Psychiatry

Prediction of early-onset bipolar using electronic health records.

BACKGROUND: Early identification of bipolar disorder (BD) provides an important opportunity for time...

Distinct neural networks of emotional valence and uncertainty in the human amygdala underlying different mental disorders.

Predicting Treatment Response of Repetitive Transcranial Magnetic Stimulation in Major Depressive Disorder Using an Explainable Machine Learning Model Based on Electroencephalography and Clinical Features.

Major depressive disorder (MDD) is highly heterogeneous in response to repetitive transcranial magne...

A systematic literature review of machine learning techniques for the detection of attention-deficit/hyperactivity disorder using MRI and/or EEG data.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition common in teenager...

Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.

This study examined mental health disparities among African Americans using AI and machine learning ...

Identification of 17 novel epigenetic biomarkers associated with anxiety disorders using differential methylation analysis followed by machine learning-based validation.

BACKGROUND: The changes in DNA methylation patterns may reflect both physical and mental well-being,...

Prediction of depressive disorder using machine learning approaches: findings from the NHANES.

BACKGROUND: Depressive disorder, particularly major depressive disorder (MDD), significantly impact ...

Interpretable machine learning approaches for children's ADHD detection using clinical assessment data: an online web application deployment.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent mental disorder character...

Efficient Neural Network Classification of Parkinson's Disease and Schizophrenia Using Resting-State EEG Data.

Timely identification of Parkinson's disease and schizophrenia is crucial for the effective manageme...

Hybrid multi-modality multi-task learning for forecasting progression trajectories in subjective cognitive decline.

While numerous studies strive to exploit the complementary potential of MRI and PET using learning-b...

Exploring Potential Medications for Alzheimer's Disease with Psychosis by Integrating Drug Target Information into Deep Learning Models: A Data-Driven Approach.

Approximately 50% of Alzheimer's disease (AD) patients develop psychotic symptoms, leading to a subt...

Comparison of logistic regression and machine learning methods for predicting depression risks among disabled elderly individuals: results from the China Health and Retirement Longitudinal Study.

BACKGROUND: Given the accelerated aging population in China, the number of disabled elderly individu...

The application of artificial intelligence in the field of mental health: a systematic review.

INTRODUCTION: The integration of artificial intelligence in mental health care represents a transfor...

Predicting antipsychotic responsiveness using a machine learning classifier trained on plasma levels of inflammatory markers in schizophrenia.

We apply machine learning techniques to navigate the multifaceted landscape of schizophrenia. Our me...

Differentiating adolescent suicidal and nonsuicidal self-harm with artificial intelligence: Beyond suicidal intent and capability for suicide.

Clinical differentiation between adolescent suicidal self-harm (SSH) and nonsuicidal self-harm (NSSH...

Revolutionizing e-health: the transformative role of AI-powered hybrid chatbots in healthcare solutions.

INTRODUCTION: The integration of Artificial Intelligence (AI) in healthcare, particularly through hy...

A systematic review of structural neuroimaging markers of psychotherapeutic and pharmacological treatment for obsessive-compulsive disorder.

Identifying individual difference factors associated with treatment response and putative mechanisms...

Efficacy and effectiveness of therapist-guided internet versus face-to-face cognitive behavioural therapy for depression via counterfactual inference using naturalistic registers and machine learning in Finland: a retrospective cohort study.

BACKGROUND: According to meta-analyses of randomised controlled trials (RCTs), therapist-guided inte...

Identifying Adolescent Depression and Anxiety Through Real-World Data and Social Determinants of Health: Machine Learning Model Development and Validation.

BACKGROUND: The prevalence of adolescent mental health conditions such as depression and anxiety has...

Apriori algorithm based prediction of students' mental health risks in the context of artificial intelligence.

INTRODUCTION: The increasing prevalence of mental health challenges among college students necessita...

A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD.

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder ...