Using Bayesian Networks to Identify Causal Relationships to the Incidence of Chronic Disease | Center for Computational Epidemiologyand Response Analysis (CeCERA)
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Using Bayesian Networks to Identify Causal Relationships to the Incidence of Chronic Disease

Due to the nature of epidemiology, data collected and studied are primarily observational rather than experimental. New methods for identifying causal relationships within large datasets must be developed to understand the prevalence of chronic diseases in populations. This understanding will lead to the creation of improved methods to control and mitigate the risk of chronic diseases. The goal of this research is to develop heuristics using Bayesian networks to identify causal relationships in epidemiological data.