AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Suicide

Showing 51 to 60 of 85 articles

Clear Filters

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.

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...

Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm.

Biometrical journal. Biometrische Zeitschrift
Clinical visit data are clustered within people, which complicates prediction modeling. Cluster size is often informative because people receiving more care are less healthy and at higher risk of poor outcomes. We used data from seven health systems ...

Detecting suicidal risk using MMPI-2 based on machine learning algorithm.

Scientific reports
Minnesota Multiphasic Personality Inventory-2 (MMPI-2) is a widely used tool for early detection of psychological maladjustment and assessing the level of adaptation for a large group in clinical settings, schools, and corporations. This study aims t...

A machine learning approach for predicting suicidal thoughts and behaviours among college students.

Scientific reports
Suicidal thoughts and behaviours are prevalent among college students. Yet little is known about screening tools to identify students at higher risk. We aimed to develop a risk algorithm to identify the main predictors of suicidal thoughts and behavi...

Predicting suicidal thoughts and behavior among adolescents using the risk and protective factor framework: A large-scale machine learning approach.

PloS one
INTRODUCTION: Addressing the problem of suicidal thoughts and behavior (STB) in adolescents requires understanding the associated risk factors. While previous research has identified individual risk and protective factors associated with many adolesc...

A direct comparison of theory-driven and machine learning prediction of suicide: A meta-analysis.

PloS one
Theoretically-driven models of suicide have long guided suicidology; however, an approach employing machine learning models has recently emerged in the field. Some have suggested that machine learning models yield improved prediction as compared to t...