AIMC Topic: Suicide
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Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records.
Translational psychiatry
Jul 31, 2024
Machine Learning models trained from real-world data have demonstrated promise in predicting suicide attempts in adolescents. However, their transportability, namely the performance of a model trained on one dataset and applied to different data, is ...
Anticipating influential factors on suicide outcomes through machine learning techniques: Insights from a suicide registration program in western Iran.
Asian journal of psychiatry
Jul 28, 2024
Suicide is a global public health concern, with increasing rates observed in various regions, including Iran. This study focuses on the province of Hamadan, Iran, where suicide rates have been on the rise. The research aims to predict factors influen...
Using natural language processing to evaluate temporal patterns in suicide risk variation among high-risk Veterans.
Psychiatry research
Jul 27, 2024
Measuring suicide risk fluctuation remains difficult, especially for high-suicide risk patients. Our study addressed this issue by leveraging Dynamic Topic Modeling, a natural language processing method that evaluates topic changes over time, to anal...
Machine Learning-Based Evaluation of Suicide Risk Assessment in Crisis Counseling Calls.
Psychiatric services (Washington, D.C.)
Jul 19, 2024
OBJECTIVE: Counselor assessment of suicide risk is one key component of crisis counseling, and standards require risk assessment in every crisis counseling conversation. Efforts to increase risk assessment frequency are limited by quality improvement...
Predicting negative attitudes towards suicide in social media texts: prediction model development and validation study.
Frontiers in public health
Jul 8, 2024
BACKGROUND: Implementing machine learning prediction of negative attitudes towards suicide may improve health outcomes. However, in previous studies, varied forms of negative attitudes were not adequately considered, and developed models lacked rigor...
Machine learning applied to the prediction of relapse, hospitalization, and suicide in bipolar disorder using neuroimaging and clinical data: A systematic review.
Journal of affective disorders
Jun 21, 2024
BACKGROUND: Bipolar disorder (BD) is associated with increased morbidity/mortality. Adverse outcome prediction might help with the management of patients with BD.
Predicting State-Level Firearm Suicide Rates: A Machine Learning Approach Using Public Policy Data.
American journal of preventive medicine
Jun 20, 2024
INTRODUCTION: Over 40,000 people die by suicide annually in the U.S., and firearms are the most lethal suicide method. There is limited evidence on the effectiveness of many state-level policies on reducing firearm suicide. The objective of this stud...
Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies.
BMC medical informatics and decision making
May 27, 2024
OBJECTIVE: Suicide is a complex and multifactorial public health problem. Understanding and addressing the various factors associated with suicide is crucial for prevention and intervention efforts. Machine learning (ML) could enhance the prediction ...
Machine Learning-Based Prediction of Suicidal Thinking in Adolescents by Derivation and Validation in 3 Independent Worldwide Cohorts: Algorithm Development and Validation Study.
Journal of medical Internet research
May 17, 2024
BACKGROUND: Suicide is the second-leading cause of death among adolescents and is associated with clusters of suicides. Despite numerous studies on this preventable cause of death, the focus has primarily been on single nations and traditional statis...
A machine learning approach to detect potentially harmful and protective suicide-related content in broadcast media.
PloS one
May 14, 2024
Suicide-related media content has preventive or harmful effects depending on the specific content. Proactive media screening for suicide prevention is hampered by the scarcity of machine learning approaches to detect specific characteristics in news ...
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