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Data Mining Large Internet Networks to Predict COVID-19 Hotspots

May 12, 2020 @ 9:00 am - 10:30 am

Every day counts in the COVID-19 response. How many lives would be saved if we were able to predict COVID-19 a week earlier? Or even a month? With the growing field of artificial intelligence, early prediction of outbreaks through large Internet networks is becoming a reality. Yet while artificial intelligence holds immense promise, challenges remain to harness its full potential.

By bringing together experts in artificial intelligence and health, this webinar will explore ways that data mining of Internet-based networks can be leveraged to predict COVID-19 hotspots; how we can overcome structural and political barriers to timely reporting and dissemination; and what partnerships are needed to reap the benefits of these tools globally.

Part of a new webinar series hosted by DASH, the Data Science and Artificial Intelligence Summits for Health. In partnership with Novartis Foundation, Harvard Global Health Institute and MIT Critical Data. Support provided by Harvard University Center for African Studies.

Elaine Nsoesie
Assistant Professor, Global Health, Boston University
Marcelo D’Agostino
Senior Advisor, Information Systems and Digital Health, Department of Evidence and Intelligence for Actions in Health, PAHO/WHO
Dr. Yu-Chuan Jack Li
Distinguished Professor, College of Medical Science and Technology, Taipei Medical University
Yuri Quintana
Chief, Division of Clinical Informatics, Beth Israel Medical Deaconess Center


May 12, 2020
9:00 am - 10:30 am
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