A Modeling Approach to Identify Factors Associated with Infant Mortality in Russia

被引:0
|
作者
Soshnikov, Sergey [1 ]
Lee, Carl [2 ]
Vladimirov, Sergey [3 ]
机构
[1] CPHRI, Dept Med & Social Problems, 11 Str Dobrolyubova, Moscow 127254, Russia
[2] Cent Michigan Univ, Dept Math, Mt Pleasant, MI USA
[3] SQLab, Independent Lab, Moscow, Russia
关键词
Data Quality; Decision Tree; Ensemble; Gradient Boosting; LARS; LASSO; Neural Network; Partial Least Squares; REGRESSION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The infant mortality has been declining in the recent decades globally. However, it continues to be an international concern. The issues are not only on what types of diseases or incidents leading to the infant death for individual cases, but also on what factors; social, economic, environment, education and other; are associated with infant mortality in the society. In this study, we collect infant mortality data along with over 100 variables using region as the sampling unit in Russia to investigate potential factors that may have significant association with infant mortality in Russia. Our purpose has two folds. First is to address the issues of data quality and the selection of modeling methodology for observational studies in general. Second is to identify possible important factors associated with infant mortality in Russia. We conclude with a discussion of pitfalls and cautions when applying predictive modeling techniques in observational studies.
引用
收藏
页码:185 / 190
页数:6
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