AIMC Topic: Suicide

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[Suicide epidemiology in the province of Málaga (Spain) [2024]: a retrospective analysis using machine learning techniques].

Revista espanola de salud publica
OBJECTIVE: Suicide constitutes a Public Health challenge whose demographic and geographical heterogeneity demands targeted interventions. The paucity of subnational studies integrating advanced data analytics restricts the precise identification of r...

Multimodal Multitask Learning for Predicting Depression Severity and Suicide Risk Using Pretrained Audio and Text Embeddings: Methodology Development and Application.

JMIR medical informatics
BACKGROUND: Depression is a critical psychological disorder necessitating urgent assessment and treatment, given its strong association with increased suicide risk (SR). Effective management hinges on promptly identifying individuals with high depres...

Detecting suicide risk in bipolar disorder patients from lymphoblastoid cell lines genetic signatures.

Translational psychiatry
This research aimed to develop a machine learning algorithm to predict suicide risk in bipolar disorder (BD) patients using RNA sequencing analysis of lymphoblastoid cell lines (LCLs). By identifying differentially expressed genes (DEGs) between high...

Recent developments in omics studies and artificial intelligence in depression and suicide.

Translational psychiatry
Major depressive disorder (MDD) is the most prevalent and severe form of mental illness and is significantly linked to suicide. At present, addressing the treatment and prevention of depression and suicide poses significant challenges, largely due to...

Predicting adolescent suicide risk using integrated data from adolescents, parents and siblings: An analysis of multiple machine learning models.

Journal of affective disorders
Adolescent suicide is a critical public health issue, yet accurately predicting suicide risk remains challenging. Few studies integrate adolescents' self-reports with mental health, especially suicidality assessments from parents and siblings. This s...

Assessment of suicidal risk factors in young depressed persons with non-suicidal self-injury based on an artificial intelligence.

BMC psychology
INTRODUCTION: The role of non-suicidal self-injury (NSSI) in the suicide process of people with major depressive disorder(MDD) remains controversial. Therefore, the purpose of this study was to investigate the role NSSI plays in suicide risk in peopl...

Prediction of suicide using web based voice recordings analyzed by artificial intelligence.

Scientific reports
The integration of machine learning (ML) and deep learning models in suicide risk assessment has advanced significantly in recent years. In this study, we utilized ML in a case-control design, we predicted completed suicides using publicly available,...

Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data.

JMIR research protocols
BACKGROUND: Suicide in local jails occurs at a higher rate than in the general population, requiring improvements to risk screening methods. Current suicide risk screening practices in jails are insufficient: They are commonly not conducted using val...

Online continuous learning of users suicidal risk on social media.

Artificial intelligence in medicine
Suicide is a tragedy for family and society. With social media becoming an integral part of people's life nowadays, assessing suicidal risk based on one's social media behavior has drawn increasing research attentions. The majority of the works train...

Interpretable Machine Learning approach for predicting clinically significant suicide risk: A case study of patients with major depressive disorder in Greece.

Psychiatry research
Suicide prevention is currently a global public health priority, since suicide has been a prevalent cause of death or potential loss of life. Multiple factors contribute to suicide risk, such as depression and a history of attempted suicide among oth...