Hi ASA Connect,
We have published quite a few episodes that haven't been advertised yet, and thought you might enjoy this one: Glen Wright Colopy (Cenduit) discusses Oxford University's research in hospital patient vital sign monitoring, with a particular focus on how probabilistic machine learning can assist with visual intuitive personalized health inference.
Why should data scientists and statisticians watch this episode?
- We start by illustrating why hospital vital signs are ripe for data-driven innovation.
- The episode is replete with animations of machine learning algorithms in action. This underlines a key point that many vital sign warning are visualizable.
- Particular attention is given to the statistical components of machine learning algorithms and how the probability is critical to clinical reasoning.
- Have you ever seen Gaussian processes train other Gaussian processes? Now's your chance!
Watch it on…
YouTube: https://www.youtube.com/watch?v=9c5lBUCWAfQ
Podbean: https://podofasclepius.podbean.com/e/s00-ep01-personalized-probabilistic-patient-monitoring-part-1-gaussian-processes-for-identifying-the-deteriorating-patient/
Also available on:
iTunes: https://podcasts.apple.com/us/podcast/the-pod-of-asclepius/id1494970096
Stitcher: https://www.stitcher.com/podcast/the-pod-of-asclepius
Podchaser: https://www.podchaser.com/podcasts/the-pod-of-asclepius-986797
Tune In Radio: https://tunein.com/podcasts/Technology-Podcasts/Pod-of-Asclepius-p1285880
and Google Play
You can catch up on all episodes using our playlists:
Season 0 Playlist Season 1 Playlist
Pod of Asclepius is sponsored by the ASA's Statistical Learning and Data Science Section, Medical Device and Diagnostics Section, and North Carolina Chapter.
Enjoy!
Nick
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Nicholas Horton
Beitzel Professor of Technology and Society (Statistics and Data Science)
Amherst College
Amherst, MA United States
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