ML and Epidemiology with Elaine Nsoesie

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Today we continue our ICML series with Elaine Nsoesie, assistant professor at Boston University.

Elaine presented a keynote talk at the ML for Global Health workshop at ICML 2020, where she shared her research centered around data-driven epidemiology. In our conversation, we discuss the different ways that machine learning applications can be used to address global health issues, including use cases like infectious disease surveillance via hospital parking lot capacity, and tracking search data for changes in health behavior in African countries. We also discuss COVID-19 epidemiology, focusing on the importance of recognizing how the disease is affecting people of different races, ethnicities, and economic backgrounds.

Thanks to our sponsor

I’d like to send a huge thank you to our friends at Qualcomm for their support of the podcast, and their sponsorship of this series! Qualcomm AI Research is dedicated to advancing AI to make its core capabilities — perception, reasoning, and action — ubiquitous across devices. Their work makes it possible for billions of users around the world to have AI-enhanced experiences on Qualcomm Technologies-powered devices. To learn more about what Qualcomm is up to on the research front, visit here.

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“More On That Later” by Lee Rosevere licensed under CC By 4.0

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