Neurology

Endometriosis Unveiled: Innovations in Diagnosis and Management of Endometriosis.

Endometriosis is a chronic inflammatory condition that can result in chronic pain through complex nociceptive, neuropathic, and nociplastic pathways. This article provides a comprehensive background on endometriosis as well as future directions in diagnosis and management. The diagnosis of endometriosis is explored, including novel imaging techniques, biomarkers, and the integration of artificial ...

Artificial-Intelligence-Driven Electromyography Adaptation for Elderly Assistance at Physiological, Functional, and Behavioral Levels.

Older adults frequently face difficulties in activities of daily living (ADLs) due to age-related declines in strength, coordination, and perception. Myoelectric control provides an intuitive human-robot interface by translating muscle activity into assistive commands. However, its practical application is still challenged by signal annotation, multijoint coordination, and cross-task generalizatio...

An explainable artificial intelligence framework for clinical decision support in stroke discharge planning.

BACKGROUND: Stroke, a leading cause of global mortality and disability, requires accurate prediction of discharge outcomes to support early care plann...

Interactions between minimal amount of exercise and low-density lipoprotein cholesterol on incident dementia after stroke.

Cognitive impairment often follows stroke. Regular physical activity has been shown to be associated with reduced dementia risk, while the association...

The effect of community intervention based on deep learning-established early screening system and model construction for stroke.

BACKGROUND: Stroke is a common cardiovascular complication. The machine learning (ML) algorithms in stroke is a new and noble approach. The objective ...

Optimizing stroke mortality prediction: a comparative study of sampling, cost-sensitive learning, and threshold adjustment.

BACKGROUND: Stroke is a leading cause of mortality and disability worldwide, creating a critical need for accurate prediction tools to support early c...

A pH-Calibrated Multi-Analyte MXene Aerogel Electrochemical Platform Assisted by Interpretable Machine Learning for CSF-Based Prescreening of Postoperative Bacterial Meningitis.

Rapid and reliable prescreening and early risk stratification of postoperative meningitis (PNM) remain challenging because clinical symptoms are nonsp...

Artificial Intelligence in Neonatal Care: The Breadth of Promise, the Depth of Challenge-An Overview.

Artificial intelligence (AI) is becoming an integral tool in clinical care. The recent position statement by the Royal Australasian College of Physici...

Nonverbal AI-Based Communication Robot for Staff in Disaster-Affected Care Facilities: Exploratory ABAB Intervention Study.

BACKGROUND: Medical and welfare facilities in the Noto region of Japan were severely affected by the 2024 Noto Peninsula earthquake and subsequent tor...

Metabolomic signatures for diagnosis and clinical severity in Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) remains challenging to diagnose at early stages owing to subtle and heterogeneous clinical manifestations and the...

Estimating blood-brain barrier exchange rate using diffusion-weighted arterial spin labeling and physics-guided neural networks.

This study proposes physics-guided neural network (PgNN) approaches for estimating perfusion and blood-brain barrier (BBB) water permeability paramete...

Predicting comorbid anxiety in adolescents with major depressive disorder: an EEG-based machine learning approach with SHAP interpretability.

Comorbid anxiety in adolescents with major depressive disorder (adMDD) is linked to higher suicide risk and poorer prognosis, necessitating precise sc...

Integrative multi-omics reveals MHC class II-mediated neuroinflammation and systemic metabolic dysregulation as transdiagnostic drivers in major brain disorders.

Psychiatric, neurodevelopmental, and neurodegenerative disorders, including Alzheimer's disease (AD), attention-deficit/hyperactivity disorder (ADHD),...

Driving Mechanisms and Future Trends of Migraine and Tension-Type Headache Burden in G20 Countries: A Comparative Analysis Utilizing Decomposition Analysis and Explainable Machine Learning.

INTRODUCTION: Migraine and tension-type headache (TTH) are leading causes of neurological disability globally. While their macro-trends are documented...

Spatiotemporal deep learning for early detection of isolated REM sleep behavior disorder and Parkinson's disease using functional MRI data.

This study aimed to develop and evaluate a spatiotemporal deep-neural-network (stDNN) using resting-state fMRI (rs-fMRI) data to identify brain biomar...

ShuffleLeNet architecture for spinal cord injury classification and level detection.

PURPOSE: To develop an automated and accurate framework for classifying spinal cord injuries (SCI) and detecting injury levels from CT images, thereby...

Classification of neurodevelopmental disorders and typical development using deep learning and a portable patch-type electroencephalography device.

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are common neurodevelopmental disorders (NDDs) in children and ofte...

A Radiomics-Driven Model to Distinguish Between Clinically Similar Myxopapillary Ependymomas and Lumbosacral Schwannomas.

BACKGROUND AND OBJECTIVES: Myxopapillary ependymomas (MPE) and intradural lumbosacral schwannomas may be challenging to distinguish based on presentin...

Association Between the Hemoglobin-to-Red Blood Cell Distribution Width Ratio and Perioperative Mortality Risk in Myasthenia Gravis Patients with Sepsis: A Retrospective Cohort Study.

BackgroundThis study aims to explore the association between the Hemoglobin/Red Cell Distribution Width Ratio (HRR) and perioperative mortality in mya...

Vibrational Spectroscopy of Clinical Biofluids: Advances in FTIR and Raman-Based Biomarker Discovery for Disease Diagnosis and Monitoring.

Human biofluids carry a continuously updated molecular record of systemic health, yet their diagnostic potential remains largely untapped by conventio...