Development of a regional-based predictive model of incidence of traumatic spinal cord injury using machine learning algorithms.

ABSTRACT:

Objective

To develop a predictive model of incidence of traumatic spinal cord injury (TSCI).

Methods

The data for training the model included both the incidence data and the covariates. The incidence data were extracted from systematic reviews and the covariates were extracted from data available in the international road federation database. Then the feature processing measures were taken. First we defined a hyper-parameter, missing-value threshold, in order to eliminate features that exceed this threshold. To tackle the problem of overfitting of model we determined the Pearson correlation of features and excluded those with more than 0.7 correlation. After feature selection three different models including simple linear regression, support vector regression, and multi-laye

SUBMITTER: Jazayeri SB 

PROVIDER: S-EPMC10943041 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature