Neurology

Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer's disease diagnosis.

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leadin...

Cost-effectiveness analysis of robotic exoskeleton versus conventional physiotherapy for stroke rehabilitation in Singapore from a health system perspective.

OBJECTIVES: This study conducted a comprehensive probabilistic cost-effectiveness analysis comparing...

Deep Learning based Collateral Scoring on Multi-Phase CTA in patients with acute ischemic stroke in MCA region.

BACKGROUND AND PURPOSE: Collateral circulation is a critical determinant of clinical outcomes in acu...

Micrographia in Parkinson's Disease: Automatic Recognition through Artificial Intelligence.

BACKGROUND: Parkinson's disease (PD) leads to handwriting abnormalities primarily characterized by m...

Feature selection using metaheuristics to predict annual amyotrophic lateral sclerosis progression.

OBJECTIVE: Amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease with no cura...

Speech production as an artificial intelligence-based 'process' measure of cognition sensitive to mild cognitive impairment and Alzheimer's disease.

Process scores in neuropsychological tests add incremental validity for detecting non-normative cog...

Evaluation of retrieval-augmented generation and large language models in clinical guidelines for degenerative spine conditions.

PURPOSE: Degenerative spinal diseases often require complex, patient-specific treatment, presenting ...

Letter to the editor concerning "Machine learning-based models for outcome prediction in skull base and spinal chordomas: a systematic review and meta-analysis" by B. Hajikarimloo, et al. (Eur spine J [2025]: doi: 10.1007/s00586-025-09053-y).

Assessing changes in whole-brain structural connectivity in the unilateral 6-hydroxydopamine rat model of Parkinson's disease using diffusion imaging and tractography.

Parkinson's disease (PD) is a multifactorial, progressive neurodegenerative disease that has a profo...

Optimal multimodal feature combination and classifier selection for music-based EEG signal analysis.

PURPOSE: Music perception is a fundamental human experience, integral to cognitive and emotional pro...

Biomimetic Analysis of Neurotransmitters for Disease Diagnosis through Light-Driven Nanozyme Sensor Array and Machine Learning.

Neurological diseases, including Alzheimer's disease, Parkinson's disease, and multiple sclerosis, p...

Automated facial nerve identification in microsurgery with an improved unet.

To develop a deep-learning model that improves the segmentation and detection of Facial Nerve in mic...

Identification of inflammation-related biomarkers and therapeutic targets for neurogenic bladder fibrosis via multi-omics analysis.

Inflammatory responses play a crucial role in the progression of pediatric neurogenic bladder (NB)-a...

Neuroimaging and biological markers of different paretic hand outcomes after stroke.

BACKGROUND: Hand dysfunction significantly affects independence after stroke, with outcomes varying ...

Early transcriptional responses reveal cell type-specific vulnerability and neuroprotective mechanisms in the neonatal ischemic hippocampus.

Neonatal hypoxic-ischemic (H-I) brain injury, a leading cause of neurodevelopmental disabilities, se...

Dosing prediction of valproic acid in pediatric patients with epilepsy: population pharmacokinetic model or machine learning model?

PURPOSE: This study develops and compares population pharmacokinetics (PopPK) models and machine lea...

MRI-based detection of multiple sclerosis using an optimized attention-based deep learning framework.

BACKGROUND: Multiple Sclerosis (MS) is a chronic neurological disorder affecting millions worldwide....

Research on transcranial magnetic stimulation for stroke rehabilitation: a visual analysis based on CiteSpace.

OBJECTIVE: This study aimed to analyze recent research and emerging trends in transcranial magnetic ...

Machine-learning based strategy identifies a robust protein biomarker panel for Alzheimer's disease in cerebrospinal fluid.

BACKGROUND: The complex pathogenesis of Alzheimer's disease (AD) has resulted in limited current bio...

Effects of device-assisted practice of activities of daily living in a close-to-normal pattern on upper extremity motor recovery in individuals with moderate to severe stroke: study protocol of a randomized control trial.

BACKGROUND: The majority of individuals with chronic stroke have residual upper extremity (UE) disab...

D-optimal candexch algorithm-enhanced machine learning UV-spectrophotometry for five-analyte determination in novel anti-glaucoma formulations and ocular fluids: four-color sustainability framework with NQS assessment and UN-SDG integration.

The novel anti-glaucoma ophthalmic preparation containing latanoprost, netarsudil, and benzalkonium ...