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Veterans

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Usability and Acceptability of Social Robot Pets Among Community-Dwelling Veterans Living With Dementia and Their Caregivers.

American journal of Alzheimer's disease and other dementias
Social robot pets promote engagement and psychosocial well-being among older adults, yet little is known about their use among community-dwelling Veterans living with dementia. This programmatic evaluation used a within subjects, pre-post design to e...

Identifying depression in the United States veterans using deep learning algorithms, NHANES 2005-2018.

BMC psychiatry
BACKGROUND: Depression is a common mental health problem among veterans, with high mortality. Despite the numerous conducted investigations, the prediction and identification of risk factors for depression are still severely limited. This study used ...

Incorporation of quantitative imaging data using artificial intelligence improves risk prediction in veterans with liver disease.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Utilization of electronic health records data to derive predictive indexes such as the electronic Child-Turcotte-Pugh (eCTP) Score can have significant utility in health care delivery. Within the records, CT scans contain phenoty...

Deep Learning of Electrocardiograms in Sinus Rhythm From US Veterans to Predict Atrial Fibrillation.

JAMA cardiology
IMPORTANCE: Early detection of atrial fibrillation (AF) may help prevent adverse cardiovascular events such as stroke. Deep learning applied to electrocardiograms (ECGs) has been successfully used for early identification of several cardiovascular di...

Sexual and Gender Minority Status and Suicide Mortality: An Explainable Artificial Intelligence Analysis.

International journal of public health
Suicide risk is elevated in lesbian, gay, bisexual, and transgender (LGBT) individuals. Limited data on LGBT status in healthcare systems hinder our understanding of this risk. This study used natural language processing to extract LGBT status and a...

A machine learning personalized treatment rule to optimize assignment to psychotherapies for grief among veterans.

Journal of affective disorders
BACKGROUND: Complex grief patterns are associated with significant suffering, functional impairments, health and mental health problems, and increased healthcare use. This burden may be even more pronounced among veterans. Behavioral Activation and T...

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

Psychiatry research
Measuring suicide risk fluctuation remains difficult, especially for high-suicide risk patients. Our study addressed this issue by leveraging Dynamic Topic Modeling, a natural language processing method that evaluates topic changes over time, to anal...

Natural Language Processing Algorithm to Extract Multiple Myeloma Stage From Oncology Notes in the Veterans Affairs Healthcare System.

JCO clinical cancer informatics
PURPOSE: Stage in multiple myeloma (MM) is an essential measure of disease risk, but its measurement in large databases is often lacking. We aimed to develop and validate a natural language processing (NLP) algorithm to extract oncologists' documenta...

Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.

Critical care explorations
BACKGROUND AND OBJECTIVE: To develop the COVid Veteran (COVet) score for clinical deterioration in Veterans hospitalized with COVID-19 and further validate this model in both Veteran and non-Veteran samples. No such score has been derived and validat...

Developing a nationwide registry of UK veterans seeking help from sector charities-a machine learning approach to stratification.

European journal of public health
The assistance to veterans in the UK is provided by the National Health Service and over 1800 military charities. These charities count services using different definitions and reporting systems, so to date a national registry of service usage does n...