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Discover high-risk factor combinations using Bayesian network from cohort data of National Stoke Screening in China

机译:使用贝叶斯网络从中国国家卒中筛查队列数据中发现高风险因素组合

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摘要

BackgroundIn recent years, the increasing incidence and prevalence of stroke has brought a heavy economic burden on families and society in China. The Ministry of Health of the Peoples’ Republic of China initiated the national stroke screening and intervention program in 2011 for stroke prevention and control. In the screening, only those who have been classified to “potential high-risk” group in preliminary screening need further examination and physician confirmation to determine the risk level of stroke in rescreening. However, at the beginning of the program, the “potential high-risk” classification method in the preliminary screening are determined by experts based on their experience. The primary aim of this study is to study the causality of stroke and risk factors in middle-aged population using the cohort data, and to explore whether the stroke screening and intervention program should include more precise “potential high-risk” evaluation criteria for this age group in preliminary screening.
机译:背景技术近年来,中风的发病率和患病率的上升给中国家庭和社会带来了沉重的经济负担。中华人民共和国卫生部于2011年启动了国家中风筛查和干预计划,以预防和控制中风。在筛查中,只有那些在初步筛查中被归类为“潜在高危”人群的患者才需要进一步检查和医师确认,以确定重新筛查中风的风险水平。但是,在程序开始时,初步筛选中的“潜在高风险”分类方法是由专家根据经验确定的。这项研究的主要目的是利用队列数据研究中年人群中风和危险因素的因果关系,并探讨中风筛查和干预计划是否应为此包括更精确的“潜在高风险”评估标准。初步筛查的年龄组。

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