AIMC Topic: Mental Disorders

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Machine Learning Model Reveals Determinators for Admission to Acute Mental Health Wards From Emergency Department Presentations.

International journal of mental health nursing
This research addresses the critical issue of identifying factors contributing to admissions to acute mental health (MH) wards for individuals presenting to the emergency department (ED) with MH concerns as their primary issue, notably suicidality. T...

Machine Learning, Deep Learning, and Data Preprocessing Techniques for Detecting, Predicting, and Monitoring Stress and Stress-Related Mental Disorders: Scoping Review.

JMIR mental health
BACKGROUND: Mental stress and its consequent mental health disorders (MDs) constitute a significant public health issue. With the advent of machine learning (ML), there is potential to harness computational techniques for better understanding and add...

Designing AI for mental health diagnosis: challenges from sub-Saharan African value-laden judgements on mental health disorders.

Journal of medical ethics
Recently clinicians have become more reliant on technologies such as artificial intelligence (AI) and machine learning (ML) for effective and accurate diagnosis and prognosis of diseases, especially mental health disorders. These remarks, however, ap...

A Deep Learning-Derived Transdiagnostic Signature Indexing Hypoarousal and Impulse Control: Implications for Treatment Prediction in Psychiatric Disorders.

Biological psychiatry. Cognitive neuroscience and neuroimaging
BACKGROUND: Psychiatric disorders are traditionally classified within diagnostic categories, but this approach has limitations. The Research Domain Criteria (RDoC) constitute a research classification system for psychiatric disorders based on dimensi...

Predicting the trajectory of non-suicidal self-injury among adolescents.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Non-suicidal self-injury (NSSI) is common among adolescents receiving inpatient psychiatric treatment and the months post-discharge is a high-risk period for self-injurious behavior. Thus, identifying predictors that shape the course of p...

Identifying momentary suicidal ideation using machine learning in patients at high-risk for suicide.

Journal of affective disorders
BACKGROUND: Strategies to detect the presence of suicidal ideation (SI) or characteristics of ideation that indicate marked suicide risk are critically needed to guide interventions and improve care during care transition periods. Some studies indica...