Development and Validation of a Machine Learning Prediction Model of Posttraumatic Stress Disorder After Military Deployment.

ABSTRACT:

Importance

Military deployment involves significant risk for life-threatening experiences that can lead to posttraumatic stress disorder (PTSD). Accurate predeployment prediction of PTSD risk may facilitate the development of targeted intervention strategies to enhance resilience.

Objective

To develop and validate a machine learning (ML) model to predict postdeployment PTSD.

Design, setting, and participants

This diagnostic/prognostic study included 4771 soldiers from 3 US Army brigade combat teams who completed assessments between January 9, 2012, and May 1, 2014. Predeployment assessments occurred 1 to 2 months before deployment to Afghanistan, and follow-up assessments occurred approximately 3 and 9 months post deployment. Machine learning models to predict postdep

SUBMITTER: Papini S 

PROVIDER: S-EPMC10314304 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature