全部 标题 作者
关键词 摘要


影响不同种族患高血压的因素分析
Analysis of Factors Influencing Hypertension in Different Ethnic Groups

DOI: 10.12677/HJDM.2016.63013, PP. 106-115

Keywords: 高血压,Logit分类,随机森林分类
Hypertension
, Logit Classification, Random Forest Classification

Full-Text   Cite this paper   Add to My Lib

Abstract:

由于现在人们得高血压的几率越来越大,而高血压所引起的并发症十分危险,高血压各种并发症病逐渐成为了现代健康杀手之一。本文选用UCI数据库中的美国健康普查数据进行分析处理。本文通过对不同种族的人的各因素用logit分类以及随机森林分类进行分析,得到了以下结论:不论种族,年龄对高血压都有显著影响;对于不同种族,其他的因素对高血压的影响程度不同。
Recently, it is more likely to have high blood pressure, and complications related to high blood pressure are dangerous. Complications of hypertension have gradually become one of the killers of modern health. In this paper, we use the United States health survey data in UCI database for analysis and processing. We dealt with each factor of people from different races using Logit Clas-sification and the Random Forest Classification, and obtained the following conclusions: Regardless of race, age had significant effects on high blood pressure; For different ethnic groups, influence of other factors on hypertension is different.

References

[1]  WHO (2002) Reducing Risks Promoting Healthy Life. World Health Organization, Geneva, 1.
[2]  孙振球. 医学统计学[M]. 北京: 人民卫生出版社, 2007: 333-341.
[3]  李英华. 高血压的现状与流行[J]. 中华心血管病杂志, 2004(7): 456.
[4]  Tian, J.Y., Cheng, Q., Song, X.M., et al. (2006) Birthweight and Risk of Type-2diabetes, Abdominal Obesity and Hypertension among Chinese Adults. European Journal of Endocrinology, 155, 601-607.
http://dx.doi.org/10.1530/eje.1.02265
[5]  Ning, G., Su, J., Li, Y., et al. (2006) Artificial Neural Network Based Model for Cardiovascular Risk Stratification in Hypertension. Medical and Biological Engineering and Computing, 44, 202-208.
http://dx.doi.org/10.1007/s11517-006-0028-2
[6]  Ture, M., Kurt, I., Yavuz, E. and Kurum, T. (2005) Comparison of Multiple Prediction Models for Hypertension (Neural Networks, Logistic Regression and Flexible Discriminant Analyses). Anadolu Kardiyoloji Dergisi, 5, 24-28.
[7]  傅传喜, 马文军, 梁建华. 高血压危险因素logistic回归与分类树分析[J]. 中华疾病控制杂志, 2006, 10(3): 652-952.
[8]  杨洋. 利用人工神经网络模型预测原发性高血压的研究[D]: [硕士学位论文]. 北京: 中国医科大学, 2010.
[9]  吴喜之. 复杂数据统计方法: 基于R的应用(第2版) [M]. 北京: 中国人民大学出版社, 2013: 63-65.

Full-Text

comments powered by Disqus