Valuing Diverse Stakeholder Collaborations

New data in public health

Novel data sources offer opportunity for high-granularity public health. In this work we have studied many types of data and their relevance in time and space.
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Smart Community-level Targeting by Combining Artificial Intelligence and Mobile Tools

This work uses machine learning to examine how to improve the reach of public health interventions to marginalized populations.
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NSF CAREER: Learning from When, Where and by Whom Data is Generated for Advancing Public Health Studies (2019-2024)

This award is focused on developing new machine learning and data science approaches motivated by the need to improve data management and analysis in the public health domain. The project will also provide educational programs informed by best practices in research for public health practitioners, students, and community members in the context of data science and public health.
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Social Determinants and Risk Prediction

Social determinants play an important role in shaping noncommunicable disease. We are examining the role of social determinants in clinical risk prediction as well as  appropriate modeling strategies for their integration.
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NYU-Moi Data Science for Social Determinants Training Program

Elevating both capacity in data science and concepts captured in data, this training program will develop future leaders in data science who are equipped to develop and analyze data to better leverage rich survey and digital data sources to capture information on the social determinants of health.
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