  Epidemiology characterizes the influence of causes to disease and health
conditions of defined populations. Cohort studies are population-based studies
involving usually large numbers of randomly selected individuals and comprising
numerous attributes, ranging from self-reported interview data to results from
various medical examinations, e.g., blood and urine samples. Since recently,
medical imaging has been used as an additional instrument to assess risk
factors and potential prognostic information. In this chapter, we discuss such
studies and how the evaluation may benefit from visual analytics. Cluster
analysis to define groups, reliable image analysis of organs in medical imaging
data and shape space exploration to characterize anatomical shapes are among
the visual analytics tools that may enable epidemiologists to fully exploit the
potential of their huge and complex data. To gain acceptance, visual analytics
tools need to complement more classical epidemiologic tools, primarily
hypothesis-driven statistical analysis.
