AIMC Topic: Self-Injurious Behavior
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Using machine learning approach to predict suicide ideation and suicide attempts among Chinese adolescents: A cross-sectional study.
Journal of affective disorders
Apr 25, 2025
BACKGROUND: Screening for suicide ideation and suicide attempts is crucial for adolescents, yet accurately predicting these outcomes remains a significant challenge. The relationship between non-suicidal self-injury and suicide ideation and attempts ...
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.
Using machine learning to identify features associated with different types of self-injurious behaviors in autistic youth.
Psychological medicine
Mar 31, 2025
BACKGROUND: Self-injurious behaviors (SIB) are common in autistic people. SIB is mainly studied as a broad category, rather than by specific SIB types. We aimed to determine associations of distinct SIB types with common psychiatric, emotional, medic...
Differentiating adolescent suicidal and nonsuicidal self-harm with artificial intelligence: Beyond suicidal intent and capability for suicide.
Journal of affective disorders
Feb 13, 2025
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...
Applications of Large Language Models in the Field of Suicide Prevention: Scoping Review.
Journal of medical Internet research
Jan 23, 2025
BACKGROUND: Prevention of suicide is a global health priority. Approximately 800,000 individuals die by suicide yearly, and for every suicide death, there are another 20 estimated suicide attempts. Large language models (LLMs) hold the potential to e...
Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.
Computers in biology and medicine
Jan 21, 2025
Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent a growing global concern. Early detection of these conditions is crucial for timely intervention and prevention of adverse outcomes. In this study, we...
Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings.
PloS one
Jan 16, 2025
Self-injury is common in all countries, and 20% of South Korean youths experience self-injury. One of the barriers to assessment and treatment planning is the tendency of young self-injurers to conceal their identities. Following a new stream of rese...
Comparison between clinician and machine learning prediction in a randomized controlled trial for nonsuicidal self-injury.
BMC psychiatry
Dec 18, 2024
BACKGROUND: Nonsuicidal self-injury is a common health problem in adolescents and associated with future suicidal behavior. Predicting who will benefit from treatment is an urgent and a critical first step towards personalized treatment approaches. M...
Predicting the trajectory of non-suicidal self-injury among adolescents.
Journal of child psychology and psychiatry, and allied disciplines
Aug 13, 2024
BACKGROUND: Non-suicidal self-injury (NSSI) is common among adolescents receiving inpatient psychiatric treatment and the months post-discharge is a high-risk period for self-injurious behavior. Thus, identifying predictors that shape the course of p...
Machine learning identifies different related factors associated with depression and suicidal ideation in Chinese children and adolescents.
Journal of affective disorders
Jun 4, 2024
BACKGROUND: Depression and suicidal ideation often co-occur in children and adolescents, yet they possess distinct characteristics. This study sought to identify the different related factors associated with depression and suicidal ideation.
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