Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling

10.1186/s12874-015-0015-0

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Main Authors:	Chong, S.-L, Liu, N, Barbier, S, Ong, M.E.H
Other Authors:	DUKE-NUS MEDICAL SCHOOL
Format:	Article
Published:	BioMed Central Ltd. 2020
Subjects:	algorithm Brain Injuries case control study child complication factual database female health survey human injury scale machine learning male multivariate analysis preschool child receiver operating characteristic retrospective study skull fracture statistical model statistics and numerical data theoretical model traffic accident unconsciousness vomiting x-ray computed tomography Accidents, Traffic Algorithms Case-Control Studies Child Child, Preschool Databases, Factual Female Humans Injury Severity Score Logistic Models Machine Learning Male Models, Theoretical Multivariate Analysis Population Surveillance Retrospective Studies ROC Curve Skull Fractures Tomography, X-Ray Computed Unconsciousness Vomiting
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/174294
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Institution:	National University of Singapore

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spelling	sg-nus-scholar.10635-1742942023-07-28T08:48:54Z Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling Chong, S.-L Liu, N Barbier, S Ong, M.E.H DUKE-NUS MEDICAL SCHOOL algorithm Brain Injuries case control study child complication factual database female health survey human injury scale machine learning male multivariate analysis preschool child receiver operating characteristic retrospective study skull fracture statistical model statistics and numerical data theoretical model traffic accident unconsciousness vomiting x-ray computed tomography Accidents, Traffic Algorithms Brain Injuries Case-Control Studies Child Child, Preschool Databases, Factual Female Humans Injury Severity Score Logistic Models Machine Learning Male Models, Theoretical Multivariate Analysis Population Surveillance Retrospective Studies ROC Curve Skull Fractures Tomography, X-Ray Computed Unconsciousness Vomiting 10.1186/s12874-015-0015-0 BMC Medical Research Methodology 15 1 22 2020-09-04T02:11:49Z 2020-09-04T02:11:49Z 2015 Article Chong, S.-L, Liu, N, Barbier, S, Ong, M.E.H (2015). Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling. BMC Medical Research Methodology 15 (1) : 22. ScholarBank@NUS Repository. https://doi.org/10.1186/s12874-015-0015-0 14712288 https://scholarbank.nus.edu.sg/handle/10635/174294 BioMed Central Ltd. Unpaywall 20200831
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	algorithm Brain Injuries case control study child complication factual database female health survey human injury scale machine learning male multivariate analysis preschool child receiver operating characteristic retrospective study skull fracture statistical model statistics and numerical data theoretical model traffic accident unconsciousness vomiting x-ray computed tomography Accidents, Traffic Algorithms Brain Injuries Case-Control Studies Child Child, Preschool Databases, Factual Female Humans Injury Severity Score Logistic Models Machine Learning Male Models, Theoretical Multivariate Analysis Population Surveillance Retrospective Studies ROC Curve Skull Fractures Tomography, X-Ray Computed Unconsciousness Vomiting
spellingShingle	algorithm Brain Injuries case control study child complication factual database female health survey human injury scale machine learning male multivariate analysis preschool child receiver operating characteristic retrospective study skull fracture statistical model statistics and numerical data theoretical model traffic accident unconsciousness vomiting x-ray computed tomography Accidents, Traffic Algorithms Brain Injuries Case-Control Studies Child Child, Preschool Databases, Factual Female Humans Injury Severity Score Logistic Models Machine Learning Male Models, Theoretical Multivariate Analysis Population Surveillance Retrospective Studies ROC Curve Skull Fractures Tomography, X-Ray Computed Unconsciousness Vomiting Chong, S.-L Liu, N Barbier, S Ong, M.E.H Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling
description	10.1186/s12874-015-0015-0
author2	DUKE-NUS MEDICAL SCHOOL
author_facet	DUKE-NUS MEDICAL SCHOOL Chong, S.-L Liu, N Barbier, S Ong, M.E.H
format	Article
author	Chong, S.-L Liu, N Barbier, S Ong, M.E.H
author_sort	Chong, S.-L
title	Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling
title_short	Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling
title_full	Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling
title_fullStr	Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling
title_full_unstemmed	Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling
title_sort	predictive modeling in pediatric traumatic brain injury using machine learning data analysis, statistics and modelling
publisher	BioMed Central Ltd.
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/174294
_version_	1772824573118513152

Predictive modeling in pediatric traumatic brain injury using machine learning Data analysis, statistics and modelling

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