Latest AI and machine learning research in psychiatry for healthcare professionals.
Precision psychiatry seeks to improve individual-level prediction, treatment selection, monitoring, and prevention by integrating clinical, biological, behavioural, digital, and contextual information. This structured narrative review assessed the clinical readiness of major approaches using a purpose-specific framework covering validity, external replication, incremental utility, actionability, p...
PURPOSE: Coercive practices in psychiatric hospitals present clinical and ethical challenges. Aiming to support prevention, we developed and evaluated machine learning models predicting mechanical restraint and a composite of related coercive measures. MATERIALS AND METHODS: The dataset comprised electronic health records from adults admitted to the Psychiatric Services in the Central Denmark Regi...
Temporal information processing is critical for brain function, supporting neural computations such as novelty detection, adaptation, and temporal nor...
Current detection models for suicidal ideation (SI) among depressed patients have primarily relied on clinical and biological features. This study aim...
OBJECTIVES: Factors associated with depression were explored in this study through logistic regression, and predictive performance was compared with v...
BACKGROUND: Internet-based cognitive behavioral therapy (iCBT) is an effective and scalable alternative to face-to-face psychotherapy, but its reach i...
BackgroundToilet training is a critical developmental milestone that may have long-term implications for children's psychosocial development if improp...
Graph Neural Networks (GNNs) model functional connectivity patterns between brain regions via neighborhood information aggregation. However, most GNN ...
BACKGROUND: Refugees and forcibly displaced populations experience elevated rates of mental health conditions, including posttraumatic stress disorder...
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INTRODUCTION: Social and occupational impairment is common in early psychosis, yet predictors of functional outcome in real-world early intervention i...
AIMS: Epigenetic regulation of the oxytocin receptor gene (OXTR), particularly DNA methylation (DNAm), has been linked to insecure attachment, anxiety...
People tend to evaluate more positively the members of their group. This study examined this behavior in autistic children to better understand the st...
AIM: To analyze the integration of Artificial Intelligence in nursing through the lens of the Fundamentals of Care framework. DESIGN: A discursive pap...
OBJECTIVE: This study seeks to explore the utility of social determinants of health (SDoH) variables in suicide prediction models. We aim to assess th...
Adolescent major depressive disorder (MDD) is a heterogeneous disorder that complicates diagnosis and treatment. However, the mechanisms underlying th...
AI-enabled self-management health tools are increasingly promoted within health care policy as part of digital self-management models for mental healt...
AIMS: Psychotic experiences (PEs) are relatively common in youth and are associated with increased risk for later psychotic disorders. Although inflam...
BACKGROUND AND HYPOTHESIS: Schizophrenia (SCZ) is characterized by deficits in emotional expression, with facial expressions serving as potential mark...
Understanding functional connectivity alterations across manic, depressive, and remitted states of bipolar disorder (BD) remains an important challeng...