Neurology

BrainPrompt+: Multi-Level Brain Prompt Learning for Knowledge-Guided Neurological Disorder Identification.

Accurate identification of neurological disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Autism Spectrum Disorder (ASD) is challenging due to subtle early-stage symptoms and heterogeneous brain dynamics. Resting-state functional MRI (rs-fMRI) enables the construction of functional brain networks, where Graph Neural Networks (GNNs) have shown promise for disease classificat...

Sensory nerves protect against preclinical tendinopathic changes through FGF1 signaling.

Chronic tendinopathy is typified by persistent tendon-associated pain, transmitted by local nociceptive neurons. However, the regulatory function of somatosensory neurons in the development of tendinopathy is unknown. Here, we show that sensory neurons grow into the tendon proper across preclinical models of chronic tendinopathy to serve a protective function against tendinopathic changes through ...

MusicAlzheimer: AI-Powered, Culturally Tailored Digital Music Therapy Prototype for Alzheimer Disease Care.

This research letter reports the development and preliminary user testing of MusicAlzheimer, an artificial intelligence-driven digital music therapy p...

Modeling Alzheimer's disease with human multi-omics profiles: Promise to personalized medicine.

Alzheimer's disease (AD) presents considerable heterogeneity in disease risk and outcomes, posing a major challenge for effective therapeutic developm...

Wearable Sensors for Monitoring Neurogenic Dysphagia: A Scoping Review.

Neurological disorders, such as Parkinson's disease and stroke, often lead to neurogenic dysphagia, a swallowing disorder that compromises nutrition a...

Closed-loop stimulation modulates attention shifting in children.

Spontaneous fluctuations in attention can impede adaptation to changing goals and environments. Endogenous control over attentional shifts, referred t...

Machine learning models for predicting readmission after stroke: A systematic review and meta-analysis.

BACKGROUND: Hospital readmission following stroke poses a significant challenge for healthcare systems. Machine learning (ML) offers the potential to ...

Quantitative sensory testing and classical pain model dataset in 127 healthy volunteers.

Experimental pain models are integral to human pain research and the development of analgesic drugs. Of many options available, it is possible to iden...

Machine learning-based study of breath sounds in children with asthma in remission and cough variant asthma.

BACKGROUND: Traditional auscultation, heavily dependent on the subjective judgment of physicians, can lead to variability in diagnoses. This study aim...

Do predictors of motor recovery differ between robotic and conventional post-stroke rehabilitation?

BACKGROUND: While research on robotic rehabilitation has largely focused on evaluating device effectiveness, there remains a clear need to investigate...

AI for Relational Reconnection and Social Support in Alzheimer's Disease: A Conceptual Framework for Socially Embedded Systems.

Alzheimer's Disease (AD) has traditionally been approached through a biomedical lens, focusing on neurodegenerative markers such as amyloid-β plaques ...

Editorial for the Special Issue on Harmonization Techniques for MRI.

This editorial introduces the special issue on neuroimaging harmonization and situates its contributions within the broader methodological landscape o...

Research progress of diffusion tensor imaging in lumbar degenerative diseases: a narrative review.

Degenerative diseases of the lumbar spine are a common cause of chronic low back pain and neurological dysfunction. Their pathological basis involves ...

Three-dimensional modeling of sensory nerve architecture and eosinophil and mast cell interactions in eosinophilic gastrointestinal disease.

Increased sensory nerve density has been described in type II inflammatory conditions and is linked to eosinophil and mast cell infiltration and neuro...

Exploring human GABA transporter 3 binders for epilepsy through quantum reactivity analysis, molecular dynamics, machine learning prediction, and network pharmacology.

CONTEXT: Drug-resistant epilepsy (DRE) remains a major therapeutic challenge, affecting millions of patients globally who do not respond to convention...

Addressing the Treatment Gap for Pediatric Headache in Underserved Regions.

PURPOSE OF REVIEW: This review explores innovative strategies to address the treatment gap for pediatric headache disorders in underserved regions wor...

Age-adjusted neurofilament light chain cutoffs for diagnosing neurodegenerative dementia: a two-threshold machine learning approach.

Clinical implementation of neurofilament light chain (NfL), a biomarker of neurodegeneration, remains challenging due to absence of reliable cutoffs a...

SPECT hybrid approach combining conventional and deep features for early detection of Parkinson's disease.

The early diagnosis of Parkinson's disease (PD) using SPECT imaging continues to be challenging due to the subtle dopaminergic deficits present in the...

Machine learning based classification of intraoperative EMG signals recorded during brain tumor surgeries: a pooled data approach for large-scale analysis and real-time applications.

This study analyzes a publicly available, 7-class iEMG dataset from West China Hospital to prevent nerve damage during brain tumor surgery. Trees, SVM...

MPAN: A Multi-Prototype Adaptive Network for Few-Shot EEG-Based Biometric Recognition.

Biometric recognition based on electroencephalography (EEG), which captures intrinsic neural dynamics via scalp-recorded electrical activity, has show...