Combining Methodical Procedures from Knowledge Discovery in Databases and Individual-Oriented Simulation -- Data Mining in Time Series

Systems analysis and the exploration of data are important tasks during the course of environmental epidemiological studies. We examine knowledge discovery in databases combined with individual-oriented modeling and simulation to support the detection of hypotheses about cause-and-effect relationships within environmental systems. An individual-oriented model and detected hypotheses can uncover possible explanations for the current state of health of a study population. Such a model can support future planning and decision making for healthcare management. The main goal of attempting to use these methods in epidemiological research is to reduce expenditures in costs and time for a study as well as to improve the analysis and interpretation of available data.

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