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Scary: New Artificial Intelligence Can now predict death.

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Artificial intelligence, has taken the place of human intelligence. And it isn’t stopping there. It has made a new mark in the medical industry, to enable overwhelmed medical professionals, and relief them of some stress.

Its functions have been significant In palliative care centers, which include nursing and health care centre.  According to industry on blast, The aging population has stretched medical and personnel resources to the limit, which just may mean this is the perfect time for Artificial Intelligence  to step in and help with both monitoring patients’ vital signs and making potentially lifesaving discoveries.

The Food and Drug Administration (FDA) just approved the first algorithm that can monitor a patient in critical care and anticipate a life-threatening change in condition by up to 6 hours. The algorithm, called Wave clinical platform and developed by medical technology company Excel medical, is able to keep a 24/7 vigil over a patient, which is simply not possible for already overworked human care workers in busy hospitals. The AI can also monitor patterns in vitals so as to determine whether, say, a sudden and simultaneous drop in oxygen saturation and a spike in blood pressure could be lethal.

Meanwhile, a research team at Stanford University is using an AI algorithm to predict patient mortality. A notoriously difficult task, predicting when a patient will die involves assessing a variety of factors from age and patient history to drug response and the illness itself. But it’s important to be as accurate as possible. Admitting a patient into end-of-life care too soon consumes valuable resources; admitting them too late risks leaving the patient cut off from their family.

Stanford’s AI has a 90% accuracy rate, which, according to some, is surprisingly and unsettlingly good. Created by feeding electronic health records (EHR) into a deep learning neural network, the AI is able to “sense” patient mortality within the next three to twelve months.

Jeremy Hsu of IEEE Spectrum described the model used as “an 18-layer Deep Neural Network that inputs the EHR data of a patient, and outputs the probability of death in the next 3-12 months”

Source: The Industry On blast

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