AIMC Topic: Suicidal Ideation

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Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

Asian journal of psychiatry
The present study aims to identify suicide risks in major depressive disorders (MDD) patients from structural MRI (sMRI) data using deep learning. In this paper, we collected the sMRI data of 288 MDD patients, including 110 patients with suicide idea...

Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review.

International journal of environmental research and public health
(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...

Detecting and Analyzing Suicidal Ideation on Social Media Using Deep Learning and Machine Learning Models.

International journal of environmental research and public health
Individuals who suffer from suicidal ideation frequently express their views and ideas on social media. Thus, several studies found that people who are contemplating suicide can be identified by analyzing social media posts. However, finding and comp...

Comparison of three machine learning models to predict suicidal ideation and depression among Chinese adolescents: A cross-sectional study.

Journal of affective disorders
BACKGROUND: Machine learning (ML) algorithms based on various clinicodemographic, psychometric, and biographic factors have been used to predict depression, suicidal ideation, and suicide attempt in adolescents, but there is still a need for more acc...

Suicidal behaviour prediction models using machine learning techniques: A systematic review.

Artificial intelligence in medicine
BACKGROUND: Early detection and prediction of suicidal behaviour are key factors in suicide control. In conjunction with recent advances in the field of artificial intelligence, there is increasing research into how machine learning can assist in the...

The Design of Psychological Education Intervention System in Universities Based on Deep Learning.

Computational intelligence and neuroscience
With the rapid development of Chinese society and economy as well as the deepening of the reform of the higher education management system and the change of employment mode of graduates, college students face various challenges of frustration and pre...

Expressions of anger during advising on life dilemmas predict suicide risk among college students.

PsyCh journal
Research has demonstrated a relationship between anger and suicidality, while real-time authentic emotions behind facial expressions could be detected during advising hypothetical protagonists in life dilemmas. This study aimed to investigate the pre...

Predicting suicidal thoughts and behavior among adolescents using the risk and protective factor framework: A large-scale machine learning approach.

PloS one
INTRODUCTION: Addressing the problem of suicidal thoughts and behavior (STB) in adolescents requires understanding the associated risk factors. While previous research has identified individual risk and protective factors associated with many adolesc...

Deep graph neural network-based prediction of acute suicidal ideation in young adults.

Scientific reports
Precise remote evaluation of both suicide risk and psychiatric disorders is critical for suicide prevention as well as for psychiatric well-being. Using questionnaires is an alternative to labor-intensive diagnostic interviews in a large general popu...