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Suicide

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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...

The Design of Psychological Education Intervention System in Universities Based on Deep Learning.

Computational intelligence and neuroscience
With the rapid development of Chinese society and economy as well as the deepening of the reform of the higher education management system and the change of employment mode of graduates, college students face various challenges of frustration and pre...

User Feedback on the Use of a Natural Language Processing Application to Screen for Suicide Risk in the Emergency Department.

The journal of behavioral health services & research
Suicide is the 10th leading cause of death in the USA and globally. Despite decades of research, the ability to predict who will die by suicide is still no better than 50%. Traditional screening instruments have helped identify risk factors for suici...

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...

Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

Journal of medical Internet research
BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people's expressions on social...

Artificial intelligence-based approaches for suicide prediction: Hope or hype?

Asian journal of psychiatry
Accurate prediction of suicide risk is important because it allows evidence-based interventions to be targeted to at-risk populations. Conventional approaches to prediction of suicide risk have shown suboptimal accuracy. In this context, artificial i...

Exploring the Potential of Artificial Intelligence in Adolescent Suicide Prevention: Current Applications, Challenges, and Future Directions.

Psychiatry
ObjectiveThe global surge in adolescent suicide necessitates the development of innovative and efficacious preventive measures. Traditionally, various approaches have been used, but with limited success. However, with the rapid advancements in artifi...

Predicting suicide risk in real-time crisis hotline chats integrating machine learning with psychological factors: Exploring the black box.

Suicide & life-threatening behavior
BACKGROUND: This study addresses the suicide risk predicting challenge by exploring the predictive ability of machine learning (ML) models integrated with theory-driven psychological risk factors in real-time crisis hotline chats. More importantly, w...

Analysis and evaluation of explainable artificial intelligence on suicide risk assessment.

Scientific reports
This study explores the effectiveness of Explainable Artificial Intelligence (XAI) for predicting suicide risk from medical tabular data. Given the common challenge of limited datasets in health-related Machine Learning (ML) applications, we use data...

Artificial Intelligence and the National Violent Death Reporting System: A Rapid Review.

Computers, informatics, nursing : CIN
As the awareness on violent deaths from guns, drugs, and suicides emerges as a public health crisis in the United States, attempts to prevent injury and mortality through nursing research are critical. The National Violent Death Reporting System prov...