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	Risk assessment of human neural tube defects using a Bayesian belief network
	Liao Y. L. ; Wang J. F. ; Guo Y. Q. ; Zheng X. Y.
	2010
关键词	Neural tube birth defects Bayesian belief network Data discretization Case-effect relationship birth-defects challenges exposure
英文摘要	Neural tube defects (NTDs) constitute the most common type of birth defects. How much risk of NTDs could an area take? The answer to this question will help people understand the geographical distribution of NTDs and explore its environmental causes. Most existing methods usually take the spatial correlation of cases into account and rarely consider the effect of environmental factors. However, especially in rural areas, the NTDs cases have a little effect on each other across space, whereas the role of environmental factors is significant. To demonstrate these points, Heshun, a county with the highest rate of NTDs in China, was selected as the region of interest in the study. Bayesian belief network was used to quantify the probability of NTDs occurred at villages with no births. The study indicated that the proposed method was easy to apply and high accuracy was achieved at a 95% confidence level.
出处	Stochastic Environmental Research and Risk Assessment
卷	24
期	1
页	93-100
收录类别	SCI
语种	英语
ISSN号	1436-3240
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/23533]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Liao Y. L.,Wang J. F.,Guo Y. Q.,et al. Risk assessment of human neural tube defects using a Bayesian belief network. 2010.

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