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

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

10.1186/s12874-015-0015-0

Saved in:

Bibliographic Details
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
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore

Description
Summary:	10.1186/s12874-015-0015-0