Better Medicine Through Machine Learning | Suchi Saria | TEDxBoston

Faster medical treatment saves lives. Machine Learning is already saving lives, by scouring a multitude of patients’ data and comparing them to one patient’s health data to detect symptoms 12 to 24 hours sooner than a doctor could. “In many pressing medical problems, the answers to knowing whom to treat, when to treat, and what to treat with, might already be in your data” says Suchi Saria. Learn how TREWS (Targeted Real-time Early Warning Score) is leading the way to save lives.

Suchi Saria is a professor of computer science and health policy, and director of the Machine Learning and Health Lab at Johns Hopkins University. Her research is focused on designing data solutions for providing individualized care.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at

3 comments

  1. Tapabrata Ghosh says:

    Wouldn’t DL or some other ML method be much better for this task than deep
    reinforcement learning?

    EDIT: The talk about deep reinforcement learning at the start was a red
    herring, they use supervised learning in the paper.

  2. Steve Major says:

    We should all have a private TREWS where we could enter day to day journal
    data like stomach ache or a headache, medicines taken, diet, test results,
    etc. that would be part of your private medical record.

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