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AI clinical health

Comment: An AI Epidemiologist Sent the First Warnings of the Wuhan Virus

…the algorithm doesn’t use social media postings because that data is too messy. But he does have one trick up his sleeve: access to global airline ticketing data that 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.

Niiler, E. (2020). An AI Epidemiologist Sent the First Warnings of the Wuhan Virus. Wired magazine.

It’s important to remember that clinical AI isn’t only going to influence how individuals interact with each other. AI-based systems that aggregate and interpret massive volumes of information moving across multiple networks is going to help us respond to medical emergencies at national and international levels. These systems won’t rely on official sources of information, like governments or peer-reviewed publications, or even unofficial sources like Twitter, but rather on the collective behaviour of thousands of people who are just going about their day.

In the same way that simply having a phone in your car while driving means that Google can make predictions about traffic throughout the day, systems that track our behaviour over time will help healthcare professionals make sense of important, large-scale events that are impossible for human beings to predict.