COVID+DS: The opportunity for wearables for early COVID detection

Recent technological advancements make it possible to closely and continuously monitor patients on multiple scales, both inside and outside of the clinic. These new technologies provide unprecedented opportunities for understanding and predicting health and disease but have also led to a deluge of biomedical data. In order to derive actionable health insights from these large volumes of data, a combination and biomedical data science and machine learning approaches are needed. 

Wearables offer a special opportunity for supporting our understanding and responsiveness to the COVID-19 pandemic. In this talk, I will discuss applications where machine learning has generated novel uses for wearable data, including real-time illness detection outside of the clinic and clinical decision support models, and will explore how these new applications are revolutionizing medicine. I will focus on use cases for how Duke is using wearable data in our response to the pandemic.

This session is part of the 8-week Duke+Data Science (+DS) program virtual Series on COVID-19 + Data Science.

On the day before the session, all registrants will receive an e-mail with a link and meeting information.

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