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Informatics Research Seminar: The Rise of Global Digital Health, Big Data and Machine Learning

January 22 @ 4:00 pm - 5:00 pm EST

Speaker: David D. Potenziani, PhD, Amy Finnegan, PhD

Presented from UNC-Chapel Hill

Broadcast Link: Seminar (There is content.  Scroll to bottom and click play.)


IntraHealth International, works in low-and middle-income countries to apply information science and technologies to support national healthcare systems. Currently, Intrahealth is applying machine learning techniques to the big data available to produce information that can support the program teams and the countries they serve. This seminar will provide an overview of the rise of global digital health to support achieving universal health coverage from the evolution of open source tools to advanced applications of machine learning for deeper analysis and answering more profound questions. The first sprint, building a data lake for our program in Uganda and performing hypothesis free and problem driven research and future directions made possible by this early work will be discussed.


David D. Potenziani, PhD, is currently Senior Informatics Advisor at IntraHealth International. He has worked in the US, Africa, and Asia with groups to develop and extend the application of digital health technologies and approaches. He swims in an array of ICT domains: mHealth, eLearning, eHealth policy, human resources for health, and machine learning. He came to IntraHealth after two decades at the University of North Carolina, serving in both the schools of Public Health and Medicine. He is a recovering historian and a writer of nerd science fiction.

Amy Finnegan, PhD, is currently Senior Data Scientist at IntraHealth International. She is a demographer and data scientist with 10 years of experience working in global health, development, and data science on four continents. Dr. Finnegan has collected and analyzed primary quantitative and qualitative data on pediatric HIV disclosure, positive parenting, and maternal and newborn survival innovations in East and West Africa. She has led and supported interdisciplinary research teams to design data collection tools and analysis plans and to apply machine learning and other creative research design methods to big, secondary data sets in global health in Uganda, Kenya, and Indonesia on topics such as family planning and maternal mortality. She co-leads Duke’s Big Data for Reproductive Health research team.


January 22
4:00 pm - 5:00 pm EST
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