AIMC Topic: Self-Injurious Behavior
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Emerging Trends of Self-Harm Using Sodium Nitrite in an Online Suicide Community: Observational Study Using Natural Language Processing Analysis.
JMIR mental health
May 2, 2024
BACKGROUND: There is growing concern around the use of sodium nitrite (SN) as an emerging means of suicide, particularly among younger people. Given the limited information on the topic from traditional public health surveillance sources, we studied ...
Exploring the promises and pitfalls of artificial intelligence interventions in predicting adolescent self-harm and suicide attempts.
General hospital psychiatry
Feb 29, 2024
Enhancing emotion regulation with an in situ socially assistive robot among LGBTQ+ youth with self-harm ideation: protocol for a randomised controlled trial.
BMJ open
Jan 9, 2024
INTRODUCTION: Purrble, a socially assistive robot, was codesigned with children to support in situ emotion regulation. Preliminary evidence has found that LGBTQ+ youth are receptive to Purrble and find it to be an acceptable intervention to assist wi...
Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review.
International journal of environmental research and public health
Jan 13, 2023
(1) Introduction: Around a million people are reported to die by suicide every year, and due to the stigma associated with the nature of the death, this figure is usually assumed to be an underestimate. Machine learning and artificial intelligence su...
Key factors selection on adolescents with non-suicidal self-injury: A support vector machine based approach.
Frontiers in public health
Nov 10, 2022
Comparing a family structure to a company, one can often think of parents as leaders and adolescents as employees. Stressful family environments and anxiety levels, depression levels, personality disorders, emotional regulation difficulties, and chil...
A Machine Learning Approach for Predicting Non-Suicidal Self-Injury in Young Adults.
Sensors (Basel, Switzerland)
Jun 24, 2022
Artificial intelligence techniques were explored to assess the ability to anticipate self-harming behaviour in the mental health context using a database collected by an app previously designed to record the emotional states and activities of a group...
Developing a Natural Language Processing tool to identify perinatal self-harm in electronic healthcare records.
PloS one
Aug 4, 2021
BACKGROUND: Self-harm occurring within pregnancy and the postnatal year ("perinatal self-harm") is a clinically important yet under-researched topic. Current research likely under-estimates prevalence due to methodological limitations. Electronic hea...
Trends in reasons for emergency calls during the COVID-19 crisis in the department of Gironde, France using artificial neural network for natural language classification.
Scandinavian journal of trauma, resuscitation and emergency medicine
Mar 31, 2021
OBJECTIVES: During periods such as the COVID-19 crisis, there is a need for responsive public health surveillance indicators in order to monitor both the epidemic growth and potential public health consequences of preventative measures such as lockdo...
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...
Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.
PloS one
Dec 31, 2020
BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making rega...
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