AI, Data Science and Global Health

AI, Data Science and Global Health

Emerging approaches for analyzing complex data sets have enormous potential for global health. In this panel, researchers who are working at the leading edge of artificial intelligence, geographic information systems and data analysis will explore how data can be harnessed to improve disease surveillance, diagnosis and allocation of health resources.

About the speakers:

Andy Tatem is Professor of spatial demography and epidemiology at the University of Southampton and is the Director of WorldPop and Flowminder, leading a group of more than 50 researchers and data scientists. He is interested in how populations, their characteristics and their dynamics can be mapped at high resolution across low and middle-income countries. His research has led to pioneering approaches to the use and integration of satellite, survey, cell phone and census data to map the distributions of vulnerable populations for disease, disaster and development applications. He runs international collaborations with national governments, UN agencies and data providers, and leads multiple research and operational projects funded by the Bill and Melinda Gates Foundation, Wellcome Trust, World Bank, Clinton Health Access Initiative and others.

Liz Turner joined the Duke Global Health Institute and the Department of Biostatistics and Bioinformatics in March 2012 to collaborate with, and provide biostatistical support to DGHI faculty and affiliates. With a PhD in statistics from McGill University, Canada, followed by four years working as a collaborative biostatistician in the Department of Medical Statistics, Faculty of Epidemiology and Population Health of the London School of Hygiene and Tropical Medicine (LSHTM), Liz has extensive experience working in both epidemiological studies and randomized trials across a range of substantive areas in developed world and resource poor settings.

Joao Vissoci is an assistant professor of surgery and global health at Duke University. He is psychologist with a PhD in Social Psychology from the Pontificia Universidade Catolica de Sao Paulo/Brazil. He is the co-Director of the Global Emergency Medicine Innovation and Implementation (GEMINI) lab, Division of Emergency Medicine, Department of Surgery, and a member of the Research Design and Analysis Core (RDAC) at the Duke Global Health Institute. His research interests include applying data science and technology to innovate in ways to address access to care and health systems gaps in global health and remote areas. His work includes the use of geospatial analysis and geostatistics, latent variable modeling, psychometrics and machine learning. Dr. Vissoci has worked in Brazil looking into population health, health systems and quality of care, and in Tanzania and Uganda with a focus on mental health, injury and alcohol.

Eric Laber is Professor of Statistical Science and Biostatistics and Bioinformatics at Duke University. Broadly, his research focuses on data-driven in sequential decision problems with applications in precision medicine, public health, defense, and retail planning.  A current focus is the development of safe decision-support systems for high-risk decision problems, e.g., adaptive systems for planning diet, exercise, and insulin adjustments for patients with type 1 diabetes.