AIMC Topic: Veterans
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Sleep disturbances and PTSD: identifying baseline predictors of insomnia response in an intensive treatment programme.
European journal of psychotraumatology
Jun 23, 2025
This study examined whether baseline demographic and clinical variables could predict clinically significant reductions in insomnia symptoms among veterans receiving a 2-week Cognitive Processing Therapy (CPT)-based intensive PTSD treatment programm...
Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.
Journal of psychopathology and clinical science
Mar 20, 2025
Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use an...
Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large veterans affairs population.
Computers in biology and medicine
Mar 5, 2025
OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic health records (EHRs) provides an alternative approach for extracting risk predictors...
Aged, 80 and over
Young Adult
Adult
Male
Middle Aged
Humans
Electronic Health Records
Female
Aged
Suicide, Completed
United States
Predictive Learning Models
Natural Language Processing
Psychological Well-Being
United States Department of Veterans Affairs
Risk Assessment
Veterans
Case-Control Studies
United States Department of Defense
Adolescent
Suicide Prevention
Assessment of PTSD in military personnel via machine learning based on physiological habituation in a virtual immersive environment.
Scientific reports
Mar 4, 2025
Posttraumatic stress disorder (PTSD) is a complex mental health condition triggered by exposure to traumatic events that leads to physical health problems and socioeconomic impairments. Although the complex symptomatology of PTSD makes diagnosis diff...
A deep learning analysis for dual healthcare system users and risk of opioid use disorder.
Scientific reports
Jan 29, 2025
The opioid crisis has disproportionately affected U.S. veterans, leading the Veterans Health Administration to implement opioid prescribing guidelines. Veterans who receive care from both VA and non-VA providers-known as dual-system users-have an inc...
Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.
Journal of psychiatric research
Dec 4, 2024
Previous models of depression outcomes have been limited by symptom heterogeneity within populations. This study conducted a retrospective analysis using latent growth mixture models to identify heterogeneous trajectories within a clinical population...
Veterans
Outpatients
Patient Health Questionnaire
Humans
Depression
Aged, 80 and over
United States
Machine Learning
Latent Class Analysis
Young Adult
Treatment Outcome
Adolescent
Retrospective Studies
Adult
Mental Health Services
Stress Disorders, Post-Traumatic
Male
Female
Area Under Curve
ROC Curve
Middle Aged
Reproducibility of Results
Outcome Assessment, Health Care
Aged
Medication Prescription Policy for US Veterans With Metastatic Castration-Resistant Prostate Cancer: Causal Machine Learning Approach.
JMIR medical informatics
Nov 19, 2024
BACKGROUND: Prostate cancer is the second leading cause of death among American men. If detected and treated at an early stage, prostate cancer is often curable. However, an advanced stage such as metastatic castration-resistant prostate cancer (mCRP...
Using Natural Language Processing to develop risk-tier specific suicide prediction models for Veterans Affairs patients.
Journal of psychiatric research
Sep 24, 2024
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 prevention advances, efforts primarily target high-risk patients with documented suic...
Using natural language processing to evaluate temporal patterns in suicide risk variation among high-risk Veterans.
Psychiatry research
Jul 27, 2024
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...
Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.
Critical care explorations
Jul 19, 2024
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...
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