Inside a bustling unit at St. Michael’s Hospital in downtown Toronto, one of Shirley Bell’s patients was suffering from a cat bite and a fever, but otherwise appeared fine — until an alert from an AI-based early warning system showed he was sicker than he seemed.

While the nursing team usually checked blood work around noon, the technology flagged incoming results several hours beforehand. That warning showed the patient’s white blood cell count was “really, really high,” recalled Bell, the clinical nurse educator for the hospital’s general medicine program.

The cause turned out to be cellulitis, a bacterial skin infection. Without prompt treatment, it can lead to extensive tissue damage, amputations and even death. Bell said the patient was given antibiotics quickly to avoid those worst-case scenarios, in large part thanks to the team’s in-house AI technology, dubbed Chartwatch.

“There’s lots and lots of other scenarios where patients’ conditions are flagged earlier, and the nurse is alerted earlier, and interventions are put in earlier,” she said. “It’s not replacing the nurse at the bedside; it’s actually enhancing your nursing care.”

  • DerisionConsulting@lemmy.ca
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    3 months ago

    This is exactly what we want machine learning to do, analyze existing data and quickly report to a human with what it found.

    Generative LLM’s are garbage, analyzing with machine learning aids is useful.

    • rekabis@lemmy.ca
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      3 months ago

      Generative LLM’s are garbage

      And they hallucinate uncontrollably. You literally cannot trust their output.