Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large Veterans affairs population

Abstract: Objective: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic …

Development and validation of machine-learning algorithms predicting retention, overdoses, and all-cause mortality among U.S. military Veterans treated with buprenorphine for opioid use disorder

Abstract: Background: Buprenorphine for opioid use disorder (B-MOUD) is essential to improving patient outcomes; however, retention is essential. Objective: To develop and validate …

Models to predict injury, physical fitness failure and attrition in recruit training: a retrospective cohort study

Abstract: Background: Attrition rate in new army recruits is higher than in incumbent troops. In the current study, we identified the risk factors for attrition due to injuries …