ArticleJournal of medical systems2010
A tree-based decision model to support prediction of the severity of asthma exacerbations in children.
Article in Journal of medical systems, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Leveraging artificial intelligence for the management of preschool wheeze: A narrative review.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2025Review
- Risk factors for pressure ulcer recurrence following surgical reconstruction: A cross-sectional retrospective analysis.Frontiers in surgery · 2023Article
- Concurrent Types of Intracranial Hemorrhage are Associated with a Higher Mortality Rate in Adult Patients with Traumatic Subarachnoid Hemorrhage: A Cross-Sectional Retrospective Study.International journal of environmental research and public health · 2019Article
- An ensemble learning method for asthma control level detection with leveraging medical knowledge-based classifier and supervised learning.Journal of medical systems · 2019Article
- Accurate and rapid screening model for potential diabetes mellitus.BMC medical informatics and decision making · 2019Article
- Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage.JAMA network open · 2019Article
- Applications of Machine Learning Approaches in Emergency Medicine; a Review Article.Archives of academic emergency medicine · 2019Review
- Identification of Pancreatic Injury in Patients with Elevated Amylase or Lipase Level Using a Decision Tree Classifier: A Cross-Sectional Retrospective Analysis in a Level I Trauma Center.International journal of environmental research and public health · 2018Article
- Article
- Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System.International journal of environmental research and public health · 2017Article
- A Statistical Classifier to Support Diagnose Meningitis in Less Developed Areas of Brazil.Journal of medical systems · 2017Article
- Comparing predictions made by a prediction model, clinical score, and physicians: pediatric asthma exacerbations in the emergency department.Applied clinical informatics · 2013Article
- Implementing an integrative multi-agent clinical decision support system with open source software.Journal of medical systems · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
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.
Indexed as
Identifiers
20703909What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.