AIMC Topic: Suicide
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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
Feb 3, 2023
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...
The Design of Psychological Education Intervention System in Universities Based on Deep Learning.
Computational intelligence and neuroscience
Jun 3, 2022
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...
Predicting suicidal thoughts and behavior among adolescents using the risk and protective factor framework: A large-scale machine learning approach.
PloS one
Nov 3, 2021
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...
Detecting suicidal risk using MMPI-2 based on machine learning algorithm.
Scientific reports
Jul 28, 2021
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
Jun 15, 2021
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...
Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm.
Biometrical journal. Biometrische Zeitschrift
May 24, 2021
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 ...
A direct comparison of theory-driven and machine learning prediction of suicide: A meta-analysis.
PloS one
Apr 12, 2021
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...
Identifying intentional injuries among children and adolescents based on Machine Learning.
PloS one
Jan 20, 2021
BACKGROUND: Compared to other studies, the injury monitoring of Chinese children and adolescents has captured a low level of intentional injuries on account of self-harm/suicide and violent attacks. Intentional injuries in children and adolescents ha...
Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities.
JAMA network open
Dec 1, 2020
IMPORTANCE: Suicide is a leading cause of death in the US. However, official national statistics on suicide rates are delayed by 1 to 2 years, hampering evidence-based public health planning and decision-making.
Detection of Suicidality Among Opioid Users on Reddit: Machine Learning-Based Approach.
Journal of medical Internet research
Nov 27, 2020
BACKGROUND: In recent years, both suicide and overdose rates have been increasing. Many individuals who struggle with opioid use disorder are prone to suicidal ideation; this may often result in overdose. However, these fatal overdoses are difficult ...
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