AIMC Topic: Suicide

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Predicting Suicides Among US Army Soldiers After Leaving Active Service.

JAMA psychiatry
IMPORTANCE: The suicide rate of military servicemembers increases sharply after returning to civilian life. Identifying high-risk servicemembers before they leave service could help target preventive interventions.

Data Quality Matters: Suicide Intention Detection on Social Media Posts Using RoBERTa-CNN.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Suicide remains a pressing global health concern, necessitating innovative approaches for early detection and intervention. This paper focuses on identifying suicidal intentions in posts from the SuicideWatch subreddit by proposing a novel deep-learn...

Interpretable Estimation of Suicide Risk and Severity from Complete Blood Count Parameters with Explainable Artificial Intelligence Methods.

Psychiatria Danubina
BACKGROUND: The peripheral inflammatory markers are important in the pathophysiology of suicidal behavior. However, methods for practical uses haven't been developed enough yet. This study developed predictive models based on explainable artificial i...

Pilot Mental Health, Methodologies, and Findings: A Systematic Review.

Aerospace medicine and human performance
Pilots' mental health has received increased attention following Germanwings Flight 9525 in 2015, where the copilot intentionally crashed the aircraft into the French Alps, killing all on board. An investigation of this incident found that the pilot...

Resampling to address inequities in predictive modeling of suicide deaths.

BMJ health & care informatics
OBJECTIVE: Improve methodology for equitable suicide death prediction when using sensitive predictors, such as race/ethnicity, for machine learning and statistical methods.

Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

JAMA psychiatry
IMPORTANCE: Suicide is a public health problem, with multiple causes that are poorly understood. The increased focus on combining health care data with machine-learning approaches in psychiatry may help advance the understanding of suicide risk.

What health records data are required for accurate prediction of suicidal behavior?

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.

Identifying Suicidal Adolescents from Mental Health Records Using Natural Language Processing.

Studies in health technology and informatics
Suicidal ideation is a risk factor for self-harm, completed suicide and can be indicative of mental health issues. Adolescents are a particularly vulnerable group, but few studies have examined suicidal behaviour prevalence in large cohorts. Electron...