Psychiatry

Large language model empowered explainable and interpretable mental health analysis.

Concern about expressing depressive symptoms on social media is growing in the digital age. Traditional detection methods can identify depression but lack clear, human-understandable explanations. We present a novel methodology "InsightDep", a mental health analysis model specifically designed to detect depression in the social media users. Furthermore, the model provides explainability for the mo...

Autism spectrum disorder identification using machine learning models on MRI data.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects sensory processing, speech, behavior and identifying the condition at an early stage is necessary to provide the treatment. The existing diagnostic methods are mainly based on personalized subjective and time consuming. This study introduces an objective diagnostic method by analyzing technical noise signature producing ...

The impact of an artificial intelligence (AI)-assisted education program on mental health, social support and quality of life in older individuals with head and neck cancer: study protocol of a randomized controlled trial.

BACKGROUND: Head and neck cancer (HNC) is a common malignant tumor, and its treatment often leads to functional impairments in speech, swallowing, and...

A survey of deep learning techniques in detecting neurological disorders using MRI.

Magnetic resonance imaging (MRI) is widely regarded as the most reliable non-invasive imaging modality for detecting neurological disorders. However, ...

Different pattern: a new EEG-based method for mental performance detection.

BACKGROUND: This study focuses on detecting mental performance from EEG signals. It provides both classification and explanation results. For this pur...

A prototype-augmented graph representation learning framework for identifying brain disorder-associated genes and facilitating drug repurposing.

Many genetic loci were identified as associated with neuropsychiatric disorders and neurodegenerative disorders by Genome-wide association studies (GW...

Capturing multi-disease states on a spectrum with machine learning and routine clinical data.

BACKGROUND: Diseases exist on spectra of risk factors, cellular perturbations, organ dysfunction, and clinical manifestations. It is unknown whether t...

Multimodal phenotypic classification of generalized anxiety and panic using structural MRI data and psychosocial factors: machine learning results from the German National Cohort (NAKO) study.

Anxiety disorders are common and impairing mental health conditions. Using data from 26,378 adults in the German National Cohort Study (NAKO), we inve...

A fully-CMOS spiking LIF neuron implementation for optimized STDP learning on memristor.

The growing demand for fast and energy-efficient computing has motivated the development of neuromorphic hardware inspired by biological neural system...

Joint trajectories of sleep duration and depressive symptoms and risk of incident multimorbidity: a longitudinal analysis with machine learning prediction.

BACKGROUND: Sleep disturbances and depressive symptoms frequently co-occur in older adults. Both conditions follow distinct, time-varying trajectories...

Machine learning and natural language processing for the identification of potential mental disorders among school-age children: a prospective birth cohort study.

BACKGROUND: Early identification of childhood mental health disorders is a critical public health objective. Existing screening approaches, largely de...

Language barriers, mobility, and health equity: clinical risks, economic burden, and policy options for universal language access.

BACKGROUND: International mobility has intensified routine contact between health systems and patients who do not speak the dominant language of care....

Displaced minds: ecologies of depression.

This issue of the Biomedical Journal explores emerging perspectives across neuropsychiatry, metabolism, aging, regenerative medicine, artificial intel...

Turning Compliance Into Action: An Augmented Intelligence-Enabled Framework for Advocacy Organizations to Drive Population Health Improvement.

Community Health Needs Assessments (CHNAs), mandated by the Affordable Care Act for tax-exempt hospitals, represent an underutilized yet rich data sou...

Early-life proteomic and microbiome features signal obesity risk across 26 years of follow-up.

UNLABELLED: Childhood obesity is rising globally. Yet, few studies have examined the microbiome and proteome in early childhood in relation to this ou...

Can Digital Tools Fix Bias in Mental Health Triage?

Recent advances in digital technologies hold both promise and potential pitfalls for mental health triage. In this News and Perspectives article, JMIR...

Quantum Machine Learning for Biomedical Classification Problems: A Feasibility Study on Real Quantum Hardware.

PURPOSE: Recent advances in quantum computing offer opportunities to explore alternative methods for the solution of classification problems commonly ...

Nurse-Led Design and Prototype Development of a Smart Care Robot to Support Mental Well-Being in Nursing and Health Care Students: A Proof-of-Concept.

BACKGROUND: Smart care robots are rarely developed for younger adults, particularly nursing and health care students, and seldom integrate nursing exp...

Unraveling EFL students' technology self-efficacy, emotions and behavioral intentions in leveraging large language models: the serial mediation of perceptions and attitudes.

With the growing momentum to integrate artificial intelligence (AI) into education, large language models (LLMs) have shown great potential for Englis...

Importance ranking and predictive model construction of WMSDs risk factors among shift-working nurses based on multiple machine-learning algorithms.

BACKGROUND AND OBJECTIVE: Nurses are essential for safeguarding public health, and their physical condition directly affects care quality and patient ...