AI Predict Death

The AI can automatically calculate the risk of patient deterioration up to six hours in advance of when a doctor might notice.

The U.S. Food and Drug Administration (FDA) has approved the very first algorithm that monitors a patient’s vitals to help predict sudden death from heart attacks or respiratory failure. This artificial technology is going to help free up the severely limited resources in medicine. 

The algorithm, called Wave Clinical Platform, has been developed by medical technology company ExcelMedical, and consists of an integrated system of hospital workstations and digital medical records that includes real-time data on a patient’s medications, age, physiology, past medical history, family history etc. With this information, the algorithm can sense subtle changes in vitals and sends alerts up to six hours before a potentially lethal event could occur. 

“I just think there’s so much ‘blah blah’ out there about predictive analytics. But this is real-time, this is actionable, and this can save lives,” Excel Medical’s Chief Strategy Officer Mary Baum told Healthcare Analytics News.


“Everything we do as an organization aligns toward and supports the goal of eradicating unexpected deaths in hospitals,” Lance Burton, General Manager of Excel Medical, said in a statement. “People may say zero unexpected deaths is unattainable. We say anything other than zero is unconscionable.”

Currently, the plan is to implement this tech in hospitals, but Burton told Healthcare Analytics News that the company hopes to eventually make the AI wearable devices usable for people at home.

Artificial intelligence is showing more, and more promise within biomedicine. Just last week, Microsoft announced a new A.I. project, where they are hoping to tackle the ‘big data problem’ by making diagnosing nearly any disease as simple as a single blood test. 

Last year, the UK’s National Health Service (NHS) and Intel announced that they would be working together to make cancer detection more efficient through AI. 

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