Psychiatry

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

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SleepDepNet: A Multi-Task Transformer Framework for Assessing Sleep Quality and Depression Risk from Social Media Narratives

The bidirectional relationship between sleep disturbances and depression presents a serious challeng...

A Computational Ethology Approach for Characterizing Behavioral Dynamics in Bipolar Disorder

Recent technologies for quantifying behavior have revolutionized animal studies in social, cognitive...

Predicting and Preventing Suicide at Entry to Mental Health Care: A Community-Engaged, Machine Learning Model Implementation

Suicide rates in the United States have increased steadily over the past twenty years, a trend coinc...

Deep Learning Cerebellar Magnetic Resonance Imaging Segmentation in Late-Onset GM2 Gangliosidosis: Implications for Phenotype

Late-onset Tay-Sachs (LOTS) disease and late-onset Sandhoff disease (LOSD) have long been considered...

The dark side of the mood: structural and functional fronto-insular and cerebellar alterations classify major depression

Despite major depressive disorder (MDD) being the leading cause of disability worldwide, the exact c...

Early Detection of Autism Spectrum Disorder in Children Using Different Machine Learning Algorithms

Autism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities...

Cross-Disorder Machine Learning Uncovers Schizophrenia Risk Variants Predictive of Alzheimer’s Disease

Alzheimer’s disease (AD) and Schizophrenia (SCZ) exhibit overlapping clinical features and biologica...

Functional improvement is a better predictor of steady work than medical improvement for individuals with mental health conditions

The Supported Employment Demonstration (SED) offered vocational and mental health services to recent...

Silencer variants are key drivers of gene upregulation in Alzheimer’s disease

Alzheimer’s disease (AD), particularly late-onset AD, stands as the most prevalent neurodegenerative...

The effect of psychotherapy on the multivariate association between insomnia and depressive symptoms in late-life depression

Late-life depression (LLD) is prevalent in older adults and linked to increased disability, mortalit...

Predicting Positive Psychological States using Machine Learning and Digital Biomarkers from Everyday Wearable Data

Wearable devices offer continuous physiological data collection, presenting new opportunities for re...

Leveraging Large Language Models for Digital Phenotyping: Detecting Depressive State Changes for Patients with Depressive Episodes

Digital phenotyping, which takes advantage of data continuously gathered from smartphones and wearab...

Changes in psychiatric documentation and treatment in primary care with artificial intelligence scribe use

Despite increasingly widespread use of artificial intelligence-driven ambient scribes in medicine, t...

Key predictors of maternal mild depression and anxiety in low resource settings: A machine learning approach

Maternal mental health (MMH) disorders, particularly depression and anxiety, are major public health...

Elucidating Emotional Patterns in Autism Spectrum Disorder: BERT-Based Analysis Reveals Novel Dimensional Structure

Autism spectrum disorder (ASD) is associated with difficulties in emotion recognition and regulation...

Development and validation of genomic biotypes for schizophrenia susceptibility from multiple polygenic scores

Understanding the genetic architecture of schizophrenia (SCZ) is invaluable for the development of p...

Machine Learning-Enabled EEG Biomarkers Predict Divergent Antidepressant and Placebo Response in a Clinical Trial of Major Depression

Major depressive disorder (MDD) is a heterogeneous neuropsychiatric disorder with highly variable an...

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