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The MaML Podcast - Medicine & Machine Learning

Latest episodes

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Oct 14, 2020 • 1h 4min

Miguel Alvarado - Delivering Big Data & AI to Patients, Providers, and Insurers in Industry

Miguel Alvarado is the CTO of Lumiata, a healthcare AI company based in SF. In this episode, we talk about Miguel’s unconventional journey from Microsoft in the 90s all the way up until the present moment where he is helping bring the power of big data and AI to patients, providers, and insurers. Just like Bruce Wayne, Miguel works during the day, but at night, has an alter ego. we will talk about his passion as an underground house and techno DJ and finally, we will close with a conversation about the importance of being present. I had a real pleasure conducting this interview with Miguel and I hope you enjoy it. 00:00 Intro 02:00 Beginnings 12:30 What does Lumiata do 23:40 Synthetic Data 30:00 Explainability in models 34:00 what do you think is the future of AI in medicine 40:00 the importance of being present 44:00 the importance of having other passions 51:00 dj’ing, techno, and being fully present 55:00 machine learning and.. music?!
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Aug 31, 2020 • 42min

Christopher J Weight, MD - Kidney Cancer & AI

Welcome to the very first episode of the Medicine and Machine Learning Podcast, AKA the MaML Podcast brought to you by the Medicine and Machine Learning Club of the University of Minnesota Medical School. We are a group of students passionate about learning more about the future of medicine and AI. This Podcast will feature interviews from prominent figures in academia, industry, and medicine exploring the cutting edge of healthcare’s newest frontier: medicine & machine learning. My guest today is Dr. Christopher Weight, the new Director of Urologic Oncology at the Cleveland Clinic. In addition to this role, Dr. Weight is currently helping build a new center for AI and Medicine at the Cleveland Clinic. In this episode, we will be talking about his unique path in medicine and how it led to building one of the largest and most comprehensive kidney cancer imaging datasets we have today.

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