Tag Archives: machine learning

Experts talk in D.C. about how to get past the A.I. buzz

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About Tina Reed

Tina Reed is executive editor of FierceHealthcare in Washington, D.C. Previously, she was a health care reporter for the Washington Business Journal. She is co-chair of AHCJ’s Washington, D.C. Chapter.

Photo: Kimberly Leonard

Trying to write critically about a new use of artificial intelligence?

Start by asking your sources three questions:

  1. How far they are away from the point of delivery?
  2. How much data are they working with and what is the diversity or scope of the population the data was gathered from?
  3. And finally, what kinds of algorithms did they apply and what sorts of devices are they limited to using?

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How machine learning and artificial intelligence might influence social determinants of health

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About Emily Willingham

Emily Willingham (@ejwillingham) is AHCJ's core topic leader on the social determinants of health. She is a science journalist whose work has appeared in the Washington Post, San Francisco Chronicle, Wall Street Journal, Scientific American, and Forbes, among others, and co-author of "The Informed Parent: A Science-Based Guide to Your Child's First Four Years."

Photo: z rahen via Flickr

This might not seem specific to social determinants of health, but machines that can be trained in health information may become gatekeepers of the future. If the artificial intelligence and medicine intersect successfully, the result could prove lifesaving for people whom social factors leave at a disadvantage. Continue reading →