This A.I. eavesdrops on emergency calls to warn of possible cardiac arrests

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When you phone 911, you’re patched through to a trained human who is able to properly triage your phone call. Soon, you could also find yourself being listened to by a robot, however, who is tuning in to very different verbal information from the human emergency dispatcher.

Developed by Danish startup Corti, this emergency call-listening artificial intelligence is designed to listen to the caller for signs that they may be about to go into cardiac arrest. When it makes such a diagnosis, it then alerts the human dispatcher so that they can take the proper steps.

“Corti is meant to be a digital co-pilot for medical personnel,” Andreas Cleve, CEO of Corti, told Digital Trends. “Like a human doctor, Corti analyzes everything a patient says and shares in real time — from journal data, symptom descriptions, voice data, acoustic data, language data, their dialect, questions, and even their breathing patterns. Corti then outputs diagnostic advice to the medical personnel, to help them diagnose patients faster. This can be especially powerful in an emergency use case where mistakes can be fatal.”

As the company’s Chief Technology Officer Lars Maaloe told us, the technology framework uses deep learning neural networks trained on years of historical emergency calls. While it hasn’t yet been peer-reviewed, the team is currently working on this. A paper describing the work is likely to published later in 2018.

“Today the technology is being used in Copenhagen EMS, who have spearheaded the application of machine learning in the prehospital space worldwide,” Cleve said. “At Copenhagen EMS, our technology is able to give emergency call takers diagnostic advice in natural language, and it’s integrated directly into the software they are already using. Our goal is to make it easier for medical personnel to do their jobs, not complicate it further with fancier technology. We are extremely skeptical of the idea of rushing to replace trained medical personnel with A.I., since from both ethical and professional perspective we prefer human contact when it comes to our health. Personally, I simply can’t see myself preferring a bot over a medically trained human agent. But the setup where humans are amplified by A.I.? That to us is a far more powerful scenario in healthcare.”