Title
A tree-based decision model to support prediction of the severity of asthma exacerbations in children.
Abstract
This paper describes the development of a tree-based decision model to predict the severity of pediatric asthma exacerbations in the emergency department (ED) at 2 h following triage. The model was constructed from retrospective patient data abstracted from the ED charts. The original data was preprocessed to eliminate questionable patient records and to normalize values of age-dependent clinical attributes. The model uses attributes routinely collected in the ED and provides predictions even for incomplete observations. Its performance was verified on independent validating data (split-sample validation) where it demonstrated AUC (area under ROC curve) of 0.83, sensitivity of 84%, specificity of 71% and the Brier score of 0.18. The model is intended to supplement an asthma clinical practice guideline, however, it can be also used as a stand-alone decision tool.
Year
DOI
Venue
2010
10.1007/s10916-009-9268-7
J. Medical Systems
Keywords
Field
DocType
decision making,asthma,child,retrospective studi es,decision trees,col,decision models,retrospective study,decision tree
Brier score,Decision tree,Asthma,Emergency department,Intensive care medicine,Triage,Decision model,Retrospective cohort study,Guideline,Medicine
Journal
Volume
Issue
ISSN
34
4
0148-5598
Citations 
PageRank 
References 
8
0.60
7
Authors
5
Name
Order
Citations
PageRank
Ken Farion110612.61
Wojtek Michalowski226641.48
Szymon Wilk346140.94
Dympna O’Sullivan4152.53
Stan Matwin53025344.20