Machine learning-based dynamic mortality prediction after traumatic brain injury
نویسندگان
چکیده
منابع مشابه
Prediction of mental disorders after Mild Traumatic Brain Injury: principle component Approach
Introduction: In Processes Modeling, when there is relatively a high correlation between covariates, multicollinearity is created, and it leads to reduction in model's efficiency. In this study, by using principle component analysis, modification of the effect of multicolinearity in Artificial Neural Network (ANN) and Logistic Regression (LR) has been studied. Also, the effect of multicolineari...
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Background: The present study assesses independent predictors of clinically important traumatic brain injury (ciTBI) in order to design a prognostic rule for identification of high risk children with mild head injury. Materials and Methods: In a retrospective cross-sectional study, 3,199 children with mild traumatic brain injury (TBI) brought to emergency ward of three hospitals in Tehran, Iran...
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متن کاملPredictive modeling in pediatric traumatic brain injury using machine learning
BACKGROUND Pediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic challenge in the emergency department (ED). While large North American research networks have derived clinical prediction rules for the head injured child, these may not be generalizable to practices in countries with traditionally low rates of computed tomography (CT). We aim to study predictors f...
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ژورنال
عنوان ژورنال: Scientific Reports
سال: 2019
ISSN: 2045-2322
DOI: 10.1038/s41598-019-53889-6