BACKGROUND: Machine learning (ML) has been widely used to predict suicidal ideation (SI) in adolescents and adults. Nevertheless, studies of accurate and efficient models of SI prediction with preadolescent children are still needed because SI is sur...
ObjectiveThe global surge in adolescent suicide necessitates the development of innovative and efficacious preventive measures. Traditionally, various approaches have been used, but with limited success. However, with the rapid advancements in artifi...
BACKGROUND: Depression is a common mental disorder and causes significant social loss. Early intervention for depression is important. Nonetheless, depressed patients tend to conceal their symptoms from others based on shame and stigma, thus hesitate...
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...
BACKGROUND: The current study developed a predictive model for suicide ideation among South Korean (Korean) adolescents using a comprehensive set of factors across demographic, physical and mental health, academic, social, and behavioral domains. The...
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...
International journal of environmental research and public health
Jan 13, 2023
(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...
International journal of environmental research and public health
Oct 3, 2022
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...
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...
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...
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