Psychiatry

Editorial: Mental health, epidemiology and machine learning.

Prediction of health anxiety using resting-state functional near-infrared spectroscopy and machine learning.

BACKGROUND: The role of cortical networks in health anxiety remain poorly understood. This study aim...

Predicting cardiovascular disease in patients with mental illness using machine learning.

BACKGROUND: Cardiovascular disease (CVD) is twice as prevalent among individuals with mental illness...

Schizophrenia more employable than depression? Language-based artificial intelligence model ratings for employability of psychiatric diagnoses and somatic and healthy controls.

Artificial Intelligence (AI) assists recruiting and job searching. Such systems can be biased agains...

The Goldilocks Zone: Finding the right balance of user and institutional risk for suicide-related generative AI queries.

Generative artificial intelligence (genAI) has potential to improve healthcare by reducing clinician...

Classification of female MDD patients with and without suicidal ideation using resting-state functional magnetic resonance imaging and machine learning.

Spontaneous blood oxygen level-dependent signals can be indirectly recorded in different brain regio...

Research on the self-efficacy and resilience of female graduate students in the era of artificial intelligence: analysis of the mechanism of mobile phone dependence, anxiety and mentoring relationship.

PURPOSE: The purpose of this study is to investigate the impact of the employment situation on the a...

A Plasma Proteomics-Based Model for Identifying the Risk of Postpartum Depression Using Machine Learning.

Postpartum depression (PPD) poses significant risks to maternal and infant health, yet proteomic ana...

EEG microstate analysis and machine learning classification in patients with obsessive-compulsive disorder.

BACKGROUND: Microstate characterization of electroencephalogram (EEG) is a data-driven approach to e...

MO-GCN: A multi-omics graph convolutional network for discriminative analysis of schizophrenia.

The methodology of machine learning with multi-omics data has been widely adopted in the discriminat...

Prediction of late-onset depression in the elderly Korean population using machine learning algorithms.

Late-onset depression (LOD) refers to depression that newly appears in elderly individuals without p...

A Trustworthy Curriculum Learning Guided Multi-Target Domain Adaptation Network for Autism Spectrum Disorder Classification.

Domain adaptation has demonstrated success in classification of multi-center autism spectrum disorde...

Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions.

INTRODUCTION: Machine learning (ML) is an effective tool for predicting mental states and is a key t...

Machine learning algorithms to predict depression in older adults in China: a cross-sectional study.

OBJECTIVE: The 2-fold objective of this research is to investigate machine learning's (ML) predictiv...

Key risk factors of generalized anxiety disorder in adolescents: machine learning study.

Adolescents worldwide are increasingly affected by mental health disorders, with anxiety disorders, ...

Applied pharmacogenetics to predict response to treatment of first psychotic episode: study protocol.

The application of personalized medicine in patients with first-episode psychosis (FEP) requires too...

Beyond the hot flashes: how machine learning is uncovering the complexity of menopause-related depression.

BACKGROUND: The transition into menopause marks a significant stage in a woman's life, indicating th...

Early detection of autism spectrum disorder: gait deviations and machine learning.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder diagnosed by clinicians and experts ...

Neural correlates of facial recognition deficits in autism spectrum disorder: a comprehensive review.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by significant impair...

DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.

In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusi...

What is the influence of psychosocial factors on artificial intelligence appropriation in college students?

BACKGROUND: In recent years, the adoption of artificial intelligence (AI) has become increasingly re...