AIMC Topic: Mental Disorders

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Bayesian model averaging based deep learning forecasts of inpatient bed occupancy in mental health facilities.

Scientific reports
Mental health disorders affect over 15% of the global working-age population, contributing to an annual economic loss of approximately USD 1 trillion due to diminished productivity and increased healthcare expenditures. In India, the post-pandemic su...

Generative AI-assisted clinical interviewing of mental health.

Scientific reports
The standard assessment of mental health typically involves clinical interviews conducted by highly trained clinicians. While effective, this approach faces substantial limitations, including high costs, high clinician workload, variability in expert...

Ethical and legal considerations of artificial intelligence applications in psychiatric violence risk assessment: A scoping review protocol.

PloS one
Violence risk assessment is a critical component of psychiatric practice, with significant clinical, ethical, and legal implications. Psychiatric patients at high risk of violence often face interventions including restraints, intramuscular injection...

The usefulness of microbiome profiling for geriatric patients with neuropsychiatric conditions: a scoping review.

Translational psychiatry
INTRODUCTION: Neuropsychiatric disorders encompass psychiatric and neurodegenerative diseases. These conditions are particularly challenging to diagnose in the elderly due to their overlapping cognitive, affective, and behavioural symptoms. Recent st...

Multi-modal deep-attention-BiLSTM based early detection of mental health issues using social media posts.

Scientific reports
The rising prevalence of mental health disorders such as depression, anxiety, and bipolar disorder underscores the urgent need for effective tools to enable early detection and intervention. Social media platforms like Reddit offer a rich source of u...

Weighing Costs and Benefits of Delay and the Acceptance of Two Decision Support Tools in Mental Health Care: Scoping Study Using Quantitative and Qualitative Data.

JMIR human factors
BACKGROUND: Mental disorders are the leading cause of disability in young people (aged 12-30 years), and their incidence constitutes a major health crisis. Primary youth mental health services are struggling to keep up due to overwhelming demand, the...

Speech Emotion Recognition in Mental Health: Systematic Review of Voice-Based Applications.

JMIR mental health
BACKGROUND: The field of speech emotion recognition (SER) encompasses a wide variety of approaches, with artificial intelligence technologies providing improvements in recent years. In the domain of mental health, the links between individuals' emoti...

Neuromodulation and neural networks in psychiatric disorders: current status and emerging prospects.

Psychological medicine
Psychiatric disorders lead to disability, premature mortality and economic burden, highlighting the urgent need for more effective treatments. The understanding of psychiatric disorders as conditions of large-scale brain networks has created new oppo...

Mortality prediction for ICU patients with mental disorders using large language models ensemble and unstructured medical notes.

PloS one
Assessing mortality risk in the intensive care unit (ICU) is crucial for improving clinical outcomes and management strategies. Conventional artificial intelligence studies often neglect vital clinical information contained in unstructured medical no...

Integrating multiple feature assessment methods to identify key predictors of repeat suicide attempts in Taiwan.

BMC psychiatry
BACKGROUND: The high rate of repeat attempts among individuals who have previously attempted suicide presents a critical challenge in public health and suicide prevention. While early and targeted intervention is crucial for this high-risk group, eff...