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Suicide, Attempted

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Comparisons of deep learning and machine learning while using text mining methods to identify suicide attempts of patients with mood disorders.

Journal of affective disorders
BACKGROUND: Suicide attempt is one of the most severe consequences for patients with mood disorders. This study aimed to perform deep learning and machine learning while using text mining to identify patients with suicide attempts and to compare thei...

Understanding and detecting behaviours prior to a suicide attempt: A mixed-methods study.

The Australian and New Zealand journal of psychiatry
OBJECTIVE: Prior research suggests there are observable behaviours preceding suicide attempts in public places. However, there are currently no ways to continually monitor such sites, limiting the potential to intervene. In this mixed-methods study, ...

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...

Interpretable Estimation of Suicide Risk and Severity from Complete Blood Count Parameters with Explainable Artificial Intelligence Methods.

Psychiatria Danubina
BACKGROUND: The peripheral inflammatory markers are important in the pathophysiology of suicidal behavior. However, methods for practical uses haven't been developed enough yet. This study developed predictive models based on explainable artificial i...

Prediction of suicidal ideation in children and adolescents using machine learning and deep learning algorithm: A case study in South Korea where suicide is the leading cause of death.

Asian journal of psychiatry
BACKGROUND: Korea has the highest suicide rate among Organisation for Economic Co-operation and Development (OECD) countries. Consequently, central and local governments and private organizations in Korea cooperate in promoting various suicide preven...

Statistical and artificial intelligence techniques to identify risk factors for suicide in children and adolescents.

Science progress
BACKGROUND: Suicidal Behaviors and Thoughts are a relevant public health issue that includes suicidal ideation, non-suicidal self-harm, attempted suicide, and failed suicides. Since there is a progression of suicidal behaviors, whereby suicide is mor...

Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population.

PloS one
Suicide among the older population is a significant public health concern in South Korea. As the older individuals have long considered suicide before committing suicide trials, it is important to analyze the suicidal ideation that precedes the suici...

Development and external validation of a logistic and a penalized logistic model using machine-learning techniques to predict suicide attempts: A multicenter prospective cohort study in Korea.

Journal of psychiatric research
Despite previous efforts to build statistical models for predicting the risk of suicidal behavior using machine-learning analysis, a high-accuracy model can lead to overfitting. Furthermore, internal validation cannot completely address this problem....