report is sent to government, business, and public health clients.

“BlueDot’s reports are then sent to public health officials in a dozen countries (including the US and Canada), airlines, and frontline hospitals where infected patients might end up,” Wired said. “BlueDot doesn’t sell their data to the general public, but they are working on it, Khan says.”

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How BlueDot came to be

Khan was motivated to create BlueDot and the algorithm after a harrowing personal experience during the SARS outbreak in 2003 while working as a hospital infectious disease specialist. 

“There’s a bit of deja vu right now,” Khan says about the coronavirus outbreak today. “In 2003, I watched the virus overwhelm the city and cripple the hospital. There was an enormous amount of mental and physical fatigue, and I thought, ‘Let’s not do this again.’”

Khan launched BlueDot in 2014 and raised $9.4 million in venture capital funding after multiple trials of various algorithm software. 

“The company now has 40 employees—physicians and programmers who devise the disease surveillance analytic program, which uses natural-language processing and machine learning techniques to sift through news reports in 65 languages, along with airline data and reports of animal disease outbreaks,” Wired reports.

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