
How artificial intelligence could influence hospital triage
01/12/22 • 6 min
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The latest surge of COVID infections has hospitals crowded, short-staffed and, in some cases, rationing care. That means sometimes hospital clinicians have to go through a triage process to prioritize who gets care first, or at all. For example, a doctor may decide that a patient suffering respiratory failure should be admitted to the intensive-care unit over someone who seems to have minor injuries from a car accident. But that distinction, especially in a crisis, might not be so clear-cut. So medical research centers like Johns Hopkins and Stanford are studying how machine learning might help. Marketplace’s Kimberly Adams speaks with Dr. Ron Li, a clinical assistant professor at Stanford Medicine, where he’s medical informatics director for digital health and artificial intelligence clinical integration.
The latest surge of COVID infections has hospitals crowded, short-staffed and, in some cases, rationing care. That means sometimes hospital clinicians have to go through a triage process to prioritize who gets care first, or at all. For example, a doctor may decide that a patient suffering respiratory failure should be admitted to the intensive-care unit over someone who seems to have minor injuries from a car accident. But that distinction, especially in a crisis, might not be so clear-cut. So medical research centers like Johns Hopkins and Stanford are studying how machine learning might help. Marketplace’s Kimberly Adams speaks with Dr. Ron Li, a clinical assistant professor at Stanford Medicine, where he’s medical informatics director for digital health and artificial intelligence clinical integration.
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