Neurology

A Qualitative Exploration of Ethical Aspects of Using AI in Parkinson Disease: Patient Panel Study.

BACKGROUND: As Parkinson disease (PD) rates increase, so does interest in finding new technological solutions for PD management. Despite substantial efforts to explore potential applications of artificial intelligence (AI) in PD management, research from the perspectives of people with PD on AI remains limited. OBJECTIVE: This study aims to explore the ethical considerations of AI in PD management...

Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods.

Deep learning for cross-subject EEG decoding is hindered by the high degree of inter-subject variability, which creates a severe domain shift between training and unseen test subjects. This survey presents a comprehensive review of deep learning methodologies specifically engineered to address this cross-subject generalization challenge. To ground this analysis, we formalize the cross-subject sett...

Retraction Note: A novel approach integrating topological deep learning from EEG Data in Alzheimer's disease.

Unveiling the causal pathway of Parkinson's disease dysphonia: A voice causal generative model (VCGM) approach.

BACKGROUND: Although artificial intelligence (AI) models have demonstrated high accuracy in diagnosing Parkinson's disease (PD) from speech signals, t...

Cognitive trajectories in early Parkinson's disease: A multimodal MRI study of brain structure and cognitive decline.

Cognitive trajectories in Parkinson's disease (PD) exhibit substantial heterogeneity, ranging from long-term stability to rapid decline. The specific ...

Essence: A benchmarking-validated transformer framework for early diagnosis of Parkinson's disease using cerebrospinal fluid protein biomarkers.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. The lack of objective molecular bi...

Incidence and prevalence of vascular cognitive impairment in China: a systematic review and meta-analysis.

OBJECTIVE: Given China's rapid population ageing and substantial stroke burden, understanding the epidemiology of vascular cognitive impairment (VCI) ...

Identification of PANoptosis-Related Biomarkers in Spinal Cord Injury (SCI) through Multi-Omics Analysis and Machine Learning.

BACKGROUND: Spinal cord injury (SCI) is a severe neurological disorder lacking early diagnostic biomarkers and precise therapeutic targets. PANoptosis...

Deep Learning Reconstruction Versus Hybrid Iterative Reconstruction for Acute Cerebral Infarction Detection on 135 kVp Non-Contrast Brain CT.

PURPOSE: Deep learning reconstruction (DLR) is useful to reduce image noise and improve contrast resolution compared with hybrid iterative reconstruct...

Increased Pre-Activation and Co-Contraction in ACL-Reconstructed Athletes: Insights from AI-based EMG Analysis.

INTRODUCTION: Anterior Cruciate Ligament (ACL) tears disrupt the neural structures within the ligament, impairing the neuromuscular control of knee-st...

Machine Learning-Derived Cardiovascular Aging Phenotypes From Cardiac Function and Stroke Risk in the UK Biobank: Cohort Study.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is widely used across various cardiac conditions and systematically assesses cardiac anatomical st...

Development of a community home-based dual-supplier cooperation care model for people with dementia based on an intelligent decision-assistance system: protocol of a 1-year randomised controlled trial in China.

INTRODUCTION: Dementia imposes significant care and financial burdens on families and countries globally. While high-quality home-based care is crucia...

Deep learning discriminates seizures from normal brain oscillations in the electroencephalogram of a rat model of post-traumatic epilepsy.

This study used machine learning to objectively identify seizures in the electroencephalogram of a model of post-traumatic epilepsy based on fluid per...

Frequency-based deep learning to identify subtle postural instability in early, untreated Parkinson's disease.

Despite evidence of early neurodegeneration, postural instability is commonly associated with later stages of Parkinson's disease (PD), mainly due to ...

An interpretable deep learning diagnostic framework for early Alzheimer's disease based on EEG microstate spectra and multi-branch CNN.

From Static Diagnosis to Dynamic Guidance : Evolution of Artificial Intelligence in Pediatric Neuroimaging.

The pediatric brain represents a dynamic biological target characterized by rapid myelination and functional reorganization, which presents unique cha...

Machine learning classification of patients after suicide attempts using demographic data, EEG connectivity and heart rate variability.

OBJECTIVE: The aim of this study was to develop a way to distinguish suicidal patients based on their electrophysiologic (EEG connectivity and heart r...

Algometric assessment of sensitization and habituation as predictive markers for OnabotulinumtoxinA response in chronic migraine.

BACKGROUND: Chronic migraine is a debilitating disorder characterized by central sensitization and impaired habituation. Although OnabotulinumtoxinA (...

Data-driven thresholds for standardized classification of severe Alzheimer's disease neuropathology using digital neuropathology.

Alzheimer's disease neuropathological changes (ADNC)-operationalized with semi-quantitative parameters-represent the consensus-based gold standard for...

Feasibility of a hybrid SSVEP-motor imagery BCI with robotic feedback for upper limb motor rehabilitation in stroke patients.

BACKGROUND: Stroke remains a leading cause of long-term disability, necessitating innovative neurorehabilitation strategies to address persistent moto...