
Sign up to save your podcasts
Or


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.
By Marketplace4.5
12561,256 ratings
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.

32,243 Listeners

30,635 Listeners

8,799 Listeners

937 Listeners

1,387 Listeners

1,649 Listeners

2,177 Listeners

5,485 Listeners

113,357 Listeners

56,985 Listeners

9,556 Listeners

10,321 Listeners

3,618 Listeners

6,111 Listeners

6,589 Listeners

6,461 Listeners

163 Listeners

2,990 Listeners

154 Listeners

1,380 Listeners

91 Listeners