Psychiatry

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

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COMPASS: Computational mapping of patient-therapist alliance strategies with language modeling.

The therapeutic working alliance is a critical predictor of psychotherapy success. Traditionally, wo...

Evaluating Generative AI in Mental Health: Systematic Review of Capabilities and Limitations.

BACKGROUND: The global shortage of mental health professionals, exacerbated by increasing mental hea...

A machine-learning-derived online prediction model for depression risk in COPD patients: A retrospective cohort study from CHARLS.

BACKGROUND: Depression associated with Chronic Obstructive Pulmonary Disease (COPD) is a detrimental...

Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data.

Depression and anxiety are common comorbidities of stroke. Research has shown that about 30% of stro...

Effectiveness of AI-Driven Conversational Agents in Improving Mental Health Among Young People: Systematic Review and Meta-Analysis.

BACKGROUND: The increasing prevalence of mental health issues among adolescents and young adults, co...

Leveraging neighborhood-level Information to Improve Model Fairness in Predicting Prenatal Depression.

IMPORTANCE: Perinatal depression (PND) affects 10-20% of pregnant women, with significant racial dis...

Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder.

According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults s...

Unmet educational accommodation needs and mental health outcomes in adults with disabilities: A machine learning approach.

BACKGROUND: No research has yet determined exactly what accommodation needs are unmet for disabled s...

Major depressive disorder recognition based on electronic handwriting recorded in psychological tasks.

BACKGROUND: This study aimed to determine whether handwriting patterns are altered in individuals ex...

Early detection of mental health disorders using machine learning models using behavioral and voice data analysis.

People of all demographics are impacted by mental illness, which has become a widespread and interna...

Realistic Subject-Specific Simulation of Resting State Scalp EEG Based on Physiological Model.

Electroencephalography (EEG) recordings are widely used in neuroscience to identify healthy individu...

Combining Artificial Intelligence and Human Support in Mental Health: Digital Intervention With Comparable Effectiveness to Human-Delivered Care.

BACKGROUND: Escalating mental health demand exceeds existing clinical capacity, necessitating scalab...

Biological markers and psychosocial factors predict chronic pain conditions.

Chronic pain is a multifactorial condition presenting significant diagnostic and prognostic challeng...

Peer Relationships Are a Direct Cause of the Adolescent Mental Health Crisis: Interpretable Machine Learning Analysis of 2 Large Cohort Studies.

BACKGROUND: Converging evidence indicates an adolescent mental health crisis in Western societies th...

Association of risk factors with mental illness in a rural community: insights from machine learning models.

BACKGROUND: Mental health conditions, particularly depression and anxiety, are highly prevalent and ...

Fatigue and management of warfighter mental endurance.

Mental fatigue (MF) is a psychobiological state induced by prolonged exertion that has the potential...

Reasoning language models for more transparent prediction of suicide risk.

BACKGROUND: We previously demonstrated that a large language model could estimate suicide risk using...

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