Having A Heart Attack? This AI Helps Emergency Dispatchers Find Out

By: Guest Author | Posted on: Jan 16, 2018

This article was originally published on ampproject.org by ADELE PETERS View the original article by clicking here. 

When someone goes into cardiac arrest outside of a hospital, time is critical: The chance of survival decreases about 10% with each minute. The first step–recognizing that it’s cardiac arrest, when your heart fully stops–is challenging for emergency dispatchers on the phone, who have to make sense of symptoms relayed by a panicked friend or relative.

In Copenhagen, dispatchers now have help from AI. If you call for an ambulance, an artificially intelligent assistant called Corti will be on the line, using speech recognition software to transcribe the conversation, and using machine learning to analyze the words and other clues in the background that point to a heart attack diagnosis. The dispatcher gets alerts from the bot in real time.

It’s a situation where dispatchers typically have to rely only on their own knowledge. “If you and I have a problem, we end up Googling or asking people,” says Andreas Cleve, CEO of the startup that created the technology. “These people are handling more or less the worst days of our lives but they have no tools to do it.”

Dispatchers in Copenhagen, who are well trained, can recognize cardiac arrest from descriptions over the phone around 73% of the time. But the AI can do better. In an early, small-scale study, the machine learning model knew the calls were reporting cardiac arrest 95% of the time. Another study, which analyzed 170,000 calls, will soon be published.

Like other machine learning technology, Corti isn’t designed to look for any particular signals. Instead, it “trains itself” by listening to the sound from a huge set of calls to identify important factors, and then continually improves its model as it works. Non-verbal sounds are often important, and the technology has to be able to sort through background noise like sirens and yelling to identify clues. In one case, when the startup was first testing the technology, a woman called the emergency number to report that her husband had fallen off the roof of their house. As the dispatcher listened, she realized that the man had broken his back, and gave instructions on what to do before the ambulance arrived. But Corti said the incident wasn’t a broken back, but that his heart had stopped...

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