Depression

On the value of radiomics in addition to clinical measures in emotional conflict fMRI for predicting sertraline response in major depressive disorder.

Most patients with major depressive disorder (MDD) do not respond to first-line treatment, and robust predictors of individual outcomes are lacking. Functional MRI (fMRI) has shown promise for identifying treatment-relevant brain markers, but standard analyses often rely on mean activation within regions of interest (ROIs). Emotional-conflict fMRI elicits spatially heterogeneous, potentially clini...

Examining public acceptance intentions for government digital human through expectation confirmation and technology acceptance models.

Government digital humans represent a significant application of the combination of generative artificial intelligence and digital governance. This study aims to explore the factors influencing public acceptance of government digital humans, providing insights for enhancing their services and user experience. By integrating expectation confirmation theory (ECT) and the technology acceptance model ...

Development and validation of a deep learning model for automatic detection of depressed skull fractures from CT scans.

BACKGROUND: Depressed skull fractures with bone depression greater than in one cortex might cause major consequences and require surgery in traumatic ...

Between Help and Harm: An Evaluation Study of Mental Health Crisis Handling by Large Language Models.

BACKGROUND: The use of large language models (LLMs)-powered chatbots has reshaped how people seek information and advice, including for emotional and ...

Informatics-Based Psychotherapeutic and Psychiatric Interventions in Dermatology: Scoping Review of Impacts on Skin Disease Severity and Mental Health Outcomes.

BACKGROUND: Chronic dermatologic conditions such as psoriasis, atopic dermatitis, and hidradenitis suppurativa are associated with a high burden of ps...

The engagement-validation loop: Sycophancy, anthropomorphic projection, and clinical risk in informal AI-based mental health support.

Approximately one billion people worldwide live with a mental disorder, yet access to minimally adequate treatment remains low. Against this backdrop,...

Corrigendum to "Machine Learning Models for detecting Suicidal ideation in Chinese in-Patients with major depressive disorder: A Single-center retrospective study" [J. Affect. Disord. 406 (2026) 121679].

A multi-view autoencoder architecture with self-adaptive feature recalibration and confidence-aware ensemble for heart disease classification.

Heart disease continues to pose a major challenge to global health, underscoring the need for early, accurate prediction models. In this study, we int...

Discriminating bipolar depression from major depressive disorder using functional and microstructural signatures of inferior fronto-occipital fasciculus: Promising results from an MRI study.

BACKGROUND: Bipolar depression (BD-d) and major depressive disorder (MDD) share overlapping clinical symptoms, posing a significant diagnostic challen...

Methodological guidance on clinical prediction models in mental health research.

Clinical prediction models play a crucial role in advancing personalized care for mental health disorders, providing essential insights for diagnosis,...

Interpretable Machine Learning to Predict Anxiety or Depression in Acute Ischemic Stroke after IV Thrombolysis: A Retrospective Cohort Study.

BACKGROUND: Acute Ischemic Stroke (AIS) represents a prevalent cerebrovascular condition characterized by significant levels of disability and mortali...

A large-scale annotated Urdu corpus and deep learning benchmark for mental health classification.

Millions of people worldwide are affected by mental health disorders, particularly anxiety and depression, which pose a growing health concern globall...

Exploration of comorbidity mechanisms between chronic pain and depression: Machine learning prediction models and SHAP interpretability analysis based on the CHARLS cohort.

INTRODUCTION: With rapid population aging in China, depression among middle-aged and older adults has become a major public health concern. Chronic pa...

Prediction of an fMRI-based schizophrenia biomarker from EEG using dynamic functional connectivity: a simultaneous EEG-fMRI study.

OBJECTIVE: Recent advances in functional magnetic resonance imaging (fMRI) have identified brain functions associated with psychiatric disorders using...

Resting-state EEG microstates as biomarkers for major depressive disorder.

OBJECTIVES: To investigate the temporal dynamics of resting-state electroencephalography (EEG) microstates in patients with Major Depressive Disorder ...

Integrating epidemiologic modeling and explainable machine learning to predict and identify factors associated with self-reported depression among adults in Tennessee, United States.

BACKGROUND: Depression is a major public health concern, with Tennessee ranking among the U.S. states with the highest prevalence. Despite its burden,...

Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Cohort Study.

BACKGROUND: Underdiagnosis and undercoding are common across mental health conditions, particularly suicide and self-harm. This leaves health care dat...

Substance-induced manic psychosis in which delusions were corroborated by a chatbot - case report.

BACKGROUND: This case describes a substance-induced manic episode with psychotic features in which interaction with an AI (artificial intelligence) ch...

Analysis of health infrastructure and suicide rates in Brazil: a nationwide ecological spatial-temporal study, 2009-2023.

BACKGROUND: Suicide remains a major global health concern and disproportionately affects low- and middle-income countries (LMICs), where socio-economi...

Suicidal Ideation in Online Spaces Through the Lens of Interpersonal Theory of Suicide: Exploratory Study of Self-Disclosure, Peer Support, and AI Responses.

BACKGROUND: Suicide is a critical global public health issue, with millions experiencing suicidal ideation (SI) each year. Global estimates suggest th...