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A Machine Learning Approach to Predicting Need for Hospitalization for Pediatric Asthma Exacerbation at the Time of Emergency Department Triage.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine 30382605
OBJECTIVES: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospitalization. Earlier identification of need for hospital-level care could triage patients more efficiently to high- or low-resource ED tracks. Existing t...
Adolescent Child Child, Preschool Emergency Service, Hospital Female Hospitalization Humans Logistic Models Machine Learning Male Retrospective Studies Risk Assessment ROC Curve Status Asthmaticus Triage
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Developing a short-term prediction model for asthma exacerbations from Swedish primary care patients' data using machine learning - Based on the ARCTIC study.

Respiratory medicine 34077873
OBJECTIVE: The ability to predict impending asthma exacerbations may allow better utilization of healthcare resources, prevention of hospitalization and improve patient outcomes. We aimed to develop models using machine learning to predict risk of ex...
Adolescent Adult Cohort Studies Comorbidity Data Interpretation, Statistical Disease Progression Environmental Exposure Female Forecasting Hospitalization Humans Machine Learning Male Middle Aged Models, Theoretical Risk Risk Assessment Status Asthmaticus Sweden Young Adult
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