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Título
Multiclassifier Systems for Predicting Neurological Outcome of Patients with Severe Trauma and Polytrauma in Intensive Care Units
Autor(es)
Palabras clave
Severe trauma
Multiclassifiers
Ensemble classifiers
Data mining
Mortality
Clasificación UNESCO
3205.07 Neurología
2404.01 Bioestadística
Fecha de publicación
2017
Editor
Springer Link
Citación
González-Robledo, J., Martín-González, F., Sánchez-Barba, M. et al.(2017) Multiclassifier Systems for Predicting Neurological Outcome of Patients with Severe Trauma and Polytrauma in Intensive Care Units . J Med Syst 41, 136 . https://doi.org/10.1007/s10916-017-0789-1
Resumen
[EN]This paper presents an ensemble based classification proposal for predicting neurological outcome of severely traumatized patients. The study comprises both the whole group of patients and a subgroup containing those patients suffering traumatic brain injury (TBI). Data was gathered from patients hospitalized in the Intensive Care Unit (ICU) of the University Hospital in Salamanca. Predictive models were induced from both epidemiologic and clinical variables taken at the emergency room and along the stay in the ICU. The large number of variables leads to a low accuracy in the classifiers even when feature selection methods are used. In addition, the presence of a much larger number of instances of one of the classes in the subgroup of TBI patients produces a significantly lesser precision for the minority class.
URI
ISSN
0148-5598
DOI
10.1007/s10916-017-0789-1
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