Data & Science with Glen Wright Colopy

The Pod of Asclepius is a healthcare technology podcast for the technical crowd. No fluff, no sales pitches, just important health tech ideas (described well!) to help everyone keep learning and becoming more of an expert in the field. Our guests are top researchers (from academia and industry), entrepreneurs, and regulatory experts. They will talk about cool technology, from data science to engineering, but also share insights on practical concerns of bridging the gap between technical innovation and a clinical solution.

Data & Science with Glen Wright Colopy is a science podcast hosted by Glen Wright Colopy, with 89 episodes on record and a Required Pod Score of 82. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Glen Wright Colopy hosts Data & Science with Glen Wright Colopy, a science show with 89 episodes published.

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  Episode #91

  Keith O’Rourke | The Logic of Statistics

  Aug 2, 20221h 13mS0

  <p>Keith O'Rourke | The Logic of Statistics</p> <p>Dr. Keith O'Rourke talks about the logical reasoning behind statistical modeling. Topics include mathematical vs scientific reasoning, whether science has become too stats focused, and vice versa.</p> <p>Watch it on...<br> Youtube: https://youtu.be/FqE4ROHBKpY<br> Podbean: https://dataandsciencepodcast.podbean.com/e/keith-o-rourke-the-logic-of-statistics/</p> <p> </p> <p>Topic List:</p> <p>0:00 - The logic of statistics<br> 0:30 - What is scientific statistics?<br> 5:15 - The logic of statistics and CS Pierce<br> 9:15 - Role of representation in statistics: explicit vs implicit<br> 14:13 - Diagrammatic Reasoning<br> 18:45 - W...

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  Episode #90

  Jack Fitzsimons | Evil Models: Hiding Malware in Neural Networks

  Jul 25, 202252 minS0

  <p>Jack Fitzsimons | Evil Models: Hiding Malware in Neural Networks</p> <p>Did you know that it's possible to hide malware in neural networks? Actually, you can hide malware in many statistical models. This is the subject of two recently-published papers (aptly titled "EvilModel" & "EvilModel 2.0"). Dr. Jack Fitzsimons makes it easy to understand how this is done, using techniques that began long before computers.  </p> <p> </p> <p>Watch or listen on... <br> Youtube: https://youtu.be/QBnk8ogL8Nk<br> Podbean: https://dataandsciencepodcast.podbean.com/e/jack-fitzsimons-evil-models-hiding-malware-in-neural-networks/</p>

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  Episode #89

  Scott Cunningham | Causal Inference (The Mixtape)

  Jul 17, 20221h 21mS0

  <p>Scott Cunningham | Causal Inference (The Mixtape)<br> Scott Cunningham (Baylor University) discusses the ideas of his book "Causal Inference: The Mixtape". Topics include trusting inference in the absence of counterfactuals and the challenges of apply scientific methods to social phenomena. </p> <p>Watch it on...<br> YouTube: https://youtu.be/yNaCudDVTkY<br> Podbean: https://dataandsciencepodcast.podbean.com/e/scott-cunningham-causal-inference-the-mixtape/</p> <p>0:00 - COMING UP...<br> 0:35 - What makes it into the mixed tape?<br> 7:10 - Coding to learn<br> 11:15 - More people are expected to work with data & code<br> 12:50 - Design vs program vs estimators<br> 20:40 - Causation w...

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  Episode #88

  Eric Daza | Important Ideas in Causal Inference

  Jul 10, 20221h 24mS0

  <p><br> Eric Daza | Important Ideas in Causal Inference</p> <p>YouTube: https://youtu.be/K5nsSMJVIT0<br> <br> </p> <p>Andrew Gelman and Aki Vehtari wrote a paper titled, "What are the most important statistical ideas of the past 50 years?". The first idea in the list is "counterfactual causal inference". Eric Daza (Evidation Health) walks us through the main ideas of the Gelman & Vehtari paper, drawing examples from several fields, including medical & healthcare statistics. </p> <p>Topics<br> 0:00 - Coming up...Correlation vs Causation<br> 1:20 - Most important statistical ideas over the last 50 years<br> 6:10 - Counterfactual Causal Inference<b...

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  Episode #28

  Wenting Cheng & Weidong Zhang | Advances in Biotech/Biopharma

  May 9, 202235 minS0

  <p>Wenting and Weidong discuss how the statistical challenges in the biopharm industry have proliferated with the unique demands of biotech and related life science industries.</p>

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