Article ID Journal Published Year Pages File Type
378167 Artificial Intelligence in Medicine 2006 15 Pages PDF
Abstract
The present study demonstrated that classification trees can be used to identify high-risk subgroups of mothers who are at risk of LBW outcomes. Although these exploratory tree analyses revealed a number of distinctive variable interactions for each geographical area, the variable selection was similar across all seven regions. This study also demonstrated that classification trees did not outperform logistic regression models or vice versa; both approaches provided useful analyses of the data.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
Authors
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