AIMC Topic: Suicidal Ideation

Clear Filters Showing 51 to 60 of 105 articles

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...

Machine learning as the new approach in understanding biomarkers of suicidal behavior.

Bosnian journal of basic medical sciences
In psychiatry, compared to other medical fields, the identification of biological markers that would complement current clinical interview, and enable more objective and faster clinical diagnosis, implement accurate monitoring of treatment response a...

Detecting suicidal risk using MMPI-2 based on machine learning algorithm.

Scientific reports
Minnesota Multiphasic Personality Inventory-2 (MMPI-2) is a widely used tool for early detection of psychological maladjustment and assessing the level of adaptation for a large group in clinical settings, schools, and corporations. This study aims t...

Convolutional Neural Network-Based Deep Learning Model for Predicting Differential Suicidality in Depressive Patients Using Brain Generalized q-Sampling Imaging.

The Journal of clinical psychiatry
OBJECTIVE: Suicide is a priority health problem. Suicide assessment depends on imperfect clinician assessment with minimal ability to predict the risk of suicide. Machine learning/deep learning provides an opportunity to detect an individual at risk ...

Using weak supervision and deep learning to classify clinical notes for identification of current suicidal ideation.

Journal of psychiatric research
Mental health concerns, such as suicidal thoughts, are frequently documented by providers in clinical notes, as opposed to structured coded data. In this study, we evaluated weakly supervised methods for detecting "current" suicidal ideation from uns...

Towards a new model and classification of mood disorders based on risk resilience, neuro-affective toxicity, staging, and phenome features using the nomothetic network psychiatry approach.

Metabolic brain disease
Current diagnoses of mood disorders are not cross validated. The aim of the current paper is to explain how machine learning techniques can be used to a) construct a model which ensembles risk/resilience (R/R), adverse outcome pathways (AOPs), stagin...