Environmental Exposure & Health: Analyzing Estimates through Artificial Intelligence
This Praxis Lab uses Salt Lake City as an exemplar and case study in focusing on the intersections of environment, health, and advances in research methodology and data collection. As environmental exposure to unhealthy air quality and extreme temperatures is becoming increasingly important in researching health, the data available must also be investigated. We will look at better models of artificial intelligence and machine learning to address the data across space and time while paying close attention to vulnerable populations and the social determinants of health. During this class, we will review the impacts of environmental exposure, discuss how this is monitored and associated data issues, introduce AI methodologies, and use hands-on exercises to produce an improved understanding of individual exposures.
Instructors:
Daniel Mendoza
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