logo
episode-header-image
Apr 2021
40m 17s

Pandemic Machine Learning Pitfalls

Kyle Polich
About this episode

Today on the show Derek Driggs, a PhD Student at the University of Cambridge. He comes on to discuss the work Common Pitfalls and Recommendations for Using Machine Learning to Detect and Prognosticate for COVID-19 Using Chest Radiographs and CT Scans.

Help us vote for the next theme of Data Skeptic!

Vote here: https://dataskeptic.com/vote

Up next
Oct 5
Implicit Interactions
How do we design robots and autonomous vehicles that understand the unwritten rules of human behavior? Kyle speaks with Cornell Tech professor Wendy Ju about implicit interaction, "Wizard of Oz" prototyping, and what studying pedestrians, self-driving cars, and even robotic furni ... Show More
44m 34s
Sep 25
The Lived Informatics Model
The data we collect about ourselves can tell us a lot—but only if the technology collecting it actually fits into our lives. Daniel Epstein explores personal informatics, from fitness trackers and food journals to baby tracking and AI, and explains why abandoning a tracking tool ... Show More
34m 13s
Sep 9
Recommender Systems Today and Tomorrow
In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user control. From fake reviews and shilling attacks to explainable recommendations and user-selected algorithms, we look at wha ... Show More
22m 46s
Recommended Episodes
Apr 2015
Starting Simple and Machine Learning in Meds
In episode nine we talk with George Dahl, of  the University of Toronto, about his work on the Merck molecular activity challenge on kaggle and speech recognition. George recently successfully defended his thesis at the end of March 2015. (Congrats George!) We learn about how net ... Show More
38m 24s
Mar 2020
345: Machine Learning At Twitter
I speak with Dan Shiebler who works as a machine learning engineer at Twitter Cortex and at the same time, is doing a Ph.D. on applying category theory in machine learning. We discuss his work at Twitter, the importance of academics, and the future of machine learning. In this e ... Show More
1h 12m
Oct 2021
Kevin Zatloukal — Machine Learning And Its Applications (EP.68)
tail spinning
51m 44s
Sep 2021
Horrorscope
<p>Andy and Dave discuss the latest in AI news and research, including:</p> <p>0:57: The Allen Institute for AI and others come together to create a publicly available "COVID-19 Challenges and Directions" search engine, building off of the corpus of COVID-related research.</p> <p ... Show More
43m 54s
Jul 2025
Can AI Accelerate Science? Dr. Andy Beam on AI’s Next Frontier
<p><a href='https://mcdn.podbean.com/mf/web/w5aftmmy3fux99mq/Episode_32_Beam_bio.pdf'>Dr. Andy Beam</a> has trained models, mentored scientists, and used data to quantify the value of treatments. In this episode of NEJM AI Grand Rounds, Raj Manrai turns the table on his co-host, ... Show More
1h 7m
Dec 2020
Michael Drake: Higher Ed in the Time of Covid
Michael Drake, newly installed as the president of the University of California, talks about the challenges in the age of Covid of running an institution of 10 campuses and some half-million students and staff.Support the show: https://www.patreon.com/clearandvividSee omnystudio. ... Show More
30m 21s
Aug 2021
Applications of Variational Autoencoders and Bayesian Optimization with José Miguel Hernández Lobato - #510
Today we’re joined by José Miguel Hernández-Lobato, a university lecturer in machine learning at the University of Cambridge. In our conversation with Miguel, we explore his work at the intersection of Bayesian learning and deep learning. We discuss how he’s been applying this to ... Show More
42m 27s