AIMC Topic: Suicidal Ideation
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Functional connectome-based predictive modeling of suicidal ideation.
Journal of affective disorders
May 27, 2025
Suicide represents an egregious threat to society despite major advancements in medicine, in part due to limited knowledge of the biological mechanisms of suicidal behavior. We apply a connectome predictive modeling machine learning approach to ident...
Suicide risk prediction for Korean adolescents based on machine learning.
Scientific reports
Apr 28, 2025
Traditional clinical risk assessment tools proved inadequate for reliably identifying individuals at high risk for suicidal behavior. As a result, machine learning (ML) techniques have become progressively incorporated into psychiatric care. This stu...
Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach.
Translational psychiatry
Apr 24, 2025
Young adults with childhood sexual abuse (CSA) are an especially vulnerable group to suicide. Suicide encompasses different phases, but for CSA survivors the salient factors precipitating suicide are rarely studied. In this study, from a progressive ...
A cohort study of predictors of short-term nonfatal suicidal and self-harm events among individuals with mental health disorders treated in the emergency department.
Journal of psychiatric research
Apr 22, 2025
BACKGROUND: Patients presenting to emergency departments (EDs) for mental health problems have an elevated short-term risk of repeat ED visits, subsequent hospitalization, and suicide.
Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic.
Scientific reports
Apr 22, 2025
Suicide causes over 700,000 deaths annually worldwide. Mental disorders are closely linked to suicidal ideation, but predicting suicide remains complex due to the multifaceted nature of contributing factors. Traditional assessment tools often fail to...
The Application of AI to Ecological Momentary Assessment Data in Suicide Research: Systematic Review.
Journal of medical Internet research
Apr 17, 2025
BACKGROUND: Ecological momentary assessment (EMA) captures dynamic processes suitable to the study of suicidal ideation and behaviors. Artificial intelligence (AI) has increasingly been applied to EMA data in the study of suicidal processes.
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...
[Not Available].
Vertex (Buenos Aires, Argentina)
Apr 10, 2025
Introducción: la ideación suicida es el pensamiento de autoeliminación no siempre reportada por los pacientes en test de depresión. El objetivo fue identificar y analizar síntomas depresivos del cuestionario de salud del paciente-9 asociados a ideaci...
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...
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...
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