Psychiatry

Linking brain structure to stress reactivity: cingulate surface area predicts acute cortisol responses.

BACKGROUND: Altered stress responses are closely linked to mental disorders, but the role of brain structure in acute cortisol responses to psychosocial stress remains underexplored, particularly in healthy individuals. Previous studies, with predominantly small samples, primarily focused on selected limbic regions and functional measures. Thus, this study investigates associations between brain s...

Electrocardiogram-Based Mental Stress Detection Amid Everyday Activities Using Machine Learning: Model Development and Validation Study.

BACKGROUND: Frequent, sustained stress is linked to poor health and requires monitoring for early intervention. Electrocardiograms (ECG) are promising biomarkers because they can be recorded noninvasively and continuously using wearable devices. However, tracking stress with ECG is challenging because daily activities elicit responses similar to mental stress (MS), and various mental stimuli that ...

Feasibility and Acceptability of AI-Powered Tools for Early Autism Screening in Egypt: Semistructured Focus Group Study.

BACKGROUND: Autism spectrum disorder (ASD) is often underdiagnosed in low- and middle-income countries due to limited specialist access, sociocultural...

The Role of Large Language Models in Teaching Psychiatric Semiology: A Systematic Review.

INTRODUCTION: Teaching psychiatric semiology faces challenges such as the limited availability of real patients for educational purposes and a shortag...

Deep learning-based differential diagnosis of major depression and bipolar disorder using microglia-cellular sensors and patient-derived small extracellular vesicles.

Evaluation of artificial intelligence-generated vignettes depicting patient chatbot use in psychiatric contexts.

Chatbot-related mental health risks have attracted increasing public attention, yet educational case materials for clinicians remain limited. We evalu...

Hybrid deep learning and feature selection approach for autism detection from rs-fMRI data.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that is primarily characterized by deficits in social communication and restricted or...

Comment on "Predictive machine learning algorithms for depression and anxiety disorders in six cancer types: a comprehensive multi-center population-based study".

How self-efficacy influences Chinese university students' GenAI dependency: A study of the mediating roles of social anxiety and rumination and the moderating role of mindfulness.

With the recent, rapid advancement of artificial intelligence (AI) technology, an increasing number of university students are relying on generative a...

Technology Matters: Emerging technologies in clinical informatics to support child and adolescent mental healthcare safety.

Electronic health records (EHRs) can support patient safety across medical settings but require thoughtful adaptation to serve specialty care. This ar...

Cleft related facial skeletal surgery: an update.

PURPOSE OF REVIEW: This review provides a comprehensive update on advancements and evolving paradigms in cleft-related facial skeletal surgery. It eva...

It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety.

Large language models are rapidly becoming embedded in everyday life through artificial intelligence (AI) chatbots that people use for practical assis...

New directions for the Edinburgh Postnatal Depression Scale: towards an EPDS-R (revised).

The Edinburgh Postnatal Depression Scale (EPDS) has been translated into over 60 languages, and for 40 years this 10-item EPDS has remained unchanged....

Identifying minimal risk factors for adolescent suicidal ideation and suicide attempts: A machine learning-optimized approach.

This study aimed to develop and validate a machine learning (ML) model to identify the minimal risk factors for adolescent suicidal behaviors, includi...

The power of context: Enhancing repetitive transcranial magnetic stimulation effects through skillful behavior.

INTRODUCTION: Non-invasive neuromodulation techniques like repetitive transcranial magnetic stimulation (rTMS) have shown promise in treating psychopa...

Predictive neuroimaging biomarkers of major depressive disorder treatment response: An umbrella review.

Major depressive disorder (MDD) is a heterogeneous condition with varied responses to pharmacological, psychotherapeutic, and neuromodulation interven...

[Simulated consciousness, pseudo-empathy and the illusion of attachment: what can psychiatry do with artificial intelligence?].

Over the past decade, the burden of mental disorders has grown while services remain capacity-constrained, pushing generative artificial intelligence ...

Challenges in translating AI-driven ASD/ADHD diagnosis: A methodological systematic review.

BACKGROUND: Early and accurate diagnosis of neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and attention-deficit/hypera...

Machine learning-based risk classification of depressive symptoms among patients with hearing loss: evidence from the Health and Retirement Study (HRS).

BACKGROUND: Depression is a common and debilitating condition among individuals with hearing loss, substantially impairing patients' quality of life. ...

Imaging and machine learning reveal pigment ring spatial characteristics in vitiligo progression.

BACKGROUND: Vitiligo is a chronic autoimmune disorder causing skin depigmentation due to melanocyte loss, with pigment ring dynamics being key to unde...