Two dynamic analytics models developed at Johns Hopkins University predicted delirium-prone patients when tested on two datasets drawn from 100,000 stays at a Boston hospital’s intensive care unit, according to new research.WHY IT MATTERS
Delirium – sudden bouts of confusion, inattention, paranoia, agitation and hallucinations – can put patients at higher risk of prolonged hospitalization, future dementia and death. By forecasting delirium, alerted clinicians could apply countermeasures that can mitigate adverse outcomes, according to the premise of artificial intelligence research published in Anesthesiology.
“For a lot of these physiological transitions, we think that there are early warning signs that may not be obvious…
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