Discovering meaningful information from large amounts of environment and health data to reduce uncertainties in formulating environmental policies

被引:4
|
作者
Lee, I-Nong
Chang, Wen-Chung
Hong, Yu-Jue
Liao, Shang-Chih [1 ]
机构
[1] Chang Gung Mem Hosp, Kaohsiung, Taiwan
[2] Kaohsiung Med Univ, Fac Med Informat Management, Kaohsiung 807, Taiwan
[3] Environm Protect Bur, Cent Reg Recovery Plant, Kaohsiung, Taiwan
[4] Kaohsiung Med Univ, Sch Publ Hlth, Kaohsiung, Taiwan
关键词
knowledge discovery; environmental policy; water hardness; health records; uncertainty;
D O I
10.1016/j.jenvman.2005.11.018
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study uses knowledge discovery concepts to analyze large amounts of data step by step for the purpose of assisting in the formulation of environmental policy. We performed data cleansing and extracting from existing nation-wide databases, and used regression and classification techniques to analyze the data. The current water hardness in Kaohsiung, Taiwan contributes to the prevention of cardiovascular disease (CVD) but exacerbates the development of renal stones (RS). However, to focus on water hardness alone to control RS would not be cost effective at all, because the existing database parameters do not adequately allow for a clear understanding of RS. Analysis of huge amounts of data can most often turn up the most reliable and convincing results and the use of existing databases can be cost-effective. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:434 / 440
页数:7
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