AIMC Topic: Self-Injurious Behavior

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Development of a Self-Harm Monitoring System for Victoria.

International journal of environmental research and public health Dec 15, 2020
The prevention of suicide and suicide-related behaviour are key policy priorities in Australia and internationally. The World Health Organization has recommended that member states develop self-harm surveillance systems as part of their suicide preve...
Humans Self-Injurious Behavior Artificial Intelligence Victoria Suicide, Attempted Adolescent Emergency Service, Hospital
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Using machine learning to classify suicide attempt history among youth in medical care settings.

Journal of affective disorders Feb 28, 2020
BACKGROUND: The current study aimed to classify recent and lifetime suicide attempt history among youth presenting to medical settings using machine learning (ML) as applied to a behavioral health screen self-report survey.
Pennsylvania Adolescent Suicidal Ideation Emergency Service, Hospital Self-Injurious Behavior Humans Machine Learning Algorithms Female Risk Factors Cross-Sectional Studies Male Suicide, Attempted
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Predicting mechanical restraint of psychiatric inpatients by applying machine learning on electronic health data.

Acta psychiatrica Scandinavica Jul 6, 2019
OBJECTIVE: Mechanical restraint (MR) is used to prevent patients from harming themselves or others during inpatient treatment. The objective of this study was to investigate whether incident MR occurring in the first 3 days following admission could ...
Predictive Value of Tests Self-Injurious Behavior Restraint, Physical Early Warning Score Case-Control Studies Humans Time Factors Hospitalization Machine Learning Inpatients Electronic Health Records Sensitivity and Specificity Mental Disorders Denmark Female Male
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Using natural language processing of clinical text to enhance identification of opioid-related overdoses in electronic health records data.

Pharmacoepidemiology and drug safety Jun 19, 2019
PURPOSE: To enhance automated methods for accurately identifying opioid-related overdoses and classifying types of overdose using electronic health record (EHR) databases.
Humans Electronic Health Records Sensitivity and Specificity Washington Predictive Value of Tests Natural Language Processing Drug Overdose Analgesics, Opioid Self-Injurious Behavior Opioid-Related Disorders Risk Datasets as Topic Heroin
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The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review.

Journal of affective disorders Nov 12, 2018
BACKGROUND: Machine learning techniques offer promise to improve suicide risk prediction. In the current systematic review, we aimed to review the existing literature on the application of machine learning techniques to predict self-injurious thought...
Suicidal Ideation Humans Predictive Value of Tests Machine Learning Self-Injurious Behavior Risk Assessment Suicide, Attempted
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Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning.

Journal of child psychology and psychiatry, and allied disciplines Apr 30, 2018
BACKGROUND: Adolescents have high rates of nonfatal suicide attempts, but clinically practical risk prediction remains a challenge. Screening can be time consuming to implement at scale, if it is done at all. Computational algorithms may predict suic...
Depression Adolescent Longitudinal Studies Self-Injurious Behavior Female Male Risk Assessment Suicide, Attempted Humans Machine Learning Retrospective Studies
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Novel Use of Natural Language Processing (NLP) to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid.

Computational and mathematical methods in medicine Sep 26, 2016
Natural language processing (NLP) and machine learning were used to predict suicidal ideation and heightened psychiatric symptoms among adults recently discharged from psychiatric inpatient or emergency room settings in Madrid, Spain. Participants re...
Diagnosis, Computer-Assisted Machine Learning Surveys and Questionnaires Hospitals, Psychiatric Psychometrics Telemedicine Algorithms Sensitivity and Specificity Humans Reproducibility of Results Follow-Up Studies Mental Health Services Spain Mental Disorders Male Self-Injurious Behavior Hospitalization Predictive Value of Tests Female Middle Aged Text Messaging Young Adult Natural Language Processing Suicide, Attempted Reminder Systems Adult Patient Discharge
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Development of an explainable machine learning model for predicting depression in adolescent girls with non-suicidal self-injury: A cross-sectional multicenter study.

Journal of affective disorders Jun 15, 2025
Non-suicidal self-injury (NSSI) in adolescent girls is a critical predictor of subsequent depression and suicide risk, yet current tools lack both accuracy and clinical interpretability. We developed the first explainable machine learning model integ...
Risk Factors Cross-Sectional Studies Depression Adolescent Humans Self-Injurious Behavior Machine Learning Female
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Machine Learning to Differentiate Risk of Suicide Attempt and Self-harm After General Medical Hospitalization of Women With Mental Illness.

Medical care Feb 1, 2021
BACKGROUND: Suicide prevention is a public health priority, but risk factors for suicide after medical hospitalization remain understudied. This problem is critical for women, for whom suicide rates in the United States are disproportionately increas...
Cohort Studies Supervised Machine Learning Patient Readmission Mental Disorders Humans Self-Injurious Behavior Women Adult Retrospective Studies Algorithms Sensitivity and Specificity Electronic Health Records Hospitalization Reproducibility of Results Middle Aged Female Aged Risk Factors Suicide, Attempted Young Adult
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Detecting and Classifying Self-injurious Behavior in Autism Spectrum Disorder Using Machine Learning Techniques.

Journal of autism and developmental disorders Nov 1, 2020
Traditional self-injurious behavior (SIB) management can place compliance demands on the caregiver and have low ecological validity and accuracy. To support an SIB monitoring system for autism spectrum disorder (ASD), we evaluated machine learning me...
Humans Machine Learning Autism Spectrum Disorder Child Electrocardiography Cluster Analysis Self-Injurious Behavior Female Male Adolescent Child, Preschool
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