Modeling of Metabolic Syndrome Using Bayesian Network

被引：0
|
作者：
Jin, Mi-Hyun [1 ]
Kim, Hyun-Ji [2 ]
Lee, Jea-Young [2 ]
机构：
[1] Sungkyunkwan Univ, Samsung Changwon Hosp, Seoul, South Korea
[2] Yeungnam Univ, Dept Stat, Kyungsan 712749, South Korea
来源：
KOREAN JOURNAL OF APPLIED STATISTICS | 2014年 / 27卷 / 05期
关键词：
Bayesian network; metabolic syndrome; posterior probability;
D O I：
10.5351/KJAS.2014.27.5.705
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Metabolic syndrome is a major factor for cardiovascular disease that can develop into a variety of complications such as stroke disease. This study utilizes a Bayesian network to model metabolic syndrome. In addition, we tried to find the best risk combinations to diagnose metabolic syndrome. We confirmed that the combinations are difference according to individual characteristics. The paper used data from 4,489 adults who responded to all health interview questions from the the 5th Korea National Health and Nutrition Examination Survey conducted in 2010.
引用
收藏
页码：705 / 715
页数：11
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