We generally think of AI in healthcare as the use of the new technology either directly in a healthcare setting or in healthcare-related research.
But as officials around the world scramble to contend with the cornoavirus outbreak out of China, AI is demonstrating its capacity to contribute well outside the usual healthcare settings.
According to an article at Vox, one key use for AI that is proving critical right now is its ability to “automatically mine through news reports and online content from around the world, helping experts recognize anomalies that could lead to a potential epidemic or, worse, a pandemic.”
To that end, the outbreak was reportedly “identified early by a Canadian firm called BlueDot, which is one of a number of companies that use data to evaluate public health risks. The company, which says it conducts ‘automated infectious disease surveillance,’ notified its customers about the new form of coronavirus at the end of December, days before both the US Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) sent out official notices.”
According to Kamran Khan, an infectious disease physician and BlueDot’s founder and CEO, “the company’s early-warning system uses artificial intelligence, including natural-language processing and machine learning, to track over 100 infectious diseases by analyzing about 100,000 articles in 65 languages every day. That data helps the company know when to notify its clients about the potential presence and spread of an infectious disease.
“Other data, like traveler itinerary information and flight paths, can help give the company additional hints about how a disease will likely spread. For instance, earlier this month, BlueDot researchers predicted other cities in Asia where the coronavirus would show up after it appeared in mainland China.”
The goal for BlueDot, said Khan, is to notify healthcare workers as quickly as possible in the hope of containing potential outbreaks.
“The difference between one case in a traveler and an outbreak depends upon your frontline health care worker recognizing that there is a particular disease. It could be the difference in preventing an outbreak from actually occurring,” he explained.
Khan added that his system can also use an array of other data — such as information about an area’s climate, temperature, or even local livestock — to predict whether someone infected with a disease is likely to cause an outbreak in that area. He points out that, back in 2016, BlueDot was able to predict the appearance of the Zika virus in Florida six months before it actually showed up there.