Early prediction of Alzheimer's disease using longitudinal electronic health records of US military Veterans

Abstract: BACKGROUND: Early prediction of Alzheimer's disease is important for timely intervention and treatment. We examine whether machine learning on longitudinal electronic …

Using the death/suicide implicit association task to prospectively predict near-term suicidal behavior in high-risk Veterans

Abstract: The 90-day period after a suicide attempt or hospitalization for suicidal behavior is a period of increased risk for psychiatric patients. However, predicting who among …

Galectin-3 is associated with risk of cardiovascular and kidney outcomes in ambulatory Veterans

Abstract: Rationale & Objective: Cardiovascular and kidney disease are highly prevalent comorbid conditions, and each is a risk factor for the other condition. We evaluated whether …

Predicting depressive symptoms through social support: A machine learning approach in military populations

Abstract: Background: Perceived Social support has been consistently shown to reduce depressive symptoms among military personnel. However, limited research has explored how …

Suicide among Veterans in Veterans Health Administration care: Differences in methods by tier of predicted suicide risk

Abstract: Veterans' suicide rates exceed those of non-Veteran adults, and Veteran suicides more often involve firearms. However, the relationship between Veteran characteristics …

Forecasting military mental health in a complete sample of Danish military personnel deployed between 1992-2013

Abstract: Objective: Mental health problems (MHP) are a relatively common consequence of deployment to war zones. Early identification of those at risk of post-deployment MHP …