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 …

Computing 3-step theory of suicide factor scores from Veterans Health Administration clinical progress notes

Abstract: Background: Literature on how to translate information extracted from clinical progress notes into numeric scores for 3-step theory of suicide (3ST) factors is …

Using natural language processing to develop risk-tier specific suicide prediction models for Veterans Affairs patients

Abstract: Suicide is a leading cause of death. Suicide rates are particularly elevated among Department of Veterans Affairs (VA) patients. While VA has made impactful suicide …

Detecting suicide risk among U.S. Service members and Veterans: A deep learning approach using social media data

Abstract: Background: Military Servicemembers and Veterans are at elevated risk for suicide, but rarely self-identify to their leaders or clinicians regarding their experience of …

Using natural language processing to evaluate temporal patterns in suicide risk variation among high-risk Veterans

Abstract: Measuring suicide risk fluctuation remains difficult, especially for high-suicide risk patients. Our study addressed this issue by leveraging Dynamic Topic Modeling, a …

Age modulates the predictive value of self-reported sleepiness for all-cause mortality risk: Insights from a comprehensive national database of Veterans

Abstract: Study Objectives: Excessive daytime sleepiness (EDS) is prevalent and overwhelmingly stems from disturbed sleep. We hypothesized that age modulates the association …

Artificial intelligence approaches for phenotyping heart failure in U.S. Veterans Health Administration electronic health record

Abstract: Aims: Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF …

Development and optimization of the Veterans Affairs' national heart failure dashboard for population health management

Abstract: BACKGROUND: In 2020, the Veterans Affairs (VA) health care system deployed a heart failure (HF) dashboard for use nationally. The initial version was notably imprecise …

Identifying clinical phenotypes of frontotemporal dementia in post-9/11 era Veterans using natural language processing

Abstract: INTRODUCTION: Frontotemporal dementia (FTD) encompasses a clinically and pathologically diverse group of neurodegenerative disorders, yet little work has quantified the …

Temporary financial assistance reduced the probability of unstable housing among Veterans for more than 1 year

Abstract: The Department of Veterans Affairs (VA) aims to reduce homelessness among veterans through programs such as Supportive Services for Veteran Families (SSVF). An important …

Using natural language processing to study homelessness longitudinally with electronic health record data subject to irregular observations

Abstract: The Electronic Health Record (EHR) contains information about social determinants of health (SDoH) such as homelessness. Much of this information is contained in clinical …

The association of Agent Orange exposure with the progression of monoclonal gammopathy of undetermined significance to multiple myeloma: A population-based study of Vietnam War Era Veterans

Abstract: Herbicide and pesticide exposure [e.g., agent orange (AO)] is associated with an increased risk of multiple myeloma (MM) due to the contaminant, …