Neurology

Zero Echo Time Magnetic Resonance Imaging of the Spine.

Zero echo time magnetic resonance imaging is an ultrashort echo time technique that enables computed...

Deep learning synthesis of virtual T2-weighted fat-suppressed MR images: a multi-center study.

OBJECTIVES: To develop a Generative Adversarial Network (GAN) for generating virtual T2 fat-suppress...

Experimental investigation of muscle-tendon unit geometry and kinematics in lower-limb muscles during gait: Current applications and future directions - A scoping review.

PURPOSE: Musculoskeletal (MSK) modeling and ultrasound imaging (USI) are complementary techniques th...

Comparison of median nerve conduction parameters from the index and middle fingers in carpal tunnel syndrome: Toward a standardized electrophysiological evaluation protocol.

BACKGROUND: Variability exists regarding which is the best digit for diagnosing and classifying the ...

Gait and movement analysis for discrimination between people with dementia and healthy control persons based on pose estimation and machine learning.

BackgroundDementia disorders are affecting millions of people globally, characterized by memory loss...

Temporal and Cell-Specific Regulation of Synaptic Homeostasis by the Chromatin Remodeler Chd1.

Disruptions in chromatin remodelers and synaptic proteins represent major genetic risk factors for a...

HyCoSwin-PD: An explainable hybrid ConvNeXtV2-Swin transformer framework for Parkinson's disease detection from neuroimaging.

Accurate detection of Parkinson's disease (PD) from structural MRI remains a significant challenge d...

Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism.

OBJECTIVE: Pre-mortem diagnosis of parkinsonism is often challenging due to atypical presentations, ...

Dose reduction for synaptic density PET imaging in Parkinson's disease.

OBJECTIVE: Dynamic PET imaging with 11C-UCB-J enables in vivo quantification of synaptic vesicle gly...

Epilepsy: Modern Treatment Approaches, Clinical Aspects, and Patent Status.

Epilepsy is a chronic neurological disorder causing recurrent seizures. Improved diagnosis and manag...

Autophagy-exosome crosstalk in neurodegeneration: Mechanisms and therapeutic opportunities.

Neurodegenerative diseases (NDs), including Alzheimer's, Parkinson's, Huntington's, amyotrophic late...

Dynamic functional connectivity changes in noise-induced hearing loss: a resting-state fMRI study with machine learning-based classification.

OBJECTIVE: Noise-induced hearing loss impacts brain health and cognition, with dynamic functional co...

Letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis".

A time-frequency cross-attention network model for epileptic seizure detection.

Epilepsy is a chronic neurological disease that profoundly impacts patients' daily lives. Electroenc...

A Machine learning pipeline to investigate tissue ingrowth in cerebral aneurysms using preclinical animal models.

Cerebral aneurysm is a life-threatening condition characterized by the formation of a saccular bulge...

Spinal disease image segmentation technology integrating U-ResNet and shape-aware attention.

The incidence of spinal diseases is rising and affecting younger people, making early and accurate d...

Estimating cognitive function score from mild cognitive impairment to moderate dementia using a hybrid model combining plasma biomarkers with electroencephalogram signal.

BackgroundPredicting cognitive function across dementia stages remains challenging. Plasma biomarker...

Decoding epilepsy's molecular blueprint: Machine learning unravels transcriptomic subtypes and regulatory networks.

OBJECTIVE: Drug-resistant epilepsy (DRE) affects approximately one-third of patients with epilepsy. ...

Integrated network toxicology and computational profiling of acetyl tributyl citrate-related mechanisms in Alzheimer's disease.

BackgroundAcetyl tributyl citrate (ATBC), an eco-friendly plasticizer, exhibits poorly characterized...

Sub-band Embedding Based EEG Spatio-Temporal Activity Representation for Emotion Recognition.

EEG-based emotion recognition is a crucial task with significant implications for mental health moni...

Automated CTA-Derived Collateral Grading and Morphologic Metrics for Enhanced Prediction of Post-Stroke Outcomes.

BACKGROUND AND PURPOSE: Collateral circulation is a key determinant of treatment response and outcom...