Psychiatry

Latest AI and machine learning research in psychiatry for healthcare professionals.

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Transforming Behavioral Neuroscience Discovery with In-Context Learning and AI-Enhanced Tensor Methods

Scientific discovery pipelines typically involve complex, rigid, and time-consuming processes, from ...

Life-course comorbidity patterns and integrated prediction of postpartum depression, multimorbidity, and symptom progression

Perinatal depression (PD) is common and disabling, yet its longitudinal comorbidity patterns and pre...

Development and cross-tissue validation of a methylation profile score for the cortisol response to stress

Hypothalamic-pituitary-adrenal axis (HPA axis) dysregulation is a risk factor for poor mental and ph...

Disparities, Perceived Discrimination, and Patient-Clinician Communication in Alcohol Use Disorder Treatment: An All of Us Cohort Study

Background and Aims: Alcohol use disorder (AUD) remains a major public health concern, with persiste...

Reproducible symptom subtypes of depression identified using unsupervised machine learning

Depression is a heterogeneous disorder, often diagnosed based on symptom co-occurrence. However, ind...

Application of Explainable AI in Neuroscience: Enhancing Autism Screening

The main challenges in the life of a child with autism are difficulties in communication, behavior, ...

Development and validation of neurological health score using machine learning algorithms

Neurological health score (NHS), indicating the health of brain and nervous system, helps in identif...

Exploring the Influence of Lifestyle, Social Health, and Demographic Factors on Psychological Well-being and Engagement Levels

Loneliness and psychological well-being are increasingly recognized as critical public health concer...

When attention falters: brain, breathing, and behavioral signals of lapses in interoceptive attention

Mind-body practices like meditation and yoga, which are widely used to support mental health, involv...

Diagnostic Accuracy and Clinical Reasoning of Multiple Large Language Models in Psychiatry

Importance: Large language models (LLMs) have demonstrated diagnostic potential in several medical s...

Deep Learning Reveals Cross-Modal Neural Representations of Auditory and Visual Mental Imagery in MEG

Mental imagery provides a unique window into the brain's ability to internally simulate sensory expe...

Domain Adaptation Enables Cross-site Classification of First-episode Schizophrenia from Multimodal Neuroimaging Data

Identifying robust neuroimaging markers associated with schizophrenia is essential for advancing res...

Beyond Pixels: Visual Metaphor Transfer via Schema-Driven Agentic Reasoning

A visual metaphor constitutes a high-order form of human creativity, employing cross-domain semantic...

Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples

Human social interactions rely on the ability to reflect on one's own and others' internal states an...

Individual Differences in Dopaminergic Modulation of Exploration-Exploitation Behaviour

Dopamine (DA) has been implicated in exploration-exploitation behaviour, i.e., exploring novel, pote...

Generation of Synthetic Data in Health Surveys Using Large Language Models

Background: Generating synthetic data using artificial intelligence, such as large language models (...

Determinants of Digital Health Technology Acceptance Among Healthcare Caregivers: A Structural Equation Modeling Approach

Background: Digital health technologies, including artificial intelligence (AI)-powered tools and vi...

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