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Combining methodical procedures from knowledge discovery in databases and individual-oriented simulation - data mining in time series-

机译:在数据库中的知识发现中与各个导向模拟中的有条件过程 - 时间序列中的数据挖掘 -

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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.
机译:系统分析和数据探索是环境流行病学研究过程中的重要任务。我们在数据库中检查知识发现,结合各个导向的建模和仿真,以支持对环境系统内的原因和效应关系的假设检测。以个人为导向的模型和检测到的假设可以揭示对学习人群的当前健康状况的可能解释。这种模型可以支持医疗管理的未来规划和决策。试图在流行病学研究中使用这些方法的主要目标是减少研究成本和时间的支出,以及改善可用数据的分析和解释。

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