AIMC Topic: Suicidal Ideation

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Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic.

Scientific reports
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
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
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)
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
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
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...

Differentiating adolescent suicidal and nonsuicidal self-harm with artificial intelligence: Beyond suicidal intent and capability for suicide.

Journal of affective disorders
Clinical differentiation between adolescent suicidal self-harm (SSH) and nonsuicidal self-harm (NSSH) is a significant challenge for mental health professionals, and its feasibility is controversial. The aim of the present study was to determine whet...

An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study.

JMIR public health and surveillance
BACKGROUND: Suicide represents a critical public health concern, and machine learning (ML) models offer the potential for identifying at-risk individuals. Recent studies using benchmark datasets and real-world social media data have demonstrated the ...

Natural language processing to identify suicidal ideation and anhedonia in major depressive disorder.

BMC medical informatics and decision making
BACKGROUND: Anhedonia and suicidal ideation are symptoms of major depressive disorder (MDD) that are not regularly captured in structured scales but may be captured in unstructured clinical notes. Natural language processing (NLP) techniques may be u...