On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry.

ABSTRACT:

Background

Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient's condition and deciding on transport destination. Data-driven On Scene Injury Severity Prediction (OSISP) models for motor vehicle crashes have shown potential for providing real-time decision support. The objective of this study is therefore to evaluate if an Artificial Intelligence (AI) based clinical decision support system can identify severely injured trauma patients in the prehospital setting.

Methods

The Swedish Trauma Registry was used to train and validate five models - Logistic Regression, Random Forest, XGBoost, Support Vector Machine and Artificial Neural Network - in a stratified 10-fold cros

SUBMITTER: Bakidou A 

PROVIDER: S-EPMC10561449 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature