Derivation and validation of different machine-learning models in mortality prediction of trauma in motorcycle riders: a cross-sectional retrospective study in southern Taiwan.

ABSTRACT:

Objectives

This study aimed to build and test the models of machine learning (ML) to predict the mortality of hospitalised motorcycle riders.

Setting

The study was conducted in a level-1 trauma centre in southern Taiwan.

Participants

Motorcycle riders who were hospitalised between January 2009 and December 2015 were classified into a training set (n=6306) and test set (n=946). Using the demographic information, injury characteristics and laboratory data of patients, logistic regression (LR), support vector machine (SVM) and decision tree (DT) analyses were performed to determine the mortality of individual motorcycle riders, under different conditions, using all samples or reduced samples, as well as all variables or selected features in the algorithm.

Primary and

SUBMITTER: Kuo PJ 

PROVIDER: S-EPMC5781097 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature