AIMC Topic: Suicide Prevention
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Crisis-line workers' perspectives on AI in suicide prevention: a qualitative exploration of risk and opportunity.
BMC public health
Jul 2, 2025
BACKGROUND: Crisis support services offer crucial intervention for individuals in acute distress, providing timely access to trained volunteers whose human connection is key to the effectiveness of these services. However, there are significant dispa...
Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data.
JMIR research protocols
Jun 25, 2025
BACKGROUND: Suicide in local jails occurs at a higher rate than in the general population, requiring improvements to risk screening methods. Current suicide risk screening practices in jails are insufficient: They are commonly not conducted using val...
Evaluating the ability of artificial intelligence to predict suicide: A systematic review of reviews.
Journal of affective disorders
Apr 22, 2025
INTRODUCTION: Suicide remains a critical global public health issue, with approximately 800,000 deaths annually. Despite various prevention efforts, suicide rates are rising, highlighting the need for more effective strategies. Traditional suicide ri...
Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach.
Journal of medical Internet research
Apr 14, 2025
BACKGROUND: Crisis hotlines serve as a crucial avenue for the early identification of suicide risk, which is of paramount importance for suicide prevention and intervention. However, assessing the risk of callers in the crisis hotline context is cons...
Protocol for socioecological study of autism, suicide risk, and mental health care: Integrating machine learning and community consultation for suicide prevention.
PloS one
Mar 19, 2025
INTRODUCTION: Autistic people experience higher risk of suicidal ideation (SI) and suicide attempts (SA) compared to non-autistic people, yet there is limited understanding of complex, multilevel factors that drive this disparity. Further, determinan...
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...
Natural Language Processing
United States Department of Veterans Affairs
Veterans
United States Department of Defense
Suicide, Completed
Predictive Learning Models
Psychological Well-Being
Case-Control Studies
Adolescent
Suicide Prevention
United States
Male
Middle Aged
Risk Assessment
Humans
Electronic Health Records
Aged
Female
Aged, 80 and over
Young Adult
Adult
Validation of a machine learning model for indirect screening of suicidal ideation in the general population.
Scientific reports
Feb 24, 2025
Suicide is among the leading causes of death worldwide and a concerning public health problem, accounting for over 700,000 registered deaths worldwide. However, suicide deaths are preventable with timely and evidence-based interventions, which are of...
Applications of Large Language Models in the Field of Suicide Prevention: Scoping Review.
Journal of medical Internet research
Jan 23, 2025
BACKGROUND: Prevention of suicide is a global health priority. Approximately 800,000 individuals die by suicide yearly, and for every suicide death, there are another 20 estimated suicide attempts. Large language models (LLMs) hold the potential to e...
Evaluating of BERT-based and Large Language Mod for Suicide Detection, Prevention, and Risk Assessment: A Systematic Review.
Journal of medical systems
Dec 30, 2024
Suicide constitutes a public health issue of major concern. Ongoing progress in the field of artificial intelligence, particularly in the domain of large language models, has played a significant role in the detection, risk assessment, and prevention...
Real-time assistance in suicide prevention helplines using a deep learning-based recommender system: A randomized controlled trial.
International journal of medical informatics
Dec 17, 2024
OBJECTIVE: To evaluate the effectiveness and usability of an AI-assisted tool in providing real-time assistance to counselors during suicide prevention helpline conversations.
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